text stringlengths 0 1.05M | meta dict |
|---|---|
from astropy import wcs as pywcs
try:
import astropy.io.fits as pyfits
except:
# If this fail there is no way out
import pyfits
pass
import numpy
from Box import Box
class XMMWCS(object):
def __init__(self, eventFile, X=None, Y=None):
header = pyfits.getheader(eventFile, 'EVENTS')
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from scipy import interpolate
from sklearn.neighbors import KernelDensity
from astroML.density_estimation import KNeighborsDensity
import numpy
import matplotlib.pyplot as plt
import sys
class DensityEstimation(object):
def __init__(self):
raise NotImplemented("This class must be subclassed.")
... | {
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"path": "XtDac/DivideAndConquer/KDE.py",
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import logging
import sys
import numexpr
import numpy as np
from threeML.io.progress_bar import progress_bar
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("bayesian_blocks")
__all__ = ['bayesian_blocks', 'bayesian_blocks_not_unique']
def bayesian_blocks_not_unique(tt, ttstart, ttstop, p0):
... | {
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"path": "threeML/utils/bayesian_blocks.py",
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import numpy
class GridGen(object):
'''
Generate a grid in detector coordinates
'''
def __init__(self, hardwareUnit):
# Store hardware unit
self.hardwareUnit = hardwareUnit
def makeGrid(self, approxSizeArcsec=80.35, unit='sky', multiplicity=2.0, get_psf_size=None):
# Co... | {
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import os
import sys
import numpy
import numexpr
try:
import scipy.stats
except:
pass
try:
import astropy.io.fits as pyfits
except:
# If this fail there is no way out
import pyfits
pass
from XtDac.BayesianBlocks import bayesian_blocks, bayesian_blocks_not_unique
class Box(object):
def __... | {
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import urllib, base64
import StringIO
import matplotlib.pyplot as plt
import time
import numpy
htmlCode1 = '''
<html>
<head>
<style>
.CSSTableGenerator {
margin:0px;padding:0px;
width:100%;
box-shadow: 10px 10px 5px #888888;
border:1px solid #000000;
-moz-border-radius-bottomleft:10px;
-webkit-border-bottom-l... | {
"repo_name": "giacomov/XtDac",
"path": "XtDac/DivideAndConquer/Results.py",
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try:
import astropy.io.fits as pyfits
except:
import pyfits
import logging
import subprocess
from XtDac.DivideAndConquer import XMMWCS
log = logging.getLogger("HardwareUnit")
def hardwareUnitFactory(eventfile):
'''Return an instance of the appropriate HarwareUnit class,
based on the content of the... | {
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__author__ = 'giacomov'
__doc__ = """"""
import collections
import copy
import exceptions
import astropy.units as u
import numpy as np
import scipy.stats
import warnings
from tree import Node
from thread_safe_unit_format import ThreadSafe
def _behaves_like_a_number(obj):
"""
:param obj:
:return: True... | {
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__author__ = 'giacomov'
from astromodels.core.polarization import Polarization
from astromodels.core.tree import Node
class SpectralComponent(Node):
# This is needed to avoid problems when constructing the class, due to the fact that we are overriding
# the __setattr__ and __getattr__ attributes
_spect... | {
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__author__ = 'giacomov'
from astromodels.core.tree import Node
from astromodels.core.parameter import Parameter
class Polarization(Node):
def __init__(self, polarization_type='linear'):
assert polarization_type in ['linear', 'stokes'], 'polarization must be linear or stokes'
self._polarization... | {
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__author__ = 'giacomov'
import astropy.table
def dict_to_table(dictionary, list_of_keys=None):
"""
Return a table representing the dictionary.
:param dictionary: the dictionary to represent
:param list_of_keys: optionally, only the keys in this list will be inserted in the table
:return: a Table... | {
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__author__ = 'giacomov'
import collections
import exceptions
import astropy.units as u
from astromodels.core.tree import Node
from astromodels.utils.pretty_list import dict_to_list
# This module keeps the configuration of the units used in astromodels
# Pre-defined values
_ENERGY = u.keV
_TIME = u.s
_ANGLE = u.de... | {
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__author__ = 'giacomov'
import collections
import exceptions
PARTICLE_SOURCE = 'particle source'
POINT_SOURCE = 'point source'
EXTENDED_SOURCE = 'extended source'
class UnknownSourceType(exceptions.Exception):
pass
class Source(object):
def __init__(self, list_of_components, src_type, spatial_shape=None)... | {
"repo_name": "giacomov/astromodels",
"path": "astromodels/sources/source.py",
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__author__ = 'giacomov'
import collections
from astropy import coordinates
from astromodels.core.parameter import Parameter
from astromodels.core.tree import Node
class WrongCoordinatePair(ValueError):
pass
class IllegalCoordinateValue(ValueError):
pass
class WrongCoordinateSystem(ValueError):
pass... | {
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"path": "astromodels/core/sky_direction.py",
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__author__ = 'giacomov'
import collections
import numpy
from astromodels.core.spectral_component import SpectralComponent
from astromodels.core.tree import Node
from astromodels.core.units import get_units
from astromodels.sources.source import Source, PARTICLE_SOURCE
from astromodels.utils.pretty_list import dict_t... | {
"repo_name": "grburgess/astromodels",
"path": "astromodels/sources/particle_source.py",
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__author__ = 'giacomov'
import collections
import os
import pandas as pd
import numpy as np
import scipy.integrate
import warnings
from astromodels.core.my_yaml import my_yaml
from astromodels.core.parameter import Parameter, IndependentVariable
from astromodels.core.tree import Node, DuplicatedNode
from astromodels... | {
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"path": "astromodels/core/model.py",
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__author__ = 'giacomov'
import collections
import ROOT
import numpy as np
import scipy.integrate
import astromodels
from threeML.io.cern_root_utils.io_utils import get_list_of_keys, open_ROOT_file
from threeML.io.cern_root_utils.tobject_to_numpy import tgraph_to_arrays, th2_to_arrays, tree_to_ndarray
from threeML.p... | {
"repo_name": "volodymyrss/3ML",
"path": "threeML/plugins/VERITASLike.py",
"copies": "1",
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"license": "bsd-3-clause",
"hash": -5048622252776983000,
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"alpha_frac": 0.5610217055,
"autogenerated": false,
"ratio": 3.8316875137151634,
"conf... |
__author__ = 'giacomov'
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
def plot_fit_results(time_resolved_results, redshift, triggername, decay_function=None, flux_type='photonFlux'):
fig, (ax1, ax2) = plt.subplots(2,1, sharex=True, gridspec_kw={'height_ratios': [3, 1... | {
"repo_name": "giacomov/lclike",
"path": "lclike/plot_fit_results.py",
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"config_tes... |
__author__ = 'giacomov'
import numpy as np
import emcee
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import corner
class BayesianAnalysis(object):
def __init__(self, parameter_names, best_fit_values, loglike, boundaries):
self.parameter_names = parameter_names
self.l... | {
"repo_name": "giacomov/lclike",
"path": "lclike/bayes_analysis.py",
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"autogenerated": false,
"ratio": 3.670147954743255,
"config_test":... |
__author__ = 'giacomov'
import re
import warnings
from astromodels.core import parameter, sky_direction, model, polarization, spectral_component
from astromodels.core.my_yaml import my_yaml
from astromodels.functions import function
from astromodels.sources import extended_source
from astromodels.sources import parti... | {
"repo_name": "grburgess/astromodels",
"path": "astromodels/core/model_parser.py",
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"autogenerated": false,
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__author__ = 'giacomov'
import yaml
import re
def _process_html(dictionary):
list_start = '<ul>\n'
list_stop = '</ul>\n'
entry_start = '<li>'
entry_stop = '</li>\n'
output=[list_start]
for key,value in dictionary.iteritems():
if isinstance(value, dict):
# Check whethe... | {
"repo_name": "grburgess/astromodels",
"path": "astromodels/utils/pretty_list.py",
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"size": "1618",
"license": "bsd-3-clause",
"hash": 8465131562287364000,
"line_mean": 20.8648648649,
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"autogenerated": false,
"ratio": 3.8250591016548463,
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__author__ = 'Giampaolo Rodola <g.rodola [AT] gmail [DOT] com>'
"""
Return disk usage statistics about the given path as a (total, used, free)
namedtuple. Values are expressed in bytes.
