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timestamp[us] | committer_date
timestamp[us] | github_id
int64 18.2k
668M
โ | star_events_count
int64 0
102k
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int64 0
38.2k
| gha_license_id
stringclasses 17
values | gha_event_created_at
timestamp[us] | gha_created_at
timestamp[us] | gha_language
stringclasses 107
values | src_encoding
stringclasses 20
values | language
stringclasses 1
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classes | is_generated
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int64 4
6.02M
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| authors
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1
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175
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
51abc3a0995b54ff641ac7d9299e5d5c875dcdd3
|
bdcf6c539bc622e2236347ecc1fea1e0b512669c
|
/Bennos Projekte/QUAX-Manager/QuaxManager3/main.py
|
7009c188da514d91b011b2b67d4d0e8dcf7f3384
|
[] |
no_license
|
TheRealCubeAD/BANDO
|
b06aa9e4d8551d07d55a6ff660e5f8b22301cb61
|
d756b81b2d8f1c92c1170a2af8bb99033cae60be
|
refs/heads/master
| 2022-09-01T12:13:00.999514 | 2022-08-07T10:10:08 | 2022-08-07T10:10:08 | 125,618,232 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 13,628 |
py
|
import os
import filecmp
import string
import time
import shutil
import datetime
import threading
IMAGE = 123
VIDEO = 789
IMAGE_ENDINGS = set(("png","dng","jpg","jpeg"))
VIDEO_ENDINGS = set(("avi","mp4","mpeg"))
IDENT_FILE = "IDENT.config"
INTERNAL = "itd"
EXTERNAL = "etd"
STORAGE = "stc"
def INTERRUPT(cause=None):
print(cause)
input()
pass
class DATE:
def __init__(self, year, month, day, from_file=None, folder=False):
if from_file:
if not folder:
file_date = os.path.getctime(from_file)
file_date = str(datetime.datetime.fromtimestamp(file_date))
file_date = file_date.split()[0].split("-")
self.year = int(file_date[0])
self.month = int(file_date[1])
self.day = int(file_date[2])
else:
self.year, self.month, self.day = from_file.split(".")
self.year = int(self.year) + 2000
self.month = int(self.month)
self.day = int(self.day)
else:
self.year = year
self.month = month
self.day = day
if type(self.year) != int or type(self.month) != int or type(self.day) != int:
raise TypeError("date-component must be int")
if self.month not in range(1, 13) or self.day not in range(1, 32):
raise AttributeError("invalid date")
def __eq__(self, other):
return self.year == other.year and self.month == other.month and self.day == other.day
def __hash__(self):
return hash(self.to_string())
def duplicate(self):
return DATE(self.year, self.month, self.day)
def to_string(self):
s_day = str(self.day)
s_month = str(self.month)
s_year = str(self.year)
if len(s_day) < 2:
s_day = "0" + s_day
if len(s_month) < 2:
s_month = "0" + s_month
s_year = s_year[2:]
return s_year + "." + s_month + "." + s_day
def __str__(self):
s_day = str(self.day)
s_month = str(self.month)
s_year = str(self.year)
if len(s_day) < 2:
s_day = "0" + s_day
if len(s_month) < 2:
s_month = "0" + s_month
s_year = s_year[2:]
return s_day + "." + s_month + "." + s_year
class FILE:
def __init__(self, path, name=None, ending=None, should_exist=False):
self.date = None
path = path.replace("\\", "/")
self.path = ""
if name:
if ending:
self.ending = ending
self.name = name
else:
self.name, self.ending = name.split(".")
self.path = path
if self.path[-1] != "/":
self.path += "/"
else:
parts = path.rstrip("/").split("/")
self.name, self.ending = parts.pop().split(".")
for part in parts:
self.path += part + "/"
if self.ending.lower() in IMAGE_ENDINGS:
self.type = IMAGE
elif self.ending.lower() in VIDEO_ENDINGS:
self.type = VIDEO
else:
print("WARNING: Unknown File-type: " + self.ending)
self.type = None
self.should_exist = should_exist
if self.should_exist:
self.load_date()
def get_full_path(self):
return self.path + self.name + "." + self.ending
def check_exsitance(self):
if self.should_exist:
while 1:
if self.is_existing():
return True
else:
INTERRUPT("missing_file")
else:
return self.is_existing()
def is_existing(self):
return os.path.exists(self.get_full_path())
def load_date(self):
self.check_exsitance()
try:
self.date = DATE(0, 0, 0, from_file=self.get_full_path())
except:
self.date = None
print("ERROR while loading file-date")
def get_size(self):
self.check_exsitance()
try:
return os.path.getsize(self.get_full_path())
except:
print("WARNING: file_size_error")
return 1
def copy(self, destination):
full_destination = destination + self.name + "." + self.ending
while 1:
try:
self.check_exsitance()
if shutil.copy2(self.get_full_path(), full_destination) != full_destination:
raise NameError
if not filecmp.cmp(self.get_full_path(), full_destination, shallow=False):
raise FileNotFoundError
return
except:
INTERRUPT("file_copy")
while 1:
if not os.path.exists(destination):
INTERRUPT("folder_missing")
continue
if os.path.exists(full_destination):
try:
os.remove(full_destination)
if not os.path.exists(full_destination):
return
print("WARNING: File could not be deleted")
except:
INTERRUPT("file_deletion")
class FOLDER:
IMAGES_PATH = "Images/"
VIDEOS_PATH = "Videos/"
def __init__(self, path, name=None):
path = path.replace("\\", "/")
self.path = ""
if name:
self.path = path.rstrip()
if self.path[-1] != "/":
self.path += "/"
self.name = name
else:
parts = path.split("/")
self.name = parts.pop()
for part in parts:
self.path += part + "/"
self.date = DATE(0, 0, 0, from_file=self.name, folder=True)
def get_full_path(self):
return self.path + self.name + "/"
def create(self):
while 1:
try:
if not os.path.exists(self.get_full_path()):
os.mkdir(self.get_full_path())
if not os.path.exists(self.get_full_path()):
raise FileNotFoundError
if not os.path.exists(self.get_full_path() + self.IMAGES_PATH):
os.mkdir(self.get_full_path() + self.IMAGES_PATH)
if not os.path.exists(self.get_full_path() + self.IMAGES_PATH):
raise FileNotFoundError
if not os.path.exists(self.get_full_path() + self.VIDEOS_PATH):
os.mkdir(self.get_full_path() + self.VIDEOS_PATH)
if not os.path.exists(self.get_full_path() + self.VIDEOS_PATH):
raise FileNotFoundError
return
except:
INTERRUPT("folder_creation")
def copy_file(self, file):
full_path = self.get_full_path()
if file.type == IMAGE:
full_path += self.IMAGES_PATH
else:
full_path += self.VIDEOS_PATH
file.copy(full_path)
def does_exist(self, file):
full_path = self.get_full_path()
if file.type == IMAGE:
full_path += self.IMAGES_PATH
else:
full_path += self.VIDEOS_PATH
while 1:
if os.path.exists(self.get_full_path()):
break
else:
INTERRUPT("folder_missing")
return os.path.exists(full_path + file.name + "." + file.ending)
def __eq__(self, other):
return self.get_full_path() == other.get_full_path()
class SOURCE:
def __init__(self, type):
self.active = False
self.path = None
self.type = type
self.files = []
self.searching = True
self.search_thread = threading.Thread(target=self.search_path)
self.search_thread.daemon = True
self.search_thread.start()
def search_path(self):
while self.searching:
available_drives = [drive + ":/" for drive in string.ascii_uppercase if os.path.exists(drive + ":")]
for drive in available_drives:
if os.path.exists(drive + IDENT_FILE):
with open(drive + IDENT_FILE, "r") as info:
lines = info.readlines()
print(lines)
if len(lines) < 2:
print("WARNING: invalid config file")
continue
if lines[0].rstrip() == self.type:
self.path = drive + lines[1].rstrip()
self.search_files()
self.active = True
print(self.type, "found")
return True
time.sleep(1)
def search_files(self):
for folder in os.listdir(self.path):
if "media" in folder.lower():
sub_path = self.path + folder + "/"
for file_name in os.listdir(sub_path):
self.check_existance()
file = FILE(sub_path, name=file_name, should_exist=True)
if file.type:
self.files.append(file)
def get_dates(self):
all_dates = set()
for file in self.files:
all_dates.add(file.date)
return all_dates
def stop_searching(self):
self.searching = False
def check_existance(self):
while 1:
if os.path.exists(self.path):
return True
else:
INTERRUPT(self.type+"_missing")
class DESTINATION:
def __init__(self):
self.path = None
self.folders = []
self.active = False
self.search_thread = threading.Thread(target=self.search_path)
self.search_thread.daemon = True
self.search_thread.start()
def search_path(self):
while 1:
available_drives = [drive + ":/" for drive in string.ascii_uppercase if os.path.exists(drive + ":")]
for drive in available_drives:
if os.path.exists(drive + IDENT_FILE):
with open(drive + IDENT_FILE, "r") as info:
lines = info.readlines()
print(lines)
if len(lines) < 2:
print("WARNING: invalid config file")
continue
if lines[0].rstrip() == STORAGE:
self.path = drive + lines[1].rstrip()
self.search_folders()
self.active = True
print("dest found")
return True
time.sleep(1)
def search_folders(self):
self.check_existance()
for folder_name in os.listdir(self.path):
try:
folder = FOLDER(self.path, name=folder_name)
self.folders.append(folder)
except:
print("Invalid Folder: " + folder_name)
def get_dates(self):
all_dates = set()
for folder in self.folders:
all_dates.add(folder.date)
return all_dates
def check_existance(self):
while 1:
if os.path.exists(self.path):
return True
else:
INTERRUPT(STORAGE+"_missing")
def create_folders(self, dates):
self.check_existance()
for date in dates:
self.check_existance()
new_folder = FOLDER(self.path, name=date.to_string())
new_folder.create()
self.folders.append(new_folder)
def copy_file(self, file):
for folder in self.folders:
if folder.date == file.date:
folder.copy_file(file)
return True
print("WARNING: Date not Found")
def does_exist(self, file):
for folder in self.folders:
if folder.date == file.date:
return folder.does_exist(file)
print("WARNING: Date not Found")
return False
class CONTROL:
def __init__(self):
self.source_internal = SOURCE(INTERNAL)
self.source_external = SOURCE(EXTERNAL)
self.destination = DESTINATION()
def start_transfer(self):
if not (self.source_external.active or self.source_internal.active) or not self.destination.active:
print("System not ready yet!")
return False
self.source_external.stop_searching()
self.source_internal.stop_searching()
to_create_dates = self.source_internal.get_dates()
to_create_dates = to_create_dates.union(self.source_external.get_dates())
to_create_dates.difference(self.destination.get_dates())
self.destination.create_folders(to_create_dates)
all_files = self.source_internal.files + self.source_external.files
to_copy = [file for file in all_files if not self.destination.does_exist(file)]
all_space = sum([file.get_size() for file in to_copy])
print("Copying " + str(all_space) + " Byte in " + str(len(to_copy)) + " Files")
for file in to_copy:
print(" Copying " + file.name + " ...")
self.destination.copy_file(file)
print("Finished!")
return True
def test(cause):
input(">>>")
c = CONTROL()
while 1:
time.sleep(1)
input()
if c.start_transfer():
break
|
[
"[email protected]"
] | |
3412bc422fb6235564f0b57b12435dcbc6b538bf
|
eb9c3dac0dca0ecd184df14b1fda62e61cc8c7d7
|
/google/cloud/kms/v1/kms-v1-py/google/cloud/kms_v1/services/key_management_service/__init__.py
|
728218e181e680e1d75ce85d1b9e2142874feb86
|
[
"Apache-2.0"
] |
permissive
|
Tryweirder/googleapis-gen
|
2e5daf46574c3af3d448f1177eaebe809100c346
|
45d8e9377379f9d1d4e166e80415a8c1737f284d
|
refs/heads/master
| 2023-04-05T06:30:04.726589 | 2021-04-13T23:35:20 | 2021-04-13T23:35:20 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 795 |
py
|
# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# 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 .client import KeyManagementServiceClient
from .async_client import KeyManagementServiceAsyncClient
__all__ = (
'KeyManagementServiceClient',
'KeyManagementServiceAsyncClient',
)
|
[
"bazel-bot-development[bot]@users.noreply.github.com"
] |
bazel-bot-development[bot]@users.noreply.github.com
|
dd6f5f85aed5431dcc5d6f54a167b1a3ad008d74
|
07daef15cc1cfe45712811c83a771a044dd03ebf
|
/myvenv/Scripts/django-admin.py
|
98020e79406622606dcd802efa3e5ce85fc40b4c
|
[] |
no_license
|
rkdtmddnjs97/kmu_likelion_lesson_8th
|
c29024ccac54f623cd6cbf7ee3921ded54204eb5
|
e9b2992b233c1d8a2e00f33d6716a6042ac49a19
|
refs/heads/master
| 2022-06-20T05:56:33.998526 | 2020-05-14T06:37:55 | 2020-05-14T06:37:55 | 263,804,501 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 173 |
py
|
#!c:\users\rkdtm\desktop\kmu_likelion8th\myvenv\scripts\python.exe
from django.core import management
if __name__ == "__main__":
management.execute_from_command_line()
|
[
"[email protected]"
] | |
0485afd33fb758d0685dc00ab7dc02c61a7c1dfe
|
b36eace4a335f2518988f5929ffdba6e48c9e97e
|
/posts/admin.py
|
73419fc31cbfc465253fb736228f37c88e9a522a
|
[] |
no_license
|
berkyaglioglu/Post-Sharing-Application
|
d3c4187a8b05cf34c65fee5cc90ab6b85740e754
|
c169af6d27dd55ea711207e3e4b04cc61e678dca
|
refs/heads/master
| 2020-06-22T22:42:56.720956 | 2019-08-01T08:40:04 | 2019-08-01T08:40:04 | 198,419,497 | 0 | 0 | null | 2019-08-01T08:40:06 | 2019-07-23T11:46:57 |
Python
|
UTF-8
|
Python
| false | false | 145 |
py
|
from django.contrib import admin
import django
from .models import Post, Ingredients
admin.site.register(Post)
admin.site.register(Ingredients)
|
[
"[email protected]"
] | |
6b47716cb6f55c7cc6a34a6b37043fb59aaa4fbb
|
6254584a5febbfcd6babed94ed05c1de4e7c80bd
|
/genCSS.py
|
3c72901514003dc76c716c171c1a975a71bbf32f
|
[] |
no_license
|
pathumego/font-process-animator
|
81304b975d0aebaf5389a3ef8bf3a0c942d341c5
|
88e23f9986b71831710452b7f3f7f3bd3b550049
|
refs/heads/master
| 2021-01-22T19:31:16.485961 | 2016-11-29T12:14:43 | 2016-11-29T12:14:43 | 40,301,812 | 2 | 1 | null | 2016-11-29T12:14:43 | 2015-08-06T11:41:37 | null |
UTF-8
|
Python
| false | false | 739 |
py
|
import os
def getFileListToArray():
elements = ( os.listdir('fonts/') )
for element in elements:
if element.endswith( '.css' ) or element.endswith( 'Log' ):
elements.remove( element )
elements.sort()
return elements
def writeToFile( fontName, fontFormat ):
CSSFile = open( 'fonts/fonts.css', 'ab+' )
elements = getFileListToArray()
for i in elements:
CSSFile.write( bytes( "@font-face {\n", 'UTF-8' ) )
CSSFile.write( bytes( ' font-family:\'' + i[ :-4 ] + "\';\n", 'UTF-8' ) )
CSSFile.write( bytes( ' src:url(\"' + fontName + "\") format(\'" + fontFormat + "\');\n", 'UTF-8' ) )
CSSFile.write( bytes( '}\n\n', 'UTF-8' ) )
CSSFile.close()
|
[
"[email protected]"
] | |
e3857d5d953a43b0d3e5f393152b820ac12e7d3b
|
5d5561589dd5a8c7e0e6fa31a484238cc903d1f7
|
/ProgressiveLoader/cetate_img.py
|
94bb81034e4dcb9e1bd9e762651673ed5ea4b23b
|
[] |
no_license
|
peixin/cn2tw
|
fccda2aa2ed95aae9a038a565f4bc99243e23674
|
6178f9cf1cbdc2de08e9ec575c35735c177b1ae3
|
refs/heads/master
| 2021-05-29T11:58:18.688251 | 2015-04-17T07:35:11 | 2015-04-17T07:35:11 | 33,116,958 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 586 |
py
|
# coding=utf-8
from PIL import Image
from PIL import ImageFile
from exceptions import IOError
def main():
img = Image.open('2.jpg')
destination = '2_py_progressive.jpeg'
try:
img.save(destination, "JPEG", quality=80, optimize=True, progressive=True)
except IOError, e:
print(e)
ImageFile.MAXBLOKC = img.size[0] * mig.zise[1]
img.save(destination, "JPEG", quality=80, optimize=True, progressive=True)
if __name__ == '__main__':
# main()
a = 4333837
print(hex(4333837), hex(1097372565632), hex(4286611584))
|
[
"[email protected]"
] | |
b86af03b4a3d06e33a2362c0b892d0b0423a6674
|
a27226dc758b2922ee2068aec4134237b821eb5e
|
/Blogger/Blog/migrations/0005_likecomment_date.py
|
a63a2e173a735e954e4df96cf92fb016576c144f
|
[] |
no_license
|
trilok002/myBlogger
|
56a0d3eaa627777b0ceb2c3842e174a7da56c2e2
|
6cbfd70f506318e35e3b99e28dededd64fd4cc9a
|
refs/heads/master
| 2023-01-09T04:42:30.465036 | 2020-11-12T10:21:27 | 2020-11-12T10:21:27 | 311,295,994 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 378 |
py
|
# Generated by Django 3.0 on 2020-01-10 11:10
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Blog', '0004_auto_20200110_1550'),
]
operations = [
migrations.AddField(
model_name='likecomment',
name='date',
field=models.DateField(null=True),
),
]
|
[
"[email protected]"
] | |
86e0e080f61ad0e8524181b4748ad09937bf617f
|
1fa9ca9ab5bd0121fa557893ae937a2cf312e564
|
/ch2/ch2_lexresources.py
|
fb42b4c068c16227a2c6c757b5a01d822b4140b9
|
[] |
no_license
|
alexbumpers/NLTK_Practice
|
b3c02f16fcfe0a2e40e7febaf4560c47f86b1f0d
|
4051ad5da02b2173c73b2d3fb771d717cdd6e366
|
refs/heads/master
| 2020-04-12T09:44:31.952080 | 2017-01-11T15:33:08 | 2017-01-11T15:33:08 | 65,736,554 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 4,690 |
py
|
import nltk
from nltk.corpus import gutenberg
#gutenberg.fileids()
#def unusual_words(text):
#text_vocab = set(w.lower() for w in text if w.isalpha())
#english_vocab = set(w.lower() for w in nltk.corpus.words.words())
## .difference() returns new set with elements in x but not y
## in this example, text_vocab = x ; english_vocab = y
#unusual = text_vocab.difference(english_vocab)
#return sorted(unusual)
#print unusual_words(nltk.corpus.gutenberg.words('austen-sense.txt'))
#print unusual_words(nltk.corpus.nps_chat.words())
## -------- stopwords --------
## stopwords are high frequency words like the, to, and, also, etc.
#from nltk.corpus import stopwords
#from nltk.corpus import gutenberg
#gutenberg.fileids()
#print stopwords.words('english')
##just returns 0 for some reason
#def content_fraction(text):
#stopwords = nltk.corpus.stopwords.words('english')
#content = [w for w in text if w.lower() not in stopwords]
#return len(content) / len(text)
#print content_fraction(nltk.corpus.gutenberg.words('austen-sense.txt'))
##same as line 26
#def content_fraction(text):
#stopwords = nltk.corpus.stopwords.words('english')
#content = [w for w in text if w.lower() not in stopwords]
#return len(content) / len(text)
#print int(content_fraction(nltk.corpus.reuters.words()))
## -------- SEE 2-6 ON PAGE 61 -------
##letters in the puzzle. They must all be used once per word.
##each word must contain 'r' and there must be at least one 9 letter word
##no plurals ending in 's', no foreign words, no proper names.
#puzzle_letters = nltk.FreqDist('egivrvonl')
#obligatory = 'r'
#wordlist = nltk.corpus.words.words()
#puzzle_solution = [w for w in wordlist if len(w) >= 4
#and obligatory in w
#and nltk.FreqDist(w) <= puzzle_letters]
#print puzzle_solution
# ----- names by gender -----
#import nltk
#from nltk.corpus import names
#print names.fileids()
#male_names = names.words('male.txt')
#female_names = names.words('female.txt')
#print [w for w in male_names if w in female_names]
##returns last letter of names by sex in c_freqdist, then plots it
#cfd = nltk.ConditionalFreqDist(
#(fileid, name[-1])
#for fileid in names.fileids()
#for name in names.words(fileid)
#)
#print cfd.plot()
## ----- CMU Pronouncing Dictionary -----
import nltk
from nltk.corpus import cmudict
entries = nltk.corpus.cmudict.entries()
print len(entries)
for entry in entries[39943:39951]:
print entry
##scans lexicon looking for entires who pronunciation consists of 3 phones
##if true, assigns contents of pron to 3 variables: ph1, ph2, ph3
for word, pron in entries:
if len(pron) == 3:
ph1, ph2, ph3 = pron
if ph1 == 'P' and ph3 == 'T':
print word, ph2
##for loop that returns/prints all words ending with -nicks pronunciation
syllable = ['N', 'IH0', 'K', 'S']
print [word for word, pron in entries if pron[-4:] == syllable]
## For loop that returns words ending with 'mn' pronunciation, where 'M'
## is pronounced with a silent n
print [w for w, pron in entries if pron[-1] == 'M' and w[-1] == 'n']
## Print beginning of words where 'N' is pronounced and the letter preceding
## it is silent (e.g.: knob, pneumonia, knife)
print sorted(set(w[:2] for w, pron in entries if pron[0] == 'N' and
w[0] != 'n'))
## Phones contain digits to represent primary stress (1), secondary stress (2),
## no stress (0).
## Function below defines function to extract stress digits and then scan
## lexicon to find words w/ particular stress pattern.
def stress(pron):
return [char for phone in pron for char in phone if char.isdigit()]
print [w for w, pron in entries if stress(pron) == ['0', '1', '2', '0']]
print [w for w, pron in entries if stress(pron) == ['0', '2', '0', '1', '0']]
## Finds all 'p' word consisting of three sounds, groups them according to
## their first and last sounds.
##p words with 3 sounds
p3 = [(pron[0] + '-' + pron[2], word)
for (word, pron) in entries
if pron[0] == 'P' and len(pron) == 3]
## ConditionalFreqDist of p3
cfd = nltk.ConditionalFreqDist(p3)
##
for template in cfd.conditions():
if len(cfd[template]) > 10:
words = cfd[template].keys()
wordlist = ' '.join(words)
print template, wordlist[:70] + "..."
prondict = nltk.corpus.cmudict.dict()
print prondict['fire']
##'blog' doesn't exist in cmudict.dict(), gives KeyError
#print prondict['blog']
##assigns pron to 'blog' in this script
prondict['blog'] = ['B', 'L', 'AA1', 'G']
print prondict['blog']
text = ['natural', 'language', 'processing']
print [ph for w in text for ph in prondict[w][0]]
|
[
"[email protected]"
] | |
4671c52d67a2c52405795ec4df4cacd024ba19c0
|
e67a3db1aef6c62eb9d419da74b37ea0b2ba8029
|
/hkyoon/love_liverpool.py
|
ce49ca23204239429e75989b4e976880415b9b3f
|
[] |
no_license
|
lilyyoon/hkyoon
|
1ad28f5e5226aee29572a5bf5c976ea7147479a2
|
6d1f38869a3c606e06966e59537eda0a17f4a386
|
refs/heads/master
| 2020-06-02T00:54:44.441211 | 2019-06-09T09:44:54 | 2019-06-09T09:44:54 | 190,985,146 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 14 |
py
|
YNWA liverpool
|
[
"[email protected]"
] | |
0dcb4282491a5b8542b9f778ff9f79a24647d434
|
269f2b3b418083c3c15e84a118d5cb55bc13fc71
|
/pythonexercicios/ex037 comversor de bases numericas.py
|
88fea769b749da32dfca0669f3dd5839c942eafe
|
[] |
no_license
|
LindomarB/Curso-em-video-python-git
|
0e38d40e091fe64fb590d16779162759f6d402dd
|
0d5f7c7eb9eed06b8495ea435f27e6623ea89354
|
refs/heads/master
| 2022-12-25T04:28:39.580278 | 2018-05-29T14:32:54 | 2018-05-29T14:32:54 | 135,308,766 | 0 | 1 | null | 2022-12-11T19:12:49 | 2018-05-29T14:30:49 |
Python
|
UTF-8
|
Python
| false | false | 374 |
py
|
#escreva um programa que leia um numero inteiro qualque
#e peรงa para o usuario escolher qual sera a base de conversao
#1 para binario
#2 para octal
#3 para hexadecimal
n = int(input('digite um numero: '))
r = int(input("""1 = binario
2 = hexadecimal
3 = octal
""" ))
if r == 1:
print(bin(n)[2:])
elif r == 2:
print(hex(n)[2:])
elif r == 3:
print(oct(n)[2:])
|
[
"[email protected]"
] | |
f03cbd0776557b97bca758eac8ddf48281a65fe1
|
aa55945714117a0a25b45a7ed110a9d42b4e9d47
|
/UserStore.py
|
811ad60cfd787a3f329f6fd102a7186c1ed27333
|
[] |
no_license
|
EnotionZ/FoodListing
|
941ef02b648cce181e8d02dce5ab00ead60c0d9a
|
8c502674cca4e3f611cef980d103548a4f116583
|
refs/heads/master
| 2021-01-04T14:06:37.375130 | 2012-03-09T01:25:21 | 2012-03-09T01:25:21 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,196 |
py
|
"""
UserInfo.py -- Grabs user info from the database.
by Sean.
"""
from Config import Config
from pymongo import Connection
from datetime import datetime
import time
from hashlib import sha256
from base64 import b64encode
import logging
class UserStore:
def __init__( self, config ):
self.config = Config( config )
self.address = self.config['mongo']['address']
self.port = self.config['mongo']['port']
self.database = "foodlisting"
self.logger = logging.getLogger( "FoodListing.DB.UserInfo" )
try:
self.database = self.config['mongo']['database']
except:
pass
self.collection = "users"
self.con = Connection( self.address, self.port )
self.db = self.con[self.database]
self.collection = self.db[self.collection]
self.food = self.db['food']
#self.collection.ensure_index( "id", unique=True )
"""
PRE: uid = fb, google, other id
name = user's real name gathered from their account
upon registration.
age = user's real age gathered from their account
upon registration.
loc = 2-tuple that contains their approximate lat/lng.
this can be gotten from facebook/google or guess
from their registration ip.
POST: The user with the above information is added,
and the object is returned from the function to be used
else where.
"""
def addUser( self, id, idType, name, password, age, zip, loc ):
user = {}
user['uid'] = id #user id
user['idType'] = idType#id type, facebook, google, ect...
user['food_history'] = [] #all food ordered by this person
user['name'] = name #name of the user
user['pass'] = b64encode( sha256( password ).digest() )
user['age'] = age #age of the person
user['location'] = loc #location
user['zip'] = zip #zip code
if self.collection.save( user ) != None:
return user['uid']
else:
return None
"""
PRE: id = the users id
POST: The RV is the user document or None if it does not exist.
"""
def getByID( self, id ):
user = self.collection.find_one( { "uid": id } )
user['_id'] = str( user['_id'] )
history = user['food_history']
food = []
for h in history:
h['date'] = str( h['date'] )
f = self.food.find_one( { "_id": h['fid'] } )
if not f == None:
try:
f['_id'] = str( f['_id'] )
f['date'] = str( f['date'] )
food.append( f )
except:
print f
user['food_history'] = food
return user
"""
PRE: username and password are defined.
POST: The RV is not none if the user and password combination work.
"""
def checkUser( self, username, password ):
p = b64encode( sha256( password ).digest() )
return self.collection.find_one( { "name": username, "pass": p } )
def addFood( self, id, fid ):
food = { "fid": fid, "date": datetime.now() }
return self.collection.update( { "uid": id }, { "$push": { "food_history": food } } )
if __name__ == "__main__":
u = UserStore( "config.json" )
a = u.addUser( "12345543215", "facebook", "Megan", "password", 21, 20151, ( 73.1, 73.1 ) )
a = u.getByID( a )
print a
|
[
"[email protected]"
] | |
069cfe8f788574fd861f98725e5d9cc0701879d0
|
11395aa469ecd56ea73efaf6f35128f17c42d5f4
|
/api/database.py
|
538550442a4474bc97bbb19062ccc487d35b6134
|
[] |
no_license
|
kottas/http-rest-demo
|
4d7f2bd395259f645781e9ff5a3c3cd1f1aa686a
|
13fdd391ab69f061767949fef89254754afa59b4
|
refs/heads/master
| 2023-03-09T06:56:11.050061 | 2021-02-14T21:16:09 | 2021-02-14T21:16:09 | 338,868,090 | 2 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,277 |
py
|
from elasticsearch import Elasticsearch, NotFoundError, RequestError, ElasticsearchException
from elasticsearch.client.indices import IndicesClient
from typing import List, Tuple
from .schemas import Document, DocumentIndex, DocumentText, SearchResult
INDEX = "en_documents"
async def document_add(elasticsearch: Elasticsearch, document: Document) -> DocumentIndex:
response = elasticsearch.index(index=INDEX, body=document.dict())
return DocumentIndex(index=response.get("_id", ""))
async def document_retrieve(elasticsearch: Elasticsearch, index: str) -> DocumentText:
response = elasticsearch.get(index=INDEX, id=index)
source = response.get("_source", {})
return DocumentText(text=source.get("text", ""))
async def document_search(
elasticsearch: Elasticsearch, vector: List[float], top_k: int
) -> List[SearchResult]:
response = elasticsearch.search(
index=INDEX,
body={
"size": top_k,
"query": {
"script_score": {
"query": {"match_all": {}},
"script": {
"source": "cosineSimilarity(params.queryVector, 'vector') + 1.0",
"params": {"queryVector": vector},
},
}
},
},
)
return [
SearchResult(index=hit["_id"], text=hit["_source"]["text"], score=hit["_score"])
for hit in response["hits"]["hits"]
]
def initialize_elastic_search() -> Tuple[Elasticsearch, IndicesClient]:
elastic_search = Elasticsearch(hosts=[{"host": "localhost", "port": 9200}])
indices_client = IndicesClient(client=elastic_search)
try:
indices_client.create(
index=INDEX,
body={
"mappings": {
"properties": {
"doc": {"type": "text"},
"vector": {"type": "dense_vector", "dims": 768},
}
}
},
)
except RequestError:
pass
return elastic_search, indices_client
async def shutdown_elastic_search(
elastic_search: Elasticsearch, indices_client: IndicesClient
) -> None:
indices_client.delete(index=INDEX)
elastic_search.close()
|
[
"[email protected]"
] | |
fc7afe7c321e18b93ea2aaee4b690db7ab2f9a6d
|
689d19292c4858f7cd30402d0eaf38405fb21ff5
|
/venv/bin/pyrsa-decrypt
|
29859a31e55c24b69991089eb158b9b9a467360b
|
[] |
no_license
|
akhilraj95/CollgeDatabase
|
205f8cf9843f70477d11d9ee4a66fbc34c5ae625
|
2d615ed3bdf81b514f1d66d9721ef6cb78f47a08
|
refs/heads/master
| 2021-01-12T16:41:03.224118 | 2017-02-12T16:20:52 | 2017-02-12T16:20:52 | 71,425,194 | 0 | 1 | null | null | null | null |
UTF-8
|
Python
| false | false | 250 |
#!/home/akhil/work/CJ/CollgeDatabase/venv/bin/python
# -*- coding: utf-8 -*-
import re
import sys
from rsa.cli import decrypt
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(decrypt())
|
[
"[email protected]"
] | ||
fdc2c39b4c6702662ee0e0425034c1cdbe6f6504
|
a4dbdd63a6b9693b35d028f1c474afec04a57c77
|
/yeonkyung/์ง์ง์ด ์ ๊ฑฐํ๊ธฐ.py
|
d392e86a26595e8346a56c2ac0982ee89ecdb156
|
[] |
no_license
|
yeonkyungJoo/algorithm_study
|
1aead72dad7badb1a7ef52e3fe1eff75feaf578a
|
f205e5c97202783c246e7dc28f2338da065e9b82
|
refs/heads/main
| 2023-06-09T03:57:11.055310 | 2021-07-04T01:53:50 | 2021-07-04T01:53:50 | 347,650,540 | 0 | 5 | null | 2021-06-24T21:51:19 | 2021-03-14T13:54:02 |
Python
|
UTF-8
|
Python
| false | false | 279 |
py
|
def solution(s):
stack = []
for ch in s:
if stack and stack[-1] == ch:
stack.pop()
else:
stack.append(ch)
if stack:
return 0
else:
return 1
if __name__ == "__main__":
s = "cdcd"
print(solution(s))
|
[
"[email protected]"
] | |
23603c3747093f0f01f514546c24ce3bad2ff880
|
fe6f6d11dde2a3205ae9758c7d4eb1f824b84102
|
/venv/lib/python2.7/site-packages/logilab/common/test/unittest_ureports_html.py
|
c849c4f82d85d7321cc94b30f3be83ecd578cec2
|
[
"MIT"
] |
permissive
|
mutaihillary/mycalculator
|
ebf12a5ac90cb97c268b05606c675d64e7ccf8a6
|
55685dd7c968861f18ae0701129f5af2bc682d67
|
refs/heads/master
| 2023-01-10T14:56:11.780045 | 2016-09-20T12:30:21 | 2016-09-20T12:30:21 | 68,580,251 | 0 | 0 |
MIT
| 2022-12-26T20:15:21 | 2016-09-19T07:27:48 |
Python
|
UTF-8
|
Python
| false | false | 2,918 |
py
|
# copyright 2003-2011 LOGILAB S.A. (Paris, FRANCE), all rights reserved.
# contact http://www.logilab.fr/ -- mailto:[email protected]
#
# This file is part of logilab-common.
#
# logilab-common is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the Free
# Software Foundation, either version 2.1 of the License, or (at your option) any
# later version.
#
# logilab-common is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
# details.
#
# You should have received a copy of the GNU Lesser General Public License along
# with logilab-common. If not, see <http://www.gnu.org/licenses/>.
'''unit tests for ureports.html_writer
'''
__revision__ = "$Id: unittest_ureports_html.py,v 1.3 2005-05-27 12:27:08 syt Exp $"
from utils import WriterTC
from logilab.common.testlib import TestCase, unittest_main
from logilab.common.ureports.html_writer import *
class HTMLWriterTC(TestCase, WriterTC):
def setUp(self):
self.writer = HTMLWriter(1)
# Section tests ###########################################################
section_base = '''<div>
<h1>Section title</h1>
<p>Section\'s description.
Blabla bla</p></div>
'''
section_nested = '''<div>\n<h1>Section title</h1>\n<p>Section\'s description.\nBlabla bla</p><div>\n<h2>Subsection</h2>\n<p>Sub section description</p></div>\n</div>\n'''
# List tests ##############################################################
list_base = '''<ul>\n<li>item1</li>\n<li>item2</li>\n<li>item3</li>\n<li>item4</li>\n</ul>\n'''
nested_list = '''<ul>
<li><p>blabla<ul>
<li>1</li>
<li>2</li>
<li>3</li>
</ul>
</p></li>
<li>an other point</li>
</ul>
'''
# Table tests #############################################################
table_base = '''<table>\n<tr class="odd">\n<td>head1</td>\n<td>head2</td>\n</tr>\n<tr class="even">\n<td>cell1</td>\n<td>cell2</td>\n</tr>\n</table>\n'''
field_table = '''<table class="field" id="mytable">\n<tr class="odd">\n<td>f1</td>\n<td>v1</td>\n</tr>\n<tr class="even">\n<td>f22</td>\n<td>v22</td>\n</tr>\n<tr class="odd">\n<td>f333</td>\n<td>v333</td>\n</tr>\n</table>\n'''
advanced_table = '''<table class="whatever" id="mytable">\n<tr class="header">\n<th>field</th>\n<th>value</th>\n</tr>\n<tr class="even">\n<td>f1</td>\n<td>v1</td>\n</tr>\n<tr class="odd">\n<td>f22</td>\n<td>v22</td>\n</tr>\n<tr class="even">\n<td>f333</td>\n<td>v333</td>\n</tr>\n<tr class="odd">\n<td> <a href="http://www.perdu.com">toi perdu ?</a></td>\n<td> </td>\n</tr>\n</table>\n'''
# VerbatimText tests ######################################################
verbatim_base = '''<pre>blablabla</pre>'''
if __name__ == '__main__':
unittest_main()
|
[
"[email protected]"
] | |
de3e7c7a99d56bbcd47d532b61dd9abdb705c05a
|
e3365bc8fa7da2753c248c2b8a5c5e16aef84d9f
|
/indices/nncuthbert.py
|
68a51f0d1e582e2bf577eed1be5fba6c8208bebd
|
[] |
no_license
|
psdh/WhatsintheVector
|
e8aabacc054a88b4cb25303548980af9a10c12a8
|
a24168d068d9c69dc7a0fd13f606c080ae82e2a6
|
refs/heads/master
| 2021-01-25T10:34:22.651619 | 2015-09-23T11:54:06 | 2015-09-23T11:54:06 | 42,749,205 | 2 | 3 | null | 2015-09-23T11:54:07 | 2015-09-18T22:06:38 |
Python
|
UTF-8
|
Python
| false | false | 139 |
py
|
ii = [('PettTHE.py', 1), ('ClarGE2.py', 2), ('BuckWGM.py', 2), ('DibdTRL2.py', 1), ('WadeJEB.py', 1), ('MartHRW.py', 1), ('BrewDTO.py', 1)]
|
[
"[email protected]"
] | |
daac803ef97a17ffd00461cc522a1b737afc3636
|
dfaaaedf0c466ccde145873befbb16cf29fee106
|
/pyentrypoint/constants.py
|
132393f8c8f2c9b94e90b63ee3733eb65974ed2a
|
[] |
no_license
|
cmehay/pyentrypoint
|
8e27c91522f875541aa4be4650f7ab4f2c7b690b
|
d552129309eeb75c4bb93b7c580bd727ad7beccb
|
refs/heads/master
| 2023-02-20T06:13:19.751500 | 2022-07-24T17:13:21 | 2022-07-24T17:13:21 | 52,220,352 | 15 | 3 | null | 2023-02-08T03:46:34 | 2016-02-21T18:14:38 |
Python
|
UTF-8
|
Python
| false | false | 44 |
py
|
ENTRYPOINT_FILE = 'entrypoint-config.yml'
|
[
"[email protected]"
] | |
abf5f26c55cbaee20359ab26aed91e4d87724511
|
bd8c661d0e3e3adebfecfdfbe55ce7b97a8b4fdb
|
/src/L0_xtc31/train_model.py
|
94b8b3cdafab3b307a8ddaa3733ca489ed4adc4f
|
[
"MIT"
] |
permissive
|
jimthompson5802/kaggle-BNP-Paribas
|
ea2d8625c0876e517b16914daa9fa36db7aedf63
|
536bcd0b1fe4cb3e1bfd55ee34e9027732cc7d5b
|
refs/heads/master
| 2021-03-08T19:34:09.855388 | 2016-05-10T02:56:06 | 2016-05-10T02:56:06 | 56,448,955 | 13 | 7 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,554 |
py
|
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 2 22:16:47 2016
@author: jim
"""
# py_train.tsv: training data set
import sys
import pickle
import zlib
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import ExtraTreesClassifier
from sklearn import ensemble
# model data stricture
# parameters gleaned from R script submission: ExtraTreesClassifier (score 0.45911)
mdl_fit = ExtraTreesClassifier(n_estimators=850,max_features= 60,
criterion = 'entropy',min_samples_split= 4,
max_depth= 40, min_samples_leaf= 2, n_jobs=7)
if __name__ == "__main__":
print "Starting training"
# retrieve work directory
work_dir = sys.argv[1]
# work_dir = "../../src/L0_xtc1"
# generate training data set file name
training_file = work_dir + "/py_train.tsv"
print training_file
# read training data
train = pd.read_csv(training_file,sep="\t")
# isoloate response variable
response = [1 if x == 'Class_1' else 0 for x in train["response"]]
# isolate predictors
predictors = train.columns[1:len(train.columns)].values
X_train = train[predictors]
# fit model
mdl_fit.fit(X_train,response)
# save fitted model structure
model_dict = {'model':mdl_fit}
model_file = work_dir + "/possible_model"
with open(model_file,"wb") as f:
pickle.dump(model_dict,f)
print "Saved " + model_file
|
[
"[email protected]"
] | |
a95baf7ce1fc8fcf328f10cda2007623bf9c70e5
|
8536fd114a5e3565c7e9958ca668f243eb678f2e
|
/tl_detection/generate_tfrecord.py
|
86100b9d1779b65ae4d8e551e151152ab7a8672f
|
[
"MIT"
] |
permissive
|
TeamDoernbach/SDCNanodegreeCapstone
|
e235bb7154d2bef7cf9bd8b0328b22e3d24484d8
|
10bdc59dc1b8f56136bf3f6f4ab64c97082420bb
|
refs/heads/master
| 2020-04-13T23:45:19.297948 | 2019-01-21T20:28:21 | 2019-01-21T20:28:21 | 163,514,891 | 4 | 4 |
MIT
| 2019-01-21T20:19:27 | 2018-12-29T13:52:26 |
Python
|
UTF-8
|
Python
| false | false | 3,580 |
py
|
"""
Usage:
# From tensorflow/models/
# Create train data:
python generate_tfrecord.py --csv_input=data/train_labels.csv --output_path=train.record
# Create test data:
python generate_tfrecord.py --csv_input=data/test_labels.csv --output_path=test.record
"""
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import os
import io
import pandas as pd
import tensorflow as tf
from PIL import Image
from object_detection.utils import dataset_util
from collections import namedtuple, OrderedDict
flags = tf.app.flags
flags.DEFINE_string('csv_input', '', 'Path to the CSV input')
flags.DEFINE_string('output_path', '', 'Path to output TFRecord')
flags.DEFINE_string('image_dir', '', 'Path to images')
FLAGS = flags.FLAGS
# TO-DO replace this with label map
def class_text_to_int(row_label):
if row_label == 'tl_red':
return 1
if row_label == 'tl_yellow':
return 2
if row_label == 'tl_green':
return 3
else:
None
def split(df, group):
data = namedtuple('data', ['filename', 'object'])
gb = df.groupby(group)
return [data(filename, gb.get_group(x)) for filename, x in zip(gb.groups.keys(), gb.groups)]
def create_tf_example(group, path):
with tf.gfile.GFile(os.path.join(path, '{}'.format(group.filename)), 'rb') as fid:
encoded_jpg = fid.read()
encoded_jpg_io = io.BytesIO(encoded_jpg)
image = Image.open(encoded_jpg_io)
width, height = image.size
filename = group.filename.encode('utf8')
image_format = b'jpg'
xmins = []
xmaxs = []
ymins = []
ymaxs = []
classes_text = []
classes = []
for index, row in group.object.iterrows():
xmins.append(row['xmin'] / width)
xmaxs.append(row['xmax'] / width)
ymins.append(row['ymin'] / height)
ymaxs.append(row['ymax'] / height)
classes_text.append(row['class'].encode('utf8'))
classes.append(class_text_to_int(row['class']))
tf_example = tf.train.Example(features=tf.train.Features(feature={
'image/height': dataset_util.int64_feature(height),
'image/width': dataset_util.int64_feature(width),
'image/filename': dataset_util.bytes_feature(filename),
'image/source_id': dataset_util.bytes_feature(filename),
'image/encoded': dataset_util.bytes_feature(encoded_jpg),
'image/format': dataset_util.bytes_feature(image_format),
'image/object/bbox/xmin': dataset_util.float_list_feature(xmins),
'image/object/bbox/xmax': dataset_util.float_list_feature(xmaxs),
'image/object/bbox/ymin': dataset_util.float_list_feature(ymins),
'image/object/bbox/ymax': dataset_util.float_list_feature(ymaxs),
'image/object/class/text': dataset_util.bytes_list_feature(classes_text),
'image/object/class/label': dataset_util.int64_list_feature(classes),
}))
return tf_example
def main(_):
writer = tf.python_io.TFRecordWriter(FLAGS.output_path)
path = os.path.join(FLAGS.image_dir)
examples = pd.read_csv(FLAGS.csv_input)
grouped = split(examples, 'filename')
for group in grouped:
tf_example = create_tf_example(group, path)
writer.write(tf_example.SerializeToString())
writer.close()
output_path = os.path.join(os.getcwd(), FLAGS.output_path)
print('Successfully created the TFRecords: {}'.format(output_path))
if __name__ == '__main__':
tf.app.run()
|
[
"[email protected]"
] | |
62ccbe5d8ee222ec7df51815f4784d75bac59406
|
284e1e7e79485586e0f347255bba01506fa9b8f3
|
/jacobi_fast_prox_nuc_norm.py
|
e15863d83ba562f83da2e02038d70c5d62f50fd7
|
[] |
no_license
|
Harry-MG/jacobi_approx_proximal
|
52340bbd57e6177ebcf0245941f22998f8c28462
|
df5996f2468405375ea7e550b030de63c1a94896
|
refs/heads/main
| 2023-05-02T21:12:04.571322 | 2021-05-26T12:26:56 | 2021-05-26T12:26:56 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,239 |
py
|
import numpy as np
import time
from cyclic_jacobi_sweeps import cyclic_jacobi_sweeps
from cyclic_jacobi_tol import cyclic_jacobi_tol
from prox_l1_norm import prox_l1_norm
def jacobi_fast_prox_nuc_norm(f, grad, max_iter, dimension, step_size, reltol, lambd, tol=None, num_sweeps=None):
if tol is not None and num_sweeps is not None:
raise Exception(
"Set only one of tol and num_sweeps. If using cyclic_jacobi_tol use tol. If using cyclic_jacobi_sweeps "
"use num_sweeps")
# Initialise
n = dimension
x = np.eye(n)
x_old = np.eye(n)
U = np.eye(n)
t = step_size
sweeps_list = np.zeros(max_iter)
times_list = np.zeros(max_iter)
rank_list = np.zeros(max_iter)
objective_value = np.zeros(max_iter)
start_main = time.time()
for k in range(2, max_iter + 2):
start = time.time()
x_old_old = x_old
x_old = x
beta = (k - 1) / (k + 2)
y = x_old + beta * (x_old - x_old_old)
z = y - t * grad(y)
if tol is not None:
D = cyclic_jacobi_tol(np.transpose(U) @ z @ U, tol).diagonal
J = cyclic_jacobi_tol(np.transpose(U) @ z @ U, tol).eigenvectors
nsweeps = cyclic_jacobi_tol(np.transpose(U) @ z @ U, tol).sweeps
sweeps_list[k] = nsweeps
else:
D = cyclic_jacobi_sweeps(np.transpose(U) @ z @ U, num_sweeps).diagonal
J = cyclic_jacobi_sweeps(np.transpose(U) @ z @ U, num_sweeps).eigenvectors
U = U @ J
prox = prox_l1_norm(np.abs(np.diag(D)), t*lambd)
Dplus = np.diag(prox)
x = U @ Dplus @ np.transpose(U)
end = time.time()
times_list[k] = end - start
rank_list[k] = np.linalg.matrix_rank(x)
objective_value[k] = f(x)
if np.abs(f(x) - f(x_old)) < reltol:
final_iter = k
break
end_main = time.time()
class outputs:
argmin = x
minimum = f(x)
objective_values = objective_value[:final_iter]
sweeps_per_iter = sweeps_list[:final_iter]
iter_times = times_list[:final_iter]
ranks = rank_list[:final_iter]
total_time = end_main - start_main
return outputs
|
[
"[email protected]"
] | |
6b00101db5a87305ec976c278a71af8819781aab
|
ed41ef435122ba229fc5dd1a94d0ec90e049ae31
|
/Nathaniel and Selina Plotting.py
|
7263b7ab04486dbfae592addf8e8bac5e582e4b2
|
[] |
no_license
|
lhaney/Intro-to-Python
|
81e632f03a188d14717ce7b5a09b236c58e16604
|
03e929296bdc0d4ab6e14a02badcab3d9580cc2f
|
refs/heads/master
| 2021-04-27T12:18:11.912594 | 2018-04-27T23:33:03 | 2018-04-27T23:33:03 | 122,578,443 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 791 |
py
|
'''
Made by Nathaniel and Selina
Writes points in a text file and plots them on a graph
3/22/18
'''
import matplotlib
from matplotlib import pyplot as plt
import numpy as np
#creates a file
filename=open('array.txt','w')
#writes a series of numbers into it
filename.write('3,9'+'\n')
filename.write('12,56'+'\n')
filename.write('47,74'+'\n')
filename.write('91,29'+'\n')
#closes the file
filename.close()
#reopens the file to read
filename=open('array.txt','r')
#defines lists
xlist=[]
ylist=[]
for line in filename:
#adds numbers to a list
xlist.append(float(line.split(',')[0]))
ylist.append(float(line.split(',')[1]))
#prints lists
print xlist
print ylist
#plots list
line=plt.plot(ylist,xlist)
#changes color to yellow)
plt.setp(line, 'color', 'y',)
#opens the plot
plt.show()
|
[
"[email protected]"
] | |
01aba594e0438ffdd0367eefacb37bc81bbda437
|
ff91e5f5815b97317f952038e19af5208ef12d84
|
/square2.py
|
98eb0412527458a11fcc5211790ef83d9f7ee25a
|
[] |
no_license
|
BryanPachas-lpsr/class-samples
|
c119c7c1280ca2a86f24230d85f6c712f18d9be8
|
a194201dce28299bd522295110814c045927ef5b
|
refs/heads/master
| 2021-01-17T07:03:42.968452 | 2016-06-12T22:35:54 | 2016-06-12T22:35:54 | 48,007,820 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 191 |
py
|
#square.py
import turtle
#make out turtle
buzz = turtle.Turtle()
#buzz makes a square
lines = 0
while lines < 4:
buzz.forward(150)
buzz.left(90)
lines = lines + 1
turtle.exitonclick()
|
[
"lps@lps-1011PX.(none)"
] |
lps@lps-1011PX.(none)
|
cd5f45fedd5a29f463733931bc43475a0785a354
|
b59f50886181367c35b0ae9a1525a4cc5e6bc930
|
/train.py
|
3bee12fa13a839bcfd4526d092af99fd1da19bff
|
[] |
no_license
|
hlfshell/deep_q_network
|
deaad2129d0b8488e698041a8c3dcc5a2fc9efb5
|
7b23b4b54a5ae1579d3aa4b87974a312bc2f2a2c
|
refs/heads/main
| 2023-03-02T01:48:06.337638 | 2021-02-03T06:03:44 | 2021-02-03T06:03:44 | 328,849,257 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 14,654 |
py
|
import torch
from torch import optim
from random import random, sample
import numpy as np
from collections import deque
import pickle
import copy
def train(
# Required inputs
model, environment, loss_function, optimizer_function,
# Standard settings
learning_rate=1e-4, episodes=5000, gamma=0.95, render=False, device=None,
# Epsilon greedy settings
epsilon=1, epsilon_minimum=0.05, epsilon_minimum_at_episode=None,
# Backpropagation settings
batch_size=64, backpropagate_every=1,
# Experience replay settings
experience_replay=True, experience_memory_size=10_00,
# Target network settings
target_network=True, sync_every_steps=500,
# Function controls
state_transform=None, on_episode_complete=None, modify_reward=None,
# Checkpoint settings
checkpoint_model=None, checkpoint_target_model=None, checkpoint_trainer=None,
save_every=None, save_to_folder="",
):
rewards = []
steps = []
# If the device is not set, determine if we are going
# to use GPU or CPU. If it is set, respect that setting
if device == None:
if torch.cuda.is_available():
device = "cuda"
else:
device = "cpu"
# Calculate the epsilon decay off of epsilon_minimum and
# epsilon_minimum_at_episode. If epsilon_minimum_at_episode
# is None, set it to the total episode count by default
if epsilon_minimum_at_episode is None:
epsilon_minimum_at_episode = episodes
# This math is derived on the idea that we want the
# decay, over epsilon_minimum_at_episode episodes
# to equal our epsilon minimum.
epsilon_decay = (epsilon_minimum / epsilon) ** (1/epsilon_minimum_at_episode)
# If needed, prep our experience replay buffer
if experience_replay:
experience_memory = deque(maxlen=experience_memory_size)
# If needed, prep our target network
if target_network:
target_model = copy.deepcopy(model)
target_model.load_state_dict(model.state_dict())
optimizer_steps = 0
# Prepare our optimizer
optimizer = optimizer_function(model.parameters(), lr=learning_rate)
