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psychic/nodes/filter.py | breuderink/psychic | 3 | 124185 | import numpy as np
from scipy import signal
from golem import DataSet
from golem.nodes import BaseNode
from psychic.utils import get_samplerate
class Filter(BaseNode):
def __init__(self, filt_design_func):
'''
Forward-backward filtering node. filt_design_func is a function that takes
the sample rate as an argument, and returns the filter coefficients (b, a).
'''
BaseNode.__init__(self)
self.filt_design_func = filt_design_func
def train_(self, d):
fs = get_samplerate(d)
self.log.info('Detected sample rate of %d Hz' % fs)
self.filter = self.filt_design_func(fs)
def apply_(self, d):
b, a = self.filter
xs = np.hstack([signal.filtfilt(b, a, d.xs[:, i]).reshape(-1, 1)
for i in range(d.nfeatures)])
return DataSet(xs=xs, default=d)
class OnlineFilter(Filter):
def __init__(self, filt_design_func):
Filter.__init__(self, filt_design_func)
self.zi = []
def apply_(self, d):
b, a = self.filter
if self.zi == []:
self.zi = [signal.lfiltic(b, a, np.zeros(b.size)) for fi in
range(d.nfeatures)]
new_zi = []
xs = []
for i in range(d.nfeatures):
xi, zii = signal.lfilter(b, a, d.xs[:, i], zi=self.zi[i])
xs.append(xi.reshape(-1, 1))
new_zi.append(zii)
self.zi = new_zi
return DataSet(xs=np.hstack(xs), default=d)
class Winsorize(BaseNode):
def __init__(self, cutoff=[.05, .95]):
self.cutoff = np.atleast_1d(cutoff)
assert self.cutoff.size == 2
BaseNode.__init__(self)
def train_(self, d):
assert len(d.feat_shape) == 1
self.lims = np.apply_along_axis(lambda x: np.interp(self.cutoff,
np.linspace(0, 1, d.ninstances), np.sort(x)), 0, d.xs)
def apply_(self, d):
return DataSet(xs=np.clip(d.xs, self.lims[0,:], self.lims[1:]),
default=d)
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src/tesk_core/helm_client.py | PlatformedTasks/PLAS-tesk-core | 0 | 102097 | <filename>src/tesk_core/helm_client.py
import subprocess
repo_name = "taskmaster-repo"
def helm_add_repo(repo_url):
try:
print(f"Adding '{repo_url}' as '{repo_name}'")
repo_add = subprocess.run(['helm', 'repo', 'add', repo_name, repo_url, '--force-update'], capture_output=True, text=True, check=True)
print(repo_add.stdout)
print(f"Updating helm repositories...")
repo_update = subprocess.run(['helm', 'repo', 'update'], capture_output=True, text=True, check=True)
print(repo_update.stdout)
except subprocess.CalledProcessError as err:
print(err.stderr)
except Exception as err:
print(err)
def helm_install(release_name, chart_name, chart_version, chart_values, namespace="default"):
try:
chart = f"{repo_name}/{chart_name}"
print(f"Installing '{release_name}' from '{chart}' in namespace '{namespace}'...")
helm_command = ['helm', 'install', release_name, chart, f'--namespace={namespace}', '--wait']
if chart_version:
helm_command.append(f'--version={chart_version}')
if chart_values:
for chart_file in chart_values:
helm_command.append(f'-f={str(chart_file)}')
release_install = subprocess.run(helm_command, capture_output=True, text=True, check=True)
print(release_install.stdout)
return release_install
except subprocess.CalledProcessError as err:
print(err.stderr)
except Exception as err:
print(err)
def helm_uninstall(release_name, namespace="default"):
try:
print(f"Uninstalling '{release_name}'...")
release_uninstall = subprocess.run(['helm', 'uninstall', release_name, f'--namespace={namespace}'], capture_output=True, text=True, check=True)
print(release_uninstall.stdout)
except subprocess.CalledProcessError as err:
print(err.stderr)
except Exception as err:
print(err)
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src/treca/data.py | evanfyang/terminus-2 | 0 | 108331 | #!/usr/bin/python
import os
import re
import platform
from Bio import AlignIO
from Bio.Seq import Seq
from Bio.Align import AlignInfo
from Bio.Align.Applications import MuscleCommandline
# define constants
HEADER = 1
SEQUENCE = 2
FORWARD = 1
REVERSE = 2
FA_LINES_PER_READ = 2
FQ_LINES_PER_READ = 4
class SequenceData:
def __init__(self, read_type, telomeric_repeat, interleaved_read_filepath=None, r1_read_filepath=None, r2_read_filepath=None, out_directory=None):
self._read_type = read_type
self._interleaved_reads_filepath = interleaved_read_filepath
self._r1_reads_filepath = r1_read_filepath
self._r2_reads_filepath = r2_read_filepath
self._out_directory = out_directory
if self._out_directory == None:
self._out_directory = os.path.abspath(os.path.join(os.path.expanduser('~'), 'terminus_output'))
os.makedirs(os.path.dirname(self._out_directory), exist_ok=True)
self._3prime_telomeric_repeat_regex = self._generate_regular_expression(telomeric_repeat, "3'")
self._5prime_telomeric_repeat_regex = self._generate_regular_expression(str(Seq(telomeric_repeat).reverse_complement()), "5'")
self._r1_telomeric_reads_filepath = None
self._r2_telomeric_reads_filepath = None
self._r1_telomeric_reads_clusters_info_filepath = None
self._r2_telomeric_reads_clusters_info_filepath = None
self._r1_telomeric_reads_clusters_directory = None
self._r2_telomeric_reads_clusters_directory = None
self._r1_telomeric_reads_clusters_alignments_directory = None
self._r2_telomeric_reads_clusters_alignments_directory = None
self._r1_telomeric_reads_clusters_consensus_filepath = None
self._r2_telomeric_reads_clusters_consensus_filepath = None
self._r1_subtelomeric_reads_filepath = None
self._r2_subtelomeric_reads_filepath = None
self._r1_subtelomeric_reads_clusters_info_filepath = None
self._r2_subtelomeric_reads_clusters_info_filepath = None
self._r1_subtelomeric_reads_clusters_directory = None
self._r2_subtelomeric_reads_clusters_directory = None
self._r1_subtelomeric_reads_clusters_alignments_directory = None
self._r2_subtelomeric_reads_clusters_alignments_directory = None
self._r1_subtelomeric_reads_clusters_consensus_filepath = None
self._r2_subtelomeric_reads_clusters_consensus_filepath = None
def get_read_type(self):
return self._read_type
def get_interleaved_reads_filepath(self):
return self._interleaved_reads_filepath
def get_r1_reads_filepath(self):
return self._r1_reads_filepath
def get_r2_reads_filepath(self):
return self._r2_reads_filepath
def get_out_directory(self):
return self._out_directory
def get_3prime_telomeric_repeat_regex(self):
return self._3prime_telomeric_repeat_regex
def get_5prime_telomeric_repeat_regex(self):
return self._5prime_telomeric_repeat_regex
def get_r1_telomeric_reads_filepath(self):
return self._r1_telomeric_reads_filepath
def get_r2_telomeric_reads_filepath(self):
return self._r2_telomeric_reads_filepath
def get_r1_telomeric_reads_clusters_info_filepath(self):
return self._r1_telomeric_reads_clusters_info_filepath
def get_r2_telomeric_reads_clusters_info_filepath(self):
return self._r2_telomeric_reads_clusters_info_filepath
def get_r1_telomeric_reads_clusters_directory(self):
return self._r1_telomeric_reads_clusters_directory
def get_r2_telomeric_reads_clusters_directory(self):
return self._r2_telomeric_reads_clusters_directory
def get_r1_telomeric_reads_clusters_alignments_directory(self):
return self._r1_telomeric_reads_clusters_alignments_directory
def get_r2_telomeric_reads_clusters_alignments_directory(self):
return self._r2_telomeric_reads_clusters_alignments_directory
def get_r1_telomeric_reads_clusters_consensus_filepath(self):
return self._r1_telomeric_reads_clusters_consensus_filepath
def get_r2_telomeric_reads_clusters_consensus_filepath(self):
return self._r2_telomeric_reads_clusters_consensus_filepath
def get_r1_subtelomeric_reads_filepath(self):
return self._r1_subtelomeric_reads_filepath
def get_r2_subtelomeric_reads_filepath(self):
return self._r2_subtelomeric_reads_filepath
def get_r1_subtelomeric_reads_clusters_info_filepath(self):
return self._r1_subtelomeric_reads_clusters_info_filepath
def get_r2_subtelomeric_reads_clusters_info_filepath(self):
return self._r2_subtelomeric_reads_clusters_info_filepath
def get_r1_subtelomeric_reads_clusters_directory(self):
return self._r1_subtelomeric_reads_clusters_directory
def get_r2_subtelomeric_reads_clusters_directory(self):
return self._r2_subtelomeric_reads_clusters_directory
def get_r1_subtelomeric_reads_clusters_alignments_directory(self):
return self._r1_subtelomeric_reads_clusters_alignments_directory
def get_r2_subtelomeric_reads_clusters_alignments_directory(self):
return self._r2_subtelomeric_reads_clusters_alignments_directory
def get_r1_subtelomeric_reads_clusters_consensus_filepath(self):
return self._r1_subtelomeric_reads_clusters_consensus_filepath
def get_r2_subtelomeric_reads_clusters_consensus_filepath(self):
return self._r2_subtelomeric_reads_clusters_consensus_filepath
def extract_telomeric_reads(self):
telomeric_reads_directory = os.path.abspath(os.path.join(self._out_directory, 'telomeric_reads'))
os.makedirs(telomeric_reads_directory, exist_ok=True)
self._r1_telomeric_reads_filepath = os.path.abspath(os.path.join(telomeric_reads_directory, 'r1_telomeric_reads.fasta'))
r1_telomeric_reads_output = open(self._r1_telomeric_reads_filepath, "w+")
self._r2_telomeric_reads_filepath = os.path.abspath(os.path.join(telomeric_reads_directory, 'r2_telomeric_reads.fasta'))
r2_telomeric_reads_output = open(self._r2_telomeric_reads_filepath, "w+")
if self._read_type == "interleaved":
print("Extracting telomeric reads from an interleaved FASTQ dataset...")
self._process_reads(self._interleaved_reads_filepath, r1_telomeric_reads_output, r2_telomeric_reads_output)
print("Done.\n")
if self._read_type == "seperated":
print("Extracting telomeric reads from R1 FASTQ dataset...")
self._process_reads(input_filepath=self._r1_reads_filepath, r1_output=r1_telomeric_reads_output, r2_output=None)
print("Done.\n")
print("Extracting telomeric reads from R2 FASTQ dataset...")
self._process_reads(input_filepath=self._r2_reads_filepath, r1_output=None, r2_output=r2_telomeric_reads_output)
print("Done.\n")
print("R1 telomeric reads saved to " + self._r1_telomeric_reads_filepath)
print("R2 telomeric reads saved to " + self._r2_telomeric_reads_filepath)
print()
def cluster_telomeric_reads(self):
# install and make wcd for clustering
print("Installing and preparing wcdest for clustering...")
os.chdir("..")
os.system("git submodule update --init --recursive >/dev/null 2>&1")
os.chdir("./lib/wcdest/code/")
os.system("./configure >/dev/null 2>&1")
# NOTE: texinfo/makeinfo must be installed for wcdest to compile correctly!!
os.system("make clean -C ./ >/dev/null 2>&1")
os.system("make -C ./ >/dev/null 2>&1")
os.system("make install -C ./ >/dev/null 2>&1")
os.chdir("../../../src")
print("Done.\n")
telomeric_reads_cluster_info_directory = os.path.abspath(os.path.join(self._out_directory, 'clusters', 'cluster_info', 'telomeric_reads'))
os.makedirs(telomeric_reads_cluster_info_directory, exist_ok=True)
self._r1_telomeric_reads_clusters_info_filepath = os.path.abspath(os.path.join(telomeric_reads_cluster_info_directory, 'r1_telomeric_reads_clusters_info.txt'))
self._r2_telomeric_reads_clusters_info_filepath = os.path.abspath(os.path.join(telomeric_reads_cluster_info_directory, 'r2_telomeric_reads_clusters_info.txt'))
# cluster forward telomeric reads and write results to file
print("Clustering telomeric reads in '" + self._r1_telomeric_reads_filepath + "'...")
os.system("../lib/wcdest/code/src/wcd -o " + self._r1_telomeric_reads_clusters_info_filepath + " -c " + self._r1_telomeric_reads_filepath + " >/dev/null 2>&1")
self._r1_telomeric_reads_clusters_directory = self._generate_clustered_reads(self._r1_telomeric_reads_filepath, self._r1_telomeric_reads_clusters_info_filepath, "telomeric", "forward")
print("Done.\n")
# cluster reverse telomeric reads and write results to file
print("Clustering telomeric reads in '" + self._r2_telomeric_reads_filepath + "'...")
os.system("../lib/wcdest/code/src/wcd -o " + self._r2_telomeric_reads_clusters_info_filepath + " -c " + self._r2_telomeric_reads_filepath + " >/dev/null 2>&1")
self._r2_telomeric_reads_clusters_directory = self._generate_clustered_reads(self._r2_telomeric_reads_filepath, self._r2_telomeric_reads_clusters_info_filepath, "telomeric", "reverse")
print("Done.\n")
print("R1 telomeric reads clustering results saved to '" + self._r1_telomeric_reads_clusters_directory)
print("R2 telomeric reads clustering results saved to '" + self._r2_telomeric_reads_clusters_directory)
print()
def extract_subtelomeric_reads(self):
# given forward telomeric clusters, retrieve the subtelomeric sequence reads
# from the reverse read file
print("Extracting subtelomeric reads from R2 sequence reads file for clustered R1 telomeric reads...")
for reads_file in os.listdir(self._r1_telomeric_reads_clusters_directory):
if reads_file.endswith(".fasta"):
if self._read_type == "interleaved":
self._r2_subtelomeric_reads_filepath = self._retrieve_subtelomeric_reads(self._interleaved_reads_filepath, os.path.abspath(os.path.join(self._r1_telomeric_reads_clusters_directory, reads_file)), "reverse")
if self._read_type == "seperated":
self._r2_subtelomeric_reads_filepath = self._retrieve_subtelomeric_reads(self._r2_reads_filepath, os.path.abspath(os.path.join(self._r1_telomeric_reads_clusters_directory, reads_file)), "reverse")
print("Done.\n")
# given reverse telomeric clusters, retrieve the subtelomeric sequence reads
# from the forward read file
print("Extracting subtelomeric reads from R1 sequence reads file for clustered R2 telomeric reads...")
for reads_file in os.listdir(self._r2_telomeric_reads_clusters_directory):
if reads_file.endswith(".fasta"):
if self._read_type == "interleaved":
self._r1_subtelomeric_reads_filepath = self._retrieve_subtelomeric_reads(self._interleaved_reads_filepath, os.path.abspath(os.path.join(self._r2_telomeric_reads_clusters_directory, reads_file)), "forward")
if self._read_type == "seperated":
self._r1_subtelomeric_reads_filepath = self._retrieve_subtelomeric_reads(self._r1_reads_filepath, os.path.abspath(os.path.join(self._r2_telomeric_reads_clusters_directory, reads_file)), "forward")
print("Done.\n")
print("R1 subtelomeric reads saved to '" + self._r1_subtelomeric_reads_filepath + "'")
print("R2 subtelomeric reads saved to '" + self._r2_subtelomeric_reads_filepath + "'")
print("\n")
def cluster_subtelomeric_reads(self):
subtelomeric_reads_cluster_info_directory = os.path.abspath(os.path.join(self._out_directory, 'clusters', 'cluster_info', 'subtelomeric_reads'))
os.makedirs(subtelomeric_reads_cluster_info_directory, exist_ok=True)
self._r1_subtelomeric_reads_clusters_info_filepath = os.path.abspath(os.path.join(subtelomeric_reads_cluster_info_directory, 'r1_subtelomeric_reads_clusters_info.txt'))
self._r2_subtelomeric_reads_clusters_info_filepath = os.path.abspath(os.path.join(subtelomeric_reads_cluster_info_directory, 'r2_subtelomeric_reads_clusters_info.txt'))
# cluster forward subtelomeric reads and write results to file
print("Clustering subtelomeric reads in '" + self._r1_subtelomeric_reads_filepath + "'...")
os.system("../lib/wcdest/code/src/wcd -o " + self._r1_subtelomeric_reads_clusters_info_filepath + " -c " + self._r1_subtelomeric_reads_filepath + " >/dev/null 2>&1")
self._r1_subtelomeric_reads_clusters_directory = self._generate_clustered_reads(self._r1_subtelomeric_reads_filepath, self._r1_subtelomeric_reads_clusters_info_filepath, "subtelomeric", "forward")
print("Done.\n")
# cluster reverse subtelomeric reads and write results to file
print("Clustering telomeric reads in '" + self._r2_subtelomeric_reads_filepath + "'...")
os.system("../lib/wcdest/code/src/wcd -o " + self._r2_subtelomeric_reads_clusters_info_filepath + " -c " + self._r2_subtelomeric_reads_filepath + " >/dev/null 2>&1")
self._r2_subtelomeric_reads_clusters_directory = self._generate_clustered_reads(self._r2_subtelomeric_reads_filepath, self._r2_subtelomeric_reads_clusters_info_filepath, "subtelomeric", "reverse")
print("Done.\n")
print("R1 subtelomeric reads clustering results saved to '" + self._r1_telomeric_reads_clusters_directory)
print("R2 subtelomeric reads clustering results saved to '" + self._r2_telomeric_reads_clusters_directory)
print()
def align_clustered_reads(self):
if platform.system() == "Linux":
os.system("chmod u=rwx,g=rwx,o=rwx ../lib/MUSCLE/muscle3.8.31_i86linux32")
muscle = r"../lib/MUSCLE/muscle3.8.31_i86linux32"
if platform.system() == "Darwin":
os.system("chmod u=rwx,g=rwx,o=rwx ../lib/MUSCLE/muscle3.8.31_i86darwin64")
muscle = r"../lib/MUSCLE/muscle3.8.31_i86darwin64"
print("Aligning clustered R1 telomeric reads in '" + self._r1_telomeric_reads_clusters_directory + "'...")
self._r1_telomeric_reads_clusters_alignments_directory = os.path.abspath(os.path.join(self._out_directory, 'alignments', 'r1_telomeric_reads'))
os.makedirs(self._r1_telomeric_reads_clusters_alignments_directory, exist_ok=True)
self._generate_alignments(muscle, self._r1_telomeric_reads_clusters_directory, self._r1_telomeric_reads_clusters_alignments_directory)
print("Done.\n")
print("Aligning clustered R2 telomeric reads in '" + self._r2_telomeric_reads_clusters_directory + "'...")
self._r2_telomeric_reads_clusters_alignments_directory = os.path.abspath(os.path.join(self._out_directory, 'alignments', 'r2_telomeric_reads'))
os.makedirs(self._r2_telomeric_reads_clusters_alignments_directory, exist_ok=True)
self._generate_alignments(muscle, self._r2_telomeric_reads_clusters_directory, self._r2_telomeric_reads_clusters_alignments_directory)
print("Done.\n")
print("Aligning clustered R1 subtelomeric reads in '" + self._r1_subtelomeric_reads_clusters_directory + "'...")
self._r1_subtelomeric_reads_clusters_alignments_directory = os.path.abspath(os.path.join(self._out_directory, 'alignments', 'r1_subtelomeric_reads'))
os.makedirs(self._r1_subtelomeric_reads_clusters_alignments_directory, exist_ok=True)
self._generate_alignments(muscle, self._r1_subtelomeric_reads_clusters_directory, self._r1_subtelomeric_reads_clusters_alignments_directory)
print("Done.\n")
print("Aligning clustered R2 subtelomeric reads in '" + self._r2_subtelomeric_reads_clusters_directory + "'...")
self._r2_subtelomeric_reads_clusters_alignments_directory = os.path.abspath(os.path.join(self._out_directory, 'alignments', 'r2_subtelomeric_reads'))
os.makedirs(self._r2_subtelomeric_reads_clusters_alignments_directory, exist_ok=True)
self._generate_alignments(muscle, self._r2_subtelomeric_reads_clusters_directory, self._r2_subtelomeric_reads_clusters_alignments_directory)
print("Done.\n")
print("Alignment results for clustered R1 telomeric reads saved to '" + self._r1_telomeric_reads_clusters_alignments_directory)
print("Alignment results for clustered R2 telomeric reads saved to '" + self._r2_telomeric_reads_clusters_alignments_directory)
print("Alignment results for clustered R1 subtelomeric reads saved to '" + self._r1_subtelomeric_reads_clusters_alignments_directory)
print("Alignment results for clustered R2 subtelomeric reads saved to '" + self._r2_subtelomeric_reads_clusters_alignments_directory)
print()
def consensus(self):
consensus_reads_directory = os.path.abspath(os.path.join(self._out_directory, 'consensus'))
os.makedirs(consensus_reads_directory, exist_ok=True)
print("Generating consensus sequences for R1 telomeric reads clusters alignments...")
self._r1_telomeric_reads_clusters_consensus_filepath = os.path.abspath(os.path.join(consensus_reads_directory, 'r1_telomeric_reads_clusters_consensus.fasta'))
r1_telomeric_reads_clusters_consensus_output = open(self._r1_telomeric_reads_clusters_consensus_filepath, "w+")
self._generate_consensus_sequences(self._r1_telomeric_reads_clusters_alignments_directory, r1_telomeric_reads_clusters_consensus_output)
print("Done.\n")
print("Generating consensus sequences for R2 telomeric reads clusters alignments...")
self._r2_telomeric_reads_clusters_consensus_filepath = os.path.abspath(os.path.join(consensus_reads_directory, 'r2_telomeric_reads_clusters_consensus.fasta'))
r2_telomeric_reads_clusters_consensus_output = open(self._r2_telomeric_reads_clusters_consensus_filepath, "w+")
self._generate_consensus_sequences(self._r2_telomeric_reads_clusters_alignments_directory, r2_telomeric_reads_clusters_consensus_output)
print("Done.\n")
print("Generating consensus sequences for R1 subtelomeric reads clusters alignments...")
self._r1_subtelomeric_reads_clusters_consensus_filepath = os.path.abspath(os.path.join(consensus_reads_directory, 'r1_subtelomeric_reads_clusters_consensus.fasta'))
r1_subtelomeric_reads_clusters_consensus_output = open(self._r1_subtelomeric_reads_clusters_consensus_filepath, "w+")
self._generate_consensus_sequences(self._r1_subtelomeric_reads_clusters_alignments_directory, r1_subtelomeric_reads_clusters_consensus_output)
print("Done.\n")
print("Generating consensus sequences for R2 subtelomeric reads clusters alignments...")
self._r2_subtelomeric_reads_clusters_consensus_filepath = os.path.abspath(os.path.join(consensus_reads_directory, 'r2_subtelomeric_reads_clusters_consensus.fasta'))
r2_subtelomeric_reads_clusters_consensus_output = open(self._r2_subtelomeric_reads_clusters_consensus_filepath, "w+")
self._generate_consensus_sequences(self._r2_subtelomeric_reads_clusters_alignments_directory, r2_subtelomeric_reads_clusters_consensus_output)
print("Done.\n")
print("Consensus sequences for clustered R1 telomeric reads saved to '" + self._r1_telomeric_reads_clusters_consensus_filepath)
print("Consensus sequences for clustered R2 telomeric reads saved to '" + self._r2_telomeric_reads_clusters_consensus_filepath)
print("Consensus sequences for clustered R1 subtelomeric reads saved to '" + self._r1_subtelomeric_reads_clusters_consensus_filepath)
print("Consensus sequences for clustered R2 subtelomeric reads saved to '" + self._r2_subtelomeric_reads_clusters_consensus_filepath)
print()
def _generate_regular_expression(self, telomeric_repeat, end):
body = telomeric_repeat * 3
regex = "(" + body + ")+"
if end == "5'":
regex = "^" + regex
if end == "3'":
regex = regex + "$"
prefix = ""
for base in reversed(telomeric_repeat[1:]):
prefix = base + prefix
if end == "5'":
regex = regex + "|^" + prefix + "(" + body + ")+"
if end == "3'":
regex = regex + "|" + prefix + "(" + body + ")+$"
return regex
def _process_reads(self, input_filepath, r1_output, r2_output):
line_counter = 0
header_line = ""
with open(input_filepath) as sequence_reads:
for line in sequence_reads:
line_counter += 1
if line_counter % FQ_LINES_PER_READ == HEADER:
header_line = line
# replace for output to FASTA format
header_line = header_line.replace("@", ">")
if line_counter % FQ_LINES_PER_READ == SEQUENCE:
start_tel_exists = re.search(self._5prime_telomeric_repeat_regex, line)
end_tel_exists = re.search(self._3prime_telomeric_repeat_regex, line)
if bool(start_tel_exists) ^ bool(end_tel_exists):
if int(header_line.split(" ")[1].split(":")[0]) == FORWARD:
r1_output.write(header_line)
r1_output.write(line)
if int(header_line.split(" ")[1].split(":")[0]) == REVERSE:
r2_output.write(header_line)
r2_output.write(line)
# retrieve telomeric reads based on clustering by wcdest
def _generate_clustered_reads(self, reads_path, reads_clusters_info_path, read_type, read_direction):
clusters = list()
rows = list()
row_num = 0 # keep track of row number of each cluster
with open(reads_clusters_info_path) as clusters_file:
# for each line in wcdest cluster file, convert to list of ints and
# remove newline and ending "." Adjust indexing.
for line in clusters_file:
row_num += 1
line = [int(i) for i in line.strip(".\n").split(" ")]
line = [i * FA_LINES_PER_READ for i in line]
# filter out singleton clusters
if len(line) > 1:
clusters.append(line)
rows.append(row_num)
row_idx = 0
# get all R1 or R2 telomeric reads
reads_file = open(reads_path, "r")
reads_lines = reads_file.readlines()
for cluster in clusters:
# specify where to save FASTA files based on read direction and the
# type reads that are being clustered
if read_type == "telomeric" and read_direction == "forward":
clustered_reads_output_directory = os.path.abspath(os.path.join(self._out_directory, 'clusters', 'r1_telomeric_reads'))
os.makedirs(clustered_reads_output_directory, exist_ok=True)
clustered_reads_output_filepath = os.path.abspath(os.path.join(clustered_reads_output_directory, 'r1_telomeric_reads_cluster_' + str(rows[row_idx]) + '.fasta'))
clustered_reads_output = open(clustered_reads_output_filepath, "w+")
if read_type == "telomeric" and read_direction == "reverse":
clustered_reads_output_directory = os.path.abspath(os.path.join(self._out_directory, 'clusters', 'r2_telomeric_reads'))
os.makedirs(clustered_reads_output_directory, exist_ok=True)
clustered_reads_output_filepath = os.path.abspath(os.path.join(clustered_reads_output_directory, 'r2_telomeric_reads_cluster_' + str(rows[row_idx]) + '.fasta'))
clustered_reads_output = open(clustered_reads_output_filepath, "w+")
if read_type == "subtelomeric" and read_direction == "forward":
clustered_reads_output_directory = os.path.abspath(os.path.join(self._out_directory, 'clusters', 'r1_subtelomeric_reads'))
os.makedirs(clustered_reads_output_directory, exist_ok=True)
clustered_reads_output_filepath = os.path.abspath(os.path.join(clustered_reads_output_directory, 'r1_subtelomeric_reads_cluster_' + str(rows[row_idx]) + '.fasta'))
clustered_reads_output = open(clustered_reads_output_filepath, "w+")
if read_type == "subtelomeric" and read_direction == "reverse":
clustered_reads_output_directory = os.path.abspath(os.path.join(self._out_directory, 'clusters', 'r2_subtelomeric_reads'))
os.makedirs(clustered_reads_output_directory, exist_ok=True)
clustered_reads_output_filepath = os.path.abspath(os.path.join(clustered_reads_output_directory, 'r2_subtelomeric_reads_cluster_' + str(rows[row_idx]) + '.fasta'))
clustered_reads_output = open(clustered_reads_output_filepath, "w+")
# given the list of clusters with singletons filtered out, append
# cluster reads to file
for i in range(len(cluster)):
index = cluster[i]
header_line = reads_lines[index]
sequence_line = reads_lines[index + 1]
# edit header to match the read direction of fastq file
if read_direction == "reverse":
header_line = header_line.replace(" 1:N", " 2:N")
if read_direction == "forward":
header_line = header_line.replace(" 2:N", " 1:N")
clustered_reads_output.write(header_line)
clustered_reads_output.write(sequence_line)
row_idx += 1
return clustered_reads_output_directory
# retrieve paired ends of a set of reads for a file with telomeric reads from
# a corresponding FASTQ file containing the paired end
def _retrieve_subtelomeric_reads(self, subtelomeric_reads_source_filepath, telomeric_reads_cluster_path, subtelomeric_reads_direction):
subtelomeric_reads_headers = set()
line_counter = 0
# store all headers from telomeric read file
with open(telomeric_reads_cluster_path) as telomeric_reads_cluster:
for line in telomeric_reads_cluster:
line_counter += 1
if line_counter % FA_LINES_PER_READ == HEADER:
# edit header to match the read direction of fastq file
if subtelomeric_reads_direction == "forward":
line = line.replace(" 2:N", " 1:N")
if subtelomeric_reads_direction == "reverse":
line = line.replace(" 1:N", " 2:N")
# edit header to match FASTQ format for searching original
subtelomeric_reads_headers.add(line.replace(">", "@"))
# specify where to save FASTA files based on the read type
if subtelomeric_reads_direction == "forward":
subtelomeric_reads_output_directory = os.path.abspath(os.path.join(self._out_directory, 'subtelomeric_reads'))
os.makedirs(subtelomeric_reads_output_directory, exist_ok=True)
r1_subtelomeric_reads_output_filepath = os.path.abspath(os.path.join(subtelomeric_reads_output_directory, 'r1_subtelomeric_reads.fasta'))
r1_subtelomeric_reads_output = open(r1_subtelomeric_reads_output_filepath , "a+")
if subtelomeric_reads_direction == "reverse":
subtelomeric_reads_output_directory = os.path.abspath(os.path.join(self._out_directory, 'subtelomeric_reads'))
os.makedirs(subtelomeric_reads_output_directory, exist_ok=True)
r2_subtelomeric_reads_output_filepath = os.path.abspath(os.path.join(subtelomeric_reads_output_directory, 'r2_subtelomeric_reads.fasta'))
r2_subtelomeric_reads_output = open(r2_subtelomeric_reads_output_filepath, "a+")
line_counter = 1
header_line = ""
# write all paired ends to file
with open(subtelomeric_reads_source_filepath) as subtelomeric_reads_source:
for line in subtelomeric_reads_source:
if line_counter % FQ_LINES_PER_READ == HEADER:
header_line = line
if line_counter % FQ_LINES_PER_READ == SEQUENCE:
# write sequence from FASTQ to file if its header is specified
# in the list tel_headers constructed earlier
if header_line in subtelomeric_reads_headers:
# edit header to match FASTA format
header_line = header_line.replace("@", ">")
if int(header_line.split(" ")[1].split(":")[0]) == FORWARD:
r1_subtelomeric_reads_output.write(header_line)
r1_subtelomeric_reads_output.write(line)
if int(header_line.split(" ")[1].split(":")[0]) == REVERSE:
r2_subtelomeric_reads_output.write(header_line)
r2_subtelomeric_reads_output.write(line)
line_counter += 1
if subtelomeric_reads_direction == "forward":
return r1_subtelomeric_reads_output_filepath
if subtelomeric_reads_direction == "reverse":
return r2_subtelomeric_reads_output_filepath
def _generate_alignments(self, muscle, clustered_reads_directory, alignment_output_directory):
for cluster_reads_file in os.listdir(clustered_reads_directory):
if cluster_reads_file.endswith(".fasta"):
cluster_reads_filepath = os.path.abspath(os.path.join(clustered_reads_directory, cluster_reads_file))
alignment_output_filename = cluster_reads_file#.split(".")[0] + ".aln"
alignment_output_filepath = os.path.abspath(os.path.join(alignment_output_directory, alignment_output_filename))
muscle_command = MuscleCommandline(muscle, input=cluster_reads_filepath, out=alignment_output_filepath)
muscle_command()
def _generate_consensus_sequences(self, clustered_reads_directory, clustered_reads_consensus_output):
for alignment_file in os.listdir(clustered_reads_directory):
if alignment_file.endswith(".fasta"):
alignment_filepath = os.path.abspath(os.path.join(clustered_reads_directory, alignment_file))
header_line = ">" + "contig" + alignment_file.split(".")[0].split("_")[-1] + "\n"
alignment = AlignIO.read(alignment_filepath, "fasta")
alignment_summary = AlignInfo.SummaryInfo(alignment)
consensus_sequence = str(alignment_summary.gap_consensus(ambiguous='N')) + "\n"
clustered_reads_consensus_output.write(header_line)
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zadanie/primer/prim 2.py | Adrenaline1a/demo-2.13 | 0 | 76345 | <filename>zadanie/primer/prim 2.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import math, datetime
if __name__ == '__main__':
math.cos(math.pi / 4)
datetime.date(2017, 3, 21)
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domoticz/plugin.py | lz129/ioplus-rpi | 5 | 169161 | <reponame>lz129/ioplus-rpi<filename>domoticz/plugin.py
# IOplus
#
# Author: <NAME>, 2020
#
#
"""
<plugin key="IOplus" name="Raspberry IOplus" author="<NAME>" version="0.1" externallink="">
<description>
IOplus 8 relay board on raspberry
</description>
<params>
<param field="Mode1" label="board number" width="75px" default="0"/>
<param field="Mode6" label="Debug" width="75px">
<options>
<option label="True" value="Debug"/>
<option label="False" value="Normal" default="true" />
</options>
</param>
</params>
</plugin>
"""
# units 1-8 are relays
# units 9-16 are inputs
import Domoticz
import libioplus as ioplus
class BasePlugin:
board = 0
running = 0
debug = 0
def set_relay(self,Unit, val):
if self.debug: Domoticz.Log("set_relay "+str(Unit)+" to "+str(val))
ioplus.setRelayCh(self.board, Unit, int(val))
def __init__(self):
return
def connection(self):
return
def onStart(self):
self.board=int(Parameters["Mode1"])
self.debug=Parameters["Mode6"]=="Debug"
Domoticz.Log("onStart - Plugin is starting, debug="+str(self.debug))
for x in range(1, 9):
if (x not in Devices): Domoticz.Device(Name="Relay_"+str(x), Unit=x, TypeName="Switch", Used=1).Create()
if (x+8 not in Devices): Domoticz.Device(Name="Input_"+str(x), Unit=x+8, TypeName="Switch", Used=1).Create()
self.set_relay(x, Devices[x].nValue)
Domoticz.Heartbeat(3)
self.running=1
def onStop(self):
Domoticz.Log("onStop - Plugin is stopping.")
def onConnect(self, Connection, Status, Description):
return
def onMessage(self, Connection, Data):
return
def onCommand(self, Unit, Command, Level, Hue):
val=Command=="On" and "1" or "0"
if (Unit in range(1,9)):
self.set_relay(Unit, Command=="On")
Devices[Unit].Update(int(val),val)
def onDisconnect(self, Connection):
unused=0
def onHeartbeat(self):
if self.running:
val=ioplus.getRelays(self.board)
inp=ioplus.getOpto(self.board)
if (self.debug): Domoticz.Log("read relays -> %02x, inputs -> %02x" % (val,inp))
for Unit in range(1,9):
val1=(val >> (Unit-1)) & 1
inp1=(inp >> (Unit-1)) & 1
if (Unit in Devices): Devices[Unit].Update(int(val1),str(val1))
if (Unit+8 in Devices): Devices[Unit+8].Update(int(inp1),str(val1))
global _plugin
_plugin = BasePlugin()
def onStart():
global _plugin
_plugin.onStart()
def onStop():
global _plugin
_plugin.onStop()
def onConnect(Connection, Status, Description):
global _plugin
_plugin.onConnect(Connection, Status, Description)
def onMessage(Connection, Data):
global _plugin
_plugin.onMessage(Connection, Data)
def onCommand(Unit, Command, Level, Hue):
global _plugin
_plugin.onCommand(Unit, Command, Level, Hue)
def onNotification(Name, Subject, Text, Status, Priority, Sound, ImageFile):
global _plugin
_plugin.onNotification(Name, Subject, Text, Status, Priority, Sound, ImageFile)
def onDisconnect(Connection):
global _plugin
_plugin.onDisconnect(Connection)
def onHeartbeat():
global _plugin
_plugin.onHeartbeat()
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] |
scripts/makeSwappHist.py | Miedema/MCNetwork | 0 | 133399 | #!/usr/bin/python3
from tools import *
from sys import argv
from os.path import join
import h5py
import matplotlib.pylab as plt
from matplotlib.patches import Wedge
import numpy as np
if len(argv) > 1:
pathToSimFolder = argv[1]
else:
pathToSimFolder = "../data/"
parameters, electrodes = readParameters(pathToSimFolder)
electrodeNumber = len(electrodes)
acceptorPos = np.zeros((int(parameters["acceptorNumber"]), 2))
try:
donorPos = np.zeros((int(parameters["donorNumber"]), 2))
except KeyError:
donorPos = np.zeros(
(int(parameters["acceptorNumber"] * parameters["compensationFactor"]), 2)
)
with open(join(pathToSimFolder, "device.txt")) as deviceFile:
line = next(deviceFile)
line = next(deviceFile)
for i in range(acceptorPos.shape[0]):
acceptorPos[i] = next(deviceFile).split(" ")
line = next(deviceFile)
line = next(deviceFile)
for i in range(donorPos.shape[0]):
donorPos[i] = next(deviceFile).split(" ")
# print(acceptorPos)
# print(donorPos)
electrodePositions = np.empty((len(electrodes), 2))
for i in range(len(electrodes)):
if parameters["geometry"] == "rect":
if electrodes[i][1] == 0:
electrodePositions[i] = [0, electrodes[i][0] * parameters["lenY"]]
if electrodes[i][1] == 1:
electrodePositions[i] = [
parameters["lenX"],
electrodes[i][0] * parameters["lenY"],
]
if electrodes[i][1] == 2:
electrodePositions[i] = [electrodes[i][0] * parameters["lenX"], 0]
if electrodes[i][1] == 3:
electrodePositions[i] = [
electrodes[i][0] * parameters["lenX"],
parameters["lenY"],
]
elif parameters["geometry"] == "circle":
electrodePositions[i] = [
parameters["radius"] * np.cos(electrodes[i][0] / 360 * 2 * np.pi),
parameters["radius"] * np.sin(electrodes[i][0] / 360 * 2 * np.pi),
]
# print(electrodePositions)
def colorMaker(x):
from matplotlib import colors
from scipy.interpolate import interp1d
cols = ["darkred", "darkgreen"]
rgbaData = np.array([colors.to_rgba(c) for c in cols])
rInterpolater = interp1d(np.linspace(0, 1, len(cols)), rgbaData[:, 0])
gInterpolater = interp1d(np.linspace(0, 1, len(cols)), rgbaData[:, 1])
bInterpolater = interp1d(np.linspace(0, 1, len(cols)), rgbaData[:, 2])
return np.array([rInterpolater(x), gInterpolater(x), bInterpolater(x), 1])
inp = ["0_0", "0_1", "1_0", "1_1"]
for fileNumber in [1, 2, 3, 4]:
# for fileNumber in [1]:
data = np.genfromtxt(
join(pathToSimFolder, f"swapTrackFile{fileNumber}.txt"),
delimiter=";",
dtype=int,
)
maxIndex = np.max(data)
added = (maxIndex + 1) * data[:, 0] + data[:, 1]
bins = np.bincount(added)
bins.resize(maxIndex + 1, maxIndex + 1)
absBins = bins + bins.T
absBins = absBins / np.max(absBins)
distances = []
swapps = []
for i in range(bins.shape[0]):
if i >= parameters["acceptorNumber"]:
x1, y1 = (
electrodePositions[i - int(parameters["acceptorNumber"])][0],
electrodePositions[i - int(parameters["acceptorNumber"])][1],
)
else:
x1, y1 = acceptorPos[i, 0], acceptorPos[i, 1]
for j in range(i):
if j >= parameters["acceptorNumber"]:
x2, y2 = (
electrodePositions[j - int(parameters["acceptorNumber"])][0],
electrodePositions[j - int(parameters["acceptorNumber"])][1],
)
else:
x2, y2 = acceptorPos[j, 0], acceptorPos[j, 1]
# ax.plot([x1,x2],[y1,y2],"k-",alpha=bins[i,j])
if (bins[i, j] + bins[j, i]) != 0:
currentRatio = bins[i, j] / (bins[i, j] + bins[j, i])
distances.append(np.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2))
swapps.append(absBins[i, j])
fig, ax = plt.subplots(1, 1, figsize=(4.980614173228346, 3.2))
ax.hist(
distances,
weights=swapps,
bins=50,
density=True,
histtype="step",
color="k",
range=[0, 100],
)
ax.set_xlabel(r"d [nm]")
ax.set_ylabel(r"P(swapp)")
plt.savefig(
join(pathToSimFolder, f"swapHist_{inp[fileNumber-1]}.png"),
bbox_inches="tight",
dpi=300,
)
# plt.show()
plt.close(fig)
fig, ax = plt.subplots(1, 1, figsize=(4.980614173228346, 3.2))
ax.hist(
distances,
weights=swapps,
bins=50,
density=True,
histtype="step",
color="k",
range=[0, 100],
log=True,
)
ax.set_xlabel(r"d [nm]")
ax.set_ylabel(r"P(swapp)")
plt.savefig(
join(pathToSimFolder, f"swapHist_{inp[fileNumber-1]}_log.png"),
bbox_inches="tight",
dpi=300,
)
# plt.show()
plt.close(fig)
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2
] |
sandbox/apps/app.py | django-oscar/django-oscar-gocardless | 3 | 101285 | <filename>sandbox/apps/app.py
from oscar.app import Shop
from apps.checkout.app import application as checkout_app
class GoCardlessShop(Shop):
checkout_app = checkout_app
shop = GoCardlessShop()
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src/sources/webnovelindonesia.py | Epicpkmn11/lightnovel-crawler | 1 | 75666 | <gh_stars>1-10
# -*- coding: utf-8 -*-
import logging
import re
from concurrent import futures
from ..utils.crawler import Crawler
logger = logging.getLogger('WEBNOVEL_INDONESIA')
chapter_list_url = 'https://webnovelindonesia.com/wp-json/writerist/v1/chapters?category=%s&perpage=100&order=ASC&paged=%s'
class WebnovelIndonesia(Crawler):
base_url = 'https://webnovelindonesia.com/'
def read_novel_info(self):
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('.breadcrumb .breadcrumb-item.active').text.strip()
logger.info('Novel title: %s', self.novel_title)
self.novel_cover = self.absolute_url(
soup.select_one('.section-novel img[class*="lazy"]')['data-src'])
logger.info('Novel cover: %s', self.novel_cover)
self.novel_author = soup.select_one('.section-novel li a[href*="/aut/"]').text.strip()
logger.info('Novel author: %s', self.novel_author)
possible_chapter_pages = soup.select('#js-chpater-jump > div.jump-to')
if not len(possible_chapter_pages):
possible_chapter_pages = [{'data-paged': '1'}]
# end if
novel_id = soup.select_one('#sortable-table')['data-category']
logger.info('Downloading chapters...')
