repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
passiweinberger/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/projections/polar.py | 69 | 20981 | import math
import numpy as npy
import matplotlib
rcParams = matplotlib.rcParams
from matplotlib.artist import kwdocd
from matplotlib.axes import Axes
from matplotlib import cbook
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import Formatter, Locator
from matplotlib.tr... | agpl-3.0 |
ElDeveloper/scikit-learn | sklearn/ensemble/partial_dependence.py | 251 | 15097 | """Partial dependence plots for tree ensembles. """
# Authors: Peter Prettenhofer
# License: BSD 3 clause
from itertools import count
import numbers
import numpy as np
from scipy.stats.mstats import mquantiles
from ..utils.extmath import cartesian
from ..externals.joblib import Parallel, delayed
from ..externals im... | bsd-3-clause |
alshedivat/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 |
RobertABT/heightmap | build/matplotlib/examples/pylab_examples/fancyarrow_demo.py | 12 | 1386 | import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
styles = mpatches.ArrowStyle.get_styles()
ncol=2
nrow = (len(styles)+1) // ncol
figheight = (nrow+0.5)
fig1 = plt.figure(1, (4.*ncol/1.5, figheight/1.5))
fontsize = 0.2 * 70
ax = fig1.add_axes([0, 0, 1, 1], frameon=False, aspect=1.)
ax.set_xlim(... | mit |
bgris/ODL_bgris | lib/python3.5/site-packages/scipy/signal/waveforms.py | 64 | 14818 | # Author: Travis Oliphant
# 2003
#
# Feb. 2010: Updated by Warren Weckesser:
# Rewrote much of chirp()
# Added sweep_poly()
from __future__ import division, print_function, absolute_import
import numpy as np
from numpy import asarray, zeros, place, nan, mod, pi, extract, log, sqrt, \
exp, cos, sin, polyval, po... | gpl-3.0 |
AndreLamurias/IBRel | src/classification/rext/kernelmodels.py | 2 | 8968 | #!/usr/bin/env python
#shallow linguistic kernel
import sys, os
import os.path
import xml.etree.ElementTree as ET
import logging
from optparse import OptionParser
import pickle
import operator
from time import time
#from pandas import DataFrame
import platform
import re
import nltk
import nltk.data
from nltk.tree impo... | mit |
rahuldhote/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 |
leejz/misc-scripts | make_alignment_mapper.py | 1 | 2562 | #!/usr/bin/env python
"""
--------------------------------------------------------------------------------
Created: Jackson Lee 2012
This script reads in the ecoli reference alignment in a particular format and
generates a mapping file which assigns a sequential count of each base pair to
the current alignment posi... | mit |
cogeorg/BlackRhino | examples/degroot/networkx/drawing/nx_pylab.py | 22 | 27761 | """
**********
Matplotlib
**********
Draw networks with matplotlib.
See Also
--------
matplotlib: http://matplotlib.sourceforge.net/
pygraphviz: http://networkx.lanl.gov/pygraphviz/
"""
# Copyright (C) 2004-2012 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Sw... | gpl-3.0 |
dsullivan7/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 |
johannah/iceview | setup.py | 1 | 1059 | import os
import setuptools
setuptools.setup(
name='iceview',
version='0.0.1',
package_data={"": ['*.jpg', '*.png', '*.json', '*.txt']},
author='Johanna Hansen',
author_email='jh1736@gmail.com',
description='Tools for creating mosaics for ice imagery collected by UAVs',
long_description=ope... | bsd-3-clause |
kaichogami/scikit-learn | sklearn/tests/test_dummy.py | 186 | 17778 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from sklearn.base import clone
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_eq... | bsd-3-clause |
agogear/corpkit | setup.py | 1 | 1451 | from setuptools import setup, find_packages
setup(name='corpkit',
version='1.5',
description='A toolkit for working with linguistic corpora',
url='http://github.com/interrogator/corpkit',
author='Daniel McDonald',
package_data={'corpkit': ['*.jar', 'corpkit/*.jar'],
'c... | mit |
Delosari/dazer | bin/lib/cloudy_library/Cloudy_plotter2.py | 1 | 5591 | from collections import OrderedDict
from lmfit import Parameters, minimize, report_fit
from lmfit.models import LinearModel
