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"""A scene object manages a TVTK scene and objects in it.
"""
# Author: Prabhu Ramachandran <prabhu_r@users.sf.net>
# Copyright (c) 2005, Enthought, Inc.
# License: BSD Style.
# Enthought library imports.
from traits.api import Event, List, Str, Instance
from traitsui.api import View, Group, Item
from apptools.persis... | {
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"""A scheduler that controls the execution of multiple "tasks"
"""
import os
import subprocess
import time
import signal
from collections import deque
import heapq
import logging
import StringIO
from inspect import isfunction, ismethod
# logging
logging.basicConfig(level=logging.DEBUG, format="%(asctime)s: %(message... | {
"repo_name": "schettino72/serveronduty",
"path": "sodd/scheduler.py",
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"""A scheduler that gets payoffs from a local simulation"""
import asyncio
import collections
import contextlib
import json
import logging
import subprocess
from gameanalysis import paygame
from gameanalysis import rsgame
from gameanalysis import utils
from egta import profsched
class _SimulationScheduler(
prof... | {
"repo_name": "egtaonline/quiesce",
"path": "egta/simsched.py",
"copies": "1",
"size": "6177",
"license": "apache-2.0",
"hash": -5309441196663598000,
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... |
"""A scheduler that gets payoffs from a local simulation"""
import asyncio
import itertools
import json
import logging
import os
import shutil
import tempfile
import zipfile
from gameanalysis import paygame
from gameanalysis import rsgame
from gameanalysis import utils
from egta import profsched
class _ZipScheduler... | {
"repo_name": "egtaonline/quiesce",
"path": "egta/zipsched.py",
"copies": "1",
"size": "6025",
"license": "apache-2.0",
"hash": -7446523688862852000,
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"alpha_frac": 0.550373444,
"autogenerated": false,
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... |
"""A scheme for assigning categories to morphs.
To change the number or meaning of categories,
only this file should need to be modified.
"""
from __future__ import unicode_literals
import collections
import locale
import logging
import math
import sys
from . import utils
PY3 = sys.version_info.major == 3
# _str is ... | {
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"path": "flatcat/categorizationscheme.py",
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"""A Scheme interpreter and its read-eval-print loop."""
from scheme_primitives import *
from scheme_reader import *
from ucb import main, trace
##############
# Eval/Apply #
##############
def scheme_eval(expr, env, _=None): # Optional third argument is ignored
"""Evaluate Scheme expression EXPR in environment ... | {
"repo_name": "tavaresdong/courses",
"path": "ucb_cs61A/projects/scheme/scheme.py",
"copies": "3",
"size": "18830",
"license": "mit",
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"""A Scientific Calculator
type h for help
Basic symbols:
-> x : multiplication
-> + : addition
-> - : subtraction
-> / : (float) division
-> mod : modulo
-> sin : sine
-> cos : cosine
-> tan : tangent
-> ^ : power
-> 2^ : power of 2
"""
# This could ... | {
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"path": "Numbers/calculator.py",
"copies": "1",
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"license": "mit",
"hash": 7801913651204185000,
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"autogenerated": false,
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# ascii animation of zooming a mandelbrot fractal, z=z^2+c
from __future__ import print_function, division
import os
import time
import platform
from server import Mandelbrot
res_x = 100
res_y = 40
def screen(start, width):
mandel = Mandelbrot()
dr = width / res_x
di = dr*(res_x/res_y)
di *= 0.8 #... | {
"repo_name": "irmen/Pyro4",
"path": "examples/distributed-mandelbrot/normal.py",
"copies": "1",
"size": "1434",
"license": "mit",
"hash": -7215749176698993000,
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"line_max": 98,
"alpha_frac": 0.5927475593,
"autogenerated": false,
"ratio": 3.1447368421052633,
"config_t... |
# ascii animation of zooming a mandelbrot fractal, z=z^2+c
from __future__ import print_function, division
import os
import time
import threading
import platform
import Pyro4
class MandelZoomer(object):
res_x = 100
res_y = 40
def __init__(self):
self.num_lines_lock = threading.Lock()
sel... | {
"repo_name": "irmen/Pyro4",
"path": "examples/distributed-mandelbrot/client_asciizoom.py",
"copies": "1",
"size": "2913",
"license": "mit",
"hash": 891772748913523000,
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"alpha_frac": 0.5894267079,
"autogenerated": false,
"ratio": 3.3872093023255814,
... |
# ascii animation of zooming a mandelbrot fractal, z=z^2+c
import os
import time
import platform
from concurrent import futures
from Pyro5.api import locate_ns, Proxy, BatchProxy
class MandelZoomer(object):
res_x = 100
res_y = 40
def __init__(self):
self.result = []
with locate_ns() as n... | {
"repo_name": "irmen/Pyro5",
"path": "examples/distributed-mandelbrot/client_asciizoom.py",
"copies": "1",
"size": "2525",
"license": "mit",
"hash": -7699707067124481000,
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"line_max": 133,
"alpha_frac": 0.5865346535,
"autogenerated": false,
"ratio": 3.4400544959128063,
... |
# ascii animation of zooming a mandelbrot fractal, z=z^2+c
import os
import time
import platform
from server import Mandelbrot
res_x = 100
res_y = 40
def screen(start, width):
mandel = Mandelbrot()
dr = width / res_x
di = dr*(res_x/res_y)
di *= 0.8 # aspect ratio correction
lines = mandel.cal... | {
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"path": "examples/distributed-mandelbrot/normal.py",
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"autogenerated": false,
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... |
# ASCII Art Generator (Image to ASCII Art Converter)
# FB - 20160925
import sys
if len(sys.argv) != 3:
print "USAGE:"
print "[python] img2asciiart.py InputImageFileName OutputTextFileName"
print "Use quotes if file paths/names contain spaces!"
sys.exit()
inputImageFileName = sys.argv[1]
OutputTextFileNa... | {
"repo_name": "ActiveState/code",
"path": "recipes/Python/580702_Image_to_ASCII_Art_Converter/recipe-580702.py",
"copies": "1",
"size": "1444",
"license": "mit",
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""" ascii based histogram generator for quick inspection of
distributions.
