repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
petosegan/scikit-learn | sklearn/decomposition/__init__.py | 147 | 1421 | """
The :mod:`sklearn.decomposition` module includes matrix decomposition
algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
this module can be regarded as dimensionality reduction techniques.
"""
from .nmf import NMF, ProjectedGradientNMF
from .pca import PCA, RandomizedPCA
from .incrementa... | bsd-3-clause |
2uller/LotF | App/Lib/site-packages/scipy/stats/kde.py | 3 | 17459 | #-------------------------------------------------------------------------------
#
# Define classes for (uni/multi)-variate kernel density estimation.
#
# Currently, only Gaussian kernels are implemented.
#
# Written by: Robert Kern
#
# Date: 2004-08-09
#
# Modified: 2005-02-10 by Robert Kern.
# Contr... | gpl-2.0 |
acbecker/BART | tests/test_bart_step.py | 1 | 7134 | __author__ = 'brandonkelly'
import unittest
import numpy as np
from scipy import stats, integrate
from tree import *
import matplotlib.pyplot as plt
from test_tree_parameters import build_test_data, SimpleBartStep
class StepTestCase(unittest.TestCase):
def setUp(self):
nsamples = 1000
nfeatures =... | mit |
verilog-to-routing/tatum | scripts/plot_level_scaling.py | 3 | 4192 | #!/usr/bin/env python
import sys, argparse
import csv
import os
import matplotlib.pyplot as plt
import numpy as np
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("csv_file", default=None, help="CSV file with level runtimes")
parser.add_argument("--scale_size", default=False, acti... | mit |
RPGOne/Skynet | scikit-learn-0.18.1/examples/text/document_classification_20newsgroups.py | 5 | 10515 | """
======================================================
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 |
mayblue9/scikit-learn | sklearn/neighbors/nearest_centroid.py | 199 | 7249 | # -*- coding: utf-8 -*-
"""
Nearest Centroid Classification
"""
# Author: Robert Layton <robertlayton@gmail.com>
# Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import warnings
import numpy as np
from scipy import sparse as sp
from ..base import BaseEstimator, ClassifierMixin
from ..met... | bsd-3-clause |
MrCodeYu/spark | python/pyspark/sql/context.py | 3 | 22432 | #
# 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 |
henriquemiranda/yambo-py | tests/test_yambopy.py | 2 | 1475 | from __future__ import print_function
#
# Author: Henrique Pereira Coutada Miranda
# Tests for yambopy
# Si
#
import matplotlib
import unittest
import sys
import os
import shutil
import argparse
import subprocess
import filecmp
import shutil as sh
from yambopy import *
from qepy import *
class TestYambopyGW(unittest.T... | bsd-3-clause |
dennisss/sympy | sympy/plotting/tests/test_plot.py | 17 | 8476 | from sympy import (pi, sin, cos, Symbol, Integral, summation, sqrt, log,
oo, LambertW, I, meijerg, exp_polar, Max)
from sympy.plotting import (plot, plot_parametric, plot3d_parametric_line,
plot3d, plot3d_parametric_surface)
from sympy.plotting.plot import unset_show
from ... | bsd-3-clause |
thesuperzapper/tensorflow | tensorflow/examples/learn/iris.py | 35 | 1654 | # 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 |
albonthenet/uDPI | estimations/confusion_matrix/cm-kneighbor.py | 1 | 2589 | import pandas
from sklearn.preprocessing import MinMaxScaler
from sklearn import cross_validation
from sklearn import preprocessing
from sklearn.tree import DecisionTreeClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC,NuSVC,LinearSVC
fr... | gpl-3.0 |
jakobworldpeace/scikit-learn | sklearn/covariance/__init__.py | 389 | 1157 | """
The :mod:`sklearn.covariance` module includes methods and algorithms to
robustly estimate the covariance of features given a set of points. The
precision matrix defined as the inverse of the covariance is also estimated.
Covariance estimation is closely related to the theory of Gaussian Graphical
Models.
