repo_name stringlengths 6 112 | path stringlengths 4 204 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 714 810k | license stringclasses 15
values |
|---|---|---|---|---|---|
yaojenkuo/BuildingMachineLearningSystemsWithPython | ch03/rel_post_20news.py | 24 | 3903 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
import sklearn.datasets
import scipy as sp
new_post = \
"""Disk drive problems. Hi, I have a probl... | mit |
hitszxp/scikit-learn | sklearn/linear_model/tests/test_ransac.py | 40 | 12814 | import numpy as np
from numpy.testing import assert_equal, assert_raises
from numpy.testing import assert_array_almost_equal
from scipy import sparse
from sklearn.utils.testing import assert_less
from sklearn.linear_model import LinearRegression, RANSACRegressor
from sklearn.linear_model.ransac import _dynamic_max_tri... | bsd-3-clause |
ChanChiChoi/scikit-learn | sklearn/covariance/tests/test_covariance.py | 142 | 11068 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_alm... | bsd-3-clause |
rupak0577/ginga | ginga/web/pgw/Plot.py | 3 | 4306 | #
# Plot.py -- Plotting widget canvas wrapper.
#
# Copyright (c) Eric R. Jeschke. All rights reserved.
# This is open-source software licensed under a BSD license.
# Please see the file LICENSE.txt for details.
#
from io import BytesIO
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from ... | bsd-3-clause |
AlexanderFabisch/scikit-learn | doc/tutorial/text_analytics/solutions/exercise_02_sentiment.py | 46 | 2798 | """Build a sentiment analysis / polarity model
Sentiment analysis can be casted as a binary text classification problem,
that is fitting a linear classifier on features extracted from the text
of the user messages so as to guess wether the opinion of the author is
positive or negative.
In this examples we will use a ... | bsd-3-clause |
paladin74/neural-network-animation | matplotlib/tests/test_dviread.py | 15 | 1788 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from nose.tools import assert_equal
import matplotlib.dviread as dr
import os.path
original_find_tex_file = dr.find_tex_file
def setup():
dr.find_tex_file = lambda x: x
def teardown():
dr... | mit |
aabadie/scikit-learn | sklearn/utils/tests/test_testing.py | 24 | 7902 | import warnings
import unittest
import sys
from nose.tools import assert_raises
from sklearn.utils.testing import (
_assert_less,
_assert_greater,
assert_less_equal,
assert_greater_equal,
assert_warns,
assert_no_warnings,
assert_equal,
set_random_state,
assert_raise_message,
ig... | bsd-3-clause |
phobson/statsmodels | statsmodels/sandbox/tsa/movstat.py | 34 | 14871 | '''using scipy signal and numpy correlate to calculate some time series
statistics
original developer notes
see also scikits.timeseries (movstat is partially inspired by it)
added 2009-08-29
timeseries moving stats are in c, autocorrelation similar to here
I thought I saw moving stats somewhere in python, maybe not)... | bsd-3-clause |
intermezzo-fr/hillary-clinton-emails | scripts/outputCsvs.py | 5 | 3577 | import numpy as np
import pandas as pd
def normalize_address(raw_address):
for c in ["'", ",", "°", "•", "`", '"', "‘", "-"]:
raw_address = raw_address.replace(c, "")
raw_address = raw_address.lower()
if "<" in raw_address:
prefix = raw_address[:raw_address.index("<")].strip()
if ... | mit |
nan86150/ImageFusion | lib/python2.7/site-packages/matplotlib/tests/__init__.py | 17 | 2578 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import difflib
import os
from matplotlib import rcParams, rcdefaults, use
_multiprocess_can_split_ = True
# Check that the test directories exist
if not os.path.exists(os.path.join(
os.... | mit |
andreugrimalt/Theano-Tutorials | 5_convolutional_net.py | 1 | 3899 | import theano
from theano import tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
import numpy as np
from load import mnist
from theano.tensor.nnet.conv import conv2d
from theano.tensor.signal.downsample import max_pool_2d
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 imp... | mit |
leesavide/pythonista-docs | Documentation/matplotlib/mpl_examples/pylab_examples/contourf_log.py | 9 | 1350 | '''
Demonstrate use of a log color scale in contourf
'''
from matplotlib import pyplot as P
import numpy as np
from numpy import ma
from matplotlib import colors, ticker, cm
from matplotlib.mlab import bivariate_normal
N = 100
x = np.linspace(-3.0, 3.0, N)
y = np.linspace(-2.0, 2.0, N)
X, Y = np.meshgrid(x, y)
# A ... | apache-2.0 |
uglyboxer/linear_neuron | net-p3/lib/python3.5/site-packages/matplotlib/tests/test_patheffects.py | 10 | 5445 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from matplotlib.testing.decorators import image_comparison, cleanup
import matplotlib.pyplot as plt
import matplotlib.patheffects as path_effects
try:
# mock in python 3.3+
... | mit |
chaluemwut/fbserver | venv/lib/python2.7/site-packages/sklearn/feature_extraction/text.py | 1 | 49725 | # -*- coding: utf-8 -*-
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Robert Layton <robertlayton@gmail.com>
# Jochen Wersdörfer <jochen@wersdoerfer.de>
# Roman Sinayev <roman.sinayev@gma... | apache-2.0 |
raghavrv/scikit-learn | sklearn/neighbors/tests/test_approximate.py | 12 | 20126 | """
Testing for the approximate neighbor search using
Locality Sensitive Hashing Forest module
(sklearn.neighbors.LSHForest).
