repo_name stringlengths 6 112 | path stringlengths 4 204 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 714 810k | license stringclasses 15
values |
|---|---|---|---|---|---|
bovee/Aston | aston/tracefile/__init__.py | 1 | 7942 | '''
Classes that can open chromatographic files and return
info from them or Traces/Chromatograms.
'''
import re
import struct
import numpy as np
from aston.trace import Chromatogram, Trace
from aston.tracefile.mime import get_mimetype, tfclasses
def find_offset(f, search_str, hint=None):
if hint is None:
... | bsd-3-clause |
rajat1994/scikit-learn | sklearn/linear_model/tests/test_coordinate_descent.py | 114 | 25281 | # 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 |
andim/scipydirect | examples/SH.py | 1 | 1031 | #!/usr/bin/python
"""
Solve the 2D Shubert function.
"""
from __future__ import division
from scipydirect import minimize
import numpy as np
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import cm
def obj(x):
"""Two Dimensional Shubert Function"""
j = np.arange(1... | mit |
samyachour/EKG_Analysis | wave.py | 1 | 19645 | import pywt
import numpy as np
import pandas as pd
import scipy.io as sio
from biosppy.signals import ecg
import scipy
from detect_peaks import detect_peaks as detect_peaks_orig
def getRPeaks(data, sampling_rate=300.):
"""
R peak detection in 1 dimensional ECG wave
Parameters
----------
data : arr... | gpl-3.0 |
glennq/scikit-learn | sklearn/linear_model/passive_aggressive.py | 28 | 11542 | # Authors: Rob Zinkov, Mathieu Blondel
# License: BSD 3 clause
from .stochastic_gradient import BaseSGDClassifier
from .stochastic_gradient import BaseSGDRegressor
from .stochastic_gradient import DEFAULT_EPSILON
class PassiveAggressiveClassifier(BaseSGDClassifier):
"""Passive Aggressive Classifier
Read mor... | bsd-3-clause |
thomaslima/PySpice | PySpice/Probe/Plot.py | 1 | 1745 | ####################################################################################################
#
# PySpice - A Spice Package for Python
# Copyright (C) 2014 Fabrice Salvaire
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published... | gpl-3.0 |
RobertABT/heightmap | build/matplotlib/examples/event_handling/poly_editor.py | 6 | 5377 | """
This is an example to show how to build cross-GUI applications using
matplotlib event handling to interact with objects on the canvas
"""
import numpy as np
from matplotlib.lines import Line2D
from matplotlib.artist import Artist
from matplotlib.mlab import dist_point_to_segment
class PolygonInteractor:
"""
... | mit |
chetan51/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/ticker.py | 69 | 37420 | """
Tick locating and formatting
============================
This module contains classes to support completely configurable tick
locating and formatting. Although the locators know nothing about
major or minor ticks, they are used by the Axis class to support major
and minor tick locating and formatting. Generic t... | gpl-3.0 |
BonexGu/Blik2D-SDK | Blik2D/addon/tensorflow-1.2.1_for_blik/tensorflow/examples/tutorials/input_fn/boston.py | 51 | 2709 | # 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... | mit |
tjhunter/karps | python/karps/row.py | 1 | 8926 | """ Utilities to express rows of data with Karps.
"""
import pandas as pd
from .proto import types_pb2
from .proto import row_pb2
from .types import *
__all__ = ['CellWithType', 'as_cell', 'as_python_object', 'as_pandas_object']
class CellWithType(object):
""" A cell of data, with its type information.
This is ... | apache-2.0 |
timsnyder/bokeh | bokeh/models/tests/test_mappers.py | 1 | 4293 | #-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2019, Anaconda, Inc., and Bokeh Contributors.
# All rights reserved.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#-------------------------------------------------------------------... | bsd-3-clause |
cogeorg/BlackRhino | examples/firesales_simple/networkx/readwrite/tests/test_gml.py | 35 | 3099 | #!/usr/bin/env python
import io
from nose.tools import *
from nose import SkipTest
import networkx
class TestGraph(object):
@classmethod
def setupClass(cls):
global pyparsing
try:
import pyparsing
except ImportError:
try:
import matplotlib.pyparsi... | gpl-3.0 |
DougBurke/astropy | astropy/visualization/wcsaxes/grid_paths.py | 2 | 3885 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from matplotlib.lines import Path
from ...coordinates.angle_utilities import angular_separation
# Tolerance for WCS round-tripping
ROUND_TRIP_TOL = 1e-1
# Tolerance for discontinuities relative to the median
DISCONT_FACTOR = 10.