# Start at episode 0
episode = 0
# If we have a checkpoint set, we will resume from that.
# So here we shall load up the checkpoint and
if checkpoint_model:
model.load(checkpoint_model)
if target_network:
target_model.load(checkpoint_target_model)
training_state = pickle.load(open(checkpoint_trainer, 'rb'))
rewards = training_state['rewards']
steps = training_state['steps']
episode = len(rewards)
optimizer_steps = training_state['optimizer_steps']
epsilon = training_state['epsilon']
experience_memory = training_state['experience_memory']
del training_state
for episode in range(episode, episodes):
state = environment.reset()
if state_transform:
state = state_transform(state)
else:
# Convert our state to pytorch - ensure it's float
state = torch.from_numpy(state).float()
if render:
environment.render()
done = False
step = 0
total_reward = 0
while not done:
step += 1
# Ensure that state is on the appropriate device
state = state.to(device)
# Get our Q values predictions for each action
Q = model(state.unsqueeze(dim=0))
if render:
environment.render()
# Convert to numpy for ease of use. If it's on GPU, we need to
# copy the tensor back to CPU
q_values = Q.cpu().data.numpy()
if random() < epsilon:
# Generate a random action from the action_space of the environment
action = environment.action_space.sample()
else:
# If we are not exploring, exploit the best predicted value
# argmax returns the index location of the higest value
action = np.argmax(q_values)
# Take our action and take a step
state2, reward, done, info = environment.step(action)
if modify_reward:
reward = modify_reward(reward)
total_reward += reward
if state_transform:
state2 = state_transform(state2)
else:
# Convert our state to pytorch - ensure it's float
state2 = torch.from_numpy(state2).float()
# If we are using experience replay, we now have everything we need to record
if experience_replay:
# We are transfering state and state2 to cpu to make use of non GPU RAM
# so that our experience replay buffer does not take up significant GPU
# RAM. We are doing this instead of storing the original state since
# often the pytorch represented state may be smaller than the actual
# original state.
experience = (state.cpu(), action, reward, state2.cpu(), done)
experience_memory.append(experience)
# If we have experience replay, we must wait until we have at least
# a single batch of memories to train on. If we aren't, just continue
# irregardless.
if experience_replay and len(experience_memory) >= batch_size:
# Create our batches from the experience memory
experience_batch = sample(experience_memory, batch_size)
# As we prepare each batch, we convert them to tensors. Since state
# and state2 are already tensors, we use torch.cat instead of
# instantiating a new Tensor. We use unsqueeze here as we want the
# tensor to be of a shape [1, <observational space>]. instead of just
# [<observational space>] to prevent the cat from just creating a
# long singular row of tensors
state_batch = torch.cat([state.unsqueeze(dim=0) for (state, action, reward, state2, done) in experience_batch])
action_batch = torch.Tensor([action for (state, action, reward, state2, done) in experience_batch]) # Take the sequence of actions, convert to tensor
reward_batch = torch.Tensor([reward for (state, action, reward, state2, done) in experience_batch]) # Take the sequence of rewards, convert to tensor
state2_batch = torch.cat([state2.unsqueeze(dim=0) for (state, action, reward, state2, done) in experience_batch])
done_batch = torch.Tensor([done for (state, action, reward, state2, done) in experience_batch]) # Take the sequence of done booleans, convert to tensor. This automatically onehot-encodes
# This is done in case the state transformation function fails to.
# It should be a no-op in the event that the tensors were already
# on the disk.
state_batch = state_batch.to(device)
action_batch = action_batch.to(device)
reward_batch = reward_batch.to(device)
state2_batch = state2_batch.to(device)
done_batch = done_batch.to(device)
# Regenerate the Q values for the given batch at our current state
# This is necessary because the batch may include old states from an
# earlier, less-accurate model
Q1 = model(state_batch)
# Grab the expected reward future reward (Q2) for this batch
# Turn off gradient for this batch as we aren't backpropagating on it
# Note that we are using the target model (theta_t) instead of the
# q model (theta_q) to prevent instability/oscillations
with torch.no_grad():
# If we are using a target network, use that here.
if target_network:
Q2 = target_model(state2_batch)
else :
Q2 = model(state2_batch)
# results is our given rewards, plus the discounted gamma of future rewards.
# By doing (1 - done_batch), we are inverting the done_batch recording. Thus
# we are ignoring the expected value of Q2 if our Q1 move finished the episode
# The dimension = 1 because of the method we generated the tensor - it is columnular.
# Or, in other words - we have a batch of N rows, each with 4 columns. We are grabbing
# the highest value for each row. torch.max in this case returns the max value in the first
# tensor, and the indicies in the second. We only care about the highest values, so
# the first tensor only (hence [0])
# Detach it from the graph - we are not backpropagating on it
results = (reward_batch + (gamma * (1 - done_batch) * torch.max(Q2, dim=1)[0])).detach()
# calculated is what our model expected for a reward
# dim=1
# - because we're batching, it is columnar data, same as before
# index=action_batch.long().unsqueeze(dim=1))
# - because we are selecting the value for the given action chosen.
# ...we must convert this to long to satisfy the function
# .unsqueeze(dim=1)
# - we need to go from a shape [200] to shape [200,1] tensor
#
# We then call gather on the tensor, which with the above seetings and
# The gather function will select values from our Q1 tensor based on the
# calculated index (which is our chosen action for the example)
#
# .squeeze():
# the gather, when done, has too many dimensions, we bring it back down to
# tensor shape of [200]
calculated = Q1.gather(dim=1, index=action_batch.long().unsqueeze(dim=1)).squeeze()
elif not experience_replay:
# Without saving the gradient, get the Q for the next state (Q2) as well
with torch.no_grad():
# If the target network is being used, we utilize that network
# to get our second state. Otherwise, use the base netwwork
if target_network:
Q2 = target_model(state2.unsqueeze(dim=0))
else:
Q2 = model(state2.unsqueeze(dim=0))
# Grab the max of the calculated next step
maxQ = torch.max(Q2)
# If the episode is over, return the last reward. If it is not,
# return our reward with the maxQ predicted for the next state,
# reduced by our gamma factor.
if not done:
reward = reward + (gamma * maxQ)
# results is our reward, separated from the graph as it's an
# observation and we don't need to back propragate on it.
results = torch.Tensor([reward]).detach()
# calculated is our calculated outcome via the chosen action's
# Q value
calculated = Q.squeeze()[action].unsqueeze(dim=0)
if (not experience_replay or (experience_replay and len(experience_memory) >= batch_size)) \
and step % backpropagate_every == 0:
# Irregardless of what method we used, we now have two tensors -
# calculated and results - which represent, respectively, what
# our Q network thinks it will get for the actions, and what it
# actually received in that situation. We can now calculate the
# loss
# Calculate our loss as per the loss function. We pass it our expected
# output, and the actual result. Here, it's the expected reward vs
# the actual reward
loss = loss_function(calculated, results)
# Zero out our gradient and backpropagate
optimizer.zero_grad()
loss.backward()
optimizer.step()
# If we have a target network for this training, we increment our count
# of optimizer steps. Every sync_every_steps we will copy the target
# network weights over to the primary network.
if target_network:
optimizer_steps += 1
if optimizer_steps % sync_every_steps == 0:
target_model.load_state_dict(model.state_dict())
# Our state2 becomes our current state
# We also transfer
state = state2
# Append the step count to steps
steps.append(step)
rewards.append(total_reward)
if save_every and (episode + 1) % save_every == 0:
model.save(f"model_episode_{episode+1}.pt")
# After each episode, we reduce the epsilon value to slow down our exploration
# rate. We never go below epsilon_minimum.
if epsilon > epsilon_minimum:
epsilon *= epsilon_decay
else:
epsilon = epsilon_minimum
# If our save_every triggers, saved the model, our target model (if used), and
# what traininer state/variables we need to continue on from this point.
# Note that this process tends to be slow
if save_every and (episode + 1) % save_every == 0:
model.save(f"{save_to_folder}/model_episode_{episode+1}.pt")
if target_network:
target_model.save(f"{save_to_folder}/target_network_episode_{episode+1}.pt")
training_state = {
"experience_memory": experience_memory,
"rewards": rewards,
"steps": steps,
"epsilon": epsilon,
"optimizer_steps": optimizer_steps,
}
pickle.dump(training_state, open(f"{save_to_folder}/training_state_{episode+1}.pt", "wb"))
del training_state # This shouldn't be needed, but I've seen some troubles with RAM post pickle write
if on_episode_complete:
stop = on_episode_complete(episode, step, steps, total_reward, rewards)
if stop:
break
return steps, rewards
|
[
"[email protected]"
] | |
5915ecc1d4f20c6bcd2de56e75f093ed7e74554e
|
485cb787a97caf96537dedc8bcf647dca906d5e3
|
/pythonx/test.py
|
7138756b901240d3c15c91b373252175d3ed95f6
|
[] |
no_license
|
MattWoelk/vim-easymarks2
|
d40cfa960c170a33a40055f69e81683c3b0cb2a2
|
f6a05d0a009f2636845a20c112afc5402f814325
|
refs/heads/master
| 2021-01-17T12:47:25.645868 | 2014-02-28T21:44:10 | 2014-02-28T21:44:10 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,086 |
py
|
import vim
# TODO add more options here TODO make customizable
possible_marks = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
def drr():
marks = get_mark_locations()
old_buf = list(vim.current.buffer)
print(marks)
a_mark = marks['a']
cur_line = vim.current.buffer[a_mark['row'] - 1]
cur_line_list = list(cur_line)
cur_line_list[a_mark['col']] = '?'
print(cur_line_list)
vim.current.buffer[a_mark['row'] - 1] = ''.join(cur_line_list)
#print(old_buf)
#print(vim.vars)
highlight_marks()
restore_buffer(old_buf)
def insert_mark_labels():
buf = vim.current.buffer
return buf
def get_mark_locations():
""" Output format: {'a': {'col': 0, 'row': 4}, etc.}"""
result = {}
for mark in possible_marks:
mark_location = vim.current.buffer.mark(mark)
if mark_location:
mark_location = {'row': mark_location[0], 'col': mark_location[1]}
result[mark] = mark_location
return result
def highlight_marks():
print("highlighting")
def restore_buffer(buf):
pass
|
[
"[email protected]"
] | |
a262d4af2b159ffdb3466c28b7cb4719109837c8
|
11a27fd404adc9a43126017b280ec4e66ce6c8b1
|
/calculation.py
|
c96f995e168d364b97db953b873bfa5b3297f68a
|
[] |
no_license
|
xm1112/unet-Precipitation-correction
|
e1f051756e8c05d8b1d346688111e375b69d6d88
|
3da387069619f569cb18f3bfe6ce2c42875208aa
|
refs/heads/master
| 2023-04-15T12:33:55.368401 | 2022-06-01T01:15:58 | 2022-06-01T01:15:58 | 498,146,340 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,512 |
py
|
"""
2021/4/15
Calculate RMSE, CC and re of predicted precipitation and real precipitation
"""
import itertools
import os
import numpy as np
import math
from PIL import Image
import matplotlib.pyplot as plt
np.set_printoptions(threshold=np.inf)
os.chdir("E:/14DL-unet-Regression/run/return/")
#####################################Read the predicted quantified precipitation file############################################
f = open("./led7rawmean_2/b12_e150_final_test_pre.txt", mode='r', encoding='utf-8')
line = f.readline()
print(line)
print(type(line)) #str
line = line.split()
list = list(line)
pre = []
for i in range(len(list)):
pre.append(float(list[i]))
print(pre)
pre = np.array(pre)
pre = pre.astype(float)
###################################################Read forecast data################################################################3
f = open("E:/14DL-unet-Regression/data_make/led7rawmean.txt", mode='r', encoding='utf-8')
line = f.readline()
print(line)
print(type(line))
led1 = line.split()
led1_data = []
for i in range(len(led1)):
led1_data.append(float(led1[i]))
led1_data = np.array(led1_data)
led1_data = led1_data.reshape(1196, 225)
led1_data = led1_data[920:1196, :] #test
#led1_data = np.divide(led1_data, 500.0)
#led1_data = led1_data[0:736, :] #train
#led1_data = led1_data[736:920, :] #val
led1_data =led1_data.reshape(-1)
led1_data = led1_data.astype(float)
##############################################Read real observed precipitation data๏ผobsn.txt๏ผ###########################################################
file_obs = open("E:/14DL-unet-Regression/data_make/obsn.txt", mode='r', encoding='utf-8')
line = file_obs.readline()
obs = []
while line:
a = line.split()
obs.append(a)
line = file_obs.readline()
file_obs.close()
print(obs)
print(len(obs[920:1196]))
test_obs = obs[920:1196] #test
#test_obs = np.divide(led1_data, 500.0)
#test_obs = obs[0:736] #train
#test_obs = obs[736:920] #val
test_obs = np.array(test_obs)
test_obs = test_obs.reshape(-1)
test_obs = test_obs.astype(np.float)
# Calculate rmseใccใre
#The input is arrays, and the type must be unified (two-dimensional array becomes one-dimensional array)
def mse(y_true, y_pred):
m = np.mean((y_true-y_pred)**2)
return m
def rmse(y_true,y_pred):
m = mse(y_true, y_pred)
if mse:
return math.sqrt(m)
else:
return None
def cc(y_true, y_pred):
y_true_mean = np.mean(y_true)
y_pred_mean = np.mean(y_pred)
s = np.sum((y_true-y_true_mean)*(y_pred-y_pred_mean))
t = np.sqrt(np.sum((y_true-y_true_mean)**2))
p = np.sqrt(np.sum((y_pred-y_pred_mean)**2))
c = s/(t*p)
return c
def bais(y_true, y_pred):
bais = np.mean(y_pred-y_true)
return bais
def re(y_true, y_pred):
r = np.sum(y_pred-y_true)
o = np.sum(y_true)
re = (r/o)*100
return re
print("__"*20)
print("Deep learning predicted precipitation data and real observed precipitation data")
print("rmse๏ผ", rmse(test_obs, pre))
print("cc๏ผ", cc(test_obs, pre))
print("bais๏ผ", bais(test_obs, pre))
print("re๏ผ", re(test_obs, pre))
print("__"*20)
print("Forecast precipitation data and real observed precipitation data")
print("rmse๏ผ", rmse(test_obs, led1_data))
print("cc๏ผ", cc(test_obs, led1_data))
print("bais๏ผ", bais(test_obs, led1_data))
print("re๏ผ", re(test_obs, led1_data))
print("__"*20)
|
[
"[email protected]"
] | |
f7ecb98c52d86587f015570263ac5a20bdfbe240
|
0567fcd808397a7024b5009cc290de1c414eff06
|
/src/1658.minimum-operations-to-reduce-x-to-zero.py
|
7f3176eb03955d6bbc0e2d39d5a8afa61e2fd290
|
[] |
no_license
|
tientheshy/leetcode-solutions
|
d3897035a7fd453b9f47647e95f0f92a03bff4f3
|
218a8a97e3926788bb6320dda889bd379083570a
|
refs/heads/master
| 2023-08-23T17:06:52.538337 | 2021-10-03T01:47:50 | 2021-10-03T01:47:50 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,481 |
py
|
#
# @lc app=leetcode id=1658 lang=python3
#
# [1658] Minimum Operations to Reduce X to Zero
#
# @lc code=start
# TAGS: Greedy, Sliding Window
class Solution:
# LTE. Time and Space O(N^2).
def minOperations(self, nums: List[int], x: int) -> int:
q = [(x, 0, len(nums) - 1)]
visited = {}
depth = 0
while q:
cur = []
for x, left, right in q:
if x == 0: return depth
if (left, right) in visited and visited[(left, right)] <= depth: continue
visited[(left, right)] = depth
if x < 0 or left > right:
continue
cur.append((x - nums[left], left + 1, right))
cur.append((x - nums[right], left, right - 1))
depth += 1
q = cur
return -1
# Think in reverse, instead of finding the minmum prefix + suffix, we can find the subarray with maximum length
def minOperations(self, nums: List[int], x: int) -> int:
prefix_sum = [0]
for num in nums:
prefix_sum.append(prefix_sum[-1] + num)
y = prefix_sum[-1] - x
ans = -1
visited = {}
for i, num in enumerate(prefix_sum):
if y + num not in visited:
visited[y + num] = i
if num in visited:
ans = max(ans, i - visited[num])
if ans == -1: return -1
return len(nums) - ans
# @lc code=end
|
[
"[email protected]"
] | |
61b401769d07af9b8953298be222d7c0e8eef4b8
|
53fab060fa262e5d5026e0807d93c75fb81e67b9
|
/backup/user_287/ch6_2020_03_09_20_09_01_051283.py
|
43555c7f67b482084ac43022e30452bb1cd602a2
|
[] |
no_license
|
gabriellaec/desoft-analise-exercicios
|
b77c6999424c5ce7e44086a12589a0ad43d6adca
|
01940ab0897aa6005764fc220b900e4d6161d36b
|
refs/heads/main
| 2023-01-31T17:19:42.050628 | 2020-12-16T05:21:31 | 2020-12-16T05:21:31 | 306,735,108 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 61 |
py
|
def celsius_para_fahrenheit(C):
F = 9/5*C+32
return F
|
[
"[email protected]"
] | |
1489d378e57780ff3019b198c1954499f4a477e2
|
2dee1b222fcf1bc75efe30679b18c17d0faaa18e
|
/day19/part1.py
|
dba8fb487852286125ce76df783cf252c4e3c935
|
[] |
no_license
|
bofh69/aoc
|
783bd26c400c51aa0407aa39d28d64ee6d13344d
|
267c2313cc775f4cd4fd82e6eb4ef386a3a64c48
|
refs/heads/master
| 2020-11-25T00:29:10.520970 | 2019-12-27T17:24:59 | 2019-12-27T17:24:59 | 228,408,482 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 11,409 |
py
|
#!/usr/bin/env python3
import itertools
import sys
prog = [109,424,203,1,21101,11,0,0,1105,1,282,21101,18,0,0,1106,0,259,2102,1,1,221,203,1,21101,0,31,0,1106,0,282,21102,38,1,0,1105,1,259,20101,0,23,2,22101,0,1,3,21101,1,0,1,21101,0,57,0,1105,1,303,2101,0,1,222,20102,1,221,3,21001,221,0,2,21101,0,259,1,21101,80,0,0,1105,1,225,21101,137,0,2,21101,91,0,0,1105,1,303,1202,1,1,223,21001,222,0,4,21102,259,1,3,21101,225,0,2,21102,225,1,1,21101,0,118,0,1106,0,225,20102,1,222,3,21101,0,88,2,21102,133,1,0,1105,1,303,21202,1,-1,1,22001,223,1,1,21101,0,148,0,1106,0,259,1202,1,1,223,20102,1,221,4,20101,0,222,3,21101,24,0,2,1001,132,-2,224,1002,224,2,224,1001,224,3,224,1002,132,-1,132,1,224,132,224,21001,224,1,1,21102,1,195,0,106,0,108,20207,1,223,2,20102,1,23,1,21101,-1,0,3,21101,0,214,0,1105,1,303,22101,1,1,1,204,1,99,0,0,0,0,109,5,2102,1,-4,249,22102,1,-3,1,22102,1,-2,2,22102,1,-1,3,21101,0,250,0,1105,1,225,22102,1,1,-4,109,-5,2106,0,0,109,3,22107,0,-2,-1,21202,-1,2,-1,21201,-1,-1,-1,22202,-1,-2,-2,109,-3,2106,0,0,109,3,21207,-2,0,-1,1206,-1,294,104,0,99,22101,0,-2,-2,109,-3,2105,1,0,109,5,22207,-3,-4,-1,1206,-1,346,22201,-4,-3,-4,21202,-3,-1,-1,22201,-4,-1,2,21202,2,-1,-1,22201,-4,-1,1,22102,1,-2,3,21102,343,1,0,1105,1,303,1105,1,415,22207,-2,-3,-1,1206,-1,387,22201,-3,-2,-3,21202,-2,-1,-1,22201,-3,-1,3,21202,3,-1,-1,22201,-3,-1,2,21202,-4,1,1,21102,1,384,0,1106,0,303,1106,0,415,21202,-4,-1,-4,22201,-4,-3,-4,22202,-3,-2,-2,22202,-2,-4,-4,22202,-3,-2,-3,21202,-4,-1,-2,22201,-3,-2,1,22101,0,1,-4,109,-5,2106,0,0]
class IntCodeInterpreter:
def __init__(self, prog, inp):
self.mem = prog.copy()
self.pc = 0
self.inp = inp.copy()
self.relative_base = 0
self.out = []
def _op_len(self, op):
if op == 1:
return 4
elif op == 2:
return 4
elif op == 3:
return 2
elif op == 4:
return 2
elif op == 5:
return 3
elif op == 6:
return 3
elif op == 7:
return 4
elif op == 8:
return 4
elif op == 9:
return 2
elif op == 99:
return 0
def _read(self, pos, mode):
if mode == 1:
return pos
idx = pos
if mode == 0:
pass
elif mode == 2:
idx = pos + self.relative_base
else:
raise Exception("Unknown mode: %d" % mode)
if idx < 0:
raise Exception("Relative position < 0")
diff = idx - len(self.mem)
if diff >= 0:
self.mem.extend([0] * (diff+1))
try:
return self.mem[idx]
except:
print(idx, len(self.mem))
raise
def _write(self, pos, mode, value):
idx = pos
if mode == 0:
pass
elif mode == 2:
idx = pos + self.relative_base
else:
raise Exception("Unknown mode: %d" % mode)
if idx < 0:
raise Exception("Relative position < 0")
diff = idx - len(self.mem)
if diff >= 0:
self.mem.extend([0] * (diff+2))
try:
self.mem[idx] = value
except:
print(idx, len(self.mem))
raise
def run(self):
param = 0
try:
while self.pc < len(self.mem):
op = self.mem[self.pc] % 100
params = self.mem[self.pc] // 100
op_len = self._op_len(op)
if(op == 99):
return 0
else:
arg = [0,0,0]
param = [0,0,0]
if op_len > 1:
arg[0] = self.mem[self.pc+1]
param[0] = params % 10
if op_len > 2:
arg[1] = self.mem[self.pc+2]
param[1] = (params // 10) % 10
if op_len > 3:
arg[2] = self.mem[self.pc+3]
param[2] = (params // 100) % 10
if(op == 1):
self._write(arg[2], param[2],
self._read(arg[0], param[0]) + self._read(arg[1], param[1]))
elif(op == 2):
self._write(arg[2], param[2],
self._read(arg[0], param[0]) * self._read(arg[1], param[1]))
elif(op == 3):
if len(self.inp) > 0:
# print("INP: ", self.inp[0])
self._write(arg[0], param[0], self.inp[0])
self.inp = self.inp[1::]
else:
return None
elif(op == 4):
# print("OUT: ", self._read(arg[0], param[0]))
self.out.append(self._read(arg[0], param[0]))
elif(op == 5): # Jump if true
if self._read(arg[0], param[0]) != 0:
self.pc = self._read(arg[1], param[1])
op = 99
elif(op == 6): # Jump if false
if self._read(arg[0], param[0]) == 0:
self.pc = self._read(arg[1], param[1])
op = 99
elif(op == 7): # less than
if self._read(arg[0], param[0]) < self._read(arg[1], param[1]):
self._write(arg[2], param[2], 1)
else:
self._write(arg[2], param[2], 0)
elif(op == 8): # equals
if self._read(arg[0], param[0]) == self._read(arg[1], param[1]):
self._write(arg[2], param[2], 1)
else:
self._write(arg[2], param[2], 0)
elif(op == 9): # Set Relative base
self.relative_base = self.relative_base + self._read(arg[0], param[0])
else:
print("Unknown op. Halting! at %d" % self.pc)
return -1
self.pc += self._op_len(op)
except Exception as e:
print("Failed at %d" % self.pc)
raise
def left(dir):
if dir == '^':
return '<'
elif dir == '<':
return 'v'
elif dir == 'v':
return '>'
elif dir == '>':
return '^'
else:
raise Exception("Unknown dir: %s" % dir)
def right(dir):
if dir == '^':
return '>'
elif dir == '<':
return '^'
elif dir == 'v':
return '<'
elif dir == '>':
return 'v'
else:
raise Exception("Unknown dir: %s" % dir)
def forward(pos, dir):
(x, y) = pos
if dir == '^':
return (x, y-1)
elif dir == '<':
return (x-1, y)
elif dir == 'v':
return (x, y+1)
elif dir == '>':
return (x+1, y)
else:
raise Exception("Unknown dir: %s" % dir)
for dir in ['v', '<', '>', '^']:
if left(right(dir)) != dir:
raise Exception("left and right doesn't match")
if right(left(dir)) != dir:
raise Exception("left and right doesn't match")
if right(dir) == dir:
raise Exception("right doesn't match")
def clear():
print("\x1b[2J")
def goto(x, y):
sys.stdout.write("\x1b[%d;%dH" % (y, x))
# map = [[0 for x in range(60)] for y in range(30)]
pos = (0, 0)
def find(tile):
for y in range(len(map)):
row = map[y]
for x in range(len(row)):
if row[x] == tile:
return (x, y)
raise Exception("Not found")
def move_to_result(dir, interp):
interp.inp = [dir]
interp.out = []
while len(interp.out) == 0:
interp.run()
def rev(dir):
if dir == 1:
return 2
if dir == 2:
return 1
if dir == 3:
return 4
if dir == 4:
return 3
raise Exception("Unknown dir: %d" % dir)
def new_pos(dir):
if dir == 1:
return (pos[0], pos[1]-1)
if dir == 2:
return (pos[0], pos[1]+1)
if dir == 3:
return (pos[0]-1, pos[1])
if dir == 4:
return (pos[0]+1, pos[1])
raise Exception("Unknown dir: %d" % dir)
def new_dirs(dir):
if dir == 1:
return [1,3,4]
if dir == 2:
return [2,3,4]
if dir == 3:
return [1,2,3]
if dir == 4:
return [1,2,4]
raise Exception("Unknown dir: %d" % dir)
def search(interp, themap):
global pos
path=[]
tries=dict()
tries[pos] = (0, [1, 2, 3, 4])
themap[pos] = '.'
while len(tries) > 0:
curr = tries[pos]
if len(curr[1]) == 0:
# Done here, backtrack
if curr[0] == 0:
# Done!
return
dir = curr[0]
move_to_result(dir, interp)
if interp.out[0] == 0:
raise Exception("Confused...")
del tries[pos]
pos = new_pos(dir)
else:
dir = curr[1].pop()
np = new_pos(dir)
if not np in themap:
move_to_result(dir, interp)
if interp.out[0] == 0:
themap[np] = '#'
else:
if interp.out[0] == 1:
themap[np] = '.'
else:
themap[np] = 'O'
tries[np] = (rev(dir), new_dirs(dir))
pos = np
def is_intersect(themap, p):
if themap.get((p[0]-1, p[1]), ' ') == '#' and themap.get((p[0]+1, p[1]), ' ') == '#' and themap.get((p[0], p[1]-1), ' ') == '#' and themap.get((p[0], p[1]+1), ' ') == '#':
return True
return False
def is_robot(c):
if c == '^' or c == 'v' or c == '<' or c == '>':
return True
return False
def get_at_most(n, s, others):
while True:
found = False
for o in others:
if s.find(o) == 0:
s = s[len(o)::]
found = True
if not found:
break
result = s[:n+1]
pos = result.rfind(',')
return result[0:pos+1]
def compress(s, words):
result = []
while True:
found = False
for i, word in enumerate(words):
if s.find(word) == 0:
s = s[len(word)::]
found = True
result.append('ABCD'[i])
if not found:
break
if len(s) == 0 and len(result) <= 10:
return ",".join(result)
def find_solution(directives):
for max_a in range(2, 21):
a = get_at_most(max_a, directives, [])
for max_b in range(2, 21):
b = get_at_most(max_b, directives, [a])
for max_c in range(2, 21):
c = get_at_most(max_c, directives, [a, b])
res = compress(directives, [a, b, c])
if res and len(res) <= 21:
return [res, a[:-1], b[:-1], c[:-1]]
clear()
themap = dict()
count = 0
for y in range(50):
for x in range(50):
interp = IntCodeInterpreter(prog, [x, y])
interp.out = []
interp.run()
if interp.out[0] == 1:
themap[(x,y)] = '#'
count = count + 1
else:
themap[(x,y)] = '.'
print(count)
|
[
"[email protected]"
] | |
4fddc48a7f0271c0fedfd2bc34e067720cfab81d
|
92f0c73936c45d683a2d3b87465840b7b1b9817a
|
/scripts/rest
|
2dce48c36886b3c8f0edf871482f7b0511147132
|
[
"MIT"
] |
permissive
|
unixeO/rest-cli
|
24b7bb7fd5b549f6d805003ed0ebdad014b5eed4
|
b689900f745a2f7456e0aec7d54e77f4af815d2d
|
refs/heads/master
| 2023-03-16T06:25:06.484026 | 2021-01-04T19:21:43 | 2021-01-04T19:21:43 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 194 |
#!/usr/bin/env python
# rest-cli - python REST client
# https://github.com/jfillmore/rest-cli
import sys
from rest_cli.shell import Shell
shell = Shell(sys.argv[1:])
sys.exit(shell.last_rv)
|
[
"[email protected]"
] | ||
7c7a476c5669fbb0f5838024df127dccffa90f98
|
f115b3351c61c9785b28015813d740a55e36774e
|
/m2m-relations/articles/migrations/0006_auto_20210912_2105.py
|
73e8e189e7b9e46fbc857f0791058ec2e743d66c
|
[] |
no_license
|
97wave/dz_ORM.2_4
|
dc59b0ea4272bfd6debd161eb173d718f96dbad3
|
0b88a76696d278755d368e0a70d81b89a382dddb
|
refs/heads/master
| 2023-08-06T21:50:50.613856 | 2021-09-22T11:07:01 | 2021-09-22T11:07:01 | 409,170,953 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 363 |
py
|
# Generated by Django 3.1.2 on 2021-09-12 18:05
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('articles', '0005_alter_article_tags'),
]
operations = [
migrations.RenameField(
model_name='article',
old_name='tags',
new_name='scopes',
),
]
|
[
"[email protected]"
] | |
070961f5207cfaa07e5c3ac149066c0718aa436f
|
da13d10e600fe9e31e6d232ccf4f1f9e9a8dd0d9
|
/setlist_gen_funcs.py
|
3eee988c71af1e422ee6ac5d44f4544c69d77e2c
|
[] |
no_license
|
dharit-tan/setlist_gen
|
5a77fab48f80f3509fc2ff08af5d514106fdd6c1
|
932fffd62e87ac93ad69642762c7bbce269ca161
|
refs/heads/master
| 2022-05-03T14:28:31.542313 | 2013-12-20T16:31:05 | 2013-12-20T16:31:05 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,893 |
py
|
# pygame shit
import pygame
import pygame.midi as pymidi
import pygame.key as pykey
import pygame.event as pyevent
import pygame.fastevent as pyfastevent
from pygame.locals import *
# other imports
import socket
import signal
import datetime
import re
HOST = 'localhost'
PORT = 8080
MIX_MIN = 20
MIX_MAX = 106
X_FADE_DIF = 80
X_FADER = (176, 0)
# did as much as I could, how the fuck do u pass decks and sock for closing?
def handler(signum, frame):
pymidi.quit()
pygame.quit()
# class def
class Deck:
def __init__(self, name):
# constants
self.PLAY = None
self.EQ_HI = None
self.EQ_MID = None
self.EQ_LO = None
self.FILT = None
self.VOL = None
self.DEFAULT_VOL = 127
self.X_FADE_SIDE = 0
self.name = name
# instance variables
self.aud = False
self.x_fade = True
self.vol = True
self.eq_hi = 63
self.eq_mid = 63
self.eq_lo = 63
self.eq = True
self.filt = True
self.play = False
def update(self):
self.eq = (self.eq_hi > MIX_MIN) or (self.eq_mid > MIX_MIN) or (self.eq_lo > MIX_MIN)
self.aud = self.x_fade & self.vol & self.eq & self.filt & self.play
def debug(a, b):
for i in [a, b]:
print i.name, "aud?", i.aud
for v in vars(i):
if v == False:
print v, "False"
def list_devices():
for i in range(pymidi.get_count()):
print pymidi.get_device_info(i)
# pass in timestamp - init_timestamp
def handle_timestamp(timestamp):
s = "[" + str(timestamp)[:7] + "]"
return s
def get_device():
while True:
try:
device_id = input('Enter device number (starts at 1): ')
device = pymidi.Input(device_id)
except NameError:
print 'NameError, try again... '
except pymidi.MidiException:
print 'MidiException, try again...'
except SyntaxError:
print 'SyntaxError, try again...'
else:
return device
def connect_to_traktor():
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.bind((HOST, PORT))
sock.listen(1)
(conn, addr) = sock.accept()
conn.send("HTTP/1.0 200 OK\r\n\r\n")
print "Connected to traktor"
return conn, sock
def handle_midi(e, deck_A, deck_B, focused_deck):
for deck in [deck_A, deck_B]:
if (e.status, e.data1) == deck.PLAY:
if e.data2 == 127:
deck.play = True
else:
deck.play = False
if (e.status, e.data1) == deck.VOL:
if e.data2 > (deck.DEFAULT_VOL / 3):
deck.vol = True
else:
deck.vol = False
if (e.status, e.data1) == deck.EQ_HI:
deck.eq_hi = e.data2
if (e.status, e.data1) == deck.EQ_MID:
deck.eq_mid = e.data2
if (e.status, e.data1) == deck.EQ_LO:
deck.eq_lo = e.data2
if (e.status, e.data1) == deck.FILT:
if (e.data2 > MIX_MIN) and (e.data2 < MIX_MAX):
deck.filt = True
else:
deck.filt = False
if (e.status, e.data1) == deck.VOL:
if e.data2 > (deck.DEFAULT_VOL / 3):
deck.vol = True
else:
deck.vol = False
if (e.status, e.data1) == X_FADER:
if abs(e.data2 - deck.X_FADE_SIDE) < X_FADE_DIF:
deck.x_fade = True
else:
deck.x_fade = False
# if focused_deck:
# print "focused deck:", focused_deck.name
# else:
# print "no focused_deck"
if focused_deck != deck_B and not deck_B.aud:
deck_B.update()
if deck_B.aud:
return datetime.datetime.now()
deck_B.update()
if focused_deck != deck_A and not deck_A.aud:
deck_A.update()
if deck_A.aud:
return datetime.datetime.now()
deck_A.update()
return None
def get_default_midi_val(prompt, decks):
print prompt
key_entered, midi_entered = False, False
while not key_entered or not midi_entered:
events = pyfastevent.get()
for e in events:
if e.type == pygame.KEYDOWN:
if (e.key == pygame.K_RETURN) and (midi_entered == True):
key_entered = True
if e.type == pymidi.MIDIIN:
val = e.data2
midi_entered = True
if decks.poll():
midi_events = decks.read(1)
events = pymidi.midis2events(midi_events, decks.device_id)
for e in events:
pyfastevent.post(e)
return val
|
[
"[email protected]"
] | |
ffcb5dfd61b8ea8406307f4d49316125cb08366c
|
54f352a242a8ad6ff5516703e91da61e08d9a9e6
|
/Source Codes/AtCoder/agc006/B/4249708.py
|
c209881efba18f1680c0d7282393670ecf313f49
|
[] |
no_license
|
Kawser-nerd/CLCDSA
|
5cbd8a4c3f65173e4e8e0d7ed845574c4770c3eb
|
aee32551795763b54acb26856ab239370cac4e75
|
refs/heads/master
| 2022-02-09T11:08:56.588303 | 2022-01-26T18:53:40 | 2022-01-26T18:53:40 | 211,783,197 | 23 | 9 | null | null | null | null |
UTF-8
|
Python
| false | false | 685 |
py
|
N,x = map(int,input().split())
if x in (1, 2 * N - 1):
print('No')
exit()
print('Yes')
if N == 2 and x == 2:
l = [1, 2, 3]
print(*l, sep='\n')
elif x == 2:
l = [4, 1, 2, 3]
rest = list(range(5, 2 * N))
m = len(rest) // 2
l = rest[:m] + l + rest[m:]
print(*l, sep='\n')
elif x == 2 * N - 2:
l = [x - 2, x + 1, x, x - 1]
rest = list(range(1, 2 * N - 4))
m = len(rest) // 2
l = rest[:m] + l + rest[m:]
print(*l, sep='\n')
else:
l = [x + 2, x - 1, x, x + 1, x - 2]
rest = list(range(1, x - 2)) + list(range(x + 3, 2 * N))
m = len(rest) // 2
l = rest[:m] + l + rest[m:]
print(*l, sep='\n')
|
[
"[email protected]"
] | |
481b8f827a0fecfaff1fbc39d098e6d4f9a3ff51
|
a3b90a6c64a13968d01ed18de66c06487378f97f
|
/flask_project1.0/date.py
|
896d2b03908a7768abe4c82c2361d62e4eecfd45
|
[] |
no_license
|
RiddMa/SoftwareEngineering2021
|
287ef83c30b351e477dc3e92b9d02201fad555eb
|
e1ca6e99ac28610bbaa1aa59755595c8fafd7c66
|
refs/heads/master
| 2023-07-12T22:32:58.202705 | 2021-07-21T15:54:51 | 2021-07-21T15:54:51 | 348,347,591 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 583 |
py
|
from pytz import utc
from pytz import timezone
from datetime import datetime
cst_tz = timezone('Asia/Shanghai')
utc_tz = timezone('UTC')
now = datetime.now().replace(tzinfo=cst_tz)
#local_dt = cst_tz.localize(now, is_dst=None)
utctime = now.astimezone(utc)
print ("now : %s"%now)
print ("format: %s"%now.strftime('%Y-%m-%d %H:%M:%S'))
print ("utc : %s"%utctime)
utcnow = datetime.utcnow()
utcnow = utcnow.replace(tzinfo=utc_tz)
china = utcnow.astimezone(cst_tz)
print ("utcnow: %s"%utcnow)
print ("format: %s"%utcnow.strftime('%Y-%m-%d %H:%M:%S'))
print ("china : %s"%china)
|
[
"[email protected]"
] | |
6d83bd86d52e7c41b5c8607183656819ac0f9d10
|
120b0b37550c3cebec83a6dbf05e53462c76ab5f
|
/Oving_2/most_common_player.py
|
a208c135c9d0e81979ee852a0bdfe7818ab03c34
|
[] |
no_license
|
Magnusld/TDT4113_Plab
|
72a0175aa6a88ea296361eb672ce1259c0c16d2e
|
360045466e543cc6006c24a96df13f01d1f7562a
|
refs/heads/master
| 2023-04-04T09:04:15.616349 | 2021-04-07T09:34:40 | 2021-04-07T09:34:40 | 354,326,501 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,772 |
py
|
"""
This is one of the player classes
"""
from player_interface import PlayerInterface
import random
class MostCommonPlayer(PlayerInterface):
"""
This player looks at what the opponent has picked the most often,
and assumes it will pick it again and then counter that pick
"""
opponents_previous = []
def __init__(self, name):
super().__init__(name)
def select_action(self):
if len(self.opponents_previous) == 0:
return random.choice(["rock", "paper", "scissors"])
else:
most_common = self.find_most_common()
if most_common == 0:
return "paper"
elif most_common == 1:
return "scissors"
else:
return "rock"
def find_most_common(self):
"""
Findes the opponents most common pick
:return:
"""
counter = [0, 0, 0]
for play in self.opponents_previous:
if play == "rock":
counter[0] += 1
elif play == "paper":
counter[1] += 1
else:
counter[2] += 1
largest = 0
largest_index = None
for number in range(len(counter)):
if counter[number] > largest:
largest = counter[number]
largest_index = number
return largest_index
def receive_result(self, result):
if result.winner is not None:
if self.name == result.winner.name:
self.points += 1
else:
self.points += 0.5
if result.player_1.name == self.name:
self.opponents_previous.append(result.p2_choice)
else:
self.opponents_previous.append(result.p1_choice)
|
[
"[email protected]"
] | |
5c56194f34aae729ad3cf0e25875e5a8ecaf2ec8
|
c72710b1712889a096df3253983a8ebf08210bd3
|
/PuLink/spiders/incliva.py
|
408238d99e4fb7fb52e375560250eaec42cc98c7
|
[] |
no_license
|
Angel-RC/PuLink
|
74233b365db5c2d5f0b4fa9f0910fd37d199614d
|
e3a2e3eeffd2728fca2bafadca0c444aac8855b0
|
refs/heads/master
| 2022-04-20T10:31:23.446094 | 2020-04-17T17:27:19 | 2020-04-17T17:27:19 | 226,748,440 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,154 |
py
|
import sys
#sys.path.append('C:/Users/Chicote/Desktop/proyectos/PuLink/Pulink')
#from items import PulinkItem
import scrapy
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from scrapy.exceptions import CloseSpider
#from PuLink.items import PulinkItem
import datetime
from scrapy.crawler import CrawlerProcess
class PulinkItem(scrapy.Item):
# define the fields for your item here like:
start_date = scrapy.Field()
entidad = scrapy.Field()
ciudad = scrapy.Field()
titulo = scrapy.Field()
deadline = scrapy.Field()
referencia = scrapy.Field()
url = scrapy.Field()
class spider_incliva(CrawlSpider):
name = 'spider_incliva'
entidad = 'INCLIVA'
ciudad = 'Valencia'
url_site = 'https://www.incliva.es/'
allowed_domain = ['https://www.incliva.es/empleo']
start_urls = ['https://www.incliva.es/empleo']
estado_abierto = ["Abierta", "ABIERTA", "Open", "OPEN"]
def parse(self, response):
"""
Parsing of each page.
"""
# seleccionamos solo los empleos que estan abiertos
empleo_list = response.xpath("//table[@id='tabla_empleo']/tbody/tr")
empleo_list = [item for item in empleo_list if item.xpath("td[5]/text()").get() in self.estado_abierto]
for empleo_item in empleo_list:
oferta = PulinkItem()
oferta['start_date'] = empleo_item.xpath("td[3]/text()").get()
oferta['entidad'] = self.entidad
oferta['ciudad'] = self.ciudad
oferta['titulo'] = empleo_item.xpath("td[1]/text()").get().replace("\n", '').replace("\r", '')
oferta['referencia'] = empleo_item.xpath("td[2]/text()").get()
oferta['url'] = self.url_site + empleo_item.xpath("td[6]/a/@href").get()
oferta['deadline'] = empleo_item.xpath("td[4]/text()").get()
yield oferta
if __name__ == "__main__":
process = CrawlerProcess({
'FEED_URI': 'data/incliva.csv',
'FEED_FORMAT': 'csv'
})
process.crawl(spider_incliva)
process.start()
|
[
"angel.r.chicote.com"
] |
angel.r.chicote.com
|
68e02bc0b29817b39b36e472da89ec1b87795889
|
9d15ae6577f1cff53a51809a6dd3177c1b4c8f2a
|
/Size/Geometric_Transform/src/color_interpolation.py
|
ee9ea9b206dc24d0c8e3e02e9da7184ae4a08ad6
|
[] |
no_license
|
LeeChungHyun/Computer-Vision
|
89f1b9e48e381e90339cfb3407663347f5fc99b9
|
0ac39478ef4cce5a8065991c8b3b2ead6c7d48e8
|
refs/heads/master
| 2021-05-21T15:21:07.372918 | 2020-06-22T12:10:22 | 2020-06-22T12:10:22 | 252,695,358 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 383 |
py
|
import cv2 as cv
import numpy as np
def color_rect():
g = np.zeros((256,256,3), np.uint8)
for i in range(256):
g[i,:,:] = (0, i, 255-i)
g[i, 255, :] = (255-i,i,i)
for j in range(256):
g[i,j,:] = (1-j/256)*src[i,0,:] + j/256*g[i,255,:]
return g
g = color_rect()
cv.imshow('Org', g)
cv.waitKey(0)
cv.destroyAllWindows()
|
[
"[email protected]"
] | |
953960235b1932b88be7cf42442ff1a77defb61a
|
9d7bcc1b03de3cf263e5807a81fb4a694f84bf06
|
/cLasstd2D.py
|
544d3ca8e695e0e05250279926d5d354b5835ec5
|
[] |
no_license
|
RiverTate/Chern
|
00aac98a0d22fccb0764305703492282c499420c
|
e6f7b6e826bfc9bfc8a8c1806bba8e82788ee8bc
|
refs/heads/master
| 2021-10-19T23:38:20.174332 | 2019-02-24T17:39:53 | 2019-02-24T17:39:53 | 279,393,140 | 1 | 0 | null | 2020-07-13T19:25:57 | 2020-07-13T19:25:56 | null |
UTF-8
|
Python
| false | false | 8,647 |
py
|
""" Class of infinite two-dimensional lattices.
The module contains hexagonal and square lattices.
"""
import numpy as np
import numpy.linalg as lg
import FL_funcs as fl
########################################
class lattice2D():
""" class of 2D infinite hexagonal lattice in k-representation.
"""
def __init__(self, Nd=2, J_hop=1., delta = 1., it = 0,
k_vec = np.zeros((2), float), **kwargs):
"""
the basic structure of a hexagonal lattice is persumed,
if no other parameter are not given
"""
self.J_hop = J_hop # the hopping coefficient
self.Nd = Nd # dimension of Hamiltonian,
self.delta = delta # time-dep hopping amplitude
self.it = it # time-interval that system is in
self.k_vec = k_vec # the k-vector
# initialize the Hamilnonian matrix
self.H_kc = fl.H_k(k_vec, it, delta)
####################
def updateH(self,k_vec,it):
"""
update the Hamiltonian matrix by new k-vector
and time-interval it
input:
------
k_vec: real (2,), 2D (kx,ky) vector
"""
self.k_vec = k_vec
self.it = it
self.H_kc = fl.H_k(k_vec, self.it, self.delta)
####################
def evolve(self, k_vec, Nt,**kwargs):
""" evolve the time-dependent parameter of a lattice
and generate effective Floquet Hamiltonian.
input:
------
Nt: int, number of intervals in one period
kwargs: depending on the form of lattice the
time-dependent variables can be different.
return:
-------
Efl_k: real (Nd, ) ndarray, sorted quasienergies of
effective Floquet Hamiltonian.
Ufl_k: complex (Nd,Nd) ndarray, sorted eigenvectors of
effective Floquet Hamiltonian
"""
M_eff = np.eye((self.Nd), dtype=complex) # aux matrix
T = 1.
for it in range(Nt):
# update the Hamiltonian for time-inteval
self.updateH(k_vec, it)
# return eigenenergies and vectors
E_k, U = lg.eig(self.H_kc)
# U^-1 * exp(H_d) U
U_inv = lg.inv(U)
# construct a digonal matrix out of a vector
M1 = (np.exp(-1.j*E_k*T) * U_inv.T).T
#MM = np.dot(U_inv,np.dot(H_M, U))
MM = np.dot(U,M1)
M_eff = np.dot(M_eff,MM)
# end of loop
Ek, Uk = lg.eig( M_eff )
idx = (np.log(Ek).imag).argsort()
Efl_k = np.log(Ek).imag[idx]
Ufl_k = Uk[idx]
return Efl_k, Ufl_k
####################
def band_structure_static(self, kx_range, ky_range, N_res):
"""
a Hamiltonian in (kx,ky) is given, evaluate the bandstructire of
a static Hamiltonian E(kx,ky)
input:
------
kx_range: real (2,), the domain of kx
ky_range: real (2,), the domain of ky
N_res: int, resolution in kx and kx direction
output:
-------
E_arr: real (Nd, N_res, N_res), eigenenergies
"""
kxR = np.linspace(kx_range[0], kx_range[1], N_res)
kyR = np.linspace(ky_range[0], ky_range[1], N_res)
E_arr = np.zeros((2,N_res,N_res), float)
# mesh over area in k-space
# Kx, Ky = np.meshgrid(kx,ky)
for ix, kx in enumerate(kxR):
for iy, ky in enumerate(kyR):
k_vec = np.array([kx,ky], float)
# Construct k-representation of Hamiltonian
self.updateH(k_vec, self.it)
E_arr[:,ix,iy] = np.sort( np.linalg.eigvalsh(self.H_kc).real )
#end-loop ky
#end-loop kx
return E_arr
####################
def band_structure_dynamic(self, kx_range, ky_range, N_res):
"""
a Hamiltonian in (kx,ky,t) is given, evaluate the quasienergy bandstructire
of a dynamic Hamiltonian E(kx,ky)
input:
------
kx_range: real (2,), the domain of kx
ky_range: real (2,), the domain of ky
N_res: int, resolution in kx and kx direction
output:
-------
E_arr: real (Nd, N_res, N_res), eigenenergies
"""
kxR = np.linspace(kx_range[0], kx_range[1], N_res)
kyR = np.linspace(ky_range[0], ky_range[1], N_res)
Nt = 3
E_arr = np.zeros((2,N_res,N_res), float)
# mesh over area in k-space
# Kx, Ky = np.meshgrid(kx,ky)
for ix, kx in enumerate(kxR):
for iy, ky in enumerate(kyR):
k_vec = np.array([kx,ky], float)
# Floquet eigenvalues and eigenenergies
E_arr[:,ix,iy] , Uaux = self.evolve(k_vec, Nt)
#end-loop ky
#end-loop kx
return E_arr
####################
def latF(self, k_vec, Dk, delta):
""" Calulating lattice field using the definition:
F12 = ln[ U1 * U2(k+1) * U1(k_2)^-1 * U2(k)^-1 ]
so for each k=(kx,ky) point, four U must be calculate.
