repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
samuelgarcia/HearingLossSimulator | hearinglosssimulator/tests/find_good_chunksize.py | 1 | 4416 | """
chunksize and backward_chunksize variables have a strong impact
on the quality of backward filtering.
Normally the backward stage pgc2 shoudl be done offline for the whole buffer.
For online it is done chunk by chunksize.
For low frequency this lead to bias the result because of side effect, so the chunksize and... | mit |
lukebarnard1/bokeh | examples/charts/file/scatter.py | 37 | 1607 |
from collections import OrderedDict
import pandas as pd
from bokeh.charts import Scatter, output_file, show, vplot
from bokeh.sampledata.iris import flowers
setosa = flowers[(flowers.species == "setosa")][["petal_length", "petal_width"]]
versicolor = flowers[(flowers.species == "versicolor")][["petal_length", "peta... | bsd-3-clause |
guillermo-carrasco/bcbio-nextgen | bcbio/utils.py | 1 | 20334 | """Helpful utilities for building analysis pipelines.
"""
import gzip
import os
import tempfile
import time
import shutil
import contextlib
import itertools
import functools
import random
import ConfigParser
import collections
import fnmatch
import subprocess
import sys
import subprocess
import toolz as tz
import yaml... | mit |
ssorgatem/qiime | qiime/group.py | 15 | 35019 | #!/usr/bin/env python
"""This module contains functions useful for obtaining groupings."""
__author__ = "Jai Ram Rideout"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Jai Ram Rideout",
"Greg Caporaso",
"Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.9.1-dev"... | gpl-2.0 |
ashhher3/pylearn2 | pylearn2/scripts/datasets/browse_small_norb.py | 44 | 6901 | #!/usr/bin/env python
import sys
import argparse
import pickle
import warnings
import exceptions
import numpy
try:
from matplotlib import pyplot
except ImportError as import_error:
warnings.warn("Can't use this script without matplotlib.")
pyplot = None
from pylearn2.datasets import norb
warnings.warn("T... | bsd-3-clause |
ndchorley/scipy | scipy/stats/_binned_statistic.py | 17 | 17622 | from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from scipy._lib.six import callable
from collections import namedtuple
def binned_statistic(x, values, statistic='mean',
bins=10, range=None):
"""
Compute a binned statistic for a set of d... | bsd-3-clause |
PatrickOReilly/scikit-learn | 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 |
fbagirov/scikit-learn | examples/linear_model/plot_ard.py | 248 | 2622 | """
==================================================
Automatic Relevance Determination Regression (ARD)
==================================================
Fit regression model with Bayesian Ridge Regression.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary l... | bsd-3-clause |
espenhgn/nest-simulator | pynest/examples/twoneurons.py | 3 | 1260 | # -*- coding: utf-8 -*-
#
# twoneurons.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST 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
... | gpl-2.0 |
jorik041/scikit-learn | examples/cluster/plot_lena_segmentation.py | 271 | 2444 | """
=========================================
Segmenting the picture of Lena in regions
=========================================
This example uses :ref:`spectral_clustering` on a graph created from
voxel-to-voxel difference on an image to break this image into multiple
partly-homogeneous regions.