"""
from ... | bsd-3-clause |
simupy/simupy | examples/vanderpol.py | 1 | 1274 | import numpy as np
import sympy as sp
import matplotlib.pyplot as plt
from simupy.systems.symbolic import DynamicalSystem, dynamicsymbols
from simupy.block_diagram import BlockDiagram, DEFAULT_INTEGRATOR_OPTIONS
from simupy.array import Array, r_
# This example simulates the Van der Pol oscillator.
DEFAULT_INTEGRATOR... | bsd-2-clause |
sytays/openanalysis | doc/conf.py | 1 | 6136 | # -*- coding: utf-8 -*-
#
# OpenAnalysis documentation build configuration file, created by
# sphinx-quickstart on Wed Jul 19 12:44:16 2017.
#
# 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.
... | gpl-3.0 |
nmartensen/pandas | pandas/tests/frame/test_sorting.py | 7 | 21261 | # -*- coding: utf-8 -*-
from __future__ import print_function
import pytest
import random
import numpy as np
import pandas as pd
from pandas.compat import lrange
from pandas import (DataFrame, Series, MultiIndex, Timestamp,
date_range, NaT, IntervalIndex)
from pandas.util.testing import assert_s... | bsd-3-clause |
ltiao/scikit-learn | sklearn/feature_extraction/tests/test_dict_vectorizer.py | 276 | 3790 | # Authors: Lars Buitinck <L.J.Buitinck@uva.nl>
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from random import Random
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from sklearn.utils.testing import (assert_equal, assert_in,
... | bsd-3-clause |
Eric89GXL/mne-python | examples/decoding/plot_decoding_csp_timefreq.py | 11 | 6452 | """
====================================================================
Decoding in time-frequency space using Common Spatial Patterns (CSP)
====================================================================
The time-frequency decomposition is estimated by iterating over raw data that
has been band-passed at differ... | bsd-3-clause |
divir94/News-Analytics | newsCollectionCopy.py | 1 | 12990 | import nltk, nltk.data, pickle, re
import email as emailProcessor
import time, imaplib
from dateutil import parser
import datetime
import numpy as np
#import ner
import bsddb, string
from nltk.stem import WordNetLemmatizer
from sklearn import decomposition
import matplotlib.pyplot as plt
import subprocess, sys, random
... | apache-2.0 |
xhochy/arrow | dev/archery/setup.py | 2 | 1819 | #!/usr/bin/env python
# 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
# "Li... | apache-2.0 |
arahuja/scikit-learn | sklearn/metrics/cluster/bicluster.py | 25 | 2741 | from __future__ import division
import numpy as np
from sklearn.utils.linear_assignment_ import linear_assignment
from sklearn.utils.validation import check_consistent_length, check_array
__all__ = ["consensus_score"]
def _check_rows_and_columns(a, b):
"""Unpacks the row and column arrays and checks their shap... | bsd-3-clause |
vermouthmjl/scikit-learn | examples/exercises/plot_cv_digits.py | 135 | 1223 | """
=============================================
Cross-validation on Digits Dataset Exercise
=============================================
A tutorial exercise using Cross-validation with an SVM on the Digits dataset.
This exercise is used in the :ref:`cv_generators_tut` part of the
:ref:`model_selection_tut` section... | bsd-3-clause |
gerberlab/mitre | setup.py | 1 | 2203 | from setuptools import setup
from setuptools.extension import Extension
from setuptools.command.build_ext import build_ext
import pkg_resources
USE_CYTHON = False
ext = '.pyx' if USE_CYTHON else '.c'
extensions = [
Extension("efficient_likelihoods",
["mitre/efficient_likelihoods" + ext],
... | gpl-3.0 |
anilmuthineni/tensorflow | tensorflow/contrib/metrics/python/kernel_tests/histogram_ops_test.py | 130 | 9577 | # 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 |
iiSeymour/pandashells | pandashells/bin/p_example_data.py | 8 | 2130 | #! /usr/bin/env python
# standard library imports
import os
import sys # noqa
import argparse
import textwrap
import pandashells
def main():
# create a dict of data-set names and corresponding files
package_dir = os.path.dirname(os.path.realpath(pandashells.__file__))
sample_data_dir = os.path.realpath... | bsd-2-clause |
hsiaoyi0504/scikit-learn | examples/applications/plot_model_complexity_influence.py | 323 | 6372 | """
==========================
Model Complexity Influence
==========================
Demonstrate how model complexity influences both prediction accuracy and
computational performance.
The dataset is the Boston Housing dataset (resp. 20 Newsgroups) for
regression (resp. classification).
