repo_name stringlengths 6 112 | path stringlengths 4 204 | copies stringlengths 1 3 | size stringlengths 4 7 | content stringlengths 711 1.04M | license stringclasses 15
values | hash int64 -9,223,328,406,218,787,000 9,223,331,109B | line_mean float64 5.74 99.7 | line_max int64 17 1k | alpha_frac float64 0.25 0.96 | autogenerated bool 1
class |
|---|---|---|---|---|---|---|---|---|---|---|
OMS-NetZero/FAIR | fair/gas_cycle/gir.py | 1 | 2430 | from __future__ import division
import numpy as np
from ..constants.general import ppm_gtc
"""Gas cycle functions from Generalised Impulse Response Model v1.0.0.
Much of this has been adapted from:
Leach et al., 2020, Geoscientific Model Development
https://www.geosci-model-dev-discuss.net/gmd-2019-379/
"""
def c... | apache-2.0 | -8,292,986,400,798,594,000 | 37.571429 | 104 | 0.680247 | false |
mathkann/hyperopt | hyperopt/tests/test_criteria.py | 7 | 1917 | import numpy as np
import hyperopt.criteria as crit
def test_ei():
rng = np.random.RandomState(123)
for mean, var in [(0, 1), (-4, 9)]:
thresholds = np.arange(-5, 5, .25) * np.sqrt(var) + mean
v_n = [crit.EI_gaussian_empirical(mean, var, thresh, rng, 10000)
for thresh in thresh... | bsd-3-clause | -1,589,826,703,282,367,200 | 29.919355 | 73 | 0.542514 | false |
cython-testbed/pandas | pandas/tests/scalar/timestamp/test_timezones.py | 1 | 12514 | # -*- coding: utf-8 -*-
"""
Tests for Timestamp timezone-related methods
"""
from datetime import datetime, date, timedelta
from distutils.version import LooseVersion
import pytest
import pytz
from pytz.exceptions import AmbiguousTimeError, NonExistentTimeError
import dateutil
from dateutil.tz import gettz, tzoffset
... | bsd-3-clause | -6,155,344,485,097,374,000 | 39.498382 | 79 | 0.590698 | false |
zhuhuifeng/PyML | mla/neuralnet/layers/basic.py | 1 | 4512 | import autograd.numpy as np
from autograd import elementwise_grad
from mla.neuralnet.activations import get_activation
from mla.neuralnet.parameters import Parameters
np.random.seed(9999)
class Layer(object):
def setup(self, X_shape):
"""Allocates initial weights."""
pass
def forward_pass(s... | apache-2.0 | 4,052,290,290,537,210,400 | 23.791209 | 77 | 0.586436 | false |
rykov8/ssd_keras | ssd_layers.py | 3 | 6719 | """Some special pupropse layers for SSD."""
import keras.backend as K
from keras.engine.topology import InputSpec
from keras.engine.topology import Layer
import numpy as np
import tensorflow as tf
class Normalize(Layer):
"""Normalization layer as described in ParseNet paper.
# Arguments
scale: Defau... | mit | 9,192,958,743,215,568,000 | 36.121547 | 78 | 0.564072 | false |
OmnesRes/pan_cancer | paper/cox_regression/KIRC/patient_info.py | 1 | 6241 | ## 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... | mit | 3,009,862,005,212,880,400 | 28.300469 | 132 | 0.645089 | false |
l-althueser/NiMoNa_DCM16 | DCM/programs/RK4.py | 1 | 1088 | # -*- coding: utf-8 -*-
"""
@author: Tobias
Timo
Beschreibung:
Runge-Kutta-Verfahren vierter Ordnung zur Lösung von gewöhnlichen DGL 1. Ordnung.
Ausgabe der Zeitentwicklung in Matrixform.
Wichtig:
Die Dimension des Eingabeparameters x_0 muss mit dem verwendetem Modell überinstimmen.
Pythonversion:... | bsd-2-clause | -8,869,651,187,784,231,000 | 29.111111 | 105 | 0.553093 | false |
dingliu0305/Tree-Tensor-Networks-in-Machine-Learning | code/tsne_mnist.py | 1 | 3214 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# import matplotlib as mpl
# mpl.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import pickle
from matplotlib.backends.backend_pdf import PdfPages
from sklearn.manifold import TSNE
data_folder = "./data/mnist/"
n_epochs = 3
bond_data = 2
bond_inner = 3
bo... | mit | 9,021,563,037,263,550,000 | 22.289855 | 75 | 0.584941 | false |
ominux/scikit-learn | examples/manifold/plot_compare_methods.py | 4 | 2211 | """
=========================================
Comparison of Manifold Learning methods
=========================================
An illustration of dimensionality reduction on the S-curve dataset
with various manifold learning methods.
