Datasets:

yushengsu
/

stack-v2-python-with-content-chunk1-modified

Dataset card Data Studio Files Files and versions Community

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train · 2.98M rows

repo_name stringlengths 5 114	repo_url stringlengths 24 133	snapshot_id stringlengths 40 40	revision_id stringlengths 40 40	directory_id stringlengths 40 40	branch_name stringclasses 209 values	visit_date timestamp[ns]	revision_date timestamp[ns]	committer_date timestamp[ns]	github_id int64 9.83k 683M ⌀	star_events_count int64 0 22.6k	fork_events_count int64 0 4.15k	gha_license_id stringclasses 17 values	gha_created_at timestamp[ns]	gha_updated_at timestamp[ns]	gha_pushed_at timestamp[ns]	gha_language stringclasses 115 values	files listlengths 1 13.2k	num_files int64 1 13.2k
rasd3/demoMaker	https://github.com/rasd3/demoMaker	70a9e0f9c9e03e2d49eaac407d2d187211b92fb9	6a2e554dc45641c0b50fcab7c65d24efb9ebee52	c203ccd3177e78901cbbc9c43681db8b24878d7e	refs/heads/master	2018-02-07T20:21:58.172434	2017-07-07T01:51:40	2017-07-07T01:51:40	96,106,919	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7906976938247681, "alphanum_fraction": 0.8062015771865845, "avg_line_length": 20.33333396911621, "blob_id": "11d91abdf209a28bd4ffe879f3f4c7eecd98f8b9", "content_id": "c67f1a54515fd7ec39ce1d25d7fe95a096794c9c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 129, "license_type": "no_license", "max_line_length": 54, "num_lines": 6, "path": "/README.md", "repo_name": "rasd3/demoMaker", "src_encoding": "UTF-8", "text": "# demoMaker\n\ncompare udacity dataset prediction & ground_truth</br>\nprint steering angle with virtual handle\n\nopencv2 img2video\n\n" }, { "alpha_fraction": 0.5151692032814026, "alphanum_fraction": 0.6085180640220642, "avg_line_length": 28.05084800720215, "blob_id": "9fb23250d6281a656b32396c8ae6a56e65174a84", "content_id": "ef3bef181bd4d3f9cb59709e97a91c56b7aa0dbe", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1714, "license_type": "no_license", "max_line_length": 126, "num_lines": 59, "path": "/demoMaker.py", "repo_name": "rasd3/demoMaker", "src_encoding": "UTF-8", "text": "import cv2\nimport pdb\nimport numpy as np\n\n# GET BEST TEST PREDICTION\n\nf = open(\"test-predictions-epoch81\",'r')\nf.readline()\n\nframe_angle = [0] * 16000\nframe_gt = [0] * 16000\nframe_dir = [0] * 16000\n\nwhile True:\n line = f.readline()\n if not line: break\n sp = line.split(',')\n frameNum = sp[0][-10:-4]\n angle = sp[1][:-2]\n frame_angle[int(frameNum)] = float(angle)\n frame_dir[int(frameNum)] = sp[0]\n\n# GET GROUND TRUTH\n\nwith open(\"/home/spolab/kjunho/End_to_End/data/dataset_csv/_slash_vehicle_slash_steering_report.csv\",'r') as f:\n\tframe_gt = [float(ln.strip().split(\",\")[7]) for ln in f.readlines()]\n\n\n# MAKE DEMO VIDEOOOOO\n\n# cv2.VideoWriter(outputFile, fourcc, frame, size)\nwriter = cv2.VideoWriter('CNNLSTM_DEMO.avi', cv2.cv.CV_FOURCC('DIVX'), 20, (640, 480))\n\nfor i in range(9800,11800):\n img = cv2.imread(frame_dir[i])\n\n # steering\n cv2.rectangle(img, (10, 440), (200, 475), (255,255,255), -1)\n cv2.putText(img, \"predicted: \" + str(round(frame_angle[i],4)), (10,450), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0))\n cv2.putText(img, \"ground_truth:\" + str(round(frame_gt[int(i2.5)],4)), (10,470), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255))\n\n\n # draw steering wheel\n rad = 50\n cv2.circle(img, (320, 460), rad, (255, 255, 255), 1)\n\n # draw circle for true angle\n x = rad * np.cos(np.pi/2 + frame_gt[int(i2.5)])\n y = rad np.sin(np.pi/2 + frame_gt[int(i2.5)])\n cv2.circle(img, (320 + int(x), 460 - int(y)), 7, (0,0,255), -1)\n\n x = rad np.cos(np.pi/2 + frame_angle[i])\n y = rad * np.sin(np.pi/2 + frame_angle[i])\n cv2.circle(img, (320 + int(x), 460 - int(y)), 4, (255,0,0), -1)\n\n writer.write(img)\n\nwriter.release()\ncv2.destroyAllWindows()\n" } ]	2
WilliamOtieno/L298N	https://github.com/WilliamOtieno/L298N	673efebbdda29ddb0c488345c6e66a34e41cc599	b92a6ef96d2e1e5c6306b5ea0e91da5c25a54a46	b6df73e90befdd71323e9d96e303633a752f8c1a	refs/heads/master	2022-12-08T15:03:12.920318	2020-08-29T17:17:49	2020-08-29T17:17:49	279,882,374	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.5504273772239685, "alphanum_fraction": 0.5880342125892639, "avg_line_length": 21.5, "blob_id": "9a49c0695b0416155134b5da3a4f2701576e3a9f", "content_id": "6319b083982bf5aec45aa56ae484a97a7729d6b8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1170, "license_type": "no_license", "max_line_length": 42, "num_lines": 52, "path": "/l298n_motor.py", "repo_name": "WilliamOtieno/L298N", "src_encoding": "UTF-8", "text": "import RPi.GPIO as GPIO\nfrom time import sleep\n\nGPIO.setmode(GPIO.BCM)\nGPIO.setwarnings(True)\n\n\nclass Motor:\n def __init__(self, Ena, In1, In2):\n self.Ena = Ena\n self.In1 = In1\n self.In2 = In2\n GPIO.setup(self.Ena, GPIO.OUT)\n GPIO.setup(self.In1, GPIO.OUT)\n GPIO.setup(self.In2, GPIO.OUT)\n self.pwm = GPIO.PWM(self.Ena, 100)\n self.pwm.start(0)\n\n def moveForward(self, x=50, t=0):\n GPIO.output(self.In1, GPIO.LOW)\n GPIO.output(self.In2, GPIO.HIGH)\n self.pwm.ChangeDutyCycle(x)\n sleep(t)\n\n def moveBackward(self, x=50, t=0):\n GPIO.output(self.In1, GPIO.HIGH)\n GPIO.output(self.In2, GPIO.LOW)\n self.pwm.ChangeDutyCycle(x)\n sleep(t)\n\n def stop(self, t=0):\n self.pwm.ChangeDutyCycle(0)\n sleep(t)\n\n\nmotor1 = Motor(23, 24, 25)\n\ntry:\n while True:\n motor1.moveForward(100, 10)\n print(\"Moving forward\")\n motor1.stop(2)\n print(\"Stopped\")\n motor1.moveBackward(50, 10)\n print(\"Moving backward\")\n\nexcept Exception:\n print(\"Found error\")\n\nfinally:\n print(\"Cleaning all ports\")\n GPIO.cleanup()\n" }, { "alpha_fraction": 0.7272727489471436, "alphanum_fraction": 0.7954545617103577, "avg_line_length": 21, "blob_id": "02073d114e259ac61681e9407a6f4e573202e550", "content_id": "2e8800ccb4972e5e1431ad75f46d6ef3cebb7b48", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 44, "license_type": "no_license", "max_line_length": 35, "num_lines": 2, "path": "/README.md", "repo_name": "WilliamOtieno/L298N", "src_encoding": "UTF-8", "text": "# L298N\nUsed Fritzing to draw the shematics\n" } ]	2
nicoleszc/motif-mark	https://github.com/nicoleszc/motif-mark	619df19f905eb9ddf4526e1c651394f13f90c6a9	148f6ea2b2b9cc6b5232c2a55ca14d538ee69fb6	a4f178a2d37e6202e76466476009d6cd71ae3725	refs/heads/main	2023-03-04T23:20:07.429282	2021-02-12T23:59:21	2021-02-12T23:59:21	338,437,747	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6887332201004028, "alphanum_fraction": 0.7010654807090759, "avg_line_length": 37.105262756347656, "blob_id": "ec10c3657d4e024bb15b0852513e278743af3591", "content_id": "3ab5fbd89321c56507961f74d34c2241a0e7b71f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 10136, "license_type": "no_license", "max_line_length": 307, "num_lines": 266, "path": "/motif-mark.py", "repo_name": "nicoleszc/motif-mark", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# Motif Mark Script\n# Nikki Szczepanski\n\n# Import necessary modules\nimport argparse\nimport re\nimport cairo\n\n# Argparse function\ndef get_args():\n \"\"\"Define the arguments needed for the script.\"\"\"\n parser = argparse.ArgumentParser(description='Given a fasta file of genes and a text file of motifs, outputs an vector image\\\n\t\tof a gene and its motifs to scale.')\n parser.add_argument(\"-f\", \"--fasta\", type=str, required=True, help='Absolute path to fasta file of genes, where introns are\\\n\t\tin lower case and exons are in upper case.')\n parser.add_argument(\"-m\", \"--motifs\", type=str, required=True, help='Absolute path to text file containing a list of motifs,\\\n\t\twhere each motif is on a new line. Accepts all IUPAC degenerate base symbols.')\n args = parser.parse_args()\n return parser.parse_args()\nparse_args = get_args()\n\n# Rename variables from argparse arguments\nfasta_file = parse_args.fasta\nmotifs_file = parse_args.motifs\n\n# Define the ouput image file to be created (with the same path as the input fasta file)\nimage_file = fasta_file.split(\".fa\")[0] + \".svg\"\n\ndef find_motifs():\n\t\"\"\"Read in the motifs file to create a list of motifs named 'motif_list'.\"\"\"\n\tmotif_list = []\n\twith open(motifs_file, 'r') as motifs:\n\t\tfor motif in motifs:\n\t\t\tmotif = motif.strip(\"\\n\")\n\t\t\tmotif_list.append(motif)\n\t\t# Sort the motifs from longest to shortest, which will aid in the visualization later on.\n\t\tmotif_list=sorted(motif_list,key=len,reverse=True)\n\treturn motif_list\nmotif_list = find_motifs()\n\n# For each IUPAC symbol, define a regex expression.\ndef degenerate_bases():\n \"\"\"\n\tCreates a dictionary in which the keys are degenerate bases and the values are the possible ATCGU base letters.\n\tThis dictionary 'bases' will be used to create regex expressions for motifs including degenerate bases, according to IUPAC.\n\t\"\"\"\n bases = {\n\t\t'A': 'A',\n\t\t'C': 'C',\n\t\t'G': 'G',\n\t\t'T': '[TU]',\n\t\t'U': '[TU]',\n\t\t'W': '[ATU]',\n\t\t'S': '[CG]',\n\t\t'M': '[AC]',\n\t\t'R': '[AG]',\n\t\t'Y': '[CTU]',\n\t\t'K': '[GTU]',\n\t\t'B': '[CGTU]',\n\t\t'D': '[AGTU]',\n\t\t'H': '[ACTU]',\n\t\t'V': '[ACG]',\n\t\t'N': '[ACGTU]'}\n return bases\nbases = degenerate_bases()\n\ndef convert_degenerates():\n\t\"\"\"\n\tIf degenerate bases are present in a motif, create a regex expression that only uses the letters ACTGU, according to IUPAC, using the pre-defined dictionary 'bases'.\n\tSaves each motif:regex pair in a dictionary 'motif_convmot'. \n\tAlso creates a dictionary 'converted_motifs' where the key is the regex expression and the value is the length of the original motif.\n\tNote: Not case sensitive (i.e., can interpret both lower and upper case motifs).\n\t\"\"\"\n\tmotif_convmot = {}\n\tconverted_motifs = {}\n\t# Iterate through each motif in the list of motifs\n\tfor motif in motif_list:\n\t\tregex = ''\n\t\t# Iterate through each letter in the motif\n\t\tfor char in motif:\n\t\t\tif char.upper() in bases.keys():\n\t\t\t\t# Add each letter's corresponding regex expression to a string \n\t\t\t\tregex += bases[char.upper()]\n\t\t\telse:\n\t\t\t\tprint(\"Error: Unrecognized base in motif. Please include only IUPAC symbols.\")\n\t\t# Once the string of regex expressions is complete, set this as the value in the motif:regex dictionary\n\t\tmotif_convmot[motif]=regex\n\t\t# Add to the dictionary of regex:original motif lengths\n\t\tconverted_motifs[regex]=len(motif)\n\treturn motif_convmot,converted_motifs\nmotif_convmot,converted_motifs = convert_degenerates()\n\ndef make_gene_seq_dict():\n\t\"\"\"\n\tCreates a dictionary 'gene_seq_dict' using the input fasta file in which the keys are the header lines (gene names) and the values are the concatenated strings of the gene's entire sequence.\n\t\"\"\"\n\twith open(fasta_file, 'r') as fasta:\n\t\tseq=''\n\t\tgene=''\n\t\tgene_seq_dict = {}\n\t\tfor line in fasta:\n\t\t\tline = line.strip('\\n')\n\t\t\t# To ensure that an empty sequence is not set as a value (occurs for the first gene in the file):\n\t\t\tif seq != '':\n\t\t\t\tgene_seq_dict[gene]=seq\n\t\t\t# Identify headers (gene names):\n\t\t\tif line.startswith('>'):\n\t\t\t\t# Remove the '>' symbol\n\t\t\t\tgene=line.split('>')[1]\n\t\t\t\t# Re-set sequence variable at the start of a new gene\n\t\t\t\tseq=''\n\t\t\t# Concatenate lines of a sequence\n\t\t\telse:\n\t\t\t\tseq+=line\n\t\t# This last 'if' statement is only for the very last line of the file; \n\t\t# otherwise the dictionary does not incorporate the last line of the last sequence.\n\t\tif fasta.readline()=='':\n\t\t\tgene_seq_dict[gene]=seq\n\treturn gene_seq_dict\ngene_seq_dict = make_gene_seq_dict()\n\ndef find_motifs():\n\t\"\"\"\n\tFor each gene in the fasta file, searches for each motif. For every match of the motif to the gene sequence, saves the starting indices in a list.\n\tReturns a list 'match_list' of tuples where each tuple includes the gene name, motif regex expression, length of original motif, and list of starting indices. If there are no matches of motif to gene, tuple is not added to the list. \n\tRefers to the pre-defined dictionary 'gene_seq_dict'.\n\t\"\"\"\n\tmatch_list=[]\n\tfor gene,seq in gene_seq_dict.items():\n\t\tfor motif,length in converted_motifs.items():\n\t\t\t# Regex expression that allows for overlapping matches. Saves starting index for each match. Case insensitive.\n\t\t\tmatch = [m.start(0) for m in re.finditer(rf'(?=({motif}))', seq, re.IGNORECASE)]\n\t\t\t# Append gene, motif, motif length and match sites to a list as long as there are motif-gene matches.\n\t\t\tif match != []:\n\t\t\t\tmatch_list.append((gene,motif,length,match))\n\treturn match_list\nmatch_list = find_motifs()\n\ndef find_exons():\n\t\"\"\"\n\tSearches for exons in the input fasta file (as denoted by capital letters) and returns a dictionary 'exon_coords_dict' in which the keys are the header lines (gene names) and the values are tuples of the exon's start and end indices (as a tuple) and the length of the gene's entire sequence (introns+exon).\n\tRefers to the pre-defined dictionary 'gene_seq_dict'.\n\t\"\"\"\n\texon_coords_dict={}\n\tfor gene,seq in gene_seq_dict.items():\n\t\t# Regex expression that saves the starting and ending indices for capital letter sequences (aka the exon)\n\t\texons = [(e.span(0)) for e in re.finditer('[ATCGUN]+', seq)]\n\t\t# Add gene name: exon start and end indices, length of entire gene sequence. Only the first exon is saved.\n\t\texon_coords_dict[gene]=(exons[0],len(seq))\n\treturn exon_coords_dict\nexon_coords_dict = find_exons()\n\ndef define_boundaries():\n\t\"\"\"\n\tDetermines the dimensions of the output svg based on the number of genes in the fasta file and the length of the longest gene sequence.\n\tRefers to the pre-defined dictionary 'exon_coords_dict'.\n\tOutputs the variables 'width' and 'height'.\n\t\"\"\"\n\tnum_genes = 0\n\tlongest_gene = 0\n\tfor gene,values in exon_coords_dict.items():\n\t\tnum_genes+=1\n\t\tif values[1] > longest_gene:\n\t\t\tlongest_gene=values[1]\n\twidth = longest_gene + 100\n\theight = 100num_genes + 25len(motif_list)+10\n\treturn width,height\n\nwidth,height = define_boundaries()\n\ndef color_scheme():\n\t\"\"\"\n\tFrom a list of pre-defined colors, associates each motif to a color.\n\tCreates a dictionary in which the keys are the motifs as regex expressions and the values are the colors in RGB notation.\n\t\"\"\"\n\t# Below is the list of default colors that will represent motifs:\n\t #blue magenta orange teal gray cyan\n\tcolor_list=[(0.1,0.4,0.7),(1,0.2,0.4),(1,0.5,0),(0,0.7,0.6),(0.8,0.8,0.8),(0,0.7,1)]\n\tcolor_dict={}\n\ti=0\n\tfor conv_motif in converted_motifs:\n\t\tcolor_dict[conv_motif]=color_list[i]\n\t\ti+=1\n\treturn color_dict\n\ncolor_dict=color_scheme()\n\ndef draw_genes():\n\t\"\"\"\n\tOutputs one svg of genes and motifs using Pycairo, where each gene is shown one after the other in the same order they appear in the fasta file. The motifs are overlaid on each gene where the sequences match. Inludes a legend that displays the motif color key.\n\t\"\"\"\n\tsurface = cairo.SVGSurface(image_file,width,height)\n\tcontext = cairo.Context(surface)\n\t# Set a background color\n\tcontext.save()\n\tcontext.set_source_rgb(1, 1, 1)\n\tcontext.paint()\n\tcontext.restore()\n\t# Set the width of the intron line\n\tcontext.set_line_width(2)\n\t# Set starting position of file (set margins)\n\typos=50\n\tindent=50\n\t# Move along the list of genes, drawing each gene one at a time\n\tfor gene,values in exon_coords_dict.items():\n\t\tmotif_counter=0\n\t\texon_start=values[0][0]\n\t\texon_length=values[0][1]-values[0][0]\n\t\texon_height=len(motif_list)5+10\n\t\t# Move to x,y position\n\t\tcontext.move_to(indent,ypos-exon_height)\n\t\tcontext.set_source_rgb(0,0,0)\n\t\tcontext.show_text(gene)\n\t\tcontext.move_to(indent,ypos)\n\t\t# Draw a line that is to scale to the entire gene sequence (the length of the entire gene is denoted by values[1])\n\t\tcontext.set_line_width(2)\n\t\tcontext.set_source_rgb(0,0,0)\n\t\tcontext.line_to(indent+values[1],ypos)\n\t\tcontext.stroke()\n\t\t# Key: context.rectangle(x start,y start,width,height)\n\t\tcontext.rectangle(indent+exon_start,ypos-exon_height/2,exon_length,exon_height)\n\t\tcontext.fill()\n\t\tfor item in match_list:\n\t\t\t# Refer to one gene at a time\n\t\t\tif gene==item[0]:\n\t\t\t\tfor conv_motif,length in converted_motifs.items():\n\t\t\t\t\t# Refer to one motif at a time\n\t\t\t\t\tif conv_motif==item[1]:\n\t\t\t\t\t\tmotif_counter+=1\n\t\t\t\t\t\tbox_height=exon_height-4motif_counter\n\t\t\t\t\t\t# Set color to associated motif color\n\t\t\t\t\t\tR,G,B=color_dict[conv_motif]\n\t\t\t\t\t\t# Draw each motif match at a time\n\t\t\t\t\t\tfor match in item[3]:\n\t\t\t\t\t\t\tcontext.rectangle(indent+match,ypos-box_height/2,length,box_height)\n\t\t\t\t\t\t\tcontext.set_source_rgb(R,G,B)\n\t\t\t\t\t\t\tcontext.fill_preserve()\n\t\t\t\t\t\t\tcontext.set_line_width(0.3)\n\t\t\t\t\t\t\tcontext.set_source_rgb(0,0,0)\n\t\t\t\t\t\t\tcontext.stroke()\n\t\typos += 100\n\t# Create box for legend\n\tbox_top = ypos-50\n\tcontext.set_source_rgb(0,0,0)\n\tcontext.rectangle(indent,box_top,len(max(motif_list,key=len))+100,motif_counter20+10)\n\tcontext.set_line_width(2)\n\tcontext.stroke()\n\t# Add motifs and motif colors to legend\n\tx=0\n\tfor motif in motif_list:\n\t\t# Print motif name in legend\n\t\tx+=1\n\t\tcontext.move_to(indent+30,box_top+15x)\n\t\tcontext.set_source_rgb(0,0,0)\n\t\tcontext.show_text(motif)\n\t\t# Associate each motif to its color value\n\t\tR,G,B=color_dict[motif_convmot[motif]]\n\t\tcontext.set_source_rgb(R,G,B)\n\t\tcontext.rectangle(indent+10,box_top+15*x-7,10,10)\n\t\tcontext.fill()\n\t# Finish drawing\n\tsurface.finish()\n\treturn\ndraw_genes()\n" }, { "alpha_fraction": 0.7496688961982727, "alphanum_fraction": 0.7509933710098267, "avg_line_length": 34.85714340209961, "blob_id": "768ab9d9f89d1883cc19f3aa45410abacf11e300", "content_id": "9d36a08520ff85502ef408e168836303cc1e3f62", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 765, "license_type": "no_license", "max_line_length": 199, "num_lines": 21, "path": "/README.md", "repo_name": "nicoleszc/motif-mark", "src_encoding": "UTF-8", "text": "# Motif Mark\n\nMotif Mark is a Python3-based script that allows the user to visualize genes and where motifs occur on them. It creates a color-coded image (.svg) using a fasta file and text file of motif sequences.\n\n## Output\n![Alt text](./example_output.svg)\n\n## Requirements\n\nMotif Mark requires two files: \n• a fasta file, where every exon is denoted by upper case letters introns by lower case letters \n• a text file of motifs, where every motif sequence is on a new line and follows IUPAC notation. \n\nAn example fasta file and motif file is found in this repo under ex_fasta.fasta and ex_motif.txt, respectively.\n\n## Installation\n\nTo run Motif Mark on your own computer, you will need the following Python modules: \n• argparse \n• re \n• cairo \n" } ]	2
397334469/radius-1xtest	https://github.com/397334469/radius-1xtest	d616af69c48e1b1102998c293e3b735b2048e567	fb9de4da70d5231be8261fa191fc36ebf42cbcb7	c559f91642ba77bef12b66a7fa8b090879129796	refs/heads/master	2020-08-31T16:55:04.252817	2018-07-03T05:56:51	2018-07-03T05:56:51	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5818815231323242, "alphanum_fraction": 0.642276406288147, "avg_line_length": 17.728260040283203, "blob_id": "99cc574714fbfac96455952f61cc99cff85451eb", "content_id": "facd0496525ca1711f1f64648733508b86b42cbf", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 2020, "license_type": "permissive", "max_line_length": 152, "num_lines": 92, "path": "/README-CN.md", "repo_name": "397334469/radius-1xtest", "src_encoding": "UTF-8", "text": "## radius-1xtest\n#### 简介\n一个简单的 802.1x 测试服务，类似于 [Masarykova 大学 ](https://radius.ics.muni.cz/eduroam-test/eduroam-test.cgi)的这个 eduroam 测试站点\n\n基于 Flask，轻量级\n\n使用 mscharpv2 发起 radius 挑战报文，其他协议之后考虑增加\n\n#### 安装\n\n需要 Python 2.7 以上版本\n\n克隆代码\n```\ngit clone https://github.com/shanghai-edu/radius-1xtest.git\ncd radius-1xtest\n```\n\n安装依赖\n```\nyum install python-pip\nyum install -y python-devel\nyum install libjpeg libjpeg-devel zlib zlib-devel\npip install virtualenv\n\nvirtualenv ./env\nsource env/bin/activate\npip install -r requirement.txt\n```\n\n#### 配置\n```\ncat config.py\n# BASIC APP CONFIG\nBIND_ADDRESS = '0.0.0.0'\nPORT = 81\nSECRET_KEY = \"session_secret_key\" # 建立 session 所使用的 key，session 用来存验证码\n\n# SSID CONFIG\nSSID_CONFIG = {\n\t\t\"test1x\":\n\t\t\t{\"RADIUS_HOST\":\"192.168.0.210\",\"RADIUS_SECRET\":\"802.1x\",\"RADIUS_PORT\":1812,\"NAS_IP\":\"192.168.80.5\"},\n\t\t\"eduroam\":\n\t\t\t{\"RADIUS_HOST\":\"192.168.0.220\",\"RADIUS_SECRET\":\"eduroam\",\"RADIUS_PORT\":1812,\"NAS_IP\":\"192.168.80.5\"},\n\t\t}\n# 字典的 key 将作为 url 的路径，例如 https://test.edu.cn/test/eduroam\n\n# API_KEY\nAPI_KEY = \"0c8d964e8fbd4cfcd040b5691d119968\"\n```\n\n#### 启动\n\n```\nchmod +x control\n./control start\n```\n\n#### 停止\n```\n./control stop\n```\n\n#### debug 模式运行\n\n```\n./env/bin/python run.py\n```\n\n#### 部署\n建议再套一层 nginx 做反向代理，以开启 https\n\n#### 运行截图\n访问 ```http://127.0.0.1:81/test/<ssid>``` 就可以测试了\n\n例如 ```http://127.0.0.1:81/test/eduroam```\n![](https://i.imgur.com/K7YlzZJ.jpg)\n\n\n#### API\nAPI 通过 header 中的 \"X-API-KEY\" 作为 API 验证。使用 `config.py` 中的 `API_KEY` 作为密钥：\n```\n#curl -H \"Content-Type: application/json\" -H \"X-API-KEY: 0c8d964e8fbd4cfcd040b5691d119968\" -d '{\"username\":\"[email protected]\",\"password\":\"test123\"}' \"https://test.edu.cn/api/v1/eduroam\"\n{\n \"result\": {\n \"method\": \"mscharpv2\", \n \"success\": true, \n \"time\": 0.36426687240600586, \n \"username\": \"[email protected]\"\n }\n}\n```" }, { "alpha_fraction": 0.6435015201568604, "alphanum_fraction": 0.6676689982414246, "avg_line_length": 33.53461456298828, "blob_id": "2028bd88b31d7f3d7968b3e52b495b2bd11f4ada", "content_id": "52eb03dcc9d34ead20a24d507c498026f14534c6", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 8979, "license_type": "permissive", "max_line_length": 97, "num_lines": 260, "path": "/lib/mschap2.py", "repo_name": "397334469/radius-1xtest", "src_encoding": "UTF-8", "text": "\"\"\"\n\tMicrosoft CHAP authentication, version 2\n\t\n\tThis code is based on the pseudocode from RFC 2759.\n\t\n\tWe since we only deal with Authentication type requests\n\tonly those methods involved in Access-Request messages\n\tare implemented\n\t\n\tReverse engineered for Python based on jradius's\n\timplementation in Java\n\t\n\t@author: lee(at)shinatama(dot)homelinux(dot)net\n\"\"\"\n# encoding=utf8\nfrom Crypto.Hash import MD4, SHA\nfrom Crypto.Cipher import DES\nfrom random import randrange\nfrom binascii import hexlify\n#from string import upper\n\nclass MSCHAP2:\n\tdef __init__(self):\n\t\tpass\n\n\t\"\"\"\n\t\t@summary: generates the content for the MS-CHAP2-Response attribute for\n\t\t\tauthentication purposes\n\t\t@param authChallenge: a 16 byte string consisting of random characters\n\t\t@type authChallenge: character string\n\t\t@param username: the contents of the User-Name attribute\n\t\t@type username: character string\n\t\t@param password: the clear-text password for the user\n\t\t@type password: character string\n\t\t@return: byte string of the encoded MS-CHAP2-Response attribute\n\t\t@rtype: string\n\t\t@note: The assembly of the MS-CHAP2-RESPONSE attribute has been taken\n\t\t\tfrom the jradius implementation which conducts the assembly like so:\n\t\t\t\t2-octets : Flags (where Flags = 0x00)\n\t\t\t 16 octets : Peer-Challenge\n\t\t\t\t8 octets : Reserved (where Reserved = 0x00)\n\t\t\t 24 octets : NT-Response\n\t\t\tThis is different from the RFC which appears to have the Flags at\n\t\t\tthe end of the field\n\t\"\"\"\n\t#def addAttrs(self, authChallenge, username, password):\n\tdef getAuthAttrs(self, username, password):\n\t\tresponse = \"\"\n\t\t#peerChallenge = \"0123456789123456\"\n\t\tauthChallenge = \"\"\n\t\tfor x in range(0,16):\n\t\t\tauthChallenge += chr(randrange(0, 256))\n\t\tpeerChallenge = \"\"\n\t\tfor x in range(0,16):\n\t\t\tpeerChallenge += chr(randrange(0, 256))\n\t\tntResponse = self._GenerateNTResponse(authChallenge, peerChallenge, username, password)\n\t\tfor x in range (0, 2):\n\t\t\tresponse += '\\x00'\n\t\tresponse += peerChallenge\n\t\tfor x in range(0, 8):\n\t\t\tresponse += '\\x00'\n\t\tresponse += ntResponse\n\t\t#print \"[DEBUG] [generate] value response: %s\" % upper(hexlify(response))\n\t\treturnAttrs= {}\n\t\treturnAttrs[\"MS-CHAP-Challenge\"] = authChallenge\n\t\treturnAttrs[\"MS-CHAP2-Response\"] = response\n\t\treturn returnAttrs\n\t\n\t\"\"\"\n\t\t@summary: checks an inbound MS-CHAP2-Response attribute to verify the NtResponse \n\t\t\tshould the it be the same as byte 26 onwards\n\t\t@param challenge: the contents of the MS-CHAP-Challenge attribute\n\t\t@type challenge: byte string\n\t\t@param response: the contents of the MS-CHAP2-Response attribute\n\t\t@type response: byte string\n\t\t@param username: the contents of the User-Name attribute\n\t\t@type username: string\n\t\t@param password: the original clear-text password for the User-Name attribute\n\t\t@return: true if the password is correct, false otherwise\n\t\t@rtype: boolean\n\t\t@note: The assembly of the MS-CHAP2-RESPONSE attribute has been taken\n\t\t\tfrom the jradius implementation which conducts the assembly like so:\n\t\t\t\t2-octets : Flags (where Flags = 0x00)\n\t\t\t 16 octets : Peer-Challenge\n\t\t\t\t8 octets : Reserved (where Reserved = 0x00)\n\t\t\t 24 octets : NT-Response\n\t\t\tThis is different from the RFC which appears to have the Flags at\n\t\t\tthe end of the field\n\t\"\"\"\n\t# commented out as this is not required for Access-Request only processing\n\t#def checkAuthAttrs(self, challenge, response, username, password):\n\t#\tpeerChallenge = response[2:16]\n\t#\tsentNtResponse = response[26:]\n\t#\tntResponse = self._GenerateNTResponse(self, challenge, peerChallenge, username, password)\n\t#\treturn ntResponse == sentNtResponse\n\t\n\t\"\"\"\n\t8.1. GenerateNTResponse()\n\t\n\t GenerateNTResponse(\n\t IN 16-octet AuthenticatorChallenge,\n\t IN 16-octet PeerChallenge,\n\t IN 0-to-256-char UserName,\n\t IN 0-to-256-unicode-char Password,\n\t OUT 24-octet Response )\n\t {\n\t 8-octet Challenge\n\t 16-octet PasswordHash\n\t\n\t ChallengeHash( PeerChallenge, AuthenticatorChallenge, UserName,\n\t giving Challenge)\n\t\n\t NtPasswordHash( Password, giving PasswordHash )\n\t ChallengeResponse( Challenge, PasswordHash, giving Response )\n\t }\n\t\"\"\"\n\tdef _GenerateNTResponse(self, AuthenticatorChallenge, PeerChallenge, UserName, Password):\n\t\tchallenge = self._ChallengeHash(PeerChallenge, AuthenticatorChallenge, UserName)\n\t\tpwHash = self._NtPasswordHash(Password)\n\t\tresponse = self._ChallengeResponse(challenge, pwHash)\n\t\treturn response\n\t\n\t\"\"\"\n\t8.2. ChallengeHash()\n\t\n\t ChallengeHash(\n\t IN 16-octet PeerChallenge,\n\t IN 16-octet AuthenticatorChallenge,\n\t IN 0-to-256-char UserName,\n\t OUT 8-octet Challenge\n\t {\n\t\n\t /\n\t SHAInit(), SHAUpdate() and SHAFinal() functions are an\n\t * implementation of Secure Hash Algorithm (SHA-1) [11]. These are\n\t * available in public domain or can be licensed from\n\t * RSA Data Security, Inc.\n\t /\n\t\n\t SHAInit(Context)\n\t SHAUpdate(Context, PeerChallenge, 16)\n\t SHAUpdate(Context, AuthenticatorChallenge, 16)\n\t\n\t /\n\t * Only the user name (as presented by the peer and\n\t * excluding any prepended domain name)\n\t * is used as input to SHAUpdate().\n\t /\n\t\n\t SHAUpdate(Context, UserName, strlen(Username))\n\t SHAFinal(Context, Digest)\n\t memcpy(Challenge, Digest, 8)\n\t }\n\t\"\"\"\n\tdef _ChallengeHash(self, PeerChallenge, AuthenticatorChallenge, UserName):\n\t\tchallenge = SHA.new(PeerChallenge + AuthenticatorChallenge + UserName).digest()\n\t\t#print \"[DEBUG] [_ChallengeHash] challenge: \" % upper(hexlify(challenge[0:8]))\n\t\treturn challenge[0:8]\n\t\n\t\"\"\"\n\t8.3. NtPasswordHash()\n\t\n\t NtPasswordHash(\n\t IN 0-to-256-unicode-char Password,\n\t OUT 16-octet PasswordHash )\n\t {\n\t /\n\t * Use the MD4 algorithm [5] to irreversibly hash Password\n\t * into PasswordHash. Only the password is hashed without\n\t * including any terminating 0.\n\t /\n\t }\n\t\"\"\"\n\tdef _NtPasswordHash(self, Password):\n\t\tunicodePw = Password.encode(\"utf-16-le\")\n\t\thashPw = MD4.new(unicodePw).digest()\n\t\t#print \"[DEBUG] [_NtPasswordHash] hashPw: %s\" % upper(hexlify(hashPw[0:17]))\n\t\treturn hashPw[0:17]\n\t\n\t\"\"\"\n\t8.5. ChallengeResponse()\n\t\n\t ChallengeResponse(\n\t IN 8-octet Challenge,\n\t IN 16-octet PasswordHash,\n\t OUT 24-octet Response )\n\t {\n\t Set ZPasswordHash to PasswordHash zero-padded to 21 octets\n\t\n\t DesEncrypt( Challenge,\n\t 1st 7-octets of ZPasswordHash,\n\t giving 1st 8-octets of Response )\n\t\n\t DesEncrypt( Challenge,\n\t 2nd 7-octets of ZPasswordHash,\n\t giving 2nd 8-octets of Response )\n\t\n\t DesEncrypt( Challenge,\n\t 3rd 7-octets of ZPasswordHash,\n\t giving 3rd 8-octets of Response )\n\t }\n\t\"\"\"\n\tdef _ChallengeResponse(self, challenge, pwhash):\n\t\tzPwHash = pwhash\n\t\t# for some reason in python we need to pad an extra byte so that\n\t\t# the offset works out correctly when we call DesEncrypt\n\t\tzPwHash += '\\x00' (22 - len(pwhash))\n\t\tresponse = \"\"\n\t\t#print \"[DEBUG] zPwHash: %s\" % upper(hexlify(zPwHash))\n\t\tfor x in range(0, 3):\n\t\t\toffset = x * 7\n\t\t\tresponse += self._DesEncrypt(challenge, zPwHash, offset)\n\t\treturn response\n\t\n\t\"\"\"\n\t8.6. DesEncrypt()\n\t\n\t DesEncrypt(\n\t IN 8-octet Clear,\n\t IN 7-octet Key,\n\t OUT 8-octet Cypher )\n\t {\n\t /\n\t Use the DES encryption algorithm [4] in ECB mode [10]\n\t * to encrypt Clear into Cypher such that Cypher can\n\t * only be decrypted back to Clear by providing Key.\n\t * Note that the DES algorithm takes as input a 64-bit\n\t * stream where the 8th, 16th, 24th, etc. bits are\n\t * parity bits ignored by the encrypting algorithm.\n\t * Unless you write your own DES to accept 56-bit input\n\t * without parity, you will need to insert the parity bits\n\t * yourself.\n\t /\n\t }\n\t \n\t This implementation was interpreted into python based on source\n\t code from jradius net.jradius.util.MSCHAP.Class#parity_key\n\t \n\t Turns a 7 octet key cut up from the NtPasswordHash into an\n\t 8 octect key as required by DES(ECB) encryption\n\t\"\"\"\n\tdef _DesEncrypt(self, clear, key, offset):\n\t\tcNext = 0\n\t\tcWorking = 0\n\t\thexKey = {}\n\t\t#print \"[DEBUG] [_56bitkey] key: %s offset: %d len(key): %d\" % (hexlify(key), offset, len(key))\n\t\tfor x in range(0,8):\n\t\t\tcWorking = 0xFF & int(hexlify(key[x + offset]),16)\n\t\t\thexKey[x] = ((cWorking >> x) \| cNext \| 1) & 0xFF\n\t\t\t#print \"[DEBUG] [_56bitKey] newKey[x]: %s x: %d\" % (hex(hexKey[x]),x)\n\t\t\tcWorking = 0xFF & int(hexlify(key[x + offset]),16) \n\t\t\tcNext = ((cWorking << (7 - x)))\n\t\t#print \"[DEBUG] [_56bitKey] hexKey: %s\" % hexKey\n\t\tnewKey = \"\"\n\t\tfor x in range(0,len(hexKey)):\n\t\t\t#print \"[DEBUG] [_56bitKey] hex(hexKey[x]): %s\" % hex(hexKey[x])\n\t\t\tnewKey += chr(int(hexKey[x]))\n\t\t#print \"[DEBUG] [_56bitKey] newKey: %s\" % hexlify(newKey)\n\t\tdes = DES.new(newKey, DES.MODE_ECB)\n\t\treturn des.encrypt(clear)\n" }, { "alpha_fraction": 0.5291750431060791, "alphanum_fraction": 0.6458752751350403, "avg_line_length": 28.235294342041016, "blob_id": "038b8f96b1f00469b40a37087ad9deb85bdbedf0", "content_id": "cd0af9502ecc26c4997901ca225cba5f76b623c1", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 547, "license_type": "permissive", "max_line_length": 104, "num_lines": 17, "path": "/config.py", "repo_name": "397334469/radius-1xtest", "src_encoding": "UTF-8", "text": "#coding=utf-8 \n# BASIC APP CONFIG\nBIND_ADDRESS = '0.0.0.0'\nPORT = 81\nSECRET_KEY = \"session_secret_key\" # 建立 session 所使用的 key，session 用来存验证码\n\n# SSID CONFIG\nSSID_CONFIG = {\n\t\t\"test1x\":\n\t\t\t{\"RADIUS_HOST\":\"192.168.0.210\",\"RADIUS_SECRET\":\"802.1x\",\"RADIUS_PORT\":1812,\"NAS_IP\":\"192.168.80.5\"},\n\t\t\"eduroam\":\n\t\t\t{\"RADIUS_HOST\":\"192.168.0.220\",\"RADIUS_SECRET\":\"eduroam\",\"RADIUS_PORT\":1812,\"NAS_IP\":\"192.168.80.5\"},\n\t\t}\n# 字典的 key 将作为 url 的路径，例如 https://test.edu.cn/test/eduroam\n\n# API_KEY\nAPI_KEY = \"0c8d964e8fbd4cfcd040b5691d119968\"\n" }, { "alpha_fraction": 0.5988950133323669, "alphanum_fraction": 0.6569060683250427, "avg_line_length": 18.255319595336914, "blob_id": "75076fcf210478354c8736629c13f45371623d25", "content_id": "6761abb15d77f85c9372e5c30fa3e816d6874729", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1814, "license_type": "permissive", "max_line_length": 152, "num_lines": 94, "path": "/README.md", "repo_name": "397334469/radius-1xtest", "src_encoding": "UTF-8", "text": "## radius-1xtest\n[中文](https://github.com/shanghai-edu/radius-1xtest/blob/master/README-CN.md)\n#### Introduction\nSimple 802.1x test server, just like [Masarykova univerzita ](https://radius.ics.muni.cz/eduroam-test/eduroam-test.cgi)\n\nBuilt by Flask\n\nuse mscharpv2 for radius challenge\n\nother protocol -- TODO \n\n#### Install\n\nYou need Python 2.7\n\nClone & Prepare\n```\ngit clone https://github.com/shanghai-edu/radius-1xtest.git\ncd radius-1xtest\n```\n\nInstall dependency\n```\nyum install python-pip\nyum install -y python-devel gcc\nyum install libjpeg libjpeg-devel zlib zlib-devel\npip install virtualenv\n\nvirtualenv ./env\nsource env/bin/activate\npip install -r requirement.txt\n```\n\n#### Configure\n```\ncat config.py\n# BASIC APP CONFIG\nBIND_ADDRESS = '0.0.0.0'\nPORT = 81\nSECRET_KEY = \"session_secret_key\" \n\n# SSID CONFIG\nSSID_CONFIG = {\n\t\t\"test1x\":\n\t\t\t{\"RADIUS_HOST\":\"192.168.0.210\",\"RADIUS_SECRET\":\"802.1x\",\"RADIUS_PORT\":1812,\"NAS_IP\":\"192.168.80.5\"},\n\t\t\"eduroam\":\n\t\t\t{\"RADIUS_HOST\":\"192.168.0.220\",\"RADIUS_SECRET\":\"eduroam\",\"RADIUS_PORT\":1812,\"NAS_IP\":\"192.168.80.5\"},\n\t\t}\n\n# API_KEY\nAPI_KEY = \"0c8d964e8fbd4cfcd040b5691d119968\"\n```\n\n\n#### start\n\n```\nchmod +x control\n./control start\n```\n\n#### stop\n```\n./control stop\n```\n\n#### debug run\n\n```\n./env/bin/python run.py\n```\n\n#### deploy\nuse nginx proxy to provide https\n\n#### Screenshots\nopen ```http://127.0.0.1:81/test/<ssid>``` in your browser.\n\nsuch as ```http://127.0.0.1:81/test/eduroam```\n![](https://i.imgur.com/K7YlzZJ.jpg)\n\n#### API\nuse API_KEY in config.py for the \"X-API-KEY\" in http header\n```\n#curl -H \"Content-Type: application/json\" -H \"X-API-KEY: 0c8d964e8fbd4cfcd040b5691d119968\" -d '{\"username\":\"[email protected]\",\"password\":\"test123\"}' \"https://test.edu.cn/api/v1/eduroam\"\n{\n \"result\": {\n \"method\": \"mscharpv2\", \n \"success\": true, \n \"time\": 0.36426687240600586, \n \"username\": \"[email protected]\"\n }\n}\n```\n" }, { "alpha_fraction": 0.6385512351989746, "alphanum_fraction": 0.6484743356704712, "avg_line_length": 41.43157958984375, "blob_id": "3d30d9603d5e22bb8200b45d5e16da29c46ff4fa", "content_id": "8f24f7a9e4b7ef330527bc1257e0da7ab27ede87", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4041, "license_type": "permissive", "max_line_length": 197, "num_lines": 95, "path": "/app/views.py", "repo_name": "397334469/radius-1xtest", "src_encoding": "UTF-8", "text": "#coding=utf-8\nimport jinja2\nimport json\nfrom time import time\nfrom flask import request,jsonify,render_template,make_response,session,url_for\nfrom app import app\nfrom utils import radius_challenge\nfrom utils import create_validate_code\nfrom functools import wraps\n\ndef require_appkey(view_function):\n @wraps(view_function)\n # the new, post-decoration function. Note args and *kwargs here.\n def decorated_function(args, *kwargs):\n if request.headers.get('X-API-KEY') and request.headers.get('X-API-KEY') == app.config[\"API_KEY\"]:\n return view_function(args, **kwargs)\n else:\n result = {\"sucess\":False,\"msg\":\"missing API-KEY or KEY is Wrong\"}\n return jsonify(result=result),403\n return decorated_function\n\[email protected]('/api/v1/<string:ssid>', methods=['POST'])\n@require_appkey\ndef radius1x_api(ssid):\n\tssid_config = app.config['SSID_CONFIG']\n\tif ssid not in ssid_config:\n\t\treturn \"404 page not found\",404\n data = request.get_json()\n if not data or not 'username' in data or not 'password' in data:\n result = {\"success\":False,\"msg\":\"username or password not found\"}\n return jsonify(result=result),400\n username = data[\"username\"].encode(\"utf-8\")\n password = data[\"password\"].encode(\"utf-8\")\n\ttsStart = time()\n try:\n\t\tres = radius_challenge(username, password, ssid_config[ssid]['RADIUS_HOST'], ssid_config[ssid]['RADIUS_SECRET'], ssid_config[ssid]['RADIUS_PORT'], ssid_config[ssid]['NAS_IP'],False)\n \tt = time() - tsStart\n \tresult = {\"username\":username,\"method\":\"mscharpv2\",\"time\":t,\"success\":res}\n \treturn jsonify(result=result),200\n\texcept:\n\t\tt = time() - tsStart\n\t\tresult = {\"username\":username,\"method\":\"mscharpv2\",\"time\":t,\"success\":False}\n\t\treturn jsonify(result=result),200\n\[email protected]('/code', methods=['GET'])\ndef code():\n \"\"\"生成验证码\n \"\"\"\n from io import BytesIO\n\n output = BytesIO()\n code_img, code_str = create_validate_code()\n code_img.save(output, 'jpeg')\n img_data=output.getvalue()\n output.close()\n response = make_response(img_data)\n response.headers['Content-Type'] = 'image/jpg'\n session['code_text'] = code_str\n return response \n\[email protected]('/test/<string:ssid>', methods=['GET','POST'])\ndef radius_test(ssid):\n ssid_config = app.config['SSID_CONFIG']\n if ssid not in ssid_config:\n return \"404 page not found\",404\n\tif request.method == 'GET':\n\t\treturn render_template('radius1x.html',ssid=ssid)\n\t\n\tusername = request.form['username'].encode(\"utf-8\")\n\tpassword = request.form['password'].encode(\"utf-8\")\n\tverify_code = request.form['verify_code']\n\tif 'code_text' in session and verify_code.lower() != session['code_text'].lower():\n\t\treturn render_template('radius1x.html',ssid=ssid,verify_error=True)\n \ttsStart = time()\n \ttry:\n \tres = radius_challenge(username, password, ssid_config[ssid]['RADIUS_HOST'], ssid_config[ssid]['RADIUS_SECRET'], ssid_config[ssid]['RADIUS_PORT'], ssid_config[ssid]['NAS_IP'],False)\n \t\tt= time() - tsStart\n\t\tresult = {\"username\":username,\"method\":\"mscharpv2\",\"time\":t,\"success\":res}\n\t\tif result[\"success\"]:\n \t \taccess = \"Access-Accept\"\n \t\telse:\n \t\taccess = \"Access-Reject\"\n \t \ttimeusage = (\"%.2f\" % result['time'])\n \t\ttimeusage = str(timeusage) + \"s\"\n \t\treturn render_template('radius1x.html', ssid=ssid,username=result['username'], method=result['method'], timeusage=timeusage, success=result['success'], access=access)\n\texcept:\n \tt = time() - tsStart\n\t\tresult = {\"username\":username,\"method\":\"mscharpv2\",\"time\":t,\"success\":False}\n\t\tif result[\"success\"]:\n\t\t\taccess = \"Access-Accept\"\n\t\telse:\n\t\t\taccess = \"Access-Reject\"\n\t\ttimeusage = (\"%.2f\" % result['time'])\n\t\ttimeusage = str(timeusage) + \"s\"\n\t\treturn render_template('radius1x.html', ssid=ssid,username=result['username'], method=result['method'], timeusage=timeusage, success=result['success'], access=access)\n" }, { "alpha_fraction": 0.5094339847564697, "alphanum_fraction": 0.698113203048706, "avg_line_length": 12.25, "blob_id": "c3853ad762658cdbf8a8486d5fb42cdab972e125", "content_id": "ee4881fdeaccea5befc0088da40b02d3ba222d9b", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 53, "license_type": "permissive", "max_line_length": 15, "num_lines": 4, "path": "/requirement.txt", "repo_name": "397334469/radius-1xtest", "src_encoding": "UTF-8", "text": "flask>=0.12\npycrypto>=2.6.1\nPillow>=4.0\ngunicorn>=19\n" } ]	6
snail-fuji/ethereum-transactions-clusters	https://github.com/snail-fuji/ethereum-transactions-clusters	f15706d8a027c1fe0796f849f0e72950506e127a	dcf48ccd9fb0270eabaed462638c19a0a339a65a	0a1c3b71bd4cb2ec38be8e487d65cd843e7bcdd0	refs/heads/master	2023-08-05T05:04:25.193385	2017-10-18T20:53:09	2017-10-19T09:10:48	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7219917178153992, "alphanum_fraction": 0.7385892271995544, "avg_line_length": 33.42856979370117, "blob_id": "6d00c4efaaedf16bd4093459299ddb9b3fc7db20", "content_id": "41aa5469c34b06be06d4eb02a40ef4ca62cd8fd7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 241, "license_type": "no_license", "max_line_length": 111, "num_lines": 7, "path": "/README.md", "repo_name": "snail-fuji/ethereum-transactions-clusters", "src_encoding": "UTF-8", "text": "## Load transactions into neo4j\n\nTo load transaction data, run:\n```bash\npython3 load_neo4j.py & # Will load tasks into redis\ncelery worker -A load_neo4j -b redis:// --loglevel=error # Will run celery with redis queue to complete loading\n```\n" }, { "alpha_fraction": 0.5717665553092957, "alphanum_fraction": 0.5922712683677673, "avg_line_length": 32.3684196472168, "blob_id": "5d1151e45a6732450c16cb110b46f60b4879c149", "content_id": "dc52006c30e2731730a2eeaf11905d49856b0820", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1268, "license_type": "no_license", "max_line_length": 102, "num_lines": 38, "path": "/load_neo4j.py", "repo_name": "snail-fuji/ethereum-transactions-clusters", "src_encoding": "UTF-8", "text": "import pandas as pd\nfrom neo4j.v1 import GraphDatabase, basic_auth\nfrom celery import Celery\nimport os\n\nIN_ADDRESS = 'from'\nOUT_ADDRESS = 'to'\nAMOUNT = 'value'\n\napp = Celery('tasks', broker='redis://')\n\[email protected]\ndef load_chunk(path):\n chunk = pd.read_csv(path)\n driver = GraphDatabase.driver(\"bolt://localhost:7687\", auth=basic_auth(\"neo4j\", \"blockchain\"))\n session = driver.session()\n \n for index, row in chunk.iterrows():\n session.run(\"MERGE (address1:Address {address:{address1}})\"\n \"MERGE (address2:Address {address:{address2}})\"\n \"CREATE UNIQUE (address1)-[t:Transactions]->(address2)\"\n \"SET t.amount = coalesce(t.amount, 0) + {amount}\"\n \"SET t.number = coalesce(t.number, 0) + 1\",\n {\"address1\": row[IN_ADDRESS], \"address2\": row[OUT_ADDRESS], 'amount': row[AMOUNT]}\n del chunk\n os.remove(path)\n session.close()\n\nprint(__name__)\nif __name__ == \"__main__\":\n ethereum = pd.read_csv(\"./transactions.csv\", chunksize=10000, iterator=True, sep=\";\", header=0)\n index = 0\n for chunk in ethereum:\n index += 1\n path = './chunks/chunk' + str(index)\n chunk.to_csv(path)\n load_chunk.delay(path)\n del chunk\n" }, { "alpha_fraction": 0.6722221970558167, "alphanum_fraction": 0.6777777671813965, "avg_line_length": 58.66666793823242, "blob_id": "d4951a287701c05706771067d43799ea2418b927", "content_id": "f9aac6a0697454bc135fab30c887a05a67f09f4d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 180, "license_type": "no_license", "max_line_length": 64, "num_lines": 3, "path": "/load_neo4j.sh", "repo_name": "snail-fuji/ethereum-transactions-clusters", "src_encoding": "UTF-8", "text": "neo4j-admin import --database addresses.db --id-type string \\\n --nodes:Address addresses_import.csv \\\n --relationships:Transaction transactions_import.csv \n" }, { "alpha_fraction": 0.694656491279602, "alphanum_fraction": 0.7010177969932556, "avg_line_length": 31.75, "blob_id": "5c514af22cfa6bc1ac6850d1ce44742ee458d32d", "content_id": "316eeacdc19e4224607b0d79a78dd0fcbe3372b8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 786, "license_type": "no_license", "max_line_length": 104, "num_lines": 24, "path": "/load_neo4j_csv.py", "repo_name": "snail-fuji/ethereum-transactions-clusters", "src_encoding": "UTF-8", "text": "import pandas as pd\n\nethereum = pd.read_csv(\"./transactions.csv\", header=0, sep=\";\", nrows=1000) # Use desired number of rows\n\naddresses = open(\"./addresses_import.csv\", \"wb\")\naddresses.write(\"address:ID(Address)\\n\".encode())\n\nall_addresses = set(ethereum[\"from\"]).union(set(ethereum[\"to\"]))\n\nfor address in all_addresses:\n addresses.write(\"{}\\n\".format(address).encode())\n\naddresses.close()\n\ntransactions = open(\"./transactions_import.csv\", \"wb\")\ntransactions.write(\":START_ID(Address), amount, :END_ID(Address)\\n\".encode())\n\nfor index, transaction in ethereum.iterrows():\n from_address = transaction[\"from\"]\n to_address = transaction[\"to\"]\n amount = transaction[\"value\"]\n transactions.write(\"{}, {}, {}\\n\".format(from_address, amount, to_address).encode())\n\ntransactions.close()\n" } ]	4
jedrzejasgard/sprawdzanie_cen	https://github.com/jedrzejasgard/sprawdzanie_cen	80d86f7569b157c51d99f163f27212c12f45b477	6b568399e0f4b0b5bd504a89a19c017cc611ea61	a88b0e0c8e63db047b7c3dee04977edddcd36e44	refs/heads/master	2023-08-21T13:52:59.893802	2021-10-07T12:15:34	2021-10-07T12:15:34	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6244344115257263, "alphanum_fraction": 0.6289592981338501, "avg_line_length": 24.674419403076172, "blob_id": "d7e010197e92707b006d57879d9d250c018ac774", "content_id": "ef9671a71c46b43917c412a4bee8b4ac71af0c75", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1108, "license_type": "no_license", "max_line_length": 111, "num_lines": 43, "path": "/porownaj_ceny.py", "repo_name": "jedrzejasgard/sprawdzanie_cen", "src_encoding": "UTF-8", "text": "import configparser\nfrom time import gmtime, strftime\nimport datetime\n\n# laduje hasla i delikatne dane\nconfig = configparser.ConfigParser()\nconfig.read('konkurencja.ini')\n\n\ndef sprawdź_cene_macma():\n macma_use = config.get('macma','usr')\n macma_pass = config.get('macma','pass')\n pass\n\ndef today_data():\n data = strftime('%Y, %m, %d', gmtime()).split(',')\n y = int(data[0])\n m = int(data[1])\n d = int(data[2])\n data = datetime.date(y, m, d).strftime(\"%V\")\n return data\n\n\ndef zapisz_blad(kto_z_konk,text_bledu):\n with open(f\"./bledy/{kto_z_konk}-bledy-tydzien{data}.txt\", 'a+') as plik:\n plik.write(f\"{text_bledu}\\n\")\n\n\ndef zapisz_wyprzedaz(kto_z_konk,indeksProd,cena_wyp,asgard_prod):\n with open(f\"./wyprz/{kto_z_konk}-wyprzedaż-tydzien{data}.txt\", 'a+') as plik:\n plik.write(f\"Asgard index: {asgard_prod} (konkurencja:{indeksProd}) cena na wyprzedaży : {cena_wyp}\\n\")\n\n\ndef format_float(wartosc):\n try:\n return round(float(wartosc.replace(',','.')), 2)\n except:\n return round(float(wartosc), 2)\n\n\n\nif __name__ == '__main__':\n main()\n\n" } ]	1
empireio/django-api-domains	https://github.com/empireio/django-api-domains	3c65f6b460cdea30239e0183176da0f0775dc641	fcb06d15ec0a707c436aefbb322fbff30b0bc536	3a3197891584ceee8fca6d3d9eefd664bb23e0ae	refs/heads/master	2023-03-18T15:10:46.953081	2021-03-17T18:27:07	2021-03-17T18:27:07	343,283,574	2	0	MIT	2021-03-01T03:54:19	2021-02-28T00:17:56	2020-04-30T23:37:05	null	[ { "alpha_fraction": 0.6238030195236206, "alphanum_fraction": 0.6238030195236206, "avg_line_length": 22.580644607543945, "blob_id": "4d7913d922e0dc65c811a10241def4aa1b36734e", "content_id": "3ce42a46e8f11a6ce1ff6a63f1cae57b1d3d6f95", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 731, "license_type": "permissive", "max_line_length": 76, "num_lines": 31, "path": "/example_domain/interfaces.py", "repo_name": "empireio/django-api-domains", "src_encoding": "UTF-8", "text": "import uuid\nfrom typing import Dict, Str # noqa\n\n# Could be an internal domain or an HTTP API client - we don't care!\nfrom src.authors.apis import AuthorAPI\n\n\n# plain example\ndef update_author_name(, author_name: Str, author_guid: uuid.UUID) -> None:\n AuthorAPI.update_author_name(\n guid=author_guid,\n name=author_name,\n )\n\n\n# class example\nclass AuthorInterface:\n @staticmethod\n def get_author(, guid: uuid.UUID) -> Dict:\n return AuthorAPI.get(guid=guid)\n\n @staticmethod\n def update_author_name(\n ,\n author_name: Str,\n author_guid: uuid.UUID,\n ) -> None:\n AuthorAPI.update_author_name(\n guid=author_guid,\n name=author_name,\n )\n" }, { "alpha_fraction": 0.7533512115478516, "alphanum_fraction": 0.7533512115478516, "avg_line_length": 34, "blob_id": "3cb26088308238c9e25dd8c4132afd481d499c60", "content_id": "73535bd6d12a348cbc903d5517874492e3cc4ec2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1119, "license_type": "permissive", "max_line_length": 193, "num_lines": 32, "path": "/apis.md", "repo_name": "empireio/django-api-domains", "src_encoding": "UTF-8", "text": "## Django REST Framework\n\n[Django REST Framework](https://www.django-rest-framework.org/) is the de facto framework for building REST API services with Django.\n\nWhen using DRF, we can organise the logic in a domain this way:\n\n- `urls.py` - Router and URL configuration.\n- `api/rest.py` - DRF view functions or view classes.\n- `serializers.py` - Serialization for models.\n\nAdditional ruling for DRF:\n\n You should serialize all models using DRF serializers.\n* You should not use the [ModelMixin](https://www.django-rest-framework.org/api-guide/generic-views/#mixins) Viewsets as they will tightly couple the data layer with the presentation layer.\n\n## Graphene Django\n\nWhen using Graphene-Django, we can organise the logic in a domain this way:\n\n- `api/graphql.py` - Queries and Mutations.\n\nAdditional ruling for Graphene-Django:\n\n* You should not tightly link an `DjangoObjectType` to a Django model as this will tightly couple the data layer with the presentation layer. Instead, use a generic `ObjectType`.\n\n\n\n[Next up, we'll take a look at testing](testing.md)\n\nor\n\n[Go back to the main page](README.md)" }, { "alpha_fraction": 0.7226890921592712, "alphanum_fraction": 0.743697464466095, "avg_line_length": 22.799999237060547, "blob_id": "71e6c73e32e1760df4cec5605148f7cb8528f9c5", "content_id": "7dbb5052102b8f18524ebba9853ae298176c4a75", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 238, "license_type": "permissive", "max_line_length": 63, "num_lines": 10, "path": "/example_domain/models.py", "repo_name": "empireio/django-api-domains", "src_encoding": "UTF-8", "text": "import uuid\n\nfrom django.db import models\n\n\nclass Article(models.Model):\n\n id = models.UUIDField(primary_key=True, default=uuid.uuid4)\n title = models.CharField(max_length=256)\n author_guid = models.UUIDField(default=uuid.uuid4)\n" }, { "alpha_fraction": 0.6111111044883728, "alphanum_fraction": 0.6111111044883728, "avg_line_length": 27.983051300048828, "blob_id": "f158008dc8d5b9eadb89e22b5c77c21288a4f5d7", "content_id": "a034c1ae288bc52d500d1f09296d2e01a6f480cc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1710, "license_type": "permissive", "max_line_length": 82, "num_lines": 59, "path": "/example_domain/services.py", "repo_name": "empireio/django-api-domains", "src_encoding": "UTF-8", "text": "import logging\nimport uuid\nfrom typing import Dict, Str # noqa\n\nfrom .interfaces import AuthorInterface\nfrom .models import Article\n\nlogger = logging.getLogger(__name__)\n\n\n# Plain example\ndef get_article(, guid: uuid.UUID) -> Dict:\n article = Article.objects.get(guid=guid)\n author = AuthorInterface.get_author(guid=article.author_guid)\n return {\n 'title': article.title,\n 'author_name': author.name,\n }\n\n\n# Class example\nclass ArticleService:\n @staticmethod\n def get_article(, guid: uuid.UUID) -> Dict:\n article = Article.objects.get(guid=guid)\n author = AuthorInterface.get_author(guid=article.author_guid)\n return {\n 'title': article.title,\n 'author_name': author.name,\n }\n\n @staticmethod\n def create_article(, title: Str, author_guid: uuid.UUID) -> Dict:\n logger.info('Creating new article')\n new_article = Article.objects.create(title=title, author_guid=author_guid)\n author = AuthorInterface.get_author(guid=new_article.author_guid)\n return {\n 'title': new_article.title,\n 'author_name': author.name,\n }\n\n @staticmethod\n def update_article_title_and_author_name(\n ,\n title: Str,\n author_name: Str,\n author_guid: uuid.UUID,\n guid: uuid.UUID,\n ) -> Dict:\n logger.info('Updating article title and author name')\n article = Article.objects.get(guid=guid).update(title=title)\n author = AuthorInterface.update_author_name(\n name=author_name,\n guid=author_guid,\n )\n return {\n 'title': article.title,\n 'author_name': author.name,\n }\n" }, { "alpha_fraction": 0.6513569951057434, "alphanum_fraction": 0.6513569951057434, "avg_line_length": 26.84883689880371, "blob_id": "4f1290ca05266592d20cec3e545a4375c271f73b", "content_id": "4ce03e07222b68bdd609cc62686e7b5372323340", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2395, "license_type": "permissive", "max_line_length": 82, "num_lines": 86, "path": "/example_domain/apis.py", "repo_name": "empireio/django-api-domains", "src_encoding": "UTF-8", "text": "import logging\nimport uuid\nfrom typing import Dict # noqa\n\nimport graphene\nfrom graphene import ObjectType, relay\n\nfrom .services import ArticleService\n\nlogger = logging.getLogger(__name__)\n\n\n# Internal API\nclass ArticleAPI:\n @staticmethod\n def get(, article_guid: uuid.UUID) -> Dict:\n logger.info('method \"get\" called')\n return ArticleService.get_article(id=article_guid)\n\n\n# graphQL Entity\nclass ArticleEntity(ObjectType):\n class Meta:\n interfaces = (relay.Node,)\n\n title = graphene.String()\n author_name = graphene.String()\n\n\n# graphQL mutation\nclass CreateArticle(relay.ClientIDMutation):\n class Input:\n article_title = graphene.String(required=True)\n author_guid = graphene.UUID(required=True)\n\n article = graphene.Field(ArticleEntity)\n\n @classmethod\n def mutate_and_get_payload(cls, root, info, input):\n new_article = ArticleService.create_article(\n title=input.get('article_title'), author_guid=input.get('author_guid')\n )\n return ArticleEntity(\n title=new_article['title'],\n author_name=new_article['author_name'],\n )\n\n\n# graphQL mutation\nclass UpdateArticleAndAuthorName(relay.ClientIDMutation):\n class Input:\n article_title = graphene.String(required=True)\n author_name = graphene.String(required=True)\n author_guid = graphene.UUID(required=True)\n article_guid = graphene.UUID(required=True)\n\n article = graphene.Field(ArticleEntity)\n\n @classmethod\n def mutate_and_get_payload(cls, root, info, *input):\n article = ArticleService.update_article_title_and_author_name(\n title=input.get('article_title'),\n id=input.get('article_guid'),\n author_guid=input.get('author_guid'),\n author_name=input.get('author_name'),\n )\n return ArticleEntity(\n title=article['title'],\n author_name=article['author_name'],\n )\n\n\nclass Mutation:\n create_article = CreateArticle.Field()\n\n\nclass Query:\n article = graphene.Field(ArticleEntity)\n\n def resolve_article(self, info):\n logger.info(f\"graphQL query for article with id {info.get('id')}\")\n article = ArticleService.get_article(id=info.get('id'))\n return ArticleEntity(\n title=article['title'],\n author_name=article['author_name'],\n )\n" } ]	5
rajpokhrel/KMeans	https://github.com/rajpokhrel/KMeans	5f6eaa002f624162582f72e5373b89d714c5fbe4	96d053377f3ded166eb4631d1ea2eeac80548e4f	2e0f5ff969a0bb93317690a1b1c6a8e40aa80b78	refs/heads/master	2020-05-24T04:53:11.428237	2019-05-16T21:16:19	2019-05-16T21:16:19	187,102,110	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.605318009853363, "alphanum_fraction": 0.6167883276939392, "avg_line_length": 30.702478408813477, "blob_id": "0493414d4e5d45debdecfa12a01e6e40ca595923", "content_id": "e8e82bcafbf6f174123f8960d7c08a647380ed97", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3836, "license_type": "no_license", "max_line_length": 93, "num_lines": 121, "path": "/kmeans.py", "repo_name": "rajpokhrel/KMeans", "src_encoding": "UTF-8", "text": "import numpy as np\nfrom sklearn.metrics import accuracy_score\nfrom sys import exit\nimport numpy as np\nfrom random import randint\nfrom copy import deepcopy\nfrom sklearn.metrics import pairwise_distances_argmin\nimport random\nfrom sklearn.metrics.cluster import normalized_mutual_info_score as NMI\nfrom sklearn.cluster import KMeans\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\nfrom sklearn.metrics import f1_score\nfrom numpy.random import RandomState\nfrom sklearn.metrics import accuracy_score\n\ndef norm(x):\n \"\"\"\n >>> Function you should not touch\n \"\"\"\n max_val = np.max(x, axis=0)\n x = x/max_val\n return x\n\ndef rand_center(data,k):\n \"\"\"\n >>> Function you need to write\n >>> Select \"k\" random points from \"data\" as the initial centroids.\n \"\"\"\n num = data.shape[1]\n centroids = np.zeros((k,num))\n for x in range(num):\n dmin,dmax = np.min(data[:,x]), np.max(data[:,x])\n centroids[:,x] = dmin + (dmax - dmin) * np.random.rand(k)\n return centroids\n\n\ndef converged(centroids1, centroids2):\n set1 = set([tuple(c) for c in centroids1])\n set2 = set([tuple(c) for c in centroids2])\n return (set1 == set2)\n\ndef update_centroids(data, centroids, k=3):\n \"\"\"\n >>> Function you need to write\n >>> check whether centroids1==centroids\n >>> add proper code to handle infinite loop if it never converges\n \"\"\"\n n = data.shape[0]\n label = np.zeros(n, dtype=np.int32)\n for i in range(n):\n min_dist,min_index = np.inf, -1\n for j in range(k):\n dist = SSE(data[i],centroids[j])\n if dist < min_dist:\n min_dist, min_index = dist,j\n label[i] = min_index\n for m in range(k):\n centroids[m] = np.mean(data[label==m],axis=0)\n return centroids,label\n\ndef kmeans(data,k=3):\n \"\"\"\n >>> Function you should not touch\n \"\"\"\n # step 1:\n centroids = rand_center(data,k)\n converge = False\n converged_counter = 1\n while not converge:\n old_centroids = np.copy(centroids)\n # step 2 & 3\n centroids, label = update_centroids(data, old_centroids, k)\n # step 4\n converge = converged(old_centroids, centroids)\n converged_counter +=1\n if converged_counter == 1000:\n print(\"infinete loop exiting\")\n exit()\n print(\">>> final centroids\")\n print(centroids)\n return centroids, label\n\ndef evaluation(predict, ground_truth):\n \"\"\"\n >>> use F1 and NMI in scikit-learn for evaluation\n \"\"\"\n score = f1_score(ground_truth, predict, average='macro')\n res = NMI(ground_truth,predict)\n acc = accuracy_score(ground_truth,predict)\n print(\"Score: \", score)\n print(\"NMI: \",res)\n print(\"Accuracy: \", acc)\n\ndef gini(predict, ground_truth):\n \"\"\"\n >>> use the ground truth to do majority vote to assign a flower type for each cluster\n >>> accordingly calculate the probability of missclassifiction and correct classification\n >>> finally, calculate gini using the calculated probabilities\n \"\"\"\n vote = np.bincount(predict).argmax()\n unique, counts = np.unique(predict, return_counts=True)\n count_dict = dict(zip(unique, counts))\n prob = count_dict[vote] * 1.0/len(predict)\n wrong_prob = 1 - prob\n gini = 1 - (prob2) + (wrong_prob2)\n print (\"Gini for Majority Vote Label \"+ str(vote) + \" is \" + str(gini))\n for x in count_dict:\n if x != vote:\n prob = count_dict[vote] * 1.0/len(predict)\n wrong_prob = 1 - prob\n gini = 1 - (prob2) + (wrong_prob2)\n print (\"Gini of Label \" + str(x) + \" is \" + str(gini))\n \n \ndef SSE(centroids, data):\n \"\"\"\n >>> Calculate the sum of squared errors for each cluster\n \"\"\"\n sse = np.sum((centroids-data)**2)\n return np.sqrt(sse)\n" } ]	1
jtzadoyko/fileSort	https://github.com/jtzadoyko/fileSort	f395b4455a7a0646776081f215d94a157185c240	0d8b28d935e19956a36770b026d41ef21c66bef0	7b191adb71e900f2d0ad2006da0c0e3df5dd1826	refs/heads/master	2022-05-19T13:41:51.172268	2022-04-30T04:29:13	2022-04-30T04:29:13	201,702,636	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6043956279754639, "alphanum_fraction": 0.6043956279754639, "avg_line_length": 29.66666603088379, "blob_id": "4e683b0c63cf8e6191866f291e3ff0ab3281cfd8", "content_id": "6ef84a06703e1ed10c3cebcd689269af37aff264", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 91, "license_type": "no_license", "max_line_length": 80, "num_lines": 3, "path": "/a.py", "repo_name": "jtzadoyko/fileSort", "src_encoding": "UTF-8", "text": "import os\n\nos.system(\"python pysort.py -s C:\\\\pysort\\\\a\\\\b -t C:\\\\pysort\\\\a\\\\b\\\\z -e .txt\")" }, { "alpha_fraction": 0.6009838581085205, "alphanum_fraction": 0.6097294092178345, "avg_line_length": 26.712121963500977, "blob_id": "e1195c621e23b6853e977e83c2687a02bf26dc92", "content_id": "2f6fe2bca91d6130096c0c6452f9c55d14ca848d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3659, "license_type": "no_license", "max_line_length": 85, "num_lines": 132, "path": "/pysort.py", "repo_name": "jtzadoyko/fileSort", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n# @Author: jtzdoyko\n# @Date: 2022-04-29 17:21:56\n# @Last Modified by: jtzdoyko\n# @Last Modified time: 2022-04-30 00:28:47\n\nimport os\nimport shutil\nimport argparse\nimport datetime\nimport uuid\nfrom typing import Optional, List\nimport sys\nimport pathlib\n\ndef set_args():\n\t\"\"\"providing arguments for exec\"\"\"\n\tparser = argparse.ArgumentParser(description='parse pysort args')\n\tparser.add_argument('-s', '--src', required=True, help='source directory')\n\tparser.add_argument('-t', '--tgt', required=True, help='target directory')\n\tparser.add_argument('-e', '--ext', required=False, nargs='*', help='file extension')\n\treturn parser.parse_args()\n\n\ndef create_dir(path: str) -> Optional[str]:\n \"\"\"creating full directory\n\n Keyword arguments:\n path -- the directory to create\n \"\"\"\n if not check_dir(path):\n os.makedirs(path)\n return path\n\n\ndef check_dir(path: str) -> bool:\n \"\"\"Checking if path/directory exists\n\n Keyword arguments:\n path -- the directory to check for exists\n \"\"\"\n return os.path.isdir(path)\n\n\ndef check_file(path: str, file: str) -> bool:\n \"\"\"Checking if file exists\n\n Keyword arguments:\n path -- the directory for the file\n file -- the name of the file\n \"\"\"\n if check_dir(path):\n f = os.path.join(path, file)\n return os.path.isfile(f)\n\n\ndef check_file_type(path: str, file: str) -> Optional[str]:\n \"\"\"Checking file type\n\n Keyword arguments:\n path -- the directory for the file\n file -- the name of the file\n \"\"\"\n if check_dir(path):\n f = os.path.join(path, file)\n if check_file(path, file):\n return os.path.splitext(f)[1]\n\n\ndef list_files(path: str) -> Optional[List[Optional[str]]]:\n \"\"\"Listing files for a particular directory\n\n Keyword arguments:\n path -- the directory to check for exists\n \"\"\"\n if check_dir(path):\n return next(os.walk(path), (None, None, []))[2] # [] if no file\n\n\ndef move_file(src_dir: str,\n src_file: str,\n tgt_dir: str,\n tgt_file: str\n ) -> Optional[str]:\n \"\"\"moving file from source to target\n\n\tKeyword arguments:\n\tsrc_dir -- the source dir of file to move from\n\tsrc_file -- the name of the source file to move from\n\ttgt_dir -- the target dir of file to move to\n\ttgt_file -- the name of the tgt file to move to\n\t\"\"\"\n src = os.path.join(src_dir, src_file)\n tgt = os.path.join(tgt_dir, tgt_file)\n if check_file(src_dir, src_file):\n if not check_dir(tgt_dir):\n create_dir(tgt_dir)\n shutil.move(src, tgt)\n return tgt\n elif not check_file(tgt_dir, tgt_file):\n shutil.move(src, tgt)\n return tgt\n else:\n new_tgt = f\"{uuid.uuid4()}_{tgt_file}\"\n shutil.move(src, os.path.join(tgt_dir, new_tgt))\n return new_tgt\n\n\ndef main():\n args = set_args()\n file_list = list_files(args.src)\n ext = args.ext if args.ext else []\n\n if not isinstance(file_list, list):\n \tprint(f\"Directory not found: {args.src}\")\n \tsys.exit()\n\n if not file_list:\n \tprint(f\"No files found: {args.src}\")\n \tsys.exit()\n\n for f in file_list:\n \tfp = os.path.join(args.src, f)\n \tif check_file_type(args.src, f) in ext:\n \t\tfile_create_time_raw = pathlib.Path(fp).stat().st_ctime\n \t\tcreate_dt = datetime.datetime.fromtimestamp(file_create_time_raw)\n \t\tcleaned_create_date = create_dt.strftime(\"%Y-%m-%d\")\n \t\tresult = move_file(args.src, f, os.path.join(args.tgt, cleaned_create_date), f)\n \t\tprint(f\"{os.path.join(args.src, f)} ---> {result}\")\n\nif __name__ == \"__main__\":\n\tmain()\n\t" }, { "alpha_fraction": 0.5954265594482422, "alphanum_fraction": 0.5954265594482422, "avg_line_length": 35.67741775512695, "blob_id": "b7866e8f220cb8b0edada5c4000535595a853bb1", "content_id": "bc1462dbf29efab1a3a66c627a03c09b0c2a2a22", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1137, "license_type": "no_license", "max_line_length": 125, "num_lines": 31, "path": "/file_xsfer.py", "repo_name": "jtzadoyko/fileSort", "src_encoding": "UTF-8", "text": "import os, shutil\nfrom datetime import datetime\n\nROOT_DIR = os.getcwd()\nIGNORE_EXT = '.py'\n\nclass dateFileSystem():\n\n def __init__(self, file_name, file_path = os.getcwd(), create_folder_location = os.getcwd()):\n self.fp = file_path\n self.fn = file_name\n self.fullpath = os.path.join(self.fp, self.fn)\n self.fd = datetime.fromtimestamp(os.path.getmtime(self.fullpath)).strftime('%Y %m')\n self.cfl = create_folder_location \n\n def create_folder(self):\n if not os.path.isdir(os.path.join(self.cfl, self.fd)):\n os.mkdir(os.path.join(self.cfl, self.fd))\n\n def move_file(self):\n if os.path.isdir(os.path.join(self.cfl, self.fd)): #and not os.path.isfile(os.path.join(self.cfl, self.fd, self.fn)):\n shutil.move(self.fullpath,os.path.join(self.cfl, self.fd))\n\nif __name__ == \"__main__\":\n for subdir, dirs, files in os.walk(ROOT_DIR):\n for file in files:\n print(file)\n if 'file_xsfer.py' != file:\n x = dateFileSystem(file_name = file, file_path = subdir)\n x.create_folder()\n x.move_file()\n" } ]	3
felipemsantos/aws-data-wrangler	https://github.com/felipemsantos/aws-data-wrangler	0aab460bbc0004740a5877ed907a4d04acab99fb	d93b8a3527575536e77bd500bf60c86cd6676b6c	54385e40f55b00982df5df787b8efbb4cdecb1c8	refs/heads/master	2022-12-15T22:32:33.199434	2020-09-01T01:13:11	2020-09-01T01:17:46	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6160278916358948, "alphanum_fraction": 0.6271777153015137, "avg_line_length": 28.285715103149414, "blob_id": "a6cffc6050af64a10a5c0b58951ee4dda23d0bcf", "content_id": "08b90c04230d20d1469dd1298c4c602d4acfbe46", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1435, "license_type": "permissive", "max_line_length": 94, "num_lines": 49, "path": "/awswrangler/s3/_read_concurrent.py", "repo_name": "felipemsantos/aws-data-wrangler", "src_encoding": "UTF-8", "text": "\"\"\"Amazon S3 CONCURRENT Read Module (PRIVATE).\"\"\"\n\nimport concurrent.futures\nimport itertools\nimport logging\nfrom typing import Any, Callable, Dict, List, Optional\n\nimport boto3\nimport pandas as pd\n\nfrom awswrangler import _utils\nfrom awswrangler.s3._read import _union\n\n_logger: logging.Logger = logging.getLogger(__name__)\n\n\ndef _caller(\n path: str,\n func: Callable[..., pd.DataFrame],\n boto3_primitives: _utils.Boto3PrimitivesType,\n func_kwargs: Dict[str, Any],\n) -> pd.DataFrame:\n boto3_session: boto3.Session = _utils.boto3_from_primitives(primitives=boto3_primitives)\n func_kwargs[\"path\"] = path\n func_kwargs[\"boto3_session\"] = boto3_session\n return func(func_kwargs)\n\n\ndef _read_concurrent(\n func: Callable[..., pd.DataFrame],\n paths: List[str],\n ignore_index: Optional[bool],\n boto3_session: boto3.Session,\n func_kwargs: Any,\n) -> pd.DataFrame:\n cpus: int = _utils.ensure_cpu_count(use_threads=True)\n with concurrent.futures.ThreadPoolExecutor(max_workers=cpus) as executor:\n return _union(\n dfs=list(\n executor.map(\n _caller,\n paths,\n itertools.repeat(func),\n itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)),\n itertools.repeat(func_kwargs),\n )\n ),\n ignore_index=ignore_index,\n )\n" } ]	1
sajingeo/blink1	https://github.com/sajingeo/blink1	e9529662239417ab7475ebc8e97155996ff2405c	cd4808dc851c70d57d3d05873789673f6f73b2ea	7394a524f78e06b979db99bb0a85888dd6d98c4c	refs/heads/master	2016-09-06T04:37:57.761559	2015-02-10T15:38:39	2015-02-10T15:38:39	30,551,216	2	0	null	null	null	null	null	[ { "alpha_fraction": 0.7356746792793274, "alphanum_fraction": 0.7504621148109436, "avg_line_length": 48.181819915771484, "blob_id": "09d66e30bb8f2428370772469a5f83b3c77f375b", "content_id": "27637c6601c35a8cf96d3dda423ae537bf8aec71", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 541, "license_type": "permissive", "max_line_length": 111, "num_lines": 11, "path": "/README.md", "repo_name": "sajingeo/blink1", "src_encoding": "UTF-8", "text": "# blink1 Mk2 Projects\n###outlook.py\n* Stand alone script that checks for new emails in Outlook and changes the color based on the type of the email\n* Glows RED to notify you of an email from your manager\n* Glows BLUE to notify you of an email from rest of the world\n* Glows GREEN if you have no unread emails :) phew...\n\n####Requirements\n- Blink1-tool from http://blink1.thingm.com/downloads/\n- Pywin32 make sure you get the right one for your OS and the Python installed on you system\n- and the blink(1) mk2 from hackaday.com (like duh...)\n" }, { "alpha_fraction": 0.5046674609184265, "alphanum_fraction": 0.5320886969566345, "avg_line_length": 25.796875, "blob_id": "a7d0367d9a35fd483aa6833dfc8fb67cc5cce5be", "content_id": "a5e07ffaa808ea7991321b4d25fb35195253ca3b", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1714, "license_type": "permissive", "max_line_length": 73, "num_lines": 64, "path": "/outlook.py", "repo_name": "sajingeo/blink1", "src_encoding": "UTF-8", "text": "import win32com.client\nimport os, time, sys\nimport re\nimport subprocess\n\nManager = 'Your Managers Domain Name'\n\n\n\ndef set_color(color):\n colorCmd = '--rgb='+str(color[0])+','+str(color[1])+','+str(color[2])\n cmd =['blink1-tool','-q',colorCmd]\n pr=subprocess.Popen(cmd)\n pr.wait()\n\n\nprint 'I will keep an eye out for your emails :) take a walk..'\nsession = win32com.client.gencache.EnsureDispatch (\"MAPI.Session\")\n\nsession.Logon (\"Outlook\")\nmessages = session.Inbox.Messages\n\n\n#while 1:\nwhile (1):\n message = messages.GetLast ()\n if (message.Unread):\n sender = str(message.Sender.Address)\n #print sender\n matchObj = re.match( r'./cn=(.)', sender, re.M\|re.I)\n try:\n From = matchObj.group(1)\n ##print From ## uncomment this to get the address \n\t\t\t\t\t ## header you might have to change \n\t\t\t\t\t ##the regex to get this working\n except:\n From = 'unknown'\n\t\t\t\n\t\t\t\n \n if (From == Manager):\n ##print 'pattern:emergency'\n ##print '#AB0005'\n set_color([130,0,0])\n while(1):\n message = messages.GetLast ()\n if (message.Unread == False):\n set_color([0,130,0])\n break\n time.sleep(2)\n #print 'you are screwed'\n else:\n #print 'pattern:yellow flashes'\n #print '#AB9700'\n #print 'you have new emails'\n set_color([0,0,130])\n \n else :\n #print 'pattern:green flashes'\n #print '#00AB19'\n set_color([0,130,0])\n #print 'you have no new email'\n ##message = messages.GetNext ()\n time.sleep (60)" } ]	2
Ilya-Plevako/test_function_pytest	https://github.com/Ilya-Plevako/test_function_pytest	57f9fa213a8089a947d533750af7e8def603848d	fcd02c836223462d30b6ff1de80ed7e108e8047b	86438d2f68ee19521fc1982aee56f0d0e88f9037	refs/heads/main	2023-02-23T16:58:49.854199	2021-01-29T19:40:25	2021-01-29T19:40:25	333,439,093	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5649510025978088, "alphanum_fraction": 0.5789215564727783, "avg_line_length": 39, "blob_id": "0522794f750b77c023c940b9dc7b26044b6cb6f5", "content_id": "524f65bf5a619a2175a083bb08eab01ea931f824", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4496, "license_type": "no_license", "max_line_length": 116, "num_lines": 102, "path": "/library/orders.py", "repo_name": "Ilya-Plevako/test_function_pytest", "src_encoding": "UTF-8", "text": "from datetime import datetime\nfrom typing import Dict, List\n\nfrom requests import post\n\nfrom library import clients\n\n\ndef create_order_and_get_order_info(alias: str, client_id: str, address: str, phone: str, item_id: int,\n price: float, quantity: int) -> List[Dict]:\n \"\"\"OAPI: Создание заказа (service/v1/order/create)\n\n Args:\n alias: псевдоним соединения.\n client_id: идентификатор клиента.\n address: адрес клиента.\n phone: номер телефона клиента.\n item_id: идентификатор товара.\n price: цена товара (за шт.).\n quantity: количество товара.\n\n Returns:\n order_info: информация о созданном заказе\n \"\"\"\n uri = \"service/v1/order/create\"\n data = {\n 'client_id': client_id,\n 'address': address,\n 'phone': phone,\n 'items': [{\n 'item_id': item_id,\n 'price': price,\n 'quantity': quantity\n }]\n }\n\n response = post(alias=alias, uri=uri, data=data)\n order_number = response.json()[\"order_number\"]\n\n order_info = [{\n 'order_number': order_number,\n 'client_id': client_id,\n 'last_purchase_date': str(datetime.now().replace(microsecond=0)),\n 'items': [{\n 'item_id': item_id,\n 'price': price,\n 'quantity': quantity\n }\n ]\n }]\n return order_info\n\n\ndef create_client_and_add_one_order(alias='token', name='Vanya', surname='Pupkin', address='Moscow, Red Square, 1',\n phone='+79265437898', item_id=7800188, price=500, quantity=2):\n \"\"\"Создание клиента и оформление ему одного заказа\n \"\"\"\n client_id = clients.create_client(alias=alias, name=name, surname=surname, phone=phone)\n order_info = create_order_and_get_order_info(alias=alias, client_id=client_id, address=address,\n phone=phone, item_id=item_id, price=price,\n quantity=quantity)\n return order_info\n\n\ndef create_client_and_add_two_orders(alias='token', name='Vanya', surname='Pupkin', address='Moscow, Red Square, 1',\n phone='+79265437898', item_id=7800188, price=500, quantity_first_order=5,\n quantity_second_order=15):\n \"\"\"Создание клиента и оформление ему двух заказаов\n \"\"\"\n client_id = clients.create_client(alias=alias, name=name, surname=surname, phone=phone)\n first_order_info = create_order_and_get_order_info(alias=alias, client_id=client_id, address=address,\n phone=phone, item_id=item_id, price=price,\n quantity=quantity_first_order)\n\n second_order_info = create_order_and_get_order_info(alias=alias, client_id=client_id, address=address,\n phone=phone, item_id=item_id, price=price,\n quantity=quantity_second_order)\n\n final_order_info = [first_order_info, second_order_info]\n return final_order_info\n\n\ndef count_item_id_from_orders(item_id, orders_info):\n \"\"\"Вычисление суммарного количества товара item_id среди переданных заказов\n \"\"\"\n sum_item_count = sum(\n [count[\"items\"][0][\"quantity\"] for count in orders_info if count[\"items\"][0][\"quantity\"] is not None\n and count[\"items\"][0][\"item_id\"] == item_id])\n\n return sum_item_count\n\n\ndef get_last_order_number(item_id, orders_info):\n \"\"\"Нахождение последнего номера заказа по item_id\n \"\"\"\n # отбираем только информацию по необходимому товару, отбрасываем другие товары\n order_info_by_item_id = [count for count in orders_info if count[\"items\"][0][\"quantity\"] is not None\n and count[\"items\"][0][\"item_id\"] == item_id]\n # сортируем по дате\n sorted_orders_info = sorted(order_info_by_item_id, key=lambda k: k['last_purchase_date'])\n\n return sorted_orders_info[-1]['order_number']\n" }, { "alpha_fraction": 0.8091602921485901, "alphanum_fraction": 0.8091602921485901, "avg_line_length": 43, "blob_id": "bdf47dd4a488d81badfc360072b42bbb605947ff", "content_id": "e1461a8a4e4cd35b7aa7f03c5431622032e840b2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 205, "license_type": "no_license", "max_line_length": 73, "num_lines": 3, "path": "/README.md", "repo_name": "Ilya-Plevako/test_function_pytest", "src_encoding": "UTF-8", "text": "## Тестовое задание для тестирования абстрактной функции\n\n![alt text](screenshots/final_result.png \"Финальный результат в консоли\")" }, { "alpha_fraction": 0.5477327108383179, "alphanum_fraction": 0.5614558458328247, "avg_line_length": 36.24444580078125, "blob_id": "92d6ae1e7a64bd99b08b61513c36a3d03cd89f11", "content_id": "bf3c0a8b6d51a277b587d01103949c8ca315b74e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1901, "license_type": "no_license", "max_line_length": 100, "num_lines": 45, "path": "/library/purchases.py", "repo_name": "Ilya-Plevako/test_function_pytest", "src_encoding": "UTF-8", "text": "import random\nfrom datetime import datetime, timedelta\nfrom typing import Dict\n\n\ndef client_purchase_by_item_id(item_ids: list = None, client_id: str = None) -> Dict:\n \"\"\"OAPI: Информация о покупах клиентом товаров {X} (service/v1/item/purchase/by-client)\n\n Args:\n item_ids: идентификаторы товаров.\n client_id: идентификатор клиента.\n\n Returns:\n Информация о количестве, дате и номер заказа или отсутствии покупки товара с таким item_ids.\n \"\"\"\n # ниже закомментирован код функции, если бы она существовала на самом деле.\n # uri = \"service/v1/item/purchase/by-client\"\n # data = {\n # 'client_id': client_id,\n # 'item_ids': [item_ids]\n # }\n\n # response = post(alias=alias, uri=uri, data=data)\n # return response\n\n # имитация ответа функции\n response = {\"items\": []}\n\n for i in item_ids:\n purchased = random.randint(0, 1)\n if purchased:\n last_order_number = str(random.randint(1000, 5000))\n last_purchase_date = str(\n datetime.now().replace(microsecond=0) - timedelta(days=random.randint(7, 10),\n minutes=random.randint(1, 60)))\n else:\n last_order_number = None\n last_purchase_date = None\n\n response[\"items\"].append({\"item_id\": i,\n \"purchased\": bool(purchased),\n \"last_order_number\": last_order_number,\n \"last_purchase_date\": last_purchase_date,\n \"purchase_count\": purchased * random.randint(1, 100)})\n return response\n" }, { "alpha_fraction": 0.603960394859314, "alphanum_fraction": 0.6072607040405273, "avg_line_length": 24.25, "blob_id": "83d4b6e0f191933aa09104297e093eff0eea9545", "content_id": "e3e9e39b76a5fb7e6272ae87fa1ced4396382893", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 714, "license_type": "no_license", "max_line_length": 74, "num_lines": 24, "path": "/library/clients.py", "repo_name": "Ilya-Plevako/test_function_pytest", "src_encoding": "UTF-8", "text": "from requests import post\n\n\ndef create_client(alias: str, name: str, surname: str, phone: str) -> str:\n \"\"\"OAPI: Создание клиента (service/v1/client/create)\n\n Args:\n alias: псевдоним соединения.\n name: имя клиента.\n surname: фамилия клиента.\n phone: номер телефона клиента.\n\n Returns:\n client_id: идентификатор созданного клиента.\n \"\"\"\n uri = \"service/v1/client/create\"\n data = {\n 'name': name,\n 'surname': surname,\n 'phone': phone\n }\n\n response = post(alias=alias, uri=uri, data=data)\n return response.json()[\"client_id\"]\n" }, { "alpha_fraction": 0.3411359488964081, "alphanum_fraction": 0.38486000895500183, "avg_line_length": 56.1767692565918, "blob_id": "692e2d2daabc2ba89b2295f4bf28000c1ef56542", "content_id": "02bddb72f8430e4bd70ba25efdf00252549c60ed", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 12337, "license_type": "no_license", "max_line_length": 120, "num_lines": 198, "path": "/tests/utest/oapi/test_client_purchases.py", "repo_name": "Ilya-Plevako/test_function_pytest", "src_encoding": "UTF-8", "text": "from unittest.mock import Mock\n\nimport pytest\n\nfrom library import orders\nfrom library import purchases\n\n\nclass TestCreateClient(object):\n\n # проверка, что для товара с purchased = True обязательно purchase_count > 0,\n # с purchased = False обязательно purchase_count = 0\n @pytest.mark.parametrize('item_ids',\n [[7800181, 7800182, 7800183]])\n def test_client_purchased_and_count_purchased(self, item_ids):\n items = purchases.client_purchase_by_item_id(item_ids)['items']\n\n assert all([item['purchased'] == (item['purchase_count'] > 0) for item in items])\n\n # проверка, что если в одном заказе успешно куплено ненулевое количество товара, то итоговое количество корректное;\n # что если в одном заказе при оформлении заказа передано quantity = 0, то и итоговое значение 0.\n @pytest.mark.parametrize('item_id,mock_value_order,mock_value_purchase',\n [('7800181', [{\n 'order_number': '999999',\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800181',\n 'price': 500,\n 'quantity': 5\n }\n ]\n }\n ], [{'item_id': 7800181,\n 'purchased': True,\n 'last_order_number': '999999',\n 'last_purchase_date': '2021-01-29 17:19:43.027852',\n 'purchase_count': 5}]),\n ('7800182', [{\n 'order_number': None,\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800182',\n 'price': None,\n 'quantity': 0\n }\n ]\n }\n ], [{'item_id': 7800182,\n 'purchased': False,\n 'last_order_number': None,\n 'last_purchase_date': None,\n 'purchase_count': 0}]\n )])\n def test_count_item_id_by_one_purchase(self, item_id, mock_value_order, mock_value_purchase):\n orders_info = orders.create_client_and_add_one_order = Mock(return_value=mock_value_order)\n result = orders.count_item_id_from_orders(item_id=item_id, orders_info=orders_info.return_value)\n exp_result = purchases.client_purchase_by_item_id = Mock(return_value=mock_value_purchase)\n assert result == exp_result.return_value[0]['purchase_count']\n\n # проверка для фиксации ожидаемого некорректного поведения, которое уже зафиксировано и скоро будет поправлено.\n @pytest.mark.xfail(reason=\"Если бы сейчас система работа некорректно и вернула на 1 товар больше, чем реально \"\n \"куплено\")\n @pytest.mark.parametrize('item_id,mock_value_order,mock_value_purchase',\n [('7800181', [{\n 'order_number': '999999',\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800181',\n 'price': 500,\n 'quantity': 6\n }\n ]\n }\n ], [{'item_id': 7800181,\n 'purchased': False,\n 'last_order_number': None,\n 'last_purchase_date': None,\n 'purchase_count': 7}])])\n def test_incorrect_count_item_id_by_one_purchase(self, item_id, mock_value_order, mock_value_purchase):\n orders_info = orders.create_client_and_add_one_order = Mock(return_value=mock_value_order)\n result = orders.count_item_id_from_orders(item_id=item_id, orders_info=orders_info.return_value)\n exp_result = purchases.client_purchase_by_item_id = Mock(return_value=mock_value_purchase)\n assert result == exp_result.return_value[0]['purchase_count']\n\n # проверка, что если в двух заказах успешно куплено ненулевое количество одного и того же товара,\n # то итоговое количество равно их сумме;\n # что если в одном заказе куплено ненулевое, а в другом заказе нулевое количество,\n # то итоговое количество равно только количеству из ненулевого заказа.\n @pytest.mark.parametrize('item_id,mock_value_order,mock_value_purchase',\n [('7800181', [{\n 'order_number': '777777',\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800181',\n 'price': 500,\n 'quantity': 5\n }\n ]\n },\n {\n 'order_number': '888888',\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800181',\n 'price': 500,\n 'quantity': 15\n }\n ]\n }\n ], [{'item_id': 7800181,\n 'purchased': True,\n 'last_order_number': 888888,\n 'last_purchase_date': '2021-01-29 17:19:43',\n 'purchase_count': 20}]),\n ('7800184', [{\n 'order_number': '777777',\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800184',\n 'price': 500,\n 'quantity': 50\n }\n ]\n },\n {\n 'order_number': None,\n 'client_id': '256865',\n 'items': [{\n 'item_id': '7800184',\n 'price': None,\n 'quantity': 0\n }\n ]\n }\n ], [{'item_id': 7800184,\n 'purchased': True,\n 'last_order_number': 777777,\n 'last_purchase_date': '2021-01-29 17:19:43',\n 'purchase_count': 50}]\n )])\n def test_count_item_id_by_several_purchase(self, item_id, mock_value_order, mock_value_purchase):\n # подменяю результат ответа функции с заказам, чтобы обработать заказ\n orders_info = orders.create_client_and_add_two_order = Mock(return_value=mock_value_order)\n # вычисляю сумму купленных товаров с одинаковым id в рамках нескольких заказов\n result = orders.count_item_id_from_orders(item_id=item_id, orders_info=orders_info.return_value)\n # подменяю ответ тестируемой функции, т.к. нет возможности её вызывать\n exp_result = purchases.client_purchase_by_item_id = Mock(return_value=mock_value_purchase)\n assert result == exp_result.return_value[0]['purchase_count']\n\n @pytest.mark.parametrize('item_id,mock_value_order,mock_value_purchase',\n [('7800188', [{\n 'order_number': '999999',\n 'client_id': '356178',\n 'last_purchase_date': '2021-01-26 14:12:43',\n 'items': [{\n 'item_id': '7800188',\n 'price': 500,\n 'quantity': 18\n }\n ]\n },\n {\n 'order_number': '111555',\n 'client_id': '356178',\n 'last_purchase_date': '2021-01-28 17:39:43',\n 'items': [{\n 'item_id': '7800187',\n 'price': 800,\n 'quantity': 34\n }\n ]\n },\n {\n 'order_number': '237987',\n 'client_id': '356178',\n 'last_purchase_date': '2020-11-12 08:39:43',\n 'items': [{\n 'item_id': '7800188',\n 'price': 700,\n 'quantity': 34\n }\n ]\n }\n ], [{'item_id': 7800188,\n 'purchased': True,\n 'last_order_number': '999999',\n 'last_purchase_date': '2021-01-29 17:19:43',\n 'purchase_count': 20}])])\n def test_last_order_number(self, item_id, mock_value_order, mock_value_purchase):\n # подменяю результат ответа функции с заказам, чтобы обработать заказ\n orders_info = orders.create_client_and_add_two_order = Mock(return_value=mock_value_order)\n # вычисляю номер последнего заказа\n result = orders.get_last_order_number(item_id=item_id, orders_info=orders_info.return_value)\n # подменяю ответ тестируемой функции, т.к. нет возможности её вызывать\n exp_result = purchases.client_purchase_by_item_id = Mock(return_value=mock_value_purchase)\n # в ответе ожидаем 999999, т.к. хоть заказ 111555 более поздний, но в нём был заказан продукт 7800187,\n # а не 7800188, который передан на вход\n assert result == exp_result.return_value[-1]['last_order_number']\n" }, { "alpha_fraction": 0.4700239896774292, "alphanum_fraction": 0.7050359845161438, "avg_line_length": 15.680000305175781, "blob_id": "193388fe71cedf5ca915fd9cc48e45f3562c457b", "content_id": "8d636106066457bf74aa6ac0b30b7e801ecde3a4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 417, "license_type": "no_license", "max_line_length": 24, "num_lines": 25, "path": "/requirements.txt", "repo_name": "Ilya-Plevako/test_function_pytest", "src_encoding": "UTF-8", "text": "atomicwrites==1.4.0\nattrs==20.2.0\ncertifi==2020.6.20\nchardet==3.0.4\ncolorama==0.4.4\nconfigparser==5.0.1\ncrayons==0.4.0\ndecorator==4.4.2\nidna==2.10\nmore-itertools==8.6.0\npackaging==20.4\npluggy==0.13.1\npy==1.9.0\npyparsing==2.4.7\npytest==5.1.1\nrequests==2.24.0\nresponses==0.12.1\nrobot==20071211\nrobotframework==3.2.2\nselenium==3.141.0\nself==2020.12.3\nsix==1.15.0\nurllib3==1.25.10\nwcwidth==0.2.5\nwebdriver-manager==3.2.2\n" } ]	6
MaxPershin/Scrapy-Crawler-for-podrugka.ru	https://github.com/MaxPershin/Scrapy-Crawler-for-podrugka.ru	b416d95dc1fd22b5b6b5986df54f3074222bd11f	51c02838d00794bb01d2f5f0f26f65cfc0f271bf	4d624a32b93a7425957b0fb9e56d97b3564a805a	refs/heads/master	2020-08-12T04:31:50.996454	2019-10-12T17:51:53	2019-10-12T17:51:53	214,690,112	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.7003121972084045, "alphanum_fraction": 0.7034339308738708, "avg_line_length": 26.485713958740234, "blob_id": "6568fa70858329636f66b95d24de5baa24b86370", "content_id": "8329e7ff0b8158b36c72fe315575f9377bd55224", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 961, "license_type": "no_license", "max_line_length": 87, "num_lines": 35, "path": "/mvideo/pipelines.py", "repo_name": "MaxPershin/Scrapy-Crawler-for-podrugka.ru", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\n# Define your item pipelines here\n#\n# Don't forget to add your pipeline to the ITEM_PIPELINES setting\n# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html\nimport sqlite3\n\nclass MvideoPipeline(object):\n\n\tdef __init__(self):\n\t\tprint('WWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWW INIT!!!! \\n \\n \\n \\n \\n')\n\t\tself.connect_to_database()\n\t\tself.create_table()\n\n\tdef connect_to_database(self):\n\t\tself.conn = sqlite3.connect('podruzhka.db')\n\t\tself.curr = self.conn.cursor()\n\n\tdef create_table(self):\n\t\tself.curr.execute('DROP TABLE IF EXISTS podruzhka_table')\n\t\tself.curr.execute('CREATE TABLE podruzhka_table(name text, price text, pic text)')\n\n\tdef put_to_database(self, item):\n\t\tself.curr.execute('INSERT INTO podruzhka_table VALUES (?,?,?)',(\n\t\t\titem['item_name'],\n\t\t\titem['item_price'],\n\t\t\titem['item_pic']\n\t\t\t))\n\n\t\tself.conn.commit()\n\n\tdef process_item(self, item, spider):\n\t\tself.put_to_database(item)\n\t\treturn item" }, { "alpha_fraction": 0.6176185607910156, "alphanum_fraction": 0.6669893264770508, "avg_line_length": 31.3125, "blob_id": "b4ec954d8a8e92cadcaa4ba7fe2ab69f968f43f8", "content_id": "cd6b94b6a1035db9f642acdaacd69b1c5e6cfa10", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1033, "license_type": "no_license", "max_line_length": 156, "num_lines": 32, "path": "/mvideo/spiders/mvideoSpider.py", "repo_name": "MaxPershin/Scrapy-Crawler-for-podrugka.ru", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\nimport scrapy\nfrom ..items import MvideoItem \n\nclass MvideospiderSpider(scrapy.Spider):\n\tname = 'mvideoSpider'\n\tstart_urls = ['https://www.podrygka.ru/catalog/ukhod/country-is-724e87fa98bf8a6a69816a93f4100878/?gclid=Cj0KCQjw84XtBRDWARIsAAU1aM3rAhxe98pVtYn0WRkLDwJUdc0XePiz7a6MHBCzFCG-dmiHSjOpjgMaAsv_EALw_wcB']\n\tcounter = 2\n\n\tdef parse(self, response):\n\t\tall_items = response.css('.col-md-3')\n\n\n\t\titems = MvideoItem()\n\n\n\t\tfor each in all_items:\n\t\t\tif each.css('.products-list-item__title::text').get() == None:\n\t\t\t\treturn\n\t\t\t\t\n\t\t\titems['item_name'] = each.css('.products-list-item__title::text').get()\n\t\t\titems['item_price'] = each.css('.value--current span::text').get()\n\t\t\titems['item_pic'] = 'www.podrygka.ru' + each.css('img::attr(src)').get()\n\n\t\t\tprint('!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!', MvideospiderSpider.counter)\n\n\t\t\tyield items\n\n\t\tnext_page = 'https://www.podrygka.ru/catalog/ukhod/country-is-724e87fa98bf8a6a69816a93f4100878/?gclid=Cj0KCQjw84XtBRDWARIsAAU1aM3rAhxe98pVtYn0WRkLDwJUdc0XePiz7a6MHBCzFCG-dmiHSjOpjgMaAsv_EALw_wcB&PAGEN_1={}'.format(MvideospiderSpider.counter)\n\n\t\tMvideospiderSpider.counter += 1\n\t\tyield response.follow(next_page, callback= self.parse)" } ]	2
Kinneyzhang/program_work	https://github.com/Kinneyzhang/program_work	eaa44ef619c246fafda658fbcd7a99f8dff0e8fe	6be2eadd445e23e31271fbe9460f8c0b64a481f5	a6e9533c7153b14d84d6703b27915c3ef46ae1d1	refs/heads/master	2018-12-27T04:25:27.482168	2018-12-20T02:06:14	2018-12-20T02:06:14	152,338,216	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7792207598686218, "alphanum_fraction": 0.7792207598686218, "avg_line_length": 37.5, "blob_id": "e1887d9b14b2367ef0c036714490063b9bf5de8c", "content_id": "e42519195b79f3aecdf0b1a26113bde753832ca4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Makefile", "length_bytes": 77, "license_type": "no_license", "max_line_length": 41, "num_lines": 2, "path": "/data_structure/Search_Repalce/Makefile", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "search_replace: search_replace.cpp\n\tg++ -o search_replace search_replace.cpp\n" }, { "alpha_fraction": 0.6750524044036865, "alphanum_fraction": 0.6750524044036865, "avg_line_length": 18.079999923706055, "blob_id": "15e24e2efd0ff48c85a9cf4fdb1770a6f71f50b7", "content_id": "6059733eca91332fc2abc4add46215b29b8b6c81", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 497, "license_type": "no_license", "max_line_length": 51, "num_lines": 25, "path": "/data_structure/Huffman_Tree/huffman_tree.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#ifndef HUFFMAN_TREE_H\n#define HUFFMAN_TREE_H\n\n#include <vector>\nusing namespace std;\n\nstruct HuffmanNode{\n char data;\n double weight;\n int parent, lchild, rchild;\n};\n\nclass HuffmanTree{\nprivate:\n vector<HuffmanNode> hufftree;\n int n; //叶子节点数\n void SelectSmall(int &least, int &less, int n);\npublic:\n HuffmanTree(vector<HuffmanNode> &leafs);\n ~HuffmanTree();\n vector<char> GetCode(int i); //取编码\n string Decode(vector<char> &code); //译码\n};\n\n#endif\n" }, { "alpha_fraction": 0.36644333600997925, "alphanum_fraction": 0.3731430172920227, "avg_line_length": 25.407691955566406, "blob_id": "e8136e5513cb8b1df59eb976260554bbfdc6fa21", "content_id": "effb7564075429a960556d64cdefdf99c364b86d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 3677, "license_type": "no_license", "max_line_length": 87, "num_lines": 130, "path": "/data_structure/Expression_Eval/main.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\n 功能：算术表达式求值\n/\n#include \"seqstack.cpp\"\n#include<iostream>\nusing namespace std;\n\ndouble Expression_Eval();\n\nint main(){\n while(true){\n char c = '\\0';\n cout << \"\\n--------Function:calculate the value of expression--------\" << endl;\n cout << \"input 's' to start or input 'q' to quit: \";\n cin >> c;\n cin.ignore(); //忽略缓冲区中的换行符\n if(c == 'q')\n break;\n else if(c == 's'){\n cout << \"please input an expression: \" << endl;\n double res = Expression_Eval(); //getchar会要求输入\n cout<< \"the result is：\"<< res <<endl;\n }else\n cout << \"error input! please input 's' or 'q'.\" << endl;\n }\n}\n\nchar Precede(char pre_op, char now_op){\n char op[] = {'+','-','','/','(',')','@'};\n char relation[7][7]={\n {'>','>','<','<','<','>','>'},\n {'>','>','<','<','<','>','>'},\n {'>','>','>','>','<','>','>'},\n {'>','>','>','>','<','>','>'},\n {'<','<','<','<','<','=','!'},\n {'>','>','>','>','!','>','>'},\n {'<','<','<','<','<','!','='}\n };\n for(int i=0; i<7; i++){\n for(int j=0; j<7; j++){\n if(pre_op == op[i] && now_op == op[j]){\n return relation[i][j];\n }\n }\n }\n return '!';\n}\n\ndouble Operate(double a, char op, double b){\n // cout<< \"a的数据类型为：\" <<typeid(a).name()<<endl;\n // cout<< \"a的结果为：\" << a <<endl;\n // cout<< \"b的数据类型为：\" <<typeid(b).name()<<endl;\n // cout<< \"b的结果为：\" << b <<endl;\n double result;\n switch(op){\n case '+':\n result = a + b;\n break;\n case '-':\n result = a - b;\n break;\n case '':\n result = a * b;\n break;\n case '/':\n result = a / b;\n break;\n }\n return result;\n}\n\ndouble stringToNum(const string& str){\n char char_str[30];\n int i=0;\n for(i=0; i<str.length(); i++){\n char_str[i] = str[i];\n }\n char_str[i] = '\\0';\n double val = atof(char_str);\n return val;\n}\n\ndouble Expression_Eval(){\n SeqStack<char, 100> OPTR; //操作符栈\n SeqStack<double, 100> OPND; //操作数栈\n OPTR.Push('@');\n \n char ch = getchar();\n // cout << \"get到的字符是的ASCII码是：\" << endl;\n // printf(\"%d\\n\", ch);\n string s = \"\";\n \n while(ch!='@' \|\| OPTR.Top()!='@'){ //解决多个char类型转化为对应的数值的问题\n if((ch>='0' && ch<='9') \|\| ch=='.'){\n while((ch>='0' && ch<='9') \|\| ch=='.'){\n s += ch;\n ch = getchar();\n }\n double value = stringToNum(s); //将string转为数值类型\n OPND.Push(value);\n s = \"\"; //清空上一个字符串\n }else if(ch == '\\n'){ \n ch = '@'; //结束标志为换行符，替换为@\n }else{\n char pre_op = OPTR.Top();\n switch(Precede(pre_op, ch)){\n case '<':\n OPTR.Push(ch);\n ch = getchar();\n break;\n case '=':\n OPTR.Pop();\n ch = getchar();\n break;\n case '>':{\n double b = OPND.Pop();\n double a = OPND.Pop(); //注意运算与出栈顺序相反\n char pre_op = OPTR.Pop();\n OPND.Push(Operate(a, pre_op, b));\n break;\n }\n case '!':\n cerr<<\"wrong input!\"<<endl;\n exit(1);\n }\n }\n }\n \n return OPND.Top();\n}\n" }, { "alpha_fraction": 0.5935727953910828, "alphanum_fraction": 0.6181474328041077, "avg_line_length": 16.064516067504883, "blob_id": "c910fd707fe7f5b8a04f29feddc5aa13777e4b9d", "content_id": "eab11ac1fd4f439b53067c9919f5aa974c8abc18", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 536, "license_type": "no_license", "max_line_length": 60, "num_lines": 31, "path": "/data_structure/MergeList/linklist.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "//\n// linklist.h\n// MergeList\n//\n// Created by Kinney凯 on 2018/9/25.\n// Copyright © 2018年 Kinney凯. All rights reserved.\n//\n\n#ifndef linklist_h\n#define linklist_h\n\ntemplate <class T>\nstruct Node{\n T data;\n Node<T> next;\n};\n\ntemplate <class T>\nclass LinkList{\n Node<T> head;\npublic:\n LinkList();\n LinkList(T a[],int n);\n int length();\n T getVal(int pos);\n void insert(int pos, T item);\n void printLinklist();\n LinkList<T> mergeLink(LinkList<T> &L1, LinkList<T> &L2);\n};\n\n#endif /* linklist_h /\n" }, { "alpha_fraction": 0.6609053611755371, "alphanum_fraction": 0.6658436059951782, "avg_line_length": 27.20930290222168, "blob_id": "7f40f504553bf538e2a485b4f0b24b5eccf25b22", "content_id": "92c3fa7f68d178188cf03b782f389971eda34c1d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1255, "license_type": "no_license", "max_line_length": 72, "num_lines": 43, "path": "/python/reptilian/wiki.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "from urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nimport datetime\nimport random\nimport re\n\n\"\"\"\nrandom.seed(datetime.datetime.now())\ndef getLink(articleUrl):\n\thtml = urlopen(\"http://en.wikipedia.org/wiki/Kevin_Bacon\")\n\tbsObj = BeautifulSoup(html)\n\tlinks = bsObj.find(\"div\",{\"id\":\"bodyContent\"}).findAll(\n\t\t\t\t\"a\", href=re.compile(\"^(/wiki/)((?!:).)$\"))\n\treturn links\n\nlinks = getLink(\"/wiki/Kevin_Bacon\")\nwhile len(links)>0:\n\tnewArticleUrl = links[random.randint(0,len(links)-1)].attrs[\"href\"]\n\tprint(newArticleUrl)\n\tlinks = getLink(newArticleUrl)\n\"\"\"\npages = set()\ndef getLinks(pageUrl):\n\tglobal pages\n\thtml = urlopen(\"http://en.wikipedia.org\" + pageUrl)\n\tbsObj = BeautifulSoup(html)\n\ttry:\n\t\tprint(bsObj.h1.get_text())\n\t\tprint(bsObj.find(id = \"mw-content-text\").findAll(\"p\")[0])\n\t\tprint(bsObj.find(id = \"ca-edit\").find(\"span\").find(\"a\").attrs[\"href\"])\n\texcept AttributeError:\n\t\tprint(\"页面缺少一些属性！不过不用担心！\")\t\n\n\tfor link in bsObj.findAll(\"a\", href=re.compile(\"^(/wiki/)\")):\n\t\tif 'href' in link.attrs:\n\t\t\tif link.attrs[\"href\"] not in pages:\n\t\t\t\t# 是新页面\n\t\t\t\tnewPageUrl = link.attrs[\"href\"]\n\t\t\t\tprint(\"----------------------\\n\" + newPageUrl)\n\t\t\t\tpages.add(newPageUrl)\n\t\t\t\tgetLinks(newPageUrl)\n\ngetLinks(\"\")\t\n\n" }, { "alpha_fraction": 0.6052141785621643, "alphanum_fraction": 0.6052141785621643, "avg_line_length": 18.178571701049805, "blob_id": "80f28c002ef4a6f9026b289ed7add528b374e082", "content_id": "81a40b07b4dbf6c6d6a6c3a84d9ed238bc2f0c09", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 537, "license_type": "no_license", "max_line_length": 43, "num_lines": 28, "path": "/data_structure/BiSort_Tree/bisort_tree.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#ifndef BISORT_TREE_H\n#define BISORT_TREE_H\n\ntemplate <class T>\nstruct BiNode{\n T data;\n BiNode<T> lchild, rchild;\n};\n\ntemplate <class T>\nclass BiSortTree{\nprivate:\n BiNode<T> root;\n void Insert(BiNode<T> &ptr, T k);\n void MidOrder(BiNode<T> p);\n BiNode<T> Search(BiNode<T> ptr, T k);\n void Delete(BiNode<T> &ptr, int k);\n void Free(BiNode<T> ptr);\npublic:\n BiSortTree(T a[], int n);\n ~BiSortTree();\n void MidOrder();\n void Insert(T k);\n bool Search(T k);\n void Delete(T k);\n};\n\n#endif\n" }, { "alpha_fraction": 0.4950787425041199, "alphanum_fraction": 0.5004921555519104, "avg_line_length": 19.525253295898438, "blob_id": "19aaf190f464cce01af4fa471c6ce4be87524e4c", "content_id": "cc5acb7fb405f83dad60423491267b559f26bef6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 2060, "license_type": "no_license", "max_line_length": 57, "num_lines": 99, "path": "/data_structure/BiSort_Tree/bisort_tree.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#include \"bisort_tree.h\"\n#include<iostream>\n\nusing namespace std;\n\ndouble stringToNum(const string& str);\nint main(){\n cout << \"----Function: binary sort tree----\" << endl;\n cout << \"please input a serial of num: \" << endl;\n int a[20];\n char ch = '\\0';\n string str = \"\";\n int i = 0;\n ch = getchar();\n while(ch != '\\n'){\n while( (ch>='0' && ch<='9') \|\| ch == '.'){\n str += ch;\n ch = getchar();\n if(ch == ' '){\n ch = getchar();\n break;\n } //空格则忽略掉!!!\n }\n double num = stringToNum(str);\n a[i++] = num;\n str = \"\"; //!!!!\n }\n BiSortTree<int> bst(a, i);\n bst.MidOrder();\n}\n\ndouble stringToNum(const string& str){\n char char_str[30];\n int i;\n for(i=0; i<str.length(); i++){\n char_str[i] = str[i];\n }\n char_str[i] = '\\0';\n double val = atof(char_str);\n return val;\n}\n\ntemplate <class T>\nvoid BiSortTree<T>::Insert(BiNode<T> &ptr, T k){\n if(ptr == NULL){\n BiNode<T> ptr = new BiNode<T>;\n ptr->data = k;\n ptr->lchild = ptr->rchild = NULL;\n }else{\n if(k<ptr->data)\n Insert(ptr->lchild, k);\n else if(k>ptr->data)\n Insert(ptr->rchild, k);\n }\n}\n\ntemplate <class T>\nvoid BiSortTree<T>::Insert(T k){\n Insert(root, k);\n}\n\ntemplate <class T>\nBiSortTree<T>::BiSortTree(T a[], int n){\n root = NULL;\n for(int i=0; i<n; i++){\n Insert(root, a[i]);\n }\n}\n\n//中序遍历\ntemplate <class T>\nvoid BiSortTree<T>::MidOrder(BiNode<T> ptr){\n if(ptr == NULL){\n return;\n }\n MidOrder(ptr->lchild);\n cout << ptr->data;\n MidOrder(ptr->rchild);\n}\ntemplate <class T>\nvoid BiSortTree<T>::MidOrder(){\n cout << \"MidOrder output: \";\n MidOrder(root);\n cout << \"\\n\";\n}\n\n//析构函数\ntemplate <class T>\nvoid BiSortTree<T>::Free(BiNode<T> p){\n if(p == NULL)\n return;\n Free(p->lchild);\n Free(p->rchild);\n delete p;\n}\ntemplate <class T>\nBiSortTree<T>::~BiSortTree(){\n Free(root);\n}\n" }, { "alpha_fraction": 0.6106557250022888, "alphanum_fraction": 0.6372950673103333, "avg_line_length": 18.520000457763672, "blob_id": "6b3ed5fc1ef44c27b66270af43929ed2fe211620", "content_id": "e08c6173dd6a14921f728b54c749f084dc6c5dce", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 495, "license_type": "no_license", "max_line_length": 80, "num_lines": 25, "path": "/data_structure/MergeList/seqlist.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "//\n// seqlist.h\n// MergeList\n//\n// Created by Kinney凯 on 2018/9/25.\n// Copyright © 2018年 Kinney凯. All rights reserved.\n//\n\n#ifndef seqlist_h\n#define seqlist_h\n\ntemplate <class T, int MaxSize>\nclass SeqList{\n T data[MaxSize];\n int length;\npublic:\n SeqList();\n SeqList(T a[], int n);\n T getVal(int pos);\n void insert(int pos, T item);\n void printSeqlist();\n SeqList<T,MaxSize> mergeSeq(SeqList<T,MaxSize> &l1, SeqList<T,MaxSize> &l2);\n};\n\n#endif / seqlist_h /\n" }, { "alpha_fraction": 0.7517401576042175, "alphanum_fraction": 0.7540603280067444, "avg_line_length": 32.153846740722656, "blob_id": "f8df4fffe810f822182325afc3dc24d1ad2a34cc", "content_id": "816951af4cd4119c5d5d0a11959bfa7f4173628a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 435, "license_type": "no_license", "max_line_length": 53, "num_lines": 13, "path": "/python/grammar/test_city.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#-- coding:utf-8 --\nimport unittest\nfrom city_functions import get_location\nclass CityTestCase(unittest.TestCase):\n\t'''测试city_functions.py'''\n\tdef test_city_country(self):\n\t\tlocation=get_location('Nanjing','Jiangsu')\n\t\tself.assertEqual(location,'Nanjing,Jiangsu')\n\tdef test_city_country_continent(self):\n\t\tlocation=get_location('Hangzhou','Zhejiang','Asia')\n\t\tself.assertEqual(location,'Hangzhou,Zhejiang,Asia')\n\nunittest.main()\n" }, { "alpha_fraction": 0.6677524447441101, "alphanum_fraction": 0.6938110589981079, "avg_line_length": 21.740739822387695, "blob_id": "72f8215231b0257dd0bc09413d084f159f931d4e", "content_id": "15f5d97a0e52a995d5ececef18586d80c080b731", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 656, "license_type": "no_license", "max_line_length": 40, "num_lines": 27, "path": "/python/grammar/restaurant.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "# -- coding:utf-8 --\nclass Restaurant():\n\tdef __init__(self,name,location):\n\t\tself.name=name\n\t\tself.location=location\n\t\tself.number_served=0\n\tdef set_number_served(self,num):\n\t\tself.number_served=num\n\tdef increment_number_served(self,num):\n\t\tself.number_served+=num\n\n\n\n'''\nrestaurant1=Restaurant('海底捞','南京')\nrestaurant1.set_number_served(20)\nprint(\"在\" + restaurant1.location + \"的\"\n\t+ restaurant1.name + \"餐馆服务了\"\n\t+ str(restaurant1.number_served) + \"人\"\n\t)\n\nrestaurant1.increment_number_served(100)\nprint(\"在\" + restaurant1.location + \"的\"\n\t+ restaurant1.name + \"餐馆服务了\"\n\t+ str(restaurant1.number_served) + \"人\"\n\t)\n'''\n" }, { "alpha_fraction": 0.6153846383094788, "alphanum_fraction": 0.620192289352417, "avg_line_length": 22, "blob_id": "22e773b1b1683dc9b3730cfcce7c482deec288a6", "content_id": "8a7ab1496bfadc0c347c608f299c207fff9eb38c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 208, "license_type": "no_license", "max_line_length": 56, "num_lines": 9, "path": "/python/grammar/name.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "'''\nname = \"kiNNey lovepython\"\nprint(name.title())\nprint(name.upper())\nprint(name.lower())\n'''\nname=['kinney', 'jack', 'jim', 'bob']\ngreetings = \"hello,\"+ name[0].title() + \"! How are you?\"\nprint(greetings)\n\n" }, { "alpha_fraction": 0.46111562848091125, "alphanum_fraction": 0.4717019498348236, "avg_line_length": 28.059171676635742, "blob_id": "0a118c379ebc38d7ed07d7ca3dcd6374627a6e89", "content_id": "94fcb88243974f3a813116b7e1187d80f44924a1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 5520, "license_type": "no_license", "max_line_length": 257, "num_lines": 169, "path": "/data_structure/Search_Repalce/search_replace.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\nFunction: search and replace\nproblem: 如何解决p串中包含t串时，替换会出现死循环的情形？\n\ntest string:\nEmacs is the extensible, customizable, self-documenting real-time display editor. This manual describes how to edit with Emacs and some of the ways to customize it; it corresponds to GNU Emacs version 26.1.\n\n/\n\n#include<iostream>\n#include<string>\n\nusing namespace std;\n\nvoid getnext(char substr, int next[]);\nint KMPmatching(char mainstr, char substr, int position, int &pos_index, int &mainstr_index);\nint replace(char mainstr, char substr, char replacestr);\n\nint main () {\n int n = 0;\n char ch = '\\0';\n char s = new char[1000];\n char t = new char[50];\n char p = new char[50];\n while(true){\n char command = '\\0';\n \n cout << \"------Function: search a string from an article and replace them by another one------\" << endl;\n cout << \"input 's' to start and input 'q' to quit:\" ;\n cin >> command;\n cin.ignore(); //忽略缓冲区中的换行符\n \n if(command == 's'){\n cout << \"please input a main string:\" << endl;\n while( (ch=getchar()) != '\\n' ){\n s[n++] = ch;\n }\n n=0;\n cout << \"please input a substring:\" << endl;\n while( (ch=getchar()) != '\\n' ){\n t[n++] = ch;\n }\n n=0;\n cout << \"please input a replace string:\" << endl;\n while( (ch=getchar()) != '\\n' ){\n p[n++] = ch;\n }\n n=0;\n \n // cout << \"old string: \";\n // for(int j = 0; j < strlen(s); j++)\n // cout << s[j];\n // cout << endl;\n \n int len = replace(s,t,p);\n cout << \"Result: \";\n for(int i = 0; i < len; i++)\n cout << s[i];\n cout << endl; \n }else if(command == 'q')\n break;\n else\n cout << \"WARNING:invalid input! please input 's' or 'q'.\" << endl;\n\n memset(s, 0, strlen(s));\n memset(t, 0, strlen(t));\n memset(p, 0, strlen(p));\n }\n}\n\nint replace(char mainstr, char substr, char replacestr){\n char s = mainstr;\n char t = substr;\n char p = replacestr;\n int slen = strlen(s); \n int tlen = strlen(t); \n int plen = strlen(p);\n int offset = plen - tlen;\n \n int pos = new int[40]; //记录匹配成功的位置\n int pos_index = 0;\n int mainstr_index = 0;\n // int mainstr_index = pos[pos_index-1] + tlen;\n while(mainstr_index < slen){\n // wrong!!! pos_index = pos[pos_index-1]+tlen;\n //不能通过这种方式来获取mainstr_index的值，因为只有最后一次匹配成功时才返回pos_index,计算mainstr_index的值，一旦失败，则死循环。应当返回mainstr_index的值，而不是 pos_index，因为mainstr_index有匹配的情况决定，而pos_index每匹配成功一次加一可以得出。固然mainstr_index的值可以通过一定的关系由pos_index计算出，但这也只是在匹配成功的情况下，对于最后一次的匹配失败无法求出，这就是导致死循环的原因。\n mainstr_index = KMPmatching(s, t, pos, pos_index, mainstr_index);\n pos_index ++;\n // cout << pos_index << endl;\n // cout << mainstr_index << endl;\n }\n\n if (offset <= 0){ //替换串比子串短\n //先替换所有，然后从后向前依次移位\n for(int i = 0 ; i < pos_index-1; i++){\n for(int j = 0; j < plen; j++){\n s[ pos[i] + j ] = p[j];\n }\n }\n for(int i = pos_index-2; i >= 0; i--){\n for(int j = pos[i]+tlen; j<slen; j++){\n s[j+offset] = s[j];\n }\n slen += offset;\n }\n }else{ //替换串比子串长\n //先从前往后(替换的位置)移位，再替换全部\n for(int i = 0; i < pos_index-1; i++){\n for(int j = slen-1; j >= pos[i]+tlen; j--){\n //每个子符在移位的时候，从后往前！从前往后会覆盖\n s[j+offset] = s[j];\n }\n slen += offset;\n pos[i+1] += offset * (i+1); //每移动一次，pos[i]的位置都要移动一倍的offset\n }\n for(int i =0; i < pos_index-1; i++){\n for(int j = 0; j < plen; j++){\n s[ pos[i] + j ] = p[j];\n }\n }\n }\n \n return slen;\n}\n\n\nint KMPmatching(char mainstr, char substr, int position, int &pos_index, int &mainstr_index){\n //一个关系：pos[k] + tlen = i \n char s = mainstr;\n char t = substr;\n int pos = position;\n int k = pos_index;\n int i = mainstr_index;\n int j = 0;\n int m = strlen(s);\n int n = strlen(t);\n int next = new int[20];\n getnext(t,next);\n while(i<m && j<n){ //子串匹配成功或者主串指针到达最后时跳出循环\n if (j==-1 \|\| s[i]==t[j]) {\n i++;\n j++;\n }else\n j = next[j];\n }\n if (j>=n){ //子串匹配成功\n // cout << \"pos[ \" << k << \" ] = \" << i-n << endl;\n pos[k] = i-n;\n }\n \n return i;\n}\n\nvoid getnext(char substr, int next[]){\n char t = substr;\n int j = 0;\n int k = -1;\n int m = strlen(t);\n next[0] = -1;\n while(j < m-1){\n if (k==-1 \|\| t[j]==t[k]) {\n j++;\n k++;\n next[j] = k;\n }else{\n k = next[k];\n }\n }\n}\n\n" }, { "alpha_fraction": 0.6648044586181641, "alphanum_fraction": 0.6703910827636719, "avg_line_length": 21.125, "blob_id": "03617750eb6962f9f4b7953652c4ed475149e37a", "content_id": "4c6e6ed4068b2e0d95d680dbe8fe20cb62d79803", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 179, "license_type": "no_license", "max_line_length": 44, "num_lines": 8, "path": "/python/grammar/city_functions.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#-- coding:utf_8 --\ndef get_location(city,country,continent=''):\n\tif continent:\n\t\tlocation=city+','+country+','+continent\n\telse:\n\t\tlocation=city+','+country\n\n\treturn location\n\t\n" }, { "alpha_fraction": 0.667870044708252, "alphanum_fraction": 0.671480119228363, "avg_line_length": 24.090909957885742, "blob_id": "38041f4106d6b07612a9f339900822528e319d22", "content_id": "763a01c525f085670cae4fe05300c1edb9a255da", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 293, "license_type": "no_license", "max_line_length": 34, "num_lines": 11, "path": "/python/grammar/icecreamstand.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "# -- coding:utf-8 --\nfrom restaurant import Restaurant\n\nclass IceCreamStand(Restaurant):\n\tdef __init__(self,name,location):\n\t\tsuper().__init__(name,location)\n\t\tself.flavors=[]\n\tdef show_flavors(self):\n\t\tprint(\"冰淇淋的口味有：\")\n\t\tfor flavor in self.flavors:\t\n\t\t\tprint(\"- \"+flavor)\n\n" }, { "alpha_fraction": 0.4650227725505829, "alphanum_fraction": 0.47480568289756775, "avg_line_length": 24.2949161529541, "blob_id": "59755ad3f2c276e07453e6bb5159cc5e3c39d3a1", "content_id": "ff003d12e076efdecbf494cc275182ffc7f6d726", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 7716, "license_type": "no_license", "max_line_length": 153, "num_lines": 295, "path": "/data_structure/Binary_Tree/binary_tree.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#include <iostream>\n#include \"binary_tree.h\"\n#include <vector>\n#include <queue>\n\nusing namespace std;\n\nvoid operation(BiTree<char> bitree);\n\nint main(){\n bool onOff = true;\n while(onOff){\n int bulid_way = 0;\n char ch = '\\0';\n int n = 0;\n cout << \"------Function: binary tree related operations------\" << endl;\n cout << \"please select a kind of way to build a binary tree or quit: 1.only by preorder 2.preorder and midorder 3.quit \" << endl;\n cout << \"input '1' to '3' to select: \" ;\n cin >> bulid_way;\n cin.ignore();\n switch(bulid_way){\n case 1:{\n char data = new char[20];\n vector<char> pre;\n cout << \"-----------------------------------\\n\";\n cout << \"please input a preorder string:\" << endl;\n while( (ch=getchar()) != '\\n' ){\n data[n++] = ch;\n }\n data[n] = '\\0';\n for(int i=0; i<n; i++){\n pre.push_back(data[i]);\n }\n n = 0;\n BiTree<char> bitree(pre);\n operation(bitree);\n delete []data;\n break;\n }\n case 2:{\n char data1 = new char[20];\n char data2 = new char[20];\n vector<char> pre;\n vector<char> mid;\n cout << \"-----------------------------------\\n\";\n cout << \"please input a preorder string:\" << endl;\n while( (ch=getchar()) != '\\n' ){\n data1[n++] = ch;\n }\n data1[n] = '\\0';\n for(int i=0; i<n; i++){\n pre.push_back(data1[i]);\n }\n n = 0;\n \n cout << \"please input a midorder string:\" << endl;\n while( (ch=getchar()) != '\\n' ){\n data2[n++] = ch;\n }\n data2[n] = '\\0';\n for(int j=0; j<n; j++){\n mid.push_back(data2[j]);\n }\n n = 0;\n BiTree<char> bitree(pre, mid);\n operation(bitree);\n delete []data1;\n delete []data2;\n break;\n }\n case 3:\n onOff = false;\n break;\n default:\n cout << \"WARNNING: invalid input! please input number 1 to 3.\" << endl;\n break;\n }\n }\n}\n\nvoid operation(BiTree<char> bitree){\n bool onOff = true;\n while(onOff){\n cout << \"-----------------------------------\\n\";\n cout << \"please select an operation to the binary tree:\" << endl;\n cout << \"1.preOrder output 2.midOrder output 3.postOrder output 4.levelOrder output 5.num of the node 6.height of the tree 7.quit\" << endl;\n cout << \"input '1' to '7' to select: \" << endl;\n int operation = 0;\n int count = 0;\n int height = 0;\n cin >> operation;\n cin.ignore();\n switch(operation){\n case 1:\n bitree.PreOrder();\n break;\n case 2:\n bitree.MidOrder();\n break;\n case 3:\n bitree.PostOrder();\n break;\n case 4:\n bitree.LevelOrder();\n break;\n case 5:\n count = bitree.Count();\n cout << \"the number of node is: \" << count << endl;\n break;\n case 6:\n height = bitree.Height();\n cout << \"the height of the binary tree is: \" << height << endl;\n break;\n case 7:\n onOff = false;\n break;\n default:\n cout << \"WARNNING: invalid input! please input number 1 to 6.\" << endl;\n break;\n }\n }\n}\n\n//先序序列构建二叉树\n//这里必须要加引用,因为需要保存函数中只有一份i的拷贝,在递归时才能正常的按次序依次加一。不加引用则每次函数调用时都会分配一个地址给i，导致返回时i也跟着返回\ntemplate <class T>\nBiNode<T> BiTree<T>::CreateByPre(vector<T> &pre, int &i){\n T e = pre[i++];\n // cout << \"i = \" << i << \" \"<< \"e = \"<< e << endl;\n if (e == '')\n return NULL;\n BiNode<T> p = new BiNode<T>;\n p->data = e;\n p->lchild = CreateByPre(pre, i);\n p->rchild = CreateByPre(pre, i);\n return p;\n}\ntemplate <class T>\nBiTree<T>::BiTree(vector<T> &pre){\n int i = 0;\n root = CreateByPre(pre, i);\n}\n\n//先序和中序构建二叉树\ntemplate <class T>\nBiNode<T> BiTree<T>::CreateByPreMid(vector<T> &pre, vector<T> &mid, int ipre, int imid, int n){\n if (n == 0)\n return NULL;\n BiNode<T> p = new BiNode<T>;\n p->data = pre[ipre];\n int i;\n for(i = 0; i < n; i++)\n if (pre[ipre] == mid[imid+i])\n break;\n p->lchild = CreateByPreMid(pre, mid, ipre+1, imid, i);\n p->rchild = CreateByPreMid(pre, mid, ipre+i+1, imid+i+1, n-i-1);\n return p;\n}\ntemplate <class T>\nBiTree<T>::BiTree(vector<T> &pre, vector<T> &mid){\n int n = pre.size();\n root = CreateByPreMid(pre, mid, 0, 0, n);\n}\n\n//拷贝构造函数\ntemplate <class T>\nBiNode<T> BiTree<T>::Copy(BiNode<T> p){\n if(p == NULL)\n return NULL;\n BiNode<T> newp = new BiNode<T>;\n newp->data = p->data;\n newp->lchild = Copy(p->lchild);\n newp->rchild = Copy(p->rchild);\n return newp;\n}\ntemplate <class T>\nBiTree<T>::BiTree(BiTree<T> &tree){\n root = Copy(tree.root);\n}\n\n//析构函数\ntemplate <class T>\nvoid BiTree<T>::Free(BiNode<T> p){\n if(p == NULL)\n return;\n Free(p->lchild);\n Free(p->rchild);\n delete p;\n}\ntemplate <class T>\nBiTree<T>::~BiTree(){\n Free(root);\n}\n\n//先序遍历\ntemplate <class T>\nvoid BiTree<T>::PreOrder(BiNode<T> p){\n if(p == NULL)\n return;\n cout << p->data;\n PreOrder(p->lchild);\n PreOrder(p->rchild);\n}\ntemplate <class T>\nvoid BiTree<T>::PreOrder(){\n cout << \"PreOrder output: \";\n PreOrder(root);\n cout << \"\\n\";\n}\n\n//中序遍历\ntemplate <class T>\nvoid BiTree<T>::MidOrder(BiNode<T> p){\n if(p == NULL){\n return;\n }\n MidOrder(p->lchild);\n cout << p->data;\n MidOrder(p->rchild);\n}\ntemplate <class T>\nvoid BiTree<T>::MidOrder(){\n cout << \"MidOrder output: \";\n MidOrder(root);\n cout << \"\\n\";\n}\n\n//后序遍历\ntemplate <class T>\nvoid BiTree<T>::PostOrder(BiNode<T> p){\n if(p == NULL)\n return;\n PostOrder(p->lchild);\n PostOrder(p->rchild);\n cout << p->data;\n}\ntemplate <class T>\nvoid BiTree<T>::PostOrder(){\n cout << \"PostOrder output: \";\n PostOrder(root);\n cout << \"\\n\";\n}\n\n//层次遍历\ntemplate <class T>\nvoid BiTree<T>::LevelOrder(){\n if (root == NULL)\n return;\n queue<BiNode<T>> q;\n q.push(root);\n cout << \"LevelOrder output: \";\n while(!q.empty()){\n BiNode<T> p = q.front();\n q.pop();\n cout << p->data;\n if (p->lchild != NULL)\n q.push(p->lchild);\n if (p->rchild != NULL)\n q.push(p->rchild);\n }\n cout << endl;\n}\n\n//计算节点树\ntemplate <class T>\nint BiTree<T>::Count(BiNode<T> p){\n if (p == NULL)\n return 0;\n int left = Count(p->lchild);\n int right = Count(p->rchild);\n return left+right+1;\n}\ntemplate <class T>\nint BiTree<T>::Count(){\n return Count(root);\n cout << \"\\n\";\n}\n\n//计算高度\ntemplate <class T>\nint BiTree<T>::Height(BiNode<T> p){\n if(p==NULL)\n return 0;\n int left = Height(p->lchild);\n int right = Height(p->rchild);\n if(left>right)\n return left+1;\n else\n return right+1;\n}\ntemplate <class T>\nint BiTree<T>::Height(){\n return Height(root);\n cout << \"\\n\";\n}\n" }, { "alpha_fraction": 0.444715291261673, "alphanum_fraction": 0.4612571895122528, "avg_line_length": 27.572139739990234, "blob_id": "05ba5eb4e5893c77632111d80140544be946b883", "content_id": "7c9ab989c1f7c054ab33a899dcf791ab1e93b555", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 5921, "license_type": "no_license", "max_line_length": 109, "num_lines": 201, "path": "/data_structure/Huffman_Tree/huffman_tree.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#include \"huffman_tree.h\"\n#include<iostream>\n#include<vector>\n#include<string>\n\nusing namespace std;\n\ndouble stringToNum(const string& str);\n\nint main(){\n<<<<<<< HEAD\n bool onOff = true;\n while(onOff){\n cout << \"--------Function: Huffman encode and decode!---------\" << endl;\n cout << \"please input the data and weight: \" << endl;\n char ch = '\\0';\n // if((ch=getchar()) == 'q')\n // break;\n // else\n // ungetc(ch, stdin);\n=======\n char ch = '\\0';\n while(true){\n cout << \"--------Function: Huffman encode and decode!---------\" << endl;\n cout << \"please input the data and weight or 'q' to quit: \" << endl;\n //getchar()最后的换行符也会被存入缓冲区 \n \n if((ch=getchar()) == 'q')\n break;\n else\n ungetc(ch, stdin);\n>>>>>>> 7c50d4f3ba2033c4a15238d6f8d0fbca2d4106ea\n \n vector<char> data;\n vector<double> weight;\n string str = \"\";\n while((ch=getchar()) != '\\n')\n if(ch != ' ')\n data.push_back(ch);\n ch = getchar();\n while(ch != '\\n'){\n while( (ch>='0' && ch<='9') \|\| ch == '.'){\n str += ch;\n ch = getchar();\n if(ch == ' '){\n ch = getchar();\n break;\n } //空格则忽略掉!!!\n }\n double num = stringToNum(str);\n weight.push_back(num);\n str = \"\"; //!!!!\n }\n\n vector<HuffmanNode> leafs;\n int n = data.size();\n struct HuffmanNode huffnode[n];\n for(int i=0; i<n; i++){\n huffnode[i].data = data[i];\n huffnode[i].weight = weight[i];\n }\n for(int i=0; i<n; i++){\n leafs.push_back(huffnode[i]);\n }\n HuffmanTree hf(leafs);\n cout << \"the results of encoding are as follows:\" << endl;\n for(int i=0; i<n; i++){\n string s = \"\";\n vector<char> code = hf.GetCode(i);\n for(int j=0; j<(int)code.size(); j++){\n s += code[j];\n }\n cout << huffnode[i].data << \":\" << s << \"\\t\";\n }\n cout << endl; //最后不换行，终端输出的时候会有多余的%\n\n while(true){\n cout << \"please input the data you want to decode or 'q' to quit: \" << endl;\n\n<<<<<<< HEAD\n if((ch=getchar()) == 'q'){\n onOff = false;\n=======\n ch = '\\0';\n if((ch=getchar()) == 'q'){\n getchar(); //读取换行符\n>>>>>>> 7c50d4f3ba2033c4a15238d6f8d0fbca2d4106ea\n break;\n }\n else\n ungetc(ch, stdin);\n\n vector<char> source;\n while((ch=getchar()) != '\\n'){\n source.push_back(ch);\n }\n cout << hf.Decode(source) << endl;\n }\n }\n}\n\ndouble stringToNum(const string& str){\n char char_str[30];\n int i=0;\n for(i=0; i<str.length(); i++){\n char_str[i] = str[i];\n }\n char_str[i] = '\\0';\n double val = atof(char_str);\n return val;\n}\n\nHuffmanTree::HuffmanTree(vector<HuffmanNode> &leafs){\n n = leafs.size();\n hufftree.resize(2n-1);\n for(int i=0; i<n; i++){\n hufftree[i].data = leafs[i].data;\n hufftree[i].weight = leafs[i].weight;\n hufftree[i].parent = hufftree[i].lchild = hufftree[i].rchild = -1;\n }\n for(int i=n; i<2n-1; i++){\n int least = 0;\n int less = 0;\n SelectSmall(least, less, i);\n // cout << \"least = \" << least << endl;\n // cout << \"less = \" << less << endl;\n hufftree[least].parent = hufftree[less].parent = i;\n hufftree[i].parent = -1;\n hufftree[i].lchild = least;\n hufftree[i].rchild = less;\n hufftree[i].weight = hufftree[least].weight + hufftree[less].weight;\n }\n}\n\nvoid HuffmanTree::SelectSmall(int &least, int &less, int n){ //??每次选择最小的两个节点，下一次排除之前的选择，特征。。。。\n int i = 0;\n vector<HuffmanNode> forest;\n while(i<n){\n if(hufftree[i].parent == -1)\n forest.push_back(hufftree[i]);\n i++;\n }\n int n2 = forest.size();\n for(i=1; i<n2; i++)\n for(int j=0; j<n2-i; j++)\n if(forest[j].weight > forest[j+1].weight){\n HuffmanNode temp = forest[j];\n forest[j] = forest[j+1];\n forest[j+1] = temp;\n }\n for(i=0; i<n2; i++){\n cout << forest[i].weight << \" \";\n }\n\n for(i=0; i<n; i++){\n if(hufftree[i].weight == forest[0].weight && hufftree[i].parent == -1)\n least = i;\n if(hufftree[i].weight == forest[1].weight && hufftree[i].parent == -1 && i != least) //!!!考虑到相同元素的情况 \n less = i;\n }\n cout << \"least=\" << least << endl;\n cout << \"less=\" << less << endl;\n}\n\nHuffmanTree::~HuffmanTree(){\n hufftree.clear();\n}\n\nvector<char> HuffmanTree::GetCode(int i){\n vector<char> code;\n int p = i; //当前节点的下标\n int parent = hufftree[i].parent;\n while(parent!=-1){\n if(hufftree[parent].lchild == p)\n code.insert(code.begin(), '0');\n else\n code.insert(code.begin(), '1');\n p = parent;\n parent = hufftree[parent].parent;\n }\n return code;\n}\n\nstring HuffmanTree::Decode(vector<char> &code){\n string target = \"\";\n int root = hufftree.size() - 1;\n int p = root;\n for(int i=0; i<(int)code.size(); i++){\n if (code[i] == '0')\n p = hufftree[p].lchild;\n else if(code[i] == '1')\n p = hufftree[p].rchild;\n else\n return \"invalid input!\";\n if (hufftree[p].lchild == -1 && hufftree[p].rchild == -1) {\n target = target + hufftree[p].data;\n p = root;\n }\n }\n return target;\n}\n" }, { "alpha_fraction": 0.5317139029502869, "alphanum_fraction": 0.5425100922584534, "avg_line_length": 15.466666221618652, "blob_id": "902397fd0989e080657b54867b500c0d80bed709", "content_id": "38be45fa9e7c9b429d4890cd7a71a402a3686d74", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 763, "license_type": "no_license", "max_line_length": 37, "num_lines": 45, "path": "/data_structure/Expression_Eval/seqstack.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\n 表达式求值\n/\n#include \"seqstack.h\"\nusing namespace std;\n\ntemplate<class T, int MaxSize>\nSeqStack<T,MaxSize>::SeqStack(){\n top = -1;\n}\n\ntemplate<class T, int MaxSize>\nvoid SeqStack<T, MaxSize>::Push(T x){\n if(top == MaxSize-1){\n cerr<<\"上溢\"<<endl;\n exit(1);\n }\n top++;\n data[top] = x;\n}\n\ntemplate<class T, int MaxSize>\nT SeqStack<T, MaxSize>::Pop(){\n if(top == -1){\n cerr<<\"下溢\"<<endl;\n exit(1);\n }\n T x = data[top];\n top--;\n return x;\n}\n\ntemplate<class T, int MaxSize>\nT SeqStack<T, MaxSize>::Top(){\n if(top == -1){\n cerr<<\"下溢\"<<endl;\n exit(1);\n }\n return data[top];\n}\n\ntemplate<class T, int MaxSize>\nbool SeqStack<T, MaxSize>::isEmpty(){\n return top==-1;\n}\n" }, { "alpha_fraction": 0.6731001138687134, "alphanum_fraction": 0.6827502846717834, "avg_line_length": 20.0256404876709, "blob_id": "4661c150a0cd1997ae6a9c7a54a6cd9334a0db58", "content_id": "ff7309949898894a9c5af5c800b04f8c0f0e6d31", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 839, "license_type": "no_license", "max_line_length": 77, "num_lines": 39, "path": "/python/reptilian/1-request.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#from urllib import request, parse, error\n#import socket\n\n'''\ndata = bytes(parse.urlencode({'name':'kinney'}),encoding='utf8')\nresponse = request.urlopen('http://httpbin.org/post', data=data, timeout=0.1)\n'''\n\n'''\ntry:\n\tresponse = request.urlopen(\"http://httpbin.org/post'\", timeout=0.1)\nexcept error.URLError as e:\n\tif isinstance(e.reason, socket.timeout):\n\t\tprint('TIME OUT!')\n'''\n\n'''\nprint(type(response))\nprint(response.status)\nprint(response.getheaders())\nprint(response.getheader('Server'))\n'''\n'''\n#更加强大的Request\nurl = 'http://httpbin.org/post'\nheaders = {\n\t'name':'kinney',\n\t'sex':'mail'\n}\ndict = {\n\t'age':12\n}\ndata = bytes(parse.urlencode(dict), encoding='utf8')\nreq = request.Request(url=url, data=data, headers=headers, method='POST')\nresponse = request.urlopen(req)\nprint(response.read())\n'''\n#opener\nimport\n\n\n\n\n\n\n\n\n\n" }, { "alpha_fraction": 0.73384028673172, "alphanum_fraction": 0.73384028673172, "avg_line_length": 17.785715103149414, "blob_id": "ce8ec30166ccb857698c0292938046edaf4e96eb", "content_id": "f72c4fe39188e982ba7a58a80c65e8c1e45aeab6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 263, "license_type": "no_license", "max_line_length": 59, "num_lines": 14, "path": "/python/grammar/list.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "city = ['nanjing','huaian','yancheng','shanghai','beijing']\nprint(city)\nprint(sorted(city))\nprint(city)\nprint(sorted(city,reverse=True))\nprint(city)\ncity.reverse()\nprint(city)\ncity.reverse()\nprint(city)\ncity.sort()\nprint(city)\ncity.sort(reverse=True)\nprint(city)\n" }, { "alpha_fraction": 0.5351758599281311, "alphanum_fraction": 0.5887772440910339, "avg_line_length": 23.875, "blob_id": "816ba9c1e03b4f48ce16b5313ef54fc44fd4ae09", "content_id": "b48f7053695f8af6a930260de4fa24092cb782aa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 1243, "license_type": "no_license", "max_line_length": 133, "num_lines": 48, "path": "/data_structure/DataSort/main.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "//\n// main.cpp\n// DataSort\n//\n// Created by Kinney凯 on 2018/9/27.\n// Copyright © 2018 Kinney凯. All rights reserved.\n// 随机产生1000个数存入磁盘文件，用各种排序算法排序\n\n#include <iostream>\n#include <stdlib.h>\n#include <fstream>\n#include \"sort.cpp\"\nusing namespace std;\n\nint main(){\n// \tofstream mydata(\"/Users/kinney/Documents/mydata.txt\",ios::out);\n// \tfor(int i=0; i<1000; i++)\n// \t\tmydata << rand()%1000 << \" \";\n// \tmydata.close();\n\t\n// \tint i,len=0;\n// \tifstream fin(\"/Users/kinney/Documents/mydata.txt\",ios::in);\n// \tofstream fout(\"/Users/kinney/Documents/result.txt\",ios::out);\n// \tint a[1000];\n// \tint b[1000];\n// \twhile(!fin.eof()){\n// \t\tfin>>a[len++];\n// \t\tfin>>b[len++];\n// \t}\n\n// //\tShellSort(a, 1000;\n// //\tQuickSort(a, 0, 1000);\n// //\tHeapSort(a, 1000);\n// //\tMergeSort1(a, b, 1000);\n\n// \tfor(int j=0; j<1000; j++){\n// \t\tfout<<a[j]<<\" \";\n// \t}\n// \tfin.close();\n// \tfout.close();\n cout << \"----Function: some sort arithmetic----\" << endl;\n cout << \"please input the data you wanna sort: \" << endl;\n int a[10];\n \n cout << \"please choose the sort arithmetic you wanna use: 1.SelectSort 2.InsertSort 3.ShellSort 4.QuickSort 5.HeapSort \" << endl;\n int method = 0;\n cin >> method;\n}\n" }, { "alpha_fraction": 0.40544000267982483, "alphanum_fraction": 0.42208001017570496, "avg_line_length": 15.891891479492188, "blob_id": "70a238d720ed9e9ee867d6b4090281f994833c2b", "content_id": "f584bc334335024094df3d1869827abb5ac4acc4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 3183, "license_type": "no_license", "max_line_length": 46, "num_lines": 185, "path": "/data_structure/DataSort/sort.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\n 各种排序算法\n /\n#include <iostream>\n#include \"sort.h\"\nusing namespace std;\n\n//二路归并排序\ntemplate <typename T>\nvoid Merge(T a[], T b[], int s, int m, int t){\n\tint i=s;\n\tint j=m+1;\n\tint k=s;\n\twhile(i<=m && j<=t){\n\t\tif(a[i]<=a[j])\n\t\t\tb[k++] = a[i++];\n\t\telse\n\t\t\tb[k++] = a[j++];\n\t}\n\tif(i<=m){\n\t\twhile(i<=m)\n\t\t\tb[k++] = a[i++];\n\t}else{\n\t\twhile(j<=t)\n\t\t\tb[k++] = a[j++];\n\t}\n}\ntemplate <typename T>\nvoid MergePass(T a[], T b[], int n, int h){\n\tint i=1;\n\twhile(i<=n-2h+1){\n\t\tMerge(a, b, i, i+h-1, i+2h-1);\n\t\ti += 2h;\n\t}\n\tif(i<n-h+1)\n\t\tMerge(a, b, i, i+h-1, n);\n\telse\n\t\tfor(int k=i; k<=n; k++)\n\t\t\tb[k] = a[k];\n}\ntemplate <typename T>\nvoid MergeSort1(T a[], T b[], int n){\n\tint h=1;\n\twhile(h<n){\n\t\tMergePass(a, b, n, h);\n\t\th=2h;\n\t\tMergePass(b, a, n, h);\n\t\th=2h;\n\t}\n}\n\n//堆排序\ntemplate <typename T>\nvoid HeapSort(T a[], int n){\n\tint i;\n\tT temp;\n\tfor(i=n/2; i>=1; i--)\n\t Sift(a, i, n);\n\tfor(i=1; i<n; i++){\n\t\ttemp = a[n-i+1];\n\t\ta[n-i+1] = a[1];\n\t\ta[1] = temp;\n\t\tSift(a, 1, n-i);\n\t}\n}\ntemplate <typename T>\nvoid Sift(T a[], int k, int m){\n\tint i=k;\n\tint j=2i;\n\tT temp;\n\twhile(j<=m){\n\t\tif(j<m && a[j]<a[j+1])\n\t\t\tj++;\n\t\tif(a[i]>a[j])\n\t\t\tbreak;\n\t\telse{\n\t\t\ttemp = a[j];\n\t\t\ta[j] = a[i];\n\t\t\ta[i] = temp;\n\t\t\ti=j;\n\t\t\tj=2i;\n\t\t}\n\t}\n}\n\n//快速排序\ntemplate <typename T>\nvoid QuickSort(T a[], int i, int j){\n\tif(i<j){\n\t\tint pivot = Partition(a,i,j);\n\t\tQuickSort(a,i,pivot-1);\n\t\tQuickSort(a,pivot+1,j);\n\t}\n}\ntemplate <typename T>\nint Partition(T a[], int i, int j){\n\tT temp = a[i];\n\twhile(i<j){\n\t\twhile(i<j && a[j]>=temp)\n\t\t\tj--;\n\t\tif(i<j)\n\t\t\ta[i++] = a[j];\n\t\twhile(i<j && a[i]<=temp)\n\t\t\ti++;\n\t\tif(i<j)\n\t\t\ta[j--] = a[i];\n\t}\n\ta[i] = temp;\n\treturn i;\n}\n\n//希尔排序\ntemplate <typename T>\nvoid ShellSort(T a[], int n){\n\tfor(int d=n/2; d>=1; d=d/2){\n\t\tfor(int i=d; i<n; i++){\n\t\t\tint j;\n\t\t\tT temp = a[i];\n\t\t\tfor(j=i-d; j>=0 && temp<a[j]; j=j-d)\n\t\t\t\ta[j+d] = a[j];\n\t\t\ta[j+d] = temp;\n\t\t}\n\t}\n}\n\n//折半插入排序\ntemplate <typename T>\nvoid BinInsertSort(T a[], int n){\n for(int i=0; i<n; i++){\n T temp = a[i];\n int low = 0;\n int high = i-1;\n while(low <= high){\n int mid = (low+high)/2;\n if(temp < a[mid])\n high = mid-1;\n else\n low = mid+1;\n }\n for(int j=i-1; j>=low; j--)\n a[j+1] = a[j];\n a[low] = temp;\n }\n}\n\ntemplate <typename T>\nvoid InsertSort(T a[], int n){\n for(int i=1; i<n; i++){\n int j;\n T temp = a[i];\n for(j=i-1; j>=0 && temp<a[j]; j--)\n a[j+1] = a[j];\n a[j+1]=temp;\n }\n}\n\ntemplate <typename T>\nvoid BubbleSort(T a[], int n){\n for(int i=0; i<n; i++){\n for(int j=0; j<n-i; j++){\n T temp;\n if(a[j] > a[j+1]){\n temp = a[j];\n a[j] = a[j+1];\n a[j+1] = temp;\n }\n }\n }\n}\n\ntemplate <typename T>\nvoid SelectSort(T a[], int n){\n for(int i=0; i<n-1; i++){\n int k = i;\n T temp;\n for(int j=i+1; j<n; j++){\n if(a[j] < a[k]){\n k = j;\n temp = a[i];\n a[i] = a[k];\n a[k] = temp;\n }\n }\n }\n}\n" }, { "alpha_fraction": 0.44871217012405396, "alphanum_fraction": 0.47898781299591064, "avg_line_length": 21.804122924804688, "blob_id": "973e9e393149fba95fbb6aeaf9548b7f380cea6d", "content_id": "8a1d1aabd5e98cf7b4a03847743775ccc1506a06", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 2303, "license_type": "no_license", "max_line_length": 97, "num_lines": 97, "path": "/data_structure/MergeList/seqlist.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\n 功能：合并两个有序线性表，用顺序表实现\n /\n\n#include <iostream>\n#include \"seqlist.h\"\nusing namespace std;\n\ntemplate <class T, int MaxSize>\nSeqList<T, MaxSize>::SeqList(){\n length = 0;\n}\n\ntemplate <class T, int MaxSize>\nSeqList<T, MaxSize>::SeqList(T a[], int n){\n if(n > MaxSize){\n cerr<<\"参数非法\"<<endl;\n exit(1);\n }\n for(int i=0; i<n; i++){\n data[i] = a[i];\n }\n length = n;\n}\n\ntemplate <class T, int MaxSize>\nvoid SeqList<T,MaxSize>::printSeqlist(){\n for(int i=0; i<length; i++)\n cout << data[i] << \" \";\n cout<<endl;\n}\n\ntemplate <class T, int MaxSize>\nT SeqList<T, MaxSize>::getVal(int pos){\n if(pos<1 \|\| pos>length){\n cerr<<\"参数非法\"<<endl;\n exit(1);\n }\n return data[pos-1];\n}\n\ntemplate <class T, int MaxSize>\nvoid SeqList<T, MaxSize>::insert(int pos, T item){\n if(length >= MaxSize){\n cerr << \"上溢\" <<endl;\n exit(1);\n }\n if(pos<1 \|\| pos>length+1){\n cerr << \"插入位置非法！\"<<endl;\n exit(1);\n }\n for(int i=length-1; i>=pos-1; i--)\n data[i+1] = data[i];\n data[pos-1] = item;\n length++;\n}\n\n//合并两个有序顺序表\ntemplate <class T, int MaxSize>\nSeqList<T,MaxSize> SeqList<T, MaxSize>::mergeSeq(SeqList<T,MaxSize> &l1, SeqList<T,MaxSize> &l2){\n SeqList<T,MaxSize> l3;\n int len1 = l1.length;\n int len2 = l2.length;\n int len3 = 0;\n int i = 1;\n int j = 1;\n while(0<i<=len1 && 0<j<=len2){\n if(l2.getVal(j) < l1.getVal(i)){\n l3.insert(i+j-1, l2.getVal(j));\n j++;\n }else if(l2.getVal(j) == l1.getVal(i)){\n l3.insert(i+j-1, l2.getVal(j));\n l3.insert(i+j, l2.getVal(j));\n j++;\n i++;\n }else if(l2.getVal(j) > l1.getVal(i)){\n l3.insert(i+j-1, l1.getVal(i));\n i++;\n }\n \n if(i == len1+1 && j == len2+1){\n break;\n }else if(i == len1+1){\n for(int k=j; k<=len2; k++){\n l3.insert(i+k-1, l2.getVal(k));\n }\n break;\n }else if(j == len2+1){\n for(int m=i; m<=len1; m++){\n l3.insert(j+m-1, l1.getVal(m));\n }\n break;\n }\n }\n len3 = len1+len2;\n return l3;\n}\n\n" }, { "alpha_fraction": 0.6516634225845337, "alphanum_fraction": 0.6653620600700378, "avg_line_length": 24.5, "blob_id": "13d30abf242b9885f24f66a421e2d0c3738fa229", "content_id": "59c94e83272e85c6392f89620a6b7c038759da4b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 511, "license_type": "no_license", "max_line_length": 64, "num_lines": 20, "path": "/python/reptilian/navigating.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "from urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nimport re\n\nhtml = urlopen(\"http://www.pythonscraping.com/pages/page3.html\")\nbsObj = BeautifulSoup(html)\n\n\"\"\"\nprint(bsObj.find(\"img\",{\"src\":\"../img/gifts/img1.jpg\"\n\t\t\t\t}).parent.previous_sibling.get_text())\n\"\"\"\n\"\"\"\n#../img/gifts/img1.jpg\nimages = bsObj.findAll(\"img\",{\"src\":re.compile\n\t\t\t\t(\"\\.\\.\\/img\\/gifts\\/img[0-9]\\.jpg\")})\nfor imag in images:\n\tprint(imag.attrs[\"src\"])\n\"\"\"\ntags = bsObj.findAll(lambda tag : len(tag.attrs) == 2) \nprint(tags)\n\n" }, { "alpha_fraction": 0.545714259147644, "alphanum_fraction": 0.5514285564422607, "avg_line_length": 22.133333206176758, "blob_id": "61fd0fb42cbd6c13b48d0abcd03a072e6717e5d7", "content_id": "25020d10544e2a70d1dc1a66eb6a4960b969c511", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 350, "license_type": "no_license", "max_line_length": 56, "num_lines": 15, "path": "/python/grammar/dic.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "kinney_info = {\n\t'first_name':'zhang',\n\t'last_name':'kai',\n\t'city':'nanjing',\n\t'age':23,\n\t}\n\n#print(\"kinney lives in \" + kinney_info['city'].title())\nfor key, value in kinney_info.items():\n\tif(key=='age'):\n\t\tprint(\"Key: \" + key)\n\t\tprint(\"Value: \" + str(value) + \"\\n\")\t\t\n\telse:\n\t\tprint(\"Key: \" + key)\n\t\tprint(\"Value: \" + str(value).title() + \"\\n\")\t\t\t\n" }, { "alpha_fraction": 0.6085271239280701, "alphanum_fraction": 0.6085271239280701, "avg_line_length": 14.176470756530762, "blob_id": "0eff56bbc78506f3df4c80617d30c0b7fef40390", "content_id": "669b7dc8c720e14190072de1475675fbeff834fd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 258, "license_type": "no_license", "max_line_length": 31, "num_lines": 17, "path": "/data_structure/Expression_Eval/seqstack.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#ifndef SEQSTACK_H\n#define SEQSTACK_H\n\n#include<iostream>\ntemplate <class T, int MaxSize>\nclass SeqStack{\n T data[MaxSize];\n int top;\n public:\n SeqStack();\n void Push(T x);\n T Pop();\n T Top();\n bool isEmpty();\n};\n\n#endif /seqstack_h/\n" }, { "alpha_fraction": 0.6456876397132874, "alphanum_fraction": 0.6596736311912537, "avg_line_length": 16.510204315185547, "blob_id": "f1e597a3f35534d0e5cee9ee771706bc9fc36c6b", "content_id": "528fbb25e54a8409b181cab66e06f05a97aa60fa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 863, "license_type": "no_license", "max_line_length": 50, "num_lines": 49, "path": "/data_structure/DataSort/sort.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "//\n// sort.h\n// DataSort\n//\n// Created by Kinney凯 on 2018/9/28.\n// Copyright © 2018 Kinney凯. All rights reserved.\n//\n\n#ifndef sort_h\n#define sort_h\n\n\ntemplate<typename T>\nvoid BubbleSort(T a[], int n);\n\ntemplate<typename T>\nvoid SelectSort(T a[], int n);\n\ntemplate<typename T>\nvoid InsertSort(T a[], int n);\n\ntemplate<typename T>\nvoid BinInsertSort(T a[], int n);\n\ntemplate<typename T>\nvoid ShellSort(T a[], int n);\n\ntemplate<typename T>\nvoid QuickSort(T a[], int i, int j);\n\ntemplate<typename T>\nint Partition(T a[], int i, int j);\n\ntemplate<typename T>\nvoid Sift(T a[], int k, int m);\n\ntemplate<typename T>\nvoid HeapSort(T a[], int n);\n\ntemplate<typename T>\nvoid Merge(T a[], T b[], int s, int m, int t);\n\ntemplate<typename T>\nvoid MergePass(T a[], T b[], int n, int h);\n\ntemplate<typename T>\nvoid MergeSort1(T a[], T b[], int n);\n\n#endif /* sort_h /\n" }, { "alpha_fraction": 0.6111111044883728, "alphanum_fraction": 0.709876537322998, "avg_line_length": 31.399999618530273, "blob_id": "02bf34ab52b11603f42b11d5bed85acf05354a68", "content_id": "6cda4f2884427ce7771b02601fa13d7fc1550f78", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 162, "license_type": "no_license", "max_line_length": 39, "num_lines": 5, "path": "/python/grammar/writ_string.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#-- coding:utf-8 --\nfilename='write.txt'\nwith open(filename,'w') as file_object:\n\tfile_object.write(\"hello Python3!\\n\")\n\tfile_object.write(str(11111111111111))\n" }, { "alpha_fraction": 0.6082272529602051, "alphanum_fraction": 0.6082272529602051, "avg_line_length": 22.204545974731445, "blob_id": "eba26a603df41cd522a5654e7b5dafbd34d1d1c3", "content_id": "dce200305ae20fc0241e722b3e686474895ca27b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 1021, "license_type": "no_license", "max_line_length": 89, "num_lines": 44, "path": "/data_structure/Binary_Tree/binary_tree.h", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#ifndef BINARY_TREE_H\n#define BINARY_TREE_H\n\n#include<vector>\nusing namespace std;\n\ntemplate<class T>\nstruct BiNode{\n T data;\n BiNode<T> lchild;\n BiNode<T> rchild;\n};\n\ntemplate <class T>\nclass BiTree{\nprivate:\n BiNode<T> root;\n BiNode<T> CreateByPre(vector<T> &pre, int &i);\n BiNode<T> CreateByPreMid(vector<T> &pre, vector<T> &mid, int ipre, int imid, int n);\n BiNode<T> Copy(BiNode<T> p);\n void Free(BiNode<T> p);\n void PreOrder(BiNode<T> p);\n void MidOrder(BiNode<T> p);\n void PostOrder(BiNode<T> p);\n void LevelOrder(BiNode<T> p);\n int Count(BiNode<T> p);\n int Height(BiNode<T> p);\npublic:\n BiTree(){root = NULL;}\n BiTree(vector<T> &pre);\n BiTree(vector<T> &pre, vector<T> &mid);\n BiTree(BiTree<T> &tree);\n ~BiTree();\n void PreOrder();\n void MidOrder();\n void PostOrder();\n void LevelOrder();\n int Count();\n int Height();\n BiNode<T> Search(T e);\n BiNode<T> SearchParent(BiNode<T> child);\n};\n\n#endif /* BINARY_TREE_H /\n" }, { "alpha_fraction": 0.6507462859153748, "alphanum_fraction": 0.6517412662506104, "avg_line_length": 21.795454025268555, "blob_id": "fb8d32aad3285e3af76f843fe64f5646d7d5890d", "content_id": "13f705274d17663af944a4c201a4d4f81ea54a10", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1005, "license_type": "no_license", "max_line_length": 79, "num_lines": 44, "path": "/python/grammar/remember.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#-- coding:utf-8 --\nimport json\n\ndef get_new_user():\n\tfilename='username.json'\n\tmessage=\"type your username,I will remember it!\\n\"\n\tmessage+=\"what's your username? \"\n\tusername=input(message)\n\twith open(filename,'w') as f_obj:\n\t\tjson.dump(username,f_obj)\n\treturn username\t\n\ndef get_stored_user():\n\tfilename='username.json'\n\ttry:\n\t\twith open(filename) as f_obj:\n\t\t\tusername=json.load(f_obj)\n\texcept FileNotFoundError:\n\t\treturn None\n\telse:\n\t\treturn username\n\t\ndef greet_user():\n\tusername=get_stored_user()\n\tif username:\n\t\twhile username:\n\t\t\tmessage=input(\"Is your username \"\n\t\t\t\t\t+username.title()+\"?[y/n] \")\n\t\t\tif message=='y':\n\t\t\t\tprint(\"Welcome back, \"+username.title()+\".\")\n\t\t\t\tbreak\n\t\t\telif message=='n':\n\t\t\t\tusername=get_new_user()\n\t\t\t\tprint(\"We will remember you when you come back,\"\t\t\t\t\t+username.title()+\".\")\n\t\t\t\tbreak\n\t\t\telse:\n\t\t\t\tprint(\"please type 'y' or 'n'!\")\n\t\t\t\n\telse:\n\t\tusername=get_new_user()\n\t\tprint(\"We will remember you when you come back, \"\n\t\t\t\t+username.title()+\".\")\n\ngreet_user()\t\t\n" }, { "alpha_fraction": 0.7058823704719543, "alphanum_fraction": 0.7058823704719543, "avg_line_length": 16, "blob_id": "b36e1b2f9182cf2efb346bfd9b519df6c4213a4b", "content_id": "3dc02bca65e118ecc0d27a8ee032a1d9342b1b71", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 163, "license_type": "no_license", "max_line_length": 28, "num_lines": 9, "path": "/python/django/learning_log/learning_logs/urls.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "\"\"\"定义learning_logs的url模式\"\"\"\n\nfrom django.urls import path\nfrom . import views\n\napp_name = 'learning_logs'\nurlpatterns = [\n\tpath('index/',views.index),\n]\n" }, { "alpha_fraction": 0.4852111041545868, "alphanum_fraction": 0.5026544332504272, "avg_line_length": 22.03643798828125, "blob_id": "eeaa31c5102c9ef92d11f96e2d8b0503e380a11c", "content_id": "a76f72ad4b1784b8a23ee07001f0eb9d8202e5db", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 14411, "license_type": "no_license", "max_line_length": 92, "num_lines": 494, "path": "/data_structure/Hash_Statistics/hash.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "GB18030", "text": "\n#include<string.h>\n//#include<malloc.h> / malloc()等 /\n#include<stdio.h> / EOF(=^Z或F6),NULL /\n#include<stdlib.h> / atoi() /\n#include<math.h> / floor(),ceil(),abs() /\ntypedef int Status; / Status是函数的类型,其值是函数结果状态代码，如OK等 /\r\ntypedef int Boolean; / Boolean是布尔类型,其值是TRUE或FALSE /\r\ntypedef char ElemType;\r\n#define TOTAL 32 //32个关键字\r\n#define MAXLEN 10 //关键字长度\r\n#define HASHLEN 41 //哈希表长度\r\nint cont=0; //统计哈希表中的关键字个数\r\n#define LIST_INIT_SIZE 100 / 线性表存储空间的初始分配量 /\r\n#define LISTINCREMENT 10 / 线性表存储空间的分配增量 /\r\ntypedef struct\r\n{\r\n ElemType elem; /* 存储空间基址 /\r\n int length; / 当前长度 /\r\n int listsize; / 当前分配的存储容量(以sizeof(ElemType)为单位) /\r\n}SqList;\r\ntypedef struct HASH //哈希表\r\n{\r\n char keyword[MAXLEN];\r\n\tint count; //出现次数（频度）\r\n\tint con; //冲突次数\r\n}; \r\nHASH HS[HASHLEN];\r\nchar KeyWords[TOTAL][MAXLEN]= //构造二维数组存储32个关键字\r\n{\r\n\t\"auto\",\"break\",\"case\",\"char\",\"const\",\"continue\",\r\n\t\"default\",\"do\",\"double\",\"else\",\"enum\",\"extern\",\r\n\t\"float\",\"for\",\"goto\",\"if\",\"int\",\"long\",\"register\",\r\n\t\"return\",\"short\",\"signed\",\"sizeof\",\"static\",\r\n\t\"struct\",\"switch\",\"typedef\",\"union\",\"unsigned\",\r\n\t\"void\",\"volatile\",\"while\",\t\r\n};\n\nint main()\r\n{\r\n\topen();\t\r\n}\n\n\r\nvoid ResetHX() //重置哈希表，\r\n{\r\n\tint i;\r\n\tfor(i=0;i<HASHLEN;i++)\r\n\t{\r\n\t\tstrcpy(HS[i].keyword,\"\"); //不能用等号赋值\r\n\t\tHS[i].count=0;\r\n\t\tHS[i].con=0;\r\n\t}\r\n} \r\nvoid jiemian()\r\n{\r\n\tprintf(\"\\n\");\r\n\tprintf(\"\\n\");\r\n\tprintf(\"\\t========1.读取一个文件===========================================\\n\");\r\n\tprintf(\"\\t========2.输出Hash表(关键字总数，冲突次数)=======================\\n\");\r\n\tprintf(\"\\t========3.查询某关键字在Hash表中的情况===========================\\n\");\r\n\tprintf(\"\\t========4.显示Hash表中的冲突关键字===============================\\n\");\r\n\tprintf(\"\\t========5.显示C语言关键字的Hash函数值(作为对照)==================\\n\");\r\n\tprintf(\"\\t========6.返回主页===============================================\\n\");\r\n printf(\"\\t========7.退出===================================================\\n\");\r\n}\r\nint isLetter(char ch) //判断是否是字母，因为关键字都是英文单词\r\n{\r\n\tif( (ch>='a'&&ch<='z')\|\|(ch>='A'&&ch<='Z') ) return 1;\r\n\telse return 0;\r\n\t//是字母就返回1，否则返回0值\r\n}\r\nint isKeyWords(char word) //判断是否关键字\r\n{\r\n\tint i;\r\n\tfor(i=0;i<TOTAL;i++)\r\n\tif(strcmp(word,KeyWords[i])==0) \r\n\treturn 1; \r\n}\r\nint GetKey(char keyword) //哈西函数\r\n{ //Hash函数为：Hash(Key)=[(Key的首字母序号)100+(Key的尾字母序号)] Mod 41\r\n\treturn ( keyword[0]100+keyword[strlen(keyword)-1] ) % 41;\r\n} \r\nint FindHX(char keyword) //查找哈希表，分块查找\r\n{\r\n\tint key,find,tem=0;\r\n if(!isKeyWords(keyword)) return -1;\r\n\tkey=GetKey(keyword); \r\n\tif(strcmp(HS[key].keyword,keyword)==0) return key;\r\n for(find=key+1;find<HASHLEN;find++)\r\n\t{\t\t//线性探查法顺序查找哈希表中是否已存在关键字\r\n\t\ttem++; //统计冲突次数\r\n\t\tif(strcmp(HS[find].keyword,keyword)==0)\r\n\t\t{\r\n\t\tHS[find].con=tem;\r\n\t\treturn find; \r\n\t\t}\r\n\t}\t\r\n for(find=0;find<key;find++)\r\n\t{\r\n\t\ttem++;\r\n\t\tif(strcmp(HS[find].keyword,keyword)==0){\r\n\t\tHS[find].con=tem;\r\n\t\treturn find; }\r\n\t}\t\r\n\r\n} \r\nint GetFreePos(int key) //在哈希表中给关键字找个位置插进去\r\n{\r\n\tint find,tem=0;\r\n\tif(key<0\|\|key>=HASHLEN) return -1;\r\n\tfor(find=key+1;find<HASHLEN;find++) //先找后面的位置\r\n\t{\r\n\t\ttem++;\r\n\t\tif(strlen(HS[find].keyword)==0){\r\n\t\tHS[find].con=tem;\r\n\t\treturn find; }\r\n\t}\r\n for(find=0;find<key;find++) //再找前面的位置\r\n\t{\r\n\t\ttem++;\r\n\t\tif(strlen(HS[find].keyword)==0){\r\n\t\t\tHS[find].con=tem;\r\n\t\t\treturn find; }\r\n\t}\r\n\treturn -1; //哈希表已满\r\n}\r\nint CreatHX(char keyword) //建立哈希表\r\n{\r\n\tint key;\r\n\tif(!isKeyWords(keyword)) return -1; \r\n\tkey=GetKey(keyword); //计算哈希值\r\n if(strlen(HS[key].keyword)>0) //判断关键字表中该位置是否存在关键字\r\n\t{ //已经存在有关键字\r\n\t\tif(strcmp(HS[key].keyword,keyword)==0)\r\n\t\t{ //再判断哈希表中该位置的关键字是否相同\r\n\t\t\tHS[key].count++;\r\n\t\t\treturn 1;\r\n\t\t}\r\n\t\tkey=FindHX(keyword); //不相同，继续查找\r\n\t\tif(key<0)\r\n\t\t{\r\n\t\t\tkey=GetFreePos(GetKey(keyword));\r\n\t\t\tif(key<0) return -1;\t\r\n\t\t\tstrcpy(HS[key].keyword,keyword); //将关键字插入哈希表\r\n\t\t}\r\n if(key<0) return -1;\r\n\t\tHS[key].count++;\r\n\t}\r\n\telse //该位置为空，直接将关键字插入该位置中\r\n\t{\r\n\t\tstrcpy(HS[key].keyword,keyword);\r\n\t\tHS[key].count++;\r\n\t}\r\n\treturn 1;\r\n}\r\nint Read(char filename) //读取文件\r\n{\r\n\tchar word[MAXLEN],ch;\r\n\tint i;\r\n\tFILE read;\r\n if( (read=fopen(filename,\"r\"))==NULL ) //只读方式打开一个文本文件,只允许读数据\t\r\n\t{\r\n\t\tprintf(\"\\t========文件不存在,请确认好再输入!\\n\");\r\n\t\treturn -1;\r\n\t}\r\n\tResetHX(); //读取文件前先清空哈希表\r\n\twhile(!feof(read)) //feof()是文件结束检测函数,如果没有结束,返回值是0,结束了是1\r\n\t{\r\n\t\ti=0;\r\n\t\tch=fgetc(read); //读取一个字符\r\n\t\twhile(isLetter(ch)==0 && feof(read)==0 ) ch=fgetc(read);\r\n\t\t//如果不是字母的话接着读取\r\n\t\twhile(isLetter(ch)==1 && feof(read)==0 )\r\n\t\t{\r\n\t\t\tif(i==MAXLEN)\r\n\t\t\t{\r\n\t\t\t\twhile(isLetter(ch)==1&& feof(read)==0)\r\n\t\t\t\t{\r\n\t\t\t\t\tch=fgetc(read);\r\n\t\t\t\t}\r\n\t\t\t\ti=0;\r\n\t\t\t\tbreak;\r\n\t\t\t}\r\n\t//超过关键字长度将跳过当前识别区域,读取后一单词\r\n\t\t\telse\r\n\t\t\t{ //将连续读取的字母存在数组里，组成一个单词\r\n\t\t\t\tword[i++]=ch;\r\n\t\t\t\tch=fgetc(read);\r\n\t\t\t}\r\n\t\t}\r\n\t\tword[i]='\\0'; //字符数组的结束标志\r\n\t\tif(isKeyWords(word))\r\n\t\t{\r\n\t\t\tCreatHX(word);\r\n\t\t}\r\n\t}\r\n\tfclose(read);\r\n\tprintf(\"\\t========读取成功，文件中关键字已经存入hash表，请继续操作\\n\");\r\n\tjiemian();\r\n\treturn 1;\r\n}\r\nint Input()\r\n{\t\r\n\tprintf(\"\\n\");\r\n\tprintf(\"\\n\");\r\n\tprintf(\"\\t========按'6'主页，请输入你的选择(1-7):\");\r\n while(true) //确保输入的为数字\r\n\t{\r\n\t\tint choice=0;\r\n\t\tif((scanf(\"%d\",&choice)))\r\n\t\t{\r\n\t\t\tif((choice<=0)\|\|(choice>9)) \r\n\t\t\t{\r\n\t\t\t printf(\"输入范围不正确，请重新输入\\n\");\r\n\t\t\t scanf(\"%d\",&choice);\r\n\t\t\t return choice; \r\n\t\t\t}\r\n\t\t}\r\n\t\treturn choice;\r\n\t}\r\n}\r\nvoid Show(int key)\r\n{\r\n\tif(key<0\|\|key>=HASHLEN)\r\n\t{\r\n\t\tprintf(\"关键字不存在!\\n\");\r\n\t\treturn;\r\n\t}\r\n\tif(strlen(HS[key].keyword)==0)\r\n\t{\r\n\t\tprintf(\"哈希表位置：%d 记录是空的\\n\",key);\r\n\t\treturn ;\r\n\t}\r\n\tprintf(\"哈希表位置: %d 关键字: %s\t出现次数: %d\\n\",key,HS[key].keyword,HS[key].count);\r\n cont++;\r\n}\r\nStatus InitList(SqList L) /* 算法2.3 /\r\n { / 操作结果：构造一个空的顺序线性表 /\r\n (L).elem=(ElemType)malloc(LIST_INIT_SIZEsizeof(ElemType));\r\n if(!(L).elem)\r\n exit(OVERFLOW); / 存储分配失败 /\r\n (L).length=0; /* 空表长度为0 /\r\n (L).listsize=LIST_INIT_SIZE; /* 初始存储容量 /\r\n return 1;\r\n }\r\n int ListLength(SqList L)\r\n { \r\n return L.length;/ 初始条件：顺序线性表L已存在。操作结果：返回L中数据元素个数 /\r\n }\r\n Status GetElem(SqList L,int i,ElemType e)\r\n { /* 初始条件：顺序线性表L已存在，1≤i≤ListLength(L) /\r\n / 操作结果：用e返回L中第i个数据元素的值 /\r\n if(i<1\|\|i>L.length)\r\n exit(0);\r\n e=(L.elem+i-1);\r\n return 1;\r\n }\r\n int LocateElem(SqList L,ElemType e,Status(compare)(ElemType,ElemType))\r\n { /* 初始条件：顺序线性表L已存在，compare()是数据元素判定函数(满足为1,否则为0) /\r\n / 操作结果：返回L中第1个与e满足关系compare()的数据元素的位序。 /\r\n / 若这样的数据元素不存在，则返回值为0。算法2.6 /\r\n ElemType p;\r\n int i=1; /* i的初值为第1个元素的位序 /\r\n p=L.elem; / p的初值为第1个元素的存储位置 /\r\n while(i<=L.length&&!compare(p++,e))\r\n ++i;\r\n if(i<=L.length)\r\n return i;\r\n else\r\n return 0;\r\n }\r\n Status ListInsert(SqList L,int i,ElemType e) / 算法2.4 /\r\n { / 初始条件：顺序线性表L已存在，1≤i≤ListLength(L)+1 /\r\n / 操作结果：在L中第i个位置之前插入新的数据元素e，L的长度加1 /\r\n ElemType newbase,q,p;\r\n if(i<1\|\|i>(L).length+1) / i值不合法 /\r\n return 0;\r\n if((L).length>=(L).listsize) / 当前存储空间已满,增加分配 /\r\n {\r\n newbase=(ElemType )realloc((L).elem,((L).listsize+LISTINCREMENT)sizeof(ElemType));\r\n if(!newbase)\r\n exit(OVERFLOW); / 存储分配失败 /\r\n (L).elem=newbase; /* 新基址 /\r\n (L).listsize+=LISTINCREMENT; /* 增加存储容量 /\r\n }\r\n q=(L).elem+i-1; /* q为插入位置 /\r\n for(p=(L).elem+(L).length-1;p>=q;--p) / 插入位置及之后的元素右移 /\r\n (p+1)=p;\r\n q=e; /* 插入e /\r\n ++(L).length; /* 表长增1 /\r\n return 1;\r\n }\r\n Status ListTraverse(SqList L,void(vi)(ElemType))\r\n { / 初始条件：顺序线性表L已存在 /\r\n / 操作结果：依次对L的每个数据元素调用函数vi()。一旦vi()失败，则操作失败 /\r\n / vi()的形参加'&'，表明可通过调用vi()改变元素的值 /\r\n ElemType p;\r\n int i;\r\n p=L.elem;\r\n for(i=1;i<=L.length;i++)\r\n vi(p++);\r\n printf(\"\\n\");\r\n return 1;\r\n }\r\n void print(ElemType c)\r\n {\r\n printf(\"%c\",c);\r\n }\r\nvoid xuanzhe(char KeyWords[][MAXLEN], int n)\r\n{\r\n int i, j, min, t;\r\n for (i=0; i<n-1; i++) /要选择的次数：0~n-2共n-1次/\r\n {\r\n min = i; /假设当前下标为i的数最小，比较后再调整/\r\n for (j=i+1; j<n; j++)/循环找出最小的数的下标是哪个/\r\n {\r\n if (KeyWords[j][MAXLEN-1] < KeyWords[min][MAXLEN-1])\r\n {\r\n min = j; /如果后面的数比前面的小，则记下它的下标/\r\n }\r\n }\r\n if (min != i) /如果min在循环中改变了，就需要交换数据/\r\n {\r\n t = KeyWords[i][MAXLEN-1];\r\n KeyWords[i][MAXLEN-1] = KeyWords[min][MAXLEN-1];\r\n KeyWords[min][MAXLEN-1] = t;\r\n }\r\n }\r\n} \r\n void shunxu()\r\n{\r\n SqList La;\r\n Status i;\r\n int j,k,l=1;\r\n i=InitList(&La);\r\n char KeyWords[TOTAL][MAXLEN]= //构造二维数组存储32个关键字\r\n {\r\n\t\"auto\",\"break\",\"case\",\"char\",\"const\",\"continue\",\r\n\t\"default\",\"do\",\"double\",\"else\",\"enum\",\"extern\",\r\n\t\"float\",\"for\",\"goto\",\"if\",\"int\",\"long\",\"register\",\r\n\t\"return\",\"short\",\"signed\",\"sizeof\",\"static\",\r\n\t\"struct\",\"switch\",\"typedef\",\"union\",\"unsigned\",\r\n\t\"void\",\"volatile\",\"while\",\t\r\n };\t\t\r\n if(i==1) /* 创建空表La成功 /\r\n for(j=0;j<TOTAL;j++) / 在表La中插入32个元素 /\r\n for(k=0;k<MAXLEN;k++)\r\n {\r\n\t i=ListInsert(&La,l,KeyWords[j][k]);\r\n\t l++;\r\n }\r\n printf(\"顺序表La= \"); / 输出表La的内容 /\r\n ListTraverse(La,print);\r\n int m,n;\r\n char x;\r\n int mid,left=0,right=31;\r\n int find1=0,find2=0;\r\n double y;\r\n xuanzhe(KeyWords,32);\r\n printf(\"\\t========请输入要查找的关键字:\");\r\n scanf(\"%s\",&x);\r\n printf(\"\\t========顺序查找:\\n\");\r\n for(m=0;m<32;++m)\r\n {\r\n while(x==KeyWords[m][MAXLEN-1])\r\n {\r\n printf(\"\\t========找到x=%s,KeyWords[%d][MAXLEN-1]\\n\",x,m);\r\n find1=1;\r\n break;\r\n }\r\n }\r\n if(find1==0)\r\n {\r\n printf(\"\\t========没有你要找的关键字\\n\");\r\n }\r\n printf(\"\\t========二分查找:\\n\");\r\n while(!find2&&left<right)\r\n {\r\n mid=(left+right)/2;\r\n if(x==KeyWords[mid][MAXLEN-1])\r\n find2=1;\r\n else if(x<KeyWords[mid][MAXLEN-1])\r\n right=mid-1;\r\n else left=mid+1;\r\n }\r\n if(find2==1)\r\n printf(\"\\t========找到x=%s ,KeyWords[%d][MAXLEN-1]\\n\",x,mid);\r\n else\r\n printf(\"\\t========没有你要找的关键字\\n\");\r\n}\r\nvoid Select(int choice)\r\n{ void open();\r\n\tchar filename[128],word[MAXLEN];\r\n\tint i,key,count;\r\n\tswitch(choice)\r\n\t{\r\n\t\tcase 1:\r\n\t\t\tprintf(\"\\t========请输入要读取的文件名(文件必须与程序在同一目录下):\");\r\n\t\t\tscanf(\"%s\",filename);\r\n\t\t\tprintf(\"\\n\");\r\n\t\t\tRead(filename);\r\n\t\t\tSelect(Input());\r\n\t\t\tbreak;\r\n case 2:\r\n\t\t\tfor(i=0;i<HASHLEN;i++)\r\n\t\t\t{\r\n\t\t\t\tShow(i); \r\n\t\t\t\tif((i)%5==0) getchar(); //为了清晰，每次显示5行\r\n\t\t\t}\r\n\t\t\tprintf(\"关键字总数为：%d\\n\",cont);\r\n\t\t\tjiemian();\r\n\t\t\tSelect(Input());\r\n\t\t\tbreak;\r\n \tcase 3:\r\n\t\t\tprintf(\"\\t========请输入你想要查找的关键字： \");\r\n\t\t\tscanf(\"%s\",&word);\r\n\t\t\tprintf(\"\\n\");\r\n\t\t\tShow(FindHX(word));\r\n\t\t\tjiemian();\r\n\t\t\tSelect(Input());\r\n\t\t\tbreak;\r\n case 4:\r\n\t\t\tprintf(\"\\t冲突关键字列表\\n\\n\");\r\n\t\t\tcount=0;\r\n\t\t\tfor(i=0;i<HASHLEN;i++)\r\n\t\t\t{\r\n\t\t\t\tif(strlen(HS[i].keyword)>0)\r\n\t\t\t\t{\r\n\t\t\t\t\tkey=GetKey(HS[i].keyword);\r\n\t\t\t\t\tif(key!=i)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\tcount++;\r\n\t\t\t\t\t\tprintf(\"\\t[关键字]: %s\\n\",HS[i].keyword);\r\n\t\t\t\t\t\tprintf(\"\\t[哈希表当前位置]: %d\\n\",i);\r\n\t\t\t\t\t\tprintf(\"\\t[冲突次数]: %d\\n\\n\",HS[i].con);\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\tif(count==0) \r\n\t\t\t\tprintf(\"没有冲突\\n\");\r\n\t\t\telse\r\n\t\t\tprintf(\"\\t冲突关键字共: %d个\\n\",count);\r\n\t\t\tjiemian();\r\n\t\t\tSelect(Input());\r\n\t\t\tbreak;\r\n case 5:\r\n\t printf(\"\\n\");\r\n\t printf(\"\\n\");\r\n\t printf(\"\\t=================================================================\\n\");\r\n printf(\"\\t=================================================================\\n\");\r\n\t\t\tprintf(\"\\t========C语言中的关键字和其在哈希表的位置:\\n\");\r\n\t\t\tfor(i=0;i<TOTAL;i++)\r\n\t\t\t{ \r\n\t\t\t printf(\"%s,%d\\n\",KeyWords[i],GetKey(KeyWords[i]));\r\n\t\t\t\tif((i+1)%4==0) printf(\"\\n\");\r\n\t\t\t}\r\n\t\t\tprintf(\"\\n\");\r\n\t\t\tjiemian();\r\n\t\t\tSelect(Input());\r\n\t\t\tbreak;\r\n case 6:\r\n\t\t open();\r\n break;\r\n case 7:\r\n break;//退出\r\n default:\r\n\t\t\tSelect(Input());\r\n\t\t\t\treturn;\r\n\t}\r\n}\r\nvoid open()\r\n{ \r\n ResetHX(); //先清空哈希表\r\n printf(\"\\t========1.hash查找===============================================\\n\");\r\n printf(\"\\t========2.二分查找===============================================\\n\");\r\n printf(\"\\t========3. 退出 ===============================================\\n\");\r\n printf(\"\\n\");\r\n printf(\"\\n\");\r\n printf(\"\\t========请输入你的选择(1-3):\");\r\n int select=0;\r\n scanf(\"%d\",&select);\r\n switch(select)\r\n {\r\n\t\t\tcase 1:\r\n\t\t\t jiemian();\r\n Select(Input());\r\n break;\r\n case 2:\r\n shunxu();\r\n break;\r\n case 3:\r\n break;\r\n }\r\n} \r\n" }, { "alpha_fraction": 0.6584269404411316, "alphanum_fraction": 0.6696628928184509, "avg_line_length": 23.66666603088379, "blob_id": "d28e61f578fa3e91d5dc405da864605334a1a712", "content_id": "40993ecd9df1eca84fc9cb18cbc01151873aabd0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 503, "license_type": "no_license", "max_line_length": 39, "num_lines": 18, "path": "/python/grammar/my_icecreamstand.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#-- coding:utf-8 --\nfrom icecreamstand import IceCreamStand\n\nicecream = IceCreamStand('米其林','上海')\nicecream.flavors=['香草','草莓','蓝莓','菠萝']\nicecream.show_flavors()\n\nicecream.set_number_served(30)\nprint(\"在\" + icecream.location + \"的\"\n\t+ icecream.name + \"餐馆服务了\"\n\t+ str(icecream.number_served) + \"人\"\n\t)\n\nicecream.increment_number_served(70)\nprint(\"在\" + icecream.location + \"的\"\n\t+ icecream.name + \"餐馆服务了\"\n\t+ str(icecream.number_served) + \"人\"\n )\n\n" }, { "alpha_fraction": 0.6629213690757751, "alphanum_fraction": 0.6629213690757751, "avg_line_length": 28.66666603088379, "blob_id": "f6de0eab54c6cd52ea2bb4aea37ab00a1907444d", "content_id": "f2865a9b884ba220b6d587b1de03f0206b50f59d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 89, "license_type": "no_license", "max_line_length": 37, "num_lines": 3, "path": "/python/grammar/loop.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "magicians = ['kinney','nancy','jack']\nfor magician in magicians:\n print(magician)\n" }, { "alpha_fraction": 0.41838133335113525, "alphanum_fraction": 0.44958847761154175, "avg_line_length": 18.70270347595215, "blob_id": "ab5d4a4d48a8df916a316d3aa209621b0c2a5491", "content_id": "a81859efa8b6891ff798e570867b0307ff981372", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 3002, "license_type": "no_license", "max_line_length": 69, "num_lines": 148, "path": "/data_structure/MergeList/linklist.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\n 功能：合并两个有序线性表，用链表实现\n /\n\n#include <iostream>\n#include \"linklist.h\"\nusing namespace std;\n\ntemplate <class T>\nLinkList<T>::LinkList(){\n head = new Node<T>;\n head->next = NULL;\n}\n\ntemplate <class T>\nLinkList<T>::LinkList(T a[], int n){\n head = new Node<T>;\n Node<T> rear = head;\n for(int i=0; i<n; i++){\n Node<T> s = new Node<T>; //移动的指针\n s->data = a[i];\n rear->next = s;\n rear = s;\n }\n rear->next = NULL;\n}\n\ntemplate <class T>\nint LinkList<T>::length(){\n int num = 0;\n Node<T> p = head->next;\n while(p){\n p = p->next;\n num++;\n }\n return num;\n}\n\ntemplate <class T>\nvoid LinkList<T>::insert(int pos, T item){\n Node<T> p = head;\n int j=0;\n while(p && j< pos-1){\n p = p->next;\n j++;\n }\n if(!p){\n cerr << \"插入位置非法\";\n exit(1);\n }else{\n Node<T> s = new Node<T>;\n s->data = item;\n s->next = p->next;\n p->next = s;\n }\n}\n\ntemplate <class T>\nT LinkList<T>::getVal(int pos){\n Node<T> p = head->next;\n int j=1;\n while(p && j< pos){\n p = p->next;\n j++;\n }\n if(!p \|\| j>pos){\n cerr << \"查找位置非法\";\n exit(1);\n }else{\n return p->data;\n }\n}\n\ntemplate <class T>\nvoid LinkList<T>::printLinklist(){\n Node<T> p = head->next;\n while(p){\n cout << p->data << \" \";\n p = p->next;\n }\n}\n\n//合并两个有序链表\ntemplate <class T>\nLinkList<T> LinkList<T>::mergeLink(LinkList<T> &l1, LinkList<T> &l2){\n LinkList<T> l3;\n int len1 = l1.length();\n int len2 = l2.length();\n int len3 = 0;\n int i = 1;\n int j = 1;\n while(0<i<=len1 && 0<j<=len2){\n if(l2.getVal(j) < l1.getVal(i)){\n l3.insert(i+j-1, l2.getVal(j));\n j++;\n }else if(l2.getVal(j) == l1.getVal(i)){\n l3.insert(i+j-1, l2.getVal(j));\n l3.insert(i+j, l2.getVal(j));\n j++;\n i++;\n }else if(l2.getVal(j) > l1.getVal(i)){\n l3.insert(i+j-1, l1.getVal(i));\n i++;\n }\n \n if(i == len1+1 && j == len2+1){\n break;\n }else if(i == len1+1){\n for(int k=j; k<=len2; k++){\n l3.insert(i+k-1, l2.getVal(k));\n }\n break;\n }else if(j == len2+1){\n for(int m=i; m<=len1; m++){\n l3.insert(j+m-1, l1.getVal(m));\n }\n break;\n }\n }\n len3 = len1+len2;\n return l3;\n}\n\n\n/\n void mergeLink(LinkList<int> &L1, LinkList<int> &L2){\n Node<int> p1 = L1.head->next;\n Node<int> p2 = L2.head->next;\n Node<int> p3 = L1.head;\n while(p1 != NULL && p2 != NULL){\n if(p1->data < p2->data){\n p3->next = p1;\n p1 = p1->next;\n p3 = p3->next;\n }else{\n p3->next = p2;\n p2 = p2->next;\n p3 = p3->next;\n }\n }\n if(p1 != NULL)\n p3->next = p1;\n if(p2 != NULL)\n p3->next = p2;\n delete L2.head;\n L2.head = NULL;\n }\n/\n" }, { "alpha_fraction": 0.4232741594314575, "alphanum_fraction": 0.4429980218410492, "avg_line_length": 25.663158416748047, "blob_id": "cd5bd94082bca847679638b3f9f9c6b4de9a5dd1", "content_id": "f325a6156723bfa02bb221d2a29e40ff5efb43fc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 2715, "license_type": "no_license", "max_line_length": 97, "num_lines": 95, "path": "/data_structure/MergeList/main.cpp", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "/\n 功能：合并两个有序线性表，用顺序表和链表两种方式实现，\n 并用菜单选择，要求交互方式友好。\n/\n\n#include <limits>\n#include <string>\n#include \"seqlist.cpp\"\n#include \"linklist.cpp\"\n\nint main(){\n int ignoreWrongType(int num);\n void runMerge(string str);\n\n bool q=true;\n while(q){\n cout << \"-----------------------------------\";\n cout << \"\\nFunction : Merge two sorted lists\" <<endl;\n cout << \"please choose the way to merge two lists：1.Seqlist 2.Linklist 3.quit\" << endl;\n cout << \"type 1 or 2 or 3: \";\n int num=0;\n //抵抗类型错误的非法输入\n num = ignoreWrongType(num);\n\n if( num == 1 \|\| num == 2 \|\| num == 3){\n switch( num ) {\n case 1 : {\n runMerge(\"seqlist\");\n break;\n }\n case 2 : {\n runMerge(\"linklist\");\n break;\n }\n case 3 : {\n runMerge(\"quit\"); \n q = false;\n break;\n }\n default : {\n break;\n }\n\t }\n\t }\n\t}\n}\n\nint ignoreWrongType(int num){\n if (cin >> num){\n }\n else{\n cin.clear(); // 把cin的错误状态清除\n cin.ignore(numeric_limits < streamsize>::max(),'\\n'); // 忽略输入流里接下来的字符，直到遇到换行符\n cout<<\"WARNNING: illegal type!\\n\";\n }\n return num;\n}\n\nvoid runMerge(string str){ //merge操作的交互功能\n if(str==\"seqlist\" \|\| str==\"linklist\"){\n int n1,n2;\n cout << \"\\nplease type the number of elements in list1: \";\n cin >> n1;\n int a[n1];\n cout << \"please type \"<< n1 << \" elements: \";\n for(int i=0; i<n1; i++)\n cin >> a[i];\n cout << endl;\n \n cout << \"please type the number of elements in list2: \";\n cin >> n2;\n int b[n2];\n cout << \"please type \"<< n2 << \" elements: \";\n for(int i=0; i<n2; i++)\n cin >> b[i];\n cout << endl;\n \n if(str == \"seqlist\"){\n SeqList<int, 20> l1(a,n1);\n SeqList<int, 20> l2(b,n2);\n cout << \"the list merged by list1 and list2 is: \";\n l1.mergeSeq(l1,l2).printSeqlist();\n }else if(str == \"linklist\"){\n LinkList<int> l1(a,n1);\n LinkList<int> l2(b,n2);\n cout << \"the list merged by list1 and list2 is: \";\n l1.mergeLink(l1,l2).printLinklist();\n }\n cout << endl;\n }else if(str == \"quit\"){\n }else{\n cerr<<\"this way of merge is not exist!\"<<endl;\n exit(1);\n }\n}\n\n\n" }, { "alpha_fraction": 0.5348115563392639, "alphanum_fraction": 0.5600886940956116, "avg_line_length": 17.867841720581055, "blob_id": "cebf092d7951af0b7922797247dc1376edcaa86a", "content_id": "a3f5b3e02de55aa698345cce4db3b34f1e72f2d4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4942, "license_type": "no_license", "max_line_length": 73, "num_lines": 227, "path": "/python/grammar/hello.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "# encoding=utf-8\r\n'''\r\n#基础输入输出\r\nprint (\"hello,world!\\nI love English\")\r\nprint (\"I love programming!\")\r\na, b, c, d = 20, 3.14, True, 4+3j\r\nc = a + b\r\n#print(type(a), type(b), type(c), type(d))\r\ns = 'Yes, he doesn\\'t.' #反斜杠转义特殊字符。\r\ns_ = r'Yes, he doesn\\'t.' #字符前加r，取消反斜杠的转义。\r\nprint('str'+'ing')\r\nprint('my'3)\r\n'''\r\n'''\r\n#字符串\r\nword = 'IlovePython'\r\nprint(word[0], word[10])\r\nprint(word[-1], word[-11]) #没有单独的字符类型，索引有两种方式；\r\nprint(word[1:5])\r\nprint(word[5:]) #获取子串，区间前闭后开；字符不能通过赋值修改；\r\n'''\r\n'''\r\n#列表\r\na = ['him', 25, 100, 'her']\r\nb = a[0:3]\r\nb += [1,2,3] #串联\r\nb[0:3] = [4,5,6] #列表可通过下标修改值\r\nb[0:3] = [] #删除元素\r\nprint(b) #列表也可以索引和切片；\r\n'''\r\n'''\r\n#元组\r\ntup = (1,2,3,4,5,6)\r\nprint(tup[1])\r\nprint(tup[0:3])\r\ntup1,tup2 = (), (1,) #元组只有一个元素需要加逗号\r\nprint(tup1)\r\nprint(tup2)\r\nprint(tup2+tup)\r\n#tup[0]=10 元组不能通过下标修改\r\n'''\r\n'''\r\n#集合\r\nstudent = {'Jim', 'Tom', 'Jack', 'Jenny', 'Kinney'}\r\nprint(student)\r\nprint('Jim' in student)\r\na = set('qwertyu')\r\nb = set('qwetasdf')\r\nprint(a)\r\nprint(a-b) #差集\r\nprint(a\|b) #并集\r\nprint(a&b) #交集\r\nprint(a^b) #并集减交集\r\n'''\r\n'''\r\n#字典\r\ndic = {}\r\ntel = {'Jack':1001, 'Tom':1002, 'Jim':1003, 'Kinney':1004}\r\nprint(tel)\r\nprint(tel['Kinney']) #通过键查找值\r\ndel tel['Jack'] #删除某个键值\r\nprint(tel)\r\ntel['Mary'] = 1005 #添加一个键值\r\nprint(tel)\r\na = list(tel.keys()) #获取所有键的列表\r\nprint(a)\r\nb = sorted(tel.keys()) #按key排序\r\nprint(b)\r\nprint('Kinney' in tel) #成员测试\r\n'''\r\n'''\r\na = 20\r\nif a==10:\r\n\t print(a)\r\n \r\nelse:\r\n\tprint(-a)\r\n'''\r\n'''\r\nanimals=['dog','cat','bear','pig']\r\nfor animal in animals:\r\n\tprint(\"A \"+ animal +\" would make a good pet!\")\r\nprint(\"every animals would be our best pet!\")\r\n'''\r\n'''\r\nlist=[num*2 for num in range(1,10000,2)]\r\nprint(sum(list))\r\n'''\r\n'''\r\n\r\nprint(\"加了两人数字\")\r\ntups=(1,2,3,4,5,6,7)\r\nfor tup in tups:\r\n\tprint(tup)\r\n'''\r\n'''\r\n#a list of dic\r\nimport json\r\np1={\r\n 'name':'kinney',\r\n 'age':22,\r\n 'city':'nanjing',\r\n 'sex':'男',\r\n }\r\np2={\r\n 'name':'nancy',\r\n 'age':21,\r\n 'city':'nanjing',\r\n 'sex':'女',\r\n }\r\np1=json.dumps(p1,ensure_ascii=False)\r\np2=json.dumps(p2,ensure_ascii=False)\r\npeople=[p1,p2]\r\nfor p in people:\r\n\tprint(p)\r\n'''\r\n'''\r\n#a list in dic\r\nimport json\r\nperson={\r\n 'name':'kinney',\r\n 'hobby':['swimming','sleeping','running'],\r\n 'sex':'男',\r\n 'family':['father','mother'],\r\n 'age':'23',\r\n}\r\n\r\njson_person=json.dumps(person,ensure_ascii=False)\r\nprint(json_person) #直接打印含有中文的字典要处理\r\nprint('---------------------------')\r\nfor keys, values in person.items():\r\n\tprint(\"key: \" + keys)\r\n\tprint(\"value: \" + str(values) + \"\\n\")\r\nprint(\"------------------------------\")\r\nfor key in sorted(person.keys()):\r\n\tprint(key)\r\nprint(\"------------------------------\")\r\nfor value in set(person['hobby']):\r\n\tprint(value)\r\nprint(\"------------------------------\")\r\n'''\r\n'''\r\n#a dic in a dic\r\nimport json\r\n\r\nperson={\r\n 'kinney':{\r\n\t'city':'nanjing',\r\n\t'age':23,\r\n\t'sex':'男',\r\n\t},\r\n 'nancy':{\r\n\t'city':'nanjing',\r\n\t'age':22,\r\n\t'sex':'女',\r\n\t},\r\n }\r\n\r\njson_person=json.dumps(person,ensure_ascii=False)\r\nprint(json_person)\r\nprint('--------------------------------')\r\nfor name in person.keys():\r\n\tprint(name)\r\n'''\r\n'''\r\nage = int(input(\"please tell me your age: \"))\r\nif age<18:\r\n\tprint('you are so young,you can\\'t play this game!')\r\nelif age>=18:\r\n\tprint('OK,let\\'s start the game now!')\r\n'''\r\n'''\r\nprompt = \"\\nTell me something, and I will repeat it back to you:\"\r\nprompt += \"\\nEnter 'quit' to end the program. \"\r\nmessage = \"\"\r\nwhile message != 'quit':\r\n\tmessage = input(prompt)\r\n\tprint(message)\r\n'''\r\n'''\r\nprint(\"---------An interesting game--------\\n\")\r\nresponses={}\r\nwhile True:\r\n\tname = input(\"\\nWhat's your name? \")\r\n\tlove_pet = input(\"\\nWhat's your favoriate pet? \")\r\n\tresponses[name]=love_pet\r\n\tmessage = input(\"\\nDo you want others to answer these questions?[y/n] \")\r\n\tif message == 'n':\r\n\t\tbreak\r\n\r\nprint(\"\\nRESPONSES:\")\r\nfor name, love_pet in responses.items():\r\n\tprint(name.title() + \"'s favoriate pet is \" + love_pet.title()+\".\")\r\n'''\r\n'''\r\ndef greet_user():\r\n\tprint(\"hello\")\r\n\r\ngreet_user()\r\n'''\r\n'''\r\n#函数练习\r\nmagicians=['kinney','jack','nancy','aden']\r\nnew_magicians=[]\r\n\r\ndef show_magicians(magicians):\r\n\tfor magician in magicians:\r\n\t\tprint(magician.title())\r\ndef make_great(magicians):\r\n\twhile magicians:\r\n\t\ttemp = 'the great ' + magicians.pop()\t\t\r\n\t\tnew_magicians.append(temp)\r\n\r\nshow_magicians(magicians)\r\nmake_great(magicians[:]) #修改副本\r\nshow_magicians(new_magicians)\r\nshow_magicians(magicians)\r\n'''\r\n'''\r\nfoods=[]\r\ndef show_sandwitch(foods):\r\n\tprint(\"三明治的食材有: \")\r\n\tfor food in foods:\r\n\t\tprint(food+' ',end='')\r\n\tprint('\\n')\r\nshow_sandwitch('egg','milk','bread')\r\n'''\r\n" }, { "alpha_fraction": 0.7202472686767578, "alphanum_fraction": 0.7233384847640991, "avg_line_length": 20.566667556762695, "blob_id": "fe2e0996f5592271a532b4cc048c5b9f57bdcbef", "content_id": "ea6cef0458f455763c13d594646582a19d545ce8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 647, "license_type": "no_license", "max_line_length": 70, "num_lines": 30, "path": "/python/reptilian/scrapetest.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "from urllib.request import urlopen\nfrom urllib.error import HTTPError\nfrom bs4 import BeautifulSoup\n\n\"\"\"\ndef getTitle(url):\n\ttry:\n\t\thtml = urlopen(url)\n\texcept HTTPError as e:\n\t\treturn None\n\ttry:\n\t\tbsObj = BeautifulSoup(html.read())\n\t\ttitle = bsObj.body.h1\n\texcept AttributeError as e:\n\t\treturn None\n\treturn title\n\nurl = \"https://stackoverflow.com\"\ntitle = getTitle(url)\nif title == None:\n\tprint(\"title could not be found!\")\nelse:\n\tprint(title)\n\"\"\"\n\nhtml = urlopen(\"http://www.pythonscraping.com/pages/warandpeace.html\")\nbsObj = BeautifulSoup(html)\nnameList = bsObj.findAll(\"span\", {\"class\":\"green\"})\nfor name in nameList:\n\tprint(name.get_text())\n" }, { "alpha_fraction": 0.7111716866493225, "alphanum_fraction": 0.7138964533805847, "avg_line_length": 21.875, "blob_id": "4c72ff6f6b0e67f5912b9aea07296228513a34f3", "content_id": "4478591da564a6695f4f1f9c434f85d19e72978e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 367, "license_type": "no_license", "max_line_length": 35, "num_lines": 16, "path": "/python/grammar/pi_string.py", "repo_name": "Kinneyzhang/program_work", "src_encoding": "UTF-8", "text": "#-- coding:utf-8 --\nfilename='pi.txt'\nwith open(filename) as file_object:\n\tlines=file_object.readlines()\npi_string=''\nfor line in lines:\n\tpi_string+=line.strip()\nprint(pi_string.strip())\n\nwith open(filename) as file_object:\n\tcontents=file_object.read()\n\tprint(contents.rstrip())\n\nwith open(filename) as file_object:\n\tfor line in file_object:\n\t\tprint(line.strip())\n\n" } ]	38
Khatijaa/Github_upload	https://github.com/Khatijaa/Github_upload	0046fa59b84364d588357d1457c53b89fe0c1541	85f669c75c5615f073804a01529c0fa8ef493bb0	f8532b8c1e60d793a0e99a235a5b4290c75df21f	refs/heads/main	2023-08-01T02:23:35.965994	2021-09-19T19:41:52	2021-09-19T19:41:52	408,220,519	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5734494924545288, "alphanum_fraction": 0.588211178779602, "avg_line_length": 43.95391845703125, "blob_id": "57d95af13949526577ddf5ed5a5f6f7c3472c249", "content_id": "4781cea252ff23d5543aca28151242eccf31105c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 9755, "license_type": "no_license", "max_line_length": 166, "num_lines": 217, "path": "/loan_analyzer.py", "repo_name": "Khatijaa/Github_upload", "src_encoding": "UTF-8", "text": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"7287487d-b41d-42cb-897b-1726f317c442\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# coding: utf-8\\n\",\n \"import csv\\n\",\n \"from pathlib import Path\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"Part 1: Automate the Calculations.\\n\",\n \"\\n\",\n \"Automate the calculations for the loan portfolio summaries.\\n\",\n \"\\n\",\n \"First, let's start with some calculations on a list of prices for 5 loans.\\n\",\n \" 1. Use the `len` function to calculate the total number of loans in the list.\\n\",\n \" 2. Use the `sum` function to calculate the total of all loans in the list.\\n\",\n \" 3. Using the sum of all loans and the total number of loans, calculate the average loan price.\\n\",\n \" 4. Print all calculations with descriptive messages.\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"loan_costs = [500, 600, 200, 1000, 450]\\n\",\n \"\\n\",\n \"# How many loans are in the list?\\n\",\n \"# @TODO: Use the `len` function to calculate the total number of loans in the list.\\n\",\n \"# Print the number of loans from the list\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"# What is the total of all loans?\\n\",\n \"# @TODO: Use the `sum` function to calculate the total of all loans in the list.\\n\",\n \"# Print the total value of the loans\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"# What is the average loan amount from the list?\\n\",\n \"# @TODO: Using the sum of all loans and the total number of loans, calculate the average loan price.\\n\",\n \"# Print the average loan amount\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"Part 2: Analyze Loan Data.\\n\",\n \"\\n\",\n \"Analyze the loan to determine the investment evaluation.\\n\",\n \"\\n\",\n \"Using more detailed data on one of these loans, follow these steps to calculate a Present Value, or a \\\"fair price\\\" for what this loan would be worth.\\n\",\n \"\\n\",\n \"1. Use get() on the dictionary of additional information to extract the Future Value and Remaining Months on the loan.\\n\",\n \" a. Save these values as variables called `future_value` and `remaining_months`.\\n\",\n \" b. Print each variable.\\n\",\n \"\\n\",\n \" @NOTE:\\n\",\n \" Future Value: The amount of money the borrower has to pay back upon maturity of the loan (a.k.a. \\\"Face Value\\\")\\n\",\n \" Remaining Months: The remaining maturity (in months) before the loan needs to be fully repaid.\\n\",\n \"\\n\",\n \"2. Use the formula for Present Value to calculate a \\\"fair value\\\" of the loan. Use a minimum required return of 20% as the discount rate.\\n\",\n \"3. Write a conditional statement (an if-else statement) to decide if the present value represents the loan's fair value.\\n\",\n \" a. If the present value of the loan is greater than or equal to the cost, then print a message that says the loan is worth at least the cost to buy it.\\n\",\n \" b. Else, the present value of the loan is less than the loan cost, then print a message that says that the loan is too expensive and not worth the price.\\n\",\n \"\\n\",\n \" @NOTE:\\n\",\n \" If Present Value represents the loan's fair value (given the required minimum return of 20%), does it make sense to buy the loan at its current cost?\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"# Given the following loan data, you will need to calculate the present value for the loan\\n\",\n \"loan = {\\n\",\n \" \\\"loan_price\\\": 500,\\n\",\n \" \\\"remaining_months\\\": 9,\\n\",\n \" \\\"repayment_interval\\\": \\\"bullet\\\",\\n\",\n \" \\\"future_value\\\": 1000,\\n\",\n \"}\\n\",\n \"\\n\",\n \"# @TODO: Use get() on the dictionary of additional information to extract the Future Value and Remaining Months on the loan.\\n\",\n \"# Print each variable.\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"\\n\",\n \"# @TODO: Use the formula for Present Value to calculate a \\\"fair value\\\" of the loan.\\n\",\n \"# Use a minimum required return of 20% as the discount rate.\\n\",\n \"# You'll want to use the monthly version of the present value formula.\\n\",\n \"# HINT: Present Value = Future Value / (1 + Discount_Rate/12) ** remaining_months\\n\",\n \"\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"# If Present Value represents what the loan is really worth, does it make sense to buy the loan at its cost?\\n\",\n \"# @TODO: Write a conditional statement (an if-else statement) to decide if the present value represents the loan's fair value.\\n\",\n \"# If the present value of the loan is greater than or equal to the cost, then print a message that says the loan is worth at least the cost to buy it.\\n\",\n \"# Else, the present value of the loan is less than the loan cost, then print a message that says that the loan is too expensive and not worth the price.\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"Part 3: Perform Financial Calculations.\\n\",\n \"\\n\",\n \"Perform financial calculations using functions.\\n\",\n \"\\n\",\n \"1. Define a new function that will be used to calculate present value.\\n\",\n \" a. This function should include parameters for `future_value`, `remaining_months`, and the `annual_discount_rate`\\n\",\n \" b. The function should return the `present_value` for the loan.\\n\",\n \"2. Use the function to calculate the present value of the new loan given below.\\n\",\n \" a. Use an `annual_discount_rate` of 0.2 for this new loan calculation.\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"# Given the following loan data, you will need to calculate the present value for the loan\\n\",\n \"new_loan = {\\n\",\n \" \\\"loan_price\\\": 800,\\n\",\n \" \\\"remaining_months\\\": 12,\\n\",\n \" \\\"repayment_interval\\\": \\\"bullet\\\",\\n\",\n \" \\\"future_value\\\": 1000,\\n\",\n \"}\\n\",\n \"\\n\",\n \"# @TODO: Define a new function that will be used to calculate present value.\\n\",\n \"# This function should include parameters for `future_value`, `remaining_months`, and the `annual_discount_rate`\\n\",\n \"# The function should return the `present_value` for the loan.\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"\\n\",\n \"# @TODO: Use the function to calculate the present value of the new loan given below.\\n\",\n \"# Use an `annual_discount_rate` of 0.2 for this new loan calculation.\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"print(f\\\"The present value of the loan is: {present_value}\\\")\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"Part 4: Conditionally filter lists of loans.\\n\",\n \"\\n\",\n \"In this section, you will use a loop to iterate through a series of loans and select only the inexpensive loans.\\n\",\n \"\\n\",\n \"1. Create a new, empty list called `inexpensive_loans`.\\n\",\n \"2. Use a for loop to select each loan from a list of loans.\\n\",\n \" a. Inside the for loop, write an if-statement to determine if the loan_price is less than 500\\n\",\n \" b. If the loan_price is less than 500 then append that loan to the `inexpensive_loans` list.\\n\",\n \"3. Print the list of inexpensive_loans.\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"loans = [\\n\",\n \" {\\n\",\n \" \\\"loan_price\\\": 700,\\n\",\n \" \\\"remaining_months\\\": 9,\\n\",\n \" \\\"repayment_interval\\\": \\\"monthly\\\",\\n\",\n \" \\\"future_value\\\": 1000,\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"loan_price\\\": 500,\\n\",\n \" \\\"remaining_months\\\": 13,\\n\",\n \" \\\"repayment_interval\\\": \\\"bullet\\\",\\n\",\n \" \\\"future_value\\\": 1000,\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"loan_price\\\": 200,\\n\",\n \" \\\"remaining_months\\\": 16,\\n\",\n \" \\\"repayment_interval\\\": \\\"bullet\\\",\\n\",\n \" \\\"future_value\\\": 1000,\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"loan_price\\\": 900,\\n\",\n \" \\\"remaining_months\\\": 16,\\n\",\n \" \\\"repayment_interval\\\": \\\"bullet\\\",\\n\",\n \" \\\"future_value\\\": 1000,\\n\",\n \" },\\n\",\n \"]\\n\",\n \"\\n\",\n \"# @TODO: Create an empty list called `inexpensive_loans`\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"# @TODO: Loop through all the loans and append any that cost $500 or less to the `inexpensive_loans` list\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"# @TODO: Print the `inexpensive_loans` list\\n\",\n \"# YOUR CODE HERE!\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"Part 5: Save the results.\\n\",\n \"\\n\",\n \"Output this list of inexpensive loans to a csv file\\n\",\n \" 1. Use `with open` to open a new CSV file.\\n\",\n \" a. Create a `csvwriter` using the `csv` library.\\n\",\n \" b. Use the new csvwriter to write the header variable as the first row.\\n\",\n \" c. Use a for loop to iterate through each loan in `inexpensive_loans`.\\n\",\n \" i. Use the csvwriter to write the `loan.values()` to a row in the CSV file.\\n\",\n \"\\n\",\n \" Hint: Refer to the official documentation for the csv library.\\n\",\n \" https://docs.python.org/3/library/csv.html#writer-objects\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"# Set the output header\\n\",\n \"header = [\\\"loan_price\\\", \\\"remaining_months\\\", \\\"repayment_interval\\\", \\\"future_value\\\"]\\n\",\n \"\\n\",\n \"# Set the output file path\\n\",\n \"output_path = Path(\\\"inexpensive_loans.csv\\\")\\n\",\n \"\\n\",\n \"# @TODO: Use the csv library and `csv.writer` to write the header row\\n\",\n \"# and each row of `loan.values()` from the `inexpensive_loans` list.\\n\",\n \"# YOUR CODE HERE!\\n\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.8\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" } ]	1
Mvegala/logs_analyzer	https://github.com/Mvegala/logs_analyzer	912e61e2f14572df642a1cb9dc1d16234712ad32	2e68eb5e47cfc654b79d09f4ba2461614fe06a4a	06e1f2824765acd2b3fd5dd1bd7b1a3122b66926	refs/heads/master	2020-04-22T13:15:59.065272	2019-02-12T23:13:15	2019-02-12T23:13:15	170,403,091	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.800000011920929, "alphanum_fraction": 0.800000011920929, "avg_line_length": 14.333333015441895, "blob_id": "087fa8d55d68e5322b2f206155e8d30af06eec41", "content_id": "b7d4c5d4c6676a88b36498fd742478fd15f7c8c7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 45, "license_type": "no_license", "max_line_length": 28, "num_lines": 3, "path": "/README.md", "repo_name": "Mvegala/logs_analyzer", "src_encoding": "UTF-8", "text": "# logs_analyzer\n\nAnalyzer of Apache log files" }, { "alpha_fraction": 0.5327783823013306, "alphanum_fraction": 0.5390218496322632, "avg_line_length": 24.289474487304688, "blob_id": "c6203d02d78779fe3eb759d4f47c073c34cd808e", "content_id": "3d88cf3d1e874309097fbc1bc2ebdaced7f3df54", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 961, "license_type": "no_license", "max_line_length": 104, "num_lines": 38, "path": "/analyzer.py", "repo_name": "Mvegala/logs_analyzer", "src_encoding": "UTF-8", "text": "import pandas as pd\n\n\ndef load_logs(path):\n # where data will be stored\n ips = []\n timestamps = []\n commands = []\n http_codes = []\n response_bytes = []\n\n # load file\n with open(path, 'r') as f:\n # analyze each line of file\n for line in f:\n # split by space\n line_splitted = line.split(' ')\n\n ips.append(line_splitted[0])\n timestamps.append(int(line_splitted[3]))\n commands.append(line_splitted[4])\n http_codes.append(int(line_splitted[5]))\n response_bytes.append(int(line_splitted[6]) if line_splitted[6].isdigit() else float('NaN'))\n\n df = pd.DataFrame(data={\n 'ip': ips,\n 'timestamp': timestamps,\n 'command': commands,\n 'http_code': http_codes,\n 'response_bytes': response_bytes,\n })\n\n return df\n\n\ndef analyze_logs(df_logs):\n # TODO: Perform analysis here\n pass\n" }, { "alpha_fraction": 0.49148935079574585, "alphanum_fraction": 0.49148935079574585, "avg_line_length": 22.5, "blob_id": "259a01075064e5e801fcb775e22e3d005d4fd849", "content_id": "06558afc7ab89a573b6a65ed12c8431a18a4e6e7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 470, "license_type": "no_license", "max_line_length": 56, "num_lines": 20, "path": "/main.py", "repo_name": "Mvegala/logs_analyzer", "src_encoding": "UTF-8", "text": "import os\nfrom analyzer import (\n load_logs,\n analyze_logs\n)\n\n# ---------------------------------------------------\n\nPROJECT_DIR = os.path.dirname(os.path.abspath(__file__))\nDATA_DIR = os.path.join(PROJECT_DIR, 'data')\nLOGS_PATH = os.path.join(DATA_DIR, 'log_small.txt')\n\n# ---------------------------------------------------\n\nif __name__ == '__main__':\n # load logs as dataframe\n df_logs = load_logs(LOGS_PATH)\n\n # analyze logs\n analyze_logs(df_logs)\n" } ]	3
buffos/aind_projects	https://github.com/buffos/aind_projects	fa89c39a6b459e85275c405367b5f00546f98e2e	19099c0899f95ba8a134bf169438004f70e745b9	1c935d7d2e2b4244e937834230594598fcb55f58	refs/heads/master	2021-01-21T19:51:43.325364	2017-07-15T08:43:21	2017-07-15T08:43:21	92,168,423	2	0	null	null	null	null	null	[ { "alpha_fraction": 0.5919166803359985, "alphanum_fraction": 0.6083101630210876, "avg_line_length": 33.639286041259766, "blob_id": "cd18ce611df784a8bb1b9c1a21544b7028a349ab", "content_id": "e5c1f3c01e87b18037b5e42c86d91ed5927dde57", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 9699, "license_type": "no_license", "max_line_length": 119, "num_lines": 280, "path": "/prj01.aind.sudoku/solution.py", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "from collections import Counter\n\nassignments = []\n\n\ndef assign_value(values, box, value, action_type):\n # type: (dict, list, str, int) -> dict\n\n \"\"\"\n Please use this function to update your values dictionary!\n Assigns a value to a given box. If it updates the board record it.\n \"\"\"\n\n # Don't waste memory appending actions that don't actually change any values\n\n global eliminate_counter, only_choice_counter, naked_twins_counter\n\n if values[box] == value:\n return values\n\n if action_type == 0:\n eliminate_counter += 1\n elif action_type == 1:\n only_choice_counter += 1\n elif action_type == 2:\n naked_twins_counter += 1\n\n values[box] = value\n if len(value) == 1:\n assignments.append(values.copy())\n return values\n\n\ndef cross(a, b):\n # type: (str, str) -> list\n \"\"\" Cross product of elements in a and elements in b.\"\"\"\n return [s + t for s in a for t in b]\n\n\ndef grid_values(grid):\n # type: (str) -> dict\n \"\"\"\n Convert grid into a dict of {square: char} with '123456789' for empties.\n\n Args:\n grid: Sudoku grid in string form, 81 characters long\n Returns:\n Sudoku grid in dictionary form:\n - keys: Box labels, e.g. 'A1'\n - values: Value in corresponding box, e.g. '8', or '123456789' if it is empty.\n \"\"\"\n global boxes\n\n assert len(grid) == 81, \"Input grid must be a string of length 81 (9x9)\"\n values = []\n all_digits = '123456789'\n for c in grid:\n if c == '.':\n values.append(all_digits)\n elif c in all_digits:\n values.append(c)\n assert len(values) == 81\n return dict(zip(boxes, values))\n\n\ndef display(values):\n # type: (dict) -> None\n \"\"\"\n Display the values as a 2-D grid.\n Args:\n values(dict): The sudoku in dictionary form\n \"\"\"\n global rows, cols\n\n width = 0\n if values:\n width = 1 + max(len(values[s]) for s in boxes)\n line = '+'.join(['-' * (width * 3)] * 3)\n for r in rows:\n print(''.join(values[r + c].center(width) + ('\|' if c in '36' else '')\n for c in cols))\n if r in 'CF':\n print(line)\n\n\ndef eliminate(values):\n # type: (dict) -> dict\n\n \"\"\"\n Eliminate values from peers of each box with a single value.\n\n Go through all the boxes, and whenever there is a box with a single value,\n eliminate this value from the set of values of all its peers.\n\n Args:\n values: Sudoku in dictionary form.\n Returns:\n Resulting Sudoku in dictionary form after eliminating values.\n \"\"\"\n global peers\n\n solved_values = [box for box in values.keys() if len(values[box]) == 1]\n for box in solved_values:\n digit = values[box]\n for peer in peers[box]: # for all the relevant boxes remove that digit from the available digit string\n assign_value(values, peer, values[peer].replace(digit, ''), action_type=0)\n # values[peer] = values[peer].replace(digit, '')\n return values\n\n\ndef only_choice(values):\n # type: (dict) -> dict\n \"\"\"\n Finalize all values that are the only choice for a unit.\n\n Go through all the units, and whenever there is a unit with a value\n that only fits in one box, assign the value to this box.\n\n Input: Sudoku in dictionary form.\n Output: Resulting Sudoku in dictionary form after filling in only choices.\n \"\"\"\n global unit_list\n for unit in unit_list:\n for digit in '123456789':\n d_places = [box for box in unit if digit in values[box]]\n if len(d_places) == 1:\n assign_value(values, d_places[0], digit, action_type=1)\n # values[d_places[0]] = digit\n return values\n\n\ndef naked_twins(values):\n # type: (dict) -> dict\n \"\"\"Eliminate values using the naked twins strategy.\n Args:\n values(dict): a dictionary of the form {'box_name': '123456789', ...}\n\n Returns:\n the values dictionary with the naked twins eliminated from peers.\n \"\"\"\n\n # Find all instances of naked twins\n # Eliminate the naked twins as possibilities for their peers\n for unit in unit_list:\n # use counter to count the multiplicity of eligible numbers\n # if multiplicity == 2 and the length of the eligible strings == 2 then its a twin\n twins = [possible_values for possible_values, times_occurred in Counter([values[box] for box in unit]).items()\n if times_occurred == 2 and len(possible_values) == 2]\n if len(twins) > 0:\n for t in twins:\n for u in unit:\n if values[u] != t: # for all boxes in the unit except the twins\n # eliminate the first digit of twins from all unit peers\n assign_value(values, u, values[u].replace(t[0], ''), action_type=2)\n # eliminate the second digit of twins from all unit peers\n assign_value(values, u, values[u].replace(t[1], ''), action_type=2)\n\n return values\n\n\ndef reduce_puzzle(values):\n # type: (dict) -> dict or bool\n \"\"\"\n Iterate eliminate() and only_choice(). If at some point, there is a box with no available values, return False.\n If the sudoku is solved, return the sudoku.\n If after an iteration of both functions, the sudoku remains the same, return the sudoku.\n Input: A sudoku in dictionary form.\n Output: The resulting sudoku in dictionary form.\n \"\"\"\n stalled = False\n while not stalled:\n # Check how many boxes have a determined value\n solved_values_before = len([box for box in values.keys() if len(values[box]) == 1])\n # Use the Eliminate Strategy\n values = eliminate(values)\n # Use the Only Choice Strategy\n values = only_choice(values)\n # Use the naked twins strategy\n values = naked_twins(values)\n # Check how many boxes have a determined value, to compare\n solved_values_after = len([box for box in values.keys() if len(values[box]) == 1])\n # If no new values were added, stop the loop.\n stalled = solved_values_before == solved_values_after\n # Sanity check, return False if there is a box with zero available values:\n if len([box for box in values.keys() if len(values[box]) == 0]):\n # print(\"Error: Sudoku cannot be solved\")\n return False\n return values\n\n\ndef search(values):\n # type: (dict) -> dict or bool\n \"\"\" Using depth-first search and propagation, try all possible values.\"\"\"\n\n # First, reduce the puzzle using the previous function\n global search_counter\n search_counter += 1\n values = reduce_puzzle(values)\n if values is False:\n return False # Failed earlier\n if all(len(values[s]) == 1 for s in boxes):\n return values # Solved!\n # Choose one of the unfilled squares with the fewest possibilities\n n, s = min((len(values[s]), s) for s in boxes if len(values[s]) > 1)\n # n is the number of possibilities and s is the square we will split on\n # Now use recurrence to solve each one of the resulting sudokus, and\n for value in values[s]:\n new_sudoku = values.copy()\n new_sudoku[s] = value\n attempt = search(new_sudoku)\n if attempt:\n return attempt\n\n\ndef solve(grid):\n # type: (str, bool) -> dict or bool\n \"\"\"\n Find the solution to a Sudoku grid.\n Args:\n grid(string): a string representing a sudoku grid.\n Example: '2.............62....1....7...6..8...3...9...7...6..4...4....8....52.............3'\n Returns:\n The dictionary representation of the final sudoku grid. False if no solution exists.\n \"\"\"\n sudoku = grid_values(grid)\n solution = search(sudoku)\n\n if type(solution) == bool:\n print(\"The sudoku cannot be solved\")\n return solution\n\n\ndef init(is_diagonal=True):\n global row_units, column_units, square_units, rows, cols\n all_units = row_units + column_units + square_units\n\n if is_diagonal:\n # for diagonal sudoku\n diagonal_1 = [rows[i] + cols[i] for i in range(9)]\n diagonal_2 = [rows[i] + cols[8 - i] for i in range(9)]\n diagonal_units = [diagonal_1, diagonal_2]\n all_units += diagonal_units # diagonals are also regions of search\n\n t_units = dict((s, [u for u in all_units if s in u]) for s in boxes)\n t_peers = dict((s, set(sum(t_units[s], [])) - {s}) for s in boxes) # all the relevant boxes for each box\n\n return all_units, t_units, t_peers\n\n\nrows = 'ABCDEFGHI'\ncols = '123456789'\nboxes = cross(rows, cols)\nrow_units = [cross(r, cols) for r in rows]\ncolumn_units = [cross(rows, c) for c in cols]\nsquare_units = [cross(rs, cs) for rs in ('ABC', 'DEF', 'GHI') for cs in ('123', '456', '789')]\n\nunit_list, units, peers = init(is_diagonal=True)\nsearch_counter = 0\neliminate_counter = 0\nonly_choice_counter = 0\nnaked_twins_counter = 0\n\nif __name__ == '__main__':\n diagonal_sudoku_grid = '2.............62....1....7...6..8...3...9...7...6..4...4....8....52.............3'\n display(solve(diagonal_sudoku_grid))\n print('Statistics: ------------------')\n print('Elimination used: {0} times'.format(eliminate_counter))\n print('Only Choice used: {0} times'.format(only_choice_counter))\n print('Naked Twins used: {0} times'.format(naked_twins_counter))\n print('Search used: {0} times'.format(search_counter))\n\n try:\n from visualize import visualize_assignments\n\n visualize_assignments(assignments)\n\n except SystemExit:\n pass\n except:\n print('We could not visualize your board due to a pygame issue. Not a problem! It is not a requirement.')\n" }, { "alpha_fraction": 0.7399871945381165, "alphanum_fraction": 0.7431861758232117, "avg_line_length": 74.14423370361328, "blob_id": "45f552b6eccc79dccf9839b36a14ac0f00044b2e", "content_id": "ba9acf613802e4d914d1ef78102628bc281e69d6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 7816, "license_type": "no_license", "max_line_length": 532, "num_lines": 104, "path": "/prj02.aind.isolation/docs/research_review_complete.md", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "## Introduction\n\nThis is a short review of \"Game Tree Searching by Min/Max approximation\" by Ron Rivest\n\n## Selecting the paper to review\n\nBeing an avid chess player for 30+ years and having witness the evolution of computer chess since the early 80's till now, I rejected the Deep Blue paper, since what it brought to the table for computer chess was just publicity. There are many more interesting chess engines that really played a role in chess programming history, among them Fruit chess engine by Fabien Letouzey or Crafty by Robert Hyatt.\nOn the other hand , the selected paper, addresses a problem that is really interesting and is certainly not closed.\n\n## Key question\n\nThe main question the paper resolves around is: \n \n Given a partial game tree E, how do you select which node you should \"extend\" \n\nIn the classical alpha beta pruning search with iterative deepening we do follow an \"expand all\" strategy from `depth d` to `depth d+1`. The question is `can we do better` and selectively expand node and if yes, `is it efficient`?\n\nThis is the main subject of the paper. There is also one more issue that arises in the discussion of the paper that will be addressed at the end.\n\n## Formulation\n\nA big part of the paper is focused in the precise formulation of the tree, the partial tree, the definition of the evaluation function etc...\nThe key parts of the paper are\n\n- Every leaf node has an evaluation, from a static evaluation function\n- Every parent has an evaluation that is either a min or a max of its children\n- the evaluation function is strictly positive. For that we may need to add a constant to the initial evaluation function, if it gives positive values for player 1 and negative for player 2\n- for every edge, connecting the parent and the child we attach a weight.\n- for every parent , we attach as information the index of the best child and call that an arrow\n- since we are dealing with partial game trees (full game trees will have all the information provided) the paper calls the terminal nodes of the partial tree tip nodes\n- we are interested on which tip node to expand next\n- for every node we define A(c) as the set of all ancestors of c\n- We are discussing acyclic game trees (no cycles - no transpositions)\n- We introduce the notion of a penalty to every node π(c)\n- The penalty of the tip nodes is zero\n- the penalty of every parent node is the penalty of its best child + the weight of the edge that connect it\n- we can also attach another \"penalty\" p(c) to every tip node, that is the sum of weights w of all of its ancestors\n- we select to expand the tip node with the least penalty\n\n## Selecting the weighting function\n\n- We want to expand that tip node that the root is most \"sensitive\" to its change (this is formulated mathematically in the paper)\n- in the context of min and max functions we are using, its obvious that we would always select the tip node that is the end of the principal variation , that is we follow from the root the best move, and we will always expand the best move.\n- to avoid that, we use a generalized notion of the min and max functions, borrowed from L<sup>p</sup> spaces\n- we define a generalized mean for every p as follows : \n\n <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;M^p_a&space;=&space;\\bigg(\\frac{1}{n}&space;&space;\\sum&space;a_i^p\\bigg)^{1/p}\" title=\"generalized mean\" />\n\n- if we let p go to +inf then what we get is the maximum function\n- if we let p go to -inf then what we get is the minimum function\n- the benefit of this formulation is that we can now have continuous approximations of the min an max functions and this calculate derivatives\n- the partial derivate of the new function M on one of its components is:\n\n <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;\\frac{\\partial&space;M^p_a}{\\partial&space;a_i}&space;=&space;\\frac{1}{n}&space;\\bigg(\\frac&space;{a_i}{M^p_a}\\bigg)^{p-1}\" title=\"partial derivatives\"/>\n\n- if we take the derivative of the max function computed on a 'father' node (denoted as f(c)) against one of its children we have\n\n [spell-off]: <> (cSpell:disable)\n\n <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;\\frac{\\partial&space;M^p(f(c))}{\\partial&space;c}&space;=&space;\\frac{1}{n}&space;\\bigg(\\frac&space;{eval(c)}{M^p(f(c)))}\\bigg)^{p-1}&space;=&space;\\frac{1}{n}&space;\\bigg(\\frac&space;{eval(c)}{eval(d)}\\bigg)^{p-1}\" title=\"\\frac{\\partial M^p(f(c))}{\\partial c} = \\frac{1}{n} \\bigg(\\frac {eval(c)}{M^p(f(c)))}\\bigg)^{p-1} = \\frac{1}{n} \\bigg(\\frac {eval(c)}{eval(d)}\\bigg)^{p-1}\" />\n\n [spell-on]: <> (cSpell:enable)\n\n where d is the sibling of c with the best evaluation\n\n- if we take logs we have\n\n [spell-off]: # (cSpell:disable)\n\n - <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;-&space;[log(1/n)&space;+&space;(p-1)log(eval(c))&space;-&space;log(eval(d))]\" title=\"- [log(1/n) + (p-1)log(eval(c)) - log(eval(d))]\" />\n \n [spell-on]: # (cSpell:enable)\n\n - this last expression quantizes how much a change in node c will affect the parent f(c)\n\n - this the negative* of this exact expression we set at the weight w(c) and attach it to the edge from f(c) to c\n\n - n in this equation is the number of siblings of c\n\n- using the chain rule we can propagate the influence of every tip node to the root (does it remind you of back propagation....??)\n\n- because we took the negative of the derivative and we want the biggest influence , we are searching for the tip node with the least penalty (defined above as the sum of weight of the path leading to c)\n\n- choosing a large value of p, thus approximating the max function will result in selecting the \"best\" moves to expand , small values of p, will result in a wider tree and more nodes expanding.\n\n## Remarks\n\n- The above approach is good not only if we want to find the best move, but if we are interested in actually evaluate the position, which in our case means create a graph that evaluates the most important positions.\n- It is a very good approach for creating an \"opening book\"\n\nActually this approach has been implemented in a chess program called Aquarium, in a internal function called IDeA (Interactive Deep Analysis), which I had a pleasure of being an alpha tester and contributing to ideas and code.\n\nThe basic idea of the program is to create a persistent chess graph, which is expanded automatically (and interactively by user assistance). The program , as in the paper\n \n - uses an static evaluator for every node (an external chess engine that returns an evaluation for the position)\n - uses evaluation >0 (internally the evaluations are shifted so the evaluations are always > 0)\n - the evaluations are minimaxed to the root(s) of the graph\n - the graph, contrary to the paper contains cycles (transpositions), which makes bottom up minimaxing challenging (I am actually very proud of solving that problem)\n - in the program , contrary to the paper, not every move to a position expanded is added to the tree (this is actually a highly debatable decision)\n - it also uses a parameter , like p in the program, to decide on which nodes to expand or not.\n\nIn my experience as a chess player at GM level at correspondence chess , this selection algorithm is very helpful when exploring the truth of a position in a complex game without time limitations, but is also as good as its static evaluator. Especially positions with sacrifices, where an early evaluation is bad (fail low) will get low priority to expand, so it might be useful to add more intelligent weight functions, depending on the game (for example in chess when there is a king attack, a pawn march, multiple exchanges).\n\nMaybe adding weights based on patterns analyzed by Neural Networks would also help\n" }, { "alpha_fraction": 0.5172219276428223, "alphanum_fraction": 0.5855448842048645, "avg_line_length": 29.534482955932617, "blob_id": "ef83e10d97d317b3e3fd8285a95cbfa01ad4f2f6", "content_id": "403934a0d7b9abd55f1cd6985b626b43b4aeaef4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1771, "license_type": "no_license", "max_line_length": 113, "num_lines": 58, "path": "/prj02.aind.isolation/los.py", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "\"\"\"Calculating the Likelihood of superiority from the match result of 2 engines\"\"\"\n\nimport sys\nimport math\n\n\ndef erf(x):\n \"\"\"\n Calculating the error function for python.\n From https://stackoverflow.com/questions/457408/is-there-an-easily-available-implementation-of-erf-for-python\n :param x: \n :return: \n \"\"\"\n # save the sign of x\n sign = 1 if x >= 0 else -1\n x = abs(x)\n\n # constants\n a1 = 0.254829592\n a2 = -0.284496736\n a3 = 1.421413741\n a4 = -1.453152027\n a5 = 1.061405429\n p = 0.3275911\n\n # A&S formula 7.1.26\n t = 1.0 / (1.0 + p * x)\n y = 1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * math.exp(-x * x)\n return sign * y # erf(-x) = -erf(x)\n\n\ndef calculate_performance(wins_, draws_, losses_):\n # from https://chessprogramming.wikispaces.com/Match+Statistics\n games_ = wins_ + losses_ + draws_\n winning_fraction_ = (wins_ + 0.5 * draws_) / games_\n elo_difference_ = - math.log(1.0 / winning_fraction_ - 1.0) * 400.0 / math.log(10.0)\n los_ = .5 + .5 * erf((wins_ - losses_) / math.sqrt(2.0 * (wins_ + losses_)))\n return games_, winning_fraction_, elo_difference_, los_\n\n\nif __name__ == \"__main__\":\n wins, draws, losses = 515, 0, 485\n\n if len(sys.argv) == 4:\n wins = sys.argv[1]\n losses = sys.argv[2]\n draws = sys.argv[3]\n elif len(sys.argv) == 1:\n pass\n else:\n print(\"Wrong number of arguments (wins, losses, draws)\")\n exit(1)\n\n games, winning_fraction, elo_difference, los = calculate_performance(wins, draws, losses)\n print(\"Number of games: \", games)\n print(\"Winning fraction: \", winning_fraction)\n print(\"Elo difference: \", elo_difference)\n print(\"Likelihood of Superiority: {} %\".format( los * 100))\n" }, { "alpha_fraction": 0.6844660043716431, "alphanum_fraction": 0.7022653818130493, "avg_line_length": 25.869565963745117, "blob_id": "0e732709ec42438f4a16f97f0642a8d58ca5c42c", "content_id": "bc440c097913773cb5ed151ac4582391c972e6eb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 618, "license_type": "no_license", "max_line_length": 73, "num_lines": 23, "path": "/prj02.aind.isolation/match.py", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "\"\"\"\nPlay a match between player A and player B\n\"\"\"\n\nimport random\nfrom isolation import Board\nfrom collections import namedtuple\n\nTIME_LIMIT = 150\n\nAgent = namedtuple(\"Agent\", [\"player\", \"name\"])\n\n# TODO: 1. change player.get_move() to return pv.line , depth, score time\n# TODO: 2. change back minimax and alpha beta to their original form.\n# TODO: 3. provide better feedback from get_move() . think....\n# TODO: 4. write quiescence search\n\n\ndef play_game(agent_1, agent_2):\n game = Board(agent_1, agent_2)\n # initialise with random move\n move = random.choice(game.get_legal_moves())\n game.apply_move(move)\n" }, { "alpha_fraction": 0.5351133346557617, "alphanum_fraction": 0.5900431275367737, "avg_line_length": 42.32530212402344, "blob_id": "09846002a0e30570bb204b14ee1a9e9da4cbc500", "content_id": "8a3fe5d57148317e7e03ef0c360a00154bfbdc44", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 7191, "license_type": "no_license", "max_line_length": 311, "num_lines": 166, "path": "/prj02.aind.isolation/docs/heuristic_analysis.md", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "## Heuristics Overview\n\nWhile exploring the new to me Isolation game, I tried various heuristics as evaluation functions.\nSince I am quite familiar with Chess and Computer Chess, although evaluation functions are important in Chess\nthey are not so important as standalone functions. Their most important role is guiding search, initiating extensions or pruning\n\nFor evaluation the influence of the various evaluations functions I tested, I used the provided tournament.py\n\nAt first I played two round robin tournaments covering all considered heuristics\n\n\n## Tournament Tables for the heuristics used\n\n\n</BR></BR>\n#### table 1:\n---\n\|Match\|Opponent\|AB_Improved\|Combined_1\|Combined_2\|Combined_3\|\n\|---\|---\|---\|---\|---\|---\|\n\n\| \| \|Won \|Lost\|Won \| Lost\| Won \| Lost\| Won \| Lost\|\n\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| 1 \| Random \|37 \| 3 \| 36 \| 4 \| 36 \| 4 \| 35 \| 5\|\n\| 2 \| MM_Open \|29 \| 11 \| 34 \| 6 \| 35 \| 5 \| 31 \| 9\|\n\| 3 \| MM_Center \|36 \| 4 \| 31 \| 9 \| 34 \| 6 \| 36 \| 4\|\n\| 4 \| MM_Improved \|31 \| 9 \| 29 \| 11 \| 30 \| 10 \| 26 \| 14\|\n\| 5 \| AB_Open \|19 \| 21 \| 19 \| 21 \| 16 \| 24 \| 22 \| 18\|\n\| 6 \| AB_Center \|29 \| 11 \| 23 \| 17 \| 23 \| 17 \| 24 \| 16\|\n\| 7 \| AB_Improved \|20 \| 20 \| 22 \| 18 \| 17 \| 23 \| 15 \| 25\|\n\| \| Win Rate \| 71.8%\| \|69.3% \| \| 68.2%\| \| 67.5% \| \|\n\n\n</BR></BR>\n\n\n#### table 2:\n---\n\|Match\|Opponent\|AB_Improved\|Distance\|Combined_4\|Common Moves\|\n\|---\|---\|---\|---\|---\|---\|\n\n\| \| \|Won \|Lost\|Won \| Lost\| Won \| Lost\| Won \| Lost\|\n\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| 1 \| Random \|37 \| 3 \| 36 \| 4 \| 39 \| 1 \| 33 \| 7 \|\n\| 2 \| MM_Open \|29 \| 11 \| 28 \| 12 \| 32 \| 8 \| 27 \| 13 \|\n\| 3 \| MM_Center \|36 \| 4 \| 34 \| 6 \| 36 \| 4 \| 32 \| 8 \|\n\| 4 \| MM_Improved \|27 \| 13 \| 29 \| 11 \| 26 \| 14 \| 22 \| 18 \|\n\| 5 \| AB_Open \|23 \| 17 \| 22 \| 18 \| 17 \| 23 \| 15 \| 25 \|\n\| 6 \| AB_Center \| 20 \| 20 \| 20 \| 20 \| 19 \| 21 \| 20 \| 20 \|\n\| 7 \| AB_Improved \| 16 \| 24 \| 21 \| 19 \| 20 \| 20 \| 18 \| 18 \|\n\| \| Win Rate \| 67.1%\| \|67.9% \| \| 67.5%\| \| 59.8% \| \|\n\n\n### Statistical Significance of Results.\n\nTo make any valid assumptions about the effectiveness of the heuristics, one should play a lot of games, because as one can see, even self playing can result in results far away from the expected 50%\n\nThis is a very common situation in evaluating chess engines and one can read more [here](https://chessprogramming.wikispaces.com/Match+Statistics)\n\nTo do that evaluation I implemented the function mentioned in the link to evaluate if there is any significance in the results (you can find the function in los.py in the repository)\n\nOf course for any meaningful results much longer matches should be played.\nFor this reason I created 2 tournament matches 1000 games long each , to get some meaningful results for the heuristics.\n\n#### match 1:\n---\n\|Match\|Opponent\|Combined_1\|Combined_2\|Combined_3\|Combined_4\|\n\|---\|---\|---\|---\|---\|---\|\n\n\|......... \|.....................\|Won\| Lost\| Won \| Lost\| Won \| Lost\| Won \| Lost\|\n\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| 1 \| AB_Improved \|503 \| 497 \| 504 \| 496 \| 516 \| 484 \| 0 \| 0 \|\n\n\n#### match 2:\n---\n\|Match\|Opponent\|Inv_Distance\|Distance\|Open_move\|Common Moves\|\n\|---\|---\|---\|---\|---\|---\|\n\n\|......... \|.....................\|Won\| Lost\| Won \| Lost\| Won \| Lost\|Won \| Lost\|\n\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\n\| 1 \| AB_Improved \|461 \|539 \| 0 \| 0 \| 476 \| 524 \| 0 \| 0 \|\n\n\n\n## Heuristics Reference and performance analysis\n\n1. Open move score: Number of legal moves available for the player.\n \n - Performance: fast and simple\n - ELO Difference:-16.69\n - Likelihood of Superiority: 6.45%\n\n2. Mobility: The difference between number of own legal moves - opponent legal moves. This is also used in the tournament.py by the AB_Improved agent\n\n - Performance: fast and simple. This is the ID_improved heuristic\n - ELO Difference: 0 \n - Likelihood of Superiority: 0\n\n3. Common Moves: This simple heuristic gives a higher score to positions where both players have squares they can both go. It counts the common squares and give that as a score for the position\n\n - Performance: slightly slower\n - ELO Difference: -61.79\n - Likelihood of Superiority: 1.30%\n\n4. Distance: This returns the distance between the two players in the board. Trying to stay as far away from the opponent as possible\n\n - Performance: fast and simple\n - ELO Difference: -13.20\n - Likelihood of Superiority: 11.47%\n\n5. Inverse Distance: This returns the 1/distance between the two players in the board. Trying to stay as close to the opponent as possible\n\n - Performance: fast and simple\n - ELO Difference: -27.155\n - Likelihood of Superiority: 0.68%\n\n6. Combined_1: A linear combination of (1), (2) and (3). \n\n - Performance: slightly slower\n - ELO Difference: 2.08\n - Likelihood of Superiority: 57.52%\n\n7. Combined_2: This heuristic gives (number of legal moves)^2 - number of opponent legal moves, when the board is more than half full (that means Its more important to have open moves when the board is full)\nand (number of legal moves) - (number of opponent legal move)^2 when the board is not , which means I care more about restricting the opponent in the early stages. This gives a slight improvement over AB_Improved and it can be more fine tuned\n\n - Performance: much slower than ID_improved\n - ELO Difference: 2.08\n - Likelihood of Superiority: 57.52%\n\n8. Combined_3: Expanding on the previous idea this returns:\n\n\n if moves_to_board >= 0.8: # closer to endgame (most squares are occupied\n return float(len(own_moves) * 4 - len(opponent_moves))\n elif 0.4 <= moves_to_board < 0.8:\n return float(len(own_moves) * 2 - len(opponent_moves))\n else:\n return float(len(own_moves) - len(opponent_moves) * 2)\n which does not change much compare to the previous heuristic\n\n\n - Performance: much slower than ID_improved\n - ELO Difference: 11.12\n - Likelihood of Superiority: 84.42%\n\n9. Combined_4: This was just a crazy idea as a shot in the dark. In short it calculates the following:\n\n score = float(own_moves 2 / (1 + opp_moves)) + float(own_moves / (1 + opp_moves 2))\n\n - Performance: fast and simple\n - ELO Difference: 10.42\n - Likelihood of Superiority: 82.86 %\n\n</BR></BR>\n\n\n\n\n\n### Summary\n\nThe results are summarized in the following graph\n\n![chart](./img/chart.png)\n\nBased on the above analysis, the heuristic of choice (based on those shallow depth matches) is combined_4 because its 10 ELO points better than the base heuristic and computationally as expensive as the base (involves the same calls to finding the legal moves of both sides) and as easy to implement" }, { "alpha_fraction": 0.6716417670249939, "alphanum_fraction": 0.6723880767822266, "avg_line_length": 29.454545974731445, "blob_id": "ee9a2df67b8c27c1aa464d01d1b2c36f10fafebf", "content_id": "9128187162d0b1626e05ab6ff8fe9d2e0e1ab76d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1340, "license_type": "no_license", "max_line_length": 73, "num_lines": 44, "path": "/prj02.aind.isolation/heuristics.py", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "\"\"\"Heuristics for the Isolation game\"\"\"\n\n\ndef mobility(game, player):\n \"\"\"\n \n :param isolation.Board game: \n :param IsolationPlayer player: \n :return: float\n \"\"\"\n own_moves = len(game.get_legal_moves(player))\n opponent_moves = len(game.get_legal_moves(game.get_opponent(player)))\n return float(own_moves - opponent_moves)\n\n\ndef mobility_scaled(game, player):\n \"\"\"\n\n :param isolation.Board game: \n :param IsolationPlayer player: \n :return: float\n \"\"\"\n max_number_of_moves = 8\n own_moves = len(game.get_legal_moves(player))\n opponent_moves = len(game.get_legal_moves(game.get_opponent(player)))\n available_empty_squares = len(game.get_blank_spaces())\n board_size = game.height * game.width\n # scaling_factor = board_size / available_empty_squares\n scaling_factor = max_number_of_moves / own_moves\n # the less the empty squares the more important the available moves\n return float(own_moves - opponent_moves) * scaling_factor\n\n\ndef common_moves(game, player):\n \"\"\"\n\n :param isolation.Board game: \n :param IsolationPlayer player: \n :return: float\n \"\"\"\n own_moves = game.get_legal_moves(player)\n opponent_moves = game.get_legal_moves(game.get_opponent(player))\n same_moves = list(set(own_moves) & set(opponent_moves))\n return float(len(same_moves))\n" }, { "alpha_fraction": 0.640759289264679, "alphanum_fraction": 0.6597421169281006, "avg_line_length": 36.72972869873047, "blob_id": "43510e9a07af9106e992898ef041d1a2de6f8b25", "content_id": "4d3f1dedc0141854082c8793b3a1fa7bf01e0825", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2792, "license_type": "no_license", "max_line_length": 114, "num_lines": 74, "path": "/prj03.aind.planning/understand_classes.py", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "from aimacode.utils import expr, Expr\nfrom lp_utils import FluentState, encode_state, decode_state\nfrom aimacode.logic import PropKB\nfrom my_air_cargo_problems import AirCargoProblem\n\nex1 = expr('At(C1, SFO)') # type: Expr\nprint(\"ex1 is of type: \", type(ex1))\nprint(\"it has 3 members. an op '{}' args {} and the hash {}\".format(ex1.op, ex1.args, ex1.__hash__()))\n\n# lets see problem 1 definitions\ncargos = ['C1', 'C2']\nplanes = ['P1', 'P2']\nairports = ['JFK', 'SFO']\n\npos = [expr('At(C1, SFO)'),\n expr('At(C2, JFK)'),\n expr('At(P1, SFO)'),\n expr('At(P2, JFK)'),\n ]\nneg = [expr('At(C2, SFO)'),\n expr('In(C2, P1)'),\n expr('In(C2, P2)'),\n expr('At(C1, JFK)'),\n expr('In(C1, P1)'),\n expr('In(C1, P2)'),\n expr('At(P1, JFK)'),\n expr('At(P2, SFO)'),\n ]\ninit = FluentState(pos, neg)\ngoal = [expr('At(C1, JFK)'),\n expr('At(C2, SFO)'),\n ]\n\n# lets see the FluentState object\n# it has 2 main functions\nprint(init.sentence())\n# that will print all predicates as a sentence like\n# (At(C1, SFO) & At(C2, JFK) & At(P1, SFO) & At(P2, JFK) & ~At(C2, SFO) & ~In(C2, P1) & ~In(C2, P2) & ~At(C1, JFK)\n# & ~In(C1, P1) & ~In(C1, P2) & ~At(P1, JFK) & ~At(P2, SFO))\n# and\nprint(init.pos_sentence())\n# that omits the negation predicates\n\n# initial state of the AirCargoProblem would be\nstate_map = init.pos + init.neg # all predicates\ninitial_state_TF = encode_state(init, state_map) # their mapped state (True or False)\nprint(\"The initial state of the Air Cargo Problem would be\", state_map)\nprint(\"The initial_TF state of the Air Cargo Problem would be\", initial_state_TF)\n# decoding a state requires giving first the truth state of the predicates and then the predicates\n# it returns a FluentObject and can extract a sentence with the sentence member function\n\n# it creates a propositional logic statement\n# based on the truth or false of the predicate\nprint(decode_state('FT', ['At(C1, SFO)', 'At(C2, SFO)']).sentence())\n\nkb = PropKB()\n# this simply extracts the sentence to atomic clauses\nkb.tell(decode_state('FT', ['At(C1, SFO)', 'At(C2, SFO)']).sentence())\nprint(kb.clauses)\n\n# Now explore the AirCargoProblem\nac = AirCargoProblem(cargos, planes, airports, init, goal)\n\nfrom aimacode.planning import Action\naction = ac.actions_list[1] # type: Action\nprint('The action has an operator <{}> , arguments {}'.format(action.name, action.args))\nprint('has positive {} and negative {} preconditions'.format(action.precond_pos, action.precond_neg))\nprint('also has additive {} and removing {} effects'.format(action.effect_add, action.effect_rem))\n\nkb = PropKB()\nkb.tell(decode_state(initial_state_TF, pos+neg).sentence())\nprint(\"kb before action: \", kb.clauses)\naction(kb, action.args)\nprint(\"kb after action: \", kb.clauses)\n" }, { "alpha_fraction": 0.708132803440094, "alphanum_fraction": 0.7122232913970947, "avg_line_length": 61.969696044921875, "blob_id": "bfd8e25a30d4b4cf555fe15ba263b672b0c209aa", "content_id": "bd8904c191b12fb5dc9b02e1df70f1eb96edcec8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 4156, "license_type": "no_license", "max_line_length": 448, "num_lines": 66, "path": "/prj02.aind.isolation/docs/research_review.md", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "## Introduction\n\nThis is a short review of \"Game Tree Searching by Min/Max approximation\" by Ron Rivest\n\n## Key question\n\nThe main question the paper resolves around is: ` Given a partial game tree E, how do you select which node you should \"extend\" `\n\nIn the classical alpha beta pruning search with iterative deepening we do follow an \"expand all\" strategy from `depth d` to `depth d+1`. The question is `can we do better` and selectively expand node and if yes, `is it efficient`?\n\nThis is the main subject of the paper. There is also one more issue that arises in the discussion of the paper that will be addressed at the end.\n\n## Formulation\n\nA big part of the paper is focused in the precise formulation of the tree, the partial tree, the definition of the evaluation function etc...\n\n- The basic idea is we want to find which leaf nodes to extend\n- for that reason we assign to every edge (from parent to child) a weighting factor\n- At every leaf node we can sum the penalties leading from the root to that node.\n- The leaf node with the least penalty is the one to be extended\n\n## Selecting the weighting function\n\n- We want to expand that tip node that the root is most \"sensitive\" to its change\n- if we used as w(c) = \|eval(c) - best(parent(c))\| then we we always expand along the principal variation because it will always have a zero penalty.\n- to avoid that, we use a generalized notion of the min and max functions, borrowed from L<sup>p</sup> spaces\n- we define a generalized mean for every p as follows : \n\n <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;M^p_a&space;=&space;\\bigg(\\frac{1}{n}&space;&space;\\sum&space;a_i^p\\bigg)^{1/p}\" title=\"generalized mean\" />\n\n- if we let p go to +inf then what we get is the maximum function and if we let p go to -inf then what we get is the minimum function. The benefit of this formulation is that we can now have continuous approximations of the min an max functions and this calculate derivatives\n- the partial derivate of the new function M on one of its components is:\n\n <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;\\frac{\\partial&space;M^p_a}{\\partial&space;a_i}&space;=&space;\\frac{1}{n}&space;\\bigg(\\frac&space;{a_i}{M^p_a}\\bigg)^{p-1}\" title=\"partial derivatives\"/>\n\n- if we take the derivative of the max function computed on a 'father' node (denoted as f(c)) against one of its children we have (where d is the sibling of c with the best evaluation)\n\n [spell-off]: <> (cSpell:disable)\n\n <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;\\frac{\\partial&space;M^p(f(c))}{\\partial&space;c}&space;=&space;\\frac{1}{n}&space;\\bigg(\\frac&space;{eval(c)}{M^p(f(c)))}\\bigg)^{p-1}&space;=&space;\\frac{1}{n}&space;\\bigg(\\frac&space;{eval(c)}{eval(d)}\\bigg)^{p-1}\" title=\"\\frac{\\partial M^p(f(c))}{\\partial c} = \\frac{1}{n} \\bigg(\\frac {eval(c)}{M^p(f(c)))}\\bigg)^{p-1} = \\frac{1}{n} \\bigg(\\frac {eval(c)}{eval(d)}\\bigg)^{p-1}\" />\n\n [spell-on]: <> (cSpell:enable)\n\n- if we take logs we have\n\n [spell-off]: # (cSpell:disable)\n\n - <img src=\"https://latex.codecogs.com/png.latex?\\bg_white&space;-&space;[log(1/n)&space;+&space;(p-1)log(eval(c))&space;-&space;log(eval(d))]\" title=\"- [log(1/n) + (p-1)log(eval(c)) - log(eval(d))]\" />\n \n [spell-on]: # (cSpell:enable)\n\n - this last expression quantizes how much a change in node c will affect the parent f(c)\n\n - the negative* of this exact expression we set at the weight w(c) and attach it to the edge from f(c) to c. N in this equation is the number of siblings of c\n\n- because we took the negative of the derivative and we want the biggest influence , we are searching for the tip node with the least penalty (defined above as the sum of weight of the path leading to c)\n\n- choosing a large value of p, thus approximating the max function will result in selecting the \"best\" moves to expand , small values of p, will result in a wider tree and more nodes expanding.\n\n## Remarks\n\n- The strategy was tested in the game \"Connect Four\". \n\nThe results are that\n - it takes fewer steps to get to a better results\n - it takes more time to get to that better result.\n" }, { "alpha_fraction": 0.7871939539909363, "alphanum_fraction": 0.7956685423851013, "avg_line_length": 47.318180084228516, "blob_id": "3f228afb608ebac1e731fff452cd9d5a439340ec", "content_id": "7195f78e9d8b9de7fe40bd65594e852eba8585a4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1062, "license_type": "no_license", "max_line_length": 143, "num_lines": 22, "path": "/README.md", "repo_name": "buffos/aind_projects", "src_encoding": "UTF-8", "text": "# aind_projects\nprojects for Udacity's AI nanodegree\n\n\n### Project 1: [Diagonal Sudoku Solver](https://github.com/buffos/aind_projects/tree/master/prj01.aind.sudoku)\n\nThe basic goal of the project is to get the student acquainted with the\nbasic idea of the course and introduce to the concepts of search and\nconstraint satisfaction\n\n### Project 2: [Build a game playing agent for the game of Isolation](https://github.com/buffos/aind_projects/tree/master/prj02.aind.isolation)\n\nIn this project we are concentrated on adversarial search and basically\nin Minimax , Alpha-Beta algorithms and Iterative Deepening. Also we see\nimportant it is to create a good heuristic.\n\n### Project 3: [Classical Planning](https://github.com/buffos/aind_projects/tree/master/prj03.aind.planning)\n\nThe goal of the project is to understand the formulation of Planning problems\nin the language of PDDL, understand forward and backward State Space Search.\nWe are also create a planning graph, the basis of GRAPHPLAN, and extract a heuristic\nto help is in the forward state space search." } ]	9
Formator/django-rest-auth	https://github.com/Formator/django-rest-auth	fa4cf4debae5bb241fee9d63eedcc97bfe57575e	f849708b90fae37d46cbdefd0cdc085d6a84351a	f06e829bea6740d02aab000c95046468e4fc32e0	refs/heads/master	2021-07-08T02:16:56.461200	2021-01-20T08:13:07	2021-01-20T08:13:07	226,867,075	0	0	MIT	2019-12-09T12:33:46	2020-05-25T13:40:05	2021-01-20T08:13:08	Python	[ { "alpha_fraction": 0.7367724776268005, "alphanum_fraction": 0.738095223903656, "avg_line_length": 31.869565963745117, "blob_id": "e9b30ae6faff0e56ac9c78e9d05b0d797f454c17", "content_id": "7fb8939250dbb48a56be3bae250ee1e729c61033", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 756, "license_type": "permissive", "max_line_length": 74, "num_lines": 23, "path": "/rest_auth/utils.py", "repo_name": "Formator/django-rest-auth", "src_encoding": "UTF-8", "text": "from six import string_types\nfrom importlib import import_module\nfrom rest_framework_simplejwt.serializers import TokenObtainPairSerializer\nfrom rest_framework_simplejwt.views import TokenObtainPairView\n\n\ndef import_callable(path_or_callable):\n if hasattr(path_or_callable, '__call__'):\n return path_or_callable\n else:\n assert isinstance(path_or_callable, string_types)\n package, attr = path_or_callable.rsplit('.', 1)\n return getattr(import_module(package), attr)\n\n\ndef default_create_token(token_model, user, serializer):\n token, _ = token_model.objects.get_or_create(user=user)\n return token\n\n\ndef jwt_encode(user):\n refresh = TokenObtainPairSerializer.get_token(user)\n return refresh.access_token, refresh\n" } ]	1
LucasManza/computer-vision_manzanelli-brieu	https://github.com/LucasManza/computer-vision_manzanelli-brieu	2549a320c13420a05829bca07c60085447116d51	71b9d5849b8476ce63619c7158299cf24c6181af	8b744aac7a93bf018d5b57413620a4c6959a1a5a	refs/heads/master	2021-03-19T05:24:20.405947	2020-04-17T18:29:46	2020-04-17T18:29:46	247,136,292	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.6802030205726624, "alphanum_fraction": 0.7010152339935303, "avg_line_length": 31.83333396911621, "blob_id": "e4fb1f9c39cf2b0fcba7ef5f259f21b9dfcd9089", "content_id": "5f5f400d4194abcc0f4b20468df2fc9e8161e3ce", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1974, "license_type": "no_license", "max_line_length": 105, "num_lines": 60, "path": "/src/practice/morphological/morphological-exercise-1.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\nimport numpy as np\n\n\n# todo Ejercicios con la cámara, en tiempo real, mostrando siempre en una ventana la imagen de la cámara.\n# Requiere imágenes binarias, que se pueden obtener por thresholding.\n# 1) Dilatar una imagen binaria, controlar el tamaño del elemento estructural con un trackbar, de 1 a 50\n\n# Generate binary image.\ndef generate_binary_image(image, threshold: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n ret, binary = cv2.threshold(gray_frame, threshold, 255, cv2.THRESH_BINARY)\n\n return binary\n\n\n# SHOW dilation image by using Ellipsis structure. Args must be de binary image and structure size\ndef show_dilation_image(binary_img, structure_size):\n dilatation_structure = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (structure_size, structure_size))\n dilatation_img = cv2.morphologyEx(binary_img, cv2.MORPH_DILATE, dilatation_structure)\n cv2.imshow('dilation image', dilatation_img)\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n cap = cv2.VideoCapture(0)\n\n threshold = 127\n dilation_struct_size = 1\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", threshold, 255, nothing)\n cv2.createTrackbar(\"Dilatation Structure Size\", \"Window\", dilation_struct_size, 50, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n dilation_struct_size = cv2.getTrackbarPos(\"Dilatation Structure Size\", \"Window\")\n dilation_struct_size = 1 if dilation_struct_size < 2 else dilation_struct_size\n\n # Display the resulting frame\n cv2.imshow('frame', frame)\n\n bin_img = generate_binary_image(frame, threshold)\n\n show_dilation_image(bin_img, dilation_struct_size)\n\n # When everything done, release the capture\n cap.release()\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.5858310461044312, "alphanum_fraction": 0.6103542447090149, "avg_line_length": 27.973684310913086, "blob_id": "bc1cfa45c55a929e01ea2dc3179e79e6d1c403a0", "content_id": "0cbf29c4d94f16d4f713115ade082913655548c8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1101, "license_type": "no_license", "max_line_length": 77, "num_lines": 38, "path": "/src/practice/moments/start_analyze/generate_img_dataset.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import imutils\nimport cv2\nimport random\n\n\ndef __cut_roi_img__(frame, size: int):\n height = frame.shape[0]\n width = frame.shape[1]\n min_height: int = int(height / 2 - size)\n max_height: int = int(height / 2 + size)\n min_width: int = int(width / 2 - size)\n max_width: int = int(width / 2 + size)\n roi = frame[min_height:max_height, min_width:max_width]\n cv2.imshow('', roi)\n return roi\n\n\ndef __resize_image__(image, fx, fy):\n return cv2.resize(image, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC)\n\n\ndef __rotate_image__(image, angle):\n return imutils.rotate(image, angle)\n\n\ndef generate_dataset(image, img_target: str):\n for i in range(1, 10):\n aux_image = __rotate_image__(image, random.randint(0, 360))\n # aux_image = __resize_image__(image, 100, 50)\n src_naming = img_target + str(i) + '.png'\n cv2.imwrite(src_naming, aux_image)\n\n\nif __name__ == '__main__':\n star_img = cv2.imread('../../../assets/star-image.png')\n cv2.imshow('', star_img)\n# target: str = '../../../assets/dataset/start/'\n# generate_dataset(star_img, target)\n" }, { "alpha_fraction": 0.6246992945671082, "alphanum_fraction": 0.6543704867362976, "avg_line_length": 23.940000534057617, "blob_id": "99365d3d6f7872fd3af5c787a5a25eaad2ac585f", "content_id": "ec018c0aa52678efba108c8736935097becde587", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1248, "license_type": "no_license", "max_line_length": 86, "num_lines": 50, "path": "/src/practice/threshold/threshold-exercise-1.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "# todo 1) Generar una imagen binaria normal y\n# otra invertida sobre la cámara, controlando el umbral con una barra deslizante\n\n\nimport cv2\n\n\n# Show normal, binary and binary inverted images.\ndef show_binary_images(image, threshold: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n ret, binary = cv2.threshold(gray_frame, threshold, 255, cv2.THRESH_BINARY)\n ret, binary_inv = cv2.threshold(gray_frame, threshold, 255, cv2.THRESH_BINARY_INV)\n\n cv2.imshow('original', gray_frame)\n cv2.imshow('binary', binary)\n cv2.imshow('binary_inv', binary_inv)\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n cap = cv2.VideoCapture(0)\n\n threshold = 127\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", 127, 255, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n print(threshold)\n\n # Display the resulting frame\n cv2.imshow('frame', frame)\n\n show_binary_images(frame, threshold)\n\n # When everything done, release the capture\n cap.release()\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6204878091812134, "alphanum_fraction": 0.6458536386489868, "avg_line_length": 25.28205108642578, "blob_id": "edd3c3fcd3927200dfa330cda7a69d2c16fa7bb8", "content_id": "c54be8c108d22a0a18ca3aa5c42bbcc876f23f47", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1025, "license_type": "no_license", "max_line_length": 91, "num_lines": 39, "path": "/src/practice/connected-components/connected-components-ex2.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\nimport numpy as np\n\n\ndef apply_color_map(img):\n img_color_map = cv2.applyColorMap(img, cv2.COLORMAP_JET)\n cv2.imshow('component', img_color_map)\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n origin_img = cv2.imread('../../assets/numbers.png')\n threshold = 127\n dilation_struct_size = 1\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", threshold, 255, nothing)\n cv2.createTrackbar(\"Erode Structure Size\", \"Window\", dilation_struct_size, 50, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n dilation_struct_size = cv2.getTrackbarPos(\"Erode Structure Size\", \"Window\")\n dilation_struct_size = 1 if dilation_struct_size < 2 else dilation_struct_size\n\n # Display the resulting frame\n cv2.imshow('Ants', origin_img)\n\n apply_color_map(origin_img)\n\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6972049474716187, "alphanum_fraction": 0.7260869741439819, "avg_line_length": 32.9052619934082, "blob_id": "7cf257fbf94d6d173714723765696a8936468ef7", "content_id": "8077c3b4be4f0b1ec814609c45e7d3f83e4f1e3f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3222, "license_type": "no_license", "max_line_length": 136, "num_lines": 95, "path": "/src/project_forms_detections/form_detections/Proyecto_detector_de_formas.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "#import section\nimport cv2 as cv\nimport numpy as np\n\n#Variables section\nblockSizeMaxGauss=150\n\nmax_elem = 2#Max number of diferent types of elements for morphologic operations\nmax_kernel_size = 50\n\ntitle_trackbar_kernel_size1 = 'Opening Kernel size:\\n 2n +1'\ntitle_trackbar_kernel_size2 = 'Closing Kernel size:\\n 2n +1'\ntitle_opening_window = 'Opening'\ntitle_closing_window = 'Closing'\ntitle_trackbar_kernel_type = 'Element:\\n 0: Rect \\n 1: Cross \\n 2: Ellipse'\n\n#Webcam init\ncap=cv.VideoCapture(0)\nret, frame=cap.read()\nimage = frame\n\n#Primer paso: Convertir la imagen a monocromáticaq\ndef convGray(img):\n return(cv.cvtColor(img, cv.COLOR_BGR2GRAY))\n \n#Segundo paso: Aplicar un threshold con umbral ajustable con una barra de desplazamiento\ndef Gauss(val,img=image):\n gray = convGray(img)\n th2 = cv.adaptiveThreshold(gray,255,cv.ADAPTIVE_THRESH_GAUSSIAN_C,cv.THRESH_BINARY,val,0)\n cv.imshow('Gauss', th2)\n return(th2)\n \ncv.namedWindow('Gauss')\ncv.createTrackbar('Trackbar', 'Gauss', 3, blockSizeMaxGauss, Gauss)\n\nGauss(3,image)\ncv.waitKey()\nP2=Gauss(cv.getTrackbarPos('Trackbar', 'Gauss'),image)\n \n#Tercero paso: Aplicar operaciones morfológicas para eliminar ruido de la imagen\ndef opening(val,img=P2):\n kernel_size1 = cv.getTrackbarPos(title_trackbar_kernel_size1, title_opening_window)\n kernel_type1 = 0\n \n #Opening type selection\n val_type1 = cv.getTrackbarPos(title_trackbar_kernel_type, title_opening_window)\n if val_type1 == 0:\n kernel_type1 = cv.MORPH_RECT\n elif val_type1 == 1:\n kernel_type1 = cv.MORPH_CROSS\n elif val_type1 == 2:\n kernel_type1 = cv.MORPH_ELLIPSE\n \n kernel1=cv.getStructuringElement(kernel_type1, (2kernel_size1 + 1, 2kernel_size1+1), (kernel_size1, kernel_size1))#Opening Element\n result=cv.morphologyEx(img, cv.MORPH_OPEN, kernel1)#Opening\n cv.imshow(title_opening_window, result)\n return(result)\n\ncv.namedWindow(title_opening_window)\ncv.createTrackbar(title_trackbar_kernel_type, title_opening_window , 0, max_elem, opening)\ncv.createTrackbar(title_trackbar_kernel_size1, title_opening_window , 0, max_kernel_size, opening)\n\nopening(0,P2)\ncv.waitKey()\nopeningP3=opening(0,P2)\n\ndef closing(val,img=openingP3):\n kernel_size2 = cv.getTrackbarPos(title_trackbar_kernel_size2, title_closing_window)\n kernel_type2 = 0\n \n #Closing type selection\n val_type2 = cv.getTrackbarPos(title_trackbar_kernel_type, title_closing_window)\n if val_type2 == 0:\n kernel_type2 = cv.MORPH_RECT\n elif val_type2 == 1:\n kernel_type2 = cv.MORPH_CROSS\n elif val_type2 == 2:\n kernel_type2 = cv.MORPH_ELLIPSE\n \n kernel2=cv.getStructuringElement(kernel_type2, (2kernel_size2 + 1, 2kernel_size2+1), (kernel_size2, kernel_size2))#Closing Element\n result=cv.morphologyEx(img, cv.MORPH_CLOSE, kernel2)#Closing\n cv.imshow(title_closing_window, result)\n return(result)\n\ncv.namedWindow(title_closing_window)\ncv.createTrackbar(title_trackbar_kernel_type, title_closing_window , 0, max_elem, closing)\ncv.createTrackbar(title_trackbar_kernel_size2, title_closing_window , 0, max_kernel_size, closing)\n\nclosing(0,openingP3)\n\n\n#Quit\ncv.waitKey()\ncap.release()\ncv.destroyAllWindows()" }, { "alpha_fraction": 0.6487568020820618, "alphanum_fraction": 0.6770505905151367, "avg_line_length": 34.70408248901367, "blob_id": "89f8fb09989117b8b84c7ebf2a4b74feefdbab54", "content_id": "6d0d3bcd597d373c0094747b28505191cee100b3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3504, "license_type": "no_license", "max_line_length": 239, "num_lines": 98, "path": "/src/practice/connected-components/connected-components-ex3.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\nimport numpy as np\n\n\n# todo\n# Ejercicios con la cámara, en tiempo real, mostrando siempre en una ventana la imagen de la cámara. Requiere imágenes binarias sin ruido, que se pueden obtener por thresholding y operaciones morfológicas con sus respectivos trackbars.\n# 1)Aplicar componentes conectados a la imagen binaria de la cámara, y visualizarla coloreando con un color diferente cada grupo, usando colorMap\n\ndef generate_binary_image(image, threshold: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n ret, binary = cv2.threshold(gray_frame, threshold, 255, cv2.THRESH_BINARY)\n\n return binary\n\n\ndef reduce_noise(binary_img, structure_size):\n structure = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (structure_size, structure_size))\n open_result = cv2.morphologyEx(binary_img, cv2.MORPH_OPEN, structure)\n closed_result = cv2.morphologyEx(binary_img, cv2.MORPH_CLOSE, structure)\n\n return closed_result\n\n\ndef show_connected_components(binary_image):\n num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(binary_image)\n binaryImageClone = np.copy(labels)\n\n # Find the max and min pixel values and their locations\n (minValue, maxValue, minPosition, maxPosition) = cv2.minMaxLoc(binaryImageClone)\n\n # normalize the image so that the min value is 0 and max value is 255\n binaryImageClone = 255 * (binaryImageClone - minValue) / (maxValue - minValue)\n\n # convert image to 8bits unsigned type\n binaryImageClone = np.uint8(binaryImageClone)\n\n # Apply a color map\n img_color_map = cv2.applyColorMap(binaryImageClone, cv2.COLORMAP_JET)\n\n red_color = (0, 0, 255)\n blue_color = (255, 0, 0)\n\n # print(stats[labels[2], cv2.CC_STAT_AREA][0])\n # print(centroids[labels[2]][0])\n\n for label in labels:\n ### Get area from a matrix of same value\n pixels = stats[label, cv2.CC_STAT_AREA][0]\n print(pixels)\n ### Exercise condition request\n if 100 < pixels < 10000:\n ### Get centroid from a matrix of same value\n centroid = centroids[label][0]\n top_left_point = (int(centroid[0] - 100), int(centroid[1] + 100))\n bottom_right_point = (int(centroid[0] + 100), int(centroid[1] - 100))\n img_color_map = cv2.rectangle(img_color_map, top_left_point, bottom_right_point, red_color, 2)\n\n cv2.imshow('component', img_color_map)\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n cap = cv2.VideoCapture(0)\n # origin_img = cv2.imread('../../assets/numbers.png')\n threshold = 127\n dilation_struct_size = 1\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", threshold, 255, nothing)\n cv2.createTrackbar(\"Erode Structure Size\", \"Window\", dilation_struct_size, 50, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n dilation_struct_size = cv2.getTrackbarPos(\"Erode Structure Size\", \"Window\")\n dilation_struct_size = 1 if dilation_struct_size < 2 else dilation_struct_size\n\n # Display the resulting frame\n cv2.imshow('Img', frame)\n\n bin_img = generate_binary_image(frame, threshold)\n\n bin_img = reduce_noise(bin_img, dilation_struct_size)\n cv2.imshow('Binary Image', bin_img)\n\n show_connected_components(bin_img)\n\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6842286586761475, "alphanum_fraction": 0.7042011022567749, "avg_line_length": 33.987953186035156, "blob_id": "2ca07397585bc81164c44b9de399e81171879dd7", "content_id": "0e55bb02176c7120512a31edd16deb22e98b6664", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2909, "license_type": "no_license", "max_line_length": 239, "num_lines": 83, "path": "/src/practice/connected-components/connected-components-ex1.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\nimport numpy as np\n\n\n# todo\n# Ejercicios con la cámara, en tiempo real, mostrando siempre en una ventana la imagen de la cámara. Requiere imágenes binarias sin ruido, que se pueden obtener por thresholding y operaciones morfológicas con sus respectivos trackbars.\n# 1)Aplicar componentes conectados a la imagen binaria de la cámara, y visualizarla coloreando con un color diferente cada grupo, usando colorMap\n\ndef generate_binary_image(image, threshold: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n ret, binary = cv2.threshold(gray_frame, threshold, 255, cv2.THRESH_BINARY_INV)\n\n return binary\n\n\ndef reduce_noise(binary_img, structure_size):\n structure = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (structure_size, structure_size))\n open_result = cv2.morphologyEx(binary_img, cv2.MORPH_OPEN, structure)\n closed_result = cv2.morphologyEx(binary_img, cv2.MORPH_CLOSE, structure)\n\n return closed_result\n\n\ndef show_connected_components(binary_image):\n # num_labels, labels = cv2.connectedComponents(binary_image)\n # img_int = np.uint8(labels)\n #\n # color_map_img = cv2.applyColorMap(img_int, cv2.COLORMAP_HSV)\n # cv2.imshow('component', color_map_img)\n\n num_labels, labels = cv2.connectedComponents(binary_image)\n binaryImageClone = np.copy(labels)\n\n # Find the max and min pixel values and their locations\n (minValue, maxValue, minPosition, maxPosition) = cv2.minMaxLoc(binaryImageClone)\n\n # normalize the image so that the min value is 0 and max value is 255\n binaryImageClone = 255 * (binaryImageClone - minValue) / (maxValue - minValue)\n\n # convert image to 8bits unsigned type\n binaryImageClone = np.uint8(binaryImageClone)\n\n # Apply a color map\n img_color_map = cv2.applyColorMap(binaryImageClone, cv2.COLORMAP_JET)\n cv2.imshow('component', img_color_map)\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n origin_img = cv2.imread('../../assets/numbers.png')\n threshold = 127\n dilation_struct_size = 1\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", threshold, 255, nothing)\n cv2.createTrackbar(\"Erode Structure Size\", \"Window\", dilation_struct_size, 50, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n dilation_struct_size = cv2.getTrackbarPos(\"Erode Structure Size\", \"Window\")\n dilation_struct_size = 1 if dilation_struct_size < 2 else dilation_struct_size\n\n # Display the resulting frame\n cv2.imshow('Img', origin_img)\n\n bin_img = generate_binary_image(origin_img, threshold)\n\n bin_img = reduce_noise(bin_img, dilation_struct_size)\n cv2.imshow('Binary Image', bin_img)\n\n show_connected_components(bin_img)\n\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.552480936050415, "alphanum_fraction": 0.569656491279602, "avg_line_length": 24.560976028442383, "blob_id": "0e3f4f8d19a75f29a24f561ed06887cdefd48fdd", "content_id": "0341c7045e60c96fd24f93ebd9bc703677938322", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1048, "license_type": "no_license", "max_line_length": 94, "num_lines": 41, "path": "/src/practice/moments/start_analyze/show_star_hus.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import practice.moments.start_analyze.hu_img_analyze as hu_analyze\nimport cv2\n\nstar_src: str = '../../../assets/star-image.png'\nstar_dataset: [str] = [\n '../../../assets/dataset/star/1.png',\n '../../../assets/dataset/star/2.png',\n '../../../assets/dataset/star/3.png',\n '../../../assets/dataset/star/4.png',\n '../../../assets/dataset/star/5.png',\n '../../../assets/dataset/star/6.png',\n '../../../assets/dataset/star/7.png',\n '../../../assets/dataset/star/8.png',\n '../../../assets/dataset/star/9.png',\n]\n\n\ndef __next_img__(index: int) -> str:\n if index > 9:\n return star_src\n else:\n return star_dataset[index - 1]\n\n\ndef __nothing__(x):\n pass\n\n\nif __name__ == '__main__':\n invert_bin_img: bool = False\n threshold = 127\n dilation_struct_size = 1\n\n frame = cv2.imread(star_src)\n\n dataset = [frame]\n for img_src in star_dataset:\n f = cv2.imread(img_src)\n dataset.append(f)\n\n hu_analyze.compare_images_hu(dataset, '', invert_bin_img, threshold, dilation_struct_size)\n" }, { "alpha_fraction": 0.5940539240837097, "alphanum_fraction": 0.6315643191337585, "avg_line_length": 28.74380111694336, "blob_id": "100b525271e625c67cbfa11132727844eb7d1233", "content_id": "bd48721539f0dc18f828be6d8b16df194f743272", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3599, "license_type": "no_license", "max_line_length": 94, "num_lines": 121, "path": "/src/practice/moments/moments_ex2.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\nimport math\n\nred_color = (0, 0, 255)\nblue_color = (255, 0, 0)\ngreen_color = (0, 255, 0)\n\n\ndef show_text(original_img, labels: list):\n font = cv2.FONT_HERSHEY_SIMPLEX\n offset = 35\n x, y = 50, 50\n for idx, label in enumerate(labels):\n cv2.putText(original_img, label, (x, y + offset * idx), font,\n 0.5, green_color, 2, cv2.LINE_AA)\n\n\ndef generate_binary_image(image, threshold: int, invert: bool):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n tresh_code = cv2.THRESH_BINARY if not invert else cv2.THRESH_BINARY_INV\n ret, binary = cv2.threshold(gray_frame, threshold, 255, tresh_code)\n\n return binary\n\n\ndef reduce_noise(binary_img, structure_size):\n structure = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (structure_size, structure_size))\n open_img = cv2.morphologyEx(binary_img, cv2.MORPH_OPEN, structure)\n result = cv2.morphologyEx(open_img, cv2.MORPH_CLOSE, structure)\n return result\n\n\ndef draw_contours_img(original_img, contours):\n cv2.drawContours(original_img, contours, -1, red_color, 2)\n\n\n# Apply a rectangle detection by contours, instead of drawing the contour per se.\ndef draw_contours_by_bounding_react(img, contours):\n img_result = img\n for cont in contours:\n x, y, w, h = cv2.boundingRect(cont)\n cv2.rectangle(img, (x, y), (x + w, y + h), green_color, 2)\n return img_result\n\n\ndef find_contours(binary_img):\n contours, _ = cv2.findContours(binary_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n return contours\n\n\ndef show_moments_data(binary_img, original_img):\n moments = cv2.moments(binary_img)\n print(moments)\n\n m00 = moments['m00']\n m10 = moments['m10']\n m01 = moments['m01']\n m11 = moments['m11']\n mu20 = moments['mu20']\n nu20 = moments['nu20']\n show_text(original_img, [\n 'M00: ' + str(m00),\n 'M11: ' + str(m11),\n 'M20: ' + str(mu20),\n 'NU20: ' + str(nu20),\n ])\n\n if m00 != 0:\n x, y = (m10 / m00, m01 / m00)\n radius = math.sqrt(m00)\n cv2.circle(original_img, (int(x), int(y)), int(radius), green_color, 3)\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n cap = cv2.VideoCapture(0)\n\n invert_bin_img: bool = False\n threshold = 127\n dilation_struct_size = 1\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", threshold, 255, nothing)\n cv2.createTrackbar(\"Erode Structure Size\", \"Window\", dilation_struct_size, 50, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n ret, frame = cap.read()\n\n # frame = cv2.imread('../../assets/star-image.png')\n\n if cv2.waitKey(1) == ord('i'):\n invert_bin_img = not invert_bin_img\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n dilation_struct_size = cv2.getTrackbarPos(\"Erode Structure Size\", \"Window\")\n dilation_struct_size = 1 if dilation_struct_size < 2 else dilation_struct_size\n\n # The following code generate binary img, reduce noise and show binary image\n bin_img = generate_binary_image(frame, threshold, invert_bin_img)\n bin_img = reduce_noise(bin_img, dilation_struct_size)\n cv2.imshow('binary', bin_img)\n\n # Find contours\n contours = find_contours(bin_img)\n\n # Draw contours in red and show moments data\n draw_contours_img(frame, contours)\n show_moments_data(bin_img, frame)\n cv2.imshow('contours_img', frame)\n\n # When everything done, release the capture\n cap.release()\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6104956269264221, "alphanum_fraction": 0.634402334690094, "avg_line_length": 30.18181800842285, "blob_id": "65d579065269d406b828ae0647f22f997d0b7551", "content_id": "9fed20022526804d3cedee4b0cac987c170696ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1718, "license_type": "no_license", "max_line_length": 117, "num_lines": 55, "path": "/src/practice/threshold/threshold-exercise-3.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "# todo 3) Generar una imagen binaria normal sobre la cámara, usando ambos métodos de umbral adaptativo\n# , controlando el tamaño de bloque con una barra deslizante\n\n\nimport cv2\nimport numpy as np\n\n\n# Show normal, binary and binary inverted images. With automatic OTSU and triangle thresh settings.\ndef show_binary_images(image, size: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n binary_adapt_media = cv2.adaptiveThreshold(gray_frame, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,\n size, 1)\n binary_adapt_gaussian = cv2.adaptiveThreshold(gray_frame, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,\n size, 1) # size only odd values ?? what's 1?\n\n cv2.imshow('binary + media', binary_adapt_media)\n cv2.imshow('binary + gaussian', binary_adapt_gaussian)\n\n\ndef nothing(x):\n print(x)\n pass\n\n\ndef set_block_size(value):\n value = int(np.ceil(value))\n if value < 2: return 3\n return value + 1 if value % 2 == 0 else value\n\n\nif __name__ == '__main__':\n block_size = 3\n camera = cv2.VideoCapture(0)\n\n cv2.namedWindow(\"Block Size\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Block Size%\", \"Block Size\", 3, 100, nothing)\n\n while True:\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = camera.read()\n\n result = cv2.getTrackbarPos(\"Block Size%\", \"Block Size\")\n block_size = set_block_size(result)\n\n # Display the resulting frames\n show_binary_images(frame, block_size)\n\n # When everything done, release the capture\n camera.release()\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6011884212493896, "alphanum_fraction": 0.6322963833808899, "avg_line_length": 30.09782600402832, "blob_id": "337ed261affead92b21ee8f41a08ae700175c14a", "content_id": "726d259496f0cd5419f4f22690d7f3f3b3189e07", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2861, "license_type": "no_license", "max_line_length": 117, "num_lines": 92, "path": "/src/practice/threshold/threshold-exercise-4.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "# todo 4) Generar una imagen binaria con dos umbrales con inRange,\n# para segmentar un objeto por su color en el espacio HSV\n\nimport cv2\nimport numpy as np\n\nmin_hue = 0\nmin_sat = 0\nmin_value = 0\nmax_hue = 180\nmax_sat = 180\nmax_value = 255\n\n\n# Show normal, binary and binary inverted images. With automatic OTSU and triangle thresh settings.\ndef show_binary_images(image, size: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n binary_adapt_media = cv2.adaptiveThreshold(gray_frame, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,\n size, 1)\n binary_adapt_gaussian = cv2.adaptiveThreshold(gray_frame, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,\n size, 1) # size only odd values ?? what's 1?\n\n cv2.imshow('original', image)\n cv2.imshow('binary + media', binary_adapt_media)\n cv2.imshow('binary + gaussian', binary_adapt_gaussian)\n\n\ndef nothing(x):\n pass\n\n\ndef create_trackbars():\n cv2.namedWindow(\"Trackbars\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Block Size%\", \"Trackbars\", 3, 100, nothing)\n cv2.createTrackbar(\"Max. H\", \"Trackbars\", max_value, 180, nothing)\n cv2.createTrackbar(\"Max. S\", \"Trackbars\", max_sat, 255, nothing)\n cv2.createTrackbar(\"Max. V\", \"Trackbars\", max_value, 255, nothing)\n cv2.createTrackbar(\"Min. H\", \"Trackbars\", min_hue, 180, nothing)\n cv2.createTrackbar(\"Min. S\", \"Trackbars\", min_sat, 255, nothing)\n cv2.createTrackbar(\"Min. V\", \"Trackbars\", min_value, 255, nothing)\n\n\ndef get_block_size():\n block_size_result = cv2.getTrackbarPos(\"Block Size%\", \"Trackbars\")\n return odd_block_size(block_size_result)\n\n\ndef get_min_hsv():\n return (cv2.getTrackbarPos(\"Min. H\", \"Trackbars\"),\n cv2.getTrackbarPos(\"Min. S\", \"Trackbars\"),\n cv2.getTrackbarPos(\"Min. V\", \"Trackbars\"))\n\n\ndef get_max_hsv():\n return (cv2.getTrackbarPos(\"Max. H\", \"Trackbars\"),\n cv2.getTrackbarPos(\"Max. S\", \"Trackbars\"),\n cv2.getTrackbarPos(\"Max. V\", \"Trackbars\"))\n\n\ndef odd_block_size(value):\n value = int(np.ceil(value))\n if value < 2: return 3\n return value + 1 if value % 2 == 0 else value\n\n\nif __name__ == '__main__':\n camera = cv2.VideoCapture(0)\n block_size = 3\n\n create_trackbars()\n\n while True:\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = camera.read()\n\n block_size = get_block_size()\n\n hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n mask = cv2.inRange(hsv, get_min_hsv(), get_max_hsv())\n\n frame = cv2.bitwise_and(frame, frame, mask=mask)\n\n # Display the resulting frames\n show_binary_images(frame, block_size)\n\n # When everything done, release the capture\n camera.release()\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6025767922401428, "alphanum_fraction": 0.6323091983795166, "avg_line_length": 25.552631378173828, "blob_id": "fb4d533970f2d5efc83b6a92ab0b2081e62c1730", "content_id": "5dd3f84970175fdc7a6da7b722360def95233830", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1011, "license_type": "no_license", "max_line_length": 96, "num_lines": 38, "path": "/src/practice/threshold/threshold-exercise-2.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "# todo 2) Aplicar los métodos de umbral automático\n\n\nimport cv2\n\n\n# Show normal, binary and binary inverted images. With automatic OTSU thresh adjust.\ndef show_binary_images(image):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n ret, binary = cv2.threshold(gray_frame, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)\n ret, binary_inv = cv2.threshold(gray_frame, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)\n\n cv2.imshow('original + otsu', gray_frame)\n cv2.imshow('binary + otsu', binary)\n cv2.imshow('binary_inv + otsu', binary_inv)\n\n\nif __name__ == '__main__':\n cap = cv2.VideoCapture(0)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n # Display the resulting frame\n cv2.imshow('frame', frame)\n\n if cv2.waitKey(1) == ord('i'):\n show_binary_images(frame)\n\n # When everything done, release the capture\n cap.release()\n cv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.6476386189460754, "alphanum_fraction": 0.6731005907058716, "avg_line_length": 27.647058486938477, "blob_id": "0420647411ab5a7f96c03cc93670d413714ca103", "content_id": "393ff889327c52d8c53b9ec89e755ccde20c4bf4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2443, "license_type": "no_license", "max_line_length": 102, "num_lines": 85, "path": "/src/practice/template-matching/template-matching-practice.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import enum\nimport cv2\nfrom matplotlib import pyplot as plt\n\n\n# 1)Al pulsar una tecla, obtener la plantilla recortando un cuadrado de 100 x 100 píxeles\n# en el centro de la imagen y mostrarla en una ventana aparte\n# 2) Aplicar matchTemplate con la plantilla sobre la imagen de la cámara y mostrar la imagen generada.\n# Usar teclas para cambiar el método.\n# 3) Buscar la posición del macheo con minMaxLoc() y\n# dibujar un recuadro de 100 x 100 sobre la imagen original, señalando la detección\n# 4) Repetir usando dos plantillas sobre la cámara, recuadrando la detección con diferente color\n\ndef cut_roi_img(frame, size: int):\n height = frame.shape[0]\n width = frame.shape[1]\n min_height: int = int(height / 2 - size)\n max_height: int = int(height / 2 + size)\n min_width: int = int(width / 2 - size)\n max_width: int = int(width / 2 + size)\n roi = frame[min_height:max_height, min_width:max_width]\n cv2.imshow('', roi)\n return roi\n\n\nred_color = (0, 0, 255)\nblue_color = (255, 0, 0)\n\n\nclass TemplateMethods:\n SQ_DIFF = 'cv2.TM_SQDIFF_NORMED'\n CORR = 'cv2.TM_CCORR_NORMED'\n\n\ndef matching_template(image, template, method: str):\n res = cv2.matchTemplate(image, template, eval(method))\n min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)\n color = red_color\n top_left = min_loc\n\n if method == TemplateMethods.CORR:\n color = blue_color\n top_left = max_loc\n\n bottom_right = (top_left[0] + rectangle_size, top_left[1] + rectangle_size)\n return top_left, bottom_right, color\n\n\n# EXECUTION\n\ncurrent_method: str = TemplateMethods.SQ_DIFF\nroi = None\nframe = None\nrectangle_size: int = 100\n\ncap = cv2.VideoCapture(0)\n\nwhile True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n frame = cv2.flip(frame, 1)\n\n if cv2.waitKey(1) == ord('1'):\n roi = cut_roi_img(frame, rectangle_size)\n current_method = TemplateMethods.SQ_DIFF\n\n if cv2.waitKey(1) == ord('2'):\n roi = cut_roi_img(frame, rectangle_size)\n current_method = TemplateMethods.CORR\n\n if roi is not None:\n matching_tuple = matching_template(roi, frame, current_method)\n frame = cv2.rectangle(frame, matching_tuple[0], matching_tuple[1], matching_tuple[2], 2)\n\n # Display the resulting frame\n cv2.imshow('frame', frame)\n\n# When everything done, release the capture\ncap.release()\ncv2.destroyAllWindows()\n" }, { "alpha_fraction": 0.5522388219833374, "alphanum_fraction": 0.58469557762146, "avg_line_length": 27.910959243774414, "blob_id": "f4a23cced06ade76878c7388afb864cfba06ca13", "content_id": "f00dd26c492e92d5b42fefd6e588a25cb8e8b776", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4221, "license_type": "no_license", "max_line_length": 94, "num_lines": 146, "path": "/src/practice/moments/start_analyze/hu_img_analyze.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\nimport math\n\nred_color = (0, 0, 255)\nblue_color = (255, 0, 0)\ngreen_color = (0, 255, 0)\n\n\ndef __show_text__(original_img, labels: list):\n font = cv2.FONT_HERSHEY_SIMPLEX\n offset = 35\n x, y = 50, 50\n for idx, label in enumerate(labels):\n cv2.putText(original_img, label, (x, y + offset * idx), font,\n 0.5, green_color, 2, cv2.LINE_AA)\n\n\ndef __generate_binary_image__(image, threshold: int, invert: bool):\n gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n tresh_code = cv2.THRESH_BINARY if not invert else cv2.THRESH_BINARY_INV\n ret, binary = cv2.threshold(gray_image, threshold, 255, tresh_code)\n\n return binary\n\n\ndef __reduce_noise__(binary_img, structure_size):\n structure = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (structure_size, structure_size))\n open_img = cv2.morphologyEx(binary_img, cv2.MORPH_OPEN, structure)\n result = cv2.morphologyEx(open_img, cv2.MORPH_CLOSE, structure)\n return result\n\n\ndef __draw_contours_img__(original_img, contours):\n cv2.drawContours(original_img, contours, -1, red_color, 2)\n\n\ndef __find_contours__(binary_img):\n contours, _ = cv2.findContours(binary_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n return contours\n\n\ndef __show_moments_data__(binary_img, original_img):\n moments = cv2.moments(binary_img)\n huMoments = cv2.HuMoments(moments)\n\n m00 = moments['m00']\n m10 = moments['m10']\n m01 = moments['m01']\n\n h0 = huMoments[0]\n h1 = huMoments[1]\n h2 = huMoments[2]\n h3 = huMoments[3]\n h4 = huMoments[4]\n h5 = huMoments[5]\n h6 = huMoments[6]\n\n __show_text__(original_img, [\n 'h0: ' + str(h0),\n 'h1: ' + str(h1),\n 'h2: ' + str(h2),\n 'h3: ' + str(h3),\n 'h4: ' + str(h4),\n 'h5: ' + str(h5),\n 'h6: ' + str(h6),\n ])\n\n if m00 != 0:\n x, y = (m10 / m00, m01 / m00)\n radius = math.sqrt(m00)\n cv2.circle(original_img, (int(x), int(y)), int(radius), green_color, 3)\n\n return huMoments\n\n\ndef __print_moments_data__(binary_images):\n all_hu_moments: list = []\n\n for bin_img in binary_images:\n moments = cv2.moments(bin_img)\n hu_moments = cv2.HuMoments(moments)\n all_hu_moments.append(hu_moments)\n\n print('----HO----')\n for hu_moments in all_hu_moments:\n h0 = hu_moments[0]\n print(h0)\n print('----H1----')\n for hu_moments in all_hu_moments:\n h1 = hu_moments[1]\n print(h1)\n print('----H2----')\n for hu_moments in all_hu_moments:\n h2 = hu_moments[2]\n print(h2)\n print('----H3----')\n for hu_moments in all_hu_moments:\n h3 = hu_moments[3]\n print(h3)\n print('----H4----')\n for hu_moments in all_hu_moments:\n h4 = hu_moments[4]\n print(h4)\n print('----H5----')\n for hu_moments in all_hu_moments:\n h5 = hu_moments[5]\n print(h5)\n print('----H6----')\n for hu_moments in all_hu_moments:\n h6 = hu_moments[6]\n print(h6)\n\n\ndef analyze(image,\n image_name: str,\n invert_bin_img: bool,\n threshold: int,\n dilation_struct_size):\n # The following code generate binary img, reduce noise and show binary image\n bin_img = __generate_binary_image__(image, threshold, invert_bin_img)\n bin_img = __reduce_noise__(bin_img, dilation_struct_size)\n # cv2.imshow('binary_' + image_name, bin_img)\n\n # Find contours\n contours = __find_contours__(bin_img)\n\n # Draw contours in red and show moments data\n __draw_contours_img__(image, contours)\n __show_moments_data__(bin_img, image)\n cv2.imshow('contours_img' + image_name, image)\n\n\ndef compare_images_hu(images,\n images_name: str,\n invert_bin_img: bool,\n threshold: int,\n dilation_struct_size):\n bin_images: list = []\n # The following code generate binary img, reduce noise and show binary image\n for image in images:\n bin_img = __generate_binary_image__(image, threshold, invert_bin_img)\n bin_img = __reduce_noise__(bin_img, dilation_struct_size)\n bin_images.append(bin_img)\n\n __print_moments_data__(bin_images)\n" }, { "alpha_fraction": 0.6395307779312134, "alphanum_fraction": 0.6640596985816956, "avg_line_length": 29.576086044311523, "blob_id": "afec9888cc4e68d544127cca4dd7cf5e68a507ca", "content_id": "a9fb7c83e59ff5470f2225a745172e2ffcaad9a4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2813, "license_type": "no_license", "max_line_length": 94, "num_lines": 92, "path": "/src/practice/contours/contours_ex3_boundingReact.py", "repo_name": "LucasManza/computer-vision_manzanelli-brieu", "src_encoding": "UTF-8", "text": "import cv2\n\nred_color = (0, 0, 255)\nblue_color = (255, 0, 0)\ngreen_color = (0, 255, 0)\n\n\ndef generate_binary_image(image, threshold: int):\n gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n ret, binary = cv2.threshold(gray_frame, threshold, 255, cv2.THRESH_BINARY)\n\n return binary\n\n\ndef reduce_noise(binary_img, structure_size):\n structure = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (structure_size, structure_size))\n open_img = cv2.morphologyEx(binary_img, cv2.MORPH_OPEN, structure)\n result = cv2.morphologyEx(open_img, cv2.MORPH_CLOSE, structure)\n return result\n\n\ndef draw_contours_img(original_img, contours):\n img = cv2.drawContours(original_img, contours, -1, red_color, 2)\n\n return img\n\n\n# Apply a rectangle detection by contours, instead of drawing the contour per se.\ndef draw_contours_by_bounding_react(img, contours):\n img_result = img\n for cont in contours:\n x, y, w, h = cv2.boundingRect(cont)\n cv2.rectangle(img, (x, y), (x + w, y + h), green_color, 2)\n return img_result\n\n\ndef find_contours(binary_img):\n contours, _ = cv2.findContours(binary_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n return contours\n\n\ndef nothing(x):\n pass\n\n\nif __name__ == '__main__':\n cap = cv2.VideoCapture(0)\n\n threshold = 127\n dilation_struct_size = 1\n approx_poly_dp = 1\n\n cv2.namedWindow(\"Window\", cv2.WINDOW_AUTOSIZE)\n cv2.createTrackbar(\"Threshold\", \"Window\", threshold, 255, nothing)\n cv2.createTrackbar(\"Erode Structure Size\", \"Window\", dilation_struct_size, 50, nothing)\n cv2.createTrackbar(\"AproxPolyDP\", \"Window\", approx_poly_dp, 50, nothing)\n\n while True:\n\n if cv2.waitKey(1) == ord('q'):\n break\n\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n threshold = cv2.getTrackbarPos(\"Threshold\", \"Window\")\n dilation_struct_size = cv2.getTrackbarPos(\"Erode Structure Size\", \"Window\")\n dilation_struct_size = 1 if dilation_struct_size < 2 else dilation_struct_size\n\n # Display the resulting frame\n cv2.imshow('frame', frame)\n\n # The following code generate binary img, reduce noise and show binary image\n bin_img = generate_binary_image(frame, threshold)\n bin_img = reduce_noise(bin_img, dilation_struct_size)\n cv2.imshow('binary', bin_img)\n\n # Find contours\n contours = find_contours(bin_img)\n\n # Draw contours and show them in red\n contours_img = draw_contours_img(frame, contours)\n cv2.imshow('contours_img', contours_img)\n\n # Draw contours and show them in red\n contours_img = draw_contours_by_bounding_react(contours_img, contours)\n cv2.imshow('special', contours_img)\n\n # When everything done, release the capture\n cap.release()\n cv2.destroyAllWindows()\n" } ]	15
dooblad/Shamir-Secret-Sharing	https://github.com/dooblad/Shamir-Secret-Sharing	4e932dd96754f3203923874279569ec47c986ec3	f9acc4b3ec99d38b312836ed5687a6f3c8b6109f	af00d0f50a2705fdd3f911bdefedb51f86a9e4c2	refs/heads/master	2018-01-08T23:39:38.595570	2016-01-03T00:24:21	2016-01-03T00:24:21	48,928,382	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7307692170143127, "alphanum_fraction": 0.75, "avg_line_length": 25, "blob_id": "5cac1f745d7d70b002f91ba5127e0f6e76c89ef4", "content_id": "8cc6bffd91dc004341c985350772f26f659db7a4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 52, "license_type": "no_license", "max_line_length": 37, "num_lines": 2, "path": "/README.md", "repo_name": "dooblad/Shamir-Secret-Sharing", "src_encoding": "UTF-8", "text": "# For Pokemon\n4th floor of Pokemon. Raise the roof!\n" }, { "alpha_fraction": 0.511318564414978, "alphanum_fraction": 0.5327888131141663, "avg_line_length": 25.128047943115234, "blob_id": "689832737aeb68cc8519975fb4a05ccb3cb2549c", "content_id": "3bef7ff19fff94dd143947b89121899760f622b3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4285, "license_type": "no_license", "max_line_length": 89, "num_lines": 164, "path": "/shamirs-secret-sharing.py", "repo_name": "dooblad/Shamir-Secret-Sharing", "src_encoding": "UTF-8", "text": "import sys\nimport random\n\n# Every arithmetic operation needs to be modded by this number!\n# Set it to -1 to disable modding.\nmod = 5992830235524142758386850633773258681119\n\n# Generates a random \"k\"-degree polynomial and \"n\" keys for testing the\n# reconstruction algorithm.\ndef test(k, n):\n poly = [random.randint(1, 1000) for i in range(k)]\n secret = poly[0]\n keys = []\n for i in range(1, n + 1):\n keys.append((i, evalPoly(poly, i)))\n\n print(\"Secret is: \" + str(secret))\n print(\"Algorithm produces: \" + str(int(reconstruct(random.sample(keys, k)))))\n\n# Evaluates \"poly\" at \"x\".\ndef evalPoly(poly, x):\n result = poly[0]\n i = 1\n while i < len(poly):\n result = add(result, mult(poly[i], exp(x, i)))\n i += 1\n return result\n\n# Returns the reconstructed lowest-order polynomial from the given \"points\", evaluated at\n# x = 0.\ndef reconstruct(points):\n i = 0\n bases = []\n for point in points:\n # Calculate the basis.\n poly = lagrangeBasis(i, points)\n # Multiply the polynomial by \"point.y\".\n scalarMultiply(poly, point[1])\n # Add it as one of our polynomial bases.\n bases.append(poly)\n i += 1\n\n # Add the bases together.\n resultPoly = []\n for base in bases:\n if len(resultPoly) == 0:\n resultPoly = base\n else:\n resultPoly = polyAdd(resultPoly, base)\n\n # The secret is the polynomial evaluated at 0.\n return evalPoly(resultPoly, 0)\n\n# Returns the lagrange basis polynomial for the \"i\"th point in \"points\".\ndef lagrangeBasis(i, points):\n # Use lists of coefficients where the list index corresponds to the power of x.\n polys = []\n k = len(points) - 1\n for j in range(0, k + 1):\n if i != j:\n # Setup the numerator.\n poly = []\n poly.append(-points[j][0])\n poly.append(1)\n # Divide by the denominator.\n denom = sub(points[i][0], points[j][0])\n poly[0] = div(poly[0], denom)\n poly[1] = div(poly[1], denom)\n # Add the polynomial.\n polys.append(poly)\n\n # Multiply the polynomials together.\n result = []\n for poly in polys:\n if len(result) == 0:\n result = poly\n else:\n result = polyMultiply(result, poly)\n\n return result\n\n# Multiplies \"poly\" by the scalar \"r\".\ndef scalarMultiply(poly, r):\n i = 0\n while i < len(poly):\n poly[i] = mult(poly[i], r)\n i += 1\n\n# Returns the result of adding polynomials \"a\" and \"b\" together.\ndef polyAdd(a, b):\n c = []\n for i in range(max(len(a), len(b))):\n c.append(0.0)\n if i < len(a):\n c[i] = add(c[i], a[i])\n if i < len(b):\n c[i] = add(c[i], b[i])\n return c\n\n# Returns the result of multiplying polynomials \"a\" and \"b\" together.\ndef polyMultiply(a, b):\n # Initialize the polynomial list with 0s.\n c = []\n for i in range(len(a) + len(b) - 1):\n c.append(0.0)\n\n i = 0\n while i < len(a):\n j = 0\n while j < len(b):\n # Since indices represent magnitude, we add the indices to get the index to\n # place the result in.\n c[i + j] = add(c[i + j], mult(a[i], b[j]))\n j += 1\n i += 1\n\n return c\n\n# Prints the coefficient list \"poly\" as a human-readable polynomial.\ndef printPolynomial(poly):\n i = 0\n result = \"\"\n while i < len(poly):\n if i == 0:\n result = str(poly[i])\n elif i == 1:\n result = str(poly[i]) + \"x + \" + result\n else:\n result = str(poly[i]) + \"x^\" + str(i) + \" + \" + result\n i += 1\n print(result)\n\n'''\nModded arithemetic operations as functions\n'''\ndef exp(a, b):\n if mod == -1:\n return ab\n else:\n return ((a % mod) (b % mod)) % mod\n\ndef mult(a, b):\n if mod == -1:\n return ab\n else:\n return ((a % mod) (b % mod)) % mod\n\ndef div(a, b):\n if mod == -1:\n return a / b\n else:\n return ((a % mod) / (b % mod)) % mod\n\ndef add(a, b):\n if mod == -1:\n return a + b\n else:\n return ((a % mod) + (b % mod)) % mod\n\ndef sub(a, b):\n if mod == -1:\n return a - b\n else:\n return ((a % mod) - (b % mod)) % mod\n" } ]	2
johanode/finance	https://github.com/johanode/finance	e64de49c9b9f76a00989d6e813e80eef5a777b97	6b58b4e92cb49c3f1d57f6bc5ba5975bda3ab2d1	b470d47627b92e00d6efd30f9dc703e11d48f0fa	refs/heads/main	2023-05-08T03:46:45.381311	2021-05-27T22:56:56	2021-05-27T22:56:56	367,734,367	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6863636374473572, "alphanum_fraction": 0.7034090757369995, "avg_line_length": 22.1842098236084, "blob_id": "760fc20c18f669c79c09513dfc5a54d9caaa4872", "content_id": "b659d658998d9d81da8e0662f1504c6d72058289", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 880, "license_type": "no_license", "max_line_length": 77, "num_lines": 38, "path": "/stocksymbols.py", "repo_name": "johanode/finance", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\nCreated on Sun May 16 13:19:02 2021\n\n@author: johode\n\"\"\"\nimport tkinter\nimport requests\n\n#%% Get stock sympols\n# Stock symbols from finnhub.io\n# You need to add your token at then end of requests\nr = requests.get('https://finnhub.io/api/v1/stock/sympol?exchange=ST&token=')\nticker_list = r.json()\n\n# Get list of ticker description\nOPTIONS = [x['description'] for x in ticker_list]\n\n# Create OptionMenu\nmaster = tkinter.Tk()\nvariable = tkinter.StringVar(master)\nvariable.set(OPTIONS[0]) \nw = tkinter.OptionMenu(master, variable, OPTIONS)\nw.pack()\n\nticker = {}\ndef get_selected():\n global ticker\n ticker = variable.get()\n print(\"Selected Option: {}\".format(ticker))\n master.destroy()\n return None\n \n# Create submit button\nsubmit_button = tkinter.Button(master, text='Ok', command=get_selected)\nsubmit_button.pack()\n \nmaster.mainloop()" }, { "alpha_fraction": 0.5609464049339294, "alphanum_fraction": 0.5847558975219727, "avg_line_length": 32.223880767822266, "blob_id": "3b4e71ff0c7e0fb05064c9cb4828700e8cb36516", "content_id": "a3919218bcf11b5dac7066299e8182eab39c0566", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6678, "license_type": "no_license", "max_line_length": 136, "num_lines": 201, "path": "/technicalanalysis.py", "repo_name": "johanode/finance", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\nCreated on Thu May 20 23:25:42 2021\n\n@author: johode\n\"\"\"\nimport pandas as pd\nimport numpy as np\nfrom scipy.signal import savgol_filter\nfrom sklearn.linear_model import LinearRegression\n\n#%% Functions\n\n# Normalize index\ndef normalize(x, dt=None, ref=None):\n if ref is None:\n ref = x\n \n if dt is None:\n return x/ref.iloc[0]100\n else:\n #return (x-x.last(dt).min())/(x.last(dt).max()-x.last(dt).min())\n return x/ref.last(dt).iloc[0]100\n \n \n# Simple moving average including bollinger bands \ndef sma(x, n, bands=None, center=False):\n if bands is None:\n return x.rolling(window=n, center=center).mean()\n else:\n m = x.rolling(window=n, center=center).mean()\n s = x.rolling(window=n, center=center).std()\n return m, m+2s, m-2s\n\n# Exponential moving average\ndef ema(x, n, adjust=False):\n return x.ewm(span=n, adjust=adjust).mean()\n\ndef pythag(pt1, pt2):\n a_sq = (pt2[0] - pt1[0]) * 2\n b_sq = (pt2[1] - pt1[1]) ** 2\n return np.sqrt(a_sq + b_sq)\n\ndef local_min_max(pts):\n # https://python.plainenglish.io/estimate-support-and-resistance-of-a-stock-with-python-beginner-algorithm-f1ae1508b66d\n local_min = []\n local_max = []\n prev_pts = [(0, pts[0]), (1, pts[1])]\n for i in range(1, len(pts) - 1):\n append_to = ''\n if pts[i-1] > pts[i] < pts[i+1]:\n append_to = 'min'\n elif pts[i-1] < pts[i] > pts[i+1]:\n append_to = 'max'\n if append_to:\n if local_min or local_max:\n prev_distance = pythag(prev_pts[0], prev_pts[1]) * 0.5\n curr_distance = pythag(prev_pts[1], (i, pts[i]))\n if curr_distance >= prev_distance:\n prev_pts[0] = prev_pts[1]\n prev_pts[1] = (i, pts[i])\n if append_to == 'min':\n local_min.append((i, pts[i]))\n else:\n local_max.append((i, pts[i]))\n else:\n prev_pts[0] = prev_pts[1]\n prev_pts[1] = (i, pts[i])\n if append_to == 'min':\n local_min.append((i, pts[i]))\n else:\n local_max.append((i, pts[i]))\n return local_min, local_max\n\n\n# Find local minima and maxima of smoth signal\ndef findpks(series, smooth='savgol'): \n # Smooth data\n if smooth=='savgol':\n month_diff = series.shape[0] // 30 # Integer divide the number of prices we have by 30\n if month_diff == 0: # We want a value greater than 0\n month_diff = 1\n smooth = int(2 * month_diff + 3) # Simple algo to determine smoothness\n smooth_series = pd.Series(savgol_filter(series, smooth, 3),index=series.index, name=series.name) # Get the smoothened price data\n else:\n smooth_series = series.copy()\n\n # Find local peaks\n #imin = (smooth_series.shift(1) > smooth_series) & (smooth_series.shift(-1) > smooth_series)\n #xmin = smooth_series.loc[imin]\n #imax = (smooth_series.shift(1) < smooth_series) & (smooth_series.shift(-1) < smooth_series)\n #xmax = smooth_series.loc[imax]\n local_min, local_max = local_min_max(smooth_series.values)\n imin = [pt[0] for pt in local_min]\n #xmin = [pt[1] for pt in local_min]\n imax = [pt[0] for pt in local_max]\n #xmax = [pt[1] for pt in local_max]\n \n \n return smooth_series.iloc[imin], smooth_series.iloc[imax]\n\n# Support and resistance using linear regression\ndef support_resistance(series, dt='12m', return_pks=False): \n if dt is not None:\n min_pks, max_pks = findpks(series.last(dt))\n idx = series.last(dt).index\n else:\n min_pks, max_pks = findpks(series)\n idx = series.index\n \n isdatetime = type(idx) == pd.core.indexes.datetimes.DatetimeIndex\n if isdatetime:\n t = ((idx.values-idx.values[0]).astype(np.float64)1e-9/(606024)) # Nanosecond to days\n else:\n t = idx\n # Linear regression\n model = LinearRegression()\n \n # Support / Local minima\n pts = min_pks\n if isdatetime:\n X = ((pts.index.values-pts.index.values[0]).astype(np.float64)1e-9/(606024)).reshape(-1, 1) # Nanosecond to days\n else:\n X = pts.index.values.reshape(-1,1)\n y = pts.values\n model.fit(X, y)\n local_min_slope = model.coef_[0]\n local_min_int = model.intercept_\n support = (local_min_slope * t) + local_min_int\n support_series = pd.Series(support, index=idx, name='support')\n \n # Resistance / Local maxima\n pts = max_pks\n if isdatetime:\n X = ((pts.index.values-pts.index.values[0]).astype(np.float64)1e-9/(606024)).reshape(-1, 1) # Nanosecond to days\n else:\n X = pts.index.values.reshape(-1,1)\n y = pts.values\n model.fit(X, y)\n local_max_slope = model.coef_[0]\n local_max_int = model.intercept_\n \n resistance = (local_max_slope t) + local_max_int\n resistance_series = pd.Series(resistance, index=idx, name='resistance')\n \n if return_pks:\n return support_series, resistance_series, (min_pks, max_pks)\n else:\n return support_series, resistance_series \n\n# RSI\ndef rsi(x):\n # Source: https://www.learnpythonwithrune.org/pandas-calculate-the-relative-strength-index-rsi-on-a-stock/\n \n # Difference between now-previous\n d = x.diff()\n \n # Defines Series\n U = pd.Series(np.zeros(x.shape),index=x.index)\n D = pd.Series(np.zeros(x.shape),index=x.index)\n \n # If up (today > previous)\n i = np.sign(x.diff())>0\n U.loc[i] = d.loc[i]\n \n # if down (previous > today)\n i = np.sign(x.diff())<0\n D.loc[i] = -1d.loc[i]\n \n # RS (Smooth can be changed)\n RS = ema(U,20)/ema(D,20) \n\n # Return RSI \n return 100-(100/(1+RS))\n \n\n# Identify trading points based in interactions of sma20 and sma100\ndef trading_sma(x, return_sma=False):\n # Short and long term moving average\n short = sma(x,20)\n long = sma(x,100)\n \n # identify nan values of moving average\n idx_nan = np.argwhere(np.logical_or(short.isna(),long.isna()).values).flatten()\n \n # Find interaction points\n d = short-long\n idx = np.setdiff1d(np.argwhere(np.diff(np.sign(d))).flatten(),idx_nan) \n \n if return_sma:\n return x.index[idx], short, long\n else:\n return pd.Series(np.sign(d.iloc[idx]),index=x.index[idx])\n\n\n# Identify trading points based on ema20\ndef trading_ema(x):\n trading_positions_raw = x - ema(x,20)\n #trading_positions_raw.tail()\n trading_positions = trading_positions_raw.apply(np.sign) 1/3\n return trading_positions.shift(1)\n" } ]	2
morrisignacio/CIS106-morrissenior	https://github.com/morrisignacio/CIS106-morrissenior	444ac2c6d1ac19503cabe9deb71c0f86a28bb9a6	a87886b2d0fe89544c7f6d7907eb2731d49693f7	f63d141064aca9275b30d251483f9956ddac3597	refs/heads/master	2022-09-03T00:21:58.442418	2020-05-29T15:44:18	2020-05-29T15:44:18	266,219,872	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7791361212730408, "alphanum_fraction": 0.7832111120223999, "avg_line_length": 135.22222900390625, "blob_id": "910278c34d61769e2530c71d9d4e74231e4c5016", "content_id": "e312c5039988f77561ad9014b5d0df9bc097c95a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1227, "license_type": "no_license", "max_line_length": 791, "num_lines": 9, "path": "/README.md", "repo_name": "morrisignacio/CIS106-morrissenior", "src_encoding": "UTF-8", "text": "# CIS106-morrissenior\n\n## Assignment 1\n\nI am taking this course because I am interested in learning code and becoming more self-aware with coding tools that will facilitate my journey as an engineer. I have already taken some classes in high school that cover the same material as this class. However, I pretty much forgot most of it, so I am trying to not only retrieve my knowledge but also learned something new.\n\n## Assignment 2\n\nI selected Python for my programming language. I searched in the book and the IDE that interested me the most is Python Tutor, however upon reviewing my options I am going to be selecting repl.it because it's easier for me to learn. I created a Flowgarithm that said Hello world, and I changed the code to Python and Auto Pseudocode. After this I had to make a change on the output and instead of world it displayed Hello \"name\" and by defining the string \"name\" as Morris I was able to display Hello Morris. I also did an explanation point at the end so that it could be different. I did this by having an output of \"Hello\" & name & \"!\". Finally, I changed the code by going in 'tools' and clicking the 'source code viewer' button to translate it to Python and Auto Pseudocode respectively. \n" }, { "alpha_fraction": 0.7157360315322876, "alphanum_fraction": 0.7157360315322876, "avg_line_length": 64.66666412353516, "blob_id": "d3156946f74eee7ab6c8b4af8e20221de825059f", "content_id": "c0d6cc12c547b6377da34bd4f98caccc3aae0f43", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 197, "license_type": "no_license", "max_line_length": 150, "num_lines": 3, "path": "/Assignment 2/Activity 1.py", "repo_name": "morrisignacio/CIS106-morrissenior", "src_encoding": "UTF-8", "text": "# This program displays Hello name, you can change and display any name you desire by just changing the string name and what name is going to be = to.\nname = \"Morris\"\nprint(\"Hello \" + name + \" !\")\n" } ]	2
nachiketgalande/UIHome	https://github.com/nachiketgalande/UIHome	c073157a72e0e1b7f0ee5a1c0bb9880b5df69a57	e9cf710656eaa6d99a3f7bfc3242e02e201e7767	498ddee0c6e37800f564b0f57df02fe71c096f59	refs/heads/master	2019-07-09T03:12:50.711031	2018-07-27T18:54:14	2018-07-27T18:54:14	89,877,184	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5829390287399292, "alphanum_fraction": 0.5847792029380798, "avg_line_length": 41.49720764160156, "blob_id": "22e1a73ef207f471fb7cac46a962a8f9e47f67b9", "content_id": "58b3407e24ffbcd2b1c356b4a7563b7fe827bbfd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7608, "license_type": "no_license", "max_line_length": 114, "num_lines": 179, "path": "/stg-nrtviewer.web.att.com/htdocs/model.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\nimport cgi\nfrom vertica_getter import VerticaGetter\n\nTABLE_OPEN = '<table id = LogPartsResult class=\"table table-striped table-bordered\" cellspacing=\"0\" width=\"100%\">'\nTHEAD_OPEN = '<thead>'\nTBODY_OPEN = '<tbody>'\nROW_OPEN = '<tr>'\nCOLUMN_OPEN = '<td>'\nTHEAD_ROW_OPEN = '<th>'\nTABLE_CLOSE = '</table>'\nROW_CLOSE = '</tr>'\nCOLUMN_CLOSE = '</td>'\nTHEAD_CLOSE = '</thead>'\nTBODY_CLOSE = '</tbody>'\nTHEAD_ROW_CLOSE = '</th>'\n\nclass ResultModel():\n \"\"\" A class to create model for the UI \"\"\"\n\n def __init__(self):\n \"\"\" The default constructor\"\"\"\n pass\n\n def __init__(self,start_date,recordID,param_name,context_name,param_value,aggr_flag,exact_flag):\n \"\"\" The contructor takes 2 arguments at the minimum\"\"\"\n self.start_date = start_date\n self.recordID = recordID\n self.param_name = param_name\n self.context_name = context_name\n self.param_value = param_value\n self.aggr_flag = aggr_flag\n self.exact_flag = exact_flag\n\n def get_data(self):\n \"\"\" A method to get data from Vertica based on different conditions\"\"\"\n data_obj = VerticaGetter()\n if self.context_name == 'PARTS':\n # Get aggregated result\n if self.aggr_flag == 'true':\n param_list = [self.start_date,self.param_name,self.param_value]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts_pattern_aggr(param_list)\n else:\n # Get records for a parameter matching a parameter value\n if self.param_value is not '' and self.param_name is not '':\n param_list = [self.start_date,self.param_name,self.param_value]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts_pattern_limit(param_list)\n # Get records for a parameter name on a given data, no parameter value\n if self.param_value is '' and self.param_name is not '' and self.recordID is '':\n param_list = [self.start_date,self.param_name]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts_param(param_list)\n # Get records for a single fileID/recordID when name and value are not selected\n if self.param_value is '' and self.recordID is not '':\n #param_list = [self.start_date,self.recordID]\n param_list = [self.recordID]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts(param_list)\n # Get records matching a particular pattern for parameter value\n if self.recordID is '' and self.exact_flag is 'true':\n param_list = [self.start_date,self.param_name,self.param_value]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts_pattern(param_list)\n else:\n if self.param_value == '':\n param_list = [self.start_date,self.recordID]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts(param_list)\n # Get records for a single fileID/recordID\n if self.param_name == '':\n param_list = [self.start_date,self.recordID]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts(param_list)\n if self.recordID == '':\n param_list = [self.start_date,self.param_name,self.param_value]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_log_parts_pattern(param_list)\n return res\n\n def format_default_result(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('File ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Parameter Name')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Parameter Value')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('UUID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Source')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def format_aggr_result(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Date')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Count')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Parameter Name')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Parameter Value')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Source')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def default_response(self,response_msg='A pretty minimal response'):\n \"\"\" A method to send a default response to the browser for testing purposes\"\"\"\n resp = []\n resp.append(\"Content-Type: text/plain\")\n resp.append(\"\")\n resp.append(response_msg)\n res_str = \"\\r\\n\".join(resp)\n return res_str\n\nif __name__ == '__main__':\n form = cgi.FieldStorage()\n date = form.getfirst('stDate','2017-06-10')\n recordID = form.getfirst('record','')\n param_name = form.getfirst('param','NONE')\n context_name = form.getfirst('context','PARTS')\n param_value = form.getfirst('paramVal','')\n aggr_flag = form.getfirst('aggr','false')\n exact_flag = form.getfirst('exactFlag','true')\n #result_flag = form.getfirsti('aggrFlag','NO')\n model = ResultModel(date,recordID,param_name,context_name,param_value,aggr_flag,exact_flag)\n res_list = model.get_data()\n if aggr_flag == 'true':\n html_res = model.format_aggr_result(res_list)\n else:\n html_res = model.format_default_result(res_list)\n print(model.default_response(html_res))\n\n" }, { "alpha_fraction": 0.5727182626724243, "alphanum_fraction": 0.5758100152015686, "avg_line_length": 37.67942428588867, "blob_id": "33f66b74fcc5f3c4e701f8d8bb095e3fd7cac967", "content_id": "3e9afe1c2b28ae86081c6eae9d6f53ad455ef5a9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 8086, "license_type": "no_license", "max_line_length": 118, "num_lines": 209, "path": "/stg-nrtviewer.web.att.com/htdocs/process_view.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\nimport cgi\nimport sys\n#sys.path.append('/opt/app/deap/oracle/instantclient_11_2/')\nfrom oracle_getter import OracleGetter \n\nTABLE_OPEN = '<table id = ControlTableResult class=\"table table-striped table-bordered\" cellspacing=\"0\" width=\"100%\">'\nTHEAD_OPEN = '<thead>'\nTBODY_OPEN = '<tbody>'\nROW_OPEN = '<tr>'\nCOLUMN_OPEN = '<td>'\nTHEAD_ROW_OPEN = '<th>'\nTABLE_CLOSE = '</table>'\nROW_CLOSE = '</tr>'\nCOLUMN_CLOSE = '</td>'\nTHEAD_CLOSE = '</thead>'\nTBODY_CLOSE = '</tbody>'\nTHEAD_ROW_CLOSE = '</th>'\n\nclass ProcessView():\n \"\"\" A class to create model for the UI \"\"\"\n\n def __init__(self):\n \"\"\" The default constructor\"\"\"\n pass\n\n def __init__(self,start_date,end_date,recordID,context_name,aggr_flag,timing_flag):\n \"\"\" The contructor takes 2 arguments at the minimum\"\"\"\n self.start_date = start_date\n self.end_date = end_date\n self.recordID = recordID\n self.context_name = context_name\n self.aggr_flag = aggr_flag\n self.timing_flag = timing_flag\n\n def get_data(self):\n \"\"\" A method to get data from Oracle \"\"\"\n data_obj = OracleGetter()\n if self.context_name == 'STG':\n if self.aggr_flag == 'true':\n param_list = [self.start_date,self.end_date]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_count_files_by_date(param_list)\n else:\n if self.recordID == '':\n param_list = [self.start_date]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_records_by_date(param_list)\n else:\n param_list = [self.recordID]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_single_record_by_fileID(param_list)\n else:\n if self.aggr_flag == 'true':\n param_list = [self.start_date,self.end_date]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_count_files_by_date(param_list)\n elif self.timing_flag == 'true':\n param_list = [self.start_date,self.end_date]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_records_timings_by_date(param_list)\n else:\n if self.recordID == '':\n param_list = [self.start_date]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_records_by_date(param_list)\n else:\n param_list = [self.recordID]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_single_record_by_fileID(param_list)\n return res\n\n def format_by_fileID(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('DAY ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('FILE NAME')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('FILE_ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('TOTAL RECORDS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('RECORDS LOADED - WT_LOGS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('RECORDS LOADED - WT_LOG_PARTS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def format_by_timings(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('DAY ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('FILE NAME')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('FILE ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('TIME TO PARSE IN MINS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('TIME TO LOAD IN MINS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('RECORDS LOADED - WT_LOGS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('RECORDS LOADED - WT_LOG_PARTS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n\n def format_count_files(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('DAY')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('PRODUCTION FLAG')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('FILES LOADED')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def default_response(self,response_msg='A pretty minimal response'):\n \"\"\" A method to send a default response to the browser for testing purposes\"\"\"\n resp = []\n resp.append(\"Content-Type: text/plain\")\n resp.append(\"\")\n resp.append(response_msg)\n res_str = \"\\r\\n\".join(resp)\n return res_str\n\nif __name__ == '__main__':\n form = cgi.FieldStorage()\n date = form.getfirst('stDate','20170611')\n end_date = form.getfirst('endDate','20170615')\n recordID = form.getfirst('record','')\n context_name = form.getfirst('context','PROD')\n aggr_flag = form.getfirst('aggr','STG')\n timing_flag = form.getfirst('timing','false')\n view = ProcessView(date,end_date,recordID,context_name,aggr_flag,timing_flag)\n data = view.get_data()\n if aggr_flag == 'true':\n html_res = view.format_count_files(data)\n elif timing_flag == 'true':\n html_res = view.format_by_timings(data)\n else:\n html_res = view.format_by_fileID(data)\n print(view.default_response(html_res))\n\n\n" }, { "alpha_fraction": 0.5999510288238525, "alphanum_fraction": 0.6053405404090881, "avg_line_length": 34.4782600402832, "blob_id": "d984fa41d0a1cf5c6cbf57de78178a812ea5c1d0", "content_id": "8e297e011d368b7eec94caef2c48691fd19526e4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4082, "license_type": "no_license", "max_line_length": 108, "num_lines": 115, "path": "/stg-nrtviewer.web.att.com/htdocs/tasktracker_view.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\nimport cgi\nfrom vertica_getter import VerticaGetter\n\nTABLE_OPEN = '<table id = AllTasks class=\"table table-striped table-bordered\" cellspacing=\"0\" width=\"100%\">'\nTHEAD_OPEN = '<thead>'\nTBODY_OPEN = '<tbody>'\nROW_OPEN = '<tr>'\nCOLUMN_OPEN = '<td>'\nTHEAD_ROW_OPEN = '<th>'\nTABLE_CLOSE = '</table>'\nROW_CLOSE = '</tr>'\nCOLUMN_CLOSE = '</td>'\nTHEAD_CLOSE = '</thead>'\nTBODY_CLOSE = '</tbody>'\nTHEAD_ROW_CLOSE = '</th>'\n\nclass ResultModel():\n \"\"\" A class to create model for the UI \"\"\"\n\n def __init__(self):\n \"\"\" The default constructor\"\"\"\n pass\n\n def __init__(self,start_date,end_date,attid):\n \"\"\" The contructor takes 2 arguments at the minimum\"\"\"\n self.start_date = start_date\n self.end_date = end_date\n self.attid = attid\n\n def get_data(self):\n \"\"\" A method to get data from Vertica based on different conditions\"\"\"\n data_obj = VerticaGetter()\n param_list = [self.attid]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_task_details_by_id(param_list)\n return res\n\n def format_default_result(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN) # header row open\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('ATT ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('STATUS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('SEVERITY')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('TASK DETAILS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('REMARKS')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('START DATE')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('END DATE')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('TASK FINISH DATE')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('INSERT DATE')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('INSERTED BY')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('UPDATE DATE')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('UPDATED BY')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE) # header row close\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def default_response(self,response_msg='A pretty minimal response'):\n \"\"\" A method to send a default response to the browser for testing purposes\"\"\"\n resp = []\n resp.append(\"Content-Type: text/plain\")\n resp.append(\"\")\n resp.append(response_msg)\n res_str = \"\\r\\n\".join(resp)\n return res_str\n\nif __name__ == '__main__':\n form = cgi.FieldStorage()\n date = form.getfirst('stDate','2017-06-10')\n end_date = form.getfirst('endDate','2017-06-10')\n attid = form.getfirst('attid','')\n #result_flag = form.getfirsti('aggrFlag','NO')\n model = ResultModel(date,end_date,attid)\n res_list = model.get_data()\n html_res = model.format_default_result(res_list)\n print(model.default_response(html_res))\n\n\n" }, { "alpha_fraction": 0.574072539806366, "alphanum_fraction": 0.5934102535247803, "avg_line_length": 47.58064651489258, "blob_id": "a366a87bc3ab931a4326c4e61c1af7d3ad1e2072", "content_id": "d1829f80c425b32098d703e0f8de59f2aa878852", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 12049, "license_type": "no_license", "max_line_length": 198, "num_lines": 248, "path": "/stg-nrtviewer.web.att.com/htdocs/vertica_getter.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\n\"\"\"\nA script for getting data objects from Vertica\nReferences: Vertica Python - https://github.com/uber/vertica-python\n\"\"\"\nimport vertica_python\nimport logging\n\n# Set the logging level to DEBUG\nlogging.basicConfig(level=logging.INFO)\n\nconn_info = {'host': 'stg-wavert01.bodc.att.com',\n 'port': 5433,\n #'user': 'ng2157',\n 'user': 'STG_WEBR_OPS',\n #'password': 'password',\n 'password': 'WEBR_OPS_STG',\n 'database': 'STG_EDM',\n # 10 minutes timeout on queries\n 'read_timeout': 600,\n # default throw error on invalid UTF-8 results\n 'unicode_error': 'strict',\n # SSL is disabled by default\n 'ssl': False,\n 'connection_timeout': 500}\n\n\nconn_info_task = {'host': 'stg-wavert01.bodc.att.com',\n 'port': 5433,\n #'user': 'ng2157',\n 'user': 'apptasks',\n #'password': 'password',\n 'password': 'tasksapp',\n 'database': 'STG_EDM',\n # 10 minutes timeout on queries\n 'read_timeout': 600,\n # default throw error on invalid UTF-8 results\n 'unicode_error': 'strict',\n # SSL is disabled by default\n 'ssl': False,\n 'connection_timeout': 500}\n\nclass VerticaGetter():\n \"\"\" A class to get data from Vertica\"\"\"\n TEST_QUERY=\"select Attuid from S08_DB.Alltasks\"\n\n def __init__(self):\n pass\n\n def __str__(self):\n return \" A vertica data getter for db {} on host {}\".format(conn_info['database'],conn_info['host'])\n\n def test_connection(self):\n \"\"\" A test method just to check connection to Vetica\"\"\"\n with vertica_python.connect(conn_info) as connection:\n print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(self.TEST_QUERY)\n for row in cur.iterate():\n print(\"The row is {}\".format(row))\n\n def get_log_parts_param(self,params=['2017-6-9','eVar13']):\n \"\"\" A method which returns values for a parameter name for a given date\"\"\"\n result =[]\n query_params = {'parameter_name':params[1],'et_log_date':params[0]}\n logging.debug(\"Query params : parameter_name {} and date {}\".format(params[1],params[0]))\n query = \"\"\"select a.key,b.parameter_name,b.parameter_value,a.uuid,b.source\n from wt_logs a,wt_log_parts b\n where a.key = b.key\n and a.et_log_date = b.et_log_date\n and a.et_log_date = :et_log_date\n and b.parameter_name = :parameter_name\n order by b.pt_hour_id desc limit 500\"\"\".replace('\\n',' ')\n logging.debug(\"The log parts part is {}\".format(query))\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n \n def get_log_parts(self,params=['1716057041010008656']):\n \"\"\" A method which returns all records for a log part with a single recordID \"\"\"\n result =[]\n #query_params = {'key':params[1],'et_log_date':params[0]}\n query_params = {'key':params[0]}\n logging.debug(\"Query params are: key {}\".format(params[0]))\n query = \"\"\"select key,parameter_name,parameter_value,'foo',source\n from stg_perf_test.wt_log_parts\n where key = :key\"\"\".replace('\\n',' ')\n logging.debug(\"The log parts part is {}\".format(query))\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n def get_log_parts_pattern(self,params=['2017-6-9','eVar85','pid=1']):\n \"\"\" A method which returns all records for a log part matching a value for parameter value\"\"\"\n result =[]\n query_params = {'parameter_name':params[1],'et_log_date':params[0],'parameter_value':''}\n logging.debug(\"Query params are: key {} and date {}\".format(params[1],params[0]))\n query = \"\"\"select b.key,b.parameter_name,b.parameter_value,a.uuid,b.source\n from wt_logs a,wt_log_parts b\n where a.key = b.key\n and a.et_log_date = b.et_log_date\n and a.et_log_date = :et_log_date\n and b.parameter_name = :parameter_name\n and b.parameter_value = :parameter_value\"\"\".replace('\\n',' ')\n logging.debug(\"The log parts part is {}\".format(query))\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n def get_log_parts_pattern_limit(self,params=['2017-6-9','eVar85','pid=1']):\n \"\"\" A method which returns all records for a log part matching a value for parameter value and limts the result ordered by the date\"\"\"\n result =[]\n query_params = {'parameter_name':params[1],'et_log_date':params[0],'parameter_value':'%' + params[2] + '%'}\n logging.debug(\"Query params are: key {} and date {}\".format(params[1],params[0]))\n query = \"\"\"select b.key,b.parameter_name,b.parameter_value,a.uuid,b.source\n from wt_logs a,wt_log_parts b\n where a.key = b.key\n and a.et_log_date = b.et_log_date\n and a.et_log_date = :et_log_date\n and b.parameter_name = :parameter_name\n and b.parameter_value LIKE :parameter_value\n order by a.et_log_date limit 500\"\"\".replace('\\n',' ')\n logging.debug(\"The log parts part is {}\".format(query))\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n def get_log_parts_pattern_aggr(self,params=['2017-6-9','eVar85','pid=1']):\n \"\"\" A method which returns aggregated records for a log part matching a value for parameter name\"\"\"\n result =[]\n query_params = {'parameter_name':params[1],'et_log_date':params[0],'parameter_value':'%' + params[2] + '%'}\n logging.debug(\"Query params are: key {} and date {}\".format(params[1],params[0]))\n query = \"\"\"select b.et_log_date,count(key),b.parameter_name,b.parameter_value,b.source\n from wt_log_parts b\n where b.et_log_date = :et_log_date\n and b.parameter_name = :parameter_name\n and b.parameter_value LIKE :parameter_value\n group by 1,3,4,5 order by 1,2\"\"\".replace('\\n',' ')\n logging.debug(\"The log parts part is {}\".format(query))\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n def get_logs(self,fields=['key','app_visitor_cookie','page_url','et_log_date'],date='2017-06-10'):\n \"\"\" A method to query wt_logs table for a given date \"\"\"\n result =[]\n query_params = {'uuid':'0000000000000000001', 'param_value':'Default'}\n logs_query = \"select uuid,param_name,param_value from log_parts_backup where uuid = :uuid and param_value =:param_value\"\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(logs_query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n def get_logs_and_parts(self):\n \"\"\" A method which joins logs and log parts table and returns a combined result\"\"\"\n result =[]\n query_params = {'key':'1715230983110018712', 'parameter_name':'imprId','et_log_date':'2017-06-01'}\n query = \"\"\"select a.key,a.uuid,a.page_url,a.domain_name,a.app_visitor_cookie,a.referral_domain\n from wt_logs a, wt_log_parts b\n where a.key = b.key\n and a.et_log_date = :et_log_date\n and a.key = :key\n and b.parameter_name = :parameter_name\"\"\".replace('\\n',' ')\n with vertica_python.connect(conn_info) as connection:\n #print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n\n def get_visitor_analysis(self,params=['2017-7-13','2017-7-15','www.att.com']):\n \"\"\" A method which returns a count of key visitor metrics filtered by the domain\"\"\"\n result =[]\n res_from_query1 = []\n\n query_params = {'domain_name':params[2],'start_date':params[0],'end_date':params[1]}\n logging.debug(\"Query params are: end date {} and start date {} for domain {}\".format(params[1],params[0],params[2]))\n query1 = \"\"\"select\n A.pt_log_date,\n TO_CHAR(count(),'fm999999999.00') as total,\n ROUND(count(A.adobe_visid_high_low),2) as mcVisIdHigh,\n count(case when D.parameter_value = '0' then null else 1 end) as mcVisIdHigh,\n count(B.parameter_value) as uuid,\n count(case when instr(B.parameter_value,'-') > 0 then null else B.parameter_value end) as auth_uuid\n from wt_logs A left outer join wt_log_parts B on A.key = B.key and A.distribution_key = B.distribution_key and B.parameter_name = 'prop48' and B.pt_log_date between :start_date and :end_date\n left outer join wt_log_parts D on A.key = D.key and A.distribution_key = D.distribution_key and D.parameter_name = 'mcVisIdHigh' and D.pt_log_date between :start_date and :end_date\n where A.pt_log_date between :start_date and :end_date\n and A.domain_name = :domain_name\n group by A.pt_log_date\"\"\".replace('\\n',' ')\n logging.info(\"The first query is {}\".format(query1))\n with vertica_python.connect(conn_info) as connection:\n cur = connection.cursor()\n cur.execute(query1,query_params)\n for row in cur.iterate():\n res_from_query1.append(row)\n\n return(res_from_query1)\n\n\n def get_task_details_by_id(self,params=['ng2157']):\n \"\"\" A method which joins logs and log parts table and returns a combined result\"\"\"\n result =[]\n query_params = {'attid':params[0]}\n query = \"\"\"select a.Attuid,a.Status,a.Severity,a.TaskDetails,a.Remarks,a.StartDate,a.EndDate,a.TaskFinishDate,a.InsertDate,a.InsertedBy,a.UpdateDate,a.UpdatedBy\n from s08_DB.Alltasks a\n where a.Attuid =:attid\"\"\".replace('\\n',' ')\n with vertica_python.connect(conn_info) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n logging.info(\"The read SQL -> {} \".format(query))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur.iterate():\n result.append(row)\n return(result)\n\n\nif __name__ == '__main__':\n vertica = VerticaGetter()\n #vertica.test_connection()\n res = vertica.get_task_details_by_id()\n #res = vertica.get_log_parts_pattern_aggr()\n for row in res:\n print(row)\n\n" }, { "alpha_fraction": 0.5970001816749573, "alphanum_fraction": 0.6013420224189758, "avg_line_length": 35.43885040283203, "blob_id": "59a10073d1eaed3f773ac75bd5f3a5325fb0dfd0", "content_id": "f0f119f611d1e527dff9ca2375297fffc887f15c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5067, "license_type": "no_license", "max_line_length": 114, "num_lines": 139, "path": "/stg-nrtviewer.web.att.com/htdocs/visitor_view.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\nimport cgi\nfrom vertica_getter import VerticaGetter\n\nTABLE_OPEN = '<table id = LogPartsResult class=\"table table-striped table-bordered\" cellspacing=\"0\" width=\"100%\">'\nTHEAD_OPEN = '<thead>'\nTBODY_OPEN = '<tbody>'\nROW_OPEN = '<tr>'\nCOLUMN_OPEN = '<td>'\nTHEAD_ROW_OPEN = '<th>'\nTABLE_CLOSE = '</table>'\nROW_CLOSE = '</tr>'\nCOLUMN_CLOSE = '</td>'\nTHEAD_CLOSE = '</thead>'\nTBODY_CLOSE = '</tbody>'\nTHEAD_ROW_CLOSE = '</th>'\n\nclass ResultModel():\n \"\"\" A class to create model for the UI \"\"\"\n\n def __init__(self):\n \"\"\" The default constructor\"\"\"\n pass\n\n def __init__(self,start_date,end_date,param_name,context_name,param_value):\n \"\"\" The contructor takes 2 arguments at the minimum\"\"\"\n self.start_date = start_date\n self.end_date = end_date\n self.param_name = param_name\n self.context_name = context_name\n self.param_value = param_value\n\n def get_data(self):\n \"\"\" A method to get data from Vertica based on different conditions\"\"\"\n data_obj = VerticaGetter()\n if self.context_name == 'PARTS':\n param_list = [self.start_date,self.end_date,self.param_name]\n param_list = [str(elem) for elem in param_list]\n res = data_obj.get_visitor_analysis(param_list)\n else:\n res = data_obj.get_visitor_analysis()\n return res\n\n def format_default_result(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('File ID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Parameter Name')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Parameter Value')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('UUID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Source')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def format_aggr_result(self,db_res):\n \"\"\" Receives an object from the database and formats to an html table\"\"\"\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Date')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Total')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Adobe VisIdHighLow')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('McVisIdHigh')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('UUID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Auth UUID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)\n\n def default_response(self,response_msg='A pretty minimal response'):\n \"\"\" A method to send a default response to the browser for testing purposes\"\"\"\n resp = []\n resp.append(\"Content-Type: text/plain\")\n resp.append(\"\")\n resp.append(response_msg)\n res_str = \"\\r\\n\".join(resp)\n return res_str\n\nif __name__ == '__main__':\n form = cgi.FieldStorage()\n date = form.getfirst('stDate','2017-06-10')\n end_date = form.getfirst('endDate','2017-06-10')\n param_name = form.getfirst('param','')\n context_name = form.getfirst('context','PARTS')\n param_value = form.getfirst('paramVal','')\n #result_flag = form.getfirsti('aggrFlag','NO')\n model = ResultModel(date,end_date,param_name,context_name,param_value)\n res_list = model.get_data()\n html_res = model.format_aggr_result(res_list)\n print(model.default_response(html_res))\n\n\n" }, { "alpha_fraction": 0.7225806713104248, "alphanum_fraction": 0.7225806713104248, "avg_line_length": 16.11111068725586, "blob_id": "e6534e3c31d8528d408a6f5d9379ec1f18b17908", "content_id": "c19a553feada673d8fc721f2db82d167d6748346", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 155, "license_type": "no_license", "max_line_length": 33, "num_lines": 9, "path": "/prod-nrtviewer.web.att.com/htdocs/test.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/deap/python/bin/python\nimport cgitb\ncgitb.enable()\n\n# Print necessary headers.\nprint(\"Content-Type: text/html\")\nprint()\n\nprint(\"Hello World!\") \n" }, { "alpha_fraction": 0.5802651047706604, "alphanum_fraction": 0.6161020994186401, "avg_line_length": 36.685184478759766, "blob_id": "c65c44209eafd1a560d8489c40501463cfed68ab", "content_id": "737932698e2df5b86b164bada024d2db865fc491", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2037, "license_type": "no_license", "max_line_length": 120, "num_lines": 54, "path": "/prod-nrtviewer.web.att.com/htdocs/firehose_view.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\nimport cgi\nimport requests\nimport json\n\nclass ResultModel():\n \"\"\" A class to create model for the UI \"\"\"\n\n def __init__(self):\n \"\"\" The default constructor\"\"\"\n pass\n\n def __init__(self,start_date,end_date,param_value):\n \"\"\" The contructor takes 2 arguments at the minimum\"\"\"\n self.start_date = start_date\n self.end_date = end_date\n self.param_value = param_value\n\n def get_data(self):\n \"\"\" A method to get data from an input source based on different conditions\"\"\"\n #url = 'http://dev-ebetl01.bodc.att.com:29002/FileService/uuid/' \n #url = 'http://stg-ebetl05.bodc.att.com:29002/FileService/search/20180419/df8d328d-cc7c-48fe-8a1d-b447521fe214' \n url = 'http://stg-ebetl05.bodc.att.com:29002/FileService/search/' \n #url = 'http://ebetl07.bodc.att.com:29002/FileService/search/' \n rest_url = url + self.start_date + '/' + self.param_value\n res = ''\n if self.param_value is not '':\n # Make the url\n #rest_url = url + self.param_value\n # call the fileservice api\n response = requests.get(rest_url)\n # convert the response to json and then a string\n res = json.dumps(response.json(),indent=4,sort_keys=True)\n return res\n\n def default_response(self,response_msg='A pretty minimal response'):\n \"\"\" A method to send a default response to the browser for testing purposes\"\"\"\n resp = []\n resp.append(\"Content-Type: text/plain\")\n resp.append(\"\")\n resp.append(response_msg)\n res_str = \"\\r\\n\".join(resp)\n return res_str\n\nif __name__ == '__main__':\n form = cgi.FieldStorage()\n date = form.getfirst('stDate','20170610')\n end_date = form.getfirst('endDate','20170610')\n param_value = form.getfirst('param','')\n model = ResultModel(date,end_date,param_value)\n res_list = model.get_data()\n print(model.default_response(res_list))\n\n\n" }, { "alpha_fraction": 0.5750448703765869, "alphanum_fraction": 0.5983753800392151, "avg_line_length": 48.00925827026367, "blob_id": "4063622c88c70fe994284e3f5144e49ca1c44535", "content_id": "861865c97985adc64d2e9ebb15feda0271ee2584", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 10587, "license_type": "no_license", "max_line_length": 224, "num_lines": 216, "path": "/prod-nrtviewer.web.att.com/htdocs/oracle_getter.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\n\"\"\"\nA script for getting data objects from Oracle\nReferences: http://www.juliandyke.com/Research/Development/UsingPythonWithOracle.php\n\"\"\"\nimport logging\nimport sys\n#sys.path.append('/opt/app/deap/oracle/instantclient_11_2/')\nimport cx_Oracle\n\n# Set the logging level to DEBUG\nlogging.basicConfig(level=logging.INFO)\n\nconn_info_stg = {'host_ip': '135.164.37.221',\n 'port': 1521,\n 'user': 'ecstg',\n 'password': 'ecstg_vert',\n 'database': 'ebrVdev'\n }\n\nconn_info = {'host_ip': '135.164.53.134',\n 'port': 1521,\n 'user': 'ecstg',\n 'password': 'ecstgedmo',\n 'database': 'edmoprd'\n }\n\n\nclass OracleGetter():\n \"\"\" A class to get data from Vertica\"\"\"\n TEST_QUERY='SELECT FROM NRT_ADOBE_LOG_CONTROL where FILE_ID = 171624083411'\n\n def __init__(self):\n \"\"\" The default constructor which creates the dsn\"\"\"\n self.dsn = cx_Oracle.makedsn(conn_info['host_ip'],conn_info['port'],conn_info['database'])\n\n def __str__(self):\n return \" An Oracle getter for db {} on host {}\".format(conn_info['database'],conn_info['host_ip'])\n\n def get_dbname(self):\n \"\"\" A method which returns the nameo the database\"\"\"\n return conn_info['database']\n\n def test_connection(self):\n \"\"\" A test method just to check connection to Vetica\"\"\"\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(self.TEST_QUERY)\n for row in cur:\n print(\"The row is {}\".format(row))\n\n def get_single_record_by_fileID(self,params=['171624083411']):\n \"\"\" A method which returns a process statistics for a single file for a given day\"\"\"\n result =[]\n query_params = {'FILE_ID':params[0]}\n query = \"\"\"select FILE_ID,FILENAME,SERVER_NAME,PARSE_INPUT,VT_LOG_SUCCESS_ROWS,VT_LOG_PARTS_SUCCESS_ROWS\n from NRT_ADOBE_LOG_CONTROL\n where FILE_ID = :FILE_ID\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def get_count_files_by_date(self,params=['20170606','20170611']):\n \"\"\" A method which returns count of dev and prod files loaded per day\"\"\"\n result =[]\n query_params = {'START_DT':params[0],'END_DT':params[1]}\n query = \"\"\"select DAY_ID,PRODUCTION_FILE_FLAG,COUNT(FILE_ID)\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID BETWEEN :START_DT and :END_DT\n group by DAY_ID,PRODUCTION_FILE_FLAG\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def get_records_by_date(self,params=['2017611']):\n \"\"\" A method which returns a process statistics for a single file for a given day\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"select FILE_ID,FILENAME,SERVER_NAME,PARSE_INPUT,VT_LOG_SUCCESS_ROWS,VT_LOG_PARTS_SUCCESS_ROWS\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID = :DAY_ID\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def get_records_timings_by_date(self,params=['2017822']):\n \"\"\" A method which returns timings on parsing and loading times per file between a date range\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"select DAY_ID,\n FILENAME,\n FILE_ID,\n CEIL((FILE_PARSED_DATE - PARSER_START_DATE )2460) as TIME_TO_PARSE_MINUTES,\n CEIL((VT_LOAD_DATE - LOAD_START_DATE )2460) as TIME_TO_LOAD_MINUTES ,\n VT_LOG_SUCCESS_ROWS as LOADED_LOG_ROWS ,\n VT_LOG_PARTS_SUCCESS_ROWS as LOADED_LOG_PARTS_ROWS\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID= :DAY_ID\n order by 5 desc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def getTenMinStats(self,params=['20180210']):\n \"\"\" A method which returns 5 min statistics starting from current time\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute as record_time,\n round(((to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi'))+interval '10' minute - to_date('19700101 000000', 'YYYYMMDD HH24MISS'))86400000) as udt ,\n parser.time_interval , total_loaded_logs ,total_loaded_log_parts,\n total_parsed_logs,total_parsed_log_parts from \n (select substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(vt_log_success_rows),0) as total_loaded_logs,\n nvl(sum(vt_log_parts_success_rows),0) as total_loaded_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and vt_load_Date >= (sysdate-4/24)\n and process_name='Load'\n and process_status ='Complete'\n group by substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0'\n ) loader full outer join \n (select substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(parse_output_logs),0) as total_parsed_logs,\n nvl(sum(parse_output_nvp),0) as total_parsed_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and file_parsed_Date >= (sysdate-4/24)\n and ( (process_name='Load'\n and process_status in ('Complete','Start')) OR \n (process_name='Parser'\n and process_status ='Complete'))\n group by substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0') parser \n on loader.time_interval = parser.time_interval\n where to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute <=sysdate\n order by record_time asc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n #cur.execute(query,query_params)\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def getOneMinStats(self,params=['20180210']):\n \"\"\" A method which returns 5 min statistics starting from current time\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute as record_time,\n round(((to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi'))+interval '10' minute - to_date('19700101 000000', 'YYYYMMDD HH24MISS'))86400) as udt ,\n parser.time_interval , total_loaded_logs ,total_loaded_log_parts,\n total_parsed_logs,total_parsed_log_parts from \n (select substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(vt_log_success_rows),0) as total_loaded_logs,\n nvl(sum(vt_log_parts_success_rows),0) as total_loaded_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and vt_load_Date >= (sysdate-1/144)\n and process_name='Load'\n and process_status ='Complete'\n group by substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0'\n ) loader full outer join \n (select substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(parse_output_logs),0) as total_parsed_logs,\n nvl(sum(parse_output_nvp),0) as total_parsed_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and file_parsed_Date >= (sysdate-1/144)\n and ( (process_name='Load'\n and process_status in ('Complete','Start')) OR \n (process_name='Parser'\n and process_status ='Complete'))\n group by substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0') parser \n on loader.time_interval = parser.time_interval\n where to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute <=sysdate\n order by record_time asc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host {} \".format(conn_info['database'],conn_info['host_ip']))\n logging.debug(\"One min stats , SQL --> {} \".format(query))\n cur = connection.cursor()\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n\nif __name__ == '__main__':\n o = OracleGetter()\n res = o.getOneMinStats()\n #res = o.get_records_timings_by_date()\n for item in res:\n print(item)\n\n" }, { "alpha_fraction": 0.7232704162597656, "alphanum_fraction": 0.7295597195625305, "avg_line_length": 16.55555534362793, "blob_id": "49028b19ad3dad21602e0aef237b5411fe51d276", "content_id": "65e4425d283b1f313f3c4b0f5bf889623c72a120", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 159, "license_type": "no_license", "max_line_length": 37, "num_lines": 9, "path": "/default/htdocs/test.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\n\n# Print necessary headers.\nprint(\"Content-Type: text/html\")\nprint()\n\nprint(\"Hello World!\") \n" }, { "alpha_fraction": 0.46862098574638367, "alphanum_fraction": 0.5103220343589783, "avg_line_length": 21.72549057006836, "blob_id": "0e9868a86690a5d20190add90d6176be1abdde18", "content_id": "78e9accbcc05cd24c36585938e1399e37aa4a6ad", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 2422, "license_type": "no_license", "max_line_length": 144, "num_lines": 102, "path": "/nodejscheatsheet.js", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "var origData = [];\r\nvar time = (new Date()).getTime();\r\nvar i;\r\n\r\nfor (i = -9; i <= 0; i += 1) {\r\n origData.push({\r\n x: time + i * 1000,\r\n y: Math.random()\r\n });\r\n}\r\n\r\n\r\nconsole.log(origData);\r\nconsole.log(\"==========================================\");\r\n\r\n\r\nvar data = [];\r\nvar input = '[[\"2018-02-10 03:00:27\", 84], [\"2018-02-10 03:00:27\", 9776]]';\r\nvar jsonRes = JSON.parse(input);\r\n\r\nfor(var item in jsonRes){\r\n var row = jsonRes[item];\r\n data.push({x:row[0],y:row[1]});\r\n}\r\n\r\nconsole.log(data);\r\nconsole.log(\"==========================================\");\r\n\r\nvar newData = {};\r\n\r\nvar flatJson = [\"2018-02-10 03:00:27\",84,\"2018-02-10 03:00:27\",9776];\r\n\r\nvar time = [];\r\nvar statVal = [];\r\n\r\nfor(var item in flatJson){\r\n if(item % 2 == 0){\r\n time.push(flatJson[item]);\r\n // newData.push({x:flatJson[item]});\r\n }\r\n else{\r\n statVal.push(flatJson[item]);\r\n // newData.push({y:flatJson[item]});\r\n }\r\n}\r\n\r\nfor( var i in time){\r\n // newData.push({x:time[i]});\r\n newData['x'].push(time[i]);\r\n}\r\n\r\n\r\nfor( var i in statVal){\r\n // newData.push({y:time[i]});\r\n newData['y'].push(statVal[i]);\r\n}\r\n\r\n// newData.push({x:time,y:statVal});\r\nconsole.log(newData);\r\n\r\n// Aggregate the reuslt set\r\n\r\nvar aggrRes = [];\r\nvar origData = [];\r\nvar time = (new Date()).getTime();\r\nvar i;\r\n\r\nfor (i = -9; i <= 0; i += 1) {\r\n origData.push({\r\n x: time + i * 1000,\r\n y: Math.random()\r\n });\r\n}\r\n\r\naggrRes.push({'current':origData , 'hist':origData});\r\nconsole.log(\"The orig data is \" , origData);\r\n\r\n\r\nconsole.log(\"The current data is \" , aggrRes[0]['current']);\r\n\r\nconsole.log(\"The hist data is \" , aggrRes[0]['hist']);\r\n\r\nconsole.log(\"==========================================\");\r\n\r\n// Dates\r\n\r\nepoch = Math.floor(Date.now());\r\n\r\nvar dateObj = new Date(epoch);\r\nvar prevDate = new Date();\r\nprevDate.setDate(prevDate.getDate() - 7);\r\n\r\n// var d = new Date(); // today!\r\n// var x = 5; // go back 5 days!\r\n// d.setDate(d.getDate() - x);\r\n\r\nvar formatDate = dateObj.getFullYear() + \"-\" + ('0' + (dateObj.getMonth() + 1)).slice(-2) + \"-\" + ('0' + (dateObj.getDate())).slice(-2);\r\n\r\nvar prevFormatDate = prevDate.getFullYear() + \"-\" + ('0' + (prevDate.getMonth() + 1)).slice(-2) + \"-\" + ('0' + (prevDate.getDate())).slice(-2); \r\n\r\nconsole.log(dateObj);\r\nconsole.log(\"The curent date :\" , formatDate , \" previous date :\" , prevFormatDate);\r\n\r\n" }, { "alpha_fraction": 0.5830000042915344, "alphanum_fraction": 0.5950000286102295, "avg_line_length": 40.65625, "blob_id": "b3ff5a3adf9ca5a0f389ecb684e3f02b1ec090a7", "content_id": "ae6025412f9280884dd1896637624c6f55b4302b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4000, "license_type": "no_license", "max_line_length": 118, "num_lines": 96, "path": "/prod-abcdash.web.att.com/htdocs/oracle_getter.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/deap/python/bin/python3\n\"\"\"\nA script for getting data objects from Oracle\nReferences: http://www.juliandyke.com/Research/Development/UsingPythonWithOracle.php\n\"\"\"\nimport logging\nimport sys\n#sys.path.append('/opt/app/deap/oracle/instantclient_11_2/')\nimport cx_Oracle\n\n# Set the logging level to DEBUG\nlogging.basicConfig(level=logging.INFO)\n\nconn_info = {'host_ip': '135.164.36.169',\n 'port': 1521,\n 'user': 'abc',\n 'password': 'abcedmo',\n 'database': 'edmoprd'\n }\n\nclass OracleGetter():\n \"\"\" A class to get ABC data from Oracle\"\"\"\n TEST_QUERY='SELECT JID, JOB_NM, JOB_TYPE, JOB_DESC, JOB_LOG_FILE, SSID, JOB_LVL, ABC_VER, JOB_NM_DTL FROM ABC_JOB'\n\n def __init__(self):\n \"\"\" The default constructor which creates the dsn\"\"\"\n self.dsn = cx_Oracle.makedsn(conn_info['host_ip'],conn_info['port'],conn_info['database'])\n\n def __str__(self):\n return \" An Oracle getter for db {} on host {}\".format(conn_info['database'],conn_info['host_ip'])\n\n def get_dbname(self):\n \"\"\" A method which returns the nameo the database\"\"\"\n return conn_info['database']\n\n def test_connection(self):\n \"\"\" A test method just to check connection to Vetica\"\"\"\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(self.TEST_QUERY)\n for row in cur:\n print(\"The row is {}\".format(row))\n\n def get_single_record_by_jobID(self,params=['1005']):\n \"\"\" A method which returns a process statistics for a single file for a given day\"\"\"\n result =[]\n query_params = {'JID':params[0]}\n query = \"\"\"SELECT JID, JOB_NM, JOB_TYPE, JOB_DESC,JOB_NM_DTL\n FROM ABC_JOB\n WHERE JID = :JID\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def get_count_files_by_date(self,params=['20170606','20170611']):\n \"\"\" A method which returns count of dev and prod files loaded per day\"\"\"\n result =[]\n query_params = {'START_DT':params[0],'END_DT':params[1]}\n query = \"\"\"select DAY_ID,PRODUCTION_FILE_FLAG,COUNT(FILE_ID)\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID BETWEEN :START_DT and :END_DT\n group by DAY_ID,PRODUCTION_FILE_FLAG\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def get_all_jobs(self,params=['2017611']):\n \"\"\" A method which returns a process statistics for a single file for a given day\"\"\"\n result =[]\n query_params = {'JIB':params[0]}\n query = \"\"\"SELECT JID, JOB_NM, JOB_TYPE, JOB_DESC,JOB_NM_DTL\n FROM ABC_JOB\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\nif __name__ == '__main__':\n o = OracleGetter()\n #o.test_connection()\n res = o.get_single_record_by_jobID()\n for elem in res:\n print(elem) \n" }, { "alpha_fraction": 0.5907067656517029, "alphanum_fraction": 0.6147151589393616, "avg_line_length": 55.315494537353516, "blob_id": "412af1cd5ada4d4abcfecfc19965fcdec69ca16c", "content_id": "89bdf932f5dfe055979916ead58b2880f98d2332", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 19993, "license_type": "no_license", "max_line_length": 224, "num_lines": 355, "path": "/stg-nrtviewer.web.att.com/htdocs/oracle_getter.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\n\"\"\"\nA script for getting data objects from Oracle\nReferences: http://www.juliandyke.com/Research/Development/UsingPythonWithOracle.php\n\"\"\"\nimport logging\nimport sys\n#sys.path.append('/opt/app/deap/oracle/instantclient_11_2/')\nimport cx_Oracle\n\n# Set the logging level to DEBUG\nlogging.basicConfig(level=logging.INFO)\n\nconn_info_stg = {'host_ip': '135.164.37.221',\n 'port': 1521,\n 'user': 'ecstg',\n 'password': 'ecstg_vert',\n 'database': 'ebrVdev'\n }\n\nconn_info = {'host_ip': '135.164.53.134',\n 'port': 1521,\n 'user': 'ecstg',\n 'password': 'ecstgedmo',\n 'database': 'edmoprd'\n }\n\n\nclass OracleGetter():\n \"\"\" A class to get data from Vertica\"\"\"\n TEST_QUERY='SELECT * FROM NRT_ADOBE_LOG_CONTROL where FILE_ID = 171624083411'\n\n def __init__(self):\n \"\"\" The default constructor which creates the dsn\"\"\"\n self.dsn = cx_Oracle.makedsn(conn_info['host_ip'],conn_info['port'],conn_info['database'])\n\n def __str__(self):\n return \" An Oracle getter for db {} on host {}\".format(conn_info['database'],conn_info['host_ip'])\n\n def get_dbname(self):\n \"\"\" A method which returns the nameo the database\"\"\"\n return conn_info['database']\n\n def test_connection(self):\n \"\"\" A test method just to check connection to Vetica\"\"\"\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(self.TEST_QUERY)\n for row in cur:\n print(\"The row is {}\".format(row))\n\n def get_single_record_by_fileID(self,params=['171624083411']):\n \"\"\" A method which returns a process statistics for a single file for a given day\"\"\"\n result =[]\n query_params = {'FILE_ID':params[0]}\n query = \"\"\"select FILE_ID,FILENAME,SERVER_NAME,PARSE_INPUT,VT_LOG_SUCCESS_ROWS,VT_LOG_PARTS_SUCCESS_ROWS\n from NRT_ADOBE_LOG_CONTROL\n where FILE_ID = :FILE_ID\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def get_count_files_by_date(self,params=['20170606','20170611']):\n \"\"\" A method which returns count of dev and prod files loaded per day\"\"\"\n result =[]\n query_params = {'START_DT':params[0],'END_DT':params[1]}\n query = \"\"\"select DAY_ID,PRODUCTION_FILE_FLAG,COUNT(FILE_ID)\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID BETWEEN :START_DT and :END_DT\n group by DAY_ID,PRODUCTION_FILE_FLAG\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def get_records_by_date(self,params=['2017611']):\n \"\"\" A method which returns a process statistics for a single file for a given day\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"select FILE_ID,FILENAME,SERVER_NAME,PARSE_INPUT,VT_LOG_SUCCESS_ROWS,VT_LOG_PARTS_SUCCESS_ROWS\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID = :DAY_ID\"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.debug(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def get_records_timings_by_date(self,params=['2017822']):\n \"\"\" A method which returns timings on parsing and loading times per file between a date range\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"select DAY_ID,\n FILENAME,\n FILE_ID,\n CEIL((FILE_PARSED_DATE - PARSER_START_DATE )2460) as TIME_TO_PARSE_MINUTES,\n CEIL((VT_LOAD_DATE - LOAD_START_DATE )2460) as TIME_TO_LOAD_MINUTES ,\n VT_LOG_SUCCESS_ROWS as LOADED_LOG_ROWS ,\n VT_LOG_PARTS_SUCCESS_ROWS as LOADED_LOG_PARTS_ROWS\n from NRT_ADOBE_LOG_CONTROL\n where DAY_ID= :DAY_ID\n order by 5 desc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n cur.execute(query,query_params)\n for row in cur:\n result.append(row)\n return(result)\n\n def getTenMinStats(self,params=['20180210']):\n \"\"\" A method which returns 5 min statistics starting from current time\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute as record_time,\n round(((to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi'))+interval '10' minute - to_date('19700101 000000', 'YYYYMMDD HH24MISS'))86400000) as udt ,\n parser.time_interval , \n nvl(total_loaded_logs,0) ,\n nvl(total_loaded_log_parts,0),\n nvl(total_parsed_logs,0),\n total_parsed_log_parts from \n (select substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(vt_log_success_rows),0) as total_loaded_logs,\n nvl(sum(vt_log_parts_success_rows),0) as total_loaded_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and vt_load_Date >= (sysdate-4/24)\n and process_name='Load'\n and process_status ='Complete'\n group by substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0'\n ) loader full outer join \n (select substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(parse_output_logs),0) as total_parsed_logs,\n nvl(sum(parse_output_nvp),0) as total_parsed_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and file_parsed_Date >= (sysdate-4/24)\n and ( (process_name='Load'\n and process_status in ('Complete','Start')) OR \n (process_name='Parser'\n and process_status ='Complete'))\n group by substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0') parser \n on loader.time_interval = parser.time_interval\n where to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute <=sysdate\n order by record_time asc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host_ip']))\n cur = connection.cursor()\n #cur.execute(query,query_params)\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n def getOneMinStats(self,params=['20180210']):\n \"\"\" A method which returns 5 min statistics starting from current time\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute as record_time,\n round(((to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi'))+interval '10' minute - to_date('19700101 000000', 'YYYYMMDD HH24MISS'))86400) as udt ,\n parser.time_interval , \n nvl(total_loaded_logs,0) ,\n nvl(total_loaded_log_parts,0),\n nvl(total_parsed_logs,0),\n nvl(total_parsed_log_parts,0) from \n (select substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(vt_log_success_rows),0) as total_loaded_logs,\n nvl(sum(vt_log_parts_success_rows),0) as total_loaded_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and vt_load_Date >= (sysdate-1/144)\n and process_name='Load'\n and process_status ='Complete'\n group by substr(to_char(vt_load_Date, 'hh24:mi'), 1, 4) \|\| '0'\n ) loader full outer join \n (select substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0' as time_interval,\n nvl(sum(parse_output_logs),0) as total_parsed_logs,\n nvl(sum(parse_output_nvp),0) as total_parsed_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and file_parsed_Date >= (sysdate-1/144)\n and ( (process_name='Load'\n and process_status in ('Complete','Start')) OR \n (process_name='Parser'\n and process_status ='Complete'))\n group by substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 4) \|\| '0') parser \n on loader.time_interval = parser.time_interval\n where to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute <=sysdate\n order by record_time asc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host {} \".format(conn_info['database'],conn_info['host_ip']))\n logging.debug(\"One min stats , SQL --> {} \".format(query))\n cur = connection.cursor()\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def getOldHourlyFullStats(self,params=['20180210']):\n \"\"\" A method which returns single hourly statistics starting for the past hour\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute as record_time,\n round(((to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi'))+interval '10' minute - to_date('19700101 000000', 'YYYYMMDD HH24MISS'))86400) as udt ,\n parser.time_interval , total_loaded_logs ,total_loaded_log_parts,\n total_parsed_logs,total_parsed_log_parts from\n (select substr(to_char(vt_load_Date, 'hh24:mi'), 1, 2) as time_interval,\n nvl(sum(vt_log_success_rows),0) as total_loaded_logs,\n nvl(sum(vt_log_parts_success_rows),0) as total_loaded_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and vt_load_Date >= (sysdate-1)\n and process_name='Load'\n and process_status ='Complete'\n group by substr(to_char(vt_load_Date, 'hh24:mi'), 1, 2)\n ) loader full outer join\n (select substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 2) as time_interval,\n nvl(sum(parse_output_logs),0) as total_parsed_logs,\n nvl(sum(parse_output_nvp),0) as total_parsed_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and file_parsed_Date >= (sysdate-1)\n and ( (process_name='Load'\n and process_status in ('Complete','Start')) OR\n (process_name='Parser'\n and process_status ='Complete'))\n group by substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 2)) parser\n on loader.time_interval = parser.time_interval\n\torder by record_time asc \n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host {} \".format(conn_info['database'],conn_info['host_ip']))\n logging.debug(\"One min stats , SQL --> {} \".format(query))\n cur = connection.cursor()\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def getHourlyFullStats(self,params=['20180210']):\n \"\"\" A method which returns single hourly statistics starting for the past hour\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select today_hours.record_time as today_record_time ,today_hours.udt as today_udt ,\n today_hours.time_interval as today_time_interval , \n today_hours.total_loaded_logs as today_total_loaded_logs , \n today_hours.total_loaded_log_parts as today_total_loaded_log_parts ,\n today_hours.total_parsed_logs as total_parsed_logs ,\n today_hours.total_parsed_log_parts as today_total_parsed_log_parts ,\n last_week_hours.record_time as last_week_record_time ,\n last_week_hours.udt as last_week_udt ,\n last_week_hours.time_interval as last_week_time_interval ,\n nvl(last_week_hours.total_loaded_logs,0) as last_week_total_loaded_logs ,\n last_week_hours.total_loaded_log_parts as last_week_loaded_log_parts ,\n last_week_hours.total_parsed_logs as last_week_parsed_logs ,\n last_week_hours.total_parsed_log_parts as last_week_parsed_log_parts \n from \n ( SELECT TO_DATE( (TO_CHAR(SYSDATE,'mm/dd/yyyy') \|\| ' ' \|\| parser.time_interval),'mm/dd/yyyy hh24') AS record_time,\n round( ( (TO_DATE( (TO_CHAR(SYSDATE,'mm/dd/yyyy') \|\| ' ' \|\| parser.time_interval),'mm/dd/yyyy hh24') ) - TO_DATE('19700101 000000','YYYYMMDD HH24MISS') ) 86400000) AS udt, \n parser.time_interval, total_loaded_logs, total_loaded_log_parts, total_parsed_logs, total_parsed_log_parts\n FROM ( SELECT substr(TO_CHAR(vt_load_date,'hh24'),1,2) AS time_interval, SUM(vt_log_success_rows) AS total_loaded_logs, SUM(vt_log_parts_success_rows) AS total_loaded_log_parts \n FROM nrt_adobe_log_control WHERE day_id = TO_CHAR(SYSDATE,'yyyymmdd') AND vt_load_date >= ( SYSDATE - 1 ) AND process_name = 'Load' AND process_status = 'Complete' \n GROUP BY substr(TO_CHAR(vt_load_date,'hh24'),1,2) ) loader \n FULL OUTER JOIN ( SELECT substr(TO_CHAR(file_parsed_date,'hh24'),1,2) AS time_interval, SUM(parse_output_logs) AS total_parsed_logs, SUM(parse_output_nvp) AS total_parsed_log_parts FROM nrt_adobe_log_control \n WHERE day_id = TO_CHAR(SYSDATE,'yyyymmdd') AND file_parsed_date >= ( SYSDATE - 1 ) AND ( ( process_name = 'Load' AND process_status IN ( 'Complete', 'Start' ) ) \n OR ( process_name = 'Parser' AND process_status = 'Complete' ) ) GROUP BY substr(TO_CHAR(file_parsed_date,'hh24'),1,2) ) parser ON loader.time_interval = parser.time_interval ) today_hours \n full outer join ( SELECT TO_DATE( (TO_CHAR(SYSDATE-7,'mm/dd/yyyy') \|\| ' ' \|\| parser.time_interval),'mm/dd/yyyy hh24') AS record_time,\n round( ( (TO_DATE( (TO_CHAR(SYSDATE-7,'mm/dd/yyyy') \|\| ' ' \|\| parser.time_interval),'mm/dd/yyyy hh24') ) - TO_DATE('19700101 000000','YYYYMMDD HH24MISS') ) * 86400000) AS udt,\n parser.time_interval, total_loaded_logs, total_loaded_log_parts, total_parsed_logs, total_parsed_log_parts FROM ( SELECT substr(TO_CHAR(vt_load_date,'hh24'),1,2) AS time_interval,\n SUM(vt_log_success_rows) AS total_loaded_logs, SUM(vt_log_parts_success_rows) AS total_loaded_log_parts FROM nrt_adobe_log_control WHERE day_id = TO_CHAR(SYSDATE-7,'yyyymmdd')\n AND process_name = 'Load' AND process_status = 'Complete' GROUP BY substr(TO_CHAR(vt_load_date,'hh24'),1,2) ) loader FULL OUTER JOIN ( SELECT substr(TO_CHAR(file_parsed_date,'hh24'),1,2)\n AS time_interval, SUM(parse_output_logs) AS total_parsed_logs, SUM(parse_output_nvp) AS total_parsed_log_parts FROM nrt_adobe_log_control WHERE day_id = TO_CHAR(SYSDATE-7,'yyyymmdd')\n AND ( ( process_name = 'Load' AND process_status IN ( 'Complete', 'Start' ) ) OR ( process_name = 'Parser' AND process_status = 'Complete' ) ) \n GROUP BY substr(TO_CHAR(file_parsed_date,'hh24'),1,2) ) parser ON loader.time_interval = parser.time_interval ) last_week_hours on today_hours.time_interval=last_week_hours.time_interval\n order by last_week_time_interval\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host {} \".format(conn_info['database'],conn_info['host_ip']))\n logging.debug(\"hourly stats , SQL --> {} \".format(query))\n cur = connection.cursor()\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n\n def getHourlySingleStats(self,params=['20180210']):\n \"\"\" A method which returns single hourly statistics starting for the past hour\"\"\"\n result =[]\n query_params = {'DAY_ID':params[0]}\n query = \"\"\"\n select to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi')+interval '10' minute as record_time,\n round(((to_date((to_char(sysdate, 'mm/dd/yyyy')\|\|' '\|\|nvl(parser.time_interval,loader.time_interval)),'mm/dd/yyyy hh24:mi'))+interval '10' minute - to_date('19700101 000000', 'YYYYMMDD HH24MISS'))86400) as udt ,\n parser.time_interval , total_loaded_logs ,total_loaded_log_parts,\n total_parsed_logs,total_parsed_log_parts from\n (select substr(to_char(vt_load_Date, 'hh24:mi'), 1, 2) as time_interval,\n nvl(sum(vt_log_success_rows),0) as total_loaded_logs,\n nvl(sum(vt_log_parts_success_rows),0) as total_loaded_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and vt_load_Date >= (sysdate-1)\n and process_name='Load'\n and process_status ='Complete'\n group by substr(to_char(vt_load_Date, 'hh24:mi'), 1, 2)\n ) loader full outer join\n (select substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 2) as time_interval,\n nvl(sum(parse_output_logs),0) as total_parsed_logs,\n nvl(sum(parse_output_nvp),0) as total_parsed_log_parts\n from nrt_Adobe_log_control\n where day_id =to_char(sysdate,'yyyymmdd')\n and file_parsed_Date >= (sysdate-1)\n and ( (process_name='Load'\n and process_status in ('Complete','Start')) OR\n (process_name='Parser'\n and process_status ='Complete'))\n group by substr(to_char(file_parsed_Date, 'hh24:mi'), 1, 2)) parser\n on loader.time_interval = parser.time_interval\n order by record_time desc\n \"\"\".replace('\\n',' ')\n with cx_Oracle.connect(conn_info['user'],conn_info['password'],self.dsn) as connection:\n logging.info(\"Connected to {} on host {} \".format(conn_info['database'],conn_info['host_ip']))\n logging.debug(\"One min stats , SQL --> {} \".format(query))\n cur = connection.cursor()\n cur.execute(query)\n for row in cur:\n result.append(row)\n return(result)\n\n\nif __name__ == '__main__':\n o = OracleGetter()\n res = o.getHourlyFullStats()\n #res = o.get_records_timings_by_date()\n for item in res:\n print(item)\n\n" }, { "alpha_fraction": 0.5989096760749817, "alphanum_fraction": 0.6105918884277344, "avg_line_length": 31.897436141967773, "blob_id": "7089e94ccc5514ea10610f66c03c805f54ee507d", "content_id": "bf54754499a135dcedfea365e96d10ce86f31683", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2568, "license_type": "no_license", "max_line_length": 86, "num_lines": 78, "path": "/prod-nrtviewer.web.att.com/htdocs/livechart_view.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "#!/opt/app/cacheDB/python/bin/python3\nimport cgitb\ncgitb.enable()\nimport cgi\nimport sys\nimport json\nimport datetime\n#sys.path.append('/opt/app/deap/oracle/instantclient_11_2/')\nfrom oracle_getter import OracleGetter \n\nclass LiveChartView():\n \"\"\" A class to create a view for the UI \"\"\"\n\n def __init__(self):\n \"\"\" The default constructor\"\"\"\n pass\n\n def __init__(self,start_date,queryFlag):\n \"\"\" The contructor takes 2 arguments at the minimum\"\"\"\n self.start_date = start_date\n self.queryFlag = queryFlag\n\n def getTenMinStats(self):\n \"\"\" A method to call the stats getter from Oracle class\"\"\"\n d = {}\n dataObj = OracleGetter()\n res = dataObj.getTenMinStats()\n # date time creates an issue in deserialization\n jsonRes = json.dumps(res,sort_keys=True,default=str)\n #d['stats'] = l\n d['stats'] = jsonRes\n return json.dumps(d)\n\n\n def getOneMinStats(self):\n \"\"\" A method to call the stats getter from Oracle class\"\"\"\n d = {}\n dataObj = OracleGetter()\n res = dataObj.getOneMinStats()\n # date time creates an issue in deserialization\n jsonRes = json.dumps(res,sort_keys=True,default=str)\n #d['stats'] = l\n d['stats'] = jsonRes\n return json.dumps(d)\n \n def generateEpochTime(self):\n \"\"\" A method used to generate 10 minute epoch time list \"\"\"\n now = datetime.datetime.now().replace(second=0,microsecond=0)\n m = now.minute\n delta = m % 10\n new = now - datetime.timedelta(minutes=delta)\n date_list = [ new - datetime.timedelta(minutes=x) for x in range(10,120,10) ]\n epoch_list = [ x.timestamp()1000 for x in date_list ]\n return epoch_list\n\n def default_response(self,response_msg='A pretty minimal response'):\n \"\"\" A method to send a default response to the browser for testing purposes\"\"\"\n resp = []\n #resp.append(\"Content-Type: text/plain\")\n resp.append(\"Content-Type: application/json\")\n resp.append(\"\")\n resp.append(response_msg)\n res_str = \"\\r\\n\".join(resp)\n return res_str\n\nif __name__ == '__main__':\n form = cgi.FieldStorage()\n date = form.getfirst('stDate','20170611')\n flag = form.getfirst('flag','batch')\n view = LiveChartView(date,flag)\n if flag == 'single':\n res = view.getOneMinStats()\n else:\n res = view.getTenMinStats()\n print(view.default_response(res))\n #print(view.generateEpochTime())\n #print(type(res))\n #print(res)\n\n\n" }, { "alpha_fraction": 0.5712831020355225, "alphanum_fraction": 0.5896130204200745, "avg_line_length": 34, "blob_id": "1d87fb2219cbc3b2f6f75fe7d0d34da8ba869e28", "content_id": "27e8c2446f2ae57432b25b59773e2f22368f52eb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 982, "license_type": "no_license", "max_line_length": 87, "num_lines": 28, "path": "/stg-nrtviewer.web.att.com/htdocs/getData.py", "repo_name": "nachiketgalande/UIHome", "src_encoding": "UTF-8", "text": "import vertica_python\n\nTEST_QUERY=\"SELECT * FROM log_parts_backup LIMIT 5\";\n\nconn_info = {'host': 'dev-wavert01.bodc.att.com',\n 'port': 5433,\n 'user': 'ng2157',\n 'password': 'DEV-ng2157',\n 'database': 'DEV_EDM',\n # 10 minutes timeout on queries\n 'read_timeout': 600,\n # default throw error on invalid UTF-8 results\n 'unicode_error': 'strict',\n # SSL is disabled by default\n 'ssl': False,\n 'connection_timeout': 5}\n\n# simple connection, with manual close\n#connection = vertica_python.connect(conn_info)\n\n# using with for auto connection closing after usage\nwith vertica_python.connect(conn_info) as connection:\n # do things\n print(\"Connected to {} on host{} \".format(conn_info['database'],conn_info['host']))\n cur = connection.cursor()\n cur.execute(TEST_QUERY)\n for row in cur.iterate():\n print(\"The row is {}\".format(row))\n\n\n" } ]	14
whoismikechan/movie_trailer_website_project	https://github.com/whoismikechan/movie_trailer_website_project	fbd463d2a0577dab73b618e5f90c3a9d33f95157	521bf3d8d94094efc509362da48c215f3cc3fc05	b981f5c52cb1836f82500c9c1ff3eccca2bd7346	refs/heads/master	2020-03-09T07:18:46.121738	2018-04-09T02:33:01	2018-04-09T02:33:01	128,661,575	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7664141654968262, "alphanum_fraction": 0.7765151262283325, "avg_line_length": 37.60975646972656, "blob_id": "bacc318aef21457d2ab9ebd05ff761a5a431345b", "content_id": "2645c4852d4afc8708e9878d60aab375b384a64b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1584, "license_type": "no_license", "max_line_length": 260, "num_lines": 41, "path": "/README.md", "repo_name": "whoismikechan/movie_trailer_website_project", "src_encoding": "UTF-8", "text": "# Project1: Movie Trailer Website\n\nMovie trailer website project, part of the Udacity Full Stack Web Developer Nanodegree.\nThe Movie Trailer Website project consists of server-side code to store a list of movies titles, along with its respective box art imagery and movie trailer website. The data is served as a web page allowing visitors to review the movies and watch the trailers\n\n\n## Project contents:\n\nThis project consists for the following files:\n\n* entertainment_center.py - main Python script to run\n* media.py - contains the class Movie that stores movie details\n* fresh_tomatoes.py - creates the HTML file for the website (Udacity supplied)\n\n\n## Requirement:\n\nPython 2.x or Python 3.X is required to run this project. The Python executable should be in your default path, which the Python installer should have set.\nMake sure all files 'media.py', 'fresh_tomatoes.py' & 'entertainment_center.py' are in the same directory\n\n\n## How to run program:\n\nDownload the project zip file to you computer and unzip the file. Or clone this repository to your desktop.\nOpen the text-based interface for your operating system (e.g. the terminal window in Linux/MacOS, the command prompt in Windows).\nNavigate to the project directory and type in the following command:\n\n```sh\npython entertainment_center.py\n```\n\nYour default browser should launch a new tab displaying the movie trailer website.\nNote: The program has been tested under Python version 2.7.10 and version 3.6.4\n\n\n## Release History:\n\n* 0.1\n * The first release\n* 0.1.1\n * Format Python source code to be PEP8 compliant\n\n" }, { "alpha_fraction": 0.6685823798179626, "alphanum_fraction": 0.6819923520088196, "avg_line_length": 42.5, "blob_id": "237cb60f5e0f499e8d705717f863556eafb6aa9a", "content_id": "68bdc252d2f3777dee7c0e6488236ba5c597088d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1044, "license_type": "no_license", "max_line_length": 108, "num_lines": 24, "path": "/entertainment_center.py", "repo_name": "whoismikechan/movie_trailer_website_project", "src_encoding": "UTF-8", "text": "from media import Movie\nfrom fresh_tomatoes import open_movies_page\n\nif __name__ == \"__main__\":\n # Movie - Finding Nemo\n nemo_movie = Movie(title='FINDING NEMO',\n poster_image_url='https://upload.wikimedia.org/wikipedia/en/2/29/Finding_Nemo.jpg', # NOQA\n trailer_youtube_url='https://www.youtube.com/watch?v=wZdpNglLbt8')\n\n # Movie - School of Rock\n school_of_rock_movie = Movie(title='School Of Rock',\n poster_image_url='https://upload.wikimedia.org/wikipedia/en/1/11/School_of_Rock_Poster.jpg', # NOQA\n trailer_youtube_url='https://www.youtube.com/watch?v=XCwy6lW5Ixc')\n\n # Movie - Hermano\n hermano_movie = Movie(title='Hermano',\n poster_image_url='https://upload.wikimedia.org/wikipedia/en/4/4e/Hermano.jpg', # NOQA\n trailer_youtube_url='https://www.youtube.com/watch?v=5vrrRJDN64U')\n\n # List of Movie\n movie_list = [nemo_movie, school_of_rock_movie, hermano_movie]\n\n # Calling open_movies_page from fresh_tomatoes to generate web page\n open_movies_page(movie_list)\n" }, { "alpha_fraction": 0.6235294342041016, "alphanum_fraction": 0.6235294342041016, "avg_line_length": 34, "blob_id": "ccdd9c96f67791b51f5ca8167b5c1b9a58e5afb2", "content_id": "12f2bd4a3ccd11120b5491c5b4cb0e9b388d6414", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 595, "license_type": "no_license", "max_line_length": 77, "num_lines": 17, "path": "/media.py", "repo_name": "whoismikechan/movie_trailer_website_project", "src_encoding": "UTF-8", "text": "class Movie():\n \"\"\"\n Movie class - Contains the details of a movie\n\n - Attribute:\n - title: A string to store the title of the movie.\n - poster_image_url: A string to store the URL of the movie postal\n - trailer_youtube_url: A string to store the URL of the movie trailer\n \"\"\"\n\n def __init__(self, title, poster_image_url, trailer_youtube_url):\n # Movie title\n self.title = title\n # Movie poster image URL\n self.poster_image_url = poster_image_url\n # Movie trailer URL\n self.trailer_youtube_url = trailer_youtube_url\n" } ]	3
andreyhitoshi1997/AC-Desenvolvimento-Sistemas	https://github.com/andreyhitoshi1997/AC-Desenvolvimento-Sistemas	2a2f28bbdd42bfe6c292585ac585a5ac710a1e92	54b7283669b134533d82bcfb1a42bd156d2d4348	587cb27b691dc566fd9e6fcf2b266d802d7cedd0	refs/heads/master	2023-05-19T19:02:56.328645	2021-06-07T03:50:25	2021-06-07T03:50:25	345,492,783	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.47698745131492615, "alphanum_fraction": 0.6931659579277039, "avg_line_length": 15.697674751281738, "blob_id": "caf0ff106a72793e79910c9111cd39937c04d5c8", "content_id": "94293053a9bfb8909e423f83c55ed0b937d14e1d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 717, "license_type": "no_license", "max_line_length": 30, "num_lines": 43, "path": "/requirements.txt", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "aniso8601==8.0.0\nappdirs==1.4.4\nastroid==2.3.3\ncertifi==2019.9.11\nchardet==3.0.4\nClick==7.0\ncolorama==0.4.3\ndecorator==4.4.0\ndistlib==0.3.1\nentrypoints==0.3\nfilelock==3.0.12\nflake8==3.7.9\nFlask==1.1.1\nFlask-JWT-Extended==3.25.0\nFlask-MySQL==1.5.1\nFlask-RESTful==0.3.8\nFlask-SQLAlchemy==2.4.4\nidna==2.8\nisort==4.3.21\nitsdangerous==1.1.0\nJinja2==2.10.3\nlazy-object-proxy==1.4.3\nMarkupSafe==1.1.1\nmccabe==0.6.1\nmysql-connector-python==8.0.21\npaho-mqtt==1.5.1\nprotobuf==3.13.0\npsycopg2==2.8.6\npy==1.8.0\npycodestyle==2.5.0\npyflakes==2.1.1\nPyJWT==1.7.1\npylint==2.4.4\nPyMySQL==0.10.1\npytz==2020.4\nrequests==2.22.0\nretry==0.9.2\nsix==1.14.0\nSQLAlchemy==1.3.20\nurllib3==1.25.6\nvirtualenv==20.0.31\nWerkzeug==0.16.0\nwrapt==1.11.2" }, { "alpha_fraction": 0.6748030185699463, "alphanum_fraction": 0.681722104549408, "avg_line_length": 49, "blob_id": "dab83e5a51ce98c51622444fa5a29a31ad71e2ae", "content_id": "bb5efa4b29ff8a94e7a1aa171ffa3a72c264d109", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5237, "license_type": "no_license", "max_line_length": 136, "num_lines": 104, "path": "/resources/vendedor.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from flask.helpers import make_response\nfrom flask_restful import Resource, reqparse\nfrom flask import render_template,request\nfrom models.vendedor import VendedorModel\nfrom werkzeug.security import safe_str_cmp\nimport traceback\nimport os\n\natributos = reqparse.RequestParser()\natributos.add_argument('nome_vendedor', type=str, required=True, help=\"Ei! o seu 'nome' é obrigatório!\")\natributos.add_argument('telefone_vendedor', type=str, required=True, help=\"Ei! o seu 'telefone' é obrigatório!\")\natributos.add_argument('cnpj_vendedor', type=str, required=True, help=\"Ei! o seu 'cnpj' é obrigatório!\")\natributos.add_argument('email_vendedor', type=str, required=True, help=\"Ei! o seu 'e-mail' é obrigatório!\")\natributos.add_argument('senha_vendedor', type=str, required=True, help=\"Ei! a sua 'senha' é obrigatória!\")\natributos.add_argument('endereco_vendedor', type=str, required=True, help=\"Ei! o seu 'endereço' é obrigatório!\")\natributos.add_argument('numero_end_vendedor', type=str, required=True, help=\"Ei! o seu 'número de endereço' é obrigatório!\")\natributos.add_argument('complemento_vendedor', type=str, required=False)\natributos.add_argument('bairro_vendedor', type=str, required=True, help=\"Ei! o seu 'bairro' é obrigatório!\")\natributos.add_argument('cep_vendedor', type=str, required=True, help=\"Ei! o seu 'cep' é obrigatório!\")\natributos.add_argument('ativado', type=bool)\n\natributos_login = reqparse.RequestParser()\natributos_login.add_argument('email_vendedor', type=str, required=True, help=\"Ei! o seu 'e-mail' é obrigatório!\")\natributos_login.add_argument('senha_vendedor', type=str, required=True, help=\"Ei! a sua 'senha' é obrigatória!\")\natributos.add_argument('ativado', type=bool)\n\n\nclass Vendedores(Resource):\n def get(self, id_vendedor):\n vendedor = VendedorModel.achar_vendedor(id_vendedor)\n if vendedor:\n return vendedor.json()\n return make_response(render_template(\"home.html\", message= \"Vendedor não encontrado.\"), 404)\n\n def put(self, id_vendedor):\n dados = atributos.parse_args()\n vendedor = VendedorModel.achar_vendedor(id_vendedor)\n if vendedor:\n vendedor.atualizar_vendedor(dados)\n vendedor.salvar_vendedor()\n return {\"message\": \"Vendedor atualizado com sucesso!\"}, 200\n vendedor = VendedorModel(dados)\n vendedor.salvar_vendedor()\n return make_response(render_template(\"home.html\", message=\"Vendedor criado com sucesso!\"), 201)\n\n def delete(self, id_vendedor):\n vendedor = VendedorModel.achar_vendedor(id_vendedor)\n if vendedor:\n vendedor.deletar_vendedor()\n return {\"message\": \"Vendedor deletado com sucesso!\"}, 200\n return make_response(render_template(\"home.html\", message=\"Vendedor não encontrado.\"), 404)\n\n\nclass VendedorRegistro(Resource):\n def post(self):\n dados = atributos.parse_args()\n if VendedorModel.achar_por_login(dados['email_vendedor']):\n return {\"message\": \"O seu login '{}' já existe\".format(dados['email_vendedor'])}\n vendedor = VendedorModel(dados)\n vendedor.ativado = False\n try:\n vendedor.salvar_vendedor()\n vendedor.enviar_email_confirmacao_vendedor()\n except:\n vendedor.deletar_vendedor()\n traceback.print_exc()\n return make_response(render_template(\"cadastro_vendedores.html\", message='Erro interno de servidor'), 500)\n return make_response(render_template(\"login_vendedor.html\", message=\"Sucesso! Cadastro pendente de confirmação via email\"), 201)\n\n\nclass VendedorLogin(Resource):\n @classmethod\n def post(cls):\n dados = atributos_login.parse_args()\n user = VendedorModel.achar_por_login(dados['email_vendedor'])\n if user and safe_str_cmp(user.senha_vendedor, dados['senha_vendedor']):\n if user.ativado:\n r = make_response(render_template(\"home_login.html\", message='Login realizado com sucesso!'), 200)\n r.set_cookie(\"login\", dados[\"email_vendedor\"], samesite=\"Strict\")\n r.set_cookie(\"senha\", dados[\"senha_vendedor\"], samesite=\"Strict\")\n # r.set_cookie(\"ativado\", dados[\"ativado\"], samesite=\"Strict\")\n return r\n return make_response(render_template(\"login.html\", message='Usuário não confirmado, por favor verifique seu e-mail'), 400)\n return make_response(render_template(\"login.html\", message='Usuário ou senha incorretos.'), 401)\n\n\nclass VendedorLogout(Resource):\n def post(self):\n r = make_response(render_template(\"cadastro_vendedores.html\", message=\"Deslogou com sucesso!\"))\n r.set_cookie(\"email_vendedor\", \"\")\n r.set_cookie(\"senha_vendedor\", \"\")\n return r\n\n\nclass VendedorConfirmado(Resource):\n @classmethod\n def get(cls, id_vendedor):\n vendedor = VendedorModel.achar_vendedor(id_vendedor)\n if not vendedor:\n return {'message': 'Vendedor não encontrado'}, 404\n vendedor.ativado = True\n vendedor.salvar_vendedor()\n headers = {'Content-Type': 'text/html'}\n return make_response(render_template('usuario_confirmado.html'), 200, headers)\n\n\n\n" }, { "alpha_fraction": 0.6630350351333618, "alphanum_fraction": 0.6710765361785889, "avg_line_length": 38.336734771728516, "blob_id": "07dcd0d9444d247c951efe3b98ba0e431a29d054", "content_id": "80bfdacc274659a51b2407fc879c98a62cd02284", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3872, "license_type": "no_license", "max_line_length": 111, "num_lines": 98, "path": "/resources/produtos.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from flask_restful import Resource, reqparse\nfrom flask import render_template,request\nfrom models.produtos import ProdutosModel\nfrom flask.helpers import make_response\nfrom werkzeug.security import safe_str_cmp\nimport random\nimport sqlite3\nimport os \n# import traceback\n\natributos = reqparse.RequestParser()\natributos.add_argument('nome_produto', type=str, required=True, help=\"Ei! o 'nome' é obrigatório!\")\natributos.add_argument('codigo_produto', type=str, required=True, help=\"Ei! o 'Codigo' é obrigatório!\")\natributos.add_argument('descricao_produto', type=str, required=False)\natributos.add_argument('preco_produto', type=float, required=True, help=\"Ei! o 'preço' é obrigatório!\")\natributos.add_argument('tipo_produto', type=str, required=True, help=\"Ei! o 'tipo' é obrigatório!\")\natributos.add_argument('filtro_produto', type=str, required=True, help=\"Ei! o 'filtro' é obrigatório!\")\natributos.add_argument('quantidade_produto', type=str, required=True, help=\"Ei! a 'quantidade' é obrigatória!\")\n\n\nclass Produto(Resource):\n def put(self, id_produto):\n dados = atributos.parse_args()\n produto = ProdutosModel.listar_por_id(id_produto)\n if produto:\n produto.atualizar_produto(dados)\n produto.salvar_produto()\n return make_response(render_template(\"home.html\", message=\"Produto atualizado com sucesso!\"), 200)\n produto = ProdutosModel(dados)\n produto.salvar_produto()\n return make_response(render_template(\"home.html\", message=\"Produto criado com sucesso!\"), 201)\n\n def delete(self, id_produto):\n produto = ProdutosModel.listar_por_id(id_produto)\n if produto:\n produto.deletar_produto()\n return make_response(render_template(\"home.html\", message=\"Produto deletado com sucesso!\"), 200)\n return make_response(render_template(\"home.html\", message=\"Produto não encontrado!\"), 404)\n\n\nclass ProdutosRegistro(Resource):\n def post(self):\n dados = atributos.parse_args()\n if ProdutosModel.achar_por_codigo(dados['codigo_produto']):\n return make_response(render_template(\"home.html\", message=\"Você já cadastrou esse produto!\"), 409)\n produtos = ProdutosModel(dados)\n produtos.salvar_produto()\n return make_response(render_template(\"home.html\", message=\"Produto cadastrado com sucesso!\"), 201)\n\n\nclass ProdutosBuscaSimples(Resource):\n def get(self):\n return {'produto': [produto.json() for produto in ProdutosModel.query.all()]}\n\n\ndef listar_produtos():\n banco = sqlite3.connect(\"banco.db\")\n cursor = banco.cursor()\n consulta = \"SELECT nome_produto,preco_produto,descricao_produto, tipo_produto, filtro_produto FROM produto\"\n cursor.execute(consulta)\n resultado = cursor.fetchall()\n produtos = []\n for linha in resultado:\n produtos.append({\n 'nome_produto': linha[0],\n 'preco_produto': linha[1],\n 'descricao_produto': linha[2],\n 'tipo_produto': linha[3],\n 'filtro_produto': linha[4]})\n return produtos\n\n\ndef extensao_arquivo(filename):\n if '.' not in filename: \n return ''\n return filename.rsplit('.', 1)[1].lower()\n\n\ndef salvar_arquivo_upload():\n import uuid\n if \"foto\" in request.files:\n foto = request.files[\"foto\"]\n e = extensao_arquivo(foto.filename)\n if e in ['jpg', 'jpeg', 'png', 'gif', 'svg', 'webp']:\n u = uuid.uuid1()\n n = f\"{u}.{e}\"\n foto.save(os.path.join(\"fotos_produtos\", n))\n return n\n return \"\"\n\n\"\"\"\nclass ProdutosBuscaFiltro(Resource):\n def get(self, filtro_produto):\n produtos = ProdutosModel.listar_produtos_especifico(filtro_produto)\n if produtos:\n return produtos.json()\n return make_response(render_template(\"home.html\", message=\"Produto não encontrado.\"), 404)\n\"\"\"\n" }, { "alpha_fraction": 0.6944230794906616, "alphanum_fraction": 0.7013461589813232, "avg_line_length": 49, "blob_id": "cc61d7fcdcaba31ae02b87cc3968ba49951a2f45", "content_id": "f1b0b1899fa0db6e78be45aaea524fb55310dffa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5237, "license_type": "no_license", "max_line_length": 127, "num_lines": 104, "path": "/resources/entregador.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from flask_restful import Resource, reqparse\nfrom flask import render_template\nfrom models.entregador import EntregadorModel\nfrom flask.helpers import make_response\nfrom werkzeug.security import safe_str_cmp\nimport traceback\n\n\natributos = reqparse.RequestParser()\natributos.add_argument('nome_entregador', type=str, required=True, help=\"Ei! o seu 'nome' é obrigatório!\")\natributos.add_argument('cpf_entregador', type=str, required=True, help=\"Ei! o seu 'cpf' é obrigatório!\")\natributos.add_argument('telefone_entregador', type=str, required=True, help=\"Ei! o seu 'telefone' é obrigatório!\")\natributos.add_argument('cnh_entregador', type=str, required=True, help=\"Ei! a sua 'cnh' é obrigatória!\")\natributos.add_argument('email_entregador', type=str, required=True, help=\"Ei! o seu 'e-mail' é obrigatório!\")\natributos.add_argument('senha_entregador', type=str, required=True, help=\"Ei! a sua 'senha' é obrigatória!\")\natributos.add_argument('endereco_entregador', type=str, required=True, help=\"Ei! o seu 'endereço' é obrigatório!\")\natributos.add_argument('numero_end_entregador', type=str, required=True, help=\"Ei! o seu 'número de endereço' é obrigatório!\")\natributos.add_argument('complemento_entregador', type=str, required=False)\natributos.add_argument('bairro_entregador', type=str, required=True, help=\"Ei! o seu 'bairro' é obrigatório!\")\natributos.add_argument('cep_entregador', type=str, required=True, help=\"Ei! o seu 'cep' é obrigatório!\")\natributos.add_argument('ativado', type=bool)\n\n\natributos_login = reqparse.RequestParser()\natributos_login.add_argument('email_entregador', type=str, required=True, help=\"Ei! o seu 'e-mail' é obrigatório!\")\natributos_login.add_argument('senha_entregador', type=str, required=True, help=\"Ei! a sua 'senha' é obrigatória!\")\natributos.add_argument('ativado', type=bool)\n\n\nclass Entregadores(Resource):\n def get(self, id_entregador):\n entregador = EntregadorModel.achar_entregador(id_entregador)\n if entregador:\n return entregador.json()\n return make_response(render_template(\"home.html\", message=\"Entregador não encontrado.\"), 404)\n\n def put(self, id_entregador):\n dados = atributos.parse_args()\n entregador = EntregadorModel.achar_entregador(id_entregador)\n if entregador:\n entregador.atualizar_entregador(dados)\n entregador.salvar_entregador()\n return {\"message\": \"Entregador atualizado com sucesso!\"}, 200\n entregador = EntregadorModel(dados)\n entregador.salvar_entregador()\n return make_response(render_template(\"home.html\", message=\"Entregador criado com sucesso!\"), 201)\n\n def delete(self, id_entregador):\n entregador = EntregadorModel.achar_entregador(id_entregador)\n if entregador:\n entregador.deletar_entregador()\n return make_response(render_template(\"home.html\", message='Entregador deletado com sucesso!'), 200)\n return make_response(render_template(\"home.html\", message='Entregador não encontrado!'), 404)\n\n\nclass EntregadorRegistro(Resource):\n def post(self):\n dados = atributos.parse_args()\n if EntregadorModel.achar_por_login(dados['email_entregador']):\n return {\"message\": \"O seu login '{}' já existe\".format(dados['email_entregador'])}\n entregador = EntregadorModel(*dados)\n entregador.ativado = False\n try:\n entregador.salvar_entregador()\n entregador.enviar_confirmacao_email_entregador()\n except:\n entregador.deletar_entregador()\n traceback.print_exc()\n return make_response(render_template(\"cadastro_entregador.html\", message='Erro interno de servidor'), 500)\n return make_response(render_template(\"login.html\", message=\"Sucesso! Cadastro pendente de confirmação via email\"), 201)\n\n\nclass EntregadorLogin(Resource):\n @classmethod\n def post(cls):\n dados = atributos_login.parse_args()\n entregador = EntregadorModel.achar_por_login(dados['email_entregador'])\n if entregador and safe_str_cmp(entregador.senha_entregador, dados['senha_entregador']):\n if entregador.ativado:\n return make_response(render_template(\"home.html\", message='Login realizado com sucesso!'), 200)\n return make_response(render_template(\"login.html\", message='Usuário não confirmado'), 400)\n return make_response(render_template(\"login.html\", message='Usuário ou senha incorretos.'), 401)\n\n\nclass EntregadorLogout(Resource):\n def post(self):\n r = make_response(render_template(\"cadastro_entregador.html\", message=\"Deslogou com sucesso!\"))\n r.set_cookie(\"email_entregador\", \"\")\n r.set_cookie(\"senha_entregador\", \"\")\n return r\n\n\nclass EntregadorConfirmado(Resource):\n @classmethod\n def get(cls, id_entregador):\n entregador = EntregadorModel.achar_entregador(id_entregador)\n\n if not entregador:\n return {'message': 'Usuário não encontrado'}, 404\n\n entregador.ativado = True\n entregador.salvar_entregador()\n headers = {'Content-Type': 'text/html'}\n return make_response(render_template('usuario_confirmado.html'), 200, headers)\n" }, { "alpha_fraction": 0.6351843476295471, "alphanum_fraction": 0.6399635672569275, "avg_line_length": 42.07843017578125, "blob_id": "45b98c2293d17d22bc9b84457c3503ea2737890b", "content_id": "a9d9f1cf82cb4ec965d15f9abcb89e858f4257c5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4396, "license_type": "no_license", "max_line_length": 204, "num_lines": 102, "path": "/models/usuario.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from operator import imod\nfrom flask.helpers import url_for\nfrom sql_alchemy import banco\nfrom flask import request\nfrom requests import post\nimport mailgun\ndomain = mailgun.MAILGUN_DOMAIN\napi_key = mailgun.MAILGUN_API_KEY\nfrom_title = mailgun.FROM_TITLE\nfrom_email = mailgun.FROM_EMAIL \n\n\nclass UsuarioModel(banco.Model):\n __tablename__ = 'usuarios'\n id_usuario = banco.Column(banco.Integer, primary_key=True)\n nome_usuario = banco.Column(banco.String(50))\n telefone_usuario = banco.Column(banco.String(11))\n cpf_usuario = banco.Column(banco.String(11))\n email_usuario = banco.Column(banco.String(50), nullable=False, unique=True)\n senha_usuario = banco.Column(banco.String(30), nullable=False)\n endereco_usuario = banco.Column(banco.String(40))\n numero_end_usuario = banco.Column(banco.String(10))\n complemento_usuario = banco.Column(banco.String(30))\n bairro_usuario = banco.Column(banco.String(20))\n cep_usuario = banco.Column(banco.String(8))\n ativado = banco.Column(banco.Boolean, default=False)\n\n def __init__(self, nome_usuario, telefone_usuario, cpf_usuario, email_usuario, senha_usuario, endereco_usuario, numero_end_usuario, complemento_usuario, bairro_usuario, cep_usuario, ativado):\n self.nome_usuario = nome_usuario\n self.telefone_usuario = telefone_usuario\n self.cpf_usuario = cpf_usuario\n self.email_usuario = email_usuario\n self.senha_usuario = senha_usuario\n self.endereco_usuario = endereco_usuario\n self.numero_end_usuario = numero_end_usuario\n self.complemento_usuario = complemento_usuario\n self.bairro_usuario = bairro_usuario\n self.cep_usuario = cep_usuario\n self.ativado = ativado\n\n def enviar_confirmacao_email(self):\n \n link = request.url_root[:-1] + url_for('usuarioconfirmado',id_usuario=self.id_usuario)\n return post('https://api.mailgun.net/v3/{}/messages'.format(domain),\n auth=('api', api_key),\n data={'from': '{} <{}>'.format(from_title, from_email),\n 'to': self.email_usuario,\n 'subject': 'Confirmação de Cadastro',\n 'text': 'Confirme seu cadastro clicando no link a seguir: {}'.format(link),\n 'html': '<html><p>\\\n Confirme seu cadastro clicando no link a seguir:<a href=\"{}\">CONFIRMAR EMAIL</a>\\\n </p><html>'.format(link)\n })\n\n def json(self):\n return {\n 'nome_usuario': self.nome_usuario,\n 'telefone_usuario': self.telefone_usuario,\n 'cpf_usuario': self.cpf_usuario,\n 'email_usuario': self.email_usuario,\n 'endereco_usuario': self.endereco_usuario,\n 'numero_end_usuario': self.numero_end_usuario,\n 'complemento_usuario': self.complemento_usuario,\n 'bairro_usuario': self.bairro_usuario,\n 'cep_usuario': self.cep_usuario,\n 'ativado': self.ativado\n }\n\n @classmethod\n def achar_usuario(cls, id_usuario):\n usuario = cls.query.filter_by(id_usuario=id_usuario).first() # SELECT FROM usuario WHERE id_usuario = $id_usuario\n if usuario:\n return usuario\n return None\n\n @classmethod\n def achar_por_login(cls, email_usuario):\n usuario = cls.query.filter_by(email_usuario=email_usuario).first()\n if usuario:\n return usuario\n return None\n\n def salvar_usuario(self):\n banco.session.add(self)\n banco.session.commit()\n\n def atualizar_usuario(self, nome_usuario, telefone_usuario, cpf_usuario, email_usuario, senha_usuario, endereco_usuario, numero_end_usuario, complemento_usuario, bairro_usuario, cep_usuario, ativado):\n self.nome_usuario = nome_usuario\n self.telefone_usuario = telefone_usuario\n self.cpf_usuario = cpf_usuario\n self.email_usuario == email_usuario\n self.senha_usuario == senha_usuario\n self.endereco_usuario = endereco_usuario\n self.numero_end_usuario = numero_end_usuario\n self.complemento_usuario = complemento_usuario\n self.bairro_usuario = bairro_usuario\n self.cep_usuario = cep_usuario\n self.ativado == ativado\n\n def deletar_usuario(self):\n banco.session.delete(self)\n banco.session.commit()\n" }, { "alpha_fraction": 0.6439964771270752, "alphanum_fraction": 0.6508640050888062, "avg_line_length": 43.69306945800781, "blob_id": "1fb0854036daabf6a1525773e61a5938e2fffc28", "content_id": "9096265af9820c709a09a4fbe4bd5827ce169df5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4516, "license_type": "no_license", "max_line_length": 216, "num_lines": 101, "path": "/models/vendedor.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from sql_alchemy import banco\nfrom flask import url_for\nfrom flask import request\nfrom requests import post\nimport mailgun\n\ndomain = mailgun.MAILGUN_DOMAIN \nsite_key = mailgun.MAILGUN_API_KEY\nfrom_title = mailgun.FROM_TITLE\nfrom_email = mailgun.FROM_EMAIL\n\nclass VendedorModel(banco.Model):\n __tablename__ = 'vendedores'\n id_vendedor = banco.Column(banco.Integer, primary_key=True)\n nome_vendedor = banco.Column(banco.String(50))\n telefone_vendedor = banco.Column(banco.String(11))\n cnpj_vendedor = banco.Column(banco.String(14))\n email_vendedor = banco.Column(banco.String(50))\n senha_vendedor = banco.Column(banco.String(30))\n endereco_vendedor = banco.Column(banco.String(40))\n numero_end_vendedor = banco.Column(banco.String(10))\n complemento_vendedor = banco.Column(banco.String(30))\n bairro_vendedor = banco.Column(banco.String(20))\n cep_vendedor = banco.Column(banco.String(8))\n ativado = banco.Column(banco.Boolean, default=False)\n\n def __init__(self, nome_vendedor, telefone_vendedor, cnpj_vendedor, email_vendedor, senha_vendedor, endereco_vendedor, numero_end_vendedor, complemento_vendedor, bairro_vendedor, cep_vendedor, ativado):\n self.nome_vendedor = nome_vendedor\n self.telefone_vendedor = telefone_vendedor\n self.cnpj_vendedor = cnpj_vendedor\n self.email_vendedor = email_vendedor\n self.senha_vendedor = senha_vendedor\n self.endereco_vendedor = endereco_vendedor\n self.numero_end_vendedor = numero_end_vendedor\n self.complemento_vendedor = complemento_vendedor\n self.bairro_vendedor = bairro_vendedor\n self.cep_vendedor = cep_vendedor\n self.ativado = ativado\n\n def enviar_email_confirmacao_vendedor(self):\n #http://127.0.0.1:5000/confirmacao_vendedor/\n link_vendedor = request.url_root[:-1] + url_for('vendedorconfirmado', id_vendedor=self.id_vendedor)\n return post('https://api.mailgun.net/v3/{}/messages'.format(domain),\n auth=('api', site_key),\n data={'from': '{} <{}>'.format(from_title, from_email),\n 'to': self.email_vendedor,\n 'subject': 'Confirmação de Cadastro',\n 'text': 'Confirme seu cadastro clicando no link a seguir: {}'.format(link_vendedor),\n 'html': '<html><p>\\\n Confirme seu cadastro clicando no link a seguir:<a href=\"{}\">CONFIRMAR EMAIL</a>\\\n </p><html>'.format(link_vendedor)\n })\n\n def json(self):\n return {\n 'nome_vendedor': self.nome_vendedor,\n 'telefone_vendedor': self.telefone_vendedor,\n 'cnpj_vendedor': self.cnpj_vendedor,\n 'email_vendedor': self.email_vendedor,\n 'endereco_vendedor': self.endereco_vendedor,\n 'numero_end_vendedor': self.numero_end_vendedor,\n 'complemento_vendedor': self.complemento_vendedor,\n 'bairro_vendedor': self.bairro_vendedor,\n 'cep_vendedor': self.cep_vendedor,\n 'ativado': self.ativado\n }\n\n @classmethod\n def achar_vendedor(cls, id_vendedor):\n vendedor = cls.query.filter_by(id_vendedor=id_vendedor).first() # SELECT * FROM vendedor WHERE id_vendedor = $id_vendedor\n if vendedor:\n return vendedor\n return None\n\n @classmethod\n def achar_por_login(cls, email_vendedor):\n vendedor = cls.query.filter_by(email_vendedor=email_vendedor).first()\n if vendedor:\n return vendedor\n return None\n\n def salvar_vendedor(self):\n banco.session.add(self)\n banco.session.commit()\n\n def atualizar_vendedor(self, nome_vendedor, telefone_vendedor, cnpj_vendedor, email_vendedor, senha_vendedor, endereco_vendedor, numero_end_vendedor, complemento_vendedor, bairro_vendedor, cep_vendedor, ativado):\n self.nome_vendedor = nome_vendedor\n self.telefone_vendedor = telefone_vendedor\n self.cnpj_vendedor = cnpj_vendedor\n self.email_vendedor == email_vendedor\n self.senha_vendedor == senha_vendedor\n self.endereco_vendedor = endereco_vendedor\n self.numero_end_vendedor = numero_end_vendedor\n self.complemento_vendedor = complemento_vendedor\n self.bairro_vendedor = bairro_vendedor\n self.cep_vendedor = cep_vendedor\n self.ativado == ativado\n\n def deletar_vendedor(self):\n banco.session.delete(self)\n banco.session.commit()\n" }, { "alpha_fraction": 0.7158253788948059, "alphanum_fraction": 0.7158253788948059, "avg_line_length": 41.69013977050781, "blob_id": "8ff2a946af70daadc3bc38173bac3ac78c2b3f3c", "content_id": "c9fe486255a55455d3502b2dea406edfdfb48390", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 9098, "license_type": "no_license", "max_line_length": 236, "num_lines": 213, "path": "/app.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from werkzeug.exceptions import PreconditionRequired\nfrom models.entregador import EntregadorModel\nfrom models.vendedor import VendedorModel\nfrom flask import Flask, render_template, request, flash, redirect, url_for, send_from_directory\nfrom flask_restful import Api\nfrom models.usuario import UsuarioModel\nfrom resources.vendedor import Vendedores, VendedorConfirmado, VendedorRegistro, VendedorLogin, VendedorLogout\nfrom resources.usuario import UsuarioConfirmado, Usuarios, UsuarioRegistro, UsuarioLogin, UsuarioLogout\nfrom resources.entregador import Entregadores, EntregadorConfirmado, EntregadorRegistro, EntregadorLogin, EntregadorLogout\nfrom resources.produtos import Produto, ProdutosRegistro, ProdutosBuscaSimples, listar_produtos\nfrom werkzeug.security import safe_str_cmp\nimport secretkeys\nimport requests\nimport json\nimport werkzeug\n\n\n\napp = Flask(__name__, template_folder='templates')\napp.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///banco.db'\napp.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False\napi = Api(app)\n\n\ndef is_human_vendedor(captcha_response):\n\n \"\"\" Validating recaptcha response from google server\n Returns True captcha test passed for submitted form else returns False.\n \"\"\"\n secret = secretkeys.SECRET_KEY_VENDEDOR\n payload = {'response': captcha_response, 'secret': secret}\n response = requests.post(\"https://www.google.com/recaptcha/api/siteverify\", payload)\n response_text = json.loads(response.text)\n return response_text['success']\n\n\ndef is_human_usuario(captcha_response):\n\n \"\"\"Validating recaptcha response from google server\n Returns True captcha test passed for submitted form else returns False.\"\"\"\n secret = secretkeys.SECRET_KEY_USUARIO\n payload = {'response': captcha_response, 'secret': secret}\n response = requests.post(\"https://www.google.com/recaptcha/api/siteverify\", payload)\n response_text = json.loads(response.text)\n return response_text['success']\n\n\ndef is_human_entregador(captcha_response):\n # Validating recaptcha response from google server\n # Returns True captcha test passed for submitted form else returns False.\n secret = secretkeys.SECRET_KEY_ENTREGADOR\n payload = {'response': captcha_response, 'secret': secret}\n response = requests.post(\"https://www.google.com/recaptcha/api/siteverify\", payload)\n response_text = json.loads(response.text)\n return response_text['success']\n\n\[email protected]_first_request\ndef cria_banco():\n banco.create_all()\n\n\[email protected]('/home')\ndef home():\n return render_template('home.html')\n\[email protected]('/home_login')\ndef main_home():\n #if login_ok_vend(request):\n return render_template('home_login.html')\n #return render_template('login.html', message=\"Sem autorização\")\"\"\"\n\n\[email protected]('/')\ndef login():\n return render_template('login.html')\n\n\[email protected](\"/login_vendedor\")\ndef login_vendedor():\n return render_template('login_vendedor.html')\n\n\[email protected]('/cadastros')\ndef cadastros():\n return render_template('cadastros.html')\n\n\[email protected]('/cadastro_vendedor')\ndef vendedor():\n if request.method == 'POST':\n nome_vendedor = request.form['nome_vendedor']\n telefone_vendedor = request.form['telefone_vendededor']\n cnpj_vendedor = request.form['cnpj_vendedor']\n email_vendedor = request.form['email_vendedor']\n senha_vendedor = request.form['senha_vendedor']\n endereco_vendedor = request.form['endereco_vendedor']\n numero_end_vendedor = request.form['numero_end_vendedor']\n complemento_vendedor = request.form['complemento_vendedor']\n bairro_vendedor = request.form['bairro_vendedor']\n cep_vendedor = request.form['cep_vendedor']\n captcha_response = request.form['g-recaptcha-response']\n if is_human_vendedor(captcha_response):\n VendedorModel(nome_vendedor, telefone_vendedor, cnpj_vendedor, email_vendedor, senha_vendedor, endereco_vendedor, numero_end_vendedor, complemento_vendedor, bairro_vendedor, cep_vendedor)\n status = 'Enviado com sucesso'\n else:\n status = 'Im not a robot não pode ficar vazio!.'\n flash(status)\n return render_template('cadastro_vendedores.html', sitekey=secretkeys.sitekey_vendedor)\n\n\[email protected]('/cadastro_usuario', methods=[\"GET\", \"POST\"])\ndef usuario():\n if request.method == 'POST':\n nome_usuario = request.form['nome_usuario']\n telefone_usuario = request.form['telefone_usuario']\n cpf_usuario = request.form['cpf_usuario']\n email_usuario = request.form['email_usuario']\n senha_usuario = request.form['senha_usuario']\n endereco_usuario = request.form['endereco_usuario']\n numero_end_usuario = request.form['numero_end_usuario']\n complemento_usuario = request.form['complemento_usuario']\n bairro_usuario = request.form['bairro_usuario']\n cep_usuario = request.form['cep_usuario']\n captcha_response = request.form['g-recaptcha-response']\n if is_human_usuario(captcha_response):\n UsuarioModel(nome_usuario, telefone_usuario, cpf_usuario, email_usuario, senha_usuario, endereco_usuario, numero_end_usuario, complemento_usuario, bairro_usuario, cep_usuario)\n status = 'Enviado com sucesso'\n else:\n status = 'Im not a robot não pode ficar vazio!.'\n flash(status)\n return render_template('cadastro_usuario.html',sitekey=secretkeys.sitekey_usuario)\n\n\[email protected]('/cadastro_entregador', methods=[\"GET\", \"POST\"])\ndef entregador():\n if request.method == 'POST':\n nome_entregador = request.form['nome_entregador']\n cpf_entregador = request.form['cpf_entregador']\n telefone_entregador = request.form['telefone_entregador']\n cnh_entregador = request.form['cnh_entregador']\n email_entregador = request.form['email_entregador']\n senha_entregador = request.form['senha_entregador']\n endereco_entregador = request.form['endereco_entregador']\n numero_end_entregador = request.form['numero_end_entregador']\n complemento_entregador = request.form['complemento_entregador']\n bairro_entregador = request.form['bairro_entregador']\n cep_entregador = request.form['cep_entregador']\n captcha_response = request.form['g-recaptcha-response']\n if is_human_entregador(captcha_response):\n EntregadorModel(nome_entregador, cpf_entregador, telefone_entregador, cnh_entregador, email_entregador, senha_entregador, endereco_entregador, numero_end_entregador, complemento_entregador, bairro_entregador, cep_entregador)\n status = 'Enviado com sucesso'\n else:\n status = 'Im not a robot não pode ficar vazio!'\n flash(status)\n return redirect(url_for('cadastro_entregador'))\n return render_template('cadastro_entregador.html', sitekey=secretkeys.sitekey_entregador)\n\n\[email protected]('/produtos')\ndef produtos():\n produtos = listar_produtos()\n #if login_ok(request):\n return render_template('produtos.html', produtos=produtos)\n\n\[email protected]('/produtos/registro')\ndef registro():\n #logado = login_ok_vend()\n #if logado is None:\n #return render_template('home.html')\n return render_template('registro_produtos.html')\n\n\ndef login_ok(req):\n login = req.cookies.get(\"login\")\n senha = req.cookies.get(\"senha\")\n user = UsuarioModel.achar_por_login(login)\n return user is not None and safe_str_cmp(user.senha_usuario, senha)\n\n\ndef login_ok_vend(request):\n login = request.cookies.get(\"login\")\n senha = request.cookies.get(\"senha\")\n ativado = request.cookies.get(\"ativado\")\n user = VendedorModel.achar_por_login(login)\n return user is not None and safe_str_cmp(user.senha_vendedor, senha)\n\n\napi.add_resource(VendedorRegistro, '/vendedor_cadastro') # POST\napi.add_resource(VendedorLogin, '/vendedor_login') # POST\napi.add_resource(VendedorLogout, '/logout') # POST\napi.add_resource(Vendedores, '/vendedores/<int:id_vendedor>') # GET\napi.add_resource(Usuarios, '/usuarios/<int:id_usuario>')\napi.add_resource(UsuarioRegistro, '/usuario_cadastro') # POST\napi.add_resource(UsuarioLogin, '/usuario_login') # POST\napi.add_resource(UsuarioLogout, '/logout') # POST\napi.add_resource(Entregadores, '/entregador/<int:id_entregador>')\napi.add_resource(EntregadorRegistro, '/entregador_cadastro') # POST\napi.add_resource(EntregadorLogin, '/entregador_login') # POST\napi.add_resource(EntregadorLogout, '/logout') # POST\napi.add_resource(UsuarioConfirmado, '/confirmacao/<int:id_usuario>') # GET\napi.add_resource(VendedorConfirmado, '/confirmacao_vendedor/<int:id_vendedor>') # GET\napi.add_resource(EntregadorConfirmado, '/confirmacao_entregador/<int:id_entregador>') # GET\napi.add_resource(Produto, '/produto/<int:id_produto>') # POST\napi.add_resource(ProdutosRegistro, '/produto/registro') # POST\napi.add_resource(ProdutosBuscaSimples, '/produto/busca') # GET\n# api.add_resource(ProdutosBuscaFiltro, '/produto/busca/<string:filtro_produto>') # GET\n\nif __name__ == '__main__':\n from sql_alchemy import banco\n banco.init_app(app)\n app.run(debug=True)\n" }, { "alpha_fraction": 0.6683107018470764, "alphanum_fraction": 0.6732429265975952, "avg_line_length": 39.54999923706055, "blob_id": "2fbe7626cc012ecb9601cd854d078102322f7a0f", "content_id": "c5d3a77fd1991d29de88b3bf61bdc6dcf7ee26f5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3245, "license_type": "no_license", "max_line_length": 146, "num_lines": 80, "path": "/models/produtos.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from sql_alchemy import banco\nimport random\n\n\nclass ProdutosModel(banco.Model):\n __tablename__ = 'produto'\n id_produto = banco.Column(banco.Integer, primary_key=True)\n nome_produto = banco.Column(banco.String(50), nullable=False)\n codigo_produto = banco.Column(banco.String(8), unique=True, nullable=False)\n descricao_produto = banco.Column(banco.String(100))\n preco_produto = banco.Column(banco.Float(precision=2))\n tipo_produto = banco.Column(banco.String(15))\n filtro_produto = banco.Column(banco.String(10))\n quantidade_produto = banco.Column(banco.String(10))\n\n def __init__(self, nome_produto, codigo_produto, descricao_produto, preco_produto, tipo_produto, filtro_produto, quantidade_produto):\n self.nome_produto = nome_produto\n self.codigo_produto = codigo_produto\n self.descricao_produto = descricao_produto\n self.preco_produto = preco_produto\n self.tipo_produto = tipo_produto\n self.filtro_produto = filtro_produto\n self.quantidade_produto = quantidade_produto\n\n def json(self):\n return {\n 'nome_produto': self.nome_produto,\n 'codigo_produto': self.codigo_produto,\n 'descricao_produto': self.descricao_produto,\n 'preco_produto': self.preco_produto,\n 'tipo_produto': self.tipo_produto,\n 'filtro_produto': self.filtro_produto,\n 'quantidade_produto': self.quantidade_produto\n }\n\n @classmethod\n def listar_por_id(cls, id_produto):\n produto = cls.query.filter_by(id_produto=id_produto).first() # SELECT * FROM produto WHERE id_produto = $id_produto\n if produto:\n return produto\n return None\n\n @classmethod\n def achar_por_codigo(cls, codigo_produto):\n codigo = cls.query.filter_by(codigo_produto=codigo_produto).first()\n if codigo:\n return codigo\n return None\n\n \"\"\"criar um @classmethod, def, de produtos, buscar apenas produtos em uma barra de buscas, retornar por nome\n (fazer checagem via nome, se um produto se chamar \"shampoo cachorro 200 ml\", e o usuário digitar \"shampoo\", retornar\n todos os produtos com \"shampoo\" no nome, independente se for na primeira ou ultima string, complicadinho, sim) \"\"\"\n # @classmethod\n # def listar_produtos_busca(cls, nome_produto):\n\n\n @classmethod\n def listar_produtos_especifico(cls, filtro_produto):\n produto_especifico = cls.query.filter_by(filtro_produto=filtro_produto)\n if produto_especifico:\n return produto_especifico\n return None\n\n\n def salvar_produto(self):\n banco.session.add(self)\n banco.session.commit()\n\n def atualizar_produto(self, nome_produto, codigo_produto, descricao_produto, preco_produto, tipo_produto, filtro_produto, quantidade_produto):\n self.nome_produto = nome_produto\n self.codigo_produto = codigo_produto\n self.descricao_produto = descricao_produto\n self.preco_produto = preco_produto\n self.tipo_produto = tipo_produto\n self.filtro_produto = filtro_produto\n self.quantidade_produto = quantidade_produto\n\n def deletar_produto(self):\n banco.session.delete(self)\n banco.session.commit()\n" }, { "alpha_fraction": 0.6469293832778931, "alphanum_fraction": 0.6539307832717896, "avg_line_length": 46.160377502441406, "blob_id": "10448ef5fb4b50ef22202476a10ea36146b30da4", "content_id": "fed183b9a8c2c848ad8c422cdc1b9a6db4c31ef8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5001, "license_type": "no_license", "max_line_length": 253, "num_lines": 106, "path": "/models/entregador.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from sql_alchemy import banco\nfrom flask import request\nfrom requests import post\nfrom flask.helpers import url_for\nimport mailgun\n\ndomain = mailgun.MAILGUN_DOMAIN\napi_key = mailgun.MAILGUN_API_KEY\ntitle = mailgun.FROM_TITLE\nemail = mailgun.FROM_EMAIL\n\n\nclass EntregadorModel(banco.Model):\n __tablename__ = 'entregador'\n id_entregador = banco.Column(banco.Integer, primary_key=True)\n nome_entregador = banco.Column(banco.String(200))\n cpf_entregador = banco.Column(banco.String(12))\n telefone_entregador = banco.Column(banco.String(11))\n cnh_entregador = banco.Column(banco.String(100))\n email_entregador = banco.Column(banco.String(50))\n senha_entregador = banco.Column(banco.String(30))\n endereco_entregador = banco.Column(banco.String(40))\n numero_end_entregador = banco.Column(banco.String(10))\n complemento_entregador = banco.Column(banco.String(30))\n bairro_entregador = banco.Column(banco.String(20))\n cep_entregador = banco.Column(banco.String(8))\n ativado = banco.Column(banco.Boolean, default=False)\n\n def __init__(self, nome_entregador, cpf_entregador, telefone_entregador, cnh_entregador, email_entregador, senha_entregador, endereco_entregador, numero_end_entregador, complemento_entregador, bairro_entregador, cep_entregador, ativado):\n self.nome_entregador = nome_entregador\n self.cpf_entregador = cpf_entregador\n self.telefone_entregador = telefone_entregador\n self.cnh_entregador = cnh_entregador\n self.email_entregador = email_entregador\n self.senha_entregador = senha_entregador\n self.endereco_entregador = endereco_entregador\n self.numero_end_entregador = numero_end_entregador\n self.complemento_entregador = complemento_entregador\n self.bairro_entregador = bairro_entregador\n self.cep_entregador = cep_entregador\n self.ativado = ativado\n\n def enviar_confirmacao_email_entregador(self):\n # http://127.0.0.1:5000/confirmacao_entregador/\n link = request.url_root[:-1] + url_for('entregadorconfirmado', id_entregador=self.id_entregador)\n return post('https://api.mailgun.net/v3/{}/messages'.format(domain),\n auth=('api', api_key),\n data={'from': '{} <{}>'.format(title, email),\n 'to': self.email_entregador,\n 'subject': 'Confirmação de Cadastro',\n 'text': 'Confirme seu cadastro clicando no link a seguir: {}'.format(link),\n 'html': '<html><p>\\\n Confirme seu cadastro clicando no link a seguir:<a href=\"{}\">CONFIRMAR EMAIL</a>\\\n </p><html>'.format(link)\n })\n\n def json(self):\n return {\n 'nome_entregador': self.nome_entregador,\n 'cpf_entregador': self.cpf_entregador,\n 'telefone_entregador': self.telefone_entregador,\n 'cnh_entregador': self.cnh_entregador,\n 'email_entregador': self.email_entregador,\n 'endereco_entregador': self.endereco_entregador,\n 'numero_end_entregador': self.numero_end_entregador,\n 'complemento_entregador': self.complemento_entregador,\n 'bairro_entregador': self.numero_end_entregador,\n 'cep_entregador': self.cep_entregador,\n 'ativado': self.ativado\n }\n\n @classmethod\n def achar_entregador(cls, id_entregador):\n entregador = cls.query.filter_by(id_entregador=id_entregador).first() # SELECT * FROM usuario WHERE id_usuario = $id_usuario\n if entregador:\n return entregador\n return None\n\n @classmethod\n def achar_por_login(cls, email_entregador):\n entregador = cls.query.filter_by(email_entregador=email_entregador).first()\n if entregador:\n return entregador\n return None\n\n def salvar_entregador(self):\n banco.session.add(self)\n banco.session.commit()\n\n def atualizar_entregador(self, nome_entregador, cpf_entregador, telefone_entregador, cnh_entregador, email_entregador, senha_entregador, endereco_entregador, numero_end_entregador, complemento_entregador, bairro_entregador, cep_entregador, ativado):\n if email_entregador == email_entregador:\n if senha_entregador == senha_entregador:\n self.nome_entregador = nome_entregador\n self.cpf_entregador = cpf_entregador\n self.telefone_entregador = telefone_entregador\n self.cnh_entregador = cnh_entregador\n self.endereco_entregador = endereco_entregador\n self.numero_end_entregador = numero_end_entregador\n self.complemento_entregador = complemento_entregador\n self.bairro_entregador = bairro_entregador\n self.cep_entregador = cep_entregador\n self.ativado == ativado\n\n def deletar_entregador(self):\n banco.session.delete(self)\n banco.session.commit()\n" }, { "alpha_fraction": 0.6693262457847595, "alphanum_fraction": 0.6746453642845154, "avg_line_length": 29.37837791442871, "blob_id": "a78c58b96aecbcbfcab9301677e13491ef35886d", "content_id": "539241725e3c8810872421c1d14b955246f11104", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 1128, "license_type": "no_license", "max_line_length": 81, "num_lines": 37, "path": "/static/js/main.js", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "let carts = document.querySelectorAll('.btn-cart');\nlet name_product = document.getElementById(\"product-name\")\nlet price_product = document.getElementById(\"product-price\")\nlet products = [{\n name:name_product,\n price:price_product,\n inCart:0\n}]\n\nfor (let i=0; i < carts.length; i++){\n carts[i].addEventListener('click', () =>{\n cartNumbers(products[i])\n })\n}\n\nfunction onLoadCartNumbers() {\n let productNumbers = localStorage.getItem('cartNumbers')\n if (productNumbers) {\n document.querySelector('.carrinho span').textContent = productNumbers;\n }\n}\n\nfunction cartNumbers(product){\n console.log(\"the product clicked is \", product)\n let productNumbers = localStorage.getItem('cartNumbers')\n productNumbers = parseInt(productNumbers)\n\n if(productNumbers){\n localStorage.setItem('cartNumbers',productNumbers + 1)\n document.querySelector('.carrinho span').textContent = productNumbers + 1\n } else{\n localStorage.setItem('cartNumbers',1)\n document.querySelector('.carrinho span').textContent = 1\n }\n }\n\n onLoadCartNumbers()\n " }, { "alpha_fraction": 0.6656169891357422, "alphanum_fraction": 0.6727022528648376, "avg_line_length": 46.48598098754883, "blob_id": "b239d1ece755cf9183271c63fab35556c572caa9", "content_id": "757b71dae40064a76fe7f73dcaf247854d287a95", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5120, "license_type": "no_license", "max_line_length": 127, "num_lines": 107, "path": "/resources/usuario.py", "repo_name": "andreyhitoshi1997/AC-Desenvolvimento-Sistemas", "src_encoding": "UTF-8", "text": "from flask_restful import Resource, reqparse\nfrom flask import render_template\nfrom models.usuario import UsuarioModel\nfrom flask.helpers import make_response\nfrom werkzeug.security import safe_str_cmp\nimport traceback\n\n\natributos = reqparse.RequestParser()\natributos.add_argument('nome_usuario', type=str, required=True, help=\"Ei! o seu 'nome' é obrigatório!\")\natributos.add_argument('telefone_usuario', type=str, required=True, help=\"Ei! o seu 'telefone' é obrigatório!\")\natributos.add_argument('cpf_usuario', type=str, required=True, help=\"Ei! o seu 'cpf' é obrigatório!\")\natributos.add_argument('email_usuario', type=str, required=True, help=\"Ei! o seu 'e-mail' é obrigatório!\")\natributos.add_argument('senha_usuario', type=str, required=True, help=\"Ei! a sua 'senha' é obrigatória!\")\natributos.add_argument('endereco_usuario', type=str, required=True, help=\"Ei! o seu 'endereço' é obrigatório!\")\natributos.add_argument('numero_end_usuario', type=str, required=True, help=\"Ei! o seu 'número de endereço' é obrigatório!\")\natributos.add_argument('complemento_usuario', type=str, required=False)\natributos.add_argument('bairro_usuario', type=str, required=True, help=\"Ei! o seu 'bairro' é obrigatório!\")\natributos.add_argument('cep_usuario', type=str, required=True, help=\"Ei! o seu 'cep' é obrigatório!\")\natributos.add_argument('ativado', type=bool)\n\natributos_login = reqparse.RequestParser()\natributos_login.add_argument('email_usuario', type=str, required=True, help=\"Ei! o seu 'e-mail' é obrigatório!\")\natributos_login.add_argument('senha_usuario', type=str, required=True, help=\"Ei! a sua 'senha' é obrigatória!\")\natributos_login.add_argument('ativado', type=bool)\n\n\nclass Usuarios(Resource):\n def get(self, id_usuario):\n usuario = UsuarioModel.achar_usuario(id_usuario)\n if usuario:\n return usuario.json()\n return make_response(render_template(\"home.html\", message=\"Usuário não encontrado.\"), 404)\n\n def put(self, id_usuario):\n dados = atributos.parse_args()\n usuario = UsuarioModel.achar_usuario(id_usuario)\n if usuario:\n usuario.atualizar_usuario(dados)\n usuario.salvar_usuario()\n return {\"message\": \"Usuário atualizado com sucesso!\"}, 200\n usuario = UsuarioModel(dados)\n usuario.salvar_usuario()\n return make_response(render_template(\"home.html\", message=\"Vendedor criado com sucesso!\"), 201)\n\n def delete(self, id_usuario):\n user = UsuarioModel.achar_usuario(id_usuario)\n if user:\n user.deletar_usuario()\n return make_response(render_template(\"home.html\", message='Usuário deletado com sucesso!'), 200)\n return make_response(render_template(\"home.html\", message='Usuário não encontrado!'), 404)\n\n\nclass UsuarioRegistro(Resource):\n def post(self):\n dados = atributos.parse_args()\n if UsuarioModel.achar_por_login(dados['email_usuario']):\n return {\"message\": \"O seu login '{}' já existe\".format(dados['email_usuario'])}\n user = UsuarioModel(**dados)\n user.ativado = False\n try:\n user.salvar_usuario()\n user.enviar_confirmacao_email()\n except:\n user.deletar_usuario()\n traceback.print_exc()\n return make_response(render_template(\"cadastro_usuario.html\", message='Erro interno de servidor'), 500)\n return make_response(render_template(\"login.html\", message=\"Sucesso! Cadastro pendente de confirmação via email\"), 201)\n\n\nclass UsuarioLogin(Resource):\n @classmethod\n def post(cls):\n dados = atributos_login.parse_args()\n user = UsuarioModel.achar_por_login(dados['email_usuario'])\n if user and safe_str_cmp(user.senha_usuario, dados['senha_usuario']):\n if user.ativado:\n r = make_response(render_template(\"home.html\", message='Login realizado com sucesso!'), 200)\n r.set_cookie(\"login\", dados['email_usuario'], samesite=\"Strict\")\n r.set_cookie(\"senha\", dados['senha_usuario'], samesite=\"Strict\")\n return r\n return make_response(render_template(\"login.html\", message='Usuário não confirmado'), 400)\n return make_response(render_template(\"login.html\", message='Usuário ou senha incorretos.'), 401)\n\n\nclass UsuarioLogout(Resource):\n def post(self):\n r = make_response(render_template(\"cadastro_usuario.html\", message=\"Deslogou com sucesso!\"))\n r.set_cookie(\"email_usuario\", \"\")\n r.set_cookie(\"senha\", \"\")\n # jwt_id = get_raw_jwt()['jti'] # JWT Token Identifier\n # BLACKLIST.add(jwt_id)\n return r\n\n\nclass UsuarioConfirmado(Resource):\n @classmethod\n def get(cls, id_usuario):\n user = UsuarioModel.achar_usuario(id_usuario)\n\n if not user:\n return {'message': 'Usuário não encontrado'}, 404\n\n user.ativado = True\n user.salvar_usuario()\n headers = {'Content-Type': 'text/html'}\n return make_response(render_template('usuario_confirmado.html', email='email_usuario'), 200, headers)\n" } ]	11
carl-di-ortus/filestat	https://github.com/carl-di-ortus/filestat	e6e901fce1236c1f2ed152af174b85a59a972e5a	e9f478dcc3f45677aa0c54aba10d9d45abff8b88	5e2e5f61964380c714b0c2235c41b8f39376a571	refs/heads/master	2016-09-06T18:39:11.099222	2014-04-01T07:48:25	2014-04-01T07:48:25	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.589304506778717, "alphanum_fraction": 0.5945732593536377, "avg_line_length": 27.97709846496582, "blob_id": "3ebe0b2be9b8667bc7d5aec087f91e6aae54990b", "content_id": "39217ac39d3808938ae61f864ba05811f4d493f6", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3796, "license_type": "permissive", "max_line_length": 75, "num_lines": 131, "path": "/filestat.py", "repo_name": "carl-di-ortus/filestat", "src_encoding": "UTF-8", "text": "#! /usr/bin/python3\n\n\"\"\"Recursively read files in a directory and calculate its statistics.\"\"\"\n\n# Scripted by Carl di Ortus \| [email protected]\n# Available in MIT license (see LICENCE)\n\n\nimport argparse\nimport copy\nimport mimetypes\nimport os\nimport tempfile\n\n\ndef get_file_list(directory):\n \"\"\"Returns a list of file paths in a given directory.\n Hidden directories and hidden files are ommited.\n File is accepted if its mimetype is None or text.\"\"\"\n\n filelist = []\n\n for root, dirs, files in os.walk(directory):\n dirs[:] = [d for d in dirs if not d[0] == '.']\n for filename in files:\n if (not filename.startswith('.') and\n mimetypes.guess_type(filename)[0] is None):\n filelist.append(os.path.join(root, filename))\n elif (not filename.startswith('.') and\n mimetypes.guess_type(filename)[0].startswith('text')):\n filelist.append(os.path.join(root, filename))\n\n return filelist\n\n\ndef calc_file_stats(filename):\n \"\"\"Calculates file statistics and returns two dictionaries\n with words and chars usage.\"\"\"\n # TODO: sort dicts (by count or by abc)\n # TODO: not possible, must convert to list or tuple!\n\n words = {}\n chars = {}\n\n f = open(filename)\n\n for line in f.readlines():\n line = line.strip()\n for char in line:\n if not char in chars.keys():\n chars[char] = 1\n else:\n chars[char] += 1\n # TODO: other separators & is it necessary\n for word in line.split(' '):\n if not word in words.keys():\n words[word] = 1\n else:\n words[word] += 1\n\n f.close()\n return words, chars\n\n\ndef dictadd(dict1, dict2):\n \"\"\"Adds two dictionaries like in set algebra.\n Returns new dictionary.\"\"\"\n\n result = copy.deepcopy(dict1)\n\n for key in dict2.keys():\n if key in result.keys():\n result[key] += dict2[key]\n else:\n result[key] = dict2[key]\n\n return result\n\n\ndef write_stats(words, chars, filehandle, context):\n \"\"\"Writes the dictionaries to a file.\"\"\"\n\n filehandle.write(bytes('\\n'+context+'\\n\\nWords usage:\\n', 'UTF-8'))\n for key in words:\n filehandle.write(bytes('\\\"'+key+'\\\": %d\\n' % words[key], 'UTF-8'))\n filehandle.write(bytes('\\nChars usage:\\n', 'UTF-8'))\n for key in chars:\n filehandle.write(bytes('\\\"'+key+'\\\": %d\\n' % chars[key], 'UTF-8'))\n\n return\n\n\ndef main():\n parser = argparse.ArgumentParser(description=\"\"\"\n Recursively read files in a directory and calculate its statistics.\n Statistics are written to a provided filename.\n (Always overwritten if file is present)\"\"\")\n parser.add_argument('filename', metavar='<filename>', type=str,\n help='location to save the statistics')\n parser.add_argument('directory', metavar='<dir>', type=str,\n help='root directory for recursive file search')\n args = parser.parse_args()\n\n filelist = get_file_list(args.directory)\n tmp = tempfile.TemporaryFile()\n totalwords = {}\n totalchars = {}\n\n for f in filelist:\n words, chars = calc_file_stats(f)\n write_stats(words, chars, tmp, f)\n totalwords = dictadd(totalwords, words)\n totalchars = dictadd(totalchars, chars)\n\n handle = open(args.filename, 'wb')\n write_stats(totalwords, totalchars, handle, \"TOTAL\")\n tmp.seek(0, 0)\n for line in tmp.readlines():\n handle.write(line)\n\n tmp.close\n handle.close()\n\n print('%d files treated\\n' % len(filelist))\n print('%d total different words\\n' % len(totalwords))\n print('%d total different chars\\n' % len(totalchars))\n return\n\n\nif __name__ == '__main__':\n main()\n" }, { "alpha_fraction": 0.7884615659713745, "alphanum_fraction": 0.7884615659713745, "avg_line_length": 25, "blob_id": "b38ba4b1ec5cac69d30dd239ff78e72d058f2493", "content_id": "4f3aa9da62f13f90f7b229affa6fb037f58023a5", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 113, "license_type": "permissive", "max_line_length": 84, "num_lines": 4, "path": "/README.md", "repo_name": "carl-di-ortus/filestat", "src_encoding": "UTF-8", "text": "filestat\n========\n\nApskaičiuoti nurodytoje direktorijoje esančių failų statistiką ir ją išvesti į failą\n" } ]	2
mtreviso/deepbond	https://github.com/mtreviso/deepbond	f3d23de8955f8ff1085b24fe53ebb7ff722a2a7f	a36ccb71e4457889d340920260f18666835d703f	9daf1ecdfc69a1a97998465fae2102f0f2845eb0	refs/heads/master	2023-04-07T22:58:34.650115	2023-03-15T16:27:58	2023-03-15T16:27:58	114,040,073	17	2	null	null	null	null	null	[ { "alpha_fraction": 0.6964341998100281, "alphanum_fraction": 0.7358788251876831, "avg_line_length": 28.579439163208008, "blob_id": "51c1466d4451c09e1a15d67ceea69e240355df3e", "content_id": "8136046567adf3ec07334fab6ec95fb4bb706682", "detected_licenses": [ "MIT", "LicenseRef-scancode-unknown-license-reference" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 3177, "license_type": "permissive", "max_line_length": 257, "num_lines": 107, "path": "/README.md", "repo_name": "mtreviso/deepbond", "src_encoding": "UTF-8", "text": "# deepbond\nDeep neural approach to Boundary and Disfluency Detection\n\nThis is part of my MSc project. More info:\n\\\n[My dissertation (ptbr)](http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05022018-090740/pt-br.php)\n • \n[EACL paper](http://www.aclweb.org/anthology/E17-1030)\n • \n[STIL paper](http://aclweb.org/anthology/W17-6618)\n • \n[PROPOR paper](https://www.researchgate.net/publication/327223308_Sentence_Segmentation_and_Disfluency_Detection_in_Narrative_Transcripts_from_Neuropsychological_Tests_13th_International_Conference_PROPOR_2018_Canela_Brazil_September_24-26_2018_Proceedings)\n • \n[LREC paper](https://www.aclweb.org/anthology/2020.lrec-1.317.pdf)\n\n\n# Installation \n\nFirst, clone this repository using `git`:\n\n```sh\ngit clone https://github.com/mtreviso/deepbond.git\n```\n\n Then, `cd` to the DeepBond folder:\n```sh\ncd deepbond\n```\n\nCreate a Python virtualenv and install all dependencies \nusing:\n```sh\npython3 -m venv env\nsource env/bin/activate\npip install -r requirements.txt\n```\n\nRun the install command:\n```sh\npython3 setup.py install\n```\n\nPlease note that since Python 3 is required, all the above commands (pip/python) \nhave to be bounded to the Python 3 version.\n\n\n\n# Data\nThe data should be put in a folder called `data` in the root dir. Here is the basic ingredients that you might need:\n\n- Corpus (see license): https://github.com/nilc-nlp/DNLT-BP\n- Word embeddings (word2vec skipgram): https://www.dropbox.com/s/rw3ti4ebctufp4j/embeddings.zip?dl=1\n- Prosodic information (only for Control and MCI): https://www.dropbox.com/s/0gmt2o2xeah13xk/prosodic.zip?dl=1 \n\nYou can also send me an e-mail if you have any questions!\n\n\n\n\n# Usage\nYou can use deepbond in two ways:\n* Via CLI interface ([example](https://github.com/mtreviso/deepbond/blob/master/experiments/train_ccl_rcnn_crf.sh))\n* Import as a library ([example](https://github.com/mtreviso/deepbond/blob/master/experiments/example_training_cinderela.py))\n\nThe full list of arguments (CLI) and options (lib) can be seen via:\n```sh\npython3 -m deepbond --help\n```\n\nTake a look at the `experiments` folder for more examples.\n\n\n# License\nMIT.\n\n\n# Cite\n\nIf you use deepbond, you can cite this paper:\n\n```\n@inproceedings{treviso2018sentence,\n author = \"Marcos Vinícius Treviso and Sandra Maria Aluísio\",\n title = \"Sentence Segmentation and Disfluency Detection in Narrative Transcripts from Neuropsychological Tests\",\n booktitle = \"Computational Processing of the Portuguese Language (PROPOR)\",\n year = \"2018\",\n publisher = \"Springer International Publishing\",\n pages = \"409--418\",\n}\n```\n\nOr the more recent publication (results without prosodic information + CRF)\n```\n@inproceedings{casanova-etal-2020-evaluating,\n title = \"Evaluating Sentence Segmentation in Different Datasets of Neuropsychological Language Tests in {B}razilian {P}ortuguese\",\n author = {Casanova, Edresson and\n Treviso, Marcos and\n H{\\\"u}bner, Lilian and\n Alu{\\'\\i}sio, Sandra},\n booktitle = \"Proceedings of The 12th Language Resources and Evaluation Conference (LREC)\",\n year = \"2020\",\n address = \"Marseille, France\",\n publisher = \"European Language Resources Association\",\n pages = \"2605--2614\",\n ISBN = \"979-10-95546-34-4\",\n}\n```\n\n\n\n\n" }, { "alpha_fraction": 0.6839897632598877, "alphanum_fraction": 0.6851549744606018, "avg_line_length": 30.792593002319336, "blob_id": "c6fb75641b217e68acd13719c1601b630676ffae", "content_id": "20c2ae4f93954e322fa6a655a9aed0fa196efda2", "detected_licenses": [ "MIT", "LicenseRef-scancode-unknown-license-reference" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4291, "license_type": "permissive", "max_line_length": 111, "num_lines": 135, "path": "/deepbond/predict_util.py", "repo_name": "mtreviso/deepbond", "src_encoding": "UTF-8", "text": "import os, re\nfrom deepbond import constants\nfrom deepbond import iterator\nfrom deepbond import models\nfrom deepbond.dataset import dataset, fields\nfrom deepbond.predicter import Predicter\nfrom deepbond import opts\nimport argparse\nimport logging\n\nlogger = logging.getLogger(__name__)\n\nclass SentenceBoundaryDetector(object):\n\n\tdef __init__(self, load='', gpu_id=None, prediction_type= \"classes\"):\n\t\t# \n\t\tparser = argparse.ArgumentParser(description='DeepBond')\n\t\topts.general_opts(parser)\n\t\topts.preprocess_opts(parser)\n\t\topts.model_opts(parser)\n\t\topts.train_opts(parser)\n\t\topts.predict_opts(parser)\n\n\t\tself.options = parser.parse_args()\n\n\t\t# set predict opts\n\t\tself.options.gpu_id = gpu_id\n\t\tself.options.prediction_type = prediction_type\n\t\tself.options.load = load \n\t\t\n\n\tdef detect(self,text=None, test_path = None):\n\n\t\tself.options.text = text\n\t\tself.options.test_path = test_path\n\n\t\twords_field = fields.WordsField()\n\t\ttags_field = fields.TagsField()\n\t\tfields_tuples = [('words', words_field), ('tags', tags_field)]\n\n\t\tdataset_iter = None\n\t\tsave_dir_path = None\n\n\t\tif self.options.test_path is None and self.options.text is None:\n\t\t\traise Exception('You should inform a path to test data or a text.')\n\n\t\tif self.options.test_path is not None and self.options.text is not None:\n\t\t\traise Exception('You cant inform both a path to test data and a text.')\n\n\n\t\tif self.options.test_path is not None and self.options.text is None:\n\t\t\tlogger.info('Building test dataset: {}'.format(self.options.test_path))\n\t\t\ttest_tuples = list(filter(lambda x: x[0] != 'tags', fields_tuples))\n\t\t\ttest_dataset = dataset.build(self.options.test_path, test_tuples, self.options)\n\n\t\t\tlogger.info('Building test iterator...')\n\t\t\tdataset_iter = iterator.build(test_dataset, self.options.gpu_id,\n\t\t\t\t\t\t\t\t\t\tself.options.dev_batch_size, is_train=False)\n\t\t\tsave_dir_path = self.options.test_path\n\n\t\tif self.options.text is not None and self.options.test_path is None:\n\t\t\tlogger.info('Preparing text...')\n\t\t\ttest_tuples = list(filter(lambda x: x[0] != 'tags', fields_tuples))\n\t\t\ttest_dataset = dataset.build_texts(self.options.text, test_tuples, self.options)\n\n\t\t\tlogger.info('Building iterator...')\n\t\t\tdataset_iter = iterator.build(test_dataset, self.options.gpu_id,self.options.dev_batch_size, is_train=False)\n\t\t\tsave_dir_path = None\n\n\n\n\t\tlogger.info('Loading vocabularies...')\n\t\tfields.load_vocabs(self.options.load, fields_tuples)\n\n\t\tlogger.info('Loading model...')\n\t\tmodel = models.load(self.options.load, fields_tuples, self.options.gpu_id)\n\n\t\tlogger.info('Predicting...')\n\t\tpredicter = Predicter(dataset_iter, model)\n\t\tpredictions = predicter.predict(self.options.prediction_type)\n\n\t\tlogger.info('Preparing to save...')\n\t\tif self.options.prediction_type == 'classes':\n\t\t\tprediction_tags = transform_classes_to_tags(tags_field, predictions)\n\t\t\tpredictions_str = transform_predictions_to_text(prediction_tags)\n\t\telse:\n\t\t\tpredictions_str = transform_predictions_to_text(predictions)\n\t\twords_labels = None\t\n\t\tif self.options.text is not None:\n\t\t\torig_words = self.options.text.split()\n\t\t\tlabels = predictions_str.split()\n\t\t\tprint(orig_words , labels)\n\t\t\twords_labels = join_words_and_labels(orig_words, labels)\n \t\n\t\treturn predictions,predictions_str,words_labels\n\n\n\ndef transform_classes_to_tags(tags_field, predictions):\n tagged_predicitons = []\n for preds in predictions:\n tags_preds = [tags_field.vocab.itos[c] for c in preds]\n tagged_predicitons.append(tags_preds)\n return tagged_predicitons\n\n\ndef transform_predictions_to_text(predictions):\n text = []\n is_prob = isinstance(predictions[0][0], list)\n for pred in predictions:\n sentence = []\n for p in pred:\n if is_prob:\n sentence.append(', '.join(['%.8f' % c for c in p]))\n else:\n sentence.append(p)\n if is_prob:\n text.append(' \| '.join(sentence))\n else:\n text.append(' '.join(sentence))\n return '\\n'.join(text)\n\n\n\t\n\ndef join_words_and_labels(words, labels):\n new_text = []\n assert len(words) == len(labels)\n for word, label in zip(words, labels):\n if label == '_':\n new_text.append(word)\n else:\n new_text.append(word)\n new_text.append(label)\n return new_text" }, { "alpha_fraction": 0.42583730816841125, "alphanum_fraction": 0.660287082195282, "avg_line_length": 13.928571701049805, "blob_id": "68fcf6f784b70fcc9fcdbaf8592c2ae720191b97", "content_id": "02dc86b27a5fa4a194ac3bf25a376e1d995b8bdc", "detected_licenses": [ "MIT", "LicenseRef-scancode-unknown-license-reference" ], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 209, "license_type": "permissive", "max_line_length": 21, "num_lines": 14, "path": "/requirements.txt", "repo_name": "mtreviso/deepbond", "src_encoding": "UTF-8", "text": "future==0.18.3\nnltk==3.8.1\nnumpy==1.24.2\npandas==1.5.3\npytest==7.2.1\nPyYAML==6.0\nscikit-learn==1.2.1\nscipy==1.10.0\nsentencepiece==0.1.97\nsix==1.16.0\ntorch==1.13.1\ntorchtext==0.5.0\ntqdm==4.64.1\ntyping==3.7.4.3\n" } ]	3
TheFakeWater/AlarmClock	https://github.com/TheFakeWater/AlarmClock	3ea4b986c3cab830a9d43a15d788cca807a62bb2	5ca786ca74dac59323f20c06510e482409d7029e	a2ec246d5ebbe4ae4d9a10e600da32894b672694	refs/heads/master	2022-11-10T11:49:12.235083	2020-06-20T12:28:35	2020-06-20T12:28:35	273,703,092	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5208333134651184, "alphanum_fraction": 0.7083333134651184, "avg_line_length": 15.333333015441895, "blob_id": "b0a86fb2d9aaaeef94ce96e3ed8366972da00900", "content_id": "5448fb378a21e5b9b8fd3277bfd7bb123611e364", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 48, "license_type": "no_license", "max_line_length": 19, "num_lines": 3, "path": "/requirements.txt", "repo_name": "TheFakeWater/AlarmClock", "src_encoding": "UTF-8", "text": "pyfiglet~=0.8.post1\nplaysound~=1.2.2\ngTTS~=2.1.1" }, { "alpha_fraction": 0.7878788113594055, "alphanum_fraction": 0.7878788113594055, "avg_line_length": 15.5, "blob_id": "67a4dadad6d4c1d9da5489535fbfa687292d07d7", "content_id": "d7218d4a69a99d598ed75d9eebfff3dff3268c69", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 33, "license_type": "no_license", "max_line_length": 19, "num_lines": 2, "path": "/README.md", "repo_name": "TheFakeWater/AlarmClock", "src_encoding": "UTF-8", "text": "# AlarmClock\nA funny alarm clock\n" }, { "alpha_fraction": 0.6136950850486755, "alphanum_fraction": 0.6343669295310974, "avg_line_length": 23.967741012573242, "blob_id": "32de55997c241a3e78f8d55c47f19c9636bcf42a", "content_id": "2496d9f772d3b91b17104d614721ad0a9bd7a1ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 774, "license_type": "no_license", "max_line_length": 65, "num_lines": 31, "path": "/AlarmClock.py", "repo_name": "TheFakeWater/AlarmClock", "src_encoding": "UTF-8", "text": "import time\nfrom time import sleep\n\nimport pyfiglet\nfrom gtts import gTTS\nfrom playsound import playsound\n\nTime = time.strftime(\"%H:%M\")\nprint(pyfiglet.figlet_format(\"Alarm Clock\"))\nalarm = input(\"Choose your time to wake up: (Example: 6:30) -> \")\n\n\nwhile Time != alarm:\n Time = time.strftime(\"%H:%M\")\n sleep(1)\n\nif Time == alarm:\n tts = gTTS(\"WAKE UP !\", lang='en')\n tts.save(\"wakeup.mp3\")\n tts = gTTS(\"It is {}\".format(Time), lang='en')\n tts.save('timeis.mp3')\n tts = gTTS(\"I said WAKE UP !\", lang='en')\n tts.save('wakeup2.mp3')\n playsound('timeis.mp3')\n playsound(\"wakeup.mp3\")\n sleep(2)\n playsound('wakeup2.mp3')\n sleep(5)\n playsound('giant.mp3')\n print(pyfiglet.figlet_format(\"Chicken Time !\"))\n playsound('chicken.mp3')\n" } ]	3
katherinechandler/week4-bill-calculator	https://github.com/katherinechandler/week4-bill-calculator	8893e89f5aa7789617b1861d65bf619872502316	b38d032985b470a259f921b8df371fcfc2b6c383	c39b5a99f0c67837c2c7758db9a8676131416239	refs/heads/master	2018-01-01T16:44:50.373253	2016-10-22T22:44:34	2016-10-22T22:44:34	71,668,591	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6785110235214233, "alphanum_fraction": 0.7021996378898621, "avg_line_length": 31.83333396911621, "blob_id": "9ffe9f78cee35f993b6434dcc9bff3180be4db9f", "content_id": "2cac7b011c8c054ad922e57c63cc300c51364ef3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 591, "license_type": "no_license", "max_line_length": 80, "num_lines": 18, "path": "/bill_calculator_v2.py", "repo_name": "katherinechandler/week4-bill-calculator", "src_encoding": "UTF-8", "text": "\ntip_amount = 0\ntotal_bill = 0\nsplit_amount = 0\n\ndef calculate_bill(original_bill_amount, tip_percentage = 18, split_number = 1):\n\tglobal tip_amount\n\tglobal total_bill\n\tglobal split_amount\n\t\n\ttip_amount = tip_amount + original_bill_amount(tip_percentage.01)\n\ttotal_bill = total_bill + original_bill_amount + tip_amount\n\tsplit_amount = split_amount + (total_bill / split_number)\n\n\tprint \"Your tip amount is \" + str(tip_amount) + \" dollars.\"\n\tprint \"Your total bill is \" + str(total_bill) + \" dollars.\"\n\tprint \"Each person owes \" + str(split_amount) + \" dollars.\"\n\ncalculate_bill(100, 18, 2)" }, { "alpha_fraction": 0.6909233331680298, "alphanum_fraction": 0.6948356628417969, "avg_line_length": 38.9375, "blob_id": "e75f5c3771c21fd4c9cbdb3ddd2ccf3c2455ec1a", "content_id": "6d9f3466ff566687de4f02429d4b5afbaefc4c81", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1278, "license_type": "no_license", "max_line_length": 88, "num_lines": 32, "path": "/bill_calculator.py", "repo_name": "katherinechandler/week4-bill-calculator", "src_encoding": "UTF-8", "text": "def calculate_tip(bill, tip_percentage):\n\ttip_amount = bill * (tip_percentage*.01)\n\treturn tip_amount\n\ndef calculate_total_bill(bill, calculate_tip):\n\ttotal_bill = bill + calculate_tip\n\treturn total_bill\n\ndef split_bill(calculate_total_bill, number_people):\n\tamount_per_person = calculate_total_bill / number_people\n\treturn amount_per_person\n\ndef main():\n\tintent = int(raw_input(\"Would you like to 1- calculate a tip, or 2- split the bill? \"))\n\tif intent == 1:\n\t\tbill = int(raw_input(\"What is your bill amount? \"))\n\t\tpercentage = int(raw_input(\"What percentage would you like to tip? \"))\t\t\n\t\ttip_amount = calculate_tip(bill, percentage)\t\t\n\t\tprint \"The tip amount is \" + str(tip_amount) + \" dollars.\"\n\t\ttotal_bill = calculate_total_bill(bill, tip_amount)\n\t\tprint \"The total bill is \" + str(total_bill) + \" dollars.\"\n\telse:\n\t\tnumber_people = int(raw_input(\"How many people are paying? \"))\n\t\tbill = int(raw_input(\"What is your bill amount? \"))\n\t\tpercentage = int(raw_input(\"What percentage would you like to tip? \"))\n\t\ttip_amount = calculate_tip(bill, percentage)\n\t\ttotal_bill = calculate_total_bill(bill, tip_amount)\n\t\tamount_per_person = split_bill(total_bill, number_people)\n\t\tprint \"Each person owes \" + str(amount_per_person) + \" dollars.\"\n\nif __name__ == '__main__':\n\tmain()\n" } ]	2
lucsof114/EE374_Project	https://github.com/lucsof114/EE374_Project	021d3e0a7927350050a8bc8868f348db010d94b9	563beb09a8b07a196cfb2012f401c8f6bfd774f1	e6fa4cef5eb396fa751bfc7dc1357b7dd2517e7e	refs/heads/master	2022-10-21T09:05:20.673205	2020-06-12T18:56:11	2020-06-12T18:56:11	266,463,704	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6000000238418579, "alphanum_fraction": 0.800000011920929, "avg_line_length": 14, "blob_id": "04dbfcfee2fb8965fbfcbc1977c40ac8c90c0776", "content_id": "ebe5a494f0dc4628349de6dcb5721e4ca0d42243", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 30, "license_type": "no_license", "max_line_length": 15, "num_lines": 2, "path": "/README.md", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "# EE374_Project\nEE374 project\n" }, { "alpha_fraction": 0.38834038376808167, "alphanum_fraction": 0.6051951050758362, "avg_line_length": 46.261112213134766, "blob_id": "d6b769e20c7c07d826d6c91c467cc83ccdf88c21", "content_id": "85fd16b3ff18760ca96e794423a7f2236d4c2ac8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 8508, "license_type": "no_license", "max_line_length": 167, "num_lines": 180, "path": "/elastico/plotting.py", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "import numpy as np\nimport matplotlib.pyplot as plt\n\ndef labelplt(x, y, beta, str1, str2, ry, rx ) : \n # x values (list)\n # y values (list)\n # beta (list)\n # xlabel (string)\n # ylabel (string)\n # minx (int/float)\n # miny (int/float)\n for xs,ys,b in zip(x,y,beta): \n plt.annotate(r'$\\beta$: ' + str(b), (xs,ys),\n textcoords=\"offset points\", # how to position the text\n xytext=(0,10), # distance from text to points (x,y)\n ha='center') # horizontal alignment can be left, right or center\n plt.plot(xs,ys, \"r\")\n plt.xlim((rx, np.max(x) + 20))\n plt.xlabel(str1)\n plt.ylabel(str2)\n plt.ylim((ry, np.max(y) + 20))\n\n plt.show()\n\ndef plot(x, y1, y2, y3, l1, l2, l3, title, xl, yl, xmin, xmax, ymin, ymax, loc, svf):\n fig, ax = plt.subplots()\n\n # Using set_dashes() to modify dashing of an existing line\n line1, = ax.plot(x, y1, 'bo', dashes=[6, 2], label=l1)\n plt.xlabel(xl)\n plt.ylabel(yl)\n plt.xlim((xmin, xmax))\n plt.ylim((ymin, ymax))\n plt.title(title)\n #line1.set_dashes([2, 2, 10, 2]) # 2pt line, 2pt break, 10pt line, 2pt break\n\n # Using plot(..., dashes=...) to set the dashing when creating a line\n line2, = ax.plot(x, y2, 'ro', dashes=[6, 2], label=l2,)\n line3, = ax.plot(x, y3, 'go', dashes=[6, 2], label=l3,)\n\n ax.legend(loc=loc)\n plt.savefig(svf)\n\ndef vary_n():\n n_vals = [500, 1000, 1500, 2000, 4000, 7000, 10000]\n l1 = \"Beta = 0\"\n l2 = \"Beta = 0.1\"\n l3 = \"Beta = 0.2\"\n #pwr = n_vals / 100\n y1_throughput = [23.9272357271, 53.2248429901, 95.372481817, 113.907705284, 236.794848305, 424.14155015, 611.616]\n y2_throughput = [24.4430844735, 51.8189133958, 93.7532457967, 112.577048721, 234.110144015, 418.741932294, 612.9876]\n y3_throughput = [23.5134039504, 50.4943017463, 91.9905837088, 112.590186574, 239.735346739, 424.283118615, 607.4589]\n title_thru = \"Elastico Throughput vs Size of Network (bpe = 50, c = 100)\"\n yl_thru = \"Throughput (TXs per second)\"\n xl_thru = \"Number of Nodes (100x mining rate)\"\n plot(n_vals, y1_throughput, y2_throughput, y3_throughput, l1, l2, l3, title_thru, xl_thru, yl_thru, 0, 11000, 0, 700, 'lower right', 'one')\n\n y1_latency = [1.19431750426, 1.21999322756, 1.22220508486, 1.23088373824, 1.23495411738, 1.25218613204, 1.243]\n y2_latency = [1.4099739445, 1.46227068345, 1.48301892511, 1.54790991273, 1.59859782302, 1.57956471009, 1.604]\n y3_latency = [1.81701336312, 1.84078462207, 1.88524701037, 1.90540553201, 1.98923511351, 2.05782317287, 2.054]\n title_lat = \"Elastico Latency vs Size of Network (bpe = 50, c = 100)\"\n yl_lat = \"Latency (seconds)\"\n xl_lat = \"Number of Nodes (100x mining rate)\"\n plot(n_vals, y1_latency, y2_latency, y3_latency, l1, l2, l3, title_thru, xl_lat, yl_lat, 0, 11000, 0, 3, 'lower right', 'two')\n\n y1_comm = [22852.046, 39168.644, 41046.0053333, 44884.7695, 47732.01775, 48912.3865714, 49441.796]\n y2_comm = [20716.72, 35299.075, 37167.5273333, 40484.504, 43001.4125, 44092.6321429, 44567.7262]\n y3_comm = [17515.742, 31307.581, 33014.738, 36101.465, 38288.017, 39313.1842857, 39709.8979]\n for i in range(7):\n y2_comm[i] = y2_comm[i] / 0.9\n y3_comm[i] = y3_comm[i] / 0.8\n title_comm = \"Elastico Communication vs Size of Network (bpe = 50, c = 100)\"\n yl_comm = \"Communication per Node (# of messages)\"\n xl_comm = \"Number of Nodes\"\n plot(n_vals, y1_comm, y2_comm, y3_comm, l1, l2, l3, title_comm, xl_comm, yl_comm, 0, 11000, 10000, 50000, 'lower right', 'three')\n\n y1_down = [103.2, 181.95, 191.1, 209.1, 222.6375, 228.328571429, 230.75]\n y2_down = [103.5, 181.85, 191.466666667, 209.2, 222.55, 228.292857143, 230.74]\n y3_down = [101.5, 181.8, 191.233333333, 209.275, 222.3625, 228.314285714, 230.795]\n title_down = \"Elastico Downloads vs Size of Network (bpe = 50, c = 100)\"\n yl_down = \"Downloads per node (# of blks downloaded)\"\n xl_down = \"Number of Nodes\"\n plot(n_vals, y1_down, y2_down, y3_down, l1, l2, l3, title_down, xl_down, yl_down, 0, 11000, 0, 300, 'lower right', 'four')\n\ndef vary_c():\n c_vals = [50, 100, 200]\n l1 = \"Beta = 0\"\n l2 = \"Beta = 0.1\"\n l3 = \"Beta = 0.2\"\n\n y1_thru = [111.6, 52.2, 23.8]\n y2_thru = [110.4, 51.8, 23.6]\n y3_thru = [0, 53.5, 23.7]\n title_thru = \"Elastico Throughput vs Shard Size (bpe = 50, n = 1000)\"\n yl_thru = \"Throughput (TXs per second)\"\n xl_thru = \"Shard Size\"\n plot(c_vals, y1_thru, y2_thru, y3_thru, l1, l2, l3, title_thru, xl_thru, yl_thru, 0, 250, 0, 200, 'upper right', 'five')\n\n y1_lat = [1.22, 1.22, 1.21]\n y2_lat = [1.56, 1.51, 1.42]\n y3_lat = [99, 1.83, 1.73]\n title_lat = \"Elastico Latency vs Shard Size (bpe = 50, n = 1000)\"\n yl_lat = \"Latency (seconds)\"\n xl_lat = \"Shard Size\"\n plot(c_vals, y1_lat, y2_lat, y3_lat, l1, l2, l3, title_lat, xl_lat, yl_lat, 0, 250, 0, 3, 'upper right', 'six')\n\n y1_comm = [22651.6, 39251.5, 45557.0]\n y2_comm = [20435.7, 35472.3, 40519.6]\n y3_comm = [18169.8, 31232.1, 36822.7]\n for i in range(3):\n y2_comm[i] = y2_comm[i] / 0.9\n y3_comm[i] = y3_comm[i] / 0.8\n title_comm = \"Elastico Communication vs Shard Size (bpe = 50, n = 1000)\"\n yl_comm = \"Communication per Node (# of messages)\"\n xl_comm = \"Shard Size\"\n plot(c_vals, y1_comm, y2_comm, y3_comm, l1, l2, l3, title_comm, xl_comm, yl_comm, 0, 250, 0, 50000, 'lower right', 'seven')\n\ndef plot2(x1, y1, x2, y2, x3, y3, n_vals, l1, l2, l3, title, xmin, xmax, ymin, ymax, xl, yl, loc, svf):\n fig, ax = plt.subplots()\n\n # Using set_dashes() to modify dashing of an existing line\n line1, = ax.plot(x1, y1, 'bo', dashes=[6, 2], label=l1)\n plt.xlabel(xl)\n plt.ylabel(yl)\n plt.xlim((xmin, xmax))\n plt.ylim((ymin, ymax))\n words = ['n = 500', 'n = 1000', 'n = 1500', 'n = 2000', 'n = 4000', 'n = 7000', 'n = 10000']\n for i in range(len(x1)):\n ax.annotate(words[i], (x1[i],y1[i]), textcoords=\"offset points\", xytext=(10,-4))\n plt.title(title)\n #line1.set_dashes([2, 2, 10, 2]) # 2pt line, 2pt break, 10pt line, 2pt break\n\n # Using plot(..., dashes=...) to set the dashing when creating a line\n line2, = ax.plot(x2, y2, 'ro', dashes=[6, 2], label=l2,)\n for i in range(len(x2)):\n ax.annotate(words[i], (x2[i],y2[i]), textcoords=\"offset points\", xytext=(10,-4))\n line3, = ax.plot(x3, y3, 'go', dashes=[6, 2], label=l3,)\n for i in range(len(x3)):\n ax.annotate(words[i], (x3[i],y3[i]), textcoords=\"offset points\", xytext=(10,-4))\n\n ax.legend(loc=loc)\n plt.savefig(svf)\n\n\ndef plot_lat_vs_thru():\n n_vals = [500, 1000, 1500, 2000, 4000, 7000, 10000]\n l1 = \"Beta = 0\"\n l2 = \"Beta = 0.1\"\n l3 = \"Beta = 0.2\"\n #pwr = n_vals / 100\n y1_throughput = [23.9272357271, 53.2248429901, 95.372481817, 113.907705284, 236.794848305, 424.14155015, 611.616]\n y2_throughput = [24.4430844735, 51.8189133958, 93.7532457967, 112.577048721, 234.110144015, 418.741932294, 612.9876]\n y3_throughput = [23.5134039504, 50.4943017463, 91.9905837088, 112.590186574, 239.735346739, 424.283118615, 607.4589]\n \n #title_thru = \"Elastico Throughput vs Size of Network (bpe = 100, c = 100)\"\n yl_thru = \"Throughput (TXs per second)\"\n xl_thru = \"Number of Nodes\"\n #plot(n_vals, y1_throughput, y2_throughput, y3_throughput, l1, l2, l3, title_thru, xl_thru, yl_thru, 0, 8000, 0, 500, 'lower right')\n\n y1_latency = [1.19431750426, 1.21999322756, 1.22220508486, 1.23088373824, 1.23495411738, 1.25218613204, 1.243]\n y2_latency = [1.4099739445, 1.46227068345, 1.48301892511, 1.54790991273, 1.59859782302, 1.57956471009, 1.604]\n y3_latency = [1.81701336312, 1.84078462207, 1.88524701037, 1.90540553201, 1.98923511351, 2.05782317287, 2.054]\n #title_lat = \"Elastico Latency vs Size of Network (bpe = 100, c = 100)\"\n yl_lat = \"Latency (seconds)\"\n xl_lat = \"Number of Nodes\"\n #plot(n_vals, y1_latency, y2_latency, y3_latency, l1, l2, l3, title_thru, xl_lat, yl_lat, 0, 8000, 0, 3, 'lower right')\n\n title = \"Latency vs Throughput (bpe = 50, c = 100)\"\n xl = \"Latency (seconds)\"\n yl = \"Throughput (TXs per second)\"\n\n plot2(y1_latency, y1_throughput, y2_latency, y2_throughput, y3_latency, y3_throughput, n_vals, l1, l2, l3, title, 1.1, 2.6, 0, 700, xl, yl, 'lower right', 'eight')\n\ndef main():\n vary_n()\n vary_c()\n plot_lat_vs_thru()\n\nif __name__ == '__main__':\n main()\n\n" }, { "alpha_fraction": 0.5336664915084839, "alphanum_fraction": 0.5394529104232788, "avg_line_length": 25.01369857788086, "blob_id": "d9e36a89c5f093ac2008c815cebb252c0eb3f061", "content_id": "5f035d4ed5caa448b917bad3906d62bed9744067", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3802, "license_type": "no_license", "max_line_length": 83, "num_lines": 146, "path": "/prism/blocks.py", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "import networkx as nx\n\n\n\nclass SuperBlock: \n def __init__(self, numVoter): \n self.propParent = []\n self.vParent = [None for _ in range(numVoter)]\n self.loneTx = []\n self.Cvoter = [[] for _ in range(numVoter)]\n\n\nclass txBlock: \n def __init__(self, ref, ind):\n self.txs = ref\n self.ind = ind\n\nclass TxChain:\n def __init__(self, TxPerBlock) : \n self.txPerBlock = TxPerBlock\n self.txList = []\n self.txlen = 0\n \n ## to be removed \n self.curr = 0\n ## \n\n def addBlock(self): \n ## to be removed \n newtx = [i for i in range(self.curr, self.curr + self.txPerBlock)]\n ##\n\n newblock = txBlock(newtx, self.txlen)\n self.txList.append(newblock)\n self.txlen += 1\n return self.txlen - 1\n\n\n\n\nclass ProposerBlock: \n def __init__(self, ref, parent, ind, time) : \n self.ind = ind\n self.parent = parent\n self.txRefs = ref\n self.level = 0\n self.numVotes = 0\n self.revProbLow = 0 #Unknown before first sync\n self.isLeader = False\n self.time = time #time block was pushed to chain\n\n\nclass ProposerChain: \n def __init__(self): \n self.chain = nx.DiGraph()\n self.propList = []\n self.propLen = 0\n self.isgenesis = True\n self.maxlevel = 0\n\n def getTip(self):\n if self.isgenesis: \n return None\n \n g = self.chain.copy()\n path = nx.dag_longest_path(g)\n prev = len(path)\n out = []\n while len(path) == prev:\n out.append(path[-1])\n g.remove_node(path[-1])\n path = nx.dag_longest_path(g)\n return out\n\n def addBlock(self, superblk, time): \n parent = superblk.propParent\n newblock = ProposerBlock(superblk.loneTx, parent, self.propLen, time)\n self.propLen += 1\n self.chain.add_node(newblock.ind)\n if len(parent) == 0: \n self.isgenesis = False ## get rid of genesis\n else:\n newblock.level = self.propList[parent[0]].level + 1 \n self.chain.add_edge(parent[0], newblock.ind)\n if newblock.level > self.maxlevel:\n self.maxlevel = newblock.level\n self.propList.append(newblock)\n\n\n\n\n\n\nclass VoterBlock:\n def __init__(self, refs, parent, ind ):\n self.reference_link = refs\n self.parent = parent\n self.ind = ind\n self.depth = 0\n\n\nclass VoterChain: \n def __init__(self, chainID) :\n self.chain = nx.DiGraph() #Genesis block\n self.voterList = []\n self.chainLen = 0\n self.isgenesis = True\n self.chainID = chainID\n self.availableProps = []\n\n def getTip(self):\n if self.isgenesis: \n return None\n # g = self.chain.copy()\n path = nx.dag_longest_path(self.chain)\n return path[-1]\n # prev = len(path)\n # out = []\n # while len(path) == prev:\n # out.append(path[-1])\n # g.remove_node(path[-1])\n # path = nx.dag_longest_path(g)\n # return out\n \n\n def getlongestpath(self) : \n pth = nx.dag_longest_path(self.chain)\n total = len(pth)\n out = []\n for i, p in enumerate(pth):\n self.voterList[p].depth = total - i\n out.append(self.voterList[p])\n\n return out\n\n\n def addBlock(self, superblk) : \n parent = superblk.vParent[self.chainID]\n newBlock = VoterBlock(superblk.Cvoter[self.chainID], parent, self.chainLen)\n self.chainLen += 1\n self.chain.add_node(newBlock.ind)\n if parent == None: \n self.isgenesis = False\n else:\n self.chain.add_edge(parent, newBlock.ind)\n self.voterList.append(newBlock)\n\n\n\n\n" }, { "alpha_fraction": 0.6074265241622925, "alphanum_fraction": 0.6271876096725464, "avg_line_length": 27.725418090820312, "blob_id": "b1836c025815c5ee428948627ed99bb1b5b1642e", "content_id": "faec51b41619367f6259c2f67c44cb9e86642d1a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 15485, "license_type": "no_license", "max_line_length": 158, "num_lines": 539, "path": "/elastico/elastico.py", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "import numpy as np \n\n#MAX_TIME = float('inf')\nMAX_TIME = 99999999\nTX_per_blk = 40\n\nclass Node(object):\n\tdef __init__(self, id_num, l, delta, isBad=False):\n\t\tself.id = id_num\n\t\tself.l = l\n\t\tself.isBad = isBad\n\t\tself.delta = delta\n\t\tself.committee = None\n\t\tself.num_communication = 0\n\t\tself.num_blocks = 0\n\tdef mine_time(self, num_blocks=1):\n\t\treturn np.random.exponential(1.0/self.l, num_blocks)\n\tdef comm_time(self, force=False):\n\t\tif self.isBad and not force:\n\t\t\treturn MAX_TIME\n\t\tself.num_communication += 1\n\t\treturn np.random.uniform(0, self.delta, 1)[0]\n\tdef make_bad(self):\n\t\tself.isBad = True\n\tdef make_good(self):\n\t\tself.isBad = False\n\tdef assign_committee(self, comm_id):\n\t\tself.committee = comm_id\n\tdef get_num_communication(self):\n\t\treturn self.num_communication\n\tdef is_bad(self):\n\t\treturn self.isBad\n\tdef incr_block_count(self):\n\t\tself.num_blocks += 1\n\tdef clear(self):\n\t\tself.committee = None\n\t\t# self.num_communication = 0\n\t\t# self.num_blocks = 0\n\n\nclass Committee(object):\n\tdef __init__(self, id_num, c, delta):\n\t\tself.id = id_num\n\t\tself.min_size = c\n\t\tself.max_size = 1.05 c\n\t\tself.curr_size = 0\n\t\tself.nodes = []\n\t\tself.delta = delta\n\t\tself.lead_id = None\n\t\tself.num_blocks_thru = 0\n\n\tdef add_node(self, node):\n\t\tif self.curr_size >= self.max_size:\n\t\t\t#print(\"ERROR: committee full\")\n\t\t\treturn -1\n\t\tfor n in self.nodes:\n\t\t\tif n.id == node.id:\n\t\t\t\tprint(\"ERROR: node is already in committee!\")\n\t\t\t\treturn -2\n\t\tself.nodes.append(node)\n\t\tself.curr_size += 1\n\t\treturn 0\n\n\tdef remove_node(self, node):\n\t\tfor n in self.nodes:\n\t\t\tif n.id == node.id:\n\t\t\t\tself.nodes.remove(node)\n\t\t\t\tself.curr_size -= 1\n\t\t\t\treturn\n\t\tprint(\"ERROR: node is not in committee!\")\n\t\treturn\n\n\tdef clear(self):\n\t\tself.nodes = []\n\t\tself.curr_size = 0\n\t\tself.lead_id = None\n\n\tdef full(self):\n\t\treturn self.curr_size >= self.min_size\n\n\tdef get_new_leader(self):\n\t\tidx = np.random.randint(0,self.curr_size)\n\t\twhile idx == self.lead_id:\n\t\t\tidx = np.random.randint(0,self.curr_size)\n\t\tself.lead_id = idx\n\t\treturn idx\n\n\tdef get_leader_id(self):\n\t\t#print(\"entered\")\n\t\tlead_idx = self.get_new_leader()\n\t\tlead_time = self.nodes[lead_idx].comm_time()\n\t\t# print(\"lead_time: \" + str(lead_time))\n\t\ttime1 = min([lead_time, self.delta])\n\t\t#print(time1)\n\t\twhile lead_time > self.delta:\n\t\t\t#view_change\n\t\t\tcomm_times = []\n\t\t\tfor i in range(self.curr_size):\n\t\t\t\tn = self.nodes[i]\n\t\t\t\tif i != lead_idx:\n\t\t\t\t\tcomm_times.append(n.comm_time())\n\t\t\ttimes_sorted = np.sort(comm_times)\n\t\t\tcutoff = times_sorted[(2.0 * self.min_size / 3.0) - 1]\n\t\t\t# print(\"cutoff: \" + str(cutoff))\n\t\t\ttime1 += cutoff\n\t\t\tlead_idx = self.get_new_leader()\n\t\t\tlead_time = self.nodes[lead_idx].comm_time()\n\t\t\t# print(\"lead_time: \" + str(lead_time))\n\t\t\ttime1 += min([lead_time, self.delta])\n\t\t\t#print(time1)\n\t\treturn lead_idx, time1\n\n\tdef run_PBFT(self, num_blks=1, gen_blks=True):\n\t\tfinal_time = 0\n\t\tfor iteration in range(num_blks):\n\t\t\t# if iteration % 10 == 0:\n\t\t\t# \tprint(\"Block #\" + str(iteration+1))\n\n\t\t\t# get leader\n\t\t\tleader_idx, time1 = self.get_leader_id()\n\t\t\tleader = self.nodes[leader_idx]\n\n\t\t\t#pre-prepare phase\n\t\t\tcomm_times1 = [leader.comm_time() for i in range(self.curr_size - 1)]\n\t\t\tcomm_times1 = np.insert(comm_times1, leader_idx, 0)\n\n\t\t\t#prepare phase\n\t\t\tcomm_times2 = []\n\t\t\tfor i in range(self.curr_size):\n\t\t\t\treceive_times = []\n\t\t\t\tsize = 0\n\t\t\t\tfor j in range(self.curr_size):\n\t\t\t\t\tif j != leader_idx and j != i:\n\t\t\t\t\t\treceive_times.append(self.nodes[j].comm_time() + comm_times1[j])\n\t\t\t\t\t\tsize += 1\n\t\t\t\tsorted_times = np.sort(receive_times)\n\t\t\t\ttime = sorted_times[(2.0 * size / 3.0) - 1]\n\t\t\t\t#print(time)\n\t\t\t\tcomm_times2.insert(i,time)\n\n\t\t\t#commit phase\n\t\t\tcomm_times3 = []\n\t\t\tfor i in range(self.curr_size):\n\t\t\t\treceive_times = []\n\t\t\t\tsize = 0\n\t\t\t\tfor j in range(self.curr_size):\n\t\t\t\t\tif j != i:\n\t\t\t\t\t\treceive_times.append(self.nodes[j].comm_time() + comm_times2[j])\n\t\t\t\t\t\tsize += 1\n\t\t\t\tsorted_times = np.sort(receive_times)\n\t\t\t\ttime = sorted_times[(2.0 * size / 3.0) - 1]\n\t\t\t\t#print(time)\n\t\t\t\tcomm_times3.insert(i,time)\n\n\t\t\t#comm_times3 = np.concatenate(comm_times3)\n\t\t\tsorted_final_times = np.sort(comm_times3)\n\t\t\ttime_required = sorted_final_times[(2.0 * self.min_size / 3.0) - 1] + time1\n\t\t\t#print(\"time required: \" + str(time_required))\n\t\t\t#if time_required >= MAX_TIME:\n\t\t\t\t#print(\"time1 to get leader: \" + str(time1))\n\t\t\t\t# print(comm_times1)\n\t\t\t\t# print(comm_times2)\n\t\t\t\t# print(comm_times3)\n\t\t\tfinal_time += time_required\n\n\t\t\tif gen_blks:\n\t\t\t\tself.num_blocks_thru += 1\n\t\t\t\tfor n in self.nodes:\n\t\t\t\t\tn.incr_block_count()\n\n\t\treturn final_time\n\n\tdef get_member_ids(self):\n\t\tarr = []\n\t\tfor n in self.nodes:\n\t\t\tarr.append(n.id)\n\t\treturn arr\n\n\tdef get_size(self):\n\t\treturn self.curr_size\n\n\tdef get_num_blks_thru(self):\n\t\treturn self.num_blocks_thru\n\n\nclass Elastico(object):\n\tdirectories_comm = 0\n\tfinal_comm = 1\n\tdef __init__(self, n, c, s, lambda_0, beta, delta, blks_per_epoch, protocol, attack=False):\n\t\t# n = number of nodes\n\t\t# c = size of committees\n\t\t# s = number of committees\n\t\t# lambda_0 = total hash power\n\t\t# beta = fraction of adversarial nodes\n\t\t# delta = max network delay\n\t\t# protocol = protocol used in each committee\n\t\tif s < 3:\n\t\t\tprint(\"ERROR: need more than 2 committees\")\n\t\tself.n = n\n\t\tself.c = c\n\t\tself.s = s\n\t\tself.lambda_0 = lambda_0\n\t\tself.beta = beta\n\t\tself.delta = delta\n\t\tself.bpe = blks_per_epoch\n\t\tself.protocol = protocol\n\t\tself.attack = attack\n\t\tself.nodes = []\n\t\tself.nodes_active = []\n\t\tself.committees = []\n\t\tself.conf_latency = -1\n\n\t\t# create nodes\n\t\tfor i in range(n):\n\t\t\tl = lambda_0 / n\n\t\t\tself.nodes.append(Node(i,l,delta))\n\n\t\t# create adversarial nodes\n\t\tif attack:\n\t\t\tfor j in range(int(beta * n)):\n\t\t\t\tself.nodes[j].make_bad()\n\n\t\t# create committees\n\t\tfor j in range(s):\n\t\t\tself.committees.append(Committee(j,c,delta))\n\n\n\tdef get_committee_assignment(self):\n\t\treturn np.random.randint(1,self.s)\n\n\tdef committees_full(self):\n\t\tfor comm in self.committees:\n\t\t\tif not comm.full():\n\t\t\t\treturn False\n\t\treturn True\n\n\tdef get_identities(self):\n\t\t# each node does a PoW\n\t\ttimes = [x.mine_time() for x in self.nodes]\n\t\ttimes = np.concatenate(times)\n\t\tsorted_times = np.sort(times)\n\t\tsorted_times = list(sorted_times)\n\t\ttimes = list(times)\n\n\t\ttime_to_fill = 0\n\t\tused = []\n\t\tfor i in range(self.n):\n\t\t\tt = sorted_times[i]\n\t\t\tidx = times.index(t)\n\t\t\tif i < self.c:\n\t\t\t\t# first c members go to directory committee\n\t\t\t\tcomm_id = 0\n\t\t\telse:\n\t\t\t\tcomm_id = self.get_committee_assignment()\n\t\t\t\twhile comm_id in used:\n\t\t\t\t\tcomm_id = self.get_committee_assignment()\n\t\t\tflag = self.committees[comm_id].add_node(self.nodes[idx])\n\t\t\twhile(flag != 0):\n\t\t\t\tused.append(comm_id)\n\t\t\t\tcomm_id = self.get_committee_assignment()\n\t\t\t\tflag = self.committees[comm_id].add_node(self.nodes[idx])\n\t\t\tself.nodes[idx].assign_committee(comm_id)\n\t\t\tself.nodes_active.append(self.nodes[idx])\n\n\t\t\t# stop once committees are full\n\t\t\tif self.committees_full():\n\t\t\t\ttime_to_fill = t\n\t\t\t\tbreak\n\t\tif not self.committees_full():\n\t\t\tself.clear()\n\t\t\treturn self.get_identities()\n\n\t\treturn time_to_fill\n\n\tdef broadcast_committees(self):\n\t\t# directory members announce themselves\n\t\tdirectory_ids = self.committees[0].get_member_ids()\n\n\t\tbroadcast_time = []\n\t\tfor n in self.nodes:\n\t\t\tcomm_times = [self.nodes[i].comm_time(force=True) for i in directory_ids]\n\t\t\tcomm_sorted = np.sort(comm_times)\n\t\t\tsize = self.committees[0].get_size()\n\t\t\tbroadcast_time.append(comm_sorted[(2.0 * size / 3.0) - 1])\n\n\t\ttime1 = np.max(broadcast_time)\n\n\t\t# all other members announce themselves to directory committee\n\t\ttime2 = -1.0\n\t\tfor i in range(1,self.s):\n\t\t\tmember_ids = self.committees[i].get_member_ids()\n\t\t\ttimes = [self.nodes[m].comm_time(force=True) for m in member_ids]\n\t\t\tmax_time = np.max(times)\n\t\t\tif max_time > time2:\n\t\t\t\ttime2 = max_time\n\n\t\t# directory connects shards to themselves\n\t\ttime3 = -1.0\n\t\tfor j in range(1,self.s):\n\t\t\tcomm = self.committees[j]\n\t\t\tfor i in range(comm.get_size()):\n\t\t\t\tconnect_times = [self.nodes[d].comm_time() for d in directory_ids]\n\t\t\t\tsorted_times = np.sort(connect_times)\n\t\t\t\tcutoff = sorted_times[(2.0 * self.c / 3.0) - 1]\n\t\t\t\tif cutoff > time3:\n\t\t\t\t\ttime3 = cutoff\n\n\t\ttotal_time = time1 + time2 + time3\n\t\treturn total_time\n\n\tdef intra_committee_consensus(self):\n\t\tif self.protocol == \"PBFT\":\n\t\t\ttimes = [self.committees[i].run_PBFT(self.bpe, gen_blks=True) for i in range(2,self.s)]\n\t\t\treturn np.max(times)\n\t\telse:\n\t\t\tprint(\"ERROR: only PBFT protocol implemented!\")\n\n\tdef final_consensus(self):\n\t\ttime = self.committees[1].run_PBFT(num_blks=1, gen_blks=False)\n\t\treturn time\n\n\tdef generate_epoch_rand(self):\n\t\tids = self.committees[1].get_member_ids()\n\n\t\ttime1_arr = []\n\t\tfor i in ids:\n\t\t\ttimes = []\n\t\t\tfor j in ids:\n\t\t\t\tif i!=j:\n\t\t\t\t\ttimes.append(self.nodes[j].comm_time())\n\t\t\tsorted_times = np.sort(times)\n\t\t\ttime1_arr.append(sorted_times[(2.0 * self.c / 3.0) - 1])\n\n\t\ttime1 = np.max(time1_arr)\n\n\t\ttime2 = self.committees[1].run_PBFT(num_blks=1, gen_blks=False)\n\n\t\ttime3_arr = []\n\t\tfor n in self.nodes_active:\n\t\t\tcomm_times = [self.nodes[idx].comm_time() for idx in ids]\n\t\t\tsorted_times = np.sort(comm_times)\n\t\t\ttime3_arr.append(sorted_times[(2.0 * self.c / 3.0) - 1])\n\n\t\tfinal_time = np.max(time3_arr)\n\t\tself.clear()\n\t\treturn final_time\n\n\tdef clear(self):\n\t\tself.nodes_active = []\n\t\tfor comm in self.committees:\n\t\t\tcomm.clear()\n\t\tfor n in self.nodes:\n\t\t\tn.clear()\n\t\treturn\n\n\tdef run_epochs(self, num_epochs=1):\n\t\tepoch_times = []\n\t\tlatencies = []\n\t\tfor i in range(num_epochs):\n\t\t\tprint(\"Epoch #\" + str(i+1))\n\t\t\t# print(\"starting Phase 1...\")\n\t\t\ttime1 = self.get_identities()\n\t\t\t#print(\"time1: \" + str(time1))\n\t\t\t# print(\"...Phase 1 done\")\n\t\t\t# print(\"starting Phase 2...\")\n\t\t\ttime2 = self.broadcast_committees()\n\t\t\t#print(\"time2: \" + str(time2))\n\t\t\t# print(\"...Phase 2 done\")\n\t\t\t# print(\"starting Phase 3...\")\n\t\t\ttime3 = self.intra_committee_consensus()\n\t\t\t#print(\"time3: \" + str(time3))\n\t\t\t# print(\"...Phase 3 done\")\n\t\t\t# print(\"starting Phase 4...\")\n\t\t\ttime4 = self.final_consensus()\n\t\t\t#print(\"time4: \" + str(time4))\n\t\t\tlatencies.append(time3 + time4)\n\t\t\t# print(\"...Phase 4 done\")\n\t\t\t# print(\"starting Phase 5...\")\n\t\t\ttime5 = self.generate_epoch_rand()\n\t\t\t# print(\"...Phase 5 done\")\n\t\t\ttime = time1 + time2 + time3 + time4 + time5\n\t\t\tepoch_times.append(time)\n\t\tconf_latency = np.mean(latencies)\n\t\tself.conf_latency = conf_latency\n\t\tprint(\"\")\n\t\treturn np.sum(epoch_times)\n\n\tdef get_total_num_communication(self):\n\t\ttotal = 0\n\t\tfor node in self.nodes:\n\t\t\ttotal += node.get_num_communication()\n\t\treturn total\n\n\tdef get_num_TXs(self):\n\t\tcount_blks = 0\n\t\tfor comm in self.committees:\n\t\t\tcount_blks += comm.get_num_blks_thru()\n\t\treturn count_blks * TX_per_blk\n\n\tdef get_throuhgput(self):\n\t\ttime = self.run_epochs(5)\n\t\tprint(\"-------THROUGHPUT-------\")\n\t\tprint(\"Time: \" + str(time))\n\t\tTX_count = self.get_num_TXs()\n\t\tprint(\"TX Count: \" + str(TX_count))\n\t\tthroughput = float(TX_count) / time\n\t\tprint(\"Throughput: \" + str(throughput) + \" TXs per second\")\n\t\tprint(\"\")\n\t\treturn throughput\n\n\tdef get_communication_per_node(self):\n\t\tprint(\"-------COMMUNICATION-------\")\n\t\tcount = self.get_total_num_communication()\n\t\tprint(\"Number of Messages Sent: \" + str(count))\n\t\tn = len(self.nodes)\n\t\tprint(\"Number of Nodes: \" + str(n))\n\t\tcomm_per_node = float(count) / n\n\t\tprint(\"Communication Per Node: \" + str(comm_per_node) + \" Messages per node\")\n\t\tprint(\"\")\n\t\treturn comm_per_node\n\n\tdef get_downloads_per_node(self):\n\t\tprint(\"-------DOWNLOADS-------\")\n\t\tcount = 0\n\t\tfor n in self.nodes:\n\t\t\tcount += n.num_blocks\n\t\tprint(\"Number of Blocks Downloaded: \" + str(count))\n\t\tsize = len(self.nodes)\n\t\tprint(\"Number of Nodes: \" + str(size))\n\t\tdownloads_per_node = float(count) / size\n\t\tprint(\"Downloads Per Node: \" + str(downloads_per_node) + \" Blocks per node\")\n\t\tprint(\"\")\n\t\treturn downloads_per_node\n\n\tdef get_conf_latency(self):\n\t\tprint(\"-------CONFIRMATION LATENCY-------\")\n\t\tprint(\"Latency: \" + str(self.conf_latency))\n\t\treturn self.conf_latency\n\n\tdef print_all(self):\n\t\tprint(\"Number of Nodes (N): \" + str(self.n))\n\t\tprint(\"Minimum Size of Each Committe (C): \" + str(self.c))\n\t\tprint(\"# of Committees (S): \" + str(self.s))\n\t\tprint(\"Overall Hashing Power (lambda_0): \" + str(self.lambda_0))\n\t\tprint(\"Percentaeg Adversarial (Beta): \" + str(self.beta))\n\t\tprint(\"Max Netowrk Delay (Delta): \" + str(self.delta))\n\t\tprint(\"# of Blocks per Epoch: \" + str(self.bpe))\n\t\tprint(\"Protocol: \" + str(self.protocol))\n\t\tprint(\"Are We Similuating an Attack?: \" + str(self.attack))\n\t\tprint(\"\")\n\t\tprint(\"Nodes: \")\n\n\t\tfor i in range(self.n):\n\t\t\tnode = self.nodes[i]\n\t\t\tprint(\"ID: \" + str(node.id) + \" Committee: \" + str(node.committee) + \" Total number of messages sent: \" + str(node.get_num_communication()))\n\n\t\tprint(\"\")\n\t\tprint(\"Committees: \")\n\t\tprint(\"\")\n\n\t\tfor i in range(self.s):\n\t\t\tcomm = self.committees[i]\n\t\t\tprint(\"Comm #\" + str(i) + \": \")\n\t\t\tprint(\"Member IDs: \")\n\t\t\tprint(comm.get_member_ids())\n\t\t\tprint(\"# of Blocks Committed: \" + str(comm.get_num_blks_thru()))\n\t\t\tprint(\"\")\n\ndef write_to_file(f, betas, bpe_vals, c_vals, n_vals, arr, title):\n\tf = open(f, \"w\")\n\n\tc_words = \"\"\n\tfor c in c_vals:\n\t\tc_words = c_words + str(c) + \", \"\n\n\tn_words = \"\"\n\tfor n in n_vals:\n\t\tn_words = n_words + str(n) + \", \"\n\n\tf.write(\"---\" + title + \" (lambda_n = 1/100, delta = 0.01, tx_per_blk = 40)---\\n\\n\")\n\tfor i, b in enumerate(betas):\n\t\tfor j, bpe in enumerate(bpe_vals):\n\t\t\tf.write(\" Beta = \" + str(b) + \" & bpe = \" + str(bpe) + \"\\n\")\n\t\t\tfor k, c in enumerate(c_vals):\n\t\t\t\tif k == 0:\n\t\t\t\t\tf.write(\"c (rows) = \" + c_words + \"\\n\")\n\t\t\t\tfor l, n in enumerate(n_vals):\n\t\t\t\t\tif k==0 and l==0:\n\t\t\t\t\t\tf.write(\"n (cols) = \" + n_words + \"\\n\")\n\t\t\t\t\tf.write(\" \" + str(arr[i][j][k][l]) + \" \")\n\t\t\t\tf.write(\"\\n\")\n\t\t\tf.write(\"\\n\")\n\tf.close()\n\ndef run_experiment(n_vals, betas, c_vals, bpe_vals):\n\tlambda_n = 1.0/100\n\tdelta = 0.01\n\tprotocol = \"PBFT\"\n\n\tthroughputs = np.zeros((len(betas), len(bpe_vals), len(c_vals), len(n_vals)))\n\tcomms = np.zeros((len(betas), len(bpe_vals), len(c_vals), len(n_vals)))\n\tdownloads = np.zeros((len(betas), len(bpe_vals), len(c_vals), len(n_vals)))\n\tlatencies = np.zeros((len(betas), len(bpe_vals), len(c_vals), len(n_vals)))\n\n\tfor i, b in enumerate(betas):\n\t\tfor j, bpe in enumerate(bpe_vals):\n\t\t\tfor k, c in enumerate(c_vals):\n\t\t\t\tfor l, n in enumerate(n_vals):\n\t\t\t\t\tprint(\"N = \" + str(n) + \" Beta = \" + str(b) + \" C = \" + str(c) + \" bpe = \" + str(bpe))\n\t\t\t\t\tl_0 = lambda_n * n\n\t\t\t\t\ts = int((0.9 * n) / c)\n\t\t\t\t\te = Elastico(n, c, s, l_0, b, delta, bpe, protocol, attack=True)\n\t\t\t\t\tval1 = e.get_throuhgput()\n\t\t\t\t\tval2 = e.get_communication_per_node()\n\t\t\t\t\tval3 = e.get_downloads_per_node()\n\t\t\t\t\tval4 = e.get_conf_latency()\n\t\t\t\t\tthroughputs[i][j][k][l] = val1\n\t\t\t\t\tcomms[i][j][k][l] = val2\n\t\t\t\t\tdownloads[i][j][k][l] = val3\n\t\t\t\t\tlatencies[i][j][k][l] = val4\n\t\t\t\t\tprint(\"\")\n\n\twrite_to_file(\"elastico_throughput_results6.txt\", betas, bpe_vals, c_vals, n_vals, throughputs, \"THROUGHPUT in TXs per sec\")\n\twrite_to_file(\"elastico_communication_results6.txt\", betas, bpe_vals, c_vals, n_vals, comms, \"COMMUNICATION in messages per node\")\n\twrite_to_file(\"elastico_download_results6.txt\", betas, bpe_vals, c_vals, n_vals, downloads, \"DOWNLOADS in blocks per node\")\n\twrite_to_file(\"elastico_latency_results6.txt\", betas, bpe_vals, c_vals, n_vals, latencies, \"CONFIRMATION LATENCY in sec\")\n\n\nif __name__ == '__main__':\n\t#n_vals = [500, 1000, 1500, 2000, 3000]\n\t#n_vals = [500, 1000, 1500, 2000, 4000, 7000]\n\tn_vals = [10000]\n\t# betas = [0.1, 0.2]\n\t# c_vals = [50, 100]\n\t# bpe_vals = [50, 75]\n\tbetas = [0.0, 0.10, 0.20]\n\tc_vals = [100]\n\tbpe_vals = [50]\n\trun_experiment(n_vals, betas, c_vals, bpe_vals)\n\n\n" }, { "alpha_fraction": 0.37943926453590393, "alphanum_fraction": 0.44112148880958557, "avg_line_length": 32.375, "blob_id": "39f0c1c5eb433e1844d315bcf3edbc6f4e1feeb3", "content_id": "3723443bd60b39d7ca60471f82bbdba370bec15c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 535, "license_type": "no_license", "max_line_length": 54, "num_lines": 16, "path": "/prism/args.py", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "\ndef load_params():\n params = { \n \"beta\" : 0.3, \n \"lv\" : 0.001, #hash rate of a voter chain\n \"lp\" : 0.1, #hash rate of a proposer chain\n \"lt\" : 1, #hash rate of transactions block\n \"l\" : 30,\n \"num_voter_chains\" : 20,\n \"prop_delay\" : 0.2, # in seconds\n \"num_miners\": 10000,\n \"txPerBlock\": 100,\n \"communication_cost\": 0.001,\n \"reversal_prob\": 0.001,\n \"eval_every\": 10,\n }\n return params\n" }, { "alpha_fraction": 0.519525408744812, "alphanum_fraction": 0.5241331458091736, "avg_line_length": 42.19403076171875, "blob_id": "2a16fc8d5f3b349b947c63dcfdc52b54c0b7bb1d", "content_id": "4a52991bdf8f81ed4dc90a0296c419d3cece4880", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 8681, "license_type": "no_license", "max_line_length": 131, "num_lines": 201, "path": "/prism/blockchain.py", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "import numpy as np \nfrom args import load_params\nfrom blocks import \nfrom scipy.stats import poisson\nimport copy\nimport time\n\nnp.random.seed(0)\nclass Prism: \n def __init__(self) : \n ###################### GET PARAMS ############################\n self.params = load_params() #Load paramaters\n self.numVoterChains = self.params[\"num_voter_chains\"]\n self.l = self.params[\"l\"]\n self.lv = 0.25self.l/self.numVoterChains\n self.lt = 0.5self.l\n self.lp = self.l - self.lt - self.lvself.numVoterChains\n self.beta = self.params[\"beta\"]\n self.lh = self.l * (1 - self.params[\"beta\"])\n self.la = self.l * self.params[\"beta\"]\n self.txPerBlock = self.params[\"txPerBlock\"]\n self.delta = self.params[\"prop_delay\"] + self.params[\"communication_cost\"] * np.log2(self.numVoterChains + self.txPerBlock)\n self.alpha = self.deltaself.lv/(1+self.deltaself.lv)\n self.epsilon = self.params[\"reversal_prob\"]\n\n\n ###################### INIT SIM VARS #########################\n self.time = 0 #Simulation time\n self.voterChains = [VoterChain(i) for i in range(self.numVoterChains)]\n self.proposerChain = ProposerChain()\n self.txchain = TxChain(self.txPerBlock)\n self.superBlock = SuperBlock(self.numVoterChains)\n self.nextsuperBlock = SuperBlock(self.numVoterChains)\n self.levelMap = {}\n self.propMap = {}\n self.leaderSequence = []\n self.ledger = []\n self.txPerSec = None\n self.confirmation_latency = []\n self.numBlocksMinded = 0\n\n def stepForward(self) : \n # update super block\n # start = time.time()\n self.superBlock = copy.deepcopy(self.nextsuperBlock)\n self.txchain.curr = len(self.txchain.txList)* self.txPerBlock ## to be removed\n #Mine Block\n self.time += np.random.exponential(1/self.lh) + self.delta\n numForked = np.random.poisson(self.lhself.delta)\n self.numBlocksMinded += numForked + 1\n for _ in range(numForked + 1): # number of forked blocks plus one none forked block\n self.getNewBlock()\n # print(\"Time to get mined blocks: \", time.time() - start )\n # start = time.time()\n if self.numBlocksMinded - self.params[\"eval_every\"] > 0:\n self.numBlocksMinded = 0\n self.updateMaps()\n self.updateProb()\n self.updateLedger()\n arr = np.array(self.confirmation_latency)\n print(\"Avg Confirmation Latency (sec) : \", np.mean(arr))\n # print(\"Time to check ledger: \", time.time() - start)\n \n\n def updateLedger(self):\n seenTxBlks = {}\n for i, leader in enumerate(self.leaderSequence): \n blk = self.proposerChain.propList[leader]\n if i > 0 and self.leaderSequence[i - 1] in blk.parent:\n blk.parent.remove(self.leaderSequence[i-1])\n for par in blk.parent:\n parblk = self.proposerChain.propList[par]\n for txind in parblk.txRefs:\n if txind not in seenTxBlks:\n self.ledger.append(self.txchain.txList[txind].txs)\n seenTxBlks[txind] = True\n for txind in blk.txRefs:\n if txind not in seenTxBlks:\n seenTxBlks[txind] = True\n self.ledger.append(self.txchain.txList[txind].txs)\n self.txPerSec = len(self.ledger)self.txPerBlock/self.time\n self.ledger = []\n self.levelMap = {}\n self.propMap = {}\n self.leaderSequence = []\n print(\"Throughput (Tx/sec): \", self.txPerSec)\n \n def updateMaps(self): \n self.levelMap = {}\n self.propMap = {}\n for i in range(self.numVoterChains): \n vchain = self.voterChains[i]\n if not vchain.isgenesis: \n voternodes = vchain.getlongestpath()\n for vnode in voternodes:\n for prop in vnode.reference_link:\n self.proposerChain.propList[prop].numVotes += 1\n if prop in self.propMap:\n if not (i, vnode.ind) in self.propMap[prop]: \n self.propMap[prop].append((i, vnode.ind))\n else :\n self.propMap[prop] = [(i,vnode.ind)]\n for node in self.proposerChain.propList :\n if node.level in self.levelMap: \n if not node.ind in self.levelMap[node.level]:\n self.levelMap[node.level].append(node.ind)\n else: \n self.levelMap[node.level] = [node.ind]\n\n \n\n def updateProb(self):\n ep = self.epsilon \n self.leaderSequence = []\n for level in self.levelMap: \n dbar = 0\n sumVotes = 0\n for bp in self.levelMap[level]:\n if bp not in self.propMap:\n continue\n for i, bv in self.propMap[bp]:\n dbar += self.voterChains[i].voterList[bv].depth\n sumVotes += self.proposerChain.propList[bp].numVotes\n self.proposerChain.propList[bp].numVotes = 0 ## maybe\n if dbar != 0 :\n dbar /= sumVotes\n da = self.betadbar/((1-self.alpha)(1-self.beta))\n va = self.numVoterChains\n for bp in self.levelMap[level]:\n mu_i = 0\n sigma_i = 0\n if bp not in self.propMap:\n continue\n for i, bv in self.propMap[bp]:\n dij = self.voterChains[i].voterList[bv].depth\n Pij = poisson.cdf(dij, da)\n for k in range(dij + 1):\n Pij -= poisson.pmf(k, da)(self.beta/(1-self.beta))(dij + 1 - k) \n\n mu_i += Pij \n sigma_i += Pij(1-Pij)\n vi_lower = (mu_i - np.sqrt(sigma_i(np.log(1/ep2) - np.log(np.log(1/ep2)) - np.log(2np.pi))))\n va -= vi_lower\n self.proposerChain.propList[bp].revProbLow = vi_lower\n for bpL in self.levelMap[level]:\n isleader = True\n vl = self.proposerChain.propList[bpL].revProbLow\n for bpi in self.levelMap[level]: \n vih = self.proposerChain.propList[bpi].revProbLow + va\n if (vl < vih and bpi != bpL) or vl < va: \n isleader = False\n if isleader: \n if not self.proposerChain.propList[bpL].isLeader: \n self.confirmation_latency.append(self.time - self.proposerChain.propList[bpL].time)\n self.proposerChain.propList[bpL].isLeader = True\n dt = self.time - self.proposerChain.propList[bpL].time\n self.confirmation_latency.append(dt)\n self.leaderSequence.append(bpL)\n else:\n isleader = True\n assert self.proposerChain.propList[bpL].isLeader == False, \"persistance failed!\"\n break\n \n def getNewBlock(self): \n sortition = np.random.uniform(0, self.l)\n thresh = 0\n for i in range(self.numVoterChains): \n thresh += self.lv\n if sortition < thresh:\n #check for same level votes\n lmap = {}\n for p in self.superBlock.Cvoter[i]:\n lev = self.proposerChain.propList[p].level \n if lev not in lmap:\n lmap[lev] = True\n else: \n self.superBlock.Cvoter[i].remove(p)\n\n self.voterChains[i].addBlock(self.superBlock)\n self.nextsuperBlock.Cvoter[i] = []\n self.nextsuperBlock.vParent[i] = self.voterChains[i].getTip()\n return \n thresh += self.lp\n if sortition < thresh: \n self.proposerChain.addBlock(self.superBlock, self.time)\n self.nextsuperBlock.loneTx = []\n tip = self.proposerChain.getTip()\n self.nextsuperBlock.propParent = tip\n for j in range(self.numVoterChains):\n self.nextsuperBlock.Cvoter[j].append(tip[0]) ### to be changed for forking\n return\n thresh += self.lt\n if sortition < thresh: \n tip = self.txchain.addBlock()\n self.nextsuperBlock.loneTx.append(tip)\n\n#### DEBUG ###### \nif __name__ == \"__main__\":\n p = Prism()\n while True:\n p.stepForward()" }, { "alpha_fraction": 0.6057692170143127, "alphanum_fraction": 0.6378205418586731, "avg_line_length": 18.5625, "blob_id": "6d30cbc43bbf07fa68287c3c26c1b3bbd3be1f13", "content_id": "f96d1ab6ed34825f03958fb4c598dde1396b3c3d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 312, "license_type": "no_license", "max_line_length": 31, "num_lines": 16, "path": "/prism/test.py", "repo_name": "lucsof114/EE374_Project", "src_encoding": "UTF-8", "text": "# import networkx as nx\n# g = nx.DiGraph()\n# g.add_edge(1,2)\n# g.add_edge(1,3)\n# lp = nx.dag_longest_path(g)\n# print(lp)\n# g2 = g.copy()\n# g2.remove_node(lp[-1])\n# lp2 = nx.dag_longest_path(g2)\n# print(lp2)\n# print(nx.dag_longest_path(g))\n\nfrom blockchain import Prism\np = Prism()\nwhile True:\n p.stepForward()" } ]	7
margomjoy/SQL_Alchemy	https://github.com/margomjoy/SQL_Alchemy	4b9d397a13ceccec45e2eebd6d4d6d7ba0d6b1b9	a919ee91d08221c085be192ea4cc27189fba3f59	9d55a809b75ed4adb40506553d5dc61b53a89555	refs/heads/master	2022-10-15T10:08:49.235090	2020-06-05T21:33:12	2020-06-05T21:33:12	269,783,637	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6009371280670166, "alphanum_fraction": 0.6345177888870239, "avg_line_length": 23.127450942993164, "blob_id": "751ad70675bc778912a2a14f791e0c39686f9b9c", "content_id": "18990a3913673fabd95f9e1d90deb2fcbbeaa422", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2561, "license_type": "no_license", "max_line_length": 137, "num_lines": 102, "path": "/Case Assignment/app.py", "repo_name": "margomjoy/SQL_Alchemy", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\r\n\"\"\"\r\nCreated on Wed Jun 3 18:28:58 2020\r\n\r\n@author: Joisel\r\n\"\"\"\r\n\r\n\r\n# import Dependencies\r\nimport numpy as np\r\nimport sqlalchemy\r\nfrom sqlalchemy.ext.automap import automap_base\r\nfrom sqlalchemy.orm import Session\r\nfrom sqlalchemy import create_engine, func ,inspect\r\nfrom flask import Flask, jsonify\r\n\r\n#%%\r\n\r\nengine = create_engine(\"sqlite:///Resources/hawaii.sqlite\")\r\n\r\n#%%\r\n\r\nBase = automap_base()\r\nBase.prepare(engine, reflect=True)\r\nBase.classes.keys()\r\n\r\n#%%\r\n\r\nMeasurement = Base.classes.measurement\r\nStation = Base.classes.station\r\n\r\n#%%\r\n\r\nsession = Session(engine)\r\ninspector = inspect(engine)\r\ninspector.get_table_names()\r\n\r\n#%%\r\n\r\napp = Flask(__name__)\r\n\r\n#%%\r\n\r\[email protected](\"/\")\r\ndef home():\r\n return(\"/api/v1.0/precipitation<br/>\"\r\n \"/api/v1.0/stations<br/>\"\r\n \"/api/v1.0/tobs<br/>\"\r\n \"/api/v1.0/2017-01-01<br/>\"\r\n \"/api/v1.0/2017-01-01/2017-01-09\")\r\n\r\[email protected](\"/api/v1.0/precipitation\")\r\ndef precipitation():\r\n results1 = session.query(Measurement.date, Measurement.prcp).filter(Measurement.date>=\"2016-08-23\").all()\r\n first_dict = list(np.ravel(results1))\r\n return jsonify(first_dict)\r\n \r\n#%%\r\n\r\[email protected](\"/api/v1.0/stations\")\r\ndef stations():\r\n results2 = session.query(Station.station, Station.name).all()\r\n sec_dict = list(np.ravel(results2))\r\n return jsonify(sec_dict)\r\n#%%\r\n\r\[email protected](\"/api/v1.0/tobs\")\r\ndef tobs():\r\n results3 = session.query(Measurement.date, Measurement.tobs).\\\r\n filter(Measurement.date>=\"2016-08-23\").\\\r\n filter(Measurement.date<=\"2017-08-23\").all()\r\n temp_dict = list(np.ravel(results3))\r\n return jsonify(temp_dict)\r\n\r\n \r\n\r\n#%%\r\n \r\[email protected](\"/api/v1.0/<start>\")\r\ndef start(start=None):\r\n\r\n from_start = session.query(Measurement.date, func.min(Measurement.tobs), func.avg(Measurement.tobs), func.max(Measurement.tobs)).\\\r\n filter(Measurement.date >= start).group_by(Measurement.date).all()\r\n from_start_list=list(from_start)\r\n return jsonify(from_start_list)\r\n\r\n\r\n#%% \r\[email protected](\"/api/v1.0/<start>/<end>\")\r\ndef start_end(start=None, end=None):\r\n between_dates = session.query(Measurement.date, func.min(Measurement.tobs), func.avg(Measurement.tobs), func.max(Measurement.tobs)).\\\r\n filter(Measurement.date >= start).\\\r\n filter(Measurement.date <= end).group_by(Measurement.date).all()\r\n between_dates_list=list(between_dates)\r\n return jsonify(between_dates_list) \r\n\r\n\r\n \r\n#%%\r\n \r\nif __name__ == '__main__':\r\n app.run(debug=True)" } ]	1
bcartmell/OSATT-CAD-parsing	https://github.com/bcartmell/OSATT-CAD-parsing	3442c02b807253534fbadc3e1d6510fc8cda3633	575599f152e2ad318ed06f2ad3472fe4b548b906	b9e78663cbccb9850f8e877220e87a13d1137910	refs/heads/master	2016-09-05T15:24:59.764474	2014-10-20T00:32:54	2014-10-20T00:32:54	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7268292903900146, "alphanum_fraction": 0.7268292903900146, "avg_line_length": 44.55555725097656, "blob_id": "d20c2c8cd005c68c67ae5e132a7270b1c52c1467", "content_id": "6d5b299fb2540c684be6c8426ff6b7311a08179f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 410, "license_type": "no_license", "max_line_length": 120, "num_lines": 9, "path": "/testScript.js", "repo_name": "bcartmell/OSATT-CAD-parsing", "src_encoding": "UTF-8", "text": "'use strict';\nvar handleFcstd = require('./handleFcstd.js');\nvar cadHand = require('./doctools.js');\n\n//cadHand.extract('./teapot_with_sketch/teapot_with_sketch.fcstd', './teapot_with_sketch/teapot_with_sketch_EXTRACTED');\n\n//cadHand.create('./teapot_with_shapes');\n//cadHand.create('./teapot_with_sketch/teapot_with_sketch_extract');\nhandleFcstd.create('./teapot_with_shapes/Document.xml', './teapot.fcstd');\n" }, { "alpha_fraction": 0.7375504970550537, "alphanum_fraction": 0.7375504970550537, "avg_line_length": 29.95833396911621, "blob_id": "0561be67c320d700ad5bbd756cb96015fa1ab0df", "content_id": "37a2c1b0e6dac923496120ed8c7d069087fb73bf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 743, "license_type": "no_license", "max_line_length": 90, "num_lines": 24, "path": "/README.md", "repo_name": "bcartmell/OSATT-CAD-parsing", "src_encoding": "UTF-8", "text": "OSATT - CAD-Parsers\n=====\n\nCurrently the only file here is doctools.py. This file is a slightly-modified\ncopy of the file by the same name from FreeCad. It's purpose is to extract and \nre-zip .FStd (FreeCad) files.\n\nTo extract FreeCad files in preparation for GIT tracking, run the following command:\n```bash\n $python <path/to/doctools.py> extract <name of FreeCad file> <desired output folder>\n```\n\n\nTo Compress an extracted folder back into a usable FreeCad file, run the following commad:\n```bash\n $python <path/to/doctools.py> create <path to 'Document.xml'> <new_file_name.FCStd>\n```\n\nThe 'Document.xml' file can be found among the files created by a previous extraction.\n\n\n### Update!\nAdding JS extractor.\n - Requires JSZip (Maybe)\n" }, { "alpha_fraction": 0.7190865874290466, "alphanum_fraction": 0.7233951091766357, "avg_line_length": 22.209999084472656, "blob_id": "5051c0a3cb77be874c4ccbe8a1ab9ed5acbe1287", "content_id": "59ad2c142dbe2fb30f84304c1a1bb885e9bd4fac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2321, "license_type": "no_license", "max_line_length": 65, "num_lines": 100, "path": "/doctools.py", "repo_name": "bcartmell/OSATT-CAD-parsing", "src_encoding": "UTF-8", "text": "#! python\n# -- coding: utf-8 --\n# (c) 2010 Werner Mayer LGPL\n# FreeCAD Python script to work with the FCStd file format.\n\n# Script modified by OSATT to be accessible from commad line for \n# to extract FreeCad files for tracking in GIT and re-compressing\n# for use.\n\nimport os,sys,string\nimport xml.sax\nimport xml.sax.handler\nimport xml.sax.xmlreader\nimport zipfile\n\n# Custom additions by OSATT\n\nimport time # for debugging\n\naction = sys.argv[1]\nfilename = sys.argv[2]\noutpath = sys.argv[3]\n# End Custom additions by OSATT\n\n# SAX handler to parse the Document.xml\nclass DocumentHandler(xml.sax.handler.ContentHandler):\n\tdef __init__(self, dirname):\n\t\tself.files = []\n\t\tself.dirname = dirname\n\n\tdef startElement(self, name, attributes):\n\t\titem=attributes.get(\"file\")\n\t\tif item != None:\n\t\t\tself.files.append(os.path.join(self.dirname,str(item)))\n\n\tdef characters(self, data):\n\t\treturn\n\n\tdef endElement(self, name):\n\t\treturn\n\ndef extractDocument(filename, outpath):\n\tzfile=zipfile.ZipFile(filename)\n\tfiles=zfile.namelist()\n\t\n\tfor i in files:\n\t\tdata=zfile.read(i)\n\t\tdirs=i.split(\"/\")\n\t\tif len(dirs) > 1:\n\t\t\tdirs.pop()\n\t\t\tcurpath=outpath\n\t\t\tfor j in dirs:\n\t\t\t\tcurpath=curpath+\"/\"+j\n\t\t\t\tos.mkdir(curpath)\n\t\toutput=open(outpath+\"/\"+i,\"wb\")\n\t\toutput.write(data)\n\t\toutput.close()\n\ndef createDocument(filename, outpath):\n files=getFilesList(filename)\n # get a list of files in this directory\n\n compress=zipfile.ZipFile(outpath,'w',zipfile.ZIP_DEFLATED)\n # create zipfile called compress.\n\n for i in files:\n dirs=os.path.split(i)\n compress.write(i,dirs[-1],zipfile.ZIP_DEFLATED)\n\n compress.close()\n\ndef getFilesList(filename):\n\tdirname=os.path.dirname(filename)\n\thandler=DocumentHandler(dirname)\n\tparser=xml.sax.make_parser()\n\tparser.setContentHandler(handler)\n\tparser.parse(filename)\n\n\tfiles=[]\n\tfiles.append(filename)\n\tfiles.extend(iter(handler.files))\n\tdirname=os.path.join(dirname,\"GuiDocument.xml\")\n\tif os.path.exists(dirname):\n\t\tfiles.append(dirname)\n\treturn files\n\n\n# Custom additions by OSATT\nif action == \"create\":\n # Create FreeCad file\n print \"Creating document...\"\n createDocument(filename, outpath)\n print \"Document created.\"\nelif action == \"extract\":\n # Extract FreeCad file\n print \"Extracting document...\"\n extractDocument(filename, outpath)\n print \"Document extracted.\"\nelse:\n print \"invalid input.\"\n" }, { "alpha_fraction": 0.6781818270683289, "alphanum_fraction": 0.6836363673210144, "avg_line_length": 25.190475463867188, "blob_id": "65a6dfa73f0c6d8554850e863ec68388fe49a102", "content_id": "c7e2209254fc0028f65621fd7ad09fcba6c5b465", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 550, "license_type": "no_license", "max_line_length": 85, "num_lines": 21, "path": "/helpers.js", "repo_name": "bcartmell/OSATT-CAD-parsing", "src_encoding": "UTF-8", "text": "var path = require('path');\n\nexports.resolveFile = function(url) {\n return path.resolve(path.normalize(url));\n};\n\nexports.whatsFilename = function(filePath, withExt) {\n var extIndex;\n\n filePath = filePath.split('/');\n // create array of path parts.\n\n filePath = filePath[filePath.length-1];\n // the last one is the file name.\n\n extIndex = filePath.indexOf('.');\n if (!withExt && extIndex > -1) filePath = filePath.slice(0, filePath.indexOf('.'));\n // if a truthy value was not past for withExt, chop off the extension.\n\n return filePath;\n}\n" }, { "alpha_fraction": 0.6973684430122375, "alphanum_fraction": 0.6973684430122375, "avg_line_length": 29.399999618530273, "blob_id": "dc27ed8b71fa1c397681d09364fc4d28900e50cf", "content_id": "6efbf30cc654b2ea38a887b1a01ffe6d02369488", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 304, "license_type": "no_license", "max_line_length": 73, "num_lines": 10, "path": "/handleFcstd.js", "repo_name": "bcartmell/OSATT-CAD-parsing", "src_encoding": "UTF-8", "text": "'use strict';\nvar child = require('child_process');\n\nexports.create = function(source, destination) {\n child.spawn('python', ['doctools.py', 'create', source, destination]);\n}\n\nexports.extract = function(source, destination) {\n child.spawn('python' ,['doctools.py', 'extract', source, destination]);\n}\n" } ]	5
koodaamo/fanstat	https://github.com/koodaamo/fanstat	c344ad17465dd059543feef91475400ac698abee	7840ef2ba90df11d27bb5a75bb408797cf4ab048	6119a1aab04ccae71bc9d6e207ea38a3a716012a	refs/heads/master	2021-01-10T19:23:19.301166	2015-05-11T05:19:32	2015-05-11T05:19:32	35,403,530	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5392205119132996, "alphanum_fraction": 0.5404538512229919, "avg_line_length": 31.43199920654297, "blob_id": "f8e83dfd1c8ba6af5b9f2413a397bf5dabe6f031", "content_id": "a2efdbeefef205f47cb72c8220885c8fa0681897", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4054, "license_type": "permissive", "max_line_length": 108, "num_lines": 125, "path": "/fanstat/cli.py", "repo_name": "koodaamo/fanstat", "src_encoding": "UTF-8", "text": "# -- encoding: utf-8 --\n\"\"\"\nfanstat - a command-line interface to build Fanstatic resources for web app use\n\nUsage:\n fanstat list \| libs \| cont [<lib>...] [ --css \| --js ]\n fanstat crossbar [<lib>...] [--prefix=<path>]\n fanstat html [--prefix=<path>] [--full] [<lib>...]\n\n list List all packages for which resources exist\n libs List all libraries\n cont List contents of all libraries\n -c --css List only css resources\n -j --js Only js\n crossbar Generate crossbar static config for libraries\n html Generate HTML for JS & CSS inclusion\n -p --prefix=<path> Set the URL path prefix for generated items\n -f --full Link to full (uncompressed) files\n <lib>... Limit to given library names (in dependency order)\n -h --help Show this screen.\n -v --version Show version.\n\n\"\"\"\n\nimport sys, logging, string, json\nfrom docopt import docopt\nimport pkg_resources\nfrom fanstatic import get_library_registry\n\n\ndef command():\n\n args = docopt(__doc__, version='fanstat 1.2')\n if len(sys.argv) == 1:\n sys.exit(__doc__)\n\n if args[\"list\"]:\n print \"\\nInstalled Python packages with Fanstatic libraries:\\n\"\n for ep in pkg_resources.iter_entry_points(group='fanstatic.libraries'):\n #print ep.name, ep.load()\n print ep.module_name\n\n\n if args[\"libs\"]:\n print \"\\nResource libraries:\\n\"\n for k,v in get_library_registry().items():\n print k, v.rootpath\n\n\n if args[\"cont\"]:\n print \"\\nResources:\\n\"\n for k,v in get_library_registry().items():\n print k, v.rootpath\n for r in v.known_resources:\n print r\n\n if args[\"html\"]:\n print \"\\nHTML for inclusion on web page:\"\n\n libnames = args[\"<lib>\"]\n eps = [ep for ep in pkg_resources.iter_entry_points(group='fanstatic.libraries')]\n if libnames:\n selected = [ep for ep in eps if ep.name in libnames]\n else:\n selected = eps\n\n # generate list of <script> and <link> tags\n links = {\"css\":{}, \"js\":{}}\n for ep in selected:\n name = ep.name\n links[\"css\"][name] = []\n links[\"js\"][name] = []\n\n lib = ep.load()\n #module = ep.module_name,\n #root = lib.rootpath\n if args[\"--full\"]:\n resources = [r for r in lib.known_resources if \".min.\" not in r]\n else:\n resources = [r for r in lib.known_resources if \".min.\" in r or \".css\" in r]\n\n for res in resources:\n safename = name.replace(\"\|\",\"_\")\n if res.endswith(\".js\"):\n prefix = args[\"--prefix\"] or \"\"\n link = '<script type=\"text/javascript\" src=\"%s\"></script>' % (prefix + safename + \"/\" + res)\n links[\"js\"][name].append(link)\n\n if res.endswith(\".css\"):\n prefix = args[\"--prefix\"] or \"\"\n link = '<link type=\"text/css\" href=\"%s\" rel=\"stylesheet\"/>' % (prefix + safename + \"/\" + res)\n links[\"css\"][name].append(link)\n\n # print CSS link tags\n if links[\"css\"]:\n print \"\\n<!-- CSS styles -->\"\n for libname in libnames:\n if links[\"css\"][libname]:\n print \"\\n\".join(links[\"css\"][libname])\n\n # print JS link tags\n if links[\"js\"]:\n print \"\\n<!-- JavaScript scripts -->\"\n for libname in libnames:\n if links[\"js\"][libname]:\n print \"\\n\".join(links[\"js\"][libname])\n\n\n if args[\"crossbar\"]:\n print \"\\nCrossbar resources configuration:\\n\"\n paths = {}\n for ep in pkg_resources.iter_entry_points(group='fanstatic.libraries'):\n name = args[\"--prefix\"] + ep.name if args[\"--prefix\"] else ep.name\n lib = ep.load()\n paths[name.replace(\"\|\",\"_\")] = {\n \"type\":\"static\",\n \"package\": ep.module_name,\n \"resource\": lib.rootpath\n }\n print json.dumps(paths, indent=3, separators=(',', ': '))\n\n\nif __name__==\"__main__\":\n\n command()\n" }, { "alpha_fraction": 0.5874125957489014, "alphanum_fraction": 0.5874125957489014, "avg_line_length": 20.450000762939453, "blob_id": "0b05d3706f91459c8019a2dc7e2bd493f421986a", "content_id": "d9ecd3461005a2db3414201241b202a01b0583c2", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "reStructuredText", "length_bytes": 429, "license_type": "permissive", "max_line_length": 58, "num_lines": 20, "path": "/README.rst", "repo_name": "koodaamo/fanstat", "src_encoding": "UTF-8", "text": "===============================\nfanstat\n===============================\n\n.. image:: https://img.shields.io/travis/petri/fanstat.svg\n :target: https://travis-ci.org/petri/fanstat\n\n.. image:: https://img.shields.io/pypi/v/fanstat.svg\n :target: https://pypi.python.org/pypi/fanstat\n\n\nCommand-line for Fanstatic\n\n* Free software: BSD license\n* Documentation: https://fanstat.readthedocs.org.\n\nFeatures\n--------\n\n* TODO\n" } ]	2
Wise-Economy/plantix	https://github.com/Wise-Economy/plantix	91b0f60d2fb8cacb78cf91e37bb37f9d9246ee83	f8f355299e3bbb1472f02042b5955fda82d4c396	983ecda70baa4632a46f44d7946f5d630459b3d4	refs/heads/master	2022-12-14T23:57:22.812081	2020-08-27T10:53:17	2020-08-27T10:53:17	290,751,681	0	1	null	null	null	null	null	[ { "alpha_fraction": 0.6931818127632141, "alphanum_fraction": 0.6931818127632141, "avg_line_length": 35.959999084472656, "blob_id": "72af54ed9cc07526be7e07cce66cc5c869f07044", "content_id": "faa44ebb1b0b8a3d434a040707794146ea28d6af", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1848, "license_type": "no_license", "max_line_length": 84, "num_lines": 50, "path": "/depth_first_search.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "from typing import Text as String\n\nfrom PlantixCommunityService import PlantixCommunityService\n\n\ndef depth_first_search_recursive(reachable_nodes: set, start: String) -> set:\n \"\"\"\n Run the depth first search algorithm to identify all\n the reachable nodes in a graph from the given start \"expert\" node.\n\n This is a recursive DFS implementation. The memory implications may\n be bad as python doesn't do \"tail call optimization\".\n\n :param reachable_nodes: Set of all nodes reachable from the start\n Initial value will be set() -> empty set.\n :param start: uid of the expert \"Node\" from which the depth first search starts.\n :return: Set of nodes that are reachable from start node.\n \"\"\"\n network = PlantixCommunityService()\n if start not in reachable_nodes:\n expert = network.get(start)\n reachable_nodes.add(start)\n for neighbour in expert.following:\n depth_first_search_recursive(reachable_nodes, neighbour)\n\n return reachable_nodes\n\n\ndef depth_first_search_iterative(start: String) -> set:\n \"\"\"\n Run the depth first search algorithm to identify all\n the reachable nodes in a graph from the given start \"expert\" node.\n\n This is a iterative DFS algorithm.\n\n :param start: uid of the expert \"Node\" from which the depth first search starts.\n :return: Set of nodes that are reachable from start node.\n \"\"\"\n\n stack = [start]\n reachable_nodes = set()\n network = PlantixCommunityService()\n while stack:\n current_expert_node = stack.pop()\n if current_expert_node not in reachable_nodes:\n reachable_nodes.add(current_expert_node)\n expert = network.get(current_expert_node)\n for following_expert_node in expert.following:\n stack.append(following_expert_node)\n return reachable_nodes\n" }, { "alpha_fraction": 0.6657484173774719, "alphanum_fraction": 0.6675849556922913, "avg_line_length": 39.33333206176758, "blob_id": "06c4d5f969ec8dd2b8a644cba2d80a8c8afa5527", "content_id": "1c1c05d4263f88371fb8f14954769b4a2f75f530", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1089, "license_type": "no_license", "max_line_length": 94, "num_lines": 27, "path": "/helper.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "from PlantixCommunityService import PlantixCommunityService\n\n\ndef generate_plant_experts_topic_count_dict(experts: set) -> dict:\n \"\"\"\n This function returns dict with plant topics covered and the number of experts\n per topic among the given set of experts.\n\n :param network: Dict of network of plant experts with \"uid\" as the keys and values are the\n corresponding PlantExpert objects.\n :param experts: Set of experts.\n :return: Dict containing plant topics(as key) covered among the experts and\n their popularity count(as value which is the number of experts\n available per topic)\n \"\"\"\n network = PlantixCommunityService()\n plant_topic_count_dict = {}\n for expert_id in experts:\n expert = network.get(expert_id)\n for plant_topic in expert.plants:\n if plant_topic in plant_topic_count_dict:\n plant_topic_count_dict[plant_topic] += 1\n else:\n plant_topic_count_dict[plant_topic] = 1\n\n print(plant_topic_count_dict)\n return plant_topic_count_dict\n" }, { "alpha_fraction": 0.699999988079071, "alphanum_fraction": 0.699999988079071, "avg_line_length": 22.1875, "blob_id": "bfdf67b925549203db1157c0d50e52af9a978f64", "content_id": "3164470f706c8d37e8e1d0f7a59171a6fd155c27", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 370, "license_type": "no_license", "max_line_length": 49, "num_lines": 16, "path": "/plant_expert.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "from dataclasses import dataclass\nfrom typing import Text as String, List\n\n\n@dataclass\nclass PlantExpert(object):\n \"\"\"\n Represents a plantix community expert.\n\n Each expert has a unique id, a list of plants\n they can give advice on and a list of other\n expert uid-s they follow.\n \"\"\"\n uid: String\n plants: List[String]\n following: List[String]" }, { "alpha_fraction": 0.6845486760139465, "alphanum_fraction": 0.6922582983970642, "avg_line_length": 41.06756591796875, "blob_id": "c7e29bbb2112ae1aa155b8f1d305b25cae0cb8ab", "content_id": "1dfa5e2f3d12d393c8481f7d957620eb86747557", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 3113, "license_type": "no_license", "max_line_length": 79, "num_lines": 74, "path": "/README.md", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "# Coding Challenge \n\n## Background\n\nPlantix Community is a social network of plant experts, supporting each other \nin diagnosing plant diseases. Each expert has a unique id, a list of plant \nspecies (topics) they can give advice on and a list of other experts they\nfollow:\n\n```\n------------------------------------\n PlantExpert\n------------------------------------\n uid: String\n plants: List[String]\n following: List[String]\n------------------------------------\n fetch(uid: String): PlantExpert\n------------------------------------\n```\n\nThe `fetch(uid)` API is already implemented and available in your Python SDK\n(`plantix.py`). Feel free to re-implement this code if you need to use a \ndifferent programming language.\n\n\n## The challenge\n\nSuppose an expert with `uid=\"0\"` exists. Can you find what topics (plants) \nare covered by the experts in his/her entire network of connections \n(any degree)?\n\n1. Implement a new SDK method in `plantix.PlantixApiClient`, which returns \n a sorted `Tuple[String]` of the `n` most covered plants in the network of \n experts reachable from expert `start`. For example, if there are 5 experts \n on `tomato`, 3 on `banana`, and 10 on `cucumber` - all reachable from user \n with `uid=\"3\"`, this method should return:\n \n ```\n >>> from plantix import *\n >>> PlantixApiClient().find_topics(start=\"3\", n=2)\n ('cucumber', 'tomato')\n ```\n \n in this order.\n2. Write unit- and integration tests for your solution.\n3. Run your solution with input `start=0, n=3`. That is, calculate the top 3 \n most covered plant species in the network of experts reachable from `uid=0`.\n4. Analyze the running time and memory complexity of your solution. Consider \n best- and worst-cases.\n5. Write a small design doc to explain the problem and your approach to solving\n it. Add your `O()` analysis in there too.\n6. Type in the output from (3) as an answer in your application form and \n attach a single zip archive containing all of your source code (1-2) and \n design doc (3-5) for review. For example, if your program produced the \n output `('cucumber', 'tomato')`, you need to type in `cucumber, tomato` in\n the application form and attach a zip file with the SDK, your code, tests,\n and design doc. \n\n\n## Requirements\n\n- This is a small task. If you find yourself writing a lot of code, you might \n want to consider a different approach. \n- Use any modern language you like; however we only provide an \"SDK\" for \n Python. You can use the standard library of your language, but no other \n packages. Your code should compile without any dependencies. \n- Write production-quality, correct, clean, maintainable, testable, tested, \n documented and scalable code. \n- Feel free to remodel `PlantixApiClient`, add new functions, methods, \n properties or classes if necessary. You can't modify `PlantExpert` however.\n- You do not have unlimited amounts of RAM. Your solution should scale.\n- Format your code the way you normally would when working in a team. If using \n Python, follow PEP8 and provide type annotations and docstrings.\n" }, { "alpha_fraction": 0.6648044586181641, "alphanum_fraction": 0.6648044586181641, "avg_line_length": 27.263158798217773, "blob_id": "6700dacffe5ae19612d786ba24c4669a4e063f33", "content_id": "005abbfe36a0d58e395fbb6100f3a3e2e8079966", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 537, "license_type": "no_license", "max_line_length": 68, "num_lines": 19, "path": "/PlantixCommunityService.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "import os\nimport json\n\nfrom typing import Any as Json\nfrom plant_expert import PlantExpert\n\n\nclass PlantixCommunityService(object):\n \"\"\"Simulates the Plantix Community API in-memory and in-process.\n \"\"\"\n COMMUNITY_CACHE = json.load(open(\n os.path.join(os.path.dirname(__file__), \"community.json\")\n ))\n\n def get(self, uid: str) -> Json:\n \"\"\"GET https://plantix.net/community/api/experts/:uid\n \"\"\"\n plants, following = self.COMMUNITY_CACHE[uid]\n return PlantExpert(uid, plants, following)\n" }, { "alpha_fraction": 0.6076672077178955, "alphanum_fraction": 0.6178629398345947, "avg_line_length": 35.05882263183594, "blob_id": "32d03e15849e6b92ff030a173085d7fbe525cf97", "content_id": "56a01997c069b7c4f27930b3e76190299f2e2340", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2452, "license_type": "no_license", "max_line_length": 86, "num_lines": 68, "path": "/tests/unit_test.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "import unittest\nimport json\nimport os\n\nfrom plant_expert import PlantExpert\nfrom tests.plantix_test_helper import PlantixApiClientForTesting\nfrom helper import generate_plant_experts_topic_count_dict\nfrom depth_first_search import depth_first_search_iterative\n\n\nclass PlantixApiClientUnitTest(unittest.TestCase):\n\n def _initiate_plantix_api_client(self):\n self.file_path = os.path.join(os.path.dirname(__file__), \"community.json\")\n self.plantix_api_client = PlantixApiClientForTesting(file_path=self.file_path)\n self.plantix_api_client._generate_network()\n\n def test_json_load(self):\n self._initiate_plantix_api_client()\n community_json = json.load(open(self.file_path))\n assert self.plantix_api_client.COMMUNITY_SERVICE == community_json\n\n def test_fetch(self):\n self._initiate_plantix_api_client()\n community_json = json.load(open(self.file_path))\n uid = \"0\"\n expert = PlantExpert(\n uid=uid,\n plants=community_json[uid][0],\n following=community_json[uid][1],\n )\n assert self.plantix_api_client.fetch(\"0\") == expert\n\n def test_depth_first_search_iterative(self):\n self._initiate_plantix_api_client()\n\n # Node \"3\" is not reachable\n for expert in [\"0\", \"1\", \"2\"]:\n reachable_nodes = depth_first_search_iterative(\n network=self.plantix_api_client.NETWORK,\n start=expert,\n )\n assert reachable_nodes == set([\"0\", \"1\", \"2\"])\n assert \"3\" not in reachable_nodes\n\n # All nodes are reachable from \"3\"\n reachable_nodes = depth_first_search_iterative(\n network=self.plantix_api_client.NETWORK,\n start=\"3\",\n )\n assert reachable_nodes == set([\"0\", \"1\", \"2\", \"3\"])\n\n def test_generate_plant_topic_count_dict(self):\n self._initiate_plantix_api_client()\n plant_topic_count_dict = generate_plant_experts_topic_count_dict(\n network=self.plantix_api_client.NETWORK,\n experts=set([\"3\"]),\n )\n assert plant_topic_count_dict == {\"asparagus\": 1, \"beetroot\": 1}\n plant_topic_count_dict = generate_plant_experts_topic_count_dict(\n network=self.plantix_api_client.NETWORK,\n experts=set([\"2\", \"1\"]),\n )\n assert plant_topic_count_dict == {\"pear\": 2, \"apple\": 1}\n\n\nif __name__ == '__main__':\n unittest.main()\n" }, { "alpha_fraction": 0.6223602294921875, "alphanum_fraction": 0.6223602294921875, "avg_line_length": 31.200000762939453, "blob_id": "b3763115181474b1a26ff63ca3bfe3801bbe086b", "content_id": "00c2e0194f5b9c0fc4a4293da031772cc9749244", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1610, "license_type": "no_license", "max_line_length": 100, "num_lines": 50, "path": "/plantix.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "import os\nimport json\n\nfrom typing import Text as String, Dict\n\nfrom depth_first_search import depth_first_search_iterative\nfrom helper import generate_plant_experts_topic_count_dict\nfrom plant_expert import PlantExpert\n\n\nclass PlantixApiClient(object):\n \"\"\"\n SDK for our Plantix Community API.\n \"\"\"\n\n def fetch(self, uid: String) -> PlantExpert:\n \"\"\"\n Fetch a plant expert by uid.\n \n @param uid: ID of the expert to fetch\n @raise KeyError: if no such uid exists\n \"\"\"\n plants, following = self.COMMUNITY_SERVICE[uid]\n return PlantExpert(uid, plants, following)\n\n def find_topics(self, start: String, n: int) -> tuple:\n \"\"\"\n Find the 'n' most covered plant topics in the network of experts reachable for the expert\n with uid=start.\n\n :param start: ID of the \"start\" expert to calculate the n\n most covered plants in the network of experts\n reachable for this expert.\n :param n: Number of most covered plants in the network of experts reachable for this expert.\n :return: Tuple with 'n' most covered plants in the network.\n \"\"\"\n\n reachable_experts = depth_first_search_iterative(\n start=start,\n )\n\n plant_experts_count_dict = generate_plant_experts_topic_count_dict(\n experts=reachable_experts,\n )\n top_n_plant_topics = sorted(\n plant_experts_count_dict,\n key=plant_experts_count_dict.get,\n reverse=True,\n )[:n]\n return tuple(top_n_plant_topics)\n" }, { "alpha_fraction": 0.6788991093635559, "alphanum_fraction": 0.6880733966827393, "avg_line_length": 24, "blob_id": "898b5e0523ef3df32028df8b713cb0b0c3412933", "content_id": "8b79cc57424889d86336c5507987a7095eb6daa3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 327, "license_type": "no_license", "max_line_length": 71, "num_lines": 13, "path": "/tests/test_payload_generator.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "import json\nimport random\nimport string\n\n\ndef generate_payload(n: int, clique: bool):\n possible_plant_topics = [id_generator() for i in range(10)]\n for node in range(n):\n pass\n\n\ndef id_generator(size=6, chars=string.ascii_uppercase + string.digits):\n return ''.join(random.choice(chars) for _ in range(size))\n\n\n" }, { "alpha_fraction": 0.644385039806366, "alphanum_fraction": 0.6524063944816589, "avg_line_length": 35.19355010986328, "blob_id": "08c40197445b470b01a0da83a4bf8ed6fa2c63e3", "content_id": "1081323a46559b98cb655232604ca8e96c2f2232", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1122, "license_type": "no_license", "max_line_length": 86, "num_lines": 31, "path": "/tests/integration_test.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "from plantix import PlantixApiClient\nfrom plant_expert import PlantExpert\nimport os\nfrom tests.plantix_test_helper import PlantixApiClientForTesting\nimport unittest\n\n\nclass PlantixApiClientIntegrationTest(unittest.TestCase):\n\n def _initiate_plantix_api_client(self):\n self.file_path = os.path.join(os.path.dirname(__file__), \"community.json\")\n self.plantix_api_client = PlantixApiClientForTesting(file_path=self.file_path)\n\n def test_find_topics(self):\n \"\"\"\n \"beetroot\" & \"asparagus\" never appear in this list\n as the expert \"3\" is not followed by anyone\n \"\"\"\n self._initiate_plantix_api_client()\n\n result = self.plantix_api_client.find_topics(start=\"0\", n=2)\n assert result == ('pear', 'apple')\n\n result = self.plantix_api_client.find_topics(start=\"1\", n=2)\n assert result == ('pear', 'apple')\n\n result = self.plantix_api_client.find_topics(start=\"2\", n=2)\n assert set(result) == set(['pear', 'apple'])\n\n result = self.plantix_api_client.find_topics(start=\"3\", n=2)\n assert result == ('pear', 'apple')\n" }, { "alpha_fraction": 0.7049180269241333, "alphanum_fraction": 0.7049180269241333, "avg_line_length": 25.88888931274414, "blob_id": "3dd34896aaefcb6ace270b71bff68d6317112f58", "content_id": "3f7865c7b84f4aac9e7ca46775993f7d2831f378", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 244, "license_type": "no_license", "max_line_length": 63, "num_lines": 9, "path": "/tests/plantix_test_helper.py", "repo_name": "Wise-Economy/plantix", "src_encoding": "UTF-8", "text": "from plantix import PlantixApiClient\nimport json\n\n\nclass PlantixApiClientForTesting(PlantixApiClient):\n\n def __init__(self, file_path=None):\n if file_path is not None:\n self.COMMUNITY_SERVICE = json.load(open(file_path))\n\n\n" } ]	10