... | bsd-3-clause |
EtienneCmb/tensorpac | tensorpac/utils.py | 1 | 29055 | """Utility functions."""
import logging
import numpy as np
from scipy.signal import periodogram
from tensorpac.methods.meth_pac import _kl_hr
from tensorpac.pac import _PacObj, _PacVisual
from tensorpac.io import set_log_level
from matplotlib.gridspec import GridSpec
import matplotlib.pyplot as plt
logger = logging... | bsd-3-clause |
yunfeilu/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 181 | 15664 | 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 |
mverzett/rootpy | docs/sphinxext/numpydoc/plot_directive.py | 5 | 19693 | """
A special directive for generating a matplotlib plot.
.. warning::
This is a hacked version of plot_directive.py from Matplotlib.
It's very much subject to change!
Usage
-----
Can be used like this::
.. plot:: examples/example.py
.. plot::
import matplotlib.pyplot as plt
plt.plot... | gpl-3.0 |
tswast/google-cloud-python | language/docs/conf.py | 2 | 11912 | # -*- coding: utf-8 -*-
#
# google-cloud-language documentation build configuration file
#
# 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 configuration values have a default; values ... | apache-2.0 |
qifeigit/scikit-learn | examples/linear_model/plot_ransac.py | 250 | 1673 | """
===========================================
Robust linear model estimation using RANSAC
===========================================
In this example we see how to robustly fit a linear model to faulty data using
the RANSAC algorithm.
"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import ... | bsd-3-clause |
toastedcornflakes/scikit-learn | sklearn/linear_model/tests/test_least_angle.py | 42 | 20925 | from nose.tools import assert_equal
import numpy as np
from scipy import linalg
from sklearn.model_selection import train_test_split
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import... | bsd-3-clause |
pierrelb/RMG-Py | rmgpy/tools/plot.py | 2 | 18806 | import matplotlib as mpl
# Force matplotlib to not use any Xwindows backend.
# This must be called before pylab, matplotlib.pyplot, or matplotlib.backends is imported
mpl.use('Agg')
import matplotlib.pyplot as plt
from rmgpy.tools.data import GenericData
def parseCSVData(csvFile):
"""
This function par... | mit |
cuiwei0322/cost_analysis | tall_building_zero_attack_angle_cost_analysis/Result/peak_ng.py | 1 | 2728 | import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib
from matplotlib import cm
from matplotlib import pyplot as plt
from itertools import product, combinations
from matplotlib import rc
from matplotlib.font_manager import FontProperties
font_size = 8
rc('font',**{'family':'serif','serif':['Times... | apache-2.0 |
TariqAHassan/BioVida | biovida/images/models/template_matching.py | 1 | 13537 | # coding: utf-8
"""
Template Matching
~~~~~~~~~~~~~~~~~
"""
import numpy as np
from scipy.misc import imread
from scipy.misc import imresize
from skimage.feature import match_template
# Notes:
# See: http://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.match_template.
# Here, t... | bsd-3-clause |
eusoubrasileiro/fatiando_seismic | cookbook/seismic_wavefd_love_wave.py | 9 | 2602 | """
Seismic: 2D finite difference simulation of elastic SH wave propagation in a
medium with a discontinuity (i.e., Moho), generating Love waves.
