repo_name stringlengths 6 100 | path stringlengths 4 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 935 727k | license stringclasses 15
values |
|---|---|---|---|---|---|
eig-2017/the-magical-csv-merge-machine | merge_machine/test_es.py | 1 | 8679 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 18 16:42:41 2017
@author: m75380
# Ideas: Learn analysers and weights for blocking on ES directly
# Put all fields to learn blocking by exact match on other fields
https://www.elastic.co/guide/en/elasticsearch/reference/current/multi-fields.html
... | mit |
elkingtonmcb/scikit-learn | sklearn/neighbors/regression.py | 100 | 11017 | """Nearest Neighbor Regression"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck <L.J.Buitinck@uva.nl>
# Multi-output support by Arna... | bsd-3-clause |
shangwuhencc/scikit-learn | examples/plot_kernel_approximation.py | 262 | 8004 | """
==================================================
Explicit feature map approximation for RBF kernels
==================================================
An example illustrating the approximation of the feature map
of an RBF kernel.
.. currentmodule:: sklearn.kernel_approximation
It shows how to use :class:`RBFSa... | bsd-3-clause |
deepesch/scikit-learn | examples/svm/plot_svm_margin.py | 318 | 2328 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
SVM Margins Example
=========================================================
The plots below illustrate the effect the parameter `C` has
on the separation line. A large value of `C` basically tells
our model that w... | bsd-3-clause |
hjanime/VisTrails | vistrails/packages/matplotlib/artists.py | 3 | 230248 | from __future__ import division
from vistrails.core.modules.vistrails_module import Module
from bases import MplProperties
import matplotlib.artist
import matplotlib.cbook
def translate_color(c):
return c.tuple
def translate_MplLine2DProperties_marker(val):
translate_dict = {'caretright': 5, 'star': '*'... | bsd-3-clause |
stonneau/cwc_tests | src/tools/plot_utils.py | 2 | 11856 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 16 09:16:56 2015
@author: adelpret
"""
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
DEFAULT_FONT_SIZE = 40;
DEFAULT_AXIS_FONT_SIZE = DEFAULT_FONT_SIZE;
DEFAULT_LINE_WIDTH = 8; #13;
DEFAULT_MARKER_SIZE = 6;... | gpl-3.0 |
kashif/scikit-learn | sklearn/ensemble/tests/test_voting_classifier.py | 22 | 6543 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble import RandomForestCl... | bsd-3-clause |
kagayakidan/scikit-learn | sklearn/metrics/cluster/supervised.py | 207 | 27395 | """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>
# License: BSD 3 clause
fr... | bsd-3-clause |
rs2/pandas | pandas/tests/groupby/test_function.py | 1 | 33782 | import builtins
from io import StringIO
import numpy as np
import pytest
from pandas.errors import UnsupportedFunctionCall
import pandas as pd
from pandas import DataFrame, Index, MultiIndex, Series, Timestamp, date_range, isna
import pandas._testing as tm
import pandas.core.nanops as nanops
from pandas.util import ... | bsd-3-clause |
sinhrks/pandas-ml | pandas_ml/snsaccessors/base.py | 1 | 7540 | #!/usr/bin/env python
import pandas as pd
from pandas_ml.core.accessor import _AccessorMethods, _attach_methods
class SeabornMethods(_AccessorMethods):
"""Accessor to ``sklearn.cluster``."""
_module_name = 'seaborn'
_module_attrs = ['palplot', 'set', 'axes_style', 'plotting_context',
... | bsd-3-clause |
lancezlin/ml_template_py | lib/python2.7/site-packages/matplotlib/backends/backend_wxagg.py | 8 | 5866 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
import matplotlib
from matplotlib.figure import Figure
from .backend_agg import FigureCanvasAgg
from . import wx_compat as wxc
from . import backend_wx
from .backend_wx i... | mit |
mugizico/scikit-learn | examples/datasets/plot_iris_dataset.py | 283 | 1928 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
The Iris Dataset
=========================================================
This data sets consists of 3 different types of irises'
(Setosa, Versicolour, and Virginica) petal and sepal
length, stored in a 150x4 numpy... | bsd-3-clause |
NMTHydro/Recharge | utils/tornadoPlot_SA.py | 1 | 4933 | # ===============================================================================
# Copyright 2016 dgketchum
#
# 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/licens... | apache-2.0 |
466152112/scikit-learn | examples/ensemble/plot_voting_decision_regions.py | 230 | 2386 | """
==================================================
Plot the decision boundaries of a VotingClassifier
==================================================
Plot the decision boundaries of a `VotingClassifier` for
two features of the Iris dataset.
