repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
deapplegate/wtgpipeline | CRNitschke/StarStripper.py | 1 | 14983 | #! /usr/bin/env python
import sys ; sys.path.append('/u/ki/awright/InstallingSoftware/pythons/')
import imagetools
from import_tools import *
import numpy
numpy.warnings.filterwarnings('ignore') #adam-tmp#
warnings.simplefilter("ignore", DeprecationWarning)
fl=sys.argv[-1]
ending=""
#fl='/nfs/slac/g/ki/ki18/anja/SUBARU... | mit |
pylayers/pylayers | pylayers/em/openems/nf2ff.py | 3 | 1578 | import h5py
import numpy as np
import matplotlib.pyplot as plt
f = h5py.File('nf2ff.h5','r')
hdf_mesh = f['Mesh']
r = np.array(hdf_mesh['r'])
theta = np.array(hdf_mesh['theta'])
phi = np.array(hdf_mesh['phi'])
nf2ff = f['nf2ff']
attrs = nf2ff.attrs.items()
freq = attrs[0][1]
Prad = attrs[1][1]
Dmax = attrs[2][1... | mit |
akrherz/iem | htdocs/plotting/auto/scripts/p67.py | 1 | 3664 | """Wind Speed by Temperature"""
import datetime
import calendar
import matplotlib.patheffects as PathEffects
import psycopg2.extras
import pandas as pd
from pyiem.util import get_autoplot_context, get_dbconn
from pyiem.plot.use_agg import plt
from pyiem.exceptions import NoDataFound
def get_description():
""" Re... | mit |
hlin117/scikit-learn | sklearn/tests/test_kernel_approximation.py | 78 | 7586 | import numpy as np
from scipy.sparse import csr_matrix
from sklearn.utils.testing import assert_array_equal, assert_equal, assert_true
from sklearn.utils.testing import assert_not_equal
from sklearn.utils.testing import assert_array_almost_equal, assert_raises
from sklearn.utils.testing import assert_less_equal
from ... | bsd-3-clause |
stylianos-kampakis/scikit-learn | examples/bicluster/plot_spectral_biclustering.py | 403 | 2011 | """
=============================================
A demo of the Spectral Biclustering algorithm
=============================================
This example demonstrates how to generate a checkerboard dataset and
bicluster it using the Spectral Biclustering algorithm.
The data is generated with the ``make_checkerboard`... | bsd-3-clause |
squilter/MAVProxy | MAVProxy/modules/lib/live_graph.py | 3 | 2920 | #!/usr/bin/env python
"""
MAVProxy realtime graphing module, partly based on the wx graphing
demo by Eli Bendersky (eliben@gmail.com)
http://eli.thegreenplace.net/files/prog_code/wx_mpl_dynamic_graph.py.txt
"""
from MAVProxy.modules.lib import mp_util
class LiveGraph():
'''
a live graph object using ... | gpl-3.0 |
mjzmjz/swift | swift/common/middleware/x_profile/html_viewer.py | 25 | 21039 | # Copyright (c) 2010-2012 OpenStack, LLC.
#
# 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 or agreed to ... | apache-2.0 |
nowls/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 |
xuleiboy1234/autoTitle | tensorflow/tensorflow/examples/learn/iris.py | 29 | 2313 | # 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... | mit |
silgon/rlpy | rlpy/Representations/LocalBases.py | 4 | 7162 | """
Representations which use local bases function (e.g. kernels) distributed
in the statespace according to some scheme (e.g. grid, random, on previous
samples)
"""
from .Representation import Representation
import numpy as np
from rlpy.Tools.GeneralTools import addNewElementForAllActions
import matplotlib.pyplot as p... | bsd-3-clause |
mcanthony/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/offsetbox.py | 69 | 17728 | """
The OffsetBox is a simple container artist. The child artist are meant
to be drawn at a relative position to its parent. The [VH]Packer,
DrawingArea and TextArea are derived from the OffsetBox.
The [VH]Packer automatically adjust the relative postisions of their
children, which should be instances of the OffsetBo... | agpl-3.0 |
ahoyosid/scikit-learn | sklearn/tests/test_common.py | 7 | 7677 | """
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 |
rsivapr/scikit-learn | sklearn/neighbors/graph.py | 10 | 2847 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def kneighbors_graph(X, n_neighbors, mode='connectivity'... | bsd-3-clause |
dsm054/pandas | asv_bench/benchmarks/plotting.py | 3 | 1454 | import numpy as np
from pandas import DataFrame, Series, DatetimeIndex, date_range
try:
from pandas.plotting import andrews_curves
except ImportError:
from pandas.tools.plotting import andrews_curves
import matplotlib
matplotlib.use('Agg')
class Plotting(object):
def setup(self):
self.s = Series(... | bsd-3-clause |
yunque/librosa | librosa/core/spectrum.py | 1 | 25275 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''Utilities for spectral processing'''
import numpy as np
import scipy.fftpack as fft
import scipy
import scipy.signal
import six
from . import time_frequency
from .. import cache
from .. import util
from ..util.exceptions import ParameterError
__all__ = ['stft', 'istft... | isc |
preghenella/AliPhysics | PWGPP/FieldParam/fitsol.py | 39 | 8343 | #!/usr/bin/env python
debug = True # enable trace
def trace(x):
global debug
if debug: print(x)
trace("loading...")