"""
## give it a function API so it is easy and quick to use.
class Histogram(object):
CHAR = '*'
BIN_COUNT = 70
TICK_PRECISION = 2
MAX_HEIGHT = 100
def __init__(self,
data,
c... | {
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"path": "lib/histogram.py",
"copies": "1",
"size": "3223",
"license": "mit",
"hash": -7713816690293762000,
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"autogenerated": false,
"ratio": 3.760793465577596,
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"""ASCII, Dammit
Stupid library to turn MS chars (like smart quotes) and ISO-Latin
chars into ASCII, dammit. Will do plain text approximations, or more
accurate HTML representations. Can also be jiggered to just fix the
smart quotes and leave the rest of ISO-Latin alone.
Sources:
http://www.cs.tut.fi/~jkorpela/latin... | {
"repo_name": "pombredanne/SourceForge-Allura",
"path": "Allura/allura/lib/AsciiDammit.py",
"copies": "5",
"size": "7036",
"license": "apache-2.0",
"hash": 8455181613443969000,
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"autogenerated": false,
"ratio": 2.9687763713080... |
"""Ascii menu class"""
from __future__ import print_function
def ascii_menu(title=None, menu_list=None):
"""
creates a simple ASCII menu from a list of tuples containing a label
and a functions reference. The function should not use parameters.
:param title: the title of the menu
:param menu_list:... | {
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"path": "cloudmesh_base/menu.py",
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'''Ascii menu class'''
from __future__ import print_function
def ascii_menu(title=None, menu_list=None):
'''
creates a simple ASCII menu from a list of tuples containing a label
and a functions refernec. The function should not use parameters.
:param title: the title of the menu
:param menu_list: ... | {
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"path": "cloudmesh/util/menu.py",
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"""AsciiPic base exception handling."""
class AsciipicException(Exception):
"""Base Asciipic exception
To correctly use this class, inherit from it and define
a `template` property.
That `template` will be formated using the keyword arguments
provided to the constructor.
"""
template = ... | {
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"path": "asciipic/common/exception.py",
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"""ASCII plots (experimental).
The plots are printed directly to standard output.
"""
import typing
if typing.TYPE_CHECKING:
from physt.histogram_nd import Histogram2D
try:
import asciiplotlib
ENABLE_ASCIIPLOTLIB = True
except ImportError:
asciiplotlib = None
ENABLE_ASCIIPLOTLIB = False
types:... | {
"repo_name": "janpipek/physt",
"path": "physt/plotting/ascii.py",
"copies": "1",
"size": "2984",
"license": "mit",
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"... |
"""ASCII Printer"""
from ..utils.singleton import Singleton
from ..algebra.core.exceptions import BasisNotSetError
from .base import QnetBasePrinter
from .sympy import SympyStrPrinter
from ._precedence import precedence, PRECEDENCE
__all__ = []
__private__ = ['QnetAsciiPrinter', 'QnetAsciiDefaultPrinter']
class Qnet... | {
"repo_name": "mabuchilab/QNET",
"path": "src/qnet/printing/asciiprinter.py",
"copies": "1",
"size": "31763",
"license": "mit",
"hash": -1833190490758432300,
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"autogenerated": false,
"ratio": 3.8688185140073084,
"config_test"... |
"""AsciiTable end to end testing."""
import sys
from textwrap import dedent
import py
import pytest
from terminaltables import AsciiTable
from terminaltables.terminal_io import IS_WINDOWS
from tests import PROJECT_ROOT
from tests.screenshot import RunNewConsole, screenshot_until_match
HERE = py.path.local(__file__)... | {
"repo_name": "Robpol86/terminaltables",
"path": "tests/test_all_tables_e2e/test_ascii_table.py",
"copies": "1",
"size": "6273",
"license": "mit",
"hash": -8738396087833148000,
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"line_max": 120,
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"autogenerated": false,
"ratio": 4.276073619631... |
"""ASCII table generator"""
class ASCIITableRenderer(object):
def render(self, table):
total_width = 0
for col in table.cols:
total_width += col.width
# Header
out = self._format_separator(total_width)
cols_widths = [col.width for col in table.cols]
out... | {
"repo_name": "ice-stuff/ice",
"path": "ice/ascii_table.py",
"copies": "1",
"size": "3755",
"license": "mit",
"hash": 4520670069431780400,
"line_mean": 28.3359375,
"line_max": 79,
"alpha_frac": 0.5360852197,
"autogenerated": false,
"ratio": 3.8044579533941234,
"config_test": false,
"has_no_ke... |
"""AsciiTable is the main table class. To be inherited by other tables. Define convenience methods here."""
from terminaltables.base_table import BaseTable
from terminaltables.terminal_io import terminal_size
from terminaltables.width_and_alignment import column_max_width, max_dimensions, table_width
class AsciiTabl... | {
"repo_name": "Robpol86/terminaltables",
"path": "terminaltables/ascii_table.py",
"copies": "3",
"size": "2734",
"license": "mit",
"hash": -5722899200528905000,
"line_mean": 48.7090909091,
"line_max": 118,
"alpha_frac": 0.6942209217,
"autogenerated": false,
"ratio": 4.068452380952381,
"config_t... |
import sys
from PDFWriter import PDFWriter
# Define the header information.
column_names = ['DEC', 'OCT', 'HEX', 'BIN', 'Symbol', 'Description']
column_widths = [4, 6, 4, 10, 7, 20]
# Define the ASCII control character information.
ascii_control_characters = \
"""
0 000 00 00000000 NUL � Null ... | {
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"path": "recipes/Python/579043_Printing_an_ASCII_table_to_PDF/recipe-579043.py",