"""
# Author: Maheshakya Wijewardena, Joel Nothman
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
parrt/lolviz | prince_dtree.py | 1 | 12296 | import IPython, graphviz, re
from io import StringIO
from IPython.display import Image
import numpy as np
import pandas as pd
import math
from sklearn import tree
from sklearn.datasets import load_boston, load_iris
from collections import defaultdict
import string
import re
YELLOW = "#fefecd" # "#fbfbd0" # "#FBFEB0"
B... | bsd-3-clause |
priseborough/InertialNav | code/plot_states.py | 6 | 2287 | #!/bin/python
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
import numpy as np
import math
# State vector:
# 0-3: quaternions (q0, q1, q2, q3)
# 4-6: Velocity - m/sec (North, East, Down)
# 7-9: Position - m (North, East, Down)
# 10-12: Delta Angle bias - rad (X,Y,Z)
#... | bsd-3-clause |
ThomasMiconi/nupic.research | projects/l2_pooling/multi_column_convergence.py | 2 | 22360 | # Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you can redistribute it and/or modify
# it under the ... | agpl-3.0 |
airware/jsbsim | tests/TestScriptOutput.py | 2 | 3376 | # TestScriptInputOutput.py
#
# Check that <output> tags specified in a script are properly handled
#
# Copyright (c) 2015 Bertrand Coconnier
#
# 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; eit... | lgpl-2.1 |
cbertinato/pandas | pandas/tests/frame/test_combine_concat.py | 1 | 34741 | from datetime import datetime
import numpy as np
import pytest
import pandas as pd
from pandas import DataFrame, Index, Series, Timestamp, date_range
import pandas.util.testing as tm
from pandas.util.testing import assert_frame_equal, assert_series_equal
class TestDataFrameConcatCommon:
def test_concat_multipl... | bsd-3-clause |
jungla/ICOM-fluidity-toolbox | 2D/RST/plot_T_spec_res.py | 1 | 8498 | import os, sys
import myfun
import numpy as np
import matplotlib as mpl
mpl.use('ps')
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from scipy import interpolate
import lagrangian_stats
import scipy.fftpack
## READ archive (too many points... somehow)
# args: name, dayi, dayf, days
label = ... | gpl-2.0 |
trankmichael/scikit-learn | sklearn/neighbors/approximate.py | 128 | 22351 | """Approximate nearest neighbor search"""
# Author: Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>
# Joel Nothman <joel.nothman@gmail.com>
import numpy as np
import warnings
from scipy import sparse
from .base import KNeighborsMixin, RadiusNeighborsMixin
from ..base import BaseEstimator
from ..utils.va... | bsd-3-clause |
dankolbman/BCIM | src/post.py | 1 | 7125 | import glob
import os
import sys
import re
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import numpy as np
import python.DataIO as DataIO
import python.graphics as graphics
import python.clusters as clusters
import python.counts as counts
# Format settings
from matplotlib i... | mit |
sugartom/tensorflow-alien | tensorflow/examples/learn/text_classification.py | 39 | 5106 | # 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 appl... | apache-2.0 |
aflaxman/scikit-learn | sklearn/metrics/regression.py | 47 | 19967 | """Metrics to assess performance on regression task
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Ma... | bsd-3-clause |
capturePointer/vigra | vigranumpy/examples/grid_graph_shortestpath.py | 8 | 3978 | import vigra
import vigra.graphs as vigraph
import pylab
import numpy
np=numpy
import sys
import matplotlib
import pylab as plt
import math
from matplotlib.widgets import Slider, Button, RadioButtons
def makeWeights(gamma):
global hessian,gradmag,gridGraph
print "hessian",hessian.min(),hessian.max()
print ... | mit |
trungnt13/scikit-learn | examples/linear_model/plot_ols.py | 220 | 1940 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Linear Regression Example
=========================================================
This example uses the only the first feature of the `diabetes` dataset, in
