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 |
|---|---|---|---|---|---|
yyjiang/scikit-learn | benchmarks/bench_plot_nmf.py | 206 | 5890 | """
Benchmarks of Non-Negative Matrix Factorization
"""
from __future__ import print_function
from collections import defaultdict
import gc
from time import time
import numpy as np
from scipy.linalg import norm
from sklearn.decomposition.nmf import NMF, _initialize_nmf
from sklearn.datasets.samples_generator import... | bsd-3-clause |
openpathsampling/openpathsampling | openpathsampling/tests/test_pathsimulator.py | 2 | 38311 | from __future__ import division
from __future__ import absolute_import
from builtins import str
from builtins import range
from past.utils import old_div
from builtins import object
from .test_helpers import (raises_with_message_like, data_filename,
CalvinistDynamics, make_1d_traj,
... | mit |
timothy1191xa/project-epsilon-1 | code/utils/scripts/eda.py | 3 | 3524 | """
This script plots some exploratory analysis plots for the raw and filtered data:
- Moisaic of the mean voxels values for each brain slices
Run with:
python eda.py
from this directory
"""
from __future__ import print_function, division
import sys, os, pdb
import numpy as np
import matplotlib.pyplot as ... | bsd-3-clause |
darthcloud/cube64-dx | notes/js_scale.py | 1 | 4921 | #!/usr/bin/env python3
"""Script for generating GC joysticks scaling tables.
--Jacques Gagnon <darthcloud@gmail.com>
"""
from collections import namedtuple
from scipy import stats
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
import numpy as np
from controller_data import CTRL_DATA, Maximum
... | gpl-2.0 |
frank-tancf/scikit-learn | sklearn/gaussian_process/tests/test_gpr.py | 23 | 11915 | """Testing for Gaussian process regression """
# Author: Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Licence: BSD 3 clause
import numpy as np
from scipy.optimize import approx_fprime
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels \
import RBF, Constan... | bsd-3-clause |
Eric89GXL/scikit-learn | sklearn/tests/test_grid_search.py | 7 | 22530 | """
Testing for grid search module (sklearn.grid_search)
"""
from collections import Iterable, Sized
from sklearn.externals.six.moves import cStringIO as StringIO
from sklearn.externals.six.moves import xrange
from itertools import chain, product
import pickle
import sys
import warnings
import numpy as np
import sci... | bsd-3-clause |
equialgo/scikit-learn | sklearn/setup.py | 69 | 3201 | import os
from os.path import join
import warnings
from sklearn._build_utils import maybe_cythonize_extensions
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
from numpy.distutils.system_info import get_info, BlasNotFoundError
import numpy
lib... | bsd-3-clause |
fulmicoton/pylearn2 | pylearn2/models/independent_multiclass_logistic.py | 44 | 2491 | """
Multiclass-classification by taking the max over a set of one-against-rest
logistic classifiers.
"""
__authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googleg... | bsd-3-clause |
LucaDiStasio/thinPlyMechanics | python/analyzeToyaSolution.py | 1 | 6627 | #!/usr/bin/env Python
# -*- coding: utf-8 -*-
'''
=====================================================================================
Copyright (c) 2016-2018 Université de Lorraine & Luleå tekniska universitet
Author: Luca Di Stasio <luca.distasio@gmail.com>
<luca.distasio@ingpec.eu>
This pr... | apache-2.0 |
hnawner/musical-forms | key-meter-id/nets/key-meter-id-rnn.py | 1 | 4597 | #!/usr/bin/env python
from __future__ import division, print_function
import tensorflow as tf
import numpy as np
import k_m_id_utils as utils
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split as tts
from tensorflow.contrib.layers import fully_connected
class RNN:
n_outputs = ... | mit |
mumuwoyou/vnpy | vn.trader/ctaAlgo/FoldStratrgy.py | 1 | 12283 | # encoding: UTF-8
from ctaBase import *
from ctaTemplate import CtaTemplate
import talib
import numpy as np
class FOLDSTRATEGY(CtaTemplate):
"""
策略基本思路是：如果连续两根K线收阳，就在两根K线的最高点回撤
一定的幅度挂多单进场单，止盈为两根K线的最高点，止损为连根K线
的最低点；做空策略相反。
注意：测试策略，切勿实盘。后果自负
"""
className = 'FOLDSTRATEGY'
... | mit |
ryfeus/lambda-packs | Pandas_numpy/source/pandas/util/_doctools.py | 5 | 6816 | import numpy as np
import pandas as pd
import pandas.compat as compat
class TablePlotter(object):
"""
Layout some DataFrames in vertical/horizontal layout for explanation.
