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 |
|---|---|---|---|---|---|
Barmaley-exe/scikit-learn | sklearn/feature_selection/rfe.py | 3 | 15243 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Vincent Michel <vincent.michel@inria.fr>
# Gilles Louppe <g.louppe@gmail.com>
#
# License: BSD 3 clause
"""Recursive feature elimination for feature ranking"""
import numpy as np
from ..utils import check_X_y, safe_sqr
from ..utils.metaes... | bsd-3-clause |
PrashntS/scikit-learn | sklearn/datasets/base.py | 196 | 18554 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import shutil
from os import environ
from os.pa... | bsd-3-clause |
f3r/scikit-learn | sklearn/utils/multiclass.py | 13 | 12964 |
# Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
#
# License: BSD 3 clause
"""
Multi-class / multi-label utility function
==========================================
"""
from __future__ import division
from collections import Sequence
from itertools import chain
from scipy.sparse import issparse
from scipy.sparse.... | bsd-3-clause |
Vvucinic/Wander | venv_2_7/lib/python2.7/site-packages/pandas/io/wb.py | 9 | 12688 | # -*- coding: utf-8 -*-
from __future__ import print_function
from pandas.compat import map, reduce, range, lrange
from pandas.io.common import urlopen
from pandas.io import json
import pandas
import numpy as np
import warnings
warnings.warn("\n"
"The pandas.io.wb module is moved to a separate package ... | artistic-2.0 |
ssaeger/scikit-learn | sklearn/cluster/tests/test_mean_shift.py | 150 | 3651 | """
Testing for mean shift clustering methods
"""
import numpy as np
import warnings
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import asser... | bsd-3-clause |
nvoron23/python-weka-wrapper | python/weka/plot/classifiers.py | 2 | 13248 | # 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 hope that it will be useful,
# bu... | gpl-3.0 |
JohnOrlando/gnuradio-bitshark | gr-utils/src/python/gr_plot_psd.py | 5 | 11977 | #!/usr/bin/env python
#
# Copyright 2007,2008 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 opt... | gpl-3.0 |
cosmoharrigan/pylearn2 | pylearn2/optimization/test_batch_gradient_descent.py | 44 | 6402 | from __future__ import print_function
from pylearn2.optimization.batch_gradient_descent import BatchGradientDescent
import theano.tensor as T
from pylearn2.utils import sharedX
import numpy as np
from theano.compat.six.moves import xrange
from theano import config
from theano.printing import min_informative_str
def t... | bsd-3-clause |
weegreenblobbie/nsound | docs/user_guide/sphinxext/plot_directive.py | 1 | 17849 | """A special directive for including a matplotlib plot.
The source code for the plot may be included in one of two ways:
1. A path to a source file as the argument to the directive::
.. plot:: path/to/plot.py
When a path to a source file is given, the content of the
directive may optionally conta... | gpl-2.0 |
halmd-org/h5md-tools | h5mdtools/_plot/tcf.py | 1 | 6265 | # -*- coding: utf-8 -*-
#
# tcf - time correlation functions
#
# Copyright © 2013 Felix Höfling
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your o... | gpl-3.0 |
henryzord/clustering | src/measures/sswc.py | 1 | 1931 | import pandas as pd
import numpy as np
from scipy.spatial.distance import cdist
__author__ = 'Henry Cagnini'
def get_partition(medoids, dataset):
medoid_index = np.flatnonzero(medoids)
medoids_sample = dataset.loc[medoid_index]
m_dist = cdist(dataset, medoids_sample, metric='euclidean')
closest = ma... | gpl-3.0 |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/api/filled_step.py | 1 | 7707 | """
=========================
Hatch-filled histograms
=========================
This example showcases the hatching capabilities of matplotlib by plotting
various histograms.
