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 |
|---|---|---|---|---|---|
alvarofierroclavero/scikit-learn | examples/semi_supervised/plot_label_propagation_digits.py | 268 | 2723 | """
===================================================
Label Propagation digits: Demonstrating performance
===================================================
This example demonstrates the power of semisupervised learning by
training a Label Spreading model to classify handwritten digits
with sets of very few labels.... | bsd-3-clause |
RomainBrault/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 |
pfnet/maf_example | caffe/util/classify.py | 1 | 1329 | import maflib.util
import numpy as np
import matplotlib.pyplot as plt
import caffe
import cPickle
def vis_square(data, padsize=1, padval=0):
data -= data.min()
data /= data.max()
n = int(np.ceil(np.sqrt(data.shape[0])))
padding = ((0, n ** 2 - data.shape[0]), (0, padsize), (0, padsize)) + ((0, 0),... | bsd-3-clause |
jergosh/slr_pipeline | bin/find_neighbourhood.py | 1 | 1938 | import re
import sys
import glob
import csv
from os import path
from argparse import ArgumentParser
from subprocess import Popen
import operator
from Bio import PDB
import numpy as np
import pandas
def rid2str(r):
return r.id[0] + str(r.id[1]) + r.id[2]
argparser = ArgumentParser()
argparser.add_argument("--pdb... | gpl-2.0 |
cactusbin/nyt | matplotlib/examples/api/legend_demo.py | 3 | 1134 | """
Demo of the legend function with a few features.
In addition to the basic legend, this demo shows a few optional features:
* Custom legend placement.
* A keyword argument to a drop-shadow.
* Setting the background color.
* Setting the font size.
* Setting the line width.
"""
import numpy as np... | unlicense |
qbilius/streams | streams/metrics/classifiers.py | 1 | 5903 | from collections import OrderedDict
import numpy as np
import scipy.stats
import pandas
import sklearn, sklearn.svm, sklearn.preprocessing, sklearn.linear_model
import streams.utils
class MatchToSampleClassifier(object):
def __init__(self, norm=True, nfeats=None, seed=None, C=1):
"""
A classifi... | gpl-3.0 |
phobson/statsmodels | statsmodels/tools/tools.py | 1 | 16566 | '''
Utility functions models code
'''
from statsmodels.compat.python import reduce, lzip, lmap, asstr2, range, long
import numpy as np
import numpy.lib.recfunctions as nprf
import numpy.linalg as L
from scipy.linalg import svdvals
from statsmodels.datasets import webuse
from statsmodels.tools.data import _is_using_pand... | bsd-3-clause |
ronggong/jingjuSingingPhraseMatching | general/dtwSankalp.py | 1 | 1657 | import sys,os
import matplotlib.pyplot as plt
# the project folder: fileDir
fileDir = os.path.dirname(os.path.realpath('__file__'))
dtwPath = os.path.join(fileDir, '../../Library_PythonNew/similarityMeasures/dtw/')
# transcribe the path string to full path
dtwPath = os.path.abspath(os.path.realpath(dtwPath))
sys.path... | agpl-3.0 |
cython-testbed/pandas | pandas/tests/indexing/test_categorical.py | 5 | 26870 | # -*- coding: utf-8 -*-
import pytest
import pandas as pd
import pandas.compat as compat
import numpy as np
from pandas import (Series, DataFrame, Timestamp, Categorical,
CategoricalIndex, Interval, Index)
from pandas.util.testing import assert_series_equal, assert_frame_equal
from pandas.util imp... | bsd-3-clause |
elenita1221/BDA_py_demos | demos_pystan/pystan_demo.py | 19 | 12220 | """Bayesian Data Analysis, 3rd ed
PyStan demo
Demo for using Stan with Python interface PyStan.
"""
import numpy as np
import pystan
import matplotlib.pyplot as plt
# edit default plot settings (colours from colorbrewer2.org)
plt.rc('font', size=14)
plt.rc('lines', color='#377eb8', linewidth=2)
plt.rc('axes', color... | gpl-3.0 |
hrjn/scikit-learn | sklearn/neural_network/tests/test_rbm.py | 225 | 6278 | import sys
import re
import numpy as np
from scipy.sparse import csc_matrix, csr_matrix, lil_matrix
from sklearn.utils.testing import (assert_almost_equal, assert_array_equal,
assert_true)
from sklearn.datasets import load_digits
from sklearn.externals.six.moves import cStringIO as ... | bsd-3-clause |
Obus/scikit-learn | sklearn/kernel_ridge.py | 44 | 6504 | """Module :mod:`sklearn.kernel_ridge` implements kernel ridge regression."""