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"ratio"... |
# asciixmas
# December 1989 Larry Bartz Indianapolis, IN
#
# $Id: xmas.py 46623 2006-06-03 22:59:23Z andrew.kuchling $
#
# I'm dreaming of an ascii character-based monochrome Christmas,
# Just like the ones I used to know!
# Via a full duplex communications channel,
# At 9600 bits per second,
# Ev... | {
"repo_name": "yqm/sl4a",
"path": "python/src/Demo/curses/xmas.py",
"copies": "34",
"size": "25499",
"license": "apache-2.0",
"hash": -3236774364321500000,
"line_mean": 27.1445916115,
"line_max": 78,
"alpha_frac": 0.5234715087,
"autogenerated": false,
"ratio": 2.5916251651590607,
"config_test":... |
# asciixmas
# December 1989 Larry Bartz Indianapolis, IN
#
# $Id: xmas.py,v 1.1 2000/12/21 16:26:37 akuchling Exp $
#
# I'm dreaming of an ascii character-based monochrome Christmas,
# Just like the one's I used to know!
# Via a full duplex communications channel,
# At 9600 bits per second,
# Even... | {
"repo_name": "OS2World/APP-INTERNET-torpak_2",
"path": "Demo/curses/xmas.py",
"copies": "1",
"size": "24891",
"license": "mit",
"hash": -6949883812525731000,
"line_mean": 26.4735099338,
"line_max": 78,
"alpha_frac": 0.5361375598,
"autogenerated": false,
"ratio": 2.50993243924574,
"config_test"... |
""" ascl.php-out_1.0.py - program for downloading and processing the ascl.php webpage of ASCL journal
entries for a user defined date (yy/mm), and outputting a structed txt file of journal entry fields
grouped and sorted for ADS submission, as well as an xls file of the fields for the user's use. Program
assumes that t... | {
"repo_name": "jconenna/ASCL-Out",
"path": "source.py",
"copies": "1",
"size": "9215",
"license": "mit",
"hash": -2354478182651200000,
"line_mean": 38.8917748918,
"line_max": 103,
"alpha_frac": 0.4813890396,
"autogenerated": false,
"ratio": 3.459084084084084,
"config_test": false,
"has_no_key... |
import re
import os
import SCons.Action
import SCons.Builder
import SCons.Scanner
## TODO - improve these regular expressions
output_re = [
re.compile(r'''png\('([^']+)'\)''', re.M)
, re.compile(r'''^[^#]*save\(.*file\s*=\s*['"]([^'"]+)['"]\s*[),].*$''', re.M)
, re.compile(r'''sink\(.*file\s*... | {
"repo_name": "kboyd/scons_r",
"path": "__init__.py",
"copies": "1",
"size": "2561",
"license": "bsd-2-clause",
"hash": 4959422635384093000,
"line_mean": 26.5376344086,
"line_max": 86,
"alpha_frac": 0.5626708317,
"autogenerated": false,
"ratio": 3.193266832917706,
"config_test": false,
"has_n... |
"""A scraper for downloading checklists from eBird.
This scraper creates checklists for recent observations for a given region
using the eBird API. Additional information for each checklist is also
scraped from the checklist web page.
"""
import json
import os
import re
from scrapy import log
from scrapy.http import... | {
"repo_name": "StuartMacKay/checklists_scrapers",
"path": "checklists_scrapers/spiders/ebird_spider.py",
"copies": "1",
"size": "28525",
"license": "bsd-3-clause",
"hash": 3322886059164118000,
"line_mean": 34.5230386052,
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"ratio":... |
"""A scraper for Malta 2007-2013."""
from datapackage_pipelines.wrapper import spew, ingest
from logging import info, debug
from lxml.html import fromstring
from requests import Session
BASE_URL = 'https://investinginyourfuture.gov.mt'
PAGINATION_URL = BASE_URL + '/ajax/loadProjects.ashx?page={counter}'
PROJECT_URLS_... | {
"repo_name": "Victordeleon/os-data-importers",
"path": "eu-structural-funds/common/processors/MT/mt_malta_scraper.py",
"copies": "1",
"size": "4034",
"license": "mit",
"hash": 4061896130228096000,
"line_mean": 45.367816092,
"line_max": 174,
"alpha_frac": 0.7198810114,
"autogenerated": false,
"ra... |
"""A scraper for Malta 2007-2013."""
import requests
import lxml
import csv
from lxml import html
__author__ = 'Fernando Blat'
# Base URL is the host of the page
BASE_URL = 'https://investinginyourfuture.gov.mt'
# Projects are fetch from the paginated list
PAGINATION_URL = 'https://investinginyourfuture.gov.mt/aja... | {
"repo_name": "Victordeleon/os-data-importers",
"path": "eu-structural-funds/common/processors/MT/scraper_original.py",
"copies": "1",
"size": "4732",
"license": "mit",
"hash": 4410809753228718000,
"line_mean": 46.32,
"line_max": 198,
"alpha_frac": 0.7115384615,
"autogenerated": false,
"ratio": 3... |
# A *SCRATCH* of a bot that watches YouTube videos through tor using selenium and stem
from stem import Signal
from stem.control import Controller
import stem.process
import time, random, signal, sys
from selenium import webdriver
from selenium.webdriver.common.proxy import *
myProxy = "localhost:9150"
proxy = Proxy(... | {
"repo_name": "iluxonchik/python-general-repo",
"path": "bots/youtube/tortube.py",
"copies": "1",
"size": "1426",
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"hash": -796480583642586900,
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"autogenerated": false,
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"config_t... |
"""A screensaver version of Newton's Cradle with an interactive mode.
"""
__docformat__ = "reStructuredText"
import os
import random
import sys
description = """
---- Newton's Cradle ----
A screensaver version of Newton's Cradle with an interactive mode
/s - Run in fullscreen screensaver mode
/p #### - Display a pr... | {
"repo_name": "viblo/pymunk",
"path": "examples/newtons_cradle.py",
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"autogenerated": false,
"ratio": 3.7890173410404624,
"config_test": false,
... |
"""A screensaver version of Newton's Cradle with an interactive mode.
"""
__version__ = "$Id:$"
__docformat__ = "reStructuredText"
import sys, random
import os
description = """
---- Newton's Cradle ----
A screensaver version of Newton's Cradle with an interactive mode
/s - Run in fullscreen screensaver mode
/p ###... | {
"repo_name": "sneharavi12/DeepLearningFinals",
"path": "pymunk-pymunk-4.0.0/examples/newtons_cradle.py",
"copies": "5",
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"alpha_frac": 0.5583119475,
"autogenerated": false,
"ratio": 3.6398... |
"""A screensaver version of Newton's Cradle with an interactive mode.