"""
import itertools
from collections import OrderedDict
from functools import partial
import numpy as np
import matplotlib.pyplot as plt
impo... | mit |
WarrenWeckesser/scikits-image | doc/ext/notebook_doc.py | 44 | 3042 | __all__ = ['python_to_notebook', 'Notebook']
import json
import copy
import warnings
# Skeleton notebook in JSON format
skeleton_nb = """{
"metadata": {
"name":""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type":... | bsd-3-clause |
macks22/scikit-learn | examples/classification/plot_classification_probability.py | 242 | 2624 | """
===============================
Plot classification probability
===============================
Plot the classification probability for different classifiers. We use a 3
class dataset, and we classify it with a Support Vector classifier, L1
and L2 penalized logistic regression with either a One-Vs-Rest or multinom... | bsd-3-clause |
shyamalschandra/scikit-learn | examples/cluster/plot_mini_batch_kmeans.py | 86 | 4092 | """
====================================================================
Comparison of the K-Means and MiniBatchKMeans clustering algorithms
====================================================================
We want to compare the performance of the MiniBatchKMeans and KMeans:
the MiniBatchKMeans is faster, but give... | bsd-3-clause |
yafeunteun/wikipedia-spam-classifier | revscoring/revscoring/scorer_models/test_statistics/recall_at_fpr.py | 1 | 3635 | import io
from collections import defaultdict
from sklearn.metrics import recall_score
from tabulate import tabulate
from . import util
from .test_statistic import ClassifierStatistic, TestStatistic
class recall_at_fpr(ClassifierStatistic):
"""
Constructs a statistics generator that measures the maximum rec... | mit |
roryyorke/python-control | examples/cruise-control.py | 1 | 17056 | # cruise-control.py - Cruise control example from FBS
# RMM, 16 May 2019
#
# The cruise control system of a car is a common feedback system encountered
# in everyday life. The system attempts to maintain a constant velocity in the
# presence of disturbances primarily caused by changes in the slope of a
# road. The cont... | bsd-3-clause |
kyleabeauchamp/testrepo | src/make_graph.py | 4 | 1173 | import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
pairs = [("openmm", "yank"), ("cmake", "openmm"), ("cuda", "openmm"), ("fftw3f", "openmm"), ("swig", "openmm"), ("mpi4py", "yank"), ("netcdf4", "yank"),
("numpy", "mdtraj"), ("scipy", "mdtraj"), # ("mdtraj", "mixtape"), ("sklearn", "mixtape"),
(... | gpl-2.0 |
pastas/pasta | tests/test_gxg.py | 1 | 4842 | # -*- coding: utf-8 -*-
"""
Author: T. van Steijn, R.A. Collenteur, 2017
"""
import numpy as np
import pandas as pd
import pastas as ps
class TestGXG(object):
def test_ghg(self):
idx = pd.to_datetime(['20160114', '20160115', '20160128', '20160214'])
s = pd.Series([10., 3., 30., 20.], index=idx... | mit |
nmayorov/scikit-learn | sklearn/decomposition/tests/test_sparse_pca.py | 160 | 6028 | # Author: Vlad Niculae
# License: BSD 3 clause
import sys
import numpy as np
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import ass... | bsd-3-clause |
cjayb/mne-python | mne/epochs.py | 1 | 133716 | # -*- coding: utf-8 -*-
"""Tools for working with epoched data."""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Matti Hämäläinen <msh@nmr.mgh.harvard.edu>
# Daniel Strohmeier <daniel.strohmeier@tu-ilmenau.de>
# Denis Engemann <denis.engemann@gmail.com>
# Mainak Jas... | bsd-3-clause |
mavrix93/LightCurvesClassifier | lcc_web/web/interface/lcc_views/visualization.py | 1 | 10603 | import os
import numpy as np
import pandas as pd
from django.conf import settings
from django.shortcuts import render
from lcc.data_manager.package_reader import PackageReader
from lcc.stars_processing.tools.visualization import plotUnsupProbabSpace
from interface.helpers import getFields, load_test_stars
from interf... | mit |
isomerase/mozziesniff | data/experiments/Dickinson_experiments/dick_pickle.py | 2 | 5178 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 2 22:17:13 2015
@author: Richard Decal
"""
from matplotlib import pyplot as plt
import seaborn as sns
#sns.set_palette("muted", 8)
import pickle
fname = './mozzie_histograms.pickle'
with open(fname) as f:
mozzie_hists = pickle.load(f)
def main(plotting = True):
... | mit |
mmoiozo/IROS | sw/airborne/test/ahrs/ahrs_utils.py | 86 | 4923 | #! /usr/bin/env python
# Copyright (C) 2011 Antoine Drouin
#
# This file is part of Paparazzi.
#
# Paparazzi 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, or (at your option)
# any later ... | gpl-2.0 |
potash/scikit-learn | sklearn/exceptions.py | 14 | 4945 | """
The :mod:`sklearn.exceptions` module includes all custom warnings and error
classes used across scikit-learn.