Used in merging.rst
"""
def __init__(self, cell_width=0.37, cell_height=0.25, font_size=7.5):
self.cell_width = cell_... | mit |
airanmehr/bio | Scripts/HLI/Tibet/samples.py | 1 | 1117 | import os
import matplotlib as mpl
mpl.use('TkAgg')
import pandas as pd;
import numpy as np;
import seaborn as sns
np.set_printoptions(linewidth=200, precision=5, suppress=True)
import pandas as pd;
from matplotlib.backends.backend_pdf import PdfPages
pd.options.display.max_rows = 50;
pd.options.display.expand_fra... | mit |
RobertABT/heightmap | build/matplotlib/lib/matplotlib/backends/backend_qt4agg.py | 3 | 5765 | """
Render to qt from agg
"""
from __future__ import division, print_function
import os, sys
import ctypes
import matplotlib
from matplotlib.figure import Figure
from backend_agg import FigureCanvasAgg
from backend_qt4 import QtCore, QtGui, FigureManagerQT, FigureCanvasQT,\
show, draw_if_interactive, backend_ve... | mit |
BioroboticsLab/diktya | tests/test_gan.py | 1 | 4589 | # Copyright 2015 Leon Sixt
#
# 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, sof... | apache-2.0 |
jlegendary/scikit-learn | examples/tree/plot_tree_regression.py | 206 | 1476 | """
===================================================================
Decision Tree Regression
===================================================================
A 1D regression with decision tree.
The :ref:`decision trees <tree>` is
used to fit a sine curve with addition noisy observation. As a result, it
learns ... | bsd-3-clause |
DamCB/tyssue | tyssue/io/csv.py | 2 | 1111 | import pandas as pd
import numpy as np
def write_storm_csv(
filename, points, coords=["x", "y", "z"], split_by=None, **csv_args
):
"""
Saves a point cloud array in the storm format
"""
columns = ["frame", "x [nm]", "y [nm]", "z [nm]", "uncertainty_xy", "uncertainty_z"]
points = points.dropna()... | gpl-3.0 |
brianlorenz/COSMOS_IMACS_Redshifts | Data_Conversion/verb_to_txt.py | 1 | 3517 | #Converts the verb files to .txt (eg j7_verb.txt to j7.txt)
###Usage - run verb_to_txt.py 'a6'
#this will convert verb_a6.txt to a6.txt
import numpy as np
from astropy.io import ascii
import sys, os, string
import pandas as pd
letnum = sys.argv[1]
#Location of verb_xx.txt
verbloc = '/Users/blorenz/COSMOS/COSMOSData... | mit |
markslwong/tensorflow | tensorflow/examples/tutorials/word2vec/word2vec_basic.py | 28 | 9485 | # 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 |
draperjames/bokeh | bokeh/charts/builders/chord_builder.py | 7 | 12304 | """This is the Bokeh charts interface. It gives you a high level API
to build complex plot is a simple way.
This is the Chord class which lets you build your Chord charts
just passing the arguments to the Chart class and calling the proper
functions.
"""
# --------------------------------------------------------------... | bsd-3-clause |
FofanovLab/VaST | VaST/analyze.py | 1 | 10882 |
from __future__ import absolute_import, print_function, division
import argparse
import sys
import json
import logging
import os
import ast
import pandas as pd
import numpy as np
from glob import glob
from collections import Counter, defaultdict
from itertools import chain, product, starmap
from utils import file_type... | mit |
bartosh/zipline | zipline/__main__.py | 1 | 9888 | import errno
import os
from functools import wraps
import click
import logbook
import pandas as pd
from six import text_type
from zipline.data import bundles as bundles_module
from zipline.utils.cli import Date, Timestamp
from zipline.utils.run_algo import _run, load_extensions
try:
__IPYTHON__
except NameError:... | apache-2.0 |
PanDAWMS/panda-bigmon-core | core/dashboards/dtctails.py | 1 | 8943 | import pandas as pd
from matplotlib import pyplot as plt
import urllib.request as urllibr
from urllib.error import HTTPError
import json
import datetime
import numpy as np
import os
from sklearn.preprocessing import scale
from core.views import initRequest, setupView, DateEncoder, setCacheData
from django.shortcuts imp... | apache-2.0 |
Clyde-fare/scikit-learn | examples/model_selection/plot_roc_crossval.py | 247 | 3253 | """
=============================================================
Receiver Operating Characteristic (ROC) with cross validation
=============================================================
Example of Receiver Operating Characteristic (ROC) metric to evaluate
classifier output quality using cross-validation.