from itertools import combinations, combinations_with_replacement
from glob import glob
from math import *
import operator
from os.path import basename
import matplotlib.pyplot as plt
import numpy as... | bsd-3-clause |
AtsushiSakai/PythonRobotics | PathPlanning/AStar/a_star_searching_from_two_side.py | 1 | 13901 | """
A* algorithm
Author: Weicent
randomly generate obstacles, start and goal point
searching path from start and end simultaneously
"""
import numpy as np
import matplotlib.pyplot as plt
import math
show_animation = True
class Node:
"""node with properties of g, h, coordinate and parent node"""
def __init_... | mit |
ricardobergamo/dataGAL | views/bmh.py | 1 | 2726 | #!/usr/bin/env python
from flask import render_template
from sqlalchemy import func
import pandas as pd
from manager import app
from models.bmh import *
from models.datagal import Regional, Laboratorio
@app.route('/bmh/painel')
def bmh_painel():
requisicao = Requisicao.get()
exames = Exames.get()
exame_s... | gpl-3.0 |
louispotok/pandas | pandas/tests/indexes/timedeltas/test_construction.py | 3 | 3568 | import pytest
import numpy as np
from datetime import timedelta
import pandas as pd
import pandas.util.testing as tm
from pandas import TimedeltaIndex, timedelta_range, to_timedelta
class TestTimedeltaIndex(object):
def test_construction_base_constructor(self):
arr = [pd.Timedelta('1 days'), pd.NaT, pd... | bsd-3-clause |
openeemeter/eemeter | eemeter/visualization.py | 1 | 4111 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Copyright 2014-2019 OpenEEmeter contributors
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/LIC... | apache-2.0 |
michellab/Sire | wrapper/Tools/Plot.py | 2 | 2857 |
import matplotlib
matplotlib.use('TkAgg')
from matplotlib import pyplot
from Sire.Maths import Histogram, HistogramValue
from Sire.Analysis import DataPoint
def _plotHistogram(histogram):
x = []
y = []
for value in list(histogram.values()):
x.append(value.minimum())
y.append(0)
x.... | gpl-2.0 |
jrversteegh/softsailor | softsailor/polars.py | 1 | 8539 | """
Polars module
Contains classes for dealing with boat polars
"""
__author__ = "J.R. Versteegh"
__copyright__ = "Copyright 2011, J.R. Versteegh"
__contact__ = "j.r.versteegh@gmail.com"
__version__ = "0.1"
__license__ = "GPLv3, No Warranty. See 'LICENSE'"
import os
import math
import numpy as np
from urllib2 import... | gpl-3.0 |
hennersz/pySpace | basemap/examples/plotsst.py | 8 | 1770 | from mpl_toolkits.basemap import Basemap
from netCDF4 import Dataset, date2index
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
date = datetime(2007,12,15,0) # date to plot.
