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# baud.py Test uasyncio at high baudrate
import pyb
import uasyncio as asyncio
import utime
import as_drivers.as_rwGPS as as_rwGPS
# Outcome
# Sleep Buffer
# 0 None OK, length limit 74
# 10 None Bad: length 111 also short weird RMC sentences
# 10 1000 OK, length 74, 37
# 10 200 Bad: 100, 37 ov... | {
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"""bayabill URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.8/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-ba... | {
"repo_name": "rapidevelop/bayabill",
"path": "bayabill/urls.py",
"copies": "1",
"size": "1129",
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"autogenerated": false,
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"config_test": false,
"h... |
"""Bay Bridge simulation."""
import os
import urllib.request
from flow.core.params import SumoParams, EnvParams, NetParams, InitialConfig, \
SumoCarFollowingParams, SumoLaneChangeParams, InFlows
from flow.core.params import VehicleParams
from flow.core.params import TrafficLightParams
from flow.core.experiment i... | {
"repo_name": "cathywu/flow",
"path": "examples/sumo/bay_bridge.py",
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"""Bay Bridge toll example."""
import os
import urllib.request
from flow.core.params import SumoParams, EnvParams, NetParams, InitialConfig, \
SumoLaneChangeParams, SumoCarFollowingParams, InFlows
from flow.core.params import VehicleParams
from flow.core.experiment import Experiment
from flow.envs.bay_bridge.bas... | {
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# bayesAgents.py
# --------------
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.e... | {
"repo_name": "omardroubi/Artificial-Intelligence",
"path": "Projects/Project4/bayesAgents.py",
"copies": "1",
"size": "18932",
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"""Bayes - determine spam likelihood using a Bayesian classifier.
This is a Bayesian-style probabilistic classifier, using an algorithm
based on the one detailed in Paul Graham's "A Plan For Spam" paper at:
http://www.paulgraham.com/spam.html
It also incorporates some other aspects taken from Graham Robinson's
webpa... | {
"repo_name": "SpamExperts/OrangeAssassin",
"path": "oa/plugins/bayes.py",
"copies": "2",
"size": "52828",
"license": "apache-2.0",
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"line_max": 187,
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"autogenerated": false,
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#Bayes Distribution Classifier
#One classifier per class- each is just a binary classifier.
import nltk
import random
rw_cards = [ card.replace(" ", "_") for card in [
"fool", "magician", "high priestess", "empress", "emperor", "hierophant","lovers",
"chariot", "strength","hermit", "wheel of fortune", "justice",... | {
"repo_name": "pgulley/tarot-nlp",
"path": "dist_bayes.py",
"copies": "1",
"size": "3714",
"license": "mit",
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"line_mean": 30.218487395,
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"alpha_frac": 0.6532040926,
"autogenerated": false,
"ratio": 2.8880248833592534,
"config_test": true,
"has_no_k... |
# bayes_exp.py
# Ronald L. Rivest and Emily Shen
# 5/31/12
# Code for working with ``Bayes Post-Election Audits''
# Specifically: for running experiments
# The auditing code itself in in bayes.py
# For efficiency reasons, it is recommended to run this code with
# "pypy" instead of the standard python interpreter.... | {
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## BAYESIAN ANALYSIS FOR PERIODOGRAMS
#
#
#
#
# TO DO LIST:
# - add functionality for mixture models/QPOs to mlprior
# - add logging
# - add smoothing to periodograms to pick out narrow signals
# - add proposal distributions to emcee implementation beyond Gaussian
#
#!/usr/bin/env python
from __future__ import print_fu... | {
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"path": "BayesPSD/bayes.py",
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# Bayesian Binary logistic regression in 1d for iris flowers
# Code is based on
# https://github.com/aloctavodia/BAP/blob/master/code/Chp4/04_Generalizing_linear_models.ipynb
import pymc3 as pm
import numpy as np
import pandas as pd
import theano.tensor as tt
#import seaborn as sns
import scipy.stats as stats
from s... | {
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"path": "scripts/logreg_iris_bayes_1d_pymc3.py",
"copies": "1",
"size": "2690",
"license": "mit",
"hash": -6731460946902615000,
"line_mean": 26.5670103093,
"line_max": 94,
"alpha_frac": 0.6071829405,
"autogenerated": false,
"ratio": 2.5384615384615383,
"config_t... |
# Bayesian Binary logistic regression in 2d for iris flwoers
# Code is based on
# https://github.com/aloctavodia/BAP/blob/master/code/Chp4/04_Generalizing_linear_models.ipynb
import pymc3 as pm
import numpy as np
import pandas as pd
import theano.tensor as tt
#import seaborn as sns
import scipy.stats as stats
from s... | {
"repo_name": "probml/pyprobml",
"path": "scripts/logreg_iris_bayes_2d_pymc3.py",
"copies": "1",
"size": "2107",
"license": "mit",
"hash": 9028580673305341000,
"line_mean": 25.7948717949,
"line_max": 94,
"alpha_frac": 0.6258373206,
"autogenerated": false,
"ratio": 2.638888888888889,
"config_tes... |
"""Bayesian confirmatory factor analysis in PyMC3.
"""
import numpy as np
import pandas as pd
import pymc3 as pm
import theano.tensor as tt
from os.path import exists
from pymc3.math import matrix_dot
from fmt_val_latex import format_for_latex
def bcfa(Y, M):
r"""Constructs a Bayesian confirmatory factor anal... | {
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"path": "assets/_scripts/bcfa.py",
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# bayesiandb.py
# old bailey
#
# naive bayesian learner
# adapted from Segaran, Programming Collective Intelligence, Ch. 6
# persists training info in SQLite DB
from pysqlite2 import dbapi2 as sqlite
stopwords = ['a', 'about', 'above', 'across', 'after', 'afterwards']
stopwords += ['again', 'against', 'all'... | {
"repo_name": "williamjturkel/Digital-History-Hacks--2005-08-",
"path": "bayesiandb.py",
"copies": "1",
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""" Bayesian Determinisitc Policy Gradient evaluated on th
didactic "chain" environment
"""
import tensorflow as tf
from tensorflow.python.layers.utils import smart_cond
from tensorflow.python.ops.variable_scope import get_local_variable
import chi
from chi import Experiment
from chi import experiment, model
from chi... | {
"repo_name": "rmst/chi",
"path": "examples/experimental/bdpg_chains.py",
"copies": "1",
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"license": "mit",
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"alpha_frac": 0.6667845773,
"autogenerated": false,
"ratio": 3.030010718113612,
"config_test": false,
"... |
"""Bayesian estimation for two groups
This module implements Bayesian estimation for two groups, providing
complete distributions for effect size, group means and their
difference, standard deviations and their difference, and the
normality of the data.
Based on:
Kruschke, J. (2012) Bayesian estimation supersedes th... | {
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"path": "best/__init__.py",
"copies": "2",
"size": "3140",
"license": "mit",
"hash": 4955351682058425000,
"line_mean": 29.4854368932,
"line_max": 80,
"alpha_frac": 0.6200636943,
"autogenerated": false,
"ratio": 3.102766798418972,
"config_test": false,
"has_no_ke... |
"""Bayesian Gaussian Mixture Model."""