order to illustrate a two-dimensional plot of this regre... | bsd-3-clause |
anirudhjayaraman/scikit-learn | sklearn/utils/tests/test_extmath.py | 70 | 16531 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis Engemann <d.engemann@fz-juelich.de>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from scipy import linalg
from scipy import stats
from sklearn.utils.testing import assert_eq... | bsd-3-clause |
SuperJohn/scikit-class | grid_search.py | 6 | 1243 | import pandas as pd
import numpy as np
df = pd.read_csv('tweets.csv')
target = df['is_there_an_emotion_directed_at_a_brand_or_product']
text = df['tweet_text']
fixed_text = text[pd.notnull(text)]
fixed_target = target[pd.notnull(text)]
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_b... | gpl-2.0 |
radiasoft/radtrack | experimental/hermite/testHermite02.py | 1 | 6919 | #
# Test executable #2 to exercise the Gauss-Hermite class
# Here, we fit a Gauss-Hermite expansion to an arbitrary profile.
# The SciPy least squares method is used.
#
# Copyright (c) 2013 RadiaBeam Technologies. All rights reserved
#
# python imports
import math
# SciPy imports
import numpy as np
import matplotlib.p... | apache-2.0 |
ritviksahajpal/Py6S | Py6S/SixSHelpers/all_angles.py | 1 | 13499 | # This file is part of Py6S.
#
# Copyright 2012 Robin Wilson and contributors listed in the CONTRIBUTORS file.
#
# Py6S is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, o... | lgpl-3.0 |
wogsland/QSTK | build/lib.linux-x86_64-2.7/QSTK/qstkfeat/classes.py | 8 | 1658 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on Nov 7, 2011
@author: John Cornwell
@contact: JohnWCornwellV@gmail.com
@summary: File containing various c... | bsd-3-clause |
meduz/scikit-learn | examples/linear_model/plot_ransac.py | 73 | 1859 | """
===========================================
Robust linear model estimation using RANSAC
===========================================
In this example we see how to robustly fit a linear model to faulty data using
the RANSAC algorithm.
"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import ... | bsd-3-clause |
nagyistoce/kaggle-galaxies | try_convnet_cc_multirotflip_3x69r45_maxout2048_extradense_pysexgen1_dup.py | 7 | 17744 | import numpy as np
# import pandas as pd
import theano
import theano.tensor as T
import layers
import cc_layers
import custom
import load_data
import realtime_augmentation as ra
import time
import csv
import os
import cPickle as pickle
from datetime import datetime, timedelta
# import matplotlib.pyplot as plt
# plt.i... | bsd-3-clause |
liyu1990/sklearn | examples/ensemble/plot_gradient_boosting_oob.py | 50 | 4764 | """
======================================
Gradient Boosting Out-of-Bag estimates
======================================
Out-of-bag (OOB) estimates can be a useful heuristic to estimate
the "optimal" number of boosting iterations.
OOB estimates are almost identical to cross-validation estimates but
they can be compute... | bsd-3-clause |
matbra/bokeh | examples/interactions/interactive_bubble/data.py | 49 | 1265 | import numpy as np
from bokeh.palettes import Spectral6
def process_data():
from bokeh.sampledata.gapminder import fertility, life_expectancy, population, regions
# Make the column names ints not strings for handling
columns = list(fertility.columns)
years = list(range(int(columns[0]), int(columns[-... | bsd-3-clause |
harterj/moose | modules/tensor_mechanics/test/tests/capped_mohr_coulomb/small_deform_hard_21.py | 12 | 1567 | #!/usr/bin/env python3
#* This file is part of the MOOSE framework
#* https://www.mooseframework.org
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moose/blob/master/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgp... | lgpl-2.1 |
wkfwkf/statsmodels | examples/run_all.py | 34 | 1740 | """run all examples to make sure we don't get an exception
Note:
If an example contaings plt.show(), then all plot windows have to be closed
manually, at least in my setup.