from numpy import log10 as nplog10, zeros, min, max, linspace, array, concatenate, isfinite, ... | mit |
zhenv5/scikit-learn | sklearn/linear_model/tests/test_theil_sen.py | 234 | 9928 | """
Testing for Theil-Sen module (sklearn.linear_model.theil_sen)
"""
# Author: Florian Wilhelm <florian.wilhelm@gmail.com>
# License: BSD 3 clause
from __future__ import division, print_function, absolute_import
import os
import sys
from contextlib import contextmanager
import numpy as np
from numpy.testing import ... | bsd-3-clause |
FluidityProject/multifluids | tests/gls-Kato_Phillips-mixed_layer_depth/mixed_layer_depth_all.py | 1 | 4603 | #!/usr/bin/env python
from numpy import arange,concatenate,array,argsort
import os
import sys
import vtktools
import math
from pylab import *
from matplotlib.ticker import MaxNLocator
import re
from scipy.interpolate import UnivariateSpline
import glob
#### taken from http://www.codinghorror.com/blog/archives/001018... | lgpl-2.1 |
jjx02230808/project0223 | 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 |
imaculate/scikit-learn | examples/applications/plot_out_of_core_classification.py | 32 | 13829 | """
======================================================
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. ... | bsd-3-clause |
Caoimhinmg/PmagPy | setup_scripts/win_pmag_gui_setup.py | 3 | 2161 | import distutils.core
from distutils.core import setup
import py2exe
import matplotlib
import os
import glob
import sys
sys.setrecursionlimit(3000)
directory = os.getcwd()
help_data = glob.glob(os.path.join(directory, 'dialogs', 'help_files') + os.path.sep + '*')
data_model = glob.glob(os.path.join(directory, 'pmagpy... | bsd-3-clause |
JQIamo/artiq | doc/manual/conf.py | 1 | 9407 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# ARTIQ documentation build configuration file, created by
# sphinx-quickstart on Thu Sep 18 16:51:53 2014.
#
# 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
# auto... | lgpl-3.0 |
PascalSteger/gravimage | programs/gi_mc_errors.py | 1 | 2025 | #!/usr/bin/env python3
## Estimates errors using Monte Carlo sampling
# Hamish Silverwood, GRAPPA, UvA, 23 February 2015
import numpy as np
import gl_helper as gh
import pdb
import pickle
import sys
import numpy.random as rand
import matplotlib.pyplot as plt
#TEST this will eventually go outside
def ErSamp_gauss_l... | gpl-2.0 |
tsherwen/AC_tools | Scripts/Basic_GEOSChem_bpch_plotter.py | 1 | 2474 | #!/usr/bin/python
# modules
import AC_tools as AC
import numpy as np
import sys
import matplotlib.pyplot as plt
# Setup, choose species
species = 'O3' # 'CO2'
RMM_species = 16.*3.
res = '4x5' # ( e.g. '4x5', '2x2.5', '0.5x0.666', '0.25x0.3125' )
unit, scale = AC.tra_unit(species, scale=True)
# debug/print verbose ... | mit |
trankmichael/scipy | doc/source/tutorial/examples/normdiscr_plot2.py | 84 | 1642 | import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
npoints = 20 # number of integer support points of the distribution minus 1
npointsh = npoints / 2
npointsf = float(npoints)
nbound = 4 #bounds for the truncated normal
normbound = (1 + 1 / npointsf) * nbound #actual bounds of truncated normal
... | bsd-3-clause |
DPRL/MathSymbolRecognizer | src/svm_lin_classifier.py | 1 | 5412 | """
DPRL Math Symbol Recognizers
Copyright (c) 2012-2014 Kenny Davila, Richard Zanibbi
This file is part of DPRL Math Symbol Recognizers.
DPRL Math Symbol Recognizers is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
t... | gpl-3.0 |
imaculate/scikit-learn | examples/linear_model/plot_logistic_multinomial.py | 50 | 2480 | """
====================================================
Plot multinomial and One-vs-Rest Logistic Regression
====================================================
Plot decision surface of multinomial and One-vs-Rest Logistic Regression.
The hyperplanes corresponding to the three One-vs-Rest (OVR) classifiers
are repre... | bsd-3-clause |
perimosocordiae/scipy | doc/source/tutorial/stats/plots/qmc_plot_conv_mc_sobol.py | 12 | 2386 | """Integration convergence comparison: MC vs Sobol'.
The function is a synthetic example specifically designed
to verify the correctness of the implementation [2]_.