ROC curv... | bsd-3-clause |
TheChymera/pyMTF | pyMTF.py | 1 | 6039 | #!/usr/bin/env python
from __future__ import division
__author__ = 'Horea Christian'
import Image
import gtk
import numpy as np
from pylab import figure, show, errorbar
import matplotlib.pyplot as plt
from matplotlib import axis
if gtk.pygtk_version < (2,3,90):
print "PyGtk 2.3.90 or later required for Plot-It"
... | gpl-3.0 |
NicovincX2/Battleship | setup.py | 1 | 1287 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from setuptools import setup, find_packages
import os
import io
import naval_battle
here = os.path.abspath(os.path.dirname(__file__))
def read(*filenames, **kwargs):
"""Lit plusieurs fichiers et les assemble.
"""
encoding = kwargs.get('encoding', 'utf-8')
... | gpl-3.0 |
marcocaccin/scikit-learn | sklearn/svm/tests/test_sparse.py | 8 | 13176 | from nose.tools import assert_raises, assert_true, assert_false
import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from sklearn import datasets, svm, linear_model, base
from sklearn.datasets import make_classif... | bsd-3-clause |
lcharleux/compmod | doc/sandbox/ludovic/cuboidTest_pseudohomo.py | 1 | 5515 | from compmod.models import CuboidTest_BC
from abapy import materials
from abapy.misc import load
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
import pickle, copy
import platform
def field_func(outputs, step):
"""
A function that defines the scalar field you want to plot
... | gpl-2.0 |
snnn/tensorflow | tensorflow/python/estimator/canned/linear_testing_utils.py | 3 | 87977 | # Copyright 2017 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 |
jm-begon/scikit-learn | sklearn/grid_search.py | 103 | 36232 | """
The :mod:`sklearn.grid_search` includes utilities to fine-tune the parameters
of an estimator.
"""
from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# ... | bsd-3-clause |
RPGOne/Skynet | scikit-learn-c604ac39ad0e5b066d964df3e8f31ba7ebda1e0e/sklearn/neighbors/tests/test_ball_tree.py | 30 | 9727 | import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors.ball_tree import (BallTree, NeighborsHeap,
simultaneous_sort, kernel_norm,
nodeheap_sort, DTYPE, ITYPE)
from sklearn.neighbors.dist_metrics impo... | bsd-3-clause |
boada/desCluster | mkSurvey/plotting/mk_bettermap.py | 4 | 5280 | import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
import numpy as np
from astLib.astCoords import decimal2hms
import h5py as hdf
def rectangle(m,lon1,lat1,lon2,lat2,ec='0.3',shading=None, step=100, ax=None):
"""Draw a projection correct rectangle on the map. RAmax, DECmax, RAmin,
DECmin is... | mit |
dwhswenson/openpathsampling | openpathsampling/tests/test_histogram.py | 2 | 11957 | from __future__ import division
from __future__ import absolute_import
from past.utils import old_div
from builtins import object
from .test_helpers import assert_items_almost_equal, assert_items_equal
import pytest
import logging
logging.getLogger('openpathsampling.initialization').setLevel(logging.CRITICAL)
logging.g... | mit |
pprett/statsmodels | statsmodels/tsa/base/tests/test_datetools.py | 1 | 3208 | from datetime import datetime
import numpy.testing as npt
from statsmodels.tsa.base.datetools import (_date_from_idx,
_idx_from_dates, date_parser, date_range_str, dates_from_str,
dates_from_range, _infer_freq, _freq_to_pandas)
def test_date_from_idx():
d1 = datetime(2008, 12, 31)
... | bsd-3-clause |
kastnerkyle/ift6268h15 | hw3/plot_it.py | 1 | 1492 | import numpy as np
import matplotlib.pyplot as plt
import sys
def dispims_color(M, border=0, bordercolor=[0.0, 0.0, 0.0], *imshow_args, **imshow_keyargs):
""" Display an array of rgb images.
The input array is assumed to have the shape numimages x numpixelsY x numpixelsX x 3
"""
bordercolor = np.array... | bsd-3-clause |
hlin117/scikit-learn | sklearn/metrics/ranking.py | 25 | 27863 | """Metrics to assess performance on classification task given scores
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.... | bsd-3-clause |
comocheng/RMG-Py | rmgpy/cantherm/main.py | 9 | 10533 | #!/usr/bin/env python
# encoding: utf-8
################################################################################
#
# RMG - Reaction Mechanism Generator
#
# Copyright (c) 2002-2009 Prof. William H. Green (whgreen@mit.edu) and the
# RMG Team (rmg_dev@mit.edu)
#
# Permission is hereby granted, free of cha... | mit |
rahuldhote/scikit-learn | sklearn/decomposition/pca.py | 192 | 23117 | """ Principal Component Analysis
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Michael Eickenberg <michael.eickenberg@inria.fr>
#
# Lice... | bsd-3-clause |
FCP-INDI/nipype | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 10 | 7893 | from __future__ import absolute_import
import re
import inspect
import textwrap
import pydoc
import sphinx
from .docscrape import NumpyDocString, FunctionDoc, ClassDoc
from nipype.external.six import string_types
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config={}):
self.use_plo... | bsd-3-clause |
pyspace/test | pySPACE/missions/nodes/sink/classification_performance_sink.py | 1 | 55361 | # This Python file uses the following encoding: utf-8