For each class of models we m... | bsd-3-clause |
Kongsea/tensorflow | tensorflow/examples/learn/iris_custom_model.py | 43 | 3449 | # 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 |
structrans/Canon | scripts/plotseq.py | 1 | 2513 | import os
import logging
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
def plot_seq(Z, step, colormap='gist_ncar', filename='untitled'):
dir = os.path.dirname(os.path.abspath(__file__))
save_directory = os.path.join(dir, '{:s}.png'.format(filename))
x_step = step[0]
y_step = ste... | mit |
toastedcornflakes/scikit-learn | examples/text/hashing_vs_dict_vectorizer.py | 93 | 3243 | """
===========================================
FeatureHasher and DictVectorizer Comparison
===========================================
Compares FeatureHasher and DictVectorizer by using both to vectorize
text documents.
The example demonstrates syntax and speed only; it doesn't actually do
anything useful with the e... | bsd-3-clause |
nikitasingh981/scikit-learn | sklearn/svm/setup.py | 83 | 3160 | import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('svm', parent_package, top_path)
config.add_subpackage('tests')
# Section L... | bsd-3-clause |
zrhans/python | exemplos/Examples.lnk/bokeh/glyphs/colors.py | 25 | 8920 | from __future__ import print_function
from math import pi
import pandas as pd
from bokeh.models import Plot, ColumnDataSource, FactorRange, CategoricalAxis, TapTool, HoverTool, OpenURL
from bokeh.models.glyphs import Rect
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources impor... | gpl-2.0 |
DGrady/pandas | pandas/tests/sparse/test_indexing.py | 11 | 39909 | # pylint: disable-msg=E1101,W0612
import pytest
import numpy as np
import pandas as pd
import pandas.util.testing as tm
class TestSparseSeriesIndexing(object):
def setup_method(self, method):
self.orig = pd.Series([1, np.nan, np.nan, 3, np.nan])
self.sparse = self.orig.to_sparse()
def test_... | bsd-3-clause |
ehocchen/trading-with-python | cookbook/reconstructVXX/reconstructVXX.py | 77 | 3574 | # -*- coding: utf-8 -*-
"""
Reconstructing VXX from futures data
author: Jev Kuznetsov
License : BSD
"""
from __future__ import division
from pandas import *
import numpy as np
import os
class Future(object):
""" vix future class, used to keep data structures simple """
def __init__(self,serie... | bsd-3-clause |
Mushirahmed/gnuradio | gr-input/python/qa_response.py | 1 | 1255 | import numpy
from gnuradio import gr,gr_unittest
from gnuradio import blocks
from Response import Response
import matplotlib.pyplot as plt
class qa_response(gr_unittest.TestCase):
def setUp(self):
self.tb = gr.top_block()
def tearDown(self):
self.tb = None
def test_001_t(self):
"""
... | gpl-3.0 |
zlatiadam/PyPortfolio | pyportfolio/statistics/robust_statistics.py | 1 | 4330 | # -*- coding: utf-8 -*-
"""
Created on Sun Nov 08 23:55:52 2015
@author: Zlati
"""
import numpy as np
from sklearn.covariance import fast_mcd, ledoit_wolf, oas, empirical_covariance
from statsmodels.robust.scale import huber
from scipy.stats import kendalltau, spearmanr
def hodges_lehmann_mean(x):
"""
Robus... | gpl-2.0 |
justincassidy/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 129 | 10192 | import pickle
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.dis... | bsd-3-clause |
bgris/ODL_bgris | lib/python3.5/site-packages/matplotlib/docstring.py | 23 | 3995 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from matplotlib import cbook
import sys
import types
class Substitution(object):
"""
A decorator to take a function's docstring and perform string
substitution on it.
This decorat... | gpl-3.0 |
rishikksh20/scikit-learn | sklearn/decomposition/tests/test_factor_analysis.py | 112 | 3203 | # Author: Christian Osendorfer <osendorf@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD3
import numpy as np
from sklearn.utils.testing import assert_warns
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing im... | bsd-3-clause |
jblackburne/scikit-learn | sklearn/metrics/cluster/supervised.py | 11 | 33436 | """Utilities to evaluate the clustering performance of models.
Functions named as *_score return a scalar value to maximize: the higher the
better.