futures_to_check = dict()
for div in possible_chapter_pages:
page = div['data-paged']
url = chapter_list_url % (novel_id, page)
task = self.executor.submit(self.extract_chapter_list, url)
futures_to_check[task] = page
# end for
temp_chapters = dict()
for future in futures.as_completed(futures_to_check):
page = int(futures_to_check[future])
temp_chapters[page] = future.result()
# end for
logger.info('Building sorted chapter list...')
for page in sorted(temp_chapters.keys()):
self.volumes.append({'id': page})
for chap in temp_chapters[page]:
chap['volume'] = page
chap['id'] = 1 + len(self.chapters)
self.chapters.append(chap)
# end for
# end for
# end def
def extract_chapter_list(self, url):
temp_list = []
logger.debug('Visiting: %s', url)
data = self.get_json(url)
for item in data:
temp_list.append({
'title': item['post_title'],
'url': self.absolute_url(item['permalink']),
})
# end for
return temp_list
# end def
def download_chapter_body(self, chapter):
'''Download body of a single chapter and return as clean html format'''
logger.info('Downloading %s', chapter['url'])
soup = self.get_soup(chapter['url'])
body = ''
for p in soup.select('#content > p'):
if p.text.strip():
body += str(p).strip()
# end if
# end for
return body
# end def
# end class
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base/server.py | memy85/2022_Federated-Learning-Base | 0 | 58426 | <reponame>memy85/2022_Federated-Learning-Base
from typing import List, Dict
import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras import models, layers, optimizers, initializers, losses, metrics
from base.networks import *
from base.client import *
from base.federated import *
class Server(object):
def __init__(self, network_config, server_config, network_module, aggregator):
"""
class for server
"""
self.num_rounds = server_config['num_rounds']
self.c_fraction = server_config['c_fraction']
self.n_clients = server_config['n_clients']
self.selected_clients_index = None
self.netmodule: Network = network_module(network_config)
self.init_global_network()
self.aggmodule: Aggregator = aggregator()
# results during a round
self.selected_client_n_k_list: List = None
self.selected_client_weight_list: List = None
self.selected_client_loss_list: List = None
# results for train
self.federated_loss_per_round: List = None
self.train_loss_per_round: List = None
self.train_eval_metric_per_round: List = None # acc , rmse, auc ..
self.valid_loss_per_round: List = None
self.valid_eval_metric_per_round: List = None # acc , rmse, auc ..
def learn(self, clients: List[Client], valid_data: List = None):
self.federated_loss_per_round = []
self.train_loss_per_round = []
self.train_eval_metric_per_round = []
if valid_data is not None:
self.valid_loss_per_round = []
self.valid_eval_metric_per_round = []
# send initialized global weights to all clients and set client's weights
self.send_global_weights()
for client in clients:
client.receive_global_weights()
client.set_global_weights(self.netmodule.network.get_weights())
# start learning round / client parally do
for round in range(self.num_rounds):
print("==========" * 5, f"Round {round + 1}")
self.train_one_round(clients)
# Valid
if valid_data is not None:
self.valid_one_round(valid_data)
print(f"Federated loss: {np.round(self.federated_loss_per_round[-1], 4)}, "
f"Train loss: {np.round(self.train_loss_per_round[-1], 4)}, "
f"Train {self.netmodule.evaluate_metric().name}: "
f"{np.round(self.train_eval_metric_per_round[-1], 4)}, \n"
f"Valid loss: {np.round(self.valid_loss_per_round[-1], 4)}, "
f"Train {self.netmodule.evaluate_metric().name}: "
f"{np.round(self.valid_eval_metric_per_round[-1], 4)}, "
)
# send and receive final global weights
self.send_global_weights()
for client in clients:
client.receive_global_weights()
client.set_global_weights(self.netmodule.network.get_weights())
def train_one_round(self, clients: List[Client]): # server
# select clients
self.select_clients() # 이 때는 client 객체 필요 없음.
selected_clients = [client for client in clients if
client.client_id in self.selected_clients_index] # client list
n_sample = sum(client.n_k_sample for client in selected_clients) # total n
# clients update parallel
self.clients_update_one_round(selected_clients)
self.receive_weights()
# aggregate clients weights
federated_weights, federated_loss = self.aggmodule.aggregate(
n_sample=n_sample,
selected_client_n_k_list=self.selected_client_n_k_list,
selected_client_loss_list=self.selected_client_loss_list,
selected_client_weight_list=self.selected_client_weight_list
)
self.set_global_weights(federated_weights) # set global weights as server weights
self.federated_loss_per_round.append(federated_loss)
# train eval for all client's input
predictions = self.netmodule.network(np.concatenate([client.input for client in selected_clients], axis=0))
labels = np.concatenate([client.label for client in selected_clients], axis=0)
# train loss
train_loss = (tf.reduce_sum(self.netmodule.loss_metric()(labels, predictions))).numpy()
self.train_loss_per_round.append(train_loss)
# train eval metric
train_eval_metric = (tf.reduce_sum(self.netmodule.evaluate_metric()(labels, predictions))).numpy()
self.train_eval_metric_per_round.append(train_eval_metric)
def valid_one_round(self, valid_data: List):
"""
:param valid_data: List(input_valid, label_valid)
:return:
"""
# valid eval for external validation dataset
predictions = self.netmodule.network(valid_data[0])
labels = valid_data[1]
# valid loss
valid_loss = (tf.reduce_sum(self.netmodule.loss_metric()(labels, predictions))).numpy()
self.valid_loss_per_round.append(valid_loss)
# train eval metric
valid_eval_metric = (tf.reduce_sum(self.netmodule.evaluate_metric()(labels, predictions))).numpy()
self.valid_eval_metric_per_round.append(valid_eval_metric)
def clients_update_one_round(self, selected_clients: List[Client]): # clients
self.selected_client_n_k_list = []
self.selected_client_weight_list = []
self.selected_client_loss_list = []
for client in selected_clients: # parallel
client.receive_global_weights() # receive weights from server
client.set_global_weights(self.netmodule.network.get_weights()) # set global weights
client.learn() # client learn
# send client information to server (weights, loss, n_k_sample)
client.send_weights()
self.selected_client_n_k_list.append(client.n_k_sample)
self.selected_client_weight_list.append(client.netmodule.network.get_weights())
self.selected_client_loss_list.append(client.netmodule.results['loss'][-1]) # TODO acc 추가?
def init_global_network(self):
self.netmodule.create_network()
self.netmodule.network._name = 'server_network'
def select_clients(self):
n_selected_clients = max(int(self.n_clients * self.c_fraction), 1)
self.selected_clients_index = np.random.choice(range(1, self.n_clients + 1), n_selected_clients, replace=False)
print(f"{len(self.selected_clients_index)} selected clients: ", self.selected_clients_index,
f"with C fraction {self.c_fraction}")
def set_global_weights(self, global_weights):
self.netmodule.network.set_weights(global_weights) # set global weights as server weights
def send_global_weights(self):
pass # not implemented, statement for client - server communication
def receive_weights(self):
"""
receive weights from selected clients
:return:
"""
pass # not implemented, statement for client - server communication
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] |
video_capture/plotting.py | FrostyDesigner/Python_Scripts | 1 | 46919 | <reponame>FrostyDesigner/Python_Scripts
from motion_capture import df
from bokeh.plotting import figure, show, output_file
from bokeh.models import HoverTool, ColumnDataSource
#convert start and end columns to strings for easy reading
df["Start_string"]=df["Start"].dt.strftime("%Y-%m-%d %H:%M:%S")
df["End_string"]=df["End"].dt.strftime("%Y-%m-%d %H:%M:%S")
cds=ColumnDataSource(df)
#commented because "responsive" does not work
#p=figure(x_axis_type='datetime', height=100, width=500, responsive=True, title="Motion Graph")
p=figure(x_axis_type='datetime', height=200, width=500, title="Motion Graph")
#remove ticks on y axis
p.yaxis.minor_tick_line_color=None
#remove grid lines from y grid
p.ygrid[0].ticker.desired_num_ticks=1
#instantiate hover tool
hover=HoverTool(tooltips=[("Start", "@Start_string"),("End", "@End_string")])
p.add_tools(hover)
#create the quad using left, right, up, down
#q=p.quad(left=df["Start"], right=df["End"], bottom=0, top=1, color="green")
#notice the source is cds (ColumnDataSource) - if you use a source the dataframe is not necessary
q=p.quad(left="Start", right="End", bottom=0, top=1, color="green", source=cds)
output_file("Graph.html")
show(p) | [
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703,
9527,
29889,
1420,
1159,
13,
4294,
29898,
29886,
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2
] |
src/lib/request/__init__.py | arnulfojr/simple-pos | 1 | 60639 |
from src import is_json
| [
1,
29871,
13,
3166,
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1053,
338,
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3126,
13,
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2
] |
var/spack/repos/builtin/packages/r-pkgload/package.py | kkauder/spack | 2,360 | 199910 | <filename>var/spack/repos/builtin/packages/r-pkgload/package.py
# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class RPkgload(RPackage):
"""Simulate Package Installation and Attach
Simulates the process of installing a package and then attaching it. This
is a key part of the 'devtools' package as it allows you to rapidly iterate
while developing a package."""
homepage = "https://cloud.r-project.org/package=pkgload"
url = "https://cloud.r-project.org/src/contrib/pkgload_1.0.2.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/pkgload/"
version('1.1.0', sha256='189d460dbba2b35fa15dd59ce832df252dfa654a5acee0c9a8471b4d70477b0d')
version('1.0.2', sha256='3186564e690fb05eabe76e1ac0bfd4312562c3ac8794b29f8850399515dcf27c')
depends_on('r-cli', when='@1.1.0:', type=('build', 'run'))
depends_on('r-crayon', when='@1.1.0:', type=('build', 'run'))
depends_on('r-desc', type=('build', 'run'))
depends_on('r-pkgbuild', type=('build', 'run'))
depends_on('r-rlang', type=('build', 'run'))
depends_on('r-rprojroot', type=('build', 'run'))
depends_on('r-rstudioapi', type=('build', 'run'))
depends_on('r-withr', type=('build', 'run'))
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ibmsecurity/isam/web/runtime/object.py | zone-zero/ibmsecurity | 46 | 184941 | <reponame>zone-zero/ibmsecurity
import logging
logger = logging.getLogger(__name__)
# *** WORK IN PROGRESS - module not done yet
def get_all(isamAppliance, isamUser, object='/', admin_domain='Default'):
"""
Retrieve a list of objects
"""
ret_obj = isamAppliance.invoke_post("Retrieve a list of objects",
"/isam/pdadmin/objectlistandshowext/v1", {
"admin_id": isamUser.username,
"admin_pwd": <PASSWORD>,
"admin_domain": admin_domain,
"object": object
})
ret_obj['changed'] = False
return ret_obj
def get(isamAppliance, isamUser, object, admin_domain='Default'):
"""
Retrieve a specific object
"""
ret_obj = isamAppliance.invoke_post("Retrieve a specific object",
"/isam/pdadmin/objectshowext/v1", {
"admin_id": isamUser.username,
"admin_pwd": <PASSWORD>,
"admin_domain": admin_domain,
"object": object
})
ret_obj['changed'] = False
return ret_obj
def compare(isamAppliance1, isamAppliance2, isamUser, admin_domain='Default'):
"""
Compare objects between two appliances
"""
ret_obj1 = get_all(isamAppliance1, isamUser, '/', admin_domain)
ret_obj2 = get_all(isamAppliance2, isamUser, '/', admin_domain)
for obj in ret_obj1['data']:
ret_obj = get(isamAppliance1, isamUser=isamUser, object=obj['id'], admin_domain=admin_domain)
obj['script'] = ret_obj['data']['contents']
for obj in ret_obj2['data']:
ret_obj = get(isamAppliance2, isamUser=isamUser, object=obj['id'], admin_domain=admin_domain)
obj['script'] = ret_obj['data']['contents']
import ibmsecurity.utilities.tools
return ibmsecurity.utilities.tools.json_compare(ret_obj1, ret_obj2, deleted_keys=[])
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cnn_training/vgg2_2_tfrecords_loose.py | bioidiap/bob.bio.face | 4 | 57384 | <filename>cnn_training/vgg2_2_tfrecords_loose.py
#!/usr/bin/env python
# coding: utf-8
"""
Crop VGG2 with loose crop based on bounding box
Usage:
vgg2_2_tfrecords.py <vgg-path> <output-path> [--factor=<kn>]
vgg2_2_tfrecords.py -h | --help
Options:
-h --help Show this screen.
--factor=<kn> Crop Factor [default: 0.3]
"""
from docopt import docopt
import numpy as np
import os
import bob.io.image
import bob.io.base
import tensorflow as tf
import sys
from datetime import datetime
def _bytes_feature(value):
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
def _int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
def search_landmark(landmark_path, img_path):
with open(landmark_path) as f:
next(f)
for line in f:
line = line.split(",")
if img_path in line[0]:
landmarks = np.array([float(line[i]) for i in [1, 2, 3, 4]])
return {
"topleft": (landmarks[1], landmarks[0]),
"dimensions": (landmarks[3], landmarks[2]),
"bottomright": (
landmarks[1] + landmarks[3],
landmarks[0] + landmarks[2],
),
}
else:
return None
def extend_annotations(annotations, img_bottom_right, factor=0.3):
width = annotations["dimensions"][1]
height = annotations["dimensions"][0]
new_annotations = {"topleft": [0, 0], "bottomright": [0, 0]}
new_annotations["topleft"][0] = max(0, annotations["topleft"][0] - height * factor)
new_annotations["topleft"][1] = max(0, annotations["topleft"][1] - width * factor)
new_annotations["bottomright"][0] = min(
img_bottom_right[1], annotations["bottomright"][0] + height * factor
)
new_annotations["bottomright"][1] = min(
img_bottom_right[0], annotations["bottomright"][1] + width * factor
)
return new_annotations
from bob.bio.face.preprocessor import FaceCrop
def align(image, annotations, cropped_image_size=(126, 126), factor=0.3):
cropped_image_height, cropped_image_width = cropped_image_size
img_bottom_right = (image.shape[1], image.shape[2])
new_annotations = extend_annotations(annotations, img_bottom_right, factor=factor)
cropped_positions = {"topleft": (0, 0), "bottomright": cropped_image_size}
cropper = FaceCrop(
cropped_image_size=cropped_image_size,
cropped_positions=cropped_positions,
color_channel="rgb",
fixed_positions=None,
annotator=None,
)
return bob.io.image.to_matplotlib(
cropper.transform([image], [new_annotations])[0]
).astype("uint8")
def get_id_by_line(line):
return line.split("/")[0]
def generate_tfrecord(
base_path, landmark_path, file_list, output_tf_record_path, indexes, factor=0.3
):
def write_single_line_tfrecord(writer, image, offset, user_id):
# Serializing
serialized_img = image.tobytes()
# Writing
feature = {
"data": _bytes_feature(serialized_img),
"label": _int64_feature(offset),
"key": _bytes_feature(str.encode(user_id)),
}
example = tf.train.Example(features=tf.train.Features(feature=feature))
writer.write(example.SerializeToString())
with tf.io.TFRecordWriter(output_tf_record_path) as tf_writer:
current_id = None
with open(file_list) as f:
for file_name in f.readlines():
user_id = get_id_by_line(file_name)
if user_id in indexes:
img = bob.io.base.load(
os.path.join(base_path, file_name).rstrip("\n")
)
l_name = file_name.rstrip(".jpg\n")
if current_id != user_id:
current_id = user_id
sys.stdout.write(
f"Writing user {current_id}. {str(datetime.now())} \n"
)
sys.stdout.flush()
landmarks = search_landmark(landmark_path, l_name)
if landmarks is None:
raise ValueError(f"Landmark for {file_name} not found!")
# aligned_image = align(img, annotations)
aligned_image = align(
img, landmarks, factor=factor, cropped_image_size=(126, 126)
)
bob.io.base.save(bob.io.image.to_bob(aligned_image), "xuucu.png")
write_single_line_tfrecord(
tf_writer, aligned_image, int(indexes[user_id]), user_id
)
def map_indexes(image_path, n_chunks):
"""
Create a dictionary mapping the ID to VGG2-ID, like:
{0: 'n000001'],
1: 'n000002']}
"""
indexes = sorted(list(set([l.split("/")[0] for l in open(image_path).readlines()])))
identities_map = {indexes[i]: i for i in range(len(indexes))}
# SPLIT THE DICTIONARY IN TOTAL_CHUNKS
indexes_as_list = list(identities_map.items())
dict_as_list = np.array_split(indexes_as_list, n_chunks)
dicts = [dict(d) for d in dict_as_list]
return dicts
if __name__ == "__main__":
args = docopt(__doc__)
VGG2_PATH = args["<vgg-path>"]
LANDMARK_PATH = os.path.join(VGG2_PATH, "bb_landmark", "loose_bb_train.csv")
if "SGE_TASK_LAST" in os.environ:
TOTAL_CHUNKS = int(os.environ["SGE_TASK_LAST"])
CURRENT_CHUNK = int(os.environ["SGE_TASK_ID"]) - 1
else:
TOTAL_CHUNKS = 1
CURRENT_CHUNK = 0
# TOTAL_CHUNKS = 140
# CURRENT_CHUNK = 0
TRAINING_LIST = os.path.join(VGG2_PATH, "train_list.txt")
# TEST_LIST = os.path.join(VGG2_PATH, "test_list.txt")
# MAP ALL INDEXES
indexes = map_indexes(TRAINING_LIST, TOTAL_CHUNKS)
generate_tfrecord(
os.path.join(VGG2_PATH, "train"),
LANDMARK_PATH,
TRAINING_LIST,
os.path.join(
args["<output-path>"], f"train_vgg2_chunk{CURRENT_CHUNK}.tfrecords"
),
indexes[CURRENT_CHUNK],
factor=float(args["--factor"]),
)
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450/Nagendra/greedy/Swap and Maximize .py | Nagendracse1/Competitive-Programming | 3 | 14701 | #code https://practice.geeksforgeeks.org/problems/swap-and-maximize/0
for _ in range(int(input())):
n = int(input())
arr = list(map(int, input().split()))
arr.sort()
max = 0
for i in range(n//2):
max -= 2*arr[i]
max += 2*arr[n-i-1]
print(max) | [
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its.py | rohan2546/TechArmy | 1 | 122045 | import pymongo
import datetime
import json
from flask import Flask, render_template, request, url_for, redirect, abort, jsonify, make_response
from flask_cors import CORS, cross_origin
from bson import json_util
from bson.json_util import dumps,ObjectId
import random
app=Flask(__name__)
@app.route('/addProblem',methods=['POST','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def addProblem():
if request.method == 'POST':
post= request.json
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&[email protected]/test?retryWrites=true&w=majority")
db=client.hack_se
posts = db.problem
post_id = posts.insert_one(post)
client.close()
return "added"
@app.route('/addContest',methods = ['POST','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def addContest():
if request.method == 'POST':
post = request.json
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&<EMAIL>/test?retryWrites=true&w=majority")
db=client.hack_se
posts = db.contest
posts1 = db.problem
posts2 = db.user
pid = post["problem_id"]
em = post["user"]
if (posts1.find({"problem_id":pid}) is not None) and (posts2.find({"email":em}) is not None):
post_id=posts.insert_one(post)
return "added"
else:
return "not added"
client.close()
else:
return jsonify({}),405
@app.route('/addUser',methods= ['POST','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def addUser():
if request.method == 'POST':
post=request.json
em = post["email"]
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&<EMAIL>Zg2fA@<EMAIL>.mongodb.net/test?retryWrites=true&w=majority")
db=client.hack_se
posts = db.user
if posts.find({"email": em}) is None:
post_id = posts.insert_one(post)
return "added"
else:
return "user exists"
client.close()
else:
return jsonify({}),405
@app.route('/getProblemDescription',methods= ['GET','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def getProblemDescription():
if request.method == 'GET':
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&[email protected]/test?retryWrites=true&w=majority")
db=client.hack_se
pid=request.args.get('problem_id',type=str)
ab=db.problem.find_one({"problem_id":pid})
ab1=json.loads(json_util.dumps(ab))
return ab1,201
else:
return jsonify({}),405
@app.route('/getTestCases',methods= ['GET','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def getTestCases():
if request.method == 'GET':
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&<EMAIL>.net/test?retryWrites=true&w=majority")
db=client.hack_se
pid=request.args.get('problem_id',type=str)
ab=db.problem.find_one({"problem_id":pid})
ab1 = json.loads(json_util.dumps(ab))
cd=ab1["Test_case"]
return cd,201
else:
return jsonify({}),405
@app.route('/getBestScore',methods= ['GET','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def getBestScore():
if request.method == 'GET':
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&9Q4GTZg2fA@<EMAIL>.mongodb.<EMAIL>/test?retryWrites=true&w=majority")
db=client.hack_se
pid=request.args.get('Contest_id',type=str)
sid=request.args.get('Student_id',type=str)
ab=db.contest.find_one({"Contest_id":pid})
ab1 = json.loads(json_util.dumps(ab))
cd=ab1["Student_list"]
for key,val in cd.items():
if key==sid:
return val["Best_score"]
else:
return jsonify({}),405
@app.route('/addBestCode',methods= ['PUT','OPTIONS'])
@cross_origin(origin='*',headers=['Content-Type','Authorization'])
def addBestCode():
if request.method == 'PUT':
client = pymongo.MongoClient("mongodb+srv://rohansharma1606:_kwB&<EMAIL>/test?retryWrites=true&w=majority")
db=client.hack_se
post=request.json
cid=post["Contest_id"]
sid=post["Student_id"]
ns=post["Best_score"]
bc=post["Best_code"]
bcl=post["Best_code_language"]
ab=db.contest.find_one({"Contest_id":cid})
ab1 = json.loads(json_util.dumps(ab))
cd=ab1["Student_list"]
new_val={}
n_val={}
for key,val in cd.items():
if key==sid and ns>val["Best_score"]:
new_val={"Student_id":sid,"Best_code":bc,"Best_score":ns,"Best_code_language":bcl}
old_val=val
dict={"$set":new_val}
myco=db.contest["Student_list"]
mycol=myco[sid]
db=db.contest
else:
return jsonify({}),405
if __name__ == '__main__':
app.run(debug=True) | [
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] |
warp.py | RezaFirouzii/fum-delta-vision | 0 | 6451 | import math
import imageio
import cv2 as cv
import numpy as np
import transformer
def fix_rotation(img):
img_copy = img.copy()
img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
rows, cols = img.shape
img = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY_INV, 15, 9)
kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (3, 3))
img = cv.morphologyEx(img, cv.MORPH_OPEN, kernel)
img = cv.medianBlur(img, 3)
contours, hierarchy = cv.findContours(img, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
roi = max(contours, key=cv.contourArea)
x, y, w, h = cv.boundingRect(roi)
corners = [[x, y], [x + w, y], [x, y + h], [x + w, y + h]]
src = np.float32(corners)
# src = np.reshape(src, (len(src), 1, 2))
# perimeter = cv.arcLength(src, True)
# corners = cv.approxPolyDP(src, perimeter // 10, True)
# corners = np.vstack(corners)
dst = np.float32([[0, 0], [cols, 0], [0, rows], [cols, rows]])
matrix = cv.getPerspectiveTransform(src, dst)
rotated_img = cv.warpPerspective(img_copy, matrix, (cols, rows))
cv.imshow('', rotated_img)
D1 = 105
D2 = 175
D3 = 275
if __name__ == "__main__":
cap = cv.VideoCapture('samples/delta.mp4')
if not cap.isOpened():
raise IOError("Video was not opened!")
mse = 0
count = 0
reader = imageio.get_reader('samples/delta.mp4')
fps = reader.get_meta_data()['fps']
writer = imageio.get_writer('samples/result.mp4', fps=fps)
while True:
res, frame = cap.read()
if not res:
break
mean_error = 0
holes_count = 0
img = frame.copy()
cv.imshow('dfa', img)
frame = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
frame_copy = frame.copy()
# frame = cv.adaptiveThreshold(frame, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY_INV, 15, 9)
# kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (3, 3))
# frame = cv.morphologyEx(frame, cv.MORPH_OPEN, kernel)
# frame = cv.medianBlur(frame, 3)
# contours, hierarchy = cv.findContours(frame, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
# roi = max(contours, key=cv.contourArea)
# x, y, w, h = cv.boundingRect(roi)
x, y, w, h = 115, 0, 445, 360
img = img[y: y+h, x: x+w]
img = transformer.rotate_along_axis(img, theta=40)
frame_copy = frame_copy[y: y+h, x: x+w]
frame_copy = transformer.rotate_along_axis(frame_copy, theta=40)
# cv.imshow('', frame_copy)
# cv.rectangle(frame_copy, (x, y), (x + w, y + h), (0, 255, 0), 2)
# cv.drawContours(frame_copy, roi, -1, (0, 0, 255), 2)
# res, mask = cv.threshold(frame_copy, 0, 255, cv.THRESH_BINARY)
# frame_copy = cv.bitwise_and(frame_copy, frame_copy, mask=mask)
# corners = cv.goodFeaturesToTrack(frame_copy, 1000, 0.0001, 1)
# corners = list(sorted(corners, key=lambda x: x[0][1]))
# print(corners[-1], corners[-2])
# print()
# corners = np.array([[38, 293], [407, 293]])
# for item in corners:
# # x, y = map(int, item.ravel())
# x, y = item
# cv.circle(img, (x, y), 5, (0, 0, 255), -1)
src = np.float32([[0, 0], [w, 0], [38, 293], [407, 293]])
dst = np.float32([[0, 0], [w, 0], [30, h], [w - 30, h]])
matrix = cv.getPerspectiveTransform(src, dst)
img = cv.warpPerspective(img, matrix, (w, h))
cv.imshow('', img)
img_copy = img.copy()
img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
img = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY_INV, 15, 9)
kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (3, 3))
img = cv.morphologyEx(img, cv.MORPH_OPEN, kernel)
img = cv.medianBlur(img, 3)
origin = (w // 2 + 4, h // 2 + 2)
o1, o2 = origin
r = w // 2 + 1
ORIGIN = (0, 0)
R = 300 # mm
contours, hierarchy = cv.findContours(img, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
contours = list(filter(lambda x: 50 < cv.contourArea(x) < 175, contours))
factor = 0.1
smooth_contours = []
for i in range(len(contours)):
epsilon = factor * cv.arcLength(contours[i], True)
approx = cv.approxPolyDP(contours[i], epsilon, True)
x, y, width, height = cv.boundingRect(approx)
area = width*height
if len(approx) == 4 and 75 < area < 200:
smooth_contours.append(contours[i])
center, radius = cv.minEnclosingCircle(approx)
radius = int(radius)
center = tuple(map(int, center))
x, y = center
X = ((x - o1) * R) / r
Y = ((y - o2) * R) / r
X, Y = round(X, 2), round(Y, 2)
cv.circle(img_copy, center, radius, (0, 255, 0), 2)
cv.putText(img_copy, str((X, Y)), center, cv.FONT_HERSHEY_SIMPLEX, 0.3, (255, 0, 255, 255), 1, cv.LINE_AA)
e1, e2, e3 = map(lambda d: abs(math.hypot(X, Y) - d), [D1, D2, D3])
error = min(e1, e2, e3)
if error < 10:
mean_error += error ** 2
holes_count += 1
cv.circle(img_copy, origin, 4, (0, 0, 255), -1)
# cv.line(img_copy, origin, (origin[0], origin[1]), (255, 0, 255), 2)
mean_error /= holes_count
mse += mean_error
count += 1
cv.imshow("Final", img_copy)
writer.append_data(img_copy)
# cv.imshow("Chg", img)
if cv.waitKey(30) == 27:
break
print("E:", mse / count, "N:", count)
writer.close()
cap.release()
cv.destroyAllWindows() | [
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] |
RSA.py | SamuelBuhan/chiffrement_python | 0 | 145890 | <gh_stars>0
from Crypto.PublicKey import RSA
from Crypto.Random import get_random_bytes
from Crypto.Cipher import AES, PKCS1_OAEP
"""encrypt data """
data = "I met aliens in UFO. Here is the map.".encode("utf-8")
file_out = open("encrypted_data.bin", "wb")
recipient_key = RSA.import_key(open("receiver.pem").read())
session_key = get_random_bytes(16)
# Encrypt the session key with the public RSA key
cipher_rsa = PKCS1_OAEP.new(recipient_key)
enc_session_key = cipher_rsa.encrypt(session_key)
# Encrypt the data with the AES session key
cipher_aes = AES.new(session_key, AES.MODE_EAX)
ciphertext, tag = cipher_aes.encrypt_and_digest(data)
[ file_out.write(x) for x in (enc_session_key, cipher_aes.nonce, tag, ciphertext) ]
file_out.close()
"""decrypt data"""
file_in = open("encrypted_data.bin", "rb")
private_key = RSA.import_key(open("private.pem").read())
enc_session_key, nonce, tag, ciphertext = \
[ file_in.read(x) for x in (private_key.size_in_bytes(), 16, 16, -1) ]
# Decrypt the session key with the private RSA key
cipher_rsa = PKCS1_OAEP.new(private_key)
session_key = cipher_rsa.decrypt(enc_session_key)
# Decrypt the data with the AES session key
cipher_aes = AES.new(session_key, AES.MODE_EAX, nonce)
data = cipher_aes.decrypt_and_verify(ciphertext, tag)
print(data.decode("utf-8")) | [
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esp_sdk/extensions/base_object.py | zimmermanc/esp-sdk-python | 6 | 123073 | class BaseObject(object):
"""
A base class to provide common features to all models.
"""
| [
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scripts/lint.py | OwenDeng1993/Husky | 117 | 149915 | #!/usr/bin/env python
import getopt
import os
import subprocess
import sys
CPPLINT_PY = os.path.dirname(os.path.abspath(__file__)) + '/cpplint.py'
CPPLINT_EXTENSIONS = ['cpp', 'hpp', 'tpp']
CPPLINT_FILTERS = ['-whitespace/indent', '-runtime/references', '+build/include_alpha', '-build/c++11', '-legal/copyright', '-readability/casting']
CPPLINT_LINE_LENGTH = 120
default_dirs = [
'base',
'core',
'io',
'lib',
'master',
'examples',
]
ignored_dirs = [
'io/input/flume_connector',
]
cpp_suffix = '*.[cht]pp'
husky_root = os.getenv('HUSKY_ROOT', '.')
os.chdir(husky_root)
def usage():
print("Run command as: $ lint.py $HUSKY_ROOT or $PATH_OF_DIR")
def list_files(paths=None):
dirs = None
if paths is not None:
dirs = paths
if dirs is None:
dirs, files = default_dirs, []
for d in dirs:
cmd = 'find {} -name "{}"'.format(d, cpp_suffix)
res = subprocess.check_output(cmd, shell=True).rstrip()
files += res.split('\n')
removes = []
for f in files:
for d in ignored_dirs:
if f.find(d) != -1:
removes.append(f)
for r in removes:
files.remove(r)
return files
cmd = 'find {} -name {}'.format(' '.join(dirs), cpp_suffix)
res = subprocess.check_output(cmd, shell=True).rstrip()
return res.split('\n')
def main(argv=None):
if argv is None:
argv = sys.argv
try:
opts, args = getopt.getopt(argv[1:], "h", ["help"])
except getopt.GetoptError as err:
print(err) # will print something like "option -a not recognized"
usage()
return 2
for o, _ in opts:
if o in ("-h", "--help"):
usage()
return 0
files = None
if len(args) == 0:
files = list_files()
else:
files = list_files(args)
if files is None:
print('[Error] Path {} does not exist'.format(args.path))
return 2
cpplint_cmd = [
CPPLINT_PY,
'--linelength={}'.format(CPPLINT_LINE_LENGTH),
'--extensions={}'.format(','.join(CPPLINT_EXTENSIONS)),
]
if (len(CPPLINT_FILTERS) > 0):
cpplint_cmd.append('--filter={}'.format(','.join(CPPLINT_FILTERS)))
run_cmd = ' '.join(cpplint_cmd) + ' ' + ' '.join(files)
os.system(run_cmd)
if __name__ == '__main__':
sys.exit(main())
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] |
sdk/python/pulumi_azure_native/authorization/v20180101preview/role_definition.py | sebtelko/pulumi-azure-native | 0 | 194432 | <filename>sdk/python/pulumi_azure_native/authorization/v20180101preview/role_definition.py<gh_stars>0
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
from ._inputs import *
__all__ = ['RoleDefinitionArgs', 'RoleDefinition']
@pulumi.input_type
class RoleDefinitionArgs:
def __init__(__self__, *,
scope: pulumi.Input[str],
assignable_scopes: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
description: Optional[pulumi.Input[str]] = None,
permissions: Optional[pulumi.Input[Sequence[pulumi.Input['PermissionArgs']]]] = None,
role_definition_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
role_type: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a RoleDefinition resource.
:param pulumi.Input[str] scope: The scope of the role definition.
:param pulumi.Input[Sequence[pulumi.Input[str]]] assignable_scopes: Role definition assignable scopes.
:param pulumi.Input[str] description: The role definition description.
:param pulumi.Input[Sequence[pulumi.Input['PermissionArgs']]] permissions: Role definition permissions.
:param pulumi.Input[str] role_definition_id: The ID of the role definition.
:param pulumi.Input[str] role_name: The role name.
:param pulumi.Input[str] role_type: The role type.
"""
pulumi.set(__self__, "scope", scope)
if assignable_scopes is not None:
pulumi.set(__self__, "assignable_scopes", assignable_scopes)
if description is not None:
pulumi.set(__self__, "description", description)
if permissions is not None:
pulumi.set(__self__, "permissions", permissions)
if role_definition_id is not None:
pulumi.set(__self__, "role_definition_id", role_definition_id)
if role_name is not None:
pulumi.set(__self__, "role_name", role_name)
if role_type is not None:
pulumi.set(__self__, "role_type", role_type)
@property
@pulumi.getter
def scope(self) -> pulumi.Input[str]:
"""
The scope of the role definition.
"""
return pulumi.get(self, "scope")
@scope.setter
def scope(self, value: pulumi.Input[str]):
pulumi.set(self, "scope", value)
@property
@pulumi.getter(name="assignableScopes")
def assignable_scopes(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
Role definition assignable scopes.
"""
return pulumi.get(self, "assignable_scopes")
@assignable_scopes.setter
def assignable_scopes(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "assignable_scopes", value)
@property
@pulumi.getter
def description(self) -> Optional[pulumi.Input[str]]:
"""
The role definition description.
"""
return pulumi.get(self, "description")
@description.setter
def description(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "description", value)
@property
@pulumi.getter
def permissions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['PermissionArgs']]]]:
"""
Role definition permissions.
"""
return pulumi.get(self, "permissions")
@permissions.setter
def permissions(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['PermissionArgs']]]]):
pulumi.set(self, "permissions", value)
@property
@pulumi.getter(name="roleDefinitionId")
def role_definition_id(self) -> Optional[pulumi.Input[str]]:
"""
The ID of the role definition.
"""
return pulumi.get(self, "role_definition_id")
@role_definition_id.setter
def role_definition_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "role_definition_id", value)
@property
@pulumi.getter(name="roleName")
def role_name(self) -> Optional[pulumi.Input[str]]:
"""
The role name.
"""
return pulumi.get(self, "role_name")
@role_name.setter
def role_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "role_name", value)
@property
@pulumi.getter(name="roleType")
def role_type(self) -> Optional[pulumi.Input[str]]:
"""
The role type.
"""
return pulumi.get(self, "role_type")
@role_type.setter
def role_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "role_type", value)
class RoleDefinition(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
assignable_scopes: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
description: Optional[pulumi.Input[str]] = None,
permissions: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PermissionArgs']]]]] = None,
role_definition_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
role_type: Optional[pulumi.Input[str]] = None,
scope: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Role definition.
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[Sequence[pulumi.Input[str]]] assignable_scopes: Role definition assignable scopes.
:param pulumi.Input[str] description: The role definition description.
:param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PermissionArgs']]]] permissions: Role definition permissions.
:param pulumi.Input[str] role_definition_id: The ID of the role definition.
:param pulumi.Input[str] role_name: The role name.
:param pulumi.Input[str] role_type: The role type.
:param pulumi.Input[str] scope: The scope of the role definition.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: RoleDefinitionArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Role definition.
:param str resource_name: The name of the resource.
:param RoleDefinitionArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(RoleDefinitionArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
assignable_scopes: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
description: Optional[pulumi.Input[str]] = None,
permissions: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['PermissionArgs']]]]] = None,
role_definition_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
role_type: Optional[pulumi.Input[str]] = None,
scope: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = RoleDefinitionArgs.__new__(RoleDefinitionArgs)
__props__.__dict__["assignable_scopes"] = assignable_scopes
__props__.__dict__["description"] = description
__props__.__dict__["permissions"] = permissions
__props__.__dict__["role_definition_id"] = role_definition_id
__props__.__dict__["role_name"] = role_name
__props__.__dict__["role_type"] = role_type
if scope is None and not opts.urn:
raise TypeError("Missing required property 'scope'")
__props__.__dict__["scope"] = scope
__props__.__dict__["name"] = None
__props__.__dict__["type"] = None
alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:authorization/v20180101preview:RoleDefinition"), pulumi.Alias(type_="azure-native:authorization:RoleDefinition"), pulumi.Alias(type_="azure-nextgen:authorization:RoleDefinition"), pulumi.Alias(type_="azure-native:authorization/v20150701:RoleDefinition"), pulumi.Alias(type_="azure-nextgen:authorization/v20150701:RoleDefinition")])
opts = pulumi.ResourceOptions.merge(opts, alias_opts)
super(RoleDefinition, __self__).__init__(
'azure-native:authorization/v20180101preview:RoleDefinition',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None) -> 'RoleDefinition':
"""
Get an existing RoleDefinition resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = RoleDefinitionArgs.__new__(RoleDefinitionArgs)
__props__.__dict__["assignable_scopes"] = None
__props__.__dict__["description"] = None
__props__.__dict__["name"] = None
__props__.__dict__["permissions"] = None
__props__.__dict__["role_name"] = None
__props__.__dict__["role_type"] = None
__props__.__dict__["type"] = None
return RoleDefinition(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="assignableScopes")
def assignable_scopes(self) -> pulumi.Output[Optional[Sequence[str]]]:
"""
Role definition assignable scopes.
"""
return pulumi.get(self, "assignable_scopes")
@property
@pulumi.getter
def description(self) -> pulumi.Output[Optional[str]]:
"""
The role definition description.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
The role definition name.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter
def permissions(self) -> pulumi.Output[Optional[Sequence['outputs.PermissionResponse']]]:
"""
Role definition permissions.
"""
return pulumi.get(self, "permissions")
@property
@pulumi.getter(name="roleName")
def role_name(self) -> pulumi.Output[Optional[str]]:
"""
The role name.
"""
return pulumi.get(self, "role_name")
@property
@pulumi.getter(name="roleType")
def role_type(self) -> pulumi.Output[Optional[str]]:
"""
The role type.
"""
return pulumi.get(self, "role_type")
@property
@pulumi.getter
def type(self) -> pulumi.Output[str]:
"""
The role definition type.