# Authors: Mathieu Blondel <mathieu@mblondel.org>
# Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# License: BSD 3 clause
import numpy as np
from .base import BaseEstimator, RegressorMixin
from .metrics.pairwise import pairwise... | bsd-3-clause |
jakirkham/bokeh | examples/models/file/latex_extension.py | 3 | 2596 | """ The LaTex example was derived from: http://matplotlib.org/users/usetex.html
"""
from bokeh.models import Label
from bokeh.palettes import Spectral4
from bokeh.plotting import output_file, figure, show
import numpy as np
from scipy.special import jv
output_file('external_resources.html')
class LatexLabel(Label):... | bsd-3-clause |
jermainewang/mxnet | example/kaggle-ndsb1/training_curves.py | 52 | 1879 | # 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 u... | apache-2.0 |
rinman24/ucsd_ch | coimbra_chamber/tests/access/experiment/exp_acc_integration_test.py | 1 | 24445 | """Integration test suite for ChamberAccess."""
import dataclasses
import datetime
from decimal import Decimal
from unittest.mock import MagicMock
import dacite
import pytest
from nptdms import TdmsFile
from pandas import DataFrame
from pytz import utc
from sqlalchemy import and_
from coimbra_chamber.access.experime... | mit |
tmrowco/electricitymap | parsers/AU.py | 1 | 22469 | #!/usr/bin/env python3
import json
# The arrow library is used to handle datetimes
import arrow
import numpy as np
import pandas as pd
# The request library is used to fetch content through HTTP
import requests
from .lib import AU_battery, AU_solar
AMEO_CATEGORY_DICTIONARY = {
'Bagasse': 'biomass',
'Black C... | gpl-3.0 |
nkhuyu/neon | setup.py | 5 | 6352 | #!/usr/bin/env python
# ----------------------------------------------------------------------------
# Copyright 2014 Nervana Systems Inc.
# 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
#
# ... | apache-2.0 |
CharlesGulian/Deconv | write_pixel_offset.py | 1 | 2549 | # -*- coding: utf-8 -*-
"""
Created on Mon Sep 26 10:37:01 2016
@author: charlesgulian
"""
# Add (x,y) pixel offset to .FITS header of an image
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
class Image:
def __init__(self,filename,category,ID):
self.filename = filena... | gpl-3.0 |
RPGOne/Skynet | test_grid_search.py | 3 | 1451 | # Copyright 2015-present Scikit Flow 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... | bsd-3-clause |
wazeerzulfikar/scikit-learn | examples/decomposition/plot_ica_blind_source_separation.py | 52 | 2228 | """
=====================================
Blind source separation using FastICA
=====================================
An example of estimating sources from noisy data.
:ref:`ICA` is used to estimate sources given noisy measurements.
Imagine 3 instruments playing simultaneously and 3 microphones
recording the mixed si... | bsd-3-clause |
dmordom/nipype | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 154 | 7759 | import re, inspect, textwrap, pydoc
import sphinx
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config={}):
self.use_plots = config.get('use_plots', False)
NumpyDocString.__init__(self, docstring, config=config)
... | bsd-3-clause |
twbattaglia/koeken | setup.py | 1 | 1924 | import setuptools
from setuptools.command.install import install
# Install Necessary R packages
class CustomInstallPackages(install):
"""Customized setuptools install command - runs R package install one-liner."""
def run(self):
import subprocess
import shlex
print "Attempting to insta... | mit |
andybrnr/QuantEcon.py | examples/evans_sargent_plot1.py | 7 | 1086 | """
Plot 1 from the Evans Sargent model.
@author: David Evans
Edited by: John Stachurski
"""
import numpy as np
import matplotlib.pyplot as plt
from evans_sargent import T, y
tt = np.arange(T) # tt is used to make the plot time index correct.