2020mt93220/upload_platform	https://github.com/2020mt93220/upload_platform	5034c3aab4042f9587e22ec23489bb09466bed99	f6774853bd1f72e9c3e6468b148dc147e0d02e71	a6c86147c4fb006ea0306b279abf6ceaa9ed47dc	refs/heads/main	2023-08-22T16:21:26.025821	2021-10-19T07:21:48	2021-10-19T07:21:48	418,155,944	0	1	null	2021-10-17T14:22:56	2021-10-18T20:21:27	2021-10-19T07:21:48	Python	[ { "alpha_fraction": 0.8235294222831726, "alphanum_fraction": 0.8235294222831726, "avg_line_length": 16, "blob_id": "31760e320326854ce2fa2659edf9fc304be79e57", "content_id": "6c381e0834541c1ffebeed44c8043d8cafc75863", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 34, "license_type": "no_license", "max_line_length": 17, "num_lines": 2, "path": "/README.md", "repo_name": "2020mt93220/upload_platform", "src_encoding": "UTF-8", "text": "# upload_platform\nupload_platform\n" }, { "alpha_fraction": 0.4637168049812317, "alphanum_fraction": 0.47079646587371826, "avg_line_length": 19.80769157409668, "blob_id": "080bacf24ad1872e34ffd9ab5ef5b6ecdcc855f1", "content_id": "c1c82615c621e4f57ac43a0f4a3a68af32ef483a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "HTML", "length_bytes": 565, "license_type": "no_license", "max_line_length": 68, "num_lines": 26, "path": "/templates/fileUploadSuccessful.html", "repo_name": "2020mt93220/upload_platform", "src_encoding": "UTF-8", "text": "<html>\r\n <head>\r\n <title>File Upload Successfully</title>\r\n <style>\r\n .success{\r\n color:green;\r\n }\r\n .danger{\r\n color:red;\r\n }\r\n </style>\r\n </head>\r\n <body>\r\n <!-- Flash Message -->\r\n {% with messages = get_flashed_messages(with_categories=true) %}\r\n {% if messages %}\r\n {% for category, message in messages %}\r\n <h3 class='{{category}}'>{{ message }}</h3>\r\n {% endfor %}\r\n {% endif %}\r\n {% endwith %}\r\n \r\n \r\n <h2>Files Uploaded Successfully ..!!</h2>\r\n </body>\r\n</html>" }, { "alpha_fraction": 0.5851955413818359, "alphanum_fraction": 0.6012569665908813, "avg_line_length": 33.79999923706055, "blob_id": "4e9df2888258314ace4ec2144d13bf78d57ed241", "content_id": "2ff37b6733995ad29ccd36e7b1f006eb54716c8b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1432, "license_type": "no_license", "max_line_length": 104, "num_lines": 40, "path": "/app.py", "repo_name": "2020mt93220/upload_platform", "src_encoding": "UTF-8", "text": "\r\nfrom flask import Flask,render_template,request,redirect,flash\r\nfrom werkzeug.utils import secure_filename\r\nimport os\r\nimport random\r\n\r\nUPLOAD_FOLDER =\"static/files\"\r\nFILE_EXTENSIONS = {'txt', 'pdf', 'png', 'jpg', 'jpeg', 'gif'}\r\n\r\napp = Flask(__name__)\r\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\r\n\r\n#check file extension\r\ndef allowed_extensions(file_name):\r\n return '.' in file_name and file_name.rsplit('.',1)[1].lower() in FILE_EXTENSIONS\r\n \r\n#file Upload\r\[email protected](\"/fileUpload\",methods=['GET','POST'])\r\ndef fileUpload():\r\n if request.method=='POST':\r\n if 'file' not in request.files:\r\n flash('No file part','danger')\r\n \r\n file = request.files['file']\r\n \r\n if file.filename == '':\r\n flash('No file selected','danger')\r\n \r\n if file and allowed_extensions(file.filename):\r\n filename, file_extension = os.path.splitext(file.filename)\r\n new_filename = secure_filename(filename+str(random.randint(10000,99999))+\".\"+file_extension)\r\n file.save(os.path.join(UPLOAD_FOLDER, new_filename)) \r\n \r\n flash(' Uploaded Successfully','success')\r\n # return render_template('fileUploadSuccessful.html')\r\n \r\n return render_template('fileUpload.html')\r\n \r\nif __name__=='__main__':\r\n app.secret_key='secret123'\r\n app.run(host='0.0.0.0',port=7000,debug=True)" } ]	3
RichardsonMark/functions-homework	https://github.com/RichardsonMark/functions-homework	c2397cb66c94c465656644449ffe016f7ee07bec	6b33d2c8370071561579e9e89590ddc4688dd8bc	8f1bf6f82b3b18efba49398d9820657421fd2ed5	refs/heads/master	2023-01-05T17:09:31.112602	2020-11-04T23:34:08	2020-11-04T23:34:08	310,067,702	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6406705379486084, "alphanum_fraction": 0.6822157502174377, "avg_line_length": 22.672412872314453, "blob_id": "cc215a8859d870269456461e1ec0585101a8729f", "content_id": "d31561e396acfc9c17ed9e6f4316669235e1f591", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1372, "license_type": "no_license", "max_line_length": 58, "num_lines": 58, "path": "/start_point/src/python_functions_practice.py", "repo_name": "RichardsonMark/functions-homework", "src_encoding": "UTF-8", "text": "def return_10():\n return 10\n\ndef add(num1, num2):\n return num1 + num2\n\ndef subtract(num1, num2):\n return num1 - num2\n\ndef multiply(num1, num2):\n return num1 * num2\n\ndef divide(num1, num2):\n return num1 / num2\n\ndef length_of_string(string):\n return len(string)\n\ndef join_string(string_1, string_2):\n return (string_1 + string_2)\n\ndef add_string_as_number(string_1, string_2):\n return (int(string_1) + int(string_2))\n\nimport calendar\ndef number_to_full_month_name(month1):\n return(calendar.month_name[month1])\n\ndef number_to_full_month_name1(month3):\n return(calendar.month_name[month3])\n\ndef number_to_full_month_name2(month9):\n return(calendar.month_name[month9])\n\ndef number_to_short_month_name(month1):\n return(calendar.month_abbr[month1])\n\ndef number_to_short_month_name(month4):\n return(calendar.month_abbr[month4])\n\ndef number_to_short_month_name(month10):\n return(calendar.month_abbr[month10])\n\ndef volume_of_cube(width):\n # work out vol and / 1000 (change from ml cubed to ml)\n volume = width * width * width\n volume = volume / 1000\n return(volume)\n\ndef reverse_string(string_forward):\n # Slice the string to reverse it\n string_reversed = \"test\" [::-1]\n return(string_reversed)\n\ndef fahrenheit_to_celsius(tempF):\n # convert to celsius\n celsius = (tempF - 32) * 5/9\n return(celsius)" } ]	1
Astoulo/master-package-astoulosock	https://github.com/Astoulo/master-package-astoulosock	021c3dc5902f049ffd28a8d3a447aa74e00174a9	9fdbc421d5b602bfb3982af1fbd0d739e7b89f77	dc48bc91df5a647d0716f273fa8868fde6f6ea0a	refs/heads/main	2023-01-22T05:35:41.517564	2020-12-03T17:57:57	2020-12-03T17:57:57	317,943,738	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6963858604431152, "alphanum_fraction": 0.7132611274719238, "avg_line_length": 45.092716217041016, "blob_id": "18263c024ebd8547b0c72c0ad697afd08d2a27c3", "content_id": "4f856b9f4816ba10b6ed92e326d78099fe297952", "detected_licenses": [ "WTFPL" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7153, "license_type": "permissive", "max_line_length": 120, "num_lines": 151, "path": "/setup.py", "repo_name": "Astoulo/master-package-astoulosock", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\r\n# -- coding: utf-8 --\r\n\r\nfrom setuptools import setup, find_packages\r\n# notez qu'on import la lib\r\n\r\nimport master_package_astousock\r\n\r\n# Ceci n'est qu'un appel de fonction. Mais il est trèèèèèèèèèèès long\r\n# et il comporte beaucoup de paramètres\r\nsetup(\r\n \r\n # le nom de votre bibliothèque, tel qu'il apparaitre sur pypi\r\n name='master_package_astousock',\r\n \r\n # la version du code\r\n version=master_package_astousock.__version__,\r\n \r\n # Liste les packages à insérer dans la distribution\r\n # plutôt que de le faire à la main, on utilise la foncton\r\n # find_packages() de setuptools qui va cherche tous les packages\r\n # python recursivement dans le dossier courant.\r\n # C'est pour cette raison que l'on a tout mis dans un seul dossier:\r\n # on peut ainsi utiliser cette fonction facilement\r\n packages=find_packages(),\r\n \r\n # votre pti nom \r\n author=\"Astou Lo Sock\",\r\n \r\n # Votre email, sachant qu'il sera publique visible, avec tous les risques\r\n # que ça implique.\r\n author_email=\"[email protected]\",\r\n \r\n # Une description courte\r\n description=\"\"\"Il existe 2 modules dans ce package:\r\n annee_bissextile() pour vérifier si la valeur saisie est bissextile ou pas \r\n multiplication() pour retourner la table de multiplication de la valeur saisie\"\"\",\r\n \r\n # Une description longue, sera affichée pour présenter la lib\r\n # Généralement on dump le README ici\r\n long_description=open('README.md').read(),\r\n \r\n # Vous pouvez rajouter une liste de dépendances pour votre lib\r\n # et même préciser une version. A l'installation, Python essayera de\r\n # les télécharger et les installer.\r\n #\r\n # Ex: [\"gunicorn\", \"docutils >= 0.3\", \"lxml==0.5a7\"]\r\n #\r\n # Dans notre cas on en a pas besoin, donc je le commente, mais je le\r\n # laisse pour que vous sachiez que ça existe car c'est très utile.\r\n # install_requires= ,\r\n \r\n # Active la prise en compte du fichier MANIFEST.in\r\n include_package_data=True,\r\n \r\n # Une url qui pointe vers la page officielle de votre lib\r\n url='https://github.com/Astoulo/master-package-astoulosock',\r\n \r\n # Il est d'usage de mettre quelques metadata à propos de sa lib\r\n # Pour que les robots puissent facilement la classer.\r\n # La liste des marqueurs autorisées est longue:\r\n # https://pypi.python.org/pypi?%3Aaction=list_classifiers.\r\n #\r\n # Il n'y a pas vraiment de règle pour le contenu. Chacun fait un peu\r\n # comme il le sent. Il y en a qui ne mettent rien.\r\n classifiers=[\r\n \"Programming Language :: Python\",\r\n \"Development Status :: 1 - Planning\",\r\n \"License :: OSI Approved\",\r\n \"Natural Language :: French\",\r\n \"Operating System :: OS Independent\",\r\n \"Programming Language :: Python :: 2.7\",\r\n \"Topic :: Communications\",\r\n ],\r\n \r\n \r\n # C'est un système de plugin, mais on s'en sert presque exclusivement\r\n # Pour créer des commandes, comme \"django-admin\".\r\n # Par exemple, si on veut créer la fabuleuse commande \"annee_bissextile-sm\", on\r\n # va faire pointer ce nom vers la fonction annee_bissextiler(). La commande sera\r\n # créé automatiquement. \r\n # La syntaxe est \"nom-de-commande-a-creer = package.module:fonction\".\r\n entry_points = {\r\n 'console_scripts': [\r\n 'annee_bissextile-sm = master_package_astousock.annee_bissextile:annee_bissextile',\r\n 'multiplication-sm = master_package_astousock.table_multiplication:multiplication',\r\n\r\n ],\r\n },\r\n \r\n # A fournir uniquement si votre licence n'est pas listée dans \"classifiers\"\r\n # ce qui est notre cas\r\n license=\"WTFPL\",\r\n \r\n # Il y a encore une chiée de paramètres possibles, mais avec ça vous\r\n # couvrez 90% des besoins\r\n \r\n)\r\n\r\n\r\n# running install\r\n# running bdist_egg\r\n# running egg_info\r\n# creating master_package.egg-info\r\n# writing master_package.egg-info\\PKG-INFO\r\n# writing dependency_links to master_package.egg-info\\dependency_links.txt\r\n# writing entry points to master_package.egg-info\\entry_points.txt\r\n# writing top-level names to master_package.egg-info\\top_level.txt\r\n# writing manifest file 'master_package.egg-info\\SOURCES.txt'\r\n# reading manifest file 'master_package.egg-info\\SOURCES.txt'\r\n# reading manifest template 'MANIFEST.in'\r\n# writing manifest file 'master_package.egg-info\\SOURCES.txt'\r\n# installing library code to build\\bdist.win-amd64\\egg\r\n# running install_lib\r\n# running build_py\r\n# creating build\r\n# creating build\\lib\r\n# creating build\\lib\\master_package\r\n# copying master_package\\annee_bissextile.py -> build\\lib\\master_package\r\n# copying master_package\\table_multiplication.py -> build\\lib\\master_package\r\n# copying master_package\\__init__.py -> build\\lib\\master_package\r\n# creating build\\bdist.win-amd64\r\n# creating build\\bdist.win-amd64\\egg\r\n# creating build\\bdist.win-amd64\\egg\\master_package\r\n# copying build\\lib\\master_package\\annee_bissextile.py -> build\\bdist.win-amd64\\egg\\master_package\r\n# copying build\\lib\\master_package\\table_multiplication.py -> build\\bdist.win-amd64\\egg\\master_package\r\n# copying build\\lib\\master_package\\__init__.py -> build\\bdist.win-amd64\\egg\\master_package\r\n# byte-compiling build\\bdist.win-amd64\\egg\\master_package\\annee_bissextile.py to annee_bissextile.cpython-37.pyc\r\n# byte-compiling build\\bdist.win-amd64\\egg\\master_package\\table_multiplication.py to table_multiplication.cpython-37.pyc\r\n# byte-compiling build\\bdist.win-amd64\\egg\\master_package\\__init__.py to __init__.cpython-37.pyc\r\n# creating build\\bdist.win-amd64\\egg\\EGG-INFO\r\n# copying master_package.egg-info\\PKG-INFO -> build\\bdist.win-amd64\\egg\\EGG-INFO\r\n# copying master_package.egg-info\\SOURCES.txt -> build\\bdist.win-amd64\\egg\\EGG-INFO\r\n# copying master_package.egg-info\\dependency_links.txt -> build\\bdist.win-amd64\\egg\\EGG-INFO\r\n# copying master_package.egg-info\\entry_points.txt -> build\\bdist.win-amd64\\egg\\EGG-INFO\r\n# copying master_package.egg-info\\top_level.txt -> build\\bdist.win-amd64\\egg\\EGG-INFO\r\n# zip_safe flag not set; analyzing archive contents...\r\n# creating dist\r\n# creating 'dist\\master_package-0.0.1-py3.7.egg' and adding 'build\\bdist.win-amd64\\egg' to it\r\n# removing 'build\\bdist.win-amd64\\egg' (and everything under it)\r\n# Processing master_package-0.0.1-py3.7.egg\r\n# Copying master_package-0.0.1-py3.7.egg to c:\\users\\tmp_sarr51958.orange-sonatel\\anaconda3\\lib\\site-packages\r\n# Adding master-package 0.0.1 to easy-install.pth file\r\n# Installing annee_bissextile-sm-script.py script to C:\\Users\\tmp_sarr51958.ORANGE-SONATEL\\Anaconda3\\Scripts\r\n# Installing annee_bissextile-sm.exe script to C:\\Users\\tmp_sarr51958.ORANGE-SONATEL\\Anaconda3\\Scripts\r\n# Installing multiplication-sm-script.py script to C:\\Users\\tmp_sarr51958.ORANGE-SONATEL\\Anaconda3\\Scripts\r\n# Installing multiplication-sm.exe script to C:\\Users\\tmp_sarr51958.ORANGE-SONATEL\\Anaconda3\\Scripts\r\n\r\n# Installed c:\\users\\tmp_sarr51958.orange-sonatel\\anaconda3\\lib\\site-packages\\master_package-0.0.1-py3.7.egg\r\n# Processing dependencies for master-package==0.0.1\r\n# Finished processing dependencies for master-package==0.0.1\r\n" }, { "alpha_fraction": 0.6258277893066406, "alphanum_fraction": 0.6274834275245667, "avg_line_length": 25.454545974731445, "blob_id": "6cf958a7f0505b1f2d0ce350e64942dd42653a41", "content_id": "2b14cccee8000d4cc9efb18c238a2ec07b98441f", "detected_licenses": [ "WTFPL" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 606, "license_type": "permissive", "max_line_length": 92, "num_lines": 22, "path": "/README.md", "repo_name": "Astoulo/master-package-astoulosock", "src_encoding": "UTF-8", "text": "Création de Packages\r\n========================================================\r\n\r\nIl existe 2 modules dans ce package:\r\n ---- annee_bissextile pour vérifier si la valeur saisie est bissextile ou pas \r\n -----table_multiplication pour retourner la table de multiplication de la valeur saisie.\r\n\r\n\r\nVous pouvez l'installer avec pip:\r\n\r\n pip install master_package\r\n\r\nExemple d'usage:\r\n\r\n >>> from .annee_bissextile import annee_bissextile\r\n >>> annee_bissextile()\r\n\r\n >>> from .table_multiplication import multiplication\r\n >>> multiplication()\r\n \r\n\r\nCe code est sous licence WTFPL.\r\n" }, { "alpha_fraction": 0.5537340641021729, "alphanum_fraction": 0.5737704634666443, "avg_line_length": 23.045454025268555, "blob_id": "838a28c886923180e9a264fec99b579fa81398a5", "content_id": "732a22277a535e56884ff3cdb9c162370d8f2160", "detected_licenses": [ "WTFPL" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 558, "license_type": "permissive", "max_line_length": 56, "num_lines": 22, "path": "/build/lib/master_package_astousock/annee_bissextile.py", "repo_name": "Astoulo/master-package-astoulosock", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\r\n# -- coding: utf-8 --\r\n \r\n\"\"\"\r\n Implémentation de l'année à verifier.\r\n \r\n Usage:\r\n \r\n >>> from .annee_bissextile import annee_bissextile\r\n >>> annee_bissextile()\r\n\"\"\" \r\n__all__ = ['annee_bissextile']\r\ndef annee_bissextile():\r\n\r\n annee = int(input(\"Entrez l'année à verifier:\"))\r\n if(annee %4== 0 and annee%100!=0 or annee%400==0):\r\n print(\"L'année est une année bissextile!\")\r\n else:\r\n print(\"L'année n'est pas une année bissextile!\")\r\n\r\nif __name__ == \"__main__\":\r\n annee_bissextile()" }, { "alpha_fraction": 0.48830682039260864, "alphanum_fraction": 0.5182413458824158, "avg_line_length": 29.5, "blob_id": "b76dfd165dcbac693cb822d802c89fcbc5908eeb", "content_id": "baac8b123259386040744626cb68469ae6d8fb6d", "detected_licenses": [ "WTFPL" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1072, "license_type": "permissive", "max_line_length": 94, "num_lines": 34, "path": "/master_package_astousock/table_multiplication.py", "repo_name": "Astoulo/master-package-astoulosock", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\r\n# -- coding: utf-8 --\r\n \r\n\"\"\"\r\n Implémentation de la table de multiplication de la valeur saisie\r\n \r\n Usage:\r\n \r\n >>> from .table_multiplication import multiplication\r\n >>> multiplication()\r\n\"\"\" \r\n__all__ = ['multiplication']\r\n\r\ndef multiplication():\r\n valeur = int(input(\"Entrez une valeur positive pour générer la table de multiplication:\"))\r\n if(valeur > 0):\r\n\r\n print(valeur , \"* 1 =\" , valeur 1)\r\n print(valeur , \" 2 =\" , valeur 2)\r\n print(valeur , \" 3 =\" , valeur 3)\r\n print(valeur , \" 4 =\" , valeur 4)\r\n print(valeur , \" 5 =\" , valeur 5)\r\n print(valeur , \" 6 =\" , valeur 6)\r\n print(valeur , \" 7 =\" , valeur 7)\r\n print(valeur , \" 8 =\" , valeur 8)\r\n print(valeur , \" 9 =\" , valeur 9)\r\n print(valeur , \" 10 =\" , valeur 10)\r\n print(valeur , \" 11 =\" , valeur 11)\r\n print(valeur , \" 12 =\" , valeur 12)\r\n else:\r\n print(\"veuillez entrer une valeur positive\")\r\n\r\nif __name__ == \"__main__\":\r\n multiplication()" }, { "alpha_fraction": 0.6723716259002686, "alphanum_fraction": 0.684596598148346, "avg_line_length": 27.35714340209961, "blob_id": "100216a9b7a6706ff0aa4112cd1738a14381cfc4", "content_id": "0009ee58ba23dee64df1d2f0fb9f59f857c95c0c", "detected_licenses": [ "WTFPL" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 409, "license_type": "permissive", "max_line_length": 92, "num_lines": 14, "path": "/build/lib/master_package_astousock/__init__.py", "repo_name": "Astoulo/master-package-astoulosock", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\r\n# -- coding: utf-8 -*-\r\n \r\n\"\"\" \r\n Il existe 2 modules dans ce package:\r\n ---- annee_bissextile pour retourner si la valeur saisie est bissextile ou pas \r\n -----table_multiplication pour retourner la table de multiplication de la valeur saisie.\r\n\r\n\"\"\"\r\n \r\n__version__ = \"0.0.1\"\r\n\r\nfrom .annee_bissextile import annee_bissextile\r\nfrom .table_multiplication import multiplication" } ]	5
EmilyPeng2017/Python_Mooc	https://github.com/EmilyPeng2017/Python_Mooc	fc416466f0a3f629c50f3a2604b05b2ea7e3a0f4	998e0547e319cd5d805555318d89c1ae7f09ea25	9f42d3daf02d3002373fbb49f6c87a7c1fd7e5e6	refs/heads/master	2020-03-13T12:54:08.940445	2018-05-02T13:47:31	2018-05-02T13:47:31	131,128,433	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.7297297120094299, "alphanum_fraction": 0.7297297120094299, "avg_line_length": 17.5, "blob_id": "c3d8226f06023402c7366a0b84ef004d808cd2e0", "content_id": "acf0ad6739470ce5751c7c7126ab54c57090a14a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 37, "license_type": "no_license", "max_line_length": 22, "num_lines": 2, "path": "/README.md", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "# Python_Mooc\n#this is from pycharm!\n" }, { "alpha_fraction": 0.5177664756774902, "alphanum_fraction": 0.5532994866371155, "avg_line_length": 16.909090042114258, "blob_id": "75aa33a72adbb5986f6a51a20775196d2b62bc48", "content_id": "b6e0a658a713d2b0fc4faf4cb9ec840ed287236b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 269, "license_type": "no_license", "max_line_length": 29, "num_lines": 11, "path": "/Practice/006.py", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "#!/usr/bin/python\n# -- coding: utf-8 --\n'''\n题目：用号输出字母C的图案。\n1.程序分析：可先用''号在纸上写出字母C，再分行输出。\n'''\nprint 'Hello Python world!\\n'\nprint '' 10\nfor i in range(5):\n print '* '\nprint '' 10\n" }, { "alpha_fraction": 0.4936247766017914, "alphanum_fraction": 0.5373406410217285, "avg_line_length": 20.959999084472656, "blob_id": "1552e39dadd8eb5bdb7d3b0d17a1e01f53d74895", "content_id": "e3cebc41b66cb51b7e9c9ff1daa4e3e18f197cf3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 651, "license_type": "no_license", "max_line_length": 44, "num_lines": 25, "path": "/Practice/009.py", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "#!/usr/bin/python\n# -- coding: utf-8 --\n'''\n题目：要求输出国际象棋棋盘。\n1.程序分析：用i控制行，j来控制列，根据i+j的和的变化来控制输出黑方格，还是白方格。\n'''\n# import sys\n# for i in range(8):\n# for j in range(8):\n# if(i + j) % 2 == 0:\n# sys.stdout.write(chr(219))\n# sys.stdout.write(chr(219))\n# else:\n# sys.stdout.write(' ')\n# print ''\nimport sys\nsys.stdout.write(chr(1))\nsys.stdout.write(chr(1))\nprint ''\n\nfor i in range(1,11):\n for j in range(1,i):\n sys.stdout.write(chr(219))\n sys.stdout.write(chr(219))\n print ''\n" }, { "alpha_fraction": 0.4900285005569458, "alphanum_fraction": 0.5925925970077515, "avg_line_length": 24.14285659790039, "blob_id": "3d9cce31a01f9103f59b0a3a589e41b68c578ce4", "content_id": "af277bd22f997360c941c02f1836c2949e3c3193", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 563, "license_type": "no_license", "max_line_length": 49, "num_lines": 14, "path": "/Practice/003.py", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "#!/usr/bin/python\n# -- coding: utf-8 --\n'''\n【程序3】\n题目：一个整数，它加上100后是一个完全平方数，再加上168又是一个完全平方数，请问该数是多少？\n1.程序分析：在10万以内判断，先将该数加上100后再开方，再将该数加上268后再开方，如果开方后\n　　　　　　的结果满足如下条件，即是结果。\n'''\nimport math\nfor i in range(0,100000):\n x = int(math.sqrt(i+100))\n y = int(math.sqrt(i+268))\n if(x * x == i+100) and (y * y == i+268):\n print i" }, { "alpha_fraction": 0.5033921599388123, "alphanum_fraction": 0.510176420211792, "avg_line_length": 17.450000762939453, "blob_id": "ef69a0b1c15094d120d4e1aba4a8e96abae98157", "content_id": "0bf989228041f76a717ee7dd03bbaeb8457a5db3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 951, "license_type": "no_license", "max_line_length": 49, "num_lines": 40, "path": "/Practice/005.py", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "#!/usr/bin/python\n# -- coding: utf-8 --\n'''\n【程序5】\n题目：输入三个整数x,y,z，请把这三个数由小到大输出。\n1.程序分析：我们想办法把最小的数放到x上，先将x与y进行比较，如果x>y则将x与y的值进行交换，\n　　　　　　然后再用x与z进行比较，如果x>z则将x与z的值进行交换，这样能使x最小。\n2.程序源代码：\n'''\n# x = int(raw_input(\"input x: \"))\n# y = int(raw_input(\"input y: \"))\n# z = int(raw_input(\"input z: \"))\n# if x>y:\n# first = x\n# x = y\n# else:\n# first = y\n# y = x\n# if z>first:\n# second = first\n# first = z\n# third = x\n# else:\n# if z>x:\n# second = z\n# third = x\n# else:\n# second = x\n# third = z\n# print third,second,first\nl = []\nfor i in range(3):\n x = int(raw_input('integer:\\n'))\n l.append(x)\n #\nl.sort()\nprint l\n# x = ['mmm', 'mm', 'mm', 'm' ]\n# x.sort(key = len)\n# print x" }, { "alpha_fraction": 0.613043487071991, "alphanum_fraction": 0.643478274345398, "avg_line_length": 15.5, "blob_id": "231c5fac856ccdc8f49e217d4d909e4673c08a90", "content_id": "52fd577140e42eb26b9b0c2c0f4b041e434fe9ee", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 380, "license_type": "no_license", "max_line_length": 51, "num_lines": 14, "path": "/python_Advantaged/2_2.py", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "#!/usr/bin/python\n# -- coding: utf-8 --\n'''\n变量可以指向函数，函数名其实就是指向函数的变量\n'''\n# print abs(-111)\n'''\n高阶函数：能够接收函数作为参数的函数\ndemo:接收abs函数作为参数，定义一个函数，接收x,y,f三个参数，其中x.y是普通的数，f是函数\n'''\ndef add(x,y,f):\n return f(x)+f(y)\n\nprint add(-1,-22,abs)" }, { "alpha_fraction": 0.523809552192688, "alphanum_fraction": 0.557823121547699, "avg_line_length": 28.399999618530273, "blob_id": "c778bc23c665571cc7ecf9dd10fede39a356ddab", "content_id": "30627c9a32bc33bda0268fed8129506fc6012f43", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 294, "license_type": "no_license", "max_line_length": 66, "num_lines": 10, "path": "/Practice/001.py", "repo_name": "EmilyPeng2017/Python_Mooc", "src_encoding": "UTF-8", "text": "'''\nthere are 1,2,3,4 four numbers, how many different three-digit\nnumbers will they compose(no same numbers in a three-digit number)\n'''\n\nfor i in range(1,5):\n for j in range(1,5):\n for k in range(1,5):\n if( i != k ) and (i != j) and (j != k):\n print i,j,k\n" } ]	7
giancarlo92/DjangoInicios	https://github.com/giancarlo92/DjangoInicios	f919f6b977531a9dbfa28a19a566d3371ca7fdd6	b587cd040099c28dba4485a50c470eef604d019f	351fad410635ff0f06bf345af8b8e2cc2bc31bf3	refs/heads/master	2022-10-09T12:58:10.250804	2019-02-21T05:59:35	2019-02-21T05:59:35	171,564,638	0	1	null	2019-02-19T23:08:28	2019-02-21T06:03:07	2019-02-21T06:03:06	Python	[ { "alpha_fraction": 0.7139107584953308, "alphanum_fraction": 0.7139107584953308, "avg_line_length": 26.285715103149414, "blob_id": "b3e2a51ca1655cb49a2fa354ac6d85c539b8942f", "content_id": "411eafceda7a4340d0be96e3621f726f8c2138e4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 381, "license_type": "no_license", "max_line_length": 103, "num_lines": 14, "path": "/libro/app/home/views.py", "repo_name": "giancarlo92/DjangoInicios", "src_encoding": "UTF-8", "text": "from django.shortcuts import render\n\nfrom django.views.generic import (\n TemplateView,\n ListView\n)\n\nclass IndexView(TemplateView):\n template_name = \"home/index.html\"\n\nclass ListaLibros(ListView):\n template_name = \"home/lista.html\"\n queryset = [\"El quijote de la mancha\", \"Codigo Limpio\", \"La sombra del viento\", \"La casa Matusita\"]\n context_object_name = \"libros\"" }, { "alpha_fraction": 0.6790697574615479, "alphanum_fraction": 0.6790697574615479, "avg_line_length": 22.88888931274414, "blob_id": "716970cac3c423f5f2a0e880ad9bb7cd9a57a08f", "content_id": "94c23e352a2e31696f8804c3b64a33b62c5a1f5b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 215, "license_type": "no_license", "max_line_length": 46, "num_lines": 9, "path": "/libro/libro/urls.py", "repo_name": "giancarlo92/DjangoInicios", "src_encoding": "UTF-8", "text": "\"\"\"libro URL Configuration\n\"\"\"\nfrom django.contrib import admin\nfrom django.urls import path, re_path, include\n\nurlpatterns = [\n re_path(r'^', include('app.home.urls')),\n re_path('admin/', admin.site.urls),\n]\n" } ]	2
saurabhmaurya45/TextUtils	https://github.com/saurabhmaurya45/TextUtils	a340356ab43dd17ec971fb90781e4fbce698fed4	dc99775df4794319bebb650f388ae2cc413d51dd	b7321ae743455da091a0e35fbab3e17d2a25a13d	refs/heads/master	2023-08-09T11:11:56.815899	2021-09-18T08:44:45	2021-09-18T08:44:45	407,797,625	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7560975551605225, "alphanum_fraction": 0.7560975551605225, "avg_line_length": 19.5, "blob_id": "bec5bad7a10f43dbb322b861c4b703a9dce787ff", "content_id": "3851538937e569957e949994dbd0394f72e4263b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 41, "license_type": "no_license", "max_line_length": 28, "num_lines": 2, "path": "/README.md", "repo_name": "saurabhmaurya45/TextUtils", "src_encoding": "UTF-8", "text": "# TextUtils\nA website to play with text.\n" }, { "alpha_fraction": 0.5818624496459961, "alphanum_fraction": 0.5824710726737976, "avg_line_length": 30.615385055541992, "blob_id": "c450359bd89a8d63797f1430ab1773a0291c5d35", "content_id": "4e8e524c0820b1b65d8dea413db8d321628cad99", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1643, "license_type": "no_license", "max_line_length": 68, "num_lines": 52, "path": "/textutils/views.py", "repo_name": "saurabhmaurya45/TextUtils", "src_encoding": "UTF-8", "text": "from django.shortcuts import render\n\n\ndef index(request):\n return render(request, 'index.html')\n\ndef response(request):\n # get text\n got_text = request.POST.get(\"text\", 'default')\n print(got_text)\n # get actions\n upper = request.POST.get(\"upper\", \"off\")\n print(upper)\n removepunc = request.POST.get(\"puncrem\", \"off\")\n print(removepunc)\n extraspaceremover = request.POST.get(\"extraspaceremover\", \"off\")\n print(extraspaceremover)\n extralineremover = request.POST.get(\"Extralinesremover\", \"off\")\n print(extralineremover)\n actions=[]\n analysed_text=\"\"\n # checks\n if (upper!=\"off\"):\n actions.append('UPPER CASE')\n got_text=got_text.upper()\n if (removepunc!=\"off\"):\n actions.append('Remove Punctuation')\n string=\"\"\n punctuations=\"\"\"!\"#$%&'()*+,-./:;<=>?@[\\]^_`{\|}~\"\"\"\n for char in got_text:\n if not(char in punctuations):\n string+=char\n got_text=string\n if (extraspaceremover!=\"off\"):\n actions.append(\"Extra Space Remover\")\n string=\"\"\n for index, char in enumerate(got_text):\n if not(got_text[index]==' ' and got_text[index+1]==' '):\n string+=char\n got_text=string\n if extralineremover==\"on\":\n actions.append(\"Extra Line Remover\")\n analyzed=\"\"\n for char in got_text:\n if char!=\"\\n\":\n analyzed=analyzed+char\n # Analyze the text\n got_text=analyzed\n print(got_text)\n print(actions)\n params = {\"purpose\": actions, \"analysed_text\": got_text}\n return render(request, 'response.html', params)" } ]	2
tryewq/Pandas-Experiment	https://github.com/tryewq/Pandas-Experiment	3c700eded0bea761be4d1be5f199edf938976cf2	8b79a316cdcb3d0ab831a9da4a8a9990d07b4b12	eb04c8f03102ddc2542229acdd2d9f5e115cd171	refs/heads/master	2020-09-22T02:20:02.284864	2019-11-30T13:26:50	2019-11-30T13:26:50	225,016,129	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.625, "alphanum_fraction": 0.65625, "avg_line_length": 22, "blob_id": "5b65b986fbe108d82d19f098be98e0a132acc4f3", "content_id": "9e60a5a9e67fae32c195dc442ce90e70b71364c7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 192, "license_type": "no_license", "max_line_length": 42, "num_lines": 8, "path": "/Problem 1.py", "repo_name": "tryewq/Pandas-Experiment", "src_encoding": "UTF-8", "text": "import pandas as pd\r\n#Load the corresponding .csv file\r\na = pd.read_csv('cars.csv')\r\n\r\n#display the first five and last five rows\r\nb = a.iloc[0:5]\r\nc = a.iloc[27:32]\r\ncars = pd.concat([b,c])\r\n" }, { "alpha_fraction": 0.6287702918052673, "alphanum_fraction": 0.6658932566642761, "avg_line_length": 31.30769157409668, "blob_id": "8a2c788145f5f37c2993e3829b7c06a17da40889", "content_id": "f1567f2b767d0ae1862057147cf60cbee50f6e7e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 431, "license_type": "no_license", "max_line_length": 81, "num_lines": 13, "path": "/Problem 2.py", "repo_name": "tryewq/Pandas-Experiment", "src_encoding": "UTF-8", "text": "import pandas as pd\r\na = pd.read_csv('cars.csv')\r\n#display the first five rows with odd-numbered columns\r\no = a.iloc[0:5,0::2]\r\n\r\n#display the row that contains the \"Model\" of \"Mazda RX4\"\r\nRowMoMazda = a.loc[[0]]\r\n\r\n#no. of cylinders that the Camaro Z28 has\r\nCamaro_cyl = a.loc[[23],['Model','cyl']]\r\n\r\n#no. of cylinders and gear type of Mazda RX4 Wag, Ford Pantera L, and Honda Civic\r\ncng = a.loc[[1,28,18],['Model','cyl','gear']]" } ]	2
davidgaleano/gevent-fastcgi	https://github.com/davidgaleano/gevent-fastcgi	645346d89fbb9938bae9ff5f71938c76535905ac	d143342208ddd45f01908689f2a53f514e9423b3	f4267e0ad246471eb99e6ca448071eb16845d256	refs/heads/master	2021-01-18T08:14:06.025463	2012-03-28T13:56:36	2012-03-28T13:56:36	3,855,446	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.5848343372344971, "alphanum_fraction": 0.5907399654388428, "avg_line_length": 32.72908401489258, "blob_id": "f13323031b28b678dffe76dbcdb4b5bf0e805cdd", "content_id": "2d87d7e1ba7514b3b640410419046e05c1809419", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 16933, "license_type": "permissive", "max_line_length": 120, "num_lines": 502, "path": "/gevent_fastcgi.py", "repo_name": "davidgaleano/gevent-fastcgi", "src_encoding": "UTF-8", "text": "# Copyright (c) 2011-2012, Alexander Kulakov\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rights\n# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n# copies of the Software, and to permit persons to whom the Software is\n# furnished to do so, subject to the following conditions:\n#\n# The above copyright notice and this permission notice shall be included in\n# all copies or substantial portions of the Software.\n#\n# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n# THE SOFTWARE.\n\n\"\"\"\nFastCGI/WSGI server implemented using gevent library.\nSupports connection multiplexing. Contains paste.server_runner entry point.\n\"\"\"\n\nimport os\nimport sys\nimport logging\nfrom tempfile import TemporaryFile\nfrom struct import pack, unpack\nfrom wsgiref.handlers import BaseCGIHandler\n\nfrom gevent import spawn, socket\nfrom gevent.server import StreamServer\nfrom gevent.event import Event\nfrom gevent.queue import Queue\nfrom gevent.greenlet import LinkedExited\n\ntry:\n from cStringIO import StringIO\nexcept ImportError:\n from StringIO import StringIO\n\n\n__version__ = '0.1.3dev'\n\n__all__ = [\n 'run_server',\n 'WSGIServer',\n 'ClientConnection',\n 'ProtocolError',\n 'InputStream',\n 'OutputStream',\n 'pack_pairs',\n 'unpack_pairs',\n ]\n\nFCGI_VERSION = 1\nFCGI_LISTENSOCK_FILENO = 0\nFCGI_HEADER_LEN = 8\nFCGI_BEGIN_REQUEST = 1\nFCGI_ABORT_REQUEST = 2\nFCGI_END_REQUEST = 3\nFCGI_PARAMS = 4\nFCGI_STDIN = 5\nFCGI_STDOUT = 6\nFCGI_STDERR = 7\nFCGI_DATA = 8\nFCGI_GET_VALUES = 9\nFCGI_GET_VALUES_RESULT = 10\nFCGI_UNKNOWN_TYPE = 11\nFCGI_MAXTYPE = FCGI_UNKNOWN_TYPE\nFCGI_NULL_REQUEST_ID = 0\nFCGI_RECORD_HEADER_LEN = 8\nFCGI_KEEP_CONN = 1\nFCGI_RESPONDER = 1\nFCGI_AUTHORIZER = 2\nFCGI_FILTER = 3\nFCGI_REQUEST_COMPLETE = 0\nFCGI_CANT_MPX_CONN = 1\nFCGI_OVERLOADED = 2\nFCGI_UNKNOWN_ROLE = 3\n\n__all__.extend(name for name in locals().keys() if name.startswith('FCGI_'))\n\nFCGI_RECORD_TYPES = {\n FCGI_BEGIN_REQUEST: 'FCGI_BEGIN_REQUEST',\n FCGI_ABORT_REQUEST: 'FCGI_ABORT_REQUEST',\n FCGI_END_REQUEST: 'FCGI_END_REQUEST',\n FCGI_PARAMS: 'FCGI_PARAMS',\n FCGI_STDIN: 'FCGI_STDIN',\n FCGI_STDOUT: 'FCGI_STDOUT',\n FCGI_STDERR: 'FCGI_STDERR',\n FCGI_DATA: 'FCGI_DATA',\n FCGI_GET_VALUES: 'FCGI_GET_VALUES',\n FCGI_GET_VALUES_RESULT: 'FCGI_GET_VALUES_RESULT',\n}\n\nFCGI_ROLES = {FCGI_RESPONDER: 'RESPONDER', FCGI_AUTHORIZER: 'AUTHORIZER', FCGI_FILTER: 'FILTER'}\n\nEXISTING_REQUEST_REC_TYPES = frozenset((FCGI_STDIN, FCGI_PARAMS, FCGI_ABORT_REQUEST))\n\nHEADER_STRUCT = '!BBHHBx'\nBEGIN_REQUEST_STRUCT = '!HB5x'\nEND_REQUEST_STRUCT = '!LB3x'\nUNKNOWN_TYPE_STRUCT = '!B7x'\n\nlogger = logging.getLogger(__file__)\n\ndef pack_pairs(pairs):\n def _len(s):\n l = len(s)\n return pack(('!L', '!B')[l < 128], l)\n\n if isinstance(pairs, dict):\n pairs = pairs.iteritems()\n return (_len(name) + _len(value) + name + value for name, value in pairs)\n\ndef unpack_pairs(stream):\n\n def read_len():\n b = stream.read(1)\n if not b:\n return None\n l = ord(b)\n if l & 128:\n b += stream.read(3)\n if len(b) != 4:\n raise ProtocolError('Failed to read name length')\n l = unpack('!L', b)[0] & 0x7FFFFFFF\n return l\n\n def read_str(l):\n s = stream.read(l)\n if len(s) != l:\n raise ProtocolError('Failed to read %s bytes')\n return s\n\n if isinstance(stream, basestring):\n stream = StringIO(stream)\n\n while True:\n name_len = read_len()\n if name_len is None:\n return\n value_len = read_len()\n if value_len is None:\n raise ProtocolError('Failed to read value length')\n yield read_str(name_len), read_str(value_len)\n\n\nclass ProtocolError(Exception):\n pass\n\n\nclass InputStream(object):\n \"\"\"\n FCGI_STDIN or FCGI_DATA stream.\n Uses temporary file to store received data after max_mem octets have been received.\n \"\"\"\n\n _block = frozenset(('read', 'readline', 'readlines', 'fileno', 'close', 'next'))\n\n def __init__(self, max_mem=1024):\n self.max_mem = max_mem\n self.landed = False\n self.file = StringIO()\n self.len = 0\n self.complete = Event()\n\n def land(self):\n if not self.landed:\n pos = self.file.tell()\n tmp_file = TemporaryFile()\n tmp_file.write(self.file.getvalue())\n self.file = tmp_file\n self.file.seek(pos)\n self.landed = True\n logger.debug('Stream landed at %s', self.len)\n\n def feed(self, data):\n if not data: # EOF mark\n logger.debug('InputStream EOF mark received %r', data)\n self.file.seek(0)\n self.complete.set()\n return\n self.len += len(data)\n if not self.landed and self.len > self.max_mem:\n self.land()\n self.file.write(data)\n\n def __iter__(self):\n return self.file\n\n def __getattr__(self, attr):\n # Block until all data is received\n if attr in self._block:\n logger.debug('Waiting for InputStream to be received in full')\n self.complete.wait()\n self._flip_attrs()\n return self.__dict__[attr]\n raise AttributeError, attr\n\n def _flip_attrs(self):\n for attr in self._block:\n if hasattr(self.file, attr):\n setattr(self, attr, getattr(self.file, attr))\n\n\nclass OutputStream(object):\n \"\"\"\n FCGI_STDOUT or FCGI_STDERR stream.\n \"\"\"\n def __init__(self, conn, req_id, rec_type):\n self.conn = conn\n self.req_id = req_id\n self.rec_type = rec_type\n self.closed = False\n\n def write(self, data):\n if self.closed:\n logger.warn('Write to closed %s', self)\n return\n if self.rec_type == FCGI_STDERR:\n sys.stderr.write(data)\n self.conn.output(self.rec_type, data, self.req_id)\n\n def flush(self):\n pass\n\n def close(self):\n if not self.closed:\n self.conn.output(self.rec_type, '', self.req_id)\n self.closed = True\n\n def __str__(self):\n return '%s-%s' % (FCGI_RECORD_TYPES[self.rec_type], self.req_id)\n\n\nclass Request(object):\n \"\"\"\n FastCGI request representation for FastCGI connection multiplexing feature.\n \"\"\"\n def __init__(self, conn, role, id, flags):\n self.role = role\n self.id = id\n self.keep_conn = flags & FCGI_KEEP_CONN\n self.stdin = InputStream()\n self.stdout = OutputStream(conn, id, FCGI_STDOUT)\n self.stderr = OutputStream(conn, id, FCGI_STDERR)\n self.data = InputStream()\n self.params = {}\n self.greenlet = None\n\n\nclass _Connection(object):\n \"\"\"\n Base class for FastCGI client and server connections.\n FastCGI wire protocol implementation.\n \"\"\"\n\n def __init__(self, sock, args, kwargs):\n self.sock = sock\n\n def write_record(self, rec_type, content='', req_id=FCGI_NULL_REQUEST_ID):\n clen = len(content)\n plen = -clen & 7\n header = pack(HEADER_STRUCT, FCGI_VERSION, rec_type, req_id, clen, plen)\n map(self.sock.sendall, (header, content, '\\x00' plen))\n\n def read_bytes(self, num):\n chunks = []\n while num > 0:\n chunk = self.sock.recv(num)\n if not chunk:\n break\n num -= len(chunk)\n chunks.append(chunk)\n return ''.join(chunks)\n \n def read_record(self):\n try:\n header = self.read_bytes(FCGI_RECORD_HEADER_LEN)\n if not header:\n logger.debug('Peer closed connection')\n return None, None, None\n ver, rec_type, req_id, clen, plen = unpack(HEADER_STRUCT, header)\n if ver != FCGI_VERSION:\n raise ProtocolError('Unsopported FastCGI version %s', ver)\n content = self.read_bytes(clen)\n if plen:\n self.read_bytes(plen)\n except socket.error, ex:\n if ex.errno == 104:\n self.close()\n return None, None, None\n else:\n raise\n except:\n self.close()\n raise\n\n logger.debug('Received %s bytes as %s record type for request %s',\n len(content), FCGI_RECORD_TYPES.get(rec_type, 'Unknown %s' % rec_type), req_id)\n return rec_type, req_id, content\n\n def close(self):\n if self.sock:\n self.sock.close()\n self.sock = None\n logger.debug('Connection closed')\n\n\nclass ServerConnection(_Connection):\n \"\"\"\n FastCGI server connection.\n Each requests is handled by separate Greenlet.\n One Greenlet started to serialize output from multiple requests.\n \"\"\"\n def __init__(self, sock, handler, max_conns, max_reqs, mpxs_conns):\n super(ServerConnection, self).__init__(sock)\n self.handler = handler\n self.max_conns = str(max_conns)\n self.max_reqs = str(max_reqs)\n self.mpxs_conns = str(int(bool(mpxs_conns)))\n self.output_queue = Queue()\n # self.output_handler = spawn_link(self.handle_output)\n self.output_handler = spawn(self.handle_output)\n self.output_handler.link() # raise LinkedException in connection Greenlet to terminate it\n\n def run(self):\n self.requests = requests = {}\n while True:\n try:\n rec_type, req_id, content = self.read_record()\n except LinkedExited:\n # output handler exited\n break\n if rec_type is None:\n # connection was closed by peer\n break\n\n if rec_type in EXISTING_REQUEST_REC_TYPES:\n req = requests.get(req_id)\n if not req:\n raise ProtocolError('%s record for non-existing request %s' % (FCGI_RECORD_TYPES[rec_type], req_id))\n if rec_type == FCGI_STDIN:\n req.stdin.feed(content)\n elif rec_type == FCGI_DATA:\n req.data.feed(content)\n elif rec_type == FCGI_PARAMS:\n if req.greenlet:\n raise ProtocolError('Unexpected FCGI_PARAMS for request %s' % req_id)\n if content:\n req.params.update(unpack_pairs(content))\n else:\n logger.debug('Starting handler for request %s: %r', req_id, req.params)\n req.greenlet = spawn(self.handle_request, req)\n elif rec_type == FCGI_ABORT_REQUEST:\n logger.debug('Abort record received for %s', req_id)\n req.complete = True\n elif rec_type == FCGI_BEGIN_REQUEST:\n role, flags = unpack(BEGIN_REQUEST_STRUCT, content)\n if role in FCGI_ROLES:\n requests[req_id] = Request(self, role, req_id, flags)\n logger.debug('New %s request %s with flags %04x', FCGI_ROLES[role], req_id, flags)\n else:\n self.output(FCGI_END_REQUEST, pack(END_REQUEST_STRUCT, 0, FCGI_UNKNOWN_ROLE), req_id)\n logger.error('Unknown request role %s', role)\n elif rec_type == FCGI_GET_VALUES:\n self.output(FCGI_GET_VALUES_RESULT, ''.join(pack_pairs([\n ('FCGI_MAX_CONNS', self.max_conns),\n ('FCGI_MAX_REQS', self.max_reqs),\n ('FCGI_MPXS_CONNS', self.mpxs_conns),\n ])))\n self.output(FCGI_GET_VALUES_RESULT)\n else:\n logger.error('Unknown record type %s received', rec_type)\n self.output(FCGI_UNKNOWN_TYPE, pack('!B7x', rec_type))\n\n logger.debug('Finishing connection handler')\n self.close()\n \n def handle_request(self, req):\n try:\n self.handler(req)\n except:\n logger.exception('Request %s handler failed', req.id)\n req.stdout.close()\n req.stderr.close()\n self.output(FCGI_END_REQUEST, pack(END_REQUEST_STRUCT, 0, FCGI_REQUEST_COMPLETE), req.id)\n self.requests.pop(req.id)\n if not self.requests and not req.keep_conn:\n logger.debug('Last handler finished')\n self.output(None)\n\n def output(self, rec_type, content='', req_id=FCGI_NULL_REQUEST_ID):\n self.output_queue.put((rec_type, content, req_id))\n\n def handle_output(self):\n exit_requested = False\n requests = self.requests\n queue = self.output_queue\n write_record = self.write_record\n while requests or not exit_requested:\n rec_type, content, req_id = queue.get()\n if rec_type is None:\n logger.debug('Request handler wants to close connection')\n exit_requested = True\n continue\n logger.debug('Sending %s %s %s', FCGI_RECORD_TYPES[rec_type], len(content), req_id)\n length = len(content)\n if length <= 0xFFFF:\n write_record(rec_type, content, req_id)\n else:\n offset = 0\n data = memoryview(content)\n while offset < length:\n write_record(rec_type, data[offset:offset+0xFFFF], req_id)\n offset += 0xFFFF\n logger.debug('Output handler finished')\n\n\nclass ClientConnection(_Connection):\n \"\"\"\n FastCGI client connection. Implemented mostly for testing purposes but can be used\n to write FastCGI client.\n \"\"\"\n\n def __init__(self, addr, timeout=None):\n if isinstance(addr, basestring):\n sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)\n elif isinstance(addr, tuple):\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM, socket.IPPROTO_TCP)\n else:\n raise ValueError('Address must be a tuple or a string not %s', type(addr))\n\n sock.connect(addr)\n super(ClientConnection, self).__init__(sock)\n\n def send_begin_request(self, req_id, role=FCGI_RESPONDER, flags=0):\n self.write_record(FCGI_BEGIN_REQUEST, pack(BEGIN_REQUEST_STRUCT, FCGI_RESPONDER, flags), req_id)\n\n def send_abort_request(self, req_id):\n self.write_record(FCGI_ABORT_REQUEST, req_id=req_id)\n\n def send_params(self, params='', req_id=1):\n if params:\n params = ''.join(pack_pairs(params))\n self.write_record(FCGI_PARAMS, params, req_id)\n\n def send_stdin(self, content='', req_id=1):\n self.write_record(FCGI_STDIN, content, req_id)\n\n def send_data(self, content='', req_id=1):\n self.write_record(FCGI_DATA, content, req_id)\n\n def send_get_values(self):\n self.write_record(FCGI_GET_VALUES)\n\n def unpack_end_request(self, data):\n return unpack(END_REQUEST_STRUCT, data)\n\n\nclass WSGIServer(StreamServer):\n\n def __init__(self, bind_address, app, max_conns=1024, max_reqs=1024 * 1024, kwargs):\n \"\"\"\n Up to max_conns Greenlets will be spawned to handle connections\n \"\"\"\n if isinstance(bind_address, basestring):\n sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)\n sock.bind(bind_address)\n sock.listen(max_conns)\n bind_address = sock\n\n super(WSGIServer, self).__init__(bind_address, self.handle_connection, spawn=max_conns, kwargs)\n self.app = app\n self.max_conns = max_conns\n self.max_reqs = max_reqs\n\n def handle_connection(self, sock, addr):\n logger.debug('New connection from %s', addr)\n conn = ServerConnection(sock, self.handle_request, self.max_conns, self.max_reqs, True)\n conn.run()\n\n def handle_request(self, req):\n \"\"\"\n FastCGI request handler will be run in separate Greenlet\n \"\"\"\n try:\n BaseCGIHandler(req.stdin, req.stdout, req.stderr, req.params).run(self.app)\n except:\n logger.exception('Failed to handle request %s', req.id)\n\n\ndef run_server(app, conf, host='127.0.0.1', port=5000, path=None, kwargs):\n addr = path or (host, int(port))\n if kwargs.pop('patch_thread', True):\n from gevent.monkey import patch_thread\n patch_thread()\n WSGIServer(addr, app, kwargs).serve_forever()\n\n" }, { "alpha_fraction": 0.6459054350852966, "alphanum_fraction": 0.6542676091194153, "avg_line_length": 37.955055236816406, "blob_id": "339a270d3878a998993376989ace8a2960c4b7ea", "content_id": "2811ead0df4b2f5ce0f381931187a97a8ddcffa3", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3468, "license_type": "permissive", "max_line_length": 81, "num_lines": 89, "path": "/tests/test_fastcgi.py", "repo_name": "davidgaleano/gevent-fastcgi", "src_encoding": "UTF-8", "text": "# Copyright (c) 2011 Alexander Kulakov <[email protected]>\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n# 1. Redistributions of source code must retain the above copyright\n# notice, this list of conditions and the following disclaimer.\n# 2. Redistributions in binary form must reproduce the above copyright\n# notice, this list of conditions and the following disclaimer in the\n# documentation and/or other materials provided with the distribution.\n#\n# THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND\n# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n# ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE\n# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\n# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS\n# OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)\n# HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT\n# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY\n# OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF\n# SUCH DAMAGE.\n#\n# $Id$\n\nimport unittest\nimport gevent\nfrom gevent_fastcgi import \nfrom struct import pack, unpack\n\nADDR = ('127.0.0.1', 6000)\nTEST_DATA = 'abc' 4096\n\nimport logging\n# logging.basicConfig(level=logging.DEBUG)\n\ndef app(environ, start_response):\n headers = [\n ('Content-type', environ['CONTENT_TYPE']),\n ('Content-length', environ['CONTENT_LENGTH']),\n ]\n start_response('200 OK', headers)\n return environ['wsgi.input']\n\nclass TestFastCGI(unittest.TestCase):\n def setUp(self):\n self.server = WSGIServer(ADDR, app)\n self.server.start()\n\n def tearDown(self):\n self.server.stop()\n\n def test_1_values(self):\n conn = ClientConnection(ADDR)\n conn.send_get_values()\n resp_type, req_id, content = conn.read_record()\n self.assertEqual(resp_type, FCGI_GET_VALUES_RESULT)\n self.assertEqual(req_id, FCGI_NULL_REQUEST_ID)\n values = dict(unpack_pairs(content))\n\n def test_2_responder(self):\n name = 'World'\n conn = ClientConnection(ADDR)\n req_id = 123\n conn.send_begin_request(req_id=req_id)\n conn.send_params([\n ('SCRIPT_NAME', '/'),\n ('PATH_INFO', '/%s' % name),\n ('REQUEST_METHOD', 'POST'),\n ('CONTENT_TYPE', 'application/octet-stream'),\n ('CONTENT_LENGTH', str(len(TEST_DATA))),\n ], req_id=req_id)\n conn.send_params(req_id=req_id)\n conn.send_stdin(TEST_DATA, req_id=req_id)\n conn.send_stdin(req_id=req_id)\n while True:\n rec_type, resp_id, content = conn.read_record()\n self.assertEqual(req_id, resp_id)\n self.assertIn(rec_type, (FCGI_STDOUT, FCGI_STDERR, FCGI_END_REQUEST))\n if rec_type == FCGI_STDERR:\n self.assertEqual(content, '')\n elif rec_type == FCGI_STDOUT:\n pass\n elif rec_type == FCGI_END_REQUEST:\n app_status, req_status = conn.unpack_end_request(content)\n self.assertEqual(app_status, 0)\n self.assertEqual(req_status, FCGI_REQUEST_COMPLETE)\n break\n\n" }, { "alpha_fraction": 0.6488706469535828, "alphanum_fraction": 0.7063655257225037, "avg_line_length": 15.199999809265137, "blob_id": "a1c02c0b3ddd847897f1857c6f424dad4c5d7793", "content_id": "a3e3200ae0604057531023e917bcf3519800f70a", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 487, "license_type": "permissive", "max_line_length": 66, "num_lines": 30, "path": "/README.md", "repo_name": "davidgaleano/gevent-fastcgi", "src_encoding": "UTF-8", "text": "#gevent-fastcgi\n\nThis is FastCGI/WSGI server implementation using gevent library.\n\n## Installation\n\n```bash\n$ python setup.py install\n```\n\n## Usage\n\n```python\nfrom gevent_fastcgi import WSGIServer\nfrom myapp import app\n\nserver = WSGIServer(('127.0.0.1', 4000), app, max_conns=1024)\nserver.serve_forever()\n```\nIt also can be used as server for paster ini-scripts as following:\n\n```\n...\n[server:main]\nuse = egg:gevent_fastcgi#fastcgi\nhost = 127.0.0.1\nport = 4000\nmax_conns = 1024\n...\n```\n\n" }, { "alpha_fraction": 0.5885758399963379, "alphanum_fraction": 0.5959089398384094, "avg_line_length": 42.16666793823242, "blob_id": "75b8ed200777554abee5058209de46f91e126a84", "content_id": "09c1b8e9e5b896d1d5d7c0190c6a2191bfce3a96", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2591, "license_type": "permissive", "max_line_length": 103, "num_lines": 60, "path": "/adapters/django/management/commands/run_gevent_fastcgi.py", "repo_name": "davidgaleano/gevent-fastcgi", "src_encoding": "UTF-8", "text": "import os\nimport re\nfrom optparse import make_option\nfrom django.core.management import BaseCommand, CommandError\n\n__all__ = ['GeventFastCGI']\n\nclass Command(BaseCommand):\n args='<host:port>'\n help='Start gevent-fastcgi server'\n option_list = BaseCommand.option_list + (\n make_option('--maxconns', type='int', dest='max_conns', default=1024,\n metavar='MAX_CONNS', help='Maximum simulteneous connections (default %default)'),\n make_option('--maxreqs', type='int', dest='max_reqs', default=1024,\n metavar='MAX_REQS', help='Maximum active requests (default %default)'),\n make_option('--daemon', action='store_true', dest='daemonize', default=False,\n help='Become a daemon'),\n make_option('--workdir', dest='our_home_dir', default='.', metavar='WORKDIR',\n help='Chande dir in daemon mode (default %default)'),\n make_option('--stdout', dest='out_log', metavar='STDOUT',\n help='stdout in daemon mode (default sys.devnull)'),\n make_option('--stderr', dest='err_log', metavar='STDERR',\n help='stderr in daemon mode (default sys.devnull)'),\n make_option('--umask', dest='umask', type='int', default=022, metavar='UMASK',\n help='umask in daemon mode (default 022)'),\n )\n\n def handle(self, args, options):\n from os.path import abspath, dirname, isdir\n from gevent_fastcgi import WSGIServer\n from django.core.handlers.wsgi import WSGIHandler\n \n if not args:\n raise CommandError('bind address is not specified')\n\n if len(args) > 1:\n raise CommandError('unexpected arguments: %s', ' '.join(args[1:]))\n\n try:\n host, port = args[0].split(':', 1)\n except ValueError:\n address = abspath(args[0])\n if not isdir(dirname(address)):\n raise CommandError('directory %s does not exist', dirname(address))\n else:\n try:\n address = (host, int(port))\n except ValueError:\n raise CommandError('port must be an integer value')\n \n if options['daemonize']:\n from django.utils.daemonize import become_daemon\n\n daemon_opts = dict((key, value) for key, value in options.items() if key in\n ('our_home_dir', 'out_log', 'err_log', 'umask'))\n become_daemon(daemon_opts)\n\n app = WSGIHandler()\n server = WSGIServer(address, app, max_conns=options['max_conns'], max_reqs=options['max_reqs'])\n server.serve_forever()\n\n" }, { "alpha_fraction": 0.6167247295379639, "alphanum_fraction": 0.6225319504737854, "avg_line_length": 32.11538314819336, "blob_id": "3a9f5c21da5581b56e99c28e33624d29199ec443", "content_id": "36d136e0af5795f9714774616d79c0d7d850884f", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 861, "license_type": "permissive", "max_line_length": 97, "num_lines": 26, "path": "/setup.py", "repo_name": "davidgaleano/gevent-fastcgi", "src_encoding": "UTF-8", "text": "from setuptools import setup, find_packages\nimport re\n\n__version__ = re.search(r'__version__\\s=\\s\\'(.)\\'', file('gevent_fastcgi.py').read()).group(1)\n\nsetup(name='gevent-fastcgi',\n version=__version__,\n description=\"FastCGI/WSGI server implementation based on gevent library\",\n long_description='''FastCGI/WSGI server implemented using gevent library.\n Supports connection multiplexing. Compatibe with PasteDeploy.''',\n keywords='fastcgi gevent wsgi',\n author='Alexander Kulakov',\n author_email='[email protected]',\n url='http://github.com/momyc/gevent-fastcgi',\n py_modules=['gevent_fastcgi'],\n zip_safe=True,\n license='MIT',\n install_requires=[\n \"gevent>=0.13.6\"\n ],\n entry_points=\"\"\"\n [paste.server_runner]\n fastcgi=gevent_fastcgi:run_server\n \"\"\",\n test_suite=\"tests\",\n )\n" } ]	5
Image-Group/test2	https://github.com/Image-Group/test2	b8f11628a240def896d6fa79d4d5463a32983541	5bf9ffa28162bf26f17538a942f084a103f39430	71c5341f04fdbf30762a30ba4463c14f4ab04671	refs/heads/master	2022-11-18T06:51:12.396130	2020-07-13T08:40:44	2020-07-13T08:40:44	279,243,632	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6851311922073364, "alphanum_fraction": 0.6997084617614746, "avg_line_length": 22.64285659790039, "blob_id": "aec1d898a3204f4c2d33107694fea8a6c8af1274", "content_id": "8fe9688fb108a29da8363959569dfa607ef184a4", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 343, "license_type": "permissive", "max_line_length": 65, "num_lines": 14, "path": "/binaryproto2npy.py", "repo_name": "Image-Group/test2", "src_encoding": "UTF-8", "text": "import caffe\r\nimport numpy as np\r\nimport sys\r\n\r\nif len(sys.argv)!=3:\r\n print \"Usage: python convert_protomean.py proto.mean out.npy\"\r\n sys.exit()\r\n\r\nblob=caffe.proto.caffe_pb2.BlobProto()\r\ndata=open(sys.argv[1],'rb').read()\r\nblob.ParseFromString(data)\r\narr=np.arry(caffe.io.blobproto_to_array(blob))\r\nout=arr[0]\r\nnp.save(sys.argv[2],out)" } ]	1
dimpetrop/RPG_LEVEL_CALCULATOR	https://github.com/dimpetrop/RPG_LEVEL_CALCULATOR	00f71b22ffe9f116e7ec3c1c891eac22686e4535	88163e536021c26593b3f6a0d0945b221ba9c114	e3740fb56116b694d8045cd716456818dd8a075f	refs/heads/master	2020-09-12T21:42:02.044518	2019-11-19T13:21:54	2019-11-19T13:21:54	222,564,626	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5566594004631042, "alphanum_fraction": 0.5892580151557922, "avg_line_length": 28.01801872253418, "blob_id": "090c2a8771590bf5aece3583466fd61a85edafc2", "content_id": "63804dbec66bc692d7f43d030b9b8e2cbc97824b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3221, "license_type": "no_license", "max_line_length": 325, "num_lines": 111, "path": "/main.py", "repo_name": "dimpetrop/RPG_LEVEL_CALCULATOR", "src_encoding": "UTF-8", "text": "from random import randrange\n\n\ndef simulation():\n print(\"Running Simulation...\")\n with open(\"simulation_results.txt\", \"w\") as f:\n for i in range(1,1001):\n PLAYERS_COMPLETED = randrange(1,1000)\n PLAYERS_IN_ZONE_NOW = randrange(1,100)\n PLAYERS_COMPLETED_AVG_LEVEL = randrange(1,100)\n PLAYER_LVL = randrange(1,100)\n ZONE_LEVEL = randrange(1,30)\n\n FACTOR_1 = PLAYERS_COMPLETED / PLAYERS_IN_ZONE_NOW\n FACTOR_2 = PLAYERS_COMPLETED_AVG_LEVEL * 0.5\n FACTOR_3 = abs((PLAYER_LVL - ZONE_LEVEL) * 2)\n DIFFICULTY = int(FACTOR_1 - FACTOR_2 - FACTOR_3)\n\n if DIFFICULTY < 0:\n DIFFICULTY *= -1\n if DIFFICULTY == 0:\n DIFFICULTY = 25\n f.write(\"\\n\\nSIMULATION \"+ str(i) + \" RESULTS \" + \"DIFFICULTY =\" + str(DIFFICULTY) + \"\\nPlayers Completed \" + str(PLAYERS_COMPLETED) + \"\\nPlayers in zone now \"+ str(PLAYERS_IN_ZONE_NOW) + \"\\nAverage Player LVL \" + str(PLAYERS_COMPLETED_AVG_LEVEL) + \"\\nPlayer LVL +\"+ str(PLAYER_LVL) + \"\\nZone Level \" + str(ZONE_LEVEL))\n print(\"Simulation Completed\")\n\ndef find_difficulties():\n array = []\n with open(\"simulation_results.txt\", \"r\") as f:\n for line in f:\n if \"=\" in line:\n toappend = line[len(line)-4:len(line)-1].replace(\"=\", \"\")\n array.append(int(toappend))\n return array\n\ndef find_player_level():\n array = []\n with open(\"simulation_results.txt\", \"r\") as f:\n for line in f:\n if \"+\" in line:\n toappend = line[len(line)-4:len(line)-1].replace(\"+\", \"\")\n array.append(int(toappend))\n return array\n\ndef calculate_values(option):\n c = 1\n sum = mid = low = high = 0\n if option == 1:\n #print(\"Option 1: difficulties (calculate_values)\") #DEBUG\n array = find_difficulties()\n else:\n #print(\"Option 2: player lvl (calculate_values)\") #DEBUG\n array = find_player_level()\n for i in array:\n c += 1\n sum += i\n\n if 25 < i < 50:\n mid += 1\n if i < 25:\n low += 1\n if i > 50:\n high +=1\n avg = sum / c\n return [avg, low, mid, high]\n\ndef count(option):\n all = False\n\n while True:\n\n if option == 3:\n option = 1\n all = True\n if option == 0:\n return\n \n if option == 1:\n array = calculate_values(1)\n print(\"\\nAverage Difficulty LVL based on Simulation\", array[0], \"\")\n print(\"Count of difficulties > 50\", array[3])\n print(\"Count of difficulties 25 - 50\", array[2])\n print(\"Count of difficulties < 25\", array[1]) \n if all:\n option = 2\n return\n if option == 2:\n array = calculate_values(2)\n print(\"\\nAverage Player LVL based on Simulation\", array[0], \"\")\n print(\"Count of Player LVL > 50\", array[3])\n print(\"Count of Player LVL 25 - 50\", array[2])\n print(\"Count of Player LVL < 25\", array[1]) \n if all:\n option = 0\n return\n\n\n\n#Program Start\nwhile True:\n option = int(input(\"\\n\\nSimulation [1]\\nCount [2]\\n\"))\n while option not in range(0,3):\n print(\"\\nIncorrect Input\")\n option = int(input(\"\\n\\nSimulation [1]\\nCount [2]\\n\"))\n\n if option == 1:\n simulation()\n elif option == 2:\n count(int(input(\"\\nCount of Difficulties [1]\\nCount of Player LVL [2]\\nAll [3]\\n\")))\n elif option == 0:\n print(\"Exiting...\")\n break\n" } ]	1
Karan-D/Python-GUI-filling-out-google-sheets-	https://github.com/Karan-D/Python-GUI-filling-out-google-sheets-	bc84236ccb3956c3e5400922b5cd82d852a1795e	2ecd0dd8259d829abc4a4ca48a905d0ff3a715af	6b58fee7d1ab372980df713c4989ac7b6cefc95a	refs/heads/master	2023-08-27T04:58:02.290904	2021-11-09T12:22:24	2021-11-09T12:22:24	406,894,825	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6391972899436951, "alphanum_fraction": 0.6840307712554932, "avg_line_length": 22.897958755493164, "blob_id": "a0c5d874af04483a07d387a8d1b44bba97678180", "content_id": "a85811a1e47f731bdbf6b6088c12822b2ec47cc3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2354, "license_type": "no_license", "max_line_length": 143, "num_lines": 98, "path": "/principal.py", "repo_name": "Karan-D/Python-GUI-filling-out-google-sheets-", "src_encoding": "UTF-8", "text": "\nfrom tkinter import \nfrom gspread.utils import a1_to_rowcol\nfrom googleapiclient.discovery import build\nfrom google.oauth2 import service_account\nfrom googleapiclient import discovery\nfrom datetime import date\nfrom ttkwidgets.autocomplete import AutocompleteCombobox\n\n\n\ndata = str(date.today())\ncat = \"categoria\"\ndesc = \"Descrição\"\nvalor = \"valor\"\n\n#print(data, desc)\n\n\ndef btclick():\n\n global data, cat, desc, valor\n #data = ed1.get()\n cat = ed2.get()\n desc = ed3.get()\n valor = ed4.get()\n janela.quit()\n\n\n\njanela = Tk()\n\n\n\n#entrada = Entry(janela)\n#entrada.place(x=100, y=100)\n\nlb1 = Label(janela, text=\"Forma de pagamento\")\nlb1.place(x=50, y=50)\ncat_pagamento = [\"Crédito\", \"Débito\", \"Dinheiro\"]\ned1 = AutocompleteCombobox(janela, width=20, completevalues= sorted (cat_pagamento))\ned1.place(x=120, y=50)\n\n\n\nlb2 = Label(janela, text=\"Categoria\")\nlb2.place(x=50,y=70)\ncat_values = [\"Alimentação\", \"Ferramentas manuais\", \"combustível\", \"Ferramentas elétricas\"] #Opções por categoria de custos\ned2 = AutocompleteCombobox(janela, width=20, completevalues = sorted(cat_values))\ned2.place(x=120, y=70)\n\nlb3 = Label(janela, text=\"Descrição\")\nlb3.place(x=50,y=90)\ned3 = Entry(janela)\ned3.place(x=120, y=90)\n\nlb4 = Label(janela, text=\"Valor R$\")\nlb4.place(x=50,y=110)\ned4 = Entry(janela)\ned4.place(x=120, y=110)\n\nbt = Button(janela, width=20, text=\"Next\", command=btclick)\nbt.place(x=100, y=150)\n\n\njanela.geometry(\"500x500+300+300\")\njanela.mainloop()\n#print (data,desc)\n\n#---------------------------------------------------------------------------------------------------------------------#\n\n#ACCES SHEETS\n\nSERVICE_ACCOUNT_FILE = 'keys.json'\nSCOPES = ['https://www.googleapis.com/auth/spreadsheets']\n\ncreds = None\ncreds = service_account.Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes = SCOPES)\n\n#the ID Spreadsheet.\nSPREADSHEET_ID = '1jFsgA0UPdZrrlbQO1uxgcqIaS8OzMAKhD1ln0yz71Z0'\n\nservice = build('sheets', 'v4' ,credentials=creds)\n\n\n\n# call the sheets API\n\nsheet = service.spreadsheets()\nresult = sheet.values().get(spreadsheetId=SPREADSHEET_ID, range=\"pag2!A1:D40\").execute()\n\nvalues = result.get('values',[])\n\n\natl = [[data,cat,desc,valor]]\n\nrequest = sheet.values().append(spreadsheetId=SPREADSHEET_ID, range=\"pag2!A:D\", valueInputOption=\"USER_ENTERED\", body={\"values\":atl}).execute()\n\nprint(request)" }, { "alpha_fraction": 0.7302025556564331, "alphanum_fraction": 0.7467771768569946, "avg_line_length": 24.279069900512695, "blob_id": "28624a2dd6d4488739bea9795d71f2bb089c5271", "content_id": "4f399d800a7fb16264856239aaa2c833ab1a13a1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1089, "license_type": "no_license", "max_line_length": 142, "num_lines": 43, "path": "/testesheets.py", "repo_name": "Karan-D/Python-GUI-filling-out-google-sheets-", "src_encoding": "UTF-8", "text": "from gspread.utils import a1_to_rowcol\nfrom googleapiclient.discovery import build\nfrom google.oauth2 import service_account\nfrom googleapiclient import discovery\n\n#from tkinter import \n\n\nSERVICE_ACCOUNT_FILE = 'keys.json'\nSCOPES = ['https://www.googleapis.com/auth/spreadsheets']\n\ncreds = None\ncreds = service_account.Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes = SCOPES)\n\n#the ID Spreadsheet.\nSPREADSHEET_ID = '1jFsgA0UPdZrrlbQO1uxgcqIaS8OzMAKhD1ln0yz71Z0'\n\nservice = build('sheets', 'v4' ,credentials=creds)\n\n\n\n# call the sheets API\n\nsheet = service.spreadsheets()\nresult = sheet.values().get(spreadsheetId=SPREADSHEET_ID, range=\"pag2!A1:D40\").execute()\n\nvalues = result.get('values',[])\n\n\n# INTERFACE GRÁFICA\n\n\ndata = input('Qual a data?')\ndesc = input('Descrição:')\ncat = input (\"Digite a categoria:\")\n#fdp = input ('Forma de pagamento:')\n#valor = input('Digite o valor:')\n\natl = [[data,desc,cat]]\n\nrequest = sheet.values().append(spreadsheetId=SPREADSHEET_ID, range=\"pag2!A1\", valueInputOption=\"USER_ENTERED\", body={\"values\":atl}).execute()\n\nprint(request)" } ]	2
NJCinnamond/NLPAssignment-1	https://github.com/NJCinnamond/NLPAssignment-1	8143bf8bce8de1044b757de28e2b0afce4169ce1	4204dcf64cf0864e6be2c5ce645f3e1ea810762f	32134ac2fa760ba7285d9bc844fa4db0be76352a	refs/heads/master	2020-12-31T10:45:22.029690	2020-02-25T01:14:43	2020-02-25T01:14:43	239,006,956	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5608283281326294, "alphanum_fraction": 0.566868007183075, "avg_line_length": 32.352516174316406, "blob_id": "715c52973d9758a579026ef80e34afbd30905a12", "content_id": "dcc4b74eaf87eec1c00054f55b18a839728e6999", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4636, "license_type": "no_license", "max_line_length": 104, "num_lines": 139, "path": "/perceptron.py", "repo_name": "NJCinnamond/NLPAssignment-1", "src_encoding": "UTF-8", "text": "\"\"\" Maximum entropy model for Assignment 1: Starter code.\n\nYou can change this code however you like. This is just for inspiration.\n\n\"\"\"\nimport os\nimport sys\nimport numpy as np\n\nfrom util import evaluate, load_data\nfrom sklearn.metrics import confusion_matrix\n\nclass PerceptronModel():\n \"\"\" Maximum entropy model for classification.\n\n Attributes:\n (float) weights\n (float) bias\n (int) num_dim\n (bool) add_bias\n\n \"\"\"\n def __init__(self, label_to_index, lr=0.02):\n self.W = None\n self.bias = None\n self.lr = lr\n self.num_dim = 0\n self.num_class = len(label_to_index)\n self.label_to_index = label_to_index\n self.index_to_label = {v: k for k, v in label_to_index.items()}\n\n def train(self, training_data):\n \"\"\" Trains the maximum entropy model.\n\n Inputs:\n training_data: Suggested type is (list of pair), where each item is\n a training example represented as an (input, label) pair.\n \"\"\"\n\n self.num_dim = len(training_data[0][0])\n self.num_epochs = 5\n self.W = {c: np.array([0.0 for _ in range(self.num_dim)]) for c in self.label_to_index.keys()}\n\n epoch = 0\n change_over_epoch = True\n while change_over_epoch and epoch < self.num_epochs:\n print(\"Epoch: \", epoch)\n epoch += 1\n correct = 0\n change_over_epoch = False\n\n for sample in training_data:\n #Get numerical value of label\n label = sample[1]\n if sample[1] not in self.label_to_index.keys():\n label = self.index_to_label[0]\n\n # Initialize arg_max value, predicted class.\n arg_max, predicted_label = 0, self.index_to_label[0]\n\n # Multi-Class Decision Rule:\n for c in self.label_to_index.keys():\n current_activation = np.dot(sample[0], self.W[c])\n if current_activation >= arg_max:\n arg_max, predicted_label = current_activation, c\n\n # Update Rule:\n if not (label == predicted_label):\n change_over_epoch = True\n self.W[label] += np.dot(self.lr, sample[0])\n self.W[predicted_label] -= np.dot(self.lr, sample[0])\n else:\n correct += 1\n \n acc = correct / len(training_data)\n print(\"Accuracy: \", str(acc))\n\n def predict(self, model_input):\n \"\"\" Predicts a label for an input.\n\n Inputs:\n model_input (features): Input data for an example, represented as a\n feature vector.\n\n Returns:\n The predicted class. \n\n \"\"\"\n # Initialize predicted label to UNK token\n arg_max, predicted_label = 0, self.index_to_label[0]\n\n # Multi-Class Decision Rule:\n for c in self.label_to_index.keys():\n current_activation = np.dot(model_input, self.W[c])\n if current_activation >= arg_max:\n arg_max, predicted_label = current_activation, c\n\n return predicted_label\n\ndef create_dummy_bias(data):\n for sample in data:\n sample[0].append(1)\n return data \n\nif __name__ == \"__main__\":\n print(\"Getting data\")\n train_data, dev_data, test_data, data_type, label_dict = load_data(sys.argv)\n print(\"Got data\")\n train_data = create_dummy_bias(train_data)\n dev_data = create_dummy_bias(dev_data)\n test_data = create_dummy_bias(test_data)\n\n print(len(train_data))\n print(len(dev_data))\n print(len(test_data))\n\n # Train the model using the training data.\n model = PerceptronModel(label_to_index=label_dict)\n model.train(train_data)\n\n # Predict on the development set. \n '''\n dev_accuracy = evaluate(model,\n dev_data,\n os.path.join(\"results\", \"perceptron_\" + data_type + \"_dev_predictions.csv\"))\n print(\"Dev accuracy: \", dev_accuracy)\n '''\n pred_label = [model.predict(example[0]) for example in dev_data]\n true_label = [example[1] for example in dev_data]\n conf_mat = confusion_matrix(true_label, pred_label, \n labels=np.sort(np.unique(true_label)))\n print(conf_mat)\n print(np.sort(np.unique(true_label)))\n # Predict on the test set.\n # Note: We don't provide labels for test, so the returned value from this\n # call shouldn't make sense.\n #evaluate(model,\n # test_data,\n # os.path.join(\"results\", \"perceptron_\" + data_type + \"_test_predictions.csv\"))\n" }, { "alpha_fraction": 0.7263513803482056, "alphanum_fraction": 0.7702702879905701, "avg_line_length": 36, "blob_id": "fb0ef682790b39e05cca2c27ab3d39bc03a0bf9f", "content_id": "a34e79c98315350f2d922a494e82ac90e1d58354", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 296, "license_type": "no_license", "max_line_length": 81, "num_lines": 8, "path": "/aretheysame/same.py", "repo_name": "NJCinnamond/NLPAssignment-1", "src_encoding": "UTF-8", "text": "import pandas as pd \n\ndf1 = pd.read_csv(\"perceptron_propername_test_predictions.csv\")\ndf2 = pd.read_csv(\"perceptron_propername_test_predictions_mask_devacc_82.7.csv\")\ndf3 = pd.read_csv(\"perceptron_propername_test_predictions_nomask_devacc80.6.csv\")\n\nprint(df1.equals(df2))\nprint(df1.equals(df3))\n" }, { "alpha_fraction": 0.561387300491333, "alphanum_fraction": 0.5655491352081299, "avg_line_length": 31.25373077392578, "blob_id": "3bc5d1b06f3abe7f4d46efea6e8ac31ef8a84c83", "content_id": "9721d11fb72740c0da6b930d2ee67275c795dc02", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4325, "license_type": "no_license", "max_line_length": 90, "num_lines": 134, "path": "/propername.py", "repo_name": "NJCinnamond/NLPAssignment-1", "src_encoding": "UTF-8", "text": "import pandas as pd \nimport numpy as np \nimport string\n\ndef propername_featurize(input_data, n_grams, data_dict, label_dict, use_mask=True):\n \"\"\" Featurizes an input for the proper name domain.\n\n Inputs:\n input_data: The input data.\n \"\"\"\n features = []\n\n for idx in range(input_data.shape[0]):\n feat = np.zeros(len(data_dict))\n\n label = input_data[idx,1]\n input_data[idx,0] = input_data[idx,0]#.lower()\n for n in n_grams:\n chars = [char for char in input_data[idx,0]]\n if use_mask and n > 2:\n chars = ['<MASK>'] + chars + ['<MASK>']\n\n for c in range(len(chars) - n):\n n_gram = ''.join(chars[c:c+n])\n if n_gram not in data_dict:\n #If you don't want UNK, just continue\n #continue\n n_gram = '<UNK>'\n feat[data_dict[n_gram]] = 1\n \n features += [(feat.tolist(), label)]\n \n return features\n\ndef propername_data_loader(train_data_filename,\n train_labels_filename,\n dev_data_filename,\n dev_labels_filename,\n test_data_filename):\n \"\"\" Loads the data.\n\n Inputs:\n train_data_filename (str): The filename of the training data.\n train_labels_filename (str): The filename of the training labels.\n dev_data_filename (str): The filename of the development data.\n dev_labels_filename (str): The filename of the development labels.\n test_data_filename (str): The filename of the test data.\n\n Returns:\n Training, dev, and test data, all represented as (input, label) format.\n\n Suggested: for test data, put in some dummy value as the label.\n \"\"\"\n\n USE_MASK = True\n N_GRAMS = [2,3]\n\n # TODO: Load the data from the text format.\n train_data = pd.read_csv(train_data_filename)\n train_labels = pd.read_csv(train_labels_filename)\n train = raw_from_df(train_data, train_labels, dummy_features=False)\n \n dev_data = pd.read_csv(dev_data_filename)\n dev_labels = pd.read_csv(dev_labels_filename)\n dev = raw_from_df(dev_data, dev_labels, dummy_features=False)\n \n test_data = pd.read_csv(test_data_filename)\n test = raw_from_df(test_data, None, dummy_features=True)\n\n # TODO: Featurize the input data for all three splits.\n data_dict, label_dict = create_dicts(train, N_GRAMS, use_mask=USE_MASK)\n\n print(\"data dict len: \", len(data_dict))\n\n train = propername_featurize(train, N_GRAMS, data_dict, label_dict, use_mask=USE_MASK)\n dev = propername_featurize(dev, N_GRAMS, data_dict, label_dict, use_mask=USE_MASK)\n test = propername_featurize(test, N_GRAMS, data_dict, label_dict, use_mask=USE_MASK)\n\n return train, dev, test, label_dict\n\ndef raw_from_df(data_df, label_df, dummy_features):\n feat_list = []\n\n for sample_id in data_df['id']:\n data = data_df.loc[data_df['id'] == sample_id]['text'].iloc[0]\n\n if dummy_features:\n label = 'dummy'\n else:\n label = label_df.loc[label_df['id'] == sample_id]['type'].iloc[0]\n\n feat_list.append(np.array((data, label)))\n\n return np.array(feat_list)\n\ndef create_dicts(input_data, n_grams, use_mask=True):\n \"\"\" Creates dicts of labels and n_grams\n\n Input:\n (list) list of n_grams to put into dict\n\n Returns:\n (dict) chars to feature index dict\n (dict) labels to output dict\n \"\"\"\n\n #Initialize dicts with UNK tokens\n data_dict = { '<UNK>' : 0}\n label_dict = { '<UNK>' : 0}\n\n if use_mask:\n data_dict['<MASK>'] = 1\n\n for n_gram in n_grams:\n for row in input_data:\n text = row[0]#.lower()\n label = row[1]\n\n if label not in label_dict:\n label_dict[label] = len(label_dict)\n\n if (len(text) - n_gram) < 0:\n continue\n\n chars = [char for char in text]\n if use_mask and n_gram > 2:\n chars = ['<MASK>'] + chars + ['<MASK>']\n\n for c in range(len(chars) - n_gram):\n txt = ''.join(chars[c:c+n_gram])\n if txt not in data_dict:\n data_dict[txt] = len(data_dict)\n\n return data_dict, label_dict\n\n\n\n" }, { "alpha_fraction": 0.4166666567325592, "alphanum_fraction": 0.8285714387893677, "avg_line_length": 41.099998474121094, "blob_id": "d0dfdbbc32330ddd745029260e18d62eaab967d7", "content_id": "7bc73d501f9a83158fed23c1534ecfa4ffc4f930", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 420, "license_type": "no_license", "max_line_length": 210, "num_lines": 10, "path": "/plots.py", "repo_name": "NJCinnamond/NLPAssignment-1", "src_encoding": "UTF-8", "text": "import numpy as np \nimport matplotlib.pyplot as pyplot\n\nnomask_losses = [1.181096193583116,0.5412596282751663,0.5168246244606765,0.5052332385726596,0.5002813002337579,0.49267008187978173,0.49703964655813976,0.49006101813005365,0.48472113194672956,0.4820000976324081]\n\npyplot.figure()\npyplot.plot(range(len(nomask_losses)),nomask_losses)\npyplot.xlabel(\"Number of Epochs\")\npyplot.ylabel(\"Cross-Entropy Loss\")\npyplot.show()" }, { "alpha_fraction": 0.8045976758003235, "alphanum_fraction": 0.8160919547080994, "avg_line_length": 42.5, "blob_id": "2c31a44bdb19855a41edec96c2a1c84eace90306", "content_id": "045cdd1015660192e161bf7d6837a095a8aea8c8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 87, "license_type": "no_license", "max_line_length": 68, "num_lines": 2, "path": "/README.md", "repo_name": "NJCinnamond/NLPAssignment-1", "src_encoding": "UTF-8", "text": "# NLPAssignment-1\nPerceptron, Maximum Entropy and MLP models for training on text data\n" } ]	5
ebmdatalab/cusum-for-opioids-notebook	https://github.com/ebmdatalab/cusum-for-opioids-notebook	13d2edeacc65d41a96178715e2487d1c94be7075	aebb23c6969c7b3d7d64134b0aadc5d7ab4ac301	f86a6cddc36f73d3a8d92bbfde4c8bbef0beb9ed	refs/heads/master	2020-12-19T00:18:58.330398	2020-02-05T09:33:11	2020-02-05T09:33:11	235,563,633	0	0	null	2020-01-22T11:55:52	2020-02-05T09:33:16	2020-03-31T10:56:40	Python	[ { "alpha_fraction": 0.7940751314163208, "alphanum_fraction": 0.7962427735328674, "avg_line_length": 52.230770111083984, "blob_id": "3d69c9f802f39eb44d26053dd2e625028174d10a", "content_id": "827db3c5230cda73fc958c067bbc37a1b0a72dbb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1384, "license_type": "no_license", "max_line_length": 378, "num_lines": 26, "path": "/README.md", "repo_name": "ebmdatalab/cusum-for-opioids-notebook", "src_encoding": "UTF-8", "text": "# CUSUM for one measure against all CCGs or Practices\n\n![status](https://github.com/ebmdatalab/cusum-for-opioids-notebook/workflows/Notebook%20checks/badge.svg)\n\nExperiments in using our existing CUSUM metholdogy to discover organisations that are quick to change\n\nThis repo supports further investigations into opioid prescribing following the Public Health England Prescribed Medicines Review. Full deatils on the background and another approach taken can be seen in the [repo where we have implemented the OpenPrescribing Change Detection python library](https://github.com/ebmdatalab/opioids-change-detection-notebook/) on opioid measures.\n\n## How to view the notebooks\n\nNotebooks live in the `notebooks/` folder (with an `ipynb`\nextension). You can most easily view them [on\nnbviewer](https://nbviewer.jupyter.org/github/ebmdatalab/cusum-for-opioids-notebook/tree/master/notebooks/),\nthough looking at them in Github should also work.\n\nYou can view and interact with any notebooks in the `notebooks/`\nfolder by launching the notebook in the free online service,\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/ebmdatalab/cusum-for-opioids-notebook/master).\n\nAny changes you make there won't be saved; to do development work,\nyou'll need to set up a local jupyter server and git repository - see\n`DEVELOPERS.md` for more detail.\n\n## How to cite\n\nXXX\n" }, { "alpha_fraction": 0.5583686828613281, "alphanum_fraction": 0.5642534494400024, "avg_line_length": 35.53499984741211, "blob_id": "c9ba148a06d654fd3fb878732959c8b0e80639d2", "content_id": "80c734be097f3fbe33a8bd75bb984145a8a161d4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7307, "license_type": "no_license", "max_line_length": 87, "num_lines": 200, "path": "/lib/cusum.py", "repo_name": "ebmdatalab/cusum-for-opioids-notebook", "src_encoding": "UTF-8", "text": "import numpy as np\nimport pandas as pd\n\n\ndef most_change_against_window(percentiles, window=12):\n \"\"\"Use CUSUM algorithm to detect cumulative change from a reference\n mean averaged over the previous `window` months.\n\n Returns a list of dicts of `measure`, `from`, and `to`\n\n \"\"\"\n improvements = []\n declines = []\n cusum = CUSUM(percentiles, window_size=window, sensitivity=5)\n cusum.work()\n\n last_alert = cusum.get_last_alert_info()\n if last_alert:\n if last_alert[\"from\"] < last_alert[\"to\"]:\n declines.append(last_alert)\n else:\n improvements.append(last_alert)\n improvements = sorted(improvements, key=lambda x: -abs(x[\"to\"] - x[\"from\"]))\n declines = sorted(declines, key=lambda x: -abs(x[\"to\"] - x[\"from\"]))\n return {\"improvements\": improvements, \"declines\": declines}\n\n\nclass CUSUM(object):\n \"\"\"See Introduction to Statistical Quality Control, Montgomery DC, Wiley, 2009\n and our paper\n http://dl4a.org/uploads/pdf/581SPC.pdf\n \"\"\"\n\n def __init__(self, data, window_size=12, sensitivity=5):\n data = np.array([np.nan if x is None else x for x in data])\n # Remove sufficient leading nulls to ensure we can start with\n # any value\n self.start_index = 0\n while pd.isnull(data[self.start_index : self.start_index + window_size]).all():\n if self.start_index > len(data):\n data = []\n break\n self.start_index += 1\n self.data = data\n self.window_size = window_size\n self.sensitivity = sensitivity\n self.pos_cusums = []\n self.neg_cusums = []\n self.target_means = []\n self.alert_thresholds = []\n self.alert_indices = []\n self.pos_alerts = []\n self.neg_alerts = []\n\n def work(self):\n for i, datum in enumerate(self.data):\n if i <= self.start_index:\n window = self.data[i : self.window_size + i]\n self.new_target_mean(window)\n self.new_alert_threshold(window)\n self.compute_cusum(datum, reset=True)\n elif self.cusum_within_alert_threshold():\n # Note this will always be true for the first `window_size`\n # data points\n self.maintain_target_mean()\n self.maintain_alert_threshold()\n self.compute_cusum(datum)\n else:\n # Assemble a moving window of the last `window_size`\n # non-null values\n window = self.data[i - self.window_size : i]\n self.new_target_mean(window)\n if self.moving_in_same_direction(datum): # this \"peeks ahead\"\n self.maintain_alert_threshold()\n self.compute_cusum(datum)\n else:\n self.new_alert_threshold(window) # uses window\n self.compute_cusum(datum, reset=True)\n # Record alert\n self.record_alert(datum, i)\n return self.as_dict()\n\n def as_dict(self):\n return {\n \"smax\": self.pos_cusums,\n \"smin\": self.neg_cusums,\n \"target_mean\": self.target_means,\n \"alert_threshold\": self.alert_thresholds,\n \"alert\": self.alert_indices,\n \"alert_percentile_pos\": self.pos_alerts,\n \"alert_percentile_neg\": self.neg_alerts,\n }\n\n def get_last_alert_info(self):\n \"\"\"If the current (most recent) month includes an alert, work out when\n that alert period started, and return numbers that approximate\n to the size of the change across that period.\n\n \"\"\"\n if any(self.alert_indices) and self.alert_indices[-1] == len(self.data) - 1:\n end_index = start_index = self.alert_indices[-1]\n for x in list(reversed(self.alert_indices))[1:]:\n if x == start_index - 1:\n start_index = x\n else:\n break\n duration = (end_index - start_index) + 1\n return {\n \"from\": self.target_means[start_index - 1],\n \"to\": self.data[end_index],\n \"period\": duration,\n }\n else:\n return None\n\n def moving_in_same_direction(self, datum):\n # Peek ahead to see what the next CUSUM would be\n next_pos_cusum, next_neg_cusum = self.compute_cusum(datum, store=False)\n going_up = (\n next_pos_cusum > self.current_pos_cusum()\n and self.cusum_above_alert_threshold()\n )\n going_down = (\n next_neg_cusum < self.current_neg_cusum()\n and self.cusum_below_alert_threshold()\n )\n return going_up or going_down\n\n def __repr__(self):\n return \"\"\"\n name: {name}\n data: {data}\n pos_cusums: {pos_cusums}\n neg_cusums: {neg_cusums}\n target_means: {target_means}\n alert_thresholds: {alert_thresholds}\"\n alert_incides: {alert_indices}\"\n \"\"\".format(\n *self.__dict__\n )\n\n def record_alert(self, datum, i):\n if self.cusum_above_alert_threshold():\n self.alert_indices.append(i)\n self.pos_alerts.append(datum)\n self.neg_alerts.append(None)\n elif self.cusum_below_alert_threshold():\n self.alert_indices.append(i)\n self.pos_alerts.append(None)\n self.neg_alerts.append(datum)\n else:\n self.pos_alerts.append(None)\n self.neg_alerts.append(None)\n\n def maintain_alert_threshold(self):\n self.alert_thresholds.append(self.alert_thresholds[-1])\n return self.alert_thresholds[-1]\n\n def maintain_target_mean(self):\n self.target_means.append(self.target_means[-1])\n return self.target_means[-1]\n\n def cusum_above_alert_threshold(self):\n return self.pos_cusums[-1] > self.alert_thresholds[-1]\n\n def cusum_below_alert_threshold(self):\n return self.neg_cusums[-1] < -self.alert_thresholds[-1]\n\n def cusum_within_alert_threshold(self):\n return not (\n self.cusum_above_alert_threshold() or self.cusum_below_alert_threshold()\n )\n\n def new_target_mean(self, window):\n self.target_means.append(np.nanmean(window))\n\n def new_alert_threshold(self, window):\n self.alert_thresholds.append(np.nanstd(window self.sensitivity))\n\n def current_pos_cusum(self):\n return self.pos_cusums[-1]\n\n def current_neg_cusum(self):\n return self.neg_cusums[-1]\n\n def compute_cusum(self, datum, reset=False, store=True):\n alert_threshold = self.alert_thresholds[-1]\n delta = 0.5 * alert_threshold / self.sensitivity\n current_mean = self.target_means[-1]\n cusum_pos = datum - (current_mean + delta)\n cusum_neg = datum - (current_mean - delta)\n if not reset:\n cusum_pos += self.pos_cusums[-1]\n cusum_neg += self.neg_cusums[-1]\n cusum_pos = round(max(0, cusum_pos), 2)\n cusum_neg = round(min(0, cusum_neg), 2)\n if store:\n self.pos_cusums.append(cusum_pos)\n self.neg_cusums.append(cusum_neg)\n return cusum_pos, cusum_neg\n" }, { "alpha_fraction": 0.6628674268722534, "alphanum_fraction": 0.6802639365196228, "avg_line_length": 31.05769157409668, "blob_id": "fac4f945736d726689c68db89b64bd39782553df", "content_id": "ef63554938f73fd7a9a9c94b21e90501e3aa5041", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1667, "license_type": "no_license", "max_line_length": 163, "num_lines": 52, "path": "/notebooks/diffable_python/cusum.py", "repo_name": "ebmdatalab/cusum-for-opioids-notebook", "src_encoding": "UTF-8", "text": "# ---\n# jupyter:\n# jupytext:\n# cell_metadata_filter: all\n# notebook_metadata_filter: all,-language_info\n# text_representation:\n# extension: .py\n# format_name: light\n# format_version: '1.5'\n# jupytext_version: 1.3.2\n# kernelspec:\n# display_name: Python 3\n# language: python\n# name: python3\n# ---\n\nimport pandas as pd\nfrom lib.cusum import most_change_against_window\nfrom ebmdatalab import bq \n\nsql = \"\"\"\nSELECT\n pct_id,\n percentile\nFROM measures.ccg_data_opioidper1000\n\"\"\"\ndf = bq.cached_read(sql, csv_path='../data/ccg_percentiles.zip')\n\nfor pct_id, grouped in df.groupby(\"pct_id\"):\n changes = most_change_against_window(grouped.percentile, window=12)\n if changes['improvements']:\n print(pct_id, changes['improvements'])\n\nsql = \"\"\"\nSELECT\n practice_id,\n percentile\nFROM measures.practice_data_opioidper1000\n\"\"\"\ndf2 = bq.cached_read(sql, csv_path='../data/practice_percentiles.zip')\n\npractice_df = pd.DataFrame(columns=[\"practice_id\", \"from\", \"to\", \"period\"])\nfor practice_id, grouped in df2.groupby(\"practice_id\"):\n changes = most_change_against_window(grouped.percentile, window=24)\n improvements = changes['improvements'] and changes['improvements'][0] or {}\n if improvements.get(\"to\", 0) > 0:\n practice_df = practice_df.append([{ 'practice_id': practice_id, 'from': improvements[\"from\"], 'to': improvements[\"to\"], 'period': improvements[\"period\"]}])\n\n#https://openprescribing.net/measure/opioidper1000/practice/{}/\"\npractice_df['delta'] = practice_df[\"from\"] - practice_df[\"to\"]\npractice_df = practice_df.sort_values(\"delta\", ascending=False)\npractice_df[practice_df.period > 1]\n" } ]	3
davidbradway/learnpytest	https://github.com/davidbradway/learnpytest	0bc7d045613687a77eb056edd96b38a3cb9e90aa	4784b2effc8c6f8ee2658e811982051eb733f916	fcaf2a82cbe7163edccafc50c2df07d2f84d2fb8	refs/heads/master	2020-12-27T09:26:48.865229	2017-09-02T16:03:02	2017-09-02T16:03:02	68,554,303	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.51871657371521, "alphanum_fraction": 0.529411792755127, "avg_line_length": 19.77777862548828, "blob_id": "64ba524c584e5fb5b43270fbac4f557b09bc7875", "content_id": "ac15fc5f92a66b7658c7c1f52640b2a7cd08c0a9", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 187, "license_type": "permissive", "max_line_length": 33, "num_lines": 9, "path": "/test_class.py", "repo_name": "davidbradway/learnpytest", "src_encoding": "UTF-8", "text": "# content of test_class.py\nclass TestClass:\n def test_one(self):\n x = \"this\"\n assert 'h' in x\n\n def test_two(self):\n x = 3-5j\n assert hasattr(x, 'real')\n" }, { "alpha_fraction": 0.6931818127632141, "alphanum_fraction": 0.6931818127632141, "avg_line_length": 10, "blob_id": "62b20a9884b0e5052ca1bb5ac5ccd878c9683612", "content_id": "e28c20213e0cce6490d654a33c6760eacf61b3b0", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 176, "license_type": "permissive", "max_line_length": 52, "num_lines": 16, "path": "/README.md", "repo_name": "davidbradway/learnpytest", "src_encoding": "UTF-8", "text": "# Pytest Tutorial\n\n## Installation\n\n```bash\npip install -U pytest\npytest --version\n```\n\n## Run it\n\n`pytest`\n\n## Reference\n\nhttp://doc.pytest.org/en/latest/getting-started.html\n" } ]	2
EduardaMarques/AgendaContatoApp	https://github.com/EduardaMarques/AgendaContatoApp	b3b3f35bd6975102789f289435b5c0bd128606d3	87a0de58e725ef5fe024c47d2bd626892b73d28e	2ef50c61e31072b9f6dfa8857331116505efae6f	refs/heads/master	2021-01-23T11:50:23.701098	2017-09-25T22:17:09	2017-09-25T22:17:09	102,635,921	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5605839490890503, "alphanum_fraction": 0.563503623008728, "avg_line_length": 25.399999618530273, "blob_id": "180f6cd640b00879f30843be4c2982fab2877c4f", "content_id": "64228ce03252826c3d00eea537156a5b7c7f7378", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 685, "license_type": "no_license", "max_line_length": 70, "num_lines": 25, "path": "/model/Agenda.py", "repo_name": "EduardaMarques/AgendaContatoApp", "src_encoding": "UTF-8", "text": "from model.Contato import Contato\r\n\r\nclass Agenda ():\r\n def __init__(self, propietario):\r\n self.propietario = propietario\r\n self.contatos = []\r\n\r\n def contarContatos(self):\r\n return len(self.contatos)\r\n\r\n def incluirContato(self,contato):\r\n self.contatos.append(contato)\r\n\r\n\r\n def listarContato(self):\r\n return self.contatos\r\n\r\n def excluirContato(self,nome):\r\n auxiliar = 0\r\n for contato in self.contatos:\r\n if (contato.pessoa.nome == nome):\r\n del self.contatos[auxiliar]\r\n print(\"contato: \" + nome + \" removido com sucesso\\n\")\r\n break\r\n auxiliar +=1\r\n" }, { "alpha_fraction": 0.5249999761581421, "alphanum_fraction": 0.6187499761581421, "avg_line_length": 43.71428680419922, "blob_id": "301f6aac8707f492c77f9cb661ff063ce000b2ea", "content_id": "1fb4ce76e7bfa1bdef142015ddd4b5cd0ad0ec23", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 320, "license_type": "no_license", "max_line_length": 89, "num_lines": 7, "path": "/AGENDA/ClassPessoa.py", "repo_name": "EduardaMarques/AgendaContatoApp", "src_encoding": "UTF-8", "text": "Python 3.6.1 (v3.6.1:69c0db5, Mar 21 2017, 17:54:52) [MSC v.1900 32 bit (Intel)] on win32\r\nType \"copyright\", \"credits\" or \"license()\" for more information.\r\n>>> class Pessoa():\r\n def __init__(self, nome, nascimento, email):\r\n self.nome = nome\r\n self.nascimento = nascimento\r\n self.email = email\r\n" }, { "alpha_fraction": 0.553329586982727, "alphanum_fraction": 0.5571388006210327, "avg_line_length": 30.96744155883789, "blob_id": "2820d024b177aee34b128f9cd44de362199fd3c4", "content_id": "b3561ec6ad3fdcd69664a4159a2bf7d53e7fb2e6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7111, "license_type": "no_license", "max_line_length": 253, "num_lines": 215, "path": "/App.py", "repo_name": "EduardaMarques/AgendaContatoApp", "src_encoding": "UTF-8", "text": "# encoding: utf-8\r\nfrom model.Agenda import Agenda\r\nfrom model.Contato import Contato\r\nfrom model.Pessoa import Pessoa\r\nfrom model.Telefone import Telefone\r\nimport json\r\nimport datetime\r\nfrom datetime import date\r\n\r\ndef CriarAgenda():\r\n while(True):\r\n try:\r\n print(\">---Criar Nova Agenda---<\")\r\n nome = str(input(\"\\nDigite o nome do propietário da agenda:\\n\"))\r\n dia = int(input(\"Digite o dia do seu nascmento:\"))\r\n mes = int(input(\"Digite o numero do mes em que você nasceu:\"))\r\n ano = int(input(\"Digite o ano em que você nasceu:\"))\r\n nascimento = date(ano,mes,dia)\r\n email = str(input(\"Digite o email do propietario: \"))\r\n\r\n propietario = Pessoa(nome,nascimento,email)\r\n agenda = Agenda(propietario)\r\n return agenda\r\n\r\n except ValueError:\r\n print(\"\\nVocê digitou um valor inválido tente novamente\\nDica: Digite um valor inteiro e um dia possivel no ano:\")\r\n\r\n\r\ndef incluirContato(agenda):\r\n #Criando Objeto Pessoa\r\n nome = str(input(\"Digite o nome do conntato:\"))\r\n trueAuxiliar = True\r\n telefones = []\r\n\r\n while(trueAuxiliar):\r\n try:\r\n dia = int(input(\"Digite o dia do seu nascmento:\"))\r\n mes = int(input(\"Digite o numero do mes em que você nasceu:\"))\r\n ano = int(input(\"Digite o ano em que você nasceu:\"))\r\n nascimento = date(ano,mes,dia)\r\n\r\n\r\n email = str(input(\"Digite o email do contato:\"))\r\n pessoa = Pessoa(nome,nascimento,email)\r\n\r\n #Criando Objeto Telefone\r\n print(\"\\nAdicionar Telefone:\")\r\n numero = int(input(\"\\nDigite o numero do telefone:\"))\r\n ddd = int(input(\"Digite o ddd do telefone:\"))\r\n codigoPais = int(input(\"Digie o codigo do Pais\\n\"))\r\n\r\n telefones.append(Telefone(numero,ddd,codigoPais))\r\n trueAuxiliar = False\r\n except ValueError:\r\n print(\"\\n!!!Valor Inválido, Dica: Digite um valor inteiro e que esteja dentro da quantidade de meses e dias possiveis!!!\\n\")\r\n\r\n #Criacao do objeto Telefone\r\n while(True):\r\n try:\r\n resposta = int(input(\"Digite:\\n 1-Incluir outro telefone;\\n 2- Sair salvar contato.\"))\r\n if (resposta == 1):\r\n\r\n print(\"Adicionar outro telefone\")\r\n numero = int(input(\"\\nDigite o numero do telefone:\"))\r\n ddd = int(input(\"Digite o ddd do telefone:\"))\r\n codigoPais = int(input(\"Digie o codigo do Pais\\n\"))\r\n telefones.append(Telefone(numero,ddd,codigoPais))\r\n\r\n elif (resposta == 2):\r\n break\r\n\r\n else:\r\n print(\"\\n!!!Resposta Inválida!!!\\n\")\r\n\r\n except ValueError:\r\n print(\"\\n!!!Digite um número INTEIRO!!!\\n\")\r\n\r\n #Instanciação e inclusao de contato\r\n criacao = date.today()\r\n contato = Contato(criacao,pessoa,telefones)\r\n agenda.incluirContato(contato)\r\n\r\n\r\n\r\ndef listarContatos(agenda):\r\n lista = agenda.listarContato()\r\n for contato in lista:\r\n print(\"Contato: \" +contato.pessoa.nome)\r\n print(\"nasc: \" + str(contato.pessoa.nascimento))\r\n print(\"email: \" + contato.pessoa.email)\r\n contador = 1\r\n print(\"::::TELEFONES::::\")\r\n for telefone in contato.telefones:\r\n print(\"\\nTelefone\" + str(contador))\r\n print(\"nº:\",telefone.numero)\r\n print(\"DDD:\",telefone.ddd)\r\n print(\"Codigo do País:\",telefone.codigoPais)\r\n\r\ndef removerContato(agenda):\r\n nome = str(input(\"Digite o nome do contato a ser removido:\"))\r\n agenda.excluirContato(nome)\r\n\r\ndef buscarContato(agenda):\r\n nome = str(input(\"Digite o nome do contato a ser buscado:\"))\r\n auxiliar = 0\r\n for contato in agenda.contatos:\r\n if (contato.pessoa.nome == nome):\r\n print(\"Contato: \" +contato.pessoa.nome)\r\n print(\"nasc: \" + str(contato.pessoa.nascimento))\r\n print(\"email: \" + contato.pessoa.email)\r\n contador = 1\r\n print(\"::::TELEFONES::::\")\r\n for telefone in contato.telefones:\r\n print(\"\\nTelefone\" + str(contador))\r\n print(\"nº:\",telefone.numero)\r\n print(\"DDD:\",telefone.ddd)\r\n print(\"Codigo do País:\",telefone.codigoPais)\r\n break\r\n auxiliar +=1\r\n\r\ndef quantidadeContatos(agenda):\r\n print(agenda.contarContatos())\r\n\r\n\r\ndef default_parser(obj):\r\n if getattr(obj, \"__dict__\",None):\r\n return obj.__dict__\r\n\r\n elif type(obj) == datetime:\r\n return obj.isoformat()\r\n\r\n else:\r\n return str(obj)\r\n\r\ndef extrairSalvar(agenda):\r\n #Transformando Contato\r\n auxiliarContato = 0\r\n\r\n\r\n salvarAgenda = str(json.dumps(agenda,default = default_parser,indent=4))\r\n arquivo = open(\"agenda.json\", \"w\",encoding=\"utf-8\")\r\n arquivo.write(salvarAgenda)\r\n arquivo.close()\r\n\r\n\r\ndef main():\r\n agenda = None\r\n continuar = True\r\n telefones = []\r\n\r\n try:\r\n arquivo = open(\"agenda.json\" ,\"r\",encoding=\"utf-8\")\r\n jsontest = json.loads(arquivo.read())\r\n arquivo.close()\r\n contatos = []\r\n\r\n for contato in jsontest[\"contatos\"]:\r\n for telefone in contato[\"telefones\"]:\r\n numero = telefone[\"numero\"]\r\n ddd = telefone[\"ddd\"]\r\n codigoPais = telefone[\"codigoPais\"]\r\n telefone = Telefone(numero,ddd,codigoPais)\r\n telefones.append(telefone)\r\n\r\n criacao = contato[\"criacao\"]\r\n nome = contato[\"pessoa\"][\"nome\"]\r\n nascimento = contato[\"pessoa\"][\"nascimento\"]\r\n email = contato [\"pessoa\"][\"email\"]\r\n pessoa = Pessoa(nome,nascimento,email)\r\n contato = Contato(criacao,pessoa,telefones)\r\n contatos.append(contato)\r\n\r\n nome = jsontest[\"propietario\"]\r\n agenda = Agenda(nome)\r\n agenda.contatos = contatos\r\n\r\n\r\n except FileNotFoundError:\r\n agenda = CriarAgenda()\r\n\r\n while(continuar):\r\n try:\r\n escolha = int(input(\"\\nDigite o número correspondente a opção deejada:\\n\\n 1-Criar Agenda;\\n 2-Incluir Contato;\\n 3-Listar Contatos;\\n 4-Remover Contato;\\n 5-Buscar Contato; \\n 6- Contar Quantidade de Contatos;\\n 7- Sair e salvar.\\n---->>\"))\r\n\r\n if (escolha == 1):\r\n agenda = CriarAgenda()\r\n\r\n elif (escolha == 2):\r\n incluirContato(agenda)\r\n\r\n elif (escolha == 3):\r\n listarContatos(agenda)\r\n\r\n\r\n elif (escolha == 4):\r\n removerContato(agenda)\r\n\r\n elif (escolha == 5):\r\n buscarContato(agenda)\r\n\r\n elif (escolha == 6):\r\n quantidadeContatos(agenda)\r\n\r\n elif (escolha == 7):\r\n extrairSalvar(agenda)\r\n break\r\n\r\n else:\r\n print(\"Opção Inválida\")\r\n\r\n except ValueError:\r\n print(\"\\n---\\n!!!!Digite um número inteiro!!!\\n---\")\r\n\r\nif (__name__ == \"__main__\"):\r\n main()\r\n" }, { "alpha_fraction": 0.5879999995231628, "alphanum_fraction": 0.5879999995231628, "avg_line_length": 29, "blob_id": "05756a2131b74c25527159799c36d44fc6463778", "content_id": "c156753db83c40ec02d7f4136e32082ca6660550", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 250, "license_type": "no_license", "max_line_length": 49, "num_lines": 8, "path": "/model/Contato.py", "repo_name": "EduardaMarques/AgendaContatoApp", "src_encoding": "UTF-8", "text": "\r\nclass Contato():\r\n def __init__(self, pessoa, telefones = []):\r\n self.criacao = str(datetime.date.today())\r\n self.pessoa = pessoa\r\n self.telefone = telefones\r\n\r\n def listarTelefones(self):\r\n return self.telefones\r\n" } ]	4
AlanAlvarez5/Web-Personal-Django	https://github.com/AlanAlvarez5/Web-Personal-Django	43728a0dab648f6436381a76614e55b281524891	38083112396e3cf2e944431b509bc5be11bae701	403a2e73ad9bc0ac6b77ec522ef151f9460adff6	refs/heads/master	2020-04-24T07:08:42.345879	2019-02-21T19:21:42	2019-02-21T19:21:42	171,788,450	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5076923370361328, "alphanum_fraction": 0.5450549721717834, "avg_line_length": 20.619047164916992, "blob_id": "3110eeb3743d5fd03912abb37e61b53a9ac2f31f", "content_id": "fee5758d279450784f1e0489b664b2626a21fec0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "HTML", "length_bytes": 455, "license_type": "no_license", "max_line_length": 92, "num_lines": 21, "path": "/webpersonal/core/templates/core/contact.html", "repo_name": "AlanAlvarez5/Web-Personal-Django", "src_encoding": "UTF-8", "text": "{% extends 'core/base.html' %}\n\n{% block titile %} Contacto {% endblock %} \n\n\n{% block background %} {% load static %}{% static 'core/img/contact-bg.jpg' %}{% endblock %}\n\n{% block header %}\n <h1>Contacto</h1>\n <span class=\"subheading\"></span>\n{% endblock%}\n\n\n{% block content %} \n<div class=\"row\"> \n <div class=\"col-lg-8 col-md-10 mx-auto\">\n <br>\n <p><b>Telefono:</b> +52 464 464 1251</p>\n </div>\n</div>\n {% endblock %} \n" }, { "alpha_fraction": 0.5271867513656616, "alphanum_fraction": 0.6004728078842163, "avg_line_length": 22.5, "blob_id": "8f863d15fd336c66196a32dd0101d2aabe0578be", "content_id": "f4a324b511dfc2ade5d412827da12b8f2c9e7f37", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 424, "license_type": "no_license", "max_line_length": 87, "num_lines": 18, "path": "/webpersonal/portfolio/migrations/0003_auto_20190220_2023.py", "repo_name": "AlanAlvarez5/Web-Personal-Django", "src_encoding": "UTF-8", "text": "# Generated by Django 2.1.7 on 2019-02-21 02:23\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('portfolio', '0002_auto_20190220_2000'),\n ]\n\n operations = [\n migrations.AlterField(\n model_name='project',\n name='url',\n field=models.URLField(blank=True, null=True, verbose_name='Dirección Web'),\n ),\n ]\n" }, { "alpha_fraction": 0.7966101765632629, "alphanum_fraction": 0.7966101765632629, "avg_line_length": 28.5, "blob_id": "c7b582c4d7f2f9b78adc25680d44cd2d45be0060", "content_id": "9d11b298ca4fcb2b4ad11d594abc5cf9c3fbbb10", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 59, "license_type": "no_license", "max_line_length": 36, "num_lines": 2, "path": "/README.md", "repo_name": "AlanAlvarez5/Web-Personal-Django", "src_encoding": "UTF-8", "text": "# Web-Personal-Django\nSitio web personal creado en Django.\n" } ]	3
davidabbey/jUnitTesting	https://github.com/davidabbey/jUnitTesting	6eef3d01fc374dcea8b51385ce61d58ddf90d167	c9a441cbe547d766dc6a5818069f1d4d0c9faece	347d96106c11271acd3425ddfae6f34e9053221c	refs/heads/master	2016-09-05T15:26:52.160621	2015-09-11T19:48:21	2015-09-11T19:48:21	42,269,819	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.598901093006134, "alphanum_fraction": 0.6098901033401489, "avg_line_length": 15.545454978942871, "blob_id": "828738b85e0e33a363375ecdf5f738211e06e195", "content_id": "d1810f2193d1225b051584da4d4151d173e79775", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 182, "license_type": "no_license", "max_line_length": 36, "num_lines": 11, "path": "/javaTest/pythonTest/src/test/Python/test_MD_XML_Task.py", "repo_name": "davidabbey/jUnitTesting", "src_encoding": "UTF-8", "text": "import unittest\n\n\nclass MyTestCase(unittest.TestCase):\n def test01_something(self):\n #pass\n self.fail('hello there')\n\n\nif __name__ =='__main__':\n unittest.main()\n" }, { "alpha_fraction": 0.682539701461792, "alphanum_fraction": 0.6888889074325562, "avg_line_length": 20.066667556762695, "blob_id": "18252b76825ccc9fe167ce602c9ed6abf9af02cf", "content_id": "28e4bf4a6455ff608e428549f3352a9aa7e56341", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 315, "license_type": "no_license", "max_line_length": 102, "num_lines": 15, "path": "/pythonTest/src/test/Python/test_MD_XML_Task.py", "repo_name": "davidabbey/jUnitTesting", "src_encoding": "UTF-8", "text": "__author__ = 'abbeyd'\nimport unittest\nimport xmlrunner.xmlrunner\n\n\n\n\nclass MyTestCase(unittest.TestCase):\n def test01_something(self):\n pass\n #self.fail('hello there')\n\n\nif __name__ =='__main__':\n unittest.main(testRunner=xmlrunner.xmlrunner.XMLTestRunner(output='test-reports',outsuffix='txt'))" } ]	2
waliamehak/LearnML	https://github.com/waliamehak/LearnML	f4268b0f7965ce15677e03d06841a425b77e30c4	1fc163f1c3f379d5e03fbb077574d3485df61f99	cfa95eb1a1f6baef58f501314484fdb1cbbe8767	refs/heads/main	2023-08-14T14:23:12.107607	2021-10-11T10:45:23	2021-10-11T10:45:23	410,338,243	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7830188870429993, "alphanum_fraction": 0.7830188870429993, "avg_line_length": 20.200000762939453, "blob_id": "361687cece6bca75c9dde3aa955afc262f95ca78", "content_id": "f9c963e501e08e70721ac46b62557f2ee861547a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 106, "license_type": "no_license", "max_line_length": 39, "num_lines": 5, "path": "/admin_classifier/apps.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from django.apps import AppConfig\n\n\nclass AdminClassifierConfig(AppConfig):\n name = 'admin_classifier'\n" }, { "alpha_fraction": 0.7788461446762085, "alphanum_fraction": 0.7788461446762085, "avg_line_length": 19.799999237060547, "blob_id": "fdc553c72ee0f0742e47d3ca9e4f58e21e6cdfb8", "content_id": "a82df9a8efe13c99bda7f269b4ca4e8e3f3cc76e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 104, "license_type": "no_license", "max_line_length": 38, "num_lines": 5, "path": "/user_classifier/apps.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from django.apps import AppConfig\n\n\nclass UserClassifierConfig(AppConfig):\n name = 'user_classifier'\n" }, { "alpha_fraction": 0.744107723236084, "alphanum_fraction": 0.7508417367935181, "avg_line_length": 22.719999313354492, "blob_id": "b9d36e6fad597abb02c3ea2e477dae75f14af989", "content_id": "8e30a12219487b7fedc8c2fc080e74ffa700e1b3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 594, "license_type": "no_license", "max_line_length": 49, "num_lines": 25, "path": "/LearnML Files/Temp Files/prac.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "# Importing the libraries\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n# Importing the dataset\ndataset = pd.read_csv(\"50_Startups.csv\")\nX = dataset.iloc[:, :-1].values\ny = dataset.iloc[:, -1].values\n\n# Feature scaling\nfrom sklearn.preprocessing import StandardScaler\nsc_X = StandardScaler()\nX = sc_X.fit_transform(X)\n\n# Fitting the model with training dataset\nfrom sklearn.linear_model import LinearRegression\nregressor = LinearRegression()\nregressor.fit(X, y)\n\nimport pickle\nwith open('regressor.pkl', 'wb') as file:\n pickle.dump(regressor, file)\n\nprint(\"Done\")\n\n" }, { "alpha_fraction": 0.5122588872909546, "alphanum_fraction": 0.7038247585296631, "avg_line_length": 16.38068199157715, "blob_id": "8ad5e9b6bf46d076cdf1f9d14d4aa2bfa892c1a2", "content_id": "76015c56f975438e67bb81a3ab47dc080d84a436", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 3059, "license_type": "no_license", "max_line_length": 36, "num_lines": 176, "path": "/requirements.txt", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "absl-py==0.13.0\nalabaster==0.7.12\nanyio==3.3.0\nappdirs==1.4.4\nargon2-cffi==20.1.0\narrow==1.1.1\nasgiref==3.4.1\nastroid==2.6.5\nastunparse==1.6.3\nasync-generator==1.10\natomicwrites==1.4.0\nattrs==21.2.0\nautopep8==1.5.7\nBabel==2.9.1\nbackcall==0.2.0\nbcrypt==3.2.0\nbinaryornot==0.4.4\nblack==21.7b0\nbleach==3.3.1\ncached-property==1.5.2\ncachetools==4.2.2\ncertifi==2021.5.30\ncffi==1.14.6\nchardet==4.0.0\ncharset-normalizer==2.0.4\nclick==8.0.1\ncloudpickle==1.6.0\ncolorama==0.4.4\ncookiecutter==1.7.3\ncryptography==3.4.7\ncycler==0.10.0\nCython==0.29.21\ndebugpy==1.4.1\ndecorator==5.0.9\ndefusedxml==0.7.1\ndiff-match-patch==20200713\nDjango==3.2.5\ndnspython==1.16.0\ndocutils==0.17.1\nentrypoints==0.3\nflake8==3.9.2\nflatbuffers==1.12\ngast==0.4.0\ngoogle-auth==1.34.0\ngoogle-auth-oauthlib==0.4.5\ngoogle-pasta==0.2.0\ngrpcio==1.34.1\ngunicorn==20.1.0\nh5py==3.1.0\nidna==3.2\nimagesize==1.2.0\nimportlib-metadata==3.10.1\ninflection==0.5.1\nintervaltree==3.1.0\nipykernel==6.0.3\nipython==7.26.0\nipython-genutils==0.2.0\nipywidgets==7.6.3\nisort==5.9.3\njedi==0.18.0\nJinja2==3.0.1\njinja2-time==0.2.0\njoblib==1.0.1\njson5==0.9.6\njsonschema==3.2.0\nkeyring==23.0.1\nkiwisolver==1.3.1\nlazy-object-proxy==1.6.0\nMarkdown==3.3.4\nMarkupSafe==2.0.1\nmccabe==0.6.1\nmistune==0.8.4\nmypy-extensions==0.4.3\nnbclassic==0.3.1\nnbclient==0.5.3\nnbconvert==6.1.0\nnbformat==5.1.3\nnest-asyncio==1.5.1\nnotebook==6.4.0\nnumpy==1.19.5\nnumpydoc==1.1.0\noauthlib==3.1.1\nopt-einsum==3.3.0\npackaging==21.0\npandas==1.3.1\npandocfilters==1.4.3\nparamiko==2.7.2\nparso==0.8.2\npathspec==0.9.0\npatsy==0.5.1\npexpect==4.8.0\npickleshare==0.7.5\nPillow==8.3.1\npluggy==0.13.1\npoyo==0.5.0\nprometheus-client==0.11.0\nprompt-toolkit==3.0.19\nprotobuf==3.17.3\npsutil==5.8.0\nptyprocess==0.7.0\npyasn1==0.4.8\npyasn1-modules==0.2.8\npybind11==2.7.0\npycodestyle==2.7.0\npycparser==2.20\npydocstyle==6.1.1\npyee==7.0.4\npyflakes==2.3.1\nPygments==2.9.0\npylint==2.9.6\npyls-spyder==0.4.0\npymongo==3.12.0\nPyNaCl==1.4.0\npyparsing==2.4.7\npyppeteer==0.2.2\nPyYAML==5.4.1\npyzmq==22.1.0\nQDarkStyle==3.0.2\nqstylizer==0.2.1\nQtAwesome==1.0.3\nqtconsole==5.1.1\nQtPy==1.9.0\nregex==2021.7.6\nrequests==2.26.0\nrequests-oauthlib==1.3.0\nrequests-unixsocket==0.2.0\nrope==0.19.0\nrsa==4.7.2\nRtree==0.9.7\nscikit-learn==0.24.2\nscipy==1.7.1\nselenium==3.141.0\nSend2Trash==1.7.1\nsix==1.15.0\nsklearn==0.0\nsmart-open==5.1.0\nsniffio==1.2.0\nsnowballstemmer==2.1.0\nsortedcontainers==2.4.0\nSphinx==4.1.2\nsphinxcontrib-applehelp==1.0.2\nsphinxcontrib-devhelp==1.0.2\nsphinxcontrib-htmlhelp==2.0.0\nsphinxcontrib-jsmath==1.0.1\nsphinxcontrib-qthelp==1.0.3\nsphinxcontrib-serializinghtml==1.1.5\nsqlparse==0.4.1\ntenacity==8.0.1\ntermcolor==1.1.0\nterminado==0.10.1\ntestpath==0.5.0\ntext-unidecode==1.3\ntextdistance==4.2.1\nthreadpoolctl==2.2.0\nthree-merge==0.1.1\ntinycss2==1.1.0\ntoml==0.10.2\ntomli==1.2.0\ntornado==6.1\ntqdm==4.62.0\ntraitlets==5.0.5\ntyped-ast==1.4.3\ntyping-extensions==3.7.4.3\nujson==4.0.2\nurllib3==1.26.6\nwaitress==2.0.0\nwatchdog==2.1.3\nwcwidth==0.2.5\nwebencodings==0.5.1\nwebsocket-client==1.1.0\nwebsockets==8.1\nWerkzeug==2.0.1\nwidgetsnbextension==3.5.1\nwrapt==1.12.1\nyapf==0.31.0\nzipp==3.5.0\n" }, { "alpha_fraction": 0.7013698816299438, "alphanum_fraction": 0.7013698816299438, "avg_line_length": 39.55555725097656, "blob_id": "ba023081c434c6b61e3411b9c5dc2eadc6e2069d", "content_id": "7f48ecedd2986ae1a679e5b848150f73c577df51", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 365, "license_type": "no_license", "max_line_length": 88, "num_lines": 9, "path": "/admin_classifier/urls.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from django.urls import path\nfrom . import views\n\nurlpatterns = [\n path('', views.Home.as_view(), name='admin_home'),\n path('classification', views.Classification.as_view(), name='admin_classification'),\n path('regression', views.Regression.as_view(), name='admin_regression'),\n path('clustering', views.Clustering.as_view(), name='admin_clustering')\n]\n" }, { "alpha_fraction": 0.5568748712539673, "alphanum_fraction": 0.5598937273025513, "avg_line_length": 46.14231491088867, "blob_id": "a620045df47af7484e5f7a550c173e14a65cf6c6", "content_id": "5f35d290cfa443008b43900ae18604a46195d1d7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 24844, "license_type": "no_license", "max_line_length": 135, "num_lines": 527, "path": "/admin_classifier/views.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "# Django Imports\nfrom django.shortcuts import render\nfrom django.views import View\n\n# Internal Imports\nfrom . import mongodb as mdb\n\n# Python Package Imports\nimport pickle\nimport pandas as pd\nfrom io import StringIO\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.metrics import accuracy_score\nfrom bson.binary import Binary\nfrom base64 import b64encode\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.metrics import mean_squared_error\nfrom sklearn.cluster import KMeans\nfrom abc import ABC, abstractmethod\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import f1_score\nfrom sklearn.preprocessing import StandardScaler\n\ndata = pd.DataFrame({})\ndb_data = mdb.access()\n\n\n# Home Module Starts\nclass Home(View):\n\n template_name = 'admin_classifier/home.html'\n context = {}\n\n def get(self, request):\n return render(request, self.template_name, self.context)\n# Home Module Ends\n\n\n# Simple Factory Pattern Starts:\nclass Algorithm(View):\n\n def get(self, request):\n pass\n\n def post(self, request):\n pass\n\n @staticmethod\n def description_update(algo_desc, ds_desc, algo_name):\n update_data = {'algo_desc': str(algo_desc), 'ds_desc': str(ds_desc)}\n update_message = mdb.update(db_data, algo_name, update_data, \"Descriptions Updated\",\n \"Unexpected error while updating descriptions\")\n return update_message\n\n @staticmethod\n def pkl_upload(upload_file, algo_name):\n if upload_file.content_type == 'application/octet-stream':\n pkl_obj = pickle.dumps(upload_file)\n mongo_data = {'pkl_data': Binary(pkl_obj), 'upload_method': 'pkl'}\n pkl_message = mdb.update(db_data, algo_name, mongo_data, \"File Uploaded\",\n \"Unexpected error while uploading pickle file\")\n else:\n pkl_message = \"Invalid File Type\"\n return pkl_message\n\n @staticmethod\n def pkl_change(pkl_features_temp, algo_name, pkl_label_notes_temp=None):\n pkl_features = []\n for feature in pkl_features_temp:\n pkl_features.append(feature.strip())\n if algo_name != \"MLR\":\n pkl_label_notes = {}\n for label in pkl_label_notes_temp:\n temp = label.split(\"=\")\n pkl_label_notes[temp[0].strip()] = temp[1].strip()\n mongo_data = {'label_notes': pkl_label_notes, 'training_features': pkl_features}\n else:\n mongo_data = {'training_features': pkl_features}\n pkl_change_message = mdb.update(db_data, algo_name, mongo_data, \"Success\", \"Error\")\n return pkl_change_message\n\n @staticmethod\n def graph_upload(image_file, algo_name):\n if image_file.content_type == 'image/png' or image_file.content_type == 'image/jpeg' or image_file.content_type == 'image/jpg':\n image_data = image_file.read()\n encoded_image = str(b64encode(image_data))[2:-1]\n mime = str(image_file.content_type)\n mime = mime + ';' if mime else ';'\n graph_image = \"data:%sbase64,%s\" % (mime, encoded_image)\n mongo_data = {'graph_image': graph_image}\n graph_message = mdb.update(db_data, algo_name, mongo_data, \"Success\", \"Error\")\n else:\n graph_message = \"Invalid Image Type\"\n return graph_message\n\n @staticmethod\n def csv_upload(upload_file):\n global data\n feature_list = []\n if upload_file.content_type == 'application/vnd.ms-excel' and upload_file.size < 50000:\n string_data = StringIO(upload_file.read().decode('utf-8'))\n data = pd.read_csv(string_data)\n feature_list = list(data.columns)\n csv_message = \"File Uploaded\"\n else:\n if upload_file.content_type != 'application/vnd.ms-excel':\n csv_message = \"Invalid File Type\"\n else:\n csv_message = \"Maximum size of the CSV file should be less than 50kb\"\n return feature_list, csv_message\n\n @staticmethod\n def scale(X_train, X_test):\n sc = StandardScaler()\n X_train = sc.fit_transform(X_train)\n X_test = sc.transform(X_test)\n return pickle.dumps(sc), X_train, X_test\n\n\nclass Classification(Algorithm):\n\n template_name = 'admin_classifier/classification.html'\n context = {}\n feature_list = []\n submit_button = None\n message = None\n pkl_message = None\n pkl_change_message = None\n csv_message = None\n update_message = None\n accuracy = None\n f1_score = None\n algo_desc = None\n ds_desc = None\n\n def get(self, request):\n\n descriptions = mdb.find(db_data, \"KNN\")\n self.algo_desc = descriptions['algo_desc']\n self.ds_desc = descriptions['ds_desc']\n self.context = {'algo_desc': self.algo_desc, 'ds_desc': self.ds_desc}\n return render(request, self.template_name, self.context)\n\n def post(self, request):\n\n global data\n descriptions = mdb.find(db_data, \"KNN\")\n self.algo_desc = descriptions['algo_desc']\n self.ds_desc = descriptions['ds_desc']\n\n if 'update' in request.POST:\n self.algo_desc = request.POST.get('algo_desc')\n self.ds_desc = request.POST.get('ds_desc')\n self.update_message = Algorithm.description_update(self.algo_desc, self.ds_desc, 'KNN')\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Classification Description\")\n self.context = {'update_message': self.update_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'pkl' in request.FILES:\n upload_file = request.FILES['pkl']\n self.pkl_message = Algorithm.pkl_upload(upload_file, 'KNN')\n self.context = {'pkl_message': self.pkl_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'pkl_change' in request.POST:\n pkl_features_temp = str(request.POST.get('pkl_features')).split(',')\n pkl_label_notes_temp = str(request.POST.get(\"pkl_label_notes\")).split(\"\\r\\n\")\n image_file = request.FILES['graph_image']\n pkl_change_message_temp = Algorithm.pkl_change(pkl_features_temp, \"KNN\", pkl_label_notes_temp)\n graph_message = Algorithm.graph_upload(image_file, \"KNN\")\n if pkl_change_message_temp == \"Success\" and graph_message == \"Success\":\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Classification Pickle File\")\n self.pkl_change_message = \"Changes Saved Successfully\"\n else:\n if graph_message != \"Success\":\n self.pkl_change_message = \"Invalid Image Type\"\n else:\n self.pkl_change_message = \"Unexpected error while saving pickle changes\"\n self.context = {'pkl_change_message': self.pkl_change_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'csv' in request.FILES:\n upload_file = request.FILES['csv']\n self.feature_list, self.csv_message = Algorithm.csv_upload(upload_file)\n self.context = {'csv_message': self.csv_message, 'features': self.feature_list, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'submit' in request.POST:\n self.submit_button = request.POST.get(\"submit\")\n image_file = request.FILES['csv_image']\n graph_message = Algorithm.graph_upload(image_file, \"KNN\")\n if graph_message == \"Success\":\n n_neighbors = int(request.POST.get(\"neighbors\"))\n leaf_size = int(request.POST.get(\"leaf\"))\n weights = str(request.POST.get(\"weights\"))\n algorithm = str(request.POST.get(\"algorithm\"))\n training_features = list(request.POST.getlist(\"training_features\"))\n training_label = str(request.POST.get(\"training_label\"))\n csv_label_notes_temp = str(request.POST.get(\"csv_label_notes\")).split(\"\\r\\n\")\n try:\n csv_label_notes = {}\n for label in csv_label_notes_temp:\n temp = label.split(\"=\")\n csv_label_notes[temp[0].strip()] = temp[1].strip()\n\n X = data.loc[:, training_features].values\n y = data.loc[:, training_label].values\n X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=0)\n classifier = KNeighborsClassifier(n_neighbors=n_neighbors,\n leaf_size=leaf_size,\n weights=weights,\n algorithm=algorithm)\n sc, X_train, X_test = Algorithm.scale(X_train, X_test)\n classifier.fit(X_train, y_train)\n y_pred = classifier.predict(X_test)\n self.accuracy = round(accuracy_score(y_test, y_pred) * 100, 2)\n self.f1_score = round(f1_score(y_test, y_pred) * 100, 2)\n if self.accuracy >= 90 and self.f1_score >= 80:\n pkl_obj = pickle.dumps(classifier)\n mongo_data = {'pkl_data': Binary(pkl_obj), 'training_features': training_features,\n 'label_notes': csv_label_notes, 'upload_method': 'csv',\n 'testing_accuracy': self.accuracy, 'f1_score': self.f1_score,\n 'scaling_obj': sc}\n self.message = mdb.update(db_data, \"KNN\", mongo_data, \"Model Successfully Trained\",\n \"Unexpected error while training the model\")\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Classification CSV File\")\n else:\n self.message = \"Model Training Failed. The accuracy of the model should be > 90% and \" \\\n \"the F1-Score should be > 80%. However, this model's accuracy \" \\\n \"is \" + str(self.accuracy) + \"% and the F1-Score \" \\\n \"is \" + str(self.f1_score) + \"%.\"\n except:\n self.message = \"Unexpected error while training the model\"\n else:\n self.message = \"Invalid Image Type\"\n\n self.context = {'submitbutton': self.submit_button, 'pkl_message': self.pkl_message,\n 'csv_message': self.csv_message, 'accuracy': self.accuracy, 'message': self.message,\n 'algo_desc': self.algo_desc, 'ds_desc': self.ds_desc, 'f1_score': self.f1_score}\n\n return render(request, self.template_name, self.context)\n\n\nclass Regression(Algorithm):\n\n template_name = 'admin_classifier/regression.html'\n context = {}\n feature_list = []\n submit_button = None\n message = None\n pkl_message = None\n pkl_change_message = None\n csv_message = None\n update_message = None\n rmse = None\n algo_desc = None\n ds_desc = None\n\n def get(self, request):\n\n descriptions = mdb.find(db_data, \"MLR\")\n self.algo_desc = descriptions['algo_desc']\n self.ds_desc = descriptions['ds_desc']\n self.context = {'algo_desc': self.algo_desc, 'ds_desc': self.ds_desc}\n return render(request, self.template_name, self.context)\n\n def post(self, request):\n\n global data\n descriptions = mdb.find(db_data, \"MLR\")\n self.algo_desc = descriptions['algo_desc']\n self.ds_desc = descriptions['ds_desc']\n\n if 'update' in request.POST:\n self.algo_desc = request.POST.get('algo_desc')\n self.ds_desc = request.POST.get('ds_desc')\n self.update_message = Algorithm.description_update(self.algo_desc, self.ds_desc, 'MLR')\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Regression Description\")\n self.context = {'update_message': self.update_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'pkl' in request.FILES:\n upload_file = request.FILES['pkl']\n self.pkl_message = Algorithm.pkl_upload(upload_file, 'MLR')\n self.context = {'pkl_message': self.pkl_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'pkl_change' in request.POST:\n pkl_features_temp = str(request.POST.get('pkl_features')).split(',')\n image_file = request.FILES['graph_image']\n pkl_change_message_temp = Algorithm.pkl_change(pkl_features_temp, \"MLR\")\n graph_message = Algorithm.graph_upload(image_file, \"MLR\")\n if pkl_change_message_temp == \"Success\" and graph_message == \"Success\":\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Regression Pickle File\")\n self.pkl_change_message = \"Changes Saved Successfully\"\n else:\n if graph_message != \"Success\":\n self.pkl_change_message = \"Invalid Image Type\"\n else:\n self.pkl_change_message = \"Unexpected error while saving pickle changes\"\n self.context = {'pkl_change_message': self.pkl_change_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'csv' in request.FILES:\n upload_file = request.FILES['csv']\n self.feature_list, self.csv_message = Algorithm.csv_upload(upload_file)\n self.context = {'csv_message': self.csv_message, 'features': self.feature_list, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'submit' in request.POST:\n self.submit_button = request.POST.get(\"submit\")\n image_file = request.FILES['csv_image']\n graph_message = Algorithm.graph_upload(image_file, \"MLR\")\n if graph_message == \"Success\":\n fit_intercept = str(request.POST.get(\"fit_intercept\"))\n fit_intercept = True if fit_intercept == \"True\" else False\n normalize = str(request.POST.get(\"normalize\"))\n normalize = True if normalize == \"True\" else False\n training_features = list(request.POST.getlist(\"training_features\"))\n training_label = str(request.POST.get(\"training_label\"))\n\n try:\n X = data.loc[:, training_features].values\n y = data.loc[:, training_label].values\n X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=0)\n sc, X_train, X_test = Algorithm.scale(X_train, X_test)\n regressor = LinearRegression(fit_intercept=fit_intercept,\n normalize=normalize)\n regressor.fit(X_train, y_train)\n y_pred = regressor.predict(X_test)\n self.rmse = round((mean_squared_error(y_test, y_pred))*0.5, 2)\n print(self.rmse, y_test.mean()0.1)\n if self.rmse <= (y_test.mean()0.1):\n pkl_obj = pickle.dumps(regressor)\n mongo_data = {'pkl_data': Binary(pkl_obj), 'training_features': training_features,\n 'rmse': self.rmse, 'scaling_obj': sc, 'upload_method': 'csv'}\n self.message = mdb.update(db_data, \"MLR\", mongo_data, \"Model Successfully Trained\",\n \"Unexpected error while training the model\")\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Regression CSV File\")\n else:\n self.message = \"Model Training Failed. The RMSE values of the model should be \" \\\n \"less than 10% of the actual values. For this model, 10% of the actual value \" \\\n \"is \" + str(round(y_test.mean()0.1, 2)) + \" and the RMSE value \" \\\n \"is \" + str(self.rmse)\n except:\n self.message = \"Unexpected error while training the model\"\n else:\n self.message = \"Invalid Image Type\"\n\n self.context = {'submitbutton': self.submit_button, 'pkl_message': self.pkl_message,\n 'csv_message': self.csv_message, 'rmse': self.rmse, 'message': self.message,\n 'algo_desc': self.algo_desc, 'ds_desc': self.ds_desc}\n\n return render(request, self.template_name, self.context)\n\n\nclass Clustering(Algorithm):\n\n template_name = 'admin_classifier/clustering.html'\n context = {}\n feature_list = []\n submit_button = None\n message = None\n pkl_message = None\n pkl_change_message = None\n csv_message = None\n update_message = None\n algo_desc = None\n ds_desc = None\n\n def get(self, request):\n\n descriptions = mdb.find(db_data, \"KM\")\n self.algo_desc = descriptions['algo_desc']\n self.ds_desc = descriptions['ds_desc']\n self.context = {'algo_desc': self.algo_desc, 'ds_desc': self.ds_desc}\n return render(request, self.template_name, self.context)\n\n def post(self, request):\n\n global data\n descriptions = mdb.find(db_data, \"KM\")\n self.algo_desc = descriptions['algo_desc']\n self.ds_desc = descriptions['ds_desc']\n\n if 'update' in request.POST:\n self.algo_desc = request.POST.get('algo_desc')\n self.ds_desc = request.POST.get('ds_desc')\n self.update_message = Algorithm.description_update(self.algo_desc, self.ds_desc, 'KM')\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Clustering Description\")\n self.context = {'update_message': self.update_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'pkl' in request.FILES:\n upload_file = request.FILES['pkl']\n self.pkl_message = Algorithm.pkl_upload(upload_file, 'KM')\n self.context = {'pkl_message': self.pkl_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'pkl_change' in request.POST:\n pkl_features_temp = str(request.POST.get('pkl_features')).split(',')\n pkl_label_notes_temp = str(request.POST.get(\"pkl_label_notes\")).split(\"\\r\\n\")\n image_file = request.FILES['graph_image']\n pkl_change_message_temp = Algorithm.pkl_change(pkl_features_temp, \"KM\", pkl_label_notes_temp)\n graph_message = Algorithm.graph_upload(image_file, \"KM\")\n if pkl_change_message_temp == \"Success\" and graph_message == \"Success\":\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Clustering Pickle File\")\n self.pkl_change_message = \"Changes Saved Successfully\"\n else:\n if graph_message != \"Success\":\n self.pkl_change_message = \"Invalid Image Type\"\n else:\n self.pkl_change_message = \"Unexpected error while saving pickle changes\"\n self.context = {'pkl_change_message': self.pkl_change_message, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'csv' in request.FILES:\n upload_file = request.FILES['csv']\n self.feature_list, self.csv_message = Algorithm.csv_upload(upload_file)\n self.context = {'csv_message': self.csv_message, 'features': self.feature_list, 'algo_desc': self.algo_desc,\n 'ds_desc': self.ds_desc}\n elif 'submit' in request.POST:\n self.submit_button = request.POST.get(\"submit\")\n image_file = request.FILES['csv_image']\n graph_message = Algorithm.graph_upload(image_file, \"KM\")\n if graph_message == \"Success\":\n n_clusters = int(request.POST.get(\"n_clusters\"))\n init = str(request.POST.get(\"init\"))\n n_init = int(request.POST.get(\"n_init\"))\n max_iter = int(request.POST.get(\"max_iter\"))\n training_features = list(request.POST.getlist(\"training_features\"))\n\n X = data.loc[:, training_features].values\n kmeans = KMeans(n_clusters=n_clusters, init=init, n_init=n_init, max_iter=max_iter)\n try:\n kmeans.fit(X)\n csv_label_notes_temp = str(request.POST.get(\"csv_label_notes\")).split(\"\\r\\n\")\n csv_label_notes = {}\n for label in csv_label_notes_temp:\n temp = label.split(\"=\")\n values = (temp[0].strip()).split(\",\")\n values = list(map(int, values))\n key = kmeans.predict([values])[0]\n csv_label_notes[str(key)] = temp[1].strip()\n pkl_obj = pickle.dumps(kmeans)\n mongo_data = {'pkl_data': Binary(pkl_obj), 'training_features': training_features,\n 'label_notes': csv_label_notes, 'upload_method': 'csv'}\n self.message = mdb.update(db_data, \"KM\", mongo_data, \"Model Successfully Trained\",\n \"Unexpected error while training the model\")\n op_data = mdb.find(db_data, 'OP')\n subject_obj = ConcreteSubject(op_data['observer_list'], op_data['update_message_list'])\n subject_obj.notify(\"Clustering CSV File\")\n except:\n self.message = \"Unexpected error while training the model\"\n else:\n self.message = \"Invalid Image Type\"\n\n self.context = {'submitbutton': self.submit_button, 'pkl_message': self.pkl_message,\n 'csv_message': self.csv_message, 'message': self.message,\n 'algo_desc': self.algo_desc, 'ds_desc': self.ds_desc}\n\n return render(request, self.template_name, self.context)\n# Simple Factory Pattern Ends\n\n\n# Observer Pattern Starts\nclass Subject(ABC):\n\n @abstractmethod\n def subscribe(self, learner):\n pass\n\n @abstractmethod\n def unsubscribe(self, learner):\n pass\n\n @abstractmethod\n def notify(self, update):\n pass\n\n\nclass ConcreteSubject(Subject):\n\n def __init__(self, learners, messages):\n\n self._learners = learners\n self._messages = messages\n\n def subscribe(self, learner):\n\n self._learners.append(learner)\n mongo_data = {'observer_list': self._learners}\n temp = mdb.update(db_data, \"OP\", mongo_data, \"Success\", \"Error\")\n\n def unsubscribe(self, learner):\n\n self._learners.remove(learner)\n mongo_data = {'observer_list': self._learners}\n temp = mdb.update(db_data, \"OP\", mongo_data, \"Success\", \"Error\")\n\n def notify(self, update):\n\n self._messages.insert(0, \"Admin Has Updated The \" + str(update))\n if len(self._messages) > 5:\n temp = self._messages.pop()\n mongo_data = {'update_message_list': self._messages}\n temp = mdb.update(db_data, \"OP\", mongo_data, \"Success\", \"Error\")\n\n\nclass Learner(ABC):\n\n @abstractmethod\n def update(self):\n pass\n\n\nclass ConcreteLearner(Learner):\n\n def update(self):\n mongo_data = mdb.find(db_data, \"OP\")\n return mongo_data\n# Observer Pattern Ends\n" }, { "alpha_fraction": 0.5896840691566467, "alphanum_fraction": 0.5914893746376038, "avg_line_length": 37.775001525878906, "blob_id": "b06c84b38f6ee096147d1013ddab3c1a381b9233", "content_id": "3b4b517be6048ef92b6e0064fb60c4fa21e9c2a4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7755, "license_type": "no_license", "max_line_length": 100, "num_lines": 200, "path": "/user_classifier/views.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "# Django Imports\nfrom django.shortcuts import render, redirect\nfrom django.contrib import messages\nfrom django.utils.decorators import method_decorator\nfrom django.contrib.auth.models import Group\nfrom django.views import View\n\n# Internal Imports\nfrom . import mongodb as mdb\nfrom .forms import CreateUserForm\nfrom admin_classifier.views import ConcreteSubject, ConcreteLearner\n\n# Python Package Imports\nimport pickle\nimport numpy as np\n\n# Create your views here.\ndb_data = mdb.access()\n\n\n# Home and Login Module Starts\nclass Home(View):\n\n template_name = 'user_classifier/home.html'\n context = {}\n\n def get(self, request):\n username = str(request.user)\n learner = ConcreteLearner()\n mongo_data = learner.update()\n len_update_messages_list = len(mongo_data['update_message_list'])\n temp = \"\\n\".join(mongo_data['update_message_list'])\n update_messages_list = [temp]\n observer_list = mongo_data['observer_list']\n self.context = {'username': str(username),\n 'observer_list': observer_list,\n 'update_messages_list': update_messages_list,\n 'len_update_messages_list': len_update_messages_list}\n return render(request, self.template_name, self.context)\n\n def post(self, request):\n username = str(request.user)\n learner = ConcreteLearner()\n mongo_data = learner.update()\n subject = ConcreteSubject(mongo_data[\"observer_list\"], mongo_data[\"update_message_list\"])\n if request.POST.get('subscribe') == \"Subscribe Updates\":\n alert_message = subject.subscribe(username)\n if request.POST.get('unsubscribe') == \"Unsubscribe Updates\":\n alert_message = subject.unsubscribe(username)\n mongo_data = learner.update()\n len_update_messages_list = len(mongo_data['update_message_list'])\n temp = \"\\n\".join(mongo_data['update_message_list'])\n update_messages_list = [temp]\n observer_list = mongo_data['observer_list']\n self.context = {'username': username,\n 'observer_list': observer_list,\n 'update_messages_list': update_messages_list,\n 'len_update_messages_list': len_update_messages_list}\n return render(request, self.template_name, self.context)\n\n# Simple Factory Pattern Starts\nclass Algorithm(View):\n\n def get(self, request):\n pass\n\n def post(self, request):\n pass\n\n\nclass Classification(Algorithm):\n\n template_name = 'user_classifier/classification.html'\n message = \"\"\n submit_button = None\n\n def get(self, request):\n\n data = mdb.find(db_data, \"KNN\")\n context = {'algo_desc': data['algo_desc'], 'ds_desc': data['ds_desc'],\n 'training_features': data['training_features']}\n\n return render(request, self.template_name, context)\n\n def post(self, request):\n\n data = mdb.find(db_data, \"KNN\")\n graph_image = data['graph_image']\n if data['upload_method'] == 'pkl':\n classifier = pickle.loads(pickle.loads(data['pkl_data']).read())\n else:\n classifier = pickle.loads(data['pkl_data'])\n if 'submit' in request.POST:\n self.submit_button = request.POST.get(\"submit\")\n output_message = data['label_notes']\n user_inputs = [np.array(request.POST.getlist('user_inputs')).astype(np.float64)]\n sc = pickle.loads(data['scaling_obj'])\n\n try:\n user_inputs = sc.transform(user_inputs)\n preds = classifier.predict(user_inputs)\n self.message = output_message[str(preds[0])]\n if data['upload_method'] == 'csv':\n accuracy = data['testing_accuracy']\n f1_score = data['f1_score']\n extra = \" (\" + str(accuracy) + \"% accuracy and \" + str(f1_score) + \"% F1-Score)\"\n self.message = self.message + extra\n except:\n self.message = \"Unexpected error while predicting the output\"\n\n context = {'algo_desc': data['algo_desc'], 'ds_desc': data['ds_desc'],\n 'training_features': data['training_features'], 'graph_image': graph_image,\n 'message': self.message, 'submitbutton': self.submit_button}\n\n return render(request, self.template_name, context)\n\n\nclass Regression(Algorithm):\n\n template_name = 'user_classifier/regression.html'\n message = \"\"\n submit_button = None\n\n def get(self, request):\n\n data = mdb.find(db_data, \"MLR\")\n context = {'algo_desc': data['algo_desc'], 'ds_desc': data['ds_desc'],\n 'training_features': data['training_features']}\n\n return render(request, self.template_name, context)\n\n def post(self, request):\n\n data = mdb.find(db_data, \"MLR\")\n graph_image = data['graph_image']\n if data['upload_method'] == 'pkl':\n regressor = pickle.loads(pickle.loads(data['pkl_data']).read())\n else:\n regressor = pickle.loads(data['pkl_data'])\n if 'submit' in request.POST:\n self.submit_button = request.POST.get(\"submit\")\n user_inputs = [np.array(request.POST.getlist('user_inputs')).astype(np.float64)]\n sc = pickle.loads(data['scaling_obj'])\n\n try:\n user_inputs = sc.transform(user_inputs)\n preds = regressor.predict(user_inputs)\n self.message = \"The predicted profit of the startup is \" + str(round(preds[0], 2))\n if data['upload_method'] == 'csv':\n rmse = data['rmse']\n extra = \" (With \" + str(rmse) + \" Root Mean-Squared Error)\"\n self.message = self.message + extra\n except:\n self.message = \"Unexpected error while predicting the output\"\n\n context = {'algo_desc': data['algo_desc'], 'ds_desc': data['ds_desc'],\n 'training_features': data['training_features'], 'graph_image': graph_image,\n 'message': self.message, 'submitbutton': self.submit_button}\n\n return render(request, self.template_name, context)\n\n\nclass Clustering(Algorithm):\n\n template_name = 'user_classifier/clustering.html'\n message = \"\"\n submit_button = None\n\n def get(self, request):\n\n data = mdb.find(db_data, \"KM\")\n context = {'algo_desc': data['algo_desc'], 'ds_desc': data['ds_desc'],\n 'training_features': data['training_features']}\n\n return render(request, self.template_name, context)\n\n def post(self, request):\n\n data = mdb.find(db_data, \"KM\")\n graph_image = data['graph_image']\n if data['upload_method'] == 'pkl':\n classifier = pickle.loads(pickle.loads(data['pkl_data']).read())\n else:\n classifier = pickle.loads(data['pkl_data'])\n if 'submit' in request.POST:\n self.submit_button = request.POST.get(\"submit\")\n output_message = data['label_notes']\n user_inputs = np.array(request.POST.getlist('user_inputs')).astype(np.float64)\n try:\n preds = classifier.predict([user_inputs])\n self.message = output_message[str(preds[0])]\n except:\n self.message = \"Unexpected error while predicting the output\"\n\n context = {'algo_desc': data['algo_desc'], 'ds_desc': data['ds_desc'],\n 'training_features': data['training_features'], 'graph_image': graph_image,\n 'message': self.message, 'submitbutton': self.submit_button}\n\n return render(request, self.template_name, context)\n# Simple Factory Pattern Ends\n" }, { "alpha_fraction": 0.707774817943573, "alphanum_fraction": 0.707774817943573, "avg_line_length": 40.44444274902344, "blob_id": "9fb2ecb5d555c1eac1470a16e8c1cbd4ce74dd58", "content_id": "3b16e6355ffab7a2b9f73c106db11604736119ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 373, "license_type": "no_license", "max_line_length": 90, "num_lines": 9, "path": "/user_classifier/urls.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from django.urls import path\nfrom . import views\n\nurlpatterns = [\n path('', views.Home.as_view(), name='learner_home'),\n path('classification', views.Classification.as_view(), name='learner_classification'),\n path('regression', views.Regression.as_view(), name='learner_regression'),\n path('clustering', views.Clustering.as_view(), name='learner_clustering')\n]\n" }, { "alpha_fraction": 0.6237037181854248, "alphanum_fraction": 0.6237037181854248, "avg_line_length": 44, "blob_id": "3c813f419d538077b1e7eef988c920ac7b841a77", "content_id": "5a4c513de0702bd913352b3016cda1d028ce1e1b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 675, "license_type": "no_license", "max_line_length": 110, "num_lines": 15, "path": "/admin_classifier/forms.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from django import forms\n\nweights_choices = [('uniform', 'uniform'),\n ('distance', 'distance')]\nalgorithm_choices = [('auto', 'auto'),\n ('ball_tree', 'ball_tree'),\n ('kd_tree', 'kd_tree'),\n ('brute', 'brute')]\n\n\nclass InputForm(forms.Form):\n n_neighbors = forms.IntegerField(help_text=\"Enter Number of Neighbors\")\n leaf_size = forms.IntegerField(help_text=\"Enter Leaf Size\")\n weights = forms.CharField(label='Select Weights Type', widget=forms.Select(choices=weights_choices))\n algorithm = forms.CharField(label='Select Algorithm Type', widget=forms.Select(choices=algorithm_choices))\n" }, { "alpha_fraction": 0.7078313231468201, "alphanum_fraction": 0.7198795080184937, "avg_line_length": 40.5, "blob_id": "47ed516c651326c0253e6c0179a549b913dd3e44", "content_id": "2bef05c2238c28363137f4c8da9549863dc1862a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 332, "license_type": "no_license", "max_line_length": 115, "num_lines": 8, "path": "/LearnML Files/Temp Files/p2.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from pymongo import MongoClient\n\nclient = MongoClient(\"mongodb+srv://user_1:[email protected]/<dbname>?retryWrites=true&w=majority\")\ndb = client.get_database('learnml_db')\ndb_data = db.algorithms\n\nmongo_data = {\"update_message_list\": [\"Welcome To Learn ML\"]}\ndb_data.update_one({'name': 'OP'}, {'$set': mongo_data})\n" }, { "alpha_fraction": 0.6677471399307251, "alphanum_fraction": 0.67423015832901, "avg_line_length": 27.045454025268555, "blob_id": "544a040412c895b7f33bc0b316a99a62c23566e3", "content_id": "38a9328b50c93ad6543a23213430c697e09e7267", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 617, "license_type": "no_license", "max_line_length": 119, "num_lines": 22, "path": "/admin_classifier/mongodb.py", "repo_name": "waliamehak/LearnML", "src_encoding": "UTF-8", "text": "from pymongo import MongoClient\n\n\ndef access():\n client = MongoClient(\"mongodb+srv://user_1:[email protected]/<dbname>?retryWrites=true&w=majority\")\n db = client.get_database('learnml_db')\n db_data = db.algorithms\n return db_data\n\n\ndef update(db_data, algo_name, update_data, success_message, error_message):\n try:\n db_data.update_one({'name': algo_name}, {'$set': update_data})\n update_message = success_message\n except:\n update_message = error_message\n\n return update_message\n\n\ndef find(db_data, algo_name):\n return db_data.find_one({'name': algo_name})\n" } ]	11
thechipsweredown/tensorflow-basic	https://github.com/thechipsweredown/tensorflow-basic	a2e27145de58341d4fd8c4ca4bc7cde99f55ffc5	c8a538579cdb352d732063158ca8ca0e8152c2d1	2cfec64ad6b19d7153376895b772bb5113b00867	refs/heads/master	2021-06-19T07:34:19.815795	2017-04-16T12:03:28	2017-04-16T12:03:28	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5241215229034424, "alphanum_fraction": 0.6128647923469543, "avg_line_length": 42.0512809753418, "blob_id": "23f7fd2988da3dc07bf83ec275c912426a4d51a0", "content_id": "786ea71159b75cba6cc9ffe966b4523b4986fcd7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1679, "license_type": "no_license", "max_line_length": 129, "num_lines": 39, "path": "/linear.py", "repo_name": "thechipsweredown/tensorflow-basic", "src_encoding": "UTF-8", "text": "from __future__ import print_function\nimport tensorflow as tf\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\nX_train = np.asarray([1.47012, 1.50210, 1.53320, 1.5810, 1.6310, 1.6501, 1.6801, 1.7020, 1.7301, 1.7502, 1.7802, 1.8003, 1.8303])\nY_train = np.asarray([ 49.03, 50.03, 51.01, 54.03, 58.02, 59.03, 60.01, 62.03, 63.03, 64.03, 66.03, 67.30, 68.30])\nd = X_train.shape[0]\n\nrandom = np.random\nlearning_rate = 0.008\ndisplay_step = 100\nX = tf.placeholder(\"float\")\nY = tf.placeholder(\"float\")\nw= tf.Variable(random.randn())\nb = tf.Variable(random.randn())\nmodel = tf.add(tf.multiply(X, w), b) # Linear model\nloss = tf.reduce_sum(tf.pow(model-Y, 2))/(2d) #squared error\noptimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(loss) # Gradient descent\ninit = tf.global_variables_initializer()\nwith tf.Session() as sess:\n sess.run(init)\n for i in range(100000):\n for (x, y) in zip(X_train, Y_train):\n sess.run(optimizer, feed_dict={X: x, Y: y})\n if (i+1) % display_step == 0:\n c = sess.run(loss, feed_dict={X: X_train, Y:Y_train})\n print(\"Epoch:\", '%04d' % (i+1), \"loss=\", \"{:.8f}\".format(c), \\\n \"w=\", sess.run(w), \"b=\", sess.run(b))\n \n training_cost = sess.run(loss, feed_dict={X: X_train, Y: Y_train})\n print(\"Training loss=\", training_loss, \"w=\", sess.run(w), \"b=\", sess.run(b), '\\n')\n y_test = 1.55sess.run(w) + sess.run(b)\n print(\"Predict weight of person with height 1.55m: %.2f (kg)\" %(y_test))\n plt.plot(X_train, Y_train, 'ro', label='Original data')\n plt.plot(X_train, sess.run(w) * X_train + sess.run(b), label='Fitted line')\n plt.legend()\n plt.show()\n" }, { "alpha_fraction": 0.6976190209388733, "alphanum_fraction": 0.7404761910438538, "avg_line_length": 69.16666412353516, "blob_id": "148aea5ddb007add2e9150a5b674d9a91947290d", "content_id": "e91b0a2c34e9413476fe98c56e3b8b79e93528cf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 509, "license_type": "no_license", "max_line_length": 270, "num_lines": 6, "path": "/readme.md", "repo_name": "thechipsweredown/tensorflow-basic", "src_encoding": "UTF-8", "text": "#Linear regression\nỞ bài này e có dựa vào VD trên blog machine learning cơ bản để làm nhưng e dùng tensorflow, đó là mối quan hệ tuyến tính của chiều cao với cân nặng, mặc dù thực ra là ko có cái mqh này, cái chương trình sau 100000 epochs thì cũng ra được giá trị lỗi chấp nhận đc(0,14).\nDự đoán 1.55m là 53,14kg (trên trang machine learning cơ bản nó ra 52, tại e có sửa số liệu đi một tí) :D\n\n\n![Screenshot](/hi.png)" }, { "alpha_fraction": 0.5909952521324158, "alphanum_fraction": 0.620853066444397, "avg_line_length": 29.042856216430664, "blob_id": "832701662554d0a6d2155252e87de0e0d3a21079", "content_id": "2345b3c7857a65a53f5df5415901ce53aea13e43", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2110, "license_type": "no_license", "max_line_length": 86, "num_lines": 70, "path": "/3layerNN.py", "repo_name": "thechipsweredown/tensorflow-basic", "src_encoding": "UTF-8", "text": "from __future__ import print_function\nfrom tensorflow.examples.tutorials.mnist import input_data\nimport tensorflow as tf\n\nmnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\n\nbatch_size = 100\ndisplay_step = 1\n\nn_hidden_1 = 256 # 1st layer \nn_hidden_2 = 256 # 2nd layer \nn_input = 784 # MNIST data input (shape: 28*28)\nn_classes = 10 # 10 classes\n\n\nx = tf.placeholder(\"float\", [None, n_input])\ny = tf.placeholder(\"float\", [None, n_classes])\n\n# w & b object\nw={\n 'h1' : tf.Variable(tf.random_normal([n_input,n_hidden_1])),\n 'h2' : tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),\n 'out' : tf.Variable(tf.random_normal([n_hidden_2,n_classes]))\n} \nb={\n 'b1' : tf.Variable(tf.random_normal([n_hidden_1])),\n 'b2' : tf.Variable(tf.random_normal([n_hidden_2])),\n 'out' : tf.Variable(tf.random_normal([n_classes]))\n} \n\n# define model\ndef NNmodel(x,w,b):\n #layer1\n l1 = tf.add(tf.matmul(x, w['h1']),b['b1'])\n l1 = tf.nn.relu(l1)\n #layer2\n l2 = tf.add(tf.matmul(l1,w['h2']),b['b2'])\n l2 = tf.nn.relu(l2)\n #output\n out = tf.matmul(l2,w['out']) + b['out']\n return out\n\n#construct model\n\nmodel = NNmodel(x,w,b)\n\n#Loss\nloss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=model, labels=y))\n\n#Optimizer\noptimizer = tf.train.AdamOptimizer(learning_rate=0.001).minimize(loss)\n\n#Init the variable\ninit = tf.global_variables_initializer()\n\nwith tf.Session() as sess:\n sess.run(init)\n #training\n for i in range(20):\n avg_loss = 0\n total_batch = int(mnist.train.num_examples/batch_size)\n for j in range(total_batch):\n x_batch, y_batch = mnist.train.next_batch(batch_size)\n _,c = sess.run([optimizer,loss],feed_dict={x : x_batch, y: y_batch})\n avg_loss += c/total_batch\n if(i % display_step==0):\n print (\"Epoch: \",'%0.4d'%(i+1), \"loss =\",\"{:.8f}\".format(avg_loss))\n pred = tf.equal(tf.argmax(model,1), tf.arg_max(y,1))\n accuracy = tf.reduce_mean(tf.cast(pred,\"float\"))\n print (\"Accuracy: \", accuracy.eval({x: mnist.test.images, y : mnist.test.labels})) " } ]	3
Taher-Dohadwala/SoftwareEngineering1	https://github.com/Taher-Dohadwala/SoftwareEngineering1	4cd0a98687c491d572b2440c48325052b4c45869	73373fc8e8d47d86db04a42149e23d0d5c4f617e	75d43b9e86c100d6c27c2298f998449417011e55	refs/heads/master	2020-06-26T05:03:58.830961	2019-07-29T23:55:14	2019-07-29T23:55:14	199,541,102	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5008121132850647, "alphanum_fraction": 0.507038414478302, "avg_line_length": 30.29660987854004, "blob_id": "4447aec27f4973f0425a6efc46f416cf29a3c7e7", "content_id": "8aba16e3d2f2e1c49b59a9a40d9a8c08517f92be", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 3694, "license_type": "no_license", "max_line_length": 105, "num_lines": 118, "path": "/Chapter-6/labs/MagicSquare.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\npublic class MagicSquare\n{\n private int magicNum = 0;\n private int [][]setArray;\n private boolean testRow;\n private boolean testCol;\n private boolean testDiag;\n private String why;\n public MagicSquare(int [][] array)\n {\n //adds up the first row of the square to create a magic number\n for (int row = 0; row == 0;row+=1){\n for (int col = 0; col < array[row].length; col++){\n magicNum += array[row][col];\n }\n }\n }\n\n public void setArray(int [][]array){\n this.setArray = array;\n }\n // returns magic number\n public int getMagicNum(){\n return magicNum;\n }\n \n \n public void addRow(int[][]array){ \n int total = 0;\n //adds up each row, then adds all the rows together\n for (int row = 0;row < array.length;row++){\n for (int col = 0; col < array[row].length;col++){\n total += array[row][col];\n }\n }\n //dividing by the number of rows in the array checks to see if the number matches the magicNum\n if ((total/array.length) == magicNum){\n System.out.println(\"Row check: TRUE\");\n testRow = true;\n }else{\n why = \"Row doesn't add up to \";\n testRow =false;\n }\n }\n \n public void addCol(int[][] array){\n int total = 0;\n //adds up the columns, then adds the columns together\n for (int row = 0; row < array.length;row++){\n for (int col = 0; col < array[row].length; col++){\n total += array[col][row];\n }\n }\n //dividing by the number of elements in a column checks to see if the number matches the magicNum\n if ((total/array[0].length)== magicNum){\n System.out.println(\"Column check: TRUE\");\n testCol = true;\n }else{\n testCol = false;\n why = \"Column doesn't add up to \";\n }\n \n \n }\n \n public void addDiag(int array[][]){\n int total = 0;\n int total2 =0;\n //adds up the diagonal from top right the bottom right\n for (int row = 0; row < array.length;row++){\n total+=array[row][row]; \n }\n //adds up the diagonal from bottom left to top right\n for (int row = array.length-1, col =0;row >= 0;row--, col++){\n total2 += array[row][col];\n }\n // checks to see if the totals of the diagonals match the magicNum\n if ((total)==(total2)){\n System.out.println(\"Diagonal check: TRUE\");\n testDiag = true;\n }\n else{\n testDiag = false;\n why = \"Diagonal doesn't add up to \";\n }\n }\n \n public void isMagic(MagicSquare obj, int array[][]){\n //runs each test\n System.out.println(\"Magic num:\" + magicNum);\n obj.addDiag(array);\n obj.addCol(array);\n obj.addRow(array);\n\n //checks to see if all test are true, and if all are true then the square is a magic square\n if (testCol == true && testRow == true && testDiag == true){\n System.out.println(\"This is a magic square!!!\"+\"\\n\");\n }else{\n System.out.println(why+magicNum);\n System.out.println(\"This is NOT a magic square!!!\"+\"\\n\");\n \n }\n \n \n }\n \n public String toString(){\n String data = \"\";\n \n for (int row =0; row < setArray.length;row++){\n for(int col = 0; col < setArray[row].length;col++){\n data+= setArray[row][col];\n }\n System.out.println();\n }\n return data;\n }\n}\n" }, { "alpha_fraction": 0.5597222447395325, "alphanum_fraction": 0.5687500238418579, "avg_line_length": 20.81818199157715, "blob_id": "5cd9589511a3b89d95d2f942d821c9462b92412c", "content_id": "2977d5ff086689eeff8d34ea6d596e95068d4c6d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1440, "license_type": "no_license", "max_line_length": 86, "num_lines": 66, "path": "/FinalProject/FinalProjectCode/Fireball.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport java.io.;\nimport javax.imageio.ImageIO;\nimport javax.swing.;\nimport java.awt.image.BufferedImage;\nimport java.awt.Graphics;\nimport java.awt.Graphics2D;\nimport java.io.File;\nimport java.io.IOException;\nimport javax.swing.JFrame;\nimport javax.swing.JPanel;\n\n/\n Write a description of class Fireball here.\n * \n * @author (your name) \n * @version (a version number or a date)\n /\npublic class Fireball extends JComponent\n{\n /* description of instance variable x (add comment for each instance variable) /\n private int x;\n private int y;\n \n private BufferedImage fireball;\n /\n Default constructor for objects of class Fireball\n /\n public Fireball(int x, int y)\n {\n this.x = x;\n this.y = y;\n \n try {\n fireball = ImageIO.read(new File(\"Images/Fireball.png\"));\n }\n catch (IOException e) {\n \n }\n }\n \n public int getX() {\n return x;\n }\n \n public int getY() {\n return y;\n }\n \n @Override\n protected void paintComponent(Graphics g) {\n super.paintComponent(g);\n g.drawImage(fireball, x, y, 300, 50, this);\n }\n \n public void attack() throws InterruptedException{\n for (int i = 0; i < 30; i++) {\n x -= 2;\n repaint();\n Thread.sleep(1);\n }\n repaint();\n Thread.sleep(10);\n \n }\n}\n" }, { "alpha_fraction": 0.5703125, "alphanum_fraction": 0.582812488079071, "avg_line_length": 19, "blob_id": "b3d5791ea45fa846318b9d8af0799271a7d816b4", "content_id": "62f9d363f54ecd7002b93fb10a02b38b08eb442f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 640, "license_type": "no_license", "max_line_length": 48, "num_lines": 32, "path": "/chapter16intro-Taher-Dohadwala/Maze/mazeTest.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import static org.junit.Assert.;\nimport org.junit.After;\nimport org.junit.Before;\nimport org.junit.Test;\nimport java.util.;\npublic class mazeTest\n{\n public static void main(String args[]){\n //create maze\n //load maze\n //.getRow(), .getCol() .getType()\n //getNeighbor();\n // .getStart() .getFinish()\n // toString\n Maze maze = new Maze();\n \n System.out.println(maze.loadMaze(\"maze-1\"));\n\n Square[][] m = maze.getMaze();\n \n m[0][1] = new Square(0,1,0,\".\");\n System.out.println(m[0][1].toString());\n System.out.println(\"\\n\\n\");\n System.out.println(maze.toString());\n\n \n\n \n \n }\n \n}\n" }, { "alpha_fraction": 0.5444839596748352, "alphanum_fraction": 0.5800711512565613, "avg_line_length": 20.075000762939453, "blob_id": "5b4e1823311792a047bdb0754b44cf8bae0ec593", "content_id": "f8d531a1413aa8a0c66c410f9657f6c8bc96edee", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 843, "license_type": "no_license", "max_line_length": 68, "num_lines": 40, "path": "/software-engineering-challenge-Taher-Dohadwala/GraphicsRepo/CityProject/Sun.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport javax.swing.;\npublic class Sun extends JComponent\n{\n Graphics2D g2;\n int trigger = 0;\n int xm = 0;\n int counter = 1;\n public void paintComponent(Graphics g){\n g2 = (Graphics2D)g;\n // creates a sun or moon\n if (trigger%2 == 0){\n //Sun\n g2.setColor(Color.YELLOW);\n g2.fillOval(xm,5,50,50);\n }else{\n //Moon\n g2.setColor(Color.WHITE);\n g2.fillOval(xm,5,50,50);\n }\n \n }\n \n //animation for moving the sun or moon from left to right\n public void nextFrame(Background obj)throws InterruptedException{ \n xm += 5;\n if (xm >= 1500){\n obj.nightsky();\n trigger += 1;\n xm = 0;\n counter ++;\n }\n repaint();\n }\n \n //used in Buildings class to create the night time light show\n public int getCount(){\n return counter;\n }\n}\n" }, { "alpha_fraction": 0.516687273979187, "alphanum_fraction": 0.53399258852005, "avg_line_length": 22.36231803894043, "blob_id": "9d63dc45105a33dfba4c77fc8ea2f19682886002", "content_id": "3eee1e6490fdbf954bfa00cf3d79834604036720", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1618, "license_type": "no_license", "max_line_length": 154, "num_lines": 69, "path": "/AI-Project/Project Testing/weather_api_test.py", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "#Requesting a weather api to naperville\n\nclass test(object):\n import requests,json\n\n\n response = requests.get(\"http://api.openweathermap.org/data/2.5/weather?q=Naperville,us&units=imperial&APPID=714964c165954619971a23be696deb1a\").json()\n\n \n print \"Today \"\n print response[\"weather\"][0][\"description\"]+\" currently\"\n print \"It's \"\n print response[\"main\"][\"temp\"]\n print \"the high today was forcast as \"\n print response[\"main\"][\"temp_max\"]\n\n command = \"What is the weather\"\n if \"in\" in command:\n print command[command.find(\"in\")+3:]\n else:\n print \"Naperville\"\n \n # ERROR: list indices must be integers, not str\n \n\n## key_words = [\"weather\",\"what is\",\"end\",\"bye\",\"hi\"]\n##\n## sentence = \"good bye\"\n\n## for x in range(len(key_words)):\n## if key_words[x] in sentence:\n## key_word = key_words[x]\n##\n## #print key_word\n##\n## def listen(self):\n## self.save_audio = \"tell me the weather\"\n##\n##\n## def what_is(self):\n## print \"what is function\"\n## \n##\n## def weather(self):\n## print \"weather function\"\n## def hi():\n## print \"hi\"\n##\n## def bye(self):\n## print \"bye\"\n## \n## def get_save(self):\n## print self.save_audio\n##\n## commands = {\"weather\":what_is,\n## \"what is\":weather,\n## \"hi\":hi,\n## \"bye\":bye}\n## \n## \n##\n## for x in commands:\n## if key_word in sentence:\n## print commands.get(key_word)\n## break\n##\n##tester = test()\n##tester.listen()\n##tester.get_save()\n\n \n" }, { "alpha_fraction": 0.5446954965591431, "alphanum_fraction": 0.5589390993118286, "avg_line_length": 19.545454025268555, "blob_id": "3bbc859b51d884018617544ebdd45b65e8115755", "content_id": "fe36a9752e7c9ff53c8e50d261adde8a7ab1f9d3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 2036, "license_type": "no_license", "max_line_length": 74, "num_lines": 99, "path": "/FinalProject/FinalProjectCode/InfernoRifleBestie.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\nimport java.awt.;\nimport java.io.;\nimport javax.imageio.ImageIO;\nimport javax.swing.;\nimport java.awt.image.BufferedImage;\nimport java.awt.Graphics;\nimport java.awt.Graphics2D;\nimport java.io.File;\nimport java.io.IOException;\nimport javax.swing.JFrame;\nimport javax.swing.JPanel;\nimport java.awt.geom.Line2D;\n//import javax.swing.UIManager;\n//import javax.swing.UnsupportedLookAndFeelException;\n\n/*\n Write a description of class InfernoRifleBestie here.\n * \n * @author (your name) \n * @version (a version number or a date)\n /\npublic class InfernoRifleBestie extends JComponent\n{\n // instance variables - replace the example below with your own\n Graphics2D g2;\n \n private int x;\n private int y;\n \n private BufferedImage img;\n private BufferedImage rocketdown;\n\n \n private int hp;\n private int atk;\n \n \n /\n Constructor for objects of class InfernoRifleBestie\n /\n public InfernoRifleBestie(int x, int y)\n {\n hp = 10000;\n atk = 5000;\n \n this.x = x;\n this.y = y;\n \n //the hero\n try {\n img = ImageIO.read(new File(\"Images/InfernoRifleBestie.png\"));\n }\n catch (IOException e) {\n \n }\n \n \n \n }\n \n @Override\n protected void paintComponent(Graphics g) {\n super.paintComponent(g);\n g.drawImage(img, x, y, 200, 119, this);\n \n }\n\n public int getX() {\n return x;\n }\n\n public int getY() {\n return y;\n }\n\n public BufferedImage getImage() {\n return img;\n }\n \n public void moveLeft(int EnemyX, int EnemyY) {\n x += (int)((EnemyX - x) / 70);\n y += (int)((EnemyY - y) / 30) - 4;\n \n repaint();\n }\n \n public void moveRight(int EnemyX, int EnemyY) {\n x -= (int)((EnemyX - x) / 70);\n y -= (int)((EnemyY - y) / 30) - 4;\n \n repaint();\n }\n \n public void setHealth(int hpCount) {\n hp += hpCount;\n }\n \n \n}\n\n" }, { "alpha_fraction": 0.526770293712616, "alphanum_fraction": 0.529879093170166, "avg_line_length": 18.42953109741211, "blob_id": "f5d9fa4b091b9740afd16782a860a2f8a96ef2c0", "content_id": "1c28b51159736781386e69b01c7eaa1d35ff5012", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 2895, "license_type": "no_license", "max_line_length": 80, "num_lines": 149, "path": "/chapter6-repo-2016-mgorczyca12/Repo for Ch6/ArrayList Purse and Question Lab/Coin_Purse_Client.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.util.;\npublic class Coin_Purse_Client\n{\n public static void main (String args[])\n {\n\n\t\tScanner input = new Scanner(System.in);\n\n\t\tPurse wallet = new Purse();\n\n\t\tCoin P = Coin.Penny;\n\t\tCoin N = Coin.Nickle;\n\t\tCoin D = Coin.Dime;\n\t\tCoin Q = Coin.Quarter;\n\n\t\tString choice = \"\";\n\t\tString coin = \"\";\n\t\tchar flag = 'y';\n\n\t\twhile(flag != 'n')\n\t\t{\n\t\t\tSystem.out.println(\"Press enter\");\n\t\t\tString junk = input.nextLine();\n\t\t\tSystem.out.println(\"A-- Add a Coin\\nR-- Remove a Coin\\nD-- Display Purse\\n\");\n\t\t\tchoice = input.nextLine();\n\n\n\t\t\tif(choice.equals(\"A\"))\n\t\t\t{\n\n\t\t\t\tSystem.out.print(\"What type of Coin do you want to add? (P,N,D,Q):\");\n\t\t\t\tcoin = input.nextLine();\n\t\t\t\tif (coin.equals(\"P\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to add?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.add(P.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\telse if (coin.equals(\"N\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to add?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.add(N.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\telse if(coin.equals(\"D\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to add?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.add(D.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\telse if (coin.equals(\"Q\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to add?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.add(Q.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t}\n\n\t\t\tif(choice.equals(\"R\"))\n\t\t\t{\n\n\t\t\t\tSystem.out.print(\"What type of Coin do you want to remove? (P,N,D,Q):\");\n\t\t\t\tcoin = input.nextLine();\n\t\t\t\tif (coin.equals(\"P\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to remove?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.remove(P.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\telse if (coin.equals(\"N\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to remove?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.remove(N.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\telse if(coin.equals(\"D\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to remove?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.remove(D.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\telse if (coin.equals(\"Q\"))\n\t\t\t\t{\n\t\t\t\t\tint count;\n\t\t\t\t\tSystem.out.println(\"How many do you want to remove?\");\n\t\t\t\t\tcount = input.nextInt();\n\n\t\t\t\t\tfor(int i = 0; i < count; i++)\n\t\t\t\t\t{\n\t\t\t\t\t\twallet.remove(Q.getOption());\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t}\n\n\t\t\tif(choice.equals(\"D\"))\n\t\t\t{\n\n\t\t\t\tSystem.out.println(wallet.toString());\n\n\t\t\t}\n\t\t\tSystem.out.println(\"Anything else (y or n)\");\n\t\t\tflag = input.next().charAt(0);\n\t\t}\n\n }//end of main\n}//end of class\n" }, { "alpha_fraction": 0.5181818008422852, "alphanum_fraction": 0.5504132509231567, "avg_line_length": 22.72549057006836, "blob_id": "844e3a4f0d52a2c3c2184201187d704bbab5e77a", "content_id": "cc186a9e088854c18bb90eb5d98edfa812fefe6b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1210, "license_type": "no_license", "max_line_length": 69, "num_lines": 51, "path": "/chapter5-repo-2016-Taher-Dohadwala/2D Graphics notes/RectangleViewer.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import javax.swing.JFrame;\nimport java.awt.;\npublic class RectangleViewer //implements Runnable\n{\n final static int ANIMATION_TIME = 60;\n public static void main(String[] args)throws InterruptedException \n {\n JFrame frame = new JFrame();\n\n frame.setSize(1000,1000);\n frame.setTitle(\"Two rectangles\");\n frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);\n \n \n RectangleComponent c1 = new RectangleComponent();\n frame.add(c1);\n frame.setVisible(true);\n \n RectangleComponent c2 = new RectangleComponent(50,200,200,250);\n frame.add(c2);\n frame.setVisible(true);\n \n /\n FaceComponent c3 = new FaceComponent();\n frame.add(c3);\n frame.setVisible(true);\n /\n //animate the frame\n /\n for (int sec = 0; sec < 60;sec++){\n c1.nextFrame(sec);\n c2.nextFrame(sec);\n Thread.sleep(17);\n }\n /\n //animation using threads\n \n }\n /\n public void run(){\n while(true){\n c1.nextFrame(); \n repaint();\n try{\n Thread.sleep(1000);\n }catch(InterruptedException e){}\n }\n }\n /\n \n}\n" }, { "alpha_fraction": 0.5400763154029846, "alphanum_fraction": 0.5419847369194031, "avg_line_length": 18.370370864868164, "blob_id": "57f995c23843200fccac824eb1e71e4af3e6683d", "content_id": "f896ddb47f64fb41152beaabb72d664aeabf85e3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 524, "license_type": "no_license", "max_line_length": 54, "num_lines": 27, "path": "/Chapter-7/Notes/Chapter 7 notes/Snake.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\npublic class Snake extends Reptile\n{\n private int snake_length;\n \n public Snake(int length){\n super(0);\n snake_length = length;\n }\n \n public Snake(int length,String type){\n super(type);\n snake_length = length;\n \n }\n public int getLength(){\n return snake_length;\n }\n \n public String move(){\n return \"Slither\";\n }\n \n public String toString(){\n return super.toString()+\n \"\\nI have \"+snake_length+ \" inches of length\";\n }\n}\n" }, { "alpha_fraction": 0.4010624289512634, "alphanum_fraction": 0.4302788972854614, "avg_line_length": 20.514286041259766, "blob_id": "a1882b20f6da369e86197b4c45c4ac8fa967bef7", "content_id": "c3b5c16fa6ac874710020fc855e3a28b643733a2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 753, "license_type": "no_license", "max_line_length": 53, "num_lines": 35, "path": "/ch7shaperepo-Taher-Dohadwala/ShapeRepo/Wheel.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import TurtleGraphics.Pen;\nclass Wheel extends Circle\n{\n private int spoke;\n public Wheel(int x, int y, int r,int num)\n {\n super(r,x,y);\n spoke = num; \n }\n\n public void draw(Pen p){\n double interval = (360.0/spoke);\n double side = 2.0 Math.PI * radius / 120.0;\n p.up();\n p.move (xPos + radius, yPos - side / 120.0);\n p.setDirection (90);\n p.down();\n for (int i = 0; i<120; i++)\n {\n p.move (side);\n p.turn(3);\n }\n \n p.up();\n p.move(xPos,yPos);\n p.down();\n for (int i = 1; i <= spoke;i++){\n p.turn(interval);\n p.move(radius);\n p.move(-radius);\n }\n \n }\n\n}\n" }, { "alpha_fraction": 0.6000000238418579, "alphanum_fraction": 0.6000000238418579, "avg_line_length": 17.3157901763916, "blob_id": "f20ebabc89876b9f91bde7700b22e9660c314444", "content_id": "2539f4b69f8f92bf14da6d3ceafe5c169c28903f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 695, "license_type": "no_license", "max_line_length": 56, "num_lines": 38, "path": "/ch7shaperepo-Taher-Dohadwala/ShapeRepo/Shape.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import TurtleGraphics.Pen;\n\npublic abstract class Shape\n{\n protected double xPos, yPos;\n\n public Shape (double x, double y)\n {\n xPos = x;\n yPos = y;\n\n }\n\n // you must write these methods here\n public double getXpos()\n {\n return xPos;\n }\n public double getYpos()\n {\n return yPos;\n }\n \n public abstract void move(double xLoc, double yLoc);\n \n public abstract void stretchby (double factor);\n\n public abstract double getArea();\n\n public abstract void draw (Pen p);\n\n //toString should display xpos, ypos\n public String toString()\n {\n return \"X position:\"+xPos+\"\\nY position\"+yPos;\n }\n\n}//end of Shape" }, { "alpha_fraction": 0.5355764031410217, "alphanum_fraction": 0.5444015264511108, "avg_line_length": 20.58333396911621, "blob_id": "5c6f63eb6aa4bc1dfe75951a4cf40cb5fdce29cb", "content_id": "fd3b1866aa0a4a248295d0687e1bb5da00cdc44a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1813, "license_type": "no_license", "max_line_length": 86, "num_lines": 84, "path": "/FinalProject/FinalProjectCode/BestieBlast.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport java.io.;\nimport javax.imageio.ImageIO;\nimport javax.swing.;\nimport java.awt.image.BufferedImage;\nimport java.awt.Graphics;\nimport java.awt.Graphics2D;\nimport java.io.File;\nimport java.io.IOException;\nimport javax.swing.JFrame;\nimport javax.swing.JPanel;\n\n/\n Write a description of class LaserBlast here.\n * \n * @author (your name) \n * @version (a version number or a date)\n /\npublic class BestieBlast extends JComponent\n{\n /* description of instance variable x (add comment for each instance variable) /\n private int x;\n private int y;\n private int width;\n private int height;\n \n private int origX;\n private int origY;\n private int origWidth;\n private int origHeight;\n \n private BufferedImage img;\n /\n Default constructor for objects of class LaserBlast\n /\n public BestieBlast(int x, int y)\n {\n width = 800;\n height = 300;\n \n this.x = x - (width / 2);\n this.y = y;\n origX = x - (width / 2);\n origY = y;\n \n try {\n img = ImageIO.read(new File(\"Images/incineration.png\"));\n }\n catch (IOException e) {\n \n }\n }\n\n public int getX() {\n return x;\n }\n \n public int getY() {\n return y;\n }\n \n @Override\n protected void paintComponent(Graphics g) {\n super.paintComponent(g);\n g.drawImage(img, x, y, width, height, this);\n\n }\n \n public void adjustSize() throws InterruptedException{\n for (int i = 0; i < 30; i++) {\n if (height > 0) {\n height -= 2;\n y += 1;\n repaint();\n Thread.sleep(1);\n }\n }\n repaint();\n }\n \n public void reset() {\n \n }\n}\n" }, { "alpha_fraction": 0.5110884308815002, "alphanum_fraction": 0.5243436098098755, "avg_line_length": 32.410255432128906, "blob_id": "0e6afa9d733d12cbcdc2c2878514dc3a2cc18be7", "content_id": "d955a5dc80dbca2d1b34d68248f54005ba9cb128", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3923, "license_type": "no_license", "max_line_length": 145, "num_lines": 117, "path": "/AI-Project/Project Testing/speech_program3.0.py", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "#Taher Dohadwala\n\n#imports\nimport speech_recognition as sr\nimport pyaudio,os,time\nfrom gtts import gTTS\nimport requests,json\nimport wolframalpha\n#------------------------------------------------------------------\n# Rules for adding new commands:\n# -Create a new method in AI Functions\n# -Add the keyword to the variable key_word in the __init__\n# -Add any api keys to the __init__\n# -Add the keyword and method to the commands dictionary\n\n\n#------------------------------------------------------\n#Things to do:\n# 1. use espeak as the voice\n# 2. add description from the weather api\n# 3. add a run() to constantly run the program waiting for keyword (NAME)\n# 4. use amazon cloud for what is command\n# 5. add spotify api\n# 6. add various other command...\nclass speech_program():\n \n\n #-----------------------------------------------------------------\n #init()\n def __init__(self):\n self.key_words = [\"weather\",\"what is\",\"end\"]\n self.weather_key = \"APPID=714964c165954619971a23be696deb1a\"\n self.wolfram_key = \"8A86L7-EQW9P7T464\"\n \n #--------------------------------------------------------------------\n #AI functions-- 1 function = 1 command\n\n def weather(self):\n if \"in\" in self.save_audio:\n self.location = self.save_audio[self.save_audio.find(\"in\")+3:]\n else:\n self.location = \"Naperville\"\n response = requests.get(\"http://api.openweathermap.org/data/2.5/weather?q=\"+self.location+\",us&units=imperial&\"+self.weather_key).json() \n a2 = \"The Temperature in\"+self.location+\" is \"+str(response[\"main\"][\"temp\"])+\" degrees fahrenheit\"\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n\n\n def what_is(self):\n client = wolframalpha.Client(self.wolfram_key)\n res = client.query(self.save_audio)\n a2 = self.save_audio+\" the answer is \"+str((next(res.results).text))\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n\n\n def end(self):\n tts = gTTS(text = \"System shutting down\")\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n #--------------------------------------------------------------------\n # AI brain\n def listen(self): \n with sr.Microphone() as source:\n print(\"Say something!\")\n audio = sr.Recognizer().listen(source)\n while audio == None:\n audio = sr.Recognizer().listen(source)\n\n try:\n self.save_audio = sr.Recognizer().recognize_google(audio)\n print (\"You said: \"+ self.save_audio)\n\n except sr.UnknownValueError:\n print(\"Google Speech Recognition could not understand audio\")\n speech_program.listen(self)\n\n except sr.RequestError as e:\n\n print(\"Could not request results from Google Speech Recognition service; {0}\".format(e))\n\n def find_keyword(self):\n #Checks if a key_word is in user said sentence\n for x in range(len(self.key_words)):\n if self.key_words[x] in self.save_audio:\n self.key_word = self.key_words[x]\n print (\"keyword finder worked\")\n break\n ############################# \n commands = {\"weather\":weather,\n \"what is\":what_is,\n \"end\":end}\n #############################\n \n def compute(self):\n\n # using key_word - made in find_keyword\n # matches the key_word to respective key and executes the key value(AI function)\n for x in self.commands:\n if self.key_word in self.save_audio:\n self.commands.get(self.key_word)(self)\n print (\"reached command\")\n break\n#---------------------------------------------------------------------------------------\n\n\ntester = speech_program()\n\ntester.listen()\ntester.find_keyword()\ntester.compute()\ninput\n \n \n" }, { "alpha_fraction": 0.5882353186607361, "alphanum_fraction": 0.591911792755127, "avg_line_length": 17.066667556762695, "blob_id": "78b4f3fdc345683f9cf6d82e42b954e116a5c794", "content_id": "6864bacf5d4a48a1d3952125970fd7858a93bf3c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 272, "license_type": "no_license", "max_line_length": 54, "num_lines": 15, "path": "/chapter16intro-Taher-Dohadwala/Maze/tester.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\npublic class tester\n{\n public static void main(String args[]){\n Maze maze = new Maze();\n \n maze.loadMaze(\"maze-2\");\n \n System.out.println(maze.toString());\n \n MazeSolverStack solve = new MazeSolverStack(maze);\n \n solve.getPath();\n \n }\n}\n" }, { "alpha_fraction": 0.5224117636680603, "alphanum_fraction": 0.5430384874343872, "avg_line_length": 25.26041603088379, "blob_id": "44e5bed1470f3a186929db5fa28a3943cb60aa43", "content_id": "9beb507a23e7a4338ed70a5b125e524c0376f9bf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2521, "license_type": "no_license", "max_line_length": 129, "num_lines": 96, "path": "/AI-Project/Project Testing/speech_program2.0.py", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import speech_recognition as sr\nimport pyaudio,os,time\nfrom gtts import gTTS\nimport requests,json\nimport wolframalpha\n\n#-------------------------------------------------------------------------\n#variables\nr = sr.Recognizer()\nkey_words = [\"weather\",\"what is\",\"end\"]\nweather_key = \"APPID=714964c165954619971a23be696deb1a\"\nwolfram_key = \"8A86L7-EQW9P7T464\"\n\n\n#-------------------------------------------------------------------------\ndef listen(): \n with sr.Microphone() as source:\n print(\"Say something!\")\n audio = r.listen(source)\n while audio == None:\n audio = r.listen(source)\n\n try:\n save_audio = r.recognize_google(audio)\n print \"You said: \"+ save_audio\n\n except sr.UnknownValueError:\n print(\"Google Speech Recognition could not understand audio\")\n\n except sr.RequestError as e:\n print(\"Could not request results from Google Speech Recognition service; {0}\".format(e))\n\n \n\n\ndef find_keyword(save_audio):\n for x in range(len(key_words)):\n if key_words[x] in save_audio:\n key_word = key_words[x]\n print \"keyword finder worked\"\n break\n return key_word\n\n\n\ndef compute(key_word):\n for x in commands:\n if key_word in save_audio:\n commands.get(key_word)\n break\n \n \n \n \n#--------------------------------------------------------------------------\n# Each function = 1 command\n\ndef weather():\n response = requests.get(\"http://api.openweathermap.org/data/2.5/weather?q=Naperville,us&units=imperial&\"+weather_key).json() \n a2 = \"The Temperature in Naperville is \"+str(response[\"main\"][\"temp\"])+\" degrees fahrenheit\"\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n \n\ndef what_is():\n client = wolframalpha.Client(wolfram_key)\n res = client.query(save_audio)\n a2 = save_audio+\" the answer is \"+str((next(res.results).text))\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n\ndef no_keyword():\n a2 = \"No command found, try again\"\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n\ndef end():\n a2 = \"System shutting down\"\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n \n#--------------------------------------------------------------------------\ncommands = {\"weather\":weather,\n \"what is\":what_is,\n \"end\":end}\n#listen()\n#find_keyword(listen())\ncompute(find_keyword(listen()))\n" }, { "alpha_fraction": 0.41700172424316406, "alphanum_fraction": 0.48248133063316345, "avg_line_length": 20.75, "blob_id": "b85d6cbe9fe0da3a4eb4869b35e3bce17b4db10f", "content_id": "26783507c2730f27a81745b696c4461d8bbc9815", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1741, "license_type": "no_license", "max_line_length": 48, "num_lines": 80, "path": "/software-engineering-challenge-Taher-Dohadwala/GraphicsRepo/CityProject/Buildings.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport javax.swing.;\npublic class Buildings extends JComponent\n{\n private int x;\n private int y;\n private int w;\n private int h;\n \n int C;\n int R;\n int G;\n int B;\n \n Graphics2D g2;\n Color color;\n public void paintComponent(Graphics g)\n {\n g2 = (Graphics2D)g;\n g2.setColor(color);\n \n g2.fill(building);\n \n g2.setColor(Color.YELLOW);\n \n / //TEST WINDOWS\n int add = 10;\n for (int i = 1; i <= 11; i++ ){\n g2.fillRect(x,y+add,10,10);\n g2.fillRect(x+25,y+add,10,10);\n g2.fillRect(x+50,y+add,10,10);\n g2.fillRect(x+75,y+add,10,10);\n g2.fillRect(x+100,y+add,10,10);\n g2.fillRect(x+125,y+add,10,10);\n g2.fillRect(x+150,y+add,10,10);\n add+= 20;\n }\n //\n //test window with a loop\n for (int tx = x+5; tx < w+x-15; tx+=25){\n for (int ty = y+5; ty < h+y-10; ty+=15 ){\n g2.fillRect(tx,ty,10,10);\n }\n }\n \n }\n\n \n Rectangle building;\n Rectangle window;\n public Buildings(int x){\n //building construction\n this.x = x;\n this.y =(int)(Math.random()200)+101;\n this.w =(int)(Math.random()125)+101;\n this.h = (450-y);\n building = new Rectangle(x,y,w,h);\n\n \n \n }\n \n //light show\n public void nextColor(Sun obj){\n if (obj.getCount()%2 != 0){\n //Color\n //C = (int)(Math.random()150);\n color = new Color(30,30,30);\n color.darker();\n }else{\n //Color\n R = (int)(Math.random()255);\n G = (int)(Math.random()255);\n B = (int)(Math.random()255);\n color = new Color(R,G,B);\n \n }\n }\n \n}\n\n" }, { "alpha_fraction": 0.5485893487930298, "alphanum_fraction": 0.5506792068481445, "avg_line_length": 21.186046600341797, "blob_id": "37078a9c4f4b68b00d96554e2a000c59bd1c4c6d", "content_id": "34b74487e546e7bd344bf53b4b6e0f777b2509f4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 957, "license_type": "no_license", "max_line_length": 60, "num_lines": 43, "path": "/Chapter-7/Notes/Chapter 7 notes/Reptile.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\n public abstract class Reptile extends Animal\n{\n private int numberOfLegs;\n \n // Creates a reptile with no legs\n \n public Reptile(){\n //call the default constructor of Animal\n //happens AUTOMATICALLY\n //super(); is called\n \n //super must be called first\n super(\"reptile\");\n //type = \"reptile\"; //Private data will cause error\n numberOfLegs = 0;\n \n }\n \n public Reptile(int numberOfLegs){\n super(\"reptile\");\n this.numberOfLegs = numberOfLegs;\n \n }\n \n public Reptile(String type){\n super(type);\n numberOfLegs = 0;\n }\n \n public String move(){\n return \"Crawl\";\n \n }\n \n public int getLegs(){\n return numberOfLegs;\n }\n //Returns a string representatino of this Reptile\n public String toString(){\n return super.toString()+\n \"\\nI have \"+getLegs()+ \" number of Legs\";\n }\n}\n\n" }, { "alpha_fraction": 0.5343511700630188, "alphanum_fraction": 0.5458015203475952, "avg_line_length": 20.325580596923828, "blob_id": "1020e2e58acab8c235d17a2d70106a45659f2790", "content_id": "92d49a3075eef96ad71d625842a5e9929e37e06b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1834, "license_type": "no_license", "max_line_length": 75, "num_lines": 86, "path": "/FinalProject/FinalProjectCode/Flamethrower.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport java.io.;\nimport javax.imageio.ImageIO;\nimport javax.swing.;\nimport java.awt.image.BufferedImage;\nimport java.awt.Graphics;\nimport java.awt.Graphics2D;\nimport java.io.File;\nimport java.io.IOException;\nimport javax.swing.JFrame;\nimport javax.swing.JPanel;\n\n/*\n Write a description of class RocketBurst here.\n * \n * @author (your name) \n * @version (a version number or a date)\n /\npublic class Flamethrower extends JComponent\n{\n // instance variables - replace the example below with your own\n private int x;\n private int y;\n \n private int origX;\n private int origY;\n \n private int origWidth;\n private int origHeight;\n \n private int width;\n private int height;\n \n private BufferedImage rocketleft;\n \n\n /\n Constructor for objects of class RocketBurst\n /\n public Flamethrower(int x, int y)\n {\n this.x = x;\n this.y = y;\n origX = x;\n origY = y;\n \n width = 550;\n height = 100;\n origWidth = 550;\n origHeight = 100;\n try {\n rocketleft = ImageIO.read(new File(\"Images/flamethrower.png\"));\n }\n catch (IOException e) {\n \n }\n }\n\n @Override\n protected void paintComponent(Graphics g) {\n super.paintComponent(g);\n g.drawImage(rocketleft, x, y, width, height, this);\n }\n \n public void attack() throws InterruptedException{\n for (int i = 0; i < 30; i++) {\n if (width > 0) {\n width -= 1;\n height -= 2;\n y += 1;\n repaint();\n Thread.sleep(1);\n }\n }\n\n\n \n }\n \n public void reset() {\n x = origX;\n y = origY;\n width = origWidth;\n height = origHeight;\n }\n}\n" }, { "alpha_fraction": 0.46670275926589966, "alphanum_fraction": 0.5046020746231079, "avg_line_length": 21.814815521240234, "blob_id": "57b3ad1d26015645c0ce7e1214c05fd4c78e8dce", "content_id": "fa0efda71c6acd297192b408cca542b264b672b1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1847, "license_type": "no_license", "max_line_length": 71, "num_lines": 81, "path": "/FinalProject/FinalProjectCode/ChiefPatTesting.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.util.;\nimport javax.swing.JFrame;\nimport java.awt.Color;\n/*\n Write a description of class Viewer here.\n \n @author (your name)\n * @version (a version number or a date)\n /\npublic class ChiefPatTesting\n{\n final static int ANIMATION_TIME_IN_SECONDS = 20;\n\n public static void main(String[] args)throws InterruptedException {\n JFrame frame = new JFrame();\n frame.setSize(1000, 800);\n\n frame.getContentPane().setBackground(Color.BLACK);\n frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);\n\n //new heroes\n\n\n ChiefPat c1 = new ChiefPat(390,220);\n Zap z1 = new Zap(200,0);\n frame.add(z1);\n frame.setVisible(true);\n \n frame.add(c1);\n frame.setVisible(true);\n AutonomousCotton ct1 = new AutonomousCotton(100,200);\n frame.add(ct1);\n frame.setVisible(true);\n\n //goes forward\n for( int i = 1; i < ANIMATION_TIME_IN_SECONDS; i++ )\n {\n\n c1.MoveToEnemy(0, 0);\n z1.Attack(100, 200);\n \n \n Thread.sleep(50);\n frame.setVisible(true);\n \n }\n Thread.sleep(500);\n Poison p1 = new Poison(200,0);\n frame.add(p1);\n frame.setVisible(true);\n for( int i = 1; i < ANIMATION_TIME_IN_SECONDS; i++ )\n {\n\n \n p1.Attack();\n \n \n Thread.sleep(50);\n frame.setVisible(true);\n \n }\n Thread.sleep(500);\n Heal h1 = new Heal(200,0);\n frame.add(h1);\n frame.setVisible(true);\n for( int i = 1; i < ANIMATION_TIME_IN_SECONDS; i++ )\n {\n\n \n h1.Attack();\n \n \n Thread.sleep(50);\n frame.setVisible(true);\n \n }\n\n\n\n }\n}" }, { "alpha_fraction": 0.5605345964431763, "alphanum_fraction": 0.5605345964431763, "avg_line_length": 17.434782028198242, "blob_id": "2cca5f63b1171abbbc33fc72f8bae14d9400dab6", "content_id": "c5e99847dfb786c2216a4ac05fe013395bbeda76", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1272, "license_type": "no_license", "max_line_length": 70, "num_lines": 69, "path": "/chapter16intro-Taher-Dohadwala/ch16 WritingDataStructures - Sutdent Repo/LinkedListStack.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.util.NoSuchElementException;\n\n/\n An implementation of a stack as a sequence of nodes.\n/\npublic class LinkedListStack\n{\n private Node top;\n\n /*\n Constructs an empty stack.\n /\n public LinkedListStack()\n {\n top = null;\n }\n\n /*\n Adds an element to the top of the stack.\n @param element the element to add\n /\n\n public void push(Object element){\n Node newNode = new Node();\n newNode.data = element; //reference to data into stack\n newNode.next = top; // pointing to the guy that was at the top\n top = newNode;\n }\n\n /*\n Removes the element from the top of the stack.\n @return the removed element\n /\n\n public Object pop(){\n if (top == null){\n throw new NoSuchElementException();\n }\n Object temp = top.data;\n top = top.next;\n \n return temp;\n \n }\n\n /*\n Checks whether this stack is empty.\n @return true if the stack is empty\n /\n\n public boolean empty(){\n return top == null;\n \n }\n \n public Object peek(){\n if (top == null ){\n throw new NoSuchElementException();\n }\n return top.data;\n }\n\n\n class Node\n {\n public Object data;\n public Node next;\n }\n}\n" }, { "alpha_fraction": 0.48990434408187866, "alphanum_fraction": 0.5727949142456055, "avg_line_length": 20.88372039794922, "blob_id": "6a8d447cadd43d63e0e8a497ad6b7a3a8bc1829d", "content_id": "afaa86facc7ed9fdb8ef9d94d4ca2594478a6d43", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 941, "license_type": "no_license", "max_line_length": 58, "num_lines": 43, "path": "/software-engineering-challenge-Taher-Dohadwala/GraphicsRepo/CityProject/Background.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport javax.swing.;\n\n\npublic class Background extends JComponent\n{\n int trigger = 0;\n Graphics2D g2;\n public void paintComponent(Graphics g){\n g2 = (Graphics2D)g;\n //sky/night\n if(trigger%2 == 0){\n g2.setColor(Color.CYAN);\n g2.fillRect(0,0,1365,450);\n }else{\n g2.setColor(Color.BLACK);\n g2.fillRect(0,0,1365,450);\n }\n \n //grass\n g2.setColor(Color.GREEN);\n g2.fillRect(0,450,1365,75);\n //road\n g2.setColor(Color.BLACK);\n g2.fillRect(0,525,1365,130);\n // yellow dashes on the road\n int x = 5;\n g.setColor(Color.YELLOW);\n for (int i=1;i<= 7;i++){\n g.fillRect(x,580,55,20);\n x += 200;\n }\n //grass\n g.setColor(Color.GREEN);\n g.fillRect(0,655,1365,75);\n \n }//end of paintcomp\n \n // this method is used in Sun class to start night mode\n public void nightsky(){\n trigger += 1;\n }\n}//end of class\n" }, { "alpha_fraction": 0.5690941214561462, "alphanum_fraction": 0.5815275311470032, "avg_line_length": 10.400809288024902, "blob_id": "256e2facfad041c04b1eebc9c1dce5160b61d4ef", "content_id": "ac71f407f33117618a038ac26de5d4b1f9a8ccd1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 2815, "license_type": "no_license", "max_line_length": 56, "num_lines": 247, "path": "/chapter6-repo-2016-mgorczyca12/Repo for Ch6/mathy.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.text.DecimalFormat;\nimport java.text.NumberFormat;\n//import cs1.Keyboard;\n//import javax.swing.;\n\npublic class mathy\n{\n\tprivate int [][] square;\n\n\t/\n\t\tdefault constructor - stubed in\n\n\t/\n\tpublic mathy()\n\t{\n\t\t\tSystem.out.println (\"hi from default constructor\");\n\n\t}\n\n\tpublic mathy(int [][] array)\n\t{\n\t\tsquare = array;\n\n\t}\n\n\n\t/*\n\t\ttake the absoulute value of the number\n\t\t@param int value\n\t\t@return absoulute value of number\n\t/\n\tpublic int abs (int x)\n\t{\n\t\tif (x < 0)\n\t\t\tx = -x;\n\n\t\treturn x;\n\n\n\n\t}//end of abs\n\n\n\n\n\n\n//}end of class\n\n\n\n\n\t/*\n\t\ttakes the odd numbers out of an array\n\t\t@param int[] values\n\t\t@return int[] odd values in the array\n\t/\n\n\tpublic int[] getOdd ( int[] num1)\n\t{\tint j = 0;\n\t\tint [] odd = new int[num1.length];\n\n\t\tfor( int i = 0; i<num1.length;i++)\n\t\t{\n\t\t\tif (num1[i] % 2 != 0)\n\t\t\t{\n\t\t\t\todd[j] = num1[i];\n\t\t\t\tj++;\n\t\t\t}\n\n\t\t}\n\n\t\treturn odd;\n\n\n\t}//end of getOdd\n\n\n\n\t/*\n\t\ttakes the even numbers out of an num array\n\t\tassigns values to evennum array\n\t\t@param int[] values, int[] evenvalues\n\t\t@none\n\t/\n\n\n\tpublic void getEven(int[] num, int evennum [])\n\t{\n\n\n\n\n\n\t}//end of getEven\n\n\n\n\n\n\n\n\t/*\n\t\ttwo int parameters and adds them\n\t\t@param 2 int values\n\t\t@return int sum of values\n\t/\n\n\n\tpublic int add (int x, int y)\n\t{\t//System.out.println(sum );\n\t\tint sum; //sum x and y are local var\n\t\tsum = x+y;\n\n\t\treturn sum;\n\n\n\t}//end of add\n\n\n\tpublic double add (double x,double y)\n\t{\n\n\t\treturn x+y;\n\t}\n\n\t/*\n\t\t\tmessage from Mathy class\n\t\t\t@param none\n\t\t\t@return String message\n\t/\n\n\n\tpublic String toString()\n\t{\n\t\treturn (\"Hi what do you want?, I'm just Mathy\");\n\n\t}\n\n\n\tpublic void switchThem (int[] a1, int a2[])\n\t{\n\t\tint [] temp = a1;\n\n\n\n\n\t}\n\tpublic void count(int[] a1, int[] a2)\n\t{\n\t\tfor (int i : a1)\n\t\t\ta2[i] ++;\n\n\n\n\t}\n\n\n\tpublic static int sum2DArray(int [][] scores)\n\t{\n\n\n\n\t\tfor ( int row=0; row < scores.length; row++)\n\t\t{\n\t\t\tfor ( int col=0; col < scores[row].length; col++)\n\n\t\t\t\tSystem.out.print (scores[row][col] + \"\\t\");\n\n\t\t\tSystem.out.println();\n \t}\n\n\n\t\treturn 0;\n\n\t}\n\n\n\n\tpublic int sumOneRow2DArray(int row)\n\t{\tint total = 0;\n\n\n\n\n\t\treturn total;\n\n\t}\n\t\tpublic int sumOneCol2DArray(int row)\n\t\t{\tint total = 0;\n\n\n\n\n\t\t\treturn total;\n\n\t}\n\n\tpublic int[] sumall2DArray(int [][] scores)\n\t{\n\t\tint [] temp = {1,2,3,4,};\n\n\n\n\n\t\treturn temp;\n\t}\n\n\t/*\n\t\tDoubles the size of an array\n\t\t@param int []\n\t\t@return int [] twice the size, with values copied over\n\t/\n public static int[] doubleSize(int[] array)\n {\n\t //make temp 2 times the size of array\n\t int[] temp = new int[array.length * 2];\n\t System.out.println(temp.length +\"-\" );\n\n\t\t//copy all the values over to new array\n\t for (int i = 0; i < array.length; i++)\n\t \t\ttemp[i] = array[i];\n\n\t\t//old array changes reference to new larger array\n array = temp;\n\n\t\treturn array;\n\n }\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n}//end of class" }, { "alpha_fraction": 0.5582959651947021, "alphanum_fraction": 0.560538113117218, "avg_line_length": 19.272727966308594, "blob_id": "27fca43b1431a20d4c83a669b6276f7160229e5e", "content_id": "bb9b72b1743b5329dd7d20b86dc9cbe2c8c9671a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 446, "license_type": "no_license", "max_line_length": 51, "num_lines": 22, "path": "/chapter16intro-Taher-Dohadwala/Maze/test.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.util.;\n/\n Write a description of class test here.\n * \n * @author (your name) \n * @version (a version number or a date)\n /\npublic class test\n{\n public static void main(String args[]){\n ArrayList<String> stack = new ArrayList<>();\n \n stack.add(\"a\");\n stack.add(\"b\");\n System.out.println(stack);\n \n System.out.println(stack.get(0));\n System.out.println(stack);\n \n \n }\n}\n" }, { "alpha_fraction": 0.6576576828956604, "alphanum_fraction": 0.707207202911377, "avg_line_length": 21.200000762939453, "blob_id": "ffc326ff2d96d8b27b9a9a24e5d09b6db31c8199", "content_id": "d13d34cd7246dd405c4d73318aa30c63cd984553", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 222, "license_type": "no_license", "max_line_length": 49, "num_lines": 10, "path": "/AI-Project/Project Testing/wolfram_Test.py", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import wolframalpha\n\nclient = wolframalpha.Client(\"8A86L7-EQW9P7T464\")\n\nres = client.query(\"What is 2 plus 2\")\n\nprint(next(res.results).text)\n#for pod in res.pods:\n # for sub in pod.subpods:\n # print sub.plaintext\n" }, { "alpha_fraction": 0.558080792427063, "alphanum_fraction": 0.5808081030845642, "avg_line_length": 25.847457885742188, "blob_id": "c28d464f18f0151ee1a022f9f9796e294d8dd9b2", "content_id": "03acb1f6d0e6f2670f557ce136bc8bdf8293fa30", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1584, "license_type": "no_license", "max_line_length": 122, "num_lines": 59, "path": "/chapter6-repo-2016-mgorczyca12/Repo for Ch6/ArrayList Purse and Question Lab/QuizTime.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.util.;\npublic class QuizTime\n{\n public static void main(String args[]){\n Scanner input = new Scanner(System.in);\n Quiz quiz1 = new Quiz();\n \n Question q1 = new Question(\"2+2\",\"4\",1);\n Question q2 = new Question(\"Integral of x^2dx\",\"1/3x^3 + c\",3);\n Question q3 = new Question(\"What is Mr.Hayes's first name\",\"Kevin\",2);\n Question q4 = new Question(\"2-0\",\"2\",1);\n Question q5 = new Question(\"What programming language is this made in\",\"java\",2);\n Question q6 = new Question(\"Derivative of x^2 \",\"2x\",3);\n\n \n System.out.println(\"Welcome to QuizTime!!!\\nThe total number of questions in this test is \"+quiz1.getTestsize()+\"\\n\");\n\n System.out.println(\"Questions:\");\n quiz1.getTest();\n \n System.out.println(\"\\nAnswers:\");\n \n \n String answer;\n boolean check = true;\n double total_correct = 0;\n double total_wrong = 0;\n ArrayList test = quiz1.getTestArray();\n Question ques;\n for (int i = 0; i <quiz1.getTestsize();i++){\n answer = input.nextLine();\n ques = (Question)(test.get(i));\n check = ques.answerCorrect(answer);\n \n if (check == true){\n total_correct++;\n }else{\n total_wrong++;\n }\n \n }\n \n \n \n System.out.println(\"Answers correct: \"+Math.round(total_correct));\n System.out.println(\"Answers Wrong: \"+Math.round(total_wrong));\n double percent = total_correct/quiz1.getTestsize();\n percent = 100;\n System.out.println(\"Score: \"+Math.round(percent)+\"%\");\n \n \n \n \n \n \n \n \n }\n}\n" }, { "alpha_fraction": 0.6535294055938721, "alphanum_fraction": 0.6841176748275757, "avg_line_length": 27.81355857849121, "blob_id": "b66e1942b6e6e4cca9302120b15c2675dc6534bb", "content_id": "584e914d30ba71ad2c20f5d3aae08b80c4e3c1e8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1700, "license_type": "no_license", "max_line_length": 155, "num_lines": 59, "path": "/AI-Project/Project Testing/speech_program.py", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import speech_recognition as sr\nimport pyaudio,os,time\nfrom gtts import gTTS\nimport requests,json\nimport wolframalpha\n\n\n# Record Audio\nr = sr.Recognizer()\nwith sr.Microphone() as source:\n print(\"Say something!\")\n audio = r.listen(source)\n while audio == None:\n audio = r.listen(source)\n \n \n# Speech recognition using Google Speech Recognition\ntry:\n # for testing purposes, we're just using the default API key\n # to use another API key, use `r.recognize_google(audio, key=\"GOOGLE_SPEECH_RECOGNITION_API_KEY\")`\n # instead of `r.recognize_google(audio)`\n save_audio = r.recognize_google(audio)\n print(\"You said: \" + save_audio\n \nexcept sr.UnknownValueError:\n print(\"Google Speech Recognition could not understand audio\")\n \nexcept sr.RequestError as e:\n print(\"Could not request results from Google Speech Recognition service; {0}\".format(e))\n\n\n\n#Saves audio and plays it back\n\nif \"weather\" in save_audio:\n if \"in\" in save_audio:\n \n response = requests.get(\"http://api.openweathermap.org/data/2.5/weather?q=Naperville,us&units=imperial&APPID=714964c165954619971a23be696deb1a\").json() \n a2 = \"The Temperature in Naperville is \"+str(response[\"main\"][\"temp\"])+\" degrees fahrenheit\"\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n\nelif \"what is\" in save_audio:\n client = wolframalpha.Client(\"8A86L7-EQW9P7T464\")\n res = client.query(save_audio)\n a2 = save_audio+\" the answer is \"+str((next(res.results).text))\n tts = gTTS(text = a2)\n tts.save(\"sample2.mp3\")\n\n os.system(\"sample2.mp3\")\n\n\n\nelse:\n tts = gTTS(text = save_audio)\n tts.save(\"sample2.mp3\")\n os.system(\"sample2.mp3\")\n" }, { "alpha_fraction": 0.4005080461502075, "alphanum_fraction": 0.5241320729255676, "avg_line_length": 23.102041244506836, "blob_id": "846e817e159e13e1ed4bbbb9cbcf91a3930149fe", "content_id": "0b0d26e6bc4d8507fa33616cdfccaf2b7eb77adc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1181, "license_type": "no_license", "max_line_length": 47, "num_lines": 49, "path": "/software-engineering-challenge-Taher-Dohadwala/GraphicsRepo/CityProject/Car.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport javax.swing.;\n\npublic class Car extends JComponent\n{\n int xmove = 0;\n int xmove2 = 0;\n int trigger = 0;\n Graphics2D g2;\n public void paintComponent(Graphics g){\n g2 = (Graphics2D)g;\n \n //Moves the car from left to right\n if (trigger%2 ==0){\n g2.setColor(Color.RED);\n g2.fillRect(100+xmove-100,470,200,100);\n g2.fillRect(300+xmove-100,520,25,50);\n \n g2.setColor(Color.BLACK);\n g2.fillOval(100+xmove-100,545,50,50);\n g2.fillOval(225+xmove-100,545,50,50);\n \n }else{\n //moves the car from right to left\n g2.setColor(Color.RED);\n g2.fillRect(1300+xmove2,470,200,100);\n g2.fillRect(1100+xmove2+175,520,25,50);\n \n g2.setColor(Color.BLACK);\n g2.fillOval(1300+xmove2+150,545,50,50);\n g2.fillOval(1175+xmove2+150,545,50,50);\n }\n \n }\n //animation for the car moving\n public void nextFrame(){\n xmove += 3;\n xmove2 -= 3;\n if (xmove >= 1500){\n trigger += 1;\n xmove = 0;\n xmove2 = 0;\n }\n repaint();\n }\n \n \n\n}\n" }, { "alpha_fraction": 0.6033519506454468, "alphanum_fraction": 0.6368715167045593, "avg_line_length": 12.730769157409668, "blob_id": "423acc3e81dee00ac00706d48e0ee9db28e5b53e", "content_id": "951c9656f4e2140713c0b725f2a124aee1300d01", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 358, "license_type": "no_license", "max_line_length": 34, "num_lines": 26, "path": "/chapter6-repo-2016-mgorczyca12/Repo for Ch6/ArrayList Purse and Question Lab/Coin.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "public enum Coin\n{\n\tPenny(\"P\", 0.01),\n\tNickle(\"N\", 0.05),\n\tDime(\"D\", 0.10),\n\tQuarter(\"Q\", 0.25);\n\n\tprivate final String option;\n\tprivate final double value;\n\n\tCoin(String option, double value)\n\t{\n\t\tthis.option = option;\n\t\tthis.value = value;\n\t}\n\n\tpublic String getOption()\n\t{\n\t\treturn this.option;\n\t}\n\n\tpublic double getValue()\n\t{\n\t\treturn this.value;\n\t}\n}\n\n" }, { "alpha_fraction": 0.5146169066429138, "alphanum_fraction": 0.5756048560142517, "avg_line_length": 21.78160858154297, "blob_id": "a7cdcb3996d26db7733e20a127abf796380e28f0", "content_id": "842b7e074c176622056c5d443b646ddc19f29541", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1984, "license_type": "no_license", "max_line_length": 73, "num_lines": 87, "path": "/FinalProject/FinalProjectCode/ButtonLocationDemo.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import javax.swing.;\nimport java.awt.;\nimport java.awt.event.;\npublic class ButtonLocationDemo extends JFrame implements ActionListener{\n\n private JButton b1;\n private JButton b2;\n private JButton b3;\n private TextField text = new TextField(20);\n int numClicks = 0;\n JPanel p;\n lukeskywalker h1;\n \n InfernoRifleBestie bestie;\n \n static Flamethrower m1;\n public ButtonLocationDemo(){\n p = new JPanel();\n b1 = new JButton(\"Lightsaber Attack\");\n b2 = new JButton(\"Lightsaber Throw\");\n b3 = new JButton(\"Special\");\n h1 = new lukeskywalker(0,0);\n bestie = new InfernoRifleBestie(0,0);\n m1 = new Flamethrower(0,0);\n \n \n p.setLayout(null);\n b1.setBounds(225,200,150,50);\n b2.setBounds(375,200,150,50);\n b3.setBounds(525,200,150,50);\n h1.setBounds(0,300,500,500);\n bestie.setBounds(0,0,200,119);\n m1.setBounds(50,50,550,100);\n p.add(b1);\n p.add(b2);\n p.add(b3);\n p.add(h1);\n p.add(bestie);\n p.add(m1);\n text.setBounds(250,900,100,25);\n \n \n //getContentPane().add(text);\n getContentPane().add(p);\n //setLayout(null);\n setDefaultCloseOperation(3);\n setSize(1000,1000);\n setVisible(true);\n \n \n b1.addActionListener(this);\n b2.addActionListener(this);\n b3.addActionListener(this);\n \n \n }\n \n public void bestieAttack1() throws InterruptedException {\n m1.attack();\n }\n \n public void actionPerformed(ActionEvent e){\n numClicks++;\n text.setText(\"Button Clicked \" + numClicks + \" times\");\n if (e.getSource() == b1){\n System.out.println(e.getSource());\n p.add(h1);\n p.repaint();\n }\n \n \n if (e.getSource() == b2){\n p.remove(h1);\n p.repaint();\n }\n \n if (e.getSource() == b3){\n p.remove(b1);\n p.repaint();\n }\n \n }\n public static void main(String[]args){\n new ButtonLocationDemo();\n \n }\n}\n\n\n" }, { "alpha_fraction": 0.7308210134506226, "alphanum_fraction": 0.7537012100219727, "avg_line_length": 23.766666412353516, "blob_id": "763f80b7fab0ad34c78423569af0fafd72608e52", "content_id": "2a92b912eeca10a0bc951c872c90ffcdd67e3910", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 743, "license_type": "no_license", "max_line_length": 145, "num_lines": 30, "path": "/chapter16intro-Taher-Dohadwala/Maze/README.TXT", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "Maze Lab\nTaher Dohadala\n# Purpose\n\n\"In this lab you will use the power of a stack and a queue to explore\n\tand find your way through a maze. The purpose of this lab is to:\n\n* Have you implement a Stack and a Queue,\n\n* Build a simple linked list of nodes,\n\n* Use your stack and queue to solve a maze,\n\n* Explore the differences between the two solution strategies.\"\n\n# Requirements\n\n* Complete the [CSCI 151 - Stacks and Queues Simply A-Maze-ing! lab](https://www.cs.oberlin.edu/~rhoyle/16s-cs151/lab03/index.html) from Oberlin.\n\n# Extensions\n\n* Try the bonus mazes.\n\n* Add more awesome.\n\n# Submission\n\n* Submit a link to your GitHub repository with this assignment.\n\nhttps://docs.google.com/document/d/1yyK-j2E9dCznOvJzKP08mHxkExLh9Vm0YZPUYUKvtIM/edit\n" }, { "alpha_fraction": 0.4764094650745392, "alphanum_fraction": 0.4905467629432678, "avg_line_length": 21.890625, "blob_id": "df766e3833201d89c3f8e3b84a4ea01b5e3c6e1d", "content_id": "ff08f09076af0ba1ec9dd515500167bc10e14545", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 5871, "license_type": "no_license", "max_line_length": 87, "num_lines": 256, "path": "/Chapter-6/Chapter 6 notes/ch6intro_to_array.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "/******************************************************************\n// These are the notes for ch 6 used in hayes class\n\n\nimport\n//***************************************************************** /\n\n\nimport java.text.DecimalFormat;\nimport java.text.NumberFormat;\nimport javax.swing.;\nimport java.util.StringTokenizer;\nimport java.util.;\nimport java.util.ArrayList;\n\npublic class ch6intro_to_array\n\n{\n final static int MAX = 15;\n\npublic static void main (String[] args)\n{\n //this is a general ArrayList\n ArrayList list = new ArrayList();\n\n //Type of ArrayList holds only the Type\n ArrayList <String> farm = new ArrayList<String>();\n\n farm.add(\"Cow\");farm.add(\"Pig\");farm.add(\"Chicken\");farm.add(\"Duck\");\n System.out.println(farm);\n\n for (int i = 0; i <10; i++){\n farm.add(\"dog\");\n farm.add(\"dog\");\n farm.add(\"Chicken\");\n farm.add(\"Chicken\");\n }\n farm.add(\"Cow\");farm.add(\"Pig\");farm.add(\"Chicken\");farm.add(\"Duck\");\n farm.add(\"Cow\");farm.add(\"Pig\");farm.add(\"Chicken\");farm.add(\"Duck\");\n farm.add(\"Cow\");farm.add(\"Pig\");farm.add(\"Chicken\");farm.add(\"Duck\");\n farm.add(\"Horse\");farm.add(\"Horse\");farm.add(\"Horse\");farm.add(\"Horse\");\n\n System.out.println(farm);\n int count = 0;\n\n //remove i++ here\n for (int i = farm.size()-1; i >= 0;i--){\n\n if(farm.get(i).equalsIgnoreCase(\"duck\"))\n count++;\n\n //.set() return the object at that index\n //farm.set(i,\"cat\");\n // set returns object and doesnt remove\n\n if (farm.get(i).equalsIgnoreCase(\"chicken\"))\n farm.remove(i);\n\n }\n\n // farm.remove(\"Chicken\"); removes 1st instance\n //while (farm.remove(\"chicken\"))\n System.out.println(\"---------------------------------------------\");\n System.out.println(farm);\n System.out.println(\"There are \"+count+\" Ducks\");\n \n ArrayList<CD> mycd = \n\n \n/\n// array's are objects and are passed by reference\n int x = 50;\n mathy useful = new mathy();\n int[] num = new int[1000000];\n int[] values = new int[20];\n int[] oddnum = new int[num.length];\n int[] evennum = new int[num.length];\n int[] negnum = new int[MAX];\n String [] names = {\"Charlie\",\"Megan\",\"Tadd\",\"Patrick\"};\n\n Random gen = new Random();\n\n\n// pop with random numbers range -50 to 50\n\n for(int i =0; i<num.length; i++)\n {\n num[i] = gen.nextInt(100)-50;\n\n }\n// prints the array of int - off by one error < not <=\n for(int i =0; i<num.length; i++)\n {\n System.out.println( num[i] );\n }\n oddnum = useful.getOdd(num);\n // for each look\n for (int s:num){\n System.out.println(s);\n }\n\n\n\n\n\n System.out.println(\"----------SORTING-----------\" );\n\n\n\n\n int look = 42;\n\n //System.out.println(\"Found \"+Searches.linearSearch(num,look) );\n Sorts.selectionSort(num);\n //Sorts.insertionSort(num);\n //System.out.println(\"FoundB \"+Searches.binarySearch(num,look) );\n\n\n\n\n //Sorts.selectionSort(num);\n System.out.println(num.length );\n num = doubleSize(num);\n\n\n for (int s : num)\n {\n }\n\n\n odd(num,oddnum);\n\n System.out.println(\"---------------\");\n\n for (int s : oddnum)\n System.out.println(s);\n\n\n\n //System.out.println(\"Enter a number\");\n //int find = Keyboard.readInt();\n\n //System.out.println(Searches. binarySearch(num,find));\n\n//searching for 412\n for (int i = 0; i < MAX; i++)\n x++;\n\n // for (int i = 0; i < MAX; i++)\n // values[num[i]+25] ++;\n // x++;\n //how do you count the #of times each value comes up?\n\n for( int i =0; i<num.length; i++)\n System.out.print(\"\\t\" + num[i]);\n\n //for (int i = 0; i<50;i++)\n // System.out.println(\"The number of times\" + (i-25) +\"is\" +\n // \"\\t\" + values[i]);\n\n\n foo(num[0]);\n\n System.out.println(\"*********\"+oddnum[7]);\n\n foo(num);\n System.out.println(\"&&&&&&&&&&\"+num[0]);\n System.out.println(oddnum[7]);\n\n //odd(num,oddnum);\n\n //negnum = neg(num);\n\n/\n///starts sorts\n // make a 2d array with an initlizer list\n //print the length of row and column\n // sums: 6 7 8 9\n int [] [] scores = { {1,2,3},{2,2,3},{3,2,3},{4,2,3} };\n\n System.out.println(scores[0].length+\"col\");\n System.out.println(scores.length+\"rows\");\n\n System.out.print (\"The sum of this array is: \"+mathy.sum2DArray(scores));\n //System.out.print (\"The sum of this row is: \"+ mathy.sumOneRow2DArray(scores[0]));\n\n\n\n\n //make a two dementional array\n int [][] table = new int[5][10];\n\n // Load the tabel with values\n for (int row = 0;row<table.length;row++){\n for(int col = 0;col <table[row].length;col++){\n table[row][col] = row 10 + col;\n }\n }\n\n\n //print the table\n for (int row = 0; row< table.length;row++){\n for (int col = 0; col< table[row].length;col++){\n System.out.print(table[row][col] +\"\\t\");\n }\n System.out.println();\n }\n\n\n///ends sorts\n}// end of main\n\n public static int[] doubleSize(int[] array)\n {\n\n\n return array;\n\n\n }\n\n public static void foo(int x)\n {\n\n\n }\n\n\n\n public static void foo(int [] num)\n {\n\n }\n\n\n\n\n public static void odd(int[] m_num, int[] m_odd)\n {\n\n int count =0;\n\n\n }// end of odd\n\n/\n //====================================================\n public static int[] neg(int[] m_num)\n {\n\n\n return negarray;\n }//end of neg\n/\n\n}// end of class\n\n\n\n\n\n\n\n\n\n\n\n" }, { "alpha_fraction": 0.5576796531677246, "alphanum_fraction": 0.5669083595275879, "avg_line_length": 22.33846092224121, "blob_id": "ca56a1d124b9641b7b1259ddddc9a5d278f57f32", "content_id": "f7edce221ce835ac4575c163079eb52909c34f55", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1517, "license_type": "no_license", "max_line_length": 86, "num_lines": 65, "path": "/FinalProject/FinalProjectCode/LaserBlast.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import java.awt.;\nimport java.io.;\nimport javax.imageio.ImageIO;\nimport javax.swing.;\nimport java.awt.image.BufferedImage;\nimport java.awt.Graphics;\nimport java.awt.Graphics2D;\nimport java.io.File;\nimport java.io.IOException;\nimport javax.swing.JFrame;\nimport javax.swing.JPanel;\n\n/*\n Write a description of class LaserBlast here.\n * \n * @author (your name) \n * @version (a version number or a date)\n /\npublic class LaserBlast extends JComponent\n{\n /* description of instance variable x (add comment for each instance variable) /\n private int x;\n private int y;\n private int width;\n private int height;\n \n private BufferedImage laser;\n /\n Default constructor for objects of class LaserBlast\n /\n public LaserBlast(int x, int y)\n {\n this.x = x;\n this.y = y;\n width = 800;\n height = 300;\n try {\n laser = ImageIO.read(new File(\"Images/laserblast.png\"));\n }\n catch (IOException e) {\n \n }\n }\n\n @Override\n protected void paintComponent(Graphics g) {\n super.paintComponent(g);\n g.drawImage(laser, x, y, width, height, this);\n System.out.println(\"pew\");\n }\n \n \n \n public void adjustSize() throws InterruptedException{\n for (int i = 0; i < 30; i++) {\n if (height > 1) {\n height -= 2;\n y += 1;\n repaint();\n Thread.sleep(1);\n }\n }\n repaint();\n }\n}\n" }, { "alpha_fraction": 0.38694268465042114, "alphanum_fraction": 0.38694268465042114, "avg_line_length": 23.84000015258789, "blob_id": "d241e24cc0104476696c31d946f0a170e7552e73", "content_id": "ba9acf6c12af8d533b5206bc2b8b4abff777b9e2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 1256, "license_type": "no_license", "max_line_length": 71, "num_lines": 50, "path": "/Chapter-7/Notes/Chapter 7 notes/Animal.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "//*****************************************************************\n// Animal.java Author: Kevin/Terrific/Hayes\n//\n// Represents an Animal.\n//****************************************************************\n\npublic abstract class Animal\n{\n private String type;\n\n public Animal()\n {//this is called by default\n type = \"Default\";\n System.out.println(\"hello from Animal Default\" );\n }\n /-----------------------------------------------------------------\n * Creates a Animal with the given type.\n /\n public Animal(String animalType)\n {\n type = animalType;\n System.out.println(\"hello from Animal\");\n }\n\n /-----------------------------------------------------------------\n Returns this Animals type.\n //\n public String getType()\n {\n return type;\n }\n\n \n /-----------------------------------------------------------------\n This Method should return a string indication how this pet moves\n /\n abstract public String move();\n \n \n \n /-----------------------------------------------------------------\n Returns a string representation of this Animal.\n //\n public String toString()\n {\n return \"My type is \" + type;\n }\n\n\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n" }, { "alpha_fraction": 0.7115384340286255, "alphanum_fraction": 0.7115384340286255, "avg_line_length": 16.16666603088379, "blob_id": "5ddbfa989b4d0769a446a4ef86cac1527ed2bc6f", "content_id": "7e232b6ef151d5587b82905c238de68afcfd000f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 104, "license_type": "no_license", "max_line_length": 38, "num_lines": 6, "path": "/chapter5-repo-2016-Taher-Dohadwala/Chapter5/Priority.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\npublic interface Priority\n{\n public double getPriority();\n public void setPriority(double p);\n\n}\n" }, { "alpha_fraction": 0.8641975522041321, "alphanum_fraction": 0.8765432238578796, "avg_line_length": 39.5, "blob_id": "82bfa07118ca749af289ab1cdef0e4e4e57c13be", "content_id": "a7d6dd1cb27e206b5dfecfc17d56d5d23a9f0ad5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 81, "license_type": "no_license", "max_line_length": 57, "num_lines": 2, "path": "/README.md", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "# SoftwareEngineering1\nHighschool Software Engineering Course notes and Projects\n" }, { "alpha_fraction": 0.5132743120193481, "alphanum_fraction": 0.5150442719459534, "avg_line_length": 16.090909957885742, "blob_id": "33bd70d6e3a79f392067428d400316966f5d95f5", "content_id": "21952a004057a668d52a3edcc094eb9da0f2d544", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Java", "length_bytes": 565, "license_type": "no_license", "max_line_length": 55, "num_lines": 33, "path": "/chapter16intro-Taher-Dohadwala/Maze/MazeSolverStack.java", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "\npublic class MazeSolverStack extends MazeSolver\n{\n\n /\n Constructor for objects of class MazeSolverStack\n */\n MyStack stack;\n public MazeSolverStack(Maze maze)\n {\n super(maze);\n }\n\n public void makeEmpty(){\n stack = new MyStack();\n }\n \n public boolean isEmpty(){\n \n if (stack.size()== 0){\n return true;\n }\n return false;\n }\n \n public void add(Square sq){\n stack.push(sq);\n }\n \n public Square next(){\n return (Square)(stack.pop());\n }\n \n}\n" }, { "alpha_fraction": 0.7302631735801697, "alphanum_fraction": 0.7302631735801697, "avg_line_length": 29.399999618530273, "blob_id": "f3e4b3c977314a26c5adee7cf7eb20cc15f44013", "content_id": "8ddd9c1f943e118711cdc91122d2607e494b1c0f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 304, "license_type": "no_license", "max_line_length": 59, "num_lines": 10, "path": "/AI-Project/Project Testing/talkey_test.py", "repo_name": "Taher-Dohadwala/SoftwareEngineering1", "src_encoding": "UTF-8", "text": "import pyttsx\ndef onStart(name):\n print 'starting', name\ndef onWord(name, location, length):\n print 'word', name, location, length\ndef onEnd(name, completed):\n print 'finishing', name, completed\nengine = pyttsx.init()\nengine.say('The quick brown fox jumped over the lazy dog.')\nengine.runAndWait()\n" } ]	37
ghmkt/ddareung	https://github.com/ghmkt/ddareung	eb1da462157ea4318e559a4db485322f98775a7d	151f8486a677789f5fa962ea34baf42034d9f4a9	d28c0b66d45bc2219408c91133cdbfd7acd3d8cd	refs/heads/master	2020-04-17T00:39:26.688492	2019-01-22T09:47:53	2019-01-22T09:47:53	166,057,553	0	2	null	null	null	null	null	[ { "alpha_fraction": 0.36021506786346436, "alphanum_fraction": 0.37401434779167175, "avg_line_length": 41.944881439208984, "blob_id": "61e617f3b8a16980bb1ddc3d466a1c9693c0b52a", "content_id": "d9a125e0f635cf12eeb4d2cd3d4d6ba71459f993", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 12246, "license_type": "no_license", "max_line_length": 180, "num_lines": 254, "path": "/daum_map_crawler.py", "repo_name": "ghmkt/ddareung", "src_encoding": "UTF-8", "text": "import pandas as pd\r\nfrom selenium.webdriver.common.keys import Keys\r\nfrom selenium import webdriver\r\nimport pickle\r\nfrom selenium.common.exceptions import UnexpectedAlertPresentException\r\nimport time\r\n\r\ndf = pd.read_csv(r'station1.csv')\r\nst_address = df['대여소 주소'].values.tolist()\r\n\r\npath = 'chromedriver.exe'\r\n\r\n# 133 x 1 벡터를 만들어서 한 row에 133개의 list를 추가해서 결과적으로 133 x 133 x 4의 3차원 array를 만듦\r\nresult = [[] * len(st_address) for row in range(len(st_address))]\r\n\r\n# 각각의 주소 i에 대해서 똑같은 주소 j에 대한 경로를 찾을거임\r\nfor x, i in enumerate(st_address):\r\n if (x < 49) and (x > 84):\r\n # 컴퓨터 두 대에서 크롬 드라이버 여러 개로 나눠서 돌리느라 enumerate로 index 지정해주고 구간 나눠줌\r\n pass\r\n else:\r\n driver = webdriver.Chrome(path)\r\n\r\n # 다음 지도 켜고 길찾기로 넘어가는 동작\r\n driver.get('http://map.daum.net')\r\n time.sleep(1.5)\r\n findroad = driver.find_element_by_xpath('//[@id=\"search.tab2\"]/a')\r\n findroad.click()\r\n time.sleep(1.5)\r\n print(i)\r\n\r\n # '출발' 에 주소 넣는 동작\r\n input_fromadd = driver.find_element_by_xpath('//[@id=\"info.route.waypointSuggest.input0\"]')\r\n input_fromadd.send_keys(i)\r\n time.sleep(1.5)\r\n input_fromadd.send_keys(Keys.ENTER)\r\n\r\n for y, j in enumerate(st_address):\r\n if y < 0:\r\n pass\r\n else:\r\n\r\n if (y != 0) and (y % 20 == 0):\r\n driver.close()\r\n driver = webdriver.Chrome(path)\r\n driver.get('http://map.daum.net')\r\n findroad = driver.find_element_by_xpath('//[@id=\"search.tab2\"]/a')\r\n findroad.click()\r\n time.sleep(1.5)\r\n input_fromadd = driver.find_element_by_xpath('//[@id=\"info.route.waypointSuggest.input0\"]')\r\n input_fromadd.send_keys(i)\r\n time.sleep(1.5)\r\n input_fromadd.send_keys(Keys.ENTER)\r\n time.sleep(1.5)\r\n\r\n print(j)\r\n # 133 x 1 벡터의 한 원소에 1 x 4 벡터를 133개 넣어주는 것. --> 133 x 133 x 4\r\n\r\n\r\n # 자기 자신의 경로는 안 찾음\r\n temp = []\r\n if i == j:\r\n result[x].append(temp)\r\n print(temp)\r\n\r\n if i != j:\r\n\r\n # while 1 --> break에 도착할 때까지 코드 무한 반복\r\n # 왜냐면 코드 속도에 비해서 크롬 속도가 느려서 element가 로딩이 안되면 alert나 invisible exception이 발생\r\n # 그거를 막기 위해서 while, try, except 사용\r\n while 1:\r\n # '도착' 에 주소 넣고 경로 찾은 다음에 자전거 경로 찾는 동작\r\n try:\r\n input_toadd = driver.find_element_by_xpath('//[@id=\"info.route.waypointSuggest.input1\"]')\r\n input_toadd.send_keys(j)\r\n time.sleep(1.5)\r\n input_toadd.send_keys(Keys.ENTER)\r\n time.sleep(1.5)\r\n driver.find_element_by_xpath('//[@id=\"biketab\"]').click()\r\n time.sleep(1.5)\r\n # print('1')\r\n break\r\n\r\n # 코드가 너무 빨리 동작해서 '도착'에 주소 넣고 엔터누른게 잘 인식이 안 된 경우\r\n except UnexpectedAlertPresentException:\r\n alert = driver.switch_to.alert\r\n alert.accept()\r\n # print('2')\r\n continue\r\n\r\n # 기타 등등. 뒤에서 나오는 exception의 경우가 다양해서 except: 로 통일\r\n except:\r\n driver.find_element_by_xpath('//[@id=\"biketab\"]').click()\r\n time.sleep(1.5)\r\n # print('3')\r\n continue\r\n\r\n\r\n # 시간\r\n while 1:\r\n # 시간이 숫자가 아니라 이미지 하나하나로 구성되어 있어서 시간에 해당하는 이미지들을 리스트로 받고\r\n # 이미지 각각의 이름에서 숫자 추출 후 int로 변환\r\n try:\r\n timelst = driver.find_elements_by_css_selector(\r\n 'li.BikeRouteItem.BikeRouteItem-HOVER > div.BikeRouteSummaryView > div.contents > p > span.time > span.ImageNumberView.minute > span')\r\n a = ''\r\n for k in timelst:\r\n a += k.get_attribute('class')[-1]\r\n a = int(a)\r\n # print('1')\r\n break\r\n\r\n except UnexpectedAlertPresentException:\r\n alert = driver.switch_to.alert\r\n alert.accept()\r\n time.sleep(1.5)\r\n # print('5')\r\n continue\r\n\r\n except:\r\n driver.find_element_by_xpath('//[@id=\"biketab\"]').click()\r\n time.sleep(1.5)\r\n try:\r\n hourlst = driver.find_elements_by_css_selector(\r\n 'li.BikeRouteItem.BikeRouteItem-HOVER > div.BikeRouteSummaryView > div.contents > p > span.time > span.ImageNumberView.hours > span')\r\n a = ''\r\n b = ''\r\n for k in hourlst:\r\n a += k.get_attribute('class')[-1]\r\n a = 60 * int(a)\r\n try:\r\n minutelst = driver.find_elements_by_css_selector(\r\n 'li.BikeRouteItem.BikeRouteItem-HOVER > div.BikeRouteSummaryView > div.contents > p > span.time > span.ImageNumberView.minuteMargin > span')\r\n for k in minutelst:\r\n b += k.get_attribute('class')[-1]\r\n b = int(b)\r\n a += b\r\n except:\r\n break\r\n # print('2')\r\n break\r\n except:\r\n continue\r\n print(a)\r\n\r\n\r\n\r\n # 거리\r\n while 1:\r\n # 거리도 숫자가 아니라 이미지와 점으로 구성되어 있어서 파일명에서 숫자 추출 후 float으로 변환\r\n try:\r\n distancelist = driver.find_elements_by_css_selector(\r\n 'li.BikeRouteItem.BikeRouteItem-HOVER > div.BikeRouteSummaryView > div.contents > p > span.distance > span.ImageNumberView.distanceImage > span')\r\n b = ''\r\n unit = driver.find_element_by_xpath(\r\n '//[@id=\"info.bikeRoute\"]/div[1]/ul/li[1]/div[1]/div[1]/p/span[2]/span[2]').text\r\n for k in distancelist:\r\n if k.get_attribute('class') == 'dot':\r\n b += '.'\r\n else:\r\n b += k.get_attribute('class')[-1]\r\n b = float(b)\r\n # print(unit)\r\n if b > 40:\r\n b = round(b / 1000, 1)\r\n break\r\n # print('7')\r\n\r\n except UnexpectedAlertPresentException:\r\n alert = driver.switch_to.alert\r\n alert.accept()\r\n time.sleep(1)\r\n # print('8')\r\n continue\r\n\r\n except:\r\n driver.find_element_by_xpath('//[@id=\"biketab\"]').click()\r\n time.sleep(1)\r\n # print('9')\r\n continue\r\n print(b)\r\n\r\n # 고도차\r\n while 1:\r\n # str 형태로 들어가있는 최대, 최소 고도 int로 변환 후 (-) 연산\r\n try:\r\n altitude = driver.find_element_by_xpath(\r\n '//[@id=\"info.bikeRoute\"]/div[1]/ul/li[1]/div[1]/div[1]/div/span[1]').text\r\n lsta = altitude.split()\r\n altdif = int(lsta[-1][:-1]) - int(lsta[2][:-2])\r\n # print('10')\r\n break\r\n\r\n except UnexpectedAlertPresentException:\r\n alert = driver.switch_to.alert\r\n alert.accept()\r\n time.sleep(1.5)\r\n # print('11')\r\n continue\r\n\r\n except:\r\n driver.find_element_by_xpath('//[@id=\"biketab\"]').click()\r\n time.sleep(1.5)\r\n # print('12')\r\n continue\r\n print(altdif)\r\n\r\n # 칼로리\r\n while 1:\r\n try:\r\n # str 형태의 칼로리 int로 변환\r\n calorie = driver.find_element_by_xpath(\r\n '//[@id=\"info.bikeRoute\"]/div[1]/ul/li[1]/div[1]/div[1]/div/span[2]').text[1:-4]\r\n calorie = int(calorie)\r\n # print('13')\r\n break\r\n except UnexpectedAlertPresentException:\r\n alert = driver.switch_to.alert\r\n alert.accept()\r\n time.sleep(1.5)\r\n # print('14')\r\n continue\r\n\r\n except:\r\n driver.find_element_by_xpath('//[@id=\"biketab\"]').click()\r\n time.sleep(1.5)\r\n # print('15')\r\n continue\r\n print(calorie)\r\n\r\n # temp 리스트에 정보 저장 후 result의 x행에 추가. 이걸 133번하면 열이 133개 생기고\r\n # 각 원소는 4개의 정보를 갖는 리스트 형태\r\n temp.append(a)\r\n temp.append(b)\r\n temp.append(altdif)\r\n temp.append(calorie)\r\n result[x].append(temp)\r\n print(temp)\r\n\r\n\r\n # print('다음y로')\r\n # 다음 도착지로 넘어가기 위해서 주소 지워주는 코드\r\n driver.find_element_by_xpath('//*[@id=\"info.route.searchBox\"]/div[2]/span[1]/a').click()\r\n time.sleep(1.5)\r\n\r\n # print('다음x로')\r\n # 다음 출발지로 넘어가기 위해서 출발 및 도착 주소 지워주는 코드\r\n # 를 짰었는데 크롬이 메모리를 몇 기가씩 차지해서 그냥 닫았다가 새로 열려고 바꿈\r\n driver.close()\r\n\r\n\r\n # result 리스트를 pickle 형태로 저장\r\n with open('ddarrung{0}.pickle'.format(x), 'wb') as f:\r\n pickle.dump(result, f)" }, { "alpha_fraction": 0.675000011920929, "alphanum_fraction": 0.800000011920929, "avg_line_length": 19, "blob_id": "482e0b38a14d1afd02bc5ee7870d971a762eb460", "content_id": "a6e6e956226facbda322ceaaaecedcf8c8a12549", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 52, "license_type": "no_license", "max_line_length": 28, "num_lines": 2, "path": "/README.md", "repo_name": "ghmkt/ddareung", "src_encoding": "UTF-8", "text": "# ddareung\n2018-2 Growth Hackers 내부프로젝트\n" }, { "alpha_fraction": 0.5979331731796265, "alphanum_fraction": 0.6322999000549316, "avg_line_length": 30.4296875, "blob_id": "97d86c5f92cee4dd205d35051699d9727a50bcaa", "content_id": "6f03113b63d6f8db05e135d0aaea2730b8f2b152", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "R", "length_bytes": 4509, "license_type": "no_license", "max_line_length": 161, "num_lines": 128, "path": "/community_analysis.R", "repo_name": "ghmkt/ddareung", "src_encoding": "UHC", "text": "\r\n#패키지 igraph\r\nlibrary(igraph)\r\n\r\n#데이터 로드 및 병합\r\npub_bike_loc<- read.csv(\"pub_bike_list.csv\",header = TRUE)\r\npub_bike_t1<- read.csv('data (1)/서울특별시 공공자전거 대여이력 정보_2017년_3분기_1.csv',header = TRUE,stringsAsFactors = FALSE)\r\npub_bike_t2<- read.csv('data (1)/서울특별시 공공자전거 대여이력 정보_2017년_3분기_2.csv',header = TRUE,stringsAsFactors = FALSE)\r\n\r\npub_bike_t<- rbind(pub_bike_t1,pub_bike_t2)\r\npub_bike_t<- as.data.frame(pub_bike_t)\r\n\r\n#데이터 문자열 처리\r\npub_bike_t[,3] <- gsub(\"'\",\"\",pub_bike_t[,3])\r\npub_bike_t[,7] <- gsub(\"'\",\"\",pub_bike_t[,7])\r\n\r\n#각 정류소 이름을 열 이름으로 설정하기 위해서 정류소 이름들 저장\r\nstagelist <- unique(c(unique((pub_bike_t[,3])),unique(pub_bike_t[,7])))\r\n\r\n#인접행렬 구서\r\nN <- length(stagelist)\r\nAdj <- matrix(0, N, N)\r\n\r\nrownames(Adj) <- stagelist\r\ncolnames(Adj) <- stagelist\r\n\r\nfor(j in 1:length(pub_bike_t[,1])){\r\n \r\n Adj[unlist(pub_bike_t[j,3]),unlist(pub_bike_t[j,7])] <- Adj[unlist(pub_bike_t[j,3]),unlist(pub_bike_t[j,7])] +1\r\n Adj[unlist(pub_bike_t[j,7]),unlist(pub_bike_t[j,3])] <- Adj[unlist(pub_bike_t[j,7]),unlist(pub_bike_t[j,3])] +1\r\n \r\n #if(j %%10000 == 0){print(j)\r\n # }else{}\r\n}\r\n\r\nAdj_df <- as.data.frame(Adj)\r\n\r\nfor(j in 1:N) {\r\n Adj_df[j,j] <- 0\r\n}\r\n\r\nAdj <- as.matrix(Adj_df)\r\n\r\n#igrph를 통해서 graph.adjacency 구성 및 cluster_fast_greedy 적ㅇ\r\ng <- graph.adjacency(Adj, mode=\"undirected\", weighted=T)\r\na <- cluster_fast_greedy(g, weights = E(g)$weight)\r\n\r\n#나누어진 cluster 할당\r\nindex = a$membership\r\ndf = as.data.frame(cbind(a$membership,a$names))\r\n\r\ncolnames(df) <- c(\"commu\",\"stnumber\")\r\naa <- as.data.frame(pub_bike_loc)\r\n#head(df)\r\n\r\n\r\npub_bike_loc_m <- merge(x = aa, y = df,by = \"stnumber\", all.x = TRUE) \r\npub_bike_loc_m <- subset(pub_bike_loc_m, is.na(pub_bike_loc_m$commu)==0)\r\n\r\n\r\n#head(pub_bike_loc_m)\r\n\r\n#community가 4인 곳만 추출하기\r\nsubAdj <- Adj_df[which(colnames(Adj_df)%in%pub_bike_loc_m[pub_bike_loc_m$commu==4,]$stnumber),]\r\nsubAdj_1 <- subAdj[,which(colnames(Adj_df)%in%pub_bike_loc_m[pub_bike_loc_m$commu==4,]$stnumber)]\r\n\r\n#추가적인 cluster_fast_greedy 적용\r\nsAdj <- as.matrix(subAdj_1)\r\ng <- graph.adjacency(sAdj, mode=\"undirected\", weighted=T)\r\nss <- cluster_fast_greedy(g, weights = E(g)$weight)\r\n\r\nindex_s = ss$membership\r\ndf_s = as.data.frame(cbind(ss$membership,ss$names))\r\ncolnames(df_s) <- c(\"commu\",\"stnumber\")\r\naa <- as.data.frame(pub_bike_loc)\r\n\r\n\r\npub_bike_loc_s <- merge(x = aa, y = df_s,by = \"stnumber\", all.x = TRUE) \r\npub_bike_loc_s <- subset(pub_bike_loc_s, is.na(pub_bike_loc_s$commu)==0)\r\n\r\n\r\n\r\n#지도에 시각화 \r\n\r\nlibrary(\"ggplot2\")\r\nlibrary(\"sp\")\r\nlibrary(\"maptools\")\r\nlibrary(\"rgdal\")\r\nlibrary(\"geosphere\")\r\n\r\n#좌표 변환계 설정\r\ncrsUTM_K <- CRS(\"+proj=tmerc +lat_0=38 +lon_0=127.5 +k=0.9996 +x_0=1000000 +y_0=2000000 +ellps=bessel +units=m +no_defs\")\r\ncrsWGS84lonlat <- CRS(\"+proj=longlat +zone=52 +ellps=WGS84 +datum=WGS84 +units=m +no_defs +lat_0=38N +lon_0=127E\")\r\n\r\n#대한민국 행정구역 shp파일 통해 지도 그ㄹ기\r\nkorea_map_shp <- readShapePoly(\"TL_SCCO_EMD.shp\", verbose =T, proj4string =crsUTM_K)\r\nseoul_shape <- korea_map_shp[grep(\"^11\",korea_map_shp$EMD_CD),]\r\nsp:::plot(seoul_shape,axes =FALSE, bty=\"n\",border = \"gray90\", bg = \"gray30\" ,col =\"gray\",main = \"Public Bicycle Station Communities via Modularity Optimization\")\r\n\r\n#좌표 변환 \r\nxy.new <- spTransform(SpatialPoints(pub_bike_loc_m[3:2],proj4string = crsWGS84lonlat),crsUTM_K) \r\nxy.new_s <- spTransform(SpatialPoints(pub_bike_loc_s[3:2],proj4string = crsWGS84lonlat),crsUTM_K) \r\n\r\n#커뮤니티 index로 색깔 부여\r\ncommu_col <- as.factor(pub_bike_loc_m$commu)\r\ncol.rainbow <- rainbow(13)\r\npalette(\"default\")\r\n\r\n#############\r\nfor(i in 1:length(pub_bike_loc_m[,1])){\r\n points(as.data.frame(xy.new[i]),pch=20, col = as.numeric(pub_bike_loc_m$commu[i]) ,cex=0.8)\r\n}\r\n\r\n\r\n####################################################\r\n\r\n\r\nfor(i in 1:8){\r\n xy.new_a <- spTransform(SpatialPoints(pub_bike_loc_m[3:2][which(pub_bike_loc_m$commu==i),],proj4string = crsWGS84lonlat),crsUTM_K) \r\n sp:::plot(seoul_shape,axes =FALSE, bty=\"n\",border = \"gray90\", bg = \"gray30\" ,col =\"gray\", main = i)\r\n \r\n for(j in 1:length(xy.new_s)){\r\n points(as.data.frame(xy.new_s[j]),pch=20, col = as.numeric(df_s$commu[j]) ,cex=0.9)\r\n }\r\n}\r\n \r\n\r\nwrite.csv(pub_bike_loc_m, \"7-9월커뮤니티.csv\")\r\nwrite.csv(pub_bike_loc_s, \"7-9월커뮤니티_4커뮤.csv\")\r\n \r\n \r\n" }, { "alpha_fraction": 0.6781194806098938, "alphanum_fraction": 0.6999121308326721, "avg_line_length": 48.11453628540039, "blob_id": "599525b8b8e5382a62e0a0e09ba5f75d07dc57cf", "content_id": "36db566cb9883afaa84d0eaebc96b267c73cf629", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "R", "length_bytes": 11746, "license_type": "no_license", "max_line_length": 152, "num_lines": 227, "path": "/clustering_tidying_for_visualization.R", "repo_name": "ghmkt/ddareung", "src_encoding": "UTF-8", "text": "library(dplyr)\r\nlibrary(ggplot2)\r\nlibrary(NbClust)\r\nlibrary(reshape2)\r\nlibrary(tidyr)\r\n\r\nweekend_lent_tidyed <- as.tibble(read.csv(\"df_weekend_lent_tidyed.csv\", stringsAsFactors = FALSE))\r\nweekday_lent_tidyed <- as.tibble(read.csv(\"df_weekday_lent_tidyed.csv\", stringsAsFactors = FALSE))\r\nweekend_return_tidyed <- as.tibble(read.csv(\"df_weekend_return_tidyed.csv\", stringsAsFactors = FALSE))\r\nweekday_return_tidyed <- as.tibble(read.csv(\"df_weekday_return_tidyed.csv\", stringsAsFactors = FALSE))\r\n\r\n##merging data not considering month, only lent\r\n\r\nweekend_lent_tidyed_nomonth <- (weekend_lent_tidyed %>% group_by(lent_where) %>% summarise_all(sum))[,-2]\r\nweekday_lent_tidyed_nomonth <- (weekday_lent_tidyed %>% group_by(lent_where) %>% summarise_all(sum))[,-2]\r\n\r\nweekend_return_tidyed_nomonth <- (weekend_return_tidyed %>% group_by(return_where) %>% summarise_all(sum))[,-2]\r\nweekday_return_tidyed_nomonth <- (weekday_return_tidyed %>% group_by(return_where) %>% summarise_all(sum))[,-2]\r\n\r\nhead(weekend_return_tidyed_nomonth)\r\n\r\n## Since we want to cluster these spots with lent change in time series, scale each lent counts first.\r\n\r\nweekend_lent_tidyed_nomonth_scaled <- weekend_lent_tidyed_nomonth\r\nweekend_lent_tidyed_nomonth_scaled[,-1] <- t(scale(t(weekend_lent_tidyed_nomonth[,-1])))\r\n\r\nweekday_lent_tidyed_nomonth_scaled <- weekday_lent_tidyed_nomonth\r\nweekday_lent_tidyed_nomonth_scaled[,-1] <- t(scale(t(weekday_lent_tidyed_nomonth[,-1])))\r\n\r\nweekend_return_tidyed_nomonth_scaled <- weekend_return_tidyed_nomonth\r\nweekend_return_tidyed_nomonth_scaled[,-1] <- t(scale(t(weekend_return_tidyed_nomonth[,-1])))\r\n\r\nweekday_return_tidyed_nomonth_scaled <- weekday_return_tidyed_nomonth\r\nweekday_return_tidyed_nomonth_scaled[,-1] <- t(scale(t(weekday_return_tidyed_nomonth[,-1])))\r\n\r\n\r\n## plot before clustering, let's see the entire data\r\n### with scaling\r\nweekend_lent_mean_whole <- weekend_lent_tidyed_nomonth_scaled %>% summarize_at( vars(-lent_where), mean )\r\nweekday_lent_mean_whole <- weekday_lent_tidyed_nomonth_scaled %>% summarize_at( vars(-lent_where), mean )\r\n\r\nall_lent_mean_whole <- rbind(weekend_lent_mean_whole, weekday_lent_mean_whole)\r\nall_lent_mean_whole$weekday <- c(\"weekend\", \"weekday\")\r\n\r\nggplot(melt(all_lent_mean_whole, id.vars = \"weekday\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=weekday, group =weekday)) + geom_point() + ggtitle(\"Lent\") +\r\ntheme(plot.title = element_text(family = \"serif\", face = \"bold\", hjust = 0.5, size = 20, color = \"darkblue\"))\r\n\r\nweekend_return_mean_whole <- weekend_return_tidyed_nomonth_scaled %>% summarize_at( vars(-return_where), mean )\r\nweekday_return_mean_whole <- weekday_return_tidyed_nomonth_scaled %>% summarize_at( vars(-return_where), mean )\r\n\r\nall_return_mean_whole <- rbind(weekend_return_mean_whole, weekday_return_mean_whole)\r\nall_return_mean_whole$weekday <- c(\"weekend\", \"weekday\")\r\n\r\nggplot(melt(all_return_mean_whole, id.vars = \"weekday\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=weekday, group =weekday)) + geom_point() + ggtitle(\"Return\") +\r\n theme(plot.title = element_text(family = \"serif\", face = \"bold\", hjust = 0.5, size = 20, color = \"darkblue\"))\r\n\r\n### without scaling\r\nweekend_lent_mean_whole_woscale <- weekend_lent_tidyed_nomonth %>% summarize_at( vars(-lent_where), mean )\r\nweekday_lent_mean_whole_woscale <- weekday_lent_tidyed_nomonth %>% summarize_at( vars(-lent_where), mean )\r\n\r\nall_lent_mean_whole_woscale <- rbind(weekend_lent_mean_whole_woscale, weekday_lent_mean_whole_woscale)\r\nall_lent_mean_whole_woscale$weekday <- c(\"weekend\", \"weekday\")\r\n\r\nggplot(melt(all_lent_mean_whole_woscale, id.vars = \"weekday\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=weekday, group =weekday)) + geom_point() + ggtitle(\"Lent_without_scaling\") +\r\n theme(plot.title = element_text(family = \"serif\", face = \"bold\", hjust = 0.5, size = 20, color = \"darkblue\"))\r\n\r\nweekend_return_mean_whole <- weekend_return_tidyed_nomonth_scaled %>% summarize_at( vars(-return_where), mean )\r\nweekday_return_mean_whole <- weekday_return_tidyed_nomonth_scaled %>% summarize_at( vars(-return_where), mean )\r\n\r\nall_return_mean_whole <- rbind(weekend_return_mean_whole, weekday_return_mean_whole)\r\nall_return_mean_whole$weekday <- c(\"weekend\", \"weekday\")\r\n\r\nggplot(melt(all_return_mean_whole, id.vars = \"weekday\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=weekday, group =weekday)) + geom_point() + ggtitle(\"Return\") +\r\n theme(plot.title = element_text(family = \"serif\", face = \"bold\", hjust = 0.5, size = 20, color = \"darkblue\"))\r\n\r\nwrite_excel_csv(all_lent_mean_whole_woscale, \"lent_by_hour_mean_789.csv\")\r\n\r\n\r\n\r\n\r\n\r\n### 시간별 특성으로 클러스터한 결과\r\n\r\n## Let's start clutering from now. We should find optimal k first.\r\n\r\n###find optimal k in weekend data\r\n#detect k\r\n##detect k by barplot\r\nweekend_lent_tidyed_nomonth_scaled[,-1] + 5\r\n\r\nnc <- NbClust((weekend_lent_tidyed_nomonth_scaled[,-1]), min.nc=2, max.nc=10, method=\"kmeans\")\r\npar(mfrow=c(1,1))\r\nbarplot(table(nc$Best.n[1,]),\r\n xlab=\"Numer of Clusters\", ylab=\"Number of Criteria\",\r\n main=\"Number of Clusters Chosen\")\r\n\r\n\r\n## Then, execute clustering and allocate the number of cluster in df.\r\n###WEEKEND\r\n### kmeans in weekend\r\n\r\nwe_kmeans2 <- kmeans(weekend_lent_tidyed_nomonth_scaled[,-1], centers = 2, iter.max = 10000)\r\nwe_cluster_k2<-we_kmeans2$cluster\r\nwe_kmeans3 <- kmeans(weekend_lent_tidyed_nomonth_scaled[,-1], centers = 3, iter.max = 10000)\r\nwe_cluster_k3<-we_kmeans3$cluster\r\nwe_kmeans4 <- kmeans(weekend_lent_tidyed_nomonth_scaled[,-1], centers = 4, iter.max = 10000)\r\nwe_cluster_k4<-we_kmeans4$cluster\r\nwe_kmeans5 <- kmeans(weekend_lent_tidyed_nomonth_scaled[,-1], centers = 5, iter.max = 10000)\r\nwe_cluster_k5<-we_kmeans5$cluster\r\n\r\n#### merge cluster_num with dataset and get means group by that cluster num\r\n\r\nwe_lent_tidyed_nomonth_scaled_cluster <- cbind(weekend_lent_tidyed_nomonth_scaled, we_cluster_k2, we_cluster_k3, we_cluster_k4, we_cluster_k5)\r\n\r\nwe_lent_mean_cluster2 <- we_lent_tidyed_nomonth_scaled_cluster[,1:26] %>% group_by(we_cluster_k2) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\nwe_lent_mean_cluster3 <- we_lent_tidyed_nomonth_scaled_cluster[,c(1:25,27)] %>% group_by(we_cluster_k3) %>% \r\nsummarize_at( vars(-lent_where), mean )\r\n\r\nwe_lent_mean_cluster4 <- we_lent_tidyed_nomonth_scaled_cluster[,c(1:25,28)] %>% group_by(we_cluster_k4) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\nwe_lent_mean_cluster5 <- we_lent_tidyed_nomonth_scaled_cluster[,c(1:25,29)] %>% group_by(we_cluster_k5) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\n\r\n#### Then, draw ggplot\r\n\r\nggplot(melt(we_lent_mean_cluster2, id.vars = \"we_cluster_k2\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=we_cluster_k2, group = we_cluster_k2)) + geom_point()\r\n\r\nggplot(melt(we_lent_mean_cluster3, id.vars = \"we_cluster_k3\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=we_cluster_k3, group = we_cluster_k3)) + geom_point()\r\n\r\nggplot(melt(we_lent_mean_cluster4, id.vars = \"we_cluster_k4\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=we_cluster_k4, group = we_cluster_k4)) + geom_point()\r\n\r\nggplot(melt(we_lent_mean_cluster5, id.vars = \"we_cluster_k5\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=we_cluster_k5, group = we_cluster_k5)) + geom_point()\r\n\r\n\r\n###WEEKDAY\r\n### kmeans in weekday\r\n\r\nwd_kmeans2 <- kmeans(weekday_lent_tidyed_nomonth_scaled[,-1], centers = 2, iter.max = 10000)\r\nwd_cluster_k2<-wd_kmeans2$cluster\r\nwd_kmeans3 <- kmeans(weekday_lent_tidyed_nomonth_scaled[,-1], centers = 3, iter.max = 10000)\r\nwd_cluster_k3<-wd_kmeans3$cluster\r\nwd_kmeans4 <- kmeans(weekday_lent_tidyed_nomonth_scaled[,-1], centers = 4, iter.max = 10000)\r\nwd_cluster_k4<-wd_kmeans4$cluster\r\nwd_kmeans5 <- kmeans(weekday_lent_tidyed_nomonth_scaled[,-1], centers = 5, iter.max = 10000)\r\nwd_cluster_k5<-wd_kmeans5$cluster\r\n\r\n#### merge cluster_num with dataset and get means group by that cluster num\r\n\r\nwd_lent_tidyed_nomonth_scaled_cluster <- cbind(weekday_lent_tidyed_nomonth_scaled, wd_cluster_k2, wd_cluster_k3, wd_cluster_k4, wd_cluster_k5)\r\n\r\nwd_lent_mean_cluster2 <- wd_lent_tidyed_nomonth_scaled_cluster[,1:26] %>% group_by(wd_cluster_k2) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\nwd_lent_mean_cluster3 <- wd_lent_tidyed_nomonth_scaled_cluster[,c(1:25,27)] %>% group_by(wd_cluster_k3) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\nwd_lent_mean_cluster4 <- wd_lent_tidyed_nomonth_scaled_cluster[,c(1:25,28)] %>% group_by(wd_cluster_k4) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\nwd_lent_mean_cluster5 <- wd_lent_tidyed_nomonth_scaled_cluster[,c(1:25,29)] %>% group_by(wd_cluster_k5) %>% \r\n summarize_at( vars(-lent_where), mean )\r\n\r\n\r\n#### Then, draw ggplot\r\n\r\nggplot(melt(wd_lent_mean_cluster2, id.vars = \"wd_cluster_k2\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=wd_cluster_k2, group = wd_cluster_k2)) + geom_point()\r\n\r\nggplot(melt(wd_lent_mean_cluster3, id.vars = \"wd_cluster_k3\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=wd_cluster_k3, group = wd_cluster_k3)) + geom_point()\r\n\r\nggplot(melt(wd_lent_mean_cluster4, id.vars = \"wd_cluster_k4\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=wd_cluster_k4, group = wd_cluster_k4)) + geom_point()\r\n\r\nggplot(melt(wd_lent_mean_cluster5, id.vars = \"wd_cluster_k5\"), aes(x= variable, y=value)) + #melt 써서 데이터 형식 바꿔줘야 ggplot 가능\r\n geom_line(aes(colour=wd_cluster_k5, group = wd_cluster_k5)) + geom_point()\r\n\r\n\r\n##data for visualization\r\n#서론, 주빈요청\r\n\r\ndf_stock_tidyedbyhour <- df_stock_tidyedbytime %>% group_by(weekend, hour) %>% \r\n summarize(under_1_sta_pro_mean_ = mean(under_1_sta_pro_mean))\r\n\r\nwrite_excel_csv(df_stock_tidyedbyhour, \"present_for_jubin_1ordown_mean.csv\")\r\n\r\n\r\n#본론 1, 시간대 관련\r\n\r\ndf_stock_withrest_tidyedbytime\r\ndf_stock_over90_tidyedbyhour <- df_stock_withrest_tidyedbytime %>% group_by(weekend, hour) %>% summarize(over_90_pro_mean = mean(over_90_sta_pro_mean))\r\n\r\nall_lent_mean_whole_woscale_ <- melt(all_lent_mean_whole_woscale)\r\nall_lent_mean_whole_woscale_$hour <- rep(0:23, each=2)\r\nall_lent_mean_whole_woscale_ <- all_lent_mean_whole_woscale_[,c(1,4,3)]\r\n\r\nall_lent_mean_whole_woscale_[all_lent_mean_whole_woscale_$weekday == \"weekend\",1] <- TRUE\r\nall_lent_mean_whole_woscale_[all_lent_mean_whole_woscale_$weekday == \"weekday\",1] <- FALSE\r\ncolnames(all_lent_mean_whole_woscale_)[1] <- \"weekend\"\r\n\r\ndf_stock_tidyedbyhour$hour <- as.integer(df_stock_tidyedbyhour$hour)\r\n\r\n\r\nall_lent_mean_whole_woscale_ <- as.tibble(all_lent_mean_whole_woscale_)\r\ncolnames(all_lent_mean_whole_woscale_)[3] <- \"lent_count_mean\"\r\n\r\n\r\nall_lent_mean_whole_woscale_$weekend <- as.logical(all_lent_mean_whole_woscale_$weekend)\r\ndf_stock_under1_tidyedbyhour\r\ndf_stock_over90_tidyedbyhour$hour <- as.integer(df_stock_over90_tidyedbyhour$hour)\r\n\r\nmain_1_visualization <- inner_join(all_lent_mean_whole_woscale_, df_stock_under1_tidyedbyhour)\r\nmain_1_visualization_ <- inner_join(main_1_visualization, df_stock_over90_tidyedbyhour)\r\n\r\nwrite_excel_csv(main_1_visualization_, \"main_1_visualization.csv\")\r\n\r\n\r\n" } ]	4
jzry/text-alert	https://github.com/jzry/text-alert	e2c6afb9d9cab20e8eecd151f524d0d642817e47	fd0ffa9bdc7c1c2649cbe24d53ca93d7becd0b07	dae76fc43c6f30c8905c8b4998899c5386ca08a9	refs/heads/main	2023-07-17T14:11:20.903583	2021-09-06T15:20:34	2021-09-06T15:20:34	387,877,065	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6846542954444885, "alphanum_fraction": 0.6885890960693359, "avg_line_length": 27.238094329833984, "blob_id": "e1951825704489b0720dae54c2a6280055e45541", "content_id": "8c2562db412d6ceefe0f157107909ea3213dcede", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3558, "license_type": "no_license", "max_line_length": 104, "num_lines": 126, "path": "/text-alert/alert.py", "repo_name": "jzry/text-alert", "src_encoding": "UTF-8", "text": "# SCRIPT TO SEND MESSAGES THROUGH GOOGLE'S GMAIL SMTP SERVER\n\nimport email, smtplib, ssl\n\nfrom email import encoders\nfrom email.mime.base import MIMEBase\nfrom email.mime.image import MIMEImage\nfrom email.mime.multipart import MIMEMultipart\nfrom email.mime.text import MIMEText\n\nfrom os.path import basename\n\nfrom etext.providers import PROVIDERS\nfrom etext.exceptions import (ProviderNotFoundException, NoMMSSupportException, NumberNotValidException)\n\n\n# Check if a number is 10 digits long.\ndef validate_number(number: str):\n\n num = \"\"\n\n # Valid phone number is 10 digits.\n for character in number:\n if character.isdigit():\n num += character\n\n # Find the length of the phone number.\n if len(num) == 10:\n return num\n\n # Number is invalid.\n raise NumberNotValidException(number)\n\n\n# Return the proper provider formatting.\ndef format_provider_email(number: str, provider: str, mms=False):\n\n # Get the service provider (AT&T, T-Mobile, Verizon, etc).\n provider_info = PROVIDERS.get(provider)\n\n # Error catching.\n if provider_info == None:\n raise ProviderNotFoundException(provider)\n\n # Find the domain for the service provider.\n domain = provider_info.get(\"sms\")\n\n # See if the service provider accepts mms.\n if mms:\n mms_domain = provider_info.get(\"mms\")\n\n # Only causes exception if mms is not supported.\n if not (mms_support = provider_info.get(\"mms_support\")):\n raise NoMMSSupportException(provider)\n\n # Use mms domain if provider allows.\n if mms_domain:\n domain = mms_domain\n\n return f\"{number}@{domain}\"\n\n# Send SMS (Text) with email (Google's SMTP server).\ndef send_sms_via_email\n(\nnumber: str,\nmessage: str,\nprovider: str,\nsender_credentials: tuple,\nsubject: str = \"AlertBot\",\nsmtp_server: str = \"smtp.gmail.com\",\nsmtp_port: int = 465\n):\n\n number = validate_number(number)\n sender_email, email_password = sender_credentials\n receiver_email = format_provider_email(number, provider)\n\n email_message = f\"Subject: {subject}\\nTo:{receiver_email}\\n{message}\"\n\n with smtplib.SMTP_SSL(smtp_server, smtp_port, context=ssl.create_default_context()) as email:\n email.login(sender_email, email_password)\n email.sendmail(sender_email, receiver_email, email_message)\n\n# Send MMS (Images) with email\ndef send_mms_via_email\n(\nnumber: str,\nmessage: str,\nfile_path: str,\nmime_maintype: str,\nmime_subtype: str,\nprovider: str,\nsender_credentials: tuple,\nsubject: str = \"sent using etext\",\nsmtp_server: str = \"smtp.gmail.com\",\nsmtp_port: int = 465,\n):\n\n number = validate_number(number)\n sender_email, email_password = sender_credentials\n receiver_email = _address(number, provider, mms=True)\n\n email_message = MIMEMultipart()\n email_message[\"Subject\"] = subject\n email_message[\"From\"] = sender_email\n email_message[\"To\"] = receiver_email\n\n email_message.attach(MIMEText(message, \"plain\"))\n\n with open(file_path, \"rb\") as attachment:\n part = MIMEBase(mime_maintype, mime_subtype)\n part.set_payload(attachment.read())\n\n encoders.encode_base64(part)\n part.add_header(\n \"Content-Disposition\",\n f\"attachment; filename={basename(file_path)}\",\n )\n\n email_message.attach(part)\n\n text = email_message.as_string()\n\n with smtplib.SMTP_SSL(smtp_server, smtp_port, context=ssl.create_default_context()) as email:\n email.login(sender_email, email_password)\n email.sendmail(sender_email, receiver_email, text)\n" }, { "alpha_fraction": 0.6511628031730652, "alphanum_fraction": 0.6860465407371521, "avg_line_length": 27.66666603088379, "blob_id": "192cbed0ad262b1709c6525999261bd042969731", "content_id": "2c17929dc538eb2d69c4b4d3f721e17f4c17ea57", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 86, "license_type": "no_license", "max_line_length": 62, "num_lines": 3, "path": "/text-alert/__init__.py", "repo_name": "jzry/text-alert", "src_encoding": "UTF-8", "text": "from .text-alert import send_sms_via_email, send_mms_via_email\n\n__version__ = \"0.0.1\"\n" } ]	2
chernyshovmaksim/parser-blog-sadovoda	https://github.com/chernyshovmaksim/parser-blog-sadovoda	ad14a86c91bb910903997bd9cb8c0970932b9ac0	92d937acc12c4462761815a9c2bf563a30fcd1ec	14e980a293cb7e2f1d3efac2b4c787149568c0af	refs/heads/master	2022-12-28T22:36:37.502555	2020-10-14T12:45:55	2020-10-14T12:45:55	304,012,661	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.550463855266571, "alphanum_fraction": 0.5735170245170593, "avg_line_length": 33.153846740722656, "blob_id": "fd6ed39d1f4b5f6d4f61f391dde2e9037247a795", "content_id": "d05eafc7eac6ddb3afe7e45c1a647b7d60dce484", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3700, "license_type": "no_license", "max_line_length": 144, "num_lines": 104, "path": "/main.py", "repo_name": "chernyshovmaksim/parser-blog-sadovoda", "src_encoding": "UTF-8", "text": "import requests\nimport csv\nfrom bs4 import BeautifulSoup\n\n\n\nHOST = 'https://web.archive.org/web/20160610111630/http://www.blog-sadovoda.ru/'\nURL = 'https://web.archive.org/web/20160610111630/http://www.blog-sadovoda.ru/category/blogoustrojstvo/'\nHEADERS = {\n 'accept' : 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,/;q=0.8,application/signed-exchange;v=b3;q=0.9',\n 'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Atom/8.1.0.31 Safari/537.36'\n} \n\nposts_links = []\nposts = []\n\ndef get_html(url, params=''):\n req = requests.get(url, headers=HEADERS, params=params)\n return req\n\n\ndef get_content(html):\n soup = BeautifulSoup(html, 'html.parser')\n items = soup.find_all('div', class_='post')\n\n for item in items:\n posts_links.append(\n item.find('h2').find('a').get('href')\n )\n\n\n\n\ndef parser_links():\n html = get_html(URL)\n if html.status_code == 200:\n print(\"Status: \" + str(html.status_code))\n \n page = BeautifulSoup(html.text, 'html.parser')\n get_content(html.text)\n print(f'Спарсили ссылки с главной страницы ✅')\n\n next_link = page.find('div', class_='nav-next').find('a')\n\n if next_link:\n for i in range(2, int(MAX_PAGES)):\n page_in_pagination = get_html(URL + f'page/{i}/')\n if page_in_pagination.status_code == 200:\n get_content(page_in_pagination.text)\n print(f'Спарсили ссылки со страницы: {i} ✅')\n else:\n break\n print('Сбор ссылок окончен')\n\n else:\n print(\"Status: \" + str(html.status_code))\n\n\n\ndef parser_contents():\n i = 0\n for link in posts_links:\n html = get_html(HOST + link)\n soup = BeautifulSoup(html.text)\n\n # POST TITLE\n if soup.find('div', class_='entry').find('h2'):\n post_title = soup.find('div', class_='entry').find('h2').get_text(strip=True)\n else:\n post_title = soup.find('div', class_='entry').find('h1').get_text(strip=True)\n\n # POST CONTENT\n post_content = soup.find('div', class_='post-content')\n if post_content.find('div', class_='crp_related'):\n post_content.find('div', class_='crp_related').decompose()\n if post_content.find('div', class_='likes'):\n post_content.find('div', class_='likes').decompose()\n if post_content.find_all('script'):\n for script in post_content.find_all('script'):\n script.decompose()\n if post_content.find('div', id='ya_direct'):\n post_content.find('div', id='ya_direct').decompose()\n if post_content.find('h3', class_='related_post_title'):\n post_content.find('h3', class_='related_post_title').decompose()\n if post_content.find('ul', class_='related_post'):\n post_content.find('ul', class_='related_post').decompose()\n if post_content.find_all('div', class_='yashare-auto-init'):\n for el in post_content.find_all('div', class_='yashare-auto-init'):\n el.decompose()\n\n posts.append({\n 'title' : post_title,\n 'content' : post_content \n })\n\n i = i + 1\n print(f'Страница #{i} - {post_title} ✔️✔️✔️')\n\n\nif __name__ == \"__main__\":\n MAX_PAGES = input('Укажите максимальное колличество страниц для парсинга - ')\n parser_links()\n parser_contents()\n print(posts)\n \n" } ]	1
automata/ovo	https://github.com/automata/ovo	3cf5b80e36da26fe02a9da1dcad4e969266a44aa	fab04f711137624cf3e4b3173d2070c9a3111b47	909563ed99039935c6028197dea2fac189272aa0	refs/heads/master	2021-01-10T20:36:15.251528	2014-09-17T21:01:42	2014-09-17T21:01:42	24,148,042	0	1	null	2014-09-17T14:27:28	2014-09-17T14:27:37	2014-09-17T21:02:37	Python	[ { "alpha_fraction": 0.6875, "alphanum_fraction": 0.7259615659713745, "avg_line_length": 16.41666603088379, "blob_id": "1b64cc0bc80ee982ccbe1b3688727eba80e1302a", "content_id": "7bb9541ad553790cf63319d3f453bf25445ecbe5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 208, "license_type": "no_license", "max_line_length": 42, "num_lines": 12, "path": "/00_test_sift_lenna.py", "repo_name": "automata/ovo", "src_encoding": "UTF-8", "text": "import cv2\n\nimg = cv2.imread('data/Lenna.jpg')\n\ngray= cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)\n\nsift = cv2.SIFT()\nkp = sift.detect(gray,None)\n\nimg=cv2.drawKeypoints(gray,kp)\n\ncv2.imwrite('out/Lenna_sift.jpg',img)" }, { "alpha_fraction": 0.5680902600288391, "alphanum_fraction": 0.6039484143257141, "avg_line_length": 30.40506362915039, "blob_id": "312ecfc82c2ff6e6b43c6418346977b0486e1ccb", "content_id": "21e4d77cfba6b89185ab2937b29a89a632e188e6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2482, "license_type": "no_license", "max_line_length": 104, "num_lines": 79, "path": "/04_haarface_contour_features_video_out.py", "repo_name": "automata/ovo", "src_encoding": "UTF-8", "text": "import cv2\nimport numpy as np\n\nface_cascade = cv2.CascadeClassifier('data/haarcascade_frontalface_default.xml')\neye_cascade = cv2.CascadeClassifier('data/haarcascade_eye.xml')\n\ncap = cv2.VideoCapture(0)\n\n# Sets camera to 320x240\nret = cap.set(3,320)\nret = cap.set(4,240)\n\n# Output video\nout = cv2.VideoWriter('output.mov',cv2.cv.CV_FOURCC('m','p','4','v'), 20.0, (320,240))\n\n# Output data\nout_file = open('output.txt', 'w')\nframe_counter = 0\nwhile(True):\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n # Our operations on the frame come here\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n\n # Find faces\n faces = face_cascade.detectMultiScale(gray, 1.3, 5)\n\n for (x,y,w,h) in faces:\n # Face ROI\n img = cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)\n roi_gray = gray[y:y+h, x:x+w]\n roi_color = frame[y:y+h, x:x+w]\n \n # Convert to binary by threshold\n ret,thresh = cv2.threshold(roi_gray,0,255,0,1)\n # Find contours\n contours,hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n \n if len(contours) > 0:\n # By hierarchy, we get just the first (bigger) contour\n cnt = contours[0]\n img = cv2.drawContours(roi_color, [cnt], -1, (0,255,0), 3)\n\n # Image moments\n #M = cv2.moments(cnt)\n\n #if M['m00'] > 0:\n #centroid_x = int(M['m10']/M['m00'])\n #centroid_y = int(M['m01']/M['m00'])\n # Some features (area, perimeter, angle)\n area = cv2.contourArea(cnt)\n perimeter = cv2.arcLength(cnt,True)\n #angle = '?'\n #if len(cnt) >= 5:\n # (x,y),(MA,ma),angle = cv2.fitEllipse(cnt)\n # Create a mask to make it possible to find its mean value of color\n #mask = np.zeros(roi_gray.shape,np.uint8)\n #pixelpoints = np.transpose(np.nonzero(mask))\n #mean_val = cv2.mean(roi_gray, mask = mask)\n #print 'Centroid: (%s,%s). Area: %d. Perimeter: %d.' % (centroid_x, centroid_y, area, perimeter)\n #print [frame_counter, area, perimeter, x, y]\n out_file.write(\"%s\\n\" % [frame_counter, area, perimeter, x, y])\n # Write to file\n #if ret==True:\n # Write the flipped frame\n out.write(frame)\n\n # Display the resulting frame\n cv2.imshow('frame', frame)\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break\n frame_counter += 1\n\n# When everything done, release the capture\ncap.release()\nout.release()\nout_file.close()\ncv2.destroyAllWindows()\n\n" }, { "alpha_fraction": 0.7297297120094299, "alphanum_fraction": 0.7297297120094299, "avg_line_length": 17.75, "blob_id": "c95ed584d2aeb11bfc1f07df8c73486f226fb953", "content_id": "be217d9255cf7032a9c1159f1048b7a7e568dd33", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 74, "license_type": "no_license", "max_line_length": 46, "num_lines": 4, "path": "/README.md", "repo_name": "automata/ovo", "src_encoding": "UTF-8", "text": "OvO - Ouvir para Olhar\n===\n\nMore details: https://etherpad.mozilla.org/ovo" }, { "alpha_fraction": 0.6062718033790588, "alphanum_fraction": 0.6533101201057434, "avg_line_length": 18.827587127685547, "blob_id": "a3d287e9e34ec3d225715f298bba723b5fc35e51", "content_id": "f4cb151d23e78c48f0a190eaf8c2320450421498", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 574, "license_type": "no_license", "max_line_length": 50, "num_lines": 29, "path": "/01_test_opencv.py", "repo_name": "automata/ovo", "src_encoding": "UTF-8", "text": "import cv2\n\ncap = cv2.VideoCapture(0)\nsift = cv2.SIFT()\n\n# Sets camera to 320x240\nret = cap.set(3,320)\nret = cap.set(4,240)\n\nwhile(True):\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n # Our operations on the frame come here\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n\n # SIFT\n kp = sift.detect(gray,None)\n\n img = cv2.drawKeypoints(gray,kp)\n\n # Display the resulting frame\n cv2.imshow('frame',img)\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break\n\n# When everything done, release the capture\ncap.release()\ncv2.destroyAllWindows()" } ]	4
stakiran/test_previewlimitsize	https://github.com/stakiran/test_previewlimitsize	c344676bde45fb516c95af17a2932f1cfae7f403	9642d49d541ac4203e8cb169a65edc3986c073e8	8b33d4d2530b9d16ccbee114df8104979b646d0a	refs/heads/master	2020-12-10T03:14:13.906028	2017-06-27T13:58:47	2017-06-27T13:58:47	95,448,546	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.550561785697937, "alphanum_fraction": 0.6891385912895203, "avg_line_length": 25.700000762939453, "blob_id": "2d235d5093ae25ecf6d0a843ea84add1963ca0bc", "content_id": "0f85dd92d9a56d57a33697a3216ece5d9ff0cc9c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 267, "license_type": "no_license", "max_line_length": 70, "num_lines": 10, "path": "/README.md", "repo_name": "stakiran/test_previewlimitsize", "src_encoding": "UTF-8", "text": "# test_previewlimitsize\nWhat is the limit size of text not to be previewed on GitHub.com repo?\n\n## Conclusion\nJust more over 1MB.\n\n## Steps\n- 1. `10241024-(24+1) = 1048551`\n- 2. `python -c \"print 'a'1048551\" > 1048551.txt`\n- 3. Add the content of 2. to skeleton.py\n" }, { "alpha_fraction": 0.625, "alphanum_fraction": 0.6666666865348816, "avg_line_length": 11, "blob_id": "cd31a68ef41610efc1b4bf7eca82647c5e2b3640", "content_id": "3846e0d6a6930fcb45299037fa2c5a6f6d339b85", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 24, "license_type": "no_license", "max_line_length": 15, "num_lines": 2, "path": "/skeleton.py", "repo_name": "stakiran/test_previewlimitsize", "src_encoding": "UTF-8", "text": "# coding: utf-8\nprint a\n" } ]	2
kainhuck/WebCrawlerTools	https://github.com/kainhuck/WebCrawlerTools	cd3edb0d8ac6a114835f69090a5253c2e3c62544	9f2ba028412ea793ca576358d53e1ae57ba9a213	1b6423a0bb3bc719c06872c3d9b35081cffa26a8	refs/heads/master	2020-07-10T13:36:34.442164	2020-02-08T10:50:45	2020-02-08T10:50:45	204,274,351	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.779411792755127, "alphanum_fraction": 0.779411792755127, "avg_line_length": 12.600000381469727, "blob_id": "4283636647d2e9ec62fcf1d75cf545788dabe22a", "content_id": "289ce8e107c19de780cf6162cbb5abe03d7b8b2c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 88, "license_type": "no_license", "max_line_length": 33, "num_lines": 5, "path": "/README.md", "repo_name": "kainhuck/WebCrawlerTools", "src_encoding": "UTF-8", "text": "# WebCrawlerTools\nsome little tools for web crawler\n\n\n## 欢迎大家提出修改意见\n" }, { "alpha_fraction": 0.4127764105796814, "alphanum_fraction": 0.45945945382118225, "avg_line_length": 21.823530197143555, "blob_id": "f9c3ab3905732761b13631fadf40b88731b9053f", "content_id": "0e05f8f601491739f2aebc83c48e4342a69fde7f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 435, "license_type": "no_license", "max_line_length": 46, "num_lines": 17, "path": "/mytools/manager.py", "repo_name": "kainhuck/WebCrawlerTools", "src_encoding": "UTF-8", "text": "\r\n\r\ndef split_job(length, sep=1):\r\n '''\r\n 将给定的长度length分成sep份,用于多线程\r\n return:\r\n [(0, 5), (5, 10), (10, 15), (15, 20)]\r\n '''\r\n job_list = []\r\n b = length // sep\r\n for i in range(sep):\r\n job_list.append((i * b, i * b + b))\r\n if length % sep:\r\n job_list.append((b * sep, length + 1))\r\n\r\n return job_list\r\n\r\nif __name__ == '__main__':\r\n print(split_job(101, 5))" } ]	2
Tomcli/refarch-reefer-ml	https://github.com/Tomcli/refarch-reefer-ml	013a2a8108e8bcd1131a5ec9cffbe74df730ed8c	40a527d8451b9ee50e8b8862ca257ba342a60b43	a4faeb9ba818eb111d720e1823a028c24b734da7	refs/heads/master	2020-07-23T16:43:03.511196	2019-09-05T00:12:29	2019-09-05T00:12:29	207,634,362	0	0	null	2019-09-10T18:31:20	2019-09-10T18:31:22	2019-10-02T16:22:59	null	[ { "alpha_fraction": 0.6612903475761414, "alphanum_fraction": 0.7043010592460632, "avg_line_length": 36.20000076293945, "blob_id": "ab2c85a3697d4c8138d1273c1c8516f228538992", "content_id": "d3ed5cc7a8a92b2c1a9624e349b4f05e288e39c4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 186, "license_type": "no_license", "max_line_length": 49, "num_lines": 5, "path": "/simulator/runReeferSimulatorApp.sh", "repo_name": "Tomcli/refarch-reefer-ml", "src_encoding": "UTF-8", "text": "source ../scripts/setenv.sh NOSET\ndocker run -p 8080:8080 -e KAFKA_ENV=$KAFKA_ENV \\\n -e KAFKA_BROKERS=$KAFKA_BROKERS \\\n -e KAFKA_APIKEY=$KAFKA_APIKEY \\\n ibmcase/reefersimulator\n" }, { "alpha_fraction": 0.7209302186965942, "alphanum_fraction": 0.7209302186965942, "avg_line_length": 85.33333587646484, "blob_id": "aca13c5bee602eb971ddd4b9c1d7baf603d1690b", "content_id": "fa15e02d6713d21c455e597fef85b75aa7f2308c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 258, "license_type": "no_license", "max_line_length": 212, "num_lines": 3, "path": "/scoring/runScoringApp.sh", "repo_name": "Tomcli/refarch-reefer-ml", "src_encoding": "UTF-8", "text": "#!/bin/bash\nsource ../scripts/setenv.sh NOSET\ndocker run -e KAFKA_BROKERS=$KAFKA_BROKERS -e KAFKA_APIKEY=$KAFKA_APIKEY -e KAFKA_ENV=$KAFKA_ENV -v $(pwd)/..:/home -ti ibmcase/python bash -c \"cd /home/scoring && export PYTHONPATH=/home && python ScoringApp.py\"" }, { "alpha_fraction": 0.6518691778182983, "alphanum_fraction": 0.6658878326416016, "avg_line_length": 25.8125, "blob_id": "2be829b190a75dff81515789207c8950f0abdc62", "content_id": "8f43cebdf56a1374c4d677f94572c9d3479830c1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 428, "license_type": "no_license", "max_line_length": 64, "num_lines": 16, "path": "/consumer/TraceContainerEventsApp.py", "repo_name": "Tomcli/refarch-reefer-ml", "src_encoding": "UTF-8", "text": "import os,sys\nfrom ContainerEventsListener import ContainerEventsListener\n\nCID=\"100\"\ndef parseArguments():\n if len(sys.argv) != 2:\n print(\"Need to have at least one argument container ID\")\n exit(1)\n CID = sys.argv[1]\n print(\"The arguments are: \" , str(sys.argv))\n\nif __name__ == '__main__':\n parseArguments()\n consumer = ContainerEventsListener()\n consumer.processEvents(CID)\n consumer.close()" }, { "alpha_fraction": 0.8311111330986023, "alphanum_fraction": 0.8311111330986023, "avg_line_length": 55.25, "blob_id": "55901cf79aa6e343dc0df4cc9e65725dc4f63d0e", "content_id": "6e9f9d58f84605eb828ac105635957a6f7fb6251", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 225, "license_type": "no_license", "max_line_length": 66, "num_lines": 4, "path": "/scoring/os-setenv.sh", "repo_name": "Tomcli/refarch-reefer-ml", "src_encoding": "UTF-8", "text": "source ../scripts/setenv.sh NOSET\noc set env dc/reeferpredictivescoring KAFKA_BROKERS=$KAFKA_BROKERS\noc set env dc/reeferpredictivescoring KAFKA_ENV=$KAFKA_ENV\noc set env dc/reeferpredictivescoring KAFKA_APIKEY=$KAFKA_APIKEY\n" }, { "alpha_fraction": 0.8809523582458496, "alphanum_fraction": 0.8809523582458496, "avg_line_length": 7.599999904632568, "blob_id": "a6fcc4a3639927f29baa83ee1b61bd8439d2c662", "content_id": "b9e4b6c7f14759dc2444b12d7d451905ccc63439", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 42, "license_type": "no_license", "max_line_length": 15, "num_lines": 5, "path": "/scoring/requirements.txt", "repo_name": "Tomcli/refarch-reefer-ml", "src_encoding": "UTF-8", "text": "numpy\npandas\nscipy\nsklearn\nconfluent_kafka" }, { "alpha_fraction": 0.6688963174819946, "alphanum_fraction": 0.6722407937049866, "avg_line_length": 41.85714340209961, "blob_id": "ae80a8a0c146e4ea639aa858e688e51af35048ae", "content_id": "1792328501ee081df3ce53e7ef15fe485c3ab18d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 299, "license_type": "no_license", "max_line_length": 98, "num_lines": 7, "path": "/consumer/runContainerConsumer.sh", "repo_name": "Tomcli/refarch-reefer-ml", "src_encoding": "UTF-8", "text": "#!/bin/bash\nsource ../scripts/setenv.sh NOSET\ndocker run -e KAFKA_BROKERS=$KAFKA_BROKERS \\\n -e KAFKA_APIKEY=$KAFKA_APIKEY \\\n -e KAFKA_ENV=$KAFKA_ENV \\\n -v $(pwd)/..:/home -ti ibmcase/python \\\n bash -c \"cd /home/consumer && export PYTHONPATH=/home && python TraceContainerEventsApp.py $1\"" } ]	6
erobakiewicz/e_learning_Djagno3	https://github.com/erobakiewicz/e_learning_Djagno3	bf7a253bfed26efac84d3d1cdaa8f7bdf170082a	04ab7a02623cd8cce12a18d6706aeb208d325500	3632f45078a19a56ca24d3fc4e50f8964510314d	refs/heads/master	2023-02-09T23:42:28.682621	2021-01-10T17:46:50	2021-01-10T17:46:50	318,857,287	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6165550947189331, "alphanum_fraction": 0.6226415038108826, "avg_line_length": 40.07500076293945, "blob_id": "ad6f884cd2a79235cea0808e6e93c9bc45a621e2", "content_id": "a0464038ca6bffbdf0455c45a935ad585e7d7318", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1643, "license_type": "no_license", "max_line_length": 96, "num_lines": 40, "path": "/courses/fields.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "from django.core.exceptions import ObjectDoesNotExist\nfrom django.db import models\n\n\"\"\"\ncustom django model field OrederField. it has optional for_fields param which is ordering\nby overriding pre_save method:\n1. checking if value already exist\n2. Build queryset to retrive all obj of model \n3. if there are any names in for_fields attr and filter the queryset by the current value of\nmodel fields in for_fields\n4. retrive obj with the highest (latest) order, if there is none order att is set to 0\n5. else if there is an obj +1 is added to order attr\n6. in setattr() order is calculated and set\n\"\"\"\n\n\nclass OrderField(models.PositiveIntegerField):\n def __init__(self, for_fields=None, args, kwargs):\n self.for_fields = for_fields\n super().__init__(args, kwargs)\n\n def pre_save(self, model_instance, add):\n if getattr(model_instance, self.attname) is None:\n # no current value\n try:\n qs = self.model.objects.all()\n if self.for_fields:\n # filter by objects with the same field values\n # for the fields in \"for_fields\"\n query = {field: getattr(model_instance, field) for field in self.for_fields}\n qs = qs.filter(query)\n # get the order of the last item\n last_item = qs.latest(self.attname)\n value = last_item.order + 1\n except ObjectDoesNotExist:\n value = 0\n setattr(model_instance, self.attname, value)\n return value\n else:\n return super().pre_save(model_instance, add)\n" }, { "alpha_fraction": 0.604627788066864, "alphanum_fraction": 0.604627788066864, "avg_line_length": 32.150001525878906, "blob_id": "0c8f84780a5479021fc6e44f9733159d660a5113", "content_id": "a30aae81cbe87a80e45e1a0176531a70f32cf3d2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1988, "license_type": "no_license", "max_line_length": 80, "num_lines": 60, "path": "/chat/consumers.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "import json\n\nfrom channels.generic.websocket import AsyncWebsocketConsumer\nfrom django.utils import timezone\n\n\nclass ChatConsumer(AsyncWebsocketConsumer):\n \"\"\"\n Consumer to connect, disconnect and receive messages text as jsons\n by the key and then echo it via self.send().\n ChatConsumer is using asyncwebsocket for asynchronous calls\n async def + await: for async functioning\n \"\"\"\n\n async def connect(self):\n \"\"\"\n async_to_sync(): wraps calls to asynchronous channel layer\n Retrieve id of course for chat, build chat for course and name it,\n provide \"add to chat\" functionality, keep the call by self.accept() with\n WebSocket connection.\n :return:\n \"\"\"\n self.user = self.scope['user']\n self.id = self.scope['url_route']['kwargs']['course_id']\n self.room_group_name = 'chat_%s' % self.id\n # join room group\n await self.channel_layer.group_add(\n self.room_group_name,\n self.channel_name\n )\n # accept connection\n await self.accept()\n\n async def disconnect(self, close_code):\n # leave room group\n await self.channel_layer.group_discard(\n self.room_group_name,\n self.channel_name\n )\n\n # receive message from WebSocket\n async def receive(self, text_data):\n text_data_json = json.loads(text_data)\n message = text_data_json['message']\n now = timezone.now()\n # send message to room group\n await self.channel_layer.group_send(\n self.room_group_name,\n {\n 'type': 'chat_message',\n 'message': message,\n 'user': self.user.username,\n 'datetime': now.isoformat()\n }\n )\n\n # retrieve message from room group\n async def chat_message(self, event):\n # send message to WebSocket, match \"type\" key with group\n await self.send(text_data=json.dumps(event))" }, { "alpha_fraction": 0.5716845989227295, "alphanum_fraction": 0.5734767317771912, "avg_line_length": 36.20000076293945, "blob_id": "b5bba882c87ddd1e50003c552324ee54a628de8d", "content_id": "7327967b6e1affe1bb5cade96e154213cf106ad7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 558, "license_type": "no_license", "max_line_length": 80, "num_lines": 15, "path": "/courses/forms.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "from django.forms import inlineformset_factory\n\nfrom courses.models import Course, Module\n\n\"\"\"\nFormset to validate all forms\nfields: fields included in all forms\nextra: number of extra empty forms to display\ncan_delete: if True Django will display checkbox input to mark objects to delete\n\"\"\"\nModuleFormSet = inlineformset_factory(Course,\n Module,\n fields=['title', 'description'],\n extra=2,\n can_delete=True)\n" }, { "alpha_fraction": 0.6700815558433533, "alphanum_fraction": 0.6832531690597534, "avg_line_length": 25.870786666870117, "blob_id": "f31caf3fb1347fc76ca99cfe82482a93a08d192c", "content_id": "9bb49cad2e73f008eb3137ce0dbd097d73c6b238", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4783, "license_type": "no_license", "max_line_length": 91, "num_lines": 178, "path": "/e_learning_Django3/settings.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "\"\"\"\nDjango settings for e_learning_Django3 project.\n\nGenerated by 'django-admin startproject' using Django 3.1.4.\n\nFor more information on this file, see\nhttps://docs.djangoproject.com/en/3.1/topics/settings/\n\nFor the full list of settings and their values, see\nhttps://docs.djangoproject.com/en/3.1/ref/settings/\n\"\"\"\nimport os\nfrom pathlib import Path\n\n# Build paths inside the project like this: BASE_DIR / 'subdir'.\nimport redis\nfrom django.urls import reverse_lazy\n\nBASE_DIR = Path(__file__).resolve().parent.parent\n\n# Quick-start development settings - unsuitable for production\n# See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/\n\nimport environ\n\nenv = environ.Env(\n # set casting, default value\n DEBUG=(bool, False)\n)\n# reading .env file\nenviron.Env.read_env()\n\n# False if not in os.environ\nDEBUG = env('DEBUG')\n\n# Raises django's ImproperlyConfigured exception if SECRET_KEY not in os.environ\nSECRET_KEY = env('SECRET_KEY')\n# SECURITY WARNING: keep the secret key used in production secret!\n\nALLOWED_HOSTS = ['e-learning-django3.herokuapp.com','127.0.0.1']\n\n# Application definition\n\nINSTALLED_APPS = [\n 'courses.apps.CoursesConfig',\n 'django.contrib.admin',\n 'django.contrib.auth',\n 'django.contrib.contenttypes',\n 'django.contrib.sessions',\n 'django.contrib.messages',\n 'django.contrib.staticfiles',\n 'students.apps.StudentsConfig',\n 'embed_video',\n 'memcache_status',\n 'rest_framework',\n 'chat',\n 'channels',\n\n]\n\nMIDDLEWARE = [\n 'django.middleware.security.SecurityMiddleware',\n 'django.contrib.sessions.middleware.SessionMiddleware',\n # 'django.middleware.cache.UpdateCacheMiddleware',\n 'django.middleware.common.CommonMiddleware',\n # 'django.middleware.cache.FetchFromCacheMiddleware',\n 'django.middleware.csrf.CsrfViewMiddleware',\n 'django.contrib.auth.middleware.AuthenticationMiddleware',\n 'django.contrib.messages.middleware.MessageMiddleware',\n 'django.middleware.clickjacking.XFrameOptionsMiddleware',\n]\n\nROOT_URLCONF = 'e_learning_Django3.urls'\n\nTEMPLATES = [\n {\n 'BACKEND': 'django.template.backends.django.DjangoTemplates',\n 'DIRS': [BASE_DIR / 'templates']\n ,\n 'APP_DIRS': True,\n 'OPTIONS': {\n 'context_processors': [\n 'django.template.context_processors.debug',\n 'django.template.context_processors.request',\n 'django.contrib.auth.context_processors.auth',\n 'django.contrib.messages.context_processors.messages',\n ],\n },\n },\n]\n\nWSGI_APPLICATION = 'e_learning_Django3.wsgi.application'\nASGI_APPLICATION = 'e_learning_Django3.routing.application'\n# Database\n# https://docs.djangoproject.com/en/3.1/ref/settings/#databases\n\nDATABASES = {\n 'default': {\n 'ENGINE': 'django.db.backends.sqlite3',\n 'NAME': BASE_DIR / 'db.sqlite3',\n }\n}\n\n# Password validation\n# https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators\n\nAUTH_PASSWORD_VALIDATORS = [\n {\n 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',\n },\n {\n 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',\n },\n {\n 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',\n },\n {\n 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',\n },\n]\n\n# Internationalization\n# https://docs.djangoproject.com/en/3.1/topics/i18n/\n\nLANGUAGE_CODE = 'en-us'\n\nTIME_ZONE = 'UTC'\n\nUSE_I18N = True\n\nUSE_L10N = True\n\nUSE_TZ = True\n\n# Static files (CSS, JavaScript, Images)\n# https://docs.djangoproject.com/en/3.1/howto/static-files/\n\nSTATIC_URL = '/static/'\nMEDIA_ROOT = os.path.join(BASE_DIR, 'media/')\nMEDIA_URL = 'media/'\n\n# after login user is redirected to his/hers course list\nLOGIN_REDIRECT_URL = reverse_lazy('student_course_list')\n\n# CACHES = {\n# 'default': {\n# 'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',\n# 'LOCATION': '127.0.0.1:11211',\n# }\n# }\n\nCACHE_MIDDLEWARE_ALIAS = 'default'\nCACHE_MIDDLEWARE_SECONDS = 60 * 15 # 15 minutes\nCACHE_MIDDLEWARE_KEY_PREFIX = 'educa'\n\nREST_FRAMEWORK = {\n 'DEFAULT_PERMISSION_CLASSES': [\n 'rest_framework.permissions.DjangoModelPermissionsOrAnonReadOnly'\n ]\n}\n\nCHANNEL_LAYERS = {\n 'default': {\n 'BACKEND': 'channels_redis.core.RedisChannelLayer',\n 'CONFIG': {\n 'hosts': [('127.0.0.1', 6379)],\n },\n },\n}\n\nSTATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles')\nSTATICFILES_DIRS = (\n os.path.join(BASE_DIR, 'static'),\n)\nSTATICFILES_STORAGE = 'whitenoise.storage.CompressedManifestStaticFilesStorage'\n\nDATABASE_URL = env('DATABASE_URL')\nr = redis.from_url(os.environ.get(\"REDIS_URL\"))\n" }, { "alpha_fraction": 0.6798780560493469, "alphanum_fraction": 0.6798780560493469, "avg_line_length": 24.230770111083984, "blob_id": "ef9507ce65d933192ee94957e462ea12205b7fea", "content_id": "b7431bed7702ad96e04f51ba1c1992456a21ee5a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 328, "license_type": "no_license", "max_line_length": 71, "num_lines": 13, "path": "/students/forms.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "from django import forms\n\nfrom courses.models import Course\n\n\"\"\"\nThis form is not to be displayed, it's function for \"enroll\" button in \ncourse detail view.\n\"\"\"\n\n\nclass CourseEnrollForm(forms.Form):\n course = forms.ModelChoiceField(queryset=Course.objects.all(),\n widget=forms.HiddenInput)\n" }, { "alpha_fraction": 0.5049327611923218, "alphanum_fraction": 0.7058296203613281, "avg_line_length": 16.421875, "blob_id": "35beaa0f6f73a7dc4da1ba8aea0d31eebaacf9b7", "content_id": "23f997e47fe0d3fa07aacc5b2bf3abf3ea0b71d9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 1115, "license_type": "no_license", "max_line_length": 27, "num_lines": 64, "path": "/requirements.txt", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "aioredis==1.3.1\nappdirs==1.4.3\nasgiref==3.3.1\nasync-timeout==3.0.1\nattrs==20.3.0\nautobahn==20.7.1\nAutomat==20.2.0\nCacheControl==0.12.6\ncertifi==2020.12.5\ncffi==1.14.4\nchannels==2.4.0\nchannels-redis==2.4.2\nchardet==3.0.4\ncolorama==0.4.3\nconstantly==15.1.0\ncontextlib2==0.6.0\ncryptography==3.3.1\ndaphne==2.5.0\ndistlib==0.3.0\ndistro==1.4.0\ndj-config-url==0.1.1\nDjango==3.1.4\ndjango-braces==1.14.0\ndjango-embed-video==1.3.3\ndjango-environ==0.4.5\ndjango-memcache-status==2.2\ndjango-redis-cache==3.0.0\ndjangorestframework==3.11.0\nenviron==1.0\ngunicorn==20.0.4\nhiredis==1.1.0\nhtml5lib==1.0.1\nhyperlink==20.0.1\nidna==2.10\nincremental==17.5.0\nipaddr==2.2.0\nlockfile==0.12.2\nmsgpack==0.6.2\npackaging==20.3\npep517==0.8.2\nPillow==7.0.0\nprogress==1.5\npsycopg2==2.8.6\npyasn1==0.4.8\npyasn1-modules==0.2.8\npycparser==2.20\nPyHamcrest==2.0.2\npyOpenSSL==20.0.0\npyparsing==2.4.6\npython-memcached==1.59\npytoml==0.1.21\npytz==2020.4\nredis==3.4.1\nrequests==2.25.0\nretrying==1.3.3\nservice-identity==18.1.0\nsix==1.15.0\nsqlparse==0.4.1\nTwisted==20.3.0\ntxaio==20.4.1\nurllib3==1.26.2\nwebencodings==0.5.1\nwhitenoise==5.2.0\nzope.interface==5.2.0\n" }, { "alpha_fraction": 0.7110266089439392, "alphanum_fraction": 0.7110266089439392, "avg_line_length": 20.91666603088379, "blob_id": "fbbe766ea9fdb8177bdcc4ed73fe9fabf1c0f038", "content_id": "c94320dcdb31dee64c4078d0a858ed999ecdb3ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 263, "license_type": "no_license", "max_line_length": 71, "num_lines": 12, "path": "/courses/templatetags/course.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "from django import template\n\nregister = template.Library()\n\n\n# model_name template custom filter to apply in templates \"\|model_name\"\[email protected]\ndef model_name(obj):\n try:\n return obj._meta.model_name\n except AttributeError:\n return None\n" }, { "alpha_fraction": 0.5180055499076843, "alphanum_fraction": 0.5706371068954468, "avg_line_length": 20.235294342041016, "blob_id": "4fdc4d486b24de390bf770046596b3ad3bbebdf6", "content_id": "10eb11576f399b16dd0c0ac90c2a5a947ac44aab", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 361, "license_type": "no_license", "max_line_length": 47, "num_lines": 17, "path": "/courses/migrations/0006_auto_20201206_1337.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "# Generated by Django 3.1.4 on 2020-12-06 13:37\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n dependencies = [\n ('courses', '0005_course_student'),\n ]\n\n operations = [\n migrations.RenameField(\n model_name='course',\n old_name='student',\n new_name='students',\n ),\n ]\n" }, { "alpha_fraction": 0.41312742233276367, "alphanum_fraction": 0.5566280484199524, "avg_line_length": 20, "blob_id": "8bcfc2ba96be2377851c2558d64d2b8c480991d1", "content_id": "64c137bd05d3dc2ebf1d2120aaddf19db93ccf86", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TOML", "length_bytes": 1554, "license_type": "no_license", "max_line_length": 32, "num_lines": 74, "path": "/Pipfile", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "[[source]]\nname = \"pypi\"\nurl = \"https://pypi.org/simple\"\nverify_ssl = true\n\n[dev-packages]\n\n[packages]\naioredis = \"==1.3.1\"\nappdirs = \"==1.4.3\"\nasgiref = \"==3.3.1\"\nasync-timeout = \"==3.0.1\"\nattrs = \"==20.3.0\"\nautobahn = \"==20.7.1\"\ncertifi = \"==2020.12.5\"\ncffi = \"==1.14.4\"\nchannels = \"==2.4.0\"\nchannels-redis = \"==2.4.2\"\nchardet = \"==3.0.4\"\ncolorama = \"==0.4.3\"\nconstantly = \"==15.1.0\"\ncontextlib2 = \"==0.6.0\"\ncryptography = \"==3.3.1\"\ndaphne = \"==2.5.0\"\ndistlib = \"==0.3.0\"\ndistro = \"==1.4.0\"\ndj-config-url = \"==0.1.1\"\ndjango-braces = \"==1.14.0\"\ndjango-embed-video = \"==1.3.3\"\ndjango-environ = \"==0.4.5\"\ndjango-memcache-status = \"==2.2\"\ndjango-redis-cache = \"==3.0.0\"\ndjangorestframework = \"==3.11.0\"\nenviron = \"==1.0\"\ngunicorn = \"==20.0.4\"\nhiredis = \"==1.1.0\"\nhtml5lib = \"==1.0.1\"\nhyperlink = \"==20.0.1\"\nidna = \"==2.10\"\nincremental = \"==17.5.0\"\nipaddr = \"==2.2.0\"\nlockfile = \"==0.12.2\"\nmsgpack = \"==0.6.2\"\npep517 = \"==0.8.2\"\nprogress = \"==1.5\"\npsycopg2 = \"==2.8.6\"\npyasn1 = \"==0.4.8\"\npyasn1-modules = \"==0.2.8\"\npycparser = \"==2.20\"\npyparsing = \"==2.4.6\"\npython-memcached = \"==1.59\"\npytoml = \"==0.1.21\"\npytz = \"==2020.4\"\nredis = \"==3.4.1\"\nrequests = \"==2.25.0\"\nretrying = \"==1.3.3\"\nsix = \"==1.15.0\"\nsqlparse = \"==0.4.1\"\ntxaio = \"==20.4.1\"\nurllib3 = \"==1.26.2\"\nwebencodings = \"==0.5.1\"\nwhitenoise = \"==5.2.0\"\n\"zope.interface\" = \"==5.2.0\"\nAutomat = \"==20.2.0\"\nCacheControl = \"==0.12.6\"\nDjango = \"==3.1.4\"\nPillow = \"==7.0.0\"\nPyHamcrest = \"==2.0.2\"\npyOpenSSL = \"==20.0.0\"\nservice_identity = \"==18.1.0\"\nTwisted = \"==20.3.0\"\n\n[requires]\npython_version = \"3.8\"\n" }, { "alpha_fraction": 0.7197668552398682, "alphanum_fraction": 0.7212238907814026, "avg_line_length": 36.436363220214844, "blob_id": "f3814fa40578cd4fe40ceb56baca36b59ac91484", "content_id": "dff0c9dd7ff3c0c69f80d8015fa4818f509688d2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2059, "license_type": "no_license", "max_line_length": 101, "num_lines": 55, "path": "/courses/api/views.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "from django.shortcuts import get_object_or_404\nfrom rest_framework import generics, viewsets\nfrom rest_framework.authentication import BasicAuthentication\nfrom rest_framework.decorators import action\nfrom rest_framework.permissions import IsAuthenticated\nfrom rest_framework.response import Response\nfrom rest_framework.views import APIView\n\nfrom courses.api.permissions import IsEnrolled\nfrom courses.api.serializers import SubjectSerializer, CourseSerializer, CourseWithContentsSerializer\nfrom courses.models import Subject, Course\n\n\nclass SubjectListView(generics.ListAPIView):\n queryset = Subject.objects.all()\n serializer_class = SubjectSerializer\n\n\nclass SubjectDetailView(generics.RetrieveAPIView):\n queryset = Subject.objects.all()\n serializer_class = SubjectSerializer\n\n\n\n\nclass CourseViewSet(viewsets.ReadOnlyModelViewSet):\n queryset = Course.objects.all()\n serializer_class = CourseSerializer\n\n @action(detail=True,\n methods=['post'],\n authentication_classes=[BasicAuthentication],\n permission_classes=[IsAuthenticated])\n def enroll(self, request, args, kwargs):\n \"\"\"\n Custom method enables to enroll students for courses, detail=True\n specifies that action is taken on single obj (e.g.course), for method\n 'post' with auth/perms specified perform enroll func: get current course\n enroll current user to it.\n \"\"\"\n course = self.get_object()\n course.students.add(request.user)\n return Response({'enrolled': True})\n\n @action(detail=True,\n methods=['get'],\n serializer_class=CourseWithContentsSerializer,\n authentication_classes=[BasicAuthentication],\n permission_classes=[IsEnrolled, IsAuthenticated])\n def contents(self, request, args, *kwargs):\n \"\"\"\n GET single object (course) to render using CourseWithContentsSerializer\n and check auth/perms and returns course object via retrieve.\n \"\"\"\n return self.retrieve(request, args, *kwargs)\n" }, { "alpha_fraction": 0.5339622497558594, "alphanum_fraction": 0.5924528241157532, "avg_line_length": 26.894737243652344, "blob_id": "957f7562310157cc5f2dd7dfda982857697835d4", "content_id": "d3bd63012005b6ae84a1f69aab35e15b9ebafc3e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 530, "license_type": "no_license", "max_line_length": 104, "num_lines": 19, "path": "/courses/migrations/0004_auto_20201206_1231.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "# Generated by Django 3.1.4 on 2020-12-06 12:31\n\nimport django.db.models.deletion\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n dependencies = [\n ('courses', '0003_auto_20201205_1951'),\n ]\n\n operations = [\n migrations.AlterField(\n model_name='module',\n name='course',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='modules',\n to='courses.course'),\n ),\n ]\n" }, { "alpha_fraction": 0.6209964156150818, "alphanum_fraction": 0.6233689188957214, "avg_line_length": 37.03007507324219, "blob_id": "11e6c8fde39e2342f11dca773edba8e03db5c69e", "content_id": "6fba645a209784efc3c65685a619d00278cbfbea", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 10116, "license_type": "no_license", "max_line_length": 94, "num_lines": 266, "path": "/courses/views.py", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "from braces.views import CsrfExemptMixin, JsonRequestResponseMixin\nfrom django.apps import apps\nfrom django.contrib.auth.mixins import LoginRequiredMixin, PermissionRequiredMixin\nfrom django.core.cache import cache\nfrom django.db.models import Count\nfrom django.forms import modelform_factory\nfrom django.shortcuts import get_object_or_404, redirect\nfrom django.urls import reverse_lazy\nfrom django.views.generic import ListView, CreateView, UpdateView, DeleteView, DetailView\nfrom django.views.generic.base import TemplateResponseMixin, View\n\nfrom courses.forms import ModuleFormSet\nfrom courses.models import Course, Module, Content, Subject\n# overriding get_queryset method to get only content created by logged in user\nfrom students.forms import CourseEnrollForm\n\n\n# def mixins\n\n\nclass OwnerMixin(object):\n def get_queryset(self):\n qs = super().get_queryset()\n return qs.filter(owner=self.request.user)\n\n\n# overriding form_valid method to set owner to current user\nclass OwnerEditMixin(object):\n def form_valid(self, form):\n form.instance.owner = self.request.user\n return super().form_valid(form)\n\n\nclass OwnerCourseMixin(OwnerMixin,\n LoginRequiredMixin,\n PermissionRequiredMixin):\n model = Course\n fields = ['subject', 'title', 'slug', 'overview']\n success_url = reverse_lazy('manage_course_list')\n\n\nclass OwnerCourseEditMixin(OwnerCourseMixin, OwnerEditMixin):\n template_name = 'courses/manage/course/form.html'\n\n\n# generic views for editing, createing, updateing and deleting courses\nclass ManageCourseListView(OwnerCourseMixin, ListView):\n template_name = 'courses/manage/course/list.html'\n permission_required = 'courses.view_course'\n\n\nclass CourseCreateView(OwnerCourseEditMixin, CreateView):\n permission_required = 'courses.add_course'\n\n\nclass CourseUpdateView(OwnerCourseEditMixin, UpdateView):\n permission_required = 'courses.change_course'\n\n\nclass CourseDeleteView(OwnerCourseMixin, DeleteView):\n template_name = 'courses/manage/course/delete.html'\n permission_required = 'courses.delete_course'\n\n\n\"\"\"\nView handles formset functionality to add, update and delete courses.\nInherits from TemplateResponseMixin (requires HTTP response and allows \nmethod \"render_to_response\" which allows to render template and View() \nbasic generic view which has methods:\nget_formset(): allows to use formset to build view\ndispatch(): takes HTTP request and it's params and delegate rendering \nto specific method here get or post using get_object_or_404 to get\ncourse and its ID/PK and user\nget(): execute GET HTTP request and builds view from formset\npost(): build formset instance using submitted data, execute is_valid() method\nfrom formset, if valid saves data by adding, updating or deleting it.\n\"\"\"\n\n\nclass CourseModuleUpdateView(TemplateResponseMixin, View):\n template_name = 'courses/manage/module/formset.html'\n course = None\n\n def get_formset(self, data=None):\n return ModuleFormSet(instance=self.course,\n data=data)\n\n def dispatch(self, request, pk):\n self.course = get_object_or_404(Course,\n id=pk,\n owner=request.user)\n return super().dispatch(request, pk)\n\n def get(self, request, args, *kwargs):\n formset = self.get_formset()\n return self.render_to_response({'course': self.course,\n 'formset': formset})\n\n def post(self, request, args, *kwargs):\n formset = self.get_formset(data=request.POST)\n if formset.is_valid():\n formset.save()\n return redirect('manage_course_list')\n return self.render_to_response({'course': self.course,\n 'formset': formset})\n\n\n\"\"\"\nView that allows to create or updated different models' contents.\nget_model(): checks if given model is either text, video, image or file\nit uses django apps to get valid existing model name\nget_form(): builds dynamic form using modelform_factory() function\nfor given model\ndispatch(): receives URL params and stores corresponding module, model\nand content obj as class attributes (module_id, model_name, id of obj if\nit is updated if not its None).\nget(): builds the model form for given model (text, video,image or file)\ninstance with given ID or if the instance is created ID = None\npost(): passes the submitted data and files, validate it, if valid\ncreate new object/update and assign to logged in user, if no ID is \nprovided, new obj is created.\n\"\"\"\n\n\nclass ContentCreateUpdateView(TemplateResponseMixin, View):\n module = None\n model = None\n obj = None\n template_name = 'courses/manage/content/form.html'\n\n def get_model(self, model_name):\n if model_name in ['text', 'video', 'image', 'file']:\n return apps.get_model(app_label='courses',\n model_name=model_name)\n\n def get_form(self, model, args, *kwargs):\n Form = modelform_factory(model, exclude=['owner',\n 'order',\n 'created'])\n return Form(args, kwargs)\n\n def dispatch(self, request, module_id, model_name, id=None):\n self.module = get_object_or_404(Module,\n id=module_id,\n course__owner=request.user\n )\n self.model = self.get_model(model_name)\n if id:\n self.obj = get_object_or_404(self.model,\n id=id,\n owner=request.user)\n return super().dispatch(request, module_id, model_name, id)\n\n def get(self, request, module_id, model_name, id=None):\n form = self.get_form(self.model, instance=self.obj)\n return self.render_to_response({'form': form,\n 'object': self.obj})\n\n def post(self, request, module_id, model_name, id=None):\n form = self.get_form(self.model,\n instance=self.obj,\n data=request.POST,\n files=request.FILES)\n if form.is_valid():\n obj = form.save(commit=False)\n obj.owner = request.user\n obj.save()\n if not id:\n # new content, doesn't have an ID\n Content.objects.create(module=self.module,\n item=obj)\n return redirect('module_content_list', self.module.id)\n return self.render_to_response({'form': form,\n 'object': self.obj})\n\n\nclass ContentDeleteView(View):\n\n def post(self, request, id):\n content = get_object_or_404(Content,\n id=id,\n module__course__owner=request.user)\n module = content.module\n content.item.delete()\n content.delete()\n return redirect('module_content_list', module.id)\n\n\nclass ModuleContentListView(TemplateResponseMixin, View):\n template_name = 'courses/manage/module/content_list.html'\n\n def get(self, request, module_id):\n module = get_object_or_404(Module,\n id=module_id,\n course__owner=request.user)\n return self.render_to_response({'module': module})\n\n\n# Views responsible for AJAX functionalities in management of courses\nclass ModuleOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):\n\n def post(self, request):\n for id, order in self.request_json.items():\n Module.objects.filter(id=id,\n course__owner=request.user).update(order=order)\n return self.render_json_response({'saved': 'OK'})\n\n\nclass ContentOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):\n\n def post(self, request):\n for id, order in self.request_json.items():\n Content.objects.filter(id=id,\n module__course__owner=request.user).update(order=order)\n return self.render_json_response({'saved': 'OK'})\n\n\n\"\"\"\nView that displays courses. \nget(): using annotate/Count it aggregate all courses and modules (total number),\nif subject is given the list is filtered to fit the subject.\n\"\"\"\n\n\nclass CourseListView(TemplateResponseMixin, View):\n model = Course\n template_name = 'courses/course/list.html'\n \"\"\"\n get(): provide by default all courses if you filter by subject show them (also cache them)\n \"\"\"\n\n def get(self, request, subject=None):\n subjects = cache.get('all_subjects')\n if not subjects:\n subjects = Subject.objects.annotate(total_courses=Count('courses'))\n cache.set('all_subjects', subjects)\n\n all_courses = Course.objects.annotate(total_modules=Count('modules'))\n if subject:\n subject = get_object_or_404(Subject, slug=subject)\n key = f'subject_{subject.id}_courses'\n courses = cache.get(key)\n if not courses:\n courses = all_courses.filter(subject=subject)\n cache.set(key, courses)\n else:\n courses = cache.get('all_courses')\n if not courses:\n courses = all_courses\n cache.set('all_courses', courses)\n return self.render_to_response({'subjects': subjects,\n 'subject': subject,\n 'courses': courses})\n\n\nclass CourseDetailView(DetailView):\n model = Course\n template_name = 'courses/course/detail.html'\n\n # adds to ctx enrollment form (it's get rendered as a button)\n def get_context_data(self, kwargs):\n context = super(CourseDetailView, self).get_context_data(**kwargs)\n context['enroll_form'] = CourseEnrollForm(\n initial={'course': self.object}\n )\n return context\n" }, { "alpha_fraction": 0.6021444797515869, "alphanum_fraction": 0.7291196584701538, "avg_line_length": 19.84705924987793, "blob_id": "2fd147af4e826d3daab92f97e317e8f334b7561b", "content_id": "6506a5c4170a726e831fb2f03e3fa3a2816b04bf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1772, "license_type": "no_license", "max_line_length": 115, "num_lines": 85, "path": "/README.md", "repo_name": "erobakiewicz/e_learning_Djagno3", "src_encoding": "UTF-8", "text": "# e-learnging-Django3 (e-llearning CMS with a chat)\nE-learning CMS platform app: allows for students to enroll and browse courses and instructors to create and manage \ncourses and their contents.\n\n\n# Functionalities\nThe app is written in python and JS using the Django framework. Django Rest framework, Redis.\n``\n# User management:\n- guest view, log-in, and log-out\n- registration\n- student can enroll for courses\n- instructors can create and manage courses (create, add, remove content)\n\n# General functionalities:\n- CMS for courses divided into modules \n- modules have variety of content types: text, images, video and files\n\n# requirements.txt\n```sh\naioredis==1.3.1\nappdirs==1.4.3\nasgiref==3.3.1\nasync-timeout==3.0.1\nattrs==20.3.0\nautobahn==20.7.1\nAutomat==20.2.0\nCacheControl==0.12.6\ncertifi==2020.12.5\ncffi==1.14.4\nchannels==2.4.0\nchannels-redis==2.4.2\nchardet==3.0.4\ncolorama==0.4.3\nconstantly==15.1.0\ncontextlib2==0.6.0\ncryptography==3.3.1\ndaphne==2.5.0\ndistlib==0.3.0\ndistro==1.4.0\ndj-config-url==0.1.1\nDjango==3.1.4\ndjango-braces==1.14.0\ndjango-embed-video==1.3.3\ndjango-environ==0.4.5\ndjango-memcache-status==2.2\ndjango-redis-cache==3.0.0\ndjangorestframework==3.11.0\nenviron==1.0\ngunicorn==20.0.4\nhiredis==1.1.0\nhtml5lib==1.0.1\nhyperlink==20.0.1\nidna==2.10\nincremental==17.5.0\nipaddr==2.2.0\nlockfile==0.12.2\nmsgpack==0.6.2\npackaging==20.3\npep517==0.8.2\nPillow==7.0.0\nprogress==1.5\npsycopg2==2.8.6\npyasn1==0.4.8\npyasn1-modules==0.2.8\npycparser==2.20\nPyHamcrest==2.0.2\npyOpenSSL==20.0.0\npyparsing==2.4.6\npython-memcached==1.59\npytoml==0.1.21\npytz==2020.4\nredis==3.4.1\nrequests==2.25.0\nretrying==1.3.3\nservice-identity==18.1.0\nsix==1.15.0\nsqlparse==0.4.1\nTwisted==20.3.0\ntxaio==20.4.1\nurllib3==1.26.2\nwebencodings==0.5.1\nwhitenoise==5.2.0\nzope.interface==5.2.0\n```\n" } ]	13
hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions	https://github.com/hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions	88357402520ce9768d6d2d4b40f1fa352c24a5a0	22cee217fd143f7b6d7a08808c028a953b5ccbea	1bb0c3d332201529d77873594e5e9137665989b2	refs/heads/master	2022-12-27T20:07:43.490181	2020-10-09T06:23:14	2020-10-09T06:23:14	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.8498402833938599, "alphanum_fraction": 0.8498402833938599, "avg_line_length": 155.5, "blob_id": "1fe06ca12892b8872fdb0c54d9afa238be102e98", "content_id": "70be760b1d308c95f094737e05db1c5e8d40f8e9", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 313, "license_type": "permissive", "max_line_length": 257, "num_lines": 2, "path": "/README.md", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "# LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions\nI have solved questions in LeetCode, GeeksForGeeks and InterviewBit using python during my placement preparations. This directory contains solutions of some of the standard questions using python. Any improvement and positive criticism will be most welcome.\n" }, { "alpha_fraction": 0.5301204919815063, "alphanum_fraction": 0.5381526350975037, "avg_line_length": 34.57143020629883, "blob_id": "6012edf060796b0163b84c0deba24fb9330847ea", "content_id": "1b4631ebf19cbce470bfbea4fa7bf7d456f8983c", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 249, "license_type": "permissive", "max_line_length": 85, "num_lines": 7, "path": "/Questions_by_Name/Permutations.py", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "class Solution:\n # @param A : list of integers\n # @return a list of list of integers\n def permute(self, A):\n if len(A)==0:\n return [[]]\n return [[A[i]]+x for i in range(len(A)) for x in self.permute(A[:i]+A[i+1:])]\n" }, { "alpha_fraction": 0.4373464286327362, "alphanum_fraction": 0.46437346935272217, "avg_line_length": 30.30769157409668, "blob_id": "749beb02eee5ad887c4d366fbc66a13950328cc4", "content_id": "6878e3e3fb713fb8a835e20d1842f5192c4c7183", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 407, "license_type": "permissive", "max_line_length": 98, "num_lines": 13, "path": "/Questions_by_Name/Gray Code.py", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "class Solution:\n # @param A : integer\n # @return a list of integers\n def grayCode(self, A):\n options = ['0','1']\n List = []\n \n def combinations(n):\n if n==1:\n return ['0','1']\n else:\n return ['0'+i for i in combinations(n-1)]+['1'+i for i in combinations(n-1)[::-1]]\n return [int(i,2) for i in combinations(A)]\n" }, { "alpha_fraction": 0.37974682450294495, "alphanum_fraction": 0.4104882478713989, "avg_line_length": 29.72222137451172, "blob_id": "83110225249f4bc3c0d77979dbee238796e08e57", "content_id": "9ec280a79e8d62ab665109a5669b638e4a5fbc4b", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 553, "license_type": "permissive", "max_line_length": 72, "num_lines": 18, "path": "/Questions_by_Name/Letter Phone.py", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "class Solution:\n # @param A : string\n # @return a list of strings\n def letterCombinations(self, A):\n Dict = {'0':'0','1':'1','2':'abc','3':'def','4':'ghi','5':'jkl',\n '6':'mno','7':'pqrs','8':'tuv','9':'wxyz'}\n \n def ret(arr):\n if len(arr)<1:\n return []\n if len(arr)==1:\n return list(Dict[arr[0]])\n else:\n M = [x+i for x in Dict[arr[0]] for i in ret(arr[1:])]\n return sorted(M)\n \n ans = ret(A)\n return ans\n" }, { "alpha_fraction": 0.35228848457336426, "alphanum_fraction": 0.373092919588089, "avg_line_length": 29.04166603088379, "blob_id": "4b454a3133ef6013c2c0d47b1b380a6138c99840", "content_id": "c8d5dc75575b2ba3d9a038512bec14d84726c81d", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 721, "license_type": "permissive", "max_line_length": 47, "num_lines": 24, "path": "/Questions_by_Name/Maximum String.py", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "class Solution:\n # @param A : string\n # @param B : integer\n # @return a strings\n def solve(self, A, B):\n def swap(string,i,j):\n s1=string[:i]\n s2=string[i+1:j]\n s3=string[j+1:]\n return s1+string[j]+s2+string[i]+s3\n def sswap(A,B,ans):\n if B==0:\n return ans[0]\n for i in range(len(A)):\n for j in range(i+1,len(A)):\n if A[j]>A[i]:\n temp=swap(A,i,j)\n if ans[0]<temp:\n ans[0]=temp\n sswap(temp,B-1,ans)\n \n ans=[A]\n sswap(A,B,ans)\n return ans[0]\n" }, { "alpha_fraction": 0.40909090638160706, "alphanum_fraction": 0.42011019587516785, "avg_line_length": 28.040000915527344, "blob_id": "7468988a9e016bc6124313ac93898f7c481d139e", "content_id": "cc4260415b8925b92af95d2df213b5bfa1a8fad0", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 726, "license_type": "permissive", "max_line_length": 52, "num_lines": 25, "path": "/Questions_by_Name/InterviewBit Hashing/Colorful Number.py", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "class Solution:\n# @param A : integer\n# @return an integer\n def colorful(self, A):\n #first find all subsebts\n A=list(str(A))\n if(len(A)>1):\n sublist = [[]] \n for i in range(len(A) + 1): \n for j in range(i + 1, len(A) + 1): \n sub = A[i:j] \n sublist.append(sub) \n #find the products of all subset digits \n #use set since set doesn't take duplicate values\n b=set()\n for i in sublist:\n p=1\n for j in i:\n p=p*int(j)\n b.add(p)\n if(len(b)==len(sublist)):\n return 1\n return 0\n else:\n return 1\n" }, { "alpha_fraction": 0.4645669162273407, "alphanum_fraction": 0.4661417305469513, "avg_line_length": 27.863636016845703, "blob_id": "a113afd41f6d66b751362adeffef8706bbfda2fc", "content_id": "0761f7e1cb0bff1aa41a0afbebfcdb2a60b29c5d", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 635, "license_type": "permissive", "max_line_length": 71, "num_lines": 22, "path": "/Questions_by_Name/Combination Sum.py", "repo_name": "hulaba/LeetCode-GeeksForGeeks-InterviewBit-Python-Solutions", "src_encoding": "UTF-8", "text": "class Solution:\n # @param A : list of integers\n # @param B : integer\n # @return a list of list of integers\n def combinationSum(self, A, B):\n Listans = []\n A.sort()\n def permute(curSum,options,Set):\n if curSum==B:\n Listans.append(Set[:])\n return\n if curSum>B:\n return\n for i in range(len(options)):\n permute(curSum+options[i],options[i:],Set+[options[i]])\n \n permute(0,A,[])\n ans = []\n for i in Listans:\n if i not in ans:\n ans.append(i)\n return ans\n" } ]	7
jaspringer/pymzlib	https://github.com/jaspringer/pymzlib	43ee9d7ec3bdf06a4bcf4e471ec67e753a91e2b5	84ebcb28f18225f99696fece3977fc6d1abbdf2f	c451cbe2b6888da059603b736afa3f1542afe732	refs/heads/master	2021-01-17T20:02:37.038455	2014-10-05T01:30:39	2014-10-05T01:30:39	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6897710561752319, "alphanum_fraction": 0.7000629901885986, "avg_line_length": 30.3157901763916, "blob_id": "3e64f1379cf7a18f246a35cb835277f26508e10e", "content_id": "1c6cd9f1c2980fa479de49712ef9760215b29be1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4761, "license_type": "no_license", "max_line_length": 104, "num_lines": 152, "path": "/filters.py", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "\"\"\"\nFilter.py\n\nAuthor: Thomas McGrew\n\nLicense:\n\tMIT license.\n \n\tPermission is hereby granted, free of charge, to any person\n\tobtaining a copy of this software and associated documentation\n\tfiles (the \"Software\"), to deal in the Software without\n\trestriction, including without limitation the rights to use,\n\tcopy, modify, merge, publish, distribute, sublicense, and/or sell\n\tcopies of the Software, and to permit persons to whom the\n\tSoftware is furnished to do so, subject to the following\n\tconditions:\n\t \n\tThe above copyright notice and this permission notice shall be\n\tincluded in all copies or substantial portions of the Software.\n\t \n\tTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n\tEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\n\tOF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n\tNONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT\n\tHOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,\n\tWHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n\tFROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\n\tOTHER DEALINGS IN THE SOFTWARE.\n\"\"\"\n\nimport numpy as numerical\n\ndef lpf2d( data, threshold ):\n\t\"\"\"\n\tPerforms a low pass filter on the passed in data.\n\t:Parameters:\n\t\tdata : numerical.ndarray\n\t\t\tA 2 dimensional array (matrix) to be filtered\n\t\tthreshold : int\n\t\t\tThe position of the cutoff for the filter. Should be from 0 to 1\n\n\trtype: numerical.ndarray\n\treturns: The filtered data\n\t\"\"\"\n\tfftData = numerical.fft.fft2( data )\n\twidth, height = fftData.shape\n\tfor x in xrange( width ):\n\t\tfor y in xrange( height ):\n\t\t\tif not _insideCircle( x, y, width, height, threshold ):\n\t\t\t\tfftData[x][y] = 0\n\treturn abs( numerical.fft.ifft2( fftData ))\n\ndef hpf2d( data, threshold ):\n\t\"\"\"\n\tPerforms a high pass filter on the passed in data.\n\t:Parameters:\n\t\tdata : numerical.ndarray\n\t\t\tA 2 dimensional array (matrix) to be filtered\n\t\tthreshold : int\n\t\t\tThe position of the cutoff for the filter. Should be from 0 to 1\n\n\trtype: numerical.ndarray\n\treturns: The filtered data\n\t\"\"\"\n\tfftData = numerical.fft.fft2( data )\n\twidth, height = fftData.shape\n\tfor x in xrange( width ):\n\t\tfor y in xrange( height ):\n\t\t\tif _insideCircle( x, y, width, height, threshold ):\n\t\t\t\tfftData[x][y] = 0\n\treturn abs( numerical.fft.ifft2( fftData ))\n\ndef lpf( data, threshold ):\n\t\"\"\"\n\tPerforms a low pass filter on the passed in data.\n\t:Parameters:\n\t\tdata : numerical.ndarray\n\t\t\tA 1 dimensional array to be filtered\n\t\tthreshold : int\n\t\t\tThe position of the cutoff for the filter. Should be from 0 to 1\n\n\trtype: numerical.ndarray\n\treturns: The filtered data\n\t\"\"\"\n\tdata = numerical.array( data )\n\tfftData = numerical.fft.fft( data )\n\tx = data.shape[0]\n\tlength = int(( x * threshold ) / 2 )\n\tif not length:\n\t\treturn data\n\tfftData[ length:-length ] = [0] * ( x - ( length * 2 ))\n\treturn numerical.fft.ifft( fftData )\n\ndef hpf( data, threshold ):\n\t\"\"\"\n\tPerforms a high pass filter on the passed in data.\n\t:Parameters:\n\t\tdata : numerical.ndarray\n\t\t\tA 1 dimensional array to be filtered\n\t\tthreshold : int\n\t\t\tThe position of the cutoff for the filter. Should be from 0 to 1\n\n\trtype: numerical.ndarray\n\treturns: The filtered data\n\t\"\"\"\n\tdata = numerical.array( data )\n\tfftData = numerical.fft.fft( data )\n\tx = data.shape[0]\n\tlength = int(( x * threshold ) / 2 )\n\tif not length:\n\t\treturn data\n\tfftData[ :length ] = [0] * length\n\tfftData[ -length: ] = [0] * length\n\treturn numerical.fft.ifft( fftData )\n\ndef bpf( data, lowThreshold, highThreshold ):\n\t\"\"\"\n\tPerforms a band pass filter on the passed in data.\n\t:Parameters:\n\t\tdata : numerical.ndarray\n\t\t\tA 1 dimensional array to be filtered\n\t\tlowThreshold : int\n\t\t\tThe position of the cutoff for the high pass filter. Should be from 0 to 1\n\t\thighThreshold : int\n\t\t\tThe position of the cutoff for the low pass filter. Should be from 0 to 1\n\n\trtype: numerical.ndarray\n\treturns: The filtered data\n\t\"\"\"\n\tdata = numerical.array( data )\n\tfftData = numerical.fft.fft( data )\n\tx = data.shape[0]\n\tlength = int(( x * highThreshold ) / 2 )\n\tif length:\n\t\tfftData[ length:-length ] = [0] * ( x - ( length * 2 ))\n\tlength = int(( x * lowThreshold ) / 2 )\n\tif length:\n\t\tfftData[ :length ] = [0] * length\n\t\tfftData[ -length: ] = [0] * length\n\treturn numerical.fft.ifft( fftData )\n\ndef _insideCircle( x, y, width, height, threshold ):\n\t\"\"\"\n\tDetermines whether a particular position in the matrix is above or below the threshold\n\n\trtype: bool\n\treturns: true if it is below the threshold, false otherwise\n\t\"\"\"\n\tfullDistance = math.sqrt( 2 * ( width/ 2 )2 )\n\t#distance = math.sqrt( abs( width/2 - x )2 + ( float( abs( height/2 - y )) * width / height) 2 )\n\tdistance = math.sqrt( min( x, width - x )2 + ( float( min( y, height - y )) * width / height) ** 2 )\n\treturn ( threshold > distance / fullDistance )\n\n" }, { "alpha_fraction": 0.7371237277984619, "alphanum_fraction": 0.7451505064964294, "avg_line_length": 30.787233352661133, "blob_id": "ae0c51e1f8c5c427633ee94c4aaee6d86de6c14b", "content_id": "af6c5a43b8686e620e11709cd8de4a1da31ef726", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1495, "license_type": "no_license", "max_line_length": 66, "num_lines": 47, "path": "/mzconvert.py", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\"\"\"\nCopyright: 2010 Thomas McGrew\n\nLicense: X11 license.\n\n\tPermission is hereby granted, free of charge, to any person\n\tobtaining a copy of this software and associated documentation\n\tfiles (the \"Software\"), to deal in the Software without\n\trestriction, including without limitation the rights to use,\n\tcopy, modify, merge, publish, distribute, sublicense, and/or sell\n\tcopies of the Software, and to permit persons to whom the\n\tSoftware is furnished to do so, subject to the following\n\tconditions:\n\n\tThe above copyright notice and this permission notice shall be\n\tincluded in all copies or substantial portions of the Software.\n\n\tTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n\tEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\n\tOF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n\tNONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT\n\tHOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,\n\tWHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n\tFROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\n\tOTHER DEALINGS IN THE SOFTWARE.\n\n\"\"\"\n\nVERSION = \"0.2\"\n\nimport mzlib\nfrom sys import argv\n\n\ndef main( options=None, args=None ):\n\t\"\"\"The main method\"\"\"\n\tif not len( args ):\n\t\tprint ( \"This program requires a filename argument\" )\n\t\tsys.exit( 1 )\n\tinputFile = args[ 0 ]\n\toutputFile = args[ 1 ]\n\trawData = mzlib.RawData( inputFile )\n\trawData.write( outputFile )\n\t\nif __name__ == \"__main__\":\n\tmain( args = argv[1:] )\n\n" }, { "alpha_fraction": 0.8518518805503845, "alphanum_fraction": 0.8518518805503845, "avg_line_length": 26, "blob_id": "8bcdf7a331c86aaefe520d509f575b43d346d5f8", "content_id": "36860e11a8a699ed51f4efb4beaccdfea569d604", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 27, "license_type": "no_license", "max_line_length": 26, "num_lines": 1, "path": "/README.md", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "forked from mcgrew/pymzlib\n" }, { "alpha_fraction": 0.6213675141334534, "alphanum_fraction": 0.6309635043144226, "avg_line_length": 31.538558959960938, "blob_id": "7277f240995bf8b12eb0ca5c4fd0e4945774b618", "content_id": "ad5c0a8252f5e560969cef3d249f9cde3b8894ca", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 25740, "license_type": "no_license", "max_line_length": 178, "num_lines": 791, "path": "/mzlib.py", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "\"\"\"\nCopyright: 2010 Thomas McGrew\n\nLicense: MIT license.\n\n\tPermission is hereby granted, free of charge, to any person\n\tobtaining a copy of this software and associated documentation\n\tfiles (the \"Software\"), to deal in the Software without\n\trestriction, including without limitation the rights to use,\n\tcopy, modify, merge, publish, distribute, sublicense, and/or sell\n\tcopies of the Software, and to permit persons to whom the\n\tSoftware is furnished to do so, subject to the following\n\tconditions:\n\n\tThe above copyright notice and this permission notice shall be\n\tincluded in all copies or substantial portions of the Software.\n\n\tTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n\tEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\n\tOF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n\tNONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT\n\tHOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,\n\tWHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n\tFROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\n\tOTHER DEALINGS IN THE SOFTWARE.\n\n\"\"\"\nimport sys\nimport os\nfrom xml.dom.minidom import parse\nimport struct\nfrom base64 import b64decode, b64encode\nimport re\nimport zlib\nimport gzip\nfrom copy import deepcopy\ntry: \n\timport json\nexcept ImportError:\n\ttry:\n\t\timport simplejson as json\n\texcept:\n\t\tjson = False\n\nVERSION = \"0.2.1.2012.02.27\"\n\nclass RawData( object ):\n\n\tdef __init__( self, _input=None ):\n\t\tif type( _input ) == RawData:\n\t\t\t# copy the passed in object\n\t\t\tself.data = deepcopy( _input.data )\n\n\t\telif type( _input ) == str:\n\t\t\t# read the passed in file name\n\t\t\tself.read( _input )\n\n\t\telse:\n\t\t\tself.data = { 'scans' : [] }\n\n\tdef getScan( self, retentionTime ):\n\t\t\"\"\"\n\t\tGets a scan from the data by retention time.\n\t\t:Parameters:\n\t\t\tretentionTime : float\n\t\t\t\tA float indicating the retention time of the scan to retrieve. The scan\n\t\t\t\tclosest to that time is returned.\n\n\t\trtype: dict\n\t\treturn: A dict containing the scan points & metadata\n\t\t\"\"\"\n\t\tdifference = 1048576\n\t\treturnvalue = None\n\t\tfor scan in self.data[ 'scans' ]:\n\t\t\tcurrentDifference = abs( scan[ 'retentionTime' ] - retentionTime )\n\t\t\tif currentDifference < difference:\n\t\t\t\tdifference = currentDifference\n\t\t\t\treturnvalue = scan\n\t\treturn returnvalue\n\t\t\n\tdef __getitem__( self, value ):\t\n\t\t\"\"\"\n\t\tReturns a list indicating the sic intensity for each scan in order. Only for\n\t\tlevel 1 scans - other scans are omitted.\n\t\t:Parameters:\n\t\t\tvalue : slice\n\t\t\t\tThe m/z indices to retrieve intensity values between.\n\n\t\trtype: list\n\t\treturn: A list of intensity values.\n\t\t\"\"\"\n\t\treturnvalue = []\n\t\tif type( value ) == slice:\n\t\t\tif ( value.start ):\n\t\t\t\tstart = value.start \n\t\t\telse:\n\t\t\t\tstart = 0\n\t\t\tif ( value.stop ):\n\t\t\t\tstop = value.stop \n\t\t\telse:\n\t\t\t\tstop = 1048576\n\t\t\treturn self.sic( start, stop, 1 )\n\t\telse:\n\t\t\treturn self.sic( value - 0.1, value + 0.1, 1 )\n\n\tdef __iter__( self ):\n\t\treturn iter( self.data['scans'] )\n\n\tdef removeScans( self, minTime=0, maxTime=sys.maxint ):\n\t\t\"\"\"\n\t\tDiscards all scans in the given time range.\n\n\t\t:Parameters:\n\t\t\tminTime : float\n\t\t\t\tThe minimum retention time for the scans to remove\n\t\t\tmaxTime : float\n\t\t\t\tThe maximum retention time for the scans to remove\n\t\t\"\"\"\n\t\tif minTime < maxTime:\n\t\t\tself.data[ 'scans' ] = [ scan for scan in self.data['scans'] if \n\t\t\t\t\t\tscan[ 'retentionTime' ] < minTime or \n\t\t\t\t\t\tscan[ 'retentionTime' ] >= maxTime ]\n\n\tdef onlyScans( self, minTime=0, maxTime=sys.maxint ):\n\t\t\"\"\"\n\t\tKeeps only the scans specified in the time range, discarding all others.\n\n\t\t:Parameters:\n\t\t\tminTime : float\n\t\t\t\tThe minimum retention time for the scans to remove\n\t\t\tmaxTime : float\n\t\t\t\tThe maximum retention time for the scans to remove\n\t\t\"\"\"\n\t\tif minTime < maxTime:\n\t\t\tself.data[ 'scans' ] = [ scan for scan in self.data['scans'] if \n\t\t\t\t\tscan[ 'retentionTime' ] >= minTime and\n\t\t\t\t\tscan[ 'retentionTime' ] < maxTime ]\n\n\tdef removeMz( self, mz, tolerance=0.1 ):\n\t\t\"\"\"\n\t\tDiscards all data points with the specified m/z +/- the specified tolerance\n\n\t\t:Parameters:\n\t\t\tmz : float\n\t\t\t\tThe m/z value of the mass to be removed from all scans.\n\t\t\ttolerance : float\n\t\t\t\tThe tolerance to use for determining if the data point should be removed.\n\t\t\t\tDefaults to 0.1.\n\t\t\"\"\"\n\t\tfor scan in self.data[ 'scans' ]:\n\t\t\ttry:\n\t\t\t\tscan[ 'mzArray' ], scan[ 'intensityArray' ] = list( zip( \n\t\t\t\t\t\t\t[ point for point in zip( scan[ 'mzArray' ], scan[ 'intensityArray' ]) \n\t\t\t\t\t\t\tif point[ 0 ] < mz - tolerance or\n\t\t\t\t\t\t\tpoint[ 0 ] >= mz + tolerance ]))\n\t\t\texcept ValueError:\n\t\t\t\tscan[ 'mzArray' ] = []\n\t\t\t\tscan[ 'intensityArray' ] = []\n\n\tdef onlyMz( self, mz, tolerance=0.1 ):\n\t\t\"\"\"\n\t\tKeeps only data points with the specified m/z +/- the specified tolerance,\n\t\tdiscarding all others.\n\n\t\t:Parameters:\n\t\t\tmz : float\n\t\t\t\tThe m/z value of the mass to be retained from all scans.\n\t\t\ttolerance : float\n\t\t\t\tThe tolerance to use for determining if the data point should be removed.\n\t\t\t\tDefaults to 0.1.\n\t\t\"\"\"\n\t\tfor scan in self.data[ 'scans' ]:\n\t\t\ttry:\n\t\t\t\tscan[ 'mzArray' ], scan[ 'intensityArray' ] = list( zip( \n\t\t\t\t\t\t\t[ point for point in zip( scan[ 'mzArray' ], scan[ 'intensityArray' ]) \n\t\t\t\t\t\t\tif point[ 0 ] >= mz - tolerance and\n\t\t\t\t\t\t\tpoint[ 0 ] < mz + tolerance ]))\n\t\t\texcept ValueError:\n\t\t\t\tscan[ 'mzArray' ] = []\n\t\t\t\tscan[ 'intensityArray' ] = []\n\n\tdef sic( self, start=0, stop=1048576, level=1 ):\n\t\t\"\"\"\n\t\tReturns a list indicating the selected intensity for each scan in order. \n\t\t:Parameters:\n\t\t\tstart : float\n\t\t\t\tThe m/z indices to retrieve intensity values higher than or equal to.\n\t\t\tstop : float\n\t\t\t\tThe m/z indecies to retrieve intensity values less than.\n\t\t\tlevel : int\n\t\t\t\tThe msLevel of the scans to get intensity values for. A value of 0 \n\t\t\t\tuses all scans.\n\n\t\trtype: list\n\t\treturn: A list of intensity values.\n\t\t\"\"\"\n\t\treturnvalue = []\n\t\tfor scan in self.data[ 'scans' ]:\n\t\t\tif not level or ( scan[ 'msLevel' ] == level ):\n\t\t\t\treturnvalue.append( sum([ int_ for mz,int_ in \n\t\t\t\t zip( scan[ 'mzArray' ], scan[ 'intensityArray' ])\n\t\t\t\t\t\t\tif mz >= start and mz < stop ]))\n\t\treturn returnvalue\n\n\tdef tic( self, level=1 ):\n\t\t\"\"\"\n\t\tReturns a list indicating the total intensity for each scan in order. \n\t\t:Parameters:\n\t\t\tlevel : int\n\t\t\t\tThe msLevel of the scans to get intensity values for. A value of 0 \n\t\t\t\tuses all scans.\n\n\t\trtype: list\n\t\treturn: A list of intensity values.\n\t\t\"\"\"\n\t\treturn [ sum( scan[ 'intensityArray' ]) for scan in self.data[ 'scans' ]\n\t\t if ( not level or ( scan[ 'msLevel' ] == level ))]\n\n\tdef bpc( self, level=1 ):\n\t\t\"\"\"\n\t\tReturns a list indicating the base intensity for each scan in order. \n\t\t:Parameters:\n\t\t\tlevel : int\n\t\t\t\tThe msLevel of the scans to get intensity values for. A value of 0\n\t\t\t\tuses all scans\n\n\t\trtype: list\n\t\treturn: A list of intensity values.\n\t\t\"\"\"\n\t\ttry: \n\t\t\treturn [ self.max_( scan[ 'intensityArray' ]) \n\t\t\t for scan in self.data[ 'scans' ] \n\t\t\t\t\t\t\t if ( not level or ( scan[ 'msLevel' ] == level ))]\n\t\texcept ValueError:\n\t\t\treturn 0;\n\n\tdef minMz( self ):\n\t\t\"\"\"\n\t\tReturns the minimum mz value in the data.\n\n\t\trtype: float\n\t\treturn: A float containing the min mz in the data.\n\t\t\"\"\"\n\t\treturn min([ x[ 'mzRange' ][ 0 ] for x in self.data[ 'scans' ]])\n\n\tdef maxMz( self ):\n\t\t\"\"\"\n\t\tReturns the maximum mz value in the data.\n\n\t\trtype: float\n\t\treturn: A float containing the max mz in the data.\n\t\t\"\"\"\n\t\treturn ( max([ x[ 'mzRange' ][ 1 ] for x in self.data[ 'scans' ]]))\n\n\n\tdef max_( self, sequence ):\n\t\tif len( sequence ):\n\t\t\treturn max( sequence )\n\t\telse:\n\t\t\treturn 0;\n\n\n\tdef read( self, filename ):\n\t\t\"\"\"\n\t\tLoad a file into this reference. This method will automatically detect the\n\t\tfile type based on the file extension.\n\n\t\t:Parameters:\n\t\t\tfilename : str\n\t\t\t\tThe name of the file to load.\n\n\t\t\"\"\"\n\t\n\t\tif not os.path.exists( filename ):\n\t\t\traise IOError( \"The file %s does not exist or is not readable\" % filename )\n\n\t\tif filename.lower( ).endswith( \".csv\" ):\n\t\t\treturn self.readCsv( filename )\n\n\t\telif filename.lower( ).endswith( \".mzdata\" ) or filename.endswith( \".mzdata.xml\" ):\n\t\t\treturn self.readMzData( filename )\n\n\t\telif filename.lower( ).endswith( \".mzxml\" ):\n\t\t\treturn self.readMzXml( filename )\n\n\t\telif filename.lower( ).endswith( \".mzml\" ):\n\t\t\treturn self.readMzMl( filename )\n\n\t\telif filename.lower( ).endswith( \".json\" ):\n\t\t\treturn self.readJson( filename )\n\n\t\telif filename.lower( ).endswith( \".json.gz\" ):\n\t\t\treturn self.readJsonGz( filename )\n\n\t\telse:\n\t\t\tsys.stderr.write( \"Unrecognized file type for %s\\n\" % filename )\n\t\t\treturn False\n\n\tdef readCsv( self, filename ):\n\t\t\"\"\"\n\t\tRead a file in Agilent csv format. \n\n\t\t:Parameters:\n\t\t\tfilename : str\n\t\t\t\tThe name of the file to load.\n\n\t\t\"\"\"\n\t\tself.data = { \"scans\" : [] }\n\t\ttry:\n\t\t\tf = open( filename, 'r' )\n\t\t\tlines = f.readlines( )\n\t\t\tf.close( )\n\t\texcept IOError:\n\t\t\tsys.stderr.write( \"Error: unable to read file '%s'\\n\" % filename )\n\t\t\treturn False\n\n\t\ti = 0\n\t\twhile( i < len( lines ) and lines[ i ][ :10 ] != \"file name,\" ):\n\t\t\ti+= 1\n\t\tself.data[ 'sourceFile' ] = lines[ i ].split( ',' )[ 1 ]\n\t\twhile ( i < len( lines ) and lines[ i ][ :9 ] != \"[spectra]\" ):\n\t\t\ti+=1\n\t\ti+=1\n\n\t\tif ( i > len( lines ) ):\n\t\t\tsys.stderr.write( \"Unable to parse the reference file '%s'\\n\" % filename ) \n\t\t\treturn False\n\n\t\tscanId = 0\n\t\tfor line in lines[ i: ]:\n\t\t\tscanId += 1\n\t\t\tvalues = line.split( ',' )\n\t\t\tif values[ 4 ] == '-':\n\t\t\t\tpolarity = -1\n\t\t\telse:\n\t\t\t\tpolarity = 1\n\t\t\trt = float( values[ 0 ])\n\t\t\tcount = float( values[ 6 ])\n\t\t\tintensityValues = [ float( x ) for x in values[ 8:-1:2 ] ]\n\t\t\tmassValues = [ float( y ) for y in values[ 7:-1:2 ] ]\n\n\t\t\tself.data[ \"scans\" ].append({ \n\t\t\t\t\"retentionTime\" : rt,\n\t\t\t\t\"polarity\" : polarity, \n\t\t\t\t\"msLevel\" : 1,\n\t\t\t\t\"id\" : scanId,\n\t\t\t\t\"mzRange\" : [ min( massValues ), max( massValues ) ],\n\t\t\t\t\"parentScan\" : None,\n\t\t\t\t\"precursorMz\" : None,\n\t\t\t\t\"collisionEnergy\" : None,\n\t\t\t\t\"mzArray\" : massValues,\n\t\t\t\t\"intensityArray\" : intensityValues\n\t\t\t})\n\t\treturn True\n\n\tdef readMzData( self, filename ):\n\t\t\"\"\"\n\t\tRead a file in mzData format. \n\n\t\t:Parameters:\n\t\t\tfilename : str\n\t\t\t\tThe name of the file to load.\n\n\t\t\"\"\"\n\t\tself.data = { \"scans\" : [] }\n\t\tdataFile = parse( filename )\n\t\tsourceFileNode = dataFile.getElementsByTagName( 'sourceFile' )[ 0 ].\\\n\t\t\tgetElementsByTagName( 'nameOfFile' )[ 0 ]\n\t\tself.data[ 'sourceFile' ] = re.sub( \"<.?>\", \"\", sourceFileNode.toxml( ))\n\t\tscans = dataFile.getElementsByTagName( 'spectrum' )\n\n\t\tfor scan in scans:\n\t\t\tparentScan = None\n\t\t\tprecursorMz = None\n\t\t\tcollisionEnergy = None\n\t\t\tscanId = int( scan.getAttribute( 'id' ))\n\t\t\tspectrumInstrument = scan.getElementsByTagName( 'spectrumInstrument' )[ 0 ]\n\t\t\tmsLevel = int( spectrumInstrument.getAttribute( 'msLevel' ))\n\t\t\tlowMz = float( spectrumInstrument.getAttribute( 'mzRangeStart' ))\n\t\t\thighMz = float( spectrumInstrument.getAttribute( 'mzRangeStop' ))\n\t\t\tparams = spectrumInstrument.getElementsByTagName( 'cvParam' )\n\t\t\tfor param in params:\n\t\t\t\tif param.getAttribute( 'name' ) == 'Polarity':\n\t\t\t\t\tif param.getAttribute( 'value' ) == 'positive':\n\t\t\t\t\t\tpolarity = 1\n\t\t\t\t\telse:\n\t\t\t\t\t\tpolarity = -1\n\t\t\t\tif param.getAttribute( 'name' ) == 'TimeInMinutes':\n\t\t\t\t\trt = float( param.getAttribute( 'value' ))\n\n\t\t\t\n\t\t\tmassValues = self._unpackMzData( \n\t\t\t\tscan.getElementsByTagName( 'mzArrayBinary' )[ 0 ].getElementsByTagName( 'data' )[ 0 ])\n\t\t\tintensityValues = self._unpackMzData( \n\t\t\t\tscan.getElementsByTagName( 'intenArrayBinary' )[ 0 ].getElementsByTagName( 'data' )[ 0 ])\n\n\t\t\tprecursors = scan.getElementsByTagName( 'precursor' )\n\t\t\tfor precursor in precursors[ 0:1 ]:\n\t\t\t\tparentScan = int( precursor.getAttribute( 'spectrumRef' ))\n\t\t\t\tcvParams = precursor.getElementsByTagName( 'cvParam' )\n\t\t\t\tfor param in cvParams:\n\t\t\t\t\tif param.getAttribute( 'name' ) == 'MassToChargeRatio':\n\t\t\t\t\t\tprecursorMz = float( param.getAttribute( 'value' ))\n#\t\t\t\t\tif param.getAttribute( 'name' ) == 'ChargeState':\n#\t\t\t\t\t\tchargeState = int( param.getAttribute( 'value' ))\n\t\t\t\t\tif param.getAttribute( 'name' ) == 'CollisionEnergy':\n\t\t\t\t\t\tcollisionEnergy = float( param.getAttribute( 'value' ))\n\n\n\n\t\t\tself.data[ \"scans\" ].append({ \n\t\t\t\t\"retentionTime\" : rt,\n\t\t\t\t\"polarity\" : polarity, \n\t\t\t\t\"msLevel\" : msLevel, \n\t\t\t\t\"id\" : scanId,\n\t\t\t\t\"mzRange\" : [ lowMz, highMz ],\n\t\t\t\t\"parentScan\" : parentScan,\n\t\t\t\t\"precursorMz\" : precursorMz,\n\t\t\t\t\"collisionEnergy\" : collisionEnergy,\n\t\t\t\t\"mzArray\" : list( massValues ),\n\t\t\t\t\"intensityArray\" : list( intensityValues )\n\t\t\t})\n\n\t\treturn True\n\n\n\tdef _unpackMzData( self, dataNode ):\n\t\t\"\"\"\n\t\tInternal function. Unpacks the scan data contained in a <data> node in mzdata \n\t\tformat.\n\n\t\t:Parameters:\n\t\t\tdataNode : xmlNode\n\t\t\t\tThe xml node containing the scan data to be unpacked.\n\n\t\t\"\"\"\n\t\tscanSize = int( dataNode.getAttribute( 'length' ))\n\t\tif not scanSize:\n\t\t\treturn []\n\t\t# else\n\t\tif dataNode.getAttribute( 'endian' ) == 'little':\n\t\t\tbyteOrder = '<'\n\t\telse:\n\t\t\tbyteOrder = '>'\n\t\tif dataNode.getAttribute( 'precision' ) == '64':\n\t\t\tdataType = 'd'\n\t\telse: \n\t\t\tdataType = 'f'\n\n\t\treturn struct.unpack( byteOrder + ( dataType scanSize ), \n\t\t\tb64decode( re.sub( \"<.?>\", \"\", dataNode.toxml( ))))\n\n\tdef readMzXml( self, filename ):\n\t\t\"\"\"\n\t\tRead a file in mzXML format.\n\n\t\t:Parameters:\n\t\t\tfilename : str\n\t\t\t\tThe name of the file to load.\n\n\t\t\"\"\"\n\t\tself.data = { \"scans\" : [] }\n\t\tdataFile = parse( filename )\n\t\tself.data[ 'sourceFile' ] = dataFile.getElementsByTagName( 'parentFile' )[ 0 ].\\\n\t\t\tgetAttribute( 'fileName' )\n\t\tscans = dataFile.getElementsByTagName( 'scan' )\n\t\tfor scan in scans:\n\t\t\tcollisionEnergy = None\n\t\t\tprecursorMz = None\n\t\t\tmsLevel = int( scan.getAttribute( \"msLevel\" ))\n\t\t\tscanSize = int( scan.getAttribute( 'peaksCount' ))\n\t\t\trt = float( scan.getAttribute( 'retentionTime' )[ 2:-1 ] ) / 60\n\t\t\tscanId = int( scan.getAttribute( 'num' ))\n\t\t\tlowMz = float( scan.getAttribute( 'lowMz' ))\n\t\t\thighMz = float( scan.getAttribute( 'highMz' ))\n\t\t\tif ( scan.getAttribute( 'polarity' ) == '+' ):\n\t\t\t\tpolarity = 1\n\t\t\telse:\n\t\t\t\tpolarity = -1\n\t\t\tif msLevel == 1:\n\t\t\t\tparentScan = None\n\t\t\telse:\n\t\t\t\tparentScan = int( scan.parentNode.getAttribute( 'num' ))\n\t\t\t\tif ( scan.getAttribute( 'collisionEnergy' )):\n\t\t\t\t\tcollisionEnergy = float( scan.getAttribute( 'collisionEnergy' ))\n\t\t\t\tprecursorTags = scan.getElementsByTagName( 'precursorMz' )\n\t\t\t\tif ( len( precursorTags )):\n\t\t\t\t\tprecursorMz = float( re.sub( r\"<.?>\", \"\", precursorTags[ 0 ].toxml( )).strip( ))\n\t\t\t\n\n\t\t\tpeaks = scan.firstChild\n\t\t\twhile not ( peaks.nodeType == peaks.ELEMENT_NODE and peaks.tagName == 'peaks' ):\n\t\t\t\tpeaks = peaks.nextSibling\n\n\t\t\tif peaks.getAttribute( 'precision' ) == '64':\n\t\t\t\ttype = 'd'\n\t\t\telse: \n\t\t\t\ttype='f'\n\t\t\tbyteOrder = '>'\n\n\t\t\t# get all of the text (non-tag) content of peaks\n\t\t\tpackedData = re.sub( r\"<.?>\", \"\", peaks.toxml( )).strip( )\n\t\t\tif not scanSize:\n\t\t\t\tmassValues = []\n\t\t\t\tintensityValues = []\n\t\t\telse:\n\t\t\t\tif ( peaks.getAttribute( 'compressionType' ) == 'zlib' ):\n\t\t\t\t\tdata = struct.unpack( byteOrder + ( type scanSize * 2 ), zlib.decompress( b64decode( packedData )))\n\t\t\t\telse:\n\t\t\t\t\tdata = struct.unpack( byteOrder + ( type * scanSize * 2 ), b64decode( packedData ))\n\t\t\t\tmassValues = data[ 0::2 ]\n\t\t\t\tintensityValues = data[ 1::2 ] \n\n\t\t\tself.data[ \"scans\" ].append({ \n\t\t\t\t\"retentionTime\" : rt,\n\t\t\t\t\"polarity\" : polarity, \n\t\t\t\t\"msLevel\" : msLevel, \n\t\t\t\t\"id\" : scanId,\n\t\t\t\t\"mzRange\" : [ lowMz, highMz ],\n\t\t\t\t\"parentScan\" : parentScan,\n\t\t\t\t\"precursorMz\" : precursorMz,\n\t\t\t\t\"collisionEnergy\" : collisionEnergy,\n\t\t\t\t\"mzArray\" : list( massValues ),\n\t\t\t\t\"intensityArray\" : list( intensityValues )\n\t\t\t})\n\t\treturn True\n\n\n\tdef readMzMl( self, filename ):\n\t\traise NotImplementedError( \n\t\t\t\"Reading from this file type has not yet been implemented.\" )\n\t\t\n\n\tdef _getChildNode( self, node, child ):\n\t\t\"\"\"\n\t\tInternal function. Finds the child node of the passed in xml node with the \n\t\tgiven tag name.\n\n\t\t:Parameters:\n\t\t\tnode : minidom node\n\t\t\t\tA minidom node object\n\t\t\tchild : str\n\t\t\t\tA string containing the tag name of the child node to return.\n\n\t\trtype: minidom node\n\t\treturn: The requested child of the minidom node.\n\t\t\"\"\"\n\t\treturnvalue = node.firstChild\n\t\twhile returnvalue and not ( \n\t\t\treturnvalue.nodeType == returnvalue.ELEMENT_NODE and \n\t\t\treturnvalue.tagName == child ):\n\n\t\t\treturnvalue = returnvalue.nextSibling\n\t\treturn returnvalue\n\n\tdef readJson( self, filename ):\n\t\t\"\"\"\n\t\tReads ms data from a file containing gzipped JSON data. No checks are done, \n\t\tso make sure the data is of the same format as that produced by this \n\t\tlibrary, otherwise, unpredictable things may happen. This method may not be\n\t\tsupported on versions of python prior to 2.5.\n\t\t:Parameters:\n\t\t\tfilename : string\n\t\t\t\tThe name of a file containing gzip compressed JSON data\n\t\t\"\"\"\n\t\tif not json:\n\t\t\traise NotImplementedError( \"This method is not supported in your version of Python\" )\n\t\tin_ = open( filename, 'r' )\n\t\tself.data = json.load( in_ )\n\t\tin_.close( )\n\t\treturn True\n\n\tdef readJsonGz( self, filename ):\n\t\t\"\"\"\n\t\tReads ms data from a file containing gzipped JSON data. No checks are done, \n\t\tso make sure the data is of the same format as that produced by this \n\t\tlibrary, otherwise, unpredictable things may happen. This method may not be\n\t\tsupported on versions of python prior to 2.5.\n\t\t:Parameters:\n\t\t\tfilename : string\n\t\t\t\tThe name of a file containing gzip compressed JSON data\n\t\t\"\"\"\n\t\tif not json:\n\t\t\traise NotImplementedError( \"This method is not supported in your version of Python\" )\n\t\tin_ = gzip.open( filename, 'r' )\n\t\tself.data = json.load( in_ )\n\t\tin_.close( )\n\t\treturn True\n\n\tdef write( self, filename ):\n\t\t\"\"\"\n\t\tLoad a file into this reference. This method will automatically detect the\n\t\tfile type based on the file extension.\n\n\t\t:Parameters:\n\t\t\tfilename : str\n\t\t\t\tThe name of the file to load.\n\n\t\t\"\"\"\n\t\n\t\tif filename.lower( ).endswith( \".csv\" ):\n\t\t\treturn self.writeCsv( filename )\n\n\t\telif ( filename.lower( ).endswith( \".mzdata\" ) or \n\t\t filename.lower( ).endswith( \".mzdata.xml\" )):\n\t\t\treturn self.writeMzData( filename )\n\n\t\telif filename.lower( ).endswith( \".mzxml\" ):\n\t\t\treturn self.writeMzXml( filename )\n\n\t\telif filename.lower( ).endswith( \".mzml\" ):\n\t\t\treturn self.writeMzMl( filename )\n\n\t\telif filename.lower( ).endswith( \".json\" ):\n\t\t\treturn self.writeJson( filename )\n\n\t\telif filename.lower( ).endswith( \".json.gz\" ):\n\t\t\treturn self.writeJsonGz( filename )\n\n\t\telse:\n\t\t\tsys.stderr.write( \"Unrecognized file type for %s\\n\" % filename )\n\t\t\treturn False\n\n\tdef writeCsv( self, filename ):\n\t\t\"\"\"\n\t\t:Parameters:\n\t\t\tfilename : string\n\t\t\t\tThe name of the file to write to.\n\n\t\trtype: bool\n\t\treturn: True if the write succeeded\n\t\t\"\"\"\n\t\tout = open( filename, 'w' )\n\t\tout.write( \"[data source]\\n\" )\n\t\tout.write( \"file name,%s\\n\" % self.data[ 'sourceFile' ] )\n\t\tout.write( \"[filters]\\n\" )\n\t\tout.write( \"mass range,%f,%f\\n\" % ( self.minMz( ), self.maxMz( )))\n\t\trtList = [ x['retentionTime'] for x in self.data['scans']]\n\t\tout.write( \"time range,%f,%f\\n\" % ( min( rtList ), max( rtList )))\n\t\tout.write( \"number of spectra,%d\\n\" % len( self.data['scans'] ))\n\t\tout.write( \"[format]\\n\" )\n\t\tout.write( \"retention time, sample, period, experiment, polarity, scan type, points, x1, y1, x2, y2, ...\\n\" )\n\t\tout.write( \"[spectra]\\n\" )\n\t\tlevel2 = False\n\t\tfor scan in self.data[ 'scans' ]:\n\t\t\tif ( scan[ 'msLevel' ] > 1 ):\n\t\t\t\tif not level2:\n\t\t\t\t\tprint( \"Agilent CSV format does not support multimensional data, ignoring scans with level > 1\" )\n\t\t\t\t\tlevel2 = True\n\t\t\t\tcontinue\n\n\t\t\tif ( scan[ 'polarity' ] > 0 ):\n\t\t\t\tpolarity = '+'\n\t\t\telse:\n\t\t\t\tpolarity = '-'\n\t\t\tout.write( \"%f,%d,%d,%d,%s,%s,%d\" % \n\t\t\t\t\t\t\t\t( scan[ 'retentionTime' ], 1, 1, 1, polarity, \"peak\", \n\t\t\t\t\t\t\t\tlen( scan[ 'mzArray' ])))\n\t\t\tfor point in zip( scan[ 'mzArray' ], scan[ 'intensityArray' ]):\n\t\t\t\tout.write( ',%f,%f' % point )\n\t\t\tout.write( \"\\n\" )\n\t\tout.close( )\n\t\t\t\n\tdef writeMzData( self, filename ):\n\t\tout = open( filename, 'w' );\n\t\tout.write( '<?xml version=\"1.0\" encoding=\"UTF-8\"?>\\n' )\n\t\tout.write( '<mzData version=\"1.05\" accessionNumber=\"psi-ms:100\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\">\\n' )\n\t\tout.write( ' <cvLookup cdLabel=\"psi\" fullName=\"The PSI Ontology\" version=\"1.00\" address=\"http://psidev.sourceforge.net/ontology\" />\\n' )\n\t\tout.write( ' <description>\\n' )\n\t\tout.write( ' <admin>\\n' )\n\t\tout.write( ' <sampleName/>\\n' )\n\t\tout.write( ' <sampleDescription comment=\"\" />\\n' )\n\t\tout.write( ' <sourceFile>\\n' )\n\t\tout.write( ' <nameOfFile />\\n' )\n\t\tout.write( ' <pathToFile />\\n' )\n\t\tout.write( ' </sourceFile>\\n' )\n\t\tout.write( ' <contact>\\n' )\n\t\tout.write( ' <name />\\n' )\n\t\tout.write( ' <institution />\\n' )\n\t\tout.write( ' <contactInfo />\\n' )\n\t\tout.write( ' </contact>\\n' )\n\t\tout.write( ' </admin>\\n' )\n\t\tout.write( ' <instrument>\\n' )\n\t\tout.write( ' <instrumentName />\\n' )\n\t\tout.write( ' <source />\\n' )\n\t\tout.write( ' <analyzerList count=\"1\">\\n' )\n\t\tout.write( ' <analyzer>\\n' )\n\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000010\" name=\"AnalyzerType\" value=\"unknown\" />\\n' )\n\t\tout.write( ' </analyzer>\\n' )\n\t\tout.write( ' </analyzerList>\\n' )\n\t\tout.write( ' <detector>\\n' )\n\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000026\" name=\"DetectorType\" value=\"unknown\" />\\n' )\n\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000029\" name=\"SamplingFrequency\" value=\"unknown\" />\\n' )\n\t\tout.write( ' </detector>\\n' )\n\t\tout.write( ' <additional />\\n' )\n\t\tout.write( ' </instrument>\\n' )\n\t\tout.write( ' <dataProcessing>\\n' )\n\t\tout.write( ' <software completionTime=\"\">\\n' )\n\t\tout.write( ' <name>pymzlib, Version=%s</name>\\n' % VERSION )\n\t\tout.write( ' <version>%s</version>\\n' % VERSION )\n\t\tout.write( ' <comments />\\n' )\n\t\tout.write( ' </software>\\n' )\n\t\tout.write( ' <processingMethod>\\n' )\n\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000033\" name=\"deisotoped\" value=\"unknown\" />\\n' )\n\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000034\" name=\"chargeDeconvolved\" value=\"unknown\" />\\n' )\n\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000035\" name=\"peakProcessing\" value=\"unknown\" />\\n' )\n\t\tout.write( ' </processingMethod>\\n' )\n\t\tout.write( ' </dataProcessing>\\n' )\n\t\tout.write( ' </description>\\n' )\n\t\tout.write( ' <spectrumList count=\"%d\">\\n' % len( self.data[ 'scans' ]))\n\t\tfor scan in self.data[ 'scans' ]:\n\t\t\tif ( scan[ 'polarity' ] > 0 ):\n\t\t\t\tpolarity = 'Positive'\n\t\t\telse:\n\t\t\t\tpolarity = 'Negative'\n\t\t\tout.write( ' <spectrum id=\"%d\">\\n' % scan[ 'id' ])\n\t\t\tout.write( ' <spectrumDesc>\\n' )\n\t\t\tout.write( ' <spectrumSettings>\\n' )\n\t\t\tout.write( ' <acqSpecification spectrumType=\"unknown\" methodOfCombination=\"unknown\" count=\"1\">\\n' )\n\t\t\tout.write( ' <acquisition number=\"%d\" />\\n' % scan[ 'id' ])\n\t\t\tout.write( ' </acqSpecification>\\n' )\n\t\t\tout.write( ' <spectrumInstrument msLevel=\"%d\" mzRangeStart=\"%f\" mzRangeStop=\"%f\">\\n' % ( scan[ 'msLevel' ], scan[ 'mzRange' ][ 0 ], scan[ 'mzRange' ][ 1 ]))\n\t\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000036\" name=\"ScanMode\" value=\"Scan\" />\\n' )\n\t\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000037\" name=\"Polarity\" value=\"%s\" />\\n' % polarity )\n\t\t\tout.write( ' <cvParam cvLabel=\"psi\" accession=\"PSI:1000038\" name=\"TimeInMinutes\" value=\"%f\" />\\n' % scan[ 'retentionTime' ])\n\t\t\tout.write( ' </spectrumInstrument>\\n' )\n\t\t\tout.write( ' </spectrumSettings>\\n' )\n\t\t\tout.write( ' </spectrumDesc>\\n' )\n\t\t\tout.write( ' <mzArrayBinary>\\n' )\n\t\t\tdataLen = len( scan[ 'mzArray' ])\n\t\t\tout.write( ' <data precision=\"64\" endian=\"little\" length=\"%d\">%s</data>\\n' % ( dataLen, b64encode( struct.pack( '<' + ( 'd' * dataLen ), scan[ 'mzArray' ]))))\n\t\t\tout.write( ' </mzArrayBinary>\\n' )\n\t\t\tout.write( ' <intenArrayBinary>\\n' )\n\t\t\tout.write( ' <data precision=\"64\" endian=\"little\" length=\"%d\">%s</data>\\n' % ( dataLen, b64encode( struct.pack( '<' + ( 'd' dataLen ), scan[ 'intensityArray' ]))))\n\t\t\tout.write( ' </intenArrayBinary>\\n' )\n\t\t\tout.write( ' </spectrum>\\n' )\n\t\tout.write( ' </spectrumList>\\n' )\n\t\tout.write( '</mzData>\\n' )\n\n\tdef writeMzXML( self, filename ):\n\t\traise NotImplementedError( \n\t\t\t\"Writing to this file type has not yet been implemented.\" )\n\n\tdef writeMzML( self, filename ):\n\t\traise NotImplementedError( \n\t\t\t\"Writing to this file type has not yet been implemented.\" )\n\n\tdef writeJson( self, filename, indent=None ):\n\t\t\"\"\"\n\t\tDumps the data to a JSON array.\n\t\t:Parameters:\n\t\t\tmaData : dict\n\t\t\t\tA dictionary object containing scan data, normally returned from\n\t\t\tfilename : string\n\t\t\t\tThe name of the file to write to.\n\t\t\tindent : int\n\t\t\t\tLevel to indent for pretty-printing, or None for no pretty-print.\n\t\t\t\tDefaults to None\n\t\t\"\"\"\n\t\tif not json:\n\t\t\traise NotImplementedError( \"This method is not supported in your version of Python\" )\n\t\tif( indent ):\n\t\t\tsep = (', ',': ')\n\t\telse:\n\t\t\tsep = (',',':')\n\t\tout = open( filename, 'w' )\n\t\tjson.dump( self.data, out, indent=indent, separators=sep )\n\t\tout.close( )\n\n\tdef writeJsonGz( self, filename, indent=None, compressionLevel=6 ):\n\t\t\"\"\"\n\t\tDumps the data to a JSON array, compressed with zlib.\n\t\t:Parameters:\n\t\t\tmaData : dict\n\t\t\t\tA dictionary object containing scan data, normally returned from\n\t\t\tfilename : string\n\t\t\t\tThe name of the file to write to.\n\t\t\tindent : int\n\t\t\t\tLevel to indent for pretty-printing, or None for no pretty-print.\n\t\t\t\tDefaults to None\n\t\t\tcompressionLevel : int\n\t\t\t\tCompression level to use - 0 for least compression, 9 for most.\n\t\t\t\tDefaults to 6.\n\t\t\"\"\"\n\t\tif( indent ):\n\t\t\tsep = (', ',': ')\n\t\telse:\n\t\t\tsep = (',',':')\n\t\tout = gzip.open( filename, 'wb', compressionLevel )\n\t\tout.write( json.dumps( self.data, indent=indent, separators=sep))\n\t\tout.close( )\n\n\n" }, { "alpha_fraction": 0.6423113942146301, "alphanum_fraction": 0.6578319072723389, "avg_line_length": 26.012903213500977, "blob_id": "5da4624160f53aff5c9cc75ddf4903f17a37faa1", "content_id": "34fcfcdd88d64803ee4897d6afec87c77a3df703", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4188, "license_type": "no_license", "max_line_length": 66, "num_lines": 155, "path": "/mzplot_cgi.py", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python \n\"\"\"\n\nCopyright: 2010 Thomas McGrew\n\nLicense: MIT license.\n\n\tPermission is hereby granted, free of charge, to any person\n\tobtaining a copy of this software and associated documentation\n\tfiles (the \"Software\"), to deal in the Software without\n\trestriction, including without limitation the rights to use,\n\tcopy, modify, merge, publish, distribute, sublicense, and/or sell\n\tcopies of the Software, and to permit persons to whom the\n\tSoftware is furnished to do so, subject to the following\n\tconditions:\n\n\tThe above copyright notice and this permission notice shall be\n\tincluded in all copies or substantial portions of the Software.\n\n\tTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n\tEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\n\tOF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n\tNONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT\n\tHOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,\n\tWHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n\tFROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\n\tOTHER DEALINGS IN THE SOFTWARE.\n\n\"\"\"\n\nVERSION = \"0.2.1\"\n\nimport cgi \nimport sys\nimport os\nimport re\nfrom base64 import b64encode\nfrom time import sleep\ntry:\n\tfrom hashlib import sha1\nexcept ImportError:\n\tfrom sha import sha as sha1\nimport cgitb; cgitb.enable( )\n\n# local imports\nos.environ[ 'HOME' ] = \"/tmp\"\nimport mzplot\n\nDATA_ROOT = \"/var/mzplot\"\nCACHE_DIR = \"/tmp/mzplot\"\n\nclass Options( object ):\n\tdef __init__( self ):\n\t\tself.minTime = 0\n\t\tself.maxTime = 0\n\t\tself.bpc = False\n\t\tself.mass = 0\n\t\tself.massWindow = 0.2\n\t\tself.connectPeaks = False\n\t\tself.showLegend = True\n\t\tself.shortFilename = True\n\t\tself.massLabels = False\n\t\tself.showPeaks = True\n\t\tself.showNoise = False\n\t\tself.markerAlpha = 1\n\t\tself.lineWidth = 1\n\t\tself.scriptMode = True\n\t\tself.verbosity = 0\n\t\tself.removeNoise = False\n\t\tself.outputFile = None\n\t\tself.width = 800\n\t\tself.height = 450\n\t\tself.dpi = 72\n\t\tself.filterLevel = 0\n\t\tself.normalize = False\n\n\tdef hash( self ):\n\t\toptHash = sha1( )\n\t\toptHash.update( str( self.__dict__ ))\n\t\treturn optHash.digest( )\n\n\ndef main( ):\n\toptions = Options( )\n\tos.nice( 10 )\n\tform = cgi.FieldStorage( )\n\tfor i in form.keys( ):\n\t\tif not i == \"files\":\n\t\t\tvalue = None\n\t\t\ttry: \n\t\t\t\tvalue = float( form[ i ].value )\n\t\t\texcept ValueError:\n\t\t\t\tif form[ i ].value.lower( ) == \"true\":\n\t\t\t\t\tvalue = True\n\t\t\t\telif form[ i ].value.lower( ) == \"false\":\n\t\t\t\t\tvalue = False\n\t\t\tif ( value ):\n\t\t\t\toptions.__setattr__( i, value )\n\n\tfiles = []\n\tif form.has_key( 'files' ):\n\t\tfor file_ in re.split( \"[,\|]\", form[ 'files' ].value ):\n\t\t\tif ( \"../\" in file_ ):\n\t\t\t\tprint \"Content-Type: text/plain\"\n\t\t\t\tprint\n\t\t\t\tprint \"Invalid path: \" + file_\n\t\t\t\treturn\n\t\t\tfiles.append( DATA_ROOT + \"/\" + file_ )\n\n\tif not os.path.exists( CACHE_DIR ):\n\t\tos.makedirs( CACHE_DIR )\n\n\tfileHash = sha1( )\n\tfileHash.update( str( sorted( files )))\n\toptions.outputFile = ( CACHE_DIR + \"/\" + \n\t b64encode( options.hash( ) + fileHash.digest( ), \"_.\") + \n\t \".png\" ).replace( \"=\", \"\" )\n\tlockfile = options.outputFile + \".lock\"\n\t\t\n\tif not os.path.exists( options.outputFile ):\n\t\tif not os.path.exists( lockfile ):\n\t\t\tf = open( lockfile, 'w' )\n\t\t\tf.write( str( os.getpid( )))\n\t\t\tf.close( )\n\t\t\ttry:\n\t\t\t\tmzplot.main( options, files )\n\t\t\tfinally:\n\t\t\t\tos.remove( lockfile )\n\t\telse:\n\t\t\twait_time = 2 #seconds\n\t\t\ttotal_wait = 120 #seconds\n\t\t\twhile total_wait > 0 and os.path.exists( lockfile ):\n\t\t\t\tsleep( wait_time )\n\t\t\t\ttotal_wait -= wait_time\n\n\t# headers\n\tprint \"Content-Type: image/png\"\n\tif os.path.exists( options.outputFile ):\n\t\timageData = open( options.outputFile, 'r' )\n\t\timageBytes = imageData.read( )\n\t\timageData.close( )\n\telse:\n\t\timageBytes = str( )\n\tprint \"Content-Length: %d\" % len( imageBytes )\n\t# arbitrary expiration date way in the future\n\t# essentially \"cache this as long as you want.\"\n#\tprint \"Expires: Sun, 31 Dec 2006 16:00:00 GMT\"\n\tprint \"Expires: Sun, 31 Dec 2034 16:00:00 GMT\"\n\tprint\n\t# end headers\n\tsys.stdout.write( imageBytes )\n\n# run the main method if this file isn't being imported.\nif ( __name__ == \"__main__\" ):\n\tmain( )\n\n" }, { "alpha_fraction": 0.5983465909957886, "alphanum_fraction": 0.6085119247436523, "avg_line_length": 35.12610626220703, "blob_id": "77b0903be3ab13edd8146848f0431f071fafd82d", "content_id": "7d5f11a0be6801cec91d2d23ae1c74b3c51f4159", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 16330, "license_type": "no_license", "max_line_length": 89, "num_lines": 452, "path": "/mzplot.py", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\"\"\"\n\nCopyright: 2010 Thomas McGrew\n\nLicense: MIT license.\n\n\tPermission is hereby granted, free of charge, to any person\n\tobtaining a copy of this software and associated documentation\n\tfiles (the \"Software\"), to deal in the Software without\n\trestriction, including without limitation the rights to use,\n\tcopy, modify, merge, publish, distribute, sublicense, and/or sell\n\tcopies of the Software, and to permit persons to whom the\n\tSoftware is furnished to do so, subject to the following\n\tconditions:\n\n\tThe above copyright notice and this permission notice shall be\n\tincluded in all copies or substantial portions of the Software.\n\n\tTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n\tEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\n\tOF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\n\tNONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT\n\tHOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,\n\tWHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n\tFROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\n\tOTHER DEALINGS IN THE SOFTWARE.\n\n\"\"\"\n\nVERSION = \"0.2.1.2012.02.27\"\n\nimport sys\nimport os\nimport os.path\n#from hashlib import sha1\n#import cPickle\nfrom optparse import OptionParser,SUPPRESS_HELP\nimport numpy as numerical\nimport math\nimport mzlib\nfrom csv import DictReader\ntry:\n\timport filters\nexcept ImportError:\n\tfilters = None\ntry:\n\timport matplotlib\n\tfrom matplotlib.font_manager import FontProperties\nexcept ImportError:\n\tsys.stderr.write( \"\\n THIS PROGRAM REQUIRES MATPLOTLIB, WHICH DOES NOT \"\n\t \"APPEAR TO BE INSTALLED \\n\" )\n\traise \n\n# To do: \n# add an option to allow indexing by scan number\n\nCOLORS = {\n\t# Available colors (the lower case letter is used for that color):\n\t# rED, gREEN, bLUE, cYAN, mAGENTA, yELLOW, BLACk, wHITE\t\n\t# html color codes can also be used.\n\t\"intensity\" : [ \"b\",\"r\",\"y\",\"c\",\"m\",\"g\" ],\n\t\"noise\" : [ \"b\",\"r\",\"y\",\"c\",\"m\",\"g\" ],\n\t\"ref\" : [ \"k\",\"c\",\"m\",\"y\",\"r\",\"g\",\"b\"]\n}\n\ndef parseOpts( ):\n\t\"\"\"\n\tParses the command line options passed into the program\n\n\treturns:\n\t\t2 element list ( opts, args ) \n\t\n\t\"\"\"\t\n\toptparser = OptionParser( version=\"%prog \" + VERSION )\n\n\toptparser.add_option( \"--minrt\", type=\"float\", default=0, \n\t dest=\"minTime\", metavar=\"RT\", help=\"The minimum \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"retention time to show on the graph\" )\n\n\toptparser.add_option( \"--maxrt\", type=\"float\", default=0, \n\t dest=\"maxTime\", metavar=\"RT\", help=\"The maximum \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"retention time to show on the graph\" )\n\n\toptparser.add_option( \"--bpc\", action=\"store_true\", default=False, dest=\"bpc\",\n\t help=\"Show only base peaks, i.e. the highest intensity \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"value at each retention time (BPC) instead of the \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"total ion chromatogram (TIC).\" )\n\n\toptparser.add_option( \"-m\", \"--mass\", type=\"float\", dest=\"mass\", \n\t help=\"Filter data by a particular mass, a.k.a Selected \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"Ion Chromatogram (SIC)\" )\n\t\n\toptparser.add_option( \"-w\", \"--mass-window\", type=\"float\", dest=\"massWindow\",\n\t default=0.2, metavar=\"SIZE\", help=\"The range of the \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"mass to be displayed in Dalton. Default is %default. \" \n\t\t\t\t\t\t\t\t\t\t\t \"This option is only used with -m (SIC mode)\" )\n\t\t\t\t\t\t\t\t\t\t\t \n\toptparser.add_option( \"-c\", \"--connect-peaks\", action=\"store_true\", \n\t dest=\"connectPeaks\", help=\"Draw lines connecting the \"\n\t\t\t\t\t\t\t\t\t\t\t\t \"peaks from Xmass output\" )\n\n\toptparser.add_option( \"-l\", \"--legend\", action=\"store_true\", default=False, \n\t dest=\"showLegend\", help=\"Display a legend.\" )\n\n\toptparser.add_option( \"--short-filename\", action=\"store_true\", default=False, \n\t dest=\"shortFilename\", help=\"Display only the filename \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"(without the path) in the legend.\" )\n\n\toptparser.add_option( \"--labels\", action=\"store_true\", dest=\"massLabels\", \n\t help=\"Show a label for each peak containing its mass\" )\n\n\toptparser.add_option( \"--hide-peaks\", action=\"store_false\", default=True, \n\t dest=\"showPeaks\", help=\"Do not show the peak bars from \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"the xmass output on the graph\" )\n\n\toptparser.add_option( \"-n\", \"--noise\", action=\"store_true\", default=False, \n\t dest=\"showNoise\", help=\"Show the noise from the xmass \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"output on the graph\" )\n\n\toptparser.add_option( \"--alpha\", type=\"float\", default=1, dest=\"markerAlpha\", \n\t metavar=\"ALPHA\", help=\"Set the starting opacity level \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"of the lines on the graph (0.0-1.0, Defaults to \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"%default)\" )\n\n\toptparser.add_option( \"--line-width\", type=\"float\", default=1, \n\t dest=\"lineWidth\", metavar=\"WIDTH\", help=\"Set the width \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"of the bars on the graph. Defaults to %default\" )\n\n\toptparser.add_option( \"-s\", \"--script\", action=\"store_true\", \n\t dest=\"scriptMode\", help=\"Run in script mode, i.e. do \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"not display the graph. This is only useful with the \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"-o option\" )\n\n\toptparser.add_option( \"-v\", \"--verbose\", action=\"count\", dest=\"verbosity\", \n\t default=0, help=\"Print more messages about what the \"\n\t\t\t\t\t\t\t\t\t\t\t \"program is doing.\" )\n\n\toptparser.add_option( \"--subtract-noise\", action=\"store_true\", \n\t dest=\"removeNoise\", help=\"Subtract the noise from the \"\n\t\t\t\t\t\t\t\t\t\t\t\t\" intensity values in the peak list\" )\n\n\toptparser.add_option( \"-o\", \"--out\", dest=\"outputFile\", metavar=\"FILE\",\n\t help=\"Save the generated graph to the given file. \"\n\t\t\t\t\t\t\t\t\t\t\t \"Supported types depends on your platform, but most \"\n\t\t\t\t\t\t\t\t\t\t\t \"platforms support png, pdf, ps, eps and svg.\" )\n\n\toptparser.add_option( \"--width\", type=\"int\", default=800, dest=\"width\",\n\t help=\"The width of the generated image. \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"Defaults to %default. For use with -o\" )\n\n\toptparser.add_option( \"--height\", type=\"int\", default=450, dest=\"height\",\n\t help=\"The height of the generated image. \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"Defaults to %default. For use with -o\" )\n\n\toptparser.add_option( \"--dpi\", type=\"int\", default=72, dest=\"dpi\",\n\t help=\"The dpi of the generated image. \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"Defaults to %default. For use with -o\" )\n\n#\toptparser.add_option( \"--by-scan\", action=\"store_true\", dest=\"byScan\",\n#\t help=\"Index the graph by scan number instead of retention time\" )\n\n\tif filters:\n\t\toptparser.add_option( \"--hpf\", type=\"float\", dest=\"hpfThreshold\", \n\t\t metavar=\"THRESHOLD\", help=\"Run any chromatogram data \"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\"through an fft high pass filter before displaying. \"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\"hpfThreshold should be a value between 0 and 1\" )\n\n\t\toptparser.add_option( \"--lpf\", type=\"float\", dest=\"lpfThreshold\", \n\t\t metavar=\"THRESHOLD\", help=\"Run any chromatogram data \"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\"through an fft low pass filter before displaying. \" \n\t\t\t\t\t\t\t\t\t\t\t\t\t\"lpfThreshold should be a value between 0 and 1\" )\n\n\toptparser.add_option( \"--snratio\", type=\"float\", default=0, \n\t dest=\"filterLevel\", metavar=\"RATIO\", help=\"Drop peaks \"\n\t\t\t\t\t\t\t\t\t\t\t\t\"whose signal/noise ratio is less than RATIO\" )\n\n\toptparser.add_option( \"--normalize\", action=\"store_true\", dest=\"normalize\",\n\t help=\"Normalize all plots to have a maximum value of 1\" )\n\n\treturn optparser.parse_args( )\n\n\ndef main( options=None, args=None ):\n\t\"\"\"The main method\"\"\"\n\tglobal COLORS\n\n\tif options.scriptMode:\n\t\tmatplotlib.use( 'Agg' )\n\timport pylab\n\n\tthisFigure = pylab.figure( )\n\n\tif options.outputFile:\n\t\tthisFigure.set_size_inches(( \n\t\t float( options.width ) / options.dpi, \n\t\t\tfloat( options.height ) / options.dpi ))\n\n\tpylab.subplots_adjust( left = 0.6 / options.width options.dpi, \n\t right = 1.0 - 0.2 / options.width * options.dpi, \n\t top = 1.0 - 0.45 / options.height * options.dpi, \n\t\t\t\t\t\t\t\t\t\t\t\t bottom = 0.5 / options.height * options.dpi )\n\tbarOffset = options.lineWidth / 2\n\tbarAlpha = options.markerAlpha * 2 / 3\n\n\n\trawFiles = [ ]\n\trawTypes = [ '.csv', '.mzdata', '.mzxml', '.mzxml.xml', \n\t '.json', '.json.gz' ]\n\tfor i in range( len( args )-1, -1, -1 ):\n\t\targ = args[ i ]\n\t\ttry:\n\t\t\t# check the extension to see if this is xmass input data\n\t\t\tfor type_ in rawTypes:\n\t\t\t\tif arg.lower( ).endswith( type_ ):\n\t\t\t\t\trawFiles.append( args.pop( i ))\n\t\t\t\t\tcontinue\n\t\texcept ValueError:\n\t\t\tpass\n\t\t\n\n\tif rawFiles:\n\t\tfor r in rawFiles:\n\t\t\tref = mzlib.RawData( )\n\t\t\tif not ( ref.read( r )):\n\t\t\t\tsys.stderr.write( \"Error: Unable to load data from '%s'\" % r )\n\t\t\t\tsys.exit( -1 )\n\n\t\t\tif options.shortFilename:\n\t\t\t\tfilename = os.path.basename( r )\n\t\t\telse:\n\t\t\t\tfilename = r\n\n\t\t\t# apply any filters\n\t\t\tif options.mass:\n\t\t\t\tref.onlyMz( options.mass, options.massWindow )\n\n\t\t\tif options.maxTime or options.minTime:\n\t\t\t\tif options.maxTime:\n\t\t\t\t\tref.onlyScans( options.minTime, options.maxTime )\n\t\t\t\telse:\n\t\t\t\t\tref.onlyScans( options.minTime )\n\n\t\t\trt = [ scan[ \"retentionTime\" ] for scan in ref if scan[ \"msLevel\" ] == 1 ]\n\t\t\tif options.bpc:\n\t\t\t\tyAxis = ref.bpc( 1 )\n\t\t\telse:\n\t\t\t\tyAxis = ref.tic( 1 )\n\n\t\t\tif filters:\n\t\t\t\tif options.lpfThreshold and options.hpfThreshold:\n\t\t\t\t\tyAxis = filters.bpf( yAxis, options.hpfThreshold, options.lpfThreshold )\n\t\t\t\telif options.lpfThreshold:\n\t\t\t\t\tyAxis = filters.lpf( yAxis, options.lpfThreshold )\n\t\t\t\telif options.hpfThreshold:\n\t\t\t\t\tyAxis = filters.hpf( yAxis, options.hpfThreshold )\n\n\t\t\tif options.normalize:\n\t\t\t\tif len( yAxis ):\n\t\t\t\t\tmax_ = max( yAxis )\n\t\t\t\t\tif max_:\n\t\t\t\t\t\tyAxis = [ x / max_ for x in yAxis ]\n\n\t\t\tif options.normalize:\n\t\t\t\tlabel = filename + \" (normalized)\"\n\t\t\telse:\n\t\t\t\tlabel = filename\n\t\t\tpylab.plot( rt, yAxis, COLORS['ref'][0] , alpha = options.markerAlpha,\n\t\t\t linewidth=options.lineWidth, \n\t\t\t\t\t label = label )\n\t\t\tCOLORS['ref'] = COLORS['ref'][1:] + [ COLORS['ref'][0]]\n\t\t\tif not options.scriptMode:\n\n\t\t\t\tdef findMedian( sortedArray ):\n\t\t\t\t\tarrayLen = len( sortedArray )\n\t\t\t\t\tif arrayLen % 2:\n\t\t\t\t\t\tmedian = sortedArray[ arrayLen // 2 ] * sortedArray[ arrayLen // 2 + 1 ]\n\t\t\t\t\telse:\n\t\t\t\t\t\tmedian = sortedArray[ arrayLen // 2 ]\n\t\t\t\t\treturn median\n\n\t\t\t\tarray = list( yAxis );\n\t\t\t\tarray.sort( )\n\t\t\t\tmedian = findMedian( array )\n\t\t\t\tq1 = findMedian( array[ : len( array ) // 2 ])\n\t\t\t\tq3 = findMedian( array[ int( math.ceil( len( array ) / 2.0 )) : ])\n\t\t\t\tmin_ = min( yAxis )\n\t\t\t\tmax_ = max( yAxis )\n\t\t\t\tprint( \"Plot statistics for %s:\" % label )\n\t\t\t\tprint( \"\\tRange: %g (%g - %g)\" % ( max_ - min_, min_, max_ ))\n\t\t\t\tprint( \"\\tMean: %g\" % numerical.mean( yAxis ))\n\t\t\t\tprint( \"\\tMedian: %g\" % median )\n\t\t\t\tprint( \"\\tInterquartile Range: %g (%g - %g)\" % ( q3 - q1, q1, q3 ))\n\t\t\t\tprint( \"\\tStandard Deviation: %g\" % numerical.std( yAxis ))\n\t\t\t\tprint( \"\\tVariance: %g\" % numerical.var( yAxis ))\n\n\n\n\t# The following section of code is specific to the OmicsDP data formats.\n\t# You can safely delete this section if you are using this software outside\n\t# of that environment.\n # BEGIN READING DLTs\n\tfor arg in args:\n\t\tscan = numerical.empty( 0, numerical.uint64 ) # scan number\n\t\tbarRt = numerical.empty( 0, numerical.float64 ) # retention time \n\t\tbarIntensity = numerical.empty( 0, numerical.float64 )\n\t\tbarNoise = numerical.empty( 0, numerical.float64 )\n\t\tlabels = [ ]\n\t\ttry:\n\t\t\tf = open( arg )\n\t\t\tlines = DictReader( f )\n\t\texcept IOError:\n\t\t\tsys.stderr.write(\"Error: unable to read file '%s'\\n\" % arg )\n\t\t\tsys.exit( -1 )\n\n\t\tif options.shortFilename:\n\t\t\tfilename = os.path.basename( arg )\n\t\telse:\n\t\t\tfilename = arg\n\n\t\tfor line in lines:\n\t\t\ttry:\n\t\t\t\tscanValue = int( line[ 'Scan' ])\n\t\t\t\trtValue = float( line[ 'RT(min)'] )\n\t\t\t\tmzValue = float( line[ 'M/Z' ] )\n\t\t\t\tnoiseValue = float( line[ 'LC_Noise' ] )\n\t\t\t\tintValue = float( line[ 'Int' ] ) \n\t\t\t\tif ( rtValue < options.minTime or \n\t\t\t\t\t ( options.maxTime and rtValue > options.maxTime )):\n\t\t\t\t\tcontinue\n\t\t\t\tif ((( not noiseValue ) or \n\t\t\t\t\t intValue/noiseValue < options.filterLevel ) or \n\t\t\t\t ( options.mass and \n\t\t\t\t\t\t\t abs( options.mass - mzValue ) > options.massWindow )):\n\t\t\t\t\tif options.verbosity:\n\t\t\t\t\t\tsys.stderr.write( \"Dropping line %s\" % ( line ))\n\t\t\t\t\tcontinue\n\t\t\t\t# using plot( ) produces a more responsive graph than vlines( )\n\t\t\t\tif len( scan ) and scanValue == scan[ -1 ]:\n\t\t\t\t\tif options.bpc:\n\t\t\t\t\t\tif intValue > barIntensity[ -2 ]:\n\t\t\t\t\t\t\tbarIntensity[ -2 ] = intValue\n\t\t\t\t\t\t\tbarNoise[ -2 ] = noiseValue\n\t\t\t\t\t\t\tlabels[ -1 ] = \"(%.2f,\" % ( mzValue - 0.005 ) #truncate, don't round\n\t\t\t\t\telse:\n\t\t\t\t\t\tbarIntensity[ -2 ] += intValue\n\t\t\t\t\t\tbarNoise[ -2 ] += noiseValue\n\t\t\t\t\t\tlabels[ -1 ] += \" %.2f,\" % ( mzValue - 0.005 ) #truncate, don't round\n\t\t\t\telse:\n\t\t\t\t\t# appending [0, value, 0] allows us to plot a bar graph using lines\n\t\t\t\t\tbarRt = numerical.append( barRt, [ rtValue, rtValue, rtValue ])\n\t\t\t\t\tbarIntensity = numerical.append( barIntensity, [ 0, intValue, 0 ])\n\t\t\t\t\tbarNoise = numerical.append( barNoise, [ 0, noiseValue, 0 ])\n\t\t\t\t\tscan = numerical.append( scan, scanValue )\n\t\t\t\t\tif ( len( labels )):\n\t\t\t\t\t\tlabels[ -1 ] = labels[ -1 ][ :-1 ] + ')' # replace the last , with )\n\t\t\t\t\tlabels.append( \"(%.2f,\" % ( mzValue - 0.005 )) #truncate, don't round\n\n\n\n\t\t\texcept ( ValueError, IndexError ):\n\t\t\t\tif options.verbosity:\n\t\t\t\t\tsys.stderr.write( \"Skipping line %s\" % ( line ))\n\n\t\tif ( len( labels )):\n\t\t\tlabels[ -1 ] = labels[ -1 ][ :-1 ] + ')' # replace the last , with )\n\n\t\tif options.normalize:\n\t\t\tif len( barIntensity ):\n\t\t\t\tmax_ = max( barIntensity )\n\t\t\t\tif max_:\n\t\t\t\t\tbarIntensity /= max_\n\t\t\t\t\tbarNoise /= max_\n\t\t\t\n\t\tif options.massLabels:\n\t\t\tfor i in xrange( len( labels )):\n\t\t\t\tpylab.annotate( labels[ i ], ( barRt[ 3 * i + 1 ], barIntensity[ 3 * i + 1 ]),\n\t\t\t\t size=9)\n\n\t\t# calculate alpha based on which file this is in the list\n\t\talpha = ( options.markerAlpha - options.markerAlpha * \n\t\t ( args.index( arg ) / float( len( args ))) * 0.75 )\n\n\t\tif options.showPeaks:\n\t\t\tif not options.removeNoise:\n\t\t\t\tbarIntensity += barNoise\n\n\t\t\tif options.normalize:\n\t\t\t\tlabel = label = ( \"%s - intensity (%d peaks, normalized)\" % \n\t\t\t\t\t\t( filename, len( barIntensity )/3))\n\t\t\telse:\n\t\t\t\tlabel = label = ( \"%s - intensity (%d peaks)\" % \n\t\t\t\t\t\t( filename, len( barIntensity )/3))\n\t\t\tpylab.plot( barRt, barIntensity, COLORS['intensity'][0] , \n\t\t\t linewidth = options.lineWidth2, alpha = alpha, label = label )\n\n\t\tif options.connectPeaks:\n\t\t\tpylab.plot( barRt[ 2::3 ], barIntensity[ 1::3 ], COLORS['intensity'][0], \n\t\t\t alpha = alpha, linewidth=options.lineWidth )\n\t\tCOLORS['intensity'] = COLORS['intensity'][1:] + [ COLORS['intensity'][0]]\n\t\t\t\t\n\t\tif options.showNoise:\n\t\t\tif options.normalize:\n\t\t\t\tlabel = ( \"%s - noise (%d points, normalized)\" % ( filename, len( barNoise )/3))\n\t\t\telse:\n\t\t\t\tlabel = ( \"%s - noise (%d points)\" % ( filename, len( barNoise )/3))\n\t\t\tpylab.plot( barRt[ 2::3 ], barNoise[ 1::3 ], COLORS['noise'][0], alpha = alpha, \n\t\t\t linewidth=options.lineWidth, label = label)\n\t\t\tCOLORS['noise'] = COLORS['noise'][1:] + [ COLORS['noise'][0]]\n\t\tif len( barRt ):\n\t\t\t#draw a horizontal black line at 0\n\t\t\tpylab.plot( [barRt[1], barRt[-2]], [0,0], 'k', linewidth=options.lineWidth )\n\n\t\tf.close( )\n\t\t# END READING DLTs\n\n\tif options.showLegend:\n\t\tlegend = pylab.legend( loc=\"upper left\", prop=FontProperties( size='small' ))\n\n\tpylab.grid( )\n\taxes = thisFigure.get_axes( )[ 0 ]\n\taxes.set_xlabel( \"Time (min)\" )\n\taxes.set_ylabel( \"Intensity\" )\n\taxes.ticklabel_format( style=\"scientific\", axis=\"y\", scilimits=(3,3) )\n\n\tif not len( rawFiles ):\n\t\tif ( options.bpc ):\n\t\t\taxes.set_title( \"Base Peaks\" )\n\t\telse:\n\t\t\taxes.set_title( \"Peaks\" )\n\telif options.bpc:\n\t\tif options.mass:\n\t\t\taxes.set_title( \n\t\t\t\t\"Selected Base Peak Chromatogram (M/Z: %f, Tolerance: %f)\" % \n\t\t\t\t( options.mass, options.massWindow ))\n\t\telse:\n\t\t\taxes.set_title( \"Base Peak Chromatogram\" )\n\telse:\n\t\tif options.mass:\n\t\t\taxes.set_title( \n\t\t\t\t\"Selected Ion Chromatogram (M/Z: %f, Tolerance: %f)\" %\n\t\t\t\t( options.mass, options.massWindow ))\n\t\telse:\n\t\t\taxes.set_title( \"Total Ion Chromatogram\" )\n\tif options.outputFile:\n\t\tthisFigure.savefig( options.outputFile, dpi=options.dpi )\n\tif not options.scriptMode:\n\t\tpylab.show( )\n## end main( )\n\t\nif ( __name__ == \"__main__\" ):\n\tmain( parseOpts( ))\n\n" }, { "alpha_fraction": 0.5259668231010437, "alphanum_fraction": 0.5867403149604797, "avg_line_length": 46.47368240356445, "blob_id": "6d746d78e4c2c3d5918bec9c52708ba3ae551a81", "content_id": "e47ef5bbca23a0fdd76972c49131018427452d48", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 905, "license_type": "no_license", "max_line_length": 83, "num_lines": 19, "path": "/test.py", "repo_name": "jaspringer/pymzlib", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python2\n\nfrom mzlib import *\n\nmzXML2 = RawData( \"testData/tiny1.mzXML2.0.mzXML\" )\nmzXML3 = RawData( \"testData/tiny1.mzXML3.0.mzXML\" )\nmzData = RawData( \"testData/tiny1.mzData1.05.xml\" )\njson = RawData( \"testData/tiny1.json\" )\njsonGz = RawData( \"testData/tiny1.json.gz\" )\n\nif __name__ == \"__main__\":\n\tprint( \"mzXML2.getScan( 5.89 )['points'] == mzXML3.getScan( 5.89 )['points']): \" +\n\t\tstr(mzXML2.getScan( 5.89 )['points'] == mzXML3.getScan( 5.89 )['points']))\n\tprint( \"mzXML2.getScan( 5.89 )['points'] == mzData.getScan( 5.89 )['points']): \" +\n\t\tstr(mzXML2.getScan( 5.89 )['points'] == mzData.getScan( 5.89 )['points']))\n\tprint( \"mzXML2[:] == mzXML3[:]: \" + str(mzXML2[:] == mzXML3[:]))\n\tprint( \"mzXML2[:] == mzData[:]: \" + str(mzXML2[:] == mzData[:]))\n\tprint( \"mzXML2[:] == json[:] : \" + str(mzXML2[:] == json[:] ))\n\tprint( \"mzXML2[:] == jsonGz[:]: \" + str(mzXML2[:] == jsonGz[:]))\n\n\n\n" } ]	7
crkg/sqlAlchemy	https://github.com/crkg/sqlAlchemy	317de874c56038ba393c1dab19ef8f477ca4545f	ca9e270c9f5c51a29ddfafce336388cf775c4c55	fd22d189f1a221d642c61ce0cbd53ea0046251fa	refs/heads/master	2022-12-10T14:32:43.484640	2019-11-09T11:49:49	2019-11-09T11:49:49	205,790,227	0	0	null	2019-09-02T06:24:02	2019-11-09T11:50:10	2022-12-08T06:10:25	Python	[ { "alpha_fraction": 0.8181818127632141, "alphanum_fraction": 0.8181818127632141, "avg_line_length": 64, "blob_id": "67dc9a512c3b8bb643d79082fef5976ccdb89e12", "content_id": "50fa0920ab7f7a919e7a815379912692e765566d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 66, "license_type": "no_license", "max_line_length": 64, "num_lines": 1, "path": "/api/tests/unit_tests/apis/learnpy_endpoint.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Resource, fields, reqparse, Namespace\r\n" }, { "alpha_fraction": 0.6523604989051819, "alphanum_fraction": 0.6523604989051819, "avg_line_length": 19.363636016845703, "blob_id": "618ca6cac9d2b8e7b3332185fa2c32ebe76ff47a", "content_id": "8845845aea03161d5b4a52ab53206e616499a810", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 233, "license_type": "no_license", "max_line_length": 65, "num_lines": 11, "path": "/api/dumyapi/app_file.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import sys\r\nsys.path.append(\"c:\\\\Users\\\\ramesh.kg\\\\PycharmProjects\\\\DumyApi\")\r\nfrom flask import Flask\r\nfrom dumyapi.apis import api\r\n\r\n\r\napp = Flask(__name__)\r\napi.init_app(app)\r\n\r\nif __name__ == '__main__':\r\n app.run(debug=True)" }, { "alpha_fraction": 0.6762749552726746, "alphanum_fraction": 0.707317054271698, "avg_line_length": 27.125, "blob_id": "4760390772c2d06e55d0f595c0575f19b534d83f", "content_id": "e068b427af1f28b2621f575e4ed99d1e0bbebdaa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 451, "license_type": "no_license", "max_line_length": 57, "num_lines": 16, "path": "/config/gunicorn_conf.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import multiprocessing\nimport getpass\n\nbase_dir = f'/Users/{getpass.getuser()}/PycharmProjects/'\ngunicorn_dir = base_dir + 'gunicorn/'\n\n#server\nbind = '0.0.0.0:8443'\nworkers = multiprocessing.cpu_count() * 2 + 1\ntimeout = 2000\ndaemon = True\n#certfile = base_dir + 'ssl_keys/<application name>.pem'\n#keyfile = base_dir + 'ssl_keys/<application_name>.key'\n\nerrorlog = gunicorn_dir + '/var/log/error.log'\nasseslog = gunicorn_dir + '/var/log/access.log'\n\n" }, { "alpha_fraction": 0.5885143280029297, "alphanum_fraction": 0.5990012288093567, "avg_line_length": 30.827869415283203, "blob_id": "a1f8dd5d70c43f39e637986979e382d0a92f969f", "content_id": "0b9854f759a7082fbf992e10c3c209c4017bf7bd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4005, "license_type": "no_license", "max_line_length": 110, "num_lines": 122, "path": "/api/AWS/resources/aws.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import boto3\r\nimport sys\r\nimport boto\r\nimport boto.ec2\r\nimport boto.utils\r\n\r\n# auth = {\"aws_access_key_id\": \"AKIAIR36LFO6363OXEQQ\",\r\n# \"aws_secret_access_key\": \"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\"}\r\n\r\n\r\ndef exception_handling(func):\r\n def inner(args, kwargs):\r\n try:\r\n return func(args, kwargs)\r\n except Exception as e1:\r\n error1 = \"Error1: {}\".format(e1)\r\n print(error1)\r\n sys.exit(0)\r\n return inner\r\n\r\n\r\nclass awsConnectRegion(object):\r\n def __init__(self, aws_id=\"AKIAIF35ZV3HKMYC2HUQ\", aws_secret=\"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\"):\r\n self.auth = dict()\r\n self.auth['aws_access_key_id'] = aws_id\r\n self.auth['aws_secret_access_key'] = aws_secret\r\n\r\n @exception_handling\r\n def connect_to_region(self, region_name):\r\n # change \"eu-west-1\" region if different\r\n ec2 = boto.ec2.connect_to_region(region_name, self.auth)\r\n return ec2\r\n\r\n\r\nclass AWSlistInstance(awsConnectRegion):\r\n\r\n def __init__(self, aws_id=\"AKIAIF35ZV3HKMYC2HUQ\", aws_secret=\"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\"):\r\n super().__init__(aws_id=aws_id, aws_secret=aws_secret)\r\n\r\n @exception_handling\r\n def listAllInstance(self, region_name):\r\n print(\"Listing all instance in region {} \".format(region_name))\r\n ec2 = self.connect_to_region(region_name)\r\n reservations = ec2.get_all_instances()\r\n return [i.instances for i in reservations]\r\n\r\n @exception_handling\r\n def listAInstance(self,region_name,instance_id):\r\n awsList = self.listAllInstance(region_name)\r\n print(f\"aws instances \\n {awsList}\")\r\n for each in awsList:\r\n if instance_id == each[0].id:\r\n return each[0].state\r\n return None\r\n\r\n\r\n\r\nclass AWSlistS3bucket(awsConnectRegion):\r\n @exception_handling\r\n def s3bucket(self, region_name, instnc):\r\n print(\"List all existing buckets for the AWS account\")\r\n ec2 = self.connect_to_region(region_name)\r\n ec2.list_buckets()\r\n\r\n\r\nclass AwsOperation(awsConnectRegion):\r\n\r\n @exception_handling\r\n def startInstance(self, region_name, instnc):\r\n print(\"Starting the instance...\")\r\n ec2 = self.connect_to_region(region_name)\r\n ec2.start_instances(instance_ids=instnc)\r\n\r\n @exception_handling\r\n def stopInstance(self, region_name, instnc):\r\n print(\"Stopping the instance...\")\r\n ec2 = self.connect_to_region(region_name)\r\n ec2.stop_instances(instance_ids=instnc)\r\n\r\n @exception_handling\r\n def terminate(self, region_name, instnc):\r\n print(\"Terminating an instance...\")\r\n ec2 = self.connect_to_region(region_name)\r\n ec2.terminate_instances(instance_ids=instnc)\r\n\r\n @exception_handling\r\n def s3bucket(self, region_name, instnc):\r\n print(\"List all existing buckets for the AWS account\")\r\n ec2 = self.connect_to_region(region_name)\r\n ec2.list_buckets()\r\n\r\n\r\ndef main():\r\n # read arguments from the command line and\r\n # check whether at least two elements were entered\r\n if len(sys.argv) < 3:\r\n print(\"Usage arguments are space seperated: python aws.py {start\|stop\|terminate\|awsRegion}\\n\")\r\n sys.exit(0)\r\n else:\r\n action = sys.argv[1]\r\n awsRegion = sys.argv[2]\r\n # awsAccessKey = sys.argv[3]\r\n # awsSecretKey = sys.argv[4]\r\n Instance = AWSlistInstance()\r\n list = Instance.listAllInstance(awsRegion)\r\n\r\n print(\"Here is the list of instance on region {}, {}\".format(awsRegion, list))\r\n for i in list:\r\n instnc = i[0].id\r\n awsop = AwsOperation()\r\n if action == \"start\":\r\n awsop.startInstance(awsRegion, instnc)\r\n elif action == \"stop\":\r\n awsop.stopInstance(awsRegion, instnc)\r\n elif action == \"terminate\":\r\n awsop.terminate(awsRegion, instnc)\r\n else:\r\n print(\"Usage arguments are space seperated: python aws.py {start\|stop\|terminate\|awsRegion}\\n\")\r\n\r\n\r\nif __name__ == '__main__':\r\n main()\r\n" }, { "alpha_fraction": 0.7120000123977661, "alphanum_fraction": 0.7200000286102295, "avg_line_length": 23.200000762939453, "blob_id": "b96fe83719821a56766a565c0750164eb1707a5f", "content_id": "6aac964d9b35223c9847a591d6be31cd4b46ebad", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 250, "license_type": "no_license", "max_line_length": 63, "num_lines": 10, "path": "/api/AWS/apis/__init__.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Api\r\nfrom AWS.apis.aws_api_endpoint import namespace as awsnamespace\r\n\r\napi = Api(\r\n title='AWS Integration',\r\n version='v0',\r\n description='Creating AWS Api along with Boto 3'\r\n)\r\n\r\napi.add_namespace(awsnamespace)" }, { "alpha_fraction": 0.4502875804901123, "alphanum_fraction": 0.6573541760444641, "avg_line_length": 15.385714530944824, "blob_id": "dc9fe4ba78efd2d54841c9a34645e1292e9df6da", "content_id": "970e17c4f6dd7cf860cea690b7b3e3a85a9a902b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 1217, "license_type": "no_license", "max_line_length": 26, "num_lines": 70, "path": "/api/REST-Plus-API/requirements.txt", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "aniso8601==7.0.0\r\nasn1crypto==0.24.0\r\natomicwrites==1.3.0\r\nattrs==19.1.0\r\naws-sam-translator==1.12.0\r\naws-xray-sdk==2.4.2\r\nboto==2.49.0\r\nboto3==1.9.191\r\nbotocore==1.12.191\r\ncertifi==2019.6.16\r\ncffi==1.12.3\r\ncfn-lint==0.22.3\r\nchardet==3.0.4\r\nClick==7.0\r\ncolorama==0.4.1\r\ncoverage==4.5.3\r\ncryptography==2.7\r\nDateTime==4.3\r\ndocker==4.0.2\r\ndocutils==0.14\r\necdsa==0.13.2\r\nFlask==1.1.0\r\nflask-restplus==0.12.1\r\nfuture==0.17.1\r\nidna==2.8\r\nimportlib-metadata==0.18\r\nitsdangerous==1.1.0\r\nJinja2==2.10.1\r\njmespath==0.9.4\r\njsondiff==1.1.2\r\njsonpatch==1.23\r\njsonpickle==1.2\r\njsonpointer==2.0\r\njsonschema==3.0.1\r\nMarkupSafe==1.1.1\r\nmock==3.0.5\r\nmore-itertools==7.1.0\r\nmoto==1.3.13\r\nnumpy==1.16.4\r\npackaging==19.0\r\npandas==0.25.0\r\npluggy==0.12.0\r\npy==1.8.0\r\npyasn1==0.4.5\r\npycparser==2.19\r\npyparsing==2.4.0\r\npypiwin32==223\r\npyrsistent==0.15.3\r\npytest==5.0.1\r\npytest-cov==2.7.1\r\npytest-mock==1.10.4\r\npython-dateutil==2.8.0\r\npython-jose==3.0.1\r\npytz==2019.1\r\npywin32==224\r\nPyYAML==5.1.1\r\nrequests==2.22.0\r\nresponses==0.10.6\r\nrsa==4.0\r\ns3transfer==0.2.1\r\nsix==1.12.0\r\nsshpubkeys==3.1.0\r\nurllib3==1.25.3\r\nwcwidth==0.1.7\r\nwebsocket-client==0.56.0\r\nWerkzeug==0.15.4\r\nwrapt==1.11.2\r\nxmltodict==0.12.0\r\nzipp==0.5.2\r\nzope.interface==4.6.0\r\n" }, { "alpha_fraction": 0.5397973656654358, "alphanum_fraction": 0.5643994212150574, "avg_line_length": 34.3684196472168, "blob_id": "0c8bfa17d21e400931b8d5af380648db7c83a556", "content_id": "0ed88045fb90c1e3358bd7b2cb9f8c70c954ea0e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 691, "license_type": "no_license", "max_line_length": 75, "num_lines": 19, "path": "/api/dumyapi/core/auth.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask import request\r\nfrom base64 import b64decode\r\nfrom functools import wraps\r\n\r\n\r\ndef authorize(f):\r\n @wraps(f)\r\n def inner(args, kwargs):\r\n if 'authorization' in request.headers:\r\n auth = request.headers.get('authorization').split()[1]\r\n username, password = b64decode(auth).decode('UTF-8').split(':')\r\n if username != 'Admin':\r\n return {'message': 'User not Authorized'}, 401\r\n if password != 'Sungard01':\r\n return {'message': 'Incorrect Password'}, 401\r\n return f(args, *kwargs)\r\n else:\r\n return {'message': 'No credentials provide'}, 401\r\n return inner\r\n" }, { "alpha_fraction": 0.6291845440864563, "alphanum_fraction": 0.6532188653945923, "avg_line_length": 32.17647171020508, "blob_id": "b3488d680fbe4313ff8656760519f66bcec38e75", "content_id": "01365045cbcb93c150737f5707bfe783df35ca64", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2330, "license_type": "no_license", "max_line_length": 82, "num_lines": 68, "path": "/api/dumyapi/apis/language_api.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Resource, fields, reqparse, Namespace\r\nfrom flask import request\r\nfrom dumyapi.core.auth import authorize\r\n\r\nlangnamespace = Namespace(\"Languages\", description='Get languages for given user')\r\n\r\nparselevel = reqparse.RequestParser()\r\nparselevel.add_argument('Username', type=str, required=True)\r\n#parselevel.add_argument('Languages', type=list, required=True)\r\n\r\n\r\nmodel = langnamespace.model('postInput', {\r\n 'username': fields.String,\r\n 'Languages': fields.List(fields.String)\r\n})\r\n\r\nlang = {}\r\n\r\[email protected]('/languages')\r\nclass language(Resource):\r\n @langnamespace.response(201, 'accepted')\r\n @langnamespace.response(400, 'Bad request')\r\n @langnamespace.response(500, 'Internal server error')\r\n @langnamespace.response(404, 'Not found')\r\n @langnamespace.response(403, 'Unauthorized')\r\n @langnamespace.expect(model)\r\n @authorize\r\n def post(self):\r\n\r\n '''Something'''\r\n payload = request.get_json()\r\n #print(payload)\r\n key = payload.get('username')\r\n value = payload.get('Languages')\r\n lang[key] = value\r\n return lang, 201\r\n\r\n @langnamespace.response(200, 'success')\r\n @langnamespace.response(400, 'Bad request')\r\n @langnamespace.response(500, 'Internal server error')\r\n @langnamespace.response(404, 'Not found')\r\n #@langnamespace.doc(parser=parselevel)\r\n #@langnamespace.marshal_with(model, code=200)\r\n @authorize\r\n def get(self):\r\n '''something2'''\r\n #payload=parselevel.parse_args()\r\n #print(payload)\r\n #key = payload.get('username')\r\n #value = payload.get('Languages')\r\n return lang, 200\r\n\r\[email protected]('/languages/<username>')\r\nclass languageByUsername(Resource):\r\n @langnamespace.response(201, 'accepted')\r\n @langnamespace.response(400, 'Bad request')\r\n @langnamespace.response(500, 'Internal server error')\r\n @langnamespace.response(404, 'Not found')\r\n @langnamespace.response(403, 'Unauthorized')\r\n # @langnamespace.doc(parser=parselevel)\r\n @authorize\r\n def get(self, username):\r\n '''SOmething 3'''\r\n # payload = parselevel.parse_args()\r\n # key = payload.get('username')\r\n #value = payload.get('Languages')\r\n #lang[key] = value\r\n return lang[username], 200\r\n\r\n\r\n\r\n" }, { "alpha_fraction": 0.7824427485466003, "alphanum_fraction": 0.7824427485466003, "avg_line_length": 31.625, "blob_id": "bb7b94f74700ef4540c2843ca617ddc514f30dc4", "content_id": "19ca1e6cc37b8cf7fc9caa4f9d747282f0b356c0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 262, "license_type": "no_license", "max_line_length": 60, "num_lines": 8, "path": "/sqlAlchemy/resources/Injectors.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from sqlAlchemy.resources.movies_ops import MovieOperations\nfrom sqlAlchemy.models.utils.movies import MovieDbOperations\n\n\ndef ins_creation:\n movies_ops_ins = MovieOperations()\n movies_db_ins = MovieDbOperations()\n return movies_db_ins, movies_ops_ins\n\n" }, { "alpha_fraction": 0.7448979616165161, "alphanum_fraction": 0.75, "avg_line_length": 26, "blob_id": "833650258f4c5bc723ea336aaf5b7dace891a049", "content_id": "1e587c2d56599e2e1c3af3bd59df6932ed12d94b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 392, "license_type": "no_license", "max_line_length": 53, "num_lines": 14, "path": "/api/REST-Plus-API/apis/__init__.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Api\r\nfrom apis.aws_ops import namespace as awsnamespace\r\nfrom apis.todos import todonamespace\r\nfrom apis.movies import namespace as moviesnamespace\r\n\r\napi = Api(\r\n title='Learn-API',\r\n version='V1',\r\n description='Learning API'\r\n)\r\n\r\napi.add_namespace(awsnamespace)\r\napi.add_namespace(todonamespace)\r\napi.add_namespace(moviesnamespace, path=\"/v1/movies\")\r\n" }, { "alpha_fraction": 0.6791744828224182, "alphanum_fraction": 0.6929330825805664, "avg_line_length": 42.13888931274414, "blob_id": "4b90a9e879be0cfc7a91412e457980a42c930df5", "content_id": "5083351d27722a18f3e5b0a972d597dec0f173c2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1599, "license_type": "no_license", "max_line_length": 91, "num_lines": 36, "path": "/api/AWS/apis/aws_api_endpoint.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Resource, fields, reqparse, Namespace\r\nfrom AWS.resources.aws import AWSlistInstance\r\n\r\nnamespace = Namespace('AWS', description='Try all AWS functions')\r\n\r\nawsschema = namespace.model('AWS', {\r\n 'AwsRegion': fields.String(description='Select the aws region', required=True),\r\n 'State': fields.String(description='Select the aws server state', required=True),\r\n 'Ec2Instance': fields.String(description='Select the aws server state', required=True),\r\n})\r\n\r\nparselevel=reqparse.RequestParser()\r\nparselevel.add_argument('Instance Name', type=str, required=True)\r\nparselevel.add_argument('AWS Region', type=str, required=True)\r\n\r\n\r\[email protected]('/aws-state')\r\n#End point resource , inherting the resource to the stop instance\r\nclass GetInstanceState(Resource):\r\n @namespace.response(200, 'success')\r\n @namespace.response(400, 'Bad request')\r\n @namespace.response(500, 'Internal server error')\r\n @namespace.response(404, 'Not found')\r\n @namespace.response(403, 'Unauthorized')\r\n @namespace.doc(parser=parselevel)\r\n @namespace.doc(description=\"\\n To get the status of the Instance\")\r\n def get(self):\r\n awsinfo = parselevel.parse_args()\r\n awsregion = awsinfo.get(\"AWS Region\")\r\n awsinstace = awsinfo.get(\"Instance Name\")\r\n instance = AWSlistInstance()\r\n instancedetails = instance.listAInstance(awsregion, awsinstace)\r\n if instancedetails is None:\r\n return {'error': 'No Instance Found with the name'}, 404\r\n else:\r\n return {'Instance': instancedetails}, 200\r\n\r\n\r\n\r\n\r\n\r\n" }, { "alpha_fraction": 0.6329618096351624, "alphanum_fraction": 0.6329618096351624, "avg_line_length": 32.88888931274414, "blob_id": "f5d9c13accc4ed1d7e005c3fe911e44115205793", "content_id": "83650ae97180c336a5d37cab0b26eab12da076bb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1256, "license_type": "no_license", "max_line_length": 92, "num_lines": 36, "path": "/api/tests/unit_tests/resources/test_worker.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from learnpy.resources.worker import Helper, WorkerService\r\nimport pytest\r\n\r\nclass FakeHelper:\r\n\r\n def get_path(self):\r\n return \"C:\\\\Program Files\\\\db\"\r\n\r\n\r\nclass TestHelper:\r\n def test_helper(self, mocker):\r\n a = Helper('db')\r\n assert isinstance(a, Helper)\r\n\r\n def test_get_path(self, mocker):\r\n mocker.patch('learnpy.resources.worker.os.getcwd', return_value='C:\\\\Program Files')\r\n a = Helper('db')\r\n assert a.get_path() == 'C:\\\\Program Files\\\\db'\r\n\r\n\r\nclass TestWorker:\r\n def test_worker_instaance_creation(self, mocker):\r\n mocker.patch('learnpy.resources.worker.Helper', return_value=FakeHelper())\r\n w = WorkerService()\r\n assert isinstance(w, WorkerService)\r\n\r\n def test_worker_work(self,mocker):\r\n mocker.patch('learnpy.resources.worker.Helper', return_value=FakeHelper())\r\n w = WorkerService()\r\n assert w.work() == 'C:\\\\Program Files\\\\db'\r\n\r\n def test_worker_work_without_fake_helper(self,mocker):\r\n mock_helper = mocker.patch('learnpy.resources.worker.Helper', autospec=True)\r\n mock_helper.return_value.get_path.return_value = 'C:\\\\Program Files\\\\db'\r\n w = WorkerService()\r\n assert w.work() == 'C:\\\\Program Files\\\\db'\r\n" }, { "alpha_fraction": 0.39743590354919434, "alphanum_fraction": 0.43589743971824646, "avg_line_length": 13.600000381469727, "blob_id": "52ae1c7bc411e2197afaf4b1ebae48710f57b4e4", "content_id": "f38ac3f69e8a2153a2601cfb29bf1484ebaee6a6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 78, "license_type": "no_license", "max_line_length": 37, "num_lines": 5, "path": "/api/learnpy/resources/learn-while.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "i = 1\r\n\r\nwhile i <= 5:\r\n print(\"Computing i {}\".format(i))\r\n i = i + 1\r\n" }, { "alpha_fraction": 0.7004910111427307, "alphanum_fraction": 0.7054010033607483, "avg_line_length": 20.821428298950195, "blob_id": "89f6f35f16b8e386162f1a46d2e2a6b4816fe6e2", "content_id": "88a7ec4031e7f2fb47f42be66ae01bc92b0a4590", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 611, "license_type": "no_license", "max_line_length": 59, "num_lines": 28, "path": "/sqlAlchemy/app_file.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import sys\nimport os\nsys.path.append(\"/Users/ramesh/PycharmProjects/sqlAlchemy\")\nfrom flask import Flask\n\nfrom sqlAlchemy.models.utils.base_db import db\n\ndef load_conf(app):\n app.config.from_object('config.app_conf_local')\n if 'CONFFILE_PATH' in os.environ:\n app.config.from_envvar('CONFFILE_PATH')\n\napp = Flask(__name__)\nload_conf(app)\napp.app_context().push()\ndb.init_app(app)\ndb.create_all()\nfrom sqlAlchemy.apis import api\napi.init_app(app)\n\n\[email protected](Exception)\ndef handle_exception(error):\n return {'message': str(error)}, 400\n\n\nif __name__ == \"__main__\":\n app.run(debug=True)\n" }, { "alpha_fraction": 0.6476323008537292, "alphanum_fraction": 0.6476323008537292, "avg_line_length": 38, "blob_id": "6eb1f3faf31a5f602424036c5abbe5cdaed161fb", "content_id": "49e922bacd59671cc6a11199c1101b935152e2ad", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 718, "license_type": "no_license", "max_line_length": 99, "num_lines": 18, "path": "/api/tests/unit_tests/resources/test_sample_os_cmd.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from learnpy.resources.sample_os_cmd import work\r\nimport pytest\r\nimport mock\r\n\r\nclass TestSampleOsCmd:\r\n def test_work(self, mocker):\r\n mocker.patch('learnpy.resources.sample_os_cmd.os.getcwd', return_value='C:\\\\Program Files')\r\n assert work() == 'C:\\\\Program Files'\r\n\r\n def test_work_other(self, mocker):\r\n mock_getcwd = mocker.patch('learnpy.resources.sample_os_cmd.os.getcwd')\r\n mock_getcwd.return_value = 'C:\\\\Program Files'\r\n assert work() == 'C:\\\\Program Files'\r\n\r\n @mock.patch('learnpy.resources.sample_os_cmd.os.getcwd')\r\n def test_work_with_patch(self, mock_cwd):\r\n mock_cwd.return_value = 'C:\\\\Program Files'\r\n assert work() == 'C:\\\\Program Files'" }, { "alpha_fraction": 0.6329479813575745, "alphanum_fraction": 0.6416184902191162, "avg_line_length": 18.235294342041016, "blob_id": "1b9a5ede1400d449e8f4643011a3aa0146413009", "content_id": "1548e509f606cd9a4816e27ba74843c9e8c1a3a8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 346, "license_type": "no_license", "max_line_length": 75, "num_lines": 17, "path": "/api/REST-Plus-API/app_file.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import sys\r\nsys.path.append(\"c:\\\\Users\\\\ramesh.kg\\\\PycharmProjects\\\\Flask-REST-full\\\\\")\r\nfrom flask import Flask\r\nfrom apis import api\r\n\r\n\r\napp = Flask(__name__)\r\napi.init_app(app)\r\n\r\n\r\[email protected](Exception)\r\ndef handle_exception(error):\r\n return {'message': str(error)}, 400\r\n\r\n\r\nif __name__ == \"__main__\":\r\n app.run(debug=True)\r\n\r\n" }, { "alpha_fraction": 0.48910751938819885, "alphanum_fraction": 0.6999297142028809, "avg_line_length": 15.74117660522461, "blob_id": "a6edeefe36abcd9b365358846755b52d0deb16bd", "content_id": "6ee8788c8ef5bc448f0ac8de6ba4572a6c17997c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 1423, "license_type": "no_license", "max_line_length": 34, "num_lines": 85, "path": "/requirements.txt", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "aniso8601==7.0.0\napispec==2.0.2\nasn1crypto==0.24.0\natomicwrites==1.3.0\nattrs==19.1.0\nautopep8==1.4.4\naws-sam-translator==1.12.0\naws-xray-sdk==2.4.2\nboto==2.49.0\nboto3==1.9.191\nbotocore==1.12.191\ncertifi==2019.6.16\ncffi==1.12.3\ncfn-lint==0.22.3\nchardet==3.0.4\nClick==7.0\ncolorama==0.4.1\ncoverage==4.5.3\ncryptography==2.7\nDateTime==4.3\nDjango==2.2.3\ndocker==4.0.2\ndocutils==0.14\necdsa==0.13.2\nentrypoints==0.3\nflake8==3.7.8\nFlask==1.1.0\nflask-marshmallow==0.10.1\nflask-restplus==0.12.1\nflask-restplus-marshmallow==0.2.20\nFlask-SQLAlchemy==2.4.0\nfuture==0.17.1\nidna==2.8\nimportlib-metadata==0.18\nitsdangerous==1.1.0\nJinja2==2.10.1\njmespath==0.9.4\njsondiff==1.1.2\njsonpatch==1.23\njsonpickle==1.2\njsonpointer==2.0\njsonschema==3.0.1\nMarkupSafe==1.1.1\nmarshmallow==2.19.5\nmccabe==0.6.1\nmock==3.0.5\nmore-itertools==7.1.0\nmoto==1.3.13\nnumpy==1.16.4\npackaging==19.0\npandas==0.25.0\npep8==1.7.1\npluggy==0.12.0\npy==1.8.0\npyasn1==0.4.5\npycodestyle==2.5.0\npycparser==2.19\npyflakes==2.1.1\npyparsing==2.4.0\npyrsistent==0.15.3\npytest==5.0.1\npytest-cov==2.7.1\npytest-mock==1.10.4\npython-dateutil==2.8.0\npython-jose==3.0.1\npytz==2019.1\npywin32==224\nPyYAML==5.1.1\nrequests==2.22.0\nresponses==0.10.6\nrsa==4.0\ns3transfer==0.2.1\nsix==1.12.0\nSQLAlchemy==1.3.8\nsqlparse==0.3.0\nsshpubkeys==3.1.0\nurllib3==1.25.3\nwcwidth==0.1.7\nwebargs==5.4.0\nwebsocket-client==0.56.0\nWerkzeug==0.15.4\nwrapt==1.11.2\nxmltodict==0.12.0\nzipp==0.5.2\nzope.interface==4.6.0\n" }, { "alpha_fraction": 0.6882129311561584, "alphanum_fraction": 0.697718620300293, "avg_line_length": 19.230770111083984, "blob_id": "c8ddea9c3a55efaaa81a3fdf407b43944aff02aa", "content_id": "a45285e795843239fcb0fd38ce04b35a039f86b5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 526, "license_type": "no_license", "max_line_length": 70, "num_lines": 26, "path": "/sqlAlchemy/scripts/start.sh", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "#!/usr/bin/env bash\n\nset -e\n\nDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" && pwd )\"\nUSER=`whoami`\nPID_FILE=\"/Users/${USER}/PycharmProjects/gunicorn/var/run/server.pid\"\n\n#< add python installation if required ; and export path with python >\n\ncd ${DIR}/..\n\nexport CONFFILE_PATH=../config/app_conf_local.py\n\n\n# pip3 install -r requirements.txt\n\necho \"checking db upgrade\"\n\n#python3 manage.py db upgrade 2>&1\n\necho \"Starting gunicorn\"\n\ngunicorn manage:app -c config/gunicorn_conf.py --pid ${PID_FILE}\n\necho \"started the service\"\n" }, { "alpha_fraction": 0.6133567690849304, "alphanum_fraction": 0.6274164915084839, "avg_line_length": 17.354839324951172, "blob_id": "c18f9ca92a34b3c8003ad341d845794141a0458c", "content_id": "824b76449512c930df93e34a3198de4c3a77aee9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 569, "license_type": "no_license", "max_line_length": 82, "num_lines": 31, "path": "/scripts/stop.sh", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "#!/usr/bin/env bash\n\nset -e\n\nDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" && pwd )\"\nUSER=`whoami`\nPID_FILE=\"/Users/${USER}/PycharmProjects/gunicorn/var/run/server.pid\"\n\n#< add python installation if required ; and export path with python >\n\ncd ${DIR}/..\n\nif [ ! -f ${PID_FILE} ]; then\n echo \"The file ${PID_FILE} does not exist, it seems server is already stopped\"\n exit 0\nfi\n\nPID=`cat ${PID_FILE}`\n\nkill -15 ${PID}\n\nsleep 2\n\nkill -0 ${PID}\n\nif [ $? -eq 0 ]; then\n echo \"Could not shut down server in time better investigate\"\n exit 1\nfi\n\nrm -f ${PID_FILE}\n" }, { "alpha_fraction": 0.5565217137336731, "alphanum_fraction": 0.560869574546814, "avg_line_length": 20.799999237060547, "blob_id": "4295e5092765f83afd40dd35e1955fff96c0160d", "content_id": "aa0f7e1b82e91e9de2b973970f58ea172bcb8108", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 460, "license_type": "no_license", "max_line_length": 51, "num_lines": 20, "path": "/api/dumyapi/apis/__init__.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Api\r\nfrom dumyapi.apis.language_api import langnamespace\r\n\r\n\r\nauthorization = {\r\n 'Basic Auth': {'type': 'basic',\r\n 'in': 'header',\r\n 'name': 'authorization'\r\n }\r\n}\r\n\r\napi = Api(\r\n title='Language-API',\r\n version='V1',\r\n description='Lunguage API',\r\n security='Basic Auth',\r\n authorizations=authorization\r\n)\r\n\r\napi.add_namespace(langnamespace, path=\"/v1\")\r\n\r\n\r\n" }, { "alpha_fraction": 0.5571969747543335, "alphanum_fraction": 0.5571969747543335, "avg_line_length": 36.18309783935547, "blob_id": "1efdfe357072f6c054de03cc256a0816234e42f4", "content_id": "92b4ad31274be2770574ed1fdb010f465b86acfa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2640, "license_type": "no_license", "max_line_length": 118, "num_lines": 71, "path": "/sqlAlchemy/sqlAlchemy/models/utils/movies.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from sqlAlchemy.models.utils.base_db import db\nfrom sqlAlchemy.models.utils.database_session import Persistance\nfrom sqlAlchemy.models.schema.movies import Movies\nfrom sqlalchemy import text\n\n\nclass MovieDbOperations:\n\n @staticmethod\n def create(dict_args):\n #print(dict_args)\n movies_model_ins = Movies(dict_args)\n with Persistance().session as session:\n session.add(movies_model_ins)\n\n @staticmethod\n def delete(moviename):\n with Persistance().session as session:\n session.query(Movies).filter(text(f\"movies.movie_name={moviename}\")).delete(synchronize_session=False)\n\n #try:\n # db.session.query(Movies).filter(text(f\"movies.movie_name={moviename}\")).delete(synchronize_session=False)\n # db.session.commit()\n #except Exception as Error:\n # db.session.rollback()\n # raise Exception(Error)\n #finally:\n # db.session.close()\n\n @staticmethod\n def update(dict_args):\n with Persistance().session as session:\n session.query(Movies).filter(text(f\"movies.movie_name={dict_args.get('moviename')}\")).update(dict_args,\n synchronize_session=False)\n # try:\n # db.session.query(Movies).filter(text(f\"movies.movie_name={moviename}\")).update(dict_args,\n # synchronize_session=False)\n # db.session.commit()\n # except Exception as Error:\n # db.session.rollback()\n # raise Exception(Error)\n # finally:\n # db.session.close()\n\n def select(self, condition, all_row):\n if all_row:\n return self._select_all(condition)\n else:\n return self._select_one(condition)\n\n def _select_one(self,condition):\n with Persistance().session as session:\n if condition:\n result = session.query(Movies).filter(text(condition)).first()\n else:\n result = session.query(Movies).first()\n if result:\n return [result.to_obj()]\n else:\n return []\n\n def _select_all(self, condition):\n with Persistance().session as session:\n if condition:\n result = session.query(Movies).filter(text(condition)).all()\n else:\n result = session.query(Movies).all()\n if result:\n return [each_row.to_obj() for each_row in result if each_row]\n else:\n return []\n" }, { "alpha_fraction": 0.6500178575515747, "alphanum_fraction": 0.6714234948158264, "avg_line_length": 37.356163024902344, "blob_id": "7d2968550d3d6018aee914a92fd5fcdc3b0c8aa9", "content_id": "c163a28a1a804002f1617b7375aff89176933613", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2803, "license_type": "no_license", "max_line_length": 96, "num_lines": 73, "path": "/sqlAlchemy/sqlAlchemy/apis/movies.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "\nfrom flask_restplus import Resource, fields, reqparse, Namespace\nfrom sqlalchemy.resources.injectors import ins_creation\n\n\nparselevel=reqparse.RequestParser()\nparselevel.add_argument('directorname', type=str, required=True, help='Enter the director name')\n\nnamespace = Namespace('Movies', description='to movies from file')\n\nmovieschema = namespace.model('Movies', {\n 'Director': fields.String(description='Director name', required=True),\n 'Movie Name': fields.String(description='Movie name', required=True),\n 'Release Year': fields.Integer(description='Year of release', required=True)\n})\n\[email protected]('/movies')\nclass TodoSimple(Resource):\n @namespace.response(200, 'success')\n @namespace.response(400, 'Bad request')\n @namespace.response(500, 'Internal server error')\n @namespace.response(404, 'Not found')\n @namespace.response(403, 'Unauthorized')\n # @namespace.doc(parser=awsparselevel)\n def get(self):\n\n mov_db_ins, mov_ins = ins_creation()\n result = mov_ins.getallmovies(movies_ins=mov_db_ins)\n if not result:\n return {\"movies\": \"movies not found\"}, 404\n else:\n return {\"movies\": result}, 200\n\n @namespace.response(201, 'success')\n @namespace.response(400, 'Bad request')\n @namespace.response(500, 'Internal server error')\n @namespace.response(404, 'Not found')\n @namespace.response(403, 'Unauthorized')\n @namespace.expect(movieschema)\n def post(self):\n payload = self.parsing_args()\n print(payload)\n movies_db_ins, movies_ops_ins = ins_creation()\n insert_db = movies_ops_ins.insertintodb(payload,movies_db_ins)\n if insert_db == 'success':\n return 'success', 201\n\n @staticmethod\n def parsing_args():\n parselevel = reqparse.RequestParser()\n parselevel.add_argument('Director', type=str, required=True)\n parselevel.add_argument('Movie Name', type=str, required=True)\n parselevel.add_argument('Release Year', type=int, required=True)\n return parselevel.parse_args()\n\n\[email protected]('/directorname')\nclass TodoSimpleDirector(Resource):\n @namespace.response(200, 'success')\n @namespace.response(400, 'Bad request')\n @namespace.response(500, 'Internal server error')\n @namespace.response(404, 'Not found')\n @namespace.response(403, 'Unauthorized')\n @namespace.doc(parser=parselevel)\n def get(self):\n payload = parselevel.parse_args()\n print(payload)\n directorname = payload.get('directorname')\n movies_db_ins, movies_ops_ins = ins_creation()\n result = movies_ops_ins.getmoviesbydir(directorname, movies_db_ins)\n if not result:\n return {\"movies\": \"movies not found\"}, 404\n else:\n return {\"movies\": result}, 200\n\n\n" }, { "alpha_fraction": 0.6823529601097107, "alphanum_fraction": 0.6823529601097107, "avg_line_length": 27.867923736572266, "blob_id": "9c8f61b809336503c244d449cc12c0842574aad1", "content_id": "88130a4b39e66b3f872fa03e0e677e0dee5c4784", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1530, "license_type": "no_license", "max_line_length": 92, "num_lines": 53, "path": "/sqlAlchemy/venv/bin/utils/database_session.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from sqlalchemy import create_engine\nfrom contextlib import contextmanager\nfrom sqlalchemy.orm import scoped_session\nfrom sqlalchemy.orm import sessionmaker\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlAlchemy.models.utils.base_db import db\n\n\ndef sql_engine(db_config: dict):\n '''This is for test case usage'''\n db_uri = (\n f\"postgresql://{db_config['user']}:{db_config['password']}\"\n f\"@{db_config['db_host']}:{db_config['db_port']}/{db_config['database']}\"\n )\n return create_engine(db_uri, convert_unicode=True)\n\nengine=db.get_engine()\nSESSION = scoped_session(sessionmaker(bind=engine, autocommit=True, expire_on_commit=False))\nBase = declarative_base()\nmetadata = Base.metadata\nmetadata.bind = engine\nBase.query = SESSION.query_property()\n\n@contextmanager\ndef session_scope():\n '''Provide a transactional scope around a series of operations'''\n session = scoped_session(sessionmaker(bind=engine, expire_on_commit=False))\n try:\n yield session\n session.commit()\n except Exception as Error:\n session.rollback()\n raise Exception(Error)\n finally:\n session.close()\n\n\nclass Persistance:\n '''Handle database releated actions/attributes'''\n @property\n def engine(self):\n '''Database enginer property'''\n return engine\n\n @property\n def base(self):\n '''Database base propery'''\n return Base\n\n @property\n def session(self):\n '''Database session propery'''\n return session_scope()\n" }, { "alpha_fraction": 0.5812274217605591, "alphanum_fraction": 0.588447630405426, "avg_line_length": 29.77777862548828, "blob_id": "43c5e441dddca03608acdebd19189655e12cddfe", "content_id": "a1cd02c9415cfe4e2c89e1d9ca7f24b2ed1718e4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 554, "license_type": "no_license", "max_line_length": 59, "num_lines": 18, "path": "/sqlAlchemy/sqlAlchemy/models/schema/movies.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from sqlAlchemy.models.utils.base_db import db\n\nclass Movies(db.Model):\n movie_name = db.Column(db.String(90), primary_key=True)\n year = db.Column(db.Integer)\n director = db.Column(db.String(80))\n\n def __init__(self, dict_args):\n self.director = dict_args.get('director')\n self.movie_name = dict_args.get('movie_name')\n self.year = int(dict_args.get('year'))\n\n def to_obj(self):\n return {\n \"movie_name\": self.movie_name,\n \"year\": self.year,\n \"director\": self.director\n }\n" }, { "alpha_fraction": 0.6509804129600525, "alphanum_fraction": 0.6705882549285889, "avg_line_length": 25.52083396911621, "blob_id": "87e846da94a484912cd6d52c53c46c1c394fe92f", "content_id": "eab007fbfc020ea7ef6ae4277d3addc15b53a88e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1275, "license_type": "no_license", "max_line_length": 132, "num_lines": 48, "path": "/FnD/fnd/apps/hello.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask import Flask\nfrom flask import make_response, render_template\nfrom flask_bootstrap import Bootstrap\n\napp = Flask(__name__)\nbootstrap = Bootstrap(app)\n\nclass Someobject:\n @staticmethod\n def somemethod():\n return 5\n\n\n#@app.route('/<path:name>')\ndef hello(name):\n return f'<h1> Hellow {name} </h1>'\n\napp.add_url_rule(endpoint='hello',view_func=hello,rule='/<path:name>')\n\[email protected]('/')\ndef index():\n response = make_response('<h1> This document is for index </h1>')\n response.set_cookie('answer', '42')\n return response\n\[email protected]('/test/<name>')\ndef template_test(name):\n return render_template('hello.html',var_name=name, mydict={'ac':40}, mylist=[1,2,3,4], myindex=1, myObject=Someobject())\n\[email protected]('/inherit/<name>')\ndef inherit_html(name):\n return render_template('inherit_hello.html',var_name=name, mydict={'ac':40}, mylist=[1,2,3,4], myindex=1, myObject=Someobject())\n\[email protected]('/body/<name>')\ndef body(name):\n return render_template('bodytemplate.html',var_name=name)\n\[email protected]('/user')\ndef user():\n return render_template('user.html')\n\[email protected]('/user_name/<name>')\ndef user_info(name):\n return render_template('user_info.html',var_name=name)\n\nif __name__ == '__main__':\n\n app.run(debug=True, port=5000)\n\n\n" }, { "alpha_fraction": 0.6634615659713745, "alphanum_fraction": 0.6744505763053894, "avg_line_length": 21.060606002807617, "blob_id": "a85bed6f242697662c7b504c8d9506299364fd54", "content_id": "7fad7d80efd787893fe52471d72b78da84328118", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 728, "license_type": "no_license", "max_line_length": 96, "num_lines": 33, "path": "/manage.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import os\nimport sys\nsys.path.append(\"/Users/ramesh/PycharmProjects/sqlAlchemy\")\nfrom flask_script import Manager\nfrom flask_migrate import MigrateCommand, Migrate\nfrom sqlAlchemy.app_file import app, db\n\n\nmigrate = Migrate(app, db)\nmanager = Manager(app)\nmanager.add_command('db', MigrateCommand)\n\n\[email protected]\ndef routes():\n '''show all routes available'''\n print(app.url_map)\n\n\[email protected]\ndef run():\n '''Run app'''\n routes()\n app.run(host='0.0.0.0',port=5000,threaded=True,debug=True)\n\n\[email protected]\ndef rm_pyc():\n '''Remove all pyc on bash only'''\n os.system('find . -type f -name \".py[co]\" -delete -or -type d -name \"__pycache__\" -delete')\n\nif __name__ == '__main__':\n manager.run()\n" }, { "alpha_fraction": 0.7288135886192322, "alphanum_fraction": 0.7372881174087524, "avg_line_length": 22.600000381469727, "blob_id": "fa6904803a9dcd56a96a970bca330fb73d3ac0c5", "content_id": "1c8d944a74e241a92b9b393cd8605464bb456de1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 236, "license_type": "no_license", "max_line_length": 63, "num_lines": 10, "path": "/sqlAlchemy/sqlAlchemy/apis/__init__.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from flask_restplus import Api\nfrom sqlAlchemy.apis.movies import namespace as moviesnamespace\n\napi = Api(\n title='Learn-API',\n version='V1',\n description='Learning API'\n)\n\napi.add_namespace(moviesnamespace, path=\"/v1/movies\")\n" }, { "alpha_fraction": 0.6521374583244324, "alphanum_fraction": 0.7015926241874695, "avg_line_length": 37.233333587646484, "blob_id": "55602fae9ccd4569f29caba65efcd84faa298f8c", "content_id": "80af08ad5e6b22aa95d63663c1b4a2ea54c65620", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1193, "license_type": "no_license", "max_line_length": 102, "num_lines": 30, "path": "/api/tests/unit_test/resources/test_aws.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "from unittest.mock import Mock, patch\r\nfrom boto.ec2.connection import EC2Connection\r\nimport boto\r\nfrom moto import mock_ec2_deprecated, mock_ec2\r\nfrom AWS.resources.aws import awsConnectRegion, AWSlistInstance\r\n\r\nclass Test_awsConnectRegion:\r\n\r\n def test_awsconnectresion_instatiation(self):\r\n awsins = awsConnectRegion(aws_id='xxx', aws_secret='asd12323')\r\n assert isinstance(awsins, awsConnectRegion)\r\n\r\n @mock_ec2_deprecated\r\n def test_connect_to_region(self):\r\n awsins = awsConnectRegion(aws_id='xxx', aws_secret='asd12323')\r\n result = awsins.connect_to_region('us-east-1')\r\n assert isinstance(result, EC2Connection)\r\n\r\n\r\n\r\nclass TestAWSlistInstance:\r\n\r\n @mock_ec2_deprecated\r\n @mock_ec2\r\n @patch.object(AWSlistInstance, 'listAllInstance')\r\n def test_listAllInstance(self, mock_instances):\r\n mock_instances.return_value = ['Instance:i-03117ab1abf9992e9', 'Instance:i-0c6aef3dfd797d6ac']\r\n aswlistins = AWSlistInstance(aws_id='xxx', aws_secret='yyy123')\r\n result = aswlistins.listAllInstance('us-east-1')\r\n assert result == ['Instance:i-03117ab1abf9992e9','Instance:i-0c6aef3dfd797d6ac']\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n" }, { "alpha_fraction": 0.6147686839103699, "alphanum_fraction": 0.6147686839103699, "avg_line_length": 33.06060791015625, "blob_id": "d4edc7a18d5318e84d5dd417b120da29771f0d84", "content_id": "c3bbec595827687edf8c360be86c3509764ee92a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1124, "license_type": "no_license", "max_line_length": 87, "num_lines": 33, "path": "/sqlAlchemy/sqlAlchemy/resources/movies_ops.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import os\nfrom sqlAlchemy.models.utils.movies import Dboperations\n\nclass MovieOperations:\n\n def getallmovies(self, movies_ins: Dboperations):\n # fpath = os.path.abspath(\"resources\\movies.csv\")\n all_db_rows = movies_ins.select(condition=None, all_row=True)\n if all_db_rows:\n return all_db_rows\n else:\n return []\n\n def getmoviesbydir(self, director, movie_ops_instance: Dboperations):\n condition = f\"movies.director = '{director}'\"\n list_by_condition = movie_ops_instance.select(condition=condition,all_row=True)\n if list_by_condition:\n return list_by_condition\n else:\n return []\n\n def insertintodb(self, payload, movie_ops_instance: Dboperations ):\n dict_args = {\n 'director': payload.get('Director'),\n 'movie_name': payload.get('Movie Name'),\n 'year': payload.get('Release Year')\n }\n movie_ops_instance.create(dict_args)\n return 'success'\n\nif __name__ == '__main__':\n movie = MovieOperations()\n #print(movie.getmoviesbydir('FrancisLawrence'))\n" }, { "alpha_fraction": 0.7294833064079285, "alphanum_fraction": 0.7294833064079285, "avg_line_length": 40, "blob_id": "5549689544218d066bcf71600ab4846992e0de7d", "content_id": "f4da4bfca4941d4136aed7b61df8163ce120b169", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 329, "license_type": "no_license", "max_line_length": 94, "num_lines": 8, "path": "/sqlAlchemy/config/app_conf_local.py", "repo_name": "crkg/sqlAlchemy", "src_encoding": "UTF-8", "text": "import os\nfrom ast import literal_eval\n_basedir = os.path.abspath(os.path.dirname(__file__))\npath = os.path.join(os.path.abspath(os.path.dirname(__file__)),'../sqlAlchemy/models/test.db')\n\nSQLALCHEMY_DATABASE_URI = os.environ.get('SQLALCHEMY_DATABASE_URI', \"sqlite:///\"+ path)\nSQLALCHEMY_TRACK_MODIFICATIONS = True\nDEBUG = True\n\n" } ]	30
munazzahkhan/hb-react-trading-cards-2	https://github.com/munazzahkhan/hb-react-trading-cards-2	0c6e481426a728299a4360b440c0c3a2cfbd86dd	7a576693966418123c7048069c6dc39c0f8446b2	b18c3f3a5a959bf32fbbdf2f5d0e8fe6dc63476d	refs/heads/master	2023-04-27T02:22:06.027339	2021-05-21T00:20:28	2021-05-21T00:20:28	369,370,104	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6452425718307495, "alphanum_fraction": 0.6490232944488525, "avg_line_length": 30.739999771118164, "blob_id": "9950531f82e3076e5fa6d41a6c80ac15579b2d2f", "content_id": "2cd25daffba2313ba100ef625be74293a6d6fa55", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1587, "license_type": "no_license", "max_line_length": 149, "num_lines": 50, "path": "/server.py", "repo_name": "munazzahkhan/hb-react-trading-cards-2", "src_encoding": "UTF-8", "text": "from flask import Flask, render_template, jsonify, request\nfrom model import db, connect_to_db, Card\napp = Flask(__name__)\n\[email protected](\"/\")\ndef show_homepage():\n \"\"\"Show the application's homepage.\"\"\"\n\n return render_template(\"homepage.html\")\n\[email protected](\"/cards\")\ndef show_cards():\n \"\"\"Show all trading cards.\"\"\"\n\n return render_template(\"cards.html\")\n\[email protected](\"/cards.json\")\ndef get_cards_json():\n \"\"\"Return a JSON response with all cards in DB.\"\"\"\n\n cards = Card.query.all()\n cards_list = []\n\n for c in cards:\n cards_list.append({\"skill\": c.skill, \"name\": c.name, \"imgUrl\": c.image_url, \"cardId\": c.card_id})\n\n return {\"cards\": cards_list}\n\[email protected](\"/add-card\", methods=[\"POST\"])\ndef add_card():\n \"\"\"Add a new card to the DB.\"\"\"\n name = request.get_json().get('name')\n skill = request.get_json().get('skill')\n\n new_card = Card(name=name, skill=skill)\n db.session.add(new_card)\n db.session.commit()\n # the new_card variable we created on line 35 did not have its card_id set\n # we call db.session.refresh(new_card) to update the variable to the version from the database\n # that way, its card_id will be set\n db.session.refresh(new_card)\n return {\"success\": True, \"cardAdded\": {\"skill\": new_card.skill, \"name\": new_card.name, \"imgUrl\": new_card.image_url, \"cardId\": new_card.card_id}}\n\[email protected](\"/cards-jquery\")\ndef show_cards_jquery():\n return render_template(\"cards-jquery.html\")\n\nif __name__ == \"__main__\":\n connect_to_db(app)\n app.run(debug=True, use_reloader=True, use_debugger=True, host=\"0.0.0.0\")\n" } ]	1
ezik/git_hub_api_tests	https://github.com/ezik/git_hub_api_tests	4dc3f66dc580c737c4c160b439bf8aca7190c30b	cfb5767c00eb823c5e50486066b7eb722a299d19	249671a73c045cc868b81b9c5334b9c46f846967	refs/heads/master	2022-12-10T18:35:16.533433	2018-11-05T13:13:31	2018-11-05T13:13:31	156,219,583	0	0	null	2018-11-05T13:09:31	2018-11-05T13:13:44	2022-12-08T01:16:35	HTML	[ { "alpha_fraction": 0.4639769494533539, "alphanum_fraction": 0.4639769494533539, "avg_line_length": 30.636363983154297, "blob_id": "69c9de9a0f9c76163a0debb4909bb933cfa867cc", "content_id": "8fa7683cb2455d989cae099a52d7a79c82a100a9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 347, "license_type": "no_license", "max_line_length": 57, "num_lines": 11, "path": "/config.py", "repo_name": "ezik/git_hub_api_tests", "src_encoding": "UTF-8", "text": "class Config:\n def __init__(self):\n self.url = {\n \"base\": \"https://api.github.com/repos\",\n \"ursus_repo\": \"/ursusrepublic/django_test\",\n \"ezik_repo\": \"/ezik/selenium_python_training\"\n }\n self.auth = {\n \"username\": \"username\",\n \"password\": \"password\"\n }" }, { "alpha_fraction": 0.5779967308044434, "alphanum_fraction": 0.5859332084655762, "avg_line_length": 45.846153259277344, "blob_id": "460c8be448bc27871d10a29ca5eea5140ce50cca", "content_id": "25437a1f62d3959eef9b6ddda7c0a1e0ceb0920d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3654, "license_type": "no_license", "max_line_length": 114, "num_lines": 78, "path": "/test_create_pull_request.py", "repo_name": "ezik/git_hub_api_tests", "src_encoding": "UTF-8", "text": "import requests\nfrom requests.auth import HTTPBasicAuth\nimport random\nimport re\n\n\ndef test_create_pull_req(app_config):\n \"\"\"This test is intended to create pull request. As precondition user has to:\n - Prepare branch basing on existing branches in repo\n - Prepare commit in new branch\n - Create pull request for the commit\n I used own repo on github to ensure that I have rights for pull requests\n Hope comments will add more transparency on what is happening inside\n Assertions in between are used to ensure that all data is created\"\"\"\n base_url = app_config.url[\"base\"]\n repo = app_config.url[\"ezik_repo\"]\n username = app_config.auth[\"username\"]\n password = app_config.auth[\"password\"]\n\n print(\"\\n=====START PRECONDITION STEPS=====\")\n\n get_branches_list_response = requests.get(base_url + repo + \"/git/refs/heads\")\n branches_list_data = get_branches_list_response.json()\n assert get_branches_list_response.status_code == 200\n\n sha_list = list()\n for sha in branches_list_data:\n sha_list.append(tuple((sha[\"ref\"], sha[\"object\"][\"sha\"])))\n assert sha_list[0][0] == \"refs/heads/branch_requests_test\"\n\n ref_branch = \"{0}_{1}\".format(sha_list[0][0], random.choice(range(101, 10000))) # generate ref branch\n head_branch_name = re.sub(r\"refs/heads/\", \"\", ref_branch, flags=re.I) # substring branch name from ref branch\n print(\"HEAD BRANCH NAME...\\n\", head_branch_name)\n\n create_branch_response = requests.post(base_url + repo + \"/git/refs\",\n json={\n \"ref\": ref_branch,\n \"sha\": sha_list[0][1]\n }, auth=HTTPBasicAuth(username=username, password=password))\n assert create_branch_response.status_code == 201\n\n new_branch_data = create_branch_response.json()\n sha_latest_commit = new_branch_data[\"object\"][\"sha\"]\n print(\"LATEST SHA COMMIT...\\n\", sha_latest_commit)\n\n sha_base_tree_response = requests.get(base_url + repo + \"/git/commits/{}\".format(sha_latest_commit))\n assert sha_base_tree_response.status_code == 200\n\n sha_base_tree_json = sha_base_tree_response.json()\n sha_base_tree = sha_base_tree_json[\"tree\"][\"sha\"]\n commit_parent = sha_base_tree_json[\"parents\"][0][\"sha\"]\n\n create_commit_response = requests.post(base_url + repo + \"/git/commits\",\n json={\n \"message\": \"freaking commit\",\n \"tree\": sha_base_tree,\n \"parents\": [commit_parent]\n }, auth=HTTPBasicAuth(username=username, password=password))\n create_commit_data = create_commit_response.json()\n assert create_commit_data[\"author\"][\"name\"] == \"ezik\"\n assert create_commit_data[\"message\"] == \"freaking commit\"\n\n print(\"=====END PRECONDITION STEPS=====\")\n\n create_pull_req_response = requests.post(base_url + repo + \"/pulls\",\n json={\n \"title\": \"Amazing new feature\",\n \"body\": \"Please pull this in!\",\n \"head\": head_branch_name,\n \"base\": \"master\"\n }, auth=HTTPBasicAuth(username=username, password=password))\n\n pull_req_data = create_pull_req_response.json()\n\n assert create_pull_req_response.status_code == 201\n assert pull_req_data[\"state\"] == \"open\"\n assert pull_req_data[\"body\"] == \"Please pull this in!\"\n assert pull_req_data[\"head\"][\"ref\"] == head_branch_name\n" }, { "alpha_fraction": 0.4577777683734894, "alphanum_fraction": 0.6844444274902344, "avg_line_length": 15.071428298950195, "blob_id": "c4258f190e9517dbd99343b143ef35fae662beeb", "content_id": "718b0942e263c684b5fd62f720da48f5edd2db30", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 225, "license_type": "no_license", "max_line_length": 22, "num_lines": 14, "path": "/requirements.txt", "repo_name": "ezik/git_hub_api_tests", "src_encoding": "UTF-8", "text": "atomicwrites==1.2.1\nattrs==18.2.0\ncertifi==2018.10.15\nchardet==3.0.4\nidna==2.7\nmore-itertools==4.3.0\npluggy==0.8.0\npy==1.7.0\npytest==3.9.3\npytest-html==1.19.0\npytest-metadata==1.7.0\nrequests==2.20.0\nsix==1.11.0\nurllib3==1.24\n" }, { "alpha_fraction": 0.7254902124404907, "alphanum_fraction": 0.7254902124404907, "avg_line_length": 18.125, "blob_id": "93043111a1fc6fee772083566dd79a91eb945223", "content_id": "404069f4aa2c68c5f4a5259d2849e35a861deab5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 153, "license_type": "no_license", "max_line_length": 39, "num_lines": 8, "path": "/conftest.py", "repo_name": "ezik/git_hub_api_tests", "src_encoding": "UTF-8", "text": "from pytest import fixture\nfrom config import Config\n\n\n@fixture(scope='session', autouse=True)\ndef app_config():\n config = Config()\n return config\n" }, { "alpha_fraction": 0.5850773453712463, "alphanum_fraction": 0.5959963798522949, "avg_line_length": 27.921052932739258, "blob_id": "d3ac3746e47e255734de0eb1727713df85fe92cd", "content_id": "0e9d1b43f4dd06f915a3ec9dce36a1916ab30951", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1099, "license_type": "no_license", "max_line_length": 61, "num_lines": 38, "path": "/test_get_requests.py", "repo_name": "ezik/git_hub_api_tests", "src_encoding": "UTF-8", "text": "import requests\n\n\ndef test_get_open_pull_reqs(app_config):\n base_url = app_config.url[\"base\"]\n repo = app_config.url[\"ursus_repo\"]\n\n r = requests.get(base_url + repo + \"/pulls?state=open\")\n\n assert len(r.json()) == 2\n assert r.json()[0][\"url\"] == base_url + repo + \"/pulls/5\"\n assert r.json()[0][\"state\"] == \"open\"\n assert r.json()[0][\"title\"] == \"random comment added\"\n\n\ndef test_get_closed_pull_reqs(app_config):\n base_url = app_config.url[\"base\"]\n repo = app_config.url[\"ursus_repo\"]\n\n r = requests.get(base_url + repo + \"/pulls?state=closed\")\n\n assert len(r.json()) == 1\n assert r.json()[0][\"url\"] == base_url + repo + \"/pulls/6\"\n assert r.json()[0][\"state\"] == \"closed\"\n assert r.json()[0][\"title\"] == \"we don't need admin.py\"\n\n\ndef test_get_branches_list(app_config):\n base_url = app_config.url[\"base\"]\n repo = app_config.url[\"ursus_repo\"]\n\n r = requests.get(base_url + repo + \"/branches\")\n json_data = r.json()\n all_branches = list()\n for el in json_data:\n all_branches.append(el[\"name\"])\n\n assert len(all_branches) == 30\n" }, { "alpha_fraction": 0.5396634340286255, "alphanum_fraction": 0.5396634340286255, "avg_line_length": 38.619049072265625, "blob_id": "88b24385be9ab584e554ffc50f2ebb1702e94a5b", "content_id": "18d38bb0c5a2e379de4a5a02fc9c833b84518144", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 832, "license_type": "no_license", "max_line_length": 84, "num_lines": 21, "path": "/test_create_an_issue.py", "repo_name": "ezik/git_hub_api_tests", "src_encoding": "UTF-8", "text": "import requests\nfrom requests.auth import HTTPBasicAuth\n\n\ndef test_create_new_issue(app_config):\n base_url = app_config.url[\"base\"]\n repo = app_config.url[\"ursus_repo\"]\n username = app_config.auth[\"username\"]\n password = app_config.auth[\"password\"]\n\n r = requests.post(base_url + repo + \"/issues\",\n json={\n \"title\": \"Issue title for test\",\n \"body\": \"Smth doesn't work!\",\n \"labels\": [\"test\", \"amazing\", \"new_issue\"],\n \"assignees\": [\"django_test\"]\n }, auth=HTTPBasicAuth(username=username, password=password))\n\n assert r.json()[\"repository_url\"] == base_url + repo\n assert r.json()[\"title\"] == \"Issue title for test\"\n assert r.json()[\"body\"] == \"Smth doesn't work!\"\n" } ]	6
dinolive666/calculation	https://github.com/dinolive666/calculation	e47c50a50ed4b1422e24571acae0b1876171f813	1e5e89b5d693bd9af5d97ba2c3fcdecba5301471	d3dd09ea92b3b9175fdba35542cdc8feeed6d446	refs/heads/main	2023-06-10T06:38:52.444451	2021-06-29T07:20:24	2021-06-29T07:20:24	381,272,220	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6292452812194824, "alphanum_fraction": 0.6537736058235168, "avg_line_length": 16.09677505493164, "blob_id": "5b60e5feb1e5c83da8c336fc34c56b5e8b2314c0", "content_id": "6d3caf75b867872cb7f32937935752834363bdc4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1270, "license_type": "no_license", "max_line_length": 79, "num_lines": 62, "path": "/interval.py", "repo_name": "dinolive666/calculation", "src_encoding": "UTF-8", "text": "#代码整理\n\nimport pandas as pd\ndata = pd.read_excel('./data5/interval.xlsx')\n#取出time_break\nt = data['time_break'].values.tolist()\n#初始化\ngroup = []\nn = 1\n#通过time_break判断创建分组\nfor num in range(len(data)):\n if t[num] == 0:\n group.append(n)\n else:\n n = n+1\n group.append(n)\n#将分组放入原数据新增一列\ndata['group'] = group\n#导出文件\nwriter = pd.ExcelWriter('./data5/group.xlsx')\ndata.to_excel(writer,float_format='%.5f')\nwriter.save()\n\n\n\n\n\n\n#整理脚本，解决读取超过65535行csv数据\n\nimport pandas as pd\nimport numpy as np\n\n\n#使用chunksize分块读取大型csv文件，这里每次读取chunksize为100万\ndata_chunk = pd.read_csv('./data5/all.csv', chunksize=1000000, iterator = True)\n\nchunk_list = [] \n\nfor chunk in data_chunk:\n chunk_list.append(chunk)\n \n#再把这些块组合成一个DataFrame\ndata = pd.concat(chunk_list) \n\n#取出time_break\nt = data['time_break'].values.tolist()\n#初始化\ngroup = []\nn = 1\n#通过time_break判断创建分组\nfor num in range(len(data)):\n if t[num] == 0:\n group.append(n)\n else:\n n = n+1\n group.append(n)\n#将分组放入原数据新增一列\ndata['group'] = group\n\n#导出文件\ndata.to_csv('./data5/all_group.csv')\n" }, { "alpha_fraction": 0.6838932037353516, "alphanum_fraction": 0.6976743936538696, "avg_line_length": 14.479999542236328, "blob_id": "35a6b7ad6dfb057462d9269b8830a441939bf158", "content_id": "b43088080fcd11f6cecbe90ae29d14bd4ebc65ef", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1253, "license_type": "no_license", "max_line_length": 54, "num_lines": 75, "path": "/relation.py", "repo_name": "dinolive666/calculation", "src_encoding": "UTF-8", "text": "# 代码整理找出所有循环\n\nimport pandas as pd\nimport networkx as nx\nimport numpy as np\nimport csv \nimport matplotlib.pyplot as plt \n\nrelation = pd.read_csv(\"./data4/relation.csv\")\n\nedges = list(zip(relation.source, relation.target))\n\n# 创建有向图\ngraph = nx.DiGraph()\ngraph.add_edges_from(edges)\nnx.draw_kamada_kawai(graph, with_labels = True)\n\n#找出所有循环\ndata = list(nx.simple_cycles(graph))\nfile = open('./data4/cycles.csv' , 'w+', newline = '')\nwith file:\n write = csv.writer(file)\n write.writerows(data)\n\n\n\n \n \n \n\n# 试验networkx中关于circle的算法\nimport pandas as pd\nimport networkx as nx\nimport numpy as np\nimport csv \nimport matplotlib.pyplot as plt \n\nG = nx.Graph()\nnx.add_cycle(G, [0, 1, 2, 3])\nnx.add_cycle(G, [0, 3, 4, 5])\nnx.draw(G, with_labels = True)\nprint(nx.cycle_basis(G, 0))\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n#找出所有连接的点\n\nimport pandas as pd\nimport networkx as nx\nimport numpy as np\nimport csv \nimport matplotlib.pyplot as plt \n\nrelation2 = pd.read_csv(\"./data4/relation2.csv\")\n\nedges = list(zip(relation2.source, relation2.target))\n\n# 创建有向图\ngraph = nx.Graph()\ngraph.add_edges_from(edges)\nnx.draw(graph, with_labels = True)\n\n#找出连接\nlist(nx.node_connected_component(graph, \"kk\"))\n" } ]	2
shireesha-reddy/CTS	https://github.com/shireesha-reddy/CTS	4b5361ca3983e31a2aec4a31f81f352b43d036a8	6eebac20447c3d6b64ee9b2d1e975fa09bc3a54e	a63584cd8f59dbebad341e0df6c008eafc046b0a	refs/heads/main	2023-03-09T13:25:05.713329	2021-02-19T12:01:25	2021-02-19T12:01:25	340,310,451	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6415094137191772, "alphanum_fraction": 0.6540880799293518, "avg_line_length": 52, "blob_id": "a3c1327e57875ca2e8392995f72921b5d4a857db", "content_id": "40a1b5317716a806b30ba3b186944cc761f1ad21", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 159, "license_type": "no_license", "max_line_length": 59, "num_lines": 3, "path": "/tcs.py", "repo_name": "shireesha-reddy/CTS", "src_encoding": "UTF-8", "text": "r[n] = start + step*n (for both positive and negative step)\nwhere, n >=0 and r[n] < stop (for positive step)\nwhere, n >= 0 and r[n] > stop (for negative step)\n" } ]	1
marijastrugar/SP-Midterm-Exam	https://github.com/marijastrugar/SP-Midterm-Exam	0b38bd1858e7fceaf332bcac6ad4783489c497b6	c2f40d9a05cc8483d3820621402ce30a726ac562	328560d2d2bb6f6bc3ac14fb3bd51873e9b30794	refs/heads/master	2020-04-05T07:13:33.760523	2018-11-08T09:34:46	2018-11-08T09:34:46	156,667,525	0	0	null	2018-11-08T07:32:29	2018-11-08T07:32:19	2018-11-08T07:32:18	null	[ { "alpha_fraction": 0.4595375657081604, "alphanum_fraction": 0.5231214165687561, "avg_line_length": 27, "blob_id": "13a6c6bb844e52a059b44940c57b1e91f2f247c4", "content_id": "8b46d179cd42693217fba0c3804bb66960f83198", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 346, "license_type": "no_license", "max_line_length": 51, "num_lines": 12, "path": "/Zadatak4.py", "repo_name": "marijastrugar/SP-Midterm-Exam", "src_encoding": "UTF-8", "text": "def insert(a):\r\n for i in range(1, len(a)):\r\n current = 0\r\n while current < i:\r\n if a[i] < a[current]:\r\n a[current], a[i]= a[i] , a[current]\r\n current = current + 1\r\n return a\r\n\r\nprint (insert([12,54,66,43,11,33,34,33,1,45]))\r\nProjects/SP-Midterm-Exam\r\nC:\\Users\\PC\\Projects\\SP-Midterm-Exam" }, { "alpha_fraction": 0.35849055647850037, "alphanum_fraction": 0.37106919288635254, "avg_line_length": 15.777777671813965, "blob_id": "e911e06f93e19d689c019c6599d8e4640d72c18a", "content_id": "f547ec2f5ced6b32e2133f6198d436b622a20655", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 318, "license_type": "no_license", "max_line_length": 33, "num_lines": 18, "path": "/Zadatak2.py", "repo_name": "marijastrugar/SP-Midterm-Exam", "src_encoding": "UTF-8", "text": "def recStep(nn, d):\r\n print(str(nn))\r\n if d < 0:\r\n if nn > 0:\r\n recStep(nn-m, d)\r\n else:\r\n recStep(nn+m, d * -1)\r\n else:\r\n if nn < n:\r\n recStep(nn+m, d)\r\n else:\r\n return\r\n\r\n\r\nn = int(input(\"N: \"))\r\nm = int(input(\"M: \"))\r\n\r\nrecStep(n, -1)" }, { "alpha_fraction": 0.5, "alphanum_fraction": 0.524193525314331, "avg_line_length": 26.769229888916016, "blob_id": "e2d742c386938894334ebcf397ca3c13f6c47f0f", "content_id": "8119992d53042f1a30b64de197279c995df5c96d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 372, "license_type": "no_license", "max_line_length": 68, "num_lines": 13, "path": "/Zadatak1.py", "repo_name": "marijastrugar/SP-Midterm-Exam", "src_encoding": "UTF-8", "text": "sum = 0\r\ncount = 0\r\nnumber = input(\"Enter a number: \")\r\nif number != '=':\r\n number = int(number)\r\nwhile number != '=':\r\n if number % 5 != 0 and number % 3 == 0:\r\n sum += number\r\n count += 1\r\n number = input(\"Enter a number: \")\r\n if number != '=':\r\n number = int(number)\r\nprint(\"Arithmetic mean: \" + str(sum/count) if count > 0 else str(0))" } ]	3
NikitaZagor/PyPennet	https://github.com/NikitaZagor/PyPennet	019ef19b7893bacf8340ac053b73ff1761c9e504	e78148a72e161353af998256011ab96ef97d5950	5208bb78e0371ed973a422382b4b8c5417e02b3a	refs/heads/master	2020-04-08T19:24:00.174351	2018-12-01T06:40:34	2018-12-01T06:40:34	127,250,268	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5788177251815796, "alphanum_fraction": 0.5867254137992859, "avg_line_length": 43.91666793823242, "blob_id": "723bbedb3e7b1873b3f5f0eeded8d090b2f7d463", "content_id": "b8f33844bd83b284ed3940c0d3b4df0163f0edde", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 8678, "license_type": "no_license", "max_line_length": 113, "num_lines": 168, "path": "/PyPennet/gui/baseFrame.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Frame, Button, Menu, StringVar\r\nfrom tkinter import BOTH, END, LEFT, RIGHT, RAISED, SUNKEN, TOP, X\r\nfrom PyPennet.gui.baseEntry import BaseEntry\r\nimport PyPennet.utility.util as my_util\r\n\r\nclass BaseFrame:\r\n def __init__(self, num, onClose, onExecution, parent=None):\r\n self.parent = parent\r\n self.onClose = onClose\r\n self.onExecution = onExecution\r\n if(parent is not None):\r\n parent.resizable(False, False) # Запрещаем изменение размеров окна\r\n self.countColumn = num\r\n self.entries = [] # В этом списке num X num будут храниться ссылки на entry результатов\r\n for i in range(num):\r\n self.entries.append([])\r\n self.columnTitles = [] # В этом списке будут храниться ссылки на entry заглавной строки\r\n self.rowTitles = [] # В этом списке будут храниться ссылки на entry заглавной колонки\r\n self.curResult = StringVar()\r\n self.initUI()\r\n\r\n def initUI(self):\r\n # Создаем контейнер для размещения матрицы полей ввода данных и вывода результатов\r\n self.entryFrame = Frame(self.parent, bd = 5, relief = SUNKEN)\r\n # Создаем меню\r\n self.makeMenu()\r\n # Размещаем поля ввода данных для верхней строки и запоминаем ссылки на них в списке: firstRow\r\n for i in range(self.countColumn + 1):\r\n entr = BaseEntry(self.countColumn, self.entryFrame)\r\n if i != 0:\r\n self.columnTitles.append(entr)\r\n entr.grid(row = 0, column = i, padx = 10, pady = 10)\r\n\r\n # Размещаем поля ввода для первой колонки и для строк вывода результатов\r\n for i in range(self.countColumn):\r\n for j in range(self.countColumn + 1):\r\n entr = BaseEntry(self.countColumn, self.entryFrame)\r\n if j == 0: # Это первое поле колонки\r\n self.rowTitles.append(entr)\r\n else: # Это поле матрицы результата\r\n self.entries[i].append(entr)\r\n entr.setReadOnly()\r\n entr.grid(row=i+1, column=j, padx = 10, pady = 10)\r\n self.entryFrame.pack(side = TOP, expand = True, fill = BOTH)\r\n\r\n # Размещаем командные кнопки\r\n self.frameBtn = Frame(self.parent, bd=5, relief=SUNKEN)\r\n self.btnExec = Button(self.frameBtn, text='Построить', command=self.onExec, bd=5, relief=RAISED)\r\n self.btnExec.pack(side = LEFT, padx = 10, pady = 10)\r\n self.btnExit = Button(self.frameBtn, text='Закрыть', command=self.onExit, bd=5, relief=RAISED)\r\n self.btnExit.pack(side = RIGHT, padx = 10, pady = 10)\r\n self.frameBtn.pack(side = TOP, expand = True, fill = X)\r\n\r\n def makeMenu(self):\r\n menubar = Menu(self.parent, tearoff=0)\r\n self.parent.config(menu=menubar)\r\n file_menu = Menu(menubar, tearoff=0)\r\n file_menu.add_command(label='Сохранить результат', command = self.saveResult)\r\n clear_menu = Menu(file_menu, tearoff=0)\r\n clear_menu.add_command(label='Очистить заголовоки колонок', command = self.clearRow)\r\n clear_menu.add_command(label='Очистить заголовки строк', command = self.clearColumn)\r\n clear_menu.add_command(label='Очистить результат', command = self.clearGrid)\r\n file_menu.add_cascade(label='Очистить данные', menu = clear_menu, underline = 0)\r\n use_menu = Menu(file_menu, tearoff=0)\r\n use_menu.add_command(label='Заполнить заголовоки колонок', command = lambda: self.fill_column_titles(''))\r\n use_menu.add_command(label='Заполнить заголовки строк', command = lambda: self.fill_row_titles(''))\r\n file_menu.add_cascade(label='Использовать результат',menu = use_menu, underline = 0)\r\n file_menu.add_separator()\r\n file_menu.add_command(label='Закрыть', command = self.onExit)\r\n menubar.add_cascade(label='Файл', menu=file_menu)\r\n\r\n def onExit(self):\r\n title = self.parent.title()\r\n result = self.curResult.get()\r\n if len(result.strip()) == 0:\r\n self.onClose(title)\r\n self.parent.destroy()\r\n\r\n def onExec(self): # Заполняем ячейки сетки и формируем строку содержимого ячеек\r\n self.curResult.set('') # Обнуляем текущие данные\r\n tmp = ''\r\n for i in range(self.countColumn): # Прхолим по строкам таблицы\r\n for j in range(self.countColumn): # Проходим по колонкам таблицы\r\n valRow = self.rowTitles[i].get()\r\n valColumn = self.columnTitles[j].get()\r\n if len(valRow) != 0 and len(valColumn) != 0:\r\n result = valRow + valColumn # Результат соединение строки из ячейки первой колонки\r\n result = my_util.sortStr(result) # и строки из ячейки первой строки\r\n entr = self.entries[i][j]\r\n entr['width'] = len(result) + 1\r\n entr.setText(result) # Заносим текст в ячейку результата\r\n tmp += result # Накапливаем результат вы строке результата\r\n tmp += ',' # Разделяем данные запятой\r\n tmp = tmp.rstrip(',')\r\n self.curResult.set(tmp)\r\n title = self.parent.title()\r\n self.onExecution(title, self.curResult.get())\r\n\r\n def saveResult(self):\r\n if len(self.curResult.get()) > 0:\r\n result = []\r\n row = my_util.getStrFromEntries(self.columnTitles)\r\n result.append(row)\r\n column = my_util.getStrFromEntries(self.rowTitles)\r\n result.append(column)\r\n result.append(self.curResult.get())\r\n my_util.saveToFile(result)\r\n\r\n def fillEntries(self, entryLst, string):\r\n lst = [s.strip() for s in string.split(',')]\r\n length = len(lst)\r\n # Очистим ячейки\r\n for i in range(self.countColumn):\r\n entryLst[i].delete(0, END)\r\n # Заносим новые значения\r\n if length > self.countColumn:\r\n for i in range(self.countColumn):\r\n entryLst[i].insert(0, lst[i])\r\n else:\r\n for i in range(length):\r\n entryLst[i].insert(0, lst[i])\r\n\r\n def fill_column_titles(self, string):\r\n if len(string) == 0:\r\n prevResult = my_util.getFromFile()\r\n if prevResult != None:\r\n self.fillEntries(self.columnTitles, prevResult)\r\n else:\r\n self.fillEntries(self.columnTitles, string)\r\n\r\n def fill_row_titles(self, string):\r\n if len(string) == 0:\r\n prevResult = my_util.getFromFile()\r\n if prevResult != None:\r\n self.fillEntries(self.rowTitles, prevResult)\r\n else:\r\n self.fillEntries(self.rowTitles, string)\r\n\r\n def clearRow(self):\r\n for entr in self.columnTitles:\r\n entr.setText('')\r\n\r\n def clearColumn(self):\r\n for entr in self.rowTitles:\r\n entr.setText('')\r\n\r\n def clearGrid(self):\r\n for i in range(self.countColumn):\r\n for j in range(self.countColumn):\r\n self.entries[i][j].setText('')\r\n\r\nif __name__ == '__main__':\r\n from tkinter import Toplevel, Tk, Label, Entry\r\n def showTopLevel(parent, entr):\r\n window = Toplevel(parent)\r\n size = entr.get()\r\n dim = int(size)\r\n baseFrame = BaseFrame(dim, window)\r\n\r\n root = Tk()\r\n btn = Button(root, text = 'Show', command = lambda: showTopLevel(root, entr))\r\n btn.grid(row = 0, column = 0, padx = 10, pady = 10)\r\n lbl = Label(text = 'Размер')\r\n lbl.grid(row = 0, column = 1, padx = 10, pady = 10)\r\n entr = Entry(root, width = 4)\r\n entr.grid(row = 0, column = 2,padx = 10, pady = 10)\r\n\r\n root.mainloop()\r\n" }, { "alpha_fraction": 0.600082516670227, "alphanum_fraction": 0.6079240441322327, "avg_line_length": 37.75409698486328, "blob_id": "b9f987d18e9533911a2f55a5588cde7b216d196e", "content_id": "d803caecfec2bd08dfe1d981b3f820b3718dbad1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2459, "license_type": "no_license", "max_line_length": 124, "num_lines": 61, "path": "/PyPennet/gui/prev_perult.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Toplevel, Frame, Button, Listbox, Scrollbar\r\nfrom tkinter import SINGLE, END, LEFT, RIGHT, RAISED, RIDGE, TOP, BOTH, X, Y, SUNKEN\r\n\r\nclass PrevResult(Toplevel):\r\n def __init__(self, grids, selected, parent=None):\r\n Toplevel.__init__(self, parent)\r\n self.parent = parent\r\n self.title('Параметры новой решетки')\r\n self.grid = grids\r\n self.select = selected\r\n self.initUI()\r\n\r\n def initUI(self):\r\n main_frame = Frame(self, bd=5, relief=RIDGE)\r\n main_frame.pack(side=TOP, expand=True, fill=BOTH)\r\n\r\n listbox = Listbox(main_frame, width=35, height=4, selectmode=SINGLE, bd=5, relief=RIDGE)\r\n listbox.bind('<<ListboxSelect>>', self.selected)\r\n scrbary = Scrollbar(main_frame, orient='vertical')\r\n scrbarx = Scrollbar(main_frame, orient='horizontal')\r\n scrbary.config(command=listbox.yview, relief=SUNKEN)\r\n scrbarx.config(command=listbox.xview, relief=SUNKEN)\r\n listbox.config(yscrollcommand=scrbary.set, xscrollcommand=scrbarx.set)\r\n scrbary.pack(side=RIGHT, fill=Y)\r\n scrbarx.pack(side='bottom', fill=X)\r\n for key in self.grid.keys():\r\n listbox.insert(END, key)\r\n listbox.pack(side=TOP, expand=True, fill=BOTH)\r\n\r\n frame_buttons = Frame(self, bd=5, relief=RIDGE)\r\n frame_buttons.pack(side=TOP, expand=True, fill=X)\r\n btn_ok = Button(frame_buttons, text='Выбрать ', bd=5, relief=RAISED, command=self.on_ok)\r\n btn_ok.pack(side=LEFT, padx=5, pady=5)\r\n btn_cancel = Button(frame_buttons, text='Отменить', bd=5, relief=RAISED, command=self.on_cancel)\r\n btn_cancel.pack(side=RIGHT, padx=5, pady=5)\r\n\r\n def selected(self, event):\r\n widget = event.widget\r\n items = widget.curselection()\r\n self.select.set(widget.get(items[0]))\r\n\r\n def on_ok(self):\r\n self.destroy()\r\n\r\n def on_cancel(self):\r\n self.select.set(None)\r\n self.destroy()\r\n\r\nif __name__ == '__main__':\r\n\r\n from tkinter import Tk, StringVar\r\n root = Tk()\r\n select = StringVar()\r\n grids = {'Test1': [2, 'Test1', 'R', 'r', 'Y','y','RY,Ry,rY,ry'], 'Test2': [2, 'Test1', 'R', 'r', 'Y','y','RY,Ry,rY,ry']}\r\n prev_res = PrevResult(grids, select, root)\r\n prev_res.pack_slaves()\r\n prev_res.focus_get()\r\n prev_res.grab_set()\r\n prev_res.wait_window()\r\n print(select.get())\r\n root.mainloop()" }, { "alpha_fraction": 0.6788092255592346, "alphanum_fraction": 0.6820733547210693, "avg_line_length": 42.26011657714844, "blob_id": "866de80bd3d4bd3d1524201df79d8475650443a8", "content_id": "52476b221b897bdfc3aa2a69f261b0f07867292a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 9548, "license_type": "no_license", "max_line_length": 123, "num_lines": 173, "path": "/PyPennet/mainWindow.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Tk, Frame, Button, Menu, Toplevel\r\nfrom tkinter import BOTH, RIGHT, LEFT, RAISED, RIDGE, TOP, X\r\nfrom tkinter import messagebox\r\nfrom tkinter import filedialog\r\nfrom tkinter import messagebox as mb\r\nimport pickle\r\nimport webbrowser\r\nfrom PyPennet.gui.listwindow import ListWindow\r\nfrom PyPennet.gui.gridparams import GridParams\r\nfrom PyPennet.gui.baseFrame import BaseFrame\r\nfrom PyPennet.gui.showresult import ShowResult\r\nfrom PyPennet.gui.about_dlg import AboutDlg\r\nfrom PyPennet.utility import constants as const\r\n\r\n# Глобальные переменные\r\nroot = None # Главное окно программы\r\nlistbox = None # Listbox со списком открытых окон (Идентификатор и заголовок окна)\r\nshow_result = None # Контейнер резултатов обработки решетки\r\ndic_grids = {} # Словарь с параметрами созданных решеток. Ключ - заголовок окна\r\n\r\ndef makeMenu(root):\r\n main_menu = Menu(root)\r\n root.config(menu=main_menu)\r\n file_menu = Menu(main_menu, tearoff=0)\r\n file_menu.add_command(label='Сохранить в файл', command=save_to_file)\r\n file_menu.add_command(label='Загрузить из файла', command=from_file)\r\n file_menu.add_separator()\r\n file_menu.add_command(label='Закрыть', command=root.quit)\r\n main_menu.add_cascade(label='Файл', menu=file_menu)\r\n help_menu = Menu(main_menu, tearoff=0)\r\n help_menu.add_command(label='Справка', command=help_app)\r\n help_menu.add_command(label='О Программе', command=about_app)\r\n main_menu.add_cascade(label='Справка', menu=help_menu)\r\n\r\ndef save_to_file():\r\n global dic_grids\r\n fout = filedialog.asksaveasfilename()\r\n with open(fout, 'wb') as f:\r\n pickle.dump(dic_grids, f, 3)\r\n\r\ndef from_file():\r\n global dic_grids\r\n dic_grids.clear()\r\n fin = filedialog.askopenfilename()\r\n with open(fin, 'rb') as f:\r\n dic_grids = pickle.load(f, encoding='UTF-8')\r\n global listbox\r\n listbox.clear()\r\n\r\n for key in dic_grids.keys():\r\n listbox.insertData(key)\r\n\r\ndef help_app():\r\n webbrowser.open_new_tab(\"index.html\")\r\n\r\ndef about_app():\r\n global root\r\n dlg = AboutDlg(root)\r\n\r\n# При выборе записи в окне списка проверим сформирована ли уже решетка\r\n# Если сформирована - выводим в окна результата\r\n# Если нет - выводим сообщение о том, что надо сформировать решетку\r\ndef showSelected(selected):\r\n global dic_grids\r\n lst = dic_grids[selected]\r\n if len(lst[const.pos_data]) == 0:\r\n messagebox.showerror('Ошибка', 'Решетка ' + selected + ' еще не сформирована')\r\n return\r\n global show_result\r\n show_result.clearData()\r\n show_result.insertData(lst)\r\n\r\n# При закрытии окна удаляем все его следы\r\ndef closeGrid(string):\r\n global dic_grids\r\n del (dic_grids[string]) # Удаляем соответствующую запись из словаря\r\n global listbox\r\n listbox.removeData(string) # Удаляем запись из Listbox\r\n global root\r\n for item in root.winfo_children(): # Проходим по списку дочерних элементов главного окна\r\n cls = item.winfo_class() # Определяем класс текущего элемента\r\n if cls == 'Toplevel': # Если это окно верхнего уровня\r\n title = item.title() # Читаем его заголовок\r\n if title == string: # Если он равен искомому удаляем окно\r\n item.destroy()\r\n break\r\n global show_result\r\n show_result.clearData()\r\n\r\n# При построении решетки, результат построения заносим в соответствующий элемент словаря\r\ndef execGrid(title, data):\r\n global dic_grids\r\n dic_grids[title][4] = data\r\n\r\n# Заголовок окна заносим в список окон и его параметры в словарь lst_grids созданных решеток\r\ndef addNewGrid(root, listbox):\r\n listParams = [] # Список содержит строки: размер решетки; заголовок окна; заголовки колонок; заголовки строк\r\n global dic_grids\r\n gridParams = GridParams(listParams, dic_grids, root) # Вызываем диалоговое окно для получения параметров новой решетки\r\n gridParams.focus_set() # Устанавливаем фокус на окно\r\n gridParams.grab_set() # Удерживаем фокус на этом окне\r\n gridParams.wait_window() # Ждем завершения работы этого окна\r\n # Если после его отработки listParams не пустой создаем окно с решеткой и введенными праметорами\r\n if len(listParams) > 1:\r\n listParams.append('') # Добавляем пустую строку для результата\r\n result = listbox.insertData(listParams[const.pos_name]) # Вставим строку с заголовком окна в Listbox\r\n if not result:\r\n return\r\n window = Toplevel(root) # Создаем окно верхнего уровня для размещения в нем создаваемой решетки\r\n size = listParams[const.pos_size]\r\n # Создаем решетку и размещаем ее на окне верхнего уровня\r\n window.title(listParams[const.pos_name]) # устанавливаем заголовок окна\r\n baseFrame = BaseFrame(int(size), closeGrid, execGrid, window)\r\n if len(listParams[const.pos_columns]) > 0:\r\n # Если задали заголовки колонок, устанавливаем их в решетке\r\n baseFrame.fill_column_titles(listParams[const.pos_columns])\r\n if len(listParams[const.pos_rows]) > 0:\r\n baseFrame.fill_row_titles(listParams[const.pos_rows]) # Аналогично с заголовками строк\r\n dic_grids[listParams[const.pos_name]] = listParams # Заносим созданный класс с парамертами решетки в список\r\n\r\n# Удаляем выбранную в Listbox решетку\r\ndef deleteGrid(root, listbox):\r\n global show_result\r\n show_result.clearData()\r\n string = listbox.getSelectedItem() # Получаем строку выбранную в Listbox, это заголовок окна\r\n if string is not None:\r\n listbox.removeData(string) # Удаляем эту строку из Listbox\r\n global dic_grids\r\n del(dic_grids[string]) # Удаляем соответствующую запись из словаря\r\n for item in root.winfo_children(): # Проходим по списку дочерних элементов главного окна\r\n cls = item.winfo_class() # Определяем класс текущего элемента\r\n if cls == 'Toplevel': # Если это окно верхнего уровня\r\n title = item.title() # Читаем его заголовок\r\n if title == string: # Усли он равен искомому удаляем окно\r\n item.destroy()\r\n break\r\n\r\n\r\ndef main():\r\n global root\r\n root = Tk()\r\n #root.geometry(\"600x400\")\r\n root.title('Решетки Пеннета для законов Менделя')\r\n makeMenu(root)\r\n # Создаем Frame контейнер для Listbox\r\n frame_listbox = Frame(root, bd=5, relief=RIDGE)\r\n frame_listbox.pack(side=TOP, expand=True, fill=BOTH)\r\n global listbox\r\n listbox = ListWindow(showSelected, frame_listbox) # Создаем экземпляр класса ListWindow\r\n listbox.pack(side=TOP) # И размещаем его в контейнере\r\n # Создаем контейнер для кнопок \"Добавить\" и \"Удалить\"\r\n frame_btn = Frame(root, bd=5, relief=RIDGE)\r\n frame_btn.pack(side=TOP, expand=True, fill=X)\r\n btnAdd = Button(frame_btn, text='Добавить', bd=5, relief=RAISED, command=lambda: addNewGrid(root, listbox))\r\n btnAdd.pack(side=LEFT, padx=5, pady=5)\r\n btnDelete = Button(frame_btn, text='Удалить', bd=5, relief=RAISED, command=lambda: deleteGrid(root, listbox))\r\n btnDelete.pack(side=RIGHT)\r\n # Создаем экземпляр класса ShowResult и размещаем его в нашем окне\r\n global show_result\r\n show_result = ShowResult(root)\r\n show_result.pack(side=TOP)\r\n status_bar = Frame(root, bd=5, relief=RIDGE)\r\n status_bar.pack(side=TOP, expand=True, fill=X)\r\n btn_quit = Button(status_bar, text='Закрыть', command=root.quit, bd=5, relief=RAISED)\r\n btn_quit.pack(side=RIGHT, padx=5, pady=5)\r\n try:\r\n root.iconbitmap('app.ico')\r\n except:\r\n mb.showerror(\"Ошибка\", \"Отсутствует файл app.ico\")\r\n root.mainloop()\r\n\r\nif __name__ == '__main__':\r\n main()\r\n\r\n" }, { "alpha_fraction": 0.5792192816734314, "alphanum_fraction": 0.5838117003440857, "avg_line_length": 36.71111297607422, "blob_id": "7404e7cf7eab8215fe15e906a747801fc12acef3", "content_id": "dc2d2dc7d403cfeb1f6f448f20bdfe1580a01b46", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4211, "license_type": "no_license", "max_line_length": 117, "num_lines": 90, "path": "/PyPennet/gui/baseEntry.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import \r\nimport PyPennet.utility.util as my_util\r\nimport PyPennet.utility.constants as const\r\n\r\nclass BaseEntry(Entry):\r\n def __init__(self, w, parent=None):\r\n Entry.__init__(self, parent)\r\n self.menu = None\r\n self.initUI(w)\r\n\r\n def initUI(self, w):\r\n # Расчитываем размер символов полей ввода\r\n fsize = 22 - w\r\n if fsize < 10:\r\n fsize = 10\r\n strFont = 'Helvetica {} bold'.format(str(fsize))\r\n # Определяем ширину поля ввода, фонт и положение текста в нем\r\n self.config(width=w + 2, font=strFont, justify=CENTER, bd=5, relief=RIDGE)\r\n # Привязываем процедуру сортировки строки к событию ввода символов в поле ввода\r\n # Если мы введем аА, то получим Аа\r\n self.bind('<KeyRelease>', self.sortStr)\r\n # Создаем всплывающее меню\r\n self.menu = Menu(self, tearoff=0)\r\n self.menu.add_command(label='Цвет фона', command=lambda: self.setBackGround(None))\r\n self.menu.add_command(label='Цвет текста', command=lambda: self.setForeGround(None))\r\n self.bind('<Button-3>', self.showMenu)\r\n\r\n def showMenu(self, event):\r\n self.menu.post(event.x_root, event.y_root)\r\n\r\n def getText(self): # Получаем строку из поля ввода\r\n return self.get()\r\n\r\n def setText(self, string): # Заносим строку в поле ввода\r\n # Так как поля ввода для резултата имеют статус только для чтения, то их надо венуть в нормальное\r\n # состояние,записать текст, а затем опять вернуть в предыдущее состояние\r\n state = self['state'] # Определяем статус поля ввода\r\n if state == DISABLED:\r\n self['state'] = NORMAL\r\n if len(self.get()) > 0: # Усли в поле ввода есть текст - удаляем его\r\n self.delete(0, END)\r\n if len(string) > 0:\r\n self.insert(0, string) # Записываем текст в поле ввода\r\n if state == DISABLED: # Устанавливаем статус в предыдущее состояние\r\n self['state'] = DISABLED\r\n\r\n def setBackGround(self,color): # Устанавливаем цвет фона поля ввода\r\n if color is None:\r\n color = my_util.selectColor()\r\n state = self['state']\r\n if state == DISABLED:\r\n self['state'] = NORMAL\r\n self.config(bg=color)\r\n self['state'] = state\r\n\r\n def setForeGround(self, color): # Устанавливаем цвет текста поля ввода\r\n if color is None:\r\n color = my_util.selectColor()\r\n state = self['state']\r\n if state == DISABLED:\r\n self['state'] = NORMAL\r\n self.config(fg=color)\r\n self['state'] = state\r\n\r\n def sortStr(self, event): # Прцедура сортировки текста в поле ввода\r\n s = self.get()\r\n if len(s) > 0:\r\n if const.orig_char in s: # Так как символ $ используется в подпрограмме сортировки, то запретим его ввод\r\n i = s.index('$')\r\n self.setText(s[:i])\r\n else:\r\n ss = my_util.sortStr(s)\r\n self.setText(ss)\r\n\r\n def setReadOnly(self): # Установка поля ввода в состояние ТОЛЬКО ДЛЯ ЧТЕНИЯ\r\n state = self['state']\r\n if state == NORMAL:\r\n self['state'] = DISABLED\r\n\r\nif __name__ == '__main__':\r\n root = Tk()\r\n frame = Frame(root)\r\n frame.pack(side=TOP)\r\n be = BaseEntry(8, frame)\r\n be.setText('Test')\r\n be.setBackGround('blue')\r\n be.setForeGround('yellow')\r\n be.pack()\r\n print(be.getText())\r\n root.mainloop()\r\n" }, { "alpha_fraction": 0.5980665683746338, "alphanum_fraction": 0.6139634847640991, "avg_line_length": 48.05376434326172, "blob_id": "9bd1d6f895961b1ab1496acb0df075e43f8dbdbe", "content_id": "8583844747a62b7b39545e5d11f02a09ad70a2fb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5112, "license_type": "no_license", "max_line_length": 143, "num_lines": 93, "path": "/PyPennet/gui/showresult.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Frame, Label, Text, Scrollbar, Entry, Button\r\nfrom tkinter import END, TOP, WORD, RIDGE, BOTH, RIGHT, LEFT, X, Y, SUNKEN, RAISED\r\nfrom PyPennet.utility import util as my_util, constants as const\r\n\r\n# Здесь будем отображать результат подсчета генотипов и фенотипа\r\nclass ShowResult(Frame):\r\n def __init__(self, parent = None):\r\n Frame.__init__(self, parent)\r\n self.parent = parent\r\n self.text_width = 65\r\n self.initUI()\r\n\r\n def initUI(self):\r\n frameSource = Frame(self, bd = 5, relief = SUNKEN)\r\n frameSource.pack(side = TOP, expand = True, fill = BOTH)\r\n lblSource = Label(frameSource, text = 'Исходные данные', font = 'Courier 10 bold')\r\n lblSource.pack(side = TOP)\r\n self.source = Text(frameSource, height = 4, width = self.text_width, bd = 5, relief = RIDGE, font = 'Courier 10 bold', wrap = WORD)\r\n scrlSource = Scrollbar(frameSource, relief = SUNKEN)\r\n scrlSource['command'] = self.source.yview\r\n self.source['yscrollcommand'] = scrlSource.set\r\n scrlSource.pack(side = RIGHT, expand = True, fill = Y)\r\n self.source.pack(side=TOP, expand=True, fill = X)\r\n\r\n frameGenotype = Frame(self, bd = 5, relief = SUNKEN)\r\n frameGenotype.pack(side = TOP, expand = True, fill = BOTH)\r\n # Создаем метку заголовка текстового поля результата вычисления генотипов\r\n lblGenotype = Label(frameGenotype, text = 'Результат вычисления генотипов', font = 'Courier 10 bold')\r\n lblGenotype.pack(side = TOP)\r\n # Сщздаем текстовое поле для представления результат вычисления генотипов\r\n self.genotype = Text(frameGenotype, height = 4, width = self.text_width, bd = 5, relief = RIDGE, font = 'Courier 10 bold', wrap = WORD)\r\n # Создаем скролбар для скроллинга текста по горизонтали\r\n scrolbar = Scrollbar(frameGenotype, relief = SUNKEN)\r\n scrolbar['command'] = self.genotype.yview\r\n self.genotype['yscrollcommand'] = scrolbar.set\r\n scrolbar.pack(side = RIGHT, expand = True, fill = Y)\r\n self.genotype.pack(side=TOP, padx=5, pady=5, expand=True, fill = X)\r\n\r\n # Создаем контейнер для элементов вычисления фенотипа\r\n frame = Frame(self, bd = 5, relief = SUNKEN)\r\n frame.pack(side = TOP, padx = 5, pady = 5, expand = True, fill = BOTH)\r\n # Создаем метку заголовка раздела вычисления фенотипа\r\n lblPhenotype = Label(frame, font = 'Courier 10 bold', text = 'Вычисление фенотипов')\r\n lblPhenotype.pack(side = TOP)\r\n lblData = Label(frame, font = 'Courier 10 bold', text = 'Искомый фенотип')\r\n lblData.pack(side = LEFT, padx = 5, pady = 5)\r\n self.entrData = Entry(frame, bd = 5, relief = RIDGE, width = 10, font = 'Courier 10 bold')\r\n self.entrData.pack(side = LEFT, padx = 5, pady = 5)\r\n lblResult = Label(frame, text = 'Результат:', font = 'Courier 10 bold')\r\n lblResult.pack(side = LEFT, padx = 5, pady = 5)\r\n self.entrResult = Entry(frame, bd = 5, relief = RIDGE, width = 10, font = 'Courier 10 bold')\r\n self.entrResult.pack(side = LEFT, padx = 5, pady = 5)\r\n self.entrData.bind('<KeyPress>', self.clearResult)\r\n btnExec = Button(frame, text = 'Вычислить', bd = 5, relief = RAISED, command = self.execPhenotype)\r\n btnExec.pack(side = RIGHT, padx = 5, pady = 5)\r\n\r\n def clearResult(self, event):\r\n self.entrResult.delete('0', END)\r\n\r\n def execPhenotype(self):\r\n string = self.source.get('3.0', END).rstrip('\\n')\r\n ss = string.split(':')\r\n data = ss[1].strip()\r\n phenotype = self.entrData.get()\r\n result = my_util.calcPhenotype(data,phenotype)\r\n self.entrResult.insert(0, result)\r\n\r\n def clearData(self):\r\n self.source.delete('1.0', END)\r\n self.genotype.delete('1.0', END)\r\n self.entrData.delete('0', END)\r\n self.entrResult.delete('0', END)\r\n\r\n def insertData(self, my_grid):\r\n temp = 'Заголовки колонок: ' + my_grid[const.pos_columns] + '\\n'\r\n self.source.insert('1.0', temp)\r\n temp = 'Загловки строк: ' + my_grid[const.pos_rows] + '\\n'\r\n self.source.insert('2.0', temp)\r\n temp = 'Данные решетки: ' + my_grid[const.pos_data] + '\\n'\r\n self.source.insert('3.0', temp)\r\n if len(my_grid[const.pos_data]) > 1: #\r\n temp = my_util.calcGenotype(my_grid[const.pos_data])\r\n self.genotype.insert('1.0', temp)\r\n\r\n\r\nif __name__ == '__main__':\r\n from tkinter import Tk\r\n\r\n root = Tk()\r\n #root.geometry('600x400')\r\n showResult = ShowResult(root)\r\n showResult.pack()\r\n root.mainloop()\r\n" }, { "alpha_fraction": 0.5095201730728149, "alphanum_fraction": 0.5384615659713745, "avg_line_length": 32.605262756347656, "blob_id": "2fc82d7edde5db420f2597efa28c0c144c734244", "content_id": "3876fedeb3b8d3cc353858ec7749e01f1b6c1ed4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1358, "license_type": "no_license", "max_line_length": 94, "num_lines": 38, "path": "/PyPennet/gui/about_dlg.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Toplevel, Button, Label\r\nfrom PIL import Image, ImageTk\r\n\r\nclass AboutDlg():\r\n\r\n def __init__(self, parent=None):\r\n self.dlg = Toplevel(parent)\r\n self.dlg.pack_slaves()\r\n self.dlg.geometry('610x375')\r\n self.dlg.title = 'О Программе'\r\n self.dlg.resizable(False,False)\r\n self.initUI()\r\n\r\n def initUI(self):\r\n try:\r\n im = Image.open(\"about.jpg\")\r\n except FileNotFoundError:\r\n lbl = Label(self.dlg, text='Генетический калькулятор', font=(\"Arial\", 24, \"bold\"))\r\n lbl.place(x=80, y=20)\r\n lbl_name = Label(self.dlg, text='Автор: Никита Загородников', font=(\"Arial\", 18, \"bold\"))\r\n lbl_name.place(x=120, y=100)\r\n lbl_mail = Label(self.dlg, text='e-mail: [email protected]', font=(\"Arial\", 18, \"bold\"))\r\n lbl_mail.place(x=100, y=130)\r\n else:\r\n photo = ImageTk.PhotoImage(im)\r\n lbl = Label(self.dlg, image=photo)\r\n lbl.place(x=0, y=0, relheight=1, relwidth=1)\r\n lbl.image = photo\r\n finally:\r\n btn = Button(self.dlg, text='Закрыть', command=self.dlg.destroy)\r\n btn.place(x=280, y=330)\r\n\r\nif __name__ == '__main__':\r\n from tkinter import Tk\r\n\r\n root = Tk()\r\n dlg = AboutDlg(root)\r\n root.mainloop()" }, { "alpha_fraction": 0.6051831245422363, "alphanum_fraction": 0.6101056933403015, "avg_line_length": 39.87272644042969, "blob_id": "d96f24457fd8c9ed5c1a185301e81525be0720f0", "content_id": "1000aa6e8aa4bce8d66c4808aacc74e42ea475e9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7718, "license_type": "no_license", "max_line_length": 119, "num_lines": 165, "path": "/PyPennet/gui/gridparams.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Toplevel, Frame, Button, Label, Entry, Menu, StringVar\r\nfrom tkinter import END, LEFT, RIGHT, RAISED, RIDGE, TOP, BOTH, X\r\nimport PyPennet.utility.util as my_util\r\nimport PyPennet.gui.prev_perult as prev\r\n\r\n# Вспомогательный класс контейнер для элементов основоного окна диалога\r\nclass FrameRow(Frame):\r\n def __init__(self, title, t_size, e_size, parent=None):\r\n Frame.__init__(self, parent)\r\n self.parent = parent\r\n self.cur_font = 'Courier 10 bold'\r\n self.enter = None\r\n self.initUI(title, t_size, e_size)\r\n\r\n def initUI(self, title, t_size, e_size):\r\n frame = Frame(self.parent)\r\n frame.pack(side=TOP, expand=True, fill=X)\r\n sf = '{: <' + str(t_size) + '}' # Шаблон для выравнивания метки контейнера к одному размеру\r\n s_title = sf.format(title)\r\n lbl = Label(frame, text=s_title, font=self.cur_font)\r\n lbl.pack(side=LEFT, padx=5, pady=5)\r\n self.enter = Entry(frame, width=e_size, bd=5, relief=RIDGE, font=self.cur_font)\r\n self.enter.pack(side=LEFT, padx=5, pady=5)\r\n\r\n def get_entry(self):\r\n return self.enter\r\n\r\n# Класс диалога для определения параметов создаваемой решетки\r\n# В качестве параметров получает: Пустой список для заполнения параметрами и ссылку на владельца окна\r\nclass GridParams(Toplevel):\r\n def __init__(self, lst_params, grids, parent=None):\r\n Toplevel.__init__(self, parent)\r\n self.resizable(False,False)\r\n self.parent = parent\r\n self.title('Параметры новой решетки')\r\n self.lst_params = lst_params\r\n self.grids = grids\r\n self.initUI()\r\n\r\n def initUI(self):\r\n grid_menubar = Menu(self, tearoff=0)\r\n self.config(menu=grid_menubar)\r\n file_menu = Menu(grid_menubar, tearoff=0)\r\n file_menu.add_command(label='Очистить заголовоки колонок', command=self.clearColumns)\r\n file_menu.add_command(label='Очистить заголовки строк', command=self.clearRows)\r\n file_menu.add_separator()\r\n file_menu.add_command(label='Заполнить колоноки из файла', command=self.fillColumns)\r\n file_menu.add_command(label='Заполнить заголовки из файла', command=self.fillRows)\r\n file_menu.add_separator()\r\n file_menu.add_command(label='Колонки из предыдущего результата', command=self.column_prev)\r\n file_menu.add_command(label='Строки из предыдущего результата', command=self.row_prev)\r\n file_menu.add_separator()\r\n file_menu.add_command(label='Закрыть', command=self.onCancel)\r\n grid_menubar.add_cascade(label='Файл', menu=file_menu)\r\n\r\n frame_params = Frame(self, bd=5, relief=RIDGE)\r\n frame_params.pack(side=TOP, expand=True, fill=BOTH)\r\n t_size = 18 # Длина всех меток\r\n # Контьейнер для ввода размера решетки\r\n frm_size = FrameRow('Размер решетки', t_size, 4, frame_params)\r\n self.entr_size = frm_size.get_entry()\r\n # Контейнер для ввода заголовка окна\r\n frm_title = FrameRow('Заголовок окна', t_size, 50, frame_params)\r\n self.entr_name = frm_title.get_entry()\r\n # Контейнер для ввода заголовок колонок\r\n frm_column_title = FrameRow('Заголовки колонок', t_size, 50, frame_params)\r\n self.entr_title_column = frm_column_title.get_entry()\r\n # Контейнер для ввода заголовок строк\r\n frm_row_title = FrameRow('Заголовки строк', t_size, 50, frame_params)\r\n self.entr_title_row = frm_row_title = frm_row_title.get_entry()\r\n\r\n frame_buttons = Frame(self, bd=5, relief=RIDGE)\r\n frame_buttons.pack(side=TOP, expand=True, fill=X)\r\n btnOk = Button(frame_buttons, text='Создать ', bd=5, relief=RAISED, command=self.onOk)\r\n btnOk.pack(side=LEFT, padx=5, pady=5)\r\n btnCancel = Button(frame_buttons, text='Отменить', bd=5, relief=RAISED, command=self.onCancel)\r\n btnCancel.pack(side=RIGHT, padx=5, pady=5)\r\n\r\n def clearColumns(self):\r\n self.entr_title_column.delete('0', END)\r\n\r\n def clearRows(self):\r\n self.entr_title_row.delete('0', END)\r\n\r\n def fillColumns(self):\r\n string = my_util.getFromFile()\r\n if string is not None:\r\n self.entr_title_column.insert(END, string)\r\n\r\n def fillRows(self):\r\n string = my_util.getFromFile()\r\n if string is not None:\r\n self.entr_title_row.insert(END, string)\r\n\r\n def getEntryTitleColumns(self):\r\n return self.entr_title_column\r\n\r\n def getEntryTitleRows(self):\r\n return self.entr_title_row\r\n\r\n def column_prev(self):\r\n name = StringVar()\r\n prev_grid = prev.PrevResult(self.grids, name, self.parent)\r\n prev_grid.focus_set()\r\n prev_grid.grab_set()\r\n prev_grid.wait_window()\r\n if name is not None:\r\n lst = self.grids[name.get()]\r\n self.entr_title_column.insert(END, lst[4])\r\n\r\n def row_prev(self):\r\n name = StringVar()\r\n prev_grid = prev.PrevResult(self.grids, name, self.parent)\r\n prev_grid.focus_set()\r\n prev_grid.grab_set()\r\n prev_grid.wait_window()\r\n if name is not None:\r\n lst = self.grids[name.get()]\r\n self.entr_title_row.insert(END, lst[4])\r\n\r\n # Процедура считывания введенных параметров\r\n def onOk(self):\r\n # Должен быть введен либо размер решетки, либо заголовки колонок (и) или загололвки строк\r\n grid_size = self.entr_size.get().strip()\r\n lst_column = [s.strip() for s in self.entr_title_column.get().split(',')]\r\n len_column = len(lst_column)\r\n lst_row = [s.strip() for s in self.entr_title_row.get().split(',')]\r\n len_row = len(lst_row)\r\n if not grid_size.isdigit():\r\n if len_column > 1:\r\n grid_size = str(len_column)\r\n elif len_row > 1:\r\n grid_size = str(len_row)\r\n else:\r\n self.destroy()\r\n self.lst_params = []\r\n return\r\n self.lst_params.append(grid_size)\r\n title = self.entr_name.get().strip()\r\n if len(title) == 0:\r\n title = 'Решетка Пенета {} на {}'.format(grid_size, grid_size) # Иначе устанавливаем стандартный заголовок\r\n self.lst_params.append(title)\r\n self.lst_params.append(self.entr_title_column.get().strip())\r\n self.lst_params.append(self.entr_title_row.get().strip())\r\n self.destroy()\r\n\r\n def onCancel(self):\r\n self.destroy()\r\n\r\nif __name__ == '__main__':\r\n from tkinter import Tk\r\n\r\n def showDialog(lst):\r\n if len(lst) > 0:\r\n lst.clear()\r\n gridParams = GridParams(lst, root)\r\n gridParams.focus_set()\r\n gridParams.grab_set()\r\n gridParams.wait_window()\r\n print(lst)\r\n\r\n lst_params = []\r\n root = Tk()\r\n btn = Button(root, text='Show Dlg', command=lambda: showDialog(lst_params)).pack()\r\n root.mainloop()" }, { "alpha_fraction": 0.8214285969734192, "alphanum_fraction": 0.8214285969734192, "avg_line_length": 13, "blob_id": "8c7867b89b1c2a3211cb077ec0f81b0f6a63f8c9", "content_id": "9b0b4ca49f0cdbbaa2297cf4f0e80a6001818358", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 28, "license_type": "no_license", "max_line_length": 16, "num_lines": 2, "path": "/README.md", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "# PyPennet\nExtended project\n" }, { "alpha_fraction": 0.6582278609275818, "alphanum_fraction": 0.6582278609275818, "avg_line_length": 25, "blob_id": "7a8c131e8ae5ada38cedc93d995fa278d15bdc8c", "content_id": "0da5fe91a0f9fdc190850e716a2674fb49cb14c1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 79, "license_type": "no_license", "max_line_length": 31, "num_lines": 3, "path": "/pypennet.pyw", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from PyPennet import mainWindow\r\nif __name__ == '__main__':\r\n\tmainWindow.main()" }, { "alpha_fraction": 0.595580518245697, "alphanum_fraction": 0.6018940806388855, "avg_line_length": 34.11392593383789, "blob_id": "6d2a23dbc7050e7e1e6d864912d6a644eda3681d", "content_id": "94131c549bb8b8b54d6eafba18abfa58cff4ecf0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2929, "license_type": "no_license", "max_line_length": 104, "num_lines": 79, "path": "/PyPennet/gui/listwindow.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter import Frame, Listbox, Label, Scrollbar\r\nfrom tkinter import RIGHT, RIDGE, SUNKEN, TOP, BOTH, X, Y, SINGLE, END\r\nfrom tkinter import messagebox\r\n\r\nclass ListWindow(Frame):\r\n def __init__(self, showSelected, parent=None):\r\n Frame.__init__(self, parent)\r\n self.parent = parent\r\n self.showSelected = showSelected\r\n self.listBox = None\r\n self.initUI()\r\n\r\n def initUI(self):\r\n frame_lbl = Frame(self.parent, bd=5, relief=RIDGE)\r\n frame_lbl.pack(side=TOP, expand=True, fill=X)\r\n lbl_name = Label(frame_lbl, text='Созданные решетки')\r\n lbl_name.pack()\r\n\r\n frame_listbox = Frame(self.parent)\r\n frame_listbox.pack(side=TOP, expand=True, fill=BOTH)\r\n self.listBox = Listbox(frame_listbox, width=65, height=4, selectmode=SINGLE, bd=5, relief=RIDGE)\r\n self.listBox.bind('<<ListboxSelect>>', self.showSelect)\r\n scrbary = Scrollbar(frame_listbox, orient='vertical')\r\n scrbarx = Scrollbar(frame_listbox, orient='horizontal')\r\n scrbary.config(command=self.listBox.yview, relief=SUNKEN)\r\n scrbarx.config(command=self.listBox.xview, relief=SUNKEN)\r\n self.listBox.config(yscrollcommand=scrbary.set, xscrollcommand=scrbarx.set)\r\n scrbary.pack(side=RIGHT, fill=Y)\r\n scrbarx.pack(side='bottom', fill=X)\r\n self.listBox.pack(side=TOP, expand=True, fill=BOTH)\r\n\r\n def showSelect(self, event):\r\n item = self.getSelectedItem()\r\n self.showSelected(item)\r\n\r\n def getSelectedItem(self):\r\n items = self.listBox.curselection()\r\n item = self.listBox.get(items[0])\r\n return item\r\n\r\n def insertData(self, item):\r\n count = self.listBox.size()\r\n for i in range(count):\r\n s = self.listBox.get(i)\r\n if s == item:\r\n messagebox.showerror('Ошибка', 'Окно с таким заголовком уже есть в списке')\r\n return False\r\n self.listBox.insert(END, item)\r\n return True\r\n\r\n def removeData(self, title):\r\n count = self.listBox.size()\r\n for i in range(count):\r\n string = self.listBox.get(i)\r\n if string == title:\r\n self.listBox.delete(i)\r\n break\r\n\r\n def clear(self):\r\n count = self.listBox.size()\r\n self.listBox.delete(0, count - 1)\r\n\r\nif __name__ == '__main__':\r\n from tkinter import Tk\r\n\r\n def showSelected(selected):\r\n print(selected)\r\n\r\n root = Tk()\r\n root.title('Тест Listbox')\r\n frame = Frame(root)\r\n frame.pack(expand = True, fill = BOTH)\r\n listWindow = ListWindow(showSelected, frame)\r\n for i in range(20):\r\n string = 'Это окно №{:0>10}'.format(i)\r\n listWindow.insertData(string)\r\n string = 'Это окно №{:0>10}'.format(10)\r\n listWindow.removeData(string)\r\n root.mainloop()" }, { "alpha_fraction": 0.6820513010025024, "alphanum_fraction": 0.7076923251152039, "avg_line_length": 19.88888931274414, "blob_id": "3c8bab0b8beda22eb129864f6e4c6c80f12ae515", "content_id": "033b87ef0072bf004bf67cb8aa1a8ae66f2d0a76", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 282, "license_type": "no_license", "max_line_length": 53, "num_lines": 9, "path": "/PyPennet/utility/constants.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "# Позиции параметров в списке параметров решетки\r\npos_size = 0\r\npos_name = 1\r\npos_columns = 2\r\npos_rows = 3\r\npos_data = 4\r\n\r\n# Служебный символ для нестандартной сортировки строк\r\norig_char = '$'" }, { "alpha_fraction": 0.6058506369590759, "alphanum_fraction": 0.6104695796966553, "avg_line_length": 34.591548919677734, "blob_id": "b009e8313962c7e88d1d060f054b488da2ae6597", "content_id": "fd5b5d23bc1c1c8874b7c4eb9e114e3fade066d2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6495, "license_type": "no_license", "max_line_length": 117, "num_lines": 142, "path": "/PyPennet/utility/util.py", "repo_name": "NikitaZagor/PyPennet", "src_encoding": "UTF-8", "text": "from tkinter.colorchooser import askcolor\r\nfrom tkinter.filedialog import \r\nfrom PyPennet.utility import constants as const\r\n\r\n# Сортирует строку символов в алфавитном порядке независимо от регистра\r\ndef sortStr(string):\r\n source = list(string)\r\n source.sort()\r\n if source[0].islower():\r\n return ''.join(source)\r\n else:\r\n result = []\r\n length = len(source)\r\n for i in range(length):\r\n char = ''\r\n if source[i] != const.orig_char:\r\n result.append(source[i])\r\n char = source[i].upper()\r\n else:\r\n continue\r\n for j in range(i + 1, length):\r\n if source[j] != const.orig_char:\r\n temp = source[j].upper()\r\n if temp == char:\r\n result.append(source[j])\r\n source[j] = const.orig_char\r\n return ''.join(result)\r\n\r\n# Выбор цвета из стандартного диалога\r\ndef selectColor():\r\n color = askcolor()\r\n return color[1]\r\n\r\n# Подсчитываем генотипы. Так как один генотип может несколько раз повторятся в данном наборе,\r\n# то количество и процентное содержание данного генотипа мы сохраняем в словаре\r\n# где ключом будет данный генотип, а данные - кортежиз количества и процентного содержания\r\ndef calcGenotype(string):\r\n ss = string.split(',') # Разбиваем строку на элементы\r\n num = len(ss) # Общее количество элементов\r\n dict_count = {} # Словарь для генотипов\r\n for elm in ss:\r\n count = ss.count(elm) # Количество данного генотипа\r\n proc = (count/num) * 100 # Процентное содержание данного геноттиипа\r\n dict_count[elm] = (count, proc) # Заносим эти данные в словарь\r\n result = ''\r\n for key in dict_count.keys():\r\n count, proc = dict_count[key]\r\n temp = '{} {} {:.2f}%, '.format(key, count, proc)\r\n result += temp\r\n result = result.rstrip(' ')\r\n result = result.rstrip(',')\r\n return result\r\n\r\ndef newList(source, data):\r\n result = []\r\n for item in source:\r\n if data in item:\r\n result.append(item)\r\n return result\r\n\r\ndef calcPhenResult(num_base, num_find):\r\n proc = (num_find/num_base) * 100\r\n result = '{} {:.2f}%'.format(num_find, proc) # Формируем строку результата\r\n return result\r\n\r\n# Вычисляем данные по конкретному фенотипу\r\n# Используем то свойство нашей сортировки строк, что символы идут в алфавитном порядке независимо от регистра\r\n# В стандартоной сортировке сначала идут символы верхнего регистра, затем символы нижнего регистра\r\n# Например стандартная: ACacgg, наша сортировка: AaCcgg\r\ndef calcPhenotype(string, phenotype):\r\n main_lst = string.split(',') # Разбиваем входную строку данных на элементы\r\n num = len(main_lst) # Общее количество элементов\r\n simbols = list(phenotype) # Преобразуем входную строку наименования фенотипа в список символов\r\n set_one = set() # Здесь будет символы, которые встречаются в фенотипе только один раз\r\n dic_more = {} # Здесь будут символы входящие в имя феноипа более одного раза\r\n for ch in simbols: # Заполняем множество и словарь\r\n number = simbols.count(ch)\r\n if number == 1:\r\n set_one.add(ch)\r\n else:\r\n dic_more[ch] = number\r\n notfind = False\r\n for ch in set_one:\r\n main_lst = newList(main_lst, ch)\r\n if len(main_lst) == 0:\r\n notfind = True\r\n break\r\n if notfind:\r\n return '0 0%'\r\n lst_keys = dic_more.keys() # Получаем список двойных символов\r\n if len(lst_keys) == 0: # Это значит двойных и более символов нет\r\n length = len(main_lst)\r\n result = calcPhenResult(num, length)\r\n return result\r\n notfind = False\r\n for key in lst_keys:\r\n number = dic_more[key]\r\n s = key * number # Формируем строку из данного количества символов\r\n main_lst = newList(main_lst, s)\r\n if len(main_lst) == 0:\r\n notfind = True\r\n break\r\n if notfind:\r\n return '0 0%'\r\n else:\r\n length = len(main_lst)\r\n result = calcPhenResult(num, length)\r\n return result\r\n\r\n# Здесь мы должны расчитать и сформировать результат\r\n# Получаем список из трех строк: заглавной строки, заглавной колонки и строки данных матрицы\r\ndef calcResult(lst_string):\r\n genotype = calcGenotype(lst_string[2])\r\n result = 'Row:{}\\nColumn:{}\\nData:{}\\nGenotype:{}\\n'.format(lst_string[0], lst_string[1], lst_string[2],genotype)\r\n return result\r\n\r\n# Сохранение результата в файле\r\ndef saveToFile(lst_string):\r\n result = calcResult(lst_string)\r\n save = asksaveasfilename()\r\n file = open(save, 'w')\r\n file.write(result)\r\n file.close()\r\n\r\n# Получение предыдущего результата из файла\r\ndef getFromFile():\r\n op = askopenfilename()\r\n file = open(op, 'r')\r\n for line in file:\r\n if line.startswith('Data:'):\r\n s = line.split(':')\r\n return s[1].rstrip('\\n')\r\n return None\r\n\r\n# Формируем строку из списка Entries\r\ndef getStrFromEntries(entries):\r\n result =''\r\n for entr in entries:\r\n result += entr.get()\r\n result += ','\r\n result = result.rstrip(',')\r\n return result\r\n" } ]	12
dinhqbao/LearnDjango	https://github.com/dinhqbao/LearnDjango	e9f1e8c0f3fe1892eebd8743706acb9bd8706731	92ce42dec2b3f05d0d5cafc62c23e336423b2004	93f54d56c6c7d8ccf3bf142968bb1ce49aa570e2	refs/heads/master	2017-12-12T04:25:14.939329	2017-02-16T18:10:40	2017-02-16T18:10:40	77,937,632	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7470238208770752, "alphanum_fraction": 0.7470238208770752, "avg_line_length": 24.846153259277344, "blob_id": "7bc7f355cce2b62f84e7b334ad40911ff570620a", "content_id": "8c2e0fc1ee4be342fc3837723ef0380f6f302303", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 336, "license_type": "no_license", "max_line_length": 52, "num_lines": 13, "path": "/Todo/urls.py", "repo_name": "dinhqbao/LearnDjango", "src_encoding": "UTF-8", "text": "from django.conf.urls import url, include\nfrom rest_framework import routers\n\nfrom Todo import views\nfrom .views import TodoViewSet\n\nrouter = routers.DefaultRouter(trailing_slash=False)\nrouter.register(r'todoapi', TodoViewSet)\n\nurlpatterns = [\n url(r'^todo/', views.TodoList.as_view()),\n url(r'^todovs/', include(router.urls)),\n]\n" }, { "alpha_fraction": 0.6789772510528564, "alphanum_fraction": 0.6960227489471436, "avg_line_length": 24.214284896850586, "blob_id": "cd73045279e57784e86019114b39daba9c29d154", "content_id": "31c09441228d2a9b967aaa8af57d8d35aa2bc89c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 352, "license_type": "no_license", "max_line_length": 59, "num_lines": 14, "path": "/Todo/models.py", "repo_name": "dinhqbao/LearnDjango", "src_encoding": "UTF-8", "text": "from __future__ import unicode_literals\nfrom django.db import models\n\n\nclass Todo(models.Model):\n title = models.CharField(max_length=50)\n content = models.CharField(max_length=1000, blank=True)\n completed = models.BooleanField(default=False)\n\n\nclass User(models.Model):\n\n def __str__(self):\n return self.title + ' _ ' + self.content" }, { "alpha_fraction": 0.5060155987739563, "alphanum_fraction": 0.5272470116615295, "avg_line_length": 29.717391967773438, "blob_id": "722d4ae29a0a1b466044886f27b63a9ca49437b9", "content_id": "8fab87ed955d8f8c1dfee31bd9c93f8248ca9885", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2826, "license_type": "no_license", "max_line_length": 112, "num_lines": 92, "path": "/Todo/views.py", "repo_name": "dinhqbao/LearnDjango", "src_encoding": "UTF-8", "text": "from rest_framework import status\nfrom rest_framework import viewsets\nfrom rest_framework.response import Response\nfrom rest_framework.views import APIView\n\nfrom .models import Todo\nfrom .serializers import TodoSerializer\n\n\nclass TodoList(APIView):\n\n def get(self, request):\n \"\"\"\n User active code\n ---\n serializer: Todo.serializers.TodoSerializer\n\n responseMessages:\n - code: 200\n message: Success\n - code: 400\n message: '{\"error\" : 400 , \"message\" : \"Not Valid\", \"data\" : {}}'\n - code: 403\n message: '{\"error\" : 403 , \"message\" : \"Insufficient rights to call this procedure\", \"data\" : {}}'\n - code: 404\n message: '{\"error\" : 404 , \"message\" : \"Not Found\", \"data\" : {}}'\n - code: 500\n message: '{\"error\" : 500 , \"message\" : \"Internal Error\", \"data\" : {}}'\n\n consumes:\n - application/json\n\n produces:\n - application/json\n \"\"\"\n todo_list = Todo.objects.all()\n serialized = TodoSerializer(todo_list, many=True)\n return Response(serialized.data)\n\n def post(self, request):\n \"\"\"\n Add new Todo\n ---\n serializer: Todo.serializers.TodoSerializer\n parameters:\n\n - name: title\n description: Title of Todo\n required: true\n type: string\n paramType: form\n\n - name: content\n description: Content of Tdo\n required: true\n type: string\n paramType: form\n\n - name: completed\n description: Is todo completed?\n required: true\n type: boolean\n paramType: form\n\n responseMessages:\n - code: 200\n message: Success\n - code: 400\n message: '{\"error\" : 400 , \"message\" : \"Not Valid\", \"data\" : {}}'\n - code: 403\n message: '{\"error\" : 403 , \"message\" : \"Insufficient rights to call this procedure\", \"data\" : {}}'\n - code: 404\n message: '{\"error\" : 404 , \"message\" : \"Not Found\", \"data\" : {}}'\n - code: 500\n message: '{\"error\" : 500 , \"message\" : \"Internal Error\", \"data\" : {}}'\n\n consumes:\n - application/json\n\n produces:\n - application/json\n \"\"\"\n serializer = TodoSerializer(data=request.data)\n if serializer.is_valid():\n serializer.save()\n return Response(serializer.data, status=status.HTTP_201_CREATED)\n return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)\n\n\nclass TodoViewSet(viewsets.ModelViewSet):\n queryset = Todo.objects.all()\n serializer_class = TodoSerializer\n" } ]	3
kuzmich/blogosphere	https://github.com/kuzmich/blogosphere	f7ef00ab275a5f43cd338093c515b5da17897595	789424559920051a2aeeace3386a29cec0e99c9e	687bdc7f1bad0004d237c4ea0ff313e3e36b7d0c	refs/heads/master	2020-04-04T00:21:30.820172	2014-11-23T04:32:19	2014-11-23T04:32:19	27,021,500	1	0	null	null	null	null	null	[ { "alpha_fraction": 0.7465564608573914, "alphanum_fraction": 0.7465564608573914, "avg_line_length": 32, "blob_id": "807b58e379d03b6b13c22e3c83e9083d434323ec", "content_id": "c919b30a8ecdbf17e6cd33f19cc7ff5e57274682", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 363, "license_type": "no_license", "max_line_length": 109, "num_lines": 11, "path": "/blog/views.py", "repo_name": "kuzmich/blogosphere", "src_encoding": "UTF-8", "text": "from django.contrib.auth.decorators import login_required\nfrom django.shortcuts import render\n\nfrom .models import Post\n\n\n@login_required\ndef personal_feed(request):\n user = request.user\n posts = Post.objects.filter(blog__in=user.subscriptions.all()).exclude(read_by=user).order_by('-created')\n return render(request, 'blog/feed.html', {'posts': posts})\n" }, { "alpha_fraction": 0.5764758586883545, "alphanum_fraction": 0.5822898149490356, "avg_line_length": 34.4603157043457, "blob_id": "5d934414a2a5e4dfdbd60788ccc41e28604c97b0", "content_id": "c0c010ac539ffeb82995ec9797bf545fe788e90d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2366, "license_type": "no_license", "max_line_length": 85, "num_lines": 63, "path": "/blog/models.py", "repo_name": "kuzmich/blogosphere", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\nfrom django.db import models\nfrom django.db.models.signals import m2m_changed, post_save\nfrom django.dispatch import receiver\n\n\nclass Blog(models.Model):\n user = models.ForeignKey('auth.User', verbose_name='пользователь')\n name = models.CharField('название', max_length=150)\n subscribers = models.ManyToManyField('auth.User',\n related_name='subscriptions',\n verbose_name='подписчики',\n blank=True)\n\n class Meta:\n verbose_name = 'блог'\n verbose_name_plural = 'блоги'\n\n def __str__(self):\n return '{0.name} ({0.user})'.format(self)\n\nclass Post(models.Model):\n blog = models.ForeignKey(Blog, related_name='posts', verbose_name='блог')\n title = models.CharField('заголовок', max_length=100)\n text = models.TextField('содержание')\n created = models.DateTimeField('создан', auto_now_add=True)\n read_by = models.ManyToManyField('auth.User',\n related_name='read_posts',\n verbose_name='прочитано пользователями',\n blank=True)\n\n class Meta:\n verbose_name = 'публикация'\n verbose_name_plural = 'публикации'\n\n def __str__(self):\n return '{0.title} ({0.blog})'.format(self)\n\n\nSubscriptions = Blog.subscribers.through\nPostReadBy = Post.read_by.through\n\n\n@receiver(m2m_changed, sender=Subscriptions)\ndef subscribers_changed(sender, kwargs):\n if kwargs['action'] == 'post_remove':\n users = kwargs['pk_set']\n blog = kwargs['instance']\n PostReadBy.objects.filter(post__in=blog.posts.all(), user__in=users).delete()\n\n@receiver(post_save, sender=Post)\ndef new_post_created(sender, kwargs):\n from django.core.mail import send_mail\n\n if kwargs['created']:\n post = kwargs['instance']\n blog = post.blog\n\n for subscriber in blog.subscribers.exclude(email=''):\n send_mail('В блоге {} новая публикая: {}'.format(blog, post.title),\n post.text,\n from_email='[email protected]',\n recipient_list=[subscriber.email])\n\n\n" }, { "alpha_fraction": 0.6990881562232971, "alphanum_fraction": 0.6990881562232971, "avg_line_length": 22.5, "blob_id": "409ea5d8a694b145e4ff5324c9d32d3da043dfe3", "content_id": "3da167b53134721efbf7e378244bde73bb3c4706", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 329, "license_type": "no_license", "max_line_length": 55, "num_lines": 14, "path": "/blog/admin.py", "repo_name": "kuzmich/blogosphere", "src_encoding": "UTF-8", "text": "from django.contrib import admin\nfrom .models import \n\n\nclass BlogAdmin(admin.ModelAdmin):\n list_display = ['name', 'user']\n\nclass PostAdmin(admin.ModelAdmin):\n list_display = ['blog', 'title', 'text', 'created']\n list_filter = ['blog__user']\n\n\nadmin.site.register(Blog, BlogAdmin)\nadmin.site.register(Post, PostAdmin)\n" }, { "alpha_fraction": 0.7241379022598267, "alphanum_fraction": 0.7379310131072998, "avg_line_length": 23.08333396911621, "blob_id": "d2672aafaf67167c01265b1853c580294c5b82cb", "content_id": "22a443d150e75ec692388a1bc32bb8549f3b3ecf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 290, "license_type": "no_license", "max_line_length": 74, "num_lines": 12, "path": "/README.md", "repo_name": "kuzmich/blogosphere", "src_encoding": "UTF-8", "text": "blogosphere\n===========\n\nRequirements:\n Python 3.4\n* Django 1.7\n\nBasic functionality:\n* You can subscribe to any blog\n* You can mark a post as read\n* You can view your personal feed of posts from subscribed blogs\n* When new post is created, every subscriber will get a email notification\n\n" }, { "alpha_fraction": 0.6510764956474304, "alphanum_fraction": 0.6577579975128174, "avg_line_length": 36.16666793823242, "blob_id": "5711c0b2e7c2b560820046c8e6a512b56c37c62d", "content_id": "6fd7c0f70856887182424d2fc85216946725785d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1367, "license_type": "no_license", "max_line_length": 91, "num_lines": 36, "path": "/blog/tests.py", "repo_name": "kuzmich/blogosphere", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\nfrom django.test import TestCase\nfrom .models import *\n\n\nclass BlogTestCase(TestCase):\n def setUp(self):\n from django.contrib.auth.models import User\n\n self.john = User.objects.create(username='john', email='[email protected]')\n self.george = User.objects.create(username='george', email='[email protected]')\n self.fan = User.objects.create(username='fan', email='[email protected]')\n\n self.jblog = Blog.objects.create(user=self.john)\n\n def test_read_marks_deletion(self):\n self.jblog.subscribers.add(self.fan, self.george)\n\n post = self.jblog.posts.create(title='Post 1', text='Всем привет!')\n post.read_by.add(self.fan, self.george)\n self.assertEqual(post.read_by.count(), 2)\n\n self.jblog.subscribers.remove(self.george)\n self.assertEqual(post.read_by.count(), 1)\n\n self.assertEqual(PostReadBy.objects.filter(post=post, user=self.george).count(), 0)\n self.assertEqual(PostReadBy.objects.filter(post=post, user=self.fan).count(), 1)\n\n def test_send_emails_to_subscribers(self):\n from django.core import mail\n\n self.assertEqual(len(mail.outbox), 0)\n\n self.jblog.subscribers.add(self.fan, self.george)\n post = self.jblog.posts.create(title='Post 1', text='Всем привет!')\n self.assertEqual(len(mail.outbox), 2)\n \n" } ]	5
angzhang1/SimpleHtmlScraper	https://github.com/angzhang1/SimpleHtmlScraper	967dc769e95fd47016348b2d05e801262cdc740c	7b96db97f9bcf4fd05e6e4067b6ba47207eeabab	dbde8450195b1588f8e9b8968554e721bb917f7d	refs/heads/master	2020-05-17T16:54:07.228011	2019-04-28T00:26:07	2019-04-28T00:26:07	183,832,228	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.8333333134651184, "alphanum_fraction": 0.8333333134651184, "avg_line_length": 29, "blob_id": "30d3003fe8a03a3a1e427cf002c8c50779910346", "content_id": "00267d355f535053c31302daaff1a9e08ea98ea3", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 60, "license_type": "permissive", "max_line_length": 39, "num_lines": 2, "path": "/README.md", "repo_name": "angzhang1/SimpleHtmlScraper", "src_encoding": "UTF-8", "text": "# SimpleHtmlScraper\nParse data from tables in Html webpages\n" }, { "alpha_fraction": 0.5830721259117126, "alphanum_fraction": 0.5961337685585022, "avg_line_length": 27.567163467407227, "blob_id": "747aa0220e76a289536c43c89fe9de234a4b2deb", "content_id": "1afcdf73a75fd251b7fcf35423a01ac5cba45058", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1914, "license_type": "permissive", "max_line_length": 115, "num_lines": 67, "path": "/get_commodity_price.py", "repo_name": "angzhang1/SimpleHtmlScraper", "src_encoding": "UTF-8", "text": "\"\"\"Get commodity price's mean and variance from local csv data in a date range\n\nCurrently, the program supports gold and silver commodities, corresponding to gold.csv and silver.csv, respectively\nThe data in csv files have Date and Price colums\n\nExample:\n $ python get_commodity_price.py 2019-04-01 2019-04-26\n\n\"\"\"\n\nimport sys\n\nimport pandas as pd\n\n\ndef read_csv(csv_file):\n return pd.read_csv(csv_file)\n\n\ndef main(start, end, commodity):\n ''' According to start and end dates, read the corresponding csv data and calculate the mean and variance\n '''\n\n if commodity.lower() == 'gold':\n df = read_csv('gold.csv')\n elif commodity.lower() == 'silver':\n df = read_csv('silver.csv')\n else:\n df = pd.DataFrame()\n raise Exception('Commodity can only be gold or silver')\n\n df['Date'] = pd.to_datetime(df['Date'])\n\n try:\n # Replace comma in the numbers\n df['Price'] = pd.to_numeric(df['Price'].str.replace(',', ''))\n except AttributeError:\n df['Price'] = pd.to_numeric(df['Price'])\n\n try:\n mask = (df['Date'] > start) & (df['Date'] <= end)\n data_in_range = df.loc[mask]\n # check if data is empty\n if not data_in_range.empty:\n mean = data_in_range['Price'].mean()\n var = data_in_range['Price'].var()\n\n # print the result\n print commodity, \"{0:.2f}\".format(mean), \"{0:.2f}\".format(var)\n else:\n print('No data in the specified date range')\n\n except TypeError as error:\n print(error)\n print('The Date format is incorrect!')\n\n\nif __name__ == '__main__':\n if len(sys.argv) != 4:\n print(\"usage: python get_commodity_price.py start_date end_date commodity\")\n exit(-1)\n else:\n start_date = sys.argv[1]\n end_date = sys.argv[2]\n commodity = sys.argv[3]\n\n main(start_date, end_date, commodity)\n" }, { "alpha_fraction": 0.6077858805656433, "alphanum_fraction": 0.6214112043380737, "avg_line_length": 31.109375, "blob_id": "773da808764dcc4e008462b38f9290cf1bf760f1", "content_id": "5a7c715c30a04d333f2d391254ecfb67f809d14a", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2055, "license_type": "permissive", "max_line_length": 146, "num_lines": 64, "path": "/html_scraper.py", "repo_name": "angzhang1/SimpleHtmlScraper", "src_encoding": "UTF-8", "text": "from lxml import html\nimport requests\nimport pandas as pd\n\n\nclass HtmlScraper:\n \"\"\"Scrape data (table) from HTML pages\n\n You may specify the table id to retrive specific table's data in the webpage\n\n \"\"\"\n\n def parse_url(self, url, headers):\n\n page = requests.get(url, headers=headers)\n return html.fromstring(page.content)\n\n @staticmethod\n def clean_text(elt):\n return elt.text_content().replace(u'\\xa0', u'')\n\n def parse_html_table(self, root, table_id):\n ''' parse the html table according to the id\n\n @return the DataFrame from the table including header and data \n '''\n\n # Get the table from the root according to the id\n table = root.get_element_by_id(table_id)\n # Retrieve the header information\n table_header = table.xpath('.//th')\n header = [self.clean_text(th) for th in table_header]\n data = [[self.clean_text(td) for td in tr.xpath('.//td')]\n for tr in table.xpath('.//tr')]\n data = [row for row in data if len(row) == len(header)]\n return pd.DataFrame(data, columns=header)\n\n # print(header)\n\n def save_to_csv(self, data, columns, filename):\n data.to_csv(path_or_buf=filename, columns=columns,\n index=False)\n\n\ndef retrieve_data_to_csv(url, filename, cols):\n ''' Scrape data and save to csv files\n '''\n headers = {\n 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36'}\n sc = HtmlScraper()\n root = sc.parse_url(url, headers)\n df = sc.parse_html_table(root, \"curr_table\")\n\n with open(filename, 'wb') as csvfile:\n sc.save_to_csv(df, cols, csvfile)\n\n\nif __name__ == \"__main__\":\n cols = ['Date', 'Price']\n url = 'https://www.investing.com/commodities/gold-historical-data'\n retrieve_data_to_csv(url, \"gold.csv\", cols)\n\n url = 'https://www.investing.com/commodities/silver-historical-data'\n retrieve_data_to_csv(url, \"silver.csv\", cols)\n" } ]	3