"""
import numpy as np
from matplotlib import animation
from fatiando import gridder
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the parameters of... | bsd-3-clause |
freeman-lab/dask | dask/dataframe/utils.py | 1 | 3562 | import pandas as pd
import numpy as np
from collections import Iterator
import toolz
def shard_df_on_index(df, divisions):
""" Shard a DataFrame by ranges on its index
Example
-------
>>> df = pd.DataFrame({'a': [0, 10, 20, 30, 40], 'b': [5, 4 ,3, 2, 1]})
>>> df
a b
0 0 5
1 ... | bsd-3-clause |
JsNoNo/scikit-learn | sklearn/metrics/pairwise.py | 49 | 44088 | # -*- coding: utf-8 -*-
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Robert Layton <robertlayton@gmail.com>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Philippe Gervais <philippe.gervais@inria.fr>
# Lars Buitinck ... | bsd-3-clause |
loli/sklearn-ensembletrees | examples/manifold/plot_manifold_sphere.py | 1 | 4619 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=============================================
Manifold Learning methods on a severed sphere
=============================================
An application of the different :ref:`manifold` techniques
on a spherical data-set. Here one can see the use of
dimensionality reducti... | bsd-3-clause |
calico/basenji | bin/basenji_data.py | 1 | 31215 | #!/usr/bin/env python
# Copyright 2017 Calico 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agr... | apache-2.0 |
OshynSong/scikit-learn | examples/manifold/plot_manifold_sphere.py | 258 | 5101 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=============================================
Manifold Learning methods on a severed sphere
=============================================
An application of the different :ref:`manifold` techniques
on a spherical data-set. Here one can see the use of
dimensionality reducti... | bsd-3-clause |
sarmstr5/kaggle_intel_mobleODT_cervix_classification | src/starting_with_keras.py | 1 | 5420 | from PIL import ImageFilter, ImageStat, Image, ImageDraw
from multiprocessing import Pool, cpu_count
from sklearn.preprocessing import LabelEncoder
import pandas as pd
import numpy as np
import glob
import cv2
import processing_images
from keras.wrappers.scikit_learn import KerasClassifier
from keras.models import Seq... | mit |
xdnian/pyml | code/optional-py-scripts/ch07.py | 4 | 19178 | # Sebastian Raschka, 2015 (http://sebastianraschka.com)
# Python Machine Learning - Code Examples
#
# Chapter 7 - Combining Different Models for Ensemble Learning
#
# S. Raschka. Python Machine Learning. Packt Publishing Ltd., 2015.
# GitHub Repo: https://github.com/rasbt/python-machine-learning-book
#
# License: MIT
#... | mit |
anirudhjayaraman/scikit-learn | sklearn/tests/test_multiclass.py | 136 | 23649 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing ... | bsd-3-clause |
mrshu/scikit-learn | sklearn/tests/test_grid_search.py | 2 | 8915 | """
Testing for grid search module (sklearn.grid_search)
"""
from cStringIO import StringIO
import sys
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_true
from sklearn.utils.testing ... | bsd-3-clause |
paalge/scikit-image | doc/examples/segmentation/plot_rag_draw.py | 7 | 1031 | """
======================================
Drawing Region Adjacency Graphs (RAGs)
======================================
This example constructs a Region Adjacency Graph (RAG) and draws it with
the `rag_draw` method.
"""
from skimage import data, segmentation
from skimage.future import graph
from matplotlib import py... | bsd-3-clause |
ahaberlie/MetPy | examples/calculations/Smoothing.py | 5 | 2418 | # Copyright (c) 2015-2018 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Smoothing
=========
Using MetPy's smoothing functions.
This example demonstrates the various ways that MetPy's smoothing function
can be utilized. While this example utili... | bsd-3-clause |
bzero/arctic | tests/integration/store/test_version_store_audit.py | 4 | 8283 | from bson import ObjectId
from datetime import datetime as dt
from mock import patch
from pandas.util.testing import assert_frame_equal
from pymongo.errors import OperationFailure
import pytest
from arctic.store.audit import ArcticTransaction
from arctic.exceptions import ConcurrentModificationException, NoDataFoundEx... | lgpl-2.1 |
Winand/pandas | pandas/tests/test_algos.py | 2 | 56095 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from numpy.random import RandomState
from numpy import nan
from datetime import datetime
from itertools import permutations
from pandas import (Series, Categorical, CategoricalIndex,
Timestamp, DatetimeIndex,
Index, Inter... | bsd-3-clause |
IshankGulati/scikit-learn | examples/classification/plot_digits_classification.py | 82 | 2414 | """
================================
Recognizing hand-written digits
================================
An example showing how the scikit-learn can be used to recognize images of
hand-written digits.
This example is commented in the
:ref:`tutorial section of the user manual <introduction>`.