n_rows = 3
fig, axes = plt.subplots(n_rows, 1, figsize=(10, 12))
plt.su... | bsd-3-clause |
ch3ll0v3k/scikit-learn | examples/plot_johnson_lindenstrauss_bound.py | 134 | 7452 | """
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected in... | bsd-3-clause |
antoinecarme/pyaf | tests/missing_data/test_missing_data_air_passengers_generic.py | 1 | 1810 |
import pandas as pd
import numpy as np
import pyaf.ForecastEngine as autof
import pyaf.Bench.TS_datasets as tsds
def add_some_missing_data_in_signal(df, col):
lRate = 0.2
df.loc[df.sample(frac=lRate, random_state=1960).index, col] = np.nan
return df
def add_some_missing_data_in_time(df, col):
lRate... | bsd-3-clause |
DBernardes/ProjetoECC | Ganho/Codigo/run.py | 1 | 2380 | #!/usr/bin/python
# -*- coding: UTF-8 -*-
"""
Criado em 08 de Novembro de 2016
Descricao: este codigo reune todas as bibliotecas responsaveis para a caracterizacao do ganho do CCD, sao elas:
plotGraph, logfile, makeList_imagesInput e Gain_processesImages. O codigo ira criar duas listas de imagens: flat e... | mit |
mjasher/gac | original_libraries/flopy-master/examples/scripts/flopy_swi2_ex3.py | 1 | 6979 | import os
import sys
import math
import numpy as np
import flopy.modflow as mf
import flopy.utils as fu
import matplotlib.pyplot as plt
# --modify default matplotlib settings
updates = {'font.family':['Univers 57 Condensed', 'Arial'],
'mathtext.default':'regular',
'pdf.compressi... | gpl-2.0 |
nikitasingh981/scikit-learn | sklearn/datasets/tests/test_svmlight_format.py | 53 | 13398 | from bz2 import BZ2File
import gzip
from io import BytesIO
import numpy as np
import scipy.sparse as sp
import os
import shutil
from tempfile import NamedTemporaryFile
from sklearn.externals.six import b
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.u... | bsd-3-clause |
supriyantomaftuh/innstereo | innstereo/main_ui.py | 1 | 116913 | #!/usr/bin/python3
"""
This module contains the startup-function and the MainWindow-class.
The MainWindow-class sets up the GUI and controls all its signals. All other
modules and clases are controlled from this class. The startup-function creates
the first instance of the GUI when the program starts.
"""
import gi
... | gpl-2.0 |
cg31/tensorflow | tensorflow/contrib/learn/python/learn/estimators/dnn_test.py | 5 | 39527 | # 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 |
wathen/PhD | MHD/FEniCS/MHD/Stabilised/SaddlePointForm/Test/SplitMatrix/ScottTest/Hartman2D/MHDfluid.py | 1 | 17145 | #!/usr/bin/python
# interpolate scalar gradient onto nedelec space
import petsc4py
import sys
petsc4py.init(sys.argv)
from petsc4py import PETSc
from dolfin import *
# from MatrixOperations import *
import numpy as np
import PETScIO as IO
import common
import scipy
import scipy.io
import time
import scipy.sparse as... | mit |
josherick/bokeh | bokeh/compat/mplexporter/tools.py | 75 | 1732 | """
Tools for matplotlib plot exporting
"""
def ipynb_vega_init():
"""Initialize the IPython notebook display elements
This function borrows heavily from the excellent vincent package:
http://github.com/wrobstory/vincent
"""
try:
from IPython.core.display import display, HTML
except I... | bsd-3-clause |
TomAugspurger/pandas | pandas/tests/series/methods/test_update.py | 2 | 4213 | import numpy as np
import pytest
from pandas import CategoricalDtype, DataFrame, NaT, Series, Timestamp
import pandas._testing as tm
class TestUpdate:
def test_update(self):
s = Series([1.5, np.nan, 3.0, 4.0, np.nan])
s2 = Series([np.nan, 3.5, np.nan, 5.0])
s.update(s2)
expected ... | bsd-3-clause |
RUBi-ZA/MODE-TASK | assemblyCovariance.py | 1 | 14726 | #!/usr/bin/env python
# assemblyCovariance.py
# Calculates covariance matrices for the following:
# 1) over all modes
# OR
# 2) specified modes
# AND
# 3) For a single asymmetric unit
# OR
# 4) For a cluster of specified asymmetric units
# Author: Caroline Ross: caroross299@gmail.com
# August 2017
# Calculates and Re... | gpl-3.0 |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/pandas/core/config.py | 13 | 22213 | """
The config module holds package-wide configurables and provides
a uniform API for working with them.
Overview
========
This module supports the following requirements:
- options are referenced using keys in dot.notation, e.g. "x.y.option - z".
- keys are case-insensitive.
