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 |
|---|---|---|---|---|---|
cdegroc/scikit-learn | examples/covariance/plot_robust_vs_empirical_covariance.py | 5 | 5860 | """
=======================================
Robust vs Empirical covariance estimate
=======================================
The usual covariance maximum likelihood estimate is very sensitive to
the presence of outliers in the data set. In such a case, one would
have better to use a robust estimator of covariance to ga... | bsd-3-clause |
rjw57/vagrant-ipython | ipython/profile_default/ipython_notebook_config.py | 1 | 19754 | # Configuration file for ipython-notebook.
c = get_config()
#------------------------------------------------------------------------------
# NotebookApp configuration
#------------------------------------------------------------------------------
# NotebookApp will inherit config from: BaseIPythonApplication, Appli... | mit |
sdh11/gnuradio | gr-digital/examples/example_fll.py | 7 | 5704 | #!/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 |
TuKo/brainiak | examples/searchlight/example_searchlight.py | 5 | 2942 | # Copyright 2016 Intel Corporation
#
# 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 |
sjsrey/pysal | docsrc/conf.py | 4 | 8315 | # -*- coding: utf-8 -*-
#
# pysal documentation build configuration file, created by
# sphinx-quickstart on Wed Jun 6 15:54:22 2018.
#
# 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.
#
# All... | bsd-3-clause |
plissonf/scikit-learn | sklearn/neighbors/graph.py | 208 | 7031 | """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 |
0x0all/scikit-learn | sklearn/datasets/tests/test_lfw.py | 50 | 6849 | """This test for the LFW require medium-size data dowloading and processing
If the data has not been already downloaded by running the examples,
the tests won't run (skipped).
If the test are run, the first execution will be long (typically a bit
more than a couple of minutes) but as the dataset loader is leveraging
... | bsd-3-clause |
ahkab/ahkab | ahkab/testing.py | 1 | 33795 | # -*- coding: utf-8 -*-
# testing.py
# Testing framework
# Copyright 2014 Giuseppe Venturini
# This file is part of the ahkab simulator.
#
# Ahkab 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, version 2 of ... | gpl-2.0 |
rjleveque/riemann_book | exact_solvers/interactive_pplanes.py | 3 | 17630 | """
Interactive phase plane plot for Euler equations with ideal gas,
Euler equations with Tammann equations of state and acoustic equations.
"""
import sys, os
import numpy as np
from scipy.optimize import fsolve
import matplotlib.pyplot as plt
from ipywidgets import widgets
from ipywidgets import interact
from IPython... | bsd-3-clause |
jayfans3/jieba | test/extract_topic.py | 65 | 1463 | import sys
sys.path.append("../")
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn import decomposition
import jieba
import time
import glob
import sys
import os
import random
if len(sys.argv)<2:
print("usage: extract_topic.py di... | mit |
nhmc/LAE | cloudy/comp7/final/model.py | 6 | 21973 | """
Make a likelihood function for use with emcee
Given input Z, nH, k_C, k_N, k_Al, aUV, NHI return ln
of the likelihood.
This module must define the following objects:
- a dictionary P with keys. The value of every key is a tuple with the
same length (the number of model parameters)
name : parameter names
... | mit |
mne-tools/mne-tools.github.io | 0.19/_downloads/8ed64d7c92012e6fcb6501cd8cdb8d25/plot_40_sensor_locations.py | 1 | 11176 | """
.. _tut-sensor-locations:
Working with sensor locations
=============================
This tutorial describes how to read and plot sensor locations, and how
the physical location of sensors is handled in MNE-Python.
.. contents:: Page contents
:local:
:depth: 2
As usual we'll start by importing the module... | bsd-3-clause |
rohit12/opencog | opencog/python/spatiotemporal/temporal_events/animation.py | 34 | 4896 | from matplotlib.lines import Line2D
from matplotlib.ticker import AutoMinorLocator
from numpy.core.multiarray import zeros
from spatiotemporal.temporal_events.trapezium import TemporalEventTrapezium
from spatiotemporal.time_intervals import TimeInterval
from matplotlib import pyplot as plt
from matplotlib import animat... | agpl-3.0 |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/sklearn/cluster/spectral.py | 5 | 19195 | # -*- coding: utf-8 -*-
"""Algorithms for spectral clustering"""
# Author: Gael Varoquaux gael.varoquaux@normalesup.org
# Brian Cheung
# Wei LI <kuantkid@gmail.com>
# License: BSD 3 clause
import warnings
import numpy as np
from ..base import BaseEstimator, ClusterMixin
from ..utils import check_rand... | mit |
TomAugspurger/pandas | pandas/tests/tseries/holiday/test_holiday.py | 2 | 8620 | from datetime import datetime
import pytest
from pytz import utc
import pandas._testing as tm
from pandas.tseries.holiday import (
MO,
SA,
AbstractHolidayCalendar,
DateOffset,
EasterMonday,
GoodFriday,
Holiday,
HolidayCalendarFactory,
Timestamp,
USColumbusDay,
USLaborDay,
... | bsd-3-clause |
ryanjmccall/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/table.py | 69 | 16757 | """
Place a table below the x-axis at location loc.