# Author: Wei Xue <xuewei4d@gmail.com>
# Thierry Guillemot <thierry.guillemot.work@gmail.com>
# License: BSD 3 clause
import math
import numpy as np
from scipy.special import betaln, digamma, gammaln
from .base import BaseMixture, _check_shape
from .gaussian_mixture impo... | {
"repo_name": "Vimos/scikit-learn",
"path": "sklearn/mixture/bayesian_mixture.py",
"copies": "17",
"size": "32965",
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"""Bayesian Gaussian Mixture Models and
Dirichlet Process Gaussian Mixture Models"""
from __future__ import print_function
# Author: Alexandre Passos (alexandre.tp@gmail.com)
# Bertrand Thirion <bertrand.thirion@inria.fr>
#
# Based on mixture.py by:
# Ron Weiss <ronweiss@gmail.com>
# Fabian Ped... | {
"repo_name": "ldirer/scikit-learn",
"path": "sklearn/mixture/dpgmm.py",
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"config_t... |
"""Bayesian Gaussian Mixture Models and
Dirichlet Process Gaussian Mixture Models"""
# Author: Alexandre Passos (alexandre.tp@gmail.com)
# Bertrand Thirion <bertrand.thirion@inria.fr>
#
# Based on mixture.py by:
# Ron Weiss <ronweiss@gmail.com>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
... | {
"repo_name": "cdegroc/scikit-learn",
"path": "sklearn/mixture/dpgmm.py",
"copies": "1",
"size": "29986",
"license": "bsd-3-clause",
"hash": 8603487796028585000,
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"autogenerated": false,
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"""Bayesian Generalized Linear Model implementation.
Implementation of Bayesian GLMs using a mixture of Gaussians posterior
approximation with the reparameterization trick and variational inference. See
[1]_ for the posterior mixture idea, and [2]_ for the inference scheme.
.. [1] Gershman, S., Hoffman, M., & Blei, D... | {
"repo_name": "NICTA/revrand",
"path": "revrand/glm.py",
"copies": "1",
"size": "25530",
"license": "apache-2.0",
"hash": 3314980036645843500,
"line_mean": 34.856741573,
"line_max": 79,
"alpha_frac": 0.5724245985,
"autogenerated": false,
"ratio": 3.906058751529988,
"config_test": false,
"has_... |
#Bayesian inference for simple linear regression with known noise variance
#The goal is to reproduce fig 3.7 from Bishop's book.
#We fit the linear model f(x,w) = w0 + w1*x and plot the posterior over w.
import numpy as np
import matplotlib.pyplot as plt
import os
import pyprobml_utils as pml
from scipy.stats ... | {
"repo_name": "probml/pyprobml",
"path": "scripts/linreg_2d_bayes_demo.py",
"copies": "1",
"size": "5078",
"license": "mit",
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"line_mean": 31.3439490446,
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"autogenerated": false,
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"config_test":... |
""" Bayesian Linear Sampler Module. """
import logging
import numpy as np
import scipy
import scipy.stats as stats
import scipy.linalg as linalg
from dora.active_sampling.base_sampler import Sampler, random_sample
log = logging.getLogger(__name__)
class BayesianLinear(Sampler):
"""Bayesian linear model.
Att... | {
"repo_name": "NICTA/dora",
"path": "dora/active_sampling/lin_sampler.py",
"copies": "1",
"size": "13768",
"license": "apache-2.0",
"hash": -6466430420537272000,
"line_mean": 33.0792079208,
"line_max": 164,
"alpha_frac": 0.5350087159,
"autogenerated": false,
"ratio": 3.9303454182129602,
"config... |
# Bayesian model selection demo for polynomial regression
# This illustartes that if we have more data, Bayes picks a more complex model.
# Based on a demo by Zoubin Ghahramani
import numpy as np
import matplotlib.pyplot as plt
import os
figdir = "../figures"
def save_fig(fname): plt.savefig(os.path.join(figdir, fnam... | {
"repo_name": "probml/pyprobml",
"path": "scripts/linreg_eb_modelsel_vs_n.py",
"copies": "1",
"size": "5689",
"license": "mit",
"hash": -2551013912274423300,
"line_mean": 35.7032258065,
"line_max": 112,
"alpha_frac": 0.607488135,
"autogenerated": false,
"ratio": 3.0036958817317845,
"config_test... |
"""bayesian_network.py
The purpose of this model is to assist with the construction of Bayesian Networks
designed for modeling the effects of a molecular mechanism. The goal is to learn
about this molecular mechanism by analysing the evidence that we have. We can then
perform a genome wide association compariang genot... | {
"repo_name": "christopher-gillies/MultiplePhenotypeAssociationBayesianNetwork",
"path": "mpabn/bayesian_network.py",
"copies": "1",
"size": "25945",
"license": "mit",
"hash": -3128055910550962700,
"line_mean": 26.5435244161,
"line_max": 234,
"alpha_frac": 0.6843322413,
"autogenerated": false,
"r... |
"""Bayesian optimization according to:
Brochu, Cora, and de Freitas' tutorial at
http://haikufactory.com/files/bayopt.pdf
Adopted from http://atpassos.me/post/44900091837/bayesian-optimization
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Alexandre Passos <alexandre.tp@gmail.... | {
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"path": "autoreject/bayesopt.py",
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# Bayesian optimization of 1d continuous function
# Modified from Martin Krasser's code
# https://github.com/krasserm/bayesian-machine-learning/blob/dev/bayesian-optimization/bayesian_optimization.ipynb
import numpy as np
from bayes_opt_utils import BayesianOptimizer, MultiRestartGradientOptimizer, expected_improveme... | {
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"path": "scripts/bayes_opt_demo.py",
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# Bayesian optimization of 1d regression
# Modified from Martin Krasser's code
# https://github.com/krasserm/bayesian-machine-learning/blob/dev/bayesian-optimization/bayesian_optimization.ipynb
import numpy as np
import matplotlib.pyplot as plt
import os
figdir = os.path.join(os.environ["PYPROBML"], "figures")
def sav... | {
"repo_name": "probml/pyprobml",
"path": "scripts/bayes_opt_demo_orig.py",
"copies": "1",
"size": "8767",
"license": "mit",
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"line_mean": 30.3071428571,
"line_max": 114,
"alpha_frac": 0.6124800365,
"autogenerated": false,
"ratio": 3.1726384364820848,
"config_test": fa... |
"""Bayesian regression for latent source model and Bitcoin.
This module implements the 'Bayesian regression for latent source model' method
for predicting price variation of Bitcoin. You can read more about the method
at https://arxiv.org/pdf/1410.1231.pdf.
"""
import numpy as np
import bigfloat as bg
from numpy.linal... | {
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"path": "bitcoin_price_prediction/bayesian_regression.py",
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"""Bayesian variant calling with FreeBayes.
https://github.com/ekg/freebayes
"""
import os
import sys
from bcbio import bam, utils
from bcbio.distributed.transaction import file_transaction
from bcbio.pipeline import config_utils
from bcbio.pipeline.shared import subset_variant_regions
from bcbio.provenance import d... | {
"repo_name": "elkingtonmcb/bcbio-nextgen",
"path": "bcbio/variation/freebayes.py",
"copies": "1",
"size": "14735",
"license": "mit",
"hash": 6933827038082164000,
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"line_max": 111,
"alpha_frac": 0.6038683407,
"autogenerated": false,
"ratio": 3.525963149078727,
"config... |
"""Bayesian variant calling with FreeBayes.
https://github.com/ekg/freebayes
"""
import os
import sys
import six
import toolz as tz
from bcbio import utils
from bcbio.distributed.transaction import file_transaction
from bcbio.heterogeneity import chromhacks
from bcbio.pipeline import config_utils, shared
from bcbio... | {
"repo_name": "vladsaveliev/bcbio-nextgen",
"path": "bcbio/variation/freebayes.py",
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"autogenerated": false,
"ratio": 3.599478539911753,
"confi... |
"""Bayesian variant calling with FreeBayes.
