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 |
|---|---|---|---|---|---|
apache/spark | python/pyspark/pandas/tests/test_typedef.py | 15 | 16852 | #
# 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 us... | apache-2.0 |
MTgeophysics/mtpy | mtpy/modeling/modem/plot_response.py | 1 | 123379 | """
==================
ModEM
==================
# Generate files for ModEM
# revised by JP 2017
# revised by AK 2017 to bring across functionality from ak branch
"""
import numpy as np
import os
from matplotlib import pyplot as plt, gridspec as gridspec
from matplotlib.ticker import MultipleLocator
from matplotlib.... | gpl-3.0 |
datapythonista/pandas | pandas/tests/arrays/floating/test_astype.py | 6 | 3917 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_astype():
# with missing values
arr = pd.array([0.1, 0.2, None], dtype="Float64")
with pytest.raises(ValueError, match="cannot convert to 'int64'-dtype NumPy"):
arr.astype("int64")
with pytest.raises(... | bsd-3-clause |
neurohackweek/avalanche | doc/sphinxext/docscrape_sphinx.py | 154 | 7759 | import re, inspect, textwrap, pydoc
import sphinx
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config={}):
self.use_plots = config.get('use_plots', False)
NumpyDocString.__init__(self, docstring, config=config)
... | apache-2.0 |
johnmgregoire/JCAPdatavis | echem_stacked_tern_batch.py | 1 | 6770 | import matplotlib.cm as cm
import numpy
import pylab
import h5py, operator, copy, os, csv, sys
from echem_plate_fcns import *
PyCodePath=os.path.split(os.path.split(os.path.realpath(__file__))[0])[0]
sys.path.append(os.path.join(PyCodePath,'ternaryplot'))
from myternaryutility import TernaryPlot
from myquaternaryutili... | bsd-3-clause |
besser82/shogun | examples/undocumented/python/graphical/preprocessor_kpca_graphical.py | 11 | 1884 | from numpy import *
import matplotlib.pyplot as p
import os, sys, inspect
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../tools'))
if not path in sys.path:
sys.path.insert(1, path)
del path
from generate_circle_data import circle_data
cir=circle_data()
number_of_points_for_circle1=42
number_of_p... | bsd-3-clause |
gibiansky/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/feeding_queue_runner_test.py | 30 | 4727 | # 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 |
Srisai85/scikit-learn | sklearn/utils/tests/test_estimator_checks.py | 202 | 3757 | import scipy.sparse as sp
import numpy as np
import sys
from sklearn.externals.six.moves import cStringIO as StringIO
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.utils.testing import assert_raises_regex, assert_true
from sklearn.utils.estimator_checks import check_estimator
from sklearn.utils.... | bsd-3-clause |
ocefpaf/cartopy | lib/cartopy/examples/arrows.py | 4 | 1195 | """
Arrows
------
Plotting arrows.
"""
__tags__ = ['Vector data']
import matplotlib.pyplot as plt
import numpy as np
import cartopy.crs as ccrs
import cartopy.feature as cfeature
def sample_data(shape=(20, 30)):
"""
Return ``(x, y, u, v, crs)`` of some vector data
computed mathematically. The returned... | lgpl-3.0 |
madan96/sympy | sympy/plotting/plot_implicit.py | 83 | 14400 | """Implicit plotting module for SymPy
The module implements a data series called ImplicitSeries which is used by
``Plot`` class to plot implicit plots for different backends. The module,
by default, implements plotting using interval arithmetic. It switches to a
fall back algorithm if the expression cannot be plotted ... | bsd-3-clause |
jamesafoster/CompSkillsF16 | summarize_Pandas_readtable.py | 2 | 2096 | #!/usr/bin/env python
# demonstration of data exploration code for Comp Bio course, Fall 2016
# James A. Foster
# WARNING: not completely error checked
'''
Usage:
summarize_Pandas.py inputFile
where inputfile is a tab delimited summary of a Hiseq dataset, as in Homework 5
Questions to answer:
- how many times do... | gpl-3.0 |
nathawkins/PHY451_FS_2017 | Pulsed_NMR/NMR Python Tutorial/SpinlabCF.py | 2 | 33740 | # -*- coding: utf-8 -*-
"""
Spinlab Curve Fitting Library
File: SpinlabCF.py
Author: Steve Fromm
Last Modified: 2017-09-05
This library provides an easy to use interface to perform non-linear function
fitting to a provided data set. The underlying curve-fitting algorithm is
from the scipy.optimize package.... | gpl-3.0 |
jdavidrcamacho/Tests_GP | 06 - Results/tests_lineardecay.py | 1 | 16712 | # -*- coding: utf-8 -*-
import Gedi as gedi
import numpy as np; #np.random.seed(13042017)
import matplotlib.pylab as pl; pl.close("all")
import astropy.table as Table
import sys
##### Spots data preparation ##################################################
print
print "**************************************... | mit |
Astroua/TurbuStat | turbustat/statistics/wavelets/wavelet_transform.py | 2 | 25354 | # Licensed under an MIT open source license - see LICENSE
from __future__ import print_function, absolute_import, division
import numpy as np
import warnings
import astropy.units as u
import statsmodels.api as sm
from warnings import warn
from astropy.utils.console import ProgressBar
from astropy.convolution import c... | mit |
sangwook236/general-development-and-testing | sw_dev/python/rnd/test/machine_learning/sklearn/sklearn_logistic_regression.py | 2 | 1182 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# REF [site] >>
# http://scikit-learn.org/stable/modules/linear_model.html
# http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
from sklearn import linear_model
from sklearn import datasets
import numpy as np
def main():
#X = n... | gpl-2.0 |
dreuven/SampleSparse | SampleSparse/scripts/sparsecoding/PersonalPlotting.py | 3 | 9713 | import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
class PPlotting:
root_directory = None
def __init__(self, directory):