"""
# Author: Giampaolo Rodola' <g.rodola [AT] gmail [DOT] com>
# License: MIT
import os
import collections
_ntuple_diskusage = co... | {
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"path": "astromodels/utils/disk_usage.py",
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__author__ = 'Gianluca Barbon'
from asip_client import AsipClient
from asip_writer import AsipWriter
import threading
from threading import Thread
import socket
import time
import sys
class TCPBoard:
# ************ BEGIN CONSTANTS DEFINITION ****************
DEBUG = True # Activates debug messages
_... | {
"repo_name": "DiNozzo97/smartHome",
"path": "Source Code/assets/pythonFiles/python_asip_client/tcp_board.py",
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__author__ = 'Gianluca Barbon'
from services.asip_service import AsipService
from asip_client import AsipClient
import sys
class SparkfunWSService(AsipService):
class Pressure(AsipService):
_serviceID = 'P'
DEBUG = False
_pressureID = 0
# The service should be attached to a clie... | {
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"path": "Source Code/assets/pythonFiles/python_asip_client/services/sparkfunws_service.py",
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__author__ = 'Gianluca Barbon'
import sys
import struct
import binascii
class PortManager:
# ************ BEGIN CONSTANTS DEFINITION ****************
__DEBUG = False # Do you want me to print verbose debug information?
__MAX_NUM_DIGITAL_PINS = 72 # 9 ports of 8 pins at most?
__MAX_NUM_ANALOG_PINS... | {
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__author__ = 'Gianluca Barbon'
import time
import sys
from asip_client import AsipClient
from threading import Thread
from asip_writer import AsipWriter
import paho.mqtt.client as mqtt
import threading
class MQTTBoard:
# ************ BEGIN CONSTANTS DEFINITION ****************
DEBUG = True # Activates d... | {
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"path": "Source Code/assets/pythonFiles/python_asip_client/mqtt_board.py",
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__author__ = 'Gianluca Barbon'
import time
import sys
from asip_client import AsipClient
from threading import Thread
import threading
from asip_writer import AsipWriter
import socket
try:
from Queue import Queue
except ImportError:
from queue import Queue
class SimpleTCPBoard:
# ************ BEGIN CON... | {
"repo_name": "DiNozzo97/smartHome",
"path": "Source Code/assets/pythonFiles/python_asip_client/old_tcp_board.py",
"copies": "1",
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"ratio... |
__author__ = 'Gianluca Barbon'
import time
import sys
from asip_client import AsipClient
from threading import Thread
try:
from Queue import Queue
except ImportError:
from queue import Queue
from asip_writer import AsipWriter
import paho.mqtt.client as mqtt
class SimpleMQTTBoard:
# ************ BEGIN ... | {
"repo_name": "DiNozzo97/smartHome",
"path": "Source Code/assets/pythonFiles/python_asip_client/old_mqtt_board.py",
"copies": "1",
"size": "9264",
"license": "mit",
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"ratio... |
__author__ = 'Gianluca Barbon'
import time
import sys
import glob
import serial
from asip_client import AsipClient
from threading import Thread
from asip_writer import AsipWriter
from serial import Serial
import threading
class SerialBoard:
# ************ BEGIN CONSTANTS DEFINITION ****************
DEBUG... | {
"repo_name": "DiNozzo97/smartHome",
"path": "Source Code/assets/pythonFiles/python_asip_client/serial_board.py",
"copies": "1",
"size": "10864",
"license": "mit",
"hash": 8142738248764015000,
"line_mean": 41.1085271318,
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"autogenerated": false,
"ratio":... |
__author__ = 'Gianluca Barbon'
import time
import sys
import glob
import serial
import select
from asip_client import AsipClient
from threading import Thread
#from Queue import Queue
from asip_writer import AsipWriter
from serial import Serial
try:
from Queue import Queue
except ImportError:
from queue import ... | {
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__author__ = "Gideon Juve"
__author__ = "Rafael Ferreira da Silva"
DB_VERSION = 3
import logging
from sqlalchemy.exc import *
from Pegasus.db.admin.admin_loader import *
from Pegasus.db.admin.versions.base_version import *
log = logging.getLogger(__name__)
class Version(BaseVersion):
def __init__(self, conne... | {
"repo_name": "pegasus-isi/pegasus",
"path": "packages/pegasus-python/src/Pegasus/db/admin/versions/v3.py",
"copies": "1",
"size": "1096",
"license": "apache-2.0",
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"ratio"... |
__author__ = 'gigi'
RANGE_SIZE = 100
primes = [2, 3, 5, 7]
last_range_start = None
def get_next_range():
global last_range_start
if last_range_start is None:
last_range_start = 10
else:
last_range_start += RANGE_SIZE
return last_range_start, last_range_start + RANGE_SIZE
def chec... | {
"repo_name": "the-gigi/prime_hunter",
"path": "simple_prime_hunter.py",
"copies": "1",
"size": "1382",
"license": "bsd-3-clause",
"hash": 3792189010379183000,
"line_mean": 22.4237288136,
"line_max": 77,
"alpha_frac": 0.6078147612,
"autogenerated": false,
"ratio": 3.455,
"config_test": false,
... |
__author__ = 'gilbert'
"""
Based off of q controller from here:
http://pages.cs.wisc.edu/~finton/qcontroller.html
"""
import gym
import random
import numpy as np
class QAgent:
def __init__(self):
#Constants
self.W_INIT = 0.0
self.NUM_BOXES = 162
self.ALPHA = 0.5 #Learning Rate... | {
"repo_name": "nerdgilbert/CartQLearner",
"path": "main.py",
"copies": "1",
"size": "3900",
"license": "mit",
"hash": 4394674882935223000,
"line_mean": 25.3513513514,
"line_max": 161,
"alpha_frac": 0.5387179487,
"autogenerated": false,
"ratio": 3.439153439153439,
"config_test": false,
"has_no... |
"""
A command line tool that allows a user to convert
a directory of raw images into "batches" for use in
the SMIA-CUKIE application.
