text stringlengths 0 1.05M | meta dict |
|---|---|
__author__ = 'shawnmehan'
"""2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder.
What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?
"""
def test_divs(number, start, stop):
no_remainder = [True]
for n in ran... | {
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__author__ = 'shawnmehan'
'''9*9*8*9 = 5832'''
inString = '''73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62... | {
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__author__ = 'shawnmehan'
""" Calculate the greatest product of 4 sequential elements in an nXm matrix, all directions"""
"""There are edges to the matrix that must be treated differently, then there is everything that is
n/2 in from the edge"""
text = """08 02 22 97 38 15 00 40 00 75 04 05 07 78 52 12 50 77 91 08
... | {
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__author__ = 'shawnmehan'
"""Class to calculate the triangle numbers and then determine how many divisors they have.
Objective is to find first triangle number with > 500 divisors"""
import math, time
ti = time.time()
def nofactors2(num):
count = 0
x = math.sqrt(num)
y = int(math.ceil(x))
if x - y ... | {
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__author__ = 'shawnmehan'
import csv, re
import xml.etree.cElementTree
def write_csv(data):
outfile = open('./Dataset1-Media-Example-EDGES.csv', 'wb')
outwriter = csv.writer(outfile, delimiter=',')
count = 0
for d in data: # iterate through each row
outwriter.writerow(d) # write the row
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__author__ = 'shawnmehan'
class Graph(object):
def __init__(self, graph_dict={}):
""" initializes a graph object """
self.__graph_dict = graph_dict
def vertices(self):
""" returns the vertices of a graph """
return list(self.__graph_dict.keys())
def edges(self):
... | {
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__author__ = 'shawnmehan'
#!/usr/bin/env python
from math import sqrt, ceil
import numpy as np
def rwh_primes(n):
""" Returns a list of primes < n """
sieve = [True] * n
for i in range(3,int(n**0.5)+1,2):
if sieve[i]:
sieve[i*i::2*i]=[False]*((n-i*i-1)/(2*i)+1)
return [2] + [i... | {
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# Factors that make the data seem artifical
# Addresses consisting of large amounts of numbers or start with numbers
# Addresses that seem very long
# ---- Imports ----
import random
import string
from sys import argv
# ---- Set Globals ----
global commonEmailProviders
global allTLDS, commonTLDS, commonTLDSx
global... | {
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"path": "Old Projects/ident/EmailGen.py",
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import ROOT
from ROOT import TVector2, TLorentzVector, TMath
ROOT.gROOT.SetBatch(True) #Do I want to run in batch mode?
from CMSobservables import *
from renormalize import *
#------------------------------------------------------------------
class minhists:
def __init__(self, tag, topdir, isdata, treetype, DSID, s... | {
"repo_name": "sschier/histMaker-repo",
"path": "CMShistograms.py",
"copies": "1",
"size": "24616",
"license": "unlicense",
"hash": 5772953055287444000,
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"line_max": 209,
"alpha_frac": 0.5999350016,
"autogenerated": false,
"ratio": 2.665511640498105,
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import ROOT
from ROOT import TVector2, TLorentzVector, TMath
ROOT.gROOT.SetBatch(True) #Do I want to run in batch mode?
from CMSobservables import *
from renormalize import *
#------------------------------------------------------------------
class lephists:
def __init__(self, tag, topdir, isdata, treetype, DSID,... | {
"repo_name": "sschier/histMaker-repo",
"path": "Effhistograms.py",
"copies": "1",
"size": "6738",
"license": "unlicense",
"hash": -2882392946130431000,
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"line_max": 209,
"alpha_frac": 0.5844464233,
"autogenerated": false,
"ratio": 3.3472429210134127,
"config_test": f... |
import numpy as np
import os
from scipy.io import loadmat
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
def fisherDiscrimVowelDemo():
data = loadmat('../data/vowelTrain')
Xtrain = data['Xtrain']
ytrain = data['yt... | {
"repo_name": "probml/pyprobml",
"path": "scripts/fisherDiscrimVowelDemo.py",
"copies": "1",
"size": "1403",
"license": "mit",
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__author__ = 'shekarnh'
import json
import subprocess
import yaml
import logging
import sys
class GetTags(object):
def __init__(self, tagFile):
self.outTagFile = tagFile
self.logger = logging.getLogger(__name__)
def update_tag_file(self):
# requires awscli installed and credentials c... | {
"repo_name": "NUCyberEd/CloudWhip",
"path": "cloudWhip/getTags.py",
"copies": "1",
"size": "1663",
"license": "mit",
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... |
__author__ = 'shekarnh'
"""
Recipe for creating and updating security groups programmatically.
Orginal author: Mike Steder
url: https://gist.github.com/steder/1498451
"""
import collections
import logging
import sys
import getTags
import os
import time
class SecurityGroups(object):
def __init__(self, ec2Conn... | {
"repo_name": "NUCyberEd/CloudWhip",
"path": "cloudWhip/secGroups.py",
"copies": "1",
"size": "4917",
"license": "mit",
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"line_max": 116,
"alpha_frac": 0.5391498881,
"autogenerated": false,
"ratio": 4.152871621621622,
"config_test": false,... |
__author__ = 'shekar_n_h'
import getTags
import os
import logging
import sys
import time
import subprocess
from boto import ec2
import netIps
class PodSetUp(object):
def __init__(self, ec2Connection, vpcConnection):
self.conn = ec2Connection
self.vpcConn = vpcConnection
se... | {
"repo_name": "NUCyberEd/CloudWhip",
"path": "cloudWhip/podSetUp.py",
"copies": "1",
"size": "11463",
"license": "mit",
"hash": 3196815106108865000,
"line_mean": 52.8564593301,
"line_max": 125,
"alpha_frac": 0.5212422577,
"autogenerated": false,
"ratio": 4.504125736738703,
"config_test": false,... |
__author__ = 'shekar_n_h'
import sys
import logging
import getTags
import os
import secGroups
import time
import netIps
class VpcSetUp(object):
def __init__(self, vpcConnection, ec2Connection):