# open dataset.
dataset = \
Dataset('http://www.ncdc.noaa.gov/thredds/dodsC/OISST-V2-AVHRR_agg')
timevar = datas... | gpl-3.0 |
DSSG-paratransit/main_repo | Access_Analysis_Project/Scripts/4moDeadheadResultsToCsvParalleled.py | 1 | 961533 | import multiprocessing as mp
import numpy as np
import pandas as pd
import os
def findZeroes(row, numRows):
os.system(['clear', 'cls'][os.name == 'nt'])
print row
print str(float(row.name) / numRows * 100) + '%' + ' done'
busRun = data[(data['ServiceDate'] == row[0]) & (data['Run'] == row[1])]
if ... | agpl-3.0 |
erdc-cm/air-water-vv | 2d/numericalTanks/nonlinearWaves/postprocess_NLW.py | 1 | 4065 | import numpy as np
import collections as cll
import csv
import os
import matplotlib.pyplot as plt
import nonlinear_waves as nlw
from proteus import WaveTools as wt
from AnalysisTools import signalFilter,zeroCrossing,reflStat
#####################################################################################... | mit |
lukebarnard1/bokeh | sphinx/source/docs/tutorials/solutions/stocks.py | 23 | 2799 | ###
### NOTE: This exercise requires a network connection
###
import numpy as np
import pandas as pd
from bokeh.plotting import figure, output_file, show, VBox
# Here is some code to read in some stock data from the Yahoo Finance API
AAPL = pd.read_csv(
"http://ichart.yahoo.com/table.csv?s=AAPL&a=0&b=1&c=2000&d=... | bsd-3-clause |
Myasuka/scikit-learn | examples/cluster/plot_adjusted_for_chance_measures.py | 286 | 4353 | """
==========================================================
Adjustment for chance in clustering performance evaluation
==========================================================
The following plots demonstrate the impact of the number of clusters and
number of samples on various clustering performance evaluation me... | bsd-3-clause |
neozhangthe1/coverage_model | scripts/evaluate.py | 1 | 2312 | #!/usr/bin/env python
import numpy
import pandas
import argparse
import matplotlib
import logging
matplotlib.use("Agg")
from matplotlib import pyplot
logger = logging.getLogger()
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--start", type=int, default=0, help="Start from this ite... | bsd-3-clause |
Eric89GXL/mne-python | mne/viz/_brain/_brain.py | 2 | 132116 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Eric Larson <larson.eric.d@gmail.com>
# Oleh Kozynets <ok7mailbox@gmail.com>
# Guillaume Favelier <guillaume.favelier@gmail.com>
# jona-sassenhagen <jona.sassenhagen@gmail.com>
# Joan Massich <mailsik@gmail.com>
#... | bsd-3-clause |
ibab/tensorflow | tensorflow/contrib/learn/__init__.py | 4 | 1832 | # Copyright 2016 Google Inc. 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 or a... | apache-2.0 |
jayflo/scikit-learn | examples/ensemble/plot_forest_importances.py | 241 | 1761 | """
=========================================
Feature importances with forests of trees
=========================================
This examples shows the use of forests of trees to evaluate the importance of
features on an artificial classification task. The red bars are the feature
importances of the forest, along wi... | bsd-3-clause |
ishanic/scikit-learn | sklearn/mixture/tests/test_gmm.py | 200 | 17427 | import unittest
import copy
import sys
from nose.tools import assert_true
import numpy as np
from numpy.testing import (assert_array_equal, assert_array_almost_equal,
assert_raises)
from scipy import stats
from sklearn import mixture
from sklearn.datasets.samples_generator import make_spd_ma... | bsd-3-clause |
Windy-Ground/scikit-learn | examples/cluster/plot_segmentation_toy.py | 258 | 3336 | """
===========================================
Spectral clustering for image segmentation
===========================================
In this example, an image with connected circles is generated and
spectral clustering is used to separate the circles.
In these settings, the :ref:`spectral_clustering` approach solve... | bsd-3-clause |
imbforge/NGSpipe2go | tools/piRNA/piRNABaseTerminalBases.py | 1 | 10850 | #!/usr/bin/env python
# encoding: utf-8
usage = '''
Takes alignments, corresponding to piRNAs, and counts how often each nucleotide occurs in the boundaries (5' and 3') of the sequence. By default the it counts nucleotide frequency at positions -20 to +20. It also outputs results for sense and antisense piRNAs to a p... | gpl-3.0 |
chris-ch/omarket | python-lab/backtest.py | 1 | 15929 | import argparse
import csv
import logging
import math
import os
from datetime import date
import numpy
import pandas
from statsmodels.formula.api import OLS
from matplotlib import pyplot
from btplatform import PositionAdjuster, process_strategy, BacktestHistory
from meanrevert import MeanReversionStrategy, PortfolioD... | apache-2.0 |
metaml/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/units.py | 70 | 4810 | """
The classes here provide support for using custom classes with
matplotlib, eg those that do not expose the array interface but know
how to converter themselves to arrays. It also supoprts classes with
units and units conversion. Use cases include converters for custom
objects, eg a list of datetime objects, as we... | agpl-3.0 |
RPGOne/scikit-learn | sklearn/covariance/tests/test_robust_covariance.py | 77 | 3825 | # 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 |
Fireblend/scikit-learn | sklearn/neighbors/tests/test_approximate.py | 142 | 18692 | """
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 |
espenhgn/nest-simulator | pynest/examples/brunel_alpha_nest.py | 2 | 13724 | # -*- coding: utf-8 -*-
#
# brunel_alpha_nest.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 Licen... | gpl-2.0 |
coufon/neon-distributed | examples/fast-rcnn/demo.py | 2 | 5520 | #!/usr/bin/env python