The table consists of a grid of cells.
The grid need not be rectangular and can have holes.
Cells are added by specifying their row and column.
For the purposes of positioning the cell at (0, 0) is
assumed to be at the top left and the cell at (max_row, max_col)
i... | gpl-3.0 |
sumspr/scikit-learn | sklearn/decomposition/nmf.py | 100 | 19059 | """ Non-negative matrix factorization
"""
# Author: Vlad Niculae
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Author: Chih-Jen Lin, National Taiwan University (original projected gradient
# NMF implementation)
# Author: Anthony Di Franco (original Python and NumPy port)
# License: BSD 3 clause
from __future__ ... | bsd-3-clause |
Udzu/pudzu | dataviz/flagsrwbpercent.py | 1 | 2803 | from pudzu.charts import *
from pudzu.sandbox.bamboo import *
import scipy.stats
df = pd.read_csv("datasets/flagsrwbpercent.csv").set_index("country")
class HeraldicPalette(metaclass=NamedPaletteMeta):
ARGENT = "#ffffff"
AZURE = "#0f47af"
GULES = "#da121a"
SABLE = "#00ff00"
def flag_image(c):
ret... | mit |
jpinedaf/pyspeckit | setup.py | 2 | 3802 | #!/usr/bin/env python
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import glob
import os
import sys
import ah_bootstrap
from setuptools import setup
#A dirty hack to get around some early import/configurations ambiguities
if sys.version_info[0] >= 3:
import builtins
else:
import __builtin_... | mit |
jseabold/scikit-learn | sklearn/ensemble/tests/test_forest.py | 26 | 41675 | """
Testing for the forest module (sklearn.ensemble.forest).
"""
# Authors: Gilles Louppe,
# Brian Holt,
# Andreas Mueller,
# Arnaud Joly
# License: BSD 3 clause
import pickle
from collections import defaultdict
from itertools import combinations
from itertools import product
import numpy ... | bsd-3-clause |
anurag313/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 |
EPFL-LCN/neuronaldynamics-exercises | neurodynex3/test/test_hopfield.py | 1 | 1162 | # import matplotlib
# matplotlib.use("Agg") # needed for plotting on travis
def test_pattern_factory():
""" Test hopfield_network.pattern_tools """
import neurodynex3.hopfield_network.pattern_tools as tools
pattern_size = 6
factory = tools.PatternFactory(pattern_size)
p1 = factory.create_checkerb... | gpl-2.0 |
kkozarev/mwacme | src/plot_max_spectra_synchrotron_integrated_subset.py | 2 | 10688 | import glob, os, sys,fnmatch
import matplotlib.pyplot as plt
from astropy.io import ascii
import numpy as np
def match_list_values(ls1,ls2):
#Return lists of the indices where the values in two lists match
#It will return only the first index of occurrence of repeating values in the lists
#Written by Kame... | gpl-2.0 |
henridwyer/scikit-learn | sklearn/linear_model/bayes.py | 220 | 15248 | """
Various bayesian regression
"""
from __future__ import print_function
# Authors: V. Michel, F. Pedregosa, A. Gramfort
# License: BSD 3 clause
from math import log
import numpy as np
from scipy import linalg
from .base import LinearModel
from ..base import RegressorMixin
from ..utils.extmath import fast_logdet, p... | bsd-3-clause |
droundy/fac | bench/plot-benchmark.py | 1 | 3227 | #!/usr/bin/python3
from __future__ import print_function
import os, sys
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import cats
import hierarchy
import dependentchains
import sleepy
import independent
#matplotlib.rc('font', size='16.0')
datadir = os.getcwd()+'/data/'
... | gpl-2.0 |
Srisai85/scikit-learn | sklearn/linear_model/__init__.py | 270 | 3096 | """
The :mod:`sklearn.linear_model` module implements generalized linear models. It
includes Ridge regression, Bayesian Regression, Lasso and Elastic Net
estimators computed with Least Angle Regression and coordinate descent. It also
implements Stochastic Gradient Descent related algorithms.