Parsing used here is specific to the Cukierman lab
use cases, but could be used as an example of the proper
format to feed into the SMIA-CUKIE application (and how
to automate this p... | {
"repo_name": "cukie/SMIA",
"path": "batch_maker/make_batches.py",
"copies": "2",
"size": "2813",
"license": "mit",
"hash": -2483268559641314300,
"line_mean": 25.5377358491,
"line_max": 101,
"alpha_frac": 0.698186989,
"autogenerated": false,
"ratio": 3.060935799782372,
"config_test": false,
"... |
__author__ = 'Gino'
import os
import time
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from common import domain
# Parametrizing the sleep allow me to set run "more defensive" tests wh... | {
"repo_name": "GinoGalotti/python-selenium-utils",
"path": "SeleniumPythonFramework/src/main/Utils/driver_utils.py",
"copies": "1",
"size": "4838",
"license": "apache-2.0",
"hash": -1724035317175957200,
"line_mean": 26.6457142857,
"line_max": 103,
"alpha_frac": 0.6593633733,
"autogenerated": false,... |
__author__ = 'Gino'
import sys
from sauceclient import SauceClient
class SauceUtils(object):
SAUCE_URL = "http://%s:%s@ondemand.saucelabs.com:80/wd/hub"
def __init__(self, user, password, tool):
self.is_sauce = (tool and tool.lower() == 'sauce')
if self.is_sauce:
self.user = use... | {
"repo_name": "GinoGalotti/python-selenium-utils",
"path": "SeleniumPythonFramework/src/main/Utils/sauce_utils.py",
"copies": "1",
"size": "1540",
"license": "apache-2.0",
"hash": 2735905147825356000,
"line_mean": 33.2222222222,
"line_max": 80,
"alpha_frac": 0.6266233766,
"autogenerated": false,
... |
__author__ = 'Gino'
import sys
from testingbotclient import TestingBotClient
class TestingbotUtils(object):
TESTINGBOT_URL = "http://%s:%s@hub.testingbot.com:4444/wd/hub"
def __init__(self, user, password, tool):
self.is_testingbot = (tool and tool.lower() == 'testingbot')
if self.is_testin... | {
"repo_name": "GinoGalotti/python-selenium-utils",
"path": "SeleniumPythonFramework/src/main/Utils/testingbot_utils.py",
"copies": "1",
"size": "1637",
"license": "apache-2.0",
"hash": -6979860740281304000,
"line_mean": 33.829787234,
"line_max": 110,
"alpha_frac": 0.6365302382,
"autogenerated": fal... |
__author__ = 'Giorgio Salluzzo <giorgio.salluzzo@gmail.com>'
__version__ = '1.99.1'
__classifiers__ = [
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Operating System :: OS Independent',
'Programming Language :: Python ::... | {
"repo_name": "BuongiornoMIP/Reding",
"path": "reding/__init__.py",
"copies": "1",
"size": "2440",
"license": "mit",
"hash": 2980704070485400600,
"line_mean": 44.1851851852,
"line_max": 479,
"alpha_frac": 0.6897540984,
"autogenerated": false,
"ratio": 4,
"config_test": false,
"has_no_keywords... |
# This program sets up a stash repository from a configuration file
import requests
import json
import yaml
import sys
import re
import time
import os
# The following class handles REST requests(and thus the name)
class rester:
def __init__(self, config):
self.config = config
self.http_host = s... | {
"repo_name": "Verigreen/stash",
"path": "stash_setup.py",
"copies": "1",
"size": "10985",
"license": "apache-2.0",
"hash": -1853351953107042000,
"line_mean": 34.5533980583,
"line_max": 105,
"alpha_frac": 0.5259899863,
"autogenerated": false,
"ratio": 4.181575942139323,
"config_test": true,
"... |
__author__ = 'Giovanni Sirio Carmantini'
"""In this file, a R-ANN is constructed from a sample Turing Machine.
Specifically, the TM decides if an input unary string is composed by
an even number of 1's.
A Generalized Shift is first created from the TM description.
Subsequently, an NDA simulating the GS dynamics is c... | {
"repo_name": "TuringMachinegun/Turing_Neural_Networks",
"path": "examples/even_vs_odd_tm.py",
"copies": "1",
"size": "4069",
"license": "mit",
"hash": -7844980483572467000,
"line_mean": 32.6280991736,
"line_max": 74,
"alpha_frac": 0.5959695257,
"autogenerated": false,
"ratio": 2.957122093023256,... |
__author__ = 'Giovanni Sirio Carmantini'
"""In this file, a R-ANN is constructed from a Turing Machine which
dynamics reproduce two gait pattern sequences, depending on the
machine control state.
A Generalized Shift is first created from the TM description.
Subsequently, an NDA simulating the GS dynamics is created.
... | {
"repo_name": "TuringMachinegun/Turing_Neural_Networks",
"path": "examples/central_pattern_generator_tm.py",
"copies": "1",
"size": "6040",
"license": "mit",
"hash": 5721827639834132000,
"line_mean": 32.7430167598,
"line_max": 74,
"alpha_frac": 0.6216887417,
"autogenerated": false,
"ratio": 2.698... |
__author__ = 'Giovanni Sirio Carmantini'
"""In this file we reproduce the simple parser from beim Graben, P.,
& Potthast, R. (2014). Universal neural field computation. In Neural
Fields (pp. 299-318).
First, the Context Free Grammar is used to create a Generalized Shift,
an NDA simulating the GS is then created, th... | {
"repo_name": "TuringMachinegun/Turing_Neural_Networks",
"path": "examples/context_free_grammar_simple_parser.py",
"copies": "1",
"size": "3060",
"license": "mit",
"hash": -4310432898095315500,
"line_mean": 29.6,
"line_max": 74,
"alpha_frac": 0.6006535948,
"autogenerated": false,
"ratio": 2.95081... |
__author__ = 'Giovanni Sirio Carmantini'
__version__ = 0.1
import numpy as np
from collections import defaultdict
class AbstractNNLayer(object):
"""
The base class for all neuron layers. Each layer has to implement the possibility to
add connections from other layers,
to compute the input to each neu... | {
"repo_name": "TuringMachinegun/Turing_Neural_Networks",
"path": "simpleNNlib.py",
"copies": "1",
"size": "5683",
"license": "mit",
"hash": 5148833374582724000,
"line_mean": 37.9246575342,
"line_max": 123,
"alpha_frac": 0.6714763329,
"autogenerated": false,
"ratio": 3.9880701754385965,
"config_... |
__author__ = 'Giovanni Sirio Carmantini'
__version__ = 0.1
import simpleNNlib as snn
import numpy as np
class NeuralTM():
"""Given an NDA, constructs the equivalent neural network described in
our submitted paper.