The lattice field has the same dimension of number of
energy bands.
input:
------
k_vec=(kx,ky),
Dk=(Dkx,Dky),
output:
-------
F12:lattice field corresponding to each band as a n
dimensional vec
E: Quasienergies
"""
k = k_vec
E_sort, psi = lg.eig( fl.H_k(k, self.it, self.delta) )
E_sort = np.sort(E_sort)
k = np.array([k_vec[0]+Dk[0], k_vec[1]], float)
E, psiDx = lg.eig( fl.H_k(k, self.it, self.delta) )
k = np.array([k_vec[0], k_vec[1]+Dk[1]], float)
E, psiDy = lg.eig( fl.H_k(k, self.it, self.delta) )
k = np.array([k_vec[0]+Dk[0], k_vec[1]+Dk[1]], float)
E, psiDxDy = lg.eig( fl.H_k(k, self.it, self.delta) )
U1x = np.zeros((self.Nd), dtype=complex)
U2y = np.zeros((self.Nd), dtype=complex)
U1y = np.zeros((self.Nd), dtype=complex)
U2x = np.zeros((self.Nd), dtype=complex)
for i in range(self.Nd):
U1x[i] = fl.build_U(psi[:,i], psiDx[:,i] )
U2y[i] = fl.build_U(psi[:,i], psiDy[:,i] )
U1y[i] = fl.build_U(psiDy[:,i], psiDxDy[:,i] )
U2x[i] = fl.build_U(psiDx[:,i], psiDxDy[:,i] )
F12 = np.zeros((self.Nd), dtype=complex)
F12 = np.log( U1x * U2x * 1./U1y * 1./U2y)
return F12, E_sort
########################################
def chernNum(self, kx_Bz=np.array([0,4*np.pi/3]),
ky_Bz=np.array([0,2*np.pi/np.sqrt(3)]),
N_res=30):
"""
To calculate the Chern number of the Hamiltonian (or the Floquet Hamiltonian)
over its Brillouin zone (BZ).
input:
------
kx_Bz: real (2,), kx BZ
ky_Bz: real (2,), ky BZ
N_res: int, resolution in kx and kx direction
output:
-------
Chrn_Num: real (Nd,), the Chern number associated with each band.
"""
x_eps = 0.3 # shift from Dirac point
x_res = 20
kx_int = 0 + x_eps # -np.pi
kx_fin = 4*np.pi/3 + x_eps
Dx = (kx_fin - kx_int)/x_res
y_res = 20
ky_int = 0 # -np.pi
ky_fin = 2*np.pi/np.sqrt(3)
Dy = (ky_fin - ky_int)/y_res
Nd = self.Nd # dimension of the Hamiltonian
Dk = np.array([Dx,Dy], float)
LF = np.zeros((Nd), dtype=complex)
LF_arr = np.zeros((Nd,x_res, y_res), dtype=float)
E_arr = np.zeros((Nd,x_res, y_res), dtype=float)
sumN = np.zeros((Nd), dtype=complex)
E_k = np.zeros((Nd), dtype=complex)
chernN = np.zeros((Nd), dtype=complex)
# Loop over kx
for ix in range(x_res):
kx = kx_int + ix*Dx
# Loop over ky
for iy in range(y_res):
ky = ky_int + iy*Dy
k_vec = np.array([kx,ky], float)
LF, E_k = self.latF(k_vec, Dk, self.delta)
sumN += LF
# # save data for plotting
LF_arr[:,ix,iy] = LF.imag
E_arr[:,ix,iy] = np.sort(E_k.real)
# End of ky Loop
# End of kx Loop
chernN = sumN.imag/(2*np.pi)
print("Chern number bands are (%.3f, %.3f) "
%(chernN[0], chernN[1]))
print("Sum of all bands Chern Number is %.2f " %(sum(chernN)))
return chernN, E_arr
####################
|
[
"[email protected]"
] | |
6124897fe7745ee9efb97ddf0a74376434848881
|
ce6cc66ad9527b32f8bc010b9aff7d44a8a9cc62
|
/ffm/singleton.py
|
f3ffe85f1ae177bd0b8a460fb9eff7c314566fc5
|
[] |
no_license
|
wayswang/recommend_sys
|
7463ef04b5198178d4f478ef85ccb815b89b5bf3
|
10cb88732a7049197220c48d4fecd11c98e779ba
|
refs/heads/master
| 2023-06-24T23:35:11.998942 | 2021-07-15T08:36:10 | 2021-07-15T08:36:10 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 497 |
py
|
# -*- coding: utf-8 -*-
# @Date : 3/2/18
# @Author : zhangchaoyang
class Singleton(type):
def __init__(cls, class_name,base_classes, attr_dict):
cls.__instance = None
super(Singleton, cls).__init__( class_name,base_classes, attr_dict)
def __call__(cls, *args, **kwargs):
if cls.__instance is None:
cls.__instance = super(Singleton, cls).__call__(*args, **kwargs)
return cls.__instance
else:
return cls.__instance
|
[
"[email protected]"
] | |
78631f8c427327a030e57ee66b8fe5df5f3beed2
|
2839ece36a5186ae0e7f90af1efa0913f701f066
|
/tools/convert_textures.py
|
8cd770e3d1d1bdd3ea642dba13d2aaf02443e7b3
|
[
"Apache-2.0"
] |
permissive
|
Longi94/rl-loadout
|
5d32badffb72d1e16561d31422e470d6e51f735e
|
07a248e16c8e5fb615ec4f8018631f3c622ac2a4
|
refs/heads/master
| 2023-01-08T07:40:42.445982 | 2020-03-14T00:00:37 | 2020-03-14T00:00:37 | 197,087,185 | 18 | 2 |
Apache-2.0
| 2023-01-07T08:47:39 | 2019-07-15T23:49:19 |
TypeScript
|
UTF-8
|
Python
| false | false | 906 |
py
|
import argparse
import os
from PIL import Image
from multiprocessing import Pool
from functools import partial
def convert(file, args):
print(f'Processing {file}...')
image = Image.open(os.path.join(args.dir, file))
image.save(os.path.join('converted', file.replace('.tga', '.png')))
image.thumbnail((image.size[0] / 2, image.size[1] / 2), Image.LANCZOS)
image.save(os.path.join('converted', file.replace('.tga', '_S.tga')))
image.save(os.path.join('converted', file.replace('.tga', '_S.png')))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--dir', '-d', type=str, required=True)
args = parser.parse_args()
if not os.path.exists('converted'):
os.makedirs('converted')
files = filter(lambda x: x.endswith('.tga'), os.listdir(args.dir))
with Pool(10) as p:
p.map(partial(convert, args=args), files)
|
[
"[email protected]"
] | |
baa3b7287586e03c59cfa147035055db68506852
|
7ff42d0f1800f6fa80845651c607e1917a6818b1
|
/examples/trading_system2/converte_xml_txt.py
|
535d2ab94416fabb8bcaa0a596928147afb18e32
|
[] |
no_license
|
LCAD-UFES/MAE
|
cff9a632c2c2bbd8916942c9a514f9306b76d54a
|
2ae6664b66091e7919e94582b022dd12b4e5842b
|
refs/heads/master
| 2021-01-10T16:55:44.737700 | 2018-08-02T23:14:27 | 2018-08-02T23:14:27 | 53,516,570 | 5 | 1 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,570 |
py
|
import sys
import os
from xml.etree.ElementTree import ElementTree
# Cria um dicionario com todos os hora-minutos do dia (das 10:00 aas 16:59). Cada elemento do dicionario contera um preco e um volume.
def init_cotacoes(hora_inicio_pregao, hora_fim_pregao):
cotacoes = {}
# hora inicio pregao (fora do horario de verao) = 10
# hora fim pregao (fora do horario de verao) = 17
for h in range(hora_inicio_pregao, hora_fim_pregao):
for m in range(0,60):
if h != hora_fim_pregao:
if m < 10:
cotacoes[str(h)+":0"+str(m)] = [-1.0, 0]
else:
cotacoes[str(h)+":"+str(m)] = [-1.0, 0]
else:
cotacoes[str(h)+":00"] = [-1.0, 0]
break
return cotacoes
def converte(arquivo_xml, hora_inicio_pregao, hora_fim_pregao):
if os.path.exists(arquivo_xml):
tree = ElementTree()
tree.parse(arquivo_xml) # Cria uma arvore com o conteudo do arquivo xml
root = tree.getroot() # Pega a raiz da arvore
quotes = tree.findall("quote") # Acha todos os quotes dentro da arvore criada
# Cria um dicionario com todos os hora-minutos do dia (das 10:00 aas 16:59)
cotacoes = init_cotacoes(hora_inicio_pregao, hora_fim_pregao)
# Le a array de quotes em ordem reversa
for quote in reversed(quotes):
# data = quote.attrib["timestamp"]
hora_minuto = quote.attrib["timestamp"][(len(quote.attrib["timestamp"])-5):(len(quote.attrib["timestamp"]))]
preco = eval(quote.find("price").text)
volume = eval(quote.find("volume").text)
try:
# Em alguns minutos nao ha contacoes: a linha abaixo gera um erro que ee descartado no except
temp = cotacoes[hora_minuto]
cotacoes[hora_minuto] = [preco, volume]
temp = cotacoes[hora_minuto]
#print hora_minuto, preco, temp
except:
pass
# Conta quantas cotacoes estao faltando no inicio do dia
num_faltando_iniciais = 0
for hora_minuto in sorted(cotacoes.keys()):
if cotacoes[hora_minuto][0] == -1.0:
num_faltando_iniciais = num_faltando_iniciais + 1
else:
primeiro_preco = cotacoes[hora_minuto][0]
break
# Preenche as cotacoes faltando com a ultima cotacao valida
i = 0
volume_anterior = 0
for hora_minuto in sorted(cotacoes.keys()):
if i < num_faltando_iniciais:
cotacoes[hora_minuto][0] = primeiro_preco
cotacoes[hora_minuto][1] = 0
i = i + 1
if cotacoes[hora_minuto][0] == -1.0:
cotacoes[hora_minuto][0] = preco_anterior
cotacoes[hora_minuto][1] = volume_anterior
print hora_minuto, cotacoes[hora_minuto][0], cotacoes[hora_minuto][1] - volume_anterior
preco_anterior = cotacoes[hora_minuto][0]
volume_anterior = cotacoes[hora_minuto][1]
if __name__ == '__main__':
if len(sys.argv) != 4:
print "Numero de paramentros errado"
print " Uso: python converte_xml_txt.py <arquivo.xml> <hora inicio pregao, ex.: 10> <hora inicio pregao, ex.: 17>"
sys.exit(1)
try:
converte (sys.argv[1], int(sys.argv[2]), int(sys.argv[3]))
except:
print "Erro em ", sys.argv[1], sys.argv[2], sys.argv[3]
|
[
"[email protected]"
] | |
32d8b503fe1035e019f17332a9f9ba9578c65a5c
|
94197cf1fd92b55d9ed0fc36772c379f7174d496
|
/my_bakery_store/bakery_store/migrations/0005_user_avt.py
|
84bd4c3231ed57a4a10465a6a1103001779fa4a0
|
[] |
no_license
|
tuyen97/Do_an_cac_cong_nghe_xay_dung_HTTT
|
42897e10c304ccef680ac9cf42a862a771edd965
|
ccb8739f23d06f8f6b133b9db7efc6b6904d39c4
|
refs/heads/master
| 2020-04-01T17:01:29.512843 | 2018-12-20T17:31:49 | 2018-12-20T17:31:49 | 153,409,413 | 0 | 0 | null | 2018-11-26T14:57:41 | 2018-10-17T06:53:06 |
JavaScript
|
UTF-8
|
Python
| false | false | 406 |
py
|
# Generated by Django 2.1.1 on 2018-10-31 09:52
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('bakery_store', '0004_auto_20181031_0920'),
]
operations = [
migrations.AddField(
model_name='user',
name='avt',
field=models.ImageField(null=True, upload_to='images/user'),
),
]
|
[
"[email protected]"
] | |
75edfbac6bf85741f7b0f433d319369072044602
|
2d6855b6940e93c6a77a4b7a16d23ea509cf66e1
|
/envdumptests/donothing.py
|
ab367d6ea74987c0614a91f81cb5284f3b3af111
|
[] |
no_license
|
eukaryote/junkdrawer
|
7239a01d88159d2728b72e11efcc406ff7b6733a
|
696f3e43cffafcc6cf833d26643a97f7b414c7d7
|
refs/heads/master
| 2020-12-24T17:08:50.021603 | 2016-03-24T03:39:26 | 2016-03-24T03:39:26 | 32,162,396 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 108 |
py
|
#!/usr/bin/env python
"""
This "null" script takes about 40 milliseconds on my laptop (cpython 2.7.9).
"""
|
[
"[email protected]"
] | |
da48c55d538e85eeafb8462ffa66006f0769a785
|
11c89364bf014d4d75a10572344b4905eea3a6b5
|
/pyth.py
|
d9aba7a5049cc2ff095fe32291a3b5f4cf7ae92a
|
[] |
no_license
|
wwalid18/pythontraining
|
aa4eba85dc706489a3ec7c91b4957c9c33321456
|
4bc5b05fc460680810cfda234b6bfbc34965d1f7
|
refs/heads/master
| 2020-11-24T21:55:35.965931 | 2019-12-16T11:09:00 | 2019-12-16T11:09:00 | 228,356,557 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 39 |
py
|
print('hello world')
print('bye world')
|
[
"[email protected]"
] | |
92b81222bf64312ec2fe4cdf6f97ddd2e6f49d7d
|
ffb56a671654cb9e2193135c9d8d2b32f5b5bef3
|
/blog/views.py
|
9c545ba4a009ec8fe69577bbf1c99819b1ae7a4f
|
[] |
no_license
|
Saltyn1/block_molchanov
|
cf1bf0fd4c6190e4c82f128da6e1aea08cf28f7e
|
ddb07450f69593189d57adcc05a0e5d827fd23de
|
refs/heads/master
| 2023-05-28T17:00:56.034223 | 2021-06-11T08:49:23 | 2021-06-11T08:49:23 | 375,961,242 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,671 |
py
|
from django.views import generic
from django.shortcuts import render, redirect
from django.shortcuts import get_object_or_404
from django.views.generic import View, CreateView
from .forms import TagForm, PostForm
from .models import Post, Tag
from .utils import ObjectDetailMixin
# Create your views here:
def posts_list(request):
posts = Post.objects.all()
return render(request, 'blog/index.html', context={'posts': posts})
class PostDetail(ObjectDetailMixin, View):
model = Post
template = 'blog/post_detail.html'
class PostCreate(View):
def get(self, request):
form = PostForm()
return render(request, 'blog/post_create_form.html', context={'form': form})
def post(self, request):
bound_form = PostForm(request.POST)
if bound_form.is_valid():
new_post = bound_form.save()
return redirect(new_post)
return render(request, 'blog/post_create_form.html', context={'form': bound_form})
class TagDetail(ObjectDetailMixin, View):
model = Tag
template = 'blog/tag_detail.html'
class TagCreate(View):
def get(self, request):
form = TagForm()
return render(request, 'blog/tag_create.html', context={'form': form})
def post(self, request):
bound_form = TagForm(request.POST)
print(bound_form)
if bound_form.is_valid():
new_tag = bound_form.save(commit=True)
return redirect(new_tag)
return render(request, 'blog/tag_create.html', context={'form': bound_form})
def tags_list(request):
tags = Tag.objects.all()
return render(request, 'blog/tags_list.html', context={'tags': tags})
|
[
"[email protected]"
] | |
a0d4235c7fc09361cbc96da609fe235b4bbd785b
|
772a996b8df470643cb04224d7b869437e8332a7
|
/Application/app.py
|
fc6620a0e8882472cbc260db38b21a59480d3f36
|
[] |
no_license
|
aniket312001/Car-Price-Predictor
|
a562b0c762759f10df74c05a4a5cf9b590438720
|
8e86fd9f5cf06c52a7694e0e0a3ae886350f5e50
|
refs/heads/main
| 2023-02-09T17:16:22.883562 | 2021-01-02T14:29:21 | 2021-01-02T14:29:21 | 326,198,649 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,234 |
py
|
from flask import Flask, render_template, request
from flask_cors import CORS
import pandas as pd
import numpy as np
import pickle
app = Flask(__name__)
CORS(app)
model = pickle.load(open('LinearRegressionModel.pkl','rb'))
df = pd.read_csv('Clean_car.csv')
@app.route('/',methods=['POST','GET'])
def home():
companies = sorted(df['company'].unique())
model_name = sorted(df['name'].unique())
year = sorted(df['year'].unique(),reverse=True)
fuel_type = df['fuel_type'].unique()
companies.insert(0,"Select Company")
return render_template('index.html', companies=companies, car_models=model_name, years=year, fuel_types=fuel_type)
@app.route('/predict',methods=['POST','GET'])
def pred():
company = request.form.get('company')
car_model = request.form.get('car_model')
year = int(request.form.get('year'))
fuel_type = request.form.get('fuel')
kms_driven = int(request.form.get('kms_driven'))
prediction = model.predict(pd.DataFrame([[car_model, company, year, kms_driven,fuel_type]], columns=['name', 'company', 'year', 'kms_driven', 'fuel_type']))
return str(np.round(prediction[0],2))
if __name__ == "__main__":
app.run(debug=True)
|
[
"[email protected]"
] | |
63ce31723463f996d20c3df361f6e287eeb675f4
|
208b6665723e6afe32af8a4b7e827a92d028db1b
|
/Ecom/ecommerce/products/models.py
|
da0f80abc5c02ebb1928916a32c2fee377fcfa92
|
[] |
no_license
|
gautamp114/django
|
3ce699473a5b9889317165298754ce06c3a5b4c8
|
5338d36e52c0835fbf502c1e3d283bb713dcb0a0
|
refs/heads/main
| 2023-02-09T20:15:55.281301 | 2021-01-07T07:03:59 | 2021-01-07T07:03:59 | 327,529,808 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,467 |
py
|
from django.db import models
# Create your models here.
class Product(models.Model):
title = models.CharField(max_length=120)
description = models.TextField(null=True, blank= True)
price = models.DecimalField(decimal_places=2,max_digits=20,default=30.00)
sales_price = models.DecimalField(decimal_places=2,max_digits=20,null=True, blank=True)
slug = models.SlugField(unique=True)
timestamp = models.DateTimeField(auto_now_add= True, auto_now=False)
updated = models.DateTimeField(auto_now_add= False, auto_now=True)
active = models.BooleanField(default=True)
def __str__(self):
return self.title
class Meta:
#to make title and slug unique together
unique_together = ('title', 'slug')
class ProductImage(models.Model):
product = models.ForeignKey(Product, on_delete=models.CASCADE)
image = models.ImageField(upload_to='products/images/')
featured = models.BooleanField(default=False)
thumbnail = models.BooleanField(default=False)
updated = models.DateTimeField(auto_now_add= False, auto_now=True)
def __str__(self):
return self.product.title
# class OrderProduct(models.Model):
# product = models.ForeignKey(Product, on_delete= models.CASCADE)
#
# def __str__(self):
# return self.product.title
#
# class Order(models.Model):
# items = models.ManyToManyField(OrderProduct)
# ordered_date = models.DateTimeField(auto_now_add=True)
# ordered = models.BooleanField(default=False)
#
# def __str__(self):
# return self.order.items
|
[
"[email protected]"
] | |
0bdb1aa44a3b4517aeed1e73574cbdff67c94608
|
22a42be59ba2c59e7bb92ee73e6ec5871d70b5cc
|
/manage.py
|
d4cb6e7b945178e15f34a6d93876b6eda9f36349
|
[] |
no_license
|
devimalka/djangoupload
|
7d5d44ca59260af372ba81666b4e84aa66c56483
|
3f25a45afe7dec676b7b4acf807ce433585ce7a3
|
refs/heads/master
| 2023-08-22T10:34:07.327978 | 2021-10-11T14:17:50 | 2021-10-11T14:17:50 | 415,957,932 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 666 |
py
|
#!/usr/bin/env python
"""Django's command-line utility for administrative tasks."""
import os
import sys
def main():
"""Run administrative tasks."""
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'sinhaladev.settings')
try:
from django.core.management import execute_from_command_line
except ImportError as exc:
raise ImportError(
"Couldn't import Django. Are you sure it's installed and "
"available on your PYTHONPATH environment variable? Did you "
"forget to activate a virtual environment?"
) from exc
execute_from_command_line(sys.argv)
if __name__ == '__main__':
main()
|
[
"[email protected]"
] | |
8743633783fdae100a42fa40825da1188212e3aa
|
bad9d9b5bfbc7c20a3daa73fea4273b333c778f1
|
/fileio_utils.py
|
5cd2fa4f011ea77d5127e1f6f6f39badf1d7fdfa
|
[] |
no_license
|
cmilke/vbf4b_coupling_scan_tools
|
acb9fef5e5c7ab51e6e87b8be4bf922cf7bdb0bc
|
c672525a880377fe44a9d50deea25febcb2bca73
|
refs/heads/master
| 2023-07-14T10:28:49.163247 | 2021-08-31T15:03:08 | 2021-08-31T15:03:08 | 319,711,860 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 6,438 |
py
|
import math
import numpy
import uproot
import inspect
Primary_coupling_file = 'basis_files/nnt_coupling_file_2021May_crypto.dat'
def retrieve_lhe_weights(ttree, kinematic_variable, bin_edges, stat_limit=None):
if stat_limit == None:
event_weights = numpy.array(ttree['weight'].array())
event_kinematics = numpy.array(ttree[kinematic_variable].array())
else:
event_weights = numpy.array(ttree['weight'].array())[:stat_limit]
event_kinematics = numpy.array(ttree[kinematic_variable].array())[:stat_limit]
weights = numpy.histogram(event_kinematics, weights=event_weights, bins=bin_edges)[0]
errors = numpy.zeros( len(weights) )
event_bins = numpy.digitize(event_kinematics,bin_edges)-1
for i in range(len(errors)):
binned_weights = event_weights[ event_bins == i ]
error2_array = binned_weights**2
error = math.sqrt( error2_array.sum() )
errors[i] = error
return weights, errors
def extract_lhe_truth_data(file_list, mHH_edges, normalize=False, stat_limit=30000, emulateSelection=False):
weight_list, error_list = [], []
for f in file_list:
f = f[0]
ttree = uproot.open(f)['tree']
if emulateSelection:
weights, errors = retrieve_lhe_weights_with_emulated_selection(ttree, mHH_edges)
else:
weights, errors = retrieve_lhe_weights(ttree, 'HH_m', mHH_edges, stat_limit=stat_limit)
if normalize:
norm = weights.sum()
weights /= norm
errors /= norm
weight_list.append(weights)
error_list.append(errors)
return weight_list, error_list
def extract_ntuple_events(ntuple, key=None, tree_name=None):
#tree_name = 'sig_highPtcat'
tree_name = 'sig'
rootfile = uproot.open(ntuple)
#DSID = rootfile['DSID']._members['fVal']
#nfiles = 1
#while( DSID / nfiles > 600050 ): nfiles += 1
#DSID = int(DSID / nfiles)
#print(ntuple, DSID)
ttree = rootfile[tree_name]
#if tree_name == 'sig':
#if True:
if False:
kinvals = ttree['m_hh'].array()
weights = ttree['mc_sf'].array()[:,0]
run_number = ttree['run_number'].array()
else: # Selections
pass_vbf_sel = ttree['pass_vbf_sel'].array()
x_wt_tag = ttree['X_wt_tag'].array() > 1.5
ntag = ttree['ntag'].array() >= 4
valid_event = numpy.logical_and.reduce( (pass_vbf_sel, x_wt_tag, ntag) )
kinvals = ttree['m_hh'].array()[valid_event]
weights = ttree['mc_sf'].array()[:,0][valid_event]
run_number = ttree['run_number'].array()[valid_event]
mc2015 = ( run_number < 296939 ) * 3.2
mc2016 = ( numpy.logical_and(296939 < run_number, run_number < 320000) ) * 24.6
mc2017 = ( numpy.logical_and(320000 < run_number, run_number < 350000) ) * 43.65
mc2018 = ( numpy.logical_and(350000 < run_number, run_number < 370000) ) * 58.45
all_years = mc2015 + mc2016 + mc2017 + mc2018
lumi_weights = weights * all_years
events = numpy.array([kinvals,lumi_weights])
return events
def retrieve_reco_weights(var_edges, reco_events):
event_weights = reco_events[1]
reco_weights = numpy.histogram(reco_events[0], bins=var_edges, weights=event_weights)[0]
reco_errors = numpy.zeros( len(reco_weights) )
event_bins = numpy.digitize(reco_events[0],var_edges)-1
for i in range(len(reco_errors)):
binned_weights = event_weights[ event_bins == i ]
error2_array = binned_weights**2
error = math.sqrt( error2_array.sum() )
reco_errors[i] = error
return [reco_weights, reco_errors]
def get_cutflow_values(filename, hist_name='VBF_FourTagCutflow'):
directory = uproot.open(filename)
cutflow_hist = directory[hist_name]
labeled_values = { k:v for k,v in zip(cutflow_hist.axis('x').labels(), cutflow_hist.values()) }
tree_name = 'sig'
ttree = directory[tree_name]
pass_vbf_sel = ttree['pass_vbf_sel'].array()
x_wt_tag = ttree['X_wt_tag'].array() > 1.5
ntag = ttree['ntag'].array() >= 4
valid_event = numpy.logical_and.reduce( (pass_vbf_sel, x_wt_tag, ntag) )
weights = ttree['mc_sf'].array()[:,0][valid_event]
final_weight = sum(weights)
labeled_values['Final'] = final_weight
labeled_values['FinalCount'] = len(weights)
return labeled_values
def get_combined_cutflow_values(parameter_list, data_files):
combined_cutflows = {}
for couplings in parameter_list:
for f in data_files[couplings]:
run_number = uproot.open(f)['sig']['run_number'].array()[0]
lumi_weight = None
if run_number < 296939: lumi_weight = 3.2 # MC2015
elif 296939 < run_number and run_number < 320000: lumi_weight = 24.6 # MC2016
elif 320000 < run_number and run_number < 350000: lumi_weight = 43.65 # MC2017
elif 350000 < run_number and run_number < 370000: lumi_weight = 58.45 # MC2018
else:
print("UNKNOWN RUN NUMBER!! -- " + str(run_number))
exit(1)
cutflows = get_cutflow_values(f)
lumi_weighted_cutflows = { key:val*lumi_weight if key != 'FinalCount' else val for key,val in cutflows.items() }
if couplings not in combined_cutflows:
combined_cutflows[couplings] = lumi_weighted_cutflows
else:
for key,val in lumi_weighted_cutflows.items():
combined_cutflows[couplings][key] += val
return combined_cutflows
def read_coupling_file(coupling_file=Primary_coupling_file):
data_files = {}
with open(coupling_file) as coupling_list:
for line in coupling_list:
if line.strip().startswith('#'): continue
linedata = line.split()
couplings = tuple([ float(p) for p in linedata[:3] ])
data_file = linedata[3]
if couplings not in data_files:
data_files[couplings] = [data_file]
else:
data_files[couplings].append(data_file)
return data_files
def get_events(parameter_list, data_files, reco=True):
events_list = []
for couplings in parameter_list:
new_events = []
for f in data_files[couplings]:
new_events.append( extract_ntuple_events(f,key='m_hh') )
events = numpy.concatenate(new_events, axis=1)
events_list.append(events)
return events_list
|
[
"[email protected]"
] | |
f48caaa4b5e38cd8d72a7c91e8ec01b32b5c33ae
|
c67a9c594112bc8bae81e9ab281630527cc6330d
|
/sync_modbus_tcp.py
|
282fe696b994f796cec7d0bb287101d2974b5da1
|
[] |
no_license
|
BhavyanshM/SCADA
|
79f54a24607ef857bcf1c8178e5aab7824c6cde3
|
6fc5a644b60bbf20be9d1ec6080d7e13f116c8cb
|
refs/heads/master
| 2020-04-12T01:51:03.055460 | 2019-05-10T14:59:38 | 2019-05-10T14:59:38 | 162,229,891 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 477 |
py
|
from pymodbus.client.sync import ModbusTcpClient
import time
UNIT = 0x00
client = ModbusTcpClient('192.168.0.40')
#client.write_coil(1, True)
f = open("log.txt", 'a')
f.write("\n----------------------------------------------------------------------\n\n"+time.ctime()+"\n\n")
while True:
rr = client.read_holding_registers(0, 8, unit=UNIT)
#result = client.read_coils(1,1)
print(rr.registers)
time.sleep(0.01)
f.write(str(rr.registers)+"\n")
f.close()
client.close()
|
[
"[email protected]"
] | |
5b0f51065868fd2232224cfb6f02ad122dca650b
|
cc5867196b2309fbfa5ba5f2beb935c512f26a54
|
/Orchestonks/test.py
|
a3257eb8a70dd5ff4baaeea8571d9fa8eb711120
|
[
"MIT"
] |
permissive
|
joy13975/Orchestonks
|
056544b8376f71a6139a2e618941100628d4b778
|
8b61ce87d0c5ad442a47edb1db2c10893fba5bab
|
refs/heads/main
| 2023-02-09T01:25:40.971761 | 2021-01-04T13:38:52 | 2021-01-04T13:38:52 | 326,351,738 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,480 |
py
|
import sys
import csv
from time import sleep
from datetime import datetime
import numpy as np
from notes import note_to_freq
from tone_player import TonePlayer
def main(file=''):
assert file
with open(file, 'r') as f:
data = list(csv.reader(f, delimiter=','))
with TonePlayer() as tp:
mat = np.asmatrix(data[1:])
# time_vals = [datetime.strptime('-'.join(row.A1), r'%Y%m%d-%H%M%S') for row in mat[:,2:4]]
open_vals, high_vals, low_vals, close_vals, vol_vals = np.asarray(mat[:,4:9].T.astype(float))
# pitch = 100.0 * (close_vals - open_vals) / close_vals
pitch = 100 * (close_vals - open_vals) / open_vals
duration = (close_vals - open_vals) / (high_vals - low_vals)
base_freq = note_to_freq('c4')
max_pitch = max(abs(pitch))
pitch_factor = 12 * 4 # 1 octaves = 12 notes
interval = 100
max_vol = max(vol_vals)
vol_cap = 1
for i, (p, d, v) in enumerate(zip(pitch, duration, vol_vals)):
h = round(pitch_factor * p / max_pitch)
freq = base_freq * (2.0 ** (h/12))
sound_vol = np.clip(v / (max_vol/2), 0, vol_cap)
print(f'i={i}, p={p:.4f}, d={d:.2f} h={h}, freq={freq:.2f}, sound_vol={sound_vol:.4f}')
tp.play(freq, duration=interval*8*d, volume=sound_vol)
sleep(interval/1000)
if __name__ == "__main__":
main(**dict(v.split('=') for v in sys.argv[1:]))
|
[
"[email protected]"
] | |
4be4119618f24eb4a854b957e68ff64726717d61
|
c27a95964b2740e1ec681b7068f52fb573d90321
|
/aliyun-python-sdk-cms/aliyunsdkcms/request/v20180308/QueryMetricListRequest.py
|
56216712133c7d35673a04cf20349e748613f843
|
[
"Apache-2.0"
] |
permissive
|
mysshget/aliyun-openapi-python-sdk
|
5cf0a0277cce9823966e93b875c23231d8b32c8a
|
333cdd97c894fea6570983e97d2f6236841bc7d3
|
refs/heads/master
| 2020-03-17T23:07:02.942583 | 2018-05-17T09:50:53 | 2018-05-17T09:50:53 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,912 |
py
|
# 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.
from aliyunsdkcore.request import RpcRequest
class QueryMetricListRequest(RpcRequest):
def __init__(self):
RpcRequest.__init__(self, 'Cms', '2018-03-08', 'QueryMetricList','cms')
def get_Cursor(self):
return self.get_query_params().get('Cursor')
def set_Cursor(self,Cursor):
self.add_query_param('Cursor',Cursor)
def get_callby_cms_owner(self):
return self.get_query_params().get('callby_cms_owner')
def set_callby_cms_owner(self,callby_cms_owner):
self.add_query_param('callby_cms_owner',callby_cms_owner)
def get_ResourceOwnerId(self):
return self.get_query_params().get('ResourceOwnerId')
def set_ResourceOwnerId(self,ResourceOwnerId):
self.add_query_param('ResourceOwnerId',ResourceOwnerId)
def get_Period(self):
return self.get_query_params().get('Period')
def set_Period(self,Period):
self.add_query_param('Period',Period)
def get_Length(self):
return self.get_query_params().get('Length')
def set_Length(self,Length):
self.add_query_param('Length',Length)
def get_Project(self):
return self.get_query_params().get('Project')
def set_Project(self,Project):
self.add_query_param('Project',Project)
def get_EndTime(self):
return self.get_query_params().get('EndTime')
def set_EndTime(self,EndTime):
self.add_query_param('EndTime',EndTime)
def get_Express(self):
return self.get_query_params().get('Express')
def set_Express(self,Express):
self.add_query_param('Express',Express)
def get_StartTime(self):
return self.get_query_params().get('StartTime')
def set_StartTime(self,StartTime):
self.add_query_param('StartTime',StartTime)
def get_Metric(self):
return self.get_query_params().get('Metric')
def set_Metric(self,Metric):
self.add_query_param('Metric',Metric)
def get_Page(self):
return self.get_query_params().get('Page')
def set_Page(self,Page):
self.add_query_param('Page',Page)
def get_Dimensions(self):
return self.get_query_params().get('Dimensions')
def set_Dimensions(self,Dimensions):
self.add_query_param('Dimensions',Dimensions)
|
[
"[email protected]"
] | |
7629cbace4c46b36ec498427fe9085047beb7f67
|
9f27ac0e633f1a75a193932eff91c56943deda58
|
/Week2/Day2/ParenthesisMatching.py
|
15884b572ac4e17b281539268417f6a1dccda3b5
|
[] |
no_license
|
afrinh/CompetitiveProgramming
|
c5a1b8c617dbd8f3bddb1323c4291d419c7bdc8f
|
2df8e25698e5ecd54c874e669f2ad0eb00c5513c
|
refs/heads/master
| 2020-03-22T00:01:28.737847 | 2018-07-21T09:28:22 | 2018-07-21T09:28:22 | 139,219,980 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,047 |
py
|
import unittest
def get_closing_paren(sentence, opening_paren_index):
open_nested_parens = 0
position = opening_paren_index + 1
for position in range(opening_paren_index + 1, len(sentence)):
char = sentence[position]
if char == '(':
open_nested_parens += 1
elif char == ')':
if open_nested_parens == 0:
return position
else:
open_nested_parens -= 1
raise Exception("No closing parenthesis :(")
# Tests
class Test(unittest.TestCase):
def test_all_openers_then_closers(self):
actual = get_closing_paren('((((()))))', 2)
expected = 7
self.assertEqual(actual, expected)
def test_mixed_openers_and_closers(self):
actual = get_closing_paren('()()((()()))', 5)
expected = 10
self.assertEqual(actual, expected)
def test_no_matching_closer(self):
with self.assertRaises(Exception):
get_closing_paren('()(()', 2)
unittest.main(verbosity=2)
|
[
"[email protected]"
] | |
021e4be28d20fb9b8e7a62b502f7cba74dea51df
|
6bf5db308a2ced233b095c955822ed0c5aba44e9
|
/mcs435_(nonlinear_optimization)/Assignment_1/venv/bin/pip
|
5c63b385f6926b13027fcf15157ebda99d85fe89
|
[] |
no_license
|
AlecHarb/school_projects
|
756e2f7f5a7435d9180975069c14391e80347fcc
|
d0c57fe34a3de0f558475da9f567511a17fdc70f
|
refs/heads/main
| 2023-03-09T10:53:15.099530 | 2021-02-28T08:35:52 | 2021-02-28T08:35:52 | 342,484,221 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 411 |
#!/Users/harberbarber/Python/MCS435/Assignment_1/venv/bin/python
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==19.0.3','console_scripts','pip'
__requires__ = 'pip==19.0.3'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('pip==19.0.3', 'console_scripts', 'pip')()
)
|
[
""
] | ||
6fb6e1524af5bc5732e4bc123217c972f05010a3
|
cf9b83d667433a5f912f8981357483197624983d
|
/editors/content/admin.py
|
75694e4aaca1e16700897e8f2668a55b4381efb9
|
[
"Apache-2.0"
] |
permissive
|
LeaseMagnetsTeam/editors.art
|
08d13e58a17c9930efe78f99d4dc4e25898612f3
|
778ca76439da798f3b7ffbac5b83f3e85b4f4fca
|
refs/heads/main
| 2023-06-26T17:17:52.336540 | 2021-07-26T00:09:30 | 2021-07-26T00:09:30 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 101 |
py
|
from django.contrib import admin
from editors.content.models import Edit
admin.site.register(Edit)
|
[
"[email protected]"
] | |
1e9ed7185ff402c3b678869fee7e4b503fb7d6bd
|
e75c5288579e5866f9618dbcd29d0485b1bddbee
|
/account/forms.py
|
3510e0152fb404abfeabdc838eb9bc3d36d85452
|
[] |
no_license
|
hkhitesh25/Learnan
|
2ae2e0690a1eacfe4d25511c0b7a789553b60516
|
a8d79141786fdd5aeb66f9127283d128ce43db02
|
refs/heads/master
| 2021-07-09T14:36:57.983818 | 2017-07-31T15:59:52 | 2017-07-31T15:59:52 | 98,341,929 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,038 |
py
|
from django.contrib.auth.models import User
from django import forms
from .models import Profile
class UserRegistrationForm(forms.ModelForm):
password = forms.CharField(label='Password',
widget=forms.PasswordInput)
password2 = forms.CharField(label='Password Again',
widget=forms.PasswordInput)
#stream = forms.ChoiceField(choices=CHOICES, required=True, label='Stream')
class Meta:
model = User
fields = ('username', 'first_name', 'email')
CHOICES = (('IIT-JEE', 'IIT-JEE'),('Medical','Medical'),('Commerce','Commerce'))
class ProfileForm(forms.ModelForm):
stream= forms.ChoiceField(choices=CHOICES, required=True, label='Stream')
class Meta:
model = Profile
fields = ('stream',)
def clean_password2(self):
cd = self.cleaned_data
if cd['password'] != cd['password2']:
raise forms.ValidationError('Passwords don\'t match.')
return cd['password2']
class LoginForm(forms.Form):
username=forms.CharField()
password=forms.CharField(widget=forms.PasswordInput)
|
[
"[email protected]"
] | |
254565bcaaa357e4dd2fd04c39baf24bc29f0943
|
caef77c22623f8cb660f614282a5ada03223ae8c
|
/copyScript.py
|
013bc275e19244992993a5e01ff85c4a8a624500
|
[] |
no_license
|
dimioan/administration_pyscripts
|
45440960398127783dba4c8aee2739c1f654bae0
|
09f4a9b91ee3543d9147f348b8320f58b197d983
|
refs/heads/master
| 2021-01-13T00:15:21.547921 | 2016-01-01T12:03:46 | 2016-01-01T12:03:46 | 48,877,047 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 945 |
py
|
# the destination folder must not already exist!!!
import shutil
import time
import sys
def copy_directories(source, destination):
shutil.copytree(source, destination)
toolbar_width = 50
# setup toolbar
sys.stdout.write("[%s]" % (" " * toolbar_width))
sys.stdout.flush()
sys.stdout.write("\b" * (toolbar_width+1)) # return to start of line, after '['
for i in xrange(toolbar_width):
time.sleep(0.1) # do real work here
# update the bar
sys.stdout.write("-")
sys.stdout.flush()
sys.stdout.write("\nDONE!!!!!!!\n")
source_dir1= '/home/bluesdio/Documents/Attiki'
destination_dir1 = '/home/bluesdio/Documents/My_Python/destination/test1'
source_dir2 = '/home/bluesdio/Documents/My_Python/Pele'
destination_dir2 = '/home/bluesdio/Documents/My_Python/destination/test2'
copy_directories(source_dir1, destination_dir1)
time.sleep(3)
copy_directories(source_dir2, destination_dir2)
|
[
"[email protected]"
] | |
06374019a4e5f98b7b8f52c6806f9f9824ff284d
|
0fb06326f2d17f054699a9943e124704cd824162
|
/Project 1 - Air Quality Index/Final_dataset_generator.py
|
03cd353808ff2f1f3cf71c49924a6f8017beb777
|
[] |
no_license
|
AvAkanksh/Data-Science-Projects
|
9cc75e4ad509e33a51c2640ae7dead7c4b6619dc
|
b16177cca4d1bfcd3ed9057d3dbc6bf24043db61
|
refs/heads/main
| 2023-05-06T06:24:06.179480 | 2021-05-30T09:30:28 | 2021-05-30T09:30:28 | 370,443,616 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,990 |
py
|
from Plot_AQI import avg_data_2013,avg_data_2014,avg_data_2015,avg_data_2016
import requests
import sys
import pandas as pd
from bs4 import BeautifulSoup
import os
import csv
def met_data(month, year):
file_html = open('Data/Html_data/{}/{}.html'.format(year,month), 'rb')
plain_text = file_html.read()
tempD = []
finalD = []
soup = BeautifulSoup(plain_text, "lxml")
for table in soup.findAll('table', {'class': 'medias mensuales numspan'}):
for tbody in table:
for tr in tbody:
a = tr.get_text()
tempD.append(a)
rows = len(tempD) / 15
for _ in range(round(rows)):
newtempD = []
for __ in range(15):
newtempD.append(tempD[0])
tempD.pop(0)
finalD.append(newtempD)
length = len(finalD)
finalD.pop(length - 1)
finalD.pop(0)
for a in range(len(finalD)):
finalD[a].pop(6)
finalD[a].pop(13)
finalD[a].pop(12)
finalD[a].pop(11)
finalD[a].pop(10)
finalD[a].pop(9)
finalD[a].pop(0)
return finalD
def data_combine(year, cs):
for a in pd.read_csv('Data/Real-Data/real_' + str(year) + '.csv', chunksize=cs):
df = pd.DataFrame(data=a)
mylist = df.values.tolist()
return mylist
if __name__ == "__main__":
if not os.path.exists("Data/Real-Data"):
os.makedirs("Data/Real-Data")
for year in range(2013, 2017):
final_data = []
with open('Data/Real-Data/real_' + str(year) + '.csv', 'w') as csvfile:
wr = csv.writer(csvfile, dialect='excel')
wr.writerow(
['T', 'TM', 'Tm', 'SLP', 'H', 'VV', 'V', 'VM', 'PM 2.5'])
for month in range(1, 13):
temp = met_data(month, year)
final_data = final_data + temp
pm = getattr(sys.modules[__name__], 'avg_data_{}'.format(year))()
if len(pm) == 364:
pm.insert(364, '-')
for i in range(len(final_data)-1):
final_data[i].insert(8, pm[i])
with open('Data/Real-Data/real_' + str(year) + '.csv', 'a') as csvfile:
wr = csv.writer(csvfile, dialect='excel')
for row in final_data:
flag = 0
for elem in row:
if elem == "" or elem == "-":
flag = 1
if flag != 1:
wr.writerow(row)
data_2013 = data_combine(2013, 600)
data_2014 = data_combine(2014, 600)
data_2015 = data_combine(2015, 600)
data_2016 = data_combine(2016, 600)
total=data_2013+data_2014+data_2015+data_2016
with open('Data/Real-Data/Real_Combine.csv', 'w') as csvfile:
wr = csv.writer(csvfile, dialect='excel')
wr.writerow(
['T', 'TM', 'Tm', 'SLP', 'H', 'VV', 'V', 'VM', 'PM 2.5'])
wr.writerows(total)
df=pd.read_csv('Data/Real-Data/Real_Combine.csv')
|
[
"[email protected]"
] | |
5998c8bd953812e35fce547ed6dfa101b44f1a4a
|
577b733677369f9f02f0c13b0a94171bd633f7c7
|
/controllerCode/js_linux.py
|
78936b415080c9f2ebd25e9c07f4dc5c61aa6e8c
|
[] |
no_license
|
hernandez-jesus/Harvard-REU-2017
|
41cdff6fd8357e2b34a0ef5350ff0b2ef3862211
|
e32138f3e5a50a3f02b9dd80cba7f86abce9c9c6
|
refs/heads/master
| 2021-06-23T14:50:11.428818 | 2017-08-16T00:20:25 | 2017-08-16T00:20:25 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 5,822 |
py
|
# Released by rdb under the Unlicense (unlicense.org)
# Based on information from:
# https://www.kernel.org/doc/Documentation/input/joystick-api.txt
import os, struct, array
import fcntl
from fcntl import ioctl
# Iterate over the joystick devices.
print('Available devices:')
for fn in os.listdir('/dev/input'):
if fn.startswith('js'):
print(' /dev/input/%s' % fn)
# We'll store the states here.
axis_states = {}
button_states = {}
# Axis and button mapping are joystick-specific
# Joystick (DragonRise Inc. Generic USB Joystick ) has 7 axes (X, Y, Z, Rx, Ry, Hat0X, Hat0Y)
# and 12 buttons (Trigger, ThumbBtn, ThumbBtn2, TopBtn, TopBtn2, PinkieBtn, BaseBtn, BaseBtn2, BaseBtn3, BaseBtn4, BaseBtn5, BaseBtn6).