# ----------------------------------------------------------------------------
# Copyright 2015 Nervana Systems Inc.
# 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
#
# ... | apache-2.0 |
BlueBrain/NEST | examples/nest/Potjans_2014/spike_analysis.py | 13 | 5601 | # -*- coding: utf-8 -*-
#
# spike_analysis.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,... | gpl-2.0 |
ANNarchy/ANNarchy | examples/multinetwork/MultiNetwork.py | 2 | 2086 | from ANNarchy import *
# Create the whole population
P = Population(geometry=1000, neuron=Izhikevich)
# Create the excitatory population
Exc = P[:800]
re = np.random.random(800)
Exc.noise = 5.0
Exc.a = 0.02
Exc.b = 0.2
Exc.c = -65.0 + 15.0 * re**2
Exc.d = 8.0 - 6.0 * re**2
Exc.v = -65.0
Exc.u = Exc.v * Exc.b
# Creat... | gpl-2.0 |
doodnayr/pilaser | calibrate.py | 1 | 4019 | import numpy as np
from picamera import PiCamera
from picamera.array import PiRGBAnalysis
from sklearn.cluster import DBSCAN
from binascii import unhexlify, hexlify
from scipy.interpolate import griddata
import os
from hipsterplot import plot
scan = DBSCAN(eps=2, min_samples=3, metric='euclidean', algorithm='ball_tree... | mit |
mrshirts/pymbar | pymbar/confidenceintervals.py | 3 | 14155 | ##############################################################################
# pymbar: A Python Library for MBAR
#
# Copyright 2016-2017 University of Colorado Boulder
# Copyright 2010-2017 Memorial Sloan-Kettering Cancer Center
# Portions of this software are Copyright 2010-2016 University of Virginia
#
# Authors: M... | mit |
imito/odin | odin/networks/mixture_density_network.py | 1 | 10035 | from __future__ import absolute_import, division, print_function
import collections
import numpy as np
import tensorflow as tf
from sklearn.mixture import GaussianMixture
from tensorflow.python import keras
from tensorflow.python.framework import tensor_shape
from tensorflow.python.keras.layers import Dense
from tens... | mit |
stylianos-kampakis/scikit-learn | sklearn/metrics/tests/test_regression.py | 272 | 6066 | from __future__ import division, print_function
import numpy as np
from itertools import product
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.... | bsd-3-clause |
wright-group/WrightTools | setup.py | 1 | 2118 | #! /usr/bin/env python3
import os
from setuptools import setup, find_packages
here = os.path.abspath(os.path.dirname(__file__))
def read(fname):
return open(os.path.join(here, fname)).read()
extra_files = {
"WrightTools": [
"datasets",
"datasets/*",
"datasets/*/*",
"datase... | mit |
RPGOne/Skynet | scikit-learn-c604ac39ad0e5b066d964df3e8f31ba7ebda1e0e/examples/svm/plot_svm_scale_c.py | 26 | 5353 | """
==============================================
Scaling the regularization parameter for SVCs
==============================================
The following example illustrates the effect of scaling the
regularization parameter when using :ref:`svm` for
:ref:`classification <svm_classification>`.
For SVC classificati... | bsd-3-clause |
awolfly9/jd_analysis | jd/management/commands/real_time_analysis.py | 1 | 6783 | #-*- coding: utf-8 -*-
import logging
import sys
import matplotlib
import time
matplotlib.use('Agg')
import os
import config
import utils
import redis
import markdown2
from scrapy.utils.log import configure_logging
from django.core.management.base import BaseCommand
from wordcloud import WordCloud
from sqlhelper im... | lgpl-3.0 |
renatopp/liac | liac/plot.py | 1 | 1988 | # =============================================================================
# Federal University of Rio Grande do Sul (UFRGS)
# Connectionist Artificial Intelligence Laboratory (LIAC)
# Renato de Pontes Pereira - rppereira@inf.ufrgs.br
# =============================================================================
... | mit |
arabenjamin/scikit-learn | examples/svm/plot_separating_hyperplane_unbalanced.py | 329 | 1850 | """
=================================================
SVM: Separating hyperplane for unbalanced classes
=================================================
Find the optimal separating hyperplane using an SVC for classes that
are unbalanced.
We first find the separating plane with a plain SVC and then plot
(dashed) the ... | bsd-3-clause |
RachitKansal/scikit-learn | sklearn/kernel_approximation.py | 258 | 17973 | """
The :mod:`sklearn.kernel_approximation` module implements several
approximate kernel feature maps base on Fourier transforms.
