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 |
|---|---|---|---|---|---|
wolfram74/numerical_methods_iserles_notes | venv/lib/python2.7/site-packages/IPython/qt/console/qtconsoleapp.py | 4 | 13971 | """ A minimal application using the Qt console-style IPython frontend.
This is not a complete console app, as subprocess will not be able to receive
input, there is no real readline support, among other limitations.
"""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD Licens... | mit |
schets/scikit-learn | examples/model_selection/plot_precision_recall.py | 249 | 6150 | """
================
Precision-Recall
================
Example of Precision-Recall metric to evaluate classifier output quality.
In information retrieval, precision is a measure of result relevancy, while
recall is a measure of how many truly relevant results are returned. A high
area under the curve represents both ... | bsd-3-clause |
rseubert/scikit-learn | examples/linear_model/plot_sgd_separating_hyperplane.py | 260 | 1219 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print(__doc__)
import numpy as n... | bsd-3-clause |
TomAugspurger/pandas | scripts/validate_unwanted_patterns.py | 1 | 11283 | #!/usr/bin/env python3
"""
Unwanted patterns test cases.
The reason this file exist despite the fact we already have
`ci/code_checks.sh`,
(see https://github.com/pandas-dev/pandas/blob/master/ci/code_checks.sh)
is that some of the test cases are more complex/imposible to validate via regex.
So this file is somewhat a... | bsd-3-clause |
jplourenco/bokeh | bokeh/_legacy_charts/builder/tests/test_histogram_builder.py | 6 | 4247 | """ This is the Bokeh charts testing interface.
"""
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with thi... | bsd-3-clause |
PatrickChrist/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 234 | 12267 | # Authors: Lars Buitinck
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from array import array
from collections import Mapping
from operator import itemgetter
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..ext... | bsd-3-clause |
iandriver/RNA-sequence-tools | RNA_Seq_analysis/cluster_1.py | 2 | 39669 | import pickle as pickle
import numpy as np
import pandas as pd
import os
from subprocess import call
import matplotlib
matplotlib.use('QT5Agg')
import matplotlib.pyplot as plt
from matplotlib.ticker import LinearLocator
import scipy
import json
from sklearn.decomposition import PCA as skPCA
from scipy.spatial.distance ... | mit |
roryyorke/python-control | examples/type2_type3.py | 3 | 1677 | # type2_type3.py - demonstration for type2 versus type3 control comparing
# tracking and disturbance rejection for two proposed controllers
# Gunnar Ristroph, 15 January 2010
import os
import matplotlib.pyplot as plt # Grab MATLAB plotting functions
from control.matlab import * # MATLAB-like functions
from scip... | bsd-3-clause |
apache/beam | sdks/python/apache_beam/dataframe/expressions_test.py | 6 | 4866 | #
# 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 |
JohanComparat/nbody-npt-functions | bin/bin_SMHMr/plot_ObscurationLaw.py | 1 | 1071 | import numpy as n
from scipy.stats import norm
from scipy.integrate import quad
from scipy.interpolate import interp1d
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as p
import glob
import astropy.io.fits as fits
import os
import time
import numpy as n
import sys
data=n.loadtxt("/data17s/darksim/so... | cc0-1.0 |
HeraclesHX/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 110 | 34127 | from __future__ import unicode_literals
import warnings
from sklearn.feature_extraction.text import strip_tags
from sklearn.feature_extraction.text import strip_accents_unicode
from sklearn.feature_extraction.text import strip_accents_ascii
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.fe... | bsd-3-clause |
arlewis/arl_galbase | extract_stamp_good.py | 2 | 24946 | import astropy.io.fits as pyfits
from astropy.io import ascii
from astropy.table import Table, Column
import astropy.wcs as pywcs
import os
import numpy as np
import montage_wrapper as montage
import shutil
import sys
import glob
import time
from matplotlib.path import Path
from scipy.ndimage import zoom
from pdb impor... | mit |
fdft/ml | ch06/utils.py | 22 | 6937 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
import os
import sys
import collections
import csv
import json
from matplotlib import pylab
import num... | mit |
timpalpant/KaggleTSTextClassification | scripts/practice/predict.3.py | 1 | 1789 | #!/usr/bin/env python
'''
Make predictions for the test data
3. Use naive Bayes, on just the boolean features,
with a separate classifier for each label.