# Run jscal -q to see the address mappings. Current output:
# jscal -u 7,0,1,2,3,4,16,17,12,288,289,290,291,292,293,294,295,296,297,298,299 /dev/input/js0
axis_names = {
0x00 : 'axis0', # Binary L/R axis for 4-way button
0x01 : 'axis1', # right joystick analog input L/R
0x02 : 'axis2', # right joystick analog input U/D
0x03 : 'axis3', # Binary U/D axis for 4-way button
}
button_names = {
0x120 : 'but0', # Triangle AND right joystick up/down
0x121 : 'but1', # Circle AND right joystick left/right
0x122 : 'but2', # Cross AND right joystick up/down
0x123 : 'but3', # Square AND right joystick left/right
0x124 : 'but4', # L2
0x125 : 'but5', # R2
0x126 : 'but6', # L1
0x127 : 'but7', # R1
0x128 : 'but8', # select
0x129 : 'but9', # start
0x130 : 'but10',
0x131 : 'but11', # analog - sends no event output
}
axis_map = []
button_map = []
# Open the joystick device.
fn = '/dev/input/js0'
print('Opening %s...' % fn)
jsdev = open(fn, 'rb')
# set to non-blocking!!!
flag = fcntl.fcntl(jsdev, fcntl.F_GETFD)
fcntl.fcntl(jsdev, fcntl.F_SETFL, flag | os.O_NONBLOCK)
# Get the device name.
# Get number of axes and buttons.
buf = array.array('B', [0])
ioctl(jsdev, 0x80016a11, buf) # JSIOCGAXES
num_axes = buf[0]
buf = array.array('B', [0])
ioctl(jsdev, 0x80016a12, buf) # JSIOCGBUTTONS
num_buttons = buf[0]
# Get the axis map.
buf = array.array('B', [0] * 0x40)
ioctl(jsdev, 0x80406a32, buf) # JSIOCGAXMAP
for axis in buf[:num_axes]:
axis_name = axis_names.get(axis, 'unknown(0x%02x)' % axis)
axis_map.append(axis_name)
axis_states[axis_name] = 0.0
# Get the button map.
buf = array.array('H', [0] * 200)
ioctl(jsdev, 0x80406a34, buf) # JSIOCGBTNMAP
for btn in buf[:num_buttons]:
btn_name = button_names.get(btn, 'unknown(0x%03x)' % btn)
button_map.append(btn_name)
button_states[btn_name] = 0
print('{:d} axes found '.format(num_axes))
print('{:d} buttons found '.format(num_buttons))
# Main control loop
# The following code is event-based. That means the values are ONLY updated on change.
# It might be more intuitive to update all buttons/axes in a continuous loop.
# how this works: every time something is pressed on the joystick, it logs an EVENT
# in the EVENT QUEUE
# We continuously read from the event queue. HOWEVER this means that if a value isn't changed,
# we don't see it in the queue.
# It MAY be possible to poll joystick values continuously (check joystick API and maybe evdev API?)
# but in the meantime we can write code that APPEARS continuous even though it is event-based
def main():
running = True
# Observe that axis map and button map contain the CURRENT STATE of each axis.
while running:
# To see a continuously updated list of the current values of all buttons and axes, uncomment the below
# print current controller state:
#for butt in button_map:
# print("{name} : {val} ".format(name=butt, val=button_states[butt]))
#for ax in axis_map:
# print("{name} : {val} ".format(name=ax, val=axis_states[ax]))
# Use current joystick state to control robot
# Axis 2 is the only analog axis BUT can act as 2 axes by combining with buttons
# Axis 2 can be controlled by:
# L/R on left toggle
# U/D on right toggle (this also toggles the states of buttons 0 or 2)
# Example code:
try:
# read
evbuf = jsdev.read(8)
if evbuf:
time, value, intype, number = struct.unpack('IhBB', evbuf)
if intype & 0x01:
button = button_map[number]
if button:
button_states[button] = value
if intype & 0x02:
axis = axis_map[number]
if axis:
fvalue = value / 32767.0
axis_states[axis] = fvalue
except:
pass
# get value from axis 2
diraxis = axis_map[2]
ax2val = axis_states[diraxis]
# check button states
butt0 = button_map[0]
butt2 = button_map[2]
# There are several methods to determine which combination of button/axes has been set!
# this is just one example
if (button_states[butt0] or button_states[butt2]):
# we should be moving forwards or backwards
if ax2val > 0:
print("Going backwards at {} ".format(ax2val))
if ax2val < 0:
print ("Going forwards at {} ".format(ax2val))
else: # we should be turning left or right
if ax2val < 0:
print("Turning left at {} ".format(ax2val))
elif ax2val > 0 :
print("Turning right at {} ".format(ax2val))
# Things to think about:
# how can we change between turning on the spot and turning while moving forward or back?
# what other controls might be useful?
if __name__ == '__main__':
main()
|
[
"[email protected]"
] | |
4ff7317dbd5aec4a5122628aade19c6d7efe7ce4
|
13e3212fe80ab14cf27164045f8d311c2ee52c29
|
/Shop/migrations/0002_auto_20210527_0745.py
|
2e3fd111af36715bdd86c3abbc83592f6147a8d4
|
[] |
no_license
|
prantacse4/MobileBazar
|
c209915240017a9bd4e07485bf6595eb0ecfbda1
|
a69a42b1658532592b19944fd6f25bfb615644c3
|
refs/heads/master
| 2023-05-14T08:46:50.641283 | 2021-06-03T11:34:04 | 2021-06-03T11:34:04 | 369,074,938 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,558 |
py
|
# Generated by Django 3.1.6 on 2021-05-27 01:45
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Shop', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Slider',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('image', models.ImageField(upload_to='uploaded_image/sliders')),
],
),
migrations.AlterField(
model_name='brand',
name='id',
field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'),
),
migrations.AlterField(
model_name='cart',
name='id',
field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'),
),
migrations.AlterField(
model_name='checkout',
name='id',
field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'),
),
migrations.AlterField(
model_name='ordered',
name='id',
field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'),
),
migrations.AlterField(
model_name='product',
name='id',
field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'),
),
]
|
[
"[email protected]"
] | |
3a8c2a36ba70b28a542910c484faf84b6338657e
|
2196d3798497fc7d3d80cd02b008dbb35dbd64d8
|
/d01/ex03/capital_city.py
|
43c2172c50975816070fc588eec89b5d5b1f9cc8
|
[] |
no_license
|
avallete/Python-Django-Pool
|
d59965e1c6315520da54205848d4f59bf05a9928
|
cee52fe4b30cbc53135caf89a8a8843842e2daeb
|
refs/heads/master
| 2021-03-30T06:36:37.546122 | 2016-10-13T15:08:40 | 2016-10-13T15:08:40 | 69,851,733 | 4 | 2 | null | null | null | null |
UTF-8
|
Python
| false | false | 511 |
py
|
# -*- coding: utf-8 -*-
import sys
def run(state):
states = {
"Oregon" : "OR",
"Alabama" : "AL",
"New Jersey": "NJ",
"Colorado" : "CO"
}
capital_cities = {
"OR": "Salem",
"AL": "Montgomery",
"NJ": "Trenton",
"CO": "Denver"
}
if state in states.keys():
print(capital_cities[states[state]])
else:
print("Unknown state")
if __name__ == '__main__':
if (len(sys.argv) == 2):
run(sys.argv[1])
|
[
"[email protected]"
] | |
5b3a2e285dac25d8fbaf09b7b6ce6bb8623be7d1
|
6b9084d234c87d7597f97ec95808e13f599bf9a1
|
/training/old/detr/eval_step.py
|
14c769d423b9428725a45145e5fecae4336afb35
|
[] |
no_license
|
LitingLin/ubiquitous-happiness
|
4b46234ce0cb29c4d27b00ec5a60d3eeb52c26fc
|
aae2d764e136ca4a36c054212b361dd7e8b22cba
|
refs/heads/main
| 2023-07-13T19:51:32.227633 | 2021-08-03T16:02:03 | 2021-08-03T16:02:03 | 316,664,903 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,953 |
py
|
import torch
import Utils.detr_misc as utils
from evaluation.evaluator.coco import CocoEvaluator
@torch.no_grad()
def evaluate(model, criterion, postprocessors, data_loader, base_ds, device, output_dir):
model.eval()
criterion.eval()
metric_logger = utils.MetricLogger(delimiter=" ")
metric_logger.add_meter('class_error', utils.SmoothedValue(window_size=1, fmt='{value:.2f}'))
header = 'Test:'
iou_types = tuple(k for k in ('segm', 'bbox') if k in postprocessors.keys())
coco_evaluator = CocoEvaluator(base_ds, iou_types)
# coco_evaluator.coco_eval[iou_types[0]].params.iouThrs = [0, 0.1, 0.5, 0.75]
for samples, targets in metric_logger.log_every(data_loader, 10, header):
samples = samples.to(device)
targets = [{k: v.to(device) for k, v in t.items()} for t in targets]
outputs = model(samples)
loss_dict = criterion(outputs, targets)
weight_dict = criterion.weight_dict
# reduce losses over all GPUs for logging purposes
loss_dict_reduced = utils.reduce_dict(loss_dict)
loss_dict_reduced_scaled = {k: v * weight_dict[k]
for k, v in loss_dict_reduced.items() if k in weight_dict}
loss_dict_reduced_unscaled = {f'{k}_unscaled': v
for k, v in loss_dict_reduced.items()}
metric_logger.update(loss=sum(loss_dict_reduced_scaled.values()),
**loss_dict_reduced_scaled,
**loss_dict_reduced_unscaled)
metric_logger.update(class_error=loss_dict_reduced['class_error'])
orig_target_sizes = torch.stack([t["orig_size"] for t in targets], dim=0)
results = postprocessors['bbox'](outputs, orig_target_sizes)
if 'segm' in postprocessors.keys():
target_sizes = torch.stack([t["size"] for t in targets], dim=0)
results = postprocessors['segm'](results, outputs, orig_target_sizes, target_sizes)
res = {target['image_id'].item(): output for target, output in zip(targets, results)}
if coco_evaluator is not None:
coco_evaluator.update(res)
# gather the stats from all processes
metric_logger.synchronize_between_processes()
print("Averaged stats:", metric_logger)
if coco_evaluator is not None:
coco_evaluator.synchronize_between_processes()
# accumulate predictions from all images
if coco_evaluator is not None:
coco_evaluator.accumulate()
coco_evaluator.summarize()
stats = {k: meter.global_avg for k, meter in metric_logger.meters.items()}
if coco_evaluator is not None:
if 'bbox' in postprocessors.keys():
stats['coco_eval_bbox'] = coco_evaluator.coco_eval['bbox'].stats.tolist()
if 'segm' in postprocessors.keys():
stats['coco_eval_masks'] = coco_evaluator.coco_eval['segm'].stats.tolist()
return stats, coco_evaluator
|
[
"[email protected]"
] | |
4fee8226361947afb1ef025ada908dc3ad5f97a7
|
163bbb4e0920dedd5941e3edfb2d8706ba75627d
|
/Code/CodeRecords/2526/48083/309473.py
|
a8d534b2af549d2506c477c229047c81420f23b7
|
[] |
no_license
|
AdamZhouSE/pythonHomework
|
a25c120b03a158d60aaa9fdc5fb203b1bb377a19
|
ffc5606817a666aa6241cfab27364326f5c066ff
|
refs/heads/master
| 2022-11-24T08:05:22.122011 | 2020-07-28T16:21:24 | 2020-07-28T16:21:24 | 259,576,640 | 2 | 1 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,340 |
py
|
from typing import List
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def getAllElements(self, root1: TreeNode, root2: TreeNode) -> List[int]:
res = []
def inOrder(root):
if root:
inOrder(root.left)
res.append(root.val)
inOrder(root.right)
inOrder(root1)
inOrder(root2)
res = filter(None, res) #
return sorted(map(int,res))
def str2arr(self,t):
t = t[1:-1]
t = t.split(',')
return t
def creatTree(self,arr):
nodes = []
for a in arr:
node = TreeNode(a)
nodes.append(node)
parentNum = len(arr) // 2 - 1
for i in range(parentNum+1):
leftIndex = 2 * i + 1
rightIndex = 2 * i + 2
if nodes[leftIndex].val!='null':
nodes[i].left = nodes[leftIndex]
if rightIndex < len(arr) and nodes[rightIndex].val!='null':
nodes[i].right = nodes[rightIndex]
return nodes[0]
s = Solution()
t1 = input()
t2 = input()
t1 = s.str2arr(t1)
t2 = s.str2arr(t2)
root1 = s.creatTree(t1)
root2 = s.creatTree(t2)
res = s.getAllElements(root1, root2)
print(res)
|
[
"[email protected]"
] | |
beb51d68a2bfda9d9043f37aca7dfab32345ec5d
|
0c66e605e6e4129b09ea14dbb6aa353d18aaa027
|
/diventi/blog/migrations/0011_auto_20200502_1924.py
|
cafdf11a5790066124e2ac11c41e6c0b8e07572d
|
[
"Apache-2.0"
] |
permissive
|
flavoi/diventi
|
58fbc8c947f387cbcc1ce607878a59a6f2b72313
|
c0b1efe2baa3ff816d6ee9a8e86623f297973ded
|
refs/heads/master
| 2023-07-20T09:32:35.897661 | 2023-07-11T19:44:26 | 2023-07-11T19:44:26 | 102,959,477 | 2 | 1 |
Apache-2.0
| 2023-02-08T01:03:17 | 2017-09-09T14:10:51 |
Python
|
UTF-8
|
Python
| false | false | 612 |
py
|
# Generated by Django 2.2.12 on 2020-05-02 17:24
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('blog', '0010_auto_20200229_1600'),
]
operations = [
migrations.AlterField(
model_name='blogcover',
name='color',
field=models.CharField(blank=True, choices=[('info', 'Blue'), ('primary', 'Rose'), ('danger', 'Red'), ('warning', 'Yellow'), ('success', 'Green'), ('default', 'Gray'), ('dark', 'Black'), ('light', 'White')], default='warning', max_length=30, verbose_name='color'),
),
]
|
[
"[email protected]"
] | |
5337ceda808da03a25bf931d536938d1881c73a9
|
f576f0ea3725d54bd2551883901b25b863fe6688
|
/sdk/paloaltonetworks/azure-mgmt-paloaltonetworksngfw/azure/mgmt/paloaltonetworksngfw/aio/operations/_firewalls_operations.py
|
8cc8d9e5ce7f000a913bdbed272f44375a317198
|
[
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-2.1-or-later"
] |
permissive
|
Azure/azure-sdk-for-python
|
02e3838e53a33d8ba27e9bcc22bd84e790e4ca7c
|
c2ca191e736bb06bfbbbc9493e8325763ba990bb
|
refs/heads/main
| 2023-09-06T09:30:13.135012 | 2023-09-06T01:08:06 | 2023-09-06T01:08:06 | 4,127,088 | 4,046 | 2,755 |
MIT
| 2023-09-14T21:48:49 | 2012-04-24T16:46:12 |
Python
|
UTF-8
|
Python
| false | false | 50,367 |
py
|
# pylint: disable=too-many-lines
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
from io import IOBase
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
from azure.core.async_paging import AsyncItemPaged, AsyncList
from azure.core.exceptions import (
ClientAuthenticationError,
HttpResponseError,
ResourceExistsError,
ResourceNotFoundError,
ResourceNotModifiedError,
map_error,
)
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import AsyncHttpResponse
from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from azure.core.tracing.decorator_async import distributed_trace_async
from azure.core.utils import case_insensitive_dict
from azure.mgmt.core.exceptions import ARMErrorFormat
from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
from ... import models as _models
from ..._vendor import _convert_request
from ...operations._firewalls_operations import (
build_create_or_update_request,
build_delete_request,
build_get_global_rulestack_request,
build_get_log_profile_request,
build_get_request,
build_get_support_info_request,
build_list_by_resource_group_request,
build_list_by_subscription_request,
build_save_log_profile_request,
build_update_request,
)
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
class FirewallsOperations:
"""
.. warning::
**DO NOT** instantiate this class directly.
Instead, you should access the following operations through
:class:`~azure.mgmt.paloaltonetworksngfw.aio.PaloAltoNetworksNgfwMgmtClient`'s
:attr:`firewalls` attribute.
"""
models = _models
def __init__(self, *args, **kwargs) -> None:
input_args = list(args)
self._client = input_args.pop(0) if input_args else kwargs.pop("client")
self._config = input_args.pop(0) if input_args else kwargs.pop("config")
self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
@distributed_trace
def list_by_subscription(self, **kwargs: Any) -> AsyncIterable["_models.FirewallResource"]:
"""List FirewallResource resources by subscription ID.
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FirewallResource or the result of cls(response)
:rtype:
~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.paloaltonetworksngfw.models.FirewallResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.FirewallResourceListResult] = kwargs.pop("cls", None)
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
def prepare_request(next_link=None):
if not next_link:
request = build_list_by_subscription_request(
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self.list_by_subscription.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
else:
# make call to next link with the client's api-version
_parsed_next_link = urllib.parse.urlparse(next_link)
_next_request_params = case_insensitive_dict(
{
key: [urllib.parse.quote(v) for v in value]
for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
}
)
_next_request_params["api-version"] = self._config.api_version
request = HttpRequest(
"GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
request.method = "GET"
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize("FirewallResourceListResult", pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem) # type: ignore
return deserialized.next_link or None, AsyncList(list_of_elem)
async def get_next(next_link=None):
request = prepare_request(next_link)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return AsyncItemPaged(get_next, extract_data)
list_by_subscription.metadata = {
"url": "/subscriptions/{subscriptionId}/providers/PaloAltoNetworks.Cloudngfw/firewalls"
}
@distributed_trace
def list_by_resource_group(
self, resource_group_name: str, **kwargs: Any
) -> AsyncIterable["_models.FirewallResource"]:
"""List FirewallResource resources by resource group.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FirewallResource or the result of cls(response)
:rtype:
~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.paloaltonetworksngfw.models.FirewallResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.FirewallResourceListResult] = kwargs.pop("cls", None)
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
def prepare_request(next_link=None):
if not next_link:
request = build_list_by_resource_group_request(
resource_group_name=resource_group_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self.list_by_resource_group.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
else:
# make call to next link with the client's api-version
_parsed_next_link = urllib.parse.urlparse(next_link)
_next_request_params = case_insensitive_dict(
{
key: [urllib.parse.quote(v) for v in value]
for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
}
)
_next_request_params["api-version"] = self._config.api_version
request = HttpRequest(
"GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
request.method = "GET"
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize("FirewallResourceListResult", pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem) # type: ignore
return deserialized.next_link or None, AsyncList(list_of_elem)
async def get_next(next_link=None):
request = prepare_request(next_link)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return AsyncItemPaged(get_next, extract_data)
list_by_resource_group.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls"
}
@distributed_trace_async
async def get(self, resource_group_name: str, firewall_name: str, **kwargs: Any) -> _models.FirewallResource:
"""Get a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: FirewallResource or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResource
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.FirewallResource] = kwargs.pop("cls", None)
request = build_get_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self.get.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize("FirewallResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}"
}
async def _create_or_update_initial(
self, resource_group_name: str, firewall_name: str, resource: Union[_models.FirewallResource, IO], **kwargs: Any
) -> _models.FirewallResource:
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.FirewallResource] = kwargs.pop("cls", None)
content_type = content_type or "application/json"
_json = None
_content = None
if isinstance(resource, (IOBase, bytes)):
_content = resource
else:
_json = self._serialize.body(resource, "FirewallResource")
request = build_create_or_update_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
content_type=content_type,
json=_json,
content=_content,
template_url=self._create_or_update_initial.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200, 201]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if response.status_code == 200:
deserialized = self._deserialize("FirewallResource", pipeline_response)
if response.status_code == 201:
deserialized = self._deserialize("FirewallResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {}) # type: ignore
return deserialized # type: ignore
_create_or_update_initial.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}"
}
@overload
async def begin_create_or_update(
self,
resource_group_name: str,
firewall_name: str,
resource: _models.FirewallResource,
*,
content_type: str = "application/json",
**kwargs: Any
) -> AsyncLROPoller[_models.FirewallResource]:
"""Create a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param resource: Resource create parameters. Required.
:type resource: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResource
:keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
Default value is "application/json".
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either FirewallResource or the result of
cls(response)
:rtype:
~azure.core.polling.AsyncLROPoller[~azure.mgmt.paloaltonetworksngfw.models.FirewallResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
@overload
async def begin_create_or_update(
self,
resource_group_name: str,
firewall_name: str,
resource: IO,
*,
content_type: str = "application/json",
**kwargs: Any
) -> AsyncLROPoller[_models.FirewallResource]:
"""Create a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param resource: Resource create parameters. Required.
:type resource: IO
:keyword content_type: Body Parameter content-type. Content type parameter for binary body.
Default value is "application/json".
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either FirewallResource or the result of
cls(response)
:rtype:
~azure.core.polling.AsyncLROPoller[~azure.mgmt.paloaltonetworksngfw.models.FirewallResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
@distributed_trace_async
async def begin_create_or_update(
self, resource_group_name: str, firewall_name: str, resource: Union[_models.FirewallResource, IO], **kwargs: Any
) -> AsyncLROPoller[_models.FirewallResource]:
"""Create a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param resource: Resource create parameters. Is either a FirewallResource type or a IO type.
Required.
:type resource: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResource or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either FirewallResource or the result of
cls(response)
:rtype:
~azure.core.polling.AsyncLROPoller[~azure.mgmt.paloaltonetworksngfw.models.FirewallResource]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.FirewallResource] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
cont_token: Optional[str] = kwargs.pop("continuation_token", None)
if cont_token is None:
raw_result = await self._create_or_update_initial(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
resource=resource,
api_version=api_version,
content_type=content_type,
cls=lambda x, y, z: x,
headers=_headers,
params=_params,
**kwargs
)
kwargs.pop("error_map", None)
def get_long_running_output(pipeline_response):
deserialized = self._deserialize("FirewallResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
if polling is True:
polling_method: AsyncPollingMethod = cast(
AsyncPollingMethod,
AsyncARMPolling(lro_delay, lro_options={"final-state-via": "azure-async-operation"}, **kwargs),
)
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output,
)
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
begin_create_or_update.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}"
}
@overload
async def update(
self,
resource_group_name: str,
firewall_name: str,
properties: _models.FirewallResourceUpdate,
*,
content_type: str = "application/json",
**kwargs: Any
) -> _models.FirewallResource:
"""Update a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param properties: The resource properties to be updated. Required.
:type properties: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResourceUpdate
:keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
Default value is "application/json".
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: FirewallResource or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResource
:raises ~azure.core.exceptions.HttpResponseError:
"""
@overload
async def update(
self,
resource_group_name: str,
firewall_name: str,
properties: IO,
*,
content_type: str = "application/json",
**kwargs: Any
) -> _models.FirewallResource:
"""Update a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param properties: The resource properties to be updated. Required.
:type properties: IO
:keyword content_type: Body Parameter content-type. Content type parameter for binary body.
Default value is "application/json".
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: FirewallResource or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResource
:raises ~azure.core.exceptions.HttpResponseError:
"""
@distributed_trace_async
async def update(
self,
resource_group_name: str,
firewall_name: str,
properties: Union[_models.FirewallResourceUpdate, IO],
**kwargs: Any
) -> _models.FirewallResource:
"""Update a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param properties: The resource properties to be updated. Is either a FirewallResourceUpdate
type or a IO type. Required.
:type properties: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResourceUpdate or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: FirewallResource or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.FirewallResource
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.FirewallResource] = kwargs.pop("cls", None)
content_type = content_type or "application/json"
_json = None
_content = None
if isinstance(properties, (IOBase, bytes)):
_content = properties
else:
_json = self._serialize.body(properties, "FirewallResourceUpdate")
request = build_update_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
content_type=content_type,
json=_json,
content=_content,
template_url=self.update.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize("FirewallResource", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
update.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}"
}
async def _delete_initial( # pylint: disable=inconsistent-return-statements
self, resource_group_name: str, firewall_name: str, **kwargs: Any
) -> None:
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self._delete_initial.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200, 202, 204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
_delete_initial.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}"
}
@distributed_trace_async
async def begin_delete(self, resource_group_name: str, firewall_name: str, **kwargs: Any) -> AsyncLROPoller[None]:
"""Delete a FirewallResource.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
:rtype: ~azure.core.polling.AsyncLROPoller[None]
:raises ~azure.core.exceptions.HttpResponseError:
"""
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
cont_token: Optional[str] = kwargs.pop("continuation_token", None)
if cont_token is None:
raw_result = await self._delete_initial( # type: ignore
resource_group_name=resource_group_name,
firewall_name=firewall_name,
api_version=api_version,
cls=lambda x, y, z: x,
headers=_headers,
params=_params,
**kwargs
)
kwargs.pop("error_map", None)
def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
if cls:
return cls(pipeline_response, None, {})
if polling is True:
polling_method: AsyncPollingMethod = cast(
AsyncPollingMethod,
AsyncARMPolling(lro_delay, lro_options={"final-state-via": "azure-async-operation"}, **kwargs),
)
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output,
)
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
begin_delete.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}"
}
@distributed_trace_async
async def get_global_rulestack(
self, resource_group_name: str, firewall_name: str, **kwargs: Any
) -> _models.GlobalRulestackInfo:
"""Get Global Rulestack associated with the Firewall.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: GlobalRulestackInfo or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.GlobalRulestackInfo
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.GlobalRulestackInfo] = kwargs.pop("cls", None)
request = build_get_global_rulestack_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self.get_global_rulestack.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize("GlobalRulestackInfo", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_global_rulestack.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}/getGlobalRulestack"
}
@distributed_trace_async
async def get_log_profile(self, resource_group_name: str, firewall_name: str, **kwargs: Any) -> _models.LogSettings:
"""Log Profile for Firewall.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: LogSettings or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.LogSettings
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.LogSettings] = kwargs.pop("cls", None)
request = build_get_log_profile_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self.get_log_profile.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize("LogSettings", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_log_profile.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}/getLogProfile"
}
@distributed_trace_async
async def get_support_info(
self, resource_group_name: str, firewall_name: str, email: Optional[str] = None, **kwargs: Any
) -> _models.SupportInfo:
"""support info for firewall.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param email: email address on behalf of which this API called. Default value is None.
:type email: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: SupportInfo or the result of cls(response)
:rtype: ~azure.mgmt.paloaltonetworksngfw.models.SupportInfo
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.SupportInfo] = kwargs.pop("cls", None)
request = build_get_support_info_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
email=email,
api_version=api_version,
template_url=self.get_support_info.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize("SupportInfo", pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_support_info.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}/getSupportInfo"
}
@overload
async def save_log_profile( # pylint: disable=inconsistent-return-statements
self,
resource_group_name: str,
firewall_name: str,
log_settings: Optional[_models.LogSettings] = None,
*,
content_type: str = "application/json",
**kwargs: Any
) -> None:
"""Log Profile for Firewall.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param log_settings: Default value is None.
:type log_settings: ~azure.mgmt.paloaltonetworksngfw.models.LogSettings
:keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
Default value is "application/json".
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None or the result of cls(response)
:rtype: None
:raises ~azure.core.exceptions.HttpResponseError:
"""
@overload
async def save_log_profile( # pylint: disable=inconsistent-return-statements
self,
resource_group_name: str,
firewall_name: str,
log_settings: Optional[IO] = None,
*,
content_type: str = "application/json",
**kwargs: Any
) -> None:
"""Log Profile for Firewall.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param log_settings: Default value is None.
:type log_settings: IO
:keyword content_type: Body Parameter content-type. Content type parameter for binary body.
Default value is "application/json".
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None or the result of cls(response)
:rtype: None
:raises ~azure.core.exceptions.HttpResponseError:
"""
@distributed_trace_async
async def save_log_profile( # pylint: disable=inconsistent-return-statements
self,
resource_group_name: str,
firewall_name: str,
log_settings: Optional[Union[_models.LogSettings, IO]] = None,
**kwargs: Any
) -> None:
"""Log Profile for Firewall.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
:type resource_group_name: str
:param firewall_name: Firewall resource name. Required.
:type firewall_name: str
:param log_settings: Is either a LogSettings type or a IO type. Default value is None.
:type log_settings: ~azure.mgmt.paloaltonetworksngfw.models.LogSettings or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
:paramtype content_type: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None or the result of cls(response)
:rtype: None
:raises ~azure.core.exceptions.HttpResponseError:
"""
error_map = {
401: ClientAuthenticationError,
404: ResourceNotFoundError,
409: ResourceExistsError,
304: ResourceNotModifiedError,
}
error_map.update(kwargs.pop("error_map", {}) or {})
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[None] = kwargs.pop("cls", None)
content_type = content_type or "application/json"
_json = None
_content = None
if isinstance(log_settings, (IOBase, bytes)):
_content = log_settings
else:
if log_settings is not None:
_json = self._serialize.body(log_settings, "LogSettings")
else:
_json = None
request = build_save_log_profile_request(
resource_group_name=resource_group_name,
firewall_name=firewall_name,
subscription_id=self._config.subscription_id,
api_version=api_version,
content_type=content_type,
json=_json,
content=_content,
template_url=self.save_log_profile.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
_stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
save_log_profile.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/PaloAltoNetworks.Cloudngfw/firewalls/{firewallName}/saveLogProfile"
}
|
[
"[email protected]"
] | |
bac3c30d02721d958e23136003c622e9b7874698
|
f2e0992e94fa31b640d97f50c576bd360bb323e0
|
/portfolio/migrations/0001_initial.py
|
1ee3bb0f226b35248c57c7af90444f588b3e5dd4
|
[] |
no_license
|
mpmckinley/personal_portfolio-project
|
01917d8582144a3a7a40766572db5f24c72a62f3
|
25782c8c8c68ab6a7738e18c889d1b6c438ad97c
|
refs/heads/master
| 2023-01-30T12:52:06.044032 | 2020-12-17T14:37:09 | 2020-12-17T14:37:09 | 322,165,904 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 685 |
py
|
# Generated by Django 3.1.4 on 2020-12-15 23:11
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Project',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=50)),
('description', models.CharField(max_length=150)),
('image', models.ImageField(upload_to='portfolio/images/')),
('url', models.URLField(blank=True)),
],
),
]
|
[
"[email protected]"
] | |
404b57be933409cdc797a676f865e78c845133f9
|
bf1c7016681b5b7c6569a5f20d037e9c5db37854
|
/VI_semester/mobile_robots/point.py
|
4141470fd0bdca014339714df82312b8f323ed3a
|
[
"Beerware"
] |
permissive
|
dainiusjocas/labs
|
ae62d4672f4c43d27b4e9d23e126fa9fb9cf58a9
|
25aa0ae2032681dbaf0afd83f3d80bedddea6407
|
refs/heads/master
| 2021-01-23T23:03:10.271749 | 2011-12-13T15:38:48 | 2011-12-13T15:38:48 | 6,511,648 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 379 |
py
|
#!/usr/bin/env python
class Point:
''' Class that represents a point in a map '''
def __init__(self, x = 0, y = 0):
self.x = x
self.y = y
def values(self):
return [self.x, self.y]
def __repr__(self):
return "({0}, {1})".format(self.x, self.y)
def __eq__(self, other):
return self.x == other.x and self.y == other.y
|
[
"[email protected]"
] | |
cac6a3f45b7111acbedec61c19bcf6ec0f01d43d
|
128c1bd8ce38d5c7bfee1f1d3fb1fec0738b3dfc
|
/venv/bin/wheel
|
ce977b896c7ae45b2814de6a86fdba70c69cb8d9
|
[] |
no_license
|
ajitesh-30/Blog
|
58b8b6a520fab32643efaae01c48d5388195a69c
|
460f48e2e7d1316855d94644db2ad9d01820af9a
|
refs/heads/master
| 2021-05-08T16:23:32.949050 | 2018-12-12T19:45:48 | 2018-12-12T19:45:48 | 120,154,122 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 238 |
#!/home/rattlesnake/Project/venv/bin/python3
# -*- coding: utf-8 -*-
import re
import sys
from wheel.cli import main
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(main())
|
[
"[email protected]"
] | ||
5802c971baf6a88738677a1750fa3adc94a4f74b
|
9ac6dad591f8c1dd512e2b1710f455f19f1ea3d3
|
/4.5_import_exercises.py
|
0f89e5b1ae3dfbf11744b9a6ca37cf99d2e84330
|
[] |
no_license
|
Padraic-Doran/python-exercises
|
d789b500938f6ca0dee33ab1786897839fb9ea66
|
fec5cd3109d899b05214c95603cad21d3630ec2f
|
refs/heads/master
| 2020-07-23T15:14:05.964961 | 2019-09-30T21:10:17 | 2019-09-30T21:10:17 | 207,604,670 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 5,527 |
py
|
# from CU_function_exercises import remove_vowels
# remove_vowels('RGJJweapr')
# import CU_function_exercises as cfe
# from CU_function_exercises import remove_vowels as rv
# print(rv('wfjnqergpvpoqweoaf'))
How many different ways can you combine the letters from "abc" with the numbers 1, 2, and 3?
# import itertools
# print(list(e for e in itertools.product('ABC', '123')))
# print(len(list(e for e in itertools.product('ABC', '123'))))
How many different ways can you combine two of the letters from "abcd"?
# print(len(list(e for e in itertools.combinations_with_replacement('ABCD', 2))))
# Save this file as profiles.json inside of your exercises directory.
# Use the load function from the json module to open this file, it will produce a list of dictionaries.
# Using this data, write some code that calculates and outputs the following information:
import json
profiles = open('profiles.json')
profiles_data = json.load(profiles)
# Total number of users
""" Remember, profiles_data is a list. Iterate like a list """
user_total = len(profiles_data)
# Number of active users
"""Remember isActive is boolean. x = a dictionary, so "for each dictionary in the list of dictionaries called
# profile_data, where the key isactive is set to True"
# """
active_total = len([x for x in profiles_data if x["isActive"]])
# print(active_total)
"""Same thing as above, but boolean is switched to False"""
inactive_total = len([x for x in profiles_data if not x["isActive"]])
# print(inactive_total)
# Grand total of balances for all users
"""Remember, the balances have unwanted character in the list, so they need to be removed.
Create a function to accomplish this task"""
def handle_balance(s):
return float(s[1:].replace(',', '')) """ Could also add a seconnd .replace() for $ """
""" Now that that/s accomplished, pass the all balance keys through the function.
List comprehension looks like this: """
balances = [handle_balance(x['balance']) for x in profile_data]
""" Above means that the variable /balances/ GETS the values of the key named /balance/ for all dictionaries "x"
in the list profile_data """
# print(balances)
# Average balance per user
""" Take the sum of balances and divide it by the number of balances """
total_balance = sum(balances)
average_balance = sum(balances) / len(balances)
# User with the lowest balance
""" from the lecture, Zach explained that anchoring the lowest balance to the first dictionary in the list
simplifies the program writing, because you're looping and replacing against a known index. As Kevin pointed out,
this could create a situation where multiple accounts have the lowest balance, and this code would not flag that """
user_with_the_lowest_balance
user_with_the_lowest_balance = profile_data[0]
for user in profile_data[1:]:
if handle_balance(user['balance']) < handle_balance(user_with_the_lowest_balance['balance']):
user_with_the_lowest_balance = user
""" The variable user_with_the_lowest_balance is set to the first index of profile_data.
For each user(dictionary) in the list profile_data, starting at the SECOND index,
if the balance key(having been run through the balance cleaning function) is less than the current
lowest balance, the variable user_with_the_lowest_balance is set to that user. """
# User with the highest balance
""" Same as above; just flipping the results from < to > and altering the variable name. """
user_with_the_highest_balance = profiles[0]
for user in profiles[1:]:
if handle_balance(user['balance']) > handle_balance(user_with_the_highest_balance['balance']):
user_with_the_highest_balance = user
### Alternative with a custom key function
""" The min function has key that you can manipulate. Here, the key is changed to read the lambda function """
min(profiles, key=lambda profile: handle_balance(profile['balance']))
""" Function created to pass the balances through the cleaning function.
Said function is then made the key in min() """
def extract_balance(profile):
return handle_balance(profile['balance'])
min(profiles, key=extract_balance)
# Most common favorite fruit
# Least most common favorite fruit
""" Using an import from a library called collection,
importing just one function called Counter. Because the function was specifically imported, there is no need
to us collections.Counter. The datatype created is a !!!Countertype!!! """
from collections import Counter
Counter([p['favoriteFruit'] for p in profile_data])
"""The list comprehension reads, roughly, the Counter function to counter the variable
of the dictionary (p) key 'favoriteFruit'
for all dictionaries 'p'
in the list of dictionaries called profile_data """
# For loop to create a dictionary of 'favoriteFruits'
fruit_counts = {}
for profile in profile_data:
fruit = profile['favoriteFruit']
if fruit in fruit_counts:
fruit_counts[fruit] += 1
else:
fruit_counts[fruit] = 1
""" This creates a dictionary as the end results, as opposed to what the Counter function would produce """
# Total number of unread messages for all users
""" The number needed for the answer is buried in a string in the key['greeting'].
A function needs to be created to extract the digits from the string. """
greetings = [profile['greeting'] for profile in profile_data]
def extract_digits(s):
return int(''.join([c for c in s if c.isdigit()]))
n_unread_messages = [extract_digits(greeting) for greeting in greetings]
sum(n_unread_messages)
|
[
"[email protected]"
] | |
af426f37de5914387a99e20ec2eba4baf60691aa
|
15905cfe5ccfbc740ee71b890297aac9139dae18
|
/computer/urls.py
|
91df3c3518b003805ae627294a2817fdbc943f3a
|
[] |
no_license
|
Yura1224/djangolesson2practise
|
82a962986601c0f27c771ea1ed11cd88c46df014
|
23855fc048b241eb1444b2006507a88cd619f6e1
|
refs/heads/master
| 2023-08-04T12:53:36.339126 | 2021-09-21T11:46:43 | 2021-09-21T11:46:43 | 408,798,094 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 335 |
py
|
from django.urls import path
from .views import ComputerListCreateView, ComputerRetrieveUpdateDeleteView
urlpatterns = [
path('', ComputerListCreateView.as_view(), name='computer_list_create'),
path('/<int:pk>', ComputerRetrieveUpdateDeleteView.as_view(), name='car_retrieve_update_delete')
]
# http:localhost:8000/computers
|
[
"[email protected]"
] | |
2c5ec191020dbe6eb0ff6d138d3c4adf6ca3187e
|
b3c1c93247e83c212f40dd271e15ba296f22be56
|
/linearregression.py
|
b11fa874f740dcd15c90a494003bb2197f8e1945
|
[] |
no_license
|
campbellbg/mypythonlearning
|
dda78f585668dc087443e3312ff02e921686297a
|
656725b6ceafbf6408d1308c81cbe430c9f8e123
|
refs/heads/master
| 2020-03-27T18:51:50.670832 | 2019-05-27T12:19:49 | 2019-05-27T12:19:49 | 146,949,278 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 5,697 |
py
|
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn import metrics
#This config fixes the truncated console writes. Makes things a lot easier
pd.set_option('display.width', 400)
pd.set_option('display.max_columns', 10)
np.set_printoptions(linewidth=400)
#Linear Regression coding exercise
#***********************************************************************************************************************
#ecommerce data. Read it and understand it
customers_all = pd.read_csv('D:\\Course Content\\python-for-data-science-and-ml-bootcamp\\11-Linear-Regression\\Ecommerce Customers')
customers = customers_all[['Avg. Session Length', 'Time on App', 'Time on Website', 'Length of Membership', 'Yearly Amount Spent']] #reduce to the numerical fields only
#print(customers.corr()) #Based on this is looks like a strong correlation between time on app and the spend
#jointplots are pretty cool. This shows a strong correlation with the Time on the App
#sb.jointplot(customers['Yearly Amount Spent'], customers['Time on Website'])
#sb.jointplot(customers['Yearly Amount Spent'], customers['Time on App'])
#sb.pairplot(customers)
#sb.lmplot(data = customers[['Yearly Amount Spent', 'Length of Membership']], x = 'Yearly Amount Spent', y = 'Length of Membership')
#plt.show()
custxtrain, custxtest, custytrain, custytest = train_test_split(customers[['Avg. Session Length', 'Time on App', 'Time on Website', 'Length of Membership']], customers['Yearly Amount Spent'], test_size = 0.3, random_state = 101)
#Tried without the lowly correlated variables but surprisingly it did not make much of a difference at all
#custxtrain, custxtest, custytrain, custytest = train_test_split(customers[['Time on App', 'Length of Membership']], customers['Yearly Amount Spent'], test_size = 0.3, random_state = 101)
#Instantiate and train the model
lm = LinearRegression()
lm.fit(X = custxtrain, y = custytrain)
#Have a look at the coefficients from the trained model
print(pd.DataFrame(data = lm.coef_, index = ['Avg. Session Length', 'Time on App', 'Time on Website', 'Length of Membership']))
#Predict the test values and then visualise the residuals
predictions = lm.predict(X = custxtest)
#sb.scatterplot(x = predictions, y = custytest)
#plt.show()
#Look at the key performance metrics of the model
print('*********************************')
print(f'Mean Abs Error = {metrics.mean_absolute_error(y_true = custytest, y_pred = predictions)}')
print(f'Mean Squared Error = {metrics.mean_squared_error(y_true = custytest, y_pred = predictions)}')
print(f'SQRT Mean Sqaured Error = {np.sqrt(metrics.mean_squared_error(y_true = custytest, y_pred = predictions))}')
''' USA Housing Data. Not real data
#***********************************************************************************************************************
#USA housing data
mydf = pd.read_csv('D:\\Course Content\\python-for-data-science-and-ml-bootcamp\\11-Linear-Regression\\USA_Housing.csv')
#mydf.info()
#print(mydf.corr()) #This is nice. A correlation matrix
#sb.heatmap(mydf.corr(), annot = True)
#sb.pairplot(mydf)
#sb.distplot(mydf['Price'])
#plt.show() #Need this in order for the chart to show within pycharm. No idea how seaborn and matplot are linked
mydfx = mydf[['Avg. Area Income', 'Avg. Area House Age', 'Avg. Area Number of Rooms', 'Avg. Area Number of Bedrooms', 'Area Population']] #remove the dependent variable and the address
mydfy = mydf['Price']
mydfx_train, mydfx_test, mydfy_train, mydfy_test = train_test_split(mydfx, mydfy, test_size = 0.3, random_state = 101)
lm = LinearRegression() #instantiate an object
lm.fit(X = mydfx_train, y = mydfy_train) #fit (train model)
#print(f'Intercept = {lm.intercept_}')
#print(pd.DataFrame(data = lm.coef_, index = mydfx_train.columns, columns = ['Coeff'])) #Put the co-efficients into a dataframe for readibility
predictions = lm.predict(mydfx_test) #will give me back an array of my dependent variable predictions
#sb.distplot(mydfy_test - predictions) #Subtraction of the two aways works by index. Plot the residual distribution
#plt.show()
print(f'The mean abs error is {metrics.mean_absolute_error(y_true = mydfy_test, y_pred = predictions)}')
print(f'The mean squared error is {metrics.mean_squared_error(y_true = mydfy_test, y_pred = predictions)}')
print(f'The root mean squared error is {np.sqrt(metrics.mean_squared_error(y_true = mydfy_test, y_pred = predictions))}')
'''
''' Playing around with some of the syntax from the initial videos
#***********************************************************************************************************************
mymodel = LinearRegression(normalize=True)
print(mymodel) #must have an internal ToString method that allows this object to be printed out
#Create a bogus set of x and values. Uses a short-hand assignment notation
x, y = np.arange(10).reshape(5, 2), range(5)
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state = 23) #random_state provides the same seed and therefore consistent results of the split
print(x_train)
print('------')
print(x_test)
print('------')
print(y_train)
print('------')
print(y_test)
print('######################')
#train (fit) the model
mymodel.fit(X = x_train, y = y_train)
#predict my values and store the result
predictions = mymodel.predict(x_test)
sum_squares = 0
for i, prediction in enumerate(predictions):
print(f'X = {x_test[i]}, Actual Y = {y_test[i]}, Predicted Y = {prediction}')
sum_squares += (prediction - y_test[i]) ** 2
print(sum_squares)
'''
|
[
"[email protected]"
] | |
8979b51513153b74eb4a26efe75e95c67319ebef
|
40b42ccf2b6959d6fce74509201781be96f04475
|
/mmocr/models/textdet/necks/fpem_ffm.py
|
c98b43f1fc2642db598a0f9094b88e4851cc9e75
|
[
"Apache-2.0"
] |
permissive
|
xdxie/WordArt
|
2f1414d8e4edaa89333353d0b28e5096e1f87263
|
89bf8a218881b250d0ead7a0287526c69586c92a
|
refs/heads/main
| 2023-05-23T02:04:22.185386 | 2023-03-06T11:51:43 | 2023-03-06T11:51:43 | 515,485,694 | 106 | 12 | null | null | null | null |
UTF-8
|
Python
| false | false | 5,999 |
py
|
# Copyright (c) OpenMMLab. All rights reserved.
import torch.nn.functional as F
from mmcv.runner import BaseModule, ModuleList
from torch import nn
from mmocr.models.builder import NECKS
class FPEM(BaseModule):
"""FPN-like feature fusion module in PANet.
Args:
in_channels (int): Number of input channels.
init_cfg (dict or list[dict], optional): Initialization configs.
"""
def __init__(self, in_channels=128, init_cfg=None):
super().__init__(init_cfg=init_cfg)
self.up_add1 = SeparableConv2d(in_channels, in_channels, 1)
self.up_add2 = SeparableConv2d(in_channels, in_channels, 1)
self.up_add3 = SeparableConv2d(in_channels, in_channels, 1)
self.down_add1 = SeparableConv2d(in_channels, in_channels, 2)
self.down_add2 = SeparableConv2d(in_channels, in_channels, 2)
self.down_add3 = SeparableConv2d(in_channels, in_channels, 2)
def forward(self, c2, c3, c4, c5):
"""
Args:
c2, c3, c4, c5 (Tensor): Each has the shape of
:math:`(N, C_i, H_i, W_i)`.
Returns:
list[Tensor]: A list of 4 tensors of the same shape as input.
"""
# upsample
c4 = self.up_add1(self._upsample_add(c5, c4)) # c4 shape
c3 = self.up_add2(self._upsample_add(c4, c3))
c2 = self.up_add3(self._upsample_add(c3, c2))
# downsample
c3 = self.down_add1(self._upsample_add(c3, c2))
c4 = self.down_add2(self._upsample_add(c4, c3))
c5 = self.down_add3(self._upsample_add(c5, c4)) # c4 / 2
return c2, c3, c4, c5
def _upsample_add(self, x, y):
return F.interpolate(x, size=y.size()[2:]) + y
class SeparableConv2d(BaseModule):
def __init__(self, in_channels, out_channels, stride=1, init_cfg=None):
super().__init__(init_cfg=init_cfg)
self.depthwise_conv = nn.Conv2d(
in_channels=in_channels,
out_channels=in_channels,
kernel_size=3,
padding=1,
stride=stride,
groups=in_channels)
self.pointwise_conv = nn.Conv2d(
in_channels=in_channels, out_channels=out_channels, kernel_size=1)
self.bn = nn.BatchNorm2d(out_channels)
self.relu = nn.ReLU()
def forward(self, x):
x = self.depthwise_conv(x)
x = self.pointwise_conv(x)
x = self.bn(x)
x = self.relu(x)
return x
@NECKS.register_module()
class FPEM_FFM(BaseModule):
"""This code is from https://github.com/WenmuZhou/PAN.pytorch.
Args:
in_channels (list[int]): A list of 4 numbers of input channels.
conv_out (int): Number of output channels.
fpem_repeat (int): Number of FPEM layers before FFM operations.
align_corners (bool): The interpolation behaviour in FFM operation,
used in :func:`torch.nn.functional.interpolate`.
init_cfg (dict or list[dict], optional): Initialization configs.
"""
def __init__(self,
in_channels,
conv_out=128,
fpem_repeat=2,
align_corners=False,
init_cfg=dict(
type='Xavier', layer='Conv2d', distribution='uniform')):
super().__init__(init_cfg=init_cfg)
# reduce layers
self.reduce_conv_c2 = nn.Sequential(
nn.Conv2d(
in_channels=in_channels[0],
out_channels=conv_out,
kernel_size=1), nn.BatchNorm2d(conv_out), nn.ReLU())
self.reduce_conv_c3 = nn.Sequential(
nn.Conv2d(
in_channels=in_channels[1],
out_channels=conv_out,
kernel_size=1), nn.BatchNorm2d(conv_out), nn.ReLU())
self.reduce_conv_c4 = nn.Sequential(
nn.Conv2d(
in_channels=in_channels[2],
out_channels=conv_out,
kernel_size=1), nn.BatchNorm2d(conv_out), nn.ReLU())
self.reduce_conv_c5 = nn.Sequential(
nn.Conv2d(
in_channels=in_channels[3],
out_channels=conv_out,
kernel_size=1), nn.BatchNorm2d(conv_out), nn.ReLU())
self.align_corners = align_corners
self.fpems = ModuleList()
for _ in range(fpem_repeat):
self.fpems.append(FPEM(conv_out))
def forward(self, x):
"""
Args:
x (list[Tensor]): A list of four tensors of shape
:math:`(N, C_i, H_i, W_i)`, representing C2, C3, C4, C5
features respectively. :math:`C_i` should matches the number in
``in_channels``.
Returns:
list[Tensor]: Four tensors of shape
:math:`(N, C_{out}, H_0, W_0)` where :math:`C_{out}` is
``conv_out``.
"""
c2, c3, c4, c5 = x
# reduce channel
c2 = self.reduce_conv_c2(c2)
c3 = self.reduce_conv_c3(c3)
c4 = self.reduce_conv_c4(c4)
c5 = self.reduce_conv_c5(c5)
# FPEM
for i, fpem in enumerate(self.fpems):
c2, c3, c4, c5 = fpem(c2, c3, c4, c5)
if i == 0:
c2_ffm = c2
c3_ffm = c3
c4_ffm = c4
c5_ffm = c5
else:
c2_ffm = c2_ffm + c2
c3_ffm = c3_ffm + c3
c4_ffm = c4_ffm + c4
c5_ffm = c5_ffm + c5
# FFM
c5 = F.interpolate(
c5_ffm,
c2_ffm.size()[-2:],
mode='bilinear',
align_corners=self.align_corners)
c4 = F.interpolate(
c4_ffm,
c2_ffm.size()[-2:],
mode='bilinear',
align_corners=self.align_corners)
c3 = F.interpolate(
c3_ffm,
c2_ffm.size()[-2:],
mode='bilinear',
align_corners=self.align_corners)
outs = [c2_ffm, c3, c4, c5]
return tuple(outs)
|
[
"[email protected]"
] | |
2c8b29f4777567834b9d0affa686caba95f48ef3
|
d1c29c9f06d56644ca2fb11fcff8c25703aced79
|
/MMCG/make_plots.py
|
891af441059f2c0d34f6177672eb9d172bde2fe6
|
[] |
no_license
|
jjhelmus/arm_vap_scripts
|
4a3d7bbe9e277972312484fe46a35c92dae1c71c
|
1d49d0e2f8affea11aabc000f74d8d1c4be75ef5
|
refs/heads/master
| 2021-01-22T05:24:35.935447 | 2013-04-12T14:38:31 | 2013-04-12T14:38:31 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 861 |
py
|
#!/usr/bin/env python
import matplotlib.pyplot as plt
import netCDF4
import pyart
# MMCG figure
dataset = netCDF4.Dataset('sgpcsaprmmcgi7.c0.20110520.110100.nc')
refl = dataset.variables['reflectivity_horizontal']
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(refl[0,4], origin='lower')
fig.savefig('mapped_figure.png')
# Test
dataset = netCDF4.Dataset('foo.dir/sgpcsaprmmcgI7.c0.20110520.110100.nc')
refl = dataset.variables['reflectivity_horizontal']
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(refl[0,4], origin='lower')
fig.savefig('exp_figure.png')
# Radial coords
"""
radar = pyart.io.read_netcdf('sgpcsaprsurcmacI7.c0.20110520.110100.nc')
display = pyart.graph.RadarDisplay(radar)
fig = plt.figure()
ax = fig.add_subplot(111)
display.plot_ppi('reflectivity_horizontal', 0, vmin=-16, vmax=48)
fig.savefig('radial_figure.png')
"""
|
[
"[email protected]"
] | |
5f16b6848d8b04d6ee0612be889a4e855a2b016d
|
87c5fcc4b167a3c09bfc96787e8f3e44216ccf51
|
/TextboxTurtle.py
|
ed42ae5544a76166fa29a4f399c17f23c18281c5
|
[] |
no_license
|
debojit666/Python-PracticeFiles
|
6c7e7d8e6031985e5484bbdf90b3bf85c2d2af40
|
a90d2102b9f9fa217853215a8605b4909c41ce0b
|
refs/heads/master
| 2020-06-30T16:10:50.168861 | 2019-10-03T19:09:33 | 2019-10-03T19:09:33 | 200,880,737 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 385 |
py
|
import turtle
name = turtle.textinput("name", "What is your name?")
name = name.lower()
if name.startswith("mr"):
print("Hello Sir, How are you?")
elif name.startswith("mrs") or name.startswith("miss") or name.startswith("ms"):
print("Hello Madam, How are you?")
else:
name = name.capitalize()
str = "Hi " + name + "! How are you?"
print(str)
turtle.exitonclick
|
[
"[email protected]"
] | |
765b302c85fb439d74794e48f3d108dc132fd8f9
|
41f185a4560b24351897ce19e4d4a71fc229c312
|
/aap_whatsapp/cron/whatsapp.py
|
93f42f045a5d9bf50ad38817e0abb48e10ba0d98
|
[] |
no_license
|
stark3998/Whatsapp-Scraper
|
46fbbbb54946f367124702722d9b14c013f31243
|
b7e23a15117381de499fe9622854e6f2a5cf8a20
|
refs/heads/master
| 2020-09-11T22:40:24.753785 | 2019-11-17T07:56:36 | 2019-11-17T07:56:36 | 222,214,172 | 0 | 0 | null | 2019-11-17T08:02:08 | 2019-11-17T07:43:44 |
HTML
|
UTF-8
|
Python
| false | false | 9,178 |
py
|
# -*- coding: utf-8 -*-
import time
import json
from datetime import datetime, timezone
from aap_whatsapp import db
from flask_script import Command
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from aap_whatsapp.constants.crawl_elem import CLASSES, CSS, SCROLL, ELS
from aap_whatsapp.model.message import Message, User, MessageReceived
from aap_whatsapp.api.user import create_user
from aap_whatsapp import logging
from bs4 import BeautifulSoup
import re
import os
emoji_pattern = re.compile("["
u"\U0001F600-\U0001F64F" # emoticons
u"\U0001F300-\U0001F5FF" # symbols & pictographs
u"\U0001F680-\U0001F6FF" # transport & map symbols
u"\U0001F1E0-\U0001F1FF" # flags (iOS)
u"\U00002702-\U000027B0"
u"\U000024C2-\U0001F251"
"]+", flags=re.UNICODE)
cwd = os.getcwd()
class Whatsapp(Command):
def run(self):
logging.info("Script Started")
_chrome_options = webdriver.ChromeOptions()
_chrome_options.add_argument("--disable-infobars")
_chrome_options.add_argument("--start-maximized")
driver = webdriver.Chrome(cwd + '/aap_whatsapp/driver/chromedriver', chrome_options=_chrome_options)
driver.get("https://web.whatsapp.com")
# self.set_storage(driver)
WebDriverWait(driver,60).until(EC.visibility_of_element_located((By.XPATH,"//*[@id=\"side\"]/div[1]/div/label/input")))
logging.info("LoggedIn to WhatsApp")
# ls = driver.execute_script("return {...window.localStorage}")
# with open('creds.json', 'w') as outfile:
# json.dump(dict(ls), outfile, indent=4)
while True:
messages = Message.query.filter_by(is_active=True).all()
logging.info("Total Active Messages found {0}".format(len(messages)))
driver.execute_script(SCROLL['to_top'])
try:
search_bar=driver.find_element_by_xpath("//*[@id=\"side\"]/div[1]/div/label/input")
except Exception as error:
print(error)
unread = []
logging.info("Extracting unread chats")
for i in range(100):
chat_list = driver.find_element_by_id('pane-side')
soup = BeautifulSoup(chat_list.get_attribute(CLASSES['html_attribute']['ml']),
CLASSES['html_attribute']['ml_type'])
chats = soup.find_all(ELS['contacts_class']['el'], ELS['contacts_class']['el_class'])
for c in chats:
if c.find("span", "P6z4j"):
try:
count = str(c.find('span', "P6z4j")).split(">")[1].split("<")[0]
print("Count",count)
except:
print("Count Error")
if count:
count = int(count)
else:
count = 1
person = c.find("span", "_19RFN")
print("Person",person)
unread.append((person['title'], int(str(count))))
driver.execute_script(SCROLL['left_panel'])
print(unread)
unread = set(unread)
logging.info("unread chats ({0}) in format (person,unread_count) -> {1}".format(len(unread), unread))
for person in unread:
try:
logging.info("extracting chat for person {0}".format(person))
search_bar.clear()
search_bar.send_keys(person[0])
search_bar.send_keys(Keys.ENTER)
chat_body = driver.find_element_by_class_name(CLASSES['chat_body'])
chat_soup = BeautifulSoup(chat_body.get_attribute(CLASSES['html_attribute']['ml']),
CLASSES['html_attribute']['ml_type'])
msgs = chat_soup.find_all(ELS['msg']['el'], ELS['msg']['el_class'])
# if len(msgs) < int(person[1]):
# print("scroll")
logging.info("Unread Messages are:")
for m in msgs[-int(person[1]):]:
msg_text = m.find("span", "selectable-text invisible-space copyable-text").text
logging.info(msg_text)
for db_msg in messages:
diff = int((datetime.now(timezone.utc) - db_msg.created_at).days)
print("Difference between Days : ", diff)
if (diff >= 3):
print("Setting Message as Inactive")
db_msg.is_active = False
db_msg.update()
continue
logging.info("matching with {0} from DB".format(db_msg))
line_count = 0
match_count = 0
b = emoji_pattern.sub(r'', msg_text).replace("\n", " ").split(" ")
a = emoji_pattern.sub(r'', db_msg.text).replace("\n", " ").split(" ")
count = 0
for x in a:
if x in b:
count += 1
print(" Match Count : ", count)
print(" Match accuracy : ", (count / len(a)) * 100)
if (count / len(a)) * 100 >= 80:
match_count = 1
if match_count:
logging.info("[MATCHED] in {0}".format(person[0]))
if person[0][0] != "+":
u = User.query.filter_by(name=person[0]).first()
if not u:
logging.info("Creating Entry in DB for user {0}", person[0])
u = create_user(name=person[0])
else:
u = User.query.filter_by(number=person[0][3:].replace(" ", "")).first()
if not u:
logging.info("Creating Entry in DB for user with number {0}",
int(person[0][3:].replace(" ", "")))
u = create_user(name="", number=int(person[0][3:].replace(" ", "")))
if u:
ob = None
logging.info("Updating Receive Info")
if db_msg.received_from_users:
for usr in db_msg.received_from_users:
if u.id == usr.user.id:
ob = MessageReceived.query.filter_by(user_id=u.id,
message_id=db_msg.id).first()
ob.receive_count += 1
ob.save()
logging.info(
"Increased receive count for {0}. New RecieveCount={1}".format(
u.name, ob.receive_count))
break
if not ob:
logging.info("Creating Entry in received for user {0}".format(u.name))
ob = MessageReceived(user_id=u.id, message_id=db_msg.id)
db_msg.received_from_users.append(ob)
db_msg.save()
except Exception as e:
logging.exception(e)
driver.execute_script(SCROLL['to_top'])
logging.info("Sleep for 1 Min")
time.sleep(60)
@staticmethod
def set_storage(driver):
if os.path.exists(cwd + '/creds.json'):
with open('creds.json', 'r') as creds:
d = json.load(creds)
for key in d:
if key == "storage_test":
continue
try:
script = "window.localStorage.setItem('{0}',JSON.stringify({1}));".format(key, d[key])
driver.execute_script(script)
except Exception as e:
logging.exception(e)
driver.refresh()
|
[
"[email protected]"
] | |
0b8609103dd7f8a320e1b62047793f8513669fc7
|
0d247fea57ee40717166b1ff753fd626092e9e78
|
/tests/test_completer.py
|
279b880925ed77714e3e343298ac7a331f4a7706
|
[] |
no_license
|
sean-heller/dockercli
|
362ff0310992b2257ed20077b76245729ca2a227
|
ab9ca8f13d01a5d8c5d3f58743c476836b06d186
|
refs/heads/master
| 2021-05-29T07:27:33.954752 | 2015-07-20T16:21:09 | 2015-07-20T16:21:09 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 10,645 |
py
|
from __future__ import unicode_literals
import pytest
from prompt_toolkit.completion import Completion
from prompt_toolkit.document import Document
from dockercli.options import all_options
from dockercli.options import COMMAND_NAMES
@pytest.fixture
def completer():
import dockercli.completer as cmp
return cmp.DockerCompleter()
@pytest.fixture
def complete_event():
from mock import Mock
return Mock()
cs1 = ['newton', 'tesla', 'einstein', 'edison']
rs1 = ['einstein', 'edison']
im1 = ['ubuntu', 'hello-world', 'postgres', 'nginx']
cs2 = ['desperate_hodgkin', 'desperate_torvalds', 'silly_fermat', 'some-percona']
def test_empty_string_completion(completer, complete_event):
"""
In the beginning of the line, all available commands are suggested.
