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 |
|---|---|---|---|---|---|
ucsd-ccbb/jupyter-genomics | src/networkAnalysis/drug_gene_heatprop.py | 1 | 5526 | # import some useful packages
import numpy as np
import matplotlib.pyplot as plt
import seaborn
import networkx as nx
import pandas as pd
import random
import json
import sys
code_path = 'source'
sys.path.append(code_path)
import network_prop
def load_DB_data(fname):
'''
Function to load drug bank data (in f... | mit |
quheng/scikit-learn | examples/exercises/plot_cv_diabetes.py | 231 | 2527 | """
===============================================
Cross-validation on diabetes Dataset Exercise
===============================================
A tutorial exercise which uses cross-validation with linear models.
This exercise is used in the :ref:`cv_estimators_tut` part of the
:ref:`model_selection_tut` section of ... | bsd-3-clause |
hsuantien/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
QuantSoftware/QuantSoftwareToolkit | QSTK/qstkfeat/classes.py | 8 | 1658 | '''
(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 Nov 7, 2011
@author: John Cornwell
@contact: JohnWCornwellV@gmail.com
@summary: File containing various c... | bsd-3-clause |
stechma2/samuraiAnalysis | PlotSamuraiXS.py | 1 | 20610 | import os
import shutil
import warnings
from datetime import datetime as dt
import matplotlib as mpl
# mpl.use('PDF')
from matplotlib import pyplot as plt
import numpy as np
import yaml
from glob import glob
import argparse
from samuraiAnalysis import gribTools,plotFLpath,samImport_masked,samImport,samPlt,makeKML,getF... | gpl-3.0 |
wroscoe/donkey | donkeycar/management/base.py | 1 | 14840 |
import sys
import os
import socket
import shutil
import argparse
import donkeycar as dk
from donkeycar.parts.datastore import Tub
from .tub import TubManager
PACKAGE_PATH = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
TEMPLATES_PATH = os.path.join(PACKAGE_PATH, 'templates')
def make_dir(path):
... | mit |
wdbm/abstraction | classification_SUSY.py | 1 | 5526 | #!/usr/bin/env python
"""
################################################################################
# #
# classification_SUSY #
# ... | gpl-3.0 |
kgullikson88/gullikson-scripts | kglib/stellar_models/StellarModel.py | 1 | 50098 | from __future__ import print_function, absolute_import, division
import os
import sys
import re
from collections import defaultdict
import warnings
from collections import OrderedDict
import itertools
import logging
from astropy import units
from scipy.interpolate import InterpolatedUnivariateSpline as spline, Linear... | mit |
googleapis/google-cloud-cpp | google/cloud/storage/benchmarks/storage_throughput_vs_cpu_plots.py | 1 | 3335 | #!/usr/bin/env python3
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | apache-2.0 |
khkaminska/scikit-learn | examples/exercises/plot_iris_exercise.py | 323 | 1602 | """
================================
SVM Exercise
================================
A tutorial exercise for using different SVM kernels.
This exercise is used in the :ref:`using_kernels_tut` part of the
:ref:`supervised_learning_tut` section of the :ref:`stat_learn_tut_index`.
"""
print(__doc__)
import numpy as np
i... | bsd-3-clause |
wmvanvliet/mne-python | examples/forward/plot_forward_sensitivity_maps.py | 14 | 4139 | """
.. _ex-sensitivity-maps:
================================================
Display sensitivity maps for EEG and MEG sensors
================================================
Sensitivity maps can be produced from forward operators that
indicate how well different sensor types will be able to detect
neural currents f... | bsd-3-clause |
valexandersaulys/airbnb_kaggle_contest | venv/lib/python3.4/site-packages/pandas/tseries/tools.py | 9 | 18157 | from datetime import datetime, timedelta
import re
import sys
import numpy as np
import pandas.lib as lib
import pandas.tslib as tslib
import pandas.core.common as com
from pandas.compat import StringIO, callable
from pandas.core.common import ABCIndexClass
import pandas.compat as compat
from pandas.util.decorators i... | gpl-2.0 |
zihua/scikit-learn | sklearn/tree/tests/test_tree.py | 7 | 55471 | """
Testing for the tree module (sklearn.tree).