:param nda: a symdyn.NonlinearDynamicalAutomaton object
"""
def __init__(self, ... | {
"repo_name": "TuringMachinegun/Turing_Neural_Networks",
"path": "neuraltm.py",
"copies": "1",
"size": "12401",
"license": "mit",
"hash": 5235028427116534000,
"line_mean": 35.1545189504,
"line_max": 79,
"alpha_frac": 0.5510039513,
"autogenerated": false,
"ratio": 3.5200113539596933,
"config_tes... |
__author__ = 'Giovanni Sirio Carmantini'
__version__ = 0.1
"""
"""
import numpy as np
import itertools as itt
def as_list(arg):
"""Convenience function used to make sure that a sequence is always
represented by a list of symbols. Sometimes a single-symbol
sequence is passed in the form of a string repr... | {
"repo_name": "TuringMachinegun/Turing_Neural_Networks",
"path": "symdyn.py",
"copies": "1",
"size": "17553",
"license": "mit",
"hash": 2560528922320449500,
"line_mean": 33.4176470588,
"line_max": 79,
"alpha_frac": 0.5780208511,
"autogenerated": false,
"ratio": 3.61619283065513,
"config_test": ... |
__author__ = 'gipmon'
import math
import time
from random import randint
import json
from instagram.client import InstagramAPI
class Bot:
def __init__(self, config_file, tags_file):
# Loading the configuration file, it has the access_token, user_id and others configs
self.config = json.load(confi... | {
"repo_name": "gipmon/instagram-bot",
"path": "bot/bot.py",
"copies": "2",
"size": "5214",
"license": "mit",
"hash": 5131013326245036000,
"line_mean": 39.1153846154,
"line_max": 120,
"alpha_frac": 0.4890678941,
"autogenerated": false,
"ratio": 3.8422991893883567,
"config_test": true,
"has_no_... |
__author__ = 'girish'
import argparse
def parse_args(args):
parser = argparse.ArgumentParser(description="reverse hashes of passwords")
parser.add_argument('--hash',type=str,help="The hash you want to reverse",required=True)
algorithm_group = parser.add_mutually_exclusive_group(required=True)
help_s = ... | {
"repo_name": "girishramnani/hacking-tools",
"path": "pyhashcat/pyhashcat/cli.py",
"copies": "3",
"size": "1279",
"license": "mit",
"hash": -5686245932541438000,
"line_mean": 52.2916666667,
"line_max": 118,
"alpha_frac": 0.7068021892,
"autogenerated": false,
"ratio": 3.4474393530997305,
"config... |
__author__ = 'girish'
import argparse
import os
import logging
import time
import hashlib
import csv
log = logging.getLogger('main._pfish')
global gl_args
global gl_hashType
def ValidateDirectory(theDir):
if not os.path.isdir(theDir):
raise argparse.ArgumentTypeError("Directory does not exist")
else:... | {
"repo_name": "girishramnani/hacking-tools",
"path": "file_hasher/_pfish_tools.py",
"copies": "3",
"size": "5301",
"license": "mit",
"hash": -935599104485104600,
"line_mean": 30.3668639053,
"line_max": 150,
"alpha_frac": 0.5589511413,
"autogenerated": false,
"ratio": 4.1674528301886795,
"config... |
__author__ = 'Girish'
import re
import json
from textwrap import wrap
try:
import urllib2 as request
from urllib import quote
except:
from urllib import request
from urllib.parse import quote
class Translator:
def __init__(self, to_lang, from_lang='auto'):
self.from_lang = from_lang
... | {
"repo_name": "JainamJhaveri/collegeProjects",
"path": "googleTranslate/Translator.py",
"copies": "3",
"size": "1366",
"license": "mit",
"hash": -3707500647423959000,
"line_mean": 34.0256410256,
"line_max": 156,
"alpha_frac": 0.6251830161,
"autogenerated": false,
"ratio": 3.475826972010178,
"co... |
__author__ = 'girish'
import time
import sys
import cli
import keyGenerator
import Hasher
def choose_key_generator(arguments):
if arguments.chars :
key_generator = keyGenerator.CharacterGenerator(arguments.chars)
elif arguments.num :
key_generator = keyGenerator.NumericGenerator(arguments.n... | {
"repo_name": "girishramnani/hacking-tools",
"path": "pyhashcat/pyhashcat/main.py",
"copies": "3",
"size": "1702",
"license": "mit",
"hash": -8856500707292794000,
"line_mean": 23.3142857143,
"line_max": 121,
"alpha_frac": 0.6398354877,
"autogenerated": false,
"ratio": 3.8419864559819414,
"confi... |
__author__ = 'Girish Ramnani'
"""
This program takes in a sudoku and solves it ,here 0 means not set so add numbers write them down
"""
'''trying the empty board '''
def moves(board, row, column):
"""
used set to i
:param board:
:param row:
:param column:
:return:list -> list of legal moves t... | {
"repo_name": "WiredProgrammers/collegeProjects",
"path": "sudoku_solver/Sudoku_test.py",
"copies": "3",
"size": "2251",
"license": "mit",
"hash": 9142518736691988000,
"line_mean": 22.4583333333,
"line_max": 97,
"alpha_frac": 0.5415370946,
"autogenerated": false,
"ratio": 3.3298816568047336,
"c... |
__author__ = 'github.com/kosior'
__license__ = 'MIT'
__version__ = '0.3.0'
import logging
try:
import readline # user input history
except ImportError:
pass
import signal
import sys
from . import settings
from .args import process_args
from .db import DB
from .render import HtmlFile
from .save import Multi,... | {
"repo_name": "kosior/taktyk",
"path": "taktyk/__init__.py",
"copies": "1",
"size": "1836",
"license": "mit",
"hash": -6035537428411863000,
"line_mean": 29.4333333333,
"line_max": 100,
"alpha_frac": 0.6380065717,
"autogenerated": false,
"ratio": 3.484732824427481,
"config_test": false,
"has_n... |
__author__ = 'github.com/phowat'
import tornado.web
from tornado.websocket import WebSocketHandler
from tornado.ioloop import IOLoop
import Queue
import json
from itertools import cycle
import base64
from passlib.apps import custom_app_context as sins_context
sessions = {}
queues = {}
pairs = {}
class SSession(objec... | {
"repo_name": "phowat/sins",
"path": "sins.py",
"copies": "1",
"size": "10483",
"license": "mit",
"hash": -1520758002368209400,
"line_mean": 33.2581699346,
"line_max": 141,
"alpha_frac": 0.5276161404,
"autogenerated": false,
"ratio": 4.189848121502798,
"config_test": false,
"has_no_keywords":... |
__author__ = 'github.com/samshadwell'
# Token constants
T_End = -1
T_Plus = 0
T_Minus = 1
T_Times = 2
T_Over = 3
T_Less = 4
T_Greater = 5
T_LParen = 10
T_RParen = 11
T_LBrace = 12
T_RBrace = 13
T_Is = 20
T_If = 21
T_Else = 22
T_True = 30
T_False = 31
T_And = 32
T_Or = 33
T_Not = 34
T_Word = 40
T_Num = 41
T_Quote ... | {
"repo_name": "samshadwell/TrumpScript",
"path": "src/trumpscript/constants.py",
"copies": "1",
"size": "2322",
"license": "mit",
"hash": -3315287347609310700,
"line_mean": 32.5942028986,
"line_max": 118,
"alpha_frac": 0.6363244176,
"autogenerated": false,
"ratio": 3.232914923291492,
"config_te... |
__author__ = 'github.com/samshadwell'
# Token constants
T_Plus = 0
T_Minus = 1
T_Times = 2
T_Over = 3
T_Less = 4
T_Greater = 5
T_LParen = 10
T_RParen = 11
T_LBrace = 12
T_RBrace = 13
T_Is = 20
T_If = 21
T_Else = 22
T_True = 30
T_False = 31
T_And = 32
T_Or = 33
T_Not = 34
T_Word = 40
T_Num = 41
T_Quote = 42
T_Make... | {
"repo_name": "cshaley/TrumpScript",
"path": "src/trumpscript/constants.py",
"copies": "1",
"size": "1360",
"license": "mit",
"hash": -4029283265133610500,
"line_mean": 27.25,
"line_max": 118,
"alpha_frac": 0.6268436578,
"autogenerated": false,
"ratio": 2.9671772428884027,
"config_test": false,... |
__author__ = 'gjlawran'
# an automated site survey of CKAN installations
# script visits each CKAN deployment and tries to determine the status, version, extensions and webserver
# script logs what it finds at each site and makes a summary of some observations
import requests
import json
import time
import logging
im... | {
"repo_name": "gjlawran/CKAN_Ecosystem",
"path": "harvest.py",
"copies": "1",
"size": "4090",
"license": "mit",
"hash": 7886121974230412000,
"line_mean": 34.8771929825,
"line_max": 113,