uncomment plt.show() to show all plot windows
"""
from __future__ import print_function
from statsmodels.compat import input
stop_on_error = Tru... | bsd-3-clause |
massmutual/scikit-learn | sklearn/utils/estimator_checks.py | 1 | 54609 | from __future__ import print_function
import types
import warnings
import sys
import traceback
import pickle
from copy import deepcopy
import numpy as np
from scipy import sparse
import struct
from sklearn.externals.six.moves import zip
from sklearn.externals.joblib import hash, Memory
from sklearn.utils.testing imp... | bsd-3-clause |
neuroidss/nupic.research | projects/sequence_classification/run_encoder_with_union.py | 9 | 8995 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
hrjn/scikit-learn | examples/cluster/plot_birch_vs_minibatchkmeans.py | 333 | 3694 | """
=================================
Compare BIRCH and MiniBatchKMeans
=================================
This example compares the timing of Birch (with and without the global
clustering step) and MiniBatchKMeans on a synthetic dataset having
100,000 samples and 2 features generated using make_blobs.
If ``n_clusters... | bsd-3-clause |
GuLinux/PySpectrum | import_image.py | 1 | 5892 | from pyui.import_image import Ui_ImportImage
from PyQt5.QtWidgets import QWidget, QToolBar, QDialog, QDialogButtonBox, QProgressDialog, QMessageBox
from PyQt5.QtGui import QIcon
from PyQt5.QtCore import Qt, QCoreApplication
from qmathplotwidget import QMathPlotWidget, QImPlotWidget
import matplotlib.pyplot as plt
from ... | gpl-3.0 |
INM-6/python-neo | neo/io/neuralynxio_v1.py | 2 | 105289 | """
Class for reading data from Neuralynx files.
This IO supports NCS, NEV and NSE file formats.
This module is an older implementation with old neo.io API.
A new class NeuralynxIO compunded by NeuralynxRawIO and BaseFromIO
superseed this one.
Depends on: numpy
Supported: Read
Author: Julia Sprenger, Carlos Canova... | bsd-3-clause |
rlouf/patterns-of-segregation | bin/plot_scaling_classes.py | 1 | 3443 | """plot_income_scaling.py
Plot the number of households from a given class as a function of the total
number of households per city
"""
import csv
import math
from matplotlib import pylab as plt
from scipy.stats import linregress
colours = {'Lower':'#4F8F6B',
'Higher':'#C1A62E',
'Middle':'#4B453C'}
... | bsd-3-clause |
liberatorqjw/scikit-learn | sklearn/tests/test_multiclass.py | 8 | 21910 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing ... | bsd-3-clause |
dshen1/trading-with-python | lib/functions.py | 76 | 11627 | # -*- coding: utf-8 -*-
"""
twp support functions
@author: Jev Kuznetsov
Licence: GPL v2
"""
from scipy import polyfit, polyval
import datetime as dt
#from datetime import datetime, date
from pandas import DataFrame, Index, Series
import csv
import matplotlib.pyplot as plt
import numpy as np
import p... | bsd-3-clause |
namccart/gnuradio | gr-digital/examples/example_costas.py | 49 | 5316 | #!/usr/bin/env python
#
# Copyright 2011-2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio 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, or (at your optio... | gpl-3.0 |
tbabej/astropy | astropy/visualization/wcsaxes/tests/test_frame.py | 2 | 5298 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
import matplotlib.pyplot as plt
from ....wcs import WCS
from ....tests.helper import pytest, remote_data
from .. import WCSAxes
from ..frame import BaseFrame
from ....tests.image_tests import IMAGE_REFERENCE_DIR
from .test_images imp... | bsd-3-clause |
blisseth/ThinkStats2 | code/regression.py | 62 | 9652 | """This file contains code used in "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2010 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function, division
import math
import pandas
import random
import numpy as np
import statsmode... | gpl-3.0 |
liyu1990/sklearn | examples/manifold/plot_swissroll.py | 330 | 1446 | """
===================================
Swiss Roll reduction with LLE
===================================
An illustration of Swiss Roll reduction
with locally linear embedding
"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# License: BSD 3 clause (C) INRIA 2011
print(__doc__)
import matplotlib.pyplot... | bsd-3-clause |