"""
print(__doc__)
# Autho... | bsd-3-clause |
xiaoxiamii/scikit-learn | sklearn/metrics/cluster/unsupervised.py | 230 | 8281 | """ Unsupervised evaluation metrics. """
# Authors: Robert Layton <robertlayton@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ...utils import check_random_state
from ..pairwise import pairwise_distances
def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random... | bsd-3-clause |
robin-lai/scikit-learn | sklearn/covariance/tests/test_covariance.py | 69 | 11116 | # 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 |
makersauce/stocks | strategy1.py | 1 | 4415 | ##Stragegy File
import datetime
from stock import Stock, piggy
from sys import argv
if __name__ == "__main__":
if len(argv) > 1:
if argv[1] == '--simulate':
if len(argv) < 3:
print 'Please specify symbol'
exit()
symbol = argv[2]
stock = S... | mit |
leewujung/ooi_sonar | during_incubator/concat_raw.py | 1 | 8982 |
import glob, os, sys
import datetime as dt # quick fix to avoid datetime and datetime.datetime confusion
from matplotlib.dates import date2num, num2date
from calendar import monthrange
import h5py
import matplotlib.pylab as plt
# from modest_image import imshow
# import numpy as np # already imported in zplsc_b
sy... | apache-2.0 |
rseubert/scikit-learn | sklearn/neighbors/tests/test_dist_metrics.py | 48 | 4949 | import itertools
import numpy as np
from numpy.testing import assert_array_almost_equal
import scipy
from scipy.spatial.distance import cdist
from sklearn.neighbors.dist_metrics import DistanceMetric
from nose import SkipTest
def cmp_version(version1, version2):
version1 = tuple(map(int, version1.split('.')[:2]... | bsd-3-clause |
google-research/google-research | talk_about_random_splits/probing/split_with_cross_validation_main.py | 1 | 4750 | # coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# 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 applicab... | apache-2.0 |
zuku1985/scikit-learn | examples/decomposition/plot_ica_vs_pca.py | 306 | 3329 | """
==========================
FastICA on 2D point clouds
==========================
This example illustrates visually in the feature space a comparison by
results using two different component analysis techniques.
:ref:`ICA` vs :ref:`PCA`.
Representing ICA in the feature space gives the view of 'geometric ICA':
ICA... | bsd-3-clause |
tayebzaidi/HonorsThesisTZ | ThesisCode/DES_Pipeline/gen_lightcurves/visualizeLCurves.py | 1 | 3137 | #!/usr/bin/env python
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import json
import os
import sys
import numpy as np
import math
import pickle
def main():
path = "./des_sn.p"
output_lightcurves_file = 'selectedLightcurves'
output_lightcurves = []
with open(path, 'rb') as f:... | gpl-3.0 |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/mixture/tests/test_dpgmm.py | 84 | 7866 | # Important note for the deprecation cleaning of 0.20 :
# All the function and classes of this file have been deprecated in 0.18.
# When you remove this file please also remove the related files
# - 'sklearn/mixture/dpgmm.py'
# - 'sklearn/mixture/gmm.py'
# - 'sklearn/mixture/test_gmm.py'
import unittest
import sys
imp... | mit |
anurag313/scikit-learn | sklearn/metrics/setup.py | 299 | 1024 | import os
import os.path
import numpy
from numpy.distutils.misc_util import Configuration
from sklearn._build_utils import get_blas_info
def configuration(parent_package="", top_path=None):
config = Configuration("metrics", parent_package, top_path)
cblas_libs, blas_info = get_blas_info()
if os.name ==... | bsd-3-clause |
spallavolu/scikit-learn | examples/plot_isotonic_regression.py | 303 | 1767 | """
===================
Isotonic Regression
===================
An illustration of the isotonic regression on generated data. The
isotonic regression finds a non-decreasing approximation of a function
while minimizing the mean squared error on the training data. The benefit
of such a model is that it does not assume a... | bsd-3-clause |
renhaocui/activityExtractor | trainFullModel.py | 1 | 22297 | from keras.preprocessing.text import Tokenizer
from keras.models import Sequential
from keras.layers import Dense, LSTM, Dropout, Merge, Input, concatenate, Lambda
from keras.layers.embeddings import Embedding
from keras.models import Model
from keras.preprocessing import sequence
from keras.utils import np_utils
from ... | mit |
bthirion/scikit-learn | examples/cluster/plot_dict_face_patches.py | 337 | 2747 | """
Online learning of a dictionary of parts of faces
==================================================
This example uses a large dataset of faces to learn a set of 20 x 20
images patches that constitute faces.
From the programming standpoint, it is interesting because it shows how
to use the online API of the sciki... | bsd-3-clause |
UNR-AERIAL/scikit-learn | examples/model_selection/plot_precision_recall.py | 249 | 6150 | """
================
Precision-Recall
================
Example of Precision-Recall metric to evaluate classifier output quality.