"""
__all__ = ['NotFittedError',
'ChangedBehaviorWarning',
'ConvergenceWarning',
'DataConversionWarning',
'DataDimensionalityWarning',
'EfficiencyWarn... | bsd-3-clause |
mwv/scikit-learn | sklearn/preprocessing/label.py | 137 | 27165 | # 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 |
tdhopper/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 |
vancan1ty/SEAT | DataProcessing.py | 1 | 7008 | # Copyright (C) 2015 Currell Berry, Justin Jackson, and Team 41 Epilepsy Modeling
#
# This file is part of SEAT (Simple EEG Analysis Tool).
#
# SEAT 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 Foundati... | gpl-3.0 |
dsm054/pandas | pandas/core/indexes/api.py | 2 | 8350 | import textwrap
import warnings
from pandas.core.indexes.base import (Index,
_new_Index,
ensure_index,
ensure_index_from_sequences,
InvalidIndexError) # noqa
from pan... | bsd-3-clause |
csherwood-usgs/landlab | setup.py | 1 | 5852 | #! /usr/bin/env python
#from ez_setup import use_setuptools
#use_setuptools()
from setuptools import setup, find_packages, Extension
from setuptools.command.install import install
from setuptools.command.develop import develop
from distutils.extension import Extension
import sys
ext_modules = [
Extension('land... | mit |
wateraccounting/wa | Generator/Sheet4/main.py | 1 | 13145 | # -*- coding: utf-8 -*-
"""
Authors: Tim Hessels
UNESCO-IHE 2017
Contact: t.hessels@unesco-ihe.org
Repository: https://github.com/wateraccounting/wa
Module: Function/Four
"""
# import general python modules
import os
import numpy as np
import pandas as pd
from netCDF4 import Dataset
def Calculate(WA_HOME_fold... | apache-2.0 |
joshbohde/scikit-learn | sklearn/manifold/tests/test_locally_linear.py | 1 | 3177 | import numpy as np
from numpy.testing import assert_almost_equal
from sklearn import neighbors, manifold
from sklearn.utils.fixes import product
eigen_solvers = ['dense', 'arpack']
def assert_lower(a, b, details=None):
message = "%r is not lower than %r" % (a, b)
if details is not None:
message += "... | bsd-3-clause |
raghavrv/scikit-learn | examples/covariance/plot_mahalanobis_distances.py | 33 | 6232 | r"""
================================================================
Robust covariance estimation and Mahalanobis distances relevance
================================================================
An example to show covariance estimation with the Mahalanobis
distances on Gaussian distributed data.
For Gaussian dis... | bsd-3-clause |
blueshiftofdeath/imessage-counter | imessageCounter.py | 1 | 6291 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime, sqlite3, os
from datetime import timedelta
from itertools import groupby
from matplotlib.dates import DayLocator, MonthLocator, WeekdayLocator
from matplotlib.dates import AutoDateFormatter, Date... | mit |
cython-testbed/pandas | pandas/tests/series/test_alter_axes.py | 1 | 11229 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
import pytest
from datetime import datetime
import numpy as np
from pandas import Series, DataFrame, Index, MultiIndex, RangeIndex
from pandas.compat import lrange, range, zip
import pandas.util.testing as tm
class TestSeriesAlterAxes(object):
def test_setind... | bsd-3-clause |
ssaeger/scikit-learn | sklearn/utils/tests/test_multiclass.py | 34 | 13405 |
from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sp... | bsd-3-clause |
eickenberg/scikit-learn | sklearn/ensemble/tests/test_gradient_boosting.py | 1 | 33972 | """
Testing for the gradient boosting module (sklearn.ensemble.gradient_boosting).
"""
import numpy as np
import warnings
from sklearn import datasets
from sklearn.base import clone
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.ensemble.gra... | bsd-3-clause |
ZGainsforth/MultiLaue | BasicProcessing.py | 1 | 7851 | # Created 2016, Zack Gainsforth
import matplotlib
#matplotlib.use('Qt4Agg')
import matplotlib.pyplot as plt
import numpy as np
import h5py
import multiprocessing
import time
def LoadScan(HDF5FileName, readwrite=False):
# Read the HDF file
if readwrite == False:
f = h5py.File(HDF5FileName, 'r') # , swm... | epl-1.0 |
Edu-Glez/Bank_sentiment_analysis | env/lib/python3.6/site-packages/numpy/lib/polynomial.py | 32 | 37972 | """
Functions to operate on polynomials.
