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 |
|---|---|---|---|---|---|
cbmoore/statsmodels | statsmodels/sandbox/examples/example_gam_0.py | 33 | 4574 | '''first examples for gam and PolynomialSmoother used for debugging
This example was written as a test case.
The data generating process is chosen so the parameters are well identified
and estimated.
Note: uncomment plt.show() to display graphs
'''
example = 2 #3 # 1,2 or 3
import numpy as np
from statsmodels.com... | bsd-3-clause |
AlexRobson/scikit-learn | benchmarks/bench_tree.py | 297 | 3617 | """
To run this, you'll need to have installed.
* scikit-learn
Does two benchmarks
First, we fix a training set, increase the number of
samples to classify and plot number of classified samples as a
function of time.
In the second benchmark, we increase the number of dimensions of the
training set, classify a sam... | bsd-3-clause |
robince/pyentropy | docs/sphinxext/inheritance_diagram.py | 98 | 13648 | """
Defines a docutils directive for inserting inheritance diagrams.
Provide the directive with one or more classes or modules (separated
by whitespace). For modules, all of the classes in that module will
be used.
Example::
Given the following classes:
class A: pass
class B(A): pass
class C(A): pass
... | gpl-2.0 |
wilsonkichoi/zipline | zipline/protocol.py | 3 | 4172 | #
# Copyright 2013 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 |
btabibian/scikit-learn | examples/model_selection/plot_nested_cross_validation_iris.py | 46 | 4415 | """
=========================================
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 |
sandeepkbhat/pylearn2 | pylearn2/expr/tests/test_probabilistic_max_pooling.py | 44 | 24662 | from __future__ import print_function
import numpy as np
import warnings
from theano.compat.six.moves import xrange
from theano import config
from theano import function
import theano.tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams
from pylearn2.expr.probabilistic_max_pooling import max_pool_python
... | bsd-3-clause |
wavemoth/wavemoth | wavemoth/cuda/sht.py | 1 | 5893 | import os
import tempita
import numpy as np
from numpy import int32
from . import flatcuda as cuda
#from .flatcuda import InOut, In, Out,
from .legendre_transform import CudaLegendreKernel
from .. import healpix, compute_normalized_associated_legendre
from ..streamutils import write_int64, write_array
def plot_ma... | gpl-2.0 |
vigilv/scikit-learn | sklearn/feature_selection/__init__.py | 244 | 1088 | """
The :mod:`sklearn.feature_selection` module implements feature selection
algorithms. It currently includes univariate filter selection methods and the
recursive feature elimination algorithm.
"""
from .univariate_selection import chi2
from .univariate_selection import f_classif
from .univariate_selection import f_... | bsd-3-clause |
Juanlu001/aquagpusph | examples/3D/spheric_testcase9_tld/cMake/plot_m.py | 1 | 6861 | #******************************************************************************
# *
# * ** * * * * *
# * * * * * * * * * *
... | gpl-3.0 |
liyu1990/sklearn | 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 |
CGATOxford/CGATPipelines | obsolete/reports/pipeline_chipseq/trackers/Manuscript.py | 1 | 2172 | import os
import sys
import re
import types
import itertools
import matplotlib.pyplot as plt
import numpy
import numpy.ma
from ChipseqReport import *
class ReproducibilityBetweenSamples(DefaultTracker):
def __call__(self, track, slice=None):
set1 = track + "R1"
set2 = track + "R2"
stat... | mit |
TNick/pylearn2 | pylearn2/train_extensions/roc_auc.py | 30 | 4854 | """
TrainExtension subclass for calculating ROC AUC scores on monitoring
dataset(s), reported via monitor channels.
"""
__author__ = "Steven Kearnes"
__copyright__ = "Copyright 2014, Stanford University"
__license__ = "3-clause BSD"
import numpy as np
try:
from sklearn.metrics import roc_auc_score
except ImportEr... | bsd-3-clause |
ChanChiChoi/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 |
anhaidgroup/py_entitymatching | py_entitymatching/blocker/attr_equiv_blocker.py | 1 | 25900 | import logging
import pandas as pd
import numpy as np
import pyprind
import six
from joblib import Parallel, delayed
import py_entitymatching.catalog.catalog_manager as cm
from py_entitymatching.blocker.blocker import Blocker
from py_entitymatching.utils.catalog_helper import log_info, get_name_for_key, add_key_colum... | bsd-3-clause |
zuku1985/scikit-learn | examples/cluster/plot_face_compress.py | 71 | 2479 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Vector Quantization Example
=========================================================
Face, a 1024 x 768 size image of a raccoon face,
is used here to illustrate how `k`-means is
used for vector quantization.