khanhha/human_estimation	https://github.com/khanhha/human_estimation	29746ce5560cea639483da291751bc8749bc0da7	02ad1972a511325ecf28007fa884f1d2845bbaa9	f1be86f2d2c6fe3d0b589b7391d2549ddd973863	refs/heads/master	2018-12-19T19:04:04.035462	2018-12-19T09:20:37	2018-12-19T09:20:37	149,005,215	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5445864796638489, "alphanum_fraction": 0.5686089992523193, "avg_line_length": 38.82035827636719, "blob_id": "d58d224c747fdc3226a115da54864b2d9c71c969", "content_id": "16620e8d44475b136638399bc8755d838e6fc9d9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 26600, "license_type": "no_license", "max_line_length": 176, "num_lines": 668, "path": "/src/caesar_slc_fix_bust.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport matplotlib.pyplot as plt\nfrom pathlib import Path\nimport pickle\nimport argparse\nimport os\nimport sys\nfrom shapely.geometry import LinearRing, LineString, Point, MultiPoint\nimport shapely.geometry as geo\nimport shapely.ops as ops\nimport math\nimport shutil\nimport src.util as util\nfrom numpy.linalg import norm\nfrom copy import copy\n\ndef roll_contour(contour, shift):\n X = np.roll(contour[:,0], shift)\n Y = np.roll(contour[:,1], shift)\n contour = np.concatenate([X.reshape(-1, 1), Y.reshape(-1, 1)], axis=1)\n return contour\n\ndef preprocess_contour(contour, resolution = 400):\n X, Y = util.smooth_contour(contour[:, 0], contour[:, 1], sigma=2)\n X, Y = util.resample_contour(X, Y, resolution)\n\n ymax_idx = np.argmax(Y)\n\n X = np.roll(X, -ymax_idx)\n Y = np.roll(Y, -ymax_idx)\n\n #clockwise order\n p0 = np.array([X[0], Y[0]])\n pnext = np.array([X[10], Y[10]])\n if (pnext - p0).dot(np.array([1.0, 0])) < 0:\n X = X[::-1]\n Y = Y[::-1]\n # plt.clf()\n # plt.axes().set_aspect(1.0)\n # plt.plot(X, Y, '-b')\n # plt.plot(X[0], Y[0], '+r', ms = 20)\n # plt.plot(X[10], Y[10], '+g', ms = 20)\n # plt.show()\n contour = np.concatenate([X.reshape(-1, 1), Y.reshape(-1, 1)], axis=1)\n\n return contour\n\ndef arm_inside_contour(contour_str, p):\n if p[0] > 0.0:\n p1 = p + 2.0np.array([1, 0])\n else:\n p1 = p + 2.0np.array([-1, 0])\n\n isct_p = LineString([p, p1]).intersection(contour_str)\n if isct_p.type == 'Point':\n return True\n else:\n return False\n\ndef extract_contour_chain(contour, x_0, x_1):\n n_point = contour.shape[0]\n chains = []\n chain = []\n for i in range(n_point):\n if x_0 < contour[i,0] and contour[i,0] < x_1:\n chain.append(i)\n else:\n if len(chain) > 0:\n chains.append(chain)\n chain = []\n return chains\n\ndef closest_point_idx(contour, point):\n diffs = contour - point\n dists = np.sum(np.square(diffs), axis=1)\n return np.argmin(dists)\n\ndef remove_arm_from_armscye_slice(contour, sup_points, debug_path = None):\n contour = preprocess_contour(contour, resolution = 100)\n\n arm_pnt_negx = np.array(sup_points['Armscye_NegX'][:2])\n arm_pnt_posx = np.array(sup_points['Armscye_PosX'][:2])\n\n if debug_path is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(arm_pnt_negx[0], arm_pnt_negx[1], '+r')\n plt.plot(arm_pnt_posx[0], arm_pnt_posx[1], '+r')\n plt.plot([arm_pnt_negx[0], arm_pnt_posx[0]], [arm_pnt_negx[1], arm_pnt_posx[1]], '-r')\n\n hor_ax = util.normalize(arm_pnt_posx - arm_pnt_negx)\n angle = np.arccos(np.dot(hor_ax, np.array([1.0, 0.0])))\n if hor_ax[1] > 0.0:\n angle = -angle\n cos_a = np.cos(angle)\n sin_a = np.sin(angle)\n\n rot_mat = np.array([[cos_a, -sin_a], [sin_a, cos_a]])\n rot_center = 0.5(arm_pnt_posx+arm_pnt_negx)\n contour = np.dot(rot_mat, (contour - rot_center).T).T + rot_center\n\n arm_pnt_negx = (np.dot(rot_mat, (arm_pnt_negx-rot_center).reshape(2,1)).T + rot_center).flatten()\n arm_pnt_posx = (np.dot(rot_mat, (arm_pnt_posx-rot_center).reshape(2,1)).T + rot_center).flatten()\n\n if debug_path is not None:\n plt.plot(contour[:,0], contour[:,1], '-b')\n plt.plot([arm_pnt_negx[0], arm_pnt_posx[0]], [arm_pnt_negx[1], arm_pnt_posx[1]], '-b')\n\n fixed_left = False\n fixed_right = False\n has_left_arm = False\n has_right_arm = False\n\n contour_str = LinearRing([contour[i,:] for i in range(contour.shape[0])])\n if arm_inside_contour(contour_str, arm_pnt_negx):\n has_right_arm = True\n\n isct_pnt = LineString([arm_pnt_negx, arm_pnt_negx + (arm_pnt_negx-arm_pnt_posx)]).intersection(contour_str)\n isct_pnt = np.array(isct_pnt.coords[:])\n\n half_arm_len = norm(isct_pnt-arm_pnt_negx)\n x_0 = arm_pnt_negx[0] - 0.2half_arm_len\n x_1 = arm_pnt_negx[0] + 0.2half_arm_len\n\n chains = extract_contour_chain(contour, x_0, x_1)\n if len(chains) < 2:\n fixed_right = False\n else:\n fixed_right = True\n chain_lens = -np.array([len(chains[i]) for i in range(len(chains))])\n chain_idxs = np.argsort(chain_lens)[:2]\n chains = [chains[idx] for idx in chain_idxs]\n\n if fixed_right:\n chain_str_0 = MultiPoint([contour[i,:] for i in chains[0]])\n chain_str_1 = MultiPoint([contour[i,:] for i in chains[1]])\n points = ops.nearest_points(chain_str_0, chain_str_1)\n\n pair_idx0 = closest_point_idx(contour, np.array(points[0].coords[:]))\n pair_idx1 = closest_point_idx(contour, np.array(points[1].coords[:]))\n\n if contour[pair_idx0, 1] > contour[pair_idx1, 1]:\n pair_idx0, pair_idx1 = pair_idx1, pair_idx0\n\n shift = 1\n pair_idx0 -= shift\n pair_idx1 += shift\n\n if debug_path is not None:\n plt.plot(contour[pair_idx0, 0], contour[pair_idx0, 1], '+r', ms=15)\n plt.plot(contour[pair_idx1, 0], contour[pair_idx1, 1], '+r', ms=15)\n\n for i in chains[0]:\n plt.plot(contour[i, 0], contour[i, 1],'+r', ms=5)\n\n for i in chains[1]:\n plt.plot(contour[i, 0], contour[i, 1], '+b', ms=5)\n\n contour = np.concatenate([contour[:pair_idx0, :], arm_pnt_negx.reshape(1,2), contour[pair_idx1:, :]], axis = 0)\n\n if arm_inside_contour(contour_str, arm_pnt_posx):\n has_left_arm = True\n\n isct_pnt = LineString([arm_pnt_posx, arm_pnt_posx + (arm_pnt_posx-arm_pnt_negx)]).intersection(contour_str)\n isct_pnt = np.array(isct_pnt.coords[:])\n half_arm_len = norm(isct_pnt-arm_pnt_posx)\n\n x_0 = arm_pnt_posx[0] - 0.2half_arm_len\n x_1 = arm_pnt_posx[0] + 0.2half_arm_len\n chains = extract_contour_chain(contour, x_0, x_1)\n if len(chains) < 2:\n fixed_left = False\n else:\n chain_lens = -np.array([len(chains[i]) for i in range(len(chains))])\n chain_idxs = np.argsort(chain_lens)[:2]\n chains = [chains[idx] for idx in chain_idxs]\n fixed_left = True\n\n if fixed_left:\n chain_str_0 = MultiPoint([contour[i,:] for i in chains[0]])\n chain_str_1 = MultiPoint([contour[i,:] for i in chains[1]])\n points = ops.nearest_points(chain_str_0, chain_str_1)\n\n pair_idx0 = closest_point_idx(contour, np.array(points[0].coords[:]))\n pair_idx1 = closest_point_idx(contour, np.array(points[1].coords[:]))\n\n shift = 1\n if contour[pair_idx0, 1] > contour[pair_idx1, 1]:\n pair_idx0, pair_idx1 = pair_idx1, pair_idx0\n\n pair_idx0 += shift\n pair_idx1 -= shift\n\n if debug_path is not None:\n plt.plot(contour[pair_idx0, 0], contour[pair_idx0, 1], '+r', ms=15)\n plt.plot(contour[pair_idx1, 0], contour[pair_idx1, 1], '+r', ms=15)\n\n for i in chains[0]:\n plt.plot(contour[i, 0], contour[i, 1],'+r', ms=5)\n\n for i in chains[1]:\n plt.plot(contour[i, 0], contour[i, 1], '+b', ms=5)\n\n contour = np.concatenate([contour[:pair_idx1, :], arm_pnt_posx.reshape(1,2), contour[pair_idx0:, :]], axis = 0)\n\n if fixed_left or fixed_right:\n X, Y = util.smooth_contour(contour[:, 0], contour[:, 1], sigma=1)\n X, Y = util.resample_contour(X, Y, 150)\n contour = np.concatenate([X.reshape(-1, 1), Y.reshape(-1, 1)], axis=1)\n\n if debug_path is not None:\n plt.plot(contour[:,0], contour[:,1], '-r')\n if fixed_left or fixed_right:\n plt.savefig(debug_path)\n\n return contour, has_left_arm, has_right_arm, fixed_left, fixed_right\n\n\n#contour: clockwise order\n#landmarks: contain points inside armt parts\ndef remove_arm_from_under_bust_slice(contour, arm_pnt_negx, arm_pnt_posx, debug_path = None):\n\n contour = preprocess_contour(contour)\n\n hor_dir = arm_pnt_posx - arm_pnt_negx\n\n if debug_path is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(contour[:,0], contour[:,1], '-b')\n plt.plot(arm_pnt_negx[0], arm_pnt_negx[1], '+r')\n plt.plot(arm_pnt_posx[0], arm_pnt_posx[1], '+r')\n\n fixed_left = False\n fixed_right = False\n has_left_arm = False\n has_right_arm = False\n\n contour_str = LinearRing([contour[i,:] for i in range(contour.shape[0])])\n if arm_inside_contour(contour_str, arm_pnt_negx):\n has_right_arm = True\n\n isct_pnt = LineString([arm_pnt_negx, arm_pnt_negx + (arm_pnt_negx-arm_pnt_posx)]).intersection(contour_str)\n isct_pnt = np.array(isct_pnt.coords[:])\n\n half_arm_len = norm(isct_pnt-arm_pnt_negx)\n x_0 = arm_pnt_negx[0] + 0.5half_arm_len\n x_1 = arm_pnt_negx[0] + 2.0half_arm_len\n\n chains = extract_contour_chain(contour, x_0, x_1)\n if len(chains) < 2:\n fixed_right = False\n else:\n fixed_right = True\n chain_lens = -np.array([len(chains[i]) for i in range(len(chains))])\n chain_idxs = np.argsort(chain_lens)[:2]\n chains = [chains[idx] for idx in chain_idxs]\n\n if fixed_right:\n chain_str_0 = MultiPoint([contour[i,:] for i in chains[0]])\n chain_str_1 = MultiPoint([contour[i,:] for i in chains[1]])\n points = ops.nearest_points(chain_str_0, chain_str_1)\n\n pair_idx0 = closest_point_idx(contour, np.array(points[0].coords[:]))\n pair_idx1 = closest_point_idx(contour, np.array(points[1].coords[:]))\n\n if contour[pair_idx0, 1] > contour[pair_idx1, 1]:\n pair_idx0, pair_idx1 = pair_idx1, pair_idx0\n\n shift = 1\n pair_idx0 -= shift\n pair_idx1 += shift\n\n if debug_path is not None:\n plt.plot(contour[pair_idx0, 0], contour[pair_idx0, 1], '+r', ms=15)\n plt.plot(contour[pair_idx1, 0], contour[pair_idx1, 1], '+r', ms=15)\n\n for i in chains[0]:\n plt.plot(contour[i, 0], contour[i, 1],'+r', ms=5)\n\n for i in chains[1]:\n plt.plot(contour[i, 0], contour[i, 1], '+b', ms=5)\n\n contour = np.concatenate([contour[:pair_idx0, :], contour[pair_idx1:, :]], axis = 0)\n\n if arm_inside_contour(contour_str, arm_pnt_posx):\n has_left_arm = True\n\n isct_pnt = LineString([arm_pnt_posx, arm_pnt_posx + (arm_pnt_posx-arm_pnt_negx)]).intersection(contour_str)\n isct_pnt = np.array(isct_pnt.coords[:])\n half_arm_len = norm(isct_pnt-arm_pnt_posx)\n\n x_0 = arm_pnt_posx[0] - 2.0half_arm_len\n x_1 = arm_pnt_posx[0] - 0.5half_arm_len\n chains = extract_contour_chain(contour, x_0, x_1)\n if len(chains) < 2:\n fixed_left = False\n else:\n chain_lens = -np.array([len(chains[i]) for i in range(len(chains))])\n chain_idxs = np.argsort(chain_lens)[:2]\n chains = [chains[idx] for idx in chain_idxs]\n fixed_left = True\n\n if fixed_left:\n chain_str_0 = MultiPoint([contour[i,:] for i in chains[0]])\n chain_str_1 = MultiPoint([contour[i,:] for i in chains[1]])\n points = ops.nearest_points(chain_str_0, chain_str_1)\n\n pair_idx0 = closest_point_idx(contour, np.array(points[0].coords[:]))\n pair_idx1 = closest_point_idx(contour, np.array(points[1].coords[:]))\n\n shift = 1\n if contour[pair_idx0, 1] > contour[pair_idx1, 1]:\n pair_idx0, pair_idx1 = pair_idx1, pair_idx0\n\n pair_idx0 += shift\n pair_idx1 -= shift\n\n if debug_path is not None:\n plt.plot(contour[pair_idx0, 0], contour[pair_idx0, 1], '+r', ms=15)\n plt.plot(contour[pair_idx1, 0], contour[pair_idx1, 1], '+r', ms=15)\n\n for i in chains[0]:\n plt.plot(contour[i, 0], contour[i, 1],'+r', ms=5)\n\n for i in chains[1]:\n plt.plot(contour[i, 0], contour[i, 1], '+b', ms=5)\n\n contour = np.concatenate([contour[:pair_idx1, :], contour[pair_idx0:, :]], axis = 0)\n\n if fixed_left or fixed_right:\n X, Y = util.smooth_contour(contour[:, 0], contour[:, 1], sigma=1)\n X, Y = util.resample_contour(X, Y, 150)\n contour = np.concatenate([X.reshape(-1, 1), Y.reshape(-1, 1)], axis=1)\n\n if debug_path is not None:\n plt.plot(contour[:,0], contour[:,1], '-r')\n if fixed_left or fixed_right:\n plt.savefig(debug_path)\n\n return contour, has_left_arm, has_right_arm, fixed_left, fixed_right\n\n#contour should be already pre-processed\ndef fix_bust_height(bust_contour, sup_points, ld_points, armscye_contour, debug_path = None):\n bust_contour = preprocess_contour(bust_contour)\n armscye_contour = preprocess_contour(armscye_contour)\n\n arm_pnt_negx = np.array(sup_points['Bust_Arm_NegX'][:2])\n arm_pnt_posx = np.array(sup_points['Bust_Arm_PosX'][:2])\n\n n_bust_contour = bust_contour.shape[0]\n\n mid_bust = ld_points[14][:2]\n neg_bust = ld_points[12][:2]\n pos_bust = ld_points[13][:2]\n\n if debug_path is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n\n #align the input contours by rotating its arm-arm axis to match to x axis\n hor_ax = util.normalize(arm_pnt_posx - arm_pnt_negx)\n angle = np.arccos(np.dot(hor_ax, np.array([1.0, 0.0])))\n if hor_ax[1] > 0.0:\n angle = -angle\n cos_a = np.cos(angle)\n sin_a = np.sin(angle)\n\n rot_mat = np.array([[cos_a, -sin_a], [sin_a, cos_a]])\n rot_center = mid_bust\n bust_contour = np.dot(rot_mat, (bust_contour - rot_center).T).T + rot_center\n\n armscye_contour = np.dot(rot_mat, (armscye_contour - rot_center).T).T + rot_center\n neg_bust = (np.dot(rot_mat, (neg_bust-rot_center).reshape(2,1)).T + rot_center).flatten()\n pos_bust = (np.dot(rot_mat, (pos_bust-rot_center).reshape(2,1)).T + rot_center).flatten()\n\n arm_pnt_negx = (np.dot(rot_mat, (arm_pnt_negx-rot_center).reshape(2,1)).T + rot_center).flatten()\n arm_pnt_posx = (np.dot(rot_mat, (arm_pnt_posx-rot_center).reshape(2,1)).T + rot_center).flatten()\n\n if debug_path is not None:\n plt.plot(armscye_contour[:,0], armscye_contour[:,1], '-c')\n plt.plot([arm_pnt_negx[0], arm_pnt_posx[0]], [arm_pnt_negx[1], arm_pnt_posx[1]], '-r')\n plt.plot(arm_pnt_negx[0], arm_pnt_negx[1], '+r')\n plt.plot(arm_pnt_posx[0], arm_pnt_posx[1], '+r')\n pass\n\n hor_ax = np.array([1.0, 0.0])\n ver_ax = np.array([0.0, 1.0])\n\n #assume that the bust base line is equavalent to the armscye contour (a bit higher than the bust contour)\n #we can't take the under bust contour as the bust base line because some people have big belly, which means their udner bust contour is even larger than their bust contour.\n armscye_contour_str = LineString([armscye_contour[i,:] for i in range(armscye_contour.shape[0])])\n bust_base_target = LineString([mid_bust-10ver_ax, mid_bust + 10ver_ax]).intersection(armscye_contour_str)\n bust_base_target = util.closest_point_points(mid_bust, bust_base_target)\n\n left_side_ids = []\n for idx in range(0, n_bust_contour):\n p = bust_contour[idx, :]\n if p[1] < bust_base_target[1] and p[0] <= bust_base_target[0]:\n left_side_ids.append(idx)\n #plt.plot(p[0], p[1], '+r', ms=5)\n\n right_side_ids = []\n for idx in range(0, n_bust_contour):\n p = bust_contour[idx, :]\n if p[1] < bust_base_target[1] and p[0] >= bust_base_target[0]:\n right_side_ids.append(idx)\n #plt.plot(p[0], p[1], '+r', ms=5)\n\n if len(left_side_ids) > 0 and len(right_side_ids) > 0:\n left_tip_idx = np.argmin(bust_contour[left_side_ids, 1])\n right_tip_idx = np.argmin(bust_contour[right_side_ids, 1])\n left_tip_idx = left_side_ids[left_tip_idx]\n right_tip_idx = right_side_ids[right_tip_idx]\n\n left_side_ids_1 = [idx for idx in left_side_ids if bust_contour[idx, 0] <= bust_contour[left_tip_idx, 0]]\n right_side_ids_1 = [idx for idx in right_side_ids if bust_contour[idx, 0] >= bust_contour[right_tip_idx, 0]]\n\n take_left = False\n tip_idx = right_tip_idx\n side_point_idxs = right_side_ids_1\n if bust_contour[left_tip_idx, 1] < bust_contour[right_tip_idx, 1]:\n tip_idx = left_tip_idx\n side_point_idxs = left_side_ids_1\n take_left = True\n\n side_bust_tip_point = bust_contour[tip_idx, :]\n\n side_mirror_points = []\n for idx in side_point_idxs:\n p = bust_contour[idx, :]\n p_mirror = util.mirror_point_through_axis(side_bust_tip_point, ver_ax, p)\n side_mirror_points.append(p_mirror)\n\n #scale mirrored points\n side_mirror_points = np.array(side_mirror_points)\n #plt.plot(side_mirror_points[:,0], side_mirror_points[:,1], '+r')\n x_range = np.max(side_mirror_points[:,0]) - np.min(side_mirror_points[:,0])\n target_range = abs(side_bust_tip_point[0]- bust_base_target[0])\n x_scale = target_range/x_range\n side_mirror_points[:, 0] = (side_mirror_points[:, 0] - side_bust_tip_point[0]) x_scale + side_bust_tip_point[0]\n #plt.plot(side_mirror_points[:,0], side_mirror_points[:,1], '+b')\n\n tmp_idxs = []\n for idx in range(n_bust_contour):\n if bust_contour[idx,0] >= bust_base_target[0] and bust_contour[idx,1] >0:\n tmp_idxs.append(idx)\n\n start_idx = np.argmin(bust_contour[tmp_idxs,0])\n start_idx = tmp_idxs[start_idx]\n bust_contour = roll_contour(bust_contour, -start_idx)\n mirror_centroid = bust_base_target\n if take_left:\n half_contour = bust_contour[left_tip_idx-start_idx:n_bust_contour, :]\n half_contour = np.concatenate([side_mirror_points[::-1, :], half_contour])\n half_contour = half_contour - mirror_centroid\n\n #mirror\n other_half_contour = copy(half_contour)\n other_half_contour[:,0] = -other_half_contour[:,0]\n\n final_contour = np.concatenate([other_half_contour[::-1,:], half_contour])\n else:\n half_contour = bust_contour[0:right_tip_idx-start_idx, :]\n half_contour = np.concatenate([half_contour, side_mirror_points[::-1, :]])\n half_contour = half_contour - mirror_centroid\n\n other_half_contour = copy(half_contour)\n other_half_contour[:,0] = -other_half_contour[:,0]\n\n final_contour = np.concatenate([half_contour, other_half_contour[::-1,:]])\n\n final_contour[:,0], final_contour[:,1] = util.smooth_contour(final_contour[:,0], final_contour[:,1], sigma=2)\n final_contour += mirror_centroid\n\n if debug_path is not None:\n plt.plot(mirror_centroid[0], mirror_centroid[1], '+b', ms=20)\n plt.plot(side_bust_tip_point[0], side_bust_tip_point[1], '+b', ms=20)\n plt.plot(final_contour[:, 0], final_contour[:, 1], '-r', label='fixed bust')\n plt.plot(bust_base_target[0], bust_base_target[1], '+r', ms=20)\n plt.plot(bust_contour[:, 0], bust_contour[:, 1], '-b', label='input bust')\n plt.legend(loc='upper right')\n plt.savefig(debug_path)\n\n return final_contour, True\n\n else:\n if debug_path is not None:\n plt.plot(bust_base_target[0], bust_base_target[1], '+r', ms=20)\n plt.plot(bust_contour[:, 0], bust_contour[:, 1], '-b', label='input bust')\n plt.legend(loc='upper right')\n plt.savefig(debug_path)\n\n return bust_contour, False\n\n#contour: clockwise order\n#landmarks: contain points inside armt parts\ndef remove_arm_from_bust_slice(contour, sup_points, debug_path = None):\n contour = preprocess_contour(contour)\n\n arm_pnt_negx = np.array(sup_points['Bust_Arm_NegX'][:2])\n arm_pnt_posx = np.array(sup_points['Bust_Arm_PosX'][:2])\n\n if debug_path is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(contour[:,0], contour[:,1], '-b')\n plt.plot(arm_pnt_negx[0], arm_pnt_negx[1], '+r')\n plt.plot(arm_pnt_posx[0], arm_pnt_posx[1], '+r')\n\n fixed_left = False\n fixed_right = False\n has_left_arm = False\n has_right_arm = False\n\n contour_str = LinearRing([contour[i,:] for i in range(contour.shape[0])])\n if arm_inside_contour(contour_str, arm_pnt_negx):\n has_right_arm = True\n\n isct_pnt = LineString([arm_pnt_negx, arm_pnt_negx + (arm_pnt_negx-arm_pnt_posx)]).intersection(contour_str)\n isct_pnt = np.array(isct_pnt.coords[:])\n\n half_arm_len = norm(isct_pnt-arm_pnt_negx)\n x_0 = arm_pnt_negx[0] + 1.1half_arm_len\n x_1 = arm_pnt_negx[0] + 2.0half_arm_len\n\n chains = extract_contour_chain(contour, x_0, x_1)\n if len(chains) < 2:\n fixed_right = False\n else:\n fixed_right = True\n chain_lens = -np.array([len(chains[i]) for i in range(len(chains))])\n chain_idxs = np.argsort(chain_lens)[:2]\n chains = [chains[idx] for idx in chain_idxs]\n\n if fixed_right:\n chain_str_0 = MultiPoint([contour[i,:] for i in chains[0]])\n chain_str_1 = MultiPoint([contour[i,:] for i in chains[1]])\n points = ops.nearest_points(chain_str_0, chain_str_1)\n\n pair_idx0 = closest_point_idx(contour, np.array(points[0].coords[:]))\n pair_idx1 = closest_point_idx(contour, np.array(points[1].coords[:]))\n\n if contour[pair_idx0, 1] > contour[pair_idx1, 1]:\n pair_idx0, pair_idx1 = pair_idx1, pair_idx0\n\n shift = 1\n pair_idx0 -= shift\n pair_idx1 += shift\n\n if debug_path is not None:\n plt.plot(contour[pair_idx0, 0], contour[pair_idx0, 1], '+r', ms=15)\n plt.plot(contour[pair_idx1, 0], contour[pair_idx1, 1], '+r', ms=15)\n\n for i in chains[0]:\n plt.plot(contour[i, 0], contour[i, 1],'+r', ms=5)\n\n for i in chains[1]:\n plt.plot(contour[i, 0], contour[i, 1], '+b', ms=5)\n\n contour = np.concatenate([contour[:pair_idx0, :], contour[pair_idx1:, :]], axis = 0)\n\n if arm_inside_contour(contour_str, arm_pnt_posx):\n has_left_arm = True\n\n isct_pnt = LineString([arm_pnt_posx, arm_pnt_posx + (arm_pnt_posx-arm_pnt_negx)]).intersection(contour_str)\n isct_pnt = np.array(isct_pnt.coords[:])\n half_arm_len = norm(isct_pnt-arm_pnt_posx)\n\n x_0 = arm_pnt_posx[0] - 2.0half_arm_len\n x_1 = arm_pnt_posx[0] - 1.1half_arm_len\n chains = extract_contour_chain(contour, x_0, x_1)\n if len(chains) < 2:\n fixed_left = False\n else:\n chain_lens = -np.array([len(chains[i]) for i in range(len(chains))])\n chain_idxs = np.argsort(chain_lens)[:2]\n chains = [chains[idx] for idx in chain_idxs]\n fixed_left = True\n\n if fixed_left:\n chain_str_0 = MultiPoint([contour[i,:] for i in chains[0]])\n chain_str_1 = MultiPoint([contour[i,:] for i in chains[1]])\n points = ops.nearest_points(chain_str_0, chain_str_1)\n\n pair_idx0 = closest_point_idx(contour, np.array(points[0].coords[:]))\n pair_idx1 = closest_point_idx(contour, np.array(points[1].coords[:]))\n\n shift = 1\n if contour[pair_idx0, 1] > contour[pair_idx1, 1]:\n pair_idx0, pair_idx1 = pair_idx1, pair_idx0\n\n pair_idx0 += shift\n pair_idx1 -= shift\n\n if debug_path is not None:\n plt.plot(contour[pair_idx0, 0], contour[pair_idx0, 1], '+r', ms=15)\n plt.plot(contour[pair_idx1, 0], contour[pair_idx1, 1], '+r', ms=15)\n\n for i in chains[0]:\n plt.plot(contour[i, 0], contour[i, 1],'+r', ms=5)\n\n for i in chains[1]:\n plt.plot(contour[i, 0], contour[i, 1], '+b', ms=5)\n\n contour = np.concatenate([contour[:pair_idx1, :], contour[pair_idx0:, :]], axis = 0)\n\n if fixed_left or fixed_right:\n X, Y = util.smooth_contour(contour[:, 0], contour[:, 1], sigma=1)\n X, Y = util.resample_contour(X, Y, 150)\n contour = np.concatenate([X.reshape(-1, 1), Y.reshape(-1, 1)], axis=1)\n\n if debug_path is not None:\n plt.plot(contour[:,0], contour[:,1], '-r')\n if fixed_left or fixed_right:\n plt.savefig(debug_path)\n\n return contour, has_left_arm, has_right_arm, fixed_left, fixed_right\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--input\", required=True, help=\"\")\n ap.add_argument(\"-l\", \"--landmark\", required=True, help=\"\")\n ap.add_argument(\"-o\", \"--output\", required=True, help=\"\")\n args = vars(ap.parse_args())\n IN_DIR = args['input']\n LD_DIR = args['landmark']\n OUT_DIR = args['output']\n\n DEBUG_DIR = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_usce/debug/'\n\n DIR_NO_ARM_CUT_OFF = f'{DEBUG_DIR}/bust_arm_cut_off/'\n shutil.rmtree(DIR_NO_ARM_CUT_OFF)\n os.makedirs(DIR_NO_ARM_CUT_OFF)\n\n os.makedirs(OUT_DIR, exist_ok=True)\n\n all_paths = [path for path in Path(IN_DIR).glob('.')]\n n_error_contour = 0\n n_fixed_contour = 0\n for i, path in enumerate(all_paths):\n\n print(f'{i}, {path.stem}')\n\n with open(path, 'rb') as file:\n slc_contours = pickle.load(file)\n lens = np.array([len(contour) for contour in slc_contours])\n contour = slc_contours[np.argmax(lens)]\n contour = np.array(contour)\n contour = contour[:, :2]\n\n ld_path = f'{LD_DIR}/{path.stem}.pkl'\n assert os.path.exists(ld_path)\n\n with open(ld_path, 'rb') as file:\n landmarks = pickle.load(file)\n\n debug_path = f'{DIR_NO_ARM_CUT_OFF}{path.stem}.png'\n contour, has_left, has_right, fixed_left, fixed_right = remove_arm_from_bust_slice(contour, landmarks, debug_path=debug_path)\n if has_left or has_right:\n n_error_contour += 1\n if not (has_left != fixed_left) or not (has_right != fixed_right):\n n_fixed_contour += 1\n\n #with open(f'{OUT_DIR}/{path.stem}.pkl', 'wb') as out_file:\n # pickle.dump(out_file, contour)\n\n print(f'n error contour = {n_error_contour}, n fixed contour = {n_fixed_contour}')\n" }, { "alpha_fraction": 0.5046824216842651, "alphanum_fraction": 0.5418014526367188, "avg_line_length": 31.453039169311523, "blob_id": "bf68bc2fe937ee4ba564e632466688e6e2326dce", "content_id": "c766cebd718b9b6abfefbc9fb6ae5fe4d5fd8bd9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5873, "license_type": "no_license", "max_line_length": 160, "num_lines": 181, "path": "/src/dataset_viz.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport matplotlib.pylab as plt\nimport argparse\nfrom pathlib import Path\nimport pickle\nfrom scipy.fftpack import ifft\n\ndef is_leg_contour(name):\n leg_names = ['UnderCrotch', 'Aux_Knee_UnderCrotch_0', 'Aux_Knee_UnderCrotch_1', 'Aux_Knee_UnderCrotch_2', 'Aux_Knee_UnderCrotch_3', 'Knee', 'Calf', 'Ankle']\n if name in leg_names:\n return True\n else:\n return False\n\ndef isect_line_line(p1, p2, p3, p4):\n a = (p1[0]-p3[0])(p3[1]-p4[1]) - (p1[1]-p3[1])(p3[0]-p4[0])\n b = (p1[0]-p2[0])(p3[1]-p4[1]) - (p1[1]-p2[1])(p3[0]-p4[0])\n t = a/b\n p = np.array([p1[0]+t(p2[0]-p1[0]), p1[1]+t(p2[1]-p1[1])])\n return p\n\ndef reconstruct_contour_fourier(fourier):\n n = len(fourier)\n fouriers = []\n fouriers.append(np.complex(0.0, 0.0))\n for i in range(0, n, 2):\n real = fourier[i]\n img = fourier[i+1]\n fouriers.append(np.complex(real, img))\n\n cpl_contour = ifft(fouriers)\n X = np.real(cpl_contour)\n Y = np.imag(cpl_contour)\n return np.concatenate([X.reshape(1, -1), Y.reshape(1, -1)], axis=0)\n\ndef reconstruct_leg_slice_contour(feature, D, W):\n p0 = np.array([Dfeature[-2]feature[-1], 0])\n n_points = len(feature) -1\n prev_p = p0\n points = []\n points.append(prev_p)\n\n angle_step = 2.0np.pi / float(n_points)\n for i in range(1, n_points):\n angle = float(i)angle_step\n\n l0_p0 = prev_p\n l0_p1 = prev_p + np.array([1.0, feature[i-1]])\n\n l1_p0 = np.array([0.0, 0.0])\n l1_p1 = np.array([np.cos(angle), np.sin(angle)])\n\n isct = isect_line_line(l0_p0, l0_p1, l1_p0, l1_p1)\n\n points.append(isct)\n\n prev_p = isct\n\n X = np.array([p[0] for p in points])\n Y = np.array([p[1] for p in points])\n\n return np.vstack([X, Y])\n\ndef reconstruct_torso_slice_contour(feature, D, W, mirror = False):\n p0 = np.array([Dfeature[-2]feature[-1], 0])\n n_points = len(feature) - 2\n half_idx = int(np.ceil(n_points / 2.0))\n assert half_idx == 4 or half_idx == 5\n\n prev_p = p0\n\n points = []\n points.append(prev_p)\n\n angle_step = np.pi / float(n_points)\n for i in range(1, n_points+1):\n angle = float(i)angle_step\n #TODO\n # if i == 4:\n # x, y = 0.0, W/2.0\n # else:\n # x = (prev_p[1] - feature[i] prev_p[0]) / (np.tan(angle) - feature[i])\n # y = np.tan(angle) * x\n #prev_p = np.array([x,y])\n #points.append(prev_p)\n\n # test\n l0_p0 = prev_p\n l0_p1 = prev_p + np.array([1.0, feature[i-1]])\n\n l1_p0 = np.array([0.0, 0.0])\n if i == half_idx:\n l1_p1 = np.array([0, W/2])\n elif i < half_idx:\n l1_p1 = np.array([1.0, np.tan(angle)])\n else:\n l1_p1 = np.array([-1.0, -np.tan(angle)])\n\n isct = isect_line_line(l0_p0, l0_p1, l1_p0, l1_p1)\n\n points.append(isct)\n\n prev_p = isct\n\n #print(isct[0] - x, isct[1] - y)\n #plt.plot([l0_p0[0], l0_p1[0]], [l0_p0[1], l0_p1[1]], 'r-')\n #plt.plot([l1_p0[0], l1_p1[0]], [l1_p0[1], l1_p1[1]], 'b-')\n #plt.plot(isct[0], isct[1], 'b+')\n\n X = np.array([p[0] for p in points])\n Y = np.array([p[1] for p in points])\n\n if mirror == True:\n X_mirror = X[1:-1][::-1]\n Y_mirror = -Y[1:-1][::-1]\n\n X = np.concatenate([X,X_mirror], axis=0)\n Y = np.concatenate([Y,Y_mirror], axis=0)\n\n return np.vstack([X, Y])\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--IN_DIR\", required=True, help=\"dataset input directory\")\n ap.add_argument(\"-s\", \"--SLC_TYPE\", required=True, help=\"slice type\")\n\n args = vars(ap.parse_args())\n IN_DIR = args['IN_DIR']\n slc_id = args['SLC_TYPE']\n\n PRE_DIR = f'{IN_DIR}/caesar_obj_slices/{slc_id}'\n POST_DIR = f'{IN_DIR}/caesar_obj_slices_post_process/{slc_id}'\n FONT_SIZE = 7\n\n all_names = [path.name for path in Path(PRE_DIR).glob('.pkl')]\n name = all_names[np.random.choice(len(all_names))]\n for name in all_names:\n with open(f'{PRE_DIR}/{name}', 'rb') as file:\n all_contours = pickle.load(file)\n\n with open(f'{POST_DIR}/{name}', 'rb') as file:\n data = pickle.load(file)\n W = data['W']\n D = data['D']\n F = data['feature'] #radial code as in the paper \"\"\n Fr = data['fourier'] #another contour code: truncated fourier.\n post_contour = data['cnt']\n\n if is_leg_contour(slc_id):\n f_contour = reconstruct_leg_slice_contour(F, D, W)\n else:\n f_contour = reconstruct_torso_slice_contour(F, D, W, mirror=True)\n\n fr_contour = reconstruct_contour_fourier(Fr)\n\n fig = plt.figure()\n fig.suptitle(f'{slc_id} - {name[:-4]}')\n ax = fig.add_subplot(2,2,1, aspect=1.0)\n for contour in all_contours:\n contour = np.array(contour)\n ax.plot(contour[:,0], contour[:,1], '-b')\n ax.set_title('origin contours cut \\nfrom mesh', fontsize=FONT_SIZE)\n ax.set_yticklabels([]), ax.set_xticklabels([])\n\n ax = fig.add_subplot(2,2,2, aspect=1.0)\n ax.plot(post_contour[0,:], post_contour[1,:], '-b')\n ax.set_title('post processed contour', fontsize=FONT_SIZE)\n ax.set_yticklabels([]), ax.set_xticklabels([])\n\n ax = fig.add_subplot(2,2,3, aspect=1.0)\n ax.plot(f_contour[0,:], f_contour[1,:], '-b')\n ax.set_title('contour reconstructed \\n from radial code', fontsize=FONT_SIZE)\n ax.set_yticklabels([]), ax.set_xticklabels([])\n\n ax = fig.add_subplot(2,2,4, aspect=1.0)\n ax.plot(fr_contour[0,:], fr_contour[1,:], '-b')\n ax.set_title('contour reconstructed \\n from fourier descriptor', fontsize=FONT_SIZE)\n ax.set_yticklabels([]), ax.set_xticklabels([])\n\n plt.show()\n plt.close('all')" }, { "alpha_fraction": 0.565666675567627, "alphanum_fraction": 0.5926666855812073, "avg_line_length": 40.65277862548828, "blob_id": "7635da5a82e83e8ef58a6b84bff8531f3db653e7", "content_id": "51cc6bb9a617a2ef6c1786157b00f8487b4387a6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3000, "license_type": "no_license", "max_line_length": 101, "num_lines": 72, "path": "/src/shape_key_analyze.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import cv2 as cv\nimport numpy as np\nimport os\nimport matplotlib.pyplot as plt\nfrom pathlib import Path\n\n\ndef pre_process(DIR_IN, DIR_OUT):\n\n for img_path in Path(DIR_OUT).glob(\".\"):\n os.remove(img_path)\n\n for img_path in Path(DIR_IN).glob(\".\"):\n img = cv.imread(str(img_path), cv.IMREAD_GRAYSCALE)\n sil_mask = img > 0\n sil = (sil_mask 255).astype(np.uint8)\n sil = cv.morphologyEx(sil, cv.MORPH_OPEN, cv.getStructuringElement(cv.MORPH_RECT, (5,5)))\n cv.imwrite(f'{DIR_OUT}{img_path.name}', sil)\n\ndef viz_shapekey_silhouette_dif(DIR_IN, DIR_OUT):\n for img_path in Path(DIR_OUT).glob(\".\"):\n os.remove(img_path)\n shapekey_paths = {}\n for img_path in Path(DIR_IN).glob(\".png\"):\n name_id = str(img_path.name).split('_')[0]\n if name_id not in shapekey_paths:\n shapekey_paths[name_id] = []\n shapekey_paths[name_id].append(img_path)\n\n sil_area = -1\n\n for id, paths in shapekey_paths.items():\n for img_path in paths:\n if 'front_0' in img_path.name:\n img_front_0 = cv.imread(str(img_path), cv.IMREAD_GRAYSCALE)\n elif 'front_1' in img_path.name:\n img_front_1 = cv.imread(str(img_path), cv.IMREAD_GRAYSCALE)\n elif 'side_0' in img_path.name:\n img_side_0 = cv.imread(str(img_path), cv.IMREAD_GRAYSCALE)\n elif 'side_1' in img_path.name:\n img_side_1 = cv.imread(str(img_path), cv.IMREAD_GRAYSCALE)\n else:\n print('error: unexpected filename')\n\n if sil_area == -1:\n sil_area = float(np.sum((img_front_0>0)[:]))\n\n dif_front = cv.bitwise_xor(img_front_0, img_front_1)\n dif_side = cv.bitwise_xor(img_side_0, img_side_1)\n\n front_change_area = np.sum((dif_front > 0)[:])\n side_change_area = np.sum((dif_side > 0)[:])\n\n if float(front_change_area)/sil_area > 0.005 or float(side_change_area)/sil_area > 0.005:\n dif_front = np.dstack([dif_front, np.zeros_like(dif_front), np.zeros_like(dif_front)])\n dif_side = np.dstack([dif_side, np.zeros_like(dif_side), np.zeros_like(dif_side)])\n\n plt.clf()\n plt.subplot(121)\n plt.imshow(img_front_0[:,600:1300], cmap='gray')\n plt.imshow(dif_front[:,600:1300], alpha=0.5)\n plt.subplot(122)\n plt.imshow(img_side_0[:,600:1300], cmap='gray')\n plt.imshow(dif_side[:,600:1300], alpha=0.5)\n plt.savefig(f'{DIR_OUT}{id}.png', dpi=500)\n\nif __name__ == '__main__':\n BLENDER_RENDER_DIR = '/home/khanhhh/data_1/projects/Oh/data/bl_models/blender_silhouette/'\n OUT_SILHOUETTE_DIR = '/home/khanhhh/data_1/projects/Oh/data/bl_models/silhouette_shapekey/'\n OUT_SIL_DIF_DIR = '/home/khanhhh/data_1/projects/Oh/data/bl_models/silhouette_shapekey_analysis/'\n pre_process(BLENDER_RENDER_DIR, OUT_SILHOUETTE_DIR)\n viz_shapekey_silhouette_dif(OUT_SILHOUETTE_DIR, OUT_SIL_DIF_DIR)\n\n" }, { "alpha_fraction": 0.8228346705436707, "alphanum_fraction": 0.834645688533783, "avg_line_length": 84, "blob_id": "e21cfe433e88b0456f5371e609a7ec5ccff3f3c4", "content_id": "f389752a19b727cb9439a98498fe90209250ba0a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 254, "license_type": "no_license", "max_line_length": 138, "num_lines": 3, "path": "/src/slice_extraction_steps.md", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "1. run blender script to calculate intersection between slice planes and victoria\n2. use blender to manually delete pointy area in crotch slice because these points make our clock-wise arrangement TSP alrogithm incorrect\n3. run script slice_preprocess.py" }, { "alpha_fraction": 0.5668046474456787, "alphanum_fraction": 0.5747083425521851, "avg_line_length": 30.595237731933594, "blob_id": "5fda4c68430bb7b49fe7a6319a5b94ad5fdf86d1", "content_id": "78e533840fb3a19a8176bef6078d6b1268c1eb01", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2657, "license_type": "no_license", "max_line_length": 137, "num_lines": 84, "path": "/src/caesar_slc_code.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import os\nfrom pathlib import Path\nimport numpy as np\nimport argparse\nimport multiprocessing\nimport pickle\nfrom functools import partial\nimport shutil\nimport src.util as util\n\nG_DEBUG_ROOT_DIR = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/debug/'\nG_DEBUG_SLC_DIR = ''\n\ndef fourier(item, n, G_DEBUG_DIR):\n name = item[0]\n contour = item[1]['cnt']\n X = contour[0,:]\n Y = contour[1,:]\n debug_path = f'{G_DEBUG_DIR}/{name}.png'\n code = util.calc_fourier_descriptor(X, Y, resolution=n, path_debug=debug_path)\n return code\n\ndef fourier_resolution(slc_id):\n if util.is_leg_contour(slc_id):\n return 9\n elif slc_id in ['Shoulder', 'Aux_Armscye_Shoulder_0']:\n return 20\n else:\n return 16\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--IN_DIR\", required=True, help=\"\")\n ap.add_argument(\"-o\", \"--OUT_DIR\", required=True, help=\"\")\n ap.add_argument(\"-ids\", \"--slc_ids\", required=True, help=\"\")\n\n args = vars(ap.parse_args())\n\n IN_DIR = args['IN_DIR']\n OUT_DIR = args['OUT_DIR']\n ids = args['slc_ids']\n\n nprocess = 12\n pool = multiprocessing.Pool(nprocess)\n\n all_ids = [path.stem for path in Path(IN_DIR).glob('./')]\n if ids == 'all':\n slc_ids = all_ids\n else:\n slc_ids = ids.split(',')\n for id in slc_ids:\n assert id in all_ids, f'{id} is unrecognized'\n\n for slc_id in slc_ids:\n SLC_DIR = f'{IN_DIR}/{slc_id}/'\n G_DEBUG_SLC_DIR = f'{G_DEBUG_ROOT_DIR}/{slc_id}_fourier/'\n\n shutil.rmtree(G_DEBUG_SLC_DIR, ignore_errors=True)\n os.makedirs(G_DEBUG_SLC_DIR)\n\n paths = [path for path in Path(SLC_DIR).glob('.pkl')]\n records = []\n names = []\n for path in paths:\n if 'CSR1228A' in path.stem:\n debug = True\n with open(str(path), 'rb') as file:\n r = pickle.load(file)\n records.append(r)\n names.append(path.stem)\n\n print(f'{slc_id} : n_slices = {len(paths)}')\n resolution = fourier_resolution(slc_id)\n codes = pool.map(func=partial(fourier, n=resolution, G_DEBUG_DIR = G_DEBUG_SLC_DIR), iterable=zip(names, records), chunksize=128)\n\n CODE_OUT_DIR = f'{OUT_DIR}/fourier/{slc_id}'\n shutil.rmtree(CODE_OUT_DIR, ignore_errors=True)\n os.makedirs(CODE_OUT_DIR)\n\n for path, record, code in zip(paths, records, codes):\n W = record['W']\n D = record['D']\n with open(f'{CODE_OUT_DIR}/{path.stem}.pkl', 'wb') as file:\n pickle.dump(file=file, obj={'Code':code, 'W':W, 'D':D})\n\n\n\n" }, { "alpha_fraction": 0.5942831039428711, "alphanum_fraction": 0.6039649844169617, "avg_line_length": 34.540985107421875, "blob_id": "c90f40da5b015a39f355a6f0c20f1e3b1ba5c87d", "content_id": "dc88f787c9c480faec7a6e36b8bf126b993b72ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2169, "license_type": "no_license", "max_line_length": 92, "num_lines": 61, "path": "/src/caesar_convert.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import scipy.io as io\nimport argparse\nimport os\nimport sys\nimport numpy as np\nfrom pathlib import Path\nfrom src.obj_util import export_mesh, export_vertices\n\ndef extract_landmark_coords(points, ld_idxs):\n points_out = []\n for idx in ld_idxs:\n idx = idx[0]\n if np.isnan(idx) or idx < 0:\n p_ld = np.array([0.0, 0.0, 0.0])\n else:\n p_ld = points[idx,:]\n points_out.append(p_ld)\n\n return np.array(points_out)\n\ndef convert_mat_to_obj(DIR_IN, DIR_OUT, face_mat_path, ld_idxs):\n faces = io.loadmat(face_mat_path)['faces']\n n_files = len([path for path in Path(DIR_IN).glob('.mat')])\n for i, fpath in enumerate(Path(DIR_IN).glob('.mat')):\n if 'CSR0001A' not in str(fpath):\n continue\n print(f'{fpath.stem}: {i}/{n_files}')\n mpoints = io.loadmat(fpath)['points']\n n_points = mpoints.shape[0]\n if n_points != 6449:\n print(f'error file {face_mat_path.stem}', file=sys.stderr)\n continue\n\n out_path = f'{DIR_OUT}{fpath.stem}.obj'\n export_mesh(out_path, mpoints, faces, add_one=False)\n\n ld_points = extract_landmark_coords(mpoints, ld_idxs)\n out_path = f'{DIR_OUT}{fpath.stem}_ld.obj'\n export_vertices(out_path, ld_points)\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--input\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-o\", \"--output\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-f\", \"--faces\", required=True, help=\"topology\")\n ap.add_argument(\"-l\", \"--landmarks\", required=True, help=\"landmarks\")\n args = vars(ap.parse_args())\n IN_DIR = args['input']\n OUT_DIR = args['output']\n face_path = args['faces']\n l_path = args['landmarks']\n\n #test = io.loadmat('/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar/evectors.mat')\n #exit()\n os.makedirs(OUT_DIR, exist_ok=True)\n\n ld_idxs = io.loadmat(l_path)['landmarksIdxs']\n ld_idxs = ld_idxs.astype(np.int32)\n #for fpath in Path(OUT_DIR).glob('.'):\n # os.remove(fpath)\n convert_mat_to_obj(IN_DIR, OUT_DIR, face_path, ld_idxs)\n\n" }, { "alpha_fraction": 0.5907257795333862, "alphanum_fraction": 0.5907257795333862, "avg_line_length": 37.153846740722656, "blob_id": "d44955a4dbcd76c6bc04224465af6f8cd302ad26", "content_id": "004226f04eccd31b647ee153653154208a423232", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1488, "license_type": "no_license", "max_line_length": 85, "num_lines": 39, "path": "/src/tree_viz.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import sklearn\nimport argparse\nimport pickle\nfrom src.caesar_rbf_net import RBFNet\nfrom sklearn.tree import export_graphviz\nimport shutil\nimport os\nfrom pathlib import Path\nfrom dtreeviz.trees import \nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--in_path\", required=True, help=\"slice obj directory\")\n ap.add_argument(\"-d\", \"--debug_dir\", required=True, help=\"slice obj directory\")\n args = vars(ap.parse_args())\n\n MODEL_PATH = Path(args['in_path'])\n\n DEBUG_DIR_PARENT = args['debug_dir']\n DEBUG_DIR = f'{DEBUG_DIR_PARENT}/tree_viz/{MODEL_PATH.stem}'\n shutil.rmtree(DEBUG_DIR, ignore_errors=True)\n os.makedirs(DEBUG_DIR)\n\n model = RBFNet.load_from_path(MODEL_PATH)\n use_graphviz = False\n if use_graphviz:\n for i, tree in enumerate(model.regressor.estimators_):\n export_graphviz(tree, out_file=f'{DEBUG_DIR}/estimator_{i}.dot')\n for path in Path(DEBUG_DIR).glob('.dot'):\n print(path)\n os.system(f'dot -Tpng {str(path)} -o {DEBUG_DIR}/{path.stem}.png')\n else:\n for i, forest in enumerate(model.regressor.estimators_):\n for j, tree in enumerate(forest.estimators_):\n viz = dtreeviz(tree,\n X_train,\n Y_train,\n feature_names=[str(i) for i in range(self.n_cluster)],\n target_name='hello')\n viz.view()\n" }, { "alpha_fraction": 0.5583437085151672, "alphanum_fraction": 0.5745572447776794, "avg_line_length": 31.916255950927734, "blob_id": "a347409bdc173328ab544587e18887e2ded5ba15", "content_id": "09cd61297e59b77656e26b85984be73a904080cb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 20045, "license_type": "no_license", "max_line_length": 167, "num_lines": 609, "path": "/src/bld_caesar_slice.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import bpy\nimport bmesh\nfrom mathutils import Vector\nfrom pathlib import Path\nimport pickle as pkl\nimport numpy as np\nimport math\nimport os\nfrom collections import defaultdict\nimport shutil\n\nscene = bpy.context.scene\ng_cur_file_name = ''\ng_mult_edge_loop_file_names = set()\n\ndef select_single_obj(obj):\n bpy.ops.object.select_all(action='DESELECT')\n obj.select = True\n bpy.context.scene.objects.active = obj\n\n#boolean will apply on obj1\ndef isect(obj1, obj2):\n select_single_obj(obj1)\n mod = obj1.modifiers.new('Boolean', type='BOOLEAN')\n mod.object = obj2\n mod.solver ='BMESH'\n mod.operation = 'INTERSECT'\n bpy.ops.object.modifier_apply(apply_as='DATA', modifier = mod.name)\n\ndef copy_obj(obj, name, location):\n select_single_obj(obj)\n bpy.ops.object.duplicate()\n obj = scene.objects.active\n obj.name = name\n return obj\n\ndef delete_obj(obj):\n select_single_obj(obj)\n bpy.ops.object.delete()\n\ndef import_obj(path, name):\n bpy.ops.import_scene.obj(filepath=path, axis_forward='Y', axis_up='Z', split_mode='OFF')\n obj = bpy.context.selected_objects[0]\n obj.name = name\n return obj\n\ndef transform_obj_caesar(obj, ld_idxs):\n mesh = obj.data\n \n s = 0.01\n bpy.ops.transform.resize(value=(s,s,s))\n bpy.ops.object.transform_apply(location=True, scale=True, rotation=True)\n \n org = mesh.vertices[ld_idxs[72]].co\n bpy.ops.transform.translate(value = -org)\n bpy.ops.object.transform_apply(location=True, scale=False, rotation=False)\n \n p0_x = mesh.vertices[ld_idxs[16]].co\n p1_x = mesh.vertices[ld_idxs[18]].co\n x = p1_x - p0_x\n x.normalize()\n angle = x.dot(Vector((1.0, 0.0, 0.0)))\n #angle = math.degrees(math.acos(angle))\n angle = math.acos(angle)\n print('angle', angle)\n bpy.ops.transform.rotate(value=angle, axis=(0.0,0.0,1.0))\n \n select_single_obj(obj)\n bpy.ops.object.transform_apply(location=True, scale=True, rotation=True)\n\ndef ucsc_transform_obj(obj):\n select_single_obj(obj)\n \n s = 5.0\n bpy.ops.transform.resize(value=(s,s,s))\n bpy.ops.object.transform_apply(location=True, scale=True, rotation=True)\n \n #org = mesh.vertices[ld_idxs[72]].co\n #bpy.ops.transform.translate(value = -org)\n #bpy.ops.object.transform_apply(location=True, scale=False, rotation=False)\n \n angle = math.radians(50.0)\n bpy.ops.transform.rotate(value=angle, axis=(0.0,0.0,1.0))\n bpy.ops.object.transform_apply(location=True, scale=True, rotation=True)\n \ndef mesh_to_numpy(mesh):\n nverts = len(mesh.vertices)\n verts = []\n for iv in range(nverts):\n verts.append(mesh.vertices[iv].co[:])\n \n faces = []\n for p in mesh.polygons:\n faces.append(p.vertices[:])\n \n return np.array(verts), faces\n\ndef collect_group_vertex_indices(obj, name_ids):\n verts = obj.data.vertices\n lds = defaultdict(list)\n for v in verts:\n for vgrp in v.groups:\n grp_name = obj.vertex_groups[vgrp.group].name\n if grp_name in name_ids:\n lds[grp_name].append(v.index)\n return lds\n \ndef set_plane_slice_loc(planes, name, loc):\n mesh = planes.data\n found = False\n for v in mesh.vertices:\n assert len(v.groups) <= 1\n for vgrp in v.groups:\n grp_name = planes.vertex_groups[vgrp.group].name\n #print('group name', grp_name, name)\n if grp_name == name:\n v.co[2] = loc[2]\n found = True\n if found == False:\n print(name)\n assert found\n\ndef centroid_vertex_set(vertices, ids):\n avg = Vector((0.0, 0.0, 0.0))\n for id in ids:\n v = vertices[id]\n avg = avg + v.co\n avg = avg / float(len(ids))\n return avg\n\ndef ucsc_calc_slice_plane_locs(cae_obj, ld_idxs):\n verts = cae_obj.data.vertices\n locs = {}\n\n for slc_id, slc_idxs in ld_idxs.items():\n locs[slc_id] = centroid_vertex_set(verts, slc_idxs)\n\n return locs\n\n#http://people.scs.carleton.ca/~c_shu/pdf/landmark-3dpvt06.pdf\ndef mpii_calc_slice_plane_locs(cae_obj, ld_idxs):\n verts = cae_obj.data.vertices\n locs = {}\n loc_0 = verts[ld_idxs[16]].co\n loc_1 = verts[ld_idxs[18]].co\n hip = 0.5(loc_0 + loc_1)\n locs['Hip'] = hip\n\n crotch = verts[ld_idxs[73-1]].co\n crotch = crotch + 0.1 * (hip - crotch)\n locs['Crotch'] = crotch\n locs['Aux_Crotch_Hip_0'] = crotch + 1.0/4.0(hip - crotch)\n locs['Aux_Crotch_Hip_1'] = crotch + 2.0/4.0(hip - crotch)\n locs['Aux_Crotch_Hip_2'] = crotch + 3.0/4.0(hip - crotch)\n\n waist = 0.5(verts[ld_idxs[20-1]].co + verts[ld_idxs[22-1]].co)\n locs['Waist'] = waist\n locs['Aux_Hip_Waist_0'] = 0.5(hip + waist)\n\n upper_bust = 0.5(verts[ld_idxs[12]].co + verts[ld_idxs[13]].co)\n under_bust_ld = verts[ld_idxs[14]].co\n alpha = 0.6\n locs['Bust'] = alphaupper_bust+(1-alpha)under_bust_ld\n\n under_bust = under_bust_ld + 0.6(under_bust_ld - upper_bust)\n locs['UnderBust'] = under_bust\n\n locs['Aux_Waist_UnderBust_0'] = waist + 1.0/3.0(under_bust - waist)\n locs['Aux_Waist_UnderBust_1'] = waist + 2.0/3.0(under_bust - waist)\n\n armscye = upper_bust + 0.6(upper_bust - under_bust_ld)\n locs['Armscye'] = armscye\n\n shoulder = 0.5(verts[ld_idxs[29-1]].co + verts[ld_idxs[41-1]].co)\n locs['Shoulder'] = shoulder\n\n locs['Aux_Armscye_Shoulder_0'] = 0.5(shoulder + armscye)\n\n locs['Aux_UnderBust_Bust_0'] = verts[ld_idxs[14]].co\n\n crotch = verts[ld_idxs[73-1]].co\n knee = 0.25(verts[ld_idxs[64-1]].co+verts[ld_idxs[54-1]].co + verts[ld_idxs[65-1]].co + verts[ld_idxs[55-1]].co)\n under_crotch = knee + 0.85 (crotch-knee)\n locs['UnderCrotch'] = under_crotch\n\n locs['Knee'] = knee\n\n locs['Aux_Knee_UnderCrotch_0'] = knee + 0.2(crotch-knee)\n locs['Aux_Knee_UnderCrotch_1'] = knee + 0.4(crotch-knee)\n locs['Aux_Knee_UnderCrotch_2'] = knee + 0.6(crotch-knee)\n locs['Aux_Knee_UnderCrotch_3'] = knee + 0.8(crotch-knee)\n\n lankle = 0.5(verts[ld_idxs[61]].co + verts[ld_idxs[62]].co)\n #rankle = 0.5(verts[ld_idxs[51]].co + verts[ld_idxs[52]].co)\n ankle = lankle #0.5(lankle + rankle)\n\n locs['Ankle'] = ankle\n locs['Calf'] = ankle + (2.0 / 3.0) (knee - ankle)\n\n #print('Hip', locs['Hip'])\n #print('Bust',locs['Bust'])\n \n return locs\n\n#should be in edit mode\ndef merge_incorrect_contour(contours):\n new_contours = []\n for contour in contours:\n for contour_1 in contours:\n if contour[0] == contour_1[0]:\n new_contour = contour[::-1]\n new_contour.extend(contour_1[1:])\n elif contour[0] == contour_1[-1]:\n new_contour = contour\n new_contour.extend(contour_1[:])\n\n \ndef contour_from_edges(edges):\n global g_cur_file_name\n global g_mult_edge_loop_file_names\n \n contours = []\n bpy.ops.mesh.select_mode(type=\"EDGE\")\n edge_mark = set(edges)\n \n centroid = Vector()\n for e in edges:\n centroid += e.verts[0].co\n centroid += e.verts[1].co\n centroid /= (2.0 * len(edges))\n \n while True:\n if len(edge_mark) == 0:\n break\n\n #select a single loop from a sample edge\n #bpy.ops.mesh.select_all(action='DESELECT')\n #prev_e = edge_mark.pop()\n #prev_e.select = True\n #bpy.ops.mesh.loop_multi_select()\n \n prev_e = edge_mark.pop()\n prev_e.select = False\n\n #sort all edges on this loop\n contour = []\n contour.append(prev_e.verts[0].co[:])\n contour.append(prev_e.verts[1].co[:])\n v_start = prev_e.verts[0]\n v_cur = prev_e.verts[1]\n while True:\n e_next = []\n for e in v_cur.link_edges:\n if e.is_valid and e != prev_e and e.select == True:\n e_next.append(e)\n\n #assert len(e_next) <= 1\n #no closed contour found\n if len(e_next) == 0:\n print('no contour found')\n break\n \n if len(e_next) > 1:\n #debug code\n #bpy.ops.mesh.select_all(action='DESELECT')\n #print('len e_next ',len(e_next))\n #for test_e in e_next:\n # test_e.select = True\n #v_start.select = True\n #v_cur.select = True \n \n #TODO\n #pick the closest one to centroid\n closest_e = None\n min_dst = 99999.0\n for e in e_next:\n mid_p = 0.5(e.verts[0].co + e.verts[1].co)\n if (mid_p - centroid).length < min_dst:\n closest_e = e\n min_dst = (mid_p - centroid).length\n e_next = closest_e\n g_mult_edge_loop_file_names.add(g_cur_file_name)\n else:\n e_next = e_next[0] \n \n #discard this edge from our edge pool\n edge_mark.discard(e_next)\n e_next.select = False\n \n v_cur = e_next.verts[1] if v_cur == e_next.verts[0] else e_next.verts[0]\n #finish a contour\n if v_cur == v_start:\n break\n\n prev_e = e_next\n\n contour.append(v_cur.co[:])\n\n contours.append(contour)\n \n return contours\n\n#mesh must be in edit mode\ndef isect_slice_plane_obj(bm, co, no):\n bpy.ops.mesh.select_all(action='SELECT')\n #after this function, all isect edges will be selected\n bpy.ops.mesh.bisect(plane_co=co, plane_no = no)\n edges = [e for e in bm.edges if e.select == True]\n assert len(edges) > 0\n return contour_from_edges(edges)\n\ndef isect_extract_slice_from_locs(locs, obj_caesar):\n no = Vector((0.0,0.0,1.0))\n \n select_single_obj(obj_caesar)\n bpy.ops.object.mode_set(mode='EDIT')\n bm = bmesh.from_edit_mesh(obj_caesar.data)\n\n slc_contours = defaultdict(list)\n for id, loc in locs.items():\n contours = isect_slice_plane_obj(bm, loc, no)\n if contours is None:\n return None\n \n slc_contours[id] = contours\n\n bpy.ops.object.mode_set(mode='OBJECT')\n\n return slc_contours\n\ndef extract_slice_from_isect_obj(locs, isect_obj, eps = 0.1): \n select_single_obj(isect_obj)\n \n bpy.ops.object.mode_set(mode='EDIT')\n bpy.ops.mesh.select_all(action='SELECT')\n bpy.ops.mesh.edge_face_add()\n \n isect_bm = bmesh.from_edit_mesh(isect_obj.data)\n \n slc_contours = defaultdict(list)\n f_marks = set()\n for id, loc in locs.items():\n for f in isect_bm.faces:\n center = f.calc_center_bounds()\n if abs(center[2] - loc[2]) < eps:\n #a face should belong to a single slice\n assert f not in f_marks\n f_marks.add(f)\n #extract face contour\n contour = []\n for v in f.verts:\n contour.append(v.co[:])\n \n slc_contours[id].append(contour)\n \n #assert that we found at least one contour for that slice\n assert id in slc_contours\n \n bpy.ops.object.mode_set(mode='OBJECT') \n return slc_contours\n\ndef mpii_is_correct_mesh(obj):\n n_verts = len(obj.data.vertices)\n n_faces = len(obj.data.polygons)\n if n_verts != 6449 or n_faces != 12894:\n return False\n else:\n return True\ndef mpii_extract_all_ld_points(obj, ld_idxs):\n mesh = obj.data\n nverts = len(mesh.vertices)\n ld_points = []\n for idx in ld_idxs:\n print(idx)\n if idx >= 0 and idx < nverts:\n ld = mesh.vertices[idx].co[:]\n ld_points.append(ld)\n else:\n ld_points.append([-1, -1, -1])\n\n return np.array(ld_points)\n\ndef mpii_process(DIR_IN_OBJ, DIR_OUT_SLICE, DIR_OUT_SUPPOINT, DIR_OUT_LD_POINT, slice_ids, debug_name = None):\n obj_planes_tpl = bpy.data.objects['Slice_planes_template']\n \n ld_path = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_meta/landmarksIdxs73.npy'\n ld_idxs = np.load(ld_path)\n\n suppoint_obj = bpy.data.objects['MPII_female_supplement_keypoints']\n support_points_ids = []\n for grp in suppoint_obj.vertex_groups:\n support_points_ids.append(grp.name)\n support_points_idxs = collect_group_vertex_indices(suppoint_obj, support_points_ids)\n \n error_obj_paths = []\n\n for id in slice_ids:\n os.makedirs(DIR_OUT_SLICE + '/' + id, exist_ok=True)\n\n ignore_files = {'nl_6289a'}\n for i, path in enumerate(Path(DIR_IN_OBJ).glob('.obj')):\n\n if (debug_name is not None) and (debug_name not in str(path)):\n continue\n\n if path.stem in ignore_files:\n continue\n\n print(i, str(path))\n obj_caesar = import_obj(str(path), path.stem)\n transform_obj_caesar(obj_caesar, ld_idxs)\n\n if not mpii_is_correct_mesh(obj_caesar):\n print('error object: ', path.stem)\n error_obj_paths.append(str(path))\n delete_obj(obj_caesar)\n continue\n\n #output landmark points\n ld_out_path = DIR_OUT_LD_POINT + '/' + path.stem + '.pkl'\n ld_points = mpii_extract_all_ld_points(obj_caesar, ld_idxs)\n with open(ld_out_path, 'wb') as file:\n pkl.dump(ld_points, file)\n\n #extract support points\n verts = obj_caesar.data.vertices\n locs = {}\n for id, idxs in support_points_idxs.items():\n locs[id] = centroid_vertex_set(verts, idxs)[:]\n suppoint_path = DIR_OUT_SUPPOINT + '/' + path.stem + '.pkl'\n with open(suppoint_path, 'wb') as file:\n pkl.dump(locs, file)\n\n if len(slice_ids) > 0:\n\n slc_locs = mpii_calc_slice_plane_locs(obj_caesar, ld_idxs)\n\n #just process on slices on demand\n slc_locs = {id:loc for id, loc in slc_locs.items() if id in slice_ids}\n #print(slc_locs)\n\n if debug_name is not None:\n obj_planes = copy_obj(obj_planes_tpl, path.stem+'_slice_planes', Vector((0.0, 0.0, 0.0)))\n for id, loc in slc_locs.items():\n set_plane_slice_loc(obj_planes, id, loc)\n\n slc_contours = isect_extract_slice_from_locs(slc_locs, obj_caesar)\n assert slc_contours is not None\n\n\n for id in slice_ids:\n id_path = DIR_OUT_SLICE + '/' + id + '/' + path.stem + '.pkl'\n contours = slc_contours[id]\n with open(id_path, 'wb') as file:\n pkl.dump(contours, file)\n\n if debug_name != None:\n return\n\n delete_obj(obj_caesar)\n if (debug_name is not None) and (obj_planes is not None):\n delete_obj(obj_planes)\n\n #if i > 5:\n # break\n \n print('error files: ', error_obj_paths)\n print('n error files: ', len(error_obj_paths))\n\ndef ucsc_extract_supplement_keypoints(DIR_OBJ, DIR_OUT, tpl_obj):\n ld_ids = []\n for grp in tpl_obj.vertex_groups:\n ld_ids.append(grp.name)\n\n ld_idxs = collect_group_vertex_indices(tpl_obj, ld_ids)\n\n for i, path in enumerate(Path(DIR_OBJ).glob('.obj')):\n print(i, str(path))\n obj_caesar = import_obj(str(path), path.stem)\n\n select_single_obj(obj_caesar)\n ucsc_transform_obj(obj_caesar)\n\n n_verts = len(obj_caesar.data.vertices)\n n_faces = len(obj_caesar.data.polygons)\n if n_verts != 12500 or n_faces != 24999:\n print('error object: ', path.stem)\n delete_obj(obj_caesar)\n continue\n\n verts = obj_caesar.data.vertices\n locs = {}\n for id, idxs in ld_idxs.items():\n locs[id] = centroid_vertex_set(verts, idxs)[:]\n\n id_path = DIR_OUT+ '/' + path.stem + '.pkl'\n with open(id_path, 'wb') as file:\n pkl.dump(locs, file)\n \n delete_obj(obj_caesar)\n\ndef ucsc_process(DIR_OBJ, DIR_SLICE, slice_ids, debug_name = None):\n obj_planes_tpl = bpy.data.objects['Slice_planes_template']\n \n error_obj_paths = []\n obj_template = bpy.data.objects['Female_template']\n\n ld_idxs = collect_group_vertex_indices(obj_template, slice_ids)\n\n for id in slice_ids:\n os.makedirs(DIR_SLICE+'/'+id, exist_ok=True)\n\n error_files = ['SPRING1212']\n for i, path in enumerate(Path(DIR_OBJ).glob('.obj')): \n if (debug_name is not None) and (debug_name not in str(path)):\n continue\n \n ignore = False\n for name in error_files:\n if name in str(path):\n ignore = True \n break\n \n if ignore == True:\n continue\n \n print(i, str(path))\n \n obj_caesar = import_obj(str(path), path.stem)\n \n select_single_obj(obj_caesar)\n bpy.ops.mesh.customdata_custom_splitnormals_clear()\n\n ucsc_transform_obj(obj_caesar)\n \n n_verts = len(obj_caesar.data.vertices) \n n_faces = len(obj_caesar.data.polygons)\n if n_verts != 12500 or n_faces != 24999:\n print('error object: ', path.stem) \n error_obj_paths.append(str(path))\n delete_obj(obj_caesar)\n continue\n \n obj_planes = copy_obj(obj_planes_tpl, path.stem+\"_pln\", Vector((0.0,0.0,0.0))) \n\n slc_locs = ucsc_calc_slice_plane_locs(obj_caesar, ld_idxs)\n #for debuggin\n #for id, loc in slc_locs.items():\n # set_plane_slice_loc(obj_planes, id, loc)\n\n obj_planes.hide = False\n obj_caesar.hide = False\n\n slc_contours = isect_extract_slice_from_locs(slc_locs, obj_caesar)\n assert slc_contours is not None\n\n for id in slice_ids:\n id_path = DIR_SLICE+'/'+id+'/'+path.stem+'.pkl'\n contours = slc_contours[id]\n with open(id_path, 'wb') as file:\n pkl.dump(contours, file)\n\n if debug_name != None:\n return\n\n delete_obj(obj_caesar)\n delete_obj(obj_planes)\n\n #if i > 10:\n # break\n\n print('error list: ', error_obj_paths)\n print('multiple edge loop name list: ', g_mult_edge_loop_file_names)\n \ndef ucsc_extract_slice():\n DIR_OBJ = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_usce/SPRING_FEMALE/'\n DIR_SLICE = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_usce/female_slice/'\n\n #'Hip', 'Crotch', 'Aux_Crotch_Hip_0'\n os.makedirs(DIR_SLICE, exist_ok=True)\n slice_ids = ['Bust']\n debug_file = 'SPRING0136'\n ucsc_process(DIR_OBJ, DIR_SLICE, slice_ids=slice_ids, debug_name=debug_file)\n\ndef ucsc_extract_supplement_points():\n DIR_OBJ = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_usce/SPRING_FEMALE/'\n DIR_LD = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_usce/female_landmarks/'\n ld_obj = bpy.data.objects['Female_landmarks']\n shutil.rmtree(DIR_LD)\n os.makedirs(DIR_LD, exist_ok=True)\n ucsc_extract_supplement_keypoints(DIR_OBJ, DIR_LD, ld_obj)\n\ndef mpii_extract_slices():\n DIR_IN_OBJ = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/caesar_obj_female/'\n DIR_OUT_SLICE = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/caesar_obj_slices/'\n DIR_OUT_SUPPOINT = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/caesar_obj_supplement_points/'\n DIR_OUT_LD = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/caesar_obj_landmark_points/'\n\n os.makedirs(DIR_OUT_LD, exist_ok=True)\n os.makedirs(DIR_OUT_SLICE, exist_ok=True)\n slice_ids = []\n slice_ids = ['Aux_Crotch_Hip_0', 'Aux_Crotch_Hip_1', 'Aux_Crotch_Hip_2']\n #debug_file = 'csr4149a.obj'\n debug_file = None\n mpii_process(DIR_IN_OBJ, DIR_OUT_SLICE=DIR_OUT_SLICE, DIR_OUT_SUPPOINT=DIR_OUT_SUPPOINT, DIR_OUT_LD_POINT = DIR_OUT_LD, slice_ids=slice_ids, debug_name=debug_file)\n\nif __name__ == '__main__':\n mpii_extract_slices()\n #mpii_extract_supplement_points()a" }, { "alpha_fraction": 0.5627282857894897, "alphanum_fraction": 0.5798940658569336, "avg_line_length": 36.632301330566406, "blob_id": "14d8ddc11ee761c43f0a24e86c40497bf6ec5906", "content_id": "48a6dfd55e163ed11015a9ecba8735d07e6e70bd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 10952, "license_type": "no_license", "max_line_length": 174, "num_lines": 291, "path": "/src/control_mesh_calc_weight_calculate.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport argparse\nfrom collections import defaultdict\nimport os\nfrom pathlib import Path\nimport pickle\nfrom copy import deepcopy\nfrom src.util import normalize\nimport matplotlib.pyplot as plt\nimport src.util as util\nfrom shapely.geometry import Polygon, Point\nimport multiprocessing\nfrom functools import partial\nfrom scipy import stats\n\nfrom enum import Enum\nclass BDPart(Enum):\n Part_Head = 1\n Part_LArm = 2\n Part_RArm = 3\n Part_LLeg = 4\n Part_RLeg = 5\n Part_Torso = 6\n\ndef dst_point_plane(point, plane_point, plane_norm):\n return np.dot(plane_norm, point - plane_point)\n\ndef parameterize(verts, vert_effect_idxs, basis):\n print('parameterize')\n P = []\n T = np.zeros((3,3),np.float32)\n for i in range(verts.shape[0]):\n v_co = verts[i,:]\n idxs = vert_effect_idxs[i]\n v_uvw = []\n for ctl_tri_idx in idxs:\n d = v_co - basis[ctl_tri_idx, 0, :]\n T[:,0] = basis[ctl_tri_idx, 1, :]\n T[:,1] = basis[ctl_tri_idx, 2, :]\n T[:,2] = basis[ctl_tri_idx, 3, :]\n local_co = np.linalg.solve(T, d)\n v_uvw.append(local_co)\n P.append(v_uvw)\n if i % 500 == 0:\n print(i,'/',verts.shape[0])\n\n return P\n\ndef vert_tri_weight(v, t_v0, t_v1, t_v2):\n beta = 1.5\n center = (t_v0+t_v1+t_v2)/3.0\n d = np.linalg.norm(v-center)\n l = (np.linalg.norm(t_v0-center) + np.linalg.norm(t_v1-center) + np.linalg.norm(t_v2-center))/3.0\n ratio = d/l\n if ratio < beta:\n return 1.0-ratio/beta\n else:\n return 0.0\n\ndef average_circumscribed_radius_tris(verts, tris, tris_idxs):\n rads = np.zeros(len(tris_idxs), dtype=np.float32)\n for j, t_idx in enumerate(tris_idxs):\n v0, v1, v2 = verts[tris[t_idx][0]], verts[tris[t_idx][1]], verts[tris[t_idx][2]]\n center = (v0+v1+v2)/3.0\n rads[j] = (np.linalg.norm(v0-center) + np.linalg.norm(v1-center) + np.linalg.norm(v2-center))/3.0\n return np.mean(rads)\n\ndef is_adjacent_tri(t0, t1):\n for i in range(3):\n v00, v01 = t0[i], t0[(i+1)%3]\n for j in range(3):\n v10, v11 = t1[j], t1[(j+1)%3]\n if (v00 == v10 and v01 == v11) or (v00 == v11 and v01 == v10):\n return True\n return False\n\ndef find_neighbour_body_part_triangles(tris_ctl, ctl_tri_bd_parts):\n n_tris = len(tris_ctl)\n bd_part_adj_tri_idxs = defaultdict(list)\n\n for tri_idx, part_id in enumerate(ctl_tri_bd_parts):\n for other_tri_idx in range(n_tris):\n #not the triangle we are processing\n if tri_idx == other_tri_idx:\n continue\n\n #not in the same body part\n if ctl_tri_bd_parts[other_tri_idx] == part_id:\n continue\n\n if is_adjacent_tri(tris_ctl[tri_idx], tris_ctl[other_tri_idx]):\n bd_part_adj_tri_idxs[part_id].append(other_tri_idx)\n\n return bd_part_adj_tri_idxs\n\ndef calc_vertex_weigth_control_mesh_local(verts_tpl, verts_ctl, tris_ctl, tpl_v_body_parts, ctl_tri_bd_parts, effective_range_factor = 6):\n\n effect_idxs = [None]* len(verts_tpl)\n effect_weights =[None]* len(verts_tpl)\n\n ctl_tri_centers = np.zeros((len(tris_ctl), 3), dtype=np.float32)\n for j, t in enumerate(tris_ctl):\n v0, v1, v2 = verts_ctl[t[0]], verts_ctl[t[1]], verts_ctl[t[2]]\n center = (v0+v1+v2)/3.0\n ctl_tri_centers[j, :] = center\n\n bd_part_ctl_tris_idxs = defaultdict(list)\n for tri_idx, _ in enumerate(tris_ctl):\n part_id = ctl_tri_bd_parts[tri_idx]\n bd_part_ctl_tris_idxs[part_id].append(tri_idx)\n\n print('generating neighbouring information for control mesh')\n bd_part_adj_ctl_tri_idxs = find_neighbour_body_part_triangles(tris_ctl, ctl_tri_bd_parts)\n\n bd_part_ctl_avg_rads = {id : average_circumscribed_radius_tris(verts_ctl, tris_ctl, part_tris_idxs) for id, part_tris_idxs in bd_part_ctl_tris_idxs.items()}\n print(bd_part_ctl_avg_rads )\n\n body_part_tpl_verts = {}\n for i, part_id in enumerate(tpl_v_body_parts):\n if part_id not in body_part_tpl_verts:\n body_part_tpl_verts[part_id] = []\n body_part_tpl_verts[part_id].append(i)\n\n print('start calculating weights')\n cnt_progress = 0\n n_zero_weights = 0\n for part_id, verts in body_part_tpl_verts.items():\n if part_id not in bd_part_ctl_avg_rads:\n print(f'missing body part of ID {part_id}')\n continue\n print(f'processing body part {part_id}')\n bd_part_avg_rad = bd_part_ctl_avg_rads[part_id]\n for v_i in verts:\n tri_idxs = []\n weights = []\n v_co = verts_tpl[v_i, :]\n\n #weights respect to control tringle in the same body part\n ctl_tris_idxs = bd_part_ctl_tris_idxs[part_id]\n for tri_idx in ctl_tris_idxs:\n d = np.linalg.norm(v_co - ctl_tri_centers[tri_idx, :])\n ratio = d / bd_part_avg_rad\n if ratio < effective_range_factor:\n w = ratio / effective_range_factor\n w = 1 - w\n #w = np.exp(-4.0ww)\n tri_idxs.append(tri_idx)\n weights.append(w)\n\n #weights respect to neighbour control triangle in the adjacent body part\n ctl_tris_idxs = bd_part_adj_ctl_tri_idxs[part_id]\n for tri_idx in ctl_tris_idxs:\n d = np.linalg.norm(v_co - ctl_tri_centers[tri_idx, :])\n ratio = d / bd_part_avg_rad\n if ratio < effective_range_factor:\n w = 1.0 - ratio / effective_range_factor\n tri_idxs.append(tri_idx)\n weights.append(w)\n\n cnt_progress += 1\n if len(tri_idxs) == 0:\n n_zero_weights += 1\n if cnt_progress % 500 == 0:\n print(cnt_progress, '/', verts_tpl.shape[0], 'zero weight vertices = ', n_zero_weights)\n\n effect_idxs[v_i] = tri_idxs\n effect_weights[v_i] = weights\n\n return effect_idxs, effect_weights\n\ndef vertex_process_global(v, tris_ref, tri_centers, tri_radius, effective_range_factor):\n idxs = []\n weights = []\n for j, t in enumerate(tris_ref):\n #w = vert_tri_weight(v, verts_ref[t[0]], verts_ref[t[1]], verts_ref[t[2]])\n d = np.linalg.norm(v - tri_centers[j, :])\n ratio = d/tri_radius[j]\n if ratio < effective_range_factor:\n #w = 1.0 - ratio / effective_range_factor\n w = ratio/effective_range_factor\n w = 1.0 - w\n #w = np.exp(ww)\n idxs.append(j)\n weights.append(w)\n\n return (idxs, weights)\n\ndef calc_vertex_weigth_control_mesh_global(verts, verts_ref, tris_ref, effective_range_factor = 4):\n print('calc_vertex_weigth_control_mesh')\n effect_idxs = []\n effect_weights = []\n\n tri_centers = np.zeros((len(tris_ref), 3), dtype=np.float32)\n tri_radius = np.zeros((len(tris_ref)), dtype=np.float32)\n for j, t in enumerate(tris_ref):\n v0, v1, v2 = verts_ref[t[0]], verts_ref[t[1]], verts_ref[t[2]]\n center = (v0+v1+v2)/3.0\n tri_centers[j, :] = center\n tri_radius[j] = (np.linalg.norm(v0-center) + np.linalg.norm(v1-center) + np.linalg.norm(v2-center))/3.0\n\n nprocess = 12\n pool = multiprocessing.Pool(nprocess)\n results = pool.map(func=partial(vertex_process_global, tris_ref=tris_ref, tri_centers=tri_centers, tri_radius =tri_radius, effective_range_factor=effective_range_factor),\n iterable=verts, chunksize=128)\n\n # for i in range(verts.shape[0]):\n # v = verts[i,:]\n # idxs = []\n # weights = []\n #\n # for j,t in enumerate(tris_ref):\n # #w = vert_tri_weight(v, verts_ref[t[0]], verts_ref[t[1]], verts_ref[t[2]])\n # d = np.linalg.norm(v-tri_centers[j,:])\n # ratio = d/tri_radius[j]\n # if ratio < effective_range_factor:\n # #w = 1.0 - ratio / effective_range_factor\n # w = ratio/effective_range_factor\n # w = np.exp(-6.0ww)\n # idxs.append(j)\n # weights.append(w)\n #\n # if i % 500 == 0:\n # print(i,'/',verts.shape[0])\n # effect_idxs.append(idxs)\n # effect_weights.append(weights)\n # effect_idxs.append([d_min_idx])\n # effect_weights.append([w_min])\n for pair in results:\n effect_idxs.append(pair[0])\n effect_weights.append(pair[1])\n\n lens = np.array([len(idxs) for idxs in effect_idxs])\n stat = stats.describe(lens)\n print(f'finish calculating weights')\n print(f'\\tneighbor size statistics:')\n print(f'\\t{stat}')\n\n return effect_idxs, effect_weights\n\ndef rect_plane(rect):\n n = np.cross(rect[2]-rect[0], rect[1]-rect[0])\n n = n / np.linalg.norm(n)\n p = np.mean(rect, axis=0)\n return p,n\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-vic\", \"--victoria\", required=True, help=\"victoria pkl file\")\n ap.add_argument(\"-o\", \"--out_dir\", required=True, help=\"directory for expxorting control mesh slices\")\n ap.add_argument(\"-g\", \"--global\", required=True, help=\"global weight\")\n args = vars(ap.parse_args())\n\n vic_path = args['victoria']\n out_path = args['out_dir']\n is_global = int(args['global']) > 0\n\n with open(vic_path, 'rb') as f:\n data = pickle.load(f)\n slc_id_locs = data['slice_locs']\n arm_bone_locs = data['arm_bone_locs']\n slice_id_vert_idxs = data['slice_vert_idxs']\n\n ctl_mesh = data['control_mesh']\n ctl_mesh_quad_dom = data['control_mesh_quad_dom']\n\n tpl_mesh = data['template_mesh']\n\n print('control mesh: nverts = {0}, nfaces = {1}'.format(ctl_mesh['verts'].shape[0], len(ctl_mesh['faces'])))\n print('victoria mesh: nverts = {0}, nfaces = {1}'.format(tpl_mesh['verts'].shape[0], len(tpl_mesh['faces'])))\n\n print('calculating weight')\n ctl_tri_bs = util.calc_triangle_local_basis(ctl_mesh['verts'], ctl_mesh['faces'])\n\n if is_global:\n vert_effect_idxs, vert_weights = calc_vertex_weigth_control_mesh_global(tpl_mesh['verts'], ctl_mesh['verts'], ctl_mesh['faces'], effective_range_factor=2)\n else:\n ctl_f_body_parts = data['control_mesh_face_body_parts']\n tpl_v_body_parts = data['template_vert_body_parts']\n body_part_dict = data['body_part_dict']\n vert_effect_idxs, vert_weights = calc_vertex_weigth_control_mesh_local(tpl_mesh['verts'], ctl_mesh['verts'], ctl_mesh['faces'], tpl_v_body_parts, ctl_f_body_parts)\n\n vert_UVW = parameterize(tpl_mesh['verts'], vert_effect_idxs, ctl_tri_bs)\n\n w_data = {}\n w_data['template_vert_UVW'] = vert_UVW\n w_data['template_vert_weight'] = vert_weights\n w_data['template_vert_effect_idxs'] = vert_effect_idxs\n w_data['control_mesh_tri_basis'] = ctl_tri_bs\n\n with open(out_path, 'wb') as f:\n pickle.dump(w_data, f)\n\n" }, { "alpha_fraction": 0.5757169127464294, "alphanum_fraction": 0.5884974598884583, "avg_line_length": 33.354244232177734, "blob_id": "690a2a53b6632c3c22d594e2ef3de8d03d6d8b7f", "content_id": "746442bc9b6737fd76fc504d5abe6a00063f3ab8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 18622, "license_type": "no_license", "max_line_length": 176, "num_lines": 542, "path": "/src/bld_ctr_mesh.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import bpy\nimport os\nimport pickle\nimport numpy as np\nimport mathutils.geometry as geo\nfrom mathutils import Vector\nfrom bpy import context\nfrom collections import defaultdict\nfrom copy import deepcopy\n\ndef select_single_obj(obj):\n bpy.ops.object.select_all(action='DESELECT')\n obj.select = True\n bpy.context.scene.objects.active = obj\n\ndef isect(obj1, obj2):\n select_single_obj(obj1)\n mod = obj1.modifiers.new('Boolean', type='BOOLEAN')\n mod.object = obj2\n mod.solver ='BMESH'\n mod.operation = 'INTERSECT'\n bpy.ops.object.modifier_apply(apply_as='DATA', modifier = mod.name)\n\ndef copy_obj(obj, new_name, location):\n obj_data = obj.data\n new_object = bpy.data.objects.new(name=new_name, object_data=obj_data)\n scene.objects.link(new_object)\n new_object.location = location\n select_single_obj(new_object)\n return new_object\n\ndef write_vertices_to_obj(path, mesh):\n with open(path, 'w') as f:\n for i,v in enumerate(mesh.vertices):\n f.write(\"v %.4f %.4f %.4f \\n\" % v.co[:])\n \ndef write_slices_to_obj(dir, obj, plane_z):\n mesh = obj.data\n print(plane_z)\n filepath = os.path.join(dir, obj.name+'.obj')\n write_vertices_to_obj(filepath, mesh)\n \n\ndef extract_vertices(obj):\n nverts = len(obj.data.vertices)\n arr = np.zeros((nverts, 3), np.float32)\n for i in range(nverts):\n arr[i,:] = obj.data.vertices[i].co[:]\n return arr \n\ndef extract_vertices_by_face(obj):\n mesh = obj.data\n verts = []\n for p in mesh.polygons:\n for i in p.vertices:\n co = mesh.vertices[i].co[:]\n verts.append(co)\n return np.array(verts)\n\ndef mesh_to_numpy(mesh):\n nverts = len(mesh.vertices)\n verts = []\n for iv in range(nverts):\n verts.append(mesh.vertices[iv].co[:])\n \n faces = []\n for p in mesh.polygons:\n faces.append(p.vertices[:])\n\n edges = []\n for e in mesh.edges:\n edges.append(e.vertices[:])\n\n v_e = [[] for _ in range(nverts)]\n nedges = len(mesh.edges)\n for ie in range(nedges):\n e = mesh.edges[ie]\n iv_0 = e.vertices[0]\n iv_1 = e.vertices[1]\n v_e[iv_0].append(ie)\n v_e[iv_1].append(ie)\n\n v_f = [[] for _ in range(nverts)]\n nfaces = len(mesh.polygons)\n for ip in range(nfaces):\n p = mesh.polygons[ip]\n for iv in p.vertices:\n v_f[iv].append(ip)\n\n e_f = [[] for _ in range(nedges)]\n for ip in range(nfaces):\n p = mesh.polygons[ip]\n for il in p.loop_indices:\n l = mesh.loops[il]\n e_f[l.edge_index].append(ip)\n\n loops = [(l.vertex_index, l.edge_index) for l in mesh.loops]\n f_l = [[] for _ in range(nfaces)]\n for ip in range(nfaces):\n p = mesh.polygons[ip]\n for il in p.loop_indices:\n f_l[ip].append(il)\n\n mesh = {'verts':np.array(verts), 'faces':faces, 'edges': edges, 'loops': loops, 'f_l':f_l, 'v_e':v_e, 'v_f':v_f, 'e_f': e_f}\n\n return mesh\n\ndef slice_type(name):\n if ( 'Knee' in name) or ('Ankle' in name) or ('Thigh' in name) or ( 'Calf' in name) or ('Foot' in name) or ('UnderCrotch' in name):\n if name[0] == 'L':\n return 'LLEG'\n else: \n return 'RLEG'\n elif 'Elbow' in name or 'Wrist' in name or 'Hand' in name: \n return 'ARM'\n else:\n return 'TORSO'\n\ndef rect_plane(rect):\n point = np.mean(rect, axis=0)\n v0 = rect[2,:] - rect[0,:]\n v1 = rect[1,:] - rect[0,:]\n n = np.cross(v0, v1)\n return Vector(point), Vector(n).normalized()\n\ndef bone_location(arm_obj, bone, type):\n if type == 'head':\n return np.array((arm_obj.location + bone.head_local)[:])\n else:\n return np.array(( arm_obj.location + bone.tail_local)[:])\n \ndef extract_armature_bone_locations(obj):\n bones = obj.data.bones\n bdata = {}\n\n mappings = [\n ['LToe', 'foot.L', 'tail'],\n ['LHeel', 'heel.L', 'tail'],\n ['LAnkle', 'shin.L', 'tail'],\n ['LKnee', 'thigh.L', 'tail'],\n ['LHip', 'thigh.L', 'head'],\n ['Crotch', 'hips', 'head'],\n ['Spine', 'spine', 'head'],\n ['Chest', 'chest', 'head'],\n ['Neck', 'neck', 'head'],\n ['NeckEnd', 'neck', 'tail'],\n ['LShoulder', 'shoulder.L', 'tail'],\n ['LElbow', 'upper_arm.L', 'tail'],\n ['LWrist', 'forearm.L', 'tail'],\n ['LHand', 'hand.L', 'tail']]\n \n for m in mappings:\n bdata[m[0]] = bone_location(obj, bones[m[1]], m[2])\n if m[0][0] == 'L':\n m[0] = 'R' + m[0][1:]\n m[1] = m[1].replace('.L', '.R') \n bdata[m[0]] = bone_location(obj, bones[m[1]], m[2])\n \n return bdata \n \ndef slice_plane(mesh, slc_vert_idxs):\n centroid = Vector((0,0,0))\n n_vert = len(slc_vert_idxs)\n for v_idx in slc_vert_idxs:\n centroid += mesh.vertices[v_idx].co\n centroid /= float(n_vert)\n p0 = mesh.vertices[slc_vert_idxs[0]].co\n p1 = mesh.vertices[slc_vert_idxs[int(n_vert/2)]].co\n normal = (p1 - centroid).cross(p0-centroid)\n normal = normal.normalized()\n return centroid, normal\n \ndef calc_slice_location(amt_obj, ctl_obj, slc_vert_idxs):\n torso_bones = ['hips', 'spine', 'chest', 'neck', 'head']\n arm_bones = ['upper_arm.R', 'forearm.R', 'hand.R', 'upper_arm.L', 'forearm.L', 'hand.L']\n lleg_bones = ['thigh.L', 'shin.L', 'foot.L']\n rleg_bones = ['thigh.R', 'shin.R', 'foot.R']\n \n bones = amt_obj.data.bones\n ctl_mesh = ctl_obj.data\n \n slc_id_locs = {}\n \n for id, v_idxs in slc_vert_idxs.items():\n body_part = slice_type(id)\n if body_part == 'ARM':\n bone_ids = arm_bones\n elif body_part == 'LLEG': \n bone_ids = lleg_bones\n elif body_part == 'RLEG':\n bone_ids = rleg_bones\n else:\n bone_ids = torso_bones\n \n pln_p, pln_n = slice_plane(ctl_mesh, v_idxs)\n \n for bone_id in bone_ids:\n b = bones[bone_id]\n head = amt_obj.location + b.head_local\n tail = amt_obj.location + b.tail_local\n isct_p = geo.intersect_line_plane(head, tail, pln_p, pln_n)\n if isct_p is not None:\n if (isct_p - head).dot(tail-head) < 0.0:\n continue\n if (isct_p - head).length > (tail-head).length:\n continue\n\n slc_id_locs[id] = np.array(isct_p[:])\n break\n \n for id, val in slc_vert_idxs.items():\n if id not in slc_id_locs:\n print('failed location: ', id)\n \n if (len(slc_id_locs.keys()) != len(slc_rects.items())):\n print('failed to find all slice locations')\n \n return slc_id_locs \n\ndef body_part_dict():\n maps = {}\n maps['Part_LArm'] = 1\n maps['Part_RArm'] = 2\n maps['Part_LLeg'] = 3\n maps['Part_RLeg'] = 4\n maps['Part_Torso'] = 5\n maps['Part_Head'] = 6\n return maps\n\ndef extract_body_part_indices(obj, grp_mark):\n mesh = obj.data\n maps = body_part_dict() \n v_types = np.zeros(len(mesh.vertices), dtype=np.uint8) \n for v in mesh.vertices:\n ##assert len(v.groups) == 1\n for vgrp in v.groups:\n grp_name = obj.vertex_groups[vgrp.group].name\n bd_part_name = grp_name.split('.')[0]\n if bd_part_name in maps:\n id = maps[bd_part_name]\n v_types[v.index] = id\n return v_types\n\ndef clockwiseangle_and_distance(point, org):\n refvec = np.array([0, 1])\n # Vector between point and the origin: v = p - o\n vector = [point[0]-org[0], point[1]-org[1]]\n # Length of vector: \|\|v\|\|\n lenvector = np.hypot(vector[0], vector[1])\n # If length is zero there is no angle\n if lenvector == 0:\n return -np.pi, 0\n\n # Normalize vector: v/\|\|v\|\|\n normalized = [vector[0]/lenvector, vector[1]/lenvector]\n\n dotprod = normalized[0]refvec[0] + normalized[1]refvec[1] # x1x2 + y1y2\n diffprod = refvec[1]normalized[0] - refvec[0]normalized[1] # x1y2 - y1x2\n angle = np.arctan2(diffprod, dotprod)\n\n # Negative angles represent counter-clockwise angles so we need to subtract them\n # from 2pi (360 degrees)\n if angle < 0:\n return 2np.pi+angle, lenvector\n\n # I return first the angle because that's the primary sorting criterium\n # but if two vectors have the same angle then the shorter distance should come first.\n return angle, lenvector\n\ndef arg_sort_points_cw(points):\n center = (np.mean(points[:,0]), np.mean(points[:,1]))\n compare_func = lambda pair: clockwiseangle_and_distance(pair[1], center)\n points = sorted(enumerate(points), key = compare_func)\n return [pair[0] for pair in points[::-1]]\n\ndef sort_leg_slice_vertices(slc_vert_idxs, mesh_verts):\n X = mesh_verts[slc_vert_idxs][:,1]\n Y = mesh_verts[slc_vert_idxs][:,0]\n\n org_points = np.concatenate([X[:, np.newaxis], Y[:, np.newaxis]], axis=1)\n\n points_0 = np.concatenate([X[:, np.newaxis], Y[:, np.newaxis]], axis=1)\n arg_points_0 = arg_sort_points_cw(points_0)\n points_0 = np.array(points_0[arg_points_0, :])\n\n #find the starting point of the leg contour\n #the contour must start at that point to match the order of the prediction contour\n #check the leg contour in the blender file for why it is this way\n start_idx = np.argmin(points_0[:,1]) + 2\n points_0 = np.roll(points_0, axis=0, shift=-start_idx)\n\n #concatenate two sorted part.\n sorted_points = points_0\n\n #map indices\n slc_sorted_vert_idxs = []\n for i in range(sorted_points.shape[0]):\n p = sorted_points[i,:]\n dsts = np.sum(np.square(org_points - p), axis=1)\n closest_idx = np.argmin(dsts)\n assert closest_idx not in slc_sorted_vert_idxs\n slc_sorted_vert_idxs.append(slc_vert_idxs[closest_idx])\n\n #sorted_X = mesh_verts[slc_sorted_vert_idxs][:,0]\n #sorted_Y = mesh_verts[slc_sorted_vert_idxs][:,1]\n #plt.clf()\n #plt.axes().set_aspect(1)\n #plt.plot(points_0[:,0], points_0[:,1], '+r')\n #plt.plot(sorted_points[:5,0], sorted_points[:5,1],'-b')\n #plt.plot(sorted_X, sorted_Y,'-r')\n #plt.show()\n return slc_sorted_vert_idxs\n\ndef sort_torso_slice_vertices(slc_vert_idxs, mesh_verts, title =''):\n X = mesh_verts[slc_vert_idxs][:,1]\n Y = mesh_verts[slc_vert_idxs][:,0]\n\n org_points = np.concatenate([X[:, np.newaxis], Y[:, np.newaxis]], axis=1)\n\n #we needs to split our point array into two part because the clockwise sort just works on convex polygon. it will fail at strong concave points at crotch slice\n #sort the upper part\n mask_0 = Y >= -0.01\n X_0 = X[mask_0]\n Y_0 = Y[mask_0]\n assert (len(X_0) > 0 and len(Y_0) > 0)\n points_0 = np.concatenate([X_0[:, np.newaxis], Y_0[:, np.newaxis]], axis=1)\n arg_points_0 = arg_sort_points_cw(points_0)\n points_0 = np.array(points_0[arg_points_0, :])\n\n #find the first point of the contour\n #the contour must start at that point to match the order of the prediction contour\n #check the leg contour in the blender file for why it is this way\n min_y = np.inf\n min_y_idx = 0\n for i in range(points_0.shape[0]):\n if points_0[i,0] > 0:\n if points_0[i,1] < min_y:\n min_y = points_0[i,1]\n min_y_idx = i\n points_0 = np.roll(points_0, axis=0, shift=-min_y_idx)\n\n #sort the below part\n mask_1 = ~mask_0\n X_1 = X[mask_1]\n Y_1 = Y[mask_1]\n assert (len(X_1) > 0 and len(Y_1) > 0)\n points_1 = np.concatenate([X_1[:, np.newaxis], Y_1[:, np.newaxis]], axis=1)\n arg_points_1 = arg_sort_points_cw(points_1)\n points_1 = np.array(points_1[arg_points_1, :])\n\n #concatenate two sorted part.\n sorted_points = np.concatenate([points_0, points_1], axis=0)\n\n #map indices\n slc_sorted_vert_idxs = []\n for i in range(sorted_points.shape[0]):\n p = sorted_points[i,:]\n dsts = np.sum(np.square(org_points - p), axis=1)\n closest_idx = np.argmin(dsts)\n assert closest_idx not in slc_sorted_vert_idxs\n slc_sorted_vert_idxs.append(slc_vert_idxs[closest_idx])\n\n # sorted_X = mesh_verts[slc_sorted_vert_idxs][:,0]\n # sorted_Y = mesh_verts[slc_sorted_vert_idxs][:,1]\n # plt.clf()\n # plt.axes().set_aspect(1)\n # plt.plot(points_0[:,0], points_0[:,1], '+r')\n # plt.plot(sorted_points[:,0], sorted_points[:,1],'-b')\n # plt.plot(sorted_X, sorted_Y,'-r')\n # plt.title(title)\n #plt.show()\n return slc_sorted_vert_idxs\n\n\ndef is_torso_slice(id):\n torso_slc_ids= {'Crotch', 'Aux_Crotch_Hip_0', 'Aux_Crotch_Hip_1', 'Aux_Crotch_Hip_2', 'Hip', 'Waist', 'UnderBust', 'Aux_Hip_Waist_0',\n 'Aux_Waist_UnderBust_0', 'Aux_Waist_UnderBust_1',\n 'Aux_UnderBust_Bust_0', 'Bust', 'Armscye', 'Aux_Armscye_Shoulder_0', 'Shoulder'}\n if id in torso_slc_ids:\n return True\n else:\n return False\n\ndef is_leg_slice(id):\n leg_slc_ids = {'LKnee', 'RKnee', 'LUnderCrotch', 'RUnderCrotch', 'LAux_Knee_UnderCrotch_3', 'LAux_Knee_UnderCrotch_2', 'LAux_Knee_UnderCrotch_1', 'LAux_Knee_UnderCrotch_0'}\n if id in leg_slc_ids :\n return True\n else:\n return False\n\ndef extract_slice_vert_indices(ctl_obj):\n print(ctl_obj.name)\n mesh = ctl_obj.data\n\n mdata = mesh_to_numpy(mesh)\n ctl_verts = mdata['verts']\n\n slc_vert_idxs = defaultdict(list)\n for v in mesh.vertices:\n #assert len(v.groups) == 1\n for vgrp in v.groups:\n grp_name = ctl_obj.vertex_groups[vgrp.group].name\n slc_vert_idxs[grp_name].append(v.index)\n output = {}\n for slc_id, idxs in slc_vert_idxs.items():\n output[slc_id] = np.array(idxs) \n\n print('sortinng slice vertices counter clockwise, starting from the extreme point on the +X axis')\n for id, slc_idxs in output.items():\n if is_leg_slice(id):\n print('\\t\\t sort slice: ', id)\n slc_idxs = sort_leg_slice_vertices(slc_idxs, ctl_verts)\n output[id] = slc_idxs\n elif is_torso_slice(id):\n print('\\t\\t sort slice: ', id)\n slc_idxs = sort_torso_slice_vertices(slc_idxs, ctl_verts, title=id)\n output[id] = slc_idxs\n else:\n print('\\t\\t ignore slice: ', id)\n\n return output\n\ndef extract_body_part_face_indices(obj, grp_mark):\n mesh = obj.data\n n_faces = len(mesh.polygons)\n \n face_types = np.zeros(len(mesh.polygons), dtype=np.uint8)\n maps = body_part_dict() \n\n for pol in mesh.polygons:\n mat_idx = pol.material_index\n mat_name = obj.material_slots[mat_idx].name\n #hack. ControlMesh_Tri is duplicated from ControlMesh\n #therefore, its material name often has postfix .00N\n bd_part_name = mat_name.split('.')[0]\n assert bd_part_name in maps \n face_types[pol.index] = maps[bd_part_name]\n \n return face_types\n\ndef find_mirror_vertices(obj, group_name, error_threshold = 1e-3):\n mesh = obj.data\n my_verts = []\n my_verts_idxs = []\n for idx, v in enumerate(mesh.vertices):\n for vgrp in v.groups:\n grp_name = obj.vertex_groups[vgrp.group].name\n if grp_name == group_name:\n my_verts.append(v)\n my_verts_idxs.append(idx)\n\n assert len(my_verts) > 0\n\n mirror_idxs = []\n for mv in my_verts:\n mirror_co = deepcopy(mv.co)\n mirror_co.x = -mirror_co.x\n dsts = np.array([(mirror_co-ov.co).length for ov in mesh.vertices])\n idx = np.argmin(dsts)\n found_co = mesh.vertices[idx].co\n error = (found_co - mirror_co).length\n assert error < error_threshold, 'distance to found symmetric vertex is large'\n mirror_idxs.append(idx)\n\n assert len(my_verts_idxs) == len(mirror_idxs)\n\n pairs = [(idx_0, idx_1) for idx_0, idx_1 in zip(my_verts_idxs, mirror_idxs)]\n\n return pairs\n\nscene = bpy.context.scene\n\nOUT_DIR = '/home/khanhhh/data_1/projects/Oh/codes/human_estimation/data/meta_data/'\n\n\nslc_rects = {}\nfor obj in scene.objects:\n n_parts = len(obj.name.split('_'))\n if 'plane' in obj.name: \n if len(obj.data.vertices) != 4: \n print('something wrong', obj.name)\n\n pln_verts = extract_vertices_by_face(obj)\n id_3d = obj.name.replace('_plane','')\n slc_rects[id_3d] = pln_verts\n \narm_bone_locs = extract_armature_bone_locations(bpy.data.objects[\"Armature\"])\n\nslc_vert_idxs = extract_slice_vert_indices(bpy.context.scene.objects[\"ControlMesh\"])\n\nslc_id_locs = calc_slice_location(bpy.data.objects[\"Armature\"], bpy.data.objects[\"ControlMesh_Tri\"], slc_vert_idxs)\n \nctl_obj_tri = scene.objects['ControlMesh_Tri']\nctl_obj_tri_mesh = mesh_to_numpy(ctl_obj_tri.data)\n\nctl_obj_quad = scene.objects['ControlMesh']\nctl_obj_quad_mesh = mesh_to_numpy(ctl_obj_quad.data)\n\nvic_obj = scene.objects['VictoriaMesh']\nvic_obj_mesh = mesh_to_numpy(vic_obj.data)\n\nvic_v_body_parts = extract_body_part_indices(vic_obj, grp_mark = 'Part_')\nctl_f_body_parts = extract_body_part_face_indices(ctl_obj_tri, grp_mark ='Part_')\nprint('classified {0} faces of control mesh to body part'.format(ctl_f_body_parts.shape[0]))\nassert ctl_f_body_parts.shape[0] == len(ctl_obj_tri.data.polygons)\n\nheight_locs = extract_vertices(scene.objects['HeightSegment'])\n\nmirror_pairs = find_mirror_vertices(bpy.data.objects['ControlMesh'], 'LBody')\n\nvic_mirror_pairs = find_mirror_vertices(bpy.data.objects['VictoriaMesh'], 'LBody')\n\nfilepath = os.path.join(OUT_DIR, 'vic_data.pkl')\nwith open(filepath, 'wb') as f:\n data = {}\n data['slice_locs'] = slc_id_locs\n data['slice_vert_idxs'] = slc_vert_idxs\n data['arm_bone_locs'] = arm_bone_locs\n\n data['control_mesh_symmetric_vert_pairs'] = mirror_pairs\n \n data['control_mesh'] = ctl_obj_tri_mesh\n data['control_mesh_face_body_parts'] = ctl_f_body_parts\n data['control_mesh_quad_dom'] = ctl_obj_quad_mesh\n \n data['template_mesh'] = vic_obj_mesh\n data['template_height'] = np.linalg.norm(height_locs)\n data['template_vert_body_parts'] = vic_v_body_parts\n data['template_symmetric_vert_pairs'] = vic_mirror_pairs\n data['body_part_dict'] = {v:k for k,v in body_part_dict().items()}\n pickle.dump(data, f)\n\n\nvictoria = scene.objects['VictoriaMesh'] \nfor obj in scene.objects:\n n_parts = len(obj.name.split('_'))\n #if obj.name.split('_')[0][0] == 'L' and obj.name.split('_')[0][1].isdigit(): \n #plane_z = obj.data.vertices[0].co[2]\n #select_single_obj(obj)\n #isect(obj, victoria) \n #write_slices_to_obj(OUT_DIR, obj, plane_z)\n #print(obj.name)3 " }, { "alpha_fraction": 0.5241467952728271, "alphanum_fraction": 0.537235677242279, "avg_line_length": 39.73833084106445, "blob_id": "d0d173b87732081d1ce6fec652f6580e84d0ee7e", "content_id": "f202bf259a543a75edb5ffd09ec201c480b466fc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 28803, "license_type": "no_license", "max_line_length": 137, "num_lines": 707, "path": "/src/caesar_rbf_net.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.cluster import KMeans\nfrom sklearn.model_selection import train_test_split\nfrom pathlib import Path\nimport pickle\nimport argparse\nimport shutil\nfrom collections import defaultdict\nfrom keras.layers import Dense, Input\nfrom keras.models import Model\nfrom keras.callbacks import ModelCheckpoint\nfrom keras.optimizers import RMSprop, Adadelta\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.ensemble import ExtraTreesRegressor, RandomForestRegressor\nfrom sklearn.ensemble import GradientBoostingRegressor\nfrom sklearn.multioutput import MultiOutputRegressor\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.tree import export_graphviz\nfrom xgboost import XGBRegressor\n\nfrom dtreeviz.trees import \n\nimport src.util as util\nfrom src.error_files import mpii_error_slices, ucsc_error_slices\n\n\ndef kmeans(X, k):\n \"\"\"Performs k-means clustering for 1D input\n Arguments:\n X {ndarray} -- A Mx1 array of inputs\n k {int} -- Number of clusters\n Returns:\n ndarray -- A kx1 array of final cluster centers\n \"\"\"\n\n # randomly select initial clusters from input data\n clusters = np.random.choice(np.squeeze(X), size=k)\n prevClusters = clusters.copy()\n stds = np.zeros(k)\n converged = False\n\n while not converged:\n \"\"\"\n compute distances for each cluster center to each point \n where (distances[i, j] represents the distance between the ith point and jth cluster)\n \"\"\"\n distances = np.squeeze(np.abs(X[:, np.newaxis] - clusters[np.newaxis, :]))\n\n # find the cluster that's closest to each point\n closestCluster = np.argmin(distances, axis=1)\n\n # update clusters by taking the mean of all of the points assigned to that cluster\n for i in range(k):\n pointsForCluster = X[closestCluster == i]\n if len(pointsForCluster) > 0:\n clusters[i] = np.mean(pointsForCluster, axis=0)\n\n # converge if clusters haven't moved\n converged = np.linalg.norm(clusters - prevClusters) < 1e-6\n prevClusters = clusters.copy()\n\n distances = np.squeeze(np.abs(X[:, np.newaxis] - clusters[np.newaxis, :]))\n closestCluster = np.argmin(distances, axis=1)\n\n clustersWithNoPoints = []\n for i in range(k):\n pointsForCluster = X[closestCluster == i]\n if len(pointsForCluster) < 2:\n # keep track of clusters with no points or 1 point\n clustersWithNoPoints.append(i)\n continue\n else:\n stds[i] = np.std(X[closestCluster == i])\n\n # if there are clusters with 0 or 1 points, take the mean std of the other clusters\n if len(clustersWithNoPoints) > 0:\n pointsToAverage = []\n for i in range(k):\n if i not in clustersWithNoPoints:\n pointsToAverage.append(X[closestCluster == i])\n pointsToAverage = np.concatenate(pointsToAverage).ravel()\n stds[clustersWithNoPoints] = np.mean(np.std(pointsToAverage))\n\n return clusters, stds\n\nclass RBFNeuralNetwork():\n def __init__(self, n_cluster = 0, n_output = 0, no_regress_at_outputs= []):\n self.n_cluster = n_cluster\n self.n_output = n_output\n self.no_regress_at_outputs = no_regress_at_outputs\n for k in self.no_regress_at_outputs:\n assert 0<=k and k < n_output\n\n @staticmethod\n def load_from_path(path):\n with open(path, 'rb') as file:\n obj = pickle.load(file)\n return obj\n\n def save_to_path(self, path):\n with open(path, 'wb') as file:\n pickle.dump(self, file)\n\n def fit(self, X, Y):\n self.cluster_data(X)\n X_1 = self.transform_data(X)\n\n nan_mask = np.isnan(X_1)\n print(f'transformed_data: nan count: {np.sum(nan_mask[:])}')\n\n N = X.shape[0]\n X_train, X_test, train_idxs, test_idxs = train_test_split(X_1, np.arange(N), test_size=0.2, shuffle=True)\n X_train, X_valid, train_idxs, valid_idxs = train_test_split(X_train, train_idxs, test_size=0.2, shuffle=True)\n\n self.train_idxs = train_idxs\n self.valid_idxs = valid_idxs\n self.test_idxs = test_idxs\n Y_train = Y[train_idxs]\n Y_valid = Y[valid_idxs]\n Y_test = Y[test_idxs]\n\n input = Input(shape=(self.n_cluster,))\n x = Dense(units=32, activation='relu')(input)\n x = Dense(units=64, activation='relu')(x)\n x = Dense(units=64, activation='relu')(x)\n x = Dense(units=self.n_output)(x)\n model = Model(input=input, output = x)\n model.summary()\n model.compile(optimizer=RMSprop(), loss='mean_squared_error', metrics=['mean_squared_error'])\n epochs = 300\n history = model.fit(X_train, Y_train, validation_data=(X_valid, Y_valid), epochs=epochs, batch_size=32)\n self.regressor = model\n plt.plot(np.arange(epochs), history.history['loss'], '-b')\n plt.plot(np.arange(epochs), history.history['val_loss'], '-r')\n plt.show()\n\n # calc median of the first and last curvature for each cluster\n self.output_cluster_median = np.zeros(shape=(self.n_cluster, self.n_output))\n for cluster in range(self.n_cluster):\n for output_idx in range(self.n_output):\n features = Y[self.training_clusters == cluster]\n self.output_cluster_median[cluster, output_idx] = np.median(features[:, output_idx])\n\n def loss(self, X, Y):\n Y_hat = self.regressor.predict(X)\n for i in range(10):\n print('')\n print('y_hat', Y_hat[i,:])\n print('y ', Y[i,:])\n l = np.sqrt(np.mean((Y-Y_hat)*2))\n return l\n\n def predict(self, X):\n if len(X.shape) == 1:\n X = np.expand_dims(X, axis=0)\n\n cluster_ids = self.kmeans_cls.predict(X)\n\n X_1 = self.transform_data(X)\n preds = self.regressor.predict(X_1)\n\n for i in range(preds.shape[0]):\n preds[i, self.no_regress_at_outputs] = self.output_cluster_median[cluster_ids[i], self.no_regress_at_outputs]\n\n return preds\n\n def rbf(self, x, c, s):\n #print(2 s ** 2)\n return np.exp(-1 / (2 * s ** 2) * (x - c) 2)\n\n def transform_data(self, X):\n X_1 = []\n for i in range(X.shape[0]):\n a = np.array([self.rbf(X[i], c, s)[0] for c, s, in zip(self.cluster_mean, self.cluster_std)])\n X_1.append(a)\n X_1 = np.array(X_1)\n return X_1\n\n def cluster_data(self, X):\n self.kmeans_cls = KMeans(n_clusters=self.n_cluster, max_iter=1000, tol=1e-6, random_state=100).fit(X)\n self.training_clusters = self.kmeans_cls.predict(X)\n\n # calculate standard variance\n self.cluster_std = np.zeros(len(self.kmeans_cls.labels_), dtype=np.float32)\n self.cluster_mean = self.kmeans_cls.cluster_centers_.flatten()\n for l in range(self.n_cluster):\n cluster_mask = (self.training_clusters== l)\n points = X[cluster_mask].flatten()\n self.cluster_std[l] = np.std(points)\n\nclass RBFNet():\n def __init__(self, slc_id, n_cluster = 0, n_output = 0, no_regress_at_outputs= [], debug_mode = False):\n self.slc_id = slc_id\n self.debug_mode = debug_mode\n self.n_cluster = n_cluster\n self.no_regress_at_outputs = no_regress_at_outputs\n\n @staticmethod\n def load_from_path(path):\n with open(path, 'rb') as file:\n obj = pickle.load(file)\n return obj\n # self.n_cluster = data.n_cluster\n # self.n_output = data.n_output\n # self.no_regress_at_outputs = data.no_regress_at_outputs\n #\n # self.kmeans_cls = data.kmeans_cls\n # self.training_clusters = data.training_clusters\n #\n # self.cluster_std = data.cluster_std\n # self.cluster_mean = data.cluster_mean\n\n def save_to_path(self, path):\n with open(path, 'wb') as file:\n pickle.dump(self, file)\n\n def fit(self, X, Y):\n self.cluster_data(X)\n X_1 = self.transform_data(X)\n\n nan_mask = np.isnan(X_1)\n nan_mask = np.sum(nan_mask, axis=1) > 0\n print(f'transformed_data: nan count: {np.sum(nan_mask[:])}')\n if np.sum(nan_mask[:]) > 0:\n X_1 = X_1[~nan_mask, :]\n Y = Y[~nan_mask, :]\n\n N = X_1.shape[0]\n X_train, X_test, train_idxs, test_idxs = train_test_split(X_1, np.arange(N), test_size=0.2, shuffle=True, random_state=200)\n self.train_idxs = train_idxs\n self.test_idxs = test_idxs\n Y_train = Y[train_idxs]\n Y_test = Y[test_idxs]\n\n if self.debug_mode == True:\n self.X_train = X_train\n self.Y_train = Y_train\n\n search = False\n if search:\n parameters = {'n_estimators':[40, 60, 80, 100, 120], 'min_samples_leaf':[20, 40, 60, 80, 100, 120]}\n regressor = ExtraTreesRegressor(random_state=200)\n clf = GridSearchCV(regressor, parameters, cv = 5)\n clf.fit(X_train, Y_train)\n print(clf.best_estimator_)\n self.regressor = clf.best_estimator_\n else:\n #self.regressor = ExtraTreesRegressor(random_state=200, n_estimators=100, min_samples_leaf=100)\n self.regressor = MultiOutputRegressor(RandomForestRegressor(n_estimators=100, min_samples_leaf=50))\n self.regressor.fit(X_train, Y_train)\n\n #self.regressor = XGBRegressor().fit(X_train, Y_train)\n #self.regressor = GradientBoostingRegressor(params).fit(X_train, Y_train)\n print('regression score on train set: ', self.regressor.score(X_train, Y_train))\n print('regression score on test set: ', self.regressor.score(X_test, Y_test))\n print('regression score on test mse loss: ', self.loss(X_test, Y_test))\n\n # calc median of the first and last curvature for each cluster\n n_ouput = Y.shape[1]\n self.output_cluster_median = np.zeros(shape=(self.n_cluster, n_ouput))\n for cluster in range(self.n_cluster):\n for output_idx in range(n_ouput):\n features = Y[self.training_clusters == cluster]\n self.output_cluster_median[cluster, output_idx] = np.median(features[:, output_idx])\n\n def loss(self, X, Y):\n Y_hat = self.regressor.predict(X)\n l = np.sqrt(np.mean((Y-Y_hat)*2))\n return l\n\n def visualize_regressor(self, DIR):\n is_viz = True\n if is_viz:\n for i, forest in enumerate(self.regressor.estimators_):\n for j, tree in enumerate(forest.estimators_):\n viz = dtreeviz(tree,\n self.X_train,\n self.Y_train[:,i],\n feature_names=[str(i) for i in range(self.n_cluster)],\n target_name=f'target_{i}')\n viz.save(f'{DIR}/{slc_id}/{i}_{j}.svg')\n\n def visualize_an_obsevation(self, x, DIR, file_name = ''):\n X = np.expand_dims(x, axis=0)\n X_1 = self.transform_data(X)\n for i, forest in enumerate(self.regressor.estimators_):\n for j, tree in enumerate(forest.estimators_):\n viz = dtreeviz(tree,\n self.X_train,\n self.Y_train[:, i],\n feature_names=[str(i) for i in range(self.n_cluster)],\n target_name=f'target_{i}',\n X = X_1.flatten())\n viz.save(f'{DIR}/{self.slc_id}/{file_name}_{i}_{j}.svg')\n\n return self.regressor.predict(X_1)\n\n def predict(self, X):\n if len(X.shape) == 1:\n X = np.expand_dims(X, axis=0)\n\n cluster_ids = self.kmeans_cls.predict(X)\n\n X_1 = self.transform_data(X)\n preds = self.regressor.predict(X_1)\n\n for i in range(preds.shape[0]):\n preds[i, self.no_regress_at_outputs] = self.output_cluster_median[cluster_ids[i], self.no_regress_at_outputs]\n\n return preds\n\n def rbf(self, x, c, s):\n #print(2 s ** 2)\n return np.exp(-1 / (2 * s ** 2) * (x - c) ** 2)\n\n def transform_data(self, X):\n X_1 = []\n for i in range(X.shape[0]):\n a = np.array([self.rbf(X[i], c, s)[0] for c, s, in zip(self.cluster_mean, self.cluster_std)])\n X_1.append(a)\n X_1 = np.array(X_1)\n return X_1\n\n def cluster_data(self, X):\n rd = 100\n while True:\n self.kmeans_cls = KMeans(n_clusters=self.n_cluster, max_iter=1000, tol=1e-6, random_state=rd).fit(X)\n self.training_clusters = self.kmeans_cls.predict(X)\n\n # calculate standard variance\n self.cluster_std = np.zeros(self.n_cluster, dtype=np.float32)\n self.cluster_mean = self.kmeans_cls.cluster_centers_.flatten()\n for l in range(self.n_cluster):\n cluster_mask = (self.training_clusters== l)\n points = X[cluster_mask].flatten()\n self.cluster_std[l] = np.std(points)\n\n zero_mask = np.isclose(self.cluster_std, 0.0)\n if np.sum(zero_mask) == 0:\n break\n else:\n print(f'cluster std is zero, reduced cluster: {self.n_cluster - 1}. repeat again', file=sys.stderr)\n self.n_cluster -= 1\n rd = np.random.randint(0, 10000)\n\ndef normalize_contour(X,Y, center):\n X = X-center[0]\n Y = Y-center[1]\n dsts = np.sqrt(np.square(X) + np.square(Y))\n mean_dst = np.max(dsts)\n X = X / mean_dst\n Y = Y / mean_dst\n return X, Y\n\nimport os\ndef plot_contour_correrlation(IN_DIR, DEBUG_DIR, K):\n ratios = []\n contours = []\n for path in Path(DEBUG_DIR).glob('.'):\n os.remove(str(path))\n\n for path in Path(IN_DIR).glob(\".\"):\n with open(str(path), 'rb') as file:\n data = pickle.load(file)\n w = data['W']\n d = data['D']\n ratios.append(w/d)\n contours.append(data['cnt'])\n\n n_contour = len(ratios)\n ratios = np.array(ratios).reshape(n_contour, 1)\n kmeans = KMeans(n_clusters=K)\n cnt_labels = kmeans.fit_predict(ratios)\n for l in kmeans.labels_:\n l_contour_idxs = np.argwhere(cnt_labels==l)[:,0]\n cls_center = kmeans.cluster_centers_[l]\n cluster_mask = (cnt_labels == l)\n points = ratios[cluster_mask].flatten()\n std = np.std(points)\n plt.clf()\n plt.axes().set_aspect(1.0)\n #cnt_centers = [util.contour_center(contours[i][:,0], contours[i][:,1]) for i in l_contour_idxs]\n #cnt_centers = np.array(cnt_centers)\n #mean_center = np.mean(cnt_centers, axis=0)\n for idx in l_contour_idxs:\n contour = contours[idx]\n X = contour[0,:]\n Y = contour[1,:]\n X,Y = normalize_contour(X,Y, util.contour_center(X,Y))\n X0 = X[0].reshape(-1)\n X = np.concatenate([X, X0], axis=0)\n Y0 = Y[0].reshape(-1)\n Y = np.concatenate([Y, Y0], axis=0)\n plt.plot(X, Y, '-b')\n plt.title(f'n_contour_in_cluster = {len(l_contour_idxs)}\\n center = {cls_center}, inertia={std}')\n\n plt.savefig(f'{DEBUG_DIR}/label_{l}.png')\n\ndef slice_model_config():\n config = defaultdict(set)\n\n config['Shoulder'] = {'n_cluster':12, 'n_output':12, 'no_regress_at_outputs':[]}\n\n config['Armscye'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[]}\n config['Bust'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[]}\n config['Aux_UnderBust_Bust_0'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[]}\n config['UnderBust'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[]}\n config['Crotch'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[0, 7]}\n\n config['Aux_Crotch_Hip_0'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[0, 7]}\n config['Aux_Crotch_Hip_1'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[0, 7]}\n config['Hip'] = {'n_cluster':12, 'n_output':10, 'no_regress_at_outputs':[0, 7]}\n\n config['UnderCrotch'] = {'n_cluster':12, 'n_output':9, 'no_regress_at_outputs':[]}\n config['Aux_Knee_UnderCrotch_3'] = {'n_cluster':12, 'n_output':9, 'no_regress_at_outputs':[]}\n config['Aux_Knee_UnderCrotch_2'] = {'n_cluster':12, 'n_output':9, 'no_regress_at_outputs':[]}\n config['Aux_Knee_UnderCrotch_1'] = {'n_cluster':12, 'n_output':9, 'no_regress_at_outputs':[]}\n config['Aux_Knee_UnderCrotch_0'] = {'n_cluster':12, 'n_output':9, 'no_regress_at_outputs':[]}\n config['Knee'] = {'n_cluster':12, 'n_output':9, 'no_regress_at_outputs':[]}\n return config\n\ndef load_bad_slice_names(DIR, slc_id):\n txt_path = None\n for path in Path(DIR).glob('.'):\n if slc_id == path.stem:\n txt_path = path\n break\n\n if txt_path is None:\n print(f'missing bad slice path of slice {slc_id}', file=sys.stderr)\n return ()\n else:\n names = set()\n with open(str(txt_path), 'r') as file:\n for name in file.readlines():\n name = name.replace('\\n','')\n names.add(name)\n return names\n\ndef print_statistic(X, Y):\n mean = np.mean(Y, axis=0)\n median = np.median(Y, axis=0)\n std = np.std(Y, axis=0)\n max = np.max(Y, axis=0)\n min = np.min(Y, axis=0)\n np.set_printoptions(suppress=True)\n print('Target Y statistics: ')\n for i in range(mean.shape[0]):\n print(f'\\tY[{i}] mean, median, std, max, min = {mean[i]}, {median[i]}, {std[i]}, {max[i]}, {min[i]}' )\n\n print('nan count: ', np.isnan(X).flatten().sum())\n print('nan count: ', np.isnan(Y).flatten().sum())\n print('inf count: ', np.isinf(X).flatten().sum())\n print('inf count: ', np.isinf(Y).flatten().sum())\n\ndef plot_all_contour_correlation():\n #plot correlation\n # print('plotting correlation k-means')\n # for path in Path(IN_DIR).glob(''):\n # slc_id = path.stem\n # if slc_id in slc_ids:\n #\n # model_config = model_configs[slc_id]\n # K = model_config['n_cluster'] if 'n_cluster' in model_config else 12\n #\n # CORR_DIR = f'{DEBUG_DIR}{slc_id}_correlation/'\n # os.makedirs(CORR_DIR, exist_ok=True)\n # plot_contour_correrlation(str(path), CORR_DIR, K)\n # exit()\n pass\n\nimport sys\nfrom copy import copy, deepcopy\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--input\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-c\", \"--code\", required=True, help=\"contour code\")\n ap.add_argument(\"-d\", \"--debug\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-m\", \"--model\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-b\", \"--bad_slice_dir\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-ids\", \"--slc_ids\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-test_infer\", \"--test_inference\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-train_infer\", \"--train_inference\", required=True, help=\"input meta data file\")\n\n args = vars(ap.parse_args())\n IN_DIR = args['input']\n CODE_DIR = args['code']\n DEBUG_DIR = args['debug']\n MODEL_DIR_ROOT = args['model']\n BAD_SLICE_DIR = args['bad_slice_dir']\n slc_ids = args['slc_ids']\n do_test_infer = int(args['test_inference']) > 0\n do_train_infer = int(args['train_inference']) > 0\n\n all_slc_ids = [path.stem for path in Path(IN_DIR).glob('./')]\n if slc_ids == 'all':\n slc_ids = all_slc_ids\n else:\n slc_ids = slc_ids.split(',')\n for id in slc_ids:\n assert id in all_slc_ids, f'{id}: unrecognized slice id'\n\n model_configs = slice_model_config()\n\n code_type = Path(CODE_DIR).stem\n MODEL_DIR = f'{MODEL_DIR_ROOT}/{code_type}/'\n os.makedirs(MODEL_DIR, exist_ok=True)\n\n #load data from disk\n for SLC_DIR in Path(IN_DIR).glob(''):\n\n slc_id = SLC_DIR.stem\n\n if slc_id in slc_ids:\n\n MODEL_PATH = f'{MODEL_DIR}/{SLC_DIR.stem}.pkl'\n\n OUTPUT_DEBUG_DIR_TRAIN = f'{DEBUG_DIR}/{SLC_DIR.stem}_prediction/train/'\n OUTPUT_DEBUG_DIR_TEST = f'{DEBUG_DIR}/{SLC_DIR.stem}_prediction/test/'\n shutil.rmtree(OUTPUT_DEBUG_DIR_TEST, ignore_errors=True)\n shutil.rmtree(OUTPUT_DEBUG_DIR_TRAIN, ignore_errors=True)\n os.makedirs(OUTPUT_DEBUG_DIR_TRAIN, exist_ok=True)\n os.makedirs(OUTPUT_DEBUG_DIR_TEST, exist_ok=True)\n\n model_config = model_configs[slc_id]\n K = model_config['n_cluster'] if 'n_cluster' in model_config else 12\n\n #collect all slices\n X = []; Y = []; W = []; D = []; contours = []\n slc_id = SLC_DIR.stem\n print('start training slice mode: ', slc_id)\n bad_slc_names = load_bad_slice_names(BAD_SLICE_DIR, slc_id)\n\n SLC_CODE_DIR = f'{CODE_DIR}/{slc_id}/'\n\n all_paths = [path for path in Path(SLC_CODE_DIR).glob('.')]\n for path in all_paths:\n\n if path.stem in bad_slc_names:\n continue\n\n with open(str(path),'rb') as file:\n record = pickle.load(file)\n w = record['W']\n d = record['D']\n\n if w == 0.0 or d == 0.0:\n print('zero w or d: ', w, d, file=sys.stderr)\n continue\n\n feature = record['Code']\n\n if np.isnan(feature).flatten().sum() > 0:\n print(f'nan feature: {path}', file=sys.stderr)\n continue\n\n if np.isnan(X).flatten().sum() > 0:\n print(f'nan X: {path}', file=sys.stderr)\n continue\n\n if np.isinf(feature).flatten().sum() > 0:\n print(f'inf feature: {path}', file=sys.stderr)\n continue\n\n if np.isinf(X).flatten().sum() > 0:\n print(f'inf X: {path}', file=sys.stderr)\n continue\n\n X.append(w/d)\n Y.append(feature)\n W.append(w)\n D.append(d)\n\n slc_path = f'{SLC_DIR}/{path.stem}.pkl'\n with open(slc_path, 'rb') as file:\n record = pickle.load(file)\n contours.append(record['cnt'])\n\n N = len(X)\n X = np.array(X)\n Y = np.array(Y)\n X = np.reshape(X, (-1, 1))\n\n #print_statistic(X, Y)\n\n if code_type == 'fourier':\n n_output = None\n no_regress_at_outputs = []\n else:\n n_output = model_config['n_output'] if 'n_output' in model_config else 10\n no_regress_at_outputs = model_config['no_regress_at_outputs'] if 'no_regress_at_outputs' in model_config else [0, 7]\n\n use_tree = True\n if use_tree:\n net = RBFNet(slc_id=slc_id, n_cluster=K, n_output=n_output, no_regress_at_outputs=no_regress_at_outputs, debug_mode=True)\n net.fit(X, Y)\n net.save_to_path(MODEL_PATH)\n #debug\n #VIZ_DEBUG_DIR = f'{DEBUG_DIR}/tree_viz/'\n #test_id = 45\n #preds = net.visualize_an_obsevation(X[test_id,:], VIZ_DEBUG_DIR, test_id.__str__())\n #print(f'prediction result of {test_id}: {preds}')\n else:\n net = RBFNeuralNetwork(n_cluster=K, n_output=n_output, no_regress_at_outputs=no_regress_at_outputs)\n net.fit(X, Y)\n net.save_to_path(MODEL_PATH)\n\n net_1 = RBFNet.load_from_path(MODEL_PATH)\n\n if do_test_infer:\n\n for i in range(len(net.test_idxs)):\n idx = net_1.test_idxs[i]\n\n print('processing test idx: ', idx)\n pred = net_1.predict(np.expand_dims(X[idx, :], axis=0))[0, :]\n\n w = W[idx]\n d = D[idx]\n contour = contours[idx]\n center = util.contour_center(contour[0, :], contour[1, :])\n\n if code_type == 'fourier':\n res_contour = util.reconstruct_contour_fourier(pred.flatten())\n res_contour_org = np.copy(res_contour)\n res_range_x = np.max(res_contour[0,:]) - np.min(res_contour[0,:])\n range_x = np.max(contour[0,:]) - np.min(contour[0,:])\n scale_x = range_x / res_range_x\n\n res_range_y = np.max(res_contour[1,:]) - np.min(res_contour[1,:])\n range_y = np.max(contour[1,:]) - np.min(contour[1,:])\n scale_y = range_y / res_range_y\n\n res_contour[0,:] = scale_x\n res_contour[1,:] = scale_y\n\n res_contour_org = max(scale_x, scale_y)\n\n error = np.sqrt(np.mean(np.square(res_contour_org - res_contour)))\n print(f'\\tmean error uniform scale vs non-uniform scale = {error}')\n #print(f'prediction = {pred}')\n\n else:\n if util.is_leg_contour(slc_id):\n res_contour = util.reconstruct_leg_slice_contour(pred, d, w)\n else:\n res_contour = util.reconstruct_torso_slice_contour(pred, d, w, mirror=True)\n\n\n res_contour[0, :] += center[0]\n res_contour[1, :] += center[1]\n last_p = res_contour[:,0].reshape(2,1)\n res_contour = np.concatenate([res_contour, last_p], axis=1)\n\n res_contour_org[0, :] += center[0]\n res_contour_org[1, :] += center[1]\n last_p = res_contour_org[:,0].reshape(2,1)\n res_contour_org = np.concatenate([res_contour_org, last_p], axis=1)\n\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(contour[0, :], contour[1, :], '-b')\n\n plt.plot(res_contour_org[0, :], res_contour_org[1, :], '-y')\n\n plt.plot(res_contour[0, :], res_contour[1, :], '-r')\n plt.plot(res_contour[0, :], res_contour[1, :], '+r')\n plt.plot(res_contour[0, 0], res_contour[1, 0], '+r', ms=20)\n plt.plot(res_contour[0, 2], res_contour[1, 2], '+g', ms=20)\n plt.savefig(f'{OUTPUT_DEBUG_DIR_TEST}{idx}.png')\n #plt.show()\n\n if do_train_infer:\n for i in range(len(net.train_idxs)):\n idx = net.train_idxs[i]\n print('processing train idx: ', idx)\n w = W[idx]\n d = D[idx]\n contour = contours[idx]\n pred = net_1.predict(np.expand_dims(X[idx, :], axis=0))[0, :]\n if code_type == 'fourier':\n res_contour = util.reconstruct_contour_fourier(pred.flatten())\n res_range_x = np.max(res_contour[0, :]) - np.min(res_contour[0, :])\n range_x = np.max(contour[0, :]) - np.min(contour[0, :])\n scale_x = range_x / res_range_x\n\n res_range_y = np.max(res_contour[1, :]) - np.min(res_contour[1, :])\n range_y = np.max(contour[1, :]) - np.min(contour[1, :])\n scale_y = range_y / res_range_y\n\n res_contour[0, :] = scale_x\n res_contour[1, :] = scale_y\n else:\n res_contour = util.reconstruct_torso_slice_contour(pred, d, w, mirror=True)\n\n center = util.contour_center(contour[0, :], contour[1, :])\n res_contour[0, :] += center[0]\n res_contour[1, :] += center[1]\n last_p = res_contour[:,0].reshape(2,1)\n res_contour = np.concatenate([res_contour, last_p], axis=1)\n plt.clf()\n plt.axes().set_aspect(1)\n #plt.plot(contour[0, :], contour[1, :], '-b')\n plt.plot(res_contour[0, :], res_contour[1, :], '-r')\n plt.plot(res_contour[0, :], res_contour[1, :], '+r')\n plt.savefig(f'{OUTPUT_DEBUG_DIR_TRAIN}{idx}.png')\n\n" }, { "alpha_fraction": 0.5802980065345764, "alphanum_fraction": 0.5852649211883545, "avg_line_length": 28.487804412841797, "blob_id": "b20550be4786e3d7c705da23269548fd16fcfa79", "content_id": "75e082fdbd92fc6a65637adafd73b10755af7cf5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1208, "license_type": "no_license", "max_line_length": 87, "num_lines": 41, "path": "/src/util_split_male_female_tool.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import pickle\nfrom pathlib import Path\nimport shutil\nimport os\n\ndef split_male_females():\n path = '/home/khanhhh/data_1/projects/Oh/data/3d_human/debug/caesar_obj_gender.pkl'\n\n OUT_DIR = '/home/khanhhh/data_1/projects/Oh/data/3d_human/'\n OUT_MALE_DIR = f'{OUT_DIR}/caesar_obj_male/'\n OUT_FEMALE_DIR = f'{OUT_DIR}/caesar_obj_female/'\n os.makedirs(OUT_MALE_DIR, exist_ok=True)\n os.makedirs(OUT_FEMALE_DIR, exist_ok=True)\n\n IN_OBJ_DIR = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/'\n\n males = set()\n females = set()\n with open(path, 'rb') as file:\n genders = pickle.load(file)\n for name, gender in genders.items():\n if gender == True:\n females.add(name)\n else:\n males.add(name)\n\n for path in Path(IN_OBJ_DIR).glob('.obj'):\n if '_ld' in path.stem:\n continue\n if path.stem in males:\n dest_path = f'{OUT_MALE_DIR}/{path.name}'\n else:\n dest_path = f'{OUT_FEMALE_DIR}/{path.name}'\n\n shutil.copy(str(path), dest_path)\n\n print('females: ', len(females))\n print('males: ', len(males))\n\nif __name__ == '__main__':\n split_male_females()" }, { "alpha_fraction": 0.7746835350990295, "alphanum_fraction": 0.7822784781455994, "avg_line_length": 48.375, "blob_id": "cf06dc913c68e28bbc68aca6dbc5cbf6e05587c1", "content_id": "a5dbdc11a9c37cc4ab3d0c98bd76fdf73a5d1cfd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 790, "license_type": "no_license", "max_line_length": 114, "num_lines": 16, "path": "/README.txt", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "# human_estimation\n1. set up enviroment \n\tconda create --name human_estimation\n\tconda install -n human_estimation -c conda-forge opencv \n\tconda install -n human_estimation scipy numpy matplotlib\n\tconda activate human_estimation\n\n2. what does shape_key_analyze do?\n this code preprocesses silhouette projections from Blender\n and compare silhouettes of each shape-key at values of 0 and 1\n \n3. instruction to analysize silhouete from blender's silhouette projections\t\n\t- download blender projects: victoria_silhouette_projection.zip\n \t- run two blender projects to project 3D models to front and side silhouettes (update the output directories)\n \t- update directories in the file shape_key_analyze.py to point to blender silhouette directories\n \t- run shape_key_analyze.py\n" }, { "alpha_fraction": 0.5553784966468811, "alphanum_fraction": 0.5701195001602173, "avg_line_length": 31.354839324951172, "blob_id": "189122f8dc3974659c0996e7c4a9074be74de13d", "content_id": "db827ef2bd91157886263e8ac7487797a02a9028", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5020, "license_type": "no_license", "max_line_length": 137, "num_lines": 155, "path": "/src/slice_preprocess.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nfrom scipy.interpolate import splprep, splev\nimport argparse\nimport os\nimport matplotlib.pyplot as plt\nfrom pathlib import Path\nfrom src.obj_util import load_vertices, export_vertices\nfrom tsp_solver.greedy import solve_tsp\nimport pickle\n\ndef hack_fix_noise_vertices(slice):\n good_candidate_z = np.median(slice[:,2], axis=0)\n epsilon = 0.00001\n slice_1 = []\n noise_cnt = 0\n for i in range(slice.shape[0]):\n co = slice[i, :]\n if np.abs(co[2] - good_candidate_z) < epsilon:\n slice_1.append(co)\n else:\n noise_cnt+=1\n\n return np.array(slice_1), noise_cnt\n\ndef resample_slice(slice, n_point, debug_path = None):\n pts = slice[:,:2]\n\n centroid = np.mean(pts, axis=0)\n\n #sort clock wise\n D = np.zeros(shape=(pts.shape[0], pts.shape[0]), dtype=np.float32)\n for i in range(pts.shape[0]):\n dsts = np.linalg.norm(pts - pts[i,:], axis=1)\n D[i,:] =dsts\n path = solve_tsp(D, optim_steps=5000)\n pts_s = pts[path, :]\n xp = pts_s[:,0]\n yp = pts_s[:,1]\n\n #remove noise\n okay = np.where(np.abs(np.diff(xp)) + np.abs(np.diff(yp)) > 0)\n xp = np.r_[xp[okay], xp[-1], xp[0]]\n yp = np.r_[yp[okay], yp[-1], yp[0]]\n\n tck, u = splprep([xp, yp], u=None, s=0.0, per=1)\n u_new = np.linspace(u.min(), u.max(), n_point)\n x_new, y_new = splev(u_new, tck, der=0)\n\n slice_new = np.vstack([x_new, y_new, np.zeros_like(y_new)]).T\n slice_new[:,2] = np.median(slice[:,2])\n\n if debug_path is not None:\n centroid_new = np.array([np.mean(x_new), np.mean(y_new)])\n plt.clf()\n plt.plot(centroid[0], centroid[1], 'ro')\n plt.plot(centroid_new[0], centroid_new[1], 'yo')\n plt.plot(xp, yp, 'ro')\n plt.plot(x_new, y_new, 'yo')\n plt.plot(x_new, y_new, 'b--')\n plt.savefig(debug_path)\n\n return slice_new\n\nimport sys\ndef map_slice_location_to_slices(slices, locs):\n loc_map = {}\n for i in range(locs.shape[0]):\n loc = locs[i,:]\n closest_slice_id = None\n #find slices which has the closest z\n min_dst = 999999999\n for id, slice in slices.items():\n dst = np.linalg.norm(loc - np.mean(slice, axis=0))\n if dst < min_dst:\n min_dst = dst\n closest_slice_id = id\n\n if closest_slice_id is None:\n print(f'cannot map slice location {loc}', file=sys.stderr)\n\n z = loc[2]\n z_adjust = np.median(slices[closest_slice_id][:,2])\n tolerance = 0.01\n if np.abs(z-z_adjust) > tolerance:\n print(f'warning, something wrong. z slice location is larger than {tolerance}', file=sys.stderr)\n\n if closest_slice_id in loc_map:\n print(f'ERROR: something wrong. another location: {loc} is mapped to the same slice id: {closest_slice_id}', file=sys.stderr)\n\n print(f'adjust z location of slice {closest_slice_id}: z_old = {z}, z_adjust = {z_adjust}, delta = {np.abs(z-z_adjust)}')\n locs[i,2] = z_adjust\n\n loc_map[closest_slice_id] = locs[i,:]\n\n return loc_map\n\ndef is_a_leg_slice(name):\n leg_hints=['Knee', 'Thigh', 'Ankle', 'Calf']\n for hint in leg_hints:\n if hint in name:\n return True\n return False\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--in_dir\", required=True, help=\"slice obj directory\")\n ap.add_argument(\"-o\", \"--out_dir\", required=True, help=\"directory for expxorting control mesh slices\")\n args = vars(ap.parse_args())\n\n DIR_IN = args['in_dir']\n DIR_OUT = args['out_dir']\n DIR_DEBUG = Path(os.path.abspath(__file__))\n DIR_DEBUG = str(DIR_DEBUG.parent) + '/../data/debug/'\n\n for fpath in Path(DIR_OUT).glob('.'):\n os.remove(fpath)\n\n slices = {}\n for fpath in Path(DIR_IN).glob('.obj'):\n if 'slice_location' in str(fpath):\n continue\n\n print(fpath)\n debug_path = f'{DIR_DEBUG}{fpath.stem}.png'\n print(debug_path)\n #if 'L14_Shoulder' not in str(fpath):\n # continue\n\n slice = load_vertices(fpath)\n slice, removed_cnt = hack_fix_noise_vertices(slice)\n if removed_cnt > 0:\n print(f'remove {removed_cnt} vertices: {fpath.stem}')\n\n if is_a_leg_slice(fpath.stem):\n resolution = 10012\n else:\n resolution = 1008\n slice = resample_slice(slice, n_point=resolution, debug_path=debug_path)\n assert slice.shape[0] == resolution\n\n slices[fpath.stem] = slice\n\n export_vertices(f'{DIR_OUT}/{fpath.name}', slice)\n\n for fpath in Path(DIR_IN).glob('.pkl'):\n if 'victoria' in str(fpath):\n with open(fpath, 'rb') as f:\n data = pickle.load(f)\n\n slice_locs = data['slice_locs']\n loc_map = map_slice_location_to_slices(slices, slice_locs)\n data['slice_locs'] = slice_locs\n\n with open(f'{DIR_OUT}/{fpath.stem}.pkl', 'wb') as f:\n pickle.dump(data, f)\n\n\n\n\n\n" }, { "alpha_fraction": 0.5062922835350037, "alphanum_fraction": 0.5451470613479614, "avg_line_length": 31.025188446044922, "blob_id": "55cfad5910dd12c0317c9ec08f6883e0c5c962c8", "content_id": "e2d6ce8f44fd7b97172d9f2249f244b80c544fdc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 12714, "license_type": "no_license", "max_line_length": 160, "num_lines": 397, "path": "/src/util.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport matplotlib.pyplot as plt\nfrom shapely.geometry import LinearRing, LineString, Point, Polygon, MultiPoint\nfrom shapely.ops import nearest_points\nimport shapely.affinity as affinity\nimport math\nfrom numpy.linalg import norm\n\ndef normalize(vec):\n len = np.linalg.norm(vec)\n if len > 0:\n return vec/len\n else:\n return vec\n\n#line dir must be normalized\ndef mirror_point_through_axis(line_p, line_dir, p):\n v = p-line_p\n a = np.dot(v, line_dir)\n proj = line_p + aline_dir\n return proj + (proj-p)\n\ndef furthest_points_line(points ,line_p, line_dir):\n dsts = np.zeros(shape=(points.shape[0],), dtype=np.float)\n for i in range(points.shape[0]):\n dsts[i] = abs(dst_point_line(points[i,:], line_p, line_dir))\n return np.argmax(dsts)\n\ndef closest_point_points(point, points):\n g0 = Point(point)\n if len(points) > 1:\n g1 = MultiPoint(points)\n closest = nearest_points(g0, g1)[1]\n return np.array([closest.x, closest.y])\n else:\n return np.array([g0.x, g0.y])\n\ndef rect_plane(rect):\n n = np.cross(rect[2]-rect[0], rect[1]-rect[0])\n n = n / np.linalg.norm(n)\n p = np.mean(rect, axis=0)\n return p,n\n\ndef dst_point_plane(point, plane_point, plane_norm):\n return np.dot(plane_norm, point - plane_point)\n\ndef dst_point_line(point, line_p, line_dir):\n v = point-line_p\n n = np.array([-line_dir[1], line_dir[0]])\n return np.dot(v, n)\n\ndef calc_triangle_local_basis(verts, tris):\n basis = np.zeros((len(tris),4, 3), dtype=np.float32)\n for i, t in enumerate(tris):\n basis[i, 0, :] = verts[t[0]]\n basis[i, 1, :] = verts[t[1]] - verts[t[0]]\n basis[i, 2, :] = verts[t[2]] - verts[t[0]]\n basis[i, 3, :] = normalize(np.cross(basis[i, 1, :], basis[i, 2, :]))\n return basis\n\nfrom scipy.ndimage import filters\ndef smooth_contour(X, Y, sigma=3):\n X_1 = filters.gaussian_filter1d(X, sigma=sigma)\n Y_1 = filters.gaussian_filter1d(Y, sigma=sigma)\n return X_1, Y_1\n\ndef isect_line_line(p1, p2, p3, p4):\n a = (p1[0]-p3[0])(p3[1]-p4[1]) - (p1[1]-p3[1])(p3[0]-p4[0])\n b = (p1[0]-p2[0])(p3[1]-p4[1]) - (p1[1]-p2[1])(p3[0]-p4[0])\n t = a/b\n p = np.array([p1[0]+t(p2[0]-p1[0]), p1[1]+t(p2[1]-p1[1])])\n return p\n\ndef closest_on_quad_to_point_v3(p, a, b, c, d):\n p_0 = closest_on_tri_to_point_v3(p, a, b, c)\n p_1 = closest_on_tri_to_point_v3(p, a, c, d)\n if norm(p - p_0) < norm(p - p_1):\n return p_0\n else:\n return p_1\n\n# * Set 'r' to the point in triangle (a, b, c) closest to point 'p' /\ndef closest_on_tri_to_point_v3(p, a, b, c):\n #Check if P in vertex region outside A\n ab = b-a\n ac = c-a\n ap = p-a\n d1 = np.dot(ab, ap)\n d2 = np.dot(ac, ap)\n if d1 <= 0.0 and d2 <= 0.0:\n return a\n\n # Check if P in vertex region outside B\n bp = p-b\n d3 = np.dot(ab, bp)\n d4 = np.dot(ac, bp)\n if d3 > 0.0 and d4 <= d3:\n return b\n\n #check if P in edge region of AB, if so return projection of P onto AB\n vc = d1 d4 - d3 * d2\n if vc <= 0.0 and d1 >= 0.0 and d3 <= 0.0:\n v = d1 / (d1 - d3)\n #barycentric coordinates (1-v,v,0)\n return a + v * ab\n\n #Check if P in vertex region outside C\n cp = p-c\n d5 = np.dot(ab, cp)\n d6 = np.dot(ac, cp)\n if d6 >= 0.0 and d5 <= d6:\n # barycentric coordinates (0,0,1)\n return c\n\n #Check if P in edge region of AC, if so return projection of P onto AC\n vb = d5 * d2 - d1 * d6\n if vb <= 0.0 and d2 >= 0.0 and d6 <= 0.0:\n w = d2 / (d2 - d6)\n #barycentric coordinates (1-w,0,w)\n return a + w * ac\n\n #Check if P in edge region of BC, if so return projection of P onto BC\n va = d3 * d6 - d5 * d4\n if va <= 0.0 and (d4 - d3) >= 0.0 and (d5 - d6) >= 0.0:\n w = (d4 - d3) / ((d4 - d3) + (d5 - d6))\n #barycentric coordinates (0,1-w,w)\n return b + w(c - b)\n\n # P inside face region. Compute Q through its barycentric coordinates (u,v,w)\n denom = 1.0 / (va + vb + vc)\n v = vb denom\n w = vc * denom\n # a + ab * v + ac * w\n return a + ab * v + ac * w\n\ndef is_leg_contour(name):\n leg_names = ['UnderCrotch', 'Aux_Knee_UnderCrotch_0', 'Aux_Knee_UnderCrotch_1', 'Aux_Knee_UnderCrotch_2', 'Aux_Knee_UnderCrotch_3', 'Knee', 'Calf', 'Ankle']\n if name in leg_names:\n return True\n else:\n return False\n\ndef is_torso_contour(name):\n torso_slc_ids = {'Crotch', 'Aux_Crotch_Hip_0', 'Aux_Crotch_Hip_1', 'Aux_Crotch_Hip_2',\n 'Hip', 'Aux_Hip_Waist_0', 'Waist',\n 'Aux_Waist_UnderBust_0', 'Aux_Waist_UnderBust_1',\n 'UnderBust',\n 'Aux_UnderBust_Bust_0', 'Bust', 'Armscye', 'Aux_Armscye_Shoulder_0', 'Shoulder'}\n if name in torso_slc_ids:\n return True\n else:\n return False\n\ndef contour_center(X, Y):\n idx_ymax, idx_ymin = np.argmax(Y), np.argmin(Y)\n center_y = 0.5 * (Y[idx_ymax] + Y[idx_ymin])\n center_x = X[idx_ymin]\n return np.array([center_x, center_y])\n\nfrom scipy.interpolate import splprep, splev\ndef resample_contour(X, Y, n_point):\n tck, u = splprep([X, Y], s=0)\n u_1 = np.linspace(0.0, 1.0, n_point)\n X, Y = splev(u_1, tck)\n return X, Y\n\nfrom scipy.fftpack import fft2, ifft2, fft, ifft, dct, idct\ndef calc_fourier_descriptor(X, Y, resolution, use_radial = False, path_debug = None):\n np.set_printoptions(suppress=True)\n cnt_complex = np.array([np.complex(x,y) for x, y in zip(X,Y)])\n #cnt_complex = cnt_complex[:int(cnt_complex.shape[0]/2)]\n half = int(resolution/2)\n tf_0 = fft(cnt_complex)\n if resolution % 2 == 0:\n tf_1 = np.concatenate([tf_0[0:half], tf_0[-half:]])\n else:\n tf_1 = np.concatenate([tf_0[0:half+1], tf_0[-half:]])\n\n #db_dif = tf_1[0:half] - tf_1[-half:]\n #print(db_dif)\n if path_debug is not None:\n res_contour = ifft(tf_1)\n\n res_contour = np.concatenate([np.real(res_contour).reshape(-1,1), np.imag(res_contour).reshape(-1, 1)], axis=1)\n\n res_range_x = np.max(res_contour[:,0]) - np.min(res_contour[:, 0])\n range_x = np.max(X) - np.min(X)\n scale_x = range_x / res_range_x\n\n res_range_y = np.max(res_contour[:,1]) - np.min(res_contour[:,1])\n range_y = np.max(Y) - np.min(Y)\n scale_y = range_y / res_range_y\n\n res_contour = max(scale_x, scale_y)\n\n plt.clf()\n plt.axes().set_aspect(1.0)\n plt.plot(X, Y, '-b')\n plt.plot(X[:2], Y[:2], '+b')\n plt.plot(res_contour[:,0], res_contour[:,1], '-r')\n plt.plot(res_contour[:,0], res_contour[:,1], '+r', ms=5)\n plt.plot(res_contour[0,1], res_contour[0,1], '+r', ms=10)\n plt.plot(res_contour[1,1], res_contour[1,1], '+g', ms=10)\n for i in range(res_contour.shape[0]):\n p = res_contour[i,:]\n plt.plot([0, p[0]], [0, p[1]], '-r', ms=10)\n plt.savefig(path_debug)\n pass\n\n #normalize\n tf_1 = tf_1 / norm(tf_1[1])\n #cut off the center\n fcode = []\n tf = tf_1[1:]\n if use_radial:\n angle = np.angle(tf)\n value = np.absolute(tf)\n for i in range(tf.shape[0]):\n fcode.append(angle[i])\n fcode.append(value[i])\n else:\n for i in range(tf.shape[0]):\n t = tf[i]\n fcode.append(np.real(t))\n fcode.append(np.imag(t))\n\n return np.array(fcode)\n\n\nfrom scipy.fftpack import ifft\ndef reconstruct_contour_fourier(fourier, use_radal = False):\n n = len(fourier)\n fouriers = []\n fouriers.append(np.complex(0.0, 0.0))\n if use_radal:\n for i in range(0, n, 2):\n angle = fourier[i]\n value = fourier[i+1]\n cpl = value np.exp(np.complex(real=0.0, imag=angle))\n fouriers.append(cpl)\n else:\n for i in range(0, n, 2):\n real = fourier[i]\n img = fourier[i+1]\n fouriers.append(np.complex(real, img))\n\n cpl_contour = ifft(fouriers)\n X = np.real(cpl_contour)\n Y = np.imag(cpl_contour)\n return np.concatenate([X.reshape(1, -1), Y.reshape(1, -1)], axis=0)\n\ndef reconstruct_leg_slice_contour(feature, D, W):\n p0 = np.array([Dfeature[-2]feature[-1], 0])\n n_points = len(feature) -1\n prev_p = p0\n points = []\n points.append(prev_p)\n\n angle_step = 2.0np.pi / float(n_points)\n for i in range(1, n_points):\n angle = float(i)angle_step\n\n l0_p0 = prev_p\n l0_p1 = prev_p + np.array([1.0, feature[i-1]])\n\n l1_p0 = np.array([0.0, 0.0])\n l1_p1 = np.array([np.cos(angle), np.sin(angle)])\n\n isct = isect_line_line(l0_p0, l0_p1, l1_p0, l1_p1)\n\n points.append(isct)\n\n prev_p = isct\n\n X = np.array([p[0] for p in points])\n Y = np.array([p[1] for p in points])\n\n return np.vstack([X, Y])\n\ndef reconstruct_torso_slice_contour(feature, D, W, mirror = False):\n p0 = np.array([Dfeature[-2]feature[-1], 0])\n n_points = len(feature) - 2\n half_idx = int(np.ceil(n_points / 2.0))\n assert half_idx == 4 or half_idx == 5\n\n prev_p = p0\n\n points = []\n points.append(prev_p)\n\n angle_step = np.pi / float(n_points)\n for i in range(1, n_points+1):\n angle = float(i)angle_step\n #TODO\n # if i == 4:\n # x, y = 0.0, W/2.0\n # else:\n # x = (prev_p[1] - feature[i] prev_p[0]) / (np.tan(angle) - feature[i])\n # y = np.tan(angle) * x\n #prev_p = np.array([x,y])\n #points.append(prev_p)\n\n # test\n l0_p0 = prev_p\n l0_p1 = prev_p + np.array([1.0, feature[i-1]])\n\n l1_p0 = np.array([0.0, 0.0])\n if i == half_idx:\n l1_p1 = np.array([0, W/2])\n elif i < half_idx:\n l1_p1 = np.array([1.0, np.tan(angle)])\n else:\n l1_p1 = np.array([-1.0, -np.tan(angle)])\n\n isct = isect_line_line(l0_p0, l0_p1, l1_p0, l1_p1)\n\n points.append(isct)\n\n prev_p = isct\n\n #print(isct[0] - x, isct[1] - y)\n #plt.plot([l0_p0[0], l0_p1[0]], [l0_p0[1], l0_p1[1]], 'r-')\n #plt.plot([l1_p0[0], l1_p1[0]], [l1_p0[1], l1_p1[1]], 'b-')\n #plt.plot(isct[0], isct[1], 'b+')\n\n X = np.array([p[0] for p in points])\n Y = np.array([p[1] for p in points])\n\n if mirror == True:\n X_mirror = X[1:-1][::-1]\n Y_mirror = -Y[1:-1][::-1]\n\n X = np.concatenate([X,X_mirror], axis=0)\n Y = np.concatenate([Y,Y_mirror], axis=0)\n\n return np.vstack([X, Y])\n\ndef align_torso_contour(X, Y, anchor_pos_x = True, debug_path = None):\n idx_ymax, idx_ymin = np.argmax(Y), np.argmin(Y)\n center_y = 0.5 * (Y[idx_ymax] + Y[idx_ymin])\n center_x = X[idx_ymin]\n\n if debug_path is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(X, Y, 'b+')\n plt.plot(center_x, center_y, 'r+')\n\n contour = Polygon([(x,y) for x, y in zip(X,Y)])\n contour_1 = contour.simplify(0.01, preserve_topology=False)\n contour_2 = contour_1.convex_hull\n for p in contour_2.exterior.coords:\n plt.plot(p[0], p[1], 'r+', ms=7)\n\n #find the anchor segment\n n_point = len(contour_2.exterior.coords)\n anchor_p1 = None\n anchor_p2 = None\n for i in range(n_point):\n p0 = np.array(contour_2.exterior.coords[i])\n p1 = np.array(contour_2.exterior.coords[(i+1)%n_point])\n c = 0.5(p0+p1)\n ymin = min(p0[1], p1[1])\n ymax = max(p0[1], p1[1])\n if (anchor_pos_x == True and c[0] > center_x) or (anchor_pos_x == False and c[0] < center_x):\n if ymin <= center_y and center_y <= ymax:\n anchor_p1 = p0\n anchor_p2 = p1\n if anchor_p1[1] > anchor_p2[1]:\n anchor_p1, anchor_p2 = anchor_p2, anchor_p1\n\n if anchor_p1 is None or anchor_p2 is None:\n return None, None\n\n dir_1 = anchor_p2 - anchor_p1\n anchor_dir = dir_1 / norm(dir_1)\n anchor_dir[1] = abs(anchor_dir[1])\n\n #rotate the contour to align the anchor line\n angle = math.acos(np.dot(anchor_dir, np.array([0, 1])))\n if anchor_dir[0] < 0:\n angle = -angle\n\n contour_aligned = affinity.rotate(contour, angle = angle, origin=Point(anchor_p1), use_radians=True)\n X_algn = [p[0] for p in contour_aligned.exterior.coords]\n Y_algn = [p[1] for p in contour_aligned.exterior.coords]\n\n if debug_path is not None:\n plt.plot(anchor_p1[0], anchor_p1[1], 'r+', ms=14)\n plt.plot(anchor_p2[0], anchor_p2[1], 'r+', ms=14)\n plt.plot([anchor_p1[0], anchor_p2[0]], [anchor_p1[1], anchor_p2[1]], 'r-', ms=14)\n\n plt.plot(X_algn, Y_algn, 'r-')\n plt.savefig(debug_path)\n #plt.show()\n\n return np.array(X_algn), np.array(Y_algn)\n" }, { "alpha_fraction": 0.4442250728607178, "alphanum_fraction": 0.45705825090408325, "avg_line_length": 29.636363983154297, "blob_id": "8d88ea6f2e0e1c64eccd24c1c1fc3b6c81d0a8d9", "content_id": "bdc18a932c0ed0b07613def39b723fb3a4014901", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1013, "license_type": "no_license", "max_line_length": 83, "num_lines": 33, "path": "/src/obj_util.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\n\ndef export_vertices(fpath, obj):\n with open(fpath, 'w') as f:\n for i in range(obj.shape[0]):\n co = tuple(obj[i, :])\n f.write(\"v %.8f %.8f %.8f \\n\" % co)\n\ndef export_mesh(fpath, verts, faces, add_one = True):\n with open(fpath, 'w') as f:\n for i in range(verts.shape[0]):\n co = tuple(verts[i, :])\n f.write(\"v %.8f %.8f %.8f \\n\" % co)\n\n for i in range(len(faces)):\n f.write(\"f\")\n for v_idx in faces[i]:\n if add_one == True:\n v_idx += 1\n f.write(\" %d\" % (v_idx))\n f.write(\"\\n\")\n\ndef load_vertices(fpath):\n coords = []\n with open(fpath, 'r') as obj:\n file = obj.read()\n lines = file.splitlines()\n for line in lines:\n elem = line.split()\n if elem:\n if elem[0] == 'v':\n coords.append((float(elem[1]), float(elem[2]), float(elem[3])))\n return np.array(coords)\n\n\n" }, { "alpha_fraction": 0.6158113479614258, "alphanum_fraction": 0.6171983480453491, "avg_line_length": 30.30434799194336, "blob_id": "e64c44c9e95c3135e5263a61028e3b6d3fc1f5c9", "content_id": "a294b127d93eff5eaf6b9b4657b77b079abdb9af", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 721, "license_type": "no_license", "max_line_length": 86, "num_lines": 23, "path": "/src/caesar_slc_model_test.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport argparse\nimport sys\nfrom pathlib import Path\nfrom src.caesar_rbf_net import RBFNet\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--in_dir\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-m\", \"--model\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-ids\", \"--model_ids\", required=True, help=\"input meta data file\")\n\n args = vars(ap.parse_args())\n\n SLC_DIR = args['in_dir']\n MODEL_DIR = args['model']\n ids = args['model_ids'].split(',')\n\n for path in Path(MODEL_DIR).glob('.pkl'):\n if len(ids) > 0 and path.stem not in ids:\n continue\n\n net = RBFNet.load_from_path(path)\n\n" }, { "alpha_fraction": 0.543535053730011, "alphanum_fraction": 0.5626134276390076, "avg_line_length": 37.092750549316406, "blob_id": "bfdca65822e36cb9a0b118a5757d9adce7477489", "content_id": "972fcab6efcde9c7c6a9f0052c2e00b7d8995f2b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 22591, "license_type": "no_license", "max_line_length": 136, "num_lines": 593, "path": "/src/control_mesh.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport argparse\nimport os\nfrom pathlib import Path\nimport pickle\nfrom numpy.linalg import norm\nfrom src.obj_util import export_mesh\nimport src.util as util\nimport shapely.geometry as geo\nfrom shapely.ops import nearest_points\nfrom src.caesar_rbf_net import RBFNet\nimport matplotlib.pyplot as plt\nfrom scipy.spatial import cKDTree, KDTree\nfrom copy import copy\n\ndef slice_id_3d_2d_mappings():\n mappings = {}\n mappings['LAnkle'] = 'Ankle'\n mappings['RAnkle'] = 'Ankle'\n\n mappings['RCalf'] = 'Calf'\n mappings['LCalf'] = 'Calf'\n\n mappings['RKnee'] = 'Knee'\n mappings['LKnee'] = 'Knee'\n\n mappings['LAux_Knee_UnderCrotch_0'] = 'Aux_Knee_UnderCrotch_0'\n mappings['LAux_Knee_UnderCrotch_1'] = 'Aux_Knee_UnderCrotch_1'\n mappings['LAux_Knee_UnderCrotch_2'] = 'Aux_Knee_UnderCrotch_2'\n mappings['LAux_Knee_UnderCrotch_3'] = 'Aux_Knee_UnderCrotch_3'\n mappings['RAux_Knee_UnderCrotch_0'] = 'Aux_Knee_UnderCrotch_0'\n mappings['RAux_Knee_UnderCrotch_1'] = 'Aux_Knee_UnderCrotch_1'\n mappings['RAux_Knee_UnderCrotch_2'] = 'Aux_Knee_UnderCrotch_2'\n mappings['RAux_Knee_UnderCrotch_3'] = 'Aux_Knee_UnderCrotch_3'\n\n mappings['RUnderCrotch'] = 'UnderCrotch'\n mappings['LUnderCrotch'] = 'UnderCrotch'\n\n mappings['Crotch'] = 'Crotch'\n mappings['Aux_Crotch_Hip_0'] = 'Aux_Crotch_Hip_0'\n mappings['Aux_Crotch_Hip_1'] = 'Aux_Crotch_Hip_1'\n mappings['Aux_Crotch_Hip_2'] = 'Aux_Crotch_Hip_2'\n\n mappings['Hip'] = 'Hip'\n mappings['Aux_Hip_Waist_0'] = 'Aux_Hip_Waist_0'\n mappings['Waist'] = 'Waist'\n mappings['Aux_Waist_UnderBust_0'] = 'Aux_Waist_UnderBust_0'\n mappings['Aux_Waist_UnderBust_1'] = 'Aux_Waist_UnderBust_1'\n mappings['UnderBust'] = 'UnderBust'\n mappings['Aux_UnderBust_Bust_0'] = 'Aux_UnderBust_Bust_0'\n mappings['Bust'] = 'Bust'\n mappings['Armscye'] = 'Armscye'\n mappings['Aux_Armscye_Shoulder_0'] = 'Aux_Armscye_Shoulder_0'\n mappings['Shoulder'] = 'Shoulder'\n mappings['Collar'] = 'Collar'\n mappings['Neck'] = 'Neck'\n return mappings\n\ndef breast_part_slice_id_3d_2d_mappings():\n id_2ds = ['Breast_Depth_Aux_UnderBust_Bust_0', 'Breast_Depth_Bust', 'Breast_Depth_Aux_Bust_Armscye_0']\n mappings = {}\n for id_2d in id_2ds:\n mappings['R' + id_2d] = id_2d\n\n for id_2d in id_2ds:\n mappings['L' + id_2d] = id_2d\n return mappings\n\ndef bone_lengths(arm_2d, ratio):\n lengths = {}\n lengths['Shin'] = rationorm(arm_2d['LAnkle'] - arm_2d['LKnee'])\n lengths['Thigh'] = rationorm(arm_2d['LHip'] - arm_2d['LKnee'])\n lengths['Torso'] = rationorm(arm_2d['MidHip'] - arm_2d['Neck'])\n lengths['Shoulder'] = rationorm(arm_2d['LShoulder'] - arm_2d['Neck'])\n lengths['UpperArm'] = rationorm(arm_2d['LShoulder'] - arm_2d['LElbow'])\n lengths['ForeArm'] = rationorm(arm_2d['LElbow'] - arm_2d['LWrist'])\n return lengths\n\ndef scale_tpl_armature(arm_3d, arm_2d, ratio):\n #leg\n blengths = bone_lengths(arm_2d, ratio)\n arm_3d['LKnee'] = arm_3d['LAnkle'] + blengths['Shin']util.normalize(arm_3d['LKnee'] - arm_3d['LAnkle'])\n arm_3d['LHip'] = arm_3d['LKnee'] + blengths['Thigh']util.normalize(arm_3d['LHip'] - arm_3d['LKnee'])\n arm_3d['RKnee'] = arm_3d['RAnkle'] + blengths['Shin']util.normalize(arm_3d['RKnee'] - arm_3d['RAnkle'])\n arm_3d['RHip'] = arm_3d['RKnee'] + blengths['Thigh']util.normalize(arm_3d['RHip'] - arm_3d['RKnee'])\n\n midhip = 0.5(arm_3d['LHip'] + arm_3d['RHip'])\n arm_3d['Neck'] = midhip + blengths['Torso']util.normalize(arm_3d['Neck'] - midhip)\n #TODO: Crotch, Spine, Chest\n\n arm_3d['LShoulder'] = arm_3d['Neck'] + blengths['Shoulder']util.normalize(arm_3d['LShoulder'] - arm_3d['Neck'])\n arm_3d['RShoulder'] = arm_3d['Neck'] + blengths['Shoulder']util.normalize(arm_3d['RShoulder'] - arm_3d['Neck'])\n\n arm_3d['LElbow'] = arm_3d['LShoulder'] + blengths['UpperArm']util.normalize(arm_3d['LElbow'] - arm_3d['LShoulder'])\n arm_3d['RElbow'] = arm_3d['RShoulder'] + blengths['UpperArm']util.normalize(arm_3d['RElbow'] - arm_3d['RShoulder'])\n\n arm_3d['LWrist'] = arm_3d['LElbow'] + blengths['ForeArm']util.normalize(arm_3d['LWrist'] - arm_3d['LElbow'])\n arm_3d['RWrist'] = arm_3d['RElbow'] + blengths['ForeArm']util.normalize(arm_3d['RWrist'] - arm_3d['RElbow'])\n\n return arm_3d\n\ndef subdivide_catmull_temp(mesh):\n verts = mesh['verts']\n faces = mesh['faces']\n edges = mesh['edges']\n loops = mesh['loops'] #l[0]: vertex, l[1]: edge\n\n nv = len(verts)\n nf = len(faces)\n ne = len(edges)\n\n e_f = mesh['e_f']\n v_f = mesh['v_f']\n v_e = mesh['v_e']\n f_l = mesh['f_l']\n\n new_vert_pnts = np.zeros(shape=(nv,3), dtype=np.float32)\n new_edge_pnts = np.zeros(shape=(ne,3), dtype=np.float32)\n new_face_pnts = np.zeros(shape=(nf,3), dtype=np.float32)\n\n for f_idx in range(nf):\n co = np.zeros(shape=(3,), dtype=np.float32)\n f = faces[f_idx]\n for vf_idx in f:\n co += verts[vf_idx, :]\n co /= len(f)\n new_face_pnts[f_idx, :] = co\n\n for e_idx in range(ne):\n co = np.zeros(shape=(3,))\n for ef_idx in e_f[e_idx]:\n co += new_face_pnts[ef_idx,:]\n\n ev0 = edges[e_idx][0]\n ev1 = edges[e_idx][1]\n co += verts[ev0,:]\n co += verts[ev1,:]\n new_edge_pnts[e_idx, :] = co/(2.0 + len(e_f[e_idx]))\n\n for v_idx in range(nv):\n co_avg_f = np.zeros(shape=(3,))\n co_avg_e = np.zeros(shape=(3,))\n\n nvf = len(v_f[v_idx])\n for vf_idx in v_f[v_idx]:\n co_avg_f += new_face_pnts[vf_idx, :]\n co_avg_f /= nvf\n\n nve = len(v_e[v_idx])\n for ve_idx in v_e[v_idx]:\n co_avg_e += new_edge_pnts[ve_idx, :]\n co_avg_e /= nve\n\n #not a boundary vertex\n if nve == nvf:\n new_vert_pnts[v_idx, :] = (co_avg_f + 2.0co_avg_e + (nve - 3.0) verts[v_idx, :]) / nve\n else:\n new_vert_pnts[v_idx, :] = verts[v_idx,:]\n\n #create new topology\n new_vert_pnts = np.concatenate([new_vert_pnts, new_face_pnts, new_edge_pnts], axis=0)\n new_faces = []\n for f_idx in range(nf):\n nl = len(f_l[f_idx])\n for idx in range(nl):\n l_0 = loops[f_l[f_idx][idx]]\n l_1 = loops[f_l[f_idx][(idx + 1) % nl]]\n v0 = nv + nf + l_0[1]\n v1 = l_1[0]\n v2 = nv + nf + l_1[1]\n v3 = nv + f_idx\n new_faces.append((v0, v1, v2, v3))\n\n new_mesh = {'verts':new_vert_pnts, 'faces': new_faces}\n\n return new_mesh\n\ndef projec_mesh_onto_mesh(mesh_0, mesh_0_vert_idxs, mesh_1):\n verts_0 = mesh_0['verts']\n nv_0 = len(verts_0)\n\n faces_1 = mesh_1['faces']\n verts_1 = mesh_1['verts']\n nf_1 = len(faces_1)\n\n centroid_faces_1 = np.zeros(shape=(nf_1, 3), dtype=np.float)\n for f_idx in range(nf_1):\n\n co = np.zeros(shape=(3,), dtype=np.float32)\n for v_idx in faces_1[f_idx]:\n co += verts_1[v_idx,:]\n co /= len(faces_1[f_idx])\n\n centroid_faces_1[f_idx, :] = co\n\n # out_path = f'{OUT_DIR}{mdata_path.stem}_debug_centroid_faces.obj'\n # print(f'\\toutput deformed mesh to {out_path}')\n # export_mesh(out_path, centroid_faces_1, [])\n\n # out_path = f'{OUT_DIR}{mdata_path.stem}_debug_mesh_0.obj'\n # print(f'\\toutput deformed mesh to {out_path}')\n # export_mesh(out_path, verts_0, [])\n\n# tree = cKDTree(centroid_faces_1, leafsize=5)\n tree = KDTree(centroid_faces_1, leafsize=5)\n\n if mesh_0_vert_idxs is None:\n mesh_0_vert_idxs = range(nv_0)\n\n for v_idx in mesh_0_vert_idxs:\n v_co = verts_0[v_idx,:]\n #query closest faces\n _, idxs = tree.query(v_co, 5)\n cls_dst = np.inf\n cls_pnt = v_co\n for f_idx in idxs:\n f = faces_1[f_idx]\n assert len(f) == 4\n on_quad_p = util.closest_on_quad_to_point_v3(v_co, verts_1[f[0],:], verts_1[f[1],:], verts_1[f[2],:], verts_1[f[3],:])\n dst = norm(on_quad_p - v_co)\n if dst < cls_dst:\n cls_dst = dst\n #cls_pnt = 0.25(verts_1[f[0],:] + verts_1[f[1],:] + verts_1[f[2],:] + verts_1[f[3],:])\n cls_pnt = on_quad_p\n verts_0[v_idx, :] = cls_pnt\n\n #out_path = f'{OUT_DIR}{mdata_path.stem}_debug_projected.obj'\n #print(f'\\toutput deformed mesh to {out_path}')\n #export_mesh(out_path, np.array(test_points), [])\n\n#the basis origin of armature is the midhip position\ndef transform_non_vertical_slice(slice, loc, loc_after, radius):\n slice_n = slice - loc\n rads = norm(slice_n, axis=1)\n max_rad = np.max(rads)\n scale = radius / max_rad\n slice_n = scale\n return loc_after + slice_n\n\ndef scale_vertical_slice(slice, w_ratio, d_ratio, scale_center = None):\n if scale_center is None:\n scale_center = np.mean(slice, axis=0)\n nslice = slice - scale_center\n nslice[:,0] = w_ratio\n nslice[:,1] = d_ratio\n nslice = nslice + scale_center\n return nslice\n\nfrom copy import deepcopy\ndef deform_template_mesh(org_mesh, effect_vert_tri_idxs, vert_weights, vert_UVWs, ctl_df_basis, deform_vert_idxs = None):\n df_mesh = deepcopy(org_mesh)\n df_verts = df_mesh['verts']\n nv = len(df_verts)\n\n if deform_vert_idxs == None:\n deform_vert_idxs = range(nv)\n\n for i in deform_vert_idxs:\n df_co = np.zeros(3, np.float32)\n W = 0.0\n for idx, ev_idx in enumerate(effect_vert_tri_idxs[i]):\n df_basis = ctl_df_basis[ev_idx,:,:]\n uvw = vert_UVWs[i][idx]\n co = df_basis[0,:] + uvw[0]df_basis[1,:]+ uvw[1]df_basis[2,:]+ uvw[2]df_basis[3,:]\n w_tri = vert_weights[i][idx]\n df_co += w_tri co\n W += w_tri\n if W > 0:\n df_co /= W\n df_verts[i,:] = df_co\n return df_mesh\n\ndef transform_arm_slices(mesh, slc_id_locs, slc_id_vert_idxs, arm_3d):\n slc_org = slc_id_locs['Slice_LElbow']\n slc_idxs = slc_id_vert_idxs['Slice_LElbow']\n slice = ctl_mesh['verts'][slc_idxs]\n radius = h_ratio * 0.5 * seg_dst_f['Elbow']\n mesh['verts'][slc_idxs, :] = transform_non_vertical_slice(slice, slc_org, arm_3d['LElbow'], radius)\n\n slc_org = slc_id_locs['Slice_LWrist']\n slc_idxs = slc_id_vert_idxs['Slice_LWrist']\n slice = ctl_mesh['verts'][slc_idxs]\n wrist_radius = h_ratio * 0.5 * 0.8 * seg_dst_f['Elbow']\n mesh['verts'][slc_idxs, :] = transform_non_vertical_slice(slice, slc_org, arm_3d['LWrist'], wrist_radius)\n\n slc_org = slc_id_locs['Slice_RElbow']\n slc_idxs = slc_id_vert_idxs['Slice_RElbow']\n slice = ctl_mesh['verts'][slc_idxs]\n radius = h_ratio * 0.5 * seg_dst_f['Elbow']\n mesh['verts'][slc_idxs, :] = transform_non_vertical_slice(slice, slc_org, arm_3d['RElbow'], radius)\n\n slc_org = slc_id_locs['Slice_LWrist']\n slc_idxs = slc_id_vert_idxs['Slice_LWrist']\n slice = ctl_mesh['verts'][slc_idxs]\n wrist_radius = h_ratio * 0.5 * 0.8 * seg_dst_f['Elbow']\n mesh['verts'][slc_idxs, :] = transform_non_vertical_slice(slice, slc_org, arm_3d['LWrist'], wrist_radius)\n\n lhand_idxs = []\n for id, idxs in slc_id_vert_idxs.items():\n if 'LHand' in id:\n lhand_idxs.append(idxs[:])\n displacement = arm_3d['LWrist'] - slc_id_locs['Slice_LWrist']\n mesh['verts'][lhand_idxs, :] += displacement\n\n rhand_idxs = []\n for id, idxs in slc_id_vert_idxs.items():\n if 'RHand' in id:\n rhand_idxs.append(idxs[:])\n displacement = arm_3d['RWrist'] - slc_id_locs['Slice_RWrist']\n mesh['verts'][rhand_idxs, :] += displacement\n\ndef is_breast_segment(id_seg_2d):\n if id_seg_2d == 'Aux_UnderBust_Bust_0' or \\\n id_seg_2d == 'Bust' or \\\n id_seg_2d == 'Aux_Bust_Armscye_0':\n return True\n else:\n return False\n\n#note: this function just works for breast slice\ndef scale_breast_height(brst_slc, slc_height):\n #hack\n #find two ending points of the breast slice\n #1. the point with smallest x\n end_0_idx = np.argmin(brst_slc[:,0])\n #2. the point with lagrest y\n end_1_idx = np.argmax(brst_slc[:,1])\n brst_hor_seg = geo.LineString([brst_slc[end_0_idx,:2], brst_slc[end_1_idx,:2]])\n\n #3: breast highest height\n cur_brst_height = 0.0\n for i in range(brst_slc.shape[0]):\n if i != end_0_idx and i != end_1_idx:\n p = brst_slc[i,:2]\n dst = geo.Point(p).distance(brst_hor_seg)\n cur_brst_height = max(dst, cur_brst_height)\n\n ratio = slc_height/cur_brst_height\n\n for i in range(brst_slc.shape[0]):\n if i != end_0_idx and i != end_1_idx:\n p = brst_slc[i,:2]\n proj = nearest_points(brst_hor_seg, geo.Point(p))[0]\n proj = np.array(proj).flatten()\n p_scaled = proj + ratio(p-proj)\n brst_slc[i,:2] = p_scaled\n\n brst_slc[end_0_idx, 2] = brst_slc[end_0_idx, 2] + 0.01\n brst_slc[end_1_idx, 2] = brst_slc[end_1_idx, 2] - 0.01\n\n return brst_slc, end_0_idx, end_1_idx\n\ndef fix_crotch_hip_cleavage(slice, depth):\n delta = 0.05depth\n clv_idx = 0\n slice[clv_idx, 1] = slice[clv_idx, 1] - delta\n return slice\n\nimport sys\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--input\", required=True, help=\"input meta data file\")\n ap.add_argument(\"-m\", \"--measure_dir\", required=True, help=\"measurement 2d data directory\")\n ap.add_argument(\"-o\", \"--out_dir\", required=True, help=\"directory for expxorting control mesh slices\")\n ap.add_argument(\"-w\", \"--weight\", required=True, help=\"deform based on weight\")\n ap.add_argument(\"-mo\", \"--model_dir\", required=True, help=\"deform based on weight\")\n\n args = vars(ap.parse_args())\n\n in_path = args['input']\n M_DIR = args['measure_dir']\n OUT_DIR = args['out_dir'] + '/'\n\n weight_path = args['weight']\n\n MODEL_DIR = args['model_dir']\n models = {}\n for path in Path(MODEL_DIR).glob('.pkl'):\n models[path.stem] = RBFNet.load_from_path(path)\n print('load models: ', models.keys())\n\n for fpath in Path(OUT_DIR).glob('.'):\n os.remove(str(fpath))\n\n with open(in_path, 'rb') as f:\n data = pickle.load(f)\n ctl_mesh = data['control_mesh']\n ctl_mesh_quad_dom = data['control_mesh_quad_dom']\n slc_id_vert_idxs = data['slice_vert_idxs']\n slc_id_locs = data['slice_locs']\n arm_3d_tpl = data['arm_bone_locs']\n\n ctl_sym_vert_pairs = data['control_mesh_symmetric_vert_pairs']\n\n tpl_sym_vert_pairs = data['template_symmetric_vert_pairs']\n tpl_lbody_vert_idxs = [pair[0] for pair in tpl_sym_vert_pairs]\n tpl_rbody_vert_idxs = [pair[1] for pair in tpl_sym_vert_pairs]\n\n tpl_mesh = data['template_mesh']\n tpl_height = data['template_height']\n\n print('control mesh: nverts = {0}, ntris = {1}'.format(ctl_mesh['verts'].shape[0], len(ctl_mesh['faces'])))\n print('victoria mesh: nverts = {0}, ntris = {1}'.format(tpl_mesh['verts'].shape[0], len(tpl_mesh['faces'])))\n\n out_path = f'{OUT_DIR}victoria_ctl.obj'\n export_mesh(out_path, ctl_mesh['verts'], ctl_mesh['faces'])\n\n out_path = f'{OUT_DIR}victoria_tpl.obj'\n export_mesh(out_path, tpl_mesh['verts'], tpl_mesh['faces'])\n\n\n for mdata_path in Path(M_DIR).glob('.npy'):\n print(mdata_path)\n\n # load 2d measurements\n mdata = np.load(mdata_path )\n seg_dst_f = mdata.item().get('landmark_segment_dst_f')\n seg_dst_s = mdata.item().get('landmark_segment_dst_s')\n seg_location = mdata.item().get('landmark_segment_location_s')\n measurements = mdata.item().get('measurement')\n height = measurements['Height']\n\n arm_2d_f = mdata.item().get('armature_f')\n h_ratio = tpl_height / height\n arm_3d = scale_tpl_armature(arm_3d_tpl, arm_2d_f, h_ratio)\n\n id_mappings = slice_id_3d_2d_mappings()\n ct_mesh_slices = {}\n\n ctl_new_mesh = deepcopy(ctl_mesh)\n\n #hack: the background z value extracted from image is not exact. therefore, we consider ankle z as the z starting point\n tpl_ankle_hor = slc_id_locs['LAnkle'][1]\n tpl_ankle_ver = slc_id_locs['LAnkle'][2]\n #slice location in relative to ankle location in side image\n for id_3d, id_2d in id_mappings.items():\n #debug\n #if id_3d not in ['L0_RAnkle', 'L0_LAnkle']:\n # continue\n\n #ignore the right body part\n if id_3d[0] == 'R':\n continue\n\n if id_3d == 'Shoulder':\n debug = True\n\n if id_3d not in slc_id_vert_idxs:\n print(f'indices of {id_3d} are not available', file=sys.stderr)\n continue\n\n slc_idxs = slc_id_vert_idxs[id_3d]\n slice = ctl_mesh['verts'][slc_idxs]\n\n if id_2d not in seg_dst_f:\n print(f'measurement of {id_2d} is not available', file=sys.stderr)\n continue\n\n if id_2d not in seg_location:\n print(f'location of {id_2d} is not available. ignore this slice', file=sys.stderr)\n continue\n\n seg_log = seg_location[id_2d]\n\n w = seg_dst_f[id_2d]\n\n d = w\n if id_2d in seg_dst_s:\n d = seg_dst_s[id_2d]\n\n slc_loc_hor = seg_log[0]\n slc_loc_ver = np.abs(seg_log[1])\n\n #transform to victoria's scale\n w = wh_ratio\n d = dh_ratio\n slc_loc_ver = slc_loc_ver * h_ratio\n slc_loc_hor = slc_loc_hor * h_ratio\n\n #slc_org = slc_id_locs[id_3d]\n\n slice_out = copy(slice)\n #TEST\n if id_2d in models:\n if id_2d == 'Shoulder':\n debug = True\n print('\\t applied ', id_2d)\n model = models[id_2d]\n ratio = w/d\n pred = model.predict(np.reshape(ratio, (1,1)))[0, :]\n fourier = True\n if fourier:\n res_contour = util.reconstruct_contour_fourier(pred)\n else:\n if util.is_leg_contour(id_2d):\n res_contour = util.reconstruct_leg_slice_contour(pred, d, w)\n else:\n res_contour = util.reconstruct_torso_slice_contour(pred, d, w, mirror=True)\n\n slice_out[:,0] = res_contour[1,:]\n slice_out[:,1] = res_contour[0,:]\n\n #right side\n if id_3d[0] == 'R':\n #mirror through X\n slice_out[:,0] = -slice_out[:,0]\n\n if util.is_leg_contour(id_2d):\n slice_out += np.mean(slice, axis=0)\n\n dim_range = np.max(slice_out, axis=0) - np.min(slice_out, axis=0)\n w_ratio = w / dim_range[0]\n d_ratio = d / dim_range[1]\n slice_out = scale_vertical_slice(slice_out, w_ratio, d_ratio)\n\n if util.is_torso_contour(id_2d):\n if id_2d == 'Hip' or 'Crotch' in id_2d:\n slice_out = fix_crotch_hip_cleavage(slice_out, d)\n\n if id_2d == 'UnderCrotch':\n plt.clf()\n plt.axes().set_aspect(1.0)\n plt.plot(res_contour[1, :], res_contour[0, :], '-r')\n plt.plot(res_contour[1, 0], res_contour[0, 0], '+r', ms=20)\n plt.plot(res_contour[1, 2], res_contour[0, 2], '+g', ms=20)\n\n plt.plot(slice_out[:, 0], slice_out[:, 1], '-b')\n plt.plot(slice_out[0, 0], slice_out[0, 1], '+r', ms=20)\n plt.plot(slice_out[2, 0], slice_out[2, 1], '+g', ms=20)\n\n plt.plot(slice[:, 0], slice[:, 1], '-y')\n plt.plot(slice[0, 0], slice[0, 1], '+r', ms=20)\n plt.plot(slice[2, 0], slice[2, 1], '+g', ms=20)\n #plt.savefig(f'{OUTPUT_DEBUG_DIR_TEST}{idx}.png')\n #plt.show()\n\n #align slice in vertical direction\n slice_out[:, 2] = slc_loc_ver + tpl_ankle_ver\n\n #align slice in horizontal direction\n #Warning: need to be careful here. we assume that the maximum point on hor dir is on the back side of Victoria's mesh\n slice_hor_anchor = np.max(slice_out[:,1])\n slice_out[:, 1] += (-slice_hor_anchor + tpl_ankle_hor + slc_loc_hor)\n\n ctl_new_mesh['verts'][slc_idxs, :] = slice_out\n\n #transform_arm_slices(ctl_new_mesh, slc_id_locs, slc_id_vert_idxs, arm_3d)\n\n verts = ctl_new_mesh['verts']\n for pair in ctl_sym_vert_pairs:\n mirror_co = deepcopy(verts[pair[0]])\n mirror_co[0] = -mirror_co[0]\n verts[pair[1]] = mirror_co\n\n ctl_mesh_quad_dom_new = deepcopy(ctl_mesh_quad_dom)\n ctl_mesh_quad_dom_new['verts'] = deepcopy(ctl_new_mesh['verts'])\n\n out_path = f'{OUT_DIR}{mdata_path.stem}_ctl.obj'\n print(f'\\toutput control mesh: {out_path}')\n export_mesh(out_path, ctl_mesh_quad_dom_new['verts'], ctl_mesh_quad_dom_new['faces'])\n\n ctl_new_mesh_1 = subdivide_catmull_temp(ctl_mesh_quad_dom_new)\n out_path = f'{OUT_DIR}{mdata_path.stem}_ctl_subdivided.obj'\n print(f'\\toutput subdivided control mesh: {out_path}')\n export_mesh(out_path, ctl_new_mesh_1['verts'], ctl_new_mesh_1['faces'])\n\n if Path(weight_path).is_file():\n with open(weight_path, 'rb') as f:\n data = pickle.load(f)\n ctl_tri_bs = data['control_mesh_tri_basis']\n vert_UVWs = data['template_vert_UVW']\n vert_weights = data['template_vert_weight']\n vert_effect_idxs = data['template_vert_effect_idxs']\n\n ctl_df_basis = util.calc_triangle_local_basis(ctl_new_mesh['verts'], ctl_new_mesh['faces'])\n tpl_df_mesh = deform_template_mesh(tpl_mesh, vert_effect_idxs, vert_weights, vert_UVWs, ctl_df_basis, deform_vert_idxs=None)\n\n out_path = f'{OUT_DIR}{mdata_path.stem}_deform.obj'\n print(f'\\toutput deformed mesh to {out_path}')\n export_mesh(out_path, tpl_df_mesh['verts'], tpl_df_mesh['faces'])\n\n projec_mesh_onto_mesh(tpl_df_mesh, tpl_lbody_vert_idxs, ctl_new_mesh_1)\n\n #mirror\n verts = tpl_df_mesh['verts']\n for pair in tpl_sym_vert_pairs:\n mirror_co = deepcopy(verts[pair[0]])\n mirror_co[0] = -mirror_co[0]\n verts[pair[1]] = mirror_co\n\n out_path = f'{OUT_DIR}{mdata_path.stem}_deform_projected.obj'\n print(f'\\toutput deformed mesh to {out_path}')\n export_mesh(out_path, tpl_df_mesh['verts'], tpl_df_mesh['faces'])\n\n\n" }, { "alpha_fraction": 0.5382602214813232, "alphanum_fraction": 0.551397442817688, "avg_line_length": 34.58100509643555, "blob_id": "cffec3a37c7de364940d6c29a9241e03f6968877", "content_id": "17fdc6fa6c9947ae375ce6848edbcb542687d24e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 19106, "license_type": "no_license", "max_line_length": 132, "num_lines": 537, "path": "/src/caesar_slc_contour_process.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport pickle\nimport argparse\nimport os\nimport matplotlib.pyplot as plt\nfrom shapely.geometry import LinearRing, LineString, Point, Polygon\nimport shapely.affinity as affinity\nfrom numpy.linalg import norm\nfrom pathlib import Path\nimport math\nimport src.util as util\nfrom src.caesar_slc_fix_bust import \\\n remove_arm_from_bust_slice, remove_arm_from_under_bust_slice, remove_arm_from_armscye_slice, fix_bust_height, preprocess_contour\nimport multiprocessing\nimport sys\nfrom scipy.spatial import ConvexHull\nimport scipy.ndimage as ndimage\nimport shutil\nfrom scipy.interpolate import splev, splrep, splprep, splev\nimport cv2 as cv\n\nG_cur_file_path = Path()\nIN_DIR = ''\nOUT_DIR = ''\nSUPPOINT_DIR = ''\nLDPOINT_DIR = ''\nDEBUG_DIR = ''\n\ndef plot_segment(p0, p1, type):\n plt.plot([p0[0], p1[0]], [p0[1], p1[1]], type)\n\ndef resample_contour(X, Y, n_point = 150, debug_path = None):\n idx_ymax, idx_ymin = np.argmax(Y), np.argmin(Y)\n center_y = 0.5 * (Y[idx_ymax] + Y[idx_ymin])\n center_x = 0.5 * (X[idx_ymin] + X[idx_ymax])\n\n X, Y = util.resample_contour(X, Y, n_point)\n\n #find the starting contour point\n min_dst = np.inf\n min_idx = 0\n i = 0\n for x, y in zip(X,Y):\n if x > center_x:\n y_dif = abs(y - center_y)\n if y_dif < min_dst:\n min_dst = y_dif\n min_idx = i\n i += 1\n\n X = np.roll(X, -min_idx)\n Y = np.roll(Y, -min_idx)\n #print('starting index: ', min_idx)\n\n\n #fix bad points\n # jump = np.sqrt(np.diff(X) 2 + np.diff(X) 2)\n # smooth_jump = ndimage.gaussian_filter1d(jump, 5, mode='wrap') # window of size 5 is arbitrary\n # limit = 2 * np.median(smooth_jump) # factor 2 is arbitrary\n # xn, yn = X[:-1], Y[:-1]\n # X = xn[(jump > 0) & (smooth_jump < limit)]\n # Y = yn[(jump > 0) & (smooth_jump < limit)]\n\n #resample\n # tck, u = splprep([X, Y], s=0)\n # u_1 = np.linspace(0.0, 1.0, 150)\n # X, Y = splev(u_1, tck)\n\n if debug_path is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(X, Y, 'b-')\n plt.plot(center_x, center_y, 'r+')\n plt.plot(X[0], Y[0], 'r+', ms = 20)\n plt.plot(X[5], Y[5], 'g+', ms = 20)\n plt.savefig(debug_path)\n return X, Y\n\ndef load_contour(type, path):\n with open(path, 'rb') as file:\n slc_contours = pickle.load(file)\n assert len(slc_contours) != 0\n if util.is_leg_contour(type):\n lens = np.array([len(contour) for contour in slc_contours])\n cnt_0, cnt_1 = np.argsort(-lens)[:2]\n contour_0 = np.array(slc_contours[cnt_0])\n contour_1 = np.array(slc_contours[cnt_1])\n center_0 = np.mean(contour_0, axis=0)\n center_1 = np.mean(contour_1, axis=0)\n if center_1[0] > center_0[0]:\n return contour_1\n else:\n return contour_0\n pass\n else:\n lens = np.array([len(contour) for contour in slc_contours])\n contour = slc_contours[np.argmax(lens)]\n contour = np.array(contour)\n contour = contour[:, :2]\n return contour\n\ndef sample_contour_radial(X, Y, center, n_sample):\n contour = LinearRing([(x,y) for x, y in zip(X,Y)])\n range_x = np.max(X) - np.min(X)\n range_y = np.max(Y) - np.min(Y)\n extend_len = max(range_x, range_y)\n angle_step = (2.0np.pi)/float(n_sample)\n points = []\n for i in range(n_sample):\n x = np.cos(iangle_step)\n y = np.sin(iangle_step)\n p = center + extend_len np.array([x,y])\n isect_ret = LineString([(center[0], center[1]), (p[0],p[1])]).intersection(contour)\n if isect_ret.geom_type == 'Point':\n isect_p = np.array(isect_ret.coords[:]).flatten()\n elif isect_ret.geom_type == 'MultiPoint':\n isect_p = np.array(isect_ret[0].coords[:]).flatten()\n else:\n #assert False, 'unsupported intersection type'\n raise Exception('sample_contour_radial: no intersection found')\n isect_p = isect_p - center\n points.append(isect_p)\n\n return points\n\ndef radial_code(points, D, half = True):\n n_points = points.shape[0]\n idx_half = int(n_points / 2) + 1\n if half:\n idx_max = int(n_points/2) + 1\n else:\n idx_max = n_points\n\n feature = []\n\n for i in range(1, idx_max):\n dy = points[i,1] - points[i-1,1]\n dx = points[i,0] - points[i-1,0]\n c = dy/dx\n #c = np.clip(c, a_min=-100.0, a_max=100.0)\n feature.append(c)\n\n D_mid = norm(points[0] - points[idx_half])\n r1 = D_mid / D\n r2 = norm(points[0]) / D_mid\n feature.extend([r1, r2])\n\n return feature\n\ndef convert_torso_contour_to_radial_code(X, Y, n_sample, path_out = None):\n idx_ymax, idx_ymin = np.argmax(Y), np.argmin(Y)\n idx_xmax, idx_xmin = np.argmax(X), np.argmin(X)\n center_y = 0.5 * (Y[idx_ymax] + Y[idx_ymin])\n center_x = 0.5 * (X[idx_ymin] + X[idx_ymax])\n center = np.array([center_x, center_y])\n\n idx_half = int(n_sample/2) + 1\n\n W = Y[idx_ymax] - Y[idx_ymin]\n D = X[idx_xmax] - X[idx_xmin]\n\n points = sample_contour_radial(X, Y, center, n_sample)\n\n if path_out is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(X, Y, 'b-')\n plt.plot(center_x, center_y, 'r+')\n\n feature = []\n for i in range(1, idx_half):\n dy = points[i][1] - points[i-1][1]\n dx = points[i][0] - points[i-1][0]\n c = dy/dx\n feature.append(c)\n\n D_mid = norm(points[0] - points[idx_half])\n r1 = D_mid / D\n r2 = norm(points[0]) / D_mid\n feature.extend([r1, r2])\n\n if path_out is not None:\n for p in points:\n p = center + p\n plt.plot([center_x, p[0]], [center_y, p[1]], 'r-')\n plt.plot(p[0], p[1], 'b+')\n\n points_1 = util.reconstruct_torso_slice_contour(feature, D, W)\n for i in range(points_1.shape[1]):\n p = points_1[:,i]\n p = center + p\n plt.plot(p[0], p[1], 'r+')\n plt.savefig(path_out)\n #plt.show()\n\n return np.array(feature), W, D\n\ndef convert_leg_contour_to_radial_code(X, Y, n_sample, path_out = None):\n idx_ymax, idx_ymin = np.argmax(Y), np.argmin(Y)\n idx_xmax, idx_xmin = np.argmax(X), np.argmin(X)\n center_y = 0.5 * (Y[idx_ymax] + Y[idx_ymin])\n center_x = X[idx_ymax]\n center = np.array([center_x, center_y])\n\n W = Y[idx_ymax] - Y[idx_ymin]\n D = X[idx_xmax] - X[idx_xmin]\n\n if path_out is not None:\n plt.clf()\n plt.axes().set_aspect(1)\n plt.plot(X, Y, 'b-')\n plt.plot(center_x, center_y, 'r+')\n plt.plot(X[idx_ymax], Y[idx_ymax], 'go', ms=5)\n plt.plot(X[idx_ymin], Y[idx_ymin], 'go', ms=5)\n #plt.show()\n\n points = sample_contour_radial(X, Y, center, n_sample)\n\n points = np.array(points)\n feature = radial_code(points, D, half=False)\n\n if path_out is not None:\n for p in points:\n p = center + p\n plt.plot([center_x, p[0]], [center_y, p[1]], 'r-')\n plt.plot(p[0], p[1], 'b+')\n\n points_1 = util.reconstruct_leg_slice_contour(feature, D, W)\n for i in range(points_1.shape[1]):\n p = points_1[:,i]\n p = center + p\n plt.plot(p[0], p[1], 'r+')\n plt.savefig(path_out)\n #plt.show()\n\n return np.array(feature), W, D\n\n\n#estimate leg axis, running from right to left (neg x => pos x)\ndef leg_hor_axis(ld_points):\n right_0 = ld_points[20][:2]\n right_1 = ld_points[16][:2]\n left_0 = ld_points[22][:2]\n left_1 = ld_points[18][:2]\n\n hor_dir = 0.5(left_0+left_1) - 0.5(right_0+right_1)\n\n return util.normalize(hor_dir)\n\ndef align_leg_contour(X, Y, ld_points):\n hor_ax = leg_hor_axis(ld_points)\n\n angle = np.arccos(np.dot(hor_ax, np.array([1.0, 0.0])))\n if hor_ax[1] > 0.0:\n angle = -angle\n cos_a = np.cos(angle)\n sin_a = np.sin(angle)\n\n rot_mat = np.array([[cos_a, -sin_a], [sin_a, cos_a]])\n rot_center = np.array([np.mean(X), np.mean(Y)])\n contour = np.concatenate([X.reshape(-1, 1), Y.reshape(-1, 1)], axis=1)\n contour_1 = np.dot(rot_mat, (contour - rot_center).T).T + rot_center\n\n #test_p0 = rot_center - 0.5hor_ax\n #test_p1 = rot_center + 0.5hor_ax\n #plt.clf()\n #plt.axes().set_aspect(1.0)\n #plt.plot([test_p0[0], test_p1[0]], [test_p0[1], test_p1[1]], '-r')\n #plt.plot(X, Y, '-b')\n #plt.plot(contour_1[:,0], contour_1[:,1], '-r')\n #plt.show()\n return contour_1[:,0], contour_1[:,1]\n\ndef process_leg_contour(path, contour, sup_points, ld_points):\n contour = preprocess_contour(contour, resolution=150)\n\n Y = contour[:, 0]\n X = contour[:, 1]\n\n X, Y = align_leg_contour(X, Y, ld_points)\n\n X, Y = resample_contour(X, Y)\n\n debug_path_out = f'{DEBUG_RADIAL_DIR}/{path.stem}.png'\n feature, W, D = convert_leg_contour_to_radial_code(X, Y, 9, path_out=debug_path_out)\n\n return X, Y, W, D, feature\n\ndef process_torso_contour(path, contour, sup_points, ld_points):\n # torso contour\n align_anchor_pos_x = True\n if slc_id == 'Armscye':\n align_anchor_pos_x = False\n\n debug_armscye_path = f'{DEBUG_ARMSCYE_DIR}/{path.stem}.png'\n contour, has_left, has_right, fixed_left, fixed_right = remove_arm_from_armscye_slice(contour,\n sup_points=sup_points,\n debug_path=debug_armscye_path)\n if has_left != fixed_left or has_right != fixed_right:\n raise Exception('Failed armscye slice')\n\n elif slc_id == 'Bust':\n align_anchor_pos_x = False\n\n armscye_path = f'{IN_DIR}/Armscye/{path.name}'\n armscye_contour = load_contour('Armscye', armscye_path)\n\n debug_bust_path = f'{DEBUG_BUST_DIR}/{path.stem}.png'\n contour, has_left, has_right, fixed_left, fixed_right = remove_arm_from_bust_slice(contour,\n sup_points=sup_points,\n debug_path=debug_bust_path)\n if has_left != fixed_left or has_right != fixed_right:\n raise Exception('Failed bust slice')\n\n debug_bust_height_path = f'{DEBUG_BUST_HEIGHT_DIR}/{path.stem}.png'\n contour, ok = fix_bust_height(contour, sup_points=sup_points, ld_points=ld_points,\n armscye_contour=armscye_contour, debug_path=debug_bust_height_path)\n\n elif slc_id == 'Aux_UnderBust_Bust_0':\n align_anchor_pos_x = False\n\n armscye_path = f'{IN_DIR}/Armscye/{path.name}'\n armscye_contour = load_contour('Armscye', armscye_path)\n\n arm_pnt_negx = np.array(sup_points['Aux_UnderBust_Bust_0_NegX'][:2])\n arm_pnt_posx = np.array(sup_points['Aux_UnderBust_Bust_0_PosX'][:2])\n debug_bust_path = f'{DEBUG_UNDERBUST_BUST_DIR}/{path.stem}_bust.png'\n contour, has_left, has_right, fixed_left, fixed_right = remove_arm_from_under_bust_slice(contour,\n arm_pnt_negx=arm_pnt_negx,\n arm_pnt_posx=arm_pnt_posx,\n debug_path=debug_bust_path)\n if has_left != fixed_left or has_right != fixed_right:\n raise Exception('Failed under_bust slice')\n\n debug_underbust_height_path = f'{DEBUG_UNDERBUST_HEIGHT_DIR}/{path.stem}.png'\n contour, ok = fix_bust_height(contour, sup_points=sup_points, ld_points=ld_points,\n armscye_contour=armscye_contour, debug_path=debug_underbust_height_path)\n else:\n contour = preprocess_contour(contour, resolution=150)\n pass\n\n # transpose, swap X and Y to make the coordinate system more natural to the contour shape\n Y = contour[:, 0]\n X = contour[:, 1]\n\n debug_align_path = f'{DEBUG_ALIGN_DIR}/{path.stem}.png'\n X, Y = util.align_torso_contour(X, Y, anchor_pos_x=align_anchor_pos_x, debug_path=debug_align_path)\n if X is None or Y is None:\n raise Exception('failed torso contour alignment')\n\n X, Y = resample_contour(X, Y)\n #X, Y = util.smooth_contour(X, Y, sigma=2.0)\n\n n_sample = 16\n if slc_id == 'Shoulder' or slc_id == 'Aux_Armscye_Shoulder_0':\n n_sample = 20\n debug_path_out = f'{DEBUG_RADIAL_DIR}/{path.stem}.png'\n feature, W, D = convert_torso_contour_to_radial_code(X, Y, n_sample, path_out=debug_path_out)\n\n return X, Y, W, D, feature\n\n\nimport warnings\ndef run_process_slice_contours(process_id, slc_id, paths, shared_data):\n n_paths = len(paths)\n #print(f'process {self.id} started. n_paths = {n_paths}')\n\n Ws = []\n Ds = []\n Fs = []\n Cs = []\n Ns = []\n\n warnings.filterwarnings('error')\n\n for i, path in enumerate(paths):\n if i % 20 == 0:\n print(f'process {process_id}: {100.0 * float(i) / float(n_paths)}%')\n\n suppoints_path = f'{SUPPOINT_DIR}/{path.stem}.pkl'\n assert os.path.exists(suppoints_path)\n with open(suppoints_path, 'rb') as file:\n sup_points = pickle.load(file)\n\n ld_path = f'{LDPOINT_DIR}/{path.stem}.pkl'\n assert os.path.exists(ld_path)\n with open(ld_path, 'rb') as file:\n ld_points = pickle.load(file)\n\n contour = load_contour(slc_id, path)\n\n if util.is_leg_contour(slc_id):\n try:\n X, Y, W, D, radial_code = process_leg_contour(path, contour, sup_points=sup_points, ld_points=ld_points)\n except Exception as exp:\n print(path.stem, exp, file=sys.stderr)\n continue\n else:\n try:\n X, Y, W, D, radial_code = process_torso_contour(path, contour, sup_points=sup_points, ld_points=ld_points)\n except Exception as exp:\n print(path.stem, f'khanh exp: {exp}', file=sys.stderr)\n continue\n except RuntimeWarning as warn:\n print(path.stem, f'khanh warn: {warn}', file=sys.stderr)\n continue\n\n #acculumate one more slice record\n Ws.append(W)\n Ds.append(D)\n Fs.append(radial_code)\n Cs.append(np.vstack([X,Y]))\n Ns.append(path.stem)\n\n shared_data[process_id] = {'Ws':Ws, 'Ds':Ds, 'Fs':Fs, 'Cs':Cs, 'Ns':Ns}\n\n print(f'process {process_id} finished. len(Ws)={len(Ws)}')\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--input\", required=True, help=\"\")\n ap.add_argument(\"-o\", \"--output\", required=True, help=\"\")\n ap.add_argument(\"-p\", \"--suppoint\", required=True, help=\"\")\n ap.add_argument(\"-l\", \"--ldpoint\", required=True, help=\"\")\n ap.add_argument(\"-ids\", \"--slc_ids\", required=True, help=\"\")\n\n args = vars(ap.parse_args())\n IN_DIR = args['input']\n OUT_DIR = args['output']\n SUPPOINT_DIR = args['suppoint']\n LDPOINT_DIR = args['ldpoint']\n slc_ids = args['slc_ids']\n\n DEBUG_DIR = '/home/khanhhh/data_1/projects/Oh/data/3d_human/caesar_obj/debug/'\n os.makedirs(DEBUG_DIR, exist_ok=True)\n\n all_slc_ids = [path.stem for path in Path(IN_DIR).glob('./')]\n if slc_ids == 'all':\n slc_ids = all_slc_ids\n else:\n slc_ids = slc_ids.split(',')\n for id in slc_ids:\n assert id in all_slc_ids, f'{id}: unrecognized slice id'\n\n n_processes = 12\n failed_slice_paths = []\n for slc_id in slc_ids:\n SLICE_DIR = f'{IN_DIR}/{slc_id}/'\n print(f'start processing slice {slc_id}')\n\n DEBUG_ALIGN_DIR = f'{DEBUG_DIR}/{slc_id}_align/'\n shutil.rmtree(DEBUG_ALIGN_DIR, ignore_errors=True)\n os.makedirs(DEBUG_ALIGN_DIR, exist_ok=True)\n\n DEBUG_RADIAL_DIR = f'{DEBUG_DIR}/{slc_id}_radial/'\n shutil.rmtree(DEBUG_RADIAL_DIR, ignore_errors=True)\n os.makedirs(DEBUG_RADIAL_DIR, exist_ok=True)\n\n if slc_id == 'Armscye':\n DEBUG_ARMSCYE_DIR = f'{DEBUG_DIR}/{slc_id}_armscye_cutoff/'\n shutil.rmtree(DEBUG_ARMSCYE_DIR, ignore_errors=True)\n os.makedirs(DEBUG_ARMSCYE_DIR, exist_ok=True)\n\n if slc_id == 'Bust':\n DEBUG_BUST_DIR = f'{DEBUG_DIR}/{slc_id}_bust_cutoff/'\n shutil.rmtree(DEBUG_BUST_DIR, ignore_errors=True)\n os.makedirs(DEBUG_BUST_DIR, exist_ok=True)\n\n DEBUG_BUST_HEIGHT_DIR = f'{DEBUG_DIR}/{slc_id}_bust_height/'\n shutil.rmtree(DEBUG_BUST_HEIGHT_DIR, ignore_errors=True)\n os.makedirs(DEBUG_BUST_HEIGHT_DIR, exist_ok=True)\n\n if slc_id == 'Aux_UnderBust_Bust_0':\n DEBUG_UNDERBUST_BUST_DIR = f'{DEBUG_DIR}/{slc_id}_aux_underbust_bust_0_cutoff/'\n shutil.rmtree(DEBUG_UNDERBUST_BUST_DIR, ignore_errors=True)\n os.makedirs(DEBUG_UNDERBUST_BUST_DIR, exist_ok=True)\n\n DEBUG_UNDERBUST_HEIGHT_DIR = f'{DEBUG_DIR}/{slc_id}_underbust_height/'\n shutil.rmtree(DEBUG_UNDERBUST_HEIGHT_DIR, ignore_errors=True)\n os.makedirs(DEBUG_UNDERBUST_HEIGHT_DIR, exist_ok=True)\n\n slc_paths = [path for path in Path(SLICE_DIR).glob('.pkl')]\n #slc_paths = slc_paths[:3]\n n_paths = len(slc_paths)\n processes = []\n npath_per_process = int(n_paths / n_processes)\n\n manager = multiprocessing.Manager()\n shared_data = manager.dict()\n\n for i in range(n_processes):\n sub_path_list = slc_paths[inpath_per_process:(i + 1) npath_per_process]\n process = multiprocessing.Process(target=run_process_slice_contours, args=(i, slc_id, sub_path_list, shared_data))\n processes.append(process)\n\n for process in processes:\n process.start()\n\n for process in processes:\n process.join()\n\n Ws = []\n Ds = []\n Fs = []\n Cs = []\n Ns = []\n print('syncronizing data across processes')\n for id, data in shared_data.items():\n n_Ws = len(data['Ws'])\n print(f'{id}, len(Ws)={n_Ws}')\n assert len(data['Ws']) > 0\n assert len(data['Ds']) > 0\n Ws.extend(data['Ws'])\n Ds.extend(data['Ds'])\n Fs.extend(data['Fs'])\n Cs.extend(data['Cs'])\n Ns.extend(data['Ns'])\n\n #dump all records of that slice\n n_contour = len(Ns)\n Fs = np.array(Fs)\n\n feature_dir_out = f'{OUT_DIR}/{slc_id}/'\n os.makedirs(feature_dir_out, exist_ok=True)\n\n for i in range(n_contour):\n W = Ws[i]\n D = Ds[i]\n F = Fs[i,:]\n C = Cs[i]\n name = Ns[i]\n with open(f'{feature_dir_out}{name}.pkl', 'wb') as file:\n pickle.dump({'W':W, 'D':D, 'feature':F, 'cnt':C}, file)\n\n print('failed slice paths')\n print(failed_slice_paths)\n print(f'n failed slices = {len(failed_slice_paths)}')" }, { "alpha_fraction": 0.5621079206466675, "alphanum_fraction": 0.5658720135688782, "avg_line_length": 26.170454025268555, "blob_id": "6a9abd25eb53dd72e82e97a510ff89cd8bb5b56f", "content_id": "ed6061e9f18005f6953360d60591fb63edfda0e1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2391, "license_type": "no_license", "max_line_length": 103, "num_lines": 88, "path": "/src/util_bad_slide_semi_auto_tool.py", "repo_name": "khanhha/human_estimation", "src_encoding": "UTF-8", "text": "import numpy as np\nimport cv2 as cv\nimport sys\nimport matplotlib.pyplot as plt\nfrom pathlib import Path\nimport argparse\nimport os\n\ng_bad_slc_names = set()\ng_cur_idx = 0\ng_all_paths = []\n\ng_fig, g_ax = plt.subplots()\nimg_ax = None\n\nIN_IMG_DIR = None\nOUT_TXT_FILE = None\nID = None\n\ndef update_draw():\n global img_ax\n path = g_all_paths[g_cur_idx]\n img = cv.imread(str(path))\n if img_ax is None:\n img_ax = g_ax.imshow(img)\n else:\n img_ax.set_data(img)\n bad = False\n if path.stem in g_bad_slc_names:\n bad = True\n g_ax.set_title(f'{ID}\\nfile_name = {path.stem}, idx = {g_cur_idx}, is_bad = {bad}')\n g_fig.canvas.draw()\n\ndef write_to_file():\n with open(OUT_TXT_FILE, 'w') as file:\n for name in g_bad_slc_names:\n file.write(f'{name}\\n')\n print(f'wrote to file {OUT_TXT_FILE}')\n\ndef press(event):\n global g_cur_idx\n if event.key == 'c':\n g_bad_slc_names.add(g_all_paths[g_cur_idx].stem)\n update_draw()\n elif event.key == 'z':\n g_bad_slc_names.remove(g_all_paths[g_cur_idx].stem)\n update_draw()\n elif event.key == 'w':\n write_to_file()\n elif event.key == 'right':\n g_cur_idx += 1\n g_cur_idx = g_cur_idx % len(g_all_paths)\n update_draw()\n elif event.key == 'left':\n g_cur_idx -= 1\n g_cur_idx = max(0, g_cur_idx)\n update_draw()\n else:\n print('unrecognized key', file=sys.stderr)\n\nif __name__ == '__main__':\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--in_dir\", required=True, help=\"slice obj directory\")\n ap.add_argument(\"-f\", \"--file\", required=True, help=\"directory for expxorting control mesh slices\")\n args = vars(ap.parse_args())\n\n IN_IMG_DIR = args['in_dir']\n OUT_TXT_FILE = Path(args['file'])\n ID = OUT_TXT_FILE.stem\n\n if os.path.exists(OUT_TXT_FILE):\n with open(OUT_TXT_FILE, 'r') as file:\n for name in file.readlines():\n name = name.replace('\\n','')\n g_bad_slc_names.add(name)\n\n g_all_paths = [path for path in Path(IN_IMG_DIR).glob('.')]\n g_cur_idx = 0\n if len(g_all_paths) > 0:\n g_fig.canvas.mpl_connect('key_press_event', press)\n g_ax.set_aspect(1.0)\n g_ax.axis('off')\n update_draw()\n plt.show()\n\n write_to_file()\n else:\n print('no file found', file=sys.stderr)\n" } ]	20
mpetersen94/drake	https://github.com/mpetersen94/drake	b0bbeb058d2a3682da9f1389225941099af2fb25	c38f22c9b2f00359679bc0b903b40947c9eeaa6e	9c6f0e7db4f48502a18c58bad1caf6cfaacd88db	refs/heads/master	2023-04-28T08:26:03.124616	2023-04-26T17:29:09	2023-04-26T17:29:09	132,493,501	0	2	NOASSERTION	2018-05-07T17:21:02	2022-01-10T20:52:51	2022-02-06T19:49:52	C++	[ { "alpha_fraction": 0.7619503140449524, "alphanum_fraction": 0.7848948240280151, "avg_line_length": 39.230770111083984, "blob_id": "74f464e872c0caab907965719ff3bc75cbfb576e", "content_id": "f801c423c1a336cb728f3f9f9ab744f8d24cb1fa", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 1046, "license_type": "permissive", "max_line_length": 220, "num_lines": 26, "path": "/systems/trajectory_optimization/stub/direct_transcription.h", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#pragma once\n\n#warning The include path drake/systems/trajectory_optimization/direct_transcription.h is deprecated and will be removed on or after 2023-05-01; instead, use drake/planning/trajectory_optimization/direct_transcription.h.\n\n#include \"drake/common/drake_deprecated.h\"\n#include \"drake/planning/trajectory_optimization/direct_transcription.h\"\n// Deprecated includes from original include file.\n#include \"drake/systems/trajectory_optimization/multiple_shooting.h\"\n\nnamespace drake {\nnamespace systems {\nnamespace trajectory_optimization {\n\nusing TimeStep DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use drake::planning::trajectory_optimization::TimeStep instead.\") =\n drake::planning::trajectory_optimization::TimeStep;\n\nusing DirectTranscription DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use drake::planning::trajectory_optimization::DirectTranscription \"\n \"instead.\") = drake::planning::trajectory_optimization::DirectTranscription;\n\n} // namespace trajectory_optimization\n} // namespace systems\n} // namespace drake\n" }, { "alpha_fraction": 0.5669013857841492, "alphanum_fraction": 0.5795774459838867, "avg_line_length": 32.411766052246094, "blob_id": "b75fe77b818c11e7d358f843180741e467d1c50b", "content_id": "eebb64a71a18b016aeb97c1d292ebb83a214de80", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 2843, "license_type": "permissive", "max_line_length": 80, "num_lines": 85, "path": "/common/benchmarking/benchmark_polynomial.cc", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#include <fmt/format.h>\n\n#include \"drake/common/symbolic/monomial_util.h\"\n#include \"drake/common/symbolic/polynomial.h\"\n#include \"drake/tools/performance/fixture_common.h\"\n\nnamespace drake {\nnamespace symbolic {\nnamespace {\nvoid BenchmarkPolynomialEvaluatePartial(benchmark::State& state) { // NOLINT\n Eigen::Matrix<symbolic::Variable, 12, 1> x =\n MakeVectorContinuousVariable(12, \"x\");\n const symbolic::Variables x_set(x);\n const auto monomial_basis =\n internal::ComputeMonomialBasis<Eigen::Dynamic>(x_set, 2);\n MatrixX<symbolic::Variable> S(monomial_basis.rows(), monomial_basis.rows());\n VectorX<symbolic::Variable> S_upper((S.rows() + 1) * S.rows() / 2);\n int upper_count = 0;\n for (int i = 0; i < monomial_basis.rows(); ++i) {\n S(i, i) = symbolic::Variable(fmt::format(\"S({}, {})\", i, i));\n S_upper(upper_count++) = S(i, i);\n for (int j = i + 1; j < monomial_basis.rows(); ++j) {\n S(i, j) = symbolic::Variable(fmt::format(\"S({}, {})\", i, j));\n S_upper(upper_count++) = S(i, j);\n S(j, i) = S(i, j);\n }\n }\n\n symbolic::Polynomial p;\n for (int i = 0; i < S.rows(); ++i) {\n p.AddProduct(S(i, i), symbolic::pow(monomial_basis(i), 2));\n for (int j = i + 1; j < S.cols(); ++j) {\n p.AddProduct(2 * S(i, j), monomial_basis(i) * monomial_basis(j));\n }\n }\n symbolic::Environment env;\n // Test with S = 𝟏 (every entry of S is 1). During EvaluatePartial, we will\n // compute S(i, j) * monomial_basis(i) * monomial_basis(j). Since S(i, j) = 1,\n // each term will have non-zero coefficient (there won't be two terms\n // cancelling each other).\n env.insert(S_upper, Eigen::VectorXd::Ones(S_upper.rows()));\n for (auto _ : state) {\n const auto p_evaluate = p.EvaluatePartial(env);\n }\n}\n\nvoid BenchmarkMatrixInnerProduct(benchmark::State& state) { // NOLINT\n const int n = state.range(0);\n const bool sparse_Q = state.range(1);\n Eigen::MatrixXd Q(n, n);\n if (sparse_Q) {\n Q.setZero();\n for (int i = 0; i < n; ++i) {\n Q(i, i) = std::sin(i);\n }\n } else {\n for (int i = 0; i < n; ++i) {\n Q(i, i) = std::sin(i);\n for (int j = i + 1; j < n; ++j) {\n Q(i, j) = std::cos(i + 2 * j);\n Q(j, i) = Q(i, j);\n }\n }\n }\n MatrixX<symbolic::Variable> X(n, n);\n for (int i = 0; i < n; ++i) {\n X(i, i) = symbolic::Variable(fmt::format(\"X({}, {})\", i, i));\n for (int j = i + 1; j < n; ++j) {\n X(i, j) = symbolic::Variable(fmt::format(\"X({}, {})\", i, j));\n X(j, i) = X(i, j);\n }\n }\n\n for (auto _ : state) {\n symbolic::Polynomial((Q * X).trace());\n }\n}\n\nBENCHMARK(BenchmarkPolynomialEvaluatePartial)->Unit(benchmark::kMicrosecond);\nBENCHMARK(BenchmarkMatrixInnerProduct)\n ->ArgsProduct({{10, 50, 100, 200}, {false, true}})\n ->Unit(benchmark::kSecond);\n} // namespace\n} // namespace symbolic\n} // namespace drake\n" }, { "alpha_fraction": 0.6719551086425781, "alphanum_fraction": 0.6834134459495544, "avg_line_length": 38.8722038269043, "blob_id": "12c98637f67de23e43e10f974cf2c9bf9e6c2e71", "content_id": "4e3daec977dd4911beec234b2378bf1f265d1297", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 12480, "license_type": "permissive", "max_line_length": 80, "num_lines": 313, "path": "/multibody/plant/test/joint_locking_test.cc", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#include <limits>\n#include <memory>\n#include <utility>\n#include <vector>\n\n#include <gmock/gmock.h>\n#include <gtest/gtest.h>\n\n#include \"drake/math/rigid_transform.h\"\n#include \"drake/multibody/plant/multibody_plant.h\"\n#include \"drake/multibody/tree/revolute_joint.h\"\n#include \"drake/multibody/tree/rigid_body.h\"\n#include \"drake/multibody/tree/spatial_inertia.h\"\n#include \"drake/systems/analysis/simulator.h\"\n#include \"drake/systems/framework/context.h\"\n\nnamespace drake {\n\nusing Eigen::Vector3d;\nusing math::RigidTransform;\nusing math::RigidTransformd;\nusing math::RotationMatrix;\nusing systems::Context;\nusing systems::Simulator;\n\nnamespace multibody {\n\nclass MultibodyPlantTester {\n public:\n MultibodyPlantTester() = delete;\n\n static const std::vector<int>& EvalJointLockingIndices(\n const MultibodyPlant<double>& plant, const Context<double>& context) {\n return plant.EvalJointLockingIndices(context);\n }\n};\n\nnamespace {\n\nconst double kTimestep = 0.01;\nconst double kElbowPosition = 0.3;\nconst double kArmLength = 0.1;\n\n// Set up a plant with 2 trees, one tree having a single floating body, the\n// second tree a serial chain of two bodies attached to each other and world by\n// revolute joints.\nclass JointLockingTest : public ::testing::TestWithParam<int> {\n public:\n void SetUp() {\n plant_ = std::make_unique<MultibodyPlant<double>>(kTimestep);\n\n // Each permutation of adding trees (children of world body) to the plant.\n switch (GetParam()) {\n case 0:\n AddFloatingPendulum();\n AddDoublePendulum();\n break;\n case 1:\n AddDoublePendulum();\n AddFloatingPendulum();\n break;\n }\n\n plant_->Finalize();\n context_ = plant_->CreateDefaultContext();\n }\n\n protected:\n std::unique_ptr<MultibodyPlant<double>> plant_;\n std::unique_ptr<Context<double>> context_;\n\n private:\n void AddFloatingPendulum() {\n // To avoid unnecessary warnings/errors, use a non-zero spatial inertia.\n plant_->AddRigidBody(\"body1\", SpatialInertia<double>::MakeUnitary());\n plant_->AddRigidBody(\"body2\", SpatialInertia<double>::MakeUnitary());\n\n std::unique_ptr<RevoluteJoint<double>> body1_body2 =\n std::make_unique<RevoluteJoint<double>>(\n \"body1_body2\", plant_->GetRigidBodyByName(\"body1\").body_frame(),\n plant_->GetRigidBodyByName(\"body2\").body_frame(),\n Vector3d::UnitZ());\n plant_->AddJoint(std::move(body1_body2));\n }\n\n void AddDoublePendulum() {\n // To avoid unnecessary warnings/errors, use a non-zero spatial inertia.\n plant_->AddRigidBody(\"body3\", SpatialInertia<double>::MakeUnitary());\n plant_->AddRigidBody(\"body4\", SpatialInertia<double>::MakeUnitary());\n\n std::unique_ptr<RevoluteJoint<double>> world_body3 =\n std::make_unique<RevoluteJoint<double>>(\n \"world_body3\", plant_->world_frame(),\n plant_->GetRigidBodyByName(\"body3\").body_frame(),\n Vector3d::UnitZ());\n std::unique_ptr<RevoluteJoint<double>> body3_body4 =\n std::make_unique<RevoluteJoint<double>>(\n \"body3_body4\", plant_->GetRigidBodyByName(\"body3\").body_frame(),\n plant_->GetRigidBodyByName(\"body4\").body_frame(),\n Vector3d::UnitZ());\n\n plant_->AddJoint(std::move(world_body3));\n plant_->AddJoint(std::move(body3_body4));\n }\n};\n\n// Test that regardless of the order the joints were added to the plant (i.e.\n// different joint indexing orders), the established joint locking velocity\n// indexing remains correct.\nTEST_P(JointLockingTest, JointLockingIndicesTest) {\n const RigidBody<double>& body1 = plant_->GetRigidBodyByName(\"body1\");\n\n const RevoluteJoint<double>& body1_body2 =\n plant_->GetJointByName<RevoluteJoint>(\"body1_body2\");\n const RevoluteJoint<double>& world_body3 =\n plant_->GetJointByName<RevoluteJoint>(\"world_body3\");\n RevoluteJoint<double>& body3_body4 =\n plant_->GetMutableJointByName<RevoluteJoint>(\"body3_body4\");\n\n const int body1_velocity_start =\n body1.floating_velocities_start() - plant_->num_positions();\n\n // No joints/bodies are locked, all joint/body velocity indices should exist.\n {\n const std::vector<int>& unlocked_indices =\n MultibodyPlantTester::EvalJointLockingIndices(plant_, context_);\n\n EXPECT_EQ(unlocked_indices.size(), 9);\n\n const std::vector<int>& expected_unlocked_indices = {\n body1_velocity_start, body1_velocity_start + 1,\n body1_velocity_start + 2, body1_velocity_start + 3,\n body1_velocity_start + 4, body1_velocity_start + 5,\n body1_body2.velocity_start(), world_body3.velocity_start(),\n body3_body4.velocity_start()};\n\n EXPECT_THAT(unlocked_indices,\n testing::UnorderedElementsAreArray(expected_unlocked_indices));\n }\n\n // Lock body3_body4 and re-evaluate joint locking indices\n {\n body3_body4.Lock(context_.get());\n const std::vector<int>& unlocked_indices =\n MultibodyPlantTester::EvalJointLockingIndices(plant_, context_);\n\n EXPECT_EQ(unlocked_indices.size(), 8);\n\n const std::vector<int>& expected_unlocked_indices = {\n body1_velocity_start, body1_velocity_start + 1,\n body1_velocity_start + 2, body1_velocity_start + 3,\n body1_velocity_start + 4, body1_velocity_start + 5,\n body1_body2.velocity_start(), world_body3.velocity_start()};\n\n EXPECT_THAT(unlocked_indices,\n testing::UnorderedElementsAreArray(expected_unlocked_indices));\n }\n\n // Unlock body3_body4 and lock body1 and re-evaluate joint locking indices.\n {\n body3_body4.Unlock(context_.get());\n body1.Lock(context_.get());\n\n const std::vector<int>& unlocked_indices =\n MultibodyPlantTester::EvalJointLockingIndices(plant_, context_);\n\n EXPECT_EQ(unlocked_indices.size(), 3);\n\n const std::vector<int>& expected_unlocked_indices = {\n body1_body2.velocity_start(), world_body3.velocity_start(),\n body3_body4.velocity_start()};\n\n EXPECT_THAT(unlocked_indices,\n testing::UnorderedElementsAreArray(expected_unlocked_indices));\n }\n}\n\nINSTANTIATE_TEST_SUITE_P(IndexPermutations, JointLockingTest,\n ::testing::Values(0, 1));\n\n// Create a plant with a XZ-planar double pendulum where the masses are\n// concentrated at the lower ends of the two links. The 0-configuration has the\n// upper arm sticking out horizontally at (-kArmLength, 0, 0) and the lower\n// arm placed at (-kArmLength, 0, 0.0) relative to the upper arm's frame. If the\n// `weld_elbow` parameter is true, then the revolute joint between bodies\n// `upper_arm` and `lower_arm` is replaced with a fixed weld corresponding to\n// the configuration (0, kElbowPosition) in the model with two joints.\nstd::unique_ptr<MultibodyPlant<double>> MakeDoublePendulumPlant(\n bool weld_elbow) {\n std::unique_ptr<MultibodyPlant<double>> plant;\n plant = std::make_unique<MultibodyPlant<double>>(kTimestep);\n\n const RigidBody<double>& body1 =\n plant->AddRigidBody(\"upper_arm\", SpatialInertia<double>::MakeUnitary());\n const RigidBody<double>& body2 =\n plant->AddRigidBody(\"lower_arm\", SpatialInertia<double>::MakeUnitary());\n\n plant->AddJoint<RevoluteJoint>(\"shoulder\", plant->world_body(), {}, body1,\n RigidTransformd(Vector3d(kArmLength, 0, 0)),\n Vector3d::UnitY());\n\n if (weld_elbow) {\n plant->WeldFrames(\n body1.body_frame(), body2.body_frame(),\n RigidTransformd(Vector3d(-kArmLength * cos(kElbowPosition), 0.0,\n kArmLength * sin(kElbowPosition))));\n } else {\n plant->AddJoint<RevoluteJoint>(\n \"elbow\", body1, {}, body2,\n RigidTransformd(Vector3d(kArmLength, 0, 0.0)), Vector3d::UnitY());\n }\n plant->Finalize();\n return plant;\n}\n\n// To verify that the physical behavior of a locked joint is identical to a weld\n// joint, we construct two plants. Each plant consists of a double pendulum with\n// the shoulder welded to the world. The elbow joint of `plant_welded` is\n// replaced with a WeldJoint fixed at configuration (0, kElbowPosition). The\n// elbow joint of `plant_locked` is a revolute joint that has been locked at the\n// configuration (0, kElbowPosition). We verify that the generalized\n// accelerations, velocities and positions match to a given accuracy at each\n// timestep.\nGTEST_TEST(JointLockingTest, TrajectoryTest) {\n // Allow 2 digits of precision loss to account for roundoff differences\n // between the two code paths. This value was determined empircally by\n // observing the maximum error between the two trajectories.\n const double kEps = 1e2 * std::numeric_limits<double>::epsilon();\n const int kNumTimesteps = 100;\n auto plant_welded = MakeDoublePendulumPlant(true);\n auto plant_locked = MakeDoublePendulumPlant(false);\n\n std::unique_ptr<systems::Context<double>> context_welded =\n plant_welded->CreateDefaultContext();\n std::unique_ptr<systems::Context<double>> context_locked =\n plant_locked->CreateDefaultContext();\n\n // Lock the elbow in the unwelded plant.\n const RevoluteJoint<double>& elbow =\n plant_locked->GetJointByName<RevoluteJoint>(\"elbow\");\n elbow.set_angle(context_locked.get(), kElbowPosition);\n elbow.Lock(context_locked.get());\n\n // Sanity check.\n ASSERT_EQ(plant_welded->num_velocities(), 1);\n ASSERT_EQ(plant_locked->num_velocities(), 2);\n\n auto simulator_welded = std::make_unique<Simulator<double>>(\n plant_welded, std::move(context_welded));\n auto simulator_locked = std::make_unique<Simulator<double>>(\n plant_locked, std::move(context_locked));\n simulator_welded->Initialize();\n simulator_locked->Initialize();\n\n // Simulate for kNumTimesteps and verify acceleration, velocity, and positions\n // at each iteration.\n for (int i = 1; i <= kNumTimesteps; ++i) {\n simulator_welded->AdvanceTo(i * kTimestep);\n simulator_locked->AdvanceTo(i * kTimestep);\n\n const auto& welded_context =\n plant_welded->GetMyContextFromRoot(simulator_welded->get_context());\n const auto& locked_context =\n plant_locked->GetMyContextFromRoot(simulator_locked->get_context());\n\n int shoulder_index_welded =\n plant_welded->GetJointByName<RevoluteJoint>(\"shoulder\")\n .velocity_start();\n int shoulder_index_locked =\n plant_locked->GetJointByName<RevoluteJoint>(\"shoulder\")\n .velocity_start();\n\n // The welded plant has only one dof, shoulder. The acceleration of each\n // plant at the corresponding dof should match.\n const auto welded_accelerations =\n plant_welded->get_generalized_acceleration_output_port().Eval(\n welded_context);\n const auto locked_accelerations =\n plant_locked->get_generalized_acceleration_output_port().Eval(\n locked_context);\n EXPECT_NEAR(welded_accelerations[shoulder_index_welded],\n locked_accelerations[shoulder_index_locked], kEps);\n // The locked elbow dof should have 0 acceleration.\n int elbow_index_locked =\n plant_locked->GetJointByName<RevoluteJoint>(\"elbow\").velocity_start();\n EXPECT_EQ(locked_accelerations[elbow_index_locked], 0);\n\n // Check that the velocities and positions of corresponding dofs match.\n Eigen::VectorBlock<const VectorX<double>> welded_positions_and_velocities =\n plant_welded->GetPositionsAndVelocities(welded_context);\n Eigen::VectorBlock<const VectorX<double>> locked_positions_and_velocities =\n plant_locked->GetPositionsAndVelocities(locked_context);\n\n EXPECT_NEAR(welded_positions_and_velocities[shoulder_index_welded],\n locked_positions_and_velocities[shoulder_index_locked], kEps);\n EXPECT_NEAR(welded_positions_and_velocities[plant_welded->num_positions() +\n shoulder_index_welded],\n locked_positions_and_velocities[plant_locked->num_positions() +\n shoulder_index_locked],\n kEps);\n\n // Position of the locked joint should be identically kElbowPosition.\n // Velocity of the locked joint should be identically 0.\n EXPECT_EQ(locked_positions_and_velocities[elbow_index_locked],\n kElbowPosition);\n EXPECT_EQ(locked_positions_and_velocities[plant_locked->num_positions() +\n elbow_index_locked],\n 0);\n }\n}\n} // namespace\n} // namespace multibody\n} // namespace drake\n" }, { "alpha_fraction": 0.7396449446678162, "alphanum_fraction": 0.7573964595794678, "avg_line_length": 30.6875, "blob_id": "fdd8f9dadb34ef60f22ec5e55cff83e4bb745342", "content_id": "ac411de344aacdca10445e056c55d4a746ca57e0", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 507, "license_type": "permissive", "max_line_length": 77, "num_lines": 16, "path": "/bindings/pydrake/solvers/mixed_integer_rotation_constraint.py", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "\"\"\"Shim module that provides vestigial names for pydrake.solvers.\n\nPrefer not to use this import path in new code; all of the code in\nthis module can be imported from pydrake.solvers directly.\n\"\"\"\n\nfrom pydrake.common.deprecation import _warn_deprecated\n\nfrom pydrake.solvers import (\n MixedIntegerRotationConstraintGenerator,\n)\n\n_warn_deprecated(\n \"Please import from the pydrake.solvers module directly, instead of the \"\n f\"deprecated {__name__} submodule.\",\n date=\"2023-05-01\", stacklevel=3)\n" }, { "alpha_fraction": 0.7638888955116272, "alphanum_fraction": 0.7861111164093018, "avg_line_length": 36.894737243652344, "blob_id": "27c1faadb999ab253805b0144771f5f2f8ea0637", "content_id": "d8d0a9091cada7bfd45a463d08d62bc4f8d603c2", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 720, "license_type": "permissive", "max_line_length": 214, "num_lines": 19, "path": "/systems/trajectory_optimization/stub/multiple_shooting.h", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#pragma once\n\n#warning The include path drake/systems/trajectory_optimization/multiple_shooting.h is deprecated and will be removed on or after 2023-05-01; instead, use drake/planning/trajectory_optimization/multiple_shooting.h.\n\n#include \"drake/common/drake_deprecated.h\"\n#include \"drake/planning/trajectory_optimization/multiple_shooting.h\"\n\nnamespace drake {\nnamespace systems {\nnamespace trajectory_optimization {\n\nusing MultipleShooting DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use drake::planning::trajectory_optimization::MultipleShooting \"\n \"instead.\") = drake::planning::trajectory_optimization::MultipleShooting;\n\n} // namespace trajectory_optimization\n} // namespace systems\n} // namespace drake\n" }, { "alpha_fraction": 0.7348754405975342, "alphanum_fraction": 0.7508896589279175, "avg_line_length": 30.22222137451172, "blob_id": "34f1710299ffe8e81fce210d59aaeff377b638ba", "content_id": "cca3cbea34058e6653e618e2811336f8ddf9ed40", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 562, "license_type": "permissive", "max_line_length": 78, "num_lines": 18, "path": "/bindings/pydrake/examples/compass_gait.py", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "\"\"\"Shim module that provides vestigial names for pydrake.examples.\nPrefer not to use this import path in new code; all of the code in\nthis module can be imported from pydrake.examples directly.\n\"\"\"\n\nfrom pydrake.common.deprecation import _warn_deprecated\n\nfrom pydrake.examples import (\n CompassGait,\n CompassGaitContinuousState,\n CompassGaitGeometry,\n CompassGaitParams,\n)\n\n_warn_deprecated(\n \"Please import from the pydrake.examples module directly, instead of the \"\n f\"deprecated {__name__} submodule.\",\n date=\"2023-05-01\", stacklevel=3)\n" }, { "alpha_fraction": 0.7301587462425232, "alphanum_fraction": 0.7402116656303406, "avg_line_length": 34, "blob_id": "05e71b0e8b9128d19a8fa19aceb790226a4b2bd9", "content_id": "60aa6f1e9a210faa775d3b9b1aef2f6f049c72ce", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 3780, "license_type": "permissive", "max_line_length": 84, "num_lines": 108, "path": "/systems/trajectory_optimization/test/deprecation_test.cc", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "// This file serves to check that our deprecation shims compile successfully,\n// aside from warning messages. We can remove this file entirely once the\n// deprecation period ends.\n#include <type_traits>\n\n#include <gtest/gtest.h>\n\n#include \"drake/common/trajectories/piecewise_polynomial.h\"\n#include \"drake/systems/primitives/linear_system.h\"\n#include \"drake/systems/trajectory_optimization/direct_collocation.h\"\n#include \"drake/systems/trajectory_optimization/direct_transcription.h\"\n#include \"drake/systems/trajectory_optimization/integration_constraint.h\"\n#include \"drake/systems/trajectory_optimization/kinematic_trajectory_optimization.h\"\n#include \"drake/systems/trajectory_optimization/multiple_shooting.h\"\n#include \"drake/systems/trajectory_optimization/sequential_expression_manager.h\"\n\nnamespace drake {\nnamespace systems {\nnamespace trajectory_optimization {\nnamespace {\n\nusing trajectories::PiecewisePolynomial;\n\nGTEST_TEST(PathDeprecation, DirectCollocationAndConstraint) {\n // Exercise the single type declared in the header.\n // xdot = -x.\n systems::LinearSystem<double> plant(\n Vector1d(-1.0), // A\n Eigen::Matrix<double, 1, 0>::Zero(), // B\n Eigen::Matrix<double, 0, 1>::Zero(), // C\n Eigen::Matrix<double, 0, 0>::Zero()); // D\n\n auto context = plant.CreateDefaultContext();\n const int kNumSampleTimes{10};\n const double kFixedTimeStep{0.1};\n EXPECT_NO_THROW(DirectCollocation(&plant, context, kNumSampleTimes,\n kFixedTimeStep, kFixedTimeStep));\n EXPECT_NO_THROW(DirectCollocationConstraint(plant, context));\n\n EXPECT_TRUE(std::is_function_v<decltype(AddDirectCollocationConstraint)>);\n}\n\nGTEST_TEST(PathDeprecation, DirectTranscription) {\n Eigen::Matrix2d A, B;\n // clang-format off\n A << 1, 2,\n 3, 4;\n B << 5, 6,\n 7, 8;\n // clang-format on\n const Eigen::MatrixXd C(0, 2), D(0, 2);\n const double kTimeStep = .1;\n LinearSystem<double> system(A, B, C, D, kTimeStep);\n\n const auto context = system.CreateDefaultContext();\n int kNumSampleTimes = 3;\n\n // Main class defined in header.\n EXPECT_NO_THROW(DirectTranscription(&system, context, kNumSampleTimes));\n\n // Supporting struct defined in header.\n EXPECT_NO_THROW(TimeStep(0.5));\n}\n\n// Minimum empty class to confirm that the base class exists.\nclass MyDirectTrajOpt : public MultipleShooting {\n public:\n // Arbitrary constants that make the base constructor sufficiently happy.\n MyDirectTrajOpt() : MultipleShooting(1, 1, 2, 1) {}\n\n PiecewisePolynomial<double> ReconstructInputTrajectory(\n const solvers::MathematicalProgramResult&) const override {\n return PiecewisePolynomial<double>();\n };\n\n PiecewisePolynomial<double> ReconstructStateTrajectory(\n const solvers::MathematicalProgramResult&) const override {\n return PiecewisePolynomial<double>();\n };\n\n private:\n void DoAddRunningCost(const symbolic::Expression& g) override {}\n};\n\nGTEST_TEST(PathDeprecation, MultipleShootings) {\n // Include both* types declared in the header file.\n EXPECT_NO_THROW(MyDirectTrajOpt());\n}\n\nGTEST_TEST(PathDeprecation, IntegrationConstraint) {\n // Arbitrary constants that make the base constructor sufficiently happy.\n EXPECT_NO_THROW(MidPointIntegrationConstraint(1));\n}\n\nGTEST_TEST(PathDeprecation, KinematicTrajectoryOptimization) {\n // Arbitrary constants that make the base constructor sufficiently happy.\n EXPECT_NO_THROW(KinematicTrajectoryOptimization(5, 5));\n}\n\nGTEST_TEST(PathDeprecation, SequentialExpressionManager) {\n // Arbitrary constants that make the base constructor sufficiently happy.\n EXPECT_NO_THROW(internal::SequentialExpressionManager(1));\n}\n\n} // namespace\n} // namespace trajectory_optimization\n} // namespace systems\n} // namespace drake\n" }, { "alpha_fraction": 0.6370262503623962, "alphanum_fraction": 0.6370262503623962, "avg_line_length": 27.58333396911621, "blob_id": "43dc7c09268ca1ee94e0297e6cce8a91a7eb3b2c", "content_id": "f3016e6a622717072051acdf80710598ef4be2d1", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 686, "license_type": "permissive", "max_line_length": 76, "num_lines": 24, "path": "/math/autodiff_gradient.cc", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#include \"drake/math/autodiff_gradient.h\"\n\nnamespace drake {\nnamespace math {\n\nbool AreAutoDiffVecXdEqual(const Eigen::Ref<const VectorX<AutoDiffXd>>& a,\n const Eigen::Ref<const VectorX<AutoDiffXd>>& b) {\n if (a.rows() != b.rows()) {\n return false;\n }\n if (math::ExtractValue(a) != math::ExtractValue(b)) {\n return false;\n }\n const Eigen::MatrixXd a_gradient = math::ExtractGradient(a);\n const Eigen::MatrixXd b_gradient = math::ExtractGradient(b);\n if (a_gradient.rows() != b_gradient.rows() \|\|\n a_gradient.cols() != b_gradient.cols()) {\n return false;\n }\n return a_gradient == b_gradient;\n}\n\n} // namespace math\n} // namespace drake\n" }, { "alpha_fraction": 0.6467005014419556, "alphanum_fraction": 0.6568527817726135, "avg_line_length": 41.826087951660156, "blob_id": "b3c2fd8c07ae48c3a95af8dbd866b01adc856a3d", "content_id": "31adfb16564b50e9c03000f25da81a0a99faa05a", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 985, "license_type": "permissive", "max_line_length": 78, "num_lines": 23, "path": "/bindings/pydrake/systems/test/trajectory_optimization_dep_test.py", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "from pydrake.common.test_utilities.deprecation import catch_drake_warnings\n\nimport unittest\n\n\nclass TestDeprecation(unittest.TestCase):\n def test_deprecated_symbols_exist(self):\n # The whole point of this test is that we can access the same symbols\n # tested in\n # /bindings/pydrake/planning/test/trajectory_optimization_test.py via\n # the old, deprecated module path. We should get a single deprecation\n # warning on the module. Otherwise, all of the given symbols should be\n # successfully imported.\n with catch_drake_warnings(expected_count=1) as w:\n from pydrake.systems.trajectory_optimization import (\n AddDirectCollocationConstraint,\n DirectCollocation,\n DirectCollocationConstraint,\n DirectTranscription,\n KinematicTrajectoryOptimization,\n TimeStep,\n )\n self.assertIn(\"2023-05-01\", str(w[0].message))\n" }, { "alpha_fraction": 0.7660455703735352, "alphanum_fraction": 0.782608687877655, "avg_line_length": 41.617645263671875, "blob_id": "fc6d33ae04f78dbd01e07a38b974250f24cad46a", "content_id": "2a18d04a8e1e12891222014b87e962806cee3cac", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 1449, "license_type": "permissive", "max_line_length": 216, "num_lines": 34, "path": "/systems/trajectory_optimization/stub/direct_collocation.h", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#pragma once\n\n#warning The include path drake/systems/trajectory_optimization/direct_collocation.h is deprecated and will be removed on or after 2023-05-01; instead, use drake/planning/trajectory_optimization/direct_collocation.h.\n\n#include \"drake/common/drake_deprecated.h\"\n#include \"drake/planning/trajectory_optimization/direct_collocation.h\"\n// Deprecated includes from original include file.\n#include \"drake/systems/trajectory_optimization/multiple_shooting.h\"\n\nnamespace drake {\nnamespace systems {\nnamespace trajectory_optimization {\n\nusing DirectCollocation DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use drake::planning::trajectory_optimization::DirectCollocation \"\n \"instead.\") = drake::planning::trajectory_optimization::DirectCollocation;\n\nusing DirectCollocationConstraint DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use \"\n \"drake::planning::trajectory_optimization::DirectCollocationConstraint \"\n \"instead.\") =\n drake::planning::trajectory_optimization::DirectCollocationConstraint;\n\n// We can't apply the deprecated attribute to this function alias (it's not\n// truly an alias). We'll rely on the #warning at the top as sufficient.\n// The odds that they are importing the right header but exercising the function\n// from the wrong namespace is small.\nusing planning::trajectory_optimization::AddDirectCollocationConstraint;\n\n} // namespace trajectory_optimization\n} // namespace systems\n} // namespace drake\n" }, { "alpha_fraction": 0.7666214108467102, "alphanum_fraction": 0.7788330912590027, "avg_line_length": 42.35293960571289, "blob_id": "926ea7ffe4a94c8abefb701eb458d9a76998eb98", "content_id": "8d1cfa9da15cf1781ec8baa8687e5e894b1ec247", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 737, "license_type": "permissive", "max_line_length": 78, "num_lines": 17, "path": "/bindings/pydrake/systems/trajectory_optimization.py", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "\"\"\"Deprecated aliases to planning resources.\"\"\"\n\nfrom pydrake.common.deprecation import _warn_deprecated\n\n# Note: This imports more than just the trajectory optimization symbols\n# (because planning is flat). If this is too generous in exposing planning\n# symbols in this module, we'll need to enumerate all the former members of\n# this module explicitly.\nfrom pydrake.planning import *\n# Historically, TimeStep belonged to the module; pull it out to maintain\n# backwards compatibility until completed deprecation.\nTimeStep = DirectTranscription.TimeStep\n\n_warn_deprecated(\n \"Please import the trajectory optimization from pydrake.planning instead \"\n f\"of the deprecated {__name__} submodule.\",\n date=\"2023-05-01\", stacklevel=3)\n" }, { "alpha_fraction": 0.7677946090698242, "alphanum_fraction": 0.7864643931388855, "avg_line_length": 36.260868072509766, "blob_id": "a849006d8a50435fff9348d7dc9292dde5c69573", "content_id": "c38fe24137b7b1bca903aa3646032bb6acc64cbd", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 857, "license_type": "permissive", "max_line_length": 238, "num_lines": 23, "path": "/systems/trajectory_optimization/stub/sequential_expression_manager.h", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#pragma once\n\n#warning The include path drake/systems/trajectory_optimization/sequential_expression_manager.h is deprecated and will be removed on or after 2023-05-01; instead, use drake/planning/trajectory_optimization/sequential_expression_manager.h.\n\n#include \"drake/common/drake_deprecated.h\"\n#include \"drake/planning/trajectory_optimization/sequential_expression_manager.h\"\n\nnamespace drake {\nnamespace systems {\nnamespace trajectory_optimization {\nnamespace internal {\n\nusing SequentialExpressionManager DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use \"\n \"drake::planning::trajectory_optimization::SequentialExpressionManager \"\n \"instead.\") = drake::planning::trajectory_optimization::internal::\n SequentialExpressionManager;\n\n} // namespace internal\n} // namespace trajectory_optimization\n} // namespace systems\n} // namespace drake\n" }, { "alpha_fraction": 0.7694267630577087, "alphanum_fraction": 0.7898089289665222, "avg_line_length": 36.380950927734375, "blob_id": "e75ce10e8532aa8ff9e116a5bc262708492f3b05", "content_id": "c09f35364c31e20d51882747d06e650a89ac7f20", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 785, "license_type": "permissive", "max_line_length": 224, "num_lines": 21, "path": "/systems/trajectory_optimization/stub/integration_constraint.h", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "#pragma once\n\n#warning The include path drake/systems/trajectory_optimization/integration_constraint.h is deprecated and will be removed on or after 2023-05-01; instead, use drake/planning/trajectory_optimization/integration_constraint.h.\n\n#include \"drake/common/drake_deprecated.h\"\n#include \"drake/planning/trajectory_optimization/integration_constraint.h\"\n\nnamespace drake {\nnamespace systems {\nnamespace trajectory_optimization {\n\nusing MidPointIntegrationConstraint DRAKE_DEPRECATED(\n \"2023-05-01\",\n \"Please use \"\n \"drake::planning::trajectory_optimization::MidPointIntegrationConstraint \"\n \"instead.\") =\n drake::planning::trajectory_optimization::MidPointIntegrationConstraint;\n\n} // namespace trajectory_optimization\n} // namespace systems\n} // namespace drake\n" }, { "alpha_fraction": 0.7320061326026917, "alphanum_fraction": 0.7404288053512573, "avg_line_length": 24.115385055541992, "blob_id": "4d86cf343da4e4ffb4bcd07fad0a19e09adf34e2", "content_id": "17f77ef9cbe437cddb5d867187622982309a66ef", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1306, "license_type": "permissive", "max_line_length": 77, "num_lines": 52, "path": "/bindings/pydrake/solvers/mathematicalprogram.py", "repo_name": "mpetersen94/drake", "src_encoding": "UTF-8", "text": "\"\"\"Shim module that provides vestigial names for pydrake.solvers.\n\nPrefer not to use this import path in new code; all of the code in\nthis module can be imported from pydrake.solvers directly.\n\"\"\"\n\nfrom pydrake.common.deprecation import _warn_deprecated\n\nfrom pydrake.solvers import (\n Binding,\n BoundingBoxConstraint,\n ChooseBestSolver,\n CommonSolverOption,\n Constraint,\n Cost,\n EvaluatorBase,\n ExponentialConeConstraint,\n GetAvailableSolvers,\n GetProgramType,\n L1NormCost,\n L2NormCost,\n LInfNormCost,\n LinearComplementarityConstraint,\n LinearConstraint,\n LinearCost,\n LinearEqualityConstraint,\n LinearMatrixInequalityConstraint,\n LorentzConeConstraint,\n MakeFirstAvailableSolver,\n MakeSolver,\n MathematicalProgram,\n MathematicalProgramResult,\n PerspectiveQuadraticCost,\n PositiveSemidefiniteConstraint,\n ProgramType,\n PyFunctionConstraint,\n QuadraticConstraint,\n QuadraticCost,\n RotatedLorentzConeConstraint,\n SolutionResult,\n Solve,\n SolverId,\n SolverInterface,\n SolverOptions,\n SolverType,\n VisualizationCallback,\n)\n\n_warn_deprecated(\n \"Please import from the pydrake.solvers module directly, instead of the \"\n f\"deprecated {__name__} submodule.\",\n date=\"2023-05-01\", stacklevel=3)\n" } ]	14
ViKrAm-Bais/Machine-Learning-with-Python	https://github.com/ViKrAm-Bais/Machine-Learning-with-Python	6707760a6ae58053c304184c41ba79862ceb9b9d	35dcaac6f3c60353962b69b35e185f4e09e26adf	a794c5d2b04218952cef4621a346d624f829a38e	refs/heads/master	2023-09-02T23:13:13.319227	2020-07-26T13:35:06	2020-07-26T13:35:06	277,098,466	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5530434846878052, "alphanum_fraction": 0.6208695769309998, "avg_line_length": 16.303030014038086, "blob_id": "46c61a2efe8fb2ffe42318330668e2b3f8cb6e05", "content_id": "608a2d6c66682520f36472a0220626c336d514fd", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 575, "license_type": "permissive", "max_line_length": 78, "num_lines": 33, "path": "/clustering/hierarchical_clustering/hierarchical_clustering.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn.cluster import AgglomerativeClustering\nx=np.array([[1,2],[3,1],[1,1],[5,7],[5,5],[4,8],[6,6],[0,0],[0,5],[1,6]])\nplt.scatter(x[:,0],x[:,1],marker=\".\",c=\"m\",s=150,linewidth=2)\nplt.show()\n\n\n# In[5]:\n\n\ncluster=AgglomerativeClustering(n_clusters=3)\ncluster.fit(x)\nlabel=cluster.labels_\nprint(label)\ncolors=['c','m','b']\n\n\n# In[13]:\n\n\nfor i in range(0,len(x)):\n plt.scatter(x[i,0],x[i,1],marker=\"\",c=colors[label[i]],s=150,linewidth=0)\nplt.show()\n\n\n# In[ ]:\n\n\n\n\n" }, { "alpha_fraction": 0.6532333493232727, "alphanum_fraction": 0.6776007413864136, "avg_line_length": 10.189474105834961, "blob_id": "c493bdd87c452320727bbb97ed9d824b0585639b", "content_id": "08ace4df805a62bb65875c0cd8dd438a7260b0d2", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1067, "license_type": "permissive", "max_line_length": 68, "num_lines": 95, "path": "/classification/random_forest/Random_Forest.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# # Random Forest\n\n# In[3]:\n\n\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.datasets import load_digits\ndigits=load_digits()\n\n\n# In[16]:\n\n\nprint(digits.keys())\nprint(digits.data.shape)\n\n\n# In[7]:\n\n\nplt.gray()\nfor i in range(4):\n plt.matshow(digits.images[i])\n\n\n# In[15]:\n\n\ndf=pd.DataFrame(digits.data)\ndf.head()\n\n\n# In[18]:\n\n\ndf['target']=digits.target\ndf.head()\n\n\n# In[22]:\n\n\nfrom sklearn.model_selection import train_test_split\nx=df.drop(['target'],axis='columns')\ny=df['target']\nx_train, x_test, y_train, y_test=train_test_split(x,y,test_size=0.2)\n\n\n# In[40]:\n\n\nfrom sklearn.ensemble import RandomForestClassifier\nmodel=RandomForestClassifier()\nmodel.fit(x_train,y_train)\n\n\n# In[41]:\n\n\nmodel.score(x_test, y_test)\n\n\n# In[42]:\n\n\ny_predicted=model.predict(x_test)\n\n\n# In[43]:\n\n\nfrom sklearn.metrics import confusion_matrix\ncm=confusion_matrix(y_test,y_predicted)\n\n\n# In[44]:\n\n\ncm\n\n\n# In[46]:\n\n\nimport seaborn as sns\nsns.heatmap(cm,annot=True)\nplt.xlabel(\"y_test\")\nplt.ylabel(\"y_predicted\")\n\n\n# In[ ]:\n\n\n\n\n" }, { "alpha_fraction": 0.6309133768081665, "alphanum_fraction": 0.6833723783493042, "avg_line_length": 12.236024856567383, "blob_id": "8dad3afc5e4ba5d7d551901b54905e7b96536188", "content_id": "db0276d0fdffff746f579d6c0be202d6c1768f40", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2135, "license_type": "permissive", "max_line_length": 87, "num_lines": 161, "path": "/regression/regression.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# In[7]:\n\n\nimport pandas as pd\nimport numpy as np\nfrom sklearn.datasets import load_boston\nimport matplotlib.pyplot as plt\n\n\n# In[8]:\n\n\n#regression\n\n\n# In[9]:\n\n\ndf=load_boston()\n\n\n# In[10]:\n\n\ndataset=pd.DataFrame(df.data)\n\n\n# In[11]:\n\n\nprint(dataset.head())\n\n\n# In[12]:\n\n\ndataset.columns=df.feature_names\n\n\n# In[13]:\n\n\nprint(dataset.head())\n\n\n# In[14]:\n\n\ndataset[\"Price\"]=df.target\n\n\n# In[15]:\n\n\nprint(dataset.head())\n\n\n# In[16]:\n\n\nx=dataset.iloc[:,:-1] # independent features\n\n\n# In[17]:\n\n\ny=dataset.iloc[:,-1] # dependent features\n\n\n# \"\"\"Linear Regression\"\"\"\n\n# In[18]:\n\n\nfrom sklearn.model_selection import cross_val_score \nfrom sklearn.linear_model import LinearRegression \nlin_reg=LinearRegression()\nmse=cross_val_score(lin_reg,x,y,scoring='neg_mean_squared_error',cv=5)\nmean_mse=np.mean(mse)\nprint(mean_mse)\n\n\n# In[19]:\n\n\n\"\"\"ridge regression\"\"\"\n\n\n# In[20]:\n\n\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.linear_model import Ridge\nridge=Ridge()\nparam={\"alpha\":[1e-15, 1e-10, 1e-8, 1e-3, 1e-2, 1, 5, 10, 20, 30, 35, 40, 45, 55, 100]}\nridge_regressor=GridSearchCV(ridge, param, scoring='neg_mean_squared_error', cv=5 )\nridge_regressor.fit(x,y)\n\n\n# In[21]:\n\n\nprint(ridge_regressor.best_params_)\nprint(ridge_regressor.best_score_)\n\n\n# In[22]:\n\n\n\"\"\"Lasso Regression\"\"\"\n\n\n# In[23]:\n\n\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.linear_model import Lasso\nlasso=Lasso()\nparam={\"alpha\":[1e-15, 1e-10, 1e-8, 1e-3, 1e-2, 1, 5, 10, 20, 30, 35, 40, 45, 55, 100]}\nlasso_regressor=GridSearchCV(lasso, param,scoring='neg_mean_squared_error', cv=5 )\nlasso_regressor.fit(x,y)\n\n\n# In[24]:\n\n\nprint(lasso_regressor.best_params_)\nprint(lasso_regressor.best_score_)\n\n\n# In[27]:\n\n\nfrom sklearn.model_selection import train_test_split\nx_train, x_test, y_train, y_test =train_test_split(x, y, test_size=0.3, random_state=0)\n\n\n# In[29]:\n\n\nprediction_lasso=lasso_regressor.predict(x_test)\nprediction_ridge=ridge_regressor.predict(x_test)\n\n\n# In[30]:\n\n\nimport seaborn as sns\nsns.distplot(y_test-prediction_lasso)\n\n\n# In[31]:\n\n\nsns.distplot(y_test-prediction_lasso)\n\n\n# In[ ]:\n\n\n\n\n" }, { "alpha_fraction": 0.6743044257164001, "alphanum_fraction": 0.6972177028656006, "avg_line_length": 14.037036895751953, "blob_id": "5a26b03e5871199ca9327805ec8190c5194a4059", "content_id": "08964e15b966d7f4627a610e6d96d5d06d601a0c", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1222, "license_type": "permissive", "max_line_length": 66, "num_lines": 81, "path": "/classification/logistic_regression/logistic regression.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# # logistic regression\n\n# importing modules\n\n# In[33]:\n\n\nimport numpy as np\nfrom sklearn.datasets import make_classification\nimport matplotlib.pyplot as plt\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import confusion_matrix\nimport pandas as pd\nimport seaborn as sns\n\n\n# In[34]:\n\n\nx, y = make_classification(\n n_samples=100,\n n_features=1,\n n_classes=2,\n n_clusters_per_class=1,\n flip_y=0.03,\n n_informative=1,\n n_redundant=0,\n n_repeated=0\n)\n\n\n# In[35]:\n\n\nplt.scatter(x,y,c=y,cmap=\"rainbow\")\nplt.title(\"classification using logistic regression\")\n\n\n# split the dataset\n\n# In[36]:\n\n\nx_train,x_test,y_train,y_test=train_test_split(x,y,random_state=1)\n\n\n# performing logistic regression\n\n# In[37]:\n\n\nlog_reg=LogisticRegression()\nlog_reg.fit(x_train,y_train)\nprint(\"Coefficient: \",log_reg.coef_)\nprint(\"Intercept: \",log_reg.intercept_)\n\n\n# testing the model\n\n# In[38]:\n\n\ny_pred=log_reg.predict(x_test)\nprint(\"x shape: \",x_test.shape)\nprint(\"y_pred shape: \",y_pred.shape)\nprint(\"y_test shape: \",y_test.shape)\n\n\n# results\n\n# In[68]:\n\n\nconfusion_matrix(y_test,y_pred)\n\n\n# In[ ]:\n\n\n\n\n" }, { "alpha_fraction": 0.7365792989730835, "alphanum_fraction": 0.7415730357170105, "avg_line_length": 35.3636360168457, "blob_id": "91d78b018161bac01f2c08eef0914ee4782572d7", "content_id": "be4076a1ffe957097642bf4cdbbeaf3946910965", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 801, "license_type": "permissive", "max_line_length": 433, "num_lines": 22, "path": "/README.md", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "# Machine-Learning-with-Python\n\nMachine Learning (ML) is basically that field of computer science with the help of which computer systems can provide sense to data in much the same way as human beings do. In simple words, ML is a type of artificial intelligence that extract patterns out of raw data by using an algorithm or method. The key focus of ML is to allow computer systems to learn from experience without being explicitly programmed or human intervention.\n\nML algorithms:\n1]classification: \n a. logistic regression \n b. support vector machine \n c. decision tree \n d. bayes \n e. random forest\n \n2]Regression\n a. linear regression\n \n3]clustering :\n a. k-mean\n b. mean shift \n c. hierarchical\n \n4]KNN algo(k nearest neighbours):\n finding nearest negihbors \n" }, { "alpha_fraction": 0.5466101765632629, "alphanum_fraction": 0.612994372844696, "avg_line_length": 14.644444465637207, "blob_id": "28e2f433ca29a4d708f73c8093aa099a19799857", "content_id": "a1ee26fd635a92a0c9edb24bf367a3ee91dff3f2", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 708, "license_type": "permissive", "max_line_length": 78, "num_lines": 45, "path": "/clustering/kmeans_clustering/kmean clustering.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# simple kmeans clustering\n\n# In[92]:\n\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn.cluster import KMeans\nx=np.array([[1,2],[3,1],[1,1],[5,7],[5,5],[4,8],[6,6],[0,0],[0,5],[1,6]])\nplt.scatter(x[:,0],x[:,1],marker=\".\",c=\"m\",s=150,linewidth=2)\nplt.show()\n\n\n# In[93]:\n\n\nkmean=KMeans(n_clusters=3)\nkmean.fit(x)\ncen=kmean.cluster_centers_\nlabel=kmean.labels_\nprint(label)\ncolors=['c','m','b']\n\n\n# In[95]:\n\n\nfor i in range(0,len(x)):\n plt.scatter(x[i,0],x[i,1],marker=\".\",c=colors[label[i]],s=150,linewidth=2)\nplt.scatter(cen[:,0],cen[:,1],marker=\"+\",c=\"k\",s=160,linewidth=2)\nplt.show()\n\n\n# kmeans clustering using datasets\n\n# In[ ]:\n\n\n\n\n\n# In[ ]:\n\n\n\n\n" }, { "alpha_fraction": 0.6539855003356934, "alphanum_fraction": 0.6802536249160767, "avg_line_length": 11.5, "blob_id": "630234f24ebf35fc0835de5398171d2aea2efbd5", "content_id": "e33deb4a1c20e5e47a60f8b1c2aa20b68b8321a7", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1104, "license_type": "permissive", "max_line_length": 62, "num_lines": 88, "path": "/classification/decision tree/decision_tree.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# # Decision Tree\n\n# In[28]:\n\n\n# importing libreries\nimport pandas as pd\ndf=pd.read_csv(\"salary.csv\")\ndf.head()\n\n\n# In[29]:\n\n\ninputs=df.drop('salary_more_then_100k', axis='columns')\ntarget=df.drop(['company','job','degree'],axis='columns')\n\n\n# In[30]:\n\n\ninputs.head()\n\n\n# In[31]:\n\n\ntarget.head()\n\n\n# In[32]:\n\n\n\"\"\"machine learning algo works only on numbers ,\nso we have to convert this text into numbers \"\"\" \nfrom sklearn.preprocessing import LabelEncoder\nljob=LabelEncoder()\nlcompany=LabelEncoder()\nldegree=LabelEncoder()\n\n\n# In[33]:\n\n\ninputs[\"ncompany\"]=lcompany.fit_transform(inputs[\"company\"])\ninputs[\"njob\"]=ljob.fit_transform(inputs[\"job\"])\ninputs[\"ndegree\"]=ldegree.fit_transform(inputs[\"degree\"])\ninputs.head()\n\n\n# In[35]:\n\n\nninputs=inputs.drop(['company','job','degree'],axis='columns')\nninputs.head()\n\n\n# In[38]:\n\n\nfrom sklearn.tree import DecisionTreeClassifier\nmodel=DecisionTreeClassifier()\n\n\n# In[39]:\n\n\n#training model \nmodel.fit(ninputs,target)\n\n\n# In[40]:\n\n\nmodel.score(ninputs,target)\n\n\n# In[41]:\n\n\n# check\nmodel.predict([[2,2,1]])\n\n\n# In[ ]:\n\n\n\n\n" }, { "alpha_fraction": 0.6105660200119019, "alphanum_fraction": 0.6399999856948853, "avg_line_length": 11.950980186462402, "blob_id": "1ccbe72b95f3e157424616dfc20f9d67ba7d88d9", "content_id": "66a17dd32d35d2a6bc5c88ed14eb6bf664e9e8e3", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1325, "license_type": "permissive", "max_line_length": 82, "num_lines": 102, "path": "/classification/support_vector_machine/Support Vector Machines.py", "repo_name": "ViKrAm-Bais/Machine-Learning-with-Python", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n# coding: utf-8\n\n# # Support Vector Machines\n\n# In[3]:\n\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\nfrom sklearn.datasets import load_iris\niris=load_iris()\n\n\n# In[5]:\n\n\ndir(iris)\n\n\n# In[13]:\n\n\ndf=pd.DataFrame(iris.data, columns=iris.feature_names)\nprint(df.head())\n\n\n# In[19]:\n\n\ndf[\"target\"]=iris.target\nprint(df.head())\n\n\n# In[21]:\n\n\nprint(iris.target_names)\n\n\n# In[29]:\n\n\ndf[\"flower_names\"]=df.target.apply(lambda x:iris.target_names[x])\nprint(df.head())\n\n\n# In[30]:\n\n\ndf0=df[df.target==0]\ndf1=df[df.target==1]\ndf2=df[df.target==2]\n\n\n# In[41]:\n\n\nplt.xlabel(\"petal length (cm)\")\nplt.ylabel(\"petal width (cm)\")\nplt.title(\"s v m\")\nplt.scatter(df0[\"petal length (cm)\"],df0[\"petal width (cm)\"],marker=\"\",color=\"m\")\nplt.scatter(df1[\"petal length (cm)\"],df1[\"petal width (cm)\"],marker=\"\",color=\"c\")\nplt.scatter(df2[\"petal length (cm)\"],df2[\"petal width (cm)\"],marker=\"\",color=\"b\")\n\n\n# In[50]:\n\n\nx=df.drop(['flower_names','target'],axis='columns')\ny=df.target\n\n\n# In[53]:\n\n\nfrom sklearn.model_selection import train_test_split\nx_train, x_test, y_train, y_test=train_test_split(x, y, test_size=0.2)\n\n\n# In[54]:\n\n\nprint(\"train: \",len(x_train))\nprint(\"test: \",len(x_test))\n\n\n# In[59]:\n\n\nfrom sklearn.svm import SVC\nmodel=SVC()\nmodel.fit(x,y)\n\n\n# In[63]:\n\n\nmodel.score(x_train,y_train)\n\n\n# In[ ]:\n\n\n\n\n" } ]	8
gtsofa/codewars	https://github.com/gtsofa/codewars	791ca3439959fce02cde20b0346fcd63efdcee6d	3d43a7fbb84651f7febd6cfbd3a288682a36a6d4	5c920aadada09b56594eee320b93853791392894	refs/heads/lists	2023-08-22T20:36:39.887468	2023-08-07T10:22:57	2023-08-07T10:22:57	92,287,894	0	0	null	2017-05-24T12:05:53	2023-08-07T10:21:45	2023-08-07T13:51:50	Python	[ { "alpha_fraction": 0.6276202201843262, "alphanum_fraction": 0.6621454954147339, "avg_line_length": 30.076923370361328, "blob_id": "0f7fa6846713161710a00baa5bd7b54020c490ca", "content_id": "4ac2f2ec0ec4000e19df139b70105a49b159c87a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 811, "license_type": "no_license", "max_line_length": 68, "num_lines": 26, "path": "/can_we_divide_it.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Can we divide it ?\n\n\"\"\"\nYour task is to create functionisDivideBy (or is_divide_by) to check\n if an integer number is divisible by each out of two arguments.\n\n Test.describe(\"Basic Tests\")\nTest.it(\"should pass basic tests\")\nTest.assert_equals(is_divide_by(-12, 2, -6), True)\nTest.assert_equals(is_divide_by(-12, 2, -5), False)\nTest.assert_equals(is_divide_by(45, 1, 6), False)\nTest.assert_equals(is_divide_by(45, 5, 15), True)\nTest.assert_equals(is_divide_by(4, 1, 4), True)\nTest.assert_equals(is_divide_by(15, -5, 3), True)\n\n\"\"\"\n# def is_divide_by(number, a, b):\n# return number % a == 0 and number % b == 0\n\n# def is_divide_by(number, a, b):\n# return not (number%a or number%b)\n\ndef is_divide_by(number, a, b):\n\n #return # good luck\n return True if ( number % a == 0 \| number % b == 0) else False\n \n" }, { "alpha_fraction": 0.6085714101791382, "alphanum_fraction": 0.6142857074737549, "avg_line_length": 16.549999237060547, "blob_id": "b4a96602089dfcfbea75acdcc2d5bc87554a5fc1", "content_id": "1d858396cef69efe6d11b832f4aa2ccaedebeeb8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 350, "license_type": "no_license", "max_line_length": 49, "num_lines": 20, "path": "/boolean_to_string_yes_or_no.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Convert boolean values to strings 'Yes' or 'No'.\n\n\"\"\"\nSample Tests:\n\n1\nTest.expect(bool_to_word(True), 'Yes')\n2\nTest.expect(bool_to_word(False), 'No')\n\"\"\"\n\n# def bool_to_word(bool):\n# return \"Yes\" if bool else \"No\"\n\n# def bool_to_word(bool):\n# return ['No', 'Yes'][bool]\n\ndef bool_to_word(bool):\n # TODO\n return 'Yes' if bool else 'No'" }, { "alpha_fraction": 0.6165884137153625, "alphanum_fraction": 0.6306729316711426, "avg_line_length": 28.045454025268555, "blob_id": "7784fde6e0d0bc8ce35e298c3a37decd67a67200", "content_id": "3bd7914b24c2dd7710865ce2393dac648fde4451", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 639, "license_type": "no_license", "max_line_length": 94, "num_lines": 22, "path": "/remove_first_last_character.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "\"\"\"\n Your goal is to create a function that removes the first and last characters of a string. \n You're given one parameter, the original string. \n You don't have to worry with strings with less than two characters.\n\"\"\"\ndef remove_first_last_character(name):\n \"\"\"A function to remove first and last character in a string.\"\"\"\n if len(name) <= 2:\n #return ''\n print('empty')\n else:\n print(name[1:-1])\n \nremove_first_last_character('ok')\n\n# def remove_char(s):\n# return '' if len(s) <= 2 else s[1:-1]\n\n# def remove_char(s):\n# #your code here\n# if s is not None and len(s) > 1:\n# return s[1:len(s)-1]\n" }, { "alpha_fraction": 0.6582064032554626, "alphanum_fraction": 0.6582064032554626, "avg_line_length": 27.190475463867188, "blob_id": "785624248f77031f2f9e63823b3fb0d953a17bc0", "content_id": "5845481f611d62d904ffe981a3d82aa9aa609ddc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 591, "license_type": "no_license", "max_line_length": 85, "num_lines": 21, "path": "/jenny_message.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Jenny's secret message#Jenny's secret message#Jenny's secret message\n\n\"\"\"\nJenny has written a function that returns a greeting for a user. \nHowever, she's in love with Johnny, and would like to greet him \nslightly different. She added a special case to her function, \nbut she made a mistake.\nCan you help her?\n\"\"\"\n\ndef greet(name):\n nome = name.title()\n if nome == \"Johnny\":\n print(\"Hello, my love\" + \"!\")\n else:\n print(\"Hello, \" + nome + \"!\" )\n\ngreet(\"julius\")\n\n# def greet(name):\n# return \"Hello, {name}!\".format(name=name) if name!=\"Johnny\" else \"Hello, my love!\"" }, { "alpha_fraction": 0.591304361820221, "alphanum_fraction": 0.6066889762878418, "avg_line_length": 23.508195877075195, "blob_id": "6ec923b9ac28524477a7cf214d12ae422b764607", "content_id": "4f85189824d1258b52089023e46653f71ade939a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1495, "license_type": "no_license", "max_line_length": 148, "num_lines": 61, "path": "/are_the_numbers_inorder.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "# Are the numbers in order?\n'''\nIn this Kata, your function receives an array of positive integers as input. Your task is to determine whether the numbers are in ascending order.\n\nFor the purposes of this Kata, you may assume that all inputs are valid (i.e. arrays containing only positive integers with a length of at least 2).\n\nFor example:\n\nin_asc_order([1,2,4,7,19]) # returns True\nin_asc_order([1,2,3,4,5]); // returns True\n'''\n\ndef in_asc_order(mylist):\n a = []\n for i in range(len(mylist)):\n for j in range(i+1, len(mylist)):\n if mylist[i] < mylist[j]:\n # use the a=[] to add True/False depending on the condition such a = [False,True,True,False] values\n a.append(True)\n else:\n a.append(False)\n #bool = [i, j for (mylist[i], mylist[j]) if mylist[i] <]\n # check to see if there is False/True value in a and return False/True accordingly.\n if False in a:\n return False\n return True\n\n# Best solution for this problem:\n'''\n#1.\ndef in_asc_order(arr):\n return arr == sorted(arr)\n \n \n#2.\ndef in_asc_order(arr):\n return sorted(arr) == arr\n \n#3.\ndef in_asc_order(arr):\n for i in range(len(arr) - 1):\n if arr[i] > arr[i + 1]: return False\n return True\n \n #4.\n in_asc_order = lambda l: sorted(l) == l\n \n # 5\n def in_asc_order(arr):\n c=0\n for x in arr:\n if x<=c:\n return False\n c=x\n return True \n \n #6.\n def in_asc_order(a):\n return all(x < y for x, y in zip(a, a[1:]))\n \n'''\n" }, { "alpha_fraction": 0.6164383292198181, "alphanum_fraction": 0.6164383292198181, "avg_line_length": 21, "blob_id": "b68279e3c0889b2fb2358f3586d9ffe9b4cce966", "content_id": "cf4f63ee71e0f524a241904004d4300e0aaacbca", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 219, "license_type": "no_license", "max_line_length": 45, "num_lines": 10, "path": "/jaden_case.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Jaden Casing Strings\n\ndef toJadenCase(string):\n if string == \"\":\n print(\"\")\n else:\n print(string.title())\n \ntoJadenCase(\"The is alot of things going on\")\ntoJadenCase(\"hello guys and ladies.\")" }, { "alpha_fraction": 0.6122881174087524, "alphanum_fraction": 0.6355932354927063, "avg_line_length": 17.19230842590332, "blob_id": "50356a06ae423ed53c97ce0ed4bb079e30eac223", "content_id": "1de1bab665e678efdbcd718916d97bfcdde1b136", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 472, "license_type": "no_license", "max_line_length": 106, "num_lines": 26, "path": "/lost_without_map.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "# Beginner - Lost Without a Map\n\n\"\"\"\nGiven and array of integers (x), return the array with each value doubled.\n\nFor example:\n\n[1, 2, 3] --> [2, 4, 6]\n\nFor the beginner, try to use the map method - it comes in very handy quite a lot so is a good one to know.\n\"\"\"\n\n# map(function_to_apply, list_of_inputs)\n\n\"\"\"\n# variation\ndef maps(a):\n return [2 * x for x in a]\n\"\"\"\n\ndef maps(a):\n doubled = list(map(lambda a: a*2, a))\n return doubled\n \nitems = [1, 2, 3]\nmaps(items)" }, { "alpha_fraction": 0.4970414340496063, "alphanum_fraction": 0.5192307829856873, "avg_line_length": 24.69230842590332, "blob_id": "763bd9dcef6b9d2a7f4dd45527c137cd2dc79c9f", "content_id": "6f7178b73e4c35dda06ada21720241fbaf4b6e1d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 676, "license_type": "no_license", "max_line_length": 96, "num_lines": 26, "path": "/odd_even.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Odd or Even\n# def oddOrEven(arr):\n# \"\"\"\n# Given an array of numbers, determine whether the sum of all of the numbers is odd or even.\n\n# Give your answer in string format as 'odd' or 'even'.\n\n# If the input array is empty consider it as: [0] (array with a zero).\n \n# Example:\n\n# oddOrEven([0]) returns \"even\"\n# oddOrEven([2, 5, 34, 6]) returns \"odd\"\n# oddOrEven([0, -1, -5]) returns \"even\"\n# \"\"\"\n# num = 0\n# for val in arr:\n# num += val\n \n# if num % 2 == 0:\n# return \"even\"\n# else:\n# return \"odd\"\n\ndef oddOrEven(arr):\n return 'even' if sum(arr) % 2 == 0 else 'odd'\n " }, { "alpha_fraction": 0.6953467726707458, "alphanum_fraction": 0.6953467726707458, "avg_line_length": 48.434783935546875, "blob_id": "cce67e6d347a64c3b159cfd6e9edb3b89bda23f0", "content_id": "319be6c6862f5977b1331604160e999ad55332d8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1139, "license_type": "no_license", "max_line_length": 113, "num_lines": 23, "path": "/my_head_is_wrong_end.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#problem statement\n\"\"\"\nYou\\'re at the zoo... all the meerkats look weird. Something has gone terribly wrong\n - someone has gone and switched their heads and tails around!\nSave the animals by switching them back. You will be given an array which will have \nthree values (tail, body, head). It is your job to re-arrange the array so that the animal is \nthe right way round (head, body, tail).Same goes for all the other arrays/lists that you will \nget in the tests: you have to change the element positions with the same exact logics - simples!\n\"\"\"\n\n#sample tests\n\"\"\"\nTest.describe(\"Basic tests\")\nTest.assert_equals(fix_the_meerkat([\"tail\", \"body\", \"head\"]), [\"head\", \"body\", \"tail\"])\nTest.assert_equals(fix_the_meerkat([\"tails\", \"body\", \"heads\"]), [\"heads\", \"body\", \"tails\"])\nTest.assert_equals(fix_the_meerkat([\"bottom\", \"middle\", \"top\"]), [\"top\", \"middle\", \"bottom\"])\nTest.assert_equals(fix_the_meerkat([\"lower legs\", \"torso\", \"upper legs\"]), [\"upper legs\", \"torso\", \"lower legs\"])\nTest.assert_equals(fix_the_meerkat([\"ground\", \"rainbow\", \"sky\"]), [\"sky\", \"rainbow\", \"ground\"])\n\"\"\"\n\n#solution\ndef fix_the_meerkat(arr):\n #code goes here\n \n" }, { "alpha_fraction": 0.599078357219696, "alphanum_fraction": 0.599078357219696, "avg_line_length": 19.28125, "blob_id": "78c617339613c649467a5c1521172ef78c05e147", "content_id": "fba9702410744798976b36b1bfcf2908587c5bd6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 651, "license_type": "no_license", "max_line_length": 90, "num_lines": 32, "path": "/dinglemouse.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#FIXME: Get Full Name\n\n\"\"\"\nhe code provided is supposed return a person's Full Name given their first and last names.\n\nBut it's not working properly.\n\nNotes\n\nThe first and/or last names are never null (None in Python), but may be empty.\n\nTask\n\nFix the bug so we can all go home early.\n\n\"\"\"\n\nclass Dinglemouse(object):\n\n def __init__(self, first_name, last_name):\n first_name = first_name\n last_name = last_name\n def get_full_name(self):\n if first_name == '':\n\n return 'last_name'\n if last_name == '':\n return first_name\n else:\n \n\n return first_name + ' ' + last_name\n\n\n" }, { "alpha_fraction": 0.6344696879386902, "alphanum_fraction": 0.6382575631141663, "avg_line_length": 20.040000915527344, "blob_id": "dce74cb008cd6c08287499ea37008ef7e0e20baf", "content_id": "3c1931460314401d4bbd55647e4cb614701d0584", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 528, "license_type": "no_license", "max_line_length": 116, "num_lines": 25, "path": "/boolean_to_string.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Convert a Boolean to a String\n\n\"\"\"\nSample tests:\nTest.assert_equals(boolean_to_string(True), \"True\", 'When we pass in true, we want the string \"true\" as output')\nTest.assert_equals(boolean_to_string(False), \"False\", 'When we pass in false, we want the string \"false\" as output')\n\"\"\"\n\n\"\"\"\n#1\ndef boolean_to_string(b):\n return str(b)\n#2\ndef boolean_to_string(b):\n return 'True' if b else 'False'\n\"\"\"\n\ndef boolean_to_string(b):\n\n #your code here\n if b == True:\n\n return str(b)\n else:\n return str(b)\n\n\n" }, { "alpha_fraction": 0.534426212310791, "alphanum_fraction": 0.5639344453811646, "avg_line_length": 16.399999618530273, "blob_id": "7ad1e6672c344c26685b254cddf7b3aa15b9847f", "content_id": "1c14b6d2f8c8be02855c8522e44ce676fccbaf9f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 610, "license_type": "no_license", "max_line_length": 54, "num_lines": 35, "path": "/get_middle_character.py", "repo_name": "gtsofa/codewars", "src_encoding": "UTF-8", "text": "#Get the Middle Character\n\"\"\"\nSample Tests:\n\n1\nTest.assert_equals(get_middle(\"test\"),\"es\")\n2\nTest.assert_equals(get_middle(\"testing\"),\"t\")\n3\nTest.assert_equals(get_middle(\"middle\"),\"dd\")\n4\nTest.assert_equals(get_middle(\"A\"),\"A\")\n5\nTest.assert_equals(get_middle(\"of\"),\"of\")\n\n\"\"\"\n\ndef get_middle(s):\n\n # x = len(s)\n # y = int(x/2)\n \n # if x % 2 == 0:\n # return s[y-1:y+1]\n # else:\n # return s[y:y+1]\n \n # #your code here\n index, odd = divmod(len(s), 2)\n return s[index] if odd else s[index - 1:index + 1]\n # return s[(len(s)-1)/2:len(s)/2+1]\n\n\n\nget_middle('company')\n\n" } ]	12
eddsalkield/DistributedPhone	https://github.com/eddsalkield/DistributedPhone	272b37d9bc408a6de271160e98724bd646ed01c2	641c98fd71fc11977f7d2999ead015e168bc7850	7b3d0f158dce6a8dff4724e5e038982733d38084	refs/heads/master	2021-04-15T10:52:53.158661	2018-05-15T09:52:35	2018-05-15T09:52:35	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5241256356239319, "alphanum_fraction": 0.5302527546882629, "avg_line_length": 32.05485153198242, "blob_id": "79c473105c7d9ea33c7b943d0fceb5930e7a84a7", "content_id": "a39fdd2ebddb068f32594ae6eaa7d6f02c348bc9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 7834, "license_type": "no_license", "max_line_length": 116, "num_lines": 237, "path": "/client/src/exec/test-util.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import Runner from \"./runner\";\n\nimport * as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport MockAPI from \"./mock_api\";\nimport {Storage} from \"./storage\";\n\nexport class TestTSDB implements stat.TSDB {\n public rejected: boolean;\n public readonly reject: (_: Error) => void;\n\n constructor(reject: (_: Error) => void) {\n this.rejected = false;\n this.reject = reject;\n }\n\n public write(at: number, data: stat.Point[]): void {\n for(const d of data) {\n console.log(d);\n }\n }\n\n public writeError(at: number, e: err.Data): void {\n if(this.rejected) return;\n this.rejected = true;\n this.reject(err.fromData(e));\n }\n}\n\nexport function arrBuf(data: number[]): Uint8Array {\n const buf = new Uint8Array(data.length);\n buf.set(data);\n return buf;\n}\n\nexport function b64Buf(data: string): Uint8Array {\n return strBuf(self.atob(data));\n}\n\n/* ISO 8859-1 encoder /\nexport function strBuf(data: string) {\n const arr: number[] = [];\n for(let i = 0; i < data.length; i += 1) {\n arr.push(data.charCodeAt(i));\n }\n return arrBuf(arr);\n}\n\nexport function writeText(text: string) {\n self.document.body.appendChild(self.document.createTextNode(text));\n}\nexport function writeLine(text: string) {\n self.document.body.appendChild(self.document.createTextNode(text));\n self.document.body.appendChild(self.document.createElement(\"br\"));\n}\n\nexport async function asyncSleep(ms: number): Promise<void> {\n return new Promise<void>((resolve, reject) => {\n self.setTimeout(() => resolve(), ms);\n });\n}\n\nexport function releaser<T = void>(): [Promise<T>, (value?: T) => void] {\n let release!: (value?: T) => void;\n const pr = new Promise<T>((resolve, reject) => {\n release = resolve;\n });\n return [pr, release!];\n}\n\nexport function withStat<T>(f: (s: stat.Sink) => Promise<T>): Promise<T> {\n return new Promise<T>((resolve, reject) => {\n const the_tsdb = new TestTSDB(reject);\n const the_stat = new stat.Root(the_tsdb);\n Promise.resolve(the_stat).then(f).then((v) => {\n self.setTimeout(() => {\n if(!the_tsdb.rejected) resolve(v);\n }, 500);\n }, (e) => {\n if(!the_tsdb.rejected) {\n the_tsdb.rejected = true;\n reject(e);\n }\n });\n });\n}\n\nexport function withRunner<T>(the_api: MockAPI, the_storage: Storage, func: (r: Runner) => Promise<T>): Promise<T> {\n return withStat((the_stat) => Runner.create(the_stat, the_api, the_storage, \"test@invalid\").then((r) => {\n return Promise.resolve(r).then(func).finally(() => r.stop());\n }));\n}\n\nenum CompareKind {\n PRIMITIVE = 0,\n OBJECT = 1,\n ARRAY = 2,\n MAP = 3,\n TYPED_ARRAY = 4,\n}\n\nfunction typename(obj: any) {\n return Object.getPrototypeOf(obj).constructor.name;\n}\n\nfunction compareKind(obj: any) {\n if(typeof obj !== \"object\") return CompareKind.PRIMITIVE;\n if(obj instanceof Array) return CompareKind.ARRAY;\n if(obj instanceof Map) return CompareKind.MAP;\n if(obj instanceof Uint8Array) return CompareKind.TYPED_ARRAY;\n if(Object.getPrototypeOf(obj) === Object.prototype) return CompareKind.OBJECT;\n throw new Error(`Don't know how to compare ${typename(obj)}`);\n}\n\nfunction diffTypedArray<T>(v1: ArrayLike<T>, v2: ArrayLike<T>): number {\n const l = Math.min(v1.length, v2.length);\n for(let i = 0; i < l; i += 1) {\n if(v1[i] !== v2[i]) return i;\n }\n if(v1.length !== v2.length) return l;\n return -1;\n}\n\nexport function compare(got: any, want: any, path: string) {\n if(want[\"@compare@func\"] !== undefined) return want[\"@compare@func\"](got);\n const kind = compareKind(want);\n if(kind === CompareKind.PRIMITIVE) {\n if(got !== want) {\n throw new Error(`got${path} !== want${path}: primitive values differ: ${got} !== ${want}`);\n }\n } else if(kind === CompareKind.OBJECT) {\n if(Object.getPrototypeOf(got) !== Object.prototype) {\n throw new Error(`got${path} !== want${path}: expected object, got ${typename(got)}`);\n }\n\n const k_got = Object.keys(got), k_want = Object.keys(want);\n\n let ignore = (k: string, v?: any) => v === undefined;\n const i = k_want.indexOf(\"@compare@ignore\");\n if(i !== -1) {\n k_want.splice(i, 1);\n const ign = want[\"@compare@ignore\"];\n if(typeof ign === \"boolean\") ignore = (k: string, v?: any) => ign;\n else if(ign instanceof Array) ignore = (k: string, v?: any) => ign.indexOf(k) === -1;\n else if(ign instanceof Function) ignore = ign;\n else throw new TypeError(\"Unknown @compare@ignore type\");\n }\n\n for(const p of k_want) {\n if(k_got.indexOf(p) === -1) {\n throw new Error(`got${path} !== want${path}: missing property ${p}`);\n }\n }\n\n for(const p of k_got) {\n if(want[p] === undefined) {\n if(!ignore(p, got[p])) {\n throw new Error(`got${path} !== want${path}: additional property ${p}`);\n }\n } else {\n compare(got[p], want[p], path + \".\" + p);\n }\n }\n } else if(kind === CompareKind.ARRAY) {\n if(!(got instanceof Array)) {\n throw new Error(`got${path} !== want${path}: expected array, got ${typename(got)}`);\n }\n\n const l1: number = got.length, l2: number = want.length;\n if(l1 !== l2) {\n throw new Error(`got${path} !== want${path}: array lengths differ`);\n }\n\n for(let i = 0; i < l1; i += 1) {\n compare(got[i], want[i], path + \"[\" + i + \"]\");\n }\n } else if(kind === CompareKind.MAP) {\n if(!(got instanceof Map)) {\n throw new Error(`got${path} !== want${path}: expected map, got ${typename(got)}`);\n }\n\n const k_got = Array.from(got.keys()), k_want = Array.from(want.keys());\n\n for(const p of k_want) {\n if(k_got.indexOf(p) === -1) {\n throw new Error(`got${path} !== want${path}: missing element ${p}`);\n }\n }\n\n for(const p of k_got) {\n if(k_want.indexOf(p) === -1) {\n throw new Error(`got${path} !== want${path}: additional member ${p}`);\n } else {\n compare(got.get(p), want.get(p), path + \"[\" + JSON.stringify(p) + \"]\");\n }\n }\n } else if(kind === CompareKind.TYPED_ARRAY) {\n if(!(got instanceof Object.getPrototypeOf(want).constructor)) {\n throw new Error(`got${path} !== want${path}: expected ${typename(want)}, got ${typename(got)}; ${got}`);\n }\n\n const diff = diffTypedArray(got, want);\n if(diff !== -1) {\n let msg = \"\";\n if(got.lenth !== want.lenth) {\n msg = `; got size ${got.lenth}, want ${want.lenth}`;\n }\n throw new Error(`got${path} !== want${path}: difference at byte ${diff}${msg}`);\n }\n } else {\n throw new Error(\"WTF\");\n }\n}\n\nexport function runTests(tests: Array<() => Promise<void>>): Promise<void> {\n return new Promise<void>((resolve, reject) => {\n let i = 0;\n const runner = () => {\n if(i === tests.length) {\n writeLine(\"Done\");\n resolve();\n return;\n }\n const test = tests[i];\n writeText(\"Running test \" + test.name + \" ... \");\n i += 1;\n new Promise<void>((res,rej) => res(test())).then(() => {\n writeLine(\"Pass\");\n }, (e) => {\n writeLine(err.format(e));\n console.error(e);\n }).then(runner);\n };\n runner();\n });\n}\n" }, { "alpha_fraction": 0.4678249657154083, "alphanum_fraction": 0.4829472303390503, "avg_line_length": 33.153846740722656, "blob_id": "b2e8451468a910a130b275f2888a436c5ff1b0f4", "content_id": "17f3860e29533f59a974371f0f336d98b80129d9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 6216, "license_type": "no_license", "max_line_length": 102, "num_lines": 182, "path": "/client/src/worker/exec.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import as workapi from \"@/exec/workapi\";\n\ndeclare interface Env {\n [name: string]: ((...args: any[]) => any) \| WebAssembly.Memory \| number;\n}\n\ndeclare interface ImportObject {\n [name: string]: Env;\n}\n\ninterface CompileCacheItem {\n id: string;\n mod: WebAssembly.Module;\n}\n\nexport default class Executor {\n private abi1(\n in_program: WebAssembly.Module,\n in_control: Uint8Array, in_data: workapi.Ref[]\n ): Promise<workapi.OutResult> {\n const getString = (view: Uint8Array): string => {\n // if(view.some((c) => ((c < 32 && c != 10) \|\| c == 127))) return \" with invalid string.\";\n if(view.every((c) => (c < 128))) {\n return \": \" + String.fromCharCode(...view);\n } else {\n return \" with Unicode string (Decoding hasn't been implemented yet)\";\n }\n };\n\n const import_env: Env = {\n pptw1_print: (ptr: any, size: any) => {\n if(typeof ptr !== \"number\" \|\| ptr !== (ptr \| 0)) {\n throw new Error(\"Invalid call to print()\");\n }\n if(typeof size !== \"number\" \|\| size !== (size \| 0)) {\n throw new Error(\"Invalid call to print()\");\n }\n if(size < 0) {\n throw new Error(\"Invalid call to print()\");\n }\n\n ptr >>>= 0;\n if(ptr + size > mem.buffer.byteLength) {\n throw new Error(\"Invalid call to print()\");\n }\n\n this.onPrint(\"Program print()\" + getString(new Uint8Array(mem.buffer, ptr, size)));\n },\n pptw1_abort: (ptr: any) => {\n if(typeof ptr !== \"number\" \|\| ptr !== (ptr \| 0)) {\n throw new Error(\"Invalid call to abort()\");\n }\n\n ptr >>>= 0;\n\n if(ptr === 0) throw new Error(\"Program abort()\");\n if(ptr >= mem.buffer.byteLength) {\n throw new Error(\"Invalid call to abort()\");\n }\n\n const view = new Uint8Array(mem.buffer, ptr);\n\n let i = 0;\n while(true) {\n const d = view[i];\n if(d === 0) {\n throw new Error(\"Program abort()\" + getString(view.subarray(0, i)));\n }\n i += 1;\n if(i === view.length) {\n throw new Error(\"Program abort() with non-terminated string\");\n }\n }\n },\n };\n\n const import_object: ImportObject = {\n env: import_env,\n };\n const inst = new WebAssembly.Instance(in_program, import_object);\n\n const mem = inst.exports.memory;\n\n inst.exports.pptw1_init();\n\n const addr_in = inst.exports.pptw1_malloc((3 + 2in_data.length) 4);\n const addr_control = inst.exports.pptw1_malloc(in_control.length);\n\n const pr_done: Array<Promise<void>> = [];\n for(let i2 = 0; i2 < in_data.length; i2 += 1) {\n const i = i2;\n pr_done.push(this.readBlob(in_data[i]).then((data) => {\n const size = data.length;\n const addr = inst.exports.pptw1_malloc(size);\n\n const view = new DataView(mem.buffer, addr_in + (3 + 2i) 4, 2 * 4);\n view.setUint32(0, addr, true);\n view.setUint32(4, size, true);\n new Uint8Array(mem.buffer, addr, size).set(data);\n }));\n }\n\n {\n const view = new DataView(mem.buffer, addr_in, 3 * 4);\n view.setUint32(0, addr_control, true);\n view.setUint32(4, in_control.length, true);\n view.setUint32(8, in_data.length, true);\n }\n new Uint8Array(mem.buffer, addr_control, in_control.length).set(in_control);\n\n return Promise.all(pr_done).then(() => {\n this.onStarted();\n let res_addr = inst.exports.pptw1_run(addr_in);\n\n let outc_blobs: number;\n {\n const view = new DataView(mem.buffer, res_addr, 4);\n res_addr += 4;\n outc_blobs = view.getUint32(0, true);\n }\n\n const res: workapi.OutResult = {\n data: [],\n };\n\n for(let i = 0; i < outc_blobs; i += 1) {\n const view = new DataView(mem.buffer, res_addr, 2 * 4);\n res_addr += 2 * 4;\n const blob_addr = view.getUint32(0, true);\n const blob_size = view.getUint32(4, true);\n\n const blob = new Uint8Array(blob_size);\n blob.set(new Uint8Array(mem.buffer, blob_addr, blob_size));\n res.data.push(blob);\n }\n\n inst.exports.pptw1_cleanup();\n\n return res;\n });\n }\n\n private runProgram(prog: WebAssembly.Module, data: workapi.InWork): Promise<workapi.OutResult> {\n return this.abi1(prog, data.control, data.data);\n }\n\n /* Keep a 3-element LRU cache /\n private readonly compile_cache: CompileCacheItem[] = [];\n private readonly compile_cache_size = 3;\n\n public run(data: workapi.InWork): Promise<workapi.OutResult> {\n const prog_ref = data.program;\n const cc = this.compile_cache;\n\n for(let i = 0; i < cc.length; i += 1) {\n const ii = cc[i];\n if(ii.id === prog_ref.id) {\n cc.splice(i, 1);\n cc.push(ii);\n return this.runProgram(ii.mod, data);\n }\n }\n\n return this.readBlob(prog_ref).then((code) => {\n const ccs = this.compile_cache_size;\n const prog_mod = new WebAssembly.Module(code);\n\n cc.push({id: prog_ref.id, mod: prog_mod});\n if(cc.length > ccs) {\n cc.splice(0, cc.length - ccs);\n }\n\n return this.runProgram(prog_mod, data);\n });\n }\n\n public readBlob(blob: workapi.Ref): Promise<Uint8Array> {\n return Promise.reject(new Error(\"readBlob: Not implemented\"));\n }\n public onPrint(msg: string) {}\n public onStarted(): void {}\n}\n" }, { "alpha_fraction": 0.6526054739952087, "alphanum_fraction": 0.6749379634857178, "avg_line_length": 32.58333206176758, "blob_id": "781e3aed9cb4c4c18c0ac400712ac1a223fee62d", "content_id": "cc43aaa8bc1626d43c857ec73e2d8030999b8868", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 403, "license_type": "no_license", "max_line_length": 83, "num_lines": 12, "path": "/testCustomer/makeNewProject.sh", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "#!/bin/bash\n# Creates a new project\n\nif [ -z \"$3\" ]; then\n\techo \"Usage\"\n \techo \"./makeNewProject username password projectname\"\n\techo \"username - the name of the customer to be created, who owns the project.\"\n\techo \"password - the password of this user.\"\n\techo \"projectname - the name of the project they are creating.\"\nelse\n\tpython3 makeProject.py \"$1\" \"$2\" \"$3\" && python3 collatzCustomer.py \"$1\" \"$2\" \"$3\"\nfi\n" }, { "alpha_fraction": 0.6567398309707642, "alphanum_fraction": 0.66144198179245, "avg_line_length": 15.35897445678711, "blob_id": "39f79e563cfc3a2ac894d96b846cdc463ae5cda5", "content_id": "0fbcb2e155181708a58f94a3abcb207018e6ba56", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 638, "license_type": "no_license", "max_line_length": 36, "num_lines": 39, "path": "/client/src/exec/workapi.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import {ErrorData} from \"./api\";\nimport {Ref} from \"./storage\";\n\nexport type ErrorData = ErrorData;\nexport type Ref = Ref;\n\nexport interface InWork {\n program: Ref;\n control: Uint8Array;\n data: Ref[];\n}\n\nexport interface InControl {\n get_blob?: [string, Uint8Array];\n}\n\nexport interface In {\n work?: InWork;\n control?: InControl;\n}\n\nexport interface OutResult {\n data: Uint8Array[];\n}\n\nexport interface OutError {\n error: ErrorData;\n}\n\nexport interface OutControl {\n notify_started?: null;\n get_blob?: Ref;\n}\n\nexport interface Out {\n error?: ErrorData;\n result?: OutResult;\n control?: OutControl;\n}\n" }, { "alpha_fraction": 0.5295138955116272, "alphanum_fraction": 0.5295138955116272, "avg_line_length": 32.882354736328125, "blob_id": "af67388597aaefd51b308f15ff48ca60be14ab44", "content_id": "4d3af95fc347f1b336afd2b6cd0e5b7a9f0ebdd9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 1152, "license_type": "no_license", "max_line_length": 77, "num_lines": 34, "path": "/client/src/dom_device.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import as obs from \"@/obs\";\n\nimport {Device} from \"./device\";\n\nexport default class DOMDevice implements Device {\n public readonly on_battery = new obs.Subject<boolean>();\n public readonly on_mobile_data = new obs.Subject<boolean>();\n\n constructor() {\n const nav: any = window.navigator;\n\n if(nav.connection === undefined) {\n this.on_mobile_data.error(new Error(\"Not available\"));\n } else {\n this.on_mobile_data.next(nav.connection.type === \"cellular\");\n nav.connection.addEventListener(\"typechange\", () => {\n this.on_mobile_data.next(nav.connection.type === \"cellular\");\n });\n }\n\n if(nav.getBattery === undefined) {\n this.on_battery.error(new Error(\"Not available\"));\n } else {\n nav.getBattery().then((bat: any) => {\n this.on_battery.next(!bat.charging);\n bat.addEventListener(\"chargingchange\", () => {\n this.on_battery.next(!bat.charging);\n });\n }, (e: Error) => {\n this.on_battery.error(e);\n });\n }\n }\n}\n" }, { "alpha_fraction": 0.7472222447395325, "alphanum_fraction": 0.769444465637207, "avg_line_length": 29, "blob_id": "28133a5edcb418b5faa34774012231606a5b3936", "content_id": "abe1dea934787298ffb3eecc9f9b9955e0b4ee3e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 360, "license_type": "no_license", "max_line_length": 98, "num_lines": 12, "path": "/build.sh", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "#!/bin/bash\n\n# Run server tests\n#cd server\n#python3 server.py 9999 & # Run server in background. Need to get PID to kill it later\n#cd servertests\n#python3 autotester.py quiet # Run tests on server. Need to make successful overall tests return 0\n\n# Asssuming tests went okay\necho Copying server data\ncp -r /home/ec2-user/DistributedPhone/server /data\necho Done\n" }, { "alpha_fraction": 0.5815498232841492, "alphanum_fraction": 0.5867158770561218, "avg_line_length": 23.636363983154297, "blob_id": "a5b76e8f9703df13c877c5ac4912c610719eac81", "content_id": "51dd0cbb7338bb4798afa7edeec07ba5a3e268d1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 1355, "license_type": "no_license", "max_line_length": 85, "num_lines": 55, "path": "/client/src/node-executor.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport * as workapi from \"@/exec/workapi\";\n\nimport Executor from \"@/worker/exec\";\n\ndeclare const process: {\n readonly argv: string[];\n};\n\ndeclare const console: any;\ndeclare const require: any;\ndeclare const Buffer: any;\ndeclare type Buffer = any;\n\nconst fs = require('fs');\n\nclass NodeExecutor extends Executor {\n public readBlob(blob: workapi.Ref): Promise<Uint8Array> {\n return new Promise((resolve, reject) => {\n fs.readFile(blob.id, (err: Error, buf: Buffer) => {\n if(err) reject(err);\n else resolve(new Uint8Array(buf.buffer, buf.byteOffset, buf.length));\n });\n });\n }\n\n public onPrint(msg: string) {\n console.log(msg);\n }\n}\n\nfunction resolve(name: string): workapi.Ref {\n return {\n id: name,\n size: fs.statSync(name).size,\n };\n}\n\nconst r = new NodeExecutor();\n\nr.readBlob(resolve(process.argv[3])).then((control) => {\n return r.run({\n program: resolve(process.argv[2]),\n control: control,\n data: process.argv.slice(4).map(resolve),\n });\n}).then((out) => {\n for(let i = 0; i < out.data.length; i += 1) {\n fs.writeFileSync(\"output-blob-\" + i, new Buffer(out.data[i]));\n }\n console.log(\"Success, wrote \" + out.data.length + \" blobs.\");\n}, (err) => {\n console.error(err);\n});\n" }, { "alpha_fraction": 0.5334115028381348, "alphanum_fraction": 0.5351699590682983, "avg_line_length": 24.27407455444336, "blob_id": "9750718b5760293e744ae927249a207ba9964883", "content_id": "bb29a1c67a3109bb2f4836d524a89e1655df998a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 3412, "license_type": "no_license", "max_line_length": 76, "num_lines": 135, "path": "/client/src/err.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "declare interface ErrorAttr {\n [name: string]: string \| number \| boolean \| Data \| undefined;\n \"cause\"?: Data;\n}\n\nexport declare interface Data extends ErrorAttr {\n \"kind\": string;\n \"message\": string;\n}\n\ninterface ErrorType {\n readonly kind: string \| null;\n new(message: string, attr?: ErrorAttr): Base;\n}\n\nexport abstract class Base extends Error {\n public static readonly kind: string \| null = null;\n public data: Data;\n\n constructor(message: string, attr?: ErrorAttr) {\n super(message);\n const tp = this.constructor as ErrorType;\n this.data = Object.assign({}, attr, {\n \"kind\": tp.kind!,\n \"message\": message,\n });\n }\n}\n\nexport class State extends Base {\n public static readonly kind: string = \"state\";\n}\n\nexport class Runtime extends Base {\n public static readonly kind: string = \"runtime\";\n}\n\nexport class Validation extends Base {\n public static readonly kind: string = \"validation\";\n}\n\nexport class Network extends Runtime {\n public static readonly kind: string = \"network\";\n}\n\nexport class Cancelled extends Base {\n public static readonly kind: string = \"cancelled\";\n}\n\nexport class Permission extends Base {\n public static readonly kind: string = \"permission\";\n}\n\nexport function fromData(d: Data): Base {\n d = Object.assign({}, d);\n const k = d[\"kind\"];\n const msg = d[\"message\"];\n delete d[\"kind\"];\n delete d[\"message\"];\n\n let kind: ErrorType;\n if(k === \"state\") {\n kind = State;\n } else if(k === \"runtime\") {\n kind = Runtime;\n } else if(k === \"validation\") {\n kind = Validation;\n } else if(k === \"network\") {\n kind = Network;\n } else if(k === \"cancelled\") {\n kind = Cancelled;\n } else if(k === \"permission\") {\n kind = Permission;\n } else {\n kind = Runtime;\n }\n\n return new kind(msg, d);\n}\n\nexport function dataOf(err: Error): Data {\n let stack = \"\" + err.stack;\n if(err instanceof Base) {\n if(err.data[\"stack\"] !== undefined) {\n stack = stack + \"\\n\\n\" + err.data[\"stack\"];\n }\n return Object.assign({}, err.data, {\n \"stack\": stack,\n });\n } else {\n return {\n \"kind\": \"runtime\",\n \"message\": err.message,\n \"stack\": stack,\n };\n }\n}\n\nexport function format(e: Error): string {\n if(e instanceof Base) {\n return formatData(e.data);\n } else {\n return `${Object.getPrototypeOf(e).constructor.name}: ${e.message}`;\n }\n}\n\nexport function formatData(data: Data): string {\n let msg = `Error [${data[\"kind\"]}]: ${data[\"message\"]}`;\n const keys = Object.keys(data);\n keys.splice(keys.indexOf(\"kind\"), 1);\n keys.splice(keys.indexOf(\"message\"), 1);\n if(keys.length > 0) {\n keys.sort((a, b) => {\n if(a < b) return -1;\n if(a > b) return 1;\n return 0;\n });\n msg += \" [\";\n let first = true;\n for(const key of keys) {\n if(first) first = false;\n else msg += \", \";\n msg += key;\n msg += \" = \";\n const value = data[key]!;\n if(typeof value === \"object\") {\n msg += `[${value[\"kind\"]}]: ${value[\"message\"]}`;\n } else {\n msg += JSON.stringify(value);\n }\n }\n msg += \"]\";\n }\n return msg;\n}\n" }, { "alpha_fraction": 0.5516672134399414, "alphanum_fraction": 0.5853416919708252, "avg_line_length": 27.847618103027344, "blob_id": "eacf5ec874c20f37c67f14fe972bfc9a44fca0aa", "content_id": "54ab047eeb873bbc70ca393ad9b3d82a340d7487", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 3029, "license_type": "no_license", "max_line_length": 108, "num_lines": 105, "path": "/testCustomer/collatzClient.c", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "#include <pptw.h>\n#include <stdlib.h>\n#include <assert.h>\n\ntypedef unsigned int seqlen_t;\n\ninline __uint128_t nextStep (__uint128_t n) {\n if (n % 2 == 0)\n return n / 2;\n __uint128_t test = 3 * n + 1;\n if (test > n)\n return 3 * n + 1;\n return 0;\n}\n\n__uint128_t u128_read(const void vin) {\n const unsigned char in = (const unsigned char)vin;\n __uint128_t val = 0;\n for (int i = 0; i < 16; i++) {\n val += (__uint128_t)in[i] << 8i;\n }\n return val;\n}\n\nvoid u128_write(const void vout, __uint128_t val) {\n unsigned char out = (unsigned char)vout;\n for (int i = 0; i < 16; i++) {\n out[i] = (val >> 8i);\n }\n}\n\nvoid seqlen_write(const void vout, seqlen_t val) {\n unsigned char out = (unsigned char)vout;\n int s = sizeof(seqlen_t);\n for (int i = 0; i < s; i++) {\n out[i] = (val >> 8i);\n }\n}\n\n// Runs a task. The request's blobs, as well as the request object itself,\n// have been allocated using pptw1_malloc().\n\n// Input on control, Output in blob\n\nstruct pptw1_response pptw1_run(struct pptw1_request req) {\n\n // Return response\n struct pptw1_response * response = malloc(sizeof(struct pptw1_response) + sizeof(struct pptw1_blobref));\n\n // assert blobs == 0 (input in control)\n assert(req->n_blobs == 0);\n\n // Output a single blob\n response->n_blobs = 1;\n\n // Extract blob data from request \n struct pptw1_blobref reqControlBlob = req->control;\n assert(reqControlBlob.size == 2 * sizeof(__uint128_t));\n __uint128_t data = (__uint128_t )(reqControlBlob.data);\n __uint128_t left = data[0];\n __uint128_t right = data[1];\n\n // Our blob memory\n char* blobMemStart = pptw1_malloc(sizeof(seqlen_t[right - left]));\n char* blobMemIndex = blobMemStart;\n\n // Write interval\n u128_write(blobMemIndex, left); blobMemIndex += sizeof(__uint128_t);\n u128_write(blobMemIndex, right); blobMemIndex += sizeof(__uint128_t);\n\n __uint128_t num; // current number we are testing\n seqlen_t seqLength; // length of that sequence\n\n // search [left..right)\n\n seqlen_t maxSeqLength = 0;\n for (__uint128_t i = left; i < right; i++) {\n num = i; seqLength = 0;\n while (num != 1) { // assuming collatz conj :)\n num = nextStep(num);\n if (num == 0) break;\n seqLength++;\n }\n // may have overflowed\n if (num == 1) {\n // seqlen_write(blobMemIndex, seqLength);\n // blobMemIndex += sizeof(seqlen_t);\n\t \n\t // compare with current max\n\t if (maxSeqLength < seqLength) {\n\t\tmaxSeqLength = seqLength;\n\t }\n }\n }\n\n // Write max to blobMem\n seqlen_write(blobMemIndex, seqLength); blobMemIndex += sizeof(seqlen_t);\n\n // Info has been written to memory[blobMem ... blobMem + 4)\n struct pptw1_blobref * thisBlob = &(response->blobs[0]); // we send a single blob\n thisBlob->data = blobMemStart;\n thisBlob->size = blobMemIndex - blobMemStart;\n\n return response;\n}\n" }, { "alpha_fraction": 0.5289689302444458, "alphanum_fraction": 0.5296235680580139, "avg_line_length": 28.660194396972656, "blob_id": "fede627faf5791f6cee7f551d9d7146638c1cc56", "content_id": "c025dd9a631ed273cadf2a3584c1ec1b86bf1896", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 3055, "license_type": "no_license", "max_line_length": 90, "num_lines": 103, "path": "/client/webpack.config.js", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "const path = require('path');\nconst webpack = require('webpack');\nconst UglifyJsPlugin = require('uglifyjs-webpack-plugin');\nconst MiniCssExtractPlugin = require('mini-css-extract-plugin');\nconst OptimizeCSSAssetsPlugin = require('optimize-css-assets-webpack-plugin');\n\ndistdir = path.resolve(__dirname, \"dist\");\n\nmodule.exports = function(env, argv) {\n if(!env) env = {dev: true, tests: true, utils: true};\n\n function makeConfig(target, tsconfig) {\n return {\n target: target,\n mode: env.dev ? \"development\" : \"production\",\n devtool: env.dev ? \"inline-source-map\" : false,\n optimization: {\n minimizer: env.dev ? [] : [\n ],\n },\n\n plugins: [\n new MiniCssExtractPlugin({\n filename: '[name].css'\n }),\n ].concat(env.dev ? [] : [\n new UglifyJsPlugin({\n cache: true,\n parallel: true,\n uglifyOptions: {\n output: {\n comments: false,\n },\n compress: {\n ecma: 6,\n },\n },\n }),\n env.dev ? null : new OptimizeCSSAssetsPlugin({}),\n env.dev ? null : new webpack.optimize.AggressiveMergingPlugin(),\n ]),\n\n module: {\n rules: [\n {\n test: /\\.tsx?$/,\n exclude: [distdir, /node_modules/],\n use: {\n loader: 'ts-loader',\n options: {\n configFile: tsconfig,\n },\n },\n }, {\n test: /\\.css$/,\n use: [MiniCssExtractPlugin.loader, 'css-loader']\n },\n ],\n },\n resolve: {\n extensions: ['.tsx', '.ts', '.js'],\n alias: {\n 'Dist': distdir,\n '@': path.resolve(__dirname, 'src'),\n 'react-router': path.resolve(__dirname, 'node_modules/react-router'),\n 'react-router-dom': path.resolve(__dirname, 'node_modules/react-router-dom/es'),\n }\n },\n entry: {},\n output: {\n path: distdir,\n filename: '[name].js',\n },\n };\n }\n\n as_worker = makeConfig(\"webworker\", \"tsconfig-worker.json\");\n as_dom = makeConfig(\"web\", \"tsconfig-dom.json\");\n as_node = makeConfig(\"node\", \"tsconfig-node.json\");\n\n as_worker.entry[\"worker\"] = \"./src/worker/worker.ts\";\n\n as_dom.entry[\"index\"] = \"./src/index.tsx\";\n if(env.tests) {\n as_dom.entry[\"exec-test-rig\"] = \"./src/exec/test-rig.ts\";\n as_dom.entry[\"client-test-rig\"] = \"./src/client-test-rig.tsx\";\n as_dom.entry[\"test-exec-repo\"] = \"./src/exec/tests/repo.ts\";\n as_dom.entry[\"test-exec-work-dispatcher\"] = \"./src/exec/tests/work-dispatcher.ts\";\n as_dom.entry[\"test-exec-runner\"] = \"./src/exec/tests/runner.ts\";\n as_dom.entry[\"test-exec-idb\"] = \"./src/exec/tests/idb.ts\";\n }\n\n if(env.utils) {\n as_node.entry[\"node-executor\"] = \"./src/node-executor.ts\";\n as_node.entry[\"test\"] = \"./src/test.ts\";\n }\n\n const outs = [];\n for(const kind of [as_worker, as_dom, as_node]) {\n if(Object.keys(kind.entry).length > 0) outs.push(kind);\n }\n return outs;\n}\n" }, { "alpha_fraction": 0.6042766571044922, "alphanum_fraction": 0.6273915767669678, "avg_line_length": 39.816253662109375, "blob_id": "85161995132d275970309242bff42da60381bfa0", "content_id": "ffa2a316a397c42086b95836322fb9e730bb571e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 11551, "license_type": "no_license", "max_line_length": 105, "num_lines": 283, "path": "/client/src/exec/test-rig.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport * as stat from \"@/stat\";\n\nimport {arrBuf, b64Buf} from \"./test-util\";\n\nimport * as api from \"./api\";\nimport MemStorage from \"./mem_storage\";\nimport Runner from \"./runner\";\n\nimport MockAPI from \"./mock_api\";\n\nclass PrintTSDB implements stat.TSDB {\n public table: HTMLElement;\n public table_data: Array<[string, string, HTMLElement]> = [];\n\n constructor(table: HTMLElement) {\n this.table = table;\n }\n\n public writeError(time: number, err: api.ErrorData) {\n console.log(err);\n }\n\n public write(time: number, update: stat.Point[]) {\n const compare = (ka: string, kb: string) => {\n if(ka < kb) return -1;\n if(ka > kb) return 1;\n return 0;\n };\n\n const lines = update.map(([name, key, value]) => {\n const key_keys = Object.keys(key);\n key_keys.sort();\n if(key_keys.length !== 0) {\n let key_fmt: string = \"\";\n for(const k of key_keys) {\n key_fmt += \",\";\n key_fmt += k;\n key_fmt += \"=\";\n key_fmt += key[k];\n }\n name += \"[\" + key_fmt.slice(1) + \"]\";\n }\n return [name, \"\" + value];\n });\n\n lines.sort((x,y) => compare(x[0], y[0]));\n\n const tbl = this.table_data;\n let at = 0;\n\n for(const [k,v] of lines) {\n at -= 1;\n let step = 1;\n while(at+step < tbl.length && compare(tbl[at+step][0], k) < 0) step <<= 1;\n while(step > 1) {\n step >>= 1;\n if(at+step < tbl.length && compare(tbl[at+step][0], k) < 0) at += step;\n }\n at += 1;\n console.assert(at === tbl.length \|\| compare(tbl[at][0], k) >= 0);\n if(at < tbl.length && compare(tbl[at][0], k) === 0) {\n if(v === null) {\n this.table.removeChild(tbl[at][2].parentNode!);\n tbl.splice(at, 1);\n } else if(v !== tbl[at][1]) {\n tbl[at][1] = v;\n const cv = tbl[at][2];\n while(cv.firstChild) cv.removeChild(cv.firstChild);\n cv.appendChild(self.document.createTextNode(v));\n }\n } else if(v !== null) {\n const ck = self.document.createElement(\"td\");\n ck.appendChild(self.document.createTextNode(k));\n const cv = self.document.createElement(\"td\");\n cv.appendChild(self.document.createTextNode(v));\n const row = self.document.createElement(\"tr\");\n row.appendChild(ck);\n row.appendChild(cv);\n\n if(at === tbl.length) {\n this.table.appendChild(row);\n } else {\n this.table.insertBefore(row, tbl[at][2].parentNode);\n }\n tbl.splice(at, 0, [k, v, cv]);\n } else {\n /* pass /\n }\n }\n }\n}\n\nfunction fibtask(prog: api.BlobRef, i: number, n: number): api.Task {\n let ns = \"\" + n, is = \"\" + i;\n if(ns.length === 1) ns = \"0\" + ns;\n if(is.length === 1) is = \"0\" + is;\n return {\n id: `fib${ns}.${is}`,\n project: \"test\",\n program: prog,\n in_control: arrBuf([n & 255, n >> 8, 0, 0, 0, 0, 0, 0]),\n in_blobs: [],\n };\n}\n\nfunction range(k: number, n?: number): number[] {\n if(n === undefined) {\n n = k;\n k = 0;\n }\n const res = [];\n for(let i = k; i < n; i += 1) res.push(i);\n return res;\n}\n\nfunction shuffle<T>(a: T[]): T[] {\n let i = a.length;\n while(i !== 1) {\n i -= 1;\n const j = Math.random() i \| 0;\n const v = a[i];\n a[i] = a[j];\n a[j] = v;\n }\n return a;\n}\n\nexport function main() {\n const tbody = self.document.getElementById(\"stat_main\")!;\n const in_cnt = self.document.getElementById(\"in_cnt\") as HTMLInputElement;\n const in_min = self.document.getElementById(\"in_min\") as HTMLInputElement;\n const in_max = self.document.getElementById(\"in_max\") as HTMLInputElement;\n const but_more = self.document.getElementById(\"but_more\")!;\n const but_start = self.document.getElementById(\"but_start\")!;\n\n const st = new stat.Root(new PrintTSDB(tbody));\n const the_api = new MockAPI(st);\n\n the_api.blobs.set(\"prog-fib\", b64Buf(\n \"AGFzbQEAAAABHgZgAX8AYAAAYAF/AX9gAn9/AGADf39/AGACf38BfwITAQNlbnYLcHB0dzFfYWJv\" +\n \"cnQAAAMLCgECAwQCAgQAAAUFAwEAAgYVA38BQaCPBAt/AEGgjwQLfwBBkQ8LB10HBm1lbW9yeQIA\" +\n \"C19faGVhcF9iYXNlAwEKX19kYXRhX2VuZAMCCnBwdHcxX2luaXQAAQ1wcHR3MV9jbGVhbnVwAAEJ\" +\n \"cHB0dzFfcnVuAAIMcHB0dzFfbWFsbG9jAAUK/RcKAwABC+gCAgR/AX4jAEEQayICIQQgAiQAAkAg\" +\n \"ACgCBEEIRgRAIAAoAgAiATEAAUIIhiABMQAAhCABMQACQhCGhCABMQADQhiGhCIFIAExAARCIIaE\" +\n \"IAExAAVCKIaEIAExAAZCMIaEIAExAAdCOIaEQn98QtoAWg0BIAIgBaciA0ERakFwcWsiASQAIAFB\" +\n \"ACADQQJqEARCACEFAkAgASADaiICQX9qIgMtAABFBEADQCACLQAADQIgAUEAEAMgBUIBfCEFIAMt\" +\n \"AABFDQALCyAAKAIAIgEEQCABEAgLQQgQBSEBIAAQCCABIAVCCIg8AAEgASAFPAAAIAEgBUIQiDwA\" +\n \"AiABIAVCGIg8AAMgASAFQiCIPAAEIAEgBUIoiDwABSABIAVCMIg8AAYgASAFQjiIPAAHQQwQBSIC\" +\n \"IAE2AgwgAkEBNgIAIAJBCDYCECAEQRBqJAAgBEEMag8LQa4KEAAAC0GACBAAAAtBlQkQAAALgAEB\" +\n \"An8DQCAAIAFBASABGyICaiIBLQAABEAgAUEAOgAAQQIhASACQQFGDQEgACACQX5qEAMgAkEBaiEB\" +\n \"DAELIAFBf2oiAy0AAARAIANBADoAACACQQFqIQEMAQsgAUEBaiIDLQAABEAgA0EAOgAAIAJBAmoh\" +\n \"AQwBCwsgAUEBOgAAC3YBAX8CQAJAIAJBCE8EQCAAQQNxRQ0CA0AgACADaiICIAE6AAAgA0EBaiED\" +\n \"IAJBAWpBA3ENAAsgA0EERg0BCwNAIAAgA2ogAToAACADQQFqIgNBBEcNAAsLDwsgACABQf8BcSID\" +\n \"QQh0IANyIgNBEHQgA3I2AgALlgEBBX8CfyAAQQdqQQN2QQFqIgEQBiIARQRAAn9BjA0oAgAiAgRA\" +\n \"IAIgAkEEaigCAEF4cWoMAQtBoI8ECyIAIAFBA3QiBGoiA0GIDSgCACIFSwRAQQAiASAFIAMQCkUN\" +\n \"AhpBiA0gAzYCAAsgACACNgIAQYwNIAA2AgAgACAEQQZyNgIEQQAiASAARQ0BGgsgAEEIagsiAQvm\" +\n \"AwEFfwJAAkACQAJAAkACQAJAAkAgAEEDTwRAAn8gAEF/aiIBQYCAAU8EQCABQQR2IQFBIgwBCyAB\" +\n \"QQh2IAEgAUH/B0siAhshAUEWQX4gAhsLIgJBDGogAiABQT9LIgMbIgJBBmogAiABQQR2IAEgAxsi\" +\n \"AUEPSyIDGyICQQNqIAIgAUECdiABIAMbIgFBB0siAxsgASADdiIBQQYgAUEGSRtqQQFqIgJBPUsN\" +\n \"AQtBPyACayEBIAJBAnRBjAtqIQIDQCABQX9qIQEgAkEEaiICKAIAIgNFDQALIAFFDQEgAygCCCIB\" +\n \"BEAgAUEEaigCAEEHcUEFRw0FIAFBDGpBADYCAAsgAiABNgIAIAMgA0EEaigCAEEDdiAAEAcgAw8L\" +\n \"QYQNKAIAIgNFDQAgAyEBA0AgAUEEaigCACICQQdxQQVHDQMgAkEDdiICIABPDQIgASgCCCIBDQAL\" +\n \"C0EADwsgASgCCCEEAkACQCABQQxqKAIAIgUEQCAFQQRqKAIAQQdxQQVHDQUgBSAENgIIIAQNAQwC\" +\n \"CyADIAFHDQYgBEUNAQsgBEEEaigCAEEHcUEFRw0EIARBDGogBTYCAAsgASACIAAQByABDwtBxQkQ\" +\n \"AAALQcUJEAAAC0HFCRAAAAtBxQkQAAALQdgKEAAAC/UCAQZ/AkACQAJAAkBBjA0oAgAgAEcEQCAB\" +\n \"IAJJDQECQCACQQJqIAFLBEAgASECDAELIAAgASACEAcgACACQQN0aiIFIAA2AgAgACABQQN0aiAF\" +\n \"NgIAQYwNKAIAIAVGDQMgASACayIBQQFNDQQCfyABQYCAAU8EQCABQQR2IQNBIgwBCyABQQh2IAEg\" +\n \"AUH/B0siBBshA0EWQX4gBBsLIQQgA0EEdiADIANBP0siBhsiA0ECdiADIANBD0siBxsiAyADQQdL\" +\n \"IgN2IghBBiAIQQZJGyAEQQxqIAQgBhsiBEEGaiAEIAcbIgRBA2ogBCADG2pBAnRBkAtqIgQoAgAh\" +\n \"AyAEIAU2AgAgACACQQN0aiIEQQRqIAFBA3RBBXI2AgAgBCADNgIIIANFDQAgA0EEaigCAEEHcUEF\" +\n \"Rw0FIANBDGogBTYCAAsgACACQQN0QQZyNgIEDwtBkA0QAAALQcUNEAAAC0H2DRAAAAtBtggQAAAL\" +\n \"QcUJEAAACwkAIABBeGoQCQvBCgEKfwJAAkACQAJAAkACQAJAAkACQAJAAkACQAJAAkACQAJAIABB\" +\n \"BGooAgAiAUEHcUEGRgRAAkACfwJAAn8CQAJAAn8CQAJAAkBBjA0oAgAgAEcEQCABQQN2IgchASAA\" +\n \"IgIgACgCACIDQQRqKAIAIgRBB3FBBUcNBxogAygCCCECIANBDGooAgAiBUUNASAFQQRqKAIAQQdx\" +\n \"QQVHDQ8gBSACNgIIIARBA3YgB2ohASACDQUMBgsgACgCACIAQQRqKAIAIgJBB3FBBUYEQCAAKAII\" +\n \"IQEgACgCACEHIABBDGooAgAiA0UNAiADQQRqKAIAQQdxQQVHDRMgAyABNgIIIAENCgwbC0GMDSAA\" +\n \"NgIADwsgBEEPTQ0SIARBgIAISQ0BQSIhBiAEQQd2DAILIAJBD00NFiACQYCACEkNBUEiIQQgAkEH\" +\n \"dgwGC0EWQX4gBEH/P0siARshBiAEQQtBAyABG3YLIgFBBHYgASABQT9LIggbIgFBAnYgASABQQ9L\" +\n \"IgkbIgEgAUEHSyIBdiIKQQYgCkEGSRsgBkEMaiAGIAgbIgZBBmogBiAJGyIGQQNqIAYgARtqQQJ0\" +\n \"QZALaiIBKAIAIANHDRAgASADNgIAIARBA3YgB2ohASACRQ0BCyACQQRqKAIAQQdxQQVHDQogAkEM\" +\n \"aiAFNgIACyADCyECIAAgB0EDdCIEaiEDIAAgBGpBBGooAgAiBEEHcUEFRgRAIAAgB0EDdGoiBygC\" +\n \"CCEAAkACQCAHQQxqKAIAIgcEQCAHQQRqKAIAQQdxQQVHDQ0gByAANgIIIAANAQwCCyAEQQ9NDREC\" +\n \"fyAEQYCACE8EQEEiIQYgBEEHdgwBC0EWQX4gBEH/P0siBRshBiAEQQtBAyAFG3YLIgVBBHYgBSAF\" +\n \"QT9LIggbIgVBAnYgBSAFQQ9LIgkbIgUgBUEHSyIFdiIKQQYgCkEGSRsgBkEMaiAGIAgbIgZBBmog\" +\n \"BiAJGyIGQQNqIAYgBRtqQQJ0QZALaiIFKAIAIANHDRIgBSADNgIAIABFDQELIABBBGooAgBBB3FB\" +\n \"BUcNDCAAQQxqIAc2AgALIARBA3YiACABaiEBIAMgAEEDdGohAwsgAyACNgIAQYwNKAIAIAJGDQQg\" +\n \"AUEBTQ0FAn8gAUGAgAFPBEAgAUEEdiEAQSIMAQsgAUEIdiABIAFB/wdLIgMbIQBBFkF+IAMbCyED\" +\n \"IABBBHYgACAAQT9LIgcbIgBBAnYgACAAQQ9LIgQbIgAgAEEHSyIAdiIFQQYgBUEGSRsgA0EMaiAD\" +\n \"IAcbIgNBBmogAyAEGyIDQQNqIAMgABtqQQJ0QZALaiIDKAIAIQAgAyACNgIAIAJBBGogAUEDdEEF\" +\n \"cjYCACACIAA2AgggAARAIABBBGooAgBBB3FBBUcNByAAQQxqIAI2AgALDwtBFkF+IAJB/z9LIgUb\" +\n \"IQQgAkELQQMgBRt2CyICQQR2IAIgAkE/SyIFGyICQQJ2IAIgAkEPSyIGGyICIAJBB0siAnYiCEEG\" +\n \"IAhBBkkbIARBDGogBCAFGyIEQQZqIAQgBhsiBEEDaiAEIAIbakECdEGQC2oiAigCACAARw0QIAIg\" +\n \"ADYCACABRQ0RCyABQQRqKAIAQQdxQQVHDQ0gAUEMaiADNgIAQYwNIAc2AgAPC0GtDhAAAAtB9g0Q\" +\n \"AAALQbYIEAAAC0HFCRAAAAtBxQkQAAALQcUJEAAAC0HFCRAAAAtBxQkQAAALQcUJEAAAC0G2CBAA\" +\n \"AAtB3w4QAAALQbYIEAAAC0HfDhAAAAtBxQkQAAALQbYIEAAAC0HfDhAAAAtBjA0gBzYCAAtQAAJA\" +\n \"IAAgAU0EQAJAIAFB//8DakEQdiAAQf//A2pBEHYiAWsiAARAIABAACIAQX9GDQEgACABRw0DC0EB\" +\n \"DwtBAA8LQeIIEAAAC0H2CRAAAAsLvwUJAEGACAuUAUFzc2VydGlvbiBgcmVxLT5jb250cm9sLnNp\" +\n \"emUgPT0gOCcgZmFpbGVkIGF0IGZpYi5jOjU1AEFzc2VydGlvbiBgc2l6ZSA+PSAyJyBmYWlsZWQg\" +\n \"YXQgbWFsbG9jLmM6OTYAQXNzZXJ0aW9uIGBvbGRfaGVhcCA8PSBuZXdfaGVhcCcgZmFpbGVkIGF0\" +\n \"IG1lbS5jOjcAQZUJC5gBQXNzZXJ0aW9uIGBpID4gMCAmJiBpIDw9IDkwJyBmYWlsZWQgYXQgZmli\" +\n \"LmM6NTgAQXNzZXJ0aW9uIGBoZHJfaXNfZnJlZShoKScgZmFpbGVkIGF0IG1hbGxvYy5jOjUxAEFz\" +\n \"c2VydGlvbiBgZ3Jvd19yZXN1bHQgPT0gb2xkX3BhZ2VzJyBmYWlsZWQgYXQgbWVtLmM6MTQAQa4K\" +\n \"C1tBc3NlcnRpb24gYCFoYXZlW2krMV0nIGZhaWxlZCBhdCBmaWIuYzo2NgBBc3NlcnRpb24gYGJr\" +\n \"dHNbYmt0XSA9PSBoJyBmYWlsZWQgYXQgbWFsbG9jLmM6MTU0AEGIDQsDoAcBAEGQDQs0QXNzZXJ0\" +\n \"aW9uIGBoICE9IGJrdHNbQktUUysxXScgZmFpbGVkIGF0IG1hbGxvYy5jOjE5NQBBxQ0LMEFzc2Vy\" +\n \"dGlvbiBgcnNpemUgPj0gc2l6ZScgZmFpbGVkIGF0IG1hbGxvYy5jOjE5NgBB9g0LNkFzc2VydGlv\" +\n \"biBgaCAhPSBia3RzW0JLVFMgKyAxXScgZmFpbGVkIGF0IG1hbGxvYy5jOjE4NQBBrQ4LMUFzc2Vy\" +\n \"dGlvbiBgaGRyX2lzX2FsbG9jKGgpJyBmYWlsZWQgYXQgbWFsbG9jLmM6NTUAQd8OCzFBc3NlcnRp\" +\n \"b24gYGJrdHNbYmt0XSA9PSBoJyBmYWlsZWQgYXQgbWFsbG9jLmM6MTQ0\"\n ));\n\n const prog = the_api.blob(\"prog-fib\");\n\n let i = -1;\n but_more.onclick = () => {\n let cnt = Number(in_cnt.value);\n while(cnt > 0) {\n cnt -= 1;\n i += 1;\n const n1 = Number(in_min.value);\n const n2 = Number(in_max.value);\n if(n1 !== n1 \|\| n2 !== n2 \|\| n1 > n2 \|\| n1 !== (n1 >>> 0) \|\| n2 !== (n2 >>> 0) \|\| n2 > 200) {\n self.alert(\"Invalid input\");\n return;\n }\n\n for(const n of shuffle(range(n1, n2 + 1))) {\n the_api.tasks.enqueue(fibtask(prog, i, n));\n }\n the_api.report();\n }\n };\n\n addRunner(the_api);\n but_start.onclick = () => addRunner(the_api);\n}\n\nexport function addRunner(the_api: api.WorkProvider) {\n const el_runners = self.document.getElementById(\"runners\")!;\n\n const el_self = self.document.createElement(\"div\");\n el_runners.appendChild(el_self);\n\n const but_stop = self.document.createElement(\"button\")!;\n el_self.appendChild(but_stop);\n\n const table = self.document.createElement(\"table\")!;\n el_self.appendChild(table);\n\n const tbody = self.document.createElement(\"tbody\")!;\n table.appendChild(tbody);\n\n const st = new stat.Root(new PrintTSDB(tbody));\n const the_storage = new MemStorage();\n\n let r: Runner \| null;\n\n const do_stop = () => {\n but_stop.innerHTML = \"Stopping\";\n but_stop.onclick = () => {};\n r!.stop().then(() => {\n r = null;\n but_stop.innerHTML = \"Start\";\n but_stop.onclick = do_start;\n });\n };\n\n const do_start = () => {\n but_stop.innerHTML = \"Starting\";\n but_stop.onclick = () => {};\n Runner.create(st, the_api, the_storage, \"test-rig@invalid\").then((rv) => {\n r = rv;\n but_stop.innerHTML = \"Stop\";\n but_stop.onclick = do_stop;\n });\n };\n\n do_start();\n}\n\nself.onload = () => main();\n" }, { "alpha_fraction": 0.4780639410018921, "alphanum_fraction": 0.4810958802700043, "avg_line_length": 31.745214462280273, "blob_id": "da45bc1770ddf99f576def899d6b22178b2f4351", "content_id": "0af0ae22474906a0f715dedb543c1aa9a7733f8a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 27375, "license_type": "no_license", "max_line_length": 117, "num_lines": 836, "path": "/client/src/controller.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import * as exec_api from \"@/exec/api\";\n\nimport * as ui_api from \"@/API\";\n\nimport * as cbor from \"@/cbor\";\nimport * as cbut from \"@/cbor-util\";\nimport {Device} from \"@/device\";\nimport * as err from \"@/err\";\nimport * as obs from \"@/obs\";\nimport * as stat from \"@/stat\";\n\nimport IDBStorage from \"@/exec/idb_storage\";\nimport Runner from \"@/exec/runner\";\n\ninterface ReqOpts {\n data?: Uint8Array;\n expect_size?: number;\n}\n\ntype Settings = ui_api.Settings;\ntype Project = ui_api.Project;\n\nfunction parseResponse(data: ArrayBuffer, handlers: {[name: string]: ((r: cbor.Reader) => void) \| undefined}): void {\n let success: boolean \| undefined;\n let error: string \| undefined;\n\n try {\n const r = new cbor.Reader(data);\n r.map();\n while(true) {\n const key = r.maybeString();\n if(key === null) break;\n if(key === \"success\") success = r.boolean();\n else if(key === \"error\") error = r.string();\n else {\n const h = handlers[key];\n if(h === undefined) r.skip();\n else h(r);\n }\n }\n r.end();\n } catch(e) {\n if(e instanceof TypeError) throw new err.Validation(e.message);\n throw e;\n }\n\n if(!success) {\n throw new err.Runtime(error \|\| \"Unknown server error\");\n }\n}\n\nconst DEFAULT_SETTINGS: Settings = {\n allow_mobile_data: true,\n allow_on_battery: true,\n projects: [],\n};\n\nexport class Controller {\n public readonly stat_root: stat.Root;\n\n public readonly user = new obs.Subject<User \| null>();\n\n constructor(\n /* Base URL with trailing slash /\n public readonly url: string,\n public readonly device: Device,\n ) {\n this.stat_root = new stat.Root({\n write: (at: number, data: stat.Point[]): void => {\n const ud = this.user.value;\n if(!ud) return;\n for(const p of data) ud.onStat(p[0], p[1], p[2]);\n },\n writeError: (at: number, e: err.Data): void => {\n console.error(e);\n },\n });\n\n const login_data = window.localStorage.login_data;\n if(login_data === undefined) {\n this.user.next(null);\n } else {\n this.user.next(User.fromJSON(this, login_data));\n }\n\n obs.switchMap(this.user, (ud): obs.Observable<string \| undefined> => {\n if(ud === null) {\n return obs.single(undefined);\n } else {\n return ud.as_json;\n }\n }).subscribe((v) => {\n if(v) window.localStorage.login_data = v;\n else delete window.localStorage.login_data;\n }).start();\n }\n\n public reset(): Promise<void> {\n return obs.first(this.user).then((u) => {\n if(u !== undefined && u !== null) return u.logout();\n else return Promise.resolve();\n }).finally(() => IDBStorage.delete(\"blob_storage\"));\n }\n\n public login(username: string, password: string): Promise<void> {\n const req = new cbor.Writer();\n req.map(3);\n req.string(\"username\");\n req.string(username);\n req.string(\"password\");\n req.string(password);\n req.string(\"accesslevel\");\n req.string(\"worker\");\n req.end();\n\n return this.request(\"login\", {\n data: req.done(),\n }).then((data) => {\n let tok: string \| undefined;\n\n parseResponse(data, {\n \"token\": (r) => {\n tok = r.string();\n },\n });\n\n if(tok === undefined) {\n throw new err.Validation(\"Server provided no token\");\n }\n\n this.user.next(new User(this, username, tok, DEFAULT_SETTINGS));\n });\n }\n\n public loggedOut(): void {\n this.user.next(null);\n }\n\n public request(path: string, opts: ReqOpts): Promise<ArrayBuffer> {\n const data = opts.data;\n const headers = new Headers();\n if(data !== undefined) headers.set(\"content-type\", \"application/cbor\");\n const url = this.url + path;\n return fetch(url, {\n method: data === undefined ? \"GET\" : \"POST\",\n body: data,\n headers: headers,\n mode: \"cors\",\n credentials: \"omit\",\n cache: \"no-store\",\n redirect: \"follow\",\n }).then((res) => {\n if(!res.ok) {\n throw new err.Network(\"HTTP error\", {\n url: url,\n http_code: res.status,\n });\n }\n return res.arrayBuffer();\n });\n }\n\n public requestGraphs(query: string): Promise<ui_api.Graphs> {\n const headers = new Headers();\n const url = `${this.url}getGraphs?${query}`;\n return fetch(url, {\n method: \"POST\",\n body: null,\n headers: headers,\n mode: \"cors\",\n credentials: \"omit\",\n cache: \"no-store\",\n redirect: \"follow\",\n }).then((res) => {\n if(!res.ok) {\n throw new err.Network(\"HTTP error\", {\n url: url,\n http_code: res.status,\n });\n }\n return res.json();\n }).then((v) => {\n if(!v.success) throw new err.Network(v.error);\n return v.graphs;\n });\n }\n}\n\nfunction readBlobRef(r: cbor.Reader, project: string): exec_api.BlobRef {\n r.map();\n let id: string \| undefined;\n let size: number \| undefined;\n while(true) {\n const key = r.maybeString();\n if(key === null) break;\n else if(key === \"id\") id = r.string();\n else if(key === \"size\") size = r.number();\n else r.skip();\n }\n if(id === undefined \|\| size === undefined) throw new TypeError(\"Invalid blob reference\");\n r.end();\n return {id: project + \"/\" + id, size: size};\n}\n\nfunction readTask(project: string, id: string, data: Uint8Array): exec_api.Task {\n let program: exec_api.BlobRef \| undefined;\n let control: Uint8Array \| undefined;\n let blobs: exec_api.BlobRef[] = [];\n\n try {\n const r = new cbor.Reader(data);\n r.map();\n while(true) {\n const key = r.maybeString();\n if(key === null) break;\n if(key === \"program\") program = readBlobRef(r, project);\n else if(key === \"control\") control = r.bytes();\n else if(key === \"blobs\") blobs = cbut.readArray(r, (rd) => readBlobRef(rd, project));\n else r.skip();\n }\n r.end();\n } catch(e) {\n if(e instanceof TypeError) throw new err.Validation(e.message);\n throw e;\n }\n if(program === undefined \|\| control === undefined) throw new err.Validation(\"Invalid task\");\n\n return {\n id: `${project}/${id}`,\n project: project,\n program: program,\n in_control: control,\n in_blobs: blobs,\n };\n}\n\nclass WorkProvider implements exec_api.WorkProvider {\n public tasks_pending_min = 10;\n public tasks_finished_max = 100;\n public send_max_bytes = 2.0e5;\n public save_timeout = 1000;\n public cache_max = 2.0e8;\n\n private req_q: Array<() => void> = [];\n private _paused: boolean = false;\n private _stopped: boolean = false;\n\n private readonly cfg: obs.Cache<Settings>;\n\n constructor(\n private readonly ctl: Controller,\n cfg: obs.Observable<Settings>,\n private readonly token: string,\n ) {\n this.cfg = new obs.Cache(cfg);\n }\n\n public get paused() {\n return this._paused;\n }\n\n public set paused(v: boolean) {\n if(v) {\n if(this._stopped) return;\n this._paused = true;\n } else {\n if(!this._paused) return;\n this._paused = false;\n const r = this.req_q.splice(0);\n for(const f of r) f();\n }\n }\n\n public stop(): void {\n this.cfg.complete();\n this._stopped = true;\n this.paused = false;\n }\n\n private request(path: string, opts: ReqOpts): Promise<ArrayBuffer> {\n return new Promise((resolve, reject) => {\n const f = () => {\n if(this._stopped) {\n reject(new err.Network(\"Stopping WorkProvider\"));\n return;\n }\n try {\n resolve(this.ctl.request(path, opts));\n } catch(e) {\n reject(e);\n }\n };\n if(this.paused) {\n this.req_q.push(f);\n } else {\n f();\n }\n });\n }\n\n public getBlob(name: string, expected_size: number): Promise<Uint8Array> {\n const ix = name.indexOf(\"/\");\n if(ix === -1) return Promise.reject(new err.State(\"Invalid blob ID\"));\n\n const req = new cbor.Writer();\n req.map(3);\n req.string(\"pname\");\n req.string(name.substr(0, ix));\n req.string(\"name\");\n req.string(name.substr(ix + 1));\n req.string(\"token\");\n req.string(this.token);\n req.end();\n\n return this.request(\"getBlob\", {\n data: req.done(),\n expect_size: expected_size,\n }).then((data) => {\n let blob: Uint8Array \| undefined;\n parseResponse(data, {\n \"blob\": (r) => {\n blob = r.bytes();\n },\n });\n\n if(blob === undefined) {\n throw new err.Validation(\"No blob provided\");\n }\n\n return cbut.own(blob);\n });\n }\n\n public getTasks(): Promise<exec_api.TaskSet> {\n return obs.first(obs.filter(this.cfg, (c) => c.projects.length !== 0)).then((c) => {\n if(c === undefined) return Promise.resolve({tasks: []});\n const p = c.projects;\n return this._getTasks(p[Math.floor(Math.random() p.length)]);\n });\n }\n\n private _getTasks(project: string): Promise<exec_api.TaskSet> {\n const req = new cbor.Writer();\n req.map(3);\n req.string(\"pname\");\n req.string(project);\n req.string(\"maxtasks\");\n req.number(50); // TODO: set to something proper.\n req.string(\"token\");\n req.string(this.token);\n req.end();\n return this.request(\"getTasks\", {\n data: req.done(),\n }).then((data): exec_api.TaskSet \| Promise<exec_api.TaskSet> => {\n let taskIDs: string[] \| undefined;\n let taskBlobs: Uint8Array[] \| undefined;\n parseResponse(data, {\n \"taskIDs\": (r) => {\n taskIDs = cbut.readArray(r, (rd) => rd.string());\n },\n \"tasks\": (r) => {\n taskBlobs = cbut.readArray(r, (rd) => rd.bytes());\n },\n });\n\n if(taskIDs === undefined) throw new err.Validation(\"taskIDs\");\n if(taskBlobs === undefined) throw new err.Validation(\"tasks missing\");\n\n const n = taskIDs.length;\n if(taskBlobs.length !== n) {\n throw new err.Validation(\"tasks.length !== taskIDs.length\");\n }\n\n const tasks: exec_api.Task[] = [];\n for(let i = 0; i < n; i += 1) {\n tasks.push(readTask(project, taskIDs[i], taskBlobs[i]));\n }\n\n if(tasks.length === 0) {\n return new Promise((resolve, reject) => {\n const tm = self.setTimeout(() => {\n resolve({tasks: tasks});\n sub.stop();\n }, 5000);\n const fin = () => {\n self.clearTimeout(tm);\n resolve({tasks: tasks});\n sub.stop();\n };\n const sub = this.cfg.subscribe(undefined, fin, fin);\n sub.start();\n });\n }\n\n return {tasks: tasks};\n });\n }\n\n public sendTasks(tasks: exec_api.TaskResult[]): Promise<void> {\n const by_project_then_id = new Map<string, Map<string, exec_api.TaskResult>>();\n for(const task of tasks) {\n const ix = task.id.indexOf(\"/\");\n if(ix === -1) throw new err.State(\"Invalid task ID\", {task_id: task.id});\n const pname = task.id.substr(0, ix);\n const tname = task.id.substr(ix + 1);\n\n let by_id = by_project_then_id.get(pname);\n if(by_id === undefined) {\n by_id = new Map();\n by_project_then_id.set(pname, by_id);\n }\n by_id.set(tname, task);\n }\n\n const req = new cbor.Writer();\n req.map(2);\n req.string(\"tasks\");\n req.map(by_project_then_id.size);\n\n for(const [pname,by_id] of by_project_then_id) {\n req.string(pname);\n req.map(by_id.size);\n for(const [tname,task] of by_id) {\n req.string(tname);\n if(task.status === \"ok\") {\n req.map(2);\n req.string(\"status\");\n req.string(\"ok\");\n req.string(\"results\");\n cbut.writeArray(req, (w,d) => w.bytes(new Uint8Array(d)), task.data);\n req.end();\n } else if(task.status === \"error\") {\n req.map(2);\n req.string(\"status\");\n req.string(\"error\");\n req.string(\"error\");\n cbut.writeError(req, task.error);\n req.end();\n } else {\n req.map(1);\n req.string(\"status\");\n req.string(\"refused\");\n req.end();\n }\n }\n req.end();\n }\n req.end();\n req.string(\"token\");\n req.string(this.token);\n req.end();\n return this.request(\"sendTasks\", {\n data: req.done(),\n }).then((data) => {\n parseResponse(data, {});\n });\n }\n}\n\ninterface RunnerData {\n readonly runner: Runner;\n stop(): Promise<void>;\n}\n\nconst enum RunnerState {\n STOPPED = 0,\n STOPPING = 1,\n STARTING = 2,\n RUNNING = 3,\n}\n\nexport class User implements ui_api.User {\n public readonly projects = new obs.Cache<Map<string, Project>>();\n public readonly settings: obs.Subject<Settings>;\n public readonly overview = new obs.Subject<string[]>();\n public readonly as_json: obs.Observable<string>;\n\n private runner_promise: Promise<RunnerData> \| null = null;\n private runner_stop_promise: Promise<void> = Promise.resolve();\n private runner_state: RunnerState = RunnerState.STOPPED;\n\n constructor(\n private readonly ctl: Controller,\n public readonly username: string,\n public readonly token: string,\n settings: Settings,\n ) {\n this.settings = new obs.Subject(settings);\n\n this.projects.attach(obs.filter<Map<string,Project>, Map<string,Project> \| null>(obs.refresh(\n () => this.requestProjects().catch((e) => null),\n 3600 * 1000\n ), (v): v is Map<string,Project> => v !== null));\n\n this.as_json = new obs.Cache(obs.map(this.settings, (s) => {\n return JSON.stringify({\n \"username\": this.username,\n \"token\": this.token,\n \"settings\": {\n \"allow_mobile_data\": s.allow_mobile_data,\n \"allow_on_battery\": s.allow_on_battery,\n \"projects\": s.projects,\n },\n });\n }));\n\n this.startExec();\n }\n\n public static fromJSON(ctl: Controller, data: string): User {\n const d = JSON.parse(data);\n const settings = Object.assign({}, DEFAULT_SETTINGS);\n const s2 = d[\"settings\"];\n if(s2) {\n if(s2[\"allow_mobile_data\"]) settings.allow_mobile_data = true;\n if(s2[\"allow_on_battery\"]) settings.allow_on_battery = true;\n if(s2[\"projects\"]) settings.projects = Array.from(s2[\"projects\"]);\n }\n return new User(ctl, d[\"username\"], d[\"token\"], settings);\n }\n\n public stop(): Promise<void> {\n return this.stopExec().catch((e) => this.ctl.stat_root.reportError(e));\n }\n\n public logout(): Promise<void> {\n const req = new cbor.Writer();\n req.map(1);\n req.string(\"token\");\n req.string(this.token);\n req.end();\n\n return Promise.all([\n this.stop(),\n this.ctl.request(\"logout\", {\n data: req.done(),\n }).then((data) => {\n parseResponse(data, {});\n }).catch((e) => this.ctl.stat_root.reportError(e)),\n ]).then(() => {\n this.ctl.loggedOut();\n });\n }\n\n private startExec(): Promise<Runner> {\n let pr = this.runner_promise;\n if(pr === null) {\n this.runner_promise = pr = this.runner_stop_promise.catch(() => {}).then(\n () => IDBStorage.create(this.ctl.stat_root, \"blob_storage\")\n ).then((storage) => {\n const wp = new WorkProvider(this.ctl, this.settings, this.token);\n return Runner.create(this.ctl.stat_root, wp, storage, this.token).then((r) => {\n const dev = this.ctl.device;\n const obs_block_work = obs.switchMap(this.settings, (s) => {\n if(s.allow_on_battery) return obs.single(false);\n else return dev.on_battery;\n });\n const obs_block_download = obs.switchMap(this.settings, (s) => {\n if(s.allow_mobile_data) return obs.single(false);\n else return dev.on_mobile_data;\n });\n\n this.have_battery = true;\n this.have_network = true;\n\n const subs = [\n obs_block_work.subscribe((v) => {\n this.ov_work_paused = v;\n this.makeOverview();\n r.paused = v;\n }, () => {\n this.ov_work_paused = false;\n this.have_battery = false;\n this.makeOverview();\n r.paused = false;\n }),\n obs_block_download.subscribe((v) => {\n this.ov_dl_paused = v;\n this.makeOverview();\n wp.paused = v;\n }, () => {\n this.ov_dl_paused = false;\n this.have_network = false;\n this.makeOverview();\n wp.paused = false;\n }),\n ];\n\n for(const sub of subs) sub.start();\n\n this.runner_state = RunnerState.RUNNING;\n this.makeOverview();\n\n return {\n runner: r,\n stop() {\n for(const sub of subs) sub.stop();\n wp.stop();\n return r.stop().finally(() => {\n storage.stop();\n });\n },\n };\n });\n });\n\n this.runner_state = RunnerState.STARTING;\n this.makeOverview();\n }\n return pr.then((rd) => rd.runner);\n }\n\n private stopExec(): Promise<void> {\n const rpr = this.runner_promise;\n if(rpr === null) return this.runner_stop_promise;\n this.runner_promise = null;\n\n return this.runner_stop_promise = rpr.then((r) => {\n this.runner_state = RunnerState.STOPPING;\n this.makeOverview();\n\n return r.stop();\n }).finally(() => {\n this.runner_state = RunnerState.STOPPED;\n this.makeOverview();\n });\n }\n\n private requestProjects(): Promise<Map<string, Project>> {\n const ud = this.ctl.user.value;\n if(ud === null) return Promise.reject(new err.State(\"Not logged in\"));\n\n const req = new cbor.Writer();\n req.map(1);\n req.string(\"token\");\n req.string(ud.token);\n req.end();\n return this.ctl.request(\"getProjectsList\", {\n data: req.done(),\n }).then((data) => {\n const ps = new Map<string, Project>();\n parseResponse(data, {\n \"projects\": (r) => {\n r.map();\n while(true) {\n const name = r.maybeString();\n if(name === null) break;\n let desc: string = name;\n r.map();\n while(true) {\n const key = r.maybeString();\n if(key === null) break;\n if(key === \"description\") desc = r.string();\n else r.skip();\n }\n r.end();\n\n ps.set(name, {\n id: name,\n title: name,\n description: desc,\n });\n }\n r.end();\n },\n });\n\n return ps;\n });\n }\n\n public updateSettingsF(f: (c: Settings) => Settings) {\n this.settings.next(f(this.settings.value));\n }\n\n public updateSettings(upd: Partial<Settings>): void {\n this.updateSettingsF((c) => Object.assign({}, c, upd));\n }\n\n public setProjectOn(name: string): void {\n this.updateSettingsF((c) => {\n return Object.assign({}, c, {\n projects: [name].concat(c.projects),\n });\n });\n }\n\n public requestGraphs(query: string): Promise<ui_api.Graphs> {\n return this.ctl.requestGraphs(query);\n }\n\n public setProjectOff(name: string): void {\n this.updateSettingsF((c) => {\n let proj = c.projects;\n const ix = proj.indexOf(name);\n if(ix === -1) return c;\n proj = Array.from(proj);\n proj.splice(ix, 1);\n return Object.assign({}, c, {\n projects: proj,\n });\n });\n }\n\n public refreshProjects(): Promise<void> {\n this.projects.reset();\n // TODO: get actual promise\n return Promise.resolve();\n }\n\n public onStat(name: string, key: stat.Key, value: number) {\n if(name === \"runner/tasks_pending\") {\n this.ov_tasks_pending = value;\n } else if(name === \"runner/tasks_finished\") {\n this.ov_tasks_finished = value;\n } else if(name === \"runner/tasks_sent\") {\n this.ov_tasks_sent = value;\n } else if(name === \"runner/tasks_running\") {\n this.ov_tasks_running = value;\n } else if(name === \"work_dispatcher/work_queue_size\") {\n this.ov_tasks_ready = value;\n } else {\n return;\n }\n this.makeOverview();\n }\n\n private have_battery: boolean = false;\n private have_network: boolean = false;\n private ov_work_paused: boolean = false;\n private ov_dl_paused: boolean = false;\n public ov_tasks_pending: number = 0;\n public ov_tasks_ready: number = 0;\n public ov_tasks_finished: number = 0;\n public ov_tasks_sent: number = 0;\n public ov_tasks_running: number = 0;\n\n private makeOverview(): void {\n const ov: string[] = [];\n switch(this.runner_state) {\n case RunnerState.STARTING:\n ov.push(\"State: Starting up\");\n break;\n case RunnerState.RUNNING:\n ov.push(\"State: Ready\");\n break;\n case RunnerState.STOPPING:\n ov.push(\"State: Stopping\");\n break;\n case RunnerState.STOPPED:\n ov.push(\"State: Stopped\");\n break;\n }\n if(!this.have_battery) {\n ov.push(\"Battery status not available\");\n }\n if(this.ov_work_paused) {\n ov.push(\"On battery; not working\");\n }\n if(!this.have_network) {\n ov.push(\"Network status not available\");\n }\n if(this.ov_dl_paused) {\n ov.push(\"On mobile data; not requesting work\");\n }\n ov.push(`Tasks waiting: ${this.ov_tasks_pending - this.ov_tasks_ready - this.ov_tasks_running}`);\n ov.push(`Tasks ready to run: ${this.ov_tasks_ready}`);\n ov.push(`Tasks in send queue: ${this.ov_tasks_finished}`);\n ov.push(`Tasks sent: ${this.ov_tasks_sent}`);\n\n if(process.env.NODE_ENV === \"development\") {\n ov.push(`navigator.connection: ${(window.navigator as any).connection}`);\n ov.push(`navigator.mozConnection: ${(window.navigator as any).mozConnection}`);\n ov.push(`navigator.webkitConnection: ${(window.navigator as any).webkitConnection}`);\n ov.push(`navigator.battery: ${(window.navigator as any).battery}`);\n ov.push(`navigator.mozBattery: ${(window.navigator as any).mozBattery}`);\n ov.push(`navigator.webkitBattery: ${(window.navigator as any).webkitBattery}`);\n ov.push(`navigator.getBattery: ${(window.navigator as any).getBattery}`);\n ov.push(`navigator.mozGetBattery: ${(window.navigator as any).mozGetBattery}`);\n ov.push(`navigator.webkitGetBattery: ${(window.navigator as any).webkitGetBattery}`);\n }\n this.overview.next(ov);\n }\n}\n\nexport class UIState implements ui_api.ClientState {\n public get user() {\n return this.ctl.user;\n }\n\n constructor(public readonly ctl: Controller) {}\n\n public login(username: string, password: string): Promise<void> {\n return this.ctl.login(username, password);\n }\n\n public loginGuest(): Promise<void> {\n const alphabet = \"abcdefghijklmnopqrstuvwxyz\";\n\n let username = \"guest-\";\n for(let i = 0; i < 10; i++) {\n username += alphabet[Math.floor(Math.random() * alphabet.length)];\n }\n\n let password = \"\";\n for(let i = 0; i < 40; i++) {\n password += alphabet[Math.floor(Math.random() * alphabet.length)];\n }\n\n return this.signUp(username, password);\n }\n\n public signUp(username: string, password: string): Promise<void> {\n const req = new cbor.Writer();\n req.map(3);\n req.string(\"username\");\n req.string(username);\n req.string(\"password\");\n req.string(password);\n req.string(\"accesslevel\");\n req.string(\"worker\");\n req.end();\n\n return this.ctl.request(\"register\", {\n data: req.done(),\n }).then((data) => {\n parseResponse(data, {});\n // Hope login succeeds.\n return this.login(username, password);\n });\n }\n\n public reset(): Promise<void> {\n return this.ctl.reset();\n }\n}\n" }, { "alpha_fraction": 0.7015098929405212, "alphanum_fraction": 0.7032520174980164, "avg_line_length": 24.323530197143555, "blob_id": "52b2e43e2a00b145f4c7212ad993dc9e05158b0f", "content_id": "b764986d94f12ed687baa0f8f567745b0e00510c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 1722, "license_type": "no_license", "max_line_length": 81, "num_lines": 68, "path": "/client/src/exec/api.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import {Data as ErrorData} from \"@/err\";\n\nexport type ErrorData = ErrorData;\n\nexport interface BlobRef {\n id: string;\n size: number;\n}\n\nexport interface Task {\n id: string;\n project: string;\n program: BlobRef;\n in_control: Uint8Array;\n in_blobs: BlobRef[];\n}\n\nexport interface TaskSet {\n tasks: Task[];\n}\n\nexport interface TaskResultBase {\n id: string;\n}\n\nexport interface TaskResultOK extends TaskResultBase {\n status: \"ok\";\n data: Uint8Array[];\n}\n\nexport interface TaskResultError extends TaskResultBase {\n status: \"error\";\n error: ErrorData;\n}\n\nexport interface TaskResultRefused extends TaskResultBase {\n status: \"refused\";\n}\n\nexport type TaskResult = TaskResultOK \| TaskResultError \| TaskResultRefused;\n\nexport interface BlobProvider {\n // expected_size is provided for accounting purposes.\n getBlob(name: string, expected_size: number): Promise<Uint8Array>;\n\n /* Maximum number of bytes to store. /\n readonly cache_max: number;\n}\n\nexport interface WorkProvider extends BlobProvider {\n / The implementation must deal with waiting/backoff in case of network\n * problems. /\n getTasks(): Promise<TaskSet>;\n sendTasks(results: TaskResult[]): Promise<void>;\n\n / If the number of tasks available drops below this, request more. /\n readonly tasks_pending_min: number;\n\n / Stop requesting more tasks if there are too many finished tasks that\n * haven't been sent yet. /\n readonly tasks_finished_max: number;\n\n / Maximum number of bytes (approximately) to send at a time. /\n readonly send_max_bytes: number;\n\n / Number of milliseconds after which to save non-important state changes. /\n readonly save_timeout: number;\n}\n" }, { "alpha_fraction": 0.49443453550338745, "alphanum_fraction": 0.4966510832309723, "avg_line_length": 30.301658630371094, "blob_id": "4dee43957ea04b3fe8eb602e1a05b8edd06ff7d5", "content_id": "2e1c0da81ce79da2784b33a91e7228781ab27e67", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 20753, "license_type": "no_license", "max_line_length": 110, "num_lines": 663, "path": "/client/src/exec/runner.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import Deque from \"double-ended-queue\";\n\nimport Backoff from \"@/backoff\";\nimport as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport * as api from \"./api\";\nimport {BlobRepo} from \"./repo\";\nimport {Ref, Storage} from \"./storage\";\nimport * as wd from \"./work-dispatcher\";\nimport * as workapi from \"./workapi\";\n\nimport * as rs from \"./runner-state\";\n\n// @ts-ignore\nimport worker_text from \"raw-loader!Dist/worker.js\";\n\nenum TaskStatus {\n OK = 0,\n ERROR = 1,\n REFUSED = 2,\n}\n\nclass Task {\n public readonly id: string;\n public readonly project: string;\n public readonly program: Ref;\n\n public in_control: Uint8Array;\n public in_blobs: Ref[];\n\n public out_status?: TaskStatus;\n public out_data?: Ref[];\n public out_error?: api.ErrorData;\n\n public tryCancel?: () => void;\n\n constructor(\n id: string, project: string, program: Ref,\n in_control: Uint8Array, in_blobs: Ref[],\n ) {\n this.id = id;\n this.project = project;\n this.program = program;\n\n this.in_control = in_control;\n this.in_blobs = in_blobs;\n }\n\n public data(): rs.TaskData {\n const d: rs.TaskData = {\n id: this.id, project: this.project, program: this.program,\n in_control: this.in_control, in_blobs: this.in_blobs,\n };\n if(this.out_status !== undefined) d.out_status = TaskStatus[this.out_status];\n if(this.out_data !== undefined) d.out_data = this.out_data;\n if(this.out_error !== undefined) d.out_error = this.out_error;\n return d;\n }\n\n public setDone(out_data: Ref[]): void {\n this.out_status = TaskStatus.OK;\n this.out_data = out_data;\n }\n\n public setError(e: api.ErrorData): void {\n this.out_status = TaskStatus.ERROR;\n this.out_error = Object.assign({}, e);\n }\n\n public setRefused(): void {\n this.out_status = TaskStatus.REFUSED;\n }\n}\n\nconst worker_blob: Blob = new Blob([worker_text], {type: \"text/javascript\"});\n\nexport default class Runner {\n private readonly st_pending = new stat.Metric(\"runner/tasks_pending\").attach(this.st);\n private readonly st_blocked = new stat.Metric(\"runner/tasks_blocked\").attach(this.st);\n private readonly st_running = new stat.Metric(\"runner/tasks_running\").attach(this.st);\n private readonly st_finished = new stat.Metric(\"runner/tasks_finished\").attach(this.st);\n private readonly st_sending = new stat.Metric(\"runner/tasks_sending\").attach(this.st);\n private readonly st_sent = new stat.Counter(\"runner/tasks_sent\").attach(this.st);\n\n private readonly dispatcher = new wd.Dispatcher(this.st, worker_blob);\n\n // Only works in Firefox?\n public static send_wasm_mod: boolean = false;\n\n private tasks = new Map<string, Task>();\n\n /* Tasks with no result yet. /\n private tasks_pending = new Set<Task>();\n / Tasks waiting for data to be downloaded. The value is a cancellation\n * function. /\n private tasks_blocked = new Set<Task>();\n / Tasks being processed by workers. /\n private tasks_running = new Set<Task>();\n / Tasks with results ready to be sent. /\n private tasks_finished = new Deque<Task>();\n / Tasks being sent right now. They might be moved back to `tasks_finished`\n * if sending fails. /\n private tasks_sending = new Set<Task>();\n\n private requesting_tasks: boolean = false;\n private readonly request_tasks_backoff = new Backoff(1000);\n private sending_results: boolean = false;\n private readonly send_results_backoff = new Backoff(1000);\n\n / If not stopping, `undefined`. Otherwise, callback indicating that the\n * Runner has stopped. Invoke through `partStop()`. /\n private stop_cb?: () => void;\n / If running, `-1`. Otherwise, the number of remaining calls to\n * `partStop()` expected. /\n private stop_count: number = 0;\n\n private constructor(\n private readonly st: stat.Sink,\n private readonly provider: api.WorkProvider,\n public readonly repo: BlobRepo,\n private readonly state_key: string\n ) {}\n\n public static create(\n st: stat.Sink,\n provider: api.WorkProvider,\n storage: Storage,\n state_key: string\n ): Promise<Runner> {\n return BlobRepo.create(st, provider, storage).then((repo) => repo.readState(\"runner\").then((data) => {\n const r = new Runner(st, provider, repo, state_key);\n if(data !== null) {\n try {\n r.load(data);\n } catch(e) {\n st.reportError(e);\n }\n }\n r.start();\n return r;\n }));\n }\n\n public get is_running(): boolean {\n return this.stop_count === -1;\n }\n\n public get is_stopped(): boolean {\n return this.stop_count === 0 && this.stop_cb === undefined;\n }\n\n public get is_stopping(): boolean {\n return this.stop_cb !== undefined;\n }\n\n private start(): void {\n if(!this.is_stopped) {\n throw new err.State(\"Runner already started\");\n }\n\n this.stop_count = -1;\n\n for(const t of this.tasks_pending) {\n this.startTask(t);\n }\n\n this.maybeRequestTasks();\n this.maybeSendResults();\n }\n\n public stop(): Promise<void> {\n if(this.stop_cb !== undefined) {\n throw new err.State(\"Already stopping Runner\");\n }\n if(this.stop_count === 0) {\n throw new err.State(\"Runner not started yet\");\n }\n const pr = new Promise<void>((resolve, reject) => {\n this.stop_cb = resolve;\n });\n\n this.stop_count = this.tasks_pending.size;\n if(this.requesting_tasks) this.stop_count += 1;\n if(this.sending_results) this.stop_count += 1;\n\n for(const t of this.tasks_pending) {\n const f = t.tryCancel;\n if(f !== undefined) f();\n }\n\n return pr.then(() => this.save(true)).then(() => {\n delete this.stop_cb;\n });\n }\n\n / Indicate a component is ready to stop. Returns `true` iff the component\n * should stop. /\n private partStop(): boolean {\n if(this.stop_cb === undefined) return false;\n console.assert(this.stop_count > 0);\n this.stop_count -= 1;\n if(this.stop_count === 0) this.stop_cb();\n return true;\n }\n\n public report() {\n this.st_pending.set(this.tasks_pending.size);\n this.st_blocked.set(this.tasks_blocked.size);\n this.st_running.set(this.tasks_running.size);\n this.st_finished.set(this.tasks_finished.length);\n this.st_sending.set(this.tasks_sending.size);\n }\n\n public addTaskSet(ts: api.TaskSet) {\n const getBlob = (b: api.BlobRef) => this.repo.fromAPI(b);\n const added_tasks: Task[] = [];\n try {\n for(const info of ts.tasks) {\n if(this.tasks.get(info.id)) {\n throw new err.State(\"Task already exists\", {task_id: info.id});\n }\n const task = new Task(\n info.id, info.project, getBlob(info.program),\n info.in_control, info.in_blobs.map(getBlob),\n );\n added_tasks.push(task);\n this.tasks.set(task.id, task);\n }\n } catch(e) {\n for(const task of added_tasks) {\n this.tasks.delete(task.id);\n }\n throw e;\n }\n\n for(const task of added_tasks) {\n this.newTask(task);\n }\n\n this.save(true);\n this.report();\n }\n\n private requestTasks() {\n if(this.partStop()) {\n this.requesting_tasks = false;\n return;\n }\n\n this.provider.getTasks().then((tasks) => {\n this.addTaskSet(tasks);\n this.request_tasks_backoff.succeed();\n }).catch((e: Error) => {\n if(!(e instanceof err.Cancelled)) {\n this.request_tasks_backoff.fail();\n this.st.reportError(e);\n }\n }).finally(() => {\n this.requesting_tasks = false;\n if(this.partStop()) return;\n this.maybeRequestTasks();\n });\n }\n\n public maybeRequestTasks() {\n if(!this.is_running) {\n if(this.is_stopping) return;\n throw new err.State(\"Not running\");\n }\n if(this.tasks_pending.size >= this.provider.tasks_pending_min) return;\n if(this.tasks_finished.length >= this.provider.tasks_finished_max) return;\n if(this.requesting_tasks) return;\n self.setTimeout(this.requestTasks.bind(this), this.request_tasks_backoff.value);\n this.requesting_tasks = true;\n }\n\n private taskResult(t: Task): Promise<api.TaskResult> {\n const st = t.out_status!;\n if(st === TaskStatus.OK) {\n const blobs = t.out_data!;\n return this.repo.withBlobs(blobs,\n () => Promise.all(blobs.map((blob) => this.repo.read(blob)))\n ).then((data) => {\n const res: api.TaskResultOK = {\n id: t.id,\n status: \"ok\",\n data: data,\n };\n return res;\n });\n } else if(st === TaskStatus.ERROR) {\n const res: api.TaskResultError = {\n id: t.id,\n status: \"error\",\n error: t.out_error!,\n };\n return Promise.resolve(res);\n } else {\n const res: api.TaskResultRefused = {\n id: t.id,\n status: \"refused\",\n };\n return Promise.resolve(res);\n }\n }\n\n private sendResults() {\n if(this.partStop()) {\n this.sending_results = false;\n return;\n }\n\n const tasks: Task[] = [];\n\n let space_left = this.provider.send_max_bytes;\n while(space_left >= 0) {\n const t = this.tasks_finished.peekFront();\n if(t === undefined) break;\n\n space_left -= 32;\n if(t.out_status === TaskStatus.OK) {\n space_left -= 4 t.out_data!.length;\n for(const blob of t.out_data!) space_left -= blob.size;\n } else if(t.out_status === TaskStatus.ERROR) {\n space_left -= 1024;\n }\n\n if(space_left < 0 && tasks.length !== 0) break;\n\n const t2 = this.tasks_finished.dequeue();\n console.assert(t === t2);\n tasks.push(t);\n }\n\n if(tasks.length === 0) {\n this.sending_results = false;\n return;\n }\n\n for(const t of tasks) {\n this.tasks_sending.add(t);\n }\n\n const results = Promise.all(tasks.map((t) => this.taskResult(t)));\n\n results.then((data) => this.provider.sendTasks(data)).then(() => {\n const unpin: Ref[] = [];\n for(const t of tasks) {\n this.tasks_sending.delete(t);\n this.tasks.delete(t.id);\n if(t.out_data !== undefined) {\n for(const ref of t.out_data) {\n unpin.push(ref);\n }\n }\n this.st_sent.inc();\n }\n this.save(false).then(() => {\n for(const ref of unpin) {\n this.repo.unpin(ref);\n }\n });\n this.send_results_backoff.succeed();\n this.report();\n }, (e: Error) => {\n for(const t of tasks) {\n if(this.tasks_sending.has(t)) {\n this.tasks_sending.delete(t);\n this.tasks_finished.insertFront(t);\n }\n }\n if(!(e instanceof err.Cancelled)) {\n this.send_results_backoff.fail();\n this.st.reportError(e);\n }\n this.report();\n }).finally(() => {\n this.sending_results = false;\n if(this.partStop()) return;\n this.maybeRequestTasks();\n this.maybeSendResults();\n });\n this.report();\n }\n\n public maybeSendResults() {\n if(!this.is_running) {\n if(this.is_stopping) return;\n throw new err.State(\"Not running\");\n }\n if(this.tasks_finished.isEmpty()) return;\n if(this.sending_results) return;\n self.setTimeout(this.sendResults.bind(this), this.send_results_backoff.value);\n this.sending_results = true;\n }\n\n private taskFinish(t: Task) {\n this.tasks_pending.delete(t);\n this.tasks_finished.enqueue(t);\n this.save(false);\n if(this.partStop()) return;\n this.maybeRequestTasks();\n this.maybeSendResults();\n this.report();\n }\n\n private taskError(t: Task, e: Error) {\n if(e instanceof err.Cancelled) {\n if(this.partStop()) return;\n t.setRefused();\n } else {\n t.setError(err.dataOf(e));\n }\n this.taskFinish(t);\n }\n\n private taskDone(t: Task, data: Uint8Array[]) {\n const refs: Ref[] = [];\n const promises = data.map((d) => {\n const [ref, pr] = this.repo.create(d);\n refs.push(ref);\n return pr;\n });\n\n Promise.all(promises).then(() => {\n t.setDone(refs);\n this.taskFinish(t);\n }, (e) => {\n for(const ref of refs) this.repo.unpin(ref);\n this.taskError(t, e);\n });\n }\n\n private onControl(ctl: wd.Controller, msg: workapi.OutControl): boolean {\n if(msg.get_blob !== undefined) {\n const ref = msg.get_blob;\n this.repo.read(ref).then((data) => {\n ctl.sendControl({get_blob: [ref.id, data]}, [data.buffer as ArrayBuffer]);\n }, (e) => {\n ctl.kill(e);\n });\n return true;\n }\n return false;\n }\n\n private newTask(t: Task) {\n this.tasks_pending.add(t);\n if(this.is_running) {\n this.startTask(t);\n }\n }\n\n private startTask(t: Task) {\n if(this.tasks_blocked.has(t)) {\n throw new err.State(\"Task already started\", {\n \"task_id\": t.id,\n });\n }\n\n this.tasks_blocked.add(t);\n\n this.repo.withBlobs([t.program].concat(t.in_blobs), () => {\n delete t.tryCancel;\n this.tasks_blocked.delete(t);\n\n let release: (() => void) \| undefined;\n const pr_release = new Promise<void>((resolve,reject) => {\n release = resolve;\n });\n\n let tm: number \| undefined;\n\n const ctl = this.dispatcher.push({\n onStart: () => {\n this.tasks_running.add(t);\n this.report();\n\n tm = self.setTimeout(() => {\n ctl.kill(new err.Runtime(\"Timed out\"));\n }, 30 * 1000);\n },\n onDone: (data: workapi.OutResult) => {\n if(tm !== undefined) self.clearTimeout(tm);\n delete t.tryCancel;\n release!();\n this.tasks_running.delete(t);\n this.taskDone(t, data.data);\n },\n onError: (e: Error) => {\n if(tm !== undefined) self.clearTimeout(tm);\n delete t.tryCancel;\n release!();\n this.tasks_running.delete(t);\n this.taskError(t, e);\n },\n onControl: (data: workapi.OutControl): boolean => {\n if(data.notify_started !== undefined) {\n release!();\n return true;\n }\n return this.onControl(ctl, data);\n },\n }, {\n program: t.program,\n control: t.in_control,\n data: t.in_blobs,\n }, []);\n\n t.tryCancel = () => {\n ctl.kill(new err.Cancelled(\"Task cancelled\"));\n };\n\n this.report();\n return pr_release;\n }, new Promise((resolve, reject) => {\n t.tryCancel = () => {\n resolve(new err.Cancelled(\"Task cancelled\"));\n };\n })).catch((e: Error) => {\n this.tasks_blocked.delete(t);\n delete t.tryCancel;\n this.taskError(t, e);\n this.report();\n });\n }\n\n private save_cur: Promise<void> = Promise.resolve();\n private save_next: Promise<void> \| null = null;\n private save_timer: number \| null = null;\n public save(now: boolean): Promise<void> {\n if(now && this.save_timer !== null) {\n clearTimeout(this.save_timer);\n this.save_timer = null;\n } else if(this.save_next) return this.save_next;\n\n const s = new Promise<void>((resolve, reject) => {\n if(now) {\n this.save_cur.then(resolve);\n } else {\n this.save_timer = self.setTimeout(() => {\n console.assert(this.save_next === s);\n this.save_timer = null;\n this.save_cur.then(resolve);\n }, this.provider.save_timeout);\n }\n }).then(() => {\n console.assert(this.save_next === s);\n this.save_next = null;\n this.save_cur = s;\n return this.repo.writeState(\"runner\", rs.dumpState(this.data()));\n }).catch((e: Error) => {\n this.st.reportError(e);\n });\n return this.save_next = s;\n }\n\n public data(): rs.RunnerData {\n return {\n state_key: this.state_key,\n tasks: Array.from(this.tasks.values()).map((t) => t.data()),\n };\n }\n\n private loadTask(d: rs.TaskData, pinned: Ref[]): Task {\n const t = new Task(\n d.id, d.project, this.repo.register(d.program),\n d.in_control, d.in_blobs.map((ref) => this.repo.register(ref)),\n );\n\n if(d.out_status === undefined) {\n // pass\n } else if(d.out_status === \"OK\") {\n if(d.out_data === undefined) {\n throw new err.State(\"Task finished but no data stored\");\n }\n t.setDone(d.out_data.map((ref) => {\n const p = this.repo.pin(ref);\n pinned.push(p);\n return p;\n }));\n } else if(d.out_status === \"ERROR\") {\n if(d.out_error === undefined) {\n throw new err.State(\"Task failed but no error stored\");\n }\n t.setError(d.out_error);\n } else if(d.out_status === \"REFUSED\") {\n t.setRefused();\n }\n\n return t;\n }\n\n private load(buf: Uint8Array) {\n let d: rs.RunnerData;\n try {\n d = rs.loadState(buf);\n } catch(e) {\n throw new err.State(\"Failed to decode state\", {\n \"cause\": err.dataOf(e),\n });\n }\n\n if(d.state_key !== this.state_key) {\n // State key changed, ignore state.\n return;\n }\n\n const tasks: Task[] = [];\n const pinned: Ref[] = [];\n\n const pinReset = (at: number) => {\n for(const ref of pinned.splice(at)) {\n this.repo.unpin(ref);\n }\n };\n\n try {\n for(const t of d.tasks) {\n tasks.push(this.loadTask(t, pinned));\n }\n } catch(e) {\n pinReset(0);\n throw e;\n }\n\n for(const task of tasks) {\n if(this.tasks.get(task.id)) {\n this.st.reportError(new err.State(\"Task already exists\", {\n \"task_id\": task.id,\n }));\n continue;\n }\n\n this.tasks.set(task.id, task);\n if(task.out_status === undefined) {\n this.newTask(task);\n } else {\n this.tasks_finished.enqueue(task);\n }\n }\n }\n\n private _unpause: (() => void) \| null = null;\n public get paused(): boolean {\n return this._unpause !== null;\n }\n public set paused(v: boolean) {\n if(v) {\n if(this._unpause !== null) return;\n this.dispatcher.pause(new Promise<void>((resolve,reject) => {\n this._unpause = resolve;\n }));\n } else {\n const cb = this._unpause;\n if(cb === null) return;\n this._unpause = null;\n cb();\n return;\n }\n }\n}\n" }, { "alpha_fraction": 0.5833333134651184, "alphanum_fraction": 0.7291666865348816, "avg_line_length": 31, "blob_id": "bfd7f23380f48e2e46563243e863ad6e3b55d1d2", "content_id": "9293ea8f209876fc3c38f6f4b13511f411c8b281", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 96, "license_type": "no_license", "max_line_length": 61, "num_lines": 3, "path": "/server/header.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "TOKENSIZE = 20\nSESSION_EXPIRE = 302460601000 # Token expiry one month\nPRODUCTION = False\n" }, { "alpha_fraction": 0.7432432174682617, "alphanum_fraction": 0.7813267707824707, "avg_line_length": 37.761905670166016, "blob_id": "1bd2918150ad8b7d6c006a662813a290065fb911", "content_id": "072ef01b71b5d3374e8fd92f2a47ef1f3c415ee9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 814, "license_type": "no_license", "max_line_length": 84, "num_lines": 21, "path": "/client/src/exec/test-blobs.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import {b64Buf, strBuf} from \"./test-util\";\n\nexport const prog_echo = b64Buf(\n \"AGFzbQEAAAABDQNgAX8AYAAAYAF/AX8CEwEDZW52C3BwdHcxX2Fib3J0AAADBAMBAgIFAwEAAgYO\" +\n \"An8AQaCIBAt/AEGSCAsHXQcGbWVtb3J5AgALX19oZWFwX2Jhc2UDAApfX2RhdGFfZW5kAwEKcHB0\" +\n \"dzFfaW5pdAABDHBwdHcxX21hbGxvYwACDXBwdHcxX2NsZWFudXAAAQlwcHR3MV9ydW4AAwquAQMD\" +\n \"AAELRwECf0GACEGACCgCACIBQQAgAGtBB3EgAGpqIgA2AgACQCAAQRB2IgA/ACICSwRAIAAgAmtA\" +\n \"AEF/Rg0BCyABDwtBhAgQAAALYAEEfyAAKAIIQQN0QQRyEAIiAyAAKAIINgIAIAAoAggEQCAAQQxq\" +\n \"IQEgA0EEaiECA0AgAiABKQIANwIAIAFBCGohASACQQhqIQIgBEEBaiIEIABBCGooAgBJDQALCyAD\" +\n \"CwsdAgBBgAgLAyAEAQBBhAgLDU91dCBvZiBtZW1vcnk=\"\n);\n\nexport const prog_abort = b64Buf(\n \"AGFzbQEAAAABDQNgAX8AYAAAYAF/AX8CEwEDZW52C3BwdHcxX2Fib3J0AAADBAMBAgIFAwEAAgYO\" +\n \"An8AQaCIBAt/AEGSCAsHXQcGbWVtb3J5AgALX19oZWFwX2Jhc2UDAApfX2RhdGFfZW5kAwEKcHB0\" +\n \"dzFfaW5pdAABDHBwdHcxX21hbGxvYwACDXBwdHcxX2NsZWFudXAAAQlwcHR3MV9ydW4AAwpVAwMA\" +\n \"AQtHAQJ/QYAIQYAIKAIAIgFBACAAa0EHcSAAamoiADYCAAJAIABBEHYiAD8AIgJLBEAgACACa0AA\" +\n \"QX9GDQELIAEPC0GECBAAAAsHAEEAEAAACwsdAgBBgAgLAyAEAQBBhAgLDU91dCBvZiBtZW1vcnk=\"\n);\n\nexport const hello_world = strBuf(\"Hello World!\");\n" }, { "alpha_fraction": 0.34272944927215576, "alphanum_fraction": 0.3623238205909729, "avg_line_length": 26.443395614624023, "blob_id": "b7f553a2e85592e6d1f4c4d978d23241f9a4510e", "content_id": "5b8629f5418815db92d32ab1185959ad7b2e5732", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2909, "license_type": "no_license", "max_line_length": 90, "num_lines": 106, "path": "/testCustomer/graphing/customGraphTest.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "# Automated tests for graph drawing\nimport sys\nfrom tests import \nimport time\nimport random, string\n\n\nVERBOSE = True # Set to true if you want all data to be printed\nPROJECT_NAME = \"Project\"\nPROJECT_DESCRIPTION = \"This is the project description\"\nCUSTOMER_NAME = \"Edd\"\nCUSTOMER_PASS = \"password\"\n\n\ndef test(res, testname):\n (succ, data) = res\n time.sleep(0.1)\n if succ:\n print(testname + \" AOK\")\n if VERBOSE:\n print(data)\n return data \n else:\n print(testname + \" FAILED\")\n if VERBOSE:\n print(data)\n sys.exit(str(data))\n\n\n# Create a custom graph to upload\ncustomGraphs = {\n \"testGraph1\": {\n \"type\": 'scatter',\n \"data\": {\n \"datasets\": [\n {\n \"label\": 'good1m80',\n \"borderColor\": 'rgb(0, 255, 0)',\n \"data\": [\n {\"x\": 0, \"y\": 0},\n {\"x\": 1, \"y\": 1},\n {\"x\": 2, \"y\": 2}\n ],\n \"showLine\": True,\n \"lineTension\": 0.1\n },\n {\n \"label\": 'bad1m90',\n \"borderColor\": 'rgb(0, 0, 255)',\n \"data\": [\n {\"x\": 0, \"y\": 0},\n {\"x\": 1, \"y\": 5},\n {\"x\": 2, \"y\": 5}\n ],\n \"showLine\": False,\n \"lineTension\": 0.1\n }]\n },\n \"options\": {\n \"scales\": {\n \"xAxes\": [{\n \"type\": 'time',\n \"time\": {\n \"unit\": 'second'\n }\n }]\n }\n }\n },\n \"testGraph2\": {\n \"type\": 'scatter',\n \"data\": {\n \"datasets\": [\n {\n \"label\": 'Good',\n \"borderColor\": 'rgb(0, 255, 0)',\n \"data\": [\n {\"x\": 0, \"y\": 0},\n {\"x\": 50, \"y\": 150},\n {\"x\": 100, \"y\": 100}\n ],\n \"showLine\": True,\n \"lineTension\": 0.1\n }\n ]\n },\n \"options\": {\n \"scales\": {\n \"xAxes\": [{\n #\"type\": 'time',\n #\"time\": {\n # \"unit\": 'second'\n #}\n }]\n }\n }\n }\n}\n\n\ntime.sleep(1)\ndata = test(registerCustomer(CUSTOMER_NAME, CUSTOMER_PASS), \"Test register customer\")\nctok = test(login(CUSTOMER_NAME, CUSTOMER_PASS, \"customer\"), \"testCustomerLogin\")[\"token\"]\ntest(createNewProject(ctok, PROJECT_NAME, PROJECT_DESCRIPTION), \"testCreateNewProject\")\n\ntest(updateGraphs(ctok, customGraphs, PROJECT_NAME), \"testUpdateGraphs\")\n" }, { "alpha_fraction": 0.5356611013412476, "alphanum_fraction": 0.5455899238586426, "avg_line_length": 26.976852416992188, "blob_id": "dec4862b04e2fdad512c922b20ad343be27cfaa6", "content_id": "c46d03df481a7ee3e3b4016972b56acd6cd423d7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6043, "license_type": "no_license", "max_line_length": 87, "num_lines": 216, "path": "/testCustomer/serverRequest.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "## Automated tests for the server\nimport requests, cbor\n\nSERVER_IP = \"35.178.90.246/api\"\n\ndef reboot():\n r = requests.post(\"http://\" + SERVER_IP + \"/reboot\")\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\n\n\n# Test ping\ndef testPing():\n r = requests.post(\"http://\" + SERVER_IP + \"/ping\")\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\n\ndef registerCustomer(username, password):\n r = requests.post(\"http://\" + SERVER_IP + \"/register\", data = cbor.dumps(\n { \"username\": username,\n \"password\": password,\n \"accesslevel\": \"customer\"\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef registerWorker(username, password):\n r = requests.post(\"http://\" + SERVER_IP + \"/register\", data = cbor.dumps(\n { \"username\": username,\n \"password\": password,\n \"accesslevel\": \"worker\"\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef login(username, password, accesslevel):\n r = requests.post(\"http://\" + SERVER_IP + \"/login\", data = cbor.dumps(\n { \"username\": username,\n \"password\": password,\n \"accesslevel\": accesslevel\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef logout(token):\n r = requests.post(\"http://\" + SERVER_IP + \"/logout\", data = cbor.dumps(\n { \"token\": token }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n \ndef createNewProject(token, pname, pdescription):\n r = requests.post(\"http://\" + SERVER_IP + \"/createNewProject\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"pdescription\": pdescription\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n \ndef createNewBlob(token, pname, blob, metadata):\n r = requests.post(\"http://\" + SERVER_IP + \"/createNewBlob\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"blob\": blob,\n \"metadata\": metadata\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef blobToTask(token, pname, blobID):\n r = requests.post(\"http://\" + SERVER_IP + \"/blobToTask\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"blobID\": blobID,\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n \ndef getBlobMetadata(token, pname, blobIDs):\n r = requests.post(\"http://\" + SERVER_IP + \"/getBlobMetadata\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"blobIDs\": blobIDs,\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n \ndef getBlob(token, pname, name):\n r = requests.post(\"http://\" + SERVER_IP + \"/getBlob\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"name\": name,\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n data[\"blob\"] = data[\"blob\"]\n data[\"metadata\"] = cbor.loads(data[\"metadata\"])\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n \ndef getTasks(token, pname, maxtasks):\n r = requests.post(\"http://\" + SERVER_IP + \"/getTasks\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"maxtasks\": maxtasks,\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef sendTasks(token, tasks):\n r = requests.post(\"http://\" + SERVER_IP + \"/sendTasks\", data = cbor.dumps(\n { \"token\": token,\n \"tasks\": tasks\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef deleteBlob(token, pname, blobID):\n r = requests.post(\"http://\" + SERVER_IP + \"/deleteBlob\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"blobID\": blobID\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef getGraphs(pname):\n r = requests.post(\"http://\" + SERVER_IP + \"/getGraphs\", data = cbor.dumps(\n { \"pname\": pname\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\n\ndef getProjectsList():\n r = requests.post(\"http://\" + SERVER_IP + \"/getProjectsList\")\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n\ndef updateGraphs(token, graphsCBOR, pname):\n r = requests.post(\"http://\" + SERVER_IP + \"/updateCustomGraphs\", data = cbor.dumps(\n { \"token\": token,\n \"pname\": pname,\n \"customGraphs\": graphsCBOR\n }))\n\n if r.status_code != 200:\n return (False, r.text)\n\n data = cbor.loads(r.content)\n return (data[\"success\"] and data[\"error\"] == \"\", data)\n" }, { "alpha_fraction": 0.6101378798484802, "alphanum_fraction": 0.6220648288726807, "avg_line_length": 29.146066665649414, "blob_id": "aba52a3ca575156faef1297e43025762a57f76aa", "content_id": "222e9556d75f8e333e0e459cd8d4413c5a33fe97", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2683, "license_type": "no_license", "max_line_length": 84, "num_lines": 89, "path": "/server/servertests/autotester.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "## Automated tests for the server\nimport sys\nfrom tests import \nimport time\n\nVERBOSE = True # Set to true if you want all data to be printed\n\ndef test(res, testname):\n (succ, data) = res\n time.sleep(0.1)\n if succ:\n print(testname + \" AOK\")\n if VERBOSE:\n print(data)\n return data \n else:\n print(testname + \" FAILED\")\n if VERBOSE:\n print(data)\n sys.exit(str(data))\n\n# Start test\nprint(\"Rebooting server...\")\nreboot()\ntime.sleep(1)\n\ntest(testPing(), \"testPing\")\ntest(registerCustomer(\"Edd\", \"password1\"), \"testRegisterCustomer\")\ntest(registerWorker(\"Hristo\", \"hunter2\"), \"testRegisterWorker\")\ndata = test(login(\"Edd\", \"password1\", \"customer\"), \"testCustomerLogin\")\nctok = data[\"token\"]\ntest(logout(ctok), \"testCustomerLogout\")\ndata = test(login(\"Edd\", \"password1\", \"customer\"), \"testCustomerLogin\")\nctok = data[\"token\"]\ndata = test(login(\"Hristo\", \"hunter2\", \"worker\"), \"testLoginWorker\")\nwtok = data[\"token\"]\n\n# Test blob creation\ntest(createNewProject(ctok, \"Project\", \"Description\"), \"testCreateNewProject\")\ndata = test(createNewBlob(ctok, \"Project\", b'blob1', b'meta1'), \"testCreateNewBlob\")\nb1 = data[\"blobID\"]\ndata = test(createNewBlob(ctok, \"Project\", b'blob2', b'meta2'), \"testCreateNewBlob\")\nb2 = data[\"blobID\"]\ndata = test(createNewBlob(ctok, \"Project\", b'blob3', b'meta3'), \"testCreateNewBlob\")\nb3 = data[\"blobID\"]\n\n# Test blobs are correctly returned\ndata = test(blobToTask(ctok, \"Project\", b1), \"testBlobToTask\")\ndata = test(blobToTask(ctok, \"Project\", b2), \"testBlobToTask\")\ndata = test(blobToTask(ctok, \"Project\", b3), \"testBlobToTask\")\n\ndata = test(getBlobMetadata(ctok, \"Project\", []), \"testGetBlobMetadata\")\n\ndata = test(getBlob(ctok, \"Project\", b1), \"testGetBlob\")\n\ndata = test(getBlob(ctok, \"Project\", b2), \"testGetBlob\")\ndata = test(getBlob(ctok, \"Project\", b3), \"testGetBlob\")\n\n# Worker tests\ndata = test(getTasks(wtok, \"Project\", 2), \"testGetTasks\")\ndata = test(getTasks(wtok, \"Project\", 2), \"testGetTasks\")\ndata = test(getTasks(wtok, \"Project\", 2), \"testGetTasks\")\n\ntasksreturned = {\n \"Project\": {\n str(b1): {\n \"results\": [\"resblob1\", \"resblob2\"],\n \"metadatas\": [],\n \"status\": \"ok\"\n },\n\n str(b2): {\n \"results\": [\"resblob3\", \"resblob4\"],\n \"metadatas\": [],\n \"status\": \"ok\"\n },\n\n str(b3): {\n \"results\": [\"resblob5\", \"resblob6\"],\n \"metadatas\": [],\n \"status\": \"ok\"\n }\n }\n}\n\ndata = test(sendTasks(wtok, tasksreturned), \"testSendTasks\")\n\ntest(getGraphs(\"Project\", \"m\"), \"testGetGraphs\")\ntest(getProjectsList(), \"testGetProjectsList\")\n" }, { "alpha_fraction": 0.565258800983429, "alphanum_fraction": 0.5674182176589966, "avg_line_length": 31.132652282714844, "blob_id": "35298cf36c179a13dfc8202f208742593d0bdf3b", "content_id": "82514882525f0d1c1a017f34afd94e17d7e8e527", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 15745, "license_type": "no_license", "max_line_length": 119, "num_lines": 490, "path": "/server/server.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import cherrypy, os, cbor\nfrom urllib.parse import urlparse\nimport database\nfrom header import \nfrom time import mktime\nfrom datetime import datetime\n\nimport json\n\nglobal debug\ndebug = True\n\ndef log(msg):\n if debug:\n print(msg)\n\n# Generic Functions\ndef getTime():\n return mktime(datetime.now().timetuple())1000\n\n\n# Checks whether the session is currently active\ndef checkSessionActive(token):\n if not database.querySession(token, \"username\")[0]:\n return False\n\n sessiontime = database.querySession(token, \"starttime\")[1]\n if sessiontime + SESSION_EXPIRE < getTime():\n return False\n\n return True\n\n\n# Generic Responses\ndef errormsg(m):\n return(cbor.dumps({'success': False, 'error': m}))\n\ndef success():\n return(cbor.dumps({'success': True, 'error': ''}))\n\n\nclass RootServer:\n @cherrypy.expose\n def ping(self):\n return success()\n\n\n @cherrypy.expose\n def register(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs\n try:\n username = str(body[\"username\"])\n password = str(body[\"password\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n try:\n accesslevel = str(body[\"accesslevel\"])\n except Exception:\n accesslevel = \"worker\"\n\n if accesslevel not in [\"customer\", \"worker\"]:\n accesslevel = \"worker\"\n\n # Registers a new user\n if not database.register(username, password, accesslevel):\n return errormsg(\"Registration failed.\")\n\n return success()\n\n\n # username, password, accesslevel\n @cherrypy.expose\n def login(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs\n try:\n username = str(body[\"username\"])\n password = str(body[\"password\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n try:\n accesslevel = str(body[\"accesslevel\"])\n except Exception:\n accesslevel = \"worker\"\n\n # Reset the current session\n database.deleteSession(username, \"username\")\n if accesslevel not in [\"customer\", \"worker\"]:\n accesslevel = \"worker\"\n\n (succ, token) = database.login(username, password, accesslevel)\n if not succ:\n return errormsg(\"Login failed. Invalid username or password.\")\n\n return cbor.dumps({'success': True, 'error': '', 'token': token})\n \n # token\n @cherrypy.expose\n def logout(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs\n try:\n token = str(body[\"token\"])\n except Exception:\n return errormsg(\"Invalid token\")\n\n # Check that the user has an active session\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n username = database.querySession(token, \"username\")[1]\n \n database.logoutGraphUpdate(username)\n database.deleteSession(token, \"token\")\n\n return success()\n\n ## Customer methods ##\n\n # token, pname, pdescription\n @cherrypy.expose\n def createNewProject(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n pdescription = str(body[\"pdescription\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n if database.querySession(token, \"accesslevel\")[1] != \"customer\":\n return errormsg(\"Invalid access level\")\n \n if not database.createNewProject(pname, pdescription):\n return errormsg(\"Sorry, project name is taken.\")\n\n return success()\n\n # token, pname, blob, metadata\n @cherrypy.expose\n def createNewBlob(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n blob = body[\"blob\"]\n metadata = body[\"metadata\"]\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not (type(blob) is bytes and type(metadata) is bytes):\n return errormsg(\"Invalid blob or metadata type - should be bytes\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n \n if database.querySession(token, \"accesslevel\")[1] != \"customer\":\n return errormsg(\"Invalid access level.\")\n\n (succ, blobID) = database.createNewBlob(pname, blob, metadata)\n if succ:\n return(cbor.dumps({'success': True, 'error': '', 'blobID': blobID}))\n else:\n return errormsg(\"Database failure: \" + str(blobID))\n\n # token, pname, blobID\n @cherrypy.expose\n def blobToTask(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n blobID = str(body[\"blobID\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n \n if database.querySession(token, \"accesslevel\")[1] != \"customer\":\n return errormsg(\"Invalid access level.\")\n\n (succ, msg) = database.blobToTask(pname, blobID)\n if not succ:\n return errormsg(\"Database failure: \" + msg)\n\n return(cbor.dumps({'success': True, 'error': ''}))\n return success()\n\n # Token, pname, blobIDs\n @cherrypy.expose\n def getBlobMetadata(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n blobIDs = []\n for i, blob in enumerate(body[\"blobIDs\"]):\n blobIDs.append(str(blob))\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n \n if database.querySession(token, \"accesslevel\")[1] != \"customer\":\n return errormsg(\"Invalid access level.\")\n\n (succ, metas) = database.getBlobMetadata(pname, blobIDs)\n if not succ:\n return errormsg(\"Database failure: \" + metas)\n return(cbor.dumps({'success': True, 'error': '', 'metadata': metas}))\n \n @cherrypy.expose\n # token, pname, name\n def getBlob(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n name = str(body[\"name\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n (succ, b, m) = database.getBlob(pname, name)\n\n if not succ:\n return errormsg(\"Database error\")\n\n return cbor.dumps({'success': True, 'error': '', 'blob': b, 'metadata': m})\n\n # token, pname, blobID\n @cherrypy.expose\n def deleteBlob(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n blobID = str(body[\"blobID\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n (succ, accesslevel) = database.querySession(token, \"accesslevel\")\n if not succ:\n return errormsg(\"Database could not identify accesslevel. Invalud session.\")\n if accesslevel != \"customer\":\n return errormsg(\"Invalid access level.\")\n\n (succ, msg) = database.deleteBlob(pname, blobID)\n if not succ:\n return errormsg(\"Database failed: \" + msg)\n return success()\n\n # token, pname, maxtasks\n @cherrypy.expose\n def getTasks(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n username = database.querySession(token, \"username\")[1]\n print(\"Session name: \" + username)\n pname = str(body[\"pname\"])\n maxtasks = int(body[\"maxtasks\"])\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n (succ, tasks, taskIDs) = database.getTasks(pname, username, maxtasks)\n if not succ:\n return errormsg(\"Database failed: \" + tasks)\n\n # Returns a list of up to maxtasks tasks\n return cbor.dumps({\"success\": True, \"error\": \"\", \"tasks\": tasks, \"taskIDs\": taskIDs})\n\n # Takes the token, the customer name and project name being worked on, the task ID, and blobsandmetas, a list of\n # tuples mapping each blob to its metadata\n # token, pname, taskID, results\n @cherrypy.expose\n def sendTasks(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs, check access level\n try:\n token = str(body[\"token\"])\n username = database.querySession(token, \"username\") [1]\n tasks = body[\"tasks\"]\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n\n\n for pname, project in tasks.items():\n for taskID, task in project.items():\n # Construct metadatas\n meta = cbor.dumps({\n \"result\": True,\n \"taskID\": taskID,\n \"control\": b'',\n \"blobs\": [],\n \"blobs_n\": 0\n })\n\n if \"results\" in task.keys():\n results = task[\"results\"]\n else:\n results = []\n for b in results:\n if not type(b) is bytes:\n return errormsg(\"Tasks were not of type bytes\")\n\n (succ, msg) = database.sendTasks(pname, taskID, results, [meta]len(results), username, task[\"status\"])\n if not succ:\n return errormsg(\"Database error: \" + msg)\n\n return success()\n\n @cherrypy.expose\n def reboot(self):\n if not PRODUCTION:\n cherrypy.engine.restart()\n return success()\n\n @cherrypy.expose\n def getProjectsList(self):\n projects = {}\n for pname, project in database.projects.items():\n projects[pname] = {\"description\": project[\"description\"]}\n return(cbor.dumps({'success': True, 'error': '', \"projects\": projects}))\n\n #pname, precision, kind (where kind in [\"standardGraphs\", \"customGraphs\"])\n @cherrypy.expose\n def getGraphs(self, pname, prec, kind):\n # Get request body\n try:\n prec = int(prec)\n pname = str(pname)\n kind = str(kind)\n except Exception:\n return errormsg(\"Invalid input types.\")\n\n if not kind in [\"standardGraphs\", \"customGraphs\"]:\n return errormsg(\"Invalid kind. Must be 'standardGraphs' or 'customgraphs'.\")\n\n try:\n description = database.projects[pname][\"description\"]\n except Exception:\n return errormsg(\"Project does not exist.\")\n\n (succ, graphs) = database.getGraphs(pname, kind)\n if not succ:\n return errormsg(\"Database error: \" + graphs)\n\n if prec > 1:\n graphs2 = {}\n for name, data in graphs.items():\n newdata = []\n prevtime = 0\n for (timecode, datum) in data:\n t = timecode - (timecode % prec)\n if t == prevtime:\n newdata = newdata[:-1]\n newdata.append(tuple((t, datum)))\n prevtime = t\n\n graphs2[name] = newdata\n \n else:\n graphs2 = graphs\n\n return json.dumps({'success': True, 'error': '', \"graphs\": graphs2, \"description\": description})\n\n # Customer only\n # token, customGraphs\n @cherrypy.expose\n def updateCustomGraphs(self):\n # Get request body\n try:\n body = cbor.loads(cherrypy.request.body.read())\n except Exception:\n return errormsg(\"Incorrectly encoded body\")\n\n # Sanity check inputs\n try:\n token = str(body[\"token\"])\n pname = str(body[\"pname\"])\n customGraphs = body[\"customGraphs\"]\n except Exception:\n return errormsg(\"Invalid inputs\")\n\n if database.querySession(token, \"accesslevel\")[1] != \"customer\":\n return errormsg(\"Invalid access level\")\n\n if not checkSessionActive(token):\n return errormsg(\"Session expired or invalid token in logout. Please try again.\")\n\n (succ, err) = database.updateCustomGraphs(customGraphs, pname)\n if not succ:\n return errormsg(\"Database error: \" + err)\n\n return success()\n\n \n\nif __name__ == '__main__':\n cherrypy.config.update({'server.socket_host': '0.0.0.0',\n 'server.socket_port': 8081,\n 'tools.sessions.on' : True,\n 'tools.sessions.timeout': 10 # Sessions time out after 10 mins\n })\n \n cherrypy.quickstart(RootServer())\n" }, { "alpha_fraction": 0.6028631925582886, "alphanum_fraction": 0.6097561120986938, "avg_line_length": 23.493507385253906, "blob_id": "b5b3d25ec5a5fd325f6e5cd3d4233482ebfcfa10", "content_id": "461c629385d2bf7c08b4b029b974541f6c360273", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1886, "license_type": "no_license", "max_line_length": 104, "num_lines": 77, "path": "/testCustomer/clientTester.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "from tests import \nimport sys\nimport time\nimport os\nimport cbor\n\ntry:\n username = sys.argv[1]\n password = sys.argv[2]\n projectName = sys.argv[3]\nexcept:\n print(\"Please enter a username, password and project you wish to work on\")\n sys.exit()\n\n(success, data) = registerWorker(username, password)\nif not success:\n print (\"Failed to register worker\")\n print (data[\"error\"])\n sys.exit()\n\ntime.sleep(1)\n\n(success, data) = login (username, password, 'worker')\nif not success:\n print (\"Failed to login\")\n sys.exit()\n\ntoken = data[\"token\"]\n\n# Now logged in \n\nwhile (True):\n (success, data) = getTasks(token, projectName, 1)\n if not success:\n print(\"no success finding tasks\")\n time.sleep(1)\n continue\n # Found task \n tasks = data[\"tasks\"]\n if (len(tasks) != 1):\n print (\"More/less tasks recieved than requested - expecting 1\")\n break\n \n taskID = data[\"taskIDs\"][0]\n\n # Get interval, write to local as InputBlob\n intervalb = tasks[0][\"control\"]\n with open(\"blobInput\", \"wb\") as f:\n f.write(intervalb)\n\n programBlobID = (tasks[0][\"program\"])[\"id\"]\n (success, data) = getBlob(token, projectName, programBlobID)\n if not success:\n print (\"Cannot retrieve webassembly blob\")\n break\n \n wacode = data[\"blob\"]\n with open(\"collatzClient\", \"wb\") as f:\n f.write(wacode)\n\n os.system(\"node1/bin/node node-executor.js collatzClient blobInput\")\n\n with open(\"output-blob-0\", \"rb\") as f:\n outputBlob = intervalb + f.read()\n \n metad = { \"result\": True }\n\n print(len(outputBlob))\n taskData = { projectName: { taskID: { \"results\": [outputBlob], \"metadatas\": [], \"status\": \"ok\" } }}\n (success, data) = sendTasks(token, taskData)\n if not success:\n print (\"oh dear\")\n print (data[\"error\"])\n \n break\n\nlogout(token)\n" }, { "alpha_fraction": 0.4674115478992462, "alphanum_fraction": 0.48230913281440735, "avg_line_length": 21.375, "blob_id": "86b0ef72a5163632269cf2bc8e353508a321afaf", "content_id": "ae35aa965c66c4923c28c9131ae7a1bd82f71ec9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 537, "license_type": "no_license", "max_line_length": 40, "num_lines": 24, "path": "/testCustomer/blob2Out.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import sys\nimport struct\n\ntry:\n blobfile = sys.argv[1]\nexcept:\n raise Exception('enter name pls')\n\nno_bytes = 4 # 4 if integer\n\nwith open(blobfile, 'rb') as f:\n while True:\n seq = f.read(no_bytes)\n if len(seq) == 0:\n print(\"Read all bytes\")\n break\n elif len(seq) < no_bytes:\n print(\"Bytes left over\")\n break\n else: # len(seq4b) == no_bytes\n v = 0\n for i in range(0, no_bytes):\n v += seq[i] << 8i \n print(v)\n" }, { "alpha_fraction": 0.6636011600494385, "alphanum_fraction": 0.6684414148330688, "avg_line_length": 29.382352828979492, "blob_id": "4e07c6afb4e041e134a32998c76b126215c4fef7", "content_id": "797a5ddf897c5b02a8895c408b9d653cea716d92", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "SQL", "length_bytes": 2066, "license_type": "no_license", "max_line_length": 58, "num_lines": 68, "path": "/database_1.sql", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "CREATE TABLE Customer (\n customerID Integer NOT NULL,\n customername Char(25) NOT NULL,\n CONSTRAINT customerPk PRIMARY KEY(customerID)\n);\n\nCREATE TABLE Worker (\n workerID Integer NOT NULL,\n username Char(25) NOT NULL,\n password Char(25) NOT NULL,\n prefwifidata Integer DEFAULT 1,\n prefbattery Integer DEFAULT 1,\n CONSTRAINT workerPk PRIMARY KEY(workerID),\n CONSTRAINT projectFk FOREIGN KEY(pID)\n REFERENCES Project(pID),\n);\n\nCREATE TABLE Project (\n pID Integer NOT NULL,\n pname Char(25) NOT NULL,\n pdescription,\n customerID Integer NOT NULL,\n CONSTRAINT projectPk PRIMARY KEY(pID),\n CONSTRAINT customerFk FOREIGN KEY(customerID)\n REFERENCES Customer(customerID) ON DELETE CASCADE,\n);\n\nCREATE TABLE Project_task (\n taskID Integer NOT NULL,\n task,\n pID Integer NOT NULL,\n workerID Integer,\n CONSTRAINT taskPk PRIMARY KEY(taskID),\n CONSTRAINT projectFk FOREIGN KEY(pID)\n REFERENCES Project(pID) ON DELETE CASCADE,\n CONSTRAINT workerFk FOREIGN KEY(workerID)\n REFERENCES Worker(workerID) ON DELETE CASCADE,\n);\n\nCREATE TABLE Data_blob (\n blobID Integer NOT NULL,\n blob,\n metadata,\n pID Integer NOT NULL,\n CONSTRAINT blobPk PRIMARY KEY(blobID),\n CONSTRAINT projectFk FOREIGN KEY(pID)\n REFERENCES Project(pID) ON DELETE CASCADE,\n);\n\nCREATE TABLE Blob_task_entity (\n blobID Integer NOT NULL,\n taskID Integer NOT NULL,\n CONSTRAINT blobtaskPk PRIMARY KEY(blobID, taskID),\n CONSTRAINT blobFk FOREIGN KEY(blobID)\n REFERENCES Data_blob(blobID) ON DELETE CASCADE,\n CONSTRAINT taskFk FOREIGN KEY(taskID)\n REFERENCES Project_task(taskID) ON DELETE CASCADE,\n);\n\nCREATE TABLE Completed_task (\n pID Integer NOT NULL,\n taskID Integer NOT NULL,\n blobs,\n blobmetadatas,\n CONSTRAINT taskIDPk PRIMARY KEY(taskID),\n CONSTRAINT pIDFk FOREIGN KEY(pID)\n REFERENCES Project(pID) ON DELETE CASCADE\n);\n" }, { "alpha_fraction": 0.5258455872535706, "alphanum_fraction": 0.533503532409668, "avg_line_length": 22.37313461303711, "blob_id": "3b8a1914219a88912a0ee32f536ee1273ea9db3e", "content_id": "54bb455747785e092ab9461b27a9675ad5d95bcb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1567, "license_type": "no_license", "max_line_length": 99, "num_lines": 67, "path": "/testCustomer/makeProject.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "from serverRequest import \nimport sys\nimport time\n\n#reboot()\n#time.sleep(1)\n\ntry:\n username = sys.argv[1]\n password = sys.argv[2]\n projectName = sys.argv[3]\nexcept:\n print(\"Please enter a username, password and projectname\")\n sys.exit()\n\ntry:\n testPing()\nexcept Exception:\n print(\"Server is down\")\n sys.exit()\n\n(success, dataRegister) = registerCustomer(username, password)\nif (not success):\n print (\"sad\")\n print (dataRegister)\n sys.exit()\n\n(success, dataLogin) = login(username, password, \"customer\")\nif (not success):\n print (\"Sad 2 ): \")\n sys.exit()\n\ntoken = dataLogin[\"token\"]\n(success, data) = createNewProject(token, projectName, \"Help us find the longest Collatz sequence\")\n\ngraphs = { \n \"highestResults\": { \n \"type\": 'scatter',\n \"data\": {\n \"datasets\": [{\n \"label\": 'Longest sequences computed from tasks',\n \"borderColor\": 'rgb(0, 255, 0)',\n \"data\": [],\n \"showLine\": True,\n \"lineTension\": 0.0 \n }]\n },\n \"options\": {\n \"scales\": {\n \"xAxes\": [{\n \"time\": {\n \"unit\": 'second' \n }\n }]\n }\n }\n }\n}\n\nupdateGraphs(token, graphs, projectName)\n\n(success, dataLogout) = logout(token)\nif (success):\n print (\"Rebooted, Registered Customer, Created new project\")\n print (\"username: \" + username)\n print (\"password: \" + password)\n print (\"projectName: \" + projectName)\n\n" }, { "alpha_fraction": 0.6078890562057495, "alphanum_fraction": 0.6110966801643372, "avg_line_length": 31.954286575317383, "blob_id": "1f8de56fdd9bce924bdad91e9f2e4850e26e1389", "content_id": "439cf5832388b612f799a26d5aa9be3bc1bb0de8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 11535, "license_type": "no_license", "max_line_length": 125, "num_lines": 350, "path": "/server/database.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "# A skeleton database program\n# NB: INPUTS ARE NOT GUARANTEED SAFE OR SANITISED. PLEASE SANITISE YOUR INPUTS FOR THE DATABASE\n\n# Test implementation\nfrom datetime import datetime\nfrom time import mktime\nfrom Crypto.Random import random\nimport numpy as np\nimport string\nimport cbor\nimport re\n\nfrom header import \n\ndef changeGraph(pID, graphname, diff):\n graphs = projects[pID][\"graphing\"][\"standardGraphs\"]\n lastActive = graphs[graphname][-1:][0][\"y\"]\n graphs[graphname].append({\"x\": getTime(), \"y\": lastActive+diff})\n\ndef getTime():\n return int(mktime(datetime.now().timetuple()))1000\n\ndef salthash(passwd, salt):\n return passwd\n\ndef generateToken():\n done = False\n while not done:\n tok = ''.join(random.choice(string.ascii_letters) for m in range(TOKENSIZE))\n done = tok not in sessions\n\n return tok\n\nusers = {}\t# Maps username to (password, accesslevel)\nsessions = {} # Maps a username to a session\n # Session comtains username, bool active, accesslevel. token, time\nprojects = {} # Maps project names to projects\n\n## AUTHENTICATION ##\n# Registers a new user in the database. Returns true iff successful\ndef register(username, password, accesslevel):\n if username in users:\n return False\n else:\n users[username] = {\"hashpass\": salthash(password, username), \"accesslevel\": accesslevel, \"issuedTasks\": {}}\n return True\n\n# Returns whether the username corresponds to the password of a user, of level accesslevel\ndef login(username, password, accesslevel):\n if username in users:\n # Test for correct credentials\n if users[username][\"hashpass\"] == salthash(password, username) and users[username][\"accesslevel\"] == accesslevel:\n # Create a new session\n token = generateToken()\n sessions[token] = {}\n\n s = sessions[token]\n t = getTime()\n s[\"username\"] = username\n s[\"starttime\"] = t\n s[\"accesslevel\"] = accesslevel\n\n # Graphing\n for pname in users[username][\"issuedTasks\"]:\n changeGraph(pname, \"activeWorkers\", 1)\n\n return (True, token)\n return (False, 0)\n\ndef logoutGraphUpdate(username):\n # Graphing\n for pname in users[username][\"issuedTasks\"]:\n # Remove active user for each project\n changeGraph(pname, \"activeWorkers\", -1)\n\n\n## Allows extraction of the user from currently active sessions. This should be cached in front of the database\ndef querySession(token, query):\n if query not in [\"username\", \"starttime\", \"accesslevel\", \"issuedTasks\"]:\n return (False, 0)\n \n if token not in sessions:\n return (False, 0)\n \n return (True, sessions[token][query])\n \n# Deletes the session\ndef deleteSession(data, kind):\n if kind == \"token\":\n if data not in sessions:\n return False\n else:\n del sessions[data]\n return True\n elif kind == \"username\":\n result = False\n for i, (token, sesh) in enumerate(sessions.items()):\n # If the user curently has an active session, destroy the session\n if sesh[\"username\"] == data:\n result = True\n del sessions[token]\n # Update graphs that this user is no longer active\n for pname in users[data][\"issuedTasks\"]:\n changeGraph(pname, \"activeWorkers\", -1)\n break\n\n return result\n else:\n return False\n\n## CUSTOMER METHODS ##\n# Creates a new project on behalf of customer username. The project is called pname, has\n# description pdescription, and is initialised in the database. It is given it a unique project\n# ID (pID) which is returned, along with whether the operation was successful\n\ndef createNewProject(pname, pdescription):\n if pname in projects:\n return False\n # No other project by this user has the given name\n \n projects[pname] = {\"blobs\": {}, \"blobids\": 0, \"unfinishedTasks\": [], \"description\": pdescription, \"graphing\":{\n \"standardGraphs\": {\n \"activeWorkers\": [{\"x\": getTime(), \"y\": 0}],\n \"totalWorkers\": [{\"x\": getTime(), \"y\": 0}],\n \"tasksCompleted\": [{\"x\": getTime(), \"y\": 0}],\n \"tasksFailed\": [{\"x\": getTime(), \"y\": 0}],\n \"tasksRefused\": [{\"x\": getTime(), \"y\": 0}],\n \"cpuTime\": [{\"x\": getTime(), \"y\": 0}]\n },\n \"customGraphs\": {}\n }}\n return True\n\n# Creates a new blob, and stores it along with its metadata\ndef createNewBlob(pID, blob, metadata):\n # Check that the project exists\n try:\n test = projects[pID]\n except Exception:\n return (False, 0)\n\n # Create the new blob\n p = projects[pID]\n bID = str(p[\"blobids\"])\n p[\"blobids\"] += 1\n\n p[\"blobs\"][bID] = {\"blob\": blob, \"metadata\": metadata, \"task\": False, \"finished\": False}\n\n return (True, bID)\n\n# Convert blob blobID in project pID into a task, which is stored in the list of unfinished tasks\ndef blobToTask(pID, blobID):\n try:\n test = projects[pID][\"blobs\"][blobID]\n except Exception:\n return (False, \"Failed to find blob\")\n\n\n # Test whether the blob actually is a task\n try:\n task = cbor.loads(projects[pID][\"blobs\"][blobID][\"blob\"])\n valid = True\n valid = valid and type(task[\"program\"][\"id\"]) is str\n valid = valid and type(task[\"program\"][\"size\"]) is int\n valid = valid and type(task[\"control\"]) is bytes\n \n for blob in task[\"blobs\"]:\n test = blob[\"id\"]\n valid = valid and type(blob[\"size\"]) is int\n except Exception:\n return (False, \"Blob is not a correctly formatted task\")\n\n if not valid:\n return (False, \"Blob not a valid task\")\n\n # The blob exists within the project\n projects[pID][\"blobs\"][blobID][\"task\"] = True\n \n\n # Push a copy onto the queue of \"to-do\" tasks\n projects[pID][\"unfinishedTasks\"].append(blobID)\n\n return (True, \"\")\n\n# Return a dict mapping blobs IDs to their metadata. Can optionally specity a list of blobs\n# whose metadata we'd like\ndef getBlobMetadata(pID, blobIDs):\n try:\n test = projects[pID]\n except Exception:\n return (False, \"Failed to find project\")\n\n metas = {}\n for blobID, blob in projects[pID][\"blobs\"].items():\n if blobIDs == [] or blobID in blobIDs:\n metas[blobID] = blob[\"metadata\"]\n\n return (True, metas)\n\n# Return blob blobID from project pID, along with its metadata\ndef getBlob(pID, blobID):\n try:\n b = projects[pID][\"blobs\"][blobID]\n except Exception:\n return (False, str(projects[pID][\"blobs\"][blobID]), 0)\n \n return (True, b[\"blob\"], b[\"metadata\"])\n\n# Deletes blob blobID from project pID, returns if successful\ndef deleteBlob(pID, blobID):\n try:\n b = projects[pID][\"blobs\"][blobID]\n except Exception:\n return (False, \"Could not fetch blobs\")\n\n del projects[pID][\"blobs\"][blobID]\n return (True, \"\")\n\n\n## WORKER METHODS ##\n\n# Returns a unique identifier for a task from the tasklist for the worker to get on with\ndef getTasks(pID, username, maxtasks):\n try:\n b = projects[pID]\n except Exception:\n return (False, \"Project does not exist. Projects: \" + str(projects), 0)\n\n # Test if the unfinished tasks array has been constructed\n try:\n users[username][\"issuedTasks\"][pID]\n except Exception:\n # This is a first-time active user\n changeGraph(pID, \"totalWorkers\", 1)\n users[username][\"issuedTasks\"][pID] = []\n \n\n if users[username][\"issuedTasks\"][pID] == []:\n # This is a first time user on this task\n changeGraph(pID, \"activeWorkers\", 1)\n\n # Find new tasks to be done\n taskIDs = list(map(str, np.setdiff1d(projects[pID][\"unfinishedTasks\"], users[username][\"issuedTasks\"][pID]) [:maxtasks]))\n\n #unf = projects[pID][\"unfinishedTasks\"]\n #taskID = unf.pop(0)\n #unf.append(taskID)\n\n # Find the associated blob with each task ID\n tasks = []\n for t in taskIDs:\n (succ, b, m) = getBlob(pID, t)\n if not succ:\n return (False, \"Task collection error: \" + str(b), 0)\n tasks.append(b)\n\n users[username][\"issuedTasks\"][pID] = users[username][\"issuedTasks\"][pID] + taskIDs\n\n return (True, tasks, taskIDs)\n\n# Stores the list of blobs in the database, along with the metadata\ndef sendTasks(pID, taskID, results, metadatas, username, status):\n try:\n b = projects[pID][\"blobs\"][taskID]\n except Exception:\n return (False, \"Task does not exist\")\n \n # Test that this phone completed tasks it was supposed to\n\n if not taskID in users[username][\"issuedTasks\"][pID]:\n return (False, \"Task was not scheduled. Scheduled tasks: \" + str(users[username][\"issuedTasks\"]))\n\n # If status is ok, count the task as completed\n if status == \"ok\":\n # Take the old task off the task list\n for i, bID in enumerate(projects[pID][\"unfinishedTasks\"]):\n if bID == taskID:\n del projects[pID][\"unfinishedTasks\"][i]\n break\n\n # Create all the new blobs\n for (blob, meta) in zip(results, metadatas):\n createNewBlob(pID, blob, meta)\n \n # Update graphing info\n changeGraph(pID, \"tasksCompleted\", 1)\n\n # If status is error, we can give the task back later\n elif status == \"error\":\n users[username][\"issuedTasks\"][pID].remove(taskID)\n changeGraph(pID, \"tasksFailed\", 1)\n\n # If status is refused, we will eventually give the task to someone else\n elif status == \"refused\":\n changeGraph(pID, \"tasksRefused\", 1)\n else:\n return (False, \"Invalid error code\")\n \n return (True, \"\")\n\n## GRAPHING METHODS\ndef getGraphs(pname, kind):\n if not pname in projects:\n return (False, \"Invalid project name\")\n\n return (True, projects[pname][\"graphing\"][kind])\n\n# GraphsData is of the graphsCBOR type, as documented in api.txt\ndef updateCustomGraphs(graphsData, pname):\n # Check that pname belongs to the user\n\n # Check the project exists\n if not pname in projects:\n return (False, \"Invalid project name\")\n\n # Check if graph data of the correct format\n \"\"\"\n valid = True\n for gname, gdict in graphsData.items():\n valid = valid and type(gname) is str\n\n valid = valid and type(gdict[\"description\"]) is str\n valid = valid and type(gdict[\"xlabel\"]) is str\n valid = valid and type(gdict[\"ylabel\"]) is str\n valid = valid and type(gdict[\"time\"]) is bool\n valid = valid and type(gdict[\"type\"]) is str\n\n for lname, ldict in gdict[\"keys\"].items():\n valid = valid and type(lname) is str\n \n # Test that colour is in correct format\n valid = valid and type(ldict[\"colour\"]) is str\n pattern = re.compile(\"rgb\$[0-9],[0-9],[0-9]\$\")\n valid = valid and (True if pattern.match(ldict[\"colour\"]) else False)\n\n valid = valid and type(ldict[\"line\"]) is bool\n\n # Test validity of data\n for point in ldict[\"data\"]:\n valid = valid and type(point[\"x\"]) is int\n valid = valid and type(point[\"y\"]) is int\n\n if not valid:\n return (False, \"graphsData has invalid format\")\n \"\"\"\n\n # Save the new custom graph\n projects[pname][\"graphing\"][\"customGraphs\"] = graphsData\n\n return (True, \"\")\n\n" }, { "alpha_fraction": 0.45364826917648315, "alphanum_fraction": 0.4554279148578644, "avg_line_length": 32.59239196777344, "blob_id": "b3ddccb2bbb7d95f7c4b4918e4e448b9763576df", "content_id": "91d5792e017bb9e9c57423b8e6c9c4593bcb9a65", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 6181, "license_type": "no_license", "max_line_length": 104, "num_lines": 184, "path": "/client/src/exec/idb_storage.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport {Ref, Storage} from \"./storage\";\n\ndeclare interface Entry {\n \"id\": string;\n \"size_nl_id\": string;\n \"data\": ArrayBuffer;\n}\n\nfunction idbReject(reject: (e: Error) => void): (event: Event) => void {\n return (event) => {\n const e = (event.target as IDBRequest).error;\n if(e instanceof Error) reject(e);\n reject(new err.Runtime(`Operation failed: ${e}`));\n };\n}\n\nexport default class IDBStorage implements Storage {\n private constructor(\n private readonly st: stat.Sink,\n private readonly db: IDBDatabase\n ) {\n db.onversionchange = () => {\n db.close();\n };\n }\n\n public static create(st: stat.Sink, name: string): Promise<IDBStorage> {\n return new Promise<IDBStorage>((resolve, reject) => {\n const req = indexedDB.open(name, 1);\n req.onerror = idbReject(reject);\n req.onsuccess = () => resolve(new IDBStorage(st, req.result));\n req.onblocked = () => {\n reject(new err.Runtime(\"Database in use by other process but upgrade needed\"));\n };\n req.onupgradeneeded = (ev) => {\n const db = req.result;\n\n if(ev.oldVersion < 1) {\n const store = db.createObjectStore(\"blobs\", {keyPath: \"id\"});\n store.createIndex(\"size_nl_id\", \"size_nl_id\");\n }\n };\n });\n }\n\n public static delete(name: string): Promise<void> {\n return new Promise<void>((resolve, reject) => {\n const req = indexedDB.deleteDatabase(name);\n req.onerror = idbReject(reject);\n req.onsuccess = () => resolve();\n });\n }\n\n public stop(): void {\n this.db.close();\n }\n\n public list(): Promise<Ref[]> {\n return new Promise<Ref[]>((resolve, reject) => {\n const tr = this.db.transaction([\"blobs\"], \"readonly\");\n tr.onerror = idbReject(reject);\n\n const req = tr.objectStore(\"blobs\").index(\"size_nl_id\").openKeyCursor();\n req.onerror = idbReject(reject);\n\n const res: Ref[] = [];\n req.onsuccess = (event) => {\n const cursor: IDBCursor \| undefined = req.result;\n if(!cursor) {\n resolve(res);\n return;\n }\n const k = cursor.key;\n try {\n if(typeof k !== \"string\") {\n throw new err.State(\"Invalid data in IDBStorage: size_nl_id key is not string\");\n }\n const i = k.indexOf(\"\\n\");\n if(i === -1) {\n throw new err.State(\"Invalid data in IDBStorage: size_nl_key invalid\");\n }\n const size = Number(k.slice(0, i));\n const id = k.slice(i+1);\n if(size !== Math.floor(size) \|\| size < 0 \|\| id !== cursor.primaryKey) {\n throw new err.State(\"Invalid data in IDBStorage: size_nl_key invalid\");\n }\n res.push({\n id: id,\n size: size,\n });\n } catch(e) {\n this.st.reportError(e);\n }\n try {\n cursor.continue();\n } catch(e) {\n reject(e);\n }\n };\n });\n }\n\n public get(id: string): Promise<Uint8Array> {\n return new Promise<Uint8Array>((resolve, reject) => {\n const tr = this.db.transaction([\"blobs\"], \"readonly\");\n tr.onerror = idbReject(reject);\n\n const req = tr.objectStore(\"blobs\").get(IDBKeyRange.only(id));\n req.onerror = idbReject(reject);\n\n req.onsuccess = (event) => {\n const res = req.result;\n if(res === undefined) {\n reject(new err.State(\"Blob not found\"));\n return;\n }\n const data = res[\"data\"];\n if(!(data instanceof ArrayBuffer)) {\n reject(new err.State(\"Invalid data in IDBStorage: data not ArrayBuffer\", {\n idb_invalid_data: \"\" + res[\"data\"],\n }));\n return;\n }\n resolve(new Uint8Array(data));\n };\n });\n }\n\n public set(id: string, d: Uint8Array): Promise<void> {\n return new Promise<void>((resolve, reject) => {\n const data = new ArrayBuffer(d.length);\n new Uint8Array(data).set(d);\n\n let ok = false;\n\n const tr = this.db.transaction([\"blobs\"], \"readwrite\");\n tr.onerror = idbReject(reject);\n tr.oncomplete = () => {\n if(ok) resolve();\n else reject(tr.error \|\| new err.Runtime(\"Transaction failed\"));\n };\n tr.onerror = () => {\n reject(tr.error);\n };\n\n const store = tr.objectStore(\"blobs\");\n\n const obj: Entry = {\n \"id\": id,\n \"size_nl_id\": `${data.byteLength}\\n${id}`,\n \"data\": data,\n };\n const req = store.put(obj);\n req.onerror = idbReject(reject);\n req.onsuccess = () => {\n ok = true;\n };\n });\n }\n\n public delete(id: string): Promise<void> {\n return new Promise<void>((resolve, reject) => {\n let ok = false;\n\n const tr = this.db.transaction([\"blobs\"], \"readwrite\");\n tr.onerror = idbReject(reject);\n tr.oncomplete = () => {\n if(ok) resolve();\n else reject(tr.error \|\| new err.Runtime(\"Transaction failed\"));\n };\n\n const store = tr.objectStore(\"blobs\");\n\n const req = store.delete(IDBKeyRange.only(id));\n req.onerror = idbReject(reject);\n req.onsuccess = () => {\n ok = true;\n };\n });\n }\n}\n" }, { "alpha_fraction": 0.5570470094680786, "alphanum_fraction": 0.5626987218856812, "avg_line_length": 30.455554962158203, "blob_id": "8f804ab19def7e2a38781cb2c804d1c4438dc2e4", "content_id": "c8f27055191c1b38b0b988faef0223888922e8d0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 2831, "license_type": "no_license", "max_line_length": 94, "num_lines": 90, "path": "/client/src/exec/tests/runner.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport MemStorage from \"../mem_storage\";\nimport MockAPI from \"../mock_api\";\nimport * as tb from \"../test-blobs\";\nimport {arrBuf, compare, runTests, withRunner} from \"../test-util\";\n\n// import * as api from \"../api\";\n\nfunction wait(ms: number): Promise<void> {\n return new Promise((resolve,reject) => self.setTimeout(() => resolve(), ms));\n}\n\nfunction testStartStop(): Promise<void> {\n const the_api = new MockAPI(null);\n const the_storage = new MemStorage();\n return withRunner(the_api, the_storage, (runner) => {\n return wait(1000);\n }).then(() => {\n if(the_api.req_cnt_blob.value !== 0) throw new Error(\"Unexpected blob request\");\n if(the_api.req_cnt_results.value !== 0) throw new Error(\"Unexpected results request\");\n });\n}\n\nfunction testRun(): Promise<void> {\n const the_api = new MockAPI(null);\n the_api.blobs.set(\"prog-echo\", tb.prog_echo);\n the_api.blobs.set(\"prog-abort\", tb.prog_abort);\n the_api.blobs.set(\"hw\", tb.hello_world);\n\n const want_results = new Map<string, any>();\n\n const blob_echo = the_api.blob(\"prog-echo\");\n const blob_abort = the_api.blob(\"prog-abort\");\n const blob_hw = the_api.blob(\"hw\");\n\n the_api.tasks.enqueue({\n id: \"echo\", project: \"\", program: blob_echo,\n in_control: tb.hello_world, in_blobs: [],\n });\n want_results.set(\"echo\", {\n id: \"echo\", status: \"ok\",\n data: [],\n });\n\n the_api.tasks.enqueue({\n id: \"echo-blobs\", project: \"\", program: blob_echo,\n in_control: arrBuf([42]), in_blobs: [blob_hw, blob_hw],\n });\n want_results.set(\"echo-blobs\", {\n id: \"echo-blobs\", status: \"ok\",\n data: [tb.hello_world, tb.hello_world],\n });\n\n the_api.tasks.enqueue({\n id: \"abort\", project: \"\", program: blob_abort,\n in_control: arrBuf([42]), in_blobs: [blob_hw, blob_hw, blob_echo],\n });\n want_results.set(\"abort\", {\n id: \"abort\", status: \"error\",\n error: {\n \"kind\": \"runtime\",\n \"message\": \"Program abort()\",\n \"@compare@ignore\": true,\n },\n });\n\n const the_storage = new MemStorage();\n\n return withRunner(the_api, the_storage, (runner) => {\n return Promise.race([\n the_api.addCondition(() => {\n return the_api.total_task_cnt >= want_results.size;\n }).then(() => true),\n wait(5000).then(() => false),\n ]);\n }).then((ok) => {\n if(!ok) throw new Error(\"Timed out\");\n if(the_api.req_cnt_results.value === 0) throw new Error(\"Expected results\");\n if(the_api.task_dup_cnt.value !== 0) throw new Error(\"Duplicated task results\");\n compare(the_api.results, want_results, \"\");\n });\n}\n\nself.onload = () => {\n runTests([\n testStartStop,\n testRun,\n ]);\n};\n" }, { "alpha_fraction": 0.5251339673995972, "alphanum_fraction": 0.5338096618652344, "avg_line_length": 30.103174209594727, "blob_id": "159fe0edcad0ff7587761439ef8c1ea34d14fc9d", "content_id": "685e0977fc90aeddbed9bb90102daaedb29eca1d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 3919, "license_type": "no_license", "max_line_length": 99, "num_lines": 126, "path": "/client/src/exec/mock_api.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import Deque from \"double-ended-queue\";\n\nimport * as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport * as api from \"./api\";\n\nexport default class MockAPI implements api.WorkProvider {\n public readonly req_cnt_blob = new stat.Counter(\n \"MockAPI/requests\", {\"type\": \"getBlob\"}\n ).attach(this.st);\n public readonly req_cnt_tasks = new stat.Counter(\n \"MockAPI/requests\", {\"type\": \"requestTasks\"}\n ).attach(this.st);\n public readonly req_cnt_results = new stat.Counter(\n \"MockAPI/requests\", {\"type\": \"sendResults\"}\n ).attach(this.st);\n public readonly task_cnt_ok = new stat.Counter(\n \"MockAPI/results\", {\"status\": \"ok\"}\n ).attach(this.st);\n public readonly task_cnt_error = new stat.Counter(\n \"MockAPI/results\", {\"status\": \"error\"}\n ).attach(this.st);\n public readonly task_cnt_refused = new stat.Counter(\n \"MockAPI/results\", {\"status\": \"refused\"}\n ).attach(this.st);\n public readonly task_dup_cnt = new stat.Counter(\n \"MockAPI/results_dup\"\n ).attach(this.st);\n\n public readonly blobs = new Map<string, Uint8Array>();\n public readonly tasks = new Deque<api.Task>();\n public readonly results = new Map<string, api.TaskResult>();\n\n private readonly conditions: Array<[() => boolean, () => void]> = [];\n\n public tasks_pending_min = 100;\n public tasks_finished_max = 1000;\n public send_max_bytes = 16384;\n public save_timeout = 1000;\n public cache_max = 1.0e6;\n\n constructor(\n public readonly st: stat.Sink \| null\n ) {}\n\n get total_task_cnt(): number {\n return this.task_cnt_ok.value! + this.task_cnt_error.value! + this.task_cnt_refused.value!;\n }\n\n public blob(id: string): api.BlobRef {\n return {id: id, size: this.blobs.get(id)!.byteLength};\n }\n\n public report() {\n const cond = this.conditions;\n let i = 0, j = 0;\n for(; i < cond.length; i += 1) {\n const t = cond[i];\n if(t[0]()) {\n t[1]();\n } else {\n if(i !== j) cond[j] = t;\n j += 1;\n }\n }\n cond.splice(j);\n }\n\n public addCondition(test: () => boolean): Promise<void> {\n return new Promise((resolve, reject) => {\n this.conditions.push([test, resolve]);\n });\n }\n\n public getBlob(id: string, expected_size: number): Promise<Uint8Array> {\n return new Promise((resolve, reject) => {\n const data = this.blobs.get(id);\n if(data) resolve(data.slice(0));\n else reject(new err.State(\"Unknown blob\", {blob_id: id}));\n this.req_cnt_blob.inc();\n });\n }\n\n public getTasks(): Promise<api.TaskSet> {\n if(this.tasks.isEmpty()) {\n return new Promise((resolve, reject) => {\n self.setTimeout(() => resolve({\n tasks: [],\n }), 500 * Math.random());\n });\n }\n\n const r = Math.floor(200 * Math.random());\n const ts: api.Task[] = [];\n while(ts.length < r) {\n const t = this.tasks.dequeue();\n if(!t) break;\n ts.push(t);\n }\n this.req_cnt_results.inc();\n this.report();\n return Promise.resolve({\n tasks: ts,\n });\n }\n\n public sendTasks(outs: api.TaskResult[]): Promise<void> {\n for(const out of outs) {\n if(this.results.get(out.id) !== undefined) {\n this.task_dup_cnt.inc();\n continue;\n }\n this.results.set(out.id, out);\n\n console.log(out);\n\n if(out.status === \"ok\") this.task_cnt_ok.inc();\n else if(out.status === \"refused\") this.task_cnt_refused.inc();\n else this.task_cnt_error.inc();\n }\n this.req_cnt_results.inc();\n this.report();\n return Promise.resolve();\n }\n}\n" }, { "alpha_fraction": 0.47570741176605225, "alphanum_fraction": 0.47677522897720337, "avg_line_length": 25.757143020629883, "blob_id": "9200eda44e6d911f149726af926d1185bdb9e18e", "content_id": "f1f6f427bf9e033fd09e8f982aed0a85eb849255", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 1873, "license_type": "no_license", "max_line_length": 75, "num_lines": 70, "path": "/client/src/worker/worker.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport * as workapi from \"@/exec/workapi\";\n\nimport Executor from \"./exec\";\n\nconst blobs_waiting = new Map<string, Array<(data: Uint8Array) => void>>();\n\nclass WorkerExecutor extends Executor {\n public readBlob(blob: workapi.Ref): Promise<Uint8Array> {\n let arr = blobs_waiting.get(blob.id);\n if(!arr) {\n arr = [];\n blobs_waiting.set(blob.id, arr);\n sendControl({get_blob: blob});\n }\n return new Promise((resolve, reject) => {\n arr!.push((data) => {\n if(data.byteLength === blob.size) {\n resolve(data);\n } else {\n reject(new Error(\"Blob size mismatch\"));\n }\n });\n });\n }\n\n public onPrint(msg: string) {\n console.log(msg);\n }\n\n public onStarted(): void {\n sendControl({notify_started: null});\n }\n}\n\nconst r = new WorkerExecutor();\n\nonmessage = (msg) => {\n const data = msg.data as workapi.In;\n if(data.work) {\n r.run(data.work).then((d) => {\n return {result: d};\n }, (e) => {\n return {error: {\n \"kind\": \"runtime\",\n \"message\": e.message,\n \"stack\": e.stack,\n }};\n }).then((out: workapi.Out) => {\n postMessage(out, undefined);\n });\n } else if(data.control) {\n const ctl = data.control;\n if(ctl.get_blob !== undefined) {\n const [blob_id, blob_data] = ctl.get_blob;\n const cbs = blobs_waiting.get(blob_id);\n if(cbs) {\n blobs_waiting.delete(blob_id);\n for(const cb of cbs) {\n cb(blob_data);\n }\n }\n }\n }\n};\n\nfunction sendControl(ctl: workapi.OutControl): void {\n postMessage({control: ctl});\n}\n" }, { "alpha_fraction": 0.5052770376205444, "alphanum_fraction": 0.5052770376205444, "avg_line_length": 21.969696044921875, "blob_id": "4dd14b1df8b8c070f9d7ca28e47f42017c9c38ed", "content_id": "5639070b7c14a20ab6d833e72560c1e7837b2d88", "detected_licenses": [], "is_generated": false, "is_vendor": true, "language": "TypeScript", "length_bytes": 758, "license_type": "no_license", "max_line_length": 50, "num_lines": 33, "path": "/client/types/double-ended-queue.d.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "declare module \"double-ended-queue\" {\n export default class Deque<T> {\n constructor(capacity?: number \| Array<T>);\n\n push(...data: T[]): void;\n enqueue(...data: T[]): void;\n insertBack(...data: T[]): void;\n\n unshift(...data: T[]): void;\n insertFront(...data: T[]): void;\n\n pop(): T \| undefined;\n removeBack(): T \| undefined;\n\n shift(): T \| undefined;\n dequeue(): T \| undefined;\n removeFront(): T \| undefined;\n\n toArray(): Array<T>;\n toJSON(): Array<T>;\n\n peekBack(): T \| undefined;\n\n peekFront(): T \| undefined;\n\n get(index: number): T \| undefined;\n\n readonly length: number;\n isEmpty(): boolean;\n\n clear(): void;\n }\n}\n" }, { "alpha_fraction": 0.5065741539001465, "alphanum_fraction": 0.5247874855995178, "avg_line_length": 28.057458877563477, "blob_id": "2d0e53c35bab66ae35a9f63665e539c49379f965", "content_id": "66e7fa03e630f4c404cf68ae7cc9e815c8e44f47", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 28825, "license_type": "no_license", "max_line_length": 104, "num_lines": 992, "path": "/client/src/cbor.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "export enum Kind {\n UINT = 0,\n NEGATIVE_INT = 1,\n BYTES = 2,\n STRING = 3,\n ARRAY = 4,\n MAP = 5,\n SEMANTIC_TAG = 6,\n SIMPLE = 7,\n FLOAT = 8,\n BREAK = 9,\n}\n\nconst kinds = [\n \"non-negative integer\",\n \"negative integer\",\n \"byte string\",\n \"text string\",\n \"array\",\n \"map\",\n \"semantic tag\",\n \"simple value\",\n \"floating-point number\",\n \"break code\",\n];\n\ndeclare const TextEncoder: any;\ndeclare const TextDecoder: any;\ndeclare const console: any;\n\nconst TAG_UINT = 0x00;\nconst TAG_UINT_END = 0x20;\nconst TAG_NINT = 0x20;\nconst TAG_NINT_END = 0x40;\nconst TAG_BYTES = 0x40;\nconst TAG_BYTES_EXT = 0x5f;\nconst TAG_BYTES_END = 0x60;\nconst TAG_STRING = 0x60;\nconst TAG_STRING_EXT = 0x7f;\nconst TAG_STRING_END = 0x80;\nconst TAG_ARRAY = 0x80;\nconst TAG_ARRAY_EXT = 0x9f;\nconst TAG_ARRAY_END = 0xa0;\nconst TAG_MAP = 0xa0;\nconst TAG_MAP_EXT = 0xbf;\nconst TAG_MAP_END = 0xc0;\nconst TAG_SEMANTIC = 0xc0;\nconst TAG_SEMANTIC_END = 0xe0;\nconst TAG_SIMPLE = 0xe0;\nconst TAG_SIMPLE_EXT = 0xe0 + 24;\nconst TAG_FLOAT16 = 0xe0 + 25;\nconst TAG_FLOAT32 = 0xe0 + 26;\nconst TAG_FLOAT64 = 0xe0 + 27;\nconst TAG_BREAK = 0xff;\n\nexport const SIMPLE_FALSE = 20;\nexport const SIMPLE_TRUE = 21;\nexport const SIMPLE_NULL = 22;\nexport const SIMPLE_UNDEFINED = 23;\n\nfunction isUint(tag: number): boolean {\n return TAG_UINT <= tag && tag < TAG_UINT_END;\n}\nfunction isNint(tag: number): boolean {\n return TAG_NINT <= tag && tag < TAG_NINT_END;\n}\nfunction isInt(tag: number): boolean {\n return TAG_UINT <= tag && tag < TAG_NINT_END;\n}\nfunction isBytes(tag: number): boolean {\n return TAG_BYTES <= tag && tag < TAG_BYTES_END;\n}\nfunction isString(tag: number): boolean {\n return TAG_STRING <= tag && tag < TAG_STRING_END;\n}\nfunction isArray(tag: number): boolean {\n return TAG_ARRAY <= tag && tag < TAG_ARRAY_END;\n}\nfunction isMap(tag: number): boolean {\n return TAG_MAP <= tag && tag < TAG_MAP_END;\n}\nfunction isSemanticTag(tag: number): boolean {\n return TAG_SEMANTIC <= tag && tag < TAG_SEMANTIC_END;\n}\nfunction isSimple(tag: number): boolean {\n return TAG_SIMPLE <= tag && tag <= TAG_SIMPLE_EXT;\n}\nfunction isFloat(tag: number): boolean {\n return tag === TAG_FLOAT16 \|\| tag === TAG_FLOAT32 \|\| tag === TAG_FLOAT64;\n}\nfunction isBreak(tag: number): boolean {\n return tag === TAG_BREAK;\n}\n\nfunction kindof(tag: number): Kind {\n if(isUint(tag)) return Kind.UINT;\n if(isNint(tag)) return Kind.NEGATIVE_INT;\n if(isBytes(tag)) return Kind.BYTES;\n if(isString(tag)) return Kind.STRING;\n if(isArray(tag)) return Kind.ARRAY;\n if(isMap(tag)) return Kind.MAP;\n if(isSemanticTag(tag)) return Kind.SEMANTIC_TAG;\n if(isSimple(tag)) return Kind.SIMPLE;\n if(isFloat(tag)) return Kind.FLOAT;\n if(isBreak(tag)) return Kind.BREAK;\n throw new TypeError(\"Unsupported encoding\");\n}\n\nconst deutf8 = (() => {\n if(typeof TextDecoder !== \"undefined\") {\n const the_decoder = new TextDecoder(\"utf-8\", {fatal: true});\n return (data: Uint8Array): string => the_decoder.decode(data);\n } else {\n return (data: Uint8Array): string => {\n if(data.every((v) => v < 128)) return String.fromCodePoint(...data);\n throw new TypeError(\"UTF-8 decoder not available\");\n };\n }\n})();\n\nconst enutf8 = (() => {\n if(typeof TextEncoder !== \"undefined\") {\n const the_encoder = new TextEncoder();\n return (data: string): Uint8Array => the_encoder.encode(data);\n } else {\n return (data: string): Uint8Array => {\n const l = data.length;\n const res = new Uint8Array(l);\n for(let i = 0; i < l; i += 1) {\n const cc = data.charCodeAt(i);\n if(cc >= 128) throw new TypeError(\"UTF-8 encoder not available\");\n res[i] = cc;\n }\n return res;\n };\n }\n})();\n\nconst enum StackKind {\n OBJECT = 0,\n ARRAY = 1,\n MAP = 2,\n}\n\nconst msg_end = [\n \"Data already read\",\n \"Attempting to read past end of array\",\n \"Attempting to read past end of map\",\n];\n\nconst msg_more = [\n \"Can't close main object\",\n \"Attempted to close array with data remaining\",\n \"Attempted to close map with data remaining\",\n];\n\nclass Stack {\n public readonly par: Stack \| null;\n public readonly len: number \| undefined;\n public readonly kind: StackKind;\n public index: number;\n public map_mid: boolean = false;\n\n constructor(par: Stack \| null, kind: StackKind, len: number \| undefined) {\n this.par = par;\n this.len = len;\n this.kind = kind;\n this.index = 0;\n }\n\n public canAdvance(): boolean {\n return this.len === undefined \|\| this.index < this.len;\n }\n\n public advance() {\n console.assert(this.canAdvance());\n if(this.kind === StackKind.MAP) {\n if(!this.map_mid) {\n this.map_mid = true;\n return;\n }\n this.map_mid = false;\n }\n this.index += 1;\n }\n}\n\nexport class Iterator {\n public readonly at: number;\n public readonly top: Stack;\n public readonly i: number[];\n\n constructor(at: number, top: Stack, i: number[]) {\n this.at = at;\n this.top = top;\n this.i = i;\n }\n}\n\nexport class Reader {\n private data: DataView;\n private at: number;\n private top: Stack;\n\n constructor(data: ArrayBuffer \| Uint8Array) {\n if(data instanceof ArrayBuffer) {\n this.data = new DataView(data);\n } else {\n this.data = new DataView(data.buffer, data.byteOffset, data.byteLength);\n }\n this.at = 0;\n this.top = new Stack(null, StackKind.OBJECT, 1);\n }\n\n private _rTag(): number {\n const tag = this.data.getUint8(this.at);\n this.at += 1;\n return tag;\n }\n\n private _peekTag(): number {\n return this.data.getUint8(this.at);\n }\n\n private _skipUint(tag: number): void {\n if(tag < 24) return;\n if(tag === 24) {\n this.at += 1;\n } else if(tag === 25) {\n this.at += 2;\n } else if(tag === 26) {\n this.at += 4;\n } else if(tag === 27) {\n this.at += 8;\n } else {\n throw new TypeError(\"Unsupported encoding\");\n }\n }\n\n private _rUint(tag: number): number {\n if(tag < 24) return tag;\n if(tag === 24) {\n const v = this.data.getUint8(this.at);\n this.at += 1;\n return v;\n } else if(tag === 25) {\n const v = this.data.getUint16(this.at);\n this.at += 2;\n return v;\n } else if(tag === 26) {\n const v = this.data.getUint32(this.at);\n this.at += 4;\n return v;\n } else if(tag === 27) {\n let v = this.data.getUint32(this.at);\n if(v > 2097152) {\n throw new TypeError(\"Integer out of JavaScript range\");\n }\n v = 4294967296;\n v += this.data.getUint32(this.at + 4);\n this.at += 8;\n return v;\n } else {\n throw new TypeError(\"Unsupported encoding\");\n }\n }\n\n private _rDataTag(): number {\n let tag = this._rTag();\n if(tag < TAG_SEMANTIC \|\| tag >= TAG_SEMANTIC_END) return tag;\n this._skipUint(tag - TAG_SEMANTIC);\n tag = this._rTag();\n if(tag < TAG_SEMANTIC \|\| tag >= TAG_SEMANTIC_END) throw new TypeError(\"Multiple semantic tags\");\n return tag;\n }\n\n private _peekDataTag(): number {\n let tag = this._peekTag();\n if(tag < TAG_SEMANTIC \|\| tag >= TAG_SEMANTIC_END) return tag;\n const at = this.at;\n this.at = at + 1;\n this._skipUint(tag);\n tag = this._peekTag();\n this.at = at;\n if(tag < TAG_SEMANTIC \|\| tag >= TAG_SEMANTIC_END) throw new TypeError(\"Multiple semantic tags\");\n return tag;\n }\n\n private _rBytes1(tag: number): Uint8Array {\n const len = this._rUint(tag);\n const r = new Uint8Array(this.data.buffer, this.data.byteOffset + this.at, len);\n this.at += len;\n return r;\n }\n\n private _rBytesv(tag_base: number, tag: number): Uint8Array[] {\n const s: Uint8Array[] = [];\n while(true) {\n const t2 = this.data.getUint8(this.at);\n if(t2 === TAG_BREAK) break;\n if(t2 < tag_base \|\| t2 >= tag_base + 31) throw new TypeError(\"Invalid encoding\");\n const b = this._rBytes1(tag - tag_base);\n if(b.byteLength !== 0) s.push(b);\n }\n return s;\n }\n\n private _skipBytes(tag_base: number, tag: number): void {\n if(tag !== tag_base + 31) {\n this.at += this._rUint(tag - tag_base);\n return;\n }\n while(true) {\n const t2 = this.data.getUint8(this.at);\n if(t2 === TAG_BREAK) break;\n if(t2 < tag_base \|\| t2 >= tag_base + 31) throw new TypeError(\"Invalid encoding\");\n this.at += this._rUint(tag - tag_base);\n }\n }\n\n private _unknown(tag: number, expected: string): never {\n const kind = kindof(tag);\n let got: string = kinds[kind];\n if(kind === Kind.SIMPLE) {\n if(tag === TAG_SIMPLE + SIMPLE_TRUE \|\| tag === TAG_SIMPLE + SIMPLE_TRUE) got = \"boolean\";\n else if(tag === TAG_SIMPLE + SIMPLE_NULL) got = \"null\";\n else if(tag === TAG_SIMPLE + SIMPLE_UNDEFINED) got = \"undefined\";\n }\n throw new TypeError(`Unexpected ${got}, wanted ${expected}`);\n }\n\n private _semanticTag(tag: number): number {\n if(isSemanticTag(tag)) return this._rUint(tag - TAG_SEMANTIC);\n return this._unknown(tag, \"semantic tag\");\n }\n\n private _int(tag: number): number {\n if(isUint(tag)) return this._rUint(tag - TAG_UINT);\n if(isNint(tag)) {\n const v = this._rUint(tag - TAG_NINT);\n if(v === 9007199254740992) {\n throw new TypeError(\"Integer out of JavaScript range\");\n }\n return -1 - v;\n }\n return this._unknown(tag, \"integer\");\n }\n\n private _uint(tag: number): number {\n if(isUint(tag)) return this._rUint(tag - TAG_UINT);\n return this._unknown(tag, \"non-negative integer\");\n }\n\n private _bytes(tag: number): Uint8Array {\n if(!isBytes(tag)) return this._unknown(tag, \"byte string\");\n if(tag !== TAG_BYTES_EXT) {\n return this._rBytes1(tag - TAG_BYTES);\n }\n const s = this._rBytesv(TAG_BYTES, tag);\n if(s.length === 0) return new Uint8Array();\n if(s.length === 1) return s[0];\n let l = 0;\n for(const b of s) l += b.byteLength;\n const r = new Uint8Array(l);\n let at = 0;\n for(const b of s) {\n r.set(b, at);\n at += b.byteLength;\n }\n console.assert(at === l);\n return r;\n }\n\n private _string(tag: number): string {\n if(!isString(tag)) return this._unknown(tag, \"text string\");\n if(tag !== TAG_STRING_EXT) {\n return deutf8(this._rBytes1(tag - TAG_STRING));\n }\n return this._rBytesv(TAG_STRING, tag).map(deutf8).join(\"\");\n }\n\n private _array(tag: number): number \| undefined {\n if(!isArray(tag)) return this._unknown(tag, \"array\");\n let len: number \| undefined;\n if(tag === TAG_ARRAY_EXT) len = undefined;\n else len = this._rUint(tag - TAG_ARRAY);\n this.top = new Stack(this.top, StackKind.ARRAY, len);\n return len;\n }\n\n private _map(tag: number): number \| undefined {\n if(!isMap(tag)) return this._unknown(tag, \"map\");\n let len: number \| undefined;\n if(tag === TAG_MAP_EXT) len = undefined;\n else len = this._rUint(tag - TAG_MAP);\n this.top = new Stack(this.top, StackKind.MAP, len);\n return len;\n }\n\n private _simple(tag: number): number {\n if(TAG_SIMPLE < tag && tag < TAG_SIMPLE_EXT) return tag - TAG_SIMPLE;\n if(tag === TAG_SIMPLE_EXT) return this._rTag();\n return this._unknown(tag, \"simple value\");\n }\n\n private _boolean(tag: number) {\n const simp = this._simple(tag);\n if(simp === SIMPLE_FALSE) return false;\n if(simp === SIMPLE_TRUE) return true;\n return this._unknown(tag, \"boolean\");\n }\n\n private _null(tag: number): void {\n const simp = this._simple(tag);\n if(simp === SIMPLE_NULL) return;\n this._unknown(tag, \"null\");\n }\n\n private _undefined(tag: number): void {\n const simp = this._simple(tag);\n if(simp === SIMPLE_UNDEFINED) return;\n this._unknown(tag, \"undefined\");\n }\n\n private _float(tag: number) {\n let r: number;\n if(tag === TAG_FLOAT16) {\n const w = this.data.getUint16(this.at);\n this.at += 2;\n\n const exp = (w >> 10) & 31;\n const mantissa = w & 1023;\n\n if(exp === 31) {\n if(mantissa !== 0) return NaN;\n r = Infinity;\n } else if(exp !== 0) {\n r = (1024 + mantissa) Math.pow(2, exp - 25);\n } else {\n r = mantissa * Math.pow(2, -24);\n }\n\n if(w & 32768) r = -r;\n } else if(tag === TAG_FLOAT32) {\n r = this.data.getFloat32(this.at);\n this.at += 4;\n } else if(tag === TAG_FLOAT64) {\n r = this.data.getFloat64(this.at);\n this.at += 8;\n } else {\n return this._unknown(tag, \"floating-point number\");\n }\n return r;\n }\n\n private _number(tag: number) {\n if(isInt(tag)) return this._int(tag);\n if(isFloat(tag)) return this._float(tag);\n return this._unknown(tag, \"number\");\n }\n\n private _checkMaybeData(): boolean {\n const t = this.top;\n if(t.len !== undefined) {\n return t.index !== t.len;\n }\n if(t.map_mid) return true;\n return this._peekTag() !== TAG_BREAK;\n }\n\n private _checkData(): void {\n if(!this._checkMaybeData()) {\n throw new TypeError(msg_end[this.top.kind]);\n }\n }\n\n private _onMaybeData(): boolean {\n if(!this._checkMaybeData()) return false;\n this.top.advance();\n return true;\n }\n\n private _onData(): void {\n if(!this._onMaybeData()) {\n throw new TypeError(msg_end[this.top.kind]);\n }\n }\n\n public tell(): Iterator {\n const i: number[] = [];\n for(let t: Stack \| null = this.top; t !== null; t = t.par) {\n if(t.kind === StackKind.MAP) i.push(2 * t.index + (t.map_mid ? 1 : 0));\n else i.push(t.index);\n }\n return new Iterator(this.at, this.top, i);\n }\n\n public seek(it: Iterator) {\n this.at = it.at;\n let t: Stack \| null = it.top;\n this.top = t!;\n for(const i of it.i) {\n if(t!.kind === StackKind.MAP) {\n t!.index = Math.floor(i / 2);\n t!.map_mid = (i % 2 === 1);\n } else {\n t!.index = i;\n }\n t = t!.par;\n }\n console.assert(t === null);\n }\n\n public hasNext(): boolean {\n return this._checkMaybeData();\n }\n\n public get index(): number {\n return this.top.index;\n }\n\n public get length(): number \| undefined {\n return this.top.len;\n }\n\n public end(): void {\n const t = this.top;\n if(\n t.kind !== StackKind.OBJECT &&\n (t.len !== undefined) ? (t.index === t.len) : (this._rTag() === TAG_BREAK)\n ) {\n this.top = t.par!;\n return;\n }\n throw new TypeError(msg_more[t.kind]);\n }\n\n public peekDataKind(): Kind {\n this._checkData();\n return kindof(this._peekDataTag());\n }\n\n public hasSemanticTag(): boolean {\n return isSemanticTag(this._peekTag());\n }\n\n public isInt(): boolean {\n this._checkData();\n return isInt(this._peekDataTag());\n }\n\n public isUint(): boolean {\n this._checkData();\n return isUint(this._peekDataTag());\n }\n\n public isBytes(): boolean {\n this._checkData();\n return isBytes(this._peekDataTag());\n }\n\n public isString(): boolean {\n this._checkData();\n return isString(this._peekDataTag());\n }\n\n public isArray(): boolean {\n this._checkData();\n return isArray(this._peekDataTag());\n }\n\n public isMap(): boolean {\n this._checkData();\n return isMap(this._peekDataTag());\n }\n\n public isSimple(): boolean {\n this._checkData();\n return isSimple(this._peekDataTag());\n }\n\n public isFloat(): boolean {\n this._checkData();\n return isFloat(this._peekDataTag());\n }\n\n public isNumber(): boolean {\n this._checkData();\n const t = this._peekDataTag();\n return isInt(t) \|\| isFloat(t);\n }\n\n public uint(): number {\n this._onData();\n return this._uint(this._rDataTag());\n }\n\n public int(): number {\n this._onData();\n return this._int(this._rDataTag());\n }\n\n public bytes(): Uint8Array {\n this._onData();\n return this._bytes(this._rDataTag());\n }\n\n public string(): string {\n this._onData();\n return this._string(this._rDataTag());\n }\n\n public array(): number \| undefined {\n this._onData();\n return this._array(this._rDataTag());\n }\n\n public map(): number \| undefined {\n this._onData();\n return this._map(this._rDataTag());\n }\n\n public simple(): number {\n this._onData();\n return this._simple(this._rDataTag());\n }\n\n public boolean(): boolean {\n this._onData();\n return this._boolean(this._rDataTag());\n }\n\n public null(): void {\n this._onData();\n this._null(this._rDataTag());\n }\n\n public undefined(): void {\n this._onData();\n this._undefined(this._rDataTag());\n }\n\n public number(): number {\n this._onData();\n return this._number(this._rDataTag());\n }\n\n public skip(): void {\n this._onData();\n const tag = this._rDataTag();\n if(isUint(tag)) this._skipUint(tag - TAG_UINT);\n else if(isNint(tag)) this._skipUint(tag - TAG_NINT);\n else if(isBytes(tag)) this._skipBytes(TAG_BYTES, tag);\n else if(isString(tag)) this._skipBytes(TAG_STRING, tag);\n else if(isArray(tag)) {\n this._array(tag);\n while(this.hasNext()) this.skip();\n this.end();\n } else if(isMap(tag)) {\n this._map(tag);\n while(this.hasNext()) {\n this.skip();\n this.skip();\n }\n this.end();\n } else if(isSimple(tag)) {\n if(tag === TAG_SIMPLE_EXT) this.at += 1;\n } else if(isFloat(tag)) {\n if(tag === TAG_FLOAT16) this.at += 2;\n else if(tag === TAG_FLOAT32) this.at += 4;\n else if(tag === TAG_FLOAT64) this.at += 8;\n else console.assert(false);\n } else {\n this._unknown(tag, \"any value\");\n }\n }\n\n public semanticTag(): number \| undefined {\n this._checkData();\n const tag = this._peekTag();\n if(!isSemanticTag(tag)) return undefined;\n this.at += 1;\n return this._semanticTag(tag);\n }\n\n public maybeUint(): null \| number {\n if(!this._onMaybeData()) return null;\n return this._uint(this._rDataTag());\n }\n\n public maybeInt(): null \| number {\n if(!this._onMaybeData()) return null;\n return this._int(this._rDataTag());\n }\n\n public maybeBytes(): null \| Uint8Array {\n if(!this._onMaybeData()) return null;\n return this._bytes(this._rDataTag());\n }\n\n public maybeString(): null \| string {\n if(!this._onMaybeData()) return null;\n return this._string(this._rDataTag());\n }\n\n public maybeArray(): null \| number \| undefined {\n if(!this._onMaybeData()) return null;\n return this._array(this._rDataTag());\n }\n\n public maybeMap(): null \| number \| undefined {\n if(!this._onMaybeData()) return null;\n return this._map(this._rDataTag());\n }\n\n public maybeSimple(): null \| number {\n if(!this._onMaybeData()) return null;\n return this._simple(this._rDataTag());\n }\n\n public maybeBoolean(): null \| boolean {\n if(!this._onMaybeData()) return null;\n return this._boolean(this._rDataTag());\n }\n\n public maybeNull(): null \| true {\n if(!this._onMaybeData()) return null;\n this._null(this._rDataTag());\n return true;\n }\n\n public maybeUndefined(): null \| true {\n if(!this._onMaybeData()) return null;\n this._undefined(this._rDataTag());\n return true;\n }\n\n public maybeNumber(): null \| number {\n if(!this._onMaybeData()) return null;\n return this._number(this._rDataTag());\n }\n\n public maybeSemanticTag(): null \| number \| undefined {\n if(!this._onMaybeData()) return null;\n const tag = this._peekTag();\n if(!isSemanticTag(tag)) return undefined;\n this.at += 1;\n return this._semanticTag(tag);\n }\n}\n\nexport class Writer {\n private readonly max_length: number \| undefined;\n private top: Stack \| null;\n private buf: ArrayBuffer;\n private data: DataView;\n private at: number;\n\n constructor(max_length?: number) {\n this.max_length = max_length;\n this.top = new Stack(null, StackKind.OBJECT, 1);\n\n this.buf = new ArrayBuffer(256);\n this.data = new DataView(this.buf);\n this.at = 0;\n }\n\n private _reserve(l: number) {\n const bl = this.buf.byteLength;\n l += this.at;\n if(l > bl) {\n if(this.max_length !== undefined && l > this.max_length) {\n throw new TypeError(\"Size limit exceeded\");\n }\n const t = bl + (bl >>> 2);\n if(t > l) l = t;\n if(this.max_length !== undefined && l > this.max_length) {\n l = this.max_length;\n }\n const buf2 = new ArrayBuffer(l);\n new Uint8Array(buf2, 0, bl).set(new Uint8Array(this.buf));\n this.buf = buf2;\n this.data = new DataView(buf2);\n }\n }\n\n private _uint(tag_base: number, val: number) {\n if(val < 0 \|\| val !== Math.floor(val)) {\n throw new TypeError(\"Cannot store number\");\n } else if(val < 24) {\n this._reserve(1);\n this.data.setUint8(this.at, tag_base + val);\n this.at += 1;\n } else if(val < 256) {\n this._reserve(2);\n this.data.setUint8(this.at, tag_base + 24);\n this.data.setUint8(this.at + 1, val);\n this.at += 2;\n } else if(val < 65536) {\n this._reserve(3);\n this.data.setUint8(this.at, tag_base + 25);\n this.data.setUint16(this.at + 1, val);\n this.at += 3;\n } else if(val < 4294967296) {\n this._reserve(5);\n this.data.setUint8(this.at, tag_base + 26);\n this.data.setUint32(this.at + 1, val);\n this.at += 5;\n } else if(val < 18446744073709551616) {\n this._reserve(9);\n this.data.setUint8(this.at, tag_base + 27);\n this.data.setUint32(this.at + 1, val / 4294967296);\n this.data.setUint32(this.at + 5, val % 4294967296);\n this.at += 9;\n } else {\n throw new TypeError(\"Cannot store number\");\n }\n }\n\n private _indef(tag_base: number) {\n this._reserve(1);\n this.data.setUint8(this.at, tag_base + 31);\n this.at += 1;\n }\n\n private _bytes(tag_base: number, val: Uint8Array) {\n const l = val.length;\n this._uint(tag_base, l);\n this._reserve(l);\n new Uint8Array(this.buf, this.at, l).set(val);\n this.at += l;\n }\n\n private _simple(val: number) {\n if(val < 0 \|\| val !== Math.floor(val) \|\| val >= 256 \|\| (val >= 24 && val < 32)) {\n throw new TypeError(\"Invalid simple value\");\n }\n if(val < 24) {\n this._reserve(1);\n this.data.setUint8(this.at, TAG_SIMPLE + val);\n this.at += 1;\n } else {\n this._reserve(2);\n this.data.setUint8(this.at, TAG_SIMPLE_EXT);\n this.data.setUint8(this.at + 1, val);\n this.at += 2;\n }\n }\n\n private _onData(): void {\n const t = this.top;\n if(t === null) throw new TypeError(\"done() already called\");\n if(!t.canAdvance()) {\n throw new TypeError(msg_end[t.kind]);\n }\n t.advance();\n }\n\n private _onSemanticTag(): void {\n const t = this.top;\n if(t === null) throw new TypeError(\"done() already called\");\n if(!t.canAdvance()) {\n throw new TypeError(msg_end[t.kind]);\n }\n }\n\n public end(): void {\n const t = this.top;\n if(t === null) throw new TypeError(\"done() already called\");\n if(t.kind === StackKind.OBJECT) {\n throw new TypeError(msg_more[t.kind]);\n // pass\n } else if(t.len !== undefined) {\n if(t.index !== t.len) {\n throw new TypeError(msg_more[t.kind]);\n }\n } else {\n if(t.map_mid) throw new TypeError(msg_more[t.kind]);\n this._reserve(1);\n this.data.setUint8(this.at, TAG_BREAK);\n this.at += 1;\n }\n\n this.top = t.par!;\n }\n\n public uint(val: number) {\n this._onData();\n this._uint(TAG_UINT, val);\n }\n\n public int(val: number) {\n this._onData();\n if(val < 0) this._uint(TAG_NINT, 1 - val);\n else this._uint(TAG_UINT, val);\n }\n\n public bytes(val: Uint8Array) {\n this._onData();\n this._bytes(TAG_BYTES, val);\n }\n\n public string(val: string) {\n this._onData();\n this._bytes(TAG_STRING, enutf8(val));\n }\n\n public array(len?: number) {\n this._onData();\n if(len === undefined) this._indef(TAG_ARRAY);\n else this._uint(TAG_ARRAY, len);\n this.top = new Stack(this.top, StackKind.ARRAY, len);\n }\n\n public map(len?: number) {\n this._onData();\n if(len === undefined) this._indef(TAG_MAP);\n else this._uint(TAG_MAP, len);\n this.top = new Stack(this.top, StackKind.MAP, len);\n }\n\n public semanticTag(val: number) {\n this._onSemanticTag();\n this._uint(TAG_SEMANTIC, val);\n }\n\n public boolean(val: boolean) {\n this._onData();\n this._simple(val ? SIMPLE_TRUE : SIMPLE_FALSE);\n }\n\n public null() {\n this._onData();\n this._simple(SIMPLE_NULL);\n }\n\n public undefined() {\n this._onData();\n this._simple(SIMPLE_UNDEFINED);\n }\n\n public float(val: number) {\n if(val !== val) {\n this._reserve(3);\n this.data.setUint8(this.at, TAG_FLOAT16);\n this.data.setUint16(this.at + 1, 0x7e00);\n this.at += 3;\n } else if(val === Infinity) {\n this._reserve(3);\n this.data.setUint8(this.at, TAG_FLOAT16);\n this.data.setUint16(this.at + 1, 0x7c00);\n this.at += 3;\n } else if(val === -Infinity) {\n this._reserve(3);\n this.data.setUint8(this.at, TAG_FLOAT16);\n this.data.setUint16(this.at + 1, 0xfc00);\n this.at += 3;\n } else if(val === 0) {\n this._reserve(3);\n this.data.setUint8(this.at, TAG_FLOAT16);\n if(1/val > 0) {\n this.data.setUint16(this.at + 1, 0);\n } else {\n this.data.setUint16(this.at + 1, 0x8000);\n }\n } else if(val === Math.fround(val)) {\n this._reserve(5);\n this.data.setUint8(this.at, TAG_FLOAT32);\n this.data.setFloat32(this.at + 1, val);\n this.at += 5;\n } else {\n this._reserve(9);\n this.data.setUint8(this.at, TAG_FLOAT64);\n this.data.setFloat64(this.at + 1, val);\n this.at += 9;\n }\n }\n\n public number(val: number) {\n if(val === Math.floor(val) && Math.abs(val) <= 9007199254740992) this.int(val);\n else this.float(val);\n }\n\n public done(): Uint8Array {\n const t = this.top;\n if(t === null) throw new TypeError(\"done() already called\");\n if(t.kind !== StackKind.OBJECT) throw new TypeError(\"Unclosed container\");\n if(t.index !== 1) throw new TypeError(\"Nothing written\");\n this.top = null;\n return new Uint8Array(this.buf, 0, this.at);\n }\n}\n" }, { "alpha_fraction": 0.6849315166473389, "alphanum_fraction": 0.6872146129608154, "avg_line_length": 35.5, "blob_id": "1afe111905f4424d7d6dd206b1a368c6377690c7", "content_id": "de7581dc5b50821f5f5f4aa19f3f26143d8454fa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 876, "license_type": "no_license", "max_line_length": 78, "num_lines": 24, "path": "/client/src/exec/storage.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "/* Descibes a blob. This is a _value type_. That is, object identity is not of\n * significance. However, it can be beneficial to deduplicate them. /\nexport interface Ref {\n id: string;\n size: number;\n}\n\n/ All write operations on Storage must be atomic and must be executed AS-IF\n * they were serialized in the order of calls. It may be possible to observe\n * a write operation that was started after a read, and all write operations\n * finished before a read has started must be observed. /\nexport interface Storage {\n / Get a list of all blobs. /\n list(): Promise<Ref[]>;\n\n / MUST RETURN A COPY! /\n get(id: string): Promise<Uint8Array>;\n\n / Should do nothing if the blob doesn't exist. /\n delete(id: string): Promise<void>;\n\n / Should overwrite the blob atomically if it exists. /\n set(id: string, data: Uint8Array): Promise<void>;\n}\n" }, { "alpha_fraction": 0.47514480352401733, "alphanum_fraction": 0.4780937433242798, "avg_line_length": 30.544851303100586, "blob_id": "3246c615d5f593dd1d67970d7effc621419e5d2a", "content_id": "51f41120c0ad6eabf15a1b43deb65661ece16873", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 18990, "license_type": "no_license", "max_line_length": 117, "num_lines": 602, "path": "/client/src/exec/repo.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport * as api from \"./api\";\nimport {Ref, Storage} from \"./storage\";\n\nfunction isRemote(ref: Ref): boolean {\n return ref.id.startsWith(\"remote/\");\n}\n\nfunction isLocal(ref: Ref): boolean {\n return ref.id.startsWith(\"local/\");\n}\n\nfunction isState(ref: Ref): boolean {\n return ref.id.startsWith(\"state/\");\n}\n\nconst enum BlobPresence {\n MISSING = 0,\n WAITING = 1,\n AVAILABLE = 2,\n}\n\ninterface BlobState {\n ref: Ref;\n present: BlobPresence;\n refcnt: number;\n\n /* Requests waiting for blob. /\n trackers: Set<BlobTracker>;\n}\n\ninterface BlobTracker {\n readonly onAvailable: (blob: BlobState) => void;\n readonly onError: (blob: BlobState, e: Error) => void;\n readonly onEviction: (blob: BlobState) => void;\n}\n\ninterface DownloadRequest {\n readonly blobs: BlobState[];\n readonly onStart: (blob: BlobState) => void;\n}\n\n/ BlobRepo implements the bookkeeping related to downloading and storing\n * blobs. It will also be responsible for rate-limiting downloading. /\nexport class BlobRepo {\n private readonly blobs = new Map<string, BlobState>();\n\n / Queue of download requests. /\n private readonly dl_reqs = new Set<DownloadRequest>();\n / Number of blobs currently being downloaded. /\n private dl_cur: number = 0;\n / Invariant: 0 <= dl_cur <= dl_max /\n private dl_max: number = 3;\n\n / Counter for labelling local blobs. /\n private local_counter: number = 0;\n\n / Total size of remote blobs in storage. /\n public cache_used: number = 0;\n / Should be equal to the total expected size of the blobs being downloaded. /\n public cache_expect: number = 0;\n\n constructor(\n private readonly st: stat.Sink,\n private readonly provider: api.BlobProvider,\n public readonly storage: Storage\n ) {}\n\n / Delete all unknown blobs, and possibly some unneeded remote blobs. /\n public static create(st: stat.Sink, provider: api.BlobProvider, storage: Storage): Promise<BlobRepo> {\n return storage.list().then((refs) => {\n const repo = new BlobRepo(st, provider, storage);\n for(const ref of refs) {\n if(ref.id.startsWith(\"local/\")) {\n const num = Number(ref.id.slice(6));\n if(num === Math.floor(num) && num >= repo.local_counter) {\n repo.local_counter = num + 1;\n }\n } else if(ref.id.startsWith(\"remote/\")) {\n repo.cache_used += ref.size;\n } else if(ref.id.startsWith(\"state/\")) {\n // pass\n }\n repo.createBlobState(ref, BlobPresence.AVAILABLE);\n }\n return repo;\n });\n }\n\n public get cache_reserved(): number {\n return this.cache_used + this.cache_expect;\n }\n\n public get cache_max(): number {\n return this.provider.cache_max;\n }\n\n public get cache_available(): number {\n return this.cache_max - this.cache_reserved;\n }\n\n / Make the blobs available, call f() with them available. The blobs will\n * be available until the promise returned by f() is resolved, and that will\n * be the final result. /\n public withBlobs<T>(refs: Ref[], f: () => Promise<T>, cancel?: Promise<err.Cancelled>): Promise<T> {\n return this.withBlobStates(refs.map((ref) => this.getOrCreateBlobState(ref)), f, cancel);\n }\n\n private withBlobStates<T>(blobs: BlobState[], f: () => Promise<T>, cancel?: Promise<err.Cancelled>): Promise<T> {\n const pinned = new Set<BlobState>();\n\n blobs = Array.from(new Set(blobs));\n\n const pin = (blob: BlobState) => {\n if(pinned.has(blob)) return;\n this.incref(blob);\n pinned.add(blob);\n };\n\n return new Promise<T>((resolve, reject) => {\n const remote: BlobState[] = [];\n let done: boolean = false;\n\n const onDone = (e: Error \| null) => {\n done = true;\n this.pull();\n for(const blob of blobs) {\n blob.trackers.delete(tracker);\n }\n if(e === null) {\n while(remote.length > 0) {\n pin(remote.pop()!);\n }\n resolve();\n } else {\n remote.splice(0, remote.length);\n reject(e);\n }\n this.dl_reqs.delete(req);\n };\n\n if(cancel !== undefined) {\n cancel.then((e) => {\n if(done) return;\n onDone(e);\n });\n }\n\n let needed: number = blobs.length + 1;\n\n const tracker: BlobTracker = {\n onAvailable: (blob) => {\n needed -= 1;\n if(needed === 0) onDone(null);\n },\n onError: (blob, e) => {\n onDone(e);\n },\n onEviction: (blob) => {\n console.assert(isRemote(blob.ref));\n needed += 1;\n return;\n },\n };\n\n const req: DownloadRequest = {\n blobs: remote,\n onStart: pin,\n };\n\n for(const blob of blobs) {\n blob.trackers.add(tracker);\n if(isRemote(blob.ref)) {\n remote.push(blob);\n } else {\n pin(blob);\n }\n\n switch(blob.present) {\n case BlobPresence.MISSING:\n console.assert(isRemote(blob.ref));\n break;\n case BlobPresence.WAITING:\n break;\n case BlobPresence.AVAILABLE:\n tracker.onAvailable(blob);\n break;\n }\n }\n\n needed -= 1;\n\n if(needed === 0) {\n onDone(null);\n return;\n }\n\n if(remote.length !== 0) {\n remote.reverse();\n let total_size = 0;\n for(const blob of remote) {\n total_size += blob.ref.size;\n }\n if(total_size > this.cache_max) {\n onDone(new err.Cancelled(\"Request size above limit\"));\n } else {\n this.dl_reqs.add(req);\n this.pull();\n }\n }\n }).then(f).finally(() => {\n for(const blob of pinned) {\n this.decref(blob);\n }\n });\n }\n\n / Read a blob that is known to be available. /\n public read(ref: Ref): Promise<Uint8Array> {\n const blob = this.blobs.get(ref.id);\n if(!blob) {\n return Promise.reject(new err.State(\"Unknown blob\", {\n blob_id: ref.id,\n }));\n }\n if(blob.present !== BlobPresence.AVAILABLE) {\n return Promise.reject(new err.State(\"Blob not available\", {\n blob_id: ref.id,\n }));\n }\n if(blob.ref.size !== ref.size) {\n return Promise.reject(new err.State(\"Blob size mismatch\", {\n blob_id: ref.id,\n got_size: blob.ref.size,\n want_size: ref.size,\n }));\n }\n\n console.assert(blob.refcnt > 0);\n return this.storage.get(blob.ref.id).then((data) => {\n if(data.byteLength !== ref.size) {\n throw new err.State(\"Blob size conflict\", {\n blob_id: ref.id,\n got_size: data.byteLength,\n want_size: ref.size,\n });\n }\n return data;\n });\n }\n\n private getOrCreateBlobState(ref: Ref) {\n const blob = this.blobs.get(ref.id);\n if(blob !== undefined) {\n if(blob.ref.size !== ref.size) {\n this.st.reportError(new err.State(\"Blob size mismatch\", {\n blob_id: ref.id,\n got_size: blob.ref.size,\n want_size: ref.size,\n }));\n }\n return blob;\n }\n if(!isRemote(ref) && !isState(ref)) {\n throw new err.State(\"Blob not found\", {\n blob_id: ref.id,\n });\n }\n return this.createBlobState(ref, BlobPresence.MISSING);\n }\n\n / Register a blob ref with the repo, and log any inconsistencies /\n public register(ref: Ref): Ref {\n const blob = this.getOrCreateBlobState(ref);\n if(blob.ref.size === ref.size) return blob.ref;\n return ref;\n }\n\n / Load a blob from the API. /\n public fromAPI(b: api.BlobRef): Ref {\n return this.register({\n id: \"remote/\" + b.id,\n size: b.size,\n });\n }\n\n private setBlobAvailable(blob: BlobState): void {\n const trackers = Array.from(blob.trackers);\n blob.present = BlobPresence.AVAILABLE;\n for(const tracker of trackers) {\n tracker.onAvailable(blob);\n }\n }\n\n private setBlobError(blob: BlobState, e: Error): void {\n const trackers = Array.from(blob.trackers);\n blob.present = BlobPresence.MISSING;\n const e2 = err.fromData(Object.assign({\"blob_id\": blob.ref.id}, err.dataOf(e)));\n for(const tracker of trackers) {\n tracker.onError(blob, e2);\n }\n }\n\n private setBlobEvicted(blob: BlobState): void {\n const trackers = Array.from(blob.trackers);\n blob.present = BlobPresence.MISSING;\n for(const tracker of trackers) {\n tracker.onEviction(blob);\n }\n }\n\n / Create a new local blob with the given data, and pin() it. /\n public create(data: Uint8Array): [Ref, Promise<void>] {\n const i = this.local_counter;\n this.local_counter = i+1;\n console.assert(\n i === Math.floor(i) &&\n this.local_counter === Math.floor(this.local_counter) &&\n this.local_counter !== i\n );\n\n const ref = {\n id: `local/${i}`,\n size: data.byteLength,\n };\n\n const blob = this.createBlobState(ref, BlobPresence.WAITING);\n\n this.incref(blob);\n\n return [ref, this.storage.set(ref.id, data).then(() => {\n this.setBlobAvailable(blob);\n return;\n }, (e) => {\n this.setBlobError(blob, e);\n throw e;\n })];\n }\n\n private incref(blob: BlobState): void {\n blob.refcnt += 1;\n if(blob.refcnt !== 1) return;\n if(blob.present === BlobPresence.MISSING) {\n blob.refcnt -= 1;\n throw new err.State(\"Blob missing\", {\n \"blob_id\": blob.ref.id,\n });\n }\n }\n\n private decref(blob: BlobState): void {\n console.assert(blob.refcnt > 0);\n blob.refcnt -= 1;\n if(blob.refcnt !== 0) return;\n\n // Eviction possible?\n if(isRemote(blob.ref)) {\n if(blob.present === BlobPresence.AVAILABLE) {\n this.pull();\n }\n } else if(isLocal(blob.ref)) {\n this.blobs.delete(blob.ref.id);\n this.setBlobEvicted(blob);\n this.storage.delete(blob.ref.id).catch((e) => this.st.reportError(e));\n }\n }\n\n / Mark the given blob as needed. /\n public pin(ref: Ref): Ref {\n const blob = this.getBlobState(ref);\n if(blob.ref.size !== ref.size) {\n throw new err.State(\"Blob size mismatch\", {\n \"blob_id\": ref.id,\n \"got_size\": blob.ref.size,\n \"want_size\": ref.size,\n });\n }\n this.incref(blob);\n return blob.ref;\n }\n\n / Mark the given blob as no longer needed. /\n public unpin(ref: Ref): void {\n const blob = this.getBlobState(ref);\n if(blob.refcnt < 1) {\n throw new err.State(\"Blob not pinned\", {\n blob_id: ref.id,\n });\n }\n if(blob.ref.size !== ref.size) {\n throw new err.State(\"Blob size mismatch\", {\n blob_id: ref.id,\n got_size: blob.ref.size,\n want_size: ref.size,\n });\n }\n this.decref(blob);\n }\n\n public readState(name: string): Promise<Uint8Array \| null> {\n const blob = this.blobs.get(\"state/\" + name);\n if(!blob) return Promise.resolve(null);\n return this.withBlobStates([blob], () => this.read(blob.ref));\n }\n\n public writeState(name: string, data: Uint8Array): Promise<void> {\n const ref = {\n id: \"state/\" + name,\n size: data.length,\n };\n let blob = this.blobs.get(ref.id);\n let oldState: BlobPresence;\n if(blob === undefined) {\n blob = this.createBlobState(ref, BlobPresence.WAITING);\n oldState = BlobPresence.MISSING;\n } else {\n if(blob.refcnt !== 0) {\n throw new err.State(\"State is being read\");\n }\n oldState = blob.present;\n blob.ref = ref;\n blob.present = BlobPresence.WAITING;\n }\n\n return this.storage.set(ref.id, data).then(() => {\n this.setBlobAvailable(blob!);\n }, (e) => {\n if(oldState === BlobPresence.AVAILABLE) {\n this.setBlobAvailable(blob!);\n } else {\n this.setBlobError(blob!, e);\n }\n throw e;\n });\n }\n\n private createBlobState(ref: Ref, present: BlobPresence): BlobState {\n const blob: BlobState = {\n ref: ref,\n present: present,\n refcnt: 0,\n trackers: new Set(),\n };\n console.assert(this.blobs.get(ref.id) === undefined);\n this.blobs.set(ref.id, blob);\n return blob;\n }\n\n / Get a BlobState from a given Ref. /\n private getBlobState(ref: Ref): BlobState {\n const blob = this.blobs.get(ref.id);\n if(blob) return blob;\n throw new err.State(\"Blob not found\", {\n blob_id: ref.id,\n });\n }\n\n private pull_scheduled: boolean = false;\n private pull(): void {\n if(this.pull_scheduled) return;\n if(this.dl_cur >= this.dl_max) return;\n this.pull_scheduled = true;\n self.setTimeout(() => this.doPull(), 0);\n }\n\n private doPull(): void {\n this.pull_scheduled = false;\n\n for(const req of this.dl_reqs) {\n if(this.dl_cur >= this.dl_max) break;\n while(true) {\n const blob = req.blobs.pop();\n if(blob === undefined) {\n this.dl_reqs.delete(req);\n break;\n }\n let dl: boolean = false;\n if(blob.present === BlobPresence.MISSING) {\n if(blob.ref.size > this.cache_available) {\n if(!this.evict(blob.ref.size - this.cache_available)) {\n req.blobs.push(blob);\n return;\n }\n }\n blob.present = BlobPresence.WAITING;\n dl = true;\n }\n req.onStart(blob);\n if(dl) {\n this.dlOne(blob);\n }\n }\n }\n }\n\n private dlOne(blob: BlobState): void {\n const id = blob.ref.id;\n const expected_size = blob.ref.size;\n\n // Maybe move most of this function into a field of BlobState set when\n // the blob is added to `dlq` for symmetry.\n const fin = (e: Error \| null) => {\n this.dl_cur -= 1;\n this.cache_expect -= expected_size;\n\n if(e !== null) {\n if(this.blobs.get(id) === blob) {\n this.blobs.delete(id);\n }\n this.setBlobError(blob, e);\n } else {\n this.setBlobAvailable(blob);\n }\n\n if(this.dl_cur === 0 && this.cache_expect !== 0) {\n this.st.reportError(new err.State(\"Expected cache size leak\", {\n \"expected_cache_size_leak\": this.cache_expect,\n }));\n this.cache_expect = 0;\n }\n\n this.pull();\n };\n\n this.dl_cur += 1;\n this.cache_expect += expected_size;\n\n try {\n console.assert(id.startsWith(\"remote/\"));\n\n this.provider.getBlob(id.slice(7), expected_size).then((data) => {\n const real_size = data.byteLength;\n if(real_size !== expected_size) {\n this.st.reportError(new err.State(\"Blob size changed\", {\n blob_id: id,\n got_size: real_size,\n want_size: expected_size,\n }));\n blob.ref = {\n id: id,\n size: real_size,\n };\n }\n return this.storage.set(id, new Uint8Array(data)).then(() => {\n this.cache_used += real_size;\n return null;\n });\n }).then(fin, fin);\n } catch(e) {\n fin(e);\n }\n }\n\n private evict(size: number): boolean {\n if(size <= 0) return true;\n\n const evictable: BlobState[] = [];\n const req_index = new Map<BlobState, number>();\n\n for(const blob of this.blobs.values()) {\n if(!isState(blob.ref) && blob.present === BlobPresence.AVAILABLE && blob.refcnt === 0) {\n evictable.push(blob);\n }\n }\n\n for(const req of this.dl_reqs) {\n const index = req_index.size;\n for(const blob of req.blobs) {\n if(!req_index.has(blob)) req_index.set(blob, index);\n }\n }\n\n evictable.sort((a, b) => {\n const la = isLocal(a.ref);\n const lb = isLocal(b.ref);\n if(la && !lb) return -1;\n if(!la && lb) return 1;\n const ia = req_index.get(a);\n const ib = req_index.get(b);\n if(ia !== ib) {\n if(ia === undefined) return -1;\n if(ib === undefined) return 1;\n if(ia > ib) return -1;\n if(ia < ib) return 1;\n console.assert(false);\n }\n return 0;\n });\n\n for(const blob of evictable) {\n this.setBlobEvicted(blob);\n size -= blob.ref.size;\n this.cache_used -= blob.ref.size;\n this.storage.delete(blob.ref.id).catch((e) => this.st.reportError(e));\n if(size <= 0) return true;\n }\n\n return false;\n }\n}\n" }, { "alpha_fraction": 0.510162889957428, "alphanum_fraction": 0.5209744572639465, "avg_line_length": 33.17241287231445, "blob_id": "e4fb6fcf31bd1a4a8c13d3dfb57de300710b1410", "content_id": "2d9574dccebefc0242dc2e0b73a267fb1cadea3c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6937, "license_type": "no_license", "max_line_length": 107, "num_lines": 203, "path": "/testCustomer/collatzCustomer.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import sys, cbor, socket, os, threading, traceback\nimport serverRequest\nimport time\nimport calendar\nfrom serverRequest import \n\n# Pass the username and password as command-line arguments\ntry:\n username = sys.argv[1]\n password = sys.argv[2]\n project_name = sys.argv[3]\nexcept:\n print(\"Please enter correct username, password and project ID\")\n sys.exit()\n\n#ollatzf = open(\"collatzClient\", 'rb')\nwith open(\"collatzClient\", \"rb\") as f:\n collatz_wa = f.read()\ncollatz_fs = os.path.getsize(\"collatzClient\")\n\nclass TaskDistributor:\n\n # For now we just have a fixed range.\n # Starting at 'search_start', we have 'number_tasks' intervals of length 'fixed_range'\n # So the total search will be between [search_start ... search_start + fixed_range * number_tasks)\n search_start = 3000000000000000000000000000\n fixed_range = 100000\n\n def __init__ (self, token):\n self.highestSeqs = []\n self.token = token\n self.startTime = calendar.timegm(time.gmtime())\n\n def go(self):\n self.thr_init = threading.Thread(target=self.initTasksLoop)\n self.thr_mon = threading.Thread(target=self.monitorBlobs)\n self.thr_init.start()\n self.thr_mon.start()\n self.thr_init.join()\n self.thr_mon.join()\n\n def makeTaskBlob(self):\n (success, data) = createNewBlob(self.token, project_name, collatz_wa, cbor.dumps({}))\n if not success:\n print(\"Error when making blob task\")\n print(data[\"error\"])\n sys.exit()\n return data[\"blobID\"]\n\n def initTasksLoop (self):\n while True:\n try:\n no_tasks = int (input(\"How many tasks would you like to add? \"))\n self.initTasks(no_tasks)\n except:\n traceback.print_exc()\n\n\n def initTasks (self, number_tasks):\n # Push blob containing web assembly to the database, return its ID\n taskBlobID = self.makeTaskBlob()\n print(\"Blob creation succeeded\")\n print (\"Taskifying \" + str(number_tasks) + \" times...\")\n\n for taskNo in range (0, number_tasks):\n\n # Calculate interval\n start = self.search_start\n end = start + self.fixed_range\n\n # Convert to bytearray data\n leftb = start.to_bytes(16, byteorder='little')\n rightb = end.to_bytes(16, byteorder='little')\n intervalb = leftb + rightb\n\n taskInfo = { \"program\": {\"id\": taskBlobID, \"size\": collatz_fs},\n \"control\": intervalb, \"blobs\": []}\n\n (success, dataBlob) = createNewBlob(token, project_name, cbor.dumps(taskInfo), cbor.dumps({}))\n if (not success):\n print(\"Error when creating blob (pre-taskify)\")\n print(dataBlob[\"error\"])\n sys.exit()\n\n (success, dataTask) = blobToTask(token, project_name, dataBlob[\"blobID\"])\n if (not success):\n print (\"Error when taskifying\")\n print (dataTask[\"error\"])\n sys.exit()\n\n self.search_start += self.fixed_range\n\n print (\"Taskifying succeeded\")\n\n def plot(self, results):\n\n graphs = {\n \"highestResults\": {\n \"type\": 'scatter',\n \"data\": {\n \"datasets\": [{\n \"label\": 'Longest sequences computed from tasks',\n \"borderColor\": 'rgb(0, 255, 0)',\n \"data\": self.highestSeqs,\n \"showLine\": False,\n \"lineTension\": 0.0,\n }],\n },\n \"options\": {\n \"scales\": {\n \"xAxes\": [{\n \"time\": {\n \"unit\": 'second',\n },\n }],\n },\n },\n }\n }\n\n updateGraphs(self.token, graphs, project_name)\n\n def processResults(self, bytedata):\n\n # Process results from a single task\n\n left = int.from_bytes(bytedata[:16], 'little')\n right = int.from_bytes(bytedata[16:32], 'little')\n highestSeqLen = int.from_bytes(bytedata[32:36], 'little')\n\n '''\n highestSeqLen = 0\n for i in range (0, right - left):\n seqLength = 0\n for j in range (0, 4): # Int sequence lengths\n seqLength += bytedata[4 * i + j + 32]<<8j\n\n highestSeqLen = max (highestSeqLen, seqLength)\n '''\n self.highestSeqs.append ( {\"x\": time.time()1000, \"y\": highestSeqLen} )\n self.plot(self.highestSeqs)\n\n # When a worker finished a computation, it places a blob in the database along with metadata\n # indicating whether the task is finished. The customer will routinely scan (will it?) the database for\n # finished blobs and will acquire their results before deleting them.\n\n def monitorBlobs(self):\n dataRecieved = 0\n print(\"Monitoring blobs...\")\n while True:\n time.sleep(5)\n try:\n\n # Get meta-data on all blobs (for now)\n (success, allData) = getBlobMetadata(self.token, project_name, [])\n if (not success):\n print (\"Error when retrieving metadata\")\n print(allData)\n continue\n\n metaDict = allData[\"metadata\"]\n\n # Convert all metadata out of CBOR form\n for bID, meta in metaDict.items():\n metaDict[bID] = cbor.loads(meta)\n\n for blobid, metadata in metaDict.items():\n if (bool(metadata)):\n if (metadata[\"result\"] == True):\n # So blobID points to a result\n (success, data) = getBlob(self.token, project_name, blobid)\n if (not success):\n print (\"Failure to retrieve result blob\")\n sys.exit()\n blobval = data[\"blob\"]\n self.processResults(blobval)\n dataRecieved += 1\n deleteBlob(self.token, project_name, blobid)\n except:\n traceback.print_exc()\n\n############### START HERE ################\nif __name__ == '__main__':\n\n # Just ping server to check it's up and running\n (success, ret) = testPing()\n if (not success):\n print(\"Server ping error\")\n print(ret[\"error\"])\n sys.exit()\n\n (success, tokenDict) = login(username, password, \"customer\")\n if (not success):\n print(\"Token acquisition failed\")\n print(tokenDict)\n sys.exit()\n\n token = tokenDict[\"token\"]\n\n # Login successful\n distributor = TaskDistributor(token)\n\n distributor.go()\n" }, { "alpha_fraction": 0.5587753057479858, "alphanum_fraction": 0.5658829808235168, "avg_line_length": 26.096296310424805, "blob_id": "0ce1c7dcf6ada42bd8aaa845ac1d61380a4a291c", "content_id": "7f59f8dcb4bf8e8046348886e588a7b9af683010", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 3658, "license_type": "no_license", "max_line_length": 70, "num_lines": 135, "path": "/client/src/API.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import {Observable, Subject} from \"@/obs\";\n\nexport interface Project {\n id: string;\n title: string;\n description: string;\n}\n\nexport interface Settings {\n allow_mobile_data: boolean;\n allow_on_battery: boolean;\n projects: string[];\n}\n\nexport interface Graphs {\n [name: string]: any;\n}\n\nexport interface User {\n readonly username: string;\n readonly settings: Observable<Settings>;\n readonly projects: Observable<Map<string, Project>>;\n readonly overview: Observable<string[]>;\n\n logout(): Promise<void>;\n stop(): Promise<void>;\n\n updateSettings(upd: Partial<Settings>): void;\n setProjectOn(name: string): void;\n setProjectOff(name: string): void;\n refreshProjects(): Promise<void>;\n requestGraphs(query: string): Promise<Graphs>;\n}\n\nexport interface ClientState {\n readonly user: Observable<User \| null>;\n\n login(username: string, password: string): Promise<void>;\n loginGuest(): Promise<void>;\n signUp(username: string, password: string): Promise<void>;\n reset(): Promise<void>;\n}\n\nexport class MockClientState implements ClientState {\n public user = new Subject<User \| null>(null);\n\n public login(username: string, password: string): Promise<void> {\n return new Promise((resolve, reject) => {\n setTimeout(() => {\n if(password !== \"a\") {\n reject(new Error(\"Password not 'a'\"));\n return;\n }\n\n this.user.next(new MockUser(this, username));\n\n resolve();\n }, 1000);\n });\n }\n\n public loginGuest(): Promise<void> {\n return new Promise((resolve, reject) => {\n setTimeout(() => {\n this.user.next(new MockUser(this, \"guest\"));\n resolve();\n }, 1000);\n });\n }\n\n public signUp(username: string, password: string): Promise<void> {\n return this.login(username, \"a\");\n }\n\n public reset(): Promise<void> {\n return Promise.resolve();\n }\n}\n\nexport class MockUser implements User {\n constructor(\n private readonly st: MockClientState,\n public readonly username: string\n ) {}\n\n public readonly settings = new Subject<Settings>({\n allow_mobile_data: true,\n allow_on_battery: true,\n projects: [\"proj1\", \"proj2\", \"proj3\"],\n });\n\n public readonly projects = new Subject(new Map([\n {\n id: \"proj1\",\n title : \"Project Title 1\",\n description: \"description1\",\n }, {\n id: \"proj2\",\n title : \"Project Title 2\",\n description: \"description2\",\n }, {\n id: \"proj3\",\n title : \"Project Title 3\",\n description: \"description3\",\n }, {\n id: \"proj4\",\n title : \"Project Title 4\",\n description: \"description4\",\n }, {\n id: \"proj5\",\n title : \"Project Title 5\",\n description: \"description5\",\n }].map((p): [string, Project] => [p.id, p]),\n ));\n\n public readonly overview = new Subject([\"This is a mock\"]);\n\n public logout(): Promise<void> {\n this.st.user.next(null);\n return Promise.resolve();\n }\n public stop(): Promise<void> {\n return Promise.resolve();\n }\n\n public updateSettings(upd: Partial<Settings>): void {}\n public setProjectOn(name: string): void {}\n public setProjectOff(name: string): void {}\n public refreshProjects(): Promise<void> {\n return Promise.resolve();\n }\n public requestGraphs(query: string): Promise<Graphs> {\n return Promise.resolve({});\n }\n}\n" }, { "alpha_fraction": 0.5213973522186279, "alphanum_fraction": 0.5257641673088074, "avg_line_length": 26.926828384399414, "blob_id": "13fc24dfc1ba4f429514d41076a17ad475ac072d", "content_id": "332d2b80a4ac7f5da768740522436451bc45b7e7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 1145, "license_type": "no_license", "max_line_length": 86, "num_lines": 41, "path": "/client/src/exec/mem_storage.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import * as err from \"@/err\";\nimport {Ref, Storage} from \"./storage\";\n\nexport default class MemStorage implements Storage {\n public readonly blobs: Map<string, Uint8Array>;\n\n constructor() {\n this.blobs = new Map();\n }\n\n public list(): Promise<Ref[]> {\n return Promise.resolve(Array.from(this.blobs.entries()).map(([key, data]) => {\n return {\n id: key,\n size: data.byteLength,\n };\n }));\n }\n\n public get(id: string): Promise<Uint8Array> {\n return new Promise((resolve, reject) => {\n const bl = this.blobs.get(id);\n if(bl) resolve(new Uint8Array(bl));\n else reject(new err.State(\"Blob not found\", {blob_id: id}));\n });\n }\n\n public delete(id: string): Promise<void> {\n return new Promise((resolve, reject) => {\n this.blobs.delete(id);\n resolve();\n });\n }\n\n public set(id: string, data: Uint8Array): Promise<void> {\n return new Promise((resolve, reject) => {\n this.blobs.set(id, new Uint8Array(data));\n resolve();\n });\n }\n}\n" }, { "alpha_fraction": 0.7116564512252808, "alphanum_fraction": 0.7116564512252808, "avg_line_length": 26.16666603088379, "blob_id": "5aa231ae33a383ac1e29bb761e1cf94be653c341", "content_id": "288ad96e155b807f3d3538ae11594c7f88b5a536", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 163, "license_type": "no_license", "max_line_length": 53, "num_lines": 6, "path": "/client/src/device.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import * as obs from \"@/obs\";\n\nexport interface Device {\n readonly on_battery: obs.Observable<boolean>;\n readonly on_mobile_data: obs.Observable<boolean>;\n}\n" }, { "alpha_fraction": 0.7558139562606812, "alphanum_fraction": 0.7674418687820435, "avg_line_length": 16.200000762939453, "blob_id": "20ca375c7e489cf7b920def861e38d6d5f609af8", "content_id": "d612e4c2344ee50b5e4bfa0509a5f946df785ca9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 86, "license_type": "no_license", "max_line_length": 34, "num_lines": 5, "path": "/githook/gitpull.sh", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "#!/bin/bash\ncd /home/ec2-user/DistributedPhone\ngit pull\necho Pull finished\n./build.sh\n" }, { "alpha_fraction": 0.5358851552009583, "alphanum_fraction": 0.5358851552009583, "avg_line_length": 28.85714340209961, "blob_id": "e8f2f5162703bfb875262149d678f6671b7722be", "content_id": "dcf022e87d42604cb28daddd0852a59c0eaa0e4e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 836, "license_type": "no_license", "max_line_length": 65, "num_lines": 28, "path": "/client/src/polyfill.js", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "if(!Promise.prototype.finally) {\n Promise.prototype.finally = function(onFinally) {\n if(onFinally === null \|\| onFinally === undefined) {\n return this.then();\n }\n return this.then(function(value) {\n return Promise.resolve(onFinally()).then(function() {\n return value;\n });\n }, function(error) {\n return Promise.resolve(onFinally()).then(function() {\n throw error;\n });\n });\n }\n}\n\nif(typeof window !== 'undefined') {\n window.document.write = function() {\n throw new Error(\"document.open() is bad\");\n }\n window.document.open = function() {\n throw new Error(\"document.open() is bad\");\n }\n window.document.close = function() {\n throw new Error(\"document.open() is bad\");\n }\n}\n" }, { "alpha_fraction": 0.4969770312309265, "alphanum_fraction": 0.5392986536026001, "avg_line_length": 25.677419662475586, "blob_id": "48e4d6a423e3c42de23130b8ef96ae8bdddd3bb6", "content_id": "b44baf9a83ac24f0b7a2d1ecd61970ccddd3a9b2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 827, "license_type": "no_license", "max_line_length": 96, "num_lines": 31, "path": "/client/src/backoff.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "export default class Backoff {\n public readonly init: number;\n public readonly max: number;\n private _value: number;\n\n constructor(init?: number, max?: number) {\n if(init === undefined) this.init = 2000;\n else this.init = Math.max(100, 0\|Math.min(86400000, init));\n\n if(max === undefined) this.max = 10 * this.init;\n else this.max = Math.min(2 * this.init, Math.max(this.init, 0\|Math.min(86400000, max)));\n\n this._value = 0;\n }\n\n public get value(): number {\n return this._value;\n }\n\n public succeed(): void {\n this._value = 0;\n }\n\n public fail(): void {\n if(this._value === 0) {\n this._value = this.init;\n } else {\n this._value = Math.min(this.max, this._value * (1.1 + 0.4 * Math.random()));\n }\n }\n}\n" }, { "alpha_fraction": 0.44951868057250977, "alphanum_fraction": 0.4529842138290405, "avg_line_length": 26.569002151489258, "blob_id": "07a3afe805d481d303597e36de8c1acfbfeecc74", "content_id": "61c3a5bfef2f5608bb3ca1877ebc1f667bac7eae", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 12985, "license_type": "no_license", "max_line_length": 106, "num_lines": 471, "path": "/client/src/obs.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "export interface Subscription {\n readonly closed: boolean;\n start(): void;\n stop(): void;\n}\n\nexport interface Observer<T> {\n next?(value: T): void;\n error?(err: Error): void;\n complete?(): void;\n}\n\nexport interface SubscriptionObserver<T> {\n readonly closed: boolean;\n next(value: T): void;\n error(err: Error): void;\n complete(): void;\n}\n\nclass SubscriptionObserverImpl<T> implements SubscriptionObserver<T> {\n private _closed: boolean = false;\n\n constructor(\n private _onNext: (value: T) => void,\n private _onError: (err: Error) => void,\n private _onComplete: () => void\n ) {}\n\n get closed() {\n return this._closed;\n }\n\n public next(value: T): void {\n if(this._closed) return;\n try {\n this._onNext(value);\n } catch(e) {\n console.error(e);\n }\n }\n\n public error(err: Error): void {\n const cb = this._onError;\n if(this._close()) return;\n try {\n cb(err);\n } catch(e) {\n console.error(e);\n }\n }\n\n public complete(): void {\n const cb = this._onComplete;\n if(this._close()) return;\n try {\n cb();\n } catch(e) {\n console.error(e);\n }\n }\n\n public _close(): boolean {\n if(this._closed) return true;\n this._closed = true;\n this._onNext = ignore;\n this._onError = ignore;\n this._onComplete = ignore;\n return false;\n }\n}\n\nexport type Subscriber<T> = (observer: SubscriptionObserver<T>) => undefined \| (() => void);\n\nexport interface ObservableLike<T> {\n subscribe(\n onNext: (value: T) => void,\n onError?: (error: Error) => void,\n onComplete?: () => void\n ): Subscription;\n\n subscribe(observer: Observer<T>): Subscription;\n}\n\nfunction ignore(): void {}\n\nexport class Observable<T> implements ObservableLike<T> {\n private _subscriber: Subscriber<T>;\n\n constructor(subscriber: Subscriber<T>) {\n this._subscriber = subscriber;\n }\n\n public subscribe(\n onNext?: (value: T) => void,\n onError?: (error: Error) => void,\n onComplete?: () => void\n ): Subscription;\n\n public subscribe(observer: Observer<T>): Subscription;\n\n public subscribe(\n obs?: ((value: T) => void) \| Observer<T>,\n onError?: (error: Error) => void,\n onComplete?: () => void\n ): Subscription {\n let onNext: (value: T) => void;\n\n if(typeof obs === \"object\") {\n onNext = (value) => {\n if(obs.next !== undefined) obs.next(value);\n };\n onError = (err) => {\n if(obs.error !== undefined) obs.error(err);\n };\n onComplete = () => {\n if(obs.complete !== undefined) obs.complete();\n };\n } else {\n onNext = obs \|\| ignore;\n onError = onError \|\| ignore;\n onComplete = onComplete \|\| ignore;\n }\n\n const so = new SubscriptionObserverImpl(onNext, onError, onComplete);\n let func: (() => void) \| undefined;\n let subscriber: Subscriber<T> \| undefined = this._subscriber;\n\n return {\n get closed() {\n return so.closed;\n },\n start() {\n const f = subscriber;\n if(f === undefined) throw new TypeError(\"Already started\");\n subscriber = undefined;\n try {\n func = f(so);\n } catch(e) {\n so.error(e);\n }\n },\n stop() {\n const f = func;\n func = undefined;\n if(so._close() && f) {\n try {\n f();\n } catch(e) {\n console.error(e);\n }\n }\n },\n };\n }\n}\n\nexport function single<T>(value: T): Observable<T> {\n return new Observable((sink) => {\n sink.next(value);\n sink.complete();\n return () => {};\n });\n}\n\nexport function first<T>(obs: ObservableLike<T> \| ObservableLike<PromiseLike<T>>): Promise<T \| undefined>;\nexport function first<T, U>(obs: ObservableLike<T \| PromiseLike<U>>): Promise<T \| U \| undefined>;\n\nexport function first<T,U>(obs: ObservableLike<T \| PromiseLike<U>>): Promise<T \| U \| undefined> {\n return new Promise((resolve, reject) => {\n const subs = obs.subscribe(\n (value) => {\n resolve(value);\n subs.stop();\n },\n (err) => reject(err),\n () => resolve(undefined),\n );\n subs.start();\n });\n}\n\nexport function last<T>(obs: ObservableLike<T> \| ObservableLike<PromiseLike<T>>): Promise<T \| undefined>;\nexport function last<T, U>(obs: ObservableLike<T \| PromiseLike<U>>): Promise<T \| U \| undefined>;\n\nexport function last<T,U>(obs: ObservableLike<T \| PromiseLike<U>>): Promise<T \| U \| undefined> {\n let val: T \| PromiseLike<U> \| undefined;\n\n return new Promise((resolve, reject) => {\n obs.subscribe(\n (value) => {\n val = value;\n },\n (err) => reject(err),\n () => resolve(val),\n ).start();\n });\n}\n\nexport function map<T, U>(obs: ObservableLike<T>, f: (val: T) => U): Observable<U> {\n return new Observable<U>((sink) => {\n const subs = obs.subscribe(\n (val: T) => {\n let val2: U;\n try {\n val2 = f(val);\n } catch(e) {\n sink.error(e);\n return;\n }\n sink.next(val2);\n },\n (e) => sink.error(e),\n () => sink.complete(),\n );\n subs.start();\n return () => subs.stop();\n });\n}\n\nexport function filter<T>(obs: ObservableLike<T>, f: (val: T) => boolean): Observable<T>;\nexport function filter<T extends U, U>(obs: ObservableLike<U>, f: (val: U) => val is T): Observable<T>;\n\nexport function filter<T>(obs: ObservableLike<T>, f: (val: T) => boolean): Observable<T> {\n return new Observable<T>((sink) => {\n const subs = obs.subscribe(\n (val: T) => {\n let ok: boolean;\n try {\n ok = f(val);\n } catch(e) {\n sink.error(e);\n return;\n }\n if(ok) sink.next(val);\n },\n (e) => sink.error(e),\n () => sink.complete(),\n );\n subs.start();\n return () => subs.stop();\n });\n}\n\nexport function switchMap<T, U>(obs: ObservableLike<T>, f: (val: T) => ObservableLike<U>): Observable<U> {\n return new Observable((sink) => {\n let sub1: Subscription \| undefined;\n const sub = obs.subscribe((v_out) => {\n if(sub1 !== undefined) {\n sub1.stop();\n sub1 = undefined;\n }\n let obs1: ObservableLike<U>;\n try {\n obs1 = f(v_out);\n } catch(e) {\n sink.error(e);\n return;\n }\n\n sub1 = obs1.subscribe((v_in) => {\n sink.next(v_in);\n }, (e) => {\n sink.error(e);\n sub1 = undefined;\n }, () => {\n sub1 = undefined;\n });\n sub1.start();\n }, (e) => {\n if(sub1 !== undefined) {\n sub1.stop();\n sub1 = undefined;\n }\n sink.error(e);\n }, () => {\n if(sub1 !== undefined) {\n sub1.stop();\n sub1 = undefined;\n }\n sink.complete();\n });\n sub.start();\n return () => {\n sub.stop();\n if(sub1 !== undefined) {\n sub1.stop();\n sub1 = undefined;\n }\n };\n });\n}\n\nexport function refresh<T>(f: () => Promise<T>, period: number): Observable<T> {\n return new Observable<T>((sink) => {\n let tm: number \| undefined;\n const cb = () => {\n tm = undefined;\n f().then((v) => {\n if(sink.closed) return;\n sink.next(v);\n tm = self.setTimeout(cb, period);\n }, (e) => {\n sink.error(e);\n });\n };\n tm = self.setTimeout(cb, 0);\n return () => {\n if(tm !== undefined) self.clearTimeout(tm);\n };\n });\n}\n\nconst stNoValue = {};\nconst stHasValue = {};\nconst stComplete = {};\n\nexport class Subject<T> extends Observable<T> implements SubscriptionObserver<T> {\n private _state: any;\n private _value: T \| undefined;\n private _subs: Array<[number, SubscriptionObserver<T>]> = [];\n\n constructor(initial?: T) {\n super((subscriber) => {\n const subs = this._subs;\n const obj: [number, SubscriptionObserver<T>] = [subs.length, subscriber];\n if(subs.length === 0) this.onAttach();\n subs.push(obj);\n\n const st = this._state;\n if(st === stHasValue) {\n subscriber.next(this._value!);\n } else if(st !== stNoValue) {\n if(st === stComplete) {\n subscriber.complete();\n } else {\n subscriber.error(st);\n }\n return;\n }\n\n return () => {\n const i = obj[0];\n if(i !== -1) {\n obj[0] = -1;\n if(i !== subs.length - 1) {\n const lastval = subs.pop()!;\n lastval[0] = i;\n subs[i] = lastval;\n } else {\n subs.pop();\n }\n if(subs.length === 0) this.onDetach();\n }\n };\n });\n\n this._value = initial;\n\n if(arguments.length >= 1) {\n this._state = stHasValue;\n } else {\n this._state = stNoValue;\n }\n }\n\n get value(): T {\n const st = this._state;\n if(st !== stHasValue) {\n if(st === stNoValue \|\| st === stComplete) throw new TypeError(\"No data available\");\n throw st;\n }\n return this._value!;\n }\n\n get closed(): boolean {\n const st = this._state;\n return st !== stNoValue && st !== stHasValue;\n }\n\n public next(value: T) {\n const st = this._state;\n if(st !== stHasValue) {\n if(st !== stNoValue) return;\n this._state = stHasValue;\n }\n this._value = value;\n for(const obj of this._subs) {\n obj[1].next(value);\n }\n }\n\n public error(err: Error) {\n const st = this._state;\n if(st !== stNoValue && st !== stHasValue) return;\n this._state = err;\n this._value = undefined;\n const subs = this._subs;\n if(subs.length !== 0) {\n this.onDetach();\n for(const obj of subs) {\n obj[0] = -1;\n obj[1].error(err);\n }\n subs.splice(0);\n }\n }\n\n public complete() {\n const st = this._state;\n if(st !== stNoValue && st !== stHasValue) return;\n this._state = stComplete;\n this._value = undefined;\n const subs = this._subs;\n if(subs.length !== 0) {\n this.onDetach();\n for(const obj of subs) {\n obj[0] = -1;\n obj[1].complete();\n }\n subs.splice(0);\n }\n }\n\n protected isEmpty(): boolean {\n return this._subs.length === 0;\n }\n protected onAttach(): void {}\n protected onDetach(): void {}\n}\n\nexport class Cache<T> extends Subject<T> {\n private _src: Observable<T> \| null = null;\n private _src_sub: Subscription \| null = null;\n\n constructor(obs?: Observable<T>) {\n super();\n if(obs !== undefined) this.attach(obs);\n }\n\n public attach(obs: Observable<T> \| null): void {\n if(this.closed) throw new TypeError(\"obs.Cache closed\");\n this._src = null;\n this.onDetach();\n if(obs !== null) {\n this._src = obs;\n if(!this.isEmpty()) this.onAttach();\n }\n }\n\n public reset(): void {\n if(this._src_sub === null) return;\n this.onDetach();\n this.onAttach();\n }\n\n protected onAttach(): void {\n if(this._src === null) return;\n if(this._src_sub !== null) return;\n const sub = this._src.subscribe(this);\n this._src_sub = sub;\n sub.start();\n }\n\n protected onDetach(): void {\n if(this._src_sub === null) return;\n const sub = this._src_sub;\n this._src_sub = null;\n if(this.closed) this._src = null;\n sub.stop();\n }\n}\n" }, { "alpha_fraction": 0.5164554119110107, "alphanum_fraction": 0.5191238522529602, "avg_line_length": 25.45294189453125, "blob_id": "603fd4184cbf67da833b749b9756b3e16691ecc0", "content_id": "810cd0c99b2cbc84bd33b2152b2b4b841d37d925", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 8994, "license_type": "no_license", "max_line_length": 93, "num_lines": 340, "path": "/client/src/exec/work-dispatcher.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import Deque from \"double-ended-queue\";\n\nimport * as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport * as workapi from \"./workapi\";\n\ntype Transferable = ArrayBuffer \| MessagePort;\n\nexport interface Callbacks {\n onStart(): void;\n onError(e: Error): void;\n onDone(out: workapi.OutResult): void;\n onControl(data: workapi.OutControl): boolean;\n}\n\nexport interface Controller {\n sendControl(data: workapi.InControl, transfer: Transferable[]): void;\n kill(e: Error): void;\n}\n\ninterface Work {\n cb: Callbacks \| null;\n input: workapi.InWork \| null;\n transfer: Transferable[] \| null;\n worker: Thread \| null;\n}\n\nclass Thread {\n public readonly st: stat.Sink;\n\n public readonly w: Worker;\n\n private work: Work \| null = null;\n\n public onDead: (graceful: boolean) => void = () => {};\n public onReady: () => void = () => {};\n\n constructor(st: stat.Sink, body: Blob) {\n this.st = st;\n const url = URL.createObjectURL(body);\n try {\n this.w = new Worker(url);\n } finally {\n URL.revokeObjectURL(url);\n }\n this.w.onerror = (e) => {\n this.kill(\"Worker error: \" + e.message);\n };\n this.w.onmessage = (event: MessageEvent) => {\n try {\n this.onMessage(event.data);\n } catch(e) {\n this.kill(new err.Runtime(\"Worker message caused exception\", {\n cause: err.dataOf(e),\n }));\n }\n };\n }\n\n private send(data: workapi.In, transfer: Transferable[] \| undefined) {\n this.w.postMessage(data, transfer);\n }\n\n public setWork(work: Work) {\n try {\n this.send({work: work.input!}, work.transfer!);\n } catch(e) {\n this.kill(\"Failed to send message\");\n throw e;\n }\n this.work = work;\n work.input = null;\n work.transfer = null;\n work.worker = this;\n work.cb!.onStart();\n }\n\n public sendControl(data: workapi.InControl, transfer?: Transferable[]) {\n this.send({control: data}, transfer);\n }\n\n public kill(e: Error \| string) {\n if(typeof e === \"string\") {\n e = new err.Runtime(e);\n }\n\n const cb = this.finWork();\n this.stop(false);\n if(cb === null) {\n this.st.reportError(e);\n } else {\n cb.onError(e);\n }\n }\n\n public stop(graceful: boolean) {\n console.assert(this.work === null);\n this.w.terminate();\n this.onDead(graceful);\n }\n\n public finWork(): Callbacks \| null {\n const work = this.work;\n if(work === null) return null;\n this.work = null;\n\n const cb = work.cb!;\n work.cb = null;\n work.worker = null;\n return cb;\n }\n\n private onError(e: Error) {\n const cb = this.finWork();\n if(cb === null) {\n this.kill(\"Worker sent result without work\");\n return;\n }\n cb.onError(e);\n }\n\n private onResult(data: workapi.OutResult) {\n const cb = this.finWork();\n if(cb === null) {\n this.kill(\"Worker sent result without work\");\n return;\n }\n cb.onDone(data);\n }\n\n private onMessage(data: workapi.Out) {\n if(data.control !== undefined) {\n const work = this.work;\n if(work && work.cb!.onControl(data.control)) return;\n this.kill(\"Worker sent unknown control message\");\n return;\n }\n\n if(data.result !== undefined) {\n this.onResult(data.result);\n } else if(data.error) {\n this.onError(err.fromData(data.error));\n } else {\n this.kill(\"Worker sent invalid message\");\n return;\n }\n\n this.onReady();\n }\n}\n\nclass WorkController implements Controller {\n constructor(private _work: Work) {}\n\n public sendControl(data: workapi.InControl, transfer: Transferable[]): boolean {\n const work = this._work;\n const wrk = work.worker;\n if(wrk === null) return false;\n wrk.sendControl(data, transfer);\n return true;\n }\n\n public kill(e: Error): void {\n const work = this._work;\n let cb: Callbacks \| null;\n\n const wrk = work.worker;\n if(wrk !== null) {\n cb = wrk.finWork();\n console.assert(cb !== null);\n wrk.stop(false);\n cb!.onError(e);\n return;\n }\n\n cb = work.cb;\n if(cb !== null) {\n work.cb = null;\n cb.onError(e);\n return;\n }\n }\n}\n\nexport class Dispatcher {\n private readonly st_work = new stat.Metric(\n \"work_dispatcher/work_queue_size\"\n ).attach(this.st);\n private readonly st_workers = new stat.Metric(\n \"work_dispatcher/workers\"\n ).attach(this.st);\n private readonly st_workers_free = new stat.Metric(\n \"work_dispatcher/workers_free\"\n ).attach(this.st);\n private readonly st_workers_started = new stat.Counter(\n \"work_dispatcher/workers_started\"\n ).attach(this.st);\n private readonly st_workers_stopped = new stat.Counter(\n \"work_dispatcher/workers_stopped\", {\"graceful\": true}\n ).attach(this.st);\n private readonly st_workers_killed = new stat.Counter(\n \"work_dispatcher/workers_stopped\", {\"graceful\": false}\n ).attach(this.st);\n\n private readonly workers = new Set<Thread>();\n private workers_free: Thread[] = [];\n\n private readonly work = new Deque<Work>();\n\n private paused: number = 0;\n\n constructor(\n private readonly st: stat.Sink,\n private readonly worker_body: Blob\n ) {}\n\n public report() {\n this.st_work.set(this.work.length);\n this.st_workers.set(this.workers.size);\n this.st_workers_free.set(this.workers_free.length);\n }\n\n public get max_workers(): number {\n const w = (self.navigator.hardwareConcurrency \| 0) - 1;\n if(w < 1) return 1;\n if(w > 128) return 128;\n return w;\n }\n\n private kill_timer: number \| null = null;\n private addWorker() {\n const wrk = new Thread(this.st, this.worker_body);\n\n this.st_workers_started.inc();\n\n wrk.onReady = () => {\n console.assert(this.workers.has(wrk));\n console.assert(this.workers_free.indexOf(wrk) === -1);\n\n if(this.workers.size > this.max_workers) {\n wrk.stop(true);\n return;\n }\n\n this.workers_free.push(wrk);\n this.pull();\n this.report();\n };\n\n wrk.onDead = (normal: boolean) => {\n const i = this.workers_free.indexOf(wrk);\n if(i !== -1) this.workers_free.splice(i, 1);\n console.assert(this.workers.delete(wrk));\n\n if(normal) {\n this.st_workers_stopped.inc();\n } else {\n this.st_workers_killed.inc();\n }\n\n if(!this.work.isEmpty() && this.workers.size < this.max_workers) {\n this.addWorker();\n }\n\n this.report();\n };\n\n this.workers.add(wrk);\n wrk.onReady();\n }\n\n public push(cb: Callbacks, input: workapi.InWork, transfer: Transferable[]): Controller {\n const work: Work = {\n cb: cb,\n input: input,\n transfer: transfer,\n worker: null,\n };\n\n this.work.push(work);\n this.pull();\n this.report();\n\n return new WorkController(work);\n }\n\n private pull_scheduled: boolean = false;\n private pull(): void {\n if(this.pull_scheduled) return;\n this.pull_scheduled = false;\n self.setTimeout(() => this.doPull(), 0);\n }\n\n private doPull(): void {\n this.pull_scheduled = false;\n if(this.paused > 0) return;\n\n while(this.workers_free.length !== 0) {\n const w = this.work.dequeue();\n if(w === undefined) {\n this.startKillTimer();\n break;\n }\n if(w.cb === null) continue;\n const wrk = this.workers_free.pop()!;\n wrk.setWork(w);\n }\n\n if(this.workers.size < this.max_workers) {\n this.addWorker();\n }\n\n this.report();\n }\n\n private startKillTimer(): void {\n if(this.kill_timer !== null) return;\n const tm = self.setInterval(() => {\n const wrk = this.workers_free.pop();\n if(wrk === undefined) {\n self.clearInterval(tm);\n this.kill_timer = null;\n } else {\n wrk.stop(true);\n }\n }, 1000);\n this.kill_timer = tm;\n }\n\n public pause(resume: Promise<void>): void {\n this.paused += 1;\n resume.finally(() => {\n this.paused -= 1;\n if(this.paused === 0) {\n this.pull();\n }\n });\n }\n}\n" }, { "alpha_fraction": 0.6096408367156982, "alphanum_fraction": 0.6209830045700073, "avg_line_length": 23.952381134033203, "blob_id": "202ba9463351092f0e4ada1f0d76774d2a248d09", "content_id": "4ce16f0d6401f74df2d09732b851d221d805a5f9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1058, "license_type": "no_license", "max_line_length": 96, "num_lines": 42, "path": "/testCustomer/graphing/graphTest.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "# Automated tests for graph drawing\nimport sys\nfrom serverRequest import \nimport time\nimport random, string\n\n\nVERBOSE = True # Set to true if you want all data to be printed\nPROJECT_NAME = \"Project\"\n\ndef test(res, testname):\n (succ, data) = res\n time.sleep(0.1)\n if succ:\n print(testname + \" AOK\")\n if VERBOSE:\n print(data)\n return data \n else:\n print(testname + \" FAILED\")\n if VERBOSE:\n print(data)\n sys.exit(str(data))\n\n\ntokenlist = []\n\nwhile True:\n time.sleep(random.randint(1,3)/2)\n print(\"Registering new user\")\n username = ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(10))\n\n test(registerWorker(username, \"hunter2\"), \"testRegisterWorker\")\n wtok = test(login(username, \"hunter2\", \"worker\"), \"testLogin\")[\"token\"]\n tokenlist.append(wtok)\n\n# Worker tests\n getTasks(wtok, PROJECT_NAME, 1)\n\n if random.randint(0,1):\n print(\"Logging off new user\")\n test(logout(tokenlist.pop()), \"testLogout\")\n \n\n" }, { "alpha_fraction": 0.5718673467636108, "alphanum_fraction": 0.5737100839614868, "avg_line_length": 26.133333206176758, "blob_id": "e70e4bcb8490d68f372552edfecddbcd690a0cba", "content_id": "acd84dec69ba4faca8e78d1bcc2fece02557eeb9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 3256, "license_type": "no_license", "max_line_length": 86, "num_lines": 120, "path": "/client/src/exec/runner-state.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import as cbor from \"@/cbor\";\nimport * as cbut from \"@/cbor-util\";\n\nimport * as api from \"./api\";\nimport {Ref} from \"./storage\";\n\nexport interface TaskData {\n id: string;\n project: string;\n program: Ref;\n\n in_control: Uint8Array;\n in_blobs: Ref[];\n\n out_status?: string;\n out_data?: Ref[];\n out_error?: api.ErrorData;\n}\n\nexport interface RunnerData {\n state_key: string;\n tasks: TaskData[];\n}\n\nexport function loadState(data: Uint8Array): RunnerData {\n const d: Partial<RunnerData> = {};\n const r = new cbor.Reader(data);\n\n r.map();\n while(true) {\n const key = r.maybeString();\n if(key === null) break;\n\n if(key === \"tasks\") d.tasks = cbut.readArray(r, readTaskData);\n else if(key === \"state_key\") d.state_key = r.string();\n else r.skip();\n }\n r.end();\n\n if(d.state_key === undefined) throw new TypeError(\"Missing RunnerData.state_key\");\n if(d.tasks === undefined) throw new TypeError(\"Missing RunnerData.tasks\");\n\n return d as RunnerData;\n}\n\nfunction readRef(r: cbor.Reader): Ref {\n r.array();\n const id = r.string();\n const size = r.uint();\n r.end();\n return {id: id, size: size};\n}\n\nfunction readTaskData(r: cbor.Reader): TaskData {\n const d: Partial<TaskData> = {};\n\n r.map();\n while(true) {\n const key = r.maybeString();\n if(key === null) break;\n\n if(key === \"id\") d.id = r.string();\n else if(key === \"project\") d.project = r.string();\n else if(key === \"program\") d.program = readRef(r);\n else if(key === \"in_control\") d.in_control = cbut.own(r.bytes());\n else if(key === \"in_blobs\") d.in_blobs = cbut.readArray(r, readRef);\n else if(key === \"out_status\") d.out_status = r.string();\n else if(key === \"out_data\") d.out_data = cbut.readArray(r, readRef);\n else if(key === \"out_error\") d.out_error = cbut.readError(r);\n else r.skip();\n }\n r.end();\n\n if(\n d.id === undefined \|\| d.project === undefined \|\| d.program === undefined \|\|\n d.in_control === undefined \|\| d.in_blobs === undefined\n ) throw new TypeError(\"Invalid task\");\n\n return d as TaskData;\n}\n\nfunction writeRef(w: cbor.Writer, d: Ref) {\n w.array(2);\n w.string(d.id);\n w.uint(d.size);\n w.end();\n}\n\nfunction writeTaskData(w: cbor.Writer, d: TaskData): void {\n w.map();\n w.string(\"id\"); w.string(d.id);\n w.string(\"project\"); w.string(d.project);\n w.string(\"program\"); writeRef(w, d.program);\n w.string(\"in_control\"); w.bytes(new Uint8Array(d.in_control));\n w.string(\"in_blobs\"); cbut.writeArray(w, writeRef, d.in_blobs);\n if(d.out_status !== undefined) {\n w.string(\"out_status\");\n w.string(d.out_status);\n }\n if(d.out_data !== undefined) {\n w.string(\"out_data\");\n cbut.writeArray(w, writeRef, d.out_data);\n }\n if(d.out_error !== undefined) {\n w.string(\"out_error\");\n cbut.writeError(w, d.out_error);\n }\n w.end();\n}\n\nexport function dumpState(d: RunnerData): Uint8Array {\n const w = new cbor.Writer();\n w.map(2);\n w.string(\"state_key\");\n w.string(d.state_key);\n w.string(\"tasks\");\n cbut.writeArray(w, writeTaskData, d.tasks);\n w.end();\n return w.done();\n}\n" }, { "alpha_fraction": 0.6234718561172485, "alphanum_fraction": 0.6320293545722961, "avg_line_length": 25.354839324951172, "blob_id": "71d4fcf78ff5b4f5c57c84ffe9b599a13ceab52f", "content_id": "902c7c32d195bf4a590836b9104feab93947c868", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 818, "license_type": "no_license", "max_line_length": 92, "num_lines": 31, "path": "/server/servertests/newWorker.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "## Automated tests for the server\nimport sys\nfrom tests import \nimport time\nimport random, string\n\nusername = ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(10))\n\nVERBOSE = True # Set to true if you want all data to be printed\n\ndef test(res, testname):\n (succ, data) = res\n time.sleep(0.1)\n if succ:\n print(testname + \" AOK\")\n if VERBOSE:\n print(data)\n return data \n else:\n print(testname + \" FAILED\")\n if VERBOSE:\n print(data)\n sys.exit(str(data))\n\n# Start test\ntest(testPing(), \"testPing\")\ntest(registerWorker(username, \"hunter2\"), \"testRegisterWorker\")\nwtok = test(login(username, \"hunter2\", \"worker\"), \"testLogin\")[\"token\"]\n\n# Worker tests\ndata = test(getTasks(wtok, \"Project\", 2), \"testGetTasks\")\n\n" }, { "alpha_fraction": 0.45701631903648376, "alphanum_fraction": 0.4737266004085541, "avg_line_length": 25.00523567199707, "blob_id": "3b1c2574c02803e10a11e4402fa512aafcc3b898", "content_id": "0a199227770e5ee114ed449fc40139fb7a6103f7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 4967, "license_type": "no_license", "max_line_length": 110, "num_lines": 191, "path": "/client/src/exec/tests/repo.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport {asyncSleep, releaser, runTests, withStat} from \"../test-util\";\n\nimport MemStorage from \"../mem_storage\";\nimport MockAPI from \"../mock_api\";\n\nimport {BlobRepo} from \"../repo\";\nimport {Ref} from \"../storage\";\n\nfunction ref(size: number, ix: number): Ref {\n return {\n id: `remote/${size}/${ix}`,\n size: size,\n };\n}\n\nfunction env(): <T>(wrapped: (the_repo: BlobRepo, the_api: MockAPI) => Promise<T>) => Promise<T> {\n const the_api = new MockAPI(null);\n for(let size = 1; size < 100; size += 1) {\n const data = new Uint8Array(size);\n for(let ix = 0; ix < 100; ix += 1) {\n the_api.blobs.set(`${size}/${ix}`, data);\n }\n }\n\n const the_storage = new MemStorage();\n\n return <T>(wrapped: (the_repo: BlobRepo, the_api: MockAPI) => Promise<T>) => withStat((st: stat.Sink) => {\n return BlobRepo.create(st, the_api, the_storage).then((the_repo) => {\n return wrapped(the_repo, the_api);\n });\n });\n}\n\nasync function testRepoCreateEmpty(): Promise<void> {\n const wrap = env();\n await wrap(async (repo, api) => {});\n}\n\nasync function testRepoDownload(): Promise<void> {\n const wrap = env();\n await wrap(async (repo, api) => {\n await repo.withBlobs<void>(\n [ref(1, 0), ref(1, 1), ref(2, 0)],\n async () => {},\n );\n if(repo.cache_used !== 4) {\n throw new Error(`Expected 4 bytes used, got ${repo.cache_used}`);\n }\n\n await repo.withBlobs<void>(\n [ref(1, 1)],\n async () => {},\n );\n if(repo.cache_used !== 4) {\n throw new Error(`Expected 4 bytes used, got ${repo.cache_used}`);\n }\n\n await repo.withBlobs<void>(\n [ref(1, 0), ref(2, 1)],\n async () => {},\n );\n // BUG: TypeScript doesn't know that await is asynchronous.\n if(repo.cache_used as number !== 6) {\n throw new Error(`Expected 6 bytes used, got ${repo.cache_used}`);\n }\n });\n}\n\nasync function testRepoLimit(): Promise<void> {\n const wrap = env();\n await wrap(async (repo, api) => {\n api.cache_max = 10;\n try {\n await repo.withBlobs<void>(\n [ref(5, 0), ref(6, 0)],\n async () => {},\n );\n throw new Error(`Expected 11-byte download to fail when the limit is 10`);\n } catch(e) {\n if(!(e instanceof err.Cancelled)) throw e;\n }\n });\n}\n\nasync function testRepoEvict(): Promise<void> {\n const wrap = env();\n await wrap(async (repo, api) => {\n api.cache_max = 10;\n\n repo.withBlobs<void>(\n [ref(4, 0)],\n async () => {\n await asyncSleep(200);\n },\n );\n\n const [pr_release, release] = releaser();\n\n let expecting = 2;\n const [pr_go, go] = releaser();\n\n repo.withBlobs<void>(\n [ref(4, 1)],\n () => {\n expecting -= 1;\n if(expecting === 0) go();\n return pr_release;\n }\n );\n\n repo.withBlobs<void>(\n [ref(4, 2)],\n () => {\n expecting -= 1;\n if(expecting === 0) go();\n return pr_release;\n }\n );\n\n await pr_go;\n\n if((repo.storage as MemStorage).blobs.get(ref(4, 0).id) !== undefined) {\n throw new Error(\"Expected remote/4/0 to have been evicted\");\n }\n\n let done: number = 0;\n\n const [pr_cancel, cancel] = releaser();\n\n const pr1 = repo.withBlobs<void>(\n [ref(4, 0)],\n async () => {\n done += 1;\n },\n pr_cancel.then(() => new err.Cancelled(\"Request cancelled\")),\n );\n\n const pr2 = repo.withBlobs<void>(\n [ref(1, 0)],\n async () => {\n done += 1;\n },\n );\n\n const pr3 = repo.withBlobs<void>(\n [ref(4, 0)],\n async () => {\n done += 1;\n },\n );\n\n await asyncSleep(200);\n if(done !== 0) {\n throw new Error(\"Expected blocked download to block the following ones\");\n }\n\n cancel();\n\n try {\n await pr1;\n throw new Error(\"Expected request to be cancelled\");\n } catch(e) {\n if(!(e instanceof err.Cancelled)) throw e;\n }\n\n await pr2;\n\n await asyncSleep(200);\n // BUG: TypeScript doesn't know that await is asynchronous.\n if(done as number !== 1) {\n throw new Error(\"Expected over-limit download to block\");\n }\n\n release();\n await pr3;\n });\n}\n\nself.onload = () => {\n runTests([\n testRepoCreateEmpty,\n testRepoDownload,\n testRepoLimit,\n testRepoEvict,\n ]);\n};\n" }, { "alpha_fraction": 0.41983282566070557, "alphanum_fraction": 0.4301861822605133, "avg_line_length": 30.2403564453125, "blob_id": "045558193db88b7a1e87acb5eb2291656fe1d4b5", "content_id": "37cf60c1681471f528474b05b904865d18c76b53", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 10528, "license_type": "no_license", "max_line_length": 117, "num_lines": 337, "path": "/client/src/exec/tests/work-dispatcher.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport * as err from \"@/err\";\nimport * as stat from \"@/stat\";\n\nimport {asyncSleep, releaser, runTests, withStat} from \"../test-util\";\n\nimport * as wd from \"../work-dispatcher\";\nimport * as workapi from \"../workapi\";\n\nconst test_worker = new Blob([`\nlet onControl = null;\nlet work_name = null;\nlet work_data = null;\nlet work_i = null;\nfunction onWork() {\n while(work_i < work_data.length) {\n const cmd = work_data[work_i];\n work_i += 1;\n if(cmd === \"done\") {\n postMessage({result: {\n control: new Uint8Array(0),\n data: [],\n }});\n } else if(cmd === \"fail\") {\n postMessage({error: {\n kind: \"validation\",\n message: \"Test task failed\",\n }});\n } else if(cmd == \"error\") {\n throw new Error(\"Test task error\");\n } else if(cmd == \"started\") {\n postMessage({control: {notify_started: null}});\n } else if(cmd == \"sleep\") {\n const timeout = Number(work_data[work_i]);\n work_i += 1;\n setTimeout(onWork, timeout);\n return;\n } else if(cmd == \"loop\") {\n while(true) {}\n } else if(cmd == \"req-blob\") {\n const name = work_data[work_i];\n postMessage({control: {get_blob: {id: name, size: 1}}});\n } else if(cmd == \"get-blob\") {\n const name = work_data[work_i];\n onControl = (ctl) => {\n if(!ctl.get_blob) throw new Error(\"Expected get_blob input\");\n if(ctl.get_blob[0] !== name) throw new Error(\"Expected different get_blob name\");\n onControl = null;\n onWork();\n };\n return;\n }\n }\n work_name = null;\n work_data = null;\n work_i = null;\n}\n\nonmessage = (event) => {\n const msg = event.data;\n if(msg.work) {\n if(work_name != null) throw new Error(\"Task already running\");\n work_name = msg.work.program.id;\n work_data = msg.work.data.map((ref) => ref.id);\n work_i = 0;\n onWork();\n } else if(msg.control) {\n onControl(msg.control)\n }\n}`]);\n\nfunction withWD<T>(f: (d: wd.Dispatcher) => Promise<T>): Promise<T> {\n return withStat((st: stat.Sink) => {\n return f(new wd.Dispatcher(st, test_worker));\n });\n}\n\nfunction task(name: string, ...steps: string[]): workapi.InWork {\n return {\n program: {id: name, size: 0},\n control: new Uint8Array(0),\n data: steps.map((s) => ({id: s, size: 0})),\n };\n}\n\nfunction testTask() {\n return withWD<void>(async (d) => {\n const [prFail, fail] = releaser<Error>();\n const [pr0, res0] = releaser();\n const [pr1, res1] = releaser();\n const [pr2, res2] = releaser();\n\n d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n res0();\n },\n onError(e: Error) {\n fail(e);\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, task(\"ok\", \"done\"), []);\n\n d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n fail(new Error(\"Expected task to fail\"));\n },\n onError(e: Error) {\n if(!(e instanceof err.Validation)) fail(e);\n else res1();\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, task(\"fail\", \"fail\"), []);\n\n d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n fail(new Error(\"Expected task to error\"));\n },\n onError(e: Error) {\n if(!(e instanceof err.Runtime)) fail(e);\n else res2();\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, task(\"error\", \"error\"), []);\n\n await Promise.race([prFail.then((e) => {throw e;}), Promise.all([\n pr0, pr1, pr2,\n ])]);\n });\n}\n\nfunction testControl() {\n return withWD<void>(async (d) => {\n const [prFail, fail] = releaser<Error>();\n const [pr0, res0] = releaser();\n const [pr1, res1] = releaser();\n const [pr2, res2] = releaser();\n\n let notified = false;\n d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n if(!notified) {\n fail(new Error(\"Expected task to send notify_started\"));\n }\n res0();\n },\n onError(e: Error) {\n fail(e);\n },\n onControl(out: workapi.OutControl) {\n if(out.notify_started !== undefined) {\n notified = true;\n return true;\n }\n return false;\n },\n }, task(\"control-notify_started\", \"started\", \"done\"), []);\n\n d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n fail(new Error(\"Expected task to be killed\"));\n },\n onError(e: Error) {\n if(!(e instanceof err.Runtime)) fail(e);\n else res1();\n },\n onControl(out: workapi.OutControl) {\n console.log(\"kill\");\n return false;\n },\n }, task(\"control-fail\", \"req-blob\", \"1\", \"get-blob\", \"done\"), []);\n\n let state = 0;\n const ctl2 = d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n if(state !== 3) fail(new Error(\"Expected task to request blobs\"));\n res2();\n },\n onError(e: Error) {\n fail(e);\n },\n onControl(out: workapi.OutControl) {\n if(out.get_blob !== undefined) {\n if(state === 0) {\n if(out.get_blob.id !== \"1\") fail(new Error(\"Expected different request\"));\n state = 1;\n } else if(state === 1) {\n if(out.get_blob.id !== \"2\") fail(new Error(\"Expected different request\"));\n state = 2;\n self.setTimeout(() => {\n ctl2.sendControl({get_blob: [\"2\", new Uint8Array(0)]}, []);\n ctl2.sendControl({get_blob: [\"1\", new Uint8Array(0)]}, []);\n state = 3;\n }, 200);\n } else {\n fail(new Error(\"Too many requests\"));\n }\n return true;\n }\n return false;\n },\n }, task(\"control-get_blob\", \"req-blob\", \"1\", \"req-blob\", \"2\", \"get-blob\", \"2\", \"get-blob\", \"1\", \"done\"), []);\n\n await Promise.race([prFail.then((e) => {throw e;}), Promise.all([\n pr0, pr1, pr2,\n ])]);\n });\n}\n\nfunction testCancel() {\n return withWD<void>(async (d) => {\n const [prFail, fail] = releaser<Error>();\n const [pr0, res0] = releaser();\n const [pr1, res1] = releaser();\n const [pr2, res2] = releaser();\n\n const ctl0 = d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n res0();\n },\n onError(e: Error) {\n fail(e);\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, task(\"ok\", \"done\"), []);\n\n const ctl1 = d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n fail(new Error(\"Expected cancellation\"));\n },\n onError(e: Error) {\n if(!(e instanceof err.Cancelled)) fail(e);\n else res1();\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, task(\"hang\"), []);\n\n const ctl2 = d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n fail(new Error(\"Expected cancellation\"));\n },\n onError(e: Error) {\n if(!(e instanceof err.Cancelled)) fail(e);\n else res2();\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, task(\"immediate-cancel\", \"done\"), []);\n\n self.setTimeout(() => {\n ctl0.kill(new err.Cancelled(\"Cancelled 0\"));\n ctl1.kill(new err.Cancelled(\"Cancelled 1\"));\n }, 200);\n\n ctl2.kill(new err.Cancelled(\"Cancelled 2\"));\n\n await Promise.race([prFail.then((e) => {throw e;}), Promise.all([\n pr0, pr1, pr2,\n ])]);\n });\n}\n\nfunction testPauseResume() {\n return withWD<void>(async (d) => {\n const [prFail, fail] = releaser<Error>();\n\n const prs: Array<Array<Promise<void>>> = [[], []];\n for(let s = 0; s < 2; s += 1) {\n for(let i = 0; i < d.max_workers; i += 1) {\n const [pr, done] = releaser();\n prs[s].push(pr);\n d.push({\n onStart() {},\n onDone(res: workapi.OutResult) {\n done();\n },\n onError(e: Error) {\n fail(e);\n },\n onControl(out: workapi.OutControl) {\n return false;\n },\n }, s === 0 ? task(\"sleepy\", \"sleep\", \"200\", \"done\") : task(\"immediate\", \"done\"), []);\n }\n }\n\n let prs1Done = false;\n Promise.all(prs[1]).then(() => {\n prs1Done = true;\n });\n\n await Promise.race([prFail.then((e) => {throw e;}), async () => {\n const [prResume, resume] = releaser<void>();\n await asyncSleep(100);\n d.pause(prResume);\n await Promise.all(prs[0]);\n await asyncSleep(200);\n if(prs1Done) {\n throw new Error(\"Expected worker to be paused\");\n }\n resume();\n await asyncSleep(100);\n if(!prs1Done) {\n throw new Error(\"Expected worker to be paused\");\n }\n }]);\n });\n}\n\nself.onload = () => {\n runTests([\n testTask,\n testControl,\n testCancel,\n testPauseResume,\n ]);\n};\n" }, { "alpha_fraction": 0.6585662364959717, "alphanum_fraction": 0.6695018410682678, "avg_line_length": 24.71875, "blob_id": "b1b809f2ed468b7cf8f9be0538679a78e0adcdf9", "content_id": "410e1558fba55596ce79cf96f0c6b58912f85a84", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1646, "license_type": "no_license", "max_line_length": 77, "num_lines": 64, "path": "/doc/client-program-abi.md", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "ABI for client programs, version 1\n===\n\nThe program provided by the client receives the following inputs:\n\n - A short bytestring, called `control`, provided in the task metadata.\n - A list of bytestrings corresponding to the contents of the input blobs.\n\nThe outputs are:\n\n - A short bytestring, called `control`, part of the output metadata.\n - A list of bytestrings, which will be available as blobs on the server.\n\nThe program must be provided as a 32-bit WebAssembly binary with the follwing\ninterface:\n\nImports\n---\n env: {\n void pptw1_abort(char)\n Aborts program execution. The argument is NULL or a pointer to the\n error message.\n\n void pptw1_print(char, size_t)\n Print a message with the given length to the console. Similar to\n (void) write(STDERR_FILENO, msg, len)\n }\n\nExports\n---\n memory\n The program's linear memory.\n\n void pptw1_init(void)\n Called when the program is started.\n\n void pptw1_cleanup(void)\n Called when the program is stopped.\n\n char pptw1_malloc(size_t)\n Allocates memory of the given size and returns pointer (offset into\n `memory`).\n\n pptw1_response pptw1_run(pptw1_request)\n Runs a task. The request's blobs, as well as the request object itself,\n have been allocated using pptw1_malloc().\n\nTypes\n---\n struct pptw1_blobref {\n void data;\n size_t size;\n };\n\n struct pptw1_request {\n struct pptw1_blobref control;\n size_t n_blobs;\n struct pptw1_blobref blobs[n_blobs];\n };\n\n struct pptw1_response {\n size_t n_blobs;\n struct pptw1_blobref blobs[n_blobs];\n };\n" }, { "alpha_fraction": 0.47460755705833435, "alphanum_fraction": 0.4759926199913025, "avg_line_length": 27.5, "blob_id": "d995ca7fe673cbd22faebdb9f31a4101417e7a73", "content_id": "ee293bccc005debf9fa1df2d6d500241c3931790", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 2166, "license_type": "no_license", "max_line_length": 99, "num_lines": 76, "path": "/client/src/cbor-util.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import * as cbor from \"@/cbor\";\nimport * as err from \"@/err\";\n\nexport function readArray<T>(r: cbor.Reader, f: (r: cbor.Reader) => T): T[] {\n const l: T[] = [];\n r.array();\n while(r.hasNext()) {\n l.push(f(r));\n }\n r.end();\n return l;\n}\n\nexport function writeArray<T>(w: cbor.Writer, f: (w: cbor.Writer, d: T) => void, d: T[]): void {\n w.array(d.length);\n for(const v of d) f(w, v);\n w.end();\n}\n\nexport function readError(r: cbor.Reader): err.Data {\n const d: Partial<err.Data> = {};\n r.map();\n while(true) {\n const k = r.maybeString();\n if(k === null) break;\n\n let v: string \| number \| boolean \| err.Data \| undefined;\n if(k === \"kind\" \|\| k === \"message\") {\n v = r.string();\n } else if(k === \"cause\") {\n try {\n v = readError(r);\n } catch(e) {\n if(!(e instanceof TypeError)) throw e;\n v = undefined;\n }\n } else {\n if(r.isString()) v = r.string();\n else if(r.isNumber()) v = r.number();\n else if(r.isSimple()) {\n const s = r.simple();\n if(s === cbor.SIMPLE_TRUE) v = true;\n else if(s === cbor.SIMPLE_FALSE) v = true;\n else v = undefined;\n } else {\n r.skip();\n v = undefined;\n }\n }\n d[k] = v;\n }\n r.end();\n\n if(d[\"kind\"] === undefined \|\| d[\"message\"] === undefined) throw new TypeError(\"Invalid error\");\n return d as err.Data;\n}\n\nexport function writeError(w: cbor.Writer, d: err.Data): void {\n const ks = Object.keys(d);\n w.map(ks.length);\n for(const k of ks) {\n w.string(k);\n const v = d[k];\n if(typeof v === \"undefined\") w.null();\n else if(typeof v === \"string\") w.string(v);\n else if(typeof v === \"number\") w.number(v);\n else if(typeof v === \"boolean\") w.boolean(v);\n else writeError(w, v);\n }\n w.end();\n}\n\nexport function own(d: Uint8Array): Uint8Array {\n if(d.byteOffset === 0 && d.byteLength === d.buffer.byteLength) return d;\n return d.slice();\n}\n" }, { "alpha_fraction": 0.41136229038238525, "alphanum_fraction": 0.42415228486061096, "avg_line_length": 27.252099990844727, "blob_id": "a886d95841cd28cf8631678553aae2c61cff5a88", "content_id": "d53cbaa02b4c3a2c942c5c2fd5a7fda486e1c395", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 3362, "license_type": "no_license", "max_line_length": 81, "num_lines": 119, "path": "/client/src/exec/tests/idb.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import \"@/polyfill\";\n\nimport {arrBuf, compare, runTests, withStat} from \"../test-util\";\n\nimport * as err from \"@/err\";\n\nimport IDBStorage from \"../idb_storage\";\n\nfunction withIDB<T>(name: string, f: (s: IDBStorage) => Promise<T>): Promise<T> {\n return withStat((the_stat) => IDBStorage.create(the_stat, name).then((s) => {\n return Promise.resolve(s).then(f).finally(() => s.stop());\n }));\n}\n\nconst data1 = arrBuf([1]);\nconst data2 = arrBuf([1,2]);\nconst data3 = arrBuf([1,2,3]);\n\nfunction testCreate() {\n return withIDB(\"test\", (s) => {\n return s.list().then((items) => {\n if(items.length !== 0) {\n throw new Error(\"Expected empty database\");\n }\n return;\n });\n });\n}\n\nfunction testReset() {\n return IDBStorage.delete(\"test\");\n}\n\nfunction testSet() {\n return withIDB(\"test\", (s) => {\n return s.set(\"key1\", new Uint8Array(data1)).then(\n () => s.set(\"key2\", new Uint8Array(data2))\n ).then(\n () => s.set(\"key2\", new Uint8Array(data3))\n );\n });\n}\n\nfunction testGet() {\n return withIDB(\"test\", (s) => {\n return s.get(\"key1\").then((data) => {\n compare(data, data1, \"\");\n }).then(\n () => s.get(\"key2\")\n ).then((data) => {\n compare(data, data3, \"\");\n }).then(() => {\n return s.get(\"key3\").then(() => {\n throw new Error(\"Expected `key3` not to exist\");\n }, (e) => {\n if(!(e instanceof err.State)) {\n throw new Error(\"Expected err.State for nonexistent blob\");\n }\n });\n }).then(() => s.list()).then((l) => {\n l.sort((a, b) => {\n if(a.id < b.id) return -1;\n if(a.id > b.id) return 1;\n return 0;\n });\n compare(l, [\n {id: \"key1\", size: data1.byteLength},\n {id: \"key2\", size: data3.byteLength},\n ], \"\");\n });\n });\n}\n\nfunction testDelete() {\n return withIDB(\"test\", (s) => {\n return s.delete(\"key3\").then(\n () => s.delete(\"key2\")\n ).then(\n () => s.delete(\"key2\")\n ).then(() => {\n return s.get(\"key2\").then(() => {\n throw new Error(\"Expected `key2` not to exist\");\n }, (e) => {\n if(!(e instanceof err.State)) {\n throw new Error(\"Expected err.State for nonexistent blob\");\n }\n });\n }).then(() => {\n return s.get(\"key1\").then(() => {\n return;\n }, (e) => {\n if(e instanceof err.State) {\n throw new Error(\"Expected `key1` to exist\");\n } else {\n throw e;\n }\n });\n }).then(() => s.list()).then((l) => {\n compare(l, [\n {id: \"key1\", size: data1.byteLength},\n ], \"\");\n }).then(() => s.delete(\"key1\")).then(() => s.list()).then((l) => {\n if(l.length !== 0) {\n throw new Error(\"Expected empty database\");\n }\n });\n });\n}\n\nself.onload = () => {\n runTests([\n testReset,\n testCreate,\n testSet,\n testGet,\n testDelete,\n testReset,\n ]);\n};\n" }, { "alpha_fraction": 0.5355029702186584, "alphanum_fraction": 0.5379394292831421, "avg_line_length": 23.767240524291992, "blob_id": "810d3efc64abce7d1b95c4f5549c294c277b813d", "content_id": "d040f6b9a9ff8ac05dd2b40e9698c347d644d338", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "TypeScript", "length_bytes": 5746, "license_type": "no_license", "max_line_length": 79, "num_lines": 232, "path": "/client/src/stat.ts", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "// Totally not Borgmon.\n\nimport * as err from \"./err\";\n\nexport declare interface Key {\n readonly [k: string]: string \| boolean;\n}\n\nexport type Point = [string, Key, number];\n\nexport interface TSDB {\n writeError(ts: number, data: err.Data): void;\n write(ts: number, data: Point[]): void;\n}\n\ninterface Base {\n readonly key: Key;\n readonly parent: Sink \| null;\n readonly root: Root \| null;\n readonly root_key: Key \| null;\n}\n\nexport interface Sink extends Base {\n readonly children: Set<Metric>;\n readonly direct_children: Set<Child>;\n\n reportError(e: Error): void;\n}\n\nexport class Root implements Sink {\n public readonly key: Key = {};\n public readonly parent = null;\n public readonly root = this;\n public readonly root_key: Key = {};\n public readonly direct_children = new Set<Metric>();\n public readonly children = new Set<Metric>();\n public readonly children_dirty = new Set<Metric>();\n public readonly tsdb: TSDB;\n\n constructor(tsdb: TSDB) {\n this.tsdb = tsdb;\n }\n\n private _dirty: boolean = false;\n public setDirty() {\n if(this._dirty) return;\n this._dirty = true;\n self.setTimeout(this._changed.bind(this), 50);\n }\n\n private _changed(): void {\n const now = new Date().getTime() / 1000;\n const cld = Array.from(this.children_dirty);\n this.children_dirty.clear();\n this._dirty = false;\n\n const data: Array<[string, Key, number]> = [];\n for(const c of cld) {\n if(c.value === undefined) continue;\n data.push([c.name, c.root_key!, c.value]);\n c.written();\n }\n this.tsdb.write(now, data);\n }\n\n public reportError(e: Error, key?: Key): void {\n const now = new Date().getTime() / 1000;\n this.tsdb.writeError(now, Object.assign({}, err.dataOf(e), key \|\| {}));\n }\n}\n\nclass Child implements Base {\n public readonly key: Key;\n\n private _parent: Sink \| null;\n private _root: Root \| null;\n private _root_key: Key \| null;\n\n constructor(key: Key) {\n this.key = key;\n this._parent = null;\n this._root = null;\n this._root_key = null;\n }\n\n get parent(): Sink \| null {\n return this._parent;\n }\n\n get root(): Root \| null {\n return this._root;\n }\n\n get root_key(): Key \| null {\n return this._root_key;\n }\n\n public attach(par: Sink \| null): this {\n const opar = this._parent;\n if(par === opar) return this;\n\n if(opar !== null) {\n opar.direct_children.delete(this);\n this.addChildren(opar.children);\n for(let p = opar.parent; p !== null; p = p.parent) {\n this.discardChildren(p.children);\n }\n }\n if(par !== null) {\n par.direct_children.add(this);\n this.addChildren(par.children);\n for(let p = par.parent; p !== null; p = p.parent) {\n this.addChildren(p.children);\n }\n }\n this._parent = par;\n\n const ort = this._root;\n if(ort !== null) this.discardChildren(ort.children_dirty);\n\n this.reroot();\n\n const rt = this._root;\n if(rt !== null) {\n this.addChildren(rt.children_dirty);\n rt.setDirty();\n }\n return this;\n }\n\n protected addChildren(s: Set<Metric>): void {}\n protected discardChildren(s: Set<Metric>): void {}\n\n public reroot() {\n const par = this._parent;\n if(par !== null) {\n const rt = par.root;\n if(rt !== null) {\n this._root = rt;\n this._root_key = Object.assign({}, this.key, par.root_key!);\n return;\n }\n }\n this._root = null;\n this._root_key = null;\n }\n}\n\nexport class Metric extends Child {\n public readonly name: string;\n\n constructor(name: string, key?: Key) {\n super(key \|\| {});\n this.name = name;\n }\n\n private _value: number \| undefined;\n\n public get value(): number \| undefined {\n return this._value;\n }\n\n public set(v: number): void {\n if(this._value !== v) {\n this._value = v;\n this._touch();\n }\n }\n\n private _touch(): void {\n const r = this.root;\n if(r === null) return;\n if(r.children_dirty.size === 0) {\n r.setDirty();\n }\n r.children_dirty.add(this);\n }\n\n public written(): void {}\n\n protected addChildren(s: Set<Metric>): void {\n s.add(this);\n }\n\n protected discardChildren(s: Set<Metric>): void {\n s.delete(this);\n }\n}\n\nexport class Group extends Child implements Sink {\n public readonly children: Set<Metric> = new Set();\n public readonly direct_children: Set<Child> = new Set();\n\n protected addChildren(s: Set<Metric>): void {\n for(const c of this.children) s.add(c);\n }\n\n protected discardChildren(s: Set<Metric>): void {\n for(const c of this.children) s.delete(c);\n }\n\n public reroot(): void {\n super.reroot();\n for(const c of this.direct_children) c.reroot();\n }\n\n public reportError(e: Error): void {\n const rt = this.root;\n if(rt !== null) {\n rt.reportError(e, this.root_key!);\n } else {\n console.error(`Unhandled exception: ${err.format(e)}`);\n }\n }\n}\n\nexport class Counter extends Metric {\n constructor(name: string, key?: Key) {\n super(name, key);\n this.reset();\n }\n\n public reset(): void {\n this.set(0);\n }\n\n public inc(v?: number): void {\n if(v === undefined) v = 1;\n else if(v <= 0 \|\| v !== v) return;\n this.set(this.value! + v);\n }\n}\n" }, { "alpha_fraction": 0.5301507711410522, "alphanum_fraction": 0.5502512454986572, "avg_line_length": 23.875, "blob_id": "2d6da1ab1c27dbadf44a928a3999b1435aea4ffc", "content_id": "3ed364f1fea0cbe128f320f0735818f281fe3970", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 398, "license_type": "no_license", "max_line_length": 59, "num_lines": 16, "path": "/githook/githook.py", "repo_name": "eddsalkield/DistributedPhone", "src_encoding": "UTF-8", "text": "import cherrypy, subprocess\n\nclass flashserver(object):\n @cherrypy.expose\n def default(self, args, *kwargs):\n subprocess.call(['./gitpull.sh'])\n return \"Success\"\n\nif __name__ == '__main__':\n cherrypy.config.update({'server.socket_host': '0.0.0.0',\n 'server.socket_port': 8081,\n })\n\n\n\n cherrypy.quickstart(flashserver())\n" } ]	52
SethForrest/empty_container	https://github.com/SethForrest/empty_container	ae698a661a2d15b992dfbee296e51cbe59a9339c	f025c57f66c145d5b17cfcdf2a2dbd4d5221e5f5	ddcb6dfbb3cdc70fc2382107a1e9de057b531d7c	refs/heads/master	2020-07-08T12:43:39.569437	2019-08-21T22:58:05	2019-08-21T22:58:05	203,675,555	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.701886773109436, "alphanum_fraction": 0.7094339728355408, "avg_line_length": 16.928571701049805, "blob_id": "029db746e7ed60f6128723d7bba7e1cf8c41e3d4", "content_id": "558850517d4be1ae5644abc5b1419f95e3381e9c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Dockerfile", "length_bytes": 265, "license_type": "no_license", "max_line_length": 47, "num_lines": 14, "path": "/app/Dockerfile", "repo_name": "SethForrest/empty_container", "src_encoding": "UTF-8", "text": "# Define what enviroment you want\r\nFROM python:3.7\r\n\r\n# working directory\r\nWORKDIR /app\r\n\r\n# copies top level stuff into working directory\r\nCOPY . /app\r\n\r\n# Install requirements\r\nRUN pip install -r requirements.txt\r\n\r\n# Run the program\r\nCMD [\"python\", \"myApp.py\"]\r\n" }, { "alpha_fraction": 0.4326923191547394, "alphanum_fraction": 0.4326923191547394, "avg_line_length": 12.571428298950195, "blob_id": "140c63c288450f6eef14a2c761888617ac23b5ef", "content_id": "1e626a92b486402c541054aa527b6133eab15e8c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 104, "license_type": "no_license", "max_line_length": 24, "num_lines": 7, "path": "/app/myApp.py", "repo_name": "SethForrest/empty_container", "src_encoding": "UTF-8", "text": "\r\ndef main():\r\n print(\"Hello There\")\r\n print(\"General Kenobi\")\r\n\r\n\r\nif __name__=='__main__':\r\n main()\r\n" }, { "alpha_fraction": 0.5222222208976746, "alphanum_fraction": 0.5222222208976746, "avg_line_length": 15.399999618530273, "blob_id": "60cb31e81a511db0a8c86c967f2f976c3e93e070", "content_id": "a214d9fb8177d51266aa0ee3e88d498e0aae99c5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 180, "license_type": "no_license", "max_line_length": 35, "num_lines": 10, "path": "/README.md", "repo_name": "SethForrest/empty_container", "src_encoding": "UTF-8", "text": "\r\n\r\n\r\n<!-- #### Build Container\r\n- `docker build --tag=<app_name> .`\r\n\r\n\r\n#### Run Container\r\n- `docker run <app_name>` -->\r\n\r\n\r\n#### Build and Run\r\n- `docker-compose up --build`\r\n" } ]	3
finnegantdewitt/Simple-Calorie-Counter-Python	https://github.com/finnegantdewitt/Simple-Calorie-Counter-Python	3c2da1f4cc7659297e17ebb97c159c35fb06743a	ef80dac668ce58a264a1fefc3685ed023a326958	2bfda2ffe7ae4bcc265e17bd8fa3ca438fb79de4	refs/heads/master	2020-06-29T13:28:01.370388	2019-08-04T23:15:02	2019-08-04T23:15:02	200,550,731	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7428571581840515, "alphanum_fraction": 0.7428571581840515, "avg_line_length": 33, "blob_id": "0f57bfa6a76f7e4aeb9c9334bb4eff4e150c0ccb", "content_id": "24c36dad52accfa8445289c8aba99d7c89b65312", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 35, "license_type": "no_license", "max_line_length": 33, "num_lines": 1, "path": "/README.md", "repo_name": "finnegantdewitt/Simple-Calorie-Counter-Python", "src_encoding": "UTF-8", "text": "\"# Simple-Calorie-Counter-Python\" \n" }, { "alpha_fraction": 0.5905253291130066, "alphanum_fraction": 0.5970919132232666, "avg_line_length": 29.913043975830078, "blob_id": "787cb48069c092ecae80e59810429d50a2d03d9e", "content_id": "3649f91ff47cacee18a36675ce34ba2220133595", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2132, "license_type": "no_license", "max_line_length": 80, "num_lines": 69, "path": "/cc.py", "repo_name": "finnegantdewitt/Simple-Calorie-Counter-Python", "src_encoding": "UTF-8", "text": "import argparse\nimport json\nfrom datetime import datetime\nfrom prettytable import PrettyTable\n\ndef timestamp():\n return int(round(datetime.timestamp(datetime.now())))\n\ndef add(args):\n meal = {\n \"food\": args.add[0],\n \"calories\": int(args.add[1]),\n \"timestamp\": timestamp()\n }\n loadedFood = []\n with open('food.json', encoding='utf-8') as foodjson:\n loadedFood = json.load(foodjson)\n\n loadedFood.append(meal)\n with open('food.json', mode='w', encoding='utf-8') as foodjson:\n json.dump(loadedFood, foodjson, indent=2)\n\ndef daysTotal():\n food = []\n with open('food.json', encoding='utf-8') as foodjson:\n food = json.load(foodjson)\n todaysCalories = 0\n for meal in food:\n mealtime = datetime.fromtimestamp(meal['timestamp'])\n if mealtime.day == datetime.now().day:\n todaysCalories += meal['calories']\n print(todaysCalories)\n\ndef listMealsToday():\n meals = []\n with open('food.json', encoding='utf-8') as foodjson:\n meals = json.load(foodjson)\n table = PrettyTable()\n table.field_names = ['Meal', 'Calories']\n calorieTotal = 0\n for meal in meals:\n mealtime = datetime.fromtimestamp(meal['timestamp'])\n if mealtime.day == datetime.now().day:\n calorieTotal += meal['calories']\n table.add_row([meal['food'], meal['calories']])\n table.add_row([\"Total\", calorieTotal])\n print(table)\n\n\ndef main():\n parser = argparse.ArgumentParser(description='Calorie Counter')\n\n parser.add_argument('-a', '--add', nargs=2, metavar=\"foodname calories\",\n default=None, help=\"Adds a food item and calorie count\")\n parser.add_argument('-t', '--total', const=42, nargs='?',\n help=\"Tells you the current total'\")\n parser.add_argument('-l', '--list', const=42, nargs='?',\n help='List meals of the day')\n\n args = parser.parse_args()\n if args.add != None:\n add(args)\n if args.total != None:\n daysTotal()\n if args.list != None:\n listMealsToday()\n\nif __name__ == \"__main__\":\n main()" } ]	2
sprockmonty/ICAV	https://github.com/sprockmonty/ICAV	cd2115f2857604098125aa8db8b2f39fb2ccb34f	c34bfdf2161219c2130a65e4d20b91809b67d46b	1d674d8019d314faa245a01eef19b042c188fc25	refs/heads/master	2020-06-04T11:41:01.084997	2019-06-14T22:14:14	2019-06-14T22:14:14	192,006,645	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6289398074150085, "alphanum_fraction": 0.6389684677124023, "avg_line_length": 33.79487228393555, "blob_id": "3e11cbdc150d0f285f5fa8c7d6df28341d0501fd", "content_id": "5093a2f1b739e7542208eec1121f5fcc27afe3a0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1396, "license_type": "no_license", "max_line_length": 181, "num_lines": 39, "path": "/gps_logger.py", "repo_name": "sprockmonty/ICAV", "src_encoding": "UTF-8", "text": "import rospy\r\nimport math\r\nimport time\r\nfrom geometry_msgs.msg import PoseStamped\r\nfrom sensor_msgs.msg import NavSatFix\r\nimport subprocess\r\nimport redis\r\nclass gpsLogger:\r\n def __init__(self):\r\n self._globalLatLong = [0.0,0.0] #global location [lat,long]\r\n self._globalAlt = 0.0 #global altitude\r\n self._log = []\r\n self._jobID = 0\r\n subprocess.Popen([\"redis-server\"])\r\n self._red = redis.Redis(host='localhost', port=6379, db=0)\r\n self._pRed = self._red.pubsub()\r\n self._pRed.subscribe('gps')\r\n\r\n def locationCallback(self,msg):\r\n self._globalLatLong[0] = msg.latitude\r\n self._globalLatLong[1] = msg.longitude\r\n self._globalAlt = msg.altitude\r\n #Use dictionary to log position, time and file location\r\n messageOut =''.join(str(self._globalLatLong))\r\n self._red.publish('gps',messageOut)\r\n print(messageOut)\r\n \r\n def getLocation():\r\n return self._globalLatLong\r\n \r\ndef main():\r\n rospy.init_node('gps_logger') # make ros node\r\n gpsLoggerInstance = gpsLogger()\r\n rospy.Subscriber(\"/mavros/global_position/global\",NavSatFix ,gpsLoggerInstance.locationCallback) #using global position rather than local (point to note, might need changing)\r\n rospy.spin() #keeps python from exiting until this node is stopped\r\n\r\n\r\nif __name__ == '__main__':\r\n main()\r\n" }, { "alpha_fraction": 0.6168091297149658, "alphanum_fraction": 0.6367521286010742, "avg_line_length": 26, "blob_id": "4556d6c58cca3bd905dac8b1d3e644c6e40cba98", "content_id": "188ed559a7fb6819d7347d4f307e33dde828f0ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 702, "license_type": "no_license", "max_line_length": 69, "num_lines": 26, "path": "/gps_receiver.py", "repo_name": "sprockmonty/ICAV", "src_encoding": "UTF-8", "text": "import redis\nimport subprocess\n\nclass gpsMessages:\n def __init__(self):\n self._globalLatLong = [0.0,0.0]\n\n def messageCallback(self,message):\n message = eval(message['data'].decode(\"utf-8\"))\n self._globalLatLong = message\n \n def getLatLong(self): \n return self._globalLatLong \n\ndef main():\n #redis setup\n red = redis.Redis(host='localhost', port=6379, db=0)\n pReceive = red.pubsub()\n gpsMessageInstance = gpsMessages()\n pReceive.subscribe(**{'gps': gpsMessageInstance.messageCallback})\n thread = pReceive.run_in_thread(sleep_time=0.001)\n while True:\n print(gpsMessageInstance.getLatLong())\n\nif __name__ == \"__main__\":\n main()\n" } ]	2