"""
# See http://scikit-le... | bsd-3-clause |
adamgreenhall/scikit-learn | examples/ensemble/plot_gradient_boosting_quantile.py | 392 | 2114 | """
=====================================================
Prediction Intervals for Gradient Boosting Regression
=====================================================
This example shows how quantile regression can be used
to create prediction intervals.
"""
import numpy as np
import matplotlib.pyplot as plt
from skle... | bsd-3-clause |
buguen/pylayers | pylayers/gis/srtm.py | 1 | 14250 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Pylint: Disable name warningsos.path.join(self.directory,continent)
# pylint: disable-msg=C0103
"""Load and process SRTM data."""
#import xml.dom.minidom
from HTMLParser import HTMLParser
import ftplib
import urllib2
import re
import pickle
import os.path
import os
imp... | lgpl-3.0 |
Garrett-R/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 16 | 5134 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from numpy.testing import assert_raises
from scipy.spatial import distance
from sklearn.utils.testing import assert_equal
from sklearn.cluster.dbscan_ import DBSCAN, dbscan
from .common import generate_clustered_data
from sklearn.metrics... | bsd-3-clause |
ahye/FYS2140-Resources | examples/plotting/three_gauss.py | 1 | 1086 | #!/usr/bin/env python
"""
Created on Mon 2 Dec 2013
Scriptet viser hvordan man kan plotte 3D-figurer med matplotlib.
@author Benedicte Emilie Braekken
"""
from matplotlib.pyplot import *
from numpy import *
from mpl_toolkits.mplot3d import Axes3D
def gauss_2d( x, y ):
'''
Todimensjonal gauss-kurve.
'''
... | mit |
terkkila/scikit-learn | sklearn/utils/multiclass.py | 92 | 13986 | # 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
import warnings
from scipy.sparse import issparse
fro... | bsd-3-clause |
abhishekkrthakur/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 20 | 11431 | # 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 |
crawfordsm/pysalt | saltspec/specsens.py | 2 | 6366 | #!/usr/bin/env python
# Copyright (c) 2009, South African Astronomical Observatory (SAAO) #
# All rights reserved. #
"""
SPECSENS calulates the calibration curve given an observation, a standard star,
and the extinction curve for the site. The task assumes a 1... | bsd-3-clause |
jereze/scikit-learn | examples/mixture/plot_gmm.py | 248 | 2817 | """
=================================
Gaussian Mixture Model Ellipsoids
=================================
Plot the confidence ellipsoids of a mixture of two Gaussians with EM
and variational Dirichlet process.
Both models have access to five components with which to fit the
data. Note that the EM model will necessari... | bsd-3-clause |
RachitKansal/scikit-learn | examples/feature_selection/plot_permutation_test_for_classification.py | 250 | 2233 | """
=================================================================
Test with permutations the significance of a classification score
=================================================================
In order to test if a classification score is significative a technique
in repeating the classification procedure aft... | bsd-3-clause |
hsaputra/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/io_test.py | 137 | 5063 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
pompiduskus/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 143 | 22295 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
tapomayukh/projects_in_python | classification/Classification_with_kNN/Single_Contact_Classification/Final/results/2-categories/test10_cross_validate_categories_mov_fixed_1200ms.py | 1 | 4331 |
# Principal Component Analysis Code :
from numpy import mean,cov,double,cumsum,dot,linalg,array,rank,size,flipud
from pylab import *
import numpy as np
import matplotlib.pyplot as pp
#from enthought.mayavi import mlab
import scipy.ndimage as ni
import roslib; roslib.load_manifest('sandbox_tapo_darpa_m3')
import ro... | mit |
theodoregoetz/clas12-dc-wiremap | scratch/ax.py | 1 | 1150 | import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
import numpy as np
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
im = np.arange(100)
im.shape = 10, 10
fig = plt.figure(1, (5., 5.))