This procedure (spe... | bsd-3-clause |
sgkang/GeophysicsToy | seismic/EOSC350widget.py | 4 | 7381 | import scipy.io
import numpy as np
import matplotlib.pyplot as plt
def ViewWiggle(syndata, obsdata):
dx = 20
fig, ax = plt.subplots(1, 2, figsize=(14, 8))
kwargs = {
'skipt':1,
'scale': 0.05,
'lwidth': 1.,
'dx': dx,
'sampr': 0.004,
'clip' : dx*10.,
}
extent = [0., 38*dx, 1.0... | mit |
andyh616/mne-python | mne/viz/misc.py | 13 | 19748 | """Functions to make simple plots with M/EEG data
"""
from __future__ import print_function
# 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... | bsd-3-clause |
run2/citytour | 4symantec/Lib/site-packages/numpy-1.9.2-py2.7-win-amd64.egg/numpy/lib/npyio.py | 21 | 66671 | from __future__ import division, absolute_import, print_function
import sys
import os
import re
import itertools
import warnings
import weakref
from operator import itemgetter
import numpy as np
from . import format
from ._datasource import DataSource
from ._compiled_base import packbits, unpackbits
from ._iotools im... | mit |
scottpurdy/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/ticker.py | 69 | 37420 | """
Tick locating and formatting
============================
This module contains classes to support completely configurable tick
locating and formatting. Although the locators know nothing about
major or minor ticks, they are used by the Axis class to support major
and minor tick locating and formatting. Generic t... | agpl-3.0 |
THEdavehogue/glassdoor-analysis | topic_modeling.py | 1 | 9413 | import os
import sys
import numpy as np
import pandas as pd
import spacy
import matplotlib.pyplot as plt
from PIL import Image
from clean_text import STOPLIST
from wordcloud import WordCloud
from itertools import combinations
from progressbar import ProgressBar
from sklearn.decomposition import NMF
from sklearn.metrics... | gpl-3.0 |
BorisJeremic/Real-ESSI-Examples | analytic_solution/test_cases/Contact/Stress_Based_Contact_Verification/SoftContact_NonLinHardSoftShear/Area/A_1e2/Normalized_Shear_Stress_Plot.py | 48 | 3533 | #!/usr/bin/python
import h5py
import matplotlib.pylab as plt
import matplotlib as mpl
import sys
import numpy as np;
plt.rcParams.update({'font.size': 28})
# set tick width
mpl.rcParams['xtick.major.size'] = 10
mpl.rcParams['xtick.major.width'] = 5
mpl.rcParams['xtick.minor.size'] = 10
mpl.rcParams['xtick.minor.width... | cc0-1.0 |
DailyActie/Surrogate-Model | 01-codes/scikit-learn-master/examples/svm/plot_svm_kernels.py | 1 | 1969 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
SVM-Kernels
=========================================================
Three different types of SVM-Kernels are displayed below.
The polynomial and RBF are especially useful when the
data-points are not linearly sep... | mit |
mhdella/scikit-learn | sklearn/datasets/species_distributions.py | 198 | 7923 | """
=============================
Species distribution dataset
=============================
This dataset represents the geographic distribution of species.
The dataset is provided by Phillips et. al. (2006).
The two species are:
- `"Bradypus variegatus"
<http://www.iucnredlist.org/apps/redlist/details/3038/0>`_... | bsd-3-clause |
lthurlow/Boolean-Constrained-Routing | networkx-1.8.1/networkx/readwrite/tests/test_gml.py | 35 | 3099 | #!/usr/bin/env python
import io
from nose.tools import *
from nose import SkipTest
import networkx
class TestGraph(object):
@classmethod
def setupClass(cls):
global pyparsing
try:
import pyparsing
except ImportError:
try:
import matplotlib.pyparsi... | mit |
LindaLS/Sausage_Biscuits | architecture/examples/2_nn_autoencoer/load.py | 6 | 1484 | # Example implementing 5 layer encoder
# Original code taken from
# https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/autoencoder.py
# First train a model using train.py
from __future__ import division, print_function, absolute_import
# Import MNIST data
from tensorflow.exampl... | gpl-3.0 |
appapantula/scikit-learn | sklearn/preprocessing/__init__.py | 268 | 1319 | """
The :mod:`sklearn.preprocessing` module includes scaling, centering,
normalization, binarization and imputation methods.
"""
from ._function_transformer import FunctionTransformer
from .data import Binarizer
from .data import KernelCenterer
from .data import MinMaxScaler
from .data import MaxAbsScaler
from .data ... | bsd-3-clause |
uglyboxer/linear_neuron | net-p3/lib/python3.5/site-packages/sklearn/neighbors/nearest_centroid.py | 25 | 7219 | # -*- coding: utf-8 -*-
"""
Nearest Centroid Classification
"""
# Author: Robert Layton <robertlayton@gmail.com>
# Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import warnings
import numpy as np
from scipy import sparse as sp
from ..base import BaseEstimator, ClassifierMixin
from ..ext... | mit |
bavardage/statsmodels | statsmodels/sandbox/km_class.py | 5 | 11704 | #a class for the Kaplan-Meier estimator
import numpy as np
from math import sqrt
import matplotlib.pyplot as plt
class KAPLAN_MEIER(object):
def __init__(self, data, timesIn, groupIn, censoringIn):
raise RuntimeError('Newer version of Kaplan-Meier class available in survival2.py')
#store the inputs... | bsd-3-clause |
scikit-beam/scikit-beam-examples | demos/xrf/demo_xrf_spectrum.py | 5 | 5373 | # ######################################################################
# Copyright (c) 2014, Brookhaven Science Associates, Brookhaven #
# National Laboratory. All rights reserved. #
# #
# @author: Li Li (lili@bnl.g... | bsd-3-clause |
atmtools/typhon | typhon/tests/plots/test_colors.py | 1 | 4724 | # -*- coding: utf-8 -*-
"""Testing the functions in typhon.plots.colors.