swarupv1/jinja2-deep-dive-day2	https://github.com/swarupv1/jinja2-deep-dive-day2	65502bd29794c0b223cfe94067c90d100fcffcc7	84441bf5e9a8169c8d69ea78cab3678223828cb2	f47c127351f993b7bdbe3606ed3c63f4e44fe591	refs/heads/master	2023-04-15T21:21:04.300936	2021-04-23T14:27:57	2021-04-23T14:27:57	361,646,682	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7634304165840149, "alphanum_fraction": 0.7647249102592468, "avg_line_length": 47.265625, "blob_id": "349dac1240d93819f0a36a249a1d2a53390cc5bb", "content_id": "3445a05d4e6ef7dde60c284189873d8c06b48d92", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 3090, "license_type": "no_license", "max_line_length": 231, "num_lines": 64, "path": "/challenges/06-netbox-ansible-api/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Using NetBox data from Ansible\n\nThe goal of this exercise is to start interacting with the NetBox API from Ansible and make use of the dynamic inventory plugin.\n\n## Exercise Overview\n\n### Prerequisites\n\nYou will need to have Ansible installed and read-only access to a Netbox instance.\n\n### Tasks\n\nSubmitting your solution for this challenge is optional - feel free to ask for help via email or at the open office hours if you get stuck! If do you send your files, make sure you remove any sensitive data like credentials/tokens!\n\n#### Task 1\n\nWrite an Ansible Playbook that queries the NetBox API for IPAM data as follows:\n\n- Query the NetBox API for all RIRs. If you don't have multiple RIRs, query for all Aggregates instead.\n- Print the total number of RIRs/Aggregates returned by the API.\n- Print a comma separated list of the RIR names from the API results.\n\nDO NOT hardcode the API token inside of the playbook - you should only provide it at execution time to `ansible-playbook`.\n\n> Hint: You do not need an inventory for this playbook as it can (and SHOULD) be run only once on localhost!\n\n#### Task 2\n\nUse the Ansible NetBox inventory plugin to build a dynamic inventory as per the following:\n\n- Instruct the plugin to group devices based on their `site` and `manufacturer`.\n- You should also use a `query_filter` to limit the amount of devices returned (especially if they are too many) by filtering devices matching only a specific field, such as `tenant` or `tag` or `rack-id`.\n- Using the `compose` function, add the `id` field (the unique numeric identifier from the NetBox API) to the inventory device facts.\n\n> Hint: Use the `ansible-inventory --graph -i netbox_inventory.yml` command to quickly view the structure of the dynamic inventory.\n> Use the `ansible-inventory -v --list -i netbox_inventory.yml` command to view the inventory structure and additional metadata pulled from NetBox.\n\n#### Task 3\n\nWrite an Ansible Playbook that uses the inventory built in `Task 2` to query NetBox for additional device metadata via the NetBox REST API.\n\nDO NOT hardcode the API token inside of the playbook - you should only provide it at execution time to `ansible-playbook`.\n\nThe playbook should perform the following tasks:\n\n- Print, for each device, its `id`, `manufacturer`, `platform` and `device_type` (this information should already be provided by the inventory plugin).\n- Query the NetBox API for the full device data based on its `id`. Use the `uri` module.\n- Print the device's `serial number` and/or `asset tag`.\n\n\n### Useful links\n\n- [NetBox Inventory Plugin](https://docs.ansible.com/ansible/latest/plugins/inventory/netbox.html)\n- [NetBox Documentation](https://netbox.readthedocs.io/en/stable/)\n- NetBox Live API Reference - `https://<YOUR_NETBOX_URL>/api/docs/`\n\n### Reference Enablement Material\n\n- NetBox & Source of Truth\n- Introduction to REST APIs\n- Network Programming and Automation Course\n- Using Ansible Jinja Filters Challenge\n\n> Note: Recordings of the relevant sessions can be found online at: https://training.networktocode.com/ \n" }, { "alpha_fraction": 0.5110027194023132, "alphanum_fraction": 0.558870255947113, "avg_line_length": 33.70866012573242, "blob_id": "285f50602421352c51c69ee01dbba66f8d92e2a4", "content_id": "cc26530aa43d4f2a9eb135f9c8f79bb0de7c272d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 8828, "license_type": "no_license", "max_line_length": 445, "num_lines": 254, "path": "/workshops/extending-ansible/lab03_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Extending Ansible - Lab 03\n\nIn this lab exercise, you will create a custom filter for Ansible that uses a third party Python library called `prettytable` to display tabular data as pure text. This type of filter will save countless hours when using Jinja templates to generate text-based reports.\n\n## Task 1 - Building the Filter Code\n\nTo start with, you will create a new filter generates a text-based table using the `prettytable` library.\n\n### Step 1\n\nIn your terminal on the lab workstation, change into the `/home/ntc/labs/lab03` folder, creating it if it doesn't exist.\n\n```\nntc@ntc-training:~$ mkdir -p /home/ntc/labs/lab03\nntc@ntc-training:~$ cd /home/ntc/labs/lab03\nntc@ntc-training:lab03$\n```\n\n### Step 2\n\nCreate a folder named `filter_plugins` and in it a file called `build_table.py`.\n```\nntc@ntc-training:lab03$ mkdir filter_plugins\nntc@ntc-training:lab03$ touch filter_plugins/build_table.py\nntc@ntc-training:lab03$ tree\n.\n└── filter_plugins\n └── build_table.py\n\n1 directory, 1 file\n```\n\n### Step 3\n\nEdit the `build_table.py` file and paste in the following content. This is the full script so take a bit of time to read through the code.\n\n```py\nfrom prettytable import PrettyTable\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"build_table\": FilterModule.build_table,\n }\n\n @staticmethod\n def build_table(table_data):\n \"\"\"Builds a text table from list data.\"\"\"\n table = PrettyTable()\n # Set the table column headers\n table.field_names = table_data.get(\"headers\")\n\n # Add in row data one by one\n for row in table_data.get(\"rows\"):\n table.add_row(row)\n\n # Return the pure text representation of the table\n return table.get_string()\n```\n\nThe `PrettyTable` class is fairly straightforward to work with, the code uses the following functionality (for more examples check out its [repository](https://github.com/jazzband/prettytable)):\n\n- `table.field_names` this property sets the table column headers and is a list of strings\n- `table.add_row()` this method allows you to add a row into the table as a list of values\n- `table.get_string()` this method returns a text representation of the table for printing\n\n### Step 4\n\nIn the terminal, ensure that the `prettytable` Python package is installed.\n\n```\nntc@ntc-training:lab03$ pip3 install prettytable --user\nCollecting prettytable\n Downloading https://files.pythonhosted.org/packages/39/da/8336296a830caa495a25304e12ffb32a8c3a9d2d08ba995f066fe16152e1/prettytable-1.0.1-py2.py3-none-any.whl\nRequirement already satisfied: setuptools in /usr/local/lib/python3.6/site-packages (from prettytable) (41.0.1)\nCollecting wcwidth (from prettytable)\n Downloading https://files.pythonhosted.org/packages/59/7c/e39aca596badaf1b78e8f547c807b04dae603a433d3e7a7e04d67f2ef3e5/wcwidth-0.2.5-py2.py3-none-any.whl\nInstalling collected packages: wcwidth, prettytable\nSuccessfully installed prettytable-1.0.1 wcwidth-0.2.5\n```\n\n### Step 5\n\nStart a Python interpreter and test your filter code.\n\n```\nntc@ntc-training:lab03$ python3 -i filter_plugins/build_table.py\n>>> table_data = {}\n>>> table_data[\"headers\"] = ['NAME','DATE CREATED', 'STATUS', 'ID', 'IP ADDRESS']\n>>> table_data[\"rows\"] = []\n>>> table_data[\"rows\"].append(['IOSXE', 'today', 'up', '098435', '10.10.10.1'])\n>>> table_data[\"rows\"].append(['NXOS', 'today', 'down', '098435', '10.10.10.2'])\n>>> table_data[\"rows\"].append(['JUNIPER', 'today', 'down', '098078', '10.10.10.3'])\n>>>\n>>> print(FilterModule.build_table(table_data))\n+---------+--------------+--------+--------+------------+\n\| NAME \| DATE CREATED \| STATUS \| ID \| IP ADDRESS \|\n+---------+--------------+--------+--------+------------+\n\| IOSXE \| today \| up \| 098435 \| 10.10.10.1 \|\n\| NXOS \| today \| down \| 098435 \| 10.10.10.2 \|\n\| JUNIPER \| today \| down \| 098078 \| 10.10.10.3 \|\n+---------+--------------+--------+--------+------------+\n```\n\n## Task 2 - Using the Filter in an Ansible Playbook\n\nWrite an Ansible Playbook that uses the `build_table` filter to save a text table representation to a file.\n\n### Step 1\n\nIn the `/home/ntc/labs/lab03` folder, create the `pb_build_table.yml` file and add the following lines to it.\n\n```yaml\n---\n\n- name: BUILD TEXT TABLE\n hosts: localhost\n gather_facts: false\n\n vars:\n table_data:\n headers: ['NAME','DATE CREATED', 'STATUS', 'ID', 'IP ADDRESS']\n rows:\n - ['IOSXE', 'today', 'up', '098435', '10.10.10.1']\n - ['NXOS', 'today', 'down', '098435', '10.10.10.2']\n - ['JUNIPER', 'today', 'down', '098078', '10.10.10.3']\n```\n\nIn this case, you are defining the input structured data as play vars inline - but in practice, you might get this data from other modules, CSV files, output from API calls etc.\n\n### Step 2\n\nFinalize the `pb_build_table.yml` playbook by adding the tasks shown below (final file included for reference):\n\n```yaml\n---\n\n- name: BUILD TEXT TABLE\n hosts: localhost\n gather_facts: false\n\n vars:\n table_data:\n headers: ['NAME','DATE CREATED', 'STATUS', 'ID', 'IP ADDRESS']\n rows:\n - ['IOSXE', 'today', 'up', '098435', '10.10.10.1']\n - ['NXOS', 'today', 'down', '098435', '10.10.10.2']\n - ['JUNIPER', 'today', 'down', '098078', '10.10.10.3']\n\n tasks:\n # This is the Python dictionary parsed from the playbook YAML vars\n - name: DISPLAY STRUCTURED INPUT DATA\n debug:\n var: table_data\n\n # This is the text table with whitespace and newlines\n - name: DISPLAY TEXT OUTPUT DATA\n debug:\n var: table_data \| build_table\n\n # Save to a file the formatted text table\n - name: SAVE TABLE REPRESENTATION TO FILE\n copy:\n content: \"{{ table_data \| build_table }}\"\n dest: table.txt\n```\n\n### Step 3\n\nRun the Ansible playbook and inspect the output.\n\n```\nntc@ntc-training:lab03$ ansible-playbook pb_build_table.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not\nmatch 'all'\n\nPLAY [BUILD TEXT TABLE] ****************************************************************************************\n\nTASK [DISPLAY STRUCTURED INPUT DATA] *************************************************************************\nok: [localhost] => {\n \"table_data\": {\n \"headers\": [\n \"NAME\",\n \"DATE CREATED\",\n \"STATUS\",\n \"ID\",\n \"IP ADDRESS\"\n ],\n \"rows\": [\n [\n \"IOSXE\",\n \"today\",\n \"up\",\n \"098435\",\n \"10.10.10.1\"\n ],\n [\n \"NXOS\",\n \"today\",\n \"down\",\n \"098435\",\n \"10.10.10.2\"\n ],\n [\n \"JUNIPER\",\n \"today\",\n \"down\",\n \"098078\",\n \"10.10.10.3\"\n ]\n ]\n }\n}\n\nTASK [DISPLAY TEXT OUTPUT DATA] ******************************************************************************\nok: [localhost] => {\n \"table_data \| build_table\": \"+---------+--------------+--------+--------+------------+\\n\| NAME \| DATE CREATED \| STATUS \| ID \| IP ADDRESS \|\\n+---------+--------------+--------+--------+------------+\\n\| IOSXE \| today \| up \| 098435 \| 10.10.10.1 \|\\n\| NXOS \| today \| down \| 098435 \| 10.10.10.2 \|\\n\| JUNIPER \| today \| down \| 098078 \| 10.10.10.3 \|\\n+---------+--------------+--------+--------+------------+\"\n}\n\nTASK [SAVE TABLE REPRESENTATION TO FILE] *********************************************************************\nchanged: [localhost]\n\nPLAY RECAP ***************************************************************************************************\nlocalhost : ok=3 changed=1 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\n```\n\n### Step 4\n\nCheck the contents of the `table.txt` file.\n\n```\nntc@ntc-training:lab03$ cat table.txt\n+---------+--------------+--------+--------+------------+\n\| NAME \| DATE CREATED \| STATUS \| ID \| IP ADDRESS \|\n+---------+--------------+--------+--------+------------+\n\| IOSXE \| today \| up \| 098435 \| 10.10.10.1 \|\n\| NXOS \| today \| down \| 098435 \| 10.10.10.2 \|\n\| JUNIPER \| today \| down \| 098078 \| 10.10.10.3 \|\n+---------+--------------+--------+--------+------------+\n```\n\n### Step 5\n\nAdd some more row data and regenerate the table!\n\nOptional challenge: \n\nTry to figure out how to save the output as HTML instead of pure text. Hint... check the PrettyTable documentation!\n" }, { "alpha_fraction": 0.7443181872367859, "alphanum_fraction": 0.7556818127632141, "avg_line_length": 28.33333396911621, "blob_id": "d8d087bc951325da5de9492b3f23a35840a686c0", "content_id": "678ea54881b30b464e61e79ec27ba4bc310b4716", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 352, "license_type": "no_license", "max_line_length": 127, "num_lines": 12, "path": "/workshops/development-environments/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "## Development Environments Workshop\n\n- [Lab Guide](lab_guide.md)\n- [Lecture Slides](DevelopmentEnvironments.pdf)\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.*\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.6105263233184814, "alphanum_fraction": 0.7368420958518982, "avg_line_length": 18, "blob_id": "3cd251ffd35b5a28dec3cb34af2ecc206b6952de", "content_id": "2d9991dc332b3294e96f9fa6c4eece112ab50317", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 95, "license_type": "no_license", "max_line_length": 48, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-IDF01-R02-SW01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-IDF01-R02-SW01\n\nThis Cisco WS-C3850-48U device is located in HQ.\n\nIts status is: Planned.\n" }, { "alpha_fraction": 0.4751640260219574, "alphanum_fraction": 0.4829740822315216, "avg_line_length": 32.69473648071289, "blob_id": "567d10f39177b892ab22fa59f99eb4bb3d45bada", "content_id": "21c7aa4738697abe9b2b2682b1674af0315bdcbb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3201, "license_type": "no_license", "max_line_length": 76, "num_lines": 95, "path": "/workshops/extending-ansible/lab04/filter_plugins/verify_intended_state.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "from ansible import errors\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"verify_intended_state\": FilterModule.verify_intended_state,\n }\n\n @staticmethod\n def verify_intended_state(operational, intended):\n \"\"\"Returns a pass/fail comparison of intended and operational state.\n\n Compares NXOS (operational) state (from the show int brief command)\n to a provided list of interface and state mappings (intended)\n\n SAMPLE intended\n [\n {\n \"name\": \"Ethernet1/1\",\n \"state\": \"up\"\n },\n {\n \"name\": \"mgmt0\",\n \"state\": \"up\"\n },\n ]\n\n SAMPLE operational\n {\n \"TABLE_interface\": {\n \"ROW_interface\": [\n {\n \"interface\": \"mgmt0\",\n \"state\": \"up\",\n \"ip_addr\": \"10.0.0.15\",\n \"speed\": \"1000\",\n \"mtu\": \"1500\"\n },\n {\n \"interface\": \"Ethernet1/1\",\n \"vlan\": \"1\",\n \"type\": \"eth\",\n \"portmode\": \"access\",\n \"state\": \"up\",\n \"state_rsn_desc\": \"none\",\n \"speed\": \"1000\",\n \"ratemode\": \"D\"\n },\n ]\n }\n }\n\n\n Args:\n operational (dict): the output of `show int brief \| json`\n intended (list): a list of interfaces and their states\n\n Returns:\n dict: A dictionary containing the lists of interfaces that\n passed and failed verification\n \"\"\"\n # First prepare the data coming from NXOS for ease of lookup\n # Change from a list of interface dictionaries to a dictionary\n # keyed on the interface name\n oper_keyed = {}\n for oper_intf in operational[\"TABLE_interface\"][\"ROW_interface\"]:\n oper_keyed[oper_intf[\"interface\"]] = oper_intf\n\n pass_list = []\n fail_list = []\n # This is a list of name/state pairs describing the intended state\n # of a bunch of interfaces (not necessarily the same set).\n for interface in intended:\n # Look for the interface name in the operational dictionary\n # as an exact match only - with UNKNOWN as a safe default\n oper_intf = oper_keyed.get(interface[\"name\"])\n if oper_intf:\n oper_state = oper_intf.get(\"state\", \"UNKNOWN\")\n else:\n oper_state = \"UNKNOWN\"\n\n # Compare operational to intended\n if oper_state != interface[\"state\"]:\n fail_list.append(interface[\"name\"])\n else:\n pass_list.append(interface[\"name\"])\n\n # Return a dictionary with two keys containing the lists for easy\n # subsequent parsing\n return {\"pass\": pass_list, \"fail\": fail_list}\n" }, { "alpha_fraction": 0.745400607585907, "alphanum_fraction": 0.7661721110343933, "avg_line_length": 32.63999938964844, "blob_id": "6b100e425443eca46969873d6e7e454de27c4494", "content_id": "e636b329531af4057e2c93505869d1f0c0dd9693", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1685, "license_type": "no_license", "max_line_length": 173, "num_lines": 50, "path": "/challenges/10-batfish/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Batfish\n \nThe goal of this exercise is to learn about the common operations in Batfish. You will learn how to interact with Batfish and work with its output.\n \nFor certain parts of this challenge you will need to refer to https://pybatfish.readthedocs.io/en/latest/questions.html to understand the question that we will need to ask. \n\n## Exercise Overview\n \n### Prerequisites\n \nYou will need to have:\n Python virtual environment created and activated\n* the required dependencies installed\n* a Batfish container running\n* the example snapshot imported\n\n```\ndocker pull batfish/allinone\ndocker run --name batfish -d -v batfish-data:/data -p 8888:8888 -p 9997:9997 -p 9996:9996 batfish/allinone\n\ncd 10-batfish\nvirtualenv --python=`which python3` venv\nsource venv/bin/activate\npip3 install -r files/requirements.txt\n\n./files/bf_snapshot_importer.py --snapshot_path files/nxos-spineleaf-001/\n```\n\n### Tasks\n \nSubmitting your solution for this challenge is optional - feel free to ask for help via email, chat, or at the open office hours if you get stuck!\n \n#### Task 1 - Snapshot Import\n \nFrom the helper file `bf_snapshot_importer.py` can you determine the line where the snapshot is initialized using the supplied snapshot path?\n\n \n#### Task 2 - Snapshot Validation\n \nUse Batfish to:\n* obtain a parsing summary of the snapshot files.\n* confirm the problematic configuration lines for each of the configurations. \n\n#### Task 3 - MTU Validation\n\nUse Batfish to confirm the MTU for each of the interfaces within our snapshot.\n \n#### Task 4 - OSPF Validation\n \nUse Batfish to validate all OSPF adjacencies are correctly established. If they are not, please confirm reason.\n\n \n" }, { "alpha_fraction": 0.6240188479423523, "alphanum_fraction": 0.6321297883987427, "avg_line_length": 26.299999237060547, "blob_id": "d1361ad88d60e3b0c019627d9b20576f2efca390", "content_id": "98d12257b9582545063e7b86efc185ab3d98145f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3822, "license_type": "no_license", "max_line_length": 84, "num_lines": 140, "path": "/workshops/jinja2-deep-dive-day2/python/j2_render.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\nimport argparse\nfrom pathlib import Path\n\nimport jinja2\nimport yaml\n\nfrom libs import ipaddr\n\nBASE_DIR = Path(__file__).parent.absolute()\nOUTPUT_DIR = BASE_DIR / \"output\"\nTEMPLATES_DIR = BASE_DIR / \"templates\"\nVARS_DIR = BASE_DIR / \"vars\"\n\nregions = {\n \"EMEA\": {\n \"sites\": [\"london\", \"paris\", \"madrid\"],\n \"logging_hosts\": [\"10.1.54.4\", \"10.4.6.16\"],\n }\n}\n\n\ndef get_lab_prefix(template_name):\n lab_prefix = \"\"\n if \"lab\" in template_name:\n lab_prefix = template_name.split(\"-\")[0]\n\n return lab_prefix\n\n\ndef load_file_vars(file_vars_name, lab_prefix):\n \"\"\"Load yaml/json file with vars\n\n using yaml module as it parses both json and yaml files\n\n Args:\n file_vars_name (str): name of the file with vars\n lab_prefix (str): identifies lab number\n\n Returns:\n dict: dictionary with parsed vars\n \"\"\"\n\n template_vars = {}\n\n if lab_prefix:\n file_all_vars = VARS_DIR / f\"{lab_prefix}-all.yml\"\n if file_all_vars.exists():\n with file_all_vars.open(mode=\"r\", encoding=\"utf8\") as fin:\n data = yaml.load(fin, Loader=yaml.SafeLoader)\n template_vars.update(data)\n\n file_vars_path = VARS_DIR / file_vars_name\n\n with file_vars_path.open(mode=\"r\", encoding=\"utf8\") as fin:\n template_vars.update(yaml.load(fin, Loader=yaml.SafeLoader))\n\n return template_vars\n\n\ndef render_template(template_name, template_data, strict, trim, lstrip):\n \"\"\"Renders template using provided data\n\n Args:\n template_name (str): template file name\n template_data (dict): data used to render template\n\n Returns:\n str: rendered template output\n \"\"\"\n undefined_class = jinja2.StrictUndefined if strict else jinja2.Undefined\n\n j2_env = jinja2.Environment(\n loader=jinja2.FileSystemLoader(TEMPLATES_DIR),\n undefined=undefined_class,\n trim_blocks=trim,\n lstrip_blocks=lstrip,\n )\n j2_env.filters.update(ipaddr.FilterModule.filter_map)\n j2_template = j2_env.get_template(template_name)\n\n if not j2_template:\n raise FileNotFoundError\n\n rendered_template = j2_template.render(template_data)\n\n return rendered_template\n\n\ndef parse_cli_args():\n \"\"\"Parse command line options\"\"\"\n cli_parser = argparse.ArgumentParser()\n cli_parser.add_argument(\"-t\", \"--template\", required=True)\n cli_parser.add_argument(\"-d\", \"--data-file\", required=False)\n cli_parser.add_argument(\"-o\", \"--output-file\", required=False)\n cli_parser.add_argument(\"-s\", \"--silent\", action=\"store_true\")\n cli_parser.add_argument(\"-strict\", action=\"store_true\")\n cli_parser.add_argument(\"-trim\", action=\"store_true\")\n cli_parser.add_argument(\"-strip\", action=\"store_true\")\n\n cli_args = cli_parser.parse_args()\n\n return cli_args\n\n\ndef main():\n cli_args = parse_cli_args()\n\n template_name = cli_args.template\n data_file = cli_args.data_file\n output_file = cli_args.output_file\n strict_check = cli_args.strict\n j2_trim = cli_args.trim\n j2_lstrip = cli_args.strip\n\n lab_prefix = get_lab_prefix(template_name)\n template_vars = {}\n if data_file:\n template_vars = load_file_vars(data_file, lab_prefix)\n render_result = render_template(\n template_name, template_vars, strict_check, j2_trim, j2_lstrip\n )\n\n if output_file:\n with Path(OUTPUT_DIR / output_file).open(mode=\"w\", encoding=\"utf8\") as fout:\n fout.write(render_result)\n\n if not cli_args.silent:\n print(f\"==== LOADED TEMPLATE: {template_name}\")\n print(f\"==== LOADED DATA FILE: {data_file}\")\n print(\"==== RENDERED TEMPLATE\")\n print(f\"{render_result}\")\n\n if output_file:\n print(f\"==== OUTPUT FILE: {output_file}\")\n\n\nif __name__ == \"__main__\":\n main()\n" }, { "alpha_fraction": 0.6536095142364502, "alphanum_fraction": 0.6935341954231262, "avg_line_length": 21.127777099609375, "blob_id": "6bc9e00a0aca33bc9425906f2ffc9aa7cee83afc", "content_id": "fadd589ddfdb05b49ecce8682291e9070ab648ca", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 7965, "license_type": "no_license", "max_line_length": 187, "num_lines": 360, "path": "/workshops/jinja2-deep-dive-day1/lab_guides/lab02_loops_conditionals.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 02 - Jinja loops, conditionals and tests\n\nGoals of this lab:\n\n- Practice use of tests.\n- Use loops to iterate over lists and dictionaries.\n- Practice use of loop variables.\n- Write templates combining loops, conditionals, and tests.\n## Task 01\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab02-task1.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate a template named `lab02-task1.j2` in `python/templates` dir.\n\nIn your template, write tests checking if variables in `lab02-task1.j2` are of a specific type.\n\nYour output should match the below one:\n```\nIs dc_name a string?\n- Yes\n\nIs number_of_devices an integer?\n- Yes\n\nIs dc_temp a float?\n- No\n\nIs vrfs a dictionary?\n- Yes\n\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab02-task1.j2 -d lab02-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use built-in tests with `{% if %}` conditionals.\n\n```\nIs dc_name a string?\n{% if dc_name is string %}\n- Yes\n{% else %}\n- No\n{% endif %}\n\nIs number_of_devices an integer?\n{% if number_of_devices is integer %}\n- Yes\n{% else %}\n- No\n{% endif %}\n\nIs dc_temp a float?\n{% if dc_temp is float %}\n- Yes\n{% else %}\n- No\n{% endif %}\n\nIs vrfs a dictionary?\n{% if vrfs is mapping %}\n- Yes\n{% else %}\n- No\n{% endif %}\n```\n\n</details>\n\n## Task 02\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab02-task2.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nA template, `python/templates/lab02-task2.j2` has been created for you. This template is used to render the site contact number read from the `lab02-task2.yml`\n\nUnfortunately, something strange happens during the rendering.\n\nThis is the output we get, which is different than the phone number recorded in the data file:\n\n```\nSite contact number: 15106296\n```\n\nChange either the template or the data, or both, so that the number is rendered correctly.\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab02-task2.j2 -d lab02-task2.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYAML tries to decide data types dynamically. Number starting with `0` consisting of digits `0-7` will be treated as octal.\n\nYou should place quotation marks around the number to explicitly make it a string.\n\n```\n---\nsite_contact: \"071500370\"\n```\n\nOptionally you can also add a conditional check to the template. This won't prevent the template from being rendered but you can easily search files for lines containing `!ERROR!` string.\n\n{% if site_contact is string %}\nSite contact number: {{ site_contact }}\n{% else %}\nSite contact number: !ERROR!: 'site_contact' MUST be string.\n{% endif %}\n\n</details>\n\n## Task 03\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab02-task3.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate template named `lab02-task3.j2` in `python/templates` dir.\n\nYour template should generate interface configuration using the data in `lab02-task3.yml`.\n\nOutput from your template should match the below text:\n\n```\ninterface Loopback0\n description Control Plane traffic\n ip address 10.255.255.34/32\n!\ninterface Management1\n description Management interface\n ip address 10.10.0.5/24\n!\ninterface Ethernet1\n description Span port - SPAN1\n ip address \n!\ninterface Ethernet2\n description PortChannel50 - port 1\n ip address \n!\ninterface Ethernet51\n description leaf01-eth51\n ip address 10.50.0.0/31\n!\ninterface Ethernet52\n description leaf02-eth51\n ip address 10.50.0.2/31\n!\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab02-task3.j2 -d lab02-task3.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use `{% for %}` loop iterating over the dictionary item.\n\nThen you should access the keys of the dictionary inside of the loop.\n\n```\n{% for intf_name, intf_data in interfaces.items() %}\ninterface {{ intf_name }}\n description {{ intf_data['description'] }}\n ip address {{ intf_data['ipv4_address'] }}\n!\n{% endfor %}\n```\n\n</details>\n\n## Task 04\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab02-task4.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nA template named `lab02-task4.j2` in `python/templates` dir was created for you.\n\nThis template is not working correctly at the moment. See below the template and output it generates.\n\nTemplate\n```\n{% for line in secure_acl['lines'] %}\nip access-list standard {{ secure_acl['name'] }}\n 10 permit {{ line['network'] }} {{ line['mask'] }}\n! Total ACL lines: {{ secure_acl['lines'] \| length }}\n{% endfor %}\n```\n\nOutput\n```\nip access-list standard SECURE_ACCESS_IN\n 10 permit 10.0.0.0 0.0.0.255\n! Total ACL lines: 3\nip access-list standard SECURE_ACCESS_IN\n 10 permit 10.0.1.0 0.0.0.255\n! Total ACL lines: 3\nip access-list standard SECURE_ACCESS_IN\n 10 permit 10.0.2.0 0.0.0.255\n! Total ACL lines: 3\n```\n\nThe access list definition repeats 3 times, the sequence numbers are not correct, and the summary line is repeated 3 times.\n\nYou need to fix this template so that the output is a valid configuration. See below output for comparison.\n\nDesired output\n```\nip access-list standard SECURE_ACCESS_IN\n 10 permit 10.0.0.0 0.0.0.255\n 20 permit 10.0.1.0 0.0.0.255\n 30 permit 10.0.2.0 0.0.0.255\n! Total ACL lines: 3\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab02-task4.j2 -d lab02-task4.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use loop index variables `first` and `last` to conditionally display lines on the first and last iteration of the loop only.\n\nUse the `index` loop variable to compute ACL sequence numbers.\n\n```\n{% for line in secure_acl['lines'] %}\n{% if loop.first %}\nip access-list standard {{ secure_acl['name'] }}\n{% endif %}\n {{ loop.index * 10 }} permit {{ line['network'] }} {{ line['mask'] }}\n{% if loop.last %}\n! Total ACL lines: {{ secure_acl['lines'] \| length }}\n{% endif %}\n{% endfor %}\n```\n\n</details>\n\n## Task 05 (Optional)\n\nThis task combines the use of different Jinja features and it might take a bit longer to complete.\n\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab02-task5.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate template named `lab02-task5.j2` in `python/templates` dir.\n\nYour template should generate interface configuration using the data in `lab02-task5.yml`.\n\nOutput from your template should match the below text:\n\n```\nDevice: sw-dist-waw-01\nLayer3 switch?: No\nName with stack pos.: sw-dist-waw-01-1\nOS > 4.19: No\nSD WAN site?: No\n----------\nDevice: sw-dist-waw-01\nLayer3 switch?: No\nName with stack pos.: sw-dist-waw-01-2\nOS > 4.19: No\nSD WAN site?: No\n----------\nDevice: sw-dist-par-01\nLayer3 switch?: Yes\nOS > 4.19: Yes\nSD WAN site?: Yes\n----------\nDevice: rtr-core-ty-01\nLayer3 switch?: No\nOS > 4.19: Yes\nSD WAN site?: Yes\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab02-task5.j2 -d lab02-task5.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use `{% for %}` loop to iterate over the list of devices.\n\nUse containment `in` operator and logical operators where appropriate.\n\nPay attention to the placement of `{% if %}` blocks.\n\n```\n{% for device in devices %}\nDevice: {{ device['name'] }}\nLayer3 switch?: {% if device['device_type'] == \"switch\" and device['layer'] == \"layer3\" %}Yes{% else %}No{% endif %}\n\n{% if device['stack_pos'] is defined %}\nName with stack pos.: {{ device['name'] ~ '-' ~ device['stack_pos'] }}\n{% endif %}\nOS > 4.19: {% if device['os_ver'] > 4.19 %}Yes{% else %}No{% endif %}\n\nSD WAN site?: {% if device['site'] in sdwan_sites %}Yes{% else %}No{% endif %}\n\n{% if not loop.last %}\n----------\n{% endif %}\n{% endfor %}\n```\n\n</details>" }, { "alpha_fraction": 0.621052622795105, "alphanum_fraction": 0.7473683953285217, "avg_line_length": 18, "blob_id": "b918516e859a1467342ad84405d4581e885212b8", "content_id": "3da7a9c1e1b44de4faf1b21f0edd711d6d7a06f9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 95, "license_type": "no_license", "max_line_length": 50, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-acme-lsw03/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-acme-lsw03\n\nThis Cisco 93180YC-FX-24 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6508193016052246, "alphanum_fraction": 0.6526656150817871, "avg_line_length": 30.17266273498535, "blob_id": "330be581c4b7b3ee0df215b1ac0a4d7dbe66a56c", "content_id": "7b0cc3e8fb74186a896a24e4dadbea63c417b379", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4333, "license_type": "no_license", "max_line_length": 109, "num_lines": 139, "path": "/workshops/extending-ansible/lab06/modules/iosxe_rest_vrf.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python3\n\nDOCUMENTATION = \"\"\"\n---\nmodule: iosxe_rest_vrf\nshort_description: This module updates VRF configuration via the IOSXE REST API.\nversion_added: \"1.0.0\"\ndescription: This module uses the requests Python library to make API calls against the IOSXE device.\noptions:\n host:\n description: Enter the IP or hostname of the IOSXE device\n required: true\n type: str\n user:\n description: Enter the device username\n required: true\n type: str\n password:\n description: Enter the device password\n required: true\n type: str\n verify:\n description: Enable or disable SSL verification, it will disabled by default\n required: false\n type: bool\n name:\n description: The VRF's name you want to manage\n required: true\n type: str\n description:\n description: The VRF's description (optional)\n required: false\n type: str\n\nauthor:\n - NetworkToCode (@networktocode)\n\"\"\"\n\nEXAMPLES = \"\"\"\n# Collect Device Version\n- name: UPDATE VRF DESCRIPTION\n iosxe_rest_vrf:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ username }}\"\n password: \"{{ password }}\"\n name: CORP\n description: VRF FOR CORPORATE USERS\n\"\"\"\n\nRETURN = \"\"\"\n# These are examples of possible return values, and in general should use other names for return values.\nsent_payload:\n description: The VRF data that will be sent to the API via the PATCH request\n type: str\n returned: always\n sample: '{\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}'\nmsg:\n description: A status message including the HTTP response code.\n type: str\n returned: always\n sample: 'OK 204'\n\"\"\"\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nimport json\n\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n # define available arguments/parameters a user can pass to the module\n module_args = dict(\n host=dict(type=\"str\", required=True),\n user=dict(type=\"str\", required=True),\n password=dict(type=\"str\", required=True, no_log=True),\n verify=dict(type=\"bool\", default=False),\n name=dict(type=\"str\", required=True),\n description=dict(type=\"str\", required=False),\n )\n module = AnsibleModule(argument_spec=module_args, supports_check_mode=False)\n\n # prepare the standard return object\n result = dict(changed=False)\n\n # set up the API request parameters\n auth = requests.auth.HTTPBasicAuth(module.params[\"user\"], module.params[\"password\"])\n # this module supports only json\n headers = {\n \"Accept\": \"application/yang-data+json\",\n \"Content-Type\": \"application/yang-data+json\",\n }\n # this module supports only the Cisco-IOS-XE-native data model\n base_url = (\n f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native\"\n )\n # manages vrf by name\n url = f\"{base_url}/Cisco-IOS-XE-native:vrf/definition={module.params['name']}\"\n\n # build PATCH request payload\n payload = {\"Cisco-IOS-XE-native:definition\": {\"name\": f\"{module.params['name']}\"}}\n\n # only set if it's defined since an empty description is not acceptable by the API\n if module.params[\"description\"]:\n payload[\"Cisco-IOS-XE-native:definition\"][\n \"description\"\n ] = f\"{module.params['description']}\"\n\n # add this to the module output for easier troubleshooting\n result[\"sent_payload\"] = payload\n\n # send the API request to the device (PATCH)\n response = requests.patch(\n url,\n data=json.dumps(payload),\n headers=headers,\n auth=auth,\n verify=module.params[\"verify\"],\n )\n\n # return the json response from the API if it exists\n if response.text:\n result[\"json\"] = response.json()\n\n # since it's a blind PATCH request, always assume a change was made\n if response.ok:\n result[\"changed\"] = True\n result[\"msg\"] = f\"OK {response.status_code}\"\n # the request failed so the module should fail as well\n else:\n result[\"msg\"] = f\"API request failed with code {response.status_code}\"\n module.fail_json(result)\n\n # return successfully and pass the results to ansible\n module.exit_json(result)\n\n\nif __name__ == \"__main__\":\n main()\n" }, { "alpha_fraction": 0.6369998455047607, "alphanum_fraction": 0.6744123697280884, "avg_line_length": 27.875648498535156, "blob_id": "63264b4369bac061c848b4ea85b90a9cbeeeb645", "content_id": "07a141e424f791631900e263c68dd11dec9c7f4d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 11146, "license_type": "no_license", "max_line_length": 276, "num_lines": 386, "path": "/challenges/09-data-structures/solution/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "### Data Structures solution\n\n# Challenge Exercise Solution Guide\n\n## Introduction to Data Structures\n\nIn this challenge you are exploring data structures, and learning how to work with them using Python.\n\n## Solution Walkthrough\n\n#### Task 1 - Basic data types\n\nIn this task you are asked to identify different data types.\n\n1.\n\n```\nhostname = \"sALBEles09\"\n```\n\nHere `hostname` holds the value of `\"sALBEles09\" `, which is a `string` date type. Notice quotation marks, `\"\"`, around the word, which tell us this is a `string`.\n\n2.\n\n```\nvc_priority = 15\n```\n\nYou assign the value of `15` to `vc_priority`. The data type here is `integer` as `15` is a whole number.\n\n3.\n\n```\ncpu_load = 72.56\n```\n\nThis is a `float`, we can see it's a float because there is a decimal point in the number `72.56`.\n\n4.\n\n```\nrouting_enabled = True\n```\n\nThis is a `boolean`. We use `boolean` type to represent truth values of logic. We can tell it's boolean because the word `True` is capitalized and is not enclosed in quotation marks.\n\n5.\n\n```\nvlan_ids = [10, 300, 301, 302, 1400]\n```\n\nThis data type is called `list` in Python. In other languages it might be also referred to as an `array`. \n\nWe can tell it's a `list` because this is a comma `,`, separated collection of elements enclosed in square brackets `[]`.\n\n6.\n\n```\nvlans = {\n \"10\": \"Production\",\n \"300\": \"Engineering\",\n \"301\": \"Voice\",\n \"302\": \"Printers\"\n}\n```\n\nThis data type is called `dictionary` in Python. In other languages it might be referred to as `hash`, `map` or `object`.\n\nWe can tell it's a `dictionary` because we have a comma `,` separated list of `key: value` pairs separated by colon `:`. And the collection is enclosed in curly braces `{}`.\n \n#### Task 2 - Accessing data - list \n \nThe below data structure is a `list` so you need to use index value using square brackets `[]` to retrieve corresponding values.\n\n```\ninterfaces = [\"GigabitEthernet1\", \"GigabitEthernet2\", \"GigabitEthernet3\", \"GigabitEthernet4\"]\n```\n\nBelow statements retrieve 1st and last interface on the list. Remember that list indexes start from `0`.\n\n```\n>>> interfaces[0]\n'GigabitEthernet1'\n>>> interfaces[3]\n'GigabitEthernet4'\n```\n\n#### Task 3 - Accessing data - dictionary\n\nThe below data structure is a `dictionary` so you need to use the key name enclosed in square brackets `[]` to access the given value.\n\n```\ncpu_process = {\n \"five_min_cpu\": 0.46,\n \"five_sec_cpu\": 0.0,\n \"invoked\": 11390,\n \"one_min_cpu\": 0.59,\n \"pid\": 9,\n \"process\": \"Check heaps\",\n \"runtime\": 192629,\n \"tty\": 0,\n \"usecs\": 16912,\n }\n```\n\nBelow is an example of retrieving asked for values and their corresponding data types:\n\n```\n>>> cpu_process[\"five_min_cpu\"]\n0.46\n>>> type(cpu_process[\"five_min_cpu\"])\n<class 'float'>\n>>> cpu_process[\"process\"]\n'Check heaps'\n>>> type(cpu_process[\"process\"])\n<class 'str'>\n>>> cpu_process[\"invoked\"]\n11390\n>>> type(cpu_process[\"invoked\"])\n<class 'int'>\n```\n\n#### Task 4 - Mixing data types\n\nThis task shows you the importance of understanding data types you're working with. When mixing data types some of the operations are not allowed, some generate unexpected results.\n\n1. \n\n```\n>>> is_cisco = \"False\"\n>>> is_switch = \"True\"\n>>> is_cisco and is_switch\n'True'\n```\n\nAt first glance the result of the operation should be `False` since we used logical `and` operator. Notice however that both of the arguments are of type `string` and not `boolean`. `\"False\"` and `\"True\"` have quotation marks around words which makes them strings.\n\nOperator `and` behaves differently with `string` type than it does with `boolean` type. \n\nOnce we use correct `boolean` types we get expected result:\n\n```\n>>> is_cisco = False\n>>> is_switch = True\n>>> is_cisco and is_switch\nFalse\n```\n\n2.\n\nThis is similar to 1. but here one variable is of type `boolean` while the other is `string`. This is why the result of `or` operation is `\"False\"`. The result is actually a `string` and not `boolean`.\n\n```\n>>> is_router = \"False\"\n>>> is_asr1000 = True\n>>> is_router or is_asr1000\n'False'\n```\n\nTo get expected result change assign `boolean` value of `False` to `is_router`:\n\n```\n>>> is_router = False\n>>> is_asr1000 = True\n>>> is_router or is_asr1000\nTrue\n```\n3.\n\nYou should get `TypeError` when executing the code. Adding `integer` type to `string` type is not allowed in Python and many other languages.\n\n```\n>>> hostname = \"rtr-sydney-01-inet\"\n>>> chassis_id = 1\n>>> hostname + chassis_id\nTraceback (most recent call last):\n File \"<stdin>\", line 1, in <module>\nTypeError: can only concatenate str (not \"int\") to str\n```\n\n4.\n\nYou can generally mix `int` and `float` types together. Resulting value will be of type `float`.\n\n```\n>>> response_time_sec = 2\n>>> delay_adjust = 0.1\n>>> response_time_sec - delay_adjust\n1.9\n```\n\n5.\n\nYou should get `TypeError` when executing the code. List items need to be accessed by corresponding index number. \n\n```\n>>> vlans = [\"5\", \"100\", \"120\"]\n>>> vlans[\"5\"]\nTraceback (most recent call last):\n File \"<stdin>\", line 1, in <module>\nTypeError: list indices must be integers or slices, not str\n```\n\nTo get the item `\"5\"` from the below list we should use its index, `0`. Index value has to be an integer and not a string.\n\n```python\n>>> vlans[0]\n'5'\n```\n\n6.\n\nYou should get `KeyError` when executing the code. This data structure is a `dictionary` so you need to use a key name to access the value of interest.\n\n```python\n>>> intf_names = {\"Eth0\": \"Uplink to core\", \"Eth24\": \"Tap switch\"}\n>>> intf_names[0]\nTraceback (most recent call last):\n File \"<stdin>\", line 1, in <module>\nKeyError: 0\n```\n\nInstead of `0` use the key name `\"Eth0\"` to retrieve the corresponding value.\n\n```python\n>>> intf_names[\"Eth0\"]\n'Uplink to core'\n```\n\n> Note that `0` could be used as a key, but you can't treat it like a list index, it would be just another key name.\n\n#### Task 5 - Accessing data in nested data structures\n\nOutput you work with in this task is a deeply nested data structure composed of many dictionaries.\n\nTo access requested values you need to navigate the hierarchy of data structures from the outermost to the innermost. At each level you need to think of the key name that contains the data structure nested below it.\n\nBelow we retrieve values requested in the task and check their data types.\n\n```python\n>>> show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"interfaces\"][\"Port-channel14\"][\"port_state\"]\n'forwarding'\n>>> type(show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"interfaces\"][\"Port-channel14\"][\"port_state\"])\n<class 'str'>\n>>>\n>>> show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"interfaces\"][\"Port-channel14\"][\"port_priority\"]\n128\n>>> type(show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"interfaces\"][\"Port-channel14\"][\"port_priority\"])\n<class 'int'>\n>>>\n>>> show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"root\"][\"priority\"]\n24776\n>>> type(show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"root\"][\"priority\"])\n<class 'int'>\n>>>\n>>> show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"root\"][\"address\"]\n'58bf.eaff.e5b6'\n>>> type(show_spanning_tree[\"rapid_pvst\"][\"vlans\"][200][\"root\"][\"address\"])\n<class 'str'>\n```\n\nThis task shows the importance of understanding container data structures like `list` and `dictionary`. Both of those types can be found at different levels of nesting and you need to know how to traverse the hierarchy to access values of interest.\n\n#### Task 6 - Modifying data structure - list\n\nIn this task you're asked to make an in-place update of the list.\n\nTo do this you need to use index and square brackets `[]` to point to the item you want to replace. Then you assign new value to that index.\n\n```python\n>>> bgp_neighbors = [\"10.40.0.5\", \"10.60.0.11\", \"10.78.0.13\", \"10.90.0.11\", \"10.90.0.13\"]\n>>> bgp_neighbors[2] = \"10.78.0.15\"\n>>> bgp_neighbors\n['10.40.0.5', '10.60.0.11', '10.78.0.15', '10.90.0.11', '10.90.0.13']\n```\n\n#### Task 7 - Modifying data structure - dictionary\n\nIn this task you're updating the value of one of the keys in an existing dictionary.\n\nTo do this update you need to point to the item by navigating the hierarchy of this nested data structure. Then you assign a new value to the item referenced by that pointer.\n\n```python\n>>> site = {\n... \"name\": \"Lessines\",\n... \"status\": {\n... \"value\": \"planned\",\n... },\n... \"region\": {\n... \"name\": \"Belgium\",\n... }\n... }\n>>> site[\"status\"][\"value\"] = \"active\"\n>>> site\n{'name': 'Lessines', 'status': {'value': 'active'}, 'region': {'name': 'Belgium'}}\n```\n\n#### Task 8 - Bonus - converting unstructured text into structured data 1\n\nIn this task you're asked to build data structure from unstructured text. You're asked to use a data type that fits input text the best and you're not allowed to use nested data structures.\n\nYou should notice that the input text contains the name of an interface and various attributes describing its state. For ease of retrieval these attributes would be best represented by key names, so you should build a dictionary and convert attributes into `key: value` pairs.\n\nChoice of key names is arbitrary, below is one of possible solutions.\n\n```python\ninterface_state = {\n \"name\": \"GigabitEthernet0/0/0\",\n \"status\": \"up\",\n \"ip_address\": \"10.134.253.57/29\",\n \"broadcast_address\": \"255.255.255.255\",\n \"mtu\": 1500,\n \"local_proxy_arp_enabled\": False,\n \"split_horizon_enabled\": True\n}\n```\n\n#### Task 9 - Bonus - converting unstructured text into structured data 2\n\nIn this task you're asked to convert unstructured text into structured data. This task is similar to task `8.` but here we are asking to record values of one of the attributes as a `list`.\n\nIn this task you should create a `dictionary`. Key names are again arbitrary but the key name you used to record multicast groups should contain a nested `list` with its items being multicast groups.\n\nBelow is an example solution.\n\n```python\ninterface_status = {\n \"name\": \"GigabitEthernet0/2.1\",\n \"status\": \"up\",\n \"ip_address\": \"192.168.154.1/24\",\n \"broadcast_address\": \"255.255.255.255\",\n \"mtu\": 1500,\n \"mcast_reserved_grups_joined\": [\n \"224.0.0.1\",\n \"224.0.0.2\",\n \"224.0.0.22\",\n \"224.0.0.13\",\n \"224.0.0.5\",\n \"224.0.0.6\",\n ]\n}\n```\n\n#### Task 10 - Bonus - Exploring JSON data\n\nIn this task you have an opportunity to explore JSON data returned from the production system.\n\nCommand `python -i netbox_device.py` will load JSON data for one device. That JSON payload has been returned by NetBox API. This data is assigned to `nb_device` variable to allow you easy access.\n\nSome examples of working with the data are below.\n\n- Name of the device:\n\n```python\n>>> nb_device[\"name\"]\n'sALBEles09'\n```\n\n- Device model:\n\n```python\n>>> nb_device[\"device_type\"][\"display_name\"]\n'Cisco C9300-48P'\n```\n\n- Device role:\n\n```python\n>>> nb_device[\"device_role\"][\"name\"]\n'switch--access-lan'\n```\n\n- Primary IP of this device:\n\n```python\n>>> nb_device[\"primary_ip\"][\"address\"]\n'10.101.122.26/24'\n```\n\n- Site where this device is located:\n\n```python\n>>> nb_device[\"site\"][\"name\"]\n'Lessines'\n```\n" }, { "alpha_fraction": 0.5397412180900574, "alphanum_fraction": 0.5409734845161438, "avg_line_length": 27.473684310913086, "blob_id": "9b39175701c7d4f0b575a25a8499dd4856030978", "content_id": "f8d782b30f8ba537895326506992431c92fc894e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1623, "license_type": "no_license", "max_line_length": 115, "num_lines": 57, "path": "/workshops/extending-ansible/lab05/modules/iosxe_gather_configs.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "#! /usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\n\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n\n module_args = dict(\n host=dict(type=\"str\", required=True),\n user=dict(type=\"str\", required=True),\n password=dict(type=\"str\", required=True, no_log=True),\n filter=dict(\n type=\"str\",\n required=False,\n default=\"all\",\n choices=[\n \"all\",\n \"version\",\n \"memory\",\n \"platform\",\n \"hostname\",\n \"username\",\n \"vrf\",\n \"ip\",\n \"cdp\",\n \"interface\",\n \"login\",\n \"snmp-server\",\n \"lldp\",\n ],\n ),\n )\n\n module = AnsibleModule(argument_spec=module_args)\n\n auth = HTTPBasicAuth(module.params[\"user\"], module.params[\"password\"])\n\n if module.params[\"filter\"] == \"all\":\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/\"\n elif module.params[\"filter\"] == \"lldp\":\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/Cisco-IOS-XE-lldp:lldp\"\n else:\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/{module.params['filter']}\"\n\n headers = {\"Accept\": \"application/yang-data+json\"}\n\n response = requests.get(url, headers=headers, auth=auth, verify=False)\n\n module.exit_json(msg=response.json())\n\n\nif __name__ == \"__main__\":\n main()\n" }, { "alpha_fraction": 0.7247706651687622, "alphanum_fraction": 0.752293586730957, "avg_line_length": 20.799999237060547, "blob_id": "ac35fbcc18dd18267dfd4c4cb911839fa67e33bb", "content_id": "ea31092642f283023b7650da82c7cf7005c60bd1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 109, "license_type": "no_license", "max_line_length": 54, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/jcy-spine-01.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# jcy-spine-01.infra.ntc.com\n\nThis Cisco Nexus 9Kv device is located in Jersey City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6105263233184814, "alphanum_fraction": 0.7368420958518982, "avg_line_length": 18, "blob_id": "7ab7044265b30699a3e3d623c4b77e5a259c2877", "content_id": "5f956a482e0ae6d6742a5318b029f7d1dd302883", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 95, "license_type": "no_license", "max_line_length": 48, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-IDF02-R01-SW02/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-IDF02-R01-SW02\n\nThis Cisco WS-C3850-48U device is located in HQ.\n\nIts status is: Planned.\n" }, { "alpha_fraction": 0.6087874174118042, "alphanum_fraction": 0.6487526297569275, "avg_line_length": 24.33333396911621, "blob_id": "7bcc8121f69c41120bcd7341deae9eeeb0f20051", "content_id": "8fc40b34ef9fe4579dbf9d1b3f40ee5fc77d3493", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 8065, "license_type": "no_license", "max_line_length": 163, "num_lines": 318, "path": "/challenges/09-data-structures/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Introduction to Data Structures\n \nThe goal of this exercise is to learn about common types of data structures. You will learn how to recognize data types and how to interact with them using Python.\n \n## Exercise Overview\n \n### Prerequisites\n \nYou will need to have a Python interpreter installed on your machine. Optionally you can also use a code editor, like VSCode, to persist your work.\n \n### Tasks\n \nSubmitting your solution for this challenge is optional - feel free to ask for help via email, chat, or at the open office hours if you get stuck!\n \n#### Task 1 - Basic data types\n \nListed below are variables containing different data types. You need to identify each of the types.\n \n1.\n \n```python\nhostname = \"sALBEles09\"\n```\n \n2. \n \n```python\nvc_priority = 15\n```\n \n \n3. \n \n```python\ncpu_load = 72.56\n```\n \n4.\n \n```python\nrouting_enabled = True\n```\n \n5. \n \n```python\nvlan_ids = [10, 300, 301, 302, 1400]\n```\n \n6. \n \n```python\nvlans = {\n \"10\": \"Production\",\n \"300\": \"Engineering\",\n \"301\": \"Voice\",\n \"302\": \"Printers\"\n}\n```\n \n> Hint: Above lines can be copy pasted into your Python interpreter, where you can use `type()` function to check variable type.\n \n#### Task 2 - Accessing data - list\n \nGiven the below list, use Python to retrieve:\n \n- Name of the 1st interface on the list.\n- Name of the last interface on the list.\n \n```python\ninterfaces = [\"GigabitEthernet1\", \"GigabitEthernet2\", \"GigabitEthernet3\", \"GigabitEthernet4\"]\n```\n \n#### Task 3 - Accessing data - dictionary\n \nGiven the below dictionary, write Python expressions retrieving values of:\n \n- Five minute cpu load.\n- Name of the process.\n- Number of times the process was invoked.\n \nWhat data type are each of these values?\n \n```python\ncpu_process = {\n \"five_min_cpu\": 0.46,\n \"five_sec_cpu\": 0.0,\n \"invoked\": 11390,\n \"one_min_cpu\": 0.59,\n \"pid\": 9,\n \"process\": \"Check heaps\",\n \"runtime\": 192629,\n \"tty\": 0,\n \"usecs\": 16912,\n }\n```\n \n#### Task 4 - Mixing data types\n \nCopy the below Python statements into your interpreter and execute them. For each example answer the below questions:\n \n- What is the result of the execution?\n- Is the observed behavior something you expected?\n- Can you think of an explanation for these results?\n \n1.\n \n```python\nis_cisco = \"False\"\nis_switch = \"True\"\nis_cisco and is_switch\n```\n \n2.\n \n```python\nis_router = \"False\"\nis_asr1000 = True\nis_router or is_asr1000\n```\n \n3.\n \n```python\nhostname = \"rtr-sydney-01-inet\"\nchassis_id = 1\nhostname + chassis_id\n```\n \n4.\n \n```python\nresponse_time_sec = 2\ndelay_adjust = 0.1\nresponse_time_sec - delay_adjust\n```\n \n5.\n \n```python\nvlans = [\"5\", \"100\", \"120\"]\nvlans[\"5\"]\n```\n \n6.\n \n```python\nintf_names = {\"Eth0\": \"Uplink to core\", \"Eth24\": \"Tap switch\"}\nintf_names[0]\n```\n \n> Hint: Think about data types used in each of the statements. \n> Use `type()` to see the type of input variables and the result.\n \n#### Task 5 - Accessing data in nested data structures\n \nYou are given the output of the `show spanning tree` command. You need to retrieve the following values from this data structure:\n \n- STP port state of \"Port-channel14\".\n- STP port priority of \"Port-channel14\".\n- Priority of the root bridge.\n- Address of the root bridge.\n \nWhat type are each of the above values?\n \n```python\nshow_spanning_tree = {\n \"rapid_pvst\": {\n \"vlans\": {\n 200: { \n \"interfaces\": {\n \"Port-channel14\": {\n \"port_state\": \"forwarding\",\n \"port_num\": 2390,\n \"port_priority\": 128,\n \"type\": \"P2p\",\n \"cost\": 3,\n \"role\": \"root\"\n }\n },\n \"root\": {\n \"hello_time\": 2,\n \"priority\": 24776,\n \"forward_delay\": 15,\n \"max_age\": 20,\n \"cost\": 3,\n \"address\": \"58bf.eaff.e5b6\",\n \"interface\": \"Port-channel14\",\n \"port\": 2390\n }\n }\n }\n }\n}\n```\n \n> Hint: This is a deeply nested dictionary. You might need to traverse a few levels before you can access the final value.\n> Think about key names for each of the levels you need to access.\n \n#### Task 6 - Modifying data structure - list\n \nBGP neighbors for one of your devices are stored in the below list. Neighbor \"10.78.0.13\" had IP conflict and needs to change its IP to \"10.78.0.15\". \n \n- Write a Python expression replacing the old IP value with the new one. \n \nDo NOT create a new list, work with the existing one.\n \n```python\nbgp_neighbors = [\"10.40.0.5\", \"10.60.0.11\", \"10.78.0.13\", \"10.90.0.11\", \"10.90.0.13\"]\n```\n \n> Hint: Values can be assigned to individual items on the list.\n \n#### Task 7 - Modifying data structure - dictionary\n \nBelow NetBox site is being moved into production. \n \n- Update status of the site to \"active\" to reflect that.\n \n```python\nsite = {\n \"name\": \"Lessines\",\n \"status\": {\n \"value\": \"planned\",\n },\n \"region\": {\n \"name\": \"Belgium\",\n }\n}\n```\n\n> Hint: Similar to lists, values can be assigned to individual keys in a dictionary.\n \n#### Task 8 - Bonus - converting unstructured text into structured data 1\n \nConvert the below unstructured text to a structured data. Use a data structure type that fits this data best.\n \nRecord the final data structure using Python syntax. Assign it to `interface_state` variable.\n \nThink about data types for each of the values you are capturing.\n \nDo NOT use nested data structures.\n \n```\nGigabitEthernet0/0/0 is up, line protocol is up\n Internet address is 10.134.253.57/29\n Broadcast address is 255.255.255.255\n MTU is 1500 bytes\n Local Proxy ARP is disabled\n Split horizon is enabled\n```\n \n> Hint: This task is open-ended, you're free to choose any names that make sense to you.\n \n#### Task 9 - Bonus - converting unstructured text into structured data 2\n \nConvert the below unstructured text to nested data structure.\n \nMulticast groups should be recorded in a list.\n \nRecord the final data structure using Python syntax. Assign it to `interface_state` variable.\n \n```\nGigabitEthernet0/2.1 is up, line protocol is up\n Internet address is 192.168.154.1/24\n MTU is 1500 bytes\n Broadcast address is 255.255.255.255\n Multicast reserved groups joined: 224.0.0.1 224.0.0.2 224.0.0.22 224.0.0.13\n 224.0.0.5 224.0.0.6\n```\n \n> Hint: You're free to choose names in your data structures that feel most appropriate to you.\n \n#### Task 10 - Bonus - Exploring JSON data\n \nIn this task you will explore, using Python, JSON data describing single device, returned by NetBox API.\n \nThis is an open-ended task. Follow instructions below to load data into your Python interpreter.\n \nTry to access values of different attributes at varying levels of nesting. Investigate data types for values you’re accessing.\n\n##### Steps for loading data\n\n- Navigate to the directory named `files` contained within the challenge directory.\n\nFor example:\n\n```\n /home/przemek/enablement/enablement-program-baxter/challenges/09-data-structures\n❯ cd files\n❯ pwd\n/home/przemek/enablement/enablement-program-baxter/challenges/09-data-structures/files\n```\n \n- Once you're in the `files` directory, execute the below command to load JSON data and launch the Python interpreter.\n \n```\npython -i netbox_device.py\n```\n \nYou should see output similar to the one below.\n \n```python\n❯ python -i netbox_device.py\nLoaded JSON data into 'nb_device' variable.\n\nYou can use 'pp(nb_device)' to display all of the data.\n>>>\n```\n \n- Loaded JSON data is assigned to the `nb_device` variable. You can use the `pp(nb_device)` statement to show you the structure of the data.\n \n \n### Reference Enablement Material\n \n- Introduction to Data Structures\n \n> Note: Recordings of the relevant sessions can be found online at: https://training.networktocode.com/ \n" }, { "alpha_fraction": 0.6688596606254578, "alphanum_fraction": 0.6820175647735596, "avg_line_length": 37, "blob_id": "a1a0b148da479d20ff5e679b2b835fac754e9e52", "content_id": "5e54ee304e01edbcd0567396fe1ad60faed490f9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 456, "license_type": "no_license", "max_line_length": 87, "num_lines": 12, "path": "/challenges/04-codelint/files/code/custom_rules/CapitalNamesRule.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "from ansiblelint import AnsibleLintRule\nclass CapitalNamesRule(AnsibleLintRule):\n id = \"289\"\n shortdesc=\"All task names should be capitalized\"\n description='Using all uppercase names creates uniformity and improves readability'\n severity='LOW'\n tags= ['formatting\", \"readability']\n version_added = \"v4.0.0\"\n\n def matchtask(self, file, task):\n if task.get(\"name\"):\n return task.get(\"name\") != task.get(\"name\").upper()\n" }, { "alpha_fraction": 0.7496516108512878, "alphanum_fraction": 0.7586103677749634, "avg_line_length": 45.94392395019531, "blob_id": "ab10d0672d72adc6e921b5a1d5c6d908f360e665", "content_id": "5f8ae55ef549a8fb457679412a1845ca19c811b0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 10046, "license_type": "no_license", "max_line_length": 306, "num_lines": 214, "path": "/challenges/11-http-apis/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Introduction to HTTP APIs\n\nThe goal of this exercise is to learn about HTTP APIs. You will learn how to recognise different types of HTTP APIs and how to interact with them using cURL and Postman.\n\n## Exercise Overview\n\n### Prerequisites\n\n- You need to have `cURL` utility installed on your machine.\n - If you don't have `cURL` you should use your package manager to install it. E.g. for Ubuntu you would use `sudo apt install curl`.\n\n- You need to have the `Postman` program installed. You can download it from [Postman website](https://www.postman.com/downloads/).\n\n### Tasks\n\nSubmitting your solution for this challenge is optional - feel free to ask for help via email, chat, or at the open office hours if you get stuck!\n\n\n#### Task 1 - HTTP methods\n\nREST APIs reuse existing HTTP methods to perform CRUD (create, retrieve, update, delete) operations.\n\nYou are asked to:\n\n1. Write down next to each of the methods what it is used for.\n\n2. Give an example of how each method could perform an operation against the API of NetBox or a network device.\n\n3. Explain the difference between PATCH and PUT methods.\n\nHTTP methods:\n\n- GET\n- POST\n- PATCH\n- PUT\n- DELETE\n\n\n#### Task 2 - HTTP headers\n\nHTTP headers carry metadata about a request and are very important when talking to APIs.\n\nBelow are the names of a few HTTP headers. Can you explain what each of them is used for?\n\n1. Accept\n\n2. Authorization\n\n3. Content-Type\n\n\n#### Task 3 - HTTP headers - content types\n\nWhen communicating with APIs you will often need to specify the type of data you want to receive or send.\n\nFor this task, you are asked to write down the header name, and the value the header should have. Do it for each of the below cases:\n\n1. You are talking to the REST API and you want to receive `json` data.\n\n2. You are creating a new resource with POST request, using `json` data, sent to REST API .\n\n3. You want a device running RESTCONF to return interface data in `xml` format.\n\n4. You want to create a new VLAN on your device using RESTCONF API and `json` data.\n\n> Hint: Pay attention to API types when choosing data type.\n\n#### Task 4 - REST and non-REST APIs\n\nRESTful APIs tend to behave in a similar way, once you learned one it's easier to get started with another. Non-REST API usually requires more effort to get started. By looking at methods and URL format used by the API we might be able to tell if an API is RESTful or not.\n\nBelow you're given some information on several APIs. Answer how likely it is that the API is RESTful for each of them. Provide a short explanation for each of your answers.\n\n1. This system has an API that uses POST method to retrieve information on the objects.\n\n2. Network device with API using GET, POST, PATCH, PUT, DELETE. Different resources use different URL paths.\n\n3. Network device with API that requires CLI commands to be sent in the data payload.\n\n> Hint: Think about REST principles and how HTTP methods map to CRUD operations in RESTful APIs.\n\n#### TASK 5 - NetBox API - getting data\n\nIn this task you are asked to retrieve some data from NetBox via API.\n\nFor this task use the below freely available online instance of NetBox:\n\n- URL: https://netboxdemo.com/\n- API token: 72830d67beff4ae178b94d8f781842408df8069d\n\n1. Using `Postman` get data on existing VLANs. Take a screenshot showing request details and response.\n\n2. Using `Postman` get data on an individual VLAN. Take a screenshot showing request details and response.\n\n3. Using `cURL` get data on device manufacturers. Copy the command you used and the output.\n\n4. Using `cURL` get data on a single device manufacturer. Copy the command you used and the output.\n\n> Hints:\n> - Don't forget to submit authorization details.\n> - API documentation is available at: https://netboxdemo.com/api/docs/\n> - NetBox documentation is available at: https://netbox.readthedocs.io/en/stable/\n> - With cURL, you can prettify output from NetBox API by adding `; indent=4` characters right after the value of the content type you want to get back.\n\n#### TASK 6 - NetBox API - modifying data\n\nIn this task you are asked to create and modify resources stored in NetBox using its API. \n\nFor this task use the below freely available online instance of NetBox:\n\n- URL: https://netboxdemo.com/\n- API token: 72830d67beff4ae178b94d8f781842408df8069d\n\n1. Using `Postman` create a new VLAN. Use VLAN ID that's not currently in use. You can give a description to your VLAN. Take a screenshot showing request details and response.\n\n2. Using `Postman` update the VLAN you just created. You need to change its description to `BACKUP_VLAN_{VID}`, where `{VID}` is VLAN ID of your VLAN, e.g. `BACKUP_VLAN_911`.\n\n Data you send to an API should contain only one key-value pair. Take a screenshot showing request details and response.\n\n3. Using `cURL` delete the VLAN object you created in step 1. Use the `-i` option to see headers in the response. This will show you response code among other things. Copy the command you used and the output.\n\n> Hints:\n> - When performing merge and delete operations you need to specify the URL object you're modifying.\n> - Don't forget to provide authentication details when using cURL.\n> - Some REST API responses contain no data but all should have HTTP response code.\n\n\n#### Task 7 - IOS-XE RESTCONF - getting data\n \nIn this task you are asked to use API to retrieve configuration items from a Cisco device running IOS-XE.\n\nFor this task use the below Cisco always-on sandbox device:\n\n- URL: https://ios-xe-mgmt.cisco.com:9443\n- username: developer\n- password: C1sco12345\n\n1. Using `Postman` retrieve interfaces configured on this device. Use the `Cisco-IOS-XE-native` YANG model for this task. Take a screenshot showing request details and response.\n\n2. Using `Postman` retrieve description of interface `GigabitEthernet1`. Use the `Cisco-IOS-XE-native` YANG model for this task. Take a screenshot showing request details and response.\n\n3. Using `cURL` retrieve route maps configured on this device. Use the `Cisco-IOS-XE-native` YANG model for this task. Copy the command you used and the output.\n\n> Hints:\n> - Base URL for RESTCONF API on IOS-XE is `https://ios-xe-mgmt.cisco.com:9443/restconf/data/`.\n> - To navigate nested data structure in RESTCONF place name of the key after `/` character. For lists use `=` notation after the name of the resource to get a specific item. E.g. `../FastEthernet=1/` would return data on interface `FastEthernet1` with `FastEthernet` being a list container.\n\n\n#### Task 8 - Bonus (Intermediate) - IOS-XE RESTCONF - creating resource\n\nIn this task you are asked to use API to create a new resource on a Cisco device running IOS-XE.\n\nFor this task use the below Cisco always-on sandbox device:\n\n- URL: https://ios-xe-mgmt.cisco.com:9443\n- username: developer\n- password: C1sco12345\n\n1. Using `Postman` create a new Loopback interface on this device. Use the first available interface number in range 100 - 999. Your interface MUST have description and IP address. Use the `Cisco-IOS-XE-native` YANG model for this task. Take a screenshot showing request details and response.\n\n> Hint: To build data needed to create interface you can reuse data returned by GET method.\n\n\n#### Task 9 - Bonus (Advanced) - IOS-XE RESTCONF - modifying resource\n\nIn this task you are asked to use API to modify an existing resource on a Cisco device running IOS-XE.\n\nFor this task use the below Cisco always-on sandbox device:\n\n- URL: https://ios-xe-mgmt.cisco.com:9443\n- username: developer\n- password: C1sco12345\n\n1. Using `Postman` change description of the Loopback interface you created in Task 8. New description should be created by appending string `-fixme` to existing description. Use the merge operation and `Cisco-IOS-XE-native` YANG model for this task. Take a screenshot showing request details and response.\n\n> Hint: To update resource you can specify the type and name of the target interface in your data or in the resource URL.\n\n#### Task 10 - Bonus (Advanced) - IOS-XE RESTCONF - deleting resource\n\nIn this task you are asked to use API to delete an existing resource on a Cisco device running IOS-XE.\n\nFor this task use the below Cisco always-on sandbox device:\n\n- URL: https://ios-xe-mgmt.cisco.com:9443\n- username: developer\n- password: C1sco12345\n\n1. Using `cURL` delete the Loopback interface you created in Task 8. Use URL to specify the interface to be deleted. Use the `Cisco-IOS-XE-native` YANG model for this task. Provide a copy of the command you used and the output.\n\n2. Using `cURL` confirm the Loopback interface is gone from the device. Use URL to specify the interface you want to check. Use the `Cisco-IOS-XE-native` YANG model for this task. Provide a copy of the command you used and the output.\n\n> Hints:\n> - You need to refer to cURL docs to find out which option is used for authentication.\n> - You need to allow a self-signed certificate in this task. Find in the cURL docs option that does that.\n> - Key name can be used in URL after the name of the resource using `=` character.\n\n### Reference Enablement Material\n \n- Introduction to Data Structures\n- Introduction to REST APIs\n- Network Programming and Automation course\n \n> Note: Recordings of the relevant sessions can be found online at: https://training.networktocode.com/ \n\n### External references\n\n- Official NetBox docs, section on API: https://netbox.readthedocs.io/en/stable/rest-api/overview/\n- NetBox Demo built-in API docs: https://netboxdemo.com/api/docs/\n- cURL Documentation: https://curl.se/docs/tooldocs.html\n- RFC8040 - RESTCONF Protocol. Very detailed and technical but still one of the best resources for learning RESTCONF: https://tools.ietf.org/html/rfc8040\n- Wikipedia article on REST. Good overview and some history of REST architecture. https://en.wikipedia.org/wiki/Representational_state_transfer\n- YANG catalog. Tools for working with and exploring YANG models. https://yangcatalog.org/\n - See for example `yang-search` results for `Cisco-IOS-XE-native` YANG model: https://yangcatalog.org/yang-search/yang_tree/Cisco-IOS-XE-native@2019-11-01\n" }, { "alpha_fraction": 0.6525518894195557, "alphanum_fraction": 0.6617861390113831, "avg_line_length": 31.7980899810791, "blob_id": "8c754cda0d8362c003b430fff0a34befa63444c0", "content_id": "c1403d8f0d22a0fd32217cc85d3e606ece1af40e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 24071, "license_type": "no_license", "max_line_length": 423, "num_lines": 733, "path": "/workshops/extending-ansible/lab06_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Extending Ansible - Lab 06\n\nIn this lab exercise you will create a custom module for Ansible that performs changes against the IOS-XE RESTCONF API endpoints, specifically to manage VRF configuration.\n\n## Task 1 - Building the VRF REST Module\n\nTo start with, you will create a new module that makes changes to a specific VRF's description via the API.\n\n### Step 1\n\nIn your terminal on the lab workstation, change into the `/home/ntc/labs/lab06` folder, creating it if it doesn't exist.\n\n```\nntc@ntc-training:~$ mkdir -p /home/ntc/labs/lab06\nntc@ntc-training:~$ cd /home/ntc/labs/lab06\nntc@ntc-training:lab06$\n```\n\n### Step 2\n\nCreate a folder named `modules` and in it a file called `iosxe_rest_vrf.py`.\n\n```\nntc@ntc-training:lab06$ mkdir modules\nntc@ntc-training:lab06$ touch modules/iosxe_rest_vrf.py\nntc@ntc-training:lab06$ tree\n.\n└── modules\n └── iosxe_rest_vrf.py\n\n1 directory, 1 file\n```\n\n### Step 3\n\nOpen the `modules/iosxe_rest_vrf.py` file in your editor and add the following code:\n\n```py\n#!/usr/bin/env python3\n\nDOCUMENTATION = \"\"\"\n\"\"\"\n\nEXAMPLES = \"\"\"\n\"\"\"\n\nRETURN = \"\"\"\n\"\"\"\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nimport json\n\nrequests.packages.urllib3.disable_warnings()\n\ndef main():\n pass\n\nif __name__ == \"__main__\":\n main()\n```\n\n> This is just the scaffolding for the module and over the following steps you will build its full functionality and documentation.\n\n### Step 4\n\nIn the `modules/iosxe_rest_vrf.py` file, change the EXAMPLES string to the following value.\n\n```py\nEXAMPLES = \"\"\"\n# Collect Device Version\n- name: UPDATE VRF DESCRIPTION\n iosxe_rest_vrf:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ username }}\"\n password: \"{{ password }}\"\n name: CORP\n description: VRF FOR CORPORATE USERS\n\"\"\"\n```\n\nYou can use this to build a visual representation of how the module would be used - it helps to work out what parameters it needs when called from a playbook.\n\nSince the module will be sending REST calls to an authenticated API, you need the device's IP or hostname (the `host` parameter), and the `user` and `password`.\n\nAs for the other parameters, the goal here is to provide an abstracted interface to make changes to a VRF's description. So you need to provide a VRF `name` and a VRF `description`.\n\n### Step 5\n\nIn the `modules/iosxe_rest_vrf.py` file, change the DOCUMENTATION string to the following value.\n\n```py\nDOCUMENTATION = \"\"\"\n---\nmodule: iosxe_rest_vrf\nshort_description: This module updates VRF configuration via the IOSXE REST API.\nversion_added: \"1.0.0\"\ndescription: This module uses the requests Python library to make API calls against the IOSXE device.\noptions:\n host:\n description: Enter the IP or hostname of the IOSXE device\n required: true\n type: str\n user:\n description: Enter the device username\n required: true\n type: str\n password:\n description: Enter the device password\n required: true\n type: str\n verify:\n description: Enable or disable SSL verification, it will disabled by default\n required: false\n type: bool\n name:\n description: The VRF's name you want to manage\n required: true\n type: str\n description:\n description: The VRF's description (optional)\n required: false\n type: str\n\nauthor:\n - NetworkToCode (@networktocode)\n\"\"\"\n```\n\nThis is what `ansible-doc` will use to generate the documentation page for the custom module and is a more programmatic way of defining each parameter you sketched out in the previous step's EXAMPLES.\n\nTake special notice of each parameter's metadata - i.e. `required`, `type`, and `description`.\n\n### Step 6\n\nContinue editing the file and replace the `pass` statement (which does nothing) in the `main()` function as shown below.\n\n```py\ndef main():\n # define available arguments/parameters a user can pass to the module\n module_args = dict(\n host=dict(type=\"str\", required=True),\n user=dict(type=\"str\", required=True),\n password=dict(type=\"str\", required=True, no_log=True),\n verify=dict(type=\"bool\", default=False),\n name=dict(type=\"str\", required=True),\n description=dict(type=\"str\", required=False),\n )\n module = AnsibleModule(argument_spec=module_args, supports_check_mode=False)\n\n # prepare the standard return object\n result = dict(changed=False)\n```\n\nThe `module_args` dictionary holds the argument spec or the actual code that specifies the module parameters as detailed in the `DOCUMENTATION` string earlier. This is used by the Ansible engine during execution.\n\nSince this module does not yet support `check mode`, we set that when instantiating the AnsibleModule class. Finally, `result` is a dictionary that holds the data you wish the module to return to the Ansible engine once it finishes execution.\n\n> The `module_args` and the `DOCUMENTATION` string should be kept in sync! Any discrepancies will only cause confusion to users of your module.\n\n### Step 7\n\nUpdate the `RETURN` string with the following code:\n\n```py\nRETURN = \"\"\"\n# These are examples of possible return values, and in general should use other names for return values.\nsent_payload:\n description: The VRF data that will be sent to the API via the PATCH request\n type: str\n returned: always\n sample: '{\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}'\nmsg:\n description: A status message including the HTTP response code.\n type: str\n returned: always\n sample: 'OK 204'\n\"\"\"\n```\n\nThis is used by documentation to explain what additional data the module is returning - here the plan is to return `sent_payload` (the JSON API payload built for the request) and `msg` which is a custom message that includes the HTTP response code (e.g. 204 or 404).\n\n### Step 8\n\nIn the `/home/ntc/labs/lab06` folder, create a new file called `ansible.cfg` with the content below. You need to tell Ansible where to find your custom module - in this case you're telling it to search in the current path for a folder called `modules`.\n\n```\n[defaults]\n\n# Disable automatic facts gathering.\ngathering = explicit\n\n# Instruct Ansible to look locally for modules\nlibrary = modules\n```\n\n### Step 9\n\nVerify that your folder structure looks like the output below.\n\n```\nntc@ntc-training:lab06$ tree\n.\n├── ansible.cfg\n└── modules\n └── iosxe_rest_vrf.py\n\n1 directory, 2 files\n```\n\n### Step 10\n\nVerify where Ansible looks for modules, also called the library or module search path.\n\n```\nntc@ntc-training:lab06$ ansible --version\nansible 2.9.9\n config file = /home/ntc/labs/lab06/ansible.cfg\n configured module search path = ['/home/ntc/labs/lab06/modules']\n ansible python module location = /usr/local/lib/python3.6/site-packages/ansible\n executable location = /usr/local/bin/ansible\n python version = 3.6.8 (default, Jun 11 2019, 01:16:11) [GCC 6.3.0 20170516]\n```\n\n### Step 11\n\nSince the module's documentation is fully defined, you can already inspect it using the `ansible-doc` command. Notice that the output is built from the information you defined in the `DOCUMENTATION`, `EXAMPLES`, and `RETURN` strings inside of your custom module file.\n\n```\nntc@ntc-training:lab06$ ansible-doc iosxe_rest_vrf\n> IOSXE_REST_VRF (/home/ntc/labs/lab06/modules/iosxe_rest_vrf.py)\n\n This module uses the requests Python library to make API calls against the IOSXE device.\n\n * This module is maintained by The Ansible Community\nOPTIONS (= is mandatory):\n\n- description\n The VRF's description (optional)\n [Default: (null)]\n type: str\n\n= host\n Enter the IP or hostname of the IOSXE device\n\n type: str\n\n= name\n The VRF's name you want to manage\n\n type: str\n\n= password\n Enter the device password\n\n type: str\n\n= user\n Enter the device username\n\n type: str\n\n- verify\n Enable or disable SSL verification, it will disabled by default\n [Default: (null)]\n type: bool\n\n\nAUTHOR: NetworkToCode (@networktocode)\n METADATA:\n status:\n - preview\n supported_by: community\n\n\nEXAMPLES:\n\n# Collect Device Version\n- name: UPDATE VRF DESCRIPTION\n iosxe_rest_vrf:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ username }}\"\n password: \"{{ password }}\"\n name: CORP\n description: VRF FOR CORPORATE USERS\n\n\nRETURN VALUES:\n\n# These are examples of possible return values, and in general should use other names for return values.\nsent_payload:\n description: The VRF data that will be sent to the API via the PATCH request\n type: str\n returned: always\n sample: '{\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}'\nmsg:\n description: A status message including the HTTP response code.\n type: str\n returned: always\n sample: 'OK 204'\n```\n\n### Step 12\n\nTime to build the actual REST API call! Edit the `iosxe_rest_vrf.py` file and add the following code to the end of the `main()` function definition.\n\n```py\n# set up the API request parameters\n auth = requests.auth.HTTPBasicAuth(module.params[\"user\"], module.params[\"password\"])\n # this module supports only json\n headers = {\n \"Accept\": \"application/yang-data+json\",\n \"Content-Type\": \"application/yang-data+json\",\n }\n # this module supports only the Cisco-IOS-XE-native data model\n base_url = (\n f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native\"\n )\n # manages vrf by name\n url = f\"{base_url}/Cisco-IOS-XE-native:vrf/definition={module.params['name']}\"\n\n # build PATCH request payload\n payload = {\"Cisco-IOS-XE-native:definition\": {\"name\": f\"{module.params['name']}\"}}\n\n # only set if it's defined since an empty description is not acceptable by the API\n if module.params[\"description\"]:\n payload[\"Cisco-IOS-XE-native:definition\"][\n \"description\"\n ] = f\"{module.params['description']}\"\n\n # add this to the module output for easier troubleshooting\n result[\"sent_payload\"] = payload\n```\n\nThis code builds the necessary variables needed to send an HTTP API call (URL, data, headers, authentication) from both hard-coded values (e.g. we only support JSON data) and dynamic module parameters (e.g. VRF name, description, hostname, user, password).\n\n### Step 13\n\nThe URL and payload are built by referencing an example output from the IOS-XE API for the VRF object. Take some time to compare the structure below to the code added in the previous step.\n\n```json\n{\n \"Cisco-IOS-XE-native:vrf\": {\n \"definition\": [\n {\n \"name\": \"CORP\",\n \"description\": \"VRF for Corporate Users\"\n },\n {\n \"name\": \"MANAGEMENT\",\n \"address-family\": {\n \"ipv4\": {\n },\n \"ipv6\": {\n }\n }\n }\n ]\n }\n}\n```\n\n### Step 14\n\nFinally, add this block of code at the end of the `main()` function. This actually sends the request to the API and handles the results accordingly.\n\n```py\n # send the API request to the device (PATCH)\n response = requests.patch(\n url,\n data=json.dumps(payload),\n headers=headers,\n auth=auth,\n verify=module.params[\"verify\"],\n )\n\n # return the json response from the API if it exists\n if response.text:\n result[\"json\"] = response.json()\n\n # since it's a blind PATCH request, always assume a change was made\n if response.ok:\n result[\"changed\"] = True\n result[\"msg\"] = f\"OK {response.status_code}\"\n # the request failed so the module should fail as well\n else:\n result[\"msg\"] = f\"API request failed with code {response.status_code}\"\n module.fail_json(result)\n\n # return successfully and pass the results to ansible\n module.exit_json(result)\n```\n\nIf the API request is successful (`response.ok` is True), then inform Ansible that the modules has performed a change.\n\nIn case of a failure (API is unavailable, authentication fails, resource does not exist etc.), you must also inform Ansible that the module has failed and provide an error message.\n\n### Step 15\n\nThe full `iosxe_rest_vrf.py` file is included below for reference - compare it with your own before going further!\n\n```py\n#!/usr/bin/env python3\n\nDOCUMENTATION = \"\"\"\n---\nmodule: iosxe_rest_vrf\nshort_description: This module updates VRF configuration via the IOSXE REST API.\nversion_added: \"1.0.0\"\ndescription: This module uses the requests Python library to make API calls against the IOSXE device.\noptions:\n host:\n description: Enter the IP or hostname of the IOSXE device\n required: true\n type: str\n user:\n description: Enter the device username\n required: true\n type: str\n password:\n description: Enter the device password\n required: true\n type: str\n verify:\n description: Enable or disable SSL verification, it will disabled by default\n required: false\n type: bool\n name:\n description: The VRF's name you want to manage\n required: true\n type: str\n description:\n description: The VRF's description (optional)\n required: false\n type: str\n\nauthor:\n - NetworkToCode (@networktocode)\n\"\"\"\n\nEXAMPLES = \"\"\"\n# Collect Device Version\n- name: UPDATE VRF DESCRIPTION\n iosxe_rest_vrf:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ username }}\"\n password: \"{{ password }}\"\n name: CORP\n description: VRF FOR CORPORATE USERS\n\"\"\"\n\nRETURN = \"\"\"\n# These are examples of possible return values, and in general should use other names for return values.\nsent_payload:\n description: The VRF data that will be sent to the API via the PATCH request\n type: str\n returned: always\n sample: '{\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}'\nmsg:\n description: A status message including the HTTP response code.\n type: str\n returned: always\n sample: 'OK 204'\n\"\"\"\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nimport json\n\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n # define available arguments/parameters a user can pass to the module\n module_args = dict(\n host=dict(type=\"str\", required=True),\n user=dict(type=\"str\", required=True),\n password=dict(type=\"str\", required=True, no_log=True),\n verify=dict(type=\"bool\", default=False),\n name=dict(type=\"str\", required=True),\n description=dict(type=\"str\", required=False),\n )\n module = AnsibleModule(argument_spec=module_args, supports_check_mode=False)\n\n # prepare the standard return object\n result = dict(changed=False)\n\n # set up the API request parameters\n auth = requests.auth.HTTPBasicAuth(module.params[\"user\"], module.params[\"password\"])\n # this module supports only json\n headers = {\n \"Accept\": \"application/yang-data+json\",\n \"Content-Type\": \"application/yang-data+json\",\n }\n # this module supports only the Cisco-IOS-XE-native data model\n base_url = (\n f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native\"\n )\n # manages vrf by name\n url = f\"{base_url}/Cisco-IOS-XE-native:vrf/definition={module.params['name']}\"\n\n # build PATCH request payload\n payload = {\"Cisco-IOS-XE-native:definition\": {\"name\": f\"{module.params['name']}\"}}\n\n # only set if it's defined since an empty description is not acceptable by the API\n if module.params[\"description\"]:\n payload[\"Cisco-IOS-XE-native:definition\"][\n \"description\"\n ] = f\"{module.params['description']}\"\n\n # add this to the module output for easier troubleshooting\n result[\"sent_payload\"] = payload\n\n # send the API request to the device (PATCH)\n response = requests.patch(\n url,\n data=json.dumps(payload),\n headers=headers,\n auth=auth,\n verify=module.params[\"verify\"],\n )\n\n # return the json response from the API if it exists\n if response.text:\n result[\"json\"] = response.json()\n\n # since it's a blind PATCH request, always assume a change was made\n if response.ok:\n result[\"changed\"] = True\n result[\"msg\"] = f\"OK {response.status_code}\"\n # the request failed so the module should fail as well\n else:\n result[\"msg\"] = f\"API request failed with code {response.status_code}\"\n module.fail_json(result)\n\n # return successfully and pass the results to ansible\n module.exit_json(result)\n\n\nif __name__ == \"__main__\":\n main()\n```\n\n## Task 2 - Using the VRF Module\n\nHere you will start using the basic VRF module you created to make some changes to a CSR's configuration.\n\n### Step 1\n\nIn the `/home/ntc/labs/lab06` folder, create a new file called `pb_vrf.yml` with the content below.\n\n```yml\n---\n\n- name: TESTING THE IOSXE_REST_VRF MODULE\n hosts: localhost\n gather_facts: false\n\n tasks:\n - name: UPDATE DESCRIPTION FOR CORP VRF\n iosxe_rest_vrf:\n host: csr1\n user: ntc\n password: ntc123\n name: CORP\n description: VRF FOR CORPORATE USERS\n```\n\n> Note: All the necessary data is embedded into the playbook, since this is early testing!\n\n### Step 2\n\nRun the playbook `pb_vrf.yml`. It will fail.\n\n```\nntc@ntc-training:lab06$ ansible-playbook pb_vrf.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match\n'all'\n\nPLAY [TESTING THE IOSXE_REST_VRF MODULE] *******************************************************************************\n\nTASK [UPDATE DESCRIPTION FOR CORP VRF] *******************************************************************************\nfatal: [localhost]: FAILED! => {\"changed\": false, \"json\": {\"errors\": {\"error\": [{\"error-message\": \"patch to a nonexistent resource\", \"error-path\": \"/Cisco-IOS-XE-native:native/vrf/definition=CORP\", \"error-tag\": \"invalid-value\", \"error-type\": \"application\"}]}}, \"msg\": \"API request failed with code 404\", \"sent_payload\": {\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}\n\nPLAY RECAP ***********************************************************************************************************\nlocalhost : ok=0 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\n```\n\nWhy did it fail? Well, the PATCH request needs to modify an existing VRF. Since the `CORP` VRF doesn't actually exist on the `csr1` device, the API call fails. Inspect the error message, do you see the \"patch to a nonexistent resource\" text in there?\n\nLook at the rest of the information provided, it is coming from your code! There's `sent_payload` in there showing you the request data, and there's `msg` showing the error code 404. The `json` field actually contains the full response given by the API.\n\n### Step 3\n\nIn a separate terminal on the lab workstation, open an SSH connection to the `csr1` device. Verify the configuration (there's no VRF CORP yet!) and manually add the `CORP` VRF into the configuration.\n\n```\nntc@ntc-training:lab06$ ssh csr1\nWarning: Permanently added 'csr1,172.18.0.6' (RSA) to the list of known hosts.\nPassword:\n\n\ncsr1#sh run vrf\nBuilding configuration...\n\nCurrent configuration : 127 bytes\nvrf definition MANAGEMENT\n !\n address-family ipv4\n exit-address-family\n !\n address-family ipv6\n exit-address-family\n!\n!\n!\nend\n\ncsr1#conf t\nEnter configuration commands, one per line. End with CNTL/Z.\ncsr1(config)#vrf definition CORP\ncsr1(config-vrf)#end\ncsr1#\n\ncsr1#sh run vrf CORP\nBuilding configuration...\n\nCurrent configuration : 27 bytes\nvrf definition CORP\n!\nend\ncsr1#\n```\n\n### Step 4\n\nRun the playbook `pb_vrf.yml` again. It will succeed since the CORP VRF now exists. It has also made a change to the VRF's description as per the module parameters!\n\n```\nntc@ntc-training:lab06$ ansible-playbook pb_vrf.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match\n'all'\n\nPLAY [TESTING THE IOSXE_REST_VRF MODULE] *****************************************************************************\n\nTASK [UPDATE DESCRIPTION FOR CORP VRF] *******************************************************************************\nchanged: [localhost]\n\nPLAY RECAP ***********************************************************************************************************\nlocalhost : ok=1 changed=1 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\n```\n\n### Step 5\n\nBack on the `csr1` CLI, check what's the running-config looking like now. As you can see, the description was successfully added.\n\n```\ncsr1#sh run vrf CORP\nBuilding configuration...\n\nCurrent configuration : 64 bytes\nvrf definition CORP\n description VRF FOR CORPORATE USERS\n!\nend\n\ncsr1#\n```\n\n### Step 6\n\nLet's make the playbook more dynamic and use an inventory with multiple devices.\n\nCreate an `inventory` file with the following content:\n\n```\n[iosxe]\ncsr[1:3]\n\n[iosxe:vars]\nansible_user=ntc\nansible_password=ntc123\n```\n\n### Step 7\n\nCreate a new playbook `pb_vrf_descriptions.yml` with the following content:\n\n```yml\n---\n\n- name: TESTING THE IOSXE_REST_VRF MODULE\n hosts: iosxe\n gather_facts: false\n\n tasks:\n - name: UPDATE DESCRIPTION FOR CORP VRF\n iosxe_rest_vrf:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ ansible_user }}\"\n password: \"{{ ansible_password }}\"\n name: CORP\n description: VRF FOR CORPORATE USERS\n delegate_to: localhost\n```\n\n> Important to note that `delegate_to: localhost` instructs Ansible to run the module locally as otherwise it would attempt to open an SSH connection an execute it remotely on the managed device (the default behavior).\n\n### Step 8\n\nRun the playbook `pb_vrf_descriptions.yml`. It's failing as expected on csr2 and csr3 since they are missing the `CORP` VRF. But you are now using your inventory data instead of hardcoding connection details inside of the playbook.\n\n```\nntc@ntc-training:lab06$ ansible-playbook -i inventory pb_vrf_descriptions.yml\n\nPLAY [TESTING THE IOSXE_REST_VRF MODULE] *****************************************************************************\n\nTASK [UPDATE DESCRIPTION FOR CORP VRF] *******************************************************************************\nfatal: [csr2 -> localhost]: FAILED! => {\"changed\": false, \"json\": {\"errors\": {\"error\": [{\"error-message\": \"patch to a nonexistent resource\", \"error-path\": \"/Cisco-IOS-XE-native:native/vrf/definition=CORP\", \"error-tag\": \"invalid-value\", \"error-type\": \"application\"}]}}, \"msg\": \"API request failed with code 404\", \"sent_payload\": {\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}\nchanged: [csr1 -> localhost]\nfatal: [csr3 -> localhost]: FAILED! => {\"changed\": false, \"json\": {\"errors\": {\"error\": [{\"error-message\": \"patch to a nonexistent resource\", \"error-path\": \"/Cisco-IOS-XE-native:native/vrf/definition=CORP\", \"error-tag\": \"invalid-value\", \"error-type\": \"application\"}]}}, \"msg\": \"API request failed with code 404\", \"sent_payload\": {\"Cisco-IOS-XE-native:definition\": {\"description\": \"VRF FOR CORPORATE USERS\", \"name\": \"CORP\"}}}\n\nPLAY RECAP ***********************************************************************************************************\ncsr1 : ok=1 changed=1 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\ncsr2 : ok=0 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\ncsr3 : ok=0 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\n```\n\n### Step 9\n\nFeel free to experiment at this stage with different descriptions and add the VRF to the other CSRs so the playbook succeeds!\n" }, { "alpha_fraction": 0.6061884760856628, "alphanum_fraction": 0.6061884760856628, "avg_line_length": 26.346153259277344, "blob_id": "dcbd6dd7a713c060a40c91e6c87753747e7130f0", "content_id": "082a06d37a2a8a77fb86d849e27fa5ee5a90987c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 711, "license_type": "no_license", "max_line_length": 61, "num_lines": 26, "path": "/workshops/extending-ansible/lab03/filter_plugins/build_table.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "from prettytable import PrettyTable\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"build_table\": FilterModule.build_table,\n }\n\n @staticmethod\n def build_table(table_data):\n \"\"\"Builds a text table from list data.\"\"\"\n table = PrettyTable()\n # Set the table column headers\n table.field_names = table_data.get(\"headers\")\n\n # Add in row data one by one\n for row in table_data.get(\"rows\"):\n table.add_row(row)\n\n # Return the pure text representation of the table\n return table.get_string()\n" }, { "alpha_fraction": 0.7209302186965942, "alphanum_fraction": 0.7674418687820435, "avg_line_length": 16.200000762939453, "blob_id": "84659edf38ff63652faf45c6cb25116e361245b9", "content_id": "c74b0ebfc2f7b8fcbdbf1cacb9a482d4c96f8965", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 86, "license_type": "no_license", "max_line_length": 53, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/pan2/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# pan2\n\nThis PaloAltoNetworks VM300 device is located in LAX.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6604402661323547, "alphanum_fraction": 0.6711140871047974, "avg_line_length": 24.423728942871094, "blob_id": "4b477e64e460929637ec9b5171e50de00f35faea", "content_id": "b5fa5233431b40c90a1db05dc5e4bc572652dad8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1499, "license_type": "no_license", "max_line_length": 74, "num_lines": 59, "path": "/challenges/10-batfish/files/bf_snapshot_importer.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python3\n\nfrom pybatfish.client.commands import bf_session, bf_set_network\nfrom pybatfish.question import bfq\nfrom pybatfish.question.question import load_questions\nfrom pybatfish.datamodel.flow import HeaderConstraints, PathConstraints\nimport click\nimport os\nimport code\nimport pandas as pd\n\nos.environ[\"PYTHONINSPECT\"] = \"TRUE\"\n\n\[email protected]()\[email protected](\n \"--snapshot_path\",\n \"-p\",\n type=click.Path(),\n required=True,\n help=\"Snapshot path.\",\n)\[email protected](\"--snapshot\", \"-s\", required=False, help=\"Snapshot name.\")\[email protected](\"--network\", \"-n\", required=False, help=\"Network name.\")\[email protected](\n \"--bf_host\",\n \"-a\",\n required=False,\n default=\"127.0.0.1\",\n show_default=True,\n help=\"Batfish host.\",\n)\ndef main(network, snapshot_path, snapshot, bf_host):\n \"\"\" Batfish Snapshot Importer \"\"\"\n bf_session.host = bf_host\n\n load_questions()\n\n if not snapshot:\n snapshot = os.path.basename(f\"{snapshot_path}_snapshot\")\n if not network:\n network = os.path.basename(f\"{snapshot_path}_network\")\n\n bf_set_network(network)\n bf_session.init_snapshot(snapshot_path, name=snapshot, overwrite=True)\n\n code.interact(local=dict(globals(), locals()))\n\n\ndef update_pd_display():\n pd.set_option(\"display.max_rows\", 500)\n pd.set_option(\"display.max_columns\", 15)\n pd.set_option(\"display.width\", 300)\n pd.set_option(\"display.max_colwidth\", 1)\n\n\nif __name__ == \"__main__\":\n #update_pd_display()\n main()" }, { "alpha_fraction": 0.6891891956329346, "alphanum_fraction": 0.6959459185600281, "avg_line_length": 15.44444465637207, "blob_id": "8d114f348a764a4562cab2b700b0624378bc93ee", "content_id": "68f9f04b9c313635f8b20588f0ad3bca305eb792", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Makefile", "length_bytes": 296, "license_type": "no_license", "max_line_length": 48, "num_lines": 18, "path": "/challenges/05-docker-tools/solution/files/Makefile", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "NAME = \"netdev/tools\"\nVERSION = \"0.1\"\n\n.PHONY: container run clean-images clean-stopped\ndefault: container\n\n\ncontainer:\n\tdocker build -t $(NAME):$(VERSION) .\n\nrun:\n\tdocker run -it $(NAME):$(VERSION)\n\nclean-images:\n\tdocker image rm -f $(NAME):$(VERSION)\n\nclean-stopped:\n\tdocker container prune -f\n" }, { "alpha_fraction": 0.6599776744842529, "alphanum_fraction": 0.6828935742378235, "avg_line_length": 25.55592155456543, "blob_id": "fb3e231f30c3ee5d85e0f923d221dd3930266b37", "content_id": "d269ea5df70ec8f10e3b9018b13de00680b7bc6a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 8073, "license_type": "no_license", "max_line_length": 138, "num_lines": 304, "path": "/workshops/jinja2-deep-dive-day1/lab_guides/lab03_whitespace_rendering.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 03 - Jinja whitespace rendering\n\nGoals of this lab:\n\n- Observe default whitespace rendering behavior.\n- Practice the use of manual stripping operators.\n- Understand the effect on the rendering of the `trim` option.\n- Understand the effect on the rendering of the `lstrip` option.\n\n## Task 01\n\n# Step 1\n\nIn this task, you will use [Online Jinja2 renderer](https://j2live.ttl255.com). Navigate to it now.\n\n# Step 2\n\nPaste the below data into the `Jinja2 Data` text area.\n\n```\n---\ninterfaces:\n - name: Loopback0\n type: layer3\n ip: 10.255.255.1/32\n - name: Ethernet1\n type: layer2_access\n access_vlan: 20\n - name: PortChannel40\n type: layer2_trunk\n native_vlan: 99\n allowed_vlans: \"20, 50, 60\"\n```\n\n![](images/j2live_data_area.png)\n\nPaste the below template into the `Jinja2 Template` text area.\n\n```\n{% for intf in interfaces %}\ninterface {{ intf['name'] }}\n {% if intf['type'] == 'layer3' %}\n ip address {{ intf['ip'] }}\n {% elif intf['type'] == 'layer2_access' %}\n switchport mode access\n switchport access vlan 20\n {% elif intf['type'] == 'layer2_trunk' %}\n switchport mode trunk\n switchport trunk encapsulation dot1q\n switchport trunk native vlan {{ intf['native_vlan'] }}\n switchport trunk allowed vlan {{ intf['allowed_vlans'] }}\n {% endif %}\n!\n{% endfor %}\n```\n\nRender the template. Notice many extra whitespaces added to the output.\n\nSwitch `Show whitespaces` toggle to on to make all of the whitespaces visible.\n\n![](images/j2_live_show_whitespace_on.png)\n\nYou should see not only extra new lines but also additional spaces inserted on some lines.\n\n![](images/lab03_task1_step2.png)\n\n# Step 3\n\nYou will now use indentation within expression blocks and manual whitespace control to improve this output.\n\nAfter you're finished Your output should match the below one, with `Show whitespaces` toggle enabled.\n\n![](images/lab03_task1_solution.png)\n\n<details>\n <summary>Reveal Answer</summary>\n\nMove indentation preceding `{% %}` expressions to the inside of the delimiter.\n\nAdd `-` manual stripping operators at the end of `{% for %}` delimiter and in front of `{% if %}`, `{% elif %}`, `{% endif %}` delimiters.\n\nOperator `-` placed at the end of the delimiter will strip all whitespaces following the delimiter.\n\nOperator `-` placed at the start of the delimiter will strip all whitespaces preceding the delimiter.\n\n```\n{% for intf in interfaces -%}\ninterface {{ intf['name'] }}\n{%- if intf['type'] == 'layer3' %}\n ip address {{ intf['ip'] }}\n{%- elif intf['type'] == 'layer2_access' %}\n switchport mode access\n switchport access vlan 20\n{%- elif intf['type'] == 'layer2_trunk' %}\n switchport mode trunk\n switchport trunk encapsulation dot1q\n switchport trunk native vlan {{ intf['native_vlan'] }}\n switchport trunk allowed vlan {{ intf['allowed_vlans'] }}\n{%- endif %}\n!\n{% endfor %}\n```\n\n</details>\n\n\n## Task 2\n\n### Step 1\n\nIn this task you will use [Online Jinja2 renderer](https://j2live.ttl255.com). Navigate to it now.\n\n### Step 2\n\nPaste the below data into the `Jinja2 Data` text area.\n\n```\n---\ninterfaces:\n - name: Loopback0\n type: layer3\n ip: 10.255.255.1/32\n - name: Ethernet1\n type: layer2_access\n access_vlan: 20\n - name: PortChannel40\n type: layer2_trunk\n native_vlan: 99\n allowed_vlans: \"all\"\n - name: PortChannel50\n type: layer2_trunk\n native_vlan: 85\n allowed_vlans: \"none\"\n - name: PortChannel60\n type: layer2_trunk\n native_vlan: 85\n allowed_vlans: \"85, 88, 90\"\n```\n\nPaste the below template into the `Jinja2 Template` text area.\n\n```\n{% for intf in interfaces %}\ninterface {{ intf['name'] }}\n {% if intf['type'] == 'layer3' %}\n ip address {{ intf['ip'] }}\n {% elif intf['type'] == 'layer2_access' %}\n switchport mode access\n switchport access vlan 20\n {% elif intf['type'] == 'layer2_trunk' %}\n switchport mode trunk\n {% if intf['native_vlan'] is defined %}\n switchport trunk native vlan {{ intf['native_vlan'] }}\n {% endif %}\n {% if intf['allowed_vlans'] == 'none' %}\n switchport trunk allowed vlan none\n {% elif intf['allowed_vlans'] == 'all' %}\n switchport trunk allowed vlan all\n {% else %}\n switchport trunk allowed vlan {{ intf['allowed_vlans'] }}\n {% endif %}\n {% endif %}\n!\n{% endfor %}\n```\n\nRender the template. Notice many extra whitespaces added to the output.\n\nClick on `Show whitespaces` toggle to make all of the whitespaces visible.\n\n# Step 3\n\nYou will now use indentation within expression blocks and manual whitespace control to improve this output.\n\nYour output should match the below one, with `Show whitespaces` toggle enabled.\n\n![](images/lab03_task2_solution.png)\n\n<details>\n <summary>Reveal Answer</summary>\n\nMove indentation preceding `{% %}` expressions to the inside of the delimiter.\n\nAdd `-` manual stripping operators at the end of `{% for %}` delimiter and in front of `{% if %}`, `{% elif %}`, `{% endif %}` delimiters.\n\nOperator `-` placed at the end of the delimiter will strip all whitespaces following the delimiter.\n\nOperator `-` placed at the start of the delimiter will strip all whitespaces preceding the delimiter.\n\n```\n{% for intf in interfaces -%}\ninterface {{ intf['name'] }}\n{%- if intf['type'] == 'layer3' %}\n ip address {{ intf['ip'] }}\n{%- elif intf['type'] == 'layer2_access' %}\n switchport mode access\n switchport access vlan 20\n{%- elif intf['type'] == 'layer2_trunk' %}\n switchport mode trunk\n{%- if intf['native_vlan'] is defined %}\n switchport trunk native vlan {{ intf['native_vlan'] }}\n{%- endif %}\n{%- if intf['allowed_vlans'] == 'none' %}\n switchport trunk allowed vlan none\n{%- elif intf['allowed_vlans'] == 'all' %}\n switchport trunk allowed vlan all\n{%- else %}\n switchport trunk allowed vlan {{ intf['allowed_vlans'] }}\n{%- endif %}\n{%- endif %}\n!\n{% endfor %}\n```\n\n</details>\n\n\n## Task 3\n\n### Step 1\n\nIn this task you will use [Online Jinja2 renderer](https://j2live.ttl255.com). Navigate to it now.\n\n### Step 2\n\nPaste the below data into the `Jinja2 Data` text area.\n\n```\n---\ninterfaces:\n - name: Loopback0\n type: layer3\n ip: 10.255.255.1/32\n - name: Ethernet1\n type: layer2_access\n access_vlan: 20\n - name: PortChannel40\n type: layer2_trunk\n native_vlan: 99\n allowed_vlans: \"all\"\n - name: PortChannel50\n type: layer2_trunk\n native_vlan: 85\n allowed_vlans: \"none\"\n - name: PortChannel60\n type: layer2_trunk\n native_vlan: 85\n allowed_vlans: \"85, 88, 90\"\n```\n\nPaste the below template into the `Jinja2 Template` text area.\n\n```\n{% for intf in interfaces %}\ninterface {{ intf['name'] }}\n {% if intf['type'] == 'layer3' %}\n ip address {{ intf['ip'] }}\n {% elif intf['type'] == 'layer2_access' %}\n switchport mode access\n switchport access vlan 20\n {% elif intf['type'] == 'layer2_trunk' %}\n switchport mode trunk\n {% if intf['native_vlan'] is defined %}\n switchport trunk native vlan {{ intf['native_vlan'] }}\n {% endif %}\n {% if intf['allowed_vlans'] == 'none' %}\n switchport trunk allowed vlan none\n {% elif intf['allowed_vlans'] == 'all' %}\n switchport trunk allowed vlan all\n {% else %}\n switchport trunk allowed vlan {{ intf['allowed_vlans'] }}\n {% endif %}\n {% endif %}\n!\n{% endfor %}\n```\n### Step 3\n\nRender the template and take a screenshot of the output with whitespaces visible.\n\n### Step 4\n\nNow enable the `Trim` option in the `Rendering options` section and render the template. \n\n![](images/j2live_trim_option.png)\n\nObserve what happened to the new lines and spaces. Use a screenshot from the previous task to compare the differences.\n### Step 5\n\nNext, enable the `Lstrip` option in the `Rendering options` section and render the template.\n\n![](images/j2live_trim_lstrip_options.png)\n\nDoes the output look better now? Make whitespaces visible and see what changed compared to the `Trim` only option.\n\nTake the screenshot of the output. We'll use it for comparison in the next step.\n\n### Step 6\n\nUncheck the `Lstrip` option but leave the `Trim` option checked.\n\nMove indentation from outside of Jinja `{% %}` delimiters to the inside of block tags.\n\nRender the template, make whitespaces visible and compare the output to the output from task 5. Can you see any differences?\n" }, { "alpha_fraction": 0.7112970948219299, "alphanum_fraction": 0.7224546670913696, "avg_line_length": 26.615385055541992, "blob_id": "f090573540af1e19d33f9245551a3804410b4584", "content_id": "02894323fbc0d3ea5fe331af183a8570b02be4c9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 717, "license_type": "no_license", "max_line_length": 156, "num_lines": 26, "path": "/workshops/telemetry-deepdive/prometheus_promql/006_aggregration_over_time.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Aggregation over Time\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with the aggregation over time based functions.\n\n\n## Exercises\n### Task 1\nCalculate the maximum number of `asa_anyconnect_client_active` over a 24 hour time period, for all sites.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nmax_over_time(asa_anyconnect_client_active{}[24h])\n```\n</details>\n\n### Task 2\nCalculate the average `dns_query_query_time_ms` over a 5 minute time range for the `site`=`lessines` and the `sensor_name`=`google-public-dns-a.google.com`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\navg_over_time(dns_query_query_time_ms{site=\"lessines\", sensor=\"google-public-dns-a.google.com\"}[5m])\n```\n</details>" }, { "alpha_fraction": 0.7296116352081299, "alphanum_fraction": 0.7424757480621338, "avg_line_length": 44.77777862548828, "blob_id": "ca2f5484b94ea02f94c8edccfb9a530eecca2541", "content_id": "0a744035ecb960aca0c3a399b05d3ab1b4003b02", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 4120, "license_type": "no_license", "max_line_length": 336, "num_lines": 90, "path": "/challenges/07-telemetry-visibility/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Using Telegraf for Telemetry and Visibility\n\nThe goal of this exercise is to interact with the different components of a TPG stack (Telegraf, Prometheus, Grafana), from a network monitoring perspective.\n\n## Exercise Overview\n\nThis exercise requires you to configure 2 Telegraf containers that are going to query external endpoints. The first instance will send HTTP probes request to get the status, HTTP status code and general response from the endpoint. The second instance will perform a DNS query to an external DNS server and get its general stats.\n\n- The HTTP telegraf container (`http-telegraf-01`) will use the [HTTP Response input plugin](https://docs.influxdata.com/telegraf/v1.15/plugins/#http_response) that will gather metrics from HTTP responses.\n- The DNS telegraf container (`dns-telegraf-01`) will use the [DNS Query input plugin](https://docs.influxdata.com/telegraf/v1.15/plugins/#dns_query) that will gather DNS query times.\n\n### Prerequisites\n\n- Have installed `docker` and `docker-compose`\n- Internet connectivity to reach the endpoints.\n- Navigate to `lab/` folder to setup and run the lab.\n\n### Setup\n\nTo perform the challenge tasks you build/start the containers.\n\n- To bring up the lab run the command\n\n```shell\ndocker-compose up -d\n```\n\n- To bring down the lab run the command\n\n```shell\ndocker-compose down\n```\n\nYou need to also configure the Grafana instance to see the data stored in Prometheus:\n\n- On your browser navigate to http://localhost:3000\n - Username: `admin`\n - Password: `admin`\n\n- You are good to go!\n\n### Task 1 - Probes Configuration\n\n#### HTTP Probe container\n\nCreate input telegraf configuration for `http-telegraf-01`:\n\n- As stated above you need to configure it with the `http_response` input plugin.\n- Requirements for the configuration:\n - URL is https://www.cloudflarestatus.com/ (Be sure to set it under the `urls` field)\n - Set the response timeout to 5 seconds.\n - Set the HTTP request method to GET.\n - Finally make the response match this substring to validate its returned data: `All Systems Operational`\n\n#### DNS Query container\n\nCreate input telegraf configuration for `dns-telegraf-01`:\n\n- As stated above you need to configure it with the `dns_query` input plugin.\n- Requirements for the configuration:\n - Set the DNS server to query: `1.1.1.1`\n - Set queries for the domains: `github.com, gitlab.com, networktocode.com`\n\nYou should save a snippet of the metrics gathered on the solution to be submitted.\n\n- HINT: The metrics being collected should be visible under http://localhost:9012/metrics and http://localhost:9013/metrics.\n- HINT: You can use Docker logs (i.e. docker logs -f `http-telegraf-01`) to verify the status of the telegraf instances and spot any errors on the configurations.\n\n### Task 2 - Data manipulation and Visualization\n\nGo to Grafana http://localhost:3000\n\n- Go to Explore and validate that you are receiving `http_response_response_time` and the `dns_query_query_time_ms` metrics. You should save some screenshot snippets to be sent on the final report.\n\n- Under a new Dashboard you will create the following panels:\n - A time series visualization of the `http_response_response_time` metric\n - Set the Axes Left Y to show the values as `seconds (s)`\n - Format the legend of the time series so it shows the `server` and the `status_code` of the query.\n - A time series of the `dns_query_query_time_ms`\n - Axes similar setup as the `http_response`\n - Filter based on `server` value: `1.1.1.1`\n - Legend formatted to show the `domain` queried and `result` in a table format.\n\n## Useful Links\n\n- [Telegraf input plugins](https://docs.influxdata.com/telegraf/v1.15/plugins/)\n - [HTTP Response input plugin](https://docs.influxdata.com/telegraf/v1.15/plugins/#http_response)\n - [DNS Query input plugin](https://docs.influxdata.com/telegraf/v1.15/plugins/#dns_query)\n- [Grafana Dashboards](https://grafana.com/docs/grafana/latest/dashboards/)\n- [Grafana Panels](https://grafana.com/docs/grafana/latest/panels/panels-overview/)\n" }, { "alpha_fraction": 0.625, "alphanum_fraction": 0.7386363744735718, "avg_line_length": 16.600000381469727, "blob_id": "1f37779d9b007975f904a04c1905f444e4c93ffa", "content_id": "f5cf6988076c7484903f79e75c27e80288952510", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 88, "license_type": "no_license", "max_line_length": 50, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/DC1-LEAF1/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# DC1-LEAF1\n\nThis Cisco 93180YC-FX-24 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7075605988502502, "alphanum_fraction": 0.7446504831314087, "avg_line_length": 40.235294342041016, "blob_id": "28da52af2896906c5bbfe198ff24ec5c562824e8", "content_id": "4bd3e7a2470d9c5f63ce09a619eab96a44c12844", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 701, "license_type": "no_license", "max_line_length": 127, "num_lines": 17, "path": "/workshops/jinja2-deep-dive-day1/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "## Jinja2 Deep-Dive Workshop\n\n### Day 1 - Jinja basics + Jinja in Python and Ansible\n\n- Lab 01 - [Jinja Basics](lab_guides/lab01_jinja_basics.md)\n- Lab 02 - [Loops, conditionals and tests](lab_guides/lab02_loops_conditionals.md)\n- Lab 03 - [Whitespace rendering](lab_guides/lab03_whitespace_rendering.md)\n- Lab 04 - [Jinja rendering with Python](lab_guides/lab04_jinja_in_python.md)\n- Lab 05 - [Jinja rendering with Ansible](lab_guides/lab05_ansible_template.md)\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2021, Network to Code, LLC.\n" }, { "alpha_fraction": 0.7289719581604004, "alphanum_fraction": 0.7476635575294495, "avg_line_length": 20.399999618530273, "blob_id": "15042a3aab4aacf401df55cb89e9b11828fd6b22", "content_id": "0f2c0b122c0ce71a7338f9730af6d0f30164c615", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 107, "license_type": "no_license", "max_line_length": 52, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/nyc-spine-01.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# nyc-spine-01.infra.ntc.com\n\nThis Arista vEOS device is located in New York City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.5875696539878845, "alphanum_fraction": 0.5929178595542908, "avg_line_length": 33.96653366088867, "blob_id": "9afe69e58631d8ccdc9bb799e5cf900903d42e65", "content_id": "07dce30863425ace4f7529a6e9d9c2791b9547c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 17775, "license_type": "no_license", "max_line_length": 391, "num_lines": 508, "path": "/workshops/extending-ansible/lab01_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Extending Ansible - Lab 01\n\nIn this lab exercise, you will create a custom Jinja2 filter for Ansible that expands short interface names - for example `gig` expands to `GigabitEthernet` and `tu` expands to `Tunnel`. This helps users still use shorthand interface names while expanding the name often required for managing configuration in an idempotent fashion using Ansible. \n\n## Task 1 - Expanding an Abbreviated Interface Name\n\nTo start with, you will create a new filter that expands a single name (i.e. a string) based on a set of predefined mappings.\n\n### Step 1\n\nIn your terminal on the lab workstation, change into the `/home/ntc/labs/lab01` folder, creating it if it doesn't exist.\n\n```\nntc@ntc-training:~$ mkdir -p /home/ntc/labs/lab01\nntc@ntc-training:~$ cd /home/ntc/labs/lab01\nntc@ntc-training:lab01$\n```\n\n### Step 2\n\nCreate a folder named `filter_plugins` and in it a file called `expand_interface_name.py`.\n\n```\nntc@ntc-training:lab01$ mkdir filter_plugins\nntc@ntc-training:lab01$ touch filter_plugins/expand_interface_name.py\nntc@ntc-training:lab01$ tree\n.\n└── filter_plugins\n └── expand_interface_name.py\n\n1 directory, 1 file\n```\n\n\n> Note: The folder `filter_plugins` is automatically searched for plugins if it is relative to where your playbooks are stored. The path for plugins can also be defined in your `ansible.cfg` file.\n\n### Step 3\n\nEdit the `expand_interface_name.py` file and add the following code to it.\n\n```py\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_interface_name\": FilterModule.expand_interface_name,\n }\n\n @staticmethod\n def expand_interface_name(interface_name):\n \"\"\"Expands abbreviated interface names.\"\"\"\n return \"NOT YET IMPLEMENTED\"\n```\n\nFirst, you're defining the class `FilterModule` which is required by Ansible - this is where it looks for the custom filters to load. Then, the function `filters` creates a mapping between the filter name `expand_interface_name` (as it will appear in Ansible playbooks or Jinja templates) and the actual function that contains the code, in this instance `FilterModule.expand_interface_name`.\n\n> Note: this is the scaffolding required for the filters you define in this specific file. It doesn't do anything useful yet.\n\n### Step 4\n\nDefine the following global variable containing a mapping of two leading characters to the full interface name. Add this at the beginning of your script, right before the `class FilterModule` definition.\n\n```py\nINTERFACE_MAPPING = {\n \"as\": \"Async\",\n \"br\": \"Bridge\",\n \"di\": \"Dialer\",\n \"et\": \"Ethernet\",\n \"fa\": \"FastEthernet\",\n \"fo\": \"FortyGigabitEthernet\",\n \"gi\": \"GigabitEthernet\",\n \"lo\": \"Loopback\",\n \"mg\": \"Mgmt\",\n \"po\": \"Port-Channel\",\n \"se\": \"Serial\",\n \"te\": \"TenGigabitEthernet\",\n \"tu\": \"Tunnel\",\n \"vl\": \"Vlan\",\n \"vx\": \"Vxlan\",\n}\n```\n\n> Note: using a dictionary allows you to easily extract the long name based on the key (leading two characters) in one operation.\n\n### Step 5\n\nReplace the `return` statement in the `expand_interface_name` function so it looks as follows:\n\n```py\n @staticmethod\n def expand_interface_name(interface_name):\n \"\"\"Expands abbreviated interface names.\"\"\"\n return INTERFACE_MAPPING.get(\n interface_name.strip().lower()[0:2], interface_name\n )\n```\n\nThe reference mapping is keyed on the leading two letters, so that's what you're extracting here with `interface_name.strip().lower()[0:2]`, also taking care to remove any whitespace and lowercase the input string.\n\nSince the `INTERFACE_MAPPING` dictionary is by no means all-encompassing, usage of the `get` method ensures that if there is no matching key, a default of the original `interface_name` will be returned unchanged.\n\n### Step 6\n\nCheckpoint! \n\nThe full `expand_interface_name.py` file should look like this:\n\n```py\nINTERFACE_MAPPING = {\n \"as\": \"Async\",\n \"br\": \"Bridge\",\n \"di\": \"Dialer\",\n \"et\": \"Ethernet\",\n \"fa\": \"FastEthernet\",\n \"fo\": \"FortyGigabitEthernet\",\n \"gi\": \"GigabitEthernet\",\n \"lo\": \"Loopback\",\n \"mg\": \"Mgmt\",\n \"po\": \"Port-Channel\",\n \"se\": \"Serial\",\n \"te\": \"TenGigabitEthernet\",\n \"tu\": \"Tunnel\",\n \"vl\": \"Vlan\",\n \"vx\": \"Vxlan\",\n}\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_interface_name\": FilterModule.expand_interface_name,\n }\n\n @staticmethod\n def expand_interface_name(interface_name):\n \"\"\"Expands abbreviated interface names.\"\"\"\n return INTERFACE_MAPPING.get(\n interface_name.strip().lower()[0:2], interface_name\n )\n\n```\n\n### Step 7\n\nThis is a Python script, so you may first test it directly by starting an interactive interpreter. Do that now and play around with the `expand_interface_name` function by throwing various values at it and checking what it returns.\n\nExecuting a script with the `-i` flag executes the script and then takes you into the interpreter.\n\n```\nntc@ntc-training:lab01$ python3 -i filter_plugins/expand_interface_name.py\n>>> FilterModule.expand_interface_name(\"vl\")\n'Vlan'\n>>> FilterModule.expand_interface_name(\"vlan\")\n'Vlan'\n>>> FilterModule.expand_interface_name(\"TUN\")\n'Tunnel'\n>>> FilterModule.expand_interface_name(\"tenGig\")\n'TenGigabitEthernet'\n>>> # \"vi\" is not mapped to anything\n>>> FilterModule.expand_interface_name(\"virtual\")\n'virtual'\n```\n\n### Step 8\n\nIn the `/home/ntc/labs/lab01` folder, create a playbook called `pb_filters.yml`. This will be used to test the filter from within an Ansible playbook.\n\n```yaml\n---\n\n- name: TEST INTERFACE EXPANSION FILTER\n hosts: localhost\n gather_facts: false\n tasks:\n - debug:\n msg: \"{{ 'gi' \| expand_interface_name }}\"\n\n - debug:\n msg: \"{{ 'loop' \| expand_interface_name }}\"\n\n - debug:\n msg: \"{{ 'TUN' \| expand_interface_name }}\"\n\n - debug:\n msg: \"{{ 'po100' \| expand_interface_name }}\"\n\n - debug:\n msg: \"{{ 'virt' \| expand_interface_name }}\"\n```\n\n> Reminder: Ansible will automatically load filters from the `filter_plugins` folder if it finds it relative to the playbook.\n\n### Step 9\n\nRun the Ansible playbook - note you do not need any inventory since you're just using `localhost` which is implicitly defined.\n\n```\nntc@ntc-training:lab01$ ansible-playbook pb_filters.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\n\nPLAY [TEST INTERFACE EXPANSION FILTER] *************************************************************************************************\n\nTASK [debug] ***********************************************************************************************\nok: [localhost] => {\n \"msg\": \"GigabitEthernet\"\n}\n\nTASK [debug] ***********************************************************************************************\nok: [localhost] => {\n \"msg\": \"Loopback\"\n}\n\nTASK [debug] ***********************************************************************************************\nok: [localhost] => {\n \"msg\": \"Tunnel\"\n}\n\nTASK [debug] ***********************************************************************************************\nok: [localhost] => {\n \"msg\": \"Port-Channel\"\n}\n\nTASK [debug] ***********************************************************************************************\nok: [localhost] => {\n \"msg\": \"virt\"\n}\n\nPLAY RECAP ***********************************************************************************************\nlocalhost : ok=5 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\n```\n\n## Task 2 - Expanding a List of Names\n\nWhat if you had a list of interface names to expand instead of a single one? It's a lot easier (and faster!) to loop in Python than in Ansible, so let's extend the filter to accept a list as well and add some type validation.\n\n### Step 1\n\nIn the same `expand_interface_name.py` file, define a new function called `expand_interface_names` - take note of the subtle difference (plural \"names\"). Normally, you would remove the old function (or extend it in place), but for the purposes of this lab we will leave them be side by side.\n\nThis function should be placed inside of the same `class FilterModule` block.\n\n```py\n @staticmethod\n def expand_interface_names(interface_names):\n \"\"\"Expands abbreviated interface names.\"\"\"\n if isinstance(interface_names, str):\n # Same as previously, it's just one interface name\n return INTERFACE_MAPPING.get(\n interface_names.strip().lower()[0:2], interface_names\n )\n```\n\nFirst, check the type of the provided `interface_names` parameter. If it is a string, then provide the same functionality as in the original filter. In this case it's a nice touch that provides backwards compatibility.\n\n### Step 2\n\nAdd another check and the code to deal with the case when a list is passed to the function.\n\n```py\n @staticmethod\n def expand_interface_names(interface_names):\n \"\"\"Expands abbreviated interface names.\"\"\"\n if isinstance(interface_names, str):\n # Same as previously, it's just one interface name\n return INTERFACE_MAPPING.get(\n interface_names.strip().lower()[0:2], interface_names\n )\n elif isinstance(interface_names, list):\n expanded_names = []\n for name in interface_names:\n long_name = INTERFACE_MAPPING.get(name.strip().lower()[0:2], name)\n expanded_names.append(long_name)\n return expanded_names\n```\n\nIf a list is passed, then you need to perform the same `INTERFACE_MAPPING` lookup operation for each of its components and return a list back with the expanded values.\n\n### Step 3\n\nThis steps adds error handling using class objects that Ansible provides to provide more graceful failing and helpful messages to the users when an error occurs.\n\nAt the top of the script, add the following import statement:\n\n```py\nfrom ansible import errors\n```\n\n### Step 4\n\nIf the function receives a parameter that is not a `string` or a `list`, then it will raise an error (in this case an exception specific to Ansible) with a custom message. Modify the `expand_interface_names` function as shown below.\n\n```py\n @staticmethod\n def expand_interface_names(interface_names):\n \"\"\"Expands abbreviated interface names.\"\"\"\n if isinstance(interface_names, str):\n # Same as previously, it's just one interface name\n return INTERFACE_MAPPING.get(\n interface_names.strip().lower()[0:2], interface_names\n )\n elif isinstance(interface_names, list):\n expanded_names = []\n for name in interface_names:\n long_name = INTERFACE_MAPPING.get(name.strip().lower()[0:2], name)\n expanded_names.append(long_name)\n return expanded_names\n else:\n raise errors.AnsibleFilterError(\n \"expand_interface_names filter error: provide a string or a list of strings!\"\n )\n```\n\n### Step 5\n\nFinally, register the new function as a filter so Ansible can find it. Add a new entry in the `def filters()` function of the `FilterModule` class.\n\n```py\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_interface_name\": FilterModule.expand_interface_name,\n \"expand_interface_names\": FilterModule.expand_interface_names,\n }\n```\n\n> Note: If you try to use it before this step, Ansible will give you an error like the following.\n\n```\nfatal: [localhost]: FAILED! => {\"msg\": \"template error while templating string: no filter named 'expand_interface_names'. String: {{ 'gi' \| expand_interface_names }}\"}\n```\n\n### Step 6\n\nCheckpoint!\n\nThe full `expand_interface_name.py` file should now look like this:\n\n```py\nfrom ansible import errors\n\nINTERFACE_MAPPING = {\n \"as\": \"Async\",\n \"br\": \"Bridge\",\n \"di\": \"Dialer\",\n \"et\": \"Ethernet\",\n \"fa\": \"FastEthernet\",\n \"fo\": \"FortyGigabitEthernet\",\n \"gi\": \"GigabitEthernet\",\n \"lo\": \"Loopback\",\n \"mg\": \"Mgmt\",\n \"po\": \"Port-Channel\",\n \"se\": \"Serial\",\n \"te\": \"TenGigabitEthernet\",\n \"tu\": \"Tunnel\",\n \"vl\": \"Vlan\",\n \"vx\": \"Vxlan\",\n}\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_interface_name\": FilterModule.expand_interface_name,\n \"expand_interface_names\": FilterModule.expand_interface_names,\n }\n\n @staticmethod\n def expand_interface_name(interface_name):\n \"\"\"Expands abbreviated interface names.\"\"\"\n return INTERFACE_MAPPING.get(\n interface_name.strip().lower()[0:2], interface_name\n )\n\n @staticmethod\n def expand_interface_names(interface_names):\n \"\"\"Expands abbreviated interface names.\"\"\"\n if isinstance(interface_names, str):\n # Same as previously, it's just one interface name\n return INTERFACE_MAPPING.get(\n interface_names.strip().lower()[0:2], interface_names\n )\n elif isinstance(interface_names, list):\n expanded_names = []\n for name in interface_names:\n long_name = INTERFACE_MAPPING.get(name.strip().lower()[0:2], name)\n expanded_names.append(long_name)\n return expanded_names\n else:\n raise errors.AnsibleFilterError(\n \"expand_interface_names filter error: provide a string or a list of strings!\"\n )\n```\n\n\n### Step 7\n\nIn the `pb_filters.yml` playbook, create a new play to test this filter. First, check that for single strings, its behavior is unchanged. Then, pass lists of names and finally an invalid value to test all code paths.\n\n```yaml\n- name: TEST MULTIPLE INTERFACE EXPANSION FILTER\n hosts: localhost\n gather_facts: false\n tasks:\n - debug:\n msg: \"{{ 'gi' \| expand_interface_names }}\"\n\n - debug:\n msg: \"{{ ['gig', 'port', 'mg' ] \| expand_interface_names }}\"\n\n - debug:\n msg: \"{{ ['loop', 'virt', 'PRI0' ] \| expand_interface_names }}\"\n\n - debug:\n msg: \"{{ 100 \| expand_interface_names }}\"\n```\n\n### Step 8\n\nRun the Ansible playbook. The last task will intentionally fail, the playbook is passing a number to the filter to check that the error message is sent accordingly.\n\n```\nntc@ntc-training:lab01$ ansible-playbook pb_filters.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not\nmatch 'all'\n\nPLAY [TEST INTERFACE EXPANSION FILTER] ***********************************************************************\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": \"GigabitEthernet\"\n}\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": \"Loopback\"\n}\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": \"Tunnel\"\n}\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": \"Port-Channel\"\n}\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": \"virt\"\n}\n\nPLAY [TEST MULTIPLE INTERFACE EXPANSION FILTER] **************************************************************\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": \"GigabitEthernet\"\n}\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": [\n \"GigabitEthernet\",\n \"Port-Channel\",\n \"Mgmt\"\n ]\n}\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": [\n \"Loopback\",\n \"virt\",\n \"PRI0\"\n ]\n}\n\nTASK [debug] *************************************************************************************************\nfatal: [localhost]: FAILED! => {\"msg\": \"expand_interface_names filter error: provide a string or a list of strings!\"}\n\nPLAY RECAP ***************************************************************************************************\nlocalhost : ok=8 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\n```\n\n\n## Task 3 - Homework Challenge (Optional)\n\nTry to do this task in your own time after the workshop and test it with as many possible combinations as you can!\n\nYou may have noticed that if you provide a string with a number in it (e.g. \"gi100\") then it is lost after expansion (e.g. \"GigabitEthernet\" is the result).\n\nImprove the filter to preserve any interface numbering during this process. \n\nHint*: you should find a way to split the name (likely letters and symbols) from the numbering part (digits and symbols like - or /) before expanding only the first part.\n" }, { "alpha_fraction": 0.572441577911377, "alphanum_fraction": 0.6380338668823242, "avg_line_length": 58.66345977783203, "blob_id": "8e98814ec51a7afcdda0e02981ed6204bbaa921e", "content_id": "57184525790d245fbd3c4156ea7fa333161ccf06", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 6205, "license_type": "no_license", "max_line_length": 173, "num_lines": 104, "path": "/challenges/10-batfish/solution/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "### Batfish Solution\n\n# Challenge Exercise Solution Guide\n\n## Introduction to Batfish\n\nThe goal of this exercise is to learn about the common operations in Batfish. You will learn how to interact with Batfish and work with its output.\n \nFor certain parts of this challenge you will need to refer to https://pybatfish.readthedocs.io/en/latest/questions.html to understand the question that we will need to ask. \n\n## Solution Walkthrough\n\n#### Task 1 - Snapshot Import\n \nIn this question you were asked:\n> From the helper file `bf_snapshot_importer.py` can you determine the line where the snapshot is initialized using the supplied snapshot path?\n \nFrom looking into this file you will see that the following line is used to initialize the snapshot.\n```python\ndef main(network, snapshot_path, snapshot, bf_host):\n ...\n\n bf_set_network(network)\n=> bf_session.init_snapshot(snapshot_path, name=snapshot, overwrite=True)\n```\n#### Task 2 - Snapshot Validation\n\nIn this question you were asked: \n> Use Batfish to:\n> obtain a parsing summary of the snapshot files.\n> * confirm the problematic configuration lines for each of the configurations. \n\nTo see the parsing summary, we use the following command:\n```\nbfq.fileParseStatus().answer().frame()\n File_Name Status Nodes\n0 configs/leaf1.cfg PARTIALLY_UNRECOGNIZED ['leaf1']\n1 configs/leaf2.cfg PARTIALLY_UNRECOGNIZED ['leaf2']\n2 configs/spine1.cfg PARTIALLY_UNRECOGNIZED ['spine1']\n3 configs/spine2.cfg PARTIALLY_UNRECOGNIZED ['spine2']\n4 hosts/server1.json PASSED ['server1']\n5 hosts/server2.json PASSED ['server2']\n6 iptables/server1.iptables PASSED ['iptables/server1.iptables']\n7 iptables/server2.iptables PASSED ['iptables/server2.iptables']\n```\n\nTo see the individual configuration elements that Batfish is unable to parse we use:\n```\nbfq.parseWarning().answer().frame()\n Filename Line Text Parser_Context Comment\n0 configs/leaf1.cfg 20 no password strength-check [s_no statement cisco_nxos_configuration] This syntax is unrecognized\n1 configs/leaf1.cfg 30 rmon event 1 log trap public description FATAL... [cisco_nxos_configuration] This syntax is unrecognized\n2 configs/leaf1.cfg 31 rmon event 2 log trap public description CRITI... [cisco_nxos_configuration] This syntax is unrecognized\n3 configs/leaf1.cfg 32 rmon event 3 log trap public description ERROR... [cisco_nxos_configuration] This syntax is unrecognized\n4 configs/leaf1.cfg 33 rmon event 4 log trap public description WARNI... [cisco_nxos_configuration] This syntax is unrecognized\n5 configs/leaf1.cfg 34 rmon event 5 log trap public description INFOR... [cisco_nxos_configuration] This syntax is unrecognized\n...\n```\n\n#### Task 3 - MTU Validation\n\nIn this question you were asked:\n> Use Batfish to confirm the MTU for each of the interfaces within our snapshot.\n \nTo validate the MTUs we can use the `interfaceProperites` question as shown below. As you will see all the interfaces are set to `1500` bytes.\n```\nbfq.interfaceProperties(properties=\"MTU\").answer().frame()\n Interface MTU\n0 spine1[Ethernet1/21] 1500\n1 spine2[Ethernet1/24] 1500\n2 spine1[Ethernet1/23] 1500\n3 server1[eth1] 1500\n4 spine1[Ethernet1/22] 1500\n...\n```\n\n#### Task 4 - OSPF Validation\n\nIn this question you were asked: \n> Use Batfish to validate all OSPF adjacencies are correctly established. If they are not, please confirm reason.\n\nTo validate the OSPF sessions we use `ospfSessionCompatibility()`. This will also tell us the reason for the session failure.\nWe will see there is an OSPF area mismatch between the 2 neighbors.\n\nNote: All the possible status values can be found at https://pybatfish.readthedocs.io/en/latest/specifiers.html#ospf-session-status-specifier.\n\n```\nbfq.ospfSessionCompatibility().answer().frame()\n Interface VRF IP Area Remote_Interface Remote_VRF Remote_IP Remote_Area Session_Status\n0 leaf2[Ethernet1/3] default 10.1.128.2 0 spine1[Ethernet1/3] default 10.1.128.1 0 ESTABLISHED\n1 spine1[Ethernet1/3] default 10.1.128.1 0 leaf2[Ethernet1/3] default 10.1.128.2 0 ESTABLISHED\n2 spine2[Ethernet1/1] default 10.2.128.1 0 leaf2[Ethernet1/1] default 10.2.128.2 0 ESTABLISHED\n3 spine2[Ethernet1/3] default 10.2.0.1 0 leaf1[Ethernet1/3] default 10.2.0.2 0 ESTABLISHED\n4 spine2[Ethernet1/4] default 10.2.0.5 0 leaf1[Ethernet1/4] default 10.2.0.6 0 ESTABLISHED\n5 leaf2[Ethernet1/4] default 10.1.0.2 0 spine1[Ethernet1/4] default 10.1.0.1 0 ESTABLISHED\n6 spine1[Ethernet1/2] default 10.0.128.1 0 leaf1[Ethernet1/2] default 10.0.128.2 2 AREA_MISMATCH\n7 leaf1[Ethernet1/3] default 10.2.0.2 0 spine2[Ethernet1/3] default 10.2.0.1 0 ESTABLISHED\n8 leaf1[Ethernet1/4] default 10.2.0.6 0 spine2[Ethernet1/4] default 10.2.0.5 0 ESTABLISHED\n9 spine2[Ethernet1/2] default 10.2.128.5 0 leaf2[Ethernet1/2] default 10.2.128.6 0 ESTABLISHED\n10 leaf2[Ethernet1/1] default 10.2.128.2 0 spine2[Ethernet1/1] default 10.2.128.1 0 ESTABLISHED\n11 spine1[Ethernet1/4] default 10.1.0.1 0 leaf2[Ethernet1/4] default 10.1.0.2 0 ESTABLISHED\n12 leaf1[Ethernet1/2] default 10.0.128.2 2 spine1[Ethernet1/2] default 10.0.128.1 0 AREA_MISMATCH\n13 leaf2[Ethernet1/2] default 10.2.128.6 0 spine2[Ethernet1/2] default 10.2.128.5 0 ESTABLISHED\n```\n" }, { "alpha_fraction": 0.7287104725837708, "alphanum_fraction": 0.7530413866043091, "avg_line_length": 30.576923370361328, "blob_id": "33f6b6906ff99f3756de7fb0d60c5506bb17f872", "content_id": "b3a631588402ffebde4f35176324505a7773b968", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 822, "license_type": "no_license", "max_line_length": 155, "num_lines": 26, "path": "/workshops/telemetry-deepdive/prometheus_promql/003_instant_range_vectors.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Instant vs Range Vectors\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with querying and returning instant vectors.\n* Familiarize yourself with querying and returning range vectors.\n\n## Exercises\n### Task 1\nPerform a query to return an instant vector for the metric `interface_in_octets` for `hostname=rAWPLblo02` and `interface=\"GigabitEthernet0/2\"`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\ninterface_in_octets{hostname=\"rAWPLblo02\",interface=\"GigabitEthernet0/2\"}\n```\n</details>\n\n### Task 2\nPerform a query to return the range vector for the metric `interface_in_octets` for `hostname=rAWPLblo02` and `interface=\"GigabitEthernet0/2\"` over 5 mins.\n<details>\n <summary>Reveal Answer</summary>\n \n```\ninterface_in_octets{hostname=\"rAWPLblo02\",interface=\"GigabitEthernet0/2\"}[5m]\n```\n</details>\n\n" }, { "alpha_fraction": 0.5493346452713013, "alphanum_fraction": 0.5659050941467285, "avg_line_length": 34.169979095458984, "blob_id": "f73c1d3e270f596d3ae44070a47da20600e85386", "content_id": "9f0b7b612ba402d3ec76418f5fbf77aac9b52b56", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 15944, "license_type": "no_license", "max_line_length": 329, "num_lines": 453, "path": "/workshops/extending-ansible/lab04_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Extending Ansible - Lab 04\n\nWhenever you're working with data in Ansible either comparing data, transforming data, or analzying it, you'll find that performing those operations within Python (in a filter) can save quite a bit of time in the long run for other engineers focused on writing playbooks.\n\nIn this lab exercise, you will create a custom filter for Ansible that compares intended interface state to the operational state pulled from an NXOS switch. \n\n## Task 1 - Reviewing the Filter Code\n\nTo start with, you will create a new filter a review the provided code and data structures.\n\n### Step 1\n\nIn your terminal on the lab workstation, change into the `/home/ntc/labs/lab04` folder, creating it if it doesn't exist.\n\n```\nntc@ntc-training:~$ mkdir -p /home/ntc/labs/lab04\nntc@ntc-training:~$ cd /home/ntc/labs/lab04\nntc@ntc-training:lab04$\n```\n\n### Step 2\n\nCreate a folder named `filter_plugins` and in it a file called `verify_intended_state.py`.\n\n```\nntc@ntc-training:lab04$ mkdir filter_plugins\nntc@ntc-training:lab04$ touch filter_plugins/verify_intended_state.py\nntc@ntc-training:lab04$ tree\n.\n└── filter_plugins\n └── verify_intended_state.py\n\n1 directory, 1 file\n```\n\n### Step 3\n\nEdit the `verify_intended_state.py` file and paste in the following content. This is the full script and you will explore it in the following steps (keep the full script and this guide side-by-side if possible).\n\n```py\nfrom ansible import errors\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"verify_intended_state\": FilterModule.verify_intended_state,\n }\n\n @staticmethod\n def verify_intended_state(operational, intended):\n \"\"\"Returns a pass/fail comparison of intended and operational state.\n\n Compares NXOS (operational) state (from the show int brief command)\n to a provided list of interface and state mappings (intended)\n\n SAMPLE intended\n [\n {\n \"name\": \"Ethernet1/1\",\n \"state\": \"up\"\n },\n {\n \"name\": \"mgmt0\",\n \"state\": \"up\"\n },\n ]\n\n SAMPLE operational\n {\n \"TABLE_interface\": {\n \"ROW_interface\": [\n {\n \"interface\": \"mgmt0\",\n \"state\": \"up\",\n \"ip_addr\": \"10.0.0.15\",\n \"speed\": \"1000\",\n \"mtu\": \"1500\"\n },\n {\n \"interface\": \"Ethernet1/1\",\n \"vlan\": \"1\",\n \"type\": \"eth\",\n \"portmode\": \"access\",\n \"state\": \"up\",\n \"state_rsn_desc\": \"none\",\n \"speed\": \"1000\",\n \"ratemode\": \"D\"\n },\n ]\n }\n }\n\n\n Args:\n operational (dict): the output of `show int brief \| json`\n intended (list): a list of interfaces and their states\n\n Returns:\n dict: A dictionary containing the lists of interfaces that\n passed and failed verification\n \"\"\"\n # First prepare the data coming from NXOS for ease of lookup\n # Change from a list of interface dictionaries to a dictionary\n # keyed on the interface name\n oper_keyed = {}\n for oper_intf in operational[\"TABLE_interface\"][\"ROW_interface\"]:\n oper_keyed[oper_intf[\"interface\"]] = oper_intf\n\n pass_list = []\n fail_list = []\n # This is a list of name/state pairs describing the intended state\n # of a bunch of interfaces (not necessarily the same set).\n for interface in intended:\n # Look for the interface name in the operational dictionary\n # as an exact match only - with UNKNOWN as a safe default\n oper_intf = oper_keyed.get(interface[\"name\"])\n if oper_intf:\n oper_state = oper_intf.get(\"state\", \"UNKNOWN\")\n else:\n oper_state = \"UNKNOWN\"\n\n # Compare operational to intended\n if oper_state != interface[\"state\"]:\n fail_list.append(interface[\"name\"])\n else:\n pass_list.append(interface[\"name\"])\n\n # Return a dictionary with two keys containing the lists for easy\n # subsequent parsing\n return {\"pass\": pass_list, \"fail\": fail_list}\n```\n\n### Step 4\n\nObserve the script's general structure - the `class FilterModule` containing the necessary binding for Ansible and the actual `verify_intended_state` function that performs the work.\n\nIn this script, you may notice that the docstring (the text between the triple quotes `\"\"\"` at the beginning of the function block) for the `verify_intended_state` function is a lot more descriptive than before (and has examples!). This is highly recommended when your functions perform work on complex data structures.\n\nTake some time to read through the docstring.\n\n### Step 5\n\nAs you can see, the `operational` and `intended` data structures are fairly different - this is quite common, especially as your data model will many times try to be vendor or OS independent. This means that you need to perfom various transformation operations in order to correlate information from both of these structures.\n\nThe first step is to make the `operational` data easier to search through. You may have noticed that it contains a list of interfaces, which means that if you ever needed to look up an interface in this list, you had to search through the whole list every time (this may become computationally expensive with large datasets).\n\nIn order to make this lookup process more optimal, the first step is to convert this list of interfaces into a dictionary, which is the perfect construct for direct single item access (there is a trade-off as always, in this case memory usage will be higher, but computational complexity lower).\n\n```py\n # First prepare the data coming from NXOS for ease of lookup\n # Change from a list of interface dictionaries to a dictionary\n # keyed on the interface name\n oper_keyed = {}\n for oper_intf in operational[\"TABLE_interface\"][\"ROW_interface\"]:\n oper_keyed[oper_intf[\"interface\"]] = oper_intf\n```\n\n### Step 6\n\nTo see what is the exact end-result of the code, you may quickly load it into a Python interpreter and explore the results of applying it to the example from the docstring.\n\n```\nntc@ntc-training:lab04$ python3\nPython 3.6.8 (default, Jun 11 2019, 01:16:11)\n[GCC 6.3.0 20170516] on linux\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>>\n>>>\n>>> operational = {\n... \"TABLE_interface\": {\n... \"ROW_interface\": [\n... {\n... \"interface\": \"mgmt0\",\n... \"state\": \"up\",\n... \"ip_addr\": \"10.0.0.15\",\n... \"speed\": \"1000\",\n... \"mtu\": \"1500\"\n... },\n... {\n... \"interface\": \"Ethernet1/1\",\n... \"vlan\": \"1\",\n... \"type\": \"eth\",\n... \"portmode\": \"access\",\n... \"state\": \"up\",\n... \"state_rsn_desc\": \"none\",\n... \"speed\": \"1000\",\n... \"ratemode\": \"D\"\n... },\n... ]\n... }\n... }\n>>> oper_keyed = {}\n>>> for oper_intf in operational[\"TABLE_interface\"][\"ROW_interface\"]:\n... oper_keyed[oper_intf[\"interface\"]] = oper_intf\n...\n>>> import json\n>>> print(json.dumps(oper_keyed, indent=4))\n{\n \"mgmt0\": {\n \"interface\": \"mgmt0\",\n \"state\": \"up\",\n \"ip_addr\": \"10.0.0.15\",\n \"speed\": \"1000\",\n \"mtu\": \"1500\"\n },\n \"Ethernet1/1\": {\n \"interface\": \"Ethernet1/1\",\n \"vlan\": \"1\",\n \"type\": \"eth\",\n \"portmode\": \"access\",\n \"state\": \"up\",\n \"state_rsn_desc\": \"none\",\n \"speed\": \"1000\",\n \"ratemode\": \"D\"\n }\n}\n>>> oper_keyed[\"mgmt0\"]\n{'interface': 'mgmt0', 'state': 'up', 'ip_addr': '10.0.0.15', 'speed': '1000', 'mtu': '1500'}\n```\n\nObserve how you can now extract a single specific interface with just one operation `oper_keyed[\"mgmt0\"]`.\n\n### Step 7\n\nThat was the hardest part. What comes after it is building two lists: `pass_list` to contain interface names that match the intended with the operational state - and `fail_list` for those that don't match. The state is simply either `up` or `down`.\n\nSince the `intended` structure is a list of interfaces, the code will loop through them one by one and try to find if they exist within the `oper_keyed` data. As per the above steps, this is now easily achieved with one dictionary lookup.\n\n```py\n for interface in intended:\n # Look for the interface name in the operational dictionary\n # as an exact match only - with UNKNOWN as a safe default\n oper_intf = oper_keyed.get(interface[\"name\"])\n if oper_intf:\n oper_state = oper_intf.get(\"state\", \"UNKNOWN\")\n else:\n oper_state = \"UNKNOWN\"\n```\n\nIf the interface is found in the operational data, then extract its operational state from the underlying dictionary. Notice the usage of the dictionary `get()` method here to make these uncertain (data may not always exist!) lookups reliable.\n\n### Step 8\n\nThe intended and operational states are compared, and based on the result, the interface name is added to the appropriate list.\n\n```py\n # Compare operational to intended\n if oper_state != interface[\"state\"]:\n fail_list.append(interface[\"name\"])\n else:\n pass_list.append(interface[\"name\"])\n```\n\n### Step 9\n\nFinally, the function returns a dictionary containing the two pass and fail lists for easy lookup in the Ansible playbook or Jinja templates.\n\n```py\n return {\"pass\": pass_list, \"fail\": fail_list}\n```\n\n\n## Task 2 - Using the Filter in an Ansible Playbook\n\nYou will write an Ansible playbook that compares static intent (stored in the playbook) to actual operational data from NXOS devices in the lab pod.\n\n### Step 1\n\nIn the `/home/ntc/labs/lab04` folder, create the `inventory` file and add the following lines to it.\n\n```\n[nxos]\nnxos-spine1\nnxos-spine2\n\n[nxos:vars]\nansible_user=ntc\nansible_password=ntc123\nansible_connection=network_cli\nansible_network_os=nxos\n```\n\n### Step 2\n\nIn the `/home/ntc/labs/lab04` folder, create the `pb_verify.yml` file and add the following lines to it.\n\n```\n---\n\n- name: NXOS INTERFACES STATE VERIFICATION\n hosts: nxos\n gather_facts: false\n\n vars:\n interface_intent:\n - name: Ethernet1/1\n state: up\n - name: Ethernet1/2\n state: up\n - name: Ethernet1/10\n state: up\n - name: Ethernet1/11\n state: down\n\n tasks:\n - name: GET INTERFACE STATE FROM SWITCH\n nxos_command:\n commands: show int brief \| json\n register: show_int_brief\n\n - name: COMPARE INTENT TO OPERATIONAL STATE\n set_fact:\n interface_pass_fail: \"{{ show_int_brief.stdout.0 \| verify_intended_state(interface_intent) }}\"\n\n - name: SHOW COMPARISON RESULTS\n debug:\n var: interface_pass_fail\n```\n\nFirst, the playbook connects to the NXOS device and retrieves the output of the `show int brief \| json` command. Then, it provides the data structure together with the `interface_intent` to the `verify_intended_state` filter to do its comparison. Finally, it displays the pass/fail dictionary returned by the filter.\n\n\n### Step 3\n\nRun the `pb_verify.yml` playbook and observe the results.\n\n```\nntc@ntc-training:lab04$ ansible-playbook -i inventory pb_verify.yml\n\nPLAY [NXOS INTERFACES STATE VERIFICATION] **********************************************************************\n\nTASK [GET INTERFACE STATE FROM SWITCH] ***********************************************************************\nok: [nxos-spine2]\nok: [nxos-spine1]\n\nTASK [COMPARE INTENT TO OPERATIONAL STATE] *******************************************************************\nok: [nxos-spine1]\nok: [nxos-spine2]\n\nTASK [SHOW COMPARISON RESULTS] *******************************************************************************\nok: [nxos-spine1] => {\n \"interface_pass_fail\": {\n \"fail\": [\n \"Ethernet1/10\"\n ],\n \"pass\": [\n \"Ethernet1/1\",\n \"Ethernet1/2\",\n \"Ethernet1/11\"\n ]\n }\n}\nok: [nxos-spine2] => {\n \"interface_pass_fail\": {\n \"fail\": [\n \"Ethernet1/10\"\n ],\n \"pass\": [\n \"Ethernet1/1\",\n \"Ethernet1/2\",\n \"Ethernet1/11\"\n ]\n }\n}\n\nPLAY RECAP ***************************************************************************************************\nnxos-spine1 : ok=3 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\nnxos-spine2 : ok=3 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\n```\n\n> Note: If you wish to view data in flight, feel free to increase Ansible's verbosity by adding one or more `-v` to the command line.\n\n### Step 4\n\nThis information can be used in a report or, as exemplified here, in an in-playbook assertion. Add the following task at the end of the `pb_verify.yml` playbook.\n\n```yaml\n - name: ASSERT THAT NO INTERFACES HAVE FAILED THE CHECKS\n assert:\n that:\n - interface_pass_fail.fail \| length == 0\n```\n\n### Step 5\n\nRun the playbook again.\n\n```\nntc@ntc-training:lab04$ ansible-playbook -i inventory pb_verify.yml\n\nPLAY [NXOS INTERFACES STATE VERIFICATION] ********************************************************************\n\nTASK [GET INTERFACE STATE FROM SWITCH] ***********************************************************************\nok: [nxos-spine2]\nok: [nxos-spine1]\n\nTASK [COMPARE INTENT TO OPERATIONAL STATE] *******************************************************************\nok: [nxos-spine1]\nok: [nxos-spine2]\n\nTASK [SHOW COMPARISON RESULTS] *******************************************************************************\nok: [nxos-spine2] => {\n \"interface_pass_fail\": {\n \"fail\": [\n \"Ethernet1/10\"\n ],\n \"pass\": [\n \"Ethernet1/1\",\n \"Ethernet1/2\",\n \"Ethernet1/11\"\n ]\n }\n}\nok: [nxos-spine1] => {\n \"interface_pass_fail\": {\n \"fail\": [\n \"Ethernet1/10\"\n ],\n \"pass\": [\n \"Ethernet1/1\",\n \"Ethernet1/2\",\n \"Ethernet1/11\"\n ]\n }\n}\n\nTASK [ASSERT THAT NO INTERFACES HAVE FAILED THE CHECKS] ******************************************************\nfatal: [nxos-spine2]: FAILED! => {\n \"assertion\": \"interface_pass_fail.fail \| length == 0\",\n \"changed\": false,\n \"evaluated_to\": false,\n \"msg\": \"Assertion failed\"\n}\nfatal: [nxos-spine1]: FAILED! => {\n \"assertion\": \"interface_pass_fail.fail \| length == 0\",\n \"changed\": false,\n \"evaluated_to\": false,\n \"msg\": \"Assertion failed\"\n}\n\nPLAY RECAP ***************************************************************************************************\nnxos-spine1 : ok=3 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\nnxos-spine2 : ok=3 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\n```\n\n### Step 6\n\nFeel free to play around with the data and change both the `interface_intent` dictionary and the configuration on the actual devices themselves!\n" }, { "alpha_fraction": 0.659335732460022, "alphanum_fraction": 0.6901256442070007, "avg_line_length": 30.383098602294922, "blob_id": "9518f818a8e859d3d3b6611e2c8a7d4fcb4685ed", "content_id": "e3aa51a7624b1314c6c050ad9e7af496624c8fd5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 11140, "license_type": "no_license", "max_line_length": 326, "num_lines": 355, "path": "/workshops/jinja2-deep-dive-day2/lab_guides/lab06_jinja_filters.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 06 - Jinja Filters\n\nGoals of this lab:\n\n- Practice the use of Jinja filters.\n- Practice filter chaining.\n- Understand the result type of filters operating on collections.\n\n## Task 01\n\n> Resources for this task:\n> - [Jinja2 built-in filters](https://jinja2docs.readthedocs.io/en/stable/templates.html#list-of-builtin-filters)\n> - [Jinja2 for loop](https://jinja2docs.readthedocs.io/en/stable/templates.html#for)\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab06-task1.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate a template named `lab06-task1.j2` in `python/templates` dir.\n\nYour template should use data from the `lab06-task1.yml` file to generate output matching the one below.\n\nYou should print only interface objects that are in the blocked state.\n\nThe final output should match the below text:\n\n```\nInterfaces in blocking state:\n{'cost': '4', 'interface': 'Gi1/3', 'port_id': '5', 'port_priority': '128', 'role': 'Altn', 'status': 'BLK', 'type': 'Shr', 'vlan_id': '1'}\n{'cost': '4', 'interface': 'Gi1/5', 'port_id': '5', 'port_priority': '128', 'role': 'Altn', 'status': 'BLK', 'type': 'Shr', 'vlan_id': '2'}\n{'cost': '4', 'interface': 'Gi1/7', 'port_id': '5', 'port_priority': '128', 'role': 'Altn', 'status': 'BLK', 'type': 'Shr', 'vlan_id': '3'}\n```\n\n> HINT: You can use loop to print each of the objects.\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task1.j2 -d lab06-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use the `selectattr` filter with the `eq` test to select only objects whose `status` attribute is equal to `BLK`.\n\nTo display selected objects you can use the `for` loop.\n\n```\nInterfaces in blocking state:\n{% for intf in show_spanning_tree \| selectattr('status', 'eq', 'BLK') %}\n{{ intf }}\n{% endfor %}\n```\n</details>\n\n### Step 4\n\nModify your template `lab06-task1.j2` to display a list of interface names only for interfaces that are in the blocking state.\n\nOutput to match\n```\nInterfaces in blocking state:\n['Gi1/3', 'Gi1/5', 'Gi1/7']\n```\n\n### Step 5\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task1.j2 -d lab06-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou need to chain the `map` filter and specify `attribute='interface'` as an argument. This will give you a collection of interface names only.\n\nFilters that give back collection return generator object. You need to convert the result to a list with the `list` filter before the final result can be displayed.\n\n```\nInterfaces in blocking state:\n{{ show_spanning_tree\| selectattr('status', 'eq', 'BLK') \| map(attribute='interface') \| list }}\n```\n\n</details>\n\n### Step 6\n\nModify your template `lab06-task1.j2` to make the output more human-friendly. List interface names on one line, separated by comma and space.\n\noutput to match\n```\nInterfaces in blocking state:\nGi1/3, Gi1/5, Gi1/7\n```\n\n### Step 7\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task1.j2 -d lab06-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use the `join` filter to generate a string resulting from concatenating collection items with the string `, ` as a separator.\n\nYou don't have to use the `list` filter here; the `join` filter works with generators as well as with lists.\n\n```\nInterfaces in blocking state:\n{{ show_spanning_tree \| selectattr('status', 'eq', 'BLK') \| map(attribute='interface') \| join(', ') }}\n```\n\n</details>\n\n## Task 02\n\n> Resources for this task:\n> - [Jinja2 built-in filters](https://jinja2docs.readthedocs.io/en/stable/templates.html#list-of-builtin-filters)\n> - [Jinja2 for loop](https://jinja2docs.readthedocs.io/en/stable/templates.html#for)\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab06-task2.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate a template named `lab06-task2.j2` in `python/templates` dir.\n\nYour template should use data from the `lab06-task2.yml` file to generate report matching the one below.\n\nOutput to match\n```\nServer type: app\nServers: [{'name': 'appFend04s', 'type': 'app', 'location': 'Seattle'}, {'name': 'appFend03s', 'type': 'app', 'location': 'Seattle'}]\nServer type: db\nServers: [{'name': 'dbAnalytics02s', 'type': 'db', 'location': 'Seattle'}, {'name': 'dbAnalytics01f', 'type': 'db', 'location': 'San Francisco'}, {'name': 'dbAnalytics01s', 'type': 'db', 'location': 'Seattle'}]\nServer type: ml\nServers: [{'name': 'mlNeural01s', 'type': 'ml', 'location': 'Seattle'}, {'name': 'mlNeural03s', 'type': 'ml', 'location': 'Seattle'}, {'name': 'mlNeural02s', 'type': 'ml', 'location': 'Seattle'}, {'name': 'mlNeural01p', 'type': 'ml', 'location': 'Portland'}, {'name': 'mlNeural01f', 'type': 'ml', 'location': 'San Francisco'}]\nServer type: redis\nServers: [{'name': 'redisCache03p', 'type': 'redis', 'location': 'Portland'}, {'name': 'redisCache01s', 'type': 'redis', 'location': 'Seattle'}, {'name': 'redisCache02f', 'type': 'redis', 'location': 'San Francisco'}]\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task2.j2 -d lab06-task2.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use the `groupby` filter with the `attribute='type'` argument to create groups of servers for each of the server types.\n\nYou should use the `for group, group_members` loop to iterate over the sequence generated by the `groupby` filter.\n\n```\n{% for server_type, servers in servers \| groupby(attribute='type') %}\nServer type: {{ server_type }}\nServers: {{ servers }}\n{% endfor %}\n```\n</details>\n\n### Step 4\n\nModify your template `lab06-task2.j2` to batch servers in units of 2 and display the names of the servers only.\n\nOutput to match\n```\nServer type: app\n['appFend04s', 'appFend03s']\nServer type: db\n['dbAnalytics02s', 'dbAnalytics01f']\n['dbAnalytics01s']\nServer type: ml\n['mlNeural01s', 'mlNeural03s']\n['mlNeural02s', 'mlNeural01p']\n['mlNeural01f']\nServer type: redis\n['redisCache03p', 'redisCache01s']\n['redisCache02f']\n```\n\n### Step 5\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task2.j2 -d lab06-task2.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use the `map` filter with the `attribute='name'` argument to create a collection of server names only for each of the server groups.\n\nYou should then apply a `batch` filter to the result, with `2` as the argument, to create batches of server names, each with 2 items.\n\nTo display resulting batches you should use the `for` loop.\n\n```\n{% for server_type, servers in servers \| groupby(attribute='type') %}\nServer type: {{ server_type }}\n{% for server_batch in servers \| map(attribute='name') \| batch(2) %}\n{{ server_batch }}\n{% endfor %}\n{% endfor %}\n```\n\n</details>\n\n### Step 6\n\nModify your template `lab06-task2.j2` to make the output more human-friendly.\n\n- Add a number to each of the batches.\n- Display server names in each batch separated by a comma and space.\n- Server names in each batch should be displayed in alphabetical order.\n- Add `---------------` divider separating server groups. \n- Divider needs to be centered in the field width of 40 characters.\n\nOutput to match\n```\nServer type: app\nBatch 1: appFend03s, appFend04s\n --------------- \nServer type: db\nBatch 1: dbAnalytics01f, dbAnalytics02s\nBatch 2: dbAnalytics01s\n --------------- \nServer type: ml\nBatch 1: mlNeural01s, mlNeural03s\nBatch 2: mlNeural01p, mlNeural02s\nBatch 3: mlNeural01f\n --------------- \nServer type: redis\nBatch 1: redisCache01s, redisCache03p\nBatch 2: redisCache02f\n --------------- \n```\n\n### Step 7\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task2.j2 -d lab06-task2.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nUse the `loop.index` variable to number each batch.\n\nYou should apply the `sort` filter to servers in a batch to have them sorted in alphabetical order.\n\nYou should use the `join` filter with `, ` argument to concatenate server names in a batch.\n\nTo center `---------------` you should use `center` filter with `40` as an argument.\n\n```\n{% for server_type, servers in servers \| groupby(attribute='type') %}\nServer type: {{ server_type }}\n{% for server_batch in servers \| map(attribute='name') \| batch(2) %}\nBatch {{ loop.index }}: {{ server_batch \| sort \| join(', ') }}\n{% endfor %}\n{{ '---------------' \| center(40) }}\n{% endfor %}\n```\n\n</details>\n\n## Task 03\n\n> Resources for this task:\n> - [Jinja2 built-in filters](https://jinja2docs.readthedocs.io/en/stable/templates.html#list-of-builtin-filters)\n> - [Jinja2 for loop](https://jinja2docs.readthedocs.io/en/stable/templates.html#for)\n\n### Step 1\n\nYou work with API that returned data structure saved in the `python/vars/lab06-task3.yml` file.\n\nThis data structure records the name of the prefix-list on some of the interfaces. If an interface has a prefix-list defined, it means the network configured on that interface needs to be added to the specified prefix list.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nA starter template, `lab06-task3.j2`, was created for you in `python/templates` dir.\n\nThis template has some issues, and it currently generates the below output:\n\n```\nip prefix-list PL_REDIST_OSPF seq 5 10.3.0.0/24\nip prefix-list PL_REDIST_BGP seq 5 10.6.7.0/24\nip prefix-list PL_REDIST_OSPF seq 5 10.23.1.0/24\nip prefix-list PL_REDIST_BGP seq 5 10.145.5.0/24\n```\n\nYou need to fix this template. It should correctly generate prefix-lists as required with entry sequence numbers starting from 5.\n\nOutput to match*\n```\nip prefix-list PL_REDIST_BGP seq 5 10.6.7.0/24\nip prefix-list PL_REDIST_BGP seq 10 10.145.5.0/24\nip prefix-list PL_REDIST_OSPF seq 5 10.3.0.0/24\nip prefix-list PL_REDIST_OSPF seq 10 10.23.1.0/24\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab06-task3.j2 -d lab06-task3.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nPrefix-lists defined in the interface objects can appear multiple times and they're not guaranteed to be ordered.\n\nIn cases like this, you should use the `groupby` filter to create groups of objects that have something in common. Here you should specify `attribute='prefix_list'` to create groups of objects with the same prefix-list.\n\nTo iterate over groups and members you should use the `for group, group_members` loop.\n\nEach of the group members is a collection of interfaces but you want IP addresses only. You should use the `for` loop and `map` filter to get a sequence of `ip` values.\n\nFinally, inside the inner loop, you should use the `loop.index` variable to generate correct sequence numbers.\n\n```\n{% for pl_name, pl_members in interfaces \| groupby(attribute='prefix_list' ) %}\n{% for ip in pl_members \| map(attribute='ip') %}\nip prefix-list {{ pl_name }} seq {{ 5 loop.index }} {{ ip \| ipaddr('network/prefix') }}\n{% endfor %}\n{% endfor %}\n```\n\n</details>" }, { "alpha_fraction": 0.7069792151451111, "alphanum_fraction": 0.732374370098114, "avg_line_length": 25.074073791503906, "blob_id": "20c931eee8c0986273e05f45fde12c378d0bb41e", "content_id": "2faccb9e69215a33807a8b8ffd1170826e2553ec", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 5631, "license_type": "no_license", "max_line_length": 217, "num_lines": 216, "path": "/workshops/jinja2-deep-dive-day1/lab_guides/lab01_jinja_basics.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 01 - Jinja basics\n\nGoals of this lab:\n\n- Refresh use of Jinja variable substitution.\n- Understand limitations of the '.' (dot) method of accessing attributes.\n- Practice creating new variables.\n- Practice applying math operator.\n- Understand when to use `~` concatenation operator.\n\n## Task 1\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab01-task1.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n### Step 2\n\nCreate a template named `lab01-task1.j2` in `python/templates` dir.\n\nYour template should use data from the `lab01-task1.yml` file to generate output matching the one below.\n\nDon't use loops in your solution.\n\nThe final output should match the below text:\n```\nhostname lab-nxos\n\nno ip domain lookup\nip domain name lab.local\nip name-server 8.8.8.8\nip name-server 8.8.4.4\n\nntp server 10.5.5.2 prefer\nntp server 10.7.5.2\n\nsnmp-server community snmpS3cr4t! RO\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab01-task1.j2 -d lab01-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use variable substitution within `{{ }}` blocks.\n\nYou can use `.` or `[]` notation for accessing dictionary keys and list items. It is recommended to use the `[]` notation to make explicit difference between key names and variables.\n\nFor keys containing special characters, e.g. `-`, you need to use `[]` notation.\n\n\n```\nhostname {{ hostname }}\n\nno ip domain lookup\nip domain name {{ dns['domain'] }}\nip name-server {{ dns['servers'][0] }}\nip name-server {{ dns['servers'][1] }}\n\nntp server {{ ntp_servers[0] }} prefer\nntp server {{ ntp_servers[1] }}\n\nsnmp-server community {{ snmp['community-string'] }} RO\n```\n</details>\n\n## Task 2\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab01-task2.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nYou will now create a template named `lab01-task2.j2` in `python/templates` dir. This template will generate an inventory report for the lab devices.\n\nLab devices are installed in cabinets in groups of 4. First 4 devices will be installed in cab # 10, next 4 in cab # 11 and so on.\n\nEach device is installed in racks starting from the bottom. Starting rack units are 6 units apart between devices. So 1st device in lab 1 will be installed at U height 8. 2nd device in lab 1 at U height 14, and so on.\n\nThe final hostname is built by appending the cabinet number and starting rack position to the device name.\n\nYour template should use data from the `lab01-task2.yml` file to generate output matching the one below.\n\nFinal output to match:\n```\nLab device onboarding report\n\nDevice hostname lab-cat9k1320\nCabinet number: 13\nRacks units occupied: 20 - 23\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab01-task2.j2 -d lab01-task2.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nUse `{% set %}` statements to define new variables. This makes the rest of the template simpler.\n\nApply mathematical operators to compute lab numbers, U height, etc.\n\nUse the `~` operator to concatenate a string with integers.\n\n```\n{% set unit_in_lab = lab_number % 4 %}\n{% set cabinet = lab_cab_start + unit_in_lab %}\n{% set rack_u_start = lab_rack_u_start + (6 * (unit_in_lab -1 )) %}\nLab device onboarding report\n\nDevice hostname {{ name ~ cabinet ~ rack_u_start }}\nCabinet number: {{ cabinet }}\nRacks units occupied: {{ rack_u_start }} - {{ rack_u_start + rack_u_height - 1 }}\n```\n\n</details>\n\n## Task 3\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab01-task3.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n## Step 2\n\nIn this task, you are a writing template generating stub of the base config for network devices.\n\nYou will now create a template named `lab01-task3.j2` in `python/templates` that accomplishes this task. Your template will use data from the `lab01-task3.yml` file.\n\nSome of the data structures are a bit tricky to work with so pay attention to the syntax.\n\nThe output of your template after rendering should match the below one:\n```\nhostname sw-dist-lon-01\n\nno ip domain lookup\nip domain name jinja2.lab\n\nsnmp-server location London Telehouse East\nsnmp-server contact_info [email protected]\n\narchive\n log config\n logging enable\n logging size 500\n notify syslog contenttype plaintext\n hidekeys\n\nlogging alarm informational\nlogging trap notifications\nlogging origin-id hostname\nlogging source-interface Loopback0\nlogging host 10.1.54.4\nlogging host 10.4.6.16\n```\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab01-task3.j2 -d lab01-task3.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nUse variable substitution `{{ }}` syntax to access values of the variables.\n\nUse `[]` notation for accessing keys containing special characters.\n\nDefine helper variable to make it easier to access nested data elements.\n\n```\n{% set device_region = sites[site]['region'] %}\nhostname {{ hostname }}\n\nno ip domain lookup\nip domain name {{ domain_name }}\n\nsnmp-server location {{ sites[site]['location-name'] }}\nsnmp-server contact_info [email protected]\n\narchive\n log config\n logging enable\n logging size {{ logging_settings['archive_logging_size'] }}\n notify syslog contenttype plaintext\n hidekeys\n\nlogging alarm informational\nlogging trap notifications\nlogging origin-id hostname\nlogging source-interface {{ logging_settings['source_interface'] }}\nlogging host {{ regions[device_region]['logging_hosts'][0] }}\nlogging host {{ regions[device_region]['logging_hosts'][1] }}\n```\n\n</details>" }, { "alpha_fraction": 0.7151898741722107, "alphanum_fraction": 0.7506328821182251, "avg_line_length": 45.47058868408203, "blob_id": "4ac6355579f62de10d2cbd32eb111e05b9c0fd13", "content_id": "418abcc1f61eb3d6d895ad54f77056f6f3671465", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 790, "license_type": "no_license", "max_line_length": 127, "num_lines": 17, "path": "/workshops/extending-ansible/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "## Extending Ansible Workshop\n\n- Lab 01 - [Expanding an Abbreviated Interface Name](lab01_guide.md)\n- Lab 02 - [Creating the Expand Range Filter](lab02_guide.md)\n- Lab 03 - [Implementing a Filter to Display PrettyTables](lab03_guide.md)\n- Lab 04 - [Implementing a Filter to Compare Intent with Operational Data](lab04_guide.md)\n- Lab 05 - [Creating a Custom Module for Querying the IOS-XE REST API](lab05_guide.md)\n- Lab 06 - [Creating a Custom Module for Making Changes to the IOS-XE REST API](lab06_guide.md)\n- [Lecture Slides](ExtendingAnsible.pdf)\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.621052622795105, "alphanum_fraction": 0.7473683953285217, "avg_line_length": 18, "blob_id": "cac9d71f36c21e864fd62c85e3398d74951a8617", "content_id": "53205f2ae4f093b3a8a329c2c89264ca28b293ec", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 95, "license_type": "no_license", "max_line_length": 50, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-acme-lsw02/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-acme-lsw02\n\nThis Cisco 93180YC-FX-24 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "1485362f2eff4dbb9873bc2c9a8214360e8a30a5", "content_id": "ec00fc333c2a0e1bfc2faf5d607d6794eb01b252", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx03/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx03\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "42b273c1be71eca54f85f9ebaa1d2ca1e181759f", "content_id": "9cabccdaebebf7fae8b5300117c6d0542133ca06", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx17/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx17\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6363636255264282, "alphanum_fraction": 0.7386363744735718, "avg_line_length": 16.600000381469727, "blob_id": "18ea429a85a81fa6800cfeda538eced4c1889556", "content_id": "32cf065faa5765d54d9e2045d5e276037cb50d6e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 88, "license_type": "no_license", "max_line_length": 47, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-CORE-SW02/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-CORE-SW02\n\nThis Cisco C9500-48Y4C device is located in HQ.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7389017343521118, "alphanum_fraction": 0.7483962178230286, "avg_line_length": 35.42523193359375, "blob_id": "2035a76496e466655df203f8df851da77d5811dd", "content_id": "92770e21a339edf4a1f1cd6f2bbc8113680170f5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 7794, "license_type": "no_license", "max_line_length": 215, "num_lines": 214, "path": "/challenges/12-git-fundamentals/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Git Fundamentals\n\nThe goal of this exercise is to learn how to work with Git Version Control System. You will practice working with the local and remote Git repositories using Git CLI client and BitBucket.\n\n## Exercise Overview\n\n### Prerequisites\n\nYou will need to have Git software installed on your machine.\n\n### Tasks\n\nSubmitting your solution for this challenge is optional - feel free to ask for help via email, chat, or at the open office hours if you get stuck!\n\n#### Task 1 - Creating new Git repository\n\nIn this task, you will create a new Git repository.\n\n- Create a directory called `git-training`.\n\n- Create a new, empty Git repository inside of the `git-training` directory.\n\n- Your initial branch should be called `main`.\n\n- Check the status of the repository you just created.\n\nSubmit Git commands you used and shell output showing the status of the repository.\n\n> Hint: Use command `git branch -m main` to rename the initial branch after you initialized your Git repository.\n\n#### Task 2 - Configure user name and email\n\nIn this task, you will configure the user name and email that Git will associate with the commits you make.\n\n- Configure Git user name.\n\n- Configure Git email address.\n\n- Run command showing configured values.\n\nSubmit Git commands you used and output showing configured values.\n\n#### Task 3 - Adding a new file and checking repository status\n\nIn this task, you will create a new file in the directory where your git repository is located. You will then check the status of the repository.\n\n- Create file called `vlans.cfg` and copy-paste the below lines into it:\n\n ```\n vlan 30\n name Data\n\n vlan 40\n name Voice\n\n vlan 50\n name Office\n ```\n\n- Check the status of the repository. Which area of Git is this file currently located in?\n\n- If you made changes to the file now, would Git be aware of them?\n\n#### Task 4 - Asking Git to track changes to the file\n\nIn this task, you will ask Git to start tracking changes made to the `vlans.cfg` file.\n\nYou are asked to:\n\n- Use the Git command to add the `vlans.cfg` file to the staging area.\n\n- Check the status of the file. What does Git tell us about this file?\n\n- Add a new VLAN with the VID `60` and name `Printers` to the `vlans.cfg` file.\n\n- Check the status of the file again. What does Git show now?\n\n- What would happen if we committed this file? Would the change we just made be included in the commit snapshot?\n\n- Use the Git command that will ensure the change we just made is included in the next commit.\n\n#### Task 5 - Committing changes\n\nIn this task, you are asked to commit the file, and changes made to it. You then will review the commit history.\n\n- In the previous task we created a file and made changes to it. You are now asked to create a point-in-time snapshot of the repository by committing staged changes. You can use any message you want for this commit.\n\n- Once you made your commit, retrieve commit history and copy output for the commit you just made.\n\n- Identify the ID of the commit you just made.\n\n#### Task 6 - Viewing differences between Git areas\n\nIn this task, you are asked to modify a file and confirm differences between the last snapshot and the current version of the file.\n\n- Remove config for the VLAN 60 and add the below VLAN config to the bottom of the `vlans.cfg` file:\n\n```\nvlan 70\n name Factory\n```\n\n- Check the difference between your working directory and the last commit. Copy the output.\n\n- What do `-` and `+` signs mean in the context of Git diffs?\n\n- Make a new snapshot by committing changes you just made. Use commit message `Adding vlan 70.`\n\n- Check commit history. How many commit entries are there now?\n\n#### Task 7 - Working with the remote repository\n\nIn this task, you are asked to create a remote private repository on BitBucket. You will then push your local repository to it.\n\nFirst, you need to create a remote repository on BitBucket. To do that follow the steps below:\n\n- Log into BitBucket using your AD credentials: [Bitbucket](https://bitbucket-prod.aws.baxter.com).\n\n- Click on your profile icon in the top-right corner and then click on the `View profile` menu item.\n \n ![](images/git-fundamentals-01.png)\n \n- On your profile page click on the `Create repository` button.\n\n ![](images/git-fundamentals-02.png)\n\n- On the repository creation form enter `git-training` (1) as the name. Use `main` as the default branch name (2) and click on the `Create repository` button (3).\n\n ![](images/git-fundamentals-03.png)\n\nYour remote repository should now be in place. Switch over to your local Git repository and complete the following tasks.\n\n- Configure your local repository to track the repository you just created in BitBucket.\n\n- Confirm your local repository is tracking the BitBucket remote repository. Copy command you used and its output.\n\n- Push contents of your local repository to the remote. Provide a copy of the output you get after the operation is completed.\n\n- After push is completed, navigate to your repository in BitBucket and take a screenshot showing differences between current and previous versions of the `vlans.cfg`.\n\n- Find and take a screenshot of the GUI page showing commit history.\n\n> Hints:\n> - Remember to retrieve the URL of the remote repository from BitBucket GUI.\n> - Remember to set upstream branch tracking.\n> - Use your AD credentials when prompted for username and password.\n\n#### Task 8 - Cloning existing remote repository\n\nIn this task, you are asked to make a local copy of a remote repository.\n\n- Switch to a new empty directory.\n\n- Make a local copy of the remote repository you created in task #7.\n\n- Check the status of the local repository. Copy the output.\n\n- Check if the local repository has any remotes configured. Copy the output.\n\n#### Task 9 - Bonus - Creating new branch\n\nIn this task, you're asked to create a pull request and merge a new branch into the `main` branch.\n\n- Create a new branch for your repository. Name it `adding-svis`.\n\n- In your new branch create a file named `svis.cfg` and add the below lines to it:\n\n ```\n interface Vlan30\n description Data_SVI\n ip address 10.90.10.1 255.255.255.0\n\n interface Vlan50\n description Office_SVI\n ip address 10.90.11.1 255.255.255.0\n ```\n\n- Add the file to staging and make a commit.\n\n- Push the `adding-svis` branch to the remote repository.\n\n- Navigate to the BitBucket GUI and take a screenshot showing the contents of the `svis.cfg` file.\n\n> Hint: You will have to either set the upstream branch for this local branch or explicitly specify the remote branch you're pushing to.\n\n#### Task 10 - Bonus - Pull request and merging branches\n\nIn this task, you will merge the `adding-svis` branch into the `main` branch.\n\n- Navigate to your repository in BitBucket.\n\n- Find the `Pull requests` space, navigate to it and create a new pull request. \n - Your pull request should merge the branch `adding-svis` into the `main` branch.\n - Use `Merging in svi configs` as the title of your pull request.\n - Take a screenshot showing diff for this pull request.\n\n- Merge your pull request. You can keep the default messages and settings.\n\n- Take a screenshot of the commit history for the `main` branch as shown in the BitBucket GUI.\n\n- Navigate back to your local repository, use the `main` branch. Synchronize the local repository with the remote repository.\n\n- Investigate commit history and confirm the merge message is there. Copy the output for the merge commit.\n\n### Reference Enablement Material\n\n- Git fundamentals\n \n> Note: Recordings of the relevant sessions can be found online at: https://training.networktocode.com/ \n\n### External references\n\n- [The Pro Git book](https://git-scm.com/book/en/v2)\n- [Git Reference Manual](https://git-scm.com/docs)" }, { "alpha_fraction": 0.6692731380462646, "alphanum_fraction": 0.6810023188591003, "avg_line_length": 37.53424835205078, "blob_id": "86e7b3d0bc9087928f4f4df09bd494d9df78971a", "content_id": "43f14ce740f4ff38128708a4c9cf5c446a27abc5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 5635, "license_type": "no_license", "max_line_length": 382, "num_lines": 146, "path": "/challenges/03-jinja2-filters/solution/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge Exercise Solution Guide\n\n## Using Ansible Jinja Filters on Network Device Data\n\nIn this challenge you have to use various Jinja2 filters (some are only available via Ansible's modifications, like ipaddr!) to query, format, filter, and present data from a network device.\n\nYou get started by loading the JSON output of a `show interfaces` command on an NX-OS switch. This output is provided as a file named `show_int_nxos.json` which should be placed next to the exercise\nplaybook named `pb_filters_challenge.yml`.\n\n## Solution Walkthrough\n\n### Task 1\n\n#### Step 1\n\nHere you are using the filter `length` which returns the number of items in a sequence. Since the actual list of interfaces is nested two levels down inside the data structure, you have to extract the list by walking through the keys `TABLE_interface.ROW_interface`.\n\n```yaml\n - name: T1S1 - GET THE NUMBER OF INTERFACES\n debug:\n msg: \"The switch has a total of {{ show_int.TABLE_interface.ROW_interface \| length }} interfaces.\"\n```\n\n#### Step 2\n\nTo avoid repeating the two keys over and over again and keep lines shorter, you create a new variable (or fact) that contains only the list of interfaces.\n\n```yaml\n - name: T1S2 - EXTRACT THE INTERFACE LIST\n set_fact:\n intf_list: \"{{ show_int.TABLE_interface.ROW_interface }}\"\n```\n\n#### Step 3\n\nEach interface is defined in a fairly large dictionary containing a lot of operational data. The only field you need is `interface` which represents the name. Use the `map` filter to only retrieve the values of that specific key for all the elements of the `intf_list` list. The map filter returns a generator object so you need to convert it to a list so it prints to the terminal.\n\n```yaml\n - name: T1S3 - LIST ALL INTERFACE NAMES\n debug:\n msg: \"List of interface names: {{ intf_list \| map(attribute='interface') \| list }}\"\n```\n\n#### Step 4\n\nInstead of printing a Python data structure (a list), use the `join(', ')` filter to join together the elements from the list of interface names with commas.\n\n```yaml\n - name: T1S4 - PRINT INTERFACE NAMES AS CSV\n debug:\n msg: \"Comma-separated interface names: {{ intf_list \| map(attribute='interface') \| list \| join(', ') }}\"\n```\n\n#### Step 5\n\nThe MAC addresses are held in a different attribute and, since the result is a list of strings, you can apply the `upper` filter to the whole list in one go. Not all filters can work on both a single value and a list!\n\n```yaml\n - name: T1S5 - LIST ALL INTERFACE MAC ADDRESSES AS UPPERCASE\n debug:\n msg: \"All MAC addresses: {{ intf_list \| map(attribute='eth_hw_addr') \| list \| upper }}\"\n```\n\n#### Step 6\n\nThe `hwaddr` filter only works with a single value, so it needs some help. `map` can also apply one filter to a list of values, making it possible to convert the previous list of MACs to a different notation.\n\n```yaml\n - name: T1S6 - CONVERT MAC ADDRESSES TO LINUX FORMAT\n debug:\n msg: \"All MAC addresses: {{ intf_list \| map(attribute='eth_hw_addr') \| map('hwaddr', 'linux') \| list }} \"\n```\n\n### Task 2\n\n#### Step 1\n\nHere all you need to do is extract two pieces of information from the first interface, `mgmt0`.\n\n```yaml\n - name: T2S1 - EXTRACT THE MGMT0 IP PREFIX\n set_fact:\n mgmt0_prefix: \"{{ intf_list.0.eth_ip_addr }}/{{ intf_list.0.eth_ip_mask }}\"\n```\n\n#### Step 2\n\nNow you apply various parameters of the `ipaddr` filter as per the documentation.\n\n```yaml\n - name: T2S2 - PRINT THE USABLE IP RANGE FOR THE MGMT0 PREFIX\n debug:\n msg: \"Usable IP range: {{ mgmt0_prefix \| ipaddr('range_usable') }}\"\n```\n\n#### Step 3\n\n```yaml\n - name: T2S3 - PRINT THE BROADCAST ADDRESS FOR THE MGMT0 PREFIX\n debug:\n msg: \"Broadcast address: {{ mgmt0_prefix \| ipaddr('broadcast') }}\"\n```\n\n#### Step 4\n\n```yaml\n - name: T2S4 - PRINT THE 555TH USABLE ADDRESS FOR THE MGMT0 SUBNET\n debug:\n msg: \"The 555th IP in the subnet: {{ mgmt0_prefix \| ipaddr('555') }}\"\n```\n\n### Task 3\n\n#### Step 1\n\nThe `selectattr` filter can use a number of operators to apply tests to the data it is parsing. In the documentation they are called [tests](https://jinja.palletsprojects.com/en/2.11.x/templates/#list-of-builtin-tests).\n\nHere, you need to check if the `admin_state` is `up` for a given interface, then count how many there are in the resulting list.\n\n```yaml\n - name: T3S1 - COUNT THE INTERFACES IN ADMIN UP STATE\n debug:\n msg: \"Number of interfaces in Admin/UP state: {{ intf_list \| selectattr('admin_state','eq', 'up') \| list \| length }}\"\n```\n\n#### Step 2\n\nThe `selectattr` filter does not reduce individual data like `map`, so you still have all of your interface parameters, including the names. Take this expression step by step and see what it returns.\n\n```yaml\n - name: T3S2 - PRINT A CSV LIST OF THE INTERFACE NAMES IN ADMIN UP STATE\n debug:\n msg: \"Interfaces in Admin/UP state: {{ intf_list \| selectattr('admin_state','eq', 'up') \| map(attribute='interface') \| list \| join(', ') }}\"\n```\n\n#### Step 3\n\nThis task should now be easy to solve - it's just a matter of adding a second `selectattr` condition, chained to the first, creating the equivalent of an `and` operator.\n\nIn pseudo code, it would look like: `if admin_state == 'up' and state == 'up'`.\n\n```yaml\n - name: T3S3 - PRINT A CSV LIST OF ALL INTERFACE NAMES IN UP/UP STATE\n debug:\n msg: \"Interfaces in Admin/UP Operational/UP state: {{ intf_list \| selectattr('admin_state','eq', 'up') \| selectattr('state','eq', 'up') \| map(attribute='interface') \| list \| join(', ') }}\"\n```\n\n" }, { "alpha_fraction": 0.6756756901741028, "alphanum_fraction": 0.6805896759033203, "avg_line_length": 19.350000381469727, "blob_id": "cc2cdb9604daa84ab53bed77a92eee957b845f3f", "content_id": "b0e6b886956e0e9bf88385ae7f2b4c72655ec7f0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 407, "license_type": "no_license", "max_line_length": 61, "num_lines": 20, "path": "/challenges/05-docker-tools/solution/files/tasks.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "from invoke import task\n\nNAME = \"netdev/tools\"\nVERSION = \"0.1\"\n\n@task\ndef container(context):\n context.run(f\"docker build -t {NAME}:{VERSION} .\")\n\n@task\ndef run(context):\n context.run(f\"docker run -it {NAME}:{VERSION}\", pty=True)\n\n@task\ndef clean_images(context):\n context.run(f\"docker image rm -f {NAME}:{VERSION}\")\n\n@task\ndef clean_stopped(context):\n context.run(f\"docker container prune -f\")\n" }, { "alpha_fraction": 0.745520830154419, "alphanum_fraction": 0.7546310424804688, "avg_line_length": 39.15853500366211, "blob_id": "9f206b4ca554630135cfc8470cdb29aef83b967c", "content_id": "e7cd50265d9dc15a6e8d3b48f9a9ffae3293f0f4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 3293, "license_type": "no_license", "max_line_length": 258, "num_lines": 82, "path": "/workshops/netbox-extensibility/lab02_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC Netbox Workshop - Lab 02\n\nIn this lab you will be interacting with the `Reports` and `Custom Scripts` that have been already provisioned in your Netbox.\n\n> You will receive the IP address of your own Netbox instance together with the credentials from the instructor during the workshop.\n\n## Task 1\n\nThis task explores Netbox's Reports feature.\n\n### Step 1\n\nOpen the Netbox web interface at the IP provided and log in.\n\n### Step 2\n\nObserve the `Reports` summary panel in the homepage of Netbox, giving you the Pass/Fail status of the latest run of each Report.\n\n![](images/lab02-1.png)\n\n### Step 3\n\nOpen the `Reports` section from the top bar menu `Other`. Notice the slightly more detailed view of each report, its individual runs and four result types (success/green, info/blue, warning/amber, failure/red).\n\n### Step 4\n\nClick the `Hostname` report link in the table to open the detailed view of this report. Observe the URL in your browser bar - `http://NETBOX_IP/extras/reports/devices.Hostname/`.\n\n> The report is defined in a file called `devices.py` and the code resides in a class called `Hostname`. It performs a simple check, that the hostname is using only UPPERCASE letters.\n\n### Step 5\n\nTake note of the results summary (13 devices succeeded the test) and the last run date of the report - not very recent!\n\nClick the `Run Report` blue button.\n\n### Step 6\n\nExplore the newly refreshed results. The date will have updated, the report is now overall `Failed` because of the 42 devices that are not compliant. Scroll down in the page and explore the results.\n\n### Step 7\n\nGo back to the main `Reports` page and open the `JuniperMigration` report. Re-run it and explore the results - notice that if the compliance check cannot be performed (data is missing), then the report code marks that result with a different label.\n\n> The device.JuniperMigration report tests whether the `platform` attribute of a device starts with the letters \"ju\".\n\n### Step 8\n\nTake some time to explore the other Reports (`Platform`, `PrimaryIP` and `Rack`). They all do very similar checks which should be easy to understand from the name of the report function (e.g. `test_device_has_primary_ip`) even without seeing the Python code.\n\n\n## Task 2\n\nThis task explores Netbox's Custom Scripts feature.\n\n### Step 1\n\nFrom the top menu, head over to `Other` and select `Scripts`.\n\n![](images/lab02-2.png)\n\n### Step 2\n\nCustom Scripts are very similar to Reports, but they have the added functionality of being able to accept user input via the Netbox UI.\n\nSelect the only script available to you from the table: `Naming Convention Check`.\n\n### Step 3\n\nThis script performs the same test as the report used in the previous task - a device is compliant if its name is all UPPERCASE. The twist is that you can run it only for devices that belong to a particular site.\n\nSelect the `HQ` site from drop-down list and click `Run Script`.\n\n> Bonus: The scripts UI allows you to inspect the Python code by selecting the `Source` tab.\n\n> You may ignore the `Commit changes` option since this script is read-only.\n\n### Step 4\n\nExplore the results and scroll down to the bottom of the page if you want to re-run the script on a different site (e.g. `DC1` will also have non-compliant devices).\n\n![](images/lab02-3.png)\n" }, { "alpha_fraction": 0.6987714171409607, "alphanum_fraction": 0.7246599197387695, "avg_line_length": 42.409523010253906, "blob_id": "0809ae3ae82cacd52daec4524bfb6690ccce39c3", "content_id": "91524015233042c765cc7ad3edd76919329d4db5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 9148, "license_type": "no_license", "max_line_length": 341, "num_lines": 210, "path": "/challenges/04-codelint/solution/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Code Linting & Formatting Challenge Solution\n\n## Introduction\n\nThis exercise requires you to fix a repository containing a few Python files and YAML Ansible playbooks. These files have various syntax and formatting errors in them and you need to fix all of them in order for the tests to pass.\n\nThe focus here is on using the `black, flake8, yamllint, and ansible-lint` tools one by one to parse the files in the `code` subfolder.\n\nA `Makefile` is provided which runs these tools with the correct parameters for you and it also can create a Python virtualenv with the correct packages installed should you need one (highly recommended).\n\n## Code formatting - black\n\nLet's start with formatting all of the python code in the `code` folder. Run the `make black` command and check what it reports.\n\n```\n(venv) .../challenges/codelint/solution (master %) make black\nblack --check --diff code\n--- code/custom_rules/CapitalNamesRule.py 2020-08-14 18:53:19.948544 +0000\n+++ code/custom_rules/CapitalNamesRule.py 2020-08-14 18:54:40.952926 +0000\n@@ -1,12 +1,16 @@\n from ansiblelint import AnsibleLintRule\n+\n+\n class CapitalNamesRule(AnsibleLintRule):\n id = \"289\"\n- shortdesc=\"All task names should be capitalized\"\n- description='Using all uppercase names creates uniformity and improves readability'\n- severity='LOW'\n- tags= ['formatting\", \"readability']\n+ shortdesc = \"All task names should be capitalized\"\n+ description = (\n+ \"Using all uppercase names creates uniformity and improves readability\"\n+ )\n+ severity = \"LOW\"\n+ tags = ['formatting\", \"readability']\n version_added = \"v4.0.0\"\n \n def matchtask(self, file, task):\n if task.get(\"name\"):\n return task.get(\"name\") != task.get(\"name\").upper()\nwould reformat code/custom_rules/CapitalNamesRule.py\nerror: cannot format code/file_copy.py: Cannot parse: 119:24: if pull is False\nOh no! 💥 💔 💥\n1 file would be reformatted, 1 file would fail to reformat.\nmake: [Makefile:20: black] Error 123\n```\n\nIt says it would reformat one file (`CapitalNamesRule.py`), but that `file_copy.py` fails due to a code error. It's complaining about line 119, so open this file and check what's wrong. It turns out there's a missing `:` after the `if` statement! Fix it, save the file, and run `make black` again.\n\n```\n<LONG DIFF OUTPUT SNIPPED>\nOh no! 💥 💔 💥\n2 files would be reformatted.\nmake: * [Makefile:20: black] Error 1\n```\n\nIt now shows you the differences (\"diffs\") between the source files and its reformatting output. The Makefile uses the `--check --diff` flags so no changes are actually made. Go ahead and let the formatter save the changes to both files by running the `black code` command (it will scan for all python files in the `code` folder).\n\n```\n(venv) .../challenges/codelint/solution (master %) black code\nreformatted /x/dev/ntc/projects/enablement-catalog/challenges/codelint/solution/code/custom_rules/CapitalNamesRule.py\nreformatted /x/dev/ntc/projects/enablement-catalog/challenges/codelint/solution/code/file_copy.py\nAll done! ✨ 🍰 ✨\n2 files reformatted.\n```\n\nYou can double check now that `make black` succeeds, reporting that no changes are needed.\n\n## Code linting - flake8\n\nUp next, run the `make flake8` command. It reports the following issues.\n\n```\n(venv) .../challenges/codelint/solution (master %) make flake8 \nflake8 --ignore E501 code\ncode/file_copy.py:4:1: F401 'pynxos.errors.CLIError' imported but unused\ncode/file_copy.py:134:20: F821 undefined name 'hostnam'\nmake: *** [Makefile:23: flake8] Error 1\n```\n\nOpen the `code/file_copy.py` file in your editor and look at line 4. If you do a quick search in the file, it does indeed look like `CLIError` is not used anywhere, so you can remove it from the `import` statement.\n\nThe second error points at line 134. If you inspect it, you will notice that it looks like a typo, the `e` at the end of `hostname` is missing. Fix the typo and save the file.\n\nNow you can run the linter again and it should all be good - in this case no output means no errors.\n\n```\nmake flake8 \nflake8 --ignore E501 code\n```\n\n## YAML Linting\n\nWith the python files fixed, it's time to look at the YAML code included in the form of Ansible playbooks. Run the `make yamllint` command and check the output.\n\n```\n(venv) .../challenges/codelint/solution (master %) make yamllint \nyamllint -s code/.yml\ncode/pb_csv_report.yml\n 3:3 error wrong indentation: expected 0 but found 2 (indentation)\n 6:19 warning truthy value should be one of [false, true] (truthy)\n 19:19 warning truthy value should be one of [false, true] (truthy)\n 36:19 warning truthy value should be one of [false, true] (truthy)\n 52:19 warning truthy value should be one of [false, true] (truthy)\n 68:19 warning truthy value should be one of [false, true] (truthy)\n 82:1 error too many blank lines (3 > 2) (empty-lines)\n 86:19 warning truthy value should be one of [false, true] (truthy)\n 91:9 error wrong indentation: expected 6 but found 8 (indentation)\n\ncode/pb_snmp_config.yml\n 1:1 error too many blank lines (1 > 0) (empty-lines)\n 2:3 warning comment not indented like content (comments-indentation)\n 3:1 warning missing document start \"---\" (document-start)\n 3:81 error line too long (101 > 80 characters) (line-length)\n 8:20 error too many spaces before colon (colons)\n 13:7 error duplication of key \"ios\" in mapping (key-duplicates)\n\nmake: *** [Makefile:27: yamllint] Error 1\n```\n\n### Fixing pb_csv_report.yml\n\nOpen `code/pb_csv_report.yml` in your editor and fix the errors. You will notice that all the plays are indented when they should not be (at 2 spaces instead of 0). In most modern code editors you should be able to select all relevant lines (from 3 to 101) and reduce their indentation by using a keyboard shortcut (e.g. `Ctrl+[` in VSCode).\n\nWhile YAML accepts `no` instead of `false`, `yamllint` gives you a warning about it. To get rid of it, you can replace all instances of `no` with `false`. Also there's one too many blank lines that you should fix on line 82.\n\nFinally, there's one more indentation problem starting at line 91 (all the way to 101). You will notice the tasks are indented 4 spaces instead of 2.\n\n### Fixing pb_snmp_config.yml\n\nOpen `code/pb_snmp_config.yml` in your editor and fix the errors. \n\nAlign the comment indentation with the entry following it. The play name is a bit too wordy, so shorten it a bit so it fits in the 80 characters line length.\n\nOn line 8, the extra space before the colon is a problem, as is the fact that the `ios` key is duplicated on line 13. On closer inspection it should really read `junos`.\n\nAt the very start, we're missing the YAML `---` document start marker so add that in and you should be done!\n\nRun the `make yamllint` command again and check the output. No news is good news.\n\n```\n(venv) .../challenges/codelint/solution (master %) make yamllint \nyamllint -s code/.yml\n```\n\n## Ansible Linting\n\nThe final check is to run `ansible-lint` by using the `make ansible-lint` command.\n\n```\n(venv) .../challenges/codelint/solution (master %) make ansible-lint \nansible-lint -Rr code/custom_rules code/pb.yml\n[502] All tasks should be named\ncode/pb_csv_report.yml:11\nTask/Handler: file path=./docs/csv/ state=directory __line__=11 __file__=code/pb_csv_report.yml\n\n[502] All tasks should be named\ncode/pb_csv_report.yml:57\nTask/Handler: eos_facts \n\n[289] All task names should be capitalized\ncode/pb_csv_report.yml:90\nTask/Handler: create master csv report\n\n[289] All task names should be capitalized\ncode/pb_csv_report.yml:95\nTask/Handler: insert columns into csv report\n\n[289] All task names should be capitalized\ncode/pb_snmp_config.yml:19\nTask/Handler: Task 1 - ensure snmp commands exist on ios and vmx devices\n\nmake: *** [Makefile:31: ansible-lint] Error 2\n```\n\nTwo of the tasks in `code/pb_csv_report.yml` are missing names so add in something descriptive!\n\nThe repository has a custom rule for `ansible-lint` that asks it to check that task names are all uppercase. It has detected a few instaces where it is not the case, so capitalize the names on the reported line numbers.\n\nOnce all issues are fixed, run the `make ansible-lint` command - if it reports nothing, success!\n\n```\n(venv) .../challenges/codelint/solution (master %) make ansible-lint \nansible-lint -Rr code/custom_rules code/pb.yml\n```\n\n## One final check\n\nTo finish the challenge, run all of the checks again by using the `make all` command. It should not report any issues.\n\n```\n(venv) .../challenges/codelint/solution (master %) make all\nblack --check --diff code\nAll done! ✨ 🍰 ✨\n2 files would be left unchanged.\nflake8 --ignore E501 code\nyamllint -s code/.yml\nansible-lint -Rr code/custom_rules code/pb.yml\n```\n\nCongratulations, you are done!\n\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.6981327533721924, "alphanum_fraction": 0.75, "avg_line_length": 44.904762268066406, "blob_id": "42525f09bb822e51c169510b9e9a849f4efb9896", "content_id": "575723d7891d8dc3a48a52d27f6d862f3d797c2c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 964, "license_type": "no_license", "max_line_length": 127, "num_lines": 21, "path": "/workshops/telemetry-deepdive/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "## Telemetry Workshop\n\n### Day 1 - Prometheus & PromQL\n\n- Lab 01 - [Label Filtering](prometheus_promql/001_label_filtering.md)\n- Lab 02 - [Offset](prometheus_promql/002_offets.md )\n- Lab 03 - [Instant Vector and Range Vector](prometheus_promql/003_instant_range_vectors.md)\n- Lab 04 - [rate, irate and increase](prometheus_promql/004_rate_irate_increase.md)\n- Lab 05 - [deriv, delta](prometheus_promql/005_deriv_delta.md)\n- Lab 06 - [aggregation over time](prometheus_promql/006_aggregration_over_time.md)\n- Lab 07 - [aggregation operators](prometheus_promql/007_aggregation_operators.md)\n- Lab 08 - [Operators](prometheus_promql/008_operator_clauses.md)\n- Lab 09 - [Advanced topics](prometheus_promql/009_advanced_topics.md)\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.7318462133407593, "alphanum_fraction": 0.7534409165382385, "avg_line_length": 52.341773986816406, "blob_id": "3571e374609685bd32062cf9f0ba8d3cea99c1b5", "content_id": "5fa2366cdb5aa5da9823b97d788f142be0c62a43", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 4214, "license_type": "no_license", "max_line_length": 266, "num_lines": 79, "path": "/challenges/08-ansible-extensibility/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Extending Ansible Custom Filters and Modules\n\nThe goal of this exercise is to improve the custom filters and modules developed during the [Extending Ansible Workshop](../../workshops/extending-ansible/).\n\n## Exercise Overview\n\n### Prerequisites\n\nFor the filters tasks 1 and 2, you only need Ansible locally on your machine.\n\nFor the module task 3, you will also need access to a CSR1000v or any other IOS-XE device with the RESTCONF API enabled. The CSR1000v is a virtual machine that can be downloaded from Cisco and is also available as an image in public cloud (e.g. AWS).\n\nIf you have not attended the [Extending Ansible Workshop](../../workshops/extending-ansible/) it is highly recommended you first watch the recording and go through the labs each task refers to!\n\n### Tasks\n\n#### Task 1\n\nIn [Extending Ansible Workshop - Lab 01](../../workshops/extending-ansible/lab01_guide.md) you wrote a filter that expanded interface names from the first two letter abbreviations to a canonical full name (e.g. \"gi\" -> \"GigabitEthernet\")\n\nYou may have noticed that if you provided it a string with a number in it (e.g. \"gi100\"), then it is lost after expansion (e.g. \"GigabitEthernet\" is the result).\n\nImprove the filter code to preserve any interface numbering during this process. Split the interface type (letters only) from the optional numbering that might follow it (digits, symbols) and preserve the latter in the end result.\n\nFor example: \"po100\" -> \"Port-Channel100\" and \"gi0/0/1\" -> \"GigabitEthernet0/0/0\"\n\n> Hint: Use the code and the playbook from the workshop as a starting point, you can find them in the repository next to the lab guide.\n\n#### Task 2\n\nIn [Extending Ansible Workshop - Lab 02](../../workshops/extending-ansible/lab02_guide.md) you wrote a filter that expanded numerical ranges into a list of items.\n\nFor example, `GigabitEthernet1/[1:5]` expands into:\n\n```json\n[\n \"GigabitEthernet1/1\",\n \"GigabitEthernet1/2\",\n \"GigabitEthernet1/3\",\n \"GigabitEthernet1/4\",\n \"GigabitEthernet1/5\"\n]\n```\n\nThis filter only accepts the range spec to be placed at the end of the string: `Eth[1:5]` is valid, but `Eth[1:5]/0` is not.\n\nModify the filter code so that it also works for cases like `Eth[1:5]/0` or `192.168.[1:100].0/24`. You will need to change the filter's regex to accept a third optional group of characters after the range spec and, if present, preserve this in the resulting output.\n\nFeel free to build the new regex online on sites such as [regex101](https://regex101.com/) and test it as shown in the workshop lab (Task 1/Step 4), with the help of the interactive python interpreter.\n\n> Hint: Use the code and the playbook from the workshop as a starting point, you can find them in the repository next to the lab guide.\n\n#### Task 3\n\nIn [Extending Ansible Workshop - Lab 06](../../workshops/extending-ansible/lab06_guide.md) you wrote a custom module that changed (patched) the description of a VRF via the IOS-XE RESTCONF API.\n\nExtend the module code to also perform the following tasks:\n\n1. Make the module idempotent.\n + It should always check if the intended configuration matches the device configuration (hint: send a GET request and compare the attributes).\n + If the VRF is not created, it should fail gracefully, since the PATCH request cannot create the VRF resource, only modify an existing one.\n + If actual configuration changes not are necessary, it should report `ok` (i.e. changed=False) and not send a PATCH request.\n2. Enable `check mode` (i.e. dry-run) support in the module.\n + If the `check mode` flag is present, it should only report whether changes would be made, without performing them. This goes hand in hand with the idempotency code.\n\n> Hint: Use the code and the playbook from the workshop as a starting point, you can find them in the repository next to the lab guide.\n\n### Useful links\n\n- [Ansible Documentation](https://docs.ansible.com)\n- [Regex101](https://regex101.com/)\n\n### Reference Enablement Material\n\n- Extending Ansible Workshop\n- Introduction to REST APIs\n- Network Programming and Automation Course\n\n> Note: Recordings of the relevant sessions can be found online at: https://training.networktocode.com/\n" }, { "alpha_fraction": 0.5997143983840942, "alphanum_fraction": 0.6248725056648254, "avg_line_length": 30.62795639038086, "blob_id": "d4835ddbf7f237c8ee36e2534e2a2f8291de84c2", "content_id": "bc91a9c662fa2c80b53a686a4a90ad51aa78085e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 14769, "license_type": "no_license", "max_line_length": 436, "num_lines": 465, "path": "/workshops/extending-ansible/lab02_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Extending Ansible - Lab 02\n\nIn this lab exercise, you will create a custom filter for Ansible that expands a range specifier to assist in quickly creating lists of things like interfaces and hostnames. \n\nFor example, `Ethernet[10:20]` would expand into the following list:\n\n```py\n[\n \"Ethernet10\",\n \"Ethernet11\",\n \"Ethernet12\",\n \"Ethernet13\",\n \"Ethernet14\",\n \"Ethernet15\",\n \"Ethernet16\",\n \"Ethernet17\",\n \"Ethernet18\",\n \"Ethernet19\",\n \"Ethernet20\"\n]\n```\n\nThis comes in to be extremely helpful when managing large YAML files. For example, think about managing 100s or 1000s of interfaces applying similar configurations to each. This may look familar:\n\n```yaml\nEthernet10:\n speed: 1000\n duplex: full\n access_vlan: 100\nEthernet11:\n speed: 1000\n duplex: full\n access_vlan: 100\nEthernet12:\n speed: 1000\n duplex: full\n access_vlan: 100\nEthernet13:\n speed: 1000\n duplex: full\n access_vlan: 100\n\n```\n\nYou would then have a loop in a Jinja template to consume that data. To simplify the YAML data in conjunction with using a filter in that template, you could represent that data as follows:\n\n```yaml\nEthernet[10:13]:\n speed: 1000\n duplex: full\n access_vlan: 100\n```\n\n\n## Task 1 - Creating the Expand Range Filter\n\nTo start with, you will create a new filter that uses regular expressions to match a specific syntax and then generate the list.\n\n### Step 1\n\nIn your terminal on the lab workstation, change into the `/home/ntc/labs/lab02` folder, creating it if it doesn't exist.\n\n```\nntc@ntc-training:~$ mkdir -p /home/ntc/labs/lab02\nntc@ntc-training:~$ cd /home/ntc/labs/lab02\nntc@ntc-training:lab02$\n```\n\n### Step 2\n\nCreate a folder named `filter_plugins` and in it a file called `expand_range.py`.\n\n```\nntc@ntc-training:lab02$ mkdir filter_plugins\nntc@ntc-training:lab02$ touch filter_plugins/expand_range.py\nntc@ntc-training:lab02$ tree\n.\n└── filter_plugins\n └── expand_range.py\n\n1 directory, 1 file\n```\n\n### Step 3\n\nIn the `expand_range.py` file, add the following initial code. This is the filter scaffolding, creating the `FilterModule` class, the filter bindings, and the actual custom code inside of the `expand_range()` function.\n\nFor now the function does nothing but raise an error. The rest of the code will be added in the following steps.\n\n```py\nimport re\nfrom ansible import errors\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_range\": FilterModule.expand_range,\n }\n\n @staticmethod\n def expand_range(text):\n \"\"\"Expands a range specifier for interface to a list.\"\"\"\n\n # No range provided or no match at all, so raise an error\n raise errors.AnsibleFilterError(\n f\"expand_range filter error: No valid range found in '{text}'!\"\n )\n```\n\n### Step 4\n\nThe first step is to build the regular expression (regex) that will match the desired range spec. To keep thing simple, the pattern should allow for any amount of text, followed by one single range at the end of the string.\n\nFor example, `Ethernet[1:5]` or `192.168.0.[100:110]` are both valid, but `Ethernet[1:5]/10` is not.\n\nThe regex to match is built as follows: `^(\\S+)(\\[\\d+:\\d+\\])$` - first, match one or more non whitespace characters `(\\S+)` as the first group, then match one instance of the range spec for the second group `(\\[\\d+:\\d+\\])`. This is made of `[`, followed by at least one digit, then a `:`, then at least one digit, and finally a `]`. The `^` and `$` tell the regex parser to find exactly this whole pattern from the beginning to the end.\n\nOpen a Python3 interpreter and test it!\n\n```\nntc@ntc-training:lab02$ python3\nPython 3.6.8 (default, Jun 11 2019, 01:16:11)\n[GCC 6.3.0 20170516] on linux\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import re\n>>> re.findall(r\"^(\\S+)(\\[\\d+:\\d+\\])$\", \"Ethernet[1:5]\")\n[('Ethernet', '[1:5]')]\n>>> re.findall(r\"^(\\S+)(\\[\\d+:\\d+\\])$\", \"192.168.0.[100:110]\")\n[('192.168.0.', '[100:110]')]\n>>> re.findall(r\"^(\\S+)(\\[\\d+:\\d+\\])$\", \"Ethernet[1:5]/10\")\n[]\n>>> re.findall(r\"^(\\S+)(\\[\\d+:\\d+\\])$\", \"[1:5]\")\n[]\n```\n\nAs you can see here, there is no match for patterns that are not allowed - the range spec MUST be at the end and there MUST be at least one leading character before the spec.\n\nFeel free to experiment with more values to get a feel for how this works and pay special attention to the data structure returned by `re.findall`!\n\n### Step 5\n\nThe regex from the previous step helpfully splits the input string into two parts: the fixed text and the range spec.\n\nThere's a bit more work to be done on the range spec before you can use it, as right now it is a string like `\"[1:5]\"`. To extract the numbers from it, you may use another regex or just string methods to remove the extra characters as seen below.\n\nExperiment with the following commands in the Python interpreter!\n\n```\n>>> # First strip the [ and ] from the string.\n>>> \"[1:5]\".strip(\"[]\")\n'1:5'\n\n>>> # Then split based on the : character.\n>>> \"[1:5]\".strip(\"[]\").split(\":\")\n['1', '5']\n\n>>> # Assign the resulting strings to the start and stop variables\n>>> start, stop =\"[1:5]\".strip(\"[]\").split(\":\")\n>>> start\n'1'\n>>> stop\n'5'\n\n>>> # Use the range() construct to obtain a list of values\n>>> # Remember: start and stop are strings, so you need to convert them to numbers!\n>>> list(range(int(start), int(stop) + 1))\n[1, 2, 3, 4, 5]\n```\n\n### Step 6\n\nBring it all together in the `expand_range.py` script - the `expand_range()` function should look like the following:\n\n```py\n @staticmethod\n def expand_range(text):\n \"\"\"Expands a range specifier for interface to a list.\"\"\"\n # Look for at least one non-whitespace character for the base\n # followed by a range spec: [x:y] where x and y are integers\n result = re.findall(r\"^(\\S+)(\\[\\d+:\\d+\\])$\", text)\n\n # Check if we have a valid match\n # \"Loopback100[1:3]\" yields [('Loopback100', '[1:3]')]\n # but \"Loopback100\" yields []\n if result:\n # Process the range spec '[1:3]' into start and stop as strings\n start, stop = result[0][1].strip(\"[]\").split(\":\")\n # Generate the expanded list by appending numbers to the\n # base string from the provided range\n base = result[0][0]\n expanded_list = []\n for i in range(int(start), int(stop) + 1):\n expanded_list.append(f\"{base}{i}\")\n\n return expanded_list\n\n # No range provided or no match at all, so raise an error\n raise errors.AnsibleFilterError(\n f\"expand_range filter error: No valid range found in '{text}'!\"\n )\n```\n\nFeel free to refer back to the previous testing you did in the Python interpreter to understand what's going on in there.\n\n### Step 7\n\nStart an interactive Python interpreter session with the `expand_range.py` script and test the new function. Play around with different values!\n\n```\nntc@ntc-training:lab02$ python3 -i filter_plugins/expand_range.py\n>>> FilterModule.expand_range(\"Loopback100[1:3]\")\n['Loopback1001', 'Loopback1002', 'Loopback1003']\n>>>\n>>>\n>>> FilterModule.expand_range(\"Loopback100\")\nTraceback (most recent call last):\n File \"<stdin>\", line 1, in <module>\n File \"filter_plugins/expand_range.py\", line 39, in expand_range\n f\"expand_range filter error: No valid range found in '{text}'!\"\nansible.errors.AnsibleFilterError: expand_range filter error: No valid range found in 'Loopback100'!\n```\n\n> Note: As you can see, if no range is given or the range spec is not at the end, an `AnsibleFilterError` exception will be raised which helps Ansible show a meaningful error message when it executes playbooks.\n\n\n## Task 2 - Using the Expand Range Filter in Ansible\n\nIt's time to use the filter in an Ansible playbook, leveraging it inside Jinja templates to quickly generate and apply configuration.\n\n### Step 1\n\nIn the `/home/ntc/labs/lab02` folder, create the `pb_range.yml` file to actually test the filter from within an Ansible playbook.\n\n```yaml\n---\n\n- name: USING THE EXPAND RANGE FILTER\n hosts: localhost\n gather_facts: false\n\n tasks:\n - debug:\n msg: \"{{ 'GigabitEthernet1/[1:5]' \| expand_range }}\"\n\n - debug:\n msg: \"{{ 'GigabitEthernet100' \| expand_range }}\"\n```\n\n### Step 2\n\nRun the Ansible playbook. As you can see below, it works as expected, expanding the range spec if it finds one, or failing with an error message otherwise.\n\n```\nntc@ntc-training:lab02$ ansible-playbook pb_range.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\n\nPLAY [USING THE EXPAND RANGE FILTER] **************************************************************************\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": [\n \"GigabitEthernet1/1\",\n \"GigabitEthernet1/2\",\n \"GigabitEthernet1/3\",\n \"GigabitEthernet1/4\",\n \"GigabitEthernet1/5\"\n ]\n}\n\nTASK [debug] *************************************************************************************************\nfatal: [localhost]: FAILED! => {\"msg\": \"expand_range filter error: No valid range found in 'GigabitEthernet100'!\"}\n\nPLAY RECAP ***************************************************************************************************\nlocalhost : ok=1 changed=0 unreachable=0 failed=1 skipped=0 rescued=0 ignored=0\n```\n\n### Step 3\n\nCreate a folder named `templates` and in it a file called `range_shutdown.j2`.\n\n```\nntc@ntc-training:lab02$ mkdir templates\nntc@ntc-training:lab02$ touch templates/range_shutdown.j2\nntc@ntc-training:lab02$ tree\n.\n├── filter_plugins\n│ ├── __pycache__\n│ │ └── expand_range.cpython-36.pyc\n│ └── expand_range.py\n├── pb_range.yml\n└── templates\n └── range_shutdown.j2\n\n3 directories, 4 files\n```\n\n### Step 4\n\nEdit the `templates/range_shutdown.j2` file and add the following contents.\n\n```\n{% for name in interface_range \| expand_range %}\ninterface {{ name }}\n shutdown\n{% endfor %}\n```\n\n### Step 5\n\nEdit a new file named `pb_range_template.yml` playbook and define a play that makes use of this Jinja template to generate a file.\n\n```yaml\n---\n\n- name: USING FILTERS IN TEMPLATES\n hosts: localhost\n gather_facts: false\n\n vars:\n interface_range: GigabitEthernet[5:9]\n\n tasks:\n - debug:\n msg: \"{{ interface_range \| expand_range }}\"\n\n - name: GENERATE CONFIG TO SHUTDOWN INTERFACES\n template:\n src: range_shutdown.j2\n dest: range_shutdown.cfg\n```\n\n> Note: This playbook simply generates config that shuts down interfaces, functionality that may already exist in certain CLIs. You may build any type of configuration here, from incrementing IPs, custom descriptions, or using more advanced range patterns that are not available on the CLI.\n\n### Step 6\n\nRun the `pb_range_template.yml` Ansible playbook. Verify the contents of the `range_shutdown.cfg` file.\n\n```\nntc@ntc-training:lab02$ ansible-playbook pb_range_template.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\n\nPLAY [USING FILTERS IN TEMPLATES] ****************************************************************************\n\nTASK [debug] *************************************************************************************************\nok: [localhost] => {\n \"msg\": [\n \"GigabitEthernet5\",\n \"GigabitEthernet6\",\n \"GigabitEthernet7\",\n \"GigabitEthernet8\",\n \"GigabitEthernet9\"\n ]\n}\n\nTASK [GENERATE CONFIG TO SHUTDOWN INTERFACES] ****************************************************************\nchanged: [localhost]\n\nPLAY RECAP ***************************************************************************************************\nlocalhost : ok=2 changed=1 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\n\nntc@ntc-training:lab02$ cat range_shutdown.cfg\ninterface GigabitEthernet5\n shutdown\ninterface GigabitEthernet6\n shutdown\ninterface GigabitEthernet7\n shutdown\ninterface GigabitEthernet8\n shutdown\ninterface GigabitEthernet9\n shutdown\n```\n\n### Step 7\n\nIn the `/home/ntc/labs/lab02` folder, create the `inventory` file and add the following lines to it.\n\n```\n[iosxe]\ncsr[1:3]\n\n[iosxe:vars]\nansible_user=ntc\nansible_password=ntc123\nansible_connection=network_cli\nansible_network_os=ios\n```\n\n### Step 8\n\nIn the `pb_range_template.yml` file, update the `hosts: localhost` line to `hosts: csr3`.\n\n### Step 9\n\nAdd a new task to the playbook to deploy the generated configurations:\n\n```yaml\n - name: APPLY RANGE SHUTDOWN TO DEVICE DIRECTLY\n ios_config:\n src: range_shutdown.j2\n```\n\nThe fully playbook should look like this:\n\n```yaml\n---\n\n- name: USING FILTERS IN TEMPLATES\n hosts: csr3\n gather_facts: false\n\n vars:\n interface_range: GigabitEthernet[5:9]\n\n tasks:\n - debug:\n msg: \"{{ interface_range \| expand_range }}\"\n\n - name: GENERATE CONFIG TO SHUTDOWN INTERFACES\n template:\n src: range_shutdown.j2\n dest: range_shutdown.cfg\n\n - name: APPLY RANGE SHUTDOWN TO DEVICE DIRECTLY\n ios_config:\n src: range_shutdown.j2\n```\n\n\n### Step 10\n\nRun the `pb_range_template.yml` Ansible playbook. It should now connect to the `csr3` router and apply the templated config leveraging your custom range expansion filter!\n\n```\nntc@ntc-training:lab02$ ansible-playbook -i inventory pb_range_template.yml\n\nPLAY [USING FILTERS IN TEMPLATES] ****************************************************************************\n\nTASK [debug] *************************************************************************************************\nok: [csr3] => {\n \"msg\": [\n \"GigabitEthernet5\",\n \"GigabitEthernet6\",\n \"GigabitEthernet7\",\n \"GigabitEthernet8\",\n \"GigabitEthernet9\"\n ]\n}\n\nTASK [GENERATE CONFIG TO SHUTDOWN INTERFACES] ****************************************************************\nchanged: [csr3]\n\nTASK [APPLY RANGE SHUTDOWN TO DEVICE DIRECTLY] ***************************************************************\nchanged: [csr3]\n\nPLAY RECAP ****************************************************************************************************\ncsr3 : ok=3 changed=2 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0\n```\n" }, { "alpha_fraction": 0.6927469968795776, "alphanum_fraction": 0.7431943416595459, "avg_line_length": 30.082839965820312, "blob_id": "b4fb01978eba95819ed4d54b201e5278bbcd4350", "content_id": "14b4e63518ee6c1083401827eb7eb6bee916d56b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 5253, "license_type": "no_license", "max_line_length": 224, "num_lines": 169, "path": "/challenges/05-docker-tools/solution/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge Exercise Solution Guide\n\n## Building a Docker Tools Container\n\nThe goal of this exercise is to build a new Docker container image with a few network automation tools and streamline the process by using either Make or Invoke.\n\n## Solution Walkthrough\n\nFirst, grab the latest docker image for the `python:3` container as instructed.\n\n```\nvagrant ants /vagrant docker pull python:3\n3: Pulling from library/python\nd6ff36c9ec48: Pull complete\nc958d65b3090: Pull complete\nedaf0a6b092f: Pull complete\n80931cf68816: Pull complete\nbc1b8aca3825: Pull complete\nedfe96a4dd20: Pull complete\n4e7c0e94bdeb: Pull complete\n8dffdfc294e3: Pull complete\n036c588c629e: Pull complete\nDigest: sha256:2c1045587e4452d49544c6dce92efe21c3b4b33864cfb56fdee66a2c8585c769\nStatus: Downloaded newer image for python:3\ndocker.io/library/python:3\n\nvagrant ants /vagrant docker image ls\nREPOSITORY TAG IMAGE ID CREATED SIZE\npython 3 79cc46abd78d 2 weeks ago 882MB\n```\n\nThen, test that you can run the container - by default you will get a Python interpreter prompt.\n\n```\nvagrant ants /vagrant docker run -it python:3\nPython 3.8.5 (default, Aug 5 2020, 08:22:02)\n[GCC 8.3.0] on linux\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>>\n```\n\n### Building the container\n\nIn preparation for the build, you need a Dockerfile, which specifies which operations Docker should apply to the base image to arrive at your desired result. Create a file called `Dockerfile` with the following contents.\n\n```Dockerfile\nFROM python:3\nLABEL maintainer=\"Jane Smith\" description=\"Python based tooling\" version=\"0.1\"\n\nCOPY requirements.txt /tmp\n\nRUN pip3 install --no-cache-dir -r /tmp/requirements.txt\nRUN apt-get update && apt-get install -y git tree curl sshpass\n\nCMD [\"/bin/bash\"]\n```\n\nLabels are just text that helps others understand what your container image is about - feel free to modify to suit your use case.\n\nThe Challenge tells you to use a `requirements.txt` file to install python packages, so you first have to copy it from the host into* the container. Then, you pass it to the `pip` command to install all the needed packages.\n\nYou are also instructed to install some other tools, namely `git tree curl sshpass` - first you need to `apt-get update` to fetch up to date information about system packages, then install them.\n\nFinally, as per the instructions, override the starting command of the container so that it is `CMD [\"/bin/bash\"]`. As you have seen earlier, the `python:3` container starts by default a python interpreter, not bash.\n\nThe contents of the requirements file should be as follows:\n\n```\nansible\nnetmiko\nnapalm\nansible-lint\nyamllint\nblack\nnetaddr\njmespath\nrequests\n```\n\nYou can now build the container manually by running the build command.\n\n```\nvagrant ants /vagrant/solution/files docker build -t netdev/tools:0.1 .\nSending build context to Docker daemon 5.12kB\nStep 1/6 : FROM python:3\n ---> 79cc46abd78d\nStep 2/6 : LABEL maintainer=\"Jane Smith\" description=\"Python based tooling\" version=\"0.1\"\n ---> Running in 8381907f4054\nRemoving intermediate container 8381907f4054\n ---> b579972c232e\nStep 3/6 : COPY requirements.txt /tmp\n ---> 358ff7034290\nStep 4/6 : RUN pip3 install --no-cache-dir -r /tmp/requirements.txt\n ---> Running in bf2be560fe99\nCollecting ansible\n Downloading ansible-2.9.12.tar.gz (14.3 MB)\n...\nOUTPUT SNIPPED\n...\nSuccessfully built ad3a33f6cf40\nSuccessfully tagged netdev/tools:0.1\n```\n\nNow run the container and enjoy its functionality!\n\n```\nvagrant ants /vagrant/solution/files docker run -it netdev/tools:0.1\nroot@01efba168042:/# ansible --version\nansible 2.9.12\n config file = None\n configured module search path = ['/root/.ansible/plugins/modules', '/usr/share/ansible/plugins/modules']\n ansible python module location = /usr/local/lib/python3.8/site-packages/ansible\n executable location = /usr/local/bin/ansible\n python version = 3.8.5 (default, Aug 5 2020, 08:22:02) [GCC 8.3.0]\n```\n\n### The Makefile\n\nIncluded below is a Makefile example that uses variables to reduce repetition and help you with versioning and naming of your containers.\n\n```\nNAME = \"netdev/tools\"\nVERSION = \"0.1\"\n\n.PHONY: container run clean-images clean-stopped\ndefault: container\n\n\ncontainer:\n\tdocker build -t $(NAME):$(VERSION) .\n\nrun:\n\tdocker run -it $(NAME):$(VERSION)\n\nclean-images:\n\tdocker image rm -f $(NAME):$(VERSION)\n\nclean-stopped:\n\tdocker container prune -f\n```\n\n### The Invoke tasks file\n\nThe same functionality as exposed in the Makefile is implemented here using Python's Invoke library.\n\nThere's only one gotcha - the `run` function needs to be told to execute its command through a terminal `pty=True` rather than just directly as a process in order for the `docker run -it` command to work interactively.\n\n```\nfrom invoke import task\n\nNAME = \"netdev/tools\"\nVERSION = \"0.1\"\n\n@task\ndef container(context):\n context.run(f\"docker build -t {NAME}:{VERSION} .\")\n\n@task\ndef run(context):\n context.run(f\"docker run -it {NAME}:{VERSION}\", pty=True)\n\n@task\ndef clean_images(context):\n context.run(f\"docker image rm -f {NAME}:{VERSION}\")\n\n@task\ndef clean_stopped(context):\n context.run(f\"docker container prune -f\")\n```\n" }, { "alpha_fraction": 0.5767494440078735, "alphanum_fraction": 0.5801354646682739, "avg_line_length": 30.087718963623047, "blob_id": "68adf14c844499baef15aa9729395ea1c168e122", "content_id": "12c019b4219c47641e3c7885aae91cfda1b76ff7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1772, "license_type": "no_license", "max_line_length": 93, "num_lines": 57, "path": "/workshops/extending-ansible/lab01/filter_plugins/expand_interface_name.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "from ansible import errors\n\nINTERFACE_MAPPING = {\n \"as\": \"Async\",\n \"br\": \"Bridge\",\n \"di\": \"Dialer\",\n \"et\": \"Ethernet\",\n \"fa\": \"FastEthernet\",\n \"fo\": \"FortyGigabitEthernet\",\n \"gi\": \"GigabitEthernet\",\n \"lo\": \"Loopback\",\n \"mg\": \"Mgmt\",\n \"po\": \"Port-Channel\",\n \"se\": \"Serial\",\n \"te\": \"TenGigabitEthernet\",\n \"tu\": \"Tunnel\",\n \"vl\": \"Vlan\",\n \"vx\": \"Vxlan\",\n}\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_interface_name\": FilterModule.expand_interface_name,\n \"expand_interface_names\": FilterModule.expand_interface_names,\n }\n\n @staticmethod\n def expand_interface_name(interface_name):\n \"\"\"Expands abbreviated interface names.\"\"\"\n return INTERFACE_MAPPING.get(\n interface_name.strip().lower()[0:2], interface_name\n )\n\n @staticmethod\n def expand_interface_names(interface_names):\n \"\"\"Expands abbreviated interface names.\"\"\"\n if isinstance(interface_names, str):\n # Same as previously, it's just one interface name\n return INTERFACE_MAPPING.get(\n interface_names.strip().lower()[0:2], interface_names\n )\n elif isinstance(interface_names, list):\n expanded_names = []\n for name in interface_names:\n long_name = INTERFACE_MAPPING.get(name.strip().lower()[0:2], name)\n expanded_names.append(long_name)\n return expanded_names\n else:\n raise errors.AnsibleFilterError(\n \"expand_interface_names filter error: provide a string or a list of strings!\"\n )\n" }, { "alpha_fraction": 0.723809540271759, "alphanum_fraction": 0.7428571581840515, "avg_line_length": 20, "blob_id": "520c17ac1c4e5b76229dbb6c746483d3884a36fa", "content_id": "5872a8bf2f3bf97f70b6515f54ebdb4784d27763", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 105, "license_type": "no_license", "max_line_length": 52, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/nyc-rtr-02.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# nyc-rtr-02.infra.ntc.com\n\nThis Juniper vMX device is located in New York City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6585366129875183, "alphanum_fraction": 0.7317073345184326, "avg_line_length": 15.399999618530273, "blob_id": "a212d7c955365a0bb2de35e608e6e6908bdfb0b3", "content_id": "6d59ec07c2be2de581f844f1cb0e70a1d3afab15", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 82, "license_type": "no_license", "max_line_length": 40, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-MDF-PDU01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-MDF-PDU01\n\nThis APC AP8941 device is located in HQ.\n\nIts status is: Planned.\n" }, { "alpha_fraction": 0.6753384470939636, "alphanum_fraction": 0.7167507410049438, "avg_line_length": 24.80821990966797, "blob_id": "7000d079672deb19811268656ac7c8f77fe62241", "content_id": "90d7fc9ac19ecba8a88cdc8671c0e7d4f2fbceab", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 3767, "license_type": "no_license", "max_line_length": 184, "num_lines": 146, "path": "/workshops/jinja2-deep-dive-day2/lab_guides/lab09_template_inheritance.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 09 - Jinja template inheritance\n\nGoals of this lab:\n\n- Practice building parent and child templates.\n- Practice use of block sections.\n\n## Task 01\n\n> Resources for this task:\n> - [Jinja2 template inheritance](https://jinja2docs.readthedocs.io/en/stable/templates.html#template-inheritance)\n\n### Step 1\n\nCreate directories named `base`, `router--edge` and `router--edge--inet` inside of the `ansible/templates` directory.\n\n```\ncd ansible/templates\nmkdir base\nmkdir router--edge\nmkdir router--edge--inet\n```\n\n### Step 2\n\nCreate a template named `bgp.j2` inside of `base` directory. Copy the below contents into it.\n\n```\nip bgp-community new-format\n{% block community_lists %}\nip community-list standard LEVEL3_HIGH_PRIORITY permit 65001:120\n{% endblock %}\n\nroute-map RM_EDGE_OUT permit 100\n match ip address prefix-list PL_EDGE_OUT\n{% block rm_edge_out %}\n{% endblock %}\nroute-map RM_EDGE_OUT deny 9999\n\nip prefix-list PL_RFC1918 seq 10 permit 10.0.0.0/8\nip prefix-list PL_RFC1918 seq 20 permit 172.16.0.0/12\nip prefix-list PL_RFC1918 seq 30 permit 192.168.0.0/16\n{% block prefix_lists %}\n{% endblock %}\n```\n\n### Step 3\n\nCreate a template named `bgp.j2` inside of `router--edge` directory. Copy the below contents into it.\n\n```\n{% block prefix_lists %}\nip prefix-list PL_EDGE_OUT seq 10 permit 10.50.0.0/24\nip prefix-list PL_EDGE_OUT seq 20 permit 10.60.0.0/24\n{% endblock %}\n```\n\n### Step 4\n\nCreate a template named `bgp.j2` inside of `router--edge--init` directory. Copy the below contents into it.\n\n```\n{% block community_lists %}\n{{ super () }}\nip community-list standard NTT_LOW_PRIORITY permit 65005:75\n{% endblock %}\n\n{% block rm_edge_out %}\nroute-map RM_EDGE_OUT permit 200\n match ip address prefix-list PL_INET_OUT\n{% endblock %}\n\n{% block prefix_lists %}\nip prefix-list PL_INET_OUT seq 10 permit 192.168.254.0/24\n{{ super () }}\n{% endblock %}\n```\n\n### Step 5\n\nTemplates named `bgp.j2` inside of `router--edge` and `router--edge--inet` should rely on the `base/bgp.j2` template. They won't work as they are right now.\n\nAdd Jinja2 expression at the top of the `bgp.j2` templates in `router--edge` and `router--edge--inet` that will extend the base `bgp.j2` template.\n\n### Step 6\n\nAn Ansible playbook was created for you to test these templates.\n\nNavigate to the `ansible` directory and execute the command below:\n\n```\nansible-playbook pb_lab09_task1.yml\n```\n\nIf your additions were correct, a file named `router--edge_bgp.cfg` will be generated in the `output` directory.\n\n### Step 7\n\nModify `pb_lab09_task1.yml` playbook and update the variable `device_role` to `router--edge--inet`.\n\n```\n vars:\n device_role: \"router--edge--inet\"\n```\n\nExecute the command below:\n\n```\nansible-playbook pb_lab09_task1.yml\n```\n\nA file named `router--edge--inet_bgp.cfg` will be generated in the `output` directory.\n\nYou should review both of the generated files as well as all of the templates.\n\nTry to follow the logic involved in inheritance and see how block override is being used.\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should use `{% extends 'parent_template_path' }` expression in unfinished `bgp.j2` templates. This will cause child templates to inherit template elements from the parent template.\n\n```\n{% extends 'base/route_map.j2' %}\n```\n\nYou can now refer to the named blocks from the parent template and override them with content specific to the role using the child template.\n\nE.g.\n```\n{% block prefix_lists %}\nip prefix-list PL_INET_OUT seq 10 permit 192.168.254.0/24\n{% endblock %}\n```\n\nIf you want to keep the block content from the parent template, you should use the `{{ super() }}` statement.\n\nE.g.\n```\n{% block community_lists %}\n{{ super() }}\nip community-list standard NTT_LOW_PRIORITY permit 65005:75\n{% endblock %}\n```\n\n</details>" }, { "alpha_fraction": 0.7443820238113403, "alphanum_fraction": 0.7612359523773193, "avg_line_length": 28.66666603088379, "blob_id": "81c90d6740b11581d19009228eb4e691857a5aaa", "content_id": "7e7d955fc37b12eecab6fc500008e051c4456158", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 356, "license_type": "no_license", "max_line_length": 127, "num_lines": 12, "path": "/challenges/03-jinja2-filters/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Using Ansible Jinja Filters on Network Device Data\n\nSee [PDF](files/Enablement-Challenge-03.pdf) for instructions.\n\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.6935483813285828, "alphanum_fraction": 0.7134724855422974, "avg_line_length": 23.174312591552734, "blob_id": "fc72180015aee0318750bf5fa321e75be28cbaea", "content_id": "d4271dcf90bd3591ba6b1dcd3deaa3443de43c7d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 5282, "license_type": "no_license", "max_line_length": 169, "num_lines": 218, "path": "/workshops/jinja2-deep-dive-day1/lab_guides/lab05_ansible_template.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 05 - Jinja template rendering with Ansible\n\nGoals of this lab:\n\n- Practice using the `template` module for rendering templates.\n- Practice whitespace control when rendering templates with Ansible.\n\n## Task 01\n\n### Step 1\n\nChange into the `ansible` directory and create `output` directory:\n\n```\nmkdir output\n```\n\n### Step 2\n\nCopy the data and template from Lab 01, task 1 into `templates` and `vars` directories, respectively.\n\nYour directories should look like so:\n\n```\ntree vars/\nvars/\n└── lab01-task1.yml\n\ntree templates/\ntemplates/\n└── lab01-task1.j2\n```\n\n### Step 3\n\nCopy the below Ansible Playbook into the file called `pb_template_render.yml` in the `ansible` directory.\n\n```ansible\n---\n- name: \"PLAY 1: TEMPLATE RENDERING\"\n hosts: \"localhost\"\n connection: \"local\"\n gather_facts: false\n\n vars:\n data_file: \"lab01-task1.yml\"\n template_file: \"lab01-task1.j2\"\n dest_file: \"lab01-task1.txt\"\n\n tasks:\n - name: \"TASK 1: LOAD VARIABLES\"\n include_vars:\n file: \"vars/{{ data_file }}\"\n\n - name: \"TASK 2: RENDER TEMPLATE\"\n template:\n src: \"{{ template_file }}\"\n dest: \"output/{{ dest_file }}\"\n\n```\n\n### Step 4\n\nExecute the playbook using the below command:\n\n```ansible-playbook pb_template_render.yml```\n\n### Step 5\n\nInvestigate output file and confirm template rendered correctly.\n\nThis is a simple example of using the Ansible `template` module to render the Jinja template.\n\nAs a minimum `template` expects `src` and `dest` arguments. Source templates are read from the local `templates` directory by default.\n\n\n## Task 02\n\n### Step 1\n\nCreate data file `lab05-task2.yml` in `./vars`. Copy the below content into it:\n\n```yaml\n---\nserver_name: machineLearning-cluster01-ch\n\nalgo: neural_network\n```\n\nCreate template file `lab05-task2.j2` in `./templates`. Copy the below content into it:\n\n```\nMachine Learning cluster: {{ server_name }}\nSelected algorithm: {{ algo }}\nProcessing power: {{ cluster_mflops }}\n```\n\n### Step 2\n\nChange the values of `data_file`, `template_file` and `dest_file` to match the below ones:\n\n```yaml\n vars:\n data_file: \"lab05-task2.yml\"\n template_file: \"lab05-task2.j2\"\n dest_file: \"lab05-task2.txt\"\n```\n\n### Step 3\n\nExecute the playbook using the below command:\n\n```ansible-playbook pb_template_render.yml```\n\nYou should get an error stating that the variable `cluster_mflops` is undefined.\n\nAnsible will raise an error by default when encountering undefined variables.\n\nThis behavior is different from the `jinja2` package in Python where you had to explicitly ask for errors to be raised for undefined variables.\n\n## Task 03\n\n### Step 1\n\nFiles `vars/lab05-task3.yml` and `templates/lab05-task3.j2` were created for you. You can review their contents.\n\n### Step 2\n\nChange the values of `data_file`, `template_file` and `dest_file` in `pb_template_render.yml` to match the below ones:\n\n```yaml\n vars:\n data_file: \"lab05-task3.yml\"\n template_file: \"lab05-task3.j2\"\n dest_file: \"lab05-task3.txt\"\n```\n\n### Step 3\n\nExecute the playbook using the below command:\n\n```ansible-playbook pb_template_render.yml```\n\n### Step 4\n\nInvestigate the output of the rendered template in the `./output` directory.\n\nYou should notice there are no new lines generated by Jinja blocks. There are still however indentation issues resulting from the whitespaces preceding Jinja blocks.\n\nAnsible by default enables the `trim` option that you had to explicitly configure in Python with the `jinja2` package.\n\nHowever, `lstrip_blocks` is set to `False` by default in Ansible, just as is the case with Python `jinja2` package.\n\n## Task 04\n\n### Step 1\n\nAdd the below line to the very top of the `lab05-task3.j2` template:\n\n```\n#jinja2: lstrip_blocks: True\n```\n\n### Step 2\n\nExecute the playbook using the below command:\n\n```ansible-playbook pb_template_render.yml```\n\n### Step 3\n\nInvestigate the output of the rendered template in the `./output` directory.\n\nThe output should not have any extra newlines or spaces. The below directive placed at the top of the template tells Ansible to strip whitespaces preceding Jinja blocks.\n\n```\n#jinja2: lstrip_blocks: True\n```\n\nThe downside of this directive is that you need to include it in each of the templates where you want line stripping to be enforced.\n\n## Task 05\n\n### Task 1\n\nRemove the line at the very top of the `lab05-task3.j2` template that you added in the previous task.\n\n```\n#jinja2: lstrip_blocks: True\n```\n\n### Step 2\n\nAdd `lstrip_blocks: false` argument to the task with `template` module. \n\n```yaml\n - name: \"TASK 2: RENDER TEMPLATE\"\n template:\n src: \"{{ template_file }}\"\n dest: \"output/{{ dest_file }}\"\n lstrip_blocks: true\n```\n\n### Step 3\n\nExecute the playbook using the below command:\n\n```ansible-playbook pb_template_render.yml```\n\n### Step 4\n\nInvestigate the output of the rendered template in the `./output` directory.\n\nThe output of the file should be unchanged compared to the previous task.\n\nYou removed the `lstrip_blocks` directive from the top of the template. Instead, you added the `lstrip_blocks: true` argument at a `template` task level.\n\nThis argument tells the `template` module to remove spaces preceding Jinja blocks. Ansible will apply this behavior to all templates rendered in this task.\n" }, { "alpha_fraction": 0.7346938848495483, "alphanum_fraction": 0.7460984587669373, "avg_line_length": 30.433961868286133, "blob_id": "cf6d720af7e377a00966a3d18c0290afca1e5b4b", "content_id": "0aa531146febc3eff907f290826063097372b177", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1666, "license_type": "no_license", "max_line_length": 249, "num_lines": 53, "path": "/workshops/netbox-extensibility/lab06_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC Netbox Workshop - Lab 06\n\nIn this lab you will be exploring the usage of Custom Fields to extend the data models in Netbox.\n\n> You will receive the IP address of your own Netbox instance together with the credentials from the instructor during the workshop.\n\n## Task 1\n\nThis task creates a new Custom Field for the Circuit/Providers object.\n\n### Step 1\n\nOpen the Netbox web interface at the IP provided and log in.\n\n### Step 2\n\nIn Netbox, to create a new Custom Field, you need to head over to the Netbox Admin panel. Open it now from the top-right user menu.\n\nClick on `Custom fields` under the `Extras` category. This is where you will see a list of your defined custom fields. Note there are some already pre-populated there.\n\n### Step 3\n\nAdd a new `Custom field` with the following parameters:\n\n- Object(s): `circuits > provider`\n- Type: Selection\n- Name: provider_sla\n- Label: SLA\n- Default: Best Effort\n- Custom Field Choices: Gold, Silver, Best Effort\n\n![](images/lab06-1.png)\n\n### Step 4\n\nOnce saved, head over to the Netbox main interface and navigate to the `Circuits -> Providers` section.\n\n### Step 5\n\nSelect the `ATT` provider and edit it, adding a `Best Effort` SLA to the new custom field.\n\n![](images/lab06-2.png)\n\n### Step 6\n\nNavigate back to the main `Circuits -> Providers` page and filter the table for SLA values of `Best Effort` in the Search panel.\n\n![](images/lab06-3.png)\n\n\n## Task 2\n\nAs an optional exploration task, head over to the Admin panel and open the list of all Custom fields. Explore the other defined fields, by identifying which objects they are defined for and searching for the information in the main Netbox interface.\n" }, { "alpha_fraction": 0.6709346771240234, "alphanum_fraction": 0.6877400875091553, "avg_line_length": 30.2450008392334, "blob_id": "8beba22cafefc1e15f391aa6ec434ae6b082211a", "content_id": "1de572294be4885cb41299c254b25c4487d1e7c2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 6248, "license_type": "no_license", "max_line_length": 342, "num_lines": 200, "path": "/workshops/jinja2-deep-dive-day2/lab_guides/lab10_building_lists_and_dicts.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 10 - Building lists and dictionaries in Ansible\n\n## Task 01\n\n> Resources for this task:\n> - [Ansible - Appending to lists and dictionaries](https://ttl255.com/ansible-appending-to-lists-and-dictionaries/)\n\n### Step 1\n\nAn Ansible playbook named `pb_lab10_task1.yml` was created for you in the `ansible` directory.\n\nOpen this playbook now and have a look at the tasks.\n\n### Step 2\n\nThe playbook contains variable definitions and some tasks. You need to modify Task 2.\n\nTask 2 is missing variable definition. The other code in that task is correct. \n\nYou need to add the missing variable definition. The end value held by the variable should be a list of server names containing strings 'DB' or 'WB'.\n\n### Step 3\n\nOnce you finished modifying Task 2, run the playbook with the below command:\n\n```\nansible-playbook pb_lab10_task1.yml\n```\n\nThe output of debugging task, Task 3, should match the below one:\n\n```\nok: [localhost] => {\n \"msg\": [\n \"srvDB01t\",\n \"srvWEB03t\",\n \"srvDB01b\",\n \"srvDB03g\"\n ]\n}\n```\n\n\n<details>\n <summary>Reveal Answer</summary>\n\nAnsible loop iterates over the server names and each item is accessible via a variable called `server_name`.\n\nYou should define a variable named `db_servers`. This variable will be assigned the result of append operation between itself and the current server name in the loop.\n\nThe server name is a string so it needs to be enclosed in square brackets `[]` to make a 1-element list. If you don't do it an error will be raised due to the incompatible types.\n\n```\n - name: \"TASK 2: ADD DB AND WEB SERVERS TO THE LIST\"\n set_fact:\n db_servers: \"{{ db_servers + [server_name] }}\"\n loop: \"{{ servers }}\"\n loop_control:\n loop_var: server_name\n when: \"{{ 'DB' in server_name or 'WEB' in server_name }}\"\n```\n\n</details>\n\n## Task 02\n\n> Resources for this task:\n> - [Ansible - Appending to lists and dictionaries](https://ttl255.com/ansible-appending-to-lists-and-dictionaries/)\n> - [Ansible `combine` filter](https://docs.ansible.com/ansible/latest/user_guide/playbooks_filters.html#combining-hashes-dictionaries)\n\n### Step 1\n\nAn Ansible playbook named `pb_lab10_task2.yml` was created for you in the `ansible` directory.\n\nOpen this playbook now and have a look at the tasks.\n\n### Step 2\n\nThe playbook contains variable definitions and some tasks. You need to modify Task 2.\n\nTask 2 is missing variable definition. The other code in that task is correct. \n\nYou need to add the missing variable definition. The end value held by the variable should be dictionary mapping interface names to default access VLAN assignment. Use VID `10` as the default VLAN assignment.\n\n### Step 3\n\nOnce you finished modifying Task 2, run the playbook with the below command:\n\n```\nansible-playbook pb_lab10_task2.yml\n```\n\nOutput of debugging task, Task 3, should match the below one:\n\n```\nok: [localhost] => {\n \"msg\": {\n \"Ethernet1\": 10,\n \"Ethernet2\": 10,\n \"Ethernet3\": 10,\n \"Ethernet4\": 10,\n \"Ethernet5\": 10,\n \"Ethernet6\": 10,\n \"Ethernet7\": 10\n }\n}\n```\n\n\n<details>\n <summary>Reveal Answer</summary>\n\nAnsible loop iterates over the interface names and each item is accessible via a variable called `intf_name`.\n\nYou should define a variable named `interfaces_w_vlan`. This variable will be assigned value resulting from dictionary merge, using filter `combine`, operation. Values merged is the current value of `interfaces_w_vlan` and key-value pair mapping interface name to VID 10.\n\nYou essentially update the `interfaces_w_vlan` dictionary with one key-value pair at the time.\n\n```\n - name: \"TASK 2: BUILD DICT WITH INTERFACES AND DEFAULT VLAN ASSIGNMENTS\"\n set_fact:\n interfaces_w_vlan: \"{{ interfaces_w_vlan \| combine({intf_name: 10}) }}\"\n loop: \"{{ interfaces }}\"\n loop_control:\n loop_var: intf_name\n```\n\n</details>\n\n## Task 03\n\n> Resources for this task:\n> - [Ansible - Appending to lists and dictionaries](https://ttl255.com/ansible-appending-to-lists-and-dictionaries/)\n\n### Step 1\n\nAn Ansible playbook named `pb_lab10_task3.yml` was created for you in the `ansible` directory.\n\nOpen this playbook now and have a look at the tasks.\n\n### Step 2\n\nThe playbook contains variable definitions and some tasks. You need to modify Task 2.\n\nTask 2 is missing variable definition, other code in that task is correct. \n\nYou need to add the missing variable definition. The end value held by the variable should be a list of dictionaries. Each dictionary should contain two keys, `name` and `role`. Key `name` should contain the name of the switch. Key `role` should contain the value `access-switch` for all of the switches.\n\n### Step 3\n\nOnce you finished modifying Task 2, run the playbook with the below command:\n\n```\nansible-playbook pb_lab10_task3.yml\n```\n\nOutput of debugging task, Task 3, should match the below one:\n\n```\nok: [localhost] => {\n \"msg\": [\n {\n \"name\": \"sw-access-par-01\",\n \"role\": \"access-switch\"\n },\n {\n \"name\": \"sw-access-waw-02\",\n \"role\": \"access-switch\"\n },\n {\n \"name\": \"sw-access-ldn-01\",\n \"role\": \"access-switch\"\n },\n {\n \"name\": \"sw-access-ny-03\",\n \"role\": \"access-switch\"\n }\n ]\n}\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nAnsible loop iterates over the switch names and each item is accessible via a variable called `switch`.\n\nYou should define a variable named `switches_w_role`. This variable will be assigned the result of append operation between itself and a 1-item list containing a dictionary. This dictionary has two keys, `name` and `role`. Key `name` should have the current `switch` as its value. Key `role` has value `access-switch` for all of the switches.\n\nDictionary you define needs to be enclosed in square brackets `[]` to make a 1-element list. If you don't do it an error will be raised due to the incompatible types.\n\n```\n - name: \"TASK 2: BUILD LIST OF DICTS WITH DEVICES AND ROLE ASSIGNMENTS\"\n set_fact:\n switches_w_role: \"{{ switches_w_role + [{'name': switch, 'role': 'access-switch'}] }}\"\n loop: \"{{ switches }}\"\n loop_control:\n loop_var: switch\n```\n\n</details>" }, { "alpha_fraction": 0.7096773982048035, "alphanum_fraction": 0.7634408473968506, "avg_line_length": 17.600000381469727, "blob_id": "d1c78c37410040e2f71308d595ec23b6795861f0", "content_id": "a9f8052e9a5f68dd89168001eb5f4058aa9ee88b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 93, "license_type": "no_license", "max_line_length": 42, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-roadrunner-lsw04/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-roadrunner-lsw04\n\nThis Arista vEOS device is located in DC1.\n\nIts status is: Staged.\n" }, { "alpha_fraction": 0.702208399772644, "alphanum_fraction": 0.7298136353492737, "avg_line_length": 32.69767379760742, "blob_id": "98c9f03e158336430d0a373b4372c680c7319ff0", "content_id": "defff23cf2135a6b1e53c4c3cd824f6a9cdaf6e3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 2898, "license_type": "no_license", "max_line_length": 211, "num_lines": 86, "path": "/workshops/netbox-extensibility/lab01_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC Netbox Workshop - Lab 01\n\nThis is an exploration lab - you will be navigating through the provided Netbox instance and getting familiar with the data populated within.\n\n> You will receive the IP address of your own Netbox instance together with the credentials from the instructor during the workshop.\n\n## Task 1\n\nThis task explores step by step some of the data pre-populated in Netbox.\n\n### Step 1\n\nOpen the Netbox web interface at the IP provided and log in.\n\n![](images/lab01-1.png)\n\n### Step 2\n\nOpen the list of `Sites` - you will find the link in the top menu under the `Organization` tab.\n\n### Step 3\n\nLook at the table of unfiltered results and the search panel on the right. Select from the `Tenant` filter the value `NTC-Prod-Demo` and click `Apply`.\n\n![](images/lab01-2.png)\n\n### Step 4\n\nOpen the `New York City` Site by clicking its name. Look at the various fields for the `Site` object.\n\n### Step 5\n\nUnder the `Stats` tab, click on the blue button labelled `Devices`.\n\n![](images/lab01-3.png)\n\n### Step 6\n\nObserve the URL in your browser bar - `http://NETBOX_IP/dcim/devices/?site=nyc` - it includes a search parameter for the site you were in. The same parameter is also reflected in the `Search` panel on the right.\n\n### Step 7\n\nFilter the list further by restricting the search only to Juniper devices (Hint: `Manufacturer`). You should see three results.\n\n### Step 8\n\nOpen the `nyc-bb-01.infra.ntc.com` Device by clicking on its entry in the search results table. Look at the various fields of the `Device` object.\n\n![](images/lab01-4.png)\n\n### Step 9\n\nScroll down to the Interfaces table and click on `172.18.0.15/24` to open the IP object.\n\n![](images/lab01-5.png)\n\n### Step 10\n\nObserve the URL in your browser bar - `http://NETBOX_IP/ipam/ip-addresses/55/`. Notice the red table reporting this IP address has a duplicate.\n\n### Step 11\n\nIdentify the Parent Prefix and open its page (`172.18.0.0/16`) by clicking the name in the table.\n\n### Step 12\n\nClick the `IP Addresses` tab and observe the URL `http://NETBOX_IP/ipam/prefixes/18/ip-addresses/`\n\n![](images/lab01-6.png)\n\n### Step 13\n\nOn closer inspection, you will notice that the `172.18.0.15/24` IP is defined twice. You may delete the occurence that is NOT assigned to a device's interface.\n\n> Hint: Click the entry in the table to open the IP address object, then select the `Delete` red button top right.\n\n\n## Task 2\n\nUsing similar workflow logic as in `Task 1`, try to perform the following operations on your own:\n\n- Find the `Power Feeds` assigned to Rack `HQ-IDF01-R01`\n- Find the `Devices` that have the role `leaf` and site `DC1`\n- Open `Cables` under the `Devices` menu. Add to the table the `Color` column\n + Hint: Use the `Configure` button, Ctrl-click to select an additional column - ensure you still have all the previous columns visible!\n + Filter the `Cables` that have only the `Black` color.\n" }, { "alpha_fraction": 0.7079482674598694, "alphanum_fraction": 0.7282809615135193, "avg_line_length": 27.5, "blob_id": "dad38bf04146228d1024c32dce236a907f9c8629", "content_id": "622416655ffd0e554ae83df3c3080f5ed7bfed95", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1082, "license_type": "no_license", "max_line_length": 171, "num_lines": 38, "path": "/workshops/telemetry-deepdive/prometheus_promql/004_rate_irate_increase.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# rate(), irate(), increase()\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with the rate() function.\n* Familiarize yourself with the irate() function.\n* Familiarize yourself with the increase() function.\n\n## Exercises\n### Task 1\nReturn the per-second increase of the `interface_in_octets` metric, over a 5 minute range for `interface` `GigabitEthernet0/2`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nrate(interface_in_octets{interface=\"GigabitEthernet0/2\"}[5m])\n```\n</details>\n\n\n### Task 2\nReturn the per-second increase of the `interface_in_octets` metric, over a 5 minute range for `interface` `GigabitEthernet0/2` between the last 2 values of the time range.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nirate(interface_in_octets{interface=\"GigabitEthernet0/2\"}[5m])\n```\n</details>\n\n### Task 3\nReturn the total increase of the `interface_in_octets` metric, over a 5 minute range for `interface` `GigabitEthernet0/2`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nincrease(interface_in_octets{interface=\"GigabitEthernet0/2\"}[5m])\n```\n</details>" }, { "alpha_fraction": 0.7173464894294739, "alphanum_fraction": 0.7334157228469849, "avg_line_length": 29.721519470214844, "blob_id": "3dc261aaad13ed02765cc5ffbedc7cbc6f2260ab", "content_id": "8235d13906a665a2176a3ddfa660660c57a589f9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 2525, "license_type": "no_license", "max_line_length": 249, "num_lines": 79, "path": "/workshops/netbox-extensibility/lab04_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC Netbox Workshop - Lab 04\n\nIn this lab you will be creating your own Custom Links in Netbox.\n\n> You will receive the IP address of your own Netbox instance together with the credentials from the instructor during the workshop.\n\n## Task 1\n\nThis task creates a new button (Custom Link) in the Device page to open an external Github repository with data about that Device.\n\n### Step 1\n\nOpen the Netbox web interface at the IP provided and log in.\n\n### Step 2\n\nIn the same browser, ensure you are logged in to your Github account and confirm you can open the following repository: [https://github.com/networktocode/enablement-program-baxter](https://github.com/networktocode/enablement-program-baxter)\n\n### Step 3\n\nIn the `workshops/netbox-extensibility/devices` subfolder of the [repository](https://github.com/networktocode/enablement-program-baxter/tree/master/workshops/netbox-extensibility/devices) you will notice a folder structure similar to the one below.\n\n```\nworkshops/netbox-extensibility/devices/\n├── DC1-LEAF1\n│ └── README.md\n├── HQ-CORE-SW01\n│ └── README.md\n├── HQ-CORE-SW02\n│ └── README.md\n├── HQ-DC-SW01\n│ └── README.md\n├── HQ-DC-SW02\n│ └── README.md\n├── HQ-IDF01-PDU01\n│ └── README.md\n├── HQ-IDF01-PDU02\n│ └── README.md\n... OUTPUT TRIMMED\n```\n\n### Step 4\n\nBack in Netbox, to create a new Custom Link, you need to head over to the Netbox Admin panel. Open it now from the top-right user menu.\n\nClick on `Custom Links` under the `Extras` category. This is where you will see a list of your defined links once you've created some.\n\n### Step 5\n\nAdd a new Custom Link with the following parameters:\n\n- Content type: `dcim > device`\n- Name: `Open Device Github Repo`\n- Button class: `Success (green)`\n- Tick the `New window` checkbox\n- Link text: `Open Github Repo`\n- URL: `https://github.com/networktocode/enablement-program-baxter/tree/master/workshops/netbox-extensibility/devices/{{ obj.name }}`\n\n### Step 6\n\nYour custom link form should look like the following:\n\n![](images/lab04-1.png)\n\n### Step 7\n\nIn the main Netbox interface, navigate to devices and select one at random. Take note of the brand new green button that is now rendered!\n\n![](images/lab04-2.png)\n\n### Step 8\n\nPush the button! A new browser tab should open with the corresponding Github subfolder for that device.\n\n![](images/lab04-3.png)\n\n### Step 9\n\nFeel free to play around with other devices and inspect the generated links.\n" }, { "alpha_fraction": 0.6967500448226929, "alphanum_fraction": 0.7315875887870789, "avg_line_length": 27.898649215698242, "blob_id": "266804e1e4c7dc51d687c48d61b1901d0caf93ce", "content_id": "48d919d94f100b0a73290ed36bed9e3f66326c5b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 4277, "license_type": "no_license", "max_line_length": 182, "num_lines": 148, "path": "/workshops/jinja2-deep-dive-day2/lab_guides/lab07_jinja_macros.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 07 - Jinja Macros\n\nGoals of this lab:\n\n- Practice writing Jinja macros.\n\n## Task 01\n\n> Resources for this task:\n> - [Jinja2 macros](https://jinja2docs.readthedocs.io/en/stable/templates.html#macros)\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab07-task1.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate a template named `lab07-task1.j2` in `python/templates` dir.\n\nYour template should use data from the `lab07-task1.yml` file to generate output matching the one below.\n\nOutput to match\n```\ninterface Ethernet10\n description Unused port, dedicated to data devices\ninterface Ethernet11\n description Unused port, dedicated to data devices\ninterface Ethernet12\n description Unused port, dedicated to voice devices\ninterface Ethernet24\n description Unused port, dedicated to wap devices\n```\n\nIn your template, you should create a macro named `default_interface_desc` which takes one argument.\n\nUse the `default_interface_desc` macro to generate interface descriptions.\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab07-task1.j2 -d lab07-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should define macro using `{% macro macro_name(arg_name) %}` syntax.\n\nYour macro should take the role of the interface as an argument and return the interface description.\n\nYou then use macro inside `for` loop to generate description for each of the interface. Use syntax `default_interface_desc(<intf_role>)` to execute defined macro.\n\n```\n{% macro default_interface_desc(intf_role) %}\nUnused port, dedicated to {{ intf_role }} devices\n{%- endmacro %}\n{% for intf in interfaces %}\ninterface {{ intf['name'] }}\n description {{ default_interface_desc(intf['role']) }}\n{% endfor %}\n```\n\n</details>\n\n\n## Task 02\n\n> Resources for this task:\n> - [Jinja2 macros](https://jinja2docs.readthedocs.io/en/stable/templates.html#macros)\n> - [Ansible `ipaddr` filter](https://docs.ansible.com/ansible/2.9/user_guide/playbooks_filters_ipaddr.html)\n\n### Step 1\n\nYou will be working with variables defined in the `ansible/vars/lab07-task2.yml` file.\n\nOpen this file now and familiarize yourself with the data.\n\n### Step 2\n\nCreate a template named `lab07-task2.j2` in `ansible/templates` dir.\n\nYour template should use data from the `lab07-task2.yml` file to generate output matching the one below.\n\nOutput to match\n```\nip access-list standard local-interfaces\n permit 10.20.0.240 0.0.0.7\n permit 10.15.62.128 0.0.0.127\n permit 10.39.0.0 0.0.0.255\n permit 10.51.2.0 0.0.1.255\n permit 172.21.0.0 0.0.255.255\n```\n\nYou're building a standard ACL and want to include all of the networks defined on your IP interfaces.\n\nYou need to write a macro named `ip_w_wildcard` which takes one argument.\n\nYour macro should take IP address with prefix length and return network address in the \n`{network} {wildcard}` format. E.g.\n\nFor the below input:\n\n`172.16.0.1/24`\n\nThe macro should generate the below output:\n\n`172.16.0.0 0.0.0.255`\n\n> HINT: You should use Ansible filter to perform IP address conversion. Use `hostmask` argument to get wildcard.\n\n### Step 3\n\nChange into `ansible` directory.\n\nRun the below command to test your template.\n\n```\nansible-playbook pb_lab07_task2.yml\n```\n\nThe output of the rendering will be saved in the `output/lab07-task2.txt` file.\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should define macro using `{% macro ip_w_wildcard(arg_name) %}` syntax.\n\nYour macro should take IP address in the `{ip}/{pfx length}` format and return IP network in the `{network} {wildcard}` format.\n\nTo achieve that, you should use Ansible `ipaddr` filter. To get network part use `ipaddr('network')` and to get wildcard part use `ipaddr('hostmask')`\n\nYou should use the `map` filter to get IP addresses only from the list of interface objects. Then you should loop over the IPs and apply the `ip_w_wildcard` macro to each of the IPs.\n\n```\n{% macro ip_w_wildcard(ip_network) %}\n{{ ip_network \| ipaddr('network') }} {{ ip_network \| ipaddr('hostmask')}}\n{%- endmacro -%}\n\nip access-list standard {{ in_std_acl_name }}\n{% for ip_address in interfaces \| map(attribute='ipv4_address') %}\n permit {{ ip_w_wildcard(ip_address) }}\n{% endfor %}\n```\n</details>\n" }, { "alpha_fraction": 0.6363636255264282, "alphanum_fraction": 0.7386363744735718, "avg_line_length": 16.600000381469727, "blob_id": "b91a7d65484e06fd3956d4890599e32b71e55a69", "content_id": "48450c2bebbf23811acc640a3620aa76354b75fc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 88, "license_type": "no_license", "max_line_length": 47, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-CORE-SW01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-CORE-SW01\n\nThis Cisco C9500-48Y4C device is located in HQ.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7096773982048035, "alphanum_fraction": 0.7634408473968506, "avg_line_length": 17.600000381469727, "blob_id": "5abcfae42299d4d2cb69035e1ca5e53954528685", "content_id": "fe60d1928464581408228514d8ce3c2287f6d15a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 93, "license_type": "no_license", "max_line_length": 42, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-roadrunner-lsw02/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-roadrunner-lsw02\n\nThis Arista vEOS device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7071742415428162, "alphanum_fraction": 0.7452415823936462, "avg_line_length": 39.17647171020508, "blob_id": "967d2c4b1928818b4cc77ff923b0a041d403d0f5", "content_id": "eb5aeec10389b1660877586769fed907589b9534", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 683, "license_type": "no_license", "max_line_length": 127, "num_lines": 17, "path": "/workshops/jinja2-deep-dive-day2/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "## Jinja2 Deep-Dive Workshop\n\n### Day 2 - Jinja advanced topics\n\n- Lab 06 - [Jinja filters](lab_guides/lab06_jinja_filters.md)\n- Lab 07 - [Jinja macros](lab_guides/lab07_jinja_macros.md)\n- Lab 08 - [Jinja include and import](lab_guides/lab08_include_import.md)\n- Lab 09 - [Jinja template inheritance](lab_guides/lab09_template_inheritance.md)\n- Lab 10 - [Building lists and dictionaries in Ansible](lab_guides/lab10_building_lists_and_dicts.md)\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2021, Network to Code, LLC.\n" }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "d02889ce93307df280ebd67f7d36584a4b6a90e5", "content_id": "1e25b9fe0e4d901af55f8477c4c529ab58794ab3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx20/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx20\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Staged.\n" }, { "alpha_fraction": 0.7176195979118347, "alphanum_fraction": 0.7269545197486877, "avg_line_length": 30.77777862548828, "blob_id": "df0b82f1ba7b1474c91720e5bd2ff9c42bf15374", "content_id": "d38216c0b9948df40c85bda62b91f526a59e7c74", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 857, "license_type": "no_license", "max_line_length": 162, "num_lines": 27, "path": "/workshops/telemetry-deepdive/prometheus_promql/009_advanced_topics.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Advanced Topics\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with the aggregation over time quantile based functions.\n* Familiarize yourself with the standard deviation operator.\n\n\n## Exercises\n### Task 1\nCalulate the top 5% `dns_query_query_time_ms` times (highest ms) for the `site`=`lessines` and the `sensor_name`=`google_public_dns_a` over a 5 minute time range.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nquantile_over_time(0.95, dns_query_query_time_ms{site=\"lessines\",sensor_name=\"google_public_dns_a\"}[5m])\n```\n</details>\n\n### Task 2\nCalculate the standard deviation of `dns_query_query_time_ms` across all devices within the site `lessines` and the sensor_name `one.one.one.one`. \n<details>\n <summary>Reveal Answer</summary>\n \n```\nstddev(dns_query_query_time_ms{site=\"lessines\", sensor=\"one.one.one.one\"})\n```\n</details>" }, { "alpha_fraction": 0.7446808218955994, "alphanum_fraction": 0.759878396987915, "avg_line_length": 20.225807189941406, "blob_id": "efb551cb9fc69adb3f13f23f6df12bb3db7d433b", "content_id": "0057d24b99b2a64be7a4e5c04bd45a4f0a2c0b40", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Makefile", "length_bytes": 658, "license_type": "no_license", "max_line_length": 64, "num_lines": 31, "path": "/challenges/04-codelint/files/Makefile", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": ".PHONY: black flake8 yamllint ansible-lint\n\ndefault:\n\techo \"Please choose a task: black flake8 yamllint ansible-lint\"\n\n# Set up the virtual environment with dependencies\nvenv: venv/bin/activate\n\nvenv/bin/activate: requirements.txt\n\ttest -d venv \|\| python3 -m venv venv\n\t. venv/bin/activate; pip3 install -Ur requirements.txt\n\ttouch venv/bin/activate\n\n# The testing targets\n\nall: black flake8 yamllint ansible-lint\n\n# Lint and format Python files\nblack:\n\tblack --check --diff code\n\nflake8:\n\tflake8 --ignore E501 code\n\n# Lint YAML files\nyamllint:\n\tyamllint -s code/.yml\n\n# Lint Ansible Playbooks\nansible-lint:\n\tansible-lint -Rr code/custom_rules code/pb.yml\n" }, { "alpha_fraction": 0.6863710880279541, "alphanum_fraction": 0.7323480844497681, "avg_line_length": 34.82352828979492, "blob_id": "310a7a406c349caa70265c18acbe4bb2762c1464", "content_id": "dbe84a25f2d9f0f57b0fc99b4b1c7008034ad20d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 609, "license_type": "no_license", "max_line_length": 127, "num_lines": 17, "path": "/workshops/netbox-extensibility/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "## Netbox Extensibility Workshop\n\n- Lab 01 - [Explore the Netbox UI](lab01_guide.md)\n- Lab 02 - [Using Netbox Reports and Custom Scripts](lab02_guide.md)\n- Lab 03 - [Creating Export Templates in Netbox](lab03_guide.md)\n- Lab 04 - [Creating Custom Links](lab04_guide.md)\n- Lab 05 - [Implementing Webhooks](lab05_guide.md)\n- Lab 06 - [Using Custom Fields](lab06_guide.md)\n\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.698113203048706, "alphanum_fraction": 0.7547169923782349, "avg_line_length": 20.200000762939453, "blob_id": "931c593fa980a8791ce6926818cdb268b8620202", "content_id": "0ce792e52d88184cd55c40821674abe78ce16c39", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 106, "license_type": "no_license", "max_line_length": 53, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/jcy-rtr-01.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# jcy-rtr-01.infra.ntc.com\n\nThis Cisco CSR1000V device is located in Jersey City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7247706651687622, "alphanum_fraction": 0.752293586730957, "avg_line_length": 20.799999237060547, "blob_id": "db18be0160d34d6997d63b9a3f66300ea18c34d5", "content_id": "6bd5c1bd5623efb580c6985cfb16915b2e3b19d1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 109, "license_type": "no_license", "max_line_length": 54, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/jcy-spine-02.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# jcy-spine-02.infra.ntc.com\n\nThis Cisco Nexus 9Kv device is located in Jersey City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7096773982048035, "alphanum_fraction": 0.7634408473968506, "avg_line_length": 17.600000381469727, "blob_id": "0ac84320e5a10f091301a92e1807a5e92693f020", "content_id": "7771153cfe3eee770183a5b12fae15c55f27eac9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 93, "license_type": "no_license", "max_line_length": 42, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-roadrunner-lsw01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-roadrunner-lsw01\n\nThis Arista vEOS device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7237353920936584, "alphanum_fraction": 0.7392995953559875, "avg_line_length": 27.55555534362793, "blob_id": "3d11b710c932b27ad035367eb1b93822a41eb444", "content_id": "6ca4aee6112ef7a6bdfc185f99ddc7139f84efea", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Dockerfile", "length_bytes": 257, "license_type": "no_license", "max_line_length": 74, "num_lines": 9, "path": "/challenges/05-docker-tools/solution/files/Dockerfile", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "FROM python:3\nLABEL maintainer=\"Jane Smith\" description=\"Python based tooling\" version=\"0.1\"\n\nCOPY requirements.txt /tmp\n\nRUN pip3 install --no-cache-dir -r /tmp/requirements.txt\nRUN apt-get update && apt-get install -y git tree curl sshpass\n\nCMD [\"/bin/bash\"]\n" }, { "alpha_fraction": 0.6704915761947632, "alphanum_fraction": 0.7073965072631836, "avg_line_length": 19.669872283935547, "blob_id": "3efaeffdf77c8f08e9715321ed6f3237725f3c97", "content_id": "6e1143fe774124fe8e0e053689da6260fce74268", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 6449, "license_type": "no_license", "max_line_length": 299, "num_lines": 312, "path": "/workshops/netbox-extensibility/lab03_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC Netbox Workshop - Lab 03\n\nIn this lab you will be creating your own custom Export Templates in Netbox.\n\n> You will receive the IP address of your own Netbox instance together with the credentials from the instructor during the workshop.\n\n## Task 1\n\nThis task creates an exportable text report that counts the number of devices per site.\n\n### Step 1\n\nOpen the Netbox web interface at the IP provided and log in.\n\n### Step 2\n\nTo create a new Export Template, you need to head over to the Netbox Admin panel. Open it now from the top-right user menu.\n\n![](images/lab03-1.png)\n\n### Step 3\n\nClick on the `Export Templates` link under the `Extras` category. This is where you will see a list of your defined templates once you've created some.\n\n### Step 4\n\nClick on the `ADD EXPORT TEMPLATE` button on the right-hand side of the page.\n\n### Step 5\n\nFill in the form as follows:\n\n- From the `Content type` drop-down, select `dcim > site`.\n- In the `Name` field input `Count Devices Per Site`.\n- Optionally, add a description if you wish.\n- Set the `File extension` field to `txt`\n- Leave the `Template language` to `Jinja2`\n\n> You're leaving the MIME type field to its default since the output will be plain text.\n\n### Step 6\n\nIn the `Template code` field add the following:\n\n```\n{% for site in queryset %}\n{{ site.name }}: {{ site.devices.count() }} devices.\n{% endfor %}\n```\n\n### Step 7\n\nDouble check that everything looks like the screenshot below and click the `SAVE` button at the bottom of the page.\n\n![](images/lab03-2.png)\n\n### Step 8\n\nOpen your main Netbox page in a separate browser tab and navigate to the `Sites` page (hint: it's under the `Organization` top menu).\n\n### Step 9\n\nNotice that the `Export` button has now turned into a drop-down. Click it and select the new addition, your export template `Count Devices Per Site`.\n\n![](images/lab03-3.png)\n\n### Step 10\n\nNetbox will offer you a file to download which is your custom export result. Save it on your disk and open it in a text editor - it will have the following contents.\n\n```\n\nDC1: 29 devices.\n\nDM/Buffalo: 0 devices.\n\nDM/Corporate: 0 devices.\n\nDM/Scranton: 0 devices.\n\nHQ: 12 devices.\n\nJersey City: 5 devices.\n\nLAX: 2 devices.\n\nNew York City: 7 devices.\n\nSite-1: 0 devices.\n\nSite-2: 0 devices.\n\nStrickland East: 0 devices.\n\nStrickland North: 0 devices.\n\nStrickland South: 0 devices.\n\nStrickland West: 0 devices.\n```\n\n### Step 11\n\nThe information in the export is great, but it has a bit too much whitespace in it. Let's fix that.\n\nHead back to the Admin panel browser tab (or open a new one) and click the export template `Count Devices Per Site` to edit it.\n\nUpdate the `Template code` with the following (there's a `-` added to the closing bracket of the for loop telling Jinja2 to trim the newline there):\n\n```\n{% for site in queryset -%}\n{{ site.name }}: {{ site.devices.count() }} devices.\n{% endfor %}\n```\n\n### Step 12\n\nBack in the main Netbox Sites page, export again and compare the result:\n\n```\nDC1: 29 devices.\nDM/Buffalo: 0 devices.\nDM/Corporate: 0 devices.\nDM/Scranton: 0 devices.\nHQ: 12 devices.\nJersey City: 5 devices.\nLAX: 2 devices.\nNew York City: 7 devices.\nSite-1: 0 devices.\nSite-2: 0 devices.\nStrickland East: 0 devices.\nStrickland North: 0 devices.\nStrickland South: 0 devices.\nStrickland West: 0 devices.\n```\n\n\n## Task 2\n\nThis task creates an exportable custom csv with IP prefix data.\n\n### Step 1\n\nIn the Netbox Admin panel, create a new Export template as follows:\n\nFill in the form as follows:\n\n- From the `Content type` drop-down, select `ipam > prefix`.\n- In the `Name` field input `Custom Prefix CSV`.\n- In the `Description` field input `Includes Site, Created Date, Role and Size.`\n- Set the `File extension` field to `csv`\n- Leave the `Template language` to `Jinja2`\n\n### Step 2\n\nIn the `Template code` field add the following:\n\n```\nprefix,site,allocated,role,size\n{% for p in queryset -%}\n {{ p.prefix }},\n {{- p.site }},\n {{- p.created.isoformat() }},\n {{- p.role }},\n {{- p.prefix.size }}\n{% endfor %}\n```\n\n> Take note of the CSV header that is simply text and then a loop over all prefixes, pulling custom data. While the template is multiline, the csv output should be one line per prefix - therefore we're using Jinja2 whitespace management to remove all the extra newlines from the output.\n\n### Step 3\n\nHead over to the `IPAM->Prefixes` page in the main Netbox interface browser tab. Perform a search to display only prefixes that belong to Site `HQ`.\n\n> The export function always takes the results from the table displayed in front of you with whatever filters are active at the time.\n\n### Step 4\n\nNow export using your custom template `Custom Prefix CSV`. The file should be called `netbox_prefixes.csv` and have the following content:\n\n```\nprefix,site,allocated,role,size\n10.40.0.0/24,HQ,2020-01-16,Enterprise Access,256\n10.63.10.0/24,HQ,2020-01-16,Enterprise Access,256\n10.63.20.0/24,HQ,2020-01-16,Enterprise Access,256\n10.63.30.0/24,HQ,2020-01-16,Enterprise Access,256\n```\n\n> If you have more than 4 prefixes, check back that you have filtered to show only the prefixes belonging to Site `HQ` before exporting.\n\n\n## Task 3\n\nOptional Challenge!\n\nYour colleague doesn't like CSV too much and asked you to export the same data from the `Task 2` `Custom Prefix CSV` template in a YAML format. Remember, YAML is still just text (conforming to a different syntax), so you will have to reshuffle the existing information around in the Jinja2 template.\n\nStarting from the template in `Task 2`, create a new export template named `Custom Prefix YAML`, so the resulting export looks like the following:\n\n```\n\n- prefix: 10.40.0.0/24\n site: HQ\n created: 2020-01-16\n role: Enterprise Access\n size: 256\n\n- prefix: 10.63.10.0/24\n site: HQ\n created: 2020-01-16\n role: Enterprise Access\n size: 256\n\n- prefix: 10.63.20.0/24\n site: HQ\n created: 2020-01-16\n role: Enterprise Access\n size: 256\n\n- prefix: 10.63.30.0/24\n site: HQ\n created: 2020-01-16\n role: Enterprise Access\n size: 256\n```\n\n\n### SOLUTION BELOW - SCROLL ONCE YOU'RE DONE TO COMPARE\n\n\n```\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n```\n\nThis is how the Jinja2 template code should look like:\n\n```\n# Custom Prefix YAML\n# Includes Site, Created Date, Role and Size.\n# yml\n{% for p in queryset %}\n- prefix: {{ p.prefix }}\n site: {{ p.site }}\n created: {{ p.created.isoformat() }}\n role: {{ p.role }}\n size: {{ p.prefix.size }}\n{% endfor %}\n```\n" }, { "alpha_fraction": 0.6263736486434937, "alphanum_fraction": 0.7362637519836426, "avg_line_length": 17.200000762939453, "blob_id": "ceaa25d0f1d6b74c9912d3d9d6bd98ccebdebbe7", "content_id": "579b47ffa8f3dcce659435998071fce6d76f5908", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 91, "license_type": "no_license", "max_line_length": 48, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-IDF01-SW01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-IDF01-SW01\n\nThis Cisco WS-C3850-48U device is located in HQ.\n\nIts status is: Planned.\n" }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "35bb959b230b4961af59447650bab26648b38fbe", "content_id": "85fb2f1c0df3ed882ce4d4ab87e2bf1b22387b51", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx04/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx04\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.741830050945282, "alphanum_fraction": 0.7549019455909729, "avg_line_length": 24.5, "blob_id": "8b7026cc118f225ed50741c96dccad7b15c6e114", "content_id": "1239f7022328b7e93c0bd9cd885e8999fddfd786", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 306, "license_type": "no_license", "max_line_length": 127, "num_lines": 12, "path": "/challenges/04-codelint/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Code Linting & Formatting Challenge\n\nSee email for instructions.\n\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n" }, { "alpha_fraction": 0.7264150977134705, "alphanum_fraction": 0.7452830076217651, "avg_line_length": 20.200000762939453, "blob_id": "06b12c6b3c7bc2cb0dc69a76c385750257a65b91", "content_id": "1c6eb31c17dcce2b4a813cba8a194957211d11ca", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 106, "license_type": "no_license", "max_line_length": 52, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/nyc-leaf-01.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# nyc-leaf-01.infra.ntc.com\n\nThis Arista vEOS device is located in New York City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.8055555820465088, "alphanum_fraction": 0.8333333134651184, "avg_line_length": 6.199999809265137, "blob_id": "442fdf3baf78fe1173fbae33ccb8317fb0f6ca76", "content_id": "3b24212557013bec58de102d9467c6fb311e7918", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 36, "license_type": "no_license", "max_line_length": 12, "num_lines": 5, "path": "/challenges/04-codelint/files/requirements.txt", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "black\nflake8\n\nyamllint\nansible-lint\n" }, { "alpha_fraction": 0.621052622795105, "alphanum_fraction": 0.7473683953285217, "avg_line_length": 18, "blob_id": "fedccc74fdb4fd263fe158250b84cbf80176757d", "content_id": "8cb3a4e88371e11101545d2495eda913c54fbcfb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 95, "license_type": "no_license", "max_line_length": 50, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-acme-lsw01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-acme-lsw01\n\nThis Cisco 93180YC-FX-24 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7174887657165527, "alphanum_fraction": 0.7269556522369385, "avg_line_length": 32.173553466796875, "blob_id": "1b6a83df6243721361b518be598d9a49f2002f39", "content_id": "9d9a9ca26f830048809cfdd365ea1080efa4329b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 4014, "license_type": "no_license", "max_line_length": 230, "num_lines": 121, "path": "/workshops/netbox-extensibility/lab05_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC Netbox Workshop - Lab 05\n\nIn this lab you will be creating Webhooks in Netbox to send notifications to a Slack channel when Create/Update/Delete (CRUD) operations are performed in Netbox.\n\n> You will receive the IP address of your own Netbox instance together with the credentials from the instructor during the workshop.\n\n> The webhook URL for the lab will also be provided during the session.\n\n## Task 1\n\nThis task creates a new webhook for the Device objects, so that a very simple message is sent to a Slack channel when any CRUD operations are performed.\n\n### Step 1\n\nOpen the Netbox web interface at the IP provided and log in.\n\n### Step 2\n\nIn Netbox, to create a new Webhook, you need to head over to the Netbox Admin panel. Open it now from the top-right user menu.\n\nClick on `Webhooks` under the `Extras` category. This is where you will see a list of your defined webhooks once you've created some.\n\n### Step 3\n\nAdd a new Webhook with the following parameters:\n\n- Name: `Slack-CRUD`\n- Object types: `dcim > device`\n- Enabled: checked.\n- Events: select all three types (Create, Update, Delete)\n- URL: ASK YOUR INSTRUCTOR!!!\n- HTTP method: POST\n- HTTP content type: application/json\n- Leave SSL verification as it is.\n\nThe Body template should be the following JSON text - replace MY_FIRST_NAME with your name!!!\n\n```json\n{\n \"text\": \"MY_FIRST_NAME's Netbox: Device {{data.name}} was {{event}} by {{username}}.\",\n}\n```\n\n### Step 5\n\nYour webhook form should look like the following:\n\n![](images/lab05-1.png)\n\n### Step 6\n\nIn the main Netbox interface, navigate to a device and `Edit` it. Make a change to a field like `Serial Number` and save it.\n\n### Step 7\n\nYour instructor will be sharing their Slack window and you should be able to see a new message pop up:\n\n```\nIncoming Webhook APP 11:05 AM\nMY_FIRST_NAME's Netbox: Device HQ-DC-SW01 was updated by ntc.\n```\n\n![](images/lab05-2.png)\n\nFeel free to Create (or Clone), Update and Delete devices to see how this looks!\n\n> Make sure you replaced MY_FIRST_NAME with your actual name in the webhook body so you can easily identify your messages in the Slack channel.\n\n\n## Task 2\n\nThis task updates the `Slack-CRUD` webhook to include more information such as a filtered link to the changelog.\n\n### Step 1\n\nUpdate the `Slack-CRUD` webhook `Body template` with the following - replace MY_FIRST_NAME with your name again and MY_NETBOX_IP with your Netbox IP!!!:\n\n```json\n{\n \"text\": \"{% if event=='deleted' %}:rotating_light:{% endif %} MY_FIRST_NAME's Netbox: Device {{data.name}} was {{event}} by {{username}}.\\nHere's the changelog: http://MY_NETBOX_IP/extras/changelog/?request_id={{request_id}}\",\n}\n```\n\nLet's disect it (the JSON text has to be a one-liner which makes it a bit harder to read) - remember we are using Jinja2 to make some decisions and plug in dynamic data!\n\nSince it's 2020, it's mandatory to include an emoji with the message - so you will add a red siren light emoji when the event is a deletion.\n\n```\n{% if event=='deleted' %}:rotating_light:{% endif %}\n```\n\nThe simple message from earlier. Have you replaced `MY_FIRST_NAME` with your name?\n\n```\nMY_FIRST_NAME's Netbox: Device {{data.name}} was {{event}} by {{username}}.\n```\n\nAnd finally, the coolest part - a dynamic link to the Changelog that shows exactly what happened! Remember to replace `MY_NETBOX_IP` with your actual Netbox IP or the link won't work!\n\n```\n\\nHere's the changelog: http://MY_NETBOX_IP/extras/changelog/?request_id={{request_id}}\n```\nIt starts with a `\\n` since we want the link to be displayed on a separate line.\n\n### Step 2\n\nTest your new and improved webhook! Make another edit to a device.\n\n![](images/lab05-3.png)\n\n### Step 3\n\nIf your message contains your name and a valid Netbox link, your instructor will paste it back into the Zoom chat for you.\n\nIf not, check back with `Step 1` to ensure everything is in place.\n\n### Step 4\n\nDelete a device that you have created. A suitably urgent message should appear in Slack.\n\n![](images/lab05-4.png)\n" }, { "alpha_fraction": 0.625, "alphanum_fraction": 0.7272727489471436, "avg_line_length": 16.600000381469727, "blob_id": "fcbc612e1b670a2e851cf58df8279e90a9035ea0", "content_id": "517cc6d7fc51d2542a8bd7daf42d8f43ea21390f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 88, "license_type": "no_license", "max_line_length": 49, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-DC-SW02/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-DC-SW02\n\nThis Cisco 93180YC-FX-24 device is located in HQ.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7413294911384583, "alphanum_fraction": 0.7442196607589722, "avg_line_length": 24.66666603088379, "blob_id": "b3b945a4791192b0e86a390ed78b339a4fe5ea70", "content_id": "638dbe822de21929181a35c9c831ec785a9c5084", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 692, "license_type": "no_license", "max_line_length": 117, "num_lines": 27, "path": "/workshops/telemetry-deepdive/prometheus_promql/007_aggregation_operators.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Aggregation Operators\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with the sum() aggregation operator.\n* Familiarize yourself with the count() aggregation operator.\n\n## Exercises\n### Task 1\nCalculate the total number of `asa_anyconnect_client_active` sessions across all devices within the `frankfurt` site.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nsum(asa_anyconnect_client_active{site=\"frankfurt\"})\n```\n</details>\n\n\n### Task 2\nCalculate the total number of devices within the `frankfurt` site using the metric `asa_anyconnect_client_active`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\ncount(asa_anyconnect_client_active{site=\"frankfurt\"})\n```\n</details>" }, { "alpha_fraction": 0.6969178318977356, "alphanum_fraction": 0.7003424763679504, "avg_line_length": 21.5, "blob_id": "29cb278d64ec659b09a0bee7b64531a929877a75", "content_id": "0bfdadc2d063cc11fb0fa5402a6b4e92e6675549", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 584, "license_type": "no_license", "max_line_length": 93, "num_lines": 26, "path": "/workshops/telemetry-deepdive/prometheus_promql/008_operator_clauses.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Operator Clauses\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with the by() and without() operator clauses.\n\n\n## Exercises\n### Task 1\nCalculate the average `dns_query_query_time_ms` by including the tags `host` and `server`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\navg by (host, server) (dns_query_query_time_ms)\n```\n</details>\n\n### Task 2\nCalculate the maximum `dns_query_query_time_ms` by excluding the tags `db` and `environment`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\navg without (db, environment) (dns_query_query_time_ms)\n```\n</details>" }, { "alpha_fraction": 0.6830015182495117, "alphanum_fraction": 0.7166922092437744, "avg_line_length": 24.153846740722656, "blob_id": "92624403df66b3a8041756b25419138f89efe581", "content_id": "3276b573da948c16989d4388ac090925190411e3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 653, "license_type": "no_license", "max_line_length": 129, "num_lines": 26, "path": "/workshops/telemetry-deepdive/prometheus_promql/005_deriv_delta.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# deriv(), delta()\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with the deriv() function.\n* Familiarize yourself with the delta() function.\n\n## Exercises\n### Task 1\nCalculate how `disk_used` is evolving per second for all disk paths on `host` `deftlnetops200` averaged over the last 10 minutes.\n<details>\n <summary>Reveal Answer</summary>\n\n```\nderiv(disk_used{host=\"deftlnetops200\"}[10m])\n```\n</details>\n\n### Task 2 \nCalculate the difference in `disk_used` for all disk paths on `host` `deftlnetops200` over a 15 minute period.\n<details>\n <summary>Reveal Answer</summary>\n\n```\ndelta(disk_used{host=\"deftlnetops200\"}[15m])\n```\n</details>" }, { "alpha_fraction": 0.625, "alphanum_fraction": 0.7272727489471436, "avg_line_length": 16.600000381469727, "blob_id": "2f3f4fa1fe18a4922f1e2c6531beb009232cf26f", "content_id": "788f7d2f06538f1d5f89e763165056059e32fff9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 88, "license_type": "no_license", "max_line_length": 49, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-DC-SW01/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-DC-SW01\n\nThis Cisco 93180YC-FX-24 device is located in HQ.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.6736934781074524, "alphanum_fraction": 0.722815990447998, "avg_line_length": 29.177515029907227, "blob_id": "342b450e0761dff6064af1563cef8f83e5dcdd48", "content_id": "b41f70d4a2bb3cdc53136c33d7cf78f0e8200160", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 10199, "license_type": "no_license", "max_line_length": 247, "num_lines": 338, "path": "/workshops/jinja2-deep-dive-day2/lab_guides/lab08_include_import.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 08 - Jinja `include` and `import` statements\n\nGoals of this lab:\n\n- Practice using include statement.\n- Practice using import statement.\n\n## Task 01\n\n> Resources for this task:\n> - [Jinja2 include](https://jinja2docs.readthedocs.io/en/stable/templates.html#include)\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab08-task1.yml` file and the initial template defined in the `python/vars/lab08-task1-init.j2` file.\n\nYou can open these to familiarize yourself with their contents.\n\n### Step 2\n\nSplit the template from the `python/vars/lab08-task1-init.j2` file into multiple smaller templates each rendering section of the initial template.\n\nUse the below section names:\n\n- aaa\n- banner\n- bgp\n- dns\n- general\n- interfaces\n- ntp\n- prefix_lists\n\nName each of your templates after the section name and place them in the `templates/sections` directory.\n\nFor example, for section `dns` you would create the `templates/sections/dns.j2` template. This should contain a template rendering DNS related configuration.\n\nOnce you created your section templates, create a template named `lab08-task1-final.j2`. This template should only contain references to section templates and nothing else.\n\nMake sure that the config generated by `lab08-task1-final.j2` matches the order of the config generated by the `lab08-task1-init.j2` template.\n\n\n<details>\n <summary><b>Output to match</b></summary>\n\n```\nhostname rtr-edge-ams-01\n!\naaa new-model\naaa authentication login default group tacacs+ local enable\naaa authentication enable default group tacacs+ enable\naaa authorization exec default group tacacs+ local if-authenticated\naaa authorization commands 1 default group tacacs+ if-authenticated\naaa authorization commands 15 default group tacacs+ if-authenticated\naaa accounting exec default start-stop group tacacs+\naaa accounting commands 1 default start-stop group tacacs+\naaa accounting commands 15 default start-stop group tacacs+\naaa accounting network default start-stop group tacacs+\naaa accounting connection default start-stop group tacacs+\naaa accounting system default start-stop group tacacs+\n!\nbanner motd ^\n=============================================\n\| This device is property of CorpCo \|\n\| Unauthorized access is unauthorized \|\n\| Only access it if you have access rights \|\n\| Access attempts and commands are logged \|\n=============================================\n^\n!\nno ip domain lookup\nip domain name local.lab\nip name-server 8.8.8.8\nip name-server 8.8.4.4\n!\nntp server 1.127.0.1 prefer\nntp server 1.200.0.127\n!\ninterface GigabitEthernet1\n WAN to US\n 10.56.0.0/31\ninterface GigabitEthernet2\n WAN to US\n 10.56.0.0/31\ninterface GigabitEthernet3\n Uplink to FW\n 10.99.15.250/31\ninterface GigabitEthernet4\n Corvil monitoring\n 10.255.0.1/30\n!\nip prefix-list PL_WAN_US_IN\n permit 0.0.0.0/0 le 32\nip prefix-list PL_WAN_US_OUT\n permit 10.0.1.0/16\n permit 10.0.2.0/16\nip prefix-list PL_WAN_JPN_IN\n permit 0.0.0.0/0 le 32\nip prefix-list RM_WAN_JPN_OUT\n permit 10.5.1.0/16\n permit 10.5.2.0/16\n!\nrouter bgp 65005\nbgp router-id 1.1.1.1\nbgp log-neighbor-changes \n address-family ipv4 unicast\n neighbor 10.56.0.1/31 remote-as 65007\n neighbor 10.56.0.1/31 description rtr-edge-ny-01\n neighbor 10.56.0.1/31 route-map RM_WAN_US_IN in\n neighbor 10.56.0.1/31 route-map RM_WAN_US_OUT out\n neighbor 10.56.0.1/31 route-reflector-client\n neighbor 10.56.0.1/31 activate\n address-family ipv4 vrf ASIA-SEGMENT\n neighbor 10.89.5.3/31 remote-as 65034\n neighbor 10.89.5.3/31 description rtr-edge-ty-01\n neighbor 10.89.5.3/31 route-map RM_WAN_JPN_IN in\n neighbor 10.89.5.3/31 route-map RM_WAN_JPN_OUT out\n neighbor 10.89.5.3/31 activate\n neighbor 10.89.5.3/31 send-community both\n ```\n</details>\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab08-task1-final.j2 -d lab08-task1.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should split the original template into multiple chunks and move them to section templates.\n\nEach section template will contain part of the original template related to the given config element.\n\nOnce all template chunks are in place combine them by using `{% include 'template_path' %}` expression.\n\n```\n{% include 'sections/general.j2' %}\n{% include 'sections/aaa.j2' %}\n{% include 'sections/dns.j2' %}\n{% include 'sections/ntp.j2' %}\n{% include 'sections/interfaces.j2' %}\n{% include 'sections/prefix_lists.j2' %}\n{% include 'sections/bgp.j2' %}\n```\n\n</details>\n\n## Task 02\n\n> Resources for this task:\n> - [Jinja2 include](https://jinja2docs.readthedocs.io/en/stable/templates.html#include)\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab08-task2.yml` file and template defined in the `python/templates/lab08-task2.j2` file.\n\nYou can open these to familiarize yourself with their contents.\n\n### Step 2\n\nTemplate `python/vars/lab08-task2.j2` uses section templates created in the Task 01.\n\nYou should now make a copy of the `bgp.j2` template you created in Task 01 and name this copy `bgp_v2.j2`.\n\nYour task is to move duplicated neighbor configuration lines in `bgp_v2.j2` to another template called `bgp_neighbor.j2` in the `templates/sections` directory. Template `bgp_v2.j2` should use this sub-template to generate a neighbor configuration.\n\nYour final output should match the output from Task 01.\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -d lab08-task2.yml -t lab08-task2.j2 -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should move the duplicated lines, generating BGP neighbor config, from `bgp_v2.j2` to `bgp_neighbor.j2` template.\n\n```\n neighbor {{ neighbor['ip'] }} remote-as {{ neighbor['as_no'] }}\n neighbor {{ neighbor['ip'] }} description {{ neighbor['description'] }}\n neighbor {{ neighbor['ip'] }} route-map {{ neighbor['rm_in'] }} in\n neighbor {{ neighbor['ip'] }} route-map {{ neighbor['rm_out'] }} out\n{% if 'send_community' in neighbor['properties'] %}\n neighbor {{ neighbor['ip'] }} send-community both\n{% endif %}\n{% if 'rr_client' in neighbor['properties'] %}\n neighbor {{ neighbor['ip'] }} route-reflector-client\n{% endif %}\n neighbor {{ neighbor['ip'] }} activate\n```\n\nLines removed from `bgp_v2.j2` should be replaced with `{% include 'sections/bgp_neighbor.j2' %}` line followed by an empty new line. A new line is needed to ensure correct formatting.\n\n```\n!\nrouter bgp {{ bgp['as_no'] }}\n bgp router-id {{ bgp['rid'] }}\n bgp log-neighbor-changes \n{% for neighbor in bgp['neighbors'] %}\n{% if neighbor['vrf'] is defined %}\n address-family ipv4 vrf {{ neighbor['vrf'] }}\n{% include 'sections/bgp_neighbor.j2' %}\n\n{% else %}\n address-family ipv4 unicast\n{% include 'sections/bgp_neighbor.j2' %}\n\n{% endif %}\n{% endfor %}\n```\n\n</details>\n\n## Task 03\n\n> Resources for this task:\n> - [Jinja2 import](https://jinja2docs.readthedocs.io/en/stable/templates.html#import)\n> - [Jinja2 macros](https://jinja2docs.readthedocs.io/en/stable/templates.html#macros)\n\n### Step 1\n\nYou will be working with variables defined in the `python/vars/lab08-task3.yml` file and macros defined in the `python/templates/macros/ip_net_format.j2` file.\n\nYou can open these to familiarize yourself with their contents.\n\n### Step 2\n\nCreate template named `lab08-task3.j2` in `python/templates` dir.\n\nIn your template use macros defined in the `python/templates/macros/ip_net_format.j2` to generate output matching the below one:\n\nOutput to match\n```\nNetworks in \"network wildcard\" format:\n10.5.0.0 0.0.1.255\n10.7.1.128 0.0.0.127\n10.11.4.192 0.0.0.63\n\nNetworks in \"network netmask\" format:\n10.5.0.0 255.255.254.0\n10.7.1.128 255.255.255.128\n10.11.4.192 255.255.255.192\n\nNetworks in \"network/pfxlen\" format:\n10.5.0.0/23\n10.7.1.128/25\n10.11.4.192/26\n```\n\nYour macros should all belong to the namespace; you can use whatever name you wish for the namespace.\n\n### Step 3\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab08-task3.j2 -d lab08-task3.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should import macros in `ip_net_format.j2` file by using `{% import %}` statement and specifying path relative to `templates` directory: `macros/ip_net_format.j2`.\n\nIn your import statement, you should use `as namespace_name` syntax to import macros from the file into the namespace named `namespace_name`.\n\nTo generate the desired output, you should create `for` loops. Inside `for` loops you should apply the corresponding macro by referring to the namespace and the macro name.\n\n```\n{% import 'macros/ip_net_format.j2' as ip_macro %}\n\nNetworks in \"network wildcard\" format:\n{% for net in networks %}\n{{ ip_macro.network_w_wildcard(net['prefix']) }}\n{% endfor %}\n\nNetworks in \"network netmask\" format:\n{% for net in networks %}\n{{ ip_macro.network_w_netmask(net['prefix']) }}\n{% endfor %}\n\nNetworks in \"network/pfxlen\" format:\n{% for net in networks %}\n{{ ip_macro.network_w_pfxlen(net['prefix']) }}\n{% endfor %}\n```\n\n</details>\n\n### Step 4\n\nModify template `lab08-task3.j2`, which you created in this task, to include macros individually. You should no longer use the namespace when using macros.\n\n### Step 5\n\nRun the below command to test your template.\n\n```\n./j2_render.py -t lab08-task3.j2 -d lab08-task3.yml -trim\n```\n\n<details>\n <summary>Reveal Answer</summary>\n\nYou should import macros individually from the `ip_net_format.j2` file by using `{% from 'macros_file' import macro1, macro2 %}` statement. \n\nIn your import statement, you should list the names of the macros you are importing.\n\nTo generate the desired output, you should create `for` loops. Inside `for` loops you should apply the corresponding macro by referring to the macro name. We're not using namespaces here.\n\n```\n{% from 'macros/ip_net_format.j2' import network_w_wildcard, network_w_netmask, network_w_pfxlen %}\n\nNetworks in \"network wildcard\" format:\n{% for net in networks %}\n{{ network_w_wildcard(net['prefix']) }}\n{% endfor %}\n\nNetworks in \"network netmask\" format:\n{% for net in networks %}\n{{ network_w_netmask(net['prefix']) }}\n{% endfor %}\n\nNetworks in \"network/pfxlen\" format:\n{% for net in networks %}\n{{ network_w_pfxlen(net['prefix']) }}\n{% endfor %}\n```\n\n</details>" }, { "alpha_fraction": 0.4584410488605499, "alphanum_fraction": 0.4687214195728302, "avg_line_length": 33.7073860168457, "blob_id": "936dd395269b427d606b20befa6a50940f83589e", "content_id": "1dc3e36135853340f7233cf4d2c18719efed2d20", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 50380, "license_type": "no_license", "max_line_length": 475, "num_lines": 1449, "path": "/workshops/extending-ansible/lab05_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Extending Ansible - Lab 05\n\nAnsible modules are the building blocks of Ansible playbooks. Modules are reusable, standalone scripts that Ansible runs on your behalf, either locally or remotely to interface with a local machine, an API, or a remote system to perform specific tasks. Ansible modules are used inside tasks within a playbook, and do all the automation work based on the purpose of the module.\n\nAnsible already comes installed with a good number of modules to cover many of the automation tasks out there, but sometimes there are going to be certain tasks that some modules might not fully support.\n\nThis lab will show you how to build an Ansible module from scratch to abstract the ability to make an HTTP API call to `GET` device configuration from the IOS-XE RESTCONF API.\n\n## Task 1 - Building the initial stages of an Ansible module\n\nThis task will show how to build a basic Python script that will be used as the initial module to test with an Ansible playbook. \n\n### Step 1\n\nIn the terminal of the workstation, change or create if not present to `/home/ntc/labs/lab05` folder. Use the `mkdir` command to create the `/home/ntc/labs/lab05` folders. \n\n```\nntc@ntc-training:~$ mkdir -p /home/ntc/labs/lab05\nntc@ntc-training:~$ cd /home/ntc/labs/lab05\nntc@ntc-training:lab05$\n```\n\n### Step 2\n\nCreate a folder named `modules` and an empty file called `iosxe_gather_configs.py`. Use the `mkdir` command to create the folder and the `touch` command to create the empty file. The `tree` command will display the folder structure.\n\n```\nntc@ntc-training:lab05$ mkdir modules\nntc@ntc-training:lab05$ touch modules/iosxe_gather_configs.py\nntc@ntc-training:lab05$ tree\n.\n└── modules\n └── iosxe_gather_configs.py\n\n1 directory, 1 file\n```\n\n### Step 3\n\nOpen up the `iosxe_gather_configs.py` script with an editor of choice. Inside the file add `#!/usr/bin/python3` on the first line and on the next line import the `AnsibleModule` class from the `ansible.module_utils.basic` library.\n\n> Note: The `AnsibleModule` class is used to pass parameters in and out of the module. \n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\n```\n\n### Step 4\n\nAfter importing the `AnsibleModule` class object build a `main()` function and create a variable called `module` to store the `AnsibleModule` object. Inside the `AnsibleModule` object pass in `argument_spec` as an argument with an empty dictionary for now. Later the `argument_spec` will be used to create the Ansible module parameters.\n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\n\ndef main():\n\n module = AnsibleModule(argument_spec={})\n```\n\n### Step 5\n\nCreate a variable called `response` with a value containing a dictionary of `{\"host\": \"csr1\"}`. For now the `response` value will be the output displayed when the Ansible playbook is executed. \n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\n\ndef main():\n\n module = AnsibleModule(argument_spec={})\n\n response = {\"host\": \"csr1\"}\n```\n\n### Step 6\n\nThe `AnsibleModule` class will help handle incoming parameters and exiting the program using the `module.exit_json()` method at the end of the script. The `module.exit_json()` method will take in `msg=response` as an argument to display the output.\n\nThe `exit_json()` method is what is going to be returned from the module without error.\n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\n\ndef main():\n\n module = AnsibleModule(argument_spec={})\n\n response = {\"host\": \"csr1\"}\n\n module.exit_json(msg=response)\n```\n\n### Step 7\n\nAt the end of the file add the entry point to the script. This will make sure the `main()` function is executed when `__name__` equals to the string `__main__` which happens when the module is ran as a Python script. \n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\n\ndef main():\n\n module = AnsibleModule(argument_spec={})\n\n response = {\"host\": \"csr1\"}\n\n module.exit_json(msg=response)\n \nif __name__ == '__main__':\n main()\n```\n\n## Task 2 Testing the Ansible module with a Playbook\n\nAfter building the Python script that will be used for the module, it's time to test it out using an Ansible playbook.\n\n### Step 1\n\nCreate a `YAML` file in the `lab05` folder called `test_module.yml`. Use the `touch` command to create the file and use the `tree` command to make sure the file is stored in the correct location.\n\n```shell\nntc@ntc-training:modules$ cd ../\nntc@ntc-training:lab05$ touch test_module.yml\nntc@ntc-training:lab05$ tree\n.\n├── modules\n│ └── iosxe_gather_configs.py\n└── test_module.yml\n\n1 directory, 2 files\nntc@ntc-training:lab05$ \n```\n\n### Step 2\n\nOpen and start editing the `test_module.yml` file and add the play definition first.\n\n> Note: Since the module is not built to communicate with networking devices, use `localhost` first to just run the task locally.\n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: localhost\n gather_facts: false\n \n tasks:\n```\n\n### Step 3\n\nBelow the `tasks` key add two tasks. The first one will be the name of the module created `iosxe_gather_configs` and add the register argument to the task to store the output.\n\nIn ansible `iosxe_gather_configs` is the module name which will be the same name of the Python script previously built called `iosxe_gather_configs.py`. \n\nEvery module has to return JSON data. In the `iosxe_gather_configs.py` script, the `module.exit_json(msg=response)` method will return that JSON data stored in the `result` variable created by the `register` argument. \n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: localhost\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs: \n register: result\n```\n\n### Step 4\n\nAdd another task using the `debug` module and the `var` parameter to view the data stored inside the `result` variable from the previous task.\n\n> Note: The `debug` module allows the user to view data stored in variables. \n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: localhost\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs: \n register: result\n\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result \n```\n\n### Step 5\n\nExecute the Ansible playbook by running the command `ansible-playbook test_module.yml`\n\n```shell\nntc@ntc-training:lab05$ ansible-playbook test_module.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\nERROR! couldn't resolve module/action 'iosxe_gather_configs'. This often indicates a misspelling, missing collection, or incorrect module path.\n\nThe error appears to be in '/home/ntc/labs/lab05/test_module.yml': line 9, column 7, but may\nbe elsewhere in the file depending on the exact syntax problem.\n\nThe offending line appears to be:\n\n\n - name: GATHER IOSXE CONFIGS\n ^ here\nntc@ntc-training:lab05$ \n```\n\n### Step 6\n\nOn the previous step the playbook failed, because it could not find the module it was trying to run. The error shows:\n\n```\nERROR! couldn't resolve module/action 'iosxe_gather_configs'. This often indicates a misspelling, missing collection, or incorrect module path.\n```\n\nTo fix this issue check where the `ansible.cfg` file is located and copy it over to the current local directory to modify the location of the Ansible module. Execute the `ansible --version` command to view the location.\n\n```shell\nntc@ntc-training:lab05$ ansible --version\nansible 2.9.9\n config file = /etc/ansible/ansible.cfg\n configured module search path = ['/etc/ntc/ansible/library']\n ansible python module location = /usr/local/lib/python3.6/site-packages/ansible\n executable location = /usr/local/bin/ansible\n python version = 3.6.8 (default, Jun 11 2019, 01:16:11) [GCC 6.3.0 20170516]\nntc@ntc-training:lab05$ \n```\n> Note: Take a look at `config file` and `configured module search path` because these will change after modifying the `ansible.cfg` file.\n> When creating a custom module also known as a third party module, Ansible needs to know where to find that custom module. To do that you need to edit the `ansible.cfg` file and indicate the location of the `iosxe_gather_configs.py` script. \n\n### Step 7\n\nCopy the `ansible.cfg` file from `/etc/ansible/ansible.cfg` to the current working directory using the `cp` Linux command. Make sure it's copied into the current working directory using the `tree` command.\n\n```shell\nntc@ntc-training:lab05$ \nntc@ntc-training:lab05$ cp /etc/ansible/ansible.cfg .\nntc@ntc-training:lab05$ \nntc@ntc-training:lab05$ tree\n.\n├── ansible.cfg\n├── modules\n│ └── iosxe_gather_configs.py\n└── test_module.yml\n\n1 directory, 3 files\nntc@ntc-training:lab05$ \n```\n\n### Step 8\n\nTo indicate the location of the custom module, modify the `ansible.cfg` file by providing the absolute path to the `modules` folder. Change into the `modules` folder and use the `pwd` Linux command to show the current working directory. \n\n\n```shell\nntc@ntc-training:lab05$ cd modules/\nntc@ntc-training:modules$ pwd\n/home/ntc/labs/lab05/modules\nntc@ntc-training:modules$ \n```\n\n### Step 9\n\nUse the path provided by `pwd` and modify the `library` argument under the `[defaults]` options of the `ansible.cfg` file. \n\n```\n[defaults]\nlibrary = /home/ntc/labs/lab05/modules\nfilter_plugins = /etc/ntc/ansible/plugins/filter\nroles_path = /etc/ntc/ansible/roles\ninterpreter_python = /usr/local/bin/python\nhost_key_checking = False\nnocows = 1\nretry_files_enabled = False\ndeprecation_warnings = False\n\n[inventory]\nenable_plugins = ini, host_list, script, auto, yaml, toml\n```\n\n### Step 10\n\nAfter saving the changes, execute the `ansible --version` command in the `lab05` folder to view the changes from the output. The output should display a different value on the `config file` and `configured module search path`, both pointing the current working directory. \n\n```\nntc@ntc-training:modules$ \nntc@ntc-training:modules$ cd ../\nntc@ntc-training:lab05$ ansible --version\nansible 2.9.9\n config file = /home/ntc/labs/lab05/ansible.cfg\n configured module search path = ['/home/ntc/labs/lab05/modules']\n ansible python module location = /usr/local/lib/python3.6/site-packages/ansible\n executable location = /usr/local/bin/ansible\n python version = 3.6.8 (default, Jun 11 2019, 01:16:11) [GCC 6.3.0 20170516]\nntc@ntc-training:lab05$ \n```\n\n> Note: Take a look at the values stored in `config file` and `configured module search path` to see how it changed from the previous change.\n\n### Step 11\n\nExecute the Ansible playbook again and view the results. \n\n```\nntc@ntc-training:lab05$ ansible-playbook test_module.yml\n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit\nlocalhost does not match 'all'\n\nPLAY [TEST CUSTOM MODULE WORKS] ******************************************************************\n\nTASK [GATHER IOSXE CONFIGS] ********************************************************************\nok: [localhost]\n\nTASK [VIEW THE DATA STORED IN RESULT] **********************************************************\nok: [localhost] => {\n \"result\": {\n \"changed\": false,\n \"failed\": false,\n \"msg\": {\n \"host\": \"csr1\"\n }\n }\n}\n\nPLAY RECAP *************************************************************************************\nlocalhost : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n### Step 12\n\nModify the `test_module.yml` playbook to see if you can access the `host` key and only return the `csr1` string from the output.\n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: localhost\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs: \n register: result\n\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result['msg']['host']\n```\n\n### Step 13\n\nExecute the Ansible playbook again and view the results. \n\n```\nntc@ntc-training:lab05$ ansible-playbook test_module.yml \n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit\nlocalhost does not match 'all'\n\nPLAY [TEST CUSTOM MODULE WORKS] ******************************************************************\n\nTASK [GATHER IOSXE CONFIGS] **********************************************************************\nok: [localhost]\n\nTASK [VIEW THE DATA STORED IN RESULT] ************************************************************\nok: [localhost] => {\n \"result['msg']['host']\": \"csr1\"\n}\n\nPLAY RECAP ***************************************************************************************\nlocalhost : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n## Task 3 Building the getter module\n\nNow that a basic module has been built to display some data, this task will focus on implementing the code that will make an API call against IOSXE devices to `GET` configuration data.\n\n### Step 1\n\nOpen the `iosxe_gather_configs.py` inside the `modules` folder to start editing the code. In the Python script import the needed libraries to make the API calls against the networking devices.\n\nThe `requests` library will be used to make HTTP or HTTPS API REST calls against servers that have APIs. The `HTTPBasicAuth` class object will be used to provide authentication details about the server and `requests.packages.urllib3.disable_warnings()` will be used to disable any warnings from the API call (since we are using self-signed certificates in the lab environment).\n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n\n module = AnsibleModule(argument_spec={})\n\n response = {\"host\": \"csr1\"}\n\n module.exit_json(changed=False, msg=response)\n \nif __name__ == '__main__':\n main()\n```\n\n### Step 2\n\nInside the `def main()` function add the `url`, `auth`, `headers` and modify the `response` variable. The `url` variable will contain the resource path to the device configuration. The `auth` variable is used to store the device credentials and the `headers` is used to indicate what data encoding to expect from the server/csr1 device. Modify the value of the `response` variable so it contains the response from the API call.\n\nAlso modify the `module.exit_json()` method so it can display the data stored inside `response.json()`. \n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n \n module = AnsibleModule(argument_spec={})\n \n auth = HTTPBasicAuth('ntc', 'ntc123')\n \n url = 'https://csr1/restconf/data/Cisco-IOS-XE-native:native/'\n\n headers = {\"Accept\": \"application/yang-data+json\"}\n \n response = requests.get(url, headers=headers, auth=auth, verify=False)\n \n module.exit_json(msg=response.json())\n \nif __name__ == '__main__':\n main()\n```\n\n### Step 3\n\nChange back to the `lab05` folder and change back the `debug` task to print the whole contents of the `result` variable.\n\n```yaml\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result\n```\n\nExecute the `test_module.yml` playbook again to see the output.\n\n> Note: Currently this module is only targeting a single device since the `module` script has the host statically defined in the `url` variable.\n\n```\nntc@ntc-training:lab05$ ansible-playbook test_module.yml \n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\n\nPLAY [TEST CUSTOM MODULE WORKS] *********************************************************************************************************\n\nTASK [GATHER IOSXE CONFIGS] *************************************************************************************************************\nok: [localhost]\n\nTASK [VIEW THE DATA STORED IN RESULT] ***************************************************************************************************\nok: [localhost] => {\n \"result\": {\n \"changed\": false,\n \"failed\": false,\n \"msg\": {\n \"Cisco-IOS-XE-native:native\": {\n \"Cisco-IOS-XE-diagnostics:diagnostic\": {\n \"bootup\": {\n \"level\": \"minimal\"\n }\n },\n \"Cisco-IOS-XE-lldp:lldp\": {\n \"run\": [\n null\n ]\n },\n \"alias\": {\n \"exec\": [\n {\n \"alias-name\": \"ntcclear\",\n \"new-alias-name\": \"clear platform software vnic-if nv\"\n }\n ]\n },\n \"archive\": {\n \"path\": \"bootflash:archive\"\n },\n \"boot-end-marker\": [\n null\n ],\n \"boot-start-marker\": [\n null\n ],\n \"call-home\": {\n \"Cisco-IOS-XE-call-home:contact-email-addr\": \"[email protected]\",\n \"Cisco-IOS-XE-call-home:profile\": [\n {\n \"active\": true,\n \"destination\": {\n \"transport-method\": \"http\"\n },\n \"profile-name\": \"CiscoTAC-1\"\n }\n ]\n },\n \"cdp\": {\n \"Cisco-IOS-XE-cdp:run-enable\": true\n },\n \"control-plane\": {},\n \"crypto\": {\n \"Cisco-IOS-XE-crypto:pki\": {\n \"certificate\": {\n \"chain\": [\n {\n \"certificate\": [\n {\n \"certtype\": \"ca\",\n \"serial\": \"01\"\n }\n ],\n \"name\": \"SLA-TrustPoint\"\n },\n {\n \"certificate\": [\n {\n \"certtype\": \"self-signed\",\n \"serial\": \"01\"\n }\n ],\n \"name\": \"TP-self-signed-1088426642\"\n }\n ]\n },\n \"trustpoint\": [\n {\n \"enrollment\": {\n \"pkcs12\": [\n null\n ]\n },\n \"id\": \"SLA-TrustPoint\",\n \"revocation-check\": [\n \"crl\"\n ]\n },\n {\n \"enrollment\": {\n \"selfsigned\": [\n null\n ]\n },\n \"id\": \"TP-self-signed-1088426642\",\n \"revocation-check\": [\n \"none\"\n ],\n \"subject-name\": \"cn=IOS-Self-Signed-Certificate-1088426642\"\n }\n ]\n }\n },\n \"hostname\": \"csr1\",\n \"interface\": {\n \"GigabitEthernet\": [\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"description\": \"MANAGEMENT_DO_NOT_CHANGE\",\n \"ip\": {\n \"address\": {\n \"primary\": {\n \"address\": \"10.0.0.15\",\n \"mask\": \"255.255.255.0\"\n }\n }\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"1\"\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"2\"\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"3\"\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"4\"\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"5\"\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"6\",\n \"shutdown\": [\n null\n ]\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"7\",\n \"shutdown\": [\n null\n ]\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"8\",\n \"shutdown\": [\n null\n ]\n },\n {\n \"Cisco-IOS-XE-ethernet:negotiation\": {\n \"auto\": true\n },\n \"mop\": {\n \"enabled\": false,\n \"sysid\": false\n },\n \"name\": \"9\",\n \"shutdown\": [\n null\n ]\n }\n ],\n \"Loopback\": [\n {\n \"ip\": {\n \"address\": {\n \"primary\": {\n \"address\": \"100.2.2.4\",\n \"mask\": \"255.255.255.0\"\n }\n }\n },\n \"name\": 100\n },\n {\n \"ip\": {\n \"address\": {\n \"primary\": {\n \"address\": \"20.0.0.1\",\n \"mask\": \"255.255.255.0\"\n }\n }\n },\n \"name\": 200\n }\n ]\n },\n \"ip\": {\n \"Cisco-IOS-XE-http:http\": {\n \"authentication\": {\n \"local\": [\n null\n ]\n },\n \"secure-server\": true,\n \"server\": true\n },\n \"access-list\": {\n \"Cisco-IOS-XE-acl:extended\": [\n {\n \"name\": \"meraki-fqdn-dns\"\n }\n ]\n },\n \"domain\": {\n \"lookup\": false,\n \"name\": \"ntc.com\"\n },\n \"forward-protocol\": {\n \"protocol\": \"nd\"\n },\n \"pim\": {\n \"Cisco-IOS-XE-multicast:autorp-container\": {\n \"autorp\": false\n }\n },\n \"scp\": {\n \"server\": {\n \"enable\": [\n null\n ]\n }\n }\n },\n \"ipv6\": {\n \"Cisco-IOS-XE-mld:mld\": {\n \"ssm-map\": {\n \"query\": {\n \"dns-leaf\": false\n }\n }\n }\n },\n \"license\": {\n \"udi\": {\n \"pid\": \"CSR1000V\",\n \"sn\": \"9SAGBHTUEE9\"\n }\n },\n \"line\": {\n \"console\": [\n {\n \"first\": \"0\",\n \"stopbits\": \"1\"\n }\n ],\n \"vty\": [\n {\n \"first\": 0,\n \"last\": 4,\n \"login\": {\n \"local\": [\n null\n ]\n },\n \"privilege\": {\n \"level\": {\n \"number\": 15\n }\n },\n \"transport\": {\n \"input\": {\n \"all\": [\n null\n ]\n },\n \"preferred\": {\n \"protocol\": \"ssh\"\n }\n }\n },\n {\n \"first\": 5,\n \"last\": 15,\n \"login\": {\n \"local\": [\n null\n ]\n },\n \"privilege\": {\n \"level\": {\n \"number\": 15\n }\n },\n \"transport\": {\n \"input\": {\n \"all\": [\n null\n ]\n },\n \"preferred\": {\n \"protocol\": \"ssh\"\n }\n }\n }\n ]\n },\n \"login\": {\n \"on-success\": {\n \"log\": {}\n }\n },\n \"memory\": {\n \"free\": {\n \"low-watermark\": {\n \"processor\": 72107\n }\n }\n },\n \"multilink\": {\n \"Cisco-IOS-XE-ppp:bundle-name\": \"authenticated\"\n },\n \"platform\": {\n \"Cisco-IOS-XE-platform:console\": {\n \"output\": \"serial\"\n },\n \"Cisco-IOS-XE-platform:punt-keepalive\": {\n \"disable-kernel-core\": true\n },\n \"Cisco-IOS-XE-platform:qfp\": {\n \"utilization\": {\n \"monitor\": {\n \"load\": 80\n }\n }\n }\n },\n \"redundancy\": {},\n \"router\": {\n \"Cisco-IOS-XE-rip:rip\": {}\n },\n \"service\": {\n \"call-home\": [\n null\n ],\n \"timestamps\": {\n \"debug\": {\n \"datetime\": {\n \"msec\": {}\n }\n },\n \"log\": {\n \"datetime\": {\n \"msec\": [\n null\n ]\n }\n }\n }\n },\n \"snmp-server\": {\n \"Cisco-IOS-XE-snmp:community\": [\n {\n \"access-list-name\": \"ro\",\n \"name\": \"NETMIKO_FROM_FILE\"\n },\n {\n \"access-list-name\": \"ro\",\n \"name\": \"SENT_WITH_NETMIKO\"\n },\n {\n \"RW\": [\n null\n ],\n \"name\": \"ntc-private\"\n },\n {\n \"RO\": [\n null\n ],\n \"name\": \"ntc-public\"\n }\n ],\n \"Cisco-IOS-XE-snmp:contact\": \"Kevin\",\n \"Cisco-IOS-XE-snmp:location\": \"Atlanta\"\n },\n \"spanning-tree\": {\n \"Cisco-IOS-XE-spanning-tree:extend\": {\n \"system-id\": [\n null\n ]\n }\n },\n \"subscriber\": {\n \"templating\": [\n null\n ]\n },\n \"username\": [\n {\n \"name\": \"ntc\",\n \"password\": {\n \"encryption\": \"0\",\n \"password\": \"ntc123\"\n },\n \"privilege\": 15\n }\n ],\n \"version\": \"17.1\",\n \"virtual-service\": [\n {\n \"name\": \"csr_mgmt\"\n }\n ],\n \"vrf\": {\n \"definition\": [\n {\n \"address-family\": {\n \"ipv4\": {},\n \"ipv6\": {}\n },\n \"name\": \"MANAGEMENT\"\n }\n ]\n }\n }\n }\n }\n}\n\nPLAY RECAP ******************************************************************************************************************************\nlocalhost : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n### Step 4\n\nModify the `test_module.yml` playbook to see if the data can be accessed and what keys are available.\n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: localhost\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs: \n register: result\n\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result['msg']['Cisco-IOS-XE-native:native'].keys()\n```\n\n### Step 5\n\nExecute the playbook and view the output. Each key returned contains data from the device configuration. These keys can also be used as a resource endpoint at the end of the `url` in the API call. Since the Python script has the `url` statically defined the data can only be accessed through the JSON output as a Python dictionary.\n\n```\nntc@ntc-training:lab05$ ansible-playbook test_module.yml \n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\n\nPLAY [TEST CUSTOM MODULE WORKS] *********************************************************************************************************\n\nTASK [GATHER IOSXE CONFIGS] *************************************************************************************************************\nok: [localhost]\n\nTASK [VIEW THE DATA STORED IN RESULT] ***************************************************************************************************\nok: [localhost] => {\n \"result['msg']['Cisco-IOS-XE-native:native'].keys()\": \"dict_keys(['version', 'boot-start-marker', 'boot-end-marker', 'memory', 'call-home', 'service', 'platform', 'hostname', 'archive', 'username', 'vrf', 'ip', 'ipv6', 'cdp', 'interface', 'control-plane', 'login', 'multilink', 'redundancy', 'spanning-tree', 'subscriber', 'crypto', 'router', 'virtual-service', 'snmp-server', 'license', 'alias', 'line', 'Cisco-IOS-XE-diagnostics:diagnostic', 'Cisco-IOS-XE-lldp:lldp'])\"\n}\n\nPLAY RECAP ******************************************************************************************************************************\nlocalhost : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n### Step 6\n\nModify the playbook so it can only access the device version. Provide the needed keys to access the device `version` information. \n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: localhost\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs: \n register: result\n\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result['msg']['Cisco-IOS-XE-native:native']['version']\n```\n\n### Step 7\n\nExecute the playbook and view the output.\n\n```\nntc@ntc-training:lab05$ ansible-playbook test_module.yml \n[WARNING]: No inventory was parsed, only implicit localhost is available\n[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'\n\nPLAY [TEST CUSTOM MODULE WORKS] *********************************************************************************************************\n\nTASK [GATHER IOSXE CONFIGS] *************************************************************************************************************\nok: [localhost]\n\nTASK [VIEW THE DATA STORED IN RESULT] ***************************************************************************************************\nok: [localhost] => {\n \"result['msg']['Cisco-IOS-XE-native:native']['version']\": \"17.1\"\n}\n\nPLAY RECAP ******************************************************************************************************************************\nlocalhost : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n## Task 4 Optimizing the module with parameters\n\nThis task will focus on improving the module so it can take in more dynamic data for different devices, credentials and a filter to only return specific data rather than the entire configuration. \n\n### Step 1\n\nOpen the `iosxe_gather_configs.py` script and create a variable called `module_args`. As a value to the `module_args` variable create a dictionary using the `dict` object.\n\n> Note: The `dict` object is just another way to build dictionary data structures. \n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n\n module_args = dict(\n host=dict(),\n user=dict(),\n password=dict()\n )\n \n module = AnsibleModule(argument_spec={})\n \n auth = HTTPBasicAuth('ntc', 'ntc123')\n \n url = 'https://csr1/restconf/data/Cisco-IOS-XE-native:native/'\n\n headers = {\"Accept\": \"application/yang-data+json\"}\n \n response = requests.get(url, headers=headers, auth=auth, verify=False)\n \n module.exit_json(changed=False, msg=response.json())\n \nif __name__ == '__main__':\n main()\n```\n\n### Step 2\n\nModify each key inside `module_args` to specify what data type to expect from the user and if the parameter is required or not. Since these parameters will be needed to communicate with the networking devices then they will need to be set as required. These dictionary keys will become the module parameters in the Ansible playbook. \n\nThese parameters will allow the user to dynamically provide input data to the module so it does not run on the same device and use the same credentials every time without the ability to modify the script.\n\nModify the `auth` variable so that it can pass in the credentials that the user will provide as value in the module task. Also modify the `url` variable so the user can dynamically provide input for what devices to target.\n\nFinally the `module` variable will need to be modified to take in the `module_args` as input into the `argument_spec` which will build the module parameters.\n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n\n module_args = dict(\n host=dict(type='str', required=True),\n user=dict(type='str', required=True),\n password=dict(type='str', required=True)\n )\n \n module = AnsibleModule(argument_spec=module_args)\n \n auth = HTTPBasicAuth(module.params['user'], module.params['password'])\n \n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/\"\n\n headers = {\"Accept\": \"application/yang-data+json\"}\n \n response = requests.get(url, headers=headers, auth=auth, verify=False)\n \n module.exit_json(changed=False, msg=response.json())\n \nif __name__ == '__main__':\n main()\n```\n\n### Step 3\n\n\nAfter making the previous changes, create an inventory file and add three `iosxe` devices.\n\n```\nntc@ntc-training:lab05$ \nntc@ntc-training:lab05$ touch inventory\nntc@ntc-training:lab05$ \nntc@ntc-training:lab05$ tree\n.\n├── ansible.cfg\n├── inventory\n├── modules\n│ └── iosxe_gather_configs.py\n└── test_module.yml\n\n1 directory, 4 files\nntc@ntc-training:lab05$ \n```\n\n### Step 4\n\nInside the `ini` inventory file add the three `csr` devices and the credentials as `group_vars`.\n\n```ini\n[iosxe]\ncsr1\ncsr2\ncsr3\n\n\n[iosxe:vars]\nusername=ntc\npassword=ntc123\n```\n\n### Step 5\n\nModify the `test_module.yml` playbook to take in all `iosxe` devices and parameterize the data that will be taken as input to the module. Also set the `connection` key as `local` and add the new parameters under the module name. The parameters are going to be the same `keys` created in `iosxe_gather_configs.py` script inside the `module_args` variable.\n\nThe values used for each parameter will be `inventory_hostname` - in turn, taking the value of every device stored in the `iosxe` group within this play. The `username` and `password` variables will be rendered from the `iosxe:vars` inside the inventory file.\n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: iosxe\n connection: local\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ username }}\"\n password: \"{{ password }}\"\n register: result\n\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result['msg']['Cisco-IOS-XE-native:native']['version']\n```\n\n### Step 6\n\nAfter making and saving the changes execute the playbook with the inventory file to view the results. Review the output and notice that this time multiple devices have been targeted and not just the `csr1` device.\n\n```\nntc@ntc-training:lab05$ \nntc@ntc-training:lab05$ ansible-playbook -i inventory test_module.yml \n\nPLAY [TEST CUSTOM MODULE WORKS] ****************************************************************************\n\nTASK [GATHER IOSXE CONFIGS] ********************************************************************************\nok: [csr3]\nok: [csr2]\nok: [csr1]\n\nTASK [VIEW THE DATA STORED IN RESULT] **********************************************************************\nok: [csr1] => {\n \"result['msg']['Cisco-IOS-XE-native:native']['version']\": \"17.1\"\n}\nok: [csr2] => {\n \"result['msg']['Cisco-IOS-XE-native:native']['version']\": \"17.1\"\n}\nok: [csr3] => {\n \"result['msg']['Cisco-IOS-XE-native:native']['version']\": \"17.1\"\n}\n\nPLAY RECAP *************************************************************************************************\ncsr1 : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \ncsr2 : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \ncsr3 : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n### Step 7\n\nCurrently the module can only return the entire device configuration. A `filter` can be created as a parameter so that the user can specify as a value to only request certain data from the API rather than the entire configuration. Modify the `iosxe_gather_configs.py` script so it can filter out the device configuration.\n\n> Note: Choices and default are two new arguments that can be used to specify the only choices available for the user to input into the parameter and a default argument is used so that when the user does not specify a choice it will get all the device configurations. \n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\n\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n\n module_args = dict(\n host=dict(type=\"str\", required=True),\n user=dict(type=\"str\", required=True),\n password=dict(type=\"str\", required=True, no_log=True),\n filter=dict(\n type=\"str\",\n required=False,\n default=\"all\",\n choices=[\n \"all\",\n \"version\",\n \"memory\",\n \"platform\",\n \"hostname\",\n \"username\",\n \"vrf\",\n \"ip\",\n \"cdp\",\n \"interface\",\n \"login\",\n \"snmp-server\",\n \"lldp\",\n ],\n ),\n )\n\n module = AnsibleModule(argument_spec=module_args)\n\n auth = HTTPBasicAuth(module.params[\"user\"], module.params[\"password\"])\n\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/\"\n\n headers = {\"Accept\": \"application/yang-data+json\"}\n\n response = requests.get(url, headers=headers, auth=auth, verify=False)\n\n module.exit_json(msg=response.json())\n\n\nif __name__ == \"__main__\":\n main()\n```\n\n### Step 8\n\nAdd some logic to the Python script so that the correct `URL` endpoint is provided based on the choice from the user.\n\n```python\n#!/usr/bin/python3\n\nfrom ansible.module_utils.basic import AnsibleModule\nimport requests\nfrom requests.auth import HTTPBasicAuth\n\nrequests.packages.urllib3.disable_warnings()\n\n\ndef main():\n\n module_args = dict(\n host=dict(type=\"str\", required=True),\n user=dict(type=\"str\", required=True),\n password=dict(type=\"str\", required=True, no_log=True),\n filter=dict(\n type=\"str\",\n required=False,\n default=\"all\",\n choices=[\n \"all\",\n \"version\",\n \"memory\",\n \"platform\",\n \"hostname\",\n \"username\",\n \"vrf\",\n \"ip\",\n \"cdp\",\n \"interface\",\n \"login\",\n \"snmp-server\",\n \"lldp\",\n ],\n ),\n )\n\n module = AnsibleModule(argument_spec=module_args)\n\n auth = HTTPBasicAuth(module.params[\"user\"], module.params[\"password\"])\n\n if module.params[\"filter\"] == \"all\":\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/\"\n elif module.params[\"filter\"] == \"lldp\":\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/Cisco-IOS-XE-lldp:lldp\"\n else:\n url = f\"https://{module.params['host']}/restconf/data/Cisco-IOS-XE-native:native/{module.params['filter']}\"\n\n headers = {\"Accept\": \"application/yang-data+json\"}\n\n response = requests.get(url, headers=headers, auth=auth, verify=False)\n\n module.exit_json(changed=False, msg=response.json())\n\n\nif __name__ == \"__main__\":\n main()\n```\n\n### Step 9\n\nModify the `test_module.yml` playbook and add the `filter` parameter and as a value choose `version`.\n\n```yaml\n---\n\n- name: TEST CUSTOM MODULE WORKS\n hosts: iosxe\n connection: local\n gather_facts: false\n \n tasks:\n\n - name: GATHER IOSXE CONFIGS\n iosxe_gather_configs:\n host: \"{{ inventory_hostname }}\"\n user: \"{{ username }}\"\n password: \"{{ password }}\"\n filter: version\n register: result\n\n - name: VIEW THE DATA STORED IN RESULT\n debug: \n var: result\n```\n\n### Step 10\n\nAfter saving the playbook execute it and view the results.\n\n```\nntc@ntc-training:lab05$ ansible-playbook -i inventory test_module.yml \n\nPLAY [TEST CUSTOM MODULE WORKS] *********************************************************************************************************\n\nTASK [GATHER IOSXE CONFIGS] *************************************************************************************************************\nok: [csr1]\nok: [csr3]\nok: [csr2]\n\nTASK [VIEW THE DATA STORED IN RESULT] ***************************************************************************************************\nok: [csr1] => {\n \"result\": {\n \"changed\": false,\n \"failed\": false,\n \"msg\": {\n \"Cisco-IOS-XE-native:version\": \"17.1\"\n }\n }\n}\nok: [csr2] => {\n \"result\": {\n \"changed\": false,\n \"failed\": false,\n \"msg\": {\n \"Cisco-IOS-XE-native:version\": \"17.1\"\n }\n }\n}\nok: [csr3] => {\n \"result\": {\n \"changed\": false,\n \"failed\": false,\n \"msg\": {\n \"Cisco-IOS-XE-native:version\": \"17.1\"\n }\n }\n}\n\nPLAY RECAP *******************************************************************************************************************************\ncsr1 : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \ncsr2 : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \ncsr3 : ok=2 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 \n\nntc@ntc-training:lab05$ \n```\n\n### Step 11\n\nTry out other value of for the `filter` parameter, both valid and invalid to see what Ansible does." }, { "alpha_fraction": 0.7096773982048035, "alphanum_fraction": 0.7634408473968506, "avg_line_length": 17.600000381469727, "blob_id": "f6624ae1ddb8d120b7f2730247634efb79eb2db1", "content_id": "d280b15a8d24af5c15a3c8eec337a6d1f240ddf9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 93, "license_type": "no_license", "max_line_length": 42, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-roadrunner-lsw03/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-roadrunner-lsw03\n\nThis Arista vEOS device is located in DC1.\n\nIts status is: Staged.\n" }, { "alpha_fraction": 0.7230632305145264, "alphanum_fraction": 0.7266250848770142, "avg_line_length": 26.365854263305664, "blob_id": "6ed3f38f4f3e752c77f6a0aef875c073122f816d", "content_id": "d2c7f6f839b043c9202eb4b31ccc216509d2467b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1123, "license_type": "no_license", "max_line_length": 133, "num_lines": 41, "path": "/workshops/telemetry-deepdive/prometheus_promql/001_label_filtering.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Label Filtering\n## Goals\nThe goals of this lab are:\n Familiarize yourself with the Thanos UI.\n* Perform basic label filtering to return the active ASA VPN clients.\n\n## Exercises\n### Basic Query\nRun the query: `asa_anyconnect_client_active` and view the results within the `Console`.\n### Query with Label Selection (Equal)\nPerform a query to return all active ASA VPN clients (`asa_anyconnect_client_active`) for `frankfurt`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nasa_anyconnect_client_active{site=\"frankfurt\"}\n```\n</details>\n\n\n### Query with Label Selection (Not Equal)\nPerform a query to return all active ASA VPN clients (`asa_anyconnect_client_active`) for all sites excluding `frankfurt`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nasa_anyconnect_client_active{site!=\"frankfurt\"}\n```\n</details>\n\n\n\n### Query with Label Selection (Regex Match)\nPerform a query to return all active ASA VPN clients (`asa_anyconnect_client_active`) for all sites ending in the numbers `2` or `3`.\n<details>\n <summary>Reveal Answer</summary>\n \n```\nasa_anyconnect_client_active{device=~\".[2-3]\"}\n```\n</details>\n\n" }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "b1affad80b99b4c18fdadf59413edbbf4b86a913", "content_id": "54e75b2f5095b64cbd466d997fa80493755aec03", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx19/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx19\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Staged.\n" }, { "alpha_fraction": 0.6497526168823242, "alphanum_fraction": 0.7168708443641663, "avg_line_length": 39.73168182373047, "blob_id": "f99ed445dd8daaa87b7550fb30b50d2b4ab8d37f", "content_id": "588977431163cfee2d23355ec6acff81f5e6c0c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 38153, "license_type": "no_license", "max_line_length": 549, "num_lines": 928, "path": "/workshops/development-environments/lab_guide.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# NTC DevEnv Workshop - Lab Guide\n\nYou will now practice some of the concepts that were demonstrated in the first part of the workshop by the instructor on your own cloud hosted virtual machine. This guide provides all the necessary commands and tasks in this lab guide should be performed in order, as they might depend on files and packages installed beforehand.\n\n\n## CONFIDENTIAL\n\n### This material is owned by Network to Code, LLC.\n\nYou are NOT permitted to distribute the material, content, slides, labs, and other related material outside of the program.\n\nCopyright 2020, Network to Code, LLC.\n\n\n## Setting Up for Remote Development\n\nYou should perform this step together with your instructor at the beginning of the session. The goal here is to be able to perform all the subsequent lab tasks inside of a VSCode session running on the lab VM.\n\nStart up your VSCode, go to the Extensions tab, and ensure the \"Remote - SSH\" extension from Microsoft is installed. If you need to install it, type \"Remote\" in the search bar up top and locate it in the populated results below (VSCode needs to be able to access the Internet for this).\n\nYou will also need a compatible SSH client - the VSCode documentation provides instructions for all of the major platforms [here](https://code.visualstudio.com/docs/remote/troubleshooting#_installing-a-supported-ssh-client).\n\nWith the prerequisites installed, you should now have a green `><` sign in the bottom left corner of your VSCode window. You may click on it to open a selection of Remote-SSH actions.\n\n> You may also open the command palette (`Ctrl-Shift-P`) and type `remote-ssh`.\n> For a full list of shortcuts, go to File->Preferences->Keyboard Shortcuts.\n\nFirst, you need to set up your remote SSH host. Select `Remote-SSH: Open Configuration File...` and choose the first option, depending on your operating system it will look like `path/to/home/folder/.ssh/config`. In this file, add a new entry (replacing the IP address):\n\n```\nHost devenv-workshop-vm\n HostName 192.0.2.1\n User ntc\n```\n\nSave this file and close it. From the `Remote-SSH` menu, now select the `Connect to host...` action. In the list that appears, you should find `devenv-workshop-vm` - select it. A new VSCode window will open, asking you for the password (unless otherwise instructed, it is `ntc123`). This window is now fully remote, giving you access to the files on the remote host. \n\nIn the menu, open `File -> Add Folder to Workspace...`, then select `lab` under the `/home/ntc` path. The remote VSCode window may reopen, asking you to input the password again. You should now see the lab folder on the left-hand side `Explorer` panel. \n\nExpand the `lab` folder and open `lab_guide.md` from within. You may read it like this or use the `Markdown: Open Preview` option from the `Command Palette` (Ctrl-Shift-P or F1) to view an HTML render of the file.\n\nIf not already open, you may start a terminal inside this window by going to the `Terminal->New Terminal` menu item.\n\nCongratulations, you are all set up!\n\n### Backup option\n\n`!!!` Only use this if you cannot get VSCode + Remote SSH to work. `!!!`\n\nYou can replicate the same functionality using the following tools:\n\n- your SSH client of choice - [PuTTY](https://putty.org/), [SecureCRT](https://www.vandyke.com/products/securecrt/) etc.\n- your code editor of choice - [SublimeText3](https://www.sublimetext.com/), [VSCode](https://code.visualstudio.com/), [Notepad++](https://notepad-plus-plus.org/), VIM/nano etc.\n- a file sync client - [CyberDuck](https://cyberduck.io/) or [WinSCP](https://winscp.net/)\n\nYou should try to keep this lab guide and an SSH terminal on the lab VM side by side (or on separate monitors) to help you focus on the lab tasks.\n\n\n## Task 1 - Using Python Remotely\n\n### Step 1\n\nIn your terminal, ensure you are in the `/home/ntc/lab/` folder. Create a new folder here called `webserver` and change into it.\n\n```\nntc devenv-01 ~ $ cd /home/ntc/lab/\nntc devenv-01 ~/lab $ mkdir webserver\nntc devenv-01 ~/lab $ cd webserver/\nntc devenv-01 ~/lab/webserver $ \n```\n\n### Step 2\n\nCreate an `index.html` file with containing the following text: `<h1>Hello there!</h1>`. You may use VSCode for this or run the command shown below.\n\n```\nntc devenv-01 ~/lab/webserver $ echo '<h1>Hello there!</h1>' > index.html\n```\n\n### Step 3\n\nStart a simple python3 webserver. Here you are calling the `http.server` module directly from the command line, a very useful feature when you need to quickly start a development webserver.\n\n```\nntc devenv-01 ~/lab/webserver $ python3 -m http.server\nServing HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ...\n```\n\n### Step 4\n\nIn your web browser of choice, open the following website: `http://YOUR_VM_IP:8000` replacing your VM's IP as appropriate. You should now see a \"Hello there!\" message on the page.\n\n### Step 5\n\nThe webserver was started by using a module that ships with python. You will now create a separate python script that works as a web client, using a third-party library called `requests`.\n\nLeave the webserver running in the current terminal and open a new one. You may do this using the `Terminal -> New Terminal` menu or by clicking the `+` sign in the top right section of the terminal panel.\n\n### Step 6\n\nCreate a new folder called `webclient` inside of `/home/ntc/lab`, then change into it.\n\n```\nntc devenv-01 ~/lab $ mkdir webclient\nntc devenv-01 ~/lab $ cd webclient/\nntc devenv-01 ~/lab/webclient $ \n```\n\n### Step 7\n\nSince you want to keep your lab VM \"clean\", you decide to install the `requests` library inside of a python virtual environment. This also allows for easier future packaging of your application.\n\nCreate a `requirements.txt` file containing the word `requests`. This will tell `pip` what to install. Verify its contents and location as per the output below.\n\n```\nntc devenv-01 ~/lab/webclient $ cat requirements.txt \nrequests\n```\n\n### Step 8\n\nIn the `webclient` folder, create a new python virtual environment called `venv` and activate it. Confirm that the python interpreter is running out of this new environment.\n\n```\nntc devenv-01 ~/lab/webclient $ python3 -m venv venv\nntc devenv-01 ~/lab/webclient $ source venv/bin/activate\n(venv) ntc devenv-01 ~/lab/webclient $ which python\n/home/ntc/lab/webclient/venv/bin/python\n```\n\n### Step 9\n\nCheck what additional python packages are installed using `pip list`, then install your project's dependencies using `pip install -r requirements.txt`\n\n```\n(venv) ntc devenv-01 ~/lab/webclient $ pip list\nPackage Version\n------------- -------\npip 20.0.2 \npkg-resources 0.0.0 \nsetuptools 44.0.0 \n\n(venv) ntc devenv-01 ~/lab/webclient $ pip install -r requirements.txt \nCollecting requests\n Downloading requests-2.24.0-py2.py3-none-any.whl (61 kB)\n \|████████████████████████████████\| 61 kB 349 kB/s \nCollecting chardet<4,>=3.0.2\n Downloading chardet-3.0.4-py2.py3-none-any.whl (133 kB)\n \|████████████████████████████████\| 133 kB 27.9 MB/s \nCollecting certifi>=2017.4.17\n Downloading certifi-2020.6.20-py2.py3-none-any.whl (156 kB)\n \|████████████████████████████████\| 156 kB 46.2 MB/s \nCollecting urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1\n Downloading urllib3-1.25.10-py2.py3-none-any.whl (127 kB)\n \|████████████████████████████████\| 127 kB 54.9 MB/s \nCollecting idna<3,>=2.5\n Downloading idna-2.10-py2.py3-none-any.whl (58 kB)\n \|████████████████████████████████\| 58 kB 8.2 MB/s \nInstalling collected packages: chardet, certifi, urllib3, idna, requests\nSuccessfully installed certifi-2020.6.20 chardet-3.0.4 idna-2.10 requests-2.24.0 urllib3-1.25.10\n```\n\n### Step 10\n\nCreate a new file in the `/home/ntc/lab/webclient` folder called `get.py`. In it, place the following code:\n\n```py\nimport requests\n\nresponse=requests.get(url='http://localhost:8000')\n\nprint(response.text)\n```\n\n### Step 11\n\nMaking sure that you are still in the terminal that has the virtual environment active, execute the script using the `python3 get.py` interpreter. \n\n> You can always check whether the virtualenv is active by looking for the bash prompt (venv) prepended name or by using the `which python` command.\n\n```\n(venv) ntc devenv-01 ~/lab/webclient $ python3 get.py \n<h1>Hello there!</h1>\n```\n\nSuccess!\n\n\n## Task 2 - Automating Common Python Tasks\n\nSince running the `get.py` web client script requires a virtual environment with dependencies installed, it's common practice to use other tools to automate the creation, activation and updates of these dependencies.\n\nYou will use the `GNU Make` utility to manage the virtualenv and run the application. \n\n### Step 1\n\nIn the `/home/ntc/lab/webclient` folder, create a new file named `Makefile` and copy/paste in the following contents:\n\n```Makefile\n.PHONY: clean run\n\ndefault: run\n\nrun: venv\n . venv/bin/activate; python3 get.py\n\nvenv: venv/bin/activate\n\nvenv/bin/activate: requirements.txt\n test -d venv \|\| python3 -m venv venv\n . venv/bin/activate; pip3 install -Ur requirements.txt\n touch venv/bin/activate\n\nclean:\n rm -rf venv\n```\n\nIn VSCode, open the `Command Palette` (Ctrl-Shift-P) and select `Convert Indentation to Tabs`. Save the file.\n\n> Most code editors convert tabs to spaces by default, but Makefiles require tabs for indentation, otherwise they will not work.\n\n### Step 2 \n\nReview the makefile. It defines the following \"targets\" or actions:\n\n- run (the default): it activates the virtualenv and executes the `get.py` python script\n- venv (a shorcut for venv/bin/activate): it ensures that the virtualenv is created and the dependencies specified in the `requirements.txt` file are installed\n- clean: it removes the virtualenv\n\n### Step 3\n\nOpen a fresh terminal and navigate to the `/home/ntc/lab/webclient` folder. Do NOT activate the virtualenv!\n\n```\nntc devenv-01 ~ $ cd lab/webclient/\nntc devenv-01 ~/lab/webclient $\n```\n\n### Step 4\n\nUse the command `make` without any arguments. It will execute the `run` default target.\n\n```\nntc devenv-01 ~/lab/webclient $ make\n. venv/bin/activate; python3 get.py\n<h1>Hello there!</h1>\n```\n\n### Step 5\n\nRun the command `make clean` to delete the virtual environment. Confirm by using `ls`.\n\n```\nntc devenv-01 ~/lab/webclient $ make clean\nrm -rf venv\nntc devenv-01 ~/lab/webclient $ ls\nMakefile get.py requirements.txt\n```\n\n### Step 6\n\nNow run `make` again. It will detect that the virtualenv is missing, create it, and then run the script successfully.\n\n```\nntc devenv-01 ~/lab/webclient $ make\ntest -d venv \|\| python3 -m venv venv\n. venv/bin/activate; pip3 install -Ur requirements.txt\nCollecting requests\n Using cached requests-2.24.0-py2.py3-none-any.whl (61 kB)\nCollecting urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1\n Using cached urllib3-1.25.10-py2.py3-none-any.whl (127 kB)\nCollecting chardet<4,>=3.0.2\n Using cached chardet-3.0.4-py2.py3-none-any.whl (133 kB)\nCollecting idna<3,>=2.5\n Using cached idna-2.10-py2.py3-none-any.whl (58 kB)\nCollecting certifi>=2017.4.17\n Using cached certifi-2020.6.20-py2.py3-none-any.whl (156 kB)\nInstalling collected packages: urllib3, chardet, idna, certifi, requests\nSuccessfully installed certifi-2020.6.20 chardet-3.0.4 idna-2.10 requests-2.24.0 urllib3-1.25.10\ntouch venv/bin/activate\n. venv/bin/activate; python3 get.py\n<h1>Hello there!</h1>\n```\n\nFeel free to play around with the various make targets (i.e. run, clean, venv).\n\n\n## Task 3\n\nInvoke is a python task execution tool & library that offers a pythonic way of implementing make functionality.\n\nYou will use `invoke` to automate code formatting and linting for your webclient application. The `black` uncompromising python formatter and the linter `pylint` are already installed on the machine.\n\n### Step 1\n\nIn the `/home/ntc/lab/webclient` folder, execute the `black` formatter in check and diff mode. It should show you output as below if you did not modify the `get.py` code.\n\n```\nntc devenv-01 ~/lab/webclient $ black --check --diff get.py \n--- get.py 2020-08-06 20:02:29.024221 +0000\n+++ get.py 2020-08-06 20:39:26.787799 +0000\n@@ -1,6 +1,6 @@\n import requests\n \n-response=requests.get(url='http://localhost:8000')\n+response = requests.get(url=\"http://localhost:8000\")\n \n print(response.text)\n \nwould reformat get.py\nOh no! 💥 💔 💥\n1 file would be reformatted.\n```\n\nAs you can see, it would add some spacing around the `=` sign and convert the single quotes into double quotes.\n\n### Step 2\n\nIn the `/home/ntc/lab/webclient` folder, execute `pylint` against the `get.py` file. It should show you output as below:\n\n```\nntc devenv-01 ~/lab/webclient $ pylint get.py \n********** Module get\nget.py:3:8: C0326: Exactly one space required around assignment\nresponse=requests.get(url='http://localhost:8000')\n ^ (bad-whitespace)\nget.py:1:0: C0114: Missing module docstring (missing-module-docstring)\n\n------------------------------------------------------------------\nYour code has been rated at 3.33/10 (previous run: 3.33/10, +0.00)\n```\n\n### Step 3\n\nBefore fixing the issues, first create the equivalent of a Makefile for `invoke`. This is the `tasks.py` file (you will need to create it). In it, you define two tasks, one that runs `black` and the other that runs `pylint`, just as you did in the previous steps.\n\n```\nntc devenv-01 ~/lab/webclient $ cat tasks.py \nfrom invoke import task\n\n@task\ndef black(context):\n context.run(\"black --check --diff get.py\")\n\n@task\ndef pylint(context):\n context.run(\"pylint get.py\")\n```\n\n### Step 4\n\nNow run `invoke`, listing the tasks it supports.\n\n```\nntc devenv-01 ~/lab/webclient $ invoke --list\nAvailable tasks:\n\n black\n pylint\n\n```\n\n### Step 5\n\nAsk `invoke` to execute the `black` task.\n\n```\nntc devenv-01 ~/lab/webclient $ invoke black\n--- get.py 2020-08-06 20:02:29.024221 +0000\n+++ get.py 2020-08-06 20:47:49.437627 +0000\n@@ -1,6 +1,6 @@\n import requests\n \n-response=requests.get(url='http://localhost:8000')\n+response = requests.get(url=\"http://localhost:8000\")\n \n print(response.text)\n \nwould reformat get.py\nOh no! 💥 💔 💥\n1 file would be reformatted.\n```\n\n### Step 6\n\nAsk `invoke` to execute the `pylint` task.\n\n```\nntc devenv-01 ~/lab/webclient $ invoke pylint\n********* Module get\nget.py:3:8: C0326: Exactly one space required around assignment\nresponse=requests.get(url='http://localhost:8000')\n ^ (bad-whitespace)\nget.py:1:0: C0114: Missing module docstring (missing-module-docstring)\n\n------------------------------------------------------------------\nYour code has been rated at 3.33/10 (previous run: 3.33/10, +0.00)\n```\n\n### Step 7\n\nLet's fix the code. Let `black` actually reformat the code, instead of reporting the changes it would make. Run the command `black get.py`.\n\n```\nntc devenv-01 ~/lab/webclient $ black get.py \nreformatted get.py\nAll done! ✨ 🍰 ✨\n1 file reformatted.\n```\n\n> Remember: if you run black without any parameters, it will reformat the files without asking any questions.\n\n### Step 8\n\nRun `invoke black` again to check that it now succeeds.\n\n```\nntc devenv-01 ~/lab/webclient $ invoke black\nAll done! ✨ 🍰 ✨\n1 file would be left unchanged.\n```\n\nIt is now, indeed, happy. Well done!\n\n\n\n\n\n\n\n\n\n## Task 4 - Using Docker Commands\n\nYou are now going to practice using some of the most common docker commands to perform operations on a docker host - that is, a VM that can build and run containers.\n\nTools and applications are nowadays also distributed as containers, making them more portable and reducing the time it takes to get them running. The goal of this task is for you to become comfortable at consuming such applications and, later on, even build a container of your own.\n\n\n### Step 1\n\nIn a terminal on the lab VM, confirm your docker version and test that the daemon is running. The `docker` command connects to the local docker daemon running on the lab VM.\n\n```\nntc devenv-01 ~/lab $ docker -v\nDocker version 19.03.12, build 48a66213fe\n\nntc devenv-01 ~/lab $ docker ps\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n```\n\n> The `docker ps` command is the short version of the `docker container ls` command and shows a list of all the running (and optionally stopped) containers.\n\n\n### Step 2\n\nRun the command `docker run ubuntu echo Hello World!`. It will download and run the command `echo Hello World!` inside of a container image called `ubuntu`.\n\n```\nntc devenv-01 ~/lab $ docker run ubuntu echo Hello World!\nUnable to find image 'ubuntu:latest' locally\nlatest: Pulling from library/ubuntu\n3ff22d22a855: Pull complete \ne7cb79d19722: Pull complete \n323d0d660b6a: Pull complete \nb7f616834fd0: Pull complete \nDigest: sha256:5d1d5407f353843ecf8b16524bc5565aa332e9e6a1297c73a92d3e754b8a636d\nStatus: Downloaded newer image for ubuntu:latest\nHello World!\n```\n\n> By default, if you don't explicitly specify a registry address, the docker command will connect to `https://hub.docker.com/`, a public repository of containers. In the example above, it downloads [this container](https://hub.docker.com/_/ubuntu).\n\n### Step 3\n\nThe `ubuntu` image is now stored locally in docker's image repository on disk. Use the `docker image ls` command to view its contents.\n\n```\nntc devenv-01 ~/lab $ docker image ls\nREPOSITORY TAG IMAGE ID CREATED SIZE\nubuntu latest 1e4467b07108 13 days ago 73.9MB\n```\n\n> You can see container image names, sizes, and their tag (or version).\n\n### Step 4\n\nContainers can contain any programs, be it short-lived shell commands or long-lived services. You ran an `echo` command in the `bash` shell, so after it printed the message the container finished its execution. Run `docker ps -a` to view a list of all (running and stopped) containers.\n\n```\nntc devenv-01 ~/lab $ docker ps -a\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n73cd9fe02d18 ubuntu \"echo Hello World!\" 6 minutes ago Exited (0) 6 minutes ago stupefied_gagarin\n```\n\n> `docker ps` only shows running containers by default, of which now you have none. Try it!\n\n### Step 5\n\nContainers that finished their execution are still there, as you may want to inspect them, do operations with their filesystems, or restart them. They take up space on disk though, so if you are sure you don't need them any more, you can use the `docker container prune` command to clean up.\n\n```\nntc devenv-01 ~/lab $ docker container prune\nWARNING! This will remove all stopped containers.\nAre you sure you want to continue? [y/N] y\nDeleted Containers:\n73cd9fe02d187da994310f933fc2d3c99b572cca685f148ff79dc6c7f421b5cc\n\nTotal reclaimed space: 0B\nntc devenv-01 ~/lab $ docker ps -a\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n```\n\n### Step 6\n\nWhen you want to run multiple commands in a container, it is common to start a shell (similar to how you start in a terminal on a remote host). In order to interact with this shell from the command line, you need to tell docker to start an interactive terminal `-it`. Optionally, you can provide the `--rm` flag to tell docker to delete (or prune) the container once it finishes running.\n\nRun the `docker run -it --rm ubuntu bash` command. When you are done with the shell, type exit to return to the docker host.\n\n```\nntc devenv-01 ~/lab $ docker run -it --rm ubuntu bash\nroot@0a83b24e5ec4:/# \nroot@0a83b24e5ec4:/# \nroot@0a83b24e5ec4:/# echo Hello World!\nHello World!\nroot@0a83b24e5ec4:/# exit\nexit\nntc devenv-01 ~/lab $\n```\n\n### Step 7\n\nIf you want the container to keep running in the background, you can provide the `-d` or detach flag. Optionally, you can give your running container a name (it must be unique!).\n\nRun the `docker run -itd --name test ubuntu bash` command now.\n\n```\nntc devenv-01 ~/lab $ docker run -itd --name test ubuntu bash\ncd68687c0816b9fb2eb07f27d2351c60e4bc8e9caaeb2cc6531a984b43c64f84\nntc devenv-01 ~/lab $\n```\n\nThe result is a unique id of the running container and the docker command returns you to your shell, while the container is still executing in the background. This is commonly done with containers that provide services which are not interactive.\n\n### Step 8\n\nRun the `docker ps` command. You will now see your `test` container in the running state.\n\n```\nntc devenv-01 ~/lab $ docker ps\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\ncd68687c0816 ubuntu \"bash\" 2 seconds ago Up 1 second test\n```\n\n### Step 9\n\nTo execute commands in an already running container, use the `docker exec` command. You may run one-shot commands or interactive (`-it`) sessions as you can see below for `bash`.\n\n```\nntc devenv-01 ~/lab $ docker exec test echo Hello again!\nHello again!\n\nntc devenv-01 ~/lab $ docker exec -it test bash\nroot@cd68687c0816:/# #This is a new shell\nroot@cd68687c0816:/# ps a \n PID TTY STAT TIME COMMAND\n 1 pts/0 Ss+ 0:00 bash\n 63 pts/1 Ss 0:00 bash\n 71 pts/1 R+ 0:00 ps a\nroot@cd68687c0816:/# exit\nexit\nntc devenv-01 ~/lab $\n```\n\n> In this case you know the name of your container, but if you didn't, you can find out the name or the ID from the `docker ps` output.\n\n> The very first command you start a container with will always be PID 1. This is the first process and, when it ends, the container execution ends as well. Your second bash shell has a PID of 63 and will stop when you type `exit`\n\n### Step 10\n\nYou can copy files from and to a container using the `docker cp` command. Copy the `webserver/index.html` file into the `test` container and then check it is there.\n\n```\nntc devenv-01 ~/lab $ docker cp webserver/index.html test:/index.html\nntc devenv-01 ~/lab $ docker exec test cat /index.html\n<h1>Hello there!</h1>\nntc devenv-01 ~/lab $\n```\n\n### Step 11\n\nIf you want to stop a running container, you may use the `docker stop` command. Run the commands as shown below.\n\n```\nntc devenv-01 ~/lab $ docker ps\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\ncd68687c0816 ubuntu \"bash\" 21 minutes ago Up 21 minutes test\n\nntc devenv-01 ~/lab $ docker stop test\ntest\n\nntc devenv-01 ~/lab $ docker ps\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n```\n\n### Step 12\n\nYou can start a stopped container again. Run the `docker start test` command, then look at the output of `docker ps`.\n\n```\nntc devenv-01 ~/lab $ docker start test\ntest\n\nntc devenv-01 ~/lab $ docker ps\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\ncd68687c0816 ubuntu \"bash\" 23 minutes ago Up 1 second test\n```\n\n> Docker still has the full configuration and state of the container as it was not deleted.\n\n### Step 13\n\nSince this is the same container as earlier, try to get the contents of the `/index.html` file.\n\n```\nntc devenv-01 ~/lab $ docker exec test cat /index.html\n<h1>Hello there!</h1>\n```\n\n### Step 14\n\nNow stop and delete your `test` container by running the commands shown below.\n\n```\ntc devenv-01 ~/lab $ docker stop test\ntest\nntc devenv-01 ~/lab $ docker rm test\ntest\nntc devenv-01 ~/lab $ docker ps -a\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n```\n\n> Your container named `test` is now gone forever. Any changes from the `ubuntu` image, such as copied files, are also lost. Containers as ephemeral by design and you need explicit actions to preserve state.\n\n### Step 15\n\nStart a new `ubuntu` container named `test` and check its filesystem. As expected, the `/index.html` is not there anymore, since you started the container from the base unmodified image.\n\n```\nntc devenv-01 ~/lab $ docker run -it --rm ubuntu bash\n\nroot@98a1f4a0b5d7:/# cat /index.html\ncat: /index.html: No such file or directory\nroot@98a1f4a0b5d7:/# exit\nexit\n\nntc devenv-01 ~/lab $\n```\n\n\n\n\n## Task 5 - Containerizing a Python Web Server\n\nOne common usage for docker containers is to package applications for distribution and portability. Here, you will use a different container image called `python` to run your simple webserver from within a container and serve the `index.html` page.\n\n### Step 1\n\nRetrieve version (or tag) `3.8-slim` of the `python` container image using the `docker pull python:3.8-slim` command.\n\n```\nntc devenv-01 ~/lab $ docker pull python:3.8-slim\n3.8-slim: Pulling from library/python\nbf5952930446: Pull complete \n385bb58d08e6: Pull complete \nab14b629693d: Pull complete \n7a5d07f2fd13: Pull complete \n56745e40505a: Pull complete \nDigest: sha256:f7edd1bb431a224e7f4f3e23cbb22738e82f4895a6d28f86294ce006177360c3\nStatus: Downloaded newer image for python:3.8-slim\ndocker.io/library/python:3.8-slim\n```\n\n### Step 2\n\nTest start a new container using this image as show below. Notice you get dropped into a `python 3.8` interpreter by default.\n\n```\nntc devenv-01 ~/lab $ docker run -it python:3.8-slim \nPython 3.8.5 (default, Aug 4 2020, 16:24:08) \n[GCC 8.3.0] on linux\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> exit()\nntc devenv-01 ~/lab $\n```\n\n### Step 3\n\nChange to the `/home/ntc/lab` folder. Check that you have the `index.html` file in the `/home/ntc/lab/webserver` folder.\n\n```\nntc devenv-01 ~/lab $ cd /home/ntc/lab/\nntc devenv-01 ~/lab $ cat webserver/index.html \n<h1>Hello there!</h1>\n```\n\n### Step 4\n\nRun the following command to start a containerized python webserver and then confirm it is running.\n\n```\nntc devenv-01 ~/lab $ docker run -d --rm --name pyweb -v $PWD/webserver:/webserver -p8888:8000 python:3.8-slim python3 -m http.server --directory /webserver/\n53f1bc49d06df7f0bedbd08e49ff348dd32f93ea01dde87046bff4797f337b8b\n\nntc devenv-01 ~/lab $ docker ps\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n53f1bc49d06d python:3.8-slim \"python3 -m http.ser…\" 3 seconds ago Up 1 second 0.0.0.0:8888->8000/tcp pyweb\n```\n\nLet's disect the command:\n\n- `-d` start container in detached mode (run it as a service)\n- `--rm` delete the container once it stops\n- `--name pyweb` give it the name `pyweb`\n- `-v $PWD/webserver:/webserver` mount the local `webserver` folder contents in the container at `/webserver`\n- `-p8888:8000` create port forwarding to publish the container internal port 8000 to the docker host's port 8888\n- `python:3.8-slim` the container image\n- `python3 -m http.server --directory /webserver/` the command to start a python web server\n\nIn your web browser of choice, open the following website: `http://YOUR_VM_IP:8888` replacing your VM's IP as appropriate. You should now see a \"Hello there!\" message on the page.\n\n### Step 5\n\nOpen the `/home/ntc/lab/webserver/index.html` file in your editor and change the message to \"Hello from Docker!\". Save the file and refresh your web browser `http://YOUR_VM_IP:8888` page.\n\nSince this file is mounted into the container, the change will be instantly reflected and you should see the new message displayed.\n\nCongratulations, you have containerized your first application!\n\n\n\n## Task 6 - Create a Network Development Container Image\n\nYou will now get started on the path of creating your own container images pre-loaded with libraried and tools that you often use. Here, you will build upon the `python` docker container image to create a `netdev` container that has `ansible` and a few other network automation libraries (netmiko, napalm, textfsm) installed.\n\n### Step 1\n\nCreate the `/home/ntc/lab/netdev` folder and change into it.\n\n```\nntc devenv-01 ~/lab $ mkdir -p /home/ntc/lab/netdev\nntc devenv-01 ~/lab $ cd /home/ntc/lab/netdev\nntc devenv-01 ~/lab/netdev $\n```\n\n### Step 2\n\nCreate a new file in the `netdev` folder named `Dockerfile`. It should have the following contents:\n\n```\nntc devenv-01 ~/lab/netdev $ cat Dockerfile \nFROM python:3.8-slim\nLABEL maintainer=\"Yours Truly\" description=\"Python based tooling\" version=\"0.1\"\n\nRUN pip3 install --no-cache-dir ansible netmiko napalm textfsm\nCMD [\"/bin/bash\"]\n```\n\n### Step 3\n\nRun the command `docker build -t netdev:0.1 .` to build a new container image named `netdev` and tag it with version `0.1`. Mind the dot at the end of the command!\n\nYou will now see the build process that executes the commands as specified in the Dockerfile and produces a container image at the end if successful.\n\n```\nntc devenv-01 ~/lab/netdev $ docker build -t netdev:0.1 .\nSending build context to Docker daemon 2.048kB\nStep 1/4 : FROM python:3.8-slim\n ---> 07ea617545cd\nStep 2/4 : LABEL maintainer=\"Yours Truly\" description=\"Python based tooling\" version=\"0.1\"\n ---> Running in 99a9ca79ed31\nRemoving intermediate container 99a9ca79ed31\n ---> 1d0a17bf2d07\nStep 3/4 : RUN pip3 install --no-cache-dir ansible netmiko napalm textfsm\n ---> Running in dcecc818fb84\nCollecting ansible\n Downloading ansible-2.9.11.tar.gz (14.2 MB)\nCollecting netmiko\n Downloading netmiko-3.2.0-py2.py3-none-any.whl (157 kB)\nCollecting napalm\n Downloading napalm-3.1.0-py2.py3-none-any.whl (229 kB)\nCollecting textfsm\n Downloading textfsm-1.1.0-py2.py3-none-any.whl (37 kB)\nCollecting jinja2\n Downloading Jinja2-2.11.2-py2.py3-none-any.whl (125 kB)\nCollecting PyYAML\n Downloading PyYAML-5.3.1.tar.gz (269 kB)\nCollecting cryptography\n Downloading cryptography-3.0-cp35-abi3-manylinux2010_x86_64.whl (2.7 MB)\nRequirement already satisfied: setuptools>=38.4.0 in /usr/local/lib/python3.8/site-packages (from netmiko) (49.2.1)\nCollecting scp>=0.13.2\n Downloading scp-0.13.2-py2.py3-none-any.whl (9.5 kB)\nCollecting paramiko>=2.4.3\n Downloading paramiko-2.7.1-py2.py3-none-any.whl (206 kB)\nCollecting pyserial\n Downloading pyserial-3.4-py2.py3-none-any.whl (193 kB)\nCollecting junos-eznc>=2.2.1\n Downloading junos-eznc-2.5.1.tar.gz (154 kB)\nCollecting future\n Downloading future-0.18.2.tar.gz (829 kB)\nCollecting cffi>=1.11.3\n Downloading cffi-1.14.1-cp38-cp38-manylinux1_x86_64.whl (409 kB)\nCollecting ciscoconfparse\n Downloading ciscoconfparse-1.5.19-py3-none-any.whl (93 kB)\nCollecting netaddr\n Downloading netaddr-0.8.0-py2.py3-none-any.whl (1.9 MB)\nCollecting pyeapi>=0.8.2\n Downloading pyeapi-0.8.3.tar.gz (137 kB)\nCollecting lxml>=4.3.0\n Downloading lxml-4.5.2-cp38-cp38-manylinux1_x86_64.whl (5.4 MB)\nCollecting requests>=2.7.0\n Downloading requests-2.24.0-py2.py3-none-any.whl (61 kB)\nCollecting six\n Downloading six-1.15.0-py2.py3-none-any.whl (10 kB)\nCollecting MarkupSafe>=0.23\n Downloading MarkupSafe-1.1.1-cp38-cp38-manylinux1_x86_64.whl (32 kB)\nCollecting pynacl>=1.0.1\n Downloading PyNaCl-1.4.0-cp35-abi3-manylinux1_x86_64.whl (961 kB)\nCollecting bcrypt>=3.1.3\n Downloading bcrypt-3.1.7-cp34-abi3-manylinux1_x86_64.whl (56 kB)\nCollecting ncclient>=0.6.3\n Downloading ncclient-0.6.8.tar.gz (117 kB)\nCollecting yamlordereddictloader\n Downloading yamlordereddictloader-0.4.0.tar.gz (3.3 kB)\nCollecting pyparsing\n Downloading pyparsing-2.4.7-py2.py3-none-any.whl (67 kB)\nCollecting transitions\n Downloading transitions-0.8.2-py2.py3-none-any.whl (76 kB)\nCollecting ntc_templates\n Downloading ntc_templates-1.5.0-py3-none-any.whl (254 kB)\nCollecting pycparser\n Downloading pycparser-2.20-py2.py3-none-any.whl (112 kB)\nCollecting colorama\n Downloading colorama-0.4.3-py2.py3-none-any.whl (15 kB)\nCollecting dnspython\n Downloading dnspython-2.0.0-py3-none-any.whl (208 kB)\nCollecting passlib\n Downloading passlib-1.7.2-py2.py3-none-any.whl (507 kB)\nCollecting chardet<4,>=3.0.2\n Downloading chardet-3.0.4-py2.py3-none-any.whl (133 kB)\nCollecting idna<3,>=2.5\n Downloading idna-2.10-py2.py3-none-any.whl (58 kB)\nCollecting certifi>=2017.4.17\n Downloading certifi-2020.6.20-py2.py3-none-any.whl (156 kB)\nCollecting urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1\n Downloading urllib3-1.25.10-py2.py3-none-any.whl (127 kB)\nBuilding wheels for collected packages: ansible, PyYAML, junos-eznc, future, pyeapi, ncclient, yamlordereddictloader\n Building wheel for ansible (setup.py): started\n Building wheel for ansible (setup.py): finished with status 'done'\n Created wheel for ansible: filename=ansible-2.9.11-py3-none-any.whl size=16176769 sha256=31b32a79e61708e9eefa87072490cf73e4f6dd91ff71e340576c3903d9aa1f60\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/96/b5/fc/646cc0302950f9dd85ce04f1108809447c7c1c20ebf23f587b\n Building wheel for PyYAML (setup.py): started\n Building wheel for PyYAML (setup.py): finished with status 'done'\n Created wheel for PyYAML: filename=PyYAML-5.3.1-cp38-cp38-linux_x86_64.whl size=44617 sha256=4481668e74b87ce7437c0bab4445e1542b5604c96ec697b49150cc55ececdcb2\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/13/90/db/290ab3a34f2ef0b5a0f89235dc2d40fea83e77de84ed2dc05c\n Building wheel for junos-eznc (setup.py): started\n Building wheel for junos-eznc (setup.py): finished with status 'done'\n Created wheel for junos-eznc: filename=junos_eznc-2.5.1-py3-none-any.whl size=190451 sha256=ac4e0a41ee9a9999dd92f240dbd6175c87e2b99517c1181dcb48044371afe99f\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/f0/4d/a0/fb9cbe8e782460ad05434b83389823c990f0ff12758700d44e\n Building wheel for future (setup.py): started\n Building wheel for future (setup.py): finished with status 'done'\n Created wheel for future: filename=future-0.18.2-py3-none-any.whl size=491058 sha256=5d78a73e00494f3141a94fa759b509b80f3d7ca911c9d6257be94804d42b247a\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/8e/70/28/3d6ccd6e315f65f245da085482a2e1c7d14b90b30f239e2cf4\n Building wheel for pyeapi (setup.py): started\n Building wheel for pyeapi (setup.py): finished with status 'done'\n Created wheel for pyeapi: filename=pyeapi-0.8.3-py3-none-any.whl size=90262 sha256=8ef9fdb2e2f203eb897faf88a101e510509ec3ae799c9e394b1636ffb565fce9\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/d1/56/be/60a2a048f7510cc33f862dafa06471e928494ebdf0a0558ec0\n Building wheel for ncclient (setup.py): started\n Building wheel for ncclient (setup.py): finished with status 'done'\n Created wheel for ncclient: filename=ncclient-0.6.8-py2.py3-none-any.whl size=103305 sha256=084051777bba962dc3c5393575964dc667bdf7d7eab4d3df91aaad43dbabefa3\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/02/03/15/2fc281ba0891ebe5f1632a0bdfc6c96e6b023baf5270e715e8\n Building wheel for yamlordereddictloader (setup.py): started\n Building wheel for yamlordereddictloader (setup.py): finished with status 'done'\n Created wheel for yamlordereddictloader: filename=yamlordereddictloader-0.4.0-py3-none-any.whl size=4052 sha256=51d614302245f4b6b2d90089d13de3fe6e8bd6d9072796f461180098056a07bd\n Stored in directory: /tmp/pip-ephem-wheel-cache-docsw7ec/wheels/50/9a/6f/9cb3312fd9cd01ea93c3fdc1dbee95f5fa0133125d4c7cb09a\nSuccessfully built ansible PyYAML junos-eznc future pyeapi ncclient yamlordereddictloader\nInstalling collected packages: MarkupSafe, jinja2, PyYAML, pycparser, cffi, six, cryptography, ansible, future, textfsm, pynacl, bcrypt, paramiko, scp, pyserial, netmiko, lxml, ncclient, netaddr, yamlordereddictloader, pyparsing, transitions, ntc-templates, junos-eznc, colorama, dnspython, passlib, ciscoconfparse, pyeapi, chardet, idna, certifi, urllib3, requests, napalm\nSuccessfully installed MarkupSafe-1.1.1 PyYAML-5.3.1 ansible-2.9.11 bcrypt-3.1.7 certifi-2020.6.20 cffi-1.14.1 chardet-3.0.4 ciscoconfparse-1.5.19 colorama-0.4.3 cryptography-3.0 dnspython-2.0.0 future-0.18.2 idna-2.10 jinja2-2.11.2 junos-eznc-2.5.1 lxml-4.5.2 napalm-3.1.0 ncclient-0.6.8 netaddr-0.8.0 netmiko-3.2.0 ntc-templates-1.5.0 paramiko-2.7.1 passlib-1.7.2 pycparser-2.20 pyeapi-0.8.3 pynacl-1.4.0 pyparsing-2.4.7 pyserial-3.4 requests-2.24.0 scp-0.13.2 six-1.15.0 textfsm-1.1.0 transitions-0.8.2 urllib3-1.25.10 yamlordereddictloader-0.4.0\nRemoving intermediate container dcecc818fb84\n ---> c691651da2be\nStep 4/4 : CMD [\"/bin/bash\"]\n ---> Running in 8cf9db0ab6db\nRemoving intermediate container 8cf9db0ab6db\n ---> 83e955040d82\nSuccessfully built 83e955040d82\nSuccessfully tagged netdev:0.1\n```\n\n### Step 4\n\nCheck the list of docker images using `docker image ls`. Notice you now have a `netdev` image.\n\n```\nntc devenv-01 ~/lab/netdev $ docker image ls\nREPOSITORY TAG IMAGE ID CREATED SIZE\nnetdev 0.1 83e955040d82 About a minute ago 281MB\npython 3.8-slim 07ea617545cd 2 days ago 113MB\nubuntu latest 1e4467b07108 13 days ago 73.9MB\n```\n\n### Step 5\n\nCreate a new container from the freshly baked `netdev:0.1` image and try running `ansible` inside of it!\n\n```\nntc devenv-01 ~/lab/netdev $ docker run -it --rm netdev:0.1\nroot@1d0325082173:/# ansible --version\nansible 2.9.11\n config file = None\n configured module search path = ['/root/.ansible/plugins/modules', '/usr/share/ansible/plugins/modules']\n ansible python module location = /usr/local/lib/python3.8/site-packages/ansible\n executable location = /usr/local/bin/ansible\n python version = 3.8.5 (default, Aug 4 2020, 16:24:08) [GCC 8.3.0]\n```\n\nCongratulations, your new network development tools container is functional!\n\n> In the future you may want to share this container image with your colleagues. You may share the Dockerfile so they can build their own from it or push the image to a Docker registry.\n" }, { "alpha_fraction": 0.5833333134651184, "alphanum_fraction": 0.5865384340286255, "avg_line_length": 22, "blob_id": "b8b80609094a30c756c22eb52bf6d07a49452618", "content_id": "8cf053d1fbbee67147dbe2b8388ecf279bc42a0f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 312, "license_type": "no_license", "max_line_length": 68, "num_lines": 13, "path": "/challenges/09-data-structures/files/netbox_device.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "import json\r\n\r\n\r\ndef pp(data):\r\n print(json.dumps(data, indent=2))\r\n\r\n\r\nif __name__ == \"__main__\":\r\n with open(\"nb_device.json\") as fin:\r\n nb_device = json.load(fin)\r\n\r\n print(\"Loaded JSON data into 'nb_device' variable.\\n\")\r\n print(\"You can use 'pp(nb_device)' to display all of the data.\")\r\n" }, { "alpha_fraction": 0.7514451146125793, "alphanum_fraction": 0.7528901696205139, "avg_line_length": 60.488887786865234, "blob_id": "9f8a5ecac983089d79f325f28b9efad3b5b278d4", "content_id": "c588159198187b40925d6bb4e7d0aff1dd37ff7f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 2768, "license_type": "no_license", "max_line_length": 289, "num_lines": 45, "path": "/challenges/05-docker-tools/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge - Building a Docker Tools Container\n\nThe goal of this exercise is to build a new Docker container image with a few network automation tools and streamline the process by using either Make or Invoke.\n\n## Exercise Overview\n\n### Prerequisites\n\nYou will need to have [Docker installed](https://www.docker.com/get-started) and either Make (in WSL / Linux VM) or Python Invoke (any OS). \n\n> Note: A cleaner option is to use a Virtual Machine and install everything you need in there - you can start from an Ubuntu Desktop live CD (to have a Graphical Environment) or just via CLI with Ubuntu Server.\n\n### Tasks\n\n1. Ensure your Docker environment is working by `pulling` and `running` the official [Python docker image](https://hub.docker.com/_/python).\n2. Create a `Dockerfile` to build a new Docker image starting from the `python:3` base.\n - Using a `requirements.txt` file, install the following python packages: `ansible, netmiko, napalm, ansible-lint, yamllint, black, netaddr, jmespath, requests`\n - Using the package manager (`apt-get`), install the following packages: `git, tree, curl, sshpass`\n - Add metadata (labels) for your new image: `maintainer, description, version`\n - Set the default command of the container to be `/bin/bash` (i.e. what's executed when you run the container)\n3. Create a Makefile or an Invoke tasks file to perform the following tasks:\n - Build the container image from the Dockerfile (e.g. `make container`)\n - Delete the container image (e.g. `make clean-images`)\n - Run a fresh container with an interactive command line (bash) (e.g. `make run`)\n - Delete all stopped containers (e.g. `make clean-stopped`)\n\n> Hint: Run bash in the base container and validate your commands manually first. When you're happy that they work (in a non-interactive manner for the build process!) you can put them in the Dockerfile.\n\n> Note: You should test that packages you installed in the container actually work - for example, try writing a simple Ansible playbook and then run it from the container. Remember, you can copy files to and from a container (be it running or stopped), but images are immutable once built.\n\nYour solution should include these files: Dockerfile, Makefile/tasks.py and requirements.txt\n\n### Useful links\n\n- [Dockerfile Reference](https://docs.docker.com/engine/reference/builder/)\n- [Docker Hub Python Image](https://hub.docker.com/_/python)\n- [Make Docs](https://www.gnu.org/software/make/manual/make.html)\n- [Invoke Docs](https://docs.pyinvoke.org/en/stable/index.html)\n\n### Reference Enablement Material\n\n- Developer Tooling & Navigation\n- Development Environments - Lab Guide\n\n> Note: Recordings of the relevant sessions can be found online at: https://training.networktocode.com/ \n" }, { "alpha_fraction": 0.44490644335746765, "alphanum_fraction": 0.6569646596908569, "avg_line_length": 15.527273178100586, "blob_id": "443d0076141395e5a6f86291c0ff831ecbff7e6b", "content_id": "35b2a3b51d9319da564414f90604e2ce726fba06", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 962, "license_type": "no_license", "max_line_length": 24, "num_lines": 55, "path": "/challenges/10-batfish/files/requirements.txt", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "appdirs==1.4.3\r\nastroid==2.3.3\r\nattrs==20.3.0\r\nbidict==0.21.2\r\nCacheControl==0.12.6\r\ncertifi==2019.11.28\r\ncffi==1.14.5\r\nchardet==3.0.4\r\nclick==7.1.2\r\ncolorama==0.4.3\r\nConfigArgParse==0.15.2\r\ncontextlib2==0.6.0\r\ncryptography==3.4.6\r\ndeepdiff==5.2.3\r\nDeprecated==1.2.11\r\ndistlib==0.3.0\r\ndistro==1.4.0\r\nhtml5lib==1.0.1\r\nidna==2.8\r\nipaddr==2.2.0\r\nipaddress==1.0.23\r\nisort==4.3.21\r\nJinja2==2.11.3\r\nlazy-object-proxy==1.4.3\r\nlockfile==0.12.2\r\nMarkupSafe==1.1.1\r\nmccabe==0.6.1\r\nmsgpack==0.6.2\r\nnetconan==0.12.1\r\nnumpy==1.20.1\r\nordered-set==4.0.2\r\npackaging==20.3\r\npandas==1.2.2\r\npasslib==1.7.4\r\npathspec==0.8.1\r\npep517==0.8.2\r\nprogress==1.5\r\npybfe==2020.2.11.935\r\npycparser==2.20\r\npylint==2.4.4\r\npyparsing==2.4.6\r\npython-dateutil==2.8.1\r\npython-dotenv==0.12.0\r\npytoml==0.1.21\r\npytz==2021.1\r\nPyYAML==5.4.1\r\nrequests==2.22.0\r\nrequests-toolbelt==0.9.1\r\nretrying==1.3.3\r\nsimplejson==3.17.2\r\nsix==1.14.0\r\nurllib3==1.25.8\r\nwebencodings==0.5.1\r\nwrapt==1.12.1\r\nyamllint==1.21.0" }, { "alpha_fraction": 0.7062045931816101, "alphanum_fraction": 0.7258249521255493, "avg_line_length": 23.53125, "blob_id": "3f26d0e9ced6d9c158948f1436d618cf8862a75a", "content_id": "bd85ce97c7a735b07354ba4e4ac131e8d7120017", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 7873, "license_type": "no_license", "max_line_length": 185, "num_lines": 320, "path": "/workshops/jinja2-deep-dive-day1/lab_guides/lab04_jinja_in_python.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Lab 04 - Jinja template rendering with Python\n\nGoals of this lab:\n\n- Practice using the `jinja2` package for rendering template.\n- Practice using the `FileSystemLoader` mode of loading templates.\n- Learn how to use the `Environment` object.\n- Practice customizing the `Environment` object to change the rendering behavior.\n\n## Task 01\n\n### Step 1\n\nCopy the below Python code into the file called `j2_string_template.py` in `python` directory.\n\n```python\nfrom jinja2 import Template\n\ndata = {\n \"name\": \"waw-rtr-core-01\",\n \"location\": \"Warsaw\",\n}\n\ntemplate = \"Device {{ name }} is located in {{ location }}.\"\n\nj2_template = Template(template)\n\nprint(j2_template.render(data))\n```\n\n### Step 2\n\nRun the program using the below command:\n\n```python j2_string_template.py```\n\n### Step 3\n\nThis is the simplest example of a Python program rendering template with Jinja.\n\nRead through the code and see if you can follow the logic. Then you can read the short walk-through below.\n\n#### Code Walk-through\n\nYou created a new `Template` object using the template stored in the string.\n\nYou then passed the dictionary with variables to the `render()` method of the `Template` object.\n\nNotice that we did not define a Jinja Environment. When using the `Template` object directly, a shared `Environment` object is created for us by Jinja in the background.\n\nThis way of rendering templates is great for quick testing but does not allow us to customize our environment.\n\n## Task 02\n\n### Step 1\n\nChange into the `python` directory and create two new directories:\n\n```\nmkdir my_vars\nmkdir my_templates\n```\n\n### Step 2\n\nCopy the data and template from Lab 01, tasks 1 and 2.\n\nYour directories should look like so:\n\n```\ntree my_vars/\nmy_vars/\n├── lab01-task1.yml\n└── lab01-task2.yml\n\ntree my_templates/\nmy_templates/\n├── lab01-task1.j2\n└── lab01-task2.j2\n```\n\n### Step 3\n\nCopy the below Python code into the file called `j2_file_loader.py` in `python` directory.\n\n```python\nfrom jinja2 import Environment, FileSystemLoader\nfrom pathlib import Path\nimport yaml\n\nTEMPLATES_DIR = \"./my_templates\"\nVARS_DIR = Path(\"./my_vars\")\n\n\ndef main():\n vars_file = \"lab01-task1.yml\"\n template_name = \"lab01-task1.j2\"\n\n with Path(VARS_DIR / vars_file).open(mode=\"r\", encoding=\"utf8\") as file_in:\n template_data = yaml.safe_load(file_in)\n\n j2_env = Environment(loader=FileSystemLoader(TEMPLATES_DIR))\n\n j2_template = j2_env.get_template(template_name)\n rendered_template = j2_template.render(template_data)\n\n print(rendered_template)\n\n\nif __name__ == \"__main__\":\n main()\n```\n\n## Step 4\n\nRun the program using the below command:\n\n```python j2_file_loader.py```\n\nYou should see the output of the template `lab01-task1.j2` rendered with variables from `lab01-task1.yml`.\n\n# Step 5\n\nChange the below lines:\n\n```python\n vars_file = \"lab01-task1.yml\"\n template_name = \"lab01-task1.j2\"\n```\n\nTo:\n\n```python\n vars_file = \"lab01-task2.yml\"\n template_name = \"lab01-task2.j2\"\n```\n\n# Step 6\n\nRun the program using the below command:\n\n```python j2_file_loader.py```\n\nYou should see the output of the template `lab02-task1.j2` rendered with variables from `lab02-task1.yml`.\n\n# Step 7\n\nThis program uses Jinja `Environment` and `FileSystemLoader` objects to load templates stored in files in the specified location.\n\nYou get more flexibility when choosing this approach. File names can be decided dynamically at the runtime, and Jinja Environment can now be customized as needed.\n\nRead through the code and see if you can follow the logic. Then you can read the short walk-through below.\n\n#### Code Walk-through\n\nYou created a new `Environment` and specified template loader as `FileSystemLoader`. `FileSystemLoader` takes a path to the directory on the disk as an argument.\n\nOnce `Environment` object is created you use `get_template(<template_file>)` method to retrieve template stored in the `<template_file>` name. This method will return `Template` object.\n\nWith template retrieved, you pass a dictionary with variables to the `render()` method of the `Template` object.\n\n## Task 03\n\n### Step 1\n\nOpen source code of the `j2_file_loader.py` program, which you created in the previous task.\n\n### Step 2\n\nCreate data file `lab04-task3.yml` in `./my_vars`. Copy the below content into it:\n\n```yaml\n---\nserver_name: machineLearning-cluster01-ch\n\nalgo: neural_network\n```\n\nCreate template file `lab04-task3.j2` in `./my_templates`. Copy the below content into it:\n\n```\nMachine Learning cluster: {{ server_name }}\nSelected algorithm: {{ algo }}\nProcessing power: {{ cluster_mflops }}\n```\n\n### Step 3\n\nChange the values of `vars_file` and `template_name` to match the below ones:\n\n```python\n vars_file = \"lab04-task3.yml\"\n template_name = \"lab04-task3.j2\"\n```\n\n### Step 4\n\nRun the program using the below command:\n\n```python j2_file_loader.py```\n\nYou should see the output of the rendered template.\n\nNotice that the line with `Processing power` has no value even though you placed a variable substitution statement in the template.\n\nThis is the default behavior of the Jinja rendering engine. Undefined variables don't generate errors, you simply get empty space in the final output.\n\n### Step 5\n\nGo back to the source code of the program and import class `StrictUndefined` from `jinja2` package.\n\nSee the final `jinja2` imports below for reference:\n\n```python\nfrom jinja2 import Environment, FileSystemLoader, StrictUndefined\n```\n\nAdd `undefined=StrictUndefined` argument when instantiating `Environment` object.\n\nYour line where the `Environment` is created should look like so:\n\n```python\n j2_env = Environment(\n loader=FileSystemLoader(TEMPLATES_DIR), undefined=StrictUndefined\n )\n```\n\n### Step 6\n\nRun the program using the below command:\n\n```python j2_file_loader.py```\n\n### Step 7\n\nYour program should fail with the `jinja2.exceptions.UndefinedError` error.\n\nUsing `StrictUndefined` in your Jinja Environment means the template will error out when encountering an undefined variable instead of silently ignoring the error.\n\n## Task 04\n\n### Step 1 \n\nOpen source code of the `j2_file_loader.py` program which you worked with in the previous tasks.\n\n### Step 2\n\nCopy files `vars/lab04-task4.yml` and `templates/lab04-task4.j2` to `my_vars` and `my_templates` directories.\n\n### Step 3\n\nChange the values of `vars_file` and `template_name` to match the below ones:\n\n```python\n vars_file = \"lab04-task4.yml\"\n template_name = \"lab04-task4.j2\"\n```\n\n### Step 4\n\nRun the program using the below command:\n\n```python j2_file_loader.py```\n\n### Step 5\n\nObserve resulting whitespace rendering.\n\n### Step 6\n\nGo back to the source code of the program and add `trim_blocks=True` argument when instantiating `Environment` object.\n\nYour line where the `Environment` is created should look like so:\n\n```python\n j2_env = Environment(\n loader=FileSystemLoader(TEMPLATES_DIR),\n undefined=StrictUndefined,\n trim_blocks=True\n )\n```\n\n### Step 7\n\nRun the program again using the below command:\n\n```python j2_file_loader.py```\n\n### Step 8\n\nObserve resulting whitespace rendering.\n\n`trim_blocks=True` told Jinja engine to automatically remove new lines placed after block statements.\n\n### Step 9\n\nGo back to the source code of the program. Add `lstrip_blocks=True` argument when instantiating the `Environment` object.\n\nYour line where the `Environment` is created should look like so:\n\n```python\n j2_env = Environment(\n loader=FileSystemLoader(TEMPLATES_DIR),\n undefined=StrictUndefined,\n lstrip_blocks=True,\n trim_blocks=True\n )\n```\n\n### Step 10\n\nRun the program again using the below command:\n\n```python j2_file_loader.py```\n\n### Step 11\n\nObserve resulting whitespace rendering.\n\n`lstrip_blocks=True` told Jinja engine to automatically remove spaces and tabs preceding the block statements." }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "b7670a149839f3825c3edc3df7570ca0d2aed74b", "content_id": "ae16e189aff43de1e0c660f07632fd4c0905ca2b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx07/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx07\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.8701298832893372, "alphanum_fraction": 0.8701298832893372, "avg_line_length": 7.55555534362793, "blob_id": "8c8b3184bee12f8a99d64034eead55d7d71775db", "content_id": "a11c325b41f82d4d63e0320d9a0288e8d111170e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 77, "license_type": "no_license", "max_line_length": 12, "num_lines": 9, "path": "/challenges/05-docker-tools/solution/files/requirements.txt", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "ansible\nnetmiko\nnapalm\nansible-lint\nyamllint\nblack\nnetaddr\njmespath\nrequests\n" }, { "alpha_fraction": 0.6898858547210693, "alphanum_fraction": 0.764659583568573, "avg_line_length": 35.29999923706055, "blob_id": "134636829a40eec57cb899c559e6823a31dc07bc", "content_id": "8040a72c74939a5d88e618a411ac517011d97abd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 2546, "license_type": "no_license", "max_line_length": 171, "num_lines": 70, "path": "/challenges/07-telemetry-visibility/solution/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Challenge Exercise Solution Guide\n\n## Using TPG Monitoring stack\n\nThe goal of this exercise is to interact with the different components of a TPG stack (Telegraf, Prometheus, Grafana), from a network monitoring perspective.\n\n## Solution Walkthrough\n\nThe configurations completed are present under the `configs/` folder:\n\n- [HTTP Telegraf configuration](configs/http-telegraf-01.conf)\n- [DNS Telegraf configuration](configs/dns-telegraf-01.conf)\n\n### Lab turnup\n\nNow, first turn up the lab.\n\n```shell\n> docker-compose up -d\nCreating network \"solution_default\" with the default driver\nCreating prometheus ... done\nCreating grafana ... done\nCreating http-telegraf-01 ... done\nCreating dns-telegraf-01 ... done\n```\n\nVerify that there are no issues with the telegraf instances, for example:\n\n```shell\n❯ docker logs -f http-telegraf-01\n2020-10-22T21:49:38Z I! Starting Telegraf 1.15.3\n2020-10-22T21:49:38Z I! Using config file: /etc/telegraf/telegraf.conf\n2020-10-22T21:49:38Z I! Loaded inputs: http_response\n2020-10-22T21:49:38Z I! Loaded aggregators:\n2020-10-22T21:49:38Z I! Loaded processors:\n2020-10-22T21:49:38Z I! Loaded outputs: prometheus_client\n2020-10-22T21:49:38Z I! Tags enabled: host=9ba69ccf02cb\n2020-10-22T21:49:38Z I! [agent] Config: Interval:10s, Quiet:false, Hostname:\"9ba69ccf02cb\", Flush Interval:10s\n2020-10-22T21:49:38Z I! [outputs.prometheus_client] Listening on http://[::]:9012/metrics\n```\n\n### Metrics verification\n\nVerify that metrics collected are exposed to the prometheus client.\n\n```shell\n❯ curl -XGET http://localhost:9012/metrics \| grep http_response\n# HELP http_response_response_time Telegraf collected metric\n# TYPE http_response_response_time untyped\nhttp_response_response_time{host=\"9ba69ccf02cb\",method=\"GET\",result=\"success\",result_type=\"success\",server=\"https://www.cloudflarestatus.com/\",status_code=\"200\"} 0.2126921\n<Output ommitted>\n```\n\nYou should be able to see the measurement like `http_response_response_time`. In the example above you can see the metric value (`0.2126921`) to that measurement.\n\nYou can also verify the metrics in the Prometheus UI.\n\n![Prometheus](promethus_metric.png)\n\n### Grafana visualizations\n\nAfter you login to Grafana (http://localhost:3000), you can go to the Explore** and verify the metrics. For example:\n\n![Grafana Explore](grafana_explore.png)\n\nHere are also example screenshots of the panels visualizations for HTTP and DNS query times:\n\n![Grafana HTTP Reponse Time Panel](grafana_http_panel.png)\n\n![Grafana DNS Query Time Panel](grafana_dns_panel.png)\n" }, { "alpha_fraction": 0.5585521459579468, "alphanum_fraction": 0.5727466344833374, "avg_line_length": 34.224998474121094, "blob_id": "85be947e1ba177c665603bb1f1f5d6f4b963d79d", "content_id": "a0d6e33aa0f0bfee6e82296954c8975e0980a277", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1409, "license_type": "no_license", "max_line_length": 75, "num_lines": 40, "path": "/workshops/extending-ansible/lab02/filter_plugins/expand_range.py", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "import re\nfrom ansible import errors\n\n\nclass FilterModule:\n \"\"\"Defines a filter module object.\"\"\"\n\n @staticmethod\n def filters():\n \"\"\"Returns the Ansible filter bindings dictionary.\"\"\"\n return {\n \"expand_range\": FilterModule.expand_range,\n }\n\n @staticmethod\n def expand_range(text):\n \"\"\"Expands a range specifier for interface to a list.\"\"\"\n # Look for at least one non-whitespace character for the base\n # followed by a range spec: [x:y] where x and y are integers\n result = re.findall(r\"^(\\S+)(\\[\\d+:\\d+\\])$\", text)\n\n # Check if we have a valid match\n # \"Loopback100[1:3]\" yields [('Loopback100', '[1:3]')]\n # but \"Loopback100\" yields []\n if result:\n # Process the range spec '[1:3]' into start and stop as strings\n start, stop = result[0][1].strip(\"[]\").split(\":\")\n # Generate the expanded list by appending numbers to the\n # base string from the provided range\n base = result[0][0]\n expanded_list = []\n for i in range(int(start), int(stop) + 1):\n expanded_list.append(f\"{base}{i}\")\n\n return expanded_list\n\n # No range provided or no match at all, so raise an error\n raise errors.AnsibleFilterError(\n f\"expand_range filter error: No valid range found in '{text}'!\"\n )\n" }, { "alpha_fraction": 0.6470588445663452, "alphanum_fraction": 0.7411764860153198, "avg_line_length": 16, "blob_id": "528702133abf03aa224a28cfed5bbaaddc56f7b7", "content_id": "06a5be470e103fb6993e2fe9cffd2981f7d869bd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 85, "license_type": "no_license", "max_line_length": 45, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-esx16/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-esx16\n\nThis Cisco UCS-C220 device is located in DC1.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7289719581604004, "alphanum_fraction": 0.7476635575294495, "avg_line_length": 20.399999618530273, "blob_id": "c9eb15dd183170eade4584c17d21c93a82249e50", "content_id": "0b102e8859cddaf97599219cb7b359624300766b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 107, "license_type": "no_license", "max_line_length": 52, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/nyc-spine-02.infra.ntc.com/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# nyc-spine-02.infra.ntc.com\n\nThis Arista vEOS device is located in New York City.\n\nIts status is: Active.\n" }, { "alpha_fraction": 0.7189873456954956, "alphanum_fraction": 0.7417721748352051, "avg_line_length": 25.399999618530273, "blob_id": "7bc2603867d56026b7cc01240b55cf49710bdb98", "content_id": "feacefe9ad3aab2e87188e49483f6465351959d9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 395, "license_type": "no_license", "max_line_length": 156, "num_lines": 15, "path": "/workshops/telemetry-deepdive/prometheus_promql/002_offets.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# Offets\n## Goals\nThe goals of this lab are:\n* Familiarize yourself with offsets.\n\n## Exercises\n### Task 1\nPerform a query to return the admin statuss of the interfaces for the device `zpa_frankfurt_fr6_1` using the `interface_ifAdminStatus` metric, 48 hours ago.\n<details>\n <summary>Reveal Answer</summary>\n \n```\ninterface_ifAdminStatus{device=\"zpa_frankfurt_fr6_1\"} offset 48h\n```\n</details>" }, { "alpha_fraction": 0.6585366129875183, "alphanum_fraction": 0.7317073345184326, "avg_line_length": 15.399999618530273, "blob_id": "f41acf18762353e12e8306208bf696c45fc842a5", "content_id": "c04650945e7c4ecc3ba98112debabc2c39e450fa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 82, "license_type": "no_license", "max_line_length": 40, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/HQ-MDF-PDU02/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# HQ-MDF-PDU02\n\nThis APC AP8941 device is located in HQ.\n\nIts status is: Planned.\n" }, { "alpha_fraction": 0.621052622795105, "alphanum_fraction": 0.7473683953285217, "avg_line_length": 18, "blob_id": "c409a85c2af09175e54d25e7d3987589efa11ef1", "content_id": "17dc9b582d8fb9d9600a131d0d322f61239aee81", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 95, "license_type": "no_license", "max_line_length": 50, "num_lines": 5, "path": "/workshops/netbox-extensibility/devices/las01-acme-lsw04/README.md", "repo_name": "swarupv1/jinja2-deep-dive-day2", "src_encoding": "UTF-8", "text": "# las01-acme-lsw04\n\nThis Cisco 93180YC-FX-24 device is located in DC1.\n\nIts status is: Active.\n" } ]	104
paste-ninja/spl_arch	https://github.com/paste-ninja/spl_arch	a2f55f055514ecd45679b5d004f405ba9a4e481a	88db68b50b8d3a4d78bd39c47e21a4151577128c	c582bf6ecd5c108c0a277b93a8d09a6c5c12fef0	refs/heads/master	2022-10-17T00:35:54.413677	2020-06-05T08:19:06	2020-06-05T08:19:06	271,533,541	0	0	null	2020-06-11T11:53:19	2020-06-05T08:19:10	2020-06-10T09:32:26	null	[ { "alpha_fraction": 0.5838348865509033, "alphanum_fraction": 0.5932931900024414, "avg_line_length": 27.365854263305664, "blob_id": "4575e88db4ab0a9effdbd9f1c63663fd0c789cb5", "content_id": "bfcccfe8fa669e718ac2bafe1f407dd1f06f95d1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1163, "license_type": "no_license", "max_line_length": 111, "num_lines": 41, "path": "/command/search_command.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: search_command\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 17:42\n\"\"\"\nfrom spl_arch.command.base_command import BaseCommand\nfrom spl_arch.extract.comma_separator_extract import CommaSeparatorExtract\n\n\nclass SearchCommand(BaseCommand):\n def __init__(self, cmd_name, cmd_type, repo):\n super(SearchCommand, self).__init__(cmd_name, cmd_type)\n self.repo = repo\n self.in_stream = None\n self.out_stream = None\n self.extract = None\n\n def set_input_stream(self, in_stream):\n self.in_stream = in_stream\n\n def set_output_stream(self, out_stream):\n self.out_stream = out_stream\n\n def stream_in(self):\n return self.in_stream.pull()\n\n def is_extract(self, val):\n self.extract = val\n\n def calc(self):\n docs = self.stream_in()\n\n if self.extract:\n for doc in docs:\n raw = doc[\"_source\"][\"_raw\"]\n extract_log = CommaSeparatorExtract(\"comma\").extract_fields(raw, [\"ch\", \"math\", \"en\", \"class\"])\n doc[\"_source\"][\"_raw\"] = extract_log\n\n self.set_output_stream(docs)\n" }, { "alpha_fraction": 0.5315315127372742, "alphanum_fraction": 0.5660660862922668, "avg_line_length": 24.615385055541992, "blob_id": "19d6929031e4c233c34245992a2d6a9a6182dacb", "content_id": "364e27d5698a6de2b0b209a733648fbddcb51345", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 694, "license_type": "no_license", "max_line_length": 74, "num_lines": 26, "path": "/extract/comma_separator_extract.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: comma_separator_extract\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 17:18\n\"\"\"\nfrom spl_arch.extract.base_extract import BaseExtract\n\n\nclass CommaSeparatorExtract(BaseExtract):\n \"\"\"\n 以逗号作为分隔符，提取字段值\n \"\"\"\n\n def __init__(self, name):\n super(CommaSeparatorExtract, self).__init__(name)\n\n def extract_fields(self, log_line, fields):\n \"\"\"\n\n :param log_line: \"87,70,50,one\"\n :param fields: [\"ch\", \"en\", \"math\", \"class\"]\n :return: {\"ch\":87, \"en\":70, \"math\":50, \"class\": \"one\"}\n \"\"\"\n return dict(zip(fields, [e.strip() for e in log_line.split(\",\")]))\n" }, { "alpha_fraction": 0.4655172526836395, "alphanum_fraction": 0.5034482479095459, "avg_line_length": 14.263157844543457, "blob_id": "29f79875841cd4db21c498dd0f7e52667c8261ba", "content_id": "1f64655590991227a275ae3dd01b325b2a0f37f8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 290, "license_type": "no_license", "max_line_length": 33, "num_lines": 19, "path": "/input/spl_input.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: spl_input\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 14:14\n\"\"\"\n\n\nclass SplInput(object):\n \"\"\"\n Spl pipeline cmd\n \"\"\"\n\n def __init__(self):\n pass\n\n def get_input(self):\n return input(\"Spl cmd: \")\n" }, { "alpha_fraction": 0.4903677701950073, "alphanum_fraction": 0.5096322298049927, "avg_line_length": 20.961538314819336, "blob_id": "7ddeb857ef69aaa61199a66d11c4b869688c0d6a", "content_id": "7015f01e1484f1ab366e120108f6b95cb4c18751", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 571, "license_type": "no_license", "max_line_length": 98, "num_lines": 26, "path": "/stream/base_stream.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: abstract_stream\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 16:04\n\"\"\"\n\n\nclass BaseStream(object):\n def __init__(self, name):\n self.name = name\n\n def pull(self):\n \"\"\"\n get data\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"pull\"))\n\n def push(self):\n \"\"\"\n push data\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"push\"))\n" }, { "alpha_fraction": 0.4173228442668915, "alphanum_fraction": 0.5039370059967041, "avg_line_length": 17.14285659790039, "blob_id": "c77d688a10c17690c4860906986da1f5f88685c2", "content_id": "babc3bce7dda540c58cd6a45955a914472389eb1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 127, "license_type": "no_license", "max_line_length": 26, "num_lines": 7, "path": "/input/__init__.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: __init__.py\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 14:45\n\"\"\"\n" }, { "alpha_fraction": 0.5573770403862, "alphanum_fraction": 0.5799180269241333, "avg_line_length": 24.6842098236084, "blob_id": "546b7cac8c596cce35db4ce33ae679e3fcd89a44", "content_id": "b61173667466e26ec86c59926e553d76c01e02ec", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 488, "license_type": "no_license", "max_line_length": 102, "num_lines": 19, "path": "/parser/base_parser.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: base_parser\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 17:51\n\"\"\"\n\n\nclass BaseParser(object):\n def __init__(self, name, cmd):\n self.name = name\n self.cmd = cmd\n\n def validate(self):\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"validate\"))\n\n def parse(self):\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"parse\"))\n" }, { "alpha_fraction": 0.5511363744735718, "alphanum_fraction": 0.5823863744735718, "avg_line_length": 17.526315689086914, "blob_id": "bcd486e7522dce92438f3fb7bb14b50a5ca2f410", "content_id": "da0e3930682bb1d5a9f688ae224837f56e6a0ddf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 352, "license_type": "no_license", "max_line_length": 50, "num_lines": 19, "path": "/stream/mem_stream.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: mem_stream\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 16:51\n\"\"\"\nfrom spl_arch.stream.base_stream import BaseStream\n\n\nclass MemStream(BaseStream):\n def __init__(self, name):\n super(MemStream, self).__init__(name)\n\n def pull(self):\n pass\n\n def push(self):\n pass\n" }, { "alpha_fraction": 0.5888399481773376, "alphanum_fraction": 0.6182085275650024, "avg_line_length": 24.22222137451172, "blob_id": "f07043ba7aa83374576de6eb39bf1dd403bf717c", "content_id": "de9874eaf4b3f842169f82e517a4cbbe0a7b5f6e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 749, "license_type": "no_license", "max_line_length": 70, "num_lines": 27, "path": "/stream/es_stream.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: es_stream\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 16:10\n\"\"\"\nfrom elasticsearch import Elasticsearch\nfrom spl_arch.stream.base_stream import BaseStream\n\n\nclass EsStream(BaseStream):\n \"\"\"\n 原始日志以{\"_raw\": \"53,93,74,two\"}的方式存入，即整条日志以_raw为字段名，整条日志作为值的方式写入ES\n \"\"\"\n\n def __init__(self, name, host, port, indexer):\n super(EsStream, self).__init__(name)\n self.client = Elasticsearch(host=host, port=port, timeout=300)\n self.indexer = indexer\n\n def pull(self):\n res = self.client.search(index=self.indexer)\n return res[\"hits\"][\"hits\"] # list\n\n def push(self):\n pass\n" }, { "alpha_fraction": 0.519959032535553, "alphanum_fraction": 0.5373592376708984, "avg_line_length": 23.424999237060547, "blob_id": "ef480b68c5e38c4722d36940b7cc661c9812090b", "content_id": "90893942ffbcb6f77235cb7ef7a8ad28fb7f392a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 977, "license_type": "no_license", "max_line_length": 81, "num_lines": 40, "path": "/scheduler/scheduler.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: scheduler\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 19:23\n\"\"\"\nimport json\nfrom threading import Thread\nfrom spl_arch.stream.es_stream import EsStream\n\n\nclass Scheduler(object):\n def __init__(self, name):\n self.name = name\n\n def schedule(self, cmd_opts):\n \"\"\"\n schedule ...\n :param cmd_opts:\n :return:\n \"\"\"\n input_stream, end = None, None\n\n for _index, cmd_opt in enumerate(cmd_opts):\n if _index == 0:\n # init cmd ---> searchcmd\n input_stream = EsStream(\"es_stream\", \"localhost\", 9200, \"mytest\")\n cmd_opt.is_extract(True)\n\n cmd_opt.set_input_stream(input_stream)\n cmd_opt.calc()\n\n input_stream = cmd_opt.out_stream\n end = cmd_opt\n\n print(json.dumps(end.out_stream, indent=4, separators=(\",\", \":\")))\n\n def paralell_schedule(self):\n pass\n" }, { "alpha_fraction": 0.5595611333847046, "alphanum_fraction": 0.5681818127632141, "avg_line_length": 26.7391300201416, "blob_id": "ba730b23d32b624b653a402c6b00f6842b1b9c86", "content_id": "73b34022b3d6a4acb01207fc1c8a0f93999343eb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1276, "license_type": "no_license", "max_line_length": 109, "num_lines": 46, "path": "/command/stats_command.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: StatsCommand\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 22:21\n\"\"\"\nfrom spl_arch.command.base_command import BaseCommand\nfrom spl_arch.function.avg import Avg\n\n\nclass StatsCommand(BaseCommand):\n def __init__(self, cmd_name, cmd_type, func, field, as_field, group_field):\n super(StatsCommand, self).__init__(cmd_name, cmd_type)\n self.func = func\n self.field = field\n self.as_field = as_field\n self.group_field = group_field\n self.in_stream = None\n self.out_stream = None\n self.output = []\n\n def set_input_stream(self, in_stream):\n self.in_stream = in_stream\n\n def set_output_stream(self, out_stream):\n self.out_stream = out_stream\n\n def stream_in(self):\n return self.in_stream\n\n def calc(self):\n docs, d = self.in_stream, {}\n\n for doc in docs:\n raw = doc[\"_source\"][\"_raw\"]\n\n if raw[\"class\"] not in d:\n d[raw[\"class\"]] = []\n\n d[raw[\"class\"]].append(int(raw[\"math\"]))\n\n for _class, _sum in d.items():\n self.output.append({\"class\": _class, self.as_field: Avg(\"avg\", \"agg\").avg(sum(_sum), len(_sum))})\n\n self.set_output_stream(self.output)\n" }, { "alpha_fraction": 0.5675675868988037, "alphanum_fraction": 0.5972973108291626, "avg_line_length": 23.66666603088379, "blob_id": "28f7e311eacfaaba714a062f428109d76c7e9582", "content_id": "2f9e527c73f2f63e2dc4187e801bc7a278728c37", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 370, "license_type": "no_license", "max_line_length": 108, "num_lines": 15, "path": "/extract/base_extract.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: base_extract\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 17:04\n\"\"\"\n\n\nclass BaseExtract(object):\n def __init__(self, name):\n self.name = name\n\n def extract_fields(self, log_line, fields):\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"extract_fields\"))\n" }, { "alpha_fraction": 0.699999988079071, "alphanum_fraction": 0.699999988079071, "avg_line_length": 9, "blob_id": "1f7ac19287b1720ff52102bbefa61dfd9a072569", "content_id": "3fddbc4566f01db1cf523e1096095e3ae3ce16ad", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 20, "license_type": "no_license", "max_line_length": 10, "num_lines": 2, "path": "/README.md", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# spl_arch\nspl arch\n" }, { "alpha_fraction": 0.5795454382896423, "alphanum_fraction": 0.5909090638160706, "avg_line_length": 25.16216278076172, "blob_id": "cc1b65dce5174952217588183e69fd898aaf1956", "content_id": "f6014dcf71cfa5bdc89f2e5c99e9e736750e2468", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 968, "license_type": "no_license", "max_line_length": 68, "num_lines": 37, "path": "/command/replace_command.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: replace_command\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 15:08\n\"\"\"\nfrom spl_arch.command.base_command import BaseCommand\n\n\nclass ReplaceCommand(BaseCommand):\n def __init__(self, cmd_name, cmd_type, val, replace_val, field):\n super(ReplaceCommand, self).__init__(cmd_name, cmd_type)\n self.val = val\n self.replace_val = replace_val\n self.field = field\n self.in_stream, self.out_stream = None, None\n\n def set_input_stream(self, in_stream):\n self.in_stream = in_stream\n\n def set_output_stream(self, out_stream):\n self.out_stream = out_stream\n\n def stream_in(self):\n return self.in_stream\n\n def calc(self):\n docs = self.in_stream\n\n for doc in docs:\n raw = doc[\"_source\"][\"_raw\"]\n\n if raw[self.field] == self.val:\n raw[self.field] = self.replace_val\n\n self.set_output_stream(docs)\n" }, { "alpha_fraction": 0.6378772258758545, "alphanum_fraction": 0.6493236422538757, "avg_line_length": 30, "blob_id": "18afca61d649c3d036987b70ed34b01f98d65bf1", "content_id": "7ce3bd49312baaa31ed34d3f3956b9b5d9799f44", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 961, "license_type": "no_license", "max_line_length": 94, "num_lines": 31, "path": "/parser/antlr_parser.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: parser\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 17:49\n\"\"\"\nfrom spl_arch.parser.base_parser import BaseParser\nfrom spl_arch.command.search_command import SearchCommand\nfrom spl_arch.command.replace_command import ReplaceCommand\nfrom spl_arch.command.stats_command import StatsCommand\n\n\nclass AntlrParser(BaseParser):\n def __init__(self, name, cmd):\n super(AntlrParser, self).__init__(name, cmd)\n self.cmd_opts = []\n\n def validate(self):\n pass\n\n def parse(self):\n search_cmd = SearchCommand(\"search\", \"streaming\", \"mytest\")\n replace_cmd = ReplaceCommand(\"replace\", \"streaming\", \"one\", \"oneClass\", \"class\")\n stats_cmd = StatsCommand(\"stats\", \"non_streaming\", \"avg\", \"math\", \"avg_math\", \"class\")\n\n self.cmd_opts.append(search_cmd)\n self.cmd_opts.append(replace_cmd)\n self.cmd_opts.append(stats_cmd)\n\n return self.cmd_opts\n" }, { "alpha_fraction": 0.5224676132202148, "alphanum_fraction": 0.5308454036712646, "avg_line_length": 25.795917510986328, "blob_id": "dbdec15bc9ced5003e22eb1189a16715261e1847", "content_id": "df2e5f1b6e07175219bb3d03c52292bc0ae2df53", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1313, "license_type": "no_license", "max_line_length": 111, "num_lines": 49, "path": "/command/base_command.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: BaseCommand\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 14:55\n\"\"\"\n\n\nclass BaseCommand(object):\n def __init__(self, cmd_name, cmd_type):\n self.cmd_name = cmd_name\n self.cmd_type = cmd_type\n\n def set_input_stream(self, in_stream):\n \"\"\"\n set input stream for cmd\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"set_input_stream\"))\n\n def set_output_stream(self, out_stream):\n \"\"\"\n set output stream for cmd\n :param out_stream:\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"set_output_stream\"))\n\n def stream_in(self):\n \"\"\"\n stream in\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"stream_in\"))\n\n def write_to(self):\n \"\"\"\n write to\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"write_to\"))\n\n def calc(self):\n \"\"\"\n cmd calculate\n :return:\n \"\"\"\n raise NotImplementedError(\"{} {} not implemented\".format(self.__class__.__name__, \"calc\"))\n" }, { "alpha_fraction": 0.4902912676334381, "alphanum_fraction": 0.5436893105506897, "avg_line_length": 16.16666603088379, "blob_id": "c12a772bbfa23edf404d1b31390b8a7bfdd931a1", "content_id": "e0862488eaf227e0c9706af2b8ba2265528da860", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 206, "license_type": "no_license", "max_line_length": 29, "num_lines": 12, "path": "/function/base_func.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: base_func\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 23:08\n\"\"\"\n\n\nclass Function(object):\n def __init__(self, name):\n self.name = name\n" }, { "alpha_fraction": 0.5677083134651184, "alphanum_fraction": 0.5963541865348816, "avg_line_length": 21.58823585510254, "blob_id": "e1baab67941cb1b89260a8fb8f5764101196fb40", "content_id": "e5c7acc146f7a3bb2564bc15ae98126768344f39", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 384, "license_type": "no_license", "max_line_length": 48, "num_lines": 17, "path": "/function/avg.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: avg\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 23:09\n\"\"\"\nfrom spl_arch.function.base_func import Function\n\n\nclass Avg(Function):\n def __init__(self, func_name, func_type):\n super(Avg, self).__init__(func_name)\n self.func_type = func_type\n\n def avg(self, total, counter):\n return total / counter\n" }, { "alpha_fraction": 0.5480132699012756, "alphanum_fraction": 0.5620861053466797, "avg_line_length": 21.79245376586914, "blob_id": "58203de53041508939793511a62bece6f8ca7b76", "content_id": "aa7b75c5a10171b7538b9f5ad46792f48a2085c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1208, "license_type": "no_license", "max_line_length": 64, "num_lines": 53, "path": "/executor/executor.py", "repo_name": "paste-ninja/spl_arch", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\n File Name: executor\n Description: \"\"\n Author: Donny.fang\n Date: 2020/6/4 14:04\n\"\"\"\nfrom spl_arch.input.spl_input import SplInput\nfrom spl_arch.parser.antlr_parser import AntlrParser\nfrom spl_arch.scheduler.scheduler import Scheduler\n\n\nclass Executor(object):\n \"\"\"\n spl bootstrap\n \"\"\"\n\n def __init__(self, name, start_time, end_time):\n self.name = name\n self.start_time = start_time\n self.end_time = end_time\n\n def time_consume(self):\n pass\n\n def execute(self):\n \"\"\"\n executer entrance\n\n 1. input\n 2. parse\n 3. scheduler --> search (extract)\n 4. ...\n :return: void\n \"\"\"\n # input module\n spl_cmd = SplInput().get_input() # search repo=\"mytest\"\n\n # parse module\n # input -> pipe_cmd\n # output -> collection of opts\n antlr_parser = AntlrParser(\"antlr\", spl_cmd)\n antlr_parser.validate()\n opts = antlr_parser.parse()\n\n # schedule module\n scheduler = Scheduler(\"scheduler\")\n scheduler.schedule(opts)\n\n\nif __name__ == \"__main__\":\n executor = Executor(\"spl\", 0, 0)\n executor.execute()\n" } ]	18
dlg/gevent-zeromq	https://github.com/dlg/gevent-zeromq	bc8366629f0f8184d52812520f6ac9fed7fdc5e3	f9dcb302e01f070f868d73d9dad2079dc5d8bba6	6714ffcc41ce357fb7bdb4c006f40d3a4d59b5cd	refs/heads/master	2021-01-19T06:56:06.387324	2011-03-03T06:18:08	2011-03-03T06:18:08	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5966257452964783, "alphanum_fraction": 0.5993865132331848, "avg_line_length": 29.185184478759766, "blob_id": "c12213cffd65e44d1c9176378831247c7554a372", "content_id": "3999ee28de9c6a429ff934765b67216b537ddd4e", "detected_licenses": [ "LicenseRef-scancode-unknown-license-reference", "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3260, "license_type": "permissive", "max_line_length": 121, "num_lines": 108, "path": "/setup.py", "repo_name": "dlg/gevent-zeromq", "src_encoding": "UTF-8", "text": "import os\nimport sys\nfrom glob import glob\nfrom distutils.core import Command, Extension, setup\nfrom distutils.command.build_ext import build_ext\nfrom traceback import print_exc\n\ncython_available = False\ntry:\n from Cython.Distutils import build_ext\n from Cython.Distutils.extension import Extension\n cython_available = True\nexcept ImportError, e:\n print 'WARNING: cython not available, proceeding with pure python implementation. (%s)' % e\n pass\n\ntry:\n import nose\nexcept ImportError:\n nose = None\n\ndef get_ext_modules():\n\n try:\n import gevent\n except ImportError, e:\n print 'WARNING: gevent must be installed to build cython version of gevent-zeromq (%s).', e\n return []\n try:\n import zmq\n except ImportError, e:\n print 'WARNING: pyzmq(>=2.1.0) must be installed to build cython version of gevent-zeromq (%s).', e\n return []\n return [\n Extension(\n 'gevent_zeromq.core',\n ['gevent_zeromq/core.pyx'],\n include_dirs = zmq.get_includes() + [os.path.dirname(os.path.dirname(zmq.__file__))]\n ),\n ]\n\n\nclass TestCommand(Command):\n \"\"\"Custom distutils command to run the test suite.\"\"\"\n\n user_options = [ ]\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run_nose(self):\n \"\"\"Run the test suite with nose.\"\"\"\n return nose.core.TestProgram(argv=[\"\", '-vvs', os.path.join(self._zmq_dir, 'tests')])\n \n def run_unittest(self):\n \"\"\"Finds all the tests modules in zmq/tests/ and runs them.\"\"\"\n testfiles = [ ]\n for t in glob(os.path.join(self._zmq_dir, 'tests', '.py')):\n name = os.path.splitext(os.path.basename(t))[0]\n if name.startswith('test_'):\n testfiles.append('.'.join(\n ['zmq.tests', name])\n )\n tests = TestLoader().loadTestsFromNames(testfiles)\n t = TextTestRunner(verbosity = 2)\n t.run(tests)\n\n def run(self):\n # crude check for inplace build:\n try:\n import gevent_zeromq\n except ImportError:\n print_exc()\n print (\"Could not import gevent_zeromq!\")\n print (\"You must build pyzmq with 'python setup.py build_ext --inplace' for 'python setup.py test' to work.\")\n print (\"If you did build gevent_zeromq in-place, then this is a real error.\")\n sys.exit(1)\n\n gevent_zeromq.monkey_patch(test_suite=True) # monkey patch\n import zmq\n self._zmq_dir = os.path.dirname(zmq.__file__)\n\n if nose is None:\n print (\"nose unavailable, falling back on unittest. Skipped tests will appear as ERRORs.\")\n return self.run_unittest()\n else:\n return self.run_nose()\n\nif cython_available:\n ext_modules = get_ext_modules()\nelse:\n ext_modules = []\n\n__version__ = (0, 0, 2)\n\nsetup(\n name = 'gevent_zeromq',\n version = '.'.join([str(x) for x in __version__]),\n packages = ['gevent_zeromq'],\n cmdclass = {'build_ext': build_ext, 'test': TestCommand},\n ext_modules = ext_modules,\n author = 'Travis Cline',\n author_email = '[email protected]',\n description = 'gevent compatibility layer for pyzmq',\n)\n" }, { "alpha_fraction": 0.6045751571655273, "alphanum_fraction": 0.6053921580314636, "avg_line_length": 32.86111068725586, "blob_id": "1ee447fde7ef3735b5dcddfe5d3fbd15395c6aca", "content_id": "dba840aa37e6fda3b03fa4e5550539ae77f58ad1", "detected_licenses": [ "LicenseRef-scancode-unknown-license-reference", "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1224, "license_type": "permissive", "max_line_length": 86, "num_lines": 36, "path": "/gevent_zeromq/tests.py", "repo_name": "dlg/gevent-zeromq", "src_encoding": "UTF-8", "text": "from gevent_zeromq import zmq\n\ndef monkey_patch_test_suite():\n \"\"\"\n Monkey patches parts of pyzmq's test suite to run them with gevent-zeromq.\n \"\"\"\n zmqtests = __import__('zmq.tests', fromlist=['', 'test_device', 'test_monqueue'])\n #import ipdb; ipdb.set_trace()\n \n import sys\n try:\n from nose import SkipTest\n except ImportError:\n class SkipTest(Exception):\n pass\n\n class GreenBaseZMQTestCase(zmqtests.BaseZMQTestCase):\n def assertRaisesErrno(self, errno, func, args, kwargs):\n if errno == zmq.EAGAIN:\n raise SkipTest(\"Skipping because we're green.\")\n try:\n func(args, **kwargs)\n except zmq.ZMQError:\n e = sys.exc_info()[1]\n self.assertEqual(e.errno, errno, \"wrong error raised, expected '%s' \\\n got '%s'\" % (zmq.ZMQError(errno), zmq.ZMQError(e.errno)))\n else:\n self.fail(\"Function did not raise any error\")\n\n zmqtests.BaseZMQTestCase = GreenBaseZMQTestCase\n \n class BlankTest(GreenBaseZMQTestCase):\n pass\n\n zmqtests.test_device.TestDevice = BlankTest\n zmqtests.test_monqueue.TestMonitoredQueue = BlankTest\n \n" } ]	2
tptrixtop/parent-controll-web	https://github.com/tptrixtop/parent-controll-web	44d8216ef26ad7e434443a70e1eb74866be2e27d	2d848193a5988b40ef1632137276301c7248f8fe	c2aaa9de04af3ba9d88c34b91996bc94e0b8de18	refs/heads/master	2021-01-12T05:51:56.329975	2017-02-23T14:08:44	2017-02-23T14:08:44	77,218,553	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5959596037864685, "alphanum_fraction": 0.5959596037864685, "avg_line_length": 38.599998474121094, "blob_id": "b4818f178f655035f9af60d93c0cbea63448b66b", "content_id": "77c8176998a944636ac42bb8a241a277783bc779", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 198, "license_type": "no_license", "max_line_length": 70, "num_lines": 5, "path": "/static/base/js/services/csrf.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var csrfService = angular.module('CsrfService', [])\n\n .service('CsrfService', ['$log', '$http', function ($log, $http) {\n this.token = $('input[name=csrfmiddlewaretoken]').val();\n }]);\n" }, { "alpha_fraction": 0.8121019005775452, "alphanum_fraction": 0.8121019005775452, "avg_line_length": 80.86956787109375, "blob_id": "b63f9bfe7f0eb7e33222daf73121e253e32b0366", "content_id": "9bf3848eb51cb36a3d22265883f3a18fac1eb293", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1888, "license_type": "no_license", "max_line_length": 244, "num_lines": 23, "path": "/README.md", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "# Parent Control\n\n##Responsible entertainment rather than control\n\nA dramatically new approach to parental control beyond its usual facilities lets you understand principles and reasons for using our modes, so you can communicate with your child in respectful and friendly manner. \n\nThe methodical support for parents will help to explain to a child of any age and sex how and why the control works, which risks it is aiming to eliminate and how it facilitates and makes life of a child fuller rather than closes opportunities.\n\nOur application is tended to be a way of effective communication between parents and children and serves to optimal safety and profound monitoring of child’s life and web activities.\n\n#####Application allows to:\n* Track child’s location\n+ Use the alarm button for your child in offline mode\n+ Chat with your child via app. Extra functionality: if you need to contact the child urgently, the application will block the device until your message is acknowledged/replied\n+ Monitor messages and calls on all the devices\n+ Guard applications and other technical information from the device, including time of usage\n+ Limit access to applications and entertainment web content such as games and social networks\n+ Monitor phone number balance, replenish account remotely with one button\n+ Manage time and activities with family calendar, notes, alarm clock, planning apps, tasks management\n+ Filter web content for a child and propose the chosen content out of theme blocks by parents choice\n+ See recommendations to parents on how to use the control applications and how to talk to children about it so the control is not felt as anything abusive\n+ Use built-in developing games inside the application with remote access, so a parent can decide which application to launch\n+ Protect your account from children if they want to change restrictions by themselves\n\n" }, { "alpha_fraction": 0.5762194991111755, "alphanum_fraction": 0.6082317233085632, "avg_line_length": 25.239999771118164, "blob_id": "4eaa2719ba2e56a9bb19b9ff6dab1a7c9a3dd153", "content_id": "9c032decb05803953a03eaf1695cbff2a2e7aa3a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 656, "license_type": "no_license", "max_line_length": 117, "num_lines": 25, "path": "/users/migrations/0009_auto_20170129_1426.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n# Generated by Django 1.10.4 on 2017-01-29 14:26\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('users', '0008_devicetypes'),\n ]\n\n operations = [\n migrations.RenameModel(\n old_name='DeviceTypes',\n new_name='DeviceModels',\n ),\n migrations.AddField(\n model_name='devices',\n name='model',\n field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='users.DeviceModels'),\n ),\n ]\n" }, { "alpha_fraction": 0.5467625856399536, "alphanum_fraction": 0.5467625856399536, "avg_line_length": 22.16666603088379, "blob_id": "a332b1e43e1c9d15aeab0863757ef775d3db9aef", "content_id": "830bd745634fb27c2e002c897a30cfee78fda855", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 278, "license_type": "no_license", "max_line_length": 66, "num_lines": 12, "path": "/static/base/js/services/loader.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var loaderService = angular.module('LoaderService', [])\n\n .service('LoaderService', ['$location', function ($location) {\n\n this.isLoad = false;\n this.global = false;\n\n this.to_login = function() {\n $location.path('/login')\n }\n\n }]);\n" }, { "alpha_fraction": 0.5757787823677063, "alphanum_fraction": 0.5799790024757385, "avg_line_length": 25.20183563232422, "blob_id": "98f88971691bf22f43d5da9e765810ba80060547", "content_id": "f3075a2674052e103e663e6d333f6de9f75a1d72", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2857, "license_type": "no_license", "max_line_length": 130, "num_lines": 109, "path": "/users/views.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "from django.shortcuts import render\nfrom django.http import HttpResponse\nfrom django.views.decorators.csrf import csrf_protect\nfrom django.contrib.auth.decorators import login_required\nfrom django.http import JsonResponse\nfrom django.contrib.auth.models import User\nfrom django.db import IntegrityError\nfrom django.contrib.auth import authenticate, login\n\nfrom .forms import \n\ndef index(request):\n if request.is_ajax():\n return render(request, 'redirect-to-login.html', {})\n else:\n return render(request, 'index.html', {})\n\n\ndef my_login(request):\n\n if not request.user.is_authenticated:\n return render(request, 'login.html', {})\n else:\n return render(request, 'already-login.html', {})\n\ndef reg(request):\n return render(request, 'reg.html', {})\n\ndef regProfile(request):\n\n resp = {}\n resp['status'] = 0\n resp['msg'] = \"\"\n resp['data'] = {}\n\n form = RegProfileForm(request.POST)\n\n if form.is_valid():\n\n try:\n user = User.objects.create_user(form.cleaned_data['email'], form.cleaned_data['email'], form.cleaned_data['password'])\n user.save()\n except IntegrityError:\n resp['status'] = 2\n resp['msg'] = \"User already exists\"\n except:\n resp['status'] = 1\n resp['msg'] = \"Unexcepted error\"\n\n return JsonResponse(resp, safe=False)\n\n resp['status'] = 1;\n resp['msg'] = \"Data is not valid\"\n\n return JsonResponse(resp, safe=False)\n\ndef checkUniqEmail(request):\n resp = {}\n resp['status'] = 0\n resp['msg'] = \"\"\n resp['data'] = {}\n\n form = CheckEmailForm(request.GET)\n\n if form.is_valid():\n try:\n user = User.objects.get(email=form.cleaned_data['email']);\n resp['status'] = 0;\n resp['msg'] = \"User with this email already exists\"\n except Exception, e:\n resp['status'] = 1\n resp['msg'] = str(e)\n else:\n resp['status'] = 2\n resp['msg'] = \"Email is not valid\"\n\n return JsonResponse(resp, safe=False)\n\ndef tryLogin(request):\n\n resp = {}\n resp['status'] = 0\n resp['msg'] = \"\"\n resp['data'] = {}\n\n form = LoginForm(request.POST)\n if form.is_valid():\n\n user = authenticate(username=form.cleaned_data['email'], password=form.cleaned_data['password'])\n \n if user is not None:\n login(request, user)\n resp['status'] = 0\n resp['msg'] = \"Login OK\"\n resp['data'] = []\n else:\n resp['status'] = 1\n resp['msg'] = \"Login/password not found\"\n resp['data'] = [] \n\n else:\n resp['status'] = 2\n resp['msg'] = \"Your data is not valid\"\n\n return JsonResponse(resp, safe=False)\n\n@login_required\ndef dashboard(request):\n return render(request, 'dashboard.html', {})\n\n" }, { "alpha_fraction": 0.4005187153816223, "alphanum_fraction": 0.40274176001548767, "avg_line_length": 30.011493682861328, "blob_id": "8f0b1d7a1997f1b6da93864a0b290779c9893e68", "content_id": "b7f2da9a2b00740c1b46f2b8dbb8ad6251a36f4e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 2699, "license_type": "no_license", "max_line_length": 85, "num_lines": 87, "path": "/static/base/js/controllers/reg.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var ctrl = angular.module('App.controllers.Reg', ['LoaderService']);\n\nctrl.controller(\n 'reg',\n ['$scope', '$http', '$log', '$timeout', 'LoaderService', '$location',\n\t function($scope, $http, $log, $timeout, LoaderService, $location) {\n\n $scope.user_data = {\n email: \"\",\n password: \"\",\n repeat_pass: \"\"\n };\n\n\n $scope.check_uniq_later_bound;\n $scope.check_uniq_later_bound_latency = 1000;\n var tooltip_destroyed = true;\n $scope.checkUniqEmail = function() {\n\n if($scope.check_uniq_later_bound) {\n $timeout.cancel($scope.check_uniq_later_bound);\n }\n\n if(!tooltip_destroyed) {\n $('#email').tooltip('destroy');\n tooltip_destroyed = true;\n }\n\n $scope.check_uniq_later_bound = $timeout(function() {\n\n if($scope.user_data.email == \"\") {\n return;\n }\n\n LoaderService.isLoad = true;\n\n $http({\n method: 'GET',\n url: \t '/users/chk-email?email=' + $scope.user_data.email,\n headers: { 'Content-Type': 'application/x-www-form-urlencoded' }\n }).then(function(res) { \n\n LoaderService.isLoad = false;\n if(res.data.status != 1) {\n $('#email').tooltip({\n title: res.data.msg,\n placement: \"right\"\n }).tooltip('show');\n tooltip_destroyed = false;\n }\n\n });\n\n }, $scope.check_uniq_later_bound_latency);\n \n }\n\n $scope.register = function() {\n\n if($scope.user_data.password != $scope.user_data.repeat_pass) {\n $('#pass').tooltip({\n title: \"Password do not match\",\n placement: \"right\"\n }).tooltip('show');\n } else {\n\n LoaderService.global = true;\n\n $http({\n method: 'POST',\n data: $.param($scope.user_data),\n url: \t '/users/reg-profile',\n headers: { 'Content-Type': 'application/x-www-form-urlencoded' }\n }).then(function(res) {\n \n LoaderService.global = false;\n if(res.data.status == 0) {\n $location.path('/')\n }\n\n });\n\n }\n\n }\n\n }]);\n\n" }, { "alpha_fraction": 0.5413534045219421, "alphanum_fraction": 0.5939849615097046, "avg_line_length": 20, "blob_id": "e638cf9c9621dd4d9d62805e396f5cb44695229f", "content_id": "a677c29a6aeb4b4f79bf76b90af5d460a0f95db4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 399, "license_type": "no_license", "max_line_length": 48, "num_lines": 19, "path": "/users/migrations/0007_remove_devices_device_type.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n# Generated by Django 1.10.4 on 2017-01-29 14:23\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('users', '0006_remove_devices_model'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='devices',\n name='device_type',\n ),\n ]\n" }, { "alpha_fraction": 0.6576763391494751, "alphanum_fraction": 0.6576763391494751, "avg_line_length": 36, "blob_id": "ea1e9ba583694c55ce016a17b1f51839a518a7af", "content_id": "f94a7bb22a7cd3a5ce0fd01a69b52981611df3c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 482, "license_type": "no_license", "max_line_length": 69, "num_lines": 13, "path": "/users/urls.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "from django.conf.urls import url\n\nfrom . import views\n\nurlpatterns = [\n url(r'^login-template', views.my_login, name='login'),\n url(r'^reg-template', views.reg, name='reg'),\n url(r'^reg-profile$', views.regProfile, name='regProfile'),\n url(r'^chk-email$', views.checkUniqEmail, name='checkUniqEmail'),\n url(r'^try-login$', views.tryLogin, name='tryLogin'),\n url(r'^dashboard-view$', views.dashboard, name='Dashboard'),\n url(r'^', views.index, name='index'),\n]\n\n" }, { "alpha_fraction": 0.5298701524734497, "alphanum_fraction": 0.5844155550003052, "avg_line_length": 19.263158798217773, "blob_id": "d8a7a1bf285ea60d737079f97cf58f7bb6b33467", "content_id": "a7de0adfe5b83699ba0a988184a71f24d11d705f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 385, "license_type": "no_license", "max_line_length": 48, "num_lines": 19, "path": "/users/migrations/0006_remove_devices_model.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n# Generated by Django 1.10.4 on 2017-01-29 14:22\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('users', '0005_devices_user'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='devices',\n name='model',\n ),\n ]\n" }, { "alpha_fraction": 0.5236842036247253, "alphanum_fraction": 0.5789473652839661, "avg_line_length": 19, "blob_id": "3e458d61efb419871515b5fe2e813bbde6197a68", "content_id": "09bc264978dda552963837e2697a18e1b1693085", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 380, "license_type": "no_license", "max_line_length": 48, "num_lines": 19, "path": "/users/migrations/0003_remove_users_fuck.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 -*-\n# Generated by Django 1.10.4 on 2017-01-29 13:59\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('users', '0002_users_fuck'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='users',\n name='fuck',\n ),\n ]\n" }, { "alpha_fraction": 0.7268370389938354, "alphanum_fraction": 0.7412140369415283, "avg_line_length": 35.764705657958984, "blob_id": "5f27fd7cf8bb2b382bbd43adbb39a7540630a734", "content_id": "c39989f60b8ca580894203f15214ba7e1328a2ba", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 626, "license_type": "no_license", "max_line_length": 80, "num_lines": 17, "path": "/users/models.py", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "from __future__ import unicode_literals\n\nfrom django.db import models\n\nclass Users(models.Model):\n name = models.CharField(max_length=200)\n email = models.CharField(max_length=200, null=True)\n cr_date = models.DateTimeField('date published')\n\nclass DeviceModels(models.Model):\n name = models.CharField(max_length=200)\n device_type = models.IntegerField()\n\nclass Devices(models.Model):\n user = models.ForeignKey(Users, on_delete=models.CASCADE, null=True)\n model = models.ForeignKey(DeviceModels, on_delete=models.CASCADE, null=True)\n last_online = models.DateTimeField('last device online in system')\n\n" }, { "alpha_fraction": 0.6057347655296326, "alphanum_fraction": 0.6057347655296326, "avg_line_length": 26.799999237060547, "blob_id": "881edca099e93567309a82668c0a4d1e8e68e19a", "content_id": "bbdc9c686ae20050f1c38226877163b146aec7eb", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 279, "license_type": "no_license", "max_line_length": 74, "num_lines": 10, "path": "/static/base/js/controllers/dashboard.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var ctrl = angular.module('App.controllers.DashBoard', ['LoaderService']);\n\nctrl.controller(\n 'dashboard',\n ['$scope', 'LoaderService', '$log', 'User',\n\t function($scope, LoaderService, $log, User) {\n\n $scope.to_login = LoaderService.to_login;\n \n }]);\n\n" }, { "alpha_fraction": 0.5163472294807434, "alphanum_fraction": 0.5169109106063843, "avg_line_length": 28.065574645996094, "blob_id": "bf58e936d6682dc741f8e3074afaef04d4f4f426", "content_id": "ef5ba29d6043123f0f9f469bbd19a9a2e34d00e7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 1774, "license_type": "no_license", "max_line_length": 87, "num_lines": 61, "path": "/static/base/js/base.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var app = angular\n .module('App', [\n 'ngRoute',\n 'App.controllers.Reg',\n 'App.controllers.Login',\n 'App.controllers.Main',\n 'App.controllers.DashBoard',\n 'User',\n 'CsrfService',\n 'LoaderService'\n ]);\n\napp.factory('httpRequestInterceptorAddHeaders', [function () {\n return {\n request: function (config) {\n\n //FIXME get token from service CsrfService\n config.headers['X-CSRFToken'] = $('input[name=csrfmiddlewaretoken]').val();\n config.headers['X-Requested-With'] = 'XMLHttpRequest';\n\n return config;\n }\n };\n}]);\n\napp.config(\n ['$locationProvider', '$httpProvider', '$routeProvider',\n function($locationProvider, $httpProvider, $routeProvider) {\n\n $httpProvider.interceptors.push('httpRequestInterceptorAddHeaders');\n\n if (!$httpProvider.defaults.headers.get) {\n $httpProvider.defaults.headers.get = {};\n }\n \n $httpProvider.defaults.headers.get['Cache-Control'] = 'no-cache';\n $httpProvider.defaults.headers.get['Pragma'] = 'no-cache';\n\n $routeProvider\n .when('/', {\n controller: 'login',\n templateUrl: '/users/login-template'\n })\n .when('/login', {\n controller: 'login',\n templateUrl: '/users/login-template'\n })\n .when('/reg', {\n controller: 'reg',\n templateUrl: '/users/reg-template'\n })\n .when('/dashboard', {\n controller: 'dashboard',\n templateUrl: '/users/dashboard-view'\n })\n ;\n\n $locationProvider.html5Mode(true);\n\n }]\n);\n\n" }, { "alpha_fraction": 0.4054054021835327, "alphanum_fraction": 0.4097297191619873, "avg_line_length": 24.66666603088379, "blob_id": "d495d299e4661f52765033c7f0364b24aad9979c", "content_id": "c5daa1631881d154c4f7872ccf7f464d4d5fcf2e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 925, "license_type": "no_license", "max_line_length": 81, "num_lines": 36, "path": "/static/base/js/controllers/login.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var ctrl = angular.module('App.controllers.Login', []);\n\nctrl.controller(\n 'login',\n ['$scope', '$http', '$log', '$location', '$timeout',\n\t function($scope, $http, $log, $location, $timeout) {\n\n $scope.user_data = {\n email: \"\",\n password: \"\"\n };\n\n $scope.login = function() {\n \n $http({\n method: 'POST',\n data: $.param($scope.user_data),\n url: '/users/try-login',\n headers: { 'Content-Type': 'application/x-www-form-urlencoded' }\n }).then(function(res) {\n\n if(res.data.status == 0) {\n $location.path('/dashboard')\n }\n\n });\n\n }\n\n $scope.alreadyLogin = function() {\n $timeout(function() {\n $location.path('/dashboard');\n }, 500);\n }\n\n }]);\n\n" }, { "alpha_fraction": 0.5, "alphanum_fraction": 0.5, "avg_line_length": 15.333333015441895, "blob_id": "f5eaa966e50385e23959eb40ee5dc5fbe995dbfa", "content_id": "e1940aafab7a520540d439f6f39dd178a449cc3d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "JavaScript", "length_bytes": 98, "license_type": "no_license", "max_line_length": 47, "num_lines": 6, "path": "/static/base/js/services/user.js", "repo_name": "tptrixtop/parent-controll-web", "src_encoding": "UTF-8", "text": "var user = angular.module('User', [])\n\n .service('User', ['$log', function ($log) {\n\n\n }]);\n" } ]	15
galactocalypse/python	https://github.com/galactocalypse/python	c8e98a1e08849bc98a13634f678752192bda7f67	de3eb250715624b5057e3a43c0b8d98058e42c6f	41f615f1c0ae662e749f0dc792ec07c35692c03d	refs/heads/master	2021-01-19T17:57:39.188227	2014-03-08T20:23:32	2014-03-08T20:23:32	16,374,093	0	2	null	null	null	null	null	[ { "alpha_fraction": 0.5100864768028259, "alphanum_fraction": 0.5365033745765686, "avg_line_length": 20.905263900756836, "blob_id": "62149415f503d5c564a7ee56832aa36127065aaa", "content_id": "7221ec4c5a631382322ffd52c33da93604d93cc2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2082, "license_type": "no_license", "max_line_length": 128, "num_lines": 95, "path": "/Unit4/sol19.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem 19: Hangman\nfrom random import randint\nfreq = [[\"e\"],[\"i\",\"t\"],[\"s\",\"a\",\"n\"],[\"h\",\"u\",\"r\",\"d\",\"m\"],[\"w\",\"g\",\"v\",\"l\",\"f\",\"b\",\"k\"], [\"o\",\"p\",\"j\",\"x\",\"c\",\"z\"], [\"y\",\"q\"]]\n\ndef get_group(i):\n\tif i <= 70:\n\t\treturn 0\n\telif i <= 130:\n\t\treturn 1\n\telif i <= 180:\n\t\treturn 2\n\telif i <= 220:\n\t\treturn 3\n\telif i <= 250:\n\t\treturn 4\n\telif i <= 270:\n\t\treturn 5\n\telif i <= 280:\n\t\treturn 6\n\telse:\n\t\treturn -1\n\ndef get_rand_guess(m):\n\tcfreq = freq\n\tfor i in range(len(cfreq)):\n\t\tfor j in range(len(cfreq[i])):\n\t\t\tif cfreq[i][j] in m:\n\t\t\t\tcfreq[i].remove(cfreq[i][j])\n\t\t\t\tj = j-1\t\n\tprint cfreq\n\tr = get_group(randint(1,280))\n\n\twhile len(cfreq[r]) == 0:\n\t\tr = get_group(randint(1,280))\n\te = randint(0, len(cfreq[r]) - 1)\n\treturn cfreq[r][e]\n\ndef is_char(c):\n\ti = ord(c)\n\treturn (i >= 97 and i <= 122)\n\ndef add_char(ans, h, c):\n\tres = \"\"\n\tfor i in range(len(ans)):\n\t\tif ans[i] == c:\n\t\t\tres = res+c\n\t\telse:\n\t\t\tres = res+h[i]\n\treturn res\n\nwhile True:\n\tans = raw_input(\"Enter name to guess: \").lower()\n\ttries = int(raw_input(\"Enter max tries: \"))\n\tfor i in range(10):\n\t\tprint \"\\n\"\n\tmissed = \"\"\n\th = \"\"\n\tfor i in ans:\n\t\tif is_char(i):\n\t\t\th = h+\"_\"\n\t\telse:\n\t\t\th = h+i\n\twhile True:\n\t\tprint \"Guess:\\n\"+h+\"\\nExhausted: [ \"+ missed +\" ]\\n\"\n\t\tch = raw_input(\"1. Guess yourself\\n2. Ask computer to guess\\n\")\n\t\tif ch == \"2\":\n\t\t\t#comp guess\n\t\t\tg = get_rand_guess(missed)\n\t\t\tprint \"Guessed: \", g, \"\\n\"\n\t\telse:\n\t\t\tgs = raw_input()\n\t\t\tg = str(gs[0]).lower()\n\t\tif g in ans:\n\t\t\tif g in h:\n\t\t\t\tprint \"Character used already.\\n \"+str(tries)+\" tries remaining\"\n\t\t\telse:\n\t\t\t\th = add_char(ans, h, g)\n\t\t\t\tprint \"Correct!\\n\"+str(tries)+\" tries remaining!\\n\\n\"\n\t\t\t\tif \"_\" not in h:\n\t\t\t\t\tch = raw_input(\"Game over. Continue?(y/n): \")\n\t\t\t\t\tif ch != \"y\" and ch != \"Y\":\n\t\t\t\t\t\texit(\"Thank you for playing!\")\n\t\t\t\t\telse:\n\t\t\t\t\t\tbreak\n\t\telse:\n\t\t\ttries = tries - 1\n\t\t\tmissed = missed + g\n\t\t\tprint \"Incorrect! \"+str(tries)+\" tries left.\\n\"\n\t\t\tif tries == 0:\n\t\t\t\tprint \"Game over! Answer: \"+ans+\"\\n\\n\"\n\t\t\t\tch = raw_input(\"Continue?(y/n): \")\n\t\t\t\tif ch != \"y\" and ch != \"Y\":\n\t\t\t\t\texit(\"Thank you for playing!\")\n\t\t\t\telse:\n\t\t\t\t\tbreak\n\n" }, { "alpha_fraction": 0.5688775777816772, "alphanum_fraction": 0.5880101919174194, "avg_line_length": 18.121952056884766, "blob_id": "0454437f1b0be23ba50a1f18a4e5380e37bce477", "content_id": "394f9d9688f8ac880f9a9c06003af16a17f5ec3a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 784, "license_type": "no_license", "max_line_length": 55, "num_lines": 41, "path": "/Unit4/sol17.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem17: Lycherel Numbers\ndef is_pal(z):\n\ts = str(z)\n\tfor i in range(len(s)>>1):\n\t\tif s[i] != s[len(s) - 1 - i]:\n\t\t\treturn False\n\treturn True\ndef reverse(ss):\n\ts = str(ss)\n\tr = \"\"\n\tfor i in range(len(s)):\n\t\tr = s[i] + r\n\treturn r\ndef add(x):\n\ty = reverse(str(x))\n\treturn int(x) + int(y)\ndef is_prob_lych(x):\n\tc = 0\n\twhile c <= 60:\n\t\tif is_pal(x):\t\n\t\t\treturn False\n\t\tc = c + 1\n\t\tx = add(x)\n\treturn True\n\na = int(raw_input('enter lower limit: '))\nb = int(raw_input('enter upper limit: '))\nn = 0\nlych = 0\npal = 0\nfor i in range(a, b + 1):\n\tif is_prob_lych(i):\n\t\tprint i, \" is probably lycherel.\"\n\t\tlych = lych + 1\n\telif is_pal(i):\n\t\tpal = pal + 1\n\telse:\n\t\tn = n + 1\nprint \"Natural palindromes: \", pal\nprint \"Non-Lycherel numbers yielding a palindrome: \", n\nprint \"Lycherels: \", lych\n" }, { "alpha_fraction": 0.5147826075553894, "alphanum_fraction": 0.5626087188720703, "avg_line_length": 18.827587127685547, "blob_id": "be5e6cdb3f910e2b613b8b994b0ebcb857e84624", "content_id": "0c7fd3a990d1181af8c996ae270e1e1dc2e2cb19", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1150, "license_type": "no_license", "max_line_length": 75, "num_lines": 58, "path": "/Unit5/sol26.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem 26: CaesarCipher\nfreq = {}\nt_f = [0]26\ntext = ''\n\ndef readfreq(ff):\n\t# reads letter freqs from file\n\tglobal freq\n\tr = readfromfile(ff).split(\"\\n\")\n\tfor l in r:\n\t\ta = l.split(\"\\t\")\n\t\tfreq[a[0]] = float(a[1])\n\ndef countfreq(s):\n\t# counts frequencies of letters in s\n\tt_f = [0]26\n\tfor i in range(26):\n\t\tt_f[i] = s.count(chr(97+i))\n\treturn t_f\n\ndef readfromfile(ff):\n\t# reads a file\n\tr = ''\n\twith open(ff) as f:\n\t\tr = f.read().strip()\n\treturn r\n\ndef shift(s, off):\n\tr = ''\n\tfor c in s:\n\t\tif ord(c) > 96 and ord(c) < 123:\n\t\t\tr = r + chr(97 + (ord(c)+off-97)%26)\n\t\telse:\n\t\t\tr = r + c\n\treturn r\n\ndef decrypt(text):\n\tlf = countfreq(text)\n\tmax1 = max(lf)\n\tarr = [x for x in range(26) if lf[x] == max1]\n\tfor a in arr:\n\t\tlf[a] = 0\n\t\tmax2 = max(lf)\n\t\tbrr = [x for x in range(26) if lf[x] == max2 and (a - 4)%26 == (x-19)%26]\n\t\tfor b in brr:\n\t\t\tlf[b] = 0\n\t\t\tmax3 = max(lf)\n\t\t\tcrr = [x for x in range(26) if lf[x] == max3 and (a - 4)%26 == x]\n\t\t\tfor c in crr:\n\t\t\t\tprint shift(text, (4 - a)%26)\n\t\t\tlf[b] = max2\n\t\tlf[a] = max1\n\n\nif __name__ == '__main__':\n\treadfreq('letter_frequencies.txt')\n\tcountfreq('cipher1.txt')\n\tdecrypt(readfromfile(raw_input()))\n" }, { "alpha_fraction": 0.45042839646339417, "alphanum_fraction": 0.4944920539855957, "avg_line_length": 20.972972869873047, "blob_id": "41880d317c3de78ca8cde391f39d2b4ce846cd67", "content_id": "072662cb6db6b90b8e976079720eb0b999d730d5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 817, "license_type": "no_license", "max_line_length": 64, "num_lines": 37, "path": "/Unit6/sol27.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem 27 - Rating Players\nkeys = []\np = []\ndef readplayers(ff):\n\tglobal keys, p\n\twith open(ff) as f:\n\t\td = f.read().strip()\n\tp = []\n\tls = d.split(\"\\n\")\n\tkeys = ls[0].split(\",\")\n\tfor i, l in enumerate(ls[1:]):\n\t\tpl = l.split(\",\")\n\t\tfor m in range(6, len(pl)):\n\t\t\tif pl[m] == 'NULL' or pl[m] == 'N':\n\t\t\t\tpl[m] = 0\n\t\t\telse:\n\t\t\t\tpl[m] = int(pl[m].strip())\n\t\tp.append(pl)\n\ndef eff(pl):\n\tif pl[6]:\n\t\ta = ((pl[8])+(pl[11])+(pl[12])+(pl[13])+(pl[14]))\n\t\tb = (((pl[17]) - (pl[18])) + ((pl[19]) - (pl[20])) + (pl[15]))\n\t\treturn (a - b)/pl[6]\n\telse:\n\t\treturn 0\n\nif __name__ == '__main__':\n\treadplayers('player_regular_season.csv')\n\teffs = []\n\tfor pl in p:\n\t\teffs.append([eff(pl), pl[2]+\" \"+pl[3]])\n\teffs.sort()\n\teffs.reverse()\n\twith open('top50', 'w') as f:\n\t\tfor e in effs[:50]:\n\t\t\tf.write(e[1] + \":\" + str(e[0])+\"\\n\")\n\t\n\t\n" }, { "alpha_fraction": 0.542330265045166, "alphanum_fraction": 0.5699915885925293, "avg_line_length": 25.44444465637207, "blob_id": "56f4a61f7ae49b9302c886920a0aa7f5c9ccd5fc", "content_id": "abb288a8459158d46ceb0350204d331c3eb1cb04", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1193, "license_type": "no_license", "max_line_length": 87, "num_lines": 45, "path": "/Unit4/sol21.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem21: CaesarCipher\n\ndef encode(s, n):\n\tres = \"\"\n\tfor ch in s:\n\t\tif ord(ch) >= 97 and ord(ch) <= 122:\n\t\t\tres += chr(97 + (ord(ch) - 97 + n)%26)\n\t\telse:\n\t\t\tres += ch\n\treturn res\n\nch = raw_input('Enter e to encode, d to decode or q to quit:').lower()\nwhile ch != 'e' and ch != 'd' and ch != 'q':\n\tch = raw_input('Invalid entry!\\nEnter e to encode, d to decode or q to quit:').lower()\nif ch == 'e':\n\ts = raw_input(\"Input string: \")\n\tn = 0\n\twhile n < 1 or n > 25:\n\t\tn = int(raw_input(\"Enter the rotation integer[1 - 25]: \"))\n\tprint 'Encoded string: ', encode(s, n)\nelif ch == 'd':\n\ts = raw_input(\"Input string: \")\n\tw = raw_input(\"Search term: \")\n\tch = raw_input(\"Part 1 or 2? : \")\n\twhile ch not in ['1', '2']:\n\t\tch = raw_input(\"Invalid input.\\nPart 1 or 2? : \")\n\tif ch == '1':\n\t\tn = int(raw_input(\"Rotation: \"))\n\t\tw = encode(w, n)\n\t\tif w in s:\n\t\t\tprint \"Decoded string; \", encode(s, 26 - n)\n\t\telse:\n\t\t\tprint \"Not found!\"\n\telse:\n\t\tfound = False\n\t\tfor i in range(26):\n\t\t\tif w in encode(s, i):\n\t\t\t\tfound = True\n\t\t\t\tprint \"Rotation: \", 26 - i\n\t\t\t\tprint \"Decoded string: \", encode(s, i) \n\t\t\t\tbreak\n\t\tif found == False:\n\t\t\tprint \"Word does not occur in any rotation.\"\nelse:\n\texit('Exiting...')\n\t\n\n" }, { "alpha_fraction": 0.559808611869812, "alphanum_fraction": 0.5789473652839661, "avg_line_length": 26.799999237060547, "blob_id": "22e75617dbd667a2e8971e36d2ea224973600c27", "content_id": "e5c8624a80c22be7c44b014687217dc7dde27174", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 418, "license_type": "no_license", "max_line_length": 52, "num_lines": 15, "path": "/Unit3/sol15.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# p15: Egyptian Multiplication\nwhile True:\n\tprint 'enter numbers to multiply:'\n\tx = a = int(raw_input('enter first number: '))\n\ty = b = int(raw_input('enter second number: '))\n\tprod = 0\n\twhile b > 0:\n\t\tif b%2 == 1:\n\t\t\tprod += a\n\t\tb = int(b/2)\n\t\ta = a2\t\n\tprint 'Product of ', x, ' and ', y, ' is: ', prod\n\tchoice = raw_input('Do you want to continue?(y/n)')\n\tif choice != 'Y' and choice != 'y':\n\t\texit('Quitting...')\n\n" }, { "alpha_fraction": 0.5090090036392212, "alphanum_fraction": 0.5585585832595825, "avg_line_length": 17.5, "blob_id": "421bbeb403a2db9f218a5df1e81da1b0ae317c46", "content_id": "18e4a245ea65d6d1eccd325257b087830d8a54e2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 222, "license_type": "no_license", "max_line_length": 83, "num_lines": 12, "path": "/Unit3/sol11.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob11: DigitCount\ndef count_digs(n, x):\n\tif x == 0:\n\t\tc = 1\n\telse:\n\t\tc = 0\n\twhile n > 0:\n\t\tif n%10 == x:\n\t\t\tc += 1\n\t\tn /= 10\n\treturn c\nprint count_digs(int(raw_input('enter number: ')), int(raw_input('enter digit: ')))\n" }, { "alpha_fraction": 0.46289753913879395, "alphanum_fraction": 0.4805653691291809, "avg_line_length": 24.727272033691406, "blob_id": "bad4c39600ba8982be871b89c88e04ba1e6f64fc", "content_id": "19fe7aba9dbc2f7e5997abc34140108d63a38aaa", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 283, "license_type": "no_license", "max_line_length": 42, "num_lines": 11, "path": "/Unit3/sol12.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob12: LatinSquares\nn = int(raw_input('enter order: '))\na = int(raw_input('enter top-left: '))\nif a < 1 or a > n:\n\texit(\"invalid offset\")\nfor i in range(n):\n\ts = \"\"\n\tfor j in range(n):\n\t\ts = s + \" \" + str(1 + (a + i + j - 1)%n)\n\tprint s\nprint \"==================================\"\n" }, { "alpha_fraction": 0.40066224336624146, "alphanum_fraction": 0.6821191906929016, "avg_line_length": 15.777777671813965, "blob_id": "ead38e367aef210295bee304923b3731d7a8e75f", "content_id": "5c625e59f0362ab1aa0e463c496c3e1e28c6b118", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 302, "license_type": "no_license", "max_line_length": 36, "num_lines": 18, "path": "/Unit1/sol3.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "s = raw_input('enter float value: ')\nm = float(s)\nprint m\nbcd = m1610117.64724\nff = m17602414/220\nmach = m31760/1130/3600\npsl = (m1610/36)/299792458\nprint bcd\nprint ff\nprint mach\nprint psl\n\"\"\"\nx3600/1609.34\n1mach = 1130ft/sec\n1 mile = 1760 yards\n1meter = 117.647 bc\n1mile = 1609.34meters\n\"\"\"\n" }, { "alpha_fraction": 0.6912751793861389, "alphanum_fraction": 0.7046979665756226, "avg_line_length": 17.625, "blob_id": "4c804acb2c4e4bbed9aa5da48737c7cecb8856ac", "content_id": "96ad6299a410f66df6d5ad9cf5109c13db2316bc", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 149, "license_type": "no_license", "max_line_length": 28, "num_lines": 8, "path": "/Unit5/sol23.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem 23: WeFeelFine\n# API broken\nimport urllib\nu = raw_input(\"Enter URL: \")\nconn = urllib.urlopen(u)\ndata = conn.read()\nconn.close()\nprint data\n" }, { "alpha_fraction": 0.5081967115402222, "alphanum_fraction": 0.6338797807693481, "avg_line_length": 25.14285659790039, "blob_id": "7c012ee6d3539237cd997a15daa5829769a9f87f", "content_id": "11983313932e0e1ec68d94236999474433a93117", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 183, "license_type": "no_license", "max_line_length": 42, "num_lines": 7, "path": "/Unit1/sol2.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "s = raw_input('Enter measure in gallons:')\ng = float(s)\nprint 'Liters: ', 3.7854g\nprint 'Barrels: ', g/19.5\nprint 'CO2: ', 20g\nprint 'Energy: ', 115000g/75700\nprint 'Price: ', 4g\n" }, { "alpha_fraction": 0.46399998664855957, "alphanum_fraction": 0.5019999742507935, "avg_line_length": 19, "blob_id": "7d28af439fe2dccb3e503d0678a98139387a784b", "content_id": "ab6af13ff1be4b4e9c40e1adfa28abfb8251ac68", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 500, "license_type": "no_license", "max_line_length": 53, "num_lines": 25, "path": "/Unit5/sol25.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem 25: Scrambled words\nfrom random import shuffle\ndef process(fn):\n\twith open(fn) as f:\n\t\twords = f.read().split(\" \")\n\t\tres = ''\n\tfor w in words:\n\t\tw = w.strip()\n\t\tl = ord(w[-1])\n\t\tif (l >= 65 and l <= 90) or (l >= 97 and l <= 122):\n\t\t\tl = 0\n\t\telse:\n\t\t\tw = w[:-1]\n\t\tif len(w) > 3:\n\t\t\tn = list(w[1:-1])\n\t\t\tshuffle(n)\n\t\t\tn = ''.join(n)\n\t\t\tn = w[0] + n + w[-1]\n\t\telse:\n\t\t\tn = w\n\t\tn = n+chr(l)\n\t\tres = res+' '+n\n\treturn res\nif __name__ == '__main__':\n\tprint process(raw_input('Enter filename: '))\n" }, { "alpha_fraction": 0.626288652420044, "alphanum_fraction": 0.6675257682800293, "avg_line_length": 24.799999237060547, "blob_id": "09ce7a3f42ad57310b84a6c1284b82a4d3a3b814", "content_id": "1f87763e1867de04ad63b91226506ae77c274906", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 388, "license_type": "no_license", "max_line_length": 46, "num_lines": 15, "path": "/Unit2/sol8.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob8: Tones\n# weird that loops have been forbidden\nfrom math import pow\ndef findFreq(pair):\n\toctave = int(pair)\n\tpitch = int(pair10) % 10\n\tprint 'Octave: ', octave\n\tprint 'Pitch class: ', pitch\n\to = octave - 4.0\n\tm = pitch - 9.0\n\treturn 440pow(2, o + m/12.0)\n\nprint 'Printing octpch values!'\npair = float(raw_input('enter octpch pair: '))\nprint 'Frequency: ', findFreq(pair), ' Hz'\n\n" }, { "alpha_fraction": 0.5316901206970215, "alphanum_fraction": 0.6056337952613831, "avg_line_length": 24.727272033691406, "blob_id": "6c6e520e30b7f29d21f09d0aa5bab369792b973f", "content_id": "8319b8dd871d9063af5e82af958d685134276aac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 284, "license_type": "no_license", "max_line_length": 82, "num_lines": 11, "path": "/Unit2/sol7.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob7: MacArthur\nmonth = int(raw_input('enter your birth month[1 for Jan, 2 for Feb and so on]: '))\nage = int(raw_input('enter your age: '))\nx = (2month + 5)50 + age - 365\nprint 'Special number: ', x\nx += 115\nna = x % 100\nx /= 100\nnm = x%10\nprint 'Age: ', na\nprint 'Month: ', nm\n\n" }, { "alpha_fraction": 0.512635350227356, "alphanum_fraction": 0.5234656929969788, "avg_line_length": 18.75, "blob_id": "9377e5efcbce64b91149cb2ca1906a8aa0dc076c", "content_id": "b4ef2c0691beb8622341bf0a31e4a8fdb07246c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 554, "license_type": "no_license", "max_line_length": 48, "num_lines": 28, "path": "/Unit3/sol16.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# p16: Calculator\nwhile True:\n\ts = raw_input('enter expression to evaluate: ')\n\tarr = s.split(\" \")\n\ta = float(arr[0])\n\tb = float(arr[2])\n\tc = arr[1]\n\tif c == \"+\":\n\t\tres = a + b\n\t\tprint 'Result: ', res\n\telif c == \"-\":\n\t\tres = a - b\n\t\tprint 'Result: ', res\n\telif c == \"\":\n\t\tres = a * b\n\t\tprint 'Result: ', res\n\telif c == \"/\":\n\t\tif b == 0:\n\t\t\tprint 'Division by zero error!'\n\t\telse:\n\t\t\tres = a / b\n\t\t\tprint 'Result: ', res\n\telse:\n\t\tprint 'Invalid operator: ', c\n\tch = raw_input('Continue?(y/n)')\n\tif ch != \"Y\" and ch != \"y\":\n\t\tprint \"Quitting...\"\n\t\tbreak\n\n" }, { "alpha_fraction": 0.5968169569969177, "alphanum_fraction": 0.6259946823120117, "avg_line_length": 21.117647171020508, "blob_id": "2fa3848defc13666d6e4004dc2a0baa7c6071e33", "content_id": "7e6dad2d4ebb1bda6f14bdec1cb3d7fa8e4ae4da", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 377, "license_type": "no_license", "max_line_length": 101, "num_lines": 17, "path": "/Unit2/sol6.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob6: Einstein\ndef rev(n):\n\tx = 0\n\twhile n:\n\t\tx = x10 + n%10\n\t\tn /= 10\n\treturn x\nn = int(raw_input('Enter a 3-digit number with the first and last digits differing by at least 2: '))\nr = rev(n)\nprint 'Original: ', n\nprint 'Reverse: ', r\ndiff = n - r\ndiff = -diff if diff < 0 else diff\nprint 'Difference: ', diff\ndr = rev(diff)\nprint 'Reverse: ', dr\nprint 'Sum: ', diff+dr\n\n" }, { "alpha_fraction": 0.5672823190689087, "alphanum_fraction": 0.6860158443450928, "avg_line_length": 22.625, "blob_id": "d14c717b6b0440c54e5732eb88e0bc6ba46d486f", "content_id": "b8fa62d4d7b6396ff7e4c5b195298e7519754e9b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 379, "license_type": "no_license", "max_line_length": 60, "num_lines": 16, "path": "/Unit1/sol5.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob5: TimeTravel\nimport math\ns = raw_input('enter speed(percentage of speed of light): ')\nperc = float(s)\nfactor = 100/math.sqrt(10000 - percperc)\nc = 299792458\nw = 70000factor\nt1 = 4.3/factor\nt2 = 6.0/factor\nt3 = 309/factor\nt4 = 2000000/factor\nprint 'weight: ', w\nprint 'Alpha centauri: ', t1\nprint 'Bernard\\'s Star: ', t2\nprint 'Betelgeuse: ', t3\nprint 'Andromeda: ', t4\n\n" }, { "alpha_fraction": 0.6078431606292725, "alphanum_fraction": 0.6666666865348816, "avg_line_length": 11.75, "blob_id": "6403251777301885f635b6831f574a8ef9324778", "content_id": "8a5804264fd23d030637f850cfe3c808977bca9f", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 51, "license_type": "no_license", "max_line_length": 35, "num_lines": 4, "path": "/README.md", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "python\n======\n\nMSU - CSE 231 Assignment Solutions.\n" }, { "alpha_fraction": 0.6020408272743225, "alphanum_fraction": 0.6020408272743225, "avg_line_length": 20.77777862548828, "blob_id": "46f2ca67e9165e9e2b4ff0048882d70e1cb21725", "content_id": "3aa75852c55b7e9d56c88fc2e4aee8c7e7eb6da2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 196, "license_type": "no_license", "max_line_length": 39, "num_lines": 9, "path": "/Unit1/sol1.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "str = raw_input('enter a number')\na = int(str)\nstr = raw_input('enter another number')\nb = int(str)\nprint 'Add: ', a+b\nprint 'Subt:', a-b\nprint 'Prod: ', ab\nprint 'Quo: ', a/b\nprint 'Rem: ', a%b\n" }, { "alpha_fraction": 0.4747330844402313, "alphanum_fraction": 0.4932384192943573, "avg_line_length": 19.970149993896484, "blob_id": "44063f90cd7dd4fd33be7a652941afdc2247837a", "content_id": "6c983db0b283ebac5ea1e459b0c56c54eed982c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1405, "license_type": "no_license", "max_line_length": 95, "num_lines": 67, "path": "/Unit4/sol22.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem 22: ROck, Paper, Scissors\nfrom random import randint\nvalid = ['r', 'p', 's', 'q']\ndef input():\n\treturn raw_input('Enter R/r for rock, P/p for paper, S/s for scissors, Q/q to quit: ').lower()\nusr = 0\ncomp = 0\nr = 0\np = 0\ns = 0\nt = 0\ndef choose():\n\tanti = {'r': 'p', 'p': 's', 's': 'r'}\n\tm = max(r, p, s)\n\tarr = []\n\tif r == m:\n\t\tarr.append('r')\n\tif p == m:\n\t\tarr.append('p')\n\tif s == m:\n\t\tarr.append('s')\n\treturn anti[arr[randint(0, len(arr) - 1)]]\nwhile True:\n\tch = choose()\n\tinp = input()\n\twhile inp not in valid:\n\t\tprint \"Invalid input!\"\n\t\tinp = input()\n\tif inp == 'q':\n\t\tprint \"Choices: R \", r, \"\\tP \", p, \"\\tS \", s\n\telse:\n\t\tif ch == inp:\n\t\t\tt += 1\n\t\t\tif inp == 'r':\n\t\t\t\tr += 1\n\t\t\tif inp == 'p':\n\t\t\t\tp += 1\n\t\t\tif inp == 's':\n\t\t\t\ts += 1\n\t\t\t\n\t\t\tprint \"Tie!\"\n\t\telif inp == 'r' and ch == 'p':\n\t\t\tr += 1\n\t\t\tprint \"Paper wraps rock!\"\n\t\t\tcomp += 1\n\t\telif inp == 'p' and ch == 's':\n\t\t\tp += 1\n\t\t\tprint \"Scissors cut paper\"\n\t\t\tcomp += 1\n\t\telif inp == 's' and ch == 'r':\n\t\t\ts += 1\n\t\t\tprint \"Rock beats scissors\"\n\t\t\tcomp += 1\n\t\telif inp == 'r' and ch == 's':\n\t\t\tr += 1\n\t\t\tprint \"Rock beats scissors\"\n\t\t\tusr += 1\n\t\telif inp == 'p' and ch == 'r':\n\t\t\tp += 1\n\t\t\tprint \"Paper wraps rock!\"\n\t\t\tusr += 1\n\t\telif inp == 's' and ch == 'p':\n\t\t\ts += 1\n\t\t\tprint \"Scissors cut paper\"\n\t\t\tusr += 1\n\t\tprint \"Scores: User \" + str(usr) + \"\\tComp \" + str(comp) + \"\\tTie \"+str(t)\n\t\tprint \"Choices: R \", r, \"\\tP \", p, \"\\tS \", s\n" }, { "alpha_fraction": 0.5638650059700012, "alphanum_fraction": 0.6062210202217102, "avg_line_length": 24.16666603088379, "blob_id": "c553265bd06498e6a42e3222cacab6623a3c477d", "content_id": "03d6b196d17382d34f72cf686fcd678ebf4cefe9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1511, "license_type": "no_license", "max_line_length": 69, "num_lines": 60, "path": "/Unit5/sol24.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem24: GDP and Unemployability\nimport numpy as np\nimport matplotlib.pyplot as pl\n\nglist = {}\nulist = {}\n\ndef readgdp(gf):\n\tglobal glist\n\twith open(gf) as g:\n\t\tr = g.read().strip().split(\"\\n\")\n\t\tfor i in range(1948, 2010):\n\t\t\tarr = [float((x.split(\" \"))[-1]) for x in r if x[:4] == str(i)]\n\t\t\tif arr:\n\t\t\t\tglist[i] = sum(arr)/len(arr)\n\ndef readunemp(uf):\n\tglobal ulist\n\twith open(uf) as u:\n\t\tr = u.read().strip().split(\"\\n\")[1:]\n\t\tfor i in range(0, len(r)):\n\t\t\tarr = r[i].replace(\",\", \" \").strip().split(\" \")\n\t\t\tvals = map(float, arr[1:])\n\t\t\ty = int(arr[0])\n\t\t\tif vals:\n\t\t\t\tavg = sum(vals)/len(vals)\n\t\t\t\tulist[y] = avg\n\ndef fetchyear(y):\n\tif y not in glist or y not in ulist:\n\t\tprint \"Year out of range! Try again...\"\n\t\treturn 0\n\telse:\n\t\tprint \"Average GDP in\", y, \":\", glist[y]\n\t\tprint \"Average unemployment in\", y, \":\", ulist[y]\n\t\treturn 1\ndef showgraph():\n\tglobal ulist, glist\n\tfig = pl.figure()\n\tax1 = fig.add_subplot(111)\n\txr = np.arange(1948, 2008, 1)\n\ty1 = [(glist[i+1]-glist[i])100/glist[i] for i in range(1948, 2008)]\n\tax1.plot(xr, y1, 'b-')\n\tax1.set_xlabel('Year')\n\tax1.set_ylabel('Change in GDP')\n\t\n\tax2 = ax1.twinx()\n\ty2 = [ulist[x] for x in range(1948, 2008, 1)]\n\tax2.plot(xr, y2, 'r-')\n\tax2.set_ylabel('Unemployment rate')\n\tax1.set_title('Change in GDP vs Unemployment')\n\tpl.show()\n\t\nif __name__ == \"__main__\":\n\treadgdp(\"gdp.txt\")\n\treadunemp(\"unemp.csv\")\n\twhile not fetchyear(int(raw_input(\"Enter year: \"))):\n\t\tpass\n\tif raw_input(\"Enter Y to generate graph: \").lower() == 'y':\n\t\tshowgraph()\n\n" }, { "alpha_fraction": 0.6000000238418579, "alphanum_fraction": 0.6000000238418579, "avg_line_length": 9, "blob_id": "5a4bd6566f7b65ad77c3bd0de157f040908f04a1", "content_id": "7957cc8475e5e3f0f89e10742d2bcc6d7f4b7a9d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 20, "license_type": "no_license", "max_line_length": 9, "num_lines": 2, "path": "/Unit1/inp1.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "print 'x'\nprint `y`\n" }, { "alpha_fraction": 0.4966159164905548, "alphanum_fraction": 0.5499153733253479, "avg_line_length": 17.761905670166016, "blob_id": "9ad84aef435a8ea6d013469b8d21a3538be2c303", "content_id": "2e43ee8d19fc29f4615456d5ddf16053f771b48b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1182, "license_type": "no_license", "max_line_length": 46, "num_lines": 63, "path": "/Unit4/sol20.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Prob20: Mastermind\ns = raw_input('Enter 4-digit key: ')\niarr = list(\"0123456789\")\narr = list(\"0123456789\")\nfor i in range(10):\n\tiarr[i] = 0\nfor i in s:\n\tif ord(i) >= 48 and ord(i) <= 57:\n\t\tiarr[ord(i) - 48] += 1\ntries = 0\ngs = []\nwhile True:\n\tinvalid = True\n\twhile invalid:\n\t\tprint 'Used guesses: ', gs\n\t\tinvalid = False\n\t\tg = raw_input('Enter guess: ')\n\t\t#Rule 1\n\t\tif len(g) != 4:\n\t\t\tinvalid = True\n\t\tif invalid:\n\t\t\tprint 'Bad guess.'\n\t\t\tcontinue\n\t\t#Rule 2\n\t\tfor i in range(10):\n\t\t\tarr[i] = 0\n\t\tfor i in g:\n\t\t\tif ord(i) >= 48 and ord(i) <= 57:\n\t\t\t\tarr[ord(i) - 48] += 1\n\t\t\telse:\n\t\t\t\tinvalid = True\n\t\t\t\tbreak\n\t\tif invalid:\n\t\t\tprint 'Bad guess.'\n\t\t\tcontinue\n\t\t#Rule 3\n\t\tfor i in range(10):\n\t\t\tif arr[i] > 1:\n\t\t\t\tinvalid = True\n\t\t\t\tbreak\n\t\tif invalid:\n\t\t\tprint 'Bad guess.'\n\n\tgs.append(g)\n\ttries += 1\n\tif g == s:\n\t\tprint 'Correct! Used ', tries, 'tries.'\n\t\tbreak\n\telse:\n\t\tprint 'Incorrect guess.'\n\t\tif tries == 12:\n\t\t\tprint 'All tries used. Game over. Key: ', s\n\t\telse:\n\t\t\tc = 0\n\t\t\td = 0\n\t\t\tfor i in range(4):\n\t\t\t\tif s[i] == g[i]:\n\t\t\t\t\td += 1\n\t\t\tprint 'Correct digits: ', d\n\t\t\tfor i in range(10):\n\t\t\t\tif arr[i] == 1 and iarr[i] == 1:\n\t\t\t\t\tc += 1\n\t\t\tprint 'Wrong positions: ', c - d\n" }, { "alpha_fraction": 0.5653846263885498, "alphanum_fraction": 0.6115384697914124, "avg_line_length": 20.66666603088379, "blob_id": "fe14e0d32baf340e84d885b8a1ff4fc59f601737", "content_id": "7bf9e7b1d6a965da9cc49a71fdff2582c47fd16d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 260, "license_type": "no_license", "max_line_length": 47, "num_lines": 12, "path": "/Unit3/sol14.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# p14: Polygonal\nfrom math import sqrt\nn = int(raw_input('enter number: '))\nx = int(sqrt(n))\nif xx < n:\n\texit('Invalid input. Must be perfect square.')\nif x%2 == 1:\n\tprint int(x(x-1)/2)\n\tprint int(x(x+1)/2)\nelse:\n\tprint int((x-1)x/2)\n\tprint int(x(x+1)/2)\n" }, { "alpha_fraction": 0.6196078658103943, "alphanum_fraction": 0.6653594970703125, "avg_line_length": 22.15151596069336, "blob_id": "40821c6dce9d98aef29ce03662c7900c9a7adece", "content_id": "622135be229b721fc4b3764054c755671e8ee722", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 765, "license_type": "no_license", "max_line_length": 58, "num_lines": 33, "path": "/Unit2/sol10.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob10: TurtleGraphicsPolygon\nimport turtle\nimport time\nimport os\nimport math\nprint 'Drawing a filled polygon with turtle'\nprint 'Enter colour values [0 - 1]'\nr = 1.0 - float(raw_input('enter red: '))\ng = 1.0 - float(raw_input('enter green: '))\nb = 1.0 - float(raw_input('enter blue: '))\nedge = int(raw_input('enter edge length: '))\nangle = 360/5\n\nlabel = \"(\" + str(r) + \", \" + str(g) + \", \" + str(b) + \")\"\nturtle.clear()\n\nturtle.fillcolor(r, g, b)\nturtle.goto(0,0)\nturtle.up()\nh = edge0.5/math.cos(54math.pi/180)\np = hmath.sin(54math.pi/180)\nturtle.forward(p)\nturtle.right(90)\nturtle.backward(edge0.5)\nturtle.down()\nturtle.begin_fill()\nfor i in range(5):\n\tturtle.forward(edge)\n\tturtle.right(angle)\nturtle.end_fill()\nturtle.done()\ntime.sleep(1)\nos._exit(1)\n\n" }, { "alpha_fraction": 0.5482189655303955, "alphanum_fraction": 0.5682015419006348, "avg_line_length": 18.16666603088379, "blob_id": "18c540d4cc74064c670ed1eb432a0441c29bda9a", "content_id": "943f1d07ed2a871b34fa4c98fc7e32653f025b28", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1151, "license_type": "no_license", "max_line_length": 67, "num_lines": 60, "path": "/Unit4/sol18.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# Problem18: NumberGuessing\nacc = False\nwhile True:\n\ttry:\n\t\ts = raw_input('enter a 5-digit number with no repeated digits: ')\n\t\tnum = s\n\t\tn = int(s)\n\t\td = dict()\n\t\tacc = True\n\t\tfor i in s:\n\t\t\tif i in d:\n\t\t\t\td[i] += 1\n\t\t\t\tacc = False\n\t\t\telse:\n\t\t\t\td[i] = 1\n\t\tnum_dict = d\n\t\tif acc:\n\t\t\tif len(s) != 5:\n\t\t\t\tprint 'Only 5 digit numbers, please'\n\t\t\telse:\n\t\t\t\tbreak\n\texcept ValueError:\n\t\texit('A number! How hard can it be?')\nfor i in range(20):\n\tprint \"\\n\"\nmax = 10\ntries = 0\nwhile True:\n\ttries += 1\n\tacc = False\n\twhile True:\n\t\ts = raw_input('guess the number: ')\n\t\ttry:\n\t\t\tn = int(s)\n\t\t\tif len(s) == 5:\n\t\t\t\tacc = True\n\t\t\tif acc:\t\n\t\t\t\tbreak\n\t\t\telse:\n\t\t\t\tprint \"Invalid input!\"\n\t\texcept ValueError:\n\t\t\tprint \"Invalid input!\"\n\t\t\tcontinue\n\td = dict()\n\tcorr = 0\n\tcorr_pos = 0\n\tfor i in range(len(s)):\n\t\tif s[i] not in d:\n\t\t\td[s[i]] = 1;\n\t\t\tif s[i] in num_dict:\n\t\t\t\tcorr += 1\n\t\t\tif s[i] == num[i]:\n\t\t\t\tcorr_pos += 1\n\tprint 'Correct digits: ', corr\n\tprint 'Correct position: ', corr_pos\n\tprint 'Tries: ', tries\n\tif tries == 10:\n\t\texit(\"Could not guess! Number was \"+ str(num))\n\tif corr == 5 and corr_pos == 5:\n\t\texit(\"Correct guess in \"+ str(tries) + \" tries!\")\n\n" }, { "alpha_fraction": 0.3724137842655182, "alphanum_fraction": 0.5241379141807556, "avg_line_length": 17.125, "blob_id": "5b411a7ada72023c99237a6d8edee72fd689c8fd", "content_id": "54567bf3ffef671f576aa44ea7acec7460c6031a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 145, "license_type": "no_license", "max_line_length": 39, "num_lines": 8, "path": "/Unit5/test.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "import random as r\nl = (2008 - 1948 + 1)12\ns = \"\"\nfor i in range(l):\n\ts = s + str(r.randint(300, 500)/100.0)\n\tif i < l-1:\n\t\ts = s + \",\"\nprint s\n" }, { "alpha_fraction": 0.5494505763053894, "alphanum_fraction": 0.6813187003135681, "avg_line_length": 25, "blob_id": "1bb8223367f47ddddca2c0b7b938d83884d7ea66", "content_id": "feea02c02e734f06564928a5207ef401e3b93830", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 182, "license_type": "no_license", "max_line_length": 39, "num_lines": 7, "path": "/Unit1/sol4.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob4: Population\ninit = 307357870\ns = raw_input('enter number of years')\nyears = int(s)\ntime = years365243600\nres = init + time/7 - time/13 + time/35\nprint 'Population: ', res\n" }, { "alpha_fraction": 0.5061224699020386, "alphanum_fraction": 0.5489795804023743, "avg_line_length": 14.3125, "blob_id": "c42233def9589657987b5034960389b2ba668cb3", "content_id": "a2bca7297a2e9f37dfbdede2e38a3d152486ebd2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 490, "license_type": "no_license", "max_line_length": 38, "num_lines": 32, "path": "/Unit3/sol13.py", "repo_name": "galactocalypse/python", "src_encoding": "UTF-8", "text": "# prob13: Persistence\ndef sum_digs(x):\n\tc = 0\n\twhile x > 0:\n\t\tc += x%10\n\t\tx /= 10\n\treturn c\ndef mult_digs(x):\n\tc = 1\n\twhile x > 0:\n\t\tc = x%10\n\t\tx /= 10\n\treturn c\ndef add_pers(x):\n\tp = 0\n\twhile x > 9:\n\t\tx = sum_digs(x)\n\t\tp += 1\n\tprint 'add_pers: ', p\n\tprint 'add_root: ', x\ndef mul_pers(x):\n\tp = 0\n\twhile x > 9:\n\t\tx = mult_digs(x)\n\t\tp = p+1\n\tprint 'mul_persistence: ', p\n\tprint 'mul_root: ', x\nn = int(raw_input('enter a number: '))\nif n < 0:\n\texit('invalid input')\nadd_pers(n)\nmul_pers(n)\n" } ]	29
grubberr/dog_and_cats	https://github.com/grubberr/dog_and_cats	af30abf888b56f2d40190339f4231ccf9d1e89d8	351086542e361f88b73c90350606a4adddce80d2	2304bba6e3d040f9d637fa5af633d6a9beb20d22	refs/heads/master	2021-05-04T13:44:58.488890	2018-02-05T15:18:08	2018-02-05T15:18:08	120,321,653	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6867924332618713, "alphanum_fraction": 0.6905660629272461, "avg_line_length": 23, "blob_id": "c9c48394a807d854b15ede0b09a1a48dc94ec61f", "content_id": "b2de79ca6006fbcdc67050229bb41e08214af022", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 265, "license_type": "no_license", "max_line_length": 64, "num_lines": 11, "path": "/utils.py", "repo_name": "grubberr/dog_and_cats", "src_encoding": "UTF-8", "text": "\nimport sys\nimport datetime\nfrom models import date_format\n\ndef get_birthday_or_exit(birthday):\n\n try:\n return datetime.datetime.strptime(birthday, date_format)\n except ValueError:\n print(\"incorrect birthday: %s\" % birthday)\n sys.exit(1)\n" }, { "alpha_fraction": 0.44680851697921753, "alphanum_fraction": 0.6808510422706604, "avg_line_length": 14.666666984558105, "blob_id": "07f61a8fbba777caad078d8ca0d30b84394a28dd", "content_id": "14cd7baade5986a396ce1ced9b73200329e6f3c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Text", "length_bytes": 47, "license_type": "no_license", "max_line_length": 19, "num_lines": 3, "path": "/requirements.txt", "repo_name": "grubberr/dog_and_cats", "src_encoding": "UTF-8", "text": "mongoengine==0.15.0\npymongo==3.6.0\nsix==1.11.0\n" }, { "alpha_fraction": 0.5489697456359863, "alphanum_fraction": 0.549987256526947, "avg_line_length": 26.29861068725586, "blob_id": "9f57c21c693183561cd2264fea8fa874afdad3e8", "content_id": "18d1ad007e01ec2dc5a97c96ff6aa16b8c1375bd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3931, "license_type": "no_license", "max_line_length": 73, "num_lines": 144, "path": "/users.py", "repo_name": "grubberr/dog_and_cats", "src_encoding": "UTF-8", "text": "#!/Users/ant/dog_and_cats/env/bin/python3\n\nimport sys\nimport argparse\nimport datetime\nfrom mongoengine.errors import ValidationError\nfrom models import User, date_format, Pet, Cat, Dog\nfrom utils import get_birthday_or_exit\n\ndef main(args):\n\n if args.subparser == 'add':\n\n birthday = get_birthday_or_exit(args.birthday)\n\n u = User(\n first_name=args.first_name,\n last_name=args.last_name,\n birthday=birthday)\n\n u.save()\n\n print(\"user created id = '%s'\" % u.pk)\n\n elif args.subparser == 'del':\n\n try:\n u = User.objects.get(id=args.pk)\n except (User.DoesNotExist, ValidationError):\n print(\"user not found id = '%s'\" % args.pk)\n else:\n u.delete()\n print(\"user removed id = '%s'\" % u.pk)\n\n elif args.subparser == 'update':\n\n try:\n u = User.objects.get(id=args.pk)\n except (User.DoesNotExist, ValidationError):\n print(\"user not found id = '%s'\" % args.pk)\n else:\n\n if args.first_name:\n u.first_name = args.first_name\n\n if args.last_name:\n u.last_name = args.last_name\n\n if args.birthday:\n birthday = get_birthday_or_exit(args.birthday)\n u.birthday = birthday\n\n u.save()\n\n print(\"user updated id = '%s'\" % u.pk)\n\n elif args.subparser == 'list':\n\n if args.pk:\n\n try:\n u = User.objects.get(id=args.pk)\n except (User.DoesNotExist, ValidationError):\n print(\"user not found id = '%s'\" % args.pk)\n else:\n print(\"pk = %s\" % u.pk)\n print(\"first_name = %s\" % u.first_name)\n print(\"last_name = %s\" % u.last_name)\n print(\"birthday = %s\" % u.birthday.strftime(date_format))\n else:\n\n for u in User.objects:\n print(u)\n\n elif args.subparser == 'list_pets':\n\n try:\n u = User.objects.get(id=args.pk)\n except (User.DoesNotExist, ValidationError):\n print(\"user not found id = '%s'\" % args.pk)\n sys.exit(1)\n\n print(\"User: %s %s has next pets:\" % (u.first_name, u.last_name))\n\n for p in Pet.objects(owner=u):\n if isinstance(p, Cat):\n print(\"Cat: \", p)\n elif isinstance(p, Dog):\n print(\"Dog: \", p)\n\n elif args.subparser == 'top':\n\n from collections import defaultdict\n TOP = defaultdict(list)\n\n for p in Pet.objects:\n TOP[p.owner].append(p)\n\n res = list(TOP.items())\n res.sort(key=lambda x:len(x[1]), reverse=True)\n\n for (u, pets) in res:\n print(\"%s %s\" % (u.first_name, u.last_name))\n\n for p in pets:\n print(\"\\t\", p.name)\n\n\n\nif __name__ == '__main__':\n\n parser = argparse.ArgumentParser()\n\n subparsers = parser.add_subparsers(dest='subparser')\n\n parser_add = subparsers.add_parser('add')\n parser_add.add_argument('--first_name', required=True)\n parser_add.add_argument('--last_name', required=True)\n parser_add.add_argument('--birthday', required=True)\n\n parser_update = subparsers.add_parser('update')\n parser_update.add_argument('--pk', required=True)\n parser_update.add_argument('--first_name')\n parser_update.add_argument('--last_name')\n parser_update.add_argument('--birthday')\n\n parser_del = subparsers.add_parser('del')\n parser_del.add_argument('--pk', required=True)\n\n parser_list = subparsers.add_parser('list')\n parser_list.add_argument('--pk')\n\n parser_list_pets = subparsers.add_parser('list_pets')\n parser_list_pets.add_argument('--pk', required=True)\n\n parser_top = subparsers.add_parser('top')\n\n args = parser.parse_args()\n\n if args.subparser is None:\n parser.print_help()\n sys.exit(1)\n\n main(args)\n" }, { "alpha_fraction": 0.5357468724250793, "alphanum_fraction": 0.5366595387458801, "avg_line_length": 27.336206436157227, "blob_id": "39a101ab88929b4603f015fce7a45668968b5aea", "content_id": "a4df8f0469c842ba039bdc6b941cf1feb4cbcf9d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3287, "license_type": "no_license", "max_line_length": 76, "num_lines": 116, "path": "/pets.py", "repo_name": "grubberr/dog_and_cats", "src_encoding": "UTF-8", "text": "#!/Users/ant/dog_and_cats/env/bin/python3\n\nimport sys\nimport argparse\nimport datetime\nfrom mongoengine.errors import ValidationError\nfrom models import User, Pet, Dog, Cat, date_format\nfrom utils import get_birthday_or_exit\n\ndef main(args):\n\n if args.subparser == 'add':\n\n birthday = get_birthday_or_exit(args.birthday)\n\n try:\n u = User.objects.get(id=args.owner)\n except (User.DoesNotExist, ValidationError):\n print(\"owner not found id = '%s'\" % args.owner)\n sys.exit(1)\n\n if args.type == 'dog':\n p = Dog(name=args.name, birthday=birthday, owner=u)\n p.save()\n print(\"Dog created id = '%s'\" % p.pk)\n\n elif args.type == 'cat':\n p = Cat(name=args.name, birthday=birthday, owner=u)\n p.save()\n print(\"Cat created id = '%s'\" % p.pk)\n\n elif args.subparser == 'del':\n\n try:\n p = Pet.objects.get(id=args.pk)\n except (Pet.DoesNotExist, ValidationError):\n print(\"pet not found id = '%s'\" % args.pk)\n else:\n p.delete()\n print(\"pet removed id = '%s'\" % p.pk)\n\n elif args.subparser == 'update':\n\n try:\n p = Pet.objects.get(id=args.pk)\n except (Pet.DoesNotExist, ValidationError):\n print(\"pet not found id = '%s'\" % args.pk)\n else:\n\n if args.name:\n p.name = args.name\n\n if args.birthday:\n p.birthday = get_birthday_or_exit(args.birthday)\n\n p.save()\n\n print(\"pet updated id = '%s'\" % p.pk)\n\n elif args.subparser == 'list':\n\n if args.pk:\n\n try:\n p = Pet.objects.get(id=args.pk)\n except (Pet.DoesNotExist, ValidationError):\n print(\"pet not found id = '%s'\" % args.pk)\n else:\n\n if isinstance(p, Cat):\n print(\"Cat\")\n elif isinstance(p, Dog):\n print(\"Dog\")\n\n print(\"pk = %s\" % p.pk)\n print(\"name = %s\" % p.name)\n print(\"birthday = %s\" % p.birthday.strftime(date_format))\n else:\n\n for p in Pet.objects:\n if isinstance(p, Cat):\n print(\"Cat: \", p)\n elif isinstance(p, Dog):\n print(\"Dog: \", p)\n\n\nif __name__ == '__main__':\n\n parser = argparse.ArgumentParser()\n\n subparsers = parser.add_subparsers(dest='subparser')\n\n parser_add = subparsers.add_parser('add')\n parser_add.add_argument('--type', choices=['cat', 'dog'], required=True)\n parser_add.add_argument('--name', required=True)\n parser_add.add_argument('--birthday', required=True)\n parser_add.add_argument('--owner', required=True)\n\n parser_update = subparsers.add_parser('update')\n parser_update.add_argument('--pk', required=True)\n parser_update.add_argument('--name')\n parser_update.add_argument('--birthday')\n\n parser_del = subparsers.add_parser('del')\n parser_del.add_argument('--pk', required=True)\n\n parser_list = subparsers.add_parser('list')\n parser_list.add_argument('--pk')\n\n args = parser.parse_args()\n\n if args.subparser is None:\n parser.print_help()\n sys.exit(1)\n\n main(args)\n" }, { "alpha_fraction": 0.5897166728973389, "alphanum_fraction": 0.5907660126686096, "avg_line_length": 23.435897827148438, "blob_id": "846a30bd7b0c1ff6da59f886cb1f45b628c723da", "content_id": "00b5663906c595a8508dd1088a74c9c13683404e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 953, "license_type": "no_license", "max_line_length": 73, "num_lines": 39, "path": "/models.py", "repo_name": "grubberr/dog_and_cats", "src_encoding": "UTF-8", "text": "#!/Users/ant/dog_and_cats/env/bin/python3\n\nfrom mongoengine import *\nconnect('mydb')\n\ndate_format = '%m/%d/%Y'\n\nclass User(Document):\n first_name = StringField(required=True)\n last_name = StringField(required=True)\n birthday = DateTimeField(required=True)\n\n def __str__(self):\n return \"pk = %s, first_name: %s, last_name: %s, birthday: %s\" % (\n self.pk,\n self.first_name,\n self.last_name,\n self.birthday.strftime(date_format))\n\n\nclass Pet(Document):\n name = StringField(required=True)\n birthday = DateTimeField(required=True)\n owner = ReferenceField('User', required=True)\n\n meta = {'allow_inheritance': True}\n\n def __str__(self):\n return \"pk = %s, name: %s, birthday: %s, owner: %s\" % (\n self.pk,\n self.name,\n self.birthday.strftime(date_format),\n self.owner.first_name)\n\nclass Cat(Pet):\n pass\n\nclass Dog(Pet):\n pass\n" } ]	5