"""
text = ''
position = 0
result = set(completer.get_completions(
Document(text=text, cursor_position=position),
complete_event))
assert result == set(map(Completion, COMMAND_NAMES))
def test_build_path_completion_absolute(completer, complete_event):
"""
Suggest build paths from filesystem root.
"""
command = 'build /'
position = len(command)
result = set(completer.get_completions(
Document(text=command, cursor_position=position),
complete_event))
expected = ['etc', 'home', 'tmp', 'usr', 'var']
expected = set(map(lambda t: Completion(t, 0), expected))
assert expected.issubset(result)
def test_build_path_completion_user(completer, complete_event):
"""
Suggest build paths from user home directory.
"""
command = 'build ~'
position = len(command)
result = set(completer.get_completions(
Document(text=command, cursor_position=position),
complete_event))
expected = ['~/Documents', '~/Downloads']
expected = set(map(lambda t: Completion(t, -1), expected))
assert expected.issubset(result)
def test_build_path_completion_user_dir(completer, complete_event):
"""
Suggest build paths from user home directory.
"""
command = 'build ~/s'
position = len(command)
result = set(completer.get_completions(
Document(text=command, cursor_position=position),
complete_event))
expected = ['src']
expected = set(map(lambda t: Completion(t, -1), expected))
assert expected.issubset(result)
@pytest.mark.parametrize("command, expected", [
("h", ['help']),
("he", ['help']),
("hel", ['help']),
("help", ['help']),
('run -d ubuntu:14.04 /bin/sh -c "w', []) # not complete in quoted string
])
def test_command_completion(command, expected):
"""
Test command suggestions.
:param command: string: text that user started typing
:param expected: list: expected completions
"""
c = completer()
e = complete_event()
position = len(command)
result = set(c.get_completions(
Document(text=command, cursor_position=position),
e))
expected = set(map(lambda t: Completion(t, -len(command)), expected))
assert result == expected
@pytest.mark.parametrize("command, expected", [
("h", ['help', 'shell', 'push', 'attach', 'search']),
("he", ['help', 'shell']),
("hel", ['help', 'shell']),
("help", ['help']),
('run -d ubuntu:14.04 /bin/sh -c "w', []) # not complete in quoted string
])
def test_command_completion_fuzzy(command, expected):
"""
Test command suggestions.
:param command: string: text that user started typing
:param expected: list: expected completions
"""
c = completer()
e = complete_event()
c.set_fuzzy_match(True)
position = len(command)
result = list(c.get_completions(
Document(text=command, cursor_position=position),
e))
expected = list(map(lambda t: Completion(t, -len(command)), expected))
assert result == expected
pso = list(filter(lambda x: x.name.startswith('-'), all_options('ps')))
@pytest.mark.parametrize("command, expected, expected_pos", [
("ps ", pso, 0),
("ps --", list(filter(
lambda x: x.long_name and x.long_name.startswith('--'), pso)), -2),
("ps --h", list(filter(
lambda x: x.long_name and x.long_name.startswith('--h'), pso)), -3),
("ps --all ", list(filter(
lambda x: x.long_name not in ['--all'], pso)), 0),
("ps --all --quiet ", list(filter(
lambda x: x.long_name not in ['--all', '--quiet'], pso)), 0),
])
def test_options_completion_long(command, expected, expected_pos):
"""
Test command options suggestions.
:param command: string: text that user started typing
:param expected: list: expected completions
"""
c = completer()
e = complete_event()
position = len(command)
result = set(c.get_completions(
Document(text=command, cursor_position=position), e))
expected = set(map(lambda t: Completion(
t.get_name(is_long=True), expected_pos, t.display), expected))
assert result == expected
def option_map(cmd, is_long):
return {
x.get_name(is_long): x.display for x in all_options(cmd) if x.name.startswith('-')
}
psm = option_map('ps', True)
@pytest.mark.parametrize("command, expected, expected_pos", [
("ps ", sorted(psm.keys()), 0),
("ps h", ['--help'], -1),
("ps i", ['--since', '--size', '--quiet'], -1),
("ps ze", ['--size'], -2),
])
def test_options_completion_long_fuzzy(command, expected, expected_pos):
"""
Test command options suggestions.
:param command: string: text that user started typing
:param expected: list: expected completions
"""
c = completer()
e = complete_event()
c.set_fuzzy_match(True)
position = len(command)
result = list(c.get_completions(
Document(text=command, cursor_position=position), e))
expected = list(map(lambda t: Completion(
t, expected_pos, psm[t]), expected))
assert result == expected
@pytest.mark.parametrize("command, expected, expected_pos", [
("ps ", pso, 0),
("ps -", filter(
lambda x: x.name.startswith('-'), pso), -1),
("ps -h", filter(
lambda x: x.short_name and x.short_name.startswith('-h'), pso), -2),
])
def test_options_completion_short(command, expected, expected_pos):
"""
Test command options suggestions.
:param command: string: text that user started typing
:param expected: list: expected completions
"""
c = completer()
e = complete_event()
c.set_long_options(False)
position = len(command)
result = set(c.get_completions(
Document(text=command, cursor_position=position), e))
expected = set(map(lambda t: Completion(
t.get_name(
is_long=c.get_long_options()), expected_pos, t.display), expected))
assert result == expected
@pytest.mark.parametrize("command, expected, expected_pos", [
("ps --before ", cs1, 0),
("ps --before e", filter(lambda x: x.startswith('e'), cs1), -1),
("ps --before ei", filter(lambda x: x.startswith('ei'), cs1), -2),
])
def test_options_container_completion(command, expected, expected_pos):
"""
Suggest container names in relevant options (ps --before)
"""
c = completer()
e = complete_event()
c.set_containers(cs1)
position = len(command)
result = set(c.get_completions(
Document(text=command, cursor_position=position), e))
expected = set(map(lambda t: Completion(t, expected_pos), expected))
assert result == expected
@pytest.mark.parametrize("command, expected, expected_pos", [
("top ", list(map(
lambda x: (x, x), rs1)) + [('--help', '-h/--help')], 0),
("top e", map(
lambda x: (x, x), filter(lambda x: x.startswith('e'), rs1)), -1),
])
def test_options_container_running_completion(command, expected, expected_pos):
"""
Suggest running container names (top [container])
"""
c = completer()
e = complete_event()
c.set_containers(cs1)
c.set_running(rs1)
position = len(command)
result = set(c.get_completions(
Document(text=command, cursor_position=position), e))
expected_completions = set()
for text, display in expected:
if display:
expected_completions.add(Completion(text, expected_pos, display))
else:
expected_completions.add(Completion(text, expected_pos))
assert result == expected_completions
@pytest.mark.parametrize("command, expected, expected_pos", [
("rm ", ['--all-stopped', ('--help', '-h/--help')] + cs2, 0),
("rm spe", ['--all-stopped', 'desperate_hodgkin', 'desperate_torvalds', 'some-percona'], -3),
])
def test_options_container_completion_fuzzy(command, expected, expected_pos):
"""
Suggest running container names (top [container])
"""
c = completer()
e = complete_event()
c.set_containers(cs2)
c.set_fuzzy_match(True)
position = len(command)
result = list(c.get_completions(
Document(text=command, cursor_position=position), e))
expected_completions = []
for x in expected:
if isinstance(x, tuple):
expected_completions.append(Completion(x[0], expected_pos, x[1]))
else:
expected_completions.append(Completion(x, expected_pos))
assert result == expected_completions
def test_options_image_completion(completer, complete_event):
"""
Suggest image names in relevant options (images --filter)
"""
command = 'images --filter '
expected = ['ubuntu', 'hello-world', 'postgres', 'nginx']
expected_pos = 0
completer.set_images(expected)
position = len(command)
result = set(completer.get_completions(
Document(text=command, cursor_position=position), complete_event))
expected = set(map(lambda t: Completion(t, expected_pos), expected))
assert result == expected
@pytest.mark.parametrize("command, expected, expected_pos", [
('images --filter ', ['hello-world', 'nginx', 'postgres', 'ubuntu'], 0),
('images --filter n', ['nginx', 'ubuntu'], -1),
('images --filter g', ['nginx', 'postgres'], -1),
('images --filter u', ['ubuntu'], -1),
])
def test_options_image_completion_fuzzy(command, expected, expected_pos):
"""
Suggest image names in relevant options (images --filter)
"""
c = completer()
e = complete_event()
c.set_images(im1)
c.set_fuzzy_match(True)
position = len(command)
result = list(c.get_completions(
Document(text=command, cursor_position=position), e))
expected = list(map(lambda t: Completion(t, expected_pos), expected))
assert result == expected
|
[
"[email protected]"
] | |
b4a013a5db1bce9ba186a85069333e15577e431f
|
438895f04e0032b3f18c3450444b1517c301d8b1
|
/RTT/200server.py
|
fed53005cae66f686e69d5f4eac37fafa905e618
|
[] |
no_license
|
iamryanmoreno/ClientServer
|
3aed1e9d4bff7609d25febb6b3729fee04f60e42
|
9ce292de9f2848dca7097091cb3fc1a8dc397577
|
refs/heads/master
| 2020-05-20T19:45:32.732898 | 2017-03-10T03:16:58 | 2017-03-10T03:16:58 | 84,514,089 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,921 |
py
|
import socket
import sys
import datetime
import time
now = datetime.datetime.now()
print str(now)
# Create a TCP/IP socket
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# Bind the socket to the port
server_address = ('localhost', 10000)
print >>sys.stderr, 'starting up on %s port %s' % server_address
#---------------------------------------------------------CONNECTION SETUP PHASE <Protocol Phase> WS <Measurement Type> WS <No. of Probes> WS <MESSAGE SIZE> WS <Server Delay>
print 's rtt 2 200 2'
sock.bind(server_address)
# Listen for incoming connections
sock.listen(1)
while True:
# Wait for a connection
print >>sys.stderr, 'waiting for a connection'
connection, client_address = sock.accept()
try:
print '200 OK'
print >>sys.stderr, 'connection from', client_address
# Receive the data in small chunks and retransmit it
while True:
data = connection.recv(200)
#---------------------------------------------------------MEASUREMENT PHASE <Protocol Phase> WS <Probe Seq. No.> WS <Payload>
print 'm 2 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111'
print >>sys.stderr, 'received "%s"' % data
if data:
time.sleep(2)
print >>sys.stderr, 'sending data back to the client'
connection.sendall(data)
else:
print >>sys.stderr, 'no more data from', client_address
break
finally:
# Clean up the connection
print '200 OK: Closing Connection'
#---------------------------------------------------------CONNECTION TERMINATION PHASE <Protocol Phase> WS
print 't .'
connection.close()
|
[
"[email protected]"
] | |
404e2885ea8d3af435aa70e108f7ee3875cdd93b
|
d1b842eb17900c2bbfc2238cb29dbf290444152e
|
/keras/ner/mlp.py
|
72003606acf8e1b605edda65b7c1961539e09cc7
|
[] |
no_license
|
cambridgeltl/RepEval-2016
|
6d07f2819439096b280cda171038f38e375a1e74
|
c52e29312c634df03602bc0d0f2ae0f40a33ca23
|
refs/heads/master
| 2020-12-25T15:09:14.054893 | 2016-11-11T21:10:18 | 2016-11-11T21:10:18 | 61,438,829 | 4 | 2 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,672 |
py
|
#!/usr/bin/env python
import sys
import numpy as np
from os import path
from logging import info, warn
from keras.models import Sequential
from keras.layers import Reshape, Dense, Activation
from keras.layers import Merge, Flatten
from keras import optimizers
from layers import Input, FixedEmbedding
import input_data
import common
import settings
# Settings
class Defaults(object):
window = 2
max_vocab_size = None
max_train_examples = None
max_develtest_examples = 100000 # for faster develtest
examples_as_indices = True
hidden_sizes = [300]
hidden_activation = 'hard_sigmoid' # 'relu'
batch_size = 50
epochs = 10
loss = 'categorical_crossentropy' # 'mse'
verbosity = 1 # 0=quiet, 1=progress bar, 2=one line per epoch
iobes = False # Map tags to IOBES on input
token_level_eval = False # Token-level eval even if IOB-like tagging
optimizer = 'adam' # 'sgd'
test = False
config = settings.from_cli(['datadir', 'wordvecs'], Defaults)
optimizer = optimizers.get(config.optimizer)
output_name = 'mlp--' + path.basename(config.datadir.rstrip('/'))
common.setup_logging(output_name)
settings.log_with(config, info)
# Data
data = input_data.read_data_sets(config.datadir, config.wordvecs, config)
embedding = common.word_to_vector_to_matrix(config.word_to_vector)
if config.max_train_examples and len(data.train) > config.max_train_examples:
warn('cropping train data from %d to %d' % (len(data.train),
config.max_train_examples))
data.train.crop(config.max_train_examples)
# Model
model = Sequential()
# Separate embedded-words and word-features sequences
embedded = Sequential()
embedded.add(FixedEmbedding(embedding.shape[0], embedding.shape[1],
input_length=data.input_size, weights=[embedding]))
features = Sequential()
features.add(Input(data.feature_shape))
model.add(Merge([embedded, features], mode='concat', concat_axis=2))
model.add(Flatten())
# Fully connected layers
for size in config.hidden_sizes:
model.add(Dense(size))
model.add(Activation(config.hidden_activation))
model.add(Dense(data.output_size))
model.add(Activation('softmax'))
model.compile(optimizer=optimizer, loss=config.loss)
def predictions(model, inputs):
output = list(model.predict(inputs, batch_size=config.batch_size))
return np.argmax(np.asarray(output), axis=1)
def eval_report(prefix, model, dataset, config, log=info):
pred = predictions(model, dataset.inputs)
gold = np.argmax(dataset.labels, axis=1)
summary = common.performance_summary(dataset.words, gold, pred, config)
for s in summary.split('\n'):
log(prefix + ' ' + s)
small_train = data.train.subsample(config.max_develtest_examples)
small_devel = data.devel.subsample(config.max_develtest_examples)
for epoch in range(1, config.epochs+1):
model.fit(data.train.inputs, data.train.labels,
batch_size=config.batch_size, nb_epoch=1,
verbose=config.verbosity)
eval_report('Ep %d train' % epoch, model, small_train, config)
eval_report('Ep %d devel' % epoch, model, small_devel, config)
data.train.shuffle()
eval_report('FINAL train', model, data.train, config)
eval_report('FINAL devel', model, data.devel, config)
pred = predictions(model, data.devel.inputs)
common.save_gold_and_prediction(data.devel, pred, config, output_name)
if config.test:
eval_report('TEST', model, data.test, config)
pred = predictions(model, data.test.inputs)
common.save_gold_and_prediction(data.test, pred, config,
'TEST--' + output_name)
|
[
"[email protected]"
] | |
7d22825383aee94201b5b6c2910f536798d1719e
|
56550a643bf655ffe5499f4b6ee9db07dae77c40
|
/mldl/11.py
|
27c22a2edc70bf4d81a5eeb2678da3c6d94f34e3
|
[] |
no_license
|
DongJoonLeeDJ/djjsp
|
06633d0a7b2d7d72449c253e265b18e3042bec72
|
87de397934748cfaa3898b56b5392c9cc63a12b0
|
refs/heads/main
| 2023-08-14T04:25:50.524691 | 2021-10-08T01:08:52 | 2021-10-08T01:08:52 | 397,157,486 | 4 | 7 | null | null | null | null |
UTF-8
|
Python
| false | false | 39 |
py
|
# print(rfclf.predict([[9.4,1.6,3.3]]))
|
[
"[email protected]"
] | |
80bb26a67114fdec2929e2a536de88f8e380d363
|
09b2adcf32f445c2a5dcd3f68cfe7b33b62427b6
|
/Sujets/Brut/DFT_003_HM/HM_003.py
|
8d6d01b28bfd80ecdc5418d42db3d1c9d793f533
|
[] |
no_license
|
aboutelier/ICM_APATHY_TASKS
|
5be93afcf43ccf362cd6cb83bac8aac5d9db96ce
|
f6b732c55656a71f447126415084ca911168dcc7
|
refs/heads/master
| 2020-04-19T10:33:16.761807 | 2019-02-25T10:19:09 | 2019-02-25T10:19:09 | 168,143,815 | 0 | 0 | null | 2019-01-29T17:08:33 | 2019-01-29T11:31:12 |
Python
|
UTF-8
|
Python
| false | false | 82,800 |
py
|
Python 3.5.2 (v3.5.2:4def2a2901a5, Jun 25 2016, 22:01:18) [MSC v.1900 32 bit (Intel)] on win32
Type "copyright", "credits" or "license()" for more information.
>>>
RESTART: C:\Users\ECOCAPTURE\Desktop\ECOCAPTURE\ICM_APATHY_TASKS\ICM_APATHY_TASKS m faible-p forte.py
Nom sujet :HM_003
TACHE VERBALE FACILE FAIBLE GAIN
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:864
clic y:474
Bien! NR=1
RT=4.384830043216375
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:420
clic y:546
Bien! NR=2
RT=2.0056607133040307
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:505
clic y:636
Bien! NR=3
RT=2.5074395836393153
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:586
clic y:559
Bien! NR=4
RT=1.8884513735783592
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:601
clic y:379
Bien! NR=5
RT=1.9225157558845076
Distracteur:[504.0, 636.0]
Cible:[504.0, 636.0]
clic x:771
clic y:565
Bien! NR=6
RT=1.5754477329659622
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:520
clic y:646
Bien! NR=7
RT=1.4008287993199584
Distracteur:[414.0, 546.0]
Cible:[414.0, 546.0]
clic x:782
clic y:560
Bien! NR=8
RT=2.709030802846522
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:598
clic y:379
Bien! NR=9
RT=2.017840395618137
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:959
clic y:553
Bien! NR=10
RT=2.0819158302229077
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:877
clic y:651
Bien! NR=11
RT=1.8090212849056115
Distracteur:[414.0, 546.0]
Cible:[414.0, 546.0]
clic x:695
clic y:476
Bien! NR=12
RT=1.6403769104599704
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:771
clic y:373
Bien! NR=13
RT=5.641351268634853
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:956
clic y:540
Bien! NR=14
RT=3.367435185694209
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:775
clic y:385
Bien! NR=15
RT=1.5580216959821982
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:424
clic y:561
Bien! NR=16
RT=1.8920070629685668
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:780
clic y:560
Bien! NR=17
RT=1.51710398596596
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:694
clic y:458
Bien! NR=18
RT=1.7655169103450987
Distracteur:[594.0, 366.0]
Cible:[594.0, 366.0]
clic x:681
clic y:455
Bien! NR=19
RT=2.761897631263487
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:419
clic y:550
Bien! NR=20
RT=1.8922322935529934
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:1042
clic y:660
Bien! NR=21
RT=2.0078391730550322
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:867
clic y:478
Bien! NR=22
RT=2.267078755217433
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:764
clic y:543
Bien! NR=23
RT=4.303699032862333
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:858
clic y:458
Bien! NR=24
RT=1.8053679545698813
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:508
clic y:643
Bien! NR=25
RT=1.6467412129302872
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:863
clic y:663
Bien! NR=26
RT=3.8917559862514963
Distracteur:[504.0, 636.0]
Cible:[504.0, 636.0]
clic x:785
clic y:546
Bien! NR=27
RT=1.53801186624667
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:516
clic y:481
Bien! NR=28
RT=1.4358503090459038
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:688
clic y:290
Bien! NR=29
RT=1.41629545329603
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:610
clic y:383
Bien! NR=30
RT=1.7990237546471803
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:683
clic y:452
Bien! NR=31
RT=1.6839707208445418
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:688
clic y:275
Bien! NR=32
RT=1.9202195526403756
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:688
clic y:635
Bien! NR=33
RT=5.274735364319696
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:492
clic y:633
Bien! NR=34
RT=1.6572125889537688
Distracteur:[414.0, 546.0]
Cible:[414.0, 546.0]
clic x:689
clic y:272
Bien! NR=35
RT=1.3060510309324798
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:410
clic y:544
Bien! NR=36
RT=2.2645093214282497
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:958
clic y:564
Bien! NR=37
RT=1.9539380890764448
Distracteur:[504.0, 636.0]
Cible:[504.0, 636.0]
clic x:602
clic y:357
Bien! NR=38
RT=2.1435350617148146
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:319
clic y:644
Bien! NR=39
RT=1.6413475763301903
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:316
clic y:642
Bien! NR=40
RT=4.451372347591914
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:526
clic y:640
Bien! NR=41
RT=1.4291680581185204
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:595
clic y:562
Bien! NR=42
RT=1.9123524821723237
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:696
clic y:284
Bien! NR=43
RT=1.885679273288801
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:689
clic y:637
Bien! NR=44
RT=3.771427469597981
Distracteur:[414.0, 546.0]
Cible:[414.0, 546.0]
clic x:973
clic y:561
Bien! NR=45
RT=5.037764892090351
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:506
clic y:468
Bien! NR=46
RT=1.8185384053018225
Distracteur:[594.0, 366.0]
Cible:[594.0, 366.0]
clic x:324
clic y:650
Bien! NR=47
RT=1.4146486854164664
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:682
clic y:470
Bien! NR=48
RT=1.5732557347645297
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:499
clic y:457
Bien! NR=49
RT=1.528984181346317
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:860
clic y:646
Bien! NR=50
RT=1.4057067440354842
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:877
clic y:656
Bien! NR=51
RT=7.924459549161398
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:515
clic y:642
Bien! NR=52
RT=2.6413959865468826
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:698
clic y:857
A cรดtรฉ!
ratรฉ!AC=1
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:698
clic y:470
Bien! NR=53
RT=1.6478624427795125
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:605
clic y:372
Bien! NR=54
RT=1.5197608042988122
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:786
clic y:382
Bien! NR=55
RT=2.0851580839728285
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:693
clic y:636
Bien! NR=56
RT=1.4003578253474416
Distracteur:[1044.0, 636.0]
Cible:[1044.0, 636.0]
clic x:423
clic y:552
Bien! NR=57
RT=1.9704246396515828
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:511
clic y:455
Bien! NR=58
RT=2.393885215273656
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:600
clic y:547
Bien! NR=59
RT=2.761315067638918
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:1055
clic y:636
Bien! NR=60
RT=1.8069749276102982
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:693
clic y:630
Bien! NR=61
RT=2.0222190586920306
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
Plus que 30 sec
clic x:862
clic y:638
Bien! NR=62
RT=8.405641923575843
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:697
clic y:461
Bien! NR=63
RT=2.0498190360459034
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:960
clic y:550
Bien! NR=64
RT=2.644956188753895
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:421
clic y:555
Bien! NR=65
RT=2.9438503024818203
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:790
clic y:375
Bien! NR=66
RT=2.180362928932965
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:862
clic y:641
Bien! NR=67
RT=1.7677454213371107
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:781
clic y:553
Bien! NR=68
RT=2.5113817342508753
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:778
clic y:570
Bien! NR=69
RT=1.7693778302540863
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:1048
clic y:654
Bien! NR=70
RT=1.5465858079296027
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:962
clic y:556
Bien! NR=71
RT=1.1508380300816157
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:329
clic y:644
Bien! NR=72
RT=4.7703739320008935
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
THE END
Bonnes rรฉponses:72
Erreurs distracteur:0
Erreurs gris:0
Erreurs ร cรดtรฉ:1
Erreurs totales:1
Nombre de rรฉponses:73
Taux de rรฉussite= 98.63
RTmoy sec= 2.423
RTmax sec= 8.406
RTmin sec= 1.151
TACHE VERBALE FACILE FORT GAIN
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:953
clic y:578
Distracteur touchรฉ!
ratรฉ!NED=1
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
Distracteur:[414.0, 546.0]
Cible:[414.0, 546.0]
clic x:869
clic y:634
Bien! NR=1
RT=1.5214941362099523
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:421
clic y:548
Bien! NR=2
RT=2.2758861326062743
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:680
clic y:458
Bien! NR=3
RT=1.544936578513557
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:781
clic y:383
Bien! NR=4
RT=1.2813376153127365
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:878
clic y:468
Bien! NR=5
RT=2.141540806940867
Distracteur:[1044.0, 636.0]
Cible:[1044.0, 636.0]
clic x:937
clic y:563
Bien! NR=6
RT=2.2641478858273842
Distracteur:[504.0, 456.0]
Cible:[504.0, 456.0]
clic x:784
clic y:548
Bien! NR=7
RT=1.9509341941052867
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:520
clic y:479
Bien! NR=8
RT=2.294131450969047
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:1039
clic y:654
Bien! NR=9
RT=4.932055850620827
Distracteur:[594.0, 366.0]
Cible:[594.0, 366.0]
clic x:1048
clic y:664
Bien! NR=10
RT=1.2686340359925623
Distracteur:[1044.0, 636.0]
Cible:[1044.0, 636.0]
clic x:510
clic y:643
Bien! NR=11
RT=2.3216936847641705
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:1055
clic y:652
Bien! NR=12
RT=7.265183782413288
Distracteur:[1044.0, 636.0]
Cible:[1044.0, 636.0]
clic x:689
clic y:276
Bien! NR=13
RT=9.016601012019692
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:505
clic y:473
Bien! NR=14
RT=1.9365210777262973
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:327
clic y:641
Bien! NR=15
RT=1.51887588194802
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:1034
clic y:660
Bien! NR=16
RT=2.0236040831966875
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:604
clic y:368
Bien! NR=17
RT=2.431268569215547
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:497
clic y:637
Bien! NR=18
RT=2.1505438764767746
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:595
clic y:378
Bien! NR=19
RT=1.76314439947123
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:420
clic y:555
Bien! NR=20
RT=1.314396870238511
Distracteur:[684.0, 276.0]
Cible:[684.0, 276.0]
clic x:687
clic y:462
Bien! NR=21
RT=1.6487658266536869
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:773
clic y:372
Bien! NR=22
RT=2.3888550655548215
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:424
clic y:561
Bien! NR=23
RT=1.6400688081486692
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:506
clic y:644
Bien! NR=24
RT=1.9421005603277308
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:1050
clic y:651
Bien! NR=25
RT=4.321855325657168
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:418
clic y:553
Bien! NR=26
RT=1.7770131060404992
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:1045
clic y:642
Bien! NR=27
RT=12.156216076950898
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:867
clic y:448
Bien! NR=28
RT=1.9561506000815143
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:509
clic y:655
Bien! NR=29
RT=1.6509619274158354
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:786
clic y:560
Bien! NR=30
RT=1.668749400000479
Distracteur:[594.0, 366.0]
Cible:[594.0, 366.0]
clic x:779
clic y:549
Bien! NR=31
RT=2.410021407161935
Distracteur:[864.0, 456.0]
Cible:[864.0, 456.0]
clic x:1039
clic y:634
Bien! NR=32
RT=1.5697172761293814
Distracteur:[1044.0, 636.0]
Cible:[1044.0, 636.0]
clic x:422
clic y:552
Bien! NR=33
RT=1.5346522792596602
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:864
clic y:447
Bien! NR=34
RT=2.081085882185903
Distracteur:[1044.0, 636.0]
Cible:[1044.0, 636.0]
clic x:508
clic y:471
Bien! NR=35
RT=2.009194659122386
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:592
clic y:559
Bien! NR=36
RT=2.1402173208473414
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
clic x:949
clic y:556
Bien! NR=37
RT=1.6372995796515966
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:675
clic y:468
Bien! NR=38
RT=2.0699560451643038
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
clic x:866
clic y:647
Bien! NR=39
RT=1.316026817619047
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:592
clic y:363
Bien! NR=40
RT=3.281584589469105
Distracteur:[504.0, 636.0]
Cible:[504.0, 636.0]
clic x:418
clic y:554
Bien! NR=41
RT=2.4338872337335715
Distracteur:[504.0, 636.0]
Cible:[504.0, 636.0]
clic x:960
clic y:559
Bien! NR=42
RT=8.055546210833882
Distracteur:[684.0, 636.0]
Cible:[684.0, 636.0]
clic x:313
clic y:636
Bien! NR=43
RT=2.396092392949811
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:777
clic y:564
Bien! NR=44
RT=2.791233402064904
Distracteur:[504.0, 456.0]
Cible:[504.0, 456.0]
clic x:415
clic y:549
Bien! NR=45
RT=2.6662808892054386
Distracteur:[504.0, 456.0]
Cible:[504.0, 456.0]
clic x:967
clic y:559
Bien! NR=46
RT=6.338205260959796
Distracteur:[684.0, 456.0]
Cible:[684.0, 456.0]
clic x:327
clic y:654
Bien! NR=47
RT=1.7664719864845324
Distracteur:[594.0, 546.0]
Cible:[594.0, 546.0]
clic x:874
clic y:644
Bien! NR=48
RT=1.5134252197536853
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:601
clic y:365
Bien! NR=49
RT=1.5399749415590236
Distracteur:[864.0, 636.0]
Cible:[864.0, 636.0]
clic x:1046
clic y:658
Bien! NR=50
RT=1.562570615326706
Distracteur:[774.0, 366.0]
Cible:[774.0, 366.0]
Plus que 30 sec
clic x:870
clic y:470
Bien! NR=51
RT=9.409381407687079
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:788
clic y:370
Bien! NR=52
RT=2.150089312747241
Distracteur:[774.0, 546.0]
Cible:[774.0, 546.0]
clic x:326
clic y:650
Bien! NR=53
RT=5.91460355724837
Distracteur:[954.0, 546.0]
Cible:[954.0, 546.0]
clic x:691
clic y:466
Bien! NR=54
RT=2.06234825653479
Distracteur:[324.0, 636.0]
Cible:[324.0, 636.0]
THE END
Bonnes rรฉponses:54
Erreurs distracteur:1
Erreurs gris:0
Erreurs ร cรดtรฉ:0
Erreurs totales:1
Nombre de rรฉponses:55
Taux de rรฉussite= 98.18
RTmoy sec= 2.871
RTmax sec= 12.156
RTmin sec= 1.269
TACHE VERBALE DIFFICILE FAIBLE GAIN
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue 1:[549.0, 501.0, 639.0, 591.0]
Red 2:[549.0, 321.0, 639.0, 411.0]
Blue 2:[459.0, 411.0, 549.0, 501.0]
Blue 3:[369.0, 501.0, 459.0, 591.0]
clic x:787
clic y:365
clicn=[774.0, 366.0]
clic x:695
clic y:293
clicn=[684.0, 276.0]
clic x:697
clic y:469
Pas consonne=1
clic x:331
clic y:640
clicn=[324.0, 636.0]
clic x:871
clic y:647
clicn=[864.0, 636.0]
clic x:694
clic y:649
clicn=[684.0, 636.0]
clic x:1055
clic y:636
clicn=[1044.0, 636.0]
Combi:[[324.0, 636.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
NR=1
RT sec=5.042898426339775
clic x:325
clic y:664
clicn=[324.0, 636.0]
clic x:697
clic y:646
Pas consonne=2
clic x:876
clic y:655
clicn=[864.0, 636.0]
clic x:692
clic y:645
clicn=[684.0, 636.0]
clic x:1046
clic y:632
clicn=[1044.0, 636.0]
clic x:327
clic y:652
clicn=[324.0, 636.0]
Combi:[[864.0, 636.0], [684.0, 636.0], [1044.0, 636.0], [324.0, 636.0]]
NR=2
RT sec=5.615073956862375
clic x:778
clic y:357
clicn=[774.0, 366.0]
clic x:686
clic y:275
clicn=[684.0, 276.0]
clic x:873
clic y:469
clicn=[864.0, 456.0]
clic x:340
clic y:634
clicn=[324.0, 636.0]
Combi:[[774.0, 366.0], [684.0, 276.0], [864.0, 456.0], [324.0, 636.0]]
clic x:326
clic y:634
NR=3
RT sec=13.657043153195332
clic sur un mรชme cercle:1
clic x:320
clic y:636
clicn=[324.0, 636.0]
clic x:861
clic y:659
clicn=[864.0, 636.0]
clic x:695
clic y:657
clicn=[684.0, 636.0]
clic x:1033
clic y:651
clicn=[1044.0, 636.0]
Combi:[[324.0, 636.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
Dรฉjร fait:1
clic x:329
clic y:647
clicn=[324.0, 636.0]
clic x:692
clic y:659
Pas consonne=3
clic x:696
clic y:475
clicn=[684.0, 456.0]
clic x:877
clic y:649
clicn=[864.0, 636.0]
clic x:687
clic y:641
clicn=[684.0, 636.0]
clic x:1057
clic y:649
clicn=[1044.0, 636.0]
Combi:[[684.0, 456.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
NR=4
RT sec=15.744350568738014
clic x:326
clic y:652
clicn=[324.0, 636.0]
clic x:687
clic y:648
Pas consonne=4
clic x:685
clic y:459
clicn=[684.0, 456.0]
clic x:871
clic y:656
clicn=[864.0, 636.0]
clic x:691
clic y:645
clicn=[684.0, 636.0]
clic x:1051
clic y:656
clicn=[1044.0, 636.0]
Combi:[[684.0, 456.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
Dรฉjร fait:2
clic x:326
clic y:647
clicn=[324.0, 636.0]
clic x:685
clic y:633
Pas consonne=5
clic x:689
clic y:460
clicn=[684.0, 456.0]
clic x:869
clic y:660
clicn=[864.0, 636.0]
clic x:694
clic y:638
clicn=[684.0, 636.0]
clic x:1048
clic y:660
clicn=[1044.0, 636.0]
Combi:[[684.0, 456.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
Dรฉjร fait:3
clic x:337
clic y:653
clicn=[324.0, 636.0]
clic x:702
clic y:633
Pas consonne=6
clic x:683
clic y:470
clicn=[684.0, 456.0]
clic x:868
clic y:641
clicn=[864.0, 636.0]
clic x:692
clic y:656
clicn=[684.0, 636.0]
clic x:1051
clic y:646
clicn=[1044.0, 636.0]
Combi:[[684.0, 456.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
Dรฉjร fait:4
clic x:324
clic y:645
clicn=[324.0, 636.0]
clic x:701
clic y:657
Pas consonne=7
clic x:692
clic y:458
clicn=[684.0, 456.0]
clic x:870
clic y:650
clicn=[864.0, 636.0]
clic x:693
clic y:657
clicn=[684.0, 636.0]
clic x:1045
clic y:651
clicn=[1044.0, 636.0]
Combi:[[684.0, 456.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
Dรฉjร fait:5
clic x:328
clic y:649
clicn=[324.0, 636.0]
clic x:692
clic y:628
Pas consonne=8
clic x:688
clic y:461
clicn=[684.0, 456.0]
Plus que 30 sec
clic x:853
clic y:653
clicn=[864.0, 636.0]
clic x:685
clic y:651
clicn=[684.0, 636.0]
clic x:1043
clic y:671
clicn=[1044.0, 636.0]
Combi:[[684.0, 456.0], [864.0, 636.0], [684.0, 636.0], [1044.0, 636.0]]
Dรฉjร fait:6
clic x:325
clic y:645
clicn=[324.0, 636.0]
clic x:695
clic y:641
Pas consonne=9
clic x:677
clic y:465
clicn=[684.0, 456.0]
THE END
Bonnes rรฉponses:4
Erreurs couleur:0
Erreurs rรฉpรฉtition:6
Erreurs mรชme cercle:1
Erreurs pas consonne:9
Erreurs pas voyelle:0
Erreurs ร cotรฉ:0
Erreurs totales:16
Nombre de rรฉponses:20
Taux de rรฉussite= 20.00
RTmoy sec= 10.015
RTmax sec= 15.744
RTmin sec= 5.043
TACHE VERBALE DIFFICILE FORT GAIN
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue 1:[819.0, 411.0, 909.0, 501.0]
Red 2:[639.0, 411.0, 729.0, 501.0]
Blue 2:[729.0, 321.0, 819.0, 411.0]
Blue 3:[909.0, 501.0, 999.0, 591.0]
clic x:425
clic y:553
clicn=[414.0, 546.0]
clic x:606
clic y:551
clicn=[594.0, 546.0]
clic x:863
clic y:638
clicn=[864.0, 636.0]
clic x:518
clic y:470
clicn=[504.0, 456.0]
Combi:[[414.0, 546.0], [594.0, 546.0], [864.0, 636.0], [504.0, 456.0]]
NR=1
RT sec=8.171537910532948
clic x:609
clic y:564
clicn=[594.0, 546.0]
clic x:511
clic y:635
Pas consonne=1
clic x:415
clic y:555
clicn=[414.0, 546.0]
clic x:604
clic y:545
clicn=[594.0, 546.0]
clic x:866
clic y:644
clicn=[864.0, 636.0]
clic x:511
clic y:460
clicn=[504.0, 456.0]
Combi:[[414.0, 546.0], [594.0, 546.0], [864.0, 636.0], [504.0, 456.0]]
Dรฉjร fait:1
clic x:603
clic y:563
clicn=[594.0, 546.0]
clic x:509
clic y:656
Pas consonne=2
clic x:601
clic y:552
clicn=[594.0, 546.0]
clic x:872
clic y:663
clicn=[864.0, 636.0]
clic x:499
clic y:471
clicn=[504.0, 456.0]
clic x:785
clic y:562
clicn=[774.0, 546.0]
Combi:[[594.0, 546.0], [864.0, 636.0], [504.0, 456.0], [774.0, 546.0]]
NR=2
RT sec=28.515942551021567
clic x:332
clic y:650
clicn=[324.0, 636.0]
clic x:596
clic y:367
clicn=[594.0, 366.0]
clic x:1047
clic y:664
clicn=[1044.0, 636.0]
clic x:864
clic y:653
clicn=[864.0, 636.0]
Combi:[[324.0, 636.0], [594.0, 366.0], [1044.0, 636.0], [864.0, 636.0]]
NR=3
RT sec=19.593391923370746
clic x:1040
clic y:641
clicn=[1044.0, 636.0]
clic x:774
clic y:554
clicn=[774.0, 546.0]
clic x:601
clic y:543
clicn=[594.0, 546.0]
clic x:866
clic y:644
clicn=[864.0, 636.0]
Combi:[[1044.0, 636.0], [774.0, 546.0], [594.0, 546.0], [864.0, 636.0]]
NR=4
RT sec=12.525986029960222
clic x:509
clic y:467
clicn=[504.0, 456.0]
clic x:858
clic y:642
clicn=[864.0, 636.0]
clic x:1053
clic y:656
clicn=[1044.0, 636.0]
clic x:778
clic y:562
clicn=[774.0, 546.0]
Combi:[[504.0, 456.0], [864.0, 636.0], [1044.0, 636.0], [774.0, 546.0]]
NR=5
RT sec=10.291150940594093
clic x:595
clic y:556
clicn=[594.0, 546.0]
clic x:868
clic y:642
clicn=[864.0, 636.0]
clic x:1050
clic y:648
clicn=[1044.0, 636.0]
clic x:780
clic y:548
clicn=[774.0, 546.0]
Combi:[[594.0, 546.0], [864.0, 636.0], [1044.0, 636.0], [774.0, 546.0]]
NR=6
RT sec=10.234278782130218
clic x:607
clic y:557
clicn=[594.0, 546.0]
clic x:865
clic y:643
clicn=[864.0, 636.0]
clic x:514
clic y:461
clicn=[504.0, 456.0]
clic x:783
clic y:553
clicn=[774.0, 546.0]
Combi:[[594.0, 546.0], [864.0, 636.0], [504.0, 456.0], [774.0, 546.0]]
Dรฉjร fait:2
clic x:868
clic y:641
clicn=[864.0, 636.0]
clic x:1050
clic y:649
clicn=[1044.0, 636.0]
clic x:776
clic y:562
clicn=[774.0, 546.0]
clic x:609
clic y:546
clicn=[594.0, 546.0]
Combi:[[864.0, 636.0], [1044.0, 636.0], [774.0, 546.0], [594.0, 546.0]]
NR=7
RT sec=7.959409264074452
clic x:873
clic y:656
clicn=[864.0, 636.0]
clic x:873
clic y:656
clic sur un mรชme cercle:1
clic x:519
clic y:462
clicn=[504.0, 456.0]
clic x:857
clic y:646
clicn=[864.0, 636.0]
clic x:1044
clic y:642
clicn=[1044.0, 636.0]
clic x:776
clic y:550
clicn=[774.0, 546.0]
Combi:[[504.0, 456.0], [864.0, 636.0], [1044.0, 636.0], [774.0, 546.0]]
Dรฉjร fait:3
clic x:605
clic y:561
clicn=[594.0, 546.0]
clic x:868
clic y:650
clicn=[864.0, 636.0]
clic x:530
clic y:471
clicn=[504.0, 456.0]
Plus que 30 sec
THE END
Bonnes rรฉponses:7
Erreurs couleur:0
Erreurs rรฉpรฉtition:3
Erreurs mรชme cercle:1
Erreurs pas consonne:2
Erreurs pas voyelle:0
Erreurs ร cotรฉ:0
Erreurs totales:6
Nombre de rรฉponses:13
Taux de rรฉussite= 53.85
RTmoy sec= 13.899
RTmax sec= 28.516
RTmin sec= 7.959
TACHE SPATIALE DIFFICILE FAIBLE GAIN
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue 1:[819.0, 411.0, 909.0, 501.0]
Red 2:[279.0, 591.0, 369.0, 681.0]
Blue 2:[639.0, 591.0, 729.0, 681.0]
Blue 3:[549.0, 321.0, 639.0, 411.0]
clic x:769
clic y:380
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:689
clic y:476
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:509
clic y:480
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:595
clic y:559
clicn=[549.0, 501.0, 639.0, 591.0]
Combi:[[459.0, 411.0, 549.0, 501.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
NR=1
RT sec=3.731926373803958
clic x:1037
clic y:631
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:945
clic y:546
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:867
clic y:645
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:768
clic y:545
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=2
RT sec=2.6430201903424404
clic x:770
clic y:371
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:683
clic y:475
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:585
clic y:572
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:500
clic y:650
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
NR=3
RT sec=2.5079212242698077
clic x:1045
clic y:640
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:962
clic y:569
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:780
clic y:559
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:861
clic y:647
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:1
clic x:788
clic y:394
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:699
clic y:480
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:591
clic y:560
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:512
clic y:642
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:2
clic x:971
clic y:557
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:782
clic y:544
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:868
clic y:651
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:1056
clic y:641
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:3
clic x:786
clic y:375
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:689
clic y:470
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:591
clic y:545
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:527
clic y:648
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:4
clic x:1056
clic y:641
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:951
clic y:563
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:779
clic y:554
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:873
clic y:658
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:5
clic x:521
clic y:485
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:428
clic y:557
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:506
clic y:661
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:694
clic y:477
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [459.0, 591.0, 549.0, 681.0], [639.0, 411.0, 729.0, 501.0]]
NR=4
RT sec=2.339248542155019
clic x:774
clic y:392
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:760
clic y:563
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:873
clic y:625
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:957
clic y:563
clicn=[909.0, 501.0, 999.0, 591.0]
Combi:[[729.0, 321.0, 819.0, 411.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0]]
NR=5
RT sec=1.4090056131235542
clic x:1039
clic y:644
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:960
clic y:573
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:876
clic y:651
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:790
clic y:558
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:6
clic x:773
clic y:375
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:695
clic y:472
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:602
clic y:566
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:530
clic y:660
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:7
clic x:795
clic y:377
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:693
clic y:461
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:603
clic y:547
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:533
clic y:660
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:8
clic x:778
clic y:562
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:876
clic y:663
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:957
clic y:531
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1045
clic y:660
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:9
clic x:777
clic y:375
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:691
clic y:471
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:602
clic y:565
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:525
clic y:647
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:10
clic x:783
clic y:561
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:964
clic y:559
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:878
clic y:657
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:1061
clic y:656
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:11
clic x:1047
clic y:653
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:964
clic y:559
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:870
clic y:658
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:778
clic y:557
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:12
clic x:786
clic y:385
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:686
clic y:489
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:599
clic y:561
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:511
clic y:654
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:13
clic x:518
clic y:456
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:424
clic y:559
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:528
clic y:639
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:612
clic y:563
clicn=[549.0, 501.0, 639.0, 591.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0]]
NR=6
RT sec=1.66764170860165
clic x:705
clic y:473
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:797
clic y:388
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:776
clic y:559
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:875
clic y:659
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
NR=7
RT sec=1.565435433488915
clic x:967
clic y:556
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1047
clic y:659
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:777
clic y:368
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:687
clic y:459
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=8
RT sec=8.303566109894518
clic x:602
clic y:544
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:536
clic y:647
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:789
clic y:558
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:883
clic y:652
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
NR=9
RT sec=1.6820642608703338
clic x:962
clic y:561
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1047
clic y:641
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:776
clic y:380
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:686
clic y:461
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:14
clic x:580
clic y:563
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:514
clic y:643
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:502
clic y:469
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:421
clic y:556
clicn=[369.0, 501.0, 459.0, 591.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0]]
Dรฉjร fait:15
clic x:784
clic y:388
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:684
clic y:461
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:803
clic y:546
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:882
clic y:641
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
Dรฉjร fait:16
clic x:965
clic y:560
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1041
clic y:658
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:1188
clic y:29
A cรดtรฉ:1
clic x:765
clic y:383
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:697
clic y:461
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:608
clic y:548
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:526
clic y:635
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:17
clic x:788
clic y:547
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:869
clic y:635
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:951
clic y:556
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1052
clic y:650
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:18
clic x:766
clic y:372
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:682
clic y:477
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:601
clic y:552
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:521
clic y:658
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:19
clic x:804
clic y:538
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:866
clic y:628
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:954
clic y:553
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1059
clic y:646
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:20
clic x:519
clic y:455
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:425
clic y:542
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:506
clic y:636
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:595
clic y:566
clicn=[549.0, 501.0, 639.0, 591.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0]]
Dรฉjร fait:21
clic x:690
clic y:475
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:762
clic y:369
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:787
clic y:550
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:876
clic y:651
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
Dรฉjร fait:22
clic x:955
clic y:566
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1042
clic y:655
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:787
clic y:357
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:691
clic y:475
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:23
clic x:608
clic y:557
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:513
clic y:644
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:788
clic y:384
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:688
clic y:467
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:24
clic x:786
clic y:547
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:869
clic y:650
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:968
clic y:551
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1044
clic y:649
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:25
clic x:519
clic y:466
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:420
clic y:554
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:520
clic y:657
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:613
clic y:561
clicn=[549.0, 501.0, 639.0, 591.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0]]
Dรฉjร fait:26
clic x:707
clic y:460
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:790
clic y:382
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:781
clic y:555
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:865
clic y:659
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
Dรฉjร fait:27
clic x:1061
clic y:637
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:956
clic y:563
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:877
clic y:663
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:783
clic y:553
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:28
clic x:760
clic y:403
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:690
clic y:475
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:593
clic y:557
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:488
clic y:657
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:29
clic x:521
clic y:474
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:419
clic y:546
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:767
clic y:374
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:686
clic y:482
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
NR=10
RT sec=2.2530098436842536
clic x:592
clic y:560
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:518
clic y:649
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:688
clic y:453
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:780
clic y:541
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0]]
NR=11
RT sec=2.3030118539389832
clic x:869
clic y:645
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:963
clic y:557
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1055
clic y:644
clicn=[999.0, 591.0, 1089.0, 681.0]
Plus que 30 sec
clic x:770
clic y:555
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:30
clic x:778
clic y:360
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:688
clic y:452
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:596
clic y:551
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:492
clic y:659
clicn=[459.0, 591.0, 549.0, 681.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:31
clic x:524
clic y:472
clicn=[459.0, 411.0, 549.0, 501.0]
clic x:426
clic y:559
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:770
clic y:396
clicn=[729.0, 321.0, 819.0, 411.0]
clic x:692
clic y:459
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [459.0, 411.0, 549.0, 501.0], [639.0, 411.0, 729.0, 501.0], [729.0, 321.0, 819.0, 411.0]]
Dรฉjร fait:32
clic x:604
clic y:538
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:513
clic y:668
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:685
clic y:458
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:790
clic y:541
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0]]
Dรฉjร fait:33
clic x:883
clic y:652
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:1046
clic y:657
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:943
clic y:550
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:787
clic y:378
clicn=[729.0, 321.0, 819.0, 411.0]
Combi:[[729.0, 321.0, 819.0, 411.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=12
RT sec=2.927058521387835
clic x:686
clic y:468
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:618
clic y:565
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:501
clic y:673
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:777
clic y:546
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0]]
Dรฉjร fait:34
clic x:866
clic y:642
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:963
clic y:558
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1055
clic y:649
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:778
clic y:383
clicn=[729.0, 321.0, 819.0, 411.0]
Combi:[[729.0, 321.0, 819.0, 411.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:35
clic x:688
clic y:472
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:596
clic y:572
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:529
clic y:642
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:789
clic y:564
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0]]
Dรฉjร fait:36
clic x:876
clic y:664
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:964
clic y:560
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1040
clic y:632
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:779
clic y:381
clicn=[729.0, 321.0, 819.0, 411.0]
Combi:[[729.0, 321.0, 819.0, 411.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:37
clic x:674
clic y:463
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:594
clic y:559
clicn=[549.0, 501.0, 639.0, 591.0]
clic x:520
clic y:662
clicn=[459.0, 591.0, 549.0, 681.0]
clic x:799
clic y:554
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[459.0, 591.0, 549.0, 681.0], [549.0, 501.0, 639.0, 591.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0]]
Dรฉjร fait:38
clic x:880
clic y:665
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:963
clic y:560
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1052
clic y:640
clicn=[999.0, 591.0, 1089.0, 681.0]
THE END
Bonnes rรฉponses:12
Erreurs couleur:0
Erreurs rรฉpรฉtition:38
Erreurs mรชme cercle:0
Erreurs ร cotรฉ:1
Erreurs totales:39
Nombre de rรฉponses:51
Taux de rรฉussite= 23.53
RTmoy sec= 2.778
RTmax sec= 8.304
RTmin sec= 1.409
TACHE SPATIALE DIFFICILE FORT GAIN
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue 1:[549.0, 501.0, 639.0, 591.0]
Red 2:[639.0, 231.0, 729.0, 321.0]
Blue 2:[459.0, 591.0, 549.0, 681.0]
Blue 3:[459.0, 411.0, 549.0, 501.0]
clic x:593
clic y:363
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:704
clic y:459
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:864
clic y:631
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:879
clic y:455
clicn=[819.0, 411.0, 909.0, 501.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0]]
NR=1
RT sec=2.6187166205402264
clic x:957
clic y:550
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1045
clic y:626
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:870
clic y:625
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:782
clic y:566
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=2
RT sec=1.873753949740376
clic x:692
clic y:465
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:596
clic y:369
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:877
clic y:456
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:683
clic y:648
clicn=[639.0, 591.0, 729.0, 681.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [639.0, 591.0, 729.0, 681.0], [819.0, 411.0, 909.0, 501.0]]
NR=3
RT sec=1.8107066168561232
clic x:769
clic y:562
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:870
clic y:641
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:960
clic y:550
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1052
clic y:648
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:1
clic x:874
clic y:488
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:601
clic y:382
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:711
clic y:447
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:789
clic y:550
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
NR=4
RT sec=1.3175353292017462
clic x:885
clic y:652
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:958
clic y:551
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1067
clic y:643
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:854
clic y:474
clicn=[819.0, 411.0, 909.0, 501.0]
Combi:[[819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=5
RT sec=1.2099756225841247
clic x:596
clic y:375
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:704
clic y:467
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:800
clic y:554
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:869
clic y:640
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
NR=6
RT sec=6.766697627325129
clic x:873
clic y:459
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:953
clic y:566
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1050
clic y:651
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:602
clic y:386
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [819.0, 411.0, 909.0, 501.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=7
RT sec=2.025702543013267
clic x:697
clic y:450
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:788
clic y:541
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:866
clic y:645
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:869
clic y:455
clicn=[819.0, 411.0, 909.0, 501.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0]]
NR=8
RT sec=1.5166613196624894
clic x:966
clic y:552
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1061
clic y:628
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:854
clic y:647
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:665
clic y:661
clicn=[639.0, 591.0, 729.0, 681.0]
Combi:[[639.0, 591.0, 729.0, 681.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=9
RT sec=1.504873431898659
clic x:774
clic y:558
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:673
clic y:460
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:878
clic y:482
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:577
clic y:367
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
Dรฉjร fait:2
clic x:428
clic y:548
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:340
clic y:641
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:603
clic y:374
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:698
clic y:445
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0]]
NR=10
RT sec=8.576587014082406
clic x:784
clic y:555
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:879
clic y:635
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:888
clic y:444
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:974
clic y:548
clicn=[909.0, 501.0, 999.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0]]
NR=11
RT sec=1.765514448808517
clic x:1044
clic y:657
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:960
clic y:562
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:873
clic y:655
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:783
clic y:544
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:3
clic x:696
clic y:450
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:606
clic y:368
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:877
clic y:462
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:785
clic y:558
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
Dรฉjร fait:4
clic x:695
clic y:642
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:866
clic y:646
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:968
clic y:575
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1047
clic y:635
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[639.0, 591.0, 729.0, 681.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:5
clic x:864
clic y:479
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:779
clic y:567
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:694
clic y:452
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:595
clic y:366
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
Dรฉjร fait:6
clic x:423
clic y:547
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:322
clic y:648
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:869
clic y:483
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:966
clic y:548
clicn=[909.0, 501.0, 999.0, 591.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [819.0, 411.0, 909.0, 501.0], [909.0, 501.0, 999.0, 591.0]]
NR=12
RT sec=14.272553622520036
clic x:1063
clic y:641
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:870
clic y:633
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:767
clic y:565
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:673
clic y:458
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [999.0, 591.0, 1089.0, 681.0]]
NR=13
RT sec=1.5379117637646686
clic x:597
clic y:368
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:692
clic y:660
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:887
clic y:447
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:787
clic y:571
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 591.0, 729.0, 681.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
NR=14
RT sec=1.483656628794506
clic x:873
clic y:642
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:963
clic y:559
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1042
clic y:648
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:674
clic y:456
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[639.0, 411.0, 729.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=15
RT sec=1.680634928709651
clic x:591
clic y:374
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:424
clic y:542
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:334
clic y:642
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:691
clic y:466
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0]]
Dรฉjร fait:7
clic x:795
clic y:543
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:861
clic y:656
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:1046
clic y:647
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:947
clic y:547
clicn=[909.0, 501.0, 999.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:8
clic x:876
clic y:468
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:679
clic y:468
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:600
clic y:383
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:786
clic y:556
clicn=[729.0, 501.0, 819.0, 591.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
Dรฉjร fait:9
clic x:867
clic y:631
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:687
clic y:642
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:409
clic y:548
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:339
clic y:653
clicn=[279.0, 591.0, 369.0, 681.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [639.0, 591.0, 729.0, 681.0], [819.0, 591.0, 909.0, 681.0]]
NR=16
RT sec=1.4388972809047118
clic x:865
clic y:466
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:953
clic y:555
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1055
clic y:642
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:830
clic y:660
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:10
clic x:866
clic y:630
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:768
clic y:538
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:683
clic y:450
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:579
clic y:370
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
Dรฉjร fait:11
clic x:409
clic y:555
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:344
clic y:649
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:716
clic y:647
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:862
clic y:652
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [639.0, 591.0, 729.0, 681.0], [819.0, 591.0, 909.0, 681.0]]
Dรฉjร fait:12
clic x:773
clic y:549
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:693
clic y:464
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:599
clic y:379
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:876
clic y:457
clicn=[819.0, 411.0, 909.0, 501.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0]]
Dรฉjร fait:13
clic x:955
clic y:561
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1064
clic y:649
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:863
clic y:459
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:885
clic y:657
clicn=[819.0, 591.0, 909.0, 681.0]
Combi:[[819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:14
clic x:784
clic y:550
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:688
clic y:471
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:609
clic y:377
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:696
clic y:652
clicn=[639.0, 591.0, 729.0, 681.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [639.0, 591.0, 729.0, 681.0], [729.0, 501.0, 819.0, 591.0]]
NR=17
RT sec=2.427868777133199
clic x:417
clic y:553
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:330
clic y:650
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:590
clic y:361
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:674
clic y:459
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0]]
Dรฉjร fait:15
clic x:796
clic y:562
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:886
clic y:654
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:883
clic y:457
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:974
clic y:556
clicn=[909.0, 501.0, 999.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0]]
Dรฉjร fait:16
clic x:1064
clic y:650
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:697
clic y:639
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:601
clic y:380
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:688
clic y:466
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [639.0, 591.0, 729.0, 681.0], [999.0, 591.0, 1089.0, 681.0]]
NR=18
RT sec=10.97462484133348
clic x:805
clic y:547
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:1293
clic y:894
A cรดtรฉ:1
clic x:880
clic y:635
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:1363
clic y:901
A cรดtรฉ:2
clic x:1044
clic y:646
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:976
clic y:545
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:890
clic y:462
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:691
clic y:654
clicn=[639.0, 591.0, 729.0, 681.0]
Combi:[[639.0, 591.0, 729.0, 681.0], [819.0, 411.0, 909.0, 501.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=19
RT sec=2.859246064208264
clic x:429
clic y:550
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:339
clic y:659
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:615
clic y:377
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:685
clic y:474
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0]]
Dรฉjร fait:17
clic x:799
clic y:544
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:881
clic y:654
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:877
clic y:463
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:972
clic y:566
clicn=[909.0, 501.0, 999.0, 591.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 411.0, 909.0, 501.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0]]
Dรฉjร fait:18
clic x:1065
clic y:656
clicn=[999.0, 591.0, 1089.0, 681.0]
clic x:694
clic y:656
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:684
clic y:470
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:594
clic y:384
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [639.0, 591.0, 729.0, 681.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:19
clic x:430
clic y:543
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:334
clic y:641
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:616
clic y:379
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:706
clic y:458
clicn=[639.0, 411.0, 729.0, 501.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0]]
Dรฉjร fait:20
clic x:791
clic y:554
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:879
clic y:642
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:972
clic y:560
clicn=[909.0, 501.0, 999.0, 591.0]
Plus que 30 sec
clic x:1072
clic y:660
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
Dรฉjร fait:21
clic x:706
clic y:630
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:680
clic y:473
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:595
clic y:380
clicn=[549.0, 321.0, 639.0, 411.0]
clic x:411
clic y:555
clicn=[369.0, 501.0, 459.0, 591.0]
Combi:[[369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [639.0, 591.0, 729.0, 681.0]]
NR=20
RT sec=1.6634460197365115
clic x:322
clic y:653
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:880
clic y:487
clicn=[819.0, 411.0, 909.0, 501.0]
clic x:956
clic y:536
clicn=[909.0, 501.0, 999.0, 591.0]
clic x:1076
clic y:620
clicn=[999.0, 591.0, 1089.0, 681.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [819.0, 411.0, 909.0, 501.0], [909.0, 501.0, 999.0, 591.0], [999.0, 591.0, 1089.0, 681.0]]
NR=21
RT sec=11.914911659559493
clic x:866
clic y:649
clicn=[819.0, 591.0, 909.0, 681.0]
clic x:791
clic y:556
clicn=[729.0, 501.0, 819.0, 591.0]
clic x:687
clic y:485
clicn=[639.0, 411.0, 729.0, 501.0]
clic x:608
clic y:375
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[549.0, 321.0, 639.0, 411.0], [639.0, 411.0, 729.0, 501.0], [729.0, 501.0, 819.0, 591.0], [819.0, 591.0, 909.0, 681.0]]
Dรฉjร fait:22
clic x:703
clic y:631
clicn=[639.0, 591.0, 729.0, 681.0]
clic x:432
clic y:540
clicn=[369.0, 501.0, 459.0, 591.0]
clic x:335
clic y:655
clicn=[279.0, 591.0, 369.0, 681.0]
clic x:600
clic y:388
clicn=[549.0, 321.0, 639.0, 411.0]
Combi:[[279.0, 591.0, 369.0, 681.0], [369.0, 501.0, 459.0, 591.0], [549.0, 321.0, 639.0, 411.0], [639.0, 591.0, 729.0, 681.0]]
NR=22
RT sec=1.7383419582833994
THE END
Bonnes rรฉponses:22
Erreurs couleur:0
Erreurs rรฉpรฉtition:22
Erreurs mรชme cercle:0
Erreurs ร cotรฉ:2
Erreurs totales:24
Nombre de rรฉponses:46
Taux de rรฉussite= 47.83
RTmoy sec= 3.772
RTmax sec= 14.273
RTmin sec= 1.210
TACHE SPATIALE FACILE FORT GAIN
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:415
clic y:552
Bien! NR=1
RT=5.023952800859206
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:416
clic y:552
Gris touchรฉ!