"""
import filecmp
import os
from tempfile import mkstemp
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import numpy as np
import pytest
from typhon.plots import colors
class TestColors:
"""Testing the cm functions.""... | mit |
ndingwall/scikit-learn | sklearn/decomposition/_base.py | 5 | 5517 | """Principal Component Analysis Base Classes"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <denis-alexander.engemann@inria.fr>
# Kyle Kastner <kastnerkyle@gmail.com>
... | bsd-3-clause |
johnwu93/find_best_mall | recomendation system/nmf_analysis.py | 3 | 2993 | __author__ = 'John'
#from mall_count_dataset import dict as data
import re
import numpy as np
from sklearn import decomposition
from numpy import linalg as LA
def get_category_matrix(data):
#get the category count matrix from the joe jean dataset.
#This dataset is clean
#constants
category_size = 0
... | mit |
brenoec/cefetmg.msc.influence.networks | simulation/pycxsimulator.py | 1 | 12602 | ## "pycxsimulator.py"
## Realtime Simulation GUI for PyCX
##
## Developed by:
## Chun Wong
## email@chunwong.net
##
## Revised by:
## Hiroki Sayama
## sayama@binghamton.edu
##
## Copyright 2012 Chun Wong & Hiroki Sayama
##
## Simulation control & GUI extensions
## Copyright 2013 Przemyslaw Szufel & Bogumi... | mit |
rdipietro/tensorflow | tensorflow/python/client/notebook.py | 33 | 4608 | # Copyright 2015 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 |
tzulitai/flink | flink-python/pyflink/table/tests/test_pandas_udf.py | 1 | 18807 | ################################################################################
# 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 |
IssamLaradji/scikit-learn | sklearn/tests/test_common.py | 5 | 16372 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
from __future__ import print_function
import os
import warnings
import sys
import pkgutil
from sklearn.externals.six import PY3
fr... | bsd-3-clause |
sknepneklab/SAMoS | analysis/plot_analysis_nematic/angle_plot_pretty_phi.py | 1 | 7874 | # * *************************************************************
# *
# * Soft Active Mater on Surfaces (SAMoS)
# *
# * Author: Rastko Sknepnek
# *
# * Division of Physics
# * School of Engineering, Physics and Mathematics
# * University of Dundee
# *
# * (c) 2013, 2014
# *
# * School of Scienc... | gpl-3.0 |
alanmcruickshank/superset-dev | tests/viz_tests.py | 1 | 23862 | from datetime import datetime
import unittest
from mock import Mock, patch
import pandas as pd
import superset.utils as utils
from superset.utils import DTTM_ALIAS
import superset.viz as viz
class BaseVizTestCase(unittest.TestCase):
def test_constructor_exception_no_datasource(self):
form_data = {}
... | apache-2.0 |
abhishekkrthakur/scikit-learn | examples/linear_model/plot_logistic.py | 312 | 1426 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logit function
=========================================================
Show in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or two, u... | bsd-3-clause |
effigies/mne-python | examples/realtime/ftclient_rt_average.py | 2 | 2816 | """
========================================================
Compute real-time evoked responses with FieldTrip client
========================================================
This example demonstrates how to connect the MNE real-time
system to the Fieldtrip buffer using FieldTripClient class.
This example was tested ... | bsd-3-clause |
Mctigger/KagglePlanetPytorch | find_best_threshold.py | 1 | 1496 | import numpy as np
from sklearn.metrics import fbeta_score, make_scorer
import itertools
import pathos.multiprocessing
def fbeta(true_label, prediction):
return fbeta_score(true_label, prediction, beta=2, average='samples')
def optimise_f2_thresholds_fast(y, p, iterations=100, verbose=True):
best_threshold =... | mit |
schae234/gingivere | tests/test_lr.py | 2 | 1117 | from sklearn.linear_model import LinearRegression
from sklearn.cross_validation import StratifiedKFold
import numpy as np
from sklearn.metrics import classification_report
from sklearn.metrics import roc_auc_score
from tests import shelve_api
XX, yy = shelve_api.load('lr')
X = XX[2700:]
y = yy[2700:]
clf = LinearRe... | mit |
xguse/scikit-bio | skbio/stats/distance/_bioenv.py | 12 | 9577 | # ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
# --------------------------------------------... | bsd-3-clause |
jbedorf/tensorflow | tensorflow/contrib/learn/python/learn/grid_search_test.py | 137 | 2035 | # 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 |
iszlai/sklearn_pycon2015 | notebooks/fig_code/sgd_separator.py | 54 | 1148 | import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import SGDClassifier
from sklearn.datasets.samples_generator import make_blobs
def plot_sgd_separator():
# we create 50 separable points
X, Y = make_blobs(n_samples=50, centers=2,
random_state=0, cluster_std=0.60... | bsd-3-clause |
lesserwhirls/scipy-cwt | scipy/signal/cwt.py | 1 | 25837 | import numpy as np
from scipy.fftpack import fft, ifft, fftshift
__all__ = ['cwt', 'ccwt', 'icwt', 'SDG', 'Morlet']
class MotherWavelet(object):
"""Class for MotherWavelets.