https://github.com/ekg/freebayes
"""
import os
import sys
import toolz as tz
from bcbio import utils
from bcbio.distributed.transaction import file_transaction
from bcbio.pipeline import config_utils, shared
from bcbio.pipeline import datadict as dd
from bcbio.provenance ... | {
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"path": "bcbio/variation/freebayes.py",
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"confi... |
from copy import deepcopy, copy
import networkx as nx
from PyBayes.ProbabilityTable import *
from warnings import warn
class BayesNet(object):
""" Bayes Net Implementation
Usage:
-
-
-
-
"""
def __init__(self, edges, variables, domains, probability... | {
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"path": "PyBayes/BayesNet.py",
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"autogenerated": false,
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# bayesNet.py
# -----------
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
# ... | {
"repo_name": "omardroubi/Artificial-Intelligence",
"path": "Projects/Project4/bayesNets/bayesNet.py",
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"autogenerated": false,
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# bayesNets2TestClasses.py
# ------------------------
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to ... | {
"repo_name": "omardroubi/Artificial-Intelligence",
"path": "Projects/Project4/bayesNets/bayesNets2TestClasses.py",
"copies": "1",
"size": "25415",
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"hash": 7159118383958792000,
"line_mean": 45.0416666667,
"line_max": 190,
"alpha_frac": 0.6622467047,
"autogenerated": false,
... |
# Bayes' Theorem
# P(A|B) = P(B|A) P(A) / P(B)
# A = "like"
# B = has key value B
# P(A) = |liked| / |url|
# P(B) = |key| / |url|
# P(B|A) = |liked from B| / |liked|
# P(A|B) = ((|liked from B| / |liked|) (|liked| / |url|)) / (|key| / |url|)
# = (|liked from B| / |url|) / (|key| / |url|) = |liked from B| / |key|... | {
"repo_name": "TobyRoseman/PS4M",
"path": "engine/analyzers/bayesScorer.py",
"copies": "1",
"size": "3041",
"license": "mit",
"hash": -100596529431874050,
"line_mean": 30.6770833333,
"line_max": 96,
"alpha_frac": 0.5501479776,
"autogenerated": false,
"ratio": 3.378888888888889,
"config_test": f... |
"""Bazaar-related utilities."""
from __future__ import absolute_import
import csv
import re
from builtins import bytes, str # pylint: disable=redefined-builtin
from six import StringIO
from readthedocs.projects.exceptions import ProjectImportError
from readthedocs.vcs_support.base import BaseVCS, VCSVersion
clas... | {
"repo_name": "pombredanne/readthedocs.org",
"path": "readthedocs/vcs_support/backends/bzr.py",
"copies": "1",
"size": "2972",
"license": "mit",
"hash": 7877630058621822000,
"line_mean": 28.4257425743,
"line_max": 78,
"alpha_frac": 0.5195154778,
"autogenerated": false,
"ratio": 3.9679572763684914... |
"""bazango URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.11/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-ba... | {
"repo_name": "rafal-jaworski/bazaNGObackend",
"path": "src/bazango/urls.py",
"copies": "1",
"size": "1543",
"license": "bsd-3-clause",
"hash": 4003575314507430400,
"line_mean": 35.7380952381,
"line_max": 120,
"alpha_frac": 0.7154893065,
"autogenerated": false,
"ratio": 3.772616136919315,
"conf... |
# bazel build polygerrit-ui/app:gr-app
# mitmdump -s "serve-app-locally.py ~/gerrit/bazel-bin/polygerrit-ui/app"
from mitmproxy import http
import argparse
import os
import zipfile
class Server:
def __init__(self, bundle):
self.bundle = bundle
self.bundlemtime = 0
self.files = {
... | {
"repo_name": "qtproject/qtqa-gerrit",
"path": "contrib/mitm-ui/serve-app-locally.py",
"copies": "1",
"size": "1490",
"license": "apache-2.0",
"hash": 4459688000218201000,
"line_mean": 31.3913043478,
"line_max": 73,
"alpha_frac": 0.5912751678,
"autogenerated": false,
"ratio": 3.6077481840193704,
... |
#################################################
# User configurable data section #
#################################################
# Put your Application ID and Secret here
APPID = '5KzQuKHIkxxxxxxxxxxxxxxxxxxSztLwiAF7'
SECRET = '0e68e582xxxxxxxxxxxxxxxxxxxx0f25f4'
#################################... | {
"repo_name": "pombreda/django-hotclub",
"path": "libs/external_libs/ybrowserauth/bbatestMAIL.py",
"copies": "5",
"size": "3094",
"license": "mit",
"hash": 3840916157860875000,
"line_mean": 40.2133333333,
"line_max": 181,
"alpha_frac": 0.5646412411,
"autogenerated": false,
"ratio": 3.415011037527... |
# BBB pinout
# http://insigntech.files.wordpress.com/2013/09/bbb_pinouts.jpg
# matrix test
from shifter import Shifter
import time
bitMap = ["00111111110000000111100111100000","00000110000000001111111111110000","00000110000000000111111111100000","00000110000000000011111111000000","00000110000000000001111110000000","0$... | {
"repo_name": "danasf/pyshift",
"path": "hs.py",
"copies": "1",
"size": "1111",
"license": "mit",
"hash": -2610692506729973000,
"line_mean": 40.1851851852,
"line_max": 188,
"alpha_frac": 0.5103510351,
"autogenerated": false,
"ratio": 3.4827586206896552,
"config_test": false,
"has_no_keywords"... |
# BBB pinout
# http://insigntech.files.wordpress.com/2013/09/bbb_pinouts.jpg
# space invader test
from shifter import Shifter
import time
frame1 = ["00001100000000000000000000000000","00011110000000000000000000000000","00111111000000000000000000000000","01101101100000000000000000000000","01111111100000000000000000000... | {
"repo_name": "danasf/pyshift",
"path": "invader.py",
"copies": "1",
"size": "1426",
"license": "mit",
"hash": 7413355258089985000,
"line_mean": 39.7428571429,
"line_max": 290,
"alpha_frac": 0.6297335203,
"autogenerated": false,
"ratio": 4.109510086455331,
"config_test": false,
"has_no_keywor... |
# BBB pinout
# http://insigntech.files.wordpress.com/2013/09/bbb_pinouts.jpg
# test
from shifter import Shifter
import time
# DATA (R1), DATA2 (R2), CLOCK, LATCH, SelA, SelB, SelC,OE
s = Shifter("P8_7","P8_13","P8_9","P8_11","P8_8","P8_10","P8_12","P8_14")
while True:
count = 0
while count < 16:
... | {
"repo_name": "danasf/pyshift",
"path": "leds.py",
"copies": "1",
"size": "1052",
"license": "mit",
"hash": 6899837230859295000,
"line_mean": 28.2222222222,
"line_max": 73,
"alpha_frac": 0.3935361217,
"autogenerated": false,
"ratio": 3.717314487632509,
"config_test": false,
"has_no_keywords":... |
# BBB_QC_Motor_Calibration.py
#
# Created by Peter Olejnik
#
# Created on: 16/01/2016
# Last concious update on: 17/01/2016
#
# Purpose - This data collection program is an outright replacement for
# the Quanser unit used up to this point. What this does is it
# collectes reading from two ADCS, each hooked up... | {
"repo_name": "ValRose/BBB_Quadcopter",
"path": "Flight_Program/Motor_Calibration.py",
"copies": "1",
"size": "4767",
"license": "mit",
"hash": 8180100545567713000,
"line_mean": 23.6994818653,
"line_max": 73,
"alpha_frac": 0.6813509545,
"autogenerated": false,
"ratio": 2.554662379421222,
"confi... |
# BBB_QC_Motor_Calibration.py
#
# Created by Peter Olejnik
#
# Created on: 16/01/2016
# Last concious update on: 17/01/2016
#
# Purpose - This program collects the data on a load cell calibration
# run.
#
# Inputs - Program wise none.
#
# Outputs - The ADC readout and pwm
#
#
############### Imports ####... | {
"repo_name": "ValRose/BBB_Quadcopter",
"path": "Data_Measurement/Load_Cell_Calibration.py",
"copies": "2",
"size": "2734",
"license": "mit",
"hash": -6834773921423108000,
"line_mean": 21.4098360656,
"line_max": 72,
"alpha_frac": 0.6686174104,
"autogenerated": false,
"ratio": 2.6187739463601534,
... |
import RPi.GPIO as GPIO
import time
import os
import random
buttonPin = 16
music = None
ledPin = 3
GPIO.setmode(GPIO.BOARD)
GPIO.setup(12, GPIO.OUT)
GPIO.setup(buttonPin, GPIO.IN)
GPIO.setup(ledPin, GPIO.OUT)
p = GPIO.PWM(12, 50)
p.start(10.5)
bb8_sounds = ['mpg321 /home/pi/Desktop/bb8/bb8_sounds/bb8_1.mp3', 'mpg... | {
"repo_name": "estefanniegg/estefannieExplainsItAll",
"path": "makes/bbCake/bb8cake.py",
"copies": "1",
"size": "1294",
"license": "mit",
"hash": -4286148329605209600,
"line_mean": 20.9322033898,
"line_max": 117,
"alpha_frac": 0.700927357,
"autogenerated": false,
"ratio": 2.5776892430278884,
"c... |
"""BBF usage guidelines plugin
See BBF Assigned Names and Numbers at https://wiki.broadband-forum.org/display/BBF/Assigned+Names+and+Numbers#AssignedNamesandNumbers-URNNamespaces
"""
import optparse
from pyang import plugin
from pyang.plugins import lint
def pyang_plugin_init():
plugin.register_plugin(BBFPlugin(... | {
"repo_name": "mbj4668/pyang",
"path": "pyang/plugins/bbf.py",
"copies": "1",
"size": "1116",
"license": "isc",
"hash": 4344616297095013400,
"line_mean": 30.8857142857,
"line_max": 147,
"alpha_frac": 0.5681003584,
"autogenerated": false,
"ratio": 3.943462897526502,
"config_test": false,
"has_... |
# *- bbgdatapuller.py *-
import os
import numpy as np
import pandas as pd
import blpapi
class BBGCaller(object):
'''
Base class serving as glue to different classes interacting with
the BBG terminal, but it has no further utility
'''
def __init__(self, **kwargs):
'''
Parameters
... | {
"repo_name": "tagomatech/ETL",
"path": "bbg/bbgdatapuller.py",
"copies": "1",
"size": "3838",
"license": "mit",
"hash": 7077557818234696000,
"line_mean": 28.984375,
"line_max": 116,
"alpha_frac": 0.5284002084,
"autogenerated": false,
"ratio": 4.297872340425532,
"config_test": false,
"has_no_... |
"""bbgo URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.11/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-based... | {
"repo_name": "genonfire/bbgo",
"path": "bbgo/urls.py",
"copies": "1",
"size": "2253",
"license": "mit",
"hash": -1764625336273409300,
"line_mean": 45.9375,
"line_max": 85,
"alpha_frac": 0.6706613404,
"autogenerated": false,
"ratio": 3.5093457943925235,
"config_test": false,
"has_no_keywords"... |
# bbigpicture crawls a subreddit and pulls out images/videos with large file sizes
import praw
from operator import itemgetter
from sys import stdout
try:
from urllib.request import urlopen
except:
from urllib2 import urlopen
subredditToProcess = 'funny'
submissionsToCheck = 100
topImageCount = 5
def getURL... | {
"repo_name": "spgar/bigpicture",
"path": "bigpicture.py",
"copies": "1",
"size": "2549",
"license": "mit",
"hash": -3922372990365256000,
"line_mean": 27.6516853933,
"line_max": 84,
"alpha_frac": 0.6539819537,
"autogenerated": false,
"ratio": 3.5304709141274238,
"config_test": false,
"has_no_... |
__author__ = 'Brady Hunsaker, Osman Ozaltin, Ted Ralphs, Aykut Bulut'
__maintainer__ = 'Aykut Bulut (aykut@lehigh.edu)'
"""
This package is for visualizing branch-and-bound. It also contains
a basic branch-and-bound implementation primarily for classroom and educational
use.
Communication with solvers is through a g... | {
"repo_name": "tkralphs/GrUMPy",
"path": "src/grumpy/BBTree.py",
"copies": "1",
"size": "97583",
"license": "epl-1.0",
"hash": -8279668600723684000,
"line_mean": 45.8698366955,
"line_max": 148,
"alpha_frac": 0.552411793,
"autogenerated": false,
"ratio": 4.095651808948208,
"config_test": false,
... |
# bbref.py
import datetime
import logging
import re
from string import ascii_lowercase
from bs4 import BeautifulSoup
from dateutil.parser import *
from nba.scraper import BasketballScraper
from nba.dates import datetostr
from nba.names import fuzzy_match
from nba.pipelines.bbref import *
from nba.player.nbacom impor... | {
"repo_name": "sansbacon/nba",
"path": "bbref.py",
"copies": "1",
"size": "15408",
"license": "mit",
"hash": -6796014073940704000,
"line_mean": 38.9170984456,
"line_max": 117,
"alpha_frac": 0.5242082035,
"autogenerated": false,
"ratio": 4.002077922077922,
"config_test": false,
"has_no_keyword... |
"""bbreminder URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.9/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-... | {
"repo_name": "samupl/bbreminder",
"path": "bbreminder/urls.py",
"copies": "1",
"size": "1062",
"license": "mit",
"hash": 7471257009328178000,
"line_mean": 41.48,
"line_max": 86,
"alpha_frac": 0.6883239171,
"autogenerated": false,
"ratio": 3.448051948051948,
"config_test": false,
"has_no_keyw... |
"""bbsauth -- verifies session token
<http://www.ietf.org/rfc/rfc4616.txt>
Copyright (c) 2009, Coptix, Inc. All rights reserved.
See the LICENSE file for license terms and warranty disclaimer.
"""
from __future__ import absolute_import
from sasl import mechanism as mech, auth
__all__ = ('BBSAuth')
class BBSAuth(me... | {
"repo_name": "HenryHu/pybbs",
"path": "bbsauth.py",
"copies": "1",
"size": "1665",
"license": "bsd-2-clause",
"hash": 1514998511847794200,
"line_mean": 25.015625,
"line_max": 70,
"alpha_frac": 0.5915915916,
"autogenerated": false,
"ratio": 3.899297423887588,
"config_test": false,
"has_no_key... |
bc = 5
mc = 5
pc = 5
while 1:
money = input("돈을 입력하세요: ")
if money == "admin":
while 1:
print("블랙커피:%s, 밀크커피:%s, 고급커피:%s" % (bc, mc, pc))
recharge = input("추가할 커피를 선택하시오-1:블랙커피,2:밀크커피,3:고급커피,4:exit: ")
if int(recharge) == 1:
plus_bc = int(input("추가할 블랙... | {
"repo_name": "imn00133/pythonSeminar17",
"path": "exercise/vending_machine/Jungu/09_10_coffee.py",
"copies": "1",
"size": "2163",
"license": "mit",
"hash": -8728807512034161000,
"line_mean": 31.0555555556,
"line_max": 75,
"alpha_frac": 0.4240323512,
"autogenerated": false,
"ratio": 1.78453608247... |
"""bcbio init"""
import os
import copy
import yaml
from itertools import izip
from scilifelab.utils.dry import dry_rsync
from scilifelab.utils.misc import opt_to_dict
from scilifelab.log import minimal_logger
from bcbio.pipeline.run_info import _unique_flowcell_info
LOG = minimal_logger(__name__)
POST_PROCESS_OPTS =... | {
"repo_name": "jun-wan/scilifelab",
"path": "scilifelab/bcbio/__init__.py",
"copies": "4",
"size": "7062",
"license": "mit",
"hash": 1018628515879511800,
"line_mean": 40.5411764706,
"line_max": 161,
"alpha_frac": 0.5872274143,
"autogenerated": false,
"ratio": 3.6685714285714286,
"config_test": ... |
"""bcbio qc module. Parsers for collecting qc metrics."""