"""
return pulumi.get(self, "type")
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] |
modeloMarkowitz.py | HubertRonald/ModeloMarkowitz | 1 | 125109 | import numpy as np
import pandas as pd
import cvxopt as opt
from cvxopt import solvers #, blas
from matplotlib import pyplot as plt
plt.style.use('seaborn')
np.random.seed(9062020)
# Cargar y limpiar datos
df = pd.read_csv("stocks.csv", sep=",", engine="python")
#���Field 1 la columna tiene caracteres extranios
df.columns = ['Field1' if i == 0 else x for i, x in enumerate(df.columns)]
df.set_index(df.columns[0], inplace=True)
# Seleccionamos 5 activos al azar
activos = np.random.permutation(df.columns)[:5]
plt.figure(figsize=(8,6))
plt.title('Historico de Algunos Activos', color='gray')
for activo in activos:
plt.plot(df[activo].to_numpy(), label=activo)
plt.ylabel('Precio del Activo', color='gray')
plt.xlabel('Observaciones', color='gray')
plt.legend(loc='upper left')
# Por que usar rendimiento logaritmicos
# https://quantdare.com/por-que-usar-rendimientos-logaritmicos/
df = df / df.shift(1)
df.dropna(inplace=True)
log_df = np.log(df)
print(log_df)
# Grafico con Rendimientos historicos
plt.figure(figsize=(8,6))
plt.title('Rendimiento de Todos los Activos', color='gray')
plt.plot(df.to_numpy(), alpha=0.2)
plt.ylabel('Rendimiento del Activo', color='gray')
plt.xlabel('Observaciones', color='gray')
def metricas_historicas_portafolio(portafolio, dias_anual):
"""
Da un pequenio reporte sobre las observaciones de
cada activo contenido en el portafolio, para
devolver finalmente dos matrices
`portafolio`: es un dataframe de observaciones (filas)
por activos (columnas) historico
`dias_anual`: es un entero que indica cuantos dias
tiene el anio, asumiendose para ellos que las
observaciones contenidas en `portafolio` son diarias
`return`: devuelve las matrices o arrays de rendimientos
esperados y la de covarianza del portafolio historico,
asi como el numero de activos
"""
# Metricas Historicas
activos_en_portafolio = portafolio.shape[1]
rendimientos_anual = dias_anual * portafolio.mean()
sigma_de_rendimientos_anual = dias_anual * portafolio.std()
varianza_de_rendimientos_anual = dias_anual * portafolio.std() ** 2 # diagonal de la covarianza de rendimientos
covarianza_de_rendimientos_anual = dias_anual * portafolio.cov()
# Reporte de Historicos
print(f"\nNumero de Activos:\n{activos_en_portafolio}")
print(f"\nRendimiento:\n{rendimientos_anual}")
print(f"\nDesviacion Estandar:\n{sigma_de_rendimientos_anual}")
print(f"\nVarianza:\n{varianza_de_rendimientos_anual}")
print(f"\nCovarianza:\n{covarianza_de_rendimientos_anual}")
# Matrices con las Estadisticas Hitoricas de Interes
# la variable `C`es mayuscula
p = np.asmatrix(rendimientos_anual.to_numpy())
C = np.asmatrix(covarianza_de_rendimientos_anual.to_numpy())
return p, C, activos_en_portafolio
p, C, numero_de_activos = metricas_historicas_portafolio(log_df, 252)
#print(p ,p.shape[1])
def resultados_portafolio(p,w,C):
"""
Dados unos pesos de colocacion para un
portafolio y teniendose los rendimientos y
covarianzas historicas, se obtiene el
rendimiento y volatilidad del portafolio
`p`: matriz con rendimientos historicos del
portafolio
`w`: peso que se empleara para colocar los
los fondos en los activos correspondientes
del portafolio
`C`: matriz con la covarianza historico del
portafolio
`return`: el redimiento y riesgo (volatilida)
del portafolio
"""
mu = w * p.T # Rendimiento Esperado
sigma = np.sqrt(w * C * w.T) # Volatilidad
return mu, sigma
def simular_pesos_portafolio(numero_de_activos):
"""
Generar pesos aleatorios para cada
activo en el portafolio
`numero_de_activos`: es entero
`return`:El peso de cada uno de los
activos en el portafolio cuya suma es 1
como matriz
"""
pesos = np.random.random(numero_de_activos)
pesos *= sum([np.random.binomial(1, 0.08, numero_de_activos) for _ in range(2)])
pesos = np.asmatrix(pesos / sum(pesos) )
return pesos
def simular_portafolio(p, C, numero_de_activos, libre_riesgo=0, limite_volatilidad=1):
"""
Genera el redimiento y la desviacion estandar
de una posible combinacion en la inversion
de cada activo para un portafolio dado
`p`: matriz con rendimientos historicos del
portafolio
`C`: matriz con la covarianza historico del
portafolio
`numero_de_activos`: entero que indica la cantidad
de activos en el portafolio
`libre de riesgo`: flotante que va de 0 a 1
`limite_volatilidad`: es para mantener la
volatilidad hasta un tope durante la
simulacion
`return`: el peso de inversion, el rendimiento
esperado (mu) y la desviacion estandar (sigma)
tambien conocida como volatilidad para el
portafolio generado así como el Sharpe Ratio
todas las salidas son arrays
"""
# Generar una posible combinacion del portafolio
p = p
w = simular_pesos_portafolio(numero_de_activos)
C = C
mu, sigma = resultados_portafolio(p,w,C)
sharpe_ratio = (mu - libre_riesgo) / sigma
# Esta recursividad reduce los valores atípicos
# para mantener el portafolio de interés
# tambien se puede desarrollar con `while` pero
# se requiere más codigo
if sigma > limite_volatilidad:
return simular_portafolio(p, C, numero_de_activos, libre_riesgo, limite_volatilidad)
return w, mu, sigma, sharpe_ratio
peso_activos, rendimiento, volatilidad, sharpe_ratio = simular_portafolio(p, C, numero_de_activos)
print("-"*40)
print('---- Portafolio Simulado ----')
print("-"*40)
print(f"\nSharpe Ratio: {sharpe_ratio}")
print(f"""
Pesos Del Portafolio Simulado:\n{peso_activos}
\nLos Pesos Suman: {peso_activos.sum():.4f}
""")
print(f"\nRedimiento del Portafolio Simulado:{rendimiento}")
print(f"\nVolatilidad del Portafolio Simulado:{volatilidad}\n")
def simulacion_de_portafolios(numero_de_portafolios, p, C,
numero_de_activos, libre_riesgo=0, limite_volatilidad=1):
"""
Genera los rendimientos y volatidades para un conjunto
de portafolios
`numero_de_portafolios`: entero que indica la
cantidad de replicas o simulaciones a efectuarse
`p`: matriz con rendimientos historicos del
portafolio
`C`: matriz con la covarianza historico del
portafolio
`numero_de_activos`: entero que indica la cantidad
de activos en el portafolio
`libre de riesgo`: flotante que va de 0 a 1
`limite_volatilidad`: es para mantener la
volatilidad hasta un tope durante la
simulacion
`return`: los pesos, rendimientos esperados así
como las volatidades `desviacion estandar`
para cada uno de los portafolios simulados
"""
pesos, rendimientos, volatilidades, sharper_ratios = zip(*[
simular_portafolio(p, C, numero_de_activos, libre_riesgo, limite_volatilidad)
for _ in range(numero_de_portafolios)
])
pesos, rendimientos, volatilidades, sharper_ratios = \
np.array(pesos), np.array(rendimientos), np.array(volatilidades), np.array(sharper_ratios)
return pesos, rendimientos, volatilidades, sharper_ratios
pesos, rendimientos, volatilidades, sharper_ratios = simulacion_de_portafolios(
numero_de_portafolios=1000,
p=p,
C=C,
numero_de_activos=numero_de_activos,
libre_riesgo=0
)
# Metricas Sharper
def rsharpe_maximo(sharper_ratios, rendimientos, volatilidades):
maximo_sharpe_ratio = sharper_ratios.max()
indice_maximo_sharpe_ratio = sharper_ratios.argmax()
pesos_optimos_simulados = pesos[indice_maximo_sharpe_ratio, :]
maximo_sharpe_ratio_rendimiento = rendimientos[indice_maximo_sharpe_ratio]
maximo_sharpe_ratio_volatilidad = volatilidades[indice_maximo_sharpe_ratio]
print("-" * 50)
print('---- Estadisticas Sharper Ratio ----')
print("-" * 50)
print(f"\nMaximo Sharpe Ratio: {maximo_sharpe_ratio}")
print(f"""Pesos Del Portafolio:\n{pesos_optimos_simulados}
\nLos Pesos Suman: {pesos_optimos_simulados.sum():.4f}
""" )
print(f"\nRedimiento del Maximo Sharpe Ratio:{maximo_sharpe_ratio_rendimiento}")
print(f"\nVolatilidad del Maximo Sharpe Ratio:{maximo_sharpe_ratio_volatilidad}\n")
return maximo_sharpe_ratio, maximo_sharpe_ratio_volatilidad, maximo_sharpe_ratio_rendimiento
# Estadisticas de Montecarlo
maximo_sharpe_ratio, maximo_sharpe_ratio_volatilidad, maximo_sharpe_ratio_rendimiento = rsharpe_maximo(sharper_ratios, rendimientos, volatilidades)
plt.figure(figsize=(8,6))
plt.title('Rendimientos y Volatilidades\n Portafolios Simulados', color='gray')
plt.scatter(volatilidades, rendimientos, c=sharper_ratios, cmap='cool')
plt.colorbar(label=r"$Sharpe\ Ratio$")
# Optimo Sharpe Ratio Simulado
plt.scatter(
maximo_sharpe_ratio_volatilidad,
maximo_sharpe_ratio_rendimiento,
c='orange', s=60, edgecolors='gray', label=f'Sharpe Ratio Optimo Simulado = {maximo_sharpe_ratio:.4f}'
)
plt.ylabel(r'$Rendimiento$', color='gray')
plt.xlabel(r'$Volatilidad\ \sigma$', color='gray')
plt.legend(loc="upper left")
# Resolviendo el modelo cuadratico
# http://cvxopt.org/userguide/coneprog.html
# http://cvxopt.org/examples/book/portfolio.html
# http://cvxopt.org/examples/tutorial/qp.html
def portafolio_optimo(p, C, numero_de_activos):
"""
Genera los puntos para la Frontera Eficiente
`p`: matriz con rendimientos historicos del
portafolio
`C`: matriz con la covarianza historico del
portafolio
`numero_de_activos`: entero que indica la cantidad
de activos en el portafolio
`retorna`: arrays, de los pesos de cada portafolio
correspondientes a cada punto de la frontera
eficiente, siendo dichos puntos el par rendimiento
y volatilidad
"""
# Se establece saltos discretos para hallar la
# la frontera eficiente estos seran los
# `targets` u objetivos que se fijan para optimizar
N = 100
n = numero_de_activos
#mus = np.power(10, 5 * np.arange(N) / N - 1) # tiene que ser lista tolist()
mus = [ 10**(5.0*t/N-1.0) for t in range(N) ]
# convertir el p y C a matrices del tipo cvxopt
# en el caso de p se trabaja con su transpuesta
pbar = opt.matrix(p.T)
S = opt.matrix(C)
# Crear las matrices de restricciones
# Gx <= h
G = -opt.matrix(np.eye(n)) # matriz identidad negativa n x n
h = opt.matrix(0.0, (n ,1))
# Ax = b
A = opt.matrix(1.0, (1, n))
b = opt.matrix(1.0) # La suma de los pesos es 1
# Calcular los pesos de la frontera eficiente
# Empleando Programacion Cuadratica
# Pero primero silenciamos el solver (es opcional)
solvers.options['show_progress'] = False
portafolios = [solvers.qp(mu*S, -pbar, G, h, A, b)['x'] for mu in mus]
# Calcular los rendimientos y volatilidades o riesgos
# para la frontera eficiente
# Estas implementaciones funcionan... hay que importar "blas"
# pero el codigo que esta fuera de este codigo
# requiere que se redimensionen los rendimientos, volatilidades
# para que funcionen
#rendimientos = [blas.dot(pbar, x) for x in portafolios]
#volatilidades = [np.sqrt(blas.dot(x, S*x)) for x in portafolios]
rendimientos, volatilidades = zip(*[
resultados_portafolio(p, np.array(w).T, C) for w in portafolios
])
# Calcular el portafolio optimo
#pesos = solvers.qp(opt.matrix(x1 * S), -pbar, G, h, A, b)['x'] # # No funciona para lo que se quiere hacer mas adelante
pesos = [np.asarray(x) for x in portafolios]
pesos = np.asarray(pesos)
rendimientos = np.asarray(rendimientos)
volatilidades = np.asarray(volatilidades)
return pesos, rendimientos, volatilidades
w_optimos, mu_optimos, sigma_optimos = portafolio_optimo(p, C, numero_de_activos)
########################################
# Frontera Eficiente y Simulacion
########################################
plt.figure(figsize=(8,6))
plt.title('Frontera eficiente', color='gray')
# Frontera eficiente
plt.plot(sigma_optimos.reshape((1,-1))[0], mu_optimos.reshape((1,-1))[0], 'y-o', color='gray', alpha=0.4, label='Frontera Eficiente')
# Simulados
plt.scatter(volatilidades, rendimientos, c=sharper_ratios, cmap='cool')
plt.colorbar(label=r"$Sharpe\ Ratio$")
# Optimo Sharpe Ratio Simulado
plt.scatter(
maximo_sharpe_ratio_volatilidad,
maximo_sharpe_ratio_rendimiento,
c='orange', s=60, edgecolors='gray', label=f'Sharpe Ratio Optimo Simulado = {maximo_sharpe_ratio:.4f}'
)
plt.ylabel(r'$Rendimiento$', color='gray')
plt.xlabel(r'$Volatilidad\ \sigma$', color='gray')
plt.legend(loc="upper left")
########################################
# Ratio de Sharper
########################################
print("\nVerificar cuales suman 1: ")
print(np.array([x.sum() for x in w_optimos]))
filtrar_pesos_positivos = np.array([(x>=0).all() for x in w_optimos])
print("\nVerificar que todos los pesos sean >= 0: ")
print(filtrar_pesos_positivos)
print(w_optimos.shape, mu_optimos.shape, sigma_optimos.shape)
w_optimos = w_optimos[filtrar_pesos_positivos]
mu_optimos = mu_optimos [filtrar_pesos_positivos]
sigma_optimos = sigma_optimos[filtrar_pesos_positivos]
print("\nVerificar que todos los pesos sean >= 0: ")
print(np.array([(x>=0).all() for x in w_optimos]))
print(w_optimos.shape, mu_optimos.shape, sigma_optimos.shape)
libre_riesgo = 0
rsharpe_optimos = (mu_optimos - libre_riesgo) / sigma_optimos
rsharpe_optimos = rsharpe_optimos.reshape((1,-1)).reshape((1,-1)) # quitarle dimensiones
maximo_rsharpe, maximo_rsharpe_volatilidad, maximo_rsharpe_rendimiento = rsharpe_maximo(rsharpe_optimos, mu_optimos, sigma_optimos)
plt.figure(figsize=(8,6))
plt.title('Sharpers de la Frontera Eficiente\nCon Pesos no Negativos', color='gray')
# Optimo Sharpe Ratio Frontera Eficiente
plt.scatter(
rsharpe_optimos[0].argmax(),
maximo_rsharpe,
c='#90ff1e', s=100, edgecolors='gray', label=f'Sharpe Ratio = {maximo_rsharpe:.4f}'
)
plt.plot(rsharpe_optimos[0], 'y-o', color='dodgerblue', alpha=0.4)
plt.ylabel(r'$Sharpe\ Ratio$', color='gray')
plt.xlabel(r'$Observaciones$', color='gray')
plt.legend(loc="upper left")
########################################
# Todo Junto:
# Ratio de Sharper Optimo
# Frontera Eficiente y Simulacion
########################################
w_optimos, mu_optimos, sigma_optimos = portafolio_optimo(p, C, numero_de_activos)
libre_riesgo = 0
rsharpe_optimos = (mu_optimos - libre_riesgo) / sigma_optimos
rsharpe_optimos = rsharpe_optimos.reshape((1,-1)).reshape((1,-1)) # quitarle dimensiones
plt.figure(figsize=(8,6))
plt.title('Frontera eficiente', color='gray')
# Frontera eficiente
plt.plot(sigma_optimos.reshape((1,-1))[0], mu_optimos.reshape((1,-1))[0], 'y-o', color='gray', alpha=0.4, label='Frontera Eficiente')
# Simulados
plt.scatter(volatilidades, rendimientos, c=sharper_ratios, cmap='cool')
plt.colorbar(label=r"$Sharpe\ Ratio$")
# Optimo Sharpe Ratio Frontera Eficiente
idx_rshape_optimo = np.where(rsharpe_optimos[0] == maximo_rsharpe)
plt.scatter(
sigma_optimos.reshape((1, -1))[0][idx_rshape_optimo], # eje volatilidad
mu_optimos.reshape((1,-1))[0][idx_rshape_optimo], # eje rendimientos
c='#90ff1e', s=100, edgecolors='gray', label=f'Sharpe Ratio Optimo = {maximo_rsharpe:.4f}'
)
# Optimo Sharpe Ratio Simulado
plt.scatter(
maximo_sharpe_ratio_volatilidad,
maximo_sharpe_ratio_rendimiento,
c='orange', s=100, edgecolors='gray', label=f'Sharpe Ratio Optimo Simulado = {maximo_sharpe_ratio:.4f}'
)
plt.ylabel(r'$Rendimiento$', color='gray')
plt.xlabel(r'$Volatilidad\ \sigma$', color='gray')
plt.legend(loc="upper left")
########################################
# Se muestran todos los lienzos
########################################
plt.show()
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2118,
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12609,
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12927,
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2433,
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1454,
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2011,
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2011,
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2011,
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2011,
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2011,
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26732,
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22111,
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1122,
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17910,
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29937,
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29889,
12181,
29961,
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13,
1753,
1121,
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637,
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13,
4706,
360,
2255,
22660,
8928,
359,
316,
28853,
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1702,
443,
13,
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2011,
2142,
324,
601,
343,
3006,
29875,
355,
852,
1232,
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24038,
343,
13,
4706,
18838,
13956,
16095,
3603,
5070,
29892,
409,
14403,
3530,
560,
13,
4706,
7697,
9043,
343,
1700,
271,
309,
2368,
628,
2011,
2142,
324,
601,
13,
13,
4706,
421,
29886,
6998,
1775,
7485,
378,
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24038,
3603,
4869,
628,
13,
4706,
2011,
2142,
324,
601,
13,
13,
4706,
421,
29893,
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8928,
29877,
712,
409,
29593,
2518,
1702,
28853,
279,
1232,
13,
4706,
1232,
6299,
359,
427,
1232,
5039,
359,
3928,
13833,
13,
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628,
2011,
2142,
324,
601,
13,
13,
539,
421,
29907,
6998,
1775,
7485,
378,
425,
18838,
13956,
1362,
3603,
1417,
628,
13,
4706,
2011,
2142,
324,
601,
13,
13,
4706,
421,
2457,
6998,
560,
2654,
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343,
28201,
1484,
313,
1555,
271,
309,
1458,
29897,
13,
4706,
628,
2011,
2142,
324,
601,
13,
1678,
9995,
13,
1678,
3887,
353,
281,
334,
282,
29889,
29911,
462,
965,
396,
390,
355,
9043,
3423,
546,
912,
13,
1678,
269,
2934,
353,
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29889,
3676,
29898,
29893,
334,
315,
334,
281,
29889,
29911,
29897,
965,
396,
3684,
271,
309,
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13,
13,
1678,
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3887,
29892,
269,
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13,
13,
268,
13,
13,
1753,
1027,
1070,
29918,
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359,
29918,
637,
2142,
324,
601,
29898,
1949,
1489,
29918,
311,
29918,
11236,
359,
1125,
13,
1678,
9995,
29871,
13,
4706,
3251,
279,
8928,
359,
8080,
1061,
2363,
1702,
9747,
13,
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1044,
4243,
427,
560,
2011,
2142,
324,
601,
13,
13,
4706,
421,
1949,
1489,
29918,
311,
29918,
11236,
359,
6998,
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875,
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13,
13,
4706,
421,
2457,
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6489,
8928,
29877,
316,
9747,
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316,
1232,
29871,
13,
308,
5039,
359,
427,
560,
2011,
2142,
324,
601,
2723,
3761,
2533,
29874,
831,
29871,
29896,
13,
308,
1986,
1775,
7485,
13,
1678,
9995,
13,
1678,
8928,
359,
353,
7442,
29889,
8172,
29889,
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29898,
1949,
1489,
29918,
311,
29918,
11236,
359,
29897,
13,
1678,
8928,
359,
334,
29922,
2533,
4197,
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29889,
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29889,
2109,
7615,
29898,
29896,
29892,
29871,
29900,
29889,
29900,
29947,
29892,
17910,
29918,
311,
29918,
11236,
359,
29897,
363,
903,
297,
3464,
29898,
29906,
29897,
2314,
13,
1678,
8928,
359,
353,
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29889,
294,
5344,
29898,
5547,
359,
847,
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5547,
359,
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13,
13,
1678,
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8928,
359,
13,
13,
13,
13,
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1027,
1070,
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637,
2142,
324,
601,
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29886,
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315,
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29918,
311,
29918,
11236,
359,
29892,
13220,
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1484,
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568,
29918,
1555,
271,
309,
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29922,
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1125,
13,
1678,
9995,
13,
4706,
3251,
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560,
2654,
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343,
425,
553,
6071,
12401,
707,
392,
279,
13,
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316,
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16337,
427,
425,
297,
3259,
13,
4706,
316,
9747,
1044,
4243,
1702,
443,
2011,
2142,
324,
601,
270,
912,
13,
13,
4706,
421,
29886,
6998,
1775,
7485,
378,
7697,
24038,
3603,
4869,
628,
13,
4706,
2011,
2142,
324,
601,
13,
13,
539,
421,
29907,
6998,
1775,
7485,
378,
425,
18838,
13956,
1362,
3603,
1417,
628,
13,
4706,
2011,
2142,
324,
601,
29871,
13,
13,
4706,
421,
1949,
1489,
29918,
311,
29918,
11236,
359,
6998,
875,
1489,
712,
1399,
983,
425,
5107,
2368,
13,
4706,
316,
5039,
359,
427,
560,
2011,
2142,
324,
601,
13,
13,
4706,
421,
492,
1030,
316,
28201,
1484,
6998,
1652,
327,
1647,
712,
2947,
316,
29871,
29900,
263,
29871,
29896,
13,
13,
4706,
421,
2576,
568,
29918,
1555,
271,
309,
2368,
6998,
831,
1702,
13694,
759,
425,
13,
4706,
1700,
271,
309,
2368,
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443,
304,
412,
6372,
425,
13,
4706,
1027,
352,
16337,
13,
13,
4706,
421,
2457,
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560,
8928,
29877,
316,
297,
3259,
29892,
560,
7697,
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13,
4706,
17451,
912,
313,
2589,
29897,
343,
425,
553,
6071,
12401,
707,
392,
279,
313,
3754,
29897,
13,
4706,
3882,
819,
11515,
1458,
1986,
1700,
271,
309,
2368,
1702,
560,
29871,
13,
4706,
2011,
2142,
324,
601,
1176,
912,
12606,
1986,
560,
1383,
279,
412,
17450,
601,
13,
4706,
17824,
1869,
4497,
8817,
1487,
7049,
13,
1678,
9995,
13,
268,
13,
1678,
396,
3251,
279,
1185,
29125,
5769,
16337,
628,
2011,
2142,
324,
601,
13,
1678,
282,
353,
282,
13,
1678,
281,
353,
1027,
1070,
29918,
5547,
359,
29918,
637,
2142,
324,
601,
29898,
1949,
1489,
29918,
311,
29918,
11236,
359,
29897,
13,
1678,
315,
353,
315,
13,
13,
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3887,
29892,
269,
2934,
353,
1121,
2255,
29918,
637,
2142,
324,
601,
29898,
29886,
29892,
29893,
29892,
29907,
29897,
13,
13,
268,
13,
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528,
279,
412,
29918,
3605,
601,
353,
313,
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448,
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29918,
2722,
1484,
29897,
847,
269,
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13,
1678,
396,
14192,
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440,
2368,
10032,
1232,
659,
2361,
472,
28304,
4869,
13,
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396,
1702,
13694,
759,
560,
2011,
2142,
324,
601,
316,
1006,
743,
13,
1678,
396,
3882,
819,
409,
11493,
25001,
279,
378,
421,
8000,
29952,
7046,
13,
1678,
396,
409,
5054,
10883,
3627,
15234,
5973,
13,
1678,
565,
269,
2934,
1405,
2485,
568,
29918,
1555,
271,
309,
2368,
29901,
13,
4706,
736,
1027,
1070,
29918,
637,
2142,
324,
601,
29898,
29886,
29892,
315,
29892,
17910,
29918,
311,
29918,
11236,
359,
29892,
13220,
29918,
2722,
1484,
29892,
2485,
568,
29918,
1555,
271,
309,
2368,
29897,
13,
268,
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] |
pyproteome/motifs/icelogo.py | white-lab/pyproteome | 8 | 1602378 | <reponame>white-lab/pyproteome
from __future__ import division
# Built-ins
import logging
import requests
try:
from IPython.display import Image
except ImportError:
Image = None
from . import motif
LOGGER = logging.getLogger('pyproteome.icelogo')
ICELOGO_BASE = 'http://iomics.ugent.be/icelogoserver'
def make_logo(data, f, m=None, letter_mod_types=None, **kwargs):
nmer_args = motif.get_nmer_args(kwargs)
fore = [
n
for n in motif.generate_n_mers(
data.filter(f)['Sequence'],
**nmer_args
)
if not m or m.match(n)
]
back = [
n
for n in motif.generate_n_mers(
data['Sequence'],
**nmer_args
)
]
return icelogo(
fore, back,
**kwargs
)
def icelogo(
foreground, background,
title='',
width=800,
height=600,
pvalue=0.05,
scoring='foldChange',
):
'''
Wraps calls to iceLogo [1]_, returning an image showing the enrichment of a
sequence in a foreground set compared to a background set.
Parameters
----------
foreground : list of str
background : list of str
title : str, optional
width : int, optional
height : int, optional
pval : float, optional
scoring : string, optional
Returns
-------
fig : :class:`IPython.display.Image`
Notes
-----
.. [1] <NAME>., <NAME>., <NAME>., <NAME>., &
<NAME>. (2009). Improved visualization of protein consensus
sequences by iceLogo. Nature Methods, 6(11), 786–787.
http://doi.org/10.1038/nmeth1109-786
'''
if len(foreground) < 1 or len(background) < 1:
return None
assert scoring in ('percentage', 'foldChange')
letter_width = len(background[0])
s = requests.Session()
response = s.post(
'{}/data/logo'.format(ICELOGO_BASE),
data={
'positiveSequences': '\n'.join(foreground),
'reference': 'reference_set',
'negativeSequences': '\n'.join(background),
'start': -(letter_width // 2),
'visualisationType': 'iceLogo',
'species': '',
'colors[]': [
'2b00e3', 'da00ba', 'd20012', 'bcc800', 'cd6300', '0000e5',
'c9af00', 'd60064', 'cf3d00', 'd8008f', 'cb8900', 'd4003b',
'8000df', 'd11500', '94c600', '5600e1', 'd200db', 'a900dd',
'47c200', '21c000', '6dc400',
],
'width': width,
'height': height,
'pValue': pvalue,
'scoringSystem': scoring,
'aaMatrix': '',
'substitutionMatrix': '',
},
)
response.raise_for_status()
path = response.content.decode('utf-8')
png = '{}/generated_images/{}.png'.format(ICELOGO_BASE, path)
if Image:
return Image(url=png)
else:
return png
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exceptions_and_logging/logging_settings.py | Agamiru/exceptions_and_logging | 1 | 175362 | <reponame>Agamiru/exceptions_and_logging
import logging
import os
EXTRA_KWARGS = ["err_type"]
DEFAULT_LOGGER_NAME = "default_logger"
MSG_FORMAT = '%(asctime)s - APPLICATION ERROR - %(levelname)s\n' \
'Error Type: %(err_type)s\n' \
'Error Message: %(message)s\n'
module_dir = os.path.dirname(__file__)
DEFAULT_LOG_CONFIG_FILE = os.path.join(module_dir, "logging_config.yaml")
class DefaultFormatter(logging.Formatter):
"""
Default message formatter. Adds extra double lines for readability.
"""
def __init__(
self, fmt=MSG_FORMAT,
datefmt='%m/%d/%Y %I:%M:%S %p'
):
super().__init__(fmt=fmt, datefmt=datefmt)
def format(self, record):
s = super().format(record)
return s + "\n" * 2
default_dict_config = {
"version": 1,
"formatters": {
"default": {
"()": DefaultFormatter,
"format": MSG_FORMAT,
}
},
"handlers": {
"console": {
"class": 'logging.StreamHandler',
"formatter": "default"
},
"file": {
"class": "logging.FileHandler",
"formatter": "default",
"filename": "application.log",
"encoding": "utf-8"
}
},
"loggers": {
DEFAULT_LOGGER_NAME: {
"level": "ERROR",
"handlers": ["console", "file"]
},
},
'root': {
'level': 'DEBUG',
'handlers': ["console"]
},
}
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core/management_utils.py | crydotsnake/djangogirls | 446 | 28144 | import djclick as click
from django.conf import settings
from django.utils.translation import gettext_lazy as _
from .forms import AddOrganizerForm
from .slack_client import slack
# "Get organizers info" functions used in 'new_event' and 'copy_event' management commands.
def get_main_organizer():
"""
We're asking user for name and address of main organizer, and return
a list of dictionary.
"""
team = []
click.echo(_("Let's talk about the team. First the main organizer:"))
main_name = click.prompt(click.style(
"First and last name", bold=True, fg='yellow'
))
main_email = click.prompt(click.style(
"E-mail address", bold=True, fg='yellow'
))
team.append({'name': main_name, 'email': main_email})
click.echo("All right, the main organizer is {0} ({1})".format(main_name, main_email))
return team
def get_team(team):
"""
We're asking user for names and address of the rest of the team,
and append that to a list we got from get_main_organizer
"""
add_team = click.confirm(click.style(
"Do you want to add additional team members?", bold=True, fg='yellow'
), default=False)
i = 1
while add_team:
i += 1
name = click.prompt(click.style(
f"First and last name of #{i} member", bold=True, fg='yellow'
))
email = click.prompt(click.style(
f"E-mail address of #{i} member", bold=True, fg='yellow'
))
if len(name) > 0:
team.append({'name': name, 'email': email})
click.echo(
f"All right, the #{i} team member of Django Girls is {name} ({email})"
)
add_team = click.confirm(click.style(
"Do you want to add additional team members?", bold=True, fg='yellow'
), default=False)
return team
def create_users(team, event):
"""
Create or get User objects based on team list
"""
members = []
for member in team:
member['event'] = event.pk
form = AddOrganizerForm(member)
user = form.save()
members.append(user)
return members
def brag_on_slack_bang(city, country, team):
"""
This is posting a message about Django Girls new event to #general channel on Slack!
"""
if settings.ENABLE_SLACK_NOTIFICATIONS:
text = f":django_pony: :zap: Woohoo! :tada: New Django Girls alert! " \
f"Welcome Django Girls {city}, {country}. " \
f"Congrats {', '.join(['{} {}'.format(x.first_name, x.last_name) for x in team])}!"
slack.chat.post_message(
channel='#general',
text=text,
username='Django Girls',
icon_emoji=':django_heart:'
)
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29918,
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11283,
13,
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2
] |
es_sink/es_sink/__init__.py | avmi/community | 305 | 192747 | __all__ = ['descriptor',
'es_transport',
'flushing_buffer',
'line_buffer',
'sqs_transport',
'transport_exceptions',
'transport_result',
'transport_utils'] | [
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one_off/extractor.py | snspam/sn_spam | 0 | 162076 | import re
import pandas as pd
import util as ut
import argparse
def extract(df, target_col='text', info_type='link', out_dir=''):
ut.makedirs(out_dir)
df = df[['com_id', target_col]]
ut.out('target column: %s, info type: %s' % (target_col, info_type))
if info_type == 'text':
ut.out('writing info to csv...\n')
df.to_csv(out_dir + info_type + '.csv', index=None)
return
d, i = {}, 0
regex = _get_regex(info_type)
df = df[['com_id', target_col]]
for ndx, com_id, text in df.itertuples():
i += 1
if i % 100000 == 0:
ut.out('(%d/%d)...' % (i, len(df)))
info = _get_items(text, regex)
if info != '':
d[com_id] = info
if len(d) > 0:
info_df = pd.DataFrame.from_dict(d, orient='index').reset_index()
info_df.columns = ['com_id', info_type]
fname = info_type + '.csv'
ut.out(str(info_df))
ut.out('writing info to csv...\n')
info_df.to_csv(out_dir + fname, index=None)
else:
ut.out('No extractions made...')
# private
def _get_regex(info_type='link'):
d = {}
d['hashtag'] = re.compile(r'(#\w+)')
d['mention'] = re.compile(r'(@\w+)')
d['link'] = re.compile(r'(http[^\s]+)')
return d[info_type]
def _get_items(text, regex, str_form=True):
items = regex.findall(str(text))
result = sorted([x.lower() for x in items])
if str_form:
result = ''.join(result)
return result
if __name__ == '__main__':
description = 'Extracts elements from strings (links, hashtags, etc.)'
parser = argparse.ArgumentParser(description=description)
parser.add_argument('-t', '--target_col', default='text',
help='column to extract from, default: %(default)s')
parser.add_argument('-i', '--info_type', default='hashtag',
help='type of element to extract default: %(default)s')
parser.add_argument('-d', '--domain', default='twitter',
help='social network, default: %(default)s')
parser.add_argument('-n', '--nrows', default=None,
help='number of rows to read, default: %(default)s')
args = parser.parse_args()
domain = args.domain
target_col = args.target_col
info_type = args.info_type
nrows = int(args.nrows) if args.nrows is not None else None
data_dir = 'independent/data/' + domain + '/'
out_dir = 'independent/data/' + domain + '/extractions/'
ut.out('reading in data...')
df = pd.read_csv(data_dir + 'comments.csv', nrows=nrows)
extract(df, target_col=target_col, info_type=info_type, out_dir=out_dir)
| [
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openconnect-cli.py | tcpipuk/OpenConnect-FE | 0 | 26741 | #!/usr/bin/env python3
import argparse, pexpect
from getpass import getpass
from time import sleep
# Set up argument parser
parser = argparse.ArgumentParser(prog='openconnect-cli', description='Automate logins to the OpenConnect SSL VPN client')
# Type of VPN to initiate
parser_type = parser.add_mutually_exclusive_group(required=False)
parser_type.add_argument('--anyconnect', action='store_true', default=False, help='Cisco AnyConnect SSL VPN')
parser_type.add_argument('--fortinet', action='store_true', default=False, help='Fortinet FortiClient SSL VPN')
parser_type.add_argument('--pulsesecure', action='store_true', default=False, help='Juniper Network Connect / Pulse Secure SSL VPN')
parser_type.add_argument('--paloalto', action='store_true', default=False, help='Palo Alto Networks (PAN) GlobalProtect SSL VPN')
# VPN server details
parser_dst = parser.add_argument_group('VPN Server Details', 'Any missing fields will be prompted on launch')
parser_dst.add_argument('--host', type=str, default=False, help='DNS hostname of SSL VPN server')
parser_dst.add_argument('--user', type=str, default=False, help='Username for SSL VPN account')
parser_dst.add_argument('--pw', type=str, default=False, help='Password for SSL VPN account')
# Import options, output help if none provided
args = vars(parser.parse_args())
#args = vars(parser.parse_args(args=None if sys.argv[1:] else ['--help']))
def vpnTypePrompt():
try:
print('Please enter one of the following and press enter:')
print('1 for Cisco AnyConnect')
print('2 for Fortinet FortiClient')
print('3 for Pulse Secure or Juniper Network Connect')
print('4 for Palo Alto Networks GlobalProtect')
protocol = int(input('SSL VPN Type: '))
if protocol == 1:
return 'anyconnect'
elif protocol == 2:
return 'fortinet'
elif protocol == 3:
return 'nc'
elif protocol == 4:
return 'gp'
else:
return False
except:
return False
if 'anyconnect' in args and args['anyconnect']:
args['protocol'] = 'anyconnect'
elif 'fortinet' in args and args['fortinet']:
args['protocol'] = 'fortinet'
elif 'pulsesecure' in args and args['pulsesecure']:
args['protocol'] = 'nc'
elif 'paloalto' in args and args['paloalto']:
args['protocol'] = 'gp'
else:
args['protocol'] = False
while args['protocol'] == False:
args['protocol'] = vpnTypePrompt()
# Fields to prompt for when False
prompt_for = {
'host': 'DNS hostname of SSL VPN server: ',
'user': 'Username for SSL VPN account: ',
'pw': 'Password for SSL VPN account: '
}
# Interate through fields and prompt for missing ones
if 'help' not in args:
for field,prompt in prompt_for.items():
if str(field) not in args or not args[field]:
while args[field] == False:
try:
if field == 'pw' and args['protocol'] != 'gp':
args[field] = 'N/A'
elif field == 'pw':
args[field] = getpass(prompt)
else:
args[field] = input(prompt)
except:
pass
# Collate arguments for command
command = [
'sudo openconnect',
'--interface=vpn0',
'--script=/usr/share/vpnc-scripts/vpnc-script',
'--protocol="' + args['protocol'] + '"',
'--user="' + args['user'] + '"',
args['host']
]
# Compile command
command = ' '.join(command)
# Start process
process = pexpect.spawnu('/bin/bash', ['-c', command])
# Automate login process for Palo Alto GlobalProtect
if args['protocol'] == 'gp':
process.expect('Password: ')
process.sendline(args['pw'])
process.expect('GATEWAY: ')
process.sendline('Primary GP')
process.expect('anything else to view:')
process.sendline('yes')
process.expect('Password: ')
process.sendline(args['pw'])
# Clear remaining private data
args = None
command = None
# Hand over input to user, wait for process to end if interactive mode ends
process.interact()
while process.isalive():
sleep(5)
| [
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ansible_collections/arista/cvp/plugins/module_utils/facts_tools.py | mtache/ansible-cvp | 0 | 168348 | #!/usr/bin/env python
# coding: utf-8 -*-
#
# GNU General Public License v3.0+
#
# Copyright 2022 Arista Networks AS-EMEA
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless 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.
#
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import traceback
import logging
import re
import os
from typing import List
from concurrent.futures import ThreadPoolExecutor
import ansible_collections.arista.cvp.plugins.module_utils.logger # noqa # pylint: disable=unused-import
from ansible_collections.arista.cvp.plugins.module_utils.resources.api.fields import Api
from ansible_collections.arista.cvp.plugins.module_utils.resources.modules.fields import FactsResponseFields
import ansible_collections.arista.cvp.plugins.module_utils.tools_schema as schema # noqa # pylint: disable=unused-import
try:
from cvprac.cvp_client import CvpClient # noqa # pylint: disable=unused-import
from cvprac.cvp_client_errors import CvpApiError, CvpRequestError # noqa # pylint: disable=unused-import
HAS_CVPRAC = True
except ImportError:
HAS_CVPRAC = False
CVPRAC_IMP_ERR = traceback.format_exc()
try:
import jsonschema # noqa # pylint: disable=unused-import
HAS_JSONSCHEMA = True
except ImportError:
HAS_JSONSCHEMA = False
MODULE_LOGGER = logging.getLogger(__name__)
MODULE_LOGGER.info('Start fact_tools module execution')
# ------------------------------------------ #
# Class
# ------------------------------------------ #
class CvFactResource():
"""
CvFactResource Helper to render facts based on resource type
"""
def __init__(self, facts_type: str = 'list'):
if facts_type == 'list':
self._cache = []
def __shorten_device_facts(self, device_fact: dict):
"""
__shorten_device_facts Filter content to return for device type resource
Parameters
----------
device_fact : dict
Dictionary of data provided by Cloudvision
Returns
-------
dict
Dict with only expected fields to be compliant with resource schema
"""
fact = {
key: device_fact[key]
for key in [
Api.device.HOSTNAME,
Api.device.FQDN,
Api.device.SERIAL,
Api.device.SYSMAC,
Api.generic.CONFIGLETS,
]
}
fact[Api.generic.PARENT_CONTAINER_NAME] = device_fact[Api.device.CONTAINER_NAME]
return fact
def _get_configlet(self):
"""
_get_configlets Generate facts for configlets resource type
EXAMPLE:
--------
>>> CvFactsResource()._get_configlet()
{
"TEAM01-alias": "alias a1 show version",
"TEAM01-another-configlet": "alias a2 show version"
}
Returns
-------
dict
dictionary of configlets.
"""
if isinstance(self._cache, list):
return {configlet[Api.generic.NAME]: configlet[Api.generic.CONFIG] for configlet in self._cache}
def _get_container(self):
"""
_get_container Generate facts for containers resource type
EXAMPLE:
--------
>>> CvFactsResource()._get_container()
{
"TEAM01": {
"parentContainerName": "Tenant"
},
"TEAM01_DC": {
"parentContainerName": "TEAM01"
},
"TEAM01_LEAFS": {
"parentContainerName": "TEAM01_DC",
"configlets": [
"GLOBAL-ALIASES"
]
}
}
Returns
-------
dict
dictionary of containers
"""
if isinstance(self._cache, list):
return {entry[Api.generic.NAME]: {
Api.generic.PARENT_CONTAINER_NAME: entry[Api.container.PARENT_NAME],
Api.generic.CONFIGLETS: entry[Api.generic.CONFIGLETS]}
for entry in self._cache if Api.generic.NAME in entry.keys()}
def _get_device(self, verbose: bool = False):
"""
_get_device Generate facts for devices resource type
EXAMPLE:
--------
>>> CvFactsResource()._get_device()
[
{
"fqdn": "CV-ANSIBLE-EOS01",
"parentContainerName": "ANSIBLE",
"configlets": [
"01TRAINING-01"
],
"systemMacAddress": "50:8d:00:e3:78:aa",
"serialNumber": "64793E1D3DE2240F547E5964354214A4"
}
]
Parameters
----------
verbose : bool, optional
Trigger to include or not all fields from CV, by default False
Returns
-------
list
List of devices
"""
if verbose:
return self._cache
else:
return [self.__shorten_device_facts(
device_fact=device) for device in self._cache]
def add(self, data):
"""
add Add an entry in the list of facts
Parameters
----------
data : Any
Data to add as a new entry in the fact list. Should be a dict
"""
if isinstance(self._cache, list):
self._cache.append(data)
def get(self, resource_model: str, verbose: bool = False):
"""
get Public method to get structured fact for a given resource
This method transform list of data available in its cache to be exposed using CV module schema.