In information retrieval, precision is a measure of result relevancy, while
recall is a measure of how many truly relevant results are returned. A high
area under the curve represents both ... | bsd-3-clause |
Flaviolib/dx | dx/dx_portfolio.py | 5 | 14390 | #
# DX Analytics Portfolio
# dx_portfolio.py
#
# (c) Dr. Yves J. Hilpisch
# The Python Quants GmbH
# You are not allowed to copy or distribute the dx library.
# Rights are only granted for a limited period of time to
# test the library in connection with the Python Quant Platform.
# See also the terms and conditions un... | agpl-3.0 |
zuku1985/scikit-learn | sklearn/utils/tests/test_metaestimators.py | 86 | 2304 | from sklearn.utils.testing import assert_true, assert_false
from sklearn.utils.metaestimators import if_delegate_has_method
class Prefix(object):
def func(self):
pass
class MockMetaEstimator(object):
"""This is a mock meta estimator"""
a_prefix = Prefix()
@if_delegate_has_method(delegate="a... | bsd-3-clause |
jj-umn/tools-iuc | tools/vsnp/vsnp_add_zero_coverage.py | 12 | 6321 | #!/usr/bin/env python
import argparse
import os
import re
import shutil
import pandas
import pysam
from Bio import SeqIO
def get_sample_name(file_path):
base_file_name = os.path.basename(file_path)
if base_file_name.find(".") > 0:
# Eliminate the extension.
return os.path.splitext(base_file_... | mit |
mkoledoye/mds_examples | experiments/evaluation.py | 2 | 1384 | import numpy as np
from matplotlib import pyplot as plt
COLORS = iter(['blue', 'red', 'green', 'magenta'])
def rmse(computed, real):
return np.sqrt(((computed - real)**2).mean())
def first_third_quartile_and_median(data):
first_quartile = np.percentile(data, 25, axis=1)
third_quartile = np.percentile(data, 75, ... | mit |
marktrovinger/Fremont-Bike-Data | jupyterworkflow/data.py | 1 | 1025 | import os
from urllib.request import urlretrieve
import pandas as pd
FREMONT_URL = 'https://data.seattle.gov/api/views/65db-xm6k/rows.csv?accessType=DOWNLOAD'
def get_fremont_data(filename='Fremont.csv', url=FREMONT_URL, force_download=False):
''''Download and cache Fremont data
Parameters
-----------
... | mit |
joakim-hove/ert | python/python/ert_gui/plottery/plots/histogram.py | 4 | 5535 | from math import sqrt, ceil, floor, log10
from matplotlib.patches import Rectangle
import numpy
from .plot_tools import PlotTools
import pandas as pd
def plotHistogram(plot_context):
""" @type plot_context: ert_gui.plottery.PlotContext """
ert = plot_context.ert()
key = plot_context.key()
config = plot... | gpl-3.0 |
jlegendary/scikit-learn | examples/model_selection/plot_underfitting_overfitting.py | 230 | 2649 | """
============================
Underfitting vs. Overfitting
============================
This example demonstrates the problems of underfitting and overfitting and
how we can use linear regression with polynomial features to approximate
nonlinear functions. The plot shows the function that we want to approximate,
wh... | bsd-3-clause |
mblondel/scikit-learn | examples/model_selection/randomized_search.py | 57 | 3208 | """
=========================================================================
Comparing randomized search and grid search for hyperparameter estimation
=========================================================================
Compare randomized search and grid search for optimizing hyperparameters of a
random forest.
... | bsd-3-clause |
ccasotto/rmtk | rmtk/parsers/vulnerability_model_converter.py | 3 | 7101 | #!/usr/bin/env python
# LICENSE
#
# Copyright (c) 2014, GEM Foundation, Anirudh Rao
#
# The rmtk 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 of the License, or (at your option) an... | agpl-3.0 |
BlueBrain/NEST | topology/pynest/tests/test_plotting.py | 13 | 4111 | # -*- 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 |
mirkix/ardupilot | Tools/scripts/tempcal_IMU.py | 16 | 20088 | #!/usr/bin/env python
'''
Create temperature calibration parameters for IMUs based on log data.
'''
from argparse import ArgumentParser
parser = ArgumentParser(description=__doc__)
parser.add_argument("--outfile", default="tcal.parm", help='set output file')
parser.add_argument("--no-graph", action='store_true', defau... | gpl-3.0 |
yonglehou/scikit-learn | examples/gaussian_process/plot_gp_probabilistic_classification_after_regression.py | 252 | 3490 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
==============================================================================
Gaussian Processes classification example: exploiting the probabilistic output
==============================================================================
A two-dimensional regression exerci... | bsd-3-clause |
ocefpaf/python-oceans | oceans/sw_extras/sw_extras.py | 2 | 29692 | from copy import copy
import numpy as np
import seawater as sw
from seawater.constants import OMEGA, earth_radius
def sigma_t(s, t, p):
"""
:math:`\\sigma_{t}` is the remainder of subtracting 1000 kg m :sup:`-3`
from the density of a sea water sample at atmospheric pressure.