"""
from __future__ import division, absolute_import, print_function
__all__ = ['poly', 'roots', 'polyint', 'polyder', 'polyadd',
'polysub', 'polymul', 'polydiv', 'polyval', 'poly1d',
'polyfit', 'RankWarning']
import re
import warnings
import numpy.core.... | apache-2.0 |
UNR-AERIAL/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 |
Dapid/GPy | GPy/models/bayesian_gplvm.py | 8 | 10126 | # Copyright (c) 2012 - 2014 the GPy Austhors (see AUTHORS.txt)
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from .. import kern
from ..core.sparse_gp_mpi import SparseGP_MPI
from ..likelihoods import Gaussian
from ..core.parameterization.variational import NormalPosterior, NormalPrior... | bsd-3-clause |
marcusrehm/serenata-de-amor | research/src/fetch_yelp_info.py | 2 | 5299 | import json
import requests
import re
import os.path
import datetime
from unicodedata import normalize
from decouple import config
import numpy as np
import pandas as pd
from pandas.io.json import json_normalize
"""
Get your API access token
1. Create an Yelp account.
2. Create an app (https://www.yelp.com/develope... | mit |
ManuSchmi88/landlab | setup.py | 1 | 5818 | #! /usr/bin/env python
#from ez_setup import use_setuptools
#use_setuptools()
from setuptools import setup, find_packages, Extension
from setuptools.command.install import install
from setuptools.command.develop import develop
from distutils.extension import Extension
import sys
ext_modules = [
Extension('land... | mit |
alvarofierroclavero/scikit-learn | sklearn/semi_supervised/label_propagation.py | 128 | 15312 | # coding=utf8
"""
Label propagation in the context of this module refers to a set of
semisupervised classification algorithms. In the high level, these algorithms
work by forming a fully-connected graph between all points given and solving
for the steady-state distribution of labels at each point.
These algorithms per... | bsd-3-clause |
faner-father/tushare | tushare/stock/classifying.py | 11 | 8914 | # -*- coding:utf-8 -*-
"""
获取股票分类数据接口
Created on 2015/02/01
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
import pandas as pd
from tushare.stock import cons as ct
from tushare.stock import ref_vars as rv
import json
import re
from pandas.util.testing import _network_error_classes
... | bsd-3-clause |
tkoziara/parmec | tests/spring_contact_moving_plane.py | 1 | 1441 | # PARMEC test --> SPRING contact moving plane test
matnum = MATERIAL (1E3, 1E9, 0.25)
nodes0 = [-0.5, -0.5, -0.2,
1.5, -0.5, -0.2,
1.5, 1.5, -0.2,
-0.5, 1.5, -0.2,
-0.5, -0.5, 0,
1.5, -0.5, 0,
1.5, 1.5, 0,
-0.5, 1.5, 0]
nodes1 = [0, 0, 1,
1, 0, 1,
1, 1, 1,
0, 1, 1,
0, 0... | mit |
meduz/scikit-learn | sklearn/preprocessing/tests/test_data.py | 30 | 61609 |
# Authors:
#
# Giorgio Patrini
#
# License: BSD 3 clause
import warnings
import numpy as np
import numpy.linalg as la
from scipy import sparse
from distutils.version import LooseVersion
from sklearn.utils import gen_batches
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing im... | bsd-3-clause |
antkillerfarm/antkillerfarm_crazy | python/ml/keras/hello_gan1.py | 1 | 8363 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import os
import matplotlib.pyplot as plt
import keras.backend as K
from keras.datasets import mnist
from keras.layers import *
from keras.models import *
from keras.optimizers import *
from keras.initializers import *
from keras.utils.generic_utils import Progbar
GPU = "0"... | gpl-3.0 |
achim1/ctplot | setup.py | 2 | 2879 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Have a look at https://pythonhosted.org/setuptools
# http://stackoverflow.com/questions/7522250/how-to-include-package-data-with-setuptools-distribute
# http://stackoverflow.com/questions/1231688/how-do-i-remove-packages-installed-with-pythons-easy-install
# http://stack... | gpl-3.0 |
zorroblue/scikit-learn | sklearn/cluster/tests/test_hierarchical.py | 17 | 21562 | """
Several basic tests for hierarchical clustering procedures
"""
# Authors: Vincent Michel, 2010, Gael Varoquaux 2012,
# Matteo Visconti di Oleggio Castello 2014
# License: BSD 3 clause
from tempfile import mkdtemp
import shutil
from functools import partial
import numpy as np
from scipy import sparse
from... | bsd-3-clause |
equialgo/scikit-learn | sklearn/metrics/classification.py | 4 | 71965 | """Metrics to assess performance on classification task given class prediction
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramf... | bsd-3-clause |
wazeerzulfikar/scikit-learn | examples/ensemble/plot_gradient_boosting_regularization.py | 355 | 2843 | """
================================
Gradient Boosting regularization
================================
Illustration of the effect of different regularization strategies
for Gradient Boosting. The example is taken from Hastie et al 2009.