Resource_type input will apply correct data transformation to be compatible with cv modules.
Parameters
----------
resource_model : str
Name of the resource to apply correct transformation. Can be ['device', 'container', 'configlet']
verbose : bool, optional
Trigger to include or not all fields from CV, by default False
Returns
-------
Any
Facts based on resource_type data model.
"""
if resource_model == 'configlet':
return self._get_configlet()
elif resource_model == 'container':
return self._get_container()
elif resource_model == 'device':
return self._get_device(verbose=verbose)
class CvFactsTools():
"""
CvFactsTools Object to operate Facts from Cloudvision
"""
def __init__(self, cv_connection):
self.__cv_client = cv_connection
self._cache = {FactsResponseFields.CACHE_CONTAINERS: None, FactsResponseFields.CACHE_MAPPERS: None}
self._max_worker = min(32, (os.cpu_count() or 1) + 4)
self.__init_facts()
def __init_facts(self):
self._facts = {FactsResponseFields.DEVICE: [], FactsResponseFields.CONFIGLET: [], FactsResponseFields.CONTAINER: []}
def facts(self, scope: List[str], regex_filter: str = '.*'):
"""
facts Public API to collect facts from Cloudvision
Examples
--------
>>> result = self.inventory.facts(scope=['configlets'])
{
"cvp_containers": {
"Tenant": {
"parentContainerName": "None",
"configlets": []
},
"Undefined": {
"parentContainerName": "Tenant",
"configlets": []
},
"EAPI": {
"parentContainerName": "Tenant",
"configlets": [
"demo"
]
}
}
}
Parameters
----------
scope : List[str]
List of elements to get from Cloudvision server, by default ['devices', 'containers']
regex_filter: str
Regular expression to filter devices and configlets. Only element with filter in their name will be exported
Returns
-------
dict
A dictionary of information with all the data from Cloudvision
"""
if 'devices' in scope:
self.__fact_devices(filter=regex_filter)
if 'containers' in scope:
self.__fact_containers()
if 'configlets' in scope:
self.__fact_configlets(filter=regex_filter)
return self._facts
def __get_container_name(self, key: str = Api.container.UNDEFINED_CONTAINER_ID):
"""
__get_container_name Helper to get container name from its key
Send a call to CV to get name of a container key
Parameters
----------
key : str, optional
Container key, by default '<PASSWORD>'
Returns
-------
str
Container name
"""
if self._cache[FactsResponseFields.CACHE_CONTAINERS] is None:
MODULE_LOGGER.warning('Build container cache from Cloudvision')
try:
self._cache[FactsResponseFields.CACHE_CONTAINERS] = self.__cv_client.api.get_containers()['data']
except CvpApiError as error:
MODULE_LOGGER.error('Can\'t get information from CV: %s', str(error))
return None
MODULE_LOGGER.debug('Current cache data is: %s', str(self._cache[FactsResponseFields.CACHE_CONTAINERS]))
for container in self._cache[FactsResponseFields.CACHE_CONTAINERS]:
if key == container[Api.generic.KEY]:
return container[Api.generic.NAME]
return None
def __device_update_info(self, device: dict):
"""
__device_update_info Helper to add missing information for device facts
Add or update fields from CV response to make output valid with arista.cvp.cv_device_v3 schema
Parameters
----------
device : dict
Device data from Cloudvision
Returns
-------
dict
Updated information
"""
if device['status'] != '':
device[Api.generic.PARENT_CONTAINER_NAME] = self.__get_container_name(key=device[Api.device.PARENT_CONTAINER_KEY])
else:
device[Api.generic.PARENT_CONTAINER_NAME] = ''
return device
def __configletIds_to_configletName(self, configletIds: List[str]):
"""
__configletIds_to_configletName Build a list of configlets name from a list of configlets ID
Extract list of configlets name from CVP mappers based on a list of configlets ID provided as an input
Parameters
----------
configletIds : List[str]
List of configlet IDs
Returns
-------
List[str]
List of configlets name
"""
if not configletIds:
return []
if self._cache[FactsResponseFields.CACHE_MAPPERS] is None:
MODULE_LOGGER.warning('Build configlet mappers cache from Cloudvision')
self._cache[FactsResponseFields.CACHE_MAPPERS] = self.__cv_client.api.get_configlets_and_mappers()['data']
configlets = self._cache[FactsResponseFields.CACHE_MAPPERS][Api.generic.CONFIGLETS]
return [configlet[Api.generic.NAME] for configlet in configlets if configlet[Api.generic.KEY] in configletIds]
def __device_get_configlets(self, netid: str):
# sourcery skip: class-extract-method
"""
__device_get_configlets Get list of attached configlets to a given device
Read Configlet Mappers to build a list of configlets name attached to a device identified by is KEY
Parameters
----------
netid : str
CVP Key mostly sysMac
Returns
-------
List[str]
List of configlets name
"""
if self._cache[FactsResponseFields.CACHE_MAPPERS] is None:
MODULE_LOGGER.warning('Build configlet mappers cache from Cloudvision')
self._cache[FactsResponseFields.CACHE_MAPPERS] = self.__cv_client.api.get_configlets_and_mappers()['data']
mappers = self._cache[FactsResponseFields.CACHE_MAPPERS]['configletMappers']
configletIds = [mapper[Api.configlet.ID] for mapper in mappers if mapper[Api.mappers.OBJECT_ID] == netid]
MODULE_LOGGER.debug('** NetelementID is %s', str(netid))
MODULE_LOGGER.debug('** Configlet IDs are %s', str(configletIds))
return self.__configletIds_to_configletName(configletIds=configletIds)
def __containers_get_configlets(self, container_id):
"""
__containers_get_configlets Get list of attached configlets to a given container
Read Configlet Mappers to build a list of configlets name attached to a container identified by is KEY
Parameters
----------
container_id : str
CVP Key for the container
Returns
-------
List[str]
List of configlets name
"""
if self._cache[FactsResponseFields.CACHE_MAPPERS] is None:
MODULE_LOGGER.warning('Build configlet mappers cache from Cloudvision')
self._cache[FactsResponseFields.CACHE_MAPPERS] = self.__cv_client.api.get_configlets_and_mappers()['data']
mappers = self._cache[FactsResponseFields.CACHE_MAPPERS]['configletMappers']
configletIds = [mapper[Api.configlet.ID]
for mapper in mappers
if (mapper[Api.container.ID] == container_id or mapper[Api.mappers.OBJECT_ID] == container_id)
]
# Deduplicate entries as containerID is present for every inherited configlets
configletIds = list(dict.fromkeys(configletIds))
MODULE_LOGGER.debug('** Container ID is %s', str(container_id))
MODULE_LOGGER.debug('** Configlet IDs are %s', str(configletIds))
return self.__configletIds_to_configletName(configletIds=configletIds)
# Fact management
def __fact_devices(self, filter: str = '.*', verbose: bool = False):
"""
__fact_devices Collect facts related to device inventory
[extended_summary]
Parameters
----------
filter : str, optional
Regular Expression to filter device. Search is done against FQDN to allow domain filtering, by default .*
verbose : str, optional
Facts verbosity: full get all data from CV where short get only cv_modules data, by default 'short'
"""
try:
cv_devices = self.__cv_client.api.get_inventory()
except CvpApiError as error_msg:
MODULE_LOGGER.error('Error when collecting devices facts: %s', str(error_msg))
MODULE_LOGGER.info('Extract device data using filter %s', str(filter))
facts_builder = CvFactResource()
for device in cv_devices:
if re.match(filter, device[Api.device.HOSTNAME]):
MODULE_LOGGER.debug('Filter has been matched: %s - %s', str(filter), str(device[Api.device.HOSTNAME]))
if verbose:
facts_builder.add(self.__device_update_info(device=device))
else:
device[Api.generic.CONFIGLETS] = self.__device_get_configlets(netid=device[Api.generic.KEY])
facts_builder.add(device)
self._facts[FactsResponseFields.DEVICE] = facts_builder.get(resource_model='device', verbose=verbose)
def __fact_containers(self):
"""
__fact_containers Collect facts related to container structure
"""
try:
cv_containers = self.__cv_client.api.get_containers()
except CvpApiError as error_msg:
MODULE_LOGGER.error('Error when collecting containers facts: %s', str(error_msg))
facts_builder = CvFactResource()
for container in cv_containers['data']:
if container[Api.generic.NAME] != 'Tenant':
MODULE_LOGGER.debug('Got following information for container: %s', str(container))
container[Api.generic.CONFIGLETS] = self.__containers_get_configlets(container_id=container[Api.container.KEY])
facts_builder.add(container)
self._facts[FactsResponseFields.CONTAINER] = facts_builder.get(resource_model='container')
def __fact_configlets(self, filter: str = '.*', configlets_per_call: int = 10):
"""
__fact_configlets Collect facts related to configlets structure
Execute parallel calls to get a list of all static configlets from CVP
Parameters
----------
filter : str, optional
Regular Expression to filter configlets, by default .*
configlets_per_call : int, optional
Number of configlets to retrieve per API call, by default 10
"""
max_range_calc = self.__cv_client.api.get_configlets(start=0, end=1)['total'] + 1
futures_list = []
results = []
with ThreadPoolExecutor(max_workers=self._max_worker) as executor:
for configlet_index in range(0, max_range_calc, configlets_per_call):
futures_list.append(
executor.submit(self.__cv_client.api.get_configlets, start=configlet_index, end=configlet_index + configlets_per_call)
)
for future in futures_list:
try:
result = future.result(timeout=60)
results.append(result)
except Exception as error:
results.append(None)
MODULE_LOGGER.critical(
'Exception in getting configlet (%s): %s',
str(error),
str(future.result())
)
facts_builder = CvFactResource()
for future in results:
for configlet in future['data']:
if re.match(filter, configlet[Api.generic.NAME]):
MODULE_LOGGER.debug('Adding configlet %s', str(configlet[Api.generic.NAME]))
facts_builder.add(configlet)
MODULE_LOGGER.debug(
'Final results for configlets: %s',
str(facts_builder.get(resource_model='configlet').keys())
)
self._facts[FactsResponseFields.CONFIGLET] = facts_builder.get(resource_model='configlet')
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sparclur/parsers/_pdfcpu.py | levelupresearch/sparclur | 0 | 166182 | <reponame>levelupresearch/sparclur
import shutil
from typing import List, Dict, Any, Union
import os
import re
import locale
import shlex
import tempfile
import subprocess
from subprocess import DEVNULL, TimeoutExpired
import yaml
from sparclur._tracer import Tracer
from sparclur._parser import VALID, VALID_WARNINGS, REJECTED, REJECTED_AMBIG, TRACER, TIMED_OUT
from sparclur.utils import hash_file
from sparclur.utils._config import _get_config_param, _load_config
class PDFCPU(Tracer):
"""Wrapper for PDFCPU (https://pdfcpu.io/)"""
def __init__(self, doc: Union[str, bytes],
skip_check: Union[bool, None] = None,
hash_exclude: Union[str, List[str], None] = None,
binary_path: Union[str, None] = None,
temp_folders_dir: Union[str, None] = None,
timeout: Union[int, None] = None
):
"""
Parameters
----------
binary_path : str
If the mutool binary is not in the system PATH, add the path to the binary here. Can also be used to trace
specific versions of the binary.
"""
config = _load_config()
skip_check = _get_config_param(PDFCPU, config, 'skip_check', skip_check, False)
hash_exclude = _get_config_param(PDFCPU, config, 'hash_exclude', hash_exclude, None)
binary_path = _get_config_param(PDFCPU, config, 'binary_path', binary_path, None)
temp_folders_dir = _get_config_param(PDFCPU, config, 'temp_folders_dir', temp_folders_dir, None)
timeout = _get_config_param(PDFCPU, config, 'timeout', timeout, None)
super().__init__(doc=doc,
temp_folders_dir=temp_folders_dir,
skip_check=skip_check,
hash_exclude=hash_exclude,
timeout=timeout)
self._pdfcpu_path = 'pdfcpu' if binary_path is None else os.path.join(binary_path, 'pdfcpu')
self._trace_exit_code = None
self._decoder = locale.getpreferredencoding()
def _check_for_tracer(self) -> bool:
if self._can_trace is None:
try:
subprocess.check_output(shlex.split(self._pdfcpu_path + " version"), shell=False)
pc_present = True
except Exception as e:
pc_present = False
self._can_trace = pc_present
return self._can_trace
@property
def validate_tracer(self) -> Dict[str, Any]:
if TRACER not in self._validity:
validity_results = dict()
if self._cleaned is None:
self._scrub_messages()
observed_messages = list(self._cleaned.keys())
if self._file_timed_out[TRACER]:
validity_results['valid'] = False
validity_results['status'] = TIMED_OUT
validity_results['info'] = 'Timed Out: %i' % self._timeout
elif self._trace_exit_code > 1:
validity_results['valid'] = False
validity_results['status'] = REJECTED
validity_results['info'] = 'Exit code: %i' % self._trace_exit_code
elif observed_messages == ['No warnings']:
validity_results['valid'] = True
validity_results['status'] = VALID
elif len([message for message in observed_messages if 'Error' in message]) > 0:
validity_results['valid'] = False
validity_results['status'] = REJECTED
validity_results['info'] = 'Errors returned'
elif len([message for message in observed_messages if 'Warning' in message]) == len(observed_messages):
validity_results['valid'] = True
validity_results['status'] = VALID_WARNINGS
validity_results['info'] = 'Warnings only'
else:
validity_results['valid'] = False
validity_results['status'] = REJECTED_AMBIG
validity_results['info'] = 'Unknown message type returned'
self._validity[TRACER] = validity_results
return self._validity[TRACER]
@staticmethod
def get_name():
return 'PDFCPU'
def _get_num_pages(self):
if not self._skip_check:
assert self._check_for_tracer(), "%s not found" % self.get_name()
with tempfile.TemporaryDirectory(dir=self._temp_folders_dir) as temp_path:
if isinstance(self._doc, bytes):
file_hash = hash_file(self._doc)
doc_path = os.path.join(temp_path, file_hash)
with open(doc_path+'.pdf', 'wb') as doc_out:
doc_out.write(self._doc)
# elif not self._doc.endswith('.pdf'):
# doc_path = os.path.join(temp_path, 'infile.pdf')
# shutil.copy2(self._doc, doc_path)
else:
doc_path = self._doc
try:
sp = subprocess.Popen([self._pdfcpu_path, 'info', doc_path], stdout=subprocess.PIPE, stderr=DEVNULL,
shell=False)
(stdout, _) = sp.communicate()
stdout = stdout.decode(self._decoder)
self._num_pages = [int(line.split(':')[1].strip())
for line in stdout.split('\n') if 'Page count:' in line][0]
except:
self._num_pages = 0
def _parse_document(self):
with tempfile.TemporaryDirectory(dir=self._temp_folders_dir) as temp_path:
if isinstance(self._doc, bytes):
file_hash = hash_file(self._doc)
doc_path = os.path.join(temp_path, file_hash + '.pdf')
with open(doc_path, 'wb') as doc_out:
doc_out.write(self._doc)
elif not self._doc.endswith('.pdf'):
doc_path = os.path.join(temp_path, 'infile.pdf')
shutil.copy2(self._doc, doc_path)
else:
doc_path = self._doc
try:
strict_cmd = '%s validate -m strict %s' % (self._pdfcpu_path, doc_path)
relaxed_cmd = '%s validate -m relaxed %s' % (self._pdfcpu_path, doc_path)
# if self._verbose:
# cmd = cmd + ' -v'
strict_sp = subprocess.Popen(
shlex.split(strict_cmd),
stderr=subprocess.PIPE, stdout=DEVNULL, shell=False)
relaxed_sp = subprocess.Popen(
shlex.split(relaxed_cmd),
stderr=subprocess.PIPE, stdout=DEVNULL, shell=False)
(_, strict_err) = strict_sp.communicate(timeout=self._timeout or 600)
strict_err = strict_err.decode(self._decoder, errors='ignore').strip()
strict_err = re.sub(r" \(try -mode=relaxed\)", '', strict_err)
(_, relaxed_err) = relaxed_sp.communicate(timeout=self._timeout or 600)
relaxed_err = relaxed_err.decode(self._decoder, errors='ignore').strip()
error_arr = [relaxed_err, strict_err] if relaxed_err not in strict_err else [relaxed_err]
# error_arr = [message for message in err.split('\n') if len(message) > 0]
self._trace_exit_code = max(strict_sp.returncode, relaxed_sp.returncode)
self._file_timed_out[TRACER] = False
except TimeoutExpired:
strict_sp.kill()
relaxed_sp.kill()
(_, strict_err) = strict_sp.communicate()
(_, relaxed_err) = relaxed_sp.communicate()
strict_err = strict_err.decode(self._decoder, errors='ignore').strip()
strict_err = re.sub(r" \(try -mode=relaxed\)", '', strict_err)
relaxed_err = relaxed_err.decode(self._decoder, errors='ignore').strip()
error_arr = [relaxed_err, strict_err] if relaxed_err not in strict_err else [relaxed_err]
error_arr.insert(0, 'Error: Subprocess timed out: %i' % (self._timeout or 600))
self._trace_exit_code = 0
self._file_timed_out[TRACER] = True
except Exception as e:
strict_sp.kill()
relaxed_sp.kill()
(_, strict_err) = strict_sp.communicate()
(_, relaxed_err) = relaxed_sp.communicate()
strict_err = strict_err.decode(self._decoder, errors='ignore').strip()
strict_err = re.sub(r" \(try -mode=relaxed\)", '', strict_err)
relaxed_err = relaxed_err.decode(self._decoder, errors='ignore').strip()
error_arr = str(e).split('\n')
pdfcpu_errs = [relaxed_err, strict_err] if relaxed_err not in strict_err else [relaxed_err]
error_arr.extend(pdfcpu_errs)
self._trace_exit_code = 0
self._file_timed_out[TRACER] = False
error_arr = [err for err in error_arr if len(err) > 0]
self._messages = ['No warnings'] if len(error_arr) == 0 else error_arr
def _scrub_messages(self):
if self._messages is None:
self._parse_document()
scrubbed_messages = [self._clean_message(err) for err in self._messages]
error_dict: Dict[str, int] = dict()
for error in scrubbed_messages:
error_dict[error] = error_dict.get(error, 0) + 1
self._cleaned = error_dict
def _clean_message(self, err):
message = err.strip()
cleaned = 'runtime error' if message.startswith('runtime:') else message
cleaned = re.sub(r"\<\<", "[", cleaned)
cleaned = re.sub(r"\>\>", "]", cleaned)
cleaned = re.sub(r"\[[^]]+\]", "<<x>>", cleaned)
cleaned = re.sub(r"\(obj\#:\d+\)", "(obj#:<x>)", cleaned)
cleaned = re.sub(r"\(obj\#\d+\)", "(obj#<x>)", cleaned)
cleaned = re.sub(r"line = \<[^>]+\>", "line = <x>", cleaned)
cleaned = re.sub(r"parsing \"[^\"]+\":", "parsing <x>:", cleaned)
cleaned = re.sub(r"problem dereferencing object \d+", "problem dereferencing object <x>", cleaned)
cleaned = re.sub(r"problem dereferencing stream \d+", "problem dereferencing stream <x>", cleaned)
cleaned = re.sub(r"unknown PDF Header Version: .+", "unknown PDF Header Version: <x>", cleaned)
cleaned = re.sub(r"\nThis file could be PDF/A compliant but pdfcpu only supports versions <= PDF V1.7", '',
cleaned)
cleaned = re.sub(r"validateDateEntry: .+ invalid date", "validateDateEntry: <x> invalid date", cleaned)
cleaned = re.sub(r"validateDateObject: .+ invalid date", "validateDateObject: <x> invalid date", cleaned)
cleaned = re.sub(r"leaf node corrupted .+", "leaf node corrupted", cleaned)
return cleaned
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rsvis/tools/canvas/imgcv.py | Tom-Hirschberger/DataVisualization | 0 | 48003 | # ===========================================================================
# imgcv.py ----------------------------------------------------------------
# ===========================================================================
# import ------------------------------------------------------------------
# ---------------------------------------------------------------------------
import rsvis.utils.imgtools as imgtools
import rsvis.utils.logger
import logging
import numpy as np
from PIL import Image, ImageTk
from tkinter import Canvas, NW
# class -------------------------------------------------------------------
# ---------------------------------------------------------------------------
class ImgCanvas(Canvas):
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def __init__(
self,
parent,
shift=[4,4],
sensitivity = 4,
logger=None,
**kwargs
):
super(ImgCanvas, self).__init__(parent)
self.bind("<Configure>", self.resize_image)
self._mask = [None]
self._mask_alpha = [150]
self._mask_color = [[0,0,0]]
self._mask_invert = [False]
self._shift = shift
self._scale = [1.0, 1.0]
self.set_size([self.winfo_reqwidth(), self.winfo_reqheight()])
self._parent = parent
self._logger = rsvis.utils.logger.Logger(logger=logger)
# key bindings ----------------------------------------------------
self._mouse_sensitivity = 4
self._mouse_box = [0, 0, 0, 0]
self._mouse_point = [0, 0]
self._mouse_event = [0, 0]
self._mouse_img = [0, 0]
self._keys = dict()
self.bind("<Button-1>", self.mouse_button_1_pressed)
self.bind("<ButtonRelease-1>", self.mouse_button_1_released)
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def clear(self, **kwargs):
pass
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_keys(self, **kwargs):
return self._keys
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_logger(self):
return self._logger
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def resize_image(self, event):
# determine the ratio of old width/height to new width/height
event_size = [event.width, event.height] #####################
self._scale = [float(e)/s for e, s in zip(event_size, self._size)]
self.set_size(event_size)
# resize the canvas
self.config(width=self._size[0], height=self._size[1]) #################
# rescale all the objects tagged with the "all" tag
self.scale("all", 0, 0, self._scale[0], self._scale[1]) ################
self.create_image()
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def resize_boxes(self, boxes, inversion=False):
scale = [float(s)/i for s, i in zip(self.get_size(), self._img_size)]
if inversion:
scale = [1/s for s in scale]
boxes = boxes if isinstance(boxes[0], list) and len(boxes[0]) !=2 else [boxes]
return [self.resize_bbox(box, scale) for box in boxes]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def resize_bbox(self, box, scale):
if len(box)==4:
return [
int(box[0]*scale[1]), int(box[1]*scale[1]),
int(box[2]*scale[0]), int(box[3]*scale[0])
]
else:
return [[int(n[0] *scale[0]), int(n[1]*scale[1])] for n in box ]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def resize_points(self, points, inversion=False):
scale = [float(s)/i for s, i in zip(self.get_size(), self._img_size)]
if inversion:
scale = [1/s for s in scale]
points = points if isinstance(points[0], list) else [points]
return [self.resize_point(point, scale) for point in points]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def resize_point(self, point, scale):
return [int(point[0]*scale[1]), int(point[1]*scale[0])]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def resize_event(self, event):
ev = [event.y, event.x]
ev[0] = ev[0] if ev[0] >= 0 else 0
ev[0] = ev[0] if ev[0] < self._img_draw.size[1] else self._img_draw.size[1]-1
ev[1] = ev[1] if ev[1] >= 0 else 0
ev[1] = ev[1] if ev[1] < self._img_draw.size[0] else self._img_draw.size[0]-1
return ev
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_event_box(self, event):
return [
min([self._mouse_point[0], self._mouse_event[0]]),
max([self._mouse_point[0], self._mouse_event[0]]),
min([self._mouse_point[1], self._mouse_event[1]]),
max([self._mouse_point[1], self._mouse_event[1]])
]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def set_img(self, img, clear_mask=True):
if not isinstance(img, np.ndarray):
return
self._img_size = [img.shape[1], img.shape[0]]
self._data_img = imgtools.expand_image_dim(img)
if not isinstance(img.dtype, np.uint8):
img = imgtools.project_and_stack(img, dtype=np.uint8, factor=255)
self._img = Image.fromarray(img)
if clear_mask:
self.set_mask(show=False)
self.create_image()
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def set_mask(self, mask=None, show=True, alpha=150, color=[0,0,0], invert=False):
self._mask = mask if isinstance(mask, list) else [mask]
self._mask_alpha = alpha if isinstance(alpha, list) else [alpha]
self._mask_color = color if isinstance(color[0], list) else [color]
self._mask_invert= invert if isinstance(invert, list) else [invert]
if show:
self.create_image()
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_mask(self, index=None, resize=False):
if index is None:
mask = self._mask[0]
for idx in range(1, len(self._mask)):
if isinstance(self._mask[idx], np.ndarray):
mask = np.where(np.logical_and(mask, self._mask[idx]), 1, 0).astype(np.uint8)
return mask
else:
if isinstance(self._mask[index], np.ndarray):
return np.asarray(Image.fromarray(self._mask[index]).resize(self.get_size())) if resize else self._mask[index]
else:
return self._mask[index]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def is_mouse_event(self, bbox):
if not (bbox[1]-bbox[0] > self._mouse_sensitivity and bbox[3]-bbox[2] > self._mouse_sensitivity):
return False
return True
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_img(self, show=False):
if show:
return np.asarray(self._img).copy()
return self._data_img.copy()
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def set_size(self, size):
self._size = [s - sh for s, sh in zip(size, self._shift)]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_size(self):
return [s + sh for s, sh in zip(self._size, self._shift)]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_shape(self):
size = self.get_size()
return (size[1], size[0], 3)
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_intial_draw_image(self):
return np.zeros(self.get_shape(), dtype=np.int16) - 1
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def create_image(self, **kwargs):
self._img_draw = self._img.resize(self.get_size())
if isinstance(self._mask[0], np.ndarray):
for idx, (mask, color, alpha, invert) in enumerate(zip(self._mask, self._mask_color, self._mask_alpha, self._mask_invert)):
mask = self.get_mask(index=idx, resize=True)
mask = mask if not invert else imgtools.invert_bool_img(mask)
mask = Image.fromarray(
imgtools.get_transparent_image(
imgtools.bool_to_img(mask, value=-1, dtype=np.int16, color=color, factor=255),
value=alpha
)
)
self._img_draw.paste(mask, (0, 0), mask)
image = Image.fromarray(
imgtools.get_transparent_image(self.draw_image(), value=200))
self._img_draw.paste(image, (0, 0), image)
self._img_canvas = ImageTk.PhotoImage(image=self._img_draw)
self._img_on_canvas = super(ImgCanvas, self).create_image(0, 0, image=self._img_canvas, anchor=NW)
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def draw_image(self, **kwargs):
img_assembly = self.get_intial_draw_image()
return img_assembly
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def mouse_button_1_pressed(self, event):
self.focus_set()
self._mouse_event = self.resize_event(event)
self._mouse_point = [self._mouse_event[0], self._mouse_event[1]]
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def get_roi(self):
if sum(self._mouse_box):
roi_xy = self.resize_boxes(self._mouse_box, inversion=True)[0]
roi = [roi_xy[2], roi_xy[0], roi_xy[3]-roi_xy[2], roi_xy[1]-roi_xy[0]]
else:
roi = [0, 0, self._data_img.shape[1]-1, self._data_img.shape[0]-1]
return roi
# method --------------------------------------------------------------
# -----------------------------------------------------------------------
def mouse_button_1_released(self, event):
self.focus_set()
self._mouse_event = self.resize_event(event)
self._mouse_box = self.get_event_box(event)
self._mouse_img = self.resize_points(self._mouse_event, inversion=True)[0]
self._logger("[MOUSE] Pixel: {}, Value: {}".format(self._mouse_img,
self._data_img[self._mouse_img[0], self._mouse_img[1], :]
)
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setup.py | understood/ytreporty | 1 | 108733 | <reponame>understood/ytreporty<gh_stars>1-10
# -*- coding: utf-8; mode: Python; -*-
#
# Licensed under the Apache License, Version 2.0 (the "License"); you
# may not use this file except in compliance with the License. You may
# obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless 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.
from setuptools import setup, find_packages
import ytreporty
setup(
name="ytreporty",
version=ytreporty.__version__,
description="CLI to the YouTube Reporting API",
author="<NAME>",
author_email="<EMAIL>",
packages=find_packages(),
)
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] |
program/condition/and_cond.py | probing-lab/polar | 2 | 87229 | from .condition import Condition
from .true_cond import TrueCond
class And(Condition):
cond1: Condition
cond2: Condition
def __init__(self, cond1, cond2):
self.cond1 = cond1
self.cond2 = cond2
def simplify(self):
self.cond1 = self.cond1.simplify()
self.cond2 = self.cond2.simplify()
if isinstance(self.cond1, TrueCond):
return self.cond2
if isinstance(self.cond2, TrueCond):
return self.cond1
return self
def reduce(self, store):
return self.cond1.reduce(store) + self.cond2.reduce(store)
def get_normalized(self, program):
self.cond1, failed_atoms1 = self.cond1.get_normalized(program)
self.cond2, failed_atoms2 = self.cond2.get_normalized(program)
return self, failed_atoms1 + failed_atoms2
def subs(self, substitutions):
self.cond1.subs(substitutions)
self.cond2.subs(substitutions)
def evaluate(self, state):
return self.cond1.evaluate(state) and self.cond2.evaluate(state)
def get_conjuncts(self):
return self.cond1.get_conjuncts() + self.cond2.get_conjuncts()
def to_arithm(self, p):
return self.cond1.to_arithm(p) * self.cond2.to_arithm(p)
def get_free_symbols(self):
return self.cond1.get_free_symbols() | self.cond2.get_free_symbols()
def is_implied_by_loop_guard(self):
if self.is_loop_guard:
return True
return self.cond1.is_implied_by_loop_guard() and self.cond1.is_implied_by_loop_guard()
def get_loop_guard(self):
if self.is_loop_guard:
return self.copy()
cond1_guard = self.cond1.get_loop_guard()
return cond1_guard if cond1_guard is not None else self.cond2.get_loop_guard()
def __str__(self):
return f"({self.cond1} ∧ {self.cond2})"
def __eq__(self, obj):
return isinstance(obj, And) and (self.cond1, self.cond2) == (obj.cond1, obj.cond2)
def __hash__(self):
return hash(("AND", self.cond1, self.cond2))
def __simple_copy__(self):
return And(self.cond1.copy(), self.cond2.copy())
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] |
config/__init__.py | kave/boilerplate-repo | 0 | 104147 | <reponame>kave/boilerplate-repo<gh_stars>0
import os
from distutils.util import strtobool
from os.path import dirname, join
from dotenv import load_dotenv
dotenv_path = join(dirname(__file__), '.env')
load_dotenv(dotenv_path, verbose=True)
# Server
HOST = os.environ.get('HOST', '0.0.0.0')
PORT = int(os.environ.get('PORT', 9000))
ENV = os.environ.get('ENV')
IS_LOCAL = ENV == 'local'
IS_HEROKU = ENV == 'heroku'
DEBUG = strtobool(os.environ.get('DEBUG'))
# Databases
DB_HOST = os.environ.get('DB_HOST')
DB_PORT = os.environ.get('DB_PORT')
DB_DATABASE = os.environ.get('DB_DATABASE')
DB_USERNAME = os.environ.get('DB_USERNAME')
DB_PASSWORD = os.environ.get('DB_PASSWORD')
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] |
CompetitiveProgramming/CodeChef/P20_MARCHA1.py | Sahil2rick/School-PythonProject | 0 | 161847 | # In the mysterious country of Byteland, everything is quite different from what you'd normally expect. In most places, if
# you were approached by two mobsters in a dark alley, they would probably tell you to give them all the money that you
# have. If you refused, or didn't have any - they might even beat you up.
#
# In Byteland the government decided that even the slightest chance of someone getting injured has to be ruled out. So,
# they introduced a strict policy. When a mobster approaches you in a dark alley, he asks you for a specific amount of
# money. You are obliged to show him all the money that you have, but you only need to pay up if he can find a subset of
# your banknotes whose total value matches his demand. Since banknotes in Byteland can have any positive integer value
# smaller than one thousand you are quite likely to get off without paying.
#
# Both the citizens and the gangsters of Byteland have very positive feelings about the system. No one ever gets hurt, the
# gangsters don't lose their jobs, and there are quite a few rules that minimize that probability of getting mugged (the
# first one is: don't go into dark alleys - and this one is said to work in other places also).
#
# Input
# The first line contains integer t, the number of test cases (about 100). Then t test cases follow. Each test case starts
# with n, the number of banknotes in your wallet, and m, the amount of money the muggers asked of you. Then n numbers
# follow, representing values of your banknotes. Your wallet does not hold more than 20 banknotes, and the value of a
# single banknote is never more than 1000.
#
# Output
# For each test case output a single line with the word 'Yes' if there is a subset of your banknotes that sums to m, and
# 'No' otherwise.
#
# Example
# Input:
# 5
# 3 3
# 1
# 1
# 1
# 5 11
# 1
# 2
# 4
# 8
# 16
# 5 23
# 1
# 2
# 4
# 8
# 16
# 5 13
# 1
# 5
# 5
# 10
# 10
# 20 132
# 17
# 6
# 4
# 998
# 254
# 137
# 259
# 153
# 154
# 3
# 28
# 19
# 123
# 542
# 857
# 23
# 687
# 35
# 99
# 999
#
# Output:
# Yes
# Yes
# Yes
# No
# Yes
from itertools import combinations
def subset(a, n, m):
for i in range(1, n+1):
array = combinations(a, i)
for j in array:
if sum(j) == m:
return "Yes"
return "No"
for _ in range(int(input())):
n, m = map(int, input().split())
a = []
for i in range(n):
a.append(int(input()))
ans = subset(a, n, m)
print(ans)
#Made by <NAME> | [
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src/pymodaq_plugins_moke/mokemacro.py | CEMES-CNRS/pymodaq_plugins_moke | 0 | 161123 | import sys
from qtpy import QtWidgets
from pymodaq.daq_utils.gui_utils import DockArea
from pymodaq.daq_viewer.daq_viewer_main import DAQ_Viewer
def main():
app = QtWidgets.QApplication(sys.argv)
win = QtWidgets.QMainWindow()
area = DockArea()
win.setCentralWidget(area)
win.resize(1000, 500)
win.setWindowTitle('PyMoDAQ Viewer')
prog = DAQ_Viewer(area, title="MokeMacro", DAQ_type='DAQ1D')
prog.detector = 'MokeMacro'
prog.init_det()
win.show()
sys.exit(app.exec_())
if __name__ == '__main__':
main()
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projects/api/components.py | Matheus158257/projects | 0 | 122955 | # -*- coding: utf-8 -*-
"""Components blueprint."""
from flask import jsonify, request
from flask_smorest import Blueprint
from ..controllers.components import create_component, get_component, update_component, \
delete_component, pagination_components, total_rows_components
from ..utils import to_snake_case
bp = Blueprint("components", __name__)
@bp.route("", methods=["GET"])
@bp.paginate(page=0)
def handle_list_components(pagination_parameters):
name = request.args.get('name')
total_rows = total_rows_components(name=name)
components = pagination_components(name=name,
page=pagination_parameters.page,
page_size=pagination_parameters.page_size)
response = {
'total': total_rows,
'components': components
}
return jsonify(response)
@bp.route("", methods=["POST"])
def handle_post_components():
"""Handles POST requests to /."""
kwargs = request.get_json(force=True)
kwargs = {to_snake_case(k): v for k, v in kwargs.items()}
component = create_component(**kwargs)
return jsonify(component)
@bp.route("<component_id>", methods=["GET"])
def handle_get_component(component_id):
"""Handles GET requests to /<component_id>."""
return jsonify(get_component(uuid=component_id))
@bp.route("<component_id>", methods=["PATCH"])
def handle_patch_component(component_id):
"""Handles PATCH requests to /<component_id>."""
kwargs = request.get_json(force=True)
kwargs = {to_snake_case(k): v for k, v in kwargs.items()}
component = update_component(uuid=component_id, **kwargs)
return jsonify(component)
@bp.route("<component_id>", methods=["DELETE"])
def handle_delete_component(component_id):
"""Handles DELETE requests to /<component_id>."""
return jsonify(delete_component(uuid=component_id))
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8KYU/first_non_consecutive.py | yaznasivasai/python_codewars | 4 | 41484 | def first_non_consecutive(arr: list) -> int:
''' This function returns the first element of an array that is not consecutive. '''
if len(arr) < 2:
return None
non_consecutive = []
for i in range(len(arr) - 1):
if arr[i+1] - arr[i] != 1:
non_consecutive.append(arr[i+1])
if len(non_consecutive) == 0:
return None
return int(''.join(map(str, non_consecutive[:1]))) | [
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commands/interactive.py | Aprelius/tplink-smart-devices | 0 | 1616428 | from tplink.discover import LoadDevices
commands = {
'toggle': 'Disable the devices',
'help': 'Display this help menu',
'quit': 'Exit this interactive prompt',
'list': 'List available devices',
'use': 'Target a specific device ID or name for commands'
}
def IsNumber(value):
try:
int(value)
except ValueError:
return False
return True
def Interactive(config, args):
target = None
devices = LoadDevices(args.devices)
if len(devices) == 1:
target = devices[0]
while True:
try:
if target is not None:
print('Using device: {}'.format(target.GetAlias()))
command = input('Select interactive option (help for menu): ')
if command is None or len(command) == 0:
continue
args = command.split(' ')
command = args.pop(0).lower()
if command == 'q' or command == 'quit':
break
elif command == 'h' or command == 'help':
print('Available options:\n')
for option, text in commands.items():
print('{}: {}'.format(option, text))
elif command == 'l' or command == 'list':
print('Available devices:\n')
for i in range(len(devices)):
print('{}) {} ({})'.format(i + 1, devices[i].GetAlias(), devices[i].address))
elif command == 'reboot':
for i in range(len(devices)):
print("Rebooting device '{}' ...".format(devices[i].GetAlias()))
result = devices[i].Set('system', 'reboot', {'delay': 1})
print("device='{}' result={}".format(devices[i].GetAlias(), result))
elif command == 'toggle':
for i in range(len(devices)):
if devices[i].IsOn():
devices[i].Off()
print("Changing active state for '{}' to 'Off'".format(
devices[i].GetAlias()))
elif devices[i].IsOff():
devices[i].On()
print("Changing active state for '{}' to 'On'".format(
devices[i].GetAlias()))
elif command == 'use':
if len(args) == 0:
if target is not None:
target = None
else:
print('Error: specify a device ID or name to select')
elif IsNumber(args[0]):
index = int(args[0])
if index > 0 and index <= len(devices):
target = devices[index - 1]
else:
print("Error: invalid device id '{}'".format(args[0]))
else:
name = ' '.join(args)
for device in devices:
if device.GetAlias() == name:
target = device
break
if target is None:
print("Error: Unknown device '{}'".format(name))
elif command == 'set':
if len(args) < 2:
print('Error: invalid set parameters')
else:
option = args[0]
value = ' '.join(args[1:])
result = False
if option == 'alias':
result = target.SetAlias(value)
else:
print("Error: invalid set-option '{}'".fomrat(option))
continue
if result:
print('Success')
else:
print('Failed')
else:
print('Error: unknown option: {}'.format(command))
print()
except KeyboardInterrupt:
print("Type 'quit' to exit the interactive utility")
print()
except EOFError:
return False
return True
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] |
isoimage.py | nuk380y/piedpiper-pakman-faas | 0 | 159656 | import yaml
import sys
import os
import pathlib
import zipfile
import shutil
import tarfile
import errno
# Read YAML file
def main(argv):
command_name = 'mkisofs'
target_directory = 'target'
if sys.version_info[0] != 3 or sys.version_info[1] < 6:
print("This script requires Python version 3.6+")
sys.exit(1)
with open(argv[0]) as stream:
if not (does_file_exists(argv[0])):
print('Can not find Yaml File :'+sys.argv[1:])
return 1
if not is_tool(command_name):
print('Command '+command_name+" Not Found on this system")
return 1
try:
data_loaded = yaml.safe_load(stream)
except yaml.YAMLError as exc:
print(exc)
return 1
# print the read file
print(" Statred Processing :"+sys.argv[1])
# validate yaml file before processing
validate_yaml_file(data_loaded)
# print(data_loaded)
mkdir_p(target_directory)
# get_iso_package_name(data_loaded,packages);
image_name = 'default.iso'
# image_type = 'iso'
structure = {}
for row in data_loaded.get('packages'):
if 'structure' in row:
# image_name = row.get('name')
# image_type = row.get('type')
# print('Image name:', image_name)
# print('Image type:', image_type)
structure = row.get('structure')
for files_row in structure.get('files'):
if 'file' in files_row:
file_name = files_row.get('file')
# unarhive = files_row.get('unarchive')
py = pathlib.Path().glob(file_name)
for file in py:
shutil.copy2(file, target_directory)
for subdirs_row in structure.get('subdirs'):
process_subdir(subdirs_row, None)
command_name += ' -V CDNAME -J -r -o '+image_name+' '
command_name += target_directory
print(" Generating Iso image", command_name)
os.system(command_name)
def isNotValid(file_name):
print("ERROR: File:"+file_name+'is not Valid')
def create_destination_directory(parent_dir, subdir):
target_directory = 'target'
# print('Subdirectory:',subdir)
# print('Parent:',parent_dir)
if(parent_dir is not None):
destination = get_dest_dir_name(target_directory, parent_dir)
destination = get_dest_dir_name(destination, subdir)
else:
destination = get_dest_dir_name(target_directory, subdir)
mkdir_p(destination)
return destination
def process_subdir(subdirs_row, parent_dir):
subdir = subdirs_row.get('subdir')
# print('Subdirectory1:',subdir)
# print('Parent1:',parent_dir)
destination = create_destination_directory(parent_dir, subdir)
# print('destination1:',destination)
if "subdirs" in subdirs_row:
if(subdirs_row.get('subdirs') is not None):
for sub_subdirs_row in subdirs_row.get('subdirs'):
# print("Processing subdirs:"+sub_subdirs_row.get('subdir'))
process_subdir(sub_subdirs_row, subdir)
if 'files' in subdirs_row:
for files_row in subdirs_row.get('files'):
file_name = files_row.get('file')
unarhive = files_row.get('unarchive')
# print('Processsing file_name:',file_name)
# print('should Unarchive:',unarhive)
if unarhive:
unarchive_file_to_destination(destination, file_name)
else:
# print('Copy file to destination')
py = pathlib.Path().glob(file_name)
for file in py:
shutil.copy2(file, destination)
def validate_subdir(subdirs_row):
# print('Validating',subdirs_row)
if "subdirs" in subdirs_row:
if(subdirs_row.get('subdirs') is not None):
for sub_subdirs_row in subdirs_row.get('subdirs'):
# print('Validating',subdirs_row.get('subdirs'))
validate_subdir(sub_subdirs_row)
if 'files' in subdirs_row:
for files_row in subdirs_row.get('files'):
file_name = files_row.get('file')
# print('Validating',file_name)
if not does_file_exists(file_name):
print("Does not found file:", file_name)
sys.exit(1)
def validate_yaml_file(data_loaded):
for row in data_loaded.get('packages'):
if 'structure' in row:
structure = row.get('structure')
for files_row in structure.get('files'):
if 'file' in files_row:
py = pathlib.Path().glob(files_row.get('file'))
for file in py:
# print('Checking file:',file)
if not does_file_exists(str(file)):
print("Does not found file:", (str(file)))
sys.exit(1)
for subdirs_row in structure.get('subdirs'):
validate_subdir(subdirs_row)
else:
print(' The file should have structure element')
sys.exit(1)
def unarchive_file_to_destination(destination, file_name):
print('unarchive the files to destination:', destination)
if (does_file_exists(file_name) and zipfile.is_zipfile(file_name)):
extract_zip_file(file_name, destination)
elif(does_file_exists(file_name) and tarfile.is_tarfile(file_name)):
extract_tar_file(file_name, destination)
else:
isNotValid(file_name)
def does_file_exists(name):
if os.path.exists(name):
return True
else:
return False
def get_dest_dir_name(destination, subdir):
return destination+str(os.sep)+subdir
def extract_zip_file(file_name, destination):
zip_ref = zipfile.ZipFile(file_name, 'r')
zip_ref.extractall(destination)
zip_ref.close()
def extract_tar_file(file_name, destination):
with tarfile.open(file_name) as tar:
tar.extractall(path=destination)
def is_tool(name):
"""Check whether 'name' is on PATH."""