import os
import re
import yaml
import glob
import xml.parsers.expat
from uuid import uuid4
import json
import numpy as np
import csv
import collections
import xml.etree.cElementTree as ET
from bs4 import BeautifulSoup
import datetime
from scilifelab.log import... | {
"repo_name": "jun-wan/scilifelab",
"path": "scilifelab/bcbio/qc/__init__.py",
"copies": "4",
"size": "41191",
"license": "mit",
"hash": 8712598117762880000,
"line_mean": 40.6070707071,
"line_max": 288,
"alpha_frac": 0.5534704183,
"autogenerated": false,
"ratio": 3.8388630009319664,
"config_tes... |
"""bcbio run module"""
import os
import re
import yaml
import glob
from itertools import chain
import pandas as pd
import datetime
from scilifelab.utils.misc import filtered_walk, query_yes_no, prune_option_list
from scilifelab.utils.dry import dry_write, dry_backup, dry_unlink, dry_rmdir, dry_makedir
from scilifelab.... | {
"repo_name": "jun-wan/scilifelab",
"path": "scilifelab/bcbio/run.py",
"copies": "4",
"size": "17863",
"license": "mit",
"hash": -6198398954029245000,
"line_mean": 45.8845144357,
"line_max": 250,
"alpha_frac": 0.6122711751,
"autogenerated": false,
"ratio": 3.4504539308479814,
"config_test": tru... |
import numpy as np
import tensorflow as tf
from GPflow.tf_wraps import eye
from GPflow.model import GPModel
from GPflow._settings import settings
from GPflow.mean_functions import Zero
from GPflow.param import Param, DataHolder
from GPflow.densities import multivariate_normal
from GPflow import kernels, transforms, li... | {
"repo_name": "ShibataLabPrivate/GPyWorkshop",
"path": "Experiments/bcgplvm.py",
"copies": "1",
"size": "5962",
"license": "mit",
"hash": 8472915980121355000,
"line_mean": 38.2236842105,
"line_max": 104,
"alpha_frac": 0.6252935257,
"autogenerated": false,
"ratio": 3.4402769763416043,
"config_te... |
# BCImage
# Get 2D list of pixels, indexed by [row][col].
# Each element is a list [red, green, blue]
# (So, it's really 3D ...)
# Return the red, green, blue values of the pixel at location (x,y) of the photo.
def _get_pixel(photo, x, y):
p = photo.get(x, y)
vals = p.split(" ")
r = int(vals[0])
... | {
"repo_name": "rootulp/school",
"path": "cs101/HW8/BCImage.py",
"copies": "1",
"size": "1130",
"license": "mit",
"hash": -3672807867271397400,
"line_mean": 30.2857142857,
"line_max": 101,
"alpha_frac": 0.5672566372,
"autogenerated": false,
"ratio": 3.021390374331551,
"config_test": false,
"ha... |
# BCOnvert.py v0.1 by Yoshi2
import time
import argparse
import os
import subprocess
from re import match
from struct import pack, unpack
from math import floor, ceil
import math
def read_vertex(v_data):
split = v_data.split("/")
#if len(split) == 3:
# vnormal = int(split[2])
#else:
# vnorm... | {
"repo_name": "RenolY2/mkdd-collision",
"path": "BCOnvert.py",
"copies": "1",
"size": "28319",
"license": "mit",
"hash": -2315562074346569700,
"line_mean": 34.0482673267,
"line_max": 139,
"alpha_frac": 0.5138599527,
"autogenerated": false,
"ratio": 3.3032777324157236,
"config_test": false,
"h... |
"""bCourses configuration
Revision ID: 50937c69da0b
Revises: 0c98b865104f
Create Date: 2016-11-14 20:16:39.879837
"""
# revision identifiers, used by Alembic.
revision = '50937c69da0b'
down_revision = '0c98b865104f'
from alembic import op
import sqlalchemy as sa
import server
def upgrade():
### commands auto ... | {
"repo_name": "Cal-CS-61A-Staff/ok",
"path": "migrations/versions/50937c69da0b_bcourses_configuration.py",
"copies": "1",
"size": "2624",
"license": "apache-2.0",
"hash": -4489860545951288300,
"line_mean": 47.5925925926,
"line_max": 138,
"alpha_frac": 0.6962652439,
"autogenerated": false,
"ratio"... |
"""BCP module."""
import asyncio
from functools import partial
from typing import List
from mpf.core.events import QueuedEvent
from mpf.core.mpf_controller import MpfController
from mpf.core.bcp.bcp_server import BcpServer
from mpf.core.utility_functions import Util
from mpf.core.bcp.bcp_interface import BcpInterfac... | {
"repo_name": "missionpinball/mpf",
"path": "mpf/core/bcp/bcp.py",
"copies": "1",
"size": "4677",
"license": "mit",
"hash": -9000619983028722000,
"line_mean": 38.3025210084,
"line_max": 106,
"alpha_frac": 0.601881548,
"autogenerated": false,
"ratio": 4.172167707404103,
"config_test": true,
"h... |
"""Bcp server for clients which connect and disconnect randomly."""
from mpf.exceptions.runtime_error import MpfRuntimeError
from mpf.core.utility_functions import Util
from mpf.core.mpf_controller import MpfController
class BcpServer(MpfController):
"""Server socket which listens for incoming BCP clients."""
... | {
"repo_name": "missionpinball/mpf",
"path": "mpf/core/bcp/bcp_server.py",
"copies": "1",
"size": "1673",
"license": "mit",
"hash": -1865973294700756700,
"line_mean": 36.1777777778,
"line_max": 119,
"alpha_frac": 0.6120741184,
"autogenerated": false,
"ratio": 4.172069825436409,
"config_test": fa... |
"""BCP Server interface for the MPF Media Controller"""
# bcp_server.py
# Mission Pinball Framework
# Written by Brian Madden & Gabe Knuth
# Released under the MIT License. (See license info at the end of this file.)
# The Backbox Control Protocol was conceived and developed by:
# Quinn Capen
# Kevin Kelm
# Gabe Knuth... | {
"repo_name": "spierepf/mpf",
"path": "mpf/media_controller/core/bcp_server.py",
"copies": "2",
"size": "6587",
"license": "mit",
"hash": 6301569814928214000,
"line_mean": 34.0372340426,
"line_max": 84,
"alpha_frac": 0.5838773341,
"autogenerated": false,
"ratio": 4.514736120630569,
"config_test... |
"""BCP Server interface for the MPF Media Controller"""
import logging
import queue
import socket
import sys
import threading
import time
import traceback
import select
import mpf.core.bcp.bcp_socket_client as bcp
from mpf.exceptions.runtime_error import MpfRuntimeError
class BCPServer(threading.Thread):
"""Pa... | {
"repo_name": "missionpinball/mpf-mc",
"path": "mpfmc/core/bcp_server.py",
"copies": "2",
"size": "9878",
"license": "mit",
"hash": -8285285205772493000,
"line_mean": 38.0434782609,
"line_max": 114,
"alpha_frac": 0.5060741041,
"autogenerated": false,
"ratio": 4.953861584754263,
"config_test": f... |
"""BCP Server interface for the MPF Media Controller"""
import logging
import queue
import socket
import threading
import os
import select
from datetime import datetime
import math
import mpf.core.bcp.bcp_socket_client as bcp
from PyQt5.QtCore import QTimer
class BCPClient(object):
def __init__(self, mpfmon,... | {
"repo_name": "missionpinball/mpf-monitor",
"path": "mpfmonitor/core/bcp_client.py",
"copies": "1",
"size": "8878",
"license": "mit",
"hash": -6553435907485042000,
"line_mean": 32.7566539924,
"line_max": 158,
"alpha_frac": 0.5544041451,
"autogenerated": false,
"ratio": 4.229633158646974,
"confi... |
"""BCP socket client."""