For a discussion and comparison of these algorithms, see the
:ref:`manifold module... | bsd-3-clause | -8,009,370,989,050,230,000 | 29.708333 | 71 | 0.620081 | false |
StongeEtienne/trimeshpy | trimeshpy/math/mesh_map.py | 1 | 6095 | # Etienne St-Onge
from __future__ import division
import numpy as np
from scipy.sparse import csc_matrix
from trimeshpy.math.util import square_length
from trimeshpy.math.mesh_global import G_DTYPE
# Mesh structure functions
# Map ( Adjacency / Connectivity ) Functions
#
# number of vertices = n
# number of ... | mit | -4,785,637,220,778,597,000 | 34.028736 | 78 | 0.474815 | false |
hosseinsadeghi/ultracold-ions | test/test_CoulombAcc.py | 2 | 4459 | import uci.CoulombAcc as uci
import numpy as np
import pyopencl as cl
import pyopencl.array as cl_array
testCtx = cl.create_some_context(interactive = True)
testQueue = cl.CommandQueue(testCtx)
def test_Constructor():
coulomb_acc = uci.CoulombAcc()
def test_ForceOnSingleParticleIsZero():
coulomb_acc = uci.Co... | mit | -2,679,120,046,525,874,700 | 30.401408 | 73 | 0.578381 | false |
hughperkins/gpu-experiments | gpuexperiments/occupancy_dyn_graphs.py | 1 | 2094 | """
Try using dynamic shared memory, see if gets optimized away, or affects occupancy
"""
from __future__ import print_function, division
import argparse
import string
import numpy as np
import os
import matplotlib.pyplot as plt
plt.rcdefaults()
import matplotlib.pyplot as plt
from os.path import join
parser = argpar... | bsd-2-clause | -6,801,072,646,690,389,000 | 26.552632 | 102 | 0.660936 | false |
ljschumacher/tierpsy-tracker | tierpsy/analysis/stage_aligment/findStageMovement.py | 2 | 58507 | import numpy as np
import warnings
import tables
from tierpsy.helper.misc import TimeCounter, print_flush, get_base_name
from tierpsy.helper.params import read_fps
from tierpsy.analysis.stage_aligment.get_mask_diff_var import get_mask_diff_var
def _matlab_std(x):
if x.size <= 1:
#in array of size 1 MAT... | mit | 6,729,585,383,931,663,000 | 43.222222 | 116 | 0.551167 | false |
fsxfreak/esys-pbi | src/pupil/pupil_src/shared_modules/frame_publisher.py | 2 | 2998 | '''
(*)~---------------------------------------------------------------------------
Pupil - eye tracking platform
Copyright (C) 2012-2017 Pupil Labs
Distributed under the terms of the GNU
Lesser General Public License (LGPL v3.0).
See COPYING and COPYING.LESSER for license details.
-----------------------------------... | mit | 2,254,809,564,954,330,000 | 33.079545 | 150 | 0.543362 | false |
dmitru/pines | pines/trees.py | 1 | 8172 | # coding=utf-8
import numpy as np
from copy import deepcopy
class BinaryDecisionTreeSplit(object):
def __init__(self, feature_id, value):
self.feature_id = feature_id
self.value = value
class BinaryDecisionTree(object):
"""
Implements a binary decision tree with array-based representation... | mit | 2,368,062,335,330,216,400 | 34.947137 | 103 | 0.55098 | false |
philouc/pyhrf | python/pyhrf/test/test_glm.py | 1 | 3214 | import unittest
import pyhrf
import os.path as op
import shutil
class NipyGLMTest(unittest.TestCase):
def setUp(self):
self.tmp_dir = pyhrf.get_tmp_path()
def tearDown(self):
shutil.rmtree(self.tmp_dir)
# def _simulate_bold(self):
# boldf, tr, paradigmf, maskf = simulate_bold(o... | gpl-3.0 | -4,689,871,972,983,716,000 | 27.192982 | 78 | 0.589919 | false |
florian-f/sklearn | examples/svm/plot_svm_margin.py | 4 | 2295 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
SVM Margins Example
=========================================================
The plots below illustrate the effect the parameter `C` has
on the seperation line. A large value of `C` basically tells
our model that w... | bsd-3-clause | -3,608,698,199,744,564,700 | 25.37931 | 76 | 0.582571 | false |
Marcello-Sega/pytim | setup.py | 1 | 5678 | # -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding: utf-8 -*-
# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
"""A python based tool for interfacial molecules analysis
"""
# To use a consistent encoding
import codecs
import os
import sys
# Always prefer setuptools over distutils
try:
from setupt... | gpl-3.0 | 2,636,920,363,843,867,600 | 34.710692 | 94 | 0.661853 | false |
Sravan2j/DIGITS | tools/test_create_db.py | 1 | 4429 | # Copyright (c) 2014-2015, NVIDIA CORPORATION. All rights reserved.
import os.path
import tempfile
import shutil
from cStringIO import StringIO
from nose.tools import raises, assert_raises
import mock
import unittest
import PIL.Image
import numpy as np
from . import create_db as _
class TestInit():
@classmetho... | bsd-3-clause | 7,553,932,435,437,362,000 | 29.972028 | 120 | 0.582298 | false |
arizona-phonological-imaging-lab/Autotrace | under-development/a3/roi.py | 2 | 5643 | #!/usr/bin/env python3
from __future__ import division
import numpy as np
import json
class ROI(object):
""" Region of Interest for a set of images
Attributes:
shape (tuple of numeric): the height and width of the ROI
offset (tuple of numeric): the lower bounds of the ROI
extent ... | mit | 4,787,143,582,170,665,000 | 34.049689 | 72 | 0.550771 | false |
dirmeier/dataframe | tests/test_cases.py | 1 | 2832 | # dataframe: a data-frame implementation using method piping