escap-data-hub/LLString	https://github.com/escap-data-hub/LLString	0610846b0d227d93dfcce0701543e642dbb866ab	71cc2ce1b3d6b72510727ebcac39d9dc97b9b804	ec2fbb011dfe11877198f4554f5fa53efa80301c	refs/heads/master	2023-04-07T13:33:23.196943	2016-05-31T20:52:57	2016-05-31T20:52:57	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7230769395828247, "alphanum_fraction": 0.7230769395828247, "avg_line_length": 31.33333396911621, "blob_id": "d8f1f2bc69ec778b740001847defd4ff8c67e973", "content_id": "c1c03867c22eef9f1146b26b6a880251b322887e", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 195, "license_type": "permissive", "max_line_length": 66, "num_lines": 6, "path": "/llstring/llstring/training/__init__.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "\"\"\"\nThe :mod:'llstring.training' module implements a trainer \nwhich builds an IDF from raw text input (either from file or list)\n\"\"\"\nfrom .idf_trainer import IDFTrainer\n__all__ = ['IDFTrainer']\n\n" }, { "alpha_fraction": 0.5881333947181702, "alphanum_fraction": 0.5963620543479919, "avg_line_length": 30.47945213317871, "blob_id": "a38e2fba2262b681c0943259b100b761d475eac6", "content_id": "ce131b8f8c9f4a104f493b084290c45fd2e8c1ad", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2309, "license_type": "permissive", "max_line_length": 98, "num_lines": 73, "path": "/examples/norm.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#! /usr/bin/env python\n\n# levenshtein_example.py\n#\n# Example script to demonstrate Levenshtein string-match classifier\n# \n# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n#\n# Imports \n#\nimport os\nimport logging\nimport cPickle as pickle\nimport sys\nimport io\n\nfrom llstring.utilities.normalization.latin_normalization import \nimport re\n\n#\n# Logging\n#\nLOG_LEVEL = logging.DEBUG\nlogging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\nlogger = logging.getLogger(__name__)\n\n\nif __name__ == \"__main__\":\n\n normalizer = MITLLLatinNormalizer()\n\n skip = 1\n for file in sys.argv:\n if (skip == 1):\n skip = 0\n else: \n with io.open(file,'r',encoding='utf8') as f:\n for line in f:\n words = line.split()\n first = words[0]\n line = line[len(first):]\n line = normalizer.normalize_unicode_composed(unicode(line))\n line = normalizer.remove_html_markup(line)\n line = re.sub(r'\\#[a-zA-Z0-9_]+', ' ',line,flags=re.UNICODE) # remove hashtags\n line = normalizer.remove_twitter_meta(line)\n line = normalizer.remove_nonsentential_punctuation(line)\n line = normalizer.remove_word_punctuation(line)\n line = normalizer.remove_repeats(line)\n line = normalizer.clean_string(line)\n if (line == ' '): line = ''\n\n both = words[0] + \"\\t\" + line\n print both\n #print newline\n \n\n\n" }, { "alpha_fraction": 0.6370370388031006, "alphanum_fraction": 0.644444465637207, "avg_line_length": 33.45744705200195, "blob_id": "453ac10631008842406ca94402b45a6a897f770e", "content_id": "de58f2825f708955fb2bfb1b5d8718cb0acdbd47", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3240, "license_type": "permissive", "max_line_length": 93, "num_lines": 94, "path": "/llstring/llstring/training/idf_trainer.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# idf_trainer.py\n#\n# Class to learn IDF weighting from training data\n# \n# Copyright 2015-2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie K. Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport logging\nimport math\nimport cPickle as pickle\n\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\n\n\nclass IDFTrainer:\n \"\"\" Class to learn IDF weighting from training data \"\"\"\n\n # Logging\n LOG_LEVEL = logging.INFO\n logging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\n logger = logging.getLogger(__name__)\n \n\n def __init__(self,min_df=2,norm=\"l2\"):\n \"\"\" Constructor \"\"\"\n self.cv = CountVectorizer(min_df=min_df)\n self.tfidf = TfidfTransformer(norm)\n\n self.LOG_IDF = None\n self.CORPUS_VOCAB = None\n self.OOV_IDF_VAL = 0 #min idf value to assign for out-of-vocabulary terms\n\n self.IDF_MODEL = dict()\n\n\n def compute_idf(self,corpus):\n \"\"\"\n Compute IDF using corpus.\n Per sklearn conventions, \"corpus\" can be either a:\n file: a file object for a file containing content (newline separated) \n content: a iterable containing all the data in memory (i.e. a list)\n filename: list of filenames of documents in which content is contained\n \"\"\"\n self.cv.fit_transform(corpus)\n self.logger.debug(self.cv.vocabulary_)\n self.CORPUS_VOCAB = self.cv.vocabulary_\n self.logger.debug(self.CORPUS_VOCAB)\n\n # if corpus is file object, seek back to beginning of file...\n if isinstance(corpus,file):\n corpus.seek(0)\n\n freq_term_matrix = self.cv.transform(corpus)\n self.tfidf.fit(freq_term_matrix)\n\n self.LOG_IDF = self.tfidf.idf_\n self.N = freq_term_matrix.shape[0] #num of \"docs\" processed\n \n if isinstance(corpus,file):\n corpus.close()\n\n # Compute OOV_IDF_VAL: min idf value to assign for out-of-vocabulary terms\n nt=1; self.OOV_IDF_VAL = math.log(self.N/(nt+1))+1\n\n # collect model components\n self.IDF_MODEL['idf'] = self.LOG_IDF\n self.IDF_MODEL['corpus_vocab'] = self.CORPUS_VOCAB\n self.IDF_MODEL['oov_idf_val'] = self.OOV_IDF_VAL\n\n\n def save_model(self,fnameout):\n \"\"\" Save-out learned IDF dictionary and associated metadata (e.g. self.IDF_MODEL) \"\"\"\n self.logger.info(\"saving IDF model to {0}\".format(fnameout))\n pickle.dump(self.IDF_MODEL,open(fnameout,\"wb\"))\n\n" }, { "alpha_fraction": 0.724416971206665, "alphanum_fraction": 0.7441694140434265, "avg_line_length": 48.43529510498047, "blob_id": "c60c4afad3e71e0df53f5fcc83fd86e7266392d0", "content_id": "d867f4049a365bd1786073026d18d1ac75dda9e1", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 5402, "license_type": "permissive", "max_line_length": 305, "num_lines": 85, "path": "/README.md", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "# LLString\n\nThis project contains the source for llstring, a soft string matching toolbox. llstring* provides:\n* Basic Soft string matching via Levenshtein, Jaro-Winkler and Soft TF-IDF similarity scoring algorithms\n* Roll-Your-Own soft string matching functionality for new data domains:\n * Full cross-validation suite (including Platt Scaling) for building classifiers based on raw string matching scores\n * TF-IDF dictionary training\n * Example models trained on English language social media data\n* Text Normalization Tools (i.e. UTF-8 encoding normalization, tweet-speak normalization, etc.)\n\n\n### Prerequisites and Installation\n\nThis package is written in Python. For easiest installation, users are encouraged to use [Anaconda](https://www.continuum.io/why-anaconda), a lightweight package manager, environment manager and Python distribution. llstring is distributed with builds for multiple platforms and can be installed via:\n\n```shell\nconda install -c file://local/path/to/llstring/conda/build llstring\n```\n\n### Running\n\nExample scripts highlighting llstring functionality can be found in the ```examples``` directory in the project root. This directory contains examples scripts and data for soft string matcher training, validation and testing on sample data. \n\n### Tweet Normalization example\n\n```\n515918-mitll:mitll-string-match go22670$ export PYTHONIOENCODING=utf-8\n515918-mitll:mitll-string-match go22670$ python examples/norm.py examples/data/twitterSample.tsv > twitterSampleNormed.tsv\n```\n\nwhich strips out @mentions, hash tags, urls, etc.\n\ne.g. original:\n\n```\n==> twitterSample.tsv <==\npt\tpensei que tinha perdido boina e caderno, mas na vdd, a gabriella que pegou, nojenta\"\nund\t@ZEECorporate A3) 5 continents #ZEE\"\nund\t@eduarda_sam ui apxnd\"\nka\tთელავი ჩოგბურთის საერთაშორისო ტურნირს მასპინძლობს: თელავში ქალთა და მამაკაცთა სერთაშორისო ტურნირი ჩოგბურთში “T... http://t.co/vzu6LgoLeH\"\nkm\tអានេះទើបហៅថា មី ពិតប្រាកដព្រោះដុតមិនឆេះទេ ខុសពី មីយួន ដុតទៅឆេះរលួយដូច ជ័រកៅស៊ូ http://t.co/0HHJkFT1tD\"\nsv\t@lisaginell Jaa verkligen,världens bästa typ som små hundar :')\"\nnl\tInpakken voor Rastede! :) Nu hoop ik eiglk dat alles in 1 weekendtas past...\"\nda\t@koefoed Der fik han lige 500 XP.\"\nfa\tاین بچه ها چه قدر تو وایبر گروه تشکیل میدن..یعنی همه جکان رو نمیتونن تو همون گروه کپی کنن؟:/\"\nit\tC'è un umidità assurda💧💧💧\"\npa\tਇਹ ਮੁਹੱਬਤ ਕਰਨ ਵਾਲੇ ਲੋਕ ਨਿਰੇ ਮੂਰਖ ਹੁੰਦੇ ਹਨ ਖ਼੍ਜ਼ਾਨੇ ਦੀ ਕੁੰਜੀ ਆਪੇ\\nਹੀ ਕਿਸੇ ਬਿਹਾਨੇ ਨੂੰ ਸੌਂਪ ਦਿੰਦੇ ਹਨ,ਤੇ ਫ਼ੇਰ ਆਪ੍ਣੇ... http://t.co/PcfxbpfzxA\"\nund\theol\"\nund\tDerbyshire 62/2 (21.4 ov) #cricket #fifa14 #FIFAWorldCup 267\"\nde\tIch habe 71,530 Goldmünzen gesammelt! http://t.co/PwPNZDFUVy #android, #androidgames, #gameinsight\"\nnot_fi\t@stevenlongo_33 oh myy 🙊\"\n```\n\nto normalized:\n\n```\n==> twitterSampleNormed.tsv <==\npt\tpensei que tinha perdido boina e caderno mas na vdd a gabriella que pegou nojenta\nund\ta3 5 continents\nund\tui apxnd\nka\tთელავი ჩოგბურთის საერთაშორისო ტურნირს მასპინძლობს თელავში ქალთა და მამაკაცთა სერთაშორისო ტურნირი ჩოგბურთში “t\nkm\tអានេះទើបហៅថា មី ពិតប្រាកដព្រោះដុតមិនឆេះទេ ខុសពី មីយួន ដុតទៅឆេះរលួយដូច ជ័រកៅស៊ូ\nsv\tjaa verkligen världens bästa typ som små hundar :')\nnl\tinpakken voor rastede :) nu hoop ik eiglk dat alles in 1 weekendtas past\nda\tder fik han lige 500 xp\nfa\tاین بچه ها چه قدر تو وایبر گروه تشکیل میدنیعنی همه جکان رو نمیتونن تو همون گروه کپی کنن؟:/\nit\tc'è un umidità assurda💧💧💧\npa\tਇਹ ਮੁਹੱਬਤ ਕਰਨ ਵਾਲੇ ਲੋਕ ਨਿਰੇ ਮੂਰਖ ਹੁੰਦੇ ਹਨ ਖ਼੍ਜ਼ਾਨੇ ਦੀ ਕੁੰਜੀ ਆਪੇ nਹੀ ਕਿਸੇ ਬਿਹਾਨੇ ਨੂੰ ਸੌਂਪ ਦਿੰਦੇ ਹਨ,ਤੇ ਫ਼ੇਰ ਆਪ੍ਣੇ\nund\theol\nund\tderbyshire 62/2 214 ov 267\nde\tich habe 71,530 goldmünzen gesammelt\nnot_fi\toh myy 🙊\n```\n\n### License\n\nCopyright 2015-2016 MIT Lincoln Laboratory, Massachusetts Institute of Technology \n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use these files except in compliance with the License.\n\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.\n" }, { "alpha_fraction": 0.7917981147766113, "alphanum_fraction": 0.7917981147766113, "avg_line_length": 38.5, "blob_id": "88747eee0e19d3f749ff2fafa10e9dd74e7125be", "content_id": "d07420ae1472ff68ddbd0850454f81d3764e256e", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 317, "license_type": "permissive", "max_line_length": 64, "num_lines": 8, "path": "/llstring/llstring/matching/__init__.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "\"\"\"\nThe :mod:'llstring.matching' module implements classifiers \nbased on basic string matching algorithms: Levenshtein Distance,\nJaro-Winkler Similarity and Soft TF-IDF Similarity.\n\"\"\"\nfrom .mitll_string_matcher import MITLLStringMatcher\nfrom .softtfidf import Softtfidf\n__all__ = ['MITLLStringMatcher','Softtfidf']\n\n" }, { "alpha_fraction": 0.5835702419281006, "alphanum_fraction": 0.5887489914894104, "avg_line_length": 31.9331111907959, "blob_id": "b87447aec733c6c54aa3e637c9fca99bac09528f", "content_id": "768bf907b297202fec26f1a68462a813f352d19f", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 9848, "license_type": "permissive", "max_line_length": 126, "num_lines": 299, "path": "/llstring/llstring/matching/mitll_string_matcher.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# mitll_string_matcher.py\n#\n# MITLLSTringMatcher:\n# SKLEARN compatable classifier implementing string matching techniques:\n# - Levenshtein Distance\n# - Jaro-Winkler \n# - Soft TF-IDF\n# \n# Copyright 2015 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n\n# Imports\nimport logging\nimport numpy as np\nimport cPickle as pickle\n\nimport jellyfish\n\nfrom sklearn.base import BaseEstimator, ClassifierMixin\nfrom sklearn.linear_model import LogisticRegression as LR\nfrom sklearn.metrics import roc_auc_score\n\nfrom .softtfidf import Softtfidf\nfrom ..utilities import normalization as normutils\n\n\nclass MITLLStringMatcher(BaseEstimator,ClassifierMixin):\n \"\"\"\n MIT-LL String Matcher as Sklearn Estimator:\n\n String Matching Techniques:\n - Levenshtein Distance\n - Jaro-Winkler \n - Soft TF-IDF\n \"\"\"\n\n # Logging\n LOG_LEVEL = logging.INFO\n logging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\n logger = logging.getLogger(__name__)\n\n def __init__(self,algorithm='jw', stf_thresh=0.6, idf_model=None, text_normalizer = None):\n \"\"\" Initialize dict containing hyperparameters \"\"\"\n\n self.algorithm = algorithm\n self.stf_thresh = stf_thresh\n self.idf_model = idf_model\n self.text_normalizer = text_normalizer\n\n\n #\n # Basic String Matching Functions\n #\n def levenshtein_similarity(self,s,t):\n \"\"\" Levenshtein Similarity \"\"\"\n\n Ns = len(s); Nt = len(t);\n\n lev_sim = 1.0 - (jellyfish.levenshtein_distance(s,t))/float(max(Ns,Nt))\n\n return lev_sim\n\n\n def jaro_winkler_similarity(self,s,t):\n \"\"\" Jaro-Winkler Similarity \"\"\"\n\n jw_sim = jellyfish.jaro_winkler(s,t)\n\n return jw_sim\n\n\n def soft_tfidf_similarity(self,s,t):\n \"\"\"\n Soft TFIDF Similarity:\n\n This similarity measure is only meaningful when you have multi-word strings. \n For single words, this measure will return 0.0\n \"\"\"\n stf = self.hyparams['matcher'] #soft tf-idf object\n\n tfidf_sim = 0.5(stf.score(s,t)+stf.score(t,s))\n\n return tfidf_sim\n\n\n #\n # Utitlity Functions\n #\n def init_hyparams(self):\n \"\"\" Initialize hyper-parameters dict \"\"\"\n\n self.hyparams = dict()\n self.hyparams['match_fcn'] = None\n self.hyparams['algo'] = self.algorithm\n self.hyparams['txt_normer'] = self.text_normalizer\n\n if self.algorithm == 'lev': #levenshtein\n self.hyparams['match_fcn'] = self.levenshtein_similarity\n\n elif self.algorithm== 'jw': #jaro-winkler\n self.hyparams['match_fcn'] = self.jaro_winkler_similarity\n\n elif self.algorithm== 'stf': #softtfidf\n self.hyparams['match_fcn'] = self.soft_tfidf_similarity\n self.hyparams['stf_thresh'] = self.stf_thresh\n self.hyparams['idf_model'] = self.idf_model\n\n\n def validate_hyparams(self):\n \"\"\" Basic hyperparameter input validation\"\"\"\n \n if self.hyparams['algo'] not in set(['lev','jw','stf']):\n raise ValueError(\"Value of algorithm has to be either 'lev','jw' or 'stf'. Got {0}\".format(self.hyparams['algo']))\n\n if self.hyparams['txt_normer'] not in set(['latin',None]):\n raise ValueError(\"The only value of txt_normer currently support is 'latin' (or None)\")\n\n if self.hyparams['algo'] == 'stf':\n if (self.hyparams['stf_thresh'] < 0) \| (self.hyparams['stf_thresh'] > 1):\n raise ValueError(\"Value of soft tf-idf's internal jaro-winkler threshold\", \\\n \"must be [0,1].\")\n\n if self.hyparams['idf_model']:\n if set(self.hyparams['idf_model'].keys()) != set(['idf','corpus_vocab','oov_idf_val']):\n raise ValueError(\"IDF model provided must contain only the following keys: \", \\\n \"'idf', 'corpus_vocab', and 'oov_idf_val'.\")\n\n if (not isinstance(self.hyparams['idf_model']['idf'],np.ndarray)) or \\\n (self.hyparams['idf_model']['idf'].dtype.type is not np.float64):\n raise ValueError(\"idf_model['idf'] must be an np.ndarray of dtype np.float64\")\n\n if not isinstance(self.hyparams['idf_model']['corpus_vocab'],dict):\n raise ValueError(\"idf_model['corpus_vocab'] must be a dict.\")\n\n if not isinstance(self.hyparams['idf_model']['oov_idf_val'],float):\n raise ValueError(\"idf_model['oov_idf_val'] must be a float.\")\n\n\n def init_algorithm(self):\n \"\"\" Validate hyperparameter inputs, init matcher object if neccessary\"\"\"\n \n self.validate_hyparams()\n\n # Initialize Soft TF-IDF matcher if needed\n if self.hyparams['algo'] == 'stf': #softtfidf\n self.hyparams['matcher'] = Softtfidf(self.hyparams['stf_thresh'],self.hyparams['idf_model'])\n\n if self.hyparams['txt_normer'] == 'latin':\n self.normalizer = normutils.latin_normalization.MITLLLatinNormalizer()\n else:\n self.normalizer = normutils.text_normalization.MITLLTextNormalizer() #generic normer\n\n \n def get_raw_similarities(self, X, y=None):\n \"\"\" Convert input to raw similarities \"\"\"\n\n #make sure we have [0,1] class encoding in y\n if y:\n if set(y) != set((0,1)):\n raise ValueError(\"y expects class labels to be from {0,1}\") \n\n similarities = list()\n\n for i in xrange(len(X)):\n pair = X[i]\n s = unicode(self.normalizer.normalize(pair[0]),'utf-8')\n t = unicode(self.normalizer.normalize(pair[1]),'utf-8')\n\n if (len(s) > 0) and (len(t) > 0):\n sim = self.hyparams['match_fcn'](s,t)\n similarities.append(sim)\n else:\n similarities.append(0.0)\n if y: y[i] = -1 #set y-value of non-conforming pair to -1\n\n sims_array = np.asarray(similarities).reshape(-1,1)\n \n if y:\n return (sims_array,y)\n else:\n return sims_array\n\n\n def save_model(self,fnameout):\n \"\"\" Save model parameters out after fitting. \"\"\"\n \n if self.lr_:\n model_out = dict()\n model_out['algo'] = self.hyparams['algo']\n model_out['txt_normer'] = self.hyparams['txt_normer']\n model_out['calibration'] = self.lr_\n if self.hyparams['algo'] == 'stf':\n model_out['stf_thresh'] = self.hyparams['stf_thresh']\n model_out['idf_model'] = self.hyparams['idf_model']\n\n pickle.dump(model_out,open(fnameout,\"wb\"))\n return self\n else:\n raise ValueError(\"save_model failed: No model has yet been fit or loaded.\")\n\n\n def load_model(self,fnamein):\n \"\"\" Load model parameters. \"\"\"\n model_in = pickle.load(open(fnamein,'rb')) # will throw I/O error if file not found\n\n self.init_hyparams() #initialize hyper-parameter dict\n\n self.hyparams['algo'] = model_in['algo']\n self.hyparams['txt_normer'] = model_in['txt_normer']\n self.lr_ = model_in['calibration']\n if model_in['algo'] == 'stf':\n self.hyparams['stf_thresh'] = model_in['stf_thresh']\n self.hyparams['idf_model'] = model_in['idf_model']\n\n self.init_algorithm() #validate hyparams (we assume object not fit when load_model called)\n\n return self\n\n\n #\n # Learning\n #\n def fit(self,X,y):\n \"\"\" Fit string matching models to training data\n Assuming X is list of tuples: (('s1',t1'),...,('sN',tN'))\n \"\"\"\n y = y[:] #shallow copy y, b/c in-place operations to follow\n\n # Initialize hyper-parameter dict then algorithm\n self.init_hyparams(); self.init_algorithm()\n\n # Get string match scores\n (s,y) = self.get_raw_similarities(X,y)\n\n # Get rid of any non-conforming pairs\n data = zip(s,y)\n for pair in reversed(data): #iterate backwards to remove items from \"data\" \n #so as not to mess up internal indexing of for-loop\n if pair[1] == -1: \n data.remove(pair)\n\n (s,y) = zip(data) \n \n # Do Platt Scaling \n self.lr_ = LR(penalty='l1',class_weight='balanced')\n self.lr_.fit(s,y)\n\n return self\n\n\n #\n # Inference\n # \n def decision_function(self,X):\n \"\"\" Take input data, turn into decision \"\"\"\n s = self.get_raw_similarities(X)\n\n return self.lr_.decision_function(s)\n\n\n def predict(self,X):\n \"\"\" Class predictions \"\"\"\n s = self.get_raw_similarities(X)\n\n return self.lr_.predict(s)\n\n\n def predict_proba(self,X):\n \"\"\" Posterior match probabilities (need this for log-loss for CV \"\"\"\n s = self.get_raw_similarities(X)\n\n return self.lr_.predict_proba(s)\n\n #\n # Evaluate\n #\n def score(self,X,y,sample_weight=None):\n \"\"\" Score matcher \"\"\"\n return roc_auc_score(y,self.predict(X),sample_weight=sample_weight)\n\n" }, { "alpha_fraction": 0.5998828411102295, "alphanum_fraction": 0.6098418235778809, "avg_line_length": 27.433332443237305, "blob_id": "e7621c57eb30a06abcf46ba814e759fd6aeea86a", "content_id": "109b0f53a0c3abcb79e87ac7939efcd0943e5e4f", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1707, "license_type": "permissive", "max_line_length": 84, "num_lines": 60, "path": "/llstring/llstring/utilities/sampling/reservoir_sampler.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# reservoir_sampler.py\n#\n# Perform uniform sampling from an (possibly infinite) input stream\n# \n# Copyright 2015-2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie K. Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport random\nimport logging\n\nclass ReservoirSampler: \n \"\"\" Class to perform uniform sampling from an input stream \"\"\"\n\n # Logging\n LOG_LEVEL = logging.INFO\n logging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\n logger = logging.getLogger(__name__)\n \n\n def __init__(self,K):\n \"\"\" Constructor \"\"\"\n self.K = K\n self.N = 0\n self.sample = list()\n\n\n def update_sample(self,item):\n \"\"\" Update sampler \"\"\"\n self.N += 1\n \n if len(self.sample) < self.K:\n self.sample.append(item)\n else:\n s = int(random.random()self.N)\n if s < self.K:\n self.sample[s] = item\n\n\n def get_sample(self):\n \"\"\" Return sample \"\"\"\n return self.sample\n\n" }, { "alpha_fraction": 0.7040441036224365, "alphanum_fraction": 0.71875, "avg_line_length": 29.19444465637207, "blob_id": "764136e4fe6a209dd13c82de83b27a1bfce726f0", "content_id": "5254cded29272d48f7eb7175f7f4b9089cf25136", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1088, "license_type": "permissive", "max_line_length": 74, "num_lines": 36, "path": "/llstring/setup.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#! /usr/bin/env python\n\n# setup.py\n#\n# Setup and Install of llstring\n# \n# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n# Imports \nfrom setuptools import setup, find_packages\n\n# Setup\nsetup(name='llstring',\n version='0.0.1',\n description='MIT-LL String Processing and Matching Tools',\n url='https://g62code.llan.ll.mit.edu/cdagli/mitll-string-match',\n author='Charlie Dagli',\n author_email='[email protected]',\n license='APLv2',\n packages=find_packages())\n\n" }, { "alpha_fraction": 0.5899147391319275, "alphanum_fraction": 0.5986281037330627, "avg_line_length": 46.72566223144531, "blob_id": "f0676749568655e6731a541b3f951003d17ff291", "content_id": "6fb45cdf587aa34ff038ca6b3f51cd90a36ab12b", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5394, "license_type": "permissive", "max_line_length": 135, "num_lines": 113, "path": "/examples/soft_tfidf_example.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#! /usr/bin/env python\n\n# soft_tfidf_example.py\n#\n# Example script to demonstrate Soft TF-IDF string-match classifier\n# \n# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n#\n# Imports \n#\nimport os\nimport logging\nimport cPickle as pickle\n\nfrom llstring.matching.mitll_string_matcher import MITLLStringMatcher\n\nfrom sklearn import cross_validation \nfrom sklearn.grid_search import GridSearchCV\n\n#\n# Logging\n#\nLOG_LEVEL = logging.DEBUG\nlogging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\nlogger = logging.getLogger(__name__)\n\n\nif __name__ == \"__main__\":\n\n # Input and Output Filenames\n exampledir = os.path.dirname(os.path.realpath(__file__))\n fnamein = os.path.join(exampledir,\"data/input/match_training_data.pckl\")\n\n # Load Training Data\n train = pickle.load(open(fnamein,\"rb\"))\n X = train['X'] #string pairs \n y = train['y'] #corresponding labels (1:match, 0:no-match)\n\n # Train/Test Splits (via sklearn)\n X_train, X_test, y_train, y_test = cross_validation.train_test_split(X,y,test_size=0.3,random_state=0)\n\n #\n # Soft TF-IDF Matcher (from training data)\n #\n idf_model = pickle.load(open(os.path.join(exampledir,\"data/output/models/english_socialmedia_idf.pckl\"),'rb'))\n # ^ see idf_training_example.py\n stf_thresh = 0.6 # Internal JW threshold \n matcher = MITLLStringMatcher(algorithm='stf',text_normalizer='latin',idf_model=idf_model,stf_thresh=stf_thresh)\n # ^ Initialize Soft TF-IDF matcher\n matcher.fit(X_train,y_train) # Fit matcher to training data\n fname_model = os.path.join(exampledir,\"data/output/models/english_socialmedia_stf_{0}.model\".format(stf_thresh)) \n # ^ Model-out filename\n matcher.save_model(fname_model) # Save model out\n\n posts = matcher.predict_proba(X_test) # Posterior probabilities of match\n preds = matcher.predict(X_test) # Predicted labels for test data\n confs = matcher.decision_function(X_test) # Confidence (as distance to hyperplane)\n score = matcher.score(X_test,y_test) # Return classificaton performance \n raw_sims = matcher.get_raw_similarities(X_test) # Return raw similarity scores (not probabilities)\n\n # Scoring an example string pair\n s = u\"Abe Lincoln\"; t = u\"Abraham Lincoln Lab\"\n post = matcher.predict_proba([(s,t)])[0][1] # Posterior probability of match\n pred = matcher.predict([(s,t)])[0] # Predicted label for pair\n logger.info(\"Example Match Posterior: {0}\".format(post))\n\n #\n # Soft TF-IDF Matcher (from pre-trained model)\n #\n matcher2 = MITLLStringMatcher(algorithm='stf',text_normalizer='latin',stf_thresh=0.6)\n # ^ Initialize Soft TF-IDF matcher\n matcher2.load_model(os.path.join(exampledir,\"data/output/models/english_socialmedia_stf_{0}.model\".format(stf_thresh)))\n # ^ Load-in model\n posts2 = matcher2.predict_proba(X_test) # Posterior probabilities of match\n\n if (posts2 == posts2).all(): logger.info(\"Soft TF-IDF Test: Pass\")\n else: logger.info(\"Soft TF-IDF Test: Fail\")\n\n #\n # Soft TF-IDF w/ hyper-parameter tuning (via sklearn Grid-Search) Example\n #\n matcher_stub = MITLLStringMatcher(algorithm='stf',idf_model=idf_model,text_normalizer = 'latin')\n # ^ Initialize Soft TF-IDF matcher stub\n param_grid = {'stf_thresh':[0.4,0.5,0.6,0.7,0.8,0.9]} # Setup hyper-parameter grid\n cv_matcher = GridSearchCV(matcher_stub,param_grid,cv=5,verbose=2) # Initialize GridSearchCV matcher of type\n # MITLLStringMatcher(algorithm='stf')\n cv_matcher.fit(X_train,y_train) # Re-train model on all training data using \n # (model fit to best performing hyper-parameter\n # combination)\n\n fname_model = os.path.join(exampledir,\"data/output/models/english_socialmedia_stf_optimal.model\") \n # ^ Model-out filename\n cv_matcher.best_estimator_.save_model(fname_model) # Save optimal model out\n\n logger.info(\"Best stf_thresh found by CV: {0}\".format(cv_matcher.best_params_['stf_thresh']))\n\n" }, { "alpha_fraction": 0.49178969860076904, "alphanum_fraction": 0.517455518245697, "avg_line_length": 35.04975128173828, "blob_id": "d20b3fdbb6a80b75a20e17429c049b4785132477", "content_id": "bdc47c7caabf5f0af79f982d7b74b9e086e2a1fa", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 7247, "license_type": "permissive", "max_line_length": 88, "num_lines": 201, "path": "/llstring/llstring/utilities/normalization/text_normalization.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# text_normalization.py\n#\n# Generic Text Normalization Routines\n# \n# Copyright 2013-2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli & William M. Cambpell\n# {dagli,wcampbell}@ll.mit.edu\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport re\nimport logging\nimport unicodedata\n\nclass MITLLTextNormalizer: \n \"\"\" Text-Normalization Routines \"\"\"\n\n # Logging\n LOG_LEVEL = logging.INFO\n logging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\n logger = logging.getLogger(__name__)\n \n\n def __init__(self):\n \"\"\" Constructor \"\"\"\n self.rewrite_hash = self.create_utf8_rewrite_hash()\n\n\n def normalize(self,ln):\n \"\"\" Text Line Normalizer \"\"\"\n # Various normalization routines -- pick and choose as needed\n ln = unicode(ln) #make sure we're in unicode\n ln = self.normalize_unicode_composed(ln) #from base-class\n ln = self.filter_unicode(ln) #from base-class\n ln = self.remove_html_markup(ln) #from base class\n if (ln == ' '):\n ln = ''\n return ln\n\n\n def normalize_unicode_composed(self,txt):\n \"\"\" Normalize unicode: Composed \"\"\"\n return unicodedata.normalize('NFKC', txt)\n\n\n def normalize_unicode_decomposed(self,txt):\n \"\"\" Normalize unicode: Decomposed (i.e. expanded unicode) \"\"\"\n return unicodedata.normalize('NFKD', txt)\n\n\n def filter_unicode(self,ln):\n \"\"\" Filter Unicode \"\"\"\n out = ''\n for i in xrange(0,len(ln)):\n if (ord(ln[i]) < 0x7f):\n out = out + ln[i]\n elif (self.rewrite_hash.has_key(ln[i])):\n out = out + self.rewrite_hash[ln[i]]\n else:\n out = out + \" \"\n\n # Clean up extra spaces\n out = re.sub('^\\s+', '', out)\n out = re.sub('\\s+$', '', out)\n out = re.sub('\\s+', ' ', out)\n out = re.sub('\\s+.$', '.', out)\n \n return out\n\n\n def create_utf8_rewrite_hash (self):\n \"\"\" \n Rewrite utf-8 chars to ascii in a rational manner\n Strictly speaking (and in python) \n any ascii character >= 128 is not valid\n \"\"\"\n\n rewrite_hash = dict([])\n rewrite_hash[u'\\xA0'] = \" \" # NO-BREAK SPACE \n rewrite_hash[u'\\xA6'] = \" \" # BROKEN BAR\n rewrite_hash[u'\\xA7'] = \" \" # SECTION SIGN\n rewrite_hash[u'\\xAC'] = \" \" # NOT SIGN\n rewrite_hash[u'\\xAD'] = \" \" # SOFT HYPHEN\n\n rewrite_hash[u'\\xB6'] = \" \" # PILCROW SIGN\n rewrite_hash[u'\\xBC'] = \" 1/4 \" # VULGAR FRACTION ONE QUARTER\n rewrite_hash[u'\\xBD'] = \" 1/2 \" # VULGAR FRACTION ONE HALF\n rewrite_hash[u'\\xBE'] = \" 3/4 \" # VULGAR FRACTION THREE QUARTERS\n\n rewrite_hash[u'\\u0336'] = \" \" # COMBINING LONG STROKE OVERLAY\n\n rewrite_hash[u'\\u2000'] = \" \" # EN QUAD\n rewrite_hash[u'\\u2001'] = \" \" # EM QUAD\n rewrite_hash[u'\\u2009'] = \" \" # THIN SPACE\n rewrite_hash[u'\\u200A'] = \" \" # HAIR SPACE\n rewrite_hash[u'\\u200B'] = \" \" # ZERO WIDTH SPACE\n\n rewrite_hash[u'\\u200E'] = \" \" # LEFT-TO-RIGHT MARK\n rewrite_hash[u'\\u200F'] = \" \" # RIGHT-TO-LEFT MARK\n\n rewrite_hash[u'\\u2010'] = \"-\" # HYPHEN\n rewrite_hash[u'\\u2011'] = \"-\" # NON-BREAKING HYPHEN\n rewrite_hash[u'\\u2013'] = \" \" # EN DASH\n rewrite_hash[u'\\u2014'] = \" \" # EM DASH\n rewrite_hash[u'\\u2015'] = \" \" # HORIZONTAL BAR\n\n rewrite_hash[u'\\u2020'] = \" \" # DAGGER\n rewrite_hash[u'\\u2021'] = \" \" # DOUBLE DAGGER\n rewrite_hash[u'\\u2022'] = \" \" # BULLET\n rewrite_hash[u'\\u2023'] = \" \" # TRIANGULAR BULLET\n rewrite_hash[u'\\u2024'] = \" \" # ONE DOT LEADER\n rewrite_hash[u'\\u2025'] = \" \" # TWO DOT LEADER\n rewrite_hash[u'\\u2026'] = \" \" # HORIZONTAL ELLIPSIS\n rewrite_hash[u'\\u2027'] = \" \" # HYPHENATION POINT\n rewrite_hash[u'\\u2028'] = \" \" # LINE SEPARATOR\n rewrite_hash[u'\\u2029'] = \"\\n\" # PARAGRAPH SEPARATOR\n rewrite_hash[u'\\u202A'] = \" \" # LEFT-TO-RIGHT EMBEDDING (???)\n rewrite_hash[u'\\u202B'] = \" \" # RIGHT-TO-LEFT EMBEDDING (???)\n rewrite_hash[u'\\u202C'] = \" \" # POP DIRECTIONAL FORMATTING (???)\n rewrite_hash[u'\\u202D'] = \" \" # LEFT-TO-RIGHT OVERRIDE\n rewrite_hash[u'\\u202E'] = \" \" # RIGHT-TO-LEFT OVERRIDE\n rewrite_hash[u'\\u202F'] = \" \" # NARROW NO-BREAK SPACE\n\n rewrite_hash[u'\\u203B'] = \" \" # REFERENCE MARK\n\n rewrite_hash[u'\\u206B'] = \" \" # ACTIVATE SYMMETRIC SWAPPING\n rewrite_hash[u'\\u206E'] = \" \" # NATIONAL DIGIT SHAPES\n rewrite_hash[u'\\u206F'] = \" \" # NOMINAL DIGIT SHAPES\n\n rewrite_hash[u'\\u2116'] = \" \" # NUMERO SIGN\n rewrite_hash[u'\\u2154'] = \"2/3\" # VULGAR FRACTION TWO THIRDS\n rewrite_hash[u'\\u2192'] = \" \" # RIGHTWARDS ARROW\n rewrite_hash[u'\\u21FC'] = \" \" # LEFT RIGHT ARROW WITH DOUBLE VERTICAL STROKE\n\n rewrite_hash[u'\\u2212'] = \"-\" # MINUS SIGN\n\n rewrite_hash[u'\\u23AF'] = \" \" # HORIZONTAL LINE EXTENSION \n rewrite_hash[u'\\u25BA'] = \" \" # BLACK RIGHT-POINTING POINTER\n rewrite_hash[u'\\u2665'] = \" \" # BLACK HEART SUIT\n\n return rewrite_hash\n\n\n def remove_html_markup (self,ln):\n \"\"\" remove HTML style angle bracketed tags \"\"\"\n\n ln = re.sub('\\<\\S+\\>', ' ', ln)\n \n # remove market symbols\n # ln = re.sub('\$[A-Z0-9a-z\\_]\\.[A-Z]+\\:[^\$]+\\)\\,?', '', ln)\n\n # remove web site URLs and links\n ln = re.sub('https?:\\/\\/?\\s\\S+\\s', ' ', ln)\n ln = re.sub('https?:\\/\\/?\\s\\S+$', '', ln)\n ln = re.sub('\$https?:\\\\\\\\\\S+\$', ' ', ln)\n ln = re.sub('\$?www\\.\\S+\$?', ' ', ln)\n ln = re.sub('\\[ID:[^\\]]+\\]', ' ', ln)\n ln = re.sub('\\[id:[^\\]]+\\]', ' ', ln)\n ln = re.sub('\$PDF\$', ' ', ln)\n \n # replace html special characters\n ln = re.sub(r'—', ' ', ln)\n ln = re.sub(r'\\&quot\\;', ' ', ln)\n ln = re.sub(r'\\&\\#39\\;', ' ', ln)\n\n # Clean up extra spaces\n ln = re.sub('^\\s+', '', ln)\n ln = re.sub('\\s+$', '', ln)\n ln = re.sub('\\s+', ' ', ln)\n\n return ln\n\n\n def clean_string(self,s):\n \"\"\" Strip leading characters, lower \"\"\"\n\n if isinstance(s,unicode):\n ss = s.lower()\n else:\n ss = unicode(s.lower(),\"utf-8\")\n\n if len(ss) == 0:\n ss = u''\n\n return ss\n\n" }, { "alpha_fraction": 0.7482678890228271, "alphanum_fraction": 0.7482678890228271, "avg_line_length": 38.272727966308594, "blob_id": "8791228c1cd10ec2591a20054a476d351311f76e", "content_id": "74a0009e51768a6e8f5d7f360e4219bc4323dca4", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 433, "license_type": "permissive", "max_line_length": 64, "num_lines": 11, "path": "/llstring/llstring/__init__.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "\"\"\"\nThe :mod:'llstring' module implements classifiers \nbased on basic string matching algorithms (Levenshtein Distance,\nJaro-Winkler Similarity and Soft TF-IDF Similarity) as well\nas provides a variety of basic string processing/normalization\ntools. \n\"\"\"\nfrom pkgutil import extend_path as __extend_path\n__path__ = __extend_path(__path__, __name__)\n__all__ = ['matching','training','utilities']\nimport matching, training, utilities\n\n" }, { "alpha_fraction": 0.8139534592628479, "alphanum_fraction": 0.8139534592628479, "avg_line_length": 42, "blob_id": "aeb48ca37afd8e088c99e9709d0f30d4397c2641", "content_id": "e4d52e4797663edd3970ba76a8e92a12bab8122a", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 344, "license_type": "permissive", "max_line_length": 61, "num_lines": 8, "path": "/llstring/llstring/utilities/normalization/__init__.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "\"\"\"\nThe :mod:'llstring.normalization' sub-package implements\ngeneric and latin script text normalization. Included\nas well are functions for web and social media normalization.\n\"\"\"\nfrom .text_normalization import MITLLTextNormalizer\nfrom .latin_normalization import MITLLLatinNormalizer\n__all__ = ['MITLLTextNormalizer','MITLLLatinNormalizer']\n" }, { "alpha_fraction": 0.7641509175300598, "alphanum_fraction": 0.7641509175300598, "avg_line_length": 29.285715103149414, "blob_id": "4f69389e00996d368389b558e8dfd58786b37a30", "content_id": "a42024092f65275742f61e721ccde6afa671240a", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 212, "license_type": "permissive", "max_line_length": 55, "num_lines": 7, "path": "/llstring/llstring/utilities/sampling/__init__.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "\"\"\"\nThe :mod:'llstring.sampling' sub-package implements\nbasic reservoir sampling: one-pass uniform sampling of \na large dataset.\n\"\"\"\nfrom .reservoir_sampler import ReservoirSampler\n__all__ = ['ReservoirSampler']\n" }, { "alpha_fraction": 0.48750433325767517, "alphanum_fraction": 0.5118338465690613, "avg_line_length": 57.6506462097168, "blob_id": "598bebfaf8fadcd4be24fd06ddb3595ce4ec576a", "content_id": "9738b3fef52f88d7000a5a9dc5c16c45bb6c7d2b", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 31731, "license_type": "permissive", "max_line_length": 101, "num_lines": 541, "path": "/llstring/llstring/utilities/normalization/latin_normalization.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# latin_normalization.py\n#\n# Text Normalization Routines for Latin Script Text (including for Twitter data)\n# \n# Copyright 2013-2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: William M. Campbell and Charlie Dagli\n# {wcampbell,dagli}@ll.mit.edu\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport re\nimport logging\n\nfrom .text_normalization import MITLLTextNormalizer\n\nclass MITLLLatinNormalizer(MITLLTextNormalizer): \n \"\"\"\n Text-Normalization Routines for Latin Script Text\n \"\"\"\n\n # Logging\n LOG_LEVEL = logging.INFO\n logging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\n logger = logging.getLogger(__name__)\n \n\n def __init__(self):\n \"\"\" Constructor \"\"\"\n MITLLTextNormalizer.__init__(self)\n self.update_utf8_rewrite_hash()\n\n\n def normalize(self,ln):\n \"\"\" Normalize text \"\"\"\n ln = MITLLTextNormalizer.normalize(self,ln)\n ln = self.convertUTF8_to_ascii(ln)\n ln = self.remove_twitter_meta(ln)\n ln = self.remove_nonsentential_punctuation(ln)\n ln = self.remove_word_punctuation(ln)\n ln = self.remove_repeats(ln)\n if (ln == ' '):\n ln = ''\n return ln\n\n\n def get_counts (self,msg):\n \"\"\" Word Count \"\"\"\n counts = {}\n for sent in msg:\n f = sent.split(' ')\n for w in f:\n if (not counts.has_key(w)):\n counts[w] = 0.0\n counts[w] += 1\n return counts\n\n\n def remove_repeats (self,msg):\n \"\"\" Remove Repeats \"\"\"\n # twitter specific repeats\n msg = re.sub(r\"(.)\\1{2,}\", r\"\\1\\1\\1\", msg) # characters repeated 3 or more times\n\n # laughs\n msg = re.sub(r\"(ja\|Ja)(ja\|Ja)+(j)?\", r\"jaja\", msg) # spanish\n msg = re.sub(r\"(rs\|Rs)(Rs\|rs)+(r)?\", r\"rsrs\", msg) # portugese\n msg = re.sub(r\"(ha\|Ha)(Ha\|ha)+(h)?\", r\"haha\", msg) # english\n\n return msg\n\n\n def splitter(self,ln):\n \"\"\" Line Splitter \"\"\"\n # horridly simple splitter\n ln = ln.replace(\". \", \".\\n\\n\").replace(\"? \",\"?\\n\\n\").replace(\"! \",\"!\\n\\n\")\n ln = ln.replace('.\"', '.\"\\n\\n')\n f = ln.split(\"\\n\")\n fout = []\n for s in f:\n s = s.rstrip()\n s = re.sub(r'^\\s+', '', s)\n if (s!=\"\"):\n fout.append(s)\n return fout\n\n\n def convertUTF8_to_ascii(self,ln):\n \"\"\" UTF8 to ASCII Converter \"\"\"\n out = ''\n for i in xrange(0,len(ln)):\n if (ord(ln[i]) < 0x7f):\n out = out + ln[i]\n elif (self.rewrite_hash.has_key(ln[i])):\n out = out + self.rewrite_hash[ln[i]]\n else:\n out = out + \" \"\n\n # Clean up extra spaces\n out = re.sub('^\\s+', '', out)\n out = re.sub('\\s+$', '', out)\n out = re.sub('\\s+', ' ', out)\n out = re.sub('\\s+.$', '.', out)\n \n out = out.encode('ascii','ignore')\n\n return out\n\n\n def update_utf8_rewrite_hash (self):\n \"\"\" Rewrite Hash \"\"\"\n # Strictly speaking (and in python) any ascii character >= 128 is not valid\n # This tries to rewrite utf-8 chars to ascii in a rational manner\n\n self.rewrite_hash[u'\\xA1'] = \" \" # INVERTED EXCLAMATION MARK\n self.rewrite_hash[u'\\xA2'] = \" cents \" # CENT SIGNS\n self.rewrite_hash[u'\\xA3'] = \" pounds \" # POUND SIGN\n self.rewrite_hash[u'\\xA4'] = \" \" # CURRENCY SIGN\n self.rewrite_hash[u'\\xA5'] = \" yen \" # YEN SIGN\n\n self.rewrite_hash[u'\\xA8'] = \" \" # DIAERESIS\n self.rewrite_hash[u'\\xA9'] = \" \" # COPYRIGHT SIGN\n self.rewrite_hash[u'\\xAA'] = \" \" # FEMININE ORDINAL INDICATOR\n self.rewrite_hash[u'\\xAB'] = \" \" # LEFT-POINTING DOUBLE ANGLE QUOTATION MARK\n self.rewrite_hash[u'\\xAE'] = \" \" # REGISTERED SIGN\n self.rewrite_hash[u'\\xAF'] = \" \" # MACRON\n\n self.rewrite_hash[u'\\xB0'] = \" degrees \" # DEGREE SIGN\n self.rewrite_hash[u'\\xB1'] = \" plus-or-minus \" # PLUS-MINUS SIGN\n self.rewrite_hash[u'\\xB2'] = \" \"\t # SUPERSCRIPT TWO\n self.rewrite_hash[u'\\xB3'] = \" \";\t # SUPERSCRIPT THREE\n self.rewrite_hash[u'\\xB4'] = \"'\"\t\t # ACUTE ACCENT\n self.rewrite_hash[u'\\xB5'] = \" micro \" # MICRO SIGN\n self.rewrite_hash[u'\\xB7'] = \" \" # MIDDLE DOT\n self.rewrite_hash[u'\\xB8'] = \" \" # CEDILLA\n self.rewrite_hash[u'\\xB9'] = \" \" # SUPERSCRIPT ONE\n self.rewrite_hash[u'\\xBA'] = \" \" # MASCULINE ORDINAL INDICATOR\n self.rewrite_hash[u'\\xBF'] = \" \" # INVERTED QUESTION MARK\n\n self.rewrite_hash[u'\\xC0'] = \"A\" # LATIN CAPITAL LETTER A WITH GRAVE\n self.rewrite_hash[u'\\xC1'] = \"A\" # LATIN CAPITAL LETTER A WITH ACUTE\n self.rewrite_hash[u'\\xC2'] = \"A\" # LATIN CAPITAL LETTER A WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xC3'] = \"A\" # LATIN CAPITAL LETTER A WITH TILDE\n self.rewrite_hash[u'\\xC4'] = \"A\" # LATIN CAPITAL LETTER A WITH DIAERESIS\n self.rewrite_hash[u'\\xC5'] = \"A\" # LATIN CAPITAL LETTER A WITH RING ABOVE\n self.rewrite_hash[u'\\xC6'] = \"AE\" # LATIN CAPITAL LETTER AE\n self.rewrite_hash[u'\\xC7'] = \"C\" # LATIN CAPITAL LETTER C WITH CEDILLA\n self.rewrite_hash[u'\\xC8'] = \"E\" # LATIN CAPITAL LETTER E WITH GRAVE\n self.rewrite_hash[u'\\xC9'] = \"E\" # LATIN CAPITAL LETTER E WITH ACUTE\n self.rewrite_hash[u'\\xCA'] = \"E\" # LATIN CAPITAL LETTER E WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xCB'] = \"E\" # LATIN CAPITAL LETTER E WITH DIAERESIS\n self.rewrite_hash[u'\\xCC'] = \"I\" # LATIN CAPITAL LETTER I WITH GRAVE\n self.rewrite_hash[u'\\xCD'] = \"I\" # LATIN CAPITAL LETTER I WITH ACUTE\n self.rewrite_hash[u'\\xCE'] = \"I\" # LATIN CAPITAL LETTER I WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xCF'] = \"I\" # LATIN CAPITAL LETTER I WITH DIAERESIS\n\n self.rewrite_hash[u'\\xD0'] = \"Th\" # LATIN CAPITAL LETTER ETH\n self.rewrite_hash[u'\\xD1'] = \"N\" # LATIN CAPITAL LETTER N WITH TILDE\n self.rewrite_hash[u'\\xD2'] = \"O\" # LATIN CAPITAL LETTER O WITH GRAVE\n self.rewrite_hash[u'\\xD3'] = \"O\" # LATIN CAPITAL LETTER O WITH ACUTE\n self.rewrite_hash[u'\\xD4'] = \"O\" # LATIN CAPITAL LETTER O WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xD5'] = \"O\" # LATIN CAPITAL LETTER O WITH TILDE\n self.rewrite_hash[u'\\xD6'] = \"O\" # LATIN CAPITAL LETTER O WITH DIAERESIS\n self.rewrite_hash[u'\\xD7'] = \"x\" # MULTIPLICATION SIGN\n self.rewrite_hash[u'\\xD8'] = \"O\" # LATIN CAPITAL LETTER O WITH STROKE\n self.rewrite_hash[u'\\xD9'] = \"U\" # LATIN CAPITAL LETTER U WITH GRAVE\n self.rewrite_hash[u'\\xDA'] = \"U\" # LATIN CAPITAL LETTER U WITH ACUTE\n self.rewrite_hash[u'\\xDB'] = \"U\" # LATIN CAPITAL LETTER U WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xDC'] = \"U\" # LATIN CAPITAL LETTER U WITH DIAERESIS \n self.rewrite_hash[u'\\xDD'] = \"Y\" # LATIN CAPITAL LETTER Y WITH ACUTE\n self.rewrite_hash[u'\\xDE'] = \"Th\" # LATIN CAPITAL LETTER THORN\n self.rewrite_hash[u'\\xDF'] = \"ss\" # LATIN SMALL LETTER SHARP S\n\n self.rewrite_hash[u'\\xE0'] = \"a\" # LATIN SMALL LETTER A WITH GRAVE\n self.rewrite_hash[u'\\xE1'] = \"a\" # LATIN SMALL LETTER A WITH ACUTE\n self.rewrite_hash[u'\\xE2'] = \"a\" # LATIN SMALL LETTER A WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xE3'] = \"a\" # LATIN SMALL LETTER A WITH TILDE\n self.rewrite_hash[u'\\xE4'] = \"a\" # LATIN SMALL LETTER A WITH DIAERESIS\n self.rewrite_hash[u'\\xE5'] = \"a\" # LATIN SMALL LETTER A WITH RING ABOVE\n self.rewrite_hash[u'\\xE6'] = \"ae\" # LATIN SMALL LETTER AE\n self.rewrite_hash[u'\\xE7'] = \"c\" # LATIN SMALL LETTER C WITH CEDILLA\n self.rewrite_hash[u'\\xE8'] = \"e\" # LATIN SMALL LETTER E WITH GRAVE\n self.rewrite_hash[u'\\xE9'] = \"e\" # LATIN SMALL LETTER E WITH ACUTE\n self.rewrite_hash[u'\\xEA'] = \"e\" # LATIN SMALL LETTER E WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xEB'] = \"e\" # LATIN SMALL LETTER E WITH DIAERESIS\n self.rewrite_hash[u'\\xEC'] = \"i\" # LATIN SMALL LETTER I WITH GRAVE\n self.rewrite_hash[u'\\xED'] = \"i\" # LATIN SMALL LETTER I WITH ACUTE\n self.rewrite_hash[u'\\xEE'] = \"i\" # LATIN SMALL LETTER I WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xEF'] = \"i\" # LATIN SMALL LETTER I WITH DIAERESIS\n\n self.rewrite_hash[u'\\xF0'] = \"th\" # LATIN SMALL LETTER ETH\n self.rewrite_hash[u'\\xF1'] = \"n\" # LATIN SMALL LETTER N WITH TILDE\n self.rewrite_hash[u'\\xF2'] = \"o\" # LATIN SMALL LETTER O WITH GRAVE\n self.rewrite_hash[u'\\xF3'] = \"o\" # LATIN SMALL LETTER O WITH ACUTE\n self.rewrite_hash[u'\\xF4'] = \"o\" # LATIN SMALL LETTER O WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xF5'] = \"o\" # LATIN SMALL LETTER O WITH TILDE\n self.rewrite_hash[u'\\xF6'] = \"o\" # LATIN SMALL LETTER O WITH DIAERESIS\n self.rewrite_hash[u'\\xF7'] = \" divided by \" # DIVISION SIGN\n self.rewrite_hash[u'\\xF8'] = \"o\" # LATIN SMALL LETTER O WITH STROKE\n self.rewrite_hash[u'\\xF9'] = \"u\" # LATIN SMALL LETTER U WITH GRAVE\n self.rewrite_hash[u'\\xFA'] = \"u\" # LATIN SMALL LETTER U WITH ACUTE\n self.rewrite_hash[u'\\xFB'] = \"u\" # LATIN SMALL LETTER U WITH CIRCUMFLEX\n self.rewrite_hash[u'\\xFC'] = \"u\" # LATIN SMALL LETTER U WITH DIAERESIS\n self.rewrite_hash[u'\\xFD'] = \"y\" # LATIN SMALL LETTER Y WITH ACUTE\n self.rewrite_hash[u'\\xFE'] = \"th\" # LATIN SMALL LETTER THORN\n self.rewrite_hash[u'\\xFF'] = \"y\" # LATIN SMALL LETTER Y WITH DIAERESIS\n\n self.rewrite_hash[u'\\u0100'] = \"A\" # LATIN CAPTIAL LETTER A WITH MACRON\n self.rewrite_hash[u'\\u0101'] = \"a\" # LATIN SMALL LETTER A WITH MACRON\n self.rewrite_hash[u'\\u0102'] = \"A\" # LATIN CAPITAL LETTER A WITH BREVE\n self.rewrite_hash[u'\\u0103'] = \"a\" # LATIN SMALL LETTER A WITH BREVE\n self.rewrite_hash[u'\\u0104'] = \"A\" # LATIN CAPITAL LETTER A WITH OGONEK\n self.rewrite_hash[u'\\u0105'] = \"a\" # LATIN SMALL LETTER A WITH OGONEK\n self.rewrite_hash[u'\\u0106'] = \"C\" # LATIN CAPITAL LETTER C WITH ACUTE\n self.rewrite_hash[u'\\u0107'] = \"c\" # LATIN SMALL LETTER C WITH ACUTE\n self.rewrite_hash[u'\\u0108'] = \"C\" # LATIN CAPITAL LETTER C WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0109'] = \"c\" # LATIN SMALL LETTER C WITH CIRCUMFLEX \n self.rewrite_hash[u'\\u010A'] = \"C\" # LATIN CAPITAL LETTER C WITH DOT ABOVE\n self.rewrite_hash[u'\\u010B'] = \"c\" # LATIN SMALL LETTER C WITH DOT ABOVE\n self.rewrite_hash[u'\\u010C'] = \"C\" # LATIN CAPITAL LETTER C WITH CARON\n self.rewrite_hash[u'\\u010D'] = \"c\" # LATIN SMALL LETTER C WITH CARON\n self.rewrite_hash[u'\\u010E'] = \"D\" # LATIN CAPITAL LETTER D WITH CARON\n self.rewrite_hash[u'\\u010F'] = \"d\" # LATIN SMALL LETTER D WITH CARON\n\n self.rewrite_hash[u'\\u0110'] = \"D\" # LATIN CAPITAL LETTER D WITH STROKE\n self.rewrite_hash[u'\\u0111'] = \"d\" # LATIN SMALL LETTER D WITH STROKE\n self.rewrite_hash[u'\\u0112'] = \"E\" # LATIN CAPITAL LETTER E WITH MACRON\n self.rewrite_hash[u'\\u0113'] = \"e\" # LATIN SMALL LETTER E WITH MACRON\n self.rewrite_hash[u'\\u0114'] = \"E\" # LATIN CAPITAL LETTER E WITH BREVE\n self.rewrite_hash[u'\\u0115'] = \"e\" # LATIN SMALL LETTER E WITH BREVE\n self.rewrite_hash[u'\\u0116'] = \"E\" # LATIN CAPITAL LETTER E WITH DOT ABOVE\n self.rewrite_hash[u'\\u0117'] = \"e\" # LATIN SMALL LETTER E WITH DOT ABOVE\n self.rewrite_hash[u'\\u0118'] = \"E\" # LATIN CAPITAL LETTER E WITH OGONEK\n self.rewrite_hash[u'\\u0119'] = \"e\" # LATIN SMALL LETTER E WITH OGONEK\n self.rewrite_hash[u'\\u011A'] = \"E\" # LATIN CAPITAL LETTER E WITH CARON\n self.rewrite_hash[u'\\u011B'] = \"e\" # LATIN SMALL LETTER E WITH CARON\n self.rewrite_hash[u'\\u011C'] = \"G\" # LATIN CAPITAL LETTER G WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u011D'] = \"g\" # LATIN SMALL LETTER G WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u011E'] = \"G\" # LATIN CAPITAL LETTER G WITH BREVE \n self.rewrite_hash[u'\\u011F'] = \"g\" # LATIN SMALL LETTER G WITH BREVE\n\n self.rewrite_hash[u'\\u0120'] = \"G\" # LATIN CAPITAL LETTER G WITH DOT ABOVE\n self.rewrite_hash[u'\\u0121'] = \"g\" # LATIN SMALL LETTER G WITH DOT ABOVE\n self.rewrite_hash[u'\\u0122'] = \"G\" # LATIN CAPITAL LETTER G WITH CEDILLA\n self.rewrite_hash[u'\\u0123'] = \"g\" # LATIN SMALL LETTER G WITH CEDILLA\n self.rewrite_hash[u'\\u0124'] = \"H\" # LATIN CAPITAL LETTER H WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0125'] = \"h\" # LATIN SMALL LETTER H WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0126'] = \"H\" # LATIN CAPITAL LETTER H WITH STROKE\n self.rewrite_hash[u'\\u0127'] = \"h\" # LATIN SMALL LETTER H WITH STROKE\n self.rewrite_hash[u'\\u0128'] = \"I\" # LATIN CAPITAL LETTER I WITH TILDE\n self.rewrite_hash[u'\\u0129'] = \"i\" # LATIN SMALL LETTER I WITH TILDE\n self.rewrite_hash[u'\\u012A'] = \"I\" # LATIN CAPITAL LETTER I WITH MACRON\n self.rewrite_hash[u'\\u012B'] = \"i\" # LATIN SMALL LETTER I WITH MACRON\n self.rewrite_hash[u'\\u012C'] = \"I\" # LATIN CAPITAL LETTER I WITH BREVE\n self.rewrite_hash[u'\\u012D'] = \"i\" # LATIN SMALL LETTER I WITH BREVE\n self.rewrite_hash[u'\\u012E'] = \"I\" # LATIN CAPITAL LETTER I WITH OGONEK\n self.rewrite_hash[u'\\u012F'] = \"i\" # LATIN SMALL LETTER I WITH OGONEK\n\n self.rewrite_hash[u'\\u0130'] = \"I\" # LATIN CAPITAL LETTER I WITH DOT ABOVE\n self.rewrite_hash[u'\\u0131'] = \"i\" # LATIN SMALL LETTER DOTLESS I\n self.rewrite_hash[u'\\u0132'] = \"IJ\" # LATIN CAPITAL LIGATURE IJ\n self.rewrite_hash[u'\\u0133'] = \"ij\" # LATIN SMALL LIGATURE IJ\n self.rewrite_hash[u'\\u0134'] = \"J\" # LATIN CAPITAL LETTER J WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0135'] = \"j\" # LATIN SMALL LETTER J WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0136'] = \"K\" # LATIN CAPITAL LETTER K WITH CEDILLA\n self.rewrite_hash[u'\\u0137'] = \"k\" # LATIN SMALL LETTER K WITH CEDILLA\n self.rewrite_hash[u'\\u0138'] = \"k\" # LATIN SMALL LETTER KRA\n self.rewrite_hash[u'\\u0139'] = \"L\" # LATIN CAPITAL LETTER L WITH ACUTE\n self.rewrite_hash[u'\\u013A'] = \"l\" # LATIN SMALL LETTER L WITH ACUTE\n self.rewrite_hash[u'\\u013B'] = \"L\" # LATIN CAPITAL LETTER L WITH CEDILLA\n self.rewrite_hash[u'\\u013C'] = \"l\" # LATIN SMALL LETTER L WITH CEDILLA\n self.rewrite_hash[u'\\u013D'] = \"L\" # LATIN CAPITAL LETTER L WITH CARON\n self.rewrite_hash[u'\\u013E'] = \"l\" # LATIN SMALL LETTER L WITH CARON\n self.rewrite_hash[u'\\u013F'] = \"L\" # LATIN CAPITAL LETTER L WITH MIDDLE DOT\n\n self.rewrite_hash[u'\\u0140'] = \"l\" # LATIN SMALL LETTER L WITH MIDDLE DOT\n self.rewrite_hash[u'\\u0141'] = \"L\" # LATIN CAPITAL LETTER L WITH STROKE\n self.rewrite_hash[u'\\u0142'] = \"l\" # LATIN SMALL LETTER L WITH STROKE\n self.rewrite_hash[u'\\u0143'] = \"N\" # LATIN CAPITAL LETTER N WITH ACUTE\n self.rewrite_hash[u'\\u0144'] = \"n\" # LATIN SMALL LETTER N WITH ACUTE\n self.rewrite_hash[u'\\u0145'] = \"N\" # LATIN CAPITAL LETTER N WITH CEDILLA\n self.rewrite_hash[u'\\u0146'] = \"n\" # LATIN SMALL LETTER N WITH CEDILLA\n self.rewrite_hash[u'\\u0147'] = \"N\" # LATIN CAPITAL LETTER N WITH CARON\n self.rewrite_hash[u'\\u0148'] = \"n\" # LATIN SMALL LETTER N WITH CARON\n self.rewrite_hash[u'\\u0149'] = \"n\" # LATIN SMALL LETTER N PRECEDED BY APOSTROPHE\n self.rewrite_hash[u'\\u014A'] = \"N\" # LATIN CAPITAL LETTER ENG\n self.rewrite_hash[u'\\u014B'] = \"n\" # LATIN SMALL LETTER ENG\n self.rewrite_hash[u'\\u014C'] = \"O\" # LATIN CAPITAL LETTER O WITH MACRON\n self.rewrite_hash[u'\\u014D'] = \"o\" # LATIN SMALL LETTER O WITH MACRON\n self.rewrite_hash[u'\\u014E'] = \"O\" # LATIN CAPITAL LETTER O WITH BREVE\n self.rewrite_hash[u'\\u014F'] = \"o\" # LATIN SMALL LETTER O WITH BREVE\n\n self.rewrite_hash[u'\\u0150'] = \"O\" # LATIN CAPITAL LETTER O WITH DOUBLE ACUTE\n self.rewrite_hash[u'\\u0151'] = \"o\" # LATIN SMALL LETTER O WITH DOUBLE ACUTE\n self.rewrite_hash[u'\\u0152'] = \"oe\" # LATIN CAPITAL LIGATURE OE\n self.rewrite_hash[u'\\u0153'] = \"oe\" # LATIN SMALL LIGATURE OE\n self.rewrite_hash[u'\\u0153'] = \"R\" # LATIN CAPITAL LETTER R WITH ACUTE\n self.rewrite_hash[u'\\u0154'] = \"R\" # LATIN CAPITAL LETTER R WITH ACUTE\n self.rewrite_hash[u'\\u0155'] = \"r\" # LATIN SMALL LETTER R WITH ACUTE\n self.rewrite_hash[u'\\u0156'] = \"R\" # LATIN CAPITAL LETTER R WITH CEDILLA\n self.rewrite_hash[u'\\u0157'] = \"r\" # LATIN SMALL LETTER R WITH CEDILLA\n self.rewrite_hash[u'\\u0158'] = \"R\" # LATIN CAPITAL LETTER R WITH CARON\n self.rewrite_hash[u'\\u0159'] = \"r\" # LATIN SMALL LETTER R WITH CARON\n self.rewrite_hash[u'\\u015A'] = \"S\" # LATIN CAPITAL LETTER S WITH ACUTE\n self.rewrite_hash[u'\\u015B'] = \"s\" # LATIN SMALL LETTER S WITH ACUTE\n self.rewrite_hash[u'\\u015C'] = \"S\" # LATIN CAPITAL LETTER S WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u015D'] = \"s\" # LATIN SMALL LETTER S WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u015E'] = \"S\" # LATIN CAPITAL LETTER S WITH CEDILLA\n self.rewrite_hash[u'\\u015F'] = \"s\" # LATIN SMALL LETTER S WITH CEDILLA\n\n self.rewrite_hash[u'\\u0160'] = \"S\" # LATIN CAPITAL LETTER S WITH CARON\n self.rewrite_hash[u'\\u0161'] = \"s\" # LATIN SMALL LETTER S WITH CARON\n self.rewrite_hash[u'\\u0162'] = \"T\" # LATIN CAPITAL LETTER T WITH CEDILLA \n self.rewrite_hash[u'\\u0163'] = \"t\" # LATIN SMALL LETTER T WITH CEDILLA\n self.rewrite_hash[u'\\u0164'] = \"T\" # LATIN CAPITAL LETTER T WITH CARON\n self.rewrite_hash[u'\\u0165'] = \"t\" # LATIN SMALL LETTER T WITH CARON\n self.rewrite_hash[u'\\u0166'] = \"T\" # LATIN CAPITAL LETTER T WITH STROKE\n self.rewrite_hash[u'\\u0167'] = \"t\" # LATIN SMALL LETTER T WITH STROKE\n self.rewrite_hash[u'\\u0168'] = \"U\" # LATIN CAPITAL LETTER U WITH TILDE\n self.rewrite_hash[u'\\u0169'] = \"u\" # LATIN SMALL LETTER U WITH TILDE\n self.rewrite_hash[u'\\u016A'] = \"U\" # LATIN CAPITAL LETTER U WITH MACRON\n self.rewrite_hash[u'\\u016B'] = \"u\" # LATIN SMALL LETTER U WITH MACRON\n self.rewrite_hash[u'\\u016C'] = \"U\" # LATIN CAPITAL LETTER U WITH BREVE\n self.rewrite_hash[u'\\u016D'] = \"u\" # LATIN SMALL LETTER U WITH BREVE\n self.rewrite_hash[u'\\u016E'] = \"U\" # LATIN CAPITAL LETTER U WITH RING ABOVE\n self.rewrite_hash[u'\\u016F'] = \"u\" # LATIN SMALL LETTER U WITH RING ABOVE\n\n self.rewrite_hash[u'\\u0170'] = \"U\" # LATIN CAPITAL LETTER U WITH DOUBLE ACUTE\n self.rewrite_hash[u'\\u0171'] = \"u\" # LATIN SMALL LETTER U WITH DOUBLE ACUTE\n self.rewrite_hash[u'\\u0172'] = \"U\" # LATIN CAPITAL LETTER U WITH OGONEK\n self.rewrite_hash[u'\\u0173'] = \"u\" # LATIN SMALL LETTER U WITH OGONEK\n self.rewrite_hash[u'\\u0174'] = \"W\" # LATIN CAPITAL LETTER W WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0175'] = \"w\" # LATIN SMALL LETTER W WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0176'] = \"Y\" # LATIN CAPITAL LETTER Y WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0177'] = \"y\" # LATIN SMALL LETTER Y WITH CIRCUMFLEX\n self.rewrite_hash[u'\\u0178'] = \"Y\" # LATIN CAPITAL LETTER Y WITH DIAERESIS\n self.rewrite_hash[u'\\u0179'] = \"Z\" # LATIN CAPITAL LETTER Z WITH ACUTE\n self.rewrite_hash[u'\\u017A'] = \"z\" # LATIN SMALL LETTER Z WITH ACUTE\n self.rewrite_hash[u'\\u017B'] = \"Z\" # LATIN CAPITAL LETTER Z WITH DOT ABOVE\n self.rewrite_hash[u'\\u017C'] = \"z\" # LATIN SMALL LETTER Z WITH DOT ABOVE\n self.rewrite_hash[u'\\u017D'] = \"Z\" # LATIN CAPITAL LETTER Z WITH CARON\n self.rewrite_hash[u'\\u017E'] = \"z\" # LATIN SMALL LETTER Z WITH CARON\n self.rewrite_hash[u'\\u017F'] = \"s\" # LATIN SMALL LETTER LONG S\n\n self.rewrite_hash[u'\\u0180'] = \"b\" # LATIN SMALL LETTER B WITH STROKE\n self.rewrite_hash[u'\\u0181'] = \"B\" # LATIN CAPITAL LETTER B WITH HOOK\n self.rewrite_hash[u'\\u0182'] = \"B\" # LATIN CAPITAL LETTER B WITH TOPBAR\n self.rewrite_hash[u'\\u0183'] = \"b\" # LATIN SMALL LETTER B WITH TOPBAR\n self.rewrite_hash[u'\\u0184'] = \"b\" # LATIN CAPITAL LETTER TONE SIX\n self.rewrite_hash[u'\\u0185'] = \"b\" # LATIN SMALL LETTER TONE SIX \n self.rewrite_hash[u'\\u0186'] = \"O\" # LATIN CAPITAL LETTER OPEN O\n self.rewrite_hash[u'\\u0187'] = \"C\" # LATIN CAPITAL LETTER C WITH HOOK\n self.rewrite_hash[u'\\u0188'] = \"c\" # LATIN SMALL LETTER C WITH HOOK\n self.rewrite_hash[u'\\u0189'] = \"D\" # LATIN CAPITAL LETTER AFRICAN D\n self.rewrite_hash[u'\\u018A'] = \"D\" # LATIN CAPITAL LETTER D WITH HOOK\n self.rewrite_hash[u'\\u018B'] = \"d\" # LATIN CAPITAL LETTER D WITH TOPBAR\n self.rewrite_hash[u'\\u018C'] = \"d\" # LATIN SMALL LETTER D WITH TOPBAR\n self.rewrite_hash[u'\\u018D'] = \" \" # LATIN SMALL LETTER TURNED DELTA\n self.rewrite_hash[u'\\u018E'] = \" \" # LATIN CAPITAL LETTER REVERSED E\n self.rewrite_hash[u'\\u018F'] = \" \" # LATIN CAPITAL LETTER SCHWA\n\n self.rewrite_hash[u'\\u0190'] = \"E\" # LATIN CAPITAL LETTER OPEN E\n self.rewrite_hash[u'\\u0191'] = \"F\" # LATIN CAPITAL LETTER F WITH HOOK\n self.rewrite_hash[u'\\u0192'] = \"f\" # LATIN SMALL LETTER F WITH HOOK\n self.rewrite_hash[u'\\u0193'] = \"G\" # LATIN CAPITAL LETTER G WITH HOOK\n self.rewrite_hash[u'\\u0194'] = \" \" # LATIN CAPITAL LETTER GAMMA\n self.rewrite_hash[u'\\u0195'] = \"hv\" # LATIN SMALL LETTER HV\n self.rewrite_hash[u'\\u0196'] = \"I\" # LATIN CAPITAL LETTER IOTA\n self.rewrite_hash[u'\\u0197'] = \"I\" # LATIN CAPITAL LETTER I WITH STROKE\n self.rewrite_hash[u'\\u0198'] = \"K\" # LATIN CAPITAL LETTER K WITH HOOK\n self.rewrite_hash[u'\\u0199'] = \"k\" # LATIN SMALL LETTER K WITH HOOK\n self.rewrite_hash[u'\\u019A'] = \"l\" # LATIN SMALL LETTER L WITH BAR\n self.rewrite_hash[u'\\u019B'] = \" \" # LATIN SMALL LETTER LAMBDA WITH STROKE\n self.rewrite_hash[u'\\u019C'] = \" \" # LATIN CAPITAL LETTER TURNED M\n self.rewrite_hash[u'\\u019D'] = \"N\" # LATIN CAPITAL LETTER N WITH LEFT HOOK\n self.rewrite_hash[u'\\u019E'] = \"n\" # LATIN SMALL LETTER N WITH LONG RIGHT LEG\n self.rewrite_hash[u'\\u019F'] = \"O\" # LATIN CAPITAL LETTER O WITH MIDDLE TILDE\n\n self.rewrite_hash[u'\\u0226'] = \"a\" # LATIN CAPITAL LETTER A WITH DOT ABOVE\n self.rewrite_hash[u'\\u0227'] = \"a\" # LATIN SMALL LETTER A WITH DOT ABOVE\n self.rewrite_hash[u'\\u02DC'] = \" \" # SMALL TILDE \n\n self.rewrite_hash[u'\\u0391'] = \"A\" # GREEK CAPITAL LETTER ALPHA\n self.rewrite_hash[u'\\u03A4'] = \"T\" # GREEK CAPITAL LETTER TAU\n self.rewrite_hash[u'\\u03A9'] = \" omega \" # GREEK CAPITAL LETTER OMEGA\n self.rewrite_hash[u'\\u03B2'] = \" beta \" # GREEK SMALL LETTER BETA\n self.rewrite_hash[u'\\u03BC'] = \" mu \" # GREEK SMALL LETTER MU\n self.rewrite_hash[u'\\u03C0'] = \" pi \" # GREEK SMALL LETTER PI\n\n self.rewrite_hash[u'\\u0441'] = \"c\" # CYRILLIC SMALL LETTER ES\n\n self.rewrite_hash[u'\\u1F7B'] = \"u\" # GREEK SMALL LETTER UPSILON WITH OXIA \n self.rewrite_hash[u'\\u1E25'] = \"h\" # LATIN SMALL LETTER H WITH DOT BELOW\n self.rewrite_hash[u'\\u1ECB'] = \"i\" # LATIN SMALL LETTER I WITH DOT BELOW\n\n self.rewrite_hash[u'\\u2018'] = \"'\" # LEFT SINGLE QUOTATION MARK\n self.rewrite_hash[u'\\u2019'] = \"'\" # RIGHT SINGLE QUOTATION MARK\n self.rewrite_hash[u'\\u201A'] = \" \" # SINGLE LOW-9 QUOTATION MARK\n self.rewrite_hash[u'\\u201C'] = \" \" # LEFT DOUBLE QUOTATION MARK\n self.rewrite_hash[u'\\u201D'] = \" \" # RIGHT DOUBLE QUOTATION MARK\n self.rewrite_hash[u'\\u201E'] = \" \" # DOUBLE LOW-9 QUOTATION MARK\n self.rewrite_hash[u'\\u201F'] = \" \" # OUBLE HIGH-REVERSED-9 QUOTATION MARK\n\n self.rewrite_hash[u'\\u2032'] = \"\\'\" # PRIME\n self.rewrite_hash[u'\\u2033'] = \" \" # DOUBLE PRIME\n\n self.rewrite_hash[u'\\u20AC'] = \" euros \" # EURO SIGN\n\n self.rewrite_hash[u'\\u2122'] = \" \" # TRADE MARK SIGN\n\n self.rewrite_hash[u'\\uFB01'] = \"fi\" # LATIN SMALL LIGATURE FI\n self.rewrite_hash[u'\\uFF00'] = \" \" # \n\n return \n\n\n def remove_word_punctuation (self,ln):\n \"\"\" Punctuation Remover \"\"\"\n ln = re.sub(\"^(\\S+)[\\.\\!\\?]\", \"\\g<1>\", ln)\n ln = re.sub(\"\\s(\\S+)[\\.\\!\\?]\", \" \\g<1>\", ln)\n ln = re.sub(\"(\\S+)[\\.\\!\\?]$\", \"\\g<1>\", ln)\n ln = re.sub(\"\\s[\\.\\!\\?]\\s\", \" \", ln)\n ln = re.sub(\"^[\\.\\!\\?]$\", \"\", ln)\n\n # Clean up extra spaces\n ln = re.sub('^\\s+', '', ln)\n ln = re.sub('\\s+$', '', ln)\n ln = re.sub('\\s+', ' ', ln)\n\n return ln\n\n\n def remove_twitter_meta (self,ln):\n \"\"\" Twitter Metadata Remover \"\"\"\n # ln = re.sub(r'\\#\\S+', ' ', ln) # remove hashtags --old version\n # ln = re.sub(r'\\@\\S+', ' ', ln) # remove @tags -- old version\n\n # ln = re.sub(r'\\#[a-zA-Z0-9_]+', ' ', ln) # remove hashtags\n ln = re.sub(r'\\@[a-zA-Z0-9_]+', ' ', ln) # remove @tags\n ln = re.sub('\\sRT\\s', ' ', ln) # remove retweet marker\n ln = re.sub('^RT\\s', ' ', ln)\n\n # Clean up extra spaces\n ln = re.sub('^\\s+', '', ln)\n ln = re.sub('\\s+$', '', ln)\n ln = re.sub('\\s+', ' ', ln)\n return ln\n\n\n def remove_nonsentential_punctuation (self,ln):\n \"\"\" Remove non-sentential punctuation \"\"\"\n\n # remove '-'\n ln = re.sub('^\\-+', '', ln)\n ln = re.sub('\\-\\-+', '', ln)\n ln = re.sub('\\s\\-+', '', ln)\n\n # remove '~'\n ln = re.sub('\\~', ' ', ln)\n\n # remove standard double quotes\n ln = re.sub('\\\"', '', ln)\n\n # remove single quotes\n ln = re.sub(\"^\\'+\", '', ln)\n ln = re.sub(\"\\'+$\", '', ln)\n ln = re.sub(\"\\'+\\s+\", ' ', ln)\n ln = re.sub(\"\\s+\\'+\", ' ', ln)\n ln = re.sub(\"\\s+\\`+\", ' ', ln)\n ln = re.sub(\"^\\`+\", ' ', ln)\n\n # remove ':'\n ln = re.sub(\"\\:\\s\", \" \", ln)\n ln = re.sub(\"\\:$\", \"\", ln)\n\n # remove ';'\n ln = re.sub('\\;\\s', ' ', ln)\n ln = re.sub('\\;$', '', ln)\n\n # remove '_'\n ln = re.sub('\\_+\\s', ' ', ln)\n ln = re.sub('^\\_+', '', ln)\n ln = re.sub('_+$', '', ln)\n ln = re.sub('\\_\\_+', ' ', ln)\n\n # remove ','\n ln = re.sub('\\,+([\\#A-Za-z])', ' \\g<1>', ln) \n ln = re.sub('\\,+$', ' ', ln)\n ln = re.sub('\\,\\.\\s', ' ', ln)\n ln = re.sub('\\,\\s', ' ', ln)\n\n # remove ''\n ln = re.sub('\\s\\+', ' ', ln)\n ln = re.sub('\\+\\s', ' ', ln)\n ln = re.sub('\\\\.', ' ', ln)\n ln = re.sub('\\s\\+\\s', ' ', ln)\n ln = re.sub('^\\+', '', ln)\n ln = re.sub('\\+$', '', ln)\n\n # Keep only one '.', '?', or '!' \n ln = re.sub('\\?[\\!\\?]+', '?', ln)\n ln = re.sub('\\![\\?\\!]+', '!', ln)\n ln = re.sub('\\.\\.+', '.', ln)\n\n # # remove '/'\n ln = re.sub('\\s\\/', ' ', ln)\n ln = re.sub('\\/\\s', ' ', ln)\n\n # remove sentence final '!' and '?' \n # ln = re.sub('[\\!\\?]+\\s$', '', ln)\n \n # remove other special characters\n ln = re.sub('\\\|', ' ', ln)\n ln = re.sub(r'\\\\', ' ', ln)\n\n # Remove parentheses that are not part of emoticons.\n # Note sure of the best way to do this, but here's a conservative \n # approach.\n ln = re.sub('\$([@\\#A-Za-z0-9])', '\\g<1>', ln)\n ln = re.sub('([@\\#A-Za-z0-9])\$', '\\g<1> ', ln)\n\n # Clean up extra spaces\n ln = re.sub('^\\s+', '', ln)\n ln = re.sub('\\s+$', '', ln)\n ln = re.sub('\\s+', ' ', ln)\n\n return ln\n\n" }, { "alpha_fraction": 0.565100908279419, "alphanum_fraction": 0.5737704634666443, "avg_line_length": 37.21084213256836, "blob_id": "0017a686ca56692335e98220f0d7952eb128f938", "content_id": "732da03c5755af857a54a34ca28e54a7def09519", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6344, "license_type": "permissive", "max_line_length": 190, "num_lines": 166, "path": "/llstring/llstring/matching/softtfidf.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python\n\n# softtfidf.py\n#\n# Soft TF-IDF String Comparison Algorithm\n# \n# Copyright 2015-2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli\n# [email protected]\n#\n# Original logic written by @drangons for the entity_resolution_spark repository:\n# https://github.com/drangons/entity_resolution_spark\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n\n#Imports\nimport logging\nimport math\n\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\n\nimport jellyfish as jf\n\n\nclass Softtfidf:\n \"\"\"\n This module implements the soft tf-idf algorithm described in:\n A Comparison of String Distance Metrics for Name-Matching Tasks\n Cohen et al., IJCAI 2003\n \"\"\"\n\n # Logging\n LOG_LEVEL = logging.INFO\n logging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\n logger = logging.getLogger(__name__)\n\n\n def __init__(self,threshold=0.6, idf_model=None):\n \"\"\" Constructor \"\"\"\n self.THRESHOLD = threshold\n\n if idf_model == None:\n self.LOG_IDF = None\n self.CORPUS_VOCAB = None\n self.OOV_IDF_VAL = None\n else:\n self.LOG_IDF = idf_model['idf']\n self.CORPUS_VOCAB = idf_model['corpus_vocab']\n self.OOV_IDF_VAL = idf_model['oov_idf_val']\n\n\n def set_model(self,idf_model):\n \"\"\" Set softtfidf matcher's model parameters \"\"\"\n # Set (or compute) IDF and corresponding vocabulary\n self.LOG_IDF = idf_model['idf']\n self.CORPUS_VOCAB = idf_model['corpus_vocab']\n self.OOV_IDF_VAL = idf_model['oov_idf_val']\n\n\n def set_threshold(self,threshold=0.6):\n \"\"\" Set threshold \"\"\"\n self.THRESHOLD = threshold\n\n\n def compute_VwS(self,s):\n \"\"\" Compute V(w,S) as defined by Cohen et al.'s IJCAI03 paper \"\"\"\n # Get term-frequency vectors and vocab list for string\n cv = CountVectorizer(min_df = 0.0, token_pattern=u'(?u)\\\\b\\\\w+\\\\b')\n tf = cv.fit_transform([s]); tf = tf.tocsr()\n vocab = cv.vocabulary_\n\n # Compute V(w,S) for string\n vprime_ws = dict()\n vprime_ws_norm = 0\n for w in vocab:\n if w in self.CORPUS_VOCAB:\n vprime_ws[w] = math.log(tf[0,vocab[w]]+1)self.LOG_IDF[self.CORPUS_VOCAB[w]]\n else:\n vprime_ws[w] = math.log(tf[0,vocab[w]]+1)self.OOV_IDF_VAL #if not in vocab, defauly to OOC_IDF_VAL\n vprime_ws_norm += vprime_ws[w]*2\n vprime_ws_norm = math.sqrt(vprime_ws_norm)\n\n return (vocab,vprime_ws,vprime_ws_norm)\n\n\n def score(self,s,t):\n \"\"\" Returns the soft tf-idf similarity \"\"\"\n\n # Check to see whether a model exists; otherwise default to degenerate solution\n if (self.LOG_IDF is None) \| (self.CORPUS_VOCAB is None) \| (self.OOV_IDF_VAL is None):\n self.logger.info(\"Either (or both) IDF or corpus vocabulary parameters not given \" \n +\"Defaulting to degenerate mode where corpus consists only of the \"\n +\"two strings given as input.\");\n self.compute_query_idf([s,t])\n\n # Get V(w,S) and V(w,T) (along with vocab lists for s and t) \n try: \n (s_vocab,vprime_ws,vprime_ws_norm) = self.compute_VwS(s)\n (t_vocab,vprime_wt,vprime_wt_norm) = self.compute_VwS(t)\n except ValueError:\n self.logger.info(\"string got stop-listed; most likely b/c \" \\\n \"it is of length 1, with the only character being a \" \\\n \"non-normalized punctuation mark. (i.e. '.')\")\n sim = 0.0\n return sim\n\n #compute D(w,T) for all w\n max_vT = dict()\n jw_sims = dict()\n for w in s_vocab:\n max_vT[w] = dict(); max_vT[w]['score'] = 0.0; max_vT[w]['max_v'] = '';\n jw_sims[w] = dict()\n for v in t_vocab:\n dist = jf.jaro_winkler(w,v)\n jw_sims[w][v] = dist\n if (dist >= max_vT[w]['score']):\n max_vT[w]['score'] = dist\n max_vT[w]['max_v'] = v\n self.logger.debug(\"max_vT: {0}\".format(max_vT))\n\n # compute soft tf-idf sim\n sim = 0.0\n self.logger.debug(s_vocab)\n for w in s_vocab:\n for v in t_vocab:\n if (jw_sims[w][v] >= self.THRESHOLD):\n inner_sum = (vprime_ws[w]/vprime_ws_norm)(vprime_wt[max_vT[w]['max_v']]/vprime_wt_norm)*max_vT[w]['score']\n self.logger.debug(u\"(w,vprime_ws[w],vprime_ws_norm): ({0},{1},{2})\".format(w,vprime_ws[w],vprime_ws_norm))\n self.logger.debug(u\"(max_vT[w]['max_v'],vprime_wt[max_vT['max_v'],vprime_wt_norm): ({0},{1},{2})\".format(max_vT[w]['max_v'],vprime_wt[max_vT[w]['max_v']],vprime_wt_norm))\n self.logger.debug(u\"(max_vT[w]['score']): ({0})\".format(max_vT[w]['score']))\n self.logger.debug(u\"(w,v,inner_sum): ({0},{1},{2})\".format(w,v,inner_sum))\n sim += inner_sum\n break\n\n self.logger.debug(\"Soft TF-IDF Similarity: {0}\".format(sim))\n\n return sim\n\n\n def compute_query_idf(self,corpus):\n \"\"\" Compute IDF from s and t in case you have no externally computed IDF to use \"\"\"\n cv = CountVectorizer(min_df = 0.0)\n cv.fit_transform(corpus)\n self.logger.debug(cv.vocabulary_)\n freq_term_matrix = cv.transform(corpus)\n tfidf = TfidfTransformer(norm=\"l2\")\n tfidf.fit(freq_term_matrix)\n log_idf = tfidf.idf_\n self.LOG_IDF = log_idf\n self.CORPUS_VOCAB = cv.vocabulary_\n\n" }, { "alpha_fraction": 0.6307892799377441, "alphanum_fraction": 0.6395955681800842, "avg_line_length": 27.644859313964844, "blob_id": "b9b3780eedfe93dfd1d46848cba2ec27ba432c52", "content_id": "79f5e41631717205ec1a07259bc6a1df280cdb04", "detected_licenses": [ "Apache-2.0" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3066, "license_type": "permissive", "max_line_length": 98, "num_lines": 107, "path": "/examples/idf_training_example.py", "repo_name": "escap-data-hub/LLString", "src_encoding": "UTF-8", "text": "#! /usr/bin/env python\n\n# idf_training_example.py\n#\n# Example script to learn IDF from a training corpus\n# \n# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory\n# version 0.1\n#\n# author: Charlie Dagli\n# [email protected]\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n#\n# Imports \n#\nimport os, logging\nimport numpy as np\n\nfrom llstring.training import idf_trainer\n\n#\n# Logging\n#\nLOG_LEVEL = logging.DEBUG\nlogging.basicConfig(level=LOG_LEVEL,\n format='%(asctime)s %(levelname)-8s %(message)s',\n datefmt='%a, %d %b %Y %H:%M:%S')\nlogger = logging.getLogger(__name__)\n\n\ndef idf_display(idft,N=10):\n \"\"\" Print tokens with highest and lowest IDF\n\n Anecdotally, high IDF corresponds to unames being used as fullnames\n\n Input: idft: trained IDFTrainer instance\n N: Number of tokens to print \n \"\"\"\n\n index2name = dict()\n for name in idft.CORPUS_VOCAB.keys():\n index2name[idft.CORPUS_VOCAB[name]] = name\n\n logger.info(\"\")\n logger.info(\"TOKENS CORRESPONDING TO LOWEST IDF VALUES\")\n logger.info(\"=========================================\")\n low_idf_inds = np.argsort(idft.LOG_IDF)\n for i in range(0,N):\n logger.info(\"{0},{1}\".format(index2name[low_idf_inds[i]],idft.LOG_IDF[low_idf_inds[i]]))\n\n logger.info(\"\")\n\n logger.info(\"TOKENS CORRESPONDING TO HIGHEST IDF VALUES\")\n logger.info(\"==========================================\")\n high_idf_inds = np.argsort(-idft.LOG_IDF)\n for i in range(0,N):\n logger.info(\"{0},{1}\".format(index2name[high_idf_inds[i]],idft.LOG_IDF[high_idf_inds[i]]))\n\n logger.info(\"\")\n\n\nif __name__ == \"__main__\":\n \n # Input and Output Filenames\n exampledir = os.path.dirname(os.path.realpath(__file__))\n fnamein = os.path.join(exampledir,\"data/input/idf_training_data.txt\")\n fnameout = os.path.join(exampledir,\"data/output/models/english_socialmedia_idf.pckl\")\n\n #\n # Train IDF from file handle\n # (i.e. for large training sets)\n #\n idft = idf_trainer.IDFTrainer()\n idft.compute_idf(open(fnamein,\"r\"))\n idft.save_model(fnameout)\n\n idf_display(idft,20)\n\n #\n # Train IDF from python list instance\n # (i.e. for training sets that can fit in memory)\n #\n\n # load-in training data\n training_data = list()\n fo = open(fnamein,\"r\")\n for line in fo: training_data.append(line.rstrip())\n fo.close()\n \n # compute IDF\n idft = idf_trainer.IDFTrainer()\n idft.compute_idf(training_data)\n idft.save_model(fnameout)\n\n idf_display(idft,20)\n\n" } ]	16
andersk/homeworld	https://github.com/andersk/homeworld	91f05cb901adee6479898a52418ef91429e41a70	fad390adaca74e09559e53ede08486e2a0a8c1b7	4d6bf8a6c24964b6f5f1d59a4e35cec4052fcabf	refs/heads/master	2020-12-03T00:35:22.582717	2017-07-02T03:01:33	2017-07-02T03:01:33	96,045,911	0	0	null	2017-07-02T19:59:03	2017-07-02T02:48:42	2017-07-02T06:38:17	null	[ { "alpha_fraction": 0.6346153616905212, "alphanum_fraction": 0.6346153616905212, "avg_line_length": 51, "blob_id": "18d5941e019f3a07618fbe15105d401ed442b912", "content_id": "50bd183ea682bc442309f5c4cee16a64ff94afcb", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 156, "license_type": "permissive", "max_line_length": 142, "num_lines": 3, "path": "/admin/ectl", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\n\nexec etcdctl --endpoints \"$(cat ~/.etcd/etcd.conf)\" --ca-file ~/.etcd/ca.pem --key-file ~/.etcd/etcli-key.pem --cert-file ~/.etcd/etcli.pem $\n" }, { "alpha_fraction": 0.6639566421508789, "alphanum_fraction": 0.6937669515609741, "avg_line_length": 20.705883026123047, "blob_id": "a1fce421d58a75475be2ecd91352000f205cde08", "content_id": "673df8404ddedef18e86c8fadbaac5928f3c39c6", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 369, "license_type": "permissive", "max_line_length": 51, "num_lines": 17, "path": "/build-flannel/build.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\ncd $(dirname $0)\nROOT=$(pwd)\nrm -rf go/\nmkdir -p go/src/github.com/coreos/\ncd go/src/github.com/coreos/\necho \"extracting...\"\ntar -xf ${ROOT}/flannel-0.7.1.tar.xz flannel-0.7.1/\necho \"extracted!\"\nexport GOPATH=${ROOT}/go\nmv flannel-0.7.1/ flannel/\ncd flannel/\nCGO_ENABLED=1 make dist/flanneld\ncd ${ROOT}\n./package.sh\necho \"built flannel binaries!\"\n" }, { "alpha_fraction": 0.7246376872062683, "alphanum_fraction": 0.7443478107452393, "avg_line_length": 46.91666793823242, "blob_id": "2e26a3be13779553a33aeba0a60137d9ae46fdcc", "content_id": "987e32a781b5b4cc6f87ff6f9ad8031d11dbab6c", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 1725, "license_type": "permissive", "max_line_length": 196, "num_lines": 36, "path": "/deployment/wrappers/launch-etcd.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\nsource /etc/hyades/cluster.conf\nsource /etc/hyades/local.conf\n\nTLS_MOUNTPOINT=/etc/hyades/certs/etcd/\nTLS_STORAGE=/etc/hyades/certs/etcd/\nPERSISTENT_DATA=/var/lib/etcd\nETCD_IMAGE=/usr/lib/hyades/images/etcd-current-linux-amd64.aci\n\nmkdir -p ${PERSISTENT_DATA}\n\n# our image is stored on disk -- better hope that's safe!\nHOSTOPT=\"--insecure-options=image\"\n# provide data directory for etcd to store persistent data\nHOSTOPT=\"$HOSTOPT --volume data-dir,kind=host,source=${PERSISTENT_DATA}\"\n# provide directory for etcd TLS certificates\nHOSTOPT=\"$HOSTOPT --volume etcd-certs,kind=host,readOnly=true,source=${TLS_STORAGE} --mount volume=etcd-certs,target=${TLS_MOUNTPOINT}\"\n# bind ports to public interface\nHOSTOPT=\"$HOSTOPT --port=client:2379 --port=peer:2380\"\n\n# etcd node name\nETCDOPT=\"--name=${HOST_NODE}\"\n# public advertisement URLs\nETCDOPT=\"$ETCDOPT --advertise-client-urls=https://${HOST_IP}:2379 --initial-advertise-peer-urls=https://${HOST_IP}:2380\"\n# listening URLs\nETCDOPT=\"$ETCDOPT --listen-client-urls=https://0.0.0.0:2379 --listen-peer-urls=https://0.0.0.0:2380\"\n# initial cluster setup\nETCDOPT=\"$ETCDOPT --initial-cluster=${ETCD_CLUSTER} --initial-cluster-token=${ETCD_TOKEN} --initial-cluster-state=new\"\n# client-to-server TLS certs\nETCDOPT=\"$ETCDOPT --cert-file=${TLS_MOUNTPOINT}/etcd-self.pem --key-file=${TLS_MOUNTPOINT}/etcd-self-key.pem --client-cert-auth --trusted-ca-file=${TLS_MOUNTPOINT}/etcd-ca-client.pem\"\n# server-to-server TLS certs\nETCDOPT=\"$ETCDOPT --peer-cert-file=${TLS_MOUNTPOINT}/etcd-self.pem --peer-key-file=${TLS_MOUNTPOINT}/etcd-self-key.pem --peer-client-cert-auth --peer-trusted-ca-file=${TLS_MOUNTPOINT}/etcd-ca.pem\"\n\nexec rkt run $HOSTOPT ${ETCD_IMAGE} -- $ETCDOPT\n" }, { "alpha_fraction": 0.6944907903671265, "alphanum_fraction": 0.7111853361129761, "avg_line_length": 27.5238094329834, "blob_id": "df4f43763374dd93e79b851951c547a5bf3d629d", "content_id": "324ef89469beb28742794855d245ece8cfc97d1b", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 599, "license_type": "permissive", "max_line_length": 113, "num_lines": 21, "path": "/auth/package.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\nVERSION=0.1.4\n\ncd $(dirname $0)\nHERE=$(pwd)\nHYBIN=$(pwd)/../binaries/\nmkdir -p ${HYBIN}\n\nFPMOPT=\"-s dir -t deb\"\nFPMOPT=\"$FPMOPT -n hyades-authserver -v ${VERSION} --iteration 1\"\nFPMOPT=\"$FPMOPT --maintainer '[email protected]'\"\nFPMOPT=\"$FPMOPT --license MIT -a x86_64\"\nFPMOPT=\"$FPMOPT --depends krb5-user\"\nFPMOPT=\"$FPMOPT --after-install auth.postinstall --after-remove auth.postremove --before-install auth.preinstall\"\nFPMOPT=\"$FPMOPT hyauth=/usr/bin/hyauth sshd_config=/etc/ssh/sshd_config.hyades-new\"\n\nfpm --vendor 'MIT SIPB Hyades Project' $FPMOPT\n\necho \"authserver package built!\"\n" }, { "alpha_fraction": 0.7223065495491028, "alphanum_fraction": 0.7329286932945251, "avg_line_length": 33.68421173095703, "blob_id": "473b177ad55fdd7eb7193a82fe24cb8cb5b4cf2d", "content_id": "4dcf1948e8f09e1983a06edd17e0a19fe6de71ce", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 659, "license_type": "permissive", "max_line_length": 92, "num_lines": 19, "path": "/build-rkt/restrip-coreos.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\ncd $(dirname $0)\ncat $(find rkt-1.27.0/ -name .manifest \| grep amd64) \| sort -u >coreos-manifest.txt\nzcat coreos_production_pxe_image.cpio.gz \| cpio -i --to-stdout usr.squashfs >coreos_squashfs\nrm -rf coreos_minimal_dir\nunsquashfs -d coreos_minimal_dir -e coreos-manifest.txt coreos_squashfs\nrm coreos_squashfs\ncd coreos_minimal_dir\nmksquashfs ./ ../coreos_resquash -root-owned -noappend\ncd ..\nrm -rf coreos_minimal_dir\nmkdir -p coreos_ncpio/etc\ncd coreos_ncpio\nmv ../coreos_resquash usr.squashfs\n(echo .; echo etc; echo usr.squashfs) \| cpio -o \| gzip -c >../coreos_restructured.cpio.gz\ncd ..\nrm -rf coreos_ncpio\nrm coreos-manifest.txt\n" }, { "alpha_fraction": 0.7019498348236084, "alphanum_fraction": 0.7047353982925415, "avg_line_length": 34.900001525878906, "blob_id": "ac4f1a124ccebd3aa7c739f3a6cbe12172dfac42", "content_id": "2a13111db6cd98b30f4e3c02bd75717c82817e65", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 359, "license_type": "permissive", "max_line_length": 151, "num_lines": 10, "path": "/deployment/wrappers/init-flannel.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\nsource /etc/hyades/cluster.conf\n\nAUTHOPT=\"--ca-file /etc/hyades/certs/kube/etcd-ca.pem --cert-file /etc/hyades/certs/kube/etcd-cert.pem --key-file /etc/hyades/certs/kube/local-key.pem\"\n\nexport ETCDCTL_API=2\n\n/usr/bin/etcdctl --endpoints ${ETCD_ENDPOINTS} ${AUTHOPT} set /coreos.com/network/config \"{ \\\"network\\\": \\\"${CLUSTER_CIDR}\\\" }\"\n" }, { "alpha_fraction": 0.6098807454109192, "alphanum_fraction": 0.6201022267341614, "avg_line_length": 26.302326202392578, "blob_id": "a807d7affc6007be6611616227102942a7b5b6d7", "content_id": "f9bd1fb89b758503b759287217703f108eaa7951", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 1174, "license_type": "permissive", "max_line_length": 110, "num_lines": 43, "path": "/admission/setup.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\nSSH_DIR=/etc/ssh/\n\ncat >server-tmp.cert <<EOCERTIFICATE_HERE\n{{SERVER CERTIFICATE}}\nEOCERTIFICATE_HERE\n\nfor type in ecdsa ed25519 rsa\ndo\n\tpub=${SSH_DIR}/ssh_host_${type}_key.pub\n\tcerttemp=${SSH_DIR}/ssh_host_${type}_cert.tmp\n\tcert=${SSH_DIR}/ssh_host_${type}_cert\n\techo \"===================== VERIFY WITH =====================\"\n\tsha256sum ${pub} \| cut -d \" \" -f 1\n\techo \"===================== VERIFY WITH =====================\"\n\trm -f -- ${certtemp}\n\twget -nv --tries=1 --ca-certificate=server-tmp.cert \"https://{{SERVER IP}}/sign/$(cat ${pub})\" -O ${certtemp}\n\tmv -- ${certtemp} ${cert}\ndone\n\necho \"Installing static details...\"\n\nrm -f ${SSH_DIR}/ssh_user_ca.pub.tmp\ncat >${SSH_DIR}/ssh_user_ca.pub.tmp <<EOSSH_USER_CA_HERE\n{{SSH CA}}\nEOSSH_USER_CA_HERE\nmv ${SSH_DIR}/ssh_user_ca.pub.tmp ${SSH_DIR}/ssh_user_ca.pub\n\nrm -f ${SSH_DIR}/sshd_config.tmp\ncat >${SSH_DIR}/sshd_config.tmp <<EOSSHD_CONFIG_HERE\n{{SSHD CONFIG}}\nEOSSHD_CONFIG_HERE\nmv ${SSH_DIR}/sshd_config.tmp ${SSH_DIR}/sshd_config\n\nwget -nv --tries=1 --ca-certificate=server-tmp.cert \"https://{{SERVER IP}}/finish\" -O /dev/null\n\nrm -f server-tmp.cert $0\n\nsystemctl restart ssh\n\necho \"Done!\"\n" }, { "alpha_fraction": 0.6955017447471619, "alphanum_fraction": 0.7162629961967468, "avg_line_length": 25.272727966308594, "blob_id": "5ef7ba680884bc623b1450532d397ac53110b063", "content_id": "7dfc59c211d70fb61c211b835bcc187cf173c268", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 289, "license_type": "permissive", "max_line_length": 78, "num_lines": 11, "path": "/pull-upstream.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n# git clone [email protected]:sipb/homeworld-upstream.git\nif [ -e \"upstream\" ]\nthen\n\t(cd upstream && git pull)\nelse\n\tgit clone https://github.com/sipb/homeworld-upstream.git upstream\nfi\ncd upstream\nsha512sum --check ../SHA512SUM.UPSTREAM \|\| (echo \"CHECKSUM MISMATCH\" && false)\n" }, { "alpha_fraction": 0.6934426426887512, "alphanum_fraction": 0.7114754319190979, "avg_line_length": 28.047618865966797, "blob_id": "7311cf7293d3c74b4db2883f412aadb752f5c659", "content_id": "948637d93fec4d8cb2334c28886d1b924d3bd228", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 610, "license_type": "permissive", "max_line_length": 83, "num_lines": 21, "path": "/deployment/build-package.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\nVERSION=0.1.3\n\n# basic structure\nFPMOPT=\"-s dir -t deb\"\n# name and version\nFPMOPT=\"$FPMOPT -n hyades-services -v ${VERSION} --iteration 1\"\n# packager\nFPMOPT=\"$FPMOPT --maintainer '[email protected]'\"\n# metadata\n# TODO: better metadata\nFPMOPT=\"$FPMOPT --license MIT -a x86_64 --url https://sipb.mit.edu/\"\n# dependencies\nFPMOPT=\"$FPMOPT -d hyades-rkt -d hyades-etcd -d hyades-flannel -d hyades-hyperkube\"\n# get binary\nFPMOPT=\"$FPMOPT wrappers/=/usr/lib/hyades/ services/=/usr/lib/systemd/system/\"\n\nfpm --vendor 'MIT SIPB Hyades Project' $FPMOPT\ncp hyades-services_${VERSION}-1_amd64.deb ../binaries\n" }, { "alpha_fraction": 0.8339483141899109, "alphanum_fraction": 0.8339483141899109, "avg_line_length": 20.68000030517578, "blob_id": "6783d6ee6e58bc13acb5e03cff98a266d43c854f", "content_id": "a70c4a6b8d96a8b367da851ebf24952315b4da1c", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 542, "license_type": "permissive", "max_line_length": 36, "num_lines": 25, "path": "/deployment/wrappers/start-master.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\necho \"starting master services...\"\n\nsystemctl daemon-reload\n\nsystemctl start etcd\nsystemctl enable etcd\nsystemctl start flannel\nsystemctl enable flannel\nsystemctl start rkt-api\nsystemctl enable rkt-api\nsystemctl start kubelet\nsystemctl enable kubelet\nsystemctl start kube-proxy\nsystemctl enable kube-proxy\nsystemctl start apiserver\nsystemctl enable apiserver\nsystemctl start kube-ctrlmgr\nsystemctl enable kube-ctrlmgr\nsystemctl start kube-scheduler\nsystemctl enable kube-scheduler\n\necho \"services started and enabled!\"\n" }, { "alpha_fraction": 0.6654275059700012, "alphanum_fraction": 0.7100371718406677, "avg_line_length": 30.647058486938477, "blob_id": "8624fb6aefe29610d6f00f3f5f5ed4eaf63eea7b", "content_id": "dfbfd516b1233c363296d654d04418d35d2c4b9b", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 538, "license_type": "permissive", "max_line_length": 108, "num_lines": 17, "path": "/build-kubernernetes/package.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\n# basic structure\nFPMOPT=\"-s dir -t deb\"\n# name and version\nFPMOPT=\"$FPMOPT -n hyades-hyperkube -v 1.6.4 --iteration 1\"\n# packager\nFPMOPT=\"$FPMOPT --maintainer '[email protected]'\"\n# metadata\nFPMOPT=\"$FPMOPT --license APLv2 -a x86_64 --url https://kubernetes.io/\"\n# get binary\nFPMOPT=\"$FPMOPT --prefix /usr/bin --chdir go/src/k8s.io/kubernetes/_output/local/bin/linux/amd64/ hyperkube\"\n\nrm -f hyades-hyperkube_1.6.4-1_amd64.deb\nfpm --vendor 'MIT SIPB Hyades Project' $FPMOPT\ncp hyades-hyperkube_1.6.4-1_amd64.deb ../binaries\n" }, { "alpha_fraction": 0.6878504753112793, "alphanum_fraction": 0.7233644723892212, "avg_line_length": 32.4375, "blob_id": "d9bd94f2c89c9652fd4a1afadacc36fc1f26b746", "content_id": "d13d78e619c65988a4f98f11a63fe384318a5668", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 535, "license_type": "permissive", "max_line_length": 138, "num_lines": 16, "path": "/build-flannel/package.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\n# basic structure\nFPMOPT=\"-s dir -t deb\"\n# name and version\nFPMOPT=\"$FPMOPT -n hyades-flannel -v 0.7.1 --iteration 2\"\n# packager\nFPMOPT=\"$FPMOPT --maintainer '[email protected]'\"\n# metadata\nFPMOPT=\"$FPMOPT --license APLv2 -a x86_64 --url https://github.com/coreos/flannel/\"\n# get binary\nFPMOPT=\"$FPMOPT go/src/github.com/coreos/flannel/dist/flanneld=/usr/bin/flanneld 10-containernet.conf=/etc/rkt/net.d/10-containernet.conf\"\n\nfpm --vendor 'MIT SIPB Hyades Project' $FPMOPT\ncp hyades-flannel_0.7.1-2_amd64.deb ../binaries\n" }, { "alpha_fraction": 0.6579247713088989, "alphanum_fraction": 0.6864309906959534, "avg_line_length": 31.481481552124023, "blob_id": "1bfc2bab236fcd4974576766ef4b7113630a9dc3", "content_id": "288c57a65d39f3f02323a30f26421af0796fbb28", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 877, "license_type": "permissive", "max_line_length": 163, "num_lines": 27, "path": "/build-etcd/build.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\nVERSION=3.1.7\n\ncd $(dirname $0)\nHYBIN=$(pwd)/../binaries/\nmkdir -p ${HYBIN}\n\ntar -xf etcd-${VERSION}.tar.xz etcd-${VERSION}/\ncd etcd-${VERSION}\n./build\n../build-aci ${VERSION}\ncp bin/etcdctl ${HYBIN}/\ncp bin/etcd-${VERSION}-linux-amd64.aci ${HYBIN}/\nrm -f ${HYBIN}/etcd-current-linux-amd64.aci\nln -s etcd-${VERSION}-linux-amd64.aci ${HYBIN}/etcd-current-linux-amd64.aci\n\nFPMOPT=\"-s dir -t deb\"\nFPMOPT=\"$FPMOPT -n hyades-etcd -v ${VERSION} --iteration 1\"\nFPMOPT=\"$FPMOPT --maintainer '[email protected]'\"\nFPMOPT=\"$FPMOPT --license APLv2 -a x86_64 --url https://github.com/coreos/etcd/\"\nFPMOPT=\"$FPMOPT ${HYBIN}/etcd-${VERSION}-linux-amd64.aci=/usr/lib/hyades/ ${HYBIN}/etcd-current-linux-amd64.aci=/usr/lib/hyades/ ${HYBIN}/etcdctl=/usr/bin/etcdctl\"\n\nfpm --vendor 'MIT SIPB Hyades Project' $FPMOPT\ncp hyades-etcd_${VERSION}-1_amd64.deb ${HYBIN}/\n\necho \"etcd built!\"\n" }, { "alpha_fraction": 0.6759776473045349, "alphanum_fraction": 0.6983240246772766, "avg_line_length": 21.375, "blob_id": "d7a67c180f94ca720a7cad8541bfc0491376ae18", "content_id": "4ca03253c1a8cb5cc89e9639d6f80deccdc0763a", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 358, "license_type": "permissive", "max_line_length": 61, "num_lines": 16, "path": "/build-kubernernetes/build.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\ncd $(dirname $0)\nROOT=$(pwd)\nrm -rf go/\nmkdir -p go/src/k8s.io/kubernetes\ncd go/src/k8s.io/kubernetes\necho \"extracting...\"\ntar -xf ${ROOT}/kubernetes-src-v1.6.4.tar.xz\necho \"extracted!\"\nexport GOPATH=${ROOT}/go\nmake\ncp _output/local/bin/linux/amd64/kubectl ${ROOT}/../binaries/\ncd ${ROOT}\n./package.sh\necho \"built kubernetes binaries!\"\n" }, { "alpha_fraction": 0.6535112261772156, "alphanum_fraction": 0.6694459915161133, "avg_line_length": 36.74126052856445, "blob_id": "d814969e692a1cd26644d89e9b376480e288942d", "content_id": "b5a646b9891f9f6ca4e60bf9311055678b1b4924", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5397, "license_type": "permissive", "max_line_length": 153, "num_lines": 143, "path": "/admission/admit.py", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python3\nimport sys\nimport tempfile\nimport threading\nimport subprocess\nimport os\nimport socket\nimport hashlib\nimport base64\nimport http.server\nimport ssl\n\nif len(sys.argv) < 5:\n\tprint(\"Usage: admit.sh <hostname> <host_ca-key> <user_ca-pubkey> <sshd_config>\", file=sys.stderr)\n\tsys.exit(1)\n\nhostname, host_ca, user_ca, sshd_config = sys.argv[1:5]\n\nassert not host_ca.endswith(\".pub\")\nassert user_ca.endswith(\".pub\")\nassert os.path.basename(sshd_config) == \"sshd_config\"\n\nif not os.path.exists(host_ca):\n\tprint(\"Host certificate authority does not exist.\", file=sys.stderr)\n\tsys.exit(1)\nif not os.path.exists(user_ca):\n\tprint(\"User certificate authority does not exist.\", file=sys.stderr)\n\tsys.exit(1)\nif not os.path.exists(sshd_config):\n\tprint(\"sshd configuration does not exist.\", file=sys.stderr)\n\tsys.exit(1)\n\nwith open(os.path.join(os.path.dirname(__file__), \"setup.sh\"), \"rb\") as f:\n\tsetup_script = f.read()\n\ndef get_local_ip():\n\ts = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n\ttry:\n\t\ts.connect(('8.8.8.8', 1)) # doesn't actually send anything\n\t\treturn s.getsockname()[0]\n\tfinally:\n\t\ts.close()\n\nlocal_ip = get_local_ip()\nsecure_token = base64.b64encode(os.urandom(10)).rstrip(b\"=\")\n\ndef stop_soon(server):\n\tprint(\"will stop\")\n\tthreading.Timer(0.1, lambda: (server.shutdown(), print(\"perform stop\"))).start()\n\nclass InitialRequestHandler(http.server.BaseHTTPRequestHandler):\n\tdef do_GET(self):\n\t\tif self.client_address[0] != socket.gethostbyname(hostname):\n\t\t\tprint(\"Got connection from wrong client\", self.client_address)\n\t\t\tself.send_error(403)\n\t\t\treturn\n\t\tif self.path == \"/setup\":\n\t\t\tself.send_response(200)\n\t\t\tself.send_header(\"Content-type\", \"text/plain\")\n\t\t\tself.send_header(\"Content-length\", len(setup_script))\n\t\t\tself.send_header(\"Last-Modified\", self.date_time_string())\n\t\t\tself.end_headers()\n\t\t\tself.wfile.write(setup_script)\n\t\t\tstop_soon(self.server)\n\t\telse:\n\t\t\tself.send_error(404)\n\nclass SecondaryRequestHandler(http.server.BaseHTTPRequestHandler):\n\tdef do_GET(self):\n\t\tif self.client_address[0] != socket.gethostbyname(hostname):\n\t\t\tprint(\"Got connection from wrong client\", self.client_address)\n\t\t\tself.send_error(403)\n\t\t\treturn\n\t\tif self.path.startswith(\"/sign/\"):\n\t\t\tpubkey_to_sign = self.path[len(\"/sign/\"):].replace(\"%20\",\" \").encode() + b\"\\n\"\n\t\t\tprint(\"======================= VERIFY ========================\")\n\t\t\tprint(hashlib.sha256(pubkey_to_sign).hexdigest())\n\t\t\tprint(\"======================= VERIFY ========================\")\n\t\t\tif input(\"Correct? (y/n) \").strip()[:1].lower() == \"y\":\n\t\t\t\twith tempfile.NamedTemporaryFile(suffix=\".pub\") as pubkey:\n\t\t\t\t\tpubkey.write(pubkey_to_sign)\n\t\t\t\t\tpubkey.flush()\n\t\t\t\t\tsubprocess.check_call([\"ssh-keygen\", \"-s\", host_ca, \"-h\", \"-I\", \"hyades_host_\" + hostname, \"-Z\", hostname, \"-V\", \"-1w:+30w\", pubkey.name])\n\t\t\t\t\t# TODO: more secure tempfile handling\n\t\t\t\t\tcertname = pubkey.name[:-4] + \"-cert.pub\"\n\t\t\t\t\ttry:\n\t\t\t\t\t\twith open(certname, \"rb\") as cert:\n\t\t\t\t\t\t\tcertdata = cert.read()\n\t\t\t\t\tfinally:\n\t\t\t\t\t\tos.remove(certname)\n\t\t\t\tself.send_response(200)\n\t\t\t\tself.send_header(\"Content-type\", \"text/plain\")\n\t\t\t\tself.send_header(\"Content-length\", len(certdata))\n\t\t\t\tself.send_header(\"Last-Modified\", self.date_time_string())\n\t\t\t\tself.end_headers()\n\t\t\t\tself.wfile.write(certdata)\n\t\t\telse:\n\t\t\t\tself.send_error(403)\n\t\telif self.path == \"/finish\":\n\t\t\tself.send_response(200)\n\t\t\tself.send_header(\"Content-type\", \"text/plain\")\n\t\t\tself.send_header(\"Content-length\", len(\"stopping...\\n\"))\n\t\t\tself.send_header(\"Last-Modified\", self.date_time_string())\n\t\t\tself.end_headers()\n\t\t\tself.wfile.write(b\"stopping...\\n\")\n\t\t\tstop_soon(self.server)\n\t\telse:\n\t\t\tself.send_error(404)\n\nPORT=20557\n\nwith tempfile.NamedTemporaryFile() as privatekey:\n\twith tempfile.NamedTemporaryFile() as certificate:\n\t\tsubprocess.check_call([\"openssl\", \"genrsa\", \"-out\", privatekey.name, \"2048\"])\n\t\tsubprocess.check_call([\"openssl\", \"req\", \"-new\", \"-x509\", \"-key\", privatekey.name, \"-out\", certificate.name, \"-days\", \"1\", \"-subj\", \"/CN=\" + local_ip])\n\n\t\tsetup_script = setup_script.replace(b\"{{SERVER CERTIFICATE}}\", certificate.read())\n\t\tsetup_script = setup_script.replace(b\"{{SERVER IP}}\", (\"%s:%d\" % (local_ip, PORT)).encode())\n\t\twith open(user_ca, \"rb\") as f:\n\t\t\tsetup_script = setup_script.replace(b\"{{SSH CA}}\", f.read())\n\t\twith open(sshd_config, \"rb\") as f:\n\t\t\tsetup_script = setup_script.replace(b\"{{SSHD CONFIG}}\", f.read())\n\t\tassert setup_script.count(b\"_HERE\") == 6 # avoid confusion of terminators\n\t\tsetup_hash = hashlib.sha256(setup_script).hexdigest()\n\n\t\tprint(\"Run on the target system:\")\n\t\tprint(\" $ wget {ip}:{port}/setup\".format(ip=local_ip, port=PORT))\n\t\tprint(\" $ sha256sum setup\")\n\t\tprint(\" {hash} setup\".format(hash=setup_hash))\n\t\tprint(\" $ # after verifying hash\")\n\t\tprint(\" $ bash setup\")\n\t\tprint(\" # and compare the output to our output ...\")\n\n\t\t# first, without SSL, to let them download /setup\n\t\thttpd = http.server.HTTPServer(('', PORT), InitialRequestHandler)\n\t\thttpd.serve_forever(poll_interval=0.1)\n\t\thttpd.server_close()\n\t\tprint(\"/setup downloaded; moving to phase two\")\n\t\t# then again, with SSL, to receive the request from the script\n\t\thttpd = http.server.HTTPServer(('', PORT), SecondaryRequestHandler)\n\t\thttpd.socket = ssl.wrap_socket(httpd.socket, certfile=certificate.name, keyfile=privatekey.name, server_side=True, ciphers=\"TLSv1.2\")\n\t\thttpd.serve_forever(poll_interval=0.1)\n\t\thttpd.server_close()\n" }, { "alpha_fraction": 0.6555835604667664, "alphanum_fraction": 0.6629722714424133, "avg_line_length": 39.236488342285156, "blob_id": "0f64d9c9408368c691c6e70f1e6e9a532dd7bef2", "content_id": "570c31c9fee7e3dc8deca546424baaead1e77879", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5955, "license_type": "permissive", "max_line_length": 169, "num_lines": 148, "path": "/deployment/config/compile-config.py", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/usr/bin/env python3\n\n# takes in setup.conf and certificates.conf in the current directory\n# and spits out a folder cluster-config/ with the generated configuration\n\nimport os\nimport sys\n\nsetup = \"setup.conf\"\ncertificates_in = \"certificates.conf\"\ncertificates_out = \"certificates.list\"\noutput = \"cluster-config/\"\ncluster_config = \"cluster.conf\"\n\nif os.path.exists(output):\n\tfor file in os.listdir(output):\n\t\tos.remove(os.path.join(output, file))\nelse:\n\tos.mkdir(output)\n\ndef parse_setup(f):\n\tlines = [line.strip() for line in f if line.strip()]\n\tconfig = {}\n\tnodes = []\n\tfor line in lines:\n\t\tif line[0] == '#':\n\t\t\tcontinue\n\t\telif \"=\" in line:\n\t\t\tk, v = line.split(\"=\")\n\t\t\tconfig[k] = v\n\t\telif line[:7] in (\"master \", \"worker \"):\n\t\t\tkind, hostname, ip = line.split()\n\t\t\tnodes.append((kind == \"master\", hostname, ip))\n\t\telse:\n\t\t\traise Exception(\"Unrecognized line: %s\" % line)\n\treturn config, nodes\n\ndef generate_etcd_info(nodes):\n\tcluster = []\n\tendpoints = []\n\tfor is_master, hostname, ip in nodes:\n\t\tif not is_master: continue\n\t\tcluster.append(\"{hostname}=https://{ip}:2380\".format(hostname=hostname, ip=ip))\n\t\tendpoints.append(\"https://{ip}:2379\".format(ip=ip))\n\treturn \",\".join(cluster), \",\".join(endpoints)\n\nwith open(setup, \"r\") as f:\n\tconfig, nodes = parse_setup(f)\n\nmasters = [(hostname, ip) for ismaster, hostname, ip in nodes if ismaster]\nworkers = [(hostname, ip) for ismaster, hostname, ip in nodes if not ismaster]\n\nconfig[\"ETCD_CLUSTER\"], config[\"ETCD_ENDPOINTS\"] = generate_etcd_info(nodes)\n\nconfig[\"APISERVER_COUNT\"] = len(masters)\nprint(\"TODO: use more than one apiserver for direct requests\")\nconfig[\"APISERVER\"] = \"https://{ip}:443\".format(ip=masters[0][1])\n\nwith open(os.path.join(output, cluster_config), \"w\") as f:\n\tf.write(\"# generated from setup.conf automatically by compile-config.py\\n\")\n\tfor kv in sorted(config.items()):\n\t\tf.write(\"%s=%s\\n\" % kv)\n\nfor ismaster, hostname, ip in nodes:\n\twith open(os.path.join(output, \"node-%s.conf\" % hostname), \"w\") as f:\n\t\tf.write(\"\"\"# generated from setup.conf automatically by compile-config.py\nHOST_NODE={hostname}\nHOST_DNS={hostname}.{DOMAIN}\nHOST_IP={ip}\nSCHEDULE_WORK={schedule_work}\n\"\"\".format(hostname=hostname, ip=ip, DOMAIN=config['DOMAIN'],\n schedule_work=('false' if ismaster else 'true')))\n\nwith open(certificates_in, \"r\") as fin:\n\twith open(os.path.join(output, certificates_out), \"w\") as fout:\n\t\tfout.write(\"# generated from certificates.conf and setup.conf automatically by compile-config.py\\n\")\n\t\tnodelists = {\"master\": masters, \"worker\": workers, \"all\": masters + workers}\n\t\tfor line in fin:\n\t\t\tline = line.strip()\n\t\t\tif not line or line[0] == '#':\n\t\t\t\tfout.write(\"\\n\")\n\t\t\telif line.startswith(\"authority \") or line.startswith(\"shared-key \"):\n\t\t\t\tfout.write(line + \"\\n\")\n\t\t\telse:\n\t\t\t\tfout.write(\"# \" + line + \"\\n\")\n\t\t\t\tcomponents = line.split(\" \")\n\t\t\t\tneeds_default_names = components[0] == \"certificate\"\n\t\t\t\tnodes_to_include = nodelists[components[1]] # must be master, worker, all\n\t\t\t\tfor hostname, ip in nodes_to_include:\n\t\t\t\t\tncomp = components[:]\n\t\t\t\t\tncomp[1] = \"%s.%s\" % (hostname, config[\"DOMAIN\"])\n\t\t\t\t\tif needs_default_names:\n\t\t\t\t\t\tncomp.append(\"ip:%s\" % ip)\n\t\t\t\t\t\tncomp.append(\"dns:%s\" % hostname)\n\t\t\t\t\t\tncomp.append(\"dns:%s.%s\" % (hostname, config[\"DOMAIN\"]))\n\t\t\t\t\tfout.write(\" \".join(ncomp) + \"\\n\")\n\nwith open(os.path.join(output, \"spin-up-all.sh\"), \"w\") as f:\n\tf.write(\"#!/bin/bash\\nset -e -u\\n\")\n\tf.write(\"# generated from setup.conf automatically by compile-config.py\\n\")\n\tf.write(\"cd $(dirname $0)\\n\")\n\tfor ismaster, hostname, ip in nodes:\n\t\tf.write(\"./spin-up.sh {host}\\n\".format(host=hostname))\n\tf.write(\"echo 'spun up all nodes!'\\n\")\n\nos.chmod(os.path.join(output, \"spin-up-all.sh\"), 0o755)\n\nwith open(os.path.join(output, \"spin-up.sh\"), \"w\") as f:\n\tf.write(\"#!/bin/bash\\nset -e -u\\n\")\n\tf.write(\"# generated from setup.conf automatically by compile-config.py\\n\")\n\tf.write(\"cd $(dirname $0)\\n\")\n\tf.write(\"HOST=$1\\n\")\n\tf.write('if [ ! -e node-$HOST.conf ]; then echo \"could not find node config for $HOST\"; exit 1; fi\\n')\n\tf.write(\"echo \\\"uploading to $HOST...\\\"\\n\")\n\tf.write(\"scp node-$HOST.conf root@$HOST.{domain}:/etc/hyades/local.conf\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"scp cluster.conf root@$HOST.{domain}:/etc/hyades/cluster.conf\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"echo \\\"uploaded to $HOST!\\\"\\n\")\n\nos.chmod(os.path.join(output, \"spin-up.sh\"), 0o755)\n\nwith open(os.path.join(output, \"pkg-install-all.sh\"), \"w\") as f:\n\tf.write(\"#!/bin/bash\\nset -e -u\\n\")\n\tf.write(\"# generated from setup.conf automatically by compile-config.py\\n\")\n\tf.write(\"cd $(dirname $0)\\n\")\n\tfor ismaster, hostname, ip in nodes:\n\t\tf.write(\"./pkg-install.sh {host} $\\n\".format(host=hostname))\n\tf.write(\"echo 'deployed to all nodes!'\\n\")\n\nos.chmod(os.path.join(output, \"pkg-install-all.sh\"), 0o755)\n\nwith open(os.path.join(output, \"pkg-install.sh\"), \"w\") as f:\n\tf.write(\"#!/bin/bash\\nset -e -u\\n\")\n\tf.write(\"# generated from setup.conf automatically by compile-config.py\\n\")\n\tf.write(\"cd $(dirname $0)\\n\")\n\tf.write(\"HOST=$1\\n\")\n\tf.write(\"shift 1\\n\")\n\tf.write(\"echo \\\"deploying to $HOST...\\\"\\n\")\n\tf.write(\"ssh root@$HOST.{domain} 'rm -rf /root/staging-pkg && mkdir /root/staging-pkg && mkdir -p /usr/lib/hyades/images/'\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"scp $ root@$HOST.{domain}:/root/staging-pkg/\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"ssh root@$HOST.{domain} 'if [ -e /root/staging-pkg/.deb ]; then dpkg -i /root/staging-pkg/.deb; fi'\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"ssh root@$HOST.{domain} 'if [ -e /root/staging-pkg/.aci ]; then cp -f /root/staging-pkg/.aci /usr/lib/hyades/images/; fi'\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"ssh root@$HOST.{domain} 'rm -rf /root/staging-pkg'\\n\".format(domain=config[\"DOMAIN\"]))\n\tf.write(\"echo \\\"deployed to $HOST!\\\"\\n\")\n\tf.write(\"echo 'TODO: START SYSTEMD SERVICES'\\n\")\n\nos.chmod(os.path.join(output, \"pkg-install.sh\"), 0o755)\n\nprint(\"Generated!\")\n" }, { "alpha_fraction": 0.5991561412811279, "alphanum_fraction": 0.7257384061813354, "avg_line_length": 17.230770111083984, "blob_id": "68a54f5729fd63954ff4e3aa71f3635e329efcc1", "content_id": "b5fb6549affa7a81551ae643e6ba7bfbd8c3c98f", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 237, "license_type": "permissive", "max_line_length": 93, "num_lines": 13, "path": "/auth/build.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e\n\ncd $(dirname $0)\n\nrm -rf goroot\nmkdir goroot\n(cd goroot && tar -xf ../golang-x-crypto-5ef0053f77724838734b6945dd364d3847e5de1d.tar.xz src)\nGOPATH=$(pwd)/goroot go build hyauth.go\n\n./package.sh\n\necho \"Build complete!\"\n" }, { "alpha_fraction": 0.5992031693458557, "alphanum_fraction": 0.6302788853645325, "avg_line_length": 20.27118682861328, "blob_id": "ef236b001d50e5354362f036a369f581b18c98ea", "content_id": "5d68baeee98a2a54b95d21216e9d615172339062", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 1255, "license_type": "permissive", "max_line_length": 119, "num_lines": 59, "path": "/auth/deploy.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\n\nif [ \"$1\" = \"\" -o \"$2\" = \"\" -o \"$3\" = \"\" -o \"$4\" = \"\" ]\nthen\n\techo \"Usage: $0 <host> <keytab> <acl> <ca> [package]\" 1>&2\n\techo \" NOTE: The keytab is not automatically rotated!\" 1>&2\n\texit 1\nfi\n\nset -e -u\n\nHOST=$1\nKEYTAB=$2\nACL=$3\nCA=$4\nPACKAGE=${5:-$(dirname $0)/hyades-authserver_0.1.4-1_amd64.deb}\n\nif [ ! -e $KEYTAB ]\nthen\n\techo \"Could not find keytab.\" 1>&2\n\texit 1\nfi\n\nif [ ! -e $ACL ]\nthen\n\techo \"Could not find acl.\" 1>&2\n\texit 1\nfi\n\nif [ ! -e $CA -o ! -e $CA.pub ]\nthen\n\techo \"Could not find ca and ca.pub.\" 1>&2\n\texit 1\nfi\n\nif [ ! -e $PACKAGE ]\nthen\n\techo \"Could not find package.\" 1>&2\n\texit 1\nfi\n\nif ssh root@${HOST} test ! -e /etc/krb5.keytab\nthen\n\techo \"Uploading keytab...\"\n\tscp $KEYTAB root@${HOST}:/etc/krb5.keytab\nelse\n\techo \"Keytab already exists -- skipping.\"\nfi\n\nscp ${PACKAGE} root@${HOST}:/root/hyauth-pkg-install.deb\nscp ${ACL} root@${HOST}:/root/.k5login\nssh root@${HOST} 'apt-get install krb5-user && dpkg -i /root/hyauth-pkg-install.deb && rm /root/hyauth-pkg-install.deb'\nscp ${ACL} root@${HOST}:/home/kauth/.k5login\nscp ${CA} root@${HOST}:/home/kauth/ca_key\nscp ${CA}.pub root@${HOST}:/home/kauth/ca_key.pub\nssh root@${HOST} chown kauth /home/kauth/ca_key\nssh root@${HOST} systemctl restart ssh\n\necho \"Finished!\"\n" }, { "alpha_fraction": 0.7313167452812195, "alphanum_fraction": 0.7313167452812195, "avg_line_length": 30.22222137451172, "blob_id": "e429b8270299f45013855959040d677e9273cf5c", "content_id": "e6f14b1648ad1496e92631f976ca53971a077bf0", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 562, "license_type": "permissive", "max_line_length": 123, "num_lines": 18, "path": "/deployment/wrappers/launch-flannel.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\nsource /etc/hyades/cluster.conf\nsource /etc/hyades/local.conf\n\n# allow verification of etcd certs\nFLANOPT=\"--etcd-cafile /etc/hyades/certs/kube/etcd-ca.pem\"\n# authenticate to etcd servers\nFLANOPT=\"$FLANOPT --etcd-certfile /etc/hyades/certs/kube/etcd-cert.pem --etcd-keyfile /etc/hyades/certs/kube/local-key.pem\"\n# endpoints\nFLANOPT=\"$FLANOPT --etcd-endpoints ${ETCD_ENDPOINTS}\"\n\nFLANOPT=\"$FLANOPT --iface ${HOST_IP}\" # the IP\nFLANOPT=\"$FLANOPT --ip-masq\"\nFLANOPT=\"$FLANOPT --public-ip ${HOST_IP}\" # the IP\n\nexec /usr/bin/flanneld $FLANOPT\n" }, { "alpha_fraction": 0.7309941649436951, "alphanum_fraction": 0.7309941649436951, "avg_line_length": 18, "blob_id": "b15bebe8dae1b127c6a6ffbf423fdbbfd4fb3ee5", "content_id": "6bfcc0bd6c85793e16e1746e0bc14c09fefbf206", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 171, "license_type": "permissive", "max_line_length": 46, "num_lines": 9, "path": "/deployment/wrappers/launch-scheduler.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\n# use known apiserver\nSRVOPT=\"--kubeconfig=/etc/hyades/kubeconfig\"\n\nSRVOPT=\"$SRVOPT --leader-elect\"\n\nexec /usr/bin/hyperkube kube-scheduler $SRVOPT\n" }, { "alpha_fraction": 0.5797101259231567, "alphanum_fraction": 0.7529930472373962, "avg_line_length": 32.0625, "blob_id": "022551a069ac4757a985974ec0508f755da2c16d", "content_id": "6bf2d0575daa67c2c7e170dd4d83796ec18eb7cf", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 1587, "license_type": "permissive", "max_line_length": 149, "num_lines": 48, "path": "/build-rkt/build.sh", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "#!/bin/bash\nset -e -u\n\ncd $(dirname $0)\n\nrm -rf rkt-1.27.0/\ntar -xf rkt-1.27.0.tar.xz rkt-1.27.0/\n\npatch -p0 <rkt.patch\n\nif gcc --version \| grep -q 'Debian 4.9'\nthen\n\trm rkt-1.27.0/stage1/usr_from_kvm/kernel/patches/0002-for-debian-gcc.patch\nfi\n\nsha512sum --check <<EOF\n85adf3715cba4a457efea8359ebed34413ac63ee58fe920c5713501dec1e727e167416e9d67a9e2d9430aa9f3a53ad0ac26a4f749984bc5a3f3c37ac504f75de linux-4.9.2.tar.xz\n10e3fcd515b746be2af55636a6dd9334706cc21ab2bb8b2ba38fe342ca51b072890fd1ae2cd8777006036b0a08122a621769cb5903ab16cfbdcc47c9444aa208 qemu-2.8.1.1.tar.xz\nEOF\n\ncp coreos_restructured.cpio.gz rkt-1.27.0/coreos_production_pxe_image.cpio.gz\nmkdir -p rkt-1.27.0/build-rkt-1.27.0/tmp/usr_from_kvm/kernel/\ncp linux-4.9.2.tar.xz rkt-1.27.0/build-rkt-1.27.0/tmp/usr_from_kvm/kernel/linux-4.9.2.tar.xz\nmkdir -p rkt-1.27.0/build-rkt-1.27.0/tmp/usr_from_kvm/qemu/\ncp qemu-2.8.1.1.tar.xz rkt-1.27.0/build-rkt-1.27.0/tmp/usr_from_kvm/qemu/qemu-2.8.1.1.tar.xz\ncd rkt-1.27.0/\n\n./autogen.sh\n\n./configure \\\n\t--disable-tpm --prefix=/usr \\\n\t--with-stage1-flavors=coreos,kvm \\\n\t--with-stage1-default-flavor=kvm \\\n\t--with-coreos-local-pxe-image-path=coreos_production_pxe_image.cpio.gz \\\n\t--with-coreos-local-pxe-image-systemd-version=v231 \\\n\t--with-stage1-default-images-directory=/usr/lib/rkt/stage1-images \\\n\t--with-stage1-default-location=/usr/lib/rkt/stage1-images/stage1-kvm.aci\n\n# make manpages\n# make bash-completion\nmake -j4\n\ncd ..\n\nBUILDDIR=rkt-1.27.0/build-rkt-1.27.0/\nBUILDDIR=${BUILDDIR} ./build-pkgs.sh 1.27.0\n\ncp ${BUILDDIR}/target/bin/hyades-rkt_1.27.0-1_amd64.deb ../binaries/\n" }, { "alpha_fraction": 0.7415770888328552, "alphanum_fraction": 0.7476702332496643, "avg_line_length": 37.75, "blob_id": "8d962047d8d2750bf95b156301b3c8ae81441fbd", "content_id": "ddb321321f04108ac9c315ea472d0793c018a7b8", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 2790, "license_type": "permissive", "max_line_length": 132, "num_lines": 72, "path": "/deploy.md", "repo_name": "andersk/homeworld", "src_encoding": "UTF-8", "text": "# How to deploy a Homeworld cluster\n\n## Building Software\n\n * Install go, acbuild, and ruby. See trust.txt for signatures.\n * Install fpm from the gems in build-rkt.\n * Build hyauth, etcd, and flannel with the ./build.sh scripts.\n * Make sure you have these installed:\n git build-essential zlib1g-dev libxml2 libxml2-dev libreadline-dev\n libssl-dev zlibc automake squashfs-tools libacl1-dev libsystemd-dev\n libcap-dev libglib2.0-dev libpcre3-dev libpcrecpp0 libpixman-1-dev\n pkg-config realpath flex bison\n * For rkt, run ./build.sh.\n You may need to tweak the removal of stage1/usr_from_kvm/kernel/patches/0002-for-debian-gcc.patch if you get '-no-pie' problems.\n * For kubernetes, run ./build.sh\n You may need to allocate additional memory to your build environment.\n * ./build-package.sh on deployment\n\n## Set up the authentication server\n\n * Request a keytab from accounts@, if necessary.\n * Provision yourself a Debian Stretch machine. Choose SSH Server.\n * Establish SSH access somehow (i.e. ssh keys)\n * Generate ssh user CA locally; save it somewhere safe.\n * Rotate the keytab locally (k5srvutil -f <keytab> change); save it somewhere safe.\n * Run auth/deploy.sh on <host> <keytab> auth-login <user-ca>\n\n * Run req-cert and see if it works.\n\nTODO: improve cryptographic strength of keytab (see note on sipb page)\n\n## Initial server setup\n\n * Provision yourself new Debian Stretch machines. Choose SSH Server only.\n * Launch an admission server from a trusted machine. Copy up the relevant files.\n * Admit the server according to the instructions. Verify all hashes carefully.\n * Make sure to add the CA key for the server into your known_hosts.\n\n @cert-authority eggs-benedict.mit.edu,huevos-rancheros.mit.edu,[...] ssh-rsa ...\n\n * Confirm that you can ssh into the server as root.\n\n## Configuration and SSL setup and package installation\n\n * Install openssl, curl, and ca-certificates on each server\n * Modify config/setup.conf\n * Run ./compile-config.py\n * Run ./compile-certificates cluster-config/certificates.list <secrets-directory>\n * Run authority-gen.sh\n * Run authority-upload.sh\n * Run private-gen.sh\n * Run shared-gen.sh\n * Run shared-upload.sh\n * Run certificate-gen-csrs.sh\n * Run certificate-sign-csrs.sh\n * Run certificate-upload-certs.sh\n * Run spin-up-all.sh\n * Run pkg-install-all.sh on the latest packages and etcd-current-linux-amd64.aci\n\tDO NOT INCLUDE hyades-authserver IN THIS INSTALLATION!\n\n## Starting everything\n\n * Manually start etcd on each master node\n * Run init-flannel.sh on one master node\n * Run start-master.sh on all master nodes\n * Run start-worker.sh on all worker nodes\n\n * Run kubectl and make sure things work (you may need to generate certs for this)\n\n## Core cluster services\n\n * kubectl create -f dns-addon.yml\n" } ]	22
gilesgardam/jagwa	https://github.com/gilesgardam/jagwa	21926faf6dd4d087aaef75c26912d7e4e9cd8181	908c01c2f49b880569d92d595a28f0b1934129eb	d5fd8f2694222280039e1f482109e4c23e7f9b9f	refs/heads/master	2021-01-24T06:13:10.995580	2012-07-23T11:40:33	2012-07-23T11:40:33	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.7307692170143127, "alphanum_fraction": 0.7307692170143127, "avg_line_length": 12.25, "blob_id": "234b8700874f0aa96a8ebcaf037499316f0f0d41", "content_id": "9eef08d6a5f2fe952e4b2c509133e991bad9f142", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 52, "license_type": "no_license", "max_line_length": 39, "num_lines": 4, "path": "/README.md", "repo_name": "gilesgardam/jagwa", "src_encoding": "UTF-8", "text": "jagwa\n=====\n\nJust another Graphviz wrapper, alright?" }, { "alpha_fraction": 0.4964788854122162, "alphanum_fraction": 0.5088028311729431, "avg_line_length": 21.719999313354492, "blob_id": "c6a2b1be0020534d1923286bbee8671c96137814", "content_id": "b23f90ecb05150a83c70b8d9eae62ad7bd402dc3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 568, "license_type": "no_license", "max_line_length": 60, "num_lines": 25, "path": "/demo1.py", "repo_name": "gilesgardam/jagwa", "src_encoding": "UTF-8", "text": "from jagwa import dot_graph\n# cube graph demo\nnodes = {}\nedges = set()\n\nk = 4\nfor i in xrange(2 ** k):\n bin_str = ('{:0' + str(k) + 'b}').format(i)\n nodes[i] = {\n 'name': bin_str,\n 'shape': 'circle',\n 'height': '0.4',\n 'fixedsize': 'true',\n 'fontsize': '8'\n }\n\nfor u in nodes:\n for v in nodes:\n # check if they differ at precisely one bit position\n # (warning: crazy bit hacks)\n delta = u ^ v\n if delta and not delta & (delta - 1):\n edges.add((u, v))\n\nprint dot_graph(nodes, edges)\n" }, { "alpha_fraction": 0.590673565864563, "alphanum_fraction": 0.6010362505912781, "avg_line_length": 15.083333015441895, "blob_id": "d9d8c4e5ae7e54627637a704a8617f14cb7aa688", "content_id": "4ede502e81284e1cce8e6954c3a60f19191be7d2", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 193, "license_type": "no_license", "max_line_length": 33, "num_lines": 12, "path": "/demo2.py", "repo_name": "gilesgardam/jagwa", "src_encoding": "UTF-8", "text": "from jagwa import dot_graph\n# cycle graph demo\nnodes = {}\nedges = set()\n\nk = 8\n\nfor i in xrange(k):\n nodes[i] = {'shape': 'point'}\n edges.add((i, (i+1)%k))\n\nprint dot_graph(nodes, edges)\n" }, { "alpha_fraction": 0.5438596606254578, "alphanum_fraction": 0.5614035129547119, "avg_line_length": 18, "blob_id": "9514f104b82e70586a89e0eefab5db1a6cee7094", "content_id": "dbd82cfab05d173670cec9dfd170b70bbc4a53ac", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Makefile", "length_bytes": 114, "license_type": "no_license", "max_line_length": 30, "num_lines": 6, "path": "/Makefile", "repo_name": "gilesgardam/jagwa", "src_encoding": "UTF-8", "text": "all: demo1.png demo2.png\n%.png: %.py\n\tpython $.py > $.dot\n\tneato -T png -o $.png $.dot\nclean:\n\trm .dot .png\n" }, { "alpha_fraction": 0.5768081545829773, "alphanum_fraction": 0.5803945064544678, "avg_line_length": 31.80392074584961, "blob_id": "beb2c97731dc4fc299562b38bd5f1a60f40fbbf3", "content_id": "b9466b48151d7fc518e00723746b99e704d33e96", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1673, "license_type": "no_license", "max_line_length": 91, "num_lines": 51, "path": "/jagwa.py", "repo_name": "gilesgardam/jagwa", "src_encoding": "UTF-8", "text": "import doctest\ndef dot_graph(nodes, edges, multigraph=False):\n \"\"\"\n Return the graph as a DOT file format string.\n\n Think of this as a very thin wrapper around the actual DOT output.\n Each 'node' can be an arbitrary (hashable) Python objects.\n Nodes is a dict that maps each 'node' to attribute dicts.\n Edges is an iterable of pairs of 'nodes' (or other collections of size 2).\n\n If you want the Python object you use as a node to have a nice name\n in the output file for readability, set the attribute 'name'.\n (Note that this is different from the 'label' used in the image.)\n\n >>> nodes = {'gday': {'shape': 'box', 'name': 'hello', 'label': 'greeting'}}\n >>> edges = [['gday', 'world']]\n >>> print dot_graph(nodes, edges)\n graph G {\n hello [shape=box,label=greeting];\n \"'world'\" -- hello;\n }\n \"\"\"\n\n if not multigraph:\n # remove duplicate edges\n edges = set(map(frozenset, edges))\n\n lines = ['']\n for node in sorted(nodes.keys()):\n att = nodes[node]\n name = node_name(node, nodes)\n att_str = ','.join(\"%s=%s\" % item for item in att.iteritems() if item[0] != 'name')\n lines.append(\"%s [%s];\" % (name, att_str))\n\n for edge in edges:\n e = list(edge)\n s = node_name(e[0], nodes)\n t = node_name(e[-1], nodes) # -1 not 1 so it works for loop edges\n lines.append(\"%s -- %s;\" % (s, t))\n\n return \"graph G {%s\\n}\" % '\\n '.join(lines)\n\ndef node_name(node, nodes):\n try:\n return nodes[node]['name']\n except KeyError:\n return \"\\\"%s\\\"\" % repr(node)\n\nif __name__ == '__main__':\n import doctest\n doctest.testmod()\n" } ]	5
TrinaDutta95/BotResponse_sentiment	https://github.com/TrinaDutta95/BotResponse_sentiment	bfeca0c08ec088d4803abaa775f0f13df5bcfbc0	3ed57573f5b5749015e6f38d0f7fd1fd76ad7ba0	9528853c886e0faae76056d53b90bb502c39dbab	refs/heads/master	2023-05-08T07:37:29.170870	2021-05-26T21:24:08	2021-05-26T21:24:08	371,166,627	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.6761904954910278, "alphanum_fraction": 0.723809540271759, "avg_line_length": 25.25, "blob_id": "2d70ea3183de0f568156c7d9b5cdba7038ea1259", "content_id": "6ab6557e25f6e38d79f8baa498211317c0b6ebef", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 105, "license_type": "no_license", "max_line_length": 49, "num_lines": 4, "path": "/setting.py", "repo_name": "TrinaDutta95/BotResponse_sentiment", "src_encoding": "UTF-8", "text": "import nltk\nnltk.download()\n#nltk.download('nps_chat')\n#posts = nltk.corpus.nps_chat.xml_posts()[:10000]\n" }, { "alpha_fraction": 0.6553672552108765, "alphanum_fraction": 0.6553672552108765, "avg_line_length": 19.823530197143555, "blob_id": "affcb9262dcfc8272a523865c3adbd2cd751dfd8", "content_id": "cf690e3455975e8e5be47db8e8cd12a0f0398127", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 354, "license_type": "no_license", "max_line_length": 43, "num_lines": 17, "path": "/web_flask.py", "repo_name": "TrinaDutta95/BotResponse_sentiment", "src_encoding": "UTF-8", "text": "import bot_response as br\nfrom flask import Flask, request\nfrom flask import jsonify\n\napp = Flask(__name__)\n\n\[email protected](\"/\", methods=[\"GET\"])\ndef generate_response():\n text = request.args.get(\"user_res\")\n print(text)\n bot_res = br.sentence_processing(text)\n return jsonify(additional_line=bot_res)\n\n\nif __name__ == \"__main__\":\n app.run()\n" }, { "alpha_fraction": 0.6431604027748108, "alphanum_fraction": 0.647169828414917, "avg_line_length": 28.44444465637207, "blob_id": "ba53ac6bd89d5b182c0d9f67a8d627c779842835", "content_id": "a4f434261d94e1bfe659c63257739a2bf90154bf", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4256, "license_type": "no_license", "max_line_length": 117, "num_lines": 144, "path": "/bot_response.py", "repo_name": "TrinaDutta95/BotResponse_sentiment", "src_encoding": "UTF-8", "text": "import string\nfrom collections import Counter\nimport nltk\nfrom nltk.tokenize import word_tokenize\nfrom nltk.corpus import stopwords\nfrom nltk.sentiment.vader import SentimentIntensityAnalyzer\nimport random\n\n\n# import matplotlib.pyplot as plt\n\n# reading text from a file and converting them to lower case with removal of punctuations\n\n\ndef read_line(text):\n lower_case = text.lower()\n cleaned_text = lower_case.translate(str.maketrans('', '', string.punctuation))\n return cleaned_text\n\n\n# tokenizing the text\n\n\ndef preprocess_line(cleaned_text):\n tokenized_words = word_tokenize(cleaned_text, \"english\")\n\n # stop_words addition\n final_words = []\n for word in tokenized_words:\n if word not in stopwords.words('english'):\n final_words.append(word)\n\n return final_words\n\n\n# identifying emotion\n\n\ndef emotion_detect(sentences):\n emotion_list = []\n with open('emotions.txt', 'r') as file:\n for line in file:\n clear_line = line.replace(\"\\n\", '').replace(\",\", '').replace(\"'\", '').strip()\n word, emotion = clear_line.split(':')\n\n if word in sentences:\n emotion_list.append(emotion)\n return emotion_list\n\n\ndef sentiment_analyse(sentiment_text):\n score = SentimentIntensityAnalyzer().polarity_scores(sentiment_text)\n # print(score)\n neg = score['neg']\n pos = score['pos']\n if neg > pos:\n sentiment = \"negative\"\n elif pos > neg:\n sentiment = \"positive\"\n else:\n sentiment = \"neutral\"\n\n return sentiment\n\n\n# type of text analysis\nposts = nltk.corpus.nps_chat.xml_posts()[:10000]\n\n\ndef dialogue_act_features(post):\n features = {}\n for word in word_tokenize(post):\n features['contains({})'.format(word.lower())] = True\n return features\n\n\ndef bot_response(sentiment):\n pos = [\"Well said.\", \"You are thinking in the right direction.\", \"Very well thought.\", \"That’s great.\",\n \"It sounds like you really know what the problems are.\", \"Nice, let’s talk about that a little.\",\n \"It seems like you’ve been thinking about this a lot.\"]\n neu = [\"That’s okay.\", \"Okay!\", \"Okay, let’s keep going.\", \"That’s really understandable. \"]\n neg = [\"I understand how you feel.\", \"I see how that can be frustrating.\", \"That must be really frustrating.\"\n , \"This is really bothering you.\"]\n if sentiment == \"negative\":\n return random.choice(neg)\n elif sentiment == \"positive\":\n return random.choice(pos)\n else:\n return random.choice(neu)\n\n\n\"\"\"\n# Plotting the emotions on the graph\n\nfig, ax1 = plt.subplots()\nax1.bar(w.keys(), w.values())\nfig.autofmt_xdate()\nplt.savefig('graph.png')\nplt.show()\n\"\"\"\n\n\n# processing sentence to get emotions/sentiments and bots response\n\n\ndef sentence_processing(text):\n cleaned_text = read_line(text)\n # count number of words in response\n words = cleaned_text.split()\n word_len = len(words)\n if word_len <= 25:\n final_words = preprocess_line(cleaned_text)\n # print(emotion_detect(final_words))\n w = Counter(emotion_detect(final_words))\n # print(w)\n # sentiment analysis\n sentiment = sentiment_analyse(cleaned_text)\n bot_res1 = bot_response(sentiment)\n else:\n long_res = [\"It sounds like you really know what the problems are.\", \"Nice, let’s talk about that a little.\",\n \"It seems like you’ve been thinking about this a lot.\",\n \"Struggling with communication is difficult\"]\n bot_res1 = random.choice(long_res)\n\n # classification of type of sentence\n featuresets = [(dialogue_act_features(post.text), post.get('class')) for post in posts]\n size = int(len(featuresets) * 0.1)\n train_set, test_set = featuresets[size:], featuresets[:size]\n classifier = nltk.NaiveBayesClassifier.train(train_set)\n # print(nltk.classify.accuracy(classifier, test_set))\n sentence_type = classifier.classify(dialogue_act_features(text))\n bot_res2 = \"\"\n if sentence_type == 'whQuestion':\n bot_res2 = \"Let's focus more on the session.\"\n\n res = bot_res1 + bot_res2\n return res\n\n\n\"\"\"\nif __name__==\"__main__\":\n text = input(\"User: \")\n print(sentence_processing(text))\n \"\"\"\n" } ]	3
aditya-malte/SemEval-SentiMix	https://github.com/aditya-malte/SemEval-SentiMix	f094a3fb06a15f7998055ce6d8270adcb4452b21	afde20b166b4a21aa054e80f4d3955a2461c5f91	74df0eb2a885f9c09280910117eb47fb14985e0f	refs/heads/master	2022-11-17T03:26:33.185479	2020-07-21T05:46:33	2020-07-21T05:46:33	259,366,271	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.572746992111206, "alphanum_fraction": 0.5746471285820007, "avg_line_length": 29.44628143310547, "blob_id": "b110b04e5cd24c2dab600cfccb067afdc9d9373d", "content_id": "16201763c81a4a2deb31954427c63a6cb8045a2a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3688, "license_type": "no_license", "max_line_length": 128, "num_lines": 121, "path": "/utils_text.py", "repo_name": "aditya-malte/SemEval-SentiMix", "src_encoding": "UTF-8", "text": "import requests\nimport re\nimport string\ntry:\n import emoji\nexcept:\n print(\"Error importing emoji library: demojisation may not work\")\nclass PreProcess:\n def __init__(self, remove_punct=False, sep_url=True, remove_url=True,\n remove_hashtag=False,remove_usertag=False,remove_no=True, lowercase=False,\n convert_emoji=True, solve_gaps=True, remove_newline=True):\n self.remove_punct = remove_punct\n self.sep_url = sep_url\n self.remove_url = remove_url\n self.remove_hashtag = remove_hashtag\n self.remove_usertag = remove_usertag\n self.remove_no = remove_no\n self.lowercase = lowercase\n self.remove_newline = remove_newline\n self.convert_emoji = convert_emoji\n self.solve_gaps = solve_gaps\n if(self.convert_emoji):\n import emoji\n\n def preprocess(self, text=\"\"):\n try:\n processed_text = text[:]\n\n #separate the external url \n if(self.sep_url):\n url = None\n processed_text, _, url = text.partition(\"…\")\n if(url!=''):\n url = \"\".join(url.split())\n url = \"https://t.co/\" + url.rsplit('/', 1)[-1]\n else:\n url=None\n\n #remove urls in text\n if(self.remove_url):\n processed_text = re.sub(\"http\\S+\", \"\", processed_text, flags=re.MULTILINE)\n \n #remove all newlines\n if(self.remove_newline):\n processed_text = processed_text.replace(\"\\n\", \" \")\n\n #handle hashtags and usernames\n if(self.remove_hashtag):\n processed_text = re.sub(\"#\", \"\", processed_text)\n if(self.remove_usertag):\n processed_text = re.sub(\"@\", \"\", processed_text)\n\n\n\n #remove repeated punctuations\n if(self.remove_punct):\n for punctuation in string.punctuation:\n while True:\n replaced = processed_text.replace(punctuation * 2, punctuation)\n if replaced == processed_text:\n break\n processed_text = replaced\n\n\n\n #tokenize punctuations\n \"\"\"\n for punctuation in string.punctuation:\n processed_text = processed_text.replace(punctuation, \" \" + punctuation+ \" \")\n \"\"\" \n\n\n #remove numbers\n if(self.remove_no):\n processed_text = re.sub(\"\\d+\", \"\", processed_text)\n\n\n\n #convert emojis\n if(self.convert_emoji):\n processed_text = emoji.demojize(processed_text)\n\n\n\n #convert multiple whitespaces to single\n #detect newline and replace with random string\n #processed_text = processed_text.replace(\"\\n\", \"QSDWDSrfefafawecsd\")\n processed_text = re.sub(\"\\s\\s+\", \" \", processed_text)\n #replace again with newline\n #processed_text = processed_text.replace(\"QSDWDSrfefafawecsd\", \"\\n\")\n\n #Convert to lower case\n if(self.lowercase): \n processed_text = processed_text.lower()\n\n if(processed_text == \"\"):\n processed_text = \"blank\"\n \n #breaks the lang labels:\n if(self.solve_gaps):\n processed_text = processed_text.replace(\"@ \", \"@\").replace(\" _ \", \"_\")\n \n if self.sep_url:\n return (processed_text, url)\n else:\n return processed_text\n except Exception as e:\n print(\"Error at: \", text, \"--\",e)\n\n\ndef clean_for_transliterate(text):\n text = re.sub(r\"[#~]\", \"\", text)\n #add for !!!!!! -> !\n return text.replace(' ’ ', '\\'').replace(' .', '.')\n\n\ndef transliterate(text):\n try:\n return (requests.get(f\"https://www.google.com/inputtools/request?text={text}&ime=transliteration_en_hi\")).json()[1][0][1][0]\n except:\n return text\n" }, { "alpha_fraction": 0.7438596487045288, "alphanum_fraction": 0.7754386067390442, "avg_line_length": 70.25, "blob_id": "0caf5f8c6e7eaf50e0f5b8940db2598a05da2ac8", "content_id": "6bc6cf67508ada3869dd68d150e37f6ca66cf0c6", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 285, "license_type": "no_license", "max_line_length": 160, "num_lines": 4, "path": "/README.md", "repo_name": "aditya-malte/SemEval-SentiMix", "src_encoding": "UTF-8", "text": "# SemEval-SentiMix\nThis repository contains code required to replicate the results of our team - Team_Swift (aditya_malte)\n\nAditya Malte, Pratik Bhavsar, Sushant Rathi, \"Team_Swift at SemEval-2020 Task 9: Tiny Data Specialists Through Domain-Specific Pre-training On Code-Mixed Data\", SemEval, COLING 2020\n" } ]	2
Hilalaksoy/CNN-Look-up	https://github.com/Hilalaksoy/CNN-Look-up	584bc429fa687eb01d1790b72d2729dc7d9ab044	b4cdcff2a2d2319c90c05bee458e76dbe1aad527	3c82740cb1459e399ecc7bce06f26ac9ce095433	refs/heads/master	2020-04-27T09:09:21.663813	2019-05-14T17:03:30	2019-05-14T17:03:30	174,202,716	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.56901615858078, "alphanum_fraction": 0.6057268977165222, "avg_line_length": 26.200000762939453, "blob_id": "8d33f5057fc104b12efe9368550a5670921bc854", "content_id": "fe801f4f6cc8027ee9c506ac159639ea25c76908", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1362, "license_type": "permissive", "max_line_length": 96, "num_lines": 50, "path": "/src/preprocessing/resizing.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\nCreated on Thu Mar 7 21:32:32 2019\n\n@author: hilal aksoy\n\"\"\"\nimport cv2\n\n\ndef resize_area(image, size):\n \"\"\"resize with OpenCv .\"\"\"\n dim = (size, size)\n return cv2.resize(image, dim, interpolation = cv2.INTER_AREA)\n\ndef resize_preserve_aspect(image, max_size):\n height, width, channel = image.shape\n \n if width > height:\n ratio = width / max_size\n new_width = max_size\n new_height = int(height // ratio)\n else:\n ratio = height / max_size\n new_width = int(width // ratio)\n new_height = max_size\n \n return cv2.resize(image, (new_width, new_height), interpolation = cv2.INTER_AREA) \n\ndef resize_with_padding(image, max_size):\n \n image = resize_preserve_aspect(image, max_size)\n height, width, channel = image.shape\n \n delta_w = max_size - width\n delta_h = max_size - height\n \n top, bottom = delta_h//2, delta_h-(delta_h//2)\n left, right = delta_w//2, delta_w-(delta_w//2)\n \n color = [0, 0, 0]\n \n return cv2.copyMakeBorder(image, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color)\n\n\nif __name__==\"__main__\":\n \"\"\"resize with OpenCv .\"\"\"\n #img = cv2.imread('./val2017img/val2017/000000000139.jpg', cv2.IMREAD_UNCHANGED)\n #print(img)\n #print('Original Dimensions : ',img.shape)\n #resize_with_matrix(img,64)\n\n\n" }, { "alpha_fraction": 0.6588075160980225, "alphanum_fraction": 0.6681024432182312, "avg_line_length": 38.738739013671875, "blob_id": "6eac48e74f813a9df0d4ebe55d8640ca8fd558b7", "content_id": "54cd50f2619ebf446336b0b2db069fcba80075d7", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 4417, "license_type": "permissive", "max_line_length": 233, "num_lines": 111, "path": "/src/preprocessing/create_db.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\"\"\"\nCreated on Sat Dec 8 18:33:59 2018\n\n@author: hilal aksoy\n\"\"\"\nimport json\nimport sqlite3\n\n\ndef tablo_olustur():\n cursor.execute(\"CREATE TABLE IF NOT EXISTS Licenses(id INT PRIMARY KEY, name TEXT,url TEXT)\")\n cursor.execute(\"CREATE TABLE IF NOT EXISTS Categories(supercategoryId INT,supercategory TEXT, id INT PRIMARY KEY,name TEXT, FOREIGN KEY (supercategoryId) REFERENCES Categories (id))\")\n cursor.execute(\"CREATE TABLE IF NOT EXISTS Images(id INT PRIMARY KEY,file_name TEXT,height INT,width INT,coco_url TEXT,date_captured TEXT,flickr_url TEXT,license INT, FOREIGN KEY (license) REFERENCES Licenses (id))\")\n cursor.execute(\"CREATE TABLE IF NOT EXISTS Annotations(id INT PRIMARY KEY,area REAL,category_id INT,image_id INT,iscrowd INT, FOREIGN KEY (category_id) REFERENCES Categories (id),FOREIGN KEY (image_id) REFERENCES Images (id) )\")\n cursor.execute(\"CREATE TABLE IF NOT EXISTS Info(contributor TEXT,date_created TEXT,description TEXT,url TEXT,version TEXT,year INT)\")\n con.commit()\n\n\ndef veri_ekleme_licenses():\n for i in range(len(jsObject['licenses'])):\n lisencesId=jsObject['licenses'][i][\"id\"]\n lisencesName=jsObject['licenses'][i][\"name\"]\n lisencesUrl=jsObject['licenses'][i][\"url\"]\n degerler3=(lisencesId,lisencesName,lisencesUrl)\n cursor.execute(\"INSERT INTO Licenses(id,name,url) VALUES(?,?,?)\",degerler3)\n con.commit()\n\ndef veri_ekleme_cat():\n \"\"\"Categories tablosuna veri ekleme\"\"\"\n supercategories = set()\n\n for cat in jsObject['categories']:\n supercategories.add(cat['supercategory'])\n supercategories_dict = {}\n\n for i,cat in enumerate(supercategories):\n supercategories_dict[cat] = 100 + i\n cursor.execute(\"INSERT INTO Categories(supercategory,id,name) VALUES (?,?,?)\",( '', 100 + i, cat))\n\n for category in jsObject['categories']:\n kategori=category[\"supercategory\"]\n sayi=category[\"id\"]\n isim=category[\"name\"]\n supercategoryId = supercategories_dict[category[\"supercategory\"]]\n degerler=(supercategoryId,kategori,sayi,isim)\n cursor.execute(\"INSERT INTO Categories(supercategoryId,supercategory,id,name) VALUES (?,?,?,?)\",degerler)\n con.commit()\n\ndef veri_ekleme_image():\n for image in jsObject['images']:\n degerler=(image['id'],image['file_name'], image['height'],\n image['width'], image['coco_url'], image['date_captured'],\n image['flickr_url'], image['license'])\n cursor.execute(\"INSERT INTO Images(id,file_name,height,width,coco_url,date_captured,flickr_url,license) VALUES (?,?,?,?,?,?,?,?)\",degerler)\n con.commit()\n\n\ndef veri_ekleme_annotation():\n for annot in jsObject['annotations']:\n degerler=(annot['id'],annot['area'], annot['category_id'],\n annot['image_id'], annot['iscrowd'])\n cursor.execute(\"INSERT INTO Annotations(id, area, category_id, image_id, iscrowd) VALUES (?,?,?,?,?)\",degerler)\n con.commit()\n\ndef veri_ekleme_info():\n contributor=jsObject['info'][\"contributor\"]\n date_created=jsObject['info'][\"date_created\"]\n description=jsObject['info'][\"description\"]\n url=jsObject['info'][\"url\"]\n version=jsObject['info'][\"version\"]\n year=jsObject['info'][\"year\"]\n degerler2=(contributor,date_created,description,url,version,year)\n cursor.execute(\"INSERT INTO Info(contributor,date_created,description,url,version,year) VALUES (?,?,?,?,?,?)\",degerler2)\n con.commit()\n\nif __name__ == \"__main__\":\n #Json dosyasını okuma\n file = open('./data/annotations_trainval2017/instances_val2017.json','r')\n strr = file.read()\n jsObject = json.loads(strr)\n jsObject.keys()\n print(len(jsObject['images']))\n\n #Veritabanı bağlantısı\n con = sqlite3.connect(\"./data/val_info.db\")\n cursor = con.cursor()\n tablo_olustur()\n veri_ekleme_cat()\n veri_ekleme_info()\n veri_ekleme_image()\n veri_ekleme_licenses()\n veri_ekleme_annotation()\n con.close()\n\n\n file=open('./data/annotations_trainval2017/instances_train2017.json','r')\n strr=file.read()\n jsObject=json.loads(strr)\n jsObject.keys()\n print(len(jsObject['images']))\n con=sqlite3.connect(\"./data/train_info.db\")\n cursor=con.cursor()\n\n tablo_olustur()\n veri_ekleme_cat()\n veri_ekleme_info()\n veri_ekleme_image()\n veri_ekleme_licenses()\n veri_ekleme_annotation()\n con.close()\n" }, { "alpha_fraction": 0.6245059370994568, "alphanum_fraction": 0.6462450623512268, "avg_line_length": 23.14285659790039, "blob_id": "03335f4f83533e0bc8debc9877b69983d77f946b", "content_id": "80811b1eeeb7f9bcfde6df24f2dfc69931f78d37", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 506, "license_type": "permissive", "max_line_length": 118, "num_lines": 21, "path": "/src/get1000test.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\n\nfrom preprocessing.read_data import db_iterator\n\nimport json\nimport numpy as np\n\nDATA_PATH = './data/val2017'\nDB_NAME = './data/train_info.db'\n\nimages = []\n\nfor x in db_iterator(DB_NAME, DATA_PATH, 'ValidationImages', read_images=False):\n\timages.append(x)\n\n\nwith open('vals.json', 'w', encoding='utf8') as fi:\n\tfor x in images:\n\t\twr = {'image': x.full_path.split('\\\\')[-1], 'labels':[int(x) for x in np.where(x.labels == 1)[0].astype(np.int32) ]}\n\t\tfi.write(json.dumps(wr) + '\\n')" }, { "alpha_fraction": 0.5481438636779785, "alphanum_fraction": 0.5510441064834595, "avg_line_length": 42.71794891357422, "blob_id": "04a7b11e19eba93febe3c76de2822bb80433c322", "content_id": "e0acc38e34fbb46c9ccbf141061cb841cd969db1", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1724, "license_type": "permissive", "max_line_length": 133, "num_lines": 39, "path": "/src/utility/data_generator.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "from preprocessing.read_data import \nfrom preprocessing.resizing import \nimport numpy as np\n\nclass DataGenerator(object):\n \"\"\"\n DataGenerator, keras modellerinin kullanabilecegi sekilde tasarlanan bir data iteratoru\n resizing method: \n ('area', resize_area)\n \"\"\"\n def __init__(self, db_name, data_path,table_name,image_size=64, resizing_method='area', batch=128, grayscale=False):\n super(DataGenerator, self).__init__()\n self.batch = batch\n self.db_name = db_name\n self.data_path = data_path\n self.table_name = table_name\n self.image_size = image_size\n self.resizing_method = resizing_method\n self.grayscale = grayscale\n \n def flow(self):\n while True:\n for chunk in get_chunks(db_iterator(self.db_name, self.data_path,self.table_name, grayscale=self.grayscale), self.batch):\n x = []\n y = []\n for resim in chunk:\n if self.resizing_method == 'area':\n x.append(resize_area(resim.get_pixel_matrix(), self.image_size))\n elif self.resizing_method == 'with_padding':\n x.append(resize_with_padding(resim.get_pixel_matrix(), self.image_size))\n elif self.resizing_method == 'no_resizing':\n x.append(resim.get_pixel_matrix())\n else:\n print('Hata DataGenerator: resizing_method (\"area\", \"with_padding\") degerlerinden birisi olmalidir.')\n y.append(resim.labels)\n x = np.array(x)\n y = np.array(y) \n yield (x, y)\n return\n \n \n \n" }, { "alpha_fraction": 0.5975467562675476, "alphanum_fraction": 0.6209112405776978, "avg_line_length": 31.923076629638672, "blob_id": "50eb2c38e563e60a949cb8fce16f6cfa98d144e0", "content_id": "6feda454d4409c876b60a14bd3fbfa7152f52205", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1712, "license_type": "permissive", "max_line_length": 151, "num_lines": 52, "path": "/src/utility/resize_and_save.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\nimport os\nimport numpy\nfrom utility.data_generator import DataGenerator \n\nVAL_DATA_PATH = './data/val2017'\nDB_NAME = './data/train_info.db'\nTRAIN_DATA_PATH = './data/train2017'\n\nIMAGE_SIZE = 128\nBATCH_SIZE = 128\nNUM_CLASSES = 80\nTRAIN_BATCH_NO = 640\nTEST_BATCH_NO = 274\nVAL_BATCH_NO = 40\n\ndata_gen = DataGenerator(DB_NAME, TRAIN_DATA_PATH, table_name='TrainImages',image_size=IMAGE_SIZE, resizing_method='with_padding', batch=BATCH_SIZE)\nSAVE_PATH = './data/resized_128_with_padding/train/'\n\nindex = 0\nfor (x,y) in data_gen.flow():\n numpy.save(SAVE_PATH + 'x' + str(index), x)\n numpy.save(SAVE_PATH + 'y' + str(index), y)\n print('Saving batch ', index)\n index += 1\n if index == TRAIN_BATCH_NO:\n break\n\ndata_gen = DataGenerator(DB_NAME, TRAIN_DATA_PATH, table_name='TestImages',image_size=IMAGE_SIZE, resizing_method='with_padding', batch=BATCH_SIZE)\nSAVE_PATH = './data/resized_128_with_padding/test/'\n\nindex = 0\nfor (x,y) in data_gen.flow():\n numpy.save(SAVE_PATH + 'x' + str(index), x)\n numpy.save(SAVE_PATH + 'y' + str(index), y)\n print('Saving batch ', index)\n index += 1\n if index == TEST_BATCH_NO:\n break\n \n\ndata_gen = DataGenerator(DB_NAME, VAL_DATA_PATH, table_name='ValidationImages',image_size=IMAGE_SIZE, resizing_method='with_padding', batch=BATCH_SIZE)\nSAVE_PATH = './data/resized_128_with_padding/val/'\n\nindex = 0\nfor (x,y) in data_gen.flow():\n numpy.save(SAVE_PATH + 'x' + str(index), x)\n numpy.save(SAVE_PATH + 'y' + str(index), y)\n print('Saving batch ', index)\n index += 1\n if index == VAL_BATCH_NO:\n break\n" }, { "alpha_fraction": 0.6244864463806152, "alphanum_fraction": 0.6594083905220032, "avg_line_length": 26.942529678344727, "blob_id": "528601a6ad5b2169a184adce9d58d62d4aa33594", "content_id": "c38ae4869447efba8bfb9f50533b5667b139f467", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2434, "license_type": "permissive", "max_line_length": 89, "num_lines": 87, "path": "/src/128_area/training2.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\n# -- coding: utf-8 --\n# -- coding: utf-8 --\n\nfrom utility.data_generator import DataGenerator\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\nimport keras.backend as K\nimport numpy as np\n\nVAL_DATA_PATH = './data/val2017'\nDB_NAME = './data/train_info.db'\nTRAIN_DATA_PATH = './data/resized/train/'\nTEST_DATA_PATH = './data/resized/test/'\nVAL_DATA_PATH = './data/resized/val/'\n\nIMAGE_SIZE = 128\nBATCH_SIZE = 128\nNUM_CLASSES = 80\nTRAIN_BATCH_NO = 640\nTEST_BATCH_NO = 274\nVAL_BATCH_NO = 40\n\n\nfrom keras import models\nfrom keras.layers import Conv2D, Activation, MaxPooling2D, Dropout, Flatten, Dense\n\n\nmodel = models.Sequential()\nmodel.add(Conv2D(32, (5, 5), activation='relu', input_shape=(IMAGE_SIZE, IMAGE_SIZE, 3)))\nmodel.add(Activation('relu'))\nmodel.add(Conv2D(32, (3, 3)))\nmodel.add(Activation('relu'))\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\nmodel.add(Dropout(0.25))\n\nmodel.add(Conv2D(64, (3, 3), padding='same'))\nmodel.add(Activation('relu'))\nmodel.add(Conv2D(64, (3, 3)))\nmodel.add(Activation('relu'))\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\nmodel.add(Dropout(0.25))\n\nmodel.add(Flatten())\nmodel.add(Dense(512))\nmodel.add(Activation('relu'))\nmodel.add(Dropout(0.5))\nmodel.add(Dense(NUM_CLASSES, activation='sigmoid'))\n\nprint(model.summary())\n\nmodel.compile(loss='binary_crossentropy',\n optimizer='adam',\n metrics=['binary_accuracy', 'top_k_categorical_accuracy'])\n\n\nx_train = np.array([], dtype=np.int64).reshape(0, IMAGE_SIZE, IMAGE_SIZE, 3)\ny_train = np.array([], dtype=np.int64).reshape(0, NUM_CLASSES)\nfor i in range(TRAIN_BATCH_NO):\n\tx = np.load(TRAIN_DATA_PATH + 'x' + str(i) + '.npy')\n\ty = np.load(TRAIN_DATA_PATH + 'y' + str(i) + '.npy')\n\tx_train = np.concatenate((x_train, x), axis=0)\n\ty_train = np.concatenate((y_train, y), axis=0)\n\n\t\nx_val = np.array([], dtype=np.int64).reshape(0, IMAGE_SIZE, IMAGE_SIZE, 3)\ny_val = np.array([], dtype=np.int64).reshape(0, NUM_CLASSES)\nfor i in range(VAL_BATCH_NO):\n\tx = np.load(VAL_DATA_PATH + 'x' + str(i) + '.npy')\n\ty = np.load(VAL_DATA_PATH + 'y' + str(i) + '.npy')\n\tx_val = np.concatenate((x_val, x), axis=0)\n\ty_val = np.concatenate((y_val, y), axis=0)\n\n\nhistory = model.fit(\n x_train, y_train,\n\t\t batch_size=BATCH_SIZE,\n validation_data=(x_val, y_val),\n epochs=10)\n\nmodel.save(\"CNN6.model\")\n\nimport json\n\nwith open('history6.json', 'w') as w:\n\tw.write(json.dumps(history.history))\n\n\n\n" }, { "alpha_fraction": 0.5494505763053894, "alphanum_fraction": 0.553113579750061, "avg_line_length": 29.296297073364258, "blob_id": "25dcf4e7248f9871bf01266a7ecceb3168454167", "content_id": "e2f3bb6ee0e1ddea8b7abe589adfdd64c69bb94c", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 819, "license_type": "permissive", "max_line_length": 115, "num_lines": 27, "path": "/src/preprocessing/image.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "import numpy as np\nimport cv2\n\nclass Image(object):\n \"\"\"Image object holds some attr's about every image\"\"\"\n def __init__(self, _id, full_path, height_value, width_value, labels_value, read_image=True,grayscale = False):\n self.full_path = full_path\n self.height = height_value\n self.width = width_value\n self.labels = labels_value\n self.id = _id\n\n if read_image:\n try:\n self.matrix = cv2.imread(self.full_path)\n except IOException as e:\n raise e\n else:\n self.matrix = None\n\n def get_pixel_matrix(self):\n if self.matrix is None:\n try:\n self.matrix = cv2.imread(self.full_path)\n except IOException as e:\n raise e\n return self.matrix\n\n" }, { "alpha_fraction": 0.5747236609458923, "alphanum_fraction": 0.5886592864990234, "avg_line_length": 27.90277862548828, "blob_id": "f3122df4d87712cb5b993bdf9cf868ca473ca4b5", "content_id": "97a5b173f244b62d632fa595581ece1bdccd16ec", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2081, "license_type": "permissive", "max_line_length": 115, "num_lines": 72, "path": "/src/preprocessing/read_data.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "\"\"\"\nCreated on Sat Feb 16 15:55:18 2019\n\n@author: hilal aksoy\n\"\"\"\nfrom itertools import islice\nimport sqlite3\nimport numpy as np\nimport os\nfrom preprocessing.image import Image\n\ndef get_chunks(iterable, max_size):\n \"\"\"Yields chunks from iterable with given max_size\"\"\"\n sourceiter = iter(iterable)\n while True:\n batchiter = islice(sourceiter, max_size)\n chunk = [x for x in batchiter]\n if len(chunk) != 0:\n yield chunk\n else:\n return\n\ndef db_iterator(db_name, data_path,table_name, read_images=True, grayscale=False):\n \"\"\"db_name veritabanindaki resimleri al\"\"\"\n db_connection = sqlite3.connect(db_name)\n cursor = db_connection.cursor()\n\n values = None\n categories = None\n annotations = None\n try:\n values = cursor.execute(\"Select id,file_name,height,width From \"+ table_name).fetchall()\n categories = cursor.execute(\"Select supercategoryId,supercategory,id,name From Categories\").fetchall()\n annotations = cursor.execute(\"Select id, area, category_id, image_id, iscrowd From Annotations\").fetchall()\n except sqlite3.ProgrammingError as e:\n print('db_iterator error:' + e)\n return\n categories = categories[12:]\n categories_index = {}\n index = 0\n for cat in categories:\n categories_index[cat[2]] = index\n index += 1\n\n if not os.path.isdir(data_path):\n raise NotADirectoryError('db_iterator error: given parameter [' + data_path + ']is not a path.')\t\n\n try:\n for i in values:\n labels = np.zeros(len(categories))\n\n for label in annotations:\n if label[3] == i[0]:\n labels[categories_index[label[2]]] = 1\n\n image = Image(\n i[0],\n os.path.abspath(os.path.join(data_path, i[1])),\n i[2],\n i[3],\n labels,\n\t\t\t\tread_image=read_images\n )\n\n yield image\n except Exception as e:\n raise e\n return\n\n\nif __name__ == \"__main__\":\n db_name = \"../val_info.db\"\n" }, { "alpha_fraction": 0.6519427299499512, "alphanum_fraction": 0.6924335360527039, "avg_line_length": 26.16666603088379, "blob_id": "48f82acf02a19e85af662e4710fd6036a749cade", "content_id": "a35996ff951436939249406fbe39205e8ac1669c", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 2445, "license_type": "permissive", "max_line_length": 106, "num_lines": 90, "path": "/src/256_area_grayscale/training.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "from utility.data_generator import DataGenerator\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\nimport keras.backend as K\nimport numpy as np\nimport keras\nfrom keras import models\nfrom keras.layers import Conv2D, Activation, MaxPooling2D, Dropout, Flatten, Dense, SeparableConv2D, Input\nfrom keras.layers.core import Reshape\n\n\nTRAIN_DATA_PATH = './data/resized_256_area_grayscale/train/'\nTEST_DATA_PATH = './data/resized_256_area_grayscale/test/'\nVAL_DATA_PATH = './data/resized_256_area_grayscale/val/'\n\nIMAGE_SIZE = 256\nBATCH_SIZE = 256\nNUM_CLASSES = 80\nTRAIN_BATCH_NO = 320\nTEST_BATCH_NO = 137\nVAL_BATCH_NO = 20\n\n\nconfig = tf.ConfigProto()\nconfig.gpu_options.allow_growth = True\nsession = tf.Session(config=config)\n\n\nmodel = models.Sequential()\n\nmodel.add(Reshape((IMAGE_SIZE, IMAGE_SIZE, 1), input_shape=(IMAGE_SIZE, IMAGE_SIZE)))\nmodel.add(Conv2D(16, (5, 5), activation='relu'))\nmodel.add(Activation('relu'))\nmodel.add(MaxPooling2D(pool_size=(3, 3)))\n\nmodel.add(Conv2D(32, (4, 4), padding='same'))\nmodel.add(Activation('relu'))\nmodel.add(MaxPooling2D(pool_size=(3, 3)))\n\nmodel.add(Conv2D(64, (3, 3), padding='same'))\nmodel.add(Activation('relu'))\nmodel.add(MaxPooling2D(pool_size=(3, 3)))\n\nmodel.add(Conv2D(128, (2, 2), padding='same'))\nmodel.add(Activation('relu'))\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\n\nmodel.add(Conv2D(256, (1, 1), padding='same'))\nmodel.add(Activation('relu'))\n\nmodel.add(Flatten())\nmodel.add(Dropout(0.25))\nmodel.add(Dense(1024))\nmodel.add(Activation('relu'))\nmodel.add(Dropout(0.25))\nmodel.add(Dense(512))\nmodel.add(Activation('relu'))\nmodel.add(Dense(NUM_CLASSES, activation='sigmoid'))\n\n\nprint(model.summary())\n\nopt = keras.optimizers.rmsprop(lr=0.00002, decay=1e-6)\n\nmodel.compile(loss='binary_crossentropy',\n optimizer=opt,\n metrics=['binary_accuracy', 'top_k_categorical_accuracy'])\n\ndef gen(batch_no, path):\n while True:\n for i in range(batch_no):\n x = np.load(path + 'x' + str(i) + '.npy')\n y = np.load(path + 'y' + str(i) + '.npy')\n yield (x, y)\n\n\n\nhistory = model.fit_generator(\n gen(TRAIN_BATCH_NO, TRAIN_DATA_PATH),\n validation_data=gen(TEST_BATCH_NO, TEST_DATA_PATH),\n steps_per_epoch=TRAIN_BATCH_NO2,\n validation_steps=VAL_BATCH_NO2,\n epochs=30)\n\nmodel.save(\"256_area_grayscale/CNN.model\")\n\nimport json\n\nwith open('256_area_grayscale/history.json', 'w') as w:\n w.write(json.dumps(history.history))\n" }, { "alpha_fraction": 0.8103448152542114, "alphanum_fraction": 0.8103448152542114, "avg_line_length": 28, "blob_id": "3b5975a4dd4f1d32bfe671cc1ab358b6c3f954a7", "content_id": "405cf3b1a3ead5051b4a3846c21f75caab9c8be5", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 58, "license_type": "permissive", "max_line_length": 43, "num_lines": 2, "path": "/README.md", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# CNN-Look-up\nDeep learning based visual searching engine\n" }, { "alpha_fraction": 0.6466822028160095, "alphanum_fraction": 0.6658905744552612, "avg_line_length": 25.430768966674805, "blob_id": "a2beac93f17de45dd78e1862bef57fbd42bc78f5", "content_id": "c3f85bf648e5b71f923aa5eed91f7f166f2ac4f2", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1718, "license_type": "permissive", "max_line_length": 137, "num_lines": 65, "path": "/src/test_model.py", "repo_name": "Hilalaksoy/CNN-Look-up", "src_encoding": "UTF-8", "text": "# -- coding: utf-8 --\n\nfrom keras.models import load_model\nfrom preprocessing.resizing import resize_area\nimport cv2\nimport json\n# -- coding: utf-8 --\n\"\"\"\nCreated on Tue Apr 16 16:08:23 2019\n\n@author: Hilal\n\"\"\"\n\nimport numpy as np\n\nmodel= load_model('256_area_grayscale/CNN.model')\n\nprint(model.summary())\n\nwith open('256_area_grayscale/history.json', 'r') as fi:\n history = json.loads(fi.read())\n\nimport matplotlib.pyplot as plt\n\ntop_k_categorical_accuracy = history[\"top_k_categorical_accuracy\"]\nval_top_k_categorical_accuracy = history['val_top_k_categorical_accuracy']\n\nepochs = range(1, len(top_k_categorical_accuracy) + 1)\n\nplt.plot(epochs, top_k_categorical_accuracy, 'bo', label='Training top_k_categorical_accuracy')\nplt.plot(epochs, val_top_k_categorical_accuracy, 'b', label='Validation top_k_categorical_accuracy')\nplt.title('Training and validation accuracy')\nplt.xlabel('Epochs')\nplt.ylabel('Accuracy')\nplt.legend()\n\nplt.show()\n##################################################\netiket = None\nimages = ['cat.jpg', 'cow.jpg', 'pc.jpg','redapple.jpg','zebra.jpg', 'dog.jpg', 'dining_table.jpg' ,'apple.jpg', 'banana.jpg', 'bus.jpg',\n\t\t 'cup_knife.jpg', 'person_with_umbrella.jpg', 'red_truck.jpg', 'sheeps.jpg']\n\nwith open('etiket.json', 'r') as fi:\n etiket = json.loads(fi.read())\n\nresimler = []\nfor f in images:\n\tresimler.append(cv2.imread('./images/' + f))\n\nfor i, img in enumerate(resimler):\n resimler[i] = resize_area(img, 256)\n\narr = np.array(resimler)\n\nvals = model.predict(arr)\n\nfirst_5 = []\nfor val in vals:\n first_5.append(np.argsort(val)[::-1][:10])\n\n\nfor i, labels in enumerate(first_5):\n print(i, '.', images[i])\n for label in labels:\n print(etiket[str(label)])\n" } ]	11
benbo/AdjustedRandCI	https://github.com/benbo/AdjustedRandCI	51e01f26d82bdc12d8ff6e84989b9d84697a9925	d0c028491da6b5b9213160f747fc38fd7b304214	aa21bfb788ef687c547cb66eb215463c3dd1ff3c	refs/heads/master	2020-05-02T15:02:52.169639	2019-03-27T19:35:58	2019-03-27T19:35:58	178,029,643	1	1	null	null	null	null	null	[ { "alpha_fraction": 0.490100622177124, "alphanum_fraction": 0.5397598147392273, "avg_line_length": 32.85714340209961, "blob_id": "ee31dd7bf44816183fbdc55f07c9a1fe79d1ca03", "content_id": "1f0890f54de394530115c5a4d65f7b537b8c9e08", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3081, "license_type": "permissive", "max_line_length": 101, "num_lines": 91, "path": "/ari_ci.py", "repo_name": "benbo/AdjustedRandCI", "src_encoding": "UTF-8", "text": "# Author: Benedikt Boecking\n# License: MIT\n# The ari computation was adapted from sklearn\n# The CI computation follows \n# Steinley, Douglas, Michael J. Brusco, and Lawrence Hubert. \"The variance of the adjusted Rand index.\" \n# Psychological methods 21.2 (2016): 261.\n\n\nimport numpy as np\nfrom scipy.special import comb as spcomb\nfrom sklearn.metrics.cluster.supervised import _comb2\nfrom sklearn.metrics.cluster.supervised import contingency_matrix\nfrom scipy.stats import norm\n\n\ndef ari_ci(clusters,trueclusters,alpha = 0.05):\n '''\n \n Steinley, Douglas, Michael J. Brusco, and Lawrence Hubert. \"The variance of the adjusted Rand index.\" \n Psychological methods 21.2 (2016): 261.\n \n Parameters\n ----------\n clusters : array, shape = [n_samples]\n Cluster labels to evaluate\n trueclusters : int array, shape = [n_samples]\n Ground truth class labels to be used as a reference\n alpha : float\n Alpha level for the normal approximation\n Returns\n -------\n ari : float\n Adjusted Rand Index between -1.0 and 1.0. \n ari_variance : float\n variance of the ARI\n lowerci : float \n CI lower limit \n upperci : float\n CI upper limit\n \n '''\n ct = contingency_matrix(clusters,trueclusters).astype(np.float)\n N = ct.sum()\n \n \n # precompute some vars\n ncomb = _comb2(N)\n ctsqsum = (ct2).sum()\n rssq = sum(ct.sum(1)2)# row sums sq\n cssq = sum(ct.sum(0)2)# col sums sq\n \n # use same var names as in Steinley et al\n a = (ctsqsum-N)/2.0\n b = (rssq - ctsqsum)/2.0 \n c = (cssq - ctsqsum)/2.0 # col sums sq\n d = (ctsqsum + N2 - rssq - cssq)/2.0\n e = 2.0 * rssq - (N + 1.0) * N\n f = 2.0 * cssq - (N + 1.0) * N\n g = 4.0 * sum(ct.sum(1)*3) - 4 (N + 1.0) * rssq + (N + 1.0)*2 N\n h = N * (N - 1.0)\n i = 4.0 * sum(ct.sum(0)*3) - 4.0 (N + 1.0) * cssq + (N + 1.0)*2 N\n \n var_aplusd = 1.0/16.0 * (2.0 * N * (N - 1.0) - ((e * f) / (N * (N - 1.0)))*2 + \\\n (4.0 (g - h) * (i - h)) / (N * (N - 1.0) * (N - 2.0))) + \\\n 1.0/16.0 * (((e*2 - 4 g + 2 * h) * (f*2 - 4.0 i + 2.0 * h)) / \\\n (N * (N - 1.0) * (N - 2.0) * (N - 3.0)))\n \n ari_variance = (ncomb*2 var_aplusd) /((ncomb*2 - ((a + b) (a + c) + (b + d) * (c + d)))*2)\n ari_std = np.sqrt(ari_variance)\n \n sum_comb_c = sum(_comb2(n_c) for n_c in np.ravel(ct.sum(axis=1)))\n sum_comb_k = sum(_comb2(n_k) for n_k in np.ravel(ct.sum(axis=0)))\n sum_comb = sum(_comb2(n_ij) for n_ij in np.ravel(ct))\n\n prod_comb = (sum_comb_c sum_comb_k) / ncomb\n mean_comb = (sum_comb_k + sum_comb_c) / 2.\n \n #compute ari\n ari = (sum_comb - prod_comb) / (mean_comb - prod_comb)\n #compute CI\n qnrm = norm.ppf(1.0-alpha/2.0)\n lowerci = ari - qnrmari_std\n upperci = ari + qnrmari_std\n \n return ari,ari_variance,lowerci,upperci\n \n \nif __name__ == \"__main__\":\n clusters = np.array([0,1,1,1,1,1,1,1,1,0,0,0,0])\n trueclusters = np.array([0,1,1,1,1,0,0,1,1,1,0,0,0])\n print(ari_ci(clusters,trueclusters,alpha = 0.05))\n" }, { "alpha_fraction": 0.6645469069480896, "alphanum_fraction": 0.7265501022338867, "avg_line_length": 30.450000762939453, "blob_id": "78123ba9cbd48fb1bf3003dc46503abd2e52c951", "content_id": "8e5784ec77268710298d0c092726197fc75e89b6", "detected_licenses": [ "MIT" ], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 629, "license_type": "permissive", "max_line_length": 175, "num_lines": 20, "path": "/README.md", "repo_name": "benbo/AdjustedRandCI", "src_encoding": "UTF-8", "text": "# AdjustedRandCI\nCompute Adjusted Rand Index and Confidence Interval. The confidence interval is an approximate normal confidence interval using the exact variance of the Adjusted Rand Index. \n\nFor details see: Steinley, Douglas, Michael J. Brusco, and Lawrence Hubert. \"The variance of the adjusted Rand index.\" Psychological methods 21.2 (2016): 261.\n\n# Dependencies \n\n`numpy,scipy,sklearn`\n\n# Example\n```\nimport numpy as np\nfrom ari_ci import ari_ci\n\nclusters = np.array([0,1,1,1,1,1,1,1,1,0,0,0,0])\ntrueclusters = np.array([0,1,1,1,1,0,0,1,1,1,0,0,0])\n\n# print ARI, variance of ARI, lower CI, upper CI\nprint(ari_ci(clusters,trueclusters,alpha = 0.05))\n```\n" } ]	2
microwriting/pro14_video	https://github.com/microwriting/pro14_video	b4f0015277f86309851ce4d34b657e0696efcff6	da35ddf8adedbcc300e0e34d612512c9cf0b2f77	cf36ca98cb51e90c5593d76dab5dcc64f5626f55	refs/heads/master	2020-03-07T21:08:53.492999	2018-04-02T07:10:48	2018-04-02T07:10:48	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.5297029614448547, "alphanum_fraction": 0.5841584205627441, "avg_line_length": 21.44444465637207, "blob_id": "e16c344aeeb7200b1d624a727bf19685d547dfc8", "content_id": "69081857db1765e8ce1ececabc979ffca9b3f1f4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 404, "license_type": "no_license", "max_line_length": 89, "num_lines": 18, "path": "/app/migrations/0002_item_name.py", "repo_name": "microwriting/pro14_video", "src_encoding": "UTF-8", "text": "# Generated by Django 2.0.3 on 2018-03-28 11:27\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('app', '0001_initial'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='item',\n name='name',\n field=models.CharField(max_length=100, null=True, verbose_name='Video name'),\n ),\n ]\n" }, { "alpha_fraction": 0.6914893388748169, "alphanum_fraction": 0.7021276354789734, "avg_line_length": 27.299999237060547, "blob_id": "35aafef5ced4ba64cbdb446d55910b56293554f5", "content_id": "34a8122cd7d30e5ccef1edc9a1e45764317d438d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 282, "license_type": "no_license", "max_line_length": 68, "num_lines": 10, "path": "/app/models.py", "repo_name": "microwriting/pro14_video", "src_encoding": "UTF-8", "text": "from django.db import models\nfrom embed_video.fields import EmbedVideoField\n\n\nclass Item(models.Model):\n name = models.CharField('Video name', max_length=100, null=True)\n video = models.URLField() # same like models.URLField()\n\n def __str__(self):\n return self.name" } ]	2
cschomak/SimplifiedModelScanTools	https://github.com/cschomak/SimplifiedModelScanTools	aee980642466bab14fb9475318f92601ba850b82	957318e16799c1171cb85d4bc3fce9dbab8f6ff7	ad0f3d2f84ee17f7709c0c6ac5dc00dcd78c5b8f	refs/heads/master	2021-01-20T10:14:04.558511	2015-01-09T09:11:29	2015-01-09T09:11:29	null	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.3856671452522278, "alphanum_fraction": 0.6005409955978394, "avg_line_length": 87.76780700683594, "blob_id": "acefd27bed4234d57677575804bb47fb9dc299ed", "content_id": "d0154d063236f190a08509f0545b9b6810224b75", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67286, "license_type": "no_license", "max_line_length": 177, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_sbottom_neutralino2_ExpXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:43:37 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,2.333353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(410,0.2461637);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.2334847);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.2110297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,1.8558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,0.8776798);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.6405285);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.4777224);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.3740262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.2960413);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.2538686);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.2267522);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,1.3563);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,0.8680927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.6465633);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.468468);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.3636762);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.2884138);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.244014);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,2.222383);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,0.8212991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.5967864);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.3545682);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.2832322);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,2.308158);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,0.8471137);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.5806403);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.3981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.5011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.6309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.7943282);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,1.584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,2.511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,3.162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,3.981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,5.011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,6.309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,7.943282);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(24,2.333353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(25,1.433789);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(26,0.9570312);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(27,0.6920776);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(28,0.5795885);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(29,0.4458663);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(30,0.3540018);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(31,0.3134362);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(32,0.2540034);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(33,0.2318928);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(34,0.2061991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(35,0.1917318);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(36,0.1848956);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(37,0.1689069);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(38,0.1613518);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(39,0.151488);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(40,0.1535455);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(41,0.1433755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(42,0.1384362);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(43,0.1344351);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(44,0.1325073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(47,2.210343);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(48,1.482397);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(49,0.9178821);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(50,0.6709509);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(51,0.4679742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(52,0.4121693);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(53,0.3407646);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(54,0.2737353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(55,0.2414169);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(56,0.2094691);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(57,0.1911704);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(58,0.1740849);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(59,0.1661964);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(60,0.1611001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(61,0.1497265);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(62,0.1403575);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(63,0.1369684);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(64,0.1374196);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(65,0.1286481);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(66,0.1245359);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(67,0.1220581);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(70,2.107113);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(71,1.533226);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(72,1.164023);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(73,0.6598581);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(74,0.5542653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(75,0.4279408);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(76,0.3365166);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(77,0.2765485);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(78,0.2445835);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(79,0.2037137);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(80,0.1879037);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(81,0.1795298);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(82,0.1683778);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(83,0.1564211);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(84,0.1482006);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(85,0.1397169);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(86,0.1307714);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(87,0.1315393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(88,0.1232084);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(89,0.1217423);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(90,0.1168513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(93,3.269558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(94,1.986826);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(95,1.226647);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(96,0.8168973);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(97,0.5927721);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(98,0.4619297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(99,0.3892671);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(100,0.289063);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(101,0.2549618);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(102,0.2173297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(103,0.2032242);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(104,0.176385);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(105,0.169896);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(106,0.15948);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(107,0.1494023);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(108,0.1452923);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(109,0.137176);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(110,0.1354932);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(111,0.1295932);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(112,0.1284065);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(113,0.1218374);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(116,6.485093);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(117,2.624554);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(118,1.584632);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(119,1.144838);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(120,0.7235739);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(121,0.5026898);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(122,0.4079126);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(123,0.3090484);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(124,0.2698789);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(125,0.2468987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(126,0.2076008);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(127,0.1969595);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(128,0.1770077);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(129,0.1741971);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(130,0.1552959);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(131,0.1526971);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(132,0.1478953);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(133,0.1357245);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(134,0.127252);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(135,0.1249561);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(136,0.1238269);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(140,4.780059);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(141,1.96472);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(142,1.322883);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(143,0.8587031);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(144,0.6339666);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(145,0.4675986);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(146,0.3874278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(147,0.2925878);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(148,0.2529376);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(149,0.221204);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(150,0.2052938);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(151,0.1850154);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(152,0.1768404);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(153,0.1648849);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(154,0.1576143);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(155,0.1518705);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(156,0.1434179);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(157,0.1418601);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(158,0.1337146);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(159,0.1247049);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(164,4.152654);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(165,1.62283);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(166,1.116746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(167,0.7770254);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(168,0.5738264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(169,0.4573542);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(170,0.3456643);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(171,0.268887);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(172,0.2386763);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(173,0.222553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(174,0.199499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(175,0.183989);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(176,0.174592);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(177,0.1628547);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(178,0.1563251);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(179,0.1521786);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(180,0.1437712);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(181,0.1407257);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(182,0.1413499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(188,3.703419);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(189,1.489343);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(190,0.9826702);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(191,0.703989);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(192,0.5496004);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(193,0.4220552);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(194,0.3352396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(195,0.2751991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(196,0.2417483);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(197,0.2067031);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(198,0.1927712);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(199,0.1819883);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(200,0.1722);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(201,0.1629615);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(202,0.1562038);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(203,0.1485749);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(204,0.1379003);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(205,0.1458492);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(212,3.76761);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(213,1.304335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(214,0.9134035);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(215,0.6570017);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(216,0.5088289);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(217,0.3868862);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(218,0.2931839);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(219,0.2668574);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(220,0.2281828);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(221,0.2074877);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(222,0.1992296);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(223,0.1802825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(224,0.1662984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(225,0.1657685);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(226,0.1602748);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(227,0.1494387);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(228,0.1425038);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(236,3.119832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(237,1.342952);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(238,0.9129346);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(239,0.6257131);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(240,0.4565594);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(241,0.3571438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(242,0.3036734);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(243,0.2454109);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(244,0.227158);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(245,0.2014978);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(246,0.1889982);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(247,0.1740757);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(248,0.170072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(249,0.1560058);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(250,0.1465305);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(251,0.1481811);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(260,2.960942);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(261,1.157761);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(262,0.8237049);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(263,0.5832232);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(264,0.446367);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(265,0.3617653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(266,0.2926451);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(267,0.2470831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(268,0.2295809);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(269,0.2049591);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(270,0.1874037);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(271,0.1823006);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(272,0.1686019);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(273,0.1634226);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(274,0.1589687);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(284,2.687343);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(285,1.087633);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(286,0.7718171);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(287,0.5717074);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(288,0.44353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(289,0.3281599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(290,0.2877783);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(291,0.2447918);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(292,0.2304436);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(293,0.2079629);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(294,0.1886354);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(295,0.1691924);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(296,0.1648433);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(297,0.1620066);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(308,2.746479);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(309,1.028987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(310,0.7609823);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(311,0.5464596);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(312,0.4203441);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(313,0.3121202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(314,0.2690293);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(315,0.2449703);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(316,0.2183159);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(317,0.201095);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(318,0.181903);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(319,0.1722258);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(320,0.1709587);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(332,2.750479);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(333,1.00039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(334,0.6808928);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(335,0.5303726);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(336,0.4112162);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(337,0.3293761);\n 92487217_m(#tilde{b}) 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"text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:38 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(808,51.165);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,55.25362);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,51.0618);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,146.74);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,71.9094);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,67.6609);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,150.0605);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,232.46);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.1660788);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(255.706);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.1660788);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.2397097);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.3459847);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.4993766);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.7207747);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,1.040329);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,1.501558);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,2.167273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,3.128131);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,4.514984);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,6.516698);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,9.405869);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,13.57595);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,19.59483);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,28.28218);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,40.82106);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,58.91903);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,85.04072);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,122.7434);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,177.1616);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(96,0.799287);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(97,1.02871);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(98,1.30507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(99,1.53042);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(100,1.88314);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(101,2.449462);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(102,2.985445);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(103,3.657683);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(104,4.26426);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(105,5.09925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(106,6.56373);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetMaximum(255.706);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetDirectory(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetZaxis()->SetTitle(\"Expected R\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.656836986541748, "alphanum_fraction": 0.6720510721206665, "avg_line_length": 40.27131652832031, "blob_id": "046193e172ff34154644ca3c079a4902c9ffe834", "content_id": "d2b9b1d4b7a115c355c81d750935117c1e1c83d4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Makefile", "length_bytes": 5324, "license_type": "no_license", "max_line_length": 135, "num_lines": 129, "path": "/LimitPlotting/Makefile", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "C=c++\nLD=c++\nF77=g77\n#O2 for optimization, g for debugging\nSPECIALFLAGS=-g # -O2 -g\nROOTCFLAGS=$(shell root-config --cflags)\nROOTLIBS=$(shell root-config --libs) -lMinuit\n\nCFLAGS = $(SPECIALFLAGS) -I. -I./include -I$(SRT_PUBLIC_CONTEXT)/include -I$(ROOTSYS)/include -Wno-deprecated\nLFLAGS = $(SPECIALFLAGS) -lz \n\n\nRCXX=$(CFLAGS) $(ROOTCFLAGS)\nRLXX=$(LFLAGS) $(ROOTLIBS)\n\n#~ SRC=table.cc Overview.cc Variable.cc OldExclusionContours.cc ConfigFile.cc GeneratorMasses.cc PlotTools.cc Plotting.cc Event.cc\nSRC=table.cc Overview.cc Variable.cc OldExclusionContours.cc ConfigFile.cc GeneratorMasses.cc PlotTools.cc Plotting.cc EventDilepton.cc\n\n%.o: %.cc\n\t\t$(C) $(RCXX) -c $<\n\nall: plotDilepton\n#~ all: plotSinglePhoton8TeV\n#plotSinglePhoton7TeV plotSinglePhoton8TeV plot_Combination\n\n\n# common object files:\nConfigFile.o: ConfigFile.cc ConfigFile.h\n\t\t$(C) $(RCXX) -c ConfigFile.cc \n\nOldExclusionContours.o: OldExclusionContours.cc OldExclusionContours.h\n\t\t$(C) $(RCXX) -c OldExclusionContours.cc \n\nEvent.o: Event.cc Event.h\n\t\t$(C) $(RCXX) -c Event.cc \n\nEventDiPhoton.o: EventDiPhoton.cc Event.h\n\t\t$(C) $(RCXX) -c EventDiPhoton.cc\n\nEventDilepton.o: EventDilepton.cc Event.h\n\t\t$(C) $(RCXX) -c EventDilepton.cc \n\nVariable.o: Variable.cc Variable.h\n\t\t$(C) $(RCXX) -c Variable.cc \n\nGeneratorMasses.o: GeneratorMasses.cc GeneratorMasses.h\n\t\t$(C) $(RCXX) -c GeneratorMasses.cc \n\nPlotTools.o: PlotTools.cc PlotTools.h \n\t\t$(C) $(RCXX) -c PlotTools.cc\n\nPlotToolsDilepton.o: PlotToolsDilepton.cc PlotTools.h \n\t\t$(C) $(RCXX) -c PlotToolsDilepton.cc\n\nPlotting.o: Plotting.cc Plotting.h \n\t\t$(C) $(RCXX) -c Plotting.cc \n\nTheLimits.o: TheLimits.cc TheLimits.h\n\t\t$(C) $(RCXX) -c TheLimits.cc \n\n# single photon 7 TeV specific ----------------------------------------------------------------------------------------\nStyleSettings_SinglePhoton_7TeV.o: StyleSettings.h \n\t\t$(C) $(RCXX) -c StyleSettings_SinglePhoton_7TeV.cc\n\nplotSinglePhoton7TeV.o: StyleSettings.h \n\t\t$(C) $(RCXX) -c plotSinglePhoton7TeV.cc \n\nplotSinglePhoton7TeV: $(SRC:.cc=.o) StyleSettings_SinglePhoton_7TeV.o plotSinglePhoton7TeV.o \n\t\t$(LD) $(SRC:.cc=.o) StyleSettings_SinglePhoton_7TeV.o plotSinglePhoton7TeV.o $(RLXX) $(JCORR) -o plotSinglePhoton7TeV\n\t\t@echo '-> plotSinglePhoton7TeV executable created.'\n\n# single photon 8 TeV specific ----------------------------------------------------------------------------------------\nStyleSettings_SinglePhoton_8TeV.o: StyleSettings.h StyleSettings_SinglePhoton_8TeV.cc\n\t\t$(C) $(RCXX) -c StyleSettings_SinglePhoton_8TeV.cc\n\nplotSinglePhoton8TeV.o: plotSinglePhoton8TeV.cc plot.h \n\t\t$(C) $(RCXX) -c plotSinglePhoton8TeV.cc \n\nplotSinglePhoton8TeV: $(SRC:.cc=.o) StyleSettings_SinglePhoton_8TeV.o plotSinglePhoton8TeV.o \n\t\t$(LD) $(SRC:.cc=.o) StyleSettings_SinglePhoton_8TeV.o plotSinglePhoton8TeV.o $(RLXX) $(JCORR) -o plotSinglePhoton8TeV\n\t\t@echo '-> plotSinglePhoton8TeV executable created.'\n\n# single photon 8 TeV, 20 fb-1 specific ----------------------------------------------------------------------------------------\nStyleSettings_SinglePhoton_8TeV20fb.o: StyleSettings.h StyleSettings_SinglePhoton_8TeV20fb.cc\n\t\t$(C) $(RCXX) -c StyleSettings_SinglePhoton_8TeV20fb.cc\n\nplotSinglePhoton8TeV20fb.o: plotSinglePhoton8TeV20fb.cc plot.h \n\t\t$(C) $(RCXX) -c plotSinglePhoton8TeV20fb.cc \n\nplotSinglePhoton8TeV20fb: $(SRC:.cc=.o) StyleSettings_SinglePhoton_8TeV20fb.o plotSinglePhoton8TeV20fb.o \n\t\t$(LD) $(SRC:.cc=.o) StyleSettings_SinglePhoton_8TeV20fb.o plotSinglePhoton8TeV20fb.o $(RLXX) $(JCORR) -o plotSinglePhoton8TeV20fb\n\t\t@echo '-> plotSinglePhoton8TeV20fb executable created.'\n\n# Dilepton 8 TeV specific ----------------------------------------------------------------------------------------\nStyleSettings_Dilepton.o: StyleSettings.h StyleSettings_Dilepton.cc\n\t\t$(C) $(RCXX) -c StyleSettings_Dilepton.cc\n\nplotDilepton.o: plotDilepton.cc plot.h \n\t\t$(C) $(RCXX) -c plotDilepton.cc \n\nplotDilepton: $(SRC:.cc=.o) EventDilepton.o StyleSettings_Dilepton.o plotDilepton.o \n\t\t$(LD) $(SRC:.cc=.o) StyleSettings_Dilepton.o plotDilepton.o $(RLXX) $(JCORR) -o plotDilepton\n\t\t@echo '-> plotDilepton executable created.'\n\n# Combination specific ----------------------------------------------------------------------------------------\nStyleSettings_Combination.o: StyleSettings.h StyleSettings_Combination.cc\n\t\t$(C) $(RCXX) -c StyleSettings_Combination.cc\n\nplot_Combination.o: plot_Combination.cc plot.h StyleSettings_Combination.cc\n\t\t$(C) $(RCXX) -c plot_Combination.cc \n\nplot_Combination: $(SRC:.cc=.o) Event.o StyleSettings_Combination.o plot_Combination.o \n\t\t$(LD) $(SRC:.cc=.o) StyleSettings_Combination.o plot_Combination.o $(RLXX) $(JCORR) -o plot_Combination\n\t\t@echo '-> plot_Combination executable created.'\n\n# di photon specific ----------------------------------------------------------------------------------------\nStyleSettings_DiPhoton.o: StyleSettings.h\n\t\t$(C) $(RCXX) -c StyleSettings_DiPhoton.cc\n\nplotDiPhoton.o: plotDiPhoton.cc plot.h\n\t\t$(C) $(RCXX) -c plotDiPhoton.cc \n\nplotDiPhoton: $(SRC:.cc=.o) EventDiPhoton.o StyleSettings_DiPhoton.o Plotting.o plotDiPhoton.o \n\t\t$(LD) $(SRC:.cc=.o) StyleSettings_DiPhoton.o EventDiPhoton.o plotDiPhoton.o Plotting.o $(RLXX) $(JCORR) -o plotDiPhoton\n\t\t@echo '-> plotDiPhoton executable created.'\n\nclean:\n\t\t@rm -f .o \n\t\t@rm -f plotSinglePhoton7TeV plotSinglePhoton8TeV\n" }, { "alpha_fraction": 0.3662070333957672, "alphanum_fraction": 0.6918726563453674, "avg_line_length": 45.55916976928711, "blob_id": "4638bf481fdcc78593ecacbb16f4c56f2a009c84", "content_id": "fe92708251c2e7512ecdeddb0040b15275323e93", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 15737, "license_type": "no_license", "max_line_length": 178, "num_lines": 338, "path": "/LimitPlotting/results/Fixed_Neutralino_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:39:10 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(69.08783,29.72973,761.6554,789.8649);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",41,193.75,706.25,45,143.75,706.25);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(32);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(43);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(32);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(43);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(32);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(43);\n 211830563_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(113);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,493.75,150);\n graph->SetPoint(1,493.6045,162.3544999);\n graph->SetPoint(2,492.6382812,173.8882812);\n graph->SetPoint(3,489.7275659,183.4775659);\n graph->SetPoint(4,484.2982846,190.5482846);\n graph->SetPoint(5,477.0899966,195.8399966);\n graph->SetPoint(6,469.7162188,200.9662188);\n graph->SetPoint(7,463.4662188,207.2162188);\n graph->SetPoint(8,458.4854967,214.7354966);\n graph->SetPoint(9,454.3055035,222.7645034);\n graph->SetPoint(10,451.1117188,230.4292813);\n graph->SetPoint(11,450.0079308,237.3544999);\n graph->SetPoint(12,451.9324376,243.75);\n graph->SetPoint(13,456.5410001,250);\n graph->SetPoint(14,462.6455001,256.1044999);\n graph->SetPoint(15,469.5707187,261.6792813);\n graph->SetPoint(16,477.2354966,266.5145033);\n graph->SetPoint(17,485.4100034,270.8399966);\n graph->SetPoint(18,493.75,275);\n graph->SetPoint(19,502.0899966,279.1600034);\n graph->SetPoint(20,510.2645034,283.4854966);\n graph->SetPoint(21,517.9292813,288.3207187);\n graph->SetPoint(22,524.8545,293.8955);\n graph->SetPoint(23,531.25,300);\n graph->SetPoint(24,537.5,306.25);\n graph->SetPoint(25,543.75,312.5);\n graph->SetPoint(26,550,318.75);\n graph->SetPoint(27,556.1045,325.1455);\n graph->SetPoint(28,561.6792813,332.0707187);\n graph->SetPoint(29,566.5145034,339.7354966);\n graph->SetPoint(30,570.8399966,347.9100034);\n graph->SetPoint(31,574.8545,356.3955001);\n graph->SetPoint(32,578.1937847,365.5562153);\n graph->SetPoint(33,580.4292813,375.8207187);\n graph->SetPoint(34,582.0707187,386.6792813);\n graph->SetPoint(35,584.3062154,396.9437847);\n graph->SetPoint(36,587.5,406.25);\n graph->SetPoint(37,590.6937847,415.5562153);\n graph->SetPoint(38,592.7837813,425.9662188);\n graph->SetPoint(39,593.75,437.5);\n graph->SetPoint(40,594.7162188,449.0337812);\n graph->SetPoint(41,596.8062154,459.4437847);\n graph->SetPoint(42,600,468.75);\n graph->SetPoint(43,603.1937847,478.0562153);\n graph->SetPoint(44,605.2837813,488.4662188);\n graph->SetPoint(45,605.9589999,500);\n graph->SetPoint(46,605.2837813,511.5337812);\n graph->SetPoint(47,603.1937847,521.9437847);\n graph->SetPoint(48,599.8545,531.1044999);\n graph->SetPoint(49,595.8399966,539.5899966);\n graph->SetPoint(50,591.5145034,547.7645034);\n graph->SetPoint(51,586.6535011,555.1382812);\n graph->SetPoint(52,580.9848621,560.4478427);\n graph->SetPoint(53,574.6038242,562.6374873);\n graph->SetPoint(54,567.5882898,561.7585948);\n graph->SetPoint(55,560.0139096,558.6148834);\n graph->SetPoint(56,552.5662639,553.7854519);\n graph->SetPoint(57,546.069048,547.6050164);\n graph->SetPoint(58,540.2476175,540.9264469);\n graph->SetPoint(59,534.0735531,534.7523825);\n graph->SetPoint(60,527.3949836,528.930952);\n graph->SetPoint(61,521.069048,522.6050164);\n graph->SetPoint(62,515.2476175,515.9264469);\n graph->SetPoint(63,509.0735531,509.7523825);\n graph->SetPoint(64,502.3949836,503.930952);\n graph->SetPoint(65,496.069048,497.6050164);\n graph->SetPoint(66,490.2476175,490.9264469);\n graph->SetPoint(67,484.0735531,484.7523825);\n graph->SetPoint(68,477.3949836,478.930952);\n graph->SetPoint(69,471.069048,472.6050164);\n graph->SetPoint(70,465.2476175,465.9264469);\n graph->SetPoint(71,459.0735531,459.7523825);\n graph->SetPoint(72,452.3949836,453.930952);\n graph->SetPoint(73,446.069048,447.6050164);\n graph->SetPoint(74,440.2476175,440.9264469);\n graph->SetPoint(75,434.0735531,434.7523825);\n graph->SetPoint(76,427.3949836,428.930952);\n graph->SetPoint(77,421.069048,422.6050164);\n graph->SetPoint(78,415.2476175,415.9264469);\n graph->SetPoint(79,409.0735531,409.7523825);\n graph->SetPoint(80,402.3949836,403.930952);\n graph->SetPoint(81,396.069048,397.6050164);\n graph->SetPoint(82,390.2476175,390.9264469);\n graph->SetPoint(83,384.0735531,384.7523825);\n graph->SetPoint(84,377.3949836,378.930952);\n graph->SetPoint(85,371.069048,372.6050164);\n graph->SetPoint(86,365.2476175,365.9264469);\n graph->SetPoint(87,359.0735531,359.7523825);\n graph->SetPoint(88,352.3949836,353.930952);\n graph->SetPoint(89,346.069048,347.6050164);\n graph->SetPoint(90,340.2476175,340.9264469);\n graph->SetPoint(91,334.0735531,334.7523825);\n graph->SetPoint(92,327.3949836,328.930952);\n graph->SetPoint(93,321.069048,322.6050164);\n graph->SetPoint(94,315.2476175,315.9264469);\n graph->SetPoint(95,309.0735531,309.7523825);\n graph->SetPoint(96,302.3949836,303.930952);\n graph->SetPoint(97,296.069048,297.6050164);\n graph->SetPoint(98,290.2476175,290.9264469);\n graph->SetPoint(99,284.0735531,284.7523825);\n graph->SetPoint(100,277.3949836,278.930952);\n graph->SetPoint(101,271.069048,272.6050164);\n graph->SetPoint(102,265.2476175,265.9264469);\n graph->SetPoint(103,259.0735531,259.7523825);\n graph->SetPoint(104,252.3949836,253.930952);\n graph->SetPoint(105,246.069048,247.6050164);\n graph->SetPoint(106,240.2476175,240.9264469);\n graph->SetPoint(107,234.0735531,234.7523825);\n graph->SetPoint(108,227.3949836,228.930952);\n graph->SetPoint(109,221.069048,222.6050164);\n graph->SetPoint(110,216.0159851,216.0977273);\n graph->SetPoint(111,210.192052,211.0095194);\n graph->SetPoint(112,200,208.4434195);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Observed limit\",113,159.4041,646.5549);\n Graph_Graph1->SetMinimum(108.7363);\n Graph_Graph1->SetMaximum(603.9012);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n \n graph = new TGraph(110);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,581.1045,150);\n graph->SetPoint(1,580.2837813,161.8472832);\n graph->SetPoint(2,578.0482846,171.9437847);\n graph->SetPoint(3,573.8882812,180.1382812);\n graph->SetPoint(4,567.7837812,186.5337812);\n graph->SetPoint(5,560.2645034,191.5145034);\n graph->SetPoint(6,552.2354966,195.9854967);\n graph->SetPoint(7,544.7162188,200.9662188);\n graph->SetPoint(8,538.4662188,207.2162188);\n graph->SetPoint(9,533.4854967,214.7354966);\n graph->SetPoint(10,529.1600034,222.9100034);\n graph->SetPoint(11,525.1455001,231.3955001);\n graph->SetPoint(12,521.9517154,240.4107153);\n graph->SetPoint(13,520.6824376,250);\n graph->SetPoint(14,522.0972155,259.4437847);\n graph->SetPoint(15,525.9662188,267.7837812);\n graph->SetPoint(16,531.3955001,274.8544999);\n graph->SetPoint(17,537.5,281.25);\n graph->SetPoint(18,543.75,287.5);\n graph->SetPoint(19,550,293.75);\n graph->SetPoint(20,556.1045,300.1455);\n graph->SetPoint(21,561.6792813,307.0707187);\n graph->SetPoint(22,566.5145034,314.7354966);\n graph->SetPoint(23,570.8399966,322.9100034);\n graph->SetPoint(24,575,331.25);\n graph->SetPoint(25,579.1600034,339.5899966);\n graph->SetPoint(26,583.3399966,347.9100034);\n graph->SetPoint(27,587.3545,356.3955001);\n graph->SetPoint(28,590.6937847,365.5562153);\n graph->SetPoint(29,592.9292813,375.8207187);\n graph->SetPoint(30,594.5707187,386.6792813);\n graph->SetPoint(31,596.8062154,396.9437847);\n graph->SetPoint(32,600,406.25);\n graph->SetPoint(33,603.1937847,415.5562153);\n graph->SetPoint(34,605.2837813,425.9662188);\n graph->SetPoint(35,606.1045,437.6455001);\n graph->SetPoint(36,606.25,450);\n graph->SetPoint(37,606.25,462.5);\n graph->SetPoint(38,606.25,475);\n graph->SetPoint(39,606.25,487.5);\n graph->SetPoint(40,606.25,500);\n graph->SetPoint(41,606.25,512.5);\n graph->SetPoint(42,606.1045,524.8544999);\n graph->SetPoint(43,605.2837813,536.5337812);\n graph->SetPoint(44,603.1937847,546.9437847);\n graph->SetPoint(45,599.8545,556.1302802);\n graph->SetPoint(46,595.6944965,564.5899146);\n graph->SetPoint(47,590.6680044,572.0230981);\n graph->SetPoint(48,584.4438667,576.681734);\n graph->SetPoint(49,577.5404017,576.7075143);\n graph->SetPoint(50,571.0948283,572.3140163);\n graph->SetPoint(51,565.2476175,565.9264469);\n graph->SetPoint(52,559.0735531,559.7523825);\n graph->SetPoint(53,552.3949836,553.930952);\n graph->SetPoint(54,546.069048,547.6050164);\n graph->SetPoint(55,540.2476175,540.9264469);\n graph->SetPoint(56,534.0735531,534.7523825);\n graph->SetPoint(57,527.3949836,528.930952);\n graph->SetPoint(58,521.069048,522.6050164);\n graph->SetPoint(59,515.2476175,515.9264469);\n graph->SetPoint(60,509.0735531,509.7523825);\n graph->SetPoint(61,502.3949836,503.930952);\n graph->SetPoint(62,496.069048,497.6050164);\n graph->SetPoint(63,490.2476175,490.9264469);\n graph->SetPoint(64,484.0735531,484.7523825);\n graph->SetPoint(65,477.3949836,478.930952);\n graph->SetPoint(66,471.069048,472.6050164);\n graph->SetPoint(67,465.2476175,465.9264469);\n graph->SetPoint(68,459.0735531,459.7523825);\n graph->SetPoint(69,452.3949836,453.930952);\n graph->SetPoint(70,446.069048,447.6050164);\n graph->SetPoint(71,440.2476175,440.9264469);\n graph->SetPoint(72,434.0735531,434.7523825);\n graph->SetPoint(73,427.3949836,428.930952);\n graph->SetPoint(74,421.069048,422.6050164);\n graph->SetPoint(75,415.2476175,415.9264469);\n graph->SetPoint(76,409.0735531,409.7523825);\n graph->SetPoint(77,402.3949836,403.930952);\n graph->SetPoint(78,396.069048,397.6050164);\n graph->SetPoint(79,390.2476175,390.9264469);\n graph->SetPoint(80,384.0735531,384.7523825);\n graph->SetPoint(81,377.3949836,378.930952);\n graph->SetPoint(82,371.069048,372.6050164);\n graph->SetPoint(83,365.2476175,365.9264469);\n graph->SetPoint(84,359.0735531,359.7523825);\n graph->SetPoint(85,352.3949836,353.930952);\n graph->SetPoint(86,346.069048,347.6050164);\n graph->SetPoint(87,340.2476175,340.9264469);\n graph->SetPoint(88,334.0735531,334.7523825);\n graph->SetPoint(89,327.3949836,328.930952);\n graph->SetPoint(90,321.069048,322.6050164);\n graph->SetPoint(91,315.2476175,315.9264469);\n graph->SetPoint(92,309.0735531,309.7523825);\n graph->SetPoint(93,302.3949836,303.930952);\n graph->SetPoint(94,296.069048,297.6050164);\n graph->SetPoint(95,290.2476175,290.9264469);\n graph->SetPoint(96,284.0735531,284.7523825);\n graph->SetPoint(97,277.3949836,278.930952);\n graph->SetPoint(98,271.069048,272.6050164);\n graph->SetPoint(99,265.2476175,265.9264469);\n graph->SetPoint(100,259.0735531,259.7523825);\n graph->SetPoint(101,252.3949836,253.930952);\n graph->SetPoint(102,246.069048,247.6050164);\n graph->SetPoint(103,240.2476175,240.9264469);\n graph->SetPoint(104,234.0735531,234.7523825);\n graph->SetPoint(105,227.3949836,228.930952);\n graph->SetPoint(106,221.069048,222.6050164);\n graph->SetPoint(107,216.0159851,216.0977273);\n graph->SetPoint(108,210.192052,211.0095194);\n graph->SetPoint(109,200,208.4434195);\n \n TH1F Graph_Graph2 = new TH1F(\"Graph_Graph2\",\"Expected limit\",110,159.375,646.875);\n Graph_Graph2->SetMinimum(107.3292);\n Graph_Graph2->SetMaximum(619.3783);\n Graph_Graph2->SetDirectory(0);\n Graph_Graph2->SetStats(0);\n Graph_Graph2->SetLineStyle(0);\n Graph_Graph2->GetXaxis()->SetNdivisions(505);\n Graph_Graph2->GetXaxis()->SetLabelFont(42);\n Graph_Graph2->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetXaxis()->SetTitleSize(32);\n Graph_Graph2->GetXaxis()->SetTitleFont(43);\n Graph_Graph2->GetYaxis()->SetLabelFont(42);\n Graph_Graph2->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetYaxis()->SetTitleSize(32);\n Graph_Graph2->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph2->GetYaxis()->SetTitleFont(43);\n Graph_Graph2->GetZaxis()->SetLabelFont(42);\n Graph_Graph2->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetZaxis()->SetTitleSize(32);\n Graph_Graph2->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph2->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph2);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.505765438079834, "alphanum_fraction": 0.6613101363182068, "avg_line_length": 63.69841384887695, "blob_id": "c13d9219e9531ca7e218821aac1fdd2e299e6036", "content_id": "3e4c228c3510defa41a64ba8fd9643ed0461ce68", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 8152, "license_type": "no_license", "max_line_length": 163, "num_lines": 126, "path": "/LimitPlotting/results/old/T6bbedge_70/Fixed_Edge_sbottom_neutralino2_Acceptance.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Fri Jun 27 19:47:02 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(8999.1);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(-0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,8999.1);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,8549.145);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,8099.19);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,7649.235);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,7199.28);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,6749.325);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,6299.37);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,5849.415);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,5399.46);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,4949.505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,4499.55);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,4049.595);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,3599.64);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,3149.685);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,2699.73);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2249.775);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,1799.82);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,1349.865);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,899.91);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,449.955);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(51);\n palette->SetFillStyle(1001);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Acceptance\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2 = new TH2F(\"266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2\",\"\",21,187.5,712.5,25,87.5,712.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->SetMinimum(8999.1);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->SetMaximum(-0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->SetEntries(315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->SetDirectory(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->SetStats(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->SetLineStyle(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetZaxis()->SetTitle(\"Acceptance\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__2->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.3847338855266571, "alphanum_fraction": 0.6020698547363281, "avg_line_length": 87.596435546875, "blob_id": "9ad42b08522a44c7193c2e909ee25d92a568abd9", "content_id": "5ca81a8ae00336b93f0e56c18fb5f0e6814bb745", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 59714, "license_type": "no_license", "max_line_length": 182, "num_lines": 674, "path": "/LimitPlotting/results/Fixed_Neutralino_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:39:08 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,22.5,881.8548,789.1667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 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211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.505694);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.620448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.851199);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,1.10713);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,1.44007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,1.87722);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,2.42326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,3.16487);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,3.94663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,5.31071);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,6.93194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,8.63949);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(47,0.0737888);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(48,0.0824616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(49,0.0978805);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(50,0.115576);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(51,0.141712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(52,0.170468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(53,0.218149);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(54,0.272795);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(55,0.353295);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(56,0.44973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(57,0.598179);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(58,0.73778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(59,0.976955);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(60,1.30043);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(61,1.69778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(62,2.22196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(63,2.89267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(64,3.74852);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(65,4.96483);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(66,6.17082);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(67,7.98974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(70,0.0962047);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(71,0.117609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(72,0.13326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(73,0.155968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(74,0.183366);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(75,0.227186);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(76,0.283668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(77,0.362781);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(78,0.462714);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(79,0.586923);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(80,0.772022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(81,0.984549);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(82,1.27963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(83,1.652);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(84,2.1247);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(85,2.82109);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(86,3.58226);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(87,4.63539);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(88,6.22715);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(89,7.69811);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(90,9.72987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(94,0.132142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(95,0.151612);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(96,0.16905);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(97,0.198752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(98,0.252277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(99,0.332733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(100,0.442712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(101,0.576659);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(102,0.772477);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(103,0.998088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,1.34111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,1.71003);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,2.16597);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,2.89461);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,3.74464);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,4.76514);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,6.25411);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,7.87975);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,10.4273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,12.9621);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,0.17582);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,0.211338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,0.229675);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,0.287935);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,0.366529);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,0.467267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,0.599368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,0.78479);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,1.05802);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,1.37155);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,1.73335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,2.26919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,2.88899);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,3.81848);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,4.92321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,6.25521);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,8.03394);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,10.1969);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,13.0074);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,0.231926);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,0.157586);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,0.17624);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,0.196217);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.246665);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.340733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.45751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.579817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.754067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.974919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,1.31767);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,1.71536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,2.24164);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,2.75303);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,3.63995);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,4.67597);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,6.08787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,7.46923);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,0.244588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,0.129368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,0.144093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,0.16332);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.220519);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.283244);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.391348);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.523347);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.666368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.911266);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,1.18248);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,1.58482);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,1.9597);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,2.57317);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,3.30334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,4.28609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,5.47202);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,0.220289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,0.127522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,0.141377);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.165608);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.220761);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.29979);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.404393);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.5254);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.698992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.918022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,1.22439);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,1.57395);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,2.00364);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,2.70474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,3.3789);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,4.32951);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.216337);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.138526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.155201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.187237);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.25229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.343456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.458831);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.570008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.788715);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,1.0334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,1.35649);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,1.8008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,2.29845);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,2.94522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,3.73168);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.211042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.166845);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.18731);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.227871);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.315189);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.401217);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.521034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.712911);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.94115);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,1.22271);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,1.55578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,2.10618);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,2.64455);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,3.39851);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.232115);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.206554);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.225819);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.288991);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.378889);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.483742);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.655804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.857727);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,1.12885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,1.45973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,1.95948);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,2.48246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,3.20662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.283976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.261598);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.291931);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.359669);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.473443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.614292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.816356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,1.06625);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,1.39653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,1.82538);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,2.34457);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,2.98097);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.318691);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.33179);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.37324);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.459538);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.58199);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.765222);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,1.00567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,1.32413);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,1.74908);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,2.20593);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,2.88313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.409435);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.435049);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.477012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.589531);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.751653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.974778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,1.27687);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,1.6637);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,2.1463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,2.81448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.496958);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.548181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.613733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.752613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.969321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,1.23363);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,1.6037);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,2.08399);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,2.7064);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.623663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.721843);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.782306);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.978495);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,1.21842);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,1.59094);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,2.03996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,2.62949);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.800222);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.901632);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,1.02347);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,1.24583);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,1.58785);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,2.01486);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,2.59943);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.99237);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.20391);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,1.3201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,1.60003);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,1.97848);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,2.53884);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.24058);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.54215);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,1.7356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,2.04289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,2.55882);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.60529);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.97293);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,2.2039);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.59692);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.99986);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,2.51632);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,2.71888);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,2.57509);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,3.25819);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,3.18164);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.06640992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(14.30814);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.06640992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.08687613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1136496);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1486742);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.1944926);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.2544313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.3328419);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.4354171);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.569604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.7451446);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.9747833);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.275192);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,1.668181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,2.182281);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,2.854816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,3.734613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,4.885546);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,6.391174);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,8.360806);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,10.93744);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(24,0.0976517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(25,0.119208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(26,0.126761);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(27,0.142308);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(28,0.16617);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(29,0.19848);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(30,0.242813);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(31,0.317769);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(32,0.410134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(33,0.505694);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(34,0.620448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(35,0.851199);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(36,1.10713);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(37,1.44007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(38,1.87722);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(39,2.42326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(40,3.16487);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(41,3.94663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(42,5.31071);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(43,6.93194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(44,8.63949);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(47,0.0737888);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(48,0.0824616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(49,0.0978805);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(50,0.115576);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(51,0.141712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(52,0.170468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(53,0.218149);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(54,0.272795);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(55,0.353295);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(56,0.44973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(57,0.598179);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(58,0.73778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(59,0.976955);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(60,1.30043);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(61,1.69778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(62,2.22196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(63,2.89267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(64,3.74852);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(65,4.96483);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(66,6.17082);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(67,7.98974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(70,0.0962047);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(71,0.117609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(72,0.13326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(73,0.155968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(74,0.183366);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(75,0.227186);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(76,0.283668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(77,0.362781);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(78,0.462714);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(79,0.586923);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(80,0.772022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(81,0.984549);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(82,1.27963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(83,1.652);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(84,2.1247);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(85,2.82109);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(86,3.58226);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(87,4.63539);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(88,6.22715);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(89,7.69811);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(90,9.72987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(94,0.132142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(95,0.151612);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(96,0.16905);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(97,0.198752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(98,0.252277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(99,0.332733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(100,0.442712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(101,0.576659);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(102,0.772477);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(103,0.998088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(104,1.34111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(105,1.71003);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(106,2.16597);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(107,2.89461);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(108,3.74464);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(109,4.76514);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(110,6.25411);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(111,7.87975);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(112,10.4273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(113,12.9621);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(118,0.17582);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(119,0.211338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(120,0.229675);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(121,0.287935);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(122,0.366529);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(123,0.467267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(124,0.599368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(125,0.78479);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(126,1.05802);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(127,1.37155);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(128,1.73335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(129,2.26919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(130,2.88899);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(131,3.81848);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(132,4.92321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(133,6.25521);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(134,8.03394);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(135,10.1969);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(136,13.0074);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(142,0.231926);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(143,0.157586);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(144,0.17624);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(145,0.196217);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(146,0.246665);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(147,0.340733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(148,0.45751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(149,0.579817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(150,0.754067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(151,0.974919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(152,1.31767);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(153,1.71536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(154,2.24164);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(155,2.75303);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(156,3.63995);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(157,4.67597);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(158,6.08787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(159,7.46923);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(166,0.244588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(167,0.129368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(168,0.144093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(169,0.16332);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(170,0.220519);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(171,0.283244);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(172,0.391348);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(173,0.523347);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(174,0.666368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(175,0.911266);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(176,1.18248);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(177,1.58482);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(178,1.9597);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(179,2.57317);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(180,3.30334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(181,4.28609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(182,5.47202);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(190,0.220289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(191,0.127522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(192,0.141377);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(193,0.165608);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(194,0.220761);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(195,0.29979);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(196,0.404393);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(197,0.5254);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(198,0.698992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(199,0.918022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(200,1.22439);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(201,1.57395);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(202,2.00364);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(203,2.70474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(204,3.3789);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(205,4.32951);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(214,0.216337);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(215,0.138526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(216,0.155201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(217,0.187237);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(218,0.25229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(219,0.343456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(220,0.458831);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(221,0.570008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(222,0.788715);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(223,1.0334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(224,1.35649);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(225,1.8008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(226,2.29845);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(227,2.94522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(228,3.73168);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(238,0.211042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(239,0.166845);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(240,0.18731);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(241,0.227871);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(242,0.315189);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(243,0.401217);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(244,0.521034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(245,0.712911);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(246,0.94115);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(247,1.22271);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(248,1.55578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(249,2.10618);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(250,2.64455);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(251,3.39851);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(262,0.232115);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(263,0.206554);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(264,0.225819);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(265,0.288991);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(266,0.378889);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(267,0.483742);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(268,0.655804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(269,0.857727);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(270,1.12885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(271,1.45973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(272,1.95948);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(273,2.48246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(274,3.20662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(286,0.283976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(287,0.261598);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(288,0.291931);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(289,0.359669);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(290,0.473443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(291,0.614292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(292,0.816356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(293,1.06625);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(294,1.39653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(295,1.82538);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(296,2.34457);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(297,2.98097);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(310,0.318691);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(311,0.33179);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(312,0.37324);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(313,0.459538);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(314,0.58199);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(315,0.765222);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(316,1.00567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(317,1.32413);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(318,1.74908);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(319,2.20593);\n 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[GeV]->SetBinContent(309,7.312381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,7.664129);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,7.613973);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,8.022725);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,7.991883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,8.986796);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,24.22033);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,21.02914);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,9.686741);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,9.431847);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,9.931825);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,10.40633);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,25.50702);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,12.92419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,26.61222);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,27.8287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,34.46705);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,33.33927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,110.0941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,41.6045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,145.3772);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,74.26761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,81.84553);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(24,0.3183421);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(25,0.3558873);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(26,0.4247782);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(27,0.4918053);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(28,0.6105172);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(29,0.7346313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(30,0.8888468);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(31,0.9958733);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(32,1.300848);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(33,1.674404);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(34,2.071489);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(35,2.603853);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(36,3.252397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(37,4.037727);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(38,4.919149);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(39,6.202226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(40,7.804258);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(41,9.653153);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(42,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(43,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(44,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(47,0.3263443);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(48,0.3568984);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(49,0.4072787);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(50,0.4685532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(51,0.5717593);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(52,0.6872733);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(53,0.7970817);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(54,0.9362969);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(55,1.219716);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(56,1.49144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(57,1.887305);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(58,2.339565);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(59,2.956782);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(60,3.653473);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(61,4.603621);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(62,5.677883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(63,7.254855);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(64,8.805595);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(65,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(66,13.21743);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(67,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(70,0.3447039);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(71,0.4321119);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(72,0.4705145);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(73,0.5281224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(74,0.601061);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(75,0.7068428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(76,0.8465272);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(77,0.9446483);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(78,1.225088);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(79,1.498426);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(80,1.853379);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(81,2.394545);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(82,2.952465);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(83,3.659903);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(84,4.556637);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(85,5.76887);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(86,7.153724);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(87,8.671228);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(88,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(89,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(90,15.77347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(93,0.4665402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(94,0.4750523);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(95,0.5548765);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(96,0.6127154);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(97,0.6692926);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(98,0.7766511);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(99,0.9143728);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(100,0.9895871);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(101,1.326286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(102,1.593726);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(103,2.00438);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(104,2.509765);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(105,3.065421);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(106,3.819291);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(107,4.595699);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(108,5.921803);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(109,7.338302);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(110,9.064348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(111,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(112,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(113,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(116,0.9717805);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(117,0.6195927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(118,0.6942865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(119,0.7494951);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(120,0.8153264);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(121,0.8831586);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(122,1.040942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(123,1.099367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(124,1.425911);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(125,1.745203);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(126,2.118717);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(127,2.593861);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(128,3.275837);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(129,4.088925);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(130,4.960702);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(131,6.203548);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(132,7.700511);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(133,9.196335);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(134,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(135,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(136,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(140,1.330971);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(141,0.8541175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(142,0.9254544);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(143,0.9871559);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(144,1.098212);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(145,1.168781);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(146,1.325979);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(147,1.576297);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(148,1.882315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(149,2.276242);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(150,2.763997);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(151,3.460606);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(152,4.200703);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(153,5.271854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(154,6.424719);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(155,7.929315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(156,9.688667);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(157,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(158,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(159,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(164,1.894675);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(165,1.15904);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(166,1.289729);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(167,1.341558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(168,1.489315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(169,1.456471);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(170,1.818412);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(171,2.085218);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(172,2.472187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(173,3.068152);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(174,3.645492);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(175,4.505431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(176,5.57011);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(177,6.833831);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(178,8.198045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(179,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(180,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(181,15.32461);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(182,19.02743);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(188,2.809702);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(189,1.610221);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(190,1.665205);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(191,1.831652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(192,1.894208);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(193,2.149219);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(194,2.459604);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(195,2.744098);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(196,3.326766);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(197,3.765365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(198,4.740629);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(199,5.82089);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(200,7.203483);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(201,8.732493);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(202,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(203,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(204,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(205,19.62877);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(212,4.396777);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(213,2.237643);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(214,2.382861);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(215,2.324348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(216,2.611343);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(217,2.85082);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(218,3.122885);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(219,3.681767);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(220,4.265149);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(221,5.160928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(222,6.256005);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(223,7.580269);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(224,9.210923);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(225,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(226,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(227,16.45481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(228,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(236,5.808396);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(237,3.423342);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(238,3.056362);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(239,3.337636);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(240,3.373724);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(241,3.69256);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(242,4.194366);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(243,4.697483);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(244,5.421604);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(245,6.574615);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(246,7.944042);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(247,9.75795);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(248,12.00507);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(249,14.14463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(250,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(251,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(260,8.245902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(261,3.912333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(262,4.322706);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(263,4.338624);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(264,4.627081);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(265,4.92946);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(266,5.364666);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(267,6.217289);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(268,7.349679);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(269,8.61076);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(270,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(271,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(272,15.09406);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(273,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(274,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(284,10.73229);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(285,5.757727);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(286,5.774555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(287,5.834333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(288,6.146652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(289,6.321007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(290,7.20622);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(291,7.848733);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(292,9.634187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(293,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(294,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(295,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(296,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(297,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(308,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(309,7.312381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(310,7.664129);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(311,7.613973);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(312,8.022725);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(313,7.991883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(314,8.986796);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(315,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(316,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(317,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(318,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(319,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(320,24.22033);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(332,21.02914);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(333,9.686741);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(334,9.431847);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(335,9.931825);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(336,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(337,10.40633);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(338,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(339,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(340,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(341,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(342,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(343,25.50702);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(356,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(357,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(358,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(359,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(360,12.92419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(361,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(362,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(363,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(364,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(365,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(366,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(380,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(381,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(382,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(383,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(384,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(385,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(386,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(387,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(388,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(389,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(404,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(405,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(406,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(407,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(408,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(409,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(410,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(411,26.61222);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(412,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(428,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(429,27.8287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(430,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(431,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(432,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(433,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(434,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(435,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(452,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(453,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(454,34.46705);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(455,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(456,33.33927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(457,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(458,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(476,110.0941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(477,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(478,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(479,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(480,41.6045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(481,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(500,145.3772);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(501,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(502,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(503,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(504,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(524,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(525,74.26761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(526,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(527,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(548,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(549,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(550,81.84553);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(572,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(573,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(596,10);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetDirectory(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitle(\"R (first guess)\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.45280030369758606, "alphanum_fraction": 0.6802043318748474, "avg_line_length": 81.47562408447266, "blob_id": "5b8e459142389f98ddb7942132bc30bf8f9833db", "content_id": "9cf18504ce65fa6bffd981fbf039f21f906fe7d9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 89651, "license_type": "no_license", "max_line_length": 157, "num_lines": 1087, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_ExpR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:25 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,0.373467);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,0.382893);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,0.4019925);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(642,49.6603);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,84.7068);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,32.5487);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,40.3841);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,35.6782);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,40.8259);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,38.0419);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,41.3594);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,46.0133);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,51.9448);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,99.4569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,45.7833);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,51.8115);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,48.5587);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,43.7761);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,44.0804);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,50.4736);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,53.5694);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,122.413);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,59.147);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,62.0238);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,58.9277);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,58.3395);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,56.9723);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,63.98);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,147.28);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,66.1168);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,64.88);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,67.3289);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,71.894);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,74.571);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,201.313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,79.7606);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,85.086);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,85.3275);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,83.7021);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,189.427);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,102.154);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,100.031);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,100.965);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,294.717);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,133.78);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,130.088);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,405.209);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,155.952);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,455.3);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.3035457);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(500.83);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.3035457);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.4396402);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.6367526);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.9222401);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,1.335726);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,1.934598);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,2.801973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,4.058236);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,5.877743);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,8.513025);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,12.32983);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,17.85791);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,25.86448);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,37.46081);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,54.25633);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,78.58212);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,113.8144);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,164.843);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,238.7502);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,345.7936);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(29,0.373467);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(30,0.382893);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(31,0.4019925);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(32,0.421092);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(33,0.571651);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(34,0.648783);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(35,0.725915);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(36,0.937737);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(37,1.10335);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(38,1.32825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(39,1.51297);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(40,2.10374);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(41,2.38211);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(42,2.79466);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(43,3.5349);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(44,4.66959);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(45,5.39814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(46,6.321);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(47,8.01287);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(48,9.53821);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(49,11.1978);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(50,15.3614);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(51,17.1548);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(52,21.3219);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(53,24.4363);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(54,29.9506);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(57,0.419707);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(58,0.369675);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(59,0.410053);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(60,0.417362);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(61,0.517247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(62,0.577868);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(63,0.702107);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(64,0.794872);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(65,0.958799);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(66,1.14949);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(67,1.38892);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(68,1.6526);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(69,2.05583);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(70,2.53645);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(71,3.14854);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(72,3.90032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(73,4.58351);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(74,5.77163);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(75,7.0351);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(76,8.5955);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(77,10.0323);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(78,12.4898);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(79,15.7852);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(80,18.8011);\n 284060385_M_{sbottom} 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[GeV]__24->SetBinContent(94,1.06391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(95,1.32719);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(96,1.55034);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(97,1.98802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(98,2.5303);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(99,2.92104);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(100,3.61319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(101,4.51628);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(102,5.44223);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(103,6.89423);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(104,8.21178);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(105,10.0417);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(106,12.7813);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(107,15.1488);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(108,19.2225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(109,21.7212);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(110,25.8758);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(113,0.470718);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(114,0.446128);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(115,0.424258);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(116,0.425867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(117,0.533602);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(118,0.568491);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(119,0.63701);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(120,0.804985);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(121,0.890504);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(122,1.096396);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(123,1.29702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(124,1.56492);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(125,2.02387);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(126,2.37803);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(127,3.052838);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(128,3.7769);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(129,4.49666);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(130,5.30442);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(131,6.95909);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(132,8.45379);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(133,10.0819);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(134,12.3678);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(135,14.9716);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(136,18.6507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(137,22.4958);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(138,25.9616);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(141,0.564817);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(142,0.516664);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(143,0.596225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(156,3.74769);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(157,4.59354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(158,5.48182);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(159,6.6476);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(160,8.26102);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(161,10.1098);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(162,12.5609);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(163,16.0664);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(164,18.7694);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(165,22.5902);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(166,27.2708);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(181,1.99621);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(182,2.4737);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(183,3.22065);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(184,3.86823);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(185,4.7691);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(186,5.72918);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(187,6.64957);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(188,8.68478);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(189,10.4074);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(190,13.1504);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(191,15.0338);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(207,1.57987);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(208,1.77794);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(209,2.05306);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(210,2.70422);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(211,3.16933);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(212,3.80395);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(213,4.67605);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(214,6.01623);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(215,6.97256);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(216,9.037);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(217,10.4882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(234,1.49226);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(235,1.65745);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(236,1.93007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(237,2.4629);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(238,2.77101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(239,3.2711);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(240,4.09026);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(241,5.21515);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(242,6.00657);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(243,7.49202);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(244,9.09423);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(262,1.6984);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(263,1.84726);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(264,1.99968);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(265,2.40488);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(266,2.86935);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(267,3.64371);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(268,4.40052);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(269,5.35051);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(270,6.22978);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(271,8.0926);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(272,9.75338);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(291,2.24438);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(292,2.28761);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(293,2.99036);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(294,3.06619);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(295,3.7656);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(296,4.65965);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(297,5.36065);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(298,6.63105);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(299,7.68657);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(300,9.94434);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(301,12.156);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(302,14.4826);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(303,17.4523);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(304,21.8621);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(305,28.7753);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(306,30.4423);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(314,3.55973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(315,2.13978);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(316,2.13184);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(317,2.44161);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(318,2.22097);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(319,2.77297);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(320,2.75993);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(321,3.09081);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(322,3.40267);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(323,3.94325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(324,4.95619);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(325,5.80934);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(326,6.86972);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(327,8.4171);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(328,9.71221);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(329,12.3363);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(330,15.3638);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__24->SetBinContent(331,18.6431);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(170,0.05801568);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.05334344);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.0495524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.04730245);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.04296116);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.04192252);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.03973507);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.03953224);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.03632704);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.03546827);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.03413639);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.03332176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.03258258);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,0.1559985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,0.0839592);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,0.06148298);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.04998768);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.0453468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.04127104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.03926163);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.03693633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.03467253);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.03364076);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.03300922);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.03109672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.02967765);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.03021084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.02876265);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.0277653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.1115689);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.06408684);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.04859616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.0408365);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.03728309);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.03553947);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.03342755);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.03008252);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.02993354);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.02909474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.02857704);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.0275782);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.02672084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.02611015);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.02516638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.08226072);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.05312752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.0405927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.0352976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.03227065);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.03033811);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.02839374);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.02798951);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.02726776);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.02644672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.02511741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.02519361);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.02395526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.02377159);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.06447376);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.04629762);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.03463577);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.03204398);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.02916566);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.02766998);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.02657896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.02563784);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.02489672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.02410382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.02410334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.02329213);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.02250337);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.05500128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.04127104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.03250925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.02841256);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.02645752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.02516389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.02446216);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.02392704);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.02309023);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.02279389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.02196588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.02136254);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.04558142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.03762722);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.03000435);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.02645752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.02463493);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.02381086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.0227664);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.02222118);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.02192139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.02146827);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.02110938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.04112271);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.03493376);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.02766998);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.02463493);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.02342008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.0221836);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.02164304);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.02132111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.02047412);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.02034829);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.03693633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.03201874);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.02622632);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.02355034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.0221836);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.02106305);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.02055889);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.0203086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.01996774);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.03370751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.03099146);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.02459242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.02257296);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.02120759);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.02050445);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.01997651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.01958801);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.03205389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.02909474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.0237336);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.02164304);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.02033972);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.01964548);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.01920746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.02935526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.02799672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.0229457);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.02088556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.0194789);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.01908088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.02760984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.02685368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.02279389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.02014202);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.01920746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.02714274);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.02584834);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.02180037);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.01952391);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.02519361);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.02528151);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.02085541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.02428735);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.02478584);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.02339104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.02481893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.03079896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.03821987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.04742881);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.05885662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.07303792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.09063615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.1124746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.139575);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.1732051);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.2149382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.2667269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,0.3309938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,0.4107456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,0.5097133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,0.6325269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,0.7849321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,0.9740587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,1.208755);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(24,0.733392);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(25,0.469734);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(26,0.2860488);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(27,0.1904518);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(28,0.1373248);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(29,0.1021195);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(30,0.08081073);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(31,0.06929456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(32,0.0601208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(33,0.051198);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(34,0.04325653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(35,0.04229185);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(36,0.03928122);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(37,0.03685);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(38,0.03505583);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(39,0.03326974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(40,0.03216312);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(41,0.03040032);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(42,0.03064639);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(43,0.03042099);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(44,0.02877955);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(47,0.551896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(48,0.333967);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(49,0.225828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(50,0.1553772);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(51,0.1159676);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(52,0.0887124);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(53,0.07289919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(54,0.05994192);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(55,0.0520928);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(56,0.0453468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(57,0.04193287);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(58,0.03647001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(59,0.03459999);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(60,0.03322501);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(61,0.03187757);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(62,0.0306612);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(63,0.02974016);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(64,0.02873632);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(65,0.02868361);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(66,0.02693985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(67,0.0270042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(70,0.696352);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(71,0.488563);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(72,0.3133712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(73,0.2192982);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(74,0.1588816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(75,0.1241723);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(76,0.1021234);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(77,0.08587424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(78,0.07317968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(79,0.06450948);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(80,0.05883499);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(81,0.05336289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(82,0.04997872);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(83,0.04675997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(84,0.04397577);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(85,0.0431862);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(86,0.04088032);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(87,0.03952079);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(88,0.04002611);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(89,0.03730052);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(90,0.03638642);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(94,0.537122);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(95,0.3836288);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(96,0.2448666);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(97,0.1784424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(98,0.1425914);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(99,0.1226289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(100,0.1084587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(101,0.09373136);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(102,0.08832874);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(103,0.07987779);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(104,0.0748011);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(105,0.06786494);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(106,0.06403747);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(107,0.06128215);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(108,0.05923156);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(109,0.05676968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(110,0.05544547);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(111,0.05256778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(112,0.05321551);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(113,0.05147359);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(118,0.4003568);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(119,0.3248498);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(120,0.211576);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(121,0.1670249);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(122,0.1407124);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(123,0.118821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(124,0.1062907);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(125,0.09571588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(126,0.08982221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(127,0.08272262);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(128,0.07454874);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(129,0.07128128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(130,0.06693341);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(131,0.06497302);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(132,0.06219344);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(133,0.05993343);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(134,0.05780278);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(135,0.05620011);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(136,0.05502266);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(142,0.3186216);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(143,0.1920152);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(144,0.1339457);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(145,0.1013161);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(146,0.08587424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(147,0.07631952);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(148,0.07262802);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(149,0.06297567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(150,0.05848086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(151,0.05532747);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(152,0.05243872);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(153,0.05103757);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(154,0.04827302);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(155,0.04475656);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(156,0.04444235);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(157,0.04242584);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(158,0.04194239);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(159,0.03968233);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(166,0.2231528);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(167,0.1180326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(168,0.08630037);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(169,0.06770036);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(170,0.05801568);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(171,0.05334344);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(172,0.0495524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(173,0.04730245);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(174,0.04296116);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(175,0.04192252);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(176,0.03973507);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(177,0.03953224);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(178,0.03632704);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(179,0.03546827);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(180,0.03413639);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(181,0.03332176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(182,0.03258258);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(190,0.1559985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(191,0.0839592);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(192,0.06148298);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(193,0.04998768);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(194,0.0453468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(195,0.04127104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(196,0.03926163);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(197,0.03693633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(198,0.03467253);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(199,0.03364076);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(200,0.03300922);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(201,0.03109672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(202,0.02967765);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(203,0.03021084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(204,0.02876265);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(205,0.0277653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(214,0.1115689);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(215,0.06408684);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(216,0.04859616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(217,0.0408365);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(218,0.03728309);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(219,0.03553947);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(220,0.03342755);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(221,0.03008252);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(222,0.02993354);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(223,0.02909474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(224,0.02857704);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(225,0.0275782);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(226,0.02672084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(227,0.02611015);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(228,0.02516638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(238,0.08226072);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(239,0.05312752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(240,0.0405927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(241,0.0352976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(242,0.03227065);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(243,0.03033811);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(244,0.02839374);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(245,0.02798951);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(246,0.02726776);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(247,0.02644672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(248,0.02511741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(249,0.02519361);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(250,0.02395526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(251,0.02377159);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(262,0.06447376);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(263,0.04629762);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(264,0.03463577);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(265,0.03204398);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(266,0.02916566);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(267,0.02766998);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(268,0.02657896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(269,0.02563784);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(270,0.02489672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(271,0.02410382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(272,0.02410334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(273,0.02329213);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(274,0.02250337);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(286,0.05500128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(287,0.04127104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(288,0.03250925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(289,0.02841256);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(290,0.02645752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(291,0.02516389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(292,0.02446216);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(293,0.02392704);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(294,0.02309023);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(295,0.02279389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(296,0.02196588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(297,0.02136254);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(310,0.04558142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(311,0.03762722);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(312,0.03000435);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(313,0.02645752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(314,0.02463493);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(315,0.02381086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(316,0.0227664);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(317,0.02222118);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(318,0.02192139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(319,0.02146827);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(320,0.02110938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(334,0.04112271);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(335,0.03493376);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(336,0.02766998);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(337,0.02463493);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(338,0.02342008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(339,0.0221836);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(340,0.02164304);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(341,0.02132111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(342,0.02047412);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(343,0.02034829);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(358,0.03693633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(359,0.03201874);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(360,0.02622632);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(361,0.02355034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(362,0.0221836);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(363,0.02106305);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(364,0.02055889);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(365,0.0203086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(366,0.01996774);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(382,0.03370751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(383,0.03099146);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(384,0.02459242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(385,0.02257296);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(386,0.02120759);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(387,0.02050445);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(388,0.01997651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(389,0.01958801);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(406,0.03205389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(407,0.02909474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(408,0.0237336);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(409,0.02164304);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(410,0.02033972);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(411,0.01964548);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(412,0.01920746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(430,0.02935526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(431,0.02799672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(432,0.0229457);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(433,0.02088556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(434,0.0194789);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(435,0.01908088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(454,0.02760984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(455,0.02685368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(456,0.02279389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(457,0.02014202);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(458,0.01920746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(478,0.02714274);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(479,0.02584834);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(480,0.02180037);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(481,0.01952391);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(502,0.02519361);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(503,0.02528151);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(504,0.02085541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(526,0.02428735);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(527,0.02478584);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(550,0.02339104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetDirectory(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.44694915413856506, "alphanum_fraction": 0.6845816373825073, "avg_line_length": 82.651611328125, "blob_id": "377df5e23e8382d8215edc5f41c9ae61d09c4ab2", "content_id": "7119bce7a665ec5e6ba26e7a16f270d94b32562c", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 90762, "license_type": "no_license", "max_line_length": 157, "num_lines": 1085, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:24 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,13.4368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,8.1328);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,5.894034);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,3.655269);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,3.2148);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,2.54653);\n 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[GeV]->SetBinContent(529,0.6137053);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(530,0.5880125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(546,10.09359);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(547,3.394357);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,2.303155);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,2.140459);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,1.658569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(551,1.232866);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(552,1.090326);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(553,0.9527159);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(554,0.893022);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(555,0.76232);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(556,0.6904812);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(557,0.6302966);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,0.6393335);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(575,9.448409);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(576,2.999701);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(577,2.405819);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(578,1.999226);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(579,1.54834);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,1.182826);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,1.124915);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,0.935588);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,0.8643456);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,0.7558113);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,0.66711);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,0.6361687);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,7.918055);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,3.32949);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,2.285687);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,1.853684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,1.466531);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,1.284775);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,1.03632);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,0.8641712);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,0.8016926);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.7469687);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.679865);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,8.998027);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,2.80351);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,2.317455);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,1.903475);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,1.528101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,1.206096);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,1.008094);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.8828151);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.7863981);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.7482581);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,8.480987);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,2.589023);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,2.479622);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,1.718056);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,1.534326);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,1.190405);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,1.029962);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.8848721);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.7816191);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,7.9294);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,2.731002);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,2.470183);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,1.849588);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,1.311693);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,1.120553);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.9728149);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.8468278);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,7.490048);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,2.772501);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,2.415938);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,1.78585);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,1.458493);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,1.116916);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,1.009548);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,7.158406);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,2.645524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,2.028177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,1.670524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,1.386434);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,1.167734);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,8.04928);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,2.543939);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,2.096821);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,1.713983);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,1.310477);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,5.984991);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,2.509225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.98671);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,1.568842);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,7.415113);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,2.639077);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,2.06215);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,7.936605);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,2.579109);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(29,13.4368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(30,8.1328);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(31,5.894034);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(32,3.655269);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(33,3.2148);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(34,2.54653);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(35,1.878261);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(36,1.681477);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(37,1.418672);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(38,1.252696);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(39,1.008872);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(40,1.032841);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(41,0.8924692);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(42,0.7978797);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(43,0.7500328);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(44,0.7287134);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(45,0.6771871);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(46,0.5974867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(47,0.6042908);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(48,0.5680608);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(49,0.5258816);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(50,0.544296);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(51,0.4993008);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(52,0.4950701);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(53,0.4590511);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(54,0.4843137);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(57,13.7997);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(58,8.07875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(59,5.191716);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(60,3.575977);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(61,2.91992);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(62,2.09715);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(63,1.7907);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(64,1.435762);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(65,1.259528);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(66,1.062266);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(67,0.92);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(68,0.8351889);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(69,0.7664265);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(70,0.7180902);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(71,0.6622556);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(72,0.6261529);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(73,0.5837974);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(74,0.5448923);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(75,0.5345334);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(76,0.4976288);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(77,0.4740097);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(78,0.454424);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(79,0.4567776);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(80,0.4266629);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(81,0.4373623);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(82,0.4260655);\n 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(379,1.137624);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(380,0.9175783);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(381,0.8623368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(382,0.7308315);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(383,0.7195049);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(384,0.6562304);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(385,0.5909767);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(386,0.594642);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(387,0.5773136);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(388,0.5463616);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(389,0.5228022);\n 284060385_M_{sbottom} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(434,1.777891);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(435,1.423413);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(436,1.174293);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(437,0.9774273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(438,0.85869);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(439,0.8222878);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(440,0.6931328);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(441,0.6790944);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(442,0.633574);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(443,0.6202656);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(444,0.6017819);\n 284060385_M_{sbottom} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(518,6.1033);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(519,2.475718);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(520,2.25527);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(521,1.604884);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(522,1.28761);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(523,1.061625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(524,0.9478272);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(525,0.8413318);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(526,0.733858);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(527,0.7275232);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(528,0.6705257);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 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[GeV]__21->SetBinContent(555,0.76232);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(556,0.6904812);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(557,0.6302966);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(558,0.6393335);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(575,9.448409);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(576,2.999701);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(577,2.405819);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(578,1.999226);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(579,1.54834);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(580,1.182826);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(581,1.124915);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->SetBinContent(582,0.935588);\n 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__21->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.45640459656715393, "alphanum_fraction": 0.678715169429779, "avg_line_length": 80.38969421386719, "blob_id": "1af66fa8dc6f44c5c2689c688610b903e08a8c8d", "content_id": "97fd49eb75b4e0bed898ee607502b5547e46bc29", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 61612, "license_type": "no_license", "max_line_length": 161, "num_lines": 757, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:32 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(24,38.1159);\n 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[GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9 = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9\",\"\",21,187.5,712.5,25,87.5,712.5);\n 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[GeV]->SetBinContent(220,0.5754209);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.5284154);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.4773221);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.4470946);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.4164961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.398097);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.3806407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.364685);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.3388157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,8.644311);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.443572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,2.248596);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,1.594799);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,1.154341);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.9220017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.7723589);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.6384342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.5512831);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.5096681);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.4669937);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.4378479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.4247564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.4016801);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.3793939);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.3639709);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,8.490947);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,2.916445);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,2.104252);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,1.526525);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,1.141317);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.8921625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.7210572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.6325397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.5676059);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.4982927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.4695204);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.4474302);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.4176948);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.3915368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.3781573);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,8.088529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,2.83851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,2.004211);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,1.452407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,1.119724);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.8565102);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.7358755);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.6111652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.5648973);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.509591);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.4572401);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.4327326);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.4139976);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.3951283);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,7.392522);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,2.574957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.902318);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.387006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,1.080595);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.8035223);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6870171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.6127649);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.5463706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.5111222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.4757081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.4340082);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.4189371);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,7.384093);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.458487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,1.744653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,1.341111);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,1.044564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.7969709);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.6820487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.6114265);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.5496511);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.4887343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.4764839);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.4455982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,6.775224);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,2.60859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,1.651039);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,1.234527);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,1.002769);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.8189365);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.6658301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.5893067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.5396491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.4992497);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.4694271);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,7.389957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,2.312811);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,1.748017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,1.28296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.9605451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.8190102);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.6566665);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.5835309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.5240518);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.4808162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,7.318472);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,2.224206);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,1.652875);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,1.229889);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.9318978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.7931305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.6537539);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.5868996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.5369934);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,7.085077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,2.202193);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,1.679199);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.200832);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.9504898);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.770232);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.6510977);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.5712707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,6.218988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,2.208572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.601876);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.199425);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.9319465);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.7358226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.6347489);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,6.593732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,2.06131);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.569036);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.172185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.916463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.729732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,6.835608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,2.101378);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.552784);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,1.157124);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.8797899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,4.092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,2.113774);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,1.452561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,1.109631);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,3.21);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,1.955335);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,1.445819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,2.5347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,1.962433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,2.0115);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(24,5.391527);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(25,3.30963);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(26,2.326171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(27,1.6914);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(28,1.35263);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(29,1.084113);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(30,0.806809);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(31,0.7228213);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(32,0.6157428);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(33,0.5690931);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(34,0.5115547);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(35,0.4686422);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(36,0.4405119);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(37,0.41074);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(38,0.3788718);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(39,0.3689726);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(40,0.3519901);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(41,0.3433284);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(42,0.327053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(43,0.3113803);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(44,0.3135218);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(47,5.448734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(48,3.415162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(49,2.415705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(50,1.63788);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(51,1.233355);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(52,0.9619021);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(53,0.7726541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(54,0.6683236);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(55,0.597613);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(56,0.5144837);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(57,0.4623882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(58,0.4238793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(59,0.3991734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(60,0.3687305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(61,0.3535345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(62,0.3334206);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(63,0.3281432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(64,0.3133122);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(65,0.2960893);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(66,0.2882351);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(67,0.2790876);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(70,5.960814);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(71,3.992268);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(72,2.62135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(73,1.834084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(74,1.3244);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(75,1.005845);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(76,0.8543699);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(77,0.6744788);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(78,0.5938432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(79,0.504384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(80,0.454671);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(81,0.4313348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(82,0.4003489);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(83,0.3688924);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(84,0.3470736);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(85,0.3357743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(86,0.3232125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(87,0.3054787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(88,0.3002527);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(89,0.29243);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(90,0.2762219);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(93,7.745135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(94,4.540952);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(95,3.085729);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(96,2.109608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(97,1.429155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(98,1.164315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(99,0.8890588);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(100,0.740405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(101,0.6326759);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(102,0.5407723);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(103,0.492217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(104,0.4518379);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(105,0.4088284);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(106,0.3831068);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(107,0.3502271);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(108,0.3474117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(109,0.3320456);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(110,0.3205495);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(111,0.3054754);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(112,0.2969722);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(113,0.2855297);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(116,16.4936);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(117,6.199843);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(118,3.703916);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(119,2.555309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(120,1.822841);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(121,1.264757);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(122,1.023891);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(123,0.7975338);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(124,0.6997734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(125,0.5909957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(126,0.5192474);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(127,0.4727913);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(128,0.4372391);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(129,0.4124885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(130,0.3819364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(131,0.3604034);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(132,0.3504903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(133,0.3218181);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(134,0.3166515);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(135,0.3088718);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(136,0.2997558);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(140,13.25571);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(141,4.963152);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(142,3.172158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(143,2.237979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(144,1.594202);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(145,1.125015);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(146,0.9602461);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(147,0.7537975);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(148,0.6402599);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(149,0.5588579);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(150,0.5027429);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(151,0.4693462);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(152,0.4260164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(153,0.4018462);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(154,0.3773903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(155,0.363601);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(156,0.3410041);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(157,0.331884);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(158,0.3267372);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(159,0.3100043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(164,11.07409);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(165,4.040449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(166,2.880111);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(167,1.99538);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(168,1.479846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(169,1.049729);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(170,0.8661184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(171,0.7038959);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(172,0.6070618);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(173,0.5512827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(174,0.4906954);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(175,0.4567291);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(176,0.4272249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(177,0.4047145);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(178,0.3745903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(179,0.3663377);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(180,0.3472);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(181,0.3365575);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(182,0.3304043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(188,10.06323);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(189,3.631376);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(190,2.521157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(191,1.793266);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(192,1.393748);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(193,1.027787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(194,0.8388167);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(195,0.6744395);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(196,0.6011672);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(197,0.5058937);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(198,0.4830587);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(199,0.4482924);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(200,0.4203629);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(201,0.3958217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(202,0.3881276);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(203,0.372925);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(204,0.3456655);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(205,0.3449662);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(212,10.06225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(213,3.26545);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(214,2.394812);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(215,1.716053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(216,1.257777);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(217,0.9667879);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(218,0.7740565);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(219,0.6741919);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(220,0.5754209);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(221,0.5284154);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(222,0.4773221);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(223,0.4470946);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(224,0.4164961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(225,0.398097);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(226,0.3806407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(227,0.364685);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(228,0.3388157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(236,8.644311);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(237,3.443572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(238,2.248596);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(239,1.594799);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(240,1.154341);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(241,0.9220017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(242,0.7723589);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(243,0.6384342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(244,0.5512831);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(245,0.5096681);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(246,0.4669937);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(247,0.4378479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(248,0.4247564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(249,0.4016801);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(250,0.3793939);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(251,0.3639709);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(260,8.490947);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(261,2.916445);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(262,2.104252);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(263,1.526525);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(264,1.141317);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(265,0.8921625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(266,0.7210572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(267,0.6325397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(268,0.5676059);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(269,0.4982927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(270,0.4695204);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(271,0.4474302);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(272,0.4176948);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(273,0.3915368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(274,0.3781573);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(284,8.088529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(285,2.83851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(286,2.004211);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(287,1.452407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(288,1.119724);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(289,0.8565102);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(290,0.7358755);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(291,0.6111652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(292,0.5648973);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(293,0.509591);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(294,0.4572401);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(295,0.4327326);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(296,0.4139976);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(297,0.3951283);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(308,7.392522);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(309,2.574957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(310,1.902318);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(311,1.387006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(312,1.080595);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(313,0.8035223);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(314,0.6870171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(315,0.6127649);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(316,0.5463706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(317,0.5111222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(318,0.4757081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(319,0.4340082);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(320,0.4189371);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(332,7.384093);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(333,2.458487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(334,1.744653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(335,1.341111);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(336,1.044564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(337,0.7969709);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(338,0.6820487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(339,0.6114265);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(340,0.5496511);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(341,0.4887343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(342,0.4764839);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(343,0.4455982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(356,6.775224);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(357,2.60859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(358,1.651039);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(359,1.234527);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(360,1.002769);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(361,0.8189365);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(362,0.6658301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(363,0.5893067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(364,0.5396491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(365,0.4992497);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(366,0.4694271);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(380,7.389957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(381,2.312811);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(382,1.748017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(383,1.28296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(384,0.9605451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(385,0.8190102);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(386,0.6566665);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(387,0.5835309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(388,0.5240518);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(389,0.4808162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(404,7.318472);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(405,2.224206);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(406,1.652875);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(407,1.229889);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(408,0.9318978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(409,0.7931305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(410,0.6537539);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(411,0.5868996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(412,0.5369934);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(428,7.085077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(429,2.202193);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(430,1.679199);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(431,1.200832);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(432,0.9504898);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(433,0.770232);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(434,0.6510977);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(435,0.5712707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(452,6.218988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(453,2.208572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(454,1.601876);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(455,1.199425);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(456,0.9319465);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(457,0.7358226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(458,0.6347489);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(476,6.593732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(477,2.06131);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(478,1.569036);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(479,1.172185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(480,0.916463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(481,0.729732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(500,6.835608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(501,2.101378);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(502,1.552784);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(503,1.157124);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(504,0.8797899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(524,4.092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(525,2.113774);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(526,1.452561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(527,1.109631);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(548,3.21);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(549,1.955335);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(550,1.445819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(572,2.5347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(573,1.962433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(596,2.0115);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4578753411769867, "alphanum_fraction": 0.6773052215576172, "avg_line_length": 80.0013198852539, "blob_id": "401d3a6cd3b6ddb11b07b924a17b1ae90ace9ce4", "content_id": "9e25f0a6ad4d82aa005d0e12bce8e4fd0c5a0154", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 61318, "license_type": "no_license", "max_line_length": 161, "num_lines": 757, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_R_firstguess.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:32 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(24,0.1060295);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(25,0.145168);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(26,0.171878);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(27,0.2100212);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(28,0.2576341);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,0.3048118);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,0.3952292);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,0.5276822);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,0.6637218);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,0.8346791);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(357,5.152938);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(358,5.667803);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(359,5.886303);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(360,6.395649);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(361,6.762368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(362,8.106313);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(363,9.172602);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(364,10.95332);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(365,13.78777);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(366,17.29794);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(380,12.39021);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(381,7.490263);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(382,7.644138);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(383,8.19602);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(384,8.496654);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(385,8.990114);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(386,10.52352);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(387,11.73621);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(388,15.07582);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(389,18.9705);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(404,18.96907);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(405,9.740091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(406,10.43134);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(407,10.46369);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(408,11.3851);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(409,12.17789);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(410,13.15302);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,15.90471);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,18.80889);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(428,25.33986);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(429,12.69053);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,13.05401);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,13.52112);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,14.97017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,15.69731);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,17.9828);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,20.24246);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(452,33.75333);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(453,18.42992);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(454,17.41797);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(455,18.11507);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,18.80515);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,20.69733);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,23.19191);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,46.63242);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,23.089);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,25.92647);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,23.90312);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,23.64228);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,27.32094);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,63.2003);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,30.35703);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,30.40924);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,30.4686);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,32.32376);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,81.56684);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,36.32804);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,38.56069);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,39.97671);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,105.8109);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,50.5128);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,52.56076);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,151.1912);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,66.1328);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,183.7567);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6 = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(24,0.1060295);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(25,0.145168);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(26,0.171878);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(27,0.2100212);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(28,0.2576341);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(29,0.3048118);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(30,0.3952292);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(31,0.5276822);\n 48134369_M_{sbottom} 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"is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 362, "license_type": "no_license", "max_line_length": 60, "num_lines": 15, "path": "/produceSystematics.sh", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "#!/bin/bash\n\nREGIONS=\"$(< Regions.txt)\" #names from names.txt file\nBINS=\"$(< Bins.txt)\" #names from names.txt file\nMASSES=\"$(< masses.txt)\" #names from names.txt file \nfor REGION in $REGIONS; do\n\techo $REGION\n\tfor BIN in $BINS; do\n\t\techo $BIN\n\t\tfor MASS in $MASSES; do\n\t\t\techo $MASS\n\t\t\tpython produceSystematicsSignal8TeV.py $REGION $BIN $MASS\n\t\tdone\n\tdone\ndone\n" }, { "alpha_fraction": 0.3822571933269501, "alphanum_fraction": 0.6039392352104187, "avg_line_length": 88.55277252197266, "blob_id": "94e966ec458eb8d05feddafe3ca1cf14934822d2", "content_id": "5cb4aaf95b1c99a992748945407ecacb86d79b26", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67881, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Sel_Eff_sbottom_neutralino2_ObsXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 09:50:02 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,5.082646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(25,3.30963);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(26,2.335433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(27,1.699339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(28,1.363114);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(29,1.06314);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(30,0.8486819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(31,0.7228213);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(32,0.6121785);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.5663301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.5087572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.4679932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,0.437936);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,0.4079806);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,0.3776933);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,0.3656851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,0.3513581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,0.3422644);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,0.325494);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,0.3107018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,0.3122411);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(47,5.448734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(48,3.415162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(49,2.248728);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(50,1.619339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(51,1.233355);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(52,0.9796363);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(53,0.7726541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(54,0.6656729);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(55,0.5826198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(56,0.5132859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(57,0.462301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(58,0.4229096);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(59,0.39654);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(60,0.3665495);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(61,0.3528624);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(62,0.3326677);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(63,0.3291961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(64,0.3114871);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(65,0.2949273);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(66,0.2881793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(67,0.2786176);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(70,6.141455);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(71,4.055606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(72,2.62135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(73,1.819858);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(74,1.329578);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(75,1.043242);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(76,0.8478979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(77,0.6691267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(78,0.5938432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(79,0.5063704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(80,0.4532978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(81,0.4297517);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(82,0.3976273);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(83,0.3671267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(84,0.3464696);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(85,0.3360592);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(86,0.3230554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(87,0.3059343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(88,0.299845);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(89,0.2917237);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(90,0.2744491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(93,7.745135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(94,4.540952);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(95,2.967848);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(96,2.109608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(97,1.506361);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(98,1.14194);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(99,0.8336285);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(100,0.740405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(101,0.6301449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(102,0.540792);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(103,0.4903015);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,0.4514866);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,0.4075348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,0.382021);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,0.3498451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,0.3455622);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,0.3307238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,0.3192346);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,0.3020621);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,0.2962312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,0.2855217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(116,16.54082);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(117,6.017507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,3.835938);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,2.578326);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,1.814078);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,1.260099);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,1.023891);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,0.8224576);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,0.6894072);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,0.588041);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,0.5185816);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,0.4693784);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,0.4359761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,0.4129023);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,0.3802279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,0.3606634);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,0.3486465);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,0.3218549);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,0.3154884);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,0.3060439);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,0.2988707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(140,13.25571);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(141,4.963152);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,3.184652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,2.305801);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,1.673894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,1.151862);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.9611868);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.7504149);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.6380479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.5562491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.4996785);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.4666391);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,0.4229174);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,0.4005374);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,0.3775463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,0.3609628);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,0.3398065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,0.3312067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,0.3251006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,0.3086077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(164,11.0945);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(165,4.040449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,2.902261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,1.99538);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,1.479846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,1.049729);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.8686457);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.7044141);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.6039912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.5519422);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.4887594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.4556987);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.4263396);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.4045381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.3726278);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.3652669);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.3454238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.334975);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.329935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,10.00897);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,3.64524);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,2.476306);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,1.821282);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,1.380017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,1.02615);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.838675);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.675164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.5989079);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.5030103);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.4815912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.4466521);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.4197004);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.3954026);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.3834736);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.3708267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.3452177);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.3426476);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,10.06855);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,3.266);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,2.385507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,1.708334);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,1.253618);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.9685761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.769664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.669773);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.572647);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.5234782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.4769194);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.445053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.4153699);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.3992905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.375478);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.3634979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.3402573);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,8.642742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.433885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,2.265368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,1.598453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,1.153739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.9128222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.7656668);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.6333996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.551529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.506864);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.464683);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.4367078);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.4248233);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.3988018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.379088);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.3632387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,8.440655);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,2.908555);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,2.09691);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,1.509259);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,1.140881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.8907126);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.7186721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.6309668);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.564941);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.5036377);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.4654295);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.4470305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.4158534);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.3921832);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.378455);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,8.087545);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,2.834857);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,1.995342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,1.45106);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,1.123711);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.8552139);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.7299274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.6068333);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.5661996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.5087006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.4557942);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.4304664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.4136554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.3953007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,7.373305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,2.569499);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.90431);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.387006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,1.069806);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.805185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6869727);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.6079083);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.5432452);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.506932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.4715405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.4331811);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.4160895);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,7.351844);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.448956);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,1.738749);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,1.33899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,1.035548);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.7954016);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.6795526);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.6063735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.5502158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.4909909);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.4738858);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.4441365);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,6.785124);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,2.607719);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,1.657064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,1.245814);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.9992309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.8166348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.6641906);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.5872238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.5364477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.497124);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.4677133);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,7.373645);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,2.3093);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,1.746315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,1.273452);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.9558219);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.8181564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.651666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.5802546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.5220857);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.4790991);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,7.292858);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,2.23001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,1.654231);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,1.221725);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.9309812);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.7913342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.650881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.5811999);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.5286343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,7.086794);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,2.198628);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,1.684653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.201966);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.9445387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.7674222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.6455357);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.5701101);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,6.218603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,2.20083);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.600384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.194651);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.9293164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.7331248);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.6326081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,6.614804);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,2.058307);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.564467);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.167894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.9140973);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.7259302);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,6.834123);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,2.107994);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.546064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,1.150982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.8781002);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,4.092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,2.111474);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,1.451944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,1.112433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,3.21);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,1.958056);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,1.446007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,2.5347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,1.955004);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,2.0115);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(24,5.082646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(25,3.30963);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(26,2.335433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(27,1.699339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(28,1.363114);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(29,1.06314);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(30,0.8486819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(31,0.7228213);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(32,0.6121785);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(33,0.5663301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(34,0.5087572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(35,0.4679932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(36,0.437936);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(37,0.4079806);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(38,0.3776933);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(39,0.3656851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(40,0.3513581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(41,0.3422644);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(42,0.325494);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(43,0.3107018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(44,0.3122411);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(47,5.448734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(48,3.415162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(49,2.248728);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(50,1.619339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(51,1.233355);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(52,0.9796363);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(53,0.7726541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(54,0.6656729);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(55,0.5826198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(56,0.5132859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(57,0.462301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(58,0.4229096);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(59,0.39654);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(60,0.3665495);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(61,0.3528624);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(62,0.3326677);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(63,0.3291961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(64,0.3114871);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(65,0.2949273);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(66,0.2881793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(67,0.2786176);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(70,6.141455);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(71,4.055606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(72,2.62135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(73,1.819858);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(74,1.329578);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(75,1.043242);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(76,0.8478979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(77,0.6691267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(78,0.5938432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(79,0.5063704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(80,0.4532978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(81,0.4297517);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(82,0.3976273);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(83,0.3671267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(84,0.3464696);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(85,0.3360592);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(86,0.3230554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(87,0.3059343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(88,0.299845);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(89,0.2917237);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(90,0.2744491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(93,7.745135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(94,4.540952);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(95,2.967848);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(96,2.109608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(97,1.506361);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(98,1.14194);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(99,0.8336285);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(100,0.740405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(101,0.6301449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(102,0.540792);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(103,0.4903015);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(104,0.4514866);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(105,0.4075348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(106,0.382021);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(107,0.3498451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(108,0.3455622);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(109,0.3307238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(110,0.3192346);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(111,0.3020621);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(112,0.2962312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(113,0.2855217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(116,16.54082);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(117,6.017507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(118,3.835938);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(119,2.578326);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(120,1.814078);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(121,1.260099);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(122,1.023891);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(123,0.8224576);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(124,0.6894072);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(125,0.588041);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(126,0.5185816);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(127,0.4693784);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(128,0.4359761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(129,0.4129023);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(130,0.3802279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(131,0.3606634);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(132,0.3486465);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(133,0.3218549);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(134,0.3154884);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(135,0.3060439);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(136,0.2988707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(140,13.25571);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(141,4.963152);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(142,3.184652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(143,2.305801);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(144,1.673894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(145,1.151862);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(146,0.9611868);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(147,0.7504149);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(148,0.6380479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(149,0.5562491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(150,0.4996785);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(151,0.4666391);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(152,0.4229174);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(153,0.4005374);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(154,0.3775463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(155,0.3609628);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(156,0.3398065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(157,0.3312067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(158,0.3251006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(159,0.3086077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(164,11.0945);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(165,4.040449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(166,2.902261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(167,1.99538);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(168,1.479846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(169,1.049729);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(170,0.8686457);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(171,0.7044141);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(172,0.6039912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(173,0.5519422);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(174,0.4887594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(175,0.4556987);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(176,0.4263396);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(177,0.4045381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(178,0.3726278);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(179,0.3652669);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(180,0.3454238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(181,0.334975);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(182,0.329935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(188,10.00897);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(189,3.64524);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(190,2.476306);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(191,1.821282);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(192,1.380017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(193,1.02615);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(194,0.838675);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(195,0.675164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(196,0.5989079);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(197,0.5030103);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(198,0.4815912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(199,0.4466521);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(200,0.4197004);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(201,0.3954026);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(202,0.3834736);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(203,0.3708267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(204,0.3452177);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(205,0.3426476);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(212,10.06855);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(213,3.266);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(214,2.385507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(215,1.708334);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(216,1.253618);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(217,0.9685761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(218,0.769664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(219,0.669773);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(220,0.572647);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(221,0.5234782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(222,0.4769194);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(223,0.445053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(224,0.4153699);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(225,0.3992905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(226,0.375478);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(227,0.3634979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(228,0.3402573);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(236,8.642742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(237,3.433885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(238,2.265368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(239,1.598453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(240,1.153739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(241,0.9128222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(242,0.7656668);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(243,0.6333996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(244,0.551529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(245,0.506864);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(246,0.464683);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(247,0.4367078);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(248,0.4248233);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(249,0.3988018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(250,0.379088);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(251,0.3632387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(260,8.440655);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(261,2.908555);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(262,2.09691);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(263,1.509259);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(264,1.140881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(265,0.8907126);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(266,0.7186721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(267,0.6309668);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(268,0.564941);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(269,0.5036377);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(270,0.4654295);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(271,0.4470305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(272,0.4158534);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(273,0.3921832);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(274,0.378455);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(284,8.087545);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(285,2.834857);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(286,1.995342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(287,1.45106);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(288,1.123711);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(289,0.8552139);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(290,0.7299274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(291,0.6068333);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(292,0.5661996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(293,0.5087006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(294,0.4557942);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(295,0.4304664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(296,0.4136554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(297,0.3953007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(308,7.373305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(309,2.569499);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(310,1.90431);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(311,1.387006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(312,1.069806);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(313,0.805185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(314,0.6869727);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(315,0.6079083);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(316,0.5432452);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(317,0.506932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(318,0.4715405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(319,0.4331811);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(320,0.4160895);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(332,7.351844);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(333,2.448956);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(334,1.738749);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(335,1.33899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(336,1.035548);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(337,0.7954016);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(338,0.6795526);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(339,0.6063735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(340,0.5502158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(341,0.4909909);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(342,0.4738858);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(343,0.4441365);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(356,6.785124);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(357,2.607719);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(358,1.657064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(359,1.245814);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(360,0.9992309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(361,0.8166348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(362,0.6641906);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(363,0.5872238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(364,0.5364477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(365,0.497124);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(366,0.4677133);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(380,7.373645);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(381,2.3093);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(382,1.746315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(383,1.273452);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(384,0.9558219);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(385,0.8181564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(386,0.651666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(387,0.5802546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(388,0.5220857);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(389,0.4790991);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(404,7.292858);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(405,2.23001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(406,1.654231);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(407,1.221725);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(408,0.9309812);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(409,0.7913342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(410,0.650881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(411,0.5811999);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(412,0.5286343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(428,7.086794);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(429,2.198628);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(430,1.684653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(431,1.201966);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(432,0.9445387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(433,0.7674222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(434,0.6455357);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(435,0.5701101);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(452,6.218603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(453,2.20083);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(454,1.600384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(455,1.194651);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(456,0.9293164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(457,0.7331248);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(458,0.6326081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(476,6.614804);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(477,2.058307);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(478,1.564467);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(479,1.167894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(480,0.9140973);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(481,0.7259302);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(500,6.834123);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(501,2.107994);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(502,1.546064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(503,1.150982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(504,0.8781002);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(524,4.092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(525,2.111474);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(526,1.451944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(527,1.112433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(548,3.21);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(549,1.958056);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(550,1.446007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(572,2.5347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(573,1.955004);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(596,2.0115);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4482265114784241, "alphanum_fraction": 0.674360454082489, "avg_line_length": 82.46415710449219, "blob_id": "63c7cb80ea9946c34a85afef760815b4a6bd9050", "content_id": "4c63c3743d05b13541e827863b40a7a4752a109d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 90809, "license_type": "no_license", "max_line_length": 155, "num_lines": 1088, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10/Fixed_Edge_sbottom_neutralino2_AcceptanceCorrected.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 11:16:28 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(37,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(38,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(39,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(40,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(41,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(42,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(43,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(44,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(45,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(49,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(50,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(51,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(52,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(53,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(54,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(57,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(58,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(59,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(60,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(61,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(62,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(63,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(64,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(65,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(66,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(67,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(68,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(69,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(70,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(71,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(72,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(73,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(74,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(75,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(76,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(77,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(78,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(79,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(80,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(81,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(82,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(85,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(86,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(87,-86.74448);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(88,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(89,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(90,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(91,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(92,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(93,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(94,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(95,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(96,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(97,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(98,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(99,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(100,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(101,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(102,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(103,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(104,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(105,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(106,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(107,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(108,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(109,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(110,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(113,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(114,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(115,-86.74448);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(116,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(117,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(118,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(119,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(120,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(121,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(122,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(123,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(124,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(125,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(126,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(127,-5265.354);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(128,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(129,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(130,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(131,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(132,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(133,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(134,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(135,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(136,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(137,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(138,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(141,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(142,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(143,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(144,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(145,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(146,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(147,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(148,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(149,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(150,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(151,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(152,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(153,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(154,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(155,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(156,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(157,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(158,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(159,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(160,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(161,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(162,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(163,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(164,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(165,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(166,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(169,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(170,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(171,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(172,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(173,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(174,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(175,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(176,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(177,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(178,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(179,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(180,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(181,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(182,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(183,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(184,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(185,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(186,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(187,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(188,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(189,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(190,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(191,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(192,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(193,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(194,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(198,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(199,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(200,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(201,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(202,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(203,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(204,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(205,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(206,-1183.432);\n 484096097_M_{sbottom} 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(575,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(576,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(577,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(578,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(579,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(-99900);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(-99900);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,-100899);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,-100799.1);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,-100699.2);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,-100599.3);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,-100499.4);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,-100399.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,-100299.6);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,-100199.7);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,-100099.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,-99999.9);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,-99900);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,-99800.1);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,-99700.2);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,-99600.3);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,-99500.4);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,-99400.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,-99300.6);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,-99200.7);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,-99100.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,-99000.9);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(19);\n palette->SetFillStyle(1001);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. [%]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4 = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(29,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(30,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(31,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(32,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(33,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(34,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(35,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(36,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(37,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(38,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(39,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(40,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(41,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(42,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(43,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(44,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(45,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(46,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(47,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(48,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(49,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(50,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(51,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(52,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(53,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(54,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(57,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(58,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(59,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(60,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(61,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(62,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(63,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(64,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(65,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(66,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(67,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(68,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(69,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(70,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(71,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(72,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(73,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(74,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(75,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(76,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(77,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(78,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(79,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(80,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(81,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(82,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(85,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(86,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(87,-86.74448);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(88,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(89,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(90,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(91,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(92,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(93,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(94,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(95,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(96,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(97,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(98,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(99,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(100,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(101,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(102,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(103,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(104,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(105,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(106,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(107,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(108,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(109,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(110,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(113,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(114,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(115,-86.74448);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(116,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(117,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(118,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(119,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(120,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(121,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(122,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(123,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(124,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(125,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(126,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(127,-5265.354);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(128,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(129,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(130,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(131,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(132,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(133,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(134,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(135,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(136,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(137,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(138,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(141,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(142,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(143,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(144,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(145,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(146,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(147,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(148,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(149,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(150,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(151,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(152,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(153,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(154,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(155,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(156,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(157,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(158,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(159,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(160,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(161,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(162,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(163,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(164,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(165,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(166,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(169,-31.57895);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(170,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(171,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(172,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(173,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(174,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(175,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(176,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(177,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(178,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(179,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(180,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(181,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(182,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(183,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(184,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(185,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(186,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(187,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(188,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(189,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(190,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(191,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(192,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(193,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(194,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(198,-52.17391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(199,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(200,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(201,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(202,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(203,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(204,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(205,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(206,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(207,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(208,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(209,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(210,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(211,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(212,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(213,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(214,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(215,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(216,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(217,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(218,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(219,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(220,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(221,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(222,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(227,-83.79888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(228,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(229,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(230,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(231,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(232,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(233,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(234,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(235,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(236,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(237,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(238,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(239,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(240,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(241,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(242,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(243,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(244,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(245,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(246,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(247,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(248,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(249,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(250,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(256,-130.1518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(257,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(258,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(259,-437.7585);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(260,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(261,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(262,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(263,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(264,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(265,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(266,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(267,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(268,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(269,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(270,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(271,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(272,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(273,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(274,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(275,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(276,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(277,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(278,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(285,-197.3684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(286,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(287,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(288,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(289,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(290,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(291,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(292,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(293,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(294,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(295,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(296,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(297,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(298,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(299,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(300,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(301,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(302,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(303,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(304,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(305,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(306,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(314,-292.6829);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(315,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(316,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(317,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(318,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(319,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(320,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(321,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(322,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(323,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(324,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(325,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(326,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(327,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(328,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(329,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(330,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(331,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(332,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(333,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(334,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(343,-425.5319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(344,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(345,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(346,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(347,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(348,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(349,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(350,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(351,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(352,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(353,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(354,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(355,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(356,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(357,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(358,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(359,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(360,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(361,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(362,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(372,-607.2875);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(373,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(374,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(375,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(376,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(377,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(378,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(379,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(380,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(381,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(382,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(383,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(384,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(385,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(386,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(387,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(388,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(389,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(390,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(401,-854.7009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(402,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(403,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(404,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(405,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(406,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(407,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(408,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(409,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(410,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(411,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(412,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(413,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(414,-30280.51);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(415,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(416,-47848.53);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(417,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(418,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(430,-1183.432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(431,-1660.526);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(432,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(433,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(434,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(435,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(436,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(437,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(438,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(439,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(440,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(441,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(442,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(443,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(444,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(445,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(446,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(459,-1630.435);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(460,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(461,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(462,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(463,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(464,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(465,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(466,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(467,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(468,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(469,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(470,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(471,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(472,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(473,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(474,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(488,-2197.802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(489,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(490,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(491,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(492,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(493,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(494,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(495,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(496,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(497,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(498,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(499,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(500,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(501,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(502,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(517,-2955.665);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(518,-3992.804);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(519,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(520,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(521,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(522,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(523,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(524,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(525,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(526,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(527,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(528,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(529,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(530,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(546,-3921.569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(547,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(548,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(549,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(550,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(551,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(552,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(553,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(554,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(555,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(556,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(557,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(558,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(575,-5172.414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(576,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(577,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(578,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(579,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(580,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(581,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(582,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(583,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(584,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(585,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(586,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(604,-6795.017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(605,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(606,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(607,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(608,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(609,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(610,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(611,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(612,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(613,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(614,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(633,-8836.524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(634,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(635,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(636,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(637,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(638,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(639,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(640,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(641,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(642,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(662,-11428.57);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(663,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(664,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(665,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(666,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(667,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(668,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(669,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(670,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(691,-14634.15);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(692,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(693,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(694,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(695,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(696,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(697,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(698,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(720,-18750);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(721,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(722,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(723,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(724,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(725,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(726,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(749,-23622.05);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(750,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(751,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(752,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(753,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(754,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(778,-30000);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(779,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(780,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(781,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(782,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(807,-37500);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(808,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(809,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(810,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(836,-47244.09);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(837,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(838,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(865,-59405.94);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(866,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(894,-73710.07);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetMinimum(-99900);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetMaximum(-99900);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetEntries(481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetDirectory(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetStats(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetLineStyle(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetNdivisions(505);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitleOffset(1.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. [%]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.5086724162101746, "alphanum_fraction": 0.5386610627174377, "avg_line_length": 35.70833206176758, "blob_id": "fd0822065bad42b6226e4507ee35e7eb5d5f6084", "content_id": "2a83630035e5cc7da1671577b75787b41a40b7d5", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6169, "license_type": "no_license", "max_line_length": 188, "num_lines": 168, "path": "/LimitTools/writeDataCards.py", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "#! /usr/bin/env python\n\nimport ROOT\n\nfrom messageLogger import messageLogger as log\nfrom optparse import OptionParser\n\n\ndef loadPickles(path):\n\tfrom glob import glob\n\timport pickle\n\tresult = {}\n\tfor pklPath in glob(path):\n\t\tpklFile = open(pklPath, \"r\")\n\t\tresult.update(pickle.load(pklFile))\n\treturn result\n\t\n\t\t\t \ndef writeDataCards():\n\tfrom ROOT import TCanvas, TPad, TH1F, TH2F, TH1I, THStack, TLegend, TMath, TF1\n\timport pickle\n\n\tlumi = 19400.\n\tprintLumi = \"19.4\"\n\tBR = \"10\"\n\t\n\tn_bins = 1\n\tn_processes = 2\n\tn_nuicance_parameters = 3\n\t\n\t\n\t\n\tTTbar_err = 0.076\n\tDY_err = 0.07\n\t\n\t\n\tpicklePath = \"/user/schomakers/GridScan/shelves\"\n\t\n\t#~ regions = [\"signalCentral\"]\n\tregions = [\"signalCentral_mll_20_70\"]\n\t#~ regions = [\"signalCentral\",\"signalCentral_100_met_cut\",\"signalCentral_150_met_cut\",\"signalCentral_2_jet_cut\",\"signalCentral_3_jet_cut\"]\n\t\n\tfor region in regions:\n\t\t\n\t\tif region == \"signalCentral_mll_20_70\":\n\t\t\tregion_label = \"Central Signal Region\"\n\t\t\tobservation = 860\n\t\t\tTTbar = 719.12\n\t\t\tDY = 10.34\n\t\t\tregion_label_2 = \"20 GeV < m_{ll} < 70 GeV\"\n\t\telif region == \"signalCentral_2_jet_cut\":\n\t\t\tregion_label = \"Central Region\"\n\t\t\tregion_label_2 = \"n_{Jets} #ge 2\"\n\t\telif region == \"signalCentral_3_jet_cut\":\n\t\t\tregion_label = \"Central Region\"\n\t\t\tregion_label_2 = \"n_{Jets} #ge 3\"\n\t\telif region == \"signalCentral_100_met_cut\":\n\t\t\tregion_label = \"Central Region\"\n\t\t\tregion_label_2 = \"#slash{E}_{T} > 100 GeV\"\n\t\telif region == \"signalCentral_150_met_cut\":\n\t\t\tregion_label = \"Central Region\"\n\t\t\tregion_label_2 = \"#slash{E}_{T} > 150 GeV\"\n\t\telif \"signalCentral\" in region:\n\t\t\tobservation = 2680.0\n\t\t\tTTbar = 2326.03\n\t\t\tDY = 66.556\n\t\t\tregion_label = \"Central Signal Region\"\n\t\t\tregion_label_2 = \"\"\n\n\t\n\t\tstep_size = 20\n\t\tm_b_min = 200\n\t\tm_b_max = 700\n\t\tm_n_min = 100\n\t\tm_n_max = 700\n\t\t\n\t\tPickles = {}\n\t\t\n\t\tm_neutr_1_fix = False\n\t\tm_neutralino_1 = \"200\"\n\t\t\n\t\t\t\n\t\trun = 0\n\t\ti = 0\n\t\twhile m_b_min + istep_size <= m_b_max:\n\t\t\tm_b = m_b_min + istep_size\n\t\t\tM_SBOTTOM = \"m_b_\"+str(m_b_min + istep_size)\n\t\t\tm_sbottom = str(m_b_min + istep_size)\n\t\t\tj = 0\n\t\t\t\n\t\t\twhile m_n_min + jstep_size <= m_n_max:\n\t\t\t\t#~ print i\n\t\t\t\tm_n = m_n_min + jstep_size\n\t\t\t\tm_neutralino_2 = str(m_n_min + jstep_size)\n\t\t\t\t#~ if m_b >= m_n:\n\t\t\t\tif m_b >= m_n and not (m_b == 320 and m_n == 260) and not (m_b == 460 and m_n == 440) and not (m_b == 480 and m_n == 160):\n\t\t\t\t\tprint \"m_b: \"+m_sbottom\n\t\t\t\t\tprint \"m_n: \"+m_neutralino_2\n\t\t\t\t\t\n\t\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\t\tm_neutralino_1 = str(m_n_min + jstep_size - 70)\n\t\t\t\t\t\n\t\t\t\t\tName= \"SF-OF_counts_SUSY_SimplifiedModel_Madgraph_FastSim_Dilepton_Edge_BR_%s_m_n_1_%s_m_b_%s_m_n_2_%s_8TeV_Scan_%s\"%(BR,m_neutralino_1,m_sbottom,m_neutralino_2,region)\n\t\t\t\t\t#~ print \"%s/%s.pkl\"%(picklePath,Name)\n\t\t\t\t\tPickles[\"%s_%s_%s\"%(m_neutralino_1,m_sbottom,m_neutralino_2)] = loadPickles(\"%s/%s.pkl\"%(picklePath,Name))\n\t\t\n\t\t\t\t\tValue = Pickles[\"%s_%s_%s\"%(m_neutralino_1,m_sbottom,m_neutralino_2)][\"Signal\"][\"val\"]\n\t\t\t\t\t\n\t\t\t\t\tif Pickles[\"%s_%s_%s\"%(m_neutralino_1,m_sbottom,m_neutralino_2)][\"Signal\"][\"val\"] > 0:\n\t\t\t\t\t\t#~ err = 1.5\n\t\t\t\t\t\terr = 1 + Pickles[\"%s_%s_%s\"%(m_neutralino_1,m_sbottom,m_neutralino_2)][\"Signal\"][\"err\"] / Pickles[\"%s_%s_%s\"%(m_neutralino_1,m_sbottom,m_neutralino_2)][\"Signal\"][\"val\"]\n\t\t\t\t\telse:\n\t\t\t\t\t\terr = 0\n\t\t\t\t\t\n\t\t\t\t\tfirstGuess = 2 TMath.Sqrt(err*2+TTbar+DY+(TTbar_errTTbar)*2+(DY_errDY)*2) / Value\n\t\t\t\t\t\n\t\t\t\t\tDataCard = open(\"DataCards/%s.txt\"%Name,'w')\n\t\t\t\t\tDataCard.write(\"# R_firstguess = %s \\n\"%str(firstGuess))\n\t\t\t\t\tDataCard.write(\"imax %s number of bins \\n\"%n_bins)\n\t\t\t\t\tDataCard.write(\"jmax %s number of processes minus 1 \\n\"%n_processes)\n\t\t\t\t\tDataCard.write(\"kmax %s number of nuisance parameters \\n\"%n_nuicance_parameters)\n\t\t\t\t\tDataCard.write(\"---------------------------------------------------------------------------------------------------------------------------------- \\n\")\n\t\t\t\t\tDataCard.write(\"bin Central \\n\")\n\t\t\t\t\tDataCard.write(\"observation %s \\n\"%observation)\n\t\t\t\t\tDataCard.write(\"---------------------------------------------------------------------------------------------------------------------------------- \\n\")\n\t\t\t\t\tDataCard.write(\"bin Central Central Central \\n\")\n\t\t\t\t\tDataCard.write(\"process SUSY ZJets ttJets \\n\")\n\t\t\t\t\tDataCard.write(\"process 0 1 2 \\n\")\n\t\t\t\t\tDataCard.write(\"rate %s %s %s \\n\"%(Value,DY,TTbar))\n\t\t\t\t\tDataCard.write(\"---------------------------------------------------------------------------------------------------------------------------------- \\n\")\n\t\t\t\t\tDataCard.write(\"Stat_signal lnN %s - - \\n\"%str(err))\n\t\t\t\t\tDataCard.write(\"R_SF/OF lnN - - %s \\n\"%(str(1+TTbar_err)))\n\t\t\t\t\tDataCard.write(\"ZJets_stat lnN - %s - \\n\"%(str(1+DY_err)))\n\n\t\n\t\t\t\tj += 1\t\t\n\t\t\ti += 1\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\n\n# This method just waits for a button to be pressed\ndef waitForInput():\n raw_input(\"Press any key to continue!