References
----------
.. [1] I. M. Sobol. The distribution of points in a cube and the accurate
evaluation of integrals. Zh. Vychisl. Mat. i Mat. Phy... | bsd-3-clause |
gnieboer/tensorflow | tensorflow/contrib/learn/python/learn/estimators/kmeans.py | 34 | 10130 | # 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 |
ah-anssi/SecuML | SecuML/core/Clustering/Cluster.py | 1 | 5432 | # SecuML
# Copyright (C) 2016-2017 ANSSI
#
# SecuML is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# SecuML is distributed in the h... | gpl-2.0 |
jdmcbr/geopandas | geopandas/tests/test_crs.py | 1 | 21680 | from distutils.version import LooseVersion
import os
import random
import numpy as np
import pandas as pd
from shapely.geometry import Point, Polygon, LineString
import pyproj
from geopandas import GeoSeries, GeoDataFrame, points_from_xy, datasets, read_file
from geopandas.array import from_shapely, from_wkb, from_... | bsd-3-clause |
alshedivat/tensorflow | tensorflow/examples/get_started/regression/imports85.py | 41 | 6589 | # 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 |
RobertABT/heightmap | build/matplotlib/lib/matplotlib/hatch.py | 6 | 6997 | """
Contains a classes for generating hatch patterns.
"""
from __future__ import print_function
import numpy as np
from matplotlib.path import Path
class HatchPatternBase:
"""
The base class for a hatch pattern.
"""
pass
class HorizontalHatch(HatchPatternBase):
def __init__(self, hatch, density... | mit |
samgoodgame/sf_crime | iterations/KK_scripts/KK_development_work/make_kaggle_format_08_20_2045.py | 2 | 1393 | # -*- coding: utf-8 -*-
"""
Created on Sat Aug 19 19:49:47 2017
@author: kalvi
"""
#required imports
import pandas as pd
import numpy as np
def make_kaggle_format(sample_submission_path, test_transformed_path, prediction_probabilities):
"""this function requires:
sample_submission_path=(filepath for 'sam... | mit |
466152112/scikit-learn | examples/manifold/plot_manifold_sphere.py | 258 | 5101 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=============================================
Manifold Learning methods on a severed sphere
=============================================
An application of the different :ref:`manifold` techniques
on a spherical data-set. Here one can see the use of
dimensionality reducti... | bsd-3-clause |
pradyu1993/scikit-learn | examples/linear_model/plot_lasso_coordinate_descent_path.py | 3 | 2804 | """
=====================
Lasso and Elastic Net
=====================
Lasso and elastic net (L1 and L2 penalisation) implemented using a
coordinate descent.
The coefficients can be forced to be positive.
"""
print __doc__
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD Style.
import numpy ... | bsd-3-clause |
martynvandijke/Stargazer | docs/source/test.py | 1 | 2173 | '''
Title: Simple Economic Dispatch
Author: Dr. Nikolaos G. Paterakis, TUE
Date: 10/1/2017
Purpose:
- Import data from excel spreadsheets using pandas
- Formulate a problem
- Perform sensitivity analysis
- Print and plot results using matplotlib
'''
#Define dependencies
import pandas
from pyomo.environ import *
def M... | mit |
benhamner/Stack-Overflow-Competition | competition_utilities.py | 2 | 3323 | from __future__ import division
from collections import Counter
import csv
import dateutil
import numpy as np
import os
import pandas as pd
data_path = None
submissions_path = None
if not data_path or not submissions_path:
raise Exception("Set the data and submission paths in competition_utilities.py!")
def parse... | bsd-2-clause |
Kirubaharan/hydrology | Lake_bathymetry/smg_bathymetry/smg_lake_bathymetry.py | 1 | 1238 | __author__ = 'kiruba'
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import itertools
import checkdam.checkdam as cd
# calibration
y_cal = np.array([100, 1000, 2000, 3000, 4000, 5000])
x_cal = np.array([1875, 2516, 3212, 3901, 4605, 5280])
a_stage = cd.polyfit(x_cal, y_cal, 1)
coeff_cal = a_st... | gpl-3.0 |
nehudesi/MSim | module/tsutil.py | 1 | 32434 | '''
Version: MRT v3.0
Type: Library
Location: C:\MRT3.0\module
Author: Chintan Patel
Email: chintanlike@gmail.com
'''
import math
import datetime as dt
#import numpy as np
import module.qsdateutil as qsdateutil
from math import sqrt
import pandas as pd
from copy import deepcopy
import matplotlib.pyp... | agpl-3.0 |
quheng/scikit-learn | sklearn/datasets/tests/test_mldata.py | 384 | 5221 | """Test functionality of mldata fetching utilities."""