"""
# Author: Andreas Mueller <amueller@ais.uni-bonn.de>
#
# License: BSD 3 clause
import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import svd
from .base im... | bsd-3-clause |
JSLBen/KnowledgeTracing | reference_py/tf_RNN.py | 1 | 15676 | # tensorflow version: 1.0.0
import numpy as np
import tensorflow as tf
from numpy.random import permutation as perm
import pandas as pd
class tf_RNN(object):
"""
RNN classifier with LSTM cells with tensorflow
"""
def __init__(self,
num_features,
... | mit |
toobaz/pandas | pandas/core/indexes/api.py | 2 | 8212 | import textwrap
import warnings
from pandas._libs import NaT, lib
import pandas.core.common as com
from pandas.core.indexes.base import (
Index,
_new_Index,
ensure_index,
ensure_index_from_sequences,
)
from pandas.core.indexes.base import InvalidIndexError # noqa:F401
from pandas.core.indexes.categor... | bsd-3-clause |
trondeau/gnuradio-old | gr-filter/examples/synth_filter.py | 58 | 2552 | #!/usr/bin/env python
#
# Copyright 2010,2012,2013 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 ... | gpl-3.0 |
automl/paramsklearn | ParamSklearn/components/classification/adaboost.py | 1 | 3787 | import numpy as np
import sklearn.ensemble
import sklearn.tree
import sklearn.multiclass
from ParamSklearn.implementations.MultilabelClassifier import MultilabelClassifier
from HPOlibConfigSpace.configuration_space import ConfigurationSpace
from HPOlibConfigSpace.hyperparameters import UniformFloatHyperparameter, \
... | bsd-3-clause |
sgraham/nope | chrome/test/nacl_test_injection/buildbot_chrome_nacl_stage.py | 12 | 11594 | #!/usr/bin/python
# Copyright (c) 2012 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Do all the steps required to build and test against nacl."""
import optparse
import os.path
import re
import shutil
import subproc... | bsd-3-clause |
xubenben/scikit-learn | examples/decomposition/plot_pca_vs_lda.py | 182 | 1743 | """
=======================================================
Comparison of LDA and PCA 2D projection of Iris dataset
=======================================================
The Iris dataset represents 3 kind of Iris flowers (Setosa, Versicolour
and Virginica) with 4 attributes: sepal length, sepal width, petal length
a... | bsd-3-clause |
chanceraine/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_qt.py | 69 | 16846 | from __future__ import division
import math
import os
import sys
import matplotlib
from matplotlib import verbose
from matplotlib.cbook import is_string_like, onetrue
from matplotlib.backend_bases import RendererBase, GraphicsContextBase, \
FigureManagerBase, FigureCanvasBase, NavigationToolbar2, cursors
from mat... | agpl-3.0 |
hlin117/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 19 | 4761 | """
===================================
Compare cross decomposition methods
===================================
Simple usage of various cross decomposition algorithms:
- PLSCanonical
- PLSRegression, with multivariate response, a.k.a. PLS2
- PLSRegression, with univariate response, a.k.a. PLS1
- CCA
Given 2 multivari... | bsd-3-clause |
timodonnell/pyopen | test/test_basics.py | 1 | 2353 | from nose.tools import eq_
from . import data_path, run_and_capture
RUN_TESTS_REQUIRING_INTERNET = True
SAMPLE_CSV_URL = "https://raw.githubusercontent.com/timodonnell/pyopen/master/test/data/SampleCSVFile_11kb.csv"
def test_csv():
eq_(
run_and_capture(
"print(f1.shape)",
[data_pa... | apache-2.0 |
murali-munna/scikit-learn | sklearn/ensemble/tests/test_base.py | 284 | 1328 | """
Testing for the base module (sklearn.ensemble.base).
"""
# Authors: Gilles Louppe
# License: BSD 3 clause
from numpy.testing import assert_equal
from nose.tools import assert_true
from sklearn.utils.testing import assert_raise_message
from sklearn.datasets import load_iris
from sklearn.ensemble import BaggingCla... | bsd-3-clause |
ReservoirWebs/GrowChinook | Bioenergetics_dev.py | 1 | 46105 | #!/usr/bin/python
import pylab
import glob
import time
import os
import numpy as np
import sys
from scipy.interpolate import interp1d
from scipy.integrate import trapz
from scipy.optimize import minimize, brute
from csv import DictReader, QUOTE_NONNUMERIC
from collections import defaultdict
from matplotlib import pypl... | gpl-3.0 |
henrykironde/scikit-learn | examples/decomposition/plot_pca_3d.py | 354 | 2432 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Principal components analysis (PCA)
=========================================================
These figures aid in illustrating how a point cloud
can be very flat in one direction--which is where PCA
comes in to ch... | bsd-3-clause |
cactusbin/nyt | matplotlib/examples/user_interfaces/embedding_in_qt4_wtoolbar.py | 6 | 2033 | from __future__ import print_function
import sys
import numpy as np
from matplotlib.figure import Figure
from matplotlib.backend_bases import key_press_handler
from matplotlib.backends.backend_qt4agg import (
FigureCanvasQTAgg as FigureCanvas,
NavigationToolbar2QTAgg as NavigationToolbar)
from PyQt4.QtCore im... | unlicense |
0/pathintmatmult | pathintmatmult/plotting.py | 1 | 1228 | """
Convenience functions for plotting the generated data.