self.conn = vpcConnection
self.ec2Conn = ec2Connection # ec2 connection for security gro... | {
"repo_name": "NUCyberEd/CloudWhip",
"path": "cloudWhip/vpcSetUp.py",
"copies": "1",
"size": "10934",
"license": "mit",
"hash": 3387496061350465000,
"line_mean": 47.0403587444,
"line_max": 149,
"alpha_frac": 0.5612767514,
"autogenerated": false,
"ratio": 3.9615942028985507,
"config_test": false... |
__author__ = 'shekkizh'
# Utils used with tensorflow implemetation
import tensorflow as tf
import numpy as np
import scipy.misc as misc
import os, sys
from six.moves import urllib
import tarfile
import zipfile
from tqdm import trange
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from mpl_tool... | {
"repo_name": "melkonyan/BA_WassersteinGAN",
"path": "utils.py",
"copies": "1",
"size": "7026",
"license": "mit",
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"alpha_frac": 0.6362083689,
"autogenerated": false,
"ratio": 3.218506642235456,
"config_test": false,
"h... |
__author__ = 'shellyan'
# == OAuth Authentication ==
#
# This mode of authentication is the new preferred way
# of authenticating with Twitter.
# The consumer keys can be found on your application's Details
# page located at https://dev.twitter.com/apps (under "OAuth settings")
consumer_key="jirJSDlasEBd6MEeXc4hsA"
c... | {
"repo_name": "shellyan/cs-339-chatapp",
"path": "src/server/twitter.py",
"copies": "1",
"size": "1191",
"license": "mit",
"hash": -8246724624339255000,
"line_mean": 37.4193548387,
"line_max": 75,
"alpha_frac": 0.7833753149,
"autogenerated": false,
"ratio": 3,
"config_test": false,
"has_no_ke... |
__author__ = 'shengjia'
import subprocess, threading
import random
import time
import os
import math
# Runs a system command without timeout
def run_command(command):
p = subprocess.Popen(command,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
return [item.... | {
"repo_name": "ShengjiaZhao/XORModelCount",
"path": "SATModelCount/sat.py",
"copies": "1",
"size": "9007",
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"hash": 3351017364979709000,
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"autogenerated": false,
"ratio": 4.0792572463768115,
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__author__ = 'shengjia'
import threading
import time
class Timer:
def __init__(self, max_time):
self.max_time = max_time
self.begin_time = time.time()
self.time_out_flag = False
self.time_out_flag_lock = threading.Lock()
self.timer_thread = threading.Thread(target=self.tim... | {
"repo_name": "ShengjiaZhao/XORModelCount",
"path": "SATModelCount/timer.py",
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"size": "1371",
"license": "mit",
"hash": -7482211240712632000,
"line_mean": 26.9795918367,
"line_max": 88,
"alpha_frac": 0.5616338439,
"autogenerated": false,
"ratio": 3.808333333333333,
"config_test":... |
__authors__ = "Heng Luo"
from pylearn2.testing.skip import skip_if_no_gpu
skip_if_no_gpu()
import numpy as np
from theano import shared
from theano.tensor import grad, constant
from pylearn2.sandbox.cuda_convnet.filter_acts import FilterActs
from pylearn2.sandbox.cuda_convnet.filter_acts import ImageActs
from theano.... | {
"repo_name": "skearnes/pylearn2",
"path": "pylearn2/sandbox/cuda_convnet/tests/test_image_acts_strided.py",
"copies": "5",
"size": "6085",
"license": "bsd-3-clause",
"hash": -5514414139275688000,
"line_mean": 40.9655172414,
"line_max": 131,
"alpha_frac": 0.5636811832,
"autogenerated": false,
"ra... |
__author__ = 'shenoisz'
from django.conf import settings
class GetPageRequest( object ):
#=======================================================
# add host, session and url for cache util
#=======================================================
def process_request( self, request ):
set... | {
"repo_name": "SHENOISZ/django-pages-cache",
"path": "Tests/pages_cache/middleware/PagesRequests.py",
"copies": "2",
"size": "1180",
"license": "bsd-3-clause",
"hash": 764992155024510600,
"line_mean": 33.7058823529,
"line_max": 92,
"alpha_frac": 0.4262711864,
"autogenerated": false,
"ratio": 5.06... |
__author__ = 'shenoisz'
from django.core.cache import cache
from django.conf import settings
#from django.utils.decorators import available_attrs
#from functools import wraps
class CacheViews( ):
"""
Class util cache with memcache
"""
#======================================
# add views... | {
"repo_name": "SHENOISZ/django-pages-cache",
"path": "Tests/pages_cache/pages_decorators.py",
"copies": "3",
"size": "5133",
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"hash": -6159798424959396000,
"line_mean": 33.6824324324,
"line_max": 80,
"alpha_frac": 0.3323592441,
"autogenerated": false,
"ratio": 6.08896797... |
__author__ = 'shenojia'
import pprint
import re
import sys
import unittest
import weakref
import numpy as np
from matplotlib.path import Path
from matplotlib.patches import PathPatch
import matplotlib.pyplot as plt
sys.path.insert(0, '..')
from R12_36211.RE import RE
from R12_36211.RG import RG
from R12_36211.PRB impo... | {
"repo_name": "shennjia/weblte",
"path": "matplot/test_prb.py",
"copies": "1",
"size": "1891",
"license": "mit",
"hash": 9133696379090656000,
"line_mean": 30,
"line_max": 96,
"alpha_frac": 0.6054997356,
"autogenerated": false,
"ratio": 2.6671368124118477,
"config_test": true,
"has_no_keywords... |
__author__ = 'shenojia'
import sys
from matplotlib.path import Path
from matplotlib.patches import PathPatch
sys.path.insert(0, '.')
sys.path.insert(0, '..')
from R12_36211.RG import RG
from R12_36xxx.HighLayer import conf
from R12_36xxx.HighLayer import cell
from R12_36xxx.TypesDefition import SubFrameType
from xlsxwr... | {
"repo_name": "shennjia/weblte",
"path": "R12_36211/SLOT.py",
"copies": "1",
"size": "3996",
"license": "mit",
"hash": 8538209631706650000,
"line_mean": 33.1538461538,
"line_max": 100,
"alpha_frac": 0.4952452452,
"autogenerated": false,
"ratio": 3.4838709677419355,
"config_test": false,
"has_... |
__author__ = 'shenojia'
import sys
import numpy as np
from matplotlib.path import Path
from matplotlib.patches import PathPatch
sys.path.insert(0, '.')
sys.path.insert(0, '..')
from R12_36211.SLOT import SLOT
from R12_36211.PRBPAIR import PRBPAIR
from R12_36211.PCFICH import *
from R12_36211.CRS import *
from R12_36211... | {
"repo_name": "shennjia/weblte",
"path": "R12_36211/SUBFRAME.py",
"copies": "1",
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"license": "mit",
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"autogenerated": false,
"ratio": 3.395872420262664,
"config_test": false,
"... |
__author__ = 'shenojia'
import sys
import numpy as np
from matplotlib.path import Path
from matplotlib.patches import PathPatch
sys.path.insert(0, '.')
sys.path.insert(0, '..')
from R12_36xxx.HighLayer import *
from R12_36xxx.TypesDefition import *
from R12_36211.RE import RE
from R12_36211.SLOT import SLOT
from R12_36... | {
"repo_name": "shennjia/weblte",
"path": "R12_36211/MBSFNRS.py",
"copies": "1",
"size": "5065",
"license": "mit",
"hash": 1323541812518900700,
"line_mean": 39.528,
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"alpha_frac": 0.4576505429,
"autogenerated": false,
"ratio": 3.571932299012694,
"config_test": false,
"has_no_ke... |
__author__ = 'shenojia'
import sys
import weakref
sys.path.insert(0, '.')
sys.path.insert(0, '..')
from R12_36xxx.HighLayer import *
from R12_36xxx.TypesDefition import *
from R12_36211.RE import RE
from R12_36211.REG import REG
from R12_36211.PRB import *
from matplotlib.path import Path
from matplotlib.patches impor... | {
"repo_name": "shennjia/weblte",
"path": "R12_36211/RG.py",
"copies": "1",
"size": "15561",
"license": "mit",
"hash": -1711594199082842000,
"line_mean": 38.7979539642,
"line_max": 142,
"alpha_frac": 0.4675149412,
"autogenerated": false,
"ratio": 3.222406295299234,
"config_test": false,
"has_n... |
__author__ = 'shenojia'
import sys
sys.path.insert(0, '.')