"""
__version__ = "$Id:$"
__docformat__ = "reStructuredText"
import sys, random
import os
description = """
---- Newton's Cradle ----
A screensaver version of Newton's Cradle with an interactive mode
/s - Run in fullscreen screensaver... | {
"repo_name": "cfobel/python___pymunk",
"path": "examples/newtons_cradle.py",
"copies": "1",
"size": "7215",
"license": "mit",
"hash": 3893974385874662000,
"line_mean": 33.8955223881,
"line_max": 127,
"alpha_frac": 0.5427581428,
"autogenerated": false,
"ratio": 3.6848825331971398,
"config_test"... |
""" A script for adding visits to the same patient
This is a manage.py command. Run with --help for documentation.
Example usage:
To run on localhost:
> python manage.py addmultiplevisits
To run on production:
> python manage.py addmultiplevisits --remote
"""
import getpass
import logging
import settings
import da... | {
"repo_name": "avastjohn/maventy_new",
"path": "healthdb/management/commands/addvisitshortstring.py",
"copies": "1",
"size": "2548",
"license": "bsd-3-clause",
"hash": -5677069154794431000,
"line_mean": 30.85,
"line_max": 108,
"alpha_frac": 0.6609105181,
"autogenerated": false,
"ratio": 3.6714697... |
# A script for analyzing the output of NPSPY and merging data about streams.
import sys
def ReadFile(filename, flags='rb'):
"""Returns the contents of a file."""
file = open(filename, flags)
result = file.read()
file.close()
return result
def WriteFile(filename, contents):
"""Overwrites the file with t... | {
"repo_name": "7kbird/chrome",
"path": "third_party/npapi/npspy/analyze_streams.py",
"copies": "1",
"size": "3057",
"license": "bsd-3-clause",
"hash": 2732773048278202000,
"line_mean": 28.1142857143,
"line_max": 184,
"alpha_frac": 0.5904481518,
"autogenerated": false,
"ratio": 3.485746864310148,
... |
# A script for analyzing the output of NPSPY and merging data about streams.
import sys
def ReadFile(filename, flags='rb'):
"""Returns the contents of a file."""
file = open(filename, flags)
result = file.read()
file.close()
return result
def WriteFile(filename, contents):
"""Overwrites t... | {
"repo_name": "BigBrother1984/android_external_chromium_org",
"path": "third_party/npapi/npspy/analyze_streams.py",
"copies": "127",
"size": "3162",
"license": "bsd-3-clause",
"hash": -7815812489917302000,
"line_mean": 28.1142857143,
"line_max": 184,
"alpha_frac": 0.5708412397,
"autogenerated": fal... |
""" A script for calculating cached latest_visit statistics on patients.
This is a manage.py command. Run with --help for documentation.
Example usage:
To run on localhost:
> manage.py visitcalc
To run on production:
> manage.py visitcalc --remote
"""
import getpass
import logging
import settings
... | {
"repo_name": "avastjohn/maventy_new",
"path": "healthdb/management/commands/visitcalc.py",
"copies": "1",
"size": "3112",
"license": "bsd-3-clause",
"hash": -5553732034112976000,
"line_mean": 29.4343434343,
"line_max": 75,
"alpha_frac": 0.6433161954,
"autogenerated": false,
"ratio": 3.7629987908... |
"""A script for converting the EPA CEMS dataset from gzip to Apache Parquet.
The original EPA CEMS data is available as ~12,000 gzipped CSV files, one for
each month for each state, from 1995 to the present. On disk they take up
about 7.3 GB of space, compressed. Uncompressed it is closer to 100 GB. That's
too much da... | {
"repo_name": "catalyst-cooperative/pudl",
"path": "src/pudl/convert/epacems_to_parquet.py",
"copies": "1",
"size": "12122",
"license": "mit",
"hash": -7244998253044602000,
"line_mean": 36.4135802469,
"line_max": 83,
"alpha_frac": 0.6236594621,
"autogenerated": false,
"ratio": 3.8300157977883096,... |
##A script for creating a table
import numpy as np
## Load necessary modules
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
def compare(first,second):
if float(first[-2])>float(second[-2]):
return 1
elif float(first[-2])<float(second[-2]):
re... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "tables/Table1/table_creation.py",
"copies": "1",
"size": "3025",
"license": "mit",
"hash": 416637377168121000,
"line_mean": 24.6355932203,
"line_max": 140,
"alpha_frac": 0.5980165289,
"autogenerated": false,
"ratio": 2.6350174216027873,
"config_test":... |
##A script for creating a table
## Load necessary modules
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
##load data for each cancer, find total genes in oncolnc, get patient info
f=open(os.path.join(BASE_DIR,'mirna','cox','BLCA','coeffs_pvalues.txt'))
data=[i for i... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "tables/Table2/table_creation.py",
"copies": "1",
"size": "7470",
"license": "mit",
"hash": 9132579757509238000,
"line_mean": 29.2429149798,
"line_max": 116,
"alpha_frac": 0.6676037483,
"autogenerated": false,
"ratio": 2.382015306122449,
"config_test":... |
##A script for creating a table
## Load necessary modules
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
##load data for each cancer, find total genes analyzed and significant genes, get patient info
f=open(os.path.join(BASE_DIR,'cox_regression','BLCA','coeffs_norm... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/tables/table 1/table_creation.py",
"copies": "1",
"size": "7812",
"license": "mit",
"hash": -2019849272320904700,
"line_mean": 33.4140969163,
"line_max": 115,
"alpha_frac": 0.7050691244,
"autogenerated": false,
"ratio": 2.6808510638297873,
"co... |
##A script for creating tables for each cancer, with the data sorted
def compare(first,second):
if float(first[-2])>float(second[-2]):
return 1
elif float(first[-2])<float(second[-2]):
return -1
else:
return 0
## Load necessary modules
import os
BASE_DIR = os.path.dirname(os.path.... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/tables/S1/table_creation.py",
"copies": "1",
"size": "5368",
"license": "mit",
"hash": -3551850941878003000,
"line_mean": 40.2923076923,
"line_max": 140,
"alpha_frac": 0.7192622951,
"autogenerated": false,
"ratio": 2.7015601409159538,
"config_... |
## A script for extracting info about the patients used in the analysis
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running from the command lin... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/LUSC/patient_info.py",
"copies": "1",
"size": "6888",
"license": "mit",
"hash": -610288040859616800,
"line_mean": 30.1674208145,
"line_max": 132,