# The upper line is needed for one comment in this module.
""" Calculate performance measures from classification results and store them
All performance sink nodes interface to the
:mod:`~pySPACE.resources.dataset_defs.metric` datasets, where the final metric value... | gpl-3.0 |
robbymeals/scikit-learn | sklearn/tests/test_kernel_approximation.py | 244 | 7588 | import numpy as np
from scipy.sparse import csr_matrix
from sklearn.utils.testing import assert_array_equal, assert_equal, assert_true
from sklearn.utils.testing import assert_not_equal
from sklearn.utils.testing import assert_array_almost_equal, assert_raises
from sklearn.utils.testing import assert_less_equal
from ... | bsd-3-clause |
keskitalo/healpy | doc/create_images.py | 3 | 1125 | import healpy as hp
import numpy as np
import matplotlib.pyplot as plt
SIZE = 400
DPI = 60
m = np.arange(hp.nside2npix(32))
hp.mollview(m, nest=True, xsize=SIZE, title="Mollview image NESTED")
plt.savefig("static/moll_nside32_nest.png", dpi=DPI)
hp.mollview(m, nest=False, xsize=SIZE, title="Mollview image RING")
plt... | gpl-2.0 |
rspavel/spack | var/spack/repos/builtin/packages/py-umi-tools/package.py | 5 | 1429 | # Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class PyUmiTools(PythonPackage):
"""Tools for handling Unique Molecular Identifiers in NGS data ... | lgpl-2.1 |
georgesung/ssd_tensorflow_traffic_sign_detection | train.py | 2 | 7894 | '''
Train the model on dataset
'''
import tensorflow as tf
from settings import *
from model import SSDModel
from model import ModelHelper
import numpy as np
from sklearn.model_selection import train_test_split
import cv2
import math
import os
import time
import pickle
from PIL import Image
def next_batch(X, y_conf, ... | mit |
saketkc/statsmodels | statsmodels/graphics/functional.py | 31 | 14477 | """Module for functional boxplots."""
from statsmodels.compat.python import combinations, range
import numpy as np
from scipy import stats
from scipy.misc import factorial
from . import utils
__all__ = ['fboxplot', 'rainbowplot', 'banddepth']
def fboxplot(data, xdata=None, labels=None, depth=None, method='MBD',
... | bsd-3-clause |
wathen/PhD | MHD/FEniCS/MHD/Stabilised/SaddlePointForm/Test/GeneralisedEigen/GeneralisedEigenvalues.py | 2 | 3030 | import scipy.sparse as sp
import petsc4py
import sys
petsc4py.init(sys.argv)
from petsc4py import PETSc
import CheckPetsc4py as CP
import MatrixOperations as MO
import matplotlib.pylab as plt
from scipy.linalg import eigvals
def IndexSet(W):
if str(W.__class__).find('list') == -1:
n = W.num_sub_spaces()
... | mit |
henrykironde/scikit-learn | benchmarks/bench_multilabel_metrics.py | 276 | 7138 | #!/usr/bin/env python
"""
A comparison of multilabel target formats and metrics over them
"""
from __future__ import division
from __future__ import print_function
from timeit import timeit
from functools import partial
import itertools
import argparse
import sys
import matplotlib.pyplot as plt
import scipy.sparse as... | bsd-3-clause |
earlbellinger/asteroseismology | misc/ce.py | 1 | 3716 | import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
#import pandas as pd
n, l, nu, dnu = np.loadtxt('../regression/data/16CygB-freqs.dat', skiprows=1).T
def normalize(x):
return (x-np.min(x))/(np.max(x)-np.min(x))
plt.figure()
xs = normalize(nu%234)
ys = nor... | gpl-2.0 |
cbertinato/pandas | pandas/tests/io/parser/test_na_values.py | 1 | 14002 | """
Tests that NA values are properly handled during
parsing for all of the parsers defined in parsers.py
"""
from io import StringIO
import numpy as np
import pytest
from pandas import DataFrame, Index, MultiIndex
import pandas.util.testing as tm
import pandas.io.common as com
def test_string_nas(all_parsers):
... | bsd-3-clause |
materialsproject/MPContribs | mpcontribs-portal/mpcontribs/users/dilute_solute_diffusion/pre_submission.py | 1 | 10916 | import os, json, requests, sys
from pandas import read_excel, isnull, ExcelWriter, Series
from mpcontribs.io.core.recdict import RecursiveDict
from mpcontribs.io.core.utils import clean_value, nest_dict
from mpcontribs.io.archieml.mpfile import MPFile
from pymatgen.ext.matproj import MPRester
project = "dilute_solute_... | mit |
Achuth17/scikit-learn | examples/tree/plot_iris.py | 271 | 2186 | """
================================================================
Plot the decision surface of a decision tree on the iris dataset
================================================================
Plot the decision surface of a decision tree trained on pairs
of features of the iris dataset.