Plot the class probabilities of the first sample in a toy dataset
pred... | bsd-3-clause |
TomAugspurger/pandas | pandas/core/arrays/sparse/scipy_sparse.py | 1 | 5381 | """
Interaction with scipy.sparse matrices.
Currently only includes to_coo helpers.
"""
from pandas.core.indexes.api import Index, MultiIndex
from pandas.core.series import Series
def _check_is_partition(parts, whole):
whole = set(whole)
parts = [set(x) for x in parts]
if set.intersection(*parts) != set(... | bsd-3-clause |
JosmanPS/scikit-learn | sklearn/decomposition/tests/test_online_lda.py | 48 | 12645 | import numpy as np
from scipy.linalg import block_diag
from scipy.sparse import csr_matrix
from scipy.special import psi
from sklearn.decomposition import LatentDirichletAllocation
from sklearn.decomposition._online_lda import (_dirichlet_expectation_1d,
_dirichlet_expect... | bsd-3-clause |
NicholasBermuda/transit-fitting | transitfit/kepler.py | 1 | 5322 | from __future__ import print_function, division
import re
import pandas as pd
import numpy as np
import kplr
from .lightcurve import LightCurve, Planet, BinaryLightCurve
KEPLER_CADENCE = 1626./86400
def lc_dataframe(lc):
"""Returns a pandas DataFrame of given lightcurve data
"""
with lc.open() as f:
... | mit |
equialgo/scikit-learn | sklearn/datasets/base.py | 5 | 26099 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import sys
import shutil
from os import environ... | bsd-3-clause |
KawalMusikIndonesia/kimi | kimiserver/apps/run_tests.py | 16 | 6040 | from dejavu.testing import *
from dejavu import Dejavu
from optparse import OptionParser
import matplotlib.pyplot as plt
import time
import shutil
usage = "usage: %prog [options] TESTING_AUDIOFOLDER"
parser = OptionParser(usage=usage, version="%prog 1.1")
parser.add_option("--secs",
action="store",
... | gpl-3.0 |
DrSkippy/php_books_database | tools/bookdbtool/visualizations.py | 1 | 1064 | import logging
import pandas as pd
import matplotlib.pyplot as plt
def running_total_comparison(df1, window=15):
fig_size = [12,12]
xlim = [0,365]
ylim = [0,max(df1.Pages)]
years = df1.Year.unique()[-window:].tolist()
y = years.pop(0)
_df = df1.loc[df1.Year == y]
ax = _df.plot("Day", "Page... | bsd-2-clause |
tomaslaz/KLMC_Analysis | DM_DOS.py | 2 | 6477 | #!/usr/bin/env python
"""
A script to plot DOS (integrated)
@author Tomas Lazauskas, David Mora Fonz, 2016
@web www.lazauskas.net
@email tomas.lazauskas[a]gmail.com
"""
import copy
import math
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
from optparse import OptionPars... | gpl-3.0 |
yl565/statsmodels | statsmodels/examples/ex_kernel_regression.py | 34 | 1785 | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 02 09:17:40 2013
Author: Josef Perktold based on test file by George Panterov
"""
from __future__ import print_function
import numpy as np
import numpy.testing as npt
import statsmodels.nonparametric.api as nparam
#import statsmodels.api as sm
#nparam = sm.nonparametri... | bsd-3-clause |
bthirion/scikit-learn | sklearn/decomposition/tests/test_nmf.py | 28 | 17934 | import numpy as np
import scipy.sparse as sp
import numbers
from scipy import linalg
from sklearn.decomposition import NMF, non_negative_factorization
from sklearn.decomposition import nmf # For testing internals
from scipy.sparse import csc_matrix
from sklearn.utils.testing import assert_true
from sklearn.utils.te... | bsd-3-clause |
simonsfoundation/CaImAn | caiman/source_extraction/volpy/mrcnn/visualize.py | 2 | 19666 | """
Mask R-CNN
Display and Visualization Functions.
Copyright (c) 2017 Matterport, Inc.