"""
import matplotlib.pyplot as plt
def plot2d(data: '[[X]]', x_range, y_range, out_path, *, x_label=None, y_label=None, colormap='jet', colorbar=True):
"""
Plot the data as a heat map.
The resulting image is saved to out_path.
Parameters:
... | mit |
hainm/scikit-learn | sklearn/tests/test_multiclass.py | 136 | 23649 | 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 |
soulmachine/scikit-learn | examples/linear_model/plot_ols_3d.py | 350 | 2040 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Sparsity Example: Fitting only features 1 and 2
=========================================================
Features 1 and 2 of the diabetes-dataset are fitted and
plotted below. It illustrates that although feature... | bsd-3-clause |
humdings/zipline | tests/calendars/test_nyse_calendar.py | 5 | 9411 | from unittest import TestCase
import pandas as pd
from .test_trading_calendar import ExchangeCalendarTestBase
from zipline.utils.calendars.exchange_calendar_nyse import NYSEExchangeCalendar
class NYSECalendarTestCase(ExchangeCalendarTestBase, TestCase):
answer_key_filename = 'nyse'
calendar_class = NYSEExch... | apache-2.0 |
semanticbits/survey_stats | src/survey_stats/etl/download.py | 1 | 2410 | import os
import io
import pandas as pd
import boto3
from botocore import UNSIGNED
from botocore.client import Config
from boto3.s3.transfer import TransferConfig
from botocore.vendored import requests
import requests_cache
from survey_stats import log
SCRATCH_DIR = 'cache/'
MAX_SOCRATA_FETCH = 2**32
TMP_API_KEY = 'Kn... | bsd-2-clause |
rlowrance/python_lib | applied_data_science/dataframe.py | 1 | 6093 | '''function that operator on pandas DataFrame instances
create_report_categorical(df, ...)
create_report_numeric(df, ...)
replace(df, old_name, new_name, new_value)
Copyright 2017 Roy E. Lowrance
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the L... | apache-2.0 |
mindw/shapely | docs/code/skew.py | 5 | 2513 | from matplotlib import pyplot
from shapely.wkt import loads as load_wkt
from shapely import affinity
from descartes.patch import PolygonPatch
from figures import SIZE, BLUE, GRAY
def add_origin(ax, geom, origin):
x, y = xy = affinity.interpret_origin(geom, origin, 2)
ax.plot(x, y, 'o', color=GRAY, zorder=1)
... | bsd-3-clause |
jmetzen/scikit-learn | sklearn/metrics/cluster/unsupervised.py | 230 | 8281 | """ Unsupervised evaluation metrics. """
# Authors: Robert Layton <robertlayton@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ...utils import check_random_state
from ..pairwise import pairwise_distances
def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random... | bsd-3-clause |
konstantinstadler/pymrio | tests/test_math.py | 1 | 18241 | """ test cases for all mathematical functions """
import os
import sys
import numpy as np
import numpy.testing as npt
import pandas as pd
import pandas.testing as pdt
import pytest
TESTPATH = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(TESTPATH, ".."))
# the function which should be tes... | gpl-3.0 |
schae234/gingivere | tests/raw_data_clf.py | 2 | 3422 | from __future__ import print_function
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.cross_validation import StratifiedKFold
from sklearn.metrics import classification_report
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.decomposition impo... | mit |
belltailjp/scikit-learn | sklearn/metrics/tests/test_pairwise.py | 105 | 22788 | import numpy as np
from numpy import linalg
from scipy.sparse import dok_matrix, csr_matrix, issparse
from scipy.spatial.distance import cosine, cityblock, minkowski, wminkowski
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing impo... | bsd-3-clause |
automl/paramsklearn | ParamSklearn/components/feature_preprocessing/kitchen_sinks.py | 1 | 2564 | import sklearn.kernel_approximation
from HPOlibConfigSpace.configuration_space import ConfigurationSpace
from HPOlibConfigSpace.hyperparameters import UniformFloatHyperparameter, \
UniformIntegerHyperparameter
from ParamSklearn.components.base import ParamSklearnPreprocessingAlgorithm
from ParamSklearn.constants ... | bsd-3-clause |
sangwook236/sangwook-library | python/test/machine_learning/keras/run_simple_training.py | 2 | 28208 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
import sys
sys.path.append('../../../src')
import os, math, shutil, argparse, logging, logging.handlers, time, datetime
import numpy as np
import tensorflow as tf
#import sklearn
#import cv2
#import matplotlib.pyplot as plt
import swl.machine_learning.util as swl_ml_util
... | gpl-2.0 |
frank-tancf/scikit-learn | examples/cluster/plot_face_segmentation.py | 71 | 2839 | """
===================================================
Segmenting the picture of a raccoon face 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... | bsd-3-clause |
cactusbin/nyt | matplotlib/lib/matplotlib/image.py | 4 | 49269 | """
The image module supports basic image loading, rescaling and display
operations.