"""
import pickle
from functools import partial
from itertools import product
import struct
import numpy as np
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from sklearn.random_projection import sparse_random... | bsd-3-clause |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/matplotlib/backends/backend_gtk3.py | 8 | 39097 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
import os, sys
def fn_name(): return sys._getframe(1).f_code.co_name
try:
import gi
except ImportError:
raise ImportError("Gtk3 backend requires pygobject to be in... | apache-2.0 |
rew4332/tensorflow | tensorflow/examples/skflow/iris.py | 5 | 1597 | # 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 |
kevin-intel/scikit-learn | sklearn/tests/test_multioutput.py | 3 | 24614 |
import pytest
import numpy as np
import scipy.sparse as sp
from joblib import cpu_count
from sklearn.utils._testing import assert_almost_equal
from sklearn.utils._testing import assert_array_equal
from sklearn.utils._testing import assert_array_almost_equal
from sklearn import datasets
from sklearn.base import clone
... | bsd-3-clause |
seckcoder/lang-learn | python/sklearn/examples/cluster/plot_affinity_propagation.py | 2 | 2258 | """
=================================================
Demo of affinity propagation clustering algorithm
=================================================
Reference:
Brendan J. Frey and Delbert Dueck, "Clustering by Passing Messages
Between Data Points", Science Feb. 2007
"""
print __doc__
from sklearn.cluster import... | unlicense |
rosswhitfield/mantid | scripts/FilterEvents/eventFilterGUI.py | 3 | 40646 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
# py... | gpl-3.0 |
huongttlan/statsmodels | statsmodels/sandbox/tsa/movstat.py | 34 | 14871 | '''using scipy signal and numpy correlate to calculate some time series
statistics
original developer notes
see also scikits.timeseries (movstat is partially inspired by it)
added 2009-08-29
timeseries moving stats are in c, autocorrelation similar to here
I thought I saw moving stats somewhere in python, maybe not)... | bsd-3-clause |
JoseGuzman/NeuralNetworks | GCNetwork/patternseparation_patterns.py | 1 | 9706 | """
patternseparation_patterns.py
Claudia Espinoza, claumespinoza@gmail.com
Jose Guzman, sjm.guzman@gmail.com
Last change: Tue Nov 8 12:22:19 CET 2016
Simulate random patterns and get the patterns from the network
"""
import numpy as np
from neuron import gui, h
from Cell_builder import BCbuilder, GCbuilder
from... | gpl-2.0 |
jmikko/fairnessML | toy_problem_plot.py | 1 | 2964 | import numpy as np
from scipy.interpolate import griddata
import matplotlib.pyplot as plt
import numpy.ma as ma
from numpy.random import uniform, seed
from matplotlib import cm
import matplotlib.patches as mpatches
def gauss(x,y,Sigma,mu):
X=np.vstack((x,y)).T
mat_multi=np.dot((X-mu[None,...]).dot(np.linalg.i... | gpl-3.0 |
ryfeus/lambda-packs | Sklearn_scipy_numpy/source/sklearn/neighbors/base.py | 8 | 31247 | """Base and mixin classes for nearest neighbors"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck <L.J.Buitinck@uva.nl>
# Multi-output... | mit |
preete-dixit-ck/incubator-airflow | tests/operators/hive_operator.py | 40 | 14061 | # -*- coding: utf-8 -*-
#
# 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 in writing, software
... | apache-2.0 |
shuangshuangwang/spark | python/pyspark/sql/pandas/functions.py | 1 | 28129 | #
# 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 |
depet/scikit-learn | examples/document_classification_20newsgroups.py | 9 | 10380 | """
======================================================
Classification of text documents using sparse features
======================================================
This is an example showing how scikit-learn can be used to classify documents
by topics using a bag-of-words approach. This example uses a scipy.spars... | bsd-3-clause |
hlin117/statsmodels | statsmodels/sandbox/examples/ex_kaplan_meier.py | 33 | 2838 | #An example for the Kaplan-Meier estimator
from __future__ import print_function
from statsmodels.compat.python import lrange
import statsmodels.api as sm
import matplotlib.pyplot as plt
import numpy as np
from statsmodels.sandbox.survival2 import KaplanMeier
#Getting the strike data as an array
dta = sm.datasets.stri... | bsd-3-clause |
maropu/spark | python/pyspark/pandas/spark/accessors.py | 2 | 42892 | #
# 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 |
smartscheduling/scikit-learn-categorical-tree | sklearn/gaussian_process/tests/test_gaussian_process.py | 267 | 6813 | """
Testing for Gaussian Process module (sklearn.gaussian_process)
"""
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# Licence: BSD 3 clause
from nose.tools import raises
from nose.tools import assert_true
import numpy as np
from sklearn.gaussian_process import GaussianProcess
from sklearn.gaussian_process ... | bsd-3-clause |
phaustin/pyman | Book/chap8/Supporting Materials/betaDecay.py | 3 | 2528 | import numpy as np
import matplotlib.pyplot as plt
def LineFitWt(x, y, sig):
"""
Returns slope and y-intercept of weighted linear fit to (x,y) data set.