"""
... | bsd-3-clause |
mattilyra/scikit-learn | examples/classification/plot_digits_classification.py | 34 | 2409 | """
================================
Recognizing hand-written digits
================================
An example showing how the scikit-learn can be used to recognize images of
hand-written digits.
This example is commented in the
:ref:`tutorial section of the user manual <introduction>`.
"""
print(__doc__)
# Autho... | bsd-3-clause |
466152112/scikit-learn | sklearn/linear_model/ransac.py | 191 | 14261 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.valid... | bsd-3-clause |
cbmoore/statsmodels | statsmodels/graphics/tests/test_correlation.py | 31 | 1112 | import numpy as np
from numpy.testing import dec
from statsmodels.graphics.correlation import plot_corr, plot_corr_grid
from statsmodels.datasets import randhie
try:
import matplotlib.pyplot as plt
have_matplotlib = True
except:
have_matplotlib = False
@dec.skipif(not have_matplotlib)
def test_plot_cor... | bsd-3-clause |
expectocode/telegramAnalysis | activedays.py | 2 | 5649 | #!/usr/bin/env python3
"""
A program to plot the activity of a chat over 24 hours
"""
import argparse
from json import loads
from datetime import date,timedelta,datetime
from os import path
from collections import defaultdict
import matplotlib.pyplot as plt
from sys import maxsize
def extract_info(event):
text_... | mit |
smartscheduling/scikit-learn-categorical-tree | sklearn/metrics/metrics.py | 233 | 1262 | import warnings
warnings.warn("sklearn.metrics.metrics is deprecated and will be removed in "
"0.18. Please import from sklearn.metrics",
DeprecationWarning)
from .ranking import auc
from .ranking import average_precision_score
from .ranking import label_ranking_average_precision_score
fro... | bsd-3-clause |
btabibian/scikit-learn | sklearn/ensemble/tests/test_voting_classifier.py | 15 | 14956 | """Testing for the VotingClassifier"""
import numpy as np
from sklearn.utils.testing import assert_almost_equal, assert_array_equal
from sklearn.utils.testing import assert_equal, assert_true, assert_false
from sklearn.utils.testing import assert_raise_message
from sklearn.exceptions import NotFittedError
from sklearn... | bsd-3-clause |
riveridea/gnuradio | gr-digital/examples/example_fll.py | 9 | 5717 | #!/usr/bin/env python
#
# Copyright 2011-2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio 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, or (at your opt... | gpl-3.0 |
benoitsteiner/tensorflow-xsmm | 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 |
eg-zhang/scikit-learn | examples/calibration/plot_calibration.py | 225 | 4795 | """
======================================
Probability calibration of classifiers
======================================
When performing classification you often want to predict not only
the class label, but also the associated probability. This probability
gives you some kind of confidence on the prediction. However,... | bsd-3-clause |
jonnor/FreeCAD | src/Mod/Plot/Plot.py | 16 | 12328 | #***************************************************************************
#* *
#* Copyright (c) 2011, 2012 *
#* Jose Luis Cercos Pita <jlcercos@gmail.com> *
#* ... | lgpl-2.1 |
fabioticconi/scikit-learn | examples/mixture/plot_gmm_sin.py | 18 | 3242 | """
=================================
Gaussian Mixture Model Sine Curve
=================================
This example highlights the advantages of the Dirichlet Process:
complexity control and dealing with sparse data. The dataset is formed
by 100 points loosely spaced following a noisy sine curve. The fit by
the GMM... | bsd-3-clause |
themrmax/scikit-learn | sklearn/decomposition/tests/test_pca.py | 9 | 21107 | import numpy as np
import scipy as sp
from itertools import product
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 sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_gre... | bsd-3-clause |
thientu/scikit-learn | sklearn/utils/tests/test_murmurhash.py | 261 | 2836 | # Author: Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import numpy as np
from sklearn.externals.six import b, u
from sklearn.utils.murmurhash import murmurhash3_32
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
from nose.tools import assert_equa... | bsd-3-clause |
Srisai85/scikit-learn | sklearn/datasets/__init__.py | 176 | 3671 | """
The :mod:`sklearn.datasets` module includes utilities to load datasets,
including methods to load and fetch popular reference datasets. It also
features some artificial data generators.