import os
import shutil
import tempfile
import scipy as sp
from sklearn import datasets
from sklearn.datasets import mldata_filename, fetch_mldata
from sklearn.utils.testing import assert_in
from sklearn.utils.testing import assert_not_in
from sklearn.utils.test... | bsd-3-clause |
daeilkim/refinery | refinery/bnpy/bnpy-dev/bnpy/viz/PlotELBO.py | 1 | 4539 | '''
PlotELBO.py
Executable for plotting the learning objective function (log evidence)
vs. time/number of passes thru data (laps)
Usage (command-line)
-------
python -m bnpy.viz.PlotELBO dataName aModelName obsModelName algName [kwargs]
'''
from matplotlib import pylab
import numpy as np
import argparse
import os
i... | mit |
AlirezaShahabi/zipline | zipline/utils/events.py | 20 | 16995 | #
# Copyright 2014 Quantopian, 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... | apache-2.0 |
imaculate/scikit-learn | examples/gaussian_process/plot_gpr_noisy_targets.py | 64 | 3706 | """
=========================================================
Gaussian Processes regression: basic introductory example
=========================================================
A simple one-dimensional regression example computed in two different ways:
1. A noise-free case
2. A noisy case with known noise-level per ... | bsd-3-clause |
GiulioGx/RNNs | sources/feat_sel_lupus.py | 1 | 10286 | import logging
import os
import pickle
from threading import Thread
import numpy
import shutil
import theano
from sklearn import metrics
from sklearn.metrics import roc_auc_score
from ActivationFunction import Tanh
from Configs import Configs
from Paths import Paths
from datasets.LupusFilter import TemporalSpanFilter... | lgpl-3.0 |
Eric89GXL/mne-python | examples/stats/plot_fdr_stats_evoked.py | 20 | 2740 | """
=======================================
FDR correction on T-test on sensor data
=======================================
One tests if the evoked response significantly deviates from 0.
Multiple comparison problem is addressed with
False Discovery Rate (FDR) correction.
"""
# Authors: Alexandre Gramfort <alexandre.... | bsd-3-clause |
jmschrei/scikit-learn | sklearn/datasets/tests/test_rcv1.py | 322 | 2414 | """Test the rcv1 loader.
Skipped if rcv1 is not already downloaded to data_home.
"""
import errno
import scipy.sparse as sp
import numpy as np
from sklearn.datasets import fetch_rcv1
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing i... | bsd-3-clause |
larsmans/scikit-learn | sklearn/metrics/cluster/supervised.py | 17 | 26843 | """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 |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/lib/matplotlib/testing/jpl_units/EpochConverter.py | 6 | 5370 | #===========================================================================
#
# EpochConverter
#
#===========================================================================
"""EpochConverter module containing class EpochConverter."""
#===========================================================================
# Pl... | mit |
louispotok/pandas | pandas/tests/dtypes/test_missing.py | 3 | 14294 | # -*- coding: utf-8 -*-
import pytest
from warnings import catch_warnings
import numpy as np
from datetime import datetime
from pandas.util import testing as tm
import pandas as pd
from pandas.core import config as cf
from pandas.compat import u
from pandas._libs import missing as libmissing
from pandas._libs.tslib ... | bsd-3-clause |
Unidata/MetPy | v0.10/_downloads/8de42c0f44fb2568ca140f44d6554022/Four_Panel_Map.py | 6 | 4683 | # Copyright (c) 2017 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Four Panel Map
===============
By reading model output data from a netCDF file, we can create a four panel plot showing:
* 300 hPa heights and winds
* 500 hPa heights and absol... | bsd-3-clause |
wlamond/scikit-learn | sklearn/cluster/k_means_.py | 9 | 60297 | """K-means clustering"""
# Authors: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Thomas Rueckstiess <ruecksti@in.tum.de>
# James Bergstra <james.bergstra@umontreal.ca>
# Jan Schlueter <scikit-learn@jan-schlueter.de>
# Nelle Varoquaux
# Peter Prettenhofer <peter.prettenh... | bsd-3-clause |
ushiro/persistlab | PersistLabPlugins/persistlabplugins/techniques.py | 1 | 1824 | #!/usr/bin/env python
import time
import re
import math
from collections import OrderedDict as OD
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from persistlab import measfile
##from persistlab import figitem
from persistlab import batlab
__version__ = '0.0'
class FigTransient(batlab.Defau... | bsd-3-clause |
dsm054/pandas | pandas/tests/frame/test_dtypes.py | 1 | 41160 | # -*- coding: utf-8 -*-
from __future__ import print_function
import pytest
from datetime import timedelta
import numpy as np
from pandas import (DataFrame, Series, date_range, Timedelta, Timestamp,
Categorical, compat, concat, option_context)
from pandas.compat import u
from pandas import _np_v... | bsd-3-clause |
karllessard/tensorflow | tensorflow/lite/micro/examples/micro_speech/apollo3/captured_data_to_wav.py | 19 | 1443 | # Copyright 2018 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 |
MikeDacre/slurmy | tests/test_pandas.py | 2 | 7325 | """
Tests submitting pandas functions.