"alpha_frac": 0.6681184669,
"autogenerated": false,
"ratio": 2.95242177453922,
"config_test": fa... |
## A script for extracting info about the patients used in the analysis
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running from the command line... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/LUSC/patient_info.py",
"copies": "1",
"size": "6885",
"license": "mit",
"hash": 3045482645298794000,
"line_mean": 30.5825688073,
"line_max": 132,
"alpha_frac": 0.6687000726,
"autogenerated": false,
"ratio": 2.9435656263360412,
"config_test":... |
## A script for extracting info about the patients used in the analysis
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not running from the command line manually... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/LUSC/patient_info.py",
"copies": "1",
"size": "6093",
"license": "mit",
"hash": -1661354683965662200,
"line_mean": 28.4347826087,
"line_max": 132,
"alpha_frac": 0.6446742163,
"autogenerated": false,
"ratio": 2.9491771539206195,
... |
## A script for finding every cox coefficient and pvalue for every BLCA lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/BLCA/cox_regression.py",
"copies": "1",
"size": "11632",
"license": "mit",
"hash": -906815388999954600,
"line_mean": 35.0123839009,
"line_max": 142,
"alpha_frac": 0.6583562586,
"autogenerated": false,
"ratio": 3.145484045429962,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every BRCA lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/BRCA/cox_regression.py",
"copies": "1",
"size": "14304",
"license": "mit",
"hash": 7387531978692712000,
"line_mean": 33.0571428571,
"line_max": 142,
"alpha_frac": 0.6505173378,
"autogenerated": false,
"ratio": 3.032435870256519,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every CESC lncRNA in the beta MiTranscriptome data set (normalized counts)
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/CESC/cox_regression.py",
"copies": "1",
"size": "11896",
"license": "mit",
"hash": -4674484514787050000,
"line_mean": 34.1952662722,
"line_max": 142,
"alpha_frac": 0.6519838601,
"autogenerated": false,
"ratio": 3.1214904224612963,
"config_t... |
## A script for finding every cox coefficient and pvalue for every COAD lncRNA in the beta MiTranscriptome data set (normalized counts)
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you ... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/COAD/cox_regression.py",
"copies": "1",
"size": "9471",
"license": "mit",
"hash": 3362725805607594000,
"line_mean": 35.8521400778,
"line_max": 142,
"alpha_frac": 0.6732129659,
"autogenerated": false,
"ratio": 3.119565217391304,
"config_test... |
## A script for finding every cox coefficient and pvalue for every GBM lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from t... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/GBM/cox_regression.py",
"copies": "1",
"size": "9487",
"license": "mit",
"hash": 7810425097567212000,
"line_mean": 35.6293436293,
"line_max": 142,
"alpha_frac": 0.6731316538,
"autogenerated": false,
"ratio": 3.1217505758473183,
"config_test... |
## A script for finding every cox coefficient and pvalue for every HNSC lncRNA in the beta MiTranscriptome data set (normalized counts)
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you ... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/HNSC/cox_regression.py",
"copies": "1",
"size": "11927",
"license": "mit",
"hash": 7812489676093152000,
"line_mean": 35.0332326284,
"line_max": 142,
"alpha_frac": 0.6519661273,
"autogenerated": false,
"ratio": 3.1157262277951934,
"config_te... |
## A script for finding every cox coefficient and pvalue for every KIRC lncRNA in the beta MiTranscriptome data set (normalized counts)
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you ... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/KIRC/cox_regression.py",
"copies": "1",
"size": "10494",
"license": "mit",
"hash": -8114452723561608000,
"line_mean": 34.5728813559,
"line_max": 142,
"alpha_frac": 0.6591385554,
"autogenerated": false,
"ratio": 3.1093333333333333,
"config_t... |
## A script for finding every cox coefficient and pvalue for every KIRP lncRNA in the beta MiTranscriptome data set (normalized counts)
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/KIRP/cox_regression.py",
"copies": "1",
"size": "9448",
"license": "mit",
"hash": 1534683241645135000,
"line_mean": 36.4920634921,
"line_max": 142,
"alpha_frac": 0.6730524979,
"autogenerated": false,
"ratio": 3.107894736842105,
"config_test... |
## A script for finding every cox coefficient and pvalue for every LAML lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from t... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/LAML/cox_regression.py",
"copies": "1",
"size": "7267",
"license": "mit",
"hash": -5186421158353493000,
"line_mean": 35.5175879397,
"line_max": 142,
"alpha_frac": 0.681299023,
"autogenerated": false,
"ratio": 3.130978026712624,
"config_test... |
## A script for finding every cox coefficient and pvalue for every LGG lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from t... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/LGG/cox_regression.py",
"copies": "1",
"size": "10067",
"license": "mit",
"hash": -7772444224204125000,
"line_mean": 35.082437276,
"line_max": 142,
"alpha_frac": 0.6656402106,
"autogenerated": false,
"ratio": 3.120582765034098,
"config_test... |
## A script for finding every cox coefficient and pvalue for every LIHC lncRNA in the beta MiTranscriptome data set (normalized counts)
##load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from th... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/LIHC/cox_regression.py",
"copies": "1",
"size": "10519",
"license": "mit",
"hash": -7833376876707980000,
"line_mean": 33.6019736842,
"line_max": 142,
"alpha_frac": 0.658237475,
"autogenerated": false,
"ratio": 3.1213649851632046,
"config_te... |
## A script for finding every cox coefficient and pvalue for every LUAD lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from t... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/LUAD/cox_regression.py",
"copies": "1",
"size": "9507",
"license": "mit",
"hash": -8872846751967021000,
"line_mean": 36.4291338583,
"line_max": 142,
"alpha_frac": 0.6731881771,
"autogenerated": false,