"""
from .base import load_diabetes
from .base import load_digits
from .base import load_files
from .base import load_iris
from .... | bsd-3-clause |
kaushik94/tardis | tardis/model/base.py | 1 | 25604 | import os
import logging
import numpy as np
import pandas as pd
from astropy import units as u
from tardis import constants
from tardis.util.base import quantity_linspace
from tardis.io.parsers.csvy import load_csvy
from tardis.io.model_reader import read_density_file, \
read_abundances_file, read_uniform_abundanc... | bsd-3-clause |
amonszpart/globOpt | RAPter/scripts/normal_distr.py | 2 | 1814 |
import healpy as hp
import numpy as np
import matplotlib.pyplot as plt
def load_ply(path):
lines = []
verts = []
norms = []
f = open(path, "r")
for line in f:
lines.append(line)
if (lines[0] != "ply\n"):
return 0
i = 1
#get number of ve... | apache-2.0 |
mne-tools/mne-python | tutorials/io/30_reading_fnirs_data.py | 3 | 10521 | # -*- coding: utf-8 -*-
r"""
.. _tut-importing-fnirs-data:
=================================
Importing data from fNIRS devices
=================================
fNIRS devices consist of two kinds of optodes: light sources (AKA "emitters" or
"transmitters") and light detectors (AKA "receivers"). Channels are defined a... | bsd-3-clause |
ElDeveloper/scikit-learn | sklearn/neighbors/approximate.py | 30 | 22370 | """Approximate nearest neighbor search"""
# Author: Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>
# Joel Nothman <joel.nothman@gmail.com>
import numpy as np
import warnings
from scipy import sparse
from .base import KNeighborsMixin, RadiusNeighborsMixin
from ..base import BaseEstimator
from ..utils.va... | bsd-3-clause |
ClimbsRocks/scikit-learn | examples/cluster/plot_kmeans_stability_low_dim_dense.py | 338 | 4324 | """
============================================================
Empirical evaluation of the impact of k-means initialization
============================================================
Evaluate the ability of k-means initializations strategies to make
the algorithm convergence robust as measured by the relative stan... | bsd-3-clause |
rrader/cdr-tools | generator/test.py | 1 | 7514 | # Author: Jendrik Poloczek <jendrik.poloczek@madewithtea.com>
# License: BSD 3 clause
from windml.datasets.nrel import NREL
from windml.visualization.plot_timeseries import plot_timeseries
from windml.preprocessing.preprocessing import destroy
from windml.preprocessing.preprocessing import interpolate
from windml.prep... | mit |
costypetrisor/scikit-learn | sklearn/cluster/birch.py | 18 | 22657 | # Authors: Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Joel Nothman <joel.nothman@gmail.com>
# License: BSD 3 clause
from __future__ import division
import warnings
import numpy as np
from scipy import sparse
from math import sqrt
fro... | bsd-3-clause |
sibis-platform/ncanda-datacore | scripts/reporting/mri_dvd_burning_script.py | 4 | 3005 | #!/usr/bin/env python
##
## See COPYING file distributed along with the ncanda-data-integration package
## for the copyright and license terms
##
"""
mri_dvd_burning_script
======================
Generate a list of eids for a special subset of subjects. this list can be used
in script/xnat/check_object_names
"""
impo... | bsd-3-clause |
usc-isi-i2/WEDC | wedc/domain/core/ml/classifier/label_propagation/knn.py | 1 | 4394 | from sklearn.neighbors import NearestNeighbors
from sklearn import preprocessing
import numpy as np
import random
def build(graph_input, output=None, n_neighbors=10, algorithm='ball_tree', top_k_rate=None):
n_neighbors += 1
# load data
pid_set = [_[0] for _ in graph_input]
X = [_[1] for _ in graph_i... | apache-2.0 |
moinulkuet/machine-learning | Part 2 - Regression/Section 4 - Simple Linear Regression/simple_linear_regression.py | 4 | 1442 | # Simple Linear Regression
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Salary_Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 1].values
# Splitting the dataset into the Training set and Test set
from sk... | gpl-3.0 |
cauchycui/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 |
Obus/scikit-learn | examples/covariance/plot_lw_vs_oas.py | 248 | 2903 | """
=============================
Ledoit-Wolf vs OAS estimation
=============================
The usual covariance maximum likelihood estimate can be regularized
using shrinkage. Ledoit and Wolf proposed a close formula to compute
the asymptotically optimal shrinkage parameter (minimizing a MSE
criterion), yielding th... | bsd-3-clause |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/lib/matplotlib/testing/jpl_units/EpochConverter.py | 3 | 5331 | #===========================================================================
#
# EpochConverter
#
#===========================================================================
"""EpochConverter module containing class EpochConverter."""