sys.path.insert(0, '..')
from R12_36xxx.HighLayer import *
from R12_36211.REG import REG
from math import floor
from matplotlib.path import Path
from matplotlib.patches import PathPatch
from xlsxwriter.worksheet import Worksheet
class PRB:
"""
Resource ... | {
"repo_name": "shennjia/weblte",
"path": "R12_36211/PRB.py",
"copies": "1",
"size": "4004",
"license": "mit",
"hash": 1211850327685366500,
"line_mean": 34.4336283186,
"line_max": 98,
"alpha_frac": 0.5087412587,
"autogenerated": false,
"ratio": 3.5654496883348172,
"config_test": false,
"has_no... |
__author__ = 'shenojia'
import sys
sys.path.insert(0, '.')
sys.path.insert(0, '..')
import numpy
def PNlfsr(taps, c__init:int, M__PN:int):
"""Function implements a linear feedback shift register
36211-c20 7.2
taps: List of Polynomial exponents for non-zero terms other than 1 and n x(n+1),x(n+2)...x(n+30)... | {
"repo_name": "shennjia/weblte",
"path": "R12_math_util/pn.py",
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"autogenerated": false,
"ratio": 2.908,
"config_test": false,
"has_no_keywords": fals... |
__author__ = 'shenojia'
import sys
import numpy as np
from math import floor
from matplotlib.path import Path
from matplotlib.patches import PathPatch
sys.path.insert(0, '.')
sys.path.insert(0, '..')
from R12_36211.SLOT import SLOT
from R12_36xxx.TypesDefition import *
from R12_36xxx.HighLayer import conf
class PCFIC... | {
"repo_name": "shennjia/weblte",
"path": "R12_36211/PCFICH.py",
"copies": "1",
"size": "4392",
"license": "mit",
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"autogenerated": false,
"ratio": 3.3732718894009217,
"config_test": false,
"has... |
__author__ = 'shenojia'
class CyclicPrefix:
"""
defition of cyclicPrefix type
"""
def __init__(self, cyclickPrefix = 0):
self.cyclicPrefix = 0
self.cyclicPrefixSymbolLen = 0
self.cyclicPrefixName = ''
if cyclickPrefix == 0:
self.cyclicPrefix = 0
... | {
"repo_name": "shennjia/weblte",
"path": "R12_36xxx/TypesDefition.py",
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"""
Simple CodePlex style wiki writer.
"""
__docformat__ = 'reStructuredText'
import sys
import os
import os.path
import time
import re
from types import ListType
try:
import Image # check for the Python Imaging Library
except ImportError:
Image = None
import docutils
from docutils ... | {
"repo_name": "shibu/pyspec",
"path": "sample/rst2codeplex/rst2codeplex.py",
"copies": "1",
"size": "49962",
"license": "mit",
"hash": -2655031932694727000,
"line_mean": 34.2093023256,
"line_max": 79,
"alpha_frac": 0.5470357472,
"autogenerated": false,
"ratio": 3.933086672439581,
"config_test":... |
__author__ = 'shihhau' # Shih-Hau Tan
#
# Copyright 2016-2020 Cuemacro
#
# 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 applic... | {
"repo_name": "cuemacro/findatapy",
"path": "findatapy_examples/cryptodata_example.py",
"copies": "1",
"size": "6072",
"license": "apache-2.0",
"hash": 7606080889383279000,
"line_mean": 43.3284671533,
"line_max": 121,
"alpha_frac": 0.5752635046,
"autogenerated": false,
"ratio": 4.0751677852349,
... |
__author__ = 'shikun'
# -*- coding: utf-8 -*-
from selenium.webdriver.support.ui import WebDriverWait
from selenium.common.exceptions import WebDriverException
from common.variable import Constants as common
import time
from common import log
# 此脚本主要用于查找元素是否存在，操作页面元素
class OperateElement:
def __init__(self, driv... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "common/operateElement.py",
"copies": "1",
"size": "5696",
"license": "apache-2.0",
"hash": 466175927227273860,
"line_mean": 34.5512820513,
"line_max": 142,
"alpha_frac": 0.6258564731,
"autogenerated": false,
"ratio": 3.237594862813777,
"co... |
__author__ = 'shikun'
# -*- coding: utf-8 -*-
import os
import subprocess
import re
# 得到手机信息
def get_phone_info(devices):
l_list = {'release': 'unknown', 'model': 'unknown', 'brand': 'unknown', 'device': 'unknown'}
cmd = "adb -s " + devices + " shell cat /system/build.prop"
(output, err) = subprocess.Pope... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "testDAL/phoneBase.py",
"copies": "1",
"size": "2878",
"license": "apache-2.0",
"hash": -1064317926265839700,
"line_mean": 30.7528089888,
"line_max": 96,
"alpha_frac": 0.5661712668,
"autogenerated": false,
"ratio": 3.252013808975834,
"confi... |
__author__ = 'shikun'
# -*- coding: utf-8 -*-
import re, os
from common import log
num_re = re.compile("\d+\.?\d*")
# 常用的性能监控
def top_cpu(devices, pkg_name):
cmd = "adb -s "+devices+" shell dumpsys cpuinfo | findstr " + pkg_name+":"
get_cmd = os.popen(cmd).read()
match = re.compile(pkg_name + ":\s+(\d+\.... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "common/appPerformance.py",
"copies": "1",
"size": "2390",
"license": "apache-2.0",
"hash": -1015742012346731600,
"line_mean": 29.6164383562,
"line_max": 117,
"alpha_frac": 0.5416293644,
"autogenerated": false,
"ratio": 2.479467258601554,
"... |
__author__ = 'shikun'
# -*- coding: utf-8 -*-
import unittest
from appium import webdriver
from common.variable import Constants
from testBLL import apkBase
def appium_test_case(device):
app_path = device["appPath"]
apk_base = apkBase.ApkInfo(app_path)
desired_caps = {}
desired_caps['platformName'] = ... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "testRunner/runnerBase.py",
"copies": "1",
"size": "1804",
"license": "apache-2.0",
"hash": -5484467456664180000,
"line_mean": 33.0377358491,
"line_max": 69,
"alpha_frac": 0.6579822616,
"autogenerated": false,
"ratio": 3.651821862348178,
"c... |
__author__ = 'shikun'
from math import floor
import subprocess
import os
import re
class ApkInfo:
def __init__(self, apkpath):
self.apkpath = apkpath
self.dump_badging = None
def get_dump_badging(self):
if not self.dump_badging:
(output, err) = subprocess.Popen("aapt dum... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "testDAL/apkBase.py",
"copies": "1",
"size": "2068",
"license": "apache-2.0",
"hash": 4898636692855292000,
"line_mean": 26.8611111111,
"line_max": 108,
"alpha_frac": 0.5503489531,
"autogenerated": false,
"ratio": 3.3322259136212624,
"config... |
__author__ = 'shikun'
import math
from common import log
def phone_avg_use_cpu(cpu):
result = "0%"
if len(cpu) > 0:
result = "%.1f" % (sum(cpu) / len(cpu)) + "%"
return result
def phone_avg_use_raw(men):
result = "0M"
if len(men) > 0:
result = str(math.ceil(sum(men) / len(men) / ... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "common/reportPhone.py",
"copies": "1",
"size": "1201",
"license": "apache-2.0",
"hash": 7607659580809021000,
"line_mean": 18.0634920635,
"line_max": 69,
"alpha_frac": 0.4970857619,
"autogenerated": false,
"ratio": 2.662971175166297,
"confi... |
__author__ = 'shikun'
import os