Licensed under the MIT License (see LICENSE for details)
Written by Waleed Abdulla
"""
import os
import sys
import random
import itertools
import colorsys
import numpy as np
from skimage.measure import find_contours
import matplo... | gpl-2.0 |
lhilt/scipy | scipy/signal/wavelets.py | 4 | 10504 | from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.dual import eig
from scipy.special import comb
from scipy.signal import convolve
__all__ = ['daub', 'qmf', 'cascade', 'morlet', 'ricker', 'cwt']
def daub(p):
"""
The coefficients for the FIR low-pass filter produc... | bsd-3-clause |
alekz112/statsmodels | statsmodels/sandbox/examples/example_crossval.py | 33 | 2232 |
import numpy as np
from statsmodels.sandbox.tools import cross_val
if __name__ == '__main__':
#A: josef-pktd
import statsmodels.api as sm
from statsmodels.api import OLS
#from statsmodels.datasets.longley import load
from statsmodels.datasets.stackloss import load
from statsmodels.iolib.tab... | bsd-3-clause |
elijah513/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
PhasesResearchLab/ESPEI | espei/plot.py | 1 | 46082 | """
Plotting of input data and calculated database quantities
"""
import warnings
from collections import OrderedDict
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
import numpy as np
import tinydb
from sympy import Symbol
from pycalphad import Model, calculate, equilibrium, variables as v
from pyca... | mit |
costypetrisor/scikit-learn | sklearn/grid_search.py | 4 | 34405 | """
The :mod:`sklearn.grid_search` includes utilities to fine-tune the parameters
of an estimator.
"""
from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# ... | bsd-3-clause |
nhuntwalker/astroML | book_figures/chapter10/fig_arrival_time.py | 3 | 4743 | """
Arrival Time Analysis
---------------------
Figure 10.24
Modeling time-dependent flux based on arrival time data. The top-right panel
shows the rate r(t) = r0[1 + a sin(omega t + phi)], along with the locations
of the 104 detected photons. The remaining panels show the model contours
calculated via MCMC; dotted li... | bsd-2-clause |
mahak/spark | python/pyspark/pandas/data_type_ops/categorical_ops.py | 5 | 2506 | #
# 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 |
nhejazi/scikit-learn | sklearn/utils/testing.py | 2 | 31011 | """Testing utilities."""
# Copyright (c) 2011, 2012
# Authors: Pietro Berkes,
# Andreas Muller
# Mathieu Blondel
# Olivier Grisel
# Arnaud Joly
# Denis Engemann
# Giorgio Patrini
# Thierry Guillemot
# License: BSD 3 clause
import os
import inspect
import p... | bsd-3-clause |
kpespinosa/BuildingMachineLearningSystemsWithPython | ch09/02_ceps_based_classifier.py | 24 | 3574 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
import numpy as np
from collections import defaultdict
from sklearn.metrics import precision_recall_cu... | mit |
benitesf/Skin-Lesion-Analysis-Towards-Melanoma-Detection | test/gabor/gabor_fourier_plots.py | 1 | 3944 | import numpy as np
import matplotlib.pyplot as plt
from scipy import fftpack
def plot_surface3d(Z):
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from matplotlib import cm
from mpl_toolkits.mplot3d import axes3d
fig = plt.figure()
ax = fig.gca(projection='3d')
x = np.floor(... | mit |
chairmanmeow50/Brainspawn | brainspawn/plots/plot.py | 1 | 2326 | """ Module for plots. Plots with one matplotlib subplot should extend from
this class. Otherwise if multiple plots are needed, must extend from actual
BasePlot.
"""
import gtk
from abc import ABCMeta, abstractmethod
from plots.base_plot import BasePlot
from plots.configuration import Configuration
import settings
cl... | bsd-3-clause |
IshankGulati/scikit-learn | examples/linear_model/plot_ols_3d.py | 350 | 2040 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Sparsity Example: Fitting only features 1 and 2
=========================================================
Features 1 and 2 of the diabetes-dataset are fitted and
plotted below. It illustrates that although feature... | bsd-3-clause |
sonnyhu/scikit-learn | examples/feature_selection/plot_rfe_with_cross_validation.py | 161 | 1380 | """
===================================================
Recursive feature elimination with cross-validation
===================================================
A recursive feature elimination example with automatic tuning of the
number of features selected with cross-validation.