# try:
# str(directory)
# except:
# print("Cannot convert input to string. Put in a name!")
self.root_directory = st... | gpl-3.0 |
cameronlai/ml-class-python | skeletons/ex8/ex8_utility.py | 2 | 3960 | import numpy as np
import matplotlib.pyplot as plt
from ex8_cofi import *
def multivariateGaussian(X, mu, Sigma2):
k = mu.size
if Sigma2.shape[0] == 1 or Sigma2.shape[1] == 1:
dim = np.max(Sigma2.shape)
diag = Sigma2
Sigma2 = np.zeros((dim, dim))
np.fill_diagonal(Sigma2, di... | mit |
AIML/scikit-learn | sklearn/feature_selection/__init__.py | 244 | 1088 | """
The :mod:`sklearn.feature_selection` module implements feature selection
algorithms. It currently includes univariate filter selection methods and the
recursive feature elimination algorithm.
"""
from .univariate_selection import chi2
from .univariate_selection import f_classif
from .univariate_selection import f_... | bsd-3-clause |
subutai/htmresearch | projects/sp_paper/plot_traces_with_errorbars.py | 10 | 5345 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# 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 ... | agpl-3.0 |
USF-COT/trdi_adcp_readers | trdi_adcp_readers/readers.py | 1 | 28613 | import numpy as np
import dask.array as darr
from dask import compute, delayed
from dask.bag import from_delayed, from_sequence
from pandas import Timedelta
from xarray import Variable, IndexVariable, DataArray, Dataset
from trdi_adcp_readers.pd0.pd0_parser_sentinelV import (ChecksumError,
... | mit |
NelisVerhoef/scikit-learn | sklearn/preprocessing/tests/test_function_transformer.py | 176 | 2169 | from nose.tools import assert_equal
import numpy as np
from sklearn.preprocessing import FunctionTransformer
def _make_func(args_store, kwargs_store, func=lambda X, *a, **k: X):
def _func(X, *args, **kwargs):
args_store.append(X)
args_store.extend(args)
kwargs_store.update(kwargs)
... | bsd-3-clause |
RuthAngus/LSST-max | code/soft/regions.py | 1 | 5812 | import numpy as np
import matplotlib.pyplot as plt
import time
def regions(seed=0, randspots, activityrate=1, cyclelength=1, cycleoverlap=0,
maxlat=70, minlat=0, tsim=1000, tstart=0, dir="."):
"""
inputs
activityrate - number of bipoles (1= solar)
cyclelength - length of cycle in years
... | mit |
LukeC92/iris | lib/iris/tests/unit/plot/test_scatter.py | 12 | 2596 | # (C) British Crown Copyright 2014 - 2016, Met Office
#
# This file is part of Iris.
#
# Iris 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, or
# (at your option) any l... | lgpl-3.0 |
abitofalchemy/hrg_nets | scale_sampled_graph.py | 1 | 6935 | __authors__ = 'saguinag,tweninge,dchiang'
__contact__ = '{authors}@nd.edu'
__version__ = "0.1.0"
# scale_sampled_graph.py
# VersionLog:
# 0.1.0 Initial state;
import math
import re
import networkx as nx
import pandas as pd
import david as pcfg
import graph_sampler as gs
# import net_metrics as metrics
import pro... | gpl-3.0 |
IssamLaradji/scikit-learn | sklearn/feature_extraction/image.py | 32 | 17167 | """
The :mod:`sklearn.feature_extraction.image` submodule gathers utilities to
extract features from images.