"""
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Wei LI <kuantkid@gmail.com>
# Diego Molla <dmolla-aliod@gmail.com>
# Arnaud Fouchet ... | bsd-3-clause |
philippjfr/bokeh | examples/models/file/colors.py | 9 | 2059 | from __future__ import print_function
from math import pi
import pandas as pd
from bokeh.models import (
Plot, ColumnDataSource, FactorRange, CategoricalAxis, TapTool, HoverTool, OpenURL, CategoricalScale)
from bokeh.models.glyphs import Rect
from bokeh.colors import groups
from bokeh.document import Document
fro... | bsd-3-clause |
unnikrishnankgs/va | venv/lib/python3.5/site-packages/matplotlib/tests/test_subplots.py | 5 | 4766 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import warnings
import six
from six.moves import xrange
import numpy
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison, cleanup
from nose.tools import assert_raises
... | bsd-2-clause |
RayMick/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 |
dwweiss/pmLib | src/tests/henonMap.py | 1 | 3170 | """
Copyright (c) 2016-18 by Dietmar W Weiss
This 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 3.0 of
the License, or (at your option) any later version.
This softwar... | lgpl-3.0 |
pylayers/pylayers | pylayers/gis/examples/ex_osmparser.py | 3 | 1883 | from pylayers.util.project import *
import pylayers.gis.osmparser as osm
import matplotlib.pyplot as plt
filename = datadir+'/osm/marne.osm'
#filename = datadir+'/osm/poland.osm'
#filename = datadir+'/osm/marne.osm'
#
coords,nodes,ways,relations= osm.osmparse(filename,typ='building',verbose=True)
#bdg = osm.building... | mit |
dvro/UnbalancedDataset | imblearn/ensemble/easy_ensemble.py | 2 | 5455 | """Class to perform under-sampling using easy ensemble."""
from __future__ import print_function
import numpy as np
from sklearn.utils import check_random_state
from ..base import BaseMulticlassSampler
from ..under_sampling import RandomUnderSampler
MAX_INT = np.iinfo(np.int32).max
class EasyEnsemble(BaseMulticl... | mit |
raghavrv/scikit-learn | benchmarks/bench_plot_svd.py | 72 | 2914 | """Benchmarks of Singular Value Decomposition (Exact and Approximate)
The data is mostly low rank but is a fat infinite tail.
"""
import gc
from time import time
import numpy as np
from collections import defaultdict
import six
from scipy.linalg import svd
from sklearn.utils.extmath import randomized_svd
from sklear... | bsd-3-clause |
nikitasingh981/scikit-learn | examples/model_selection/plot_roc.py | 102 | 5056 | """
=======================================
Receiver Operating Characteristic (ROC)
=======================================
Example of Receiver Operating Characteristic (ROC) metric to evaluate
classifier output quality.
ROC curves typically feature true positive rate on the Y axis, and false
positive rate on the X a... | bsd-3-clause |
peterwilletts24/Python-Scripts | Radiosonde_Data/weekly_cross_section.py | 1 | 9413 | #Monthly
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.mlab as ml
import datetime
from dateutil.relativedelta import relativedelta
import re
import numpy as np
from math import sin, cos, atan2, radians, sqrt
import scipy.interpolate
import gc
import pdb
import imp
imp.load_source('GenMe... | mit |
nipunagarwala/cs224s_final_project | code/utils/dataAugmentation_filter.py | 1 | 1502 | import pickle
import numpy as np
from scipy.signal import butter, lfilter
from dataAugmentation_additive import add_noise
import matplotlib.pyplot as plt
# Filters out 60 Hz noise
def butter_bandstop_filter(data, lowcut, highcut, fs, order=2):
def butter_bandstop(lowcut, highcut, fs, order=2):
nyq = ... | mit |
almarklein/scikit-image | doc/examples/plot_threshold_adaptive.py | 5 | 1306 | """
=====================
Adaptive Thresholding
=====================
Thresholding is the simplest way to segment objects from a background. If that
background is relatively uniform, then you can use a global threshold value to
binarize the image by pixel-intensity. If there's large variation in the
background intensi... | bsd-3-clause |
smorante/continuous-goal-directed-actions | simulated-CGDA/generalization/generalization_old_test2.py | 1 | 7027 |
from __future__ import division
import itertools
from sklearn import mixture, metrics
from sklearn.cluster import DBSCAN
from scipy import linalg
from scipy.spatial import distance
import pylab as pl
import matplotlib as mpl
from scipy.interpolate import Rbf, InterpolatedUnivariateSpline
import csv
import numpy as np... | mit |
pelson/cartopy | lib/cartopy/io/ogc_clients.py | 2 | 35545 | # (C) British Crown Copyright 2014 - 2018, Met Office