"""
print(__doc__)
import matplotlib.p... | bsd-3-clause |
abelfunctions/abelfunctions | abelfunctions/differentials.py | 1 | 23366 | r"""Differentials :mod:`abelfunctions.differentials`
================================================
This module contains functions for computing a basis of holomorphic
differentials of a Riemann surface given by a complex plane algebraic curve
:math:`f \in \mathbb{C}[x,y]`. A differential :math:`\omega = h(x,y)dx` d... | mit |
3324fr/spinalcordtoolbox | dev/tamag/old/msct_get_centerline_from_labels.py | 1 | 10205 | #!/usr/bin/env python
import numpy as np
import commands, sys
# Get path of the toolbox
status, path_sct = commands.getstatusoutput('echo $SCT_DIR')
# Append path that contains scripts, to be able to load modules
sys.path.append(path_sct + '/scripts')
sys.path.append('/home/tamag/code')
from msct_image import Imag... | mit |
ryfeus/lambda-packs | LightGBM_sklearn_scipy_numpy/source/sklearn/neighbors/regression.py | 8 | 10967 | """Nearest Neighbor Regression"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck
# Multi-output support by Arnaud Joly <a.joly@ulg.ac... | mit |
bchappet/dnfpy | src/dnfpyUtils/stats/clusterMap1.py | 1 | 1863 | from dnfpy.core.map2D import Map2D
import numpy as np
from sklearn.cluster import DBSCAN
import scipy.spatial.distance as dist
from dnfpyUtils.stats.clusteMap import ClusterMap
class ClusterMap1(ClusterMap):
"""
For 1 bubble!! 1 cluster is computed simply as barycenter
Params:
"continuity" : float ... | gpl-2.0 |
kevalds51/sympy | sympy/plotting/plot.py | 55 | 64797 | """Plotting module for Sympy.
A plot is represented by the ``Plot`` class that contains a reference to the
backend and a list of the data series to be plotted. The data series are
instances of classes meant to simplify getting points and meshes from sympy
expressions. ``plot_backends`` is a dictionary with all the bac... | bsd-3-clause |
ysig/BioClassSim | source/classify/classifier.py | 1 | 1697 | import numpy as np
from sklearn import svm
def kernelization(X,t=0):
# for 1 to 3 array is considered symmetric
if(t==1):
#spectrum clip
e,v = np.linalg.eig(X)
ep = np.maximum.reduce([e,np.zeros(e.shape[0])])
S = np.dot(v.T,np.dot(np.diag(ep),v))
... | apache-2.0 |
ucbtrans/sumo-project | examples/10_cars/runner-update_6_9_16.py | 1 | 18135 | #!/usr/bin/env python
#@file runner.py
import os
import sys
import optparse
import subprocess
import random
import pdb
import matplotlib.pyplot as plt
import math
import numpy, scipy.io
sys.path.append(os.path.join('..', '..', 'utils'))
# import python modules from $SUMO_HOME/tools directory
try:
sys.path.appen... | bsd-2-clause |
mne-tools/mne-python | logo/generate_mne_logos.py | 13 | 7174 | # -*- coding: utf-8 -*-
"""
===============================================================================
Script 'mne logo'
===============================================================================
This script makes the logo for MNE.
"""
# @author: drmccloy
# Created on Mon Jul 20 11:28:16 2015
# License: BSD ... | bsd-3-clause |
Achuth17/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 |
sinkap/trappy | tests/test_baretrace.py | 2 | 3406 | # Copyright 2015-2016 ARM Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in w... | apache-2.0 |
NunoEdgarGub1/scikit-learn | examples/ensemble/plot_ensemble_oob.py | 259 | 3265 | """
=============================
OOB Errors for Random Forests
=============================
The ``RandomForestClassifier`` is trained using *bootstrap aggregation*, where
each new tree is fit from a bootstrap sample of the training observations
:math:`z_i = (x_i, y_i)`. The *out-of-bag* (OOB) error is the average er... | bsd-3-clause |
herow/planning_qgis | python/plugins/processing/algs/qgis/PolarPlot.py | 5 | 3040 | # -*- coding: utf-8 -*-
"""
***************************************************************************
BarPlot.py
---------------------
Date : January 2013
Copyright : (C) 2013 by Victor Olaya
Email : volayaf at gmail dot com
******************************... | gpl-2.0 |
vermouthmjl/scikit-learn | sklearn/decomposition/tests/test_fastica.py | 272 | 7798 | """
Test the fastica algorithm.