jarathomas/openVA-Pipeline | pipeline.py | 1 | 49777 | #-------------------------------------------------------------------------------------------------------------------------------------------#
# openVA Pipeline: pipeline.py -- Software for processing Verbal Autopsy data with automated cause of death assignment. #
# Copyright (C) 2018 Jason Thomas,... | gpl-3.0 |
gfyoung/pandas | pandas/tests/frame/indexing/test_getitem.py | 2 | 5364 | import numpy as np
import pytest
from pandas import (
Categorical,
CategoricalDtype,
CategoricalIndex,
DataFrame,
MultiIndex,
Series,
Timestamp,
get_dummies,
period_range,
)
import pandas._testing as tm
from pandas.core.arrays import SparseArray
class TestGetitem:
def test_get... | bsd-3-clause |
hmendozap/master-arbeit-projects | autosk_dev_test/component/LinReg.py | 1 | 8756 | import numpy as np
import scipy.sparse as sp
from HPOlibConfigSpace.configuration_space import ConfigurationSpace
from HPOlibConfigSpace.conditions import EqualsCondition, InCondition
from HPOlibConfigSpace.hyperparameters import UniformFloatHyperparameter, \
UniformIntegerHyperparameter, CategoricalHyperparameter... | mit |
PrashntS/scikit-learn | sklearn/linear_model/ridge.py | 60 | 44642 | """
Ridge regression
"""
# Author: Mathieu Blondel <mathieu@mblondel.org>
# Reuben Fletcher-Costin <reuben.fletchercostin@gmail.com>
# Fabian Pedregosa <fabian@fseoane.net>
# Michael Eickenberg <michael.eickenberg@nsup.org>
# License: BSD 3 clause
from abc import ABCMeta, abstractmethod
impor... | bsd-3-clause |
vipulroxx/sympy | sympy/physics/quantum/circuitplot.py | 58 | 12941 | """Matplotlib based plotting of quantum circuits.
Todo:
* Optimize printing of large circuits.
* Get this to work with single gates.
* Do a better job checking the form of circuits to make sure it is a Mul of
Gates.
* Get multi-target gates plotting.
* Get initial and final states to plot.
* Get measurements to plo... | bsd-3-clause |
dsquareindia/scikit-learn | sklearn/tests/test_cross_validation.py | 79 | 47914 | """Test the cross_validation module"""
from __future__ import division
import warnings
import numpy as np
from scipy.sparse import coo_matrix
from scipy.sparse import csr_matrix
from scipy import stats
from sklearn.exceptions import ConvergenceWarning
from sklearn.utils.testing import assert_true
from sklearn.utils.t... | bsd-3-clause |
srowen/spark | python/run-tests.py | 15 | 13614 | #!/usr/bin/env python3
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "L... | apache-2.0 |
jinglining/flink | flink-python/setup.py | 5 | 12946 | ################################################################################
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this... | apache-2.0 |
rhnvrm/iot-hackerearth | py/sim/wo/work.py | 1 | 5919 | from __future__ import division
import requests
import random
import time
import threading
import rethinkdb as r
import math
import numpy as np
import cv2
import matplotlib
from matplotlib import pyplot as plt
import matplotlib.patches as patches
from scipy.misc import imread
import os
plt.scatter([0,5],[0,5])
plt.io... | mit |
tiagofrepereira2012/tensorflow | tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined_test.py | 52 | 69800 | # 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 |
shanzhenren/ClusType | src/algorithm.py | 1 | 10630 | from collections import defaultdict
from operator import itemgetter
from math import log, sqrt
import random as rn
import time
from numpy import * # install numpy
from scipy import * # install scipy
from numpy.linalg import norm
import numpy.linalg as npl
from scipy.sparse import *
import scipy.sparse.linalg as spsl
fr... | gpl-3.0 |
JasonKessler/scattertext | scattertext/test/test_PriorFactory.py | 1 | 4207 | from unittest import TestCase
import numpy as np
import pandas as pd
from scattertext import LogOddsRatioInformativeDirichletPrior
from scattertext.PriorFactory import PriorFactory
from scattertext.test.test_semioticSquare import get_test_corpus
class TestPriorFactory(TestCase):
def test_all_categories(self):
... | apache-2.0 |
atcemgil/notes | DrawNN.py | 1 | 2429 | #Code from https://gist.github.com/craffel/2d727968c3aaebd10359
import matplotlib.pyplot as plt
def draw_neural_net(ax, left, right, bottom, top, layer_sizes, bias=0, draw_edges=False):
'''
Draw a neural network cartoon using matplotilb.