#
# This file is part of cartopy.
#
# cartopy 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)... | lgpl-3.0 |
javadba/Python-ELM | elm_notebook.py | 9 | 6784 | # -*- coding: utf-8 -*-
# <nbformat>2</nbformat>
# <codecell>
# Demo python notebook for sklearn elm and random_hidden_layer modules
#
# Author: David C. Lambert [dcl -at- panix -dot- com]
# Copyright(c) 2013
# License: Simple BSD
# <codecell>
from time import time
from sklearn.cluster import k_means
from elm impo... | bsd-3-clause |
francescobaldi86/Ecos2015PaperExtension | Analyse/create_histograms.py | 1 | 16110 | import pandas as pd
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import os
import unicodedata
import re
%pylab
# This is for inline plotting
project_path = os.path.realpath('.')
project_path
database_path = project_path + os.sep + 'Database' + os.sep
graph_path = project_path + os.sep + 'Analyse' + ... | mit |
jwkvam/plotlywrapper | doc/figures.py | 1 | 1915 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import plotlywrapper as pw
import numpy as np
import pandas as pd
# from numpy import random as rng
import random
random.seed(0)
# rng.seed(0)
options = dict(output='file', plotlyjs=False, show_link=False)
datas = 'range(1, 6)'
data = eval(datas)
data2s = 'range(2, 12... | mit |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/pandas/plotting/_misc.py | 7 | 18199 | # being a bit too dynamic
# pylint: disable=E1101
from __future__ import division
import numpy as np
from pandas.util._decorators import deprecate_kwarg
from pandas.core.dtypes.missing import notnull
from pandas.compat import range, lrange, lmap, zip
from pandas.io.formats.printing import pprint_thing
from pandas.p... | mit |
tjhei/burnman | setup.py | 5 | 1333 | from __future__ import absolute_import
import re
versionstuff = dict(
re.findall("(.+) = '(.+)'\n", open('burnman/version.py').read()))
metadata = dict(name='burnman',
version=versionstuff['version'],
description='a thermoelastic and thermodynamic toolkit for Earth and planetary sc... | gpl-2.0 |
holsety/tushare | tushare/internet/boxoffice.py | 7 | 7205 | # -*- coding:utf-8 -*-
"""
电影票房
Created on 2015/12/24
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
import pandas as pd
from tushare.stock import cons as ct
from tushare.util import dateu as du
try:
from urllib.request import urlopen, Request
except ImportError:
from urllib2 import urlopen... | bsd-3-clause |
MATH497project/MATH497-DiabeticRetinopathy | ICO.py | 1 | 13492 | import numpy as np
import pandas as pd
import re
class Data:
def __init__(self, filepath):
table_names = {'all_encounter_data': 'all_encounter_data.pickle',
'demographics': 'demographics_Dan_20170304.pickle',
'encounters': 'encounters.pickle',
... | mit |
MJuddBooth/pandas | pandas/tests/extension/base/groupby.py | 2 | 2975 | import pytest
import pandas as pd
import pandas.util.testing as tm
from .base import BaseExtensionTests
class BaseGroupbyTests(BaseExtensionTests):
"""Groupby-specific tests."""