#
# Copyright (C) 2016 Simon Dirmeier
#
# This file is part of dataframe.
#
# dataframe is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either versi... | gpl-3.0 | -3,136,135,424,214,697,500 | 24.754545 | 77 | 0.647952 | false |
DavideCanton/Python3 | pyIAprove/labyrinth.py | 1 | 12404 | from math import sqrt
import numpy as np
from collections import defaultdict, namedtuple
from PIL import Image
DIRS = U, L, D, R, UL, UR, DL, DR = [(0, -1), (-1, 0), (0, 1), (1, 0), (-1, -1),
(1, -1), (-1, 1), (1, 1)]
def dist_2(p1, p2):
dx = p1[0] - p2[0]
dy = p1[1] - p2... | gpl-3.0 | -3,098,687,144,941,617,000 | 31.814815 | 80 | 0.484844 | false |
J4sp3r/damrobot | Project/lib/util.py | 1 | 1474 | #!/usr/local/bin/python
import cv2,os
import numpy as np
import matplotlib.pyplot as plt
from lib import log
def imshow(img):
cv2.namedWindow("preview")
cv2.imshow("preview",img)
rval = True
while rval:
key = cv2.waitKey(27)
if key == 27: # exit on ESC
break
cv2.destroyWindow("preview")
def imshow2(img):
... | mit | -8,841,574,868,602,686,000 | 24 | 235 | 0.656716 | false |
bccp/abopt | abopt/legacy/vmad2.py | 1 | 32837 | from __future__ import print_function
import warnings
import functools
import logging
logger = logging.getLogger("VMAD")
_logging_handler = logging.StreamHandler()
logger.addHandler(_logging_handler)
# TODO:
# Add visualization
def ZeroType():
""" creates a special type of ZeroType; """
def self(self, *args)... | gpl-3.0 | -5,166,341,015,161,290,000 | 33.063278 | 107 | 0.548588 | false |
rinatzakirov/vhdl | drivers/ddr_analyze.py | 1 | 1995 | import pyqtgraph as pg
import numpy as np
def drawFft(filename, side):
data = np.fromfile("dump.dat", dtype="uint16").astype(float)
data = data[side::2]
#data = data[:-1]
#data = data[:8192]
#pg.plot(data)
#return
print "raw"
print np.min(data)
print np.max(data)
data -= np.average(data)
data = d... | lgpl-2.1 | -8,487,399,865,354,513,000 | 28.352941 | 164 | 0.578947 | false |
petebachant/scipy | scipy/linalg/_interpolative_backend.py | 143 | 44935 | #******************************************************************************
# Copyright (C) 2013 Kenneth L. Ho
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# Redistributions of source code must retain t... | bsd-3-clause | 3,825,534,668,686,145,000 | 25.923307 | 79 | 0.532035 | false |
miso-belica/sumy | sumy/summarizers/text_rank.py | 1 | 4579 | # -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals
import math
try:
import numpy
except ImportError:
numpy = None
from ._summarizer import AbstractSummarizer
class TextRankSummarizer(AbstractSummarizer):
"""An implementation... | apache-2.0 | -5,269,407,314,558,454,000 | 38.817391 | 117 | 0.652544 | false |
timothydmorton/isochrones | isochrones/priors.py | 1 | 16204 | from __future__ import print_function, division
import numpy as np
import pandas as pd
import scipy.stats
from scipy.stats import uniform, lognorm
from scipy.integrate import quad
from scipy.stats._continuous_distns import _norm_pdf, _norm_cdf, _norm_logpdf
import matplotlib.pyplot as plt
import numba as nb
from math... | mit | -6,676,794,714,651,641,000 | 30.22158 | 130 | 0.522155 | false |
PaddlePaddle/Paddle | python/paddle/fluid/tests/unittests/dygraph_to_static/ifelse_simple_func.py | 2 | 10102 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | apache-2.0 | 5,161,546,916,633,578,000 | 28.538012 | 119 | 0.517323 | false |
zuphilip/ocropy | ocrolib/exceptions.py | 5 | 2139 | import inspect
import numpy
def summary(x):
"""Summarize a datatype as a string (for display and debugging)."""
if type(x)==numpy.ndarray:
return "<ndarray %s %s>"%(x.shape,x.dtype)
if type(x)==str and len(x)>10:
return '"%s..."'%x
if type(x)==list and len(x)>10:
return '%s...'%... | apache-2.0 | -5,357,816,646,254,686,000 | 28.30137 | 71 | 0.570827 | false |
Milias/ModellingSimulation | Week7/python/lattice.py | 1 | 3006 | # -*- coding: utf8 -*-
from numpy import *
import json
def RecursiveSC(level, N, count, points):
if level:
for i in range(N[level]):
RecursiveSC(level - 1, N, count, points)
count[level] += 1
count[level] = 0
else:
for i in range(N[0]):
points.append(count[:])
count[0] += 1
... | mit | 875,898,410,095,977,100 | 29.673469 | 133 | 0.617432 | false |
FedericoMuciaccia/SistemiComplessi | src/percolation.py | 1 | 5670 |
# coding: utf-8
# # Percolation
# In[2]:
import numpy, networkx, pandas
# import graph_tool
# from graph_tool.all import *
# from matplotlib import pyplot
# %matplotlib inline
# In[3]:
# simple parallelization
# import multiprocessing
# cpus = multiprocessing.cpu_count()
# pool = multiprocessing.Pool(proce... | mit | -4,597,681,802,934,022,000 | 32.526627 | 129 | 0.678433 | false |
pokornyv/SPEpy | parlib2.py | 1 | 13136 | ###########################################################
# SPEpy - simplified parquet equation solver for SIAM #
# Copyright (C) 2019 Vladislav Pokorny; pokornyv@fzu.cz #
# homepage: github.com/pokornyv/SPEpy #
# parlib2.py - library of functions #
####################... | gpl-3.0 | -2,502,053,832,222,385,000 | 39.294479 | 103 | 0.619062 | false |
uzgit/ardupilot | Tools/LogAnalyzer/tests/TestPitchRollCoupling.py | 3 | 6116 | from LogAnalyzer import Test,TestResult
import DataflashLog
from VehicleType import VehicleType
import collections
class TestPitchRollCoupling(Test):
'''test for divergence between input and output pitch/roll, i.e. mechanical failure or bad PID tuning'''
# TODO: currently we're only checking for roll/pitch o... | gpl-3.0 | -7,586,790,118,497,596,000 | 45.687023 | 157 | 0.567528 | false |
relh/keras | examples/lstm_benchmark.py | 9 | 3008 | '''Compare LSTM implementations on the IMDB sentiment classification task.
consume_less='cpu' preprocesses input to the LSTM which typically results in
faster computations at the expense of increased peak memory usage as the
preprocessed input must be kept in memory.
consume_less='mem' does away with the preprocessin... | mit | 3,519,658,746,247,531,500 | 35.240964 | 91 | 0.706782 | false |
cseed/hail | hail/python/test/hail/experimental/test_dnd_array.py | 1 | 11934 | import numpy as np
import hail as hl
from hail.utils import new_temp_file
from ..helpers import startTestHailContext, stopTestHailContext, fails_local_backend
setUpModule = startTestHailContext
tearDownModule = stopTestHailContext
def test_range_collect():
n_variants = 10
n_samples = 10
block_size = 3
... | mit | 8,407,039,667,649,245,000 | 31.606557 | 85 | 0.588906 | false |
bjornsturmberg/EMUstack | backend/materials.py | 2 | 16446 | """
materials.py is a subroutine of EMUstack that defines Material objects,
these represent dispersive lossy refractive indices and possess
methods to interpolate n from tabulated data.