Parameters
---------... | bsd-3-clause |
aewhatley/scikit-learn | sklearn/datasets/mlcomp.py | 289 | 3855 | # Copyright (c) 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
"""Glue code to load http://mlcomp.org data as a scikit.learn dataset"""
import os
import numbers
from sklearn.datasets.base import load_files
def _load_document_classification(dataset_path, metadata, set_=None, **kwargs):
if ... | bsd-3-clause |
trachelr/mne-python | mne/inverse_sparse/mxne_optim.py | 13 | 37011 | from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Daniel Strohmeier <daniel.strohmeier@gmail.com>
#
# License: Simplified BSD
from copy import deepcopy
import warnings
from math import sqrt, ceil
import numpy as np
from scipy import linalg
from .mxn... | bsd-3-clause |
zhengfaxiang/Runge-Kutta-Fehlberg | src/hill_surf.py | 1 | 4678 | #!/usr/bin/env python
"""
Script to plot Hill surface.
"""
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
def Hill_Surf(n, Miu, Cj):
"""Implicit equation of Hill surface."""
def hill_surf(x, y, z):
r1 = ((x + Miu)**2 + y**2 + z**2)**0.5
r2 = ((x + ... | mit |
gpospelov/BornAgain | Examples/varia/MaterialProfileWithParticles.py | 1 | 1734 | """
Example for producing a profile of SLD of a multilayer with particles
and slicing.
"""
import bornagain as ba
from bornagain import deg, angstrom, nm
import numpy as np
import matplotlib.pyplot as plt
def get_sample():
"""
Defines sample and returns it
"""
# creating materials
m_ambient = ba... | gpl-3.0 |
dennisobrien/bokeh | sphinx/source/conf.py | 3 | 9540 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from os.path import abspath, dirname, join
#
# Bokeh documentation build configuration file, created by
# sphinx-quickstart on Sat Oct 12 23:43:03 2013.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not a... | bsd-3-clause |
datapythonista/pandas | pandas/tests/frame/indexing/test_insert.py | 3 | 2888 | """
test_insert is specifically for the DataFrame.insert method; not to be
confused with tests with "insert" in their names that are really testing
__setitem__.
"""
import numpy as np
import pytest
from pandas.errors import PerformanceWarning
from pandas import (
DataFrame,
Index,
)
import pandas._testing as ... | bsd-3-clause |
jklenzing/pysat | pysat/instruments/pysat_testing_xarray.py | 2 | 8837 | # -*- coding: utf-8 -*-
"""
Produces fake instrument data for testing.
"""
from __future__ import print_function
from __future__ import absolute_import
import os
import numpy as np
import pandas as pds
import xarray
import pysat
from pysat.instruments.methods import testing as test
# pysat required parameters
platfo... | bsd-3-clause |
AlexanderFabisch/scikit-learn | sklearn/linear_model/tests/test_omp.py | 272 | 7752 | # Author: Vlad Niculae
# Licence: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equa... | bsd-3-clause |
dchabot/bluesky | bluesky/testing/noseclasses.py | 4 | 4638 | ########################################################################
# This file contains code from numpy and matplotlib (noted in the code)#
# which is (c) the respective projects. #
# #
# Modifications and original... | bsd-3-clause |
plissonf/scikit-learn | sklearn/datasets/__init__.py | 176 | 3671 | """
The :mod:`sklearn.datasets` module includes utilities to load datasets,
including methods to load and fetch popular reference datasets. It also
features some artificial data generators.