def test_grouping_grouper(self, data_for_grouping):
df = pd.DataFrame({
"A": ["B", "B", None, None, "A", "A",... | bsd-3-clause |
kavvkon/enlopy | enlopy/generate.py | 1 | 21354 | # -*- coding: utf-8 -*-
"""
Methods that generate or adjusted energy related timeseries based on given assumptions/input
"""
from __future__ import absolute_import, division, print_function
import numpy as np
import pandas as pd
import scipy.interpolate
import scipy.linalg
import scipy.stats
from .utils import make_t... | bsd-3-clause |
trycs/ozelot | examples/leonardo/leonardo/common/analysis.py | 1 | 3069 | """Analysis output generation, common for all model/pipeline variants
"""
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from os import path
import io
import jinja2
import numpy as np
from matplotlib import pyplot as plt
import seaborn
from ozelot impo... | mit |
kjung/scikit-learn | sklearn/tests/test_naive_bayes.py | 32 | 17897 | 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 |
frank-tancf/scikit-learn | sklearn/decomposition/base.py | 313 | 5647 | """Principal Component Analysis Base Classes"""
# 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>
# Kyle Kastner <kastnerkyle@gmail.com>
#
# Licen... | bsd-3-clause |
ic-hep/DIRAC | Core/Utilities/Graphs/GraphData.py | 1 | 17342 | ########################################################################
# $HeadURL$
########################################################################
""" GraphData encapsulates input data for the DIRAC Graphs plots
The DIRAC Graphs package is derived from the GraphTool plotting package of the
CMS/... | gpl-3.0 |
jblackburne/scikit-learn | sklearn/cluster/dbscan_.py | 24 | 12278 | # -*- coding: utf-8 -*-
"""
DBSCAN: Density-Based Spatial Clustering of Applications with Noise
"""
# Author: Robert Layton <robertlayton@gmail.com>
# Joel Nothman <joel.nothman@gmail.com>
# Lars Buitinck
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from ..base import BaseEst... | bsd-3-clause |
panoptes/environmental-analysis-system | scripts/plot_weather.py | 3 | 33190 | #!/usr/bin/env python3
import numpy as np
import os
import pandas as pd
import sys
import warnings
import yaml
from plotly import plotly
from datetime import datetime as dt
from datetime import timedelta as tdelta
from astropy.table import Table
from astropy.time import Time
from astroplan import Observer
from ast... | mit |
heli522/scikit-learn | sklearn/linear_model/__init__.py | 270 | 3096 | """
The :mod:`sklearn.linear_model` module implements generalized linear models. It
includes Ridge regression, Bayesian Regression, Lasso and Elastic Net
estimators computed with Least Angle Regression and coordinate descent. It also
implements Stochastic Gradient Descent related algorithms.
"""
# See http://scikit-le... | bsd-3-clause |
pacificgilly1992/PGrainrate | Backups/PGRRpost/PGRRpost1.0.7.py | 1 | 5483 | ############################################################################
# Project: The Lenard effect of preciptation at the RUAO,
# Title: Ensemble processing of the PG, Time and Rain Rate data,
# Author: James Gilmore,
# Email: james.gilmore@pgr.reading.ac.uk.
# Version: 1.0.7
# Date: 18/01/16
# Status: Operation... | gpl-3.0 |
s-t-e-a-l-t-h/Eclipsing-binaries-library | intersection/edge_intersection.py | 1 | 4837 | import matplotlib.pyplot as plt
import numpy as np
def edge_intersection_2d(pt1_xy, pt2_xy, pt3_xy, pt4_xy):
# return: tuple
# 0: intersection_status:
# False: parallel
# True: intersection
# 1: segment intersection:
# False: no inters... | gpl-3.0 |
gkunter/coquery | coquery/visualizer/boxplot.py | 1 | 2037 | # -*- coding: utf-8 -*-
"""
boxplot.py is part of Coquery.
Copyright (c) 2017 Gero Kunter (gero.kunter@coquery.org)
Coquery is released under the terms of the GNU General Public License (v3).
For details, see the file LICENSE that you should have received along
with Coquery. If not, see <http://www.gnu.org/licenses/>... | gpl-3.0 |
justincassidy/scikit-learn | sklearn/externals/joblib/__init__.py | 86 | 4795 | """ Joblib is a set of tools to provide **lightweight pipelining in
Python**. In particular, joblib offers:
1. transparent disk-caching of the output values and lazy re-evaluation
(memoize pattern)
2. easy simple parallel computing
3. logging and tracing of the execution
Joblib is optimized to be **fast*... | bsd-3-clause |
uglyboxer/linear_neuron | docs/source/conf.py | 1 | 9436 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# mini_net documentation build configuration file, created by