import json
from urllib.parse import urlsplit, parse_qs, quote, unquote, urlunparse
import asyncio
from typing import Tuple
from mpf._version import __version__, __bcp_version__
from mpf.core.bcp.bcp_client import BaseBcpClient
class MpfJSONEncoder(json.JSONEncoder):
"""Encoder which ... | {
"repo_name": "missionpinball/mpf",
"path": "mpf/core/bcp/bcp_socket_client.py",
"copies": "1",
"size": "10954",
"license": "mit",
"hash": 2759327995862957000,
"line_mean": 30.0311614731,
"line_max": 119,
"alpha_frac": 0.5624429432,
"autogenerated": false,
"ratio": 4.158694001518603,
"config_te... |
"""bcrypt and hmac implementation for Django."""
import base64
import hashlib
import logging
import bcrypt
import hmac
from django.conf import settings
from django.contrib.auth.models import get_hexdigest
from django.utils.encoding import smart_str
log = logging.getLogger('django_sha2')
def create_hash(userpwd):
... | {
"repo_name": "fwenzel/django-sha2",
"path": "django_sha2/bcrypt_auth.py",
"copies": "1",
"size": "3139",
"license": "bsd-3-clause",
"hash": -3546868525839659500,
"line_mean": 33.1195652174,
"line_max": 88,
"alpha_frac": 0.6396941701,
"autogenerated": false,
"ratio": 3.5670454545454544,
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"""bcrypt and hmac implementation for Django."""
import base64
import hashlib
import bcrypt
import hmac
from django.conf import settings
def create_hash(userpwd):
"""Given a password, create a key to be stored in the DB."""
if not settings.HMAC_KEYS:
raise ImportError('settings.HMAC_KEYS must not be... | {
"repo_name": "brianloveswords/django-sha2",
"path": "django_sha2/bcrypt_auth.py",
"copies": "1",
"size": "1794",
"license": "bsd-3-clause",
"hash": 9055262426584656000,
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"line_max": 76,
"alpha_frac": 0.6599777035,
"autogenerated": false,
"ratio": 3.4302103250478013,
... |
# BCrypt was developed to replace md5_crypt for BSD systems.
# It uses a modified version of the Blowfish stream cipher.
# Featuring a large salt and variable number of rounds,
# it's currently the default password hash for many systems
# (notably BSD), and has no known weaknesses.
# See: http://pythonhosted.org/passli... | {
"repo_name": "RichardKnop/django-oauth2-server",
"path": "oauth2server/apps/credentials/models.py",
"copies": "1",
"size": "3525",
"license": "mpl-2.0",
"hash": 4428923000508719000,
"line_mean": 30.203539823,
"line_max": 79,
"alpha_frac": 0.6314893617,
"autogenerated": false,
"ratio": 4.02397260... |
## bctg.py
## by andrew wayne teesdale jr.
class LL:
def __init__(self, ll, name):
import random
self.randnum=random.choice(['True', 'False'])
self.msg=random.choice(['I dont know.', 'Oh, Yes '+ll, 'I think '+name+' knows.'])
def say_to(self, msg):
## msging system
print ... | {
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"path": "recipes/Python/578623_adventure_game_base/recipe-578623.py",
"copies": "1",
"size": "4302",
"license": "mit",
"hash": -4176467536647650000,
"line_mean": 28.6689655172,
"line_max": 96,
"alpha_frac": 0.5172013017,
"autogenerated": false,
"ratio": 3.4554216... |
"""BD2013 dataset loader to be used with DeepMHC."""
from __future__ import division
from __future__ import print_function
__author__ = "Vignesh Ram Somnath"
__license__ = "MIT"
import numpy as np
import os
import logging
import deepchem as dc
DATASET_URL = "http://tools.iedb.org/static/main/binding_data_2013.zip"... | {
"repo_name": "peastman/deepchem",
"path": "contrib/DeepMHC/bd13_datasets.py",
"copies": "5",
"size": "5208",
"license": "mit",
"hash": 5854156926600183000,
"line_mean": 33.72,
"line_max": 95,
"alpha_frac": 0.6380568356,
"autogenerated": false,
"ratio": 3.0798344175044354,
"config_test": true,
... |
"""bdalg.py
This file contains some standard block diagram algebra.
Routines in this module:
append
series
parallel
negate
feedback
connect
"""
"""Copyright (c) 2010 by California Institute of Technology
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are perm... | {
"repo_name": "murrayrm/python-control",
"path": "control/bdalg.py",
"copies": "2",
"size": "12183",
"license": "bsd-3-clause",
"hash": -4822685365977349000,
"line_mean": 31.4015957447,
"line_max": 80,
"alpha_frac": 0.641631782,
"autogenerated": false,
"ratio": 3.9073123797305964,
"config_test"... |
# bdateutil
# -----------
# Adds business day logic and improved data type flexibility to
# python-dateutil. 100% backwards compatible with python-dateutil,
# simply replace dateutil imports with bdateutil.
#
# Author: ryanss <ryanssdev@icloud.com>
# Website: https://github.com/ryanss/bdateutil
# License: MIT ... | {
"repo_name": "pganssle/bdateutil",
"path": "bdateutil/relativedelta.py",
"copies": "1",
"size": "10420",
"license": "mit",
"hash": 7595475299879946000,
"line_mean": 42.5983263598,
"line_max": 78,
"alpha_frac": 0.4717850288,
"autogenerated": false,
"ratio": 4.203307785397338,
"config_test": fal... |
"""bdist_mpkg.cmd_bdist_mpkg
Implements the Distutils 'bdist_mpkg' command (create an OS X "mpkg"
binary distribution)."""
import os
import sys
import zipfile
from setuptools import Command
from distutils.util import get_platform, byte_compile
from distutils.dir_util import remove_tree, mkpath
from distutils.errors... | {
"repo_name": "bitcraft/pyglet",
"path": "tools/genmpkg/bdist_mpkg_pyglet/cmd_bdist_mpkg.py",
"copies": "1",
"size": "17741",
"license": "bsd-3-clause",
"hash": -7712228298910726000,
"line_mean": 34.7681451613,
"line_max": 86,
"alpha_frac": 0.5702046108,
"autogenerated": false,
"ratio": 4.0671710... |
"""bdist_nsi.bdist_nsi
Implements the Distutils 'bdist_nsi' command: create a Windows NSIS installer.
"""
# Created 2005/05/24, j-cg , inspired by the bdist_wininst of the python
# distribution
# June/July 2009 (Amorilia):
# - further developed, 2to3, blender, maya
# December 2009/January 2010 (Amorilia):
# - a... | {
"repo_name": "amorilia/bdist_nsi",
"path": "bdist_nsi/bdist_nsi.py",
"copies": "1",
"size": "69126",
"license": "bsd-3-clause",
"hash": 8809018936613052000,
"line_mean": 35.9262820513,
"line_max": 381,
"alpha_frac": 0.585293522,
"autogenerated": false,
"ratio": 3.439446711115534,
"config_test"... |
bdLibPath=os.path.abspath(sys.argv[0]+"..")