Contains methods related to mother wavelets. Also used to ensure that new
mother wavelet objects contain the minimum requirements ... | bsd-3-clause |
booya-at/paraBEM | examples/plots/far_field_error_src.py | 2 | 1317 | # -*- coding: utf-8 -*-
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import parabem
from parabem.pan3d import src_3_0_vsaero, src_3_0_n0
from parabem.utils import check_path
pnt1 = parabem.PanelVector3(-0.5, -0.5, 0)
pnt2 = parabem.PanelVector3(0.5, -0.5, 0)
pnt3 = parabe... | gpl-3.0 |
pannarale/pycbc | pycbc/results/followup.py | 6 | 4568 | # Copyright (C) 2014 Alex Nitz
#
# 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 License, or (at your
# option) any later version.
#
# This program is distributed in the ... | gpl-3.0 |
WangWenjun559/Weiss | classifier/daily_train.py | 1 | 1788 | """
This file builds a model from training data, which can be incorporated into daily pipeline.
===========================================================================================
TODO(wenjunw@cs.cmu.edu):
- change the path of training file, its transformed feature file, and the model file
currently these fi... | apache-2.0 |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/pandas/util/clipboard/__init__.py | 7 | 3420 | """
Pyperclip
A cross-platform clipboard module for Python. (only handles plain text for now)
By Al Sweigart al@inventwithpython.com
BSD License
Usage:
import pyperclip
pyperclip.copy('The text to be copied to the clipboard.')
spam = pyperclip.paste()
if not pyperclip.copy:
print("Copy functionality unav... | gpl-3.0 |
dhermes/bezier | src/python/bezier/curved_polygon.py | 1 | 9291 | # 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under t... | apache-2.0 |
ruymanengithub/vison | vison/flat/BF01aux.py | 1 | 6503 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Auxiliary Functions and resources to BF01.
Created on Tue Jul 31 17:50:00 2018
:author: Ruyman Azzollini
"""
# IMPORT STUFF
from pdb import set_trace as stop
import numpy as np
import os
from collections import OrderedDict
import string as st
import pandas as pd
... | gpl-3.0 |
siou83/trading-with-python | sandbox/spreadCalculations.py | 78 | 1496 | '''
Created on 28 okt 2011
@author: jev
'''
from tradingWithPython import estimateBeta, Spread, returns, Portfolio, readBiggerScreener
from tradingWithPython.lib import yahooFinance
from pandas import DataFrame, Series
import numpy as np
import matplotlib.pyplot as plt
import os
symbols = ['SPY','... | bsd-3-clause |
chengjunjian/tushare | tushare/util/dateu.py | 27 | 2184 | # -*- coding:utf-8 -*-
import datetime
import pandas as pd
def year_qua(date):
mon = date[5:7]
mon = int(mon)
return[date[0:4], _quar(mon)]
def _quar(mon):
if mon in [1, 2, 3]:
return '1'
elif mon in [4, 5, 6]:
return '2'
elif mon in [7, 8, 9]:
... | bsd-3-clause |
magnunor/hyperspy | hyperspy/misc/holography/tools.py | 4 | 3063 | # -*- coding: utf-8 -*-
# Copyright 2007-2017 The HyperSpy developers
#
# This file is part of HyperSpy.
#
# HyperSpy 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... | gpl-3.0 |
sgrid/pysgrid | demos/basic_interp.py | 3 | 2452 | import numpy as np
import matplotlib.pyplot as plt
import pysgrid
node_lon = np.array(([1, 3, 5], [1, 3, 5], [1, 3, 5]))
node_lat = np.array(([1, 1, 1], [3, 3, 3], [5, 5, 5]))
edge2_lon = np.array(([0, 2, 4, 6], [0, 2, 4, 6], [0, 2, 4, 6]))
edge2_lat = np.array(([1, 1, 1, 1], [3, 3, 3, 3], [5, 5, 5, 5]))
edge1_lon = n... | bsd-3-clause |
lucalianas/openmicroscopy | components/tools/OmeroPy/src/omero/install/jvmcfg.py | 2 | 16253 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2014 Glencoe Software, Inc. All Rights Reserved.