:usage:
>>> fig = plt.figure(figsize=(12, 12))
... | mit |
uberpye/gwdetchar | gwdetchar/io/tests/test_html.py | 1 | 22674 | # -*- coding: utf-8 -*-
# Copyright (C) Alex Urban (2019)
#
# This file is part of the GW DetChar python package.
#
# GW DetChar 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,... | gpl-3.0 |
dacb/elvizCluster | unit_tests/test_elviz_abundance_utils.py | 2 | 1469 | import unittest
import pandas as pd
class testCompletenessOfSummarisedData(unittest.TestCase):
def test_animal_data(self):
"""
Make sure each sample's fraction of abundance values sums very close
to 1. On toy data set only.
"""
animal_df = pd.read_csv("./summarised_animals... | bsd-3-clause |
ajdawson/colormaps | setup.py | 1 | 2163 | """Build and install the colormaps package."""
# Copyright (c) 2012 Andrew Dawson
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the right... | mit |
stefan-balke/librosa | tests/test_display.py | 2 | 9298 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
# CREATED:2015-02-14 22:51:01 by Brian McFee <brian.mcfee@nyu.edu>
'''Unit tests for display module'''
import warnings
# Disable cache
import os
try:
os.environ.pop('LIBROSA_CACHE_DIR')
except KeyError:
pass
import matplotlib
matplotlib.use('Agg')
matplotlib.rc... | isc |
jstoxrocky/statsmodels | statsmodels/regression/tests/test_regression.py | 6 | 37622 | """
Test functions for models.regression
"""
# TODO: Test for LM
from statsmodels.compat.python import long, lrange
import warnings
import pandas
import numpy as np
from numpy.testing import (assert_almost_equal, assert_approx_equal,
assert_raises, assert_equal, assert_allclose)
from scipy.l... | bsd-3-clause |
google/rysim | python/results_analyzer/Main.py | 1 | 119456 | # Copyright 2014 The RySim 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 applicable law o... | apache-2.0 |
mmottahedi/neuralnilm_prototype | scripts/e349.py | 2 | 6140 | 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,
Bidirectio... | mit |
eg-zhang/scikit-learn | benchmarks/bench_mnist.py | 76 | 6136 | """
=======================
MNIST dataset benchmark
=======================
Benchmark on the MNIST dataset. The dataset comprises 70,000 samples
and 784 features. Here, we consider the task of predicting
10 classes - digits from 0 to 9 from their raw images. By contrast to the
covertype dataset, the feature space is... | bsd-3-clause |
rssenar/PyToolkit | JoinDatasets.py | 1 | 2552 |
#!/usr/bin/env python3.4
# ---------------------------------------------------------------------------- #
import os, csv, glob, re
import pandas as pd
from Constants import ConvPercentage
from tqdm import tqdm
# ---------------------------------------------------------------------------- #
os.chdir('../../../../Deskto... | bsd-2-clause |
low-sky/pyspeckit | pyspeckit/spectrum/models/n2hp.py | 4 | 11414 | """
===========
N2H+ fitter
===========
Reference for line params:
Dore (Private Communication), improving on the determinations from
L. Pagani, F. Daniel, and M. L. Dubernet A&A 494, 719-727 (2009)
DOI: 10.1051/0004-6361:200810570
http://www.strw.leidenuniv.nl/~moldata/N2H+.html
http://adsabs.harvard.edu/abs/2005M... | mit |
agoose77/hivesystem | manual/movingpanda/panda-7.py | 1 | 4435 | import dragonfly
import dragonfly.pandahive
import bee
from bee import connect
import math, functools
from panda3d.core import NodePath
import dragonfly.scene.unbound
import dragonfly.std
import dragonfly.io
import dragonfly.canvas
import Spyder
# ## random matrix generator
from random import random
def random_m... | bsd-2-clause |
open2c/bioframe | bioframe/io/fileops.py | 1 | 21340 | from collections import OrderedDict
from contextlib import closing
import tempfile
import json
import io
import numpy as np
import pandas as pd
try:
import bbi
except ImportError:
bbi = None
try:
import pyBigWig
except ImportError:
pyBigWig = None
from ..core.stringops import parse_region
from ..cor... | mit |
RPGOne/Skynet | scikit-learn-c604ac39ad0e5b066d964df3e8f31ba7ebda1e0e/examples/linear_model/plot_iris_logistic.py | 283 | 1678 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic Regression 3-class Classifier
=========================================================