Copyright (C) 2015 Bjorn Sturmberg, Kokou Dossou, Felix Lawrence
EMUstack is free software: you can redi... | gpl-3.0 | 5,210,394,253,854,883,000 | 48.140244 | 173 | 0.452937 | false |
habi/GlobalDiagnostiX | FocusPlotLine.py | 1 | 5139 | # -*- coding: utf-8 -*-
"""
Script to plot line on TIFF, useful for 'calculating' the best focus of
the EssentialMed Setup. Since the objective doesn't really have the focal
distance Edmund optics stated...
Reads TIFF-Stack with images from focus shifting on the LINOS-rail. Plots
a line (coordinates read from a txt-Fi... | unlicense | 8,246,217,816,463,031,000 | 40.780488 | 112 | 0.557696 | false |
dmytroKarataiev/MachineLearning | smartcab/smartcab/simulator.py | 1 | 9740 | import os
import time
import random
import importlib
import numpy as np
class Simulator(object):
"""Simulates agents in a dynamic smartcab environment.
Uses PyGame to display GUI, if available.
"""
colors = {
'black' : ( 0, 0, 0),
'white' : (255, 255, 255),
'red' ... | mit | 4,681,323,323,775,302,000 | 47.944724 | 220 | 0.54117 | false |
strets123/pyms | Gapfill/Function.py | 7 | 9648 | '''
@summary: # Functions to fill missing peak objects
@author: Jairus Bowne
@author: Sean O'Callaghan
'''
import csv
import string
import sys, os, errno, string, numpy
sys.path.append("/x/PyMS")
from pyms.GCMS.IO.ANDI.Function import ANDI_reader
from pyms.GCMS.IO.MZML.Function import mzML_reader
from pyms.... | gpl-2.0 | 8,064,595,078,807,377,000 | 28.686154 | 93 | 0.565713 | false |
stephanie-wang/ray | python/ray/tune/suggest/hyperopt.py | 1 | 9289 | import numpy as np
import copy
import logging
from functools import partial
import pickle
try:
hyperopt_logger = logging.getLogger("hyperopt")
hyperopt_logger.setLevel(logging.WARNING)
import hyperopt as hpo
except ImportError:
hpo = None
from ray.tune.error import TuneError
from ray.tune.suggest.sugge... | apache-2.0 | 1,423,453,493,068,253,700 | 40.10177 | 79 | 0.590268 | false |
albertoferna/compmech | doc/source/conf_scipy.py | 3 | 6677 | # -*- coding: utf-8 -*-
import sys, os, re
# Check Sphinx version
import sphinx
if sphinx.__version__ < "1.1":
raise RuntimeError("Sphinx 1.1 or newer required")
needs_sphinx = '1.1'
# -----------------------------------------------------------------------------
# General configuration
# -----------------------... | bsd-3-clause | 5,327,442,863,046,868,000 | 30.347418 | 93 | 0.606859 | false |
radioxoma/immunopy | immunopy/stain/cdeconvcl.py | 1 | 6396 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
from __future__ import division
"""
Created on Wed Aug 06 19:37:30 2014
@author: radioxoma
"""
import os
import numpy as np
from skimage import color
import pyopencl as cl
import pyopencl.array as cla
from scipy import misc
import matplotlib.pyplot as plt
VERBOSE = Fal... | mit | 6,577,647,387,119,431,000 | 42.510204 | 149 | 0.61601 | false |
shunsukeaihara/pysas | pysas/pyexcite.py | 1 | 1172 | # -*- coding: utf-8 -*-
import numpy as np
try:
from numba import jit
except ImportError:
from pysas.decorators import do_nothing as jit
@jit
def gen_frame(cur_f0, prev_f0, frame, samplingrate, gen_samples, gauss):
if cur_f0 == 0.0 or prev_f0 == 0.0:
if gauss:
return np.random.normal(0... | mit | 3,515,681,140,772,425,000 | 27.585366 | 97 | 0.585324 | false |
QISKit/qiskit-sdk-py | qiskit/visualization/pulse/matplotlib.py | 1 | 22579 | # -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modif... | apache-2.0 | 9,021,072,622,400,497,000 | 36.197694 | 96 | 0.529829 | false |
jungla/ICOM-fluidity-toolbox | 2D/U/plot_W_t.py | 1 | 3442 | import os, sys
import vtktools
import fluidity_tools
import numpy as np
import matplotlib as mpl
mpl.use('ps')
import matplotlib.pyplot as plt
#label = sys.argv[1]
#basename = sys.argv[2]
path0 = path1 = path2 = '../RST/stat_files/'
path2b = '/scratch/jmensa/m_10_1/'
#
file0 = 'm_50_6f.stat'
filepath0 = path0+file... | gpl-2.0 | 3,574,806,178,951,072,000 | 30.009009 | 96 | 0.665892 | false |
m4rx9/rna-pdb-tools | rna_tools/tools/rna_filter/rna_filter.py | 2 | 11906 | #!/usr/bin/env python
"""rna_filter.py - calculate distances based on given restrants on PDB files or SimRNA trajectories.
Changes: weight is always 1 (at least for now). ,>,=,>=,<= .