"""
import itertools
import warnings
import numpy as np
from scipy import stats
from nose.tools import assert_raises
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from skl... | bsd-3-clause |
glennq/scikit-learn | examples/linear_model/plot_logistic_l1_l2_sparsity.py | 384 | 2601 | """
==============================================
L1 Penalty and Sparsity in Logistic Regression
==============================================
Comparison of the sparsity (percentage of zero coefficients) of solutions when
L1 and L2 penalty are used for different values of C. We can see that large
values of C give mo... | bsd-3-clause |
Erotemic/plottool | plottool_ibeis/__MPL_INIT__.py | 1 | 8661 | # -*- coding: utf-8 -*-
"""
Notes:
To use various backends certian packages are required
PyQt
...
Tk
pip install
sudo apt-get install tk
sudo apt-get install tk-dev
Wx
pip install wxPython
GTK
pip install PyGTK
pip install pygobject
pip install pygobject
Cair... | apache-2.0 |
Aasmi/scikit-learn | sklearn/externals/joblib/__init__.py | 36 | 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 |
jswanljung/iris | docs/iris/src/userguide/plotting_examples/1d_with_legend.py | 12 | 1235 |
from __future__ import (absolute_import, division, print_function)
from six.moves import (filter, input, map, range, zip) # noqa
import matplotlib.pyplot as plt
import iris
import iris.plot as iplt
fname = iris.sample_data_path('air_temp.pp')
# Load exactly one cube from the given file
temperature = iris.load_cu... | lgpl-3.0 |
danstowell/markovrenewal | experiments/chiffchaff.py | 1 | 35302 | #!/bin/env python
# script to analyse mixtures of chiffchaff audios
# by Dan Stowell, summer 2012
from glob import glob
from subprocess import call
import os.path
import csv
from math import log, exp, pi, sqrt, ceil, floor
from numpy import array, mean, cov, linalg, dot, median, std
import numpy as np
import tempfile... | gpl-2.0 |
acaciawater/spaarwater | spaarwater/management/commands/dump_resprobes.py | 1 | 1958 | '''
Created on Mar 15, 2018
@author: theo
'''
'''
Created on Feb 13, 2014
@author: theo
'''
from django.core.management.base import BaseCommand
from acacia.data.models import Series
import os,logging
import pandas as pd
logger = logging.getLogger('acacia.data')
resprobes = (502,687)
class Command(BaseCommand):
... | apache-2.0 |
gamahead/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_gtkcairo.py | 69 | 2207 | """
GTK+ Matplotlib interface using cairo (not GDK) drawing operations.
Author: Steve Chaplin
"""
import gtk
if gtk.pygtk_version < (2,7,0):
import cairo.gtk
from matplotlib.backends import backend_cairo
from matplotlib.backends.backend_gtk import *
backend_version = 'PyGTK(%d.%d.%d) ' % gtk.pygtk_version + \
... | gpl-3.0 |
jreback/pandas | pandas/tests/frame/methods/test_compare.py | 8 | 6158 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize("align_axis", [0, 1, "index", "columns"])
def test_compare_axis(align_axis):
# GH#30429
df = pd.DataFrame(
{"col1": ["a", "b", "c"], "col2": [1.0, 2.0, np.nan], "col3": [1.0, 2.0, 3.0]},
... | bsd-3-clause |
hhbyyh/spark | python/pyspark/sql/tests/test_pandas_udf_grouped_map.py | 4 | 20450 | #
# 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 |
geoscixyz/em_examples | em_examples/InductionSphereTEM.py | 1 | 19333 | from __future__ import print_function
from __future__ import absolute_import
from __future__ import unicode_literals
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter, FormatStrFormatter
from matplotlib.path import Path
import matplotlib.patches as patc... | mit |
lenovor/scikit-learn | sklearn/svm/tests/test_svm.py | 116 | 31653 | """
Testing for Support Vector Machine module (sklearn.svm)
TODO: remove hard coded numerical results when possible
"""
import numpy as np
import itertools
from numpy.testing import assert_array_equal, assert_array_almost_equal
from numpy.testing import assert_almost_equal
from scipy import sparse
from nose.tools im... | bsd-3-clause |
sanketloke/scikit-learn | examples/covariance/plot_robust_vs_empirical_covariance.py | 73 | 6451 | r"""
=======================================
Robust vs Empirical covariance estimate
=======================================
The usual covariance maximum likelihood estimate is very sensitive to the