from common import log
class OperateFile:
def __init__(self, file, method='w+'):
self.file = file
self.method = method
self.fileHandle = None
def write_txt(self, line):
OperateFile(self.file).check_file()
self.fileHandle = open(self.file... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "common/operateFile.py",
"copies": "1",
"size": "1334",
"license": "apache-2.0",
"hash": -2568958405141611500,
"line_mean": 26.7916666667,
"line_max": 58,
"alpha_frac": 0.5607196402,
"autogenerated": false,
"ratio": 3.6648351648351647,
"con... |
__author__ = 'shikun'
from schematics.models import Model
from schematics.types import StringType,IntType, FloatType
from schematics.types.compound import ListType,MultiType
class GetAppCase(Model):
element_info = StringType() # (查找类型：name/id/xpah)
operate_type = StringType() # 具体的详情,如xpath:“/android.widge... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "testModel/appCase.py",
"copies": "1",
"size": "1589",
"license": "apache-2.0",
"hash": -8686433670999805000,
"line_mean": 33.5526315789,
"line_max": 106,
"alpha_frac": 0.6656511805,
"autogenerated": false,
"ratio": 2.4314814814814816,
"con... |
__author__ = 'shikun'
class Constants(object):
TEST_ID = "test_id"
TEST_DESC = "test_desc"
FIND_TYPE = "find_type"
SWIPE_DIRECTION = "direction"
SWIPE_TIMES = "times"
WAITE_TIMEOUT = "timeout"
TAP_POINT = "point"
OPERATION_TYPE = "operate_type"
ELEMENT_INFO = "element_info"
FI... | {
"repo_name": "pqpo/appiumn_auto_re-develope",
"path": "common/variable.py",
"copies": "1",
"size": "1377",
"license": "apache-2.0",
"hash": 5739017338017265000,
"line_mean": 25.2156862745,
"line_max": 46,
"alpha_frac": 0.6222887061,
"autogenerated": false,
"ratio": 2.546666666666667,
"config_t... |
__author__ = 'ShivamMistry'
class Menu:
""" A wrapper for a Dominos menu """
def __init__(self, client, data):
self.pizzas = [Product(x) for x in data["pizzas"][0]]
self.starters = [Product(x) for x in data["starters"][0]]
self.desserts = [Product(x) for x in data["desserts"][0]]
... | {
"repo_name": "freecode/dominos-cli",
"path": "dominoscli/menu.py",
"copies": "1",
"size": "3156",
"license": "mit",
"hash": 142942163781718900,
"line_mean": 40.5263157895,
"line_max": 75,
"alpha_frac": 0.5627376426,
"autogenerated": false,
"ratio": 3.5580608793686586,
"config_test": false,
"... |
__author__ = "Shivam Shekhar"
import os
import sys
import pygame
import random
from pygame import *
pygame.mixer.pre_init(44100, -16, 2, 2048) # fix audio delay
pygame.init()
scr_size = (width,height) = (600,150)
FPS = 60
gravity = 0.6
black = (0,0,0)
white = (255,255,255)
background_col = (235,235,235)
high_scor... | {
"repo_name": "shivamshekhar/Chrome-T-Rex-Rush",
"path": "main.py",
"copies": "1",
"size": "16277",
"license": "mit",
"hash": -4467983112845631000,
"line_mean": 30.9156862745,
"line_max": 95,
"alpha_frac": 0.5358481293,
"autogenerated": false,
"ratio": 3.5469601220309435,
"config_test": false,
... |
__author__ = 'shkiper'
from . import morph
def get_best_parse(word: str, part: str):
possibilities = [x for x in morph.parse(word) if x.tag.POS == part]
if len(possibilities) == 0:
return None
else:
return max(possibilities, key=lambda x: (x.score, x.word))
WHO_PARSE = get_best_parse('кт... | {
"repo_name": "hatbot-team/hatbot_resources",
"path": "preparation/lang_utils/morphology/replace_with_gap.py",
"copies": "1",
"size": "2900",
"license": "mit",
"hash": 5497285231975757000,
"line_mean": 32.7195121951,
"line_max": 83,
"alpha_frac": 0.6385672938,
"autogenerated": false,
"ratio": 2.9... |
__author__ = 'shkiper'
# noinspection PyProtectedMember
from preparation.resources.book_titles import _raw_data
from preparation.resources.Resource import gen_resource
from hb_res.explanations import Explanation
from preparation import modifiers
import re
import copy
@modifiers.modifier_factory
def add_common_prefix(... | {
"repo_name": "hatbot-team/hatbot_resources",
"path": "preparation/resources/book_titles/parse_book_titles.py",
"copies": "1",
"size": "1970",
"license": "mit",
"hash": -2703557629420150300,
"line_mean": 30.5,
"line_max": 89,
"alpha_frac": 0.6021505376,
"autogenerated": false,
"ratio": 3.72,
"c... |
__author__ = 'shkiper'
# noinspection PyProtectedMember
from preparation.resources.crosswords import _raw_data
from preparation.resources.Resource import gen_resource
from hb_res.explanations import Explanation
from preparation import modifiers
crosswords_mods = [
modifiers.re_replace('p', 'р'),
modifiers.str... | {
"repo_name": "hatbot-team/hatbot_resources",
"path": "preparation/resources/crosswords/parse_crosswords.py",
"copies": "1",
"size": "1032",
"license": "mit",
"hash": 5810879810310250000,
"line_mean": 33.3666666667,
"line_max": 75,
"alpha_frac": 0.6411251212,
"autogenerated": false,
"ratio": 3.30... |
__author__ = 'shkiper'
# noinspection PyProtectedMember
from preparation.resources.film_titles import _raw_data
from preparation.resources.Resource import gen_resource
from hb_res.explanations import Explanation
from preparation import modifiers
import re
import copy
@modifiers.modifier_factory
def add_common_prefix(... | {
"repo_name": "hatbot-team/hatbot_resources",
"path": "preparation/resources/film_titles/parse_film_titles.py",
"copies": "1",
"size": "1460",
"license": "mit",
"hash": 6669594193957870000,
"line_mean": 31.3333333333,
"line_max": 87,
"alpha_frac": 0.6323024055,
"autogenerated": false,
"ratio": 3.... |
__author__ = 'ShlomiB'
import socket
import json
class HCRequestsFactory(object):
def __init__(self):
pass
def get_request_from_json(self, json_string):
loaded_object = json.loads(json_string)
ret_obj = None
if loaded_object['RequestType'] == 'ListMayors':
ret_obj... | {
"repo_name": "shlomibe/Homechestrator",
"path": "HCProtocol/HCRequests.py",
"copies": "1",
"size": "2439",
"license": "unlicense",
"hash": 2200822088520500200,
"line_mean": 29.8860759494,
"line_max": 74,
"alpha_frac": 0.594095941,
"autogenerated": false,
"ratio": 3.8591772151898733,
"config_te... |
__author__ = 'ShlomiB'
import sys
import socket
from time import sleep
from HCProtocol.HCRequests import HCRequestsFactory
from HCShared.HCLogger import *
import uuid
class HCRequestHandler(object):
def __init__(self, name, in_socket):
self._name = name
self._socket = in_socket
# TODO: pr... | {
"repo_name": "shlomibe/Homechestrator",
"path": "HCServer/HCRequestHandler.py",
"copies": "1",
"size": "1921",
"license": "unlicense",
"hash": -6526094035792639000,
"line_mean": 35.9423076923,
"line_max": 105,
"alpha_frac": 0.5663716814,
"autogenerated": false,
"ratio": 4.562945368171022,
"con... |
#Modification of the server(even from here) can result in additional security issues.