\")\n return\n\n# entry point\n#-------------\nif (__name__ == \"__main__\"):\n # use option parser to allow verbose mode\n parser = OptionParser()\n parser.add_option(\"-v\", \"--verbose\", dest=\"verbose\", action=\"store_true\", default=False,\n help=\"talk about everything\")\n #~ parser.add_option(\"-b\", \"--base_path\", dest=\"base_path\", default=\"/user/schomakers/AnalysisData/PAT/Histos/sw532v0474/cutsV22DileptonTriggerSignal/TTJets/processedTrees_Simulation\",\n #~ help=\"path to the directory containing simulated events\")\n #~ parser.add_option(\"-n\", \"--nEvents\", dest=\"nEvents\", default=\"-1\",\n #~ help=\"number of events to read (default = -1 = all). use smaller numbers for tests\")\n (opts, args) = parser.parse_args()\n if (opts.verbose):\n # print out all output\n log.outputLevel = 5\n else:\n # ignore output with \"debug\" level\n log.outputLevel = 4\n\n # start\n #~ plot(opts.base_path, int(opts.nEvents), opts.observable)\n writeDataCards()\n \n" }, { "alpha_fraction": 0.38361629843711853, "alphanum_fraction": 0.6027897000312805, "avg_line_length": 88.28363800048828, "blob_id": "1796304de537181748cadce1b4876fab3973bb55", "content_id": "17efa43ae35343da95d8e425a9eb82feef5ee27a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67677, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_sbottom_neutralino2_ExpXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:43:38 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,2.107576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(25,1.359652);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(26,0.9557264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(27,0.6946082);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(28,0.5554868);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(29,0.4416825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(30,0.3611053);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(31,0.3020478);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(32,0.2599288);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.2390459);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.2147723);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.1985271);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,0.1878738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,0.1734987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,0.1603553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,0.154996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,0.1499631);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,0.1453456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,0.1400356);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,0.1332881);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,0.1333739);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(47,2.179804);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(48,1.369562);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(49,0.9178096);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(50,0.6624838);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(51,0.5107764);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(52,0.4074756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(53,0.3200944);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(54,0.28127);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(55,0.2404118);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(56,0.2123742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(57,0.1942216);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(58,0.1780195);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(59,0.1678138);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(60,0.1560975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(61,0.1490528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(62,0.141429);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(63,0.1391131);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(64,0.1326044);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(65,0.1260756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(66,0.1230102);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(67,0.1181601);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(70,2.107576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(71,1.611366);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(72,1.053864);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(73,0.7267326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(74,0.5321336);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(75,0.417249);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(76,0.3389853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(77,0.28127);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(78,0.2404118);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(79,0.2123742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(80,0.1902507);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(81,0.1794153);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(82,0.1651437);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(83,0.1551325);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(84,0.1476378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(85,0.142471);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(86,0.1367869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(87,0.1302881);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(88,0.1269494);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(89,0.1236723);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(90,0.1161316);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(93,3.155808);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(94,1.795692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(95,1.236199);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(96,0.8417904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(97,0.582832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(98,0.4515812);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(99,0.3611053);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(100,0.2937048);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(101,0.2571458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(102,0.2219068);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(103,0.2035042);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,0.1873368);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,0.1718275);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,0.1619);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,0.1476378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,0.145604);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,0.1398869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,0.1349206);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,0.1295656);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,0.1263248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,0.1222171);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(116,6.2042);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(117,2.410112);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,1.557377);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,1.027653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,0.7153664);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,0.5114746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,0.4115615);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,0.3248448);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,0.2766627);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,0.2418984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,0.2141105);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,0.192932);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,0.182525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,0.1715625);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,0.1575297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,0.1518665);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,0.1460869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,0.1360806);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,0.1330556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,0.1296415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,0.1252599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(140,4.780584);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(141,1.976692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,1.299727);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,0.869258);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,0.6338927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,0.4588693);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.3871249);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.2996406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.2580867);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.2287047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.2050528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.1905524);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,0.1764);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,0.1674172);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,0.1560415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,0.1495738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,0.1430294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,0.1391644);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,0.1359406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,0.1303311);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(164,4.105609);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(165,1.645556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,1.142311);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,0.7954044);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,0.5786726);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,0.4214002);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.3442406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.2847584);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.2459292);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.2255486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.2012499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.1860625);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.1773091);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.1654335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.1538369);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.1511344);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.1435256);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.1412456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.1384451);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,3.726103);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,1.493008);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,0.993629);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,0.7221298);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,0.5459072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.4111407);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.3342742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.2717915);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.2432646);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.2065987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.1942775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.1829603);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.1737835);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.1635262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.1580831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.1531245);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.1452244);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.1425021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,3.664456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,1.287207);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.9429264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.6829553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.4975576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.3904701);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.3062576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.2656334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.2319988);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.2116787);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.1956734);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.180046);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.1712738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.1650319);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.1557406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.1492031);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.1425021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,3.122727);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,1.343428);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.9091722);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.6327491);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.4590266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.3645835);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.3029146);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.2520588);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.2232775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.2041503);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.1894415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.1805738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.1731406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.1609755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.1571606);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.1506161);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,3.014781);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,1.158293);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.8278831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.5999674);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.4494335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.3551084);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.2901675);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.2532425);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.2267553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.205096);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.1883262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.1824056);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.1705744);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.1624656);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.1567016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,2.748348);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,1.120566);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.7961533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.5753848);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.4417798);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.3409849);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.29287);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.2422985);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.2264921);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.2053738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.1858781);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.1771175);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.1687648);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.16228);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,2.731732);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,1.009478);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.7610027);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.5536236);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.429235);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.3238);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.276206);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.2431921);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.2177738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.2044081);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.190205);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.1757281);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.1709011);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,2.643718);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,0.9810696);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.6915702);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.5308613);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.4117525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.3235318);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.2703329);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.2410262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.2183056);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.1980575);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.1903169);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.1790151);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,2.428831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,1.032685);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.6605749);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.5006825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.394177);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.3246079);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.2658262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.2327831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.2172525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.1996006);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.1881434);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,2.438194);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,0.9226551);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.6920587);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.507202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.3788829);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.3200738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.2576819);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.2329575);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.2112048);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.1932146);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,2.473793);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,0.8931038);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.6527194);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.4822125);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.37045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.3132719);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.2573875);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.2340831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.2119783);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,2.451202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,0.8787694);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.6617375);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.48205);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.3763906);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.3064653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.2566294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.2282062);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,2.232244);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,0.872575);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.6293);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.4748313);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.368195);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.2950906);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.2545767);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,2.27955);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,0.81685);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.6138062);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.465915);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.3620662);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.2931182);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,2.3126);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,0.8329809);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.609005);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.4602087);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.3458593);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,2.142531);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,0.8349825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.5726089);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.4432273);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,2.186485);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,0.7599412);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.5700085);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,2.220143);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,0.7840152);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,1.941275);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.3981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.5011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.6309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.7943282);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,1.584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,2.511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,3.162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,3.981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,5.011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,6.309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,7.943282);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(24,2.107576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(25,1.359652);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(26,0.9557264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(27,0.6946082);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(28,0.5554868);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(29,0.4416825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(30,0.3611053);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(31,0.3020478);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(32,0.2599288);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(33,0.2390459);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(34,0.2147723);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(35,0.1985271);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(36,0.1878738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(37,0.1734987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(38,0.1603553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(39,0.154996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(40,0.1499631);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(41,0.1453456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(42,0.1400356);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(43,0.1332881);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(44,0.1333739);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(47,2.179804);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(48,1.369562);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(49,0.9178096);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(50,0.6624838);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(51,0.5107764);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(52,0.4074756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(53,0.3200944);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(54,0.28127);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(55,0.2404118);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(56,0.2123742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(57,0.1942216);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(58,0.1780195);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(59,0.1678138);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(60,0.1560975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(61,0.1490528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(62,0.141429);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(63,0.1391131);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(64,0.1326044);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(65,0.1260756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(66,0.1230102);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(67,0.1181601);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(70,2.107576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(71,1.611366);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(72,1.053864);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(73,0.7267326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(74,0.5321336);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(75,0.417249);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(76,0.3389853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(77,0.28127);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(78,0.2404118);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(79,0.2123742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(80,0.1902507);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(81,0.1794153);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(82,0.1651437);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(83,0.1551325);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(84,0.1476378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(85,0.142471);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(86,0.1367869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(87,0.1302881);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(88,0.1269494);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(89,0.1236723);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(90,0.1161316);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(93,3.155808);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(94,1.795692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(95,1.236199);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(96,0.8417904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(97,0.582832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(98,0.4515812);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(99,0.3611053);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(100,0.2937048);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(101,0.2571458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(102,0.2219068);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(103,0.2035042);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(104,0.1873368);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(105,0.1718275);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(106,0.1619);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(107,0.1476378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(108,0.145604);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(109,0.1398869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(110,0.1349206);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(111,0.1295656);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(112,0.1263248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(113,0.1222171);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(116,6.2042);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(117,2.410112);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(118,1.557377);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(119,1.027653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(120,0.7153664);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(121,0.5114746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(122,0.4115615);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(123,0.3248448);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(124,0.2766627);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(125,0.2418984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(126,0.2141105);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(127,0.192932);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(128,0.182525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(129,0.1715625);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(130,0.1575297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(131,0.1518665);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(132,0.1460869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(133,0.1360806);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(134,0.1330556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(135,0.1296415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(136,0.1252599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(140,4.780584);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(141,1.976692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(142,1.299727);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(143,0.869258);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(144,0.6338927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(145,0.4588693);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(146,0.3871249);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(147,0.2996406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(148,0.2580867);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(149,0.2287047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(150,0.2050528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(151,0.1905524);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(152,0.1764);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(153,0.1674172);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(154,0.1560415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(155,0.1495738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(156,0.1430294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(157,0.1391644);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(158,0.1359406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(159,0.1303311);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(164,4.105609);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(165,1.645556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(166,1.142311);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(167,0.7954044);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(168,0.5786726);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(169,0.4214002);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(170,0.3442406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(171,0.2847584);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(172,0.2459292);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(173,0.2255486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(174,0.2012499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(175,0.1860625);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(176,0.1773091);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(177,0.1654335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(178,0.1538369);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(179,0.1511344);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(180,0.1435256);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(181,0.1412456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(182,0.1384451);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(188,3.726103);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(189,1.493008);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(190,0.993629);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(191,0.7221298);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(192,0.5459072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(193,0.4111407);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(194,0.3342742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(195,0.2717915);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(196,0.2432646);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(197,0.2065987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(198,0.1942775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(199,0.1829603);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(200,0.1737835);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(201,0.1635262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(202,0.1580831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(203,0.1531245);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(204,0.1452244);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(205,0.1425021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(212,3.664456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(213,1.287207);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(214,0.9429264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(215,0.6829553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(216,0.4975576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(217,0.3904701);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(218,0.3062576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(219,0.2656334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(220,0.2319988);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(221,0.2116787);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(222,0.1956734);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(223,0.180046);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(224,0.1712738);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(225,0.1650319);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(226,0.1557406);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(227,0.1492031);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(228,0.1425021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(236,3.122727);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(237,1.343428);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(238,0.9091722);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(239,0.6327491);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(240,0.4590266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(241,0.3645835);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(242,0.3029146);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(243,0.2520588);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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false, "is_vendor": false, "language": "C", "length_bytes": 89122, "license_type": "no_license", "max_line_length": 157, "num_lines": 1079, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:38 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,0.365607);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,0.365219);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,0.43781);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,0.410381);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,0.551442);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,0.648726);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,0.690126);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,0.882543);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(579,19.5751);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,19.1742);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,22.8736);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,25.20645);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,28.0478);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,30.7829);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,34.3105);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,40.4773);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,45.6044);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,25.3027);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,22.5673);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,23.5057);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,23.7931);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,26.1075);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,26.8476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,27.9352);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,32.6823);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,38.2948);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,43.3674);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,67.4036);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,27.7766);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,29.201);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,30.7964);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,28.5854);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,31.2414);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,32.573);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,35.9741);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,40.4813);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,47.4104);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,82.6244);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,32.7578);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,39.9377);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,40.54417);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,41.88169);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,41.54626);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,43.25506);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,45.3299);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,49.8347);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,98.8107);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,44.1602);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,50.1431);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,49.59316);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,42.3857);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,45.554);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,49.867);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,54.0866);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,97.12155);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,62.0978);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,57.367);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,59.4081);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,57.3666);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,64.2722);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,144.1);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,68.6458);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,65.8347);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,67.8447);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,71.4581);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,74.4578);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,205.787);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,137.288);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,85.2713);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,87.5142);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,83.526);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,192.259);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,102.502);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,106.2084);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,99.4965);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,297.171);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,135.321);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,130.473);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,296.3615);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,462.25);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.303813);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(508.475);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.303813);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.4403414);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.6382234);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.9250301);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,1.340723);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,1.943221);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,2.816471);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,4.082146);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,5.916593);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,8.575409);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,12.42905);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,18.01446);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,26.10985);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,37.84317);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,54.84924);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,79.49756);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,115.2224);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,167.0014);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,242.049);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,350.8217);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS} #sqrt{s} = 8 TeV\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(29,0.365607);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(30,0.365219);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(31,0.43781);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(32,0.410381);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(33,0.551442);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(34,0.648726);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(35,0.690126);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(36,0.882543);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(37,1.04694);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(38,1.28146);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(39,1.618665);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(40,1.95587);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__11->SetBinContent(66,1.09545);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(67,1.38255);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(68,1.689928);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(69,1.95675);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(70,2.48664);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(71,2.95448);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(72,3.66518);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(73,4.43986);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(74,5.38688);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(75,6.72656);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(76,8.047);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(77,10.1024);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(78,13.0598);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(79,15.20725);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(80,18.8407);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(81,22.43485);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(82,28.20255);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(85,0.33757);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(86,0.347646);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(87,0.424894);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(88,0.427778);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(89,0.443804);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(90,0.5371352);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(153,2.29416);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(154,2.680387);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(155,3.060195);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(156,3.53252);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(157,4.363438);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(158,5.1905);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(159,6.38181);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(160,7.75472);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(161,9.4451);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(162,11.8849);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(163,14.8755);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(232,1.14359);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(233,1.18711);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(234,1.44474);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(235,1.55669);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(236,1.83301);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(237,2.27709);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(238,2.58232);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(239,3.13673);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(240,3.84512);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(241,4.89273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(242,5.6413);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(290,1.88417);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(291,2.11198);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(292,2.20637);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(293,2.79554);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(294,2.93593);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(295,3.57154);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(296,4.34815);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(297,5.1245);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(298,6.38695);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(299,7.42093);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(300,9.45076);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__11->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitle(\"Observed R\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4598800837993622, "alphanum_fraction": 0.6759116649627686, "avg_line_length": 79.63672637939453, "blob_id": "6fd205b0ae5c3756a27e92518badc5e45816f3c9", "content_id": "0bea755113274141f68b467972ed637ff730f589", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 61042, "license_type": "no_license", "max_line_length": 163, "num_lines": 757, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_ExpR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:32 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n 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[GeV]->SetBinContent(549,52.9578);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,53.5185);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,48.1983);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,67.5644);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,183.056);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.07811703);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(201.3616);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.07811703);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.1156931);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.171344);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.2537642);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.3758304);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.5566131);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.8243564);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,1.22089);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,1.808165);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,2.677933);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,3.966077);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,5.873848);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,8.699299);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,12.88386);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,19.08127);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,28.25979);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,41.85337);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,61.98577);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,91.8023);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,135.9612);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12 = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(24,0.106029);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(25,0.145168);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(26,0.146528);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(27,0.210021);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(28,0.243964);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(29,0.274038);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(30,0.354426);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(31,0.478279);\n 48134369_M_{sbottom} 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48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(44,13.1242);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(47,0.0867967);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(48,0.130821);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(49,0.131265);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(50,0.174318);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(51,0.190724);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(52,0.248759);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(53,0.336913);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(54,0.40998);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(55,0.51291);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(56,0.673196);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",41,193.75,706.25,49,93.75,706.25);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(32);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(43);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(32);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(43);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(32);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(43);\n 92487219_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(23);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,343.75,100);\n graph->SetPoint(1,343.75,112.5);\n graph->SetPoint(2,343.75,125);\n graph->SetPoint(3,343.75,137.5);\n graph->SetPoint(4,343.6045,149.8544999);\n graph->SetPoint(5,342.7837813,161.5337812);\n graph->SetPoint(6,340.5482846,171.7982846);\n graph->SetPoint(7,336.5337813,180.2837812);\n graph->SetPoint(8,331.1045,187.3545);\n graph->SetPoint(9,325,193.75);\n graph->SetPoint(10,318.75,200);\n graph->SetPoint(11,312.3545,206.1045);\n graph->SetPoint(12,305.2837812,211.5337813);\n graph->SetPoint(13,296.7982846,215.5482846);\n graph->SetPoint(14,286.5337812,217.7837813);\n graph->SetPoint(15,274.8544999,218.6045);\n graph->SetPoint(16,262.5,218.75);\n graph->SetPoint(17,250.1197198,218.6045);\n graph->SetPoint(18,238.3465809,217.8095615);\n graph->SetPoint(19,227.8055396,215.8392028);\n graph->SetPoint(20,219.1515959,212.8960939);\n graph->SetPoint(21,210.9088591,210.0175204);\n graph->SetPoint(22,200,208.2979194);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Observed limit\",100,185.625,358.125);\n Graph_Graph1->SetMinimum(88.125);\n Graph_Graph1->SetMaximum(230.625);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n \n graph = new TGraph(44);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,431.3955001,100);\n graph->SetPoint(1,432.2162188,111.8472832);\n graph->SetPoint(2,434.3062154,122.0892847);\n graph->SetPoint(3,437.3545,131.1044999);\n graph->SetPoint(4,439.7275659,139.5899966);\n graph->SetPoint(5,439.7275659,147.9100034);\n graph->SetPoint(6,437.3545,156.3955001);\n graph->SetPoint(7,434.3062154,165.5562153);\n graph->SetPoint(8,432.0707187,175.8207187);\n graph->SetPoint(9,430.4292813,186.6792813);\n graph->SetPoint(10,428.1937847,196.9437847);\n graph->SetPoint(11,425,206.25);\n graph->SetPoint(12,421.6607153,215.4107153);\n graph->SetPoint(13,418.75,225);\n graph->SetPoint(14,415.6937847,234.4437847);\n graph->SetPoint(15,411.3882812,242.6382812);\n graph->SetPoint(16,405.2837812,249.0337812);\n graph->SetPoint(17,397.7645034,254.0145034);\n graph->SetPoint(18,389.7354966,258.4854967);\n graph->SetPoint(19,382.0707187,263.3207187);\n graph->SetPoint(20,375,268.75);\n graph->SetPoint(21,367.9292813,274.1792813);\n graph->SetPoint(22,360.2645034,279.0145034);\n graph->SetPoint(23,352.2354966,283.1944965);\n graph->SetPoint(24,344.5707187,286.3882812);\n graph->SetPoint(25,337.5,287.6375693);\n graph->SetPoint(26,330.2837812,286.5337813);\n graph->SetPoint(27,321.7982846,284.1864956);\n graph->SetPoint(28,311.5337812,282.3616369);\n graph->SetPoint(29,299.9742197,281.6203136);\n graph->SetPoint(30,288.4663008,280.7041682);\n graph->SetPoint(31,278.6521205,277.8192331);\n graph->SetPoint(32,271.2403284,272.4595163);\n graph->SetPoint(33,265.2476175,265.9264469);\n graph->SetPoint(34,259.0735531,259.7523825);\n graph->SetPoint(35,252.3949836,253.930952);\n graph->SetPoint(36,246.069048,247.6050164);\n graph->SetPoint(37,240.2476175,240.9264469);\n graph->SetPoint(38,234.0735531,234.7523825);\n graph->SetPoint(39,227.3949836,228.930952);\n graph->SetPoint(40,221.069048,222.6050164);\n graph->SetPoint(41,216.0159851,216.0977273);\n graph->SetPoint(42,210.192052,211.0095194);\n graph->SetPoint(43,200,208.4434195);\n \n TH1F Graph_Graph2 = new TH1F(\"Graph_Graph2\",\"Expected limit\",100,176.0272,463.7003);\n Graph_Graph2->SetMinimum(81.23624);\n Graph_Graph2->SetMaximum(306.4013);\n Graph_Graph2->SetDirectory(0);\n Graph_Graph2->SetStats(0);\n Graph_Graph2->SetLineStyle(0);\n Graph_Graph2->GetXaxis()->SetNdivisions(505);\n Graph_Graph2->GetXaxis()->SetLabelFont(42);\n Graph_Graph2->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetXaxis()->SetTitleSize(32);\n Graph_Graph2->GetXaxis()->SetTitleFont(43);\n Graph_Graph2->GetYaxis()->SetLabelFont(42);\n Graph_Graph2->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetYaxis()->SetTitleSize(32);\n Graph_Graph2->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph2->GetYaxis()->SetTitleFont(43);\n Graph_Graph2->GetZaxis()->SetLabelFont(42);\n Graph_Graph2->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetZaxis()->SetTitleSize(32);\n Graph_Graph2->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph2->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph2);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.44657930731773376, "alphanum_fraction": 0.6847080588340759, "avg_line_length": 82.69457244873047, "blob_id": "b162ee09798e194e1404aa6e49d01cdd3609ef93", "content_id": "d44d46fd96e2a5e0d6fd731922ea97c02321ba1d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 90976, "license_type": "no_license", "max_line_length": 157, "num_lines": 1087, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_ObsXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:24 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,13.57219);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,8.5606);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,6.121511);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,3.682422);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,3.222066);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,2.553075);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,1.884084);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,1.687227);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(37,1.424786);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(38,1.255494);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(39,1.010149);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(40,1.036313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(41,0.8973534);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(42,0.801105);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(43,0.7514689);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(44,0.7290543);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(45,0.6795025);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,0.5983425);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,0.6071403);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,0.5690336);\n 284060385_M_{sbottom} 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(75,0.5373132);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(76,0.4990144);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(77,0.4759249);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(78,0.455634);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(79,0.4569088);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(80,0.4278579);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(81,0.4386491);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(82,0.4263341);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(85,12.50189);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(86,7.636563);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(87,5.885577);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(88,3.797202);\n 284060385_M_{sbottom} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(115,5.628405);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(116,3.644085);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(117,2.954482);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(118,2.159839);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(119,1.658738);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(120,1.430673);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(121,1.149258);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(122,1.017609);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(123,0.8778309);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(124,0.7883667);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(125,0.7519972);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(126,0.6845251);\n 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,2.65152);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,2.037344);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,1.674343);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,1.392588);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,1.168269);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,8.07088);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,2.55568);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,2.10124);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,1.719969);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,1.313666);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,6.037616);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,2.51808);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.998073);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,1.571818);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,7.440701);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,2.65225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,2.068757);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,7.964113);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,2.591491);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,7.40626);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(29,13.57219);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(30,8.5606);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(31,6.121511);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(32,3.682422);\n 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(387,0.5802176);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(388,0.5485422);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(389,0.5253293);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(390,0.5158611);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(401,10.15682);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(402,4.346273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(403,3.241535);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(404,2.347773);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(405,1.854236);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(406,1.448702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__19->SetBinContent(407,1.181727);\n 284060385_M_{sbottom} 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280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.446927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,2.292451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,1.613107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,1.16335);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.9149199);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.7652067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.63397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.5519232);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.5065975);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.4680948);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.7250704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.6311932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.566765);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.5069614);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.4678756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.4496972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.4196433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.3973649);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.3823929);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,8.138707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,2.831976);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,2.014182);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,1.45583);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,1.12735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.8628358);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.7348568);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.6083966);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.5670136);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.5115256);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.4624778);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.4363567);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.4158513);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.401254);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,7.427559);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,2.572701);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.91879);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.399637);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,1.08968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.8141268);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6963087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.6129345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.5483488);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.5093722);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.4731433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.4369738);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.4253518);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,7.441533);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.452209);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,1.748187);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,1.34893);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,1.039798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.8073463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.6871405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.6083763);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.5519972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.4965442);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.4739382);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.4462982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,6.786224);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,2.625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,1.660807);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,1.25017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,1.003957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.8160853);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.6683863);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.5860972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.5433567);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.4976968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.471442);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,7.384938);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,2.325161);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,1.774655);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,1.28155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.9644521);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.8211613);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.6500278);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.5868308);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.5280625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.4840205);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,7.291406);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,2.250314);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,1.651675);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,1.218815);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.9411988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.7906972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.6537058);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.5874674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.5301107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,7.098581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,2.206863);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,1.674542);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.214011);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.9420057);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.7724116);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.6521614);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.5762143);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,6.236606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,2.197421);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.598673);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.202025);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.9329116);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.7419236);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.6390669);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,6.641687);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,2.067928);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.581394);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.180338);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.9214649);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.735458);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,6.831225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,2.122725);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.558187);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,1.156457);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.8800312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,6.29145);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,2.126625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,1.457453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,1.118897);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,6.486875);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,1.959112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,1.454147);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,6.489888);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,1.969594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,5.829159);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(24,5.257565);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(25,3.357874);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(26,2.372741);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(27,1.696968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(28,1.342973);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(29,1.064389);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(30,0.8691165);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(31,0.7267104);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(32,0.6183361);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(33,0.5662592);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(34,0.5093319);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(35,0.469706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(36,0.4395325);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(37,0.4101273);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(38,0.3782085);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(39,0.3656489);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(40,0.3532856);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(41,0.3420639);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(42,0.3301913);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(43,0.3128749);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(44,0.3132509);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(47,5.451095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(48,3.394254);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(49,2.28854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(50,1.619712);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(51,1.259516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(52,0.993206);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(53,0.7805007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(54,0.6829056);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(55,0.5788757);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(56,0.5060384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(57,0.4648567);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(58,0.4234186);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(59,0.3980006);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(60,0.3704728);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(61,0.3527735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(62,0.3329775);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(63,0.3287369);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(64,0.3122332);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(65,0.2967538);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(66,0.2891163);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(67,0.2797259);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(70,6.018783);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(71,4.103664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(72,2.65557);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(73,1.827504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(74,1.326793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(75,1.026276);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(76,0.8320039);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(77,0.6882408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(78,0.5825464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(79,0.5111552);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(80,0.4574599);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(81,0.4315746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(82,0.3969636);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(83,0.3704728);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(84,0.350464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(85,0.3382682);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(86,0.3232894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(87,0.3079639);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(88,0.3001029);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(89,0.2917524);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(90,0.2755353);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(93,7.966985);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(94,4.52931);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(95,3.13055);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(96,2.127204);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(97,1.468158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(98,1.132771);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(99,0.8986551);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(100,0.7210944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(101,0.632652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(102,0.5406752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(103,0.4945385);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(104,0.4561125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(105,0.4111705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(106,0.3857335);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(107,0.3527735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(108,0.3471087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(109,0.3342019);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(110,0.3207583);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(111,0.3067904);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(112,0.2996776);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(113,0.2881072);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(116,16.69519);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(117,5.988148);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(118,3.912108);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(119,2.614716);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(120,1.80454);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(121,1.286348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(122,1.024384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(123,0.8033688);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(124,0.6792704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(125,0.5970912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(126,0.520427);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(127,0.469706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(128,0.4395325);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(129,0.4131716);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(130,0.3805477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(131,0.3656489);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(132,0.3505619);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(133,0.3250139);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(134,0.3168163);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(135,0.3075943);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(136,0.2985803);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(140,13.03859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(141,4.911725);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(142,3.264732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(143,2.203941);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(144,1.60359);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(145,1.157686);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(146,0.9679176);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(147,0.749198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(148,0.6431424);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(149,0.561204);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(150,0.5024);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(151,0.4678425);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(152,0.4253489);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(153,0.4059827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(154,0.3797802);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(155,0.3587506);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(156,0.3441918);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(157,0.334375);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(158,0.3260807);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(159,0.3111522);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(164,11.09078);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(165,4.123872);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(166,2.902253);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(167,1.975762);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(168,1.46822);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(169,1.066759);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(170,0.8710666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(171,0.712416);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(172,0.6093776);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(173,0.5582377);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(174,0.4921602);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(175,0.4573926);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(176,0.4291081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(177,0.4009658);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(178,0.3723869);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(179,0.3655111);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(180,0.3460808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(181,0.336642);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(182,0.3321054);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(188,10.06859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(189,3.675506);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(190,2.463398);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(191,1.826849);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(192,1.387433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(193,1.028725);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(194,0.8379744);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(195,0.6797414);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(196,0.6072438);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(197,0.5083892);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(198,0.4833085);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(199,0.449924);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(200,0.4221739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(201,0.3969356);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(202,0.383625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(203,0.3694817);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(204,0.3498393);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(205,0.3425853);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(212,10.07954);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(213,3.317039);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(214,2.389218);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(215,1.71653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(216,1.250988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(217,0.9762592);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(218,0.7741921);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(219,0.6698434);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(220,0.5772461);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(221,0.5260073);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(222,0.4834721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(223,0.4469092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(224,0.4187606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(225,0.4017389);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(226,0.3795183);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(227,0.3630451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(228,0.3446772);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(236,8.757812);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(237,3.446927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(238,2.292451);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(239,1.613107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(240,1.16335);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(241,0.9149199);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(242,0.7652067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(243,0.63397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(244,0.5519232);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(245,0.5065975);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(246,0.4680948);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(247,0.4433269);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(248,0.4283778);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(249,0.3945625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(250,0.381523);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(251,0.3656304);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(260,8.402596);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(261,2.928744);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(262,2.100581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(263,1.501584);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(264,1.144598);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(265,0.8959129);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(266,0.7250704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(267,0.6311932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(268,0.566765);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(269,0.5069614);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(270,0.4678756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(271,0.4496972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(272,0.4196433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(273,0.3973649);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(274,0.3823929);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(284,8.138707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(285,2.831976);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(286,2.014182);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(287,1.45583);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(288,1.12735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(289,0.8628358);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(290,0.7348568);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(291,0.6083966);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(292,0.5670136);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(293,0.5115256);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(294,0.4624778);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(295,0.4363567);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(296,0.4158513);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(297,0.401254);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(308,7.427559);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(309,2.572701);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(310,1.91879);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(311,1.399637);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(312,1.08968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(313,0.8141268);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(314,0.6963087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(315,0.6129345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(316,0.5483488);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(317,0.5093722);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(318,0.4731433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(319,0.4369738);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(320,0.4253518);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(332,7.441533);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(333,2.452209);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(334,1.748187);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(335,1.34893);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(336,1.039798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(337,0.8073463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(338,0.6871405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(339,0.6083763);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(340,0.5519972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(341,0.4965442);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(342,0.4739382);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(343,0.4462982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(356,6.786224);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(357,2.625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(358,1.660807);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(359,1.25017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(360,1.003957);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(361,0.8160853);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(362,0.6683863);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(363,0.5860972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(364,0.5433567);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(365,0.4976968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(366,0.471442);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(380,7.384938);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(381,2.325161);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(382,1.774655);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(383,1.28155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(384,0.9644521);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(385,0.8211613);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(386,0.6500278);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(387,0.5868308);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(388,0.5280625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(389,0.4840205);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(404,7.291406);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(405,2.250314);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(406,1.651675);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(407,1.218815);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(408,0.9411988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(409,0.7906972);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(410,0.6537058);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(411,0.5874674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(412,0.5301107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(428,7.098581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(429,2.206863);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(430,1.674542);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(431,1.214011);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(432,0.9420057);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(433,0.7724116);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(434,0.6521614);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(435,0.5762143);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(452,6.236606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(453,2.197421);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(454,1.598673);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(455,1.202025);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(456,0.9329116);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(457,0.7419236);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(458,0.6390669);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(476,6.641687);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(477,2.067928);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(478,1.581394);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(479,1.180338);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(480,0.9214649);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(481,0.735458);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(500,6.831225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(501,2.122725);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(502,1.558187);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(503,1.156457);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(504,0.8800312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(524,6.29145);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(525,2.126625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(526,1.457453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(527,1.118897);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(548,6.486875);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(549,1.959112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(550,1.454147);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(572,6.489888);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(573,1.969594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(596,5.829159);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.38973695039749146, "alphanum_fraction": 0.5963212847709656, "avg_line_length": 86.718994140625, "blob_id": "0aae4cf7ae189d7deedc6a542fac697e842b5bfc", "content_id": "1ff364370c013e422ee492eaeb91e6ab4ae0fb93", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 66491, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_sbottom_neutralino2_ExpR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:43:38 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n 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[GeV]->SetBinContent(428,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,19.4134);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,19.1775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,19.263);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,20.1849);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,21.2064);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,23.9273);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,27.9458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,25.9908);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,26.0711);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,25.2816);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,26.0513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,27.1832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,30.0732);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,66.5384);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,33.1169);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,32.2065);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,33.4183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,34.9066);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,93.0709);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,60.6815);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,71.5603);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1023975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(102.378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1023975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1446389);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.204306);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2885871);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.4076363);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.575796);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.8133258);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,1.148842);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,1.622767);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,2.292198);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,3.237785);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,4.573449);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,6.460107);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,9.125057);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,12.88936);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,18.20653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,25.71717);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,36.32612);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,51.31152);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,72.47876);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(24,0.125991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(25,0.144681);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(26,0.171634);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(27,0.211128);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(28,0.290375);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(29,0.355839);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(30,0.438501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(31,0.589831);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(32,0.711893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(33,0.95116);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(34,1.21508);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(35,1.60714);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(36,2.1605);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(37,2.73047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(38,3.56894);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(39,4.53557);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(40,6.19135);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(41,7.73748);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(42,9.91663);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(43,12.6706);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(44,16.3307);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(47,0.119349);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(48,0.149586);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(49,0.164613);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(50,0.204683);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(51,0.234456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(52,0.328946);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(53,0.422104);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(54,0.515121);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(55,0.676617);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(56,0.859184);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(57,1.12652);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(58,1.45922);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(59,1.942);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(60,2.60427);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(61,3.3118);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(62,4.20232);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(63,5.52292);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(64,7.41606);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(65,9.21548);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(66,11.7376);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(67,15.0429);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(70,0.113775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(71,0.154715);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(72,0.208756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(73,0.201299);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(74,0.277688);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(75,0.341533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(76,0.416842);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(77,0.520415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(78,0.685492);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(79,0.835577);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(80,1.10727);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(81,1.50486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(82,1.96749);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(83,2.52863);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(84,3.27805);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(85,4.18314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(86,5.27304);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(87,7.09872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(88,8.82582);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(89,11.4743);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(90,14.4012);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(93,0.176542);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(94,0.200487);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(95,0.219987);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(96,0.249206);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(97,0.29698);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(98,0.368659);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(99,0.482184);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(100,0.543965);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(101,0.714579);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(102,0.891426);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(103,1.19755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(104,1.4785);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(105,1.98523);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(106,2.57808);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(107,3.30463);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(108,4.35007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(109,5.53129);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(110,7.3121);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(111,9.28318);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(112,12.1024);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(113,15.0157);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(116,0.350167);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(117,0.264839);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(118,0.284188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(119,0.349249);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(120,0.362512);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(121,0.401189);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(122,0.50528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(123,0.581574);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(124,0.756387);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(125,1.01271);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(126,1.22334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(127,1.65096);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(128,2.06833);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(129,2.81599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(130,3.43499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(131,4.57177);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(132,5.96352);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(133,7.32458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(134,9.11547);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(135,11.7772);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(136,15.2609);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(140,0.482347);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(141,0.352353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(142,0.403564);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(143,0.430212);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(144,0.505959);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(145,0.579213);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(146,0.72907);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(147,0.820033);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(148,1.03748);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(149,1.3035);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(150,1.72082);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(151,2.1619);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(152,2.85872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(153,3.64709);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(154,4.71899);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(155,6.12381);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(156,7.73977);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(157,10.1619);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(158,12.6027);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(159,15.3691);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(164,0.744737);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(165,0.495067);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(166,0.559492);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(167,0.620132);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(168,0.710797);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(169,0.860659);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(170,0.96879);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(171,1.1029);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(172,1.40646);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(173,1.86549);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(174,2.33114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(175,2.97428);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(176,3.8618);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(177,4.87589);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(178,6.30343);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(179,8.21255);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(180,10.2988);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(181,13.2635);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(182,17.4205);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(188,1.12978);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(189,0.746164);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(190,0.784254);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(191,0.872029);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(192,1.03425);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(193,1.18289);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(194,1.37506);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(195,1.62168);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(196,2.02639);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(197,2.41532);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(198,3.11625);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(199,4.0254);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(200,5.15569);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(201,6.57103);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(202,8.42978);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(203,10.6429);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(204,12.9972);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(205,17.975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(212,1.88758);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(213,1.04097);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(214,1.13143);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(215,1.23636);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(216,1.42609);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(217,1.5869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(218,1.72766);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(219,2.23686);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(220,2.66631);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(221,3.35415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(222,4.40676);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(223,5.39768);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(224,6.70558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(225,8.94595);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(226,11.481);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(227,14.0847);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(228,17.5627);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(236,2.48989);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(237,1.66351);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(238,1.71798);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(239,1.75368);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(240,1.87268);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(241,2.10456);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(242,2.54546);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(243,2.86762);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(244,3.67213);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(245,4.45693);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(246,5.65863);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(247,7.01918);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(248,9.1782);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(249,11.1752);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(250,13.8106);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(251,18.2624);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(260,3.66771);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(261,2.1787);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(262,2.30859);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(263,2.39222);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(264,2.63033);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(265,3.0324);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(266,3.41955);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(267,3.99423);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(268,5.0781);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(269,6.1365);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(270,7.5566);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(271,9.83813);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(272,12.0775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(273,15.4027);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(274,19.5919);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(284,5.0571);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(285,3.0483);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(286,3.16578);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(287,3.36893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(288,3.71777);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(289,3.83454);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(290,4.65209);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(291,5.41455);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(292,6.89951);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(293,8.3856);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(294,10.18);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(295,12.1198);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(296,15.5366);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(297,19.9663);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(308,7.69753);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(309,4.22062);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(310,4.48428);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(311,4.58055);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(312,4.91171);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(313,5.04559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(314,5.95066);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(315,7.33444);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(316,8.80306);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(317,10.8524);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(318,13.0303);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(319,16.2324);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(320,21.0696);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(332,11.2817);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(333,5.89505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(334,5.7074);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(335,6.19739);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(336,6.64753);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(337,7.28547);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(338,8.13767);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(339,9.62836);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(340,11.6493);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(341,14.4612);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(342,17.693);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(343,21.9622);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(356,14.2239);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(357,8.46307);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(358,7.70505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(359,8.05979);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(360,8.75262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(361,9.76011);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(362,11.816);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(363,12.0692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(364,15.4058);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(365,17.8458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(366,22.8341);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(380,20.5781);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(381,10.9599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(382,11.0531);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(383,11.3361);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(384,10.871);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(385,13.2389);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(386,13.8908);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(387,16.6998);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(388,19.7521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(389,23.4455);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(404,29.2289);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(405,14.1067);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(406,13.9778);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(407,14.0799);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(408,14.3519);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(409,16.043);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(410,17.6335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(411,22.0061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(412,26.0081);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(428,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(429,19.4134);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(430,19.1775);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(431,19.263);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(432,20.1849);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(433,21.2064);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(434,23.9273);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(435,27.9458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(452,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(453,25.9908);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(454,26.0711);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(455,25.2816);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(456,26.0513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(457,27.1832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(458,30.0732);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(476,66.5384);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(477,33.1169);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(478,32.2065);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(479,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(480,33.4183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(481,34.9066);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(500,93.0709);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(501,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(502,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(503,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(504,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(524,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(525,60.6815);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(526,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(527,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(548,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(549,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(550,71.5603);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(572,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(573,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(596,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetMinimum(0.1023975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetMaximum(102.378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetDirectory(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitle(\"Expected R\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.37960106134414673, "alphanum_fraction": 0.6076949834823608, "avg_line_length": 88.92729949951172, "blob_id": "189db64244a143815a6933c36da1bfc8e4392cdc", "content_id": "3777be373203860a7ad42cb4808e9dff8a48bf78", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 60611, "license_type": "no_license", "max_line_length": 180, "num_lines": 674, "path": "/LimitPlotting/results/Fixed_Neutralino_sbottom_neutralino2_ObsXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:39:08 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,22.5,881.8548,789.1667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,0.06527654);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,0.0645923);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,0.06060533);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,0.4881977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,0.1620981);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,0.1163263);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,0.08678824);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.07868118);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.06905489);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.06641176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.0624353);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.05702777);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.05637091);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.05345992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.05293299);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.04860056);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.04768084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.04611463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.04547542);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.04439997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,0.2760221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,0.1029485);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,0.07512774);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.05908893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.05382153);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.05087436);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.04824409);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.04496373);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.04323965);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.04150378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.04089463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.03903396);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.03712745);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.03775817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.03585013);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.03512964);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.1746489);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.07361272);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.05537572);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.04564838);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.04281361);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.0409743);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.03926676);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.0352607);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.0356578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.03451556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.03364095);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.03336882);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.03208636);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.03124878);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.03027885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.1121477);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.0595303);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.04566618);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.03866971);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.03760205);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.03433615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.03223116);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.03223071);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.03143441);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.03032321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.0288286);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.02940227);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.02805868);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.02757551);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.08281863);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.05035787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.03832148);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.03447663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.03242532);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.02992428);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.0296489);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.02864808);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.02799548);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.0270488);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.02735434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.0263389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.02601852);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.06923335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.04439318);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.03482737);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.03078047);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.02928718);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.02777214);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.02726629);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.026443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.0258777);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.0254823);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.02487589);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.02418759);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.05408186);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.03958255);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.03194188);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.02842702);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.02631177);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.02555841);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.02494062);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.02453613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.02441716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.02340492);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.02339372);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.0488456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.03723149);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.02950796);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.0266527);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.02510521);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.02417449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.0236604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.02322525);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.02277224);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.02283669);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.04252966);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.03391048);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.02774687);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.02513727);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.02403916);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.02285916);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.02238765);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.02211113);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.02195973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.03857979);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.03263452);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.02612902);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.02426668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.02257732);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.02220952);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.02164398);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.02133568);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.03617804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.03011451);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.02538206);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.02308523);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.02216639);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.02137766);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.02109177);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.03314516);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.02985697);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.02446145);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.02233642);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.02099167);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.02060015);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.03076638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.02857604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.02422898);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.02167506);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.02076226);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.02974602);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.0275421);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.02338338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.02107141);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.02791805);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.02669816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.02206099);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.02732171);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.02643695);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.02581583);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.02481893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.03079896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.03821987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.04742881);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.05885662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.07303792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.09063615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.1124746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.139575);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.1732051);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.2149382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.2667269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,0.3309938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,0.4107456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,0.5097133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,0.6325269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,0.7849321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,0.9740587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,1.208755);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(24,1.808509);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(25,1.181351);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(26,0.7068194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(27,0.4664856);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(28,0.3316753);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(29,0.2486954);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(30,0.1960229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(31,0.1688624);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(32,0.1463358);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(33,0.1232882);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(34,0.10529);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(35,0.101548);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(36,0.09474818);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(37,0.08908273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(38,0.08486912);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(39,0.08093689);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(40,0.07848877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(41,0.07313105);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(42,0.07413751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(43,0.07354788);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(44,0.07010082);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(47,1.366569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(48,0.8171945);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(49,0.5457817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(50,0.3788581);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(51,0.2828571);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(52,0.2135964);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(53,0.1761117);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(54,0.1449633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(55,0.1260557);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(56,0.1096442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(57,0.101511);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(58,0.08801715);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(59,0.08360781);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(60,0.0804446);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(61,0.07675663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(62,0.07421347);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(63,0.07173821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(64,0.06946008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(65,0.06930903);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(66,0.0654724);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(67,0.06482875);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(70,1.781711);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(71,1.165505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(72,0.7430578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(73,0.5112631);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(74,0.3659985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(75,0.2846641);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(76,0.2290052);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(77,0.1927818);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(78,0.1650964);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(79,0.1430918);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(80,0.1310121);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(81,0.1174567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(82,0.1095107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(83,0.1021927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(84,0.09605769);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(85,0.09422441);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(86,0.08884005);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(87,0.08589378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(88,0.08693101);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(89,0.08167695);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(90,0.07894816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(94,1.309527);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(95,0.8453885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(96,0.5541459);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(97,0.396709);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(98,0.3161031);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(99,0.2686154);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(100,0.2352572);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(101,0.2057519);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(102,0.1883299);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(103,0.1693755);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(104,0.1599944);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(105,0.1463444);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(106,0.1339869);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(107,0.1308653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(108,0.125071);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(109,0.1181755);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(110,0.1158887);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(111,0.1100013);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(112,0.1106337);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(113,0.1051745);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(118,0.9803723);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(119,0.692766);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(120,0.4584313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(121,0.3607826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(122,0.2958989);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(123,0.2483057);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(124,0.2138545);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(125,0.1913318);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(126,0.179546);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(127,0.1636259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(128,0.1483401);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(129,0.1403721);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(130,0.1306112);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(131,0.1275372);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(132,0.1220956);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(133,0.115909);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(134,0.1121538);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(135,0.1081891);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(136,0.105542);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(142,0.7602534);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(143,0.3145417);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(144,0.2208287);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(145,0.158406);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(146,0.1310778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(147,0.1215735);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(148,0.1115409);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(149,0.09839495);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(150,0.0899602);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(151,0.08343357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(152,0.08151107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(153,0.07755142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(154,0.07487077);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(155,0.06827515);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(156,0.06744827);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(157,0.06527654);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(158,0.0645923);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(159,0.06060533);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(166,0.4881977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(167,0.1620981);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(168,0.1163263);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(169,0.08678824);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(170,0.07868118);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(171,0.06905489);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(172,0.06641176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(173,0.0624353);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(174,0.05702777);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(175,0.05637091);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(176,0.05345992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(177,0.05293299);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(178,0.04860056);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(179,0.04768084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(180,0.04611463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(181,0.04547542);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(182,0.04439997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(190,0.2760221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(191,0.1029485);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(192,0.07512774);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(193,0.05908893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(194,0.05382153);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(195,0.05087436);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(196,0.04824409);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(197,0.04496373);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(198,0.04323965);\n 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c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.38440656661987305, "alphanum_fraction": 0.6015160083770752, "avg_line_length": 87.93535614013672, "blob_id": "bfaf227c51ec0ae7c4d69e0931f89de5b5a843aa", "content_id": "3e4ffa598f13bac610db39a63d428b4d9fe756b8", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67413, "license_type": "no_license", "max_line_length": 181, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Sel_Eff_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 09:50:02 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.960799);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,1.10443);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,1.34122);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,1.61067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,1.96839);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,2.37898);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,2.92735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,3.50914);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,4.30226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,5.07468);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,1.54197);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,0.906756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.806755);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.870916);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.879374);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.962588);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,1.09836);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,1.2216);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,1.41309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,1.7118);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,2.05521);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,2.50119);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,3.11454);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,3.72712);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,4.48678);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,5.41743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,2.22885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,1.03581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,1.1425);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,1.15035);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,1.20308);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,1.27774);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,1.38606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,1.61662);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,1.90794);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,2.2275);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,2.66569);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,3.27735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,3.88648);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,4.64177);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,5.64437);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,2.88018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,1.54457);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,1.52084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,1.53017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,1.61198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,1.6494);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,1.87017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,2.04942);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,2.5042);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,2.91352);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,3.3416);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,4.02305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,4.89591);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,5.89561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,4.01734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,1.95846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,2.00813);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.98968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,2.06327);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,2.06299);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,2.32007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,2.68867);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,3.11137);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,3.71651);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,4.40692);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,5.12701);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,6.20566);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,5.60354);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.58247);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,2.49426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,2.58243);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,2.65321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,2.68626);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,3.00554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,3.47293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,4.03384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,4.5887);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,5.60878);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,6.62396);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,7.15504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,3.74081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,3.19588);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,3.19194);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,3.37464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,3.61183);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,3.80407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,4.30516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,5.01353);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,5.88382);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,6.97559);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,10.5776);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,4.45381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,4.47429);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,4.30075);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,4.22743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,4.68589);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,4.77761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,5.42294);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,6.17926);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,7.1454);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,14.0653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,5.71358);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,5.58673);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,5.40347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,5.33208);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,5.80157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,6.083);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,6.87892);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,7.88418);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,18.1573);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,7.42529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,7.45092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,6.88411);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,6.92477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,7.17217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,7.64038);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,8.50276);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,21.0017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,9.73388);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,9.166);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,8.75844);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,8.6852);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,8.67706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,9.43487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,29.2561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,11.7887);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,11.4697);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,10.9149);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,10.819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,10.8267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,39.1416);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,15.4545);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,14.4492);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,13.6227);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,13.0962);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,19.7334);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,17.1848);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,16.5911);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,23.175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,21.5661);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,29.1574);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.07090965);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(43.05576);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.07090965);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.09769484);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1345978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1854403);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.255488);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3519953);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4849569);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.668143);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.9205252);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.268242);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.747303);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,2.407324);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,3.31666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,4.569484);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,6.295547);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,8.673608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,11.94995);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,16.46389);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,22.68291);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,31.25108);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(24,0.0787885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(25,0.0909739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(26,0.108172);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(27,0.127578);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(28,0.160065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(29,0.189677);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(30,0.224104);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(31,0.257415);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(32,0.333545);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(33,0.431654);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(34,0.536494);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(35,0.671343);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(36,0.844621);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(37,1.0453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(38,1.27556);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(39,1.61736);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(40,2.01236);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(41,2.50927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(42,3.042);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(43,3.67738);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(44,4.65684);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(47,0.0844634);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(48,0.0938747);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(49,0.104156);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(50,0.121572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(51,0.144828);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(52,0.174779);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(53,0.204028);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(54,0.237063);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(55,0.31744);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(56,0.391224);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(57,0.487505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(58,0.60667);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(59,0.764783);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(60,0.939148);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(61,1.1917);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(62,1.47133);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(63,1.88543);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(64,2.28363);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(65,2.75633);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(66,3.41081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(67,4.15537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(70,0.0952016);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(71,0.111479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(72,0.121415);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(73,0.136626);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(74,0.156127);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(75,0.186127);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(76,0.223897);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(77,0.238293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(78,0.323555);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(79,0.385953);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(80,0.478011);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(81,0.616485);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(82,0.76688);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(83,0.940627);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(84,1.17011);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(85,1.48633);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(86,1.85026);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(87,2.24292);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(88,2.80229);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(89,3.45276);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(90,4.0932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(93,0.120061);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(94,0.12482);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(95,0.137464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(96,0.158379);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(97,0.176886);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(98,0.203736);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(99,0.220129);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(100,0.263677);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(101,0.343334);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(102,0.412189);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(103,0.517032);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(104,0.647664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(105,0.785988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(106,0.978788);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(107,1.18151);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(108,1.52836);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(109,1.89418);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(110,2.34043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(111,2.82301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(112,3.50611);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(113,4.25834);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(116,0.256407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(117,0.165407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(118,0.177672);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(119,0.193568);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(120,0.21302);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(121,0.224817);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(122,0.27037);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(123,0.292898);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(124,0.375623);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(125,0.448202);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(126,0.546854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(127,0.67333);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(128,0.840841);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(129,1.05791);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(130,1.28412);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(131,1.59515);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(132,1.99683);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(133,2.35964);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(134,2.94849);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(135,3.62225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(136,4.45743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(140,0.364368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(141,0.229882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(142,0.239088);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(143,0.270761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(144,0.298643);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(145,0.304162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(146,0.342303);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(147,0.408863);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(148,0.486317);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(149,0.586575);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(150,0.716796);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(151,0.899979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(152,1.08357);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(153,1.35271);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(154,1.66982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(155,2.06737);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(156,2.49125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(157,3.09539);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(158,3.8478);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(159,4.60265);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(164,0.513872);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(165,0.303337);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(166,0.340801);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(167,0.356);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(168,0.39077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(169,0.373835);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(170,0.473281);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(171,0.536901);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(172,0.63692);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(173,0.791769);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(174,0.942641);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(175,1.16756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(176,1.43985);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(177,1.7892);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(178,2.13418);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(179,2.67791);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(180,3.22826);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(181,3.96467);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(182,4.92073);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(188,0.751424);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(189,0.428046);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(190,0.441803);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(191,0.48093);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(192,0.491459);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(193,0.559097);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(194,0.639234);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(195,0.711973);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(196,0.859142);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(197,0.970126);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(198,1.2339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(199,1.50845);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(200,1.85626);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(201,2.26462);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(202,2.81139);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(203,3.46567);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(204,4.0859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(205,5.11033);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(212,1.18231);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(213,0.582694);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(214,0.62992);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(215,0.608381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(216,0.683033);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(217,0.738244);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(218,0.811625);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(219,0.960799);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(220,1.10443);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(221,1.34122);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(222,1.61067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(223,1.96839);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(224,2.37898);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(225,2.92735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(226,3.50914);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(227,4.30226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(228,5.07468);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(236,1.54197);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(237,0.906756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(238,0.806755);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(239,0.870916);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(240,0.879374);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(241,0.962588);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(242,1.09836);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(243,1.2216);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(244,1.41309);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(245,1.7118);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(246,2.05521);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(247,2.50119);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(248,3.11454);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(249,3.72712);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(250,4.48678);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(251,5.41743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(260,2.22885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(261,1.03581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(262,1.1425);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(263,1.15035);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(264,1.20308);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(265,1.27774);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(266,1.38606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(267,1.61662);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(268,1.90794);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(269,2.2275);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(270,2.66569);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(271,3.27735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(272,3.88648);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(273,4.64177);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(274,5.64437);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(284,2.88018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(285,1.54457);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(286,1.52084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(287,1.53017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(288,1.61198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(289,1.6494);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(290,1.87017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(291,2.04942);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(292,2.5042);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(293,2.91352);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(294,3.3416);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(295,4.02305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(296,4.89591);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(297,5.89561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(308,4.01734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(309,1.95846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(310,2.00813);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(311,1.98968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(312,2.06327);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(313,2.06299);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(314,2.32007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(315,2.68867);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(316,3.11137);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(317,3.71651);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(318,4.40692);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(319,5.12701);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(320,6.20566);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(332,5.60354);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(333,2.58247);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(334,2.49426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(335,2.58243);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(336,2.65321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(337,2.68626);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(338,3.00554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(339,3.47293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(340,4.03384);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(341,4.5887);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(342,5.60878);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(343,6.62396);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(356,7.15504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(357,3.74081);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(358,3.19588);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(359,3.19194);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(360,3.37464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(361,3.61183);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(362,3.80407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(363,4.30516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(364,5.01353);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(365,5.88382);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(366,6.97559);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(380,10.5776);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(381,4.45381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(382,4.47429);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(383,4.30075);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(384,4.22743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(385,4.68589);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(386,4.77761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(387,5.42294);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(388,6.17926);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(389,7.1454);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(404,14.0653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(405,5.71358);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(406,5.58673);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(407,5.40347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(408,5.33208);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(409,5.80157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(410,6.083);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(411,6.87892);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(412,7.88418);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(428,18.1573);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(429,7.42529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(430,7.45092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(431,6.88411);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(432,6.92477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(433,7.17217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(434,7.64038);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(435,8.50276);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(452,21.0017);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(453,9.73388);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(454,9.166);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(455,8.75844);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(456,8.6852);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(457,8.67706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(458,9.43487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(476,29.2561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(477,11.7887);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(478,11.4697);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(479,10.9149);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(480,10.819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(481,10.8267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(500,39.1416);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(501,15.4545);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(502,14.4492);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(503,13.6227);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(504,13.0962);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(524,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(525,19.7334);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(526,17.1848);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(527,16.5911);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(548,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(549,23.175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(550,21.5661);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(572,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(573,29.1574);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(596,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetMinimum(0.07090965);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetMaximum(43.05576);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitle(\"Observed R\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.44744765758514404, "alphanum_fraction": 0.6841694712638855, "avg_line_length": 82.57575988769531, "blob_id": "1477ad45106a2722d903aa281e68a541db272998", "content_id": "3b9bee85c21a2fed3f629269f0fcbc87940fb797", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 91014, "license_type": "no_license", "max_line_length": 155, "num_lines": 1089, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10/Fixed_Edge_sbottom_neutralino2_ExpXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 11:16:28 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,3.693106);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,2.214636);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,1.644094);\n 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2} [GeV]->SetBinContent(470,0.188547);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(471,0.1875824);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(472,0.1709725);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(473,0.1684428);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(474,0.1636466);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(488,2.966554);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(489,0.9467433);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(490,0.7888405);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(491,0.5805266);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(492,0.4737639);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(493,0.3847832);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(494,0.3131531);\n 484096097_M_{sbottom} 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[GeV]->SetBinContent(547,0.972167);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,0.6382024);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,0.6046264);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,0.4738492);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(551,0.3449109);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(552,0.3091056);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(553,0.2669185);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(554,0.25346);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(555,0.2166976);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(556,0.1981111);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(557,0.1755976);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,0.179373);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,2.144569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,0.936375);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,0.6459337);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,0.529146);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,0.4104288);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,0.3609391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,0.292178);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,0.2474416);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,0.2283765);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.2071237);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.188082);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,2.351968);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,0.794514);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,0.6581771);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,0.5254912);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.3893947);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.340968);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.2858352);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.2502332);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.2223828);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.2050906);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,2.251893);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,0.7501401);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,0.6938592);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.4839157);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.423052);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.3354176);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.2865019);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.2488741);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.2138419);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,2.094936);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,0.76232);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,0.6729298);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,0.523668);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.37356);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.307359);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.2730111);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.234992);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,1.983216);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,0.7741565);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,0.649586);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.4628176);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.4012184);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.3167774);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.2758793);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,1.981845);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,0.721212);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,0.562608);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.4615955);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.3837111);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.3077168);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,2.13576);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,0.6684896);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,0.5577116);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.4489975);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.3395544);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,1.570864);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,0.6885331);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,0.5268918);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.1096352);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,1.899704);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,0.6814955);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,0.5360051);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,2.073843);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,0.6893497);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,1.948456);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8 = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(29,3.693106);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(30,2.214636);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(31,1.644094);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(32,0.9965115);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(33,0.9349672);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(363,0.1687601);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(364,0.1512);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(365,0.1411125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(366,0.1358362);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(380,1.55775);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(381,0.6484575);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(382,0.4702937);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(383,0.3660571);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(384,0.2773108);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(385,0.2182825);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(386,0.1897634);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(387,0.1633507);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(388,0.1543625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(389,0.1495725);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(404,1.628031);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(405,0.5972937);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(406,0.4673429);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(407,0.3431892);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(408,0.2801925);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(409,0.2214866);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(410,0.1827);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,0.1623125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,0.1490638);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(428,1.575594);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(429,0.5715179);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,0.435625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,0.3349625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,0.271425);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,0.2187);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,0.1848375);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,0.1602563);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(452,1.545262);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(453,0.61625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(454,0.4294175);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(455,0.330175);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,0.2637);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,0.2126625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,0.1841675);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,1.56825);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,0.5794375);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,0.47705);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,0.3339);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,0.2444625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,0.2167275);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,1.595438);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,0.56635);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,0.4313246);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,0.3160125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,0.2589538);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,1.5463);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,0.5202);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,0.4008125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,0.3205125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,0.4149);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,0.54325);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,0.425315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,0.53265);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,0.539275);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,1.524215);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10 = new TH2F(\"266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10\",\"\",21,187.5,712.5,25,87.5,712.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(24,1.8924);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(25,1.32613);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(26,0.907764);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(27,0.650073);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(28,0.48257);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(29,0.364038);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(30,0.3027333);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(31,0.2686296);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(32,0.2263936);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(33,0.1961762);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(34,0.1766864);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(35,0.157418);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(36,0.1483175);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(37,0.138411);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(38,0.1321582);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(39,0.1259054);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(40,0.1154913);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(41,0.1125067);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(42,0.1084493);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(43,0.1076557);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(44,0.1032763);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(47,1.6986);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(48,1.20291);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} 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266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(61,0.1139397);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(62,0.1067804);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(63,0.1051712);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(64,0.1013433);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(65,0.09675072);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(66,0.09374428);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(67,0.09284647);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(70,1.8088);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(71,1.22816);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(72,0.773916);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(73,0.528079);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(74,0.391345);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(75,0.298506);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(76,0.2507958);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(77,0.2151448);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(78,0.1803936);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(79,0.1625778);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(80,0.1443728);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(81,0.1302992);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(82,0.1245207);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(83,0.1175766);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(84,0.1088791);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(85,0.1067804);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(86,0.1012038);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(87,0.09781828);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(88,0.09224928);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(89,0.09308072);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(90,0.08775897);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(93,2.2173);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(94,1.38572);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(95,0.94666);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(96,0.63356);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(97,0.44239);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(98,0.318759);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(99,0.2799639);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(100,0.2151448);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(101,0.184736);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(102,0.1694847);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(103,0.1491952);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(104,0.1351352);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(105,0.1231344);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(106,0.1195578);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(107,0.1103236);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(108,0.1054544);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(109,0.1019962);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__10->SetBinContent(340,0.1533366);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(341,0.1462493);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(342,0.1384625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(343,0.1266787);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(356,1.952509);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(357,0.6180656);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(358,0.4815087);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(359,0.3581781);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(360,0.281416);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(361,0.2194054);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(362,0.1960575);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(363,0.1687601);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(364,0.1512);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(365,0.1411125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(366,0.1358362);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(380,1.55775);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(381,0.6484575);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(382,0.4702937);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(383,0.3660571);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(384,0.2773108);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(385,0.2182825);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(386,0.1897634);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(387,0.1633507);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(388,0.1543625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(389,0.1495725);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(404,1.628031);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(405,0.5972937);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(406,0.4673429);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(407,0.3431892);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(408,0.2801925);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(409,0.2214866);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(410,0.1827);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(411,0.1623125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(412,0.1490638);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(428,1.575594);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(429,0.5715179);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(430,0.435625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(431,0.3349625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(432,0.271425);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(433,0.2187);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(434,0.1848375);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(435,0.1602563);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(452,1.545262);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(453,0.61625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(454,0.4294175);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(455,0.330175);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(456,0.2637);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(457,0.2126625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(458,0.1841675);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(476,1.56825);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(477,0.5794375);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(478,0.47705);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(479,0.3339);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(480,0.2444625);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(481,0.2167275);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(500,1.595438);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(501,0.56635);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(502,0.4313246);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(503,0.3160125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(504,0.2589538);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(524,1.5463);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(525,0.5202);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(526,0.4008125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(527,0.3205125);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(548,0.4149);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(549,0.54325);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(550,0.425315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(572,0.53265);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(573,0.539275);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(596,1.524215);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetMinimum(0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetMaximum(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetEntries(315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetDirectory(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetStats(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetLineStyle(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.6807979941368103, "alphanum_fraction": 0.7353609800338745, "avg_line_length": 95.98158264160156, "blob_id": "37861437bafde350c57066dce31322327b5d06c8", "content_id": "3c5f2170e1b5586a4180974b7d940b75ba81aa39", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 194839, "license_type": "no_license", "max_line_length": 652, "num_lines": 2009, "path": "/produceSystematicsSignal8TeV.py", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "####################################################################################################\n# FastSim lepton scaling factors were not in included in the trees #\n# -> One has to run over each event to scale it properly #\n# For the slepton model (fixed neutralino 1): Events have to be scaled to Z/slepton BR either via #\n# the number of generated sleptons (new, has to be implemented) or the number of generated leptons #\n# (with a neutralino 2 as mother) and the mother PDG ID (old) #\n####################################################################################################\n\n\n\nimport ROOT\nimport numpy as np\nfrom ROOT import TH1F\nfrom math import sqrt\nattic = []\n\n\nROOT.gStyle.SetOptStat(0)\n\nptScales = {\"EE\":{\"Barrel\":\"1.012\",\"Endcap\":\"1.03\"},\"MuMu\":{\"Barrel\":\"1.004\",\"Endcap\":\"1.004\"}}\n\netaCuts = {\n\t\t\t\"Barrel\":\"abs(eta1) < 1.4 && abs(eta2) < 1.4\",\n\t\t\t\"Endcap\":\"(((abs(eta1) < 1.4 \|\| abs(eta1) > 1.6) && (abs(eta2) < 1.4 \|\| abs(eta2) > 1.6)) && 1.6 <= TMath::Max(abs(eta1),abs(eta2)))\",\n\t\t\t\"BothEndcap\":\"abs(eta1) > 1.6 && abs(eta2) > 1.6\",\n\t\t\t\"Inclusive\":\"abs(eta1) < 2.4 && abs(eta2) < 2.4 && ((abs(eta1) < 1.4 \|\| abs(eta1) > 1.6) && (abs(eta2) < 1.4 \|\| abs(eta2) > 1.6))\"\n\t\t\t}\n\t\t\t\nmllCuts = {\n\t\t\t\"lowMll\":\"p4.M() < 70 && p4.M() > 20\",\n\t\t\t\"ZPeak\":\"p4.M() < 101 && p4.M() > 81\",\n\t\t\t\"highMll\":\"p4.M() > 120\",\n\t\t\t}\n\neventLowerMllCuts = {\n\t\t\t\"lowMll\": 20,\n\t\t\t\"ZPeak\": 81,\n\t\t\t\"highMll\":120,\n\t\t\t}\n\t\t\t\neventUpperMllCuts = {\n\t\t\t\"lowMll\": 70 ,\n\t\t\t\"ZPeak\": 101,\n\t\t\t\"highMll\":10000,\n\t\t\t}\n\ndef readPDFHistsFromFile(filePath, dileptonCombination, pdfSet):\n\tfrom ROOT import TH1F, TFile\n\tfrom random import randint\n\tfrom sys import maxint\n\tname1 = \"%x\"%(randint(0, maxint))\t\n\tname2 = \"%x\"%(randint(0, maxint))\t\n\tname3 = \"%x\"%(randint(0, maxint))\t\n\tresult = {}\n\tf1 = TFile(filePath,\"READ\")\n\t\n\tfirstBin = 20\n\tlastBin = 300\n\tnBins = 280/5\n\thistoMean = TH1F(name1,name1, nBins, firstBin, lastBin)\n\thistoMean = (f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dileptonCombination,\"mean\"))).Clone()\n\tresult[\"mean\"] = histoMean.Clone()\n\tresult[\"up\"] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dileptonCombination,\"up\")).Clone(name2)\n\tresult[\"down\"] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dileptonCombination,\"down\")).Clone(name3)\n\tf1.Close()\n\tprint result\n\treturn result\n\ndef readPDFHists(path,dileptonCombination):\n\t\n\tresult = {}\n\tfor sampleName, filePath in getFilePathsAndSampleNames(path).iteritems():\n\t\tresult[sampleName] = {}\n\t\tprint readPDFHistsFromFile(filePath, dileptonCombination,\"CT10\")\n\t\tresult[sampleName][\"CT10\"] = readPDFHistsFromFile(filePath, dileptonCombination,\"CT10\")\n\t\tresult[sampleName][\"MSTW\"] = readPDFHistsFromFile(filePath, dileptonCombination,\"MSTW\")\n\t\tresult[sampleName][\"NNPDF\"] = readPDFHistsFromFile(filePath, dileptonCombination,\"NNPDF\")\n\t\t\n\treturn result\t\n\ndef readTreeFromFile(path, dileptonCombination):\n\t\"\"\"\n\thelper functionfrom argparse import ArgumentParser\n\tpath: path to .root file containing simulated events\n\tdileptonCombination: EMu, EMu, or EMu for electron-electron, electron-muon, or muon-muon events\n\n\treturns: tree containing events for on sample and dileptonCombination\n\t\"\"\"\n\tfrom ROOT import TChain\n\tresult = TChain()\n\tresult.Add(\"%s/cutsV23DileptonFinalTrees/%sDileptonTree\"%(path, dileptonCombination))\n\treturn result\n\t\ndef getFilePathsAndSampleNames(path):\n\t\"\"\"\n\thelper function\n\tpath: path to directory containing all sample files\n\n\treturns: dict of smaple names -> path of .root file (for all samples in path)\n\t\"\"\"\n\tresult = []\n\tfrom glob import glob\n\tfrom re import match\n\tresult = {}\n\tfor filePath in glob(\"%s/sw538.root\"%path):\n\t\t#~ sampleName = match(\".sw538v.\\.processed.\\.(.).root\", filePath).groups()[0]\n\t\tsampleName = match(\".sw538v0477.processed\\.(.).root\", filePath).groups()[0]\n\t\t#for the python enthusiats: yield sampleName, filePath is more efficient here :)\n\t\tresult[sampleName] = filePath\n\treturn result\n\t\ndef totalNumberOfGeneratedEvents(path):\n\t\"\"\"\n\tpath: path to directory containing all sample files\n\n\treturns dict samples names -> number of simulated events in source sample\n\t\t\t(note these include events without EMu EMu EMu signature, too )\n\t\"\"\"\n\tfrom ROOT import TFile\n\tresult = {}\n\tfor sampleName, filePath in getFilePathsAndSampleNames(path).iteritems():\n\t\trootFile = TFile(filePath, \"read\")\n\t\tresult[sampleName] = rootFile.FindObjectAny(\"analysis paths\").GetBinContent(1)\n\treturn result\n\t\ndef readTrees(path, dileptonCombination):\n\t\"\"\"\n\tpath: path to directory containing all sample files\n\tdileptonCombination: \"EMu\", \"EMu\", or pyroot\"EMu\" for electron-electron, electron-muon, or muon-muon events\n\n\treturns: dict of sample names -> trees containing events (for all samples for one dileptonCombination)\n\t\"\"\"\n\tresult = {}\n\tfor sampleName, filePath in getFilePathsAndSampleNames(path).iteritems():\t\t\n\t\tresult[sampleName] = readTreeFromFile(filePath, dileptonCombination)\n\t\t\n\treturn result\n\t\n\t\ndef createHistoFromTree(tree, variable, weight, nBins, firstBin, lastBin, nEvents = -1):\n\t\"\"\"\n\ttree: tree to create histo from)\n\tvariable: variable to plot (must be a branch of the tree)\n\tweight: weights to apply (e.g. \"var1(var2 > 15)\" will use weights from var1 and cut on var2 > 15\n\tnBins, firstBin, lastBin: number of bins, first bin and last bin (same as in TH1F constructor)\n\tnEvents: number of events to process (-1 = all)\n\t\"\"\"\n\tfrom ROOT import TH1F\n\tfrom random import randint\n\tfrom sys import maxint\n\tif nEvents < 0:\n\t\tnEvents = maxint\n\t#make a random name you could give something meaningfull here,\n\t#but that would make this less readable\n\tname = \"%x\"%(randint(0, maxint))\n\tresult = TH1F(name, \"\", nBins, firstBin, lastBin)\n\tresult.Sumw2()\n\ttree.Draw(\"%s>>%s\"%(variable, name), weight, \"goff\", nEvents)\n\treturn result\n\t\n\t\ndef setTDRStyle():\n\tfrom ROOT import TStyle\n\tfrom ROOT import kWhite\n\tfrom ROOT import kTRUE\n\ttdrStyle = TStyle(\"tdrStyle\",\"Style for P-TDR\")\n\t\n\t# For the canvas:\n\ttdrStyle.SetCanvasBorderMode(0)\n\ttdrStyle.SetCanvasColor(kWhite)\n\t# For the canvas:\n\ttdrStyle.SetCanvasBorderMode(0)\n\ttdrStyle.SetCanvasColor(kWhite)\n\ttdrStyle.SetCanvasDefH(600) #Height of canvas\n\ttdrStyle.SetCanvasDefW(600)#Width of canvas\n\ttdrStyle.SetCanvasDefX(0) #POsition on screen\n\ttdrStyle.SetCanvasDefY(0)\n\t\n\t# For the Pad:\n\ttdrStyle.SetPadBorderMode(0)\n\t# tdrStyle->SetPadBorderSize(Width_t size = 1);\n\ttdrStyle.SetPadColor(kWhite)\n\ttdrStyle.SetPadGridX(0)\n\ttdrStyle.SetPadGridY(0)\n\ttdrStyle.SetGridColor(0)\n\ttdrStyle.SetGridStyle(3)\n\ttdrStyle.SetGridWidth(1)\n\t\n\t# For the frame:\n\ttdrStyle.SetFrameBorderMode(0)\n\ttdrStyle.SetFrameBorderSize(1)\n\ttdrStyle.SetFrameFillColor(0)\n\ttdrStyle.SetFrameFillStyle(0)\n\ttdrStyle.SetFrameLineColor(1)\n\ttdrStyle.SetFrameLineStyle(1)\n\ttdrStyle.SetFrameLineWidth(1)\n\t\n\t# For the histo:\n\t# tdrStyle->SetHistFillColor(1);\n\t# tdrStyle->SetHistFillStyle(0);\n\ttdrStyle.SetHistLineColor(1)\n\ttdrStyle.SetHistLineStyle(0)\n\ttdrStyle.SetHistLineWidth(1)\n\t# tdrStyle->SetLegoInnerR(Float_t rad = 0.5);\n\t# tdrStyle->SetNumberContours(Int_t number = 20);\n\t\n\ttdrStyle.SetEndErrorSize(2)\n\t# tdrStyle->SetErrorMarker(20);\n\ttdrStyle.SetErrorX(0.)\n\t\n\ttdrStyle.SetMarkerStyle(20)\n\t\n\t#For the fit/function:\n\ttdrStyle.SetOptFit(1)\n\ttdrStyle.SetFitFormat(\"5.4g\")\n\ttdrStyle.SetFuncColor(2)\n\ttdrStyle.SetFuncStyle(1)\n\ttdrStyle.SetFuncWidth(1)\n\t\n\t#For the date:\n\ttdrStyle.SetOptDate(0)\n\t# tdrStyle->SetDateX(Float_t x = 0.01);\n\t# tdrStyle->SetDateY(Float_t y = 0.01);\n\t\n\t# For the statistics box:\n\ttdrStyle.SetOptFile(0)\n\ttdrStyle.SetOptStat(\"emr\") # To display the mean and RMS: SetOptStat(\"mr\");\n\ttdrStyle.SetStatColor(kWhite)\n\ttdrStyle.SetStatFont(42)\n\ttdrStyle.SetStatFontSize(0.025)\n\ttdrStyle.SetStatTextColor(1)\n\ttdrStyle.SetStatFormat(\"6.4g\")\n\ttdrStyle.SetStatBorderSize(1)\n\ttdrStyle.SetStatH(0.1)\n\ttdrStyle.SetStatW(0.15)\n\t# tdrStyle->SetStatStyle(Style_t style = 100.1);\n\t# tdrStyle->SetStatX(Float_t x = 0);\n\t# tdrStyle->SetStatY(Float_t y = 0);\n\t\n\t# Margins:\n\ttdrStyle.SetPadTopMargin(0.05)\n\ttdrStyle.SetPadBottomMargin(0.13)\n\ttdrStyle.SetPadLeftMargin(0.15)\n\ttdrStyle.SetPadRightMargin(0.05)\n\t\n\t# For the Global title:\n\ttdrStyle.SetOptTitle(0)\n\ttdrStyle.SetTitleFont(42)\n\ttdrStyle.SetTitleColor(1)\n\ttdrStyle.SetTitleTextColor(1)\n\ttdrStyle.SetTitleFillColor(10)\n\ttdrStyle.SetTitleFontSize(0.05)\n\t# tdrStyle->SetTitleH(0); # Set the height of the title box\n\t# tdrStyle->SetTitleW(0); # Set the width of the title box\n\t# tdrStyle->SetTitleX(0); # Set the position of the title box\n\t# tdrStyle->SetTitleY(0.985); # Set the position of the title box\n\t# tdrStyle->SetTitleStyle(Style_t style = 100.1);\n\t# tdrStyle->SetTitleBorderSize(2);\n\t\n\t# For the axis titles:\n\ttdrStyle.SetTitleColor(1, \"XYZ\")\n\ttdrStyle.SetTitleFont(42, \"XYZ\")\n\ttdrStyle.SetTitleSize(0.06, \"XYZ\")\n\t# tdrStyle->SetTitleXSize(Float_t size = 0.02); # Another way to set the size?\n\t# tdrStyle->SetTitleYSize(Float_t size = 0.02);\n\ttdrStyle.SetTitleXOffset(0.9)\n\ttdrStyle.SetTitleYOffset(1.2)\n\t# tdrStyle->SetTitleOffset(1.1, \"Y\"); # Another way to set the Offset\n\t\n\t# For the axis labels:\n\ttdrStyle.SetLabelColor(1, \"XYZ\")\n\ttdrStyle.SetLabelFont(42, \"XYZ\")\n\ttdrStyle.SetLabelOffset(0.007, \"XYZ\")\n\ttdrStyle.SetLabelSize(0.05, \"XYZ\")\n\t\n\t# For the axis:\n\ttdrStyle.SetAxisColor(1, \"XYZ\")\n\ttdrStyle.SetStripDecimals(kTRUE)\n\ttdrStyle.SetTickLength(0.03, \"XYZ\")\n\ttdrStyle.SetNdivisions(408, \"XYZ\")\n\t\n\t#~ tdrStyle->SetNdivisions(510, \"XYZ\");\n\ttdrStyle.SetPadTickX(1) # To get tick marks on the opposite side of the frame\n\ttdrStyle.SetPadTickY(1)\n\t\n\t# Change for log plots:\n\ttdrStyle.SetOptLogx(0)\n\ttdrStyle.SetOptLogy(0)\n\ttdrStyle.SetOptLogz(0)\n\t\n\t# Postscript options:\n\ttdrStyle.SetPaperSize(20.,20.);\n\t# tdrStyle->SetLineScalePS(Float_t scale = 3);\n\t# tdrStyle->SetLineStyleString(Int_t i, const char text);\n\t# tdrStyle->SetHeaderPS(const char* header);\n\t# tdrStyle->SetTitlePS(const char* pstitle);\n\t\n\t#tdrStyle->SetBarOffset(Float_t baroff = 0.5);\n\t#tdrStyle->SetBarWidth(Float_t barwidth = 0.5);\n\t#tdrStyle->SetPaintTextFormat(const char* format = \"g\");\n\ttdrStyle.SetPalette(1)\n\t#tdrStyle->SetTimeOffset(Double_t toffset);\n\t#tdrStyle->SetHistMinimumZero(kTRUE);\n\t\n\t\n\t\n\t\n\tROOT.gROOT.ForceStyle()\n\t\n\ttdrStyle.cd()\n\ndef produceMETUncertainty(tree,cuts,dilepton):\n\t\n\tuncertaintySources = [\"patPFMetJetEnUp\",\"patPFMetJetEnDown\",\"patPFMetJetResUp\",\"patPFMetJetResDown\",\"patPFMetElectronEnUp\",\"patPFMetElectronEnDown\",\"patPFMetMuonEnUp\",\"patPFMetMuonEnDown\",\"patPFMetTauEnUp\",\"patPFMetTauEnDown\",\"patPFMetUnclusteredEnUp\",\"patPFMetUnclusteredEnDown\"]\n\tcolors=[ROOT.kBlue,ROOT.kGreen+3,ROOT.kGreen+3,ROOT.kGreen,ROOT.kGreen,ROOT.kOrange+2,ROOT.kOrange+2,ROOT.kPink,ROOT.kPink,ROOT.kBlack,ROOT.kBlack,ROOT.kBlue+3,ROOT.kBlue+3]\n\tresult = 0.\n\tdefaultTree = tree.CopyTree(cuts)\n\thistos = [createHistoFromTree(tree, \"patPFMet\", \"\", 40, 0, 400)]\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\tfor index, source in enumerate(uncertaintySources):\n\t\tif index == 0:\n\t\t\tcuts = cuts.replace(\"patPFMet\",source)\n\t\telse:\n\t\t\tcuts = cuts.replace(uncertaintySources[index-1],source)\n\t\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\t\thistos.append(createHistoFromTree(tree, source, \"\", 40, 0, 400))\n\tif yields[0] > 0:\n\t\tresult = sqrt( max((yields[1]-yields[0])/yields[0],(yields[1]-yields[0])/yields[0])2 + max((yields[3]-yields[0])/yields[0],(yields[4]-yields[0])/yields[0])2 + max((yields[5]-yields[0])/yields[0],(yields[6]-yields[0])/yields[0])2 + max((yields[7]-yields[0])/yields[0],(yields[8]-yields[0])/yields[0])2 + max((yields[9]-yields[0])/yields[0],(yields[10]-yields[0])/yields[0])2 + max((yields[11]-yields[0])/yields[0],(yields[12]-yields[0])/yields[0])2)\n\telse:\n\t\tresult = 0\n\t\n\t\n\t#~ hCanvas = TCanvas(\"hCanvas\", \"Distribution\", 800,800)\n\n\t#~ plotPad = ROOT.TPad(\"plotPad\",\"plotPad\",0,0,1,1)\n\t#~ ratioPad = ROOT.TPad(\"ratioPad\",\"ratioPad\",0,0.,1,0.3)\n\t#~ setTDRStyle()\t\t\n\t#~ plotPad.UseCurrentStyle()\n\t#~ ratioPad.UseCurrentStyle()\n\t#~ plotPad.Draw()\t\n\t#~ ratioPad.Draw()\t\n\t#~ plotPad.cd()\t\n#~ \n#~ \n\t#~ legend = TLegend(0.4, 0.4, 0.95, 0.95)\n\t#~ legend.SetFillStyle(0)\n\t#~ legend.SetBorderSize(1)\n\t\t\t#~ \n\t#~ hCanvas.DrawFrame(0,0.1,400,1500,\"; %s ; %s\" %(\"E^{miss}_{T} [GeV]\",\"Events / 10 GeV\"))\n#~ \n\t#~ latex = ROOT.TLatex()\n\t#~ latex.SetTextSize(0.05)\n\t#~ latex.SetTextFont(42)\n\t#~ latex.SetNDC(True)\n\t#~ latex.DrawLatex(0.13, 0.96, \"CMS Simulation, #sqrt{s} = 8 TeV,\t #scale[0.6]{#int}Ldt = 19.4 fb^{-1}\")\t\n\t#~ \n\t#~ \n\t#~ for i, histo in enumerate(histos):\n\t\t#~ histo.SetLineColor(colors[i])\n\t\t#~ if i == 0:\n\t\t\t#~ histo.SetLineWidth(4)\n\t\t\t#~ legend.AddEntry(histo,\"E_{T}^{miss}\",\"l\")\n\t\t#~ else:\n\t\t\t#~ histo.SetLineWidth(2)\n\t\t\t#~ legend.AddEntry(histo,uncertaintySources[i-1],\"l\")\n\t\t#~ histo.Draw(\"samehist\")\n\t\t\t#~ \n\t#~ legend.Draw(\"same\")\n\t#~ hCanvas.Print(\"fig/metUncertainty_%s_%s.pdf\"%(sampleName,dilepton))\t\n\n\t\n\t\n\t\n\treturn result,yields[0],yields[1],yields[2],yields[3],yields[4],yields[5],yields[6],yields[7],yields[8],yields[9],yields[10],yields[11],yields[12]\t\t\n\t\ndef produceJetUncertainty(tree,cuts,dilepton):\n\t\n\tuncertaintySources = [\"nJetsEnUp\",\"nJetsEnDown\",\"nJetsResUp\",\"nJetsResDown\"]\n\tcolors=[ROOT.kBlack,ROOT.kBlue,ROOT.kGreen+3,ROOT.kGreen+3,ROOT.kOrange+2,ROOT.kOrange+2]\n\n\tresult = 0.\n\tdefaultTree = tree.CopyTree(cuts)\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\thistos = [createHistoFromTree(tree, \"nJets\", \"\", 10, 0, 10)]\n\thistos.append(createHistoFromTree(tree, \"nJetsSmeared\", \"\", 10, 0, 10))\n\n\tfor index, source in enumerate(uncertaintySources):\n\t\tif index == 0:\n\t\t\tcuts = cuts.replace(\"nJetsSmeared\",source)\n\t\telse:\n\t\t\tcuts = cuts.replace(uncertaintySources[index-1],source)\n\t\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\t\thistos.append(createHistoFromTree(tree, source, \"\", 10, 0, 10))\n\t\n\tif \tyields[0] > 0:\n\t\tresult = sqrt( max((yields[1]-yields[0])/yields[0],(yields[1]-yields[0])/yields[0])2 + max((yields[3]-yields[0])/yields[0],(yields[4]-yields[0])/yields[0])2 )\n\telse:\n\t\tresult = 0\t\n\n\t#~ hCanvas = TCanvas(\"hCanvas\", \"Distribution\", 800,800)\n\n\t#~ plotPad = ROOT.TPad(\"plotPad\",\"plotPad\",0,0,1,1)\n\t#~ ratioPad = ROOT.TPad(\"ratioPad\",\"ratioPad\",0,0.,1,0.3)\n\t#~ setTDRStyle()\t\t\n\t#~ plotPad.UseCurrentStyle()\n\t#~ ratioPad.UseCurrentStyle()\n\t#~ plotPad.Draw()\t\n\t#~ ratioPad.Draw()\t\n\t#~ plotPad.cd()\t\n\n\n\t#~ legend = TLegend(0.5, 0.6, 0.95, 0.95)\n\t#~ legend.SetFillStyle(0)\n\t#~ legend.SetBorderSize(1)\n\t\t\t\n\t#~ hCanvas.DrawFrame(0,0.1,10,4000,\"; %s ; %s\" %(\"N_{jets}\",\"Events\"))\n#~ \n\t#~ latex = ROOT.TLatex()\n\t#~ latex.SetTextSize(0.05)\n\t#~ latex.SetTextFont(42)\n\t#~ latex.SetNDC(True)\n\t#~ latex.DrawLatex(0.13, 0.96, \"CMS Simulation, #sqrt{s} = 8 TeV,\t #scale[0.6]{#int}Ldt = 19.4 fb^{-1}\")\t\n\t#~ \n\t#~ \n\t#~ for i, histo in enumerate(histos):\n\t\t#~ histo.SetLineColor(colors[i])\n\t\t#~ if i == 0:\n\t\t\t#~ histo.SetLineWidth(4)\n\t\t\t#~ legend.AddEntry(histo,\"N_{jets}\",\"l\")\n\t\t#~ elif i == 1:\n\t\t\t#~ histo.SetLineWidth(4)\n\t\t\t#~ legend.AddEntry(histo,\"N_{jets} smeared\",\"l\")\n\t\t#~ else:\n\t\t\t#~ histo.SetLineWidth(2)\n\t\t\t#~ legend.AddEntry(histo,uncertaintySources[i-2],\"l\")\n\t\t#~ histo.Draw(\"samehist\")\n\t\t\t#~ \n\t#~ legend.Draw(\"same\")\n\t#~ hCanvas.Print(\"fig/jetUncertainty_%s_%s.pdf\"%(sampleName,dilepton))\t\n\n\n\treturn result,yields[0],yields[1],yields[2],yields[3],yields[4]\n\t\n#~ def produceLeptonUncertainty(tree,cuts,dilepton):\n\t#~ \n\t#~ uncertaintySources = [\"pt1ScaleUp\",\"pt1ScaleDown\",\"pt2ScaleUp\",\"pt2ScaleDown\"]\n\t#~ result = 0.\n\t#~ defaultTree = tree.CopyTree(cuts)\n\t#~ yields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\t#~ if yields[0] > 0:\n\t\t#~ if dilepton == \"EMu\":\n\t\t\t#~ for index, source in enumerate(uncertaintySources):\n\t\t\t\t#~ if index == 0:\n\t\t\t\t\t#~ cuts = cuts.replace(\"pt1\",source)\n\t\t\t\t#~ elif index == 2:\n\t\t\t\t\t#~ cuts = cuts.replace(uncertaintySources[1],\"pt1\")\n\t\t\t\t\t#~ cuts = cuts.replace(\"pt2\",source)\n\t\t\t\t#~ else:\n\t\t\t\t\t#~ cuts = cuts.replace(uncertaintySources[index-1],source)\n\t\t\t\t#~ yields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\t\t\t#~ result = sqrt( max((yields[1]-yields[0])/yields[0],(yields[1]-yields[0])/yields[0])2 + max((yields[3]-yields[0])/yields[0],(yields[4]-yields[0])/yields[0])2 )\t\t\n\t\t#~ else:\n\t\t\t#~ cuts = cuts.replace(\"pt1\",\"pt1ScaleUp\")\n\t\t\t#~ cuts = cuts.replace(\"pt2\",\"pt2ScaleUp\")\n\t\t\t#~ yields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\t\t\t#~ result = sqrt(result2 + ((yields[1]-yields[0])/yields[0])2)\t\n\t\t\t#~ cuts = cuts.replace(\"pt1ScaleUp\",\"pt1ScaleDown\")\n\t\t\t#~ cuts = cuts.replace(\"pt2ScaleUp\",\"pt2ScaleDown\")\n\t\t\t#~ yields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\t\t\t#~ result = sqrt(max(result2 ,((yields[2]-yields[0])/yields[0])2))\n\t#~ else:\n\t\t#~ result = 0\n\t\t\t#~ \n\t#~ return result\n\ndef produceLeptonUncertaintyEMu(tree,cuts,dilepton,region):\n \n\tuncertaintySources = [\"pt1ScaleUp\",\"pt1ScaleDown\",\"pt2ScaleUp\",\"pt2ScaleDown\"]\n\tresult = 0.\n\tdefaultTree = tree.CopyTree(cuts)\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\tfor index, source in enumerate(uncertaintySources):\n\t\tif index == 0:\n\t\t\tcuts = cuts.replace(\"pt1\",source)\n\t\telif index == 2:\n\t\t\tcuts = cuts.replace(uncertaintySources[1],\"pt1\")\n\t\t\tcuts = cuts.replace(\"pt2\",source)\n\t\telse:\n\t\t\tcuts = cuts.replace(uncertaintySources[index-1],source)\n\t\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\tif yields[0] > 0:\n\t\tresult = sqrt( max((yields[1]-yields[0])/yields[0],(yields[2]-yields[0])/yields[0])2 + max((yields[3]-yields[0])/yields[0],(yields[4]-yields[0])/yields[0])2 )\n\telse:\n\t\tresult = 0\n\treturn result,yields[0],yields[1],yields[2],yields[3],yields[4]\n\t\n\t \ndef produceLeptonUncertaintySF(tree,cuts,dilepton,region):\n \n\tuncertaintySources = [\"pt1ScaleUp\",\"pt1ScaleDown\",\"pt2ScaleUp\",\"pt2ScaleDown\"]\n\tresult = 0.\n\tdefaultTree = tree.CopyTree(cuts)\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\tcuts = cuts.replace(\"pt1\",\"pt1ScaleUp\")\n\tcuts = cuts.replace(\"pt2\",\"pt2ScaleUp\")\n\tcuts = cuts.replace(\"p4.M()\",\"p4.M()%s\"%ptScales[dilepton][region])\n\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\tif yields[0] > 0:\n\t\tresult = sqrt(result2 + ((yields[1]-yields[0])/yields[0])2)\n\telse:\n\t\tresult = 0\n\tcuts = cuts.replace(\"pt1ScaleUp\",\"pt1ScaleDown\")\n\tcuts = cuts.replace(\"pt2ScaleUp\",\"pt2ScaleDown\")\n\tcuts = cuts.replace(\"p4.M()%s\"%ptScales[dilepton][region],\"p4.M()/%s\"%ptScales[dilepton][region])\n\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\tif yields[0] > 0:\n\t\tresult = sqrt(max(result2 ,((yields[2]-yields[0])/yields[0])2))\n\telse:\n\t\tresult = 0\n\t#~ return result\t\n\treturn result,yields[0],yields[1],yields[2]\n\t\t\t\ndef produceISRUncertainty(tree,cuts,dilepton,ISR_incl_cuts):\n\t\n\tuncertaintySources = [\"(sbottomWeight+(1-sbottomWeight))\",\"(sbottomWeight-(1-sbottomWeight))\"]\n\tresult = 0.\n\t#~ defaultTree = tree.CopyTree(cuts)\n\tincl_yields_unweighted = float(createHistoFromTree(tree, \"p4.M()\", ISR_incl_cuts, 300, 0, 300).Integral())\n\tincl_yields_weighted = float(createHistoFromTree(tree, \"p4.M()\", \"sbottomWeight * %s\"%ISR_incl_cuts, 300, 0, 300).Integral())\n\tif incl_yields_weighted > 0:\n\t\tcorrectionFactor = incl_yields_unweighted / incl_yields_weighted\n\telse:\n\t\tcorrectionFactor = 0\n\t\tprint \"ISR rewweighting not possible\"\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())correctionFactor]\n\tcuts = cuts.replace(\"sbottomWeight\",\"(sbottomWeight+(1-sbottomWeight))\")\n\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\tif yields[0] > 0:\n\t\tresult = sqrt(result2 + ((yields[1]-yields[0])/yields[0])2)\t\n\tcuts = cuts.replace(\"(sbottomWeight+(1-sbottomWeight))\",\"(sbottomWeight-(1-sbottomWeight))\")\n\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())correctionFactor2)\n\tif yields[0] > 0:\n\t\tresult = sqrt(max(result2 ,((yields[2]-yields[0])/yields[0])*2))\n\telse:\n\t\tresult = 0\n\t\n\t#~ print \"Incl yields unweighted: \"+str(incl_yields_unweighted)\n\t#~ print \"Incl yields ISR weighted: \"+str(incl_yields_weighted)\n\t#~ print \"Correction Factor: \"+str(correctionFactor)\n\t#~ print \"ISR weighted yields: \"+str(yields[0])\n\t#~ print \"2x ISR weighted yields: \"+str(yields[2])\n\t#~ print \"Unweighted yields: \"+str(yields[1])\n\t\t\t\n\t#~ return result\n\treturn result,yields[0],yields[1],yields[2],correctionFactor\n\t\ndef signalNumbers(tree,etaRegion,mllRegion,dilepton,electronScaleFactors,muonScaleFactors,additionalCut,m_neutr_1_fix):\n\t\t\n\t### Only to check whether the normalization is right for the slepton model for the files in which the generated slepton number is not correct\n\tFourGenLeptonEvents = 0\n\tThreeGenLeptonEvents = 0\n\tOneGenLeptonNeutrinoEvents = 0\n\tOneGenLeptonQuarkEvents = 0\n\tTwoGenLeptonNeutrinoEvents = 0\n\tTwoGenLeptonZQuarkEvents = 0\n\tTwoGenLeptonSleptonEvents = 0\n\tFourGenLeptonEventsReweighted = 0\n\tThreeGenLeptonEventsReweighted = 0\n\tOneGenLeptonNeutrinoEventsReweighted = 0\n\tOneGenLeptonQuarkEventsReweighted = 0\n\tTwoGenLeptonNeutrinoEventsReweighted = 0\n\tTwoGenLeptonZQuarkEventsReweighted = 0\n\tTwoGenLeptonSleptonEventsReweighted = 0\n\t####\n\t\n\tsignalEvents = 0\n\tMCEvents = 0\n\tmll_lower_Cut = eventLowerMllCuts[mllRegion]\n\tmll_upper_Cut = eventUpperMllCuts[mllRegion]\n\tif m_neutr_1_fix == False:\n\t\tif additionalCut == \"NJets3Cut\":\n\t\t\tif dilepton == \"EE\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\telif dilepton == \"MuMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\telif dilepton == \"EMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\n\t\telif additionalCut == \"Met150Cut\":\n\t\t\tif dilepton == \"EE\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree: \n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMet > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMet > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\telif dilepton == \"MuMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMet > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMet > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\telif dilepton == \"EMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMet > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMet > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\n\t\telse:\n\t\t\tif dilepton == \"EE\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\telif dilepton == \"MuMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt1),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\telif dilepton == \"EMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.04 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.2796 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 0 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 9 * 0.4887 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * muonScaleFactors.GetBinContent(muonScaleFactors.GetXaxis().FindBin(ev.pt2),muonScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\telse:\n\t\tif additionalCut == \"NJets3Cut\":\n\t\t\tif dilepton == \"EE\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\telif dilepton == \"MuMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\telif dilepton == \"EMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.nJetsSmeared >= 3 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\t\t\t\n\t\telif additionalCut == \"Met150Cut\":\n\t\t\tif dilepton == \"EE\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMET > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMET > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\telif dilepton == \"MuMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMET > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMET > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\telif dilepton == \"EMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMET > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ev.patPFMET > 150 and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tprint \"Right selection not found\"\n\t\t\t\t\t\t\t\tprint \"nGenLeptons: \"+str(ev.nGenSUSYLeptons)\n\t\t\n\t\telse:\n\t\t\tif dilepton == \"EE\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tFourGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tFourGenLeptonEventsReweighted += 90.0102 \n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tThreeGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tThreeGenLeptonEventsReweighted += 3. * 0.101\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEventsReweighted += 3. * 0.2\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEventsReweighted += 3. * 0.6991\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEventsReweighted += 9./2. * 0.1411\n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEvents += 1\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEventsReweighted += 9./2. * 0.0404\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEventsReweighted += 1\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tFourGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tFourGenLeptonEventsReweighted += 90.0102 \n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tThreeGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tThreeGenLeptonEventsReweighted += 3. * 0.101\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEventsReweighted += 3. * 0.2\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEventsReweighted += 3. * 0.6991\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEventsReweighted += 9./2. * 0.1411\n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEvents += 1\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEventsReweighted += 9./2. * 0.0404\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEventsReweighted += 1\n\t\t\telif dilepton == \"MuMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tFourGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tFourGenLeptonEventsReweighted += 90.0102 \n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tThreeGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tThreeGenLeptonEventsReweighted += 3. * 0.101\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEventsReweighted += 3. * 0.2\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEventsReweighted += 3. * 0.6991\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEventsReweighted += 9./2. * 0.1411\n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEvents += 1\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEventsReweighted += 9./2. * 0.0404\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEventsReweighted += 1\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tFourGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tFourGenLeptonEventsReweighted += 90.0102 \n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tThreeGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tThreeGenLeptonEventsReweighted += 3. * 0.101\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEventsReweighted += 3. * 0.2\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEventsReweighted += 3. * 0.6991\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEventsReweighted += 9./2. * 0.1411\n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEvents += 1\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEventsReweighted += 9./2. * 0.0404\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEventsReweighted += 1\n\t\t\telif dilepton == \"EMu\":\n\t\t\t\tif etaRegion == \"Barrel\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and abs(ev.eta1) < 1.4 and abs(ev.eta2) < 1.4 and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tFourGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tFourGenLeptonEventsReweighted += 90.0102 \n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tThreeGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tThreeGenLeptonEventsReweighted += 3. * 0.101\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEventsReweighted += 3. * 0.2\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEventsReweighted += 3. * 0.6991\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEventsReweighted += 9./2. * 0.1411\n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEvents += 1\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEventsReweighted += 9./2. * 0.0404\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEventsReweighted += 1\n\t\t\t\telif etaRegion == \"Endcap\":\n\t\t\t\t\tfor ev in tree:\n\t\t\t\t\t\tif ev.chargeProduct < 0 and (((abs(ev.eta1) < 1.4 or abs(ev.eta1) > 1.6) and (abs(ev.eta2) < 1.4 or abs(ev.eta2) > 1.6)) and 1.6 <= max(abs(ev.eta1),abs(ev.eta2))) and ev.pt1 > 20 and ev.pt2 > 20 and ev.inv > mll_lower_Cut and ev.inv < mll_upper_Cut and ((ev.patPFMet > 100 and ev.nJetsSmeared >= 3) or (ev.patPFMet > 150 and ev.nJetsSmeared >=2)) and abs(ev.eta1) < 2.4 and abs(ev.eta2) < 2.4 and ev.deltaR > 0.3:\n\t\t\t\t\t\t\tMCEvents +=1\n\t\t\t\t\t\t\tif ev.nGenSUSYLeptons == 4:\n\t\t\t\t\t\t\t\tFourGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tFourGenLeptonEventsReweighted += 90.0102 \n\t\t\t\t\t\t\t\tsignalEvents += 90.0102 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 3:\n\t\t\t\t\t\t\t\tThreeGenLeptonEvents += 1\n\t\t\t\t\t\t\t\tThreeGenLeptonEventsReweighted += 3. * 0.101\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.101 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 2:\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonNeutrinoEventsReweighted += 3. * 0.2\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.2 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 1 and ev.nGenSUSYNeutrinos == 0:\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEvents += 1\n\t\t\t\t\t\t\t\tOneGenLeptonQuarkEventsReweighted += 3. * 0.6991\n\t\t\t\t\t\t\t\tsignalEvents += 3. * 0.6991 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEventsReweighted += 9./2. * 0.1411\n\t\t\t\t\t\t\t\tTwoGenLeptonZQuarkEvents += 1\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.1411 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t#~ elif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.nGenSUSYSleptons == 0 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 2 and ev.motherPdgId1 != 1000011 and ev.motherPdgId1 != 2000011 and ev.motherPdgId1 != 1000013 and ev.motherPdgId1 != 2000013 and ev.motherPdgId2 != 1000011 and ev.motherPdgId2 != 2000011 and ev.motherPdgId2 != 1000013 and ev.motherPdgId2 != 2000013: \n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonNeutrinoEventsReweighted += 9./2. * 0.0404\n\t\t\t\t\t\t\t\tsignalEvents += 9./2. * 0.0404 * ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\telif ev.nGenSUSYLeptons == 2 and ev.nGenSUSYNeutrinos == 0 and (ev.motherPdgId1 == 1000011 or ev.motherPdgId1 == 2000011 or ev.motherPdgId1 == 1000013 or ev.motherPdgId1 == 2000013 or ev.motherPdgId2 == 1000011 or ev.motherPdgId2 == 2000011 or ev.motherPdgId2 == 1000013 or ev.motherPdgId2 == 2000013): \n\t\t\t\t\t\t\t\tsignalEvents += ev.weight * ev.sbottomWeight * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt1),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta1))) * electronScaleFactors.GetBinContent(electronScaleFactors.GetXaxis().FindBin(ev.pt2),electronScaleFactors.GetYaxis().FindBin(abs(ev.eta2)))\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEvents += 1\n\t\t\t\t\t\t\t\tTwoGenLeptonSleptonEventsReweighted += 1\n\t\n\t#~ print \"ZZ to 4l Events: \"+str(FourGenLeptonEvents)\n\t#~ print \"ZZ to 4l Events Reweighted: \"+str(FourGenLeptonEventsReweighted)\n\t#~ print \"Slepton + Z to 2l Events: \"+str(ThreeGenLeptonEvents)\n\t#~ print \"Slepton + Z to 2l Events Reweighted: \"+str(ThreeGenLeptonEventsReweighted)\n\t#~ print \"Slepton + Z to 2nu Events: \"+str(OneGenLeptonNeutrinoEvents)\n\t#~ print \"Slepton + Z to 2nu EventsReweighted: \"+str(OneGenLeptonNeutrinoEventsReweighted)\n\t#~ print \"Slepton + Z to 2q Events: \"+str(OneGenLeptonQuarkEvents)\n\t#~ print \"Slepton + Z to 2q EventsReweighted: \"+str(OneGenLeptonQuarkEventsReweighted)\n\t#~ print \"Z to 2l + Z to 2q Events: \"+str(TwoGenLeptonZQuarkEvents)\n\t#~ print \"Z to 2l + Z to 2q EventsReweighted: \"+str(TwoGenLeptonZQuarkEventsReweighted)\n\t#~ print \"Z to 2l + Z to 2nu Events: \"+str(TwoGenLeptonNeutrinoEvents)\n\t#~ print \"Z to 2l + Z to 2nu EventsReweighted: \"+str(TwoGenLeptonNeutrinoEventsReweighted)\n\t#~ print \"2 Slepton Events: \"+str(TwoGenLeptonSleptonEvents)\n\treturn signalEvents, MCEvents\n\t\ndef signalYields(tree,cuts,scalingLumi,dilepton):\n\thisto = createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300)\n\thisto.Scale(scalingLumi)\n\tyields = float(histo.Integral())\n\treturn yields\n\t\t\t\ndef produceSignalEfficiency(tree,cuts,weight,dilepton):\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\tresult = yields[0]/weight\n\treturn result\n\t\t\t\ndef statisticalUncertainty(tree,cuts,dilepton):\n\thisto = createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300)\n\terrInt = ROOT.Double()\n\tInt = histo.IntegralAndError(0,histo.GetNbinsX()+1,errInt)\n\tif Int > 0:\n\t\terr = float(errInt)/float(Int)\n\telse:\n\t\terr = 0\n\treturn err\t\t\n\ndef producePileupUncertainty(tree,cuts,dilepton):\n\t\n\tuncertaintySources = [\"weightUp\",\"weightDown\"]\n\tcolors=[ROOT.kBlack,ROOT.kBlue,ROOT.kRed]\n\n\tresult = 0.\n\tdefaultTree = tree.CopyTree(cuts)\n\ttotalWeight = 0\n\ttotalWeightUp = 0\n\ttotalWeightDown = 0\n\tfor event in tree:\n\t\t#~ print event.weight, event.weightUp, event.weightDown\n\t\ttotalWeight = totalWeight + event.weight\n\t\ttotalWeightUp = totalWeightUp + event.weightUp\n\t\ttotalWeightDown = totalWeightDown + event.weightDown\n\t#~ print totalWeight/tree.GetEntries(), totalWeightUp/tree.GetEntries(), totalWeightDown/tree.GetEntries()\t\n\t#~ print cuts\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\thistos = [createHistoFromTree(tree, \"p4.M()\", cuts, 60, 0, 300)]\n\tfor index, source in enumerate(uncertaintySources):\n\t\tif index == 0:\n\t\t\tcuts = cuts.replace(\"weight\",source)\n\t\telse:\n\t\t\tcuts = cuts.replace(uncertaintySources[index-1],source)\n\t\t#~ print cuts\n\t\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\t\thistos.append(createHistoFromTree(tree, \"p4.M()\", cuts, 60, 0, 300))\n\n\t#~ print yields\n\tif yields[0] > 0 and yields[2] > 0:\n\t\tresult = sqrt( max((yields[1]-yields[0])/yields[0],(yields[2]-yields[0])/yields[2])2 )\t\t\n\telif yields[0] > 0:\n\t\tresult = (yields[1]-yields[0])/yields[0]\n\telif yields[2] > 0:\n\t\tresult = (yields[2]-yields[0])/yields[2]\n\telse:\n\t\tresult = 0\n\t\t\t\n\n\t#~ hCanvas = TCanvas(\"hCanvas\", \"Distribution\", 800,800)\n\n\t#~ plotPad = ROOT.TPad(\"plotPad\",\"plotPad\",0,0,1,1)\n\t#~ ratioPad = ROOT.TPad(\"ratioPad\",\"ratioPad\",0,0.,1,0.3)\n\t#~ setTDRStyle()\t\t\n\t#~ plotPad.UseCurrentStyle()\n\t#~ ratioPad.UseCurrentStyle()\n\t#~ plotPad.Draw()\t\n\t#~ ratioPad.Draw()\t\n\t#~ plotPad.cd()\t\n#~ \n#~ \n\t#~ legend = TLegend(0.5, 0.6, 0.95, 0.95)\n\t#~ legend.SetFillStyle(0)\n\t#~ legend.SetBorderSize(1)\n\t\t\t#~ \n\t#~ hCanvas.DrawFrame(20,0.1,300,250,\"; %s ; %s\" %(\"m_{ll}\",\"Events\"))\n#~ \n\t#~ latex = ROOT.TLatex()\n\t#~ latex.SetTextSize(0.05)\n\t#~ latex.SetTextFont(42)\n\t#~ latex.SetNDC(True)\n\t#~ latex.DrawLatex(0.13, 0.96, \"CMS Simulation, #sqrt{s} = 8 TeV,\t #scale[0.6]{#int}Ldt = 19.4 fb^{-1}\")\t\n\t#~ \n\t#~ \n\t#~ for i, histo in enumerate(histos):\n\t\t#~ histo.SetLineColor(colors[i])\n\t\t#~ if i == 0:\n\t\t\t#~ histo.SetLineWidth(1)\n\t\t\t#~ legend.AddEntry(histo,\"default\",\"l\")\n\t\t#~ else:\n\t\t\t#~ histo.SetLineWidth(1)\n\t\t\t#~ legend.AddEntry(histo,uncertaintySources[i-2],\"l\")\n\t\t#~ histo.Draw(\"samehist\")\n\t\t\t#~ \n\t#~ legend.Draw(\"same\")\n\t#~ hCanvas.Print(\"fig/pileUpUncertainty_%s_%s.pdf\"%(sampleName,dilepton))\t\n\n\treturn result,yields[0],yields[1],yields[2]\t\n\t\n\t\ndef produceScalingUncertainty(tree,cuts):\n\t\n\tuncertaintySources = [\"IDScaleFactorUp\",\"IDScaleFactorDown\",\"GSFScaleFactorUp\",\"GSFScaleFactorDown\",\"trackingScaleFactorUp\",\"trackingScaleFactorDown\",\"isolationScaleFactorUp\",\"isolationScaleFactorDown\"]\n\tresult = 0.\n\tdefaultTree = tree.CopyTree(cuts)\n\tyields = [float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral())]\n\tfor index, source in enumerate(uncertaintySources):\n\t\tif index == 0:\n\t\t\tcuts = cuts.replace(\"IDScaleFactor\",source)\n\t\telif index == 2:\n\t\t\tcuts = cuts.replace(uncertaintySources[1],\"IDScaleFactor\")\n\t\t\tcuts = cuts.replace(\"GSFScaleFactor\",source)\n\t\telif index == 4:\n\t\t\tcuts = cuts.replace(uncertaintySources[3],\"GSFScaleFactor\")\n\t\t\tcuts = cuts.replace(\"trackingScaleFactor\",source)\n\t\telif index == 6:\n\t\t\tcuts = cuts.replace(uncertaintySources[5],\"trackingScaleFactor\")\n\t\t\tcuts = cuts.replace(\"isolationScaleFactor\",source)\n\t\telse:\n\t\t\tcuts = cuts.replace(uncertaintySources[index-1],source)\n\t\tyields.append(float(createHistoFromTree(tree, \"p4.M()\", cuts, 300, 0, 300).Integral()))\n\n\tif yields[0] > 0:\n\t\tresult = sqrt( max((yields[1]-yields[0])/yields[0],(yields[1]-yields[0])/yields[0])2 + max((yields[3]-yields[0])/yields[0],(yields[4]-yields[0])/yields[0])2 + max((yields[5]-yields[0])/yields[0],(yields[6]-yields[0])/yields[0])2 + max((yields[7]-yields[0])/yields[0],(yields[8]-yields[0])/yields[0])2 )\n\telse:\n\t\tresult = 0\n\treturn result\t\n\t\n\t\n#~ def producePDFUncertainty(sampleName,path,dilepton):\n\t#~ from ROOT import TH1F, TFile\n#~ \n\t#~ result = 0.\n\t#~ \n\t#~ pdfHists = readPDFHists(path,dilepton)\n\t#~ \n\t#~ pdfHists = {}\n\t#~ yields = {}\n\t#~ uncertHistsUp = {}\n\t#~ uncertHistsDown = {}\n\t#~ f1 = TFile(\"%s/sw538v0477.processed.%s.root\"%(path,sampleName),\"READ\")\n\t#~ for pdfSet in [\"CT10\",\"MSTW\",\"NNPDF\"]:\n\t\t#~ pdfHists[pdfSet] = {}\n\t\t#~ yields[pdfSet] = {}\n\t\t#~ for type in [\"mean\",\"up\",\"down\"]:\n\t\t\t#~ pdfHists[pdfSet][type] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dilepton,type)).Clone()\n\t\t\t#~ yields[pdfSet][type] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dilepton,type)).Integral()\n\t\t#~ uncertHistsUp[pdfSet] = pdfHists[pdfSet][\"up\"].Clone()\n\t\t#~ uncertHistsUp[pdfSet].Add(pdfHists[pdfSet][\"mean\"].Clone(),-1)\n\t\t#~ uncertHistsUp[pdfSet].Divide(pdfHists[pdfSet][\"mean\"].Clone())\t\n\t\t#~ uncertHistsDown[pdfSet] = pdfHists[pdfSet][\"down\"].Clone()\n\t\t#~ uncertHistsDown[pdfSet].Add(pdfHists[pdfSet][\"mean\"].Clone(),-1)\n\t\t#~ uncertHistsDown[pdfSet].Divide(pdfHists[pdfSet][\"mean\"].Clone())\t\n\t#~ \n\t #~ \n\t#~ integratedUncertainty = max(max((yields[\"CT10\"][\"up\"]-yields[\"CT10\"][\"mean\"])/yields[\"CT10\"][\"mean\"],abs((yields[\"CT10\"][\"down\"]-yields[\"CT10\"][\"mean\"])/yields[\"CT10\"][\"mean\"]) ), max( max((yields[\"MSTW\"][\"up\"]-yields[\"MSTW\"][\"mean\"])/yields[\"MSTW\"][\"mean\"],abs((yields[\"MSTW\"][\"down\"]-yields[\"MSTW\"][\"mean\"])/yields[\"MSTW\"][\"mean\"]) ), max((yields[\"NNPDF\"][\"up\"]-yields[\"NNPDF\"][\"mean\"])/yields[\"NNPDF\"][\"mean\"],abs((yields[\"NNPDF\"][\"down\"]-yields[\"NNPDF\"][\"mean\"])/yields[\"NNPDF\"][\"mean\"]) ) ) )\n\t#~ \n\t#~ \n\t#~ envelopeDown = TH1F(\"envelopeDown\",\"envelopeDown\",int(280/5),20,300)\n\t#~ envelopeUp = TH1F(\"envelopeUp\",\"envelopeUp\",int(280/5),20,300)\n\t#~ \n\t#~ for i in range(0,envelopeDown.GetNbinsX()+1):\n\t\t#~ envelopeDown.SetBinContent(i,float(min(uncertHistsDown[\"CT10\"].GetBinContent(i),min(uncertHistsDown[\"MSTW\"].GetBinContent(i),uncertHistsDown[\"NNPDF\"].GetBinContent(i)))))\n\t\t#~ envelopeUp.SetBinContent(i,max(uncertHistsUp[\"CT10\"].GetBinContent(i),max(uncertHistsUp[\"MSTW\"].GetBinContent(i),uncertHistsUp[\"NNPDF\"].GetBinContent(i))))\n#~ \n\t#~ hCanvas = TCanvas(\"hCanvas\", \"Distribution\", 800,800)\n#~ \n\t#~ plotPad = ROOT.TPad(\"plotPad\",\"plotPad\",0,0,1,1)\n\t#~ ratioPad = ROOT.TPad(\"ratioPad\",\"ratioPad\",0,0.,1,0.3)\n\t#~ setTDRStyle()\t\t\n\t#~ plotPad.UseCurrentStyle()\n\t#~ ratioPad.UseCurrentStyle()\n\t#~ plotPad.Draw()\t\n\t#~ ratioPad.Draw()\t\n\t#~ plotPad.cd()\t\n#~ \n#~ \n\t#~ legend = TLegend(0.5, 0.65, 0.95, 0.95)\n\t#~ legend.SetFillStyle(0)\n\t#~ legend.SetBorderSize(1)\n\t\t\t#~ \n\t#~ hCanvas.DrawFrame(20,-0.25,300,0.35,\"; %s ; %s\" %(\"m_{ll} [GeV]\",\"rel. PDF Uncert.\"))\n#~ \n\t#~ latex = ROOT.TLatex()\n\t#~ latex.SetTextSize(0.05)\n\t#~ latex.SetTextFont(42)\n\t#~ latex.SetNDC(True)\n\t#~ latex.DrawLatex(0.13, 0.96, \"CMS Simulation, #sqrt{s} = 8 TeV,\t #scale[0.6]{#int}Ldt = 19.4 fb^{-1}\")\n#~ \n\t#~ uncertHistsUp[\"CT10\"].SetLineColor(ROOT.kRed)\t\t\n\t#~ uncertHistsDown[\"CT10\"].SetLineColor(ROOT.kRed)\t\t\n\t#~ uncertHistsUp[\"MSTW\"].SetLineColor(ROOT.kGreen+3)\t\t\n\t#~ uncertHistsDown[\"MSTW\"].SetLineColor(ROOT.kGreen+3)\t\t\n\t#~ uncertHistsUp[\"NNPDF\"].SetLineColor(ROOT.kOrange)\t\t\n\t#~ uncertHistsDown[\"NNPDF\"].SetLineColor(ROOT.kOrange)\t\t\n\t#~ envelopeDown.SetLineColor(ROOT.kBlue)\n\t#~ envelopeUp.SetLineColor(ROOT.kBlue)\n#~ \n\t#~ uncertHistsUp[\"CT10\"].Rebin(2)\t\t\n\t#~ uncertHistsDown[\"CT10\"].Rebin(2)\t\t\n\t#~ uncertHistsUp[\"MSTW\"].Rebin(2)\t\t\n\t#~ uncertHistsDown[\"MSTW\"].Rebin(2)\t\t\n\t#~ uncertHistsUp[\"NNPDF\"].Rebin(2)\t\t\n\t#~ uncertHistsDown[\"NNPDF\"].Rebin(2)\t\t\n\t#~ envelopeDown.Rebin(2)\n\t#~ envelopeUp.Rebin(2)\n\t#~ \n\t#~ \n\t#~ legend.AddEntry(uncertHistsUp[\"CT10\"],\"CT10\",\"l\")\n\t#~ legend.AddEntry(uncertHistsUp[\"MSTW\"],\"MSTW 2008\",\"l\")\n\t#~ legend.AddEntry(uncertHistsUp[\"NNPDF\"],\"NNPDF 2.3\",\"l\")\n\t#~ legend.AddEntry(envelopeUp,\"envelope\",\"l\")\n\t#~ \n\t#~ uncertHistsUp[\"CT10\"].Draw(\"samehist\")\t\t\n\t#~ uncertHistsDown[\"CT10\"].Draw(\"samehist\")\t\t\n\t#~ uncertHistsUp[\"MSTW\"].Draw(\"samehist\")\t\t\n\t#~ uncertHistsDown[\"MSTW\"].Draw(\"samehist\")\t\t\t\n\t#~ uncertHistsUp[\"NNPDF\"].Draw(\"samehist\")\t\t\t\n\t#~ uncertHistsDown[\"NNPDF\"].Draw(\"samehist\")\t\t\t\n\t#~ envelopeDown.Draw(\"samehist\")\t\n\t#~ envelopeUp.Draw(\"samehist\")\t\n\t#~ \n\t#~ legend.Draw(\"same\")\n#~ \n\t#~ hCanvas.Print(\"pdfUncertainty_%s.pdf\"%sampleName)\t\n\t#~ \n\t#~ \n\t#~ return integratedUncertainty\ndef producePDFUncertainty(sampleName,path,dilepton):\n\tfrom ROOT import TH1F, TFile\n\n\tresult = 0.\n\t\n\t#~ pdfHists = readPDFHists(path,dilepton)\n\t\n\tpdfHists = {}\n\tyields = {}\n\tuncertHistsUp = {}\n\tuncertHistsDown = {}\n\tf1 = TFile(\"%s/sw538v0477.processed.%s.root\"%(path,sampleName),\"READ\")\n\tfor pdfSet in [\"CT10\",\"MSTW\",\"NNPDF\"]:\n\t\tpdfHists[pdfSet] = {}\n\t\tyields[pdfSet] = {}\n\t\tfor type in [\"mean\",\"up\",\"down\"]:\n\t\t\tpdfHists[pdfSet][type] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dilepton,type)).Clone()\n\t\t\tyields[pdfSet][type] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dilepton,type)).Integral()\n\t\tuncertHistsUp[pdfSet] = pdfHists[pdfSet][\"up\"].Clone()\n\t\tuncertHistsUp[pdfSet].Add(pdfHists[pdfSet][\"mean\"].Clone(),-1)\n\t\tuncertHistsUp[pdfSet+\"Rel\"]=uncertHistsUp[pdfSet].Clone()\n\t\tuncertHistsUp[pdfSet+\"Rel\"].Divide(pdfHists[pdfSet][\"mean\"].Clone())\t\n\t\tuncertHistsDown[pdfSet] = pdfHists[pdfSet][\"down\"].Clone()\n\t\tuncertHistsDown[pdfSet].Add(pdfHists[pdfSet][\"mean\"].Clone(),-1)\n\t\tuncertHistsDown[pdfSet+\"Rel\"]=uncertHistsDown[pdfSet].Clone()\n\t\tuncertHistsDown[pdfSet+\"Rel\"].Divide(pdfHists[pdfSet][\"mean\"].Clone())\t\n\t\t\n\t\t#~ uncertHistsDown[pdfSet].Divide(pdfHists[pdfSet][\"mean\"].Clone())\t\n\t\n\t \n\tintegratedUncertainty = max(max((yields[\"CT10\"][\"up\"]-yields[\"CT10\"][\"mean\"])/yields[\"CT10\"][\"mean\"],abs((yields[\"CT10\"][\"down\"]-yields[\"CT10\"][\"mean\"])/yields[\"CT10\"][\"mean\"]) ), max( max((yields[\"MSTW\"][\"up\"]-yields[\"MSTW\"][\"mean\"])/yields[\"MSTW\"][\"mean\"],abs((yields[\"MSTW\"][\"down\"]-yields[\"MSTW\"][\"mean\"])/yields[\"MSTW\"][\"mean\"]) ), max((yields[\"NNPDF\"][\"up\"]-yields[\"NNPDF\"][\"mean\"])/yields[\"NNPDF\"][\"mean\"],abs((yields[\"NNPDF\"][\"down\"]-yields[\"NNPDF\"][\"mean\"])/yields[\"NNPDF\"][\"mean\"]) ) ) )\n\t\n\t\n\tenvelopeDown = TH1F(\"envelopeDown\",\"envelopeDown\",int(280/5),20,300)\n\tenvelopeUp = TH1F(\"envelopeUp\",\"envelopeUp\",int(280/5),20,300)\n\tU = TH1F(\"U\",\"U\",int(280/5),20,300)\n\tD = TH1F(\"D\",\"D\",int(280/5),20,300)\n\tM = TH1F(\"D\",\"D\",int(280/5),20,300)\n\t\n\tfor i in range(0,envelopeDown.GetNbinsX()+1):\n\t\tD.SetBinContent(i,min(pdfHists[\"CT10\"][\"mean\"].GetBinContent(i)+uncertHistsDown[\"CT10\"].GetBinContent(i),min(pdfHists[\"MSTW\"][\"mean\"].GetBinContent(i)+uncertHistsDown[\"MSTW\"].GetBinContent(i),pdfHists[\"NNPDF\"][\"mean\"].GetBinContent(i)+uncertHistsDown[\"NNPDF\"].GetBinContent(i))))\n\t\tU.SetBinContent(i,max(pdfHists[\"CT10\"][\"mean\"].GetBinContent(i)+uncertHistsUp[\"CT10\"].GetBinContent(i),max(pdfHists[\"MSTW\"][\"mean\"].GetBinContent(i)+uncertHistsUp[\"MSTW\"].GetBinContent(i),pdfHists[\"NNPDF\"][\"mean\"].GetBinContent(i)+uncertHistsUp[\"NNPDF\"].GetBinContent(i))))\n\t\n\tM = D.Clone()\n\tM.Add(U.Clone(),1)\n\t#~ M.Add(M.Clone(),0.5)\n\tfor i in range(0,envelopeDown.GetNbinsX()+1):\n\t\tM.SetBinContent(i,M.GetBinContent(i)/2)\n\tenvelopeUp = U.Clone()\n\tenvelopeUp.Add(M.Clone(),-1)\n\tenvelopeUp.Divide(M.Clone())\n\t\n\tenvelopeDown = envelopeUp.Clone()\n\tenvelopeDown.Add(envelopeUp.Clone(),-2)\n\t\t\n\t#~ hCanvas = TCanvas(\"hCanvas\", \"Distribution\", 800,800)\n\t#~ plotPad = ROOT.TPad(\"plotPad\",\"plotPad\",0,0,1,1)\n\t#~ ratioPad = ROOT.TPad(\"ratioPad\",\"ratioPad\",0,0.,1,0.3)\n\t#~ setTDRStyle()\t\t\n\t#~ plotPad.UseCurrentStyle()\n\t#~ ratioPad.UseCurrentStyle()\n\t#~ plotPad.Draw()\t\n\t#~ ratioPad.Draw()\t\n\t#~ plotPad.cd()\t\n\n#~ \n\t#~ legend = TLegend(0.5, 0.65, 0.95, 0.95)\n\t#~ legend.SetFillStyle(0)\n\t#~ legend.SetBorderSize(1)\n\t\t\t#~ \n\t#~ hCanvas.DrawFrame(20,-0.5,300,0.5,\"; %s ; %s\" %(\"m_{ll} [GeV]\",\"rel. PDF Uncert.\"))\n#~ \n\t#~ latex = ROOT.TLatex()\n\t#~ latex.SetTextSize(0.05)\n\t#~ latex.SetTextFont(42)\n\t#~ latex.SetNDC(True)\n\t#~ latex.DrawLatex(0.13, 0.96, \"CMS Simulation, #sqrt{s} = 8 TeV,\t #scale[0.6]{#int}Ldt = 19.4 fb^{-1}\")\n\n\t#~ uncertHistsUp[\"CT10Rel\"].SetLineColor(ROOT.kRed)\t\t\n\t#~ uncertHistsDown[\"CT10Rel\"].SetLineColor(ROOT.kRed)\t\t\n\t#~ uncertHistsUp[\"MSTWRel\"].SetLineColor(ROOT.kGreen+3)\t\t\n\t#~ uncertHistsDown[\"MSTWRel\"].SetLineColor(ROOT.kGreen+3)\t\t\n\t#~ uncertHistsUp[\"NNPDFRel\"].SetLineColor(ROOT.kOrange)\t\t\n\t#~ uncertHistsDown[\"NNPDFRel\"].SetLineColor(ROOT.kOrange)\t\t\n\t#~ envelopeDown.SetLineColor(ROOT.kBlue)\n\t#~ envelopeUp.SetLineColor(ROOT.kBlue)\n\n\t#~ uncertHistsUp[\"CT10\"].Rebin(2)\t\t\n\t#~ uncertHistsDown[\"CT10\"].Rebin(2)\t\t\n\t#~ uncertHistsUp[\"MSTW\"].Rebin(2)\t\t\n\t#~ uncertHistsDown[\"MSTW\"].Rebin(2)\t\t\n\t#~ uncertHistsUp[\"NNPDF\"].Rebin(2)\t\t\n\t#~ uncertHistsDown[\"NNPDF\"].Rebin(2)\t\t\n\t#~ envelopeDown.Rebin(2)\n\t#~ envelopeUp.Rebin(2)\n\t\n\t\n\t#~ legend.AddEntry(uncertHistsUp[\"CT10\"],\"CT10\",\"l\")\n\t#~ legend.AddEntry(uncertHistsUp[\"MSTW\"],\"MSTW 2008\",\"l\")\n\t#~ legend.AddEntry(uncertHistsUp[\"NNPDF\"],\"NNPDF 2.3\",\"l\")\n\t#~ legend.AddEntry(envelopeUp,\"envelope\",\"l\")\n\t#~ \n\t#~ uncertHistsUp[\"CT10Rel\"].Draw(\"samehist\")\t\t\n\t#~ uncertHistsDown[\"CT10Rel\"].Draw(\"samehist\")\t\t\n\t#~ uncertHistsUp[\"MSTWRel\"].Draw(\"samehist\")\t\t\n\t#~ uncertHistsDown[\"MSTWRel\"].Draw(\"samehist\")\t\t\t\n\t#~ uncertHistsUp[\"NNPDFRel\"].Draw(\"samehist\")\t\t\t\n\t#~ uncertHistsDown[\"NNPDFRel\"].Draw(\"samehist\")\t\t\t\n\t#~ envelopeDown.Draw(\"samehist\")\t\n\t#~ envelopeUp.Draw(\"samehist\")\t\n\t#~ \n\t#~ legend.Draw(\"same\")\n#~ \n\t#~ hCanvas.Print(\"fig/pdfUncertainty_%s.pdf\"%sampleName)\t\n\t\n\t\n\treturn integratedUncertainty\n\t\ndef producePDFUncertainty2(sampleName,path,dilepton):\n\tfrom ROOT import TH1F, TFile\n\n\tresult = 0.\n\t\n\t#~ pdfHists = readPDFHists(path,dilepton)\n\t\n\tpdfHists = {}\n\tyields = {}\n\tabsYields = {}\n\trelative = {}\n\tuncertHistsUp = {}\n\tuncertHistsDown = {}\n\t#~ print path\n\t#~ print sampleName\n\tf1 = TFile(\"%s/sw538v0477.processed.%s.root\"%(path,sampleName),\"READ\")\n\tf2 = TFile(\"/user/schomakers/trees/pdfTest/pdfNominatorTest.cutsV23DileptonPDFUncertaintyNominator.%s.root\"%(sampleName),\"READ\")\n\tfor pdfSet in [\"CT10\",\"MSTW\",\"NNPDF\"]:\n\t\tyields[pdfSet] = {}\n\t\tabsYields[pdfSet] = {}\n\t\trelative[pdfSet] = {}\n\t\tfor type in [\"mean\",\"up\",\"down\"]:\n\t\t\t#~ print type \n\t\t\tyields[pdfSet][type] = f1.Get(\"%s_%sDileptonTree_%s\"%(pdfSet,dilepton,type)).Integral()\n\t\t\tabsYields[pdfSet][type] = f2.Get(\"%s_Tree_%s\"%(pdfSet,type)).Integral()\n\t\t\trelative[pdfSet][type] = yields[pdfSet][type]/absYields[pdfSet][type]\n\t\t\t#~ print yields[pdfSet][type]\n\t\t\t#~ print absYields[pdfSet][type]\n\t\t\t#~ print relative[pdfSet][type]\n\t\t\n\t\t#~ uncertHistsDown[pdfSet].Divide(pdfHists[pdfSet][\"mean\"].Clone())\t\n\t\n\t \n\t#~ integratedUncertainty = max(max((yields[\"CT10\"][\"up\"]-yields[\"CT10\"][\"mean\"])/yields[\"CT10\"][\"mean\"],abs((yields[\"CT10\"][\"down\"]-yields[\"CT10\"][\"mean\"])/yields[\"CT10\"][\"mean\"]) ), max( max((yields[\"MSTW\"][\"up\"]-yields[\"MSTW\"][\"mean\"])/yields[\"MSTW\"][\"mean\"],abs((yields[\"MSTW\"][\"down\"]-yields[\"MSTW\"][\"mean\"])/yields[\"MSTW\"][\"mean\"]) ), max((yields[\"NNPDF\"][\"up\"]-yields[\"NNPDF\"][\"mean\"])/yields[\"NNPDF\"][\"mean\"],abs((yields[\"NNPDF\"][\"down\"]-yields[\"NNPDF\"][\"mean\"])/yields[\"NNPDF\"][\"mean\"]) ) ) )\n\tintegratedUncertainty = max(max((relative[\"CT10\"][\"up\"]-relative[\"CT10\"][\"mean\"])/relative[\"CT10\"][\"mean\"],abs((relative[\"CT10\"][\"down\"]-relative[\"CT10\"][\"mean\"])/relative[\"CT10\"][\"mean\"]) ), max( max((relative[\"MSTW\"][\"up\"]-relative[\"MSTW\"][\"mean\"])/relative[\"MSTW\"][\"mean\"],abs((relative[\"MSTW\"][\"down\"]-relative[\"MSTW\"][\"mean\"])/relative[\"MSTW\"][\"mean\"]) ), max((relative[\"NNPDF\"][\"up\"]-relative[\"NNPDF\"][\"mean\"])/relative[\"NNPDF\"][\"mean\"],abs((relative[\"NNPDF\"][\"down\"]-relative[\"NNPDF\"][\"mean\"])/relative[\"NNPDF\"][\"mean\"]) ) ) )\n\t\n\treturn integratedUncertainty,yields[\"CT10\"][\"mean\"],absYields[\"CT10\"][\"mean\"],yields[\"CT10\"][\"up\"],absYields[\"CT10\"][\"up\"],yields[\"CT10\"][\"down\"],absYields[\"CT10\"][\"down\"],yields[\"MSTW\"][\"mean\"],absYields[\"MSTW\"][\"mean\"],yields[\"MSTW\"][\"up\"],absYields[\"MSTW\"][\"up\"],yields[\"MSTW\"][\"down\"],absYields[\"MSTW\"][\"down\"],yields[\"NNPDF\"][\"mean\"],absYields[\"NNPDF\"][\"mean\"],yields[\"NNPDF\"][\"up\"],absYields[\"NNPDF\"][\"up\"],yields[\"NNPDF\"][\"down\"],absYields[\"NNPDF\"][\"down\"]\n\n\n\t\t\nif (__name__ == \"__main__\"):\n\tsetTDRStyle()\n\t\n\tfrom sys import argv\n\timport pickle\t\n\tfrom ROOT import TCanvas, TPad, TH1F, TH1I, THStack, TLegend, TF1, TH2F, TH2D, TFile\n\timport ratios\n\tfrom defs import sbottom_masses\n\tfrom math import sqrt\n\t\n\tElectronFactors = TFile(\"electron_FastSim_EWKino.root\")\n\tMuonFactors = TFile(\"muon_FastSim_EWKino.root\")\n\t\n\tElectronScaleFactors = ElectronFactors.Get(\"SF\")\n\tMuonScaleFactors = MuonFactors.Get(\"SF\")\n\t\n\n\tlumi = 19400\n\t\t\n\tstep_size = 25\n\tm_b_min = int(argv[3])\n\tm_b_max = int(argv[3])\n\tm_n_max = 700\n\t\t\n\tm_neutr_1_fix = False\n\tif m_neutr_1_fix == False:\n\t\tMultiQuarkScaleFactor = \"((nGenSUSYLeptons == 0 && nGenSUSYNeutrinos == 0) * 9 * 0.4887)\"\n\t\tNeutrinoQuarkScaleFactor = \"((nGenSUSYLeptons == 0 && nGenSUSYNeutrinos == 2) * 9./2. * 0.2796)\"\n\t\tMultiNeutrinoScaleFactor = \"((nGenSUSYLeptons == 0 && nGenSUSYNeutrinos == 4) * 9 * 0.04)\"\n\t\tDileptonNeutrinoScaleFactor = \"((nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 2) * 9./2. * 0.0404)\"\n\t\tDileptonQuarkScaleFactor = \"((nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 0) * 9./2. * 0.1411)\"\n\t\tMultileptonScaleFactor = \"((nGenSUSYLeptons == 4)90.0102)\"\n\t\tpath = \"/user/schomakers/trees/sw538v0477/GridScanZDecay\"\n\t\tm_n_min = 100\n\telse:\n\t\tSleptonNeutrinoScaleFactor = \"((nGenSUSYLeptons == 1 && nGenSUSYNeutrinos == 2) * 3. * 0.2)\"\n\t\tSleptonQuarkScaleFactor = \"((nGenSUSYLeptons == 1 && nGenSUSYNeutrinos == 0) * 3. * 0.6991)\"\n\t\tSleptonLeptonScaleFactor = \"((nGenSUSYLeptons == 3) * 3. * 0.101)\"\n\t\t#~ DileptonQuarkScaleFactor = \"((nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 0 && nGenSUSYSleptons == 0 && motherPdgId1 != 1000011 && motherPdgId1 != 2000011 && motherPdgId1 != 1000013 && motherPdgId1 != 2000013 && motherPdgId2 != 1000011 && motherPdgId2 != 2000011 && motherPdgId2 != 1000013 && motherPdgId2 != 2000013 ) * 9./2. * 0.1411)\"\n\t\t#~ DileptonNeutrinoScaleFactor = \"((nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 2 && nGenSUSYSleptons == 0 && motherPdgId1 != 1000011 && motherPdgId1 != 2000011 && motherPdgId1 != 1000013 && motherPdgId1 != 2000013 && motherPdgId2 != 1000011 && motherPdgId2 != 2000011 && motherPdgId2 != 1000013 && motherPdgId2 != 2000013 ) * 9./2. * 0.0404)\"\n\t\tDileptonQuarkScaleFactor = \"((nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 0 && motherPdgId1 != 1000011 && motherPdgId1 != 2000011 && motherPdgId1 != 1000013 && motherPdgId1 != 2000013 && motherPdgId2 != 1000011 && motherPdgId2 != 2000011 && motherPdgId2 != 1000013 && motherPdgId2 != 2000013 ) * 9./2. * 0.1411)\"\n\t\tDileptonNeutrinoScaleFactor = \"((nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 2 && motherPdgId1 != 1000011 && motherPdgId1 != 2000011 && motherPdgId1 != 1000013 && motherPdgId1 != 2000013 && motherPdgId2 != 1000011 && motherPdgId2 != 2000011 && motherPdgId2 != 1000013 && motherPdgId2 != 2000013 ) * 9./2. * 0.0404)\"\n\t\tDiSleptonScaleFactor = \"(nGenSUSYLeptons == 2 && nGenSUSYNeutrinos == 0 && (motherPdgId1 == 1000011 \|\| motherPdgId1 == 2000011 \|\| motherPdgId1 == 1000013 \|\| motherPdgId1 == 2000013 \|\| motherPdgId2 == 1000011 \|\| motherPdgId2 == 2000011 \|\| motherPdgId2 == 1000013 \|\| motherPdgId2 == 2000013 ) )\"\n\t\tMultileptonScaleFactor = \"((nGenSUSYLeptons == 4)90.0102)\"\n\t\tpath = \"/user/schomakers/trees/sw538v0477/GridScanSlepton\"\n\t\tm_n_min = 150\n\t\tm_neutralino_1 = \"100\"\n\n\tptCut = \"pt1 > 20 && pt2 > 20\"\n\tptCutLabel = \"20\"\n\tmllCut = mllCuts[argv[2]]\n\tvariable = \"p4.M()\"\n\tetaCut = etaCuts[argv[1]]\n\tadditionalCut = \"\"\n\tif additionalCut == \"NJets3Cut\":\n\t\tsuffix = argv[1]+\"_\"+argv[2]+\"_NJets3Cut\"\n\t\tcuts = \"weightsbottomWeight(chargeProduct < 0 && %s && %s && %s && nJetsSmeared >= 3 && abs(eta1) < 2.4 && abs(eta2) < 2.4 && deltaR > 0.3)\"%(ptCut,etaCut,mllCut)\n\telif additionalCut == \"Met150Cut\":\n\t\tsuffix = argv[1]+\"_\"+argv[2]+\"_Met150Cut\"\n\t\tcuts = \"weightsbottomWeight(chargeProduct < 0 && %s && %s && %s && patPFMet > 150 && abs(eta1) < 2.4 && abs(eta2) < 2.4 && deltaR > 0.3)\"%(ptCut,etaCut,mllCut)\n\telse:\n\t\tsuffix = argv[1]+\"_\"+argv[2]\n\t\tcuts = \"weightsbottomWeight(chargeProduct < 0 && %s && %s && %s && ((patPFMet > 100 && nJetsSmeared >= 3) \|\| (patPFMet > 150 && nJetsSmeared >=2)) && abs(eta1) < 2.4 && abs(eta2) < 2.4 && deltaR > 0.3)\"%(ptCut,etaCut,mllCut)\n\t\n\tif m_neutr_1_fix == False:\n\t\tISR_incl_cuts = \"weight(%s+%s+%s+%s+%s+%s)\"%(MultiQuarkScaleFactor,NeutrinoQuarkScaleFactor,MultiNeutrinoScaleFactor,DileptonNeutrinoScaleFactor,DileptonQuarkScaleFactor,MultileptonScaleFactor)\n\t\tcuts = \"%s (%s+%s+%s+%s+%s+%s)\"%(cuts,MultiQuarkScaleFactor,NeutrinoQuarkScaleFactor,MultiNeutrinoScaleFactor,DileptonNeutrinoScaleFactor,DileptonQuarkScaleFactor,MultileptonScaleFactor)\n\telse:\n\t\tISR_incl_cuts = \"weight(%s+%s+%s+%s+%s+%s+%s)\"%(SleptonNeutrinoScaleFactor,SleptonQuarkScaleFactor,SleptonLeptonScaleFactor,DileptonQuarkScaleFactor,DileptonNeutrinoScaleFactor,DiSleptonScaleFactor,MultileptonScaleFactor)\n\t\tcuts = \"%s (%s+%s+%s+%s+%s+%s+%s)\"%(cuts,SleptonNeutrinoScaleFactor,SleptonQuarkScaleFactor,SleptonLeptonScaleFactor,DileptonQuarkScaleFactor,DileptonNeutrinoScaleFactor,DiSleptonScaleFactor,MultileptonScaleFactor)\n\t\t\t\n\tif argv[1] == \"Barrel\":\n\t\tEETriggerEff = 0.971\n\t\tEMuTriggerEff = 0.941\n\t\tMuMuTriggerEff = 0.97\n\telif \"Endcap\" in argv[1]:\n\t\tEETriggerEff = 0.974\n\t\tEMuTriggerEff = 0.873\n\t\tMuMuTriggerEff = 0.967\n\telif argv[1] == \"Inclusive\":\n\t\tEETriggerEff = 0.972\n\t\tEMuTriggerEff = 0.927\n\t\tMuMuTriggerEff = 0.969\n\t\n\ttriggerEffUncertainty = 0.05\n\tlumiUncertainty = 0.026\n\t\n\t#~ if argv[1] == \"Endcap\":\n\t\t#~ FastSimUncertainty = 0.02\n\t#~ else:\n\t\t#~ FastSimUncertainty = 0.1\n\tFastSimUncertainty = 0.02\n\t\n\t\n\t\n\t\n\ttotalEvents = totalNumberOfGeneratedEvents(path)\n\t\n\ti = 0\n\twhile m_b_min + istep_size <= m_b_max:\n\t\tm_b = m_b_min + istep_size\n\t\tM_SBOTTOM = \"m_b_\"+str(m_b_min + istep_size)\n\t\tm_sbottom = str(m_b_min + istep_size)\n\t\tj = 0\n\t\twhile m_n_min + jstep_size <= m_n_max:\n\t\t\tm_n_2 = m_n_min + jstep_size\n\t\t\tm_neutralino_2 = str(m_n_min + jstep_size)\n\t\t\tif m_b >= m_n_2:\t\t\n\t\t\t#~ if m_b >= m_n_2 and not (m_b == 225 and m_n_2 == 150):\n\t\t\t#~ if m_b >= m_n_2 and not (m_b == 450 and m_n_2 == 150) and not (m_b == 450 and m_n_2 == 400) and not (m_b == 475 and m_n_2 == 175) and not (m_b == 525 and m_n_2 == 350):\n\t\t\t\tprint \"m_b: \"+m_sbottom\n\t\t\t\tprint \"m_n: \"+m_neutralino_2\n\t\t\t\t\n\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\t#~ m_neutralino_1 = \"m_n_1_\"+str(m_n_min + jstep_size - 70)\n\t\t\t\t\tm_neutralino_1 = str(m_n_min + jstep_size - 70)\n\n\n\t\t\t\tEMutrees = readTrees(path, \"EMu\")\t\n\t\t\t\tEEtrees = readTrees(path, \"EE\")\t\n\t\t\t\tMuMutrees = readTrees(path, \"MuMu\")\t\n\t\t\t\n\t\t\t\n\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\tsampleName = \"SUSY_Simplified_Model_Madgraph_FastSim_T6bblledge_%s_%s_%s_8TeV\"%(m_sbottom,m_neutralino_2,m_neutralino_1)\n\t\t\t\t\tfileName = \"SUSY_Simplified_Model_Madgraph_FastSim_T6bblledge_%s_%s_%s_8TeV\"%(m_sbottom,m_neutralino_2,m_neutralino_1)\n\t\t\t\telse:\n\t\t\t\t\tsampleName = \"SUSY_Simplified_Model_Madgraph_FastSim_T6bbslepton_%s_%s_%s_8TeV\"%(m_sbottom,m_neutralino_2,m_neutralino_1)\n\t\t\t\t\tfileName = \"SUSY_Simplified_Model_Madgraph_FastSim_T6bbslepton_%s_%s_%s_8TeV\"%(m_sbottom,m_neutralino_2,m_neutralino_1)\n\n\t\t\t\txsection = getattr(sbottom_masses, M_SBOTTOM).cross_section\n\t\t\t\t\n\t\t\t\tscalingLumi = lumixsection/totalEvents[sampleName]\n\t\t\t\tweight = 1./totalEvents[sampleName]\n\t\t\t\tfor sample, tree in EEtrees.iteritems():\n\t\t\t\t\tif sample == sampleName:\n\t\t\t\t\t\tEEISRUncertainty,EEISRMean,EEISRUp,EEISRDown,EEISRCorrectionFactor = produceISRUncertainty(tree,cuts,\"EE\",ISR_incl_cuts)\n\t\t\t\t\t\tEEsignalNumber, EEMCEvents = signalNumbers(tree,argv[1],argv[2],\"EE\",ElectronScaleFactors,MuonScaleFactors,additionalCut,m_neutr_1_fix)\n\t\t\t\t\t\tEEsignalYield = EEsignalNumber * EETriggerEff * scalingLumi * EEISRCorrectionFactor\n\t\t\t\t\t\tEEsignalEfficiency = EEsignalNumber * EETriggerEff * weight\n\t\t\t\t\t\tEEstatUncertainty = statisticalUncertainty(tree,cuts,\"EE\")\n\t\t\t\t\t\tEEmetUncertainty,EEPFMetMean,EEPFMetJetEnUp,EEPFMetJetEnDown,EEpatPFMetJetResUp,EEpatPFMetJetResDown,EEpatPFMetElectronEnUp,EEpatPFMetElectronEnDown,EEpatPFMetMuonEnUp,EEpatPFMetMuonEnDown,EEpatPFMetTauEnUp,EEpatPFMetTauEnDown,EEpatPFMetUnclusteredEnUp,EEpatPFMetUnclusteredEnDown = produceMETUncertainty(tree,cuts,\"EE\")\n\t\t\t\t\t\tEEjetUncertainty,EEnJetsMean,EEnJetsEnUp,EEnJetsEnDown,EEnJetsResUp,EEnJetsResDown = produceJetUncertainty(tree,cuts,\"EE\")\n\t\t\t\t\t\tEEleptonUncertainty,EEleptonptMean,EEleptonptScaleUp,EEleptonptScaleDown = produceLeptonUncertaintySF(tree,cuts,\"EE\",argv[1])\n\t\t\t\t\t\tEEpileupUncertainty,EEPileupMean,EEPileupUp,EEPileupDown = producePileupUncertainty(tree,cuts,\"EE\")\n\t\t\t\t\t\t#~ EEscalingUncertainty = produceScalingUncertainty(tree,cuts)\n\t\t\t\t\t\t#~ EEpdfUncertainty = producePDFUncertainty(sample,path,\"EE\")\n\t\t\t\t\t\tEEpdfUncertainty,EECT10Mean,EECT10AbsMean,EECT10Up,EECT10AbsUp,EECT10Down,EECT10AbsDown,EEMSTWMean,EEMSTWAbsMean,EEMSTWUp,EEMSTWAbsUp,EEMSTWDown,EEMSTWAbsDown,EENNPDFMean,EENNPDFAbsMean,EENNPDFUp,EENNPDFAbsUp,EENNPDFDown,EENNPDFAbsDown = producePDFUncertainty2(sample,path,\"EE\")\n\t\t\t\t\t\tEEsystUncertainty = sqrt(EEmetUncertainty2+EEjetUncertainty2+EEleptonUncertainty2+EEpileupUncertainty2+EEpdfUncertainty2+EEISRUncertainty2+triggerEffUncertainty2+lumiUncertainty2+FastSimUncertainty*2)\n\t\t\t\t\t\tcounts = {}\n\t\t\t\t\t\t#~ counts[\"EE\"] = {\"EEval\":EEsignalYield,\"EEsignalEfficiency\":EEsignalEfficiency,\"EEstatUncertainty\":EEstatUncertainty,\"EETotSystUncertainty\":EEsystUncertainty,\"EEmetUncertainty\":EEmetUncertainty,\"EEjetUncertainty\":EEjetUncertainty,\"EEleptonUncertainty\":EEleptonUncertainty,\"EEpileupUncertainty\":EEpileupUncertainty,\"EEscalingUncertainty\":EEscalingUncertainty,\"EEpdfUncertainty\":EEpdfUncertainty,\"EEpdfUncertainty2\":EEpdfUncertainty2,\"EEISRUncertainty\":EEISRUncertainty}\n\t\t\t\t\t\tcounts[\"EE\"] = {\"EEMCEvents\":EEMCEvents,\"EEval\":EEsignalYield,\"EEsignalEfficiency\":EEsignalEfficiency,\"EEstatUncertainty\":EEstatUncertainty,\"EETotSystUncertainty\":EEsystUncertainty,\n\t\t\t\t\t\t\"EEmetUncertainty\":EEmetUncertainty,\"EEPFMetMean\":EEPFMetMean,\"EEPFMetJetEnUp\":EEPFMetJetEnUp,\"EEPFMetJetEnDown\":EEPFMetJetEnDown,\"EEpatPFMetJetResUp\":EEpatPFMetJetResUp,\"EEpatPFMetJetResDown\":EEpatPFMetJetResDown,\"EEpatPFMetElectronEnUp\":EEpatPFMetElectronEnUp,\"EEpatPFMetElectronEnDown\":EEpatPFMetElectronEnDown,\"EEpatPFMetMuonEnUp\":EEpatPFMetMuonEnUp,\"EEpatPFMetMuonEnDown\":EEpatPFMetMuonEnDown,\"EEpatPFMetTauEnUp\":EEpatPFMetTauEnUp,\"EEpatPFMetTauEnDown\":EEpatPFMetTauEnDown,\"EEpatPFMetUnclusteredEnUp\":EEpatPFMetUnclusteredEnUp,\"EEpatPFMetUnclusteredEnDown\":EEpatPFMetUnclusteredEnDown,\n\t\t\t\t\t\t\"EEjetUncertainty\":EEjetUncertainty,\"EEnJetsMean\":EEnJetsMean,\"EEnJetsEnUp\":EEnJetsEnUp,\"EEnJetsEnDown\":EEnJetsEnDown,\"EEnJetsResUp\":EEnJetsResUp,\"EEnJetsResDown\":EEnJetsResDown,\n\t\t\t\t\t\t\"EEleptonUncertainty\":EEleptonUncertainty,\"EEleptonptMean\":EEleptonptMean,\"EEleptonptScaleUp\":EEleptonptScaleUp,\"EEleptonptScaleDown\":EEleptonptScaleDown,\n\t\t\t\t\t\t\"EEpileupUncertainty\":EEpileupUncertainty,\"EEPileupMean\":EEPileupMean,\"EEPileupUp\":EEPileupUp,\"EEPileupDown\":EEPileupDown,\n\t\t\t\t\t\t\"EEpdfUncertainty\":EEpdfUncertainty,\"EECT10Mean\":EECT10Mean,\"EECT10AbsMean\":EECT10AbsMean,\"EECT10Up\":EECT10Up,\"EECT10AbsUp\":EECT10AbsUp,\"EECT10Down\":EECT10Down,\"EECT10AbsDown\":EECT10AbsDown,\"EEMSTWMean\":EEMSTWMean,\"EEMSTWAbsMean\":EEMSTWAbsMean,\"EEMSTWUp\":EEMSTWUp,\"EEMSTWAbsUp\":EEMSTWAbsUp,\"EEMSTWDown\":EEMSTWDown,\"EEMSTWAbsDown\":EEMSTWAbsDown,\"EENNPDFMean\":EENNPDFMean,\"EENNPDFAbsMean\":EENNPDFAbsMean,\"EENNPDFUp\":EENNPDFUp,\"EENNPDFAbsUp\":EENNPDFAbsUp,\"EENNPDFDown\":EENNPDFDown,\"EENNPDFAbsDown\":EENNPDFAbsDown,\n\t\t\t\t\t\t\"EEISRUncertainty\":EEISRUncertainty,\"EEISRMean\":EEISRMean,\"EEISRUp\":EEISRUp,\"EEISRDown\":EEISRDown}\n\t\t\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\t\t\toutFilePkl = open(\"shelvesZDecayLeptonScaling/%s_%s_EE.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t#~ print \"shelvesSleptonLeptonScaling/%s_%s_EE.pkl\"%(fileName,suffix)\n\t\t\t\t\t\t\toutFilePkl = open(\"shelvesSleptonLeptonScalingReweighted/%s_%s_EE.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t\t\tpickle.dump(counts, outFilePkl)\n\t\t\t\t\t\toutFilePkl.close()\n\t\t\t\tfor sample, tree in EMutrees.iteritems():\n\t\t\t\t\tif sample == sampleName:\n\t\t\t\t\t\tEMuISRUncertainty,EMuISRMean,EMuISRUp,EMuISRDown, EMuISRCorrectionFactor = produceISRUncertainty(tree,cuts,\"EMu\",ISR_incl_cuts)\n\t\t\t\t\t\tEMusignalNumber, EMuMCEvents = signalNumbers(tree,argv[1],argv[2],\"EMu\",ElectronScaleFactors,MuonScaleFactors,additionalCut,m_neutr_1_fix)\n\t\t\t\t\t\tEMusignalYield = EMusignalNumber EMuTriggerEff * scalingLumi * EMuISRCorrectionFactor\n\t\t\t\t\t\tEMusignalEfficiency = EMusignalNumber * EMuTriggerEff * weight\n\t\t\t\t\t\tEMustatUncertainty = statisticalUncertainty(tree,cuts,\"EMu\")\n\t\t\t\t\t\tEMumetUncertainty,EMuPFMetMean,EMuPFMetJetEnUp,EMuPFMetJetEnDown,EMupatPFMetJetResUp,EMupatPFMetJetResDown,EMupatPFMetElectronEnUp,EMupatPFMetElectronEnDown,EMupatPFMetMuonEnUp,EMupatPFMetMuonEnDown,EMupatPFMetTauEnUp,EMupatPFMetTauEnDown,EMupatPFMetUnclusteredEnUp,EMupatPFMetUnclusteredEnDown = produceMETUncertainty(tree,cuts,\"EMu\")\n\t\t\t\t\t\tEMujetUncertainty,EMunJetsMean,EMunJetsEnUp,EMunJetsEnDown,EMunJetsResUp,EMunJetsResDown = produceJetUncertainty(tree,cuts,\"EMu\")\n\t\t\t\t\t\tEMuleptonUncertainty,EMuleptonptMean,EMuleptonpt1ScaleUp,EMuleptonpt2ScaleUp,EMuleptonpt1ScaleDown,EMuleptonpt2ScaleDown = produceLeptonUncertaintyEMu(tree,cuts,\"EMu\",argv[1])\n\t\t\t\t\t\tEMupileupUncertainty,EMuPileupMean,EMuPileupUp,EMuPileupDown = producePileupUncertainty(tree,cuts,\"EMu\")\n\t\t\t\t\t\t#~ EMuscalingUncertainty = produceScalingUncertainty(tree,cuts)\n\t\t\t\t\t\t#~ EMupdfUncertainty = producePDFUncertainty(sample,path,\"EMu\")\n\t\t\t\t\t\tEMupdfUncertainty,EMuCT10Mean,EMuCT10AbsMean,EMuCT10Up,EMuCT10AbsUp,EMuCT10Down,EMuCT10AbsDown,EMuMSTWMean,EMuMSTWAbsMean,EMuMSTWUp,EMuMSTWAbsUp,EMuMSTWDown,EMuMSTWAbsDown,EMuNNPDFMean,EMuNNPDFAbsMean,EMuNNPDFUp,EMuNNPDFAbsUp,EMuNNPDFDown,EMuNNPDFAbsDown = producePDFUncertainty2(sample,path,\"EMu\")\n\t\t\t\t\t\tEMusystUncertainty = sqrt(EMumetUncertainty2+EMujetUncertainty2+EMuleptonUncertainty2+EMupileupUncertainty2+EMupdfUncertainty2+EMuISRUncertainty2+triggerEffUncertainty2+lumiUncertainty2+FastSimUncertainty*2)\n\t\t\t\t\t\tcounts = {}\n\t\t\t\t\t\t#~ counts[\"EMu\"] = {\"EMuval\":EMusignalYield,\"EMusignalEfficiency\":EMusignalEfficiency,\"EMustatUncertainty\":EMustatUncertainty,\"EMuTotSystUncertainty\":EMusystUncertainty,\"EMumetUncertainty\":EMumetUncertainty,\"EMujetUncertainty\":EMujetUncertainty,\"EMuleptonUncertainty\":EMuleptonUncertainty,\"EMupileupUncertainty\":EMupileupUncertainty,\"EMuscalingUncertainty\":EMuscalingUncertainty,\"EMupdfUncertainty\":EMupdfUncertainty,\"EMupdfUncertainty2\":EMupdfUncertainty2,\"EMuISRUncertainty\":EMuISRUncertainty}\n\t\t\t\t\t\tcounts[\"EMu\"] = {\"EMuMCEvents\":EMuMCEvents,\"EMuval\":EMusignalYield,\"EMusignalEfficiency\":EMusignalEfficiency,\"EMustatUncertainty\":EMustatUncertainty,\"EMuTotSystUncertainty\":EMusystUncertainty,\n\t\t\t\t\t\t\"EMumetUncertainty\":EMumetUncertainty,\"EMuPFMetMean\":EMuPFMetMean,\"EMuPFMetJetEnUp\":EMuPFMetJetEnUp,\"EMuPFMetJetEnDown\":EMuPFMetJetEnDown,\"EMupatPFMetJetResUp\":EMupatPFMetJetResUp,\"EMupatPFMetJetResDown\":EMupatPFMetJetResDown,\"EMupatPFMetElectronEnUp\":EMupatPFMetElectronEnUp,\"EMupatPFMetElectronEnDown\":EMupatPFMetElectronEnDown,\"EMupatPFMetMuonEnUp\":EMupatPFMetMuonEnUp,\"EMupatPFMetMuonEnDown\":EMupatPFMetMuonEnDown,\"EMupatPFMetTauEnUp\":EMupatPFMetTauEnUp,\"EMupatPFMetTauEnDown\":EMupatPFMetTauEnDown,\"EMupatPFMetUnclusteredEnUp\":EMupatPFMetUnclusteredEnUp,\"EMupatPFMetUnclusteredEnDown\":EMupatPFMetUnclusteredEnDown,\n\t\t\t\t\t\t\"EMujetUncertainty\":EMujetUncertainty,\"EMunJetsMean\":EMunJetsMean,\"EMunJetsEnUp\":EMunJetsEnUp,\"EMunJetsEnDown\":EMunJetsEnDown,\"EMunJetsResUp\":EMunJetsResUp,\"EMunJetsResDown\":EMunJetsResDown,\n\t\t\t\t\t\t\"EMuleptonUncertainty\":EMuleptonUncertainty,\"EMuleptonptMean\":EMuleptonptMean,\"EMuleptonpt1ScaleUp\":EMuleptonpt1ScaleUp,\"EMuleptonpt2ScaleUp\":EMuleptonpt2ScaleUp,\"EMuleptonpt1ScaleDown\":EMuleptonpt1ScaleDown,\"EMuleptonpt2ScaleDown\":EMuleptonpt2ScaleDown,\n\t\t\t\t\t\t\"EMupileupUncertainty\":EMupileupUncertainty,\"EMuPileupMean\":EMuPileupMean,\"EMuPileupUp\":EMuPileupUp,\"EMuPileupDown\":EMuPileupDown,\n\t\t\t\t\t\t\"EMupdfUncertainty\":EMupdfUncertainty,\"EMuCT10Mean\":EMuCT10Mean,\"EMuCT10AbsMean\":EMuCT10AbsMean,\"EMuCT10Up\":EMuCT10Up,\"EMuCT10AbsUp\":EMuCT10AbsUp,\"EMuCT10Down\":EMuCT10Down,\"EMuCT10AbsDown\":EMuCT10AbsDown,\"EMuMSTWMean\":EMuMSTWMean,\"EMuMSTWAbsMean\":EMuMSTWAbsMean,\"EMuMSTWUp\":EMuMSTWUp,\"EMuMSTWAbsUp\":EMuMSTWAbsUp,\"EMuMSTWDown\":EMuMSTWDown,\"EMuMSTWAbsDown\":EMuMSTWAbsDown,\"EMuNNPDFMean\":EMuNNPDFMean,\"EMuNNPDFAbsMean\":EMuNNPDFAbsMean,\"EMuNNPDFUp\":EMuNNPDFUp,\"EMuNNPDFAbsUp\":EMuNNPDFAbsUp,\"EMuNNPDFDown\":EMuNNPDFDown,\"EMuNNPDFAbsDown\":EMuNNPDFAbsDown,\n\t\t\t\t\t\t\"EMuISRUncertainty\":EMuISRUncertainty,\"EMuISRMean\":EMuISRMean,\"EMuISRUp\":EMuISRUp,\"EMuISRDown\":EMuISRDown}\n\t\t\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\t\t\toutFilePkl = open(\"shelvesZDecayLeptonScaling/%s_%s_EMu.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\toutFilePkl = open(\"shelvesSleptonLeptonScalingReweighted/%s_%s_EMu.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t\t\tpickle.dump(counts, outFilePkl)\n\t\t\t\t\t\toutFilePkl.close()\n\t\t\t\tfor sample, tree in MuMutrees.iteritems():\n\t\t\t\t\tif sample == sampleName:\n\t\t\t\t\t\tMuMuISRUncertainty,MuMuISRMean,MuMuISRUp,MuMuISRDown,MuMuISRCorrectionFactor = produceISRUncertainty(tree,cuts,\"MuMu\",ISR_incl_cuts)\n\t\t\t\t\t\tMuMusignalNumber, MuMuMCEvents = signalNumbers(tree,argv[1],argv[2],\"MuMu\",ElectronScaleFactors,MuonScaleFactors,additionalCut,m_neutr_1_fix)\n\t\t\t\t\t\tMuMusignalYield = MuMusignalNumber MuMuTriggerEff * scalingLumi * MuMuISRCorrectionFactor\n\t\t\t\t\t\tMuMusignalEfficiency = MuMusignalNumber * MuMuTriggerEff * weight\n\t\t\t\t\t\tMuMustatUncertainty = statisticalUncertainty(tree,cuts,\"MuMu\")\n\t\t\t\t\t\tMuMumetUncertainty,MuMuPFMetMean,MuMuPFMetJetEnUp,MuMuPFMetJetEnDown,MuMupatPFMetJetResUp,MuMupatPFMetJetResDown,MuMupatPFMetElectronEnUp,MuMupatPFMetElectronEnDown,MuMupatPFMetMuonEnUp,MuMupatPFMetMuonEnDown,MuMupatPFMetTauEnUp,MuMupatPFMetTauEnDown,MuMupatPFMetUnclusteredEnUp,MuMupatPFMetUnclusteredEnDown = produceMETUncertainty(tree,cuts,\"MuMu\")\n\t\t\t\t\t\tMuMujetUncertainty,MuMunJetsMean,MuMunJetsEnUp,MuMunJetsEnDown,MuMunJetsResUp,MuMunJetsResDown = produceJetUncertainty(tree,cuts,\"MuMu\")\n\t\t\t\t\t\tMuMuleptonUncertainty,MuMuleptonptMean,MuMuleptonptScaleUp,MuMuleptonptScaleDown = produceLeptonUncertaintySF(tree,cuts,\"MuMu\",argv[1])\n\t\t\t\t\t\tMuMupileupUncertainty,MuMuPileupMean,MuMuPileupUp,MuMuPileupDown = producePileupUncertainty(tree,cuts,\"MuMu\")\n\t\t\t\t\t\t#~ MuMuscalingUncertainty = produceScalingUncertainty(tree,cuts)\n\t\t\t\t\t\t#~ MuMupdfUncertainty = producePDFUncertainty(sample,path,\"MuMu\")\n\t\t\t\t\t\tMuMupdfUncertainty,MuMuCT10Mean,MuMuCT10AbsMean,MuMuCT10Up,MuMuCT10AbsUp,MuMuCT10Down,MuMuCT10AbsDown,MuMuMSTWMean,MuMuMSTWAbsMean,MuMuMSTWUp,MuMuMSTWAbsUp,MuMuMSTWDown,MuMuMSTWAbsDown,MuMuNNPDFMean,MuMuNNPDFAbsMean,MuMuNNPDFUp,MuMuNNPDFAbsUp,MuMuNNPDFDown,MuMuNNPDFAbsDown = producePDFUncertainty2(sample,path,\"MuMu\")\n\t\t\t\t\t\tMuMusystUncertainty = sqrt(MuMumetUncertainty2+MuMujetUncertainty2+MuMuleptonUncertainty2+MuMupileupUncertainty2+MuMupdfUncertainty2+MuMuISRUncertainty2+triggerEffUncertainty2+lumiUncertainty2+FastSimUncertainty*2)\n\t\t\t\t\t\tcounts = {}\n\t\t\t\t\t\t#~ counts[\"MuMu\"] = {\"MuMuval\":MuMusignalYield,\"MuMusignalEfficiency\":MuMusignalEfficiency,\"MuMustatUncertainty\":MuMustatUncertainty,\"MuMuTotSystUncertainty\":MuMusystUncertainty,\"MuMumetUncertainty\":MuMumetUncertainty,\"MuMujetUncertainty\":MuMujetUncertainty,\"MuMuleptonUncertainty\":MuMuleptonUncertainty,\"MuMupileupUncertainty\":MuMupileupUncertainty,\"MuMuscalingUncertainty\":MuMuscalingUncertainty,\"MuMupdfUncertainty\":MuMupdfUncertainty,\"MuMupdfUncertainty2\":MuMupdfUncertainty2,\"MuMuISRUncertainty\":MuMuISRUncertainty}\n\t\t\t\t\t\tcounts[\"MuMu\"] = {\"MuMuMCEvents\":MuMuMCEvents,\"MuMuval\":MuMusignalYield,\"MuMusignalEfficiency\":MuMusignalEfficiency,\"MuMustatUncertainty\":MuMustatUncertainty,\"MuMuTotSystUncertainty\":MuMusystUncertainty,\n\t\t\t\t\t\t\"MuMumetUncertainty\":MuMumetUncertainty,\"MuMuPFMetMean\":MuMuPFMetMean,\"MuMuPFMetJetEnUp\":MuMuPFMetJetEnUp,\"MuMuPFMetJetEnDown\":MuMuPFMetJetEnDown,\"MuMupatPFMetJetResUp\":MuMupatPFMetJetResUp,\"MuMupatPFMetJetResDown\":MuMupatPFMetJetResDown,\"MuMupatPFMetElectronEnUp\":MuMupatPFMetElectronEnUp,\"MuMupatPFMetElectronEnDown\":MuMupatPFMetElectronEnDown,\"MuMupatPFMetMuonEnUp\":MuMupatPFMetMuonEnUp,\"MuMupatPFMetMuonEnDown\":MuMupatPFMetMuonEnDown,\"MuMupatPFMetTauEnUp\":MuMupatPFMetTauEnUp,\"MuMupatPFMetTauEnDown\":MuMupatPFMetTauEnDown,\"MuMupatPFMetUnclusteredEnUp\":MuMupatPFMetUnclusteredEnUp,\"MuMupatPFMetUnclusteredEnDown\":MuMupatPFMetUnclusteredEnDown,\n\t\t\t\t\t\t\"MuMujetUncertainty\":MuMujetUncertainty,\"MuMunJetsMean\":MuMunJetsMean,\"MuMunJetsEnUp\":MuMunJetsEnUp,\"MuMunJetsEnDown\":MuMunJetsEnDown,\"MuMunJetsResUp\":MuMunJetsResUp,\"MuMunJetsResDown\":MuMunJetsResDown,\n\t\t\t\t\t\t\"MuMuleptonUncertainty\":MuMuleptonUncertainty,\"MuMuleptonptMean\":MuMuleptonptMean,\"MuMuleptonptScaleUp\":MuMuleptonptScaleUp,\"MuMuleptonptScaleDown\":MuMuleptonptScaleDown,\n\t\t\t\t\t\t\"MuMupileupUncertainty\":MuMupileupUncertainty,\"MuMuPileupMean\":MuMuPileupMean,\"MuMuPileupUp\":MuMuPileupUp,\"MuMuPileupDown\":MuMuPileupDown,\n\t\t\t\t\t\t\"MuMupdfUncertainty\":MuMupdfUncertainty,\"MuMuCT10Mean\":MuMuCT10Mean,\"MuMuCT10AbsMean\":MuMuCT10AbsMean,\"MuMuCT10Up\":MuMuCT10Up,\"MuMuCT10AbsUp\":MuMuCT10AbsUp,\"MuMuCT10Down\":MuMuCT10Down,\"MuMuCT10AbsDown\":MuMuCT10AbsDown,\"MuMuMSTWMean\":MuMuMSTWMean,\"MuMuMSTWAbsMean\":MuMuMSTWAbsMean,\"MuMuMSTWUp\":MuMuMSTWUp,\"MuMuMSTWAbsUp\":MuMuMSTWAbsUp,\"MuMuMSTWDown\":MuMuMSTWDown,\"MuMuMSTWAbsDown\":MuMuMSTWAbsDown,\"MuMuNNPDFMean\":MuMuNNPDFMean,\"MuMuNNPDFAbsMean\":MuMuNNPDFAbsMean,\"MuMuNNPDFUp\":MuMuNNPDFUp,\"MuMuNNPDFAbsUp\":MuMuNNPDFAbsUp,\"MuMuNNPDFDown\":MuMuNNPDFDown,\"MuMuNNPDFAbsDown\":MuMuNNPDFAbsDown,\n\t\t\t\t\t\t\"MuMuISRUncertainty\":MuMuISRUncertainty,\"MuMuISRMean\":MuMuISRMean,\"MuMuISRUp\":MuMuISRUp,\"MuMuISRDown\":MuMuISRDown}\n\t\t\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\t\t\toutFilePkl = open(\"shelvesZDecayLeptonScaling/%s_%s_MuMu.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\toutFilePkl = open(\"shelvesSleptonLeptonScalingReweighted/%s_%s_MuMu.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t\t\tpickle.dump(counts, outFilePkl)\n\t\t\t\t\t\toutFilePkl.close()\n\t\t\t\t\n\t\t\t\t#~ counts = {}\n\t\t\t\t#~ SFYield = EEsignalYield + MuMusignalYield\n\t\t\t\t#~ if SFYield > 0:\n\t\t\t\t\t#~ SFUncertainty = sqrt((EEsignalYieldEEsystUncertainty)*2 + (MuMusignalYieldMuMusystUncertainty)*2)/SFYield\n\t\t\t\t\t#~ SFStatUncertainty = sqrt((EEsignalYieldEEstatUncertainty)*2 + (MuMusignalYieldMuMustatUncertainty)*2)/SFYield\n\t\t\t\t#~ else: \n\t\t\t\t\t#~ SFUncertainty = 0\n\t\t\t\t\t#~ SFStatUncertainty = 0\n\t\t\t\t\t#~ \n\t\t\t\t#~ SFOFYield = EEsignalYield + MuMusignalYield - EMusignalYield\n\t\t\t\t#~ if SFOFYield > 0:\n\t\t\t\t\t#~ SFOFUncertainty = sqrt((EEsignalYieldEEsystUncertainty)*2 + (MuMusignalYieldMuMusystUncertainty)*2 + (EMusignalYieldMuMusystUncertainty)*2)/SFOFYield\n\t\t\t\t\t#~ SFOFStatUncertainty = sqrt((EEsignalYieldEEstatUncertainty)*2 + (MuMusignalYieldMuMustatUncertainty)*2 + (EMusignalYieldMuMustatUncertainty)*2)/SFOFYield\n\t\t\t\t#~ else:\n\t\t\t\t\t#~ SFOFUncertainty = 0\n\t\t\t\t\t#~ SFOFStatUncertainty = 0\n\t\t\t\t\t#~ \n\t\t\t\t#~ counts[\"Signal\"] = {\"SFYield\":SFYield,\"SFUncertainty\":SFUncertainty,\"SFStatUncertainty\":SFStatUncertainty,\"SFOFYield\":SFOFYield,\"SFOFUncertainty\":SFOFUncertainty,\"SFOFStatUncertainty\":SFOFStatUncertainty,\"EEYield\":EEsignalYield,\"EEsystUncertainty\":EEsystUncertainty,\"EEstatncertainty\":EEstatUncertainty,\"MuMuYield\":MuMusignalYield,\"MuMusystUncertainty\":MuMusystUncertainty,\"MuMustatUncertainty\":MuMustatUncertainty,\"EMuYield\":EMusignalYield,\"EMusystUncertainty\":EMusystUncertainty,\"EMustatUncertainty\":EMustatUncertainty}\t\t\n\t\t\t\t#~ if m_neutr_1_fix == False:\n\t\t\t\t\t#~ outFilePkl = open(\"shelvesZDecayLeptonScaling/%s_%s.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t#~ else:\n\t\t\t\t\t#~ outFilePkl = open(\"shelvesSleptonLeptonScaling/%s_%s.pkl\"%(fileName,suffix),\"w\")\n\t\t\t\t#~ pickle.dump(counts, outFilePkl)\n\t\t\t\t#~ outFilePkl.close()\n\t\t\t\n\t\t\tj += 1\n\t\ti += 1\n\t\t\n" }, { "alpha_fraction": 0.3849862813949585, "alphanum_fraction": 0.6012313365936279, "avg_line_length": 87.9248046875, "blob_id": "cdbd0c5490199309c8993ee4d8ec610729872b05", "content_id": "01e424007bbb68c698fef6f3d0090cda8a94dbe7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67405, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Direct_sbottom_neutralino2_ExpXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:27 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,19.06206);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(227,1.270054);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,1.197084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,33.07942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,13.07348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,8.482519);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,5.663273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,4.123236);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,3.258596);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,2.677017);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,2.231572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,1.924815);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,1.77933);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,1.63196);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,1.546224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,1.487401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,1.378545);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,1.329847);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,1.279441);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,31.6002);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,11.04569);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,7.703727);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,5.329554);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,4.071905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,3.167204);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,2.577655);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,2.247347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,1.98411);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,1.760756);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,1.632609);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,1.56313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,1.463856);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,1.37804);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,1.339713);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,30.63696);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,10.44074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,7.341362);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,5.194313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,4.004358);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,3.027921);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,2.579629);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,2.14062);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,1.993757);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,1.792025);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,1.613271);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,1.49188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,1.460486);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,1.390838);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,27.76401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,9.587703);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,7.040805);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,4.979378);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,3.882481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,2.85497);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,2.436083);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,2.123567);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,1.91056);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,1.788299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,1.645767);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,1.518074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,1.480323);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,27.7219);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,9.088602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,6.373537);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,4.859356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,3.674273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,2.81324);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,2.388566);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,2.133053);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,1.941368);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,1.7464);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,1.665078);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,1.574207);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,25.66299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,9.719526);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,6.031348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,4.506365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,3.548137);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,2.885986);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,2.333739);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,2.073334);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,1.899293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,1.74754);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,1.627773);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,20.913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,8.684512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,6.416571);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,4.570333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,3.364413);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,2.868853);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,2.275452);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,2.048141);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,1.83383);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,1.674835);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,15.555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,8.371037);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,6.040381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,4.332144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,3.301337);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,2.771252);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,2.301142);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,2.044295);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,1.871305);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,11.709);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,8.223111);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,6.055455);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,4.276425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,3.333248);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,2.68921);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,2.296996);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,8.883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,6.783);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,5.80346);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,3.320863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,24.97795);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,5.238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,3.233187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,25.38213);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,7.854313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,5.275032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(24,19.06206);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(25,12.54259);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(26,8.557866);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(27,5.98056);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(28,4.810152);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(29,3.778947);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(30,3.090287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(31,2.572361);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(32,2.148796);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(33,2.007281);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(34,1.787109);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(35,1.650844);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(36,1.530057);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(37,1.443591);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(38,1.327872);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(39,1.279075);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(40,1.240163);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(41,1.198043);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(42,1.152871);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(43,1.097407);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(44,1.098876);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(47,20.39458);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(48,12.42643);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(49,8.038885);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(50,5.845269);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(51,4.451654);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(52,3.534502);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(53,2.75928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(54,2.410539);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(55,2.022853);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(56,1.774585);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(57,1.624552);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(58,1.481561);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(59,1.394915);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(60,1.29644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(61,1.243356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(62,1.182944);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(63,1.153493);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(64,1.089286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(65,1.044341);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(66,1.018037);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(67,0.9768515);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(70,22.58431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(71,14.67631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(72,9.613099);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(73,6.555065);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(74,4.691039);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(75,3.624585);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(76,2.939659);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(77,2.417073);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(78,2.042987);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(79,1.793622);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(80,1.591959);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(81,1.522926);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(82,1.39224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(83,1.302404);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(84,1.228507);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(85,1.179602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(86,1.127249);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(87,1.08387);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(88,1.068364);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(89,1.018214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(90,0.9655737);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(93,30.46788);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(94,16.91393);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(95,11.42944);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(96,7.580052);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(97,5.220734);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(98,4.014184);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(99,3.183769);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(100,2.529491);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(101,2.236747);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(102,1.910338);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(103,1.737826);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(104,1.579064);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(105,1.434513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(106,1.362217);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(107,1.233286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(108,1.211629);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(109,1.172441);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(110,1.118878);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(111,1.088115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(112,1.04259);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(113,1.01224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(116,63.8549);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(117,22.64935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(118,14.66719);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(119,9.485905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(120,6.523725);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(121,4.545431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(122,3.658469);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(123,2.810527);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(124,2.399159);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(125,2.062792);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(126,1.837492);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(127,1.706229);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(128,1.547401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(129,1.463609);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(130,1.332577);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(131,1.279296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(132,1.229764);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(133,1.14184);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(134,1.116171);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(135,1.082359);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(136,1.051974);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(140,50.15274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(141,18.50254);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(142,11.86648);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(143,8.090916);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(144,5.765191);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(145,4.063602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(146,3.430197);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(147,2.66136);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(148,2.240804);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(149,1.964384);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(150,1.763991);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(151,1.636287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(152,1.499564);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(153,1.424952);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(154,1.315873);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(155,1.256034);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(156,1.193411);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(157,1.168354);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(158,1.144307);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(159,1.088222);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(164,42.42694);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(165,15.49369);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(166,10.72718);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(167,7.119751);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(168,5.262226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(169,3.761484);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(170,3.058681);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(171,2.516062);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(172,2.14697);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(173,1.964302);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(174,1.725682);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(175,1.59973);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(176,1.51255);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(177,1.413903);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(178,1.302657);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(179,1.283426);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(180,1.216034);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(181,1.186003);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(182,1.160126);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(188,37.95161);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(189,13.43024);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(190,9.072982);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(191,6.579193);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(192,4.934134);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(193,3.672997);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(194,3.002827);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(195,2.381561);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(196,2.114214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(197,1.78196);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(198,1.675687);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(199,1.564456);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(200,1.476476);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(201,1.392367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(202,1.346754);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(203,1.285584);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(204,1.225925);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(205,1.211017);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(212,38.15747);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(213,12.28734);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(214,8.61232);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(215,6.258218);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(216,4.428197);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(217,3.432218);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(218,2.705168);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(219,2.343232);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(220,2.02004);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(221,1.840581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(222,1.684013);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(223,1.580174);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(224,1.478602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(225,1.412913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(226,1.325366);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(227,1.270054);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(228,1.197084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(236,33.07942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(237,13.07348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(238,8.482519);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(239,5.663273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(240,4.123236);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(241,3.258596);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(242,2.677017);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(243,2.231572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(244,1.924815);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(245,1.77933);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(246,1.63196);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(247,1.546224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(248,1.487401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(249,1.378545);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(250,1.329847);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(251,1.279441);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(260,31.6002);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(261,11.04569);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(262,7.703727);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(263,5.329554);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(264,4.071905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(265,3.167204);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(266,2.577655);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(267,2.247347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(268,1.98411);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(269,1.760756);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(270,1.632609);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(271,1.56313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(272,1.463856);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(273,1.37804);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(274,1.339713);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(284,30.63696);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(285,10.44074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(286,7.341362);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(287,5.194313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(288,4.004358);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(289,3.027921);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(290,2.579629);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(291,2.14062);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(292,1.993757);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(293,1.792025);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(294,1.613271);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(295,1.49188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(296,1.460486);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(297,1.390838);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(308,27.76401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(309,9.587703);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(310,7.040805);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(311,4.979378);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(312,3.882481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(313,2.85497);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(314,2.436083);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(315,2.123567);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(316,1.91056);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(317,1.788299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(318,1.645767);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(319,1.518074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(320,1.480323);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(332,27.7219);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(333,9.088602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(334,6.373537);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(335,4.859356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(336,3.674273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(337,2.81324);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(338,2.388566);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(339,2.133053);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(340,1.941368);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(341,1.7464);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(342,1.665078);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(343,1.574207);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(356,25.66299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(357,9.719526);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(358,6.031348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(359,4.506365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(360,3.548137);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(361,2.885986);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(362,2.333739);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(363,2.073334);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(364,1.899293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(365,1.74754);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(366,1.627773);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(380,20.913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(381,8.684512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(382,6.416571);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(383,4.570333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(384,3.364413);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(385,2.868853);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(386,2.275452);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(387,2.048141);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(388,1.83383);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(389,1.674835);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(404,15.555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(405,8.371037);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(406,6.040381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(407,4.332144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(408,3.301337);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(409,2.771252);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(410,2.301142);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(411,2.044295);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(412,1.871305);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(428,11.709);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(429,8.223111);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(430,6.055455);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(431,4.276425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(432,3.333248);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(433,2.68921);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(434,2.296996);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(435,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(452,8.883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(453,6.783);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(454,5.80346);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(455,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(456,3.320863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(457,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(458,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(476,24.97795);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(477,5.238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(478,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(479,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(480,3.233187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(481,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(500,25.38213);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(501,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(502,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(503,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(504,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(524,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(525,7.854313);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(526,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(527,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(548,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(549,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(550,5.275032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(572,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(573,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(596,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetDirectory(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4930935204029083, "alphanum_fraction": 0.6800000071525574, "avg_line_length": 44.424835205078125, "blob_id": "37c84b7eda8f0305f35bb0dab95086b53583a14d", "content_id": "77cf881c438deacd096ff634e95620d6034e4d98", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 6950, "license_type": "no_license", "max_line_length": 155, "num_lines": 153, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:34 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(59.79729,-39.18919,769.2568,805.4054);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 48134370_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(14);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,362.5000001,100);\n graph->SetPoint(1,362.5000001,125);\n graph->SetPoint(2,362.2089999,149.7089999);\n graph->SetPoint(3,360.5675625,173.0675625);\n graph->SetPoint(4,356.0965692,193.5965692);\n graph->SetPoint(5,347.7765624,210.2765624);\n graph->SetPoint(6,335.2765624,222.7765624);\n graph->SetPoint(7,318.5965692,231.0965692);\n graph->SetPoint(8,298.0675625,235.619123);\n graph->SetPoint(9,274.9484395,237.1572754);\n graph->SetPoint(10,251.6931619,236.1204745);\n graph->SetPoint(11,230.2515968,232.3088279);\n graph->SetPoint(12,212.5286324,226.2935392);\n graph->SetPoint(13,200,221.2121297);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Observed limit\",100,183.75,378.75);\n Graph_Graph1->SetMinimum(86.28427);\n Graph_Graph1->SetMaximum(250.873);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n \n graph = new TGraph(24);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,462.5000001,100);\n graph->SetPoint(1,462.5000001,125);\n graph->SetPoint(2,462.5000001,150);\n graph->SetPoint(3,462.2089999,174.7089999);\n graph->SetPoint(4,460.5675625,198.0675625);\n graph->SetPoint(5,456.3875694,218.8875693);\n graph->SetPoint(6,449.7089999,237.2089999);\n graph->SetPoint(7,441.6799932,254.1799932);\n graph->SetPoint(8,433.0290068,270.5290068);\n graph->SetPoint(9,423.0675625,285.5675625);\n graph->SetPoint(10,410.2765624,297.7765624);\n graph->SetPoint(11,393.5965692,306.0965692);\n graph->SetPoint(12,373.0675625,310.619123);\n graph->SetPoint(13,349.9484395,312.1572754);\n graph->SetPoint(14,326.6931619,311.1204745);\n graph->SetPoint(15,305.8505188,306.9662673);\n graph->SetPoint(16,288.5627395,299.121826);\n graph->SetPoint(17,274.2367366,288.3179736);\n graph->SetPoint(18,261.3910263,276.1058241);\n graph->SetPoint(19,248.8941759,263.6089737);\n graph->SetPoint(20,236.3910263,251.1058241);\n graph->SetPoint(21,223.6378146,238.9515344);\n graph->SetPoint(22,211.0950181,228.2775373);\n graph->SetPoint(23,200,221.5031298);\n \n TH1F Graph_Graph2 = new TH1F(\"Graph_Graph2\",\"Expected limit\",100,173.75,488.75);\n Graph_Graph2->SetMinimum(78.78427);\n Graph_Graph2->SetMaximum(333.373);\n Graph_Graph2->SetDirectory(0);\n Graph_Graph2->SetStats(0);\n Graph_Graph2->SetLineStyle(0);\n Graph_Graph2->GetXaxis()->SetNdivisions(505);\n Graph_Graph2->GetXaxis()->SetLabelFont(42);\n Graph_Graph2->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetXaxis()->SetTitleSize(32);\n Graph_Graph2->GetXaxis()->SetTitleFont(43);\n Graph_Graph2->GetYaxis()->SetLabelFont(42);\n Graph_Graph2->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetYaxis()->SetTitleSize(32);\n Graph_Graph2->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph2->GetYaxis()->SetTitleFont(43);\n Graph_Graph2->GetZaxis()->SetLabelFont(42);\n Graph_Graph2->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetZaxis()->SetTitleSize(32);\n Graph_Graph2->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph2->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph2);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.38388505578041077, "alphanum_fraction": 0.6024438738822937, "avg_line_length": 88.0699234008789, "blob_id": "0aaf97b0eac5b01ba8c1ab5541568d33df6c198e", "content_id": "096a2ee59247f37be7546ac007ac4b327a84df55", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67515, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Sel_Eff_sbottom_neutralino2_R_firstguess.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 09:50:02 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,0.08197557);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(25,0.0920526);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(26,0.1098894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(27,0.1270819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(28,0.157602);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(29,0.1897137);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(30,0.2296345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(31,0.2574148);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(32,0.3361717);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.4320944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.5342559);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.672646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,0.8396202);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,1.042318);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,1.269899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,1.600185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,2.014635);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,2.489708);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,3.059931);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,3.664943);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,4.625959);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(47,0.08446342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(48,0.09225304);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(49,0.1053103);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(50,0.1210724);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(51,0.1477131);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(52,0.1775535);\n 280730369_m(#tilde{b}) 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[GeV]->SetBinContent(264,1.196044);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,1.274824);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,1.385013);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,1.606117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,1.900541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,2.226862);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,2.654043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,3.262881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,3.899225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,4.65911);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,5.642953);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(295,4.049769);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,4.882262);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,5.926434);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,3.880034);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,1.889988);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.976056);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.9675);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,2.074382);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,2.06674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,2.324959);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,2.682806);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,3.102864);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,3.699826);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,4.388697);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,5.114275);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,6.259937);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,5.450776);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.500651);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,2.439048);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,2.564476);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,2.632442);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,2.689652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,3.0018);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,3.458288);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,4.009705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,4.602777);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,5.57308);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,6.591648);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,6.918873);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,3.640127);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,3.132294);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,3.160293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,3.339123);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,3.57692);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,3.799472);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,4.266633);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,5.038926);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,5.850757);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,6.946541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,4.324032);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,4.426183);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,4.239766);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,4.204695);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,4.636396);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,4.723184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,5.421702);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,6.18238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,7.168906);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,5.590381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,5.43917);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,5.30539);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,5.315122);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,5.743065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,6.04882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,6.880711);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,7.849961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,7.189101);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,7.233362);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,6.825326);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,6.83561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,7.113951);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,7.637677);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,8.493562);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,9.400339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,8.915216);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,8.649788);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,8.63107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,8.696213);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,9.468165);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,28.33025);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,11.4791);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,11.27561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,10.76409);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,10.87404);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,37.66139);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,19.24593);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,21.1752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,10);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(24,0.08197557);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(25,0.0920526);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(26,0.1098894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(27,0.1270819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(28,0.157602);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(29,0.1897137);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(30,0.2296345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(31,0.2574148);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(32,0.3361717);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(33,0.4320944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(34,0.5342559);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(35,0.672646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(36,0.8396202);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(37,1.042318);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(38,1.269899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(39,1.600185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(40,2.014635);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(41,2.489708);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(42,3.059931);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(43,3.664943);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(44,4.625959);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(47,0.08446342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(48,0.09225304);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(49,0.1053103);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(50,0.1210724);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(51,0.1477131);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(52,0.1775535);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(53,0.2056341);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(54,0.2417841);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(55,0.3149792);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(56,0.3852053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(57,0.4871881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(58,0.60401);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(59,0.7631103);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(60,0.9424257);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(61,1.188329);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(62,1.465612);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(63,1.872103);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(64,2.272508);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(65,2.758717);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(66,3.41162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(67,4.129162);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(70,0.08960128);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(71,0.1114793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(72,0.1214151);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(73,0.1366261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(74,0.1555192);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(75,0.1825599);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(76,0.2187695);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(77,0.2440111);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(78,0.3161058);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(79,0.3874664);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(80,0.4786614);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(81,0.6186178);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(82,0.7624645);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(83,0.9451705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(84,1.176983);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(85,1.490211);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(86,1.846529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(87,2.240344);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(88,2.785155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(89,3.435735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(90,4.072715);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(93,0.1200615);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(94,0.1228996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(95,0.1430631);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(96,0.1583793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(97,0.1732338);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(98,0.2006727);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(99,0.2366143);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(100,0.255555);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(101,0.3427851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(102,0.4121663);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(103,0.517032);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(104,0.6493494);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(105,0.7916244);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(106,0.9861993);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(107,1.186031);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(108,1.528586);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(109,1.89588);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(110,2.34061);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(111,2.844238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(112,3.509655);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(113,4.275918);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(116,0.2498196);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(117,0.1603947);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(118,0.1796069);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(119,0.1935676);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(120,0.2107551);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(121,0.2279339);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(122,0.2693177);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(123,0.2840221);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(124,0.3684279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(125,0.4511169);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(126,0.5478295);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(127,0.6705685);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(128,0.8468191);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(129,1.056133);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(130,1.280942);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(131,1.60403);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(132,1.989323);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(133,2.372967);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(134,2.942743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(135,3.621826);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(136,4.419039);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(140,0.3429347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(141,0.2204118);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(142,0.2400254);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(143,0.2548336);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(144,0.2836798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(145,0.3023882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(146,0.3429728);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(147,0.407979);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(148,0.4860313);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(149,0.5876791);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(150,0.714909);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(151,0.8947682);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(152,1.08554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(153,1.362568);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(154,1.661413);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(155,2.049476);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(156,2.501572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(157,3.096191);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(158,3.835096);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(159,4.607381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(164,0.4908225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(165,0.2998235);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(166,0.3329965);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(167,0.346525);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(168,0.3847581);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(169,0.3767325);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(170,0.4700674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(171,0.538547);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(172,0.6389306);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(173,0.7929357);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(174,0.9423619);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(175,1.164277);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(176,1.440431);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(177,1.764966);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(178,2.11929);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(179,2.664298);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(180,3.215293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(181,3.962745);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(182,4.915267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(188,0.7263781);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(189,0.4166525);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(190,0.4305735);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(191,0.4735316);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(192,0.4902852);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(193,0.5559846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(194,0.6359177);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(195,0.7103456);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(196,0.860467);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(197,0.9739622);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(198,1.225989);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(199,1.503686);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(200,1.861441);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(201,2.258599);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(202,2.790501);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(203,3.43697);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(204,4.110887);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(205,5.072964);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(212,1.131821);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(213,0.5782654);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(214,0.6157755);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(215,0.6010482);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(216,0.6756434);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(217,0.7369217);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(218,0.8076115);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(219,0.9534811);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(220,1.103165);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(221,1.334401);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(222,1.618955);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(223,1.962613);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(224,2.378264);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(225,2.929084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(226,3.512172);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(227,4.25387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(228,5.107352);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(236,1.499704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(237,0.885092);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(238,0.7921831);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(239,0.8643857);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(240,0.8738774);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(241,0.9552599);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(242,1.085251);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(243,1.215095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(244,1.402514);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(245,1.700166);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(246,2.053718);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(247,2.520474);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.38491091132164, "alphanum_fraction": 0.6011896729469299, "avg_line_length": 87.93535614013672, "blob_id": "0f11ae87348b3728be1d9398c2cacbc5fa3788c6", "content_id": "1e459181ccd5fec39d7fea618fd3baed1131ee44", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67413, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Direct_sbottom_neutralino2_ObsXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:27 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,1.194523);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,32.81772);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,12.94923);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,8.435597);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,5.675533);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,4.092522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,3.228431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,2.671454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,2.212305);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,1.905226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,1.768286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,1.622733);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,1.533681);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,1.477035);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,1.370296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,1.332255);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,1.270986);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,31.61388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,11.04333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,7.689558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,5.33673);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,4.064898);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,3.157459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,2.565797);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,2.227649);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,1.974419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,1.75987);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,1.622928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,1.563771);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,1.457522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,1.375776);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,1.336427);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,30.65999);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,10.41136);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,7.310136);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,5.187514);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,3.980727);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,3.00421);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,2.566593);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,2.133199);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,1.981744);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,1.769833);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,1.60761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,1.493367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,1.453397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,1.385427);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,27.71262);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,9.531942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,7.01577);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,4.981783);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,3.86998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,2.842094);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,2.42643);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,2.11924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,1.900957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,1.771863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,1.640235);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,1.515058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,1.468348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,27.7631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,9.064743);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,6.344244);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,4.848322);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,3.667118);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,2.812627);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,2.384383);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,2.116693);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,1.914688);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,1.73845);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,1.654863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,1.559657);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,25.60457);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,9.712555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,6.016415);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,4.484352);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,3.531437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,2.854919);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,2.326318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,2.051101);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,1.893451);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,1.732924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,1.623046);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,20.913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,8.676165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,6.400569);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,4.543092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,3.355889);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,2.864959);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,2.257515);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,2.032058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,1.830121);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,1.662646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,15.555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,8.375057);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,6.019713);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,4.326785);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,3.303205);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,2.765701);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,2.289682);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,2.039665);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,1.843855);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,11.709);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,8.196374);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,6.053195);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,4.240423);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,3.335976);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,2.681794);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,2.278881);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,8.883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,6.783);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,5.7684);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,3.294797);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,25.03379);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,5.238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,3.230788);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,25.41757);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,7.793933);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,3.21);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,5.257404);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(24,19.29281);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(25,12.54259);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(26,8.485172);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(27,5.965522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(28,4.796526);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(29,3.770568);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(30,3.066129);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(31,2.548215);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(32,2.155073);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(33,1.995224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(34,1.777067);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(35,1.647115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(36,1.521689);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(37,1.42381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(38,1.317885);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(39,1.269122);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(40,1.233793);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(41,1.184082);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(42,1.148228);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(43,1.092785);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(44,1.094424);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(47,19.67794);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(48,12.33038);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(49,8.071832);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(50,5.816138);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(51,4.446434);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(52,3.507581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(53,2.739811);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(54,2.395199);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(55,2.017475);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(56,1.757437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(57,1.617942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(58,1.467402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(59,1.389383);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(60,1.293817);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(61,1.236215);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(62,1.175247);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(63,1.149961);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(64,1.087055);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(65,1.035715);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(66,1.013981);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(67,0.9732509);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(70,22.58431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(71,14.9556);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(72,9.578878);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(73,6.515944);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(74,4.664818);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(75,3.617388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(76,2.908957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(77,2.404128);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(78,2.03047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(79,1.78184);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(80,1.591134);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(81,1.510518);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(82,1.386531);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(83,1.298548);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(84,1.219787);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(85,1.176231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(86,1.122711);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(87,1.078818);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(88,1.060311);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(89,1.010872);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(90,0.9591301);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(93,30.40672);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(94,16.79152);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(95,11.36815);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(96,7.553053);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(97,5.198822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(98,3.983513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(99,3.163671);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(100,2.526661);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(101,2.211144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(102,1.89193);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(103,1.724379);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(104,1.571368);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(105,1.43092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(106,1.345669);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(107,1.228501);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(108,1.207424);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(109,1.167129);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(110,1.114998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(111,1.080165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(112,1.038492);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(113,1.006628);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(116,64.13778);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(117,22.722);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(118,14.61902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(119,9.469481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(120,6.489558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(121,4.540162);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(122,3.628332);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(123,2.794861);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(124,2.380934);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(125,2.071241);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(126,1.814098);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(127,1.641183);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(128,1.54246);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(129,1.455214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(130,1.324577);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(131,1.266981);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(132,1.222567);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(133,1.135512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(134,1.108937);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(135,1.070531);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(136,1.044887);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(140,49.97084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(141,18.4425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(142,11.79659);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(143,8.021569);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(144,5.701406);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(145,4.043229);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(146,3.417448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(147,2.642143);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(148,2.236593);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(149,1.962839);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(150,1.755214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(151,1.626975);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(152,1.487238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(153,1.415938);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(154,1.30944);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(155,1.250059);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(156,1.192769);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(157,1.160479);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(158,1.137362);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(159,1.082603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(164,42.33173);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(165,15.50968);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(166,10.72233);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(167,7.103665);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(168,5.245487);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(169,3.74107);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(170,3.044328);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(171,2.500856);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(172,2.137336);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(173,1.950486);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(174,1.712533);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(175,1.590851);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(176,1.501052);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(177,1.408508);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(178,1.297145);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(179,1.278588);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(180,1.203707);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(181,1.178002);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(182,1.152771);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(188,38.04072);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(189,13.51736);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(190,9.051234);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(191,6.54742);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(192,4.913944);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(193,3.672337);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(194,2.975983);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(195,2.370276);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(196,2.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(197,1.772912);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(198,1.66429);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(199,1.553089);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(200,1.471237);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(201,1.383495);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(202,1.339871);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(203,1.276221);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(204,1.218109);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(205,1.198626);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(212,38.10288);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(213,12.29188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(214,8.629096);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(215,6.23216);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(216,4.394225);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(217,3.413666);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(218,2.70201);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(219,2.328537);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(220,2.013164);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(221,1.826928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(222,1.673454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(223,1.56463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(224,1.468487);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(225,1.403379);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(226,1.321739);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(227,1.264883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(228,1.194523);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(236,32.81772);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(237,12.94923);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(238,8.435597);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(239,5.675533);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(240,4.092522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(241,3.228431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(242,2.671454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(243,2.212305);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(244,1.905226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(245,1.768286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(246,1.622733);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(247,1.533681);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(248,1.477035);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(249,1.370296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(250,1.332255);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(251,1.270986);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(260,31.61388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(261,11.04333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(262,7.689558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(263,5.33673);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(264,4.064898);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(265,3.157459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(266,2.565797);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(267,2.227649);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(268,1.974419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(269,1.75987);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(270,1.622928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(271,1.563771);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(272,1.457522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(273,1.375776);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(274,1.336427);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(284,30.65999);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(285,10.41136);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(286,7.310136);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(287,5.187514);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(288,3.980727);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(289,3.00421);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(290,2.566593);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(291,2.133199);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(292,1.981744);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(293,1.769833);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(294,1.60761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(295,1.493367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(296,1.453397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(297,1.385427);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(308,27.71262);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(309,9.531942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(310,7.01577);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(311,4.981783);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(312,3.86998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(313,2.842094);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(314,2.42643);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(315,2.11924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(316,1.900957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(317,1.771863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(318,1.640235);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(319,1.515058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(320,1.468348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(332,27.7631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(333,9.064743);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(334,6.344244);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(335,4.848322);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(336,3.667118);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(337,2.812627);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(338,2.384383);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(339,2.116693);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(340,1.914688);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(341,1.73845);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(342,1.654863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(343,1.559657);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(356,25.60457);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(357,9.712555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(358,6.016415);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(359,4.484352);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(360,3.531437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(361,2.854919);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(362,2.326318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(363,2.051101);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(364,1.893451);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(365,1.732924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(366,1.623046);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(380,20.913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(381,8.676165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(382,6.400569);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(383,4.543092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(384,3.355889);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(385,2.864959);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(386,2.257515);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(387,2.032058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(388,1.830121);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(389,1.662646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(404,15.555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(405,8.375057);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(406,6.019713);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(407,4.326785);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(408,3.303205);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(409,2.765701);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(410,2.289682);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(411,2.039665);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(412,1.843855);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(428,11.709);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(429,8.196374);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(430,6.053195);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(431,4.240423);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(432,3.335976);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(433,2.681794);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(434,2.278881);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(435,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(452,8.883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(453,6.783);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(454,5.7684);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(455,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(456,3.294797);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(457,2.5347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(458,2.0115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(476,25.03379);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(477,5.238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(478,4.092);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(479,3.21);\n 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152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.45394599437713623, "alphanum_fraction": 0.6695973873138428, "avg_line_length": 80.84259033203125, "blob_id": "7cbe252c943d7cef6ad38a6c30d3437f254eb23f", "content_id": "2b6c587ec388403162ce974be3a739233e1e6b89", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 61873, "license_type": "no_license", "max_line_length": 161, "num_lines": 756, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_AcceptanceCorrected.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:32 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(24,-31.57895);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(25,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(26,-104.8951);\n 48134369_M_{sbottom} 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(191,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(192,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(193,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(194,-2445.652);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(195,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(196,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(197,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(198,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(199,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(200,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(201,-24201.51);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(202,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(203,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(204,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(205,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(212,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(213,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(214,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(215,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(216,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(217,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(218,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(219,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(220,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(221,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(222,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(223,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(224,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(225,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(226,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(227,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(228,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(236,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(237,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(238,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(239,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(240,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(241,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(242,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(243,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(244,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(245,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(246,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(247,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(248,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(249,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(250,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(251,-73710.07);\n 48134369_M_{sbottom} 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(272,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(273,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(274,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(284,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(285,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(286,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(287,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(288,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(289,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(290,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(291,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(292,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(293,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(294,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(295,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(296,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(297,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(308,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(309,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(310,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(311,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(312,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(313,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(314,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(315,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(316,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(317,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(318,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(319,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(320,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(332,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(333,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(334,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(335,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(336,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(337,-12958.96);\n 48134369_M_{sbottom} 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(362,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(363,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(364,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(365,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(366,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(380,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(381,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(382,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(383,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(384,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(385,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(386,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(387,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(388,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(389,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(404,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(405,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(406,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(407,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(408,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(409,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(410,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(428,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(429,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(452,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(453,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(454,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(455,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(-99900);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(-99900);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,-100899);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,-100799.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,-100699.2);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,-100599.3);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,-100499.4);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,-100399.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,-100299.6);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,-100199.7);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,-100099.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,-99999.9);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,-99900);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,-99800.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,-99700.2);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,-99600.3);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,-99500.4);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,-99400.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,-99300.6);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,-99200.7);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,-99100.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,-99000.9);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(19);\n palette->SetFillStyle(1001);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. [%]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4 = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(24,-31.57895);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(25,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(26,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(27,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(28,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(29,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(30,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(31,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(32,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(33,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(34,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(35,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(36,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(37,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(38,-13547.94);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(39,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(40,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(41,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(42,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(43,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(44,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(47,-31.57895);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(48,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(49,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(50,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(51,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(52,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(53,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(54,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(55,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(56,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(57,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(58,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(59,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(60,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(61,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(62,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(63,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(64,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(65,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(66,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(67,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(70,-31.57895);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(71,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(72,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(73,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(74,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(75,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(76,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(77,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(78,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(79,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(80,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(81,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(82,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(83,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(84,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(85,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(86,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(87,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(88,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(89,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(90,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(93,-31.57895);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(94,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(95,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(96,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(97,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(98,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(99,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(100,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(101,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(102,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(103,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(104,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(105,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(106,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(107,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(108,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(109,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(110,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(111,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(112,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(113,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(116,-31.57895);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(117,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(118,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(119,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(120,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(121,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(122,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(123,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(124,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(125,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(126,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(127,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(128,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(129,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(130,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(131,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(132,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(133,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(134,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(135,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(136,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(140,-59.40594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(141,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(142,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(143,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(144,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(145,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(146,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(147,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(148,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(149,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(150,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(151,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(152,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(153,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(154,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(155,-24201.51);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(156,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(157,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(158,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(159,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(164,-104.8951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(165,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(166,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(167,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(168,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(169,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(170,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(171,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(172,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(173,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(174,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(175,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(176,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(177,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(178,-23622.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(179,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(180,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(181,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(182,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(188,-178.0415);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(189,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(190,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(191,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(192,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(193,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(194,-2445.652);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(195,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(196,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(197,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(198,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(199,-12958.96);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(200,-17647.06);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(201,-24201.51);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(202,-31914.89);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(203,-41666.67);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(204,-56603.77);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(205,-73710.07);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(212,-292.6829);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(213,-465.1163);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(214,-722.0217);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(215,-1094.891);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(216,-1630.435);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(217,-2371.542);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(218,-3409.091);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(219,-4838.709);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(220,-6795.017);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->SetBinContent(221,-9448.819);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__4->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__4->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. 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"num_lines": 1085, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_ExpXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:25 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,1.017313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,0.804);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,0.7088175);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,0.5725);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,0.477);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,0.4421188);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.4122063);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.3754575);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,4.905775);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,1.542187);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,1.276125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,1.044);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.8395731);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.6625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.554);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.4873625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.4333526);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.4120875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,4.633125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,1.419625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,1.364);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.942975);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.8425);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.658);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.5667375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.4885875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.4310382);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,4.338313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,1.492);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,1.35255);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,1.01625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.722);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.6175375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.537825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.466015);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,4.104);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,1.51765);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,1.325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.98);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.803275);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.6157849);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.555555);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,3.91795);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,1.4525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,1.114);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.917575);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.7638125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.645095);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,4.405);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,1.396);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,1.152525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.941825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.7214075);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,3.242);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,1.379537);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.093325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.8618225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,4.060825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,1.450613);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,1.133495);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,4.345525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,1.418395);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(29,7.3283);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(30,4.43555);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(31,3.221602);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(32,2.007655);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(33,1.763504);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(34,1.398094);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(35,1.032684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(36,0.92625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(37,0.7815366);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(38,0.6911931);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(39,0.5563056);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(40,0.5694507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(41,0.4932291);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(42,0.4386816);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(43,0.4150596);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(44,0.4014913);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(45,0.3723907);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(46,0.329763);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(47,0.3344042);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(48,0.3129984);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(49,0.2897175);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(50,0.30125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(51,0.275);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(52,0.2738437);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(53,0.2537625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(54,0.2670937);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(57,7.5335);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(58,4.4137);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(59,2.83894);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(60,1.971697);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(61,1.609072);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(62,1.157225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(63,0.983193);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(64,0.7911904);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(65,0.6937866);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(66,0.5842161);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(67,0.5074352);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(68,0.4585581);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(69,0.4234377);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(70,0.3956427);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(71,0.3643096);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(72,0.34354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(73,0.3214658);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(74,0.301056);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(75,0.2959708);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(76,0.2750016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(77,0.2611425);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(78,0.25125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(79,0.252);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(80,0.2357437);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(81,0.2414526);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(82,0.2350425);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(85,6.6975);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(86,4.1216);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(87,3.202668);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(88,2.080032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(89,1.430928);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(90,1.1972);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(91,0.933561);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(92,0.7988968);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(93,0.6334146);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(94,0.5446194);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(95,0.490176);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(96,0.4286919);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(97,0.4139373);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(98,0.3813066);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(99,0.3380356);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(100,0.3242288);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(101,0.3044908);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(102,0.289569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(103,0.2780292);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(104,0.2609984);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(105,0.2563825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(106,0.25625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(107,0.241);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(108,0.2373313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(109,0.2278813);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(110,0.2207975);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(113,8.7951);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(114,5.0991);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(293,0.6074166);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(294,0.478125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(295,0.4440596);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(296,0.409765);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(297,0.368147);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(298,0.356013);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(299,0.3241542);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(300,0.3209984);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(301,0.3087675);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(302,0.29375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(303,0.277);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(523,0.5868125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(524,0.522);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(525,0.4651375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(526,0.40375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(527,0.402);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(528,0.3698875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(529,0.3396125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(530,0.3240738);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(546,5.527125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(547,1.86325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(548,1.263794);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(577,1.319806);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(578,1.097576);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(579,0.8533125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(580,0.654);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(581,0.6207125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(582,0.51625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(583,0.477);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(584,0.4167188);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(585,0.3673875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(586,0.3510375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(604,4.337738);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(635,1.276125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(636,1.044);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(637,0.8395731);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(638,0.6625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(639,0.554);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(640,0.4873625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(641,0.4333526);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(642,0.4120875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(662,4.633125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(663,1.419625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(664,1.364);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(665,0.942975);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(666,0.8425);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(667,0.658);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(668,0.5667375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(669,0.4885875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(670,0.4310382);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(691,4.338313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(692,1.492);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(693,1.35255);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(694,1.01625);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(695,0.722);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(696,0.6175375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(697,0.537825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(698,0.466015);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(720,4.104);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(721,1.51765);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(722,1.325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(723,0.98);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(724,0.803275);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(725,0.6157849);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(726,0.555555);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(749,3.91795);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(750,1.4525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(751,1.114);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(752,0.917575);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(753,0.7638125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(754,0.645095);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(778,4.405);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(779,1.396);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(780,1.152525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(781,0.941825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(782,0.7214075);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(807,3.242);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(808,1.379537);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(809,1.093325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(810,0.8618225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(836,4.060825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(837,1.450613);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(838,1.133495);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(865,4.345525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetBinContent(866,1.418395);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetMinimum(0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetMaximum(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetDirectory(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__22->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.49294182658195496, "alphanum_fraction": 0.679559588432312, "avg_line_length": 43.83544158935547, "blob_id": "d1f6b0582af9512f71be7e235496bd7d0ba60e3d", "content_id": "a2358b8f26e143304822b1167b936e93251247bd", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 7084, "license_type": "no_license", "max_line_length": 149, "num_lines": 158, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10/Fixed_Edge_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 11:16:29 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(63.51351,-35.67568,766.2162,802.1622);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 484096098_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(17);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,370,100);\n graph->SetPoint(1,370,120);\n graph->SetPoint(2,370,140);\n graph->SetPoint(3,369.7671999,159.7671999);\n graph->SetPoint(4,368.45405,178.45405);\n graph->SetPoint(5,364.8772554,194.8772554);\n graph->SetPoint(6,358.2212499,208.2212499);\n graph->SetPoint(7,348.2212499,218.2212499);\n graph->SetPoint(8,334.8772554,224.8772554);\n graph->SetPoint(9,318.45405,228.45405);\n graph->SetPoint(10,299.7671999,229.7671999);\n graph->SetPoint(11,280,230.0412485);\n graph->SetPoint(12,260.1915517,229.9586205);\n graph->SetPoint(13,241.3545295,228.8963796);\n graph->SetPoint(14,224.2012774,225.8470623);\n graph->SetPoint(15,210.0229059,221.0348314);\n graph->SetPoint(16,200,216.9697038);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Observed limit\",100,183,387);\n Graph_Graph1->SetMinimum(86.99588);\n Graph_Graph1->SetMaximum(243.0454);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n \n graph = new TGraph(26);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,430,100);\n graph->SetPoint(1,430,120);\n graph->SetPoint(2,430,140);\n graph->SetPoint(3,430,160);\n graph->SetPoint(4,429.7671999,179.7671999);\n graph->SetPoint(5,428.45405,198.45405);\n graph->SetPoint(6,425.1100555,215.1100555);\n graph->SetPoint(7,419.7671999,229.7671999);\n graph->SetPoint(8,413.1111944,243.1111944);\n graph->SetPoint(9,405.1100555,255.1100555);\n graph->SetPoint(10,395.1100555,265.1100555);\n graph->SetPoint(11,383.1111944,273.1111944);\n graph->SetPoint(12,369.7671999,279.7671999);\n graph->SetPoint(13,355.3428556,284.8772554);\n graph->SetPoint(14,340,286.9081);\n graph->SetPoint(15,324.6571444,284.8772554);\n graph->SetPoint(16,310,280.0412484);\n graph->SetPoint(17,295.3016071,274.848565);\n graph->SetPoint(18,279.8085795,270.4423297);\n graph->SetPoint(19,264.4476149,265.8058139);\n graph->SetPoint(20,250.8501916,259.2974608);\n graph->SetPoint(21,239.3893892,250.6543789);\n graph->SetPoint(22,229.112821,240.8846593);\n graph->SetPoint(23,218.9102516,231.1612275);\n graph->SetPoint(24,208.8760145,222.6220298);\n graph->SetPoint(25,200,217.2025039);\n \n TH1F Graph_Graph2 = new TH1F(\"Graph_Graph2\",\"Expected limit\",100,177,453);\n Graph_Graph2->SetMinimum(81.30919);\n Graph_Graph2->SetMaximum(305.5989);\n Graph_Graph2->SetDirectory(0);\n Graph_Graph2->SetStats(0);\n Graph_Graph2->SetLineStyle(0);\n Graph_Graph2->GetXaxis()->SetNdivisions(505);\n Graph_Graph2->GetXaxis()->SetLabelFont(42);\n Graph_Graph2->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetXaxis()->SetTitleSize(32);\n Graph_Graph2->GetXaxis()->SetTitleFont(43);\n Graph_Graph2->GetYaxis()->SetLabelFont(42);\n Graph_Graph2->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetYaxis()->SetTitleSize(32);\n Graph_Graph2->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph2->GetYaxis()->SetTitleFont(43);\n Graph_Graph2->GetZaxis()->SetLabelFont(42);\n Graph_Graph2->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetZaxis()->SetTitleSize(32);\n Graph_Graph2->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph2->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph2);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.3862013518810272, "alphanum_fraction": 0.600113034248352, "avg_line_length": 87.6860122680664, "blob_id": "6ab2b1bb10f0ff716c9ff0c6aa6c112727348d5a", "content_id": "8e7c153d3ed82cd36d1ffc567ffeb437db60dbad", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67224, "license_type": "no_license", "max_line_length": 177, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:43:38 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,5.011512);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(25,3.2703);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(26,2.283372);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(27,1.666207);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(28,1.336122);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(29,1.065426);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(30,0.8663136);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(31,0.7300904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(32,0.6253991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.5753436);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.5173474);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.4766512);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,0.4592651);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,0.4174746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,0.3871694);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,0.3736692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,0.3629802);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,0.3521664);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,0.3388567);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,0.3216443);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,0.3224447);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(293,0.4981303);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.4511462);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.4291444);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.408207);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.3930462);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,6.835182);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,2.511189);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.876186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.356584);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,1.044829);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.7848673);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6681631);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.5900945);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.5262585);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.494221);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.4607735);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.4264944);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.4140793);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,6.651986);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.431343);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,1.701504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,1.294021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,1.002825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.7825489);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.65463);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.5859025);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.5297653);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.4796405);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.4612676);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.4332486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,6.041031);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,2.566823);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,1.628759);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,1.220541);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.9623853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.7870176);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.6461442);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.567031);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.5259863);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.4837821);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.4548319);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,6.065713);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,2.300014);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,1.70227);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,1.24224);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.9232094);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.7779562);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.6253412);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.5635889);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.5119039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.4692772);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,6.187716);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,2.222655);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,1.598228);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,1.1805);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.9061548);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.7603675);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.6267984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.5690387);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.5123528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,6.144102);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,2.177634);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,1.634563);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.176462);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.9190324);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.744854);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.6243624);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.5536832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,5.560202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,2.156595);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.550501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.16427);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.8976266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.7178418);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.6178852);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,5.690472);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,2.029915);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.516534);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.14037);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.8810449);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.7103872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,5.770761);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,2.07047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.501473);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,1.12771);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.8396862);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,5.364559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,2.072468);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,1.411316);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,1.084871);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,5.460384);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,1.880342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,1.407198);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,5.560176);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,1.949685);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,4.843822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.3981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.5011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.6309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.7943282);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,1.584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,2.511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,3.162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,3.981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,5.011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,6.309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,7.943282);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(24,5.011512);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(25,3.2703);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(26,2.283372);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(27,1.666207);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(28,1.336122);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(29,1.065426);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(30,0.8663136);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(31,0.7300904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(32,0.6253991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(33,0.5753436);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(34,0.5173474);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(35,0.4766512);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(36,0.4592651);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(37,0.4174746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(38,0.3871694);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(39,0.3736692);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(40,0.3629802);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(41,0.3521664);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(42,0.3388567);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(43,0.3216443);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(44,0.3224447);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(47,5.281904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(48,3.321832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(49,2.199174);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(50,1.597042);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(51,1.227141);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(52,0.9772147);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(53,0.765159);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(54,0.6742935);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(55,0.5778376);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(56,0.5108829);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(57,0.4691696);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(58,0.4292533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(59,0.4026539);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(60,0.3749025);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(61,0.3600976);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(62,0.3411075);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(63,0.3367617);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(64,0.3194869);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(65,0.3049729);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(66,0.2969739);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(67,0.2865865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(70,5.285608);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(71,3.906522);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(72,2.556596);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(73,1.753402);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(74,1.274446);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(75,1.000896);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(76,0.8143235);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(77,0.6747717);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(78,0.5784442);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(79,0.5111998);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(80,0.459327);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(81,0.4328204);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(82,0.3983492);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(83,0.374618);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(84,0.3550477);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(85,0.3442605);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(86,0.3303683);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(87,0.3146264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(88,0.3068045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(89,0.2985919);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(90,0.2821408);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(93,7.754324);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(94,4.367337);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(95,2.987621);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(96,2.034982);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(97,1.395004);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(98,1.085474);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(99,0.8698658);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(100,0.7062306);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(101,0.6175494);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(102,0.53636);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(103,0.4905518);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(104,0.4517891);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(105,0.4118794);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(106,0.3893035);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(107,0.3554365);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(108,0.3504996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(109,0.3374759);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(110,0.3268581);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(111,0.3124695);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(112,0.305185);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(113,0.2944579);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(116,15.24937);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(117,5.920234);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(118,3.783316);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(119,2.493247);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(120,1.72674);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(121,1.23433);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(122,0.9870857);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(123,0.7802546);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(124,0.6667165);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(125,0.5835353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(126,0.514717);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(127,0.4651268);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(128,0.4386146);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(129,0.4130454);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(130,0.3799177);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(131,0.3669524);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(132,0.3523882);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(133,0.3292151);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(134,0.3218548);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(135,0.3128369);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(136,0.3033995);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(140,11.86921);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(141,4.855023);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(142,3.153764);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(143,2.112766);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(144,1.536429);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(145,1.113428);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(146,0.9310659);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(147,0.7197013);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(148,0.6226896);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(149,0.5519662);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(150,0.4936992);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(151,0.4589142);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(152,0.4251885);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(153,0.4017225);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(154,0.3770393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(155,0.3612393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(156,0.3462923);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(157,0.3373755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(158,0.3289938);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(159,0.3144443);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(164,10.19572);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(165,4.051936);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(166,2.802983);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(167,1.939393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(168,1.398809);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(169,1.017472);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(170,0.8278117);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(171,0.687516);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(172,0.5949173);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(173,0.5433638);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(174,0.4843828);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(175,0.4483984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(176,0.4275103);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(177,0.3996844);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(178,0.3717197);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(179,0.3660991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(180,0.3472801);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(181,0.3411189);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(182,0.3350546);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(188,9.313782);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(189,3.695395);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(190,2.436584);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(191,1.7495);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(192,1.325046);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(193,0.9960072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(194,0.8062953);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(195,0.6585209);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(196,0.5885189);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(197,0.4985035);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(198,0.4699071);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(199,0.4407071);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(200,0.4196677);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(201,0.3952128);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(202,0.3830021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(203,0.3707958);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(204,0.3502212);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(205,0.3441423);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(212,9.133297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(213,3.165203);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(214,2.309443);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(215,1.664982);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(216,1.208375);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(217,0.9364358);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(218,0.7399599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(219,0.6429435);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(220,0.5596675);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(221,0.5127266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(222,0.4710792);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(223,0.4353824);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(224,0.4124041);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(225,0.3995198);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(226,0.3766115);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(227,0.3613755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(228,0.3457229);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(236,7.798421);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(237,3.325107);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(238,2.228426);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(239,1.538843);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(240,1.118993);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(241,0.8809975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(242,0.7340648);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(243,0.6091841);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(244,0.5372479);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(245,0.4937339);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(246,0.4576368);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:43:38 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(244,8.71712);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,10.8958);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,13.7051);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,17.6086);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,22.621);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,27.9974);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,9.30971);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,5.38468);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,5.70263);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,6.01416);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,6.41865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,7.15914);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,8.23387);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,9.90972);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,12.1638);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,14.888);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,18.4285);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,23.7367);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,29.565);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,37.047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,46.1782);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,12.9497);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,7.82321);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,8.03437);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,8.28407);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,9.01141);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,9.67333);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,11.4515);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,13.0015);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,16.5396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,20.0336);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,24.2855);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,19.3415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,10.292);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,11.0675);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,11.3882);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,12.2576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,12.6765);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,14.8047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,17.5934);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,21.2326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,26.6796);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,40.1501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,51.1794);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,27.4914);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,14.4393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,14.3459);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,15.1445);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,16.1615);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,17.3542);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,19.6021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,23.6303);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,28.5758);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,43.4329);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,53.2876);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,21.6535);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,19.1659);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,19.759);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,21.3396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,23.6197);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,25.4939);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,37.6946);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,27.0331);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,27.6504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,27.4945);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,27.666);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,31.3922);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,33.8366);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,20.5526);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,53.7623);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,48.5899);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,62.8148);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,64.3999);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,67.7028);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,76.1589);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,170.061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,82.44);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,81.9325);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,83.4201);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,87.5816);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,234.605);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,148.566);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,174.22);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.2457144);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(258.0655);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.2457144);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.347933);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.492675);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.6976306);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.9878488);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,1.398799);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,1.980708);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,2.804693);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,3.971461);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,5.623612);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,7.963065);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,11.27574);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,15.96652);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,22.60868);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,32.01402);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,45.33202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,64.1904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,90.89396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,128.7064);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,182.2489);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(24,0.273016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(25,0.330033);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(26,0.411631);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(27,0.51395);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(28,0.673017);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(29,0.853834);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(30,1.07279);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(31,1.37235);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(32,1.75695);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(33,2.36139);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(34,3.05336);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(35,4.01573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(36,5.37348);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(37,6.75011);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(38,8.58996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(39,11.1939);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(40,14.6493);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(41,18.9678);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(42,24.2845);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(43,30.3446);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(44,39.776);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(47,0.287424);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(48,0.335734);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(49,0.392216);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(50,0.490507);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(51,0.620776);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(52,0.779452);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(53,0.951085);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(54,1.27116);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(55,1.62741);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(56,2.09727);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(57,2.76333);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(58,3.61209);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(59,4.71549);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(60,6.0799);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(61,7.98397);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(62,10.2213);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(63,13.5708);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(64,17.2029);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(65,21.8013);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(66,27.9846);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(67,35.3051);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(70,0.28476);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(71,0.395431);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(72,0.463178);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(73,0.538957);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(74,0.656246);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(75,0.799194);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(76,1.0184);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(77,1.27625);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(78,1.63047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(79,2.09065);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(80,2.70709);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(81,3.63651);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(82,4.66494);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(83,6.09989);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(84,7.89106);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(85,10.3525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(86,13.3811);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(87,17.041);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(88,21.9404);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(89,27.82);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(90,34.8596);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(93,0.439091);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(94,0.443264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(95,0.540499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(96,0.636995);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(97,0.705145);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(98,0.869363);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(99,1.08042);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(100,1.33004);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(101,1.73407);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(102,2.20094);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(103,2.88751);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(104,3.80346);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(105,4.81597);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(106,6.31753);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(107,7.87879);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(108,10.5284);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(109,13.6155);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(110,17.5847);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(111,22.3199);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(112,28.8204);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(113,36.2057);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(116,0.829813);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(117,0.601661);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(118,0.684722);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(119,0.76398);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(120,0.872185);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(121,0.986266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(122,1.22652);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(123,1.46836);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(124,1.87148);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(125,2.3954);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(126,3.02995);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(127,3.91181);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(128,5.14719);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(129,6.69941);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(130,8.43539);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(131,10.983);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(132,14.2529);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(133,17.7546);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(134,23.0684);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(135,29.4741);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(136,37.3581);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(140,1.20431);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(141,0.879898);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(142,0.964652);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(143,1.06444);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(144,1.23013);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(145,1.38305);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(146,1.7632);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(147,2.01737);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(148,2.56334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(149,3.25125);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(150,4.13458);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(151,5.37832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(152,6.92828);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(153,8.89628);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(154,11.3255);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(155,14.5547);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(156,18.7345);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(157,24.0778);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(158,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(159,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(164,1.83976);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(165,1.2414);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(166,1.41428);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(167,1.54343);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(168,1.73529);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(169,1.92347);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(170,2.32506);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(171,2.82667);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(172,3.49957);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(173,4.55679);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(174,5.67885);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(175,7.26016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(176,9.46214);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(177,11.9955);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(178,14.9341);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(179,19.7454);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(180,24.8659);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(181,32.1607);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(182,41.3098);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(188,2.87025);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(189,1.85462);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(190,1.94553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(191,2.17312);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(192,2.50561);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(193,2.79805);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(194,3.30447);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(195,3.87755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(196,4.93694);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(197,5.84473);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(198,7.59219);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(199,9.75703);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(200,12.5485);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(201,15.9496);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(202,20.664);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(203,26.5268);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(204,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(205,42.4399);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(212,4.60239);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(213,2.54174);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(214,2.87008);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(215,3.14891);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(216,3.39904);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(217,3.83999);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(218,4.36832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(219,5.41373);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(220,6.54212);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(221,8.30897);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(222,10.4352);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(223,12.863);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(224,16.6499);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(225,21.6297);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(226,26.9862);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(227,34.0117);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(228,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(236,6.27569);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(237,4.14568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(238,4.20197);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(239,4.32388);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(240,4.5918);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(241,5.20952);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(242,6.15448);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(243,7.11923);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(244,8.71712);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(245,10.8958);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(246,13.7051);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(247,17.6086);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(248,22.621);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(249,27.9974);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(250,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(251,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(260,9.30971);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(261,5.38468);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(262,5.70263);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(263,6.01416);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(264,6.41865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(265,7.15914);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(266,8.23387);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(267,9.90972);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(268,12.1638);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(269,14.888);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(270,18.4285);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(271,23.7367);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(272,29.565);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(273,37.047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(274,46.1782);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(284,12.9497);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(285,7.82321);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(286,8.03437);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(287,8.28407);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(288,9.01141);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(289,9.67333);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(290,11.4515);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(291,13.0015);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(292,16.5396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(293,20.0336);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(294,24.2855);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(295,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(296,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(297,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(308,19.3415);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(309,10.292);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(310,11.0675);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(311,11.3882);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(312,12.2576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(313,12.6765);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(314,14.8047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(315,17.5934);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(316,21.2326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(317,26.6796);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(318,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(319,40.1501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(320,51.1794);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(332,27.4914);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(333,14.4393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(334,14.3459);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(335,15.1445);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(336,16.1615);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(337,17.3542);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(338,19.6021);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(339,23.6303);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(340,28.5758);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(341,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(342,43.4329);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(343,53.2876);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(356,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(357,21.6535);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(358,19.1659);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(359,19.759);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(360,21.3396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(361,23.6197);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(362,25.4939);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(363,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(364,37.6946);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(365,20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(366,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(380,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(381,27.0331);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(382,27.6504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(383,27.4945);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(384,27.666);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(385,31.3922);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(386,33.8366);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(387,20.5526);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(388,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(389,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(404,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(405,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(406,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(407,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(408,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(409,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(410,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(411,53.7623);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(412,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(428,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(429,48.5899);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(430,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(431,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(432,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(433,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(434,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(435,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(452,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(453,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(454,62.8148);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(455,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(456,64.3999);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(457,67.7028);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(458,76.1589);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(476,170.061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(477,82.44);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(478,81.9325);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(479,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(480,83.4201);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(481,87.5816);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(500,234.605);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(501,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(502,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(503,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(504,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(524,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(525,148.566);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(526,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(527,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(548,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(549,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(550,174.22);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(572,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(573,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(596,30);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetMinimum(0.2457144);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetMaximum(258.0655);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetDirectory(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitle(\"Observed R\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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"repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 09:50:01 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",0,0,900,800);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.060345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(70.961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.060345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.08593305);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1223712);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1742601);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2481516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3533751);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.5032165);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.716595);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,1.020452);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.453154);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,2.069334);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,2.946792);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,4.196318);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,5.975679);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,8.509542);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,12.11784);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,17.25616);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,24.57327);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,34.99306);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,49.83114);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"NLO cross section [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(24,64.51);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(25,36.38);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(26,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(27,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(28,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(29,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(30,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(31,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(32,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(33,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(34,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(35,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(36,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(37,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(38,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(39,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(40,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(41,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(42,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(43,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(44,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(47,64.51);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(48,36.38);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(49,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(50,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(51,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(52,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(53,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(54,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(55,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(56,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(57,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(58,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(59,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(60,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(61,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(62,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(63,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(64,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(65,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(66,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(67,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(70,64.51);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(71,36.38);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(72,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(73,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(74,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(75,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(76,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(77,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(78,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(79,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(80,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(81,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(82,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(83,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(84,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(85,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(86,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(87,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(88,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(89,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(90,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(93,64.51);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(94,36.38);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(95,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(96,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(97,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(98,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(99,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(100,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(101,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(102,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(103,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(104,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(105,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(106,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(107,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(108,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(109,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(110,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(111,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(112,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(113,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(116,64.51);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(117,36.38);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(118,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(119,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(120,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(121,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(122,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(123,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(124,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(125,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(126,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(127,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(128,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(129,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(130,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(131,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(132,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(133,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(134,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(135,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(136,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(140,36.38);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(141,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(142,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(143,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(144,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(145,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(146,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(147,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(148,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(149,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(150,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(151,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(152,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(153,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(154,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(155,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(156,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(157,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(158,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(159,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(164,21.59);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(165,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(166,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(167,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(168,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(169,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(170,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(171,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(172,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(173,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(174,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(175,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(176,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(177,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(178,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(179,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(180,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(181,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(182,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(188,13.32);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(189,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(190,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(191,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(192,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(193,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(194,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(195,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(196,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(197,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(198,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(199,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(200,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(201,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(202,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(203,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(204,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(205,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(212,8.516);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(213,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(214,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(215,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(216,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(217,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(218,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(219,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(220,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(221,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(222,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(223,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(224,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(225,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(226,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(227,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(228,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(236,5.605);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(237,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(238,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(239,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(240,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(241,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(242,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(243,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(244,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(245,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(246,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(247,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(248,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(249,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(250,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(251,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(260,3.787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(261,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(262,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(263,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(264,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(265,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(266,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(267,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(268,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(269,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(270,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(271,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(272,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(273,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(274,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(284,2.808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(285,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(286,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(287,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(288,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(289,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(290,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(291,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(292,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(293,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(294,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(295,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(296,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(297,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(308,1.83537);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(309,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(310,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(311,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(312,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(313,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(314,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(315,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(316,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(317,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(318,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(319,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(320,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(332,1.312);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(333,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(334,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(335,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(336,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(337,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(338,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(339,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(340,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(341,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(342,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(343,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(356,0.9483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(357,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(358,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(359,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(360,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(361,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(362,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(363,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(364,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(365,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(366,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(380,0.6971);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(381,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(382,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(383,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(384,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(385,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(386,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(387,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(388,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(389,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(404,0.5185);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(405,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(406,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(407,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(408,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(409,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(410,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(411,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(412,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(428,0.3903);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(429,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(430,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(431,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(432,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(433,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(434,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(435,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(452,0.2961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(453,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(454,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(455,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(456,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(457,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(458,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(476,0.2261);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(477,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(478,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(479,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(480,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(481,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(500,0.1746);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(501,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(502,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(503,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(504,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(524,0.1364);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(525,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(526,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(527,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(548,0.107);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(549,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(550,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(572,0.08449);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(573,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(596,0.06705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetMinimum(0.060345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetMaximum(70.961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetZaxis()->SetTitle(\"NLO cross section [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4459982216358185, "alphanum_fraction": 0.6851536631584167, "avg_line_length": 82.83688354492188, "blob_id": "c8dc37c40bc4110407b704eae7bcc7cf8cea9c77", "content_id": "30aed61aed917b59622f4d3cea6b1b45e0da5b98", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 90460, "license_type": "no_license", "max_line_length": 157, "num_lines": 1079, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_ExpXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:38 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 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[GeV]->SetBinContent(635,0.6585625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,0.5409984);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.3984625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.34375);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.2864992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.2516187);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.2240938);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.2126575);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,2.355937);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,0.7341542);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.593402);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.4975066);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.4030826);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.3258302);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.2520263);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.2228325);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,2.198625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,0.774);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,0.695325);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,0.555815);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.375);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.3190875);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.2764875);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.2411475);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,1.341437);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,0.6825);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.504);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.4143375);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.3194125);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.2866806);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,1.98755);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,0.7525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,0.578);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.4746625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.3951625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.3322138);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,2.245);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,1.267181);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,0.593725);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.4860625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.3713875);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,1.652);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,0.714375);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,0.5987525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.4446475);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,2.060575);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,0.749925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,0.584045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,1.320206);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,2.056367);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS} #sqrt{s} = 8 TeV\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(29,3.7658);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(30,2.3023);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(31,1.699068);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(32,1.040016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(33,0.911392);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(34,0.726725);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(35,0.535659);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(36,0.4804644);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(37,0.4017546);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(38,0.3574857);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(39,0.3253711);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(40,0.2932566);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(41,0.2545417);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(42,0.2277099);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(43,0.2147856);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(44,0.2076463);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(45,0.1925576);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(46,0.171444);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(47,0.1723271);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(48,0.1624992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(49,0.1504163);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(50,0.155624);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(51,0.1424992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(52,0.1408913);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(53,0.1319312);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(54,0.1378713);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(57,3.8779);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(58,2.2793);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(59,1.475676);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(60,1.012817);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(61,0.8284);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(62,0.5986);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(63,0.508164);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(64,0.4071548);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(65,0.3578796);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(66,0.3020199);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(67,0.2740341);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(68,0.2508558);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(69,0.2180626);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(70,0.2079532);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(71,0.1894048);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(72,0.1786662);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(73,0.1660359);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(74,0.1554472);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(75,0.1518271);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(76,0.1415008);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(77,0.141685);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(78,0.14375);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(79,0.1334992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(80,0.1317625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(81,0.1248294);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(82,0.1256613);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(85,3.4789);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(86,2.14475);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(87,1.656824);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(88,1.075974);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(89,0.739328);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(90,0.6079928);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(91,0.483348);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(92,0.411008);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(93,0.3276936);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(94,0.2802189);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(95,0.253736);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(96,0.2228772);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(97,0.2133124);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(98,0.1966356);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(99,0.1744524);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(100,0.1676287);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(101,0.1608593);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(102,0.1513557);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(103,0.1458705);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(104,0.1355008);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(105,0.1329538);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(106,0.131876);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(107,0.1244992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(108,0.1226337);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(109,0.1177276);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(110,0.1134512);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(113,4.49445);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(114,2.63925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(115,1.587372);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(116,1.030796);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(117,0.840256);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(118,0.610695);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(119,0.47094);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(120,0.4033016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(121,0.3249558);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(122,0.2821962);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(123,0.2493936);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(124,0.2239419);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(125,0.2133124);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(126,0.1942335);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(127,0.179499);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(128,0.1703925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(129,0.1607329);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(130,0.1464278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(131,0.1492646);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(132,0.1395008);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(133,0.1329538);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(134,0.129062);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(135,0.1244992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(136,0.1234288);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(137,0.1196224);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(138,0.1144688);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(141,5.51);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(142,3.02105);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(143,2.216736);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(144,1.328141);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(145,0.923248);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(146,0.68265);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(147,0.546657);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(148,0.4187144);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(149,0.3468582);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(150,0.3183235);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(151,0.288687);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(152,0.2636681);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(153,0.2393644);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(154,0.2162025);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(155,0.1919859);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(156,0.17177);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(157,0.1617971);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(158,0.149709);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(159,0.1441396);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(160,0.1364992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(161,0.1321587);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(162,0.130624);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(163,0.1304992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(164,0.1242212);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(165,0.1183599);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(166,0.1185388);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(170,3.96405);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(171,2.202416);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(172,1.526371);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(173,1.14304);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(174,0.73472);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(175,0.564564);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(176,0.4856699);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(177,0.40344);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(178,0.3432417);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(179,0.2709584);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(180,0.2463279);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(181,0.2133124);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(182,0.1990224);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(183,0.1839644);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(184,0.1772887);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(185,0.1649766);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(186,0.1587285);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(187,0.151975);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(188,0.1471041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(189,0.1414243);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(190,0.1371972);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(191,0.1327991);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(192,0.1271139);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(193,0.1221474);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(194,0.1195562);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(198,6.76085);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(199,2.811016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(200,2.007655);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(201,1.39536);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(202,1.101055);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(203,0.641691);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(204,0.5306548);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(205,0.4393086);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(206,0.3767281);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(207,0.3090464);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(208,0.2856604);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(209,0.26638);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(210,0.2472682);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(211,0.2297714);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(212,0.2134479);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(213,0.1974665);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(214,0.1805601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(215,0.1635914);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(216,0.1495008);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(217,0.1393038);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(218,0.139376);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(219,0.1364992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(220,0.1281913);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(221,0.1256188);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(222,0.1226088);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(227,5.95712);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(228,2.386136);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(229,1.549792);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(230,1.117045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(231,0.795945);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(232,0.615524);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(233,0.4593186);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(234,0.402051);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(235,0.314824);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(236,0.2740647);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(237,0.2545417);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(238,0.2181474);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(239,0.2002856);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(240,0.1869488);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(241,0.1830109);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(242,0.162834);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(243,0.1569521);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(244,0.152);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(245,0.1480337);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(246,0.1435427);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(247,0.1384992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(248,0.1329538);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(249,0.1281437);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(250,0.1260426);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(257,2.930256);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(258,1.411322);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(259,1.012098);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(260,0.7043452);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(261,0.5621616);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(262,0.4495569);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->SetBinContent(263,0.3550464);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__10->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__10->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4612653851509094, "alphanum_fraction": 0.6746224761009216, "avg_line_length": 80.49674224853516, "blob_id": "51ff390a9c0c4fc579986c55f4ca0158dec5240d", "content_id": "d6b2c3ed10503abc6b3ad71f67969c67b60f29ec", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 87609, "license_type": "no_license", "max_line_length": 157, "num_lines": 1075, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_Xsection.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:24 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,11.5);\n 284060385_M_{sbottom} 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[GeV]->SetBinContent(306,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(314,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(315,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(316,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(317,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(318,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(319,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(320,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(321,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(322,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(323,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(324,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(325,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(326,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(327,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(328,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(329,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(330,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(331,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(332,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(333,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(334,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(343,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(344,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(345,0.702);\n 284060385_M_{sbottom} 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[GeV]->SetBinContent(581,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.0257);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.007326);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20.9);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.007326);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.01090513);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01623285);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.02416344);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.03596854);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.05354103);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.0796986);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.1186355);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.1765951);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.262871);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3912971);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.582466);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.8670308);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.29062);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.921155);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.859739);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,4.25687);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,6.336572);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,9.432316);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,14.04049);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"NLO cross section [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(29,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(30,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(31,8.055);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(32,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(33,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(34,2.225);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(35,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(36,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(37,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(38,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(39,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(40,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(41,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(42,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(43,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(44,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(45,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(46,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(47,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(48,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(49,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(50,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(51,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(52,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(53,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(54,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(57,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(58,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(59,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(60,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(61,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(62,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(63,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(64,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(65,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(66,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(67,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(68,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(69,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(70,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(71,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(72,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(73,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(74,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(75,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(76,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(77,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(78,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(79,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(80,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(81,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(82,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(85,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(86,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(87,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(88,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(89,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(90,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(91,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(92,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(93,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(94,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(95,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(96,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(97,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(98,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(99,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(100,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(101,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(102,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(103,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(104,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(105,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(106,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(107,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(108,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(109,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(110,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(113,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(114,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(115,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(116,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(117,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(118,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(119,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(120,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(121,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(122,0.521);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(123,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(124,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(125,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(126,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(127,0.118325);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(128,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(129,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(130,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(131,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(132,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(133,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(134,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(135,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(136,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(137,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(138,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(141,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(142,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(143,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(144,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(145,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(146,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(147,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(148,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(149,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(150,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(151,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(152,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(153,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(154,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(155,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(156,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(157,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(158,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(159,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(160,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(161,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(162,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(163,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(164,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(165,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(166,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(169,19);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(170,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(171,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(172,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(173,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(174,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(175,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(176,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(177,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(178,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(179,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(180,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(181,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(182,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(183,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(184,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(185,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(186,0.053475);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(187,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(188,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(189,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(190,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(191,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(192,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(193,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(194,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(198,11.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(199,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(200,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(201,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(202,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(203,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(204,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(205,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(206,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(207,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(208,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(209,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(210,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(211,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(212,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(213,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(214,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(215,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(216,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(217,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(218,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(219,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(220,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(221,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(222,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(227,7.16);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(228,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(229,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(230,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(231,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(232,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(233,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(234,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(235,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(236,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(237,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(238,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(239,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(240,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(241,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(242,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(243,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(244,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(245,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(246,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(247,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(248,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(249,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(250,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(256,4.61);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(257,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(258,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(259,1.4645);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(260,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(261,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(262,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(263,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(264,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(265,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(266,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(267,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(268,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(269,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(270,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(271,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(272,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(273,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(274,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(275,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(276,0.012875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(277,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(278,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(285,3.04);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(286,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(287,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(288,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(289,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(290,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(291,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(292,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(293,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(294,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(295,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(296,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(297,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(298,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(299,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(300,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(301,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(302,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(303,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(304,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(305,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(306,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(314,2.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(315,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(316,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(317,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(318,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(319,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(320,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(321,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(322,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(323,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(324,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(325,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(326,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(327,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(328,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(329,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(330,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(331,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(332,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(333,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(334,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(343,1.41);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(344,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(345,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(346,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(347,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(348,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(349,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(350,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(351,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(352,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(353,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(354,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(355,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(356,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(357,0.0257);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(358,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(359,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(360,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(361,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(362,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(372,0.988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(373,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(374,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(375,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(376,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(377,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(378,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(379,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(380,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(381,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(382,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(383,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(384,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(385,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(386,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(387,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(388,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(389,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(390,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(401,0.702);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(402,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(403,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(404,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(405,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(406,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(407,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(408,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(409,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(410,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(411,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(412,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(413,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(414,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(415,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(416,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(417,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(418,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(430,0.507);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(431,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(432,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(433,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(434,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(435,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(436,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(437,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(438,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(439,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(440,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(441,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(442,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(443,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(444,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(445,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(446,0.00814);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(459,0.368);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(460,0.273);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(461,0.203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(462,0.153);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(463,0.116);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(464,0.0883);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(465,0.0679);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(466,0.0525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(467,0.041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(468,0.032);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(469,0.0254);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(470,0.02);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(471,0.016);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(472,0.0127);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__13->SetBinContent(473,0.0101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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"num_lines": 745, "path": "/LimitPlotting/results/Fixed_Edge_sbottom_neutralino2_Xsection.