Pandas is hard to install, so this isn't part of the travis py.test.
"""
import sys
import argparse
from uuid import uuid4
import fyrd
import pytest
try:
import numpy as np
import pandas as pd
canrun = True
except ImportError:
canrun = False
env = fyrd.get_cluster... | mit |
ljchang/nltools | examples/02_Analysis/plot_similarity_example.py | 1 | 1669 | """
Similarity and Distance
=======================
This tutorial illustrates how to calculate similarity and distance between images.
"""
#########################################################################
# Load Data
# ---------
#
# First, let's load the pain data for this example.
from nltools.datasets i... | mit |
adrienpacifico/openfisca-france-data | openfisca_france_data/input_data_builders/build_openfisca_survey_data/step_03_fip.py | 2 | 13040 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
# OpenFisca -- A versatile microsimulation software
# By: OpenFisca Team <contact@openfisca.fr>
#
# Copyright (C) 2011, 2012, 2013, 2014, 2015 OpenFisca Team
# https://github.com/openfisca
#
# This file is part of OpenFisca.
#
# OpenFisca is free software; you can redist... | agpl-3.0 |
alexjc/pylearn2 | pylearn2/sandbox/cuda_convnet/specialized_bench.py | 44 | 3906 | __authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"
from pylearn2.testing.skip import skip_if_no_gpu
skip_if_no_gpu()
import numpy as np
from theano.... | bsd-3-clause |
Odingod/mne-python | mne/time_frequency/tests/test_psd.py | 12 | 5211 | import numpy as np
import os.path as op
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_true
from mne import io, pick_types, Epochs, read_events
from mne.utils import requires_scipy_version, slow_test
from mne.time_frequency import compute_raw_psd, compute_epochs_psd
base_dir = op.jo... | bsd-3-clause |
rseubert/scikit-learn | examples/covariance/plot_mahalanobis_distances.py | 348 | 6232 | r"""
================================================================
Robust covariance estimation and Mahalanobis distances relevance
================================================================
An example to show covariance estimation with the Mahalanobis
distances on Gaussian distributed data.
For Gaussian dis... | bsd-3-clause |
ephes/scikit-learn | sklearn/metrics/tests/test_pairwise.py | 105 | 22788 | import numpy as np
from numpy import linalg
from scipy.sparse import dok_matrix, csr_matrix, issparse
from scipy.spatial.distance import cosine, cityblock, minkowski, wminkowski
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing impo... | bsd-3-clause |
ApachePointObservatory/InstrumentBlockGUI | instcalc.py | 1 | 6088 | #!/usr/bin/python
from scipy import optimize
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from operator import itemgetter
class GridData(object):
def __init__(self, data=None, bin = None):
if data is None:
raise Exception("Data must be specified to create a GridData obj... | mit |
gerbaudo/fbu | fbu/monitoring.py | 1 | 1915 | import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
from numpy import mean,std,arange,array
def plothistandtrace(name,xx,lower,upper):
ax = plt.subplot(211)
mu = mean(xx) if 'truth' in name else 0.
sigma = std(xx) if 'truth' in name else 1.
n, bins, patches = plt.hist(xx, bins=50, normed=1, ... | gpl-2.0 |
zuku1985/scikit-learn | sklearn/cross_decomposition/cca_.py | 151 | 3192 | from .pls_ import _PLS
__all__ = ['CCA']
class CCA(_PLS):
"""CCA Canonical Correlation Analysis.