#YOU have been WARNED!
#If you want output to be a file(good if output is large to save ram)use Output_File_Path,only used if Output_Content is empty.
#BE CAREFUL Output_File_Path bypasses the allowed folders security checks so it c... | {
"repo_name": "Shb743/HT-PY",
"path": "Custom.py",
"copies": "1",
"size": "6292",
"license": "bsd-3-clause",
"hash": -8080054651334875000,
"line_mean": 31.6010362694,
"line_max": 177,
"alpha_frac": 0.7217101081,
"autogenerated": false,
"ratio": 3.121031746031746,
"config_test": false,
"has_no... |
import time
from threading import Thread
import datetime
import os
#Imports
#Globals
File_Path = os.getcwd()+"/"
DOS_Candidates = {}
Blocked_Candidates = []
On = 1#Is HouseKeeping Active
Log_Out = []#Logging
ELog_Out = []#Error Logging
TLock = None#Thread Lock for safe cross threading
#FileName & path for Logs(For HTT... | {
"repo_name": "Shb743/HT-PY",
"path": "HouseKeeping.py",
"copies": "1",
"size": "2936",
"license": "bsd-3-clause",
"hash": 5762957302434876000,
"line_mean": 26.9714285714,
"line_max": 132,
"alpha_frac": 0.7108310627,
"autogenerated": false,
"ratio": 2.904055390702275,
"config_test": false,
"h... |
HDANA = ["content-type","accept-ranges","content-length","etag"]#-MUST BE IN LOWER CASE-HeaderDuplicatesAreNotALlowed these headers will have their values replaced if duplicate custom headers are present
#Construct Output Header
def Construct_Header(Custom_Headers,Keep_Alive,Mime,Cont_Size,Code="200 OK",Ranges="bytes"... | {
"repo_name": "Shb743/HT-PY",
"path": "GF.py",
"copies": "1",
"size": "1857",
"license": "bsd-3-clause",
"hash": 5375847385539932000,
"line_mean": 52.0857142857,
"line_max": 203,
"alpha_frac": 0.7199784599,
"autogenerated": false,
"ratio": 3.1315345699831365,
"config_test": false,
"has_no_key... |
#Imports
import socket
import threading
from threading import Thread
from multiprocessing import Process
import datetime#Needed for logging purposes
import os,sys
import urllib#Unquote urls
import json#Decoding Settings Files
import uuid#Generating Temporary file names & Service Thread ID's ~
import GF#Global Function... | {
"repo_name": "Shb743/HT-PY",
"path": "Server.py",
"copies": "1",
"size": "31012",
"license": "bsd-3-clause",
"hash": -1987197843247004200,
"line_mean": 32.0628997868,
"line_max": 178,
"alpha_frac": 0.6875080614,
"autogenerated": false,
"ratio": 3.0380094043887147,
"config_test": false,
"has_... |
__author__ = "shoe116"
class HLLRegister(list):
def __init__(self, registerIndexSize):
list.__init__(self)
self.registerIndexSize = registerIndexSize
self.mask = int('1' * registerIndexSize, 2)
## all value is 0 as init
for i in xrange(0, 2**registerIndexSize):
... | {
"repo_name": "PhysicsEngine/kHLL",
"path": "kHLL/HLL/hyperloglog.py",
"copies": "1",
"size": "1281",
"license": "mit",
"hash": 1185772706778833700,
"line_mean": 31.025,
"line_max": 66,
"alpha_frac": 0.6151444184,
"autogenerated": false,
"ratio": 3.8238805970149254,
"config_test": false,
"has... |
__author__ = 'shreyas'
import twitter
import time
from datetime import datetime
import math
import pytz
from nltk.corpus import stopwords
api = twitter.Api(
consumer_key='*****',
consumer_secret='*****',
access_token_key='*****',
access_token_secret='*****',
)
companies = ['aapl','msft','goog','crm']
stopwo... | {
"repo_name": "ss4609/SS4609-Github",
"path": "FetchAndProcessTwitterData.py",
"copies": "2",
"size": "3755",
"license": "mit",
"hash": -444648001361482700,
"line_mean": 33.4495412844,
"line_max": 494,
"alpha_frac": 0.5379494008,
"autogenerated": false,
"ratio": 3.193027210884354,
"config_test"... |
import sys
import random
import numpy as np
import pdb
from collections import defaultdict
from itertools import combinations
from pyspark import SparkConf, SparkContext
from pyspark.mllib.linalg.distributed import MatrixEntry
from pyspark.mllib.linalg.distributed import RowMatrix
from pyspark.mllib.linalg import Vect... | {
"repo_name": "shreyas15/Product-Recommender-Engine",
"path": "User_based_cos_sim_parallelized/final.py",
"copies": "1",
"size": "7155",
"license": "mit",
"hash": -8600201756875235000,
"line_mean": 40.3583815029,
"line_max": 128,
"alpha_frac": 0.6644304682,
"autogenerated": false,
"ratio": 3.4103... |
__author__ = 'shuai'
class ListNode(object):
def __init__(self, x):
self.val = x
self.next = None
class Solution(object):
def addTwoNumbers(self, l1, l2):
"""
:type l1: ListNode
:type l2: ListNode
:rtype: ListNode
"""
ret = ListNode(0)
... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num002.py",
"copies": "1",
"size": "1088",
"license": "apache-2.0",
"hash": 236160411723583040,
"line_mean": 22.170212766,
"line_max": 45,
"alpha_frac": 0.4577205882,
"autogenerated": false,
"ratio": 3.228486646884273,
"config_test": fa... |
__author__ = 'shuai'
class Solution(object):
def countSmaller(self, nums):
"""
:type nums: List[int]
:rtype: List[int]
"""
count = []
ret = [0] * len(nums)
for i in range(len(nums)):
count.append({'index': i,
'value': num... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num315.py",
"copies": "1",
"size": "1742",
"license": "apache-2.0",
"hash": 7276113327916469000,
"line_mean": 24.6176470588,
"line_max": 62,
"alpha_frac": 0.3777267509,
"autogenerated": false,
"ratio": 3.629166666666667,
"config_test": ... |
__author__ = 'shuai'
class Solution(object):
def findLongestWord(self, s, d):
"""
:type s: str
:type d: List[str]
:rtype: str
"""
def _compare(a, b):
if len(a) < len(b):
return 1
elif len(a) == len(b):
return 0
... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num524.py",
"copies": "1",
"size": "1046",
"license": "apache-2.0",
"hash": 1679614205635905000,
"line_mean": 22.7727272727,
"line_max": 54,
"alpha_frac": 0.3652007648,
"autogenerated": false,
"ratio": 3.8175182481751824,
"config_test":... |
__author__ = 'shuai'
class Solution(object):
def findMedianSortedArrays(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: float
"""
ret = []
len1 = len(nums1)
len2 = len(nums2)
dst = (len1 + len2)/2
pos1 = ... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num004.py",
"copies": "1",
"size": "1432",
"license": "apache-2.0",
"hash": 3260205277902042600,
"line_mean": 28.8333333333,
"line_max": 59,
"alpha_frac": 0.4092178771,
"autogenerated": false,
"ratio": 3.588972431077694,
"config_test": ... |
__author__ = 'shuai'
class Solution(object):
def maximumGap(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
if not nums:
return 0
min_val = nums[0]
max_val = nums[0]
for i in range(len(nums)):
if nums[i] < min_val:
... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num164.py",
"copies": "1",
"size": "1393",
"license": "apache-2.0",
"hash": 5338041377777560000,
"line_mean": 26.86,
"line_max": 69,
"alpha_frac": 0.4443646805,
"autogenerated": false,
"ratio": 3.364734299516908,
"config_test": false,
... |
__author__ = 'shuai'
# Definition for a binary tree node.
class TreeNode(object):
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution(object):
def largestValues(self, root):
"""
:type root: TreeNode
:rtype: List[int]
"""... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num515.py",
"copies": "1",
"size": "1539",
"license": "apache-2.0",
"hash": -9127119960239513000,
"line_mean": 25.0847457627,
"line_max": 56,
"alpha_frac": 0.4470435348,
"autogenerated": false,
"ratio": 3.529816513761468,
"config_test":... |
__author__ = 'shuai'
# Definition for a binary tree node.
class TreeNode(object):
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution(object):
def convertBST(self, root):
"""
:type root: TreeNode
:rtype: TreeNode
"""
... | {
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"path": "leetcode-python/num538.py",
"copies": "1",
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"license": "apache-2.0",
"hash": 2123808125316393500,
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"autogenerated": false,
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__author__ = 'shuai'
# Definition for an interval.
class Interval(object):
def __init__(self, s=0, e=0):
self.start = s
self.end = e
def __str__(self):
return str(self.start) + "-" + str(self.end)
class Solution(object):
def merge(self, intervals):
"""
:type interv... | {
"repo_name": "shuaizi/leetcode",
"path": "leetcode-python/num056.py",
"copies": "1",
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__author__ = 'shua'
import argparse
import numpy as np
import wave
import os
from os import listdir
from os.path import isfile, join
import math
from scipy.fftpack.realtransforms import dct
from scipy.signal import lfilter, hamming
from copy import deepcopy
from scipy.fftpack import fft, ifft
from scikits.talkbox.linp... | {
"repo_name": "MLSpeech/DeepFormants",
"path": "extract_features.py",
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"autogenerated": false,
"ratio": 3.2123955431754876,
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__author__ = 'shubham_dokania'
#from django.db import models
#from models import Controller
def ConvertAndSave(s = '000000000000000000000000000000111111111111110101'):
array = []
for i in range(0, 6):
array.append(s[(i*8):((i+1)*8)])
#idno = int(str(int(array[0], 2))+str(int(array[1], 2... | {
"repo_name": "shubham1810/aquabrim_project",
"path": "machine/receiver.py",
"copies": "1",
"size": "6021",
"license": "mit",
"hash": -837828421625557000,
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"line_max": 82,
"alpha_frac": 0.387809334,
"autogenerated": false,
"ratio": 3.4965156794425085,
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__author__ = 'shubham_dokania'
def ConvertAndSave(Controller, s = '000000000000000000000000000000111111111111110101'):
array = []
for i in range(0, 6):
array.append(s[(i*8):((i+1)*8)])
idno = int(str(int(array[0], 2))+str(int(array[1], 2))+str(int(array[2], 2)))
# print idno
com... | {
"repo_name": "nikaashpuri/aquabrim_project",
"path": "machine/receiver.py",
"copies": "1",
"size": "6313",
"license": "mit",
"hash": 3325225012762434000,
"line_mean": 30.0558375635,
"line_max": 87,
"alpha_frac": 0.3931569777,
"autogenerated": false,
"ratio": 3.480154355016538,
"config_test": f... |
import urllib2
import cookielib
from getpass import getpass
import sys
import os
from stat import *
def regain():
message = raw_input("Enter text: ")
number = raw_input("Enter number: ")
message = "+".join(message.split(' '))
#logging into the sms site
url ='http://site24.way2sms.com/Login1.action?'... | {
"repo_name": "Shubham05178/Pythonmobilemessage",
"path": "MessageByWay2Sms.py",
"copies": "1",
"size": "1492",
"license": "mit",
"hash": -3027171868475877400,
"line_mean": 26.1272727273,
"line_max": 132,
"alpha_frac": 0.6327077748,
"autogenerated": false,
"ratio": 3.1880341880341883,
"config_t... |
__author__ = 'ShubhamTripathi'
import re
from nltk import word_tokenize as wt
from batchio import *
from random import randint
#main = get_training_data()
#cleaned = clean(main['utter_x'], main['utter_y'])
class engTextSeparate:
cleaned_1=[]
def __init__(self,cleaned_1):
self.cleaned_1 = cleaned_1
... | {
"repo_name": "saatvikshah1994/hline",
"path": "Subtask1-Revised/engTextSeparate.py",
"copies": "1",
"size": "4536",
"license": "mit",
"hash": 5004679116326688000,
"line_mean": 33.1052631579,
"line_max": 160,
"alpha_frac": 0.4905202822,
"autogenerated": false,
"ratio": 3.699836867862969,
"confi... |
__author__ = 'Shyue Ping Ong'
__copyright__ = 'Copyright 2013, The Materials Project'
__version__ = '0.1'
__maintainer__ = 'Shyue Ping Ong'
__email__ = 'ongsp@ucsd.edu'
__date__ = '1/31/14'
import logging
from pymatgen import Structure
from fireworks import FireTaskBase, FWAction, explicit_serialize
from custodian imp... | {
"repo_name": "materialsvirtuallab/fireworks-vasp",
"path": "fireworks_vasp/tasks.py",
"copies": "1",
"size": "3990",
"license": "mit",
"hash": -785811105756976100,
"line_mean": 35.6055045872,
"line_max": 79,
"alpha_frac": 0.6152882206,
"autogenerated": false,
"ratio": 3.667279411764706,
"confi... |
__author__ = 'Shyue Ping Ong'
__copyright__ = 'Copyright 2014, The Materials Virtual Lab'
__version__ = '0.1'
__maintainer__ = 'Shyue Ping Ong'
__email__ = 'ongsp@ucsd.edu'
__date__ = '1/24/14'
import unittest
import numpy as np
import json
import datetime
import six
from monty.json import MSONable, MSONError, Monty... | {
"repo_name": "gpetretto/monty",
"path": "tests/test_json.py",
"copies": "1",
"size": "3133",
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"hash": -8300203540013810000,
"line_mean": 28.2803738318,
"line_max": 74,
"alpha_frac": 0.5738908395,
"autogenerated": false,
"ratio": 3.3329787234042554,
"config_test": true,
"has_... |
__authors__ = "Ian Goodfellow, David Warde-Farley"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow, David Warde-Farley"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"
from pylearn2.testing.skip import skip_if_no_gpu
skip_if_... | {
"repo_name": "shiquanwang/pylearn2",
"path": "pylearn2/sandbox/cuda_convnet/tests/test_common.py",
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"size": "2802",
"license": "bsd-3-clause",
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"ratio": 3.79... |
__authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"
from pylearn2.models.model import Model
from pylearn2.utils import sharedX
import numpy as np
impo... | {
"repo_name": "jamessergeant/pylearn2",
"path": "pylearn2/models/mnd.py",
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"size": "4148",