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:43:37 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",0,0,900,800);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 92487217_m(#tilde{b}) 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[GeV]->SetBinContent(244,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.0073026);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20.372);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.0073026);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.01085814);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.01614482);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.02400551);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.03569347);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.05307213);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.07891224);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.1173335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.1744616);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.2594047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.3857053);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.5735);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.8527293);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.267912);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,1.885241);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,2.803139);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,4.167949);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,6.197268);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,9.214633);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,13.70111);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"NLO cross section [pb]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(24,18.52);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(25,9.91);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(26,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(27,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(28,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(29,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(30,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(31,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(32,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(33,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(34,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(35,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(36,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(37,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(38,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(39,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(40,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(41,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(42,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(43,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(44,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(47,18.52);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(48,9.91);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(49,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(50,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(51,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(52,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(53,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(54,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(55,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(56,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(57,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(58,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(59,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(60,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(61,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(62,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(63,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(64,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(65,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(66,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(67,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(70,18.52);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(71,9.91);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(72,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(73,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(74,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(75,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(76,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(77,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(78,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(79,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(80,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(81,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(82,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(83,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(84,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(85,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(86,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(87,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(88,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(89,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(90,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(93,18.52);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(94,9.91);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(95,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(96,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(97,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(98,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(99,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(100,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(101,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(102,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(103,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(104,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(105,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(106,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(107,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(108,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(109,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(110,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(111,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(112,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(113,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(116,18.52);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(117,9.91);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(118,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(119,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(120,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(121,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(122,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(123,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(124,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(125,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(126,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(127,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(128,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(129,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(130,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(131,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(132,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(133,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(134,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(135,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(136,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(140,9.91);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(141,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(142,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(143,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(144,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(145,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(146,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(147,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(148,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(149,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(150,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(151,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(152,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(153,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(154,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(155,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(156,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(157,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(158,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(159,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(164,5.576);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(165,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(166,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(167,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(168,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(169,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(170,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(171,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(172,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(173,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(174,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(175,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(176,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(177,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(178,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(179,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(180,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(181,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(182,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(188,3.278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(189,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(190,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(191,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(192,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(193,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(194,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(195,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(196,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(197,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(198,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(199,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(200,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(201,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(202,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(203,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(204,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(205,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(212,1.996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(213,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(214,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(215,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(216,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(217,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(218,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(219,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(220,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(221,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(222,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(223,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(224,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(225,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(226,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(227,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(228,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(236,1.253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(237,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(238,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(239,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(240,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(241,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(242,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(243,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(244,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(245,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(246,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(247,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(248,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(249,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(250,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(251,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(260,0.8073);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(261,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(262,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(263,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(264,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(265,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(266,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(267,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(268,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(269,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(270,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(271,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(272,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(273,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(274,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(284,0.5314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(285,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(286,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(287,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(288,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(289,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(290,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(291,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(292,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(293,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(294,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(295,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(296,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(297,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(308,0.3568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(309,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(310,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(311,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(312,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(313,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(314,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(315,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(316,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(317,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(318,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(319,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(320,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(332,0.2438);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(333,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(334,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(335,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(336,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(337,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(338,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(339,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(340,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(341,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(342,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(343,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(356,0.1697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(357,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(358,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(359,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(360,0.04521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(361,0.0334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(362,0.0248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(363,0.01853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(364,0.01396);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(365,0.01061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(366,0.008114);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(380,0.1193);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(381,0.08558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__1->SetBinContent(382,0.06186);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(244,3.980399);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,4.989101);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,6.262023);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,8.038896);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,10.32418);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,12.73147);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,3.963398);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,2.350208);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,2.528821);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,2.686474);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,2.919323);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,3.292393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,3.752463);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,4.519597);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,5.55016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,6.774907);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,8.414433);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,10.84513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,13.46773);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,16.84084);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(360,9.593674);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,11.81599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,17.13266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,14.22525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,15.30689);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,24.37791);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,20.76019);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,27.41517);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,28.94555);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,30.58902);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,34.49137);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,72.75695);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,35.26973);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,35.76892);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,37.27867);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,39.56301);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,99.21111);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,64.14704);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,76.29678);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.3981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.5011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.6309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.7943282);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,1.584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,2.511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,3.162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,3.981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,5.011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,6.309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,7.943282);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(24,0.1289521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(25,0.1541758);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(26,0.1937083);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(27,0.2383537);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(28,0.3104363);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(29,0.3940294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(30,0.5021044);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(31,0.6347155);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(32,0.8105645);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(33,1.090572);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(34,1.404378);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(35,1.845533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(36,2.402482);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(37,3.103287);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(38,3.931376);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(39,5.123431);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(40,6.700808);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(41,8.682929);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(42,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(43,13.81814);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(44,18.1335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(47,0.1322203);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(48,0.1529325);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(49,0.1845724);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(50,0.2242318);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(51,0.2861865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(52,0.3647892);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(53,0.4453922);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(54,0.5914782);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(55,0.7523335);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(56,0.9688619);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(57,1.274983);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(58,1.656317);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(59,2.17263);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(60,2.798527);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(61,3.66613);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(62,4.67756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(63,6.223615);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(64,7.908671);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(65,9.992484);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(66,12.82465);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(67,16.1528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(70,0.1200967);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(71,0.1807687);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(72,0.208756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(73,0.2494983);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(74,0.2989253);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(75,0.3719288);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(76,0.4678497);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(77,0.5928682);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(78,0.748);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(79,0.9692643);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(80,1.2459);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(81,1.675533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(82,2.149704);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(83,2.790175);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(84,3.623213);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(85,4.747694);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(86,6.112383);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(87,7.7669);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(88,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(89,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(90,15.86498);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(93,0.186266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(94,0.2004865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(95,0.2453326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(96,0.2866484);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(97,0.3306177);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(98,0.4025504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(99,0.503104);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(100,0.616222);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(101,0.8042247);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(102,1.01792);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(103,1.330754);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(104,1.749949);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(105,2.224382);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(106,2.903968);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(107,3.619793);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(108,4.836658);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(109,6.24324);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(110,8.081769);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(111,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(112,13.14585);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(113,16.62646);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(116,0.3662614);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(117,0.2648388);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(118,0.3107959);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(119,0.3492486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(120,0.3987123);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(121,0.4530952);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(122,0.5682948);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(123,0.6793032);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(124,0.863239);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(125,1.104169);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(126,1.404271);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(127,1.797408);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(128,2.363122);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(129,3.08334);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(130,3.881112);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(131,5.058183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(132,6.51639);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(133,8.146283);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(134,10.5542);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(135,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(136,17.0979);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(140,0.5144724);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(141,0.384779);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(142,0.4374225);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(143,0.4849232);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(144,0.5629431);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(145,0.6315903);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(146,0.814769);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(147,0.9338483);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(148,1.177734);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(149,1.492587);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(150,1.90957);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(151,2.471465);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(152,3.157637);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(153,4.097225);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(154,5.180128);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(155,6.688811);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(156,8.554077);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(157,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(158,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(159,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(164,0.7880722);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(165,0.5441945);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(166,0.6269822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(167,0.7005969);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(168,0.7976402);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(169,0.8866289);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(170,1.075639);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(171,1.291975);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(172,1.608392);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(173,2.096871);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(174,2.596587);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(175,3.339556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(176,4.33566);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(177,5.4891);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(178,6.870757);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(179,9.036797);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(180,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(181,14.67801);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(182,18.88853);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(188,1.214166);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(189,0.8063742);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(190,0.8654404);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(191,0.9837381);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(192,1.140485);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(193,1.276754);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(194,1.520113);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(195,1.773221);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(196,2.259871);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(197,2.668579);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(198,3.483942);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(199,4.465555);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(200,5.759732);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(201,7.271386);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(202,9.451737);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(203,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(204,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(205,19.36174);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(212,1.96312);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(213,1.12892);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(214,1.279915);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(215,1.407464);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(216,1.54339);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(217,1.772056);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(218,2.001962);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(219,2.470459);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(220,3.01605);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(221,3.80347);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(222,4.78562);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(223,5.976671);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(224,7.628294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(225,9.850221);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(226,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(227,15.55678);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(228,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(236,2.67568);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(237,1.811411);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(238,1.854822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(239,1.94305);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(240,2.081238);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(241,2.370412);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(242,2.820767);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(243,3.263564);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(244,3.980399);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(245,4.989101);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(246,6.262023);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(247,8.038896);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(248,10.32418);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(249,12.73147);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(250,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(251,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(260,3.963398);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(261,2.350208);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(262,2.528821);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(263,2.686474);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(264,2.919323);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(265,3.292393);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(266,3.752463);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(267,4.519597);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(268,5.55016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(269,6.774907);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(270,8.414433);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(271,10.84513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(272,13.46773);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(273,16.84084);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(274,21.29234);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(284,5.542511);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(285,3.371222);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(286,3.536793);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(287,3.735897);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(288,4.067452);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(289,4.389983);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(290,5.211501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(291,5.898674);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(292,7.515955);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(293,9.153016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(294,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(295,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(296,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(297,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(308,8.114857);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(309,4.461896);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(310,4.875648);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(311,5.084722);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(312,5.514084);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(313,5.749712);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(314,6.723928);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(315,8.046573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(316,9.680039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(317,12.14525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(318,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(319,18.28051);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(320,23.1828);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(332,11.40753);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(333,6.217887);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(334,6.266391);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(335,6.807453);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(336,7.331949);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(337,7.861763);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(338,8.913248);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(339,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(340,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(341,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(342,19.78559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(343,24.25847);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(356,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(357,9.265548);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(358,8.350728);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(359,8.820264);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(360,9.593674);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(361,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(362,11.81599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(363,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(364,17.13266);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(365,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(366,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(380,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(381,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(382,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(383,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(384,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(385,14.22525);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(386,15.30689);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(387,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(388,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(389,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(404,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(405,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(406,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(407,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(408,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(409,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(410,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(411,24.37791);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(412,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(428,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(429,20.76019);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(430,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(431,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(432,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(433,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(434,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(435,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(452,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(453,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(454,27.41517);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(455,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(456,28.94555);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(457,30.58902);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(458,34.49137);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(476,72.75695);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(477,35.26973);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(478,35.76892);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(479,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(480,37.27867);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(481,39.56301);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(500,99.21111);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(501,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(502,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(503,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(504,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(524,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(525,64.14704);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(526,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(527,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(548,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(549,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(550,76.29678);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(572,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(573,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(596,10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetMinimum(0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetMaximum(10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetDirectory(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitle(\"R (first guess)\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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"{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:27 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,4.213125);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,3.242304);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.589806);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,25.53525);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,7.8089);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,5.630875);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,4.137374);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,3.109444);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,23.5972);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,7.83775);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,5.291186);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,3.997856);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,24.31575);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,7.234456);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,5.246663);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,24.33312);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,7.258162);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,21.74096);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(24,19.08851);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(25,12.11454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(26,8.476234);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(27,6.009984);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(28,4.773218);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(29,3.776649);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(30,3.062168);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(31,2.555842);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(32,2.18666);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(33,2.003818);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(34,1.800253);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(35,1.66105);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(36,1.543367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(37,1.44532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(38,1.327831);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(39,1.282417);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(40,1.249472);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(41,1.206294);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(42,1.160287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(43,1.096393);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(44,1.093753);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(47,20.09487);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(48,12.32918);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(49,8.158861);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(50,5.80086);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(51,4.474307);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(52,3.514335);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(53,2.75883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(54,2.402244);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(55,2.043317);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(56,1.78865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(57,1.637335);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(58,1.486775);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(59,1.397513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(60,1.298957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(61,1.244538);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(62,1.169367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(63,1.151277);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(64,1.095456);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(65,1.046588);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(66,1.016516);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(67,0.9764156);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(70,22.2366);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(71,14.9922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(72,9.573006);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(73,6.529464);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(74,4.706793);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(75,3.634282);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(76,2.93644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(77,2.424146);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(78,2.057633);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(79,1.798883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(80,1.607653);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(81,1.519469);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(82,1.397513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(83,1.298957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(84,1.226032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(85,1.190552);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(86,1.140347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(87,1.078406);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(88,1.053287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(89,1.027077);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(90,0.9659357);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(93,30.36486);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(94,16.69842);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(95,11.42759);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(96,7.623036);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(97,5.239043);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(98,3.995805);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(99,3.180323);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(100,2.533659);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(101,2.229608);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(102,1.911584);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(103,1.740984);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(104,1.595732);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(105,1.446148);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(106,1.359961);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(107,1.244538);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(108,1.218815);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(109,1.173102);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(110,1.129556);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(111,1.073338);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(112,1.0482);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(113,1.009941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(116,63.75523);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(117,22.66474);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(118,14.54734);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(119,9.44388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(120,6.503669);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(121,4.575922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(122,3.624159);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(123,2.829902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(124,2.387449);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(125,2.101299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(126,1.829934);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(127,1.650175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(128,1.551456);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(129,1.457536);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(130,1.337069);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(131,1.282417);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(132,1.227648);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(133,1.146606);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(134,1.113463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(135,1.082528);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(136,1.043466);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(140,49.73874);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(141,18.47025);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(142,11.91474);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(143,8.016962);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(144,5.758017);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(145,4.097534);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(146,3.433342);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(147,2.645502);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(148,2.265299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(149,1.978059);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(150,1.759062);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(151,1.64463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(152,1.494107);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(153,1.420362);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(154,1.32481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(155,1.260402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(156,1.206294);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(157,1.171982);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(158,1.145896);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(159,1.093753);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(164,41.99903);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(165,15.45386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(166,10.67821);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(167,7.137407);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(168,5.251433);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(169,3.762158);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(170,3.068555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(171,2.511299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(172,2.141072);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(173,1.955156);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(174,1.72562);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(175,1.603899);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(176,1.503625);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(177,1.413125);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(178,1.304052);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(179,1.283006);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(180,1.213787);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(181,1.177579);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(182,1.160803);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(188,37.87942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(189,13.63923);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(190,9.064406);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(191,6.538634);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(192,4.935903);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(193,3.656424);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(194,2.962234);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(195,2.378147);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(196,2.118556);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(197,1.790432);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(198,1.689257);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(199,1.57765);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(200,1.490858);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(201,1.391353);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(202,1.342694);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(203,1.300713);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(204,1.230386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(205,1.200611);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(212,37.9226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(213,12.30466);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(214,8.727899);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(215,6.208207);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(216,4.459398);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(217,3.454234);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(218,2.718966);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(219,2.363587);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(220,2.017276);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(221,1.83562);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(222,1.688688);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(223,1.561492);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(224,1.467723);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(225,1.410894);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(226,1.327463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(227,1.272631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(228,1.211091);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(236,32.6665);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(237,12.8402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(238,8.358293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(239,5.764163);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(240,4.120467);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(241,3.244988);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(242,2.690388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(243,2.227943);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(244,1.933195);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(245,1.781219);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(246,1.646279);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(247,1.555022);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(248,1.494003);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(249,1.380963);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(250,1.335998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(251,1.286522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(260,31.59797);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(261,10.9248);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(262,7.65698);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(263,5.391533);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(264,4.07475);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(265,3.169644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(266,2.552005);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(267,2.22592);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(268,1.989437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(269,1.773483);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(270,1.631428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(271,1.572856);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(272,1.477937);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(273,1.390122);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(274,1.334711);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(284,30.537);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(285,10.52475);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(286,7.318467);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(287,5.230443);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(288,3.99745);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(289,3.02187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(290,2.57356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(291,2.137487);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(292,1.985429);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(293,1.784202);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(294,1.624006);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(295,1.531438);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(296,1.452172);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(297,1.401761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(308,27.64526);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(309,9.552935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(310,7.0233);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(311,5.032226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(312,3.872573);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(313,2.866285);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(314,2.433587);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(315,2.155004);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(316,1.916514);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(317,1.781725);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(318,1.665187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(319,1.526101);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(320,1.479291);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(332,27.88);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(333,9.0978);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(334,6.339288);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(335,4.84476);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(336,3.689545);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(337,2.840724);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(338,2.409367);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(339,2.133403);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(340,1.935175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(341,1.745438);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(342,1.663397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(343,1.563103);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(356,25.42629);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(357,9.802969);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(358,6.059969);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(359,4.500628);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(360,3.562438);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(361,2.868644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(362,2.348911);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(363,2.054525);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(364,1.905938);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(365,1.747887);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(366,1.646916);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(380,27.62259);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(381,8.652469);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(382,6.464344);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(383,4.575663);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(384,3.405631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(385,2.891813);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(386,2.276175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(387,2.053062);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(388,1.842938);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(389,1.701394);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(404,27.44809);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(405,8.35484);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(406,5.977519);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(407,4.366556);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(408,3.328312);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(409,2.789803);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(410,2.293813);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(411,2.054163);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(412,1.852256);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(428,26.63798);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(429,8.179763);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->SetBinContent(430,6.132963);\n 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[GeV]__10->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitle(\"Expected asympt. cross section limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__10->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.3788589835166931, "alphanum_fraction": 0.6085947155952454, "avg_line_length": 89.11127471923828, "blob_id": "742a051793fc555ce0918198cf365773e0a843cb", 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211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,0.08555087);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,0.07272092);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,0.07158749);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,0.0676102);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,0.06559794);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,0.06104545);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,0.05697012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,0.05701432);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,0.05620573);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,0.05401376);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,0.3204363);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,0.1977753);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,0.1457013);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,0.1003111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.08535825);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.08201012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.07245346);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.06457373);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.05785334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.05514707);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,0.05214613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,0.05038203);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,0.04737556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,0.04499687);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,0.04412623);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,0.04200564);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,0.04222027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,0.0399221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,0.2258734);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,0.124243);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,0.08395032);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,0.06760896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.05628128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.05518584);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.05236246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.04677347);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.04201088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.04070017);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.03951381);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.03925769);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.03562446);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.03547809);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.03432778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.03320134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.03157222);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,0.1683882);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,0.08377352);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,0.06032293);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.04843381);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.04525147);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.04039318);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.04109742);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.03473752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.03457256);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.03394019);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.03279442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.03044423);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.02994244);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.03024155);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.02864424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.02814333);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.1038817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.05964806);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.04641362);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.04031574);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.03820609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.03441065);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.03418741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.03026092);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.02984588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.03175565);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.02780105);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.02760229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.02643815);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.02629434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.02501408);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.08420724);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.05402059);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.04053102);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.03494259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.03213023);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.02917448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.02817451);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.02708816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.0272397);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.02581308);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.02487968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.02523256);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.02393107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.02340905);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.06839214);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.04441012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.03525976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.03208239);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.03169378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.02659937);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.02660532);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.02449165);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.02466439);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.02397245);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.02441744);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.02301277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.02298226);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.05732762);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.04054388);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.03218917);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.02920246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.02693496);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.0250765);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.02442251);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.02400434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.02312655);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.02229873);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.0223314);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.02078085);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.04577793);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.03752617);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.02994059);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.02644063);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.02430128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.02392896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.02269108);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.02203662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.02176908);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.02168514);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.02118501);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.04358912);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.03506555);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.02933475);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.02448619);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.02335989);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.02176748);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.02147683);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.02146853);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.020272);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.0202127);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.03648857);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.03225331);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.02586134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.02335849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.02243775);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.02090277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.02075196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.02051242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.02020224);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.03353728);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.0306144);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.02491122);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.02255146);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.021104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.02016438);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.01984781);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.01965057);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.03236652);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.02878656);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.02341599);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.02170437);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.02029407);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.0198877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.0187448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.02877273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.02813064);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.02278653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.02092576);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.01939519);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.01935652);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.02782758);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.02713793);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.0229931);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.02021067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.01922815);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.02609673);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.02598235);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.02206243);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.01959912);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.02514615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.02513933);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.02073224);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.02400587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.02463735);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.02351956);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.02481893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.03079896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.03821987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.04742881);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.05885662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.07303792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.09063615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.1124746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.139575);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.1732051);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.2149382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.2667269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,0.3309938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,0.4107456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,0.5097133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,0.6325269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,0.7849321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,0.9740587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,1.208755);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(24,0.7121533);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(25,0.5108545);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(26,0.3073441);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(27,0.1929827);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(28,0.1426821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(29,0.1123856);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(30,0.07820582);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(31,0.0665993);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(32,0.05524013);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(33,0.05013674);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(34,0.04408382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(35,0.04256731);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(36,0.03833205);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(37,0.03634232);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(38,0.0349826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(39,0.03319459);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(40,0.03180724);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(41,0.02969303);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(42,0.03140749);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(43,0.02961707);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(44,0.02876234);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(47,0.5657564);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(48,0.3236586);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(49,0.2459852);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(50,0.1579245);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(51,0.10906);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(52,0.0815292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(53,0.07314703);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(54,0.05636454);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(55,0.0532763);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(56,0.04716067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(57,0.04519281);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(58,0.03650043);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(59,0.03504852);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(60,0.03080059);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(61,0.03080976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(62,0.02956692);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(63,0.02925036);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(64,0.02859364);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(65,0.02810944);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(66,0.02703004);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(67,0.02762062);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(70,0.7501971);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(71,0.5152972);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(72,0.3112501);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(73,0.2276384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(74,0.1533543);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(75,0.1271933);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(76,0.09509186);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(77,0.09200766);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(78,0.07069992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(79,0.0661817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(80,0.05747009);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(81,0.05230768);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(82,0.04785659);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(83,0.04531591);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(84,0.04507084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(85,0.04477838);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(86,0.04091628);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(87,0.03857501);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(88,0.04073416);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(89,0.03692959);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(90,0.03753893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(94,0.5478248);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(95,0.3834649);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(96,0.2488549);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(97,0.1836717);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(98,0.1426328);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(99,0.1273968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(100,0.1041693);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(101,0.09187101);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(102,0.09296435);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(103,0.08257076);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(104,0.07454007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(105,0.06547169);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(106,0.06156518);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(107,0.05965505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(108,0.05843764);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(109,0.05575214);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(110,0.05505782);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(111,0.05220677);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(112,0.05372055);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(113,0.05231648);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(118,0.3622593);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(119,0.3395877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(120,0.2126059);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(121,0.169868);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(122,0.1469415);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(123,0.1174559);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(124,0.1069094);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(125,0.09767798);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(126,0.09351047);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(127,0.08555087);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(128,0.07272092);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(129,0.07158749);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(130,0.0676102);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(131,0.06559794);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(132,0.06104545);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(133,0.05697012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(134,0.05701432);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(135,0.05620573);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(136,0.05401376);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(142,0.3204363);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(143,0.1977753);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(144,0.1457013);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(145,0.1003111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(146,0.08535825);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(147,0.08201012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(148,0.07245346);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(149,0.06457373);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(150,0.05785334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(151,0.05514707);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(152,0.05214613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(153,0.05038203);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(154,0.04737556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(155,0.04499687);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(156,0.04412623);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(157,0.04200564);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(158,0.04222027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(159,0.0399221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(166,0.2258734);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(167,0.124243);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(168,0.08395032);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(169,0.06760896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(170,0.05628128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(171,0.05518584);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(172,0.05236246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(173,0.04677347);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(174,0.04201088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(175,0.04070017);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(176,0.03951381);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(177,0.03925769);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(178,0.03562446);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(179,0.03547809);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(180,0.03432778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(181,0.03320134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(182,0.03157222);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(190,0.1683882);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(191,0.08377352);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(192,0.06032293);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(193,0.04843381);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(194,0.04525147);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(195,0.04039318);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(196,0.04109742);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(197,0.03473752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(198,0.03457256);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(199,0.03394019);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(200,0.03279442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(201,0.03044423);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(202,0.02994244);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(203,0.03024155);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(204,0.02864424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(205,0.02814333);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(214,0.1038817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(215,0.05964806);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(216,0.04641362);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(217,0.04031574);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(218,0.03820609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(219,0.03441065);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(220,0.03418741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(221,0.03026092);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(222,0.02984588);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(223,0.03175565);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(224,0.02780105);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(225,0.02760229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(226,0.02643815);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(227,0.02629434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(228,0.02501408);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(238,0.08420724);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(239,0.05402059);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(240,0.04053102);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(241,0.03494259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(242,0.03213023);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(243,0.02917448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(244,0.02817451);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(245,0.02708816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(246,0.0272397);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(247,0.02581308);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(248,0.02487968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(249,0.02523256);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(250,0.02393107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(251,0.02340905);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(262,0.06839214);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(263,0.04441012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(264,0.03525976);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(265,0.03208239);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(266,0.03169378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(267,0.02659937);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(268,0.02660532);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(269,0.02449165);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(270,0.02466439);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(271,0.02397245);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(272,0.02441744);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(273,0.02301277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(274,0.02298226);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(286,0.05732762);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(287,0.04054388);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(288,0.03218917);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(289,0.02920246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(290,0.02693496);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(291,0.0250765);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(292,0.02442251);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(293,0.02400434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(294,0.02312655);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(295,0.02229873);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(296,0.0223314);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(297,0.02078085);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(310,0.04577793);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(311,0.03752617);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(312,0.02994059);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(313,0.02644063);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(314,0.02430128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(315,0.02392896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(316,0.02269108);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(317,0.02203662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(318,0.02176908);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(319,0.02168514);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(320,0.02118501);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(334,0.04358912);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(335,0.03506555);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(336,0.02933475);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(337,0.02448619);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(338,0.02335989);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(339,0.02176748);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(340,0.02147683);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(341,0.02146853);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(342,0.020272);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(343,0.0202127);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(358,0.03648857);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(359,0.03225331);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(360,0.02586134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(361,0.02335849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(362,0.02243775);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(363,0.02090277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(364,0.02075196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(365,0.02051242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(366,0.02020224);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(382,0.03353728);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(383,0.0306144);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(384,0.02491122);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(385,0.02255146);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(386,0.021104);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(387,0.02016438);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(388,0.01984781);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(389,0.01965057);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(406,0.03236652);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(407,0.02878656);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(408,0.02341599);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(409,0.02170437);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(410,0.02029407);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(411,0.0198877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(412,0.0187448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(430,0.02877273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(431,0.02813064);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(432,0.02278653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(433,0.02092576);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(434,0.01939519);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(435,0.01935652);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(454,0.02782758);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(455,0.02713793);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(456,0.0229931);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__8->SetBinContent(457,0.02021067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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"max_line_length": 181, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Direct_sbottom_neutralino2_ExpR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:27 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,5.81987);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,7.19378);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,8.74935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,10.9192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,13.5437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,16.23);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(164,1.96512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(165,1.16319);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,1.25965);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,1.27025);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,1.38955);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,1.33956);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,1.66652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,1.91773);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,2.26402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,2.81782);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,3.32822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,4.09872);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,5.10824);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,6.25344);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,7.46081);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,9.40928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,11.3648);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,14.0372);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,17.3024);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,2.84922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,1.57706);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,1.61873);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,1.73731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,1.75717);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,2.00123);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,2.28874);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,2.5114);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,3.03287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,3.43676);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,4.29333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,5.28354);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,6.53019);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,7.97461);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,9.87356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,12.0148);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,14.5097);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,18.0614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,4.48068);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,2.19221);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,2.27418);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,2.22871);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,2.4127);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,2.61602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,2.85265);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,3.3614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,3.89593);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,4.71581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,5.68731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,6.98883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,8.46851);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,10.3586);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,12.3866);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,15.032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,17.8536);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,5.90177);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.4522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,3.02084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,3.08563);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,3.14271);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,3.43625);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,3.84022);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,4.3039);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,4.93163);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,6.00922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,7.21787);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,8.85581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,10.9047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,12.8836);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,15.7397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,19.0819);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,8.34439);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,3.93365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,4.19737);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,4.06216);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,4.2939);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,4.5434);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,4.97137);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,5.758);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,6.70081);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,7.78751);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,9.35057);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,11.4599);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,13.6809);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,16.3101);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,19.9808);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,10.9106);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,5.68863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,5.59555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,5.4775);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,5.74431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,5.83977);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,6.60935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,7.22938);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,8.81803);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,10.2636);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,11.8275);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,13.9428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,17.2859);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,20.7433);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,15.1272);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,7.3077);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,7.42466);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,7.14299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,7.48791);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,7.31481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,8.22723);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,9.39216);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,10.9425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,13.1107);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,15.381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,17.9675);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,22.0779);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,21.1295);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,9.5841);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,9.14293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,9.37195);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,9.41397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,9.50098);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,10.5642);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,12.2168);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,14.2329);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,16.3215);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,19.7074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,23.4781);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,27.0621);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,13.9428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,11.6323);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,11.5459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,11.9829);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,12.7642);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,13.3662);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,15.2004);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,17.7504);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,20.6834);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,24.277);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,16.7493);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,16.4401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,15.4351);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,14.8802);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,16.431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,16.6822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,19.1415);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,21.7047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,24.9789);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,21.4477);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,20.3998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,19.1603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,18.908);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,20.3171);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,21.506);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,24.1957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,27.9091);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,27.7714);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,26.7822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,24.4927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,24.4373);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,25.1328);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,27.1866);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,33.2386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,31.0361);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,110.473);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,38.2671);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,145.373);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,73.4048);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,78.6731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.265941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(159.9103);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.265941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.3662181);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.5043063);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.6944628);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.9563206);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,1.316916);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,1.813479);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,2.49728);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,3.438917);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,4.735614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,6.52125);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,8.980188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,12.36631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,17.02921);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,23.45034);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,32.29265);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,44.46909);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,61.23684);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,84.32713);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,116.124);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(24,0.29549);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(25,0.344766);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(26,0.396381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(27,0.448991);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(28,0.564837);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(29,0.67421);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(30,0.816025);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(31,0.916083);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(32,1.17077);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(33,1.52994);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(34,1.88454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(35,2.36816);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(36,2.95093);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(37,3.69867);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(38,4.48454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(39,5.65712);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(40,7.10288);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(41,8.78331);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(42,10.7745);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(43,12.9886);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(44,16.3889);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(47,0.316146);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(48,0.341573);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(49,0.372343);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(50,0.438834);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(51,0.52274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(52,0.630598);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(53,0.728619);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(54,0.858454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(55,1.10215);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(56,1.35258);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(57,1.71312);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(58,2.12532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(59,2.69029);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(60,3.32165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(61,4.19911);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(62,5.23195);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(63,6.60649);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(64,7.98597);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(65,9.7602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(66,12.0492);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(67,14.569);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(70,0.35009);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(71,0.403417);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(72,0.445257);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(73,0.492122);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(74,0.55085);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(75,0.64667);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(76,0.77625);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(77,0.860781);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(78,1.11312);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(79,1.36709);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(80,1.67875);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(81,2.18466);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(82,2.68513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(83,3.33693);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(84,4.14896);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(85,5.21717);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(86,6.45618);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(87,7.94626);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(88,9.98471);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(89,12.0513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(90,14.4008);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(93,0.472297);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(94,0.464924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(95,0.529386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(96,0.569073);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(97,0.61305);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(98,0.716179);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(99,0.84071);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(100,0.900816);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(101,1.21869);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(102,1.45605);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(103,1.83257);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(104,2.26519);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(105,2.76666);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(106,3.49018);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(107,4.1651);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(108,5.35882);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(109,6.71501);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(110,8.20292);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(111,10.1693);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(112,12.3398);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(113,15.0968);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(116,0.989845);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(117,0.622577);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(118,0.679351);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(119,0.712155);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(120,0.766055);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(121,0.81096);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(122,0.96606);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(123,1.0009);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(124,1.30718);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(125,1.57225);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(126,1.93767);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(127,2.44761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(128,2.98438);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(129,3.74996);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(130,4.50043);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(131,5.6581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(132,7.04332);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(133,8.37126);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(134,10.4315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(135,12.8105);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(136,15.6894);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(140,1.37858);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(141,0.856996);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(142,0.890877);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(143,0.950084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(144,1.02858);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(145,1.07304);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(146,1.22158);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(147,1.45004);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(148,1.70793);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(149,2.07148);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(150,2.53047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(151,3.15581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(152,3.84208);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(153,4.8124);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(154,5.81987);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(155,7.19378);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(156,8.74935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(157,10.9192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(158,13.5437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(159,16.23);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(164,1.96512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(165,1.16319);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(166,1.25965);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(167,1.27025);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(168,1.38955);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(169,1.33956);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(170,1.66652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(171,1.91773);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(172,2.26402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(173,2.81782);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(174,3.32822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(175,4.09872);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(176,5.10824);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(177,6.25344);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(178,7.46081);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(179,9.40928);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(180,11.3648);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(181,14.0372);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(182,17.3024);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(188,2.84922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(189,1.57706);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(190,1.61873);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(191,1.73731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(192,1.75717);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(193,2.00123);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(194,2.28874);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(195,2.5114);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(196,3.03287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(197,3.43676);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(198,4.29333);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(199,5.28354);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(200,6.53019);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(201,7.97461);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(202,9.87356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(203,12.0148);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(204,14.5097);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(205,18.0614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(212,4.48068);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(213,2.19221);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(214,2.27418);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(215,2.22871);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(216,2.4127);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(217,2.61602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(218,2.85265);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(219,3.3614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(220,3.89593);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(221,4.71581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(222,5.68731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(223,6.98883);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(224,8.46851);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(225,10.3586);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(226,12.3866);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(227,15.032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(228,17.8536);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(236,5.90177);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(237,3.4522);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(238,3.02084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(239,3.08563);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(240,3.14271);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(241,3.43625);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(242,3.84022);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(243,4.3039);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(244,4.93163);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(245,6.00922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(246,7.21787);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(247,8.85581);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(248,10.9047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(249,12.8836);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(250,15.7397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(251,19.0819);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(260,8.34439);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(261,3.93365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(262,4.19737);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(263,4.06216);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(264,4.2939);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(265,4.5434);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(266,4.97137);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(267,5.758);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(268,6.70081);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(269,7.78751);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(270,9.35057);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(271,11.4599);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(272,13.6809);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(273,16.3101);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(274,19.9808);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(284,10.9106);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(285,5.68863);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(286,5.59555);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(287,5.4775);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(288,5.74431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(289,5.83977);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(290,6.60935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(291,7.22938);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(292,8.81803);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(293,10.2636);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(294,11.8275);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(295,13.9428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(296,17.2859);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(297,20.7433);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(308,15.1272);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(309,7.3077);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(310,7.42466);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(311,7.14299);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(312,7.48791);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(313,7.31481);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(314,8.22723);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(315,9.39216);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(316,10.9425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(317,13.1107);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(318,15.381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(319,17.9675);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(320,22.0779);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(332,21.1295);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(333,9.5841);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(334,9.14293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(335,9.37195);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(336,9.41397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(337,9.50098);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(338,10.5642);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(339,12.2168);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(340,14.2329);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(341,16.3215);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(342,19.7074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(343,23.4781);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(356,27.0621);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(357,13.9428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(358,11.6323);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(359,11.5459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(360,11.9829);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(361,12.7642);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(362,13.3662);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(363,15.2004);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(364,17.7504);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(365,20.6834);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(366,24.277);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(380,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(381,16.7493);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(382,16.4401);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(383,15.4351);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(384,14.8802);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(385,16.431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(386,16.6822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(387,19.1415);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(388,21.7047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(389,24.9789);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(404,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(405,21.4477);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(406,20.3998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(407,19.1603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(408,18.908);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(409,20.3171);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(410,21.506);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(411,24.1957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(412,27.9091);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(428,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(429,27.7714);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(430,26.7822);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(431,24.4927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(432,24.4373);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(433,25.1328);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(434,27.1866);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(435,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(452,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(453,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(454,33.2386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(455,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(456,31.0361);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(457,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(458,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(476,110.473);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(477,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(478,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(479,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(480,38.2671);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(481,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(500,145.373);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(501,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(502,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(503,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(504,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(524,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(525,73.4048);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(526,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(527,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(548,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(549,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(550,78.6731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(572,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(573,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(596,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetMinimum(0.265941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetMaximum(159.9103);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetDirectory(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitle(\"Expected R\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.6052871346473694, "alphanum_fraction": 0.6349133849143982, "avg_line_length": 26.0864200592041, "blob_id": "8e98bd593ff6a0f31ad15decce65f7967627b72c", "content_id": "e9f80db7163edbf28aa050b92fcbf83a9e9e180d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 2194, "license_type": "no_license", "max_line_length": 97, "num_lines": 81, "path": "/LimitTools/Orig.sh~", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "#!/bin/bash\n\n #exec > /dev/null 2>/dev/null\n \n WORKDIR=AUniquePlaceholderName\n #CONFIGDIR=ConfigDirPlaceholderName\n RELEASEDIR=ReleaseDirPlaceholderName\n \n# ZERO=\"\" #$SGE_TASK_ID\n# if [ $SGE_TASK_ID -lt 1000 ]; then\n# ZERO=\"0\"\n# fi\n# if [ $SGE_TASK_ID -lt 100 ]; then\n# ZERO=\"00\"\n# fi\n# if [ $SGE_TASK_ID -lt 10 ]; then\n# ZERO=\"000\"\n# fi\n JOB=`printf \"%04d\" \"$SGE_TASK_ID\"`\n\n # change to scratch directory (local, not lustre in this example)\n #cd $TMPDIR\n # copy raw data to scratch directory (here from the afs)\n # DO NOT USE afscp UNTIL FURTHER NOTICE afscp /afs/naf.desy.de/group/vo/rawdata/bigfile bigfile\n # cp /afs/naf.desy.de/group/vo/rawdata/bigfile bigfile\n #sleep $SGE_TASK_ID\n \n #cp -r $RELEASEDIR .\n #RELEASEBASE=`basename $RELEASEDIR`\n cd $RELEASEDIR/src\n #ini cmssw\n #cmsenv\n #pwd > stdout.txt\n #module use -a /afs/desy.de/group/cms/modulefiles/\n #module load cmssw/slc5_amd64_gcc472\n #cmsenv\n #which combine > stdout.txt\n# setenv SCRAM_ARCH slc5_amd64_gcc472\n# module load cmssw/slc5_amd64_gcc472\n# setcms\n #ini root530 \n\n cd $WORKDIR\n \n mkdir job$JOB/results\n mkdir job$JOB/log\n cd job$JOB\n\n pwd > stdout.txt\n \n export SCRAM_ARCH=\"slc5_amd64_gcc472\" \n export VO_CMS_SW_DIR=\"/cvmfs/cms.cern.ch\" \n echo \"VO_CMS_SW_DIR = $VO_CMS_SW_DIR, SCRAM_ARCH = $SCRAM_ARCH\" >> stdout.txt\n source $VO_CMS_SW_DIR/cmsset_default.sh >> stdout.txt\n ini cmssw >> stdout.txt\n ##cmsenv >> stdout.txt\n eval `scramv1 runtime -sh` >> stdout.txt \n \n which combine >> stdout.txt\n echo \"SGE_TASK_ID = $SGE_TASK_ID\" >> stdout.txt\n date >> stdout.txt\n for i in `cat config/config_`\n do \n echo $i >> stdout.txt\n cat ../../$i >> stdout.txt\n file=\"${i##/}\"\n echo \"copying ../../$i to config/$file\" >> stdout.txt\n cp ../../$i config/$file \n echo \"calling ../../limit config/$file\" >> stdout.txt\n ../../limit_V2_13TeV config/$file\n done\n du -h --max-depth=1 >> stdout.txt\n date >> stdout.txt\n ls -l >> stdout.txt\n\n #cp results/ job$SGE_TASK_ID/results/.\n mv stdout.txt log/.\n #cp stderr.txt log/.\n #cp -r job$SGE_TASK_ID $RESULTPATH/.\n\n### qsub -t 1-3609 -l h_cpu=00:15:00 -l h_vmem=4000M job.sh\n" }, { "alpha_fraction": 0.4624400734901428, "alphanum_fraction": 0.6737852692604065, "avg_line_length": 80.31958770751953, "blob_id": "1315afbc6cc01e0c634b0de65477c15d1cc3303a", "content_id": "b754ee83780293e01bb0b509967190bf91ebc647", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 86768, "license_type": "no_license", "max_line_length": 155, "num_lines": 1067, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_Xsection.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:37 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",0,0,900,800);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(37,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(38,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(39,0.39);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(40,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(41,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(42,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(43,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(44,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(45,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(49,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(50,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(51,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(52,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(53,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(54,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(57,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(58,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(59,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(60,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(61,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(62,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(63,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(64,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(65,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(66,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(67,0.4056667);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(68,0.2918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(69,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(70,0.15625);\n 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[GeV]->SetBinContent(692,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,0.02028);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,0.016175);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,0.01026);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.007326);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20.9);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.007326);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.01090513);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01623285);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.02416344);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.03596854);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.05354103);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.0796986);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.1186355);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.1765951);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.262871);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3912971);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.582466);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.8670308);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.29062);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.921155);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.859739);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,4.25687);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,6.336572);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,9.432316);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,14.04049);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"NLO cross section [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(29,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(30,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(31,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(32,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(33,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(34,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(35,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(36,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(37,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(38,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(39,0.39);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(40,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(41,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(42,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(43,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(44,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(45,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(46,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(47,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(48,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(49,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(50,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(51,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(52,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(53,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(54,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(57,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(58,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(59,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(60,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(61,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(62,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(63,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(64,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(65,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(66,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(67,0.4056667);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(68,0.2918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(69,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(70,0.15625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(71,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(72,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(73,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(74,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(75,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(76,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(77,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(78,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(79,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(80,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(81,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(82,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(85,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(86,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(87,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(88,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(89,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(90,2.1375);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(91,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(92,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(93,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(94,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(95,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(96,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(97,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(98,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(99,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(100,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(101,0.07211667);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(102,0.0576);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(103,0.04438333);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(104,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(105,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(106,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(107,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(108,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(109,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(110,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(113,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(114,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(115,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(116,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(117,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(118,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(119,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(120,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(121,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(122,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(123,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(124,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(125,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(126,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(127,0.11786);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(128,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(129,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(130,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(131,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(132,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(133,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(134,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(135,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(136,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(137,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(138,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(141,19);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(142,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(143,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(144,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(145,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(146,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(147,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(148,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(149,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(150,0.5753);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(151,0.4914);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(152,0.4021);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(153,0.3183556);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(154,0.2390556);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(155,0.15798);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(156,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(157,0.06915);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(158,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(159,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(160,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(161,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(162,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(163,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(164,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(165,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(166,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(170,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(171,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(172,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(173,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(174,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(175,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(176,1.095667);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(177,0.8088571);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(178,0.56775);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(179,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(180,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(181,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(182,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(183,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(184,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(185,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(186,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(187,0.04481);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(188,0.03852222);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(189,0.03234445);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(190,0.02643333);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(191,0.02083333);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(192,0.01538889);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(193,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(194,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(198,11.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(199,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(200,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(201,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(202,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(203,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(204,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(205,0.7416667);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(206,0.536);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(207,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(208,0.3201818);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(209,0.2769091);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(210,0.2372727);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(211,0.2);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(212,0.1644182);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(213,0.1301636);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(214,0.09681818);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(215,0.06225);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(216,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(217,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(218,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(219,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(220,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(221,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(222,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(227,7.16);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(228,4.61);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(229,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(230,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(231,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(232,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(233,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(234,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(235,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(236,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(237,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(238,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(239,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(240,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(241,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(242,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(243,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(244,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(245,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(246,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(247,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(248,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(249,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(250,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(257,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(258,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(259,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(260,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(261,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(262,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(263,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(264,0.27925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(265,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(266,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(267,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(268,0.090125);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(269,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(270,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(271,0.041625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(272,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(273,0.02658333);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(274,0.02134286);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(275,0.01687143);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(276,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(277,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(278,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(285,3.04);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(286,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(287,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(288,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(289,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(290,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(291,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(292,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(293,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(294,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(295,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(296,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(297,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(298,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(299,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(300,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(301,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(302,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(303,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(304,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(305,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(306,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(314,2.05);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(315,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(316,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(317,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(318,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(319,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(320,0.27925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(321,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(322,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(323,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(324,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(325,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(326,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(327,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(328,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(329,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(330,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(331,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(332,0.0127);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(333,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(334,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(343,1.41);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(344,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(345,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(346,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(347,0.368);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(348,0.273);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(349,0.203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(350,0.153);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(351,0.116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(352,0.0883);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(353,0.0679);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(354,0.0525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(355,0.041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(356,0.032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(357,0.0254);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(358,0.02);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(359,0.016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(360,0.012875);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(361,0.0101);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(362,0.00814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(372,0.988);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(373,0.702);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(374,0.507);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 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[GeV]->SetBinContent(245,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(-99900);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(-99900);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,-100899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,-100799.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,-100699.2);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,-100599.3);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,-100499.4);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,-100399.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,-100299.6);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,-100199.7);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,-100099.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,-99999.9);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,-99900);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,-99800.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,-99700.2);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,-99600.3);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,-99500.4);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,-99400.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,-99300.6);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,-99200.7);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,-99100.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,-99000.9);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(19);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. [%]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(24,-9.300883);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(25,-16.49258);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(26,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(27,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(28,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(29,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(30,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(31,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(32,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(33,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(34,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(35,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(36,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(37,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(38,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(39,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(40,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(41,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(42,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(43,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(44,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(47,-9.300883);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(48,-16.49258);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(49,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(50,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(51,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(52,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(53,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(54,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(55,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(56,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(57,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(58,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(59,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(60,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(61,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(62,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(63,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(64,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(65,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(66,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(67,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(70,-9.300883);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(71,-16.49258);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(72,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(73,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(74,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(75,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(76,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(77,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(78,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(79,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(80,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(81,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(82,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(83,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(84,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(85,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(86,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(87,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(88,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(89,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(90,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(93,-9.300883);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(94,-16.49258);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(95,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(96,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(97,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(98,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(99,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(100,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(101,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(102,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(103,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(104,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(105,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(106,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(107,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(108,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(109,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(110,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(111,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(112,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(113,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(116,-9.300883);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(117,-16.49258);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(118,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(119,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(120,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(121,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(122,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(123,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(124,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(125,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(126,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(127,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(128,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(129,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(130,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(131,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(132,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(133,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(134,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(135,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(136,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(140,-16.49258);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(141,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(142,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(143,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(144,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(145,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(146,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(147,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(148,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(149,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(150,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(151,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(152,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(153,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(154,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(155,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(156,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(157,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(158,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(159,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(164,-27.79064);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(165,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(166,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(167,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(168,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(169,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(170,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(171,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(172,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(173,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(174,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(175,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(176,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(177,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(178,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(179,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(180,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(181,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(182,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(188,-45.04504);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(189,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(190,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(191,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(192,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(193,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(194,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(195,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(196,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(197,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(198,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(199,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(200,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(201,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(202,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(203,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(204,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(205,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(212,-70.45561);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(213,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(214,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(215,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(216,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(217,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(218,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(219,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(220,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(221,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(222,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(223,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(224,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(225,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(226,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(227,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(228,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(236,-107.0473);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(237,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(238,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(239,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(240,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(241,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(242,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(243,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(244,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(245,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(246,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(247,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(248,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(249,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(250,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(251,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(260,-158.4368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(261,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(262,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(263,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(264,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(265,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(266,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(267,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(268,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(269,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(270,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(271,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(272,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(273,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(274,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(284,-213.6752);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(285,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(286,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(287,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(288,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(289,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(290,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(291,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(292,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(293,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(294,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(295,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(296,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(297,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(308,-326.9095);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(309,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(310,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(311,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(312,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(313,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(314,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(315,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(316,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(317,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(318,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(319,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(320,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(332,-457.3171);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(333,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(334,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(335,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(336,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(337,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(338,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(339,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(340,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(341,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(342,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(343,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(356,-632.7112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(357,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(358,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(359,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(360,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(361,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(362,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(363,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(364,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(365,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(366,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(380,-860.7087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(381,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(382,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(383,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(384,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(385,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(386,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(387,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(388,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(389,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(404,-1157.184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(405,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(406,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(407,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(408,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(409,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(410,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(411,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(412,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(428,-1537.279);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(429,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(430,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(431,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(432,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(433,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(434,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(435,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(452,-2026.342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(453,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(454,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(455,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(456,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(457,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(458,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(476,-2653.693);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(477,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(478,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(479,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(480,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(481,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(500,-3436.426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(501,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(502,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(503,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(504,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(524,-4398.827);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(525,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(526,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(527,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(548,-5607.477);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(549,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(550,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(572,-7101.432);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(573,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(596,-8948.546);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetMinimum(-99900);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetMaximum(-99900);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. 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"license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Sel_Eff_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 09:50:02 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n 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[GeV]->SetBinContent(220,0.5763127);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.5253048);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.483324);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.4474067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.418621);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.4029392);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.3785553);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.3625043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.3448113);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,8.746602);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.458288);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,2.28515);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,1.610721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,1.162038);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.9175751);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.7634639);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.6344366);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.551572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.5079595);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.4673939);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.4433094);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.4261136);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.3951403);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.3819793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.3659723);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,8.394264);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,2.928463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,2.106638);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,1.49791);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,1.144977);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.8966798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.7243963);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.6330666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.5670611);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.5085441);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.4676486);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.448265);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.4213446);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.3966721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.3811524);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,8.130564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,2.837666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,2.011296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,1.457158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,1.123865);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.8592582);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.7329053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.6061167);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.568732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.5116653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.4636782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.4374267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.416485);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.400208);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,7.394155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,2.570208);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.919644);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.396222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,1.092272);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.8146732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6959534);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.611397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.5460615);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.5094267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.4734322);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.4363486);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.4227167);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,7.446387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.452493);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,1.741077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,1.352818);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,1.042179);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.8063099);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.6858065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.6099826);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.5525155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.4962874);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.4744029);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.4463787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,6.81932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,2.633295);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,1.666044);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,1.256961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,1.002802);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.8183237);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.6699926);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.5876385);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.5445016);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.4980009);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.4702015);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,7.377828);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,2.323087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,1.773796);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,1.279122);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.9635252);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.8182105);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.650287);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.5845624);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.5262544);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.4850464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,7.302917);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,2.258003);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,1.652149);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,1.218543);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.9392433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.7930705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.6541873);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.5874928);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.5312371);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,7.09944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,2.206596);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,1.679742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.213365);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.946084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.770507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.6519164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.5739681);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,6.234829);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,2.198212);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.593836);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.200756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.9344203);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.7417293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.641226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,6.65869);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,2.068766);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.578912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.182564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.9212198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.7371008);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,6.847864);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,2.119479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.554368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,1.156322);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.880742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,6.315156);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,2.129407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,1.456134);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,1.119286);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,6.503674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,1.95286);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,1.453161);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,6.494628);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,1.96893);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,5.836702);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(24,129.5554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(25,73.06195);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(26,43.3117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(27,26.72125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(28,17.08395);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(29,1.066071);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(30,0.8698739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(31,0.7264296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(32,0.6201715);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(33,0.569408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(34,0.5099009);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(35,0.4704031);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(36,0.4382881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(37,0.409815);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(38,0.3786823);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(39,0.3642697);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(40,0.3545602);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(41,0.3423367);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(42,0.3294851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(43,0.3124271);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(44,0.3122183);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(47,129.5554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(48,73.06195);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(49,43.3117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(50,26.72125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(51,17.08395);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(52,11.24419);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(53,0.7789859);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(54,0.68094);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(55,0.5796099);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(56,0.5076128);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(57,0.4645722);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(58,0.4236277);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(59,0.3980525);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(60,0.3691067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(61,0.3541356);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(62,0.3337462);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(63,0.329348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(64,0.3121105);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(65,0.2975349);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(66,0.2904851);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(67,0.278995);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(70,129.5554);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(71,72.98192);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(72,43.3117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(73,26.72125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(74,17.08395);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(75,11.24419);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(76,0.8312465);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(77,0.6868368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(78,0.5840147);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(79,0.511024);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(80,0.4571754);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(81,0.4324808);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(82,0.3973784);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(83,0.3704337);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(84,0.3505232);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(85,0.3390822);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(86,0.3237782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(87,0.3080594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(88,0.3002206);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(89,0.292479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(90,0.2754347);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(93,129.4135);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(94,72.98192);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(95,43.3117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(96,26.72125);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(97,17.08395);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(98,1.129968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(99,0.8967616);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(100,0.7208136);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(101,0.6308167);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(102,0.5432992);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(103,0.4927367);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(104,0.4551366);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(105,0.4128297);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(106,0.386436);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(107,0.3535434);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(108,0.347674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(109,0.3326828);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(110,0.3216448);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(111,0.3061163);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(112,0.2983257);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(113,0.2886637);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(116,16.68874);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(117,72.98192);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(118,43.3117);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(119,2.61072);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(120,1.808798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(121,1.289711);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(122,1.022869);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(123,0.8022456);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(124,0.6809223);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(125,0.5955168);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(126,0.5210909);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(127,0.4706819);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(128,0.4404657);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(129,0.413757);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(130,0.381436);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(131,0.3646089);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(132,0.3499159);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(133,0.3260915);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(134,0.3173192);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(135,0.3084983);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(136,0.2983658);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(140,13.03495);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(141,4.907407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(142,3.251412);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(143,2.19798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(144,1.604151);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(145,1.154278);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(146,0.9667944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(147,0.7514005);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(148,0.6406496);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(149,0.5604453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(150,0.5018423);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(151,0.4671685);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(152,0.4271053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(153,0.4060715);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(154,0.3781975);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(155,0.3604268);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(156,0.3433734);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(157,0.3335297);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(158,0.325709);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(159,0.310817);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(164,11.04976);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(165,4.123872);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(166,2.896291);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(167,1.970158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(168,1.471249);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(169,1.065355);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(170,0.8668453);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(171,0.7129408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(172,0.6107052);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(173,0.5574012);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(174,0.491901);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(175,0.4578219);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(176,0.429878);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(177,0.4018701);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(178,0.3728409);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(179,0.3663704);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(180,0.3462948);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(181,0.33796);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(182,0.3325143);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(188,10.07392);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(189,3.655919);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(190,2.474607);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(191,1.817381);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(192,1.389118);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(193,1.032212);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(194,0.8408608);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(195,0.6799311);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(196,0.6052919);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(197,0.5084411);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(198,0.4823327);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(199,0.4492133);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(200,0.4244349);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(201,0.3980182);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(202,0.3839114);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(203,0.3711295);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(204,0.35038);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(205,0.3433228);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(212,10.0574);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(213,3.322644);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(214,2.378994);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(215,1.719338);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(216,1.254843);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(217,0.9762592);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(218,0.773718);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(219,0.6694251);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(220,0.5763127);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(221,0.5253048);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(222,0.483324);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(223,0.4474067);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(224,0.418621);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(225,0.4029392);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(226,0.3785553);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(227,0.3625043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(228,0.3448113);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(236,8.746602);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(237,3.458288);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(238,2.28515);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(239,1.610721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(240,1.162038);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(241,0.9175751);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(242,0.7634639);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(243,0.6344366);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(244,0.551572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(245,0.5079595);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(246,0.4673939);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(247,0.4433094);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(248,0.4261136);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(249,0.3951403);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(250,0.3819793);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(251,0.3659723);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(260,8.394264);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(261,2.928463);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(262,2.106638);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(263,1.49791);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(264,1.144977);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(265,0.8966798);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(266,0.7243963);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(267,0.6330666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(268,0.5670611);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(269,0.5085441);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(270,0.4676486);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(271,0.448265);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(272,0.4213446);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(273,0.3966721);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(274,0.3811524);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(284,8.130564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(285,2.837666);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(286,2.011296);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(287,1.457158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(288,1.123865);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(289,0.8592582);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(290,0.7329053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(291,0.6061167);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(292,0.568732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(293,0.5116653);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(294,0.4636782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(295,0.4374267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(296,0.416485);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(297,0.400208);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(308,7.394155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(309,2.570208);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(310,1.919644);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(311,1.396222);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(312,1.092272);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(313,0.8146732);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(314,0.6959534);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(315,0.611397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(316,0.5460615);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(317,0.5094267);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(318,0.4734322);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(319,0.4363486);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(320,0.4227167);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(332,7.446387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(333,2.452493);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(334,1.741077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(335,1.352818);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(336,1.042179);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(337,0.8063099);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(338,0.6858065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(339,0.6099826);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(340,0.5525155);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(341,0.4962874);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(342,0.4744029);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(343,0.4463787);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(356,6.81932);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(357,2.633295);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(358,1.666044);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(359,1.256961);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(360,1.002802);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(361,0.8183237);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(362,0.6699926);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(363,0.5876385);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(364,0.5445016);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(365,0.4980009);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(366,0.4702015);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(380,7.377828);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(381,2.323087);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(382,1.773796);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(383,1.279122);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(384,0.9635252);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(385,0.8182105);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(386,0.650287);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(387,0.5845624);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(388,0.5262544);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(389,0.4850464);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(404,7.302917);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(405,2.258003);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(406,1.652149);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(407,1.218543);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(408,0.9392433);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(409,0.7930705);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(410,0.6541873);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(411,0.5874928);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(412,0.5312371);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(428,7.09944);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(429,2.206596);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(430,1.679742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(431,1.213365);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(432,0.946084);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(433,0.770507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(434,0.6519164);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(435,0.5739681);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(452,6.234829);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(453,2.198212);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(454,1.593836);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(455,1.200756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(456,0.9344203);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(457,0.7417293);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(458,0.641226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(476,6.65869);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(477,2.068766);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(478,1.578912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(479,1.182564);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(480,0.9212198);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(481,0.7371008);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(500,6.847864);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(501,2.119479);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(502,1.554368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(503,1.156322);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(504,0.880742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(524,6.315156);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(525,2.129407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(526,1.456134);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(527,1.119286);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(548,6.503674);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(549,1.95286);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(550,1.453161);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(572,6.494628);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(573,1.96893);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(596,5.836702);\n 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[GeV]__9->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.38645312190055847, "alphanum_fraction": 0.6000208854675293, "avg_line_length": 87.4643783569336, "blob_id": "17ba7aed7b664d9ae3a6e00a7c45704f6d8506f2", "content_id": "afb3321c2641f48b8671bb1cffa2816fe072f43e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67056, "license_type": "no_license", "max_line_length": 181, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Direct_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:27 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 152184705_m(#tilde{b}) 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,1.33229);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,1.6587);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,1.90614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,2.25386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,2.798);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,3.30286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,4.07597);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,5.06941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,6.22958);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,7.42924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,9.37381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,11.2496);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,13.9425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,17.1927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,2.85591);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,1.58729);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,1.61485);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,1.72892);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,1.74998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,2.00087);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,2.26828);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,2.4995);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,3.01248);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,3.41931);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,4.26413);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,5.24515);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,6.50702);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,7.9238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,9.8231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,11.9273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,14.4172);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,17.8766);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,4.47427);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,2.19302);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,2.27861);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,2.21943);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,2.39419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,2.60188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,2.84932);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,3.34032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,3.88267);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,4.68083);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,5.65165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,6.92008);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,8.41058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,10.2887);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,12.3527);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,14.9708);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,17.8154);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,5.85508);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.41939);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,3.00413);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,3.09231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,3.1193);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,3.40444);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,3.83224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,4.26674);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,4.88144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,5.97192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,7.17706);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,8.78397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,10.8287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,12.8065);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,15.7682);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,18.9558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,8.348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,3.93281);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,4.18965);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,4.06763);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,4.28651);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,4.52942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,4.9485);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,5.70753);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,6.66808);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,7.78359);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,9.29512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,11.4646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,13.6217);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,16.2833);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,19.9318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,10.9188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,5.67262);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,5.57175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,5.47033);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,5.71041);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,5.79404);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,6.57595);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,7.20432);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,8.7649);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,10.1365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,11.786);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,13.9567);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,17.202);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,20.6626);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,15.0992);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,7.2652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,7.39826);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,7.14644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,7.4638);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,7.28182);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,8.19463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,9.37302);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,10.8875);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,12.9902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,15.3293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,17.9318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,21.8993);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,21.1609);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,9.55894);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,9.10091);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,9.35067);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,9.39564);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,9.49891);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,10.5457);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,12.1231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,14.0373);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,16.2472);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,19.5865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,23.2611);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,27.0005);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,13.9328);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,11.6035);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,11.4895);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,11.9265);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,12.6268);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,13.3237);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,15.0374);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,17.6958);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,20.5104);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,24.2065);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,16.7332);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,16.3991);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,15.3431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,14.8425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,16.4087);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,16.5507);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,18.9912);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,21.6608);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,24.7971);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,21.458);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,20.33);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,19.1366);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,18.9187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,20.2764);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,21.3989);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,24.1409);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,27.4997);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,27.6811);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,26.7722);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,24.2865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,24.4573);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,25.0635);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,26.9722);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,33.0378);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,30.7925);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,110.72);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,38.2387);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,145.576);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,72.8405);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,78.4102);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.2691603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(160.1336);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.2691603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.3704542);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.5098684);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.7017489);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.9658402);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,1.329318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,1.829584);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,2.518118);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,3.465769);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,4.770053);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,6.565181);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,9.035877);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,12.43638);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,17.1166);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,23.55814);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,32.42385);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,44.62602);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,61.42027);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,84.53476);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,116.348);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(24,0.299067);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(25,0.344766);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(26,0.393014);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(27,0.447862);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(28,0.563237);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(29,0.672715);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(30,0.809646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(31,0.907484);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(32,1.17419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(33,1.52075);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(34,1.87395);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(35,2.36281);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(36,2.93479);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(37,3.64799);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(38,4.45081);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(39,5.6131);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(40,7.0664);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(41,8.68095);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(42,10.7311);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(43,12.9339);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(44,16.3225);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(47,0.305037);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(48,0.338933);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(49,0.373869);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(50,0.436647);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(51,0.522127);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(52,0.625795);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(53,0.723478);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(54,0.852991);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(55,1.09922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(56,1.33951);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(57,1.70615);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(58,2.10501);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(59,2.67962);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(60,3.31493);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(61,4.17499);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(62,5.19791);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(63,6.58626);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(64,7.96961);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(65,9.67958);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(66,12.0012);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(67,14.5153);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(70,0.35009);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(71,0.411094);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(72,0.443672);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(73,0.489185);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(74,0.547771);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(75,0.645386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(76,0.768143);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(77,0.856171);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(78,1.1063);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(79,1.35811);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(80,1.67788);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(81,2.16686);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(82,2.67412);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(83,3.32705);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(84,4.11951);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(85,5.20226);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(86,6.43019);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(87,7.90922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(88,9.90945);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(89,11.9644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(90,14.3047);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(93,0.471349);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(94,0.461559);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(95,0.526547);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(96,0.567046);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(97,0.610477);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(98,0.710707);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(99,0.835403);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(100,0.899808);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(101,1.20474);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(102,1.44202);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(103,1.81839);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(104,2.25415);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(105,2.75973);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(106,3.44778);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(107,4.14894);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(108,5.34022);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(109,6.68459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(110,8.17447);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(111,10.095);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(112,12.2913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(113,15.0131);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(116,0.99423);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(117,0.624574);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(118,0.67712);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(119,0.710922);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(120,0.762043);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(121,0.81002);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(122,0.958102);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(123,0.995321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(124,1.29725);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(125,1.57869);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(126,1.913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(127,2.3543);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(128,2.97485);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(129,3.72845);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(130,4.47341);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(131,5.60363);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(132,7.0021);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(133,8.32487);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(134,10.3639);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(135,12.6705);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(136,15.5837);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(140,1.37358);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(141,0.854215);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(142,0.88563);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(143,0.941941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(144,1.0172);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(145,1.06766);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(146,1.21704);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(147,1.43957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(148,1.70472);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(149,2.06985);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(150,2.51788);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(151,3.13785);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(152,3.8105);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(153,4.78196);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(154,5.79142);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(155,7.15956);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(156,8.74464);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(157,10.8456);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(158,13.4615);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(159,16.1462);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(164,1.96071);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(165,1.16439);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(166,1.25908);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(167,1.26738);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(168,1.38513);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(169,1.33229);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(170,1.6587);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(171,1.90614);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(172,2.25386);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(173,2.798);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(174,3.30286);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(175,4.07597);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(176,5.06941);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(177,6.22958);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(178,7.42924);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(179,9.37381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(180,11.2496);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(181,13.9425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(182,17.1927);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(188,2.85591);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(189,1.58729);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(190,1.61485);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(191,1.72892);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(192,1.74998);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(193,2.00087);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(194,2.26828);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(195,2.4995);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(196,3.01248);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(197,3.41931);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(198,4.26413);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(199,5.24515);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(200,6.50702);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(201,7.9238);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(202,9.8231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(203,11.9273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(204,14.4172);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(205,17.8766);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(212,4.47427);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(213,2.19302);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(214,2.27861);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(215,2.21943);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(216,2.39419);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(217,2.60188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(218,2.84932);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(219,3.34032);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(220,3.88267);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(221,4.68083);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(222,5.65165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(223,6.92008);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(224,8.41058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(225,10.2887);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(226,12.3527);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(227,14.9708);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(228,17.8154);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(236,5.85508);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(237,3.41939);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(238,3.00413);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(239,3.09231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(240,3.1193);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(241,3.40444);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(242,3.83224);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(243,4.26674);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(244,4.88144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(245,5.97192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(246,7.17706);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(247,8.78397);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(248,10.8287);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(249,12.8065);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(250,15.7682);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(251,18.9558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(260,8.348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(261,3.93281);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(262,4.18965);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(263,4.06763);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(264,4.28651);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(265,4.52942);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(266,4.9485);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(267,5.70753);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(268,6.66808);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(269,7.78359);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(270,9.29512);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(271,11.4646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(272,13.6217);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(273,16.2833);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(274,19.9318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(284,10.9188);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(285,5.67262);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(286,5.57175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(287,5.47033);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(288,5.71041);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(289,5.79404);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(290,6.57595);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(291,7.20432);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(292,8.7649);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(293,10.1365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(294,11.786);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(295,13.9567);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(296,17.202);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(297,20.6626);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(308,15.0992);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(309,7.2652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(310,7.39826);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(311,7.14644);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(312,7.4638);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(313,7.28182);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(314,8.19463);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(315,9.37302);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(316,10.8875);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(317,12.9902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(318,15.3293);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(319,17.9318);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(320,21.8993);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(332,21.1609);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(333,9.55894);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(334,9.10091);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(335,9.35067);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(336,9.39564);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(337,9.49891);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(338,10.5457);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(339,12.1231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(340,14.0373);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(341,16.2472);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(342,19.5865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(343,23.2611);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(356,27.0005);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(357,13.9328);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(358,11.6035);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(359,11.4895);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(360,11.9265);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(361,12.6268);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(362,13.3237);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(363,15.0374);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(364,17.6958);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(365,20.5104);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(366,24.2065);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(380,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(381,16.7332);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(382,16.3991);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(383,15.3431);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(384,14.8425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(385,16.4087);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(386,16.5507);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(387,18.9912);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(388,21.6608);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(389,24.7971);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(404,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(405,21.458);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(406,20.33);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(407,19.1366);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(408,18.9187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(409,20.2764);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(410,21.3989);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(411,24.1409);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(412,27.4997);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(428,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(429,27.6811);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(430,26.7722);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(431,24.2865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(476,110.72);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(477,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(478,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(479,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(480,38.2387);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(481,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(500,145.576);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(501,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(502,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(503,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(504,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(524,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(525,72.8405);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(526,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(527,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(548,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(549,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(550,78.4102);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(572,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(573,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetBinContent(596,30);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetMinimum(0.2691603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetMaximum(160.1336);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetDirectory(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitle(\"Observed R\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__11->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.453128844499588, "alphanum_fraction": 0.6799722909927368, "avg_line_length": 81.41582489013672, "blob_id": "31c7b31b9fc47194d7be54e84dfec02aaca76b1f", "content_id": "64416ce14004db20f8b2dff701ba1b6dd972532b", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 89586, "license_type": "no_license", "max_line_length": 157, "num_lines": 1087, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:25 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,0.714326);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,0.7444);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,0.771595);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,0.79879);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,1.05989);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,1.19806);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,1.33623);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,1.70772);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(37,2.02961);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(38,2.47632);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(39,2.74497);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(40,3.79602);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(41,4.42046);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(42,5.23598);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(43,6.47818);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(44,8.25656);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(45,10.0074);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,11.397);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,14.8083);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,17.7823);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(49,20.7729);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(50,27.2276);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(51,31.2672);\n 284060385_M_{sbottom} 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[GeV]->SetBinContent(866,318.365);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,909.86);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.5921946);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(1000.846);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.5921946);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.8587358);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,1.245245);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,1.805718);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,2.618454);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,3.796996);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,5.505988);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,7.984182);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,11.57779);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,16.78884);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,24.34534);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,35.30295);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,51.19247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,74.23373);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,107.6456);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,156.0959);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,226.3532);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,328.2327);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,475.9671);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,690.1955);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(29,0.714326);\n 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(216,16.5011);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(217,19.2359);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(218,24.7343);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(219,30.0913);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(220,35.7085);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(221,43.984);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(222,52.9199);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(227,3.04932);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(228,1.83276);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(229,1.85803);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(230,1.92056);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(403,8.80852);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(404,8.5999);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(405,9.13417);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(406,9.46864);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(407,10.1873);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(408,11.3708);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(409,13.6315);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(410,15.5449);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(411,17.3304);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(412,21.4724);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(413,25.3976);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(437,14.434);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(438,16.4237);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(439,20.1586);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(440,21.6767);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(441,26.7655);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(442,31.8521);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(443,38.9333);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(444,47.6038);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(445,56.5327);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(446,66.1934);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__23->SetBinContent(459,25.5382);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(77,0.6781992);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(78,0.5817517);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(79,0.5097005);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(80,0.4593932);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(81,0.4338357);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(82,0.3992256);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(83,0.3773392);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(84,0.3567548);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(85,0.3457735);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(86,0.3318513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(87,0.3157697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(88,0.306288);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(89,0.2951702);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(90,0.2828508);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(93,8.131966);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(94,4.392746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(95,3.013822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(96,2.08807);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(97,1.407469);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(98,1.089312);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(99,0.8722231);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(100,0.7067832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(101,0.6187162);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(102,0.5365891);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(103,0.4900104);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,0.4537528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,0.4121507);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,0.3908024);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,0.3562001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,0.3516486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,0.3376644);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,0.3258445);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,0.3115858);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,0.3057844);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,0.2937731);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(116,15.36814);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(117,5.962461);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,3.81801);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,2.504326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,1.740881);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,1.235791);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,0.9901696);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,0.7802865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,0.667744);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,0.5839985);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,0.5141825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,0.4666789);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,0.4404965);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,0.4144255);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,0.381364);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,0.3668322);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,0.3534719);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,0.3289927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,0.3220349);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,0.3127202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,0.3031236);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(140,11.93471);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(141,4.906311);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,3.162129);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,2.124622);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,1.541353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,1.116536);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.9369645);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.7197976);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.6249423);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.5517371);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.4932554);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.4602766);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,0.4285834);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,0.4022008);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,0.3782717);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,0.3609565);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,0.3471503);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,0.3361261);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(164,10.2585);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(165,4.069309);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,2.822903);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,1.933918);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,1.4009);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,1.022132);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.8295814);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.6891422);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.593877);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.5436251);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.485996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.4491135);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.4277833);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.4006497);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.3703657);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.3658822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.347128);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.341225);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.3351877);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,9.40868);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,3.701822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,2.437749);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,1.75436);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,1.331481);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.9983442);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.8056298);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.6580203);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.5889769);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.500192);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.4696529);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.4411153);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.4191199);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.3955501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.3829039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.3703141);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.3443573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,9.186371);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,3.1848);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,2.317016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,1.673331);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,1.212777);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.9361895);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.7413039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.645858);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.5598747);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.5139929);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.4717754);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.4296242);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.4129175);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.4007984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.3767273);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.3608641);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,7.86344);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,3.346807);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,2.232927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,1.54276);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,1.119481);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.8840556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.7342294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.6092637);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.539241);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.4925991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.4577504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.4366933);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.4191671);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.3908437);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,7.515729);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,2.861419);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,2.034698);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,1.466252);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,1.089245);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.8540854);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.7046546);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.6130153);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.5499254);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.4972592);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.4570268);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.4398411);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.4127274);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.3930687);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.3746899);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,6.881471);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,2.791321);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,1.958779);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,1.405807);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,1.075061);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.8278436);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.7083898);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.5877978);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.5524226);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.4968333);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.4500103);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,6.901047);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,2.50919);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,1.878155);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,1.358612);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,1.049005);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.7841683);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6693205);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.5876195);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.5265685);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.494373);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.4259925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.4152696);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,6.702404);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,2.450349);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,1.711466);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,1.296066);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.9997504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.7845834);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.6547101);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.5860314);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.5295095);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.4608231);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.4323756);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,5.091);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,2.583262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,1.640218);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,1.222292);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.9647633);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.788898);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.6322487);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.5262166);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.2122);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,3.579);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,2.313493);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,1.710454);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,1.243026);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.9240444);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.7785265);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.6269922);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.2869143);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,2.5674);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,1.8558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,1.3563);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,1.002);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.744);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.570418);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,1.8558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,2.196749);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,1.002);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.744);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,1.3563);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,1.002);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.557807);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.8990226);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.7183267);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.6179533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,5.680037);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,2.044512);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.518209);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.8850873);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.7106371);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,5.818204);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,0.5559);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,2.073981);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,0.4188);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,1.413621);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(10);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.3981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.5011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.6309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.7943282);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.258925);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,1.584893);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.995262);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,2.511886);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,3.162278);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,3.981072);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,5.011872);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,6.309573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,7.943282);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(24,5.056256);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(25,3.270627);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(26,2.295254);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(27,1.684728);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(28,1.343342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(29,1.069854);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(30,0.8660634);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(31,0.7292668);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(32,0.6268798);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(33,0.5757069);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(34,0.5181552);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(35,0.4790766);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(36,0.4598624);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(37,0.4175618);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(38,0.3883521);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(39,0.3738763);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(40,0.3633026);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(41,0.3514733);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(42,0.3390116);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(43,0.3219562);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(44,0.3227425);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(47,5.323092);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(48,3.327124);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(49,2.186996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(50,1.607882);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(51,1.239069);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(52,0.9766533);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(53,0.7678109);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(54,0.6754944);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(55,0.5806599);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(56,0.5113145);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(57,0.4689371);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(58,0.4309223);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(59,0.4035516);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(60,0.3761026);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(61,0.3609553);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(62,0.3413914);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(63,0.3365558);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(64,0.3187697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(65,0.3043461);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(66,0.2969166);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(67,0.2864656);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(70,5.273755);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(71,3.918721);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(72,2.58268);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(73,1.766701);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(74,1.309867);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(75,1.00139);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(76,0.8221543);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(77,0.6781992);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(78,0.5817517);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(79,0.5097005);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(80,0.4593932);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(81,0.4338357);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(82,0.3992256);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(83,0.3773392);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(84,0.3567548);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(85,0.3457735);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(86,0.3318513);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(87,0.3157697);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(88,0.306288);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(89,0.2951702);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(90,0.2828508);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(93,8.131966);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(94,4.392746);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(95,3.013822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(96,2.08807);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(97,1.407469);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(98,1.089312);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(99,0.8722231);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(100,0.7067832);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(101,0.6187162);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(102,0.5365891);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(103,0.4900104);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(104,0.4537528);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(105,0.4121507);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(106,0.3908024);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(107,0.3562001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(108,0.3516486);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(109,0.3376644);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(110,0.3258445);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(111,0.3115858);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(112,0.3057844);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(113,0.2937731);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(116,15.36814);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(117,5.962461);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(118,3.81801);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(119,2.504326);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(120,1.740881);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(121,1.235791);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(122,0.9901696);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(123,0.7802865);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(124,0.667744);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(125,0.5839985);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(126,0.5141825);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(127,0.4666789);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(128,0.4404965);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(129,0.4144255);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(130,0.381364);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(131,0.3668322);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(132,0.3534719);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(133,0.3289927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(134,0.3220349);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(135,0.3127202);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(136,0.3031236);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(140,11.93471);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(141,4.906311);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(142,3.162129);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(143,2.124622);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(144,1.541353);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(145,1.116536);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(146,0.9369645);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(147,0.7197976);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(148,0.6249423);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(149,0.5517371);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(150,0.4932554);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(151,0.4602766);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(152,0.4285834);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(153,0.4022008);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(154,0.3782717);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(155,0.3609565);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(156,0.3471503);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(157,0.3361261);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(158,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(159,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(164,10.2585);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(165,4.069309);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(166,2.822903);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(167,1.933918);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(168,1.4009);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(169,1.022132);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(170,0.8295814);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(171,0.6891422);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(172,0.593877);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(173,0.5436251);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(174,0.485996);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(175,0.4491135);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(176,0.4277833);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(177,0.4006497);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(178,0.3703657);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(179,0.3658822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(180,0.347128);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(181,0.341225);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(182,0.3351877);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(188,9.40868);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(189,3.701822);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(190,2.437749);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(191,1.75436);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(192,1.331481);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(193,0.9983442);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(194,0.8056298);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(195,0.6580203);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(196,0.5889769);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(197,0.500192);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(198,0.4696529);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(199,0.4411153);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(200,0.4191199);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(201,0.3955501);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(202,0.3829039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(203,0.3703141);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(204,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(205,0.3443573);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(212,9.186371);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(213,3.1848);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(214,2.317016);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(215,1.673331);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(216,1.212777);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(217,0.9361895);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(218,0.7413039);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(219,0.645858);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(220,0.5598747);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(221,0.5139929);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(222,0.4717754);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(223,0.4296242);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(224,0.4129175);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(225,0.4007984);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(226,0.3767273);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(227,0.3608641);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(228,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(236,7.86344);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(237,3.346807);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(238,2.232927);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(239,1.54276);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(240,1.119481);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(241,0.8840556);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(242,0.7342294);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(243,0.6092637);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(244,0.539241);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(245,0.4925991);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(246,0.4577504);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(247,0.4366933);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(248,0.4191671);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(249,0.3908437);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(250,0.3183);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(251,0.24342);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__7->SetBinContent(260,7.515729);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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"is_vendor": false, "language": "C", "length_bytes": 90884, "license_type": "no_license", "max_line_length": 155, "num_lines": 1089, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10/Fixed_Edge_sbottom_neutralino2_ObsXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 11:16:28 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n 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2} [GeV]->SetBinContent(528,0.3454984);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(529,0.3171743);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(530,0.3025459);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(546,5.120589);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(547,1.769673);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,1.197772);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,1.107483);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,0.857052);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(551,0.6370744);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(552,0.5656768);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(553,0.4943449);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(554,0.460198);\n 484096097_M_{sbottom} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,0.4462144);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,0.3904399);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,0.3397135);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,0.3299647);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,4.050524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,1.722616);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,1.184547);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,0.9600519);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,0.7572832);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,0.665414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,0.536432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,0.4483792);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,0.4156532);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.3864816);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.3518426);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,4.574111);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,1.45876);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,1.205462);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,0.9813312);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.7247484);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.623942);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.5199872);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.4573448);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.4073532);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.3859776);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,4.331276);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,1.343066);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,1.280032);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.8907501);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.790734);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.6175616);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.534021);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.45723);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.4044107);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,4.050661);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,1.417024);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,1.269441);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,0.951594);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.6816576);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.5789714);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.5018821);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.4373427);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,3.822048);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,1.442141);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,1.24582);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.9187552);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.7560361);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.5794168);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.5215428);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,3.649726);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,1.377826);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,1.052906);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.8630996);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.7210976);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.5997589);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,4.12672);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,1.320235);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,1.082912);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.8833601);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.6779749);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,3.080064);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,1.302334);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.029079);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.811357);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,3.774453);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,1.368782);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,1.065257);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,4.08549);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,1.342286);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,3.771246);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7 = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(29,7.017118);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(30,4.194153);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(31,3.108364);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(32,1.889883);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(33,1.6569);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(34,1.323283);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(35,0.9756326);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(36,0.873065);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(37,0.7357311);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(38,0.6498422);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(39,0.5236897);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(40,0.5363849);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(41,0.4619021);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(42,0.4153797);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(43,0.3885443);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(44,0.3770127);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(45,0.3504828);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(46,0.3104855);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(47,0.3138058);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(48,0.2951664);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(49,0.2731668);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(50,0.282678);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(51,0.2594576);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(52,0.2559012);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(53,0.2386115);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(54,0.2517474);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(57,7.258779);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(58,4.187219);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(59,2.698447);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(60,1.866054);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(61,1.528931);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(62,1.096125);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(63,0.9263065);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(64,0.7397966);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(65,0.651317);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(66,0.5509974);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(67,0.4774432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(68,0.4318669);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(69,0.3969868);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(70,0.3723026);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(71,0.3432707);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(72,0.325684);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(73,0.3020036);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(74,0.2823744);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(75,0.2773015);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(76,0.2584397);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(77,0.2460955);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(78,0.235162);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(79,0.2370976);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(80,0.2214232);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(81,0.2265844);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(82,0.2211296);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(85,6.465985);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(86,3.981932);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(87,3.084132);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(88,1.988358);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(89,1.350563);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(90,1.125733);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(91,0.8781353);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(92,0.7490571);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(93,0.5928208);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(94,0.5118216);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(95,0.4611408);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(96,0.4030654);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(97,0.3887572);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(98,0.3577492);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(99,0.3173354);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(100,0.3043657);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(101,0.2857273);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(102,0.2707084);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(103,0.2611651);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(104,0.24504);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(105,0.2411034);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(106,0.240294);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(107,0.2268016);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(108,0.2232304);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(109,0.2139715);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(110,0.2068667);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(113,8.386904);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(114,4.938203);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(115,3.523715);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(116,1.874975);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(129,0.2925858);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(130,0.26734);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(131,0.2704114);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(132,0.253321);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(133,0.2418232);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(134,0.235108);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(135,0.226056);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(136,0.225519);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(137,0.2171237);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(138,0.2082692);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(141,10.24385);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(154,0.3369978);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(155,0.3426744);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(156,0.3113564);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(157,0.2912374);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(158,0.272444);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(159,0.2617284);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(160,0.2476509);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(161,0.240696);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(162,0.238006);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(163,0.2365232);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(164,0.2254098);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(179,0.4935174);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(180,0.4469337);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(181,0.3885948);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(182,0.3632786);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(183,0.3351704);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(184,0.3222455);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(185,0.3002226);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(186,0.2877194);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(187,0.265901);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(188,0.265728);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(189,0.2532174);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(205,0.7365946);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(206,0.6324065);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(207,0.5601218);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(208,0.4640782);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(209,0.3914652);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(210,0.386989);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(211,0.351625);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(212,0.3248743);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(213,0.3052268);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(214,0.2960134);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(215,0.2749321);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(232,1.122408);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(233,0.8338005);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(234,0.732326);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(235,0.5719162);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(236,0.4995054);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(237,0.4620361);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(238,0.3970166);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(239,0.3631438);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(240,0.3398393);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(241,0.3317655);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(242,0.2961047);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(260,1.280379);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(261,1.026268);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(262,0.8168987);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(263,0.6454499);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(264,0.5082932);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(265,0.4712381);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(266,0.4063267);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(267,0.3976167);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(268,0.3737792);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(269,0.3424557);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(270,0.3132218);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(289,1.145159);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(290,0.9556544);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(291,0.7777717);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(292,0.6016483);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(293,0.568132);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(294,0.4486021);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(295,0.4145956);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(296,0.3849412);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(297,0.345264);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(298,0.3344481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(299,0.3044373);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(497,0.3836518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(498,0.388196);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(499,0.358696);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(500,0.3152127);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(501,0.3111881);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(502,0.2967876);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(517,4.619468);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(518,3.114839);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(519,1.277032);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(520,1.162884);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(521,0.8237017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(549,1.107483);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(550,0.857052);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(551,0.6370744);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(552,0.5656768);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(553,0.4943449);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(554,0.460198);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(555,0.3948832);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(556,0.357472);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(557,0.3261068);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(558,0.3300721);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(575,4.799837);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.3844001293182373, "alphanum_fraction": 0.6019632816314697, "avg_line_length": 88.1015853881836, "blob_id": "dccff75a48769ab7f0366b13e1d461f890c58a7f", "content_id": "7cd9bdca202c080c365d82207078a6fff9219fb7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 67539, "license_type": "no_license", "max_line_length": 179, "num_lines": 758, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Direct_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:27 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n 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[GeV]->SetBinContent(341,1.740933);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,1.661504);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,1.561769);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,25.49448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,9.828552);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,6.051414);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,4.488723);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,3.553881);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,2.882752);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,2.352857);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,2.062136);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,1.906761);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,1.74596);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,1.645273);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,27.73127);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,8.689645);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,6.454898);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,4.567994);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,3.407214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,2.883327);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,2.285982);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,2.054603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,1.847686);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,1.696828);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,27.41932);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,8.342311);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,5.985454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,4.364657);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,3.336309);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,2.785915);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,2.296691);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,2.060382);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,1.860027);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,26.70351);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,8.184115);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,6.12064);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,4.315274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,3.348388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,2.711498);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,2.286477);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,2.014544);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,23.2021);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,8.119884);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,5.782455);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,4.300951);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,3.306728);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,2.615058);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,2.248388);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,24.97247);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,7.67126);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,5.7804);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,4.219684);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,3.255484);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.583993);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,25.57572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,7.831147);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,5.637648);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,4.143052);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,3.107218);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,23.63063);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,7.850558);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,5.288364);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,4.007304);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,24.34016);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,7.220321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,5.259295);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,24.36738);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,7.257123);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,21.71209);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.1);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1303321);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1698646);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.2213882);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.28854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3760603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.4901274);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6387935);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.8325532);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.085084);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.414214);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,1.843175);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,2.402249);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,3.130902);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,4.080572);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,5.318296);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,6.931448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,9.033905);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,11.77408);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,15.34541);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9 = new TH2F(\"152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9\",\"\",21,187.5,712.5,25,87.5,712.5);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(24,129.4135);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(25,72.98192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(26,43.3117);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(27,6.036624);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(28,4.787695);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(29,3.787298);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(30,3.075801);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(31,2.565108);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(32,2.185375);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(33,2.003818);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(34,1.793046);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(35,1.657983);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(36,1.542123);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(37,1.442119);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(38,1.332006);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(39,1.281331);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(40,1.243187);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(41,1.203444);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(42,1.157751);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(43,1.097559);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(44,1.096603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(47,129.4135);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(48,72.98192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(49,43.3117);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(50,5.80086);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(51,4.474307);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(52,3.525545);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(53,2.748605);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(54,2.400278);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(55,2.043501);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(56,1.786813);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(57,1.635343);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(58,1.487681);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(59,1.400106);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(60,1.300597);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(61,1.242228);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(62,1.170068);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(63,1.157074);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(64,1.096356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(65,1.042801);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(66,1.017598);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(67,0.9797011);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(70,129.4135);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(71,72.98192);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(72,9.592437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(73,6.545448);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(74,4.709348);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(75,3.635963);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(76,2.944014);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(77,2.41825);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(78,2.058734);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(79,1.79311);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(80,1.606325);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(81,1.524);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(82,1.393365);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(83,1.303797);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(84,1.231628);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(85,1.190891);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(86,1.140225);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(87,1.077901);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(88,1.052142);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(89,1.024543);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(90,0.9640784);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(93,30.23584);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(94,16.75663);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(95,11.38873);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(96,7.613712);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(97,5.230527);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(98,3.994123);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(99,3.171991);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(100,2.538432);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(101,2.227772);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(102,1.908304);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(103,1.737949);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(104,1.598102);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(105,1.450815);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(106,1.359844);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(107,1.239771);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(108,1.219289);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(109,1.16989);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(110,1.126459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(111,1.074815);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(112,1.049509);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(113,1.011503);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(116,63.85845);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(117,22.60653);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(118,14.54518);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(119,9.447876);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(120,6.501966);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(121,4.589934);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(122,3.62681);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(123,2.828218);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(124,2.39681);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(125,2.094608);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(126,1.836573);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(127,1.64913);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(128,1.548137);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(129,1.457107);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(130,1.340622);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(131,1.28045);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(132,1.228381);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(133,1.142814);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(134,1.110403);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(135,1.081371);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(136,1.045216);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(140,49.70599);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(141,18.44865);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(142,11.91874);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(143,7.994821);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(144,5.732794);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(145,4.091096);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(146,3.427726);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(147,2.645869);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(148,2.256246);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(149,1.976921);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(150,1.761363);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(151,1.639445);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(152,1.495356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(153,1.42504);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(154,1.327117);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(155,1.264314);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(156,1.204521);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(157,1.169456);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(158,1.141409);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(159,1.089093);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(164,42.11345);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(165,15.4885);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(166,10.6731);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(167,7.141331);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(168,5.255977);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(169,3.773671);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(170,3.070758);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(171,2.512349);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(172,2.147236);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(173,1.956899);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(174,1.729301);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(175,1.603782);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(176,1.506823);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(177,1.411);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(178,1.30531);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(179,1.280564);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(180,1.213444);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(181,1.180165);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(182,1.16258);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(188,37.92604);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(189,13.61112);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(190,9.04703);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(191,6.555297);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(192,4.940676);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(193,3.651836);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(194,2.966038);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(195,2.382414);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(196,2.124691);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(197,1.786336);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(198,1.687501);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(199,1.5762);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(200,1.48819);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(201,1.390497);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(202,1.341576);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(203,1.29608);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(204,1.224437);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(205,1.199632);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(212,37.97199);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(213,12.31811);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(214,8.694952);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(215,6.216631);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(216,4.450222);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(217,3.449773);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(218,2.720957);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(219,2.354037);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(220,2.025728);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(221,1.843231);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(222,1.693603);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(223,1.56676);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(224,1.465715);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(225,1.408357);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(226,1.325034);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(227,1.270535);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(228,1.208503);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(236,32.66874);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(237,12.87428);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(238,8.339198);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(239,5.772789);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(240,4.116663);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(241,3.242712);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(242,2.679792);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(243,2.228876);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(244,1.933858);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(245,1.778347);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(246,1.643001);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(247,1.557903);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(248,1.493157);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(249,1.379316);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(250,1.336843);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(251,1.281332);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(260,31.51579);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(261,10.90459);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(262,7.671663);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(263,5.384186);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(264,4.078069);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(265,3.174454);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(266,2.552161);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(267,2.220573);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(268,1.989289);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(269,1.777869);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(270,1.633854);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(271,1.574356);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(272,1.473208);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(273,1.391888);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(274,1.332954);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(284,30.57126);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(285,10.50144);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(286,7.335917);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(287,5.232056);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(288,3.991246);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(289,3.025759);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(290,2.587611);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(291,2.127064);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(292,1.990652);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(293,1.786734);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(294,1.623337);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(295,1.52735);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(296,1.458145);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(297,1.399937);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(308,27.63425);\n 152184705_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(309,9.548473);\n 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c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4485568702220917, "alphanum_fraction": 0.6833474040031433, "avg_line_length": 82.3586654663086, "blob_id": "835c14942754ab10b0af4a8448ab5ca4218b5ac8", "content_id": "ebc50492d5a99545e94cdb51827717cf786e72f4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 89944, "license_type": "no_license", "max_line_length": 155, "num_lines": 1079, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:38 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n 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[GeV]->SetBinContent(670,0.4037326);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,4.022933);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,1.412022);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,1.268804);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,1.012009);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.678816);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.5788622);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.5019538);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.4378498);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,2.453722);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,1.244398);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.9165936);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.7542962);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.5777745);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.520264);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,3.638641);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,1.371108);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,1.049715);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.8627986);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.717705);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.6026783);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,4.099674);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,2.319207);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,1.079974);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.8825017);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.6769086);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,3.047464);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,1.301224);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.089533);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.8107953);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,3.758051);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,1.363609);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,1.062355);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,2.407637);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,3.752919);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new 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[GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS} #sqrt{s} = 8 TeV\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(29,6.9217);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(30,4.1975);\n 416758881_M_{sbottom} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(54,0.2507136);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(57,7.1231);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(58,4.1745);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(59,2.693592);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(60,1.844922);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(61,1.513616);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(62,1.08814);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(63,0.92637);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(64,0.740012);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(65,0.6502626);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(66,0.5493852);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(79,0.2427032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(80,0.2391734);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(81,0.2258865);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(82,0.2284743);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(85,6.3935);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(86,3.9514);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(87,3.026532);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(88,1.956484);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(89,1.340336);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(90,1.104264);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(91,0.876456);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(104,0.2454752);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(105,0.2408301);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(106,0.240032);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(107,0.2264912);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(108,0.2225446);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(109,0.2137443);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(110,0.206235);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(113,8.27925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(114,4.83345);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(115,2.8998);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(116,1.873965);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__9->SetBinContent(721,2.453722);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(722,1.244398);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(723,0.9165936);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(724,0.7542962);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(725,0.5777745);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(726,0.520264);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(749,3.638641);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(750,1.371108);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(751,1.049715);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(752,0.8627986);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(753,0.717705);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(754,0.6026783);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(778,4.099674);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(779,2.319207);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(780,1.079974);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(781,0.8825017);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(782,0.6769086);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(807,3.047464);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(808,1.301224);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(809,1.089533);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(810,0.8107953);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(836,3.758051);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(837,1.363609);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(838,1.062355);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(866,2.407637);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetBinContent(894,3.752919);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetMinimum(0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetMaximum(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetDirectory(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__9->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4874601662158966, "alphanum_fraction": 0.6811694502830505, "avg_line_length": 44.10625076293945, "blob_id": "64a0b8b32190af7b0c05557b8ac2cc69646f7ea1", "content_id": "735e82293dcc5f8283d5992ad32aa9cbe21e683e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 7217, "license_type": "no_license", "max_line_length": 149, "num_lines": 160, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:39 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(63.51351,-35.67568,766.2162,802.1622);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 416758882_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(18);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,370,100);\n graph->SetPoint(1,370,120);\n graph->SetPoint(2,369.7671999,139.7671999);\n graph->SetPoint(3,368.45405,158.45405);\n graph->SetPoint(4,365.1100555,175.1100555);\n graph->SetPoint(5,359.7671999,189.7671999);\n graph->SetPoint(6,353.1111944,203.1111944);\n graph->SetPoint(7,344.8772554,214.8772554);\n graph->SetPoint(8,333.5641054,223.5641055);\n graph->SetPoint(9,318.2212499,228.2212499);\n graph->SetPoint(10,299.7671999,229.7671999);\n graph->SetPoint(11,280,230.0412485);\n graph->SetPoint(12,260.1915517,229.9586205);\n graph->SetPoint(13,241.5460812,228.6223311);\n graph->SetPoint(14,225.8433928,224.1096918);\n graph->SetPoint(15,214.8438308,215.7438056);\n graph->SetPoint(16,207.4770804,205.7151152);\n graph->SetPoint(17,200,198.5570334);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Observed limit\",100,183,387);\n Graph_Graph1->SetMinimum(86.99588);\n Graph_Graph1->SetMaximum(243.0454);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n \n graph = new TGraph(27);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,430,100);\n graph->SetPoint(1,430,120);\n graph->SetPoint(2,429.7671999,139.7671999);\n graph->SetPoint(3,428.45405,158.45405);\n graph->SetPoint(4,425.1100555,175.1100555);\n graph->SetPoint(5,420,190);\n graph->SetPoint(6,414.8899446,204.8899446);\n graph->SetPoint(7,411.31315,221.3131499);\n graph->SetPoint(8,408.45405,238.45405);\n graph->SetPoint(9,403.5641055,253.5641054);\n graph->SetPoint(10,394.8772554,264.8772554);\n graph->SetPoint(11,383.1111944,273.1111944);\n graph->SetPoint(12,369.7671999,279.7671999);\n graph->SetPoint(13,355.3428556,284.8772554);\n graph->SetPoint(14,340,286.9081);\n graph->SetPoint(15,324.6571444,284.8772554);\n graph->SetPoint(16,310.1915517,279.7671999);\n graph->SetPoint(17,296.464585,273.385243);\n graph->SetPoint(18,282.9429133,266.8886744);\n graph->SetPoint(19,269.4544136,260.5925018);\n graph->SetPoint(20,256.0635037,254.2906621);\n graph->SetPoint(21,242.9430445,247.5200451);\n graph->SetPoint(22,230.7676947,239.4476329);\n graph->SetPoint(23,220.5523671,229.2323053);\n graph->SetPoint(24,213.1064603,217.331004);\n graph->SetPoint(25,207.2030319,205.9479153);\n graph->SetPoint(26,200,198.5570334);\n \n TH1F Graph_Graph2 = new TH1F(\"Graph_Graph2\",\"Expected limit\",100,177,453);\n Graph_Graph2->SetMinimum(81.30919);\n Graph_Graph2->SetMaximum(305.5989);\n Graph_Graph2->SetDirectory(0);\n Graph_Graph2->SetStats(0);\n Graph_Graph2->SetLineStyle(0);\n Graph_Graph2->GetXaxis()->SetNdivisions(505);\n Graph_Graph2->GetXaxis()->SetLabelFont(42);\n Graph_Graph2->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetXaxis()->SetTitleSize(32);\n Graph_Graph2->GetXaxis()->SetTitleFont(43);\n Graph_Graph2->GetYaxis()->SetLabelFont(42);\n Graph_Graph2->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetYaxis()->SetTitleSize(32);\n Graph_Graph2->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph2->GetYaxis()->SetTitleFont(43);\n Graph_Graph2->GetZaxis()->SetLabelFont(42);\n Graph_Graph2->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph2->GetZaxis()->SetTitleSize(32);\n Graph_Graph2->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph2->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph2);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.5084485411643982, "alphanum_fraction": 0.6772657632827759, "avg_line_length": 44.20833206176758, "blob_id": "368a72650d6666124202f2f75e07671f512c11ea", "content_id": "de4e18540b029491bbdc67d22ef6406304e17361", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 6510, "license_type": "no_license", "max_line_length": 149, "num_lines": 144, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:25 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(63.51351,-35.67568,766.2162,802.1622);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060386_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(11);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,290,100);\n graph->SetPoint(1,289.7671999,119.7671999);\n graph->SetPoint(2,288.2212499,138.2212499);\n graph->SetPoint(3,283.5641055,153.5641054);\n graph->SetPoint(4,274.8772554,164.8772554);\n graph->SetPoint(5,263.3439945,172.8783943);\n graph->SetPoint(6,251.3131499,178.2212499);\n graph->SetPoint(7,240,180.2201109);\n graph->SetPoint(8,229.4983968,178.45405);\n graph->SetPoint(9,217.3602594,174.6571445);\n graph->SetPoint(10,200,171.7787502);\n \n TH1F Graph_Graph3 = new TH1F(\"Graph_Graph3\",\"Observed limit\",100,191,299);\n Graph_Graph3->SetMinimum(91.97799);\n Graph_Graph3->SetMaximum(188.2421);\n Graph_Graph3->SetDirectory(0);\n Graph_Graph3->SetStats(0);\n Graph_Graph3->SetLineStyle(0);\n Graph_Graph3->GetXaxis()->SetNdivisions(505);\n Graph_Graph3->GetXaxis()->SetLabelFont(42);\n Graph_Graph3->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph3->GetXaxis()->SetTitleSize(32);\n Graph_Graph3->GetXaxis()->SetTitleFont(43);\n Graph_Graph3->GetYaxis()->SetLabelFont(42);\n Graph_Graph3->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph3->GetYaxis()->SetTitleSize(32);\n Graph_Graph3->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph3->GetYaxis()->SetTitleFont(43);\n Graph_Graph3->GetZaxis()->SetLabelFont(42);\n Graph_Graph3->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph3->GetZaxis()->SetTitleSize(32);\n Graph_Graph3->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph3->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph3);\n \n graph->Draw(\"l\");\n \n graph = new TGraph(18);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,351.7787502,100);\n graph->SetPoint(1,354.8899446,117.5930595);\n graph->SetPoint(2,360,131.0443468);\n graph->SetPoint(3,364.8772554,144.6571444);\n graph->SetPoint(4,366.9081,160);\n graph->SetPoint(5,364.6444553,175.1100555);\n graph->SetPoint(6,358.45405,188.45405);\n graph->SetPoint(7,349.7671999,199.7671999);\n graph->SetPoint(8,339.7671999,209.7671999);\n graph->SetPoint(9,328.45405,218.45405);\n graph->SetPoint(10,314.8772554,224.8772554);\n graph->SetPoint(11,298.45405,228.45405);\n graph->SetPoint(12,279.7671999,229.8084484);\n graph->SetPoint(13,260.1915517,229.9586205);\n graph->SetPoint(14,241.3545295,228.8963796);\n graph->SetPoint(15,224.2012774,225.8470623);\n graph->SetPoint(16,210.0229059,221.0348314);\n graph->SetPoint(17,200,216.9697038);\n \n TH1F Graph_Graph4 = new TH1F(\"Graph_Graph4\",\"Expected limit\",100,183.3092,383.5989);\n Graph_Graph4->SetMinimum(87.00414);\n Graph_Graph4->SetMaximum(242.9545);\n Graph_Graph4->SetDirectory(0);\n Graph_Graph4->SetStats(0);\n Graph_Graph4->SetLineStyle(0);\n Graph_Graph4->GetXaxis()->SetNdivisions(505);\n Graph_Graph4->GetXaxis()->SetLabelFont(42);\n Graph_Graph4->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph4->GetXaxis()->SetTitleSize(32);\n Graph_Graph4->GetXaxis()->SetTitleFont(43);\n Graph_Graph4->GetYaxis()->SetLabelFont(42);\n Graph_Graph4->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph4->GetYaxis()->SetTitleSize(32);\n Graph_Graph4->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph4->GetYaxis()->SetTitleFont(43);\n Graph_Graph4->GetZaxis()->SetLabelFont(42);\n Graph_Graph4->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph4->GetZaxis()->SetTitleSize(32);\n Graph_Graph4->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph4->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph4);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.5700684189796448, "alphanum_fraction": 0.5986313819885254, "avg_line_length": 28.208696365356445, "blob_id": "94d6f27ccc2c1e44820a4fb0b3fab40bdbd927ba", "content_id": "b05e3bebdaef79bebc73fa15980286d039168f7a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3361, "license_type": "no_license", "max_line_length": 188, "num_lines": 115, "path": "/LimitTools/calculateLimits.py", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "#! /usr/bin/env python\n\nimport ROOT\n\nfrom messageLogger import messageLogger as log\nfrom optparse import OptionParser\nimport os\n\n\ndef loadPickles(path):\n\tfrom glob import glob\n\timport pickle\n\tresult = {}\n\tfor pklPath in glob(path):\n\t\tpklFile = open(pklPath, \"r\")\n\t\tresult.update(pickle.load(pklFile))\n\treturn result\n\t\n\t\t\t \ndef writeDataCards():\n\t#~ from ROOT import TCanvas, TPad, TH1F, TH2F, TH1I, THStack, TLegend, TMath, TF1\n\timport pickle\n\n\tlumi = 19400.\n\tprintLumi = \"19.4\"\n\tBR = \"10\"\n\tbaseDir = \"/user/schomakers/LimitTools/SimplifiedModelLimits/\"\n\t\n\t\n\t#~ regions = [\"signalCentral\"]\n\tregions = [\"signalCentral_mll_20_70\"]\n\t#~ regions = [\"signalCentral\",\"signalCentral_100_met_cut\",\"signalCentral_150_met_cut\",\"signalCentral_2_jet_cut\",\"signalCentral_3_jet_cut\"]\n\t\n\t#set cmssw environment\n\tos.chdir(\"%s\"%(baseDir))\n\tos.system (\"mycmssw611\")\n\t\n\tfor region in regions:\n\t\n\t\tstep_size = 20\n\t\tm_b_min = 200\n\t\tm_b_max = 700\n\t\tm_n_min = 100\n\t\tm_n_max = 700\n\t\t\n\t\tPickles = {}\n\t\t\n\t\tm_neutr_1_fix = False\n\t\tm_neutralino_1 = \"200\"\n\t\t\n\t\t\t\n\t\trun = 0\n\t\ti = 0\n\t\twhile m_b_min + istep_size <= m_b_max:\n\t\t\tm_b = m_b_min + istep_size\n\t\t\tM_SBOTTOM = \"m_b_\"+str(m_b_min + istep_size)\n\t\t\tm_sbottom = str(m_b_min + istep_size)\n\t\t\tj = 0\n\t\t\t\n\t\t\twhile m_n_min + jstep_size <= m_n_max:\n\t\t\t\t#~ print i\n\t\t\t\tm_n = m_n_min + jstep_size\n\t\t\t\tm_neutralino_2 = str(m_n_min + jstep_size)\n\t\t\t\t#~ if m_b >= m_n:\n\t\t\t\tif m_b >= m_n and not (m_b == 320 and m_n == 260) and not (m_b == 460 and m_n == 440) and not (m_b == 480 and m_n == 160):\n\t\t\t\t\tprint \"m_b: \"+m_sbottom\n\t\t\t\t\tprint \"m_n: \"+m_neutralino_2\n\t\t\t\t\t\n\t\t\t\t\tif m_neutr_1_fix == False:\n\t\t\t\t\t\tm_neutralino_1 = str(m_n_min + jstep_size - 70)\n\t\t\t\t\t\n\t\t\t\t\tName= \"SF-OF_counts_SUSY_SimplifiedModel_Madgraph_FastSim_Dilepton_Edge_BR_%s_m_n_1_%s_m_b_%s_m_n_2_%s_8TeV_Scan_%s\"%(BR,m_neutralino_1,m_sbottom,m_neutralino_2,region)\n\t\t\t\t\t\n\t\t\t\t\tos.system (\"./../limit_V2 DataCards/%s.txt\"%(Name))\n\t\t\t\t\tos.system (\"rm roostats-\")\n\t\t\t\t\tos.system (\"rm .root\")\n\t\t\t\t\tos.system (\"rm .log\")\n\t\t\t\t\tos.system (\"mv %s.txt.result.txt results/%s.result.txt\"%(Name,Name))\n\t\t\t\t\tos.system (\"rm %s.\"%Name)\n\t\t\n\n\t\n\t\t\t\tj += 1\t\t\n\t\t\ti += 1\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\n\n# This method just waits for a button to be pressed\ndef waitForInput():\n raw_input(\"Press any key to continue!\")\n return\n\n# entry point\n#-------------\nif (__name__ == \"__main__\"):\n # use option parser to allow verbose mode\n parser = OptionParser()\n parser.add_option(\"-v\", \"--verbose\", dest=\"verbose\", action=\"store_true\", default=False,\n help=\"talk about everything\")\n #~ parser.add_option(\"-b\", \"--base_path\", dest=\"base_path\", default=\"/user/schomakers/AnalysisData/PAT/Histos/sw532v0474/cutsV22DileptonTriggerSignal/TTJets/processedTrees_Simulation\",\n #~ help=\"path to the directory containing simulated events\")\n #~ parser.add_option(\"-n\", \"--nEvents\", dest=\"nEvents\", default=\"-1\",\n #~ help=\"number of events to read (default = -1 = all). use smaller numbers for tests\")\n (opts, args) = parser.parse_args()\n if (opts.verbose):\n # print out all output\n log.outputLevel = 5\n else:\n # ignore output with \"debug\" level\n log.outputLevel = 4\n\n # start\n #~ plot(opts.base_path, int(opts.nEvents), opts.observable)\n writeDataCards()\n \n" }, { "alpha_fraction": 0.4457096457481384, "alphanum_fraction": 0.6854033470153809, "avg_line_length": 82.86200714111328, "blob_id": "2b5c6d3f11373522bb18f1c29a07f4e1d6307a0f", "content_id": "0ab709a2926a1a02fbe0397b0cdf62615d54c904", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 91158, "license_type": "no_license", "max_line_length": 157, "num_lines": 1087, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_ExpXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:24 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,7.095873);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,4.403269);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,3.172252);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,1.941234);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,1.737819);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,1.38068);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,1.02354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,0.9264842);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(37,0.7745517);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(38,0.6734228);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(39,0.5567729);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(40,0.574321);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(41,0.4835683);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(42,0.427583);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(43,0.4100484);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(44,0.4123248);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(45,0.3665337);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,0.3318525);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,0.3285277);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,0.3052227);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(49,0.2844241);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(50,0.307228);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(51,0.2744768);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(52,0.2707881);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(53,0.2468066);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(54,0.2437979);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(57,7.974433);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(58,4.251263);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(59,2.935979);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(60,1.924039);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(61,1.572431);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(62,1.184629);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(63,0.9899709);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(64,0.7853335);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(65,0.6730769);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(66,0.5827914);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(67,0.5111226);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(68,0.4511598);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(69,0.4173335);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(70,0.3880768);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(71,0.3652306);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(72,0.3443983);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(73,0.3112203);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(74,0.3030106);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(75,0.2884391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(76,0.275056);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(77,0.2548204);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(78,0.249796);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(79,0.2525632);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(80,0.238774);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(81,0.2440938);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(82,0.2287014);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(85,6.408187);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(86,4.147981);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(87,3.21585);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(88,2.021808);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(89,1.440629);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(90,1.199506);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(91,0.9404432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(92,0.7873105);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(93,0.6303932);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(94,0.5394024);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(95,0.4884059);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(96,0.4232428);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(97,0.4035681);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(98,0.3871359);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(99,0.3388406);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(100,0.3190447);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(101,0.3066554);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(102,0.2857171);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(103,0.2826634);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(104,0.262777);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(105,0.2550592);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(106,0.255626);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(107,0.2423808);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(108,0.2441258);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(109,0.2193841);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(110,0.210629);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(113,8.943642);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(114,5.130472);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(115,3.037687);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(116,1.963247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(117,1.62215);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(118,1.165407);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(119,0.8981841);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(120,0.7953252);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(121,0.6251338);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(122,0.5542134);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(123,0.4773034);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(124,0.4272231);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(125,0.4108456);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(126,0.3638386);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(127,0.3499709);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(128,0.3335003);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(129,0.3053232);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(130,0.278482);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(131,0.2853227);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(132,0.2705213);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(133,0.2560803);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(134,0.247356);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(135,0.2395456);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(136,0.2368639);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(137,0.2272076);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(138,0.2113274);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(141,10.73152);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(142,5.941636);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(143,4.268971);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(144,2.557997);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(145,1.760735);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(146,1.345101);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(147,1.061521);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(148,0.7915125);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(149,0.6827048);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(150,0.5750141);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(151,0.4565666);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(152,0.4387874);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(153,0.4333258);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(154,0.3591721);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(155,0.3637041);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(156,0.330921);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(157,0.3119014);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(158,0.2877955);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(159,0.2725516);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(160,0.2643526);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(161,0.2567889);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(162,0.251218);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(163,0.2570624);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(612,0.4311587);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.3999681);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.35146);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,4.557903);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,1.485692);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,1.23485);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,1.00847);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.8054477);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.625866);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.5394816);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.4705629);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.4166533);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.4042349);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,4.447107);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,1.334497);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,1.292291);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.9062263);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.816518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.6086704);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.5252644);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.4647343);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.4228307);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,4.077733);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,1.465066);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.5207972);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,3.740912);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,1.322336);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,1.03808);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.855077);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.7261294);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.6070079);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,4.02626);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,1.27617);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,1.080592);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.8618078);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.6813351);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,3.030832);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,1.297356);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.010313);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.8218551);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,3.742906);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,1.351178);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,1.058916);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,4.092611);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,1.269449);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,3.706142);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->SetBinContent(29,7.095873);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->SetBinContent(30,4.403269);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->SetBinContent(31,3.172252);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->SetBinContent(32,1.941234);\n 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[GeV]_M_{neutralino 2} [GeV]__20->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__20->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4605969190597534, "alphanum_fraction": 0.6754065155982971, "avg_line_length": 79.51123046875, "blob_id": "2b8ea9538eaf9989588799a1eefad412dd3583c4", "content_id": "9bf93e168cfd20099cac111e5218b90148c1b9d0", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 60947, "license_type": "no_license", "max_line_length": 163, "num_lines": 757, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:32 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(24,0.251819);\n 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[GeV]->SetBinContent(386,25.4731);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(387,28.8818);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(388,36.999);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(389,46.4082);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(404,47.3731);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(405,24.0239);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(406,25.814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(407,25.7468);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(408,27.8245);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(409,30.0007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(410,31.9738);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,38.9897);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,46.9484);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(428,63.3394);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(429,31.6731);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,32.5498);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,33.6675);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,36.6686);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,38.6196);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,44.5388);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,50.2004);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(452,86.3529);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(453,46.691);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(454,43.084);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(455,45.0528);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,46.6114);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,51.3164);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,57.7452);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,119.224);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,58.7119);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,64.9547);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,58.9833);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,59.0233);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,68.2103);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,162.524);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,77.716);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,77.2002);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,76.7735);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,81.9032);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,215.781);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,93.2908);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,97.2408);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,102.255);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,21.8665);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,133.721);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,135.08);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,24.401);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,172.307);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,492.815);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.20088);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(542.0965);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.20088);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.2981904);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.44264);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.657064);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.9753594);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,1.447844);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,2.149209);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,3.19033);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,4.735792);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,7.029908);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,10.43534);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,15.49044);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,22.99432);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,34.13325);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,50.6681);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,75.21278);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,111.6474);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,165.7317);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,246.0156);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,365.1906);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11 = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(24,0.251819);\n 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48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(62,7.88187);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(63,10.4533);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(64,13.5234);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(65,17.043);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(66,22.3421);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(67,28.8693);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(70,0.240329);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(71,0.303245);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(72,0.335196);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(73,0.389496);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(74,0.483468);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} 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48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(101,1.24927);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(102,1.66245);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(103,2.10437);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(104,2.72329);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(105,3.48981);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(106,4.70836);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(107,5.97449);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(108,7.74854);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(109,10.1562);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(110,13.2581);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(111,16.6697);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(112,22.1526);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(113,28.4126);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(116,0.706583);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(117,0.383397);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(118,0.479487);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(119,0.504824);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(120,0.631793);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(121,0.71257);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(122,0.886329);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(123,1.04291);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(124,1.29218);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(125,1.6772);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(126,2.06952);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(127,2.87663);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(128,3.68935);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(129,4.84478);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(130,6.19889);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(131,8.18071);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(132,10.3545);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(133,13.3726);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(134,17.3323);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(135,22.7824);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(136,28.9568);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__11->SetBinContent(429,31.6731);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(430,32.5498);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(431,33.6675);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(432,36.6686);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(433,38.6196);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(434,44.5388);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(435,50.2004);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(452,86.3529);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(453,46.691);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(454,43.084);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(455,45.0528);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(456,46.6114);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(457,51.3164);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(458,57.7452);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(476,119.224);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(477,58.7119);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(478,64.9547);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(479,58.9833);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(480,59.0233);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(481,68.2103);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(500,162.524);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(501,77.716);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(502,77.2002);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(503,76.7735);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(504,81.9032);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(524,215.781);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(525,93.2908);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(526,97.2408);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(527,102.255);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(548,21.8665);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(549,133.721);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(550,135.08);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(572,24.401);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(573,172.307);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(596,492.815);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetMinimum(0.20088);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetMaximum(542.0965);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetEntries(315);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetDirectory(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetStats(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetLineStyle(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitle(\"Observed R\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.6306451559066772, "alphanum_fraction": 0.6645161509513855, "avg_line_length": 27.159090042114258, "blob_id": "0731ef6e61c355e03f8b9aa0578f8594a1b40c3e", "content_id": "e1a47e418331f9c2f313b8fe1c2b90853cf4b4a4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 1240, "license_type": "no_license", "max_line_length": 97, "num_lines": 44, "path": "/LimitTools/Orig_test.sh", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "#!/bin/bash\n\n #exec > /dev/null 2>/dev/null\n \n #WORKDIR=AUniquePlaceholderName\n #CONFIGDIR=ConfigDirPlaceholderName\n RELEASEDIR=~/CMSSW_release/CMSSW_6_1_1\n \n# ZERO=\"\" #$SGE_TASK_ID\n# if [ $SGE_TASK_ID -lt 1000 ]; then\n# ZERO=\"0\"\n# fi\n# if [ $SGE_TASK_ID -lt 100 ]; then\n# ZERO=\"00\"\n# fi\n# if [ $SGE_TASK_ID -lt 10 ]; then\n# ZERO=\"000\"\n# fi\n JOB=`printf \"%04d\" \"$SGE_TASK_ID\"`\n\n # change to scratch directory (local, not lustre in this example)\n #cd $TMPDIR\n # copy raw data to scratch directory (here from the afs)\n # DO NOT USE afscp UNTIL FURTHER NOTICE afscp /afs/naf.desy.de/group/vo/rawdata/bigfile bigfile\n # cp /afs/naf.desy.de/group/vo/rawdata/bigfile bigfile\n #sleep $SGE_TASK_ID\n \n #cp -r $RELEASEDIR .\n #RELEASEBASE=`basename $RELEASEDIR`\n cd $RELEASEDIR/src\n #ini cmssw\n #cmsenv\n pwd > stdout.txt\n export SCRAM_ARCH=\"slc5_amd64_gcc472\" \n export VO_CMS_SW_DIR=\"/cvmfs/cms.cern.ch\" \n echo \"VO_CMS_SW_DIR = $VO_CMS_SW_DIR, SCRAM_ARCH = $SCRAM_ARCH\" >> stdout.txt\n source $VO_CMS_SW_DIR/cmsset_default.sh >> stdout.txt\n ini cmssw >> stdout.txt\n cmsenv\n which combine > stdout.txt\n# setenv SCRAM_ARCH slc5_amd64_gcc472\n# module load cmssw/slc5_amd64_gcc472\n# setcms\n #ini root530 \n" }, { "alpha_fraction": 0.3803591728210449, "alphanum_fraction": 0.607183575630188, "avg_line_length": 88.80267333984375, "blob_id": "dd8af6f31d4be2dee2b10847f7b8d3d0fffa8ffa", "content_id": "c7a935d6926acf933e7645bcd72ff222ebda97c1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 60527, "license_type": "no_license", "max_line_length": 180, "num_lines": 674, "path": "/LimitPlotting/results/Fixed_Neutralino_sbottom_neutralino2_ObsXsecLimitasym.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:39:08 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,22.5,881.8548,789.1667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,37.19371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(25,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(26,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(27,6.583208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(28,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(29,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(30,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(31,0.167391);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(32,0.1460026);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.1237285);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.1047558);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.1022997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,0.09475417);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,0.08901035);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,0.08470546);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,0.0809449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,0.0783184);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,0.07347701);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,0.07420857);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,0.07337876);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,0.0697593);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(47,37.19371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(48,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(49,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(50,6.583208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(51,4.008567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(52,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(53,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(54,0.1445408);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(55,0.1252011);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(56,0.1097831);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(57,0.101277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(58,0.08807919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(59,0.08366301);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(60,0.08025716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(61,0.07687508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(62,0.0741814);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(63,0.07168936);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(64,0.06941523);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(65,0.06928208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(66,0.06527484);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(67,0.06495176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(70,37.19371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(71,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(72,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(73,6.583208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(74,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(75,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(76,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(77,0.1911977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(78,0.1628435);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(79,0.142111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(80,0.1301938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(81,0.1168543);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(82,0.1086695);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(83,0.1017968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(84,0.0955016);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(85,0.09341312);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(86,0.08845664);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(87,0.08542886);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(88,0.08630491);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(89,0.08097234);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(90,0.07855569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(94,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(95,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(96,6.575996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(97,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(98,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(99,0.2698804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(100,0.2325938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(101,0.205267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(102,0.1878479);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(103,0.1681218);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,0.1591701);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,0.1453148);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,0.1333454);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,0.1295628);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,0.1245319);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,0.1175198);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,0.1149675);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,0.1092147);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,0.1101668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,0.1042892);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,6.575996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,0.2925655);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,0.2446566);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,0.2126171);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,0.1902859);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,0.1780832);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,0.1625343);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,0.147848);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,0.1401624);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,0.1295357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,0.1266662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,0.1215522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,0.1150769);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,0.1115027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,0.1076724);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,0.1048134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,6.575996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.132106);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.1206341);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.1119042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.09844297);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.08974939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.08336348);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,0.08105516);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,0.0775668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,0.07469242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,0.0679272);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,0.06737508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,0.06511921);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,0.06413957);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,0.06045741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,1.066042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.07749696);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.0696049);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.06548723);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.06250127);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.0573386);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.05647818);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.05336136);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,0.05284214);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,0.04858072);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,0.04778516);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,0.0459647);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,0.04557525);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,0.04454505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,1.066042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.0602992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.05397732);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.05068939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.04768421);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.04514345);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.043302);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.04158416);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.04120892);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,0.03906248);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,0.03723048);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,0.03780787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,0.03592334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,0.03518474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,1.066042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.05505424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.04602944);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.04257773);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.04170728);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.03881053);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.03500658);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.03579728);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.03449552);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,0.0336536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,0.03345221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,0.03226156);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,0.03148517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,0.03034068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.1144636);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.05990672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.04600506);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.03933646);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.03664896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.03440316);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.03220432);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.03243817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.03135592);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,0.03052384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,0.02906616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,0.02956449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,0.02797326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,0.02787321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.08181424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.05039346);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.03796189);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.03448963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.03234068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.03044131);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.02946788);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.02864384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.0280736);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,0.02718166);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,0.02749422);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,0.02654622);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,0.02601916);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.0691173);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.04396927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.03464472);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.03093717);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.02883295);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.02787196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.02723102);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.02647896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,0.025879);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,0.0256152);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,0.02486029);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,0.02412698);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.05401551);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.0398462);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.03210106);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.02857932);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.02661965);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.02563784);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.02508024);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,0.02452631);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,0.02443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,0.02355526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,0.02342836);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.04804211);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.03725297);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.02952578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.02663321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.02507672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.02429904);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,0.02376473);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,0.02326434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,0.02282317);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,0.02270378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.04280712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.034023);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.02786292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.02519696);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.02398904);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,0.02288826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,0.02245047);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,0.02215156);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,0.02200841);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.03853259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.03254668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.02599188);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.02417008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,0.0226696);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,0.0222313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,0.02185554);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,0.02134712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.03634432);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.0302771);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.02547952);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,0.02310876);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,0.02216569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,0.02141522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,0.02108017);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.03303928);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,0.02970048);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,0.02448739);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,0.0222997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,0.0211139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,0.0205982);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,0.03093304);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,0.02862885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,0.0242541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,0.02173671);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,0.02072072);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,0.02981477);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,0.02762265);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,0.02336428);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,0.02108748);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,0.02789068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,0.02700669);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,0.02224372);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,0.02727619);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,0.02659201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,0.02593153);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.02481893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.03079896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.03821987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.04742881);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.05885662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.07303792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.09063615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.1124746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.139575);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.1732051);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.2149382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.2667269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,0.3309938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,0.4107456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,0.5097133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,0.6325269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,0.7849321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,0.9740587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,1.208755);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(24,37.19371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(25,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(26,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(27,6.583208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(28,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(29,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(30,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(31,0.167391);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(32,0.1460026);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(33,0.1237285);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(34,0.1047558);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(35,0.1022997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(36,0.09475417);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(37,0.08901035);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(38,0.08470546);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(39,0.0809449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(40,0.0783184);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(41,0.07347701);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(42,0.07420857);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(43,0.07337876);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(44,0.0697593);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(47,37.19371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(48,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(49,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(50,6.583208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(51,4.008567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(52,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(53,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(54,0.1445408);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(55,0.1252011);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(56,0.1097831);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(57,0.101277);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(58,0.08807919);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(59,0.08366301);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(60,0.08025716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(61,0.07687508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(62,0.0741814);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(63,0.07168936);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(64,0.06941523);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(65,0.06928208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(66,0.06527484);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(67,0.06495176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(70,37.19371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(71,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(72,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(73,6.583208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(74,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(75,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(76,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(77,0.1911977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(78,0.1628435);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(79,0.142111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(80,0.1301938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(81,0.1168543);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(82,0.1086695);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(83,0.1017968);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(84,0.0955016);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(85,0.09341312);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(86,0.08845664);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(87,0.08542886);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(88,0.08630491);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(89,0.08097234);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(90,0.07855569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(94,19.90225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(95,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(96,6.575996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(97,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(98,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(99,0.2698804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(100,0.2325938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(101,0.205267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(102,0.1878479);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(103,0.1681218);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(104,0.1591701);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(105,0.1453148);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(106,0.1333454);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(107,0.1295628);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(108,0.1245319);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(109,0.1175198);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(110,0.1149675);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(111,0.1092147);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(112,0.1101668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(113,0.1042892);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(118,11.19828);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(119,6.575996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(120,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(121,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(122,0.2925655);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(123,0.2446566);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(124,0.2126171);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(125,0.1902859);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(126,0.1780832);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(127,0.1625343);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(128,0.147848);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(129,0.1401624);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(130,0.1295357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(131,0.1266662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(132,0.1215522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(133,0.1150769);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(134,0.1115027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(135,0.1076724);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(136,0.1048134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(142,6.575996);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(143,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(144,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(145,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(146,0.132106);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(147,0.1206341);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(148,0.1119042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(149,0.09844297);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(150,0.08974939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(151,0.08336348);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(152,0.08105516);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(153,0.0775668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(154,0.07469242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(155,0.0679272);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(156,0.06737508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(157,0.06511921);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(158,0.06413957);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(159,0.06045741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(166,4.004176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(167,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(168,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(169,1.066042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(170,0.07749696);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(171,0.0696049);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(172,0.06548723);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(173,0.06250127);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(174,0.0573386);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(175,0.05647818);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(176,0.05336136);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(177,0.05284214);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(178,0.04858072);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(179,0.04778516);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(180,0.0459647);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(181,0.04557525);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(182,0.04454505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(190,2.513643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(191,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(192,1.066042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(193,0.0602992);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(194,0.05397732);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(195,0.05068939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(196,0.04768421);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(197,0.04514345);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(198,0.043302);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(199,0.04158416);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(200,0.04120892);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(201,0.03906248);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(202,0.03723048);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(203,0.03780787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(204,0.03592334);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(205,0.03518474);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(214,1.619524);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(215,1.066042);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(216,0.05505424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(217,0.04602944);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(218,0.04257773);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(219,0.04170728);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(220,0.03881053);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(221,0.03500658);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(222,0.03579728);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(223,0.03449552);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(224,0.0336536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(225,0.03345221);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(226,0.03226156);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(227,0.03148517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(228,0.03034068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(238,0.1144636);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(239,0.05990672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(240,0.04600506);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(241,0.03933646);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(242,0.03664896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(243,0.03440316);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(244,0.03220432);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(245,0.03243817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(246,0.03135592);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(247,0.03052384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(248,0.02906616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(249,0.02956449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(250,0.02797326);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(251,0.02787321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(262,0.08181424);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(263,0.05039346);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(264,0.03796189);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(265,0.03448963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(266,0.03234068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(267,0.03044131);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(268,0.02946788);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(269,0.02864384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(270,0.0280736);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(271,0.02718166);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(272,0.02749422);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(273,0.02654622);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(274,0.02601916);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(286,0.0691173);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(287,0.04396927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(288,0.03464472);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(289,0.03093717);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(290,0.02883295);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(291,0.02787196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(292,0.02723102);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(293,0.02647896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(294,0.025879);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(295,0.0256152);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(296,0.02486029);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(297,0.02412698);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(310,0.05401551);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(311,0.0398462);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(312,0.03210106);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(313,0.02857932);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(314,0.02661965);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(315,0.02563784);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(316,0.02508024);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(317,0.02452631);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(318,0.02443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(319,0.02355526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(320,0.02342836);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(334,0.04804211);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(335,0.03725297);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(336,0.02952578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(337,0.02663321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(338,0.02507672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(339,0.02429904);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(340,0.02376473);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(341,0.02326434);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(342,0.02282317);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(343,0.02270378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(358,0.04280712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(359,0.034023);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(360,0.02786292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(361,0.02519696);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(362,0.02398904);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(363,0.02288826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(364,0.02245047);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(365,0.02215156);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(366,0.02200841);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(382,0.03853259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(383,0.03254668);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(384,0.02599188);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(385,0.02417008);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(386,0.0226696);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(387,0.0222313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(388,0.02185554);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(389,0.02134712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(406,0.03634432);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(407,0.0302771);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(408,0.02547952);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(409,0.02310876);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(410,0.02216569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(411,0.02141522);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(412,0.02108017);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(430,0.03303928);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(431,0.02970048);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(432,0.02448739);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(433,0.0222997);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(434,0.0211139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(435,0.0205982);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(454,0.03093304);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(455,0.02862885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(456,0.0242541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(457,0.02173671);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(458,0.02072072);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(478,0.02981477);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(479,0.02762265);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(480,0.02336428);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(481,0.02108748);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(502,0.02789068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(503,0.02700669);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(504,0.02224372);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(526,0.02727619);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(527,0.02659201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetBinContent(550,0.02593153);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetDirectory(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitle(\"Observed asympt. cross section limit [pb]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__9->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.5200225114822388, "alphanum_fraction": 0.634118914604187, "avg_line_length": 44.751678466796875, "blob_id": "c9097af5fbf9c200c250f89ad9a0e63b8b680606", "content_id": "afe9469ae58339d7616daad37cb29e0c03820e6e", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 40904, "license_type": "no_license", "max_line_length": 182, "num_lines": 894, "path": "/LimitPlotting/Plotting.cc", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "// $Id: Plotting.cc,v 1.2 2012/06/29 20:27:21 auterman Exp $\n\n/ ------------------------------------------------------------------------------------------------------- \n TheBetterPlotScript, a tool to plot final results, limits and exclusion contours, based on 'PlotScript'\n\n Christian Autermann, Hamburg University/LPC, February 2012\n ------------------------------------------------------------------------------------------------------- /\n\n\n#include \"Plotting.h\"\n\n#include \"StyleSettings.h\"\n#include \"OldExclusionContours.h\"\n\n\nvoid DrawPlot2D(PlotTools PlotTool, TCanvascanvas, TH2 h, const std::string& flag, const string& x, const std::string& y, const std::string& var, \n const std::string& ztitel, double zmin, double zmax, styles)\n{\n TH2F plot2D = (TH2F)h->Clone();\n plot2D->GetZaxis()->SetTitle(ztitel.c_str());\n PlotTool->Area(plot2D, x, y, var);\n plot2D->GetZaxis()->SetTitleOffset(1.5);\n if (zmin!=-999) plot2D->SetMinimum(zmin);\n if (zmax!=-999) plot2D->SetMaximum(zmax);\n if (zmin==-999&&zmax==-999) SetZRange(plot2D);\n if (s&&s->SetMoreLogLabels) {\n plot2D->GetZaxis()->SetMoreLogLabels();\n plot2D->GetZaxis()->SetLabelSize(0.035);\n plot2D->GetZaxis()->SetTitleOffset(2.1);\n c1->SetRightMargin(0.22); \n c1->SetLeftMargin(0.15); \n } \n\n plot2D->GetXaxis()->SetNdivisions(505);\n plot2D->Draw(\"colz\"); \n double tx=400;\n double ty=1.045(plot2D->GetYaxis()->GetXmax()-plot2D->GetYaxis()->GetXmin())+plot2D->GetYaxis()->GetXmin(); \n\n if (s&&s->cmsprelimTemperaturePlot) s->cmsprelimTemperaturePlot->Draw();\n if (s&&s->lumiTemperaturePlot) s->lumiTemperaturePlot->Draw();\n gPad->RedrawAxis();\n string namePlot = \"results/\" + flag + \"_\"+x+\"_\"+y+\"_\"+var;\n if (plotPrelim) canvas->SaveAs((namePlot + \"_prelim.pdf\").c_str());\n if (plotPNG && plotPrelim) canvas->SaveAs((namePlot + \"_prelim.png\").c_str());\n if (plotC && plotPrelim) canvas->SaveAs((namePlot + \"_prelim.C\").c_str());\n //\n plot2D->Draw(\"colz\"); \n if (s&&s->cmsTemperaturePlot) s->cmsTemperaturePlot->Draw();\n if (s&&s->lumiTemperaturePlot) s->lumiTemperaturePlot->Draw();\n gPad->RedrawAxis();\n canvas->SaveAs((namePlot + \".pdf\").c_str());\n if (plotPNG) canvas->SaveAs((namePlot + \".png\").c_str());\n if (plotC) canvas->SaveAs((namePlot + \".C\").c_str());\n}\n \nvoid DrawHist1D(PlotTools PlotTool, TCanvascanvas, const std::string& flag, const string& x, const std::string& y, const std::string& var, \n const std::string& titel, int n)\n{\n std::vector<double> vec;\n PlotTool->VectorOf(vec, var);\n if (vec.size()<=0) return;\n std::sort(vec.begin(), vec.end());\n double median = vec[vec.size()/2];\n double quant16 = vec[vec.size()/6.25];\n double quant84 = vec[vec.size()/1.2];\n double xmin = vec.front();\n double xmax = vec.back();\n std::string name = flag+\"_\"+x+\"_\"+y+\"_\"+var+\"_1D\";\n TH1F h1D = new TH1F(name.c_str(),\";;number of cMSSM points\", n, xmin-sqrt(fabs(xmin)), xmax+sqrt(fabs(xmax)));\n h1D->GetXaxis()->SetTitle(titel.c_str());\n PlotTool->Hist(h1D, var);\n TLegend leg = new TLegend(0.19, 0.7, 0.4, 0.88);\n leg->SetBorderSize(0);\n leg->SetFillColor(0);\n leg->SetTextSize(0.025);\n { std::stringstream ss; ss << \"16% quantile: \" << setprecision(3) << quant16;\n leg->AddEntry((TObject)0,ss.str().c_str(),\"\"); }\n { std::stringstream ss; ss << \"median : \" << setprecision(3) << median;\n leg->AddEntry((TObject)0,ss.str().c_str(),\"\"); }\n { std::stringstream ss; ss << \"84% quantile: \" << setprecision(3) << quant84;\n leg->AddEntry((TObject)0,ss.str().c_str(),\"\"); }\n h1D->Draw(\"h\");\n leg->Draw(\"same\");\n std::string namePlot = \"results/\" + flag +\"_\"+x+\"_\"+y+\"_\"+var+\"_1D\";\n c1->SaveAs((namePlot + \".pdf\").c_str());\n if (plotPNG) c1->SaveAs((namePlot + \".png\").c_str());\n}\n\n\nvoid DrawStandardUncertaintyPlots(PlotTools pt, const std::string& flag, const std::string& x, const std::string& y, styles, TH2h)\n{\n c1->SetRightMargin(0.18); \n //Log z-scale\n c1->SetLogz(1);\n DrawPlot2D(pt,c1,h,flag,x,y,\"Luminosity\", \"Luminosity [pb^{-1}]\", 0, 6000.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalStatUnc\", \"Rel. Signal Statistical uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalSysUnc\", \"Rel. Signal Systematic uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalPDFAccUnc\", \"Rel. Signal PDF Accept. uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalPDFXsecUnc\", \"Rel. Signal PDF cross-section uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalScaleUnc\", \"Rel. Signal Scale uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalJesUpUnc\", \"Rel. Signal JES (up) uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalJesDnUnc\", \"Rel. Signal JES (dn) uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalJerUpUnc\", \"Rel. Signal JER (up) uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalJerDnUnc\", \"Rel. Signal JER (dn) uncertainty\", 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"SignalTotalUnc\", \"Rel. Signal Total uncertainty\", 0.01, 100.);\n}\n\nvoid DrawStandardPlots(PlotTools pt, const std::string& flag, const std::string& x, const std::string& y, styles, TH2h)\n{\n //gStyle->SetPadRightMargin(0.2);\n //gStyle->SetPadLeftMargin(0.2);\n //gStyle->SetTitleOffset(1.3, \"xyz\");\n //gStyle->SetTitleOffset(1.9, \"y\");\n //gStyle->SetNdivisions(505);\n gStyle->SetTitleFont(43, \"xyz\");\n gStyle->SetTitleSize(32, \"xyz\");\n c1->UseCurrentStyle();\n\n //Require an observed CLs limit:\n //pt->Remove(\"Acceptance\", Compare::less, s->MinAccZ);\n //pt->Remove(\"Acceptance\", Compare::greater, s->MaxAccZ);\n //Fill the holes by 2D interpolation in gl-sq\n //pt->FillEmptyPointsByInterpolation(x, y);\n \n //Log z-scale\n c1->SetLogz(1);\n DrawPlot2D(pt,c1,h,flag,x,y,\"Xsection\", \"NLO cross section [pb]\");\n\n //Linear z-scale\n c1->SetLogz(0);\n DrawPlot2D(pt,c1,h,flag,x,y,\"Acceptance\", \"Acceptance\", s->MinAccZ, s->MaxAccZ, s );\n DrawPlot2D(pt,c1,h,flag,x,y,\"AcceptancePercent\", \"Acceptance [%]\", s->MinAccZ100., s->MaxAccZ100., s );\n DrawPlot2D(pt,c1,h,flag,x,y,\"AcceptanceCorrected\", \"Acceptance corr. f. sig. cont. [%]\", s->MinAccZ100., s->MaxAccZ100., s );\n DrawPlot2D(pt,c1,h,flag,x,y,\"ContaminationRelToSignal\", \"Signal contamination / Signal yield [%]\" );\n\n //1D Histograms\n DrawHist1D(pt,c1,flag,x,y,\"SignalStatUnc\",\t \"Rel. Signal Statistical uncertainty\", 20);\n DrawHist1D(pt,c1,flag,x,y,\"SignalSysUnc\",\t \"Rel. Signal Systematic uncertainty\", 20);\n DrawHist1D(pt,c1,flag,x,y,\"SignalPDFAccUnc\", \"Rel. Signal PDF Accept. uncertainty\", 20);\n DrawHist1D(pt,c1,flag,x,y,\"SignalPDFXsecUnc\", \"Rel. Signal PDF cross-section uncertainty\", 20);\n DrawHist1D(pt,c1,flag,x,y,\"SignalScaleUnc\", \"Rel. Signal Scale uncertainty\", 20);\n\n //DrawHist1D(pt,c1,flag,x,y,\"ObsRmM2\", \"ObsR - ExpR-2sigma\", 20);\n //DrawHist1D(pt,c1,flag,x,y,\"ObsRmP2\", \"ObsR - ExpR+2sigma\", 20);\n //DrawHist1D(pt,c1,flag,x,y,\"ObsRdM2\", \"ObsR / ExpR-2sigma\", 20);\n //DrawHist1D(pt,c1,flag,x,y,\"ObsRdP2\", \"ObsR / ExpR+2sigma\", 20);\n}\n\nvoid DrawStandardLimitPlots(PlotTools pt, const std::string& flag, const std::string& x, const std::string& y, styles, TH2h)\n{\n c1->UseCurrentStyle();\n\n //Require an observed CLs limit:\n// pt->Remove(\"ObsXsecLimit\", Compare::less, s->MinXsecZ);\n //Fill possible holes by 2D interpolation in gl-sq\n// pt->FillEmptyPointsByInterpolation(x, y);\n \n \n //Log z-scale\n c1->SetLogz(1);\n //DrawPlot2D(pt,c1,h,flag+\"_FixedBinning\",x,y,\"ObsXsecLimit\", \"Observed cross section limit [pb]\",0.001,0.02);\n DrawPlot2D(pt,c1,h,flag,x,y,\"R_firstguess\", \"R (first guess)\", s->MinXsecZ, s->MaxXsecZ, s );\n DrawPlot2D(pt,c1,h,flag,x,y,\"ObsXsecLimit\", \"95% CL cross section upper limit [pb]\", s->MinXsecZ, s->MaxXsecZ, s );\n DrawPlot2D(pt,c1,h,flag,x,y,\"ExpXsecLimit\", \"Expected cross section limit [pb]\", s->MinXsecZ, s->MaxXsecZ, s);\n //DrawPlot2D(pt,c1,h,flag,x,y,\"ObsNsignalLimit\", \"Observed limit on number signal events\");\n //DrawPlot2D(pt,c1,h,flag,x,y,\"ExpNsignalLimit\", \"Expected limit on number signal events\");\n DrawPlot2D(pt,c1,h,flag,x,y,\"ObsXsecLimitasym\", \"Observed asympt. cross section limit [pb]\", s->MinXsecZ, s->MaxXsecZ, s);\n DrawPlot2D(pt,c1,h,flag,x,y,\"ExpXsecLimitasym\", \"Expected asympt. cross section limit [pb]\", s->MinXsecZ, s->MaxXsecZ, s);\n\n //Linear z-scale\n c1->SetLogz(1);\n //DrawPlot2D(pt,c1,h,flag,x,y,\"ObsR\", \"Observed R\", 0.5, 2.);\n //DrawPlot2D(pt,c1,h,flag,x,y,\"ExpR\", \"Expected R\", 0.5, 2.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"ObsR\", \"Observed R\", -999, -999, s);\n DrawPlot2D(pt,c1,h,flag,x,y,\"ExpR\", \"Expected R\", -999, -999, s);\n //DrawPlot2D(pt,c1,h,flag,x,y,\"ObsDivExp\", \"Observed / Expected\", 0.0, 2.);\n}\n\n\nvoid DrawStandardPlotsPerBin(PlotTools pt, const std::string& flag, const std::string& x, const std::string& y, styles, TH2h)\n{\n for (int bin=0; bin<nchannels; ++bin) {\n std::stringstream binlabel, binl;\n binlabel << \", bin \"<<bin;\n binl << bin;\n const std::string bl = binlabel.str();\n const std::string b = binl.str();\n c1->SetLogz(1);\n \n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b, \t\"Signal event yield\"+bl, 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_acceptance\", \t\"Acceptance [%]\"+bl, 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_contamination\", \"Signal contamination [%]\"+bl, 0.01, 100.);\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_stat_UP\",\t\"Signal Stat. UP [%]\"+bl, 0.01, 100.);\t\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_stat_DN\",\t\"Signal Stat. DN [%]\"+bl, 0.01, 100.);\t\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_syst_UP\",\t\"Signal Syst. UP [%]\"+bl, 0.01, 100.);\t\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_syst_DN\",\t\"Signal Syst. DN [%]\"+bl, 0.01, 100.);\t\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_theory_UP\",\t\"Signal Theory UP [%]\"+bl, 0.01, 100.);\t\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_theory_DN\",\t\"Signal Theory DN [%]\"+bl, 0.01, 100.);\t\n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_trigger_UP\",\t\"Signal trigger UP [%]\"+bl, 0.01, 100.); \n DrawPlot2D(pt,c1,h,flag,x,y,\"signal_\"+b+\"_trigger_DN\", \t\"Signal trigger DN [%]\"+bl, 0.01, 100.); \n\n //1D Histograms\n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_contamination\", \"Signal contamination [%]\"+bl, 20);\n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_stat_UP\", \"Signal Stat. UP [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_stat_DN\", \"Signal Stat. DN [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_syst_UP\", \"Signal Syst. UP [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_syst_DN\", \"Signal Syst. DN [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_theory_UP\", \"Signal Acc. PDF UP [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_theory_DN\", \"Signal Acc. PDF DN [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_trigger_UP\", \"Signal trigger UP [%]\"+bl, 20); \n DrawHist1D(pt,c1,flag,x,y,\"signal_\"+b+\"_trigger_DN\", \"Signal trigger DN [%]\"+bl, 20); \n }\n \n}\n\nTGraph InOutPlot(PlotTools PlotTool, TCanvascanvas, std::string flag, const std::string& x, const std::string& y, const std::string& R, TH2h, unsigned idx, int color, int style)\n{\n canvas->cd();\n \n PlotTool->InOutFromR(h, x, y, R, 3);\n FillEmptyPoints(h,0.5);\n h->GetZaxis()->SetTitleOffset(1.5);\n h->SetMinimum(-0);h->SetMaximum(1.);\n std::vector<TGraph> contours = GetContours(h, 3);\n /// :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::\n h->Draw(\"colz\");\n int col = kBlue - 10;\n for (std::vector<TGraph>::iterator cont = contours.begin(); cont != contours.end(); ++cont) {\n \t if (!cont) continue;\n \t double x, y;\n \t (cont)->GetPoint(0, x, y);\n \t (cont)->SetLineColor(col);\n \t (cont)->Draw(\"l\");\n \t TLatex l;\n \t l.SetTextSize(0.04);\n \t l.SetTextColor(col++);\n \t char val[20];\n \t sprintf(val, \"%d\", (int) (cont - contours.begin()));\n \t l.DrawLatex(x, y, val);\n \t if (cont-contours.begin()>13) break;\n }\n //drawCmsPrel(PlotTool->SingleValue(Luminosity), METCut);\n string nameXsPlot = \"results/\" + flag + \"_\"+x+\"_\"+y+\"_\"+\"InOut\"+R;\n canvas->SaveAs((nameXsPlot + \".pdf\").c_str());\n if (plotPNG) canvas->SaveAs((nameXsPlot + \".png\").c_str());\n delete h;\n TGraph res = (contours.size()>idx?(TGraph)contours[idx]->Clone():0);\n if (res) {res->SetLineColor(color);\n res->SetLineStyle(style);}\n return res;\n}\n\nvoid DrawExclusion(PlotTools PlotTool, std::string flag, const std::string& x, const std::string& y, \n TH1hp, TH1h,TH1old_hp, TH1old_h, styles)\n{\n //Require an observed CLs limit:\n //PlotTool->Remove(\"ObsR\", Compare::less, 0.0);\n //PlotTool->FillEmptyPointsByInterpolation1D(x, y);\n \n \n \n TH2F hs = (TH2F)h->Clone();\n TH2F hplot = (TH2F)hp->Clone();\n TH2F old_hs = (TH2F)old_h->Clone();\n TH2F old_hplot = (TH2F)old_hp->Clone();\n hs->GetZaxis()->SetTitle(\"\");\n\n if (s->PreExclusionPlotting) s->PreExclusionPlotting(s, PlotTool );\n\n //In/Out Plot\n hplot->GetZaxis()->SetTitle(\"Observed in/out\");\n TGraph gCLsObsExcl\t = InOutPlot(PlotTool,c1,flag,x,y,\"ObsR\",(TH2F)h->Clone(), s->iCLsObsExcl, kBlue, 1);\n\n hplot->GetZaxis()->SetTitle(\"Expected in/out\");\n TGraph gCLsExpExcl = InOutPlot(PlotTool,c1,flag,x,y,\"ExpR\",(TH2F)h->Clone(), s->iCLsExpExcl, kOrange + 9, 9);\n\n hplot->GetZaxis()->SetTitle(\"Expected -1 #sigma_{experimental} in/out\");\n TGraph gCLsExpExclm1 = InOutPlot(PlotTool,c1,flag,x,y,\"ExpRM1\",(TH2F)h->Clone(), s->iCLsExpExclm1, kOrange - 3, 3);\n\n hplot->GetZaxis()->SetTitle(\"Expected +1 #sigma_{experimental} in/out\");\n TGraph gCLsExpExclp1 = InOutPlot(PlotTool,c1,flag,x,y,\"ExpRP1\",(TH2F)h->Clone(), s->iCLsExpExclp1, kOrange - 3, 3);\n\n hplot->GetZaxis()->SetTitle(\"Expected -2 #sigma_{experimental} in/out\");\n TGraph gCLsExpExclm2= InOutPlot(PlotTool,c1,flag,x,y,\"ExpRM2\",(TH2F)h->Clone(), s->iCLsExpExclm2, kOrange - 2, 3);\n\n hplot->GetZaxis()->SetTitle(\"Expected +2 #sigma_{experimental} in/out\");\n TGraph gCLsExpExclp2 = InOutPlot(PlotTool,c1,flag,x,y,\"ExpRP2\",(TH2F)h->Clone(), s->iCLsExpExclp2, kOrange - 2, 3);\n\n hplot->GetZaxis()->SetTitle(\"Observed -1 #sigma_{theory} in/out\");\n TGraph gCLsObsTheom1 = InOutPlot(PlotTool,c1,flag,x,y,\"ObsRTheoM1\",(TH2F)h->Clone(), s->iCLsObsTheom1, kBlue, 3);\n\n hplot->GetZaxis()->SetTitle(\"Observed +1 #sigma_{theory} in/out\");\n TGraph gCLsObsTheop1 = InOutPlot(PlotTool,c1,flag,x,y,\"ObsRTheoP1\",(TH2F)h->Clone(), s->iCLsObsTheop1, kBlue, 3);\n \n\n\n {\n //Exclusion Contours\n //gStyle->SetPadRightMargin(0.08);\n //gStyle->SetPadLeftMargin(0.2);\n //gStyle->SetTitleOffset(1.3, \"xyz\");\n //gStyle->SetTitleOffset(1.9, \"y\");\n //gStyle->SetNdivisions(505);\n //gStyle->SetTitleFont(43, \"xyz\");\n //gStyle->SetTitleSize(32, \"xyz\");\n \n //Compromise agreed on with Dongwook:\n gStyle->SetOptStat(0);\n gStyle->SetPalette(1);\n gStyle->SetPadRightMargin(0.08);\n gStyle->SetPadLeftMargin(0.18);\n gStyle->SetPadTopMargin(0.1);\n gStyle->SetPadBottomMargin(0.15);\n gStyle->SetTitleOffset(1.0, \"x\");\n gStyle->SetTitleOffset(1.5, \"y\");\n gStyle->SetTitleOffset(1.2, \"z\");\n gStyle->SetNdivisions(505);\n gStyle->SetTitleFont(43, \"xyz\");\n gStyle->SetTitleSize(32, \"xyz\");\n //gStyle->SetLabelSize(0.03, \"XYZ\");\n c1->UseCurrentStyle();\n c1->SetLogz(0);\n c1->SetTopMargin(0.11);\n\n \n \n gCLsObsExcl->SetLineWidth(3);\n gCLsExpExcl->SetLineWidth(3);\n \n\n TGraph gObsUnsmoothed = (TGraph)gCLsObsExcl->Clone();\n TGraph gObsUnsmooth = (TGraph)gCLsObsExcl->Clone();\n TGraph gObsUnsmoothExpExcl = (TGraph)gCLsExpExcl->Clone();\n TGraph gObsUnsmoothExpExclp1 = (TGraph)gCLsExpExclp1->Clone();\n TGraph gObsUnsmoothExpExclm1 = (TGraph)gCLsExpExclm1->Clone();\n TGraph gObsUnsmoothExpExclp2 = (TGraph)gCLsExpExclp2->Clone();\n TGraph gObsUnsmoothExpExclm2 = (TGraph)gCLsExpExclm2->Clone();\n Smooth(gCLsObsExcl, s->smooth_points, s->smooth_flag);\n Smooth(gCLsExpExcl, s->smooth_points, s->smooth_flag);\n Smooth(gCLsExpExclm1, s->smooth_points, s->smooth_flag);\n Smooth(gCLsExpExclp1, s->smooth_points, s->smooth_flag);\n Smooth(gCLsExpExclm2, s->smooth_points, s->smooth_flag);\n Smooth(gCLsExpExclp2, s->smooth_points, s->smooth_flag);\n Smooth(gCLsObsTheom1, s->smooth_points, s->smooth_flag);\n Smooth(gCLsObsTheop1, s->smooth_points, s->smooth_flag);\n if (s->second_smooth) {\n Smooth(gCLsObsExcl, s->second_smooth, s->smooth_flag);\n Smooth(gCLsExpExcl, s->second_smooth, s->smooth_flag);\n Smooth(gCLsExpExclm1, s->second_smooth, s->smooth_flag);\n Smooth(gCLsExpExclp1, s->second_smooth, s->smooth_flag);\n Smooth(gCLsExpExclm2, s->second_smooth, s->smooth_flag);\n Smooth(gCLsExpExclp2, s->second_smooth, s->smooth_flag);\n Smooth(gCLsObsTheom1, s->second_smooth, s->smooth_flag);\n Smooth(gCLsObsTheop1, s->second_smooth, s->smooth_flag);\n }\n\n TGraph gCLs1Sigma = MakeBand(gCLsExpExclm1, gCLsExpExclp1);\n gCLs1Sigma->SetFillStyle(1001);\n gCLs1Sigma->SetFillColor(kOrange - 3);\n TGraph * gCLs2Sigma = MakeBand(gCLsExpExclm2, gCLsExpExclp2);\n gCLs2Sigma->SetFillStyle(1001);\n gCLs2Sigma->SetFillColor(kOrange - 4);\n hplot->GetYaxis()->SetTitleOffset(1.9);\n hplot->GetXaxis()->SetTitleOffset(1.1);\n //Drawing the contours\n hplot->Draw(\"h\");\n gCLs2Sigma->Draw(\"f\");\n gCLs1Sigma->Draw(\"f\");\n gCLsObsExcl->Draw(\"l\");\n //~ gObsUnsmooth->Draw(\"l\");\n gCLsExpExcl->Draw(\"l\");\n //~ gObsUnsmoothExpExcl->Draw(\"l\");\n //~ gObsUnsmoothExpExclp1->Draw(\"l\");\n //~ gObsUnsmoothExpExclm1->Draw(\"l\");\n// gCLsExpTheom1->Draw(\"l\");\n gCLsObsTheom1->Draw(\"l\");\n// gCLsExpTheop1->Draw(\"l\");\n gCLsObsTheop1->Draw(\"l\");\n\n //Legends\n TLegend* leg = s->leg;\n TH1F * legdummy = 0;\n leg->AddEntry(gCLsObsExcl, \"Observed\", \"l\");\n leg->AddEntry(gCLsObsTheop1, \"Observed #pm1#sigma theory\", \"l\");\n TH1F* legExp = (TH1F)gCLs1Sigma->Clone();\n legExp->SetLineStyle(gCLsExpExcl->GetLineStyle());\n legExp->SetLineColor(gCLsExpExcl->GetLineColor());\n legExp->SetLineWidth(gCLsExpExcl->GetLineWidth());\n leg->AddEntry(legExp, \"Expected #pm1#sigma exp.\", \"lf\");\n leg->AddEntry(gCLs2Sigma, \"Expected #pm2#sigma exp.\", \"f\");\n //leg->AddEntry(gCLsExpTheop1, \"Exp. limit #pm1#sigma signal theory\", \"l\");\n\n if (s->PostExclusionPlotting) s->PostExclusionPlotting(s,leg);\n if (s->excluded) s->excluded->Draw();\n leg->Draw();\n s->lumi->Draw();\n s->cms->Draw();\n s->cmsprelim->Draw();\n\n gPad->RedrawAxis();\n string nameExcl = \"results/\"+ flag + \"_\"+x+\"_\"+y+\"_Exclusion_\";\n c1->SaveAs((nameExcl + \".pdf\").c_str());\n if (plotPNG) c1->SaveAs((nameExcl + \".png\").c_str());\n if (plotROOT) c1->SaveAs((nameExcl + \"canvas.C\").c_str());\n if (plotC ) {\n h->GetZaxis()->SetTitle(\"\");\n h->Draw(\"h\");\n gCLsObsExcl->SetName(\"Observed limit\");\n gCLsObsExcl->SetTitle(\"Observed limit\");\n gCLsObsExcl->Draw(\"l\");\n gCLsExpExcl->SetName(\"Expected limit\");\n gCLsExpExcl->SetTitle(\"Expected limit\");\n gCLsExpExcl->Draw(\"l\");\n c1->SaveAs((nameExcl + \".C\").c_str());\n }\n \n \n\n ///------------------------------------------------------------------------------------\n /// same, but preliminary:\n gCLs1Sigma->Draw(\"f\");\n gCLsObsExcl->Draw(\"l\");\n gCLsExpExcl->Draw(\"l\");\n gCLsObsTheom1->Draw(\"l\");\n gCLsObsTheop1->Draw(\"l\");\n if (s->excluded) s->excluded->Draw();\n if (s->PostExclusionPlotting) s->PostExclusionPlotting(s,0); \n leg->Draw();\n s->lumi->Draw();\n s->cmsprelim->Draw();\n gPad->RedrawAxis();\n nameExcl = \"results/\"+ flag + \"_\"+x+\"_\"+y+\"_Exclusion_prelim\";\n if (plotPrelim) c1->SaveAs((nameExcl + \".pdf\").c_str());\n \n {\n\t gStyle->SetOptStat(0);\n\t gStyle->SetPalette(1);\n\t gStyle->SetPadRightMargin(0.08);\n\t gStyle->SetPadLeftMargin(0.18);\n\t gStyle->SetPadTopMargin(0.1);\n\t gStyle->SetPadBottomMargin(0.15);\n\t gStyle->SetTitleOffset(1.0, \"x\");\n\t gStyle->SetTitleOffset(1.5, \"y\");\n\t gStyle->SetTitleOffset(1.2, \"z\");\n\t gStyle->SetNdivisions(505);\n\t gStyle->SetTitleFont(43, \"xyz\");\n\t gStyle->SetTitleSize(32, \"xyz\");\n\t //gStyle->SetLabelSize(0.03, \"XYZ\");\n\t c1->UseCurrentStyle();\n\t c1->SetLogz(0);\n\t c1->SetTopMargin(0.11);\n\t \n\t //~ TGraphcover = new TGraph(0);\n\t //~ cover->SetPoint(0, 0, 0);\n\t //~ cover->SetPoint(1, 0, 1000);\n\t //~ cover->SetPoint(2, 1000, 1000);\n\t //~ cover->SetPoint(3, 1000, 0);\n\t //~ cover->SetFillColor(kWhite);\n\t //~ cover->Draw(\"f\");\n\t \n\t //~ TGraphFixed_Edge = new TGraph(0);\n\t\t//~ Fixed_Edge->SetPoint(0, 50, 50);\n\t\t//~ Fixed_Edge->SetPoint(1, 3000, 3000);\n\t\t//~ Fixed_Edge->SetPoint(2, 50, 3000);\n\t\t//~ Fixed_Edge->SetPoint(3, 50, 50);\n\t\t//~ Fixed_Edge->SetFillColor(kGray);\n\t\t//~ Fixed_Edge->Draw(\"f\");\n\t\n\t //~ TGraph Obs8TeV = new TGraph(23);\n\t //~ Obs8TeV->SetName(\"Observed 8 TeV limit\");\n\t //~ Obs8TeV->SetTitle(\"Observed 8 TeV limit\");\n\t //~ Obs8TeV->SetFillColor(100);\n\t//~ \n\t //~ Obs8TeV->SetLineColor(1);\n\t //~ Obs8TeV->SetLineWidth(3);\n\t //~ Obs8TeV->SetPoint(0,343.75,100);\n\t //~ Obs8TeV->SetPoint(1,343.75,112.5);\n\t //~ Obs8TeV->SetPoint(2,343.75,125);\n\t //~ Obs8TeV->SetPoint(3,343.6045,137.3544999);\n\t //~ Obs8TeV->SetPoint(4,342.7837813,149.0337812);\n\t //~ Obs8TeV->SetPoint(5,340.6937847,159.4437847);\n\t //~ Obs8TeV->SetPoint(6,337.3545,168.6044999);\n\t //~ Obs8TeV->SetPoint(7,333.3399966,177.0899966);\n\t //~ Obs8TeV->SetPoint(8,329.0145034,185.2645034);\n\t //~ Obs8TeV->SetPoint(9,324.0337812,192.7837812);\n\t //~ Obs8TeV->SetPoint(10,317.7837812,199.0337812);\n\t //~ Obs8TeV->SetPoint(11,310.2645034,204.0145034);\n\t //~ Obs8TeV->SetPoint(12,302.0899966,208.3399966);\n\t //~ Obs8TeV->SetPoint(13,293.6044999,212.3545);\n\t //~ Obs8TeV->SetPoint(14,284.4437847,215.6937847);\n\t //~ Obs8TeV->SetPoint(15,274.0337812,217.7837813);\n\t //~ Obs8TeV->SetPoint(16,262.3544999,218.6045);\n\t //~ Obs8TeV->SetPoint(17,250.1197198,218.6045);\n\t //~ Obs8TeV->SetPoint(18,238.3465809,217.8095615);\n\t //~ Obs8TeV->SetPoint(19,227.8055396,215.8392028);\n\t //~ Obs8TeV->SetPoint(20,219.1515959,212.8960939);\n\t //~ Obs8TeV->SetPoint(21,210.9088591,210.0175204);\n\t //~ Obs8TeV->SetPoint(22,200,208.2979194);\n\t //~ \n\t //~ TH1F Graph_Obs8TeV = new TH1F(\"Graph_Obs8TeV\",\"Observed limit\",100,185.625,358.125);\n\t //~ Graph_Obs8TeV->SetMinimum(88.13955);\n\t //~ Graph_Obs8TeV->SetMaximum(230.4649);\n\t //~ Graph_Obs8TeV->SetDirectory(0);\n\t //~ Graph_Obs8TeV->SetStats(0);\n\t //~ Graph_Obs8TeV->SetLineStyle(0);\n\t //~ Graph_Obs8TeV->GetXaxis()->SetNdivisions(505);\n\t //~ Graph_Obs8TeV->GetXaxis()->SetLabelFont(42);\n\t //~ Graph_Obs8TeV->GetXaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Obs8TeV->GetXaxis()->SetTitleSize(32);\n\t //~ Graph_Obs8TeV->GetXaxis()->SetTitleFont(43);\n\t //~ Graph_Obs8TeV->GetYaxis()->SetLabelFont(42);\n\t //~ Graph_Obs8TeV->GetYaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Obs8TeV->GetYaxis()->SetTitleSize(32);\n\t //~ Graph_Obs8TeV->GetYaxis()->SetTitleOffset(1.5);\n\t //~ Graph_Obs8TeV->GetYaxis()->SetTitleFont(43);\n\t //~ Graph_Obs8TeV->GetZaxis()->SetLabelFont(42);\n\t //~ Graph_Obs8TeV->GetZaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Obs8TeV->GetZaxis()->SetTitleSize(32);\n\t //~ Graph_Obs8TeV->GetZaxis()->SetTitleOffset(1.2);\n\t //~ Graph_Obs8TeV->GetZaxis()->SetTitleFont(43);\n\t //~ Obs8TeV->SetHistogram(Graph_Obs8TeV);\n\t //~ \n\t //~ Obs8TeV->Draw(\"l\");\n\t //~ \n\t //~ TGraph Exp8TeV = new TGraph(41);\n\t //~ Exp8TeV->SetName(\"Expected 8 TeV limit\");\n\t //~ Exp8TeV->SetTitle(\"Expected 8 TeV limit\");\n\t //~ Exp8TeV->SetFillColor(100);\n\t//~ \n\t //~ Exp8TeV->SetLineColor(kOrange + 9);\n\t //~ Exp8TeV->SetLineStyle(9);\n\t //~ Exp8TeV->SetLineWidth(3);\n\t //~ Exp8TeV->SetPoint(0,422.3134321,100);\n\t //~ Exp8TeV->SetPoint(1,425,106.9027168);\n\t //~ Exp8TeV->SetPoint(2,428.1937847,115.5562153);\n\t //~ Exp8TeV->SetPoint(3,430.2837813,125.9662188);\n\t //~ Exp8TeV->SetPoint(4,431.1045,137.6455001);\n\t //~ Exp8TeV->SetPoint(5,431.25,150);\n\t //~ Exp8TeV->SetPoint(6,431.1045,162.3544999);\n\t //~ Exp8TeV->SetPoint(7,430.2837813,174.0337812);\n\t //~ Exp8TeV->SetPoint(8,428.1937847,184.4437847);\n\t //~ Exp8TeV->SetPoint(9,425,193.75);\n\t //~ Exp8TeV->SetPoint(10,421.6607153,202.9107153);\n\t //~ Exp8TeV->SetPoint(11,418.75,212.5);\n\t //~ Exp8TeV->SetPoint(12,415.6937847,221.9437847);\n\t //~ Exp8TeV->SetPoint(13,411.5337813,230.2837812);\n\t //~ Exp8TeV->SetPoint(14,406.1045,237.3545);\n\t //~ Exp8TeV->SetPoint(15,400,243.75);\n\t //~ Exp8TeV->SetPoint(16,393.75,250);\n\t //~ Exp8TeV->SetPoint(17,387.3545,256.1045);\n\t //~ Exp8TeV->SetPoint(18,380.4292813,261.6792813);\n\t //~ Exp8TeV->SetPoint(19,372.7645034,266.5145034);\n\t //~ Exp8TeV->SetPoint(20,364.5899966,270.8399966);\n\t //~ Exp8TeV->SetPoint(21,356.1044999,274.8545);\n\t //~ Exp8TeV->SetPoint(22,346.9437847,278.1937847);\n\t //~ Exp8TeV->SetPoint(23,336.5337812,280.2837813);\n\t //~ Exp8TeV->SetPoint(24,324.8544999,281.1302802);\n\t //~ Exp8TeV->SetPoint(25,312.5,281.3954181);\n\t //~ Exp8TeV->SetPoint(26,300.1197198,281.4748135);\n\t //~ Exp8TeV->SetPoint(27,288.4663008,280.7041682);\n\t //~ Exp8TeV->SetPoint(28,278.6521205,277.8192331);\n\t //~ Exp8TeV->SetPoint(29,271.2403284,272.4595163);\n\t //~ Exp8TeV->SetPoint(30,265.2476175,265.9264469);\n\t //~ Exp8TeV->SetPoint(31,259.0735531,259.7523825);\n\t //~ Exp8TeV->SetPoint(32,252.3949836,253.930952);\n\t //~ Exp8TeV->SetPoint(33,246.069048,247.6050164);\n\t //~ Exp8TeV->SetPoint(34,240.2476175,240.9264469);\n\t //~ Exp8TeV->SetPoint(35,234.0735531,234.7523825);\n\t //~ Exp8TeV->SetPoint(36,227.3949836,228.930952);\n\t //~ Exp8TeV->SetPoint(37,221.069048,222.6050164);\n\t //~ Exp8TeV->SetPoint(38,216.0159851,216.0977273);\n\t //~ Exp8TeV->SetPoint(39,210.192052,211.0095194);\n\t //~ Exp8TeV->SetPoint(40,200,208.4434195);\n\t //~ \n\t //~ TH1F Graph_Exp8TeV = new TH1F(\"Graph_Exp8TeV\",\"Expected limit\",100,176.875,454.375);\n\t //~ Graph_Exp8TeV->SetMinimum(81.85252);\n\t //~ Graph_Exp8TeV->SetMaximum(299.6223);\n\t //~ Graph_Exp8TeV->SetDirectory(0);\n\t //~ Graph_Exp8TeV->SetStats(0);\n\t //~ Graph_Exp8TeV->SetLineStyle(0);\n\t //~ Graph_Exp8TeV->GetXaxis()->SetNdivisions(505);\n\t //~ Graph_Exp8TeV->GetXaxis()->SetLabelFont(42);\n\t //~ Graph_Exp8TeV->GetXaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp8TeV->GetXaxis()->SetTitleSize(32);\n\t //~ Graph_Exp8TeV->GetXaxis()->SetTitleFont(43);\n\t //~ Graph_Exp8TeV->GetYaxis()->SetLabelFont(42);\n\t //~ Graph_Exp8TeV->GetYaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp8TeV->GetYaxis()->SetTitleSize(32);\n\t //~ Graph_Exp8TeV->GetYaxis()->SetTitleOffset(1.5);\n\t //~ Graph_Exp8TeV->GetYaxis()->SetTitleFont(43);\n\t //~ Graph_Exp8TeV->GetZaxis()->SetLabelFont(42);\n\t //~ Graph_Exp8TeV->GetZaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp8TeV->GetZaxis()->SetTitleSize(32);\n\t //~ Graph_Exp8TeV->GetZaxis()->SetTitleOffset(1.2);\n\t //~ Graph_Exp8TeV->GetZaxis()->SetTitleFont(43);\n\t //~ Exp8TeV->SetHistogram(Graph_Exp8TeV);\n\t //~ \n\t //~ Exp8TeV->Draw(\"l\");\n\t //~ \n\t //~ TGraph Exp13TeVDirect = new TGraph(30);\n\t //~ Exp13TeVDirect->SetName(\"Expected limit\");\n\t //~ Exp13TeVDirect->SetTitle(\"Expected limit\");\n\t //~ Exp13TeVDirect->SetFillColor(100);\n\t//~ \n\t //~ Exp13TeVDirect->SetLineColor(kRed);\n\t //~ Exp13TeVDirect->SetLineStyle(9);\n\t //~ Exp13TeVDirect->SetLineWidth(3);\n\t //~ Exp13TeVDirect->SetPoint(0,382.3617189,100);\n\t //~ Exp13TeVDirect->SetPoint(1,384.3062154,110.9956622);\n\t //~ Exp13TeVDirect->SetPoint(2,387.5,119.4027168);\n\t //~ Exp13TeVDirect->SetPoint(3,390.5482846,127.9107153);\n\t //~ Exp13TeVDirect->SetPoint(4,391.8175625,137.5);\n\t //~ Exp13TeVDirect->SetPoint(5,390.5482846,147.0892847);\n\t //~ Exp13TeVDirect->SetPoint(6,387.5,156.25);\n\t //~ Exp13TeVDirect->SetPoint(7,384.1607153,165.4107153);\n\t //~ Exp13TeVDirect->SetPoint(8,381.25,175);\n\t //~ Exp13TeVDirect->SetPoint(9,378.1937847,184.4437847);\n\t //~ Exp13TeVDirect->SetPoint(10,373.8882812,192.6382812);\n\t //~ Exp13TeVDirect->SetPoint(11,367.7837812,199.0337812);\n\t //~ Exp13TeVDirect->SetPoint(12,360.2645034,204.0145034);\n\t //~ Exp13TeVDirect->SetPoint(13,352.0899966,208.3399966);\n\t //~ Exp13TeVDirect->SetPoint(14,343.6044999,212.3545);\n\t //~ Exp13TeVDirect->SetPoint(15,334.5892847,215.8392847);\n\t //~ Exp13TeVDirect->SetPoint(16,325,218.75);\n\t //~ Exp13TeVDirect->SetPoint(17,315.4107153,221.6607153);\n\t //~ Exp13TeVDirect->SetPoint(18,306.25,225);\n\t //~ Exp13TeVDirect->SetPoint(19,296.9437847,228.1937847);\n\t //~ Exp13TeVDirect->SetPoint(20,286.6792813,230.1382812);\n\t //~ Exp13TeVDirect->SetPoint(21,275.8207187,230.1382812);\n\t //~ Exp13TeVDirect->SetPoint(22,265.5562153,228.1937847);\n\t //~ Exp13TeVDirect->SetPoint(23,256.25,225);\n\t //~ Exp13TeVDirect->SetPoint(24,247.0635045,221.6607153);\n\t //~ Exp13TeVDirect->SetPoint(25,237.3803622,218.7757803);\n\t //~ Exp13TeVDirect->SetPoint(26,227.6600395,215.9847028);\n\t //~ Exp13TeVDirect->SetPoint(27,219.1515959,212.8960939);\n\t //~ Exp13TeVDirect->SetPoint(28,210.9088591,210.0175204);\n\t //~ Exp13TeVDirect->SetPoint(29,200,208.2979194);\n\t //~ \n\t //~ TH1F Graph_Exp13TeVDirect = new TH1F(\"Graph_Exp13TeVDirect\",\"Expected limit\",100,180.8182,410.9993);\n\t //~ Graph_Exp13TeVDirect->SetMinimum(86.98617);\n\t //~ Graph_Exp13TeVDirect->SetMaximum(243.1521);\n\t //~ Graph_Exp13TeVDirect->SetDirectory(0);\n\t //~ Graph_Exp13TeVDirect->SetStats(0);\n\t //~ Graph_Exp13TeVDirect->SetLineStyle(0);\n\t //~ Graph_Exp13TeVDirect->GetXaxis()->SetNdivisions(505);\n\t //~ Graph_Exp13TeVDirect->GetXaxis()->SetLabelFont(42);\n\t //~ Graph_Exp13TeVDirect->GetXaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp13TeVDirect->GetXaxis()->SetTitleSize(32);\n\t //~ Graph_Exp13TeVDirect->GetXaxis()->SetTitleFont(43);\n\t //~ Graph_Exp13TeVDirect->GetYaxis()->SetLabelFont(42);\n\t //~ Graph_Exp13TeVDirect->GetYaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp13TeVDirect->GetYaxis()->SetTitleSize(32);\n\t //~ Graph_Exp13TeVDirect->GetYaxis()->SetTitleOffset(1.5);\n\t //~ Graph_Exp13TeVDirect->GetYaxis()->SetTitleFont(43);\n\t //~ Graph_Exp13TeVDirect->GetZaxis()->SetLabelFont(42);\n\t //~ Graph_Exp13TeVDirect->GetZaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp13TeVDirect->GetZaxis()->SetTitleSize(32);\n\t //~ Graph_Exp13TeVDirect->GetZaxis()->SetTitleOffset(1.2);\n\t //~ Graph_Exp13TeVDirect->GetZaxis()->SetTitleFont(43);\n\t //~ Exp13TeVDirect->SetHistogram(Graph_Exp13TeVDirect);\n\t //~ \n\t //~ Exp13TeVDirect->Draw(\"l\");\n\t //~ \n\t //~ TGraph Exp13TeVEff = new TGraph(59);\n\t //~ Exp13TeVEff->SetName(\"Expected limit\");\n\t //~ Exp13TeVEff->SetTitle(\"Expected limit\");\n\t //~ Exp13TeVEff->SetFillColor(100);\n\t//~ \n\t //~ Exp13TeVEff->SetLineColor(kBlue);\n\t //~ Exp13TeVEff->SetLineStyle(9);\n\t //~ Exp13TeVEff->SetLineWidth(3);\n\t //~ Exp13TeVEff->SetPoint(0,519.8617189,100);\n\t //~ Exp13TeVEff->SetPoint(1,521.8062154,110.9956622);\n\t //~ Exp13TeVEff->SetPoint(2,525,119.4027168);\n\t //~ Exp13TeVEff->SetPoint(3,528.1937847,128.0562153);\n\t //~ Exp13TeVEff->SetPoint(4,530.2837813,138.4662188);\n\t //~ Exp13TeVEff->SetPoint(5,530.9589999,150);\n\t //~ Exp13TeVEff->SetPoint(6,530.2837813,161.5337812);\n\t //~ Exp13TeVEff->SetPoint(7,528.1937847,171.9437847);\n\t //~ Exp13TeVEff->SetPoint(8,525,181.25);\n\t //~ Exp13TeVEff->SetPoint(9,521.6607153,190.4107153);\n\t //~ Exp13TeVEff->SetPoint(10,518.75,200);\n\t //~ Exp13TeVEff->SetPoint(11,515.8392847,209.5892847);\n\t //~ Exp13TeVEff->SetPoint(12,512.5,218.75);\n\t //~ Exp13TeVEff->SetPoint(13,509.3062154,228.0562153);\n\t //~ Exp13TeVEff->SetPoint(14,507.0707187,238.3207187);\n\t //~ Exp13TeVEff->SetPoint(15,505.4292813,249.1792813);\n\t //~ Exp13TeVEff->SetPoint(16,503.1937847,259.4437847);\n\t //~ Exp13TeVEff->SetPoint(17,499.8545,268.6044999);\n\t //~ Exp13TeVEff->SetPoint(18,495.8399966,277.0899966);\n\t //~ Exp13TeVEff->SetPoint(19,491.5145034,285.2645034);\n\t //~ Exp13TeVEff->SetPoint(20,486.6792813,292.9292813);\n\t //~ Exp13TeVEff->SetPoint(21,481.1045,299.8545);\n\t //~ Exp13TeVEff->SetPoint(22,475,306.25);\n\t //~ Exp13TeVEff->SetPoint(23,468.75,312.5);\n\t //~ Exp13TeVEff->SetPoint(24,462.3545,318.6045);\n\t //~ Exp13TeVEff->SetPoint(25,455.2837812,324.0337813);\n\t //~ Exp13TeVEff->SetPoint(26,446.7982846,328.0482846);\n\t //~ Exp13TeVEff->SetPoint(27,436.6792813,330.4292813);\n\t //~ Exp13TeVEff->SetPoint(28,425.8207187,332.0707187);\n\t //~ Exp13TeVEff->SetPoint(29,415.5562153,334.3062154);\n\t //~ Exp13TeVEff->SetPoint(30,406.3955001,337.3545);\n\t //~ Exp13TeVEff->SetPoint(31,397.9100034,339.7275659);\n\t //~ Exp13TeVEff->SetPoint(32,389.5899966,339.7275659);\n\t //~ Exp13TeVEff->SetPoint(33,381.25,337.2089999);\n\t //~ Exp13TeVEff->SetPoint(34,372.9100034,333.3399966);\n\t //~ Exp13TeVEff->SetPoint(35,364.5899966,329.1600034);\n\t //~ Exp13TeVEff->SetPoint(36,356.1044999,325.1455001);\n\t //~ Exp13TeVEff->SetPoint(37,347.0635045,321.6607153);\n\t //~ Exp13TeVEff->SetPoint(38,337.3803622,318.7757803);\n\t //~ Exp13TeVEff->SetPoint(39,327.6600395,315.9847028);\n\t //~ Exp13TeVEff->SetPoint(40,318.5545086,312.7248135);\n\t //~ Exp13TeVEff->SetPoint(41,310.1594096,308.7603835);\n\t //~ Exp13TeVEff->SetPoint(42,302.5662639,303.7854519);\n\t //~ Exp13TeVEff->SetPoint(43,296.069048,297.6050164);\n\t //~ Exp13TeVEff->SetPoint(44,290.2476175,290.9264469);\n\t //~ Exp13TeVEff->SetPoint(45,284.0735531,284.7523825);\n\t //~ Exp13TeVEff->SetPoint(46,277.3949836,278.930952);\n\t //~ Exp13TeVEff->SetPoint(47,271.069048,272.6050164);\n\t //~ Exp13TeVEff->SetPoint(48,265.2476175,265.9264469);\n\t //~ Exp13TeVEff->SetPoint(49,259.0735531,259.7523825);\n\t //~ Exp13TeVEff->SetPoint(50,252.3949836,253.930952);\n\t //~ Exp13TeVEff->SetPoint(51,246.069048,247.6050164);\n\t //~ Exp13TeVEff->SetPoint(52,240.2476175,240.9264469);\n\t //~ Exp13TeVEff->SetPoint(53,234.0735531,234.7523825);\n\t //~ Exp13TeVEff->SetPoint(54,227.3949836,228.930952);\n\t //~ Exp13TeVEff->SetPoint(55,221.069048,222.6050164);\n\t //~ Exp13TeVEff->SetPoint(56,216.0159851,216.0977273);\n\t //~ Exp13TeVEff->SetPoint(57,210.192052,211.0095194);\n\t //~ Exp13TeVEff->SetPoint(58,200,208.4434195);\n\t //~ \n\t //~ TH1F Graph_Exp13TeVEff = new TH1F(\"Graph_Exp13TeVEff\",\"Expected limit\",100,166.9041,564.0549);\n\t //~ Graph_Exp13TeVEff->SetMinimum(76.02724);\n\t //~ Graph_Exp13TeVEff->SetMaximum(363.7003);\n\t //~ Graph_Exp13TeVEff->SetDirectory(0);\n\t //~ Graph_Exp13TeVEff->SetStats(0);\n\t //~ Graph_Exp13TeVEff->SetLineStyle(0);\n\t //~ Graph_Exp13TeVEff->GetXaxis()->SetNdivisions(505);\n\t //~ Graph_Exp13TeVEff->GetXaxis()->SetLabelFont(42);\n\t //~ Graph_Exp13TeVEff->GetXaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp13TeVEff->GetXaxis()->SetTitleSize(32);\n\t //~ Graph_Exp13TeVEff->GetXaxis()->SetTitleFont(43);\n\t //~ Graph_Exp13TeVEff->GetYaxis()->SetLabelFont(42);\n\t //~ Graph_Exp13TeVEff->GetYaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp13TeVEff->GetYaxis()->SetTitleSize(32);\n\t //~ Graph_Exp13TeVEff->GetYaxis()->SetTitleOffset(1.5);\n\t //~ Graph_Exp13TeVEff->GetYaxis()->SetTitleFont(43);\n\t //~ Graph_Exp13TeVEff->GetZaxis()->SetLabelFont(42);\n\t //~ Graph_Exp13TeVEff->GetZaxis()->SetLabelOffset(0.007);\n\t //~ Graph_Exp13TeVEff->GetZaxis()->SetTitleSize(32);\n\t //~ Graph_Exp13TeVEff->GetZaxis()->SetTitleOffset(1.2);\n\t //~ Graph_Exp13TeVEff->GetZaxis()->SetTitleFont(43);\n\t //~ Exp13TeVEff->SetHistogram(Graph_Exp13TeVEff);\n\t //~ \n\t //~ Exp13TeVEff->Draw(\"l\");\n\t //~ \n\t //~ TLegend legSMS = s->leg;\n\t //~ std::string header = legSMS->GetHeader();\n\t //~ legSMS->Clear();\n\t //~ legSMS->SetHeader(header.c_str());\n\t //~ legSMS->AddEntry(Obs8TeV, \"Obs. 8 TeV\", \"l\");\n\t //~ legSMS->AddEntry(Exp8TeV, \"Exp. 8 TeV\", \"l\");\n\t //~ legSMS->AddEntry(Exp13TeVDirect, \"Exp. 13 TeV, SF BG from MC \", \"l\");\n\t //~ legSMS->AddEntry(Exp13TeVEff, \"Exp. 13 TeV, Extrapolation Meth.\", \"l\");\n\t //~ legSMS->Draw();\n\t //~ s->lumiTemperaturePlot->Draw();\n\t //~ s->cms->Draw();\n\t //~ s->cmsprelim->Draw();\n\t //~ gPad->RedrawAxis();\n\t //~ string nameExcl = \"results/8_and_13TeV_Exclusion_Limits\";\n\t //~ c1->SaveAs((nameExcl + \".pdf\").c_str());\n }\n\n\n ///------------------------------------------------------------------------------------\n /// Exclusion plot SMS style with x-sect limit\n gStyle->SetOptStat(0);\n gStyle->SetPalette(1);\n gStyle->SetPadRightMargin(0.2);\n gStyle->SetPadLeftMargin(0.18);\n gStyle->SetPadTopMargin(0.1);\n gStyle->SetPadBottomMargin(0.15);\n gStyle->SetTitleOffset(1.0, \"x\");\n gStyle->SetTitleOffset(1.5, \"y\");\n gStyle->SetTitleOffset(1.2, \"z\");\n gStyle->SetNdivisions(505);\n gStyle->SetTitleFont(43, \"xyz\");\n gStyle->SetTitleSize(32, \"xyz\");\n c1->UseCurrentStyle();\n c1->SetLogz(1);\n \n\n TH2F plot2D = (TH2F)old_hp->Clone();\n plot2D->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n PlotTool->Area(plot2D, x, y, \"ObsXsecLimit\");\n plot2D->GetZaxis()->SetTitleOffset(1.5);\n if (s->MinXsecZ!=-999) plot2D->SetMinimum(s->MinXsecZ);\n if (s->MaxXsecZ!=-999) plot2D->SetMaximum(s->MaxXsecZ);\n if (s->MinXsecZ==-999&&s->MaxXsecZ==-999) SetZRange(plot2D);\n if (s&&s->SetMoreLogLabels) {\n plot2D->GetZaxis()->SetMoreLogLabels();\n plot2D->GetZaxis()->SetLabelSize(0.035);\n plot2D->GetZaxis()->SetTitleOffset(2.1);\n c1->SetRightMargin(0.22); \n c1->SetLeftMargin(0.15); \n } \n plot2D->Draw(\"colz\"); \n gCLsObsExcl->SetLineWidth(3);\n gCLsObsExcl->SetLineColor(kBlack);\n gCLsObsTheom1->SetLineColor(kBlack);\n gCLsObsTheop1->SetLineColor(kBlack);\n gCLsObsTheom1->SetLineStyle(3);\n gCLsObsTheop1->SetLineStyle(3);\n gCLsObsTheom1->SetLineWidth(2);\n gCLsObsTheop1->SetLineWidth(2);\n gCLsExpExclm1->SetLineWidth(2);\n gCLsExpExclp1->SetLineWidth(2);\n gCLsExpExclm2->SetLineWidth(2);\n gCLsExpExclp2->SetLineWidth(2);\n gCLsExpExcl->SetLineWidth(3);\n gCLsExpExcl->SetLineStyle(9);\n gCLsExpExcl->SetLineColor(kOrange + 9);\n gCLsExpExclm1->SetLineColor(kOrange + 9);\n gCLsExpExclp1->SetLineColor(kOrange + 9);\n gCLsExpExclm2->SetLineColor(kOrange + 8);\n gCLsExpExclp2->SetLineColor(kOrange + 8);\n gCLsExpExclm1->Draw(\"l\");\n gCLsExpExclp1->Draw(\"l\");\n gCLsExpExclm2->Draw(\"l\");\n gCLsExpExclp2->Draw(\"l\");\n gCLsObsExcl->Draw(\"l\");\n gCLsExpExcl->Draw(\"l\");\n gCLsObsTheom1->Draw(\"l\");\n gCLsObsTheop1->Draw(\"l\");\n if (s->excluded) s->excluded->Draw();\n TLegend* legSMS = s->legTemperaturePlot;\n std::string header = legSMS->GetHeader();\n legSMS->Clear();\n legSMS->SetHeader(header.c_str());\n legSMS->AddEntry(gCLsObsExcl, \"Observed\", \"l\");\n legSMS->AddEntry(gCLsObsTheop1, \"Observed #pm1#sigma theory\", \"l\");\n legSMS->AddEntry(gCLsExpExcl, \"Expected\", \"l\");\n legSMS->AddEntry(gCLsExpExclm1, \"Expected #pm1#sigma exp.\", \"l\");\n legSMS->AddEntry(gCLsExpExclm2, \"Expected #pm2#sigma exp.\", \"l\");\n if (s->PostExclusionPlotting) s->PostExclusionPlotting(s,legSMS); \n legSMS->Draw();\n s->lumiTemperaturePlot->Draw();\n s->cmsTemperaturePlot->Draw();\n //~ s->cmsprelimTemperaturePlot->Draw();\n gPad->RedrawAxis();\n nameExcl = \"results/\"+ flag + \"_\"+x+\"_\"+y+\"_Exclusion_witXsecLimit\";\n c1->SaveAs((nameExcl + \".pdf\").c_str());\n }\n \n \n \n}\n\n\n\n\n\nvoid GetPlotTools(PlotTools& plotTools, std::string filename, const std::string& x, const std::string& y, std::string GeneratorFile, unsigned factor)\n{\n if (!c1) c1 = new TCanvas(\"c_squ\", \"c_squ\", 900, 800);\n c1->cd();\n \n Events events = new Events();\n ReadEvents(events, filename);\n \n //plotting helper functions\n plotTools = new PlotTools(events);\n\n //Require an observed CLs limit:\n plotTools->Remove(\"ObsR\", Compare::less, 0.00001);\n plotTools->Remove(\"Xsection\", Compare::less, 0.0);\n\n //Fill the holes by 2D interpolation in gl-sq\n plotTools->FillEmptyPointsByInterpolation(x, y);\n plotTools->FillEmptyPointsByInterpolation(x, y);\n\n //Make grid in Mzero, Mhalf finer by factors of 2 by linear interpolation\n for (int i=2; i<=factor; i=2)\n plotTools->ExpandGrid(x, y);\n // New 'pseudo' points are added, therefore the binning of all plots has to be made finer by a factor\n // of 2 in x and y for each \"ExpandGrid\n \n //Add generator information of particles masses if a file is given\n if (GeneratorFile!=\"\") {\n std::vector<GeneratorMasses> GenMasses;\n ReadGeneratorMasses(GenMasses, GeneratorFile);\n Match( GenMasses, events);\n } \n} \n\n" }, { "alpha_fraction": 0.38278165459632874, "alphanum_fraction": 0.604058027267456, "avg_line_length": 88.06379699707031, "blob_id": "c485ce6a46520066963decf6e83497fe9ff12c9f", "content_id": "1975b840860686ab3edcef217d2fb7bd092ece4a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 60029, "license_type": "no_license", "max_line_length": 180, "num_lines": 674, "path": "/LimitPlotting/results/Fixed_Neutralino_sbottom_neutralino2_R_firstguess.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:39:08 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,22.5,881.8548,789.1667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(24,0.04274631);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(25,0.05154939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(26,0.05653441);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(27,0.06413844);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(28,0.0759633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(29,0.08969321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(30,0.1102132);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(31,0.1434722);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(32,0.1859943);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(33,0.231174);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(34,0.2806268);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(35,0.3898565);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(36,0.5036972);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(37,0.6553614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(38,0.8537312);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(39,1.100904);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(40,1.420815);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(41,1.805201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(42,2.417678);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(43,3.150086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(44,3.919556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(47,0.03268149);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(48,0.03664953);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(49,0.04411505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(50,0.05283518);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(51,0.06478258);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(52,0.07820752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(53,0.09972573);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(54,0.1249292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(55,0.1617953);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(56,0.2057747);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(57,0.2734534);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(58,0.3378751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(59,0.4466064);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(60,0.5931823);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(61,0.7771063);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(62,1.011601);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(63,1.319885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(64,1.713002);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(65,2.267413);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(66,2.805636);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(67,3.652172);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(70,0.04050737);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(71,0.06017205);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(72,0.06795716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(73,0.08165231);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(74,0.0979229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(75,0.1234816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(76,0.1635568);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(77,0.2101178);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(78,0.2692155);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(79,0.3474826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(80,0.4600035);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(81,0.5964139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(82,0.8039787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(83,1.027194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(84,1.326646);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(85,1.77778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(86,2.298695);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(87,2.96246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(88,3.999804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(89,4.90261);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(90,6.307854);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(94,0.06170025);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(95,0.09392101);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(96,0.09617076);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(97,0.1169663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(98,0.1501925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(99,0.2028087);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(100,0.276088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(101,0.3514875);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(102,0.5105397);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(103,0.6530067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,0.8799664);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,1.114436);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,1.407729);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,1.871821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,2.415967);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,3.053422);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,3.976629);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,5.09289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,6.75977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,8.310555);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,0.08154002);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,0.1380165);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,0.1475456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,0.1882792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,0.2354621);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,0.3098973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,0.3904276);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,0.5096694);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,0.6911683);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,0.8901336);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,1.110913);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,1.460165);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,1.868179);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,2.430938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,3.130382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,4.06927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,5.174487);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,6.623935);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,8.398442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,0.1075602);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,0.1029133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,0.1162821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,0.1350313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,0.1721925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,0.229849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,0.3182682);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,0.3975011);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,0.5262022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,0.6934982);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,0.9168959);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,1.208422);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,1.563318);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,1.949924);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,2.595517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,3.304916);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,4.285604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,5.346745);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,0.1416613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,0.09915638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,0.1124635);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,0.1348713);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,0.1721121);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,0.2324054);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,0.3101711);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,0.4213111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,0.5377398);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,0.7249382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,0.9448026);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,1.263604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,1.568356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,2.061009);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,2.632895);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,3.405638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,4.343698);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,0.1344322);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,0.1102884);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,0.1239461);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,0.1503385);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,0.1989963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,0.2601567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,0.354536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.4640004);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.6058175);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.8052335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,1.067225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,1.358567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,1.744442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,2.336793);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,2.947389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,3.733504);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.1462578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.1303775);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.1475933);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.1815637);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.2378877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.3232521);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.4240468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.5287027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.7209109);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.9507678);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,1.258801);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,1.624761);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,2.093906);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,2.679741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,3.402022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.1620689);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.1624046);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.1816336);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.2278714);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.2966488);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.3875901);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.5044335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.6769019);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.8964469);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,1.167737);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,1.487049);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,1.990556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,2.485877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,3.22703);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.1916816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.2081807);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.223203);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.2947482);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.375952);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.4914209);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.6462741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.8444847);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,1.106311);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,1.432893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,1.908683);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,2.422983);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,3.0666);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.239927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.2680107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.3001832);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.3666716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.4725208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.6164846);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.8113839);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,1.066202);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,1.376484);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,1.810145);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,2.293741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,2.913596);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.2882854);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.3495404);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.3884113);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.4741437);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.6056475);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.7924734);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,1.023574);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,1.334674);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,1.751559);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,2.250541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,2.886964);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.3721083);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.4527105);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.495744);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.6070616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.7792684);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.9936028);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,1.298463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,1.703861);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,2.156084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,2.791526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.4677259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.5739039);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.6467316);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.7839898);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,1.001404);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,1.269985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,1.640841);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,2.138643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,2.748357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.5980965);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.7631803);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.8230492);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,1.015685);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,1.276586);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,1.641194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,2.10295);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,2.696569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.7766753);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.9748303);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,1.0735);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,1.306679);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,1.628382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,2.080299);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,2.655063);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.9644068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.260332);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,1.388324);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,1.678682);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,2.063396);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,2.640196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.228258);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.620492);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,1.82218);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,2.13279);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,2.65732);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.622506);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,2.071635);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,2.302804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.698617);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,2.004409);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,2.677912);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,2.889709);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,2.54606);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,3.429157);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,3.213443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.02481893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.03079896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.03821987);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.04742881);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.05885662);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.07303792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.09063615);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.1124746);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.139575);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.1732051);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.2149382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.2667269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,0.3309938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,0.4107456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,0.5097133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,0.6325269);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,0.7849321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,0.9740587);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,1.208755);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(24,0.04274631);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(25,0.05154939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(26,0.05653441);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(27,0.06413844);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(28,0.0759633);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(29,0.08969321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(30,0.1102132);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(31,0.1434722);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(32,0.1859943);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(33,0.231174);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(34,0.2806268);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(35,0.3898565);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(36,0.5036972);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(37,0.6553614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(38,0.8537312);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(39,1.100904);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(40,1.420815);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(41,1.805201);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(42,2.417678);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(43,3.150086);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(44,3.919556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(47,0.03268149);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(48,0.03664953);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(49,0.04411505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(50,0.05283518);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(51,0.06478258);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(52,0.07820752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(53,0.09972573);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(54,0.1249292);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(55,0.1617953);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(56,0.2057747);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(57,0.2734534);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(58,0.3378751);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(59,0.4466064);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(60,0.5931823);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(61,0.7771063);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(62,1.011601);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(63,1.319885);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(64,1.713002);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(65,2.267413);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(66,2.805636);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(67,3.652172);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(70,0.04050737);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(71,0.06017205);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(72,0.06795716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(73,0.08165231);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(74,0.0979229);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(75,0.1234816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(76,0.1635568);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(77,0.2101178);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(78,0.2692155);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(79,0.3474826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(80,0.4600035);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(81,0.5964139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(82,0.8039787);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(83,1.027194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(84,1.326646);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(85,1.77778);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(86,2.298695);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(87,2.96246);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(88,3.999804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(89,4.90261);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(90,6.307854);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(94,0.06170025);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(95,0.09392101);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(96,0.09617076);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(97,0.1169663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(98,0.1501925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(99,0.2028087);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(100,0.276088);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(101,0.3514875);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(102,0.5105397);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(103,0.6530067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(104,0.8799664);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(105,1.114436);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(106,1.407729);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(107,1.871821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(108,2.415967);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(109,3.053422);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(110,3.976629);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(111,5.09289);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(112,6.75977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(113,8.310555);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(118,0.08154002);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(119,0.1380165);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(120,0.1475456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(121,0.1882792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(122,0.2354621);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(123,0.3098973);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(124,0.3904276);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(125,0.5096694);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(126,0.6911683);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(127,0.8901336);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(128,1.110913);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(129,1.460165);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(130,1.868179);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(131,2.430938);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(132,3.130382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(133,4.06927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(134,5.174487);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(135,6.623935);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(136,8.398442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(142,0.1075602);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(143,0.1029133);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(144,0.1162821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(145,0.1350313);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(146,0.1721925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(147,0.229849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(148,0.3182682);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(149,0.3975011);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(150,0.5262022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(151,0.6934982);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(152,0.9168959);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(153,1.208422);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(154,1.563318);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(155,1.949924);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(156,2.595517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(157,3.304916);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(158,4.285604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(159,5.346745);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(166,0.1416613);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(167,0.09915638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(168,0.1124635);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(169,0.1348713);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(170,0.1721121);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(171,0.2324054);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(172,0.3101711);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(173,0.4213111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(174,0.5377398);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(175,0.7249382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(176,0.9448026);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(177,1.263604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(178,1.568356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(179,2.061009);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(180,2.632895);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(181,3.405638);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(182,4.343698);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(190,0.1344322);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(191,0.1102884);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(192,0.1239461);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(193,0.1503385);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(194,0.1989963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(195,0.2601567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(196,0.354536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(197,0.4640004);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(198,0.6058175);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(199,0.8052335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(200,1.067225);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(201,1.358567);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(202,1.744442);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(203,2.336793);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(204,2.947389);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(205,3.733504);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(214,0.1462578);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(215,0.1303775);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(216,0.1475933);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(217,0.1815637);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(218,0.2378877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(219,0.3232521);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(220,0.4240468);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(221,0.5287027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(222,0.7209109);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(223,0.9507678);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(224,1.258801);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(225,1.624761);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(226,2.093906);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(227,2.679741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(228,3.402022);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(238,0.1620689);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(239,0.1624046);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(240,0.1816336);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(241,0.2278714);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(242,0.2966488);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(243,0.3875901);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(244,0.5044335);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(245,0.6769019);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(246,0.8964469);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(247,1.167737);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(248,1.487049);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(249,1.990556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(250,2.485877);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(251,3.22703);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(262,0.1916816);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(263,0.2081807);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(264,0.223203);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(265,0.2947482);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(266,0.375952);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(267,0.4914209);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(268,0.6462741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(269,0.8444847);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(270,1.106311);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(271,1.432893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(272,1.908683);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(273,2.422983);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(274,3.0666);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(286,0.239927);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(287,0.2680107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(288,0.3001832);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(289,0.3666716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(290,0.4725208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(291,0.6164846);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(292,0.8113839);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(293,1.066202);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(294,1.376484);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(295,1.810145);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(296,2.293741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(297,2.913596);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(310,0.2882854);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(311,0.3495404);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(312,0.3884113);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(313,0.4741437);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(314,0.6056475);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(315,0.7924734);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(316,1.023574);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(317,1.334674);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(318,1.751559);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(319,2.250541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(320,2.886964);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(334,0.3721083);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(335,0.4527105);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(336,0.495744);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(337,0.6070616);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(338,0.7792684);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(339,0.9936028);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(340,1.298463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(341,1.703861);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(342,2.156084);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(343,2.791526);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(358,0.4677259);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(359,0.5739039);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(360,0.6467316);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(361,0.7839898);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(362,1.001404);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(363,1.269985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(364,1.640841);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(365,2.138643);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(366,2.748357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(382,0.5980965);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(383,0.7631803);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(384,0.8230492);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(385,1.015685);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(386,1.276586);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(387,1.641194);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(388,2.10295);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(389,2.696569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(406,0.7766753);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(407,0.9748303);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(408,1.0735);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(409,1.306679);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(410,1.628382);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(411,2.080299);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(412,2.655063);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(430,0.9644068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(431,1.260332);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(432,1.388324);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(433,1.678682);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(434,2.063396);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(435,2.640196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(454,1.228258);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(455,1.620492);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(456,1.82218);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(457,2.13279);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(458,2.65732);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(478,1.622506);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(479,2.071635);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(480,2.302804);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(481,2.698617);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(502,2.004409);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(503,2.677912);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(504,2.889709);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(526,2.54606);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(527,3.429157);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetBinContent(550,3.213443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetMinimum(0.02);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetMaximum(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetDirectory(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitle(\"R (first guess)\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__6->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.5070372819900513, "alphanum_fraction": 0.5885526537895203, "avg_line_length": 36.231441497802734, "blob_id": "6c77347ab3e6e56b68a70824434ed6eb93740a54", "content_id": "4e8522ee521554182cbd1ff76a6c1c927a03c998", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 8526, "license_type": "no_license", "max_line_length": 139, "num_lines": 229, "path": "/LimitPlotting/StyleSettings_Dilepton.cc", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "// $Id: StyleSettings_SinglePhoton_8TeV.cc,v 1.1 2012/06/29 20:27:21 auterman Exp $\n\n/ ------------------------------------------------------------------------------------------------------- \n TheBetterPlotScript, a tool to plot final results, limits and exclusion contours, based on 'PlotScript'\n\n Christian Autermann, Hamburg University/LPC, February 2012\n ------------------------------------------------------------------------------------------------------- /\n\n#include <iostream>\n\n#include \"TString.h\"\n#include \"TStyle.h\"\n#include \"TLatex.h\"\n#include \"TGraph.h\"\n#include \"TH2F.h\"\n\n#include \"StyleSettings.h\"\n#include \"OldExclusionContours.h\"\n#include \"Overview.h\"\n\nvoid SetDefault(style s=0)\n{\n if (!s) return;\n if (s->legTemperaturePlot) {\n s->legTemperaturePlot->SetBorderSize(0);\n s->legTemperaturePlot->SetLineColor(0);\n //~ s->legTemperaturePlot->SetFillColor(10);\n s->legTemperaturePlot->SetFillColor(0);\n s->legTemperaturePlot->SetFillStyle(1001);\n s->legTemperaturePlot->SetTextFont(42);\n s->legTemperaturePlot->SetTextSize(0.04);\n }\n if (s->leg) {\n s->leg->SetBorderSize(0);\n s->leg->SetLineColor(0);\n //~ s->leg->SetFillColor(10);\n s->leg->SetFillColor(0);\n s->leg->SetFillStyle(1001);\n s->leg->SetTextFont(42);\n s->leg->SetTextSize(0.03);\n }\n if (s->excluded) {\n s->excluded->SetNDC(true);\n s->excluded->SetTextColor(1);\n s->excluded->SetTextFont(43);\n s->excluded->SetTextSize(25);\n }\n if (s->cmsprelim) {\n s->cmsprelim->SetNDC(true);\n //~ s->cmsprelim->SetTextColor(1);\n s->cmsprelim->SetTextFont(52);\n s->cmsprelim->SetTextSize(0.03);\n }\n if (s->lumi) {\n s->lumi->SetNDC(true);\n //~ s->lumi->SetTextColor(1);\n s->lumi->SetTextFont(42);\n s->lumi->SetTextSize(0.04);\n s->lumi->SetTextAlign(31);\n }\n if (s->cms) {\n s->cms->SetNDC(true);\n //~ s->cms->SetTextColor(1);\n s->cms->SetTextFont(61);\n s->cms->SetTextSize(0.055);\n }\n //~ s->legTemperaturePlot = new TLegend(0.175,0.6,0.525,0.9,\"T6bblledge: #Deltam =70 GeV\");\n s->legTemperaturePlot = new TLegend(0.18,0.605,0.5,0.885,\"Fixed edge, #Deltam = 70 GeV\");\n //~ s->legTemperaturePlot = new TLegend(0.175,0.6,0.525,0.9,\"#splitline{T6bblledge: #Deltam =70 GeV}{Selection Efficiency Method}\");\n //~ s->legTemperaturePlot = new TLegend(0.175,0.6,0.525,0.9,\"#splitline{T6bblledge: #Deltam =70 GeV}{SF background from MC}\");\n //~ s->legTemperaturePlot = new TLegend(0.18,0.605,0.53,0.885,\"Slepton model, m(#tilde{#chi}_{1}^{0}) = 100 GeV\");\n s->legTemperaturePlot->SetTextSize(0.03);\n s->legTemperaturePlot->SetFillColor(0);\n //~ s->lumiTemperaturePlot = new TLatex(0.48, 0.912, \"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\n s->lumiTemperaturePlot = new TLatex(0.8, 0.91, \"19.4 fb^{-1} (8 TeV)\");\n //~ s->lumiTemperaturePlot = new TLatex(0.85, 0.91, \"20 fb^{-1} (13 TeV)\");\n s->lumiTemperaturePlot->SetNDC(true);\n //~ s->lumiTemperaturePlot->SetTextColor(1);\n s->lumiTemperaturePlot->SetTextFont(42);\n s->lumiTemperaturePlot->SetTextSize(0.04);\n s->lumiTemperaturePlot->SetTextAlign(31);\n s->cmsTemperaturePlot = new TLatex(0.18, 0.91, \"CMS\");\n s->cmsTemperaturePlot->SetNDC(true);\n //~ s->cmsTemperaturePlot->SetTextColor(1);\n s->cmsTemperaturePlot->SetTextFont(61);\n s->cmsTemperaturePlot->SetTextSize(0.055);\n //~ s->cmsprelimTemperaturePlot = new TLatex(0.65, 0.81, \"Preliminary\");\n //~ s->cmsprelimTemperaturePlot = new TLatex(0.65, 0.81, \"Private Work\");\n s->cmsprelimTemperaturePlot->SetNDC(true);\n //~ s->cmsprelimTemperaturePlot->SetTextColor(1);\n s->cmsprelimTemperaturePlot->SetTextFont(52);\n s->cmsprelimTemperaturePlot->SetTextSize(0.03);\n\n}\n\n/// ----------- Fixed Neutralino ------------ /// ----------------------------------------------------------------------------------\n\nvoid Draw_Fixed_Neutralino_CoverUp(style * s=0, TLegendl=0) {\n\tTGraphcover = new TGraph(0);\n\tcover->SetPoint(0, 200, 300);\n\tcover->SetPoint(1, 880, 920);\n\tcover->SetPoint(2, 900, 900);\n\tcover->SetPoint(3, 0, 0);\n\tcover->SetFillColor(kWhite);\n\t//cover->SetLineColor(kBlack);\n\tcover->Draw(\"f\");\n\n\tTGraphFixed_Neutralino = new TGraph(0);\n\tFixed_Neutralino->SetPoint(0, 50, 50);\n\tFixed_Neutralino->SetPoint(1, 3000, 3005);\n\tFixed_Neutralino->SetPoint(2, 50, 3000);\n\tFixed_Neutralino->SetPoint(3, 50, 50);\n\t//~ Fixed_Neutralino->SetFillColor(kGray);\n\tFixed_Neutralino->SetFillColor(kWhite);\n\tFixed_Neutralino->Draw(\"f\");\n\n\tTLatex tex;\n\ttex.SetTextSize(0.03);\n\ttex.SetTextFont(62);\n\ttex.SetNDC(true);\n\t//~ tex.DrawLatex(0.6, 0.25, \"Fixed Neutralino\");\n\tgPad->RedrawAxis();\n\t\n}\n\n\nstyle Fixed_Neutralino_Style(){ \n style * s = new style();\n //~ s->leg = new TLegend(0.2,0.6,0.6,0.89,\"m(#tilde{#chi}_{1}^{0}) = 100 GeV, BR 10 %\");\n //~ s->lumi = new TLatex(0.525, 0.902, \"L_{int} = 19.4 fb^{ -1}, SF,\");\n //~ s->cms = new TLatex(0.18, 0.902, \"#bf{CMS preliminary}, #sqrt{s} = 8 TeV\");\n //~ s->cmsprelim = new TLatex(0.18, 0.902, \"#bf{CMS preliminary}, #sqrt{s} = 8 TeV\");\n s->leg = new TLegend(0.175,0.6,0.525,0.9,\"m(#tilde{#chi}_{1}^{0}) = 100 GeV\"); \n s->lumi = new TLatex(0.85, 0.91, \"19.4 fb^{-1} (8 TeV)\");\n //~ s->cmsprelim = new TLatex(0.65, 0.81, \"Preliminary\");\n s->cms = new TLatex(0.65, 0.85, \"CMS\");\n //~ s->excluded = new TLatex(0.35, 0.25, \"Excluded\");\n s->smooth_flag=4;\n s->smooth_points=25;\n s->PostExclusionPlotting=Draw_Fixed_Neutralino_CoverUp;\n s->iCLsObsExcl=1; \n s->iCLsExpExcl=0; \n s->iCLsExpExclm1=0;\n s->iCLsExpExclp1=0;\n s->iCLsObsTheom1=0;\n s->iCLsObsTheop1=0;\n s->MinXsecZ=0.005;\n s->MaxXsecZ=5.;\n s->MinAccZ=0;\n s->MaxAccZ=0.8;\n\n SetDefault(s);\n return s;\n}\n\n/// ----------- Fixed Edge ------------ /// ----------------------------------------------------------------------------------\nvoid Draw_Fixed_Edge_CoverUp(style * s=0, TLegendl=0) {\n\tTGraphcover = new TGraph(0);\n\tcover->SetPoint(0, 300, 350);\n\tcover->SetPoint(1, 950, 1000);\n\tcover->SetPoint(2, 1000, 1000);\n\tcover->SetPoint(3, 0, 0);\n\tcover->SetFillColor(kWhite);\n\t//cover->SetLineColor(kBlack);\n//\tcover->Draw(\"f\");\n\n\tTGraphFixed_Edge = new TGraph(0);\n\tFixed_Edge->SetPoint(0, 50, 50);\n\tFixed_Edge->SetPoint(1, 3000, 3000);\n\tFixed_Edge->SetPoint(2, 50, 3000);\n\tFixed_Edge->SetPoint(3, 50, 50);\n\t//~ Fixed_Edge->SetFillColor(kGray);\n\tFixed_Edge->SetFillColor(kWhite);\n\tFixed_Edge->Draw(\"f\");\n\t\n\n\t//~ TLatex tex;\n\t//~ tex.SetTextSize(0.04);\n\t//~ tex.SetTextFont(62);\n\t//~ tex.SetNDC(true);\n\t//~ tex.DrawLatex(0.423, 0.215, \"x\");\n\t//~ gPad->RedrawAxis();\n}\n\nstyle Fixed_Edge_Style(){ \n style * s = new style();\n //~ s->leg = new TLegend(0.2,0.6,0.6,0.89,\"Fixed Edge: #Deltam =70 GeV, BR: 10%\");\n //~ s->leg = new TLegend(0.5,0.6,0.92,0.89,\"Fixed Edge: #Deltam =70 GeV\");\n //~ s->leg = new TLegend(0.175,0.6,0.55,0.9,\"T6bbllslepton: m(#tilde{#chi}_{1}^{0}) = 100 GeV\");\n //~ s->leg = new TLegend(0.4,0.6,0.91,0.875,\"T6bblledge: #Deltam =70 GeV, 19.4 resp. 20 fb^{-1}\"); \n s->leg = new TLegend(0.4,0.6,0.91,0.875,\"T6bblledge: #Deltam =70 GeV\"); \n //~ s->leg = new TLegend(0.175,0.6,0.55,0.9,\"#splitline{T6bblledge: #Deltam =70 GeV}{Selection Efficiency Method}\"); \n //~ s->leg = new TLegend(0.175,0.6,0.55,0.9,\"#splitline{T6bblledge: #Deltam =70 GeV}{SF background from MC}\"); \n //~ s->lumi = new TLatex(0.92, 0.9, \"\");\n //~ s->lumi = new TLatex(0.92, 0.9, \"20 fb^{-1} (13 TeV)\");\n //~ s->cmsprelim = new TLatex(0.75, 0.8, \"Preliminary\");\n //~ s->cmsprelim = new TLatex(0.2, 0.8, \"Private Work\");\n //~ s->cmsprelim = new TLatex(0.2, 0.8, \"Preliminary\");\n s->cms = new TLatex(0.2, 0.84, \"CMS\");\n //~ s->lumi = new TLatex(0.525, 0.902, \"L_{int} = 19.4 fb^{ -1}, SF\");\n s->lumi = new TLatex(0.92, 0.9, \"19.4 fb^{-1} (8 TeV)\");\n //~ s->cms = new TLatex(0.21, 0.902, \"#bf{CMS} #sqrt{s} = 8 TeV\");\n //~ s->cmsprelim = new TLatex(0.20, 0.80, \"Preliminary\");\n //~ s->cms = new TLatex(0.20, 0.84, \"CMS\");\n //~ s->excluded = new TLatex(0.35, 0.25, \"Excluded\");\n //~ s->excluded = new TLatex(0.2, 0.225, \"Excluded\");\n s->smooth_flag=2;\n s->smooth_points=5;\n s->second_smooth=3;\n s->PostExclusionPlotting=Draw_Fixed_Edge_CoverUp;\n s->iCLsObsExcl=0; \n s->iCLsExpExcl=0; \n s->iCLsExpExclm1=0;\n s->iCLsExpExclp1=0;\n s->iCLsExpExclm2=0;\n s->iCLsExpExclp2=0;\n s->iCLsObsTheom1=0;\n s->iCLsObsTheop1=0;\n\n //~ s->MinXsecZ=0.02;\n //~ s->MaxXsecZ=1.5;\n s->MinXsecZ=0.1;\n s->MaxXsecZ=10;\n //~ s->MaxXsecZ=20;\n\n SetDefault(s);\n\n return s;\n}\n" }, { "alpha_fraction": 0.4502502679824829, "alphanum_fraction": 0.6818943619728088, "avg_line_length": 81.95458984375, "blob_id": "b2d9132596381284f831b351c3c5bc639d3861f6", "content_id": "1e1a0c6f32daed73c925dfbf813a8d392e71aee7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 89508, "license_type": "no_license", "max_line_length": 155, "num_lines": 1079, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_R_firstguess.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:38 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,0.1902346);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,0.1925773);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(584,16.48655);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,18.32911);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,21.6851);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,24.08134);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,13.47981);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,12.0024);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,12.521);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,12.68614);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,13.97395);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,14.34505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,14.99244);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,17.52649);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,20.4781);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,23.1797);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,35.27436);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,14.79111);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,15.60894);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,16.43723);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,15.25626);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,16.6976);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,17.46697);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,19.27302);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,21.60221);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,25.46566);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,43.3769);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,17.3732);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,21.33653);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,21.65752);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,22.40835);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,22.263);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,23.18926);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,24.3097);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,26.64535);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,51.81732);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,23.414);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,26.69055);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,26.52904);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,22.77187);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,24.47649);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,26.69767);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,28.9048);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,51.22422);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,33.2426);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,30.65543);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,31.76783);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,30.7213);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,34.32911);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,75.7579);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,36.59754);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,35.0339);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,36.36063);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,38.13636);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,39.75341);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,108.3234);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,71.75253);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,45.46978);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,46.75837);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,44.50319);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,98.18301);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,54.72151);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,56.66692);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,53.17992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,156.5638);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,72.00787);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,69.77341);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,156.8306);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,243.8877);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.18,0.912,\"#bf{CMS} #sqrt{s} = 8 TeV\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(29,0.1902346);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(30,0.1925773);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(31,0.2296219);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(32,0.2190979);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(33,0.291672);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(34,0.3445514);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(47,4.101869);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(48,4.937451);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(49,5.763449);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(50,7.575736);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(51,8.698775);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(52,10.83253);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(53,12.67337);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(54,16.56012);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(57,0.195605);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(58,0.1915949);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(59,0.19996);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__6->SetBinContent(60,0.2129968);\n 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[GeV]->SetBinContent(103,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(104,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(105,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(106,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(107,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(108,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(109,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(110,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(111,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(112,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(113,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(116,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(117,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(118,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(119,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(120,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(121,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(122,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(123,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(124,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(125,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(126,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(127,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(140,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(141,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(143,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(144,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(145,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(146,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(147,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(148,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(149,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(150,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(151,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(152,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(153,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(164,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(165,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(188,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(189,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(212,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(213,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(236,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(237,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(260,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(261,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(284,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(285,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(308,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(309,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(332,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(333,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(356,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(357,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(380,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(381,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(404,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(405,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(428,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(429,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(452,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(453,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(476,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,nan);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,nan);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(51);\n palette->SetFillStyle(1001);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Signal contamination / Signal yield [%]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n \n TH2F 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5 = new TH2F(\"92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5\",\"\",21,187.5,712.5,25,87.5,712.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(24,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(25,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(26,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(27,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(28,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(29,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(30,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(31,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(32,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(33,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(34,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(35,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(36,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(37,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(38,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(39,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(40,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(41,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(42,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(43,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(44,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(47,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(48,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(49,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(50,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(51,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(52,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(53,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(54,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(55,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(56,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(57,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(58,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(59,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(60,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(61,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(62,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(63,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(64,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(65,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(66,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(67,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(70,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(71,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(72,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(73,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(74,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(75,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(76,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(77,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(78,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(79,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(80,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(81,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(82,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(83,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(84,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(85,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(86,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(87,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(88,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(89,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(90,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(93,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(94,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(95,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(96,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(97,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(98,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(99,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(100,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(101,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(102,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(103,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(104,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(105,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(106,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(107,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(108,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(109,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(110,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(111,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(112,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(113,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(116,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(117,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(118,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(119,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(120,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(121,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(122,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(123,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(124,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(125,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(126,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(127,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(128,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(129,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(130,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(131,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(132,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(133,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(134,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(135,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(136,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(140,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(141,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(142,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(143,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(144,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(145,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(146,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(147,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(148,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(149,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(150,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(151,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(152,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(153,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(154,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(155,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(156,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(157,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(158,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(159,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(164,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(165,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(166,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(167,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(168,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(169,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(170,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(171,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(172,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(173,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(174,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(175,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(176,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(177,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(178,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(179,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(180,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(181,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(182,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(188,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(189,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(190,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(191,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(192,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(193,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(194,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(195,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(196,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(197,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(198,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(199,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(200,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(201,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(202,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(203,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(204,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(205,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(212,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(213,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(214,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(215,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(216,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(217,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(218,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(219,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(220,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(221,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(222,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(223,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(224,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(225,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(226,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(227,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(228,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(236,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(237,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(238,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(239,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(240,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(241,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(242,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(243,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(244,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(245,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(246,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(247,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(248,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(249,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(250,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(251,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(260,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(261,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(262,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(263,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(264,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(265,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(266,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(267,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(268,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(269,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(270,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(271,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(272,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(273,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(274,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(284,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(285,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(286,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(287,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(288,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(289,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(290,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(291,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(292,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(293,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(294,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(295,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(296,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(297,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(308,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(309,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(310,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(311,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(312,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(313,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(314,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(315,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(316,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(317,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(318,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(319,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(320,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(332,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(333,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(334,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(335,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(336,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(337,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(338,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(339,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(340,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(341,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(342,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(343,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(356,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(357,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(358,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(359,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(360,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(361,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(362,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(363,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(364,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(365,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(366,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(380,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(381,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(382,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(383,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(384,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(385,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(386,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(387,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(388,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(389,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(404,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(405,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(406,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(407,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(408,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(409,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(410,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(411,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(412,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(428,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(429,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(430,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(431,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(432,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(433,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(434,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(435,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(452,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(453,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(454,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(455,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(456,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(457,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(458,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(476,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(477,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(478,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(479,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->SetBinContent(480,-inf);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetXaxis()->SetNdivisions(505);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetXaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetXaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetXaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetXaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetXaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetYaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetYaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetYaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetYaxis()->SetTitleOffset(1.8);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetYaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetZaxis()->SetTitle(\"Signal contamination / Signal yield [%]\");\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetZaxis()->SetLabelFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetZaxis()->SetLabelOffset(0.007);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetZaxis()->SetTitleSize(0.045);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetZaxis()->SetTitleOffset(1.5);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->GetZaxis()->SetTitleFont(42);\n 92487217_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__5->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4457482099533081, "alphanum_fraction": 0.6761906743049622, "avg_line_length": 82.88858032226562, "blob_id": "7e9f1b1eaa5e8b20bd5fd09ab4e2e785b06a67b9", "content_id": "1abc96114b179a21f40d07fe418ca88563d5b15d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 91103, "license_type": "no_license", "max_line_length": 157, "num_lines": 1086, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_AcceptanceCorrected.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:24 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,-31.57895);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,-52.17391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,-91.16288);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,-311.4502);\n 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(417,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(418,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(436,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(437,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(438,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(439,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(440,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(441,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(442,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(443,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(444,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(445,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(446,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(459,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(460,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(461,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(462,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(463,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(464,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(465,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(466,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(467,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(468,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(469,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(470,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(471,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(472,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(473,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(474,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(488,-2197.802);\n 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(517,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(518,-3992.804);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(519,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(520,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(521,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(522,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(523,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(528,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(529,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(530,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(546,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(547,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(551,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(552,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(553,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(554,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(555,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(556,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(557,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(575,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(576,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(577,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(578,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(579,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,-23998.52);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(-99900);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(-99900);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,-100899);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,-100799.1);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,-100699.2);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,-100599.3);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,-100499.4);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,-100399.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,-100299.6);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,-100199.7);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,-100099.8);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,-99999.9);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,-99900);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,-99800.1);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,-99700.2);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,-99600.3);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,-99500.4);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,-99400.