# Use is subject to license terms supplied in LICENSE.txt
#
# 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
# th... | gpl-2.0 |
LLNL/spack | var/spack/repos/builtin/packages/py-misopy/package.py | 5 | 1114 | # Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class PyMisopy(PythonPackage):
"""MISO (Mixture of Isoforms) is a probabilistic framework that
... | lgpl-2.1 |
rkuchan/Tax-Calculator | taxcalc/tests/test_records.py | 3 | 1742 | import os
import sys
CUR_PATH = os.path.abspath(os.path.dirname(__file__))
sys.path.append(os.path.join(CUR_PATH, "../../"))
import numpy as np
from numpy.testing import assert_array_equal
import pandas as pd
import pytest
import tempfile
from numba import jit, vectorize, guvectorize
from taxcalc import *
from taxcalc.... | mit |
VisualComputingInstitute/towards-reid-tracking | track.py | 1 | 15761 | #TODO: comments/doc
import numpy as np
from filterpy.kalman import KalmanFilter
import scipy
from scipy import ndimage
from scipy import signal
from scipy.linalg import block_diag,inv
from filterpy.common import Q_discrete_white_noise
from filterpy.stats import plot_covariance_ellipse
import matplotlib.pyplot as plt
f... | mit |
Srisai85/scikit-learn | sklearn/setup.py | 225 | 2856 | import os
from os.path import join
import warnings
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
from numpy.distutils.system_info import get_info, BlasNotFoundError
import numpy
libraries = []
if os.name == 'posix':
libraries.appe... | bsd-3-clause |
prabhjyotsingh/incubator-zeppelin | python/src/main/resources/python/mpl_config.py | 41 | 3653 | # 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 "License"); you may not use ... | apache-2.0 |
ddboline/pylearn2 | pylearn2/scripts/plot_monitor.py | 37 | 10204 | #!/usr/bin/env python
"""
usage:
plot_monitor.py model_1.pkl model_2.pkl ... model_n.pkl
Loads any number of .pkl files produced by train.py. Extracts
all of their monitoring channels and prompts the user to select
a subset of them to be plotted.
"""
from __future__ import print_function
__authors__ = "Ian Goodfell... | bsd-3-clause |
codematician/study | study/ml/tests/test_classifiers.py | 1 | 3754 | import unittest
import pandas as pd
from study.ml.classifiers import DecisionTreeClassifier, LookUpClassifier, MajorityClassifier
class ClassifierBaseTest(unittest.TestCase):
data1_df = pd.DataFrame({'one': [1., 2., 3., 4.],
'two': [1., 3., 2., 1.]})
class TestDecisionTreeClassif... | apache-2.0 |
kikimaroca/beamtools | beamtools/dev/specplot.py | 1 | 1194 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 8 17:47:28 2018
@author: cpkmanchee
"""
import numpy as np
import matplotlib.pyplot as plt
import beamtools as bt
from matplotlib.gridspec import GridSpec
show_plt = True
save_plt = False
dpi=600
wlim = [1005,1065]
f_sp ='/Users/cpkmanchee/Googl... | mit |
davidsamu/seal | seal/io/convert.py | 1 | 2457 | """
Functions related to converting TPLCell data into Seal data.
@author: David Samu
"""
import os
import pandas as pd
from seal.util import util, constants
from seal.object import unit, unitarray
def task_TPL_to_Seal(f_tpl, f_seal, task, rec_info):
"""Convert TPLCell data to Seal data of single task."""