See :ref:`decision tree ... | bsd-3-clause |
exa-analytics/exatomic | exatomic/va/va.py | 2 | 41588 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2020, Exa Analytics Development Team
# Distributed under the terms of the Apache License 2.0
"""
Vibrational Averaging
#########################
Collection of classes for VA program
"""
import numpy as np
import pandas as pd
import glob
import re
import os
from exa.util.cons... | apache-2.0 |
heliopython/heliopy | heliopy/data/util.py | 1 | 13179 | """
Utility functions for data downloading.
**Note**: these methods are liable to change at any time.
"""
import abc
import collections as coll
import datetime as dt
import io
import logging
import os
import pathlib as path
import re
import shutil
import sys
import urllib.error as urlerror
import urllib.request as url... | gpl-3.0 |
myuuuuun/NumericalCalculation | chapter2/chap2.py | 1 | 11780 | #!/usr/bin/python
#-*- encoding: utf-8 -*-
"""
Copyright (c) 2015 @myuuuuun
https://github.com/myuuuuun/NumericalCalculation
This software is released under the MIT License.
"""
from __future__ import division, print_function
import math
import numpy as np
import functools
import sys
import types
import matplotlib.pyp... | mit |
vogelsgesang/checkmate | checkmate/contrib/plugins/git/test/lib/test_repository.py | 3 | 4705 | """
This file is part of checkmate, a meta code checker written in Python.
Copyright (C) 2015 Andreas Dewes, QuantifiedCode UG
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3... | agpl-3.0 |
rishikksh20/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 25 | 16022 | from __future__ import division
from collections import defaultdict
from functools import partial
import numpy as np
import scipy.sparse as sp
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing imp... | bsd-3-clause |
fyffyt/scikit-learn | examples/ensemble/plot_gradient_boosting_regression.py | 227 | 2520 | """
============================
Gradient Boosting regression
============================
Demonstrate Gradient Boosting on the Boston housing dataset.
This example fits a Gradient Boosting model with least squares loss and
500 regression trees of depth 4.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prett... | bsd-3-clause |
Obus/scikit-learn | examples/linear_model/plot_ridge_path.py | 254 | 1655 | """
===========================================================
Plot Ridge coefficients as a function of the regularization
===========================================================
Shows the effect of collinearity in the coefficients of an estimator.
.. currentmodule:: sklearn.linear_model
:class:`Ridge` Regressi... | bsd-3-clause |
ACarfi/Regularization-networks | regularizationNetworks/holdoutCVKernRLS.py | 1 | 3384 | import numpy as np
from regularizedKernLSTrain import regularizedkernlstrain
from regularizedKernLSTest import regularizedkernlstest
def holdoutcvkernrls(x, y, kernel, perc, nrip, intlambda, intkerpar):
'''
Input:
xtr: the training examples
ytr: the training labels
kernel: the kernel function... | mit |
jougs/nest-simulator | pynest/nest/tests/test_spatial/test_plotting.py | 12 | 5748 | # -*- coding: utf-8 -*-
#
# test_plotting.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 |
shikhardb/scikit-learn | sklearn/calibration.py | 12 | 18774 | """Calibration of predicted probabilities."""
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Balazs Kegl <balazs.kegl@gmail.com>
# Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Mathieu Blondel <mathieu@mblondel.org>
#
# License: BSD 3 clause
from __future__ impo... | bsd-3-clause |
ResourceHog/POMDPCapstone | simulator.py | 1 | 15092 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 13 16:48:10 2017
@author: ECOWIZARD
"""
###########################################
# Suppress matplotlib user warnings
# Necessary for newer version of matplotlib
import warnings
warnings.filterwarnings("ignore", category = UserWarning, module = "matplotlib")... | gpl-3.0 |
mindriot101/bokeh | examples/plotting/file/elements.py | 5 | 1855 | import pandas as pd
from bokeh.models import ColumnDataSource, LabelSet
from bokeh.plotting import figure, show, output_file
from bokeh.sampledata.periodic_table import elements
elements = elements.copy()
elements = elements[elements["atomic number"] <= 82]
elements = elements[~pd.isnull(elements["melting point"])]
m... | bsd-3-clause |
weissercn/learningml | learningml/GoF/p_value_scoring_object.py | 1 | 14168 | from __future__ import print_function
import sys
import numpy as np
from scipy import stats
import adaptive_binning_chisquared_2sam
def weisser_searchsorted(l_test1, l_test2):
l_test1, l_test2 = np.array(l_test1), np.array(l_test2)
#print("l_test1 : ", l_test1)
l_tot = np.sort(np.append(l_test... | mit |
caidongyun/Dato-Core | src/unity/python/graphlab/data_structures/sgraph.py | 13 | 58501 | """
.. warning:: This product is currently in a beta release. The API reference is
subject to change.