The loss function used is binomial deviance. Regularization via
shrinkage (``lear... | bsd-3-clause |
gromitsun/sim-xrf-py | others/scatt_bg/scatt_bg3_wpw.py | 1 | 4121 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from matplotlib.colors import LogNorm
RECALC = False
if RECALC:
from scipy.integrate import dblquad
import sys, os
sys.path.append(o... | mit |
jbloomlab/dms_tools2 | dms_tools2/utils.py | 1 | 59560 | """
===================
utils
===================
Miscellaneous utilities for ``dms_tools2``.
"""
import os
import math
import sys
import time
import platform
import importlib
import logging
import tempfile
import textwrap
import itertools
import collections
import random
import re
import pysam
import numpy
import ... | gpl-3.0 |
oesteban/mriqc | mriqc/classifier/sklearn/preprocessing.py | 1 | 22145 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
# @Author: oesteban
# @Date: 2017-06-08 17:11:58
"""
Extensions to the sklearn's default data preprocessing filters
"""
import numpy as np
import pandas as p... | bsd-3-clause |
SpencerDodd/CrossBLAST | hist_results.py | 1 | 2749 | import matplotlib.pyplot as plt
import numpy as np
import csv
import sys
class HistogramParser:
def __init__(self, other, superfamily, family, subfamily, genus, species, subspecies):
self.other = other
self.superfamily = superfamily
self.family = family
self.subfamily = subfamily
self.genus = genus
self... | mit |
josemao/nilmtk | nilmtk/results.py | 6 | 7403 | import abc
import pandas as pd
import copy
from .timeframe import TimeFrame
from nilmtk.utils import get_tz, tz_localize_naive
class Results(object):
"""Stats results from each node need to be assigned to a specific
class so we know how to combine results from multiple chunks. For
example, Energy can be s... | apache-2.0 |
quasars100/Resonance_testing_scripts | alice/multiplesim.py | 1 | 6288 | import rebound
import numpy as np
import reboundxf
import matplotlib.pyplot as plt
from pylab import *
from rebound.interruptible_pool import InterruptiblePool
def anglerange(val):
while val < 0:
val += 2*np.pi
while val > 2*np.pi:
val -= 2*np.pi
return val*180/np.pi
def calc(args):
taue=a... | gpl-3.0 |
sssundar/Drone | motor/quadratic_drag.py | 1 | 2709 | # Solves for the dynamics if a linear torque, quadratic drag model of our DC brushed motor.
# See notes from 8/4/2018-8/12/2018. We're trying to find the relations between Bd, Bm, Gamma, nd Jprop
# that give us linear relations between thrust and the duty cycle, which was measured,
# and which match a mechanical timesc... | gpl-3.0 |
hagabbar/pycbc_copy | pycbc/results/legacy_grb.py | 1 | 22775 | #!/usr/bin/env python
# Copyright (C) 2015 Andrew R. Williamson
#
# 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.
#
# T... | gpl-3.0 |
ebolyen/q2d2 | q2d2/__init__.py | 2 | 16324 | #!/usr/bin/env python
__version__ = "0.0.0-dev"
import random
import io
import itertools
from collections import defaultdict, namedtuple
import hashlib
import os
import shutil
import glob
import math
from functools import partial
import numpy as np
import pandas as pd
from IPython.html import widgets
from IPython.h... | bsd-3-clause |
wzbozon/statsmodels | statsmodels/stats/tests/test_diagnostic.py | 21 | 40146 | # -*- coding: utf-8 -*-
"""Tests for Regression Diagnostics and Specification Tests
Created on Thu Feb 09 13:19:47 2012
Author: Josef Perktold
License: BSD-3
currently all tests are against R
"""
#import warnings
#warnings.simplefilter("default")
# ResourceWarning doesn't exist in python 2
#warnings.simplefilter("i... | bsd-3-clause |
FluVigilanciaBR/seasonality | methods/data_filter/delay_table_4Weeks.py | 1 | 5515 | __author__ = 'Marcelo Ferreira da Costa Gomes'
import pandas as pd
import numpy as np
import episem
import sys
import datetime
import calendar
import argparse
from argparse import RawDescriptionHelpFormatter
def readtable(fname):
tgt_cols = ['SG_UF_NOT', 'DT_SIN_PRI_epiyear', 'DT_SIN_PRI_epiweek', 'SinPri2Digita... | gpl-3.0 |
sarahgrogan/scikit-learn | examples/manifold/plot_mds.py | 261 | 2616 | """
=========================
Multi-dimensional scaling
=========================
An illustration of the metric and non-metric MDS on generated noisy data.