"license": "bsd-3-clause",
"hash": 1736454755651706400,
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"line_max": 108,
"alpha_frac": 0.543876567,
"autogenerated": false,
"ratio": 3.222999222999223,
"config_t... |
__authors__ = ["Ian Goodfellow", "Vincent Dumoulin"]
__copyright__ = "Copyright 2012-2013, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "Ian Goodfellow"
import time
import warnings
import numpy as np
from theano import tensor as T, function, config
import thea... | {
"repo_name": "thompsonj/deepspeechsynthesis",
"path": "layer.py",
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"line_mean": 29.6543240557,
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"autogenerated": false,
"ratio": 4.000810845874416,
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from OpenGL.GL import GL_ARRAY_BUFFER, GL_DYNAMIC_DRAW, glFlush
import pyopencl as cl
import sys
import numpy
class CLKernel(object):
def __init__(self, filename):
plats = cl.get_platforms()
from pyopencl.tools import get_gl_sharing_context_properties
import sys
if ... | {
"repo_name": "cjld/adventures_in_opencl",
"path": "experiments/reduce/clutil.py",
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"alpha_frac": 0.528835691,
"autogenerated": false,
"ratio": 4.205949656750572,
"config_tes... |
__author__ = 'sibirrer'
# description of the polar shapelets in potential space
import numpy as np
import math
import numpy.polynomial.hermite as hermite
class CartShapelets(object):
"""
this class contains the function and the derivatives of the cartesian shapelets
"""
def function(self, x, y, coe... | {
"repo_name": "sibirrer/astrofunc",
"path": "astrofunc/LensingProfiles/shapelet_pot_2.py",
"copies": "1",
"size": "8671",
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"hash": -1789807527746215000,
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"line_max": 174,
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"autogenerated": false,
"ratio": 3.1599854227405246,
... |
__author__ = 'sibirrer'
# description of the polar shapelets in potential space
import numpy as np
import scipy.special
import math
import astrofunc.util as util
class PolarShapelets(object):
"""
this class contains the function and the derivatives of the Singular Isothermal Sphere
"""
def __init__(... | {
"repo_name": "sibirrer/astrofunc",
"path": "astrofunc/LensingProfiles/shapelet_pot.py",
"copies": "1",
"size": "9958",
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"hash": 7851743750203683000,
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"alpha_frac": 0.5248041775,
"autogenerated": false,
"ratio": 3.2864686468646864,
"con... |
__author__ = 'sibirrer'
#file which contains class for lens model routines
class LensModel(object):
"""
class for handling different lens models
"""
def __init__(self, lens_type):
if lens_type == 'SIS':
from easylens.FunctionSet.sis import SIS
self.func = SIS()
... | {
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"path": "easylens/DeLens/lens_model.py",
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__author__ = 'sibirrer'
from astrofunc.LensingProfiles.shapelet_pot import PolarShapelets
from astrofunc.LensingProfiles.shapelet_pot_2 import CartShapelets
import numpy as np
import numpy.testing as npt
import pytest
class TestPolarShapelets(object):
"""
tests the Gaussian methods
"""
def setup(sel... | {
"repo_name": "sibirrer/astrofunc",
"path": "test/test_shapelet_pot.py",
"copies": "1",
"size": "2221",
"license": "mit",
"hash": 7762030565547535000,
"line_mean": 26.775,
"line_max": 75,
"alpha_frac": 0.5416479063,
"autogenerated": false,
"ratio": 2.997300944669366,
"config_test": true,
"has... |
__author__ = 'sibirrer'
from astrofunc.LensingProfiles.sis_truncate import SIS_truncate
import numpy as np
import pytest
class TestSIS_truncate(object):
"""
tests the Gaussian methods
"""
def setup(self):
self.SIS = SIS_truncate()
def test_function(self):
x = np.array([1])
... | {
"repo_name": "sibirrer/astrofunc",
"path": "test/test_sis_truncate.py",
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"size": "2375",
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"config_test": tru... |
__author__ = 'sibirrer'
from astrofunc.LensingProfiles.spep import SPEP
from astrofunc.LensingProfiles.spp import SPP
from astrofunc.LensingProfiles.sis import SIS
import numpy as np
import numpy.testing as npt
import pytest
class TestSPEP(object):
"""
tests the Gaussian methods
"""
def setup(self):
... | {
"repo_name": "sibirrer/astrofunc",
"path": "test/test_spp.py",
"copies": "1",
"size": "4841",
"license": "mit",
"hash": 4501388276592535000,
"line_mean": 36.2461538462,
"line_max": 83,
"alpha_frac": 0.5224127246,
"autogenerated": false,
"ratio": 2.3603120429058997,
"config_test": true,
"has_... |
__author__ = 'sibirrer'
from astrofunc.LensingProfiles.spp import SPP
from astrofunc.LensingProfiles.spemd_smooth import SPEMD_SMOOTH
class SPEMD(object):
"""
class for smooth power law ellipse mass density profile
"""
def __init__(self):
self.s2 = 0.00000001
self.spp = SPP()
... | {
"repo_name": "sibirrer/astrofunc",
"path": "astrofunc/LensingProfiles/spemd.py",
"copies": "1",
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"line_max": 105,
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"autogenerated": false,
"ratio": 2.9655831739961758,
"config_t... |
__author__ = 'sibirrer'
from easylens.DeLens.de_lens import DeLens
from easylens.FunctionSet.shapelets import Shapelets
import numpy as np
class DeLensMultiBand(DeLens):
"""
multi-band reconstruction
"""
def get_param_WLS_multi_band(self, A_list, C_D_inv_list, d_list, w_SED, inv_bool=True):
... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/DeLens/de_lens_multi_band.py",
"copies": "1",
"size": "4360",
"license": "mit",
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"autogenerated": false,
"ratio": 3.2708177044261064,
"config_t... |
__author__ = 'sibirrer'
from easylens.DeLens.de_lens import DeLens
import numpy as np
class DeLensMultiExp(DeLens):
"""
class to deal with multiple exposures of the same band
"""
def get_param_WLS_multi(self, A_list, C_D_inv_list, d_list, inv_bool=True):
"""
returns the parameter val... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/DeLens/de_lens_multi_exposure.py",
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"size": "1332",
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"ratio": 3.1714285714285713,
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__author__ = 'sibirrer'
from scipy import fftpack
import numpy as np
import util
class Correlation(object):
"""
class to analyse correlations in an image or in the residuals
"""
def correlation_2D(self, image):
"""
:param residuals:
:return:
"""
# Take the fou... | {
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"autogenerated": false,