"alpha_frac": 0.6535452323,
"autogenerated": false,
"ratio": 3.8657844990548202,
"config_test": false,
"has... |
__author__ = 'gjones'
import numpy as np
from matplotlib import pyplot as plt
from kid_readout.equipment.hittite_controller import hittiteController
import rtlsdr
class RtlKidReadout(object):
def __init__(self,hittite_addr='192.168.1.70'):
self.hittite = hittiteController(addr=hittite_addr)
self.r... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "kid_readout/equipment/rtlkid.py",
"copies": "1",
"size": "2563",
"license": "bsd-2-clause",
"hash": 4568762549387746000,
"line_mean": 39.6825396825,
"line_max": 113,
"alpha_frac": 0.6383144752,
"autogenerated": false,
"ratio": 2.847777777777778,
... |
__author__ = 'gjones'
import numpy as np
from matplotlib import pyplot as plt
import joblib
import itertools
import os
import glob
from kid_readout.interactive import *
def validate_resonator(res):
if res.Q / np.abs(res.Q_e) < 0.01:
print "failed shallow"
return False
if res.Q_e_real < 1000:
... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "apps/data_analysis_scripts/heterodyne_resonator_search.py",
"copies": "1",
"size": "3556",
"license": "bsd-2-clause",
"hash": -711139026983391200,
"line_mean": 33.8725490196,
"line_max": 111,
"alpha_frac": 0.5992688414,
"autogenerated": false,
"ra... |
__author__ = 'gjones'
import time
import sys
import numpy as np
from kid_readout.roach import heterodyne
from kid_readout.utils import data_file, sweeps
from kid_readout.equipment import hittite_controller, lockin_controller
hittite = hittite_controller.hittiteController(addr='192.168.0.200')
lockin = lockin_contro... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "apps/data_taking_scripts/2015-10-jpl-park/sweep_and_stream_at_min_s21_two_groups.py",
"copies": "1",
"size": "5481",
"license": "bsd-2-clause",
"hash": -701342082463831200,
"line_mean": 32.8395061728,
"line_max": 116,
"alpha_frac": 0.6028097063,
"au... |
__author__ = 'gjones'
import time
import numpy as np
from matplotlib import pyplot as plt
import kid_readout.utils.acquire
import kid_readout.roach.baseband
import kid_readout.utils.data_file
import kid_readout.analysis.resonator.legacy_resonator
import kid_readout.analysis.iqnoise
ri = kid_readout.roach.baseband.R... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "apps/data_taking_scripts/old_scripts/sweep_and_stream.py",
"copies": "1",
"size": "2016",
"license": "bsd-2-clause",
"hash": -875367396299045900,
"line_mean": 28.6470588235,
"line_max": 150,
"alpha_frac": 0.7013888889,
"autogenerated": false,
"rat... |
__author__ = 'gjones'
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import mlab
from kid_readout.analysis.timeseries import filters
class CrossSpectralAnalysis(object):
def __init__(self,snm1=None,snm2=None):
if snm1 is not None:
self.get_data_from_snms(snm1,snm2)
... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "kid_readout/analysis/timeseries/cross_spectrum.py",
"copies": "1",
"size": "4530",
"license": "bsd-2-clause",
"hash": -7926873167301054000,
"line_mean": 46.6842105263,
"line_max": 128,
"alpha_frac": 0.6631346578,
"autogenerated": false,
"ratio": 2... |
__author__ = 'gjones'
import numpy as np
from matplotlib import pyplot as plt
import logging
from kid_readout.analysis import detect_peaks
from kid_readout.analysis.resonator import lmfit_resonator
logger = logging.getLogger(__name__)
def find_resonators(frequency, s21, s21_error, frequency_span=1e6, detect_peaks_t... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "kid_readout/analysis/resonator/find_resonators.py",
"copies": "1",
"size": "4735",
"license": "bsd-2-clause",
"hash": -3027341216642132000,
"line_mean": 38.7983193277,
"line_max": 169,
"alpha_frac": 0.6209081309,
"autogenerated": false,
"ratio": 2... |
__author__ = 'gjones'
import time
import numpy as np
from kid_readout.measurement.io.data_block import SweepData, DataBlock
def do_sweep(ri,center_freqs,offsets,nsamp,
nchan_per_step=8,reads_per_step=2,callback = None, sweep_data=None,
demod=True, loopback=False):
if nchan_per_step > cen... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "kid_readout/measurement/legacy/r2sweeps.py",
"copies": "1",
"size": "2673",
"license": "bsd-2-clause",
"hash": 6902617493196987000,
"line_mean": 40.78125,
"line_max": 131,
"alpha_frac": 0.5432098765,
"autogenerated": false,
"ratio": 3.466926070038... |
__author__ = 'gjones'
class MockRoach(object):
def __init__(self, host, port=7147, tb_limit=20, timeout=10.0, logger=None,
_fpga_clk=256.0, sleep_for_fake_data=False):
self._fpga_clk = _fpga_clk
self._is_programmed = False
self._boffile_list = []
self.sleep_for_fa... | {
"repo_name": "ColumbiaCMB/kid_readout",
"path": "kid_readout/roach/tests/mock_roach.py",
"copies": "1",
"size": "1758",
"license": "bsd-2-clause",
"hash": 6951783735958159000,
"line_mean": 26.0461538462,
"line_max": 119,
"alpha_frac": 0.5728100114,
"autogenerated": false,
"ratio": 3.447058823529... |
__author__ = 'gkisel'
import pprint as _pprint
import os
from robot.libraries.BuiltIn import BuiltIn
from robot.api import logger
_vars = None
_builtin = BuiltIn()
def pprint(data, level='INFO', html=False, console=False, repr=False):
if not isinstance(data, basestring):
data = _pprint.pformat(data)
... | {
"repo_name": "guykisel/robotframework-guyutils",
"path": "src/GuyUtils/keywords.py",
"copies": "1",
"size": "4960",
"license": "mit",
"hash": -8735608318638739000,
"line_mean": 30,
"line_max": 90,
"alpha_frac": 0.6163306452,
"autogenerated": false,
"ratio": 3.6904761904761907,
"config_test": f... |
__author__ = 'gk'
# Implements look up Table for user to ID and ID to user, as the end Result class for storing user rank and score
class ScreenNameIndex:
nameToIdMap = dict()
idToNameMap = dict()
def __init__(self,screen_names):
super().__init__()
id = 0
for item in screen_names:... | {
"repo_name": "ganesh-karthick/TwitterUserRanker",
"path": "PageRank/ScreenNameIndex.py",
"copies": "1",
"size": "1251",
"license": "apache-2.0",
"hash": 6825418838995320000,
"line_mean": 24.5306122449,
"line_max": 113,
"alpha_frac": 0.5651478817,
"autogenerated": false,
"ratio": 3.50420168067226... |
__author__ = 'gk'
import optparse
import os
from ParserUtils.Parser import Parser
from PageRank.TweetInfo import asTweetInfo,asPartialTweetInfo, TweetInfo
from PageRank.ScreenNameIndex import ScreenNameIndex,UserRank
from PageRank.TransitionProbablity import buildInitialStateMatrixInfo,buildLinkMatrixInfo,LinkMatrix,I... | {
"repo_name": "ganesh-karthick/TwitterUserRanker",
"path": "PageRank/main.py",
"copies": "1",
"size": "2579",
"license": "apache-2.0",
"hash": 3462898317297066500,
"line_mean": 30.0722891566,
"line_max": 153,
"alpha_frac": 0.7716169058,
"autogenerated": false,
"ratio": 3.485135135135135,
"confi... |
__author__ = 'gk'
# Parses JSON file contain Tweets in the following format per line
#
# {
# "text": "Over ongeveer een uur landt @MarsCuriosity op de rode planeet!",
# "created_at": "Mon Aug 06 04:29:10 +0000 2012",
# "entities": {
# "user_mentions": [
# {
# "indices": ... | {
"repo_name": "ganesh-karthick/TwitterUserRanker",
"path": "ParserUtils/Parser.py",
"copies": "1",
"size": "2318",
"license": "apache-2.0",
"hash": 6268023207333694000,
"line_mean": 28.3417721519,
"line_max": 149,
"alpha_frac": 0.5064710958,
"autogenerated": false,
"ratio": 3.184065934065934,
"... |
__author__ = 'gladson'
import json
import csv
import pandas as pd
def extract_stopwords(source):
with open(source, 'r') as json_file:
ugly_json = json_file.readlines()
formatted_json = []
stopwords = []
[formatted_json.append(json.loads(x)) for x in ugly_json]