The reconstructed points using the metric MDS and non metric MDS are slightly
shifted to avoid overlapping.
"""
# Author: Nelle Varoquaux <nelle.varoquaux@gmail.... | bsd-3-clause |
embeddedarm/android_external_chromium_org | chrome/browser/nacl_host/test/gdb_rsp.py | 99 | 2431 | # 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.
# This file is based on gdb_rsp.py file from NaCl repository.
import re
import socket
import time
def RspChecksum(data):
checksum = 0
for char in ... | bsd-3-clause |
endolith/scipy | scipy/integrate/odepack.py | 21 | 10740 | # Author: Travis Oliphant
__all__ = ['odeint']
import numpy as np
from . import _odepack
from copy import copy
import warnings
class ODEintWarning(Warning):
pass
_msgs = {2: "Integration successful.",
1: "Nothing was done; the integration time was 0.",
-1: "Excess work done on this call (per... | bsd-3-clause |
alvarofierroclavero/scikit-learn | examples/bicluster/bicluster_newsgroups.py | 162 | 7103 | """
================================================================
Biclustering documents with the Spectral Co-clustering algorithm
================================================================
This example demonstrates the Spectral Co-clustering algorithm on the
twenty newsgroups dataset. The 'comp.os.ms-windows... | bsd-3-clause |
grlee77/pywt | demo/plot_wavelets.py | 8 | 2656 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Plot scaling and wavelet functions for db, sym, coif, bior and rbio families
import itertools
import matplotlib.pyplot as plt
import pywt
plot_data = [('db', (4, 3)),
('sym', (4, 3)),
('coif', (3, 2))]
for family, (rows, cols) in plot_dat... | mit |
MMKrell/pyspace | pySPACE/missions/operations/comp_analysis.py | 4 | 36892 | """ Creates various comparing plots on several levels for a :class:`~pySPACE.resources.dataset_defs.performance_result.PerformanceResultSummary`
This module contains implementations of an operation and
a process for analyzing data contained in a csv file (typically the result
of a Weka Classification Operation).
A *C... | gpl-3.0 |
wrshoemaker/ffpopsim | tests/python_lowd.py | 2 | 1442 | # vim: fdm=indent
'''
author: Fabio Zanini
date: 14/05/12
content: Test script for the python bindings to the low-dimensional
simulation
'''
# Import module
import sys
sys.path.insert(0, '../pkg/python')
import numpy as np
import matplotlib.pyplot as plt
import FFPopSim as h
# Construct class... | gpl-3.0 |
ChanderG/scikit-learn | 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 |
dsquareindia/scikit-learn | sklearn/feature_extraction/tests/test_image.py | 38 | 11165 | # Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
import numpy as np
import scipy as sp
from scipy import ndimage
from numpy.testing import assert_raises
from sklearn.feature_extraction.image import (
img_to_gra... | bsd-3-clause |
kgullikson88/General | Expectations.py | 1 | 5027 | import pandas as pd
import numpy as np
import pysynphot
from scipy.optimize import leastsq
from astropy import units as u
import SpectralTypeRelations
import Mamajek_Table
MS = SpectralTypeRelations.MainSequence()
MT = Mamajek_Table.MamajekTable()
MT.mam_df['radius'] = 10 ** (0.5 * MT.mam_df.logL - 2.0 * MT.mam_df.l... | gpl-3.0 |
jeffmkw/DAT210x-Lab | Module5/assignment6.py | 1 | 9272 | import random, math
import pandas as pd
import numpy as np
import scipy.io
import matplotlib
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
# If you'd like to try this lab with PCA instead of Isomap for dimensionality
# reduction technique:
Test_PCA = False
matplotlib.style.use('ggplot') # ... | mit |
anirudhjayaraman/scikit-learn | examples/neural_networks/plot_rbm_logistic_classification.py | 258 | 4609 | """
==============================================================
Restricted Boltzmann Machine features for digit classification
==============================================================