Inputs: x and y data array and uncertainty array (unc) for y data set.
Ouputs: slope and y-intercept of best fit to data.
"""
sig2 = sig**2
... | cc0-1.0 |
juliusbierk/scikit-image | doc/ext/notebook.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 |
marcocaccin/LearningMetaDynamics | grad1dtest.py | 1 | 1626 | from sklearn.kernel_ridge import KernelRidge
import matplotlib.pyplot as plt
import scipy as sp
from gpfit import test_points
def fun(x):
return sp.sin(x)**2 + sp.exp(- sp.cos(x))
def dfun(x):
return 2*sp.sin(x)*sp.cos(x) + sp.exp(-sp.cos(x)) * sp.sin(x)
lengthscale = 1.
gamma = 1 / (2 * lengthscale**2)
k... | gpl-2.0 |
jaeilepp/eggie | mne/utils.py | 1 | 53547 | """Some utility functions"""
from __future__ import print_function
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import warnings
import logging
from distutils.version import LooseVersion
import os
import os.path as op
from functools import wraps
import inspect
fro... | bsd-2-clause |
georgeke/caravel | tests/core_tests.py | 1 | 18555 | """Unit tests for Caravel"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from datetime import datetime
import doctest
import json
import imp
import os
import unittest
from mock import Mock, patch
from flask import... | apache-2.0 |
aringh/odl | examples/solvers/deconvolution_1d.py | 1 | 1605 | """Example of a deconvolution problem with different solvers (CPU)."""
import numpy as np
import matplotlib.pyplot as plt
import scipy.signal
import odl
class Convolution(odl.Operator):
def __init__(self, kernel, adjkernel=None):
self.kernel = kernel
self.adjkernel = (adjkernel if adjkernel is n... | mpl-2.0 |
pypot/scikit-learn | examples/model_selection/plot_learning_curve.py | 250 | 4171 | """
========================
Plotting Learning Curves
========================
On the left side the learning curve of a naive Bayes classifier is shown for
the digits dataset. Note that the training score and the cross-validation score
are both not very good at the end. However, the shape of the curve can be found
in ... | bsd-3-clause |
kurtgeebelen/rawesome | studies/testMheMpc.py | 2 | 5886 | # Copyright 2012-2013 Greg Horn
#
# This file is part of rawesome.
#
# rawesome is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
... | lgpl-3.0 |
OpenBookProjects/ipynb | 101notebook/ipython-rel-2.1.0-examples/Parallel Computing/wave2D/parallelwave-mpi.py | 4 | 6671 | #!/usr/bin/env python
"""
A simple python program of solving a 2D wave equation in parallel.
Domain partitioning and inter-processor communication
are done by an object of class MPIRectPartitioner2D
(which is a subclass of RectPartitioner2D and uses MPI via mpi4py)
An example of running the program is (8 processors, 4... | mit |
hansehe/Wind-Blade-Inspection | Settings/TestData.py | 1 | 15964 | '''
Author: Hans Erik Heggem
Email: hans.erik.heggem@gmail.com
Project: Master's Thesis - Autonomous Inspection Of Wind Blades
Repository: Master's Thesis - CV (Computer Vision)
'''
import glob, warnings, os
'''
@brief Class for getting test sets
Change data sets as preferred to use for testing.