Show below is a logistic-regression classifiers decision boundaries on the
`iris <http://en.wikipedia.org/wiki/Iris_f... | bsd-3-clause |
clemkoa/scikit-learn | examples/plot_johnson_lindenstrauss_bound.py | 39 | 7489 | r"""
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected i... | bsd-3-clause |
teoliphant/numpy-refactor | numpy/lib/twodim_base.py | 5 | 22944 | """ Basic functions for manipulating 2d arrays
"""
__all__ = ['diag','diagflat','eye','fliplr','flipud','rot90','tri','triu',
'tril','vander','histogram2d','mask_indices',
'tril_indices','tril_indices_from','triu_indices','triu_indices_from',
]
from numpy.core.numeric import asanyarr... | bsd-3-clause |
boddmg/dsp-playground | experiment.py | 1 | 2717 | from matplotlib import pyplot as plt
import numpy as np
import math
import pickle
from scipy import signal
from numpy.fft import rfft, irfft
from numpy import argmax, sqrt, mean, absolute, arange, log10
from scipy.signal import blackmanharris
import thdn
def single_frequency_filter(input_signal):
y_f_all = np.fft.... | mit |
pratapvardhan/pandas | pandas/tests/test_base.py | 2 | 46174 | # -*- coding: utf-8 -*-
from __future__ import print_function
import re
import sys
from datetime import datetime, timedelta
import pytest
import numpy as np
import pandas as pd
import pandas.compat as compat
from pandas.core.dtypes.common import (
is_object_dtype, is_datetimetz, is_datetime64_dtype,
needs_i8_... | bsd-3-clause |
tensorflow/models | research/delf/delf/python/examples/extract_boxes.py | 1 | 7510 | # 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 applicab... | apache-2.0 |
jurajmajor/ltl3tela | Experiments/ltlcross_runner.py | 1 | 23078 | # -*- coding: utf-8 -*-
import subprocess
import sys
import os.path
import re
import math
import spot
from IPython.display import SVG
from datetime import datetime
import pandas as pd
from experiments_lib import hoa_to_spot, dot_to_svg, pretty_print
def bogus_to_lcr(form):
"""Converts a formula as it is printed in... | gpl-3.0 |
wcalvert/LPC11U_LPC13U_CodeBase | src/drivers/sensors/testscripts/plot_xyz_plus_mag_sma.py | 2 | 3774 | #-------------------------------------------------------------------------------
# Name: plot_sensors_event.py
# Purpose: Plots logged sensors_event_t data from logger.c CSV files
#
# Author: K. Townsend
#
# Created: 09/06/2013
# Copyright: (c) K. Townsend 2013
# Licence: BSD
#----------------... | bsd-3-clause |
transientskp/aartfaac-arthur | scripts/arthur-plot.py | 1 | 1440 | #!/usr/bin/env python3
import sys
import numpy as np
from arthur.imaging import full_calculation, calculate_lag
from arthur.io import read_full
from arthur.plot import plot_image, plot_lag, plot_chan_power, plot_corr_mat, plot_diff
from arthur.constants import NUM_CHAN
from matplotlib import pyplot
FRQ = 58398437.5 ... | gpl-3.0 |
magic2du/contact_matrix | Contact_maps/DeepLearning/DeepLearningTool/DL_contact_matrix_load2-new10fold_01_09_2015_01.py | 1 | 25014 |
# coding: utf-8
# In[1]:
# this part imports libs and load data from csv file
import sys
sys.path.append('../../../libs/')
import csv
from dateutil import parser
from datetime import timedelta
from sklearn import svm
import numpy as np
import pandas as pd
import pickle
from sklearn.cross_validation import train_test... | gpl-2.0 |
rvraghav93/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 8 | 35969 | from __future__ import unicode_literals
import warnings
from sklearn.feature_extraction.text import strip_tags
from sklearn.feature_extraction.text import strip_accents_unicode
from sklearn.feature_extraction.text import strip_accents_ascii
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.fe... | bsd-3-clause |
allinpaybusiness/ACS | allinpay projects/creditscoreMLP/classMLP.py | 1 | 9585 | # -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import sys;
import os;
sys.path.append("allinpay projects")
from creditscore.creditscore import CreditScore
import numpy as np
import pandas as pd
import time
from sklearn.model_selection import train_test_split
from sklearn.linear_model ... | apache-2.0 |
surchs/brainbox | visu/base.py | 1 | 8414 | __author__ = 'surchs'
import sys
import numpy as np
from matplotlib import gridspec
from nilearn import plotting as nlp