For greyscale image data where pixel values can be interpreted as degrees of
blackness on a white background, like handwritten... | bsd-3-clause |
jakobworldpeace/scikit-learn | examples/svm/plot_custom_kernel.py | 93 | 1562 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
wazeerzulfikar/scikit-learn | sklearn/tests/test_metaestimators.py | 30 | 5040 | """Common tests for metaestimators"""
import functools
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.externals.six import iterkeys
from sklearn.datasets import make_classification
from sklearn.utils.testing import assert_true, assert_false, assert_raises
from sklearn.utils.validation import... | bsd-3-clause |
StongeEtienne/dipy | setup_helpers.py | 11 | 14073 | ''' Distutils / setuptools helpers
'''
import os
import sys
from os.path import join as pjoin, split as psplit, splitext, dirname, exists
import tempfile
import shutil
from distutils.version import LooseVersion
from distutils.command.install_scripts import install_scripts
from distutils.errors import CompileError, Li... | bsd-3-clause |
moutai/scikit-learn | sklearn/feature_extraction/tests/test_image.py | 25 | 11187 | # Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
import numpy as np
import scipy as sp
from scipy import ndimage
from nose.tools import assert_equal, assert_true
from numpy.testing import assert_raises
from sklearn... | bsd-3-clause |
eike-welk/clair | src/clairweb/libclair/test/test_prices.py | 1 | 24394 | # -*- coding: utf-8 -*-
###############################################################################
# Clair - Project to discover prices on e-commerce sites. #
# #
# Copyright (C) 2013 by Eike Welk ... | gpl-3.0 |
ales-erjavec/scipy | scipy/interpolate/interpolate.py | 25 | 80287 | """ Classes for interpolating values.
"""
from __future__ import division, print_function, absolute_import
__all__ = ['interp1d', 'interp2d', 'spline', 'spleval', 'splmake', 'spltopp',
'ppform', 'lagrange', 'PPoly', 'BPoly', 'RegularGridInterpolator',
'interpn']
import itertools
from numpy impo... | bsd-3-clause |
geopandas/geopandas | geopandas/tools/clip.py | 2 | 8098 | """
geopandas.clip
==============
A module to clip vector data using GeoPandas.
"""
import warnings
import numpy as np
import pandas as pd
from shapely.geometry import Polygon, MultiPolygon
from geopandas import GeoDataFrame, GeoSeries
from geopandas.array import _check_crs, _crs_mismatch_warn
def _clip_points(g... | bsd-3-clause |
DrigerG/IIITB-ML | project/TexCounter/tex_counter.py | 1 | 9127 | #!/usr/bin/env python
"""TexCounter.py: Counts the number of garments in a shelf"""
import cv2
import sys
import logging
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.cluster import MeanShift, estimate_bandwidth
__author__ = "Pradeep Kumar A.V."
logging.basicConfig(filena... | apache-2.0 |
robotenique/intermediateProgramming | MAC0209/paretoLaw.py | 1 | 2832 | '''
Problem 1.1 of the book 'Introduction to Computer Simulation Methods',
chapter one: Distribution of Money
'''
__author__ = "Juliano Garcia de Oliveira"
import random as rnd
import matplotlib.pyplot as plt
import numpy as np
def createAgents(n, m0):
# Create a dictionary with n pairs of 'agent : m0', and r... | unlicense |
gamahead/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/__init__.py | 72 | 2225 |
import matplotlib
import inspect
import warnings
# ipython relies on interactive_bk being defined here
from matplotlib.rcsetup import interactive_bk
__all__ = ['backend','show','draw_if_interactive',
'new_figure_manager', 'backend_version']
backend = matplotlib.get_backend() # validates, to match all_bac... | gpl-3.0 |
sonnyhu/scikit-learn | sklearn/naive_bayes.py | 4 | 30634 | # -*- coding: utf-8 -*-
"""
The :mod:`sklearn.naive_bayes` module implements Naive Bayes algorithms. These
are supervised learning methods based on applying Bayes' theorem with strong
(naive) feature independence assumptions.