[stopwords.append(formatted_j... | {
"repo_name": "gladsonvm/pycsvqna",
"path": "csvqna.py",
"copies": "1",
"size": "1172",
"license": "mit",
"hash": -6455281453344252000,
"line_mean": 34.5151515152,
"line_max": 100,
"alpha_frac": 0.6424914676,
"autogenerated": false,
"ratio": 3.617283950617284,
"config_test": false,
"has_no_ke... |
__author__ = 'Glenn and Lyman Hurd'
# Note two blank lines before each top-level (i.e., not part of a class) def.
WINNER_TUPLE = ((0, 1, 2), (0, 3, 6), (0, 4, 8), (1, 4, 7),
(3, 4, 5), (2, 5, 8), (6, 7, 8), (2, 4, 6))
def blank_list(board_string):
"""
Given a board string return a list of the... | {
"repo_name": "glennqhurd/TicTacToe",
"path": "boardutils.py",
"copies": "1",
"size": "3246",
"license": "mit",
"hash": 1569587717232760000,
"line_mean": 22.5217391304,
"line_max": 113,
"alpha_frac": 0.5628465804,
"autogenerated": false,
"ratio": 3.475374732334047,
"config_test": false,
"has_... |
__author__ = 'glevine@penguinrandomhouse.com'
from bs4 import BeautifulSoup
import urllib2
import csv
import pandas as pd
import time
import lxml
import datetime
import pickle
import requests
import re
import sys
import os
import pymongo
from retry import retry as _retry
from endpoints import Search_all
#from endpoin... | {
"repo_name": "gabelev/MISMI",
"path": "debug/AMZ_tracker_intake_debug.py",
"copies": "2",
"size": "10692",
"license": "mit",
"hash": 8129727054071956000,
"line_mean": 38.1684981685,
"line_max": 139,
"alpha_frac": 0.6408529742,
"autogenerated": false,
"ratio": 3.2687251605013756,
"config_test":... |
__author__ = 'glevine@penguinrandomhouse.com'
__version__ = 'MISMI 0.3'
from bs4 import BeautifulSoup
import urllib2
import time
import lxml
import csv
import requests
import re
import sys
import os
from retry import retry as _retry
from tracker_functions import Tracker
from reformat_functions import Reformat
from... | {
"repo_name": "gabelev/MISMI",
"path": "main.py",
"copies": "1",
"size": "2118",
"license": "mit",
"hash": 1486340179961946400,
"line_mean": 25.4875,
"line_max": 107,
"alpha_frac": 0.6293673277,
"autogenerated": false,
"ratio": 3.223744292237443,
"config_test": false,
"has_no_keywords": false... |
__author__ = 'gmazlami'
from django.contrib.auth.models import User
from rest_framework import authentication
from rest_framework import exceptions
from models import Device
class ApikeyAuthentication(authentication.BaseAuthentication):
def authenticate(self, request):
api_key = request.META.get('HTTP_A... | {
"repo_name": "probr/probr-core",
"path": "devices/authentication.py",
"copies": "1",
"size": "1061",
"license": "mit",
"hash": -156687738702545570,
"line_mean": 33.2580645161,
"line_max": 126,
"alpha_frac": 0.671065033,
"autogenerated": false,
"ratio": 4.348360655737705,
"config_test": false,
... |
__author__ = 'gmgilmore'
from tower_status_tracker import tower_status, barracks_status
def process_response(arr):
processed_response = map(get_match_info, arr)
return processed_response
def get_team_name(is_radiant, dota_side_obj):
if (is_radiant):
result = dota_side_obj.get(u"radiant_team",{})... | {
"repo_name": "ggilmore/DotaBlaze",
"path": "helpers.py",
"copies": "1",
"size": "1733",
"license": "mit",
"hash": -6561395707951362000,
"line_mean": 39.3023255814,
"line_max": 120,
"alpha_frac": 0.5966532025,
"autogenerated": false,
"ratio": 2.9725557461406518,
"config_test": false,
"has_no_... |
__author__ = 'gmgilmore'
import time
import event_types
class Game(object):
def __init__(self, match_id, *listeners):
self.id = match_id
self.game_events = [] # event = (time_stamp, event_type, event_description)
self.event_listeners = []
self.event_listeners.extend(*listeners)
... | {
"repo_name": "ggilmore/DotaBlaze",
"path": "game.py",
"copies": "1",
"size": "10871",
"license": "mit",
"hash": 767222837422434400,
"line_mean": 53.904040404,
"line_max": 137,
"alpha_frac": 0.4733695152,
"autogenerated": false,
"ratio": 4.091456529920963,
"config_test": false,
"has_no_keywor... |
__author__ = 'gmgilmore'
ANCIENT_TOWER_INDEX = 2
BOTTOM_TOWER_INDEX = 5
MIDDLE_TOWER_INDEX = 8
TOP_TOWER_INDEX = 11
BOTTOM_BARRACKS_INDEX = 2
MIDDLE_BARRACKS_INDEX = 4
TOP_BARRACKS_INDEX = 6
def get_side_string(is_radiant):
if is_radiant:
return "radiant"
else:
return "dire"
def tower_stat... | {
"repo_name": "ggilmore/DotaBlaze",
"path": "tower_status_tracker.py",
"copies": "1",
"size": "2971",
"license": "mit",
"hash": -283251294046664600,
"line_mean": 36.1375,
"line_max": 84,
"alpha_frac": 0.6704813194,
"autogenerated": false,
"ratio": 3.007085020242915,
"config_test": false,
"has... |
__author__ = 'gmgilmore'
from enum import Enum
class EventType(Enum):
MATCH_STARTED = 1
MATCH_ENDED = 2
DESTROYED_TOWER = 3
DESTROYED_BARRACKS = 4
ROSHAN_KILLED = 5
GAME_OVER = 6
TEAM_NOT_FOUND = 7
LOST_TOWER = 8
LOST_BARRACKS = 9
def generate_description(event_type, event_informat... | {
"repo_name": "ggilmore/DotaBlaze",
"path": "event_types.py",
"copies": "1",
"size": "2110",
"license": "mit",
"hash": 2090571432114740200,
"line_mean": 42.0612244898,
"line_max": 120,
"alpha_frac": 0.6369668246,
"autogenerated": false,
"ratio": 3.430894308943089,
"config_test": false,
"has_n... |
__author__ = 'Gobin'
import argparse
import logging
import json
from cliff import show
from cliff import command
from cliff import lister
from redditcli.api import account
class Me(lister.Lister):
log = logging.getLogger(__name__)
def get_parser(self, program_name):
parser = super(Me, self).get_par... | {
"repo_name": "gobins/python-reddit-api",
"path": "redditcli/commands/account.py",
"copies": "2",
"size": "2502",
"license": "apache-2.0",
"hash": 3513708022336116000,
"line_mean": 25.9139784946,
"line_max": 89,
"alpha_frac": 0.5451638689,
"autogenerated": false,
"ratio": 4.0420032310177705,
"c... |
__author__ = 'Godfrey Takavarasha'
import calendar
import datetime
#from datetime import date
#from datetime import timedelta
__Thirty_Day_Months = [4, 6, 9, 11]
__Digits = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
class PeriodTypes:
""" Provides a named list of the period types used in the module
... | {
"repo_name": "luiscape/hdx-monitor-funnel-stats",
"path": "scripts/ga_collect/datecalc.py",
"copies": "1",
"size": "14750",
"license": "mit",
"hash": -2656007189129905000,
"line_mean": 33.064665127,
"line_max": 130,
"alpha_frac": 0.5748474576,
"autogenerated": false,
"ratio": 3.304951826125924,
... |
__author__ = 'Godfrey Takavarasha'
import os
import time
import json
import datecalc
from httplib2 import Http
from datetime import date
from datetime import timedelta
from apiclient.discovery import build
from apiclient.errors import HttpError
from oauth2client.client import SignedJwtAssertionCredentials
dir = os.... | {
"repo_name": "luiscape/hdx-monitor-funnel-stats",
"path": "scripts/ga_collect/ga_collect.py",
"copies": "1",
"size": "7809",
"license": "mit",
"hash": -5325648652621733000,
"line_mean": 31.4024896266,
"line_max": 110,
"alpha_frac": 0.6084005635,
"autogenerated": false,
"ratio": 3.922149673530889... |
from django.shortcuts import render
import feedparser #need the lib to be installed system-wide [ToDo: Make it also work with in-app installation of lib]