if not bdLibPath in sys.path: sys.path.append(bdLibPath)
from _lib import *
import unittest
class SmokeTests(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_001_GoogleSearch(self):
LaunchB... | {
"repo_name": "YoTsenkov/TelerikSoftwareAcademyHomeworks",
"path": "QA/Sikuli/sikuli_tests/smoke_tests.sikuli/smoke_tests.py",
"copies": "1",
"size": "3679",
"license": "mit",
"hash": -6714345372082455000,
"line_mean": 32.4454545455,
"line_max": 109,
"alpha_frac": 0.6841533025,
"autogenerated": fal... |
"""bdo_tools URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.9/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-b... | {
"repo_name": "zsommers/bdo_chronicle",
"path": "bdo_tools/bdo_tools/urls.py",
"copies": "1",
"size": "1728",
"license": "mit",
"hash": -561749877013865600,
"line_mean": 40.1428571429,
"line_max": 85,
"alpha_frac": 0.6996527778,
"autogenerated": false,
"ratio": 3.4979757085020244,
"config_test"... |
# Be able to call directly such as `python test_annotators.py`
try:
from .context import loctext
except SystemError: # Parent module '' not loaded, cannot perform relative import
pass
from loctext.util import PRO_ID, LOC_ID, ORG_ID, REL_PRO_LOC_ID, UNIPROT_NORM_ID, GO_NORM_ID, TAXONOMY_NORM_ID
from nalaf.lear... | {
"repo_name": "Rostlab/LocText",
"path": "tests/test_corpus_stats.py",
"copies": "2",
"size": "4461",
"license": "apache-2.0",
"hash": -7051875492359709000,
"line_mean": 41.8942307692,
"line_max": 266,
"alpha_frac": 0.6494059628,
"autogenerated": false,
"ratio": 2.8596153846153847,
"config_test... |
# Be able to call directly such as `python test_annotators.py`
try:
from .context import loctext
except SystemError: # Parent module '' not loaded, cannot perform relative import
pass
from pytest import raises
from loctext.util import PRO_ID, LOC_ID, REL_PRO_LOC_ID, repo_path, UNIPROT_NORM_ID, GO_NORM_ID
from... | {
"repo_name": "juanmirocks/LocText",
"path": "tests/test_loctext_writing_of_normalizations.py",
"copies": "2",
"size": "3876",
"license": "apache-2.0",
"hash": -2464471812397149700,
"line_mean": 38.1515151515,
"line_max": 161,
"alpha_frac": 0.6767285862,
"autogenerated": false,
"ratio": 3.5494505... |
"""Be able to merge a CSV file that IDOT provides"""
import sys
import datetime
import pandas as pd
from pyiem.util import get_dbconn
pgconn = get_dbconn("postgis")
cursor = pgconn.cursor()
xref = {}
cursor.execute("""SELECT idot_id, segid from roads_base""")
for row in cursor:
xref[row[0]] = row[1]
ROADCOND = {... | {
"repo_name": "akrherz/iem",
"path": "scripts/roads/idot_csv_ingest.py",
"copies": "1",
"size": "1493",
"license": "mit",
"hash": -235465106682183040,
"line_mean": 27.7115384615,
"line_max": 60,
"alpha_frac": 0.6383121232,
"autogenerated": false,
"ratio": 2.997991967871486,
"config_test": false... |
"""Beacon advertisement parser."""
from construct import ConstructError
from .structs import LTVFrame
from .packet_types import EddystoneUIDFrame, EddystoneURLFrame, EddystoneEncryptedTLMFrame, \
EddystoneTLMFrame, EddystoneEIDFrame, IBeaconAdvertisement, \
EstimoteT... | {
"repo_name": "citruz/beacontools",
"path": "beacontools/parser.py",
"copies": "1",
"size": "3670",
"license": "mit",
"hash": 6683110906443822000,
"line_mean": 42.1764705882,
"line_max": 99,
"alpha_frac": 0.6354223433,
"autogenerated": false,
"ratio": 3.4952380952380953,
"config_test": false,
... |
"""beacon
Functions for interacting with the remote beacon to retrieve records.
rest api root:
https://beacon.nist.gov/rest/
rest api example endpoints:
https://beacon.nist.gov/rest/record/1395971640
https://beacon.nist.gov/rest/record/previous/1395971640
https://beacon.nist.gov/rest/record/next/139... | {
"repo_name": "codycollier/netropy",
"path": "netropy/beacon.py",
"copies": "1",
"size": "2405",
"license": "mit",
"hash": 990609983646429000,
"line_mean": 26.6436781609,
"line_max": 76,
"alpha_frac": 0.6869022869,
"autogenerated": false,
"ratio": 3.500727802037846,
"config_test": false,
"has... |
"""BeagleBone Black specific PWM driver sysfs interface"""
import sys
import os
import glob
sys.path.append(os.path.abspath(".."))
import pwmpy.pwm as linux_pwm
# import pwmpy from https://github.com/scottellis/pwmpy
# override __init__ to find_pwm devices on beaglebone black instead of rpi
__author__ = 'Coburn Wig... | {
"repo_name": "coburnw/bbb-pwm",
"path": "bbb_pwm.py",
"copies": "1",
"size": "6046",
"license": "mit",
"hash": -8829086615908924000,
"line_mean": 34.3567251462,
"line_max": 126,
"alpha_frac": 0.5605358915,
"autogenerated": false,
"ratio": 3.5212580081537563,
"config_test": false,
"has_no_key... |
"""Beaker utilities"""
from ._compat import PY2, string_type, unicode_text, NoneType, dictkeyslist, im_class, im_func
try:
import threading as _threading
except ImportError:
import dummy_threading as _threading
from datetime import datetime, timedelta
import os
import re
import string
import types
import weak... | {
"repo_name": "jvanasco/beaker",
"path": "beaker/util.py",
"copies": "3",
"size": "15373",
"license": "bsd-3-clause",
"hash": -5931180874862488000,
"line_mean": 32.8612334802,
"line_max": 97,
"alpha_frac": 0.5802380798,
"autogenerated": false,
"ratio": 4.060486001056524,
"config_test": true,
... |
"""Beaker utilities"""
from ._compat import PY2, string_type, unicode_text, NoneType, dictkeyslist, im_class, im_func, pickle, func_signature, \
default_im_func
try:
import threading as _threading
except ImportError:
import dummy_threading as _threading
from datetime import datetime, timedelta
import os
i... | {
"repo_name": "stefanv/aandete",
"path": "app/lib/beaker/util.py",
"copies": "2",
"size": "16487",
"license": "bsd-3-clause",
"hash": 4828358153595487000,
"line_mean": 33.3479166667,
"line_max": 121,
"alpha_frac": 0.5941650998,
"autogenerated": false,
"ratio": 4.0688548864758145,
"config_test":... |
"""Beaker utilities"""
try:
import thread as _thread
import threading as _threading
except ImportError:
import dummy_thread as _thread
import dummy_threading as _threading
from datetime import datetime, timedelta
import os
import re
import string
import types
import weakref
import warnings
import sys
... | {
"repo_name": "anedos/beaker",
"path": "beaker/util.py",
"copies": "1",
"size": "12369",
"license": "bsd-3-clause",
"hash": 7529617728857624000,
"line_mean": 31.1272727273,
"line_max": 87,
"alpha_frac": 0.5778963538,
"autogenerated": false,
"ratio": 4.107937562271671,
"config_test": true,
"ha... |
"""Beam center finding algorithms"""
from typing import Tuple, Dict
import numpy as np
import scipy.optimize
from . import integrate2
class Centering:
"""Find the beam center on a scattering pattern using various algorithms
Beam center coordinates are (row, column), starting from 0.
mask: True if pixe... | {
"repo_name": "awacha/sastool",
"path": "sastool/utils2d/centering2.py",
"copies": "1",
"size": "9807",
"license": "bsd-3-clause",
"hash": 8361848156571785000,
"line_mean": 52.8076923077,
"line_max": 119,
"alpha_frac": 0.6040028592,
"autogenerated": false,
"ratio": 3.8194227769110762,
"config_t... |
"""Beam DoFns specific to `code_search.dataflow.transforms.function_embeddings`."""
import apache_beam as beam
from code_search.t2t.query import get_encoder, encode_query
class EncodeFunctionTokens(beam.DoFn):
"""Encode function tokens.