grid = ImageGrid(fig, (0.1, 0.4, 0.2, 0.2), # similar to subplot(111)
nrows_... | gpl-3.0 |
gsnyder206/synthetic-image-morph | candelize.py | 1 | 11413 | import cProfile
import pstats
import math
import string
import sys
import struct
import matplotlib
import numpy as np
import scipy.ndimage
import scipy.stats as ss
import scipy.signal
import scipy as sp
import scipy.odr as odr
import glob
import os
import gzip
import tarfile
import shutil
import congrid
import astropy.... | gpl-2.0 |
taynaud/sparkit-learn | splearn/linear_model/base.py | 2 | 5024 | # encoding: utf-8
import operator
import numpy as np
import scipy.sparse as sp
from sklearn.base import copy
from sklearn.linear_model.base import LinearRegression
from ..utils.validation import check_rdd
class SparkLinearModelMixin(object):
def __add__(self, other):
"""Add method for Linear models wi... | apache-2.0 |
GaelVaroquaux/scikits.image | doc/ext/docscrape_sphinx.py | 62 | 7703 | import re, inspect, textwrap, pydoc
import sphinx
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config={}):
self.use_plots = config.get('use_plots', False)
NumpyDocString.__init__(self, docstring, config=config)
... | bsd-3-clause |
doanduyhai/incubator-zeppelin | python/src/main/resources/grpc/python/zeppelin_python.py | 9 | 4436 | #
# 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 |
geoscixyz/em_examples | em_examples/DCWidgetResLayer2D.py | 1 | 28082 | from __future__ import print_function
from __future__ import absolute_import
from __future__ import unicode_literals
from SimPEG import Mesh, Maps, SolverLU, Utils
from SimPEG.Utils import ExtractCoreMesh
import numpy as np
from SimPEG.EM.Static import DC
import matplotlib
import matplotlib.pyplot as plt
import matplo... | mit |
fraser-lab/EMRinger | Figures/S5/S5.py | 1 | 12942 | #! /usr/bin/env phenix.python
# Rotamer distribution analysis tool for validation of models generated from cryoEM data.
# Written by Benjamin Barad
# Written for use with Ringer's (http://bl831.als.lbl.gov/ringer/) output.
#
# Ringer Reference:
# Lang PT, Ng HL, Fraser JS, Corn JE, Echols N, Sales M, Holton JM, Albe... | bsd-3-clause |
smcantab/pele | pele/amber/amberSystem.py | 4 | 26626 | """
System class for biomolecules using AMBER ff.
Set up using prmtop and inpcrd files used in Amber GMIN and Optim.
Potential parameters (e.g. non-bonded cut-offs are set in
TODO:
Parameters
----------
prmtopFname : str
prmtop file name
inpcrdFname : str
inpcrd file name
... | gpl-3.0 |
cuemacro/finmarketpy | finmarketpy/curve/fxoptionscurve.py | 1 | 39487 | __author__ = 'saeedamen' # Saeed Amen
#
# Copyright 2016-2020 Cuemacro - https://www.cuemacro.com / @cuemacro
#
# 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/LI... | apache-2.0 |
ashhher3/pylearn2 | pylearn2/scripts/train.py | 34 | 8573 | #!/usr/bin/env python
"""
Script implementing the logic for training pylearn2 models.
This is a "driver" that we recommend using for all but the most unusual
training experiments.
Basic usage:
.. code-block:: none
train.py yaml_file.yaml
The YAML file should contain a pylearn2 YAML description of a
`pylearn2.t... | bsd-3-clause |
choderalab/perses | perses/analysis/analyse_sams_convergence.py | 1 | 1762 | import matplotlib.pyplot as plt
import os
import sys
from glob import glob
from perses.analysis import utils
if __name__ == '__main__':
directory = sys.argv[1]
files = sorted(glob(os.path.join(os.getcwd(), directory, '*.nc')))
files = [x for x in files if 'checkpoint' not in x]
f, axarr = plt.subplots(... | mit |
dimroc/tensorflow-mnist-tutorial | lib/python3.6/site-packages/matplotlib/testing/__init__.py | 10 | 3767 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import warnings
from contextlib import contextmanager
from matplotlib.cbook import is_string_like, iterable
from matplotlib import rcParams, rcdefaults, use
def _is_list_like(obj):
"""Returns whether the... | apache-2.0 |
dr-guangtou/hs_galspec | manga/cframe/mgCFrameRead.py | 1 | 2529 | #!/usr/bin/env python
# Filename : mgCFrameRead.py
import numpy
import os
from astropy.io import fits
from matplotlib import pyplot as plt
"""
Data model for mgCFrame file:
HDU[0] = Empty, only used to store header
HDU[1] = Flux [NPixels,NFiber], in Unit of 10^(-17) erg/s/cm^2/Ang/Fiber
HDU[2] = InverseVariance of t... | bsd-3-clause |
MSeifert04/astropy | astropy/visualization/wcsaxes/tests/test_formatter_locator.py | 7 | 22451 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from numpy.testing import assert_almost_equal
from matplotlib import rc_context
from astropy import units as u
from astropy.tests.helper import assert_quantity_allclose
from astropy.units import UnitsError
from astropy.v... | bsd-3-clause |
jss-emr/openerp-7-src | openerp/addons/resource/faces/timescale.py | 15 | 3899 | ############################################################################