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,-99300.6);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,-99200.7);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,-99100.8);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,-99000.9);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(19);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. [%]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(29,-31.57895);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(30,-52.17391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(31,-91.16288);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(32,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(33,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(34,-311.4502);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(35,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(36,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(37,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(38,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(39,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(40,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(41,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(42,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(43,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(44,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(45,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(46,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(47,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(48,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(49,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(50,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(51,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(52,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(53,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(54,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(57,-31.57895);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(58,-52.17391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(59,-83.79888);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(60,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(61,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(62,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(63,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(64,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(65,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(66,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(67,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(68,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(69,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(70,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(71,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(72,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(73,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(74,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(75,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(76,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(77,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(78,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(79,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(80,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(81,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(82,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(85,-31.57895);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(86,-52.17391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(87,-83.79888);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(88,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(89,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(90,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(91,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(92,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(93,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(94,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(95,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(96,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(97,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(98,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(99,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(100,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(101,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(102,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(103,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(104,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(105,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(106,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(107,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(108,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(109,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(110,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(113,-31.57895);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(114,-52.17391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(115,-83.79888);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(116,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(117,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(118,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(119,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(120,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(121,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(122,-1213);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(123,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(124,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(125,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(126,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(127,-5265.354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(128,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(129,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(130,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(131,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(132,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(133,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(134,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(135,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__16->SetBinContent(149,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(150,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(151,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(152,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(153,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(154,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(155,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(156,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(157,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(158,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(159,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__16->SetBinContent(198,-52.17391);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(199,-83.79888);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(200,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(201,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(202,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(203,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(204,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(205,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(206,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(207,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(208,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(209,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(210,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(211,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(212,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(213,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(214,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(215,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(216,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(217,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(218,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(219,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(220,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(221,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(222,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(227,-83.79888);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(228,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(229,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(230,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(231,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(232,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(233,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(234,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(235,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(236,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(237,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(238,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(239,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(240,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(241,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(242,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(243,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(244,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(245,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(246,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(247,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(248,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(249,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(250,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(256,-130.1518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(257,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(258,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(259,-437.7585);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(260,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(261,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(262,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(263,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(264,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(265,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(266,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(267,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(268,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(269,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(270,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(271,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(272,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(273,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(274,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(275,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(276,-47848.53);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(277,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(278,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(285,-197.3684);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(286,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(287,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(288,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(289,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(290,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(291,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(292,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(293,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(294,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(295,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(296,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(297,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(298,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(299,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(300,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(301,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(302,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(303,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(304,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(305,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(306,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(314,-292.6829);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(315,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(316,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(317,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(318,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(319,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(320,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(321,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(322,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(323,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(324,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(325,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(326,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(327,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(328,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(329,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(330,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(331,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(332,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(333,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(334,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(343,-425.5319);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(344,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(345,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(346,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(347,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(348,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(349,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(350,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(351,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(352,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(353,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(354,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(355,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(356,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(357,-23998.52);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(358,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(359,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(360,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(361,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(362,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(372,-607.2875);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(373,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(374,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(375,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(376,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(377,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(378,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(379,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(380,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(381,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(382,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(383,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(384,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(385,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(386,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(387,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(388,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(389,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(390,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(401,-854.7009);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(402,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(403,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(404,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(405,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(406,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(407,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(408,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(409,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(410,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(411,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(412,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(413,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(414,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(415,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(416,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(417,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(418,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(430,-1183.432);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(431,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(432,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(433,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(434,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(435,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(436,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(437,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(438,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(439,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(440,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(441,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(442,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(443,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(444,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(445,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(446,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(459,-1630.435);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(460,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(461,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(462,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(463,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(464,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(465,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(466,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(467,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(468,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(469,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(470,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(471,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(472,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(473,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(474,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(488,-2197.802);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(489,-2955.665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(490,-3921.569);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(491,-5172.414);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(492,-6795.017);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(493,-8836.524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(494,-11428.57);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(495,-14634.15);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(496,-18750);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(497,-23622.05);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(498,-30000);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(499,-37500);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(500,-47244.09);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(501,-59405.94);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__16->SetBinContent(502,-73710.07);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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161, "num_lines": 745, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_20/Fixed_Edge_sbottom_neutralino2_Xsection.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Sat Jun 28 21:01:31 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",0,0,900,800);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 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[GeV]->SetBinContent(381,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(382,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(383,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(384,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(385,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(386,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(387,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(388,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(389,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(404,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(405,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(406,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(407,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(408,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(409,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(410,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(428,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(429,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(452,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(453,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(454,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(455,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.007326);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20.9);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.007326);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.01090513);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01623285);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.02416344);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.03596854);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.05354103);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.0796986);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.1186355);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.1765951);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.262871);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3912971);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.582466);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.8670308);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.29062);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.921155);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.859739);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,4.25687);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,6.336572);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,9.432316);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,14.04049);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"NLO cross section [pb]\");\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n \n TH2F 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1 = new TH2F(\"48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1\",\"\",21,187.5,712.5,25,87.5,712.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(24,19);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(25,10.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(26,5.72);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(27,3.37);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(28,2.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(29,1.29);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(30,0.831);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(31,0.548);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(32,0.368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(33,0.253);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(34,0.176);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(35,0.124);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(36,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(37,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(38,0.04875);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(39,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(40,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(41,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(42,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(43,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(44,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(47,19);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(48,10.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(49,5.72);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(50,3.37);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(51,2.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(52,1.29);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(53,0.831);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(54,0.548);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(55,0.368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(56,0.253);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(57,0.176);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(58,0.124);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(59,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(60,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(61,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(62,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(63,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(64,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(65,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(66,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(67,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(70,19);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(71,10.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(72,5.72);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(73,3.37);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(74,2.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(75,1.29);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(76,0.831);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(77,0.548);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(78,0.368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(79,0.253);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(80,0.176);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(81,0.124);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(82,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(83,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(84,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(85,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(86,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(87,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(88,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(89,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(90,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(93,19);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(94,10.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(95,5.72);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(96,3.37);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(97,2.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(98,1.29);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(99,0.831);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(100,0.548);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(101,0.368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(102,0.253);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(103,0.176);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(104,0.124);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(105,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(106,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(107,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(108,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(109,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(110,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(111,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(112,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(113,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(116,19);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(117,10.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(118,5.72);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(119,3.37);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(120,2.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(121,1.29);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(122,0.831);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(123,0.548);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(124,0.368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(125,0.253);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(126,0.176);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(127,0.124);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(128,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(129,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(130,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(131,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(132,0.0254);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(133,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(134,0.0144);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(135,0.0106);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(136,0.00814);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(140,10.1);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(141,5.72);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(142,3.37);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(143,2.05);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(144,1.29);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(145,0.831);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(146,0.548);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(147,0.368);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(148,0.253);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(149,0.176);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(150,0.124);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(151,0.0883);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(152,0.0635);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(153,0.0463);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(154,0.034);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(155,0.0259);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->SetBinContent(156,0.0188);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_M_{neutralino 2} [GeV]__1->GetZaxis()->SetTitleSize(0.045);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->GetZaxis()->SetTitleOffset(1.5);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->GetZaxis()->SetTitleFont(42);\n 48134369_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__1->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.3841356337070465, "alphanum_fraction": 0.6026886701583862, "avg_line_length": 87.73442077636719, "blob_id": "341f9a6a4f06f53f388278def80f2f4f0913b0ce", "content_id": "eebaf2e64c600df21ee6d7b356514b289823b07d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 59807, "license_type": "no_license", "max_line_length": 182, "num_lines": 674, "path": "/LimitPlotting/results/Fixed_Neutralino_sbottom_neutralino2_ExpR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Tue Nov 4 13:39:08 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,22.5,881.8548,789.1667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(196,0.344488);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,0.405907);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,0.558884);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,0.750723);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,0.981869);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,1.22759);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,1.61589);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,2.1663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,2.69974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,3.46849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,0.128678);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,0.112247);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,0.130083);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,0.165364);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,0.225139);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,0.288438);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,0.399479);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,0.489184);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,0.660161);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,0.950768);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,1.12101);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,1.4896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,1.89385);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,2.47826);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,3.08283);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,0.158463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,0.151403);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,0.166247);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,0.205908);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,0.269323);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,0.340903);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,0.455456);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,0.599163);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,0.81556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,1.04085);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,1.34267);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,1.80749);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,2.25552);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,2.88502);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,0.191682);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,0.182158);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,0.207777);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,0.268922);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,0.370341);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,0.429993);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,0.588483);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,0.733283);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,0.994532);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,1.29371);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,1.7491);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,2.16897);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,2.83242);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,0.235142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,0.238915);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,0.269817);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,0.34123);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(290,0.435418);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(291,0.554667);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(292,0.731213);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(293,0.967917);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(294,1.24806);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(295,1.59733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(296,2.10475);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(297,2.56111);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(310,0.269758);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(311,0.314553);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(312,0.349855);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,0.427427);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,0.53752);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,0.716436);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,0.914963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,1.18924);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,1.55939);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,2.04384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,2.61092);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,0.365374);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,0.40974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(336,0.474212);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(337,0.54161);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(338,0.699398);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(339,0.877721);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(340,1.15903);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(341,1.53786);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(342,1.91065);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(343,2.49109);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(358,0.426368);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(359,0.521392);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(360,0.572027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(361,0.699356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(362,0.904748);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(363,1.12805);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(364,1.48653);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(365,1.93331);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(366,2.4898);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(382,0.542148);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(383,0.67716);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(384,0.745845);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(385,0.909333);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(386,1.13891);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(387,1.44444);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(388,1.87067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(389,2.42181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(406,0.715915);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(407,0.861873);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(408,0.944193);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(409,1.17131);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(410,1.45373);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(411,1.87443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(412,2.31018);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(430,0.861459);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,1.1343);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,1.22971);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,1.49898);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,1.82801);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,2.38557);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,1.12208);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,1.46454);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,1.64707);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,1.90487);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,2.36975);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,1.40835);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,1.8612);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,2.0794);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,2.41547);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,1.8013);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,2.3694);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,2.55512);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,2.26257);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,3.0364);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,2.89864);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.02749356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(7.322546);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.02749356);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.03634984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.04805893);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.06353977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.08400733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.1110679);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.1468454);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.1941475);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.2566867);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,0.3393712);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,0.4486901);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,0.5932232);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,0.7843134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,1.036958);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,1.370985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,1.81261);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,2.396491);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,3.168454);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,4.189083);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,5.538479);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(24,0.0384532);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(25,0.0515494);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(26,0.0551191);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(27,0.0588721);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(28,0.071484);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(29,0.0896932);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(30,0.0968733);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(31,0.125328);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(32,0.154821);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(33,0.205647);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(34,0.259775);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(35,0.356809);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(36,0.447909);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(37,0.587493);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(38,0.77378);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(39,0.99385);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(40,1.28255);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(41,1.60243);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(42,2.24982);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(43,2.79143);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(44,3.54478);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(47,0.0305484);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(48,0.0326598);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(49,0.044115);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(50,0.0481771);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(51,0.0546393);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(52,0.0650672);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(53,0.090607);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(54,0.106068);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(55,0.149317);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(56,0.19344);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(57,0.26631);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(58,0.305955);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(59,0.409541);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(60,0.497908);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(61,0.681481);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(62,0.885237);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(63,1.17945);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(64,1.5431);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(65,2.01357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(66,2.5476);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(67,3.40407);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(70,0.0405074);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(71,0.0519977);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(72,0.0558196);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(73,0.0694443);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(74,0.0768308);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(75,0.101511);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(76,0.11779);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(77,0.173142);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(78,0.19815);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(79,0.271459);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(80,0.338657);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(81,0.438455);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(82,0.559203);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(83,0.732556);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(84,0.996922);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(85,1.34067);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(86,1.64985);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(87,2.08176);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(88,2.91792);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(89,3.48064);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(90,4.62644);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(94,0.05528);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(95,0.0687706);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(96,0.0759167);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(97,0.0920199);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(98,0.113833);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(99,0.157806);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(100,0.196028);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(101,0.257486);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(102,0.381314);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(103,0.486569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(104,0.624812);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(105,0.765035);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(106,0.995234);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(107,1.31951);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(108,1.74963);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(109,2.24807);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(110,2.97128);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(111,3.73974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(112,5.0632);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(113,6.44768);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(118,0.0649676);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(119,0.103596);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(120,0.106516);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(121,0.135569);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(122,0.182016);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(123,0.221031);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(124,0.299634);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(125,0.400648);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(126,0.551034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(127,0.717107);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(128,0.849742);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(129,1.15725);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(130,1.49547);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(131,1.96401);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(132,2.46151);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(133,3.07448);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(134,4.08412);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(135,5.29743);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(136,6.65686);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(142,0.0977536);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(143,0.0990858);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(144,0.116282);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(145,0.124255);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(146,0.160629);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(147,0.229849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(148,0.297184);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(149,0.380517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(150,0.48494);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(151,0.644392);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(152,0.84297);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(153,1.1144);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(154,1.41843);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(155,1.81439);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(156,2.38134);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(157,3.009);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(158,3.97929);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(159,4.92015);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(166,0.113163);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(167,0.0991564);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(168,0.103989);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(169,0.127228);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(170,0.157739);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(171,0.226357);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(172,0.308559);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(173,0.392066);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(174,0.490896);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(175,0.65794);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(176,0.874006);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(177,1.17538);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(178,1.43647);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(179,1.91463);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(180,2.45901);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(181,3.12925);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(182,3.89108);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(190,0.134388);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(191,0.10377);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(192,0.113517);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(193,0.135745);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(194,0.185609);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(195,0.238027);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(196,0.344488);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(197,0.405907);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(198,0.558884);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(199,0.750723);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(200,0.981869);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(201,1.22759);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(202,1.61589);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(203,2.1663);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(204,2.69974);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(205,3.46849);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(214,0.128678);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(215,0.112247);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(216,0.130083);\n 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266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(363,0.1693271);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(364,0.1468958);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(365,0.1451363);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(366,0.1381024);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(380,1.579673);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(381,0.6546077);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(382,0.4761649);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(383,0.37319);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(384,0.2832533);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(385,0.2167286);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(386,0.1992781);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(387,0.1660147);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(388,0.1578764);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(389,0.1497337);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(404,1.683166);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(405,0.5890076);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(406,0.4748852);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(407,0.3488876);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(408,0.278605);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(409,0.2280891);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(410,0.1880366);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,0.1590562);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,0.1537206);\n 266647745_M_{sbottom} 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266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,0.2718202);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,0.2161022);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,0.1773136);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,1.577773);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,0.5962828);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,0.477144);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,0.3342542);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,0.2413853);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,0.215605);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,1.570706);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,0.556574);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,0.433512);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,0.3159659);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,0.2577865);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,1.533456);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,0.5138338);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,0.4221789);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,0.314029);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,0.4157453);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,0.5613527);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,0.4356406);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,0.510902);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,0.5499742);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,1.490076);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8 = new TH2F(\"266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8\",\"\",21,187.5,712.5,25,87.5,712.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(24,2.014551);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(25,1.466197);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(26,0.8381402);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(27,0.7077708);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(28,0.5001262);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(29,0.353509);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(30,0.294528);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(31,0.2620969);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(32,0.2232513);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(33,0.1991664);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(34,0.1744822);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(35,0.1538468);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(36,0.1480093);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(37,0.1344346);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(38,0.1278923);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(39,0.1213501);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(40,0.1195565);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(41,0.1150376);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(42,0.1067875);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(43,0.1061452);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(44,0.106831);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(47,1.649137);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_M_{neutralino 2} [GeV]__8->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4262063205242157, "alphanum_fraction": 0.6565728187561035, "avg_line_length": 45.80132293701172, "blob_id": "98476f8b5470bf53db0c6322a6259e007533b6c6", "content_id": "5ebaabac0e37cda87a5a48b4d54389939c4b83af", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 7067, "license_type": "no_license", "max_line_length": 177, "num_lines": 151, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Direct_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 14:25:29 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(69.08783,-30.40541,761.6554,797.2973);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",41,193.75,706.25,49,93.75,706.25);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(32);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(43);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(32);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(43);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(32);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(43);\n 152184707_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(30);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,382.3617189,100);\n graph->SetPoint(1,384.3062154,110.9956622);\n graph->SetPoint(2,387.5,119.4027168);\n graph->SetPoint(3,390.5482846,127.9107153);\n graph->SetPoint(4,391.8175625,137.5);\n graph->SetPoint(5,390.5482846,147.0892847);\n graph->SetPoint(6,387.5,156.25);\n graph->SetPoint(7,384.1607153,165.4107153);\n graph->SetPoint(8,381.25,175);\n graph->SetPoint(9,378.1937847,184.4437847);\n graph->SetPoint(10,373.8882812,192.6382812);\n graph->SetPoint(11,367.7837812,199.0337812);\n graph->SetPoint(12,360.2645034,204.0145034);\n graph->SetPoint(13,352.0899966,208.3399966);\n graph->SetPoint(14,343.75,212.5);\n graph->SetPoint(15,335.4100034,216.6600034);\n graph->SetPoint(16,327.0899966,220.8399966);\n graph->SetPoint(17,318.6044999,224.8545);\n graph->SetPoint(18,309.4437847,228.1937847);\n graph->SetPoint(19,299.0337812,230.2837813);\n graph->SetPoint(20,287.5,230.9589999);\n graph->SetPoint(21,275.9662188,230.2837813);\n graph->SetPoint(22,265.5562153,228.1937847);\n graph->SetPoint(23,256.25,225);\n graph->SetPoint(24,247.0635045,221.6607153);\n graph->SetPoint(25,237.3803622,218.7757803);\n graph->SetPoint(26,227.6600395,215.9847028);\n graph->SetPoint(27,219.1515959,212.8960939);\n graph->SetPoint(28,210.9088591,210.0175204);\n graph->SetPoint(29,200,208.2979194);\n graph->Draw(\"l\");\n \n graph = new TGraph(30);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,382.3617189,100);\n graph->SetPoint(1,384.3062154,110.9956622);\n graph->SetPoint(2,387.5,119.4027168);\n graph->SetPoint(3,390.5482846,127.9107153);\n graph->SetPoint(4,391.8175625,137.5);\n graph->SetPoint(5,390.5482846,147.0892847);\n graph->SetPoint(6,387.5,156.25);\n graph->SetPoint(7,384.1607153,165.4107153);\n graph->SetPoint(8,381.25,175);\n graph->SetPoint(9,378.1937847,184.4437847);\n graph->SetPoint(10,373.8882812,192.6382812);\n graph->SetPoint(11,367.7837812,199.0337812);\n graph->SetPoint(12,360.2645034,204.0145034);\n graph->SetPoint(13,352.0899966,208.3399966);\n graph->SetPoint(14,343.6044999,212.3545);\n graph->SetPoint(15,334.5892847,215.8392847);\n graph->SetPoint(16,325,218.75);\n graph->SetPoint(17,315.4107153,221.6607153);\n graph->SetPoint(18,306.25,225);\n graph->SetPoint(19,296.9437847,228.1937847);\n graph->SetPoint(20,286.6792813,230.1382812);\n graph->SetPoint(21,275.8207187,230.1382812);\n graph->SetPoint(22,265.5562153,228.1937847);\n graph->SetPoint(23,256.25,225);\n graph->SetPoint(24,247.0635045,221.6607153);\n graph->SetPoint(25,237.3803622,218.7757803);\n graph->SetPoint(26,227.6600395,215.9847028);\n graph->SetPoint(27,219.1515959,212.8960939);\n graph->SetPoint(28,210.9088591,210.0175204);\n graph->SetPoint(29,200,208.2979194);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Expected limit\",100,180.8182,410.9993);\n Graph_Graph1->SetMinimum(86.98617);\n Graph_Graph1->SetMaximum(243.1521);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.7365313768386841, "alphanum_fraction": 0.7719557285308838, "avg_line_length": 32.875, "blob_id": "718ba1eb5a87df5d0bf3fa37290897031206c68f", "content_id": "ebefbe36a8046de6ec5cd27de58f874dd6c33668", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 1355, "license_type": "no_license", "max_line_length": 47, "num_lines": 40, "path": "/LimitPlotting/OldExclusionContours.h", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "#ifndef OLDEXCLUSIONCONTOURS_H\n#define OLDEXCLUSIONCONTOURS_H\n\nclass TGraph;\n\nTGraph Obs_7TeV_Bino2j_squark_gluino();\nTGraph* Exp_7TeV_Bino2j_squark_gluino();\nTGraph* Obs_7TeV_Wino2j_squark_gluino();\nTGraph* Exp_7TeV_Wino2j_squark_gluino();\nTGraph* Obs_8TeV_Bino2j_squark_gluino();\nTGraph* Exp_8TeV_Bino2j_squark_gluino();\nTGraph* Obs_8TeV_Wino2j_squark_gluino();\nTGraph* Exp_8TeV_Wino2j_squark_gluino();\n\nTGraph* Obs_Bino_Single78corr_squark_gluino();\nTGraph* Exp_Bino_Single78corr_squark_gluino();\nTGraph* Obs_Wino_Single78corr_squark_gluino();\nTGraph* Exp_Wino_Single78corr_squark_gluino();\nTGraph* Obs_Bino_Single78unco_squark_gluino();\nTGraph* Exp_Bino_Single78unco_squark_gluino();\nTGraph* Obs_Wino_Single78unco_squark_gluino();\nTGraph* Exp_Wino_Single78unco_squark_gluino();\n\n\nTGraph* Obs_7TeV_DiPhoton_Bino_squark_gluino();\nTGraph* Exp_7TeV_DiPhoton_Bino_squark_gluino();\nTGraph* Obs_7TeV_DiPhoton_Wino_squark_gluino();\nTGraph* Exp_7TeV_DiPhoton_Wino_squark_gluino();\nTGraph* Obs_8TeV_DiPhoton_Bino_squark_gluino();\nTGraph* Exp_8TeV_DiPhoton_Bino_squark_gluino();\nTGraph* Obs_8TeV_DiPhoton_Wino_squark_gluino();\nTGraph* Exp_8TeV_DiPhoton_Wino_squark_gluino();\n\nTGraph* Obs_Bino_DiP78unco_squark_gluino();\nTGraph* Exp_Bino_DiP78unco_squark_gluino();\nTGraph* Obs_Wino_DiP78unco_squark_gluino();\nTGraph* Exp_Wino_DiP78unco_squark_gluino();\n\n\n#endif\n" }, { "alpha_fraction": 0.44722017645835876, "alphanum_fraction": 0.6842414736747742, "avg_line_length": 82.58294677734375, "blob_id": "01366c1ebca2848fcc43ee4733b682e9a5ae8b25", "content_id": "cb5057e0afff7829d9858601979a5a9868887c95", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 90186, "license_type": "no_license", "max_line_length": 155, "num_lines": 1079, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10_Limits_not_complete/Fixed_Edge_sbottom_neutralino2_ExpXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 10:43:38 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,4.249654);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,2.343067);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,1.72894);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,1.038333);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,0.8866829);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(34,0.7063295);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(35,0.5450284);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(36,0.4962862);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(37,0.4041407);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(38,0.3558359);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(39,0.3214764);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(40,0.2871168);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(41,0.2543083);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(42,0.232026);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(43,0.2094357);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(44,0.2010547);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(45,0.1901356);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,0.1649041);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,0.1699159);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,0.1614218);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(49,0.1490078);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(50,0.1534828);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(51,0.1404155);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(52,0.1401915);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(53,0.1310394);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(54,0.1383898);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(57,3.919225);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(58,2.203342);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(59,1.512035);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(60,0.9819162);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(61,0.8151699);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(62,0.5774624);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(63,0.5102015);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(64,0.3969083);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(65,0.3582432);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(66,0.2989647);\n 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(79,0.1323936);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(80,0.1307189);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(81,0.1236578);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(82,0.1250695);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(85,3.506108);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(86,2.145601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(87,1.607642);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(88,1.043072);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(89,0.7366376);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(90,0.5995269);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(91,0.4704324);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(92,0.4050029);\n 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(119,0.4693016);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(120,0.4019036);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(121,0.317278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(122,0.2930506);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(123,0.2459109);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(124,0.2193429);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(125,0.2093965);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(126,0.1924801);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(127,0.179695);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(128,0.1704923);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(129,0.1600994);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(586,0.1780755);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,2.15663);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,0.9401638);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,0.6545595);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,0.5285023);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,0.4222112);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,0.3635299);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,0.297954);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,0.2468624);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,0.2347887);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,0.2187751);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,0.1907992);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,2.338171);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,0.7898625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,0.6285095);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,0.5345568);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,0.3992931);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,0.345872);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,0.2877968);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,0.2495779);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,0.2194164);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.2076766);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,2.178141);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,0.7279837);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,0.6931008);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,0.5812677);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.4875317);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.394585);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.3195505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.2434625);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.2099029);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,1.948111);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,0.7611296);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,0.6537147);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,0.5283719);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.3577088);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.3203245);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.2699942);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.2378117);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,1.276767);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,0.642282);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.4924704);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.3994518);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.3067037);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.2749322);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,1.899818);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,0.68675);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,0.5390096);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.4543374);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.3946767);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.3120526);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,2.05336);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,1.193864);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,0.5931091);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.4734708);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.3524946);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,1.589976);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,0.6497955);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,0.5662986);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.4156431);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,1.863598);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,0.7262849);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,0.5507597);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,1.221492);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,1.892224);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected cross section limit [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex tex = new TLatex(0.18,0.912,\"#bf{CMS} #sqrt{s} = 8 TeV\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(29,4.249654);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(30,2.343067);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(31,1.72894);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(32,1.038333);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(33,0.8866829);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->SetBinContent(34,0.7063295);\n 416758881_M_{sbottom} 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416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__8->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.44804221391677856, "alphanum_fraction": 0.6835518479347229, "avg_line_length": 82.35970306396484, "blob_id": "2dfef1e589a4a7dd66b220d670539b327b1b0efb", "content_id": "a4b6d316fb3d027351b4b43ca91976356c7e78ad", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 90612, "license_type": "no_license", "max_line_length": 157, "num_lines": 1087, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_5/Fixed_Edge_sbottom_neutralino2_R_firstguess.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 14:09:24 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", 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[GeV]->SetBinContent(725,59.38271);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,66.61267);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,148.8789);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,70.66177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,67.67919);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,70.38906);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,73.66183);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,77.01692);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,212.4688);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,84.74833);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,88.26247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,90.79641);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,86.14247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,192.3384);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,105.503);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,104.9861);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,102.874);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,308.6825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,139.3191);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,135.4076);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,414.8037);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,169.1426);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,476.7436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new 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[GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"R (first guess)\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(57,0.3791894);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(58,0.3699799);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(59,0.3850083);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(60,0.4132141);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(61,0.5130473);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(62,0.5467382);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(63,0.6801346);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(64,0.777905);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(65,0.9628115);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(66,1.12477);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(67,1.342573);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(80,18.06701);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(81,23.29348);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(82,28.15112);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(85,0.3377067);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(86,0.3422411);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(87,0.4332545);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(88,0.4385703);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(89,0.4558393);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(90,0.5682618);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(91,0.6459643);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(92,0.7836359);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(143,0.5780292);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(144,0.5387657);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(145,0.570302);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(146,0.6297587);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(147,0.7310993);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(148,0.7942519);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(149,0.9270043);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(150,1.110484);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(151,1.2216);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(152,1.606825);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(153,2.031518);\n 284060385_M_{sbottom} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(190,12.9784);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(191,14.77685);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(192,18.90124);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(193,22.84193);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(194,27.84322);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(198,1.083717);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(199,0.7333111);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(200,0.8028085);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(201,0.8631572);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(202,1.013025);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(203,0.8542921);\n 284060385_M_{sbottom} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(288,1.824724);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(289,1.680052);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(290,1.94593);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(291,2.194892);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(292,2.272022);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(293,2.90744);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(294,3.041412);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(295,3.716433);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(296,4.526915);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(297,5.286008);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(298,6.633169);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(318,2.131326);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(319,2.75018);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(320,2.783393);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(321,3.0665);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(322,3.385336);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(323,3.943237);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(324,4.884959);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(325,5.755529);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(326,6.841836);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(327,8.30984);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(328,9.573799);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(349,3.45096);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(350,3.757807);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(351,4.2697);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(352,5.04008);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(353,5.956571);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(354,7.266436);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(355,8.554387);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(356,10.70913);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(357,12.72029);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(358,15.38342);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(359,18.11027);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(360,21.70638);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(361,27.81687);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(362,33.12513);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(372,6.302882);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(373,3.37723);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(374,3.680946);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(375,3.636786);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(376,3.927488);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(377,3.783737);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(378,4.249803);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(379,5.259916);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(380,5.580298);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(381,6.81964);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(382,7.482098);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(383,9.430524);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(384,11.025);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(385,12.50722);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(386,15.98667);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(387,19.39473);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(388,23.13209);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(389,27.82515);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(390,33.94822);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(401,7.5353);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(414,16.56195);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(415,19.86836);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(416,24.18205);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(417,27.73193);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(418,35.27827);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(430,12.13664);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(431,5.405987);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(432,5.94518);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(433,6.704439);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(434,6.227612);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(435,6.573769);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(460,6.471471);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(461,6.901773);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(462,8.083872);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(463,7.615491);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(464,8.613837);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(465,9.079128);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(466,9.811038);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(467,11.11736);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(468,13.22681);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(469,15.36448);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(470,17.96223);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(604,47.32501);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(605,26.1605);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(606,23.23885);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(607,24.18247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(608,24.53822);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(609,27.14838);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(610,27.81716);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(611,28.98715);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(612,33.91463);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(613,39.69239);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(614,44.88209);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(664,41.37891);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(665,36.19105);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(666,41.06468);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(667,39.94375);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(668,43.55796);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(669,47.07314);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(670,51.57996);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(691,102.0108);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(692,45.26816);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(693,51.94821);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(694,49.46136);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(750,70.66177);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(751,67.67919);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(752,70.38906);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(753,73.66183);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(754,77.01692);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(778,212.4688);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(779,84.74833);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(780,88.26247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(781,90.79641);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(782,86.14247);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetBinContent(807,192.3384);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 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[GeV]_M_{neutralino 2} [GeV]__18->SetDirectory(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetZaxis()->SetTitle(\"R (first guess)\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__18->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.45058998465538025, "alphanum_fraction": 0.6826183199882507, "avg_line_length": 81.39894104003906, "blob_id": "f85a8a33022854a0f38f10fc813b2effe027b79b", "content_id": "b395c74501b69831be522a8e2337c32894a5ca57", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 62376, "license_type": "no_license", "max_line_length": 163, "num_lines": 757, "path": "/LimitPlotting/results/old/T6bbedge_70/Fixed_Edge_sbottom_neutralino2_ObsXsecLimit.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Fri Jun 27 19:47:03 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(35.08064,-37.5,881.8548,795.8333);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n 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[GeV]->SetBinContent(271,0.3373002);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(272,0.3268555);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(273,0.3054062);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(274,0.2937474);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(284,4.630868);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(285,1.891542);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(286,1.364133);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(287,0.9456233);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(288,0.7612955);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(289,0.5903252);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(290,0.5132045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(291,0.4296964);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(292,0.4150584);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(293,0.3597656);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(294,0.3480519);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(295,0.3274719);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(296,0.3192487);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(297,0.3092313);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(308,4.913425);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(309,1.857529);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(310,1.338786);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(311,0.9630398);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(312,0.7267734);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(313,0.5797842);\n 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[GeV]->SetBinContent(336,0.7209346);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(337,0.6063309);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(338,0.470611);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(339,0.4155084);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(340,0.3887502);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(341,0.3685651);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(342,0.3500438);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(343,0.3215162);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(356,4.997854);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(357,1.575643);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(358,1.209092);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(359,0.9042146);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 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266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(411,0.4132908);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(412,0.38216);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(428,4.022052);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(429,1.466465);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(430,1.106693);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(431,0.8551545);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(432,0.6893697);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(433,0.5561222);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(434,0.4721113);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(435,0.4086313);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(452,3.998139);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(453,1.587494);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(454,1.094334);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(455,0.8469926);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(456,0.6712041);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(457,0.5439538);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(458,0.4700459);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(476,4.053616);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(477,1.491282);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(478,1.221148);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(479,0.8493595);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(480,0.625647);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(481,0.5552319);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,4.128109);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,1.461061);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,1.111683);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(503,0.8137991);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(504,0.666692);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,4.056683);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,1.343387);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,1.030752);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,0.8323557);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,0.3148776);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,1.417443);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,1.099551);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(572,0.2586506);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(573,1.402579);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(596,4.011514);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(315);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.4 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7 = new TH2F(\"266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7\",\"\",21,187.5,712.5,25,87.5,712.5);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(24,4.784561);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(25,3.287863);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(26,2.250471);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(27,1.614604);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(28,1.191433);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(29,0.9011695);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(30,0.7483354);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(31,0.6678367);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(32,0.5603241);\n 266647745_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(33,0.4858511);\n 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,0.3859206);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,4.337781);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,1.34307);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,1.278006);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,1.081366);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,0.9051619);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,0.7326925);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,0.5921059);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,0.457832);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,0.4056545);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,4.051239);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,1.413126);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,1.273635);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,1.012109);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,0.6781712);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,0.5785358);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,0.5036567);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,0.4402649);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,2.466887);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,1.241956);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,0.917872);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,0.7544829);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,0.5794027);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,0.5231757);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,3.66014);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,1.372916);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,1.053355);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,0.8616277);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,0.7217268);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,0.6060865);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,4.11574);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,2.332046);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,1.082945);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,0.8838934);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,0.6799017);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,3.076144);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,1.301775);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,1.090578);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,0.8099015);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,3.774072);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,1.366742);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,1.06205);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,2.412383);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,3.762715);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(476);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.005);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.007569601);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.01145977);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.01734918);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.02626528);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,0.03976354);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,0.06019882);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,0.09113622);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,0.137973);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,0.2088801);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,0.3162278);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,0.4787436);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,0.7247797);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,1.097259);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,1.661162);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,2.514867);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,3.807308);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,5.763961);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,8.726177);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,13.21074);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS} #sqrt{s} = 8 TeV\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(25);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7 = new TH2F(\"416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7\",\"\",26,190,710,31,90,710);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(29,6.946533);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(30,4.200018);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(31,3.13472);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(32,1.891856);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(33,1.676384);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(34,1.329888);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(35,0.9730777);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(36,0.8719525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(37,0.7349519);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(38,0.6497002);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(39,0.5918264);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(40,0.5339525);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(41,0.4627284);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(42,0.4134764);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(43,0.3893528);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(44,0.3764105);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(45,0.3506159);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(46,0.3108362);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(47,0.3140079);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(48,0.2946061);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(49,0.2727198);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(50,0.282116);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(51,0.25912);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(52,0.2555875);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(53,0.2389933);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(54,0.2518907);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(57,7.142632);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(58,4.197971);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(59,2.715222);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(60,1.877492);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(61,1.513169);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(62,1.099589);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(63,0.9363697);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(64,0.7428396);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(65,0.6515459);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(66,0.5553932);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(67,0.5026689);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(68,0.4578284);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(69,0.3972203);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(70,0.3775864);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(71,0.3427197);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(72,0.3236354);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(73,0.3014665);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(74,0.2828112);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(75,0.275789);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(76,0.257504);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(77,0.2566011);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(78,0.261196);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(79,0.243316);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(80,0.2392769);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(81,0.226592);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(82,0.2295687);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(85,6.41383);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(86,3.997929);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(87,3.042241);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(88,1.972057);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(89,1.349164);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(90,1.111277);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(91,0.8785315);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(92,0.7510114);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(93,0.5962816);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(94,0.5111777);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(95,0.4650379);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(96,0.4053559);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(97,0.3880304);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(98,0.3569291);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(99,0.3174317);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(100,0.3044716);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(101,0.2922634);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(102,0.2749952);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(103,0.2646609);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(104,0.2457693);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(105,0.2404824);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(106,0.240276);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(107,0.227512);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(108,0.2229663);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(109,0.2141907);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(110,0.2072468);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(113,8.322769);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(114,4.83905);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(115,2.894108);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(116,1.887214);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->SetBinContent(117,1.52335);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__7->GetXaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetXaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetXaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetYaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetYaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetYaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetYaxis()->SetTitleOffset(1.8);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetYaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetZaxis()->SetTitle(\"95% CL cross section upper limit [pb]\");\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetZaxis()->SetLabelFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetZaxis()->SetLabelOffset(0.007);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetZaxis()->SetTitleSize(0.045);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetZaxis()->SetTitleOffset(1.5);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->GetZaxis()->SetTitleFont(42);\n 416758881_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__7->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4523552656173706, "alphanum_fraction": 0.6805118322372437, "avg_line_length": 81.59596252441406, "blob_id": "37c6c520b16dd2ec62311107bb2ed82103ad4b59", "content_id": "e032dbf4145fcb805ae0389862ad334e64041233", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 89947, "license_type": "no_license", "max_line_length": 157, "num_lines": 1089, "path": 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[GeV]->SetBinContent(460,3.34113);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(461,3.62337);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(462,4.22709);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(463,4.08791);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(464,4.42692);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(465,4.781);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(466,5.16519);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(467,5.9127);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(468,7.00368);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(469,8.11071);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(470,9.42735);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(471,11.7239);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(497,8.34697);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(498,10.8655);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(499,12.0679);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(500,13.217);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(501,17.0501);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(502,19.8929);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(517,12.1759);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(518,10.35383);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(519,6.05369);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(520,7.02553);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(521,6.65828);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(522,6.95118);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(523,7.4971);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(524,8.50918);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(525,9.38444);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(526,10.4873);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(527,12.6874);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(528,14.8276);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(529,17.3561);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(530,20.2774);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(546,18.0299);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(547,8.38075);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,7.22766);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,8.90466);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,9.0257);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(551,8.41246);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(552,9.65955);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(553,10.5086);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(554,12.673);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(555,13.5436);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(556,15.5993);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(557,17.3859);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,22.036);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(575,21.7637);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(576,9.58805);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(577,9.88947);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(578,10.7267);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(579,11.0099);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,10.424);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,12.4683);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,13.2467);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,15.2909);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,16.79);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,18.5965);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,21.9319);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,24.2873);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,13.7905);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,12.3035);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,12.906);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,12.8259);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,14.2102);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,14.6089);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,15.4651);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,17.9824);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,20.5073);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,23.1059);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,34.6387);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,15.1336);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,16.0531);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,16.4216);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,15.3305);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,17.0484);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,17.8647);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,19.7034);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,22.0181);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,25.1954);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,42.8932);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,18.2961);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,21.6831);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,19.0518);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,21.1526);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,20.9636);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,22.5592);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,24.641);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,26.2705);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,51.096);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,23.8225);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,26.4933);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,26.1834);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,23.3475);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,24.2015);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,27.0308);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,28.8688);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,61.9755);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,30.4786);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,32.4793);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,28.9261);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,31.592);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,31.3641);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,33.8918);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,78.0254);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,36.0606);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,35.163);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,36.3461);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,37.9912);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,37.80305);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,106.788);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,41.7806);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,43.9143);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,44.4552);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,41.7143);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,98.179);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,54.2152);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,52.1675);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,13.4687);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,149.583);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,67.4748);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,65.8483);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,205.331);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,84.6867);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,239.368);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.1733193);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(263.3048);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.1733193);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.2499928);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.3605854);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.5201022);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,0.7501866);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,1.082056);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,1.56074);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,2.251184);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,3.24707);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,4.683519);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,6.755428);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,9.743914);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,14.05446);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,20.27191);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,29.23986);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,42.17507);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,60.8326);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,87.74391);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,126.5603);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,182.5485);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12 = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(29,0.194374);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(30,0.192577);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(31,0.229622);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(32,0.216163);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(33,0.307555);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(34,0.353307);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(35,0.368816);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(36,0.484473);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(37,0.574934);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__12->SetBinContent(38,0.680413);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(442,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(443,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(444,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(445,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(446,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(459,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(460,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(461,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(462,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(463,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(464,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(465,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(546,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(547,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(548,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(549,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(550,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(551,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(552,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(553,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(554,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(555,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(556,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(557,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(575,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(576,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(577,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(578,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(579,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,nan);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,nan);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(32);\n palette->SetFillColor(51);\n palette->SetFillStyle(1001);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Signal contamination / Signal yield [%]\");\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(32);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(43);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n \n TH2F 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17 = new TH2F(\"284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17\",\"\",26,190,710,31,90,710);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(29,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(30,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(31,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(32,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(33,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(34,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(35,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(36,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(37,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(38,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(39,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(40,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(41,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(42,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(43,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(44,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(45,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(46,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(47,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(48,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(49,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(50,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(51,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(52,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(53,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(54,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(57,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(58,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(59,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(60,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(61,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(62,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(63,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(64,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(65,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(66,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(67,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(68,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(69,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(70,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(71,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(72,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(73,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(74,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(75,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(76,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(77,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(78,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(79,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(80,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(81,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(82,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(85,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(86,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(87,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(88,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(89,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(90,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(91,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(92,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(93,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(94,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(95,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(96,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(97,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(98,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(99,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(100,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(101,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(102,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(103,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(104,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(105,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(106,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(107,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(108,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(109,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(110,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(113,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(114,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(115,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(116,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(117,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(118,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(119,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(120,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(121,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(122,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(123,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(124,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(125,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(126,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(127,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(128,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(129,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(130,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(131,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(132,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(133,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(134,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(135,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(136,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(137,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(138,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(141,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(142,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(143,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(144,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(145,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(146,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(147,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(148,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(149,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(150,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(151,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(152,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(153,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(154,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(155,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(156,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(157,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(158,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(159,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(160,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(161,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(162,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(163,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(164,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(165,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(166,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(169,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(170,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(171,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(172,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(173,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(174,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(175,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(176,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(177,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(178,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(179,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(180,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(181,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(182,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(183,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(184,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(185,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(186,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(187,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(188,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(189,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(190,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(191,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(192,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(193,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(194,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(198,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(199,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(200,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(201,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(202,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(203,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(204,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(205,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(206,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(207,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(208,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(209,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(210,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(211,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(212,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(213,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(214,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(215,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(216,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(217,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(218,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(219,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(220,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(221,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(222,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(227,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(228,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(229,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(230,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(231,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(232,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(233,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(234,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(235,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(236,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(237,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(238,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(239,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(240,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(241,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(242,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(243,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(244,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(245,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(246,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(247,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(248,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(249,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(250,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(256,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(257,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(258,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]__17->SetBinContent(385,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(386,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(387,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(388,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(389,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(390,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(401,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(402,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(403,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(404,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(405,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(406,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(407,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(408,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(409,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(410,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(411,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(412,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(413,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(414,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(415,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(416,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(417,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(418,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(430,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(431,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(432,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(433,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(434,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(435,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(436,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(437,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(438,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(439,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(440,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(441,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(442,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(443,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(444,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(445,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(446,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(459,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(460,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(461,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(462,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(463,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(464,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(465,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(466,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(467,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(468,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(469,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(470,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(471,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(472,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(473,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(474,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(488,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(489,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(490,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(491,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(492,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(493,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(494,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(495,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(496,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(497,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(498,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(499,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(500,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(501,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(502,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(517,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(518,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(519,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(520,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(521,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(522,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(523,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(524,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(525,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(526,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(527,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(528,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(529,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(530,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(546,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(547,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(548,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(549,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(550,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(551,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(552,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(553,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(554,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__17->SetBinContent(555,-inf);\n 284060385_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(127,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(128,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(129,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(130,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(131,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(132,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(133,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(134,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(135,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(136,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(142,-183.0384);\n 211830561_m(#tilde{b}) 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211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(154,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(155,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(156,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(157,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(158,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(159,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(166,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(167,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(168,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(169,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(170,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(171,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(172,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(173,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(174,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(175,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(176,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(177,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(178,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(179,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(180,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(181,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(182,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(190,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(191,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(192,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(193,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(194,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(195,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(196,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(197,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(198,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(199,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(200,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(201,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(202,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(203,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(204,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(205,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(214,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(215,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(216,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(217,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(218,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(219,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(220,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(221,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(222,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(223,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(224,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(225,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(226,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(227,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(228,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(238,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(239,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(240,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(241,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(242,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(243,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(244,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(245,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(246,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(247,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(248,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(249,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(250,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(251,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(262,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(263,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(264,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(265,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(266,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(267,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(268,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(269,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(270,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(271,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(272,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(273,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(274,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(286,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(287,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(288,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(289,-7010.984);\n 211830561_m(#tilde{b}) 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211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(313,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(314,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(315,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(316,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(317,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(318,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(319,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(320,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(334,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(335,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) 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[GeV]->SetBinContent(430,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(431,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(432,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(433,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(434,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(435,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(454,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(455,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(456,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(457,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(458,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(-99900);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(-99900);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,-100899);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,-100799.1);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,-100699.2);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,-100599.3);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,-100499.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,-100399.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,-100299.6);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,-100199.7);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,-100099.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,-99999.9);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,-99900);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,-99800.1);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,-99700.2);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,-99600.3);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,-99500.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,-99400.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,-99300.6);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,-99200.7);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,-99100.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,-99000.9);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,137.5,754.8387,712.5,211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(19);\n palette->SetFillStyle(1001);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. [%]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.91,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.8,0.91,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4 = new TH2F(\"211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4\",\"\",21,187.5,712.5,23,137.5,712.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(24,-32.39741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(25,-60.5449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(26,-107.604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(27,-183.0384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(28,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(29,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(30,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(31,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(32,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(33,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(34,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(35,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(36,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(37,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(38,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(39,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(40,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(41,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(42,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(43,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(44,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(47,-32.39741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(48,-60.5449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(49,-107.604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(50,-183.0384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(51,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(52,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(53,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(54,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(55,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(56,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(57,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(58,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(59,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(60,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(61,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(62,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(63,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(64,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(65,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(66,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(67,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(70,-32.39741);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(71,-60.5449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(72,-107.604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(73,-183.0384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(74,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(75,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(76,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(77,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(78,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(79,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(80,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(81,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(82,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(83,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(84,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(85,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(86,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(87,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(88,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(89,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(90,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(94,-60.5449);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(95,-107.604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(96,-183.0384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(97,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(98,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(99,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(100,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(101,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(102,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(103,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(104,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(105,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(106,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(107,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(108,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(109,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(110,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(111,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(112,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(113,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(118,-107.604);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(119,-183.0384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(120,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(121,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(122,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(123,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(124,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(125,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(126,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(127,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(128,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(129,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(130,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(131,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(132,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(133,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(134,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(135,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(136,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(142,-183.0384);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(143,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(144,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(145,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(146,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(147,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(148,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(149,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(150,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(151,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(152,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(153,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(154,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(155,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(156,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(157,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(158,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(159,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(166,-300.6012);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(167,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(168,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(169,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(170,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(171,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(172,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(173,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(174,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(175,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(176,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(177,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(178,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(179,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(180,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(181,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(182,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(190,-478.8508);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(191,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(192,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(193,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(194,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(195,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(196,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(197,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(198,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(199,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(200,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(201,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(202,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(203,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(204,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(205,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(214,-743.2181);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(215,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(216,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(217,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(218,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(219,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(220,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(221,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(222,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(223,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(224,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(225,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(226,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(227,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(228,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(238,-1129.093);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(239,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(240,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(241,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(242,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(243,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(244,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(245,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(246,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(247,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(248,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(249,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(250,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(251,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(262,-1681.614);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(263,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(264,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(265,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(266,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(267,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(268,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(269,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(270,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(271,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(272,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(273,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(274,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(286,-2461.034);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(287,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(288,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(289,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(290,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(291,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(292,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(293,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(294,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(295,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(296,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(297,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(310,-3535.651);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(311,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(312,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(313,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(314,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(315,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(316,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(317,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(318,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(319,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(320,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(334,-5029.338);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(335,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(336,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(337,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(338,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(339,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(340,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(341,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(342,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(343,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(358,-7010.984);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(359,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(360,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(361,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(362,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(363,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(364,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(365,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(366,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(382,-9699.321);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(383,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(384,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(385,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(386,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(387,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(388,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(389,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(406,-13271.4);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(407,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(408,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(409,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(410,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(411,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(412,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(430,-17964.07);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(431,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(432,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(433,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(434,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(435,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(454,-24193.55);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(455,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(456,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(457,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(458,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(478,-32379.92);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(479,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(480,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(481,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(502,-42979.94);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(503,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(504,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(526,-56550.43);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(527,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetBinContent(550,-73946.27);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetMinimum(-99900);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetMaximum(-99900);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetEntries(273);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetDirectory(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetStats(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->SetLineStyle(0);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetNdivisions(505);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitleOffset(1.5);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetXaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetLabelFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetLabelOffset(0.007);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitleSize(0.045);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitleOffset(1.8);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetYaxis()->SetTitleFont(42);\n 211830561_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__4->GetZaxis()->SetTitle(\"Acceptance corr. f. sig. cont. 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[GeV]->SetBinContent(476,29.1629);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(477,11.8059);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(478,11.5032);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(479,10.955);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(480,10.847);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(481,10.8834);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(500,39.1501);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(501,15.406);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(502,14.512);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(503,13.6954);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(504,13.1214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(524,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(525,19.7549);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(526,17.1921);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(527,16.5493);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(548,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(549,23.1428);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(550,21.5633);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(572,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(573,29.2682);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetBinContent(596,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMinimum(0.07521894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetMaximum(43.06511);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContour(20);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(0,0.07521894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(1,0.1033278);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(2,0.1419407);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(3,0.1949831);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(4,0.2678471);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(5,0.3679398);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(6,0.5054366);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(7,0.6943151);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(8,0.9537763);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(9,1.310197);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(10,1.799809);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(11,2.472386);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(12,3.396301);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(13,4.665478);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(14,6.408938);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(15,8.803918);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(16,12.09389);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(17,16.6133);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(18,22.82158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetContourLevel(19,31.34986);\n \n TPaletteAxis palette = new TPaletteAxis(716.7339,87.5,754.8387,712.5,280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitle(\"Expected R\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.65,0.85,\"CMS\");\ntex->SetNDC();\n tex->SetTextFont(61);\n tex->SetTextSize(0.055);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.95,0.96,\"19.4 fb^{-1} (8 TeV)\");\ntex->SetNDC();\n tex->SetTextAlign(31);\n tex->SetTextFont(42);\n tex->SetTextSize(0.04);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12 = new TH2F(\"280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12\",\"\",21,187.5,712.5,25,87.5,712.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(24,0.0835766);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(25,0.0909739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(26,0.107743);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(27,0.126982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(28,0.158834);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(29,0.193419);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(30,0.213047);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(31,0.257415);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(32,0.335487);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(33,0.43376);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(34,0.539444);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(35,0.672274);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(36,0.849589);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(37,1.05237);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(38,1.27954);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(39,1.6319);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(40,2.01598);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(41,2.51707);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(42,3.05657);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(43,3.68541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(44,4.67594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(47,0.0844634);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(48,0.0938747);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(49,0.11189);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(50,0.122964);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(51,0.144828);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(52,0.171615);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(53,0.204028);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(54,0.238007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(55,0.325609);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(56,0.392137);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(57,0.487597);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(58,0.608061);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(59,0.769862);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(60,0.944736);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(61,1.19397);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(62,1.47466);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(63,1.8794);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(64,2.29701);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(65,2.76719);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(66,3.41147);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(67,4.16238);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(70,0.0924014);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(71,0.109738);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(72,0.121415);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(73,0.137694);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(74,0.155519);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(75,0.179455);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(76,0.225606);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(77,0.240199);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(78,0.323555);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(79,0.384439);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(80,0.479459);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(81,0.618756);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(82,0.772129);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(83,0.945151);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(84,1.17215);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(85,1.48507);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(86,1.85116);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(87,2.23958);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(88,2.8061);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(89,3.46112);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(90,4.11964);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(93,0.120061);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(94,0.12482);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(95,0.142924);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(96,0.158379);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(97,0.16782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(98,0.207728);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(99,0.234766);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(100,0.263677);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(101,0.344713);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(102,0.412174);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(103,0.519052);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(104,0.648168);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(105,0.788483);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(106,0.98157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(107,1.1828);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(108,1.53654);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(109,1.90175);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(110,2.35007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(111,2.85491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(112,3.51488);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(113,4.25846);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(116,0.255675);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(117,0.170419);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(118,0.171557);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(119,0.19184);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(120,0.214049);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(121,0.225648);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(122,0.27037);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(123,0.284022);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(124,0.381271);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(125,0.450454);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(126,0.547556);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(127,0.678226);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(128,0.843277);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(129,1.05685);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(130,1.28989);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(131,1.594);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(132,2.00739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(133,2.35937);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(134,2.95936);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(135,3.65572);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(136,4.47063);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(140,0.364368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(141,0.229882);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(142,0.23815);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(143,0.262797);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(144,0.284425);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(145,0.297073);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(146,0.341968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(147,0.410706);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(148,0.488003);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(149,0.589326);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(150,0.721192);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(151,0.9052);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(152,1.09151);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(153,1.35713);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(154,1.66913);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(155,2.08248);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(156,2.50003);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(157,3.10172);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(158,3.86717);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(159,4.62348);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(164,0.512927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(165,0.303337);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(166,0.3382);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(167,0.356);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(168,0.39077);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(169,0.373835);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(170,0.471904);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(171,0.536506);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(172,0.640158);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(173,0.790823);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(174,0.946375);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(175,1.1702);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(176,1.44284);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(177,1.78998);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(178,2.14542);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(179,2.68576);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(180,3.24486);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(181,3.9834);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(182,4.92773);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(188,0.755498);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(189,0.426418);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(190,0.449805);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(191,0.473532);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(192,0.496349);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(193,0.559989);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(194,0.639342);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(195,0.711209);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(196,0.862383);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(197,0.975687);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(198,1.23766);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(199,1.51399);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(200,1.85919);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(201,2.26702);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(202,2.84551);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(203,3.48528);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(204,4.0912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(205,5.14491);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(212,1.18157);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(213,0.582596);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(214,0.632377);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(215,0.61113);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(216,0.685299);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(217,0.736881);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(218,0.816257);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(219,0.967138);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(220,1.10978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(221,1.35387);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(222,1.61203);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(223,1.97742);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(224,2.38543);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(225,2.9186);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(226,3.55739);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(227,4.31631);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(228,5.05318);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(236,1.54225);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(237,0.909314);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(238,0.800782);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(239,0.868925);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(240,0.879833);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(241,0.972268);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(242,1.10796);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(243,1.23131);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(244,1.41246);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(245,1.72127);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(246,2.06543);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(247,2.50772);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(248,3.11405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(249,3.75402);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(250,4.4904);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(251,5.42835);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(260,2.24213);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(261,1.03862);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(262,1.1465);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(263,1.16351);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(264,1.20354);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(265,1.27982);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(266,1.39066);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(267,1.62065);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(268,1.91694);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(269,2.20386);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(270,2.68912);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(271,3.28028);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(272,3.90369);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(273,4.63412);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(274,5.63993);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(284,2.88053);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(285,1.54656);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(286,1.5276);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(287,1.53159);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(288,1.60626);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(289,1.6519);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(290,1.88541);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(291,2.06405);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(292,2.49844);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(293,2.91862);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(294,3.3522);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(295,4.04423);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(296,4.89996);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(297,5.89304);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(308,4.02781);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(309,1.96262);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(310,2.00603);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(311,1.98968);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(312,2.08408);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(313,2.05873);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(314,2.32022);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(315,2.71015);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(316,3.12927);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(317,3.74723);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(318,4.44587);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(319,5.1368);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(320,6.24813);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(332,5.62812);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(333,2.59252);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(334,2.50273);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(335,2.58652);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(336,2.67631);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(337,2.69156);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(338,3.01658);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(339,3.50187);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(340,4.0297);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(341,4.56761);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(342,5.63953);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(343,6.64576);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(356,7.1446);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(357,3.74206);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(358,3.18426);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(359,3.16302);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(360,3.38659);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(361,3.62201);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(362,3.81346);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(363,4.32043);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(364,5.04345);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(365,5.90898);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(366,7.00115);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(380,10.601);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(381,4.46058);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(382,4.47865);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(383,4.33286);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(384,4.24832);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(385,4.69078);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(386,4.81427);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(387,5.45356);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(388,6.20253);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(389,7.17101);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(404,14.1147);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(405,5.69871);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(406,5.58215);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(407,5.43958);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(408,5.33733);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(409,5.81474);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(410,6.10985);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(411,6.94638);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(412,8.00885);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(428,18.1529);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(429,7.43733);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(430,7.4268);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(431,6.87762);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(432,6.9684);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(433,7.19843);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(434,7.70621);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(435,8.52007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(452,21.003);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(453,9.76812);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(454,9.17455);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(455,8.79344);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(456,8.70978);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(457,8.70899);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(458,9.4668);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(476,29.1629);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(477,11.8059);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(478,11.5032);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(479,10.955);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(480,10.847);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(481,10.8834);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(500,39.1501);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(501,15.406);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(502,14.512);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(503,13.6954);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(504,13.1214);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(524,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(525,19.7549);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(526,17.1921);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(527,16.5493);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(548,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(549,23.1428);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(550,21.5633);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(572,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(573,29.2682);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetBinContent(596,30);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetMinimum(0.07521894);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetMaximum(43.06511);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetEntries(315);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetDirectory(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetStats(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->SetLineStyle(0);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetNdivisions(505);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetXaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleOffset(1.8);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetYaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitle(\"Expected R\");\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetLabelFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetLabelOffset(0.007);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleSize(0.045);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleOffset(1.5);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->GetZaxis()->SetTitleFont(42);\n 280730369_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]__12->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.3849928379058838, "alphanum_fraction": 0.6752197742462158, "avg_line_length": 45.803829193115234, "blob_id": "6f32e65754f50214b9db7816be9fb3a9a8230a75", "content_id": "18e431ddbf15a25b1b63eef938b33703b1db6353", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 9782, "license_type": "no_license", "max_line_length": 177, "num_lines": 209, "path": "/LimitPlotting/results/Fixed_Edge_13TeV_Sel_Eff_sbottom_neutralino2_Exclusion_.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Sep 3 09:50:05 2014) by ROOT version5.34/07\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(69.08783,-30.40541,761.6554,797.2973);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.08);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV] = new TH2F(\"280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]\",\"\",41,193.75,706.25,49,93.75,706.25);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetStats(0);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->SetLineStyle(0);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitle(\"m(#tilde{b}) [GeV]\");\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetNdivisions(505);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelFont(42);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleSize(32);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetXaxis()->SetTitleFont(43);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitle(\"m(#tilde{#chi}_{2}^{0}) [GeV]\");\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelFont(42);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleSize(32);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleOffset(1.5);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetYaxis()->SetTitleFont(43);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelFont(42);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleSize(32);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleOffset(1.2);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->GetZaxis()->SetTitleFont(43);\n 280730371_m(#tilde{b}) [GeV]_m(#tilde{#chi}_{2}^{0}) [GeV]->Draw(\"h\");\n \n TGraph graph = new TGraph(59);\n graph->SetName(\"Observed limit\");\n graph->SetTitle(\"Observed limit\");\n graph->SetFillColor(100);\n\n Int_t ci; // for color index setting\n ci = TColor::GetColor(\"#0000ff\");\n graph->SetLineColor(ci);\n graph->SetLineWidth(3);\n graph->SetPoint(0,519.8617189,100);\n graph->SetPoint(1,521.8062154,110.9956622);\n graph->SetPoint(2,525,119.4027168);\n graph->SetPoint(3,528.1937847,128.0562153);\n graph->SetPoint(4,530.2837813,138.4662188);\n graph->SetPoint(5,530.9589999,150);\n graph->SetPoint(6,530.2837813,161.5337812);\n graph->SetPoint(7,528.1937847,171.9437847);\n graph->SetPoint(8,525,181.25);\n graph->SetPoint(9,521.8062154,190.5562153);\n graph->SetPoint(10,519.5707187,200.8207187);\n graph->SetPoint(11,517.9292813,211.6792813);\n graph->SetPoint(12,515.6937847,221.9437847);\n graph->SetPoint(13,512.5,231.25);\n graph->SetPoint(14,509.1607153,240.4107153);\n graph->SetPoint(15,506.25,250);\n graph->SetPoint(16,503.3392847,259.5892847);\n graph->SetPoint(17,499.8545,268.6044999);\n graph->SetPoint(18,495.8399966,277.0899966);\n graph->SetPoint(19,491.5145034,285.2645034);\n graph->SetPoint(20,486.6792813,292.9292813);\n graph->SetPoint(21,481.1045,299.8545);\n graph->SetPoint(22,475,306.25);\n graph->SetPoint(23,468.75,312.5);\n graph->SetPoint(24,462.3545,318.6045);\n graph->SetPoint(25,455.2837812,324.0337813);\n graph->SetPoint(26,446.7982846,328.0482846);\n graph->SetPoint(27,436.6792813,330.4292813);\n graph->SetPoint(28,425.8207187,332.0707187);\n graph->SetPoint(29,415.5562153,334.3062154);\n graph->SetPoint(30,406.3955001,337.3545);\n graph->SetPoint(31,397.9100034,339.7275659);\n graph->SetPoint(32,389.5899966,339.7275659);\n graph->SetPoint(33,381.25,337.2089999);\n graph->SetPoint(34,372.9100034,333.3399966);\n graph->SetPoint(35,364.5899966,329.1600034);\n graph->SetPoint(36,356.1044999,325.1455001);\n graph->SetPoint(37,347.0635045,321.6607153);\n graph->SetPoint(38,337.3803622,318.7757803);\n graph->SetPoint(39,327.6600395,315.9847028);\n graph->SetPoint(40,318.5545086,312.7248135);\n graph->SetPoint(41,310.1594096,308.7603835);\n graph->SetPoint(42,302.5662639,303.7854519);\n graph->SetPoint(43,296.069048,297.6050164);\n graph->SetPoint(44,290.2476175,290.9264469);\n graph->SetPoint(45,284.0735531,284.7523825);\n graph->SetPoint(46,277.3949836,278.930952);\n graph->SetPoint(47,271.069048,272.6050164);\n graph->SetPoint(48,265.2476175,265.9264469);\n graph->SetPoint(49,259.0735531,259.7523825);\n graph->SetPoint(50,252.3949836,253.930952);\n graph->SetPoint(51,246.069048,247.6050164);\n graph->SetPoint(52,240.2476175,240.9264469);\n graph->SetPoint(53,234.0735531,234.7523825);\n graph->SetPoint(54,227.3949836,228.930952);\n graph->SetPoint(55,221.069048,222.6050164);\n graph->SetPoint(56,216.0159851,216.0977273);\n graph->SetPoint(57,210.192052,211.0095194);\n graph->SetPoint(58,200,208.4434195);\n graph->Draw(\"l\");\n \n graph = new TGraph(59);\n graph->SetName(\"Expected limit\");\n graph->SetTitle(\"Expected limit\");\n graph->SetFillColor(100);\n\n ci = TColor::GetColor(\"#cc3300\");\n graph->SetLineColor(ci);\n graph->SetLineStyle(9);\n graph->SetLineWidth(3);\n graph->SetPoint(0,519.8617189,100);\n graph->SetPoint(1,521.8062154,110.9956622);\n graph->SetPoint(2,525,119.4027168);\n graph->SetPoint(3,528.1937847,128.0562153);\n graph->SetPoint(4,530.2837813,138.4662188);\n graph->SetPoint(5,530.9589999,150);\n graph->SetPoint(6,530.2837813,161.5337812);\n graph->SetPoint(7,528.1937847,171.9437847);\n graph->SetPoint(8,525,181.25);\n graph->SetPoint(9,521.6607153,190.4107153);\n graph->SetPoint(10,518.75,200);\n graph->SetPoint(11,515.8392847,209.5892847);\n graph->SetPoint(12,512.5,218.75);\n graph->SetPoint(13,509.3062154,228.0562153);\n graph->SetPoint(14,507.0707187,238.3207187);\n graph->SetPoint(15,505.4292813,249.1792813);\n graph->SetPoint(16,503.1937847,259.4437847);\n graph->SetPoint(17,499.8545,268.6044999);\n graph->SetPoint(18,495.8399966,277.0899966);\n graph->SetPoint(19,491.5145034,285.2645034);\n graph->SetPoint(20,486.6792813,292.9292813);\n graph->SetPoint(21,481.1045,299.8545);\n graph->SetPoint(22,475,306.25);\n graph->SetPoint(23,468.75,312.5);\n graph->SetPoint(24,462.3545,318.6045);\n graph->SetPoint(25,455.2837812,324.0337813);\n graph->SetPoint(26,446.7982846,328.0482846);\n graph->SetPoint(27,436.6792813,330.4292813);\n graph->SetPoint(28,425.8207187,332.0707187);\n graph->SetPoint(29,415.5562153,334.3062154);\n graph->SetPoint(30,406.3955001,337.3545);\n graph->SetPoint(31,397.9100034,339.7275659);\n graph->SetPoint(32,389.5899966,339.7275659);\n graph->SetPoint(33,381.25,337.2089999);\n graph->SetPoint(34,372.9100034,333.3399966);\n graph->SetPoint(35,364.5899966,329.1600034);\n graph->SetPoint(36,356.1044999,325.1455001);\n graph->SetPoint(37,347.0635045,321.6607153);\n graph->SetPoint(38,337.3803622,318.7757803);\n graph->SetPoint(39,327.6600395,315.9847028);\n graph->SetPoint(40,318.5545086,312.7248135);\n graph->SetPoint(41,310.1594096,308.7603835);\n graph->SetPoint(42,302.5662639,303.7854519);\n graph->SetPoint(43,296.069048,297.6050164);\n graph->SetPoint(44,290.2476175,290.9264469);\n graph->SetPoint(45,284.0735531,284.7523825);\n graph->SetPoint(46,277.3949836,278.930952);\n graph->SetPoint(47,271.069048,272.6050164);\n graph->SetPoint(48,265.2476175,265.9264469);\n graph->SetPoint(49,259.0735531,259.7523825);\n graph->SetPoint(50,252.3949836,253.930952);\n graph->SetPoint(51,246.069048,247.6050164);\n graph->SetPoint(52,240.2476175,240.9264469);\n graph->SetPoint(53,234.0735531,234.7523825);\n graph->SetPoint(54,227.3949836,228.930952);\n graph->SetPoint(55,221.069048,222.6050164);\n graph->SetPoint(56,216.0159851,216.0977273);\n graph->SetPoint(57,210.192052,211.0095194);\n graph->SetPoint(58,200,208.4434195);\n \n TH1F Graph_Graph1 = new TH1F(\"Graph_Graph1\",\"Expected limit\",100,166.9041,564.0549);\n Graph_Graph1->SetMinimum(76.02724);\n Graph_Graph1->SetMaximum(363.7003);\n Graph_Graph1->SetDirectory(0);\n Graph_Graph1->SetStats(0);\n Graph_Graph1->SetLineStyle(0);\n Graph_Graph1->GetXaxis()->SetNdivisions(505);\n Graph_Graph1->GetXaxis()->SetLabelFont(42);\n Graph_Graph1->GetXaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetXaxis()->SetTitleSize(32);\n Graph_Graph1->GetXaxis()->SetTitleFont(43);\n Graph_Graph1->GetYaxis()->SetLabelFont(42);\n Graph_Graph1->GetYaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetYaxis()->SetTitleSize(32);\n Graph_Graph1->GetYaxis()->SetTitleOffset(1.5);\n Graph_Graph1->GetYaxis()->SetTitleFont(43);\n Graph_Graph1->GetZaxis()->SetLabelFont(42);\n Graph_Graph1->GetZaxis()->SetLabelOffset(0.007);\n Graph_Graph1->GetZaxis()->SetTitleSize(32);\n Graph_Graph1->GetZaxis()->SetTitleOffset(1.2);\n Graph_Graph1->GetZaxis()->SetTitleFont(43);\n graph->SetHistogram(Graph_Graph1);\n \n graph->Draw(\"l\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" }, { "alpha_fraction": 0.4526924788951874, "alphanum_fraction": 0.680273711681366, "avg_line_length": 81.53443145751953, "blob_id": "d999fc851c08274389095994c2d43aeb3a4641e1", "content_id": "68fedf58a8ef7f6e90be4b893793ec2453a8fc88", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "C", "length_bytes": 89880, "license_type": "no_license", "max_line_length": 157, "num_lines": 1089, "path": "/LimitPlotting/results/old/Fixed_Edge_70_BR_10/Fixed_Edge_sbottom_neutralino2_ObsR.C", "repo_name": "cschomak/SimplifiedModelScanTools", "src_encoding": "UTF-8", "text": "{\n//=========Macro generated from canvas: c_squ/c_squ\n//========= (Wed Jun 4 11:16:29 2014) by ROOT version5.32/00\n TCanvas c_squ = new TCanvas(\"c_squ\", \"c_squ\",1,1,900,776);\n gStyle->SetOptStat(0);\n c_squ->SetHighLightColor(2);\n c_squ->Range(39.03225,-34,877.7419,792.6667);\n c_squ->SetFillColor(0);\n c_squ->SetBorderMode(0);\n c_squ->SetBorderSize(2);\n c_squ->SetLogz();\n c_squ->SetTickx(1);\n c_squ->SetTicky(1);\n c_squ->SetLeftMargin(0.18);\n c_squ->SetRightMargin(0.2);\n c_squ->SetBottomMargin(0.15);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n c_squ->SetFrameFillColor(1);\n c_squ->SetFrameFillStyle(0);\n c_squ->SetFrameLineStyle(0);\n c_squ->SetFrameBorderMode(0);\n \n TH2F 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV] = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(29,0.369322);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(30,0.364709);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(31,0.434129);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(32,0.409953);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(33,0.545033);\n 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[GeV]_M_{neutralino 2} [GeV]->SetBinContent(46,5.91401);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(47,7.6538);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(48,9.22395);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(49,10.7546);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(50,14.1339);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(51,16.2161);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(52,20.1497);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(53,23.6249);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(54,30.9272);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(57,0.382041);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(58,0.364106);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(59,0.376878);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]->SetBinContent(557,32.2878);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(558,40.5494);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(575,41.3779);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(576,17.6471);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(577,18.4227);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(578,19.5653);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(579,19.5822);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(580,19.1773);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(581,22.8751);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(582,24.2437);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(583,27.8884);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(584,30.7433);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(585,33.635);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(586,40.5362);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(604,45.8723);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(605,25.3699);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(606,22.5628);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(607,23.4159);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(608,23.6651);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(609,26.1974);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(610,26.8216);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(611,28.0237);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(612,32.7286);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(613,38.2655);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(614,43.2239);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(633,67.3654);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(634,27.7859);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(635,29.4015);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(636,30.6666);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(637,28.5334);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(638,31.1971);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(639,32.4992);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(640,36.0114);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(641,40.332);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(642,47.4174);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(662,82.5005);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(663,32.7577);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(664,40.001);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(665,35.0689);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(666,39.5367);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(667,38.5976);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(668,42.0489);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(669,45.2703);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(670,49.6819);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(691,98.7966);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(692,44.282);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(693,49.978);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(694,47.5797);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(695,42.6036);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(696,45.5883);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(697,49.6913);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(698,53.7276);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(720,119.439);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(721,56.7772);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(722,62.291);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(723,57.4222);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(724,59.5304);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(725,57.368);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(726,64.0716);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(749,143.69);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(750,68.8913);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(751,65.8066);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(752,67.9606);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(753,71.3958);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(754,73.68045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(778,206.336);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(779,82.5147);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(780,85.2687);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(781,87.4614);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(782,83.2893);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(807,192.504);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(808,102.546);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(809,101.889);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(810,99.6753);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(836,297.201);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(837,135.523);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(838,130.867);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(865,404.504);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(866,164.9);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetBinContent(894,463.298);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMinimum(0.3062835);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetMaximum(509.6278);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetEntries(481);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetStats(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContour(20);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(0,0.3062835);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(1,0.4437926);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(2,0.6430379);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(3,0.9317364);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(4,1.350049);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(5,1.956167);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(6,2.834409);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(7,4.106946);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(8,5.950801);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(9,8.622474);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(10,12.49362);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(11,18.10276);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(12,26.23018);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(13,38.00649);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(14,55.0699);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(15,79.79409);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(16,115.6185);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(17,167.5266);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(18,242.7393);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetContourLevel(19,351.7197);\n \n TPaletteAxis palette = new TPaletteAxis(714.1935,90,751.9355,710,484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]);\npalette->SetLabelColor(1);\npalette->SetLabelFont(42);\npalette->SetLabelOffset(0.007);\npalette->SetLabelSize(0.04);\npalette->SetTitleOffset(1.5);\npalette->SetTitleSize(0.045);\n palette->SetFillColor(100);\n palette->SetFillStyle(1001);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetListOfFunctions()->Add(palette,\"br\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->SetLineStyle(0);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitle(\"M_{sbottom} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetNdivisions(505);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetXaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitle(\"M_{neutralino 2} [GeV]\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleOffset(1.8);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetYaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitle(\"Observed R\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]->Draw(\"colz\");\n TLatex * tex = new TLatex(0.18,0.912,\"#bf{CMS preliminary}, #sqrt{s} = 8 TeV,\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n tex = new TLatex(0.48,0.912,\"L_{int} = 19.8 fb^{ -1}, SF, central signal region\");\ntex->SetNDC();\n tex->SetTextFont(43);\n tex->SetTextSize(20);\n tex->SetLineWidth(2);\n tex->Draw();\n \n TH2F *484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11 = new TH2F(\"484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11\",\"\",26,190,710,31,90,710);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(29,0.369322);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(30,0.364709);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(31,0.434129);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(32,0.409953);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(33,0.545033);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(34,0.645504);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(35,0.691938);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(36,0.883669);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(37,1.04805);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(38,1.28174);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(39,1.42307);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(40,1.96478);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(41,2.27538);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(42,2.7149);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(43,3.34952);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(44,4.26968);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(45,5.16175);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(46,5.91401);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(47,7.6538);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(48,9.22395);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(49,10.7546);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(50,14.1339);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(51,16.2161);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(52,20.1497);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(53,23.6249);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(54,30.9272);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(57,0.382041);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(58,0.364106);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(59,0.376878);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(60,0.404784);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(61,0.502938);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(62,0.534695);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(63,0.656955);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(64,0.748782);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(65,0.927802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(66,1.08678);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(67,1.2974);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(68,1.58193);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(69,1.9556);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(70,2.43335);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(71,2.95923);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(72,3.68838);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(73,4.44777);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(74,5.37856);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(75,6.76345);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(76,8.07624);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(77,9.6888);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(78,11.7581);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(79,14.8186);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(80,17.4349);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(81,22.4341);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(82,27.1658);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(85,0.340315);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(86,0.346255);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(87,0.4194906);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(88,0.431314);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(89,0.444264);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(90,0.549138);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(91,0.622791);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(92,0.758155);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(93,0.844474);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(94,1.00951);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(95,1.2531);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(96,1.47643);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(97,1.91506);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(98,2.33823);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(99,2.73565);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(100,3.44695);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(101,4.20806);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(102,5.15635);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(103,6.36988);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(104,7.6575);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(105,9.49226);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(106,12.0147);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(107,14.1751);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(108,17.5772);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(109,21.1853);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(110,25.4136);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(113,0.441416);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(114,0.429409);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(115,0.4690524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(116,0.406719);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(117,0.501599);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(118,0.544705);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(119,0.615297);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(120,0.745372);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(121,0.843017);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(122,1.01193);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(123,1.23612);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(124,1.4906);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(125,1.90215);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(126,2.30793);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(127,2.880753);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(128,3.52534);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(129,4.30907);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(130,5.09219);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(131,6.5954);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(132,7.91628);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(133,9.5206);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(134,11.7554);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(135,14.1285);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(136,17.7574);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(137,21.4974);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(138,25.5859);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(141,0.53915);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(142,0.486457);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(143,0.566128);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(144,0.526685);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(145,0.548012);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(146,0.60984);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(147,0.696691);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(148,0.770694);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(149,0.89384);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(150,1.07182);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(151,1.17668);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(152,1.54736);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(153,1.95615);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(154,2.2026);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(155,2.95409);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(156,3.52612);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(157,4.28921);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(158,5.18941);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(159,6.38362);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(160,7.73909);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(161,9.47622);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(162,11.9003);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(163,14.7827);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(164,17.7488);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(165,21.2747);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(166,26.4586);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(169,1.04039);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(170,0.63494);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(171,0.572592);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(172,0.606823);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(173,0.687575);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(174,0.653767);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(175,0.727947);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(176,0.834882);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(177,0.95808);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(178,1.11388);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(179,1.34108);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(180,1.63712);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(181,1.91426);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(182,2.37437);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(183,2.8894);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(184,3.64944);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(185,4.42154);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(186,5.48037);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(187,6.48539);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(188,8.304);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(189,9.96919);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(190,12.4682);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(191,14.2646);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(192,18.2414);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(193,21.947);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(194,26.6936);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(198,1.10738);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(199,0.724404);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(200,0.808623);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(201,0.836288);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(202,0.982018);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(203,0.836918);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(204,0.97132);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(205,1.04928);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(206,1.24735);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(207,1.52207);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(208,1.69992);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(209,1.9284);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(210,2.52934);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(211,3.03125);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(212,3.67921);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(213,4.49524);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(214,5.63835);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(215,6.70566);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(216,8.49867);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(217,9.97404);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(218,12.7061);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(219,15.5431);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(220,18.381);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(221,22.5976);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(222,27.3638);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(227,1.54718);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(228,0.946575);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(229,0.949057);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(230,0.99468);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(231,1.02734);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(232,1.13604);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(233,1.18775);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(234,1.44443);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(235,1.55412);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(236,1.82969);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(237,2.27604);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(238,2.59488);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(239,3.13055);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(240,3.84869);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(241,4.88609);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(242,5.64009);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(243,6.93611);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(244,8.61331);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(245,10.6242);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(246,12.7636);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(247,15.8162);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(248,19.0337);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(249,23.7923);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(250,28.0143);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(256,2.58105);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(257,1.18968);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(258,1.31935);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(259,1.30823);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(260,1.29593);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(261,1.46192);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(262,1.61124);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(263,1.75394);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(264,1.86188);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(265,2.32137);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(266,2.65573);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(267,3.42773);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(268,4.23306);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(269,5.04353);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(270,5.96613);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(271,7.49065);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(272,9.19218);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(273,10.9386);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(274,13.3018);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(275,16.0868);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(276,19.7293);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(277,23.4868);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(278,28.9099);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(285,2.62871);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(286,1.5223);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(287,1.5903);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(288,1.77962);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(289,1.63128);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(290,1.88492);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(291,2.11351);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(292,2.20384);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(293,2.79868);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(294,2.93204);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(295,3.5741);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(296,4.35947);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(297,5.08489);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(298,6.37044);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(299,7.4253);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(300,9.42311);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(301,11.3545);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(302,13.7789);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(303,16.2338);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(304,20.4761);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(305,25.5752);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(306,29.6876);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(314,3.47356);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(315,2.03709);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(316,2.03301);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(317,2.25025);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(318,2.06886);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(319,2.66262);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(320,2.68775);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(321,2.95432);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(322,3.26191);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(323,3.79986);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(324,4.70465);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(325,5.54638);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(326,6.57682);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(327,8.01862);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(328,9.18765);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(329,11.8334);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(330,14.4851);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(331,17.291);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(332,20.7434);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(333,25.0935);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(354,6.98644);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(355,8.22702);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(356,10.302);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(357,12.2295);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(358,14.7698);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(359,17.429);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(360,20.9027);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(361,26.6536);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(362,31.8679);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(372,6.12497);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(373,3.29595);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(386,15.3495);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(387,18.6516);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(388,22.1415);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(389,26.7769);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(390,32.5688);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(401,7.38538);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(402,4.44237);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(403,4.53473);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(404,4.44268);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(405,4.72514);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(406,4.89866);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(553,19.4624);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(554,23.0099);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(555,24.6802);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(556,28.1474);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(557,32.2878);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(558,40.5494);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(575,41.3779);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(576,17.6471);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(577,18.4227);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(578,19.5653);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(579,19.5822);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(580,19.1773);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(581,22.8751);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(582,24.2437);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(583,27.8884);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(584,30.7433);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(585,33.635);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(586,40.5362);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(604,45.8723);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(605,25.3699);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(606,22.5628);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(607,23.4159);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(608,23.6651);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(609,26.1974);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(610,26.8216);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(611,28.0237);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(612,32.7286);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(613,38.2655);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(614,43.2239);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(633,67.3654);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(634,27.7859);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(635,29.4015);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(636,30.6666);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->SetBinContent(637,28.5334);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} 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[GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitle(\"Observed R\");\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetLabelFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetLabelOffset(0.007);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleSize(0.045);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleOffset(1.5);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->GetZaxis()->SetTitleFont(42);\n 484096097_M_{sbottom} [GeV]_M_{neutralino 2} [GeV]__11->Draw(\"sameaxis\");\n c_squ->Modified();\n c_squ->cd();\n c_squ->SetSelected(c_squ);\n}\n" } ]	84
jeanson-JinSheng/Pytorch-ENet-Nice	https://github.com/jeanson-JinSheng/Pytorch-ENet-Nice	172998cd469ac08adf42694dbaf2e4ba2de76de4	af5b288c62c52612f77f062f82aa27b84927786a	bfffe06c1d581c6d28a88c86b8065cdb0905126d	refs/heads/master	2020-06-06T19:15:12.949888	2019-06-19T19:37:27	2019-06-19T19:37:27	192,831,671	1	0	BSD-3-Clause	2019-06-20T02:05:15	2019-06-20T02:05:13	2019-06-19T19:37:28	null	[ { "alpha_fraction": 0.7710843086242676, "alphanum_fraction": 0.7710843086242676, "avg_line_length": 82, "blob_id": "eda6912bc356c9c8ebd1f2b01c1cad9cb92b6f83", "content_id": "163c144fe638a88814366b2454c80f6a26a9707b", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Shell", "length_bytes": 83, "license_type": "permissive", "max_line_length": 82, "num_lines": 1, "path": "/datasets/Cityscapes/scaleDownSampling/build.sh", "repo_name": "jeanson-JinSheng/Pytorch-ENet-Nice", "src_encoding": "UTF-8", "text": "g++ -o scaleDownSampling scaleDownSampling.cpp `pkg-config --cflags --libs opencv`\n" }, { "alpha_fraction": 0.5110001564025879, "alphanum_fraction": 0.5484474897384644, "avg_line_length": 34.40884017944336, "blob_id": "08d8b76d8c449178cd1a7d7075bde081c927067c", "content_id": "a319deec7b406990386436e3a9c17e1fa2ff2f97", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 6409, "license_type": "permissive", "max_line_length": 137, "num_lines": 181, "path": "/train.py", "repo_name": "jeanson-JinSheng/Pytorch-ENet-Nice", "src_encoding": "UTF-8", "text": "import torch\nimport torch.nn as nn\nfrom utils import \nfrom models.ENet import ENet\nfrom models.ENet_encoder import ENet_encoder\nimport sys\nfrom tqdm import tqdm\n\ndef train(FLAGS):\n\n # Defining the hyperparameters\n device = FLAGS.cuda\n batch_size = FLAGS.batch_size\n epochs = FLAGS.epochs\n lr = FLAGS.learning_rate\n print_every = FLAGS.print_every\n eval_every = FLAGS.eval_every\n save_every = FLAGS.save_every\n nc = FLAGS.num_classes\n wd = FLAGS.weight_decay\n ip = FLAGS.input_path_train\n lp = FLAGS.label_path_train\n ipv = FLAGS.input_path_val\n lpv = FLAGS.label_path_val\n\n\n train_mode = FLAGS.train_mode\n pretrain_model = FLAGS.pretrain_model\n cityscapes_path = FLAGS.cityscapes_path\n resume_model_path = FLAGS.resume_model_path\n print ('[INFO]Defined all the hyperparameters successfully!')\n\n # Get the class weights\n print ('[INFO]Starting to define the class weights...')\n if len(cityscapes_path):\n pipe = loader_cityscapes(ip, cityscapes_path, batch_size='all')\n class_weights = get_class_weights(pipe, nc, isCityscapes=True)\n #class_weights = np.array([3.03507951, 13.09507946, 4.54913664, 37.64795738, 35.78537802, 31.50943831, 45.88744201, 39.936759,\n # 6.05101481, 31.85754823, 16.92219283, 32.07766734, 47.35907214, 11.34163794, 44.31105748, 45.81085476,\n # 45.67260936, 48.3493813, 42.02189188])\n else:\n pipe = loader(ip, lp, batch_size='all')\n class_weights = get_class_weights(pipe, nc)\n print ('[INFO]Fetched all class weights successfully!')\n\n # Get an instance of the model\n if train_mode.lower() == 'encoder-decoder':\n enet = ENet(nc)\n if len(pretrain_model):\n checkpoint0 = torch.load(pretrain_model)\n pretrain_dict = checkpoint0['state_dict']\n enet_dict = enet.state_dict()\n pretrain_dict = {k: v for k, v in pretrain_dict.items() if k in enet_dict}\n enet_dict.update(pretrain_dict)\n enet.load_state_dict(enet_dict)\n print('[INFO]Previous model Instantiated!')\n else:\n enet = ENet_encoder(nc)\n\n print ('[INFO]Model Instantiated!')\n\n # Move the model to cuda if available\n enet = enet.to(device)\n\n # Define the criterion and the optimizer\n if len(cityscapes_path):\n criterion = nn.CrossEntropyLoss(weight=torch.FloatTensor(class_weights).to(device), ignore_index=255)\n else:\n criterion = nn.CrossEntropyLoss(weight=torch.FloatTensor(class_weights).to(device))\n\n optimizer = torch.optim.Adam(enet.parameters(), lr=lr, weight_decay=wd)\n scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode=\"min\", factor=0.5, patience=2, verbose=True, threshold=0.01)\n # scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer, mode=\"min\", factor=0.5, patience=2, verbose=True,\n # threshold=0.005)\n print ('[INFO]Defined the loss function and the optimizer')\n\n # Training Loop starts\n print ('[INFO]Staring Training...')\n print ()\n\n train_losses = []\n eval_losses = []\n\n\n if len(cityscapes_path):\n # Assuming we are using the Cityscapes Dataset\n bc_train = 2975 // batch_size\n bc_eval = 500 // batch_size\n\n pipe = loader_cityscapes(ip, cityscapes_path, batch_size)\n eval_pipe = loader_cityscapes(ipv, cityscapes_path, batch_size)\n else:\n # Assuming we are using the CamVid Dataset\n bc_train = 367 // batch_size\n bc_eval = 101 // batch_size\n\n pipe = loader(ip, lp, batch_size)\n eval_pipe = loader(ipv, lpv, batch_size)\n\n epoch = 1\n if len(resume_model_path):\n checkpoint1 = torch.load(resume_model_path)\n epoch = checkpoint1['epochs'] + 1\n enet.load_state_dict(checkpoint1['state_dict'])\n\n epochs = epochs\n \n for e in range(epoch, epochs+1):\n \n train_loss = 0\n print ('-'15,'Epoch %d' % e, '-'15)\n\n enet.train()\n \n for _ in tqdm(range(bc_train)):\n X_batch, mask_batch = next(pipe)\n \n #assert (X_batch >= 0. and X_batch <= 1.0).all()\n \n X_batch, mask_batch = X_batch.to(device), mask_batch.to(device)\n\n optimizer.zero_grad()\n\n out = enet(X_batch.float())\n\n loss = criterion(out, mask_batch.long())\n loss.backward()\n optimizer.step()\n\n train_loss += loss.item()\n\n \n print ()\n train_losses.append(train_loss)\n \n if (e+1) % print_every == 0:\n print ('Epoch {}/{}...'.format(e, epochs),\n 'Loss {:6f}'.format(train_loss))\n\n scheduler.step(train_loss)\n \n if e % eval_every == 0:\n with torch.no_grad():\n enet.eval()\n \n eval_loss = 0\n \n for _ in tqdm(range(bc_eval)):\n inputs, labels = next(eval_pipe)\n\n inputs, labels = inputs.to(device), labels.to(device)\n out = enet(inputs)\n \n loss = criterion(out, labels.long())\n\n eval_loss += loss.item()\n\n print ()\n print ('Loss {:6f}'.format(eval_loss))\n \n eval_losses.append(eval_loss)\n\n if e % save_every == 0:\n checkpoint = {\n 'epochs' : e,\n 'state_dict' : enet.state_dict()\n }\n if train_mode.lower() == 'encoder-decoder':\n torch.save(checkpoint,\n './logs/ckpt-enet-{}-{}-{}.pth'.format(e, optimizer.state_dict()['param_groups'][0]['lr'],\n train_loss))\n else:\n torch.save(checkpoint,\n './logs/ckpt-enet_encoder-{}-{}-{}.pth'.format(e, optimizer.state_dict()['param_groups'][0]['lr'],\n train_loss))\n print ('Model saved!')\n\n print ('Epoch {}/{}...'.format(e+1, epochs),\n 'Total Mean Loss: {:6f}'.format(sum(train_losses) / epochs))\n\n print ('[INFO]Training Process complete!')\n" }, { "alpha_fraction": 0.5621242523193359, "alphanum_fraction": 0.5721442699432373, "avg_line_length": 37.346153259277344, "blob_id": "fedf8a814d0f124b629f4d5a467144d3e811787a", "content_id": "3f0dfe1e59072f25f11d7808a8dbd1aebb4367ac", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 998, "license_type": "permissive", "max_line_length": 180, "num_lines": 26, "path": "/datasets/Cityscapes/makepairs.py", "repo_name": "jeanson-JinSheng/Pytorch-ENet-Nice", "src_encoding": "UTF-8", "text": "import os \nimport sys\nimport cv2\nimport numpy as np\n\ndef makepairs():\n train = open(\"train_cityscapes.txt\", 'w')\n val = open(\"val_cityscapes.txt\", 'w')\n\n dataname = [\"train/\", \"val/\"]\n for i in range(2):\n imagedirs = os.listdir(\"leftImg8bit/\" + dataname[i])\n dir_num = len(imagedirs)\n for j in range(dir_num):\n images = os.listdir(\"leftImg8bit/\" + dataname[i] + \"/\" + imagedirs[j])\n image_num = len(images)\n for k in range(image_num):\n image = images[k]\n lists = image.split('leftImg8bit.png')\n if i == 0:\n train.write(\"/Cityscapes/leftImg8bit/train/\" + imagedirs[j] + \"/\" + image + \" /Cityscapes/gtFine/train/\" + imagedirs[j] + \"/\" + lists[0] + \"gtFine_labelTrainIds.png\\n\")\n else:\n val.write(\"/Cityscapes/leftImg8bit/val/\" + imagedirs[j] + \"/\" + image + \" /Cityscapes/gtFine/val/\" + imagedirs[j] + \"/\" + lists[0] + \"gtFine_labelTrainIds.png\\n\")\n\nif __name__ == '__main__':\n makepairs()\n\n" }, { "alpha_fraction": 0.5371129512786865, "alphanum_fraction": 0.5750227570533752, "avg_line_length": 28.381271362304688, "blob_id": "385667a400133847d674c772fde05d4c09af72b7", "content_id": "4b0999deecb5c370a52e7cacb6989f826356b5ee", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 8784, "license_type": "permissive", "max_line_length": 110, "num_lines": 299, "path": "/utils.py", "repo_name": "jeanson-JinSheng/Pytorch-ENet-Nice", "src_encoding": "UTF-8", "text": "import numpy as np\nimport cv2\nimport matplotlib.pyplot as plt\nimport sys\nimport os\nfrom PIL import Image\nimport torch\n\ndef create_class_mask(img, color_map, is_normalized_img=True, is_normalized_map=False, show_masks=False):\n \"\"\"\n Function to create C matrices from the segmented image, where each of the C matrices is for one class\n with all ones at the pixel positions where that class is present\n\n img = The segmented image\n\n color_map = A list with tuples that contains all the RGB values for each color that represents\n some class in that image\n\n is_normalized_img = Boolean - Whether the image is normalized or not\n If normalized, then the image is multiplied with 255\n\n is_normalized_map = Boolean - Represents whether the color map is normalized or not, if so\n then the color map values are multiplied with 255\n\n show_masks = Wherether to show the created masks or not\n \"\"\"\n\n if is_normalized_img and (not is_normalized_map):\n img = 255\n\n if is_normalized_map and (not is_normalized_img):\n img = img / 255\n \n mask = []\n hw_tuple = img.shape[:-1]\n for color in color_map:\n color_img = []\n for idx in range(3):\n color_img.append(np.ones(hw_tuple) * color[idx])\n\n color_img = np.array(color_img, dtype=np.uint8).transpose(1, 2, 0)\n\n mask.append(np.uint8((color_img == img).sum(axis = -1) == 3))\n\n return np.array(mask)\n\n\ndef loader(training_path, segmented_path, batch_size, h=512, w=512):\n \"\"\"\n The Loader to generate inputs and labels from the Image and Segmented Directory\n\n Arguments:\n\n training_path - str - Path to the directory that contains the training images\n\n segmented_path - str - Path to the directory that contains the segmented images\n\n batch_size - int - the batch size\n\n yields inputs and labels of the batch size\n \"\"\"\n\n filenames_t = os.listdir(training_path)\n total_files_t = len(filenames_t)\n \n filenames_s = os.listdir(segmented_path)\n total_files_s = len(filenames_s)\n \n assert(total_files_t == total_files_s)\n \n if str(batch_size).lower() == 'all':\n batch_size = total_files_s\n \n idx = 0\n while(1):\n batch_idxs = np.random.randint(0, total_files_s, batch_size)\n \n \n inputs = []\n labels = []\n \n for jj in batch_idxs:\n img = plt.imread(training_path + filenames_t[jj])\n #img = cv2.resize(img, (h, w), cv2.INTER_NEAREST)\n inputs.append(img)\n \n img = Image.open(segmented_path + filenames_s[jj])\n img = np.array(img)\n #img = cv2.resize(img, (h, w), cv2.INTER_NEAREST)\n labels.append(img)\n \n inputs = np.stack(inputs, axis=2)\n inputs = torch.tensor(inputs).transpose(0, 2).transpose(1, 3)\n \n labels = torch.tensor(labels)\n \n yield inputs, labels\n\n\ndef loader_cityscapes(txt_path, cityscapes_path, batch_size):\n \"\"\"\n The Loader to generate inputs and labels from the txt file\n\n Arguments:\n\n txt_path - str - Path to the txt file that contains the training images and segmented images path\n\n cityscapes_path - str - Cityscapes Path to the directory of Cityscapes image\n\n batch_size - int - the batch size\n\n yields inputs and labels of the batch size\n \"\"\"\n\n lines = open(txt_path, 'r').readlines()\n total_files = len(lines)\n\n images = []\n gts = []\n for line in lines:\n line = line.strip().split(\" \")\n images.append(line[0])\n gts.append(line[1])\n\n if str(batch_size).lower() == 'all':\n batch_size = total_files\n while (1):\n batch_idxs = np.random.randint(0, total_files, batch_size)\n\n labels = []\n for jj in batch_idxs:\n img = Image.open(cityscapes_path + gts[jj])\n img = np.array(img)\n #img5 = scale_downsample(img, 0.5, 0.5)\n\n labels.append(img)\n\n labels = torch.tensor(labels)\n\n yield labels\n\n idx = 0\n while (1):\n batch_idxs = np.random.randint(0, total_files, batch_size)\n\n inputs = []\n labels = []\n for jj in batch_idxs:\n\n img = plt.imread(cityscapes_path + images[jj])\n #img5 = scale_downsample(img, 0.5, 0.5)\n inputs.append(img)\n\n img = Image.open(cityscapes_path + gts[jj])\n img = np.array(img)\n #img5 = scale_downsample(img, 0.5, 0.5)\n labels.append(img)\n\n inputs = np.stack(inputs, axis=2)\n inputs = torch.tensor(inputs).transpose(0, 2).transpose(1, 3)\n\n labels = torch.tensor(labels)\n\n yield inputs, labels\n\n\n\ndef decode_segmap(image, cityscapes):\n Sky = [128, 128, 128]\n Building = [128, 0, 0]\n Column_Pole = [192, 192, 128]\n Road_marking = [255, 69, 0]\n Road = [128, 64, 128]\n Pavement = [60, 40, 222]\n Tree = [128, 128, 0]\n SignSymbol = [192, 128, 128]\n Fence = [64, 64, 128]\n Car = [64, 0, 128]\n Pedestrain = [64, 64, 0]\n Bicyclist = [0, 128, 192]\n\n\n road = [128,64,128]\n Lsidewalk = [244,35,232]\n building = [70,70,70]\n wall = [102,102,156]\n fence = [190,153,153]\n pole = [153,153,153]\n traffic_light = [250,170,30]\n traffic_sign = [220,220,0]\n vegetation = [107,142,35]\n terrain = [152,251,152]\n sky = [70,130,180]\n person = [220,20,60]\n Lrider = [255,0,0]\n car = [0,0,142]\n truck = [0,0,70]\n bus = [0,60,100]\n train = [0,80,100]\n motorcycle = [0,0,230]\n bicycle = [119,11,32]\n\n\n if cityscapes:\n label_colors = np.array([road, Lsidewalk, building, wall, fence, pole, traffic_light, traffic_sign,\n vegetation, terrain, sky, person, Lrider, car, truck, bus, train, motorcycle,\n bicycle]).astype(np.uint8)\n else:\n label_colors = np.array([Sky, Building, Column_Pole, Road_marking, Road,\n Pavement, Tree, SignSymbol, Fence, Car,\n Pedestrain, Bicyclist]).astype(np.uint8)\n\n r = np.zeros_like(image).astype(np.uint8)\n g = np.zeros_like(image).astype(np.uint8)\n b = np.zeros_like(image).astype(np.uint8)\n\n for label in range(len(label_colors)):\n b[image == label] = label_colors[label, 0]\n g[image == label] = label_colors[label, 1]\n r[image == label] = label_colors[label, 2]\n\n rgb = np.zeros((image.shape[0], image.shape[1], 3)).astype(np.uint8)\n rgb[:, :, 0] = r\n rgb[:, :, 1] = g\n rgb[:, :, 2] = b\n\n return rgb\n\ndef show_images(images, in_row=True):\n '''\n Helper function to show 3 images\n '''\n total_images = len(images)\n\n rc_tuple = (1, total_images)\n if not in_row:\n rc_tuple = (total_images, 1)\n\n #figure = plt.figure(figsize=(20, 10))\n for ii in range(len(images)):\n plt.subplot(rc_tuple, ii+1)\n plt.title(images[ii][0])\n plt.axis('off')\n plt.imshow(images[ii][1])\n # plt.savefig(\"./Enet.png\")\n plt.show()\n\ndef get_class_weights(loader, num_classes, c=1.02, isCityscapes=False):\n '''\n This class return the class weights for each class\n \n Arguments:\n - loader : The generator object which return all the labels at one iteration\n Do Note: That this class expects all the labels to be returned in\n one iteration\n\n - num_classes : The number of classes\n\n Return:\n - class_weights : An array equal in length to the number of classes\n containing the class weights for each class\n '''\n if isCityscapes:\n labels = next(loader)\n else:\n _, labels = next(loader)\n all_labels = labels.flatten()\n all_len = len(all_labels)\n each_class = np.bincount(all_labels, minlength=num_classes)\n if isCityscapes:\n each_class = each_class[0:19]\n num = 0\n for i in each_class:\n num += i\n all_len = num\n prospensity_score = each_class / all_len\n class_weights = 1 / (np.log(c + prospensity_score))\n print(\"class_weights: \")\n print(class_weights)\n return class_weights\n\n\ndef scale_downsample(img, kx, ky):\n rows = int(np.round(np.abs(img.shape[0] kx)))\n cols = int(np.round(np.abs(img.shape[1] * ky)))\n\n if len(img.shape) == 3 and img.shape[2] >= 3:\n dist = np.zeros((rows, cols, img.shape[2]), img.dtype)\n else:\n dist = np.zeros((rows, cols), img.dtype)\n\n for y in range(rows):\n for x in range(cols):\n new_y = int((y + 1) / ky + 0.5) - 1\n new_x = int((x + 1) / kx + 0.5) - 1\n\n dist[y, x] = img[new_y, new_x]\n\n return dist" }, { "alpha_fraction": 0.5020586848258972, "alphanum_fraction": 0.5200720429420471, "avg_line_length": 31.358333587646484, "blob_id": "e051847c1dbfe3805f90c92f28a27d01042e542d", "content_id": "bb4b5f4c56930e4028570a9cccac24b2e747995e", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "C++", "length_bytes": 4014, "license_type": "permissive", "max_line_length": 88, "num_lines": 120, "path": "/datasets/Cityscapes/scaleDownSampling/scaleDownSampling.cpp", "repo_name": "jeanson-JinSheng/Pytorch-ENet-Nice", "src_encoding": "UTF-8", "text": "#include <iostream>\n#include <fstream>\n#include <string>\n#include <stdlib.h>\n#include <opencv2/opencv.hpp>\nusing namespace cv;\nusing namespace std;\nvoid scaleDownSampling(const Mat &src, Mat &dst, double xRatio, double yRatio)\n{\n //判断是否为uchar型的像素\n CV_Assert(src.depth() == CV_8U);\n\n // 计算缩小后图像的大小，取整防止越界\n int rows = static_cast<int>(src.rows * xRatio);\n int cols = static_cast<int>(src.cols * yRatio);\n\n dst.create(rows, cols, src.type());\n\n const int channels = src.channels();\n\n switch (channels)\n {\n case 1: //单通道图像\n {\n uchar p;\n const uchar origal;\n\n for (int i = 0; i < rows; i++){\n p = dst.ptr<uchar>(i);\n //间隔采样取基数行\n int row = static_cast<int>((i + 1) / xRatio + 0.5) - 1;\n origal = src.ptr<uchar>(row);\n for (int j = 0; j < cols; j++){\n //间隔采样取基数列\n int col = static_cast<int>((j + 1) / yRatio + 0.5) - 1;\n p[j] = origal[col]; //把像素值赋给dst\n }\n }\n break;\n }\n\n case 3://三通道图像\n {\n Vec3b p;\n const Vec3b origal;\n\n for (int i = 0; i < rows; i++) {\n p = dst.ptr<Vec3b>(i);\n int row = static_cast<int>((i + 1) / xRatio + 0.5) - 1;\n origal = src.ptr<Vec3b>(row);\n for (int j = 0; j < cols; j++){\n int col = static_cast<int>((j + 1) / yRatio + 0.5) - 1;\n p[j] = origal[col]; //把RGB三个值赋给dst\n }\n }\n break;\n }\n }\n}\nvector<string> split(const string& s, const string& sep)\n{\n vector<string> v; \n string::size_type pos1, pos2;\n pos2 = s.find(sep);\n pos1 = 0;\n while(string::npos != pos2)\n {\n v.push_back(s.substr(pos1, pos2-pos1));\n \n pos1 = pos2 + sep.size();\n pos2 = s.find(sep, pos1);\n }\n if(pos1 != s.length())\n v.push_back(s.substr(pos1));\n return v;\n}\n\nint main(int argc, char* argv[])\n{\n\n if(argv[1] == \"help\" \|\| argc < 8){\n\tcout << \"please enter 8 parameter\" << endl;\n cout << \"argv[1]: Original cityscapes datasets txt file\" << endl;\n cout << \"argv[2]: Path to Original cityscapes datasets\" << endl;\n cout << \"argv[3]: New txt file of the resized cityscapes datasets\" << endl;\n cout << \"argv[4]: Path to the resized cityscapes datasets\" << endl;\n cout << \"argv[5]: Image x-axis reduction ratio\" << endl;\n cout << \"argv[6]: Image y-axis reduction ratio\" << endl;\n cout << \"argv[7]: Label x-axis reduction ratio\" << endl;\n cout << \"argv[8]: Label y-axis reduction ratio\" << endl;\n return 0;\n }\n ofstream writeTxt(argv[3]);\n ifstream readTxt(argv[1]);\n\n string new_Cityscapes_path = argv[4];\n double image_xRatio = atof(argv[5]);\n double image_yRatio = atof(argv[6]);\n double label_xRatio = atof(argv[7]);\n double label_yRatio = atof(argv[8]);\n\n string fimage, flabel, Wimage, Wlabel;\n int i = 0;\n while (readTxt >> fimage >> flabel){\n Mat new_image, new_label_image;\n Mat image = imread(argv[2] + fimage);\n Mat label_image = imread(argv[2] + flabel, 0);\n scaleDownSampling(image, new_image, image_xRatio, image_yRatio);\n scaleDownSampling(label_image, new_label_image, label_xRatio, label_yRatio);\n vector<string> iFolder = split(fimage, \"/\");\n vector<string> lFolder = split(flabel, \"/\");\n Wimage = new_Cityscapes_path+\"/leftImg8bit/\"+iFolder[3]+\"/\"+to_string(i)+\".png\";\n Wlabel = new_Cityscapes_path+\"/gtFine/\"+lFolder[3]+\"/\"+to_string(i)+\".png\";\n imwrite(Wimage, new_image);\n imwrite(Wlabel, new_label_image);\n writeTxt << \"/\"+Wimage+\" /\"+Wlabel+\"\\n\"; \n i++;\n }\n return 0;\n}\n\n\n\n" }, { "alpha_fraction": 0.45213812589645386, "alphanum_fraction": 0.4569690525531769, "avg_line_length": 36.763511657714844, "blob_id": "9b69ecf261a8397ce3cd84e12085c5a35729f195", "content_id": "fcce4556e570c9aff862bc1e8afe1d6077b86d31", "detected_licenses": [ "BSD-3-Clause" ], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 5589, "license_type": "permissive", "max_line_length": 103, "num_lines": 148, "path": "/init.py", "repo_name": "jeanson-JinSheng/Pytorch-ENet-Nice", "src_encoding": "UTF-8", "text": "import numpy as np\nimport argparse\nfrom train import \nfrom test import \n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n\n parser.add_argument('-m',\n type=str,\n default='./datasets/CamVid/ckpt-camvid-enet.pth',\n help='The path to the pretrained enet model')\n\n parser.add_argument('-i', '--image-path',\n type=str,\n help='The path to the image to perform semantic segmentation')\n\n parser.add_argument('-rh', '--resize-height',\n type=int,\n default=1024,\n help='The height for the resized image')\n\n parser.add_argument('-rw', '--resize-width',\n type=int,\n default=512,\n help='The width for the resized image')\n\n parser.add_argument('-lr', '--learning-rate',\n type=float,\n default=5e-3,\n help='The learning rate')\n\n parser.add_argument('-bs', '--batch-size',\n type=int,\n default=10,\n help='The batch size')\n\n parser.add_argument('-wd', '--weight-decay',\n type=float,\n default=2e-4,\n help='The weight decay')\n\n parser.add_argument('-c', '--constant',\n type=float,\n default=1.02,\n help='The constant used for calculating the class weights')\n\n parser.add_argument('-e', '--epochs',\n type=int,\n default=102,\n help='The number of epochs')\n\n parser.add_argument('-nc', '--num-classes',\n type=int,\n default=12,\n help='The number of classes')\n\n parser.add_argument('-se', '--save-every',\n type=int,\n default=10,\n help='The number of epochs after which to save a model')\n\n parser.add_argument('-iptr', '--input-path-train',\n type=str,\n default='./datasets/CamVid/train/',\n help='The path to the input dataset')\n\n parser.add_argument('-lptr', '--label-path-train',\n type=str,\n default='./datasets/CamVid/trainannot/',\n help='The path to the label dataset')\n\n parser.add_argument('-ipv', '--input-path-val',\n type=str,\n default='./datasets/CamVid/val/',\n help='The path to the input dataset')\n\n parser.add_argument('-lpv', '--label-path-val',\n type=str,\n default='./datasets/CamVid/valannot/',\n help='The path to the label dataset')\n\n parser.add_argument('-iptt', '--input-path-test',\n type=str,\n default='./datasets/CamVid/test/',\n help='The path to the input dataset')\n\n parser.add_argument('-lptt', '--label-path-test',\n type=str,\n default='./datasets/CamVid/testannot/',\n help='The path to the label dataset')\n\n parser.add_argument('-pe', '--print-every',\n type=int,\n default=1,\n help='The number of epochs after which to print the training loss')\n\n parser.add_argument('-ee', '--eval-every',\n type=int,\n default=10,\n help='The number of epochs after which to print the validation loss')\n\n parser.add_argument('--cuda',\n type=bool,\n default=False,\n help='Whether to use cuda or not')\n\n parser.add_argument('--mode',\n choices=['train', 'test'],\n default='train',\n help='Whether to train or test')\n\n parser.add_argument('--test_mode',\n choices=['cityscapes', 'camvid'],\n default='cityscapes',\n help='Whether to test cityscape model or camvid model')\n\n parser.add_argument('--train_mode',\n choices=['encoder-decoder', 'encoder'],\n default='encoder-decoder',\n help='Select to train mode of Enet')\n\n parser.add_argument('--pretrain_model',\n type=str,\n default='',\n help='Import previous train model of encoder ENet')\n\n parser.add_argument('--cityscapes_path',\n type=str,\n default='',\n help='Cityscapes Path to the directory of Cityscapes image')\n\n parser.add_argument('--resume_model_path',\n type=str,\n default='',\n help='Model path to resume training')\n\n \n FLAGS, unparsed = parser.parse_known_args()\n\n FLAGS.cuda = torch.device('cuda:0' if torch.cuda.is_available() and FLAGS.cuda else 'cpu')\n\n if FLAGS.mode.lower() == 'train':\n train(FLAGS)\n elif FLAGS.mode.lower() == 'test':\n test(FLAGS)\n else:\n raise RuntimeError('Unknown mode passed. \\n Mode passed should be either of \"train\" or \"test\"')\n" } ]	6
tukkyr/docker-st	https://github.com/tukkyr/docker-st	875f49d58d6297ce367693f6b5d35e5878e9e3e1	a889dcf9045106b97851281b2576ac46ef386510	2ba7c63e49b8a1c8ccf29ce8edcf3df7333baea3	refs/heads/master	2021-07-12T19:43:15.439973	2020-09-04T01:57:45	2020-09-04T01:57:45	199,300,255	6	3	null	null	null	null	null	[ { "alpha_fraction": 0.6810049414634705, "alphanum_fraction": 0.6932812929153442, "avg_line_length": 18.1384334564209, "blob_id": "2e4a130e15496df6127bb970fc14d22f9bc9a64e", "content_id": "786f21b68cbd3cedff3a8e3e7cde781ca41bd836", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 12954, "license_type": "no_license", "max_line_length": 146, "num_lines": 549, "path": "/ch4.md", "repo_name": "tukkyr/docker-st", "src_encoding": "UTF-8", "text": "# 色々なプログラミング環境で使うDockerのコツ\n\nFinal\n\n[参考資料](https://docs.docker.com/compose/)\n\ndocker swarm は対象にしていません\n\n## 復習\n\n### dockerの基本構成\n\n![dockerimg](https://docs.docker.com/engine/images/architecture.svg)\n\n> RegistryとRepositoryの違い\n> - Registry: dockerhub, ECR, GCP Container Registry などのimage置き場そのもの\n> - Repository: Registryに置かれる　同じimage名で異なるtagを持つイメージのセット置き場\n\nimageはReadOnlyなlayerを持っている\n\n![img](docker2.png)\n\n同じイメージは使いまわし < cacheが効く >\n\nContainerもWritableな独自のLayerを持っている\n\n> だたし、他のContainerとは独立している\n\n### 基本コマンド\n```sh\ndocker info\ndocker pull debian\ndocker run -it alpine ash\n/ # exit\ndocker run -d --name st debian sleep infinity\ndocker container inspect st\ndocker exec -it st bash\ndocker ps\ndocker ps -f status=exited\ndocker images\ndocker container prune\ndocker image prune\ndocker stop st\ndocker start st\ndocker rm -f $(docker ps -a -q)\ndocker rmi -f $(docker images -q)\n# New : 使われていない(＝containerの状態がUPでない)すべてのリソースを削除\ndocker system prune -a\ndocker volume prune\n```\n\n\n### docker volume\n\n他のContainerやhostpsとデータを共有するするために使用、データの永続化のために作成\n\n![イメージ](https://docs.docker.com/storage/images/types-of-mounts-volume.png)\n\n\n![img](docker2-3.png)\n\n```sh\ndocker volume create ssh\n# container作成時にattach(mount)する\ndocker run -d --name ssh --mount src=ssh,dst=/root/.ssh debian sleep infinity\ndocker exec -it ssh bash\n```\n\n> windowのhostpsとfile共有するとパーミッションが755になるので注意\n\n### docker network\n\n> コンテナ間の通知のやり取り\n\n![img](docker2-2.png)\n\n```sh\ndocker network create backend\ndocker run -d --name db --network backend debian sleep infinity\n# networkを明示的に指定することで dockerが提供するDNSを使えるようになる\n# default bridge は container名ではやり取りできない IPアドレスを直接指定することは可能\ndocker run -it --rm --network debian bash\n$ ping db -c 3\n```\n\n### docker file\n\n- remote registory から pull したイメージに独立したlayerを追加して新たなイメージを作成する設計図となる\n\n- Environment variables \n - FROM\n - COPY\n - RUN\n - ENV : containerの動作後に使う環境変数\n - ARG : build時に使う環境変数\n - CMD\n\n> shellの環境変数はbuild時に利用できない\n\n```dockerfile\nFROM debian\nRUN set -x \\\n && apt-get update \\\n && apt-get install -y git vim \\\n && rm -rf /var/lib/apt/list/\n\nARG VIMRC_VERSION\n\nCOPY ./vimrc_${VIMRC_VERSION} /root/.vimrc\n```\n\napt-getを使うのはaptではshをサポートしてないため警告が表示されるため\n\n```sh\nexport VIMRC_VERSION=0.2.0\ndocker build --build-arg 'VIMRC_VERSION=0.1.0' -t t:1 .\n# contextがDockerfileのある場所とこの異なる場合\n# docker build --build-arg 'VIMRC_VERSION=0.1.0' -t t:2 -f Dockerfile-Alt ./context\ndocker run -it t:1 bash\n```\n\n### docker-compose とは\n\n#### できること\n\n- 上記で説明したDokcer container間の連携を宣言的に記述できる\n- 一つのhostに独立した環境を作成することができる\n - `-p` or COMPOSE_PROJECT_NAMEを使うことでproject名を明示的に指定できる, 指定しないとディレクトリ名\n- データを引き継いだまま updateできる\n - docker-compose up ( imageを更新する場合は --build フラグをつける )\n- multiple compose file [override](https://docs.docker.com/compose/extends/)\n\n#### 使われ方\n\n- 開発環境\n- 自動テスト環境\n- single host deployments\n\n### docker-composeのインストール\n\n> docker for mac (or windows)の方はデフォルトでインストール済み\n\nlinux\n\n```sh\nsudo curl -L \"https://github.com/docker/compose/releases/download/1.24.1/docker-compose-$(uname -s)-$(uname -m)\" -o /usr/local/bin/docker-compose\n\nsudo chmod +x /usr/local/bin/docker-compose\n\n# Alternative install options\n\npip install docker-compose\n```\n\n### docker-composeのための3ステップ\n\n- サービス(app)の実装\n- Dockerfileの定義\n- docker-compose.ymlの定義\n- `docker-compose up` によるアプリの起動\n\n### 実際の使用例\n\n[Docker Engine](https://docs.docker.com/install/) と [Docker Compose](https://docs.docker.com/compose/install/) があればOK\n\n#### python + redis\n\nFLASKとRedisを使ってアクセスカウンタを作成する\n\nプロジェクトについて\n名前空間を分ける `docker-compose -p`オプションで指定, 指定しないとディレクトリ名でプロジェクトが作成される\n\n- サービス(app)の実装\n\napp.py\n\n```python\nimport time\n\nimport redis\nfrom flask import Flask\n\napp = Flask(__name__)\ncache = redis.Redis(host='redis', port=6379)\n\n\ndef get_hit_count():\n retries = 5\n while True:\n try:\n return cache.incr('hits')\n except redis.exceptions.ConnectionError as exc:\n if retries == 0:\n raise exc\n retries -= 1\n time.sleep(0.5)\n\n\[email protected]('/')\ndef hello():\n count = get_hit_count()\n return 'Hello World! I have been seen {} times.\\n'.format(count)\n```\nrequirements.txt\n\n```txt\nflask\nredis\n```\n\nFLASKのdefault portは5000\n\nDockerfile\n\n```docker\nFROM python:3.7-alpine\nWORKDIR /code\nENV FLASK_APP app.py\nENV FLASK_RUN_HOST 0.0.0.0\nRUN apk add --no-cache gcc musl-dev linux-headers bash\nCOPY requirements.txt requirements.txt\nRUN pip install -r requirements.txt\nCOPY . .\nCMD [\"flask\", \"run\"]\n```\ndocker-compose\n\n```yaml\nversion: '3.7'\nservices:\n web:\n build: .\n ports:\n - \"5000:5000\"\n redis:\n image: \"redis:alpine\"\n```\n\nBuild and run\n\n```sh\n# build コンテキストの変更が反映されないので --build オプションをつけたほうが無難 cacheは効く\n$ docker-compose up --build\n\n# 立ち上がったサービスには docker-compose exec でプロセスを立ち上げることができる\n# docker-compose execはデフォルトでTTYを確保する\n# コンテナ名ではなくサービス名を入れることに注意\n$ docker-compose exec web bash\n\n# cmdを上書きし別のcontainerを立ち上げる\n$ docker-compose run web bash\n```\n\nRe-build\n\ndocker-compose fileを編集する\n\n```yaml\nversion: '3.7'\nservices:\n web:\n build: .\n ports:\n - \"5000:5000\"\n volumes:\n - .:/code\n environment:\n FLASK_ENV: development\n redis:\n image: \"redis:alpine\"\n```\n\n> FLASK_ENV=development は appが変化した場合Flask ServerをReloadし直す\n\n```sh\ndocker-compose up\ndocker-compose down\n# 指定したserviceのcontainerを立ち上げる ※depends_onに指定されているサービスも立ち上げる\ndocker-run \ndocker-compose stop\n# 無名volumeを一緒に削除 redisは無名volumeをdockerfileの中で作成するのでそのvolumeを削除\n# docker compose file内で定義した volume も削除する\n# docker-compose down --volumes\n```\n\n> docker-composeを使うときは、コンテキストに位置に注意する docker-composeがdocker-compose.ymlを見つけれないと実行できない\n\n### Multiple Compose files\n\nデフォルトでは docker-compose.ymlとdocker-compose.override.yml\n\n```sh\ndocker-compose -f docker-compose.yml -f docker-compose.dev.yml up\n```\n\nでdocker-compose.ymlをベースにdocker-compose.dev.ymlを上書きできる\n\ndocker-compose.dev.yml\n\n```yaml\nversion: \"3.7\"\nservices:\n web:\n volumes:\n - .:/code\n environment:\n FLASK_ENV: development\n```\n\n### 環境変数\n\ndocker-composeならhostpcのshellの環境変数をそのまま利用することができる\ndocker-compose.yamlと同じディレクトリに置かれた`.env` fileがデフォルトの環境変数ファイルとなる\n\n> Dockerfileは直接 shellの環境変数を扱うことができない\n\n> ```yaml\n> version: '3.7'\n> services:\n> web:\n> build:\n> context: .\n> args:\n> buildarg: 1\n> #or - buildarg=1 リストでも指定可能\n> ports:\n> - \"5000:5000\"\n> volumes:\n> - .:/code\n> environment:\n> FLASK_ENV: development\n> redis:\n> image: \"redis:alpine\"\n> ```\n\n環境変数の優先順位\n\n1. Compose file\n1. Shell environment variables\n1. Environment file (.env)\n1. Dockerfile (ENV)\n1. Variable is not defined\n\napi.env\n\n```txt\nCOMPOSE_ENV=test\n```\n\ndocker-compose.yaml\n\n```yaml\nversion: '3'\nservices:\n api:\n image: 'debian:10'\n env_file:\n - ./api.env\n environment:\n - COMPOSE_ENV=production\n command:\n - sleep\n - infinity\n```\n\n```sh\nexport COMPOSE_ENV=shell\ndocker-compose up\ndocker-compose exec api bash\n$ env \| grep COMPOSE_ENV\n```\n\n### network aliases\n\n```yaml\nversion: \"3.7\"\n\nservices:\n web:\n image: \"nginx:alpine\"\n networks:\n - new\n\n worker:\n image: \"my-worker-image:latest\"\n networks:\n - legacy\n\n db:\n image: mysql\n networks:\n new:\n aliases:\n - database\n # newのnetworkでは db or databeseとして公開される\n legacy:\n aliases:\n - mysql\n # legacyのnetworkでは db or mysqlとして公開される\n\nnetworks:\n new:\n legacy:\n```\n\n### VSCode Remote Container Debug\n\n[VSCode Extention](https://code.visualstudio.com/docs/remote/containers)\n\n```sh\ngit clone https://github.com/Microsoft/vscode-remote-try-python\n```\n\n#### 要素の説明\n\n- `.devcontainer`\n - Dockerfile\n - docker-compose.yaml\n - devcontainer.json : vscode用の設定ファイル\n- `.vscode`\n - launch.json : debug時に実行する環境の定義\n - task.json : debug実行時に実行するコマンド定義 lauch.jsonから参照される\n\n### Dind\n\ndocker in docker のデモ dockerの中でdocker containerを作成できるから便利\n\ndocker-compose.yaml\n\n```yaml\nversion: '3.7'\nservices:\n dind:\n image: docker:dind\n networks:\n - dind-net\n environment:\n DOCKER_TLS_CERTDIR:\n privileged: true\n \n python3:\n build:\n context: .\n target: python3-dev \n networks:\n - dind-net\n volumes:\n - app-data=/app\n environment: \n DOCKER_TLS_CERTDIR:\n DOCKER_HOST: tcp://dind:2375\n command: 'sh -c \"while sleep 3600; do :; done\"'\n \n init: true\n\nnetworks:\n dind-net:\n\nvolumes:\n app-data:\n```\n\nDockerfile\n\n```dockerfile\nFROM docker:stable AS base-stage \n\n# RUN addgroup -S -g 1000 tukky && adduser -S -G tukky -u 999 tukky\n\nRUN apk add --no-cache bash tzdata curl wget vim git sudo shadow \\\n && cp /usr/share/zoneinfo/Asia/Tokyo /etc/localtime \\\n && apk del tzdata\n\n# USER tukky\n\nRUN wget https://raw.githubusercontent.com/git/git/master/contrib/completion/git-prompt.sh -O ${HOME}/.git-prompt.sh \\\n && mkdir -p ${HOME}/.vim/autoload && wget https://raw.githubusercontent.com/junegunn/vim-plug/master/plug.vim -O ${HOME}/.vim/autoload/plug.vim \\\n && echo . ${HOME}/.git-prompt.sh >> ${HOME}/.bashrc \\\n && echo \"PS1='\\[\\e[36m\\]\\h\\[\\e[m\\] \\[\\e[32m\\]\\W\\[\\e[m\\] <\\t> \\$(__git_ps1 \\\"( %s ) \\\") \\$ '\" >> ${HOME}/.bashrc\n\nRUN [ -z ${http_proxy} ] \|\| echo export http_proxy=${http_proxy} >> ${HOME}/.bashrc\n\nRUN echo -e \"set nocompatible\\n\\\nfiletype off\\n\\n\\\ncall plug#begin('~/.vim/plugged')\\n\\n\\\nPlug 'VundleVim/Vundle.vim'\\n\\n\\\ncall plug#end()\\n\\\nfiletype plugin indent on\\n\\\nsyntax enable \\n\\n\\\nset st=4 ts=4 sw=4\" \| tee ${HOME}/.vimrc\n\nCMD [\"sh\", \"-c\", \"while sleep 3600; do :; done\"]\n\nFROM base-stage AS python3-dev\n\nWORKDIR /venv\n\nRUN apk add --no-cache python3 python-dev gcc g++ gfortran openblas-dev linux-headers\\\n && python3 -m venv .venv \\\n && . .venv/bin/activate \\\n && pip install -U pip setuptools \\\n && pip install python-language-server flake8 \\\n && echo . /venv/.venv/bin/activate >> ${HOME}/.bashrc\n\nWORKDIR /app\n\nCMD [\"bash\"]\n```\n\n```sh\ndocker-compose up -d --build\ndocker-compose exec python3 bash\ndocker-compose run python3\ndocker-compose down --volume\n```\n\n### リファレンス\n\nビルドコンテキスト内で飲み有効なコマンドとdocker-compose全体に対するコマンドを区別する\n\n- version\n- < service name >\n- build\n - context\n - dockerfile\n - args: docker build --build-argと同じ obj or list で指定\n - cache_from : ci のとき有効\n - shm_size\n - target : multi stage buildのtarget指定\n- image\n - 単体で使うと registoryからimageのダウンロード\n - buildとあわせるとimage名の指定\n- cap_add,cap_drop\n- init: init プロセスから起動されるようになる (docker-init) version 3.7 以降\n - 子プロセスのゾンビ化を防ぐ\n- command\n- depends_on\n- devices\n- entrypoint\n- env_file\n- environment\n- expose\n- logging\n- networks: short format, long format\n - aliasesとの組み合わせが強力\n- ports\n- restart: no, always, on-failure, unless-stopped\n- volumes: short format, long format\n- name\n\n" }, { "alpha_fraction": 0.7117767930030823, "alphanum_fraction": 0.7345917224884033, "avg_line_length": 24.02053451538086, "blob_id": "aa1f5accc4693afe741385ce8f7496122061bf2a", "content_id": "dab87ff3b6e747f24b31b3cd62c4d831dd45ba1d", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 16301, "license_type": "no_license", "max_line_length": 260, "num_lines": 487, "path": "/ch2.md", "repo_name": "tukkyr/docker-st", "src_encoding": "UTF-8", "text": "# いろいろなプログラミング環境で使うDockerのコツ\n\n## 第二回目\n\n### 第二回目の目標\n\n注意: linuxのコマンドを前提にしているのでwindowsの方はwindows用のコマンドに置き換えて実行してください\n\n#### 第一回目の振り返り\n\n- Dockerの基本的な概念 docker image, container について\n- Docker で最も使うコマンドの復習\n\n[第一回目リンク先](https://github.com/tukkyr/docker-st/blob/master/ch1.md)\n\n![dockerimg](https://docs.docker.com/engine/images/architecture.svg)\n\n```sh\ndocker info\ndocker run -it alpine ash\n/ # exit\ndocker run -d --name st debian sleep infinity\ndocker container inspect st\ndocker exec -it st bash\ndocker ps\ndocker ps -f status=exited\ndocker images\ndocker container prune\ndocker image prune\ndocker stop st\ndocker start st\ndocker rm -f $(docker ps -a -q)\ndocker rmi -f $(docker images -q)\n```\n\n#### Dockerのstrageとvolumeについて\n\n- imageのLayer管理について\n- Container 独自のLayerについて\n\n- image type\n - volume\n - bind\n - tempfs\n\n- 実際にデモで\n - volumeを使う\n - コンテナ間のデータの共有\n - bindを使う\n - データのバックアップ\n\n#### Dockerのネットワーク\n\n- ネットワークの確認方法\n - ping コマンド\n - ss コマンド\n - ip コマンド\n - dig コマンド\n - tcpdump\n\n- container間の通信\n - デフォルト network (bridge)\n - user network (type bridge)\n\n#### etcdをマルチコンテナーで構成 or localdynamodb\n\n[etcd](https://etcd.io)\n\n- k8sのdbとして使われている key-value型の分散ストレージ\n - マルチノードで動作する\n\n#### 次回に向けて\n\n- Dockerfileの書き方\n\n絶対に見ておくべき資料\n\n[ベストプラクティス](https://docs.docker.com/develop/develop-images/dockerfile_best-practices/)\n\n- Docker compose\n\n---\n\n### Dockerのストレージ\n\n![img](docker2.png)\n\nimageがLayer構成になっていることは説明したが、\nContainerも独自のLayerを持っている\n\nimage名:tag名 = layer(ro)のセットに名前をつけている\n\n```sh\ndocker pull python:latest\ndocker history python:latest\n# python:latestの実態を表示\n```\n\nContainerとイメージの差分はdiffで取得できる\n(削除も追加も記録される削除してもimageのサイズは変更されない)\n\n```sh\ndocker run -it alpine ash\n# 以下alpine linuxでの作業\n/ # cd\n/ # touch test.txt\n/ # head -c 1024 /dev/urandom > test2.txt\n/ # ctl+p, ctl+q\n# 以下host psでの作業\ndocker diff <container id>\n\n# or\n# runを使わずにash(bash)を立ち上げる方法 <こっちの方が好み>\ndocker run -d alpine sh -c 'while sleep 3600; do :; done'\n# debianの場合は docker run -d debian sleep infinity でOK\n#<container id>\ndocker exec -it <container id> ash\n/ # ps -ef で sleep と ash が起動していることを確認\n```\n\n```sh\ndocker ps -s\n# size: R/W layer で利用した size\n# virtual size: imase + R/W layer\n# CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES SIZE\n# 606d3c712c48 alpine \"ash\" 5 minutes ago Up 5 minutes pensive_ride 1.42MB (virtual 7MB)\n```\n\n実装はlnux kernel1の`overlayfs`で実現されている\n\n```sh\ndocker info\n```\n\n※[実際はLinux distributionによって異なる](https://docs.docker.com/storage/storagedriver/select-storage-driver/)\n\n```sh\nsudo ls /var/lib/docker/containers\nsudo du -sh /var/lib/docker/containers/\n```\n\n> docker for macの人は vm上に作成されているため直接 /var/lib/docker 以下を見ることができない\n>\n> `screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty` で vmのttyにアタッチすることで確認可能 (ctl+a,dでデタッチ可能)\n> docker for windows の方は hyper-vのvmにアクセスする必要があるのですが、windows pcで作業確認時間がなく未確認です　すいません\n\ncontainerのlayerはcontainer毎にことなるため、変化内容をcontainer間で共有することが\nできない、そこで volume が登場する\n\n### Dockerのvolume\n\n![img](docker2-3.png)\n\nDockerのvolumeではよく使われるものが3種類ある\n\n- 永続化可能\n - volume: docker専用領域を使うデフォルトでは /var/lib/docker/volume/XX/_data\n - bind: host pcのfilesystemの領域をそのまま containerでも利用する\n- 永続化不可能\n - tempfs: memory上に一時的に領域を確保する\n\n> docker for macの人は vm上に作成されているため直接 /var/lib/docker 以下を見ることができない\n>\n> `screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty` で vmのttyにアタッチすることで確認可能\n\n![イメージ](https://docs.docker.com/storage/images/types-of-mounts-volume.png)\n\n-v (--volume) と --mount のオプションがあり\nDocker 17.06 から --mount オプションを使うことを推奨されている\nただしこちらは削除予定はなく`should`レベルにとどまっている\n\n > New users should try --mount syntax which is simpler than --volume syntax.\n\n本イベントでは`--mount`を使う\n\n- The type of the mount, which can be `bind`, `volume`, or `tmpfs`. This topic discusses volumes, so the type is always `volume`.\n- The source of the mount. For named volumes, this is the name of the volume. For anonymous volumes, this field is omitted. May be specified as `source` or `src`.\n- The destination takes as its value the path where the file or directory is mounted in the container. May be specified as `destination`, `dst`, or `target`.\n- The readonly option, if present, causes the bind mount to be mounted into the container as `read-only`.\nThe volume-opt option, which can be specified more than once, takes a key-value pair consisting of the option name and its value.\n\n英語で書かれているが、要するに type(マウントタイプ)とsource(マウント元)とdestination(マウント先)を決めて、\nread-onlyにするかどうか選ぶこと\n\n`--mount type=volume,src=vol,dst=/app`のように使う\n\n#### volumeを作成する(type volume)\n\n```sh\ndocker volume create vol\ndocker volume inspect vol\n# 存在しないvolumeを指定すると自動的に新しいvolumeが作成される\ndocker run -d --name devtest --mount src=vol2,dst=/app nginx:latest\n# docker run -d --name devtest -v myvol2:/app nginx:latest\ndocker run -d --name nonametest --mount dst=/app nginx:latest\n# 名前を指定しないと適当なハッシュ値でvolumeを作成する\ndocker volume ls\n```\n\n#### volume mount 共有\n\n```sh\ndocker run -d --mount src=vol,dst=/app alpine touch /app/test.txt\ndocker ps -a\ndocker run -it --mount src=vol,dst=/app alpine ash\n# 後片付け\ndocker volume prune\ndocker rm -f $(docker ps -a -q)\n```\n\n#### bind\n\n```sh\ndocker run -it --name devtest --mount type=bind,source=\"$(pwd)\"/target,target=/app alpine ash\n# docker run -d -it --name devtest -v \"$(pwd)\"/target:/app nginx:latest\n# macのかたは Docker for mac でfileシェアを有効にしておく必要がある\n# windows のかたは c:/<path> のように指定する Docker for windows で fileシェアを有効にしておくひつようが有る\n```\n\n#### Backup (時間が余った方は)\n\ndockerの領域は直接Accessできないためtype volumeとbindを使ってcontainerを介して行う\n\n```sh\n# backup a container\ndocker run --mount dst=/dbdata --name dbstore ubuntu /bin/bash\ndocker run --rm --volumes-from dbstore --mount type=bind,src=$(pwd),dst=/backup ubuntu tar cvf /backup/backup.tar /dbdata\n# --volumes-from は指定した containerの volue設定をそのまま受け継ぐ\n```\n\n```sh\n# restore container from backup\ndocker run --mount dst=/dbdata --name dbstore2 ubuntu /bin/bash\ndocker rundocker run --rm --volumes-from dbstore2 --mount type=bind,src=$(pwd),dst=/backup ubuntu bash -c \"cd /dbdata && tar xvf /backup/backup.tar --strip 1\"\n```\n\n[参考](https://docs.docker.com/storage/volumes/)\n\n---\n\n### Dockerのネットワークについて\n\nipv4のネットワークとvethによる仮想L2スイッチ, brctlによる仮想L３スイッチが内部で使われているため\nネットワークのL2,L3に詳しくないとついていくのは厳しいかも\n\n内容が理解できなかった方はcontainer間の通信方法注目していただけると助かります\n\n![img](docker2-2.png)\n\n上の図のようにBridge networkを利用して通信を行う\n実際の実装は kernel namespace と veth(L2トンネリング) と brctl(L3スイッチ) により実現\n\n--linkと環境変数をつかったやり方は将来削除予定のため今回は説明の対象外　詳しくは[こちら](https://docs.docker.com/network/links/)\n\n> Warning: The --link flag is a legacy feature of Docker. It may eventually be removed. Unless you absolutely need to continue using it, we recommend that you use user-defined networks to facilitate communication between two containers instead of using --link.\n\n#### ネットワーク調査用のツール\n\n- ping: 疎通確認\n- ss: tcp, udp port, linux scket の状態確認\n - `ss -nplt`: は LISTEN portを見るのによく使う\n- ip: ネットワークの設定確認\n - `ip link show`, `ip addr show`\n - `ip -f inet -o addr show eth0 \| awk '{print $4}' \| cut -d/ -f 1`: eth0のipaddrを抜き出す\n - `ip route show local`: ローカルのroute tableの表示\n - `ip route show main`: 外部との通信を行う際のtableを表示\n- dig: DNS のリクエスト情報の確認 (`apt install dnsutils`でインストール)\n - dig www.google.com: google DNS サーバーへの DNS呼び出しをトレースする\n - nslookupでもOK\n- tcpdump: 今回は時間の都合上省略する tpcのパケットを調査するときに使う\n- ps: Processを確認するのに利用 (`apt install procps`でインストール)\n\n#### 公式のチュートリアルにトライしよう\n\n[リンク先](https://docs.docker.com/network/network-tutorial-standalone/)\n\n> 公式チュートリアルでは alpine linux を使っていますが、より細かい情報を取得するために\n> debian linuxを本イベントで利用します。\n\n##### User-Dridge\n\n```sh\ndocker run -dit --name co1 --network net debian bash\ndocker run -dit --name co2 --network net debian bash\ndocker run -dit --name co3 debian bash\ndocker run -dit --name co4 --network net debian bash\ndocker network connect bridge co4 # bridgeをco4にアタッチ\n```\n\nサブネット知識が必要になる\n\n- ipaddr : 自分に振られているIPアドレス\n- subnet mask: network部とhost部に分ける 172.17.0.2/16のような表記になっていることが多い (CIDR)\n - 上記の例だと11111111111111110000000000000000のようなマスクをipaddrに適応することで 172.17.0.0というnetworkアドレスを取得する\n- gateway: 別のネットワーク部にpopするためのアドレス 172.17.0.1 今回は brctlによって内部にL3仮想スイッチが作られている\n\n- 同じnetworkに属する host同士直接通信が可能\n- 異なるnetworkに属する host同士 gatewayを通して通信可能 napt(out方向), portmapping,portforward(in方向) (brctl, iptableによって実現)\n\n```sh\ndocker container ls -f name=co\ndocker network inspect bridge\ndocker network inspect net\n\n# どこかにメモしておく\n# Subnetが 172.17.0.0 と 172.18.0.0 でネットワークが分離されている\n```\n\n```sh\ndocker container attach co1\n# ip -f inet -o addr show で eth0の状態を確認\n/ # apt update\n/ # apt install -y dnsutils\n/ # ping -c 2 co2\n/ # ping -c 2 co4\n/ # ping -c 2 co3\n# 同じネットワーク上にいないので見つからない `docker network inspect net`\n/ # cat /etc/resolv.conf\n/ # dig co2\n```\n\n```sh\ndocker container attach co4\n/ # ping -c 2 co1\n/ # ping -c 3 co3\n# bad address 'co3'\n/ # ping -c 172.17.0.2 #co3 のipaddressを直接指定\n```\n\n以上のことより dockerのcontainer間で通信するには\n\nhost名に対象の名前を指定してすれば良い\n\n細くネットワーク設定がどうなっているか調べる\n\n```sh\nip link show\ndocker container attach co4\n/ # ip link show\n/ # apt update\n/ # apt install dnsutils\n/ # dig co1 A\n/ # cat /etc/resolv.conf\n# 127.0.0.11 に向いているはず\ndocker container attach co3\n/ # cat /etc/resolv.conf\n# host pc と同じ DNS server に向いているはず\n```\n\n後片付け\n\n```sh\ndocker rm -f co1 co2 co3 co4\ndocker network rm net\n```\n\n応用編 NAPTの設定を確認する\n\n```sh\nsudo bridge-utils\nbrctl show\ndocker network create test-net\ndocker run -it --net test-net alpine sleep infinity\ndocker run -it --name napt --net test-net debian bash\n/ apt update\n/ apt install dnsutils\n/ ip link show eth0\n# veth のペアを調べる\n# デタッチ\nip link show\n# veth のベアを調べる\nbrctl show\nsudo iptables --table nat --list\nip route show table local\nip route get 8.8.8.8\ndocker attach napt\n/ ip route get 8.8.8.8\n# 172.17.0.0から来たパケットはallに渡される hostで `ip route get 8.8.8.8`したときと同じRouteを通る\n/ ip route show table main\n/ ip route show table local\n```\n\n#### host pcからcontainer内にアクセスする\n\nportmappingを使う, docker runの実行時に指定する\n\nrun以外のタイミングでは指定できない\n\n```sh\ndocker run -it --name py-server1 -p 8080:8080 python:3 bash\n# / mkdir /app\n# / cd /app\n# / cat /etc/hostname > index.html\n# / ip addr\n# / python -m http.server 8080\n# デタッチして\nsudo iptables --table nat --list\n# portforwordingを確認\nsudo ss -lnpt\n# :8080でlistenされていることを確認\n\n# ブラウザからアクセス localhost:8080\ndocker run -it --name py-server2 --expose 8081 -P python:3 bash\n# / python -m http.server 8081\n# デタッチして\nsudo ss -lnpt\n```\n\nrun時に -p オプションを指定することで hostpcからcontainerにアクセスできる\n\n[networkアーキテクチャで参考になりやすそうなサイト](https://success.docker.com/article/networking)\n\n---\n\n### Docker内部からhostPCにアクセスする\n\n#### hostPCがlinuxの場合\n\n```sh\nip -f inet -o addr show docker0\n# docker0 gateway の broadcastアドレスを調べる\nip -f inet -o addr\n# host pc の docker0 の転送先のipを調べる\ndocker run -i alpine ping -c 2 < host ip >\n# 疎通確認をする\n```\n\n#### hostPCがdocker for mac (or windows)の場合\n\nvm上で Docker Demonが立ち上がっているため osのip を調べてもたどり着かない\n\n公式ページに解決方法が記載されている (host.docker.internal) を利用する\n\n```sh\ndocker run -i alpine ping -c 2 host.docker.internal\n```\n\n[for mac](https://docs.docker.com/docker-for-mac/networking/)\n\n[for windows](https://docs.docker.com/docker-for-windows/networking/)\n\n##### ホストネットワーク\n\nlocalhostでお互いと通信することができる\n\nhostのnetifをそのまま利用している\n\neh0もdocker0のnetifもそのまま利用できる\n\n[リンク先](https://docs.docker.com/network/network-tutorial-host/)\n\n### etcdを使う\n\nT.B.D\n\n> Enable synchronize-panes: ctrl+b then shift :. Then type set synchronize-panes on at the prompt. To disable synchronization: set synchronize-panes off.\n\n```sh\ndocker network create etcd-net\ntmux\ndocker run -it --name srv1 --net etcd-net debian bash\n#eh0のuser bridgeのip address取得\nip -f inet -o addr show eth0 \| awk '{print $4}' \| cut -d/ -f 1\nexport ETCD_IP_ADDR=$(!!)\nwget https://github.com/etcd-io/etcd/releases/download/v3.4.0-rc.2/etcd-v3.4.0-rc.2-linux-amd64.tar.gz\ntar xvfz etcd-v3.4.0-rc.2-linux-amd64.tar.gz\ncd etcd-v3.4.0-rc.2-linux-amd64/bin\n./etcd --name ${HOSTNAME} --listen-peer-urls http://${ETCD_IP_ADDR} --initial-advertise-peer-urls http://${ETCD_IP_ADDR} --initial-cluster srv1=http://172.18.0.2:2380,srv2=http://172.18.0.3:2380 &\n./etcdctl member list\n# 片方のcontainerで\n./etcdctl set /foo bar\n./etcdctl get /foo\n./etcdctl ls\n# などを実行\n```\n\n### 補足\n\n#### Docker の logging\n\n[loging](https://docs.docker.com/config/containers/logging/configu)\n\n#### Docker のセキュリティー\n\n```sh\n--cap-add=SYS_PTRACE --security-opt seccomp=unconfined\n```\n" }, { "alpha_fraction": 0.7180553078651428, "alphanum_fraction": 0.725971519947052, "avg_line_length": 18.947368621826172, "blob_id": "6c55889af363ddfa87ab962e0366739df2ebe8c0", "content_id": "d9e2440eda82fa1bba43c940cdfe59c0f92c1846", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 18690, "license_type": "no_license", "max_line_length": 138, "num_lines": 627, "path": "/ch3.md", "repo_name": "tukkyr/docker-st", "src_encoding": "UTF-8", "text": "# 色々なプログラミング環境で使うDockerのコツ\n\n## 第３回目\n\n参考資料\n\n- https://www.slideshare.net/Docker/dcsf19-dockerfile-best-practices/52\n- https://docs.docker.com/develop/develop-images/dockerfile_best-practices/\n- https://www.slideshare.net/zembutsu/dockerfile-bestpractices-19-and-advice?next_slideshow=1\n- https://www.slideshare.net/AkihiroSuda/buildkit\n\n### 今までの振り返り\n\n#### Dockerの基本的な概念\n- Docker Registry, Images, Containers\n- Docker volume, network\n\n#### Dockerで最も使うコマンドの復習\n\n```sh\ndocker info\ndocker run -it alpine ash\n/ # exit\ndocker run -d --name st debian sleep infinity\ndocker container inspect st\ndocker exec -it st bash\ndocker ps\ndocker ps -f status=exited\ndocker images\ndocker container prune\ndocker image prune\ndocker stop st\ndocker start st\ndocker rm -f $(docker ps -a -q)\ndocker rmi -f $(docker images -q)\n```\n\n#### 図でDockerの概要を振り返る\n- Docker repgitry image container\n\n![dockerimg](https://docs.docker.com/engine/images/architecture.svg)\n\n- repgitry: パブリック・ローカルのdocker image 管理場所 (docker における git repgitry みたいなもの)\n- image: クラス\n- container: インスタンス\n\n- Dokcer image の階層構造\n\n![img](docker2.png)\n\n- docker history < container id > で確認できる\n- コンテナは独自のlayerを持っている\n\n- volumeのマウント\n\n![img](docker2-3.png)\n\n- --mount オプションを `docker run` 時に使う\n- type: volume, bind, tmpfs など\n\n- docker container 間の Network \n\n![img](docker2-2.png)\n\n- --net オプションを `docker run`に使う\n- 指定しないと defualt bridge が使われる ipで通信できるが host名で通信できない\n- `docker network create xx` で新しい　bridge networkが作成できる host名で通信できる\n - `docker network inspect` で networkに所属するcontainerの情報を確認できる\n\n### Dockerfileの基本コマンド\n\n- `FROM` < base layer の取得 >\n- `COPY` < layer が作成される >\n- `RUN` < layer が作成される >\n- `CMD`\n - `[\"bash\"]` `[]`を省略すると bin/shから呼び出されたことになる\n- `WORKDIR`\n\n> ADD は使わないことを推奨\n> For other items (files, directories) that do not require ADD’s tar auto-extraction capability, you should always use COPY.\n\n### stdinを利用して Docker imageを作成する\n\n- Build Context なし\n- Build Context あり\n - local build context\n - remote build context (from Github < https: xxx >)\n- .dockerignore\n\n### image サイズビルド時間をへらすコツ\n\n- 不要なパッケージのインストールをへらす `--no-install-recommends` `apk add --no-cache`\n- multi-stage builds はアーティファクトのみ入れる\n- パッケージ用のキャッシュは削除\n - `rm -rf /var/lib/apt/list/`\n - `rm -rf /var/cache/yum/`\n\n### 構築キャッシュの利用\n\n- ADDとCOPYはチェックサムをチェックする\n - ADDは余計なものもキャッシュする可能性がある (curl tar を使う)\n- RUN 命令文の差分しか見ない RUN apt-get update が古くても比較されない\n- 最小限のものをコピーする\n\n### ENV と ARG の使い分け\n\n- ARGもENVもimageのヒストリーに値が記録されてしまう\n- ARGはbuild時に指定して変更することができる\n- ENVは変化しない値として Dockerfile CMD なので使う\n - ARG docker build時のみ RUNの前で渡される\n - ENVは docker container 上でも使える \n - http_proxyとhttps_proxyをargとして使った場合は特別にヒストリーに値が保存されない\n\n### multi-stage builds\n\n- Imagenのサイズ減らすコツ\n- CIパイプラインの構築もできる\n\n> cacheをへらす手段もある\n- ステージとしての検討例 (stage を base に image にイメージを作成できる)\n - builder: 依存関係\n - build: builder + ビルド成果物\n - cross: 複数プラットフォーム向けに構築\n - dev: builder + 開発 / デバッグツール\n - lint: 最小限の構築チェック\n - test\n - release\n- COPY --from で並列化 (18.09からサポートされている buildkitを有効にする必要がある)\n - prefixをつける\n\n### パイプの利用\n\n- `\|`,`&&`,`\|\|`の3パターン\n\n#### 本番環境で使う\n\n- 構築部分は依存関係をチェック\n- multi-stage buildsで生成物のみ入れる\n- user `exec gosu`, `exec su-exec`\n\n### Docker BuildKit\n\n### その他のコマンド\n\n- `USER`\n\n---\n## 初めてのDockerfile\n\nDockerfileを作成する際に最低限覚えておく必要があるコマンド\n\n- FROM : ベースとなるイメージの指定\n- RUN : docker上で実行するコマンド実行\n - 後記しますが、 `&&` と `\\` 連結することで RUNコマンドで複数コマンドを実行することができる\n- COPY : hostpc コンテキストをdocker上にcopyする\n - 似たようなコマンドにAddがありますが公式でも非推奨 copyで代用できる\n- CMD : docker run で実行コマンドを省略したときに実行される　[\"sleep\" \"infinity\"] のように使う\n\n> For other items (files, directories) that do not require ADD’s tar auto-extraction capability, you should always use COPY.\n\n### stdinを使ったデモ\n\n```sh\necho -e 'FROM alpine:3\\nRUN echo \"hello Dockerfile?\"' \| docker build -t t:t -\n\n# またはヒアドキュメントを使って\n\ndocker build -t t:t --no-cache -<<EOF\nFROM alpine:3\nRUN echo \"hello Dockerfile?\"\nEOF\n```\n\nコンテキストつき hostpcのファイルをdocker上に copyする\n\n> コンテキストとはhostps上に存在するディレクトリを指定するとそれ以下のファイルをすべて COPYコマンドで build 中に扱うことができるようになる\n> すべてのファイルを一度コピーするのでビルドに時間がかかるようになる\n> コンテキストは最低限にどうしても入れる必要がある場合(templateの保持など) .dockerignoreでコピー対象外とすることができる\n\n```sh\necho \"hello context\" > hello.txt\nmkdir child && echo \"child context\" > child/ctx.txt\necho -e 'FROM alpine:3\\nCOPY . /root/ \\nRUN cat /root/hello.txt && cat /root/child/ctx.txt' \| docker build -t t:t -f- .\n```\n\n- コンテキストで指定した親フォルダをしていすることはできない `..`\n- かんたんなコマンドを実行するなら, stdinの利用でOK\n\n### Dockerfileを使ったデモ\n\n```sh\ncat -<<EOF > Dockerfile\nFROM alpine:3\nRUN echo \"hello Dockerfile?\"\nEOF\n\ndocker build -t t:t .\n```\n\nこのようにしておけばベースを作ったあとDockerfileの編集をvimなどのEditorで編集を継続できる\n\n---\n\n## Dockerfile上で環境変数を使いたい\n```sh\nexport ST_ENV=hello\n\necho ${ST_ENV}\n\necho -e 'FROM alpine:3\\nRUN set -ux && echo ${ST_ENV} > /root/hello.txt' \| docker build -t t:t -\n\n# hostの環境変数は引き継ぐことができない\n```\n\n### Dockerfileで環境変数を扱う前に考えること\n\nいつのタイミングでその値が必要になるかで使うコマンド等が異なる\n\n- docker build 時のみ: 機密でなければARGを使おう\n- docker build 時のみ: 機密であれば　--mount\n- docker cmd 時 : 機密でなければ ENVを使いましょう\n- docker cmd 時 : 機密であれば `docker run` の引数として渡しましょう\n\n### ARGを使ったデモ\n\nbuild時に値を変更できる\n\n> 注意: docker historyを使うと設定した値を取得できてしまう\n> https_proxy, http_proxyに関しては historyに残さずに利用できるようになっている\n> https://github.com/moby/moby/issues/30721 に記載あり\n\n```sh\n# ヒアドキュメンで変数が展開されてしまうので \\EOF or \"EOF\" とする\ncat -<<\\EOF > Dockerfile\nARG PYTHON_VERSION_ARG=2\nFROM python:\"${PYTHON_VERSION_ARG}\"\nARG test=1\nRUN python --version\nEOF\n\n# 何もつけないと python:2 をbase imageとしてビルドを行う\ndocker build -t t:t .\n# Status: Downloaded newer image for python:2\n\n# 指定すると build時に好きなtag を指定することができる\ndocker build --build-arg PYTHON_VERSION_ARG=3 --build-arg test=2 -t t:t .\n# Status: Downloaded newer image for python:3\ndocker image history t:t\n# RUNコマンドの前に変数として渡される\n```\n\nビルド時にbaseとするイメージの指定指定がなければデフォルトバージョンを利用する\n\n### ENVを使ったデモ\n\ncmd実行時に利用する (利用の仕方はビルド時に決定してcmd実行に使う定数として使うイメージ)\n\napp.py\n\n```python\nimport os\n\nprint(f'BUILD_ARG is {os.environ.get(\"BUILD_ARG\", \"not found\")}')\nprint(f'BUILD_ENV is {os.environ.get(\"BUILD_ENV\", \"not found\")}')\n```\n\n```sh\ncat -<<\\EOF > Dockerfile\nFROM python:3\n\nWORKDIR /app\n\nARG BUILD_ARG=\"hello\"\nENV BUILD_ENV=${BUILD_ARG}\n\nCOPY app.py .\n\nCMD [\"python\", \"app.py\"]\nEOF\n# ちなみに[\"\", \"\"]を使わずCMD を直接書くと sh -c として実行される\n# [\"\", \"\"]の形書くと execから呼ばれる = processが書き換わる\n# entrypoitに関しても同様\n\ndocker build -t t:t .\n```\n\n---\n\n## RUN の使い方のコツ\n\n### 出来上がるイメージのサイズを削減する\n\nRUN 実行時一回に付き, レイヤーが一つ作られる\n\n```sh\n\ncat -<<\\EOF > Dockerfile\nFROM alpine\n\nWORKDIR /app\nRUN head -c 1000000 /dev/random > rand\nRUN rm rand\nEOF\n\ndocker build -t t:1 .\ndocker image history t:1\n```\n\n改善しましょう\n\n```sh\ncat -<<\\EOF > Dockerfile\nFROM alpine\n\nWORKDIR /app\nRUN set -x && head -c 1000000 /dev/random > rand \\\n && rm rand\nEOF\n# ワンライナーで &&で接続するとどこでエラーがでたか後でトレースしにくい set -x でデバッグ表示\n# && は前のコマンドが成功したら次のコマンドを実行する\n\ndocker build -t t:2 .\ndocker image history t:2\ndocker images\n```\n\n余計なレイヤーができていないことが確認できる\nどういうときに有効なのapt-getなどのchachを削除するとき\n\n`apt-get update && apt-get install --no-install-recommends xx && rm -rf /var/lib/apt/list/` のようにセットとして利用すると良い\n\nalpine linux を使う場合は`apk add --no-cache xx` そもそもキャッシュしない\n\nオフィシャルがdockerhubにイメージを上げているならofficialのものを使う\n\n```sh\n\ndocker build -t python:myenv -<<EOF\nFROM debian:10\n\nRUN set -x && apt-get update \\\n && apt-get install --no-install-recommends python3 python3-pip \\\n && rm -rf /var/lib/apt/list/\n\n# 他のコマンド\nEOF\n\n#このように使うより\n\ndocker build -t python:myenv -<<EOF\n\nFROM python:3\n\n# 他のコマンド\nEOF\n\n# のようにしたほうが良い\n```\n\n> baseを alpine linux にしても良いが開発環境として使う場合やりすぎかも\n> pip install numpy 時にインストールが失敗するなど、ちょっと開発としての環境としては削減しすぎ <あくまで個人的な感想>\n\n時間を減らすためには前述したコンテキストを最低限にするのも効果的\n\n> .dockerignoreの利用\n\nキャッシュが利くようにコマンドの順番に気をつける\n\nキャッシュが利くタイミング\n\n- ADD, COPY: 対象のコンテキストのハッシュ値\n- RUN: docker file の　更新履歴\n\n> RUNの場合は docker fileのRUNコマンドが変更されたかどうかしか見ていない = `RUN apt-get update` を別に書いてしまうと以降の`RUN apt-get install xx`の対象を変更しても古い listを使ってしまう可能性がある\n> RUN一つで apt-get update と　apt-get install を実行するようにしましょう。\n\n### `\|`, `&&` , `\|\|` のパイプの使い分け\n\n```sh\nfalse \|\| echo 1\ntrue \|\| echo 1\n# \|\| 前のコマンドの実行が失敗した場合のみ実行\ntrue && echo 1\n# && 前のコマンドの実行が成功した場合のみ実行\nfalse \| true \| echo 1\n# \| 結果に関わらず実行\n```\n\n> && の使い所　[-n ${ENV}] \|\| exit 1 のように環境変数が定義されているかどうか確かめるときに使う\n> set -u && でもOK\n\n---\n\n## マルチビルドについて\n\n- 本番リリースのためにビルド環境とリリース環境を分ける\n - CIパイプラインがDockerfile一つでかけるのではないかと思うほど強力\n- ベース環境を作って言語ごとに環境を使い回す\n\nmain.go\n```go\npackage main\n\nimport \"fmt\"\n\nfunc main() {\n fmt.Println(\"test\")\n}\n```\n\n`go mod init` で作成\n\ngo.mod\n```go\nmodule tukky/multibuild\n\ngo 1.13\n```\n\nリリース用 Dockerfile\n\n```docker\nFROM golang:1-buster AS builder\n\nWORKDIR /app\n\nCOPY . . \n\nRUN GOOS=linux GOARCH=amd64 go build -o a.out\n\nFROM alpine:3\n\nWORKDIR /app\n\nCOPY --from=builder /app/a.out . \n\nCMD [\"/app/a.out\"]\n```\nalpine linuxをベースにリリース環境を構築できるのでimageサイズを小さくできる\n\n> go GOOS と GOARCH を指定するとクロスコンパイルできる更にシングルバイナリ　コンテナと相性バツグン\n\n開発用 Dockerfile\n\n```docker\nFROM golang:1-buster AS base-env\nWORKDIR /app\n\nFROM base-env AS dev-env\n\nRUN set -x && apt-get update && apt-get install -y --no-install-recommends vim && rm -rf /var/lib/apt/list/\nCMD [\"bash\"]\n\nFROM base-env AS builder\n\nCOPY . . \nRUN GOOS=linux GOARCH=amd64 go build -o a.out\n\nFROM alpine:3 AS release\nWORKDIR /app\nCOPY --from=builder /app/a.out . \nCMD [\"/app/a.out\"]\n```\nWORKDIR も引き継ぐことができる\n\n```sh\n#targetでステージを指定\ndocker build --target dev-env -t t:t .\ndocker run -it --mount type=bind,src=$(pwd),dst=/app t:t\n\ndocker build --target release -t t:t .\n\nexport DOKCER_BUILDKIT=1\ndocker build --target release -t t:t .\n```\n\n> Defaultのbuildでは `--target release`としても依存関係のない builder stageもビルドしようとするなので対策としてDockerfileを２つ用意した\n>\n> 後述する [buildkit](https://github.com/moby/buildkit) を使えば依存関係のあるステージのみビルドするようになる\n\n### gitlab へのimageのアップ\n\ngitlab.comは無料で使えるイメージリポジトリ tagのバージョン管理もできるので個人開発用途なら利用するの良いかも\n\n```sh\ndocker login registry.gitlab.com -p < access token > -u < user name >\ndocker tag t:t registry.gitlab.com/<user name>/<project>/t:v0.1.0\ndocker push registry.gitlab.com/<user name>/<project>/t:v0.1.0\ndocker logout registry.gitlab.com\n```\n\n> access token を使うと、個人用のpassもssh key も必要ない scope は api のみ\n\n### 本番環境のリリースについて補足\n\n今まですべて root 権限で動作させてきた本番環境では user 設定が必要 redis が参考としてわかりやすい\n\nhttps://hub.docker.com/_/redis\n\ndocker-entrypoint.sh\n```sh\n#!/bin/sh\nset -e\n\n# first arg is `-f` or `--some-option`\n# or first arg is `something.conf`\nif [ \"${1#-}\" != \"$1\" ] \|\| [ \"${1%.conf}\" != \"$1\" ]; then\n\tset -- redis-server \"$@\"\nfi\n\n# allow the container to be started with `--user`\nif [ \"$1\" = 'redis-server' -a \"$(id -u)\" = '0' ]; then\n\tfind . \\! -user redis -exec chown redis '{}' +\n\texec gosu redis \"$0\" \"$@\"\nfi\n\nexec \"$@\"\n```\n\n```docker\n# 抜粋\nENTRYPOINT [\"docker-entrypoint.sh\"]\n\nEXPOSE 6379\nCMD [\"redis-server\"]\n```\n\nこれを呼び出すと `docker-entrypoint.sh redis-server` として呼び出される\nサービスに必要なファイルだけオーナーを redisに変えて exec gosu redis でユーザーを redisに変えて\ndocker-entroypoint.sh を呼び出し直す\n\n> gosu ユーザーを指定して実行 apline linux では su-exec\n\n---\n\n## その他のチェックポイント\n\n- 本番リリース環境では1コンテナ1プロセスを守る\n- latestタグを本番環境で使わない tagは明示する\n- キャッシュする順番が重要\n- 行はまとめる (特に`apt-update`などを分けると古いものをキャッシュしてしまう)\n- Docker公式のパッケージを使う\n- タグの指定をする(プログラムで使いたいバージョンを指定する)\n- BaseImageを最小のものを使う (numpyを使いたい場合はalpineを使わないこともある)\n- WORKDIRでrootファイルを移動 COPY XXX . の相対パスを使う\n- `>>` よりも `{} \| tee` を使う\n\n---\n\n## moby/buildkit の利用\n\n[moby/buildkit](https://github.com/moby/buildkit/blob/master/frontend/dockerfile/docs/experimental.md)\n\n```sh\nexport DOCKER_BUILDKIT=1\n```\nで一部機能を有効かできる\n\n```sh\n# 無効化は\nunset DOCKER_BUILDKIT\n```\n\n### buildkitの効果\n\n- buildが早い\n- multi build の効率化\n - 関連するステージのみのビルド\n - --from xx と --from yy が独立している場合はビルドの並列処理を行う\n\n- 新機能の追\n - `# syntax` の行を Dockerfileのはじめに追加する必要がある\n - build 時の特定のRUNコマンドのみで利用できる host psの情報を `--mount`する機能の追加\n - コンテキストマウント : hostのコンテキストをRUNコマンド実行時に行う copyが発生しないので通常のbuildより早い\n - キャッシュ : hostに直接キャッシュすることができる同じパスのcacheは使いまわしできる\n - SECRET: おすすめビルド時だけ必要な情報を `docker build`時にしていでき、imageのヒストリーには一切情報を残さない\n\n> docker for window では現在サポートされていない\n\n### 新機能の一部紹介 (SECRET)\n\n```dockerfile\n# syntax=docker/dockerfile:experimental\n\nFROM alpine:3\n\nWORKDIR /app\n\nRUN set -x && apk add --no-cache git jq\n\nRUN --mount=type=secret,id=test,target=/app/secret.json jq '.' secret.json > check\n```\n\nsecret.json\n\n```json\n{\"TEST\": \"HELLO\"}\n```\n\n```sh\ndocker build --secret id=test,src=$(pwd)/secret.json -t t:t .\ndocker run -it --rm t:t ash\n/app # ls -lh\n# secret.jsonが0byteのfileとして残っているはず\n```\n\n## 次回\n\n### docker-compose\n\n#### 新機能を有効にする\n- https://github.com/moby/buildkit/blob/master/frontend/dockerfile/docs/experimental.md\n- dockerfileの中でmount\n - cache ホスト上でキャッシュ\n - docker builder prune で削除\n - `/var/cache/apt`\n - `/var/lib/apt`\n - `~/.cache/go-build`\n- docker secret ビルド時のみの参照\n\n- docker --mount=type,target=.,rw\n - コンテキストをbuild時に指定できる copyの必要がなくなる\n- docker cache キャッシュを有効にする\n- git clone `https://username:[email protected]`\n\n\n> windowsでは対応してない" }, { "alpha_fraction": 0.7322103381156921, "alphanum_fraction": 0.7467876076698303, "avg_line_length": 18.13429832458496, "blob_id": "5d65744c9821eb9830f795faf627d86ce34b826e", "content_id": "ac776744e0f36d5a59491cc4105b0aa824b58350", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 13243, "license_type": "no_license", "max_line_length": 132, "num_lines": 484, "path": "/ch1.md", "repo_name": "tukkyr/docker-st", "src_encoding": "UTF-8", "text": "# いろいろなプログラミング環境で使うDockerのコツ\n\n## 第一回目\n\n今回は初心者-中級者向けです。もうすでにdockerを使いこなしている方には退屈かもしれませんが\n回を重ねるごとにデープな内容になっていく予定ですので楽しみにしていてください。\n\ndocker内部のDNSの仕組みだったり、overlay mountがどのようにDockerに生かされてるとか\ngitlab.comのプライベートリポジトリにイメージpushしてCI／CAパイプラインで回す方法とかマルチステージビルドとかをやる予定です。\n\n### 一回目目標\n\n#### docker上にjupyterサーバーを立てて, web browserからアクセスできるようにする\n\n#### dockerをpull, runをしたあとに,現環境のdockerの状態を確認できるようにする\n\n- docker installを完了する\n - windows10 pro (docker for windows)\n - mac (docker for mac)\n - linux\n - CentOS\n - Debian\n - Ubuntu\n\n- docker runでpythonの最新環境(3.7.4)を立ち上げる\n - bashでアクセスしてpythonを動作させてみる\n\n- docker runからのデタッチ\n - `ctl-p ctl-q`\n\n- docker bashで変更した内容を確認してみる\n - `bocker diff`\n\n- dockerのimage, containerって何が違うの\n - イメージの中身を確認してみる `docker container history`\n\n- デタッチしたcontainerにAttachし直す\n - `docker attach`\n\n- docker に jupyterサーバーを立てる\n\n- 次回はcommitで作成したimageをDockerfileで作成する\n\n---\n\n## 用語\n\n- NIC: network interface cardの略\n- host PC: docker daemon を動かしているPC\n\n---\n\n## docker install\n\n### もうインストールしたよって方は、VM,AWS,GCPにサーバーを立てて、Dockerをインストールして見ましょう\n\n### windows10 pro\n\nhttps://docs.docker.com/docker-for-windows/install/\n\n- hyper-vの有効化: [参照](https://docs.microsoft.com/ja-jp/virtualization/hyper-v-on-windows/quick-start/enable-hyper-v)\n - Window管理ツールにHyper-v マネージャーが表示されていればOK\n\n- dockerhubのアカウントを作成\n- [インストール先](https://hub.docker.com/editions/community/docker-ce-desktop-windows)\n\n---\n\n### mac\n\nhttps://docs.docker.com/docker-for-mac/install/\n\n- [インストール先](https://hub.docker.com/editions/community/docker-ce-desktop-mac)\n- `Docker.dmg`をダブルクリックすればOK\n\n---\n\n### linux\n\nhttps://docs.docker.com/install/\n\n#### CentOS\n\n```sh\nsudo yum remove docker \\\n docker-client \\\n docker-client-latest \\\n docker-common \\\n docker-latest \\\n docker-latest-logrotate \\\n docker-logrotate \\\n docker-engine\n\nsudo yum install -y yum-utils \\\n device-mapper-persistent-data \\\n lvm2\n\nsudo yum-config-manager \\\n --add-repo \\\n https://download.docker.com/linux/centos/docker-ce.rep\n\nsudo yum install docker-ce docker-ce-cli containerd.io\n\nsudo systemctl start docker\n\n# 再起動後も有効にしたい場合は\nsudo systemctl enable docker\n\n# sudo なしで dockerを実行するため一回shellを再起動する必要がある\nsudo usermod -aG docker your-user\n\n# 動作確認\ndocker info\n```\n\n---\n\n#### Debian\n\n```sh\nsudo apt-get remove docker docker-engine docker.io containerd runc\n\nsudo apt-get install \\\n apt-transport-https \\\n ca-certificates \\\n curl \\\n gnupg2 \\\n software-properties-common\n\ncurl -fsSL https://download.docker.com/linux/debian/gpg \| sudo apt-key add -\n\n# x86_64 / amd64 アーキの場合\nsudo add-apt-repository \\\n \"deb [arch=amd64] https://download.docker.com/linux/debian \\\n $(lsb_release -cs) \\\n stable\"\n\nsudo apt-get update\n\nsudo apt-get install docker-ce docker-ce-cli containerd.io\n\n# systemctl list-units --type=service でdockerのサービス名を確認する\nsudo systemctl start docker.service\n\n# 再起動後も有効にしたい場合は\nsudo systemctl enable docker.service\n\n# sudo なしで dockerを実行するため一回shellを再起動する必要がある\nsudo usermod -aG docker your-user\n\n# 動作確認\ndocker info\n```\n\n---\n\n#### Ubuntu\n\n```sh\nsudo apt-get remove docker docker-engine docker.io containerd runc\n\nsudo apt-get update\n\nsudo apt-get install \\\n apt-transport-https \\\n ca-certificates \\\n curl \\\n gnupg-agent \\\n software-properties-common\n\ncurl -fsSL https://download.docker.com/linux/ubuntu/gpg \| sudo apt-key add -\n\nsudo apt-key fingerprint 0EBFCD88\n\n# x86_64 / amd64 アーキの場合\nsudo add-apt-repository \\\n \"deb [arch=amd64] https://download.docker.com/linux/ubuntu \\\n $(lsb_release -cs) \\\n stable\"\n\nsudo apt-get update\n\nsudo apt-get install docker docker-compose\n\n# systemctl list-units --type=service でdockerのサービス名を確認する\nsudo systemctl start docker.service\n\n# 再起動後も有効にしたい場合は\nsudo systemctl enable docker.service\n\n# sudo なしで dockerを実行するため一回shellを再起動する必要がある\nsudo usermod -aG docker your-user\n\n# 動作確認\ndocker info\n```\n\n## Pythonの環境を立ち上げる\n\nofficial repo: https://hub.docker.com/_/python\n\n```sh\ndocker search python\ndocker run -it python:3.7.4-buster bash\n```\n\ndocker が localに python:3.7.4-busterのimageがなければ Dockerhubからimageを取得する\n\nimageはコンテナを作成する設計図だと思ってくれればOK\n\n`-it` 標準入力とターミナルを作成することを指定今回はbashを動かすためにしていていると思ってくれればOK\n\n- `--interactive` 対話\n- `--tty`\n\npython:3.7.4-buster は image名:tagの組み合わせでできている\n\nタグの一覧は\n\nhttps://registry.hub.docker.com/v2/repositories/library/${image}/tags/\n\n```sh\n# 例\ncurl https://registry.hub.docker.com/v2/repositories/library/python/tags/?page=4 \| jq .results[].name\n```\n\nから取得できるレスポンスがjsonフォーマットなので`jq`で加工すれば良い\nhttps://stedolan.github.io/jq/manual/\n\n※windows for dockerはpullに失敗する404 not foundを出す可能性が有るその際は settingからDNSサーバーを8.8.8.8(google dns)にすれば解決することがある\n\n```sh\nroot@host名(コンテナ名):\n```\n\nのような表示になるはず\n\n```sh\ncat /etc/debian_version\nuname -a\npython --version\n```\n\nを実行すれば debian, linux, python のバージョンを確認することできる\n\nせっかくなので python3.7.4 からサポートされた `dataclasses` を使ってみましょう\n\nエディターはcontainer上から好きなものをインストールして使ってください\n\n```sh\n# docker\n# vimをインストールする例\napt update\napt install -y vim iproute2\n```\n\n```py\nimport dataclasses\n\[email protected]\nclass Point:\n x: float\n y: float\n z: float = 0.0\n\np = Point(1.5, 2.5)\n\nprint(f'Set your Point is {p}')\n```\n\n動作することを確認したら一旦コンテナから抜け出して見ましょう\n\n`ctl-p, clt-q`を順番に押せば抜け出すことができます。 - attachで復帰\n\n※ `exit`でも終了することができますが復帰するときのコマンドが異なります。 - docker start で復帰\n\n## docker image と docker container ってなに\n\n### docker imageは設計図(Registryは設計図置き場)\n\n### docker containerは実際にできたもの\n\n![dockerimg](https://docs.docker.com/engine/images/architecture.svg)\n\n関係値でいうと\n\n- class = image\n- instance = container\n\nのように考えるとわかりやすい\n\nなので、containerには状態があって、imageには状態がない\n\ncontainerからimage, imageからcontainerを作成することができる\n\nimageを確認するコマンド (host pcで実行)\n\n```sh\ndocker images\ndocker image ls\n\n# imageの中身実際にimageは積層された単なるファイルの塊なのですが詳しくは次回以降にやります\ndocker image history <imagename>\n```\n\ncontainerを確認するコマンド\n\n```sh\ndocker ps\n# exit した container も確認する\ndocker ps -a\n```\n\n---\n\n## コンテナの状態\n\n[dockerコマンド一覧](https://docs.docker.com/engine/reference/commandline/docker/)\n\n![dockersts](https://miro.medium.com/max/2258/1vca4e-SjpzSL5H401p4LCg.png)\n\n結構わかりにくい\n\n覚えておきたいポイント、runningとstop状態がある\n\nまずは対になるコマンドのみ覚えよう\n\n- docker run - docker stop : running -> stop\n- docker stop - docker rm : stop -> deleted\n- docker run (c-p,c-qで抜けた) - docker attach: running -> running\n- docker stop - docker start : stop -> running\n- docker run - docker exec : runnig さらに別のプロセスをcontainer上で実行\n\n~~注意点はdeletedするためにはstop状態にする必要がある~~\n`docker rm -f` で強制的に削除できました。\n\n### localのDocker環境と確認・整理する\n\n#### container\n\n- コンテナのリストを表示 `docker container ls -a` or `docker ps -a`\n- stop状態のcontainerを一斉削除 `docker container prune`\n- すべての動作中のcontainerをstop状態にする `docker stop $(docker ps -q)`\n\n`q`オプションを付けることで、containerのidのみ表示することができる = 他のコマンドと連携しやすい\n\n#### image\n\n- imageのリスト表示 `docker image ls` or `docker images`\n- imageの詳細表示 `docker image history <containerid>`\n- 使われていないかつtagがついていないimageの削除 `docker image prune`\n- すべてのイメージを強制的に削除 `docker rmi -f $(docker images -q)`\n\nコンテナに状態を残す必要はないとおもっていますので必要がなくなれば消してしまってよいと思います\n\n- データの永続化、設計書のカスタマイズ(Dockerfile)の作成は次回以降にやります\n\n---\n\n## Jupiterの環境を整える\n\n```sh\ndocker ps\ndocker attach <container id>\n```\n\nでdockercontainerの中に入れます\n\n```sh\n\npip install jupyter\njupyter-notebook --generate-config\n# Writing default config to: /root/.jupyter/jupyter_notebook_config.py\ncd\n# /roo\nvim .jupyter/jupyter_notebook_config.py\n# # c.NotebookApp.open_browser = True -> c.NotebookApp.open_browser = False\n# # c.NotebookApp.port = 8888 -> c.NotebookApp.port = 8888\n# \"eth0のipaddressに ap address コマンドで調べる\"\n# c.NotebookApp.ip = '0.0.0.0'\njupyter-notebook --allow-root\nss -tnlp # jupyter-notebootが立ち上がっていることを確認\n```\n\nこれで立ち上がるのですが、このままだとhost psからjupyter-notebookにAccessできません\n\nアクセスできるように host psのportをcontainerにバインドするひつようがあります\n\nしかも、docker runにしかportのバインドを指定することができません\n\nなので、ここまでの変更をcontainerからimageを作って再現できるようにします。\n\ndetatch(c-p, c-q)で抜けます\n\n```sh\ndocker diff\n```\n\nで python:3.7.4-busterとの差分確認\n\n```sh\ndocker commit <container id> jupyter-notebook:latest\n```\n\nで新しくイメージを作成します。\n\n```sh\ndocker run -d -p 8888:8888 -w /root jupyter:latest jupyter-notebook --allow-root\n```\n\nでdocker containerを立ち上げて\n\n```sh\ndocker log <container id>\n```\n\nでtokenを調べる\n\n- .\n- .\n- .\n\nじつは上のコマンドにセキュリティー上おおきな問題がありますなにかわかりますか\n\n-p NICを指定してあげないと、:8888 でbindされてしまう同じLANから見えてしまう\n\n```sh\ndocker run -d -p 127.0.0.1:8888:8888 -w /root imagename:tag jupyter-notebook --allow-host\n```\n\nでlocalhostからのみしか見えないように改善できる\n\n- rootで起動している\n- tlsを使ってないので平文で通信している\n\n---\n\n## 宿題\n\njupyter-note ブックで変更した内容を\nhost pc にコピーする\n\nヒント：\n\n```sh\ndocker cp --help\n```\n\nでコピーの使い方を見てみよう\n\ncontainer上にhttpserverを立ち上げて、host pcからアクセスする\n\nヒント：\n\n```sh\npython -m http.server 8080\n```\n\nで http server port 8080 で立ち上げることができる\n\n---\n\n## これから課題\n\n- bash上でやったことをDockerfileに記述したい(冪等性を確保する)\n- rootで起動しているため、jupyter専用のユーザーを作成してjyupyterサーバーを立ち上げたい\n- notobookの内容を別のcontainerとも共有したい\n- hostpc <-> container間でファイルのやり取りをしたい\n - `docker run --mount`, `docker cp src dst`\n- docker compose\n\n![compose](https://knowledge.sakura.ad.jp/images/2019/04/docker-compose-01-04-fix-680x445.png)\n- 開発環境用のpip moduleとサービス用のpip モジュールを分けたい\n\n## TODO\n\n- 実験環境を記載する\n- cis dockerを確認する\n\n## おまけ\n\n- [Best practices for Dockerfiles](https://docs.docker.com/develop/develop-images/dockerfile_best-practices/) これは絶対に読みましょう　日本語版は古いです\n- mac はこれで docker daemon が動作しているttyにアタッチできる\n`screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty`\n" }, { "alpha_fraction": 0.5935483574867249, "alphanum_fraction": 0.6322580575942993, "avg_line_length": 13.090909004211426, "blob_id": "e2fb0419ff72ca65350522cb7419a6f89fc87eb5", "content_id": "dc6d9d1fa5de23e82c82b0b534b2c59dd9fad9d7", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 155, "license_type": "no_license", "max_line_length": 31, "num_lines": 11, "path": "/main.py", "repo_name": "tukkyr/docker-st", "src_encoding": "UTF-8", "text": "import dataclasses\n\[email protected]\nclass Point:\n x: float\n y: float\n z: float = 0.0\n\np = Point(1.5, 2.5)\n\nprint(f'Set your Point is {p}')\n" }, { "alpha_fraction": 0.6235954761505127, "alphanum_fraction": 0.6380417346954346, "avg_line_length": 34.599998474121094, "blob_id": "ad7cd6164ab82e9253ee8231cbd39d3e4f99bfc3", "content_id": "1fac77782453fa4a249dad35be88184537a3690a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Dockerfile", "length_bytes": 1246, "license_type": "no_license", "max_line_length": 146, "num_lines": 35, "path": "/Dockerfile", "repo_name": "tukkyr/docker-st", "src_encoding": "UTF-8", "text": "FROM alpine:3 AS base-stage \n\nRUN apk add --no-cache bash tzdata curl wget vim git \\\n && cp /usr/share/zoneinfo/Asia/Tokyo /etc/localtime \\\n && wget https://raw.githubusercontent.com/git/git/master/contrib/completion/git-prompt.sh -O ${HOME}/.git-prompt.sh \\\n && mkdir -p ${HOME}/.vim/autoload && wget https://raw.githubusercontent.com/junegunn/vim-plug/master/plug.vim -O ${HOME}/.vim/autoload/plug.vim \\\n && echo . ${HOME}/.git-prompt.sh >> ${HOME}/.bashrc \\\n && echo \"PS1='\\[\\e[36m\\]\\h\\[\\e[m\\] \\[\\e[32m\\]\\W\\[\\e[m\\] <\\t> \\$(__git_ps1 \\\"( %s ) \\\")\\n\\$'\" >> ${HOME}/.bashrc \\\n && apk del tzdata\n\nRUN [ -z ${http_proxy} ] \|\| echo export http_proxy=${http_proxy} >> ${HOME}/.bashrc\n\nRUN echo -e \"set nocompatible\\n\\\nfiletype off\\n\\n\\\ncall plug#begin('~/.vim/plugged')\\n\\n\\\nPlug 'VundleVim/Vundle.vim'\\n\\n\\\ncall plug#end()\\n\\\nfiletype plugin indent on\\n\\\nsyntax enable \\n\\n\\\nset st=4 ts=4 sw=4\" \| tee ${HOME}/.vimrc\n\nCMD [\"sh\", \"-c\", \"while sleep 3600; do :; done\"]\n\nFROM base-stage AS python3-dev\n\nWORKDIR /app\n\nRUN apk add --no-cache python3 \\\n && python3 -m venv .venv \\\n && . .venv/bin/activate \\\n && pip install -U pip setuptools \\\n && pip install python-language-server flake8 \\\n && echo . .venv/bin/activate >> ${HOME}/.bashrc\n\nCMD [\"bash\"]\n" } ]	6
kitzmanlab/pou1f1_splicing	https://github.com/kitzmanlab/pou1f1_splicing	da586ddf58d7d9d8c792d0b6a49f22c1a6a93580	fb65040bbb1b64724b2a912c1513ea0b3f89e291	5380706320319436cd4a9eb2f0579e9592f37d5d	refs/heads/master	2023-05-03T06:21:34.292593	2021-05-14T17:24:54	2021-05-14T17:24:54	367,402,258	0	0	null	null	null	null	null	[ { "alpha_fraction": 0.4749336838722229, "alphanum_fraction": 0.4832783639431, "avg_line_length": 32.90131759643555, "blob_id": "69b1cdaaf4a8c47e812013f67a8f7ff29ac303f7", "content_id": "b0f5943e14889283c70ca2e859ded1f5bd2b5788", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 15459, "license_type": "no_license", "max_line_length": 132, "num_lines": 456, "path": "/splfxseq/splanl/gmap_align.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import pandas as pd\nimport numpy as np\nimport pysam\nimport subprocess as subp\nfrom os import path\nimport itertools\n\ndef trim_Tn5_adaptors( infq1,\n infq2,\n outdir = None,\n outfiles = None,\n print_out = True,\n print_err = False ):\n\n #if outdirectory is unspecified, save in same directory as input\n if not outdir:\n outdir = ''.join( fq1.split( '/' )[ : -1 ] )\n\n #sets outfile names\n if not outfiles:\n #if not provided same as input file with the indication it was trimmed\n outfq1 = '.'.join( infq1.split( '/' )[ -1 ].split( '.' )[ :-1 ] ) + '.trim.fq.gz'\n outfq2 = '.'.join( infq2.split( '/' )[ -1 ].split( '.' )[ :-1 ] ) + '.trim.fq.gz'\n else:\n outfq1 = outfiles[ 0 ]\n outfq2 = outfiles[ 1 ]\n\n out = subp.run( 'cutadapt \\\n -a CTGTCTCTTATACACATCTCCGAGCCCACGAGAC \\\n -A CTGTCTCTTATACACATCTGACGCTGCCGACGA \\\n --minimum-length 20 \\\n -q 15 \\\n -O 12 \\\n -e 0.1 \\\n -o %s \\\n -p %s \\\n %s %s' % ( outdir+outfq1, outdir+outfq2, infq1, infq2 ),\n stdout = subp.PIPE,\n stderr = subp.PIPE,\n shell = True,\n )\n\n if print_out:\n #the formatting of the output is annoying - trying to make it look nice\n out_nl = out.stdout.decode('utf-8').split( '\\n' )\n print(out_nl, sep='\\n')\n\n if print_err:\n #the formatting of the output is annoying - trying to make it look nice\n err_nl = out.stderr.decode('utf-8').split( '\\n' )\n print(err_nl, sep='\\n')\n\ndef filter_by_snv( satbl ):\n\n sa = satbl.copy()\n\n sa_singlevar = sa.query( 'n_variants_passing == 1' ).copy()\n\n sa_singlevar[ 'ref' ] = [ str( s ).split( ':' )[ 2 ] for s in sa_singlevar.variant_list ]\n sa_singlevar[ 'alt' ] = [ str( s ).split( ':' )[ 3 ] for s in sa_singlevar.variant_list ]\n\n sa_snvs = sa_singlevar.loc[ (sa_singlevar.ref.str.len() == 1) & (sa_singlevar.alt.str.len() == 1) ].copy()\n\n return sa_snvs\n\ndef unzip( infile,\n outfile = 'temp',\n directory = None ):\n\n file_ext = infile.split( '.' )[ -2 ]\n\n subp.run( 'zcat %s > %s' % ( infile, directory + outfile + '.' + file_ext ),\n shell = True,\n )\n\ndef extract_snv_bcs( satbl ):\n\n sa = satbl.reset_index().copy()\n\n var = sa.variant_list.tolist()\n bc = sa.readgroupid.tolist()\n\n var_to_bc_d = {}\n for v, b in zip(var, bc):\n if v in var_to_bc_d:\n var_to_bc_d[v].append(b)\n else:\n var_to_bc_d[v] = [ b ]\n\n return var_to_bc_d\n\ndef create_varseq( refseq,\n variant ):\n\n pos = int( variant.split( ':' )[ 1 ] )\n ref = str( variant.split( ':' )[ 2 ] )\n alt = str( variant.split( ':' )[ 3 ] )\n\n assert refseq[ pos - 1 ] == ref, 'Reference sequence does not match variant reference allele'\n\n return refseq[ : ( pos -1 ) ] + alt + refseq[ pos : ]\n\ndef write_temp_fa( refseq,\n variant,\n tempdir ):\n\n with open( tempdir + 'temp.fa', 'w' ) as fa:\n fa.write( '>' + variant + '\\n' )\n\n if variant == 'WT':\n fa.write( refseq )\n else:\n fa.write( create_varseq( refseq,\n variant ) )\n\ndef build_index( tempdir,\n variant,\n reffile = 'temp.fa',\n print_out = True,\n print_err = False ):\n\n out = subp.run( '/home/smithcat/bin/gmap_build -d %s -D %s -k 8 -w 0 %s' % ( variant, tempdir + 'indices/', tempdir + reffile ),\n stdout = subp.PIPE,\n stderr = subp.PIPE,\n shell = True,\n )\n\n if print_out:\n #the formatting of the output is annoying - trying to make it look nice\n out_nl = out.stdout.decode('utf-8').split( '\\n' )\n print(out_nl, sep='\\n')\n\n if print_err:\n #the formatting of the output is annoying - trying to make it look nice\n err_nl = out.stderr.decode('utf-8').split( '\\n' )\n print(err_nl, sep='\\n')\n\ndef convert_fq_to_bam( fq_file1,\n fq_file2,\n sample_name,\n tempdir,\n append_bc = True ):\n\n if append_bc:\n\n #convert forward fq to unaligned bam\n subp.run( 'java -Xmx8g -jar /nfs/kitzman2/lab_software/platform_indep/picard-tools-2.9.0/picard.jar \\\n FastqToSam F1=%s SM=%s O=%s' % ( fq_file1, sample_name, tempdir + 'temp.bam' ),\n shell = True,\n stdout = subp.PIPE,\n stderr = subp.PIPE )\n\n append_bcs( tempdir, fq_file2 )\n\n subp.run( 'samtools sort -@8 -m8G -o %s -t RX %s' % ( tempdir + sample_name + '_unaligned.bam', tempdir + 'temp_bc.bam' ),\n shell = True,\n stdout = subp.PIPE,\n stderr = subp.PIPE )\n\n else:\n\n #convert forward fq to unaligned bam\n subp.run( 'java -Xmx8g -jar /nfs/kitzman2/lab_software/platform_indep/picard-tools-2.9.0/picard.jar \\\n FastqToSam F1=%s SM=%s O=%s' % ( fq_file1, sample_name, tempdir + sample_name + '_unaligned1.bam' ),\n shell = True,\n stdout = subp.PIPE,\n stderr = subp.PIPE )\n\n subp.run( 'java -Xmx8g -jar /nfs/kitzman2/lab_software/platform_indep/picard-tools-2.9.0/picard.jar \\\n FastqToSam F1=%s SM=%s O=%s' % ( fq_file2, sample_name, tempdir + sample_name + '_unaligned2.bam' ),\n shell = True,\n stdout = subp.PIPE,\n stderr = subp.PIPE )\n\n\ndef write_temp_fq( pysam_align_in,\n reads,\n tempdir,\n print_err = False ):\n\n with pysam.AlignmentFile( tempdir + 'temp.bam', 'wb', template = pysam_align_in ) as bam_out:\n\n for read in reads:\n bam_out.write( read )\n\n out = subp.run( 'samtools fastq --threads 8 %s > %s'\n % ( tempdir + 'temp.bam', tempdir + 'temp.fq' ) ,\n shell = True,\n stderr = subp.PIPE\n )\n\n if print_err:\n #the formatting of the output is annoying - trying to make it look nice\n err_nl = out.stderr.decode('utf-8').split( '\\n' )\n print(err_nl, sep='\\n')\n\ndef align_reads( tempdir,\n variant,\n fqfile = 'temp.fq',\n print_err = False,\n outbam = 'temp.bam'\n ):\n\n\n out = subp.run( '/home/smithcat/bin/gmap -d %s -D %s -t 8 -f samse --microexon-spliceprob=1.0 --allow-close-indels=2 %s > %s'\n % ( variant, tempdir + 'indices/', fqfile, tempdir + 'temp.sam' ) ,\n stderr = subp.PIPE,\n shell = True,\n )\n\n subp.run( 'samtools view -S -b %s > %s'\n % ( tempdir + 'temp.sam', tempdir + outbam ) ,\n stderr = subp.PIPE,\n shell = True,\n )\n\n if print_err:\n #the formatting of the output is annoying - trying to make it look nice\n err_nl = out.stderr.decode('utf-8').split( '\\n' )\n print(err_nl, sep='\\n')\n\ndef append_bcs( tempdir,\n fq_file2,\n bam_in = 'temp.bam',\n bcbam_out = 'temp_bc.bam' ):\n\n #add BCs from reverse fq to unaligned bam\n out = subp.run( 'java -Xmx8g -jar /nfs/kitzman2/lab_software/platform_indep/fgbio-0.8.1/fgbio-0.8.1.jar \\\n AnnotateBamWithUmis --fail-fast=true --input=%s --fastq=%s --output=%s'\n % ( tempdir + bam_in, fq_file2, tempdir + bcbam_out ),\n shell = True,\n stdout = subp.PIPE,\n stderr = subp.PIPE )\n\ndef coordsort_bam( tempdir,\n bamfile = 'temp.bam',\n print_err = False ):\n\n out = subp.run( 'samtools sort %s > %s ' % ( tempdir + 'temp.sam', tempdir + bamfile ),\n stderr = subp.PIPE,\n shell = True,\n )\n\n if print_err:\n #the formatting of the output is annoying - trying to make it look nice\n err_nl = out.stderr.decode('utf-8').split( '\\n' )\n print(err_nl, sep='\\n')\n\ndef align_pe_reads( tempdir,\n variant,\n fqfile1 = 'for.temp.fq',\n fqfile2 = 'rev.temp.fq',\n print_err = False,\n outbam = 'temp.bam'\n ):\n\n\n out = subp.run( '/home/smithcat/bin/gsnap -d %s -D %s -N 1 -t 8 --format sam %s %s > %s'\n % ( variant, tempdir + 'indices/', fqfile1, fqfile2, tempdir + 'temp.sam' ) ,\n stderr = subp.PIPE,\n shell = True,\n )\n\n subp.run( 'samtools view -S -b %s > %s'\n % ( tempdir + 'temp.sam', tempdir + outbam ) ,\n stderr = subp.PIPE,\n shell = True,\n )\n\n if print_err:\n #the formatting of the output is annoying - trying to make it look nice\n err_nl = out.stderr.decode('utf-8').split( '\\n' )\n print(err_nl, sep='\\n')\n\ndef align_sample( satbl,\n refseq,\n tempdir,\n fq_file1,\n fq_file2,\n chrom_name,\n sample_name = 'sample',\n create_indices = False,\n print_err = False\n ):\n\n sa_snvs = filter_by_snv( satbl )\n\n var_to_bc_d = extract_snv_bcs( sa_snvs )\n\n #don't need to recreate indices for every sample\n if create_indices:\n\n #create folder to store indices\n subp.run( 'mkdir %s' % ( tempdir + 'indices/' ),\n shell = True,\n )\n\n #for each variant create a temporary fa file\n #then create an index within indices directory named by the variant\n for var in var_to_bc_d.keys():\n\n write_temp_fa( refseq, var, tempdir )\n build_index( tempdir, var )\n\n convert_fq_to_bam( fq_file1, fq_file2, sample_name, tempdir )\n\n #import with check_sq as False since this bam is unaligned\n sample_bam = pysam.AlignmentFile( tempdir + sample_name + '_unaligned.bam', 'rb', check_sq = False )\n\n #fake header junk\n header = { 'HD': {'VN': '1.5'},\n 'SQ': [{'LN': 6490, 'SN': chrom_name}] }\n\n with pysam.AlignmentFile( tempdir + sample_name + '.bam', 'wb', header = header ) as bam_out:\n\n for bc, _reads in itertools.groupby( sample_bam, lambda _r: _r.get_tag( 'RX' ) ):\n\n if bc not in sa_snvs.index:\n #print( 'Barcode:', bc, 'not in the subassembly table')\n continue\n\n var = satbl.loc[ bc ].variant_list\n\n #possible that _reads will work.... dunno\n reads = list(_reads)\n\n write_temp_fq( sample_bam, reads, tempdir, print_err )\n\n align_reads( tempdir, var, tempdir + 'temp.fq' )\n\n with pysam.AlignmentFile( tempdir + 'temp.bam', 'rb' ) as bc_bam:\n\n for read in bc_bam:\n bam_out.write( read )\n\n append_bcs( tempdir, fq_file2, bam_in = sample_name + '.bam', bcbam_out = sample_name + '_bc.bam' )\n\n sample_bam.close()\n\ndef filter_secondary_alignments( tempdir,\n infile ):\n\n outfile = '.'.join( infile.split( '.' )[ :-1 ] )\n\n with pysam.AlignmentFile( tempdir + infile, 'rb' ) as unfiltered_bam:\n\n with pysam.AlignmentFile( tempdir + outfile + '_filt.bam', 'wb', template = unfiltered_bam ) as filt_bam:\n\n for read in unfiltered_bam:\n\n if not( read.has_tag( 'HI' ) ) or read.get_tag( 'HI' ) == 1:\n filt_bam.write( read )\n\n\ndef align_indiv_sample( variant,\n refseq,\n tempdir,\n fq_file1,\n chrom_name,\n fq_file2 = None,\n sample_name = 'sample',\n create_indices = False,\n print_err = False\n ):\n\n #don't need to recreate indices for every sample\n if create_indices:\n\n #create folder to store indices\n subp.run( 'mkdir %s' % ( tempdir + 'indices/' ),\n shell = True,\n )\n\n #for the variant create a temporary fa file\n #then create an index within indices directory named by the variant\n write_temp_fa( refseq, variant, tempdir )\n build_index( tempdir, variant, print_err = print_err )\n\n if not fq_file2:\n\n align_reads( tempdir,\n variant,\n fq_file1,\n outbam = sample_name + '.bam',\n print_err = print_err )\n\n else:\n\n align_pe_reads( tempdir,\n variant,\n fq_file1,\n fq_file2,\n outbam = sample_name + '.bam',\n print_err = print_err )\n\ndef align_WT_sample( wt_bcs,\n refseq,\n tempdir,\n fq_file1,\n fq_file2,\n chrom_name,\n sample_name = 'sample',\n create_indices = False,\n print_err = False\n ):\n\n var_to_bc_d = { 'WT': wt_bcs }\n\n #don't need to recreate indices for every sample\n if create_indices:\n\n #create folder to store indices\n subp.run( 'mkdir %s' % ( tempdir + 'indices/' ),\n shell = True,\n )\n\n #for each variant create a temporary fa file\n #then create an index within indices directory named by the variant\n for var in var_to_bc_d.keys():\n\n write_temp_fa( refseq, var, tempdir )\n build_index( tempdir, var )\n\n convert_fq_to_bam( fq_file1, fq_file2, sample_name , tempdir )\n\n #import with check_sq as False since this bam is unaligned\n sample_bam = pysam.AlignmentFile( tempdir + sample_name + '_unaligned.bam', 'rb', check_sq = False )\n\n #fake header junk\n header = { 'HD': {'VN': '1.5'},\n 'SQ': [{'LN': 6490, 'SN': chrom_name}] }\n\n with pysam.AlignmentFile( tempdir + sample_name + '_wt.bam', 'wb', header = header ) as bam_out:\n\n for bc, _reads in itertools.groupby( sample_bam, lambda _r: _r.get_tag( 'RX' ) ):\n\n if bc not in wt_bcs:\n #print( 'Barcode:', bc, 'not in the subassembly table')\n continue\n\n var = 'WT'\n\n reads = list(_reads)\n\n write_temp_fq( sample_bam, reads, tempdir, print_err )\n\n align_reads( tempdir, var, tempdir + 'temp.fq' )\n\n with pysam.AlignmentFile( tempdir + 'temp.bam', 'rb' ) as bc_bam:\n\n for read in bc_bam:\n bam_out.write( read )\n\n append_bcs( tempdir, fq_file2, bam_in = sample_name + '_wt.bam', bcbam_out = sample_name + '_bc_wt.bam' )\n\n sample_bam.close()\n" }, { "alpha_fraction": 0.6161776185035706, "alphanum_fraction": 0.6161776185035706, "avg_line_length": 24.200000762939453, "blob_id": "466f14f41c4730695a9b32032ae93c352db8ebcd", "content_id": "3b1e80e66eb952c80c845a6ca3e76e6e0284c379", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 1261, "license_type": "no_license", "max_line_length": 118, "num_lines": 50, "path": "/splfxseq/spliceprocess/index_tagsorted_bam.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import sys\n\nimport os\nimport os.path\nimport argparse\nfrom collections import defaultdict, OrderedDict\n\nimport numpy as np\n\nimport pandas as pd\n\nimport pysam\nimport itertools \n\ndef main():\n opts = argparse.ArgumentParser()\n\n opts.add_argument('--in_bam', dest='in_bam',\n help='path to bam file containing insert-matching reads, tagged with clone ID', required=True)\n\n opts.add_argument('--clone_id_tag', default='BC', dest='clone_id_tag' )\n\n opts.add_argument('--out_bcindex', dest='out_bcindex',\n help='path to output per-bam barcode index; should include placeholder {i} which will be replaced by chunk #',\n required=True )\n \n o = opts.parse_args()\n \n bam = pysam.AlignmentFile( o.in_bam, 'rb' )\n\n bcindex_cur = OrderedDict( [(k,[]) for k in \n ['barcode','start_ofs'] ] )\n\n lastofs=bam.tell()\n lasttag=None\n\n for l in bam:\n curtag = dict(l.tags)[ o.clone_id_tag ]\n if curtag != lasttag:\n bcindex_cur['barcode'].append(curtag)\n bcindex_cur['start_ofs'].append(lastofs)\n lasttag = curtag\n\n lastofs=bam.tell()\n\n pd.DataFrame(bcindex_cur).to_csv( o.out_bcindex, sep='\\t', index=False )\n\n\nif __name__ == '__main__': \n main()\n\n" }, { "alpha_fraction": 0.49753814935684204, "alphanum_fraction": 0.5056098103523254, "avg_line_length": 34.54949951171875, "blob_id": "38b12b5bfd4f67d1ac7dc0c9af431565be7cbf33", "content_id": "751a4d20f4aa355c6ee24b174293bb5c5ab6e577", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 24778, "license_type": "no_license", "max_line_length": 148, "num_lines": 697, "path": "/splfxseq/splanl/post_processing.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import pandas as pd\nimport numpy as np\nimport scipy.stats as ss\nimport pysam\n\ndef get_refseq( fa_file ):\n\n refseq = []\n\n with pysam.FastxFile(fa_file) as fa:\n for entry in fa:\n refseq.append( entry.sequence )\n\n return refseq\n\ndef get_kmers(seq,\n k):\n\n return( [ seq[ i : i+k ] for i in range( len( seq ) - k + 1 ) ] )\n\ndef acceptors_donors(refseq,\n byvartbl,\n sdv_col,\n out_col_suffix = '' ):\n\n tbv = byvartbl.copy()\n\n assert sdv_col in tbv, '%s is not in the dataframe columns' % sdv_col\n\n min_pos = tbv.pos.min()\n max_pos = tbv.pos.max()\n\n #accounts for 1 based numbering\n vec_seq = refseq.upper()[ min_pos-1: max_pos ]\n\n di_nts = get_kmers(vec_seq, 2 )\n\n for col in ['wt_acc','wt_don','psbl_snv_acc','psbl_snv_don']:\n tbv[ col ] = False\n\n for p, dnt in enumerate( di_nts ):\n\n #first check for cryptic exon locations\n if dnt == 'AG':\n tbv.loc[ ( tbv.pos == ( p + min_pos ) ) \| ( tbv.pos == ( p + min_pos + 1 ) ), 'wt_acc' ] = True\n elif dnt == 'GT':\n tbv.loc[ ( tbv.pos == ( p + min_pos ) ) \| ( tbv.pos == ( p + min_pos + 1 ) ), 'wt_don' ] = True\n #ok now look for possible acceptors and donors\n elif dnt.startswith( 'A' ):\n tbv.loc[ ( tbv.pos == ( p + min_pos + 1 ) ) & ( tbv.alt == 'G' ), 'psbl_snv_acc' ] = True\n elif dnt.endswith( 'G' ):\n tbv.loc[ ( tbv.pos == ( p + min_pos ) ) & ( tbv.alt == 'A' ), 'psbl_snv_acc' ] = True\n elif dnt.startswith( 'G' ):\n tbv.loc[ ( tbv.pos == ( p + min_pos + 1 ) ) & ( tbv.alt == 'T' ), 'psbl_snv_don' ] = True\n elif dnt.endswith( 'T' ):\n tbv.loc[ ( tbv.pos == ( p + min_pos ) ) & ( tbv.alt == 'G' ), 'psbl_snv_don' ] = True\n\n tbv[ 'snv_acc' + out_col_suffix ] = ( tbv[ sdv_col ] ) & ( tbv.psbl_snv_acc )\n tbv[ 'snv_don' + out_col_suffix ] = ( tbv[ sdv_col ] ) & ( tbv.psbl_snv_don )\n\n return tbv\n\ndef sdvs(byvartbl,\n sdv_col,\n sdv_thresh,\n abs_vals = True):\n\n tbv = byvartbl.copy()\n\n if abs_vals:\n tbv['sdv'] = np.abs( tbv[ sdv_col ] ) >= sdv_thresh\n else:\n tbv['sdv'] = tbv[ sdv_col ] >= sdv_thresh\n\n return tbv\n\ndef print_summary_info( byvartbl ):\n\n tbv = byvartbl.loc[ byvartbl.n_bc_passfilt > 0 ].copy()\n\n pos_var = 3( tbv.pos.max() - tbv.pos.min() )\n seen_var = tbv.shape[0]\n seen_per = 100( seen_var / pos_var )\n\n print( 'Out of %i possible variants, we see %i (%.2f%%).' % ( pos_var, seen_var, seen_per ) )\n\n sdvs = tbv.sdv.sum()\n sdv_per = 100( sdvs / seen_var )\n\n print( 'Out of %i variants, %i (%.2f%%) are splice disrupting.' % ( seen_var, sdvs, sdv_per ) )\n\n if 'var_type' in tbv.columns:\n\n syn_tbv = tbv.query( 'var_type == \"Synonymous\"' ).copy()\n syn = syn_tbv.shape[0]\n syn_sdvs = syn_tbv.sdv.sum()\n syn_sdv_per = 100( syn_sdvs / syn )\n\n print( 'Out of %i synononymous variants, %i (%.2f%%) are splice disrupting.' % ( syn, syn_sdvs, syn_sdv_per ) )\n\n if 'sdv_exon' in tbv.columns:\n\n ex_tbv = tbv.query( 'var_type != \"Intronic\"' ).copy()\n ex = ex_tbv.shape[0]\n ex_sdvs = ex_tbv.sdv_exon.sum()\n ex_sdv_per = 100( ex_sdvs / ex )\n\n print( 'Out of %i exonic variants, %i (%.2f%%) are splice disrupting.' % ( ex, ex_sdvs, ex_sdv_per ) )\n\n if 'sdv_intron' in tbv.columns:\n\n intron_tbv = tbv.query( 'var_type == \"Intronic\"' ).copy()\n intron = intron_tbv.shape[0]\n intron_sdvs = intron_tbv.sdv_intron.sum()\n intron_sdv_per = 100( intron_sdvs / intron )\n\n print( 'Out of %i intronic variants, %i (%.2f%%) are splice disrupting.' % ( intron, intron_sdvs, intron_sdv_per ) )\n\n pos_acc = tbv.psbl_snv_acc.sum()\n used_acc = tbv.snv_acc.sum()\n acc_per = 100( used_acc / pos_acc )\n\n print( 'Out of %i possible alternate acceptors, %i (%.2f%%) have a high OTHER value.' % ( pos_acc, used_acc, acc_per ) )\n\n pos_don = tbv.psbl_snv_don.sum()\n used_don = tbv.snv_don.sum()\n don_per = 100( used_don / pos_don )\n\n print( 'Out of %i possible alternate donors, %i (%.2f%%) have a high OTHER value.\\n' % ( pos_don, used_don, don_per ) )\n\ndef stdize_cols_by_sample( tbv,\n std_cols ):\n\n out_tbl = tbv.copy()\n\n #if this is a long dataset\n if 'sample' in out_tbl.columns:\n\n for col in std_cols:\n #creates z score by sample while ignoring any missing values\n out_tbl[ 'z' + col ] = out_tbl.groupby( [ 'sample' ] )[ col ].transform( lambda x : ss.zscore( x, nan_policy='omit' ) )\n\n #if the data contains only one sample\n else:\n\n for col in std_cols:\n out_tbl[ 'z' + col ] = ss.zscore( out_tbl[ col ], nan_policy='omit' )\n\n return( out_tbl )\n\ndef across_sample_stats(ltbls,\n lsampnames,\n med_col_names):\n\n out_tbl = { 'sample_group':[],\n 'sample':[],\n 'psbl_var':[],\n 'n_var':[],\n 'n_var_ex':[],\n 'n_var_in':[],\n 'n_reads':[],\n 'n_reads_passfilt':[],\n 'n_usable_reads':[],\n 'n_bc':[],\n 'n_bc_passfilt':[],\n 'n_unmapped':[],\n 'n_badstart':[],\n 'n_badend':[],\n 'n_softclip':[],\n 'n_otheriso':[],\n 'n_sdv':[],\n 'n_sdv_ex':[],\n 'n_sdv_in':[],\n 'psbl_alt_acc':[],\n 'psbl_alt_don':[],\n 'n_alt_acc':[],\n 'n_alt_don':[]\n }\n\n for col in med_col_names:\n out_tbl['med_'+col] = []\n\n i=0\n for grp, _lsamp in lsampnames.items():\n for lsamp in _lsamp:\n\n lsamp_df = ltbls[ i ].query( 'sample==\"%s\"' % lsamp ).copy()\n lsamp_filt_df = lsamp_df.query( 'n_bc_passfilt > 0' )\n\n out_tbl['sample_group'].append( grp )\n out_tbl['sample'].append( grp+'_'+lsamp )\n out_tbl['psbl_var'].append( 3( lsamp_df.pos.max() - lsamp_df.pos.min() ) )\n out_tbl['n_var'].append( int( lsamp_filt_df.shape[0] ) )\n out_tbl['n_reads'].append( int( lsamp_df.sum_reads.sum() ) )\n out_tbl['n_reads_passfilt'].append( int( lsamp_df.sum_reads_passfilt.sum() ) )\n out_tbl['n_usable_reads'].append( int( lsamp_df.sum_usable_reads.sum() ) )\n out_tbl['n_bc'].append( int( lsamp_df.n_bc.sum() ) )\n out_tbl['n_bc_passfilt'].append( int( lsamp_df.n_bc_passfilt.sum() ) )\n out_tbl['n_unmapped'].append( int( lsamp_df.sum_unmapped_reads.sum() ) )\n out_tbl['n_badstart'].append( int( lsamp_df.sum_badstart_reads.sum() ) )\n out_tbl['n_badend'].append( int( lsamp_df.sum_badend_reads.sum() ) )\n out_tbl['n_softclip'].append( int( lsamp_df.sum_softclipped_reads.sum() ) )\n out_tbl['n_otheriso'].append( int( lsamp_df.sum_otheriso.sum() ) )\n out_tbl['n_sdv'].append( int( lsamp_filt_df.sdv.sum() ) )\n out_tbl['psbl_alt_acc'].append( int( lsamp_filt_df.psbl_snv_acc.sum() ) )\n out_tbl['psbl_alt_don'].append( int( lsamp_filt_df.psbl_snv_don.sum() ) )\n out_tbl['n_alt_acc'].append( int( lsamp_filt_df.snv_acc.sum() ) )\n out_tbl['n_alt_don'].append( int( lsamp_filt_df.snv_don.sum() ) )\n for col in med_col_names:\n out_tbl['med_'+col].append( float( lsamp_df[ col ].median() ) )\n\n if 'var_type' in lsamp_filt_df.columns:\n out_tbl['n_var_ex'].append( int( lsamp_filt_df.query( 'var_type != \"Intronic\"' ).shape[0] ) )\n out_tbl['n_var_in'].append( int( lsamp_filt_df.query( 'var_type == \"Intronic\"' ).shape[0] ) )\n out_tbl['n_sdv_ex'].append( int( lsamp_filt_df.sdv_exon.sum() ) )\n out_tbl['n_sdv_in'].append( int( lsamp_filt_df.sdv_intron.sum() ) )\n else:\n out_tbl['n_var_ex'].append( None )\n out_tbl['n_var_in'].append( None )\n out_tbl['n_sdv_ex'].append( None )\n out_tbl['n_sdv_in'].append( None )\n i+=1\n\n out_tbl = pd.DataFrame( out_tbl )\n\n out_tbl['per_var_seen'] = 100( out_tbl.n_var / out_tbl.psbl_var )\n out_tbl['per_reads_passfilt'] = 100( out_tbl.n_reads_passfilt / out_tbl.n_reads )\n out_tbl['per_bc_passfilt'] = 100( out_tbl.n_bc_passfilt / out_tbl.n_bc )\n out_tbl['per_usable'] = 100( out_tbl.n_usable_reads / out_tbl.n_reads_passfilt )\n out_tbl['per_unmapped'] = 100( out_tbl.n_unmapped / out_tbl.n_reads_passfilt )\n out_tbl['per_badstart'] = 100( out_tbl.n_badstart / out_tbl.n_reads_passfilt )\n out_tbl['per_badend'] = 100( out_tbl.n_badend / out_tbl.n_reads_passfilt )\n out_tbl['per_softclip'] = 100( out_tbl.n_softclip / out_tbl.n_reads_passfilt )\n out_tbl['per_otheriso'] = 100( out_tbl.n_otheriso / out_tbl.n_reads_passfilt )\n out_tbl['per_sdv'] = 100( out_tbl.n_sdv / out_tbl.n_var )\n out_tbl['per_sdv_ex'] = 100( out_tbl.n_sdv_ex / out_tbl.n_var_ex )\n out_tbl['per_sdv_in'] = 100( out_tbl.n_sdv_in / out_tbl.n_var_in )\n out_tbl['per_acc_used'] = 100( out_tbl.n_alt_acc / out_tbl.psbl_alt_acc )\n out_tbl['per_don_used'] = 100( out_tbl.n_alt_don / out_tbl.psbl_alt_don )\n\n return out_tbl\n\n#This is the one letter universal translation table\n#It handles cases of DNA ambiguity where the encoded amino acid is unambiguous.\n#You need to deal with the missing cases where ambiguity codes would result in\n#an ambiguous amino acid assignment. It is suggested that you use 'X' in these\n#cases as this is the standard character for an unknown amino acid.\n#Only Y (pyrimidine), R (purine) and N (any) degeneracy symbols are handled at\n#this time. (need to add M,K,W,S,B,D,H,V where appropriate)\n#Stop codons are symbolized as X\n#Reassign TAA, TAG, TAR and TGA to change the stop codon symbol if desired.\n\ntransTab1L = {\n'TTT': 'F', 'TTC': 'F', 'TTA': 'L', 'TTG': 'L',\n'TCT': 'S', 'TCC': 'S', 'TCA': 'S', 'TCG': 'S',\n'TAT': 'Y', 'TAC': 'Y', 'TAA': 'X', 'TAG': 'X',\n'TGT': 'C', 'TGC': 'C', 'TGA': 'X', 'TGG': 'W',\n'CTT': 'L', 'CTC': 'L', 'CTA': 'L', 'CTG': 'L',\n'CCT': 'P', 'CCC': 'P', 'CCA': 'P', 'CCG': 'P',\n'CAT': 'H', 'CAC': 'H', 'CAA': 'Q', 'CAG': 'Q',\n'CGT': 'R', 'CGC': 'R', 'CGA': 'R', 'CGG': 'R',\n'ATT': 'I', 'ATC': 'I', 'ATA': 'I', 'ATG': 'M',\n'ACT': 'T', 'ACC': 'T', 'ACA': 'T', 'ACG': 'T',\n'AAT': 'N', 'AAC': 'N', 'AAA': 'K', 'AAG': 'K',\n'AGT': 'S', 'AGC': 'S', 'AGA': 'R', 'AGG': 'R',\n'GTT': 'V', 'GTC': 'V', 'GTA': 'V', 'GTG': 'V',\n'GCT': 'A', 'GCC': 'A', 'GCA': 'A', 'GCG': 'A',\n'GAT': 'D', 'GAC': 'D', 'GAA': 'E', 'GAG': 'E',\n'GGT': 'G', 'GGC': 'G', 'GGA': 'G', 'GGG': 'G',\n}\n\ndef get_ref_amino( vartbl,\n refseq,\n exon_coords,\n frame_shift = 0 ):\n\n assert isinstance( frame_shift, int) and frame_shift < 3, 'Frameshift must be a non-negative integer less than 3'\n\n tbv = vartbl.set_index( 'pos' ).copy()\n\n exon_seq = refseq[ exon_coords[0] - 1 + frame_shift : exon_coords[1] ].upper()\n\n daminos = { ( i + exon_coords[0] + frame_shift ) : transTab1L[ exon_seq[ i: i+3 ] ]\n for i in range( 0, len( exon_seq ), 3 )\n if len( exon_seq[ i: i+3 ] ) == 3 }\n\n #fills in the other positions\n for pos in list( daminos.keys() ):\n amino = daminos[pos]\n daminos[ pos + 1 ] = amino\n daminos[ pos + 2 ] = amino\n\n aa_df = pd.DataFrame.from_dict( daminos, orient='index' ).reset_index()\n aa_df = aa_df.rename( columns={'index':'pos', 0:'ref_aa'}).sort_values(by='pos').set_index('pos')\n\n out_tbl = pd.merge( tbv, aa_df, left_index=True, right_index=True, how = 'outer' ).reset_index()\n\n #drop rows that aren't associated with a variant, can't do an inner merge bc we'll lose any intronic variants\n out_tbl = out_tbl.dropna( subset=['varlist'] )\n\n return out_tbl\n\ndef get_snv_alt_amino( vartbl,\n refseq,\n exon_coords,\n frame_shift = 0 ):\n\n assert isinstance( frame_shift, int) and frame_shift < 3, 'Frameshift must be a non-negative integer less than 3'\n\n tbv = vartbl.set_index( [ 'pos', 'alt' ] ).copy()\n\n exon_seq = refseq[ exon_coords[0] - 1 + frame_shift : exon_coords[1] ].upper()\n\n lcodons = [ exon_seq[ i: i+3 ] for i in range( 0, len( exon_seq ), 3 ) ]\n\n nt_sub = ['A', 'C', 'G', 'T']\n\n daminos = {}\n\n #handles the case in which the initial bases go to a codon in the upstream exon\n for i in range( frame_shift ):\n\n #adjust for 1 and 0 based coordinates\n ref = refseq[ exon_coords[0] - 1 + i ].upper()\n\n if ( i + exon_coords[0] ) not in daminos:\n daminos[ i + exon_coords[0] ] = {}\n\n for snv in nt_sub:\n\n if snv == ref:\n continue\n\n daminos[ i + exon_coords[0] ][ snv ] = 'Exonic - out of frame'\n\n for i in range( exon_coords[1] - exon_coords[0] - frame_shift ):\n\n #adjust for 1 and 0 based coordinates\n ref = refseq[ exon_coords[0] - 1 + frame_shift + i ].upper()\n codon = lcodons[ i // 3 ]\n snv_pos = i % 3\n\n if ( i + exon_coords[0] + frame_shift ) not in daminos:\n daminos[ i + exon_coords[0] + frame_shift ] = {}\n\n for snv in nt_sub:\n\n if snv == ref:\n continue\n\n if len( codon ) == 3:\n daminos[ i + exon_coords[0] + frame_shift ][ snv ] = transTab1L[ codon[ :snv_pos ] + snv + codon[ snv_pos + 1: ] ]\n #handles the case in which the final codon goes into the next downstream exon\n else:\n daminos[ i + exon_coords[0] + frame_shift ][ snv ] = 'Exonic - out of frame'\n\n #creates dataframe indexed on position and alt with alternate aminos as the only column\n aa_df = pd.concat( { k: pd.DataFrame.from_dict( v, 'index', columns = [ 'alt_aa' ] ) for k, v in daminos.items() }, axis=0 ).reset_index()\n aa_df = aa_df.rename( columns={ 'level_0':'pos', 'level_1':'alt' } ).set_index( [ 'pos', 'alt' ] )\n\n out_tbl = pd.merge( tbv, aa_df, left_index=True, right_index=True, how = 'outer' ).reset_index()\n\n #drop rows that aren't associated with a variant, can't do an inner merge bc we'll lose any intronic variants\n out_tbl = out_tbl.dropna( subset=['varlist'] )\n\n return out_tbl\n\ndef extract_var_type( vartbl,\n refseq,\n exon_coords,\n frame_shift = 0,\n overwrite = True ):\n\n assert isinstance( frame_shift, int) and frame_shift < 3, 'Frameshift must be a non-negative integer less than 3'\n\n tbv = vartbl.sort_values( by = 'pos' ).copy()\n\n if 'ref_aa' not in tbv.columns or overwrite:\n tbv = get_ref_amino( tbv, refseq, exon_coords, frame_shift )\n\n if 'alt_aa' not in tbv.columns or overwrite:\n tbv = get_snv_alt_amino( tbv, refseq, exon_coords, frame_shift )\n\n var_type = []\n\n for ref, alt in zip( tbv.ref_aa.values, tbv.alt_aa.values ):\n\n #checking if alt is missing but with a work around since np.isnan fails with strings\n if not isinstance( alt, str ):\n var_type.append( 'Intronic' )\n elif alt == 'Exonic - out of frame':\n var_type.append('Exonic - out of frame')\n elif ref == alt:\n var_type.append( 'Synonymous' )\n elif alt == 'X':\n var_type.append( 'Nonsense' )\n else:\n var_type.append( 'Missense' )\n\n tbv['var_type'] = var_type\n\n return tbv\n\ndef sdv_by_var_type( vartbl ):\n\n tbv = vartbl.copy()\n\n #check that variant type is in the data and not all missing\n assert ( 'var_type' in tbv.columns ) and ( tbv.shape[0] != tbv.var_type.isnull().sum() ), \\\n 'var_type must be a non-empty column in the dataframe'\n\n assert ( 'sdv' in tbv.columns ), 'sdv must be a column in the dataframe'\n\n tbv['sdv_exon'] = ( ( tbv.sdv ) & ( tbv.var_type != 'Intronic' ) )\n\n tbv['sdv_intron'] = ( ( tbv.sdv ) & ( tbv.var_type == 'Intronic' ) )\n\n return tbv\n\ndef identify_var( vartbl,\n pat_pos_alt,\n out_col ):\n\n tbv = vartbl.copy()\n\n tbv[ out_col ] = False\n\n for pos, alt in pat_pos_alt:\n\n tbv.loc[ ( tbv.pos == pos ) & ( tbv.alt == alt ), out_col ] = True\n\n return tbv\n\ndef frameshift( tbl_byvar,\n acc_don_bool,\n exon_bd,\n acc = True\n ):\n\n tbv = tbl_byvar.copy()\n\n if acc:\n col = 'frameshift_acc'\n else:\n col = 'frameshift_don'\n\n tbv[ col ] = False\n\n posl = tbv.loc[ tbv[ acc_don_bool ] ].pos\n altl = tbv.loc[ tbv[ acc_don_bool ] ].alt\n\n if acc:\n assert len( set( altl ) ) == 2 and 'C' not in set( altl ) and 'T' not in set( altl ), \\\n 'Alternate alleles for acceptor have bases other than A/G'\n else:\n assert len( set( altl ) ) and 'A' not in set( altl ) and 'C' not in set( altl ), \\\n 'Alternate alleles for donor have bases other than G/T'\n\n fs = []\n\n for p,a in zip( posl, altl ):\n\n if acc:\n\n #for this exon bd should be vec_coord of first exonic base\n if a.upper() == 'A':\n\n fs.append( ( ( ( exon_bd - ( p + 2 ) ) % 3 ) != 0 ) )\n\n elif a.upper() == 'G':\n\n fs.append( ( ( ( exon_bd - ( p + 1 ) ) % 3 ) != 0 ) )\n\n else:\n\n #for this exon bd should be vec_coord of last exonic base\n if a.upper() == 'G':\n\n fs.append( ( ( ( exon_bd - ( p + 1 ) ) % 3 ) != 0 ) )\n\n elif a.upper() == 'T':\n\n fs.append( ( ( ( exon_bd - p ) % 3 ) != 0 ) )\n\n tbv.loc[ tbv[ acc_don_bool ], col ] = fs\n\n return tbv\n\ndef bootstrap_null_distribution( n_bcs,\n wt_bc_df,\n byvar_df,\n seed = 1687,\n iso_names = None ):\n\n wt_psi = wt_bc_df.copy()\n tbv = byvar_df.copy()\n\n assert all( n > 0 for n in n_bcs ), 'Inputting a sample with 0 barcodes will lead to division by 0 errors'\n\n wt_bcs = wt_psi.index.tolist()\n\n if not iso_names:\n\n iso_names = [ col[:-4] for col in wt_psi if col.endswith( '_psi' ) ]\n\n assert len( iso_names ) > 0, 'Could not infer isoform names - please input names to use'\n\n np.random.seed( seed )\n\n wt_dfs = [ wt_psi.loc[ np.random.choice( wt_bcs, int( n ) ) ] for n in n_bcs ]\n\n for iso in iso_names:\n\n wmeans = [ ( wt_df.usable_reads wt_df[ iso + '_psi' ] ).sum() / wt_df.usable_reads.sum()\n for wt_df in wt_dfs ]\n\n tbv[ 'wmean_bs_WT_' + iso ] = np.mean( wmeans )\n tbv[ 'wstdev_bs_WT_' + iso ] = np.std( wmeans )\n\n return tbv\n\ndef compute_intron_null_allvar( tbl_byvar,\n exon_cds,\n intron_bds,\n pos_col = 'pos',\n iso_names = None\n ):\n\n tbv = tbl_byvar.copy()\n\n if not iso_names:\n\n iso_names = [ col[ 6: ] for col in tbv if col.startswith( 'wmean_' ) ]\n\n assert iso_names, 'Isoform names could not be inferred, please enter them directly'\n\n introns = tbv.loc[ ( tbv[ pos_col ] < exon_cds[ 0 ] - intron_bds ) \| ( tbv[ pos_col ] > exon_cds[ 1 ] + intron_bds ) ].copy()\n exons = tbv.loc[ ( tbv[ pos_col ] >= exon_cds[ 0 ] - intron_bds ) \| ( tbv[ pos_col ] <= exon_cds[ 1 ] + intron_bds ) ].copy()\n\n for iso in iso_names:\n\n tbv[ 'wmean_int_' + iso ] = introns[ 'wmean_' + iso ].mean()\n tbv[ 'wstdev_int_' + iso ] = introns[ 'wmean_' + iso ].std()\n\n tbv[ 'sq_inv_eff_' + iso ] = ( ( len( introns ) * len( exons ) ) * ( len( introns ) + len( exons ) - 2 ) ) \\\n / ( ( len( introns ) + len( exons ) ) \\\n * ( ( ( len( introns ) - 1 ) * introns[ 'wmean_' + iso ].std()*2 ) \\\n + ( ( len( exons ) - 1 ) exons[ 'wmean_' + iso ].std()*2 ) ) )\n\n return tbv\n\ndef bootstrap_varsp_null_distribution( null_bc_df,\n byvar_df,\n seed = 1687,\n iso_names = None,\n bootstraps = 1000, ):\n\n null_psi = null_bc_df.copy()\n tbv = byvar_df.copy()\n\n n_bcs = tbv.n_bc_passfilt.tolist()\n\n assert all( n > 0 for n in n_bcs ), 'Inputting a sample with 0 barcodes will lead to division by 0 errors'\n\n null_bcs = null_psi.index.tolist()\n\n if not iso_names:\n\n iso_names = [ col[ : -4 ] for col in null_psi if col.endswith( '_psi' ) ]\n\n assert len( iso_names ) > 0, 'Could not infer isoform names - please input names to use'\n\n usable_reads = null_psi.usable_reads.to_numpy()\n\n sample_tbl = {}\n null_iso = {}\n\n for iso in iso_names:\n\n sample_tbl[ 'wmean_bs_null_' + iso ] = []\n sample_tbl[ 'wstdev_bs_null_' + iso ] = []\n\n null_iso[ iso ] = null_psi[ iso + '_psi' ].to_numpy()\n\n bcs_sampled = {}\n\n for i,n_bc in enumerate( n_bcs ):\n\n if n_bc in bcs_sampled:\n\n idx = bcs_sampled[ n_bc ]\n\n for iso in iso_names:\n\n sample_tbl[ 'wmean_bs_null_' + iso ].append( sample_tbl[ 'wmean_bs_null_' + iso ][ idx ] )\n sample_tbl[ 'wstdev_bs_null_' + iso ].append( sample_tbl[ 'wstdev_bs_null_' + iso ][ idx ] )\n\n continue\n\n bcs_sampled[ n_bc ] = i\n\n np.random.seed( seed )\n\n null_idx = np.random.randint( len( null_psi ), size = ( bootstraps, int( n_bc ) ) )\n\n for iso in iso_names:\n\n mus = ( usable_reads[ null_idx ] null_iso[ iso ][ null_idx ] ).sum( axis = 1 ) / usable_reads[ null_idx ].sum( axis = 1 )\n\n sample_tbl[ 'wmean_bs_null_' + iso ].append( np.mean( mus ) )\n sample_tbl[ 'wstdev_bs_null_' + iso ].append( np.std( mus ) )\n\n samp_df = pd.DataFrame( sample_tbl )\n\n tbv = pd.concat( [ tbv.reset_index(), samp_df.reset_index() ],\n axis = 1, )\n\n print( 'done' )\n\n return tbv\n\ndef compute_null_zscores( tbl_byvar,\n null_stem,\n iso_names ):\n\n tbv = tbl_byvar.copy()\n\n for iso in iso_names:\n\n tbv[ '_'.join( [ 'zwmean', null_stem, iso ] ) ] = ( tbv[ 'wmean_' + iso ] \\\n - tbv[ '_'.join( [ 'wmean', null_stem, iso ] ) ] ) \\\n / tbv[ '_'.join( [ 'wstdev', null_stem, iso ] ) ]\n\n return tbv\n\ndef stouffers_z( tbl_byvar_wide,\n iso_names,\n zcol = 'zmean_',\n weight = False ):\n\n tbv = tbl_byvar_wide.copy()\n\n for iso in iso_names:\n\n if not weight:\n\n tbv[ zcol + iso ] = tbv[ [ col for col in tbv if col.endswith( zcol + iso ) ] ].sum( axis = 1 ) \\\n / np.sqrt( tbv[ [ col for col in tbv if col.endswith( zcol + iso ) ] ].notnull().sum( axis = 1 ) )\n\n else:\n\n tbv[ zcol[ 1: ] + iso ] = ( tbv[ [ col for col in tbv if col.endswith( zcol[ :-2 ] + '_' + iso ) ] ] * weight[ iso ] ).sum( axis = 1 ) \\\n / np.sqrt( ( weight[ iso ]*2 ).sum() )\n\n return tbv\n\ndef sdv_by_iso( tbl_byvar,\n iso_names,\n z_col_stem,\n z_thresh,\n fc_col_stem,\n fc_thresh,\n out_col_stem = 'sdv_',\n abs_val = True ):\n\n tbv = tbl_byvar.copy()\n\n for iso in iso_names:\n\n if abs_val:\n tbv[ out_col_stem + iso ] = ( np.abs( tbv[ z_col_stem + iso ] ) >= z_thresh ) \\\n & ( tbv[ fc_col_stem + iso ] >= fc_thresh )\n else:\n tbv[ out_col_stem + iso ] = ( tbv[ z_col_stem + iso ] >= z_thresh ) \\\n & ( tbv[ fc_col_stem + iso ] >= fc_thresh )\n\n return tbv\n\ndef compute_fold_change( tbl_byvar,\n null_col_stem,\n test_col_stem,\n iso_names = None,\n out_col = 'fc_' ):\n\n tbv = tbl_byvar.copy()\n\n if not iso_names:\n\n iso_names = [ col[ len( null_col_stem ): ] for col in tbv if col.startswith( null_col_stem ) ]\n\n assert len( iso_names ) > 0, 'Cannot infer isoform names - please provide them directly'\n\n for iso in iso_names:\n\n tbv[ out_col + iso ] = tbv[ test_col_stem + iso ] / tbv[ null_col_stem + iso ]\n\n return tbv\n" }, { "alpha_fraction": 0.5446485280990601, "alphanum_fraction": 0.556998074054718, "avg_line_length": 36.595237731933594, "blob_id": "325ebfeaefb7cbe7ea32cb570e803b83ac97ba94", "content_id": "0bf96d178ce0bfdb0cd82d6181e075bb75b11b1a", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 3158, "license_type": "no_license", "max_line_length": 152, "num_lines": 84, "path": "/splfxseq/splanl/coords.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "def pos_to_hgvspos(\n lvecpos,\n vec_corange_cloned,\n vec_corange_exons,\n cdna_corange_exons ):\n\n \"\"\"\n Convert from vector position to HGVS cDNA location\n\n Arguments:\n lvecpos {pandas dataframe column} -- pandas dataframe column with the vector positions\n vec_corange_cloned {tuple of ints} -- range of vector coordinates which contain the cloned insert\n vec_corange_exons {list of tuples of ints} -- range of vector coordinates for each exon\n cdna_corange_exons {list of tuples of ints} -- range of cdna coordinates for each exon\n\n Returns:\n list -- list of cdna coordinates\n \"\"\"\n\n\n assert len(vec_corange_exons)==len(cdna_corange_exons), 'must be same # of exons in both parameters'\n\n for (corng_vec,corng_ex) in zip(vec_corange_exons,cdna_corange_exons):\n assert corng_ex[1]-corng_ex[0]+1 == corng_vec[1]-corng_vec[0]+1 , 'exons must be same lengths'\n assert corng_vec[0] >= vec_corange_cloned[0] and corng_vec[1] <= vec_corange_cloned[1], 'exon must be entirely within cloned region'\n\n loutpos=[]\n\n for vecpos in lvecpos:\n if vecpos < vec_corange_cloned[0] or vecpos > vec_corange_cloned[1]:\n coordstr=None\n else:\n # is there only one exon?\n if len( vec_corange_exons ) == 1:\n # is the location before the exon, after, or inside?\n if vecpos < vec_corange_exons[0][0]:\n coordstr = 'c.{:d}-{:d}'.format(\n cdna_corange_exons[0][0],\n vec_corange_exons[0][0]-vecpos )\n elif vecpos > vec_corange_exons[0][1]:\n coordstr = 'c.{:d}+{:d}'.format(\n cdna_corange_exons[0][1],\n vecpos-vec_corange_exons[0][1] )\n else:\n coordstr = 'c.{:d}'.format( cdna_corange_exons[0][0] + vecpos - vec_corange_exons[0][0] )\n else:\n # not handling multiple exons yet; if in an intron, we'd need to figure out which is nearer, then create the coordinate relative to that\n assert 1==0, 'not implemented yet'\n\n loutpos.append(coordstr)\n\n return loutpos\n\n\ndef pos_to_gDNA(\n vec_pos,\n gdna_exon_end,\n vec_exon_match,\n rev_transcribed=False\n ):\n\n if rev_transcribed:\n out_pos = [ gdna_exon_end + ( vec_exon_match-pos ) for pos in vec_pos ]\n else:\n out_pos = [ gdna_exon_end - ( vec_exon_match-pos ) for pos in vec_pos ]\n return(out_pos)\n\ndef vpos_to_gpos(\n vec_pos,\n vec_crange,\n gdna_crange,\n rev_strand=False\n ):\n\n gdna_crange.sort()\n\n assert ( vec_crange[ 1 ] - vec_crange[ 0 ] ) == ( gdna_crange[ 1 ] - gdna_crange[ 0 ] ), \\\n 'Vector range and genomic DNA range are of different lengths'\n\n if rev_strand:\n out_pos = [ gdna_crange[ 0 ] + ( vec_crange[ 1 ] - pos ) for pos in vec_pos ]\n else:\n out_pos = [ gdna_crange[ 0 ] + ( pos - vec_crange[ 0 ] ) for pos in vec_pos ]\n return(out_pos)\n" }, { "alpha_fraction": 0.5515215396881104, "alphanum_fraction": 0.5604691505432129, "avg_line_length": 39.50226974487305, "blob_id": "13e61517fff0451da86160d3e665752e094e04f5", "content_id": "65867cb60c5cad3a7f54870a394cdd95337dfea1", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 44593, "license_type": "no_license", "max_line_length": 205, "num_lines": 1101, "path": "/splfxseq/splanl/junction_scorer.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import pysam\nimport os\nimport pandas as pd\nimport numpy as np\nimport networkx as nx\nfrom collections import Counter\nimport matplotlib.pyplot as plt\nimport copy\nimport itertools\nimport pybedtools as pbt\nfrom ast import literal_eval\n\ndef adjust_junctions(pysam_align,\n refseq,\n cnst_exons,\n outfile):\n\n for bc, _reads in itertools.groupby( pysam_align, lambda _r: _r.get_tag( 'RX' ) ):\n\n reads = list(_reads)\n\n for read in reads:\n\n iso = read.get_blocks()\n\n #don't check junctions for unmapped reads or if there's only one block\n if read.is_unmapped or len( iso )==1:\n outfile.write( read )\n continue\n\n #if all of the ends of junctions are before (downstream) the end of the downstream constant exon\n #OR all of the starts of junctions are after (upstream) the start of the upstream constant exon\n #the read is garbage anyway so just skip it\n if all( jn[1] < cnst_exons[0][1] for jn in iso ) or all( jn[0] > cnst_exons[1][0] for jn in iso ):\n outfile.write( read )\n continue\n\n #check if the end of any junction is more upstream than the expected end of the upstream exon\n #check if the end of any junction is at the expected end of the upstream exon\n if any( jn[1] < cnst_exons[0][1] for jn in iso ) and not( any( jn[1] == cnst_exons[0][1] for jn in iso ) ):\n #grabs the last junction which is less than the expected end of the constant exon\n bad_jn = [ jn for jn in iso if jn[1] < cnst_exons[0][1] ][-1]\n #grabs junction following the screwed up junction\n next_jn = iso[ iso.index(bad_jn)+1 ]\n\n #if the next exonic region is smaller than the difference from the bad to expected junction\n #write the read as is and move to next read\n if (next_jn[1] - next_jn[0]) < (cnst_exons[0][1] - bad_jn[1]):\n outfile.write( read )\n continue\n\n #if its not also check if the suffix of whats missing from the constant exon matches the prefix of the next junction\n if refseq[ bad_jn[1]:cnst_exons[0][1] ] == refseq[ next_jn[0]:next_jn[0] + ( cnst_exons[0][1] - bad_jn[1] ) ]:\n cigarlist = [ list(tup) for tup in read.cigartuples ]\n #gets indices that are a match and need editing\n match_idx = [ idx for idx, tup in enumerate( read.cigartuples ) if tup[0] == 0 ]\n bad_jn_idx = match_idx[ iso.index(bad_jn) ]\n\n assert len(match_idx) > iso.index(bad_jn), bc+'\\nNo matched segments after bad junction'\n next_jn_idx = match_idx[ iso.index(bad_jn) + 1 ]\n\n #adds bases back to the bad junction to force it to end at the expected constant exon end\n cigarlist[ bad_jn_idx ][1]+=cnst_exons[0][1] - bad_jn[1]\n #subtract bases from the next matched segment\n cigarlist[ next_jn_idx ][1]-=cnst_exons[0][1] - bad_jn[1]\n read.cigartuples = tuple( tuple(l) for l in cigarlist )\n\n #check if the start of any junction is farther upstream than the expected start of the constant downstream exon\n #check if the start of any junction is at the expected start of the constant downstream exon\n elif any( jn[0] > cnst_exons[1][0] for jn in iso ) and not( any( jn[0] == cnst_exons[1][0] for jn in iso ) ):\n #grabs the first junction which is less than the expected end of the constant exon\n bad_jn = [ jn for jn in iso if jn[0] > cnst_exons[1][0] ][0]\n #grabs junction preceeding the screwed up junction\n prev_jn = iso[ iso.index(bad_jn)-1 ]\n\n #if the previous exonic region is smaller than the difference from the bad to expected junction\n #write the read as is and move to next read\n if (prev_jn[1] - prev_jn[0]) < (bad_jn[0] - cnst_exons[1][0]):\n outfile.write( read )\n continue\n\n #finally check if the prefix lost on the constant upstream matches the suffix on the previous junction\n if refseq[ cnst_exons[1][0]:bad_jn[0] ] == refseq[ prev_jn[1]-( bad_jn[0] - cnst_exons[1][0] ):prev_jn[1] ]:\n cigarlist = [ list(tup) for tup in read.cigartuples ]\n #gets indices that are a match and need editing\n match_idx = [ idx for idx, tup in enumerate( read.cigartuples ) if tup[0] == 0 ]\n bad_jn_idx = match_idx[ iso.index(bad_jn) ]\n\n assert iso.index(bad_jn) > 0, bc+'\\nNo matched segments before bad junction'\n\n prev_jn_idx = match_idx[ iso.index(bad_jn) - 1 ]\n\n #adds bases back to the bad junction to force it to start at the expected constant exon start\n cigarlist[ bad_jn_idx ][1]+=bad_jn[0] - cnst_exons[1][0]\n #removes bases from the previous matched segment\n cigarlist[ prev_jn_idx ][1]-=bad_jn[0] - cnst_exons[1][0]\n read.cigartuples = tuple( tuple(l) for l in cigarlist )\n\n #sanity check that we didn't alter the length of the read\n assert ( read.infer_query_length() == read.query_length ), bc+'\\nWrong read length - invalid cigar'\n\n outfile.write( read )\n\n #make sure to flush the buffer!\n outfile.close()\n\n\ndef clean_jns(jns,\n cnst_exons,\n tol = 3,\n min_matches = 120 ):\n \"\"\"Removes any junctions within the constant exons,\n joins adjacent junctions,\n and removes the last junction if its <= 3 bp long\n\n Args:\n jns (list of tuples): list of tuples from a PySam read_blocks() function call\n cnst_exons (list of tuples): coords of known constant exons\n\n Returns:\n jns_joined (list of tuples): same list of tuples as input with\n junctions within the constant exons removed\n \"\"\"\n jns_joined = []\n\n prev_jn = None\n #used to check if downstream constant in read\n ds_cnst = soft_clipped = False\n\n #screens out reads with too many bases soft_clipped\n if sum( jn[1] - jn[0] + 1 for jn in jns ) < min_matches:\n soft_clipped = True\n\n #handles the case in which the read doesn't make it to the downstream constant\n #empty junctions implies the read was unmapped - also let that pass\n if jns == [] or jns[-1][1] < cnst_exons[1][0]:\n ds_cnst = True\n\n for _jn in jns:\n\n if not( ds_cnst ) and ( cnst_exons[1][0] - tol ) <= _jn[0] <= ( cnst_exons[1][0] + tol ):\n ds_cnst = True\n\n #changes to 1-based inclusive numbering\n jn = (_jn[0]+1, _jn[1])\n\n if jn[0] >= cnst_exons[0][1] and jn[1] < ( cnst_exons[1][0]+1 ):\n jns_joined.append(jn)\n cur_jn = jn\n #joins adjacent junctions\n if prev_jn:\n if cur_jn[0] == prev_jn[1]+1:\n jns_joined[-2:]=[ (prev_jn[0], cur_jn[1]) ]\n prev_jn=cur_jn\n\n #removes the last junction if its less than 3 bp long\n #hard to align a so few reads accurately so ignore them\n if len(jns_joined)>0 and ( jns_joined[-1][1] - jns_joined[-1][0] ) <= 3:\n jns_joined = jns_joined[:-1]\n\n jns_joined = tuple( jns_joined )\n\n if not ds_cnst:\n jns_joined = None\n elif soft_clipped:\n jns_joined = 0\n\n return jns_joined\n\ndef get_all_isoforms(align_by_samp_dict,\n cnst_exons = None ):\n \"\"\"Gets all isoforms within a pysam alignment file\n\n Args:\n align_dict (dictionary): dictionary with sample names as keys and pysam alignment files as values\n\n Returns:\n out_tbls (dictionary): dictionary with sample names as keys and pandas dataframes with isoform tuples as the\n index and number of reads representing each isoform as the only column\n \"\"\"\n out_tbls = {}\n\n for samp in align_by_samp_dict:\n\n print(samp)\n\n if cnst_exons:\n #creates a counter object of all of the exon junctions\n all_isos_cnt = Counter( [ clean_jns( read.get_blocks(), cnst_exons ) for read in align_by_samp_dict[ samp ] ] )\n else:\n all_isos_cnt = Counter( [ tuple( read.get_blocks() ) for read in align_by_samp_dict[ samp ] ] )\n\n #removes None type from counter - represents reads not mapping to the downstream constant\n del all_isos_cnt[None]\n #removes 0 from counter - represents reads with not enough matches\n del all_isos_cnt[0]\n\n iso_df = pd.DataFrame.from_dict( all_isos_cnt, orient='index' ).reset_index()\n iso_df = iso_df.rename(columns={'index':'isoform', 0:'read_count'}).sort_values(by='read_count', ascending=False)\n iso_df = iso_df.set_index('isoform')\n\n out_tbls[ samp ] = iso_df\n\n return( out_tbls )\n\ndef number_and_merge_isoforms( isodf_by_samp_dict,\n existing_iso_df = None ):\n\n if existing_iso_df:\n cur_df = existing_iso_df.copy()\n\n out_tbl = { samp+'_read_count': [] for samp in isodf_by_samp_dict }\n\n out_tbl[ 'isoform' ] = list( set ( [ iso for samp in isodf_by_samp_dict\n for iso in isodf_by_samp_dict[ samp ].index ] ) )\n\n #this if/else not tested\n if existing_iso_df:\n out_tbl[ 'isonum' ] = []\n\n non_matches = 0\n for iso in out_tbl[ 'isoform' ]:\n\n if iso in cur_df.isoform:\n out_tbl[ 'isonum' ].append( cur_df.index[ cur_df.isoform == iso ] )\n else:\n out_tbl[ 'isonum' ].append( 'iso'+str( cur_df.shape[0] ) )\n non_matches += 1\n else:\n #number all isoforms so they are of the form iso0001\n out_tbl[ 'isonum' ] = [ 'iso'+str(i).zfill( len( str( len( out_tbl[ 'isoform' ] ) ) ) )\n for i in range( len( out_tbl[ 'isoform' ] ) ) ]\n\n for samp in isodf_by_samp_dict:\n\n print(samp)\n\n #set all the read counts as zero\n out_tbl[ samp+'_read_count' ] = [ 0 for i in range( len( out_tbl[ 'isoform' ] ) ) ]\n\n for idx, iso in enumerate( isodf_by_samp_dict[ samp ].index ):\n\n out_tbl[ samp+'_read_count' ][ out_tbl[ 'isoform' ].index( iso ) ] = isodf_by_samp_dict[ samp ].iloc[ idx ].read_count\n\n out_tbl = pd.DataFrame( out_tbl )\n\n #reorder columns so isoform is first column\n ordered_col = ['isoform'] + [ col for col in out_tbl.columns if col != 'isoform' ]\n out_tbl = out_tbl[ ordered_col ]\n\n out_tbl = out_tbl.set_index('isonum')\n\n return out_tbl\n\ndef check_tolerance(var_pos,\n unique_jns,\n tol):\n\n within_tol = False\n\n for jn in unique_jns:\n if var_pos >= ( jn - tol ) and var_pos <= ( jn + tol ):\n within_tol = True\n break\n\n return within_tol\n\ndef cluster_vars(var_bc_counts,\n min_cluster_size,\n tol,\n clustered_bc_ave):\n\n clusters = {}\n i = 0\n\n for variants in var_bc_counts:\n for var in variants.split(','):\n var_pos = int( var.split(':')[1] )\n if not clusters:\n clusters[ 'cluster'+str(i) ] = [ (var_pos,), var_bc_counts[ variants ] ]\n i+=1\n continue\n for cluster, info in clusters.items():\n var_clustered = False\n #if the variant is nearby first variant in cluster add to cluster\n if check_tolerance( var_pos, [ info[0][0] ], tol):\n clusters[ cluster ][0]+= ( var_pos, )\n clusters[ cluster ][1] += var_bc_counts[ variants ]\n var_clustered = True\n #if we've reached the minimum cluster count and the average bc count is at threshold exit\n if len( clusters[ cluster ][0] ) == min_cluster_size and \\\n ( clusters[ cluster ][1] / len( clusters[ cluster ][0] ) ) >= clustered_bc_ave:\n return( True )\n #either way we clustered the variant so break outta the loop\n break\n #otherwise make a new cluster for it\n if not var_clustered:\n clusters[ 'cluster'+str(i) ] = [ (var_pos,), var_bc_counts[ variants ] ]\n i+=1\n\n return( False )\n\n\ndef summarize_isos_by_var_bc(align_by_samp_dict,\n cnst_exons,\n satbl,\n iso_df,\n unique_jns,\n canonical_isos,\n exising_iso_stats_df=None,\n print_count=5,\n min_maxbc_count=100,\n tol=10,\n min_cluster_size=3,\n clustered_bc_ave=3,\n min_bc_max_reads=(2,2)):\n \"\"\"Gets counts for number of variants and barcodes per isoform. Prints variants with the most number of barcodes.\n\n Args:\n pysam_align (PySam AlignmentFile): a tag sorted pysam alignment file with all of the reads for the sample\n cnst_exons (list of tuples): coords of known constant exons\n satbl (pandas dataframe): subassembly dataframe which maps barcodes to variants\n Indexed on readgroupid\n iso_df (pandas dataframe): dataframe of isoforms, isoform groups, and read counts created from get_all_isoforms\n and create_isogrps\n Indexed on isogrp\n print_count (int): number of desired variants to print out per isoform - program will print the variants\n with the highest number of barcodes\n\n Returns:\n iso_df (pandas dataframe): Original iso_df with the addition of number of variants per isoform and number\n of barcodes per isoform\n \"\"\"\n\n if exising_iso_stats_df:\n cur_df = exising_iso_stats_df.copy()\n\n out_tbl = iso_df.copy()\n satbl_c = satbl.copy()\n\n satbl_c = satbl_c.dropna(subset=['variant_list'])\n\n for samp in align_by_samp_dict:\n\n print(samp)\n\n isogrp_to_bc = {}\n\n bc_cnt, read_cnt = 0,0\n\n for bc, _reads in itertools.groupby( align_by_samp_dict[ samp ], lambda _r: _r.get_tag( 'RX' ) ):\n\n if bc not in satbl_c.index:\n continue\n\n for iso, reads in itertools.groupby( _reads, lambda _r: clean_jns( _r.get_blocks(), cnst_exons ) ):\n\n #ignore read if it doesn't splice to downtstream constant or has too few matches\n if iso == None or iso == 0:\n continue\n\n r=list(reads)\n\n isogrp = out_tbl.loc[out_tbl['isoform']==iso].index\n\n assert len(isogrp)==1, 'The isoform matches '+str( len( isogrp ) )+' isogroups instead of the expected 1'\n\n isogrp=isogrp[0]\n\n if isogrp not in isogrp_to_bc:\n isogrp_to_bc[ isogrp ]={}\n\n if bc not in isogrp_to_bc[ isogrp ]:\n isogrp_to_bc[ isogrp ][ bc ] = len(r)\n else:\n isogrp_to_bc[ isogrp ][ bc ] += len(r)\n\n read_cnt+=len(r)\n\n bc_cnt+=1\n\n if bc_cnt%10000==0:\n print('Barcodes processed:',bc_cnt,'Reads processed:',read_cnt)\n\n #takes 16 minutes to get here\n isogrp_var_count = { isogrp: [ len( isogrp_to_bc[ isogrp ] ),\n #should count number of variants\n len( set( satbl_c.loc[ bc ].variant_list\n for bc in isogrp_to_bc[ isogrp ] ) ),\n max( isogrp_to_bc[ isogrp ].values() )\n ]\n for isogrp in isogrp_to_bc\n }\n\n chucked_bcs, chucked_reads = 0,0\n missed_bcs, missed_reads = 0,0\n\n for isogrp in isogrp_to_bc:\n\n bcs = [ bc for bc in isogrp_to_bc[ isogrp ] ]\n\n var_to_bc = {}\n for bc in bcs:\n var = satbl_c.loc[ bc ].variant_list\n if var in var_to_bc:\n var_to_bc[ var ].add(bc)\n else:\n var_to_bc[ var ] = { bc }\n\n var_bc_counts = { var: len(var_to_bc[ var ]) for var in var_to_bc }\n\n var_bc_counts_sort = { var: count for var, count in sorted(var_bc_counts.items(), key=lambda item: -item[1])}\n\n #get the variant with the highest number of barcodes\n top_var = list( itertools.islice( var_bc_counts_sort.items(), 1 ) ) [0]\n\n #get max bcs from one variant for each isogrp\n isogrp_var_count[ isogrp ].append( top_var[1] )\n\n print( 'For isoform:', out_tbl.loc[ isogrp ].isoform )\n print( 'The variants with the top', print_count, 'number of barcodes are:')\n print( list(itertools.islice( var_bc_counts_sort.items(), print_count ) ) )\n\n #get a list of all variants\n var_list = [ v for var in var_bc_counts_sort for v in var.split(',') ]\n var_list_unique = list( set( var_list ) )\n\n #this gets the first position where the isoform differs from expected junctions\n jn_diff = list( { jn for jns in out_tbl.loc[isogrp].isoform for jn in jns }\n - set( unique_jns ) )\n if len( jn_diff )>1:\n jn_diff = [ min( jn_diff ) ]\n\n #lets keep the best isoforms\n #first check if the isoform exactly matches an isoform we're expecting to see\n if any( [ out_tbl.loc[ isogrp ].isoform == can_iso for can_iso in canonical_isos ] ):\n isogrp_var_count[ isogrp ].append( 1 )\n #then check if the max bc per isoform is greater than 100\n elif top_var[1] >= min_maxbc_count:\n isogrp_var_count[ isogrp ].append( 2 )\n #requires the top variant to have at least x barcodes and the top barcode to have at least y reads\n elif top_var[1] <= min_bc_max_reads[0] and isogrp_var_count[ isogrp ][2] <= min_bc_max_reads[1]:\n chucked_bcs += isogrp_var_count[ isogrp ][0]\n chucked_reads += out_tbl.loc[ isogrp ][ samp+'_read_count' ]\n isogrp_var_count[ isogrp ].append( 0 )\n continue\n #check if the var with the max bc is within tolerance of the where the isoform differs\n elif any( [ check_tolerance( int( var.split(':')[1] ),\n jn_diff,\n tol )\n for var in top_var[0].split(',') ] ):\n isogrp_var_count[ isogrp ].append( 3 )\n #check if at least min_cluster_size of variants are within a tol of each other\n elif cluster_vars( var_bc_counts_sort,\n min_cluster_size,\n tol,\n clustered_bc_ave ):\n isogrp_var_count[ isogrp ].append( 4 )\n #check if a double variant is also listed as a single variant\n elif len( var_list ) != len( var_list_unique ):\n isogrp_var_count[ isogrp ].append( 5 )\n else:\n isogrp_var_count[ isogrp ].append( 0 )\n missed_bcs += isogrp_var_count[ isogrp ][0]\n missed_reads += out_tbl.loc[ isogrp ][ samp+'_read_count' ]\n\n print('%i (%.2f%%) barcodes failed the min_bc_max_reads filter' \\\n % ( chucked_bcs, 100(chucked_bcs/sum(i[0] for i in isogrp_var_count.values() ) ) ) )\n print('%i (%.2f%%) reads failed the min_bc_max_reads filter' \\\n % ( chucked_reads, 100(chucked_reads/out_tbl[ samp+'_read_count' ].sum() ) ) )\n print('%i (%.2f%%) barcodes did not fulfill any filter' \\\n % ( missed_bcs, 100(missed_bcs/sum(i[0] for i in isogrp_var_count.values() ) ) ) )\n print('%i (%.2f%%) reads did not fulfill any filter'\\\n % ( missed_reads, 100(missed_reads/out_tbl[ samp+'_read_count' ].sum() ) ) )\n\n cols = [ samp + suffix for suffix in ['_num_bcs','_num_vars','_max_reads_per_bc','_max_bc_per_var','_filter'] ]\n iso_cnts = pd.DataFrame.from_dict(isogrp_var_count, orient='index',\n columns=cols)\n\n out_tbl = pd.merge(out_tbl, iso_cnts, left_index=True, right_index=True, how=\"outer\")\n\n out_tbl.index.name = 'isonum'\n\n #if iso_counts doesn't contain all the isoforms, the values will be null for those rows\n #change to zeros\n out_tbl = out_tbl.fillna(0)\n\n #get totals across samples\n for suffix in [ '_read_count', '_num_bcs', '_num_vars' ]:\n\n #sum of each row across the columns\n col = [ col for col in out_tbl.columns if suffix in col ]\n out_tbl[ 'total'+suffix ] = out_tbl[ col ].sum( axis=1 )\n\n #counts number of samples passing filter for each isoform\n #specifically, counting non zero filter values\n filter_col = [ col for col in out_tbl.columns if 'filter' in col ]\n out_tbl[ 'total_passfilt' ] = out_tbl[ filter_col ].astype( bool ).sum( axis=1 )\n\n if exising_iso_stats_df:\n out_tbl = pd.merge( cur_df, out_tbl, left_index=True, right_index=True, how=\"outer\" )\n out_tbl = out_tbl.fillna(0)\n\n return(out_tbl)\n\ndef summarize_isos_wt_bc(align_by_samp_dict,\n cnst_exons,\n wt_bcs,\n iso_df,\n canonical_isos,\n exising_iso_stats_df=None,\n min_maxbc_count=100,\n min_bc_max_reads=(2,2)):\n \"\"\"Gets counts for number of variants and barcodes per isoform. Prints variants with the most number of barcodes.\n\n Args:\n pysam_align (PySam AlignmentFile): a tag sorted pysam alignment file with all of the reads for the sample\n cnst_exons (list of tuples): coords of known constant exons\n satbl (pandas dataframe): subassembly dataframe which maps barcodes to variants\n Indexed on readgroupid\n iso_df (pandas dataframe): dataframe of isoforms, isoform groups, and read counts created from get_all_isoforms\n and create_isogrps\n Indexed on isogrp\n print_count (int): number of desired variants to print out per isoform - program will print the variants\n with the highest number of barcodes\n\n Returns:\n iso_df (pandas dataframe): Original iso_df with the addition of number of variants per isoform and number\n of barcodes per isoform\n \"\"\"\n\n if exising_iso_stats_df:\n cur_df = exising_iso_stats_df.copy()\n\n out_tbl = iso_df.copy()\n\n for samp in align_by_samp_dict:\n\n print(samp)\n\n isogrp_to_bc = {}\n\n bc_cnt, read_cnt = 0,0\n\n for bc, _reads in itertools.groupby( align_by_samp_dict[ samp ], lambda _r: _r.get_tag( 'RX' ) ):\n\n if bc not in wt_bcs:\n continue\n\n for iso, reads in itertools.groupby( _reads, lambda _r: clean_jns( _r.get_blocks(), cnst_exons ) ):\n\n #ignore read if it doesn't splice to downtstream constant or has too few matches\n if iso == None or iso == 0:\n continue\n\n r=list(reads)\n\n isogrp = out_tbl.loc[ out_tbl[ 'isoform' ] == iso ].index\n\n assert len(isogrp)==1, 'The isoform matches '+str( len( isogrp ) )+' isogroups instead of the expected 1'\n\n isogrp=isogrp[0]\n\n if isogrp not in isogrp_to_bc:\n isogrp_to_bc[ isogrp ]={}\n\n if bc not in isogrp_to_bc[ isogrp ]:\n isogrp_to_bc[ isogrp ][ bc ] = len(r)\n else:\n isogrp_to_bc[ isogrp ][ bc ] += len(r)\n\n read_cnt+=len(r)\n\n bc_cnt+=1\n\n if bc_cnt%10000==0:\n print('Barcodes processed:',bc_cnt,'Reads processed:',read_cnt)\n\n #takes 16 minutes to get here\n isogrp_count = { isogrp: [ len( isogrp_to_bc[ isogrp ] ),\n max( isogrp_to_bc[ isogrp ].values() )\n ]\n for isogrp in isogrp_to_bc\n }\n\n chucked_bcs, chucked_reads = 0,0\n\n for isogrp in isogrp_to_bc:\n\n bcs = [ bc for bc in isogrp_to_bc[ isogrp ] ]\n\n bc_counts = len( bcs )\n\n print( 'For isoform:', out_tbl.loc[ isogrp ].isoform )\n print( 'There are', bc_counts, 'WT barcodes represented')\n\n #lets keep the best isoforms\n #first check if the isoform exactly matches an isoform we're expecting to see\n if any( [ out_tbl.loc[ isogrp ].isoform == can_iso for can_iso in canonical_isos ] ):\n isogrp_count[ isogrp ].append( 1 )\n #then check if the max bc per isoform is greater than 100\n elif bc_counts >= min_maxbc_count:\n isogrp_count[ isogrp ].append( 2 )\n #requires the top variant to have at least x barcodes and the top barcode to have at least y reads\n elif bc_counts > min_bc_max_reads[ 0 ] and isogrp_count[ isogrp ][ 1 ] > min_bc_max_reads[ 1 ]:\n isogrp_count[ isogrp ].append( 6 )\n else:\n isogrp_count[ isogrp ].append( 0 )\n chucked_bcs += isogrp_count[ isogrp ][0]\n chucked_reads += out_tbl.loc[ isogrp ][ samp+'_read_count' ]\n\n print('%i (%.2f%%) barcodes did not fulfill any filter' \\\n % ( chucked_bcs, 100(chucked_bcs/sum(i[0] for i in isogrp_count.values() ) ) ) )\n print('%i (%.2f%%) reads did not fulfill any filter' \\\n % ( chucked_reads, 100(chucked_reads/out_tbl[ samp+'_read_count' ].sum() ) ) )\n\n cols = [ samp + suffix for suffix in ['_num_bcs','_max_reads_per_bc','_filter'] ]\n iso_cnts = pd.DataFrame.from_dict(isogrp_count, orient='index',\n columns=cols)\n\n out_tbl = pd.merge( out_tbl, iso_cnts, left_index=True, right_index=True, how=\"outer\")\n\n out_tbl.index.name = 'isonum'\n\n #if iso_counts doesn't contain all the isoforms, the values will be null for those rows\n #change to zeros\n out_tbl = out_tbl.fillna(0)\n\n #get totals across samples\n for suffix in [ '_read_count', '_num_bcs', ]:\n\n #sum of each row across the columns\n col = [ col for col in out_tbl.columns if suffix in col ]\n out_tbl[ 'total'+suffix ] = out_tbl[ col ].sum( axis=1 )\n\n #counts number of samples passing filter for each isoform\n #specifically, counting non zero filter values\n filter_col = [ col for col in out_tbl.columns if 'filter' in col ]\n out_tbl[ 'total_passfilt' ] = out_tbl[ filter_col ].astype( bool ).sum( axis=1 )\n\n if exising_iso_stats_df:\n out_tbl = pd.merge( cur_df, out_tbl, left_index=True, right_index=True, how=\"outer\" )\n out_tbl = out_tbl.fillna(0)\n\n return(out_tbl)\n\ndef combine_isoforms(iso_df,\n cryptic_exons,\n data_from_csv = False):\n\n out_tbl = iso_df.copy()\n\n filter_cols = [ col for col in out_tbl.columns if 'filter' in col ]\n out_tbl.drop( columns = filter_cols, inplace=True )\n\n isoform_comb = []\n\n for iso in out_tbl.isoform:\n\n #this will make sure any strings are converted to tuples\n if data_from_csv:\n iso = literal_eval(iso)\n\n cur_iso = []\n prev_jn = None\n\n for jn in iso:\n\n #don't add junctions overlapping the cryptic_exons\n if not ( any( [ jn[0] in range( ce[0],ce[1] ) or jn[1] in range( ce[0],ce[1] )\n for ce in cryptic_exons ] ) ):\n cur_iso.append( jn )\n cur_jn = jn\n if prev_jn:\n #combine adjacent junctions\n if cur_jn[0] == prev_jn[1]:\n cur_iso[-2:]=[ (prev_jn[0], cur_jn[1]) ]\n prev_jn=cur_jn\n\n cur_iso = tuple( cur_iso )\n isoform_comb.append( cur_iso )\n\n out_tbl[ 'comb_isoform' ] = isoform_comb\n\n #sums across matching isoforms\n max_cols = [ col for col in out_tbl.columns if 'max' in col ]\n sums_df = out_tbl.groupby(['comb_isoform'],as_index=False).sum().drop(columns=max_cols)\n #max across matching isoforms\n other_cols = [ col for col in out_tbl.columns for name in ['read_count','num_bcs','num_vars','isoform'] if name in col and col!= 'comb_isoform' ]\n max_df = out_tbl.groupby(['comb_isoform'],as_index=False).max().drop(columns=other_cols)\n #counts number of isoforms per isogrp\n counts_df = out_tbl.groupby(['comb_isoform'],as_index=False).count()[['comb_isoform','isoform']].rename(columns={\"isoform\": \"isoform_counts\"})\n #concatenates isoform numbers to track from previous tables\n #iso_nums_df = out_tbl.reset_index().groupby(['comb_isoform'])['index'].apply(','.join).reset_index()\n iso_nums_df = out_tbl.reset_index().groupby(['comb_isoform'])['isonum'].apply(','.join).reset_index()\n #concatenates all isoforms to track from previous table\n isoform_df = out_tbl.reset_index().groupby(['comb_isoform'])['isoform'].apply(tuple).reset_index()\n\n out_tbl = pd.merge(sums_df,max_df,on='comb_isoform')\n out_tbl = pd.merge(out_tbl,counts_df,on='comb_isoform')\n out_tbl = pd.merge(out_tbl,isoform_df,on='comb_isoform')\n out_tbl = pd.merge(out_tbl,iso_nums_df,on='comb_isoform').rename(columns={\"index\": \"comb_iso_nums\"})\n out_tbl = out_tbl.sort_values(by='total_read_count', ascending=False)\n\n out_tbl['isogrp'] = ['isogrp'+str(i).zfill( len( str( out_tbl.shape[0] ) ) ) for i in range( out_tbl.shape[0] ) ]\n out_tbl.set_index('isogrp',inplace=True)\n\n return (out_tbl)\n\ndef create_iso_dict_no_cnst(iso_df):\n\n iso_df_c = iso_df.copy()\n\n #pandas hate tuples so this ensures any strings come out as tuples\n isogrpdict = { iso: literal_eval( iso_df_c.loc[ iso ].isoform )\n for iso in iso_df_c.index }\n\n return( isogrpdict )\n\ndef make_junction_graph(exon_bed):\n\n \"\"\"Create a graph of all possible traversals of specified exons\n\n Args:\n exon_bed (PyBedTool): bed file with exon records. The first record is assumed to be the constant first exon,\n and the last record is assumed to be the constant final exon\n\n Returns:\n dict (str -> tuple): dictionary of named path (ie isoform) traversing exons. Keys are path names,\n values are tuple (series) of tuples corresponding to exons on that path. The exon coordinates returned are\n 1-based, inclusive.\n\n \"\"\"\n\n gr = nx.DiGraph()\n\n nex = len(exon_bed)\n\n gr.add_node( exon_bed[0].start+1 )\n gr.add_node( exon_bed[0].end )\n\n # add donors and acceptors\n for iex in range(1, len(exon_bed)):\n gr.add_node( exon_bed[iex].start+1 ) # +1 to make this 1-based,inclusive\n gr.add_node( exon_bed[iex].end ) # +0 to make this 1-based,inclusive\n\n # loop through donors in order\n for iex in range(len(exon_bed)):\n gr.add_edge( exon_bed[iex].start+1, exon_bed[iex].end )\n # at each donor, add a path to any acceptor which is >= donor position\n for jex in range(len(exon_bed)):\n if exon_bed[jex].start+1 > exon_bed[iex].end:\n gr.add_edge( exon_bed[iex].end, exon_bed[jex].start+1 )\n\n gr.add_node( exon_bed[nex-1].start+1 )\n gr.add_node( exon_bed[nex-1].end )\n\n lpaths = list( [path for path in\n nx.all_simple_paths( gr, exon_bed[0].start+1, exon_bed[nex-1].end )] )\n\n # convert paths to series of (exonstart,exonend) for legibility\n\n lpaths = [ tuple( [ (path[i2],path[i2+1]) for i in range(int(len(path)/2)) ] )\n for path in lpaths ]\n\n lpathnames = ['iso{:02d}'.format( i ) for i in range(len(lpaths)) ]\n\n return dict(zip(lpathnames, lpaths))\n\n\ndef trunc_isoforms_by_readlayout_SE(\n pathdict,\n read_start,\n read_length ):\n\n \"\"\"Create \"compatibility\" group of isoforms cropped by a given single end read of fixed length and\n fixed starting position\n\n Args:\n pathdict (dict<str> -> tuple): isoform name to path dictionary\n read_start (int): fixed starting position of a read; 1-based, inclusive\n read_length (int): fixed read length\n\n Returns:\n - dict (str -> tuple): dictionary of isoform truncated by read position and length. Keys = compatbility group name, values = exon (or partial exon) starts and ends, in 1-based inclusive coordiantes\n\n - dict (str -> list of str) - within each named compatbility group (keys) --> which named isoforms from pathdict are equivalent (values)\n\n \"\"\"\n\n # compat_grp --> ( visible path, [ isonames from paths input ] )\n\n m_iso_vispath = {}\n\n for pathname in pathdict:\n path = pathdict[pathname]\n found_ex = False\n for iex in range(int(len(path))):\n coord_ex = ( path[iex][0], path[iex][1] )\n if read_start >= coord_ex[0] and read_start <= coord_ex[1]:\n found_ex=True\n break\n\n if not found_ex:\n # this read start position does not exist on this path.\n m_iso_vispath[ pathname ] = None\n continue\n\n # truncate path to what is 'visible' given the proposed layout\n path_vis = []\n read_bp_remain = read_length\n\n in_first_ex = True\n while read_bp_remain > 0 and iex < int(len(path)):\n coord_ex = ( path[iex][0], path[iex][1] )\n\n if in_first_ex :\n coord_start = read_start\n in_first_ex = False\n else:\n coord_start = coord_ex[0]\n\n coord_end = min( coord_ex[1], coord_start+read_bp_remain-1 )\n\n path_vis.append( (coord_start,coord_end) )\n\n read_bp_remain -= (coord_end - coord_start + 1)\n\n iex += 1\n\n path_vis = tuple(path_vis) # change to hashable type\n\n m_iso_vispath[ pathname ] = path_vis\n\n m_vispath_name = {}\n m_name_vispath = {}\n\n n_vispath = 0\n for vispath in set(m_iso_vispath.values()):\n vispathname = 'isogrp{:02d}'.format(n_vispath)\n m_name_vispath[vispathname] = vispath\n m_vispath_name[vispath] = vispathname\n n_vispath+=1\n\n m_vispath_liso = {}\n for pathname in pathdict:\n vispath = m_iso_vispath[ pathname ]\n vispathname = m_vispath_name[vispath]\n\n if vispathname not in m_vispath_liso:\n m_vispath_liso[ vispathname ] = [ pathname ]\n else:\n m_vispath_liso[ vispathname] .append( pathname )\n\n return m_name_vispath, m_vispath_liso\n\n\ndef compute_isoform_counts(\n bam,\n isogrpdict,\n cnst_exons,\n tol_first_last=0,\n min_reads=1,\n count_otherisos=False\n):\n \"\"\"\n Create per-barcode counts of reads matching each isoform. Resulting dataset contains a count of total reads, unmapped\n reads, reads with a bad start (greater than 5 (default) basepairs away from most common start), how many reads\n match each isoform, and the psis for each isoform (matching reads/usable reads).\n\n Args:\n bam (pysam.AlignmentFile): a barcode tag-grouped bam file of spliced alignments to reporter sequence\n isogrpdict (dict): isoform compatbility group name --> list of exon start, end coodinates (1-based, inclusive)\n read_start_coord (int): expected fixed read start position\n tol_first_last (int): allow up to this many bases tolerance at the first and last exons\n min_reads (int): require at least this many reads to be present per barcode group\n count_otherisos (bool): should reads not matching any of the known isoforms be counted in the total?\n\n Returns:\n Pandas data frame with per-barcode read counts\n \"\"\"\n\n rowList = []\n\n ctr_bcs,ctr_reads=0,0\n\n for tag, _reads in itertools.groupby( bam, lambda _r:_r.get_tag( 'RX' )):\n\n reads=list(_reads)\n\n if len(reads)<min_reads:\n continue\n\n n_umapped=0\n n_badstart=0\n n_badend=0\n n_softclip=0\n n_nomatch = 0\n ln_matches=[0] len( isogrpdict )\n\n for read in reads:\n if read.is_unmapped:\n n_umapped+=1\n #if the end of the upstream constant exon isn't within the tolerance count it as a bad start\n elif not( any( jn[1] <= cnst_exons[ 0 ][ 1 ] + tol_first_last\n or jn[1] > cnst_exons[ 0 ][ 1 ] - tol_first_last\n for jn in read.get_blocks() ) ):\n n_badstart+=1\n else:\n cur_matches = check_junctions2( read, isogrpdict, cnst_exons, tol_first_last )\n\n if cur_matches == None:\n n_badend+=1\n elif cur_matches == .1:\n n_softclip+=1\n elif sum(cur_matches)==0:\n n_nomatch+=1\n else:\n assert sum(cur_matches) <= 1, ( str(read),str(cur_matches) )\n\n # for now, not dealing with read groups matching multiple isoform groups - this should not happen\n\n for i in range(len(cur_matches)):\n ln_matches[i]+=cur_matches[i]\n\n total = n_umapped + n_badstart + n_badend + n_softclip + n_nomatch + sum(ln_matches)\n\n ctr_bcs+=1\n ctr_reads+=len(reads)\n\n # for debugging only go through a few\n # if ctr_bcs==10:break\n\n if ctr_bcs % 1000 == 0 :\n print('processed {} bcs, {} reads'.format( ctr_bcs, ctr_reads ))\n\n rowList.append( [tag,total,n_umapped,n_badstart,n_badend,n_softclip,n_nomatch]+ln_matches )\n\n # from IPython.core.debugger import set_trace\n # set_trace()\n\n psidf=pd.DataFrame(rowList, columns=['barcode','num_reads','unmapped_reads','bad_starts','bad_ends','soft_clipped','other_isoform']+list(isogrpdict.keys()))\n\n if not count_otherisos:\n psidf['usable_reads']=psidf.num_reads-(psidf.unmapped_reads+psidf.bad_starts+psidf.bad_ends+psidf.soft_clipped+psidf.other_isoform)\n\n #comment this out to save on memory\n #for iso in isogrpdict:\n #psidf[iso+'_psi'] = psidf[iso] / psidf.usable_reads\n else:\n psidf['usable_reads']=psidf.num_reads-(psidf.unmapped_reads+psidf.bad_starts+psidf.bad_ends+psidf.soft_clipped)\n\n #comment this out to save on memory\n #for iso in isogrpdict:\n #psidf[iso+'_psi'] = psidf[iso] / psidf.usable_reads\n\n #psidf['other_isoform_psi'] = psidf['other_isoform'] / psidf.usable_reads\n\n #sets psi to 0 instead of nan if none of the reads map to that isoform'((1201, 1266),)'\n psidf = psidf.fillna(0)\n psidf = psidf.set_index('barcode')\n\n return psidf\n\n# check coverage of exon and of junctions\ndef check_junctions2( read, isogrpdict, cnst_exons, tol_first_last=0 ):\n\n \"\"\"Check an individual aligned read vs a list of isoforms\n\n Args:\n read (pysam.AlignedSegment): a single aligned read\n isogrpdict (dict): isoform compatbility group name --> list of exon start, end coodinates (1-based, inclusive)\n tol_first_last (int): allow up to this many bases tolerance at the first and last exons\n\n Returns:\n list of bools indicating whether this alignment is consistent with each of the provided isoform compat. groups.\n \"\"\"\n # get blocks of reference coverage from the read.\n l_refcoord_blks_cleaned = clean_jns( read.get_blocks(), cnst_exons )\n\n if l_refcoord_blks_cleaned == None:\n lmatches = None\n elif l_refcoord_blks_cleaned == 0:\n lmatches = .1\n else:\n lmatches=[]\n\n # now compare to isogrps\n for isogrpname in isogrpdict:\n isogrp = isogrpdict[isogrpname]\n #print(isogrpname,isogrp)\n\n match = False\n lblks = len( l_refcoord_blks_cleaned )\n if lblks == len( isogrp ) and isogrp == l_refcoord_blks_cleaned:\n match=True\n\n lmatches.append( match )\n\n return lmatches\n\ndef filter_on_barc_len( jxnbybctbl, max_len=35 ):\n li = jxnbybctbl.index.str.len() <= max_len\n subtbl = jxnbybctbl.loc[li].copy()\n return subtbl\n\ndef create_named_isogrps(iso_grp_dict,\n iso_names_dict,\n remove_exon_coords,\n upstream_ex_len,\n read_len,\n tol = 0):\n\n named_iso_grps = { isoname: [] for isoname in iso_names_dict }\n #set up an other category for isoforms that don't match\n named_iso_grps['OTHER']=[]\n\n for isonum,iso in iso_grp_dict.items():\n\n iso_cleaned = []\n for jn in iso:\n #check if the junction overlaps the exons to remove\n if not( any ( jn[0] in range( r_exon[0], r_exon[1] ) or jn[1] in range( r_exon[0], r_exon[1] )\n for r_exon in remove_exon_coords ) ):\n iso_cleaned.append(jn)\n\n #more likely to be off by a base if we are near the read length\n bases_used = sum( jn[1] - jn[0] +1 for jn in iso_cleaned ) + upstream_ex_len\n\n #this will fail if there's two possible isoform matches\n #would that ever happen?\n match=False\n for isoname, iso_to_match in iso_names_dict.items():\n #check if it perfectly matches the named isoform\n if iso_cleaned == iso_to_match:\n match = isoname\n break\n\n #if they're different lengths don't bother going through all the tolerance checks\n elif len( iso_to_match ) != len( iso_cleaned ):\n continue\n\n #if we have are using a tolerance and we are near the read length\n elif tol > 0 and bases_used in range( read_len - tol, read_len +tol ):\n #check if the final junction is within the tolerance (allows for deletions in the upstream exon)\n\n #gets index of all mismatched junctions\n mismatched_jn = [ iso_cleaned.index( jn_c )\n for jn_m, jn_c in zip( iso_to_match, iso_cleaned )\n if jn_m != jn_c ]\n\n #we only want to allow mismatches at the end of the last junction\n #so first check the only mismatch is the last junction\n #then check the start of the junction matches\n #then check if the final junction is within tolerance\n if mismatched_jn[0] == len( iso_cleaned ) - 1 \\\n and iso_cleaned[-1][0] == iso_to_match[-1][0] \\\n and iso_cleaned[-1][1] in range(iso_to_match[-1][1] - tol, iso_to_match[-1][1] + tol):\n match = isoname\n break\n\n if match:\n named_iso_grps[ match ].append( isonum )\n else:\n named_iso_grps[ 'OTHER' ].append( isonum )\n\n return(named_iso_grps)\n\ndef combine_isogrps(\n new_grpnames_to_old_grpnames,\n jxnbybctbl\n ):\n \"\"\" combine barcode groups\n Arguments:\n new_grpnames_to_old_grpnames {[type]} -- [description]\n \"\"\"\n\n newtbl = pd.DataFrame()\n for c in ['num_reads','unmapped_reads','bad_starts','bad_ends','soft_clipped','other_isoform','usable_reads']:\n newtbl[c] = jxnbybctbl[c]\n\n for newgrp in new_grpnames_to_old_grpnames:\n oldgrp = new_grpnames_to_old_grpnames[ newgrp ]\n\n if type(oldgrp)==str:\n oldgrp=[oldgrp]\n else:\n assert type(oldgrp)==list\n\n if len(oldgrp)==1:\n newtbl[newgrp] = jxnbybctbl[oldgrp]\n else:\n newtbl[newgrp] = jxnbybctbl[oldgrp].sum(axis=1)\n\n for newgrp in new_grpnames_to_old_grpnames:\n newtbl[newgrp+'_psi'] = newtbl[newgrp] / newtbl['usable_reads']\n\n #fills in missing PSI values with 0 so we can create sparse datasets\n newtbl = newtbl.fillna(0)\n\n return newtbl\n" }, { "alpha_fraction": 0.609338104724884, "alphanum_fraction": 0.6142479181289673, "avg_line_length": 36.09632110595703, "blob_id": "be331ade5182cf07e795829bbcb9493d5265f9ac", "content_id": "2dfe5d40ef6370fd2e58437650aee3d67627d3b9", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 21186, "license_type": "no_license", "max_line_length": 161, "num_lines": 571, "path": "/splfxseq/splanl/merge_bcs.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import os\nimport pandas as pd\nimport numpy as np\nimport scipy.stats as ss\n\nfrom collections import OrderedDict as odict # default is for keys to come back out in order after I think python 3.7\n\nimport splanl.coords as cds\n\n\n# make (ordered) dict of lists\ndef blanktbl(colnames):\n \"\"\"Make a blank dictionary of column names --> lists\n Can append entries to these lists, then convert it to pandas DataFrame\n\n Args:\n colnames (list of str): column names, will become keys of resulting dict\n\n Returns:\n dict of column names, each associated w/ a blank list\n\n \"\"\"\n return odict( [ (k,[]) for k in colnames] )\n\n\ndef merge_subasm_and_rna_tbls(\n subasm_tbl,\n rna_tbl,\n ):\n\n \"\"\"\n Merge a subassembly and an RNA table; each should be indexed by barcode\n\n Args:\n subasm_tbl (pd.DataFrame): subassembly results, indexed by barcode seq\n rna_tbl (pd.DataFrame): RNAseq results (e.g., psi values), indexed by barcode seq\n\n Returns:\n merged table, in DataFrame, containing the barcodes in both\n\n \"\"\"\n\n # get rid of extra columns\n loc = subasm_tbl\n loc_remove = [ 'ref_target_length','minbq' ] + [c for c in loc if c.startswith('nbp_ge_') ]\n loc = [ c for c in loc if c not in loc_remove ]\n subasm_tbl2 = subasm_tbl[ loc ]\n\n join_tbl = pd.merge( subasm_tbl2,\n rna_tbl,\n how='inner',\n left_index=True,\n right_index=True,\n suffixes=('_subasm','_rna') )\n\n return join_tbl\n\ndef compute_psi_values(\n in_df,\n iso_col = None,\n read_count_col = 'usable_reads'\n):\n \"\"\"\n\n Args:\n\n\n Returns:\n\n \"\"\"\n\n out_df = in_df.copy()\n\n if not iso_col:\n iso_col = [ col for col in out_df.columns if col.startswith( 'iso' ) ]\n\n assert iso_col, 'Please specify columns for PSI'\n\n assert read_count_col in out_df.columns, '%s is not within %s' % ( read_count_col, str( in_df ) )\n\n for col in iso_col:\n out_df[ col + '_psi' ] = out_df[ col ] / out_df[ read_count_col ]\n\n return out_df\n\ndef summarize_byvar_singlevaronly(\n subasm_tbl,\n rna_tbl,\n exon_coords,\n min_usable_reads_per_bc,\n isonames=None ):\n \"\"\"\n Summarize per-variant effects across associated barcodes.\n Considers only single-variant clones; barcodes w/ ≥1 variants are ignored.\n\n Args:\n subasm_tbl (pd.DataFrame): subassembly results, indexed by barcode seq\n rna_tbl (pd.DataFrame): RNAseq results (e.g., psi values), indexed by barcode seq\n exon_coords (list of int tuples): coordinates of cloned exons\n min_usable_reads_per_bc (int): min # reads associated with barcode to be considered\n isonames (list of str): names of isoforms; for each entry 'x', a column 'x_psi' should exist in rna_tbl\n\n Returns:\n pd.DataFrame with per-variant summary values; mean_x, wmean_x, and median_x are the\n across barcodes mean, read-count-weighted mean, and median psi values for each\n isoform x\n \"\"\"\n\n sa_filt = subasm_tbl.query( 'n_variants_passing==1' ).copy()\n\n li_rna = rna_tbl.index.intersection( sa_filt.index )\n\n rna_isect = rna_tbl.loc[ li_rna ].copy()\n\n rna_isect_psi = compute_psi_values( rna_isect, iso_col = isonames )\n\n if isonames is None:\n isonames = [ cn[ :cn.rindex('_') ] for cn in rna_isect_psi.columns if cn.endswith('psi') ]\n assert len(isonames)>0, 'cant infer the isoform name columns; please specify them in parameter isonames'\n\n rna_isect_psi['varlist'] = sa_filt.loc[ li_rna, 'variant_list' ]\n\n out_tbl = blanktbl(\n ['chrom','pos','ref','alt','varlist','n_bc','n_bc_passfilt',\n 'sum_reads',\n 'sum_reads_passfilt',\n 'sum_usable_reads',\n 'sum_unmapped_reads',\n 'sum_badstart_reads',\n 'sum_badend_reads',\n 'sum_softclipped_reads',\n 'sum_otheriso'] +\n [ 'mean_{}'.format(cn) for cn in isonames ] +\n [ 'wmean_{}'.format(cn) for cn in isonames ] +\n [ 'median_{}'.format(cn) for cn in isonames ]\n )\n\n for singlevar, subtbl in rna_isect_psi.groupby( 'varlist' ):\n\n subtbl_filt = subtbl.loc[ subtbl.usable_reads > min_usable_reads_per_bc ].copy()\n\n out_tbl['varlist'].append(singlevar)\n out_tbl['chrom'].append(singlevar.split(':')[0])\n out_tbl['pos'].append(int(singlevar.split(':')[1]))\n out_tbl['ref'].append(singlevar.split(':')[2])\n out_tbl['alt'].append(singlevar.split(':')[3])\n\n out_tbl['n_bc'].append( subtbl.shape[0] )\n out_tbl['n_bc_passfilt'].append( subtbl_filt.shape[0] )\n\n out_tbl['sum_reads'].append( subtbl['num_reads'].sum() )\n\n if subtbl_filt.shape[0]==0:\n out_tbl['sum_reads_passfilt'].append( 0 )\n out_tbl['sum_usable_reads'].append( 0 )\n out_tbl['sum_unmapped_reads'].append( 0 )\n out_tbl['sum_badstart_reads'].append( 0 )\n out_tbl['sum_badend_reads'].append( 0 )\n out_tbl['sum_softclipped_reads'].append( 0 )\n out_tbl['sum_otheriso'].append( 0 )\n\n for iso in isonames:\n out_tbl[ f'mean_{iso}' ].append( None )\n out_tbl[ f'wmean_{iso}' ].append( None )\n out_tbl[ f'median_{iso}' ].append( None )\n\n continue\n #this is tricky to think about\n #currently set so that its counting reads after removing the barcodes not passing the filter\n else:\n out_tbl['sum_reads_passfilt'].append( subtbl_filt['num_reads'].sum() )\n out_tbl['sum_usable_reads'].append( subtbl_filt['usable_reads'].sum() )\n out_tbl['sum_unmapped_reads'].append( subtbl_filt['unmapped_reads'].sum() )\n out_tbl['sum_badstart_reads'].append( subtbl_filt['bad_starts'].sum() )\n out_tbl['sum_badend_reads'].append( subtbl_filt['bad_ends'].sum() )\n out_tbl['sum_softclipped_reads'].append( subtbl_filt['soft_clipped'].sum() )\n out_tbl['sum_otheriso'].append( subtbl_filt['other_isoform'].sum() )\n\n for iso in isonames:\n # mean psi\n out_tbl[ f'mean_{iso}' ].append( subtbl_filt[ f'{iso}_psi' ].mean() )\n # mean psi, weighted by #usable reads\n if subtbl_filt['usable_reads'].sum() != 0:\n out_tbl[ f'wmean_{iso}' ].append( ( subtbl_filt[ f'{iso}_psi' ] * subtbl_filt['usable_reads'] ).sum() / subtbl_filt['usable_reads'].sum() )\n else:\n out_tbl[ f'wmean_{iso}' ].append( np.nan )\n # median psi\n out_tbl[ f'median_{iso}' ].append( subtbl_filt[ f'{iso}_psi' ].median() )\n\n out_tbl = pd.DataFrame( out_tbl )\n\n out_tbl = count_bcs_per_var_sa( out_tbl,\n sa_filt )\n\n #these two are have the total barcode/read count in the denominator\n out_tbl['per_bc_passfilt'] = 100( out_tbl.n_bc_passfilt / out_tbl.n_bc )\n out_tbl['per_reads_passfilt'] = 100( out_tbl.sum_reads_passfilt / out_tbl.sum_reads )\n\n #these columns are based of barcodes which are passing the filter\n #so only reads from barcodes passing the filter are used in the denominator\n out_tbl['per_reads_usable'] = 100( out_tbl.sum_usable_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_unmapped'] = 100( out_tbl.sum_unmapped_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_badend'] = 100( out_tbl.sum_badend_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_badstart'] = 100( out_tbl.sum_badstart_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_softclipped'] = 100( out_tbl.sum_softclipped_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_otheriso'] = 100( out_tbl.sum_otheriso / out_tbl.sum_reads_passfilt )\n\n\n return out_tbl\n\ndef count_bcs_per_var_sa( rna_tbl,\n satbl ):\n\n #count the number of rows for each variant\n #this is the number of barcodes for that variant\n count_tbl = satbl.copy().groupby( [ 'variant_list' ] )[ 'variant_list' ].count().rename('n_bc_sa')\n\n rna_tbl = rna_tbl.copy().set_index( 'varlist' )\n\n out_tbl = pd.merge( rna_tbl, count_tbl, left_index = True, right_index = True )\n\n out_tbl.index.name = 'varlist'\n\n out_tbl = out_tbl.reset_index()\n\n assert rna_tbl.shape[0] == out_tbl.shape[0], 'RNA table rows were lost in the merge'\n\n return out_tbl\n\ndef summarize_byvar_WT( rna_tbl,\n exon_coords,\n min_usable_reads_per_bc,\n chrom,\n isonames=None ):\n \"\"\"\n Summarize per-variant effects across associated barcodes.\n Considers only single-variant clones; barcodes w/ ≥1 variants are ignored.\n\n Args:\n subasm_tbl (pd.DataFrame): subassembly results, indexed by barcode seq\n rna_tbl (pd.DataFrame): RNAseq results (e.g., psi values), indexed by barcode seq\n exon_coords (list of int tuples): coordinates of cloned exons\n min_usable_reads_per_bc (int): min # reads associated with barcode to be considered\n isonames (list of str): names of isoforms; for each entry 'x', a column 'x_psi' should exist in rna_tbl\n\n Returns:\n pd.DataFrame with per-variant summary values; mean_x, wmean_x, and median_x are the\n across barcodes mean, read-count-weighted mean, and median psi values for each\n isoform x\n \"\"\"\n\n rna_psi = compute_psi_values( rna_tbl, iso_col = isonames )\n\n if isonames is None:\n isonames = [ cn[ :cn.rindex('_') ] for cn in rna_psi.columns if cn.endswith('psi') ]\n assert len(isonames)>0, 'cant infer the isoform name columns; please specify them in parameter isonames'\n\n rna_psi_filt = rna_psi.loc[ rna_psi.usable_reads > min_usable_reads_per_bc ].copy()\n\n out_tbl = {}\n\n out_tbl[ 'chrom' ] = [ chrom ]\n out_tbl[ 'varlist' ] = [ 'WT' ]\n\n out_tbl[ 'n_bc' ] = [ rna_psi.shape[ 0 ] ]\n out_tbl[ 'n_bc_passfilt' ] = [ rna_psi_filt.shape[ 0 ] ]\n\n out_tbl[ 'sum_reads' ] = [ rna_psi.num_reads.sum() ]\n\n if rna_psi_filt.shape[ 0 ] == 0:\n\n out_tbl[ 'sum_reads_passfilt' ] = [ 0 ]\n out_tbl[ 'sum_usable_reads' ] = [ 0 ]\n out_tbl[ 'sum_unmapped_reads' ] = [ 0 ]\n out_tbl[ 'sum_badstart_reads' ] = [ 0 ]\n out_tbl[ 'sum_badend_reads' ] = [ 0 ]\n out_tbl[ 'sum_softclipped_reads' ] = [ 0 ]\n out_tbl[ 'sum_otheriso' ] = [ 0 ]\n\n for iso in isonames:\n out_tbl[ f'mean_{iso}' ] = [ None ]\n out_tbl[ f'wmean_{iso}' ] = [ None ]\n out_tbl[ f'median_{iso}' ] = [ None ]\n out_tbl[ f'stdev_{iso}' ] = [ None ]\n\n else:\n\n out_tbl[ 'sum_reads_passfilt' ] = [ rna_psi_filt.num_reads.sum() ]\n out_tbl[ 'sum_usable_reads' ] = [ rna_psi_filt.usable_reads.sum() ]\n out_tbl[ 'sum_unmapped_reads' ] = [ rna_psi_filt.unmapped_reads.sum() ]\n out_tbl[ 'sum_badstart_reads' ] = [ rna_psi_filt.bad_starts.sum() ]\n out_tbl[ 'sum_badend_reads' ] = [ rna_psi_filt.bad_ends.sum() ]\n out_tbl[ 'sum_softclipped_reads' ] = [ rna_psi_filt.soft_clipped.sum() ]\n out_tbl[ 'sum_otheriso' ] = [ rna_psi_filt.other_isoform.sum() ]\n\n for iso in isonames:\n # mean psi\n out_tbl[ f'mean_{iso}' ] = [ rna_psi_filt[ f'{iso}_psi' ].mean() ]\n # mean psi, weighted by #usable reads\n if rna_psi_filt.usable_reads.sum() != 0:\n out_tbl[ f'wmean_{iso}' ] = [ ( rna_psi_filt[ f'{iso}_psi' ] * rna_psi_filt.usable_reads ).sum() / rna_psi_filt.usable_reads.sum() ]\n else:\n out_tbl[ f'wmean_{iso}' ] = [ np.nan ]\n # median psi\n out_tbl[ f'median_{iso}' ] = [ rna_psi_filt[ f'{iso}_psi' ].median() ]\n out_tbl[ f'stdev_{iso}' ] = [ rna_psi_filt[ f'{iso}_psi' ].std() ]\n out_tbl[ f'wstdev_{iso}' ] = [ np.sqrt( ( rna_psi_filt.usable_reads * ( rna_psi_filt[ f'{iso}_psi' ] - out_tbl[ f'wmean_{iso}' ][ 0 ] )*2 ).sum() \\\n / ( rna_psi_filt.usable_reads.sum() - 1 ) ) ]\n\n out_tbl = pd.DataFrame( out_tbl )\n\n #these two are have the total barcode/read count in the denominator\n out_tbl['per_bc_passfilt'] = 100( out_tbl.n_bc_passfilt / out_tbl.n_bc )\n out_tbl['per_reads_passfilt'] = 100( out_tbl.sum_reads_passfilt / out_tbl.sum_reads )\n\n #these columns are based of barcodes which are passing the filter\n #so only reads from barcodes passing the filter are used in the denominator\n out_tbl['per_reads_usable'] = 100( out_tbl.sum_usable_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_unmapped'] = 100( out_tbl.sum_unmapped_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_badend'] = 100( out_tbl.sum_badend_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_badstart'] = 100( out_tbl.sum_badstart_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_softclipped'] = 100( out_tbl.sum_softclipped_reads / out_tbl.sum_reads_passfilt )\n out_tbl['per_otheriso'] = 100( out_tbl.sum_otheriso / out_tbl.sum_reads_passfilt )\n\n return out_tbl\n\n\n####################################\n#\n# routines to combine replicate per-variant tables\n#\n\ndef combine_rep_pervartbls_wide(\n ltbls,\n lsampnames,\n indexcols=['chrom','pos','ref','alt','varlist'],\n group_cols_by_samp=False ):\n\n \"\"\"\n Combine replicate variant effect tables in wide format\n\n Args:\n ltbls (list of pd.DataFrame): list of per-variant effect tables, one per replicate or condition\n lsampnames (list of str): list of respective names for those replciates or conditions\n indexcols (list of str): what columns to use to index each variant table\n group_cols_by_samp (bool): should columns from each sample by grouped together\n\n Returns:\n New pd.DataFrame with by variant effect tables merged together. There may be NAs for variants that are absent from some of the reps/conditions.\n \"\"\"\n\n ltbls_ixd = [ tbl.set_index(indexcols).copy() for tbl in ltbls ]\n\n lcolnames = list(ltbls_ixd[0].columns)\n\n # all tables must have the same set of columns\n for t in ltbls_ixd:\n assert list(t.columns)==lcolnames\n\n for (tbl,sampname) in zip(ltbls_ixd,lsampnames):\n tbl.columns = [ '{}_{}'.format( sampname,col ) for col in tbl.columns ]\n\n tblout = pd.concat( ltbls_ixd, axis=1 )\n\n if group_cols_by_samp:\n loc = []\n for col in lcolnames:\n loc += [ '{}_{}'.format(sampname,col) for sampname in lsampnames ]\n tblout = tblout[loc]\n\n\n tblout = tblout.reset_index()\n\n return tblout\n\n\ndef combine_rep_pervartbls_long(\n ltbls,\n lsampnames,\n indexcols=['chrom','pos','ref','alt','varlist'],\n):\n\n \"\"\"\n Combine replicate variant effect tables in long format\n\n Args:\n ltbls (list of pd.DataFrame): list of per-variant effect tables, one per replicate or condition\n lsampnames (list of str): list of respective names for those replciates or conditions\n indexcols (list of str): what columns to use to index each variant table\n\n Returns:\n New pd.DataFrame with by variant effect tables merged together, with each replicate appearing as a separate row\n \"\"\"\n\n ltbls_ixd = [ tbl.set_index(indexcols).copy() for tbl in ltbls ]\n\n lcolnames = list(ltbls_ixd[0].columns)\n\n # all tables must have the same set of columns\n for t in ltbls_ixd:\n assert list(t.columns)==lcolnames\n\n for (tbl,sampname) in zip(ltbls_ixd,lsampnames):\n\n #allows us to create long tables from long tables that already include a sample column\n if 'sample' in lcolnames:\n tbl['sample_grp']=sampname\n else:\n tbl['sample']=sampname\n\n tblout = pd.concat( ltbls_ixd, axis=0 )\n\n tblout = tblout[ ['sample_grp' if 'sample' in lcolnames else 'sample']+[cn for cn in lcolnames] ]\n\n tblout = tblout.reset_index()\n\n return tblout\n\ndef combine_rep_perbctbls_long(\n ltbls,\n lsampnames\n):\n\n \"\"\"\n Combine replicate variant effect tables in long format\n\n Args:\n ltbls (list of pd.DataFrame): list of per-variant effect tables, one per replicate or condition\n lsampnames (list of str): list of respective names for those replciates or conditions\n indexcols (list of str): what columns to use to index each variant table\n\n Returns:\n New pd.DataFrame with by variant effect tables merged together, with each replicate appearing as a separate row\n \"\"\"\n\n ltbls_ixd = [ tbl.copy() for tbl in ltbls ]\n\n lcolnames = list(ltbls_ixd[0].columns)\n\n # all tables must have the same set of columns\n for t in ltbls_ixd:\n assert list(t.columns)==lcolnames\n\n for (tbl,sampname) in zip(ltbls_ixd,lsampnames):\n\n #allows us to create long tables from long tables that already include a sample column\n if 'sample' in lcolnames:\n tbl['sample_grp']=sampname\n else:\n tbl['sample']=sampname\n\n tblout = pd.concat( ltbls_ixd, axis=0 )\n\n tblout = tblout[ ['sample_grp' if 'sample' in lcolnames else 'sample']+[cn for cn in lcolnames] ]\n\n tblout.index.name = 'barcode'\n\n return tblout\n\n\ndef combine_allisos_pervartbls_long(\n ltbls,\n lsampnames,\n indexcols=['chrom','pos','ref','alt','varlist'],\n):\n\n \"\"\"\n Combine replicate variant effect tables with all isoforms (not necessarily matching column names) in long format\n\n Args:\n ltbls (list of pd.DataFrame): list of per-variant effect tables with all isoforms, one per replicate or condition\n lsampnames (list of str): list of respective names for those replciates or conditions\n indexcols (list of str): what columns to use to index each variant table\n\n Returns:\n New pd.DataFrame with by variant effect tables merged together, with each replicate appearing as a separate row\n Columns not represented in one input dataframe compared to other input dataframes will contain nan values\n \"\"\"\n\n lcolnames = list( set( [ col for tbl in ltbls for col in tbl ] ) )\n\n ltbls_ixd = [ tbl.set_index(indexcols).copy() for tbl in ltbls ]\n\n for (tbl,sampname) in zip(ltbls_ixd,lsampnames):\n\n #allows us to create long tables from long tables that already include a sample column\n if 'sample' in lcolnames:\n tbl['sample_grp']=sampname\n else:\n tbl['sample']=sampname\n\n tblout = ltbls_ixd[0].append( ltbls_ixd[1:], sort = True)\n\n tblout = tblout.reset_index()[ ['sample_grp' if 'sample' in lcolnames else 'sample']+[cn for cn in lcolnames] ]\n\n return tblout\n\ndef combine_allisos_perbctbls_long(\n ltbls,\n lsampnames\n):\n\n \"\"\"\n Combine replicate barcode effect tables with all isoforms (not necessarily matching column names) in long format\n\n Args:\n ltbls (list of pd.DataFrame): list of per-variant effect tables with all isoforms, one per replicate or condition\n lsampnames (list of str): list of respective names for those replciates or conditions\n indexcols (list of str): what columns to use to index each variant table\n\n Returns:\n New pd.DataFrame with by variant effect tables merged together, with each replicate appearing as a separate row\n Columns not represented in one input dataframe compared to other input dataframes will contain nan values\n \"\"\"\n\n lcolnames = list( set( [ col for tbl in ltbls for col in tbl ] ) )\n\n ltbls_ixd = [ tbl.copy() for tbl in ltbls ]\n\n for (tbl,sampname) in zip(ltbls_ixd,lsampnames):\n\n #allows us to create long tables from long tables that already include a sample column\n if 'sample' in lcolnames:\n tbl['sample_grp']=sampname\n else:\n tbl['sample']=sampname\n\n tblout = ltbls_ixd[0].append( ltbls_ixd[1:], sort = True)\n\n tblout = tblout[ ['sample_grp' if 'sample' in lcolnames else 'sample']+[cn for cn in lcolnames] ]\n\n #makes all missing columns 0's\n tblout = tblout.fillna(0)\n\n tblout.index.name = 'barcode'\n\n return tblout\n\ndef filter_byvartbl_snvonly(\n byvar_tbl\n):\n \"\"\"\n Filter by variant table to only SNVs\n\n Args:\n byvar_tbl (pd.DataFrame): per-variant effect table\n Returns:\n Copy of per-variant effect table with only SNV lines included\n \"\"\"\n\n byvar_snvonly = byvar_tbl.loc[ (byvar_tbl.ref.str.len() == 1) & (byvar_tbl.alt.str.len() == 1) ].copy()\n return byvar_snvonly\n\ndef create_sparse_df( large_df,\n sparse_val = 'nan' ):\n\n \"\"\"Make sure the large_df has no meaningful index columns - ie enter as df.reset_index()\"\"\"\n\n in_df = large_df.copy()\n\n non_num_col = list( in_df.select_dtypes(exclude=np.number).columns )\n\n #the sparse dataframe can't have any non-numerical columns so lets set them all as indices\n out_df = in_df.set_index( non_num_col ).select_dtypes(include=np.number)\n\n if sparse_val == 'nan':\n out_df = out_df.astype( pd.SparseDtype( \"float\", np.nan ) )\n elif isinstance(sparse_val, int):\n out_df = out_df.astype( pd.SparseDtype( \"float\", sparse_val ) )\n\n return out_df.reset_index()\n" }, { "alpha_fraction": 0.4920336604118347, "alphanum_fraction": 0.4988124668598175, "avg_line_length": 36.635009765625, "blob_id": "0dba84207baef915139c61bac0523c7c5b048c3e", "content_id": "493c5be5bafa01c71b3e314ebeec579076e106e4", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 20210, "license_type": "no_license", "max_line_length": 150, "num_lines": 537, "path": "/splfxseq/splanl/score_motifs.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import pandas as pd\nimport numpy as np\nimport zipfile as zp\nfrom maxentpy import maxent\nimport scipy.stats as ss\n\ndef ImportFastA(fastafile):\n \"\"\"Opens a fasta file, discards the header, and returns the sequence.\n\n Args:\n fasta file (str): /path/and/name/to.fa\n (file must be unzipped)\n\n Returns:\n sequence (string): sequence of nucleotides with the case of the base retained.\n\n Usage:\n seq = ImportFastA('/path/and/name/to.fa')\n \"\"\"\n seq=''\n with open(fastafile,'rt') as f:\n for line in f:\n if line.startswith('>'):\n next\n else:\n seq+=line.strip()\n return(seq)\n\ndef RNA_to_DNA( RNA_motif_tbl ):\n\n DNA_mtf_tbl = RNA_motif_tbl.copy()\n\n DNA_mtf_tbl.index = DNA_mtf_tbl.index.str.replace( 'U', 'T' )\n DNA_mtf_tbl.index = DNA_mtf_tbl.index.str.replace( 'u', 't' )\n\n return( DNA_mtf_tbl )\n\ndef ExtractKmers( seq,\n k ):\n \"\"\"Takes a sequence of length 2k-1 and extracts all kmers of length k from that sequence.\n\n Args:\n seq (str): sequence to extract kmers from\n k (int): length of kmers\n\n Returns:\n kmers (list of str): list of k kmers from the sequence\n\n Usage:\n kmers=ExtractKmers('GGCATGTAACT',6)\n print(kmers)\n ['GGCATG', 'GCATGT', 'CATGTA', 'ATGTAA', 'TGTAAC', 'GTAACT']\n \"\"\"\n assert len( seq ) == 2k - 1\n return( [ seq[ i: i + k ] for i in range( k ) ] )\n\ndef score_motifs_max( refseq,\n motif_df,\n score_col,\n vardf,\n k,\n col_stem):\n\n tbv = vardf.copy()\n mdf = motif_df.copy()\n\n pos_min = tbv.pos.min()\n\n cloneseq = refseq[ pos_min - k: tbv.pos.max() + k ]\n\n wt = { i + pos_min: np.max( [ float( mdf.loc[ kseq, score_col ] ) if kseq in mdf.index else 0\n for kseq in ExtractKmers( cloneseq[ i: i + ( 2k - 1) ], k ) ] )\n for i in range( len( cloneseq ) - 2( k - 1 ) ) }\n\n wtdf = pd.DataFrame( list( wt.values() ), index = list( wt.keys() ), columns = [ col_stem + '_wtMAX' ] )\n\n mut = { ( i + pos_min, alt ) : np.max( [ float( mdf.loc[ kseq, score_col ] ) if kseq in mdf.index else 0\n for kseq in ExtractKmers( cloneseq[ i: i + ( k - 1) ] + alt + cloneseq[ i + k : i + ( 2k - 1) ], k ) ] )\n for i in range( len( cloneseq ) - 2( k - 1 ) )\n for alt in [ 'A', 'C', 'G', 'T' ] if cloneseq[ i + k - 1 ] != alt\n }\n\n mutdf = pd.DataFrame( list( mut.values() ), index=pd.MultiIndex.from_tuples( mut ), columns=[ col_stem+'_snvMAX' ] )\n mutdf.index = mutdf.index.set_names ( [ 'pos', 'alt' ] )\n\n change = { ( p, a ): mut[ ( p, a ) ] - wt[ p ] for p,a in mutdf.index }\n\n changedf = pd.DataFrame( list( change.values() ), index=pd.MultiIndex.from_tuples( change ), columns=[ col_stem+'_chgMAX' ] )\n changedf.index = changedf.index.set_names ( [ 'pos', 'alt' ] )\n\n outdf = pd.merge( tbv, wtdf, how = 'left', left_on = 'pos', right_on = wtdf.index ).set_index( [ 'pos', 'alt' ] )\n outdf = pd.merge( outdf, mutdf, how = 'left', left_index = True, right_index = True )\n outdf = pd.merge( outdf, changedf, how = 'left', left_index = True, right_index = True ).reset_index()\n firstCol = [ 'chrom', 'pos', 'ref', 'alt' ]\n outdf = outdf[ firstCol + [ c for c in outdf.columns if c not in firstCol ] ]\n\n return outdf\n\ndef score_motifs_mean( refseq,\n motif_df,\n score_col,\n vardf,\n k,\n col_stem):\n\n tbv = vardf.copy()\n mdf = motif_df.copy()\n\n pos_min = tbv.pos.min()\n\n cloneseq = refseq[ pos_min - k: tbv.pos.max() + k ]\n\n wt = { i + pos_min: np.mean( [ float( mdf.loc[ kseq, score_col ] ) if kseq in mdf.index else 0\n for kseq in ExtractKmers( cloneseq[ i: i + ( 2k - 1) ], k ) ] )\n for i in range( len( cloneseq ) - 2( k - 1 ) ) }\n\n wtdf = pd.DataFrame( list( wt.values() ), index = list( wt.keys() ), columns = [ col_stem + '_wtMEAN' ] )\n\n mut = { ( i + pos_min, alt ) : np.mean( [ float( mdf.loc[ kseq, score_col ] ) if kseq in mdf.index else 0\n for kseq in ExtractKmers( cloneseq[ i: i + ( k - 1) ] + alt + cloneseq[ i + k : i + ( 2k - 1) ], k ) ] )\n for i in range( len( cloneseq ) - 2( k - 1 ) )\n for alt in [ 'A', 'C', 'G', 'T' ] if cloneseq[ i + k - 1 ] != alt\n }\n\n mutdf = pd.DataFrame( list( mut.values() ), index=pd.MultiIndex.from_tuples( mut ), columns=[ col_stem+'_snvMEAN' ] )\n mutdf.index = mutdf.index.set_names ( [ 'pos', 'alt' ] )\n\n change = { ( p, a ): mut[ ( p, a ) ] - wt[ p ] for p,a in mutdf.index }\n\n changedf = pd.DataFrame( list( change.values() ), index=pd.MultiIndex.from_tuples( change ), columns=[ col_stem+'_chgMEAN' ] )\n changedf.index = changedf.index.set_names ( [ 'pos', 'alt' ] )\n\n outdf = pd.merge( tbv, wtdf, how = 'left', left_on = 'pos', right_on = wtdf.index ).set_index( [ 'pos', 'alt' ] )\n outdf = pd.merge( outdf, mutdf, how = 'left', left_index = True, right_index = True )\n outdf = pd.merge( outdf, changedf, how = 'left', left_index = True, right_index = True ).reset_index()\n firstCol = [ 'chrom', 'pos', 'ref', 'alt' ]\n outdf = outdf[ firstCol + [ c for c in outdf.columns if c not in firstCol ] ]\n\n return outdf\n\ndef WT_binding_df( refseq,\n motifdf,\n score_col,\n vardf,\n k,\n col_stem):\n\n mdf = motifdf.copy()\n vdf = vardf.copy()\n\n wt_dict = { pos + 1 : [ np.mean( [ mdf.loc[ s ][ score_col ]\n for s in [ refseq[ i: i+k ]\n for i in range( pos-k, pos ) ] ] ),\n vdf.loc[ vdf.pos == pos + 1 ][ 'ref' ].values[0],\n vdf.loc[ vdf.pos == pos + 1 ][ 'hgvs_pos' ].values[0]\n ]\n for pos in range( vdf.pos.min() + k, vdf.pos.max() - k ) }\n\n wt_df = pd.DataFrame.from_dict( wt_dict, orient='index', columns=[col_stem+'_WT','ref','hgvs_pos' ] )\n wt_df.index.name = 'pos'\n wt_df.reset_index(inplace=True)\n\n return wt_df\n\ndef create_hal_input_df( varlist,\n refseq,\n exon_coords,\n wt_psi ):\n\n out_dict = { 'var_name': [],\n 'refseq': [],\n 'altseq': [],\n 'psi': [] }\n\n for var in varlist:\n\n pos = int( var.split( ':' )[ 1 ] )\n\n if exon_coords[ 1 ]>= pos >= exon_coords[ 0 ]:\n\n ref = var.split( ':' )[ 2 ]\n alt = var.split( ':' )[ 3 ]\n\n #adjust for 0 and 1 based numbering\n assert refseq[ pos - 1 ] == ref, \\\n 'Expected reference allele does not match sequence - check numbering'\n\n out_dict[ 'var_name' ].append( var )\n #hal only works on exonic sequences and wants 6 downstream intronic bases in lowercase\n out_dict[ 'refseq' ].append( refseq[ exon_coords[ 0 ] - 1: exon_coords[ 1 ] ] \\\n + refseq[ exon_coords[ 1 ]: exon_coords[ 1 ] + 6 ].lower() )\n #adds in the alternate allele at the reference spot - only tested for SNVS\n out_dict[ 'altseq' ].append( refseq[ exon_coords[ 0 ] - 1: pos - 1 ] \\\n + alt\n + refseq[ pos: exon_coords[ 1 ] ]\n + refseq[ exon_coords[ 1 ]: exon_coords[ 1 ] + 6 ].lower() )\n out_dict[ 'psi' ] = wt_psi\n\n out_tbl = pd.DataFrame( out_dict )\n\n return out_tbl\n\ndef merge_hal( var_df,\n hal_df,\n index = [ 'varlist' ]):\n\n tbv = var_df.copy().set_index( index )\n\n thal = hal_df.copy()\n thal = thal.rename( columns = { 'VARIANT_NAME': 'varlist', 'DELTA_PSI': 'hal_chgPER' } )\n thal = thal[ index + [ 'hal_chgPER' ] ].set_index( index )\n\n out_tbl = pd.merge( tbv, thal, how = 'left', on = index ).reset_index()\n\n return out_tbl\n\ndef get_spidex_scores( chrom,\n coords,\n spidex_dir,\n rev_strand = False ):\n\n if len( str( chrom ) ) > 2:\n chrom = int( chrom[3:] )\n\n if rev_strand:\n trans_tbl = str.maketrans( 'ACGT', 'TGCA' )\n\n out_dict = { 'chrom': [],\n 'gdna_pos_hg19': [],\n 'ref': [],\n 'alt': [],\n 'spanr_chgPER_tissue': [],\n 'spanr_chgZPER': []\n }\n\n zf = zp.ZipFile( spidex_dir )\n with zf.open( 'hg19_spidex.txt' ) as f:\n\n first_line = True\n\n for line in f:\n\n if first_line:\n\n first_line = False\n continue\n\n else:\n\n row = line.decode('utf-8').strip().split( '\\t' )\n\n if int( row[ 0 ] ) != chrom:\n continue\n\n pos = int( row[1] )\n\n if coords[ 0 ] <= pos <= coords[ 1 ]:\n\n out_dict[ 'chrom' ].append( int( row[ 0 ] ) )\n out_dict[ 'gdna_pos_hg19' ].append( pos )\n\n if rev_strand:\n out_dict[ 'ref' ].append( row[ 3 ].translate( trans_tbl ) )\n out_dict[ 'alt' ].append( row[ 4 ].translate( trans_tbl ) )\n else:\n out_dict[ 'ref' ].append( row[ 3 ] )\n out_dict[ 'alt' ].append( row[ 4 ] )\n out_dict[ 'spanr_chgPER_tissue' ].append( float( row[ 5 ] ) )\n out_dict[ 'spanr_chgZPER' ].append( float( row[ 6 ] ) )\n\n #trying to save some time since I'm not iterating efficiently here\n elif pos > coords[ 1 ]:\n\n break\n\n out_tbl = pd.DataFrame( out_dict )\n\n return out_tbl\n\ndef merge_spidex( var_df,\n spidex_df,\n index = [ 'gdna_pos_hg19', 'ref', 'alt' ] ):\n\n tbv = var_df.copy().set_index( index )\n\n tsp = spidex_df.copy().set_index( index )\n tsp = tsp.drop( columns = 'chrom' )\n\n out_tbl = pd.merge( tbv, tsp, how = 'left', on = index ).reset_index()\n\n return out_tbl\n\ndef compute_maxent_scores( byvartbl,\n refseq,\n wt_accept_col,\n wt_donor_col,\n var_accept_col,\n var_donor_col ):\n\n tbv = byvartbl.copy()\n\n wt_a = list( tbv.loc[ tbv[ wt_accept_col ] ].pos )\n wt_a_scores = { pos: score_acceptor( pos, refseq ) for pos in wt_a }\n wt_a_df = pd.DataFrame( wt_a_scores.items(), columns = [ 'pos', 'wt_acc_maxent'] ).set_index( 'pos' )\n\n wt_d = list( tbv.loc[ tbv[ wt_donor_col ] ].pos )\n wt_d_scores = { pos: score_donor( pos, refseq ) for pos in wt_d }\n wt_d_df = pd.DataFrame( wt_d_scores.items(), columns = [ 'pos', 'wt_don_maxent'] ).set_index( 'pos' )\n\n var_a = list( zip( tbv.loc[ tbv[ var_accept_col ] ].pos,\n tbv.loc[ tbv[ var_accept_col ] ].alt ) )\n var_a_scores = { ( pos, alt ): score_acceptor( pos, refseq, alt ) for pos, alt in var_a }\n var_a_df = pd.Series( var_a_scores ).reset_index()\n var_a_df.columns = [ 'pos', 'alt', 'snv_acc_maxent' ]\n var_a_df = var_a_df.set_index( [ 'pos', 'alt' ] )\n\n var_d = list( zip( tbv.loc[ tbv[ var_donor_col ] ].pos,\n tbv.loc[ tbv[ var_donor_col ] ].alt ) )\n var_d_scores = { ( pos, alt ): score_donor( pos, refseq, alt ) for pos, alt in var_d }\n var_d_df = pd.Series( var_d_scores ).reset_index()\n var_d_df.columns = [ 'pos', 'alt', 'snv_don_maxent' ]\n var_d_df = var_d_df.set_index( [ 'pos', 'alt' ] )\n\n out_tbl = tbv.set_index( [ 'pos' ] )\n\n out_tbl = pd.merge( out_tbl, wt_a_df, left_index = True, right_index = True, how = 'outer')\n out_tbl = pd.merge( out_tbl, wt_d_df, left_index = True, right_index = True, how = 'outer')\n\n out_tbl = out_tbl.reset_index().set_index( [ 'pos', 'alt' ] )\n\n out_tbl = pd.merge( out_tbl, var_a_df, left_index = True, right_index = True, how = 'outer')\n out_tbl = pd.merge( out_tbl, var_d_df, left_index = True, right_index = True, how = 'outer')\n\n out_tbl = out_tbl.reset_index()\n\n return out_tbl\n\ndef score_acceptor( pos,\n refseq,\n alt_allele = False ):\n\n if not alt_allele:\n\n assert refseq[ pos - 1 ] == 'A' or refseq[ pos - 1 ] == 'G', \\\n 'Reference does not contain A or G at position %i' % pos\n\n if refseq[ pos - 1 ] == 'A':\n score = maxent.score3( refseq[ pos - 19: pos + 4 ] )\n else:\n score = maxent.score3( refseq[ pos - 20: pos + 3 ] )\n\n else:\n\n assert alt_allele == 'A' or alt_allele == 'G', \\\n 'Alternate allele is not A or G'\n\n if alt_allele == 'A':\n score = maxent.score3( refseq[ pos - 19: pos - 1 ] + alt_allele + refseq[ pos: pos + 4 ] )\n else:\n score = maxent.score3( refseq[ pos - 20: pos - 1 ] + alt_allele + refseq[ pos: pos + 3 ] )\n\n return score\n\ndef score_donor( pos,\n refseq,\n alt_allele = False ):\n\n if not alt_allele:\n\n assert refseq[ pos - 1 ] == 'G' or refseq[ pos - 1 ] == 'T', \\\n 'Reference does not contain G or T at position %i' % pos\n\n if refseq[ pos - 1 ] == 'G':\n score = maxent.score5( refseq[ pos - 4: pos + 5 ] )\n else:\n score = maxent.score5( refseq[ pos - 5: pos + 4 ] )\n\n else:\n\n assert alt_allele == 'G' or alt_allele == 'T', \\\n 'Alternate allele is not G or T'\n\n if alt_allele == 'G':\n score = maxent.score5( refseq[ pos - 4: pos - 1 ] + alt_allele + refseq[ pos: pos + 5 ] )\n else:\n score = maxent.score5( refseq[ pos - 5: pos - 1 ] + alt_allele + refseq[ pos: pos + 4 ] )\n\n return score\n\ndef score_RBP_motifs(refseq,\n motifdf,\n vardf,\n k,\n col_stem ):\n \"\"\"Computes change scores from WT for motifs using an existing database\n\n Args:\n fasta file (str): /path/and/name/to.fa (file must be unzipped)\n motifdf (pandas df) - pandas df of motif scores with the motif as the index\n vardf (pandas df) - pandas df of splicing scores by variants\n k (int) - size of the kmer\n col_stem (str) - desired stem for the columns containing the new scores\n\n Returns:\n vardf (pandas df) - same dataframe with the change in motif score (mean) appended\n \"\"\"\n mdf = motifdf.copy()\n vdf = vardf.copy().set_index( [ 'pos', 'alt' ] )\n\n #score kmers for wt and mutant - assigns 0 if not in motifDict\n #numbering adjusts for 0-based and 1-based coordinates\n wt = { p: np.mean( [ mdf.loc[ kmer ] if kmer in mdf.index else 0\n for kmer in sm.ExtractKmers( refseq[ p - k: p + ( k - 1 ) ], k ) ] )\n for p in vdf.index.unique( level = 'pos' ) }\n\n wtdf = pd.DataFrame( list( wt.values() ), index = list( wt.keys() ), columns = [ col_stem+'_wtMEAN' ] )\n\n #same as above but substitute the mutated base\n mut = { ( p, a ): np.mean( [ mdf.loc[ kmer ] if kmer in mdf.index else 0\n for kmer in sm.ExtractKmers( refseq[ p - k : p - 1 ] + a + refseq[ p : p + ( k - 1 ) ], k ) ] )\n for p,a in vdf.index }\n\n mutdf = pd.DataFrame( list( mut.values() ), index=pd.MultiIndex.from_tuples( mut ), columns=[ col_stem+'_snvMEAN' ] )\n\n #outdf = pd.concat( [ vdf, changedf ],axis=1 )\n #outdf = pd.merge( vdf, wtdf, how = 'left', left_on = 'pos', right_on = wtdf.index ).set_index( [ 'pos', 'alt' ] )\n outdf = pd.merge( vdf.reset_index().set_index( 'pos' ),\n wtdf,\n how = 'left',\n left_index = True,\n right_index = True )\n outdf.index.name = 'pos'\n\n outdf = pd.merge( outdf.reset_index().set_index( [ 'pos', 'alt' ] ),\n ( mutdf.reset_index()\n .rename( columns = { 'level_0': 'pos', 'level_1': 'alt' } )\n .set_index( [ 'pos', 'alt' ] ) ),\n how = 'left',\n left_index = True,\n right_index = True ).reset_index()\n\n outdf[ col_stem + '_chgMEAN' ] = outdf[ col_stem + '_snvMEAN' ] - outdf[ col_stem + '_wtMEAN' ]\n\n\n firstCol = [ 'chrom', 'pos', 'ref', 'alt' ]\n outdf = outdf[ firstCol + [ c for c in outdf.columns if c not in firstCol ] ]\n\n return outdf\n\ndef merge_mmsplice( var_df,\n mmsplice_df,\n index = [ 'gdna_pos_hg19', 'ref', 'alt' ] ):\n\n tbv = var_df.set_index( index ).copy()\n\n tmm = mmsplice_df.copy()\n tmm = tmm.rename( columns = { 'delta_logit_psi': 'mmsplice_chgPERlogit' } )\n tmm = tmm[ index + [ 'mmsplice_chgPERlogit' ] ].set_index( index )\n\n out_tbl = pd.merge( tbv, tmm, how = 'left', on = index ).reset_index()\n\n return out_tbl\n\ndef nom_RBPs( tbl_byvar,\n rbp_info,\n sdv_col,\n region_cds,\n wt_bind_thresh,\n chg_thresh,\n p_thresh,\n rbp_suff = '_wtMAX', ):\n\n tbv = tbl_byvar.loc[ ( tbl_byvar.pos >= region_cds[ 0 ] ) & ( tbl_byvar.pos <= region_cds[ 1 ] ) ].copy()\n info = rbp_info.copy()\n\n rbp_cols = [ col for col in tbv if col.endswith( rbp_suff ) ]\n\n #counts number of sdvs\n sdv = tbv[ sdv_col ].sum()\n\n #counts total number of variants in region\n total = len( tbv )\n\n out_dict = {}\n\n for motif_id in rbp_cols:\n\n rbp_name = info[ ( info.Motif_ID == motif_id[ : -len( rbp_suff ) ] ) \\\n & ( info.RBP_Species == 'Homo_sapiens') ].RBP_Name.tolist()\n\n #some of the RBP aren't from humans - skip these\n if len( rbp_name ) == 0:\n continue\n\n #gets the maximum WT binding 'affinity' to SDVs in the defined region\n wtmax = ( tbv.loc[ ( tbv[ sdv_col ] ) ][ [ 'pos', motif_id ] ]\n .groupby( [ 'pos' ] )\n .agg( np.nanmean ) ).max()[ 0 ]\n\n #if it is below the set threshold, the protein doesn't bind there - move on\n if wtmax < wt_bind_thresh:\n continue\n\n #counts the number of variants (not necessarily SDV) which break the motif\n #counting the number of variants in the defined region with a change score lower than the threshold\n snv_below = ( tbv[ motif_id.replace( 'wt', 'chg' ) ] <= chg_thresh ).sum()\n\n #if no variants break the motif, move on\n if snv_below == 0:\n continue\n\n #counts number of sdv positions with WT binding above threshold\n wt_above = ( ( tbv.loc[ ( tbv[ sdv_col ] ) ][ [ 'pos', motif_id ] ]\n .groupby( [ 'pos', ] )\n .agg( np.nanmean ) ) >= wt_bind_thresh ).sum()\n\n #counts number of SDVs with a change score below threshold\n sdv_snv_below = ( tbv.loc[ tbv[ sdv_col ] ]\n [ motif_id.replace( 'wt', 'chg' ) ] <= chg_thresh ).sum()\n\n assert sdv_snv_below + ( sdv - sdv_snv_below ) + ( snv_below - sdv_snv_below ) + ( total - sdv ) - ( snv_below - sdv_snv_below ) == len( tbv )\n #compares the number of variants breaking the motif between SDVs and neutral variants\n odds, p = ss.fisher_exact( [ [ sdv_snv_below, sdv - sdv_snv_below ],\n [ snv_below - sdv_snv_below, ( total - sdv ) - ( snv_below - sdv_snv_below ) ] ]\n )\n\n #checks that the relationship is significant, and in the right direction (odds ratio > 1)\n if p < p_thresh and odds > 1:\n out_dict[ '_'.join( rbp_name + [ motif_id[ : -len( rbp_suff ) ] ] ) ] = \\\n ( wtmax,\n ss.fisher_exact( [ [ sdv_snv_below,\n sdv - sdv_snv_below ],\n [ snv_below - sdv_snv_below,\n ( total - sdv ) - ( snv_below - sdv_snv_below ) ] ] )\n )\n\n return out_dict\n" }, { "alpha_fraction": 0.7582967877388, "alphanum_fraction": 0.7733249664306641, "avg_line_length": 227.14285278320312, "blob_id": "cc3e895c5c703be3a49f72d830e309944840d6fd", "content_id": "65d56a8a8b8c0a4d7c019404ba4cb1b7ca5015a3", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Markdown", "length_bytes": 1597, "license_type": "no_license", "max_line_length": 1045, "num_lines": 7, "path": "/README.md", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "# High-throughput splicing assays identify missense and silent splice-disruptive POU1F1 variants underlying pituitary hormone deficiency\n\n### Peter Gergics, Cathy Smith, Hironori Bando, Alexander A. L. Jorge, Denise Rockstroh-Lippold, Sebastian A. Vishnopolska, Frederic Castinetti, Mariam Maksutova, Luciani Renata Silveira Carvalho, Julia Hoppmann, Julián Martínez Mayer, Frédérique Albarel, Debora Braslavsky, Ana Keselman, Ignacio Bergadá, Marcelo A. Martí, Alexandru Saveanu, Anne Barlier, Rami Abou Jamra, Michael H. Guo, Andrew Dauber, Marilena Nakaguma, Berenice B. Mendonca, Sajini N. Jayakody, A. Mendonça, A Bilge Ozel, Qing Fang, Qianyi Ma, Jun Z. Li, Thierry Brue, María Ines Pérez Millán, Ivo J. P. Arnhold, Roland Pfaeffle, Jacob O. Kitzman, Sally A. Camper\n\nPituitary hormone deficiency occurs in ~1:4,000 live births. Approximately 3% of the cases are due to mutations in the alpha isoform of POU1F1, a pituitary-specific transcriptional activator. We found four separate heterozygous missense variants in unrelated hypopituitarism patients that were predicted to affect a minor isoform, POU1F1 beta, which can act as a transcriptional repressor. These variants retain repressor activity, but they shift splicing to favor the expression of the beta isoform, resulting in dominant negative loss of function. Using a high throughput splicing reporter assay, we tested 1,070 single nucleotide variants in POU1F1. We identified 96 splice disruptive variants, including 14 synonymous variants. In separate cohorts, we found two additional synonymous variants nominated by this screen that co-segregate with hypopituitarism. This study underlines the importance of evaluating the impact of variants on splicing and provides a catalog for interpretation of variants of unknown significance in the POU1F1 gene.\n\nThe notebooks in this repo will create datasets from bam files and then recapitulate the plots and analyses from the paper.\n" }, { "alpha_fraction": 0.6948176622390747, "alphanum_fraction": 0.6948176622390747, "avg_line_length": 20.625, "blob_id": "3a441e32718fd6fb7a65e91deda62746d3a7f50f", "content_id": "138fe8fdafcfbab500b6f9750fe3139585a56912", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 521, "license_type": "no_license", "max_line_length": 73, "num_lines": 24, "path": "/splfxseq/setup.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "from setuptools import setup\n#from distutils.core import setup\nfrom distutils.extension import Extension\nfrom Cython.Build import cythonize\nfrom Cython.Distutils import build_ext\n\nimport pysam\nimport numpy \nimport glob\nimport os.path as op\n\nsetup(\n name=\"splfxseq\",\n\n packages=['spliceprocess','splanl'],\n\n include_dirs = [numpy.get_include()]+pysam.get_include(),\n\n entry_points = {\n 'console_scripts': [ \n 'index_tagsorted_bam = spliceprocess.index_tagsorted_bam:main', \n ]\n }\n)\n\n\n" }, { "alpha_fraction": 0.42938515543937683, "alphanum_fraction": 0.4408257305622101, "avg_line_length": 33.67551040649414, "blob_id": "69edce2649a03b16a6fc5cab855b40a2dccfca00", "content_id": "0813cd770061285cb9ceb35570e0296b72a94c67", "detected_licenses": [], "is_generated": false, "is_vendor": false, "language": "Python", "length_bytes": 103229, "license_type": "no_license", "max_line_length": 145, "num_lines": 2977, "path": "/splfxseq/splanl/plots.py", "repo_name": "kitzmanlab/pou1f1_splicing", "src_encoding": "UTF-8", "text": "import altair as alt\nimport pandas as pd\nimport numpy as np\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nimport matplotlib.transforms as tfrms\nfrom matplotlib.artist import Artist as art\nfrom matplotlib import gridspec\nfrom collections import Counter\nimport splanl.coords as cds\nimport splanl.merge_bcs as mbcs\nimport splanl.post_processing as pp\nfrom sklearn.metrics import roc_curve\nfrom sklearn.metrics import auc\nfrom sklearn.metrics import precision_recall_curve\nimport upsetplot as up\n\ngithub_colors = '3182bd6baed69ecae1c6dbefe6550dfd8d3cfdae6bfdd0a231a35474c476a1d99bc7e9c0756bb19e9ac8bcbddcdadaeb636363969696bdbdbdd9d9d9'\nlight_colors = [ '#' + github_colors[i:i+6] for i in range( 0, len( github_colors ), 6 ) ]\n\ndef waterfall_plot(\n bctbl,\n col_read_counts,\n percentile,\n title='',\n x_ax_title='Read Count Rank Log10',\n y1_ax_title='Read Count Log10',\n y2_ax_title='Cumulative Read Count Percentile'\n):\n\n bc_ranks = bctbl.copy()\n\n bc_ranks.sort_values(by=[col_read_counts],ascending=False,inplace=True)\n\n bc_ranks[col_read_counts+'_rank'] = np.arange(bc_ranks.shape[0])\n bc_ranks[col_read_counts+'_log10']=np.log10(bc_ranks[col_read_counts]+.1)\n bc_ranks[col_read_counts+'_rank_log10']=np.log10(bc_ranks[col_read_counts+'_rank']+1)\n bc_ranks['cumulative_read_percentage'] = 100bc_ranks[col_read_counts].cumsum()/bc_ranks[col_read_counts].sum()\n percentile_cutoff = bc_ranks.loc[bc_ranks['cumulative_read_percentage']>=percentile][col_read_counts+'_rank_log10'].reset_index(drop=True)[0]\n read_count_cutoff = bc_ranks.loc[bc_ranks['cumulative_read_percentage']>=percentile][col_read_counts].reset_index(drop=True)[0]\n\n fig, ax1 = plt.subplots()\n\n color = 'blue'\n ax1.set_xlabel(x_ax_title)\n ax1.set_ylabel(y1_ax_title, color=color)\n ax1.plot(bc_ranks[col_read_counts+'_rank_log10'], bc_ranks[col_read_counts+'_log10'], color=color)\n ax1.tick_params(axis='y', labelcolor=color)\n\n ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis\n\n color = 'red'\n ax2.set_ylabel(y2_ax_title, color=color) # we already handled the x-label with ax1\n ax2.plot(bc_ranks[col_read_counts+'_rank_log10'], bc_ranks['cumulative_read_percentage'], color=color)\n ax2.tick_params(axis='y', labelcolor=color)\n\n plt.axvline(percentile_cutoff, color='black')\n\n fig.tight_layout() # otherwise the right y-label is slightly clipped\n plt.show()\n\n print('The read count cut off at the',percentile,'th percentile is',read_count_cutoff)\n\n\n##########################################################################################\n##########################################################################################\n##########################################################################################\n##\n## psi by coordinate plots\n##\n\n\n##########################################################################################\n## altair-style, one sample\n\ndef altplot_psi_by_pos_onesamp(\n tblbyvar,\n col_iso_y,\n addl_cols_tooltip,\n fill_col='alt',\n lposrng_exon=None,\n yscale=None,\n height=100,\n width=800,\n title='',\n x_ax_title='pos',\n y_ax_title=None\n):\n assert (tblbyvar.ref.str.len() == 1).all()\n assert (tblbyvar.alt.str.len() == 1).all()\n\n tbv = tblbyvar.copy()\n tbv['pos_display'] = tbv['pos']\n for ofs,mut in zip( (0.1,0.3,0.5,0.7), 'ACGT' ):\n tbv.loc[ tbv.alt==mut, 'pos_display' ]+=ofs\n\n if yscale is None:\n y = alt.Y('{}:Q'.format(col_iso_y), axis=alt.Axis(title=y_ax_title) )\n else:\n y = alt.Y('{}:Q'.format(col_iso_y), scale=yscale, axis=alt.Axis(title=y_ax_title) )\n\n if y_ax_title is None:\n y_ax_title=col_iso_y\n\n points = alt.Chart( tbv , title=title ).mark_circle(\n size=15\n ).encode(\n x=alt.X('pos_display:Q', scale=alt.Scale(zero=False) ,\n axis=alt.Axis(title=x_ax_title)),#, sort=list( pos_display_categ.categories )),\n y=y,\n tooltip=['pos','ref','alt']+addl_cols_tooltip,\n fill=alt.Color(fill_col+':N',scale=alt.Scale(scheme='category10'))\n ).properties( height=height, width=width )\n\n gr = points\n\n if lposrng_exon is not None:\n exonbox=pd.DataFrame( {'x':[lposrng_exon[i][0] for i in range(len(lposrng_exon))],\n 'x2':[lposrng_exon[i][1] for i in range(len(lposrng_exon))],\n 'y':tblbyvar[col_iso_y].min(), 'y2':tblbyvar[col_iso_y].max()} )\n ex = alt.Chart( exonbox ).mark_rect( color='yellow', opacity=0.1 ).encode( x='x', x2='x2', y='y', y2='y2' )\n gr = ex + gr\n\n return gr\n\n##########################################################################################\n## altair-style, one sample w/ zoom\n\ndef altplot_psi_by_pos_onesamp_wzoom(\n tblbyvar,\n col_iso_y,\n addl_cols_tooltip,\n fill_col='alt',\n lposrng_exon=None,\n yscale=None,\n height=100,\n width=800,\n zoom_frac = 0.5,\n title=''\n):\n\n zoom_frac = max(0.1, min(0.9, zoom_frac))\n\n assert (tblbyvar.ref.str.len() == 1).all()\n assert (tblbyvar.alt.str.len() == 1).all()\n\n tbv = tblbyvar.copy()\n tbv['pos_display'] = tbv['pos']\n for ofs,mut in zip( (0.1,0.3,0.5,0.7), 'ACGT' ):\n tbv.loc[ tbv.alt==mut, 'pos_display' ]+=ofs\n\n if yscale is None:\n y = alt.Y('{}:Q'.format(col_iso_y))\n else:\n y = alt.Y('{}:Q'.format(col_iso_y), scale=yscale )\n\n selbrush = alt.selection(type='interval', encodings=['x'])\n\n points = alt.Chart( tbv, title=title ).mark_point(\n size=15\n ).encode(\n x=alt.X('pos_display:Q', scale=alt.Scale(zero=False, domain=selbrush)),#, sort=list( pos_display_categ.categories )),\n y=y,\n tooltip=['pos','ref','alt']+addl_cols_tooltip,\n # fill='alt:N'\n fill=alt.Color(fill_col+':N',scale=alt.Scale(scheme='category10'))\n ).properties( height=height, width=int(1-zoom_frac)width )\n\n gr = points\n\n if lposrng_exon is not None:\n exonbox=pd.DataFrame( {'x':[lposrng_exon[i][0] for i in range(len(lposrng_exon))],\n 'x2':[lposrng_exon[i][1] for i in range(len(lposrng_exon))],\n 'y':np.min(tblbyvar.col_iso_y), 'y2':1} )\n ex = alt.Chart( exonbox ).mark_rect( color='yellow', opacity=0.1 ).encode( x='x', x2='x2', y='y', y2='y2' )\n gr = ex + gr\n\n\n pointszoom = points.properties( width=int(zoom_frac)width ).add_selection( selbrush )\n\n gr_ret = pointszoom \| gr\n\n return gr_ret\n\ndef altplot_psi_by_pos_onesamp_multiiso_wzoom(\n tblbyvar,\n l_col_iso_y,\n addl_cols_tooltip,\n lposrng_exon=None,\n yscale=None,\n height=100,\n width=800,\n zoom_frac = 0.5,\n title='' ):\n\n zoom_frac = max(0.1, min(0.9, zoom_frac))\n\n assert (tblbyvar.ref.str.len() == 1).all()\n assert (tblbyvar.alt.str.len() == 1).all()\n\n tbv = tblbyvar.copy()\n tbv['pos_display'] = tbv['pos']\n for ofs,mut in zip( (0.1,0.3,0.5,0.7), 'ACGT' ):\n tbv.loc[ tbv.alt==mut, 'pos_display' ]+=ofs\n\n selbrush = alt.selection(type='interval', encodings=['x'])\n\n # hack to get a title over everything\n tpl = alt.Chart( {'values':[{'text':title}]} ).mark_text( size=14 ).encode( text='text:N' )\n\n lpoints = [tpl]\n\n for col_iso_y in l_col_iso_y:\n if yscale is None:\n y = alt.Y('{}:Q'.format(col_iso_y))\n else:\n y = alt.Y('{}:Q'.format(col_iso_y), scale=yscale )\n\n points = alt.Chart( tbv ).mark_point(\n size=15\n ).encode(\n x=alt.X('pos_display:Q', scale=alt.Scale(zero=False, domain=selbrush)),#, sort=list( pos_display_categ.categories )),\n y=y,\n tooltip=['pos','ref','alt']+addl_cols_tooltip,\n # fill='alt:N'\n fill=alt.Color('alt:N',scale=alt.Scale(scheme='category10'))\n ).properties( height=height, width=int(1-zoom_frac)width )\n\n pointszoom = points.properties( width=int(zoom_frac)width ).add_selection( selbrush )\n\n if lposrng_exon is not None:\n exonbox=pd.DataFrame( {'x':[lposrng_exon[i][0] for i in range(len(lposrng_exon))],\n 'x2':[lposrng_exon[i][1] for i in range(len(lposrng_exon))],\n 'y':0, 'y2':1} )\n ex = alt.Chart( exonbox ).mark_rect( color='yellow', opacity=0.1 ).encode( x='x', x2='x2', y='y', y2='y2' )\n points = ex + points\n\n lpoints.append( pointszoom \| points )\n\n gr = alt.vconcat( lpoints ).configure_view( stroke=None ).configure_concat( spacing=1 )\n\n return gr\n\ndef altplot_scatter_onesamp(\n tblbyvar,\n col_iso_y,\n col_x,\n addl_cols_tooltip=[],\n fill_col='var_type',\n yscale=None,\n height=300,\n width=300,\n title=''\n):\n\n tbv = tblbyvar.copy()\n\n if yscale is None:\n y = alt.Y('{}:Q'.format(col_iso_y))\n else:\n y = alt.Y('{}:Q'.format(col_iso_y), scale=yscale )\n\n points = alt.Chart( tbv , title=title ).mark_circle(\n size=20\n ).encode(\n x=alt.X(col_x+':Q', scale=alt.Scale(zero=False)),#, sort=list( pos_display_categ.categories )),\n y=y,\n tooltip=addl_cols_tooltip,\n fill=alt.Color(fill_col+':N',scale=alt.Scale(scheme='category10'))\n ).properties( height=height, width=width )\n\n gr = points\n\n return gr\n\ndef altplot_scatter_nofill(\n tblbyvar,\n col_iso_y,\n col_x,\n addl_cols_tooltip=[],\n yscale=None,\n height=300,\n width=300,\n title=''\n):\n\n tbv = tblbyvar.copy()\n\n if yscale is None:\n y = alt.Y('{}:Q'.format(col_iso_y))\n else:\n y = alt.Y('{}:Q'.format(col_iso_y), scale=yscale )\n\n points = alt.Chart( tbv , title=title ).mark_circle(\n size=20\n ).encode(\n x=alt.X(col_x+':Q', scale=alt.Scale(zero=False)),#, sort=list( pos_display_categ.categories )),\n y=y,\n tooltip=addl_cols_tooltip\n ).properties( height=height, width=width )\n\n gr = points\n\n return gr\n\ndef altplot_violin_onesamp(\n tblbyvar,\n col_y,\n col_cat_x,\n yscale=None,\n height=400,\n width=400,\n title=''\n):\n assert (tblbyvar.ref.str.len() == 1).all()\n assert (tblbyvar.alt.str.len() == 1).all()\n\n tbv = tblbyvar.copy()\n\n points = alt.Chart( tbv , title=title ).transform_density(\n col_y,\n as_=[col_y,'density'],\n groupby=[col_cat_x]\n ).mark_area(\n orient='horizontal'\n ).encode(\n y=col_y+':Q',\n color=col_cat_x+':N',\n x=alt.X(\n 'density:Q',\n stack='center',\n axis=alt.Axis(labels=False, values=[0],grid=False, ticks=True),\n ),\n column=alt.Column(\n col_cat_x+':N',\n header=alt.Header(\n titleOrient='bottom',\n labelOrient='bottom',\n labelPadding=0,\n )\n ),\n ).properties( height=height, width=width )\n\n gr = points\n\n return gr\n\ndef PlotPSIByPos(vardf,\n col_y_isoform,\n shade_exons,\n gene_name,\n fig_size = (20,7),\n coords = 'cdna',\n vec_corange_cloned = None,\n vec_corange_exons = None,\n cdna_corange_exons = None,\n zoom=None,\n tick_spacing=10,\n legend_loc='best',\n y_ax_title='',\n legend_title='Nucleotide Substitution from WT',\n y_ax_lim = (0,1),\n invert_x = False,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n rev_trans = False,\n hlines = None\n ):\n\n tbv=vardf.copy()\n\n tbv.sort_values( by = ['pos'], inplace = True )\n bcs_tbl = tbv.pivot( index = 'pos', columns = 'alt', values = col_y_isoform )\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n bcs_tbl = bcs_tbl.loc[ zoom[0]:zoom[1] ]\n\n #check if plot will lose bars due to not enough space for all the pixels\n dpi = 100\n if ( bcs_tbl.shape[0]6 ) > ( fig_size[0]dpi ):\n fig_height = fig_size[1]\n fig_size = ( ( bcs_tbl.shape[0]6 / dpi ), fig_height )\n print('Adjusting figure width to accomodate all pixels...')\n\n if print_ex_count:\n print('This figure shows %i exonic bases.' % sum( c[1]-c[0] for c in shade_exons ) )\n\n #usually want to represent alternate as seen on the forward strand so reverse complement columns\n if rev_trans:\n bcs_tbl = bcs_tbl.rename( columns = { \"A\": \"T\", \"C\": \"G\", \"G\": \"C\", \"T\": \"A\" } )\n\n bcs_tbl.loc[:,['A', 'C', 'G', 'T']].plot.bar( color = [ '#C00001', '#00AD4F', '#FFCF07', '#002966' ],\n align='center',\n width=1,\n figsize= fig_size )\n\n plt.title(\n col_y_isoform+' '+y_ax_title+' by Position for Single Nucleotide Variants in $\\it{%s}$'%gene_name,\n fontsize=24)\n\n if y_ax_lim:\n plt.ylim( y_ax_lim )\n\n plt.ylabel(col_y_isoform+' '+y_ax_title,fontsize=22)\n plt.yticks(fontsize=18)\n\n if coords.lower() == 'cdna':\n plt.xlabel('cDNA Position',fontsize=22)\n bcs_tbl['hgvs_pos'] = cds.pos_to_hgvspos( bcs_tbl.index,\n vec_corange_cloned,\n vec_corange_exons,\n cdna_corange_exons\n )\n plt.xticks( [idx for idx,p in enumerate(bcs_tbl.index) if idx%tick_spacing==0],\n [c for idx,c in enumerate(bcs_tbl.hgvs_pos) if idx%tick_spacing==0],\n fontsize=18,\n rotation='vertical' )\n\n elif coords.lower() == 'gdna':\n plt.xlabel('gDNA Position',fontsize=22)\n plt.xticks( [idx for idx,p in enumerate(bcs_tbl.index) if idx%tick_spacing==0],\n [c for idx,c in enumerate(bcs_tbl.index) if idx%tick_spacing==0],\n fontsize=18,\n rotation='vertical' )\n\n elif coords.lower() == 'vector':\n plt.xlabel('Vector Position',fontsize=22)\n plt.xticks( [idx for idx,p in enumerate(bcs_tbl.index) if idx%tick_spacing==0],\n [c for idx,c in enumerate(bcs_tbl.index) if idx%tick_spacing==0],\n fontsize=18,\n rotation='vertical' )\n\n if hlines:\n for line in hlines:\n plt.axhline( line, c = 'black', ls = '--', alpha = .6 )\n\n legend = plt.legend( title = legend_title,\n ncol = 2,\n loc = legend_loc,\n fontsize = 14)\n plt.setp(legend.get_title(),fontsize=14)\n\n for ex in shade_exons:\n plt.axvspan( bcs_tbl.index.get_loc( ex[0] ) - .5,\n bcs_tbl.index.get_loc( ex[1] ) + .5,\n facecolor = 'gray',\n alpha = 0.15)\n\n if invert_x:\n plt.gca().invert_xaxis()\n\n if scale_bar:\n ax = plt.gca()\n trans = tfrms.blended_transform_factory( ax.transData, ax.transAxes )\n plt.errorbar( tick_spacing, 0.96, xerr=tick_spacing/2, color='black', capsize=3, transform=trans)\n plt.text( tick_spacing, 0.94, str( tick_spacing )+' bases', horizontalalignment='center',\n verticalalignment='top', transform=trans, fontsize = 14 )\n\n if tight:\n plt.tight_layout()\n\n plt.show()\n\ndef PlotBCsByPos(vardf,\n vec_corange_cloned,\n vec_corange_exons,\n cdna_corange_exons,\n shade_exons,\n gene_name,\n y_ax_lim=None,\n fig_size = (20,7) ):\n\n tbv=vardf.copy()\n\n tbv.sort_values(by=['pos'],inplace=True)\n bcs_tbl=tbv.pivot(index='pos',columns='alt',values='n_bc_passfilt')\n bcs_tbl['hgvs_pos'] = cds.pos_to_hgvspos( bcs_tbl.index,\n vec_corange_cloned,\n vec_corange_exons,\n cdna_corange_exons\n )\n\n #check if plot will lose bars due to not enough space for all the pixels\n dpi = 100\n if ( bcs_tbl.shape[0]1.5 ) > ( fig_size[0]dpi ):\n fig_height = fig_size[1]\n fig_size = ( ( bcs_tbl.shape[0]1.5 / dpi ), fig_height )\n print('Adjusting figure width to accomodate all pixels...')\n\n bcs_tbl.loc[:,['A','C', 'G', 'T']].plot.bar( stacked = True,\n color = [ '#C00001', '#00AD4F', '#FFCF07', '#002966' ],\n figsize = fig_size )\n\n plt.title(\n 'Number of Distinct Barcodes Present by Position for Single Nucleotide Variants in $\\it{%s}$'%gene_name,\n fontsize=24)\n\n if y_ax_lim:\n plt.ylim(0,y_ax_lim)\n\n plt.ylabel('Number of Distinct Barcodes',fontsize=22)\n plt.yticks(fontsize=18)\n\n plt.xlabel('cDNA Position',fontsize=22)\n plt.xticks( [idx for idx,p in enumerate(bcs_tbl.index) if idx%10==0],\n [c for idx,c in enumerate(bcs_tbl.hgvs_pos) if idx%10==0],\n fontsize=18,\n rotation='vertical' )\n\n legend = plt.legend(title='Nucleotide Substitution from WT',\n ncol=2,\n loc='upper left',\n fontsize=14)\n plt.setp(legend.get_title(),fontsize=14)\n\n for ex in shade_exons:\n plt.axvspan(bcs_tbl.index.get_loc(ex[0])-.5,\n bcs_tbl.index.get_loc(ex[1])+.5,\n facecolor='gray',\n alpha=0.15)\n\n plt.tight_layout()\n plt.show()\n\n #counts entries that are missing - one is missing per position as its reference\n missing = sum( bcs_tbl.isnull().sum() ) - bcs_tbl.shape[0]\n #counts number of entries with 0 barcodes passing the filter\n zero = 4bcs_tbl.shape[0] - sum( bcs_tbl[[ 'A', 'C', 'G', 'T' ]].astype( bool ).sum() )\n print( 100 * ( 1- ( ( missing + zero ) / (3bcs_tbl.shape[0] ) ) ), '% of all possible mutations present' )\n\ndef plot_corr_waterfalls(benchmark_df,\n compare_df_long,\n corr_col,\n benchmark_samp_name,\n merge_idx = ['chrom','pos','ref','alt','varlist'],\n sample_col = 'sample'):\n\n rank_df = benchmark_df.copy()[ merge_idx + [corr_col] ]\n rank_df[ corr_col+'_rank' ] = np.argsort( np.argsort( np.array( -rank_df[ corr_col ] ) ) )\n rank_df = rank_df.set_index( merge_idx )\n\n compare_df = compare_df_long.copy().set_index( merge_idx )\n\n merge_df = compare_df.merge( rank_df[ corr_col+'_rank' ], left_index=True, right_index=True )\n\n for samp in list( set( merge_df[ sample_col ] ) ):\n print(samp)\n plt.scatter(merge_df.query('sample == \"%s\"' %samp)[ corr_col+'_rank' ],\n merge_df.query('sample == \"%s\"' %samp)[ corr_col ],\n s=5)\n\n plt.ylabel(samp + ' ' + corr_col)\n plt.xlabel( benchmark_samp_name + ' ' + corr_col + ' rank')\n plt.show()\n\ndef barplot_allisos( allisos_df,\n isoform_df,\n psi_cols,\n stat,\n title = ''):\n\n plot_df = allisos_df.copy()\n iso_df = isoform_df.copy()\n\n if stat == 'max':\n plot_df[ psi_cols ].max().plot( kind = 'bar',\n figsize = ( 40, 5 ),\n title = title,\n ylim = ( 0, 1 ) )\n\n if stat == 'min':\n plot_df[ psi_cols ].min().plot( kind = 'bar',\n figsize = ( 40, 5 ),\n title = title,\n ylim = ( 0, 1 ) )\n\n if stat == 'mean':\n plot_df[ psi_cols ].mean().plot( kind = 'bar',\n figsize = ( 40, 5 ),\n title = title,\n ylim = ( 0, 1 ) )\n\n loc, labels = plt.xticks()\n\n plt.xticks( loc,\n iso_df.loc[ [ iso.split('_')[1] for iso in psi_cols ] ].isoform.tolist(),\\\n fontsize=14,\n rotation='vertical' )\n\nplt.show()\n\ndef barplot_across_samples( byvartbl_long,\n bar_col,\n y_scale = None,\n y_label = None,\n title = '',\n y_lim = None,\n color_col = None,\n color_dict = None):\n\n tbv = byvartbl_long.copy()\n\n assert ( color_col and color_dict ) or not( color_col or color_dict ), \\\n \"color_col and color_dict must either both be none or both entered\"\n\n if color_col:\n tbv.set_index('sample')[ bar_col ].plot.bar( color=[ color_dict[i] for i in tbv[ color_col ] ] )\n else:\n tbv.set_index('sample')[ bar_col ].plot.bar()\n\n if y_label:\n plt.ylabel( y_label )\n\n if y_lim:\n plt.ylim( y_lim )\n\n if y_scale:\n plt.yscale( y_scale )\n\n plt.title( title )\n\n plt.show()\n\ndef per_sdv_by_thresh( byvartbl,\n sdv_col,\n thresh_range = None,\n abs_vals = True,\n num_pts = 20,\n title = '',\n y_lim = None,\n vlines = ( 1.96, 3 ),\n fig_size = ( 12, 9.5 ) ):\n\n tbv = byvartbl.loc[ byvartbl.n_bc_passfilt > 0 ].copy()\n\n samp = 'sample' in tbv.columns\n\n if thresh_range:\n thresh = np.arange( thresh_range[0],\n thresh_range[1],\n ( thresh_range[1] - thresh_range[0] ) / num_pts )\n else:\n min_thresh = 0 if tbv[ sdv_col ].min() <= 0 else tbv[ sdv_col ].min()\n thresh = np.arange( min_thresh,\n tbv[ sdv_col ].max(),\n ( tbv[ sdv_col ].max() - min_thresh ) / num_pts )\n\n #add vline points into array while maintaining sort order\n for pt in vlines:\n thresh = np.insert( thresh, thresh.searchsorted( float( pt ) ), float( pt ) )\n\n plt.figure( figsize = fig_size )\n\n if samp:\n for smpl in set( tbv['sample'] ):\n sdv_per = []\n for t in thresh:\n tbv_samp = tbv.query( 'sample == \"%s\"' % smpl ).copy()\n tbv_samp = pp.sdvs( tbv_samp, sdv_col, t, abs_vals = abs_vals )\n sdv_per.append( 100( tbv_samp.sdv.sum() / tbv_samp.shape[0] ) )\n\n plt.plot( thresh, sdv_per, label = smpl )\n\n print( smpl )\n for pt in vlines:\n per = sdv_per[ np.where( thresh == pt )[0][0] ]\n print( 'At a threshold of %.2f, %.2f%% of variants are splice disrupting.' % ( pt, per ) )\n\n plt.legend()\n\n else:\n sdv_per = []\n for t in thresh:\n tbv = pp.sdvs( tbv.query( 'sample == \"%s\"' % smpl ), sdv_col, t, abs_vals = abs_vals )\n sdv_per.append( 100( tbv.sdv.sum() / tbv.shape[0] ) )\n\n plt.plot( thresh, sdv_per, label = smpl )\n\n for pt in vlines:\n per = sdv_per[ np.where( thresh == pt ) ]\n print( 'At a threshold of %.2f, %.2f%% of variants are splice disrupting.' % ( pt, per ) )\n\n for pt in vlines:\n plt.axvline( x = pt, color = 'gray', linestyle = '--' )\n\n if y_lim:\n plt.ylim( y_lim )\n else:\n plt.ylim( ( 0, 100 ) )\n\n plt.ylabel( 'Percentage splice disrupting variants' )\n plt.xlabel( sdv_col + ' threshold' )\n\n plt.title( title )\n\n plt.show()\n\ndef per_repeat_sdv( byvartbl,\n sdv_col = None,\n thresh = None,\n abs_vals = True,\n title = '',\n y_lim = None, ):\n\n tbv = byvartbl.loc[ byvartbl.n_bc_passfilt > 0 ].copy()\n\n n_var = len( set( tbv.varlist ) )\n\n assert ( sdv_col and thresh ) or ( 'sdv' in tbv.columns ), \\\n 'Please specify a column and threshold to determine splice disrupting variants'\n\n if ( sdv_col and thresh ):\n tbv = pp.sdvs( tbv, sdv_col, thresh, abs_vals = abs_vals )\n\n n_samp = len( set( tbv[ 'sample' ] ) )\n\n assert n_samp > 1, 'Please provide a dataset with more than one sample'\n\n sdvs = tbv.loc[ tbv.sdv ]\n\n #this gets you a counter { n_samples: n_sdvs }\n repeat_counts = Counter( Counter( sdvs.varlist ).values() )\n\n n_sdvs = sum( repeat_counts.values() )\n\n print( '%i of %i variants (%.2f%%) are splice disrupting in at least one sample.' \\\n % ( n_sdvs, n_var, 100( n_sdvs / n_var ) ) )\n\n #adds zero counts to create plot with full range of possible values\n for i in range( 1, n_samp + 1 ):\n if i not in repeat_counts:\n repeat_counts[ i ] = 0\n\n print( '%i of %i variants (%.2f%%) are splice disrupting in all samples.' \\\n % ( repeat_counts[ n_samp ], n_var, 100( repeat_counts[ n_samp ] / n_var ) ) )\n\n #gives us a list sorted by n_samples in ascending order\n repeat_counts = sorted( repeat_counts.items() )\n\n labels, counts = zip( repeat_counts )\n\n per = [ 100( count / n_sdvs ) for count in counts ]\n\n indexes = np.arange( n_samp )\n\n plt.bar( indexes, per )\n\n plt.xticks(indexes, labels)\n\n if y_lim:\n plt.ylim( y_lim )\n else:\n plt.ylim( ( 0, 100 ) )\n\n plt.ylabel( 'Percent of splice disrupting variants' )\n plt.xlabel( 'Number of samples' )\n\n plt.title( title )\n\n plt.show()\n\ndef plot_stacked_psi( var_df,\n zcols,\n pos_col,\n colors,\n color_col = 'alt',\n fig_size = ( 20, 5 ),\n shade_exons = False,\n zoom=None,\n tick_spacing = 10,\n alt_labels = False,\n bar_labels = False,\n title = '',\n y_ax_title='',\n y_ax_lim = None,\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n rev_trans = False,\n hlines = None,\n savefile = None ):\n\n tbv = var_df.sort_values( by = [ 'pos', 'alt' ] ).copy()\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n tbv_filt = tbv.set_index( 'pos' ).loc[ zoom[0]:zoom[1] ].reset_index()\n else:\n tbv_filt = tbv\n\n #check if plot will lose bars due to not enough space for all the pixels\n dpi = 100\n if ( tbv_filt.shape[0]1.5 ) > ( fig_size[0]dpi ):\n fig_height = fig_size[1]\n fig_size = ( ( tbv_filt.shape[0]1.5 / dpi ), fig_height )\n print('Adjusting figure width to accomodate all pixels...')\n\n if print_ex_count:\n print('This figure shows %i exonic bases.' % sum( c[1]-c[0] for c in shade_exons ) )\n\n col_pivot = tbv_filt.set_index( ['pos', 'alt'] )[ zcols ]\n\n col_pivot.plot.bar( color = colors,\n stacked = True,\n align = 'center',\n width = 1,\n figsize = fig_size )\n\n ax = plt.gca()\n\n if alt_labels or bar_labels:\n\n rects = ax.patches\n\n heights = [ rect.get_height() for rect in rects ]\n\n n_bars = int( len( heights ) / len( zcols ) )\n\n pos_ht_sum = [ sum( heights[ i ] for i in range( j, len( heights ), n_bars ) if heights[ i ] > 0 )\n for j in range( n_bars ) ]\n neg_ht_sum = [ sum( heights[ i ] for i in range( j, len( heights ), n_bars ) if heights[ i ] < 0 )\n for j in range( n_bars ) ]\n\n if alt_labels:\n\n labels = [ idx[1] for idx in col_pivot.index ]\n\n min_ht = min( neg_ht_sum )\n\n for rect, label in zip( rects, labels ):\n height = rect.get_height()\n ax.text( rect.get_x() + rect.get_width() / 2,\n min_ht - 1.5,\n label,\n fontsize = 14,\n fontweight = 'bold',\n ha='center',\n va='bottom' )\n\n if bar_labels:\n\n for iidx, colmark in enumerate( bar_labels ):\n\n col, marker = colmark\n\n #true false vector for where to put the marker\n locs = tbv_filt[ col ]\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc:\n\n ax.text( rect.get_x() + rect.get_width() /2,\n pos_ht_sum[ jidx ] + .1 + .9iidx,\n marker,\n fontsize = 10,\n ha = 'center',\n va = 'bottom' )\n\n plt.title( title, fontsize = 24 )\n\n if not( y_ax_lim ) and ( bar_labels or alt_labels ):\n\n col_pivot[ 'y_max' ] = col_pivot[ col_pivot > 0 ].sum( axis = 1 )\n col_pivot[ 'y_min' ] = col_pivot[ col_pivot < 0 ].sum( axis = 1 )\n\n if bar_labels and alt_labels:\n y_ax_lim = ( col_pivot.y_min.min() - 1.6,\n col_pivot.y_max.max() + .1 + .9len( bar_labels ) )\n elif bar_labels:\n y_ax_lim = ( col_pivot.y_min.min()1.01,\n col_pivot.y_max.max() + .1 + .9len( bar_labels ) )\n else:\n y_ax_lim = ( col_pivot.y_min.min() - 1.6,\n col_pivot.y_max.max()1.01 )\n\n if y_ax_lim:\n plt.ylim( y_ax_lim )\n\n plt.ylabel( y_ax_title, fontsize = 22 )\n plt.yticks( fontsize = 18 )\n\n plt.xlabel( x_ax_title, fontsize = 22 )\n plt.xticks( [ idx for idx,p in enumerate( tbv_filt.index ) if idx%( 3tick_spacing ) == 1 ],\n [ c for idx,c in enumerate( tbv_filt[ pos_col ] ) if idx%( 3tick_spacing ) == 1 ],\n fontsize=18,\n rotation='vertical' )\n\n if hlines:\n for line in hlines:\n plt.axhline( line, c = 'black', ls = '--', alpha = .6 )\n\n if legend:\n\n if legend_labels:\n legend = plt.legend( title = legend_title,\n ncol = 2,\n loc = legend_loc,\n labels = legend_labels,\n fontsize = 14 )\n else:\n legend = plt.legend( title = legend_title,\n ncol = 2,\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n ax.legend_ = None\n plt.draw()\n\n if shade_exons:\n for ex in shade_exons:\n plt.axvspan( col_pivot.index.get_loc( ex[0] ).start - .5,\n col_pivot.index.get_loc( ex[1] ).stop,\n facecolor = 'gray',\n alpha = 0.15 )\n\n if scale_bar:\n trans = tfrms.blended_transform_factory( ax.transData, ax.transAxes )\n plt.errorbar( 3tick_spacing, 0.96, xerr = ( 3tick_spacing / 2 ), color='black', capsize=3, transform=trans)\n txt = str( tick_spacing ) + ' bases' if tick_spacing > 1 else str( tick_spacing ) + ' base'\n plt.text( 3tick_spacing, 0.94, txt, horizontalalignment='center',\n verticalalignment='top', transform=trans, fontsize = 14 )\n\n if tight:\n plt.tight_layout()\n\n if savefile:\n plt.savefig( savefile )\n\n plt.show()\n\ndef subplot_psi_by_alt( var_df,\n y_col,\n pos_col,\n colors,\n color_col = 'alt',\n edge_col = None,\n ax = None,\n shade_by_base = False,\n shade_exons = False,\n tick_spacing = 10,\n bar_labels = False,\n bar_label_loc = 'middle',\n darken_bars = None,\n darken_edges = None,\n labels_legend = False,\n labels_legend_title = '',\n labels_legend_loc = 'best',\n wt_labels = False,\n title = '',\n y_ax_lim = None,\n y_ax_title='',\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n scale_bar_loc = 'left',\n rev_trans = False,\n hlines = None ):\n\n tbv = var_df.copy()\n\n if print_ex_count:\n print('This figure shows %i exonic bases.' % sum( c[1]-c[0] for c in shade_exons ) )\n\n if ax:\n ax = ax\n else:\n ax = plt.gca()\n\n col_pivot = tbv.pivot( index = [ 'pos', 'ref', pos_col ], columns = color_col, values = y_col )\n #col_pivot = tbv.pivot( index = [ 'pos', 'ref', pos_col ], columns = 'alt', values = y_col )\n\n col_pivot.plot.bar( ax = ax,\n color = colors,\n edgecolor = edge_col,\n align = 'center',\n width = 1,\n )\n\n if bar_labels or wt_labels or shade_by_base or darken_bars or darken_edges:\n\n rects = ax.patches\n\n heights = [ rect.get_height() for rect in rects ]\n neg_ht = [ h for h in heights if h < 0 ]\n\n if bar_label_loc == 'above':\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transAxes )\n elif bar_label_loc == 'middle':\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transData )\n\n if darken_bars:\n\n column, colors = darken_bars\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = 'alt', values = column )\n\n #bars are ordered with all A's first then all C's... this creates a colors vector to match that pattern\n colors_vec = [ c for c in colors for i in range( _locs.shape[0] ) ]\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc and not np.isnan( loc ):\n\n color = colors_vec[ jidx ]\n\n rect.set_facecolor( color )\n\n if darken_edges:\n\n column, color = darken_edges\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = 'alt', values = column )\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc and not np.isnan( loc ):\n\n rect.set_edgecolor( color )\n\n if wt_labels:\n\n labels = col_pivot.index.get_level_values( 'ref' )\n\n min_ht = min( neg_ht ) if len( neg_ht ) > 0 else 0\n neg_ht_mean = np.mean( neg_ht ) if len( neg_ht ) > 0 else -4\n\n #the way I'm messing with rects should get the label in the middle of the four bars for the pos\n for rect, label in zip( rects[ 2len( labels ): ], labels ):\n ax.text( rect.get_x(),\n min_ht + 4neg_ht_mean,\n label,\n fontsize = 18,\n fontweight = 'bold',\n ha='center',\n va='bottom' )\n\n if bar_labels:\n\n if bar_label_loc == 'middle':\n\n max_rect_ht = y_ax_lim[ 1 ] if y_ax_lim else ax.get_ylim()[ 1 ]\n\n mid_rect_ht = max_rect_ht / 2\n\n mid_label = int( len( bar_labels ) / 2 )\n\n #sets up constant y label positions\n #first label is the lowest and they are centered in the middle of the positive y axis\n label_pos = [ mid_rect_ht + ( i - ( mid_label ) ).2max_rect_ht for i in range( len( bar_labels ) ) ]\n\n elif bar_label_loc == 'above':\n\n label_pos = [ 1 + .1i for i in range( len( bar_labels ) ) ]\n\n for iidx, colmark in enumerate( bar_labels ):\n\n col, marker, _label, fsize = colmark\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = color_col, values = col )\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc and not np.isnan( loc ):\n\n ax.text( rect.get_x() + rect.get_width() / 2,\n label_pos[ iidx ],\n marker,\n fontsize = fsize,\n transform = trans,\n ha = 'center',\n va = 'bottom' )\n\n plt.title( title, fontsize = 24 )\n\n ax.set_ylabel( y_ax_title, fontsize = 18 )\n ax.tick_params( axis = 'y', which='major', labelsize = 24 )\n\n plt.xlabel( x_ax_title, fontsize = 22 )\n plt.xticks( [ idx for idx,p in enumerate( col_pivot.index.get_level_values( 'pos' ) ) if idx%( tick_spacing ) == 0 ],\n [ c for idx,c in enumerate( col_pivot.index.get_level_values( pos_col ) ) if idx%( tick_spacing ) == 0 ],\n fontsize=18,\n rotation='vertical' )\n\n if hlines:\n for line in hlines:\n plt.axhline( line, c = 'black', ls = '--', alpha = .6 )\n\n if shade_by_base:\n\n for i in range( len( set( tbv.pos ) ) ):\n\n #shade only every other position\n if i % 2 == 0:\n\n rect = rects[ i ]\n\n #this plot has four bases at every position\n ax.axvspan( rect.get_x(),\n rect.get_x() + 4rect.get_width(),\n facecolor = 'gray',\n alpha = 0.15 )\n\n if shade_exons:\n\n for ex in shade_exons:\n\n plt.axvspan( col_pivot.index.get_loc( ex[0] ).start - .5,\n col_pivot.index.get_loc( ex[1] ).stop - .5,\n facecolor = 'gray',\n alpha = 0.15 )\n\n if scale_bar:\n\n assert scale_bar_loc.lower() in [ 'left', 'middle', 'right' ], \\\n 'Scale bar location can be \"left\", \"middle\", or \"right\".'\n\n if scale_bar_loc == 'left':\n x_loc = 3tick_spacing\n elif scale_bar_loc == 'middle':\n x_loc = tbv.shape[0] / 2\n else:\n x_loc = tbv.shape[0] - 3tick_spacing\n\n trans = tfrms.blended_transform_factory( ax.transData, ax.transAxes )\n ax.errorbar( x_loc,\n 0.92,\n xerr = ( tick_spacing / 2 ),\n color = 'black',\n capsize=3,\n transform=trans )\n\n txt = str( tick_spacing ) + ' bases' if tick_spacing > 1 else str( tick_spacing ) + ' base'\n plt.text( x_loc,\n 0.90,\n txt,\n horizontalalignment = 'center',\n verticalalignment = 'top',\n transform = trans,\n fontsize = 14 )\n\n if legend:\n\n if legend_labels:\n legend = ax.legend( title = legend_title,\n ncol = 2,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n labels = legend_labels,\n fontsize = 14 )\n else:\n legend = ax.legend( title = legend_title,\n ncol = 2,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n elif labels_legend:\n\n fake_handles = [ plt.Rectangle( (0, 0), 0, 0, fill=False, edgecolor='none', visible = 'False')\n for i in range( len( bar_labels ) ) ]\n\n legend = ax.legend( handles = fake_handles,\n title = labels_legend_title,\n bbox_to_anchor = ( 0, 1 ), #if you turn that on you can put legend outside of plot\n loc = labels_legend_loc,\n labels = ( symbol + ' '6 + label for _col, symbol, label, _fsize in bar_labels ),\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n ax.legend_ = None\n plt.draw()\n\n if tight:\n plt.tight_layout()\n\n return ax\n\ndef subplots_wrapper( var_df,\n y_cols,\n pos_col,\n colors,\n fig_size = ( 30, 10 ),\n share_x = True,\n share_y = True,\n color_col = 'alt',\n edge_col = None,\n shade_by_base = False,\n shade_exons = False,\n zoom=None,\n tick_spacing = 10,\n wt_labels = False,\n bar_labels = False,\n bar_label_loc = 'middle',\n darken_bars = None,\n darken_edges = None,\n labels_legend = False,\n labels_legend_title = '',\n labels_legend_loc = 'best',\n title = '',\n y_ax_title='',\n y_ax_lim = None,\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n scale_bar_loc = 'left',\n rev_trans = False,\n hlines = None,\n savefile = None,\n ):\n\n tbv = var_df.sort_values( by = [ 'pos', 'alt' ] ).copy()\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n tbv_filt = tbv.set_index( 'pos' ).loc[ zoom[0]:zoom[1] ].reset_index()\n else:\n tbv_filt = tbv\n\n fig, axes = plt.subplots( len( y_cols),\n sharex = share_x,\n sharey = share_y,\n figsize = fig_size )\n\n if len( y_cols ) == 1:\n axes = [ axes ]\n\n if bar_label_loc == 'above':\n all_bar_labels = False\n elif bar_label_loc == 'middle':\n all_bar_labels = bar_labels\n\n #this whole loop is basically to give each its own y axis labels\n #and to only have the legend & scale bar on the top plot\n #and to only have wt labels on the bottom plot\n for idx, col in enumerate( y_cols ):\n\n if idx == 0 and len( y_cols ) > 1:\n subplot_psi_by_alt( tbv_filt,\n col,\n pos_col,\n colors,\n ax = axes[ idx ],\n color_col = color_col,\n edge_col = edge_col,\n shade_by_base = shade_by_base,\n shade_exons = shade_exons,\n tick_spacing = tick_spacing,\n bar_labels = bar_labels,\n bar_label_loc = bar_label_loc,\n darken_bars = darken_bars,\n darken_edges = darken_edges,\n labels_legend = labels_legend,\n labels_legend_title = labels_legend_title,\n labels_legend_loc = labels_legend_loc,\n title = title,\n y_ax_lim = y_ax_lim,\n y_ax_title = y_ax_title[ idx ],\n legend = legend,\n legend_title = legend_title,\n legend_loc = legend_loc,\n legend_labels = legend_labels,\n tight = tight,\n print_ex_count = print_ex_count,\n scale_bar = scale_bar,\n scale_bar_loc = scale_bar_loc,\n rev_trans = rev_trans,\n hlines = hlines, )\n elif idx == ( len( y_cols ) - 1 ):\n subplot_psi_by_alt( tbv_filt,\n col,\n pos_col,\n colors,\n ax = axes[ idx ],\n color_col = color_col,\n edge_col = edge_col,\n shade_by_base = shade_by_base,\n shade_exons = shade_exons,\n tick_spacing = tick_spacing,\n bar_labels = all_bar_labels,\n darken_bars = darken_bars,\n darken_edges = darken_edges,\n wt_labels = wt_labels,\n legend = False,\n y_ax_lim = y_ax_lim,\n y_ax_title = y_ax_title[ idx ],\n tight = tight,\n rev_trans = rev_trans,\n hlines = hlines,\n x_ax_title = x_ax_title, )\n else:\n subplot_psi_by_alt( tbv_filt,\n col,\n pos_col,\n colors,\n ax = axes[ idx ],\n color_col = color_col,\n edge_col = edge_col,\n shade_by_base = shade_by_base,\n shade_exons = shade_exons,\n tick_spacing = tick_spacing,\n bar_labels = all_bar_labels,\n darken_bars = darken_bars,\n darken_edges = darken_edges,\n y_ax_lim = y_ax_lim,\n legend = False,\n y_ax_title = y_ax_title[ idx ],\n tight = tight,\n rev_trans = rev_trans,\n hlines = hlines, )\n\n if wt_labels:\n\n ht_max = tbv_filt[ y_cols ].max().max()\n ht_min = tbv_filt[ y_cols ].min().min()\n\n y_max = y_ax_lim[ 1 ] if y_ax_lim else 1.01ht_max\n y_min = ht_min + ht_min if ht_min < 0 else -20\n y_ax_lim = ( y_min,\n y_max )\n\n if y_ax_lim:\n plt.ylim( y_ax_lim )\n\n if savefile:\n plt.savefig( savefile,\n dpi = 300,\n bbox_inches = 'tight' )\n\n plt.show()\n\ndef pr_curves( var_df,\n truth_col,\n pred_cols,\n colors,\n fig_size = ( 5, 5 ),\n grid = False,\n x_ax_label = 'Recall\\n(%)',\n y_ax_label = 'Precision\\n(%)',\n add_point = False,\n savefile = None,\n *kwargs\n ):\n\n #pr curve function hates missing values\n tbv = var_df.dropna(subset = [ truth_col ] ).copy()\n\n if tbv.shape[ 0 ] != var_df.shape[ 0 ]:\n print( 'Missing values in truth column.', str( var_df.shape[ 0 ] - tbv.shape[ 0 ] ), 'rows removed.' )\n\n plt.figure( figsize = fig_size )\n\n for column, color in zip( pred_cols, colors ):\n\n col_df = tbv.dropna( subset = [ column ] ).copy()\n\n if tbv.shape[ 0 ] != col_df.shape[ 0 ]:\n print( 'Missing values in', column, 'column.', \\\n str( tbv.shape[ 0 ] - col_df.shape[ 0 ] ), 'rows removed.' )\n\n precision, recall, _ = precision_recall_curve( col_df[ truth_col ],\n col_df[ column ] )\n\n plt.plot( 100recall,\n 100precision,\n color = color,\n kwargs )\n\n print( column, auc( recall, precision ) )\n\n if add_point:\n plt.plot( add_point[ 0 ],\n add_point[ 1 ],\n color = 'black',\n marker = add_point[ 2 ],\n markersize = add_point[ 3 ]\n )\n\n plt.xlabel( x_ax_label, fontsize = 24 )\n plt.xticks( fontsize = 20 )\n\n plt.ylabel( y_ax_label, fontsize = 24 )\n plt.yticks( fontsize = 20 )\n\n plt.grid( grid )\n\n if savefile:\n plt.savefig( savefile,\n dpi = 300,\n bbox_inches = 'tight' )\n\n plt.show()\n\ndef plot_RBP_chg( var_df,\n y_col,\n x_col,\n arrow_col,\n colors,\n color_col = 'alt',\n arrow_filt = None,\n ax = None,\n title = '',\n y_ax_lim = None,\n x_ax_lim = None,\n y_ax_title='',\n x_ax_title = '',\n marker_col = None,\n marker = 'o',\n kwargs ):\n\n tbv = var_df.copy()\n\n if ax:\n ax = ax\n else:\n ax = plt.gca()\n\n if not marker_col:\n\n ax.scatter( tbv[ x_col ],\n tbv[ y_col ],\n color = tbv[ color_col ],\n kwargs\n )\n\n else:\n\n for m, v in marker.items():\n\n tbv_filt = tbv.loc[ tbv[ marker_col ] == v[ 0 ] ]\n\n ax.scatter( tbv_filt[ x_col ],\n tbv_filt[ y_col ],\n color = tbv_filt[ color_col ],\n marker = m,\n s = v[ 1 ],\n kwargs\n )\n\n arrow_x_start = tbv[ x_col ].values\n arrow_y_start = tbv[ y_col ].values\n arrow_len = tbv[ arrow_col ].values\n\n #add arrows to plot\n for i, alt in enumerate( tbv.alt ):\n\n if arrow_filt and arrow_x_start[ i ] < arrow_filt:\n continue\n\n ax.arrow( arrow_x_start[ i ],\n arrow_y_start[ i ],\n 0, #change in x\n arrow_len[ i ], #change in y\n head_width = 0.3( np.abs( arrow_len[ i ] ) / 2 ), #arrow head width\n head_length = 0.1( np.abs( arrow_len[ i ] ) / 2 ), #arrow head length\n width = 0.03, #arrow stem width\n fc = colors[ alt ], #arrow fill color\n ec = colors[ alt ]\n ) #arrow edge color\n\n plt.title( title, fontsize = 24 )\n\n ax.set_xlabel( x_ax_title, fontsize = 18 )\n ax.tick_params( axis = 'x', which='major', labelsize = 12 )\n\n ax.set_ylabel( y_ax_title, fontsize = 18 )\n ax.tick_params( axis = 'y', which='major', labelsize = 12 )\n\n if x_ax_lim:\n ax.set_xlim( x_ax_lim )\n\n if y_ax_lim:\n ax.set_ylim( y_ax_lim )\n\n plt.show()\n\ndef subplot_psi_wt( var_df,\n y_col,\n pos_col,\n colors,\n color_col = 'ref',\n edge_col = None,\n ax = None,\n zoom = None,\n shade_exons = False,\n tick_spacing = 10,\n title = '',\n y_ax_lim = None,\n y_ax_title='',\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n scale_bar_loc = 'left',\n rev_trans = False,\n hlines = None,\n snap = False):\n\n tbv = var_df.copy()\n\n if print_ex_count:\n print('This figure shows %i exonic bases.' % sum( c[1]-c[0] for c in shade_exons ) )\n\n if ax:\n ax = ax\n else:\n ax = plt.gca()\n\n d2c = dict( zip( [ 'A', 'C', 'G', 'T' ], colors) )\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n tbv = tbv.set_index( 'pos' ).loc[ zoom[0]:zoom[1] ].reset_index()\n\n tbv.plot.bar( x = 'pos',\n y = y_col,\n ax = ax,\n color = map( d2c.get, tbv[ color_col ] ),\n edgecolor = edge_col,\n align = 'center',\n width = 1,\n )\n\n plt.title( title, fontsize = 24 )\n\n ax.set_ylabel( y_ax_title, fontsize = 18 )\n ax.tick_params( axis = 'y', which='major', labelsize = 36 )\n\n plt.xlabel( x_ax_title, fontsize = 36 )\n plt.xticks( [ idx for idx,p in enumerate( tbv.pos ) if idx%( tick_spacing ) == 0 ],\n [ c for idx,c in enumerate( tbv[ pos_col ] ) if idx%( tick_spacing ) == 0 ],\n fontsize=36,\n rotation='vertical' )\n\n if hlines:\n for line in hlines:\n x_cds, col, style, lw = line\n ax.axhline( x_cds, c = col, ls = style, linewidth = lw, alpha = .6 )\n\n if shade_exons:\n\n for ex in shade_exons:\n\n plt.axvspan( col_pivot.index.get_loc( ex[0] ).start - .5,\n col_pivot.index.get_loc( ex[1] ).stop,\n facecolor = 'gray',\n alpha = 0.15 )\n\n if scale_bar:\n\n assert scale_bar_loc.lower() in [ 'left', 'middle', 'right' ], \\\n 'Scale bar location can be \"left\", \"middle\", or \"right\".'\n\n if scale_bar_loc == 'left':\n x_loc = 3tick_spacing\n elif scale_bar_loc == 'middle':\n x_loc = tbv.shape[0] / 2\n else:\n x_loc = tbv.shape[0] - 3tick_spacing\n\n trans = tfrms.blended_transform_factory( ax.transData, ax.transAxes )\n ax.errorbar( x_loc,\n 0.92,\n xerr = ( tick_spacing / 2 ),\n color = 'black',\n capsize=3,\n transform=trans )\n\n txt = str( tick_spacing ) + ' bases' if tick_spacing > 1 else str( tick_spacing ) + ' base'\n plt.text( x_loc,\n 0.90,\n txt,\n horizontalalignment = 'center',\n verticalalignment = 'top',\n transform = trans,\n fontsize = 14 )\n\n if legend:\n\n legend = ax.legend( title = legend_title,\n ncol = 2,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n ax.legend_ = None\n plt.draw()\n\n if y_ax_lim:\n ax.set_ylim( y_ax_lim )\n\n art.set_snap( ax, snap )\n\n if tight:\n plt.tight_layout()\n\n return ax\n\ndef subplot_psi_by_alt( var_df,\n y_col,\n pos_col,\n colors,\n color_col = 'alt',\n edge_col = None,\n ax = None,\n shade_by_base = False,\n shade_exons = False,\n tick_spacing = 10,\n bar_labels = False,\n bar_label_loc = 'middle',\n bar_labels_offset = True,\n darken_bars = None,\n darken_bars2 = None,\n darken_edges = None,\n labels_legend = False,\n labels_legend_title = '',\n labels_legend_loc = 'best',\n wt_labels = False,\n title = '',\n y_ax_lim = None,\n y_ax_title='',\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n scale_bar_loc = 'left',\n rev_trans = False,\n hlines = None,\n snap = False ):\n\n tbv = var_df.copy()\n\n if print_ex_count:\n print('This figure shows %i exonic bases.' % sum( c[1]-c[0] for c in shade_exons ) )\n\n if ax:\n ax = ax\n else:\n ax = plt.gca()\n\n\n col_pivot = tbv.pivot( index = [ 'pos', 'ref', pos_col ], columns = 'alt', values = y_col )\n\n col_pivot.plot.bar( ax = ax,\n color = colors,\n edgecolor = edge_col,\n align = 'center',\n width = 1,\n )\n\n if bar_labels or wt_labels or shade_by_base or darken_bars or darken_edges:\n\n rects = ax.patches\n\n heights = [ rect.get_height() for rect in rects ]\n neg_ht = [ h for h in heights if h < 0 ]\n\n if bar_label_loc == 'above':\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transAxes )\n elif bar_label_loc == 'middle':\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transData )\n\n if darken_bars2:\n\n column, colors = darken_bars2\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = 'alt', values = column )\n\n #bars are ordered with all A's first then all C's... this creates a colors vector to match that pattern\n colors_vec = [ c for c in colors for i in range( _locs.shape[0] ) ]\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc and not np.isnan( loc ):\n\n color = colors_vec[ jidx ]\n\n rect.set_facecolor( color )\n\n if darken_bars:\n\n column, colors = darken_bars\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = 'alt', values = column )\n\n #bars are ordered with all A's first then all C's... this creates a colors vector to match that pattern\n colors_vec = [ c for c in colors for i in range( _locs.shape[0] ) ]\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc and not np.isnan( loc ):\n\n color = colors_vec[ jidx ]\n\n rect.set_facecolor( color )\n\n if darken_edges:\n\n column, color = darken_edges\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = 'alt', values = column )\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc and not np.isnan( loc ):\n\n rect.set_edgecolor( color )\n\n if wt_labels:\n\n labels = col_pivot.index.get_level_values( 'ref' )\n\n min_ht = min( neg_ht ) if len( neg_ht ) > 0 else 0\n neg_ht_mean = np.mean( neg_ht ) if len( neg_ht ) > 0 else -4\n\n #the way I'm messing with rects should get the label in the middle of the four bars for the pos\n for rect, label in zip( rects[ 2len( labels ): ], labels ):\n ax.text( rect.get_x(),\n min_ht + 4neg_ht_mean,\n label,\n fontsize = 18,\n fontweight = 'bold',\n ha='center',\n va='bottom' )\n\n if bar_labels:\n\n if bar_labels_offset:\n\n if bar_label_loc == 'middle':\n\n max_rect_ht = y_ax_lim[ 1 ] if y_ax_lim else ax.get_ylim()[ 1 ]\n\n mid_rect_ht = max_rect_ht / 2\n\n mid_label = int( len( bar_labels ) / 2 )\n\n #sets up constant y label positions\n #first label is the lowest and they are centered in the middle of the positive y axis\n label_pos = [ mid_rect_ht + ( i - ( mid_label ) ).2max_rect_ht for i in range( len( bar_labels ) ) ]\n\n elif bar_label_loc == 'above':\n\n label_pos = [ 1 + .1i for i in range( len( bar_labels ) ) ]\n\n else:\n\n if bar_label_loc == 'middle':\n\n pos_ht_mean = np.mean( pos_ht_sum )\n\n max_rect_ht = y_ax_lim[ 1 ] if y_ax_lim else ax.get_ylim()[ 1 ]\n\n mid_rect_ht = max_rect_ht / 2\n\n #sets up constant y label positions\n #they are centered in the middle of the positive y axis\n label_pos = [ mid_rect_ht for i in range( len( bar_labels ) ) ]\n\n elif bar_label_loc == 'above':\n\n label_pos = [ .885 if marker == r\"$\\bullet$\" else 1.01 for _col, marker, _label, _fsize in bar_labels ]\n\n for iidx, colmark in enumerate( bar_labels ):\n\n col, marker, _label, fsize = colmark\n\n #true false vector for where to put the marker\n _locs = tbv.pivot( index = [ 'pos' ], columns = 'alt', values = col )\n\n locs = []\n for col in _locs.columns:\n locs.extend( _locs[ col ].tolist() )\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n xpos = rect.get_x() + rect.get_width() / 2\n\n if marker == r\"$\\bullet$\":\n xpos = .99( xpos )\n\n if loc and not np.isnan( loc ):\n\n ax.text( xpos,\n label_pos[ iidx ],\n marker,\n fontsize = fsize,\n transform = trans,\n ha = 'center',\n va = 'bottom' )\n\n plt.title( title, fontsize = 24 )\n\n ax.set_ylabel( y_ax_title, fontsize = 18 )\n ax.tick_params( axis = 'y', which='major', labelsize = 36 )\n\n plt.xlabel( x_ax_title, fontsize = 36 )\n plt.xticks( [ idx for idx,p in enumerate( col_pivot.index.get_level_values( 'pos' ) ) if idx%( tick_spacing ) == 0 ],\n [ c for idx,c in enumerate( col_pivot.index.get_level_values( pos_col ) ) if idx%( tick_spacing ) == 0 ],\n fontsize=36,\n rotation='vertical' )\n\n if hlines:\n for line in hlines:\n x_cds, col, style, lw = line\n ax.axhline( x_cds, c = col, ls = style, linewidth = lw, alpha = .6 )\n\n if shade_by_base:\n\n for i in range( len( set( tbv.pos ) ) ):\n\n #shade only every other position\n if i % 2 == 0:\n\n rect = rects[ i ]\n\n #this plot has four bases at every position\n ax.axvspan( rect.get_x(),\n rect.get_x() + 4rect.get_width(),\n facecolor = 'gray',\n alpha = 0.15 )\n\n if shade_exons:\n\n for ex in shade_exons:\n\n plt.axvspan( col_pivot.index.get_loc( ex[0] ).start - .5,\n col_pivot.index.get_loc( ex[1] ).stop,\n facecolor = 'gray',\n alpha = 0.15 )\n\n if scale_bar:\n\n assert scale_bar_loc.lower() in [ 'left', 'middle', 'right' ], \\\n 'Scale bar location can be \"left\", \"middle\", or \"right\".'\n\n if scale_bar_loc == 'left':\n x_loc = 3tick_spacing\n elif scale_bar_loc == 'middle':\n x_loc = tbv.shape[0] / 2\n else:\n x_loc = tbv.shape[0] - 3tick_spacing\n\n trans = tfrms.blended_transform_factory( ax.transData, ax.transAxes )\n ax.errorbar( x_loc,\n 0.92,\n xerr = ( tick_spacing / 2 ),\n color = 'black',\n capsize=3,\n transform=trans )\n\n txt = str( tick_spacing ) + ' bases' if tick_spacing > 1 else str( tick_spacing ) + ' base'\n plt.text( x_loc,\n 0.90,\n txt,\n horizontalalignment = 'center',\n verticalalignment = 'top',\n transform = trans,\n fontsize = 14 )\n\n if legend:\n\n if legend_labels:\n legend = ax.legend( title = legend_title,\n ncol = 2,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n labels = legend_labels,\n fontsize = 14 )\n else:\n legend = ax.legend( title = legend_title,\n ncol = 2,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n elif labels_legend:\n\n fake_handles = [ plt.Rectangle( (0, 0), 0, 0, fill=False, edgecolor='none', visible = 'False')\n for i in range( len( bar_labels ) ) ]\n\n legend = ax.legend( handles = fake_handles,\n title = labels_legend_title,\n bbox_to_anchor = ( 0, 1 ), #if you turn that on you can put legend outside of plot\n loc = labels_legend_loc,\n labels = ( symbol + ' '6 + label for _col, symbol, label, _fsize in bar_labels ),\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n ax.legend_ = None\n plt.draw()\n\n if y_ax_lim:\n ax.set_ylim( y_ax_lim )\n\n art.set_snap( ax, snap )\n\n if tight:\n plt.tight_layout()\n\n return ax\n\ndef subplots_wrapper( var_df,\n y_cols,\n pos_col,\n colors,\n fig_size = ( 30, 10 ),\n share_x = True,\n share_y = True,\n color_col = 'alt',\n edge_col = None,\n shade_by_base = False,\n shade_exons = False,\n zoom=None,\n tick_spacing = 10,\n wt_labels = False,\n bar_labels = False,\n bar_label_loc = 'middle',\n bar_labels_offset = True,\n darken_bars = None,\n darken_bars2 = None,\n darken_edges = None,\n labels_legend = False,\n labels_legend_title = '',\n labels_legend_loc = 'best',\n title = '',\n y_ax_title='',\n y_ax_lim = None,\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n scale_bar_loc = 'left',\n rev_trans = False,\n hlines = None,\n savefile = None,\n snap = False\n ):\n\n tbv = var_df.sort_values( by = [ 'pos', 'alt' ] ).copy()\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n tbv_filt = tbv.set_index( 'pos' ).loc[ zoom[0]:zoom[1] ].reset_index()\n else:\n tbv_filt = tbv\n\n fig, axes = plt.subplots( len( y_cols ),\n sharex = share_x,\n sharey = share_y,\n figsize = fig_size )\n\n if len( y_cols ) == 1:\n axes = [ axes ]\n\n if bar_label_loc == 'above':\n all_bar_labels = False\n elif bar_label_loc == 'middle':\n all_bar_labels = bar_labels\n\n if not darken_bars:\n dbar_dict = { i: None for i in range( len( y_cols) ) }\n elif len( darken_bars ) == 1:\n dbar_dict = { i: darken_bars[ 0 ] for i in range( len( y_cols) ) }\n elif len( darken_bars ) == len( y_cols ):\n dbar_dict = { i: darken_bars[ i ] for i in range( len( y_cols) ) }\n else:\n print( 'Something is wrong with how you entered the darken bars argument!' )\n\n if not darken_bars2:\n dbar2_dict = { i: None for i in range( len( y_cols) ) }\n elif len( darken_bars2 ) == 1:\n dbar2_dict = { i: darken_bars2[ 0 ] for i in range( len( y_cols) ) }\n elif len( darken_bars2 ) == len( y_cols ):\n dbar2_dict = { i: darken_bars2[ i ] for i in range( len( y_cols) ) }\n else:\n print( 'Something is wrong with how you entered the darken bars2 argument!' )\n\n if not hlines:\n hline_dict = { i: None for i in range( len( y_cols) ) }\n elif len( hlines ) == 1:\n hline_dict = { i: hlines[ 0 ] for i in range( len( y_cols) ) }\n elif len( hlines ) == len( y_cols ):\n hline_dict = { i: hlines[ i ] for i in range( len( y_cols) ) }\n else:\n print( 'Something is wrong with how you entered the hlines argument!' )\n\n if not y_ax_lim:\n ylim_dict = { i: None for i in range( len( y_cols) ) }\n elif len( y_ax_lim ) == 1:\n ylim_dict = { i: y_ax_lim[ 0 ] for i in range( len( y_cols) ) }\n elif len( y_ax_lim ) > 1 and share_y:\n print( 'You specified too many y axis limits to have them all sharey' )\n elif len( y_ax_lim ) == len( y_cols ):\n ylim_dict = { i: y_ax_lim[ i ] for i in range( len( y_cols) ) }\n else:\n print( 'Something is wrong with how you entered the y axis limits argument!' )\n\n if wt_labels:\n\n ht_max = tbv_filt[ y_cols ].max().max()\n ht_min = tbv_filt[ y_cols ].min().min()\n\n y_max = y_ax_lim[ -1 ][ 1 ] if y_ax_lim else 1.01ht_max\n y_min = ht_min + ht_min if ht_min < 0 else -20\n ylim_dict[ len( y_cols ) - 1 ] = ( y_min, y_max )\n\n #this whole loop is basically to give each its own y axis labels\n #and to only have the legend & scale bar on the top plot\n #and to only have wt labels on the bottom plot\n for idx, col in enumerate( y_cols ):\n\n if idx == 0:\n subplot_psi_by_alt( tbv_filt,\n col,\n pos_col,\n colors,\n ax = axes[ idx ],\n color_col = color_col,\n edge_col = edge_col,\n shade_by_base = shade_by_base,\n shade_exons = shade_exons,\n tick_spacing = tick_spacing,\n bar_labels = bar_labels,\n bar_label_loc = bar_label_loc,\n bar_labels_offset = bar_labels_offset,\n darken_bars = dbar_dict[ idx ],\n darken_bars2 = dbar2_dict[ idx ],\n darken_edges = darken_edges,\n labels_legend = labels_legend,\n labels_legend_title = labels_legend_title,\n labels_legend_loc = labels_legend_loc,\n title = title,\n y_ax_lim = ylim_dict[ idx ],\n y_ax_title = y_ax_title[ idx ],\n legend = legend,\n legend_title = legend_title,\n legend_loc = legend_loc,\n legend_labels = legend_labels,\n tight = tight,\n print_ex_count = print_ex_count,\n scale_bar = scale_bar,\n scale_bar_loc = scale_bar_loc,\n rev_trans = rev_trans,\n hlines = hline_dict[ idx ],\n snap = snap )\n elif idx == ( len( y_cols ) - 1 ):\n subplot_psi_by_alt( tbv_filt,\n col,\n pos_col,\n colors,\n ax = axes[ idx ],\n color_col = color_col,\n edge_col = edge_col,\n shade_by_base = shade_by_base,\n shade_exons = shade_exons,\n tick_spacing = tick_spacing,\n bar_labels = all_bar_labels,\n darken_bars = dbar_dict[ idx ],\n darken_bars2 = dbar2_dict[ idx ],\n darken_edges = darken_edges,\n wt_labels = wt_labels,\n legend = False,\n y_ax_lim = ylim_dict[ idx ],\n y_ax_title = y_ax_title[ idx ],\n tight = tight,\n rev_trans = rev_trans,\n hlines = hline_dict[ idx ],\n x_ax_title = x_ax_title,\n snap = snap )\n else:\n subplot_psi_by_alt( tbv_filt,\n col,\n pos_col,\n colors,\n ax = axes[ idx ],\n color_col = color_col,\n edge_col = edge_col,\n shade_by_base = shade_by_base,\n shade_exons = shade_exons,\n tick_spacing = tick_spacing,\n bar_labels = all_bar_labels,\n darken_bars = dbar_dict[ idx ],\n darken_bars2 = dbar2_dict[ idx ],\n darken_edges = darken_edges,\n y_ax_lim = ylim_dict[ idx ],\n legend = False,\n y_ax_title = y_ax_title[ idx ],\n tight = tight,\n rev_trans = rev_trans,\n hlines = hline_dict[ idx ],\n snap = snap )\n\n if savefile:\n plt.savefig( savefile,\n #dpi = 300,\n bbox_inches = 'tight'\n )\n\n plt.show()\n\ndef split_ax_bcs( var_df,\n bc_col,\n pos_col,\n colors,\n y_lims,\n index_cols = [ 'pos', 'alt' ],\n fig_size = ( 30, 5 ),\n hratios = [ 1, 1 ],\n zoom=None,\n tick_spacing = 10,\n title = '',\n y_ax_title='',\n y_ax_lim = None,\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n savefile = None\n ):\n\n tbv = var_df.sort_values( by = index_cols ).copy()\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n tbv_filt = tbv.set_index( 'pos' ).loc[ zoom[0]:zoom[1] ].reset_index()\n else:\n tbv_filt = tbv\n\n #check if plot will lose bars due to not enough space for all the pixels\n dpi = 100\n if ( tbv_filt.shape[0]1.5 ) > ( fig_size[0]dpi ):\n fig_height = fig_size[1]\n fig_size = ( ( tbv_filt.shape[0]1.5 / dpi ), fig_height )\n print('Adjusting figure width to accomodate all pixels...')\n\n fig = plt.figure( figsize = fig_size )\n gs = gridspec.GridSpec( nrows = len( y_lims ),\n ncols = 1,\n height_ratios = hratios )\n\n col_pivot = tbv_filt.pivot( index = 'pos', columns = 'alt', values = bc_col )\n\n axes = []\n for i in range( len( y_lims ) ):\n axes.append( plt.subplot( gs[ i ],\n #sharex = True\n )\n )\n col_pivot.plot.bar( ax = axes[ -1 ],\n color = colors,\n stacked = True,\n align = 'center',\n width = 1, )\n axes[ - 1 ].set_ylim( y_lims[ i ] )\n axes[ -1 ].tick_params( axis = 'y', which='major', labelsize = 36 )\n\n for i, ax in enumerate( axes ):\n if i != ( len( y_lims ) - 1 ):\n ax.spines[ 'bottom' ].set_visible( False )\n ax.tick_params( axis='x', # changes apply to the x-axis\n which='both', # both major and minor ticks are affected\n bottom=False, # ticks along the bottom edge are off\n top=False, # ticks along the top edge are off\n labelbottom=False) # labels along the bottom edge are off\n ax.set_xlabel( '' )\n else:\n ax.set_xlabel( x_ax_title, fontsize = 36 )\n ax.tick_params( axis = 'x', which='major', labelsize = 36, labelrotation = 90 )\n\n if i != 0:\n ax.spines[ 'top' ].set_visible( False )\n\n pos_pivot = tbv_filt.pivot( index = 'pos', columns = 'alt', values = pos_col )\n pos_pivot = pos_pivot.fillna( '' )\n pos_pivot[ pos_col ] = [ a if a != '' else c for a,c in zip( pos_pivot.A, pos_pivot.C ) ]\n plt.xticks( [ idx for idx,p in enumerate( col_pivot.index ) if idx % tick_spacing == 1 ],\n [ c for idx,c in enumerate( pos_pivot[ pos_col ] ) if idx % tick_spacing == 1 ],)\n\n if legend:\n\n if legend_labels:\n legend = plt.legend( title = legend_title,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n labels = legend_labels,\n fontsize = 14 )\n else:\n legend = plt.legend( title = legend_title,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n for ax in axes:\n ax.legend_ = None\n plt.draw()\n\n if tight:\n plt.tight_layout()\n\n if savefile:\n plt.savefig( savefile,\n #dpi = 300,\n bbox_inches = 'tight'\n )\n\n plt.show()\n\ndef plot_stacked_psi( var_df,\n zcols,\n pos_col,\n colors,\n index_cols = [ 'pos', 'alt' ],\n edge_col = None,\n fig_size = ( 30, 5 ),\n shade_exons = False,\n shade_by_base = False,\n zoom=None,\n tick_spacing = 10,\n alt_labels = False,\n bar_labels = False,\n bar_label_loc = 'middle',\n bar_labels_offset = True,\n darken_bars = False,\n darken_edges = False,\n labels_legend = False,\n labels_legend_title = '',\n labels_legend_loc = 'best',\n title = '',\n y_ax_title='',\n y_ax_lim = None,\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n print_ex_count = False,\n scale_bar = False,\n scale_bar_loc = 'left',\n rev_trans = False,\n hlines = None,\n savefile = None ):\n\n tbv = var_df.sort_values( by = index_cols ).copy()\n\n if zoom:\n assert zoom[1] > zoom[0], 'Your final zoom coordinate must be larger than the first zoom coordinate'\n tbv_filt = tbv.set_index( 'pos' ).loc[ zoom[0]:zoom[1] ].reset_index()\n else:\n tbv_filt = tbv\n\n #check if plot will lose bars due to not enough space for all the pixels\n dpi = 100\n if ( tbv_filt.shape[0]1.5 ) > ( fig_size[0]dpi ):\n fig_height = fig_size[1]\n fig_size = ( ( tbv_filt.shape[0]1.5 / dpi ), fig_height )\n print('Adjusting figure width to accomodate all pixels...')\n\n if print_ex_count:\n print('This figure shows %i exonic bases.' % sum( c[1]-c[0] for c in shade_exons ) )\n\n #col_pivot = tbv_filt.set_index( index_cols )[ zcols ]\n\n col_pivot = tbv_filt.pivot( index = 'pos', columns = 'alt', values = zcols )\n\n col_pivot.plot.bar( color = colors,\n edgecolor = edge_col,\n stacked = True,\n align = 'center',\n width = 1,\n figsize = fig_size )\n\n ax = plt.gca()\n\n if alt_labels or bar_labels or shade_by_base or scale_bar or darken_bars or darken_edges:\n\n rects = ax.patches\n\n heights = [ rect.get_height() for rect in rects ]\n\n n_bars = int( len( heights ) / len( zcols ) )\n\n pos_ht_sum = [ sum( heights[ i ] for i in range( j, len( heights ), n_bars ) if heights[ i ] > 0 )\n for j in range( n_bars ) ]\n neg_ht_sum = [ sum( heights[ i ] for i in range( j, len( heights ), n_bars ) if heights[ i ] < 0 )\n for j in range( n_bars ) ]\n\n if bar_label_loc == 'above':\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transAxes )\n else:\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transData )\n\n if darken_bars:\n\n column, colors = darken_bars\n\n locs = tbv_filt[ column ]\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc:\n\n for iidx in range( len( zcols ) ):\n\n color = colors[ iidx ]\n\n rects[ jidx + iidxn_bars ].set_facecolor( color )\n\n if darken_edges:\n\n column, color = darken_edges\n\n locs = tbv_filt[ column ]\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc:\n\n for iidx in range( len( zcols ) ):\n\n rects[ jidx + iidxn_bars ].set_edgecolor( color )\n\n if alt_labels:\n\n labels = col_pivot.index.get_level_values( 'alt' )\n\n min_ht = min( neg_ht_sum )\n neg_ht_mean = np.mean( neg_ht_sum )\n\n for rect, label in zip( rects, labels ):\n ax.text( rect.get_x() + rect.get_width() / 2,\n min_ht + .75neg_ht_mean,\n label,\n fontsize = 16,\n fontweight = 'bold',\n ha='center',\n va='bottom' )\n\n if bar_labels:\n\n if bar_labels_offset:\n\n if bar_label_loc == 'middle':\n\n pos_ht_mean = np.mean( pos_ht_sum )\n\n max_rect_ht = y_ax_lim[ 1 ] if y_ax_lim else ax.get_ylim()[ 1 ]\n\n mid_rect_ht = max_rect_ht / 2\n\n mid_label = int( len( bar_labels ) / 2 )\n\n #sets up constant y label positions\n #first label is the lowest and they are centered in the middle of the positive y axis\n label_pos = [ mid_rect_ht + ( i - ( mid_label ) ).2max_rect_ht for i in range( len( bar_labels ) ) ]\n\n elif bar_label_loc == 'above':\n\n label_pos = [ 1 + .1i for i in range( len( bar_labels ) ) ]\n\n else:\n\n if bar_label_loc == 'middle':\n\n pos_ht_mean = np.mean( pos_ht_sum )\n\n max_rect_ht = y_ax_lim[ 1 ] if y_ax_lim else ax.get_ylim()[ 1 ]\n\n mid_rect_ht = max_rect_ht / 2\n\n #sets up constant y label positions\n #they are centered in the middle of the positive y axis\n label_pos = [ mid_rect_ht for i in range( len( bar_labels ) ) ]\n\n elif bar_label_loc == 'above':\n\n label_pos = [ 1.01 for i in range( len( bar_labels ) ) ]\n\n for iidx, colmark in enumerate( bar_labels ):\n\n col, marker, _label, fsize = colmark\n\n #true false vector for where to put the marker\n locs = tbv_filt[ col ]\n\n for jidx, rloc in enumerate( zip( rects, locs ) ):\n\n rect, loc = rloc\n\n if loc:\n\n ax.text( rect.get_x() + rect.get_width() /2,\n label_pos[ iidx ],\n marker,\n fontsize = fsize,\n transform = trans,\n ha = 'center',\n va = 'bottom' )\n\n plt.title( title, fontsize = 24 )\n\n if alt_labels:\n\n col_pivot[ 'y_min' ] = col_pivot[ col_pivot < 0 ].sum( axis = 1 )\n col_pivot[ 'y_max' ] = col_pivot[ col_pivot > 0 ].sum( axis = 1 )\n\n y_max = y_ax_lim[ 1 ] if y_ax_lim else 1.01col_pivot.y_max.max()\n y_ax_lim = ( col_pivot.y_min.min() + neg_ht_mean,\n y_max )\n\n if y_ax_lim:\n plt.ylim( y_ax_lim )\n\n plt.ylabel( y_ax_title, fontsize = 36 )\n plt.yticks( fontsize = 36 )\n\n plt.xlabel( x_ax_title, fontsize = 36 )\n\n pos_pivot = tbv_filt.pivot( index = 'pos', columns = 'alt', values = pos_col )\n\n pos_pivot = pos_pivot.fillna( '' )\n\n pos_pivot[ pos_col ] = [ a if a != '' else c for a,c in zip( pos_pivot.A, pos_pivot.C ) ]\n\n plt.xticks( [ idx for idx,p in enumerate( col_pivot.index ) if idx % tick_spacing == 1 ],\n [ c for idx,c in enumerate( pos_pivot[ pos_col ] ) if idx % tick_spacing == 1 ],\n fontsize=36,\n rotation='vertical' )\n\n if hlines:\n for line in hlines:\n plt.axhline( line, c = 'black', ls = '--', alpha = .6 )\n\n if shade_by_base:\n\n for i in range( len( set( tbv_filt.pos ) ) ):\n\n #shade only every other position\n if i % 2 == 0:\n\n #three bases are non-missing at each position\n rect = rects[ 3i ]\n\n plt.axvspan( rect.get_x(),\n rect.get_x() + 3rect.get_width(),\n facecolor = 'gray',\n alpha = 0.2 )\n\n if shade_exons:\n for ex in shade_exons:\n plt.axvspan( col_pivot.index.get_loc( ex[0] ).start - .5,\n col_pivot.index.get_loc( ex[1] ).stop,\n facecolor = 'gray',\n alpha = 0.15 )\n\n if scale_bar:\n\n assert scale_bar_loc.lower() in [ 'left', 'middle', 'right' ], \\\n 'Scale bar location can be \"left\", \"middle\", or \"right\".'\n\n if scale_bar_loc == 'left':\n x_loc = 3tick_spacing\n elif scale_bar_loc == 'middle':\n x_loc = tbv_filt.shape[0] / 2\n else:\n x_loc = tbv_filt.shape[0] - 3tick_spacing\n\n trans = tfrms.blended_transform_factory( ax.transData,\n ax.transAxes )\n plt.errorbar( x_loc,\n 0.96,\n #xerr = ( 3tick_spacing / 2 ),\n xerr = ( 3tick_spacingrects[0].get_width() / 2 ),\n color = 'black',\n capsize=3,\n transform=trans )\n\n txt = str( tick_spacing ) + ' bases' if tick_spacing > 1 else str( tick_spacing ) + ' base'\n plt.text( x_loc,\n 0.94,\n txt,\n horizontalalignment = 'center',\n verticalalignment = 'top',\n transform = trans,\n fontsize = 14 )\n\n if legend:\n\n if legend_labels:\n legend = plt.legend( title = legend_title,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n labels = legend_labels,\n fontsize = 14 )\n else:\n legend = plt.legend( title = legend_title,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n elif labels_legend:\n\n fake_handles = [ plt.Rectangle( (0, 0), 0, 0, fill=False, edgecolor='none', visible = 'False')\n for i in range( len( bar_labels ) ) ]\n\n legend = plt.legend( handles = fake_handles,\n title = labels_legend_title,\n bbox_to_anchor = ( 0, 1 ), #if you turn that on you can put legend outside of plot\n loc = labels_legend_loc,\n labels = ( symbol + ' '6 + label for _col, symbol, label, _fsize in bar_labels ),\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n ax.legend_ = None\n plt.draw()\n\n if tight:\n plt.tight_layout()\n\n if savefile:\n plt.savefig( savefile,\n #dpi = 300,\n #bbox_inches = 'tight'\n )\n\n plt.show()\n\ndef swarm_plot( tblbyvar,\n x_col,\n y_col,\n x_ax_label = '',\n x_tick_labels = None,\n y_ax_label = '',\n hlines = None,\n savefile = None,\n kwargs ):\n\n sns.set_style( 'ticks' )\n\n tbv = tblbyvar.copy()\n\n ax = sns.swarmplot( x = x_col,\n y = y_col,\n data = tbv,\n kwargs )\n\n ax.set_xlabel( x_ax_label,\n fontsize = 18 )\n\n ax.set_ylabel( y_ax_label,\n fontsize = 18 )\n\n if x_tick_labels:\n ax.set_xticklabels( x_tick_labels,\n fontsize = 14 )\n\n plt.yticks( fontsize = 14 )\n\n if hlines:\n for hl in hlines:\n ax.axhline( hl, color = 'black', linestyle = '--' )\n\n if savefile:\n plt.savefig( savefile )\n\n plt.show()\n\ndef violin( tbl_byvar,\n cat_col,\n val_col,\n ylim = None,\n x_ax_label = '',\n y_ax_label = '',\n x_tick_labels = None,\n savefig = None,\n kwargs ):\n\n tbv = tbl_byvar.copy()\n\n ax = sns.violinplot( x = cat_col,\n y = val_col,\n data = tbv,\n kwargs\n )\n\n if ylim:\n ax.set_ylim( ylim )\n\n ax.set_xlabel( x_ax_label,\n fontsize = 18 )\n\n ax.set_ylabel( y_ax_label,\n fontsize = 18 )\n\n if x_tick_labels:\n ax.set_xticklabels( x_tick_labels,\n fontsize = 14 )\n\n plt.yticks( fontsize = 14 )\n\n if savefig:\n plt.savefig( savefig,\n bbox_to_inches = 'tight' )\n\n plt.show()\n\ndef upset_plot( byvartbl,\n cat_cols,\n fig_size = ( 10, 20 ),\n dist_cols = None,\n dist_cols_kind = None,\n dist_cols_col = None,\n violin_inner = None,\n savefig = None,\n kwargs ):\n\n tbv = byvartbl.set_index( cat_cols ).copy()\n\n up_df = up.UpSet( tbv, kwargs )\n\n inner = { }\n\n\n if dist_cols:\n\n for i, col in enumerate( dist_cols ):\n\n if dist_cols_kind[ i ] == 'violin':\n\n up_df.add_catplot( value = col,\n kind = dist_cols_kind[ i ],\n color = dist_cols_col[ i ],\n inner = 'points',\n #jitter = True,\n #s = 1.5,\n elements = 3,\n cut = 0,\n scale = 'width',\n #linewidth = 1,\n width = .5,\n #bw = 2\n )\n else:\n\n up_df.add_catplot( value = col,\n kind = dist_cols_kind[ i ],\n color = dist_cols_col[ i ],\n #s = 3,\n elements = 2,\n #linewidth = 0,\n )\n\n #fig1 = plt.figure( figsize = fig_size )\n\n fig1 = plt.gcf()\n\n fig1.set_size_inches(20, 40)\n\n up_df.plot( fig = fig1 )\n\n #g.fig.set_figwidth(20)\n #g.fig.set_figheight(20)\n\n if savefig:\n\n plt.savefig( savefig,\n bbox_inches = 'tight' )\n\n plt.show()\n\ndef sdv_waterfall_plot(\n vartbl,\n waterfall_col,\n percentile = None,\n title = '',\n x_ax_title = '',\n y_ax_title = '',\n ):\n\n ranks = vartbl.copy()\n\n ranks = ranks.sort_values( by = [ waterfall_col ],\n ascending = False )\n\n ranks[ waterfall_col + '_rank' ] = np.arange( ranks.shape[0] )\n\n fig, ax1 = plt.subplots()\n\n color = 'blue'\n ax1.set_xlabel( x_ax_title )\n ax1.set_ylabel( y_ax_title, color=color )\n ax1.plot( ranks[ waterfall_col + '_rank' ],\n ranks[ waterfall_col ], color=color)\n\n if percentile:\n percentile_cutoff = ranks.iloc[ int( ranks.shape[0]percentile0.01 ) ][ waterfall_col ]\n plt.axvline( int( ranks.shape[0]percentile0.01 ),\n color = 'black' )\n print( ' To call %d%% of variants as SDV, use the threshold %.2f ' % ( percentile, percentile_cutoff ) )\n\n fig.tight_layout() # otherwise the right y-label is slightly clipped\n plt.show()\n\ndef barplot_per_repeat( table_by_var,\n sdv_col,\n nsamp,\n ylim = None,\n ylabel = '',\n xlabel = '',\n savefig = False,\n kwargs ):\n\n tbv = table_by_var.copy()\n\n vals = tbv[ sdv_col ].value_counts()\n\n total = vals.sum()\n\n xvals = [ i for i in range( 1, nsamp + 1 ) ]\n\n yvals = []\n for x in xvals:\n\n if x in vals:\n yvals.append( 100( int( vals[ x ] ) / total ) )\n else:\n yvals.append( 0 )\n\n plt.bar( xvals, yvals, *kwargs )\n\n ax = plt.gca()\n\n rects = ax.patches\n\n trans = tfrms.blended_transform_factory( ax.transData, ax.transData )\n\n for rect, y in zip( rects, yvals ):\n\n if y > 0:\n\n ax.text( rect.get_x() + rect.get_width() /2,\n rect.get_height(),\n str( round( ( y / 100 )total ) ),\n fontsize = 16,\n transform = trans,\n ha = 'center',\n va = 'bottom' )\n\n if ylim:\n plt.ylim( ylim )\n\n plt.ylabel( ylabel, fontsize = 18 )\n plt.yticks( fontsize = 18 )\n\n plt.xlabel( xlabel, fontsize = 18 )\n plt.xticks( fontsize = 18 )\n\n plt.tight_layout()\n\n if savefig:\n plt.savefig( savefig,\n bbox_inches = 'tight' )\n\n plt.show()\n\ndef pr_curves_bytruth( var_df,\n truth_cols,\n pred_col,\n colors,\n fig_size = ( 5, 5 ),\n grid = False,\n x_ax_label = 'Recall\\n(%)',\n y_ax_label = 'Precision\\n(%)',\n add_point = False,\n savefile = None,\n *kwargs\n ):\n\n #pr curve function hates missing values\n tbv = var_df.dropna(subset = [ pred_col ] ).copy()\n\n if tbv.shape[ 0 ] != var_df.shape[ 0 ]:\n print( 'Missing values in predictor column.', str( var_df.shape[ 0 ] - tbv.shape[ 0 ] ), 'rows removed.' )\n\n plt.figure( figsize = fig_size )\n\n for truth, color in zip( truth_cols, colors ):\n\n #pr curve function hates missing values\n vdf = tbv.dropna(subset = [ truth ] ).copy()\n\n if vdf.shape[ 0 ] != tbv.shape[ 0 ]:\n print( 'Missing values in truth column.', str( tbv.shape[ 0 ] - vdf.shape[ 0 ] ), 'rows removed.' )\n\n precision, recall, _ = precision_recall_curve( vdf[ truth ],\n vdf[ pred_col ] )\n\n plt.plot( 100recall,\n 100precision,\n color = color,\n kwargs )\n\n print( truth, auc( recall, precision ) )\n\n if add_point:\n plt.plot( add_point[ truth ][ 0 ],\n add_point[ truth ][ 1 ],\n color = 'black',\n marker = add_point[ truth ][ 2 ],\n markersize = add_point[ truth ][ 3 ]\n )\n\n plt.xlabel( x_ax_label, fontsize = 24 )\n plt.xticks( fontsize = 20 )\n\n plt.ylabel( y_ax_label, fontsize = 24 )\n plt.yticks( fontsize = 20 )\n\n plt.grid( grid )\n\n if savefile:\n plt.savefig( savefile,\n dpi = 300,\n bbox_inches = 'tight' )\n\n plt.show()\n\ndef plot_stacked_bar( var_df,\n ycols,\n xcol,\n sort_cols = [ 'pos', 'alt' ],\n title = '',\n y_ax_title='',\n y_ax_lim = None,\n x_ax_title = '',\n legend = True,\n legend_title = '',\n legend_loc = 'best',\n legend_labels = None,\n tight = True,\n hlines = None,\n savefile = None,\n kwargs ):\n\n tbv = var_df.sort_values( by = sort_cols ).set_index( xcol ).copy()\n\n tbv[ ycols ].plot.bar( stacked = True,\n *kwargs )\n\n plt.title( title, fontsize = 24 )\n\n if y_ax_lim:\n plt.ylim( y_ax_lim )\n\n plt.ylabel( y_ax_title, fontsize = 20 )\n plt.yticks( fontsize = 18 )\n\n plt.xlabel( x_ax_title, fontsize = 18 )\n plt.xticks( fontsize = 15 )\n\n if hlines:\n for line in hlines:\n plt.axhline( line, c = 'black', ls = '--', alpha = .6 )\n\n ax = plt.gca()\n\n if legend:\n\n legend = plt.legend( title = legend_title,\n bbox_to_anchor = ( 1, 1 ), #if you turn that on you can put legend outside of plot\n loc = legend_loc,\n fontsize = 14 )\n plt.setp( legend.get_title(), fontsize=14 )\n else:\n ax.legend_ = None\n plt.draw()\n\n if tight:\n plt.tight_layout()\n\n if savefile:\n plt.savefig( savefile, )\n\n plt.show()\n" } ]	10

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