This DoFn prepares the function tokens for
inference by a SavedModel est... | {
"repo_name": "kubeflow/examples",
"path": "code_search/src/code_search/dataflow/do_fns/function_embeddings.py",
"copies": "1",
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"license": "apache-2.0",
"hash": 2458677965950059500,
"line_mean": 25.5939393939,
"line_max": 83,
"alpha_frac": 0.5720145852,
"autogenerated": false,
"ra... |
"""Beam DoFns specific to `code_search.dataflow.transforms.github_dataset`."""
import logging
import apache_beam as beam
from apache_beam import pvalue
import code_search.dataflow.utils as utils
class SplitRepoPath(beam.DoFn):
"""Update element keys to separate repo path and file path.
This DoFn's only purpose i... | {
"repo_name": "kubeflow/examples",
"path": "code_search/src/code_search/dataflow/do_fns/github_dataset.py",
"copies": "1",
"size": "3387",
"license": "apache-2.0",
"hash": 1222041487153300500,
"line_mean": 25.6692913386,
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"""Beamform visibilities to the location of known sources."""
import numpy as np
import scipy.interpolate
from skyfield.api import Star, Angle
from caput import config
from caput import time as ctime
from cora.util import units
from ..core import task, containers, io
from ..util._fast_tools import beamform
from ..u... | {
"repo_name": "radiocosmology/draco",
"path": "draco/analysis/beamform.py",
"copies": "1",
"size": "46320",
"license": "mit",
"hash": 6385820505524366000,
"line_mean": 36.4757281553,
"line_max": 91,
"alpha_frac": 0.5558721934,
"autogenerated": false,
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"config_test": ... |
# Beam In Vessel Test
import sys
sys.path.append('../lib/')
from BeamDynamicsTools import *
import pylab as pl
# Input Sigma Matrix
S1 = matrix(loadtxt('../data/SigmaInjection.dat'))
#S1 = matrix([
#[ 1.502802755999999818e+01,-1.284540872159999791e+00, 0.000000000000000000e+00, 0.000000000000000000e+00, 0.0000000000... | {
"repo_name": "hbar/python-BeamDynamicsTools",
"path": "test/Test_TrajectoriesAndDetection.py",
"copies": "1",
"size": "7006",
"license": "mit",
"hash": -1824403414029123800,
"line_mean": 30.2767857143,
"line_max": 225,
"alpha_frac": 0.6512988867,
"autogenerated": false,
"ratio": 2.18323465253973... |
# Beam In Vessel Test
import sys
sys.path.append('../lib/')
from BeamDynamicsTools import *
import pylab as pl
#------------------------------------------------------------------------------
# Input Sigma Matrix
S1 = matrix([
[ 1.502802755999999818e+01,-1.284540872159999791e+00, 0.000000000000000000e+00, 0.0000000000... | {
"repo_name": "hbar/python-BeamDynamicsTools",
"path": "test/Test_BeamInVessel.py",
"copies": "1",
"size": "4415",
"license": "mit",
"hash": 2180595728272910000,
"line_mean": 36.1008403361,
"line_max": 165,
"alpha_frac": 0.562400906,
"autogenerated": false,
"ratio": 2.819284802043423,
"config_t... |
"""Beam lifetime calculation."""
import os as _os
import importlib as _implib
from copy import deepcopy as _dcopy
import numpy as _np
from mathphys import constants as _cst, units as _u, \
beam_optics as _beam
from . import optics as _optics
if _implib.util.find_spec('scipy'):
import scipy.integrate as _int... | {
"repo_name": "lnls-fac/pyaccel",
"path": "pyaccel/lifetime.py",
"copies": "1",
"size": "21169",
"license": "mit",
"hash": 3322612445438544000,
"line_mean": 30.8195488722,
"line_max": 79,
"alpha_frac": 0.5572306238,
"autogenerated": false,
"ratio": 3.2745280099040546,
"config_test": false,
"h... |
"""Beam Optics functions."""
import math as _math
import numpy as _np
from mathphys import constants as _c
from mathphys import units as _u
# NOTE: This function is used in siriuspy!
def beam_rigidity(**kwargs):
"""Beam rigidity."""
# TODO: cleanup this function (and siriuspy Normalizer)
electron_rest_en... | {
"repo_name": "lnls-fac/mathphys",
"path": "mathphys/beam_optics.py",
"copies": "1",
"size": "2384",
"license": "mit",
"hash": -7282463313370352000,
"line_mean": 33.5507246377,
"line_max": 72,
"alpha_frac": 0.5927013423,
"autogenerated": false,
"ratio": 3.343618513323983,
"config_test": false,
... |
# Beam.py
from numpy import *
#import scipy as sp
import pylab as pl
from numpy.linalg import inv,norm
from Trajectory import *
from Target import *
from Ellipse import *
class Beam(Trajectory):
# inputs:
# sigma = 6x6 sigma matrix
# s0 = 3x3 matrix for local beam coordinate system
def __init__(self,trajectory,si... | {
"repo_name": "hbar/python-BeamDynamicsTools",
"path": "lib/BeamDynamicsTools/Beam.py",
"copies": "1",
"size": "13482",
"license": "mit",
"hash": 7512085720315209000,
"line_mean": 30.3534883721,
"line_max": 163,
"alpha_frac": 0.4296840231,
"autogenerated": false,
"ratio": 2.4274396831112712,
"c... |
"""Beam search decoder.
This module implements the beam search algorithm for autoregressive decoders.
As any autoregressive decoder, this decoder works dynamically, which means
it uses the ``tf.while_loop`` function conditioned on both maximum output
length and list of finished hypotheses.
The beam search decoder us... | {
"repo_name": "ufal/neuralmonkey",
"path": "neuralmonkey/decoders/beam_search_decoder.py",
"copies": "1",
"size": "24043",
"license": "bsd-3-clause",
"hash": 2149791837008164600,
"line_mean": 39.3406040268,
"line_max": 79,
"alpha_frac": 0.6173522439,
"autogenerated": false,
"ratio": 4.28497594011... |
"""Beam search decoder.
This module implements the beam search algorithm for the recurrent decoder.
As well as the recurrent decoder, this decoder works dynamically, which means
it uses the ``tf.while_loop`` function conditioned on both maximum output
length and list of finished hypotheses.
The beam search decoder w... | {
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"path": "neuralmonkey/decoders/beam_search_decoder.py",
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# beam search implementation in PyTorch."""
#
#
# hyp1#-hyp1---hyp1 -hyp1
# \ /
# hyp2 \-hyp2 /-hyp2#hyp2
# / \
# hyp3#-hyp3---hyp3 -hyp3
# ========================
#
# Takes care of beams, back pointers, and scores.
# Code ... | {
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"path": "beam_search.py",
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"config_... |
"""Beam search implementation in PyTorch."""
#
#
# hyp1#-hyp1---hyp1 -hyp1
# \ /
# hyp2 \-hyp2 /-hyp2#hyp2
# / \
# hyp3#-hyp3---hyp3 -hyp3
# ========================
#
# Takes care of beams, back pointers, and scores.
# Code... | {
"repo_name": "yotamfr/prot2vec",
"path": "src/python/beam_search.py",
"copies": "1",
"size": "3546",
"license": "mit",
"hash": -515618012324584800,
"line_mean": 28.7983193277,
"line_max": 78,
"alpha_frac": 0.5578116187,
"autogenerated": false,
"ratio": 3.4527750730282376,
"config_test": false,... |
"""Beam search parameters tuning for DeepSpeech2 model."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import os
import numpy as np
import argparse
import functools
import gzip
import logging
import paddle.v2 as paddle
import _init_paths
from ... | {
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"path": "deep_speech_2/tools/tune.py",
"copies": "1",
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"config_tes... |
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