# sphinx-quickstart on Thu Oct 8 06:58:02 2015.
#
# 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
# a... | mit |
ville-k/tensorflow | tensorflow/contrib/learn/python/learn/estimators/multioutput_test.py | 136 | 1696 | # 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 |
boland1992/SeisSuite | build/lib/ambient/spectrum/find_maxima.py | 8 | 13563 | # -*- coding: utf-8 -*-
"""
Created on Fri July 6 11:04:03 2015
@author: boland
"""
import os
import datetime
import numpy as np
import multiprocessing as mp
import matplotlib.pyplot as plt
from scipy import signal
from obspy import read
from scipy.signal import argrelextrema
from info_dataless import locs_from_dat... | gpl-3.0 |
zorroblue/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 21 | 26665 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from numpy.testing import run_module_suite
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from... | bsd-3-clause |
boland1992/seissuite_iran | build/lib/ambient/ant/stack.py | 8 | 12789 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 11 12:17:56 2015
@author: boland
The following script is being used in order to explore and develop
python methods for phase-stacking, and phase-weighted stacking between
two seismic waveforms. Input uses one file per station waveform. Needs
a minimum of two channels to... | gpl-3.0 |
astropy/astropy | astropy/coordinates/tests/test_finite_difference_velocities.py | 8 | 9762 | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from astropy.units import allclose as quantity_allclose
from astropy import units as u
from astropy import constants
from astropy.time import Time
from astropy.coordinates.builtin_frames import IC... | bsd-3-clause |
gclenaghan/scikit-learn | sklearn/linear_model/tests/test_sgd.py | 30 | 44274 | import pickle
import unittest
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing ... | bsd-3-clause |
vzg100/Post-Translational-Modification-Prediction | pred.py | 1 | 25609 | def warn(*args, **kwargs): #Mutes Sklearn warnings
pass
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
from Bio.SeqUtils.ProtParam import ProteinAnalysis
import random
from random import randint
import numpy as np
from sklearn.neural_network import MLPClassifier
from sklearn import svm
from... | mit |
ClimbsRocks/scikit-learn | sklearn/discriminant_analysis.py | 13 | 28628 | """
Linear Discriminant Analysis and Quadratic Discriminant Analysis
"""
# Authors: Clemens Brunner
# Martin Billinger
# Matthieu Perrot
# Mathieu Blondel
# License: BSD 3-Clause
from __future__ import print_function
import warnings
import numpy as np
from scipy import linalg
from .extern... | bsd-3-clause |
apache/spark | python/pyspark/pandas/data_type_ops/num_ops.py | 6 | 21133 | #
# 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 |
nikitasingh981/scikit-learn | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 408 | 8061 | import re
import inspect
import textwrap
import pydoc
from .docscrape import NumpyDocString
from .docscrape import FunctionDoc
from .docscrape import ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config=None):
config = {} if config is None else config
self.use_plots... | bsd-3-clause |
inkenbrandt/ArcPy | Box_and_Whisker/BoxAndWhisker.py | 2 | 5739 | # -*- coding: utf-8 -*-
"""
Created on Tue Jun 24 09:44:39 2014
Box and Whisker
http://matplotlib.org/examples/pylab_examples/boxplot_demo2.html
http://matplotlib.org/examples/pylab_examples/boxplot_demo.html
http://stackoverflow.com/questions/16592222/matplotlib-group-boxplots
@author: paulinkenbrandt
"""
from pyl... | gpl-2.0 |
tosolveit/scikit-learn | sklearn/linear_model/ransac.py | 191 | 14261 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.valid... | bsd-3-clause |
strint/tensorflow | tensorflow/python/estimator/inputs/queues/feeding_functions.py | 10 | 13502 | # 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 |
sumspr/scikit-learn | sklearn/datasets/svmlight_format.py | 114 | 15826 | """This module implements a loader and dumper for the svmlight format
This format is a text-based format, with one sample per line. It does
not store zero valued features hence is suitable for sparse dataset.
The first element of each line can be used to store a target variable to
predict.
This format is used as the... | bsd-3-clause |
murali-munna/scikit-learn | examples/calibration/plot_compare_calibration.py | 241 | 5008 | """
========================================
Comparison of Calibration of Classifiers
========================================
Well calibrated classifiers are probabilistic classifiers for which the output
of the predict_proba method can be directly interpreted as a confidence level.
For instance a well calibrated (bi... | bsd-3-clause |
calico/basenji | bin/archive/basenji_map.py | 1 | 10036 | #!/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 |
rohit21122012/DCASE2013 | runs/2016/dnn2016med_traps/traps32/src/dataset.py | 55 | 78980 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import locale
import socket
import tarfile
import urllib2
import zipfile
from sklearn.cross_validation import StratifiedShuffleSplit, KFold
from files import *
from general import *
from ui import *
class Dataset(object):
"""Dataset base class.