presence of outliers in the data set. In such a case, it would be better to
use a robust estimator of covariance to guar... | bsd-3-clause |
berkeley-stat159/project-epsilon | code/utils/scripts/eda.py | 3 | 3524 | """
This script plots some exploratory analysis plots for the raw and filtered data:
- Moisaic of the mean voxels values for each brain slices
Run with:
python eda.py
from this directory
"""
from __future__ import print_function, division
import sys, os, pdb
import numpy as np
import matplotlib.pyplot as ... | bsd-3-clause |
elijah513/scikit-learn | examples/classification/plot_lda_qda.py | 164 | 4806 | """
====================================================================
Linear and Quadratic Discriminant Analysis with confidence ellipsoid
====================================================================
Plot the confidence ellipsoids of each class and decision boundary
"""
print(__doc__)
from scipy import lin... | bsd-3-clause |
wavelets/pandashells | pandashells/test/p_df_test.py | 7 | 5636 | #! /usr/bin/env python
import os
import subprocess
import tempfile
from mock import patch, MagicMock
from unittest import TestCase
import pandas as pd
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
from pandashells.bin.p_df import (
needs_plots,
get_modules_and_shortcu... | bsd-2-clause |
quheng/scikit-learn | examples/svm/plot_svm_nonlinear.py | 268 | 1091 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learned by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn imp... | bsd-3-clause |
jason-neal/equanimous-octo-tribble | octotribble/SpectralTools.py | 1 | 8065 | # SpectralTools.py
# Collection of useful tools for dealing with spectra:
from __future__ import division
import time
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d
def BERVcorr(wl, Berv):
"""Barycentric Earth Radial Velocity correction from tapas.
A wavelength W... | mit |
ahoyosid/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 3 | 10258 | 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 |
LEX2016WoKaGru/pyClamster | pyclamster/coordinates.py | 1 | 38336 | # -*- coding: utf-8 -*-
"""
Created on 25.06.2016
Created for pyclamster
Copyright (C) {2016}
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
the Free Software Foundation, either version 3 of the License, or
... | gpl-3.0 |
akrherz/iem | htdocs/plotting/auto/scripts/p94.py | 1 | 3424 | """Bias computing hi/lo"""
import datetime
import numpy as np
import pandas as pd
import psycopg2.extras
from pyiem.plot import figure_axes
from pyiem.util import get_autoplot_context, get_dbconn
from pyiem.exceptions import NoDataFound
def get_description():
""" Return a dict describing how to call this plotter... | mit |
shusenl/scikit-learn | sklearn/ensemble/tests/test_bagging.py | 72 | 25573 | """
Testing for the bagging ensemble module (sklearn.ensemble.bagging).
"""
# Author: Gilles Louppe
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.te... | bsd-3-clause |
anntzer/scikit-learn | sklearn/linear_model/_ridge.py | 5 | 77086 | """
Ridge regression
"""
# Author: Mathieu Blondel <mathieu@mblondel.org>
# Reuben Fletcher-Costin <reuben.fletchercostin@gmail.com>
# Fabian Pedregosa <fabian@fseoane.net>
# Michael Eickenberg <michael.eickenberg@nsup.org>
# License: BSD 3 clause
from abc import ABCMeta, abstractmethod
impor... | bsd-3-clause |
mcdeaton13/dynamic | Data/Calibration/Firm_Calibration_Python/parameters/employment/script_wages.py | 6 | 1821 | '''
-------------------------------------------------------------------------------
Date created: 5/22/2015
Last updated 5/22/2015
-------------------------------------------------------------------------------
-------------------------------------------------------------------------------
Packages:
--------------... | mit |
r-mart/scikit-learn | sklearn/decomposition/nmf.py | 100 | 19059 | """ Non-negative matrix factorization
"""
# Author: Vlad Niculae
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Author: Chih-Jen Lin, National Taiwan University (original projected gradient
# NMF implementation)
# Author: Anthony Di Franco (original Python and NumPy port)
# License: BSD 3 clause
from __future__ ... | bsd-3-clause |
pianomania/scikit-learn | sklearn/mixture/gmm.py | 19 | 32365 | """
Gaussian Mixture Models.