ratรฉ!NEG=1
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:419
clic y:553
Gris touchรฉ!
ratรฉ!NEG=2
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:314
clic y:641
Bien! NR=2
RT=0.900465312438655
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:333
clic y:641
Gris touchรฉ!
ratรฉ!NEG=3
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:318
clic y:642
Gris touchรฉ!
ratรฉ!NEG=4
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:689
clic y:648
Bien! NR=3
RT=1.1936150206236107
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:316
clic y:651
Bien! NR=4
RT=1.317344560127367
Red 1:[639.0, 411.0, 729.0, 501.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:326
clic y:635
Gris touchรฉ!
ratรฉ!NEG=5
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:874
clic y:489
Bien! NR=5
RT=1.0260836709057912
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:866
clic y:460
Gris touchรฉ!
ratรฉ!NEG=6
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[549.0, 501.0, 639.0, 591.0]
clic x:614
clic y:548
Bien! NR=6
RT=0.9073473580740483
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:591
clic y:561
Rouge touchรฉ!
ratรฉ!NER=1
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:518
clic y:444
Bien! NR=7
RT=1.396368905543568
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:517
clic y:466
Gris touchรฉ!
ratรฉ!NEG=7
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1056
clic y:643
Bien! NR=8
RT=0.9359024115672128
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:1043
clic y:661
Gris touchรฉ!
ratรฉ!NEG=8
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:518
clic y:627
Bien! NR=9
RT=1.2023686544666816
Red 1:[639.0, 411.0, 729.0, 501.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:504
clic y:637
Gris touchรฉ!
ratรฉ!NEG=9
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1060
clic y:652
Bien! NR=10
RT=2.0724622995180653
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:874
clic y:459
Bien! NR=11
RT=7.521821110300607
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:333
clic y:648
Bien! NR=12
RT=1.2796395654238495
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:878
clic y:469
Bien! NR=13
RT=7.649287672379387
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:695
clic y:297
Bien! NR=14
RT=1.2052281393000612
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:519
clic y:456
Bien! NR=15
RT=1.5265472602688988
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[549.0, 501.0, 639.0, 591.0]
clic x:600
clic y:573
Bien! NR=16
RT=1.1507079789062118
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:960
clic y:568
Bien! NR=17
RT=1.415876581844941
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:956
clic y:549
Bien! NR=18
RT=2.1427313700664854
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:951
clic y:546
Bien! NR=19
RT=1.3874372205643795
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:866
clic y:454
Bien! NR=20
RT=1.4073350503917936
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:867
clic y:642
Bien! NR=21
RT=1.3059086720750201
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:771
clic y:373
Bien! NR=22
RT=1.825728553248382
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:514
clic y:628
Bien! NR=23
RT=1.893712087210588
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:301
clic y:641
Bien! NR=24
RT=1.6462997773951429
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:704
clic y:466
Bien! NR=25
RT=3.144887675989594
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:691
clic y:463
Bien! NR=26
RT=4.911754739073103
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[549.0, 501.0, 639.0, 591.0]
clic x:689
clic y:451
Gris touchรฉ!
ratรฉ!NEG=10
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:702
clic y:467
Gris touchรฉ!
ratรฉ!NEG=11
Red 1:[639.0, 411.0, 729.0, 501.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:788
clic y:567
Bien! NR=27
RT=0.695816044458752
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:788
clic y:567
Gris touchรฉ!
ratรฉ!NEG=12
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:967
clic y:549
Bien! NR=28
RT=1.1621668412990402
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:962
clic y:557
Gris touchรฉ!
ratรฉ!NEG=13
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:506
clic y:454
Bien! NR=29
RT=1.2988432419747369
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:519
clic y:465
Gris touchรฉ!
ratรฉ!NEG=14
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:697
clic y:459
Bien! NR=30
RT=1.0201144450343236
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:697
clic y:459
Gris touchรฉ!
ratรฉ!NEG=15
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:694
clic y:467
Bien! NR=31
RT=9.899046236680078
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:504
clic y:650
Bien! NR=32
RT=10.771699879630887
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:863
clic y:644
Bien! NR=33
RT=10.436973179919278
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:519
clic y:455
Bien! NR=34
RT=3.521585213058188
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1059
clic y:644
Bien! NR=35
RT=5.764916705709311
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:418
clic y:555
Bien! NR=36
RT=2.3968932128054803
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:863
clic y:459
Bien! NR=37
RT=7.888210963519214
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:688
clic y:477
Bien! NR=38
RT=7.892916190427741
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1051
clic y:649
Bien! NR=39
RT=1.3945038814326836
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:523
clic y:676
Bien! NR=40
RT=0.8892928087855125
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:523
clic y:676
Gris touchรฉ!
ratรฉ!NEG=16
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:767
clic y:372
Bien! NR=41
RT=7.383035172894324
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:433
clic y:553
Bien! NR=42
RT=1.2723415201301123
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
Plus que 30 sec
clic x:601
clic y:376
Bien! NR=43
RT=26.208897059366564
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:860
clic y:478
Bien! NR=44
RT=1.75873865949643
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:392
clic y:551
Bien! NR=45
RT=1.7956555522825965
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:952
clic y:544
Bien! NR=46
RT=1.891153320079411
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:505
clic y:652
Bien! NR=47
RT=1.9156685820155417
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:610
clic y:378
Bien! NR=48
RT=1.8060522617006427
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:797
clic y:400
Bien! NR=49
RT=1.9126277639977616
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:885
clic y:648
Bien! NR=50
RT=2.8816243022570234
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:869
clic y:661
Gris touchรฉ!
ratรฉ!NEG=17
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[279.0, 591.0, 369.0, 681.0]
THE END
Bonnes rรฉponses:50
Erreurs rouge:1
Erreurs gris:17
Erreurs ร cรดtรฉ:0
Erreurs totales:18
Nombre de rรฉponses:68
Taux de rรฉussite= 73.53
RTmoy sec= 3.425
RTmax sec= 26.209
RTmin sec= 0.696
TACHE SPATIALE FACILE FAIBLE GAIN
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:604
clic y:370
Bien! NR=1
RT=1.171132577532262
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1045
clic y:644
Bien! NR=2
RT=1.1453537268891978
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:435
clic y:543
Bien! NR=3
RT=0.8888115784109232
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:686
clic y:640
Bien! NR=4
RT=1.1439194716558632
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:426
clic y:552
Bien! NR=5
RT=0.9142047883449322
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:959
clic y:556
Bien! NR=6
RT=1.0457870393540816
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:528
clic y:645
Bien! NR=7
RT=1.1808646721110563
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:412
clic y:546
Bien! NR=8
RT=1.142514754859576
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:707
clic y:264
Bien! NR=9
RT=2.6937955332959973
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:598
clic y:358
Bien! NR=10
RT=1.428266725524736
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:767
clic y:558
Bien! NR=11
RT=1.0549275446746833
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:964
clic y:553
Bien! NR=12
RT=1.1457278804282396
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:503
clic y:641
Bien! NR=13
RT=3.323126298973193
Red 1:[639.0, 411.0, 729.0, 501.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:940
clic y:571
Bien! NR=14
RT=2.0691445586508053
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:517
clic y:466
Bien! NR=15
RT=1.1488478778685476
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:594
clic y:373
Bien! NR=16
RT=1.1400958850495044
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:877
clic y:635
Bien! NR=17
RT=1.1444048045909767
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:696
clic y:295
Bien! NR=18
RT=1.0605012836913374
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:505
clic y:634
Bien! NR=19
RT=1.1609053038723687
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:602
clic y:356
Bien! NR=20
RT=1.150119671696757
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:334
clic y:651
Bien! NR=21
RT=1.1404007053122314
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:509
clic y:636
Bien! NR=22
RT=1.20185091130179
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1062
clic y:635
Bien! NR=23
RT=1.2740547494934162
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:592
clic y:378
Bien! NR=24
RT=1.2651546542322194
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1034
clic y:641
Bien! NR=25
RT=1.0530120590669867
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:865
clic y:493
Bien! NR=26
RT=0.9404496898876005
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:679
clic y:636
Bien! NR=27
RT=0.9436681487850365
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:690
clic y:454
Bien! NR=28
RT=6.912526020491441
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1043
clic y:651
Bien! NR=29
RT=1.515283269511201
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:318
clic y:645
Bien! NR=30
RT=1.763159989201995
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:607
clic y:399
Bien! NR=31
RT=1.0019282035459582
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:406
clic y:549
Bien! NR=32
RT=1.2900994542774242
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:680
clic y:453
Bien! NR=33
RT=0.909637817733028
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:509
clic y:637
Bien! NR=34
RT=1.4212439620562236
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:790
clic y:551
Bien! NR=35
RT=1.3947520863571299
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:685
clic y:644
Bien! NR=36
RT=7.279805719133947
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:779
clic y:558
Bien! NR=37
RT=1.3244362466164148
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:877
clic y:483
Bien! NR=38
RT=0.8952706500344902
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:431
clic y:563
Bien! NR=39
RT=1.1536811046717048
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:772
clic y:371
Bien! NR=40
RT=1.0098806072774096
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:690
clic y:291
Bien! NR=41
RT=5.396231059502725
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:780
clic y:375
Bien! NR=42
RT=1.3133142044600845
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:1222
clic y:524
A cรดtรฉ!
ratรฉ!AC=1
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:767
clic y:381
Bien! NR=43
RT=5.203623217540098
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:689
clic y:459
Bien! NR=44
RT=1.141726242686218
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:689
clic y:459
Gris touchรฉ!
ratรฉ!NEG=1
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:684
clic y:463
Gris touchรฉ!
ratรฉ!NEG=2
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:684
clic y:463
Gris touchรฉ!
ratรฉ!NEG=3
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:695
clic y:289
Bien! NR=45
RT=1.0550338009979896
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:695
clic y:289
Gris touchรฉ!
ratรฉ!NEG=4
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:686
clic y:279
Gris touchรฉ!
ratรฉ!NEG=5
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:695
clic y:454
Gris touchรฉ!
ratรฉ!NEG=6
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[549.0, 501.0, 639.0, 591.0]
clic x:695
clic y:454
Gris touchรฉ!
ratรฉ!NEG=7
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:423
clic y:542
Gris touchรฉ!
ratรฉ!NEG=8
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:420
clic y:558
Bien! NR=46
RT=1.529061719744277
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:420
clic y:558
Rouge touchรฉ!
ratรฉ!NER=1
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[549.0, 501.0, 639.0, 591.0]
clic x:611
clic y:547
Bien! NR=47
RT=1.0772778853104228
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:611
clic y:547
Gris touchรฉ!
ratรฉ!NEG=9
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:332
clic y:646
Bien! NR=48
RT=1.141459576238276
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:332
clic y:646
Gris touchรฉ!
ratรฉ!NEG=10
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:676
clic y:286
Bien! NR=49
RT=2.0409250946256634
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:680
clic y:284
Gris touchรฉ!
ratรฉ!NEG=11
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:404
clic y:547
Bien! NR=50
RT=1.1500179281904366
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:861
clic y:464
Bien! NR=51
RT=1.096433972156774
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:416
clic y:546
Bien! NR=52
RT=13.712631210148857
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:772
clic y:579
Bien! NR=53
RT=1.0157304486315297
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:513
clic y:448
Bien! NR=54
RT=1.270278752591821
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:601
clic y:366
Bien! NR=55
RT=1.165787351148765
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:776
clic y:564
Bien! NR=56
RT=0.8992657236792638
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:960
clic y:569
Bien! NR=57
RT=1.054808980669577
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:419
clic y:545
Bien! NR=58
RT=1.1426784470329494
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:512
clic y:483
Bien! NR=59
RT=1.0275511568811453
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:860
clic y:467
Bien! NR=60
RT=1.0320758711172857
Red 1:[729.0, 501.0, 819.0, 591.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:414
clic y:552
Bien! NR=61
RT=0.9044825399116689
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:683
clic y:645
Bien! NR=62
RT=1.0320676659957826
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:335
clic y:640
Bien! NR=63
RT=1.2744929029800005
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:503
clic y:456
Bien! NR=64
RT=1.3966884950248186
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:756
clic y:565
Bien! NR=65
RT=0.9324542092683714
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:686
clic y:287
Bien! NR=66
RT=1.5206793676475172
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:674
clic y:463
Bien! NR=67
RT=1.2721347510687337
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:774
clic y:561
Bien! NR=68
RT=0.9394613830061189
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:960
clic y:567
Bien! NR=69
RT=1.147277417618625
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:879
clic y:649
Bien! NR=70
RT=1.2517622549642056
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:682
clic y:649
Bien! NR=71
RT=1.023378852612268
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[279.0, 591.0, 369.0, 681.0]
clic x:336
clic y:661
Bien! NR=72
RT=1.1696507325943912
Red 1:[639.0, 411.0, 729.0, 501.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:316
clic y:623
Gris touchรฉ!
ratรฉ!NEG=12
Red 1:[459.0, 411.0, 549.0, 501.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:408
clic y:550
Bien! NR=73
RT=1.6825286707455689
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:949
clic y:544
Bien! NR=74
RT=1.2015276295157946
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1029
clic y:649
Bien! NR=75
RT=1.1781180076980036
Red 1:[819.0, 411.0, 909.0, 501.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:671
clic y:647
Bien! NR=76
RT=2.6543773092289484
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:398
clic y:559
Bien! NR=77
RT=1.6425086010185623
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:686
clic y:457
Bien! NR=78
RT=1.1407658332177562
Red 1:[639.0, 411.0, 729.0, 501.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:671
clic y:654
Bien! NR=79
RT=1.2662287046327947
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:591
clic y:365
Bien! NR=80
RT=1.5275482850884146
Red 1:[909.0, 501.0, 999.0, 591.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:1043
clic y:642
Bien! NR=81
RT=1.5547285704792557
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[639.0, 591.0, 729.0, 681.0]
clic x:695
clic y:653
Bien! NR=82
RT=2.5309189489896653
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[819.0, 411.0, 909.0, 501.0]
Plus que 30 sec
clic x:862
clic y:472
Bien! NR=83
RT=1.389110244832409
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:858
clic y:646
Bien! NR=84
RT=1.08073060042625
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:867
clic y:477
Bien! NR=85
RT=1.0499437538921939
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[909.0, 501.0, 999.0, 591.0]
clic x:947
clic y:576
Bien! NR=86
RT=1.0432775029519235
Red 1:[639.0, 591.0, 729.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:607
clic y:363
Bien! NR=87
RT=1.2641651165824896
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:860
clic y:663
Bien! NR=88
RT=1.4325629271279468
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:777
clic y:556
Bien! NR=89
RT=1.395880700815951
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:503
clic y:471
Bien! NR=90
RT=1.2971570895122113
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:597
clic y:362
Bien! NR=91
RT=1.6711120647285043
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[459.0, 591.0, 549.0, 681.0]
clic x:506
clic y:657
Bien! NR=92
RT=1.8853490171493377
Red 1:[549.0, 501.0, 639.0, 591.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:683
clic y:278
Bien! NR=93
RT=1.5125214256236177
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[729.0, 321.0, 819.0, 411.0]
clic x:829
clic y:356
A cรดtรฉ!
ratรฉ!AC=2
Red 1:[639.0, 231.0, 729.0, 321.0]
Blue:[999.0, 591.0, 1089.0, 681.0]
clic x:791
clic y:384
Gris touchรฉ!
ratรฉ!NEG=13
Red 1:[279.0, 591.0, 369.0, 681.0]
Blue:[639.0, 231.0, 729.0, 321.0]
clic x:677
clic y:290
Bien! NR=94
RT=2.4256550353600232
Red 1:[729.0, 321.0, 819.0, 411.0]
Blue:[819.0, 591.0, 909.0, 681.0]
clic x:869
clic y:673
Bien! NR=95
RT=1.0793221913254456
Red 1:[549.0, 321.0, 639.0, 411.0]
Blue:[639.0, 411.0, 729.0, 501.0]
clic x:697
clic y:463
Bien! NR=96
RT=1.1872375899588405
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[729.0, 501.0, 819.0, 591.0]
clic x:774
clic y:561
Bien! NR=97
RT=1.30518415984875
Red 1:[369.0, 501.0, 459.0, 591.0]
Blue:[819.0, 411.0, 909.0, 501.0]
clic x:866
clic y:472
Bien! NR=98
RT=0.9020751572718382
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[369.0, 501.0, 459.0, 591.0]
clic x:433
clic y:570
Bien! NR=99
RT=1.6516815165689422
Red 1:[999.0, 591.0, 1089.0, 681.0]
Blue:[459.0, 411.0, 549.0, 501.0]
clic x:512
clic y:456
Bien! NR=100
RT=1.264391167678923
Red 1:[819.0, 591.0, 909.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
clic x:612
clic y:402
Bien! NR=101
RT=0.9453965576233259
Red 1:[459.0, 591.0, 549.0, 681.0]
Blue:[549.0, 321.0, 639.0, 411.0]
THE END
Bonnes rรฉponses:101
Erreurs rouge:1
Erreurs gris:13
Erreurs ร cรดtรฉ:2
Erreurs totales:16
Nombre de rรฉponses:117
Taux de rรฉussite= 86.32
RTmoy= 1.617
RTmax= 13.713
RTmin= 0.889
ordre tรขches : ['Verbale Facile Facile', 'Verbale Facile Forte', 'Verbale Difficile Faible', 'Verbale Difficile Fort', 'Spatiale Difficile Faible', 'Spatiale Difficile Fort', 'Spatiale Facile Fort', 'Spatiale Facile Faible']
>>>
|
[
"[email protected]"
] | |
1c725c18b3b21a31f7fe5dc8cf9f9f4b63fdd24b
|
fd6747673bad3628eba33d3892b63180db5fb044
|
/tensorflow/compiler/xla/python/xla_extension/__init__.pyi
|
61d1e478c9013a9376efd36b851a37e6b8793772
|
[
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] |
permissive
|
gautam1858/tensorflow
|
2cbdc251a470eefd27ce31fd4e6fe31253e9d07a
|
bd56b0b3a00432896cffbb412bedbb13579ec598
|
refs/heads/master
| 2022-06-04T22:09:41.533559 | 2022-05-10T15:51:20 | 2022-05-10T15:51:20 | 59,177,861 | 2 | 0 |
Apache-2.0
| 2022-03-17T14:48:17 | 2016-05-19T05:56:42 |
C++
|
UTF-8
|
Python
| false | false | 16,725 |
pyi
|
# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
#
# 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 enum
import inspect
import types
import typing
from typing import Any, Callable, ClassVar, Dict, List, Optional, Sequence, Tuple, Type, TypeVar, Union, overload
import numpy as np
from . import ops
from . import jax_jit
from . import mlir
from . import outfeed_receiver
from . import pmap_lib
from . import profiler
from . import pytree
from . import transfer_guard_lib
_LiteralSlice = Any
_Status = Any
_Dtype = Any
_XlaOpMetadata = Any
_T = TypeVar("_T")
class XlaRuntimeError(RuntimeError):
pass
class PrimitiveType(enum.IntEnum):
PRIMITIVE_TYPE_INVALID: PrimitiveType
PRED: PrimitiveType
S8: PrimitiveType
S16: PrimitiveType
S32: PrimitiveType
S64: PrimitiveType
U8: PrimitiveType
U16: PrimitiveType
U32: PrimitiveType
U64: PrimitiveType
BF16: PrimitiveType
F16: PrimitiveType
F32: PrimitiveType
F64: PrimitiveType
C64: PrimitiveType
C128: PrimitiveType
TUPLE: PrimitiveType
OPAQUE_TYPE: PrimitiveType
TOKEN: PrimitiveType
def bfloat16_dtype() -> Type[Any]: ...
# === BEGIN xla_compiler.cc
class Shape:
def __init__(self, s: str): ...
@staticmethod
def tuple_shape(shapes: Sequence[Shape]) -> Shape: ...
@staticmethod
def array_shape(
type: Union[np.dtype, PrimitiveType],
dims_seq: Any = ...,
layout_seq: Any = ...,
dynamic_dimensions: Optional[List[bool]] = ...) -> Shape: ...
@staticmethod
def token_shape() -> Shape: ...
@staticmethod
def scalar_shape(type: Union[np.dtype, PrimitiveType]) -> Shape: ...
def dimensions(self) -> Tuple[int, ...]: ...
def xla_element_type(self) -> PrimitiveType: ...
def element_type(self) -> np.dtype: ...
def numpy_dtype(self) -> np.dtype: ...
def is_tuple(self) -> bool: ...
def is_array(self) -> bool: ...
def is_token(self) -> bool: ...
def is_static(self) -> bool: ...
def is_dynamic(self) -> bool: ...
def is_dynamic_dimension(self, dimension: int) -> bool: ...
def set_dynamic_dimension(self, dimension: int, is_dynamic: bool) -> None: ...
def rank(self) -> int: ...
def to_serialized_proto(self) -> bytes: ...
def tuple_shapes(self) -> List[Shape]: ...
def leaf_count(self) -> int: ...
def with_major_to_minor_layout_if_absent(self) -> Shape: ...
def __eq__(self, other: Shape) -> bool: ...
def __ne__(self, other: Shape) -> bool: ...
def __hash__(self) -> int: ...
def __repr__(self) -> str: ...
class Layout:
def minor_to_major(self) -> Tuple[int, ...]: ...
def to_string(self) -> str: ...
def __eq__(self, other: Layout) -> bool: ...
def __ne__(self, other: Layout) -> bool: ...
def __hash__(self) -> int: ...
class ProgramShape:
def __init__(self, params: Sequence[Shape], result: Shape) -> None: ...
def parameter_shapes(self) -> List[Shape]: ...
def result_shape(self) -> Shape: ...
def __repr__(self) -> str: ...
class ShapeIndex:
def __init__(self, indices: List[int]) -> ShapeIndex: ...
def __eq__(self, other: Shape) -> bool: ...
def __ne__(self, other: Shape) -> bool: ...
def __hash__(self) -> int: ...
def __repr__(self) -> str: ...
class Literal:
def __repr__(self) -> str: ...
class XlaComputation:
def __init__(self, serialized_hlo_module_proto: bytes) -> None: ...
def get_hlo_module(self) -> HloModule: ...
def program_shape(self) -> ProgramShape: ...
def as_serialized_hlo_module_proto(self) -> bytes: ...
def as_hlo_text(self, print_large_constants: bool=False) -> str: ...
def as_hlo_dot_graph(self) -> str: ...
def hash(self) -> int: ...
def as_hlo_module(self) -> HloModule: ...
class HloPrintOptions:
def __init__(self) -> None: ...
@staticmethod
def short_parsable() -> HloPrintOptions: ...
@staticmethod
def canonical() -> HloPrintOptions: ...
@staticmethod
def fingerprint() -> HloPrintOptions: ...
print_large_constants: bool
print_metadata: bool
print_backend_config: bool
print_result_shape: bool
print_operand_shape: bool
print_operand_names: bool
print_ids: bool
print_extra_attributes: bool
print_program_shape: bool
print_percent: bool
print_control_dependencies: bool
compact_operands: bool
include_layout_in_shapes: bool
canonicalize_instruction_names: bool
canonicalize_computations: bool
indent_amount: int
is_in_nested_computation: bool
class HloModule:
spmd_output_sharding: Optional[OpSharding]
spmd_parameters_shardings: Optional[List[OpSharding]]
@property
def name(self) -> str: ...
def to_string(self, options: HloPrintOptions = ...) -> str: ...
def as_serialized_hlo_module_proto(self)-> bytes: ...
@staticmethod
def from_serialized_hlo_module_proto(
serialized_hlo_module_proto: bytes) -> HloModule: ...
def hlo_module_to_dot_graph(hlo_module: HloModule) -> str: ...
def hlo_module_cost_analysis(
client: Client,
module: HloModule) -> Dict[str, float]: ...
class XlaOp: ...
class XlaBuilder:
def __init__(self, name: str) -> None: ...
def Build(self, root: Optional[XlaOp] = ...) -> XlaComputation: ...
def GetShape(self, __op: XlaOp) -> Shape: ...
build = Build
def clear_op_metadata(self) -> None: ...
get_shape = GetShape
def get_program_shape(self, root: Optional[XlaOp] = ...) -> ProgramShape: ...
def is_constant(self, __op: XlaOp) -> bool: ...
def set_op_metadata(self, metadata: _XlaOpMetadata) -> None: ...
def set_sharding(self, sharding: OpSharding_Type) -> None: ...
def clear_sharding(self) -> None: ...
def setup_alias(
self,
__output_index: Sequence[int],
__param_number: int,
__param_index: Sequence[int]) -> None: ...
class DeviceAssignment:
@staticmethod
def create(array: np.ndarray) -> DeviceAssignment: ...
def replica_count(self) -> int: ...
def computation_count(self) -> int: ...
def __repr__(self) -> str: ...
def serialize(self) -> bytes: ...
class CompileOptions:
def __init__(self) -> None: ...
argument_layouts: Optional[List[Shape]]
parameter_is_tupled_arguments: bool
executable_build_options: ExecutableBuildOptions
tuple_arguments: bool
num_replicas: int
num_partitions: int
device_assignment: Optional[DeviceAssignment]
def register_custom_call_target(fn_name: str, capsule: Any, platform: str) -> _Status: ...
class DebugOptions:
def __repr__(self) -> str: ...
xla_cpu_enable_fast_math: bool
xla_cpu_fast_math_honor_infs: bool
xla_cpu_fast_math_honor_nans: bool
xla_cpu_fast_math_honor_division: bool
xla_cpu_fast_math_honor_functions: bool
xla_gpu_enable_fast_min_max: bool
xla_backend_optimization_level: int
xla_cpu_enable_xprof_traceme: bool
xla_llvm_disable_expensive_passes: bool
xla_test_all_input_layouts: bool
class CompiledMemoryStats:
generated_code_size_in_bytes: int
argument_size_in_bytes: int
output_size_in_bytes: int
alias_size_in_bytes: int
temp_size_in_bytes: int
def __str__(self) -> str: ...
class ExecutableBuildOptions:
def __init__(self) -> None: ...
def __repr__(self) -> str: ...
result_layout: Optional[Shape]
num_replicas: int
num_partitions: int
debug_options: DebugOptions
device_assignment: Optional[DeviceAssignment]
use_spmd_partitioning: bool
use_auto_spmd_partitioning: bool
auto_spmd_partitioning_mesh_shape: List[int]
auto_spmd_partitioning_mesh_ids: List[int]
class PrecisionConfig_Precision(enum.IntEnum):
DEFAULT: int
HIGH: int
HIGHEST: int
class OpSharding_Type(enum.IntEnum):
REPLICATED: int
MAXIMAL: int
TUPLE: int
OTHER: int
MANUAL: int
class OpSharding:
Type: typing.Type[OpSharding_Type]
type: OpSharding_Type
replicate_on_last_tile_dim: bool
last_tile_dims: Sequence[Type]
tile_assignment_dimensions: Sequence[int]
tile_assignment_devices: Sequence[int]
tuple_shardings: Sequence[OpSharding]
def SerializeToString(self) -> bytes: ...
class ChannelHandle_ChannelType(enum.IntEnum):
CHANNEL_TYPE_INVALID: int
DEVICE_TO_DEVICE: int
DEVICE_TO_HOST: int
HOST_TO_DEVICE: int
class ChannelHandle:
type: ChannelHandle_ChannelType
handle: int
def __repr__(self) -> str: ...
class FftType(enum.IntEnum):
FFT: int
IFFT: int
RFFT: int
IRFFT: int
# === END xla_compiler.cc
class Device:
id: int
host_id: int
process_index: int
platform: str
device_kind: str
client: Client
def __repr__(self) -> str: ...
def __str__(self) -> str: ...
def transfer_to_infeed(self, literal: _LiteralSlice): ...
def transfer_from_outfeed(self, shape: Shape): ...
def live_buffers(self) -> List[Buffer]: ...
def __getattr__(self, name: str) -> Any: ...
class GpuDevice(Device):
pass
class TpuDevice(Device):
pass
class _GpuAllocatorKind(enum.IntEnum):
DEFAULT: int
PLATFORM: int
BFC: int
CUDA_ASYNC: int
class GpuAllocatorConfig:
# TODO(b/194673104): Remove once pytype correctly resolves a nested enum.
Kind = _GpuAllocatorKind
def __init__(
self,
kind: _GpuAllocatorKind = ...,
memory_fraction: float = ...,
preallocate: bool = ...) -> None: ...
class HostBufferSemantics(enum.IntEnum):
IMMUTABLE_ONLY_DURING_CALL: HostBufferSemantics
IMMUTABLE_UNTIL_TRANSFER_COMPLETES: HostBufferSemantics
ZERO_COPY: HostBufferSemantics
class Client:
platform: str
platform_version: str
runtime_type: str
def device_count(self) -> int: ...
def local_device_count(self) -> int: ...
def devices(self) -> List[Device]: ...
def local_devices(self) -> List[Device]: ...
def live_buffers(self) -> List[Buffer]: ...
def live_executables(self) -> List[Executable]: ...
def host_id(self) -> int: ...
def process_index(self) -> int: ...
@overload
def get_default_device_assignment(
self,
num_replicas: int,
num_partitions: int) -> List[List[Device]]: ...
@overload
def get_default_device_assignment(
self,
num_replicas: int) -> List[Device]: ...
def create_channel_handle(self) -> ChannelHandle: ...
def create_device_to_host_channel_handle(self) -> ChannelHandle: ...
def create_host_to_device_channel_handle(self) -> ChannelHandle: ...
def buffer_from_pyval(
self,
argument: Any,
device: Device = ...,
force_copy: bool = ...,
host_buffer_semantics: HostBufferSemantics = ...) -> Buffer: ...
def make_cross_host_receive_buffers(
self,
shapes: Sequence[Shape],
device: Device) -> List[Tuple[Buffer, bytes]]: ...
def compile(
self,
computation: XlaComputation,
compile_options: CompileOptions = ...) -> Executable: ...
def serialize_executable(self, executable: Executable) -> bytes: ...
def deserialize_executable(
self, serialized: bytes,
options: CompileOptions) -> Executable: ...
# TODO(skyewm): remove when jax stop providing hlo_module
def deserialize_executable(
self, serialized: bytes,
hlo_module: HloModule,
options: CompileOptions) -> Executable: ...
def heap_profile(self) -> bytes: ...
def defragment(self) -> _Status: ...
def get_emit_python_callback_descriptor(
self, callable: Callable, operand_shapes: Sequence[XlaOp],
results_shapes: Sequence[Shape]) -> Tuple[Any, Any]: ...
def emit_python_callback(
self, callable: Callable, builder: XlaBuilder, operands: Sequence[XlaOp],
results_shapes: Sequence[Shape],
operand_layouts: Optional[Sequence[Shape]] = ...,
has_side_effects: bool = ...) -> Tuple[XlaOp, Any]: ...
def get_cpu_client(asynchronous: bool = ...) -> Client: ...
def get_tfrt_cpu_client(asynchronous: bool = ...) -> Client: ...
def get_interpreter_client() -> Client: ...
def get_gpu_client(
asynchronous: bool = ...,
allocator_config: GpuAllocatorConfig = ...,
distributed_client: Optional[DistributedRuntimeClient] = ...,
node_id: int = ...,
allowed_devices: Optional[Any] = ...,
platform_name: Optional[str] = ...) -> Client:...
def get_tpu_client(max_inflight_computations: int = ...) -> Client: ...
class DeviceArrayBase: ...
class DeviceArray(DeviceArrayBase):
__array_priority__: int
_device: Optional[Device]
aval: Any
weak_type: Optional[bool]
@property
def device_buffer(self: _T) -> _T: ...
shape: Tuple[int, ...]
dtype: np.dtype
size: int
ndim: int
_value: np.ndarray
def copy_to_device(self, dst_device: Device) -> DeviceArray: ...
def copy_to_remote_device(self,
descriptor: bytes) -> Tuple[_Status, bool]: ...
def on_device_size_in_bytes(self) -> int: ...
def delete(self) -> None: ...
def is_ready(self) -> bool: ...
def is_known_ready(self) -> bool: ...
def block_until_ready(self) -> DeviceArray: ...
def copy_to_host_async(self) -> _Status: ...
def to_py(self) -> np.ndarray: ...
def xla_shape(self) -> Shape: ...
def xla_dynamic_shape(self) -> Shape: ...
client: Client
def device(self) -> Device: ...
def platform(self) -> str: ...
def is_deleted(self) -> bool: ...
def unsafe_buffer_pointer(self) -> Any: ...
__cuda_array_interface__: Dict[str, Any]
traceback: Traceback
def clone(self) -> DeviceArray: ...
PyLocalBuffer = DeviceArray
Buffer = DeviceArray
class Executable:
client: Client
def local_logical_device_ids(self) -> List[Tuple[int, int]]: ...
def local_devices(self) -> List[Device]: ...
def size_of_generated_code_in_bytes(self) -> int: ...
def delete(self) -> None: ...
def execute(self, arguments: Sequence[DeviceArray]) -> List[DeviceArray]: ...
def execute_sharded_on_local_devices(
self,
arguments: Sequence[List[DeviceArray]]) -> List[List[DeviceArray]]: ...
def hlo_modules(self) -> List[HloModule]: ...
def keep_alive(self) -> None: ...
traceback: Traceback
fingerprint: Optional[bytes]
def buffer_to_dlpack_managed_tensor(
buffer: Buffer,
take_ownership: bool = ...) -> Any: ...
def dlpack_managed_tensor_to_buffer(
tensor: Any, cpu_backend: Optional[Client] = ...,
gpu_backend: Optional[Client] = ...) -> Buffer: ...
# === BEGIN py_traceback.cc
class Frame:
file_name: str
function_name: str
function_line_start: int
line_num: int
def __repr__(self) -> str: ...
class Traceback:
enabled: ClassVar[bool]
@staticmethod
def get_traceback() -> Traceback: ...
frames: Sequence[Frame]
def __str__(self) -> str: ...
def as_python_traceback(self) -> Any: ...
def raw_frames(self) -> Tuple[List[types.CodeType], List[int]]: ...
@staticmethod
def code_addr2line(code: types.CodeType, lasti: int) -> int: ...
def replace_thread_exc_traceback(traceback: Any): ...
# === END py_traceback.cc
class DistributedRuntimeService:
def shutdown(self) -> None: ...
class DistributedRuntimeClient:
def connect(self) -> _Status: ...
def shutdown(self) -> _Status: ...
def get_distributed_runtime_service(
address: str,
num_nodes: int,
heartbeat_interval: Optional[int] = ...,
max_missing_heartbeats: Optional[int] = ...,
enumerate_devices_timeout: Optional[int] = ...,
shutdown_timeout: Optional[int] = ...) -> DistributedRuntimeService: ...
def get_distributed_runtime_client(
address: str,
node_id: int,
rpc_timeout: Optional[int] = ...,
init_timeout: Optional[int] = ...,
shutdown_timeout: Optional[int] = ...,
heartbeat_interval: Optional[int] = ...,
max_missing_heartbeats: Optional[int] = ...,
missed_heartbeat_callback: Optional[Any] = ...,
shutdown_on_destruction: Optional[bool] = ...) -> DistributedRuntimeClient: ...
def collect_garbage() -> None: ...
def is_optimized_build() -> bool: ...
def json_to_pprof_profile(json: str) -> bytes: ...
def pprof_profile_to_json(proto: bytes) -> str: ...
class CompiledFunction:
def __call__(self, *args, **kwargs) -> Any: ...
def __getstate__(self) -> Any: ...
def __setstate__(self, Any): ...
__signature__: inspect.Signature
def _cache_size(self) -> int: ...
def _clear_cache(self) -> None: ...
class PmapFunction:
def __call__(self, *args, **kwargs) -> Any: ...
def __getstate__(self) -> Any: ...
def __setstate__(self, Any): ...