from distutils.spawn import find_executable
return find_executable(name) is not None
def mkdir_p(path):
try:
os.makedirs(path, exist_ok=True)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
raise
if __name__ == "__main__":
sys.exit(main(sys.argv[1:]))
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test.py | dharshini-raman/SeniorYear | 0 | 160824 | <reponame>dharshini-raman/SeniorYear<gh_stars>0
# Importing libraries
import pandas as pd
import numpy as np
import math
import operator
import matplotlib.pyplot as plt
from sklearn import datasets, neighbors
from mlxtend.plotting import plot_decision_regions
#### Start of STEP 1
# Importing data
data = pd.read_csv('artists1.csv')
#Normalization
#cols_to_norm = ['years', 'genre', 'nationality']
#data[cols_to_norm] = data[cols_to_norm].apply(lambda x: (x - x.min()) / (x.max()-x.min()) )
print(data.head(5))
# Defining a function which calculates euclidean distance between two data points
def euclideanDistance(data1, data2, length):
distance = 0
distance += np.square(data1[0] - data2[0])
distance += np.square(data1[1] - data2[1])
distance += (0.5*(np.square(data1[2] - data2[2])))
return np.sqrt(distance)
# Defining a function which calculates manhattan distance between two data points
def manhattanDistance(data1, data2, length):
distance = 0
for x in range(length):
distance += np.abs((data1[x] - data2[x]))
return (distance)
def L3(data1, data2, length):
distance = 0
for x in range(length):
distance += np.square((data1[x] - data2[x])) * (data1[x] - data2[x])
return (distance**(1/3))
# Defining our KNN model
def knn(trainingSet, testInstance, k):
distances = {}
sort = {}
length = testInstance.shape[1]
#### Start of STEP 3
# Calculating euclidean distance between each row of training data and test data
for x in range(len(trainingSet)):
#### Start of STEP 3.1
dist = euclideanDistance(testInstance, trainingSet.iloc[x], length)
distances[x] = dist[0]
#### End of STEP 3.1
#### Start of STEP 3.2
# Sorting them on the basis of distance
sorted_d = sorted(distances.items(), key=operator.itemgetter(1))
#### End of STEP 3.2
neighbors = []
#### Start of STEP 3.3
# Extracting top k neighbors
for x in range(k):
neighbors.append(sorted_d[x][0])
#### End of STEP 3.3
classVotes = {}
#### Start of STEP 3.4
# Calculating the most freq class in the neighbors
for x in range(len(neighbors)):
response = trainingSet.iloc[neighbors[x]][-1]
if response in classVotes:
classVotes[response] += 1
else:
classVotes[response] = 1
#### End of STEP 3.4
#### Start of STEP 3.5
sortedVotes = sorted(classVotes.items(), key=operator.itemgetter(1), reverse=True)
return(sortedVotes[0][0], neighbors)
#### End of STEP 3.5
testSet = [[1798, 3, 9]]
test = pd.DataFrame(testSet)
#### Start of STEP 2
# Setting number of neighbors = 1
print('\n\nWith 1 Nearest Neighbour \n\n')
k = 1
#### End of STEP 2
# Running KNN model
result,neigh = knn(data, test, k)
# Predicted class
print('\nPredicted Class of the datapoint = ', result)
# Nearest neighbor
print('\nNearest Neighbour of the datapoints = ',neigh)
print('\n\nWith 3 Nearest Neighbours\n\n')
# Setting number of neighbors = 3
k = 3
# Running KNN model
result,neigh = knn(data, test, k)
# Predicted class
print('\nPredicted class of the datapoint = ',result)
# Nearest neighbor
print('\nNearest Neighbours of the datapoints = ',neigh)
print('\n\nWith 5 Nearest Neighbours\n\n')
# Setting number of neighbors = 3
k = 5
# Running KNN model
result,neigh = knn(data, test, k)
# Predicted class
print('\nPredicted class of the datapoint = ',result)
# Nearest neighbor
print('\nNearest Neighbours of the datapoints = ',neigh)
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linkedList/143 reorder list.py | windowssocket/py_leetcode | 3 | 86874 | # Definition for singly-linked list.
# class ListNode(object):
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution(object):
def reorderList(self, head):
"""
:type head: ListNode
:rtype: void Do not return anything, modify head in-place instead.
"""
# 起码需要两个点
if head == None or head.next == None:
return
slow, fast = head, head
while fast.next != None and fast.next.next != None:
fast = fast.next.next
slow = slow.next
# 1->2->3->4->5
# low = 3
# 1->2->3->4->5->6
# low = 3
# 1->2->3->6->5->4
prevMiddle = slow
prevCurrent = prevMiddle.next
while prevCurrent.next != None:
current = prevCurrent.next
prevCurrent.next = current.next
current.next = prevMiddle.next
prevMiddle.next = current
# 1->6->2->5->3->4
p1 = head
p2 = prevMiddle.next
# 跳出条件
while p1 != prevMiddle:
prevMiddle.next = p2.next
p2.next = p1.next
p1.next = p2
p1 = p2.next
p2 = prevMiddle.next
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] |
tests/google/conftest.py | UUUM/backup-google-drive | 6 | 1617352 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
import os
import pytest
import gdsync
from gdsync.google.drive import Drive
TEST_FOLDER_NAME = 'gdsync-test'
@pytest.fixture()
def delete_db_file(request, sqlite_file):
def fin():
if os.path.isfile(sqlite_file):
os.unlink(sqlite_file)
request.addfinalizer(fin)
fin()
@pytest.fixture()
def sqlite_file(request):
return os.path.join(gdsync.VAR_DIR, 'test.db')
@pytest.fixture(scope='session')
def test_folder(request):
def fin():
res.delete()
request.addfinalizer(fin)
res = Drive().create_folder(TEST_FOLDER_NAME)
return res
@pytest.fixture(scope='session')
def dest_folder(request, test_folder):
def fin():
res.delete()
request.addfinalizer(fin)
res = test_folder.create_folder('バックアップ先')
return res
@pytest.fixture(scope='session')
def src_folder(request, test_folder):
def fin():
res.delete()
request.addfinalizer(fin)
res = test_folder.create_folder('バックアップ元')
sub_folder = res.create_folder('フォルダ')
sub_folder.create('テストsub', content='test')
return res
@pytest.fixture(scope='session')
def src_file(request, src_folder):
def fin():
for file in files:
file.delete()
request.addfinalizer(fin)
files = []
files.append(src_folder.create('テスト', content='test'))
files.append(src_folder.create('テスト', content='foo,bar', mime_type='text/csv'))
return files[0]
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] |
uzbplaces/urls.py | heykarimoff/uzbplaces | 2 | 188414 | from django.conf.urls import url
from apps.address import views
urlpatterns = [
url(r'^provinces/$', views.ProvinceList.as_view(), name='provinces'),
url(r'^regions/(?P<province>[0-9]+)/$', views.RegionList.as_view(), name='province_regions'),
url(r'^regions/(?P<province>[0-9]+)/(?P<code>[0-9]+)/$', views.RegionDetail.as_view(), name='region_detail'),
]
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old_stuff/serial_game/mb_control.py | jrmhaig/microbit_playground | 1 | 69512 | <gh_stars>1-10
import microbit
key_delay = 100
acc = microbit.accelerometer
a = microbit.button_a
b = microbit.button_b
img = microbit.display.image
while True:
microbit.display.clear()
x = acc.get_x()
y = acc.get_y()
if x > 300:
print('r')
img.set_pixel_value(4, 2, 1)
elif x < -300:
print('l')
img.set_pixel_value(0, 2, 1)
if y > 300:
print('d')
img.set_pixel_value(2, 4, 1)
elif y < -300:
print('u')
img.set_pixel_value(2, 0, 1)
if a.is_pressed():
print('a')
img.set_pixel_value(1, 2, 1)
if b.is_pressed():
print('b')
img.set_pixel_value(3, 2, 1)
microbit.sleep(key_delay)
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_singleActions-AsScripts/02_LoadPhotosInNewChunk.py | campbell-ja/MetashapePythonScripts | 4 | 118196 | <reponame>campbell-ja/MetashapePythonScripts
# This script created by <NAME> - 03/2021
""" Set up Working Environment """
# import Metashape library module
import Metashape
# create a reference to the current project via Document Class
doc = Metashape.app.document
""" Prompt User to Select Images """
# create array/list of images via user input gui
images = Metashape.app.getOpenFileNames()
""" Create New Chunk and Rename It """
# create new chunk to avoid changing any currently existing chunks
newChunk = doc.addChunk()
# set new chunk as active chunk
Metashape.app.document.chunk = newChunk
# set a new reference for the new chunk
activeChunk = newChunk
"""Rename the New Active Chunk"""
# get full list of chunks
chunkList = doc.chunks
# rename the new chunk,but only if it exists
# also add the integer position in chunks list
# this ensures each time the script runs each chunk has a unique name.
if activeChunk in chunkList:
activeChunk.label = 'pyChunk_' + str(len(chunkList)-1)
""" Add User Selected Photos to Active Chunk"""
# add images to chunk from array/list created earlier
activeChunk.addPhotos(images)
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r-net.py | gypleon/SQuAD | 0 | 53558 | import tensorflow as tf
import numpy as np
from word_embedding import WORD_EMBEDDING as WE
class R_NET(object):
'''
refer to
R-NET: Machine Reading Comprehension with Self-matching Networks
Natural Language Computing Group, Microsoft Research Asia
https://www.microsoft.com/en-us/research/publication/mrc/
'''
def __init__(self, path_dataset, path_vocab, batch_size = 1, train = True, dimension_word_embeddings = 300,
length_gru_state = 75, length_attention_state = 75, learning_rate = 1, dropout_keep_prob = 0.8,
rho = .95, epsilon = 1e-6):
self.path_ds = path_dataset
self.vocab = WE(path_vocab, dimension_word_embeddings)
self.batch_size = batch_size
self.len_gs = length_gru_state
self.len_as = length_attention_state
self.lr = learning_rate
self.keep_prob = dropout_keep_prob
self.rho = rho
self.eps = epsilon
self.graph = self.build()
@property
def answers(self):
return self.answers
def build(self, scope = 'rnet'):
''' build model graph
input:
questions: a batch of questions, []
passages: a batch of corresponding passage ids, recover passages from ids in order to reduce duplicated passage
copies in memory
answers: a batch of corresponding answers
output:
self.answers: predicted answers, [start_pointer, end_pointer]
self.losses: losses between predicted and target answers
'''
with tf.variable_scope(scope):
# placeholders
questions = tf.placeholder(tf.int32, shape=[self.batch_size, self.sequence_length, ])
passages = tf.placeholder()
# question and passage encoder
u_Q = self.encode(questions)
u_P = self.encode(passages)
# gated attention-based rnn
gated_u_P = self.gated_attn(u_Q, u_P)
# self-matching attention
h_P = self.self_matching_attn(gated_u_P)
# output layer - pointer networks
self.answers = output_layer(h_P, u_Q)
self.losses = tf.losses.softmax_cross_entropy(answers, self.answers)
return
def inference(self):
''' inference
input:
inputs: tuples of passage, question and answer: (passage, question, truth)
output:
losses:
'''
passages = tf.slice(inputs, [], [])
questions = tf.slice(inputs, [], [])
truths = tf.slice(inputs, [], [])
return self.answers, self.losses
def train(self):
optimizer = tf.train.AdadeltaOptimizer(learning_rate = self.lr, beta1 = self.rho, epsilon = self.eps)
optimizer.minimize(self.losses)
def encode(self, words):
''' encode token sequence as a list of new token representations
input:
words: list of tokens
output:
representations: list of final representations
'''
# TODO: new biRNN for each word? how to batch words for embedding?
# build graph for the longest word, traverse corpus in advance?
sequence = [self.embedding(word) for word in words]
outputs = self.bidirectionalGRU(sequence, 3)
representations = tf.squeeze(outputs)
return representations
def gated_attn(self, seq_1, seq_2, num_units = self.len_gs, scope = 'GatedAttn'):
''' gated attention for seq_2 w.r.t seq_1
input:
seq_1: query sequence in attention mechanism
seq_2: encoder sequence in attention mechanism
output:
outputs:
v_P:
context:
'''
u_Q = seq_1
u_P = seq_2
cell = self.GRUCellGPU(num_units)
with tf.variable_scope(scope):
attn_v = tf.get_variable('attn_v', [num_units])
w_u_Q = tf.get_variable('weight_ques')
w_u_P = tf.get_variable('weight_pass_orig')
w_v_P = tf.get_variable('weight_pass_ques')
v_P = tf.get_variable('embedding_pass_ques')
score = tf.reduce_sum(attn_v * tf.tanh(w_u_Q * u_Q + w_u_P * u_P + w_v_P * v_P), [2]) # scores of all tokens
alignments = tf.softmax(score)
alignments = tf.expand_dims(alignments, 1)
u_Q = tf.expand_dims(u_Q, 1)
context = tf.reduce_sum(tf.matmul(alignments, u_Q, transpose_b=True), [2])
# gate
inputs = tf.concat([u_Q, context], 1)
w_g = tf.get_variable('weight_gate')
g = tf.sigmoid(tf.reduce_sum(w_g * inputs))
gated_inputs = g * inputs
outputs, v_P = cell(gated_inputs, v_P)
return outputs, v_P
def self_matching_attn(self, seq, scope = 'SelfMatchAttn'):
''' self-matching attention of seq
input:
output:
'''
v_P = seq
with tf.variable_scope(scope):
attn_v = tf.get_variable('attn_v')
w_v_P = tf.get_variable('weight_passage')
w_v_P_w = tf.get_variable('weight_passage_wave')
score = tf.reduce_sum(attn_v * tf.tanh(w_v_P * v_P + w_v_P_w * v_P), [2]) # scores for all tokens
alignments = tf.softmax(score)
alignments = tf.expand_dims(alignments, 1)
v_P = tf.expand_dims(u_Q, 1)
context = tf.reduce_sum(tf.matmul(alignments, v_P, transpose_b=True), [2])
inputs = tf.concat([seq, context], 1)
outputs = self.bidirectionalGRU(inputs, 1)
h_P = outputs
return h_P
def output_layer(self, seq_1, seq_2, scope = 'PointerNetwork'):
h_P = seq_1
u_Q = seq_2
cell = self.GRUCellGPU(num_units)
with tf.variable_scope(scope):
# initialize hidden state of answer
attn_v_a = tf.get_varialbe('attn_v')
w_u_Q = tf.get_varialbe('weight_passage')
w_v_Q = tf.get_varialbe('weight_answer')
V_Q = tf.get_varialbe('weight_answer')
score_a = tf.reduce_sum(attn_v_a * tf.tanh(w_u_Q * u_Q + w_a * h_a), [2]) # scores for all tokens
alignments_a = tf.softmax(score_a)
r_Q = tf.reduce_sum(tf.matmul(alignments_a, u_Q, transpose_b=True), [2])
attn_v = tf.get_varialbe('attn_v')
w_P = tf.get_varialbe('weight_passage')
w_a = tf.get_varialbe('weight_answer')
h_a = tf.get_varialbe('embedding_answer')
score = tf.reduce_sum(attn_v * tf.tanh(w_P * h_P + w_a * h_a), [2]) # scores for all tokens
alignments = tf.softmax(score)
alignments = tf.expand_dims(alignments, 1)
v_P = tf.expand_dims(u_Q, 1)
context = tf.reduce_sum(tf.matmul(alignments, v_P, transpose_b=True), [2])
outputs, h_a = cell(h_a, context)
self.answer = outputs
return self.answer
def GRUCellGPU(self, num_units = self.len_gs, gpu_num = 0, scope = 'GRUCellGPU'):
''' wrapper GRUCell with Dropout & GPU device
'''
gru_cell = tf.contrib.rnn.DeviceWrapper(
tf.contrib.rnn.DropoutWrapper(
tf.nn.rnn_cell.GRUCell(num_units),
input_keep_prob = self.keep_prob, output_keep_prob = self.keep_prob, state_keep_prob = self.keep_prob),
"/device:GPU:%i" % gpu_num)
return gru_cell
def bidirectionalGRU(self, sequence, num_layers, num_units = self.len_gs, scope = 'bidirectionalGRU'):
''' bidirectional rnn layer using GRU cells
input:
sequence: sequencial token/char inputs
num_layers: number of bidirectionalGRU layers
num_units: number of dimension of GRU's hidden states
scope: name of variable scope
output:
results: results of biRNN layers, (outputs, output_state_fw, output_state_bw)
outputs: [batch_size, max_time, layers_output]
output_state_fw: final states, one tensor per layer, of the forward rnn.
output_state_bw: similiar to fw above.
'''
with tf.variable_scope(scope):
gru_fw = self.GRUCellGPU(num_units)
gru_bw = self.GRUCellGPU(num_units)
# shape: [batch_size, max_time_step, ...]
# TODO: decide batch_size_word based on the batch with the largest amount of unique words.
# char embedding: [batch_size_word, word_length, 300],
# sentence: [batch_size, seq_len, 300+75]
inputs = np.array([sequence])
# TODO: length of each sequence should be provided
outputs, _, _ = tf.contrib.rnn.stack_bidirectional_dynamic_rnn([gru_fw] * num_layers, [gru_bw] * num_layers,
inputs)
return outputs
def embedding(self, word, scope = 'embedding'):
'''
input:
word: tokenized word
output:
embed: embedding combining both word-level and character-level
'''
word_embed, char_embeds = self.vocab.embedding(word)
with tf.variable_scope(scope):
# char_embeds: [word_length, vocab_dim]
# TODO: dynamic word_length needs padding?
# NO need, since dynamic rnn adopted. But length of each word should be provided.
# TODO: BUT how to batch words?
# MAX_TIME should be provided, traverse words of a batch to get the largest word length
char_embed = self.bidirectionalGRU(char_embeds, 2)
embed = tf.concat([word_embed, char_embed], axis = 0)
return embed
if __name__ == '__main__':
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] |
tests/io/test_processing.py | syuoni/eznlp | 9 | 111696 | <gh_stars>1-10
# -*- coding: utf-8 -*-
import pytest
from eznlp.io import PostIO
@pytest.mark.parametrize("absorb_attr_types", [[],
['Analyzed'],
['Analyzed', 'Denied'],
['Unconfirmed', 'Analyzed', 'Denied']])
def test_absorb_attributes(absorb_attr_types, HwaMei_demo):
data = HwaMei_demo
post_io = PostIO()
data_abs = post_io.absorb_attributes(data, absorb_attr_types=absorb_attr_types)
assert all(attr_type not in absorb_attr_types for entry_abs in data_abs for attr_type, ck in entry_abs['attributes'])
if len(absorb_attr_types) > 0:
assert len(set(ck[0] for entry in data for ck in entry['chunks'])) < len(set(ck[0] for entry in data_abs for ck in entry['chunks']))
assert all(ck in entry['chunks'] for entry in data_abs for attr_type, ck in entry['attributes'])
assert all(head in entry['chunks'] and tail in entry['chunks'] for entry in data_abs for rel_type, head, tail in entry['relations'])
data_retr = post_io.exclude_attributes(data_abs)
assert all(entry['tokens'] == entry_retr['tokens'] for entry, entry_retr in zip(data, data_retr))
assert all(entry['chunks'] == entry_retr['chunks'] for entry, entry_retr in zip(data, data_retr))
assert all(set(entry['attributes']) == set(entry_retr['attributes']) for entry, entry_retr in zip(data, data_retr))
assert all(entry['relations'] == entry_retr['relations'] for entry, entry_retr in zip(data, data_retr))
@pytest.mark.parametrize("group_rel_types", [[],
['Group_DS', 'Group_Test'],
['Group_DS', 'Group_Test', 'Syn_Treat']])
def test_infer_relations(group_rel_types, HwaMei_demo):
data = HwaMei_demo
post_io = PostIO()
data_inf = post_io.infer_relations(data, group_rel_types=group_rel_types)
assert all(entry['tokens'] == entry_inf['tokens'] for entry, entry_inf in zip(data, data_inf))
assert all(entry['chunks'] == entry_inf['chunks'] for entry, entry_inf in zip(data, data_inf))
assert all(entry['attributes'] == entry_inf['attributes'] for entry, entry_inf in zip(data, data_inf))
assert all(set(entry['relations']).issubset(set(entry_inf['relations'])) for entry, entry_inf in zip(data, data_inf))
if len(group_rel_types) > 0:
assert sum(len(entry_inf['relations']) - len(entry['relations']) for entry, entry_inf in zip(data, data_inf)) == 14
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annex_counts_app/admin.py | birkin/annex_counts_project | 0 | 165196 | # -*- coding: utf-8 -*-
from .models import Counter
from django.contrib import admin
class CounterAdmin(admin.ModelAdmin):
list_display = [ 'create_datetime', 'date_key', 'hay_accessions', 'hay_refiles', 'non_hay_accessions', 'non_hay_refiles', 'notes' ]
list_filter = [
'create_datetime',
'date_key',
]
ordering = [ '-date_key' ]
readonly_fields = [ 'create_datetime' ]
prepopulated_fields = {}
save_on_top = True
## class CounterAdmin()
admin.site.register( Counter, CounterAdmin )
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torch/jit/_fuser.py | ljhOfGithub/pytorch | 1 | 11885 | <reponame>ljhOfGithub/pytorch
import contextlib
import torch
from typing import List, Tuple
@contextlib.contextmanager
def optimized_execution(should_optimize):
"""
A context manager that controls whether the JIT's executor will run
optimizations before executing a function.
"""
stored_flag = torch._C._get_graph_executor_optimize()
torch._C._set_graph_executor_optimize(should_optimize)
try:
yield
finally:
torch._C._set_graph_executor_optimize(stored_flag)
@contextlib.contextmanager
def fuser(name):
"""
A context manager that facilitates switching between
backend fusers.
Valid names:
* ``fuser0`` - enables only legacy fuser
* ``fuser1`` - enables only NNC
* ``fuser2`` - enables only nvFuser
"""
old_cpu_fuse = torch._C._jit_can_fuse_on_cpu()
old_gpu_fuse = torch._C._jit_can_fuse_on_gpu()
old_texpr_fuser_state = torch._C._jit_texpr_fuser_enabled()
old_nvfuser_state = torch._C._jit_nvfuser_enabled()
if name == 'fuser0': # legacy fuser
torch._C._jit_override_can_fuse_on_cpu(True)
torch._C._jit_override_can_fuse_on_gpu(True)
torch._C._jit_set_texpr_fuser_enabled(False)
torch._C._jit_set_nvfuser_enabled(False)
elif name == 'fuser1': # NNC
old_profiling_executor = torch._C._jit_set_profiling_executor(True)
old_profiling_mode = torch._C._jit_set_profiling_mode(True)
torch._C._jit_override_can_fuse_on_cpu(True)
torch._C._jit_override_can_fuse_on_gpu(True)
torch._C._jit_set_texpr_fuser_enabled(True)
torch._C._jit_set_nvfuser_enabled(False)
elif name == 'fuser2': # nvFuser
torch._C._jit_override_can_fuse_on_cpu(False)
torch._C._jit_override_can_fuse_on_gpu(False)
torch._C._jit_set_texpr_fuser_enabled(False)
torch._C._jit_set_nvfuser_enabled(True)
else:
raise Exception("unrecognized fuser option")
try:
yield
finally:
if name == 'fuser1': # NNC
torch._C._jit_set_profiling_executor(old_profiling_executor)
torch._C._jit_set_profiling_mode(old_profiling_mode)
# recover the previous values
torch._C._jit_override_can_fuse_on_cpu(old_cpu_fuse)
torch._C._jit_override_can_fuse_on_gpu(old_gpu_fuse)
torch._C._jit_set_texpr_fuser_enabled(old_texpr_fuser_state)
torch._C._jit_set_nvfuser_enabled(old_nvfuser_state)
last_executed_optimized_graph = torch._C._last_executed_optimized_graph
def _get_differentiable_graph_node(node, diff_node):
if node.kind() == 'prim::DifferentiableGraph':
diff_node.append(node)
else:
for block in node.blocks():
for n in block.nodes():
_get_differentiable_graph_node(n, diff_node)
def _graph_for(self, *args, **kwargs):
return _script_method_graph_for(self, self, *args, **kwargs)
def _script_method_graph_for(self, parent, *args, **kwargs):
try:
dbs = parent.get_debug_state()
eps = list(dbs.execution_plans.values())
assert(len(eps) == 1)
graph = eps[0].graph.copy()
# graph_executor_states for differentiable node
fw_states = eps[0].code.differentiable_op_executor_states()
diff_nodes: List[torch._C.Node] = []
for n in graph.nodes():
_get_differentiable_graph_node(n, diff_nodes)
assert(len(fw_states) == len(diff_nodes))
# swap each differentiable graph with optimized graph in their execution plan
for n, state in zip(diff_nodes, fw_states):
fw_execution_plans = list(state.execution_plans.values())
# we can only update the subgraph when there's a unique execution
# plan. Avoid assert here so we would skip the ones that can't be
# updated while try the best effort to update other nodes.
if len(fw_execution_plans) == 1:
n.g_('Subgraph', fw_execution_plans[0].graph)
return graph
except Exception:
# fallback approach, we just ran the graph and return the recorded optimized
# graph
self(*args, **kwargs)
return last_executed_optimized_graph()
def set_fusion_strategy(strategy: List[Tuple[str, int]]):
"""
Sets the type and number of specializations that can occur during fusion.
Usage: provide a list of pairs (type, depth) where type is one of "STATIC" or "DYNAMIC"
and depth is an integer.
Behavior - static vs dynamic:
In STATIC fusion, fused ops are compiled to have fixed input shapes. The shape is determined
based on some initial profiling runs.
In DYNAMIC fusion, fused ops are compiled to have variable input shapes, so that multiple
shapes are possible.
In both cases, we also recompile on new striding behavior, device, or dtype.
Behavior - fallback functions & depth:
When an input doesn't match the format required by the specialized compiled op, it will run
a fallback function. Fallback functions are recursively be compiled and specialized based
on the observed tensor shapes. Since compilation can be slow, the "depth" parameter is provided to
limit the number of specializations that can be compiled, before giving up on recompiling and
falling back to a completely un-fused, un-specialized implementation.
The list of (type, depth) pairs controls the type of specializations and the number of
specializations. For example: [("STATIC", 2), ("DYNAMIC", 2)] indicates that the first
two specializations will use static fusions, the following two specializations will use
dynamic fusion, and any inputs that satisfy none of the 4 options will run an
unfused implementation.
NB: in the future, if more as more fusion backends are added there may be more granular
apis for specific fusers.
"""
return torch._C._jit_set_fusion_strategy(strategy)
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estimate.py | rxm562/SeismoPi | 0 | 173639 | """
This file to define Estimate various parameters
"""
import numpy as np
import pandas as pd
from scipy.spatial import distance
import matplotlib.pyplot as plt
import networkx as nx
from pyproj import Proj
from pyproj import Proj, transform
# trasforming latlong into mercetor coordinates
def tran(data):
utmxy = {}
rx=[]
ry=[]
for index, row in data.iterrows():
x = row['x']
y = row['y']
inProj = Proj(init='epsg:4326')
outProj = Proj(init='epsg:3395')
cz = transform(inProj,outProj,x,y)
r1=cz[0]
r2=cz[1]
rx.append(r1)
ry.append(r2)
rx=np.array(rx)
ry=np.array(ry)
return rx,ry
# data1 and data2 should be node and link, respectively
def Length(data1,data2):
dist=[]
for index, row in data2.iterrows():
sp=data1[data1.id==row['start_node']]
start_x, start_y = (list(sp.x),list(sp.y))
ep=data1[data1.id==row['end_node']]
end_x,end_y=(list(ep.x),list(ep.y))
lal = distance.euclidean((start_x, start_y),(end_x,end_y))
dist.append(lal)
dist=np.array(dist)
return dist
# data1 and data2 should be node and link, respectively
def C_Check(data):
maint=[]
for index,row in data.iterrows():
if (row['ind']>=0.5) & (row['dl']>0):
mm=2
elif (row['ind']<0.5) & (row['dl']>0):
mm=1
else:
mm=0
maint.append(mm)
maint=np.array(maint)
return maint
def C_Est(data):
cost=[]
for index,row in data.iterrows():
if (row['MA']==1):
mm=row['repair_C']*row['nNoB']
elif (row['MA']==2):
mm=row['replace_C']
else:
mm=0
cost.append(mm)
cost=np.array(cost)
return cost
def T_cost(data,pipe_cost=None):
"""
"""
nrpr = []
nrpl = []
network_cost = 0
if pipe_cost is None:
diameter = [4, 6, 8, 10, 12, 14, 16, 18, 20, 24, 28, 30, 32, 34, 36] # inch
rpl = [600, 630, 675, 750, 825, 1200, 1950, 2400, 2700, 3450, 4350, 4650, 5250, 5700, 6300] # replace cost/m
rpr = [400, 420, 450, 500, 550, 800, 1300, 1600, 1800, 2300, 2900, 3100, 3500, 3800, 4200] # repair cost
# diameter = np.array(diameter)*0.0254 # m
repair_cost = pd.Series(rpr,diameter)
replace_cost = pd.Series(rpl,diameter)
# Pipe construction cost
for index, row in data.iterrows():
dia = row['dia']
length=row['link_m']
idxrpr = np.argmin([np.abs(repair_cost.index - dia)])
idxrpl = np.argmin([np.abs(replace_cost.index - dia)])
#print(link_name, pipe_cost.iloc[idx], link.length)
repair_C = network_cost + repair_cost.iloc[idxrpr]
replace_C = network_cost + replace_cost.iloc[idxrpl]*length
nrpr.append(repair_C)
nrpl.append(replace_C)
nrpr = np.array(nrpr)
nrpl = np.array(nrpl)
return nrpr,nrpl
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] |
tests/algorithms/test_rigid_body.py | UCL/scikit-surgeryarucotracker | 0 | 161996 | <reponame>UCL/scikit-surgeryarucotracker<filename>tests/algorithms/test_rigid_body.py
# -*- coding: utf-8 -*-
"""Tests for the rigid body classes"""
import pytest
import numpy as np
from cv2 import aruco
import sksurgeryarucotracker.algorithms.rigid_bodies as rgbd
# pylint: disable=no-member
def test_rigid_body_init():
"""
Test class initialises
"""
#pylint: disable=protected-access
rigid_body = rgbd.ArUcoRigidBody(rigid_body_name = 'test')
rigid_body.load_3d_points('data/reference.txt', 'DICT_ARUCO_ORIGINAL')
pattern_wdth = min(np.ptp([i[:,0] for i in rigid_body._ar_board.objPoints]),
np.ptp([i[:,1] for i in rigid_body._ar_board.objPoints]))
assert pattern_wdth == 49.50
rigid_body.scale_3d_tags(measured_pattern_width = 10)
pattern_wdth = min(np.ptp([i[:,0] for i in rigid_body._ar_board.objPoints]),
np.ptp([i[:,1] for i in rigid_body._ar_board.objPoints]))
assert pattern_wdth == 10.00
def test_make_aruco_no_board():
"""
Test for make aruco board fails when no board entries
"""
with pytest.raises(ValueError):
board = np.zeros((0,0),dtype = np.float64)
rgbd._make_aruco_board(board, aruco.DICT_ARUCO_ORIGINAL) \
#pylint: disable=protected-access
def test_make_aruco_wrong_board():
"""
Test for make aruco board fails when no board is wrong shape
"""
with pytest.raises(ValueError):
board = np.zeros((1,4),dtype = np.float64)
rgbd._make_aruco_board(board, aruco.DICT_ARUCO_ORIGINAL) \
#pylint: disable=protected-access
def test_configuration():
"""
Tests for the configuration routine.
"""
#should throw a value error if there is no filename
configuration = {
'rigid bodies' : [{}]
}
with pytest.raises(ValueError):
rgbd.configure_rigid_bodies(configuration)
#should throw a value error for a made up dictionary
configuration = {
'rigid bodies' : [{
'filename' : 'data/reference.txt',
'aruco dictionary' : 'made up'
}]
}
with pytest.raises(ImportError):
rgbd.configure_rigid_bodies(configuration)
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2
] |
ClientePY.py | G2000G/webService-java | 0 | 95167 | <filename>ClientePY.py
from suds.client import Client
url = "http://localhost:13000/conversor?wsdl"
client = Client(url)
tipo = int(input("Bem-vindo ao Conversor de Temperaturas, digite: \n1 para converter de Celsius para Kelvin: \n2 para converter de Kelvin para Celsius:\n>>> "))
temp = int(input("Digite a temperatura que deseja converter:\n>>> "))
response = client.service.conversor(tipo,temp)
print(response)
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src/mlb_statsapi/model/api/config.py | power-edge/mlb_statsapi_etl | 0 | 153604 | <gh_stars>0
"""
created by nikos at 4/26/21
"""
import os.path
from ..base import MLBStatsAPIEndpointModel
from mlb_statsapi.utils.stats_api_object import configure_api
class ConfigModel(MLBStatsAPIEndpointModel):
@configure_api
def awards(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def baseballStats(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def eventTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def fielderDetailTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def gameStatus(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def gameTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def gamedayTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def groupByTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def hitTrajectories(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def jobTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def languages(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def leagueLeaderTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def logicalEvents(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def metrics(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def pitchCodes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def pitchTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def platforms(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def playerStatusCodes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def positions(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def reviewReasons(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def rosterTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def runnerDetailTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def scheduleEventTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def sitCodes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def sky(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def aggregateSortEnum(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def standingsTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statFields(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statGroups(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statSearchConfig(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statSearchGroupByTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statSearchParams(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def statSearchStats(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def transactionTypes(self, **kwargs):
return self.get_api_file_object(**kwargs)
@configure_api
def windDirection(self, **kwargs):
return self.get_api_file_object(**kwargs)
@property
def _methods(self): return {m.__name__: m for m in (
self.awards,
self.baseballStats,
self.eventTypes,
self.fielderDetailTypes,
self.gameStatus,
self.gameTypes,
self.gamedayTypes,
self.groupByTypes,
self.hitTrajectories,
self.jobTypes,
self.languages,
self.leagueLeaderTypes,
self.logicalEvents,
self.metrics,
self.pitchCodes,
self.pitchTypes,
self.platforms,
self.playerStatusCodes,
self.positions,
self.reviewReasons,
self.rosterTypes,
self.runnerDetailTypes,
self.scheduleEventTypes,
self.sitCodes,
self.sky,
self.aggregateSortEnum,
self.standingsTypes,
self.statFields,
self.statGroups,
self.statTypes,
self.statSearchConfig,
self.statSearchGroupByTypes,
self.statSearchParams,
self.statSearchStats,
self.transactionTypes,
self.windDirection,
)}
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snoop/management/commands/doctor.py | hoover/snoop | 5 | 92399 | <filename>snoop/management/commands/doctor.py
from pathlib import Path
import subprocess
import re
import sys
import urllib.request
import urllib.error
import json
from django.core.management.base import BaseCommand
from django.conf import settings
from django.db import connections
from django.db.utils import OperationalError
ELASTICSEARCH_MIN_VERSION = (2, 0, 0)
ELASTICSEARCH_MAX_VERSION = (2, 4, 4)
PST_MIN_VERSION = (0, 2, 0)
TIKA_MIN_VERSION = (1, 13)
def path_exists(path):
return Path(path).exists()
def http_get_content(link):
try:
with urllib.request.urlopen(link) as content:
return content.read()
except (urllib.error.HTTPError, urllib.error.URLError):
return None
def get_version(exe_path, version_argument='--version',
regex=r'([\d\.]+)', check_output=True,
is_numeric=True):
if check_output:
output = subprocess.check_output([exe_path, version_argument])
else:
completed = subprocess.run(
[exe_path, version_argument],
check=False,
stderr=subprocess.STDOUT,
stdout=subprocess.PIPE)
output = completed.stdout
string_output = str(output)
matches = re.search(regex, string_output, re.MULTILINE)
if not matches:
return None
if is_numeric:
return tuple(int(x) for x in matches.group(1).split("."))
return matches.group(1)
class Command(BaseCommand):
help = "Sanity check for snoop. Run with no arguments."
def handle(self, *args, **options):
checkers = [
('python', self.check_python, False),
('database', self.check_database, False),
('elasticsearch', self.check_es, False),
('msgconvert', self.check_msgconvert, settings.SNOOP_MSGCONVERT_SCRIPT is None),
('readpst', self.check_readpst, settings.SNOOP_READPST_BINARY is None),
('Apache Tika', self.check_tika, settings.SNOOP_TIKA_SERVER_ENDPOINT is None),
('7z', self.check_7z, settings.SNOOP_SEVENZIP_BINARY is None),
('gpg', self.check_gpg, settings.SNOOP_GPG_BINARY is None),
]
have_errors = False
for name, check_fun, skip in checkers:
if skip:
self.print_message("Skipping the check for " + name + ".")
else:
self.print_message("Checking " + name + ".")
result = check_fun()
if result:
self.print_success(' ' * 9 + name + " ok.")
else:
have_errors = True
self.print_error(name + " failed the check.")
self.print_message('')
if have_errors:
self.print_error("The setup has failed some checks.")
self.print_error("For more information please see")
self.print_error("https://github.com/hoover/snoop/blob/master/Readme.md")
sys.exit(1)
else:
self.print_success("All checks have passed.")
def check_python(self):
if sys.version_info[0] != 3 or sys.version_info[1] < 5:
self.print_error("The Python version supplied is {}.".format(sys.version))
self.print_error("Hoover needs at least Python 3.5 to work.")
self.print_error("Please use a supported version of Python.")
return False
return True
def check_database(self):
db_conn = connections['default']
try:
c = db_conn.cursor()
except OperationalError:
self.print_error("The database settings are not valid.")
self.print_error("Please check the database access data under DATABASES.")
return False
return True
def check_msgconvert(self):
msgconvert_path = settings.SNOOP_MSGCONVERT_SCRIPT
if not path_exists(msgconvert_path):
self.print_error("You enabled msgconvert support but")
self.print_error("SNOOP_MSGCONVERT_SCRIPT is not set to a valid path.")