"""
from .base import load_diabetes
from .base import load_digits
from .base import load_files
from .base import load_iris
from .... | bsd-3-clause |
cheral/orange3 | Orange/preprocess/score.py | 2 | 12309 | from collections import defaultdict
from itertools import chain
import numpy as np
from sklearn import feature_selection as skl_fss
from Orange.misc.wrapper_meta import WrapperMeta
from Orange.statistics import contingency, distribution
from Orange.data import Domain, Variable, DiscreteVariable, ContinuousVariable
fr... | bsd-2-clause |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/pandas/tests/test_common.py | 7 | 5050 | # -*- coding: utf-8 -*-
import nose
import numpy as np
from pandas import Series, Timestamp
from pandas.compat import range, lmap
import pandas.core.common as com
import pandas.util.testing as tm
_multiprocess_can_split_ = True
def test_mut_exclusive():
msg = "mutually exclusive arguments: '[ab]' and '[ab]'"
... | gpl-3.0 |
claesenm/HPOlib | HPOlib/Plotting/plotTraceWithStd_perTime.py | 4 | 9873 | #!/usr/bin/env python
##
# wrapping: A program making it easy to use hyperparameter
# optimization software.
# Copyright (C) 2013 Katharina Eggensperger and Matthias Feurer
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# ... | gpl-3.0 |
kdebrab/pandas | pandas/tests/sparse/series/test_indexing.py | 4 | 3127 | import pytest
import numpy as np
from pandas import SparseSeries, Series
from pandas.util import testing as tm
pytestmark = pytest.mark.skip("Wrong SparseBlock initialization (GH 17386)")
@pytest.mark.parametrize('data', [
[1, 1, 2, 2, 3, 3, 4, 4, 0, 0],
[1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, np.nan, np.n... | bsd-3-clause |
Eric89GXL/scikit-learn | examples/applications/plot_hmm_stock_analysis.py | 12 | 2783 | """
==========================
Gaussian HMM of stock data
==========================
This script shows how to use Gaussian HMM.
It uses stock price data, which can be obtained from yahoo finance.
For more information on how to get stock prices with matplotlib, please refer
to date_demo1.py of matplotlib.
"""
from __f... | bsd-3-clause |
stonebig/winpython_afterdoc | docs/minesweeper.py | 2 | 7264 | """
Matplotlib Minesweeper
----------------------
A simple Minesweeper implementation in matplotlib.
Author: Jake Vanderplas <vanderplas@astro.washington.edu>, Dec. 2012
License: BSD
"""
import numpy as np
from itertools import product
from scipy.signal import convolve2d
import matplotlib.pyplot as plt
from matplotlib... | mit |
rohanp/scikit-learn | examples/gaussian_process/plot_gpc_iris.py | 81 | 2231 | """
=====================================================
Gaussian process classification (GPC) on iris dataset
=====================================================
This example illustrates the predicted probability of GPC for an isotropic
and anisotropic RBF kernel on a two-dimensional version for the iris-dataset.
... | bsd-3-clause |
uglyboxer/linear_neuron | net-p3/lib/python3.5/site-packages/sklearn/tests/test_random_projection.py | 1 | 14003 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from sklearn.metrics import euclidean_distances
from sklearn.random_projection import johnson_lindenstrauss_min_dim
from sklearn.random_projection import gaussian_random_matrix
from sklearn.random_projection import sparse_random_matrix
from... | mit |
asteca/ASteCA | packages/out/make_A2_plot.py | 1 | 2412 |
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from os.path import join
from . import mp_cent_dens
from . import add_version_plot
from . import prep_plots
from . prep_plots import grid_x, grid_y, figsize_x, figsize_y
def main(npd, cld_i, pd, clp):
"""
Make A2 block plots.
"""
... | gpl-3.0 |
JohnGBaker/ptmcmc | python/corner_with_covar.py | 1 | 27157 | # -*- coding: utf-8 -*-
#This code is adaped from
# https://github.com/dfm/corner.py
# git hash 5c2cd63 on May 25
# Modifications by John Baker NASA-GSFC (2016-18)
#Copyright (c) 2013-2016 Daniel Foreman-Mackey
#All rights reserved.
#
#Redistribution and use in source and binary forms, with or without
#modification, a... | apache-2.0 |
rs2/pandas | pandas/core/groupby/groupby.py | 1 | 95861 | """
Provide the groupby split-apply-combine paradigm. Define the GroupBy
class providing the base-class of operations.
The SeriesGroupBy and DataFrameGroupBy sub-class
(defined in pandas.core.groupby.generic)
expose these user-facing objects to provide specific functionality.
"""
from contextlib import contextmanager... | bsd-3-clause |
xiaoxiamii/scikit-learn | examples/bicluster/plot_spectral_coclustering.py | 276 | 1736 | """
==============================================
A demo of the Spectral Co-Clustering algorithm
==============================================
This example demonstrates how to generate a dataset and bicluster it
using the the Spectral Co-Clustering algorithm.