This package defines the GraphLab Create SGraph, Vertex, and Edge objects. The SGraph
is a directed graph, consisting of a set of Vertex objects and Edges that
connect pairs of Vertices. The methods in this module are... | agpl-3.0 |
mantidproject/mantid | qt/python/mantidqt/widgets/plotconfigdialog/test/test_apply_all_properties.py | 3 | 18083 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2019 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 +
# T... | gpl-3.0 |
alexeyum/scikit-learn | benchmarks/bench_covertype.py | 57 | 7378 | """
===========================
Covertype dataset benchmark
===========================
Benchmark stochastic gradient descent (SGD), Liblinear, and Naive Bayes, CART
(decision tree), RandomForest and Extra-Trees on the forest covertype dataset
of Blackard, Jock, and Dean [1]. The dataset comprises 581,012 samples. It ... | bsd-3-clause |
lht142934/trading-with-python | cookbook/getDataFromYahooFinance.py | 77 | 1391 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 16 18:37:23 2011
@author: jev
"""
from urllib import urlretrieve
from urllib2 import urlopen
from pandas import Index, DataFrame
from datetime import datetime
import matplotlib.pyplot as plt
sDate = (2005,1,1)
eDate = (2011,10,1)
symbol = 'SPY'
fNa... | bsd-3-clause |
jswoboda/MahaliPlotting | makeTECtimeplot.py | 1 | 1446 | #!/usr/bin/env python
"""
Created on Thu Mar 3 14:45:35 2016
@author: swoboj
"""
import os, glob,getopt,sys
import scipy as sp
import matplotlib
matplotlib.use('Agg') # for use where you're running on a command line
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from GeoData.plotting import scatt... | mit |
luigift/pybrain | examples/supervised/evolino/superimposed_sine.py | 25 | 3496 | from __future__ import print_function
#!/usr/bin/env python
__author__ = 'Michael Isik'
from pylab import plot, show, ion, cla, subplot, title, figlegend, draw
import numpy
from pybrain.structure.modules.evolinonetwork import EvolinoNetwork
from pybrain.supervised.trainers.evolino import EvolinoTrainer
from l... | bsd-3-clause |
ithemal/Ithemal | learning/pytorch/data/data.py | 1 | 2131 | #main data file
import numpy as np
import common_libs.utilities as ut
import random
import torch.nn as nn
import torch.autograd as autograd
import torch.optim as optim
import torch
import matplotlib.pyplot as plt
class Data(object):
"""
Main data object which extracts data from a database, partition it and ... | mit |
cybernet14/scikit-learn | sklearn/tree/tree.py | 59 | 34839 | """
This module gathers tree-based methods, including decision, regression and
randomized trees. Single and multi-output problems are both handled.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Da... | bsd-3-clause |
abhishekgahlot/scikit-learn | examples/linear_model/plot_sgd_comparison.py | 167 | 1659 | """
==================================
Comparing various online solvers
==================================
An example showing how different online solvers perform
on the hand-written digits dataset.
"""
# Author: Rob Zinkov <rob at zinkov dot com>
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot a... | bsd-3-clause |
hugobowne/scikit-learn | sklearn/neural_network/tests/test_mlp.py | 46 | 18585 | """
Testing for Multi-layer Perceptron module (sklearn.neural_network)
"""
# Author: Issam H. Laradji
# Licence: BSD 3 clause
import sys
import warnings
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_equal
from sklearn.datasets import load_digits, load_boston
from sklearn.datasets i... | bsd-3-clause |
liyu1990/sklearn | sklearn/utils/tests/test_estimator_checks.py | 69 | 3894 | import scipy.sparse as sp
import numpy as np
import sys
from sklearn.externals.six.moves import cStringIO as StringIO
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.utils.testing import assert_raises_regex, assert_true
from sklearn.utils.estimator_checks import check_estimator
from sklearn.utils.... | bsd-3-clause |
BorisJeremic/Real-ESSI-Examples | analytic_solution/test_cases/Contact/Stress_Based_Contact_Verification/SoftContact_ElPPlShear/Shear_Zone_Length/SZ_h_1e3/Normal_Stress_Plot.py | 72 | 2800 | #!/usr/bin/python
import h5py
import matplotlib.pylab as plt
import matplotlib as mpl
import sys
import numpy as np;
import matplotlib;
import math;
from matplotlib.ticker import MaxNLocator
plt.rcParams.update({'font.size': 28})
# set tick width
mpl.rcParams['xtick.major.size'] = 10
mpl.rcParams['xtick.major.width']... | cc0-1.0 |
bkomboz/pymltk | pymltk/exploration.py | 1 | 6123 | # imports
import numpy as np
import pandas as pd
import dask.dataframe as dd
import matplotlib.pyplot as plt
from . import utils
# functions
def summarize(data=None, features=None, size=5,
digits=3, as_df=False, verbose=True, **kwargs):
"""
Summarize features of a given pandas/dask dataframe.