'''
class Test... | mit |
simon-pepin/scikit-learn | sklearn/linear_model/tests/test_coordinate_descent.py | 44 | 22866 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from sys import version_info
import numpy as np
from scipy import interpolate, sparse
from copy import deepcopy
from sklearn.datasets import load_boston
from sklearn.utils.testing ... | bsd-3-clause |
YihaoLu/statsmodels | statsmodels/examples/try_polytrend.py | 33 | 1477 |
from __future__ import print_function
import numpy as np
#import statsmodels.linear_model.regression as smreg
from scipy import special
import statsmodels.api as sm
from statsmodels.datasets.macrodata import data
dta = data.load()
gdp = np.log(dta.data['realgdp'])
from numpy import polynomial
from scipy import spe... | bsd-3-clause |
Nacturne/CoreNLP_copy | python_tools/Commands/rootF1Global.py | 1 | 1591 | import config
import argparse
import pandas as pd
import warnings
from Core import TreeClass
from sklearn import metrics
parser = argparse.ArgumentParser()
parser.add_argument('Original', metavar='original_file', type=str, help="The path of the original file")
parser.add_argument('Predicted', metavar='predicted_file... | gpl-2.0 |
hbwzhsh/pyrallel | pyrallel/mmap_utils.py | 2 | 4036 | """Utilities for Memory Mapping cross validation folds
Author: Olivier Grisel <olivier@ogrisel.com>
Licensed: MIT
"""
import os
from IPython.parallel import interactive
from pyrallel.common import get_host_view
@interactive
def persist_cv_splits(X, y, name=None, n_cv_iter=5, suffix="_cv_%03d.pkl",
... | mit |
pllim/astropy | astropy/modeling/utils.py | 5 | 28585 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This module provides utility functions for the models package.
"""
# pylint: disable=invalid-name
from collections import deque, UserDict
from collections.abc import MutableMapping
from inspect import signature
import numpy as np
import warnings
from... | bsd-3-clause |
derekjchow/models | research/deep_speech/data/download.py | 4 | 7722 | # Copyright 2018 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 |
ortylp/scipy | scipy/signal/spectral.py | 14 | 34751 | """Tools for spectral analysis.
"""
from __future__ import division, print_function, absolute_import
import numpy as np
from scipy import fftpack
from . import signaltools
from .windows import get_window
from ._spectral import lombscargle
import warnings
from scipy._lib.six import string_types
__all__ = ['periodogr... | bsd-3-clause |
Nyker510/scikit-learn | examples/model_selection/plot_train_error_vs_test_error.py | 349 | 2577 | """
=========================
Train error vs Test error
=========================
Illustration of how the performance of an estimator on unseen data (test data)
is not the same as the performance on training data. As the regularization
increases the performance on train decreases while the performance on test
is optim... | bsd-3-clause |
e-koch/VLA_Lband | 14B-088/HI/analysis/higher_moments.py | 1 | 15571 |
from spectral_cube import SpectralCube, Projection
import numpy as np
import matplotlib.pyplot as p
from astropy.io import fits
from astropy.wcs import WCS
import astropy.units as u
import os
from reproject import reproject_interp
from astropy.visualization import AsinhStretch
from astropy.visualization.mpl_normalize ... | mit |
dvro/UnbalancedDataset | examples/under-sampling/plot_nearmiss_3.py | 2 | 1837 | """
==========
Nearmiss 3
==========
An illustration of the nearmiss 3 method.
"""
print(__doc__)
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
# Define some color for the plotting
almost_black = '#262626'
palette = sns.color_palette()
from sklearn.datasets import make_classification
from sklear... | mit |
nok/sklearn-porter | sklearn_porter/utils/Environment.py | 1 | 3826 | # -*- coding: utf-8 -*-
import os
import sys
try:
from shutil import which
except ImportError:
def which(cmd, mode=os.F_OK | os.X_OK, path=None):
"""Given a command, mode, and a PATH string, return the path which
conforms to the given mode on the PATH, or None if there is no such
file.... | mit |
liam2/larray | larray/inout/stata.py | 2 | 1668 | from __future__ import absolute_import, print_function
import pandas as pd
from larray.inout.pandas import from_frame
__all__ = ['read_stata']
def read_stata(filepath_or_buffer, index_col=None, sort_rows=False, sort_columns=False, **kwargs):
r"""
Reads Stata .dta file and returns an Array with the contents... | gpl-3.0 |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/sklearn/neighbors/base.py | 19 | 30908 | """Base and mixin classes for nearest neighbors"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck
# Multi-output support by Arnaud Jol... | mit |
krischer/wfdiff | setup.py | 1 | 2246 | #!/usr/bin/env python
# -*- encoding: utf8 -*-
import glob
import inspect
import io
import os
from setuptools import find_packages
from setuptools import setup
changelog = os.path.join(os.path.dirname(os.path.abspath(
inspect.getfile(inspect.currentframe()))), "CHANGELOG.md")
with open(changelog, "rt") as fh:
... | gpl-3.0 |
3manuek/scikit-learn | sklearn/preprocessing/tests/test_label.py | 48 | 18419 | import numpy as np
from scipy.sparse import issparse
from scipy.sparse import coo_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import dok_matrix
from scipy.sparse import lil_matrix
from sklearn.utils.multiclass import type_of_target
from sklearn.utils.testing impor... | bsd-3-clause |
yl565/statsmodels | statsmodels/iolib/foreign.py | 5 | 42776 | """
Input/Output tools for working with binary data.