- functions should accept partial/regex k... | apache-2.0 |
jhanley634/testing-tools | problem/bench/traffic/top_wikipedia_pages.py | 1 | 1926 | #! /usr/bin/env python
# Copyright 2020 John Hanley.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, me... | mit |
ueshin/apache-spark | python/pyspark/pandas/tests/test_rolling.py | 15 | 6920 | #
# 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 |
hunterowens/data-pipelines | dc_pipeline.py | 1 | 3588 | import pandas as pd
import requests
import folium
import luigi
YEARS = {2012: 'http://opendata.dc.gov/datasets/5f4ea2f25c9a45b29e15e53072126739_7.csv',
2013: 'http://opendata.dc.gov/datasets/4911fcf3527246ae9bf81b5553a48c4d_6.csv',
2014: 'http://opendata.dc.gov/datasets/d4891ca6951947538f6707a6b07ae2... | mit |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/utils/tests/test_linear_assignment.py | 421 | 1349 | # Author: Brian M. Clapper, G Varoquaux
# License: BSD
import numpy as np
# XXX we should be testing the public API here
from sklearn.utils.linear_assignment_ import _hungarian
def test_hungarian():
matrices = [
# Square
([[400, 150, 400],
[400, 450, 600],
[300, 225, 300]],
... | mit |
AISystena/web_crawler | lib/image_cnn_gpu/ImageTrainer.py | 1 | 6005 | # coding: utf-8
import six
import sys
import os.path
import pickle
import numpy as np
from sklearn.cross_validation import train_test_split
import chainer
import chainer.links as L
from chainer import optimizers, cuda
import matplotlib.pyplot as plt
import Util
from ImageCnn import ImageCnn
plt.style.use('ggplot')
... | mit |
davidam/python-examples | scikit/datasets/plot_out_of_core_classification.py | 3 | 13644 | """
======================================================
Out-of-core classification of text documents
======================================================
This is an example showing how scikit-learn can be used for classification
using an out-of-core approach: learning from data that doesn't fit into main
memory. ... | gpl-3.0 |
MartinDelzant/scikit-learn | examples/neighbors/plot_kde_1d.py | 347 | 5100 | """
===================================
Simple 1D Kernel Density Estimation
===================================
This example uses the :class:`sklearn.neighbors.KernelDensity` class to
demonstrate the principles of Kernel Density Estimation in one dimension.
The first plot shows one of the problems with using histogram... | bsd-3-clause |
datascopeanalytics/scrubadub | scrubadub/comparison.py | 1 | 13150 | import re
import copy
import random
from faker import Faker
from . import filth as filth_module
from .filth import Filth
from .detectors.known import KnownFilthItem
from typing import List, Dict, Union, Optional, Tuple
import pandas as pd
import sklearn.metrics
def get_filth_classification_report(
filth_li... | mit |
byzin/Nanairo | tool/spectral_transport/spectral_transport.py | 1 | 27081 | # file: spectral_transport.py
# Import system plugins
import math
import os
import sys
import time
# Import custom plugins
def printPluginError(plugin_name, package_name):
sys.stderr.write("'{}' is required.".format(plugin_name))
sys.stderr.write(" Please install the package using 'pip install {}'.\n".format(... | mit |
zihua/scikit-learn | examples/feature_selection/plot_f_test_vs_mi.py | 75 | 1647 | """
===========================================
Comparison of F-test and mutual information
===========================================
This example illustrates the differences between univariate F-test statistics
and mutual information.
We consider 3 features x_1, x_2, x_3 distributed uniformly over [0, 1], the
targ... | bsd-3-clause |
rrohan/scikit-learn | examples/classification/plot_lda.py | 70 | 2413 | """
====================================================================
Normal and Shrinkage Linear Discriminant Analysis for classification
====================================================================
Shows how shrinkage improves classification.
"""
from __future__ import division
import numpy as np
import... | bsd-3-clause |
MTgeophysics/mtpy | mtpy/imaging/plot_mt_response.py | 1 | 63921 | # -*- coding: utf-8 -*-
"""
=================
plot_mt_response
=================
Plots the resistivity and phase for different modes and components
Created 2017
@author: jpeacock
"""
# ==============================================================================
import os
import numpy as np
import matplotlib.pypl... | gpl-3.0 |
empeeu/numpy | numpy/core/tests/test_multiarray.py | 2 | 218049 | from __future__ import division, absolute_import, print_function
import collections
import tempfile
import sys
import os
import shutil
import warnings
import operator
import io
import itertools
if sys.version_info[0] >= 3:
import builtins
else:
import __builtin__ as builtins
from decimal import Decimal
impor... | bsd-3-clause |
cainiaocome/scikit-learn | examples/svm/plot_weighted_samples.py | 188 | 1943 | """
=====================
SVM: Weighted samples
=====================
Plot decision function of a weighted dataset, where the size of points
is proportional to its weight.