... | apache-2.0 |
Adai0808/scikit-learn | examples/mixture/plot_gmm_sin.py | 248 | 2747 | """
=================================
Gaussian Mixture Model Sine Curve
=================================
This example highlights the advantages of the Dirichlet Process:
complexity control and dealing with sparse data. The dataset is formed
by 100 points loosely spaced following a noisy sine curve. The fit by
the GMM... | bsd-3-clause |
nhzandi/openface | util/align-dlib.py | 12 | 6566 | #!/usr/bin/env python2
#
# Copyright 2015-2016 Carnegie Mellon University
#
# 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 |
AlexanderFabisch/scikit-learn | examples/covariance/plot_mahalanobis_distances.py | 348 | 6232 | r"""
================================================================
Robust covariance estimation and Mahalanobis distances relevance
================================================================
An example to show covariance estimation with the Mahalanobis
distances on Gaussian distributed data.
For Gaussian dis... | bsd-3-clause |
shahankhatch/scikit-learn | sklearn/tests/test_cross_validation.py | 29 | 46740 | """Test the cross_validation module"""
from __future__ import division
import warnings
import numpy as np
from scipy.sparse import coo_matrix
from scipy.sparse import csr_matrix
from scipy import stats
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.test... | bsd-3-clause |
rstoneback/pysat | setup.py | 2 | 3859 | """A setuptools based setup module.
See:
https://packaging.python.org/en/latest/distributing.html
https://github.com/pypa/sampleproject
"""
# Always prefer setuptools over distutils
from setuptools import setup
# To use a consistent encoding
import codecs
import os
import sys
here = os.path.abspath(os.path.dirname(__... | bsd-3-clause |
florentchandelier/zipline | zipline/utils/calendars/us_holidays.py | 6 | 4015 | from pandas import (
Timestamp,
DateOffset,
date_range,
)
from pandas.tseries.holiday import (
Holiday,
sunday_to_monday,
nearest_workday,
)
from dateutil.relativedelta import (
MO,
TH
)
from pandas.tseries.offsets import Day
from zipline.utils.calendars.trading_calendar import (
... | apache-2.0 |
markslwong/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/dataframe_test.py | 62 | 3753 | # 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 |
chris-ch/cointeg | src/mktdatadb/__init__.py | 1 | 7663 | from collections import OrderedDict
from decimal import Decimal
import glob
import logging
import os
from urllib.parse import quote, unquote
from zipfile import ZipFile
from datetime import timedelta, datetime
import itertools
import pandas
import pytz
__author__ = 'Christophe'
ON_TIME_NYSEARCA = '093000'
OFF_TIME_NY... | gpl-3.0 |
zorojean/scikit-learn | benchmarks/bench_sgd_regression.py | 283 | 5569 | """
Benchmark for SGD regression
Compares SGD regression against coordinate descent and Ridge
on synthetic data.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
# License: BSD 3 clause
import numpy as np
import pylab as pl
import gc
from time import time
from sklearn.linear_model i... | bsd-3-clause |
RomainBrault/scikit-learn | examples/gaussian_process/plot_compare_gpr_krr.py | 84 | 5205 | """
==========================================================
Comparison of kernel ridge and Gaussian process regression
==========================================================
Both kernel ridge regression (KRR) and Gaussian process regression (GPR) learn
a target function by employing internally the "kernel trick... | bsd-3-clause |
anntzer/scikit-learn | sklearn/inspection/tests/test_permutation_importance.py | 5 | 19332 | import pytest
import numpy as np
from numpy.testing import assert_allclose
from sklearn.compose import ColumnTransformer
from sklearn.datasets import load_diabetes
from sklearn.datasets import load_iris
from sklearn.datasets import make_classification
from sklearn.datasets import make_regression
from sklearn.dummy im... | bsd-3-clause |
ScienceStacks/SciSheets | mysite/scisheets/plugins/test_groupBy.py | 2 | 3305 | """ Tests for groupBy. """
from scisheets.core.helpers_test import TEST_DIR
from groupBy import groupBy
from roundValues import roundValues
import os
import pandas as pd
import numpy as np
import pickle
import unittest
CAT1 = ['a', 'a', 'b', 'b']
CAT2 = ['x', 'y', 'x', 'y']
CAT1_LIST = list(CAT1)
CAT1_LIST.extend(CAT... | apache-2.0 |
bert9bert/statsmodels | statsmodels/graphics/tests/test_boxplots.py | 3 | 2315 | import numpy as np
from numpy.testing import dec
from statsmodels.graphics.boxplots import violinplot, beanplot
from statsmodels.datasets import anes96
try:
import matplotlib.pyplot as plt
have_matplotlib = True
except:
have_matplotlib = False
@dec.skipif(not have_matplotlib)
def test_violinplot_beanpl... | bsd-3-clause |
mlperf/training_results_v0.7 | Fujitsu/benchmarks/resnet/implementations/implementation_open/mxnet/example/ssd/dataset/pycocotools/coco.py | 11 | 17747 | __author__ = 'tylin'