The Stata input tools were originally written by Joe Presbrey as part of PyDTA.
You can find more information here http://presbrey.mit.edu/PyDTA
See also
---------
numpy.lib.io
"""
from statsmodels.compat.python import (zip, lzip, lmap, lrange, string_types, long,... | bsd-3-clause |
Hbl15/ThinkStats2 | code/hinc.py | 67 | 1494 | """This file contains code used in "Think Stats",
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
import numpy as np
import pandas
import thinkplot
import thinkstats2
def Clean(s):... | gpl-3.0 |
eggplantbren/Flotsam | src/Python/emcee/TDModel.py | 1 | 4258 | import numpy as np
import numpy.random as rng
import scipy.linalg as la
import matplotlib.pyplot as plt
from Data import Data
class Limits:
"""
A singleton class that just holds prior bounds
"""
@staticmethod
def initialise(data):
# Mean magnitudes
Limits.magMin = data.yMean - 10.*data.yStDev
Limits.magMax ... | gpl-3.0 |
HeraclesHX/scikit-learn | examples/cluster/plot_birch_vs_minibatchkmeans.py | 333 | 3694 | """
=================================
Compare BIRCH and MiniBatchKMeans
=================================
This example compares the timing of Birch (with and without the global
clustering step) and MiniBatchKMeans on a synthetic dataset having
100,000 samples and 2 features generated using make_blobs.
If ``n_clusters... | bsd-3-clause |
anilmuthineni/tensorflow | tensorflow/examples/learn/iris_val_based_early_stopping.py | 62 | 2827 | # 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 |
georgid/sms-tools | lectures/4-STFT/plots-code/blackman-even-odd.py | 24 | 1481 | import matplotlib.pyplot as plt
import numpy as np
from scipy.fftpack import fft, fftshift
from scipy import signal
M = 32
N = 128
hN = N/2
hM = M/2
fftbuffer = np.zeros(N)
w = signal.blackman(M)
plt.figure(1, figsize=(9.5, 6))
plt.subplot(3,2,1)
plt.plot(np.arange(-hM, hM), w, 'b', lw=1.5)
plt.axis([-hM, hM-1,... | agpl-3.0 |
blbarker/spark-tk | python/sparktk/frame/ops/classification_metrics_value.py | 7 | 3082 | # vim: set encoding=utf-8
# Copyright (c) 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 require... | apache-2.0 |
rlnsanz/delft | delft/export_utils.py | 2 | 37130 | # -*- coding: utf-8 -*-
"""
Copyright 2016 Randal S. Olson
This file is part of the TPOT library.
The TPOT library 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 op... | gpl-3.0 |
TimBizeps/BachelorAP | V503_Millikan Versuch/Auswertung.py | 1 | 3001 | import matplotlib as mpl
mpl.use('pgf')
import numpy as np
import scipy.constants as const
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from uncertainties import ufloat
import uncertainties.unumpy as unp
from uncertainties.unumpy import (nominal_values as noms, std_devs as stds)
mpl.rcParams.upd... | gpl-3.0 |
michigraber/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 286 | 2378 | """
=====================================================================
Decision boundary of label propagation versus SVM on the Iris dataset
=====================================================================
Comparison for decision boundary generated on iris dataset
between Label Propagation and SVM.
This demon... | bsd-3-clause |
bharcode/MachineLearning | GEFlightQuest/PythonModule/geflight/summarize/diverted_or_redirected_flights_in_public_leaderboard.py | 3 | 2338 | import csv
import os
import pandas as pd
flight_path = os.path.join(os.environ["DataPath"], "GEFlight")
public_solution_path = os.path.join(flight_path, "Release 6", "FinalEvaluationSolution", "solution_combined.csv")
raw_public_leaderboard_flight_history_path = os.path.join(flight_path, "RawFinalEvaluationSet", "Fli... | gpl-2.0 |
RachitKansal/scikit-learn | sklearn/utils/__init__.py | 79 | 14202 | """
The :mod:`sklearn.utils` module includes various utilities.