CCA inherits from PLS with mode="B" and deflation_mode="canonical".
Read more in the :ref:`User Guide <cross_decomposition>`.
Parameters
----------
n_components : int, (default 2).
numb... | bsd-3-clause |
zorojean/scikit-learn | sklearn/linear_model/tests/test_perceptron.py | 378 | 1815 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_raises
from sklearn.utils import check_random_state
from sklearn.datasets import load_iris
from sklearn.linear_model import Pe... | bsd-3-clause |
santosjorge/cufflinks | cufflinks/ta.py | 1 | 16745 | ## TECHNICHAL ANALYSIS
import pandas as pd
import numpy as np
# import talib
from plotly.graph_objs import Figure
from .utils import make_list
class StudyError(Exception):
pass
def _ohlc_dict(df_or_figure,open='',high='',low='',close='',volume='',
validate='',**kwargs):
"""
Returns a dictionary with the act... | mit |
JT5D/scikit-learn | sklearn/linear_model/tests/test_base.py | 8 | 3587 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.linear_model.... | bsd-3-clause |
britram/qof | pytools/ipfix2hdf5.py | 1 | 1861 | import ipfix
import qof
import pandas as pd
import argparse
import bz2
from sys import stdin, stdout, stderr
args = None
def parse_args():
global args
parser = argparse.ArgumentParser(description="Convert an IPFIX file or stream to HDF5")
parser.add_argument('ienames', metavar="ie", nargs="+",
... | gpl-2.0 |
strets123/cbh_chembl_ws_extension | cbh_chembl_ws_extension/compounds.py | 1 | 79983 | from tastypie.resources import ALL
from tastypie.resources import ALL_WITH_RELATIONS
from tastypie.resources import ModelResource
from django.conf import settings
from django.conf.urls import *
from django.core.exceptions import ObjectDoesNotExist
from tastypie.authorization import Authorization
from tastypie import ht... | mit |
IshankGulati/scikit-learn | sklearn/cluster/tests/test_bicluster.py | 143 | 9461 | """Testing for Spectral Biclustering methods"""
import numpy as np
from scipy.sparse import csr_matrix, issparse
from sklearn.model_selection import ParameterGrid
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
... | bsd-3-clause |
rhattersley/iris | docs/iris/example_code/General/projections_and_annotations.py | 6 | 5396 | """
Plotting in different projections
=================================
This example shows how to overlay data and graphics in different projections,
demonstrating various features of Iris, Cartopy and matplotlib.
We wish to overlay two datasets, defined on different rotated-pole grids.
To display both together, we m... | lgpl-3.0 |
thushear/MLInAction | nlp/bayes.py | 1 | 3077 | from sklearn import datasets
iris = datasets.load_iris()
print(iris.data[:5])
print(iris.target[:5])
from sklearn.naive_bayes import GaussianNB
gnb = GaussianNB()
y_pred = gnb.fit(iris.data, iris.target).predict(iris.data)
print('='*40)
print(iris.target)
print('='*40)
print(y_pred)
right_num = (iris.target == y_pred)... | apache-2.0 |
draperjames/qtpandas | qtpandas/models/SupportedDtypes.py | 1 | 5907 | from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from builtins import super
from future import standard_library
standard_library.install_aliases()
import numpy as np
from qtpandas.compat import QtCore
class SupportedDty... | mit |
OpenSeizureDetector/OpenSeizureDetector | kinect_version/benFinder/timeSeries.py | 2 | 9965 | #!/usr/bin/python
#
#############################################################################
#
# Copyright Graham Jones, December 2013
#
# Original version by Joseph Howse in his book, "OpenCV Computer Vision with
# Python" (Packt Publishing, 2013).
# http://nummist.com/opencv/
# http://www.packt... | gpl-3.0 |
nilbody/h2o-3 | h2o-py/tests/testdir_algos/kmeans/pyunit_DEPRECATED_get_modelKmeans.py | 1 | 1238 | from __future__ import print_function
from builtins import range
import sys
sys.path.insert(1,"../../../")
import h2o
from tests import pyunit_utils
import numpy as np
from sklearn.cluster import KMeans
from sklearn.preprocessing import Imputer
def get_modelKmeans():
# Connect to a pre-existing cluster
#... | apache-2.0 |
TomAugspurger/pandas | pandas/core/arrays/_arrow_utils.py | 1 | 4430 | from distutils.version import LooseVersion
import json
import numpy as np
import pyarrow
from pandas.core.arrays.interval import _VALID_CLOSED
_pyarrow_version_ge_015 = LooseVersion(pyarrow.__version__) >= LooseVersion("0.15")
def pyarrow_array_to_numpy_and_mask(arr, dtype):
"""
Convert a primitive pyarrow... | bsd-3-clause |
LeeKamentsky/CellProfiler | cellprofiler/utilities/matplotlib_axes_monkey_patch.py | 3 | 7571 | # Patches to prior versions of matplotlib