#===========================================================================
# Pla... | gpl-2.0 |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/backends/backend_gtk3agg.py | 21 | 3815 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import sys
import warnings
from . import backend_agg
from . import backend_gtk3
from .backend_cairo import cairo, HAS_CAIRO_CFFI
from matplotlib.figure import Figure
from matplot... | gpl-3.0 |
anntzer/scikit-learn | sklearn/tests/test_kernel_ridge.py | 9 | 3320 | import pytest
import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_regression
from sklearn.linear_model import Ridge
from sklearn.kernel_ridge import KernelRidge
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils._testing import ignore_warnings
from sklearn.utils._test... | bsd-3-clause |
tynn/numpy | numpy/core/tests/test_multiarray.py | 2 | 274846 | from __future__ import division, absolute_import, print_function
try:
# Accessing collections abstract classes from collections
# has been deprecated since Python 3.3
import collections.abc as collections_abc
except ImportError:
import collections as collections_abc
import tempfile
import sys
import sh... | bsd-3-clause |
andreabedini/PyTables | doc/sphinxext/ipython_directive.py | 12 | 19507 | # -*- coding: utf-8 -*-
"""Sphinx directive to support embedded IPython code.
This directive allows pasting of entire interactive IPython sessions, prompts
and all, and their code will actually get re-executed at doc build time, with
all prompts renumbered sequentially.
To enable this directive, simply list it in you... | bsd-3-clause |
Roboticmechart22/sms-tools | lectures/06-Harmonic-model/plots-code/f0-TWM-errors-1.py | 22 | 3586 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackman
import math
import sys, os, functools, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel as DFT
import utilFunctions as UF
def TWM (pfreq, p... | agpl-3.0 |
sandeepgupta2k4/tensorflow | tensorflow/examples/learn/wide_n_deep_tutorial.py | 29 | 8985 | # 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 |
nan86150/ImageFusion | lib/python2.7/site-packages/matplotlib/backends/backend_gtk3agg.py | 21 | 3815 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import sys
import warnings
from . import backend_agg
from . import backend_gtk3
from .backend_cairo import cairo, HAS_CAIRO_CFFI
from matplotlib.figure import Figure
from matplot... | mit |
chris-chris/tensorflow | tensorflow/examples/learn/iris_custom_model.py | 50 | 2613 | # 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 |
DentonJC/virtual_screening | moloi/bin/svc.py | 1 | 3988 | #!/usr/bin/env python
import os
import sys
import time
import logging
import numpy as np
import pandas as pd
from datetime import datetime
from sklearn.svm import SVC
from sklearn.model_selection import RandomizedSearchCV
from sklearn.preprocessing import MinMaxScaler
from moloi.config_processing import read_model_con... | gpl-3.0 |
magnusax/ml-meta-wrapper | gazer/classifiers/gbm.py | 1 | 3404 | import numpy as np
from scipy.stats import randint, uniform
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import GradientBoostingClassifier
from ..base import BaseClassifier
from ..utils.stats import _uniform
class MetaGradBoostingClassifier(BaseClassifier):
"""
Meta classifier wr... | mit |
mross-22/dinsdale | src/two_inverted_pendulums/tools/thesis.py | 4 | 1607 | import numpy as np
import matplotlib
def figsize(scale):
fig_width_pt = 426.79135 # Get this from LaTeX using \the\textwidth
inches_per_pt = 1.0/72.27 # Convert pt to inch
golden_mean = (np.sqrt(5.0)-1.0)/2.0 # Aesthetic ratio (you could change this)
fig_width = fig_width_pt*inches_per_pt*scale # width... | gpl-3.0 |
Z2PackDev/Z2Pack | z2pack/plot.py | 1 | 7739 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""This submodule contains all functions for plotting Z2Pack results."""