"""
from collections import Sequence
import numpy as np
from scipy.sparse import issparse
import warnings
from .murmurhash import murmurhash3_32
from .validation import (as_float_array,
assert_all_finite,
... | bsd-3-clause |
chengsoonong/acton | tests/test_integration.py | 1 | 18921 | #!/usr/bin/env python3
"""
test_integration
----------------------------------
Integration tests.
"""
import sys
sys.path.append("..")
import os.path
import struct
import unittest
import unittest.mock
import acton.cli
import acton.database
import acton.proto.io
import acton.proto.wrappers
import acton.proto.acton... | bsd-3-clause |
SpatialMetabolomics/SM_distributed | tests/test_es_exporter.py | 2 | 10310 | import logging
from datetime import datetime
from unittest.mock import MagicMock, patch
import pandas as pd
import time
from sm.engine import MolecularDB
from sm.engine.es_export import ESExporter, ESIndexManager, DATASET_SEL, ANNOTATIONS_SEL
from sm.engine import DB
from sm.engine.ion_centroids_gen import IonCentroid... | apache-2.0 |
jdrudolph/scikit-bio | skbio/stats/ordination/_redundancy_analysis.py | 8 | 8953 | # ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
# --------------------------------------------... | bsd-3-clause |
QuLogic/specfem3d | EXAMPLES/meshfem3D_examples/cavity/DATA/py/forcesolution_generation.py | 3 | 1297 | import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure, show, axes, sci
from matplotlib import cm, colors
from matplotlib.font_manager import FontProperties
from numpy import amin, amax, ravel
from numpy.random import rand
#****************************************************... | gpl-2.0 |
ushiro/persistlab | persistlab/figitem.py | 1 | 16756 | """
persistlab.figitem
~~~~~~~~~~
This module provides a matplotlib figure manager
to deal with the figure elements as dictionnary elements
:copyright: (c) 2013 by Stephane Henry..
:license: BSD, see LICENSE for more details.
Comments:
~~~~~~~
Ideally it should be possible t... | bsd-3-clause |
vermouthmjl/scikit-learn | examples/bicluster/plot_spectral_coclustering.py | 127 | 1732 | """
==============================================
A demo of the Spectral Co-Clustering algorithm
==============================================
This example demonstrates how to generate a dataset and bicluster it
using the Spectral Co-Clustering algorithm.
The dataset is generated using the ``make_biclusters`` funct... | bsd-3-clause |
hugobowne/scikit-learn | examples/linear_model/plot_polynomial_interpolation.py | 168 | 2088 | #!/usr/bin/env python
"""
========================
Polynomial interpolation
========================
This example demonstrates how to approximate a function with a polynomial of
degree n_degree by using ridge regression. Concretely, from n_samples 1d
points, it suffices to build the Vandermonde matrix, which is n_samp... | bsd-3-clause |
edwintye/pygotools | bin/workingScript/testPoly.py | 1 | 10729 |
## setting up G and h
G = matrix(numpy.append(numpy.append(numpy.eye(2),-numpy.eye(2),axis=0),numpy.array([[-1,1]]),axis=0))
h = matrix([1.0,1.0,0.0,0.0,0.0])
from pyOptimUtil.direct import rectOperation
from pyOptimUtil.direct import polyOperation
boxBounds = [
(0.0,1.0),
(0.0,1.0)
]
sol = polyOpera... | gpl-2.0 |
dssg/wikienergy | disaggregator/build/pandas/pandas/computation/eval.py | 14 | 8348 | #!/usr/bin/env python
"""Top level ``eval`` module.
"""
import tokenize
from pandas.core import common as com
from pandas.computation.expr import Expr, _parsers, tokenize_string
from pandas.computation.scope import _ensure_scope
from pandas.compat import DeepChainMap, builtins
from pandas.computation.engines import _... | mit |
Regenerator/kdnets | lib/processors/shapenet.py | 1 | 7588 | import os
import numpy as np
import pandas as pd
import h5py as h5
def prepare(path2data, path2save, pose='normal'):
raw_label_data = pd.read_csv(path2data + '/train.csv').append(pd.read_csv(path2data + '/val.csv'), ignore_index=True)
label_idx = 0
labelId2label = {}
for labelId in raw_label_data['s... | mit |
renmengye/deep-dashboard | demo/vae.py | 1 | 11546 | """
This code implements VAE (Variational Autoencoder) [1] on MNIST.
Author: Mengye Ren (mren@cs.toronto.edu)
Usage: python vae_mnist.py -logs {path to log folder}
Reference:
[1] D.P. Kingma, M. Welling. Auto-encoding variational Bayes. ICLR 2014.