[PREVIOUS DOCUMENTATION - TO BE REMOVED]
rna_filter.py -s 4gxy_rpr.pdb -r rp06_MohPairs.rfrestrs
d:A5-A42 100.0 measured: 26... | mit | 4,392,061,652,920,878,600 | 37.160256 | 446 | 0.529733 | false |
stefanseefeld/numba | numba/tests/test_array_iterators.py | 1 | 14037 | from __future__ import division
import itertools
import numpy as np
from numba import unittest_support as unittest
from numba import jit, typeof, types
from numba.compiler import compile_isolated
from .support import TestCase, CompilationCache, MemoryLeakMixin, tag
def array_iter(arr):
total = 0
for i, v i... | bsd-2-clause | -1,506,032,949,859,428,900 | 30.402685 | 79 | 0.568355 | false |
karllessard/tensorflow | tensorflow/python/autograph/impl/api_test.py | 4 | 35611 | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 | -160,551,979,138,421,540 | 27.128752 | 86 | 0.642526 | false |
djhshih/genomic | utils/genompy/genompy/plot/cn.py | 1 | 6009 | #!/usr/bin/env python3
import numpy as np
import matplotlib
import matplotlib.lines as lines
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib.ticker as ticker
from .. import cn
def plot_sample_profile(x, y, seg_x=None, seg_y=None, subplot_spec=None, ax=None, hide_xaxis=False,... | gpl-3.0 | 1,947,092,367,173,622,500 | 24.0375 | 122 | 0.668497 | false |
nan86150/ImageFusion | lib/python2.7/site-packages/scipy/_lib/_version.py | 65 | 4792 | """Utility to compare (Numpy) version strings.
The NumpyVersion class allows properly comparing numpy version strings.
The LooseVersion and StrictVersion classes that distutils provides don't
work; they don't recognize anything like alpha/beta/rc/dev versions.
"""
import re
from scipy._lib.six import string_types
... | mit | 985,191,422,128,744,100 | 29.916129 | 79 | 0.536728 | false |
rtrwalker/geotecha | geotecha/speccon/test/test_speccon1d_vrw.py | 1 | 176841 | # geotecha - A software suite for geotechncial engineering
# Copyright (C) 2018 Rohan T. Walker (rtrwalker@gmail.com)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the L... | gpl-3.0 | 7,107,741,138,485,871,000 | 36.641975 | 162 | 0.514174 | false |
thekingofkings/embedding | python/crawl_zillow.py | 1 | 6999 | # -*- coding: utf-8 -*-
"""
Created on Sun Aug 28 15:18:12 2016
@author: gjz5038
"""
import requests
import numpy as np
import time
session = requests.Session()
session.headers.update({'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36',
... | mit | 1,120,078,061,290,505,300 | 31.253456 | 175 | 0.519074 | false |
tosanai/wbai_hackathon_2017 | agent/cognitive/module.py | 1 | 5528 | # coding: utf-8
import copy
import os
import brica1.gym
import numpy as np
import _pickle as pickle
from ml.cnn_feature_extractor import CnnFeatureExtractor
from ml.q_net import QNet
from ml.experience import Experience
from config.model import CNN_FEATURE_EXTRACTOR, CAFFE_MODEL, MODEL_TYPE
from config.log import ... | apache-2.0 | -2,209,802,420,271,121,200 | 37.657343 | 118 | 0.625181 | false |
MioGit/RobotSimFramework | robots.py | 1 | 7491 | # -*- coding: utf-8 -*-
# Python 2.7.8
"""
Author:
Isaac Sanchez Ruiz
appllgc@gmail.com
Copyright (C) 2014 Isaac Sanchez Ruiz
This file is part of RobotSimFramework.
RobotSimFramework is free software: you can redistribute it and/or modify
it under the terms of the Lesser GNU General Public License as ... | gpl-3.0 | -5,374,866,057,185,673,000 | 52.12766 | 229 | 0.690696 | false |
Eric89GXL/vispy | vispy/glsl/build-spatial-filters.py | 1 | 20537 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# glumpy is an OpenGL framework for the fast visualization of numpy arrays.
# Copyright (C) 2009-2011 Nicolas P. Rougier. All rights reserved.
#
# Redistribution and use in source and binary fo... | bsd-3-clause | 5,926,030,809,813,368,000 | 27.564067 | 125 | 0.511044 | false |
michaelaye/spexpy | guide_movie.py | 1 | 1229 | import numpy as np
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import matplotlib.animation as manimation
import pyfits
import glob
import os
from scipy.ndimage import median_filter
os.chdir('/raid1/maye/irtf/140918/guidedog/scan1')
def read_scan1(fname):
data = pyfits.getdata(fname, 0)... | bsd-3-clause | -6,363,818,092,243,812,000 | 26.311111 | 62 | 0.676973 | false |
plotly/octogrid | setup.py | 1 | 1811 | from os.path import dirname, join
from octogrid import __version__
from setuptools import setup
def read(filename):
"""
Read content from utility files
"""
return open(join(dirname(__file__), filename)).read()
setup(
name='octogrid',
version=__version__,
author='Pravendra Singh',
au... | mit | -7,434,494,033,731,529,000 | 29.694915 | 162 | 0.575373 | false |
valiantljk/graph-partition | drawing/nx_pylab.py | 1 | 29867 | """
**********
Matplotlib
**********
Draw networks with matplotlib.