__signature__: inspect.Signature
def _cache_size(self) -> int: ...
def _clear_cache(self) -> None: ...
|
[
"[email protected]"
] | |
1f03b8aad24c2370d520e48b592152a4703341a1
|
a5774cd1c577f4c0ea5353ebbfc752e4ba30326d
|
/Iteration-1/test/test_bowlinggame.py
|
e8fe42173fe111f91ad18161a571db1266d187b8
|
[
"Unlicense"
] |
permissive
|
xray/py-bowling-game-kata
|
9faaa115ea57b38d441bcc083590b4d7f5aa551c
|
25da4a8d4bccf6a955ef0bbb7604d0c9d3a4599b
|
refs/heads/master
| 2020-03-31T10:02:43.606459 | 2018-10-08T21:24:34 | 2018-10-08T21:24:34 | 152,120,495 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,067 |
py
|
from bowlinggame.game import Score
def gen_all_x_except_y_frame(number_to_set, frame_to_change, arr=[]):
game = []
for frame in range(10):
if frame == (frame_to_change - 1):
game.append(arr)
else:
if frame == 9:
if number_to_set == 10:
game.append([number_to_set, number_to_set, number_to_set])
else:
game.append([number_to_set, number_to_set, 0])
elif number_to_set == 10:
game.append([number_to_set, 0])
else:
game.append([number_to_set, number_to_set])
return game
def test_gutter_game():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(0, 0)) == 0
def test_all_ones_game():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(1, 0)) == 20
def test_spare_in_frame_one_zeros():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(0, 1, [1, 9])) == 10
def test_spare_in_frame_one_ones():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(1, 1, [1, 9])) == 29
def test_strike_in_frame_one_ones():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(1, 1, [10, 0])) == 30
def test_various_game():
rolls = [[6, 3], [6, 4], [6, 2], [4, 6], [10, 0], [10, 0], [3, 2], [5, 5], [4, 3], [3, 1, 0]]
new_score = Score()
assert new_score.calculate(rolls) == 121
def test_all_strikes_except_last_frame():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(10, 10, [0, 0, 0])) == 240
def test_last_frame_spare():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(0, 10, [9, 1, 9])) == 19
def test_last_frame_strikes():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(0, 10, [10, 10, 10])) == 30
def test_all_strikes():
new_score = Score()
assert new_score.calculate(gen_all_x_except_y_frame(10, 10, [10, 10, 10])) == 300
|
[
"[email protected]"
] | |
800d097e7641deb96cee13bca8df9f1242e5f9cb
|
f214ad554e5c227724be6358bd896ed41a0ae866
|
/dakota/template_dir/model_command_line_driver3.py
|
7667ea0fc2c3fe27fcad19943d07dbe7bfc44e1a
|
[] |
no_license
|
SiccarPoint/how_wrong_is_the_code
|
f42584fedf6fbea1c37564994b289ed3a07130ae
|
7533b679418d9d9abe78f8c7c73484952acb4641
|
refs/heads/master
| 2021-05-20T22:03:41.442612 | 2020-07-02T16:00:22 | 2020-07-02T16:00:22 | 252,392,215 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,594 |
py
|
import sys
import os
import numpy as np
from subprocess import call
from yaml import safe_load
from bug_model.simulate_bug_decay import run_with_exponential_num_bugs_floats_in
from bug_model.simulate_bug_decay import DATA_DIR
from bug_model.driver import create_bins
BINNING_SCALE = 20
LOW_COMMITS = 10
REPEATS = 3
# This script much indebted to Katy Barnhart's exceptional tutorial on
# Dakota for calibration; see
# https://github.com/kbarnhart/calibration_with_dakota_clinic
# STEP 1: Use Dakota-created input files to prepare for run
input_template = "input_template.yml"
inputs = "inputs.yml"
call(["dprepro", sys.argv[1], input_template, inputs])
call(['rm', input_template])
# STEP 2: Run model
# Load parameters from the yaml formatted input.
with open(inputs, "r") as f:
params = safe_load(f)
R = params["R"]
S = params["S"]
F = params["F"]
# load the data
real_bfr = np.loadtxt(os.path.join(DATA_DIR,
'all_real_data_bug_find_rate.txt'))
real_commits = np.loadtxt(os.path.join(DATA_DIR,
'all_real_data_total_commits.txt'))
real_bins, real_bin_counts, real_binned_bfr = create_bins(
BINNING_SCALE, real_commits, real_bfr
)
# launch the simulation
avg_sim_bin_bfr = np.zeros_like(real_binned_bfr, dtype=float)
avg_sim_std_low_commits = 0
for i in range(REPEATS):
num_bugs, bug_rate, num_commits = run_with_exponential_num_bugs_floats_in(
R, S, F, num_realisations='from_data', stochastic=True
)
bins, bin_counts, sim_bin_bfr = create_bins(
BINNING_SCALE, num_commits, bug_rate
)
avg_sim_bin_bfr += sim_bin_bfr / float(REPEATS)
low_commit_repos = num_commits < LOW_COMMITS
avg_sim_std_low_commits += np.std(
bug_rate[low_commit_repos]
) / float(REPEATS)
# Step 3: Write output in format Dakota expects
# Each of the metrics listed in the Dakota .in file needs to be written to
# the specified output file given by sys.argv[2]. This is how information is
# sent back to Dakota.
# calc the rmse
# repo lengths are used directly by model and remain in order so simply now
rmse = (np.mean((real_binned_bfr - avg_sim_bin_bfr) ** 2)) ** 0.5
# calc the diff_std_at_low_commits
# note we have to use each individual sim, not the std of the averaged run
real_std_low_commits = np.std(real_bfr[real_commits < LOW_COMMITS])
diff_std_at_low_commits = np.abs(real_std_low_commits - avg_sim_std_low_commits)
# Write both to the expected file.
with open(sys.argv[2], "w") as fp:
fp.write(str(rmse) + '\n' + str(diff_std_at_low_commits))
|
[
"[email protected]"
] | |
c3a4c828b1b352960cd0ad0b3544c00b0b4a1a0b
|
f4bca02f5d447c13056767bd1723aaf6af25e7b9
|
/attendance/admin.py
|
db800eb82e231860cbd1ac92552f9a08a96ad836
|
[] |
no_license
|
ainc/student-progress
|
f9ae72f99f741227306dfbf04f2a54498dcebfef
|
9959d390822613cd7e3d314e92a7579de91af7a5
|
refs/heads/master
| 2021-01-21T13:56:35.060947 | 2016-07-19T17:44:42 | 2016-07-19T17:44:42 | 46,016,575 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 830 |
py
|
from django.contrib import admin
from .models import Coach, Student, Class, ClassSession, AttendanceRecord, Enrollment, StudentGuardian, StudentProfile, CoachNote, StudentGoal, Skill, Subskill, StudentProgress, Relationship, Team, TeamMember, PassPhrase
# Register your models here.
admin.site.register(Coach)
admin.site.register(ClassSession)
admin.site.register(AttendanceRecord)
admin.site.register(Class)
admin.site.register(Student)
admin.site.register(Enrollment)
admin.site.register(StudentGuardian)
admin.site.register(StudentProfile)
admin.site.register(CoachNote)
admin.site.register(StudentGoal)
admin.site.register(Skill)
admin.site.register(Subskill)
admin.site.register(StudentProgress)
admin.site.register(Relationship)
admin.site.register(Team)
admin.site.register(TeamMember)
admin.site.register(PassPhrase)
|
[
"[email protected]"
] | |
a893b8bc1eb62b75bdbe515d99cf5df8147152ae
|
7985897a15d89d18597a5cc73fcb5a5bfb81fbff
|
/powerdnsadmin/models/account_user.py
|
81bb43abc78abe866311e9bc5d6cdbc795c24b21
|
[
"MIT"
] |
permissive
|
Atisom/PowerDNS-Admin
|
5623e93fde89ccfde1ccc19e52732a3e783a1e3b
|
1d31b7bf818425c8e2b81008ab14704d16caf2a6
|
refs/heads/master
| 2021-04-24T00:17:47.919494 | 2020-11-27T14:43:46 | 2020-11-27T14:43:46 | 250,041,982 | 2 | 0 |
MIT
| 2020-03-25T17:11:53 | 2020-03-25T17:11:52 | null |
UTF-8
|
Python
| false | false | 569 |
py
|
from .base import db
class AccountUser(db.Model):
__tablename__ = 'account_user'
id = db.Column(db.Integer, primary_key=True)
account_id = db.Column(db.Integer,
db.ForeignKey('account.id'),
nullable=False)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
def __init__(self, account_id, user_id):
self.account_id = account_id
self.user_id = user_id
def __repr__(self):
return '<Account_User {0} {1}>'.format(self.account_id, self.user_id)
|
[
"[email protected]"
] | |
e92271f1c78474217bc02f56b883490d97558c08
|
d3ab828a7a11db5f35f308f4e30e4ffc5e2cf964
|
/jd/items.py
|
0ddb078f594520bd69574980d37a547ad236cd17
|
[] |
no_license
|
DahuK/Crawler
|
95a693fc3bdfbf8977ecd9351d20949cf3dde472
|
f6cd3d0af7a5a9b01bdee92150254b406dc8af11
|
refs/heads/master
| 2020-04-28T02:09:21.284569 | 2016-01-18T11:27:50 | 2016-01-18T11:27:50 | 40,756,401 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 551 |
py
|
# -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html
from scrapy.item import Item, Field
class TutorialItem(Item):
# define the fields for your item here like:
# name = Field()
pass
class JdbookItem(Item):
name = Field()
price = Field()
publisher = Field()
author = Field()
commit = Field()
shop = Field()
# category = Field()
# link = Field()
# desc = Field()
# rank = Field()
|
[
"[email protected]"
] | |
ffd1967fdd6141f81536c15df8db6f38b79377a7
|
edc5caaf86094e01fd1fb94817e8004cefaff780
|
/TP4/workspace-buildoutput/catkin_ws/build/turtlebot3/turtlebot3_description/catkin_generated/pkg.develspace.context.pc.py
|
6393b6898e69481fcaf13804491f14bd2290a0bb
|
[] |
no_license
|
waelkedi/IA
|
73a04c85e1410ddbf08c3cd11974e8d22f6ef26b
|
a658ea7600a094a687c6274abef5d49fcbe40688
|
refs/heads/master
| 2020-03-29T23:14:27.269859 | 2019-01-14T16:11:54 | 2019-01-14T16:11:54 | 150,463,256 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 391 |
py
|
# generated from catkin/cmake/template/pkg.context.pc.in
CATKIN_PACKAGE_PREFIX = ""
PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else []
PROJECT_CATKIN_DEPENDS = "urdf;xacro".replace(';', ' ')
PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else []
PROJECT_NAME = "turtlebot3_description"
PROJECT_SPACE_DIR = "/root/ros/catkin_ws/devel"
PROJECT_VERSION = "1.1.0"
|
[
"[email protected]"
] | |
70c3c7e641524c77f72502fe9dc156224c6de638
|
2228dbdfd5f1cb4ede5ae87a5e3554f6d4d50258
|
/Extended_source/Source_estimation/source_lens.py
|
6eabd2ef5376d6f8453bc19edf0217b78bc2c4c6
|
[] |
no_license
|
ialopezt/GalLenspy
|
b5d65403cffecdce8420265b0b220669489b49bf
|
59af3329f9c390d0b4dbfe1ef36dd414c1691674
|
refs/heads/master
| 2023-05-08T07:59:20.275380 | 2021-05-29T04:06:16 | 2021-05-29T04:06:16 | 267,147,572 | 3 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 13,016 |
py
|
from scipy.misc import *
import numpy as np
import pylab as plb
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from scipy.integrate import quad
from scipy.integrate import nquad
from scipy.misc import derivative
import pandas as pd
import emcee
import corner
from astropy import table as Table # For fast and easy reading / writing with tables using numpy library
from galpy.potential import MiyamotoNagaiPotential, NFWPotential, RazorThinExponentialDiskPotential, BurkertPotential # GALPY potentials
# In[ ]:
tt=Table.Table.read('coordinates.txt', format='ascii.tab') # importando los datos de las imรกgenes
#Import coordinates of images
theta1=tt['theta1']
theta2=tt['theta2']
sigma=tt['sigma']
theta=np.zeros(len(theta1),float)
for i in range(len(theta1)):
theta[i]=np.sqrt(theta1[i]**2+theta2[i]**2)
tt=Table.Table.read('alpha.txt', format='ascii.tab') # Import the values of the angles belonging to the circle for the arc
#Import the values alpha
alpha=tt['alpha']
tt=Table.Table.read('Cosmological_distances.txt', format='ascii.tab') # importando los datos de distancias cosmolรณgicas
#Importando distancias cosmolรณgicas y Sigma Crรญtico
D_ds=tt['D_ds'][0]
D_d=tt['D_d'][0]
D_s=tt['D_s'][0]
SIGMA_CRIT=tt['SIGMA_CRIT'][0]
tt=Table.Table.read('init_guess_params.txt', format='ascii.tab') # importando los datos de distancias cosmolรณgicas
#Importando distancias cosmolรณgicas y Sigma Crรญtico
R = tt['value'][0]
r = R*np.pi/(180*3600)
CX = tt['value'][1]
h = CX*np.pi/(180*3600)
CY = tt['value'][2]
k = CY*np.pi/(180*3600)
escala_r = tt['value'][3]
den_0 = tt['value'][4]
#R = 0.03
#r = R*np.pi/(180*3600)
#CX = -0.09
#h = CX*np.pi/(180*3600)
#CY = -0.01
#k = CY*np.pi/(180*3600)
Beta1 = r*np.cos(alpha)+h
Beta2 = r*np.sin(alpha)+k
FC = np.pi/(180*3600) #conversion factor between arcs and radians
#escala_r = 18
#den_0 = 44.5e8
#Illustration of obtained images with initial Guess
def POTDEFdisk_exp1(x):
def integ(TheTa, theta):
Sigma = den_0*np.exp(-D_d*TheTa/escala_r) #Volumetric density
return 2*TheTa*np.log(THETA/TheTa)*Sigma/(SIGMA_CRIT**3)
THETA = np.sqrt(x**2 + theta2[l]**2)
x = quad(integ, 0, theta[l], limit=100, args=(theta))[0]
return x
def POTDEFdisk_exp2(x):
def integ(TheTa, theta):
Sigma = den_0*np.exp(-D_d*TheTa/escala_r) #Volumetric density
return 2*TheTa*np.log(THETA/TheTa)*Sigma/(SIGMA_CRIT**3)
THETA = np.sqrt(x**2 + theta1[l]**2)
x = quad(integ, 0, theta[l], limit=100, args=(theta))[0]
return x
#Obteniendo gradiente del potencial deflector
GRADPOT1disk_exp = np.zeros((len(theta1)), float)
GRADPOT2disk_exp = np.zeros((len(theta1)), float)
GRADPOT1 = np.zeros((len(theta1)), float)
GRADPOT2 = np.zeros((len(theta1)), float)
THETA1 = np.zeros((len(theta1)), float)
THETA2 = np.zeros((len(theta1)), float)
for l in range(len(theta1)):
GRADPOT1disk_exp[l]= derivative(POTDEFdisk_exp1, theta1[l], dx=1e-9, order=7)
GRADPOT2disk_exp[l]= derivative(POTDEFdisk_exp2, theta2[l], dx=1e-9, order=7)
GRADPOT1[l]=(SIGMA_CRIT**2)*(GRADPOT1disk_exp[l])
GRADPOT2[l]=(SIGMA_CRIT**2)*(GRADPOT2disk_exp[l])
#Images obtained with initial guess
for l in range(len(theta1)):
THETA1[l] = Beta1[l]+GRADPOT1[l]
THETA2[l] = Beta2[l]+GRADPOT2[l]
# In[ ]:
#Graphics of source and images
fig = plt.figure()
plt.rcParams['figure.figsize'] =(10,10)
plb.plot(Beta1*1e6, Beta2*1e6, '--r')
plb.plot(theta1*1e6, theta2*1e6, 'ob')
plb.plot(THETA1*1e6, THETA2*1e6, 'og')
plb.xlim(-2.5*np.pi*1e6/(180*3600),2.5*np.pi*1e6/(180*3600))
plb.ylim(-2.5*np.pi*1e6/(180*3600),2.5*np.pi*1e6/(180*3600))
plb.savefig('Guess_initial_source_lens.pdf')
# In[ ]:
print ("\n#####################################################################")
print("MCMC------GALLENSPY")
#Model of the lens
def model(parameters, theta1, theta2, sigma):
RAD, H, K, SIGMA_0, H_R = parameters
r = RAD*np.pi/(180*3600)
h = H*np.pi/(180*3600)
k = K*np.pi/(180*3600)
Beta1 = r*np.cos(alpha)+h
Beta2 = r*np.sin(alpha)+k
def POTDEFdisk_exp1(TheTa1,theta):
TheTa = np.sqrt(TheTa1**2+theta2[l]**2)
R = D_d*TheTa
Sigma = SIGMA_0*np.exp(-D_d*TheTa/H_R) #Volumetric density
kappa = Sigma/SIGMA_CRIT
return (2/theta1[l])*TheTa1*kappa/SIGMA_CRIT**2
def POTDEFdisk_exp2(TheTa2,theta):
TheTa = np.sqrt(TheTa2**2+theta1[l]**2)
R = D_d*TheTa
Sigma = SIGMA_0*np.exp(-D_d*TheTa/H_R) #Volumetric density
kappa = Sigma/SIGMA_CRIT
return (2/theta2[l])*TheTa2*kappa/SIGMA_CRIT**2
GRADPOT1disk_exp = np.zeros((len(theta1)), float)
GRADPOT2disk_exp = np.zeros((len(theta1)), float)
GRADPOT1 = np.zeros((len(theta1)), float)
GRADPOT2 = np.zeros((len(theta1)), float)
THETA1 = np.zeros((len(theta1)), float)
THETA2 = np.zeros((len(theta1)), float)
for l in range(len(theta1)):
GRADPOT1disk_exp[l]= quad(POTDEFdisk_exp1, 0, theta1[l], limit=100, args=(theta[l]))[0]
GRADPOT2disk_exp[l]= quad(POTDEFdisk_exp2, 0, theta2[l], limit=100, args=(theta[l]))[0]
for l in range(len(theta1)):
GRADPOT1[l]=(SIGMA_CRIT**2)*(GRADPOT1disk_exp[l])
GRADPOT2[l]=(SIGMA_CRIT**2)*(GRADPOT2disk_exp[l])
for l in range(len(theta1)):
THETA1[l] = Beta1[l]+GRADPOT1[l]
THETA2[l] = Beta2[l]+GRADPOT2[l]
THETA_teor = np.zeros((len(theta1)), float)
for l in range(len(theta1)):
THETA_teor[l] = np.sqrt(THETA1[l]**2+THETA2[l]**2)
return THETA_teor
# In[ ]:
#Likelihood function
def lnlike(parameters, theta1, theta2, sigma):
RAD, H, K, SIGMA_0, H_R = parameters
THETA_teor = model(parameters, theta1, theta2, sigma)
X = np.zeros((len(theta1)),float)
for l in range(len(theta1)):
X[l]=((theta[l]-THETA_teor[l])**2)/(sigma[l]**2)
return -0.5*np.sum(X)
# In[ ]:
#initial guess in the MCMC
start=np.zeros(5,float)
start[0] = R
start[1] = CX
start[2] = CY
start[3] = den_0
start[4] = escala_r
# In[ ]:
#Parametric space in the MCMC
def lnprior(parameters):
RAD, H, K, SIGMA_0, H_R = parameters
# if 0.05<R_S<32 and 0.05e11<m_0<12e11 and 0.8e8<SIGMA_0<17e8 and 1<H_R<7 and 0.05<B<17 and 0.09e10<MASS<1.1e10:
if -0.2<H<0.2 and -0.2<K<0.2 and 1e8<SIGMA_0<60e8 and 2<H_R<24 and 0<RAD<0.2:
return 0.0
return -np.inf
# In[ ]:
#Probability function
def lnprob(parameters, theta1, theta2, sigma):
lp = lnprior(parameters)
if not np.isfinite(lp):
return -np.inf
return lp + lnlike(parameters, theta1, theta2, sigma)
# In[ ]:
#Dimension and walkers
ndim, nwalkers = 5, 100
#initial posicion and step length
pos_step = 1e-8
pos_in = [abs(start + pos_step*start*np.random.randn(ndim)+1e-9*np.random.randn(ndim)) for i in range(nwalkers)]
# In[ ]:
sampler = emcee.EnsembleSampler(nwalkers, ndim, lnprob, args=(theta1, theta2,sigma))
# In[ ]:
#Number of Steps
sampler.run_mcmc(pos_in, 1000, progress=True)
# In[ ]:
fig = plt.figure()
ax = fig.add_axes((0.15, 0.3, 0.75, 0.6))
chain_steps = [i for i in range(len(sampler.chain[:,:,0].T))]
chain_W = []
for i in range(nwalkers):
chain_value = sampler.chain[:,:,0].T[:][:,i]
ax.plot(chain_steps, chain_value, '-', color='k', alpha=0.3)
ax.plot(chain_steps, len(chain_steps)*[start[0]], '-', color='r', lw=1)
ax.set_xlim(0, len(chain_steps)-1)
plb.savefig('h.pdf')
# In[ ]:
fig = plt.figure()
ax = fig.add_axes((0.15, 0.3, 0.75, 0.6))
chain_steps = [i for i in range(len(sampler.chain[:,:,1].T))]
chain_W = []
for i in range(nwalkers):
chain_value = sampler.chain[:,:,1].T[:][:,i]
ax.plot(chain_steps, chain_value, '-', color='k', alpha=0.3)
ax.plot(chain_steps, len(chain_steps)*[start[1]], '-', color='r', lw=1)
ax.set_xlim(0, len(chain_steps)-1)
plb.savefig('k.pdf')
# In[ ]:
fig = plt.figure()
ax = fig.add_axes((0.15, 0.3, 0.75, 0.6))
chain_steps = [i for i in range(len(sampler.chain[:,:,2].T))]
chain_W = []
for i in range(nwalkers):
chain_value = sampler.chain[:,:,2].T[:][:,i]
ax.plot(chain_steps, chain_value, '-', color='k', alpha=0.3)
ax.plot(chain_steps, len(chain_steps)*[start[2]], '-', color='r', lw=1)
ax.set_xlim(0, len(chain_steps)-1)
plb.savefig('Sigma_0.pdf')
# In[ ]:
fig = plt.figure()
ax = fig.add_axes((0.15, 0.3, 0.75, 0.6))
chain_steps = [i for i in range(len(sampler.chain[:,:,3].T))]
chain_W = []
for i in range(nwalkers):
chain_value = sampler.chain[:,:,3].T[:][:,i]
ax.plot(chain_steps, chain_value, '-', color='k', alpha=0.3)
ax.plot(chain_steps, len(chain_steps)*[start[3]], '-', color='r', lw=1)
ax.set_xlim(0, len(chain_steps)-1)
plb.savefig('h_r.pdf')
# In[ ]:
#Step of cut in the MCMC
samples = sampler.chain[:, 600:, :].reshape((-1, ndim))
# In[ ]:
percentage=0.68
#Contours of values
fig = corner.corner(samples, labels=["$r$", "$h$", r"$k$", r"$\Sigma_0$", "$h_r$"],
quantiles = [0.5-0.5*percentage, 0.5, 0.5+0.5*percentage],fill_contours=True, plot_datapoints=True)
fig.savefig("contours_source_lens.pdf")
# In[ ]:
#Parameters and errors
para = []
parap68=[]; paran68=[]
parap95=[]; paran95=[]
fit_para = []
for i in range(ndim):
mcmc = np.percentile(samples[:, i], [50.-0.5*95, 50.-0.5*68, 50., 50.+0.5*68, 50.+0.5*95])
para.append(mcmc[2])
fit_para.append(mcmc[2])
parap68.append(mcmc[3]-mcmc[2])
paran68.append(mcmc[2]-mcmc[1])
parap95.append(mcmc[4]-mcmc[2])
paran95.append(mcmc[2]-mcmc[0])
# In[ ]:
#Visualization of generated images for the parameter set obtained
R = para[0]
H = para[1]
K = para[2]
Sigma_0 = para[3]
h_r = para[4]
r = R*np.pi/(180*3600)
h = H*np.pi/(180*3600)
k = K*np.pi/(180*3600)
Beta1 = r*np.cos(alpha)+h
Beta2 = r*np.sin(alpha)+k
def POTDEFdisk_exp1(x):
def integ(TheTa, theta):
Sigma = Sigma_0*np.exp(-D_d*TheTa/h_r) #Volumetric density
return 2*TheTa*np.log(THETA/TheTa)*Sigma/(SIGMA_CRIT**3)
THETA = np.sqrt(x**2 + theta2[l]**2)
x = quad(integ, 0, theta[l], limit=100, args=(theta))[0]
return x
def POTDEFdisk_exp2(x):
def integ(TheTa, theta):
Sigma = Sigma_0*np.exp(-D_d*TheTa/h_r) #Volumetric density
return 2*TheTa*np.log(THETA/TheTa)*Sigma/(SIGMA_CRIT**3)
THETA = np.sqrt(x**2 + theta1[l]**2)
x = quad(integ, 0, theta[l], limit=100, args=(theta))[0]
return x
#Obteniendo gradiente del potencial deflector
GRADPOT1disk_exp = np.zeros((len(theta1)), float)
GRADPOT2disk_exp = np.zeros((len(theta1)), float)
GRADPOT1 = np.zeros((len(theta1)), float)
GRADPOT2 = np.zeros((len(theta1)), float)
THETA1 = np.zeros((len(theta1)), float)
THETA2 = np.zeros((len(theta1)), float)
for l in range(len(theta1)):
GRADPOT1disk_exp[l]= derivative(POTDEFdisk_exp1, theta1[l], dx=1e-9, order=7)
GRADPOT2disk_exp[l]= derivative(POTDEFdisk_exp2, theta2[l], dx=1e-9, order=7)
GRADPOT1[l]=(SIGMA_CRIT**2)*(GRADPOT1disk_exp[l])
GRADPOT2[l]=(SIGMA_CRIT**2)*(GRADPOT2disk_exp[l])
#Images obtained with initial guess
for l in range(len(theta1)):
THETA1[l] = Beta1[l]+GRADPOT1[l]
THETA2[l] = Beta2[l]+GRADPOT2[l]
# In[ ]:
#Graphics of source and images
fig = plt.figure()
plt.rcParams['figure.figsize'] =(10,10)
plb.plot(Beta1/FC, Beta2/FC, '--r')
plb.plot(theta1/FC, theta2/FC, 'ob')
plb.plot(THETA1/FC, THETA2/FC, 'og')
plb.xlim(-2.5,2.5)
plb.ylim(-2.5,2.5)
plb.legend(['Source', 'Observational data', 'Model values'], loc='upper right', fontsize=15)
#plb.show()
plt.savefig('fitting.pdf')
# In[ ]:
#Parameters and errors
r= para[0]; r_95pos = parap95[0]; r_95neg = paran95[0]; r_68pos = parap68[0]; r_68neg = paran68[0]
h= para[1]; h_95pos = parap95[1]; h_95neg = paran95[1]; h_68pos = parap68[1]; h_68neg = paran68[1]
k = para[2]; k_95pos = parap95[2]; k_95neg = paran95[2]; k_68pos = parap68[2]; k_68neg = paran68[2]
Sigma_0 = para[3]; Sigma_0_95pos = parap95[3]; Sigma_0_95neg = paran95[3]; Sigma_0_68pos = parap68[3]; Sigma_0_68neg = paran68[3]
h_r = para[4]; h_r_95pos = parap95[4]; h_r_95neg = paran95[4]; h_r_68pos = parap68[4]; h_r_68neg = paran68[4]
# In[ ]:
table_data = []
table_para = [r"r",r"h",r"k",r"Sigma_0", r"h_r"]
table_units = [r"arcs",r"arcs",r"arcs", r"Solar_Mass/Kpc^2", r"Kpc"]
para = [r, h, k, Sigma_0, h_r]
parap68=[r_68pos, h_68pos, k_68pos, Sigma_0_68pos, h_r_68pos]
paran68=[r_68neg, h_68neg, k_68neg, Sigma_0_68neg, h_r_68neg]
parap95=[r_95pos, h_95pos, k_95pos, Sigma_0_95pos, h_r_95pos]
paran95=[r_95neg, h_95neg, k_95neg, Sigma_0_95neg, h_r_95neg]
index=[r"r",r"h",r"k",r"Sigma_0", r"h_r"]
for i in range(len(para)):
table_data.append([table_para[i], table_units[i], para[i], parap95[i], paran95[i], parap68[i], paran68[i]])
column_name = [r"PARAMETER", r"UNITS", r"FIT", r"95%(+)", r"95%(-)", r"68%(+)", r"68%(-)"]
table_p = pd.DataFrame(table_data, index=index, columns=column_name)
table_p.to_csv("parameters_lens_source.txt", sep='\t', encoding='utf-8')
print ("\n#####################################################################")
print(table_p)
print ("\nDone")
print ("\n#####################################################################\n")
|
[
"[email protected]"
] | |
967748c947304582173245dab50b88d282158a96
|
eab97fdb3a2fd93afaa4c5ad172c46e42d32b27a
|
/math_operations.py
|
a6e8bb0a2d1586a51315fb305472fbaec961a78d
|
[] |
no_license
|
chdzr/basic_python
|
ac2c1727677c58ca92404d404aaa6329570d2424
|
b2b014526eb6f8c3e618c28df95d504b18719231
|
refs/heads/main
| 2023-02-28T07:36:20.964822 | 2021-01-30T23:43:41 | 2021-01-30T23:43:41 | 328,090,701 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 67 |
py
|
print(2+3)
print(3-2)
print(2*3)
print(6/2)
print(1%2)
print(5**2)
|
[
"[email protected]"
] | |
0285446a48aec8a5abe62bc424a19ff2e89ae8c3
|
ac50f3ac63fe399cd229f2a5e584494a9299b759
|
/homework.py
|
8db383975cbc0a86ae7c5b67b88adc2153173cf9
|
[
"MIT"
] |
permissive
|
zoltanvasile/homework-session-2
|
62bed5fe684758239e493f044c850f701915a711
|
7d1149db3115375e471b6f1d7bb1975934b47f8a
|
refs/heads/master
| 2022-11-13T06:31:45.204906 | 2020-06-25T12:55:45 | 2020-06-25T12:55:45 | 274,914,335 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 792 |
py
|
# 1.Reverse the order of the items in an array.
# Example:
# a = [1, 2, 3, 4, 5]
# Result:
# a = [5, 4, 3, 2, 1]
def reverseFunction(aList):
return aList.reverse()
a=[1,2,3,4,5]
reverseFunction(a)
print(a)
# 2. Get the number of occurrences of var b in array a.
# Example:
# a = [1, 1, 2, 2, 2, 2, 3, 3, 3]
# b = 2
# Result:
# 4
def occurencesNr(aList,elem):
return aList.count(elem)
b = [1,1,2,2,2,2,3,3,3]
c = 3
d = occurencesNr(b,c)
print(d)
# 3. Given a sentence as string, count the number of words in it.
# Example:
# a = 'ana are mere si nu are pere'
# Result:
# 7
def wordsCounter(aString):
return len(aString.split())
string = 'ana are mere si nu are pere'
ret = wordsCounter(string)
print(ret)
|
[
"[email protected]"
] | |
0396eb254b1de5fa42497fb6a7b869393ca51085
|
29c58b3bec6ac0fcdb3070efc118600ee92004da
|
/test/test_unread_count.py
|
42aeede4b08156288cd84090b1b6d8c211d1374e
|
[
"MIT"
] |
permissive
|
mailslurp/mailslurp-client-python
|
a2b5a0545206714bd4462ae517f242852b52aaf9
|
5c9a7cfdd5ea8bf671928023e7263847353d92c4
|
refs/heads/master
| 2023-06-23T00:41:36.257212 | 2023-06-14T10:10:14 | 2023-06-14T10:10:14 | 204,662,133 | 8 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,807 |
py
|
# coding: utf-8
"""
MailSlurp API
MailSlurp is an API for sending and receiving emails from dynamically allocated email addresses. It's designed for developers and QA teams to test applications, process inbound emails, send templated notifications, attachments, and more. ## Resources - [Homepage](https://www.mailslurp.com) - Get an [API KEY](https://app.mailslurp.com/sign-up/) - Generated [SDK Clients](https://docs.mailslurp.com/) - [Examples](https://github.com/mailslurp/examples) repository # noqa: E501
The version of the OpenAPI document: 6.5.2
Contact: [email protected]
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import unittest
import datetime
import mailslurp_client
from mailslurp_client.models.unread_count import UnreadCount # noqa: E501
from mailslurp_client.rest import ApiException
class TestUnreadCount(unittest.TestCase):
"""UnreadCount unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def make_instance(self, include_optional):
"""Test UnreadCount
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included """
# model = mailslurp_client.models.unread_count.UnreadCount() # noqa: E501
if include_optional :
return UnreadCount(
count = 56
)
else :
return UnreadCount(
count = 56,
)
def testUnreadCount(self):
"""Test UnreadCount"""
inst_req_only = self.make_instance(include_optional=False)
inst_req_and_optional = self.make_instance(include_optional=True)
if __name__ == '__main__':
unittest.main()
|
[
"[email protected]"
] | |
69aa220a34896f8d7cf9b804ed9aa05956608b82
|
7e0f269b9199d7fc1e56377ad53c5e0011a002a3
|
/main/homework6/1.py
|
3c91fd0a96f2f063eebbbea7d3ab0c4594c10ec5
|
[] |
no_license
|
IgnacioCastro0713/exercises
|
8fb91fe3c27f27087a26902c118d313173ec36ec
|
e45c4dc39fb64ed5d310b5422bc4fdc67b840621
|
refs/heads/master
| 2020-03-26T13:24:16.862854 | 2018-10-01T03:22:42 | 2018-10-01T03:22:42 | 144,937,116 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 564 |
py
|
# Josรฉ Ignacio Menchaca Castro
# 215818166
lista = ['Ana', 'Luis', 'Pedro', 'Juan']
x = 0
while True:
print('Seleciona una opciรณn de la lista a remplazar: ')
for i in lista:
x += 1
print(x, '.-', i)
remove = int(input('Opcion: '))
lista.remove(lista[remove - 1])
print('Lista: ', lista)
replace = input('Escribe el nuevo nombre de la lista: ')
lista.insert(remove - 1, replace.capitalize())
print('Lista: ', lista)
ask = input('ยฟDesea terminar el programa? s/n: ')
if ask.lower() != 'n':
break
|
[
"[email protected]"
] | |
30a0136e2f51eab008da29509e4c56e638b5286a
|
279d4e5428398d0ddc529e4a45b97c830e10469d
|
/Projects/Project9_test.py
|
bfd5617a318ac1186de9dbdad72df2c3c2fb575d
|
[] |
no_license
|
michaelstreyle/CS160
|
ffa5a2f7c21b10699458b12dcf14f99a12af397e
|
b5ac2d5d3d74a1ad131f27480b154556ca6cc0e0
|
refs/heads/master
| 2020-09-11T10:34:20.278305 | 2019-11-16T02:44:51 | 2019-11-16T02:44:51 | 222,036,835 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,850 |
py
|
"""
Testing the module morse
Karina Hoff, 2018
"""
#!/usr/bin/python3
import pytest
from Project9 import Coder
class TestMorseMethods:
"""Testing module morse"""
@pytest.fixture(scope="function", autouse=True)
def setup_class(self):
"""Setting up"""
self.the_tree = Coder("morse.txt")
def test_init_error(self):
"""Test __init__ error"""
with pytest.raises(Exception) as excinfo:
tree = Coder() # pylint: disable=no-value-for-parameter, unused-variable
exception_message = excinfo.value.args[0]
assert (
exception_message
== "__init__() missing 1 required positional argument: 'file_in'"
)
def test_find_path(self):
"""Test find_path"""
assert self.the_tree.find_path(self.the_tree.morse_tree, "e", "") == "."
assert not self.the_tree.find_path(self.the_tree.morse_tree, "$", "")
def test_follow_and_retrieve(self):
"""Test follow_and_retrieve"""
assert self.the_tree.follow_and_retrieve("-.-.") == "c"
assert self.the_tree.follow_and_retrieve("...") == "s"
assert not self.the_tree.follow_and_retrieve("-.-..") == "ฤ"
assert not self.the_tree.follow_and_retrieve("...-...") == "ล"
def test_follow_and_insert(self):
"""Test follow_and_insert"""
self.the_tree.follow_and_insert("-.-..", "ฤ")
assert self.the_tree.follow_and_retrieve("-.-..") == "ฤ"
self.the_tree.follow_and_insert("...-...", "ล")
assert self.the_tree.follow_and_retrieve("...-...") == "ล"
def test_follow_and_insert_replacement(self):
"""Test follow_and_insert with replacement"""
self.the_tree.follow_and_insert(".", "CS160")
assert self.the_tree.follow_and_retrieve(".") == "CS160"
assert not self.the_tree.follow_and_retrieve(".") == "e"
def test_encode(self):
"""Test encoding"""
assert self.the_tree.encode("sos") == "... --- ... "
def test_encode_error(self):
"""Test encoding error"""
with pytest.raises(ValueError) as excinfo:
self.the_tree.encode("$$")
exception_message = excinfo.value.args[0]
assert (
exception_message
== "Could not encode $$: $ is not in the tree"
)
def test_decode(self):
"""Test decode"""
assert self.the_tree.decode("... --- ...") == "sos"
def test_decode_error(self):
"""Test decoding error"""
with pytest.raises(ValueError) as excinfo:
self.the_tree.decode("...---...")
exception_message = excinfo.value.args[0]
assert (
exception_message
== "Could not decode ...---...: ...---... is not in the tree"
)
if __name__ == "__main__":
pytest.main(["Project9_test.py"])
|
[
"[email protected]"
] | |
1d9f9d6e6fe20f63cf554997baf332c28a44b7e6
|
7520659adb4bb3a36b29a68894c449cfff2f241e
|
/trab1.py
|
4587ffb68fa3b62c35e4345f5ef38ddf46d1a2b8
|
[] |
no_license
|
thiagouft/Trabalho-1-TCLFA
|
6df2f78c6f43771a0d314d2015c0b4755271c3ba
|
43a5e91e16dc9199da28847d57cc89bceafbb7f6
|
refs/heads/master
| 2021-05-16T11:06:53.946436 | 2017-09-27T23:37:15 | 2017-09-27T23:37:15 | 104,926,075 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 8,348 |
py
|
๏ปฟ#Aluno: Thiago Silva Pereira
def transicao_estendida(estado, valor):
#print(valor)
if valor == '&':
return 'q0'
i = len(valor)
e = transicao_estendida(estado,valor[:len(valor)-1])
#print(e)
return trasicao_afd(e,valor[i-1])
def trasicao_afd(estado, palavra):
if estado == 'q0':
if (palavra == 'a'):
print("q0 entrou \"" + palavra + "\"" + " vai para q2.")
return 'q2'
else:
print("q0 entrou \"" + palavra + "\"" + " vai para q1.")
return 'q1'
if estado == 'q1':
if (palavra == 'a'):
print("q1 entrou \"" + palavra + "\"" + " vai para q4.")
return 'q4'
else:
print("q1 entrou \"" + palavra + "\"" + " vai para q3.")
return 'q3'
if estado == 'q2':
if (palavra == 'a'):
print("q2 entrou \"" + palavra + "\"" + " vai para q6.")
return 'q6'
else:
print("q2 entrou \"" + palavra + "\"" + " vai para q5.")
return 'q5'
if estado == 'q3':
if (palavra == 'a'):
print("q3 entrou \"" + palavra + "\"" + " vai para q8.")
return 'q8'
else:
print("q3 entrou \"" + palavra + "\"" + " vai para q7.")
return 'q7'
if estado == 'q4':
if (palavra == 'a'):
print("q4 entrou \"" + palavra + "\"" + " vai para q8.")
return 'q8'
else:
print("q4 entrou \"" + palavra + "\"" + " vai para q9.")
return 'q9'
if estado == 'q5':
if (palavra == 'a'):
print("q5 entrou \"" + palavra + "\"" + " vai para q8.")
return 'q8'
else:
print("q5 entrou \"" + palavra + "\"" + " vai para q10.")
return 'q10'
if estado == 'q6':
if (palavra == 'a'):
print("q6 entrou \"" + palavra + "\"" + " vai para q8.")
return 'q8'
else:
print("q6 entrou \"" + palavra + "\"" + " vai para q11.")
return 'q11'
if estado == 'q7':
if (palavra == 'a'):
print("q7 entrou \"" + palavra + "\"" + " vai para q12.")
return 'q12'
else:
print("q7 entrou \"" + palavra + "\"" + " vai para q7.")
return 'q7'
if estado == 'q8':
if (palavra == 'a'):
print("q8 entrou \"" + palavra + "\"" + " vai para q8.")
return 'q8'
else:
print("q8 entrou \"" + palavra + "\"" + " vai para q8.")
return 'q8'
if estado == 'q9':
if (palavra == 'a'):
print("q9 entrou \"" + palavra + "\"" + " vai para q13.")
return 'q13'
else:
print("q9 entrou \"" + palavra + "\"" + " vai para q10.")
return 'q10'
if estado == 'q10':
if (palavra == 'a'):
print("q10 entrou \"" + palavra + "\"" + " vai para q12.")
return 'q12'
else:
print("q10 entrou \"" + palavra + "\"" + " vai para q7.")
return 'q7'
if estado == 'q11':
if (palavra == 'a'):
print("q11 entrou \"" + palavra + "\"" + " vai para q13.")
return 'q13'
else:
print("q11 entrou \"" + palavra + "\"" + " vai para q10.")
return 'q10'
if estado == 'q12':
if (palavra == 'a'):
print("q12 entrou \"" + palavra + "\"" + " vai para q14.")
return 'q14'
else:
print("q12 entrou \"" + palavra + "\"" + " vai para q9.")
return 'q9'
if estado == 'q13':
if (palavra == 'a'):
print("q13 entrou \"" + palavra + "\"" + " vai para q14.")
return 'q14'
else:
print("q13 entrou \"" + palavra + "\"" + " vai para q9.")
return 'q9'
if estado == 'q14':
if (palavra == 'a'):
print("q14 entrou \"" + palavra + "\"" + " vai para q15.")
return 'q15'
else:
print("q14 entrou \"" + palavra + "\"" + " vai para q11.")
return 'q11'
if estado == 'q15':
if (palavra == 'a'):
print("q15 entrou \"" + palavra + "\"" + " vai para q15.")
return 'q15'
else:
print("q15 entrou \"" + palavra + "\"" + " vai para q11.")
return 'q11'
'''palavra = input("Digite uma palavra do alfabeto (a,b) minusculo")
estado = ['q0']
i = 0
tam_palavra = len(palavra)
while tam_palavra > 0:
if estado[i] == 'q0':
if(palavra[i] == 'a'):
estado.append('q2')
tam_palavra -= 1
else:
estado.append('q1')
tam_palavra -= 1
if estado[i] == 'q1':
if(palavra[i] == 'a'):
estado.append('q4')
tam_palavra -= 1
else:
estado.append('q3')
tam_palavra -= 1
if estado[i] == 'q2':
if(palavra[i] == 'a'):
estado.append('q6')
tam_palavra -= 1
else:
estado.append('q5')
tam_palavra -= 1
if estado[i] == 'q3':
if(palavra[i] == 'a'):
estado.append('q8')
tam_palavra -= 1
else:
estado.append('q7')
tam_palavra -= 1
if estado[i] == 'q4':
if(palavra[i] == 'a'):
estado.append('q8')
tam_palavra -= 1
else:
estado.append('q9')
tam_palavra -= 1
if estado[i] == 'q5':
if(palavra[i] == 'a'):
estado.append('q8')
tam_palavra -= 1
else:
estado.append('q10')
tam_palavra -= 1
if estado[i] == 'q6':
if(palavra[i] == 'a'):
estado.append('q8')
tam_palavra -= 1
else:
estado.append('q11')
tam_palavra -= 1
if estado[i] == 'q7':
if(palavra[i] == 'a'):
estado.append('q12')
tam_palavra -= 1
else:
estado.append('q7')
tam_palavra -= 1
if estado[i] == 'q8':
if(palavra[i] == 'a'):
estado.append('q8')
tam_palavra -= 1
else:
estado.append('q8')
tam_palavra -= 1
if estado[i] == 'q9':
if(palavra[i] == 'a'):
estado.append('q13')
tam_palavra -= 1
else:
estado.append('q10')
tam_palavra -= 1
if estado[i] == 'q10':
if(palavra[i] == 'a'):
estado.append('q12')
tam_palavra -= 1
else:
estado.append('q7')
tam_palavra -= 1
if estado[i] == 'q11':
if(palavra[i] == 'a'):
estado.append('q13')
tam_palavra -= 1
else:
estado.append('q10')
tam_palavra -= 1
if estado[i] == 'q12':
if(palavra[i] == 'a'):
estado.append('q14')
tam_palavra -= 1
else:
estado.append('q9')
tam_palavra -= 1
if estado[i] == 'q13':
if(palavra[i] == 'a'):
estado.append('q14')
tam_palavra -= 1
else:
estado.append('q9')
tam_palavra -= 1
if estado[i] == 'q14':
if(palavra[i] == 'a'):
estado.append('q15')
tam_palavra -= 1
else:
estado.append('q11')
tam_palavra -= 1
if estado[i] == 'q15':
if(palavra[i] == 'a'):
estado.append('q15')
tam_palavra -= 1
else:
estado.append('q11')
tam_palavra -= 1
print("Entrou \"" + palavra[i] + "\" estado " +estado[i+1])
i += 1
if estado[-1] == 'q7' or estado[-1] == 'q9' or estado[-1] == 'q12' or estado[-1] == 'q14':
print("Palavra \"" + palavra + "\" do alfabeto \"a,b\" Reconhecida com sucesso")
else:
print("Palavra \"" + palavra + "\" do alfabeto \"a,b\" Nรฃo reconhecida")'''
palavra = input("Digite uma palavra do alfabeto (a,b) em minusculo")
palavra_com_vazio = "&"+palavra
aux = transicao_estendida('q0',palavra_com_vazio)
if aux == 'q7' or aux == 'q9' or aux == 'q12' or aux == 'q14':
print("Palavra \""+ palavra+"\" " + "Reconhecida com Sucesso.")
else:
print("Palavra \"" + palavra + "\" " + "Nรฃo Reconhecida.")
|
[
"[email protected]"
] | |
aa96742c1637323518cf8e3c63e7ed393d460c7d
|
d04ed5c974b8cdf41cf1b9fcd48b9c12ac049c77
|
/app/__init__.py
|
050c5d9eb285800470126b37cbf1e9c04fe552f5
|
[] |
no_license
|
KCzenczek/Flask_MG
|
5f9a44d30a9f8942e1b5f7a1fceb5fbf6991a654
|
f3823af347517ff75b275ea75aa4a7d271b06869
|
refs/heads/main
| 2023-02-12T03:28:38.115294 | 2021-01-12T20:17:22 | 2021-01-12T20:17:22 | 322,925,083 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,326 |
py
|
from flask import Flask
from flask_bootstrap import Bootstrap
from flask_mail import Mail
from flask_moment import Moment
from flask_sqlalchemy import SQLAlchemy
from config import config
from flask_login import LoginManager
from flask_migrate import Migrate
from flask_pagedown import PageDown
from flask_wtf.csrf import CSRFProtect
bootstrap = Bootstrap()
mail = Mail()
moment = Moment()
db = SQLAlchemy()
migrate = Migrate()
pagedown = PageDown()
csrf = CSRFProtect()
login_manager = LoginManager()
login_manager.login_view = 'auth.login'
def create_app(config_name):
app = Flask(__name__)
app.config.from_object(config[config_name])
config[config_name].init_app(app)
bootstrap.init_app(app)
mail.init_app(app)
moment.init_app(app)
db.init_app(app)
migrate.init_app(app, db)
login_manager.init_app(app)
pagedown.init_app(app)
csrf.init_app(app)
if app.config['SSL_REDIRECT']:
from flask_sslify import SSLify
sslify = SSLify(app)
from .main import main as main_blueprint
app.register_blueprint(main_blueprint)
from .auth import auth as auth_blueprint
app.register_blueprint(auth_blueprint, url_prefix='/auth')
from .api import api as api_blueprint
app.register_blueprint(api_blueprint, url_prefix='/api/v1')
return app
|
[
"[email protected]"
] | |
5676c70152b1f096593b050e73984295b82952ee
|
6674ecfc4a2c0a3a5bdc45b458e7f18e9b134092
|
/src/lvgl/scripts/release.py
|
28370c668b96a1bc915498d83c2659b7a44e2049
|
[
"MIT"
] |
permissive
|
AlexGoodyear/TTGO_TWatch_Library
|
0ab8b76b0d96cadcf5982bafc028bdf0ad6a5ac4
|
d982092b2700ba2a4deba8be38bf338ffde855c1
|
refs/heads/master
| 2022-12-05T03:26:52.905530 | 2020-08-21T19:28:45 | 2020-08-21T19:28:45 | 276,957,141 | 5 | 0 |
MIT
| 2020-08-12T10:32:06 | 2020-07-03T17:46:09 |
C
|
UTF-8
|
Python
| false | false | 13,699 |
py
|
#!/usr/bin/env python
# Release lvgl, lv_examples, lv_drivers. docs, blog and prepare the development of the next major, minoror bugfix release
# Usage: ./release,py bugfix | minor | major
# The option means what type of versin to prepare for development after release
#
# STEPS:
# - clone all 5 repos
# - get the version numnber from lvgl.h
# - set release branch (e.g. "release/v7")
# - prepare lvgl
# - run lv_conf_internal.py
# - run code formatter
# - clear LVGL_VERSION_INFO (set to "")
# - run Doxygen
# - update the version in lvgl's library.json, library.properties, lv_conf_template.h
# - update CHANGELOG.md
# - commit changes
# - prepare lv_examples
# - upadte the required LVGL version in lv_examples.h (LV_VERSION_CHECK)
# - update the version in lv_ex_conf_template.h
# - prepare lv_drivers
# - update the version in library.json, lv_drv_conf_template.h
# - prepare docs
# - update API XML
# - clear the versiopn info (should be plain vx.y.z)
# - tag all repos with the new version
# - merge to release branches
# - blog: add release post
# - push tags and commits
# - docs: run ./updade.py release/vX
#
# If --patch
# - merge master to dev branches
# - increment patch version by 1 and append "-dev". E.g. "vX.Y.(Z+1)-dev"
# - update version numbers in lvgl and docs
# - commit and push
# - docs: run ./updade.py latest dev
#
# Else (not --patch)
# - merge master to dev
# - merge the dev to master
# - increment version number like "vX.(Y+1).0-dev"
# - apply the new version in dev branches of lvgl, lv_examples, lv_drivers, docs
# - commit and push to dev branches
# - docs: run ./updade.py latest dev
import re
import os, fnmatch
import os.path
from os import path
from datetime import date
import sys
upstream_org_url = "https://github.com/lvgl/"
workdir = "./release_tmp"
ver_major = -1
ver_minor = -1
ver_patch = -1
ver_str = ""
dev_ver_str = ""
release_br = ""
release_note = ""
prepare_type = ['major', 'minor', 'bugfix']
dev_prepare = 'minor'
def upstream(repo):
return upstream_org_url + repo + ".git"
def cmd(c, exit_on_err = True):
print("\n" + c)
r = os.system(c)
if r:
print("### Error: " + str(r))
if exit_on_err: exit(int(r))
def define_set(fn, name, value):
print("In " + fn + " set " + name + " to " + value)
new_content = ""
f = open(fn, "r")
for i in f.read().splitlines():
r = re.search(r'^ *# *define +' + name, i)
if r:
d = i.split("define")
i = d[0] + "define " + name + " " + value
new_content += i + '\n'
f.close()
f = open(fn, "w")
f.write(new_content)
f.close()
def clone_repos():
cmd("rm -fr " + workdir)
cmd("mkdir " + workdir)
os.chdir(workdir)
#For debuging just copy the repos
#cmd("cp -a ../repos/. .")