"""
# Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Olivier Grisel
# Vlad Niculae
# License: BSD 3 clause
fro... | bsd-3-clause |
hansomesong/TracesAnalyzer | Plot/Plot_variable_time/Plot_variable_time_Case4-1_scatter.py | 1 | 1899 | __author__ = 'yueli'
import numpy as np
import matplotlib.pyplot as plt
from config.config import *
# Import the targeted raw CSV file
rawCSV_file = os.path.join(PLANET_CSV_DIR, 'liege', 'planetlab1-EID-153.16.47.16-MR-149.20.48.61.log.csv')
# In this situation(this file), there is only RoundNormal and NoMapReply, no... | gpl-2.0 |
openelections/openelections-data-ca | src/parse_general_2014.py | 2 | 3793 | import pandas as pd
import re
from swdb.util import COUNTIES
url_prefix = 'http://elections.cdn.sos.ca.gov/sov/2014-general/xls/'
state_level_files = [
('19-governor.xls', 'Governor'),
('22-lieutenant-governor.xls', 'Lieutenant Governor'),
('25-secretary-of-state.xls', 'Secretary of State'),
('28-cont... | mit |
jdorvi/MonteCarlos_SLC | calculate_gap.py | 1 | 1836 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 17 17:57:40 2016
@author: jdorvinen
"""
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
# <codecell>
# Model data fit: alpha=1.498, beta=-0.348, gamma=1.275
# Callaghan et al. used: alpha=21.46, beta=1.08, gamma=1.07
a = 12*1.49... | mit |
henridwyer/scikit-learn | examples/feature_selection/plot_rfe_with_cross_validation.py | 226 | 1384 | """
===================================================
Recursive feature elimination with cross-validation
===================================================
A recursive feature elimination example with automatic tuning of the
number of features selected with cross-validation.
"""
print(__doc__)
import matplotlib.p... | bsd-3-clause |
yhat/ggplot | tests/test_bar.py | 1 | 2275 | from ggplot import *
import pandas as pd
import numpy as np
import sys
df = pd.DataFrame({
'x': ['a', 'b', 'c', 'b', 'b', 'b', 'a', 'c', 'b', 'c', 'a'],
'wt': [2, 3, 4, 10, 1, 1, 2, 10, 10, 4, 1],
'thingy': ['hi','bye', 'hi', 'bye', 'bye', 'bye', 'bye', 'hi', 'bye', 'bye', 'bye'],
'filler': ['limegreen... | bsd-2-clause |
esdalmaijer/CancellationTools | setup.py | 1 | 6601 | # IMPORTS
# import every package we use, this prevents some errors
import matplotlib, numpy, pygame
# import everything we need to package stuff
from distutils.core import setup
import distutils.sysconfig as sysconfig
from py2exe.build_exe import py2exe
# import modules to to some file magic
import compileall
import os... | gpl-3.0 |
davidgbe/scikit-learn | sklearn/feature_extraction/tests/test_dict_vectorizer.py | 276 | 3790 | # Authors: Lars Buitinck <L.J.Buitinck@uva.nl>
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from random import Random
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from sklearn.utils.testing import (assert_equal, assert_in,
... | bsd-3-clause |
abhisg/scikit-learn | sklearn/tests/test_common.py | 4 | 8719 | """
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 |
gkunter/coquery | test/test_functionlist.py | 1 | 6558 | # -*- coding: utf-8 -*-
"""
This module tests the functionlist module.
Run it like so:
coquery$ python -m test.test_functionlist
"""
from __future__ import unicode_literals
import warnings
import pandas as pd
from argparse import Namespace
import logging
from coquery.functionlist import FunctionList
from coquery.... | gpl-3.0 |
michelp/pywt | demo/dwt_swt_show_coeffs.py | 6 | 2469 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import pywt
import pywt.data
ecg = pywt.data.ecg()
data1 = np.concatenate((np.arange(1, 400),
np.arange(398, 600),
np.arange(601, 1024)))
x = np.linspace(0.082, 2.128, nu... | mit |
kubeflow/pipelines | components/PyTorch/_samples/Train_fully-connected_network.pipeline.py | 1 | 3627 | from kfp import components
chicago_taxi_dataset_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/e3337b8bdcd63636934954e592d4b32c95b49129/components/datasets/Chicago%20Taxi/component.yaml')
pandas_transform_csv_op = components.load_component_from_url('https://raw.githubuse... | apache-2.0 |
dustinbcox/biodatalogger | biodata_grapher.py | 1 | 1356 | #!/usr/bin/python2.7
"""
Biodata_grapher
2015-08-30
"""
import glob
import csv
import os
import matplotlib.pyplot as plt
import matplotlib
from datetime import datetime
import traceback
for filename in glob.glob('*_biodatalogger_readings.csv'):
filename_png = filename.replace('.csv', '.png')
if os.path.exist... | gpl-2.0 |
robintw/scikit-image | doc/examples/plot_polygon.py | 17 | 2597 | """
==================================
Approximate and subdivide polygons
==================================
This example shows how to approximate (Douglas-Peucker algorithm) and subdivide
(B-Splines) polygonal chains.