See Also
--------
matplotlib: http://matplotlib.org/
pygraphviz: http://pygraphviz.github.io/
"""
# Copyright (C) 2004-2012 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>... | gpl-2.0 | 8,915,198,073,067,984,000 | 29.199191 | 124 | 0.572639 | false |
AlchemicalChest/Gaussian-Process-with-Stochastic-Variational-Inference | GPSVI/test/test20newsgroups.py | 1 | 1417 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 30 11:24:55 2015
@author: Ziang
"""
import time
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn import datasets
from sklearn.cross_validation import train_test_split
from sklearn.decomposition impor... | mit | -1,960,622,932,607,665,700 | 25.259259 | 77 | 0.690191 | false |
xray/xray | xarray/plot/plot.py | 1 | 33300 | """
Use this module directly:
import xarray.plot as xplt
Or use the methods on a DataArray or Dataset:
DataArray.plot._____
Dataset.plot._____
"""
import functools
import numpy as np
import pandas as pd
from .facetgrid import _easy_facetgrid
from .utils import (
_add_colorbar,
_assert_valid_xy,
... | apache-2.0 | 1,388,698,512,246,744,800 | 33.08393 | 106 | 0.593393 | false |
ECP-CANDLE/Benchmarks | Pilot3/P3B4/p3b4_baseline_keras2.py | 1 | 4652 | from __future__ import print_function
import numpy as np
import os, sys, gzip
import time
import keras
from tf_mthcan import hcan
import argparse
import p3b4 as bmk
import candle
def initialize_parameters(default_model = 'p3b4_default_model.txt' ):
# Build benchmark object
p3b3Bmk = bmk.BenchmarkP3B3(bmk.... | mit | -1,971,844,952,446,747,100 | 26.204678 | 143 | 0.567068 | false |
karla3jo/menpo-old | menpo/io/mesh/base.py | 1 | 13479 | import abc
from collections import namedtuple
import commands
import os.path as path
import tempfile
from menpo.io.base import Importer, find_alternative_files, \
map_filepath_to_importer
from menpo.io.mesh.assimp import AIImporter
from menpo.io.exceptions import MeshImportError
from menpo.shape import TexturedTriM... | bsd-3-clause | -1,672,173,169,141,588,000 | 35.928767 | 117 | 0.602196 | false |
phockett/ePSproc | epsproc/efield/efields.py | 1 | 41523 | """
ePSproc Efield class
"""
import numpy as np
from scipy import constants as scipy_constants
import pprint
import xarray as xr
# Additional imports for plotting
import matplotlib.pyplot as plt
import holoviews as hv
from holoviews import opts
# Use dictionary to create field defns intially? Gets confusing ot... | gpl-3.0 | 7,585,800,800,355,117,000 | 43.552575 | 219 | 0.525155 | false |
kamcpp/tensorflow | tensorflow/contrib/distributions/python/kernel_tests/operator_pd_diag_test.py | 19 | 3260 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 | 6,146,617,093,454,137,000 | 30.650485 | 80 | 0.708589 | false |
hmenke/espresso | src/python/object_in_fluid/oif_classes.py | 1 | 67795 | # Copyright (C) 2010-2018 The ESPResSo project
#
# This file is part of ESPResSo.
#
# ESPResSo is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later v... | gpl-3.0 | -7,041,708,817,716,287,000 | 46.409091 | 200 | 0.496069 | false |
bcongdon/Data-Science-Projects | election_tweets/tweet_tokenizer.py | 1 | 1301 | import re,json
import numpy as np
import scipy.stats as sp
emoticons_str = r"""
(?:
[:=;] # Eyes
[oO\-]? # Nose (optional)
[D\)\]\(\]/\\OpP] # Mouth
)"""
regex_str = [
emoticons_str,
r'<[^>]+>', # HTML tags
r'(?:@[\w_]+)', # @-mentions
r"(?:\#+[\w_]+[\w\'_\-]*[\w_]+)",... | gpl-3.0 | -1,501,399,698,604,844,000 | 26.680851 | 92 | 0.500384 | false |
bikash/h2o-dev | py2/h2o_util.py | 1 | 29314 | import subprocess
import gzip, shutil, random, time, re, copy
import os, zipfile, json, csv
import sys, math
import errno
from h2o_test import verboseprint, dump_json
import h2o_print as h2p
#************************************************************************
# stuff from ray
# list or tuple is okay. so are dicts... | apache-2.0 | 7,380,870,850,780,625,000 | 38.613514 | 130 | 0.596268 | false |
JohnGriffiths/dipy | dipy/align/metrics.py | 4 | 46496 | """ Metrics for Symmetric Diffeomorphic Registration """
from __future__ import print_function
import abc
import numpy as np
import scipy as sp
from scipy import gradient, ndimage
from ..utils.six import with_metaclass
from . import vector_fields as vfu
from . import sumsqdiff as ssd
from . import crosscorr as cc
fro... | bsd-3-clause | -8,108,721,500,854,902,000 | 42.292365 | 81 | 0.584287 | false |
mmaelicke/scikit-gstat | skgstat/Kriging.py | 1 | 17552 | """
The kriging module offers only an Ordinary Kriging routine (OK) that can be
used together with the skgstat.Variogram class. The usage of the class is
inspired by the scipy.interpolate classes.
"""
import time
import numpy as np
from scipy.spatial.distance import squareform
from scipy.linalg import solve as scipy_s... | mit | -6,802,020,258,376,292,000 | 31.868914 | 155 | 0.582384 | false |
ghislainv/deforestprob | forestatrisk/niceplot.py | 1 | 3199 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# ==============================================================================
# author :Ghislain Vieilledent
# email :ghislain.vieilledent@cirad.fr, ghislainv@gmail.com
# web :https://ecology.ghislainv.fr
# python_version :>=2.7
# license... | gpl-3.0 | 5,391,069,074,789,299,000 | 33.031915 | 80 | 0.563926 | false |
astrobayes/BMAD | chapter_5/code_5.28.py | 1 | 1554 | # From: Bayesian Models for Astrophysical Data, Cambridge Univ. Press
# (c) 2017, Joseph M. Hilbe, Rafael S. de Souza and Emille E. O. Ishida
#
# you are kindly asked to include the complete citation if you used this
# material in a publication
# Code 5.28 - Binomial model in Python using Stan
# 1 response (y) and... | gpl-3.0 | -7,941,266,955,851,620,000 | 20.887324 | 73 | 0.618404 | false |
nortikin/sverchok | nodes/analyzer/path_length_2.py | 2 | 6715 | # ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distrib... | gpl-3.0 | -5,332,234,326,293,690,000 | 35.693989 | 109 | 0.618317 | false |
seung-lab/neuroglancer | python/examples/flood_filling_simulation.py | 1 | 7883 | #!/usr/bin/env python
"""Example of display interactive flood-filling "inference" results.
shift+mousedown0 triggers the simulated flood filling to start with an initial
seed at the mouse position. The computed mask values are displayed as an image,
while the seed points chosen are displayed as point annotations.