import colorsys
import decorator
import numpy as np
from fsc.export import export
from ._utils import _pol_step
def _plot(proj_3d=False):
"""Decorator that sets up the figure axes and handles ... | gpl-3.0 |
ppaulojr/CrazyCorrelation | weather/fill_coords.py | 1 | 2110 | #!/usr/bin/env python
import math
from collections import defaultdict
from matplotlib.mlab import griddata
import matplotlib.pyplot as plt
import numpy as np
# http://en.wikipedia.org/wiki/Extreme_points_of_the_United_States#Westernmost
top = 49.3457868 # north lat
left = -124.7844079 # west long
right = -66.9513812 #... | mit |
PythonCharmers/bokeh | bokeh/cli/utils.py | 42 | 8119 | from __future__ import absolute_import, print_function
from collections import OrderedDict
from six.moves.urllib import request as urllib2
import io
import pandas as pd
from .. import charts
from . import help_messages as hm
def keep_source_input_sync(filepath, callback, start=0):
""" Monitor file at filepath ch... | bsd-3-clause |
equialgo/scikit-learn | sklearn/cluster/k_means_.py | 19 | 59631 | """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 |
tntnatbry/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/tensorflow_dataframe_test.py | 7 | 12865 | # 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 |
nomadcube/scikit-learn | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 408 | 8061 | import re
import inspect
import textwrap
import pydoc
from .docscrape import NumpyDocString
from .docscrape import FunctionDoc
from .docscrape import ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config=None):
config = {} if config is None else config
self.use_plots... | bsd-3-clause |
YangLiu928/NDP_Projects | Python_Projects/NLP/keyword assignment/TrashBin/preprosessing_bigram.py | 2 | 2737 | import cPickle as pickle
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
import json
from sklearn.naive_bayes import MultinomialNB
import numpy as np
from sklearn.linear_model import SGDClassifier
from nltk import word_tokenize
from nltk... | mit |
mauriceleutenegger/windprofile | PyWindProfile/examples/testOpticalDepth_scalar_vs_2D.py | 1 | 1144 | #!/usr/bin/env python
from __future__ import print_function # for python 2 backwards compatibility
import numpy as np
import matplotlib.pyplot as pl
import PyWindProfile as wp
# calculate t(p,z) for a large grid of points that shows
# how much faster it is to calculate using the 2d-array returning function
# vs. the ... | gpl-2.0 |
anntzer/scipy | scipy/optimize/zeros.py | 12 | 50109 | import warnings
from collections import namedtuple
import operator
from . import _zeros
import numpy as np
_iter = 100
_xtol = 2e-12
_rtol = 4 * np.finfo(float).eps
__all__ = ['newton', 'bisect', 'ridder', 'brentq', 'brenth', 'toms748',
'RootResults']
# Must agree with CONVERGED, SIGNERR, CONVERR, ... i... | bsd-3-clause |
CVML/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 130 | 50966 | # Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com> (main author)
# Mathieu Blondel (partial_fit support)
#
# License: BSD 3 clause
"""Classification and regression using Stochastic Gradient Descent (SGD)."""
import numpy as np
import scipy.sparse as sp
from abc import ABCMeta, abstractmethod
from ... | bsd-3-clause |
bikong2/scikit-learn | examples/plot_kernel_ridge_regression.py | 230 | 6222 | """
=============================================
Comparison of kernel ridge regression and SVR
=============================================
Both kernel ridge regression (KRR) and SVR learn a non-linear function by
employing the kernel trick, i.e., they learn a linear function in the space
induced by the respective k... | bsd-3-clause |
jreback/pandas | pandas/core/config_init.py | 1 | 20304 | """
This module is imported from the pandas package __init__.py file
in order to ensure that the core.config options registered here will
be available as soon as the user loads the package. if register_option
is invoked inside specific modules, they will not be registered until that
module is imported, which may or may... | bsd-3-clause |
AlexanderFabisch/scikit-learn | sklearn/feature_extraction/text.py | 4 | 50320 | # -*- coding: utf-8 -*-
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Robert Layton <robertlayton@gmail.com>
# Jochen Wersdörfer <jochen@wersdoerfer.de>
# Roman Sinayev <roman.sinayev@gma... | bsd-3-clause |
Jimmy-Morzaria/scikit-learn | examples/semi_supervised/plot_label_propagation_digits_active_learning.py | 294 | 3417 | """
========================================
Label Propagation digits active learning
========================================
Demonstrates an active learning technique to learn handwritten digits
using label propagation.