"""
import cslab_environ
import argparse
import datetime
import logg... | mit |
SerCeMan/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 |
anaderi/lhcb_trigger_ml | tests/test_commonutils.py | 1 | 5043 | from __future__ import division, print_function, absolute_import
import numpy
import pandas
from numpy.random.mtrand import RandomState
from sklearn.metrics.pairwise import pairwise_distances
from hep_ml import commonutils
from hep_ml.commonutils import weighted_percentile, build_normalizer, \
compute_cut_for_effi... | mit |
pypot/scikit-learn | sklearn/covariance/tests/test_graph_lasso.py | 272 | 5245 | """ Test the graph_lasso module.
"""
import sys
import numpy as np
from scipy import linalg
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_less
from sklearn.covariance import (graph_lasso, GraphLasso, GraphLassoCV,
empirical_... | bsd-3-clause |
andrewnc/scikit-learn | benchmarks/bench_plot_fastkmeans.py | 294 | 4676 | from __future__ import print_function
from collections import defaultdict
from time import time
import numpy as np
from numpy import random as nr
from sklearn.cluster.k_means_ import KMeans, MiniBatchKMeans
def compute_bench(samples_range, features_range):
it = 0
results = defaultdict(lambda: [])
chun... | bsd-3-clause |
yavalvas/yav_com | build/matplotlib/doc/mpl_examples/pylab_examples/tricontour_vs_griddata.py | 3 | 1486 | """
Comparison of griddata and tricontour for an unstructured triangular grid.
"""
from __future__ import print_function
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
from numpy.random import uniform, seed
from matplotlib.mlab import griddata
import time
seed(0)
npts = 200
ngridx = 10... | mit |
xiaoxiamii/scikit-learn | sklearn/metrics/scorer.py | 211 | 13141 | """
The :mod:`sklearn.metrics.scorer` submodule implements a flexible
interface for model selection and evaluation using
arbitrary score functions.
A scorer object is a callable that can be passed to
:class:`sklearn.grid_search.GridSearchCV` or
:func:`sklearn.cross_validation.cross_val_score` as the ``scoring`` parame... | bsd-3-clause |
devs1991/test_edx_docmode | venv/lib/python2.7/site-packages/ease/model_creator.py | 2 | 7871 | #Provides interface functions to create and save models
import numpy
import re
import nltk
import sys
from sklearn.feature_extraction.text import CountVectorizer
import pickle
import os
import sklearn.ensemble
from itertools import chain
base_path = os.path.dirname(__file__)
sys.path.append(base_path)
from essay_set... | agpl-3.0 |
rkmaddox/mne-python | tutorials/simulation/80_dics.py | 6 | 12327 | # -*- coding: utf-8 -*-
"""
DICS for power mapping
======================
In this tutorial, we'll simulate two signals originating from two
locations on the cortex. These signals will be sinusoids, so we'll be looking
at oscillatory activity (as opposed to evoked activity).
We'll use dynamic imaging of coherent sourc... | bsd-3-clause |
aavanian/bokeh | examples/plotting/file/burtin.py | 3 | 4763 | from collections import OrderedDict
from math import log, sqrt
import numpy as np
import pandas as pd
from six.moves import cStringIO as StringIO
from bokeh.plotting import figure, show, output_file
antibiotics = """
bacteria, penicillin, streptomycin, neomycin, gram
Mycobacterium tuberculosis... | bsd-3-clause |
gandalfcode/gandalf | tests/grav_tests/freefall.py | 1 | 2263 | #==============================================================================