"""
from __future__ import division, print_function
import os
import warnings
import math
import numpy as np
from numpy import ma
from matplotlib import rcParams
import matplotlib.artist as martist
from matplotlib.artist import allo... | unlicense |
ves-code/plumed2-ves | user-doc/tutorials/others/ves-lugano2017-kinetics/TRAJECTORIES-1700K/cdf-analysis.py | 6 | 1134 | #!/usr/bin/env python
import numpy as np
from scipy.stats import ks_2samp
from scipy.optimize import curve_fit
from statsmodels.distributions.empirical_distribution import ECDF
import matplotlib.pyplot as plt
f=open('fpt.dat','r')
# define theoretical CDF
def func(x,tau):
return 1-np.exp(-x/tau)
x = []
count=0
... | lgpl-3.0 |
mehdidc/scikit-learn | examples/cluster/plot_cluster_comparison.py | 12 | 4718 | """
=========================================================
Comparing different clustering algorithms on toy datasets
=========================================================
This example aims at showing characteristics of different
clustering algorithms on datasets that are "interesting"
but still in 2D. The last ... | bsd-3-clause |
Jimmy-Morzaria/scikit-learn | examples/applications/plot_model_complexity_influence.py | 323 | 6372 | """
==========================
Model Complexity Influence
==========================
Demonstrate how model complexity influences both prediction accuracy and
computational performance.
The dataset is the Boston Housing dataset (resp. 20 Newsgroups) for
regression (resp. classification).
For each class of models we m... | bsd-3-clause |
FofanovLab/VaST | VaST/Pattern.py | 1 | 13973 | import copy
import json
import logging
from functools import partial
from itertools import combinations
import numpy as np
import pandas as pd
from utils import cartesian_product, get_ambiguous_pattern
class Patterns:
def __init__(self):
self._patterns = {}
self._genomes = {}
self._amp_2... | mit |
Transkribus/TranskribusDU | TranskribusDU/tasks/TablePrototypes/DU_ABPTableRG41.py | 1 | 38778 | # -*- coding: utf-8 -*-
"""
DU task for ABP Table: doing jointly row BIESO and horizontal grid lines
block2line edges do not cross another block.
Here we make consistent label when any N grid lines have no block in-between
each other.
In that case, those N grid lines must have consistent... | bsd-3-clause |
sniemi/EuclidVisibleInstrument | analysis/FlatfieldCalibration.py | 1 | 27797 | """
Flat Field Calibration
======================
This simple script can be used to study the number of flat fields required to meet the VIS calibration requirements.
The following requirements related to the flat field calibration has been taken from GDPRD.
R-GDP-CAL-054:
The contribution of the residuals of VIS fl... | bsd-2-clause |
kushalbhola/MyStuff | Practice/PythonApplication/env/Lib/site-packages/numpy/lib/histograms.py | 4 | 39639 | """
Histogram-related functions
"""
from __future__ import division, absolute_import, print_function
import contextlib
import functools
import operator
import warnings
import numpy as np
from numpy.compat.py3k import basestring
from numpy.core import overrides
__all__ = ['histogram', 'histogramdd', 'histogram_bin_ed... | apache-2.0 |
mikebenfield/scikit-learn | sklearn/linear_model/tests/test_passive_aggressive.py | 42 | 10505 | from sklearn.utils.testing import assert_true
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal, assert_array_equal
from sklearn.utils.testing import assert_almost_equal... | bsd-3-clause |
lisa-1010/smart-tutor | code/test_control_problems.py | 1 | 3012 | # implementation based on https://github.com/lisa-1010/transfer_rl/blob/master/code/gym_pipeline.py
import gym
import matplotlib.pyplot as plt
# TODO: import agents
ENV_NAME = 'CartPole-v0'
NUM_TEST_TRIALS = 100
class EnvWrapper(object):
"""
Wraps the Environment class from gym, so we can make environment... | mit |
shoshber/fmriprep | fmriprep/workflows/confounds.py | 2 | 12081 | '''
Workflow for discovering confounds.