k... | apache-2.0 | -612,087,195,509,239,300 | 35.665116 | 96 | 0.554231 | false |
xfxf/veyepar | tests/upload_log_analyser.py | 4 | 2988 | #!/usr/bin/python
import datetime
import csv
import StringIO
import pprint
# seconds from midnight, timestamp, bytes sent
log="""56521.93324, 2011-06-24 15:42:01.933240, 0
56521.933569, 2011-06-24 15:42:01.933569, 1292
56521.933722, 2011-06-24 15:42:01.933722, 1488
56522.022575, 2011-06-24 15:42:02.022575, 16488
565... | mit | -1,260,176,071,623,473,000 | 31.129032 | 78 | 0.676372 | false |
WillArmentrout/galSims | plotting/ClusterAngular.py | 1 | 8649 | import matplotlib.pyplot as plt
import math
import csv
import argparse
'''parser = argparse.ArgumentParser()
parser.add_argument("iterTotal", type=int,
help="Number of Clustering Iterations")
args = parser.parse_args()
iterTot = args.iterTotal''' # Prompt User for number of iterations of clustering... | gpl-2.0 | 4,347,766,149,789,477,400 | 47.864407 | 152 | 0.530582 | false |
vascotenner/holoviews | holoviews/element/comparison.py | 1 | 24350 | """
Helper classes for comparing the equality of two HoloViews objects.
These classes are designed to integrate with unittest.TestCase (see
the tests directory) while making equality testing easily accessible
to the user.
For instance, to test if two Matrix objects are equal you can use:
Comparison.assertEqual(matri... | bsd-3-clause | 8,527,686,448,773,649,000 | 35.074074 | 98 | 0.604928 | false |
jostep/tensorflow | tensorflow/python/debug/cli/analyzer_cli.py | 3 | 55928 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 | -3,123,995,718,131,566,000 | 34.285804 | 80 | 0.610338 | false |
joshmoore/openmicroscopy | components/tools/OmeroWeb/omeroweb/webclient/controller/container.py | 1 | 57620 | #!/usr/bin/env python
#
#
#
# Copyright (c) 2008-2011 University of Dundee.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) an... | gpl-2.0 | 360,977,168,249,794,500 | 46.191646 | 232 | 0.564596 | false |
Fougere87/unsec | hugo_test.py | 1 | 7674 | #!/usr/bin/python3
import os
import logging
import unsec
from sklearn import cluster
import matplotlib.pyplot as plt
import matplotlib as mpl
from sklearn import metrics
from mpl_toolkits.mplot3d import Axes3D
from sklearn import decomposition
from sklearn.metrics import pairwise
from sklearn import mixture
import mat... | unlicense | -4,882,499,110,803,133,000 | 34.041096 | 144 | 0.6595 | false |
ishalyminov/memn2n | single.py | 1 | 4686 | """Example running MemN2N on a single bAbI task.
Download tasks from facebook.ai/babi """
from __future__ import absolute_import
from __future__ import print_function
from data_utils import load_task, vectorize_data
from sklearn import cross_validation, metrics
from memn2n import MemN2N
from itertools import chain
fro... | mit | 3,172,476,606,770,828,000 | 40.105263 | 132 | 0.660478 | false |
JackKelly/neuralnilm_prototype | scripts/e487.py | 2 | 6833 | from __future__ import print_function, division
import matplotlib
import logging
from sys import stdout
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import (Net, RealApplianceSource,
BLSTMLayer, DimshuffleLayer,
Bidirectiona... | mit | 5,616,429,882,336,762,000 | 31.538095 | 133 | 0.590517 | false |
DavidAce/PT | Data_Analysis/dataanaylysis.py | 1 | 1536 | import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import os.path
import h5py
filename = '../output/data.h5'
if(not os.path.exists(filename)):
print("File does not exist.")
exit(1)
store = pd.HDFStore(filename,mode='r') #Use this to read hdf5 tables. Open in read mode.
h5f = h5py.Fi... | gpl-3.0 | 5,602,338,793,825,159,000 | 44.205882 | 142 | 0.667318 | false |
wallinm1/kaggle-facebook-bot | hyperopt_xgb.py | 1 | 2608 | import pandas as pd
from sklearn.cross_validation import cross_val_score, StratifiedKFold
from sklearn.feature_selection import SelectPercentile, chi2
from sklearn.externals import joblib
from sklearn.pipeline import Pipeline
import xgboost as xgb
from hyperopt import fmin, tpe, hp, STATUS_OK, Trials
import os
def sco... | mit | 2,690,637,892,772,345,000 | 41.080645 | 80 | 0.593942 | false |
freedomtan/tensorflow | tensorflow/python/keras/layers/preprocessing/benchmarks/hashing_benchmark.py | 4 | 3895 | # Copyright 2020 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 | 8,939,267,146,637,729,000 | 33.776786 | 80 | 0.661617 | false |
scivision/dmcutils | cam_intensity.py | 1 | 6411 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Assumes observing from 66.986330° N, 50.943941° W. I did not take into account slight ground distance between camera and radar.
E-region magnetic zenith at 79.7213° el, 150.11° az clockwise from geographic north.
But the beam was pointed at F-region magnetic zenith?
S... | gpl-3.0 | 8,059,602,880,121,933,000 | 33.446237 | 134 | 0.568129 | false |
andreabedini/numexpr | bench/vml_timing.py | 5 | 5869 | ###################################################################
# Numexpr - Fast numerical array expression evaluator for NumPy.
#
# License: MIT
# Author: See AUTHORS.txt
#
# See LICENSE.txt and LICENSES/*.txt for details about copyright and
# rights to use.
##########################################... | mit | 7,529,341,098,715,401,000 | 33.321637 | 81 | 0.613733 | false |
tuanvu216/udacity-course | intro_to_machine_learning/lesson/lesson_13_validation/KFold CV in sklearn.py | 1 | 1245 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 02 15:14:27 2015
@author: tvu
"""
from sklearn.cross_validation import KFold
t0 = time()
kf = KFold(len(authors), 2)
for train_indices, test_indices in kf:
#make training and testing datasets
features_train = [word_data[ii] for ii in train_indices]
features_... | mit | -1,931,519,531,409,667,300 | 35.647059 | 89 | 0.686747 | false |
0x7678/gr-gsm | docs/doxygen/doxyxml/generated/compoundsuper.py | 2 | 360038 | #!/usr/bin/env python3