"""
# Author: Vincent Michel <vincent.michel@inria.fr>
# Minor fixes by Fabian Pedre... | bsd-3-clause |
davidgbe/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 |
bubae/gazeAssistRecognize | test.py | 1 | 2664 | import numpy as np
from sklearn import svm
from sklearn import datasets
from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import LinearSVC
# from sklearn.pipeline import Pipeline
# from sklearn.feature_extraction.text import CountVectorizer
# from sklearn.svm import LinearSVC
# from sklearn.feature_ex... | mit |
puruckertom/ubertool | ubertool/agdrift/tests/test_agdrift_integration.py | 1 | 10694 | from __future__ import division #brings in Python 3.0 mixed type calculation rules
import datetime
import inspect
import numpy.testing as npt
import os.path
import pandas as pd
import pkgutil
import sys
from tabulate import tabulate
import unittest
try:
from StringIO import StringIO #BitesIO?
except ImportError:
... | unlicense |
jeffery-do/Vizdoombot | doom/lib/python3.5/site-packages/matplotlib/backend_bases.py | 4 | 110334 | """
Abstract base classes define the primitives that renderers and
graphics contexts must implement to serve as a matplotlib backend
:class:`RendererBase`
An abstract base class to handle drawing/rendering operations.
:class:`FigureCanvasBase`
The abstraction layer that separates the
:class:`matplotlib.fi... | mit |
dpshelio/sunpy | sunpy/instr/lyra.py | 2 | 31288 | import csv
import copy
import urllib
import os.path
import sqlite3
import datetime
from warnings import warn
import numpy as np
import pandas
from astropy.io import fits
from astropy.time import Time
from sunpy.time import parse_time
from sunpy.util.net import check_download_file
from sunpy.util.config import get_an... | bsd-2-clause |
michalsenkyr/spark | examples/src/main/python/sql/arrow.py | 16 | 5034 | #
# 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 |
hugobowne/scikit-learn | examples/ensemble/plot_gradient_boosting_regression.py | 87 | 2510 | """
============================
Gradient Boosting regression
============================
Demonstrate Gradient Boosting on the Boston housing dataset.
This example fits a Gradient Boosting model with least squares loss and
500 regression trees of depth 4.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prett... | bsd-3-clause |
tobybreckon/bee-wi | examples/pathFollower.py | 1 | 17217 | # Copyright (c) 2014
# Joey Green, School of Engineering and Computer Sciences, Durham University, UK
# All versions of this software (both binary and source) must retain
# and display this copyright notice.
# License : GPL - http://www.gnu.org/copyleft/gpl.html
# ******************** PATH FOLLOWER MODULE **... | gpl-2.0 |
PAIR-code/recommendation-rudders | hyperbolic-rs/rudders/graph/analysis/plot_hyperbolicity.py | 1 | 1050 | import argparse
import logging
import numpy as np
import matplotlib.pyplot as plt
from utils import annotate_vline, remove_extensions
parser = argparse.ArgumentParser(description='Plot delta-hyperbolicities')
parser.add_argument(
'--input', type=str, required=True, help='The hyperbolicities file.')
args = pa... | apache-2.0 |
fengzhyuan/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 |
BMP-TECH/mavlink | pymavlink/tools/mavgraph.py | 8 | 9809 | #!/usr/bin/env python
'''
graph a MAVLink log file
Andrew Tridgell August 2011
'''
import sys, struct, time, os, datetime
import math, re
import matplotlib
from math import *
from pymavlink.mavextra import *
# cope with rename of raw_input in python3
try:
input = raw_input
except NameError:
pass
colourmap =... | lgpl-3.0 |
abhishekgahlot/scikit-learn | sklearn/ensemble/tests/test_base.py | 28 | 1334 | """
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 |
cimat/data-visualization-patterns | display-patterns/Discrete Quantities/Pruebas/A36Span_Chart_Pyqtgraph.py | 1 | 1080 | from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph as pg
from datos import data
import pandas as pd
d=data('mtcars')
subset1, subset2, subset3= d[d.cyl==4], d[d.cyl==6], d[d.cyl==8]
datos=pd.DataFrame ({'Max': [max(subset1.mpg), max(subset2.mpg), max(subset3.mpg)],
'Min': [min(subset1.mpg), min(subset2.mpg... | cc0-1.0 |
fireball-QMD/progs | pyfb/geometry/dinamic.py | 1 | 5380 | from pyfb.geometry.step import step
from pyfb.geometry.atom import atom
import pandas as pd
import numpy as np
class dinamic:
def __init__(self):
self.step=[]
#lee las cargas de cada atomo despues de las posiciones:
# x y z Qtot qs qp qd .....
self.out=[]
def print_total_steps(self):
print(l... | gpl-3.0 |
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