Calculates frame displacement, segment regressors, global regressor, dvars, aCompCor, tCompCor
'''
from nipype.interfaces import utility, nilearn, fsl
from nipype.algorithms import confounds
from nipype.pipeline import engine as pe
from niworkflows.interfaces.masks import ACompCo... | bsd-3-clause |
ChanderG/scipy | scipy/stats/_binned_statistic.py | 26 | 17723 | from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from scipy._lib.six import callable
from collections import namedtuple
__all__ = ['binned_statistic',
'binned_statistic_2d',
'binned_statistic_dd']
def binned_statistic(x, values, statistic='me... | bsd-3-clause |
liganega/Gongsu-DataSci | previous/y2017/W11-pandas-intro/GongSu25_Statistics_Sampling_Distribution.py | 2 | 5188 |
# coding: utf-8
# In[1]:
from __future__ import print_function, division
# #### ์๋ฃ ์๋ด: ์ฌ๊ธฐ์ ๋ค๋ฃจ๋ ๋ด์ฉ์ ์๋ ์ฌ์ดํธ์ ๋ด์ฉ์ ์ฐธ๊ณ ํ์ฌ ์์ฑ๋์์.
#
# https://github.com/rouseguy/intro2stats
# # ํ๋ณธ๋ถํฌ์ ์ ๋ขฐ๊ตฌ๊ฐ
# ## ์ฃผ์๋ด์ฉ
#
# ์์ [GongSu22](https://github.com/liganega/Gongsu-DataSci/blob/master/Notes/W10/GongSu22_Statistics_Population_Varia... | gpl-3.0 |
nansencenter/DAPPER | examples/basic_2.py | 1 | 2760 | # ## Illustrate usage of DAPPER to benchmark multiple DA methods.
# #### Imports
# <b>NB:</b> If you're on <mark><b>Gooble Colab</b></mark>,
# then replace `%matplotlib notebook` below by
# `!python -m pip install git+https://github.com/nansencenter/DAPPER.git` .
# Also note that liveplotting does not work on Colab.
... | mit |
alvarofierroclavero/scikit-learn | examples/feature_selection/plot_feature_selection.py | 249 | 2827 | """
===============================
Univariate Feature Selection
===============================
An example showing univariate feature selection.
Noisy (non informative) features are added to the iris data and
univariate feature selection is applied. For each feature, we plot the
p-values for the univariate feature s... | bsd-3-clause |
larsmans/scikit-learn | doc/conf.py | 11 | 8021 | # -*- coding: utf-8 -*-
#
# scikit-learn documentation build configuration file, created by
# sphinx-quickstart on Fri Jan 8 09:13:42 2010.
#
# This file is execfile()d with the current directory set to its containing
# dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
... | bsd-3-clause |
justincassidy/scikit-learn | sklearn/datasets/tests/test_rcv1.py | 322 | 2414 | """Test the rcv1 loader.
Skipped if rcv1 is not already downloaded to data_home.
"""
import errno
import scipy.sparse as sp
import numpy as np
from sklearn.datasets import fetch_rcv1
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing i... | bsd-3-clause |
kylerbrown/bark | bark/tools/labelview.py | 1 | 21160 | import os
import sys
import string
import yaml
import numpy as np
from scipy.signal import spectrogram
import matplotlib.pyplot as plt
import bark
from bark.io.eventops import (OpStack, write_stack, read_stack, Update, Merge,
Split, Delete, New)
import warnings
warnings.filterwarnings('ign... | gpl-2.0 |
jblackburne/scikit-learn | examples/linear_model/plot_iris_logistic.py | 119 | 1679 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic Regression 3-class Classifier
=========================================================
Show below is a logistic-regression classifiers decision boundaries on the
`iris <https://en.wikipedia.org/wiki/Iris_... | bsd-3-clause |
winklerand/pandas | pandas/errors/__init__.py | 6 | 1697 | # flake8: noqa
"""
Expose public exceptions & warnings
"""
from pandas._libs.tslib import OutOfBoundsDatetime
class PerformanceWarning(Warning):
"""
Warning raised when there is a possible
performance impact.
"""
class UnsupportedFunctionCall(ValueError):
"""
Exception raised when attemptin... | bsd-3-clause |
KAPPS-/vincent | examples/stacked_area_examples.py | 11 | 2281 | # -*- coding: utf-8 -*-
"""
Vincent Stacked Area Examples
"""
#Build a Stacked Area Chart from scratch
from vincent import *
import pandas as pd
import pandas.io.data as web
all_data = {}
for ticker in ['AAPL', 'GOOG', 'IBM', 'YHOO', 'MSFT']:
all_data[ticker] = web.get_data_yahoo(ticker, '1/1/2010', '1/1/2013')... | mit |
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