# Copyright (C) 2005 by Reithinger GmbH
# mreithinger@web.de
#
# This file is part of faces.
#
# faces is free software; you can redistribute it and/or modify
# ... | agpl-3.0 |
mhdella/deeppy | setup.py | 16 | 2509 | #!/usr/bin/env python
import os
import re
from setuptools import setup, find_packages, Command
from setuptools.command.test import test as TestCommand
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
with open('requirements.txt') as f:
install_requires = [l.strip() for l ... | mit |
bvnayak/image_recognition | recognition/classification.py | 1 | 2384 | import numpy as np
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import *
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt
import utils
import math
# histogram intersection kernel
def histogramIntersection(M, N):
m = M.shape[0]
n = N.shape[0]
result = np.z... | mit |
CforED/Machine-Learning | examples/neighbors/plot_kde_1d.py | 347 | 5100 | """
===================================
Simple 1D Kernel Density Estimation
===================================
This example uses the :class:`sklearn.neighbors.KernelDensity` class to
demonstrate the principles of Kernel Density Estimation in one dimension.
The first plot shows one of the problems with using histogram... | bsd-3-clause |
alpenwasser/laborjournal | versuche/skineffect/python/hohlzylinder_cu_frequenzabhaengig_approx2.py | 1 | 12509 | #!/usr/bin/env python3
from sympy import *
from mpmath import *
from matplotlib.pyplot import *
import numpy as np
#init_printing() # make things prettier when we print stuff for debugging.
# ************************************************************************** #
# Magnetic field inside copper coil with ho... | mit |
carrillo/scikit-learn | sklearn/linear_model/tests/test_randomized_l1.py | 214 | 4690 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.linear_model.randomized_l1 i... | bsd-3-clause |
MJuddBooth/pandas | pandas/core/sparse/frame.py | 1 | 37597 | """
Data structures for sparse float data. Life is made simpler by dealing only
with float64 data
"""
from __future__ import division
import warnings
import numpy as np
from pandas._libs.sparse import BlockIndex, get_blocks
import pandas.compat as compat
from pandas.compat import lmap
from pandas.compat.numpy import... | bsd-3-clause |
paztronomer/kepler_tools | UncertSine_mcmc_v01.py | 1 | 14619 | # Script to estimate uncertainties in sine fit to a Kepler light curve
# If use/modify/distribute, refer to: Francisco Paz-Chinchon,
# francisco at dfte.ufrn.br
# DFTE, UFRN, Brazil.
import emcee
from pandas import *
import numpy as np
import mat... | mit |
altairpearl/scikit-learn | benchmarks/bench_isolation_forest.py | 46 | 3782 | """
==========================================
IsolationForest benchmark
==========================================
A test of IsolationForest on classical anomaly detection datasets.
"""
print(__doc__)
from time import time
import numpy as np
import matplotlib.pyplot as plt
from sklearn.ensemble import IsolationFore... | bsd-3-clause |
xbenjox/CryptoTrade | dataui.py | 1 | 3760 | from tkinter import *
import matplotlib
import numpy as np
from os import listdir
from os.path import isfile, join
from lxml import etree as ET
import math
class DataUI(Toplevel):
markets = list()
doge_data = list()
def __init__(self, parent, c_api):
Toplevel.__init__(self, parent)
self.c =... | lgpl-3.0 |
ligovirgo/gwdetchar | gwdetchar/scattering/tests/test_plot.py | 1 | 1814 | # -*- coding: utf-8 -*-
# Copyright (C) Alex Urban (2019)
#
# This file is part of the GW DetChar python package.
#
# GW DetChar 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,... | gpl-3.0 |
nhejazi/scikit-learn | sklearn/decomposition/tests/test_fastica.py | 70 | 7808 | """
Test the fastica algorithm.