__version__ = '2.0'
# Interface for accessing the Microsoft COCO dataset.
# Microsoft COCO is a large image dataset designed for object detection,
# segmentation, and caption generation. pycocotools is a Python API that
# assists in loading, parsing and visualizing the annotations in COCO.
# Pleas... | apache-2.0 |
cwu2011/scikit-learn | sklearn/ensemble/gradient_boosting.py | 126 | 65552 | """Gradient Boosted Regression Trees
This module contains methods for fitting gradient boosted regression trees for
both classification and regression.
The module structure is the following:
- The ``BaseGradientBoosting`` base class implements a common ``fit`` method
for all the estimators in the module. Regressio... | bsd-3-clause |
jjunell/paparazzi | sw/airborne/test/ahrs/ahrs_utils.py | 86 | 4923 | #! /usr/bin/env python
# Copyright (C) 2011 Antoine Drouin
#
# This file is part of Paparazzi.
#
# Paparazzi is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2, or (at your option)
# any later ... | gpl-2.0 |
ambikeshwar1991/gnuradio-3.7.4 | gr-digital/examples/berawgn.py | 17 | 4897 | #!/usr/bin/env python
#
# Copyright 2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your optio... | gpl-3.0 |
nextgenusfs/amptk | amptk/amptk.py | 1 | 46407 | #!/usr/bin/env python
from __future__ import (absolute_import, division,
print_function, unicode_literals)
import sys
import os
import importlib
from natsort import natsorted
from amptk import amptklib
from pkg_resources import get_distribution
__version__ = get_distribution('amptk').version
d... | bsd-2-clause |
CforED/Machine-Learning | doc/sphinxext/gen_rst.py | 106 | 40198 | """
Example generation for the scikit learn
Generate the rst files for the examples by iterating over the python
example files.
Files that generate images should start with 'plot'
"""
from __future__ import division, print_function
from time import time
import ast
import os
import re
import shutil
import traceback
i... | bsd-3-clause |
tgsmith61591/smrt | smrt/balance/tests/test_smote.py | 1 | 1656 | # -*- coding: utf-8 -*-
#
# Author: Taylor Smith <taylor.smith@alkaline-ml.com>
#
# Test the SMOTE balancer
from __future__ import division, absolute_import, division
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from smrt.testing import load_imbalanced_mnist
from sklearn.datasets import loa... | bsd-3-clause |
verdverm/pypge | experiments/01_baseline/thegp.py | 1 | 6425 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from sklearn.metrics import r2_score
import data as DATA
import operator
import math
import random
import numpy
import multiprocessing
from deap import algorithms
fro... | mit |
kyleabeauchamp/HMCNotes | code/obsolete/analyze_inefficiency_alanine.py | 1 | 2886 | import statsmodels.api as sm
import schwalbe_couplings
import mdtraj as md
import msmbuilder.decomposition, msmbuilder.featurizer, msmbuilder.msm
import pymbar
import pandas as pd
lag_time = 25
filename0 = "./data/mixed_alanineexplicit_LangevinIntegrator_2.000_0.%s"
#filename1 = "./data/mixed_alanineexplicit_XCGHMCRE... | gpl-2.0 |
jaidevd/scikit-learn | examples/linear_model/plot_sgd_comparison.py | 112 | 1819 | """
==================================
Comparing various online solvers
==================================
An example showing how different online solvers perform
on the hand-written digits dataset.
"""
# Author: Rob Zinkov <rob at zinkov dot com>
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot a... | bsd-3-clause |
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