... | gpl-3.0 |
KarlTDebiec/Moldynplot | moldynplot/PDistFigureManager.py | 2 | 15841 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# moldynplot.PDistFigureManager.py
#
# Copyright (C) 2015-2017 Karl T Debiec
# All rights reserved.
#
# This software may be modified and distributed under the terms of the
# BSD license. See the LICENSE file for details.
"""
Generates probability distribution figures... | bsd-3-clause |
clingsz/GAE | misc/cv/collect_ND5_3.py | 1 | 12374 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 24 10:53:51 2017
@author: cling
"""
# collect ND5_3
import misc.cv.exp_test as exp_test
from misc.utils import saveobj,getJobOpts,loadobj,spearmancorr
import numpy
from misc.data_gen import DataOpts,load_data
import misc.data_gen as data_gen
from gae.model.trainer impor... | gpl-3.0 |
grlee77/scipy | scipy/stats/_discrete_distns.py | 2 | 50643 | #
# Author: Travis Oliphant 2002-2011 with contributions from
# SciPy Developers 2004-2011
#
from functools import partial
from scipy import special
from scipy.special import entr, logsumexp, betaln, gammaln as gamln, zeta
from scipy._lib._util import _lazywhere, rng_integers
from numpy import floor, ceil, ... | bsd-3-clause |
terentjew-alexey/market-analysis-system | data/create_picture.py | 1 | 1393 | import time
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('dark_background')
from mas_tools.data import timeseries_to_img
lpath = 'E:/Projects/market-analysis-system/data/transformed/'
spath = 'E:/Projects/market-analysis-system/data/test/'
fn = 'GBPUSD240'
window = 50
new_data = np.genfromtxt(lp... | mit |
AnasGhrab/scikit-learn | sklearn/mixture/tests/test_dpgmm.py | 261 | 4490 | import unittest
import sys
import numpy as np
from sklearn.mixture import DPGMM, VBGMM
from sklearn.mixture.dpgmm import log_normalize
from sklearn.datasets import make_blobs
from sklearn.utils.testing import assert_array_less, assert_equal
from sklearn.mixture.tests.test_gmm import GMMTester
from sklearn.externals.s... | bsd-3-clause |
darcyabjones/bioplotlib | bioplotlib/collections.py | 1 | 14622 | """ Extension of matplotlib collections.
Classes for the efficient drawing of large collections of objects that
share most properties, e.g., a large number of line segments or
polygons.
The classes are not meant to be as flexible as their single element
counterparts (e.g., you may not be able to select all line style... | bsd-3-clause |
dogwood008/DeepFX | histdata_converter.py | 1 | 2444 |
# coding: utf-8
# In[ ]:
# histdata.comでDLした1分足のデータを任意の足に変換する
# http://www.histdata.com/download-free-forex-historical-data/?/ascii/1-minute-bar-quotes/usdjpy/2017/10
# In[ ]:
import pandas as pd
import numpy as np
from hist_data import HistData, BitcoinHistData
# In[ ]:
def get_new_index(old_dataframe, fr... | mit |
sys-bio/tellurium | examples/notebooks-py/tellurium_stochastic.py | 2 | 2082 |
# coding: utf-8
# Back to the main [Index](../index.ipynb)
# #### Stochastic simulation
#
# Stochastic simulations can be run by changing the current integrator type to 'gillespie' or by using the `r.gillespie` function.
# In[1]:
#!!! DO NOT CHANGE !!! THIS FILE WAS CREATED AUTOMATICALLY FROM NOTEBOOKS !!! CHANGE... | apache-2.0 |
saulberardo/MagikEDA | test/univarTest.py | 1 | 1687 | """
Test Case for module univar.py
"""
import unittest
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from magikeda import univar
class UnivarTestCase(unittest.TestCase):
def test_plot_bar_chart(self):
# Test series with categorical data
d1 = pd.Series(pd.Categorical(['... | gpl-2.0 |
Lawrence-Liu/scikit-learn | sklearn/preprocessing/tests/test_label.py | 156 | 17626 | import numpy as np
from scipy.sparse import issparse
from scipy.sparse import coo_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import dok_matrix
from scipy.sparse import lil_matrix
from sklearn.utils.multiclass import type_of_target
from sklearn.utils.testing impor... | bsd-3-clause |
shikhardb/scikit-learn | examples/linear_model/plot_sgd_weighted_samples.py | 344 | 1458 | """
=====================
SGD: Weighted samples
=====================
Plot decision function of a weighted dataset, where the size of points
is proportional to its weight.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
# we create 20 points
np.random.seed(0)
X ... | bsd-3-clause |
jakereimer/pipeline | python/pipeline/legacy/aodtrk.py | 6 | 18511 | import datajoint as dj
import pandas as pd
from . import aodpre
import warnings
from IPython import embed
import glob
import numpy as np
import dateutil.parser
from . import utils
import cv2
import os,shutil
try:
from pupil_tracking.pupil_tracker_aod import PupilTracker
except ImportError:
warnings.warn("Failed... | lgpl-3.0 |
yavalvas/yav_com | build/matplotlib/examples/api/custom_projection_example.py | 9 | 18246 | from __future__ import unicode_literals
import matplotlib
from matplotlib.axes import Axes
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import NullLocator, Formatter, FixedLocator
from matplotlib.transforms import Affine2D, BboxTransformTo, Transform
from matplotlib.pro... | mit |
SanketDG/networkx | examples/graph/napoleon_russian_campaign.py | 44 | 3216 | #!/usr/bin/env python
"""
Minard's data from Napoleon's 1812-1813 Russian Campaign.