The dataset is generated using the ``make_biclusters`` f... | bsd-3-clause |
HrWangChengdu/CS231n | assignment1/cs231n/features.py | 30 | 4807 | import matplotlib
import numpy as np
from scipy.ndimage import uniform_filter
def extract_features(imgs, feature_fns, verbose=False):
"""
Given pixel data for images and several feature functions that can operate on
single images, apply all feature functions to all images, concatenating the
feature vectors fo... | mit |
USStateDept/FPA_Core | openspending/lib/apihelper.py | 2 | 26540 | import logging
import urlparse
from dateutil import parser
# import pandas as pd
# import numpy as np
from flask import current_app,request, Response
from openspending.core import db
from openspending.lib.helpers import get_dataset
from openspending.lib.cubes_util import get_cubes_breaks
log = logging.getLogger(... | agpl-3.0 |
stylianos-kampakis/scikit-learn | examples/svm/plot_custom_kernel.py | 171 | 1546 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
yejingfu/samples | tensorflow/gene_sample.py | 1 | 2963 | #!/usr/bin/env python3
#%matplotlib inline
import numpy as np
import pandas as pd
from scipy import stats
import matplotlib.pyplot as plt
plt.style.use('/Users/jeff/code/elegant-scipy/style/elegant.mplstyle')
def reduceXaxisLabels(ax, factor):
plt.setp(ax.xaxis.get_ticklabels(), visible = False)
for l in ax.xa... | mit |
allthroughthenight/aces | python/drivers/wave_forces.py | 1 | 17366 | import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import sys
sys.path.append('../functions')
from base_driver import BaseDriver
from helper_objects import BaseField
from helper_objects import ComplexUtil
import USER_INPUT
from ERRSTP import ERRSTP
from ERRWAVBRK1 impor... | gpl-3.0 |
numenta/htmresearch | projects/thalamus/run_experiment.py | 2 | 9869 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2019, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
huangziwei/MorphoPy | tests/test_utils.py | 1 | 3616 | import numpy as np
import sys
sys.path.append('..')
#### TEST GET_ANGLE #####
from morphopy._utils.summarize import get_angle
def test_get_angle_with_orthogonal_vectors():
v0 = np.array([0, 0, 1])
v1 = np.array([0, 1, 0])
r, d = get_angle(v0, v1)
assert(r == 90*np.pi/180), "returned angle should be... | mit |
manipopopo/tensorflow | tensorflow/contrib/factorization/python/ops/gmm_test.py | 41 | 8716 | # 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 |
mattilyra/scikit-learn | sklearn/externals/joblib/testing.py | 45 | 2720 | """
Helper for testing.
"""
import sys
import warnings
import os.path
import re
import subprocess
import threading
from sklearn.externals.joblib._compat import PY3_OR_LATER
def warnings_to_stdout():
""" Redirect all warnings to stdout.
"""
showwarning_orig = warnings.showwarning
def showwarning(msg... | bsd-3-clause |
mrgloom/python-topic-model | ptm/whdsp.py | 3 | 20653 | import numpy as np
import time
import utils
from scipy.special import gammaln, psi
#epsilon
eps = 1e-100
class hdsp:
"""
hierarchical dirichlet scaling process (hdsp)
"""
def __init__(self, num_topics, num_words, num_labels, dir_prior=0.5):
self.K = num_topics # number of topics
... | apache-2.0 |
duane-edgington/stoqs | stoqs/contrib/analysis/crossproduct_biplots.py | 3 | 8932 | #!/usr/bin/env python
'''
Script to create biplots of a cross product of all Parameters in a database.
Mike McCann
MBARI 10 February 2014
'''
import os
import sys
if 'DJANGO_SETTINGS_MODULE' not in os.environ:
os.environ['DJANGO_SETTINGS_MODULE']='settings'
sys.path.insert(0, os.path.join(os.path.dirname(__file__... | gpl-3.0 |
dphang/sage | dota/learner/learner.py | 1 | 1348 | """
Uses scikit-learn to train a knn classifier on a set of labeled replay data, in JSON format. We can then use this classifier
to classify similar important events in future replays.
Events have a few labels:
farm: hero is simply hitting creeps to gain experience and gold. This will be the default event should ther... | mit |
arabenjamin/scikit-learn | sklearn/preprocessing/tests/test_imputation.py | 213 | 11911 | 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.utils.testing import assert_false
from sklearn.utils.testing import assert_true
from sklearn.preprocessing.imputa... | bsd-3-clause |
jorge2703/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 181 | 15664 | 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 |
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