#return
cmd("git clone " + upstream("lvgl") + " lvgl; cd lvgl; git checkout master")
cmd("git clone " + upstream("lv_examples") + "; cd lv_examples; git checkout master")
cmd("git clone " + upstream("lv_drivers") + "; cd lv_drivers; git checkout master")
cmd("git clone --recurse-submodules " + upstream("docs") + "; cd docs; git checkout master")
cmd("git clone " + upstream("blog") + "; cd lv_drivers; git checkout blog")
def get_lvgl_version(br):
print("Get LVGL's version")
global ver_str, ver_major, ver_minor, ver_patch, release_br
os.chdir("./lvgl")
cmd("git checkout " + br)
f = open("./lvgl.h", "r")
lastNum = re.compile(r'(?:[^\d]*(\d+)[^\d]*)+')
for i in f.read().splitlines():
r = re.search(r'^#define LVGL_VERSION_MAJOR ', i)
if r:
m = lastNum.search(i)
if m: ver_major = m.group(1)
r = re.search(r'^#define LVGL_VERSION_MINOR ', i)
if r:
m = lastNum.search(i)
if m: ver_minor = m.group(1)
r = re.search(r'^#define LVGL_VERSION_PATCH ', i)
if r:
m = lastNum.search(i)
if m: ver_patch = m.group(1)
f.close()
cmd("git checkout master")
ver_str = "v" + str(ver_major) + "." + str(ver_minor) + "." + str(ver_patch)
print("New version:" + ver_str)
release_br = "release/v" + ver_major
os.chdir("../")
def update_version():
templ = fnmatch.filter(os.listdir('.'), '*templ*')
if templ[0]:
print("Updating version in " + templ[0])
cmd("sed -i -r 's/v[0-9]+\.[0-9]+\.[0-9]+/"+ ver_str +"/' " + templ[0])
if os.path.exists("library.json"):
print("Updating version in library.json")
cmd("sed -i -r 's/[0-9]+\.[0-9]+\.[0-9]+/"+ ver_str[1:] +"/' library.json")
if path.exists("library.properties"):
print("Updating version in library.properties")
cmd("sed -i -r 's/version=[0-9]+\.[0-9]+\.[0-9]+/"+ "version=" + ver_str[1:] + "/' library.properties")
def lvgl_prepare():
print("Prepare lvgl")
global ver_str, ver_major, ver_minor, ver_patch
os.chdir("./lvgl")
define_set("./lvgl.h", "LVGL_VERSION_INFO", '\"\"')
# Run some scripts
os.chdir("./scripts")
cmd("./code-format.sh")
cmd("./lv_conf_checker.py")
cmd("doxygen")
os.chdir("../")
update_version()
#update CHANGLELOG
new_content = ""
f = open("./CHANGELOG.md", "r")
global release_note
release_note = ""
note_state = 0
for i in f.read().splitlines():
if note_state == 0:
r = re.search(r'^## ' + ver_str, i)
if r:
i = i.replace("planned on ", "")
note_state+=1
elif note_state == 1:
r = re.search(r'^## ', i)
if r:
note_state+=1
else:
release_note += i + '\n'
new_content += i + '\n'
f.close()
f = open("./CHANGELOG.md", "w")
f.write(new_content)
f.close()
cmd('git commit -am "prepare to release ' + ver_str + '"')
os.chdir("../")
def lv_examples_prepare():
print("Prepare lv_examples")
global ver_str, ver_major, ver_minor, ver_patch
os.chdir("./lv_examples")
update_version()
cmd("sed -i -r 's/LV_VERSION_CHECK\([0-9]+, *[0-9]+, *[0-9]+\)/"+ "LV_VERSION_CHECK(" + ver_major + ", " + ver_minor + ", " + ver_patch + ")/' lv_examples.h")
cmd('git commit -am "prepare to release ' + ver_str + '"')
os.chdir("../")
def lv_drivers_prepare():
print("Prepare lv_drivers")
global ver_str, ver_major, ver_minor, ver_patch
os.chdir("./lv_drivers")
update_version()
cmd('git commit -am "prepare to release ' + ver_str + '"')
os.chdir("../")
def docs_prepare():
print("Prepare docs")
global ver_str, ver_major, ver_minor, ver_patch
os.chdir("./docs")
cmd("git co latest --")
cmd("rm -rf xml");
cmd("cp -r ../lvgl/docs/api_doc/xml .");
cmd("git add xml");
cmd("sed -i -r \"s/'v[0-9]+\.[0-9]+\.[0-9]+.*'/\'" + ver_str + "'/\" conf.py")
cmd('git commit -am "prepare to release ' + ver_str + '"')
os.chdir("../")
def blog_add_post():
global ver_str, release_note
os.chdir("./blog/_posts")
post = "---\nlayout: post\ntitle: " + ver_str + " is released\nauthor: \"kisvegabor\"\ncover: /assets/release_cover.png\n---\n\n"
post += release_note
today = date.today()
d = today.strftime("%Y-%m-%d")
f = open(d + "_release_" + ver_str + ".md", "w")
f.write(post)
f.close()
cmd("git add .")
cmd("git commit -am 'Add " + ver_str + " release post'")
os.chdir("../../")
def add_tags():
global ver_str
tag_cmd = " git tag -a " + ver_str + " -m 'Release " + ver_str + "' "
cmd("cd lvgl; " + tag_cmd)
cmd("cd lv_examples; " + tag_cmd)
cmd("cd lv_drivers; " + tag_cmd)
cmd("cd docs; " + tag_cmd)
def update_release_branches():
global release_br
merge_cmd = " git checkout " + release_br + "; git pull origin " + release_br + "; git merge master -X ours; git push origin " + release_br + "; git checkout master"
cmd("cd lvgl; " + merge_cmd)
cmd("cd lv_examples; " + merge_cmd)
cmd("cd lv_drivers; " + merge_cmd)
merge_cmd = " git checkout " + release_br + "; git pull origin " + release_br + "; git merge latest -X ours; git push origin " + release_br + "; git checkout latest"
cmd("cd docs; " + merge_cmd)
def publish_master():
pub_cmd = "git push origin master; git push origin " + ver_str
cmd("cd lvgl; " + pub_cmd)
cmd("cd lv_examples; " + pub_cmd)
cmd("cd lv_drivers; " + pub_cmd)
pub_cmd = "git push origin latest; git push origin " + ver_str
cmd("cd docs; " + pub_cmd)
cmd("cd docs; git checkout master; ./update.py " + release_br)
pub_cmd = "git push origin master"
cmd("cd blog; " + pub_cmd)
def merge_to_dev():
merge_cmd = "git checkout dev; git merge master -X ours; git checkout master"
cmd("cd lvgl; " + merge_cmd)
merge_cmd = "git checkout dev; git merge latest -X ours; git checkout master"
cmd("cd docs; " + merge_cmd)
def merge_from_dev():
merge_cmd = "git checkout master; git merge dev;"
cmd("cd lvgl; " + merge_cmd)
merge_cmd = "git checkout latest; git merge dev;"
cmd("cd docs; " + merge_cmd)
def lvgl_update_master_version():
global ver_major, ver_minor, ver_patch, ver_str
os.chdir("./lvgl")
cmd("git checkout master")
define_set("./lvgl.h", "LVGL_VERSION_MAJOR", ver_major)
define_set("./lvgl.h", "LVGL_VERSION_MINOR", ver_minor)
define_set("./lvgl.h", "LVGL_VERSION_PATCH", ver_patch)
define_set("./lvgl.h", "LVGL_VERSION_INFO", "dev")
templ = fnmatch.filter(os.listdir('.'), '*templ*')
if templ[0]:
print("Updating version in " + templ[0])
cmd("sed -i -r 's/v[0-9]+\.[0-9]+\.[0-9]+/"+ ver_str +"/' " + templ[0])
cmd("git commit -am 'Update version'")
os.chdir("../")
def docs_update_latest_version():
global ver_str
os.chdir("./docs")
cmd("git checkout latest --")
cmd("sed -i -r \"s/'v[0-9]+\.[0-9]+\.[0-9]+.*'/\'" + ver_str + "'/\" conf.py")
cmd("git commit -am 'Update version'")
cmd("git checkout master --")
os.chdir("../")
def lvgl_update_dev_version():
global ver_major, ver_minor, ver_patch, dev_ver_str
os.chdir("./lvgl")
cmd("git checkout dev")
define_set("./lvgl.h", "LVGL_VERSION_MAJOR", ver_major)
define_set("./lvgl.h", "LVGL_VERSION_MINOR", ver_minor)
define_set("./lvgl.h", "LVGL_VERSION_PATCH", ver_patch)
define_set("./lvgl.h", "LVGL_VERSION_INFO", "\"dev\"")
templ = fnmatch.filter(os.listdir('.'), '*templ*')
if templ[0]:
print("Updating version in " + templ[0])
cmd("sed -i -r 's/v[0-9]+\.[0-9]+\.[0-9]+/"+ dev_ver_str +"/' " + templ[0])
cmd("git commit -am 'Update dev version'")
cmd("git checkout master")
os.chdir("../")
def docs_update_dev_version():
global dev_ver_str
os.chdir("./docs")
cmd("git checkout dev --")
cmd("sed -i -r \"s/'v[0-9]+\.[0-9]+\.[0-9]+.*'/\'" + dev_ver_str + "'/\" conf.py")
cmd("git commit -am 'Update dev version'")
cmd("git checkout master --")
os.chdir("../")
def publish_dev():
pub_cmd = "git checkout dev; git push origin dev"
cmd("cd lvgl; " + pub_cmd)
pub_cmd = "git checkout dev; git push origin dev"
cmd("cd docs; " + pub_cmd)
cmd("cd docs; git checkout master; ./update.py latest dev")
def cleanup():
os.chdir("../")
cmd("rm -fr " + workdir)
if __name__ == '__main__':
if(len(sys.argv) != 2):
print("Argument error. Usage ./release.py bugfix | minor | major")
exit(1)
dev_prepare = sys.argv[1]
if not (dev_prepare in prepare_type):
print("Invalid argument. Usage ./release.py bugfix | minor | major")
exit(1)
clone_repos()
get_lvgl_version("master")
lvgl_prepare()
lv_examples_prepare()
lv_drivers_prepare()
docs_prepare()
blog_add_post()
add_tags()
update_release_branches()
publish_master()
if dev_prepare == 'bugfix':
ver_patch = str(int(ver_patch) + 1)
ver_str = "v" + ver_major + "." + ver_minor + "." + ver_patch + "-dev"
print("Prepare bugfix version " + ver_str)
lvgl_update_master_version()
docs_update_latest_version()
get_lvgl_version("dev")
dev_ver_str = "v" + ver_major + "." + ver_minor + "." + ver_patch + "-dev"
merge_to_dev()
lvgl_update_dev_version()
docs_update_dev_version()
publish_dev()
else:
get_lvgl_version("dev")
if dev_prepare == 'minor':
ver_minor = str(int(ver_minor) + 1)
ver_patch = "0"
else:
ver_major = str(int(ver_major) + 1)
ver_minor = "0"
ver_patch = "0"
dev_ver_str = "v" + ver_major + "." + ver_minor + "." + ver_patch + "-dev"
print("Prepare minor version " + ver_str)
merge_to_dev()
merge_from_dev()
lvgl_update_dev_version()
docs_update_dev_version()
publish_dev()
cleanup()
|
[
"[email protected]"
] | |
68d0e1293ce58896cd7ef5a2be74639b3686fcb9
|
7f50d37ba987fade8bce93fb10286292a9a0d7e1
|
/sentry.conf.py
|
f381b1ea1c92503f43337372fa43c0fff2a7968e
|
[] |
no_license
|
rochacon/docker-sentry
|
db4ac5be75392b6d7fdabdf211532b3b5b9eca34
|
32d41ab39a2dbc222e5ed6080ca943b2225cc07a
|
refs/heads/master
| 2021-01-18T14:06:01.265851 | 2014-10-27T19:02:54 | 2014-10-27T19:02:54 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,043 |
py
|
# /etc/sentry.conf.py
# edit this to your liking
import os
import dj_database_url
DATABASES = {'default': dj_database_url.config()}
# No trailing slash!
SENTRY_URL_PREFIX = 'http://127.0.0.1.xip.io' # FIXME modify this to your domain
# SENTRY_KEY is a unique randomly generated secret key for your server, and it
# acts as a signing token
SENTRY_KEY = '0123456789abcde' # FIXME modify this to an unique key
SENTRY_WEB_HOST = '0.0.0.0'
SENTRY_WEB_PORT = 9000
SENTRY_WEB_OPTIONS = {
'workers': 3, # the number of gunicorn workers
'secure_scheme_headers': {'X-FORWARDED-PROTO': 'https'}, # detect HTTPS mode from X-Forwarded-Proto header
}
_redis_endpoint = os.environ.get('REDIS_ENDPOINT', '127.0.0.1:6379')
SENTRY_REDIS_OPTIONS = {
'hosts': {
0: {
'host': _redis_endpoint.split(':')[0],
'port': _redis_endpoint.split(':')[1],
}
}
}
# TODO
#EMAIL_HOST = 'localhost'
#EMAIL_HOST_PASSWORD = ''
#EMAIL_HOST_USER = ''
#EMAIL_PORT = 25
#EMAIL_USE_TLS = False
ALLOWED_HOSTS = ['*']
|
[
"[email protected]"
] | |
3652511f4a3c2e9b77748a3cf8132b152949bf44
|
ffe4c155e228f1d3bcb3ff35265bb727c684ec1a
|
/Codes/Quiz/number_of_factors.py
|
68ce727aa40589c018b92480a89b9de9e4e47ed7
|
[] |
no_license
|
yuuee-www/Python-Learning
|
848407aba39970e7e0058a4adb09dd35818c1d54
|
2964c9144844aed576ea527acedf1a465e9a8664
|
refs/heads/master
| 2023-03-12T00:55:06.034328 | 2021-02-28T13:43:14 | 2021-02-28T13:43:14 | 339,406,816 | 0 | 0 | null | 2021-02-28T11:27:40 | 2021-02-16T13:26:46 |
Jupyter Notebook
|
UTF-8
|
Python
| false | false | 269 |
py
|
def numberOfFactors(num):
ans = 1
x = 2
while x * x <= num:
cnt = 1
while num % x == 0:
cnt += 1
num /= x
ans = cnt
x += 1
return ans * (1 + (num > 1))
n = int(input())
print(numberOfFactors(n))
|
[
"[email protected]"
] | |
e61843b913feb2b63ff73da2ce6702eab8d0d073
|
618408b7e89798b8a745ae5aaf6a098d17af5468
|
/luo_hao_reid/transforms.py
|
7ee514ed3d24e9d5a768d03e943565419472a3ee
|
[
"MIT"
] |
permissive
|
Mr-Da-Yang/Python_learning
|
3fc832325aa9aff4e11a15cad5b3636918dd61bc
|
23586139fc44fe76c7dbcd83929a1804485be5f4
|
refs/heads/master
| 2023-01-08T21:35:42.324510 | 2020-10-26T13:01:02 | 2020-10-26T13:01:02 | 281,889,544 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,316 |
py
|
'''OK
transformๅฎ็ฐๆฐๆฎๅขๅนฟ๏ผpytorchไธญ่ชๅธฆ็้ๆบ็ฟป่ฝฌ๏ผๅชๅๅฏไปฅ่งฃๅณ90%็้ฎ้ข๏ผไธ้ขๆฏ่ชๅทฑๅฆไฝๅไธไธชtransform
'''
from __future__ import absolute_import
from torchvision.transforms import *
from PIL import Image
import random
import numpy as np
import matplotlib.pyplot as plt
class Random2DTranslation(object):#้ๆบๆพๅคงๅนถcrop
"""
With a probability, first increase image size to (1 + 1/8), and then perform random crop.
Args:
height (int): target height.
width (int): target width.
p (float): probability of performing this transformation. Default: 0.5.
"""
def __init__(self, height,width, p=0.5, interpolation=Image.BILINEAR):
self.height = height
self.width = width
self.p = p
self.interpolation = interpolation#ๆพๅคงๆถ็จ็ๆๅผ
def __call__(self, img):
"""
Args:
img (PIL Image): Image to be cropped.
Returns:
PIL Image: Cropped image.
"""
if random.random() < self.p:#randomไบง็ไธไธช0-1ๅๆญฅ็้ๆบๆฐ๏ผ่ฅๆฐๅญๅฐไบP๏ผๅฐฑไธ่ฟ่กๆฐๆฎๅขๅนฟ
return img.resize((self.width, self.height), self.interpolation)
new_width, new_height = int(round(self.width * 1.125)), int(round(self.height * 1.125))#ๆพๅคง1/8/roundๅไธ้๏ผๅ ไธintๆด็จณ
resized_img = img.resize((new_width, new_height), self.interpolation)
x_maxrange = new_width - self.width
y_maxrange = new_height - self.height#crop็ๆๅคง่ๅด
x1 = int(round(random.uniform(0, x_maxrange)))#crop็่ตทๅง็น
y1 = int(round(random.uniform(0, y_maxrange)))
croped_img = resized_img.crop((x1, y1, x1 + self.width, y1 + self.height))
return croped_img
# if __name__ == '__main__':
# import torchvision.transforms as transform
# img=Image.open('E:\LINYANG\python_project\luohao_person_reid\dataset\Market-1501-v15.09.15\query\\0004_c1s6_016996_00.jpg')
#
# transform=transform.Compose([
# Random2DTranslation(128, 256, 0.5),
# transforms.RandomHorizontalFlip(p=0.8),
# #transform.ToTensor()
# ])
# img_t=transform(img)
# plt.subplot(121)
# plt.imshow(img)
# plt.subplot(122)
# plt.imshow(img_t)
# plt.show()
|
[
"[email protected]"
] | |
7e1adfe0c0fd5a509cb006c917e00fe88395a01b
|
00cb09b91cfccb285be8acd86da9612defd003d7
|
/python/infrastructure/lib/command_interface.py
|
3d080c16bb83e6e59f78ff89f8586dc42afd6ed7
|
[] |
no_license
|
jasonraimondi/flask-command-query
|
8838fa61211f0e568e02e5b4ce37a6bff04d850d
|
678b7d3f48a5c40b06c122302727392f982482e3
|
refs/heads/master
| 2021-05-07T08:31:00.273681 | 2017-11-15T03:15:51 | 2017-11-15T03:15:51 | 109,299,679 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 91 |
py
|
class CommandInterface(object):
def execute(self):
raise NotImplementedError()
|
[
"[email protected]"
] | |
cf27aee94cb1f21c671752c877f0bda9db9d2401
|
025765a4289ad9229225f6627a5a1eaa56fe7726
|
/Module/Test8.py
|
72dd475a2d82df1ea67f60054c03e3f2e584cca1
|
[] |
no_license
|
dongyeon94/Kiwoom_Open_API
|
dc12b85623994314f4d045a5dda6d5bc7c3e5ef2
|
df3bca5f6f8ce92a34947f28b21e277693560e05
|
refs/heads/master
| 2022-09-07T02:55:03.235742 | 2020-05-23T15:23:28 | 2020-05-23T15:23:28 | 243,203,485 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 33,087 |
py
|
import sys
from PyQt5.QtWidgets import *
from PyQt5.QAxContainer import *
from PyQt5.QtCore import pyqtSlot, QTimer, QObject, QThread, QTime
import datetime
import time
import threading
global current_data
current_data = 0
CODE = "CLJ20" # crude oil
COM_DATE = datetime.datetime.now().strftime('%Y%m%d%H%M%S')
sale_time = None
bong_start = None
bong_end = None
# Head for Doubly LinkedList(๋งค์ํ ์ ๋ฌผ ๋ฆฌ์คํธ)
head = None
# ์ง์
ํ์
type_buy = 2 # ๋งค์ ์ง์
type_sell = 1 # ๋งค๋ ์ง์
#์ง์
ํ๋๊ทธ
transaction_flag = False
# ์ง์
ํ๋จ ํ๋ผ๋ฏธํฐ
bongP = 0
bongPlus = None
# ๋ง์ง๋ง ๊ฐ๊ฒฉ. ์ฒซ ๊ฐ๊ฒฉ์ผ๋ก ์๋์ผ๋ก ๋ฐ๋.
lastTickPrice = None
debug_file_started = False
# Hardcoded
numBought = 1
total = 0
class MyWindow(QMainWindow):
def __init__(self):
# ์ด๊ธฐ setup ๋ชจ๋ ๋ก๋ฉ ๋ฑ
super().__init__()
self.setWindowTitle("PyStock")
self.setGeometry(300, 150, 400, 800)
self.kiwoom = QAxWidget("KFOpenAPI.KFOpenAPICtrl.1")
# ์
๋ ฅ ๊ธฐ๋ฅ ์ ๋ฆฌ
self.account = QLineEdit(self)
self.account.move(200, 20)
self.account.resize(100, 30)
self.account.setPlaceholderText('๊ณ์ข๋ฒํธ๋ฅผ ์
๋ ฅํ์ธ์')
self.password = QLineEdit(self)
self.password.move(200, 70)
self.password.resize(100, 30)
self.password.setPlaceholderText('๋น๋ฐ๋ฒํธ๋ฅผ ์
๋ ฅํ์ธ์')
self.stoct_code = QLineEdit(self)
self.stoct_code.move(200, 120)
self.stoct_code.resize(100, 30)
self.stoct_code.setPlaceholderText('์ข
๋ชฉ ์ฝ๋๋ฅผ ์
๋ ฅํ์ธ์')
self.stoct_num = QLineEdit(self)
self.stoct_num.move(200, 170)
self.stoct_num.resize(100, 30)
self.stoct_num.setPlaceholderText('์ฃผ๋ฌธ๋')
# option - version -
self.ChekGroup1 = QCheckBox('option1', self)
self.ChekGroup1.move(200, 220)
self.ChekGroup1.clicked.connect(self.checkbox)
self.ChekGroup2 = QCheckBox('option2', self)
self.ChekGroup2.move(200, 245)
self.ChekGroup2.clicked.connect(self.checkbox)
self.starttime = QTimeEdit(self)
self.starttime.setDisplayFormat("hh:mm:ss")
self.starttime.move(200, 280)
self.endtime = QTimeEdit(self)
self.endtime.setDisplayFormat("hh:mm:ss")
self.endtime.move(200, 320)
self.endtime.setTime(QTime(23, 59,59))
# ๋๋ฒ๊น
๋ชจ๋
self.debug_check = QCheckBox('๋๋ฒ๊น
๋ชจ๋', self)
self.debug_check.move(200, 600)
self.debug_check.clicked.connect(self.debug_check_fun)
self.debug_file = QPushButton('๋๋ฒ๊น
ํ์ผ', self)
self.debug_file.move(200, 650)
self.debug_file.clicked.connect(self.debug_file_fun)
self.debug_file_obj = None
self.option_warning = QMessageBox(self)
self.option_warning.resize(300,500)
# ์์
module_start = QPushButton('๊ฑฐ๋ ์์', self)
module_start.move(200, 450)
module_start.clicked.connect(self.data_loading)
# ๋ก๊ทธ์ธ
login_btn = QPushButton("๋ก๊ทธ์ธ", self)
login_btn.move(20, 20)
login_btn.clicked.connect(self.login_clicked)
info_btn = QPushButton('๋ก๊ทธ์ธ ํ์ธ', self)
info_btn.move(20, 70)
info_btn.clicked.connect(self.login_info)
search_btm = QPushButton('์ฃผ์ ์กฐํ', self)
search_btm.move(20, 170)
search_btm.clicked.connect(self.subject_search)
buy_btn = QPushButton('๋งค์๋ฒํผ', self)
buy_btn.move(20, 270)
buy_btn.clicked.connect(self.stock_buy_order)
sale_btn = QPushButton('๋งค๋ ๋ฒํผ', self)
sale_btn.move(20, 320)
sale_btn.clicked.connect(self.stock_sale_order)
# ๋ฐ์ดํฐ ์์ ์ด๋ฒคํธ
self.kiwoom.OnReceiveTrData.connect(self.receive_trdata)
self.kiwoom.OnReceiveChejanData.connect(self.get_transaction_data)
# ๋ก๊ทธํ์ผ
self.log_file = None
test_ = QPushButton(' ํ
์คํธ', self)
test_.move(20, 600)
test_.clicked.connect(self.get_transaction_data)
self.stoct_code.setText('CLK20')
self.stoct_num.setText('1')
def test1(self):
print('test22')
# data = self.test()
# data = self.kiwoom.OnReceiveChejanData.connect(self.test)
# print(data)
def get_transaction_data(self, sGubun, nItemCnt):
global transaction_flag
# ๋งค์ 2 ๋งค๋ 1
if sGubun == '1' and transaction_flag:
print('test์ค')
price = float(self.kiwoom.GetChejanData(910))
type_buy = int(self.kiwoom.GetChejanData(907))
sale_time = int(self.kiwoom.GetChejanData(908))
ll_append(Transaction(type_buy, price, numBought))
if type_buy == 2:
pri = round(price + 0.03, 2)
self.log_file.write(str(sale_time) + ',' + str(True) + ',_,' + str(0) + + "," + str(price) + '์ ๋งค์ ์ง์
,' + str(pri) + '์ ๋งค๋ ์์ฝ\n')
self.stock_sale_order(pri)
else:
pri = round(price - 0.03, 2)
self.log_file.write(str(sale_time) + ',' + str(True) + ',_,' + str(0) + "," + str(price) + '์ ๋งค๋ ์ง์
,' + str(pri) + '์ ๋งค์ ์์ฝ\n')
self.stock_buy_order(pri)
transaction_flag = False
def get_transaction_data_debug(self, price, type_buy, sale_time, bongP):
global transaction_flag
print('test์ค')
ll_append(Transaction(type_buy, price, numBought))
transaction_flag = False
if type_buy == type_buy:
pri = round(price + 0.03, 2)
print(str(sale_time) + ',' + str(True) + ',' + str(price) + ',' + str(bongP) + "," + str(price) + '์ ๋งค์ ์ง์
,' + str(pri) + '์ ๋งค๋ ์์ฝ')
else:
pri = round(price - 0.03, 2)
print(str(sale_time) + ',' + str(True) + ',' + str(price) + ',' + str(bongP) + "," + str(price) + '์ ๋งค๋ ์ง์
,' + str(pri) + '์ ๋งค์ ์์ฝ')
def debug_check_fun(self):
if self.debug_check.isChecked():
return True
else:
return False
def debug_file_fun(self):
fname = QFileDialog.getOpenFileName(self, 'Open file', "",
"All Files(*);; Python Files(*.py)", '/home')
if not fname[0]:
QMessageBox.about(self, "Warning", "ํ์ผ์ ์ ํํ์ง ์์์ต๋๋ค.")
else:
self.debug_file_name = fname[0]
def run(self, price, bongPlus, tickFlag, bongFlag, sale_time, option):
global head, type_sell, type_buy, bongP, lastTickPrice, total, transaction_flag
if self.debug_check_fun() is False and self.log_file is None:
self.log_file = open('log' + COM_DATE + '_๊ฑฐ๋.csv', mode='wt', encoding='utf-8')
self.log_file.write('์ฒด๊ฒฐ์๊ฐ,BongFlag,๊ฐ๊ฒฉ,๋ด์นด์ดํธ,๊ฑฐ๋๋ด์ญ\n')
self.log_file.flush()
if price is None:
return
if lastTickPrice == None:
lastTickPrice = price
if self.debug_check_fun() is False:
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + "," + str(bongP) + '\n')
self.log_file.flush()
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + "," + str(bongP))
return
curr = head
while curr is not None:
tickSold = False
if tickFlag:
if price > lastTickPrice:
curr.tickP += 1
elif price < lastTickPrice:
curr.tickP -= 1
if curr.type == type_buy:
# Option2: ๋งค์๊ฑฐ๋๊ฐ 3ํฑ์ด์ ์ฌ๋์๋ ๋งค๋
if curr.tickP == 3:
if self.debug_check_fun() is False:
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt2_์ต์ $' + str(curr.price) + '์ ๋งค์ ํ $' + str(price) + '์ ๋งค๋\n')
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt2_์ต์ $' + str(curr.price) + '์ ๋งค์ ํ $' + str(price) + '์ ๋งค๋')
# ์ต์ ์ ์์ฝ์์ ์์์ ํ๋ฆผ
remove_elem(curr)
tickSold = True
total += (price - curr.price) * numBought
# Option4: ๋งค์๊ฑฐ๋๊ฐ 6ํฑ์ด์ ํ๋ฝํ์๋ ๋งค๋
elif curr.tickP == -6:
if self.debug_check_fun() is False:
self.stock_buy_wait()
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt4_์์ $' + str(curr.price) + '์ ๋งค์ ํ $' + str(price) + '์ ๋งค๋\n')
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt4_์์ $' + str(curr.price) + '์ ๋งค์ ํ $' + str(price) + '์ ๋งค๋')
remove_elem(curr)
tickSold = True
total += (price - curr.price) * numBought
else:
# Option2_reverse: ๋งค๋๊ฑฐ๋๊ฐ 3ํฑ์ด์ ๋ด๋ ธ์ ๋ ๋งค๋
if curr.tickP == -3:
if self.debug_check_fun() is False:
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt2r_์ต์ $' + str(curr.price) + '์ ๋งค๋ ํ $' + str(price) + '์ ๋งค์\n')
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt2r_์ต์ $' + str(curr.price) + '์ ๋งค๋ ํ $' + str(price) + '์ ๋งค์')
remove_elem(curr)
tickSold = True
total += (price - curr.price) * numBought
# Option4_reverse: ๋งค๋๊ฑฐ๋๊ฐ 6ํฑ์ด์ ์์นํ์๋ ๋งค๋
elif curr.tickP == 6:
if self.debug_check_fun() is False:
self.stock_sale_wait()
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt4r_์์ $' + str(curr.price) + '์ ๋งค๋ ํ $' + str(price) + '์ ๋งค์\n')
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt4r_์์ $' + str(curr.price) + '์ ๋งค๋ ํ $' + str(price) + '์ ๋งค์')
remove_elem(curr)
tickSold = True
total += (price - curr.price) * numBought
if bongFlag and not tickSold:
curr.bongCount += 1
if bongPlus > 0:
curr.bongP += 1
elif bongPlus < 0:
curr.bongP -= 1
if curr.type == type_buy:
if curr.bongP == -1 and curr.bongCount == 2:
# Option3: ๋งค์์ง์
์งํ ๋ง์ด๋์ค ๋ด์ผ๋ ๋ฐ๋ก ํ (์ง์
ํ ๋ด์ ๋ฌด์)
if self.debug_check_fun() is False:
self.stock_buy_wait()
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt3_์์ $' + str(curr.price) + '์ ๋งค์ ํ $' + str(price) + '์ ๋งค๋\n')
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt3_์์ $' + str(curr.price) + '์ ๋งค์ ํ $' + str(price) + '์ ๋งค๋')
remove_elem(curr)
total += (price - curr.price) * numBought
else:
if curr.bongP == 1 and curr.bongCount == 2:
# Option3_reverse: ๋งค๋์ง์
์งํ ํ๋ฌ์ค ๋ด์ผ๋ ๋ฐ๋ก ํ (์ง์
ํ ๋ด์ ๋ฌด์)
if self.debug_check_fun() is False:
self.stock_sale_wait()
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt3r_์์ $' + str(curr.price) + '์ ๋งค๋ ํ $' + str(price) + '์ ๋งค์\n')
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
bongP) + ',' + 'opt3r_์์ $' + str(curr.price) + '์ ๋งค๋ ํ $' + str(price) + '์ ๋งค์')
remove_elem(curr)
total += (price - curr.price) * numBought
curr = curr.next
if bongFlag:
if bongP is None:
if bongPlus > 0:
bongP = 1
elif bongPlus < 0:
bongP = -1
else:
bongP = 0
else:
if option[0] == '1' and bongP <= -3:
if bongPlus > 0:
# ๋งค์์ง์
: bong 3๋ฒ ๋ด๋ ค๊ฐ๋ค๊ฐ ํ๋ฒ ์ค๋ฅด๋ฉด '์ผ'
transaction_flag = True
# pri = round(price + 0.03, 2)
if self.debug_check_fun() is False:
print('๋งค์ ์ง์
', price)
self.stock_buy_order()
# time.sleep(1)
# self.stock_sale_order(pri)
# self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
# bongP + '\n'))
else:
# print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(bongP))
self.get_transaction_data_debug(price, 2, sale_time, bongP)
# ll_append(Transaction(type_buy, price, numBought))
elif option[1] == '1' and bongP >= 3:
if bongPlus < 0:
transaction_flag = True
# ๋งค๋์ง์
: bong 3๋ฒ ์ฌ๋๋ค๊ฐ ํ๋ฒ ๋ด๋ฆฌ๋ฉด ์ผ
# pri = round(price - 0.03, 2)
if self.debug_check_fun() is False:
print('๋งค๋ ์ง์
', price)
self.stock_sale_order()
# time.sleep(1)
# self.stock_buy_order(pri)
# self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(
# bongP + '\n'))
else:
# print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(bongP))
self.get_transaction_data_debug(price, 1, sale_time, bongP)
# ll_append(Transaction(type_sell, price, numBought))
if bongPlus > 0:
if bongP > 0:
bongP += 1
else:
bongP = 1
elif bongPlus < 0:
if bongP < 0:
bongP -= 1
else:
bongP = -1
lastTickPrice = price
if self.debug_check_fun() is False:
self.log_file.write(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(bongP) + '\n')
self.log_file.flush()
else:
print(str(sale_time) + ',' + str(bongFlag) + ',' + str(price) + ',' + str(bongP))
# ------ ์ฃผ์ ์ฃผ๋ฌธ start -------
# ์ฃผ์ ๋งค์
def stock_buy_order(self, price=0):
print('๋งค์์ค', price)
getPrice = 0
# ๊ตฌ๋ถ , ํ๋ฉด๋ฒํธ , ๊ณ์ข , ์ฃผ๋ฌธ์ ํ ,์ข
๋ชฉ์ฝ๋, ๊ฐ์,๊ฐ๊ฒฉ, stop๊ฐ๊ฒฉ, ๊ฑฐ๋๊ตฌ๋ถ, ์ฃผ๋ฌธ๋ฒํธ
if price == 0:
data = self.kiwoom.SendOrder('์ฃผ์๋งค์', "1211", self.account.text(), 2, self.stoct_code.text(),
int(self.stoct_num.text()), str(price), "", "1", "")
else:
data = self.kiwoom.SendOrder('์ฃผ์๋งค์', "1211", self.account.text(), 2, self.stoct_code.text(),
int(self.stoct_num.text()), str(price), "", "2", "")
return getPrice
# ์ฃผ์ ๋งค๋
def stock_sale_order(self, price=0):
print('๋งค๋์ค', price)
# ๊ตฌ๋ถ , ํ๋ฉด๋ฒํธ , ๊ณ์ข , ์ฃผ๋ฌธ์ ํ ,์ข
๋ชฉ์ฝ๋, ๊ฐ์,๊ฐ๊ฒฉ, stop๊ฐ๊ฒฉ, ๊ฑฐ๋๊ตฌ๋ถ, ์ฃผ๋ฌธ๋ฒํธ
if price == 0:
data = self.kiwoom.SendOrder('์ฃผ์๋งค๋', "1212", self.account.text(), 1, self.stoct_code.text(),
int(self.stoct_num.text()), str(price), "", "1", "")
else:
data = self.kiwoom.SendOrder('์ฃผ์๋งค๋', "1212", self.account.text(), 1, self.stoct_code.text(),
int(self.stoct_num.text()), str(price), "", "2", "")
# ์ฃผ์ ๋งค๋ ์ ์ ์ทจ์
def stock_sale_modify(self, code):
# ๊ตฌ๋ถ , ํ๋ฉด๋ฒํธ , ๊ณ์ข , ์ฃผ๋ฌธ์ ํ ,์ข
๋ชฉ์ฝ๋, ๊ฐ์,๊ฐ๊ฒฉ, stop๊ฐ๊ฒฉ, ๊ฑฐ๋๊ตฌ๋ถ, ์ฃผ๋ฌธ๋ฒํธ
data = self.kiwoom.SendOrder('์ฃผ์์ ์ ', "1213", self.account.text(), 3, self.stoct_code.text(),
int(self.stoct_num.text()), "0", "0", "2", str(code[6:]))
time.sleep(1)
print(data)
self.stock_sale_order()
# ์ฃผ์ ๋งค์ ์ ์ ์ทจ์
def stock_buy_modify(self, code):
# ๊ตฌ๋ถ , ํ๋ฉด๋ฒํธ , ๊ณ์ข , ์ฃผ๋ฌธ์ ํ ,์ข
๋ชฉ์ฝ๋, ๊ฐ์,๊ฐ๊ฒฉ, stop๊ฐ๊ฒฉ, ๊ฑฐ๋๊ตฌ๋ถ, ์ฃผ๋ฌธ๋ฒํธ
data = self.kiwoom.SendOrder('์ฃผ์์ ์ ', "1213", self.account.text(), 4, self.stoct_code.text(),
int(self.stoct_num.text()), "0", "0", "2", str(code[6:]))
time.sleep(1)
print(data)
self.stock_buy_order()
# ------ ์ฃผ์ ์ฃผ๋ฌธ end -------
# ------ ๋ฐ์ดํฐ ์์ ๊ธฐ๋ฅ start -------
def data_loading(self):
global debug_file_started, total
print('๋ฐ์ดํฐ ๋ก๋ฉ')
if self.checkbox()=='':
# self.option_warning.showMessage('์ต์
์ ์ ํํด์ฃผ์ธ์')
self.option_warning.about(self,'ํ๋ก๊ทธ๋จ ๊ฒฝ๊ณ ','์์ ์ ์ต์
ฅ์ ์ ํํด์ฃผ์ธ์')
# show('์ต์
์ ์ ํํด์ฃผ์ธ์')
return
# ์ค์๊ฐ ์ฒด๊ฒฐ ๋ฐ์ดํฐ ๋ก๋ฉ
if self.debug_check_fun() is False:
self.kiwoom.SetInputValue('์ข
๋ชฉ์ฝ๋', self.stoct_code.text())
self.kiwoom.SetInputValue('์๊ฐ๋จ์', "1")
res = self.kiwoom.CommRqData('ํด์ธ์ ๋ฌผ์์ธ', 'opt10011', "0", 'opt10011')
print(res)
if res == 0:
print('์์ฒญ์ฑ๊ณต')
else:
print('์์ฒญ ์คํจ')
self.kiwoom.OnReceiveRealData.connect(self.realData)
else:
debugFile = open(self.debug_file_name, mode='rt',encoding="utf-8")
while True:
try:
if debug_file_started is False:
# ์ฒซ์ค ๋ ๋ ค๋ฒ๋ฆฌ๊ธฐ
debugFile.readline()
time.sleep(0.2)
debug_file_started = True
dataline = debugFile.readline()
time.sleep(0.2)
if dataline == '':
print("๋๋ฒ๊ทธ ํ์ผ ์ฝ๊ธฐ ๋")
print("Total", total)
debugFile.close()
break
self.realData('', "ํด์ธ์ ๋ฌผ์์ธ", dataline.strip().split(","))
except EOFError:
print("๋๋ฒ๊ทธ ํ์ผ ์ฝ๊ธฐ ๋")
print("Total", total)
debugFile.close()
# ์ค์๊ฐ ์ฒด๊ฒฐ ์ ๋ณด ์์ ๋ฐ์ดํฐ
def realData(self, sJongmokCode, sRealType, sRealData):
global sale_time, bong_start, bong_end, bongPlus
if sRealType == "ํด์ธ์ ๋ฌผ์์ธ":
bongFlag = False
if self.debug_check_fun():
tmp_time = int(sRealData[0])
if sRealData[2] == '_':
return
current_data = float(sRealData[2])
else:
current_data = self.kiwoom.GetCommRealData(sRealType, 10)
# market_data = self.kiwoom.GetCommRealData(sJongmokCode, 16)
tmp_time = int(self.kiwoom.GetCommRealData(sRealType, 20))
if sale_time is None:
if tmp_time / 100 == tmp_time // 100:
bong_start = abs(float(str(current_data)))
print("ํ๋ก๊ทธ๋จ ์์ ์๊ฐ: ", tmp_time // 100)
else:
startTime = str(tmp_time // 100 + 1)
print("ํ๋ก๊ทธ๋จ ์์ ์๊ฐ: ", startTime)
sale_time = tmp_time
if tmp_time // 100 > sale_time // 100 or tmp_time // 100 == 0:
if bong_start is None:
bong_start = abs(float(str(current_data)))
bongPlus = 0
else:
bongPlus = bong_end - bong_start
if round(abs(bongPlus), 2) <= 0.01:
bongPlus = 0
#0.01์ธ๊ฒฝ์ฐ ๋ฌด์
bong_start = abs(float(str(current_data)))
else:
bong_start = abs(float(str(current_data)))
bongFlag = True
else:
bong_end = abs(float(str(current_data)))
if bongPlus is not None:
sale_time = tmp_time
if self.debug_check_fun() is False:
if int(self.start_time()) <= sale_time <= int(self.end_time()):
self.run(abs(float(str(current_data))), bongPlus, True, bongFlag, str(sale_time), self.checkbox())
else:
self.disconnect()
else:
self.run(abs(float(str(current_data))), bongPlus, True, bongFlag, str(sale_time), self.checkbox())
# ์ค์๊ฐ ๋ฐ์ดํฐ ( ์ข
๋ชฉ์ ๋ํด ์ค์๊ฐ ์ ๋ณด ์์ฒญ์ ์คํํจ)
def real_data(self):
if self.debug_check_fun() is False:
self.kiwoom.SetInputValue('์ข
๋ชฉ์ฝ๋', self.stoct_code.text())
self.kiwoom.SetInputValue('์๊ฐ๋จ์', "1")
res = self.kiwoom.CommRqData('ํด์ธ์ ๋ฌผ์์ธ', 'opt10011', "0", 'opt10011')
self.kiwoom.OnReceiveRealData.connect(self.realData)
# ์ค์๊ฐ ๋ฐ์ดํฐ ๋์ค์ปค๋ฅ
def real_data_disconnect(self):
if self.debug_check_fun() is False:
self.kiwoom.DisconnectRealData('opt10011')
# ๋งค๋ ๋ฏธ์ฒด๊ฒฐ ์ทจ์ ์กฐํ
def stock_buy_wait(self):
print('๋ฏธ์ฒด๊ฒฐ ์กฐํ์ค')
self.kiwoom.SetInputValue('๊ณ์ข๋ฒํธ', self.account.text())
self.kiwoom.SetInputValue("๋น๋ฐ๋ฒํธ", self.password.text())
self.kiwoom.SetInputValue('๋น๋ฐ๋ฒํธ์
๋ ฅ๋งค์ฒด', "00") # ๋ฌด์กฐ๊ฑด 00
self.kiwoom.SetInputValue('์ข
๋ชฉ์ฝ๋', self.stoct_code.text())
self.kiwoom.SetInputValue('ํตํ์ฝ๋', "USD")
self.kiwoom.SetInputValue('๋งค๋์๊ตฌ๋ถ', "1")
res = self.kiwoom.CommRqData("๋งค๋๋ฏธ์ฒด๊ฒฐ", "opw30001", "", "opw30001")
time.sleep(1)
# ๋งค์ ๋ฏธ์ฒด๊ฒฐ ์กฐํ
def stock_sale_wait(self):
print('๋ฏธ์ฒด๊ฒฐ ์กฐํ์ค')
self.kiwoom.SetInputValue('๊ณ์ข๋ฒํธ', self.account.text())
self.kiwoom.SetInputValue("๋น๋ฐ๋ฒํธ", self.password.text())
self.kiwoom.SetInputValue('๋น๋ฐ๋ฒํธ์
๋ ฅ๋งค์ฒด', "00") # ๋ฌด์กฐ๊ฑด 00
self.kiwoom.SetInputValue('์ข
๋ชฉ์ฝ๋', self.stoct_code.text())
self.kiwoom.SetInputValue('ํตํ์ฝ๋', "USD")
self.kiwoom.SetInputValue('๋งค๋์๊ตฌ๋ถ', "2")
res = self.kiwoom.CommRqData("๋งค์๋ฏธ์ฒด๊ฒฐ", "opw30001", "", "opw30001")
time.sleep(1)
# ๋ฐ์ดํฐ ์์ ์ค
def receive_trdata(self, sScrNo, sRQName, sTrCode, sRecordName, sPreNext):
# print(sRQName)
if sRQName == "๋งค๋๋ฏธ์ฒด๊ฒฐ":
# dataCount = self.kiwoom.GetRepeatCnt(sTrCode, sRQName)
# dataCount2 = self.kiwoom.GetChejanData(9203)
try:
num = self.kiwoom.GetCommData(sTrCode, sRQName, 0, "์ฃผ๋ฌธ๋ฒํธ")
# typ = self.kiwoom.GetCommData(sTrCode, sRQName, 0, "๊ตฌ๋ธ")
print(num)
if int(num) > 0:
self.stock_sale_modify(num)
except:
print('๋งค๋ ๋ฏธ์ฒด๊ฒฐ ๋ด์ญ ์์')
if sRQName == "๋งค์๋ฏธ์ฒด๊ฒฐ":
# dataCount = self.kiwoom.GetRepeatCnt(sTrCode, sRQName)
# dataCount2 = self.kiwoom.GetChejanData(9203)
try:
num = self.kiwoom.GetCommData(sTrCode, sRQName, 0, "์ฃผ๋ฌธ๋ฒํธ")
# typ = self.kiwoom.GetCommData(sTrCode, sRQName, 0, "๊ตฌ๋ธ")
print(num)
if int(num) > 0:
self.stock_buy_modify(num)
except:
print('๋งค์ ๋ฏธ์ฒด๊ฒฐ ๋ด์ญ ์์')
if sRQName == "์ฃผ๊ฐ์กฐํ":
print('์ฃผ๊ฐ์กฐํ')
dataCount = self.kiwoom.GetRepeatCnt(sTrCode, sRQName)
print('์ด ๋ฐ์ดํฐ ์ : ', dataCount)
code = self.kiwoom.GetCommData(sTrCode, sRQName, 0, "์ข
๋ชฉ์ฝ๋")
print("์ข
๋ชฉ์ฝ๋: " + code)
print("------------------------------")
# ๊ฐ์ฅ์ต๊ทผ์์ 10 ๊ฑฐ๋์ผ ์ ๊น์ง ๋ฐ์ดํฐ ์กฐํ
for dataIdx in range(10):
inputVal = ["์ฒด๊ฒฐ์๊ฐn", "ํ์ฌ๊ฐn", "์๊ฐ", "๊ณ ๊ฐ", "์ ๊ฐ", "๊ฑฐ๋๋"]
outputVal = ['', '', '', '', '', '']
for idx, j in enumerate(inputVal):
outputVal[idx] = self.kiwoom.GetCommData(sTrCode, sRQName, dataIdx, j)
for idx, output in enumerate(outputVal):
print(inputVal[idx] + ' : ' + output)
print('----------------')
if sRQName == "๋ถ๋ด์ ๋ณด":
# print('๋ถ๋ด ๋ฐ์ดํฐ')
dataCount = self.kiwoom.GetRepeatCnt(sTrCode, sRQName)
# print('์ด ๋ฐ์ดํฐ ์ : ', dataCount)
code = self.kiwoom.GetCommData(sTrCode, sRQName, 0, "์ข
๋ชฉ์ฝ๋")
# print("์ข
๋ชฉ์ฝ๋: " + code)
# print("------------------------------")
# ๊ฐ์ฅ์ต๊ทผ์์ 10 ๊ฑฐ๋์ผ ์ ๊น์ง ๋ฐ์ดํฐ ์กฐํ
for dataIdx in range(1):
inputVal = ["์ฒด๊ฒฐ์๊ฐn", "ํ์ฌ๊ฐn", "๋ฑ๋ฝ์จn", "์๊ฐn", "๊ณ ๊ฐn", "์ ๊ฐn"]
outputVal = ['', '', '', '', '', '']
for idx, j in enumerate(inputVal):
outputVal[idx] = self.kiwoom.GetCommData(sTrCode, sRQName, dataIdx, j)
# print(outputVal[1])
# self.run(abs(float(str(outputVal[1]))), abs(float(str(outputVal[1]))), True, True, outputVal[0], debugFlag)
# self.run(current_data,outputVal[1],True,True)
# for idx, output in enumerate(outputVal):
# print(inputVal[idx] + ' : ' + output)
# print('----------------')
def start_time(self):
return self.starttime.time().toString().replace(':', '')
def end_time(self):
return self.endtime.time().toString().replace(':', '')
def checkbox(self):
te = ''
if self.ChekGroup1.isChecked():
te = '10'
if self.ChekGroup2.isChecked():
te = '01'
if self.ChekGroup1.isChecked() and self.ChekGroup2.isChecked():
te = '11'
return te
# ------ ๋ฐ์ดํฐ ์์ ๊ธฐ๋ฅ end -------
# ------ ์ ์ ์ ๋ณด start -------
def login_clicked(self):
ret = self.kiwoom.dynamicCall("CommConnect(0)")
print(ret)
def staate_clicked(self):
if self.kiwoom.dynamicCall("GetConnectState()") == 0:
self.statusBar().showMessage("Not connected")
print('---------------------------------')
print('๋ก๊ทธ์ธ ์คํจ')
print('---------------------------------')
else:
self.statusBar().showMessage("Connected")
print('---------------------------------')
print('๋ก๊ทธ์ธ ์ฑ๊ณต')
print('---------------------------------')
def login_info(self):
info_user_id = self.kiwoom.dynamicCall('GetLoginInfo("USER_ID")')
info_user_name = self.kiwoom.dynamicCall('GetLoginInfo("USER_NAME")')
info_account_cnt = self.kiwoom.dynamicCall('GetLoginInfo("ACCOUNT_CNT")')
info_accno = self.kiwoom.dynamicCall('GetLoginInfo("ACCNO")')
info_key_bsecgb = self.kiwoom.dynamicCall('GetLoginInfo("KEY_BSECGB")')
info_firew_secgb = self.kiwoom.dynamicCall('GetLoginInfo("FIREW_SECGB")')
self.account.setText(info_accno.split(';')[0])
print('---------------------------------')
print('user_id : ', info_user_id)
print('user_name : ', info_user_name)
print('์ ์ฒด๊ณ์ข ๊ฐฏ์ : ', info_account_cnt)
print('๊ณ์ข ์ ๋ณด :', info_accno)
print('ํค๋ณด๋ ๋ณด์ ์ฌ๋ถ : ', info_key_bsecgb, ' [0:์ ์ / 1:ํด์ง]')
print('๋ฐฉํ๋ฒฝ ์ค์ ์ฌ๋ถ :', info_firew_secgb, ' [0:๋ฏธ์ค์ / 1:์ค์ / 2:ํด์ง]')
print('---------------------------------')
# ------ ์ ์ ์ ๋ณด end -------
# ------ ์ข
๋ชฉ ์ ๋ณด start -------
def subject_search(self):
self.kiwoom.SetInputValue("์ข
๋ชฉ์ฝ๋", self.stoct_code.text())
res = self.kiwoom.CommRqData("์ฃผ๊ฐ์กฐํ", "opt10001", "0", "opt10001")
print(res)
def minute_data(self):
self.kiwoom.SetInputValue("์ข
๋ชฉ์ฝ๋", self.stoct_code.text())
self.kiwoom.SetInputValue("์๊ฐ๋จ์", "1")
# self.kiwoom.SetInputValue("๊ธฐ์ค์ผ์", datetime.datetime.now().strftime('%Y%m%d%H%M%S'))
# self.kiwoom.SetInputValue("์์ ์ฃผ๊ฐ๊ตฌ๋ถ","1")
# res = self.kiwoom.CommRqData("๋ถ๋ด์ ๋ณด","opt10012","0",datetime.datetime.now().strftime('%Y%m%d%H%M%S'))
res = self.kiwoom.CommRqData("๋ถ๋ด์ ๋ณด", "opt10012", "0", "opt10012")
print(res)
if res == 0:
print('์กฐํ ์ฑ๊ณต')
else:
print('์กฐํ ์คํจ')
# ------ ์ ์ ์ ๋ณด end -------
# Transaction: Node
class Transaction:
def __init__(self, typeIn, priceIn, count):
self.type = typeIn
self.price = priceIn
self.count = count
# ์ด๊ธฐ ์ธํ
self.bongP = 0
self.tickP = 0
self.bongCount = 0
# Doubly Linked List๋ผ์ prev & next ์กด์ฌ
self.prev = None
self.next = None
def __str__(self):
return '์ฒด๊ฒฐ ๋
ธ๋. ๊ฐ๊ฒฉ: ' + str(self.price)
# LinkedList ์์ญ
def ll_append(newNode):
global head
"""
Insert a new element at the end of the list.
Takes O(n) time.
"""
if not head:
head = newNode
return
curr = head
while curr.next:
curr = curr.next
curr.next = newNode
def remove_elem(node):
global head
"""
Unlink an element from the list.
Takes O(1) time.
"""
prev = node.prev
if node.prev:
node.prev.next = node.next
if node.next:
node.next.prev = node.prev
if node is head:
head = node.next
node.prev = None
node.next = None
return prev
if __name__ == "__main__":
app = QApplication(sys.argv)
# log_file = open('log' + COM_DATE + '_๊ฑฐ๋.csv', 'w')
# log_file.write('์ฒด๊ฒฐ์๊ฐ,BongFlag,๊ฐ๊ฒฉ,๋ด์นด์ดํธ,๊ฑฐ๋๋ด์ญ\n')
# log_file.flush()
myWindow = MyWindow()
myWindow.show()
app.exec_()
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