The sample weighting rescales the C parameter, which means that the classifier
puts more emphasis on getting these points right. The effect might ... | bsd-3-clause |
florian-f/sklearn | examples/linear_model/plot_sgd_separating_hyperplane.py | 12 | 1201 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print(__doc__)
import numpy as n... | bsd-3-clause |
spallavolu/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 242 | 5885 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
BorisJeremic/Real-ESSI-Examples | analytic_solution/test_cases/Contact/Stress_Based_Contact_Verification/SoftContact_NonLinHardSoftShear/Area/Normal_Stress_Plot.py | 6 | 4510 | #!/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 |
SCECcode/BBP | bbp/comps/bbp_status.py | 1 | 9070 | #!/usr/bin/env python
"""
Copyright 2010-2018 University Of Southern California
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 appli... | apache-2.0 |
faraz117/Traffic-Congestion-Estimator | EdgeDetection2.py | 1 | 16913 |
from __future__ import division
import cv2
import numpy as np
import time
import os
import imutils
from sklearn.externals import joblib
from scipy.cluster.vq import *
# initialize the current frame of the video, along with the list of
# ROI points along with whether or not this is input mode
roiPts = []
inputMode = F... | gpl-2.0 |
jseabold/scikit-learn | examples/linear_model/lasso_dense_vs_sparse_data.py | 348 | 1862 | """
==============================
Lasso on dense and sparse data
==============================
We show that linear_model.Lasso provides the same results for dense and sparse
data and that in the case of sparse data the speed is improved.
"""
print(__doc__)
from time import time
from scipy import sparse
from scipy ... | bsd-3-clause |
dsquareindia/scikit-learn | sklearn/datasets/__init__.py | 61 | 3734 | """
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_breast_cancer
from .base import load_boston
from .base import load_diabetes
from .base import load_digi... | bsd-3-clause |
ningchi/scikit-learn | examples/applications/wikipedia_principal_eigenvector.py | 233 | 7819 | """
===============================
Wikipedia principal eigenvector
===============================
A classical way to assert the relative importance of vertices in a
graph is to compute the principal eigenvector of the adjacency matrix
so as to assign to each vertex the values of the components of the first
eigenvect... | bsd-3-clause |
rcompton/black-market-recommender-systems | bmrs/parsers/silkroad2.py | 1 | 3561 | #!/usr/bin/python3
# coding: utf-8
from bs4 import BeautifulSoup
import re
import pandas as pd
import dateutil
import os
import traceback
import unicodedata as ud
import logging
FORMAT = '%(asctime)-15s %(levelname)-6s %(message)s'
DATE_FORMAT = '%b %d %H:%M:%S'
formatter = logging.Formatter(fmt=FORMAT, datefmt=DATE_F... | gpl-3.0 |
Salahub/uwaterloo-igem-2015 | models/tridimensional/docking_validation/csv_results_clusterscore.py | 6 | 10637 | import argparse
import csv
import matplotlib.pyplot as plt
import numpy as np
import os
import scipy.cluster.hierarchy as hac
import scipy.spatial.distance as scidist
from csv_results import csv_header_bugfix
from constants import CSV_HEADER, DNA_ALPHABET
from utility import safe_mkdir
def csv_load(fullpath):
""... | mit |
ryfeus/lambda-packs | Tensorflow_LightGBM_Scipy_nightly/source/numpy/core/function_base.py | 18 | 12340 | from __future__ import division, absolute_import, print_function
import warnings
import operator
from . import numeric as _nx
from .numeric import (result_type, NaN, shares_memory, MAY_SHARE_BOUNDS,
TooHardError,asanyarray)
__all__ = ['logspace', 'linspace', 'geomspace']
def _index_deprecate(... | mit |
lbdreyer/iris | docs/iris/src/conf.py | 2 | 10980 | # Copyright Iris contributors
#
# This file is part of Iris and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
# -*- coding: utf-8 -*-
#
# Iris documentation build configuration file, created by
# sphinx-quickstart on Tue May 25 13:26:23... | lgpl-3.0 |
toastedcornflakes/scikit-learn | examples/manifold/plot_mds.py | 88 | 2731 | """
=========================
Multi-dimensional scaling
=========================
An illustration of the metric and non-metric MDS on generated noisy data.