return False
version = get_version(msgconvert_path, '--help', regex='(msgconvert)',
check_output=False, is_numeric=False)
if not version:
self.print_error("Could run the script provided in SNOOP_MSGCONVERT_SCRIPT")
return False
cache_dir = settings.SNOOP_MSG_CACHE
if not cache_dir or not Path(cache_dir).is_dir():
self.print_error("SNOOP_MSG_CACHE does not point to a valid directory.")
return False
return True
def check_readpst(self):
readpst_path = settings.SNOOP_READPST_BINARY
if not path_exists(readpst_path):
self.print_error("You enabled readpst support but")
self.print_error("SNOOP_READPST_BINARY is not set to a valid path.")
return False
version = get_version(readpst_path, '-V')
if not version:
self.print_error("Failed to check the readpst version.")
self.print_error("Please check if SNOOP_READPST_BINARY points to a valid executable.")
return False
if version < PST_MIN_VERSION:
self.print_error("Please install a more recent version of readpst.")
return False
cache_dir = settings.SNOOP_PST_CACHE_ROOT
if not cache_dir or not Path(cache_dir).is_dir():
self.print_error("SNOOP_PST_CACHE_ROOT does not point to a valid directory.")
return False
return True
def check_es(self):
es_link = settings.SNOOP_ELASTICSEARCH_URL
content = http_get_content(es_link)
if not content:
self.print_error("Could not connect to elasticsearch using")
self.print_error("the link supplied in SNOOP_ELASTICSEARCH_URL.")
return False
try:
data = json.loads(content)
except json.JSONDecodeError:
self.print_error("elasticsearch's response could not be decoded.")
self.print_error("Please restart the elasticsearch server and try again.")
return False
version_string = data['version']['number']
version_string = re.sub(r'[^\d\.]+', '', version_string)
version = tuple(int(x) for x in version_string.split('.'))
if not ELASTICSEARCH_MIN_VERSION <= version <= ELASTICSEARCH_MAX_VERSION:
self.print_error("elasticsearch is version {}, but".format(version))
self.print_error("Hoover needs elasticsearch to be in between versions")
self.print_error("{} and {}".format(ELASTICSEARCH_MIN_VERSION,
ELASTICSEARCH_MAX_VERSION))
return False
return True
def check_tika(self):
tika_link = settings.SNOOP_TIKA_SERVER_ENDPOINT
content = http_get_content(tika_link + "/version")
if not content:
self.print_error("Could not connect to Apache Tika using")
self.print_error("the link supplied in SNOOP_TIKA_SERVER_ENDPOINT.")
return False
version_string = str(content)
matches = re.search('([\d\.]+)', version_string, re.MULTILINE)
if not matches:
self.print_error("Apache Tika's response did not contain a valid version number.")
self.print_error("Please restart the Apache Tika server and try again.")
return False
version_string = matches.group(1)
version = tuple(int(x) for x in version_string.split('.'))
if version < TIKA_MIN_VERSION:
self.print_error("tika is version {}, but")
self.print_error("Hoover needs tika to be at least version {}".format(TIKA_MIN_VERSION))
self.print_error("Download tika from https://tika.apache.org/download")
return False
return True
def check_7z(self):
seven_zip_path = settings.SNOOP_SEVENZIP_BINARY
if not path_exists(seven_zip_path):
self.print_error("You enabled 7z support but")
self.print_error("SNOOP_SEVENZIP_BINARY is not set to a valid path.")
return False
version = get_version(seven_zip_path, '--help', r'Version +([\d\.]+)', is_numeric=False)
if not version:
self.print_error("Failed to check the version for 7z.")
self.print_error("Please check if SNOOP_SEVENZIP_BINARY points to a valid executable.")
return False
cache_dir = settings.SNOOP_ARCHIVE_CACHE_ROOT
if not cache_dir or not Path(cache_dir).is_dir():
self.print_error("SNOOP_ARCHIVE_CACHE_ROOT does not point to a valid directory.")
return False
return True
def check_gpg(self):
gpg_path = settings.SNOOP_GPG_BINARY
if not path_exists(gpg_path):
self.print_error("You enabled gpg support but")
self.print_error("SNOOP_GPG_BINARY is not set to a valid path.")
return False
version = get_version(gpg_path)
if not version:
self.print_error("Failed to check the version for gpg.")
self.print_error("Please check if SNOOP_GPG_BINARY points to a valid executable.")
return False
cache_dir = settings.SNOOP_GPG_HOME
if not cache_dir or not Path(cache_dir).is_dir():
self.print_error("SNOOP_GPG_HOME does not point to a valid directory.")
return False
return True
def print_error(self, string):
self.stdout.write(self.style.ERROR(string))
def print_message(self, string):
self.stdout.write(string)
def print_success(self, string):
self.stdout.write(self.style.SUCCESS(string))
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2
] |
tests/integration/test_security.py | Rogdham/bigxml | 4 | 105719 | <reponame>Rogdham/bigxml
from defusedxml import EntitiesForbidden
import pytest
from bigxml import Parser
def handler_get_text(node):
yield node.text
@pytest.mark.parametrize(
"xml",
(
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a "bigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbig">\n'
b"]>\n"
b"<root>&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;</root>\n"
),
id="one entity (1kb)",
),
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a "bigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbig">\n'
b' <!ENTITY b "&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;">\n'
b' <!ENTITY c "&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;">\n'
b' <!ENTITY d "&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;">\n'
b' <!ENTITY e "&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;">\n'
b"]>\n"
b"<root>&e;</root>\n"
),
id="bomb (5Mb)",
),
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a "bigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbigbig">\n'
b' <!ENTITY b "&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;&a;">\n'
b' <!ENTITY c "&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;&b;">\n'
b' <!ENTITY d "&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;&c;">\n'
b' <!ENTITY e "&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;&d;">\n'
b' <!ENTITY f "&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;&e;">\n'
b' <!ENTITY g "&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;&f;">\n'
b' <!ENTITY h "&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;&g;">\n'
b"]>\n"
b"<root>&h;</root>\n"
),
id="bomb (33Gb)",
),
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a "something &b;">\n'
b' <!ENTITY b "&a;">\n'
b"]>\n"
b"<root>&a;</root>\n"
),
id="recursive",
),
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a SYSTEM "file:///etc/hosts">\n'
b"]>\n"
b"<root>&a;</root>\n"
),
id="resolution (file)",
),
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a SYSTEM "https://example.com/">\n'
b"]>\n"
b"<root>&a;</root>\n"
),
id="resolution (http)",
),
pytest.param(
(
b"<!DOCTYPE foobar [\n"
b' <!ENTITY a SYSTEM "expect://id">\n'
b"]>\n"
b"<root>&a;</root>\n"
),
id="resolution (expect)",
),
),
)
def test_external_entities(xml):
with pytest.raises(EntitiesForbidden):
Parser(xml).return_from(handler_get_text)
| [
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task_scripts/merge_seginfo.py | ZettaAI/Synaptor | 7 | 49289 | """
Segment Info Merging Wrapper Script
- Takes an id mapping across segments as input
- Merges the segment info dataframes into one for the entire dataset
"""
import synaptor as s
import argparse
parser = argparse.ArgumentParser()
# Inputs & Outputs
parser.add_argument("storagestr")
parser.add_argument("hashval", type=int)
parser.add_argument("--aux_storagestr", default=None)
parser.add_argument("--timing_tag", default=None)
parser.add_argument("--szthresh", type=int, default=None)
args = parser.parse_args()
args.storagestr = s.io.parse_storagestr(args.storagestr)
args.aux_storagestr = s.io.parse_storagestr(args.aux_storagestr)
print(vars(args))
s.proc.tasks_w_io.merge_seginfo_task(**vars(args))
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tests/connect_tests.py | adyekjaer/VersionOne.SDK.Python | 2 | 42117 | <filename>tests/connect_tests.py
from testtools import TestCase
from testtools.assertions import assert_that
from testtools.matchers import Equals
from testtools.content import text_content
import sys
if sys.version_info >= (3,0):
from urllib.error import HTTPError
else:
from urllib2 import HTTPError
# try the old version, then fallback to the new one
try:
from xml.etree import ElementTree
from xml.etree.ElementTree import parse, fromstring, Element
except ImportError:
from elementtree import ElementTree
from elementtree.ElementTree import parse, fromstring, Element
from v1pysdk.client import *
from v1pysdk import V1Meta
from .common_test_server import PublicTestServerConnection
class TestV1Connection(TestCase):
def test_connect(self):
username = PublicTestServerConnection.username
password = <PASSWORD>
address = PublicTestServerConnection.address
instance = PublicTestServerConnection.instance
self.addDetail('URL', text_content(address + "/" + instance))
self.addDetail('username', text_content(username))
server = V1Server(address=address, username=username, password=password,instance=instance)
# The story names, but limit to only the first result so we don't get inundated with results
code, body = server.fetch('/rest-1.v1/Data/Story?sel=Name&page=1,0')
self.addDetail('Code', text_content(str(code)))
self.addDetail('Body', text_content(str(body)))
elem = fromstring(body)
self.assertThat(elem.tag, Equals('Assets'))
def test_meta_connect_instance_url(self):
v1 = None
self.addDetail('URL', text_content(PublicTestServerConnection.instance_url))
self.addDetail('username', text_content(PublicTestServerConnection.username))
try:
v1 = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
username = PublicTestServerConnection.username,
password = <PASSWORD>TestServerConnection.password,
)
except Exception as e:
assert_that(False, Equals(True), message="Error trying to create connection: " + str(e))
try:
items = v1.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from connection: " + str(e))
def test_meta_connect_instance_and_address(self):
v1 = None
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance', text_content(PublicTestServerConnection.instance))
self.addDetail('username', text_content(PublicTestServerConnection.username))
try:
v1 = V1Meta(
address = PublicTestServerConnection.address,
instance = PublicTestServerConnection.instance,
username = PublicTestServerConnection.username,
password = <PASSWORD>,
)
except Exception as e:
assert_that(False, Equals(True), message="Error trying to create connection: " + str(e))
try:
items = v1.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from connection: " + str(e))
def test_meta_connect_instance_url_overrides_separate(self):
v1 = None
address = self.getUniqueString() #garbage
instance = self.getUniqueString() #garbage
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance-url', text_content(PublicTestServerConnection.instance_url))
self.addDetail('instance', text_content(address))
self.addDetail('username', text_content(instance))
try:
v1 = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
address = address,
instance = instance,
username = PublicTestServerConnection.username,
password = <PASSWORD>,
)
except Exception as e:
assert_that(False, Equals(True), message="Error trying to create connection: " + str(e))
try:
items = v1.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from connection: " + str(e))
def test_meta_connect_oauth(self):
v1 = None
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance', text_content(PublicTestServerConnection.instance))
try:
v1 = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
#no username
password = <PASSWORD>,
use_password_as_token=True,
)
except Exception as e:
assert_that(False, Equals(True), message="Error trying to create connection: " + str(e))
try:
items = v1.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from connection: " + str(e))
def test_meta_connect_oauth_ignores_username(self):
v1 = None
username = self.getUniqueString() #garbage
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance', text_content(PublicTestServerConnection.instance))
self.addDetail('username', text_content(username))
try:
v1 = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
username = username,
password = <PASSWORD>,
use_password_as_token=True,
)
except Exception as e:
assert_that(False, Equals(True), message="Error trying to create connection: " + str(e))
try:
items = v1.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from connection: " + str(e))
def test_connect_fails_when_invalid(self):
v1bad = None
username = self.getUniqueString() #garbage
password = <PASSWORD>.getUniqueString() #garbage
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance', text_content(PublicTestServerConnection.instance))
self.addDetail('bad-username', text_content(username))
self.addDetail('bad-password', text_content(password))
try:
v1bad = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
username = username,
password = password,
use_password_as_token=False,
)
# we have to try to use it to get it to connect and fail
items = v1bad.Story.select('Name').page(size=1)
items.first() #run the query
except HTTPError as e:
assert_that(e.code, Equals(401), message="Connection failed for reasons other than authorization")
else:
assert_that(False, Equals(True), message="Connection succeeded with bad credentials")
def test_reconnect_succeeds_after_invalid(self):
v1bad = None
username = self.getUniqueString() #garbage
password = <PASSWORD>() #garbage
self.addDetail('bad-username', text_content(username))
self.addDetail('bad-password', text_content(password))
try:
v1bad = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
username = username,
password = password,
use_password_as_token=False,
)
items = v1bad.Story.select('Name').page(size=1)
items.first() #run the query
except HTTPError as e:
assert_that(e.code, Equals(401), message="Connection failed for reasons other than authorization")
else:
assert_that(False, Equals(True), message="First connection succeeded with bad credentials, cannot continue test")
v1good = None
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance', text_content(PublicTestServerConnection.instance))
# Connect correctly first
try:
v1good = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
password = PublicTestServerConnection.token,
use_password_as_token=True,
)
items = v1good.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from good connection: " + str(e))
def test_reconnect_fails_when_invalid(self):
v1good = None
self.addDetail('address', text_content(PublicTestServerConnection.address))
self.addDetail('instance', text_content(PublicTestServerConnection.instance))
# Connect correctly first
try:
v1good = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
password = <PASSWORD>,
use_password_as_token=True,
)
items = v1good.Story.select('Name').page(size=1)
items.first() #run the query
except Exception as e:
assert_that(False, Equals(True), message="Error running query from good connection, cannot perform test: " + str(e))
v1bad = None
username = self.getUniqueString() #garbage
password = <PASSWORD>.getUniqueString() #garbage
self.addDetail('bad-username', text_content(username))
self.addDetail('bad-password', text_content(password))
try:
v1bad = V1Meta(
instance_url = PublicTestServerConnection.instance_url,
username = username,
password = password,
use_password_as_token=False,
)
items = v1bad.Story.select('Name').page(size=1)
items.first() #run the query
except HTTPError as e:
assert_that(e.code, Equals(401), message="Connection failed for reasons other than authorization")
else:
assert_that(False, Equals(True), message="Second connection succeeded with bad credentials")
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src/bratdb/scripts/build.py | kpwhri/bratdb | 0 | 155368 | from bratdb.reader import build_brat_dump
from bratdb.logger import initialize_logging
def main():
import argparse
parser = argparse.ArgumentParser(fromfile_prefix_chars='@!')
parser.add_argument('anndir',
help='Path to directory containing brat annotation files')
parser.add_argument('txtdir', default=None,
help='Path to directory containing brat annotation files')
parser.add_argument('outdir', default='bratdb',
help='Path to output directory where brat data will be stored.')
parser.add_argument('--logdir', default='.',
help='Directory to place log files.')
args = parser.parse_args()
initialize_logging(logdir=args.logdir)
build_brat_dump(args.anndir, args.txtdir, args.outdir)
if __name__ == '__main__':
main()
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{{cookiecutter.directory_name}}/config/settings/development.py | ragnarok22/cookiecutter-django | 2 | 28724 | <reponame>ragnarok22/cookiecutter-django
"""
This is the settings file that you use when you're working on the project locally.
Local development-specific include DEBUG mode, log level, and activation of developer tools like django-debug-toolsbar
"""
from .base import *
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '<KEY>'
ALLOWED_HOSTS = ['*']
MEDIA_ROOT = os.path.join(BASE_DIR, '{{cookiecutter.directory_name}}', 'media')
# email settings
EMAIL_BACKEND = 'django.core.mail.backends.console.EmailBackend'
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git_verkefni_forritun.py | JonasFreyrB/Forritun | 0 | 14176 | #<NAME>
#25.01.2017
#Forritun
#Liður 1
#Byð notanda um tölu 1
tala1=int(input("Sláðu inn tölu 1 "))
#Byð notanda um tölu 2
tala2=int(input("Sláðu inn tölu 2 "))
#Birti tölu 1 og 2 lagðar saman
print("Tölurnar lagðar saman ",tala1+tala2)
#Birti tölu 1 og 2 margfaldaðar saman
print("Tölurnar margfaldaðar saman ",tala1*tala2)
#Liður 2
#Byð notanda um fornafn
fornafn=input("Sláðu inn fornafnið þitt ")
#Byð notanda um eftirnafn
eftirnafn=input("Sláðu inn eftirnafnið þitt ")
#Birti skilaboð ásamt bæði nöfnin lögð saman
print("Halló",fornafn,eftirnafn)
#Liður 3
#Byð notanda um texta
text=input("Sláðu inn texta ")
#Bý til teljara fyrir lágstafi
tellagstafi=0
#Bý til teljara fyrir hágstafi
telhastafi=0
#Bý til teljara fyrir lágstafi á eftir hástafi
tellagstafieftir=0
#Bý til for lykkju sem keyrir í gegnum textann
for x in range(len(text)):
#Ef stafurinn í texta er bókstafur og er í hástaf
if (text[x].isalpha() and text[x].isupper()):
#Bæti 1 við teljara fyrir hágstafi
telhastafi=telhastafi+1
#Ef næsti stafur er lágstafur
if (text[x +1].islower()):
#Bæti 1 við teljara fyrir lágstafi á eftir hástafi
tellagstafieftir=tellagstafieftir+1
#Ef stafurinn í texta er bókstafur og er í lágstaf
elif(text[x].isalpha() and text[x].islower()):
#Bæti 1 við teljara fyrir lágstafi
tellagstafi=tellagstafi+1
#Birti fjölda hástafi
print("Það komu",telhastafi,"hástafir")
#Birti fjölda lágstafi
print("Það komu",tellagstafi,"lágstafir")
#Birti fjölda lágstafi á eftir hástafi
print("Það komu",tellagstafieftir,"lágstafir koma strax á eftir hástaf")
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application/core/factory/account_factory.py | yntonfon/dashboard-plus | 0 | 41551 | from application.core.entity.account import Account
from application.core.port.create_account_port import CreateAccountPort
class AccountFactory(CreateAccountPort):
def create_account(self, payload: dict) -> Account:
return Account(**payload)
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nls/_speech_transcriber.py | aliyun/alibabacloud-nls-python-sdk | 15 | 177968 | """
_speech_transcriber.py
Copyright 1999-present Alibaba Group Holding Ltd.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless 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.
"""
import logging
import uuid
import json
import threading
from nls._core import NlsCore
from . import _logging
__SPEECH_TRANSCRIBER_NAMESPACE__ = "SpeechTranscriber"
__SPEECH_TRANSCRIBER_REQUEST_CMD__ = {
"start": "StartTranscription",
"stop": "StopTranscription",
"control": "ControlTranscriber"
}
__URL__ = "wss://nls-gateway.cn-shanghai.aliyuncs.com/ws/v1"
__all__ = ["NlsSpeechTranscriber"]
class NlsSpeechTranscriber:
"""
Api for realtime speech transcription
"""
def __init__(self, url=__URL__,
akid=None, aksecret=None,
token=None, appkey=None,
on_start=None,
on_sentence_begin=None,
on_sentence_end=None,
on_result_changed=None,
on_completed=None,
on_error=None, on_close=None,
callback_args=[]):
"""
NlsSpeechTranscriber initialization
Parameters:
-----------
url: str
websocket url.
akid: str
access id from aliyun. if you provide a token, ignore this argument.
aksecret: str
access secret key from aliyun. if you provide a token, ignore this
argument.
token: str
access token. if you do not have a token, provide access id and key
secret from your aliyun account.
appkey: str
appkey from aliyun
on_start: function
Callback object which is called when recognition started.
on_start has two arguments.
The 1st argument is message which is a json format string.
The 2nd argument is *args which is callback_args.
on_sentence_begin: function
Callback object which is called when one sentence started.
on_sentence_begin has two arguments.
The 1st argument is message which is a json format string.
The 2nd argument is *args which is callback_args.
on_sentence_end: function
Callback object which is called when sentence is end.
on_sentence_end has two arguments.
The 1st argument is message which is a json format string.
The 2nd argument is *args which is callback_args.
on_result_changed: function
Callback object which is called when partial recognition result
arrived.
on_result_changed has two arguments.
The 1st argument is message which is a json format string.
The 2nd argument is *args which is callback_args.
on_completed: function
Callback object which is called when recognition is completed.
on_completed has two arguments.
The 1st argument is message which is a json format string.
The 2nd argument is *args which is callback_args.
on_error: function
Callback object which is called when any error occurs.
on_error has two arguments.
The 1st argument is message which is a json format string.
The 2nd argument is *args which is callback_args.
on_close: function
Callback object which is called when connection closed.
on_close has one arguments.
The 1st argument is *args which is callback_args.
callback_args: list
callback_args will return in callbacks above for *args.
"""
self.__response_handler__ = {
"SentenceBegin": self.__sentence_begin,
"SentenceEnd": self.__sentence_end,
"TranscriptionStarted": self.__transcription_started,
"TranscriptionResultChanged": self.__transcription_result_changed,
"TranscriptionCompleted": self.__transcription_completed,
"TaskFailed": self.__task_failed
}
self.__callback_args = callback_args
self.__url = url
self.__akid = akid
self.__aksecret = aksecret
self.__appkey = appkey
self.__token = token
self.__start_cond = threading.Condition()
self.__start_flag = False
self.__on_start = on_start
self.__on_sentence_begin = on_sentence_begin
self.__on_sentence_end = on_sentence_end
self.__on_result_changed = on_result_changed
self.__on_completed = on_completed
self.__on_error = on_error
self.__on_close = on_close
self.__allow_aformat = (
"pcm", "opus", "opu"
)
def __handle_message(self, message):
_logging.debug("__handle_message")
try:
__result = json.loads(message)
if __result["header"]["name"] in self.__response_handler__:
__handler = self.__response_handler__[
__result["header"]["name"]]
__handler(message)
else:
_logging.error("cannot handle cmd{}".format(
__result["header"]["name"]))
return
except json.JSONDecodeError:
_logging.error("cannot parse message:{}".format(message))
return
def __tr_core_on_open(self):
_logging.debug("__tr_core_on_open")
def __tr_core_on_msg(self, msg, *args):
_logging.debug("__tr_core_on_msg:msg={} args={}".format(msg, args))
self.__handle_message(msg)
def __tr_core_on_error(self, msg, *args):
_logging.debug("__tr_core_on_error:msg={} args={}".format(msg, args))
def __tr_core_on_close(self):
_logging.debug("__tr_core_on_close")
if self.__on_close:
self.__on_close(*self.__callback_args)
with self.__start_cond:
self.__start_flag = False
self.__start_cond.notify()
def __sentence_begin(self, message):
_logging.debug("__sentence_begin")
if self.__on_sentence_begin:
self.__on_sentence_begin(message, *self.__callback_args)
def __sentence_end(self, message):
_logging.debug("__sentence_end")
if self.__on_sentence_end:
self.__on_sentence_end(message, *self.__callback_args)
def __transcription_started(self, message):
_logging.debug("__transcription_started")
if self.__on_start:
self.__on_start(message, *self.__callback_args)
with self.__start_cond:
self.__start_flag = True
self.__start_cond.notify()
def __transcription_result_changed(self, message):
_logging.debug("__transcription_result_changed")
if self.__on_result_changed:
self.__on_result_changed(message, *self.__callback_args)
def __transcription_completed(self, message):
_logging.debug("__transcription_completed")
self.__nls.shutdown()
_logging.debug("__transcription_completed shutdown done")
if self.__on_completed:
self.__on_completed(message, *self.__callback_args)
with self.__start_cond:
self.__start_flag = False
self.__start_cond.notify()
def __task_failed(self, message):
_logging.debug("__task_failed")
with self.__start_cond:
self.__start_flag = False
self.__start_cond.notify()
if self.__on_error:
self.__on_error(message, *self.__callback_args)
def start(self, aformat="pcm", sample_rate=16000, ch=1,
enable_intermediate_result=False,
enable_punctutation_prediction=False,
enable_inverse_text_normalization=False,
timeout=10,
ping_interval=8,
ping_timeout=None,
ex={}):
"""
Transcription start
Parameters:
-----------
aformat: str
audio binary format, support: "pcm", "opu", "opus", default is "pcm"
sample_rate: int
audio sample rate, default is 16000
ch: int
audio channels, only support mono which is 1
enable_intermediate_result: bool
whether enable return intermediate recognition result, default is False
enable_punctutation_prediction: bool
whether enable punctutation prediction, default is False
enable_inverse_text_normalization: bool
whether enable ITN, default is False
timeout: int
wait timeout for connection setup
ping_interval: int
send ping interval, 0 for disable ping send, default is 8
ping_timeout: int
timeout after send ping and recive pong, set None for disable timeout check and default is None
ex: dict
dict which will merge into "payload" field in request
"""
self.__nls = NlsCore(
url=self.__url, akid=self.__akid, aksecret=self.__aksecret,
token=self.__token,
on_open=self.__tr_core_on_open,
on_message=self.__tr_core_on_msg,
on_close=self.__tr_core_on_close,
on_error=self.__tr_core_on_error,
callback_args=[])
if ch != 1:
raise ValueError("not support channel: {}".format(ch))
if aformat not in self.__allow_aformat:
raise ValueError("format {} not support".format(aformat))
__id4 = uuid.uuid4().hex
self.__task_id = uuid.uuid4().hex
self.__audio_format = aformat
__header = {
"message_id": __id4,
"task_id": self.__task_id,
"namespace": __SPEECH_TRANSCRIBER_NAMESPACE__,
"name": __SPEECH_TRANSCRIBER_REQUEST_CMD__["start"],
"appkey": self.__appkey
}
__payload = {
"format": aformat,
"sample_rate": sample_rate,
"enable_intermediate_result": enable_intermediate_result,
"enable_punctuation_prediction": enable_punctutation_prediction,
"enable_inverse_text_normalization": enable_inverse_text_normalization
}
for key in ex:
__payload[key] = ex[key]
__msg = {
"header": __header,
"payload": __payload
}
__jmsg = json.dumps(__msg)
with self.__start_cond:
if self.__start_flag:
_logging.debug("already start...")
return False
if self.__nls.start(__jmsg, ping_interval, ping_timeout):
if self.__start_flag == False:
if self.__start_cond.wait(timeout):
return self.__start_flag == True
else:
return False
else:
return False
def stop(self, timeout=10):
"""
Stop transcription and mark session finished
Parameters:
-----------
timeout: int
timeout for waiting completed message from cloud
"""
__id4 = uuid.uuid4().hex
__header = {
"message_id": __id4,
"task_id": self.__task_id,
"namespace": __SPEECH_TRANSCRIBER_NAMESPACE__,
"name": __SPEECH_TRANSCRIBER_REQUEST_CMD__["stop"],
"appkey": self.__appkey
}
__msg = {
"header": __header
}
__jmsg = json.dumps(__msg)
with self.__start_cond:
if not self.__start_flag:
_logging.debug("not start yet...")
return False
self.__nls.send(__jmsg, False)
if self.__start_flag == True:
_logging.debug("stop wait..")
if self.__start_cond.wait(timeout):
return self.__start_flag == False
else:
return False
else:
return True
def ctrl(self, ex={}):
"""
Send control message to cloud
Parameters:
-----------
ex: dict
dict which will merge into "payload" field in request
"""
__id4 = uuid.uuid4().hex
__header = {
"message_id": __id4,
"task_id": self.__task_id,
"namespace": __SPEECH_TRANSCRIBER_NAMESPACE__,
"name": __SPEECH_TRANSCRIBER_REQUEST_CMD__["control"],
"appkey": self.__appkey
}
__msg = {
"header": __header,
"payload": ex
}
__jmsg = json.dumps(__msg)
with self.__start_cond:
if not self.__start_flag:
_logging.debug("not start yet...")
return False
self.__nls.send(__jmsg, False)
return True
def shutdown(self):
"""
Shutdown connection immediately
"""
self.__nls.shutdown()
def send_audio(self, pcm_data):
"""
Send audio binary, audio size prefer 20ms length
Parameters:
-----------
pcm_data: bytes
audio binary which format is "aformat" in start method
"""
__data = pcm_data
with self.__start_cond:
if not self.__start_flag:
return False
try:
self.__nls.send(__data, True)
except ConnectionResetError as __e:
_logging.error("connection reset")
self.__start_flag = False
self.__nls.shutdown()
raise __e
return False
return True
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] |
hic_covid_repository/versions/002_Virology.py | LCBRU/hic_covid | 0 | 38136 | <filename>hic_covid_repository/versions/002_Virology.py
from sqlalchemy import (
MetaData,
Table,
Column,
Integer,
NVARCHAR,
DateTime,
Date,
Boolean,
)
meta = MetaData()
def upgrade(migrate_engine):
meta.bind = migrate_engine
t = Table(
"virology",
meta,
Column("id", Integer, primary_key=True),
Column("uhl_system_number", NVARCHAR(50), index=True, nullable=False),
Column("test_id", Integer, nullable=False, index=True, unique=True),
Column("laboratory_code", NVARCHAR(50)),
Column("order_code", NVARCHAR(50)),
Column("order_name", NVARCHAR(50)),
Column("test_code", NVARCHAR(50)),
Column("test_name", NVARCHAR(50)),
Column("organism", NVARCHAR(50)),
Column("test_result", NVARCHAR(50)),
Column("sample_collected_date_time", DateTime),
Column("sample_received_date_time", DateTime),
Column("sample_available_date_time", DateTime),
Column("order_status", NVARCHAR(50)),
)
t.create()
def downgrade(migrate_engine):
meta.bind = migrate_engine
t = Table("virology", meta, autoload=True)
t.drop()
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580,
13,
2
] |
hdp-ambari-mpack-3.1.4.0/stacks/HDP/3.0/services/OOZIE/package/scripts/oozie_client.py | dropoftruth/dfhz_hdp_mpack | 3 | 197302 | <filename>hdp-ambari-mpack-3.1.4.0/stacks/HDP/3.0/services/OOZIE/package/scripts/oozie_client.py<gh_stars>1-10
#!/usr/bin/env python
"""
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless 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.
"""
import sys
from resource_management.libraries.script.script import Script
from resource_management.libraries.functions import stack_select
from resource_management.libraries.functions.constants import StackFeature
from resource_management.libraries.functions.stack_features import check_stack_feature
from resource_management.core.logger import Logger
from resource_management.core.exceptions import ClientComponentHasNoStatus
from oozie import oozie
from oozie_service import oozie_service
class OozieClient(Script):
def install(self, env):
self.install_packages(env)
self.configure(env)
def configure(self, env):
import params
env.set_params(params)
oozie(is_server=False)
def status(self, env):
raise ClientComponentHasNoStatus()
def pre_upgrade_restart(self, env, upgrade_type=None):
import params
env.set_params(params)
# this function should not execute if the version can't be determined or
# the stack does not support rolling upgrade
if not (params.version and check_stack_feature(StackFeature.ROLLING_UPGRADE, params.version)):
return
Logger.info("Executing Oozie Client Stack Upgrade pre-restart")
stack_select.select_packages(params.version)
# We substitute some configs (oozie.authentication.kerberos.principal) before generation (see oozie.py and params.py).
# This function returns changed configs (it's used for config generation before config download)
def generate_configs_get_xml_file_content(self, filename, dictionary):
if dictionary == 'oozie-site':
import params
config = self.get_config()
return {'configurations': params.oozie_site,
'configuration_attributes': config['configurationAttributes'][dictionary]}
else:
return super(OozieClient, self).generate_configs_get_xml_file_content(filename, dictionary)
if __name__ == "__main__":
OozieClient().execute()
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] |
tensorflow-example/tensor_placeholder.py | dinkar1708/machine-learning-examples | 0 | 44922 | <reponame>dinkar1708/machine-learning-examples
import numpy as np
import tensorflow as tf
# placeholder - Inserts a placeholder for a tensor that will be always fed.
# Example1-
a = tf.placeholder(tf.float32)
b = tf.placeholder(tf.float32)
adder_node = a + b
sess = tf.Session()
print(sess.run(adder_node, {a: [1, 2], b: [2, 3]}))
sess.close()
# Example2
x = tf.placeholder(tf.float32, shape=(1024, 1024))
y = tf.matmul(x, x)
with tf.Session() as sess:
# print(sess.run(y)) # ERROR: will fail because x was not fed.
rand_array = np.random.rand(1024, 1024)
print(sess.run(y, feed_dict={x: rand_array})) # Will succeed.
| [
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396,
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13,
2
] |
baekjoon/not-classified/1630/1630.py | honux77/algorithm | 2 | 113811 | n = input()
def gcd(m, n):
while True:
m %= n
if m == 0:
return n
n %= m
if n == 0:
return m
def lcm(m, n):
g = gcd(m ,n)
return m * n / g
def omin(n):
r = n
for i in range(2, n):
if r % i != 0:
r = lcm(r, i)
return r
print omin(n) | [
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] |
code/pgms/merge-sort.py | souradeepta/PythonPractice | 0 | 144110 | from typing import List
def merge_sort(input: List):
length = len(input)
for step in range(1, length):
key = input[step]
j = step - 1
while j >= 0 and key < input[j]:
input[j+1] = input[j]
j = j - 1
input[j+1] = key
return input
def main():
sample = [7,4,5,1,0,9,1,4]
result = merge_sort(sample)
print(f"output is: {result}")
if __name__ =="__main__":
main() | [
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codes/globo_videos_cuts/core/tests/models/processed_video_model_test_case.py | lariodiniz/teste_meta | 0 | 135947 | # coding: utf-8
__author__ = "<NAME>"
from django.test import TestCase
from model_mommy import mommy
from core.models import ProcessedVideo
class ProcessedVideoModelTestCase(TestCase):
"""Class Testing Model processed """
def setUp(self):
"""
Initial Test Settings
"""
self.processed_video = mommy.make(ProcessedVideo)
def tearDown(self):
"""Final method"""
self.processed_video.delete()
def test_there_are_fields(self):
"""test the fields the model"""
self.assertTrue('title' in dir(ProcessedVideo), 'Class Program does not have the field title')
self.assertTrue('duration' in dir(ProcessedVideo), 'Class Program does not have the field start_time')
self.assertTrue('name' in dir(ProcessedVideo), 'Class Program does not have the field end_time')
def test_there_is_a_program(self):
"""test if you are creating a Program correctly"""
self.assertEquals(ProcessedVideo.objects.count(), 1)
self.assertEquals(ProcessedVideo.objects.all()[0].title, self.processed_video.title)
self.assertEquals(ProcessedVideo.objects.all()[0].duration, self.processed_video.duration)
self.assertEquals(ProcessedVideo.objects.all()[0].name, self.processed_video.name)
| [
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] |
migrations/metadata.py | gntzh/fastapi-tmpl | 0 | 169429 | <filename>migrations/metadata.py
from src.domain import Item, User # noqa: F401
from src.domain.mapper import mapper_registry
__all__ = ["metadata"]
metadata = mapper_registry.metadata
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setup.py | colincsl/StructuredModels | 1 | 118754 |
'''
Configure:
python setup.py build
StructuredModels
<NAME>
2013
'''
from distutils.core import setup
# from setuptools import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
import numpy as np
# ext_modules = [
# Extension("pyKinectTools_algs_Dijkstras", ["pyKinectTools/algs/dijkstras.pyx"],language='c++'),
# Extension("pyKinectTools_algs_local_occupancy_pattern", ["pyKinectTools/algs/LocalOccupancyPattern.pyx"],language='c++'),
# ]
#
# for e in ext_modules:
# e.pyrex_directives = {
# "boundscheck": False,
# "wraparound": False,
# "infer_types": True
# }
# e.extra_compile_args = ["-w"]
setup(
author = '<NAME>',
author_email = '<EMAIL>',
description = '',
license = "FreeBSD",
version= "0.1",
name = 'StructuredModels',
cmdclass = {'build_ext': build_ext},
include_dirs = [np.get_include()],
packages= [ "StructuredModels",
"StructuredModels.models",
],
# package_data={'':['*.xml', '*.png', '*.yml', '*.txt']},
# ext_modules = ext_modules
)
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locr/constants.py | thatandromeda/locr | 1 | 179617 | TIMEOUT = 2
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1,
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HW6/YuliiaKutsyk/3_ unfinished_loop_bug_fixing.py | kolyasalubov/Lv-677.PythonCore | 0 | 2018 | def create_array(n):
res=[]
i=1
while i<=n:
res.append(i)
i += 1
return res
| [
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glc/cli/subs/c_mr.py | evinoca/MyCli | 1 | 80482 | <filename>glc/cli/subs/c_mr.py
from __future__ import absolute_import
from __future__ import unicode_literals
import click
@click.group()
@click.pass_obj
def cli(config):
"""
Merge Requests.
"""
click.echo("calling sub cmd repo")
@cli.command("ls", short_help="List MR")
def ls():
click.echo("repo list")
@cli.command("add", short_help="Create merge request from current repo")
def add():
click.echo("repo add")
@cli.command("update", short_help="update MR")
def update():
click.echo("repo update")
@cli.command("status", short_help="Show status repo")
def status():
click.echo("repo desc")
| [
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] |
Bots/Python/Consumers/CodeFirst/WaterfallHostBot/dialogs/sso/sso_signin_dialog.py | gabog/BotFramework-FunctionalTests | 28 | 49495 | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
from botbuilder.dialogs import (
ComponentDialog,
WaterfallDialog,
WaterfallStepContext,
OAuthPrompt,
OAuthPromptSettings,
)
class SsoSignInDialog(ComponentDialog):
def __init__(self, connection_name: str):
super().__init__(SsoSignInDialog.__name__)
self.add_dialog(
OAuthPrompt(
OAuthPrompt.__name__,
OAuthPromptSettings(
connection_name=connection_name,
text=f"Sign in to the host bot using AAD for SSO and connection {connection_name}",
title="Sign In",
timeout=60000,
),
)
)
self.add_dialog(
WaterfallDialog(
WaterfallDialog.__name__,
[
self.signin_step,
self.display_token,
],
)
)
self.initial_dialog_id = WaterfallDialog.__name__
async def signin_step(self, step_context: WaterfallStepContext):
return await step_context.begin_dialog(OAuthPrompt.__name__)
async def display_token(self, step_context: WaterfallStepContext):
sso_token = step_context.result
if sso_token:
if isinstance(sso_token, dict):
token = sso_token.get("token")
else:
token = sso_token.token
await step_context.context.send_activity(f"Here is your token: {token}")
else:
await step_context.context.send_activity("No token was provided.")
return await step_context.end_dialog()
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] |
Independent Component Analysis.py | Queen-s-Cerebral-Language-Innovation/EEG-Preprocesing | 0 | 1600824 | <filename>Independent Component Analysis.py
import csv
from mne.preprocessing import (ICA)
from mne import Epochs, pick_types
from mne.channels import make_standard_montage
from mne.io import concatenate_raws, read_raw_edf
from mne.datasets import eegbci
import numpy as np
allICAs = []
subject = []
chosen = 1 #Subject to be preprocessed
def addICA(raw):
ica = ICA(n_components=15, random_state=97)
ica.fit(raw)
global allICAs
icaArray = ica.apply()
global subject
global choosen
# if (subject == chosen):
# icaArray.append(1)
# else:
# icaArray.append(0)
allICAs.append(icaArray)
print("\n ---- \n")
print(allICAs)
def makeArray():
global allICAs
runs = [5, 6, 9, 10, 13, 14]
allICAs = []
# allICAs = [[]]
global chosen
for subject in range(1, 110):
allICAs[subject].append(1) if subject == chosen else allICAs[subject].append(0)
tmin, tmax = -1., 4.
event_id = dict(hands=2, feet=3)
for run in runs:
raw_fnames = eegbci.load_data(subject, run)
raw = concatenate_raws(
[read_raw_edf(f, preload=True) for f in raw_fnames])
eegbci.standardize(raw)
montage = make_standard_montage('standard_1005')
raw.set_montage(montage)
raw.rename_channels(lambda x: x.strip('.'))
raw.crop(tmax=60.)
raw.filter(14., 30.)
picks = pick_types(raw.info, eeg=True)
# events, _ = events_from_annotations(raw, event_id=dict(T1=2, T2=3))
# 7
# epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks, preload=True)
# labels = epochs.events[:, -1] - 2;
# filename = "eeg" + str(i) + "-"+ str(j) +".csv"
addICA(raw)
with open('allICAs', 'w') as f:
f_csv = csv.writer(f)
f_csv.writerows(allICAs)
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] |
kokon/utils/functions.py | KoalicjaOtwartyKrakow/backend | 0 | 99188 | import functools
import json
from typing import Optional
from flask import Response, Request as FlaskRequest
from marshmallow import ValidationError
import sentry_sdk
from kokon.orm import User
from kokon.serializers import UUIDEncoder
from .auth import upsert_user_from_jwt
from .db import DB
from .errors import AppError
class Request(FlaskRequest):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.db: Optional[DB] = None
self.user: Optional[User] = None
class JSONResponse(Response):
def __init__(self, response, status=200, **kwargs):
if not isinstance(response, str):
# The json returned here is always returned as the only part of the
# response, with mimetype set to json. There is no raw interpolation
# with js happening, so setting ensure_ascii is safe, no risk of XSS.
#
# For more context see https://v8.dev/features/subsume-json
response = json.dumps(response, cls=UUIDEncoder, ensure_ascii=False)
super(JSONResponse, self).__init__(
response=response, status=status, mimetype="application/json", **kwargs
)
def function_wrapper(func):
@functools.wraps(func)
def wrapper(request: FlaskRequest):
try:
# https://cloud.google.com/endpoints/docs/openapi/migrate-to-esp-v2#receiving_auth_results_in_your_api
jwt_header_encoded = request.headers.get("X-Endpoint-API-UserInfo", "")
db = DB()
request.user = upsert_user_from_jwt(db, jwt_header_encoded)
request.db = db
return func(request)
except ValidationError as e:
return JSONResponse({"validationErrors": e.messages}, status=422)
except AppError as e:
return JSONResponse({"message": e.message}, status=e.status)
except Exception as e:
sentry_sdk.capture_exception(e)
sentry_sdk.flush()
raise e
return wrapper
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] |
stylegan2_torch/discriminator/blocks.py | ppeetteerrs/stylegan2-torch | 0 | 97712 | <filename>stylegan2_torch/discriminator/blocks.py
import math
from typing import List
from stylegan2_torch.equalized_lr import Blur, EqualConv2d
from stylegan2_torch.op.fused_act import FusedLeakyReLU
from stylegan2_torch.utils import proxy
from torch import nn
from torch.functional import Tensor
class ConvBlock(nn.Sequential):
"""
Convolution in feature space
EqualConv2d: 2D convolution with equalized learning rate
FusedLeakyReLU: LeakyReLU with a bias added before activation
"""
def __init__(self, in_channel: int, out_channel: int, kernel_size: int):
super().__init__(
EqualConv2d(
in_channel,
out_channel,
kernel_size,
padding=kernel_size // 2,
stride=1,
bias=False,
),
FusedLeakyReLU(out_channel, bias=True),
)
def __call__(self, input: Tensor) -> Tensor:
return super().__call__(input)
class DownConvBlock(nn.Sequential):
"""
Downsampling convolution in feature space
Blur: Gaussian filter as low-pass filter for anti-aliasing + adjust tensor shape to preserve downsampled tensor shape
EqualConv2d: 2D (downsampling) convolution with equalized learning rate
FusedLeakyReLU: LeakyReLU with a bias added before activation
"""
def __init__(
self,
in_channel: int,
out_channel: int,
kernel_size: int,
down: int,
blur_kernel: List[int],
):
super().__init__(
Blur(blur_kernel, -down, kernel_size),
EqualConv2d(
in_channel, out_channel, kernel_size, padding=0, stride=down, bias=False
),
FusedLeakyReLU(out_channel, bias=True),
)
def __call__(self, input: Tensor) -> Tensor:
return super().__call__(input)
class RGBDown(nn.Sequential):
"""
Downsampling convolution in RGB space, hence no need nonlinearity
Blur: Gaussian filter as low-pass filter for anti-aliasing + adjust tensor shape to preserve downsampled tensor shape
EqualConv2d: 2D (downsampling) convolution with equalized learning rate
"""
def __init__(
self,
in_channel: int,
out_channel: int,
kernel_size: int,
down: int,
blur_kernel: List[int],
):
super().__init__(
Blur(blur_kernel, -down, kernel_size),
EqualConv2d(
in_channel, out_channel, kernel_size, padding=0, stride=down, bias=False
),
)
def __call__(self, input: Tensor) -> Tensor:
return super().__call__(input)
class ResBlock(nn.Module):
"""
Residual block
ConvBlock + DownConvBlock: Convolution + downsampling
RGBDown: Skip connection from higher (double) resolution RGB image
"""
def __init__(self, in_channel: int, out_channel: int, blur_kernel: List[int]):
super().__init__()
self.conv = ConvBlock(in_channel, in_channel, 3)
self.down_conv = DownConvBlock(
in_channel, out_channel, 3, down=2, blur_kernel=blur_kernel
)
self.skip = RGBDown(in_channel, out_channel, 1, down=2, blur_kernel=blur_kernel)
def forward(self, input: Tensor) -> Tensor:
out = self.conv(input)
out = self.down_conv(out)
skip = self.skip(input)
# sqrt 2 to adhere to equalized learning rate philosophy
# (i.e. preserve variance in forward pass not initialization)
return (out + skip) / math.sqrt(2)
__call__ = proxy(forward)
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] |
mir/sre/__init__.py | darkfeline/mir.sre | 2 | 99182 | <filename>mir/sre/__init__.py
# Copyright (C) 2017 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless 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.