"""
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
from... | bsd-3-clause |
szhem/spark | examples/src/main/python/sql/arrow.py | 13 | 3997 | #
# 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 us... | apache-2.0 |
meduz/scikit-learn | sklearn/utils/tests/test_fixes.py | 28 | 3156 | # Authors: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Justin Vincent
# Lars Buitinck
# License: BSD 3 clause
import pickle
import numpy as np
import math
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_true
... | bsd-3-clause |
jaeilepp/eggie | mne/epochs.py | 1 | 82772 | """Tools for working with epoched data"""
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Matti Hamalainen <msh@nmr.mgh.harvard.edu>
# Daniel Strohmeier <daniel.strohmeier@tu-ilmenau.de>
# Denis Engemann <denis.engemann@gmail.com>
# Mainak Jas <mainak@neuro... | bsd-2-clause |
glennhickey/hgvm-graph-bakeoff-evaluations | scripts/barchart.py | 6 | 11581 | #!/usr/bin/env python2.7
"""
barchart: plot a bar chart of a TSV file of numbers. The file should be a
column of int or text labels and a column of floats, with one value per label.
Re-uses sample code and documentation from
<http://users.soe.ucsc.edu/~karplus/bme205/f12/Scaffold.html>
"""
import argparse, sys, os, ... | mit |
timqian/sms-tools | lectures/3-Fourier-properties/plots-code/convolution-2.py | 24 | 1259 | import matplotlib.pyplot as plt
import numpy as np
from scipy.fftpack import fft, fftshift
plt.figure(1, figsize=(9.5, 7))
M = 64
N = 64
x1 = np.hanning(M)
x2 = np.cos(2*np.pi*2/M*np.arange(M))
y1 = x1*x2
mY1 = 20 * np.log10(np.abs(fftshift(fft(y1, N))))
plt.subplot(3,2,1)
plt.title('x1 (hanning)')
plt.plot(np.arange... | agpl-3.0 |
rcharp/toyota-flask | venv/lib/python2.7/site-packages/numpy/linalg/linalg.py | 35 | 67345 | """Lite version of scipy.linalg.
Notes
-----
This module is a lite version of the linalg.py module in SciPy which
contains high-level Python interface to the LAPACK library. The lite
version only accesses the following LAPACK functions: dgesv, zgesv,
dgeev, zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetr... | apache-2.0 |
CCI-Tools/ect-core | cate/webapi/mpl.py | 2 | 12044 | # The MIT License (MIT)
# Copyright (c) 2016, 2017 by the ESA CCI Toolbox development team and contributors
#
# 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 wi... | mit |
gotomypc/scikit-learn | sklearn/utils/tests/test_utils.py | 215 | 8100 | import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import pinv2
from itertools import chain
from sklearn.utils.testing import (assert_equal, assert_raises, assert_true,
assert_almost_equal, assert_array_equal,
SkipTest, ... | bsd-3-clause |
fyffyt/scikit-learn | benchmarks/bench_isotonic.py | 268 | 3046 | """
Benchmarks of isotonic regression performance.
We generate a synthetic dataset of size 10^n, for n in [min, max], and
examine the time taken to run isotonic regression over the dataset.
The timings are then output to stdout, or visualized on a log-log scale
with matplotlib.