from matplotlib import pyplot as plt
from matplotlib import colors as mpc
def add_subplot_axes(ax, rect, axisbg='w'):
fig = plt.gcf()
box = ax.get_position()
width = box.width
height... | mit |
rhiever/bokeh | sphinx/source/docs/tutorials/exercises/unemployment.py | 23 | 2160 | import numpy as np
from bokeh.models import HoverTool
from bokeh.plotting import ColumnDataSource, figure, output_file, show
from bokeh.sampledata.unemployment1948 import data
# Read in the data with pandas. Convert the year column to string
data['Year'] = [str(x) for x in data['Year']]
years = list(data['Year'])
mon... | bsd-3-clause |
yousrabk/mne-python | mne/viz/tests/test_misc.py | 17 | 4858 | # Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
# Cathy Nangini <cnangini@gmail.com>
# Mainak Jas <mainak@neuro.hut.fi>
#... | bsd-3-clause |
CVML/scikit-learn | examples/model_selection/plot_underfitting_overfitting.py | 230 | 2649 | """
============================
Underfitting vs. Overfitting
============================
This example demonstrates the problems of underfitting and overfitting and
how we can use linear regression with polynomial features to approximate
nonlinear functions. The plot shows the function that we want to approximate,
wh... | bsd-3-clause |
tipsybear/actors-simulation | tests/test_viz.py | 1 | 1179 | # test_viz
# Vizualization tests
#
# Author: Benjamin Bengfort <bengfort@cs.umd.edu>
# Created: Sun Dec 06 20:45:32 2015 -0500
#
# Copyright (C) 2015 University of Maryland
# For license information, see LICENSE.txt
#
# ID: test_viz.py [] benjamin@bengfort.com $
"""
Vizualization tests
"""
########################... | mit |
ky822/scikit-learn | examples/decomposition/plot_kernel_pca.py | 353 | 2011 | """
==========
Kernel PCA
==========
This example shows that Kernel PCA is able to find a projection of the data
that makes data linearly separable.
"""
print(__doc__)
# Authors: Mathieu Blondel
# Andreas Mueller
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomp... | bsd-3-clause |
DSLituiev/scikit-learn | examples/plot_johnson_lindenstrauss_bound.py | 8 | 7473 | r"""
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected i... | bsd-3-clause |
bigdataelephants/scikit-learn | sklearn/datasets/tests/test_lfw.py | 50 | 6849 | """This test for the LFW require medium-size data dowloading and processing
If the data has not been already downloaded by running the examples,
the tests won't run (skipped).
If the test are run, the first execution will be long (typically a bit
more than a couple of minutes) but as the dataset loader is leveraging
... | bsd-3-clause |
DESHRAJ/crowdsource-platform | crowdsourcing/models.py | 4 | 22804 | from django.contrib.auth.models import User
from django.db import models
from django.utils import timezone
from oauth2client.django_orm import FlowField, CredentialsField
from crowdsourcing.utils import get_delimiter
import pandas as pd
import os
class RegistrationModel(models.Model):
user = models.OneToOneField(... | mit |
elkingtonmcb/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 103 | 22297 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
georgid/sms-tools | lectures/5-Sinusoidal-model/plots-code/sine-analysis-synthesis.py | 2 | 1538 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import sys, os, functools, time
from scipy.fftpack import fft, ifft, fftshift
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel as DFT
import ... | agpl-3.0 |
thaole16/Boids | boids/boids.py | 1 | 4866 | """
A refactored implementation of Boids from a deliberately bad implementation of
[Boids](http://dl.acm.org/citation.cfm?doid=37401.37406): an exercise for class.
"""
from matplotlib import pyplot as plt
from matplotlib import animation
import numpy as np
class Boids(object):
def __init__(self,
... | mit |
Ziqi-Li/bknqgis | pandas/pandas/tests/io/parser/quoting.py | 18 | 5813 | # -*- coding: utf-8 -*-
"""
Tests that quoting specifications are properly handled
during parsing for all of the parsers defined in parsers.py
"""
import csv
import pandas.util.testing as tm
from pandas import DataFrame
from pandas.compat import PY3, StringIO, u
class QuotingTests(object):
def test_bad_quote_... | gpl-2.0 |
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