"""
import itertools
import warnings
import numpy as np
from scipy import stats
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
... | bsd-3-clause |
jupsal/schmies-jTEM | jeremy/Test4Plotting.py | 1 | 1876 | ###########################################################################
# This file holds the plotting routine for the KP solution from the Schmiesy
# Thesie. There is no timestepping, it plots only the initial condition.
############################################################################
import matplotli... | bsd-2-clause |
Thomsen22/MissingMoney | Peak Load Reserve - EU system/PLR_optclass.py | 1 | 8145 | # Python standard modules
import numpy as np
import gurobipy as gb
import networkx as nx
from collections import defaultdict
import pandas as pd
# Own modules
import loaddataEU as data
import PLR_opt as plrmodel
class expando(object):
'''
# A class for capacity market clearing
'''
pas... | gpl-3.0 |
ClinicalGraphics/scikit-image | doc/examples/edges/plot_circular_elliptical_hough_transform.py | 6 | 4826 | """
========================================
Circular and Elliptical Hough Transforms
========================================
The Hough transform in its simplest form is a `method to detect
straight lines <http://en.wikipedia.org/wiki/Hough_transform>`__
but it can also be used to detect circles or ellipses.
The algo... | bsd-3-clause |
Michal-Fularz/decision_tree | decision_trees/datasets/digits_raw.py | 1 | 4649 | from typing import Tuple
import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets
from sklearn import svm, metrics
from decision_trees.datasets.dataset_base import DatasetBase
def sample_from_scikit():
# The digits dataset
digits = datasets.load_digits()
# The data that we are int... | mit |
hippke/TTV-TDV-exomoons | create_figures/create_figure_4a.py | 1 | 7168 | """n-body simulator to derive TDV+TTV diagrams of planet-moon configurations.
Credit for part of the source is given to
https://github.com/akuchling/50-examples/blob/master/gravity.rst
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License
"""
import numpy
import math
import matplotlib.pylab as plt... | mit |
sergiy-evision/math-algorithms | sf-crime/main.py | 1 | 3238 | from __future__ import division
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.cross_validation import KFold
from sklearn.cross_validation import cross_val_score
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ens... | mit |
dismalpy/dismalpy | dismalpy/model.py | 1 | 6371 | """
Model
Author: Chad Fulton
License: Simplified-BSD
"""
import numpy as np
import pandas as pd
class Model(object):
"""
Model
`endog` is one of:
- a name (str)
k_endog = 1
nobs = 0
names = [name]
endog = np.zeros((k_endog,0))
- iterable of names (str)
k_... | bsd-2-clause |
FluidityStokes/fluidity | examples/backward_facing_step_3d/postprocessor_3d.py | 1 | 10081 | #!/usr/bin/env python3
import glob
import sys
import os
import vtktools
import numpy
import pylab
import re
import extract_data
from math import log
def get_filelist(sample, start):
def key(s):
return int(s.split('_')[-1].split('.')[0])
list = glob.glob("*vtu")
list = [l for l in list if 'che... | lgpl-2.1 |
Barmaley-exe/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 |
cowlicks/blaze | blaze/server/tests/test_server.py | 2 | 20838 | from __future__ import absolute_import, division, print_function
import pytest
pytest.importorskip('flask')
from base64 import b64encode
from contextlib import contextmanager
from copy import copy
import datashape
from datashape.util.testing import assert_dshape_equal
import numpy as np
from odo import odo, convert
... | bsd-3-clause |
calatre/epidemics_network | models/SIR_non_spacial.py | 1 | 2531 | # Universidade de Aveiro - Physics Department
# 2016/2017 Project - Andre Calatre, 73207
# "Simulation of an epidemic" - 7/6/2017
# Simulation of a (non-spacial) SIR Epidemic Model
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from matplotlib import colors
#Possible status of a ... | apache-2.0 |
openpathsampling/openpathsampling | openpathsampling/analysis/tis/crossing_probability.py | 3 | 5290 | import collections
import openpathsampling as paths
from openpathsampling.netcdfplus import StorableNamedObject
from openpathsampling.numerics import LookupFunction
import pandas as pd
import numpy as np
from .core import EnsembleHistogrammer, MultiEnsembleSamplingAnalyzer
class FullHistogramMaxLambdas(EnsembleHistog... | mit |