from .models import Website
# Create your views here.
def index(request):
feed_websites = Website.objects.all()
#template = loader.get_template('rssfeed... | {
"repo_name": "GokulEvuri/iFeed",
"path": "rssfeed/views.py",
"copies": "1",
"size": "1277",
"license": "bsd-2-clause",
"hash": 2146655233827015400,
"line_mean": 31.7435897436,
"line_max": 117,
"alpha_frac": 0.6632732968,
"autogenerated": false,
"ratio": 3.489071038251366,
"config_test": false,... |
__author__ = 'goldhand'
from django import forms
from django.utils.translation import ugettext_lazy as _
from crispy_forms.bootstrap import FormActions
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Div, Field, Submit, Button, Fieldset, HTML
from crispy_forms.bootstrap import Inlin... | {
"repo_name": "goldhand/art-portfolio",
"path": "art-portfolio/pages/forms.py",
"copies": "1",
"size": "1180",
"license": "bsd-3-clause",
"hash": 9064439593534044000,
"line_mean": 34.7878787879,
"line_max": 100,
"alpha_frac": 0.6677966102,
"autogenerated": false,
"ratio": 3.653250773993808,
"co... |
# GCM derived from Go's implementation in crypto/cipher.
#
# https://golang.org/src/crypto/cipher/gcm.go
# GCM works over elements of the field GF(2^128), each of which is a 128-bit
# polynomial. Throughout this implementation, polynomials are represented as
# Python integers with the low-order terms at the most sign... | {
"repo_name": "axinging/chromium-crosswalk",
"path": "third_party/tlslite/tlslite/utils/aesgcm.py",
"copies": "56",
"size": "6772",
"license": "bsd-3-clause",
"hash": -922787420542072300,
"line_mean": 34.0880829016,
"line_max": 80,
"alpha_frac": 0.5863851152,
"autogenerated": false,
"ratio": 3.56... |
import os
p = (
115792089210356248762697446949407573530086143415290314195533631308867097853951)
order = (
115792089210356248762697446949407573529996955224135760342422259061068512044369)
p256B = 0x5ac635d8aa3a93e7b3ebbd55769886bc651d06b0cc53b0f63bce3c3e27d2604b
baseX = 0x6b17d1f2e12c4247f8bce6e563a440f277037d... | {
"repo_name": "guorendong/iridium-browser-ubuntu",
"path": "third_party/tlslite/tlslite/utils/p256.py",
"copies": "54",
"size": "4364",
"license": "bsd-3-clause",
"hash": -8534859588914929000,
"line_mean": 25.9382716049,
"line_max": 89,
"alpha_frac": 0.5657653529,
"autogenerated": false,
"ratio":... |
__author__ = "Gopi Raghavan"
__copyright__ = "Copyright (C) 2015 Gopi Raghavan"
__license__ = "GPL"
__version__ = "1.0"
from timeit import default_timer as timer
import json
import random
import decimal
import string
import datetime
from datetime import date
import multiprocessing as mp
# Define an output queue
outpu... | {
"repo_name": "mohigo/tdm",
"path": "data_generator.py",
"copies": "1",
"size": "7109",
"license": "apache-2.0",
"hash": 5447963271277156000,
"line_mean": 29.3803418803,
"line_max": 106,
"alpha_frac": 0.6588831059,
"autogenerated": false,
"ratio": 2.8538739462063427,
"config_test": true,
"has... |
__author__ = 'gordonnstevenson'
__project__ = 'ColorMapToITKSNAP'
import xml.etree.ElementTree as xml
import numpy as np
import io
class ColorMapWriter(object):
ctrl_pt_number = None
lookuptable = None
filename = None
def __init__(self, lookuptable, filename, ctrl_pt_num = 10):
if not i... | {
"repo_name": "gordon-n-stevenson/colormap_to_ITKSNAP",
"path": "ColorMapWriter.py",
"copies": "1",
"size": "4942",
"license": "mit",
"hash": -1301389911198642700,
"line_mean": 37.0153846154,
"line_max": 308,
"alpha_frac": 0.5855928774,
"autogenerated": false,
"ratio": 3.2153545868575146,
"conf... |
from flask import Flask, Response, request, render_template
from flask.ext.login import LoginManager, UserMixin, login_required
from itsdangerous import JSONWebSignatureSerializer
app = Flask(__name__)
login_manager = LoginManager()
login_manager.init_app(app)
class ProtectedUser(UserMixin):
# proxy for a data... | {
"repo_name": "acogdev/olaf",
"path": "flask-login-example.py",
"copies": "1",
"size": "2211",
"license": "mit",
"hash": -7683922956027329000,
"line_mean": 28.48,
"line_max": 72,
"alpha_frac": 0.6413387607,
"autogenerated": false,
"ratio": 3.6666666666666665,
"config_test": false,
"has_no_key... |
__author__ = 'Gouthaman Balaraman'
__version__ = '0.1.0'
import sys
import os
import win32event
import win32service
import win32serviceutil
import win32api
import win32con
import logging
import servicemanager
from ZEO.runzeo import ZEOOptions, ZEOServer
from ZEO.runzeo import logger as zeo_logger
from ZEO.runzeo im... | {
"repo_name": "gouthambs/ZEO-WinService",
"path": "zeo_winservice.py",
"copies": "1",
"size": "5537",
"license": "mit",
"hash": 2633392397848781000,
"line_mean": 33.3913043478,
"line_max": 114,
"alpha_frac": 0.6201914394,
"autogenerated": false,
"ratio": 3.746278755074425,
"config_test": false,... |
__author__ = 'gouthaman'
import os
import unittest
import threading
from flask import Flask, Blueprint, request
from flask_deploy import get_server
import requests
import time
def _start_server(server):
print "Starting server"
try:
server.start()
finally:
server.stop()
class BaseTestCase... | {
"repo_name": "gouthambs/flask-deploy",
"path": "test_flask_deploy.py",
"copies": "1",
"size": "3706",
"license": "mit",
"hash": 3076882165729899000,
"line_mean": 25.4714285714,
"line_max": 83,
"alpha_frac": 0.5588235294,
"autogenerated": false,
"ratio": 4.187570621468926,
"config_test": true,
... |
__author__ = 'gpratt'
__author__ = 'gpratt'
__author__ = 'gpratt'
import argparse
import subprocess
import os
def wrap_wait_error(wait_result):
if wait_result != 0:
raise NameError("Failed to execute command correctly {}".format(wait_result))
def pre_process_fastq(fq, fq01, fq02, fq03, fq04, fq05, fq06,... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/downsample_fastq.py",
"copies": "1",
"size": "2792",
"license": "mit",
"hash": 2038905931419555000,
"line_mean": 35.2597402597,
"line_max": 129,
"alpha_frac": 0.5705587393,
"autogenerated": false,
"ratio": 3.3842424242424243,
"config_te... |
__author__ = 'gpratt'
#collection of scripts to perform clipseq barcode metrics code