# freefalltest.py
# Run the freefall collapse test using initial conditions specified in the
# file 'freefall.dat'.
#==============================================================================
from gandalf.analysis.facade import *
from g... | gpl-2.0 |
blink1073/scikit-image | doc/examples/edges/plot_medial_transform.py | 11 | 2257 | """
===========================
Medial axis skeletonization
===========================
The medial axis of an object is the set of all points having more than one
closest point on the object's boundary. It is often called the **topological
skeleton**, because it is a 1-pixel wide skeleton of the object, with the same
... | bsd-3-clause |
zhewang/lcvis | python_scripts/PLV_SDSS/pca_with_period.py | 2 | 2342 | import argparse
import csv
import json
import pickle
import numpy as np
from matplotlib.mlab import PCA
def loadMagData(fileName):
data_file = open(fileName, 'r')
data = json.load(data_file)
mag = np.array(data[0]["mag"])
phase = np.array(data[0]["phase"])
magPeak = 100
phasePeak = -1
for ... | gpl-2.0 |
Myasuka/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 130 | 50966 | # 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
import scipy.sparse as sp
from abc import ABCMeta, abstractmethod
from ... | bsd-3-clause |
jpautom/scikit-learn | sklearn/linear_model/tests/test_base.py | 19 | 12955 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from scipy import linalg
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_almost_e... | bsd-3-clause |
mne-tools/mne-tools.github.io | 0.14/_downloads/plot_raw_objects.py | 15 | 5335 | """
.. _tut_raw_objects
The :class:`Raw <mne.io.RawFIF>` data structure: continuous data
================================================================
"""
from __future__ import print_function
import mne
import os.path as op
from matplotlib import pyplot as plt
###################################################... | bsd-3-clause |
vybstat/scikit-learn | sklearn/utils/metaestimators.py | 283 | 2353 | """Utilities for meta-estimators"""
# Author: Joel Nothman
# Andreas Mueller
# Licence: BSD
from operator import attrgetter
from functools import update_wrapper
__all__ = ['if_delegate_has_method']
class _IffHasAttrDescriptor(object):
"""Implements a conditional property using the descriptor protocol.
... | bsd-3-clause |
IssamLaradji/scikit-learn | sklearn/covariance/tests/test_covariance.py | 28 | 10115 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_alm... | bsd-3-clause |
orbitfold/tardis | tardis/plasma/tests/conftest.py | 1 | 8877 | import os
import numpy as np
import pandas as pd
from astropy import units as u
import pytest
import tardis
from tardis.atomic import AtomData
from tardis.plasma.standard_plasmas import LegacyPlasmaArray
from tardis.plasma.properties import *
# INPUTS
@pytest.fixture
def atomic_data(selected_atoms):
atomic_db_f... | bsd-3-clause |
meduz/scikit-learn | sklearn/tests/test_naive_bayes.py | 72 | 19944 | import pickle
from io import BytesIO
import numpy as np
import scipy.sparse
from sklearn.datasets import load_digits, load_iris
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_val_score
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert... | bsd-3-clause |
puruckertom/ubertool | ubertool/beerex/tests/beerex_process_qaqc.py | 1 | 1380 | from __future__ import division #brings in Python 3.0 mixed type calculation rules
import os
# needs to be run whenever the qaqc csv is updated
csv_path = os.path.join(os.path.dirname(__file__),"beerex_qaqc.csv")
csv_in = os.path.join(os.path.dirname(__file__),"beerex_qaqc_in_transpose.csv")
csv_exp = os.path.join(os... | unlicense |
harisbal/pandas | pandas/tests/indexes/datetimes/test_timezones.py | 2 | 44972 | # -*- coding: utf-8 -*-
"""
Tests for DatetimeIndex timezone-related methods
"""
from datetime import date, datetime, time, timedelta, tzinfo
from distutils.version import LooseVersion
import dateutil
from dateutil.tz import gettz, tzlocal
import numpy as np
import pytest
import pytz
from pandas._libs.tslibs import c... | bsd-3-clause |
cleinias/Homeo | src/Simulator/HomeoGeneralGUI.py | 1 | 59437 | '''
Provides a general interface to control a Homeostat simulation including an unlimited number of units.
It can start and stop a simulation from a GUI, as well as save and graph the simulation's data.
Created on May 5, 2013
@author: stefano
'''
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from Core.Homeost... | gpl-3.0 |
Reagankm/KnockKnock | venv/lib/python3.4/site-packages/matplotlib/sphinxext/ipython_console_highlighting.py | 11 | 4601 | """reST directive for syntax-highlighting ipython interactive sessions.
XXX - See what improvements can be made based on the new (as of Sept 2009)
'pycon' lexer for the python console. At the very least it will give better
highlighted tracebacks.
"""
from __future__ import (absolute_import, division, print_function,
... | gpl-2.0 |
tody411/ColorHistogram | color_histogram/results/hist_1d.py | 2 | 2771 | # -*- coding: utf-8 -*-
# # @package color_histogram.results.hist_1d
#
# Compute 1D color histogram result.
# @author tody
# @date 2015/08/28
import os
import numpy as np
import matplotlib.pyplot as plt
from color_histogram.io_util.image import loadRGB
from color_histogram.cv.image import rgb, to32F
f... | mit |
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