The specific da... | mit |
jereze/scikit-learn | sklearn/feature_extraction/hashing.py | 183 | 6155 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: BSD 3 clause
import numbers
import numpy as np
import scipy.sparse as sp
from . import _hashing
from ..base import BaseEstimator, TransformerMixin
def _iteritems(d):
"""Like d.iteritems, but accepts any collections.Mapping."""
return d.iteritems() if... | bsd-3-clause |
plotly/plotly.py | packages/python/plotly/plotly/tests/test_optional/test_px/test_px.py | 1 | 10577 | import plotly.express as px
import plotly.io as pio
import numpy as np
import pytest
from itertools import permutations
def test_scatter():
iris = px.data.iris()
fig = px.scatter(iris, x="sepal_width", y="sepal_length")
assert fig.data[0].type == "scatter"
assert np.all(fig.data[0].x == iris.sepal_wid... | mit |
lzyeasyboy/tushare | tushare/stock/reference.py | 27 | 25190 | # -*- coding:utf-8 -*-
"""
投资参考数据接口
Created on 2015/03/21
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
from __future__ import division
from tushare.stock import cons as ct
from tushare.stock import ref_vars as rv
from tushare.util import dateu as dt
import pandas as pd
import time
i... | bsd-3-clause |
Machyne/econ_comps | full_1984.py | 1 | 6348 | import os
import numpy as np
import pandas as pd
from pandas.tools.plotting import scatter_matrix
import pylab
import statsmodels.formula.api as smf
import statsmodels.stats.api as sms
"""
USAGE:
python full_1984.py
CREATES:
results/1984/clean.csv
results/1984/corr.txt
results/1984/het_breushpagan.txt
results/1984/o... | bsd-3-clause |
beni55/networkx | examples/drawing/labels_and_colors.py | 44 | 1330 | #!/usr/bin/env python
"""
Draw a graph with matplotlib, color by degree.
You must have matplotlib for this to work.
"""
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
import matplotlib.pyplot as plt
import networkx as nx
G=nx.cubical_graph()
pos=nx.spring_layout(G) # positions for all nodes
# nodes
nx.draw... | bsd-3-clause |
jonathanstrong/NAB | tests/integration/corpus_test.py | 10 | 4895 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2014, 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 |
saullocastro/pyNastran | pyNastran/op2/tables/oes_stressStrain/real/oes_springs.py | 1 | 22438 | from __future__ import (nested_scopes, generators, division, absolute_import,
print_function, unicode_literals)
from six import iteritems
from six.moves import zip
import numpy as np
from numpy import zeros, array_equal
from itertools import count
from pyNastran.op2.tables.oes_stressStrain.real... | lgpl-3.0 |
MagicUmom/pattern_recognition_project | mysvm.py | 1 | 2161 | print(__doc__)
# Author: Gael Varoquaux <gael dot varoquaux at normalesup dot org>
# License: BSD 3 clause
# Standard scientific Python imports
import matplotlib.pyplot as plt
# Import datasets, classifiers and performance metrics
from sklearn import datasets, svm, metrics
# The digits dataset
digits = datasets.loa... | mit |
jensengrouppsu/rapid | rapid/__main__.py | 1 | 2598 | #! /usr/bin/env python
'''\
Spectral exchange can be run from the command line non-interactively
by giving it a text-based input file and having it generate data from
the input, or it can be run as an interactive GUI.
Authors: Seth M. Morton, Lasse Jensen
'''
from __future__ import print_function, division, absolute_... | mit |
madscatt/zazzie | src/scripts/convergence_test.py | 3 | 31326 | # from __future__ import absolute_import
# from __future__ import division
# from __future__ import print_function
# # from __future__ import unicode_literals
"""SASSIE: Copyright (C) 2011-2015 Joseph E. Curtis, Ph.D.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU G... | gpl-3.0 |
Adai0808/scikit-learn | sklearn/tests/test_common.py | 127 | 7665 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
from __future__ import print_function
import os
import warnings
import sys
import pkgutil
from sklearn.externals.six import PY3
fr... | bsd-3-clause |
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