http://www.math.yorku.ca/SCS/Gallery/minard/minard.txt
"""
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
# Copyright (C) 2006 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <sw... | bsd-3-clause |
facebookincubator/prophet | python/prophet/forecaster.py | 2 | 64372 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function
import logging
from collections import OrderedDict, d... | bsd-3-clause |
jreback/pandas | pandas/tests/indexes/multi/test_sorting.py | 1 | 8730 | import random
import numpy as np
import pytest
from pandas.errors import PerformanceWarning, UnsortedIndexError
from pandas import CategoricalIndex, DataFrame, Index, MultiIndex, RangeIndex
import pandas._testing as tm
from pandas.core.indexes.frozen import FrozenList
def test_sortlevel(idx):
tuples = list(idx... | bsd-3-clause |
kiyoto/statsmodels | statsmodels/stats/tests/test_panel_robustcov.py | 34 | 2750 | # -*- coding: utf-8 -*-
"""Test for panel robust covariance estimators after pooled ols
this follows the example from xtscc paper/help
Created on Tue May 22 20:27:57 2012
Author: Josef Perktold
"""
from statsmodels.compat.python import range, lmap
import numpy as np
from numpy.testing import assert_almost_equal
fro... | bsd-3-clause |
henrykironde/scikit-learn | sklearn/feature_selection/variance_threshold.py | 238 | 2594 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: 3-clause BSD
import numpy as np
from ..base import BaseEstimator
from .base import SelectorMixin
from ..utils import check_array
from ..utils.sparsefuncs import mean_variance_axis
from ..utils.validation import check_is_fitted
class VarianceThreshold(BaseEstim... | bsd-3-clause |
lavizhao/Tyrion | learner.py | 1 | 4231 | #coding: utf-8
'''
这个是学习的主要文件
'''
from data import load_label,load_data,load_data_total
from scipy.sparse import csr_matrix
import numpy as np
from sklearn.naive_bayes import GaussianNB as NB
from sklearn import linear_model
from sklearn import svm
from sklearn.ensemble import RandomForestClassifier as RF
from skle... | mit |
akiradeveloper/blktrace | btt/btt_plot.py | 8 | 13237 | #! /usr/bin/env python
#
# btt_plot.py: Generate matplotlib plots for BTT generate data files
#
# (C) Copyright 2009 Hewlett-Packard Development Company, L.P.
#
# 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 So... | gpl-2.0 |
bikong2/scikit-learn | examples/covariance/plot_robust_vs_empirical_covariance.py | 248 | 6359 | r"""
=======================================
Robust vs Empirical covariance estimate
=======================================
The usual covariance maximum likelihood estimate is very sensitive to the
presence of outliers in the data set. In such a case, it would be better to
use a robust estimator of covariance to guar... | bsd-3-clause |
hrjn/scikit-learn | examples/decomposition/plot_pca_iris.py | 49 | 1511 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
PCA example with Iris Data-set
=========================================================
Principal Component Analysis applied to the Iris dataset.