'''
import argparse
from common import *
from scipy.stats import itemfreq
from sklearn.naive_bayes import GaussianNB
def prepare_features(data):
return dat... | gpl-3.0 |
nsdf/nsdf | graphviz/figure1_twocells.py | 1 | 30501 | # This script was written by Chaitanya Chintaluri c.chinaluri@nencki.gov.pl
# This software is available under GNU GPL3 License.
# Uses pygraphviz to illustrate the inner structure of NSDF file format
# This is to use in the NSDF paper and to generate machine readable file structure
# for the convenience of the user.
... | gpl-3.0 |
gwpy/gwpy.github.io | docs/latest/plotter/colors-1.py | 7 | 1123 | from __future__ import division
import numpy
from matplotlib import (pyplot, rcParams)
from matplotlib.colors import to_hex
from gwpy.plotter import colors
rcParams.update({
'text.usetex': False,
'font.size': 15
})
th = numpy.linspace(0, 2*numpy.pi, 512)
names = [
'gwpy:geo600',
'gwpy:kagra',
'... | gpl-3.0 |
EvoML/EvoML | evoml/subsampling/test_auto_segmentEG_FEMPO.py | 2 | 1315 | import pandas as pd
from sklearn.datasets import load_boston
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.cross_validation import train_test_split
from sklearn.metrics import mean_squared_error
from .auto_segment_FEMPO import BasicSegmenter_FEMPO
def d... | gpl-3.0 |
cyberphox/MissionPlanner | Lib/site-packages/numpy/lib/recfunctions.py | 58 | 34495 | """
Collection of utilities to manipulate structured arrays.
Most of these functions were initially implemented by John Hunter for matplotlib.
They have been rewritten and extended for convenience.
"""
import sys
import itertools
import numpy as np
import numpy.ma as ma
from numpy import ndarray, recarray
from nump... | gpl-3.0 |
KarchinLab/2020plus | src/utils/python/p_value.py | 1 | 6214 | import numpy as np
import pandas as pd
import bisect
# genes to be removed from MLFC calc
mlfc_remove_genes = set([
'PLCG1', 'CRLF2', 'SMARCD1', 'SH2B3', 'STK11', 'MEN1', 'IKBKB', 'AKT1', 'B2M', 'MLH1',
'USP28', 'TSHR', 'FGFR4', 'GPS2', 'CDC73', 'PIK3CA', 'MAP3K1', 'CACNA1D', 'FGFR3', 'TSC1',
'ZC3H13', 'CB... | apache-2.0 |
hongliuuuu/Results_Dis | ndR4.py | 1 | 15791 | from sklearn.kernel_approximation import (RBFSampler,Nystroem)
from sklearn.ensemble import RandomForestClassifier
import pandas
import numpy as np
import random
from sklearn.svm import SVC
from sklearn.metrics.pairwise import rbf_kernel,laplacian_kernel,chi2_kernel,linear_kernel,polynomial_kernel,cosine_similarity
fro... | apache-2.0 |
vitordouzi/sigtrec_eval | sigtrec_eval_old.py | 1 | 9270 | # -*- coding: utf-8 -*-
"""
Created on Mon Out 1 10:07:00 2017
@author: Vítor Mangaravite
"""
import sys
import os
import subprocess
import argparse
import numpy as np
import pandas as pd
import multiprocessing
from sklearn.model_selection import KFold
from scipy.stats.mstats import ttest_rel
from scipy.stats import t... | mit |
aflaxman/scikit-learn | sklearn/feature_selection/tests/test_chi2.py | 49 | 3080 | """
Tests for chi2, currently the only feature selection function designed
specifically to work with sparse matrices.