This implementation corresponds to frequentist (non-Bayesian) formulation
of Gaussian Mixture Models.
"""
# Author: Ron Weiss <ronweiss@gmail.com>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Bertrand Thirion <bertrand.thirion@inria.fr>
# Important note for the deprec... | bsd-3-clause |
fabianp/scikit-learn | examples/linear_model/plot_lasso_model_selection.py | 311 | 5431 | """
===================================================
Lasso model selection: Cross-Validation / AIC / BIC
===================================================
Use the Akaike information criterion (AIC), the Bayes Information
criterion (BIC) and cross-validation to select an optimal value
of the regularization paramet... | bsd-3-clause |
IndraVikas/scikit-learn | sklearn/manifold/locally_linear.py | 206 | 25061 | """Locally Linear Embedding"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) INRIA 2011
import numpy as np
from scipy.linalg import eigh, svd, qr, solve
from scipy.sparse import eye, csr_matrix
from ..base import B... | bsd-3-clause |
Manolo94/manolo94.github.io | MLpython/HW5.py | 1 | 7050 | import pandas as pd
import numpy as np
import sys
import random
import copy
# Task 1
task1_data = {'Wins_2016': [3, 3, 2, 2, 6, 6, 7, 7, 8, 7], 'Wins_2017': [5, 4, 8, 3, 2, 4, 3, 4, 5, 6]}
task1_pd = pd.DataFrame(data=task1_data)
iris_df = pd.read_csv('./iris_input/iris.data', names=['sepal_length', 'sepal_width', 'p... | apache-2.0 |
datapythonista/pandas | pandas/tests/plotting/common.py | 3 | 21514 | """
Module consolidating common testing functions for checking plotting.
Currently all plotting tests are marked as slow via
``pytestmark = pytest.mark.slow`` at the module level.
"""
from __future__ import annotations
import os
from typing import (
TYPE_CHECKING,
Sequence,
)
import warnings
import numpy as... | bsd-3-clause |
bradmontgomery/ml | book/ch01/analyze_webstats.py | 23 | 5113 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
import os
from utils import DATA_DIR, CHART_DIR
import scipy as sp
import matplotlib.pyplot as plt
sp.... | mit |
arabenjamin/scikit-learn | sklearn/metrics/regression.py | 175 | 16953 | """Metrics to assess performance on regression task
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Ma... | bsd-3-clause |
roofit-dev/parallel-roofit-scripts | tensorflow_testing/tensorflow_roofit_demo.py | 1 | 13599 | # -*- coding: utf-8 -*-
# @Author: patrick
# @Date: 2016-09-01 17:04:53
# @Last Modified by: patrick
# @Last Modified time: 2016-10-04 15:44:41
import tensorflow as tf
import numpy as np
# import scipy as sc
import matplotlib.pyplot as plt
from timeit import default_timer as timer
def apply_constraint(var, const... | apache-2.0 |
nmartensen/pandas | pandas/tests/indexes/timedeltas/test_setops.py | 15 | 2556 | import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas import TimedeltaIndex, timedelta_range, Int64Index
class TestTimedeltaIndex(object):
_multiprocess_can_split_ = True
def test_union(self):
i1 = timedelta_range('1day', periods=5)
i2 = timedelta_range('3day',... | bsd-3-clause |
socrata/arcs | setup.py | 1 | 2008 | import os
import sys
from setuptools import setup
from setuptools.command.test import test as TestCommand
def read(fname):
"""Utility function to read the README file into the long_description."""