The reconstructed points using the metric MDS and non metric MDS are slightly
shifted to avoid overlapping.
"""
# Author: Nelle Varoquaux <nelle.varoquaux@gmail.... | bsd-3-clause |
kpolimis/sklearn-forest-ci | doc/conf.py | 2 | 10581 | # -*- coding: utf-8 -*-
#
# project-template documentation build configuration file, created by
# sphinx-quickstart on Mon Jan 18 14:44:12 2016.
#
# 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 fi... | bsd-3-clause |
Silmathoron/NNGT | doc/examples/groups_and_metagroups.py | 1 | 3612 | #!/usr/bin/env python
#-*- coding:utf-8 -*-
#
# This file is part of the NNGT project to generate and analyze
# neuronal networks and their activity.
# Copyright (C) 2015-2019 Tanguy Fardet
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License a... | gpl-3.0 |
JohnBSmith/JohnBSmith.github.io | templates/Matplotlib/plot-center.py | 1 | 2470 |
# A template for simple plots, viewed on screen
# and included in HTML documents.
import matplotlib as mp
import matplotlib.pyplot as plot
from numpy import arange, array
from math import pi, sin, cos, tan, exp, log
lw_grid = 1.6
lw_line = 2.2
axes_color = "#505050"
blue = [0,0.2,0.6,0.8]
green = [0,0.46,0,0.8]
mag... | cc0-1.0 |
ChanChiChoi/scikit-learn | sklearn/tree/tests/test_tree.py | 72 | 47440 | """
Testing for the tree module (sklearn.tree).
"""
import pickle
from functools import partial
from itertools import product
import platform
import numpy as np
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from sklearn.random_projection import sparse_rand... | bsd-3-clause |
joshpeng/Network-Intrusions-Flask | app/views.py | 1 | 3102 | """
Contains main routes for the Prediction App
"""
from flask import render_template
from flask_wtf import Form
from wtforms import fields
from wtforms.validators import Required
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
from . import app, target... | mit |
jakereps/qiime2 | qiime2/metadata/tests/test_io.py | 1 | 42757 | # ----------------------------------------------------------------------------
# Copyright (c) 2016-2021, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... | bsd-3-clause |
gem/oq-engine | openquake/calculators/base.py | 1 | 55094 | # -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2014-2021 GEM Foundation
#
# OpenQuake 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 Licen... | agpl-3.0 |
ettm2012/MissionPlanner | Lib/site-packages/numpy/doc/creation.py | 94 | 5411 | """
==============
Array Creation
==============
Introduction
============
There are 5 general mechanisms for creating arrays:
1) Conversion from other Python structures (e.g., lists, tuples)
2) Intrinsic numpy array array creation objects (e.g., arange, ones, zeros,
etc.)
3) Reading arrays from disk, either from... | gpl-3.0 |
MBARIMike/stoqs | stoqs/contrib/analysis/classify.py | 3 | 21623 | #!/usr/bin/env python
"""
Script to execute steps in the classification of measurements including:
1. Labeling specific MeasuredParameters
2. Tagging MeasuredParameters based on a model
Mike McCann
MBARI 16 June 2014
"""
import os
import sys
# Insert Django App directory (parent of config) into python path
sys.pat... | gpl-3.0 |
imaculate/scikit-learn | sklearn/tests/test_grid_search.py | 68 | 28856 | """
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 warnings
import sys
import numpy as np
import sci... | bsd-3-clause |
paulmueller/bornscat | examples/compare_mie_2d.py | 2 | 1390 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
""" TODO
compare scattered field of Rytov with Mie scattering
"""
from __future__ import division
from __future__ import print_function
import numpy as np
import matplotlib
matplotlib.use("wxagg")
from matplotlib import pylab as plt
import os
import sys
import time
imp... | bsd-3-clause |
unnikrishnankgs/va | venv/lib/python3.5/site-packages/mpl_toolkits/axes_grid1/mpl_axes.py | 10 | 5045 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import warnings
import matplotlib.axes as maxes
from matplotlib.artist import Artist
from matplotlib.axis import XAxis, YAxis
class SimpleChainedObjects(object):
def __init__(self, objects):
... | bsd-2-clause |
rs2/pandas | pandas/core/flags.py | 1 | 3566 | import weakref
class Flags:
"""
Flags that apply to pandas objects.