"""
import warnings
import numpy as np
from scipy.sparse import coo_matrix, csr_matrix
import scipy.stats
from sklearn.feature_selection import SelectKBest, chi2
from sklearn.feature_selection.univar... | bsd-3-clause |
jhmatthews/cobra | source/plot_emissiv.py | 1 | 2033 | #! /Library/Frameworks/Python.framework/Versions/2.7/Resources/Python.app/Contents/MacOS/Python
'''
University of Southampton -- JM -- 30 September 2013
plot_emissiv.py
Synopsis:
Plot macro atom level emissivities and other information from
diag file
Usage:
Arguments:
'''
import matplotlib.pyplot ... | gpl-2.0 |
gsmaxwell/phase_offset_rx | gnuradio-core/src/examples/volk_benchmark/volk_plot.py | 78 | 6117 | #!/usr/bin/env python
import sys, math
import argparse
from volk_test_funcs import *
try:
import matplotlib
import matplotlib.pyplot as plt
except ImportError:
sys.stderr.write("Could not import Matplotlib (http://matplotlib.sourceforge.net/)\n")
sys.exit(1)
def main():
desc='Plot Volk performanc... | gpl-3.0 |
Winand/pandas | pandas/_version.py | 5 | 15765 | # This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains th... | bsd-3-clause |
buguen/pylayers | pylayers/signal/device.py | 2 | 6088 | #!/usr/bin/python
# -*- coding: utf-8 -*-
#
"""
.. currentmodule:: pylayers.signal.device
This module describes the radio devices to be used for electromagentic simulations
Device Class
============
.. autosummary::
:toctree: generated/
Device.__init__
"""
import doctest
import numpy as np
import matplot... | lgpl-3.0 |
jasonabele/gnuradio | gr-msdd6000/src/python-examples/ofdm/gr_plot_ofdm.py | 8 | 10704 | #!/usr/bin/env python
#
# Copyright 2007 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 option)
... | gpl-3.0 |
bjodah/chemreac | examples/steady_state.py | 2 | 4970 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
from math import log
import argh
import numpy as np
from chemreac import ReactionDiffusion
from chemreac.integrate import run
from chemreac.util.plotting import plot_solver_linear_error
def efield_cb(x, ... | bsd-2-clause |
zaxtax/scikit-learn | examples/bicluster/plot_spectral_coclustering.py | 276 | 1736 | """
==============================================
A demo of the Spectral Co-Clustering algorithm
==============================================
This example demonstrates how to generate a dataset and bicluster it
using the the Spectral Co-Clustering algorithm.
The dataset is generated using the ``make_biclusters`` f... | bsd-3-clause |
walterst/qiime | scripts/make_distance_boxplots.py | 15 | 13899 | #!/usr/bin/env python
from __future__ import division
__author__ = "Jai Ram Rideout"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Jai Ram Rideout"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Jai Ram Rideout"
__email__ = "jai.rideout@gmail.com"
from os.path import join
from ... | gpl-2.0 |
bobwalker99/Pydev | plugins/org.python.pydev/pysrc/pydevd.py | 1 | 61172 | '''
Entry point module (keep at root):
This module starts the debugger.
'''
from __future__ import nested_scopes # Jython 2.1 support
import atexit
import os
import sys
import traceback
from _pydevd_bundle.pydevd_constants import IS_JYTH_LESS25, IS_PY3K, IS_PY34_OLDER, get_thread_id, dict_keys, dict_pop, dict_conta... | epl-1.0 |
isomerase/mozziesniff | lorentz_animation.py | 2 | 2375 | import numpy as np
from scipy import integrate
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from matplotlib import animation
N_trajectories = 20
def lorentz_deriv((x, y, z), t0, sigma=10., beta=8./3, rho=28.0):
"""Compute the time-derivative o... | mit |
btabibian/scikit-learn | examples/ensemble/plot_forest_iris.py | 18 | 6190 | """
====================================================================
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 |
DSLituiev/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 34 | 50761 | # Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com> (main author)
# Mathieu Blondel (partial_fit support)
#
# License: BSD 3 clause
"""Classification and regression using Stochastic Gradient Descent (SGD)."""