"""This module implements structural regular expressions.
Read <NAME>'s paper and the manual page for the sam editor for more
context.
Functions:
x_iter()
y_iter()
x_join()
y_join()
"""
__version__ = '0.1.0'
import re
def x_iter(pattern, string, flags=0):
"""Return an iterable over regexp matches."""
yield from (m.group(0) for m in re.finditer(pattern, string, flags))
def y_iter(pattern, string, flags=0):
"""Return an iterable over the strings around regexp matches."""
pattern = f'({pattern})'
for i, substring in enumerate(re.split(pattern, string, flags)):
if not i % 2:
yield substring
def x_join(pattern, string, func, flags=0):
"""Apply a function to regexp matches.
Each regexp match in string is substituted with the return value of
func when called with the matched substring.
"""
pattern = f'({pattern})'
parts = []
for i, substring in enumerate(re.split(pattern, string, flags)):
if i % 2:
parts.append(func(substring))
else: # Includes first and last
parts.append(substring)
return ''.join(parts)
def y_join(pattern, string, func, flags=0):
"""Apply a function to the strings around regexp matches.
The substrings before, between, and after each regexp match in
string is substituted with the return value of func when called with
said substring.
"""
pattern = f'({pattern})'
parts = []
for i, substring in enumerate(re.split(pattern, string, flags)):
if i % 2:
parts.append(substring)
else: # Includes first and last
parts.append(func(substring))
return ''.join(parts)
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openstack/telemetry/v2/alarm_change.py | sivel/python-openstacksdk | 1 | 66602 | # Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless 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.
from openstack import resource
from openstack.telemetry import telemetry_service
class AlarmChange(resource.Resource):
id_attribute = 'event_id'
resource_key = 'alarm_change'
base_path = '/v2/alarms/%(alarm_id)s/history'
service = telemetry_service.TelemetryService()
# Supported Operations
allow_list = True
# Properties
alarm_id = resource.prop('alarm_id')
detail = resource.prop('detail')
event_id = resource.prop('event_id')
on_behalf_of = resource.prop('on_behalf_of')
project_id = resource.prop('project_id')
triggered_at = resource.prop('timestamp')
type = resource.prop('type')
user_id = resource.prop('user_id')
@classmethod
def list(cls, session, path_args=None, **params):
url = cls.base_path % path_args
resp = session.get(url, service=cls.service, params=params)
changes = []
for item in resp.body:
changes.append(cls.existing(**item))
return changes
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] |
uwsgiconf/options/subscriptions.py | graceshaw/uwsgiconf | 0 | 41669 | from ..base import OptionsGroup
from ..exceptions import ConfigurationError
from ..utils import KeyValue, filter_locals
from .subscriptions_algos import *
class Subscriptions(OptionsGroup):
"""
This allows some uWSGI instances to announce their presence to subscriptions managing server,
which in its turn can address those nodes (e.g. delegate request processing to them)
and automatically remove dead nodes from the pool.
Some routers provide subscription server functionality. See `.routing.routers`.
.. note:: Subscription system in many ways relies on Master Process.
.. warning:: The subscription system is meant for "trusted" networks.
All of the nodes in your network can potentially make a total mess with it.
* http://uwsgi.readthedocs.io/en/latest/SubscriptionServer.html
"""
class algorithms:
"""Balancing algorithms available to use with ``subscribe``."""
ip_hash = IpHash
least_reference_count = LeastReferenceCount
weighted_least_reference_count = WeightedLeastReferenceCount
weighted_round_robin = WeightedRoundRobin
def set_server_params(
self, client_notify_address=None, mountpoints_depth=None, require_vassal=None,
tolerance=None, tolerance_inactive=None, key_dot_split=None):
"""Sets subscription server related params.
:param str client_notify_address: Set the notification socket for subscriptions.
When you subscribe to a server, you can ask it to "acknowledge" the acceptance of your request.
pointing address (Unix socket or UDP), on which your instance will bind and
the subscription server will send acknowledgements to.
:param int mountpoints_depth: Enable support of mountpoints of certain depth for subscription system.
* http://uwsgi-docs.readthedocs.io/en/latest/SubscriptionServer.html#mountpoints-uwsgi-2-1
:param bool require_vassal: Require a vassal field (see ``subscribe``) from each subscription.
:param int tolerance: Subscription reclaim tolerance (seconds).
:param int tolerance_inactive: Subscription inactivity tolerance (seconds).
:param bool key_dot_split: Try to fallback to the next part in (dot based) subscription key.
Used, for example, in SNI.
"""
# todo notify-socket (fallback) relation
self._set('subscription-notify-socket', client_notify_address)
self._set('subscription-mountpoint', mountpoints_depth)
self._set('subscription-vassal-required', require_vassal, cast=bool)
self._set('subscription-tolerance', tolerance)
self._set('subscription-tolerance-inactive', tolerance_inactive)
self._set('subscription-dotsplit', key_dot_split, cast=bool)
return self._section
def set_server_verification_params(
self, digest_algo=None, dir_cert=None, tolerance=None, no_check_uid=None,
dir_credentials=None, pass_unix_credentials=None):
"""Sets peer verification params for subscription server.
These are for secured subscriptions.
:param str digest_algo: Digest algorithm. Example: SHA1
.. note:: Also requires ``dir_cert`` to be set.
:param str dir_cert: Certificate directory.
.. note:: Also requires ``digest_algo`` to be set.
:param int tolerance: Maximum tolerance (in seconds) of clock skew for secured subscription system.
Default: 24h.
:param str|int|list[str|int] no_check_uid: Skip signature check for the specified uids
when using unix sockets credentials.
:param str|list[str] dir_credentials: Directories to search for subscriptions
key credentials.
:param bool pass_unix_credentials: Enable management of SCM_CREDENTIALS in subscriptions UNIX sockets.
"""
if digest_algo and dir_cert:
self._set('subscriptions-sign-check', f'{digest_algo}:{dir_cert}')
self._set('subscriptions-sign-check-tolerance', tolerance)
self._set('subscriptions-sign-skip-uid', no_check_uid, multi=True)
self._set('subscriptions-credentials-check', dir_credentials, multi=True)
self._set('subscriptions-use-credentials', pass_unix_credentials, cast=bool)
return self._section
def set_client_params(
self, start_unsubscribed=None, clear_on_exit=None, unsubscribe_on_reload=None,
announce_interval=None):
"""Sets subscribers related params.
:param bool start_unsubscribed: Configure subscriptions but do not send them.
.. note:: Useful with master FIFO.
:param bool clear_on_exit: Force clear instead of unsubscribe during shutdown.
:param bool unsubscribe_on_reload: Force unsubscribe request even during graceful reload.
:param int announce_interval: Send subscription announce at the specified interval. Default: 10 master cycles.
"""
self._set('start-unsubscribed', start_unsubscribed, cast=bool)
self._set('subscription-clear-on-shutdown', clear_on_exit, cast=bool)
self._set('unsubscribe-on-graceful-reload', unsubscribe_on_reload, cast=bool)
self._set('subscribe-freq', announce_interval)
return self._section
def subscribe(
self, server=None, key=None, address=None, address_vassal=None,
balancing_weight=None, balancing_algo=None, modifier=None, signing=None, check_file=None, protocol=None,
sni_cert=None, sni_key=None, sni_client_ca=None):
"""Registers a subscription intent.
:param str server: Subscription server address (UDP or UNIX socket).
Examples:
* 127.0.0.1:7171
:param str key: Key to subscribe. Generally the domain name (+ optional '/< mountpoint>').
Examples:
* mydomain.it/foo
* mydomain.it/foo/bar (requires ``mountpoints_depth=2``)
* mydomain.it
* ubuntu64.local:9090
:param str|int address: Address to subscribe (the value for the key)
or zero-based internal socket number (integer).
:param str address: Vassal node address.
:param int balancing_weight: Load balancing value. Default: 1.
:param balancing_algo: Load balancing algorithm to use. See ``balancing_algorithms``
.. note:: Since 2.1
:param Modifier modifier: Routing modifier object. See ``.routing.modifiers``
:param list|tuple signing: Signing basics, expects two elements list/tuple:
(signing_algorithm, key).
Examples:
* SHA1:idlessh001
:param str check_file: If this file exists the subscription packet is sent,
otherwise it is skipped.
:param str protocol: the protocol to use, by default it is ``uwsgi``.
See ``.networking.socket_types``.
.. note:: Since 2.1
:param str sni_cert: Certificate file to use for SNI proxy management.
* http://uwsgi.readthedocs.io/en/latest/SNI.html#subscription-system-and-sni
:param str sni_key: sni_key Key file to use for SNI proxy management.
* http://uwsgi.readthedocs.io/en/latest/SNI.html#subscription-system-and-sni
:param str sni_client_ca: Ca file to use for SNI proxy management.
* http://uwsgi.readthedocs.io/en/latest/SNI.html#subscription-system-and-sni
"""
# todo params: inactive (inactive slot activation)
if not any((server, key)):
raise ConfigurationError('Subscription requires `server` or `key` to be set.')
address_key = 'addr'
if isinstance(address, int):
address_key = 'socket'
if balancing_algo:
backup = getattr(balancing_algo, 'backup_level', None)
if signing:
signing = ':'.join(signing)
if modifier:
modifier1 = modifier
if modifier.submod:
modifier2 = modifier.submod
rule = KeyValue(
filter_locals(locals(), drop=['address_key', 'modifier']),
aliases={
'address': address_key,
'address_vassal': 'vassal',
'signing': 'sign',
'check_file': 'check',
'balancing_weight': 'weight',
'balancing_algo': 'algo',
'protocol': 'proto',
'sni_cert': 'sni_crt',
'sni_client_ca': 'sni_ca',
},
)
self._set('subscribe2', rule)
return self._section
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testsuite/cases/cv2.py | jcupitt/pillow-perf | 0 | 36770 | # coding: utf-8
from __future__ import print_function, unicode_literals, absolute_import
import cv2
from .base import BaseTestCase, root
try:
cv2.setNumThreads(1)
except AttributeError:
print('!!! You are using OpenCV which does not allow you to set '
'the number of threads')
class Cv2TestCase(BaseTestCase):
filter_ids = {
cv2.INTER_AREA: 'sup',
cv2.INTER_NEAREST: 'ner',
cv2.INTER_LINEAR: 'bil',
cv2.INTER_CUBIC: 'bic',
cv2.INTER_LANCZOS4: 'lzs4',
}
def create_test_data(self):
im = cv2.imread(root('resources', 'color_circle.png'),
flags=cv2.IMREAD_UNCHANGED)
if self.mode == 'RGB':
im = im[:, :, :3]
elif self.mode == 'RGBA':
pass
elif self.mode == 'L':
im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
else:
raise ValueError('Unknown mode: {}'.format(self.mode))
# Fine for upscaling
im = cv2.resize(im, tuple(self.size), interpolation=cv2.INTER_CUBIC)
return [im]
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config.py | PsychoBots/Kylie-Music | 0 | 142035 | <reponame>PsychoBots/Kylie-Music<filename>config.py
import os
import re
from youtube_dl import YoutubeDL
class Config:
APP_ID = int(os.environ.get("APP_ID", ""))
API_HASH = os.environ.get("API_HASH", "")
BOT_TOKEN = os.environ.get("BOT_TOKEN", "")
START_MSG = os.environ.get("START_MSG", "<b>Hi {},\nI am Kylie Simple Youtube to Mp3 Downloader Bot\nI can Download Any Music with best quality👀 Just send me name or Link with using command of `/song`</b>\nExample:/song Can we kiss Forever\n\n C R E A T O R: @Psycho_Bots")
START_IMG = os.environ.get("START_IMG", "")
OWNER = os.environ.get("OWNER", "Alone_loverboy")
DOWNLOAD_LOCATION = os.environ.get("DOWNLOAD_LOCATION", "./DOWNLOADS/")
msg = {}
# Builder Pack of FFMPEG: https://github.com/jonathanong/heroku-buildpack-ffmpeg-latest
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contrib/cirrus/podbot.py | juhp/libpod | 2 | 10472 | #!/usr/bin/env python3
# Simple and dumb script to send a message to the #podman IRC channel on frenode
# Based on example from: https://pythonspot.com/building-an-irc-bot/
import os
import time
import random
import errno
import socket
import sys
class IRC:
response_timeout = 10 # seconds
irc = socket.socket()
def __init__(self, server, nickname, channel):
self.server = server
self.nickname = nickname
self.channel = channel
self.irc = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
def _send(self, cmdstr):
self.irc.send(bytes(cmdstr + '\r\n', 'utf-8'))
def message(self, msg):
data = 'PRIVMSG {0} :{1}\r\n'.format(self.channel, msg)
print(data)
self._send(data)
@staticmethod
def fix_newlines(bufr):
return bufr.replace('\\r\\n', '\n')
def _required_response(self, needle, haystack):
start = time.time()
end = start + self.response_timeout
while time.time() < end:
if haystack.find(needle) != -1:
return (False, haystack)
time.sleep(0.1)
try:
haystack += str(self.irc.recv(4096, socket.MSG_DONTWAIT))
except socket.error as serr:
if serr.errno == errno.EWOULDBLOCK:
continue
raise # can't handle this
return (True, haystack) # Error
def connect(self, username, password):
# This is ugly as sin, but seems to be a working send/expect sequence
print("connecting to: {0}".format(self.server))
self.irc.connect((self.server, 6667)) #connects to the server
self._send("USER {0} {0} {0} :I am {0}".format(self.nickname))
self._send("NICK {0}".format(self.nickname))
err, haystack = self._required_response('End of /MOTD command.'
''.format(self.nickname), "")
if err:
print(self.fix_newlines(haystack))
print("Error connecting to {0}".format(self.server))
return True
print("Logging in as {0}".format(username))
self._send("PRIVMSG NickServ :IDENTIFY {0} {1}".format(username, password))
err, _ = self._required_response("You are now identified for", "")
if err:
print("Error logging in to {0} as {1}".format(self.server, username))
return True
print("Joining {0}".format(self.channel))
self._send("JOIN {0}".format(self.channel))
err, haystack = self._required_response("{0} {1} :End of /NAMES list."
"".format(self.nickname, self.channel),
haystack)
print(self.fix_newlines(haystack))
if err:
print("Error joining {0}".format(self.channel))
return True
return False
def quit(self):
print("Quitting")
self._send("QUIT :my work is done here")
self.irc.close()
if len(sys.argv) < 3:
print("Error: Must pass desired nick and message as parameters")
else:
irc = IRC("irc.freenode.net", sys.argv[1], "#podman")
err = irc.connect(*os.environ.get('IRCID', 'Big Bug').split(" ", 2))
if not err:
irc.message(" ".join(sys.argv[2:]))
time.sleep(5.0) # avoid join/quit spam
irc.quit()
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] |
request.py | codeofdusk/Amanda | 0 | 127903 | <gh_stars>0
"""Contains the Request class.
Copyright 2018 - <NAME> <<EMAIL>>. Licensed under MIT."""
import random
import components
import config
import utils
class request(object):
"Contains attributes for handling user requests and returning responses. Instantiate this class to make a request."
def __init__(self, message, driver=None, *args, **kwargs):
"Take a string and return a response (if available) or False for no response."
self._message = message
self.driver = driver
self.accepted = False
self.response = None
self.content = None
self.invocation = None
# Expose extra args
self.args = args
self.kwargs = kwargs
try:
# First attempt to call plugin explicitly
if config.conf['advanced']['allow_explicit'] and self._message.startswith(
"!"):
self.accept()
# Get the plugin name and args
qt = self._message[1:].split(" ")
self.invocation = qt[0]
self.content = ' '.join(qt[1:])
# Is the user requesting the full motd?
# Note: if we need to implement another special command like this that's a core function, we should create a CorePlugin object that's always loaded and not part of the config that contains these commands.
try:
sendmotd = config.conf['general']['sendmotd']
if (sendmotd == 'full' or sendmotd == 'retracted') and (sendmotd == 'retracted' or self.driver.short_announcements) and self.invocation == "help":
self.response = utils.build_plugin_ad()
except AttributeError:
pass
# Search for the plugin
for plugin in components.plugins:
try:
if self.invocation.lower() in plugin.invocations:
self.response = plugin.run(self)
except AttributeError:
continue
# Attempt to call plugin implicitly
if config.conf['advanced']['allow_implicit'] and not self._message.startswith(
"!"):
for plugin in components.plugins:
try:
self.content = plugin.match(self._message)
except (AttributeError, NotImplementedError):
continue
else:
if self.content:
self.accept()
self.response = plugin.run(self)
except BaseException:
import traceback
self.response = traceback.format_exc()
finally:
self.finalize()
def __str__(self):
if not self.response:
# do we have huh messages?
if config.conf['general']['huh_messages']:
self.response = random.choice(
config.conf['general']['huh_messages'])
else:
self.response = "I don't understand."
return self.response
def accept(self):
try:
self.driver.working(True, request=self)
except (AttributeError, NotImplementedError):
pass
self.accepted = True
def finalize(self):
if self.accepted:
try:
self.driver.say(str(self), request=self)
except (AttributeError, NotImplementedError):
pass
try:
self.driver.working(False, request=self)
except (AttributeError, NotImplementedError):
pass
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2
] |
nzmath/poly/univar.py | turkeydonkey/nzmath3 | 1 | 65984 | <reponame>turkeydonkey/nzmath3
"""
Univariate Polynomials
The polynomials are immutable data types, under the public API. If
one tries to manipulate its underlying data attributes, immutability
will be able to be broken.
"""
import warnings
import nzmath.ring as _ring
import nzmath.poly.formalsum as formalsum
class PolynomialInterface(formalsum.FormalSumContainerInterface):
"""
Base class for all univariate polynomials.
"""
def __init__(self, coefficients, **kwds):
"""
For any descendants of PolynomialInterface, `coefficients'
have to be given. Other arguments, if necessary, should be
passed as keyword arguments. Note that in this __init__
method, no actual initialization happens.
"""
formalsum.FormalSumContainerInterface.__init__(self)
self.number_of_variables = 1
def __eq__(self, other):
"""
self == other
"""
if not isinstance(other, PolynomialInterface):
warnings.warn("comparison falls back to that of formal sum.")
return formalsum.FormalSumContainerInterface.__eq__(self, other)
sterms = [t for t in self.iterterms() if t[1]]
sterms.sort()
oterms = [t for t in other.iterterms() if t[1]]
oterms.sort()
return sterms == oterms
def __hash__(self):
val = sum([hash(t) for t in self.iterterms() if t[1]])
return val
def __pow__(self, index):
"""
self ** index
"""
raise NotImplementedError("should be overridden")
def ring_mul(self, other):
"""
Multiplication of two polynomials in the same ring.
"""
mul_coeff = {}
for ds, cs in self:
for do, co in other:
term_degree = ds + do
if term_degree in mul_coeff:
mul_coeff[term_degree] += cs*co
else:
mul_coeff[term_degree] = cs*co
return self.construct_with_default(sorted([(d, c) for (d, c) in mul_coeff.items() if c]))
def scalar_mul(self, scale):
"""
Return the result of scalar multiplication.
"""
return self.construct_with_default([(d, c * scale) for (d, c) in self if c])
def term_mul(self, term):
"""
Return the result of multiplication with the given term.
The term can be given as a tuple (degree, coeff) or as a
Polynomial instance.
"""
if isinstance(term, PolynomialInterface):
degree, coeff = next(iter(term))
else:
degree, coeff = term
return self.construct_with_default([(d + degree, c * coeff) for (d, c) in self])
def square(self):
"""
Return square of this polynomial.
"""
raise NotImplementedError("should be overridden")
def differentiate(self):
"""
Return the formal differentiation of self.
"""
result = {}
for d, c in self:
if d > 0:
dc = d * c
if dc:
result[d - 1] = dc
return self.construct_with_default(result)
def upshift_degree(self, slide):
"""
Return the polynomial obtained by shifting upward all terms
with degrees of 'slide'.
f.upshift_degree(slide) is equivalent to
f.term_mul((slide, 1)).
"""
return self.bases_map(lambda x: x + slide)
def downshift_degree(self, slide):
"""
Return the polynomial obtained by shifting downward all terms
with degrees of 'slide'.
Be careful that if the least degree term has the degree less
than 'slide' then the result is not mathematically a
polynomial. Even in such a case, the method does not raise an
exception.
f.downshift_degree(slide) is equivalent to
f.upshift_degree(-slide).
"""
return self.bases_map(lambda x: x - slide)
def terms_map(self, func):
"""
Create a new formal sum container by applying func to each
term. func must be a function taking 2 arguments.
"""
terms = []
for t in self:
b, c = func(*t)
if c:
terms.append((b, c))
return self.construct_with_default(terms)
def construct_with_default(self, terms):
"""
Create a new univariate polynomial of the same class with
self, with given only the terms and use copy of self's data if
necessary.
"""
return self.__class__(terms, **self._init_kwds)
class BasicPolynomial(PolynomialInterface):
"""
Basic polynomial data type ignoring a variable name and the ring.
"""
def __init__(self, coefficients, **kwds):
"""
BasicPolynomial(coefficients)
coefficients can be any dict initial values.
"""
PolynomialInterface.__init__(self, coefficients, **kwds)
self._coefficients = dict(coefficients)
self._init_kwds = kwds
def __add__(self, other):
"""
self + other
"""
sum_coeff = dict(iter(self))
for term, coeff in other:
if term in sum_coeff:
sum_coeff[term] += coeff
else:
sum_coeff[term] = coeff
return self.construct_with_default([(d, c) for (d, c) in sum_coeff.items() if c])
def __sub__(self, other):
"""
self - other
"""
dif_coeff = dict(iter(self))
for term, coeff in other:
if term in dif_coeff:
dif_coeff[term] -= coeff
else:
dif_coeff[term] = -coeff
return self.construct_with_default([(d, c) for (d, c) in dif_coeff.items() if c])
def __mul__(self, other):
"""
self * other
If type of other is Polynomial, do multiplication in ring.
Otherwise, do scalar multiplication.
"""
if isinstance(other, PolynomialInterface):
return self.ring_mul(other)
else:
try:
return self.scalar_mul(other)
except TypeError:
return NotImplemented
def __rmul__(self, other):
"""
other * self
If type of other does not support multiplication with self
from left, this method is called. In the context, it is only
posiible that other be a scalar.
"""
try:
return self.scalar_mul(other)
except TypeError:
return NotImplemented
def __neg__(self):
"""
-self
"""
return self.construct_with_default([(d, -c) for (d, c) in self])
def __pos__(self):
"""
+self
"""
return self.construct_with_default(self._coefficients)
def square(self):
"""
Return the square of self.
"""
# zero
if not self:
return self
data_length = len(self._coefficients)
# monomial
if data_length == 1:
return self.construct_with_default([(d*2, c**2) for (d, c) in self])
# binomial
if data_length == 2:
(d1, c1), (d2, c2) = self.terms()
return self.construct_with_default({d1*2:c1**2, d1+d2:c1*c2*2, d2*2:c2**2})
# general (inefficient)
items = list(self._coefficients.items())
fst, snd = {}, {}
if data_length & 1:
b, c = items.pop()
fst[b] = c
while items:
b, c = items.pop()
fst[b] = c
b, c = items.pop()
snd[b] = c
fst = self.__class__(fst, **self._init_kwds)
snd = self.__class__(snd, **self._init_kwds)
mid = fst.ring_mul(snd.scalar_mul(2))
return fst.square() + mid + snd.square()
def __pow__(self, index):
"""
self ** index
"""
# special indices
if index < 0:
raise ValueError("negative index is not allowed.")
elif index == 0:
for c in self.itercoefficients():
if c:
one = _ring.getRing(c).one
break
else:
one = 1
return self.construct_with_default({0: one})
elif index == 1:
return self
elif index == 2:
return self.square()
# special polynomials
if not self:
return self
elif len(self._coefficients) == 1:
return self.construct_with_default([(d*index, c**index) for (d, c) in self])
# general
power_product = self.construct_with_default({0: 1})
power_of_2 = self
while index:
if index & 1:
power_product *= power_of_2
index //= 2
if index:
power_of_2 = power_of_2.square()
return power_product
def __call__(self, val):
"""
substitution
"""
items = list(self._coefficients.items())
if not items:
return 0*val
d, c = items.pop()
result = c * val**d
for d, c in items:
result += c * val**d
return result
def iterterms(self):
"""
iterator for (degree, coefficient) pairs.
The iterator is equivalent to
zip(self.iterbases(), self.itercoefficients())
"""
return iter(self._coefficients.items())
def itercoefficients(self):
"""
iterator for coefficients.
"""
return iter(self._coefficients.values())
def iterbases(self):
"""
iterator for degrees.
"""
return iter(self._coefficients.keys())
def __getitem__(self, degree):
"""
Return the coefficient of specified degree.
If there is no term of degree, return 0.
"""
return self._coefficients.get(degree, 0)
def __contains__(self, degree):
"""
Return True if there is a term of specified degree.
False otherwise.
"""
return degree in self._coefficients
def __len__(self):
"""
Return the number of data entries.
"""
return len(self._coefficients)
def __eq__(self, other):
"""
self == other
"""
if self is other:
return True
return PolynomialInterface.__eq__(self, other)
def __hash__(self):
return PolynomialInterface.__hash__(self)
def __repr__(self): # for debug
return "%s(%s)" % (self.__class__.__name__, repr(self._coefficients))
class SortedPolynomial (PolynomialInterface):
"""
SortedPolynomial stores terms of a polynomial in sorted manner.
All methods and operations keep it sorted.
"""
def __init__(self, coefficients, _sorted=False, **kwds):
"""
SortedPolynomial(coefficients)
'coefficients' can be any dict initial values.
Optionally '_sorted' can be True if the coefficients is
already sorted.
"""
PolynomialInterface.__init__(self, coefficients, **kwds)
self.sorted = []
if not _sorted or isinstance(coefficients, dict):
for t in dict(coefficients).items():
self._insort(t)
else:
self.sorted = list(coefficients)
self._init_kwds = kwds
self._init_kwds['_sorted'] = True
def _insort(self, term):
"""
Insert the term into self.seorted list, and keep it sorted.
- This method is destructive.
- This method is not in a part of the API.
"""
self.sorted.insert(self._bisect(term[0]), term)
def _bisect(self, degree):
"""
Return the index where to insert term of degree.
- This method is not in a part of the API.
- The code is just adapting bisect.bisect_right to the
context.
"""
lo, hi = 0, len(self.sorted)
while lo < hi:
mid = (lo + hi) >> 1
if degree < self.sorted[mid][0]:
hi = mid
else:
lo = mid + 1
return lo
def __pos__(self):
"""
+self
"""
return self.construct_with_default(self.sorted)
def __neg__(self):
"""
-self
"""
return self.construct_with_default([(d, -c) for (d, c) in self])
def __add__(self, other):
"""
self + other
"""
if self.sorted:
iter_self = iter(self.sorted)
self_term = next(iter_self)
else:
self_term = None
if other.sorted:
iter_other = iter(other.sorted)
other_term = next(iter_other)
else:
other_term = None
sorted = []
while self_term and other_term:
compared = cmp(self_term[0], other_term[0])
if compared < 0:
sorted.append(self_term)
try:
self_term = next(iter_self)
except StopIteration:
self_term = None
break
elif compared == 0:
c = self_term[1] + other_term[1]
if c:
sorted.append((self_term[0], c))
try:
self_term = next(iter_self)
except StopIteration:
self_term = None
try:
other_term = next(iter_other)
except StopIteration:
other_term = None
if self_term is None or other_term is None:
break
else:
sorted.append(other_term)
try:
other_term = next(iter_other)
except StopIteration:
other_term = None
break
if other_term is None and self_term:
sorted.append(self_term)
for term in iter_self:
sorted.append(term)
elif self_term is None and other_term:
sorted.append(other_term)
for term in iter_other:
sorted.append(term)
return self.construct_with_default(sorted)
def __sub__(self, other):
"""
self - other
It is something like merge sort.
"""
if self.sorted:
iter_self = iter(self.sorted)
self_term = next(iter_self)
else:
self_term = None
if other.sorted:
iter_other = iter(other.sorted)
other_term = next(iter_other)
else:
other_term = None
sorted = []
while self_term and other_term:
compared = cmp(self_term[0], other_term[0])
if compared < 0:
sorted.append(self_term)
try:
self_term = next(iter_self)
except StopIteration:
self_term = None
break
elif compared == 0:
c = self_term[1] - other_term[1]
if c:
sorted.append((self_term[0], c))
try:
self_term = next(iter_self)
except StopIteration:
self_term = None
try:
other_term = next(iter_other)
except StopIteration:
other_term = None
if self_term is None or other_term is None:
break
else:
sorted.append((other_term[0], -other_term[1]))
try:
other_term = next(iter_other)
except StopIteration:
other_term = None
break
if other_term is None and self_term:
sorted.append(self_term)
for term in iter_self:
sorted.append(term)
elif self_term is None and other_term:
sorted.append((other_term[0], -other_term[1]))
for term in iter_other:
sorted.append((term[0], -term[1]))
return self.construct_with_default(sorted)
def __mul__(self, other):
"""
self * other
If type of other is SortedPolynomial, do multiplication
in ring. Otherwise, do scalar multiplication.
"""
if isinstance(other, PolynomialInterface):
return self.ring_mul(other)
else:
try:
return self.scalar_mul(other)
except TypeError:
return NotImplemented
def __rmul__(self, other):
"""
other * self
If type of other does not support multiplication with self
from left, this method is called. In the context, it is only
posiible that other be a scalar.
"""
try:
return self.scalar_mul(other)
except TypeError:
return NotImplemented
def ring_mul_karatsuba(self, other):
"""
Multiplication of two polynomials in the same ring.
Computation is carried out by Karatsuba method.
"""
polynomial = self.construct_with_default
# zero
if not self or not other:
return polynomial(())
# monomial
if len(self.sorted) == 1:
return other.term_mul(self)
if len(other.sorted) == 1:
return self.term_mul(other)
# binomial
if len(self.sorted) == 2:
p, q = [other.term_mul(term) for term in self]
return p + q
if len(other.sorted) == 2:
p, q = [self.term_mul(term) for term in other]
return p + q
# suppose self is black and other is red.
black_left_degree, black_right_degree = self.sorted[0][0], self.sorted[-1][0]
red_left_degree, red_right_degree = other.sorted[0][0], other.sorted[-1][0]
left_degree = min(black_left_degree, red_left_degree)
right_degree = max(black_right_degree, red_right_degree)
# we assert here that order is of ascending. (is it correct?)
assert left_degree < right_degree
half_degree = (left_degree + right_degree) >> 1
black_half_index = self._bisect(half_degree)
red_half_index = other._bisect(half_degree)
if not black_half_index:
return (self.downshift_degree(black_left_degree).ring_mul_karatsuba(other)).upshift_degree(black_left_degree)
if not red_half_index:
return (self.ring_mul_karatsuba(other.downshift_degree(red_left_degree))).upshift_degree(red_left_degree)
club = polynomial([(d - left_degree, c) for (d, c) in self.sorted[:black_half_index]])
spade = polynomial([(d - half_degree, c) for (d, c) in self.sorted[black_half_index:]])
dia = polynomial([(d - left_degree, c) for (d, c) in other.sorted[:red_half_index]])
heart = polynomial([(d - half_degree, c) for (d, c) in other.sorted[red_half_index:]])
weaker = club.ring_mul_karatsuba(dia)
stronger = spade.ring_mul_karatsuba(heart)
karatsuba = (club + spade).ring_mul_karatsuba(dia + heart) - weaker - stronger
if left_degree:
return (weaker.upshift_degree(left_degree * 2) +
karatsuba.upshift_degree(left_degree + half_degree) +
stronger.upshift_degree(half_degree * 2))
else:
return (weaker +
karatsuba.upshift_degree(half_degree) +
stronger.upshift_degree(half_degree * 2))
def scalar_mul(self, scale):
"""
Return the result of scalar multiplication.
"""
keep_ring = True
if "coeffring" in self._init_kwds:
new_coeff = []
coeffring = self._init_kwds["coeffring"]
for d, c in self:
if c:
scaled = c * scale
if keep_ring and scaled not in coeffring:
coeffring = coeffring.getCommonSuperring(_ring.getRing(scaled))
new_coeff.append((d, scaled))
self._init_kwds["coeffring"] = coeffring
else:
new_coeff = [(d, c * scale) for (d, c) in self if c]
return self.construct_with_default(new_coeff)
def square(self):
"""
Return the square of self.
"""
# zero
if not self:
return self
polynomial = self.construct_with_default
data_length = len(self.sorted)
# monomial
if data_length == 1:
d, c = self.sorted[0]
if d:
return polynomial([(d*2, c**2)])
else:
return polynomial([(0, c**2)])
# binomial
if data_length == 2:
(d1, c1), (d2, c2) = [(d, c) for (d, c) in self]
return polynomial({d1*2:c1**2, d1+d2:c1*c2*2, d2*2:c2**2})
# general (Karatsuba)
right_degree = self.sorted[-1][0]
left_degree = self.sorted[0][0]
half_degree = (right_degree + left_degree) >> 1
half_index = self._bisect(half_degree)
fst = polynomial([(d - left_degree, c) for (d, c) in self.sorted[:half_index]])
snd = polynomial([(d - half_degree, c) for (d, c) in self.sorted[half_index:]])
fst_squared = fst.square()
snd_squared = snd.square()
karatsuba = (fst + snd).square() - fst_squared - snd_squared
if left_degree:
return (fst_squared.upshift_degree(left_degree * 2) +
karatsuba.upshift_degree(left_degree + half_degree) +
snd_squared.upshift_degree(half_degree * 2))
else:
return (fst_squared +
karatsuba.upshift_degree(half_degree) +
snd_squared.upshift_degree(half_degree * 2))
def __pow__(self, index):
"""
self ** index
No ternary powering is defined here, because there is no
modulus operator defined.
"""
# special indices
if index < 0:
raise ValueError("negative index is not allowed.")
elif index == 0:
for c in self.itercoefficients():
if c:
one = _ring.getRing(c).one
break
else:
one = 1
return self.construct_with_default([(0, one)])
elif index == 1:
return self
elif index == 2:
return self.square()
# special polynomials
if not self:
return self
elif len(self.sorted) == 1:
return self.construct_with_default([(d*index, c**index) for (d, c) in self])
# general
power_product = self.construct_with_default([(0, 1)])
power_of_2 = self
while index:
if index & 1:
power_product *= power_of_2
index //= 2
if index:
power_of_2 = power_of_2.square()
return power_product
def degree(self):
"""
Return the degree of self
"""
assert self.sorted == sorted(self.sorted)
for d, c in self.sorted[::-1]:
if c:
return d
return -1
def leading_coefficient(self):
"""
Return the leading coefficient
"""
assert self.sorted == sorted(self.sorted)
for d, c in self.sorted[::-1]:
if c:
return c
return 0
def leading_term(self):
"""
Return the leading term as a tuple (degree, coefficient).
"""
assert self.sorted == sorted(self.sorted)
for d, c in self.sorted[::-1]:
if c:
return (d, c)
return (-1, 0)
def iterterms(self):
"""
iterator for (base, coefficient) pairs.
The iterator is equivalent to
zip(self.iterbases(), self.itercoefficients())
"""
return iter(self.sorted)
def iterbases(self):
"""
iterator for bases.
"""
for term in self.sorted:
yield term[0]
def itercoefficients(self):
"""
iterator for coefficients.
"""
for term in self.sorted:
yield term[1]
def __getitem__(self, degree):
"""
Return the coefficient of specified degree.
If there is no term of degree, return 0.
"""
if self.sorted:
rindex = self._bisect(degree)
if self.sorted[rindex - 1][0] == degree:
return self.sorted[rindex - 1][1]
return 0
def __contains__(self, degree):
"""
Return True if there is a term of specified degree.
False otherwise.
"""
rindex = self._bisect(degree)
if self.sorted[rindex - 1][0] == degree:
return True
return False
def __len__(self):
"""
Return the number of data entries.