This alows the scaling of the algorith... | bsd-3-clause |
nhejazi/scikit-learn | sklearn/svm/tests/test_sparse.py | 63 | 13366 | import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from sklearn import datasets, svm, linear_model, base
from sklearn.datasets import make_classification, load_digits, make_blobs
from sklearn.svm.tests import te... | bsd-3-clause |
enigmampc/catalyst | catalyst/assets/synthetic.py | 1 | 8861 | from itertools import product
from string import ascii_uppercase
import pandas as pd
from pandas.tseries.offsets import MonthBegin
from six import iteritems
from .futures import CME_CODE_TO_MONTH
def make_rotating_equity_info(num_assets,
first_start,
frequ... | apache-2.0 |
trichter/sito | bin/rf/rf_timevari2_old.py | 1 | 13003 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# by TR
from IPython import embed
from obspy.core import UTCDateTime as UTC
from operator import neg
from sito import read
from sito.stream import Stream
from termcolor import colored
import cPickle
import collections
import matplotlib as mpl
import numpy as np
import pylab... | mit |
adiIspas/Machine-Learning_A-Z | Machine Learning A-Z/Part 3 - Classification/Section 19 - Decision Tree Classification/decision_tree_classification.py | 5 | 2725 | # Decision Tree Classification
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Social_Network_Ads.csv')
X = dataset.iloc[:, [2, 3]].values
y = dataset.iloc[:, 4].values
# Splitting the dataset into the Training set and Te... | mit |
rajat1994/scikit-learn | examples/text/document_clustering.py | 230 | 8356 | """
=======================================
Clustering text documents using k-means
=======================================
This is an example showing how the scikit-learn can be used to cluster
documents by topics using a bag-of-words approach. This example uses
a scipy.sparse matrix to store the features instead of ... | bsd-3-clause |
lanfker/tdma_imac | src/flow-monitor/examples/wifi-olsr-flowmon.py | 27 | 7354 | # -*- Mode: Python; -*-
# Copyright (c) 2009 INESC Porto
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation;
#
# This program is distributed in the hope that it will be useful,
#... | gpl-2.0 |
nicproulx/mne-python | mne/preprocessing/tests/test_ica.py | 2 | 31454 | from __future__ import print_function
# Author: Denis Engemann <denis.engemann@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import os
import os.path as op
import warnings
from nose.tools import (assert_true, assert_raises, assert_equal, assert_false,
... | bsd-3-clause |
luo66/scikit-learn | sklearn/cluster/tests/test_affinity_propagation.py | 341 | 2620 | """
Testing for Clustering methods
"""
import numpy as np
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.cluster.affinity_propagation_ import AffinityPropagation
from sklearn.cluster.affinity_propagatio... | bsd-3-clause |
paula-tataru/SpikeyTree | src/optimize.py | 1 | 8262 | # This file is part of SpikeyTree.
# Copyright (C) 2015 Paula Tataru
# SpikeyTree 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.
# T... | gpl-3.0 |
juanshishido/okcupid | utils/clean_up.py | 1 | 1270 | import re
import numpy as np
import pandas as pd
from bs4 import BeautifulSoup
def clean_up(input_df, col_names, min_words=5):
'''
Input : data frame and list of columns to clean up
Returns: cleaned data frame (overwrites those columns)
Drops user if any essay has < min_words number of words (default... | mit |
hall-lab/svtools | svtools/sv_classifier.py | 1 | 25139 | #!/usr/bin/env python
import argparse, sys, copy, gzip, math
import numpy as np
import pandas as pd
from scipy import stats
from collections import namedtuple
import statsmodels.formula.api as smf
from operator import itemgetter
import warnings
from svtools.vcf.file import Vcf
from svtools.vcf.variant import Variant
i... | mit |
molliewebb/aston | aston/qtgui/PlotSpec.py | 3 | 5186 | import time
import numpy as np
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg
from matplotlib.backends.backend_qt4 import NavigationToolbar2QT
#from matplotlib.ticker import AutoMinorLocator
#from aston.spectra import Spectrum
class SpecPlotter(object):
def _... | gpl-3.0 |
Mushirahmed/gnuradio | gr-utils/src/python/plot_psd_base.py | 75 | 12725 | #!/usr/bin/env python
#
# Copyright 2007,2008,2010,2011 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 ... | gpl-3.0 |
amozie/amozie | testzie/table_test.py | 1 | 3048 | import numpy as np
import pandas as pd
lt = 'f:/lt/'
region = pd.read_csv(lt + 'region.csv',sep='\t', index_col=0)
# 排除内蒙古和西藏
# prvs = ['北京', '天津', '河北', '山东', '辽宁', '江苏', '上海', '浙江', '福建', '广东', '海南', '吉林',
# '黑龙江', '山西', '河南', '安徽', '江西', '湖北', '湖南', '广西', '重庆', '四川', '贵州', '云南',
# '陕西', '甘肃', '青海', '... | apache-2.0 |
taknevski/tensorflow-xsmm | tensorflow/python/estimator/inputs/pandas_io.py | 86 | 4503 | # 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 |
femtotrader/ig-markets-stream-api-python-library | tests/test_historical_prices_flat.py | 2 | 9617 | from trading_ig.rest import IGService