import numpy as np
from abc import ABCMeta, abstractmethod
from ..externals.joblib import ... | bsd-3-clause |
Midnighter/pyorganism | scripts/control_analysis.py | 1 | 32278 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (division, print_function)
import sys
import os
import logging
import argparse
import json
import codecs
import shelve
import pickle
import numpy as np
import pyorganism as pyorg
import pyorganism.regulation as pyreg
import pyorganism.io.microar... | bsd-3-clause |
jasper-chen/ThinkStats2 | code/thinkstats2.py | 68 | 68825 | """This file contains code for use with "Think Stats" and
"Think Bayes", both by Allen B. Downey, available from greenteapress.com
Copyright 2014 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function, division
"""This file contains class definitions for:
H... | gpl-3.0 |
JavierAntonioGonzalezTrejo/SCAZAC | scripts/temporaryInsertDataScazac.py | 1 | 2293 | # Register of change
# Modification 20170721: use of the make_aware function to make a proper treatment to the DateTimeField
# Modification 20170807: Dates will be naive on the TimeZone
from random import randint
from django.core.wsgi import get_wsgi_application # To run the webserver
from django.utils.timezone import ... | gpl-3.0 |
jonyroda97/redbot-amigosprovaveis | lib/matplotlib/tests/test_cycles.py | 2 | 7995 | import warnings
from matplotlib.testing.decorators import image_comparison
from matplotlib.cbook import MatplotlibDeprecationWarning
import matplotlib.pyplot as plt
import numpy as np
import pytest
from cycler import cycler
@image_comparison(baseline_images=['color_cycle_basic'], remove_text=True,
... | gpl-3.0 |
Obus/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 |
polyanskiy/refractiveindex.info-scripts | scripts/Rakic 1998 - Ti (BB model).py | 1 | 2588 | # -*- coding: utf-8 -*-
# Author: Mikhail Polyanskiy
# Last modified: 2017-04-02
# Original data: Rakić et al. 1998, https://doi.org/10.1364/AO.37.005271
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import wofz as w
π = np.pi
# Brendel-Bormann (BB) model parameters
ωp = 7.29 #eV
f0 = 0.126
Γ... | gpl-3.0 |
khushhallchandra/Deep-Learning | kaggle/fbPrediction/src/timePlot.py | 1 | 1744 | import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory
import matplotlib.pyplot as plt
df... | mit |
Anmol-Singh-Jaggi/Machine-Learning | svm/demo.py | 294 | 1273 | """
=========================================
SVM: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a Support Vector Machine classifier with
linear kernel.
"""
print(__doc__)
import numpy as np
impor... | mit |
hdmetor/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 |
harshaneelhg/scikit-learn | sklearn/tests/test_calibration.py | 213 | 12219 | # Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from sklearn.utils.testing import (assert_array_almost_equal, assert_equal,
assert_greater, assert_almost_equal,
... | bsd-3-clause |
ycaihua/scikit-learn | sklearn/ensemble/partial_dependence.py | 36 | 14909 | """Partial dependence plots for tree ensembles. """
# Authors: Peter Prettenhofer
# License: BSD 3 clause
from itertools import count
import numbers
import numpy as np
from scipy.stats.mstats import mquantiles
from ..utils.extmath import cartesian
from ..externals.joblib import Parallel, delayed
from ..externals im... | bsd-3-clause |
jereze/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 |
ningchi/scikit-learn | examples/linear_model/plot_sgd_weighted_samples.py | 344 | 1458 | """
=====================
SGD: Weighted samples
=====================
Plot decision function of a weighted dataset, where the size of points
is proportional to its weight.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
# we create 20 points
np.random.seed(0)
X ... | bsd-3-clause |
micahhausler/pandashells | pandashells/lib/arg_lib.py | 7 | 6681 | from pandashells.lib import config_lib
def _check_for_recognized_args(*args):
"""
Raise an error if unrecognized argset is specified
"""
allowed_arg_set = set([
'io_in',
'io_out',
'example',
'xy_plotting',
'decorating',
])
in_arg_set = set(args)
unr... | bsd-2-clause |
wxgeo/geophar | wxgeometrie/sympy/physics/quantum/state.py | 4 | 29157 | """Dirac notation for states."""
from __future__ import print_function, division
from sympy import (cacheit, conjugate, Expr, Function, integrate, oo, sqrt,
Tuple)
from sympy.core.compatibility import range
from sympy.printing.pretty.stringpict import stringPict
from sympy.physics.quantum.qexpr imp... | gpl-2.0 |
Danie1Johnson/research | bg_anim_test.py | 1 | 4065 | import numpy as np
import matplotlib.pyplot as plt
from time import time
import matplotlib.animation as animation
import bga_4_0 as bga
import manifold_reflected_brownian_motion as mrbm
bga = reload(bga)
mrbm = reload(mrbm)
def face_position(bg_int, face_num, faces, dim=3):
"""Return the current and last positio... | mit |
ch3ll0v3k/scikit-learn | sklearn/utils/tests/test_sparsefuncs.py | 157 | 13799 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from numpy.testing import assert_array_almost_equal, assert_array_equal
from sklearn.datasets import make_classification
from sklearn.utils.sparsefuncs import (mean_variance_axis,
inplace_column_scale,
... | bsd-3-clause |
nmartensen/pandas | asv_bench/benchmarks/reshape.py | 7 | 4225 | from .pandas_vb_common import *
from pandas import melt, wide_to_long
class melt_dataframe(object):
goal_time = 0.2
def setup(self):
self.index = MultiIndex.from_arrays([np.arange(100).repeat(100), np.roll(np.tile(np.arange(100), 100), 25)])
self.df = DataFrame(np.random.randn(10000, 4), inde... | bsd-3-clause |
mardom/GalSim | devel/external/test_cf/test_cf.py | 1 | 3573 | # Copyright 2012, 2013 The GalSim developers:
# https://github.com/GalSim-developers
#
# This file is part of GalSim: The modular galaxy image simulation toolkit.
#
# GalSim 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... | gpl-3.0 |
lucidfrontier45/scikit-learn | sklearn/tests/test_cross_validation.py | 1 | 18705 | """Test the cross_validation module"""
import numpy as np
import warnings
from scipy.sparse import coo_matrix
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_greater
from sklearn.utils... | bsd-3-clause |
nikitasingh981/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 9 | 51137 | # Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com> (main author)
# Mathieu Blondel (partial_fit support)
#
# License: BSD 3 clause
"""Classification and regression using Stochastic Gradient Descent (SGD)."""
import numpy as np
from abc import ABCMeta, abstractmethod
from ..externals.joblib import ... | bsd-3-clause |
qPCR4vir/orange3 | Orange/clustering/dbscan.py | 9 | 1770 | import sklearn.cluster as skl_cluster
from Orange.data import Table, DiscreteVariable, Domain, Instance
from Orange.projection import SklProjector, Projection
from numpy import atleast_2d, ndarray, where
__all__ = ["DBSCAN"]
class DBSCAN(SklProjector):
__wraps__ = skl_cluster.DBSCAN
def __init__(self, eps=0... | bsd-2-clause |
nicovince/mche | mche.py | 1 | 64134 | #!/usr/bin/env python
import os
import sys
import re
import logging
import itertools
import argparse
import nbt
from io import BytesIO
import zlib
import gzip
from binascii import hexlify
from binascii import unhexlify
import matplotlib
#matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
from ruam... | gpl-3.0 |
bzero/arctic | tests/util.py | 2 | 1376 | from contextlib import contextmanager
from cStringIO import StringIO
from dateutil.rrule import rrule, DAILY
import dateutil
from datetime import datetime as dt
import pandas
import numpy as np
import sys
def read_str_as_pandas(ts_str):
labels = [x.strip() for x in ts_str.split('\n')[0].split('|')]
pd = panda... | lgpl-2.1 |
mortada/scipy | scipy/signal/wavelets.py | 23 | 10483 | from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.dual import eig
from scipy.special import comb
from scipy import linspace, pi, exp
from scipy.signal import convolve
__all__ = ['daub', 'qmf', 'cascade', 'morlet', 'ricker', 'cwt']
def daub(p):
"""
The coefficient... | bsd-3-clause |
henridwyer/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 |
rustychris/stompy | stompy/grid/rebay.py | 1 | 12410 | """
Pure python implementation of Rebay frontal delaunay method
"""
import heapq
from itertools import chain
import matplotlib.pyplot as plt
import numpy as np
from . import unstructured_grid, front, exact_delaunay
from ..spatial import field
from .. import utils
DELETED=-1
UNSET=0
EXT=1
WAITING=2
ACTIVE=3
DONE=4
... | mit |
DSLituiev/scikit-learn | examples/classification/plot_digits_classification.py | 289 | 2397 | """
================================
Recognizing hand-written digits
================================
An example showing how the scikit-learn can be used to recognize images of
hand-written digits.
This example is commented in the
:ref:`tutorial section of the user manual <introduction>`.
"""
print(__doc__)
# Autho... | bsd-3-clause |
CrazyGuo/bokeh | bokeh/compat/mpl.py | 32 | 2834 | "Supporting objects and functions to convert Matplotlib objects into Bokeh."