"ratio": 3.124219520210319,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every LUSC lncRNA in the beta MiTranscriptome data set (normalized counts)
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "lncrna/cox/LUSC/cox_regression.py",
"copies": "1",
"size": "9500",
"license": "mit",
"hash": -7051402246589650000,
"line_mean": 36.2549019608,
"line_max": 142,
"alpha_frac": 0.6736842105,
"autogenerated": false,
"ratio": 3.115775664152181,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in BLCA Tier 3 data downloaded Jan. 6th 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/BLCA/cox_regression.py",
"copies": "1",
"size": "11660",
"license": "mit",
"hash": -3303342178257248000,
"line_mean": 35.3239875389,
"line_max": 142,
"alpha_frac": 0.6439108062,
"autogenerated": false,
"ratio": 3.0603674540682415,
"config_te... |
## A script for finding every cox coefficient and pvalue for every miRNA in BRCA Tier 3 data downloaded Jan. 6th 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/BRCA/cox_regression.py",
"copies": "1",
"size": "14465",
"license": "mit",
"hash": 2730063554618802000,
"line_mean": 33.3586698337,
"line_max": 142,
"alpha_frac": 0.6398202558,
"autogenerated": false,
"ratio": 2.9738898026315788,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in CESC Tier 3 data downloaded Jan 6th 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fr... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/CESC/cox_regression.py",
"copies": "1",
"size": "12060",
"license": "mit",
"hash": -5372441177180242000,
"line_mean": 34.366568915,
"line_max": 142,
"alpha_frac": 0.6389718076,
"autogenerated": false,
"ratio": 3.0477634571645185,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in COAD Tier 3 data downloaded Jan. 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running f... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/COAD/cox_regression.py",
"copies": "1",
"size": "9643",
"license": "mit",
"hash": 8954970475131569000,
"line_mean": 36.2316602317,
"line_max": 142,
"alpha_frac": 0.6564347195,
"autogenerated": false,
"ratio": 3.0257295262001884,
"config_test... |
## A script for finding every cox coefficient and pvalue for every miRNA in ESCA Tier 3 data downloaded Jan 6th 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fr... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/ESCA/cox_regression.py",
"copies": "1",
"size": "10583",
"license": "mit",
"hash": -4095795354324827600,
"line_mean": 34.8745762712,
"line_max": 142,
"alpha_frac": 0.6485873571,
"autogenerated": false,
"ratio": 3.0437158469945356,
"config_te... |
## A script for finding every cox coefficient and pvalue for every miRNA in GBM Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/GBM/cox_regression.py",
"copies": "1",
"size": "9135",
"license": "mit",
"hash": -1769685292696447000,
"line_mean": 34.5447470817,
"line_max": 134,
"alpha_frac": 0.6556102901,
"autogenerated": false,
"ratio": 3.0592766242464835,
"config_test... |
## A script for finding every cox coefficient and pvalue for every miRNA in HNSC Tier 3 data downloaded Jan 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fr... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/HNSC/cox_regression.py",
"copies": "1",
"size": "12092",
"license": "mit",
"hash": -1552545316746449000,
"line_mean": 34.9880952381,
"line_max": 142,
"alpha_frac": 0.6389348329,
"autogenerated": false,
"ratio": 3.0420125786163523,
"config_te... |
## A script for finding every cox coefficient and pvalue for every miRNA in KIRC Tier 3 data downloaded Jan. 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running f... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/KIRC/cox_regression.py",
"copies": "1",
"size": "10658",
"license": "mit",
"hash": 2355818516007938000,
"line_mean": 34.7651006711,
"line_max": 142,
"alpha_frac": 0.6443047476,
"autogenerated": false,
"ratio": 3.024404086265607,
"config_test... |
## A script for finding every cox coefficient and pvalue for every miRNA in KIRP Tier 3 data downloaded Jan. 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running ... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/KIRP/cox_regression.py",
"copies": "1",
"size": "9616",
"license": "mit",
"hash": 5556062649598266000,
"line_mean": 37.1587301587,
"line_max": 142,
"alpha_frac": 0.6566139767,
"autogenerated": false,
"ratio": 3.015365318281593,
"config_test"... |
## A script for finding every cox coefficient and pvalue for every miRNA in LAML Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/LAML/cox_regression.py",
"copies": "1",
"size": "7430",
"license": "mit",
"hash": -772812124370821000,
"line_mean": 36.15,
"line_max": 142,
"alpha_frac": 0.6596231494,
"autogenerated": false,
"ratio": 3.005663430420712,
"config_test": false,... |
## A script for finding every cox coefficient and pvalue for every miRNA in LGG Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/LGG/cox_regression.py",
"copies": "1",
"size": "10226",
"license": "mit",
"hash": -1702310522581083600,
"line_mean": 35.5214285714,
"line_max": 142,
"alpha_frac": 0.6501075689,
"autogenerated": false,
"ratio": 3.030823947836396,
"config_test... |
## A script for finding every cox coefficient and pvalue for every miRNA in LIHC Tier 3 data downloaded Jan. 6th, 2016
##load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
#... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/LIHC/cox_regression.py",
"copies": "1",
"size": "10678",
"license": "mit",
"hash": 6980963000249970000,
"line_mean": 34.0098360656,
"line_max": 142,
"alpha_frac": 0.6434725604,
"autogenerated": false,
"ratio": 3.0352472996020468,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in LUAD Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/LUAD/cox_regression.py",
"copies": "1",
"size": "9666",
"license": "mit",
"hash": -6026977238778096000,
"line_mean": 36.9058823529,
"line_max": 142,
"alpha_frac": 0.6566314918,
"autogenerated": false,
"ratio": 3.029144468818552,
"config_test... |
## A script for finding every cox coefficient and pvalue for every miRNA in LUSC Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/LUSC/cox_regression.py",
"copies": "1",
"size": "9660",
"license": "mit",
"hash": -3005834714614659600,
"line_mean": 36.5875486381,
"line_max": 142,
"alpha_frac": 0.6570393375,
"autogenerated": false,