#
# Code below is adapted from matplotlib:
#
# 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.
#
# Subject ... | gpl-2.0 |
aetilley/scikit-learn | examples/cluster/plot_lena_compress.py | 271 | 2229 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Vector Quantization Example
=========================================================
The classic image processing example, Lena, an 8-bit grayscale
bit-depth, 512 x 512 sized image, is used here to illustrate
how ... | bsd-3-clause |
jimhw/trading-with-python | lib/qtpandas.py | 77 | 7937 | '''
Easy integration of DataFrame into pyqt framework
Copyright: Jev Kuznetsov
Licence: BSD
'''
from PyQt4.QtCore import (QAbstractTableModel,Qt,QVariant,QModelIndex,SIGNAL)
from PyQt4.QtGui import (QApplication,QDialog,QVBoxLayout, QHBoxLayout, QTableView, QPushButton,
QWidget,QTabl... | bsd-3-clause |
ChristianKniep/QNIB | serverfiles/usr/local/lib/networkx-1.6/build/lib/networkx/readwrite/gml.py | 3 | 11740 | """
Read graphs in GML format.
"GML, the G>raph Modelling Language, is our proposal for a portable
file format for graphs. GML's key features are portability, simple
syntax, extensibility and flexibility. A GML file consists of a
hierarchical key-value lists. Graphs can be annotated with arbitrary
data structures. The... | gpl-2.0 |
JelteF/statistics | 5/descent.py | 1 | 1092 | import numpy as np
import numpy.random as rd
import matplotlib.pyplot as plt
from pylatex import Plt
from scipy.optimize import minimize
th1 = 2
th2 = .5
x = np.linspace(0, 10, 101)
y = th1 * np.sin(th2 * x) + 0.3 * rd.randn(*x.shape)
def J(th):
return np.sum((y - th[0] * np.sin(th[1] * x))**2)
def derivative1... | mit |
TheChymera/LabbookDB | labbookdb/report/utilities.py | 1 | 6075 | import pandas as pd
def concurrent_cagetreatment(df, cagestays,
protect_duplicates=[
'Animal_id',
'Cage_id',
'Cage_Treatment_start_date',
'Cage_Treatment_end_date',
'Cage_TreatmentProtocol_code',
'Treatment_end_date',
'Treatment_end_date',
'TreatmentProtocol_code',
],
):
"""
Return a `pandas.Data... | bsd-3-clause |
xho95/BuildingMachineLearningSystemsWithPython | ch03/noise_analysis.py | 24 | 2412 | # 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 sklearn.datasets
groups = [
'comp.graphics', 'comp.os.ms-windows.misc', 'comp.sys.ibm.pc.ha... | mit |
neilvallon/pyMap | app.py | 1 | 2337 | from bottle import *
import random, math
from datetime import datetime
from MapGenerator import *
from Tessellation import *
def buildHTMLMap(seed, width, height):
tstart = datetime.now()
m = MapGenerator(int(width), int(height), str(seed))
#m.makeRandom().smooth().smooth().smooth().removeIslands().findSpawns()
... | mit |
codrut3/tensorflow | tensorflow/contrib/labeled_tensor/python/ops/ops.py | 77 | 46403 | # 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 |
PatrickOReilly/scikit-learn | examples/applications/plot_outlier_detection_housing.py | 110 | 5681 | """
====================================
Outlier detection on a real data set
====================================
This example illustrates the need for robust covariance estimation
on a real data set. It is useful both for outlier detection and for
a better understanding of the data structure.
We selected two sets o... | bsd-3-clause |
q1ang/scikit-learn | sklearn/tests/test_base.py | 216 | 7045 | # Author: Gael Varoquaux
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing impo... | bsd-3-clause |
ujfjhz/vnpy | docker/dockerTrader/ctaStrategy/tools/multiTimeFrame/ctaStrategyMultiTF.py | 5 | 15034 | # encoding: UTF-8
"""
This file tweaks ctaTemplate Module to suit multi-TimeFrame strategies.