import responses
import json
import pandas as pd
import datetime
import pytest
"""
unit tests for historical prices methods with flat output formatting
"""
class TestHistoricalPricesFlat:
@responses.activate
def test_historical_prices_v3_defaults_happy(self):
#... | bsd-3-clause |
poryfly/scikit-learn | sklearn/manifold/isomap.py | 229 | 7169 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
bsipocz/statsmodels | statsmodels/sandbox/rls.py | 33 | 5179 | """Restricted least squares
from pandas
License: Simplified BSD
"""
from __future__ import print_function
import numpy as np
from statsmodels.regression.linear_model import WLS, GLS, RegressionResults
class RLS(GLS):
"""
Restricted general least squares model that handles linear constraints
Parameters
... | bsd-3-clause |
leesavide/pythonista-docs | Documentation/matplotlib/pyplots/text_layout.py | 6 | 2085 | import matplotlib.pyplot as plt
import matplotlib.patches as patches
# build a rectangle in axes coords
left, width = .25, .5
bottom, height = .25, .5
right = left + width
top = bottom + height
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
# axes coordinates are 0,0 is bottom left and 1,1 is upper right
p = patche... | apache-2.0 |
galfaroi/trading-with-python | cookbook/workingWithDatesAndTime.py | 77 | 1551 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 16 17:45:02 2011
@author: jev
"""
import time
import datetime as dt
from pandas import *
from pandas.core import datetools
# basic functions
print 'Epoch start: %s' % time.asctime(time.gmtime(0))
print 'Seconds from epoch: %.2f' % time.time()
t... | bsd-3-clause |
ktaneishi/deepchem | examples/binding_pockets/binding_pocket_datasets.py | 9 | 6311 | """
PDBBind binding pocket dataset loader.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
import os
import numpy as np
import pandas as pd
import shutil
import time
import re
from rdkit import Chem
import deepchem as dc
def compute_binding_pocket_fea... | mit |
wanggang3333/scikit-learn | sklearn/metrics/cluster/__init__.py | 312 | 1322 | """
The :mod:`sklearn.metrics.cluster` submodule contains evaluation metrics for
cluster analysis results. There are two forms of evaluation:
- supervised, which uses a ground truth class values for each sample.
- unsupervised, which does not and measures the 'quality' of the model itself.
"""
from .supervised import ... | bsd-3-clause |
harisbal/pandas | pandas/tests/scalar/interval/test_ops.py | 1 | 2370 | """Tests for Interval-Interval operations, such as overlaps, contains, etc."""
import pytest
from pandas import Interval, Timedelta, Timestamp
import pandas.util.testing as tm
@pytest.fixture(params=[
(Timedelta('0 days'), Timedelta('1 day')),
(Timestamp('2018-01-01'), Timedelta('1 day')),
(0, 1)], ids=l... | bsd-3-clause |
moutai/scikit-learn | examples/cluster/plot_face_compress.py | 71 | 2479 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Vector Quantization Example
=========================================================
Face, a 1024 x 768 size image of a raccoon face,
is used here to illustrate how `k`-means is
used for vector quantization.
"""
... | bsd-3-clause |
pianomania/scikit-learn | examples/mixture/plot_gmm_selection.py | 95 | 3310 | """
================================
Gaussian Mixture Model Selection
================================
This example shows that model selection can be performed with
Gaussian Mixture Models using information-theoretic criteria (BIC).
Model selection concerns both the covariance type
and the number of components in the ... | bsd-3-clause |
chenyyx/scikit-learn-doc-zh | examples/zh/linear_model/plot_sgd_loss_functions.py | 86 | 1234 | """
==========================
SGD: convex loss functions
==========================
A plot that compares the various convex loss functions supported by
:class:`sklearn.linear_model.SGDClassifier` .
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def modified_huber_loss(y_true, y_pred):
z ... | gpl-3.0 |
ankanch/tieba-zhuaqu | DSV-user-application-plugin-dev-kit/default-plugins/tiebaX/lib/graphicsData.py | 1 | 3707 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
import numpy
import os
font_set = FontProperties(fname=r"c:\\windows\\fonts\\simsun.ttc", size=15)
#重要全局变量
PATH_SUFFIX = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir))
PATH_SU... | gpl-3.0 |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/legend_handler.py | 6 | 22594 | """
This module defines default legend handlers.
It is strongly encouraged to have read the :ref:`legend guide
<plotting-guide-legend>` before this documentation.
Legend handlers are expected to be a callable object with a following
signature. ::
legend_handler(legend, orig_handle, fontsize, handlebox)
Where *l... | gpl-3.0 |
Lawrence-Liu/scikit-learn | examples/svm/plot_svm_regression.py | 249 | 1451 | """
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
===================================================================
Toy example of 1D regression using linear, polynomial and RBF kernels.