"ratio": 3.020637898686679,
"config_test... |
## A script for finding every cox coefficient and pvalue for every miRNA in OV Tier 3 data downloaded Jan. 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fro... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/OV/cox_regression.py",
"copies": "1",
"size": "10377",
"license": "mit",
"hash": 7671918509012205000,
"line_mean": 34.2959183673,
"line_max": 142,
"alpha_frac": 0.6467187048,
"autogenerated": false,
"ratio": 3.038653001464129,
"config_test":... |
## A script for finding every cox coefficient and pvalue for every miRNA in PAAD Tier 3 data downloaded Jan. 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running f... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/PAAD/cox_regression.py",
"copies": "1",
"size": "10704",
"license": "mit",
"hash": -3085435677635653000,
"line_mean": 35.0404040404,
"line_max": 142,
"alpha_frac": 0.6448056801,
"autogenerated": false,
"ratio": 3.033153867951261,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in READ Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/READ/cox_regression.py",
"copies": "1",
"size": "9664",
"license": "mit",
"hash": 6353988321956900000,
"line_mean": 36.75,
"line_max": 142,
"alpha_frac": 0.6571812914,
"autogenerated": false,
"ratio": 3.0351758793969847,
"config_test": false... |
## A script for finding every cox coefficient and pvalue for every miRNA in SARC Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/SARC/cox_regression.py",
"copies": "1",
"size": "9640",
"license": "mit",
"hash": 5407489945504302000,
"line_mean": 36.65625,
"line_max": 142,
"alpha_frac": 0.6566390041,
"autogenerated": false,
"ratio": 3.027638190954774,
"config_test": fal... |
## A script for finding every cox coefficient and pvalue for every miRNA in SKCM Tier 3 data downloaded Jan. 6th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/SKCM/cox_regression.py",
"copies": "1",
"size": "9664",
"license": "mit",
"hash": -7430986892123306000,
"line_mean": 37.3492063492,
"line_max": 142,
"alpha_frac": 0.6553187086,
"autogenerated": false,
"ratio": 3.0209440450140668,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in STAD Tier 3 data downloaded Jan. 6th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running f... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/STAD/cox_regression.py",
"copies": "1",
"size": "10460",
"license": "mit",
"hash": 1931067833772044000,
"line_mean": 34.3378378378,
"line_max": 142,
"alpha_frac": 0.6471319312,
"autogenerated": false,
"ratio": 3.0336426914153134,
"config_tes... |
## A script for finding every cox coefficient and pvalue for every miRNA in UCEC Tier 3 data downloaded Jan. 6th 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mirna/cox/UCEC/cox_regression.py",
"copies": "1",
"size": "13817",
"license": "mit",
"hash": -2111816502972982300,
"line_mean": 33.8035264484,
"line_max": 142,
"alpha_frac": 0.639067815,
"autogenerated": false,
"ratio": 2.978443630092692,
"config_test... |
## A script for finding every cox coefficient and pvalue for every mRNA in BLCA Tier 3 data downloaded Feb. 2015
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are n... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/BLCA/cox_regression.py",
"copies": "1",
"size": "10115",
"license": "mit",
"hash": 3971779708980136000,
"line_mean": 32.4933774834,
"line_max": 142,
"alpha_frac": 0.6125556105,
"autogenerated": false,
"ratio": 3.1422802112457284,
... |
## A script for finding every cox coefficient and pvalue for every mRNA in BLCA Tier 3 data downloaded Jan. 5th 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/BLCA/cox_regression.py",
"copies": "1",
"size": "11254",
"license": "mit",
"hash": 6934990945183843000,
"line_mean": 34.726984127,
"line_max": 142,
"alpha_frac": 0.6395948107,
"autogenerated": false,
"ratio": 3.1226415094339623,
"config_test"... |
## A script for finding every cox coefficient and pvalue for every mRNA in BRCA Tier 3 data downloaded Feb. 2015
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are n... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/BRCA/cox_regression.py",
"copies": "1",
"size": "12294",
"license": "mit",
"hash": -6061850855121882000,
"line_mean": 30.442455243,
"line_max": 142,
"alpha_frac": 0.5896372214,
"autogenerated": false,
"ratio": 3.1595990747879723,
... |
## A script for finding every cox coefficient and pvalue for every mRNA in BRCA Tier 3 data downloaded Jan. 5th 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/BRCA/cox_regression.py",
"copies": "1",
"size": "14067",
"license": "mit",
"hash": 5882410756879780000,
"line_mean": 32.7338129496,
"line_max": 142,
"alpha_frac": 0.6362408474,
"autogenerated": false,
"ratio": 3.0186695278969955,
"config_test... |
## A script for finding every cox coefficient and pvalue for every mRNA in CESC Tier 3 data downloaded Feb. 2015
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not running from the command... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/CESC/cox_regression.py",
"copies": "1",
"size": "10559",
"license": "mit",
"hash": -1478629582691320600,
"line_mean": 31.3895705521,
"line_max": 142,
"alpha_frac": 0.6079174164,
"autogenerated": false,
"ratio": 3.1285925925925926,... |
## A script for finding every cox coefficient and pvalue for every mRNA in CESC Tier 3 data downloaded Jan 5th 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fro... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/CESC/cox_regression.py",
"copies": "1",
"size": "11661",
"license": "mit",
"hash": 5131012387982858000,
"line_mean": 33.6023738872,
"line_max": 142,
"alpha_frac": 0.6346797016,
"autogenerated": false,
"ratio": 3.1104294478527605,
"config_test... |
## A script for finding every cox coefficient and pvalue for every mRNA in COAD Tier 3 data downloaded Feb. 2015
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not running from the command ... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/COAD/cox_regression.py",
"copies": "1",
"size": "8485",
"license": "mit",
"hash": -6111629300363947000,
"line_mean": 33.3522267206,
"line_max": 143,
"alpha_frac": 0.6321744255,
"autogenerated": false,
"ratio": 3.1171932402645113,
... |