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.t... | bsd-3-clause |
hail-is/hail | benchmark/python/benchmark_hail/compare/compare.py | 2 | 3215 | import json
import os
import sys
from scipy.stats.mstats import gmean, hmean
import numpy as np
def load_file(path):
if path.endswith('.json'):
with open(path, 'r') as f:
js_data = json.load(f)
elif path.endswith('.tsv'):
import pandas as pd
js_data = pd.read_table(path).t... | mit |
HerdOfBears/Learning_Machine_Learning | Reinforcement Learning/double_DQN_cartpole.py | 1 | 7804 | """
Author: Jyler Menard
Purpose implement a Deep Q Network that uses a double DQN inspired by van Hasselt in 'Deep Reinforcement Learning with Double Q-Learning'.
Q-learning can easily overestimate the value of an action from a state, resulting in overoptimistic value estimates.
Double Q-learning decouples the action... | mit |
ysasaki6023/NeuralNetworkStudy | cifar02/train_DropTest.py | 8 | 9985 | #!/usr/bin/env python
import argparse
import time
import numpy as np
import six
import os
import shutil
import chainer
from chainer import computational_graph
from chainer import cuda
import chainer.links as L
import chainer.functions as F
from chainer import optimizers
from chainer import serializers
from chainer.ut... | mit |
cloud-fan/spark | python/pyspark/sql/tests/test_pandas_udf_scalar.py | 22 | 53224 | #
# 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 |
shyamalschandra/scikit-learn | sklearn/linear_model/passive_aggressive.py | 60 | 10566 | # Authors: Rob Zinkov, Mathieu Blondel
# License: BSD 3 clause
from .stochastic_gradient import BaseSGDClassifier
from .stochastic_gradient import BaseSGDRegressor
from .stochastic_gradient import DEFAULT_EPSILON
class PassiveAggressiveClassifier(BaseSGDClassifier):
"""Passive Aggressive Classifier
Read mor... | bsd-3-clause |
saiwing-yeung/scikit-learn | sklearn/feature_selection/tests/test_mutual_info.py | 56 | 6268 | from __future__ import division
import numpy as np
from numpy.testing import run_module_suite
from scipy.sparse import csr_matrix
from sklearn.utils.testing import (assert_array_equal, assert_almost_equal,
assert_false, assert_raises, assert_equal)
from sklearn.feature_selection.mut... | bsd-3-clause |
thientu/scikit-learn | examples/feature_stacker.py | 246 | 1906 | """
=================================================
Concatenating multiple feature extraction methods
=================================================
In many real-world examples, there are many ways to extract features from a
dataset. Often it is beneficial to combine several methods to obtain good
performance. Th... | bsd-3-clause |
rameshvs/nipype | nipype/pipeline/utils.py | 5 | 46302 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Utility routines for workflow graphs
"""
from copy import deepcopy
from glob import glob
from collections import defaultdict
import os
import pwd
import re
from uuid import uuid1
import numpy as np
fro... | bsd-3-clause |
passiweinberger/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/mathtext.py | 69 | 101723 | r"""
:mod:`~matplotlib.mathtext` is a module for parsing a subset of the
TeX math syntax and drawing them to a matplotlib backend.
For a tutorial of its usage see :ref:`mathtext-tutorial`. This
document is primarily concerned with implementation details.
The module uses pyparsing_ to parse the TeX expression.
.. _p... | agpl-3.0 |
treverhines/RBF | docs/scripts/gproc.j.py | 1 | 4852 | '''
Use Gaussian process regression to perform 2-D interpolation of
scattered data and then differentiate the interpolant.
'''
import matplotlib.pyplot as plt
import numpy as np
from rbf.basis import spwen32
from rbf.gproc import gpiso, gppoly
# get a verbose log of what is going on
import logging
logging.basicConfig... | mit |
l2xBrain/chineseocr | finger.py | 1 | 1356 | # coding: utf-8
from __future__ import print_function
import cv2
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import os
def identity(filename):
"""
:param filename:
:return:
"""
is_figure = False
img = cv2.imread(filename)
for i in range(img.shape[0]):
for j in range(img.sha... | mit |
asalomatov/variants | variants/work/train_script.py | 1 | 6042 | import sys
sys.path.insert(0, '/mnt/xfs1/home/asalomatov/projects/variants/variants')
import ped
import variants
import func
import pandas
import numpy
import os
import features
from multiprocessing import Pool
from sklearn.cross_validation import train_test_split
from sklearn.ensemble import GradientBoostingClassifier... | mit |
GaryLv/GaryLv.github.io | codes/Logistic Regression/LRNB.py | 1 | 2115 | # -*- coding: utf-8 -*-
"""
LR 非线性边界分类
"""
import numpy as np
import matplotlib.pyplot as plt
def loadDataSet():
x = []; y = [];
fr = open('ex2data2.txt')
for line in fr.readlines():
lineArr = line.strip().split(',')
x.append([1.0, float(lineArr[0]), float(lineArr[1])])
y.append(f... | apache-2.0 |
duncanmmacleod/gwpy | gwpy/timeseries/statevector.py | 3 | 35849 | # -*- coding: utf-8 -*-