"""
print(__doc__)
import numpy as np
... | bsd-3-clause |
xiaoxiamii/scikit-learn | sklearn/tests/test_discriminant_analysis.py | 5 | 11057 | try:
# Python 2 compat
reload
except NameError:
# Regular Python 3+ import
from importlib import reload
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.t... | bsd-3-clause |
benjello/openfisca-france-indirect-taxation | openfisca_france_indirect_taxation/non_working_tests/tests_aids_categ.py | 4 | 4880 | # -*- coding: utf-8 -*-
"""
Created on Thu Jul 09 18:41:37 2015
@author: thomas.douenne
"""
# To do : change this test to fit with energy instead of categ
import pandas as pd
from openfisca_france_indirect_taxation.almost_ideal_demand_system.aids_dataframe_builder_categ import \
aggregates_data_frame, df, produ... | agpl-3.0 |
gena/qgis-earthengine-plugin | contrib/palettes.py | 1 | 45630 | # Copyright (c) 2018 Gennadii Donchyts. All rights reserved.
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
# Contributors:
# * 2018-08-01: Fedor Baart (f.baart@gmail.com) - added cmocean
# * 2019-01-18: Justin Braaten (jstnbraaten@gmail.com) - ... | mit |
robin-lai/scikit-learn | sklearn/neural_network/tests/test_rbm.py | 225 | 6278 | import sys
import re
import numpy as np
from scipy.sparse import csc_matrix, csr_matrix, lil_matrix
from sklearn.utils.testing import (assert_almost_equal, assert_array_equal,
assert_true)
from sklearn.datasets import load_digits
from sklearn.externals.six.moves import cStringIO as ... | bsd-3-clause |
MVilstrup/visualize | decision_regions.py | 1 | 3766 | # This code is a modified version of Sebastian Raschka's file of same name
# Original code can be found here:
# https://github.com/rasbt/mlxtend/blob/master/mlxtend/evaluate/decision_regions.py
from itertools import cycle
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
... | mit |
YzPaul3/h2o-3 | py2/h2o_gbm.py | 30 | 16328 |
import re, random, math
import h2o_args
import h2o_nodes
import h2o_cmd
from h2o_test import verboseprint, dump_json, check_sandbox_for_errors
def plotLists(xList, xLabel=None, eListTitle=None, eList=None, eLabel=None, fListTitle=None, fList=None, fLabel=None, server=False):
if h2o_args.python_username!='kevin':
... | apache-2.0 |
barak/autograd | examples/fluidsim/fluidsim.py | 1 | 4629 | from __future__ import absolute_import
from __future__ import print_function
import autograd.numpy as np
from autograd import value_and_grad
from scipy.optimize import minimize
from scipy.misc import imread
import matplotlib
import matplotlib.pyplot as plt
import os
from builtins import range
# Fluid simulation code... | mit |
b-cuts/airflow | airflow/hooks/base_hook.py | 20 | 1812 | from builtins import object
import logging
import os
import random
from airflow import settings
from airflow.models import Connection
from airflow.utils import AirflowException
CONN_ENV_PREFIX = 'AIRFLOW_CONN_'
class BaseHook(object):
"""
Abstract base class for hooks, hooks are meant as an interface to
... | apache-2.0 |
dhuppenkothen/stingray | stingray/tests/test_io.py | 1 | 6788 | from __future__ import (absolute_import, unicode_literals, division,
print_function)
import numpy as np
import os
from ..io import read, write
import warnings
curdir = os.path.abspath(os.path.dirname(__file__))
datadir = os.path.join(curdir, 'data')
class TestIO(object):
"""Real unit te... | mit |
michaelerule/neurotools | stats/matzner_bar-gad_PLoS_2015.py | 1 | 3690 | #!/usr/bin/python
# -*- coding: UTF-8 -*-
from __future__ import absolute_import
from __future__ import with_statement
from __future__ import division
from __future__ import nested_scopes
from __future__ import generators
from __future__ import unicode_literals
from __future__ import print_function
from neurotools.syst... | gpl-3.0 |
florentchandelier/zipline | zipline/__main__.py | 1 | 12454 | import errno
import os
from importlib import import_module
from functools import wraps
import click
import logbook
import pandas as pd
from six import text_type
import pkgutil
from zipline.data import bundles as bundles_module
from zipline.utils.cli import Date, Timestamp
from zipline.utils.run_algo import _run, lo... | apache-2.0 |
ODM2/ODMToolsPython | odmtools/lib/ObjectListView/virtualObjectListviewExample.py | 1 | 16457 | import wx