## A script for finding every cox coefficient and pvalue for every mRNA in COAD Tier 3 data downloaded Jan. 5th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fr... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/COAD/cox_regression.py",
"copies": "1",
"size": "9249",
"license": "mit",
"hash": -4718978002478678000,
"line_mean": 35.2705882353,
"line_max": 143,
"alpha_frac": 0.650556817,
"autogenerated": false,
"ratio": 3.102650117410265,
"config_test":... |
## A script for finding every cox coefficient and pvalue for every mRNA in ESCA Tier 3 data downloaded Jan 5th 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fro... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/ESCA/cox_regression.py",
"copies": "1",
"size": "10196",
"license": "mit",
"hash": 3291891384934671400,
"line_mean": 33.7986348123,
"line_max": 142,
"alpha_frac": 0.6432914869,
"autogenerated": false,
"ratio": 3.119951040391677,
"config_test"... |
## A script for finding every cox coefficient and pvalue for every mRNA in GBM Tier 3 data downloaded Feb. 2015
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/GBM/cox_regression.py",
"copies": "1",
"size": "8147",
"license": "mit",
"hash": 761838528711713800,
"line_mean": 33.5211864407,
"line_max": 142,
"alpha_frac": 0.6407266478,
"autogenerated": false,
"ratio": 3.0848163574403635,
"... |
## A script for finding every cox coefficient and pvalue for every mRNA in GBM Tier 3 data downloaded Jan. 5th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
#... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/GBM/cox_regression.py",
"copies": "1",
"size": "9246",
"license": "mit",
"hash": -1008117323300189300,
"line_mean": 34.8372093023,
"line_max": 142,
"alpha_frac": 0.6519576033,
"autogenerated": false,
"ratio": 3.103726082578046,
"config_test":... |
## A script for finding every cox coefficient and pvalue for every mRNA in HNSC Tier 3 data downloaded Feb. 2015
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not running from the command... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/HNSC/cox_regression.py",
"copies": "1",
"size": "10573",
"license": "mit",
"hash": -9125553782175850000,
"line_mean": 31.8354037267,
"line_max": 143,
"alpha_frac": 0.6070178757,
"autogenerated": false,
"ratio": 3.1188790560471977,... |
## A script for finding every cox coefficient and pvalue for every mRNA in HNSC Tier 3 data downloaded Jan 5th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fro... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/HNSC/cox_regression.py",
"copies": "1",
"size": "11703",
"license": "mit",
"hash": 3601466821139916000,
"line_mean": 34.1441441441,
"line_max": 143,
"alpha_frac": 0.6341109117,
"autogenerated": false,
"ratio": 3.1034208432776453,
"config_test... |
## A script for finding every cox coefficient and pvalue for every mRNA in KIRC Tier 3 data downloaded Feb. 2015
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not running from the command ... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/KIRC/cox_regression.py",
"copies": "1",
"size": "9445",
"license": "mit",
"hash": -7048869404970509000,
"line_mean": 31.7951388889,
"line_max": 142,
"alpha_frac": 0.6208575966,
"autogenerated": false,
"ratio": 3.1079302402105955,
... |
## A script for finding every cox coefficient and pvalue for every mRNA in KIRC Tier 3 data downloaded Jan. 5th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running fr... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/KIRC/cox_regression.py",
"copies": "1",
"size": "10258",
"license": "mit",
"hash": -3638448818155716000,
"line_mean": 33.6554054054,
"line_max": 142,
"alpha_frac": 0.6396958471,
"autogenerated": false,
"ratio": 3.095353047676524,
"config_test... |
## A script for finding every cox coefficient and pvalue for every mRNA in KIRP Tier 3 data downloaded Feb. 2015
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not running from the comman... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/KIRP/cox_regression.py",
"copies": "1",
"size": "8289",
"license": "mit",
"hash": -6886103651173132000,
"line_mean": 33.1111111111,
"line_max": 143,
"alpha_frac": 0.6297502714,
"autogenerated": false,
"ratio": 3.0814126394052046,
... |
## A script for finding every cox coefficient and pvalue for every mRNA in KIRP Tier 3 data downloaded Jan. 5th, 2016
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
##If you are not running f... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/KIRP/cox_regression.py",
"copies": "1",
"size": "9021",
"license": "mit",
"hash": 8307401601167608000,
"line_mean": 35.2289156627,
"line_max": 143,
"alpha_frac": 0.6485977164,
"autogenerated": false,
"ratio": 3.074642126789366,
"config_test":... |
## A script for finding every cox coefficient and pvalue for every mRNA in LAML Tier 3 data downloaded Feb. 2015
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/LAML/cox_regression.py",
"copies": "1",
"size": "6524",
"license": "mit",
"hash": -7133557067043312000,
"line_mean": 33.5185185185,
"line_max": 143,
"alpha_frac": 0.6434702636,
"autogenerated": false,
"ratio": 3.1007604562737643,
... |
## A script for finding every cox coefficient and pvalue for every mRNA in LAML Tier 3 data downloaded Jan. 5th, 2016
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
import re
##This call will only work if you are running python from the command line.
#... | {
"repo_name": "OmnesRes/onco_lnc",
"path": "mrna/cox/LAML/cox_regression.py",
"copies": "1",
"size": "6971",
"license": "mit",
"hash": -609931933921508900,
"line_mean": 34.5663265306,
"line_max": 143,
"alpha_frac": 0.6522737054,
"autogenerated": false,
"ratio": 3.099599822143175,
"config_test":... |
## A script for finding every cox coefficient and pvalue for every mRNA in LGG Tier 3 data downloaded Feb. 2015
## Load necessary modules
from rpy2 import robjects as ro
import numpy as np
import os
ro.r('library(survival)')
##This call will only work if you are running python from the command line.
##If you are not... | {
"repo_name": "OmnesRes/pan_cancer",
"path": "paper/cox_regression/LGG/cox_regression.py",
"copies": "1",
"size": "8870",
"license": "mit",
"hash": 4592270440754724000,
"line_mean": 32.5984848485,
"line_max": 142,
"alpha_frac": 0.6340473506,
"autogenerated": false,
"ratio": 3.0820013898540655,
... |
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