.. versionadded:: 1.2.0
Parameters
----------
obj : Series or DataFrame
The object these flags are associated with
allows_duplicate_labels : bool, default True
Whether to allow duplicate labels in this ob... | bsd-3-clause |
jstoxrocky/statsmodels | statsmodels/genmod/_prediction.py | 27 | 9437 | # -*- coding: utf-8 -*-
"""
Created on Fri Dec 19 11:29:18 2014
Author: Josef Perktold
License: BSD-3
"""
import numpy as np
from scipy import stats
# this is similar to ContrastResults after t_test, partially copied and adjusted
class PredictionResults(object):
def __init__(self, predicted_mean, var_pred_mean... | bsd-3-clause |
andyh616/mne-python | examples/inverse/plot_lcmv_beamformer_volume.py | 18 | 3046 | """
===================================================================
Compute LCMV inverse solution on evoked data in volume source space
===================================================================
Compute LCMV inverse solution on an auditory evoked dataset in a volume source
space. It stores the solution in... | bsd-3-clause |
castelao/CoTeDe | cotede/qctests/tukey53H.py | 1 | 3985 | # -*- coding: utf-8 -*-
"""
Shall I use a decorator??
DATA = [25.32, 25.34, 25.34, 25.31, 24.99, 23.46, 21.85, 17.95, 15.39, 11.08, 6.93, 7.93, 5.71, 3.58, np.nan, 1, 1]
tukey53H(np.array, np.maskedArray, pd.Series, xr.DataArray)
delta = tukey53H(x)
w = np.hamming(l)
sigma = (ma.convolve(x, w, mode... | bsd-3-clause |
glouppe/scikit-learn | sklearn/neighbors/tests/test_nearest_centroid.py | 305 | 4121 | """
Testing for the nearest centroid module.
"""
import numpy as np
from scipy import sparse as sp
from numpy.testing import assert_array_equal
from numpy.testing import assert_equal
from sklearn.neighbors import NearestCentroid
from sklearn import datasets
from sklearn.metrics.pairwise import pairwise_distances
# t... | bsd-3-clause |
0x0all/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/numerix/__init__.py | 69 | 5473 | """
numerix imports either Numeric or numarray based on various selectors.
0. If the value "--numpy","--numarray" or "--Numeric" is specified on the
command line, then numerix imports the specified
array package.
1. The value of numerix in matplotlibrc: either Numeric or numarray
2. If none of the above is... | gpl-3.0 |
fspaolo/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 |
francesco-mannella/dmp-esn | parametric/parametric_dmp/bin/tr_datasets/e_cursive_curves_angles_LWPR_10/data/results/plot.py | 18 | 1043 | #!/usr/bin/env python
import glob
import numpy as np
import matplotlib.pyplot as plt
import os
import sys
pathname = os.path.dirname(sys.argv[0])
if pathname:
os.chdir(pathname)
n_dim = None
trains = []
for fname in glob.glob("tl*"):
t = np.loadtxt(fname)
trains.append(t)
tests = []
for fname in glob... | gpl-2.0 |
yavalvas/yav_com | build/matplotlib/lib/mpl_toolkits/axes_grid1/inset_locator.py | 8 | 10138 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from matplotlib.offsetbox import AnchoredOffsetbox
#from matplotlib.transforms import IdentityTransform
import matplotlib.transforms as mtrans
from .parasite_axes import HostAxes # subclasses mpl... | mit |
alvarofierroclavero/scikit-learn | examples/linear_model/plot_bayesian_ridge.py | 248 | 2588 | """
=========================
Bayesian Ridge Regression
=========================
Computes a Bayesian Ridge Regression on a synthetic dataset.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary least squares) estimator, the coefficient
weights are slightly shift... | bsd-3-clause |
alexeyum/scikit-learn | sklearn/covariance/tests/test_covariance.py | 79 | 12193 | # 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 |
nuclear-wizard/moose | python/peacock/tests/postprocessor_tab/test_PostprocessorViewer.py | 12 | 4638 | #!/usr/bin/env python3
#* This file is part of the MOOSE framework
#* https://www.mooseframework.org
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moose/blob/master/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgp... | lgpl-2.1 |
smarden1/airflow | airflow/hooks/postgres_hook.py | 3 | 2076 | import psycopg2
from airflow import settings
from airflow.utils import AirflowException
from airflow.models import Connection
class PostgresHook(object):
'''
Interact with Postgres.