#
# Generated Thu Jun 11 18:44:25 2009 by generateDS.py.
#
from __future__ import print_function
from __future__ import unicode_literals
import sys
from xml.dom import minidom
from xml.dom import Node
import six
#
# User methods
#
# Calls to the methods in these classes are generated by ge... | gpl-3.0 | 5,698,839,263,969,963,000 | 42.138989 | 641 | 0.59627 | false |
GUR9000/Deep_MRI_brain_extraction | NNet_Core/NN_Analyzer.py | 1 | 4154 | """
This software is an implementation of
Deep MRI brain extraction: A 3D convolutional neural network for skull stripping
You can download the paper at http://dx.doi.org/10.1016/j.neuroimage.2016.01.024
If you use this software for your projects please cite:
Kleesiek and Urban et al, Deep MRI brain extraction: A 3... | mit | 4,321,185,761,625,126,000 | 40.54 | 163 | 0.614107 | false |
mespe/SolRad | collection/compare_cimis_cfsr/compare_cimis_cfsr.py | 1 | 2737 | import pandas as pd
import matplotlib.pyplot as plt
from netCDF4 import Dataset
import netCDF4
def load_CFSR_data():
my_example_nc_file = 'RES.nc' # latitude, longitude = (39.5, -122)
fh = Dataset(my_example_nc_file, mode='r')
print(fh.variables.keys())
print(help(fh.variables['time'... | mit | -8,473,513,301,691,959,000 | 26.938776 | 186 | 0.523201 | false |
samzhang111/scikit-learn | sklearn/grid_search.py | 3 | 38126 | """
The :mod:`sklearn.grid_search` includes utilities to fine-tune the parameters
of an estimator.
"""
from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# ... | bsd-3-clause | -8,075,441,600,595,167,000 | 37.433468 | 87 | 0.608168 | false |
Monika319/EWEF-1 | Cw2Rezonans/Karolina/Oscyloskop/OscyloskopZ5W2.py | 1 | 1312 | # -*- coding: utf-8 -*-
"""
Plot oscilloscope files from MultiSim
"""
import numpy as np
import matplotlib.pyplot as plt
import sys
import os
from matplotlib import rc
rc('font',family="Consolas")
files=["real_zad5_05f_p2.txt"]
for NazwaPliku in files:
print NazwaPliku
Plik=open(NazwaPliku)
#print DeltaT
... | gpl-2.0 | -1,034,745,225,697,455,700 | 23.603774 | 72 | 0.578221 | false |
cBeaird/SemEval_Character-Identification-on-Multiparty-Dialogues | Classifiers/Random_Forest/Learning_Curve.py | 1 | 2718 | #!/usr/bin/env python
"""
File to plot the Learning Curve of a Random Forrest
"""
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
import matplotlib as mpl
from sklearn.model_selection import KFold
from sklearn.model_selection import learning_curve
mpl.use('TkAgg')
import matp... | mit | -2,796,158,065,937,514,500 | 34.298701 | 120 | 0.649007 | false |
ciyer/stockscape | src/python/Stockscape/stockscape/dsr.py | 1 | 6058 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
dsr.py
Utilities for the DeLong-Shiller Redux (dsr).
Created by Chandrasekhar Ramakrishnan on 2017-10-02.
Copyright (c) 2017 Chandrasekhar Ramakrishnan. All rights reserved.
"""
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import seabo... | bsd-3-clause | 6,513,744,225,531,852,000 | 35.715152 | 109 | 0.643447 | false |
ryfeus/lambda-packs | Skimage_numpy/source/scipy/optimize/minpack.py | 11 | 30534 | from __future__ import division, print_function, absolute_import
import warnings
from . import _minpack
import numpy as np
from numpy import (atleast_1d, dot, take, triu, shape, eye,
transpose, zeros, product, greater, array,
all, where, isscalar, asarray, inf, abs,
... | mit | -4,117,547,933,951,803,400 | 36.100851 | 87 | 0.588917 | false |
robwarm/gpaw-symm | gpaw/test/pw/lfc.py | 1 | 1771 | import numpy as np
from gpaw.test import equal
from gpaw.grid_descriptor import GridDescriptor
from gpaw.spline import Spline
import gpaw.mpi as mpi
from gpaw.lfc import LocalizedFunctionsCollection as LFC
from gpaw.wavefunctions.pw import PWDescriptor, PWLFC
from gpaw.kpt_descriptor import KPointDescriptor
x = 2.0
... | gpl-3.0 | 1,479,708,894,144,279,600 | 26.671875 | 82 | 0.568041 | false |
apatil/covariance-prior | cov_prior/givens_step.py | 1 | 1366 | # Author: Anand Patil
# Date: 2 June 2009
# License: Creative Commons BY-NC-SA
####################################
from fast_givens import fg
import pymc as pm
import numpy as np
from ortho_basis import OrthogonalBasis
__all__ = ['fast_givens', 'GivensStepper']
def fast_givens(o,i,j,t):
"Givens rotates the matr... | mit | 5,670,105,406,355,458,000 | 26.34 | 63 | 0.541728 | false |
ndingwall/scikit-learn | examples/linear_model/plot_poisson_regression_non_normal_loss.py | 10 | 22927 | """
======================================
Poisson regression and non-normal loss
======================================
This example illustrates the use of log-linear Poisson regression on the
`French Motor Third-Party Liability Claims dataset
<https://www.openml.org/d/41214>`_ from [1]_ and compares it with a linear... | bsd-3-clause | 8,887,515,850,015,059,000 | 39.012216 | 79 | 0.689973 | false |
ezekial4/atomic_neu | examples/profiles.py | 1 | 3306 | """
typical carbon content is n_c / n_e = 0.05
"""
import numpy as np
import matplotlib.pyplot as plt
import atomic
from ensemble_average import annotate_lines
def parabolic_profile(y0):
x = np.linspace(1., 0, 50)
y = 1 - x**2
y *= y0
return x, y
r, temperature = parabolic_profile(3e3)
r, density =... | mit | -6,893,652,996,516,458,000 | 22.784173 | 73 | 0.680278 | false |
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