from collections import defaultdict, Counter
import numpy as np
import pandas as pd
from matplotlib import cm
try:
barcodes_df = pd.read_csv("/nas3/gpratt/projects/encode/scripts/barcodes/fixed_barcodes.txt",
... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/clipseq/clipseq_barcode_metrics.py",
"copies": "1",
"size": "6939",
"license": "mit",
"hash": -753990361343963500,
"line_mean": 33.0196078431,
"line_max": 112,
"alpha_frac": 0.6120478455,
"autogenerated": false,
"ratio": 4.135280095351609,
"con... |
__author__ = 'gpratt'
import argparse
import subprocess
import os
import pysam
def pre_process_bam(bam, bam01, bam02):
#split bam file into two, return file handle for the two bam files
p = subprocess.Popen("samtools view {} | wc -l".format(bam), shell=True, stdout=subprocess.PIPE) # Number of reads in the tag... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/split_bam.py",
"copies": "1",
"size": "1708",
"license": "mit",
"hash": 1841744623737061600,
"line_mean": 39.6666666667,
"line_max": 178,
"alpha_frac": 0.6487119438,
"autogenerated": false,
"ratio": 3.139705882352941,
"config_test": fal... |
__author__ = 'gpratt'
import argparse
import subprocess
import tempfile
def sort_fastq_inplace(fastq, out_fastq):
handle, tmp_file = tempfile.mkstemp()
call = "cat {0} | sed 's/\t/ /' | paste - - - - | sort -k1,1 -S 3G | tr '\t' '\n' > {2} && mv {2} {1}".format(fastq, out_fastq, tmp_file)
subprocess.cal... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/clipseq/sort_fastq.py",
"copies": "1",
"size": "1195",
"license": "mit",
"hash": 3732811498443917300,
"line_mean": 41.6785714286,
"line_max": 143,
"alpha_frac": 0.6769874477,
"autogenerated": false,
"ratio": 3.1613756613756614,
"config_test": f... |
__author__ = 'gpratt'
import glob
import os
import argparse
from itertools import izip
import shutil
def warn_possibly_made(files):
"""
Checks if all files are the same length, if they are don't do anything
othewise warn and kill pasting, if ignore is set just warn, but don't kill
"""
if len(set... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/cat_biogem.py",
"copies": "1",
"size": "2217",
"license": "mit",
"hash": -2762026775502407000,
"line_mean": 30.2253521127,
"line_max": 110,
"alpha_frac": 0.6156968877,
"autogenerated": false,
"ratio": 3.6166394779771616,
"config_test": ... |
__author__ = 'gpratt'
import pandas as pd
import pyBigWig
import pybedtools
import scipy
def counts_to_rpkm(featureCountsTable):
"""
Given a dataframe or a text file from featureCounts and converts that thing into a dataframe of RPKMs
"""
if isinstance(featureCountsTable, str):
featureCountsTabl... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/rnaseq/helpers.py",
"copies": "1",
"size": "4503",
"license": "mit",
"hash": 7686571426444394000,
"line_mean": 40.3211009174,
"line_max": 181,
"alpha_frac": 0.6597823673,
"autogenerated": false,
"ratio": 3.3730337078651687,
"config_test": false... |
__author__ = 'gpratt'
__author__ = 'gpratt'
import argparse
import subprocess
import os
def wrap_wait_error(wait_result):
if wait_result != 0:
raise NameError("Failed to execute command correctly {}".format(wait_result))
def pre_process_bam(bam, bam01, bam02, bam03, bam04, bam05, bam06, bam07, bam08, ba... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/downsample_bam.py",
"copies": "1",
"size": "4356",
"license": "mit",
"hash": 3460759044747988500,
"line_mean": 40.8846153846,
"line_max": 170,
"alpha_frac": 0.5975665748,
"autogenerated": false,
"ratio": 3.3741285824941905,
"config_test... |
__author__ = 'gpratt'
from collections import Counter
import gzip
import os
from optparse import OptionParser
def parse_barcode_file(barcodes_file, out_file1, out_file2):
barcodes = {}
with open(barcodes_file) as barcodes_file:
for line in barcodes_file:
line = line.strip("\n").split("\... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/clipseq/pe_barcode_splitter.py",
"copies": "1",
"size": "3761",
"license": "mit",
"hash": -2842498232793791500,
"line_mean": 36.62,
"line_max": 143,
"alpha_frac": 0.6184525392,
"autogenerated": false,
"ratio": 3.694499017681729,
"config_test": ... |
__author__ = 'gpratt'
from subprocess import call
import subprocess
import os
import pysam
def genome_coverage_bed(in_bam=None, out_bed_graph=None, genome=None, strand=None, scale=1, five_prime=False):
with open(out_bed_graph, 'w') as out_bed_graph:
call = "genomeCoverageBed -ibam {} -bg -strand {} -scale... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/make_bigwig_files_pe.py",
"copies": "1",
"size": "3548",
"license": "mit",
"hash": 1122934740866638500,
"line_mean": 35.9583333333,
"line_max": 112,
"alpha_frac": 0.5772266065,
"autogenerated": false,
"ratio": 3.7905982905982905,
"confi... |
__author__ = 'gpratt'
from subprocess import call
import subprocess
import os
def genome_coverage_bed(in_bam=None, in_bed=None, out_bed_graph=None, genome=None, strand=None, split=True, dont_flip=False):
with open(out_bed_graph, 'w') as out_bed_graph:
if in_bam is not None and in_bed is not None:
... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/make_bigwig_files.py",
"copies": "1",
"size": "4514",
"license": "mit",
"hash": 3933380670954565600,
"line_mean": 39.6666666667,
"line_max": 235,
"alpha_frac": 0.6552946389,
"autogenerated": false,
"ratio": 3.2082444918265813,
"config_t... |
__author__ = 'gpratt'
import gzip
from optparse import OptionParser
import sys
def add_back_randomers(in_file_name, out_file_name):
#reads through initial file parses everything out
with gzip.open(in_file_name) as fastq_file, gzip.open(out_file_name, 'w') as out_file:
while True:
try:
... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/clipseq/add_randomer.py",
"copies": "1",
"size": "1335",
"license": "mit",
"hash": 7410285708743052000,
"line_mean": 32.375,
"line_max": 90,
"alpha_frac": 0.5378277154,
"autogenerated": false,
"ratio": 3.494764397905759,
"config_test": false,
... |
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