# Copyright (C) Duncan Macleod (2014-2020)
#
# This file is part of GWpy.
#
# GWpy 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)... | gpl-3.0 |
darshanthaker/nupic | examples/opf/tools/MirrorImageViz/mirrorImageViz.py | 50 | 7221 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
buguen/pylayers | pylayers/antprop/examples/ex_antenna51.py | 3 | 2027 | from pylayers.antprop.antenna import *
from pylayers.antprop.antvsh import *
import matplotlib.pylab as plt
from numpy import *
import pdb
"""
This test :
1 : loads a measured antenna
2 : applies an electrical delay obtained from data with getdelay method
3 : evaluate the antenna vsh coefficient with a down... | lgpl-3.0 |
xuleiboy1234/autoTitle | tensorflow/tensorflow/examples/get_started/regression/test.py | 8 | 3181 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | mit |
mfittere/SixDeskDB | old/danilo/DA_FullStat_public.py | 2 | 6452 | #!/usr/bin/python
# python re-implementation of read10b.f done by Danilo Banfi (danilo.banfi@cern.ch)
# This compute DA starting from the local .db produced by CreateDB.py
# Below are indicated thing that need to be edited by hand.
# You only have to provide the name of the study <study_name> like
# python CreateDB... | lgpl-2.1 |
JoanThibault/DAGaml | extra/script_dagaml_vs_abc_on_cnf_uf75.py | 1 | 3733 | import sys
import math
import lib
#read inputs
file_csv = sys.argv[1]
file_out = sys.argv[2]
#read csv
FILE = open(sys.argv[1])
T = FILE.read().split('\n')
FILE.close()
<<<<<<< HEAD
M = [line.split(' ') for line in T if line!='']
K = M[0]
print('keys: ('+' '.join(K)+')')
=======
M = [line.split(', ') for line in T i... | mpl-2.0 |
jreback/pandas | pandas/tests/reshape/test_util.py | 3 | 2846 | import numpy as np
import pytest
from pandas import Index, date_range
import pandas._testing as tm
from pandas.core.reshape.util import cartesian_product
class TestCartesianProduct:
def test_simple(self):
x, y = list("ABC"), [1, 22]
result1, result2 = cartesian_product([x, y])
expected1 =... | bsd-3-clause |
xysmas/microsoft_malware_challenge | src/models/random_forest/model.py | 2 | 6659 | """
Template code to be used in the
Microsoft Malware Classification challenge.
"""
__authors__ = 'Aaron Gonzales, Andres Ruiz'
__licence__ = 'Apache'
__email__ = 'afruizc@cs.unm.edu'
import sys
import numpy as np
import pymongo
import joblib
from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.tex... | apache-2.0 |
INM-6/nest-git-migration | topology/examples/test_3d_gauss.py | 13 | 2641 | # -*- coding: utf-8 -*-
#
# test_3d_gauss.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 |
matthieudumont/dipy | scratch/very_scratch/simulation_comparisons.py | 20 | 12707 | import nibabel
import os
import numpy as np
import dipy as dp
#import dipy.core.generalized_q_sampling as dgqs#dipy.
import dipy.reconst.gqi as dgqs
import dipy.io.pickles as pkl
import scipy as sp
from matplotlib.mlab import find
#import dipy.core.sphere_plots as splots
import dipy.core.sphere_stats as sphats
import d... | bsd-3-clause |
jneer/knifedge | knifedge/tracing.py | 1 | 6788 | # -*- coding: utf-8 -*-
import numpy as np
from scipy.optimize import curve_fit
import attr
import matplotlib.pyplot as plt
import matplotlib
import yaml
matplotlib.rc('font', family='DejaVu Sans')
#TODO: use ODR instead of curve_fit to include z-error: http://stackoverflow.com/questions/26058792/correct-fitting-wit... | mit |
davek44/Basset | src/dna_io.py | 1 | 13190 | #!/usr/bin/env python
from __future__ import print_function
import pdb
import random
import sys
from collections import OrderedDict
import numpy as np
import numpy.random as npr
from sklearn import preprocessing
################################################################################
# dna_io.py
#
# Methods t... | mit |
aetilley/scikit-learn | examples/cluster/plot_lena_segmentation.py | 271 | 2444 | """
=========================================
Segmenting the picture of Lena in regions
=========================================
This example uses :ref:`spectral_clustering` on a graph created from
voxel-to-voxel difference on an image to break this image into multiple
partly-homogeneous regions.