grahesh/Stock-Market-Event-Analysis | quicksim/strategies/bollinger.py | 4 | 3609 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on Jan 1, 2011
@author:Drew Bratcher
@contact: dbratcher@gatech.edu
@summary: Contains tutorial for backteste... | bsd-3-clause |
wwf5067/statsmodels | statsmodels/base/model.py | 25 | 76781 | from __future__ import print_function
from statsmodels.compat.python import iterkeys, lzip, range, reduce
import numpy as np
from scipy import stats
from statsmodels.base.data import handle_data
from statsmodels.tools.tools import recipr, nan_dot
from statsmodels.stats.contrast import ContrastResults, WaldTestResults
f... | bsd-3-clause |
dymkowsk/mantid | Framework/PythonInterface/plugins/algorithms/StringToPng.py | 1 | 1866 | #pylint: disable=no-init,invalid-name
from __future__ import (absolute_import, division, print_function)
from six import u
import mantid
class StringToPng(mantid.api.PythonAlgorithm):
def category(self):
""" Category
"""
return "DataHandling\\Plots"
def name(self):
""" Algori... | gpl-3.0 |
rpalovics/Alpenglow | python/test_alpenglow/evaluation/test_DcgScore.py | 2 | 4634 | import alpenglow as prs
import alpenglow.Getter as rs
import alpenglow.evaluation
import pandas as pd
import math
import unittest
class TestDcgScore(unittest.TestCase):
def test_dcgScore(self):
ranks = [102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102... | apache-2.0 |
jmontgom10/PRISM_pyBDP | 02_buildCalibration.py | 2 | 14442 | #This scirpt will build the master calibration fields
#==========
#MasterBias
#MasterDark
#MasterFlat
#Import whatever modules will be used
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
from astropy.table import Table
from astropy.table import Column
from astropy.io import fits, ascii
from sc... | mit |
jat255/hyperspy | hyperspy/drawing/_widgets/range.py | 4 | 22490 | # -*- coding: utf-8 -*-
# Copyright 2007-2020 The HyperSpy developers
#
# This file is part of HyperSpy.
#
# HyperSpy is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at... | gpl-3.0 |
juanshishido/project-eta | code/utils/linear_fit.py | 3 | 3780 | from __future__ import division
import numpy as np # the Python array package
import pandas as pd
import matplotlib.pyplot as plt # the Python plotting package
from scipy.stats import gamma
import nibabel as nib
import numpy.linalg as npl
from utils.load_data import *
from utils.stimuli import events2neural
def... | bsd-3-clause |
mikegraham/dask | dask/dataframe/tests/test_dataframe.py | 1 | 61150 | from operator import getitem
from distutils.version import LooseVersion
import pandas as pd
import pandas.util.testing as tm
import numpy as np
import pytest
import dask
from dask.async import get_sync
from dask.utils import raises, ignoring
import dask.dataframe as dd
from dask.dataframe.core import (repartition_di... | bsd-3-clause |
Akshay0724/scikit-learn | sklearn/neighbors/tests/test_lof.py | 34 | 4142 | # Authors: Nicolas Goix <nicolas.goix@telecom-paristech.fr>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
from math import sqrt
import numpy as np
from sklearn import neighbors
from numpy.testing import assert_array_equal
from sklearn import metrics
from sklearn.metr... | bsd-3-clause |
alexandrebarachant/mne-python | tutorials/plot_introduction.py | 1 | 15178 | # -*- coding: utf-8 -*-
"""
.. _intro_tutorial:
Basic MEG and EEG data processing
=================================
MNE-Python reimplements most of MNE-C's (the original MNE command line utils)
functionality and offers transparent scripting.
On top of that it extends MNE-C's functionality considerably
(customize even... | bsd-3-clause |
Merinorus/adaisawesome | Homework/03 - Interactive Viz/Mapping onto Switzerland.py | 1 | 1723 |
# coding: utf-8
# In this part of the exercise, we now need to put the data which we have procured about the funding levels of the different universities that are located in different cantons onto a canton map. We will do so using Folio and take the example TopoJSON mapping which they use.
# In[15]:
import folium
i... | gpl-3.0 |
wmvanvliet/mne-python | examples/decoding/plot_decoding_spoc_CMC.py | 9 | 3007 | """
====================================
Continuous Target Decoding with SPoC
====================================
Source Power Comodulation (SPoC) :footcite:`DahneEtAl2014` allows to identify
the composition of
orthogonal spatial filters that maximally correlate with a continuous target.