See `here <https://en.wikipedia.org/wiki/Iris_flower_data_set>`_ f... | bsd-3-clause |
rohanp11/IITIGNSSR | src/vtecvtime.py | 1 | 7938 | # Imports
import os,copy,csv
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import radians,sin
from datetime import date, timedelta as td
# Function to cheak if leap year
def checkleap(year):
return ((year % 400 == 0) or ((year % 4 == 0) and (year % 100 != 0)))
# Date of the year Co... | mit |
lenovor/scikit-learn | sklearn/preprocessing/label.py | 35 | 28877 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Olivier Grisel <olivier.grisel@ensta.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Joel Nothman <joel.nothman@gmail.com>
# Hamzeh Alsalhi <ha258@cornell.edu>
# Licens... | bsd-3-clause |
Parallel-in-Time/pySDC | pySDC/playgrounds/deprecated/Dedalus/dynamo_playground.py | 1 | 4660 | import numpy as np
import sys
import matplotlib.pyplot as plt
from mpi4py import MPI
from pySDC.helpers.stats_helper import filter_stats, sort_stats
from pySDC.implementations.collocation_classes.gauss_radau_right import CollGaussRadau_Right
from pySDC.implementations.controller_classes.controller_MPI import controlle... | bsd-2-clause |
phdowling/scikit-learn | examples/neighbors/plot_species_kde.py | 282 | 4059 | """
================================================
Kernel Density Estimate of Species Distributions
================================================
This shows an example of a neighbors-based query (in particular a kernel
density estimate) on geospatial data, using a Ball Tree built upon the
Haversine distance metric... | bsd-3-clause |
kdebrab/pandas | pandas/tests/sparse/test_combine_concat.py | 3 | 15360 | # pylint: disable-msg=E1101,W0612
import pytest
import numpy as np
import pandas as pd
import pandas.util.testing as tm
import itertools
class TestSparseSeriesConcat(object):
def test_concat(self):
val1 = np.array([1, 2, np.nan, np.nan, 0, np.nan])
val2 = np.array([3, np.nan, 4, 0, 0])
... | bsd-3-clause |
JsNoNo/scikit-learn | sklearn/cluster/spectral.py | 233 | 18153 | # -*- coding: utf-8 -*-
"""Algorithms for spectral clustering"""
# Author: Gael Varoquaux gael.varoquaux@normalesup.org
# Brian Cheung
# Wei LI <kuantkid@gmail.com>
# License: BSD 3 clause
import warnings
import numpy as np
from ..base import BaseEstimator, ClusterMixin
from ..utils import check_rand... | bsd-3-clause |
jjx02230808/project0223 | examples/ensemble/plot_forest_iris.py | 335 | 6271 | """
====================================================================
Plot the decision surfaces of ensembles of trees on the iris dataset
====================================================================
Plot the decision surfaces of forests of randomized trees trained on pairs of
features of the iris dataset.
... | bsd-3-clause |
andaag/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 |
jacenkow/beard-server | beard_server/modules/predictor/arxiv.py | 2 | 8502 | # -*- coding: utf-8 -*-
#
# This file is part of Inspire.
# Copyright (C) 2016 CERN.
#
# Inspire 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... | gpl-2.0 |
gfyoung/pandas | pandas/tests/scalar/test_na_scalar.py | 4 | 7335 | import pickle
import numpy as np
import pytest
from pandas._libs.missing import NA
from pandas.core.dtypes.common import is_scalar
import pandas as pd
import pandas._testing as tm
def test_singleton():
assert NA is NA
new_NA = type(NA)()
assert new_NA is NA
def test_repr():
assert repr(NA) == "<... | bsd-3-clause |
VirusTotal/msticpy | msticpy/sectools/syslog_utils.py | 1 | 9857 | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
syslog... | mit |
addfor/addutils | addutils/palette.py | 1 | 5095 | # The MIT License (MIT)
#
# Copyright (c) 2015 addfor s.r.l.
#
# 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 rights
# to use, copy, m... | mit |
liangz0707/scikit-learn | sklearn/ensemble/tests/test_bagging.py | 72 | 25573 | """
Testing for the bagging ensemble module (sklearn.ensemble.bagging).
"""
# Author: Gilles Louppe
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.te... | bsd-3-clause |
BeiLuoShiMen/nupic | examples/opf/tools/MirrorImageViz/mirrorImageViz.py | 50 | 7221 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, 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 |
marionleborgne/nupic.research | projects/sequence_prediction/continuous_sequence/run_adaptive_filter.py | 12 | 5310 | # ----------------------------------------------------------------------
# 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 |
parenthetical-e/pyentropy | docs/sphinxext/inheritance_diagram.py | 98 | 13648 | """
Defines a docutils directive for inserting inheritance diagrams.
Provide the directive with one or more classes or modules (separated
by whitespace). For modules, all of the classes in that module will
be used.
Example::
Given the following classes:
class A: pass
class B(A): pass
class C(A): pass
... | gpl-2.0 |
romanorac/discomll | discomll/tests/tests_classification.py | 1 | 4525 | import unittest
import numpy as np
import Orange
from disco.core import result_iterator
import datasets
class Tests_Classification(unittest.TestCase):
@classmethod
def setUpClass(self):
import chunk_testdata
from disco import ddfs
ddfs = ddfs.DDFS()
if not ddfs.exists("test:... | apache-2.0 |
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