'''
def __init__(
self, host=None, login=None,
psw=None, db=None, port=None, postgres_conn_id=... | apache-2.0 |
dvida/UWO-PA-Python-Course | Lecture 6/L6_lecture.py | 1 | 6176 | from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
# Let's create some noisy data that should follow a line
# Parameters of a line
m = 2.6
k = 10.8
# Let's define a function describing a line
def line(x, m, k):
return m*x + k
# Generate the line data
... | mit |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/matplotlib/tests/test_agg.py | 3 | 4896 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
import io
import os
import numpy as np
from numpy.testing import assert_array_almost_equal
from matplotlib.image import imread
from matplotlib.backends.backend_agg import... | apache-2.0 |
ibaidev/gplib | gplib/plot.py | 1 | 7181 | # -*- coding: utf-8 -*-
#
# Copyright 2018 Ibai Roman
#
# This file is part of GPlib.
#
# GPlib is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your ... | gpl-3.0 |
yavalvas/yav_com | build/matplotlib/examples/pylab_examples/multiple_yaxis_with_spines.py | 6 | 1582 | import matplotlib.pyplot as plt
def make_patch_spines_invisible(ax):
ax.set_frame_on(True)
ax.patch.set_visible(False)
for sp in ax.spines.itervalues():
sp.set_visible(False)
fig, host = plt.subplots()
fig.subplots_adjust(right=0.75)
par1 = host.twinx()
par2 = host.twinx()
# Offset the right spi... | mit |
rkmaddox/expyfun | doc/conf.py | 1 | 10310 | # -*- coding: utf-8 -*-
#
# Expyfun documentation build configuration file, created by
# sphinx-quickstart on Fri Jun 11 10:45:48 2010.
#
# 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.
#
# A... | bsd-3-clause |
wsmorgan/782 | docs/conf.py | 1 | 10259 | # -*- coding: utf-8 -*-
#
# basis documentation build configuration file, created by
# sphinx-quickstart on Tue Sep 27 09:52:04 2016.
#
# 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... | mit |
Avsecz/concise | concise/utils/plot.py | 1 | 9272 | import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import MaxNLocator
from mpl_toolkits.axes_grid1 import make_axes_locatable
import math
from concise.preprocessing.sequence import DNA, RNA, AMINO_ACIDS
from concise.utils.letters import all_letters
from collections import OrderedDict
from matpl... | mit |
planetarymike/IDL-Colorbars | IDL_py_test/093_Multihue_Red1.py | 1 | 8802 | from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
cm_data = [[0.0000208612, 0.0000200049, 0.0000198463],
[0.00038926, 0.000346551, 0.000249987],
[0.00114175, 0.000989297, 0.000648277],
[0.00225249, 0.00190778, 0.00116452],
[0.003715, 0.00307964, 0.001769],
[0.00552993, 0.00448905, 0.00244... | gpl-2.0 |
pprett/scikit-learn | examples/ensemble/plot_adaboost_hastie_10_2.py | 355 | 3576 | """
=============================
Discrete versus Real AdaBoost
=============================
This example is based on Figure 10.2 from Hastie et al 2009 [1] and illustrates
the difference in performance between the discrete SAMME [2] boosting
algorithm and real SAMME.R boosting algorithm. Both algorithms are evaluate... | bsd-3-clause |
ndingwall/scikit-learn | examples/model_selection/plot_nested_cross_validation_iris.py | 23 | 4413 | """
=========================================
Nested versus non-nested cross-validation
=========================================
This example compares non-nested and nested cross-validation strategies on a
classifier of the iris data set. Nested cross-validation (CV) is often used to
train a model in which hyperparam... | bsd-3-clause |
Windy-Ground/scikit-learn | sklearn/linear_model/sag.py | 64 | 9815 | """Solvers for Ridge and LogisticRegression using SAG algorithm"""
# Authors: Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
#
# Licence: BSD 3 clause
import numpy as np
import warnings
from ..utils import ConvergenceWarning
from ..utils import check_array
from .base import make_dataset
from .sgd_fast import Log, Squ... | bsd-3-clause |
shusenl/scikit-learn | sklearn/linear_model/coordinate_descent.py | 59 | 76336 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Gael Varoquaux <gael.varoquaux@inria.fr>
#
# License: BSD 3 clause
import sys
import warnings
from abc import ABCMeta, abstractmethod
import n... | bsd-3-clause |
nan86150/ImageFusion | lib/python2.7/site-packages/matplotlib/patches.py | 10 | 142681 | # -*- coding: utf-8 -*-
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import map, zip
import math
import matplotlib as mpl
import numpy as np
import matplotlib.cbook as cbook
import matplotlib.artist as artist
from matplotlib.a... | mit |
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