This procedure (spe... | bsd-3-clause |
MatthieuBizien/scikit-learn | sklearn/neighbors/graph.py | 14 | 6663 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
import warnings
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def _check_params(X, metric, p, metric_... | bsd-3-clause |
holmes/intellij-community | python/helpers/pydev/pydevconsole.py | 41 | 15763 | from _pydev_imps._pydev_thread import start_new_thread
try:
from code import InteractiveConsole
except ImportError:
from pydevconsole_code_for_ironpython import InteractiveConsole
from code import compile_command
from code import InteractiveInterpreter
import os
import sys
import _pydev_threading as threadi... | apache-2.0 |
apache/incubator-superset | tests/fixtures/energy_dashboard.py | 1 | 5318 | # 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 u... | apache-2.0 |
TakayukiSakai/tensorflow | tensorflow/python/client/notebook.py | 33 | 4608 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
petercable/xray | xray/core/dataset.py | 1 | 79004 | import functools
import warnings
from collections import Mapping
from numbers import Number
import numpy as np
import pandas as pd
from . import ops
from . import utils
from . import common
from . import groupby
from . import indexing
from . import alignment
from . import formatting
from .. import conventions
from .a... | apache-2.0 |
FRESNA/vresutils | vresutils/reatlas.py | 1 | 9656 | # -*- coding: utf-8 -*-
## Copyright 2015-2017 Frankfurt Institute for Advanced Studies
## 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 optio... | gpl-3.0 |
datapythonista/pandas | pandas/core/arrays/interval.py | 1 | 54425 | from __future__ import annotations
import operator
from operator import (
le,
lt,
)
import textwrap
from typing import (
Sequence,
TypeVar,
cast,
)
import numpy as np
from pandas._config import get_option
from pandas._libs import NaT
from pandas._libs.interval import (
VALID_CLOSED,
Inte... | bsd-3-clause |
hanteng/pyCHNadm1 | pyCHNadm1/_examples/matplotlib_IPop_GDP_2004-2013.py | 1 | 3786 | # -*- coding: utf-8 -*-
#歧視無邊，回頭是岸。鍵起鍵落，情真情幻。
## Loading datasets
import pyCHNadm1 as CHN
## Loading seaborn and other scientific analysis and visualization modules
## More: http://stanford.edu/~mwaskom/software/seaborn/tutorial/axis_grids.html
import numpy as np
import pandas as pd
import seaborn as sns
from scipy i... | gpl-3.0 |
ec-geolink/d1lod | d1lod/d1lod/people/graph/graph.py | 1 | 12622 | #!/usr/bin/python
# -*- coding: utf-8 -*-
""" create_graph.py
Creates an RDF graph from a JSON dump.
"""
import os
import sys
import json
import RDF
import uuid
import pandas
import unicodecsv as csv
def addStatement(model, s, p, o):
# Assume subject is a URI string if it is not an RDF.Node
if type(s)... | apache-2.0 |
SheffieldML/GPy | GPy/util/netpbmfile.py | 31 | 12223 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# netpbmfile.py
# Copyright (c) 2011-2013, Christoph Gohlke
# Copyright (c) 2011-2013, The Regents of the University of California
# Produced at the Laboratory for Fluorescence Dynamics.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or ... | bsd-3-clause |
mmagnus/rna-pdb-tools | rna_tools/tools/rna_alignment/utils/rna_alignment_get_species.py | 1 | 10485 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
The output you simply get from the screen, save it it to a file.
Example::
rna_alignment_get_species.py RF00004.stockholm.stk
# STOCKHOLM 1.0
Sorex-araneus-(European-shrew) AUCGCU-UCU----CGGCC--UUU-U
Examples 2::
[dhcp177-lan203] ... | gpl-3.0 |
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