return open(os.path.join(os.path.dirname(__file__), fname)).read()
install_requires_list = ['pandas>=0.18.1',
... | mit |
ldirer/scikit-learn | sklearn/metrics/cluster/tests/test_bicluster.py | 394 | 1770 | """Testing for bicluster metrics module"""
import numpy as np
from sklearn.utils.testing import assert_equal, assert_almost_equal
from sklearn.metrics.cluster.bicluster import _jaccard
from sklearn.metrics import consensus_score
def test_jaccard():
a1 = np.array([True, True, False, False])
a2 = np.array([T... | bsd-3-clause |
canast02/csci544_fall2016_project | yelp-sentiment/experiments/sentiment_decisiontree.py | 1 | 2591 | import numpy as np
from nltk import TweetTokenizer, accuracy
from nltk.stem.snowball import EnglishStemmer
from sklearn import tree
from sklearn.cross_validation import StratifiedKFold
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics import accuracy_score
from sklearn.metrics import clas... | gpl-3.0 |
GuessWhoSamFoo/pandas | pandas/tests/series/test_repr.py | 1 | 14865 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
from datetime import datetime, timedelta
import numpy as np
import pandas.compat as compat
from pandas.compat import lrange, range, u
import pandas as pd
from pandas import (
Categorical, DataFrame, Index, Series, date_range, option_context,
period_range, tim... | bsd-3-clause |
gnagel/backtrader | backtrader/plot/multicursor.py | 3 | 12203 | # LICENSE AGREEMENT FOR MATPLOTLIB 1.2.0
# --------------------------------------
#
# 1. This LICENSE AGREEMENT is between John D. Hunter ("JDH"), and the
# Individual or Organization ("Licensee") accessing and otherwise using
# matplotlib software in source or binary form and its associated
# documentation.
#
# 2. Sub... | gpl-3.0 |
gbrammer/unicorn | object_examples.py | 2 | 57686 | import os
import pyfits
import numpy as np
import glob
import shutil
import matplotlib.pyplot as plt
USE_PLOT_GUI=False
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg
import threedhst
import threedhst.eazyPy as eazy
import threedhst.catIO as catIO
import unicorn
imp... | mit |
AndreasMadsen/tensorflow | tensorflow/contrib/learn/python/learn/estimators/classifier_test.py | 16 | 5175 | # 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 |
gandalf221553/CodeSection | kivy_matplotlib.py | 1 | 25927 | import kivy
kivy.require('1.9.1') # replace with your current kivy version !
############
#per installare i garden components
#C:\Users\Von Braun\Downloads\WinPython-64bit-3.5.2.3Qt5\python-3.5.2.amd64\Scripts
#https://docs.scipy.org/doc/numpy/f2py/index.html
#!python garden install nomefile
############
from kivy.app... | mit |
xuleiboy1234/autoTitle | tensorflow/tensorflow/contrib/learn/python/learn/estimators/linear_test.py | 58 | 71789 | # 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... | mit |
vybstat/scikit-learn | examples/text/hashing_vs_dict_vectorizer.py | 284 | 3265 | """
===========================================
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 |
eWaterCycle/ewatercycle | ewatercycle/config/_validators.py | 1 | 5383 | """List of config validators."""
import warnings
from collections.abc import Iterable
from functools import lru_cache
from pathlib import Path
class ValidationError(ValueError):
"""Custom validation error."""
# The code for this function was taken from matplotlib (v3.3) and modified
# to fit the needs of eWate... | apache-2.0 |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/subplots_axes_and_figures/fahrenheit_celsius_scales.py | 1 | 1776 | """
=================================
Different scales on the same axes
=================================
Demo of how to display two scales on the left and right y axis.
This example uses the Fahrenheit and Celsius scales.
"""
import matplotlib.pyplot as plt
import numpy as np
# nodebox section
if __name__ == '__bui... | mit |
tmhm/scikit-learn | sklearn/utils/tests/test_multiclass.py | 128 | 12853 |
from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sp... | bsd-3-clause |
sposs/DIRAC | Core/Utilities/Graphs/Legend.py | 11 | 7713 | ########################################################################
# $HeadURL$
########################################################################
""" Legend encapsulates a graphical plot legend drawing tool
The DIRAC Graphs package is derived from the GraphTool plotting package of the
CMS/Phed... | gpl-3.0 |
hrjn/scikit-learn | examples/linear_model/plot_ard.py | 32 | 3912 | """
==================================================
Automatic Relevance Determination Regression (ARD)
==================================================
Fit regression model with Bayesian Ridge Regression.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary l... | bsd-3-clause |
ammarkhann/FinalSeniorCode | lib/python2.7/site-packages/IPython/lib/tests/test_latextools.py | 8 | 3869 | # encoding: utf-8
"""Tests for IPython.utils.path.py"""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
try:
from unittest.mock import patch
except ImportError:
from mock import patch
import nose.tools as nt
from IPython.lib import latextools
from IPython... | mit |
pratapvardhan/scikit-learn | sklearn/datasets/svmlight_format.py | 19 | 16759 | """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 |
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