import wx.xrc
import sys
sys.path.insert(0, "/home/jmeline/Projects/ODMToolsPython/odmtools/lib")
from ObjectListView import VirtualObjectListView as OLV, ColumnDefn
import pandas as pd
import numpy as np
# Simple minded model objects for our examples
import datetime
class Track(object):
"""
Simpl... | bsd-3-clause |
renewables-ninja/gsee | gsee/climatedata_interface/pre_gsee_processing.py | 1 | 14293 | import math as m
import pandas as pd
import warnings
import numpy as np
import xarray as xr
import scipy.stats as st
from calendar import monthrange
from gsee.climatedata_interface import kt_h_sinusfunc as cyth
from gsee.climatedata_interface.progress import progress_bar
from gsee import trigon, brl_model
from gsee imp... | bsd-3-clause |
whn09/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/pandas_io_test.py | 111 | 7865 | # 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 |
tkralphs/Dip | Dip/scripts/plot_bounds.py | 2 | 2055 | import matplotlib.pyplot as plt
plt.rc('axes', grid=True)
plt.rc('grid', color='0.75', linestyle='-', linewidth=0.5)
#textsize = 9
#left, width = 0.1, 0.8
#rect1 = [left, 0.7, width, 0.2]
#rect2 = [left, 0.3, width, 0.4]
#rect3 = [left, 0.1, width, 0.2]
fig = plt.figure(facecolor='white')
axescolor = ... | epl-1.0 |
gregreen/legacypipe | py/legacypipe/runbrick.py | 1 | 124870 | '''
Main "pipeline" script for the Dark Energy Camera Legacy Survey (DECaLS)
data reductions.
For calling from other scripts, see:
- :py:func:`run_brick`
Or for much more fine-grained control, see the individual stages:
- :py:func:`stage_tims`
- :py:func:`stage_image_coadds`
- :py:func:`stage_srcs`
- :py:func:`stag... | gpl-2.0 |
Lawrence-Liu/scikit-learn | doc/sphinxext/gen_rst.py | 142 | 40026 | """
Example generation for the scikit learn
Generate the rst files for the examples by iterating over the python
example files.
Files that generate images should start with 'plot'
"""
from __future__ import division, print_function
from time import time
import ast
import os
import re
import shutil
import traceback
i... | bsd-3-clause |
trungnt13/scikit-learn | sklearn/manifold/tests/test_isomap.py | 226 | 3941 | from itertools import product
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from sklearn import datasets
from sklearn import manifold
from sklearn import neighbors
from sklearn import pipeline
from sklearn import preprocessing
from sklearn.utils.testing import assert_less
... | bsd-3-clause |
ecell/epdp | samples/rebind/plot.py | 3 | 3514 | #!/usr/bin/env/python
# varying kf
# python plot.py 05/data/rebind_1_0.1_ALL_t.dat 05/data/rebind_1_1_ALL_t.dat 05/data/rebind_1_10_ALL_t.dat
# 0.01 didn't run correctly?
# 05/data/rebind_1_0.01_ALL_t.dat
# varying D
# python plot.py 07/data/rebind_0.1_10_0_ALL_t.dat 07/data/rebind_1_10_0_ALL_t.dat 07/data/rebind... | gpl-2.0 |
deeplook/bokeh | examples/compat/seaborn/violin.py | 34 | 1153 | import seaborn as sns
from bokeh import mpl
from bokeh.plotting import output_file, show
tips = sns.load_dataset("tips")
sns.set_style("whitegrid")
# ax = sns.violinplot(x="size", y="tip", data=tips.sort("size"))
# ax = sns.violinplot(x="size", y="tip", data=tips,
# order=np.arange(1, 7), palett... | bsd-3-clause |
yashu-seth/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 |
btabibian/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 83 | 5888 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
detrout/debian-statsmodels | statsmodels/examples/ex_regressionplots.py | 34 | 4457 | # -*- coding: utf-8 -*-
"""Examples for Regression Plots
Author: Josef Perktold
"""
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
from statsmodels.sandbox.regression.predstd import wls_prediction_std
import statsmodels.graphics.regressionplots ... | bsd-3-clause |
pvalienteverde/ElCuadernillo | ElCuadernillo/20160725_SistemasDeRecomendacionContentBased/Scripts/ContendBased.py | 1 | 2180 | import pandas as pd
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.neighbors import NearestNeighbors
import numpy as np
from nltk.corpus import stopwords
class ContentBased(object):
"""
Modelo de recomendación de articulos basad... | mit |
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