SPoC can be seen as an exten... | bsd-3-clause |
ADM91/PowerSystem-RL | visualize/visualize_state.py | 1 | 10292 | from matplotlib import pyplot as plt
from matplotlib import animation
import matplotlib.patches as mpatches
import matplotlib.lines as mlines
import numpy as np
from oct2py import octave
def visualize_state(ideal_case, ideal_state, state_list, fig_num=1, frames=20, save=False):
color_map = {0: 'black',
... | gpl-3.0 |
gibiansky/tensorflow | tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined_test.py | 2 | 51684 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
fcooper8472/useful_scripts | system_monitor.py | 1 | 2019 | import psutil
import time
import matplotlib
matplotlib.use('svg')
from matplotlib import pyplot as plt
list_of_times = []
list_of_mem_free = []
list_of_swap_used = []
start_time = time.time()
timeout = 7200 # 2 hours
try:
while True:
list_of_times.append(time.time() - start_time)
# Current me... | bsd-3-clause |
pranavtbhat/EE219 | project3/part5.py | 1 | 3598 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cross_validation import KFold
import part1
def load_dataset():
df = pd.read_csv(
'ml-100k/u.data',
delimiter='\t',
names = ['user_id', 'item_id', 'rating', 'timestamp'],
header=0
)
R = df.pi... | unlicense |
jjinking/datsci | datsci/recsys.py | 1 | 4947 | """Recommender systems
"""
# Author : Jin Kim jjinking(at)gmail(dot)com
# Creation date : 2014.03.25
# Last Modified : 2014.03.27
#
# License : MIT
import numpy as np
import pandas as pd
import scipy as sp
import scipy.spatial
from collections import defaultdict
class RecommenderFrame(pd.DataF... | mit |
lukeiwanski/tensorflow-opencl | tensorflow/examples/learn/iris.py | 19 | 1651 | # 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... | apache-2.0 |
INCF/pybids | bids/layout/layout.py | 1 | 55524 | """BIDSLayout class."""
import os
import json
import re
from collections import defaultdict
from io import open
from functools import partial, lru_cache
from itertools import chain
import copy
import warnings
import enum
import difflib
import sqlalchemy as sa
from bids_validator import BIDSValidator
from ..utils impo... | mit |
iABC2XYZ/abc | Epics/rnn/DataRnnBPM1.5.py | 1 | 4527 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function, division
import numpy as np
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import tensorflow as tf
import matplotlib.pyplot as plt
plt.close('all')
numEpoch=2000000
batchSize= 50
stepRec = 200
learningRate=0.01
rnnSize=16
rn... | gpl-3.0 |
kevin-intel/scikit-learn | sklearn/conftest.py | 2 | 7197 | import os
from os import environ
from functools import wraps
import platform
import sys
import pytest
from threadpoolctl import threadpool_limits
from _pytest.doctest import DoctestItem
from sklearn.utils import _IS_32BIT
from sklearn.utils._openmp_helpers import _openmp_effective_n_threads
from sklearn.externals imp... | bsd-3-clause |
Chandra-MARX/marxs | marxs/visualization/tests/test_utils.py | 2 | 6107 | # Licensed under GPL version 3 - see LICENSE.rst
import numpy as np
import pytest
from ..utils import (plane_with_hole, combine_disjoint_triangulations,
get_color, color_tuple_to_hex,
MARXSVisualizationWarning,
DisplayDict)
from ..mayavi import plot_object... | gpl-3.0 |
mne-tools/mne-python | mne/viz/backends/tests/test_utils.py | 14 | 1696 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Eric Larson <larson.eric.d@gmail.com>
# Joan Massich <mailsik@gmail.com>
# Guillaume Favelier <guillaume.favelier@gmail.com>
#
# License: Simplified BSD
import pytest
from mne.viz.backends._utils import _get_colormap_from_array, _... | bsd-3-clause |
CORE-GATECH-GROUP/serpent-tools | serpentTools/objects/xsdata.py | 1 | 13731 | """Holds cross section data pertaining to Serpent xsplot output."""
from collections.abc import Mapping
import numpy as np
from matplotlib import pyplot
from serpentTools.messages import error
from serpentTools.objects.base import NamedObject
from serpentTools.utils.plot import magicPlotDocDecorator, formatPlot
__al... | mit |
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