"""
return len(self.sorted)
def __eq__(self, other):
"""
self == other
"""
if self is other:
return True
if not isinstance(other, SortedPolynomial):
return PolynomialInterface.__eq__(self, other)
if [t for t in self if t[1]] == [t for t in other if t[1]]:
return True
return False
def __hash__(self):
val = sum([hash(t) for t in self if t[1]])
return val
def __call__(self, val):
"""
substitution
"""
items = list(self.sorted)
if not items:
return 0 * val
val_pow = {1:val}
d, c = items.pop()
result = c
while len(items) > 0:
(e, f) = items.pop()
result = result * val_pow.setdefault(d - e, val ** (d - e)) + f
d = e
if d:
return result * val_pow.get(d, val ** d)
else:
return result
def __repr__(self): # debug
return repr(self.sorted)
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mayan/apps/document_states/migrations/0020_auto_20200311_1714.py | sophiawa/Mayan-EDMS | 0 | 1603560 | # Generated by Django 2.2.10 on 2020-03-11 17:14
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('document_states', '0019_workflowtransition_condition'),
]
operations = [
migrations.AddField(
model_name='workflowstateaction',
name='condition',
field=models.TextField(blank=True, help_text="The condition that will determine if this state action is executed or not. The condition is evaluated against the workflow instance. Conditions that return None or an empty string ('') are considered to be logical false, any other value is considered to be the logical true.", verbose_name='Condition'),
),
migrations.AlterField(
model_name='workflowtransition',
name='condition',
field=models.TextField(blank=True, help_text="The condition that will determine if this transition is enabled or not. The condition is evaluated against the workflow instance. Conditions that return None or an empty string ('') are considered to be logical false, any other value is considered to be the logical true.", verbose_name='Condition'),
),
]
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tests/test_discord_pretty_help.py | zaanposni/discord-pretty-help | 0 | 193704 | import discord
from discord.ext import commands
from pretty_help import Navigation, PrettyHelp, __version__
def test_version():
assert __version__ == "1.2.0"
# replace with your token
TOKEN = "TOKEN"
# ":discord:743511195197374563" is a custom discord emoji format. Adjust to match your own custom emoji.
nav = Navigation(":discord:743511195197374563", "👎", "\U0001F44D")
bot = commands.Bot(command_prefix="!", description="this is the bots descripton")
bot.help_command = PrettyHelp(navigation=nav)
@bot.event
async def on_ready():
print(f"Logged in as: {bot.user.name}")
print(f"With ID: {bot.user.id}")
class TestCog(commands.Cog):
"""This is a cog for testing purposes"""
@commands.command()
async def testcommand(self, ctx: commands.Context):
await ctx.send("This is a test command")
class ACog(commands.Cog, name="Z Cog"):
"""This is a cog for testing purposes"""
@commands.group()
async def atestcommand(self, ctx: commands.Context):
await ctx.send("This is a test command")
@atestcommand.command()
async def atestgroupcommand(self, ctx):
await ctx.send("this is a subcommand")
@bot.command()
async def test(ctx: commands.Context):
await ctx.send("this is the test command")
bot.add_cog(TestCog(bot))
bot.add_cog(ACog(bot))
bot.run(TOKEN)
# run !help in discord after starting the script
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xos/synchronizer/steps/sync_iperfserverinstance.py | cewuandy/iperfserver | 0 | 141658 | <filename>xos/synchronizer/steps/sync_iperfserverinstance.py
# Copyright 2017-present Open Networking Foundation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless 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.
import os
import sys
from synchronizers.new_base.SyncInstanceUsingAnsible import SyncInstanceUsingAnsible
from synchronizers.new_base.modelaccessor import *
from xos.logger import Logger, logging
parentdir = os.path.join(os.path.dirname(__file__), "..")
sys.path.insert(0, parentdir)
logger = Logger(level=logging.INFO)
class SyncIperfServerInstance(SyncInstanceUsingAnsible):
observes = VIPSServiceInstance
template_name = "iperfserverinstance_playbook.yaml"
service_key_name = "/opt/xos/synchronizers/rcord/rcord_private_key"
def __init__(self, *args, **kwargs):
super(SyncVIPSServiceInstance, self).__init__(*args, **kwargs)
def get_extra_attributes(self, o):
fields = {}
return fields
def get_my_ip_address(self, o, network_name, parameter=None):
return self.get_ip_address_from_peer_service_instance_instance(network_name, o, o, parameter)
def get_ip_address_from_peer_service_instance(self, network_name, sitype, o, parameter=None):
peer_si = self.get_peer_serviceinstance_of_type(sitype, o)
return self.get_ip_address_from_peer_service_instance_instance(network_name, peer_si, o, parameter)
def get_ip_address_from_peer_service_instance_instance(self, network_name, peer_si, o, parameter=None):
try:
net_id = self.get_network_id(network_name)
ins_id = peer_si.leaf_model.instance_id
ip_address = Port.objects.get(
network_id=net_id, instance_id=ins_id).ip
except Exception:
self.log.error("Failed to fetch parameter",
parameter=parameter,
network_name=network_name)
self.defer_sync(o, "Waiting for parameters to become available")
return ip_address
def get_peer_serviceinstance_of_type(self, sitype, o):
prov_link_set = ServiceInstanceLink.objects.filter(
subscriber_service_instance_id=o.id)
try:
peer_service = next(
p.provider_service_instance for p in prov_link_set if p.provider_service_instance.leaf_model_name == sitype)
except StopIteration:
sub_link_set = ServiceInstanceLink.objects.filter(
provider_service_instance_id=o.id)
try:
peer_service = next(
s.subscriber_service_instance for s in sub_link_set if s.subscriber_service_instance.leaf_model_name == sitype)
except StopIteration:
self.log.error(
'Could not find service type in service graph', service_type=sitype, object=o)
raise ServiceGraphException(
"Synchronization failed due to incomplete service graph")
return peer_service
# To get each network id
def get_network_id(self, network_name):
return Network.objects.get(name=network_name).id
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] |
leetcode/medium/1396-Design_underground.py | shubhamoli/practice | 1 | 49664 | <filename>leetcode/medium/1396-Design_underground.py
"""
Leetcode #1396
"""
from collections import defaultdict
class UndergroundSystem:
def __init__(self):
self.transit = defaultdict(list)
self.dest = defaultdict(list)
def checkIn(self, id: int, stationName: str, t: int) -> None:
self.transit[id] = [stationName, t]
def checkOut(self, id: int, stationName: str, t: int) -> None:
startStation, startTime = self.transit[id]
route = (startStation, stationName)
self.dest[route].append(t - startTime)
def getAverageTime(self, startStation: str, endStation: str) -> float:
route = (startStation, endStation)
return sum(self.dest[route])/len(self.dest[route])
if __name__ == "__main__":
# Your UndergroundSystem object will be instantiated and called as such:
obj = UndergroundSystem()
obj.checkIn(5,"A",8)
obj.checkIn(6,"A",8)
obj.checkOut(5,"C",10)
obj.checkOut(6,"D",11)
assert obj.getAverageTime("A","C") == 2
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test/tf/param/test_auto_save.py | jihuacao/Putil | 1 | 1616320 | # coding=utf-8
from optparse import OptionParser
import Putil.loger as plog
from colorama import Fore
import functools
import Putil.test.test_helper as th
parser = OptionParser(usage='usage %prog [options] arg1 arg2')
level_default = 'Debug'
parser.add_option(
'--level',
action='store',
dest='Level',
type=str,
default=level_default,
help='specify the log level for the app'
'default: {0}'.format(level_default)
)
parser.add_option(
'--test_ImproveSave',
action='store_true',
default=False,
dest='TestImproveSave',
help='set this flag while you want to test ImproveSave'
)
(options, args) = parser.parse_args()
plog.PutilLogConfig.config_log_level(stream=plog.LogReflect(options.Level).Level)
plog.PutilLogConfig.config_handler(plog.stream_method)
plog.PutilLogConfig.config_format(
"%(filename)s: %(lineno)d: %(levelname)s: %(name)s: %(message)s")
root_logger = plog.PutilLogConfig('tf/test/tf/param/test_auto_save').logger()
root_logger.setLevel(plog.DEBUG)
TestImproveSaveLogger = root_logger.getChild('TestImproveSave')
TestImproveSaveLogger.setLevel(plog.DEBUG)
import Putil.tf.param.auto_save as auto_save
class model:
def __init__(self):
self._auto_save = auto_save.ImproveSave(5).UseDefaultDecider(max=True).SetIndicatorGet(self.Output).CheckAutoSave()
self._data = [0.0, 1.0, 1.2, 1.3, 1.4, 1.1, 1.3, 1.7, 1.9, 1.0, 1.5]
self._i = -1
pass
def ModelCheck(self):
if self._auto_save.Save() is True:
TestImproveSaveLogger.debug('save in acc: {0}'.format(self.Output()))
return True
else:
return False
pass
@property
def AutoSave(self):
return self._auto_save
def TrainCv(self):
self._i += 1
pass
@property
def Data(self):
return self._data
def Output(self):
return self.Data[self._i]
def __test_improve_save():
print(th.information(0, 'start testing imrpove_save', Fore.GREEN) + Fore.RESET)
m = model()
print(m._auto_save._regular)
assert m._auto_save.IndicatorGetter == m.Output
assert m._auto_save.DecisionGenerator == m._auto_save._decider
hit_target = [1, 2, 3, 4, 7, 8]
for i in range(0, 11):
m.TrainCv()
if m.ModelCheck() is True:
if i in hit_target:
pass
else:
print(th.information(0, 'test improve_save failed', Fore.LIGHTRED_EX) + Fore.RESET)
pass
pass
pass
print(th.information(0, 'test improve_save successful', Fore.LIGHTGREEN_EX) + Fore.RESET)
pass
if __name__ == '__main__':
if options.TestImproveSave:
__test_improve_save()
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] |
setup.py | adjs/qclib | 1 | 64856 | """
pypi setup
"""
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="qclib",
version="0.0.8",
author="<NAME>",
author_email="<EMAIL>",
description="A quantum computing library using qiskit",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/qclib/qclib",
packages=setuptools.find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"Operating System :: OS Independent",
],
python_requires='>=3.7',
install_requires=[
'scipy>=1.7.1',
'qiskit>=0.18.3',
'deprecation',
'graphviz'
]
)
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2
] |
core/dbt/flags.py | tskleonard/dbt-core | 0 | 12290 | import os
import multiprocessing
if os.name != "nt":
# https://bugs.python.org/issue41567
import multiprocessing.popen_spawn_posix # type: ignore
from pathlib import Path
from typing import Optional
# PROFILES_DIR must be set before the other flags
# It also gets set in main.py and in set_from_args because the rpc server
# doesn't go through exactly the same main arg processing.
DEFAULT_PROFILES_DIR = os.path.join(os.path.expanduser("~"), ".dbt")
PROFILES_DIR = os.path.expanduser(os.getenv("DBT_PROFILES_DIR", DEFAULT_PROFILES_DIR))
STRICT_MODE = False # Only here for backwards compatibility
FULL_REFRESH = False # subcommand
STORE_FAILURES = False # subcommand
# Global CLI commands
USE_EXPERIMENTAL_PARSER = None
STATIC_PARSER = None
WARN_ERROR = None
WRITE_JSON = None
PARTIAL_PARSE = None
USE_COLORS = None
DEBUG = None
LOG_FORMAT = None
VERSION_CHECK = None
FAIL_FAST = None
SEND_ANONYMOUS_USAGE_STATS = None
PRINTER_WIDTH = 80
WHICH = None
INDIRECT_SELECTION = None
LOG_CACHE_EVENTS = None
EVENT_BUFFER_SIZE = 100000
QUIET = None
# Global CLI defaults. These flags are set from three places:
# CLI args, environment variables, and user_config (profiles.yml).
# Environment variables use the pattern 'DBT_{flag name}', like DBT_PROFILES_DIR
flag_defaults = {
"USE_EXPERIMENTAL_PARSER": False,
"STATIC_PARSER": True,
"WARN_ERROR": False,
"WRITE_JSON": True,
"PARTIAL_PARSE": True,
"USE_COLORS": True,
"PROFILES_DIR": DEFAULT_PROFILES_DIR,
"DEBUG": False,
"LOG_FORMAT": None,
"VERSION_CHECK": True,
"FAIL_FAST": False,
"SEND_ANONYMOUS_USAGE_STATS": True,
"PRINTER_WIDTH": 80,
"INDIRECT_SELECTION": "eager",
"LOG_CACHE_EVENTS": False,
"EVENT_BUFFER_SIZE": 100000,
"QUIET": False,
}
def env_set_truthy(key: str) -> Optional[str]:
"""Return the value if it was set to a "truthy" string value, or None
otherwise.
"""
value = os.getenv(key)
if not value or value.lower() in ("0", "false", "f"):
return None
return value
def env_set_bool(env_value):
if env_value in ("1", "t", "true", "y", "yes"):
return True
return False
def env_set_path(key: str) -> Optional[Path]:
value = os.getenv(key)
if value is None:
return value
else:
return Path(value)
MACRO_DEBUGGING = env_set_truthy("DBT_MACRO_DEBUGGING")
DEFER_MODE = env_set_truthy("DBT_DEFER_TO_STATE")
ARTIFACT_STATE_PATH = env_set_path("DBT_ARTIFACT_STATE_PATH")
ENABLE_LEGACY_LOGGER = env_set_truthy("DBT_ENABLE_LEGACY_LOGGER")
def _get_context():
# TODO: change this back to use fork() on linux when we have made that safe
return multiprocessing.get_context("spawn")
# This is not a flag, it's a place to store the lock
MP_CONTEXT = _get_context()
def set_from_args(args, user_config):
# N.B. Multiple `globals` are purely for line length.
# Because `global` is a parser directive (as opposed to a language construct)
# black insists in putting them all on one line
global STRICT_MODE, FULL_REFRESH, WARN_ERROR, USE_EXPERIMENTAL_PARSER, STATIC_PARSER
global WRITE_JSON, PARTIAL_PARSE, USE_COLORS, STORE_FAILURES, PROFILES_DIR, DEBUG, LOG_FORMAT
global INDIRECT_SELECTION, VERSION_CHECK, FAIL_FAST, SEND_ANONYMOUS_USAGE_STATS
global PRINTER_WIDTH, WHICH, LOG_CACHE_EVENTS, EVENT_BUFFER_SIZE, QUIET
STRICT_MODE = False # backwards compatibility
# cli args without user_config or env var option
FULL_REFRESH = getattr(args, "full_refresh", FULL_REFRESH)
STORE_FAILURES = getattr(args, "store_failures", STORE_FAILURES)
WHICH = getattr(args, "which", WHICH)
# global cli flags with env var and user_config alternatives
USE_EXPERIMENTAL_PARSER = get_flag_value("USE_EXPERIMENTAL_PARSER", args, user_config)
STATIC_PARSER = get_flag_value("STATIC_PARSER", args, user_config)
WARN_ERROR = get_flag_value("WARN_ERROR", args, user_config)
WRITE_JSON = get_flag_value("WRITE_JSON", args, user_config)
PARTIAL_PARSE = get_flag_value("PARTIAL_PARSE", args, user_config)
USE_COLORS = get_flag_value("USE_COLORS", args, user_config)
PROFILES_DIR = get_flag_value("PROFILES_DIR", args, user_config)
DEBUG = get_flag_value("DEBUG", args, user_config)
LOG_FORMAT = get_flag_value("LOG_FORMAT", args, user_config)
VERSION_CHECK = get_flag_value("VERSION_CHECK", args, user_config)
FAIL_FAST = get_flag_value("FAIL_FAST", args, user_config)
SEND_ANONYMOUS_USAGE_STATS = get_flag_value("SEND_ANONYMOUS_USAGE_STATS", args, user_config)
PRINTER_WIDTH = get_flag_value("PRINTER_WIDTH", args, user_config)
INDIRECT_SELECTION = get_flag_value("INDIRECT_SELECTION", args, user_config)
LOG_CACHE_EVENTS = get_flag_value("LOG_CACHE_EVENTS", args, user_config)
EVENT_BUFFER_SIZE = get_flag_value("EVENT_BUFFER_SIZE", args, user_config)
QUIET = get_flag_value("QUIET", args, user_config)
def get_flag_value(flag, args, user_config):
lc_flag = flag.lower()
flag_value = getattr(args, lc_flag, None)
if flag_value is None:
# Environment variables use pattern 'DBT_{flag name}'
env_flag = f"DBT_{flag}"
env_value = os.getenv(env_flag)
if env_value is not None and env_value != "":
env_value = env_value.lower()
# non Boolean values
if flag in [
"LOG_FORMAT",
"PRINTER_WIDTH",
"PROFILES_DIR",
"INDIRECT_SELECTION",
"EVENT_BUFFER_SIZE",
]:
flag_value = env_value
else:
flag_value = env_set_bool(env_value)
elif user_config is not None and getattr(user_config, lc_flag, None) is not None:
flag_value = getattr(user_config, lc_flag)
else:
flag_value = flag_defaults[flag]
if flag in ["PRINTER_WIDTH", "EVENT_BUFFER_SIZE"]: # must be ints
flag_value = int(flag_value)
if flag == "PROFILES_DIR":
flag_value = os.path.abspath(flag_value)
return flag_value
def get_flag_dict():
return {
"use_experimental_parser": USE_EXPERIMENTAL_PARSER,
"static_parser": STATIC_PARSER,
"warn_error": WARN_ERROR,
"write_json": WRITE_JSON,
"partial_parse": PARTIAL_PARSE,
"use_colors": USE_COLORS,
"profiles_dir": PROFILES_DIR,
"debug": DEBUG,
"log_format": LOG_FORMAT,
"version_check": VERSION_CHECK,
"fail_fast": FAIL_FAST,
"send_anonymous_usage_stats": SEND_ANONYMOUS_USAGE_STATS,
"printer_width": PRINTER_WIDTH,
"indirect_selection": INDIRECT_SELECTION,
"log_cache_events": LOG_CACHE_EVENTS,
"event_buffer_size": EVENT_BUFFER_SIZE,
"quiet": QUIET,
}
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] |
Tools/Scripts/webkitpy/common/checkout/baselineoptimizer_unittest.py | quanganh2627/bytm-x64-L-w05-2015_external_chromium_org_third_party_WebKit | 0 | 1612228 | <gh_stars>0
# Copyright (C) 2011 Google Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following disclaimer
# in the documentation and/or other materials provided with the
# distribution.
# * Neither the name of Google Inc. nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import webkitpy.thirdparty.unittest2 as unittest
from webkitpy.common.checkout.baselineoptimizer import BaselineOptimizer
from webkitpy.common.checkout.scm.scm_mock import MockSCM
from webkitpy.common.host_mock import MockHost
from webkitpy.common.webkit_finder import WebKitFinder
class ExcludingMockSCM(MockSCM):
def __init__(self, exclusion_list, filesystem=None, executive=None):
MockSCM.__init__(self, filesystem, executive)
self._exclusion_list = exclusion_list
def exists(self, path):
if path in self._exclusion_list:
return False
return MockSCM.exists(self, path)
def delete(self, path):
return self.delete_list([path])
def delete_list(self, paths):
for path in paths:
if path in self._exclusion_list:
raise Exception("File is not SCM managed: " + path)
return MockSCM.delete_list(self, paths)
def move(self, origin, destination):
if origin in self._exclusion_list:
raise Exception("File is not SCM managed: " + origin)
return MockSCM.move(self, origin, destination)
class BaselineOptimizerTest(unittest.TestCase):
def test_move_baselines(self):
host = MockHost(scm=ExcludingMockSCM(['/mock-checkout/third_party/WebKit/LayoutTests/platform/mac/another/test-expected.txt']))
host.filesystem.write_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/platform/win/another/test-expected.txt', 'result A')
host.filesystem.write_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/platform/mac/another/test-expected.txt', 'result A')
host.filesystem.write_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/another/test-expected.txt', 'result B')
baseline_optimizer = BaselineOptimizer(host, host.port_factory.all_port_names(), skip_scm_commands=False)
baseline_optimizer._move_baselines('another/test-expected.txt', {
'/mock-checkout/third_party/WebKit/LayoutTests/platform/win': 'aaa',
'/mock-checkout/third_party/WebKit/LayoutTests/platform/mac': 'aaa',
'/mock-checkout/third_party/WebKit/LayoutTests': 'bbb',
}, {
'/mock-checkout/third_party/WebKit/LayoutTests': 'aaa',
})
self.assertEqual(host.filesystem.read_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/another/test-expected.txt'), 'result A')
def test_move_baselines_skip_scm_commands(self):
host = MockHost(scm=ExcludingMockSCM(['/mock-checkout/third_party/WebKit/LayoutTests/platform/mac/another/test-expected.txt']))
host.filesystem.write_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/platform/win/another/test-expected.txt', 'result A')
host.filesystem.write_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/platform/mac/another/test-expected.txt', 'result A')
host.filesystem.write_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/another/test-expected.txt', 'result B')
baseline_optimizer = BaselineOptimizer(host, host.port_factory.all_port_names(), skip_scm_commands=True)
baseline_optimizer._move_baselines('another/test-expected.txt', {
'/mock-checkout/third_party/WebKit/LayoutTests/platform/win': 'aaa',
'/mock-checkout/third_party/WebKit/LayoutTests/platform/mac': 'aaa',
'/mock-checkout/third_party/WebKit/LayoutTests': 'bbb',
}, {
'/mock-checkout/third_party/WebKit/LayoutTests/platform/linux': 'bbb',
'/mock-checkout/third_party/WebKit/LayoutTests': 'aaa',
})
self.assertEqual(host.filesystem.read_binary_file('/mock-checkout/third_party/WebKit/LayoutTests/another/test-expected.txt'), 'result A')
self.assertEqual(baseline_optimizer._files_to_delete, [
'/mock-checkout/third_party/WebKit/LayoutTests/platform/win/another/test-expected.txt',
])
self.assertEqual(baseline_optimizer._files_to_add, [
'/mock-checkout/third_party/WebKit/LayoutTests/another/test-expected.txt',
'/mock-checkout/third_party/WebKit/LayoutTests/platform/linux/another/test-expected.txt',
])
def _assertOptimization(self, results_by_directory, expected_new_results_by_directory, baseline_dirname='', expected_files_to_delete=None):
host = MockHost()
fs = host.filesystem
webkit_base = WebKitFinder(fs).webkit_base()
baseline_name = 'mock-baseline-expected.txt'
for dirname, contents in results_by_directory.items():
path = fs.join(webkit_base, 'LayoutTests', dirname, baseline_name)
fs.write_binary_file(path, contents)
baseline_optimizer = BaselineOptimizer(host, host.port_factory.all_port_names(), skip_scm_commands=expected_files_to_delete is not None)
self.assertTrue(baseline_optimizer.optimize(fs.join(baseline_dirname, baseline_name)))
for dirname, contents in expected_new_results_by_directory.items():
path = fs.join(webkit_base, 'LayoutTests', dirname, baseline_name)
if contents is None:
self.assertTrue(not fs.exists(path) or path in baseline_optimizer._files_to_delete)
else:
self.assertEqual(fs.read_binary_file(path), contents)
# Check that the files that were in the original set have been deleted where necessary.
for dirname in results_by_directory:
path = fs.join(webkit_base, 'LayoutTests', dirname, baseline_name)
if not dirname in expected_new_results_by_directory:
self.assertTrue(not fs.exists(path) or path in baseline_optimizer._files_to_delete)
if expected_files_to_delete:
self.assertEqual(baseline_optimizer._files_to_delete, expected_files_to_delete)
def test_linux_redundant_with_win(self):
self._assertOptimization({
'platform/win': '1',
'platform/linux': '1',
}, {
'platform/win': '1',
})
def test_covers_mac_win_linux(self):
self._assertOptimization({
'platform/mac': '1',
'platform/win': '1',
'platform/linux': '1',
'': None,
}, {
'': '1',
})
def test_overwrites_root(self):
self._assertOptimization({
'platform/mac': '1',
'platform/win': '1',
'platform/linux': '1',
'': '2',
}, {
'': '1',
})
def test_no_new_common_directory(self):
self._assertOptimization({
'platform/mac': '1',
'platform/linux': '1',
'': '2',
}, {
'platform/mac': '1',
'platform/linux': '1',
'': '2',
})
def test_local_optimization(self):
self._assertOptimization({
'platform/mac': '1',
'platform/linux': '1',
'platform/linux-x86': '1',
}, {
'platform/mac': '1',
'platform/linux': '1',
})
def test_local_optimization_skipping_a_port_in_the_middle(self):
self._assertOptimization({
'platform/mac-snowleopard': '1',
'platform/win': '1',
'platform/linux-x86': '1',
}, {
'platform/mac-snowleopard': '1',
'platform/win': '1',
})
def test_baseline_redundant_with_root(self):
self._assertOptimization({
'platform/mac': '1',
'platform/win': '2',
'': '2',
}, {
'platform/mac': '1',
'': '2',
})
def test_root_baseline_unused(self):
self._assertOptimization({
'platform/mac': '1',
'platform/win': '2',
'': '3',
}, {
'platform/mac': '1',
'platform/win': '2',
})
def test_root_baseline_unused_and_non_existant(self):
self._assertOptimization({
'platform/mac': '1',
'platform/win': '2',
}, {
'platform/mac': '1',
'platform/win': '2',
})
def test_virtual_root_redundant_with_actual_root(self):
self._assertOptimization({
'virtual/softwarecompositing': '2',
'compositing': '2',
}, {
'virtual/softwarecompositing': None,
'compositing': '2',
}, baseline_dirname='virtual/softwarecompositing')
def test_virtual_root_redundant_with_ancestors(self):
self._assertOptimization({
'virtual/softwarecompositing': '2',
'platform/mac/compositing': '2',
'platform/win/compositing': '2',
}, {
'virtual/softwarecompositing': None,
'compositing': '2',
}, baseline_dirname='virtual/softwarecompositing')
def test_virtual_root_redundant_with_ancestors_skip_scm_commands(self):
self._assertOptimization({
'virtual/softwarecompositing': '2',
'platform/mac/compositing': '2',
'platform/win/compositing': '2',
}, {
'virtual/softwarecompositing': None,
'compositing': '2',
},
baseline_dirname='virtual/softwarecompositing',
expected_files_to_delete=[
'/mock-checkout/third_party/WebKit/LayoutTests/virtual/softwarecompositing/mock-baseline-expected.txt',
'/mock-checkout/third_party/WebKit/LayoutTests/platform/mac/compositing/mock-baseline-expected.txt',
'/mock-checkout/third_party/WebKit/LayoutTests/platform/win/compositing/mock-baseline-expected.txt',
])
def test_virtual_root_not_redundant_with_ancestors(self):
self._assertOptimization({
'virtual/softwarecompositing': '2',
'platform/mac/compositing': '1',
}, {
'virtual/softwarecompositing': '2',
'platform/mac/compositing': '1',
}, baseline_dirname='virtual/softwarecompositing')
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models/gaze_rnn77.py | yj-yu/Recurrent_Gaze_Prediction | 9 | 34304 | <reponame>yj-yu/Recurrent_Gaze_Prediction
#-*- coding: utf-8 -*-
"""
gaze_rnn7.py
Implement a simple recurrent gaze prediction model based on RNN(GRU).
In this version, the gaze DIM is REDUCED to 7x7 dimension.
"""
# TODO separate pupil from gazemaps, AWFUL design
import numpy as np
import os
import sys
import time
from PIL import Image
import tensorflow as tf
rnn_cell = tf.nn.rnn_cell
from collections import OrderedDict
import cPickle as pkl
import crc_input_data_seq
from util import log, override
from models.base import ModelBase, BaseModelConfig
from models.saliency_shallownet import SaliencyModel
from models.model_util import tf_normalize_map, normalize_probability_map
from models.model_util import tf_softmax_2d, tf_softmax_cross_entropy_with_logits_2d
from evaluation_metrics import saliency_score, AVAILABLE_METRICS
from easydict import EasyDict as E
CONSTANTS = E()
CONSTANTS.image_width = 98
CONSTANTS.image_height = 98
CONSTANTS.gazemap_width = 7
CONSTANTS.gazemap_height = 7
CONSTANTS.saliencymap_width = 49
CONSTANTS.saliencymap_height = 49
# config : changed as paramter later
class GRUModelConfig(BaseModelConfig):
def __init__(self):
super(GRUModelConfig, self).__init__()
self.n_lstm_steps = 35
self.batch_size = 7 # XXX XXX XXX XXX
self.dim_feature = 1024 #1024
self.dim_sal = 1024*49 #196
self.dim_sal_proj = 1024
# use adam by default
self.optimization_method = 'adam'
self.loss_type = 'l2'
from gaze_rnn import GazePredictionGRU as GazePredictionGRU4949
class GazePredictionGRU(GazePredictionGRU4949):
# Does not compatible model.py yet. mount that to this model. TODO"
def __init__(self,
session,
data_sets,
config=GRUModelConfig()
):
self.session = session
self.data_sets = data_sets
self.config = config
#assert isinstance(self.config, GRUModelConfig)
super(GazePredictionGRU, self).__init__(session, data_sets, config)
# other configuration
self.batch_size = config.batch_size
self.n_lstm_steps = config.n_lstm_steps
self.dim_feature = config.dim_feature
self.dim_sal = config.dim_sal # 49 * 49
self.dim_sal_proj = config.dim_sal_proj # 14 * 14 = 196
self.dim_cnn_proj = 32
self.initial_learning_rate = config.initial_learning_rate
self.learning_rate_decay = config.learning_rate_decay
self.max_grad_norm = config.max_grad_norm
self.gazemap_height = CONSTANTS.gazemap_height # 7
self.gazemap_width = CONSTANTS.gazemap_width # 7
self.image_height = CONSTANTS.image_height
self.image_width = CONSTANTS.image_width
# Finally, build the model and optimizer
self.build_model()
#self.build_generator()
self.build_train_op()
self.session.run(tf.initialize_all_variables())
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] |
bspump/unittest/__init__.py | thatch/BitSwanPump | 17 | 197200 | from .pipeline import UnitTestPipeline
from .sink import UnitTestSink
from .source import UnitTestSource
from .unit_test_case import ProcessorTestCase
from .unit_test_case import TestCase
__all__ = (
'UnitTestPipeline',
'UnitTestSink',
'UnitTestSource',
'ProcessorTestCase',
'TestCase',
)
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process_image_withTensorFlow.py | DimasVeliz/yolov4-deepsort | 0 | 104743 | <reponame>DimasVeliz/yolov4-deepsort
import os
import tensorflow as tf
physical_devices = tf.config.experimental.list_physical_devices('GPU')
if len(physical_devices) > 0:
tf.config.experimental.set_memory_growth(physical_devices[0], True)
from absl import app, flags, logging
from absl.flags import FLAGS, Flag
import core.utils as utils
from core.yolov4 import filter_boxes
from tensorflow.python.saved_model import tag_constants
from core.config import cfg
from PIL import Image
import cv2
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession
flags.DEFINE_string('framework', 'tf', '(tf, tflite, trt')
flags.DEFINE_string('weights', './checkpoints/yolov4-416','path to weights file')
flags.DEFINE_integer('size', 416, 'resize images to')
flags.DEFINE_boolean('tiny', False, 'yolo or yolo-tiny')
flags.DEFINE_string('model', 'yolov4', 'yolov3 or yolov4')
flags.DEFINE_float('iou', 0.45, 'iou threshold')
flags.DEFINE_float('score', 0.50, 'score threshold')
flags.DEFINE_boolean('dont_show', False, 'dont show image output')
def buildObjectDetected(class_id, confidence, x, y, x_plus_w, y_plus_h, classes):
label = str(classes[class_id])
obj={ }
obj["class"]=label
obj["confidence"]=confidence
obj["x"]=x
obj["y"]=y
obj["height"]=y_plus_h
obj["width"]=x_plus_w
return obj
def do_image_processing(imagePath,saved_model_loaded,infer,STRIDES, ANCHORS, NUM_CLASS, XYSCALE,input_size):
frame = cv2.imread(imagePath)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
image = Image.fromarray(frame)
frame_size = frame.shape[:2]
image_data = cv2.resize(frame, (input_size, input_size))
image_data = image_data / 255.
image_data = image_data[np.newaxis, ...].astype(np.float32)
batch_data = tf.constant(image_data)
pred_bbox = infer(batch_data)
for key, value in pred_bbox.items():
boxes = value[:, :, 0:4]
pred_conf = value[:, :, 4:]
boxes, scores, classes, valid_detections = tf.image.combined_non_max_suppression(
boxes=tf.reshape(boxes, (tf.shape(boxes)[0], -1, 1, 4)),
scores=tf.reshape(
pred_conf, (tf.shape(pred_conf)[0], -1, tf.shape(pred_conf)[-1])),
max_output_size_per_class=50,
max_total_size=50,
iou_threshold=FLAGS.iou,
score_threshold=FLAGS.score
)
# convert data to numpy arrays and slice out unused elements
num_objects = valid_detections.numpy()[0]
bboxes = boxes.numpy()[0]
bboxes = bboxes[0:int(num_objects)]
scores = scores.numpy()[0]
scores = scores[0:int(num_objects)]
classes = classes.numpy()[0]
classes = classes[0:int(num_objects)]
# format bounding boxes from normalized ymin, xmin, ymax, xmax ---> xmin, ymin, width, height
original_h, original_w, _ = frame.shape
bboxes = utils.format_boxes(bboxes, original_h, original_w)
# store all predictions in one parameter for simplicity when calling functions
pred_bbox = [bboxes, scores, classes, num_objects]
# read in all class names from config
class_names = utils.read_class_names(cfg.YOLO.CLASSES)
# by default allow all classes in .names file
allowed_classes = list(class_names.values())
# custom allowed classes (uncomment line below to customize tracker for only people)
#allowed_classes = ['person']
# loop through objects and use class index to get class name, allow only classes in allowed_classes list
names = []
deleted_indx = []
for i in range(num_objects):
class_indx = int(classes[i])
class_name = class_names[class_indx]
if class_name not in allowed_classes:
deleted_indx.append(i)
else:
names.append(class_name)
names = np.array(names)
count = len(names)
# delete detections that are not in allowed_classes
bboxes = np.delete(bboxes, deleted_indx, axis=0)
scores = np.delete(scores, deleted_indx, axis=0)
response=[]
for index in range(len(classes)):
class_name=class_names[classes[index]]
bbox=bboxes[index]
col=int(bbox[0])
row=int(bbox[1])
width=col+int(bbox[2])
heigth=row+ int(bbox[3])
newObj=buildObjectDetected(classes[index], scores[i], col, row, width, heigth, class_names)
response.append(newObj)
#cv2.rectangle(frame, (col,row), (width, heigth), (255,0,255), 2)
#cv2.putText(frame, class_name,(int(bbox[0]), int(bbox[1]-10)),0, 0.75, (255,255,255),2)
#result = np.asarray(frame)
#result = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
#if not FLAGS.dont_show:
#cv2.imshow("Output Video", result)
#
#if cv2.waitKey(0) & 0xFF == ord('q'):
#cv2.destroyAllWindows()
#return
return response
def configure(_argv):
# load configuration for object detector
config = ConfigProto()
config.gpu_options.allow_growth = True
session = InteractiveSession(config=config)
STRIDES, ANCHORS, NUM_CLASS, XYSCALE = utils.load_config(FLAGS)
input_size = FLAGS.size
# load standard tensorflow saved model
saved_model_loaded = tf.saved_model.load(FLAGS.weights, tags=[tag_constants.SERVING])
infer = saved_model_loaded.signatures['serving_default']
return saved_model_loaded,infer,input_size,STRIDES, ANCHORS, NUM_CLASS, XYSCALE
def main(_argv):
FLAGS.weights= "./checkpoints/yolov4-tiny-416"
FLAGS.model="yolov4"
FLAGS.tiny =True
saved_model_loaded,infer,input_size,STRIDES, ANCHORS, NUM_CLASS, XYSCALE =configure([])
imagePath="./data/testImage.jpg"
response =do_image_processing(imagePath,saved_model_loaded,infer,STRIDES, ANCHORS, NUM_CLASS, XYSCALE,input_size)
print(response)
if __name__ == '__main__':
try:
app.run(main)
except SystemExit:
pass | [
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] |
dataset.py | donghankim/comma_ai_speed_challenge | 0 | 19007 | import os
import pandas as pd
import numpy as np
import torch
from torchvision import transforms
from torch.utils.data import Dataset
import matplotlib.pyplot as plt
from skimage import io
import pdb
class FrameDataset(Dataset):
def __init__(self, csv_file, train_dir):
self.labels = pd.read_csv(csv_file)
self.train_dir = train_dir
self.transform = transforms.Compose([
transforms.ToPILImage(),
transforms.Resize((66,220)),
transforms.ToTensor(),
transforms.Normalize(mean = [0.485, 0.456, 0.406], std = [0.229, 0.224, 0.225]),
])
def show_img(self, img, denormalize = True):
inv_normalize = transforms.Normalize(mean=[-0.485/0.229, -0.456/0.224, -0.406/0.225], std=[1/0.229, 1/0.224, 1/0.225])
if denormalize:
img = inv_normalize(img)
plt.imshow(np.transpose(img.numpy(), (1,2,0)))
plt.show()
def __len__(self):
return len(self.labels)
def __getitem__(self, index):
img_path = os.path.join(self.train_dir, self.labels.iloc[index][0])
image = io.imread(img_path)
y_label = torch.tensor(float(self.labels.iloc[index][1]))
if self.transform:
image = self.transform(image)
return (image, y_label)
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13,
13,
2
] |
Python3.01.06.py | MrMontag/python_test | 0 | 178067 | <gh_stars>0
import os
print("Hallo, ich habe 5 Fragen an Sie. Sie können zwischen den Fragen wählen.")
punkte=0
while True:
print("Geben Sie die Nummer der gewünschten Frage ein.")
print("Geben Sie STOP ein, wenn Sie das Programm verlassen möchten.")
nummer=input()
if nummer.upper()=="STOP":
print("Sie haben "+str(punkte)+" Punkt(e) erreicht.")
os.system("pause")
break
elif nummer.isalpha() or int(nummer)>5 or int(nummer)<1:
print("Es muss eine Nummer von 1 bis 5 sein!")
elif nummer.lower=="ok":
print("Sie haben noch einen Versuch! (Glaube ich...")
else:
if int(nummer)==1:
print("Was ist 1+1?")
print("A: 4\nB: 2\nC: 9")
print("Gebe nun A, B oder C als Antwort ein.")
buchstabe1=input()
if buchstabe1=="A" or buchstabe1=="C":
print("Falsch!")
elif buchstabe1=="B":
print("Richtig!")
punkte+=1
else:
print("Benutzen Sie einen gültigen Buchstaben! Zur Strafe müssen Sie von vorne anfangen.")
if int(nummer)==2:
print("Wo steht der Eifelturm von Pisa?")
print("A: in Pisa\nB: in Paris\nC: Hahahahahaha!!!")
print("Gebe nun A, B oder C als Antwort ein.")
buchstabe2=input()
if buchstabe2=="A" or buchstabe2=="B":
print("Falsch!")
elif buchstabe2=="C":
print("Richtig!")
punkte+=1
else:
print("Benutzen Sie einen gültigen Buchstaben! Zur Strafe müssen Sie von vorne anfangen.")
if int(nummer)==3:
print("lst in diesem Satz etwas falsch geschrieben?")
print("J: Ja"+"\n"+"N: Nein")
print("Gebe nun J oder N als Antwort ein.")
buchstabe3=input()
if buchstabe3=="N":
print("Falsch!")
elif buchstabe3=="J":
print("Richtig!")
punkte+=1
else:
print("Benutzen Sie einen gültigen Buchstaben! Zur Strafe müssen Sie von vorne anfangen.")
if int(nummer)==4:
print("Welche Aussage ist falsch?")
print("A:Keine"+"\n"+"B:Ich kann lesen"+"\n"+"C:Es gibt eine")
print("Gebe nun A, B oder C als Antwort ein.")
buchstabe4=input()
if buchstabe4=="B" or buchstabe4=="C":
print("Falsch!")
elif buchstabe4=="A":
print("Richtig!")
punkte+=1
else:
print("Benutzen Sie einen gültigen Buchstaben! Zur Strafe müssen Sie von vorne anfangen.")
if int(nummer)==5:
print("Ein Würfel ist rund.")
print("J: Ja"+"\n"+"N: Nein")
print("Gebe nun J oder N als Antwort ein.")
buchstabe5=input()
if buchstabe5=="J":
print("Falsch!")
elif buchstabe5=="N":
print("Richtig!")
punkte+=1
else:
print("Benutzen Sie einen gültigen Buchstaben! Zur Strafe müssen Sie von vorne anfangen.")
| [
1,
529,
12443,
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] |
bootstrap/p1.5.0/src/common/const.py | apurwaj2/df-on-k8s | 0 | 5526 |
class Constants(object):
LOGGER_CONF = "common/mapr_conf/logger.yml"
USERNAME = "mapr"
GROUPNAME = "mapr"
USERID = 5000
GROUPID = 5000
ADMIN_USERNAME = "custadmin"
ADMIN_GROUPNAME = "custadmin"
ADMIN_USERID = 7000
ADMIN_GROUPID = 7000
ADMIN_PASS = "<PASSWORD>"
MYSQL_USER = "admin"
MYSQL_PASS = "<PASSWORD>"
LDAPADMIN_USER = "admin"
LDAPADMIN_PASS = "<PASSWORD>"
LDAPBIND_USER = "readonly"
LDAPBIND_PASS = "<PASSWORD>"
EXAMPLE_LDAP_NAMESPACE = "hpe-ldap"
CSI_REPO = "quay.io/k8scsi"
KDF_REPO = "docker.io/maprtech" #registry.hub.docker.com/maprtech
KUBEFLOW_REPO = "gcr.io/mapr-252711/kf-ecp-5.3.0"
OPERATOR_REPO = "gcr.io/mapr-252711"
KUBELET_DIR = "/var/lib/kubelet"
ECP_KUBELET_DIR = "/var/lib/docker/kubelet"
LOCAL_PATH_PROVISIONER_REPO= ""
KFCTL_HSP_ISTIO_REPO = ""
BUSYBOX_REPO = ""
def enum(**named_values):
return type('Enum', (), named_values)
AUTH_TYPES = enum(CUSTOM_LDAP='customLDAP', RAW_LINUX_USERS='rawLinuxUsers', EXAMPLE_LDAP='exampleLDAP')
# OPEN SSL
OPENSSL = '/usr/bin/openssl'
KEY_SIZE = 1024
DAYS = 3650
CA_CERT = 'ca.cert'
CA_KEY = 'ca.key'
# http://www.openssl.org/docs/apps/openssl.html#PASS_PHRASE_ARGUMENTS
X509_EXTRA_ARGS = ()
OPENSSL_CONFIG_TEMPLATE = """
prompt = no
distinguished_name = req_distinguished_name
req_extensions = v3_req
[ req_distinguished_name ]
C = US
ST = CO
L = Fort Collins
O = HPE
OU = HCP
CN = %(service)s
emailAddress = <EMAIL>
[ v3_req ]
# Extensions to add to a certificate request
basicConstraints = CA:FALSE
keyUsage = nonRepudiation, digitalSignature, keyEncipherment
subjectAltName = @alt_names
[ alt_names ]
DNS.1 = %(service)s
DNS.2 = %(service)s.%(namespace)s
DNS.3 = %(service)s.%(namespace)s.svc
"""
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29908,
13,
2
] |
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