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__author__ = 'sibirrer'
import astrofunc.util as util
import numpy as np
class ExternalShear_old(object):
"""
class to deal with external shear. We do not include external convergence at this stage
"""
def function(self, x, y, gamma_ext, psi_ext):
# change to polar coordinates
theta, ... | {
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"... |
__author__ = 'sibirrer'
import easylens.util as util
import numpy as np
class ExternalShear(object):
"""
new class for external shear e1, e2 expression
"""
def function(self, x, y, e1, e2):
# change to polar coordinates
psi_ext, gamma_ext = util.ellipticity2phi_gamma(e1, e2)
t... | {
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"path": "easylens/FunctionSet/external_shear.py",
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"autogenerated": false,
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__author__ = 'sibirrer'
import MultiLens.Utils.constants as const
import numpy as np
class PointMass(object):
"""
class to compute the physical deflection angle of a point mass, given as an Einstein radius
"""
def __init__(self):
self.r_min = 10**(-8)
# alpha = 4*const.G * (mass*const... | {
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__author__ = 'sibirrer'
import numpy as np
from fastell4py import fastell4py
from astrofunc.LensingProfiles.spp import SPP
class SPEMD_SMOOTH(object):
"""
class for smooth power law ellipse mass density profile
"""
def __init__(self):
self.spp = SPP()
def _parameter_constraints(self, the... | {
"repo_name": "sibirrer/astrofunc",
"path": "astrofunc/LensingProfiles/spemd_smooth.py",
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__author__ = 'sibirrer'
import numpy as np
from fastell4py import fastell4py
import easylens.util as util
from easylens.FunctionSet.external_shear import ExternalShear
class SPEMD(object):
"""
class for smooth power law ellipse mass density profile
"""
def __init__(self):
self.s2 = 0.01
d... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/FunctionSet/spemd.py",
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"autogenerated": false,
"ratio": 2.428826257581163,
"config_test": fa... |
__author__ = 'sibirrer'
import numpy as np
import astropy.wcs as pywcs
import astropy.io.fits as pyfits
def array2image(array):
"""
returns the information contained in a 1d array into an n*n 2d array (only works when lenght of array is n**2)
:param array: image values
:type array: array of size n**... | {
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"has_... |
__author__ = 'sibirrer'
import numpy as np
import astropy.wcs as pywcs
import easylens.util as util
class LensSystem(object):
"""
data class for handling the different exposures/bands of an object
"""
def __init__(self, name, ra, dec):
self.name = name
self.available_frames = []
... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/Data/lens_system.py",
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"autogenerated": false,
"ratio": 3.544943820224719,
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__author__ = 'sibirrer'
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid, make_axes_locatable
import easylens.util as util
class ShowLens(object):
"""
class to plot the lens system
"""
def __init__(self, lensSystem):
"""
:param lensDES:... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/Data/show_lens.py",
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__author__ = 'sibirrer'
import numpy as np
import numpy.polynomial.hermite as hermite
import math
import scipy.interpolate as interpolate
class Shapelets(object):
"""
"""
def __init__(self, interpolation=False, precalc=True):
"""
load interpolation of the Hermite polynomials in a range [-... | {
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"autogenerated": false,
"ratio": 3.2870036101083033,
"config_test... |
__author__ = 'sibirrer'
import numpy as np
import numpy.polynomial.hermite as hermite
import math
import astrofunc.util as util
class Shapelets(object):
"""
"""
def __init__(self, interpolation=False, precalc=True):
"""
load interpolation of the Hermite polynomials in a range [-30,30] in... | {
"repo_name": "sibirrer/astrofunc",
"path": "astrofunc/LightProfiles/shapelets.py",
"copies": "1",
"size": "8688",
"license": "mit",
"hash": -8809175969699259000,
"line_mean": 33.2047244094,
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"autogenerated": false,
"ratio": 3.2551517422255527,
"confi... |
__author__ = 'sibirrer'
import numpy as np
import pickle
import os.path
from scipy import integrate
import astrofunc.util as util
class BarkanaIntegrals(object):
def I1(self, nu1, nu2, s_, gamma):
"""
integral of Barkana et al. (18)
:param nu2:
:param s_:
:param gamma:
... | {
"repo_name": "sibirrer/astrofunc",
"path": "astrofunc/LensingProfiles/barkana_integrals.py",
"copies": "1",
"size": "6043",
"license": "mit",
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"ratio": 3.0184815184815186,... |
__author__ = 'sibirrer'
import numpy as np
import scipy.ndimage.interpolation as interp
import astropy.io.fits as pyfits
import pyextract.pysex as pysex
import easylens.util as util
class ImageAnalysis(object):
"""
class for analysis routines acting on a single image
"""
def __init__(self):
... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/Data/image_analysis.py",
"copies": "1",
"size": "7851",
"license": "mit",
"hash": 4386949266567468500,
"line_mean": 35.0137614679,
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"alpha_frac": 0.5596739269,
"autogenerated": false,
"ratio": 3.350832266325224,
"config_test": f... |
__author__ = 'sibirrer'
import numpy as np
import sys
import scipy.ndimage as ndimage
import scipy.signal as signal
from easylens.FunctionSet.shapelets import Shapelets
import easylens.util as util
class DeLens(object):
"""
class for the de-lensing algorithm
"""
def __init__(self):
self.sha... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/DeLens/de_lens.py",
"copies": "1",
"size": "6737",
"license": "mit",
"hash": 306186146530633800,
"line_mean": 35.2204301075,
"line_max": 149,
"alpha_frac": 0.542526347,
"autogenerated": false,
"ratio": 3.465534979423868,
"config_test": false,
... |
__author__ = 'sibirrer'
import numpy as np
class SIS(object):
"""
this class contains the function and the derivatives of the Singular Isothermal Sphere
"""
def function(self, x, y, phi_E, center_x=0, center_y=0):
x_shift = x - center_x
y_shift = y - center_y
f_ = phi_E * np.sq... | {
"repo_name": "DES-SL/EasyLens",
"path": "easylens/FunctionSet/sis.py",
"copies": "1",
"size": "2708",
"license": "mit",
"hash": -1706052903300190200,
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"line_max": 90,
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"autogenerated": false,
"ratio": 2.754832146490336,
"config_test": false,
"has... |
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