"""
from strategyAtrRsi import *
from ctaBase import *
from ctaTemplate import CtaTemplate
########################################################################
class TC11(CtaTemplate):
# Strategy name and author
... | mit |
mattgiguere/scikit-learn | benchmarks/bench_glm.py | 297 | 1493 | """
A comparison of different methods in GLM
Data comes from a random square matrix.
"""
from datetime import datetime
import numpy as np
from sklearn import linear_model
from sklearn.utils.bench import total_seconds
if __name__ == '__main__':
import pylab as pl
n_iter = 40
time_ridge = np.empty(n_it... | bsd-3-clause |
rahul-c1/scikit-learn | sklearn/feature_extraction/hashing.py | 29 | 5648 | # 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 |
IshankGulati/scikit-learn | examples/neighbors/plot_classification.py | 58 | 1790 | """
================================
Nearest Neighbors Classification
================================
Sample usage of Nearest Neighbors classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColorm... | bsd-3-clause |
clemkoa/scikit-learn | sklearn/externals/joblib/__init__.py | 54 | 5087 | """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** and **r... | bsd-3-clause |
anntzer/scikit-learn | sklearn/setup.py | 11 | 3287 | import sys
import os
from sklearn._build_utils import cythonize_extensions
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
import numpy
libraries = []
if os.name == 'posix':
libraries.append('m')
config = Configuration('sklearn', ... | bsd-3-clause |
ianrenton/geckocam | pi/drawgraphs.py | 1 | 4269 | #! /usr/bin/env python
# Vivarium monitoring sensor script. Run by a cron job. Reads temperature and
# humidity values written to the log file. Outputs charts of the last seven
# days for each sensor with min/max lines. Sends alert emails if either figure
# goes out of bounds.
# Written by Ian Renton (http://ianrento... | bsd-2-clause |
wilsonkichoi/zipline | docs/source/conf.py | 7 | 3115 | import sys
import os
from zipline import __version__ as version
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
sys.path.insert(... | apache-2.0 |
Jimmy-Morzaria/scikit-learn | sklearn/metrics/pairwise.py | 13 | 41710 | # -*- coding: utf-8 -*-
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Robert Layton <robertlayton@gmail.com>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Philippe Gervais <philippe.gervais@inria.fr>
# Lars Buitinck ... | bsd-3-clause |
trungnt13/scikit-learn | sklearn/linear_model/logistic.py | 105 | 56686 | """
Logistic Regression
"""
# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Fabian Pedregosa <f@bianp.net>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Lars Buitinck
# Simon Wu <s8wu@uwaterloo.ca>
imp... | bsd-3-clause |
wzbozon/scikit-learn | examples/applications/topics_extraction_with_nmf_lda.py | 133 | 3517 | """
========================================================================================
Topics extraction with Non-Negative Matrix Factorization And Latent Dirichlet Allocation
========================================================================================
This is an example of applying Non Negative Matr... | bsd-3-clause |
soylentdeen/cuddly-weasel | gfVerification/compareGfs.py | 1 | 3065 | import matplotlib.pyplot as pyplot
import numpy
import scipy
import sys
import MoogTools
import AstroUtils
fig = pyplot.figure(0)
fig.clear()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
baseName = sys.argv[1]
arcturusConfig = AstroUtils.parse_config(baseName+"_Solar.cfg")
solarConfig = AstroUtils.parse_config(baseName+"... | mit |
jniediek/mne-python | mne/viz/utils.py | 1 | 58956 | """Utility functions for plotting M/EEG data
"""
from __future__ import print_function
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
# ... | bsd-3-clause |
fcolamar/AliPhysics | PWGLF/NUCLEX/Nuclei/NucleiPbPb/macros_pp13TeV/CorrelationFraction.py | 19 | 2196 | import uproot
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.cm as cm
shift_list = [[1, -2], [2, -1], [3, 1], [4, 2]]
dcaxy_list = [[0, 1.0], [1, 1.4]]
dcaz_list = [[0, 0.5], [1, 0.75], [2, 1.25], [3, 1.50]]
pid_list = [[0, 3.25], [1, 3.5]]
tpc_list = [[0, 60], [1, 65], [2, 75]... | bsd-3-clause |
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