We start by training a label propagation model with only 10 labeled points,
then we select the t... | bsd-3-clause |
mne-tools/mne-tools.github.io | 0.16/_downloads/plot_decoding_csp_eeg.py | 8 | 5516 | """
===========================================================================
Motor imagery decoding from EEG data using the Common Spatial Pattern (CSP)
===========================================================================
Decoding of motor imagery applied to EEG data decomposed using CSP.
Here the classifier... | bsd-3-clause |
dsullivan7/scikit-learn | sklearn/metrics/classification.py | 9 | 61632 | """Metrics to assess performance on classification task given classe prediction
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.gram... | bsd-3-clause |
quantopian/alphalens | setup.py | 1 | 1841 | #!/usr/bin/env python
from setuptools import setup, find_packages
import versioneer
import sys
long_description = ''
if 'upload' in sys.argv:
with open('README.rst') as f:
long_description = f.read()
install_reqs = [
'matplotlib>=1.4.0',
'numpy>=1.9.1',
'pandas>=0.18.0',
'scipy>=0.14.0',
... | apache-2.0 |
spatialaudio/sweep | log_sweep_kaiser_window_script1/log_sweep_kaiser_window_script1_1.py | 2 | 2181 | #!/usr/bin/env python3
"""The influence of windowing of log. sweep signals when using a
Kaiser Window by fixing beta (=2) and fade_out (=0).
fstart = 1 Hz
fstop = 22050 Hz
Unwindowed Deconvolution
"""
import sys
sys.path.append('..')
import measurement_chain
import plotting
import calculation
import ge... | mit |
boomsbloom/dtm-fmri | DTM/for_gensim/lib/python2.7/site-packages/pandas/tests/types/test_concat.py | 7 | 3320 | # -*- coding: utf-8 -*-
import nose
import pandas as pd
import pandas.types.concat as _concat
import pandas.util.testing as tm
class TestConcatCompat(tm.TestCase):
_multiprocess_can_split_ = True
def check_concat(self, to_concat, exp):
for klass in [pd.Index, pd.Series]:
to_concat_klass... | mit |
phobson/statsmodels | statsmodels/datasets/heart/data.py | 3 | 1871 | """Heart Transplant Data, Miller 1976"""
__docformat__ = 'restructuredtext'
COPYRIGHT = """???"""
TITLE = """Transplant Survival Data"""
SOURCE = """ Miller, R. (1976). Least squares regression with censored dara. Biometrica, 63 (3). 449-464.
"""
DESCRSHORT = """Survival times after receiving a hear... | bsd-3-clause |
openfisca/openfisca-france-data | openfisca_france_data/__init__.py | 1 | 7336 | # -*- coding: utf-8 -*-
import inspect
import logging
import os
import pkg_resources
import pandas
from openfisca_core import reforms # type: ignore
import openfisca_france # type: ignore
# Load input variables and output variables into entities
from openfisca_france_data.model import common, survey_variables, i... | agpl-3.0 |
thouska/spotpy | spotpy/examples/dds/benchmark_dds.py | 2 | 3254 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from pprint import pprint
import numpy as np
import matplotlib.pylab as plt
import json
import time
try:
import spotpy
except ImportError:
import sys
sys.pa... | mit |
cheind/py-motmetrics | motmetrics/metrics.py | 1 | 26009 | # py-motmetrics - Metrics for multiple object tracker (MOT) benchmarking.
# https://github.com/cheind/py-motmetrics/
#
# MIT License
# Copyright (c) 2017-2020 Christoph Heindl, Jack Valmadre and others.
# See LICENSE file for terms.
"""Obtain metrics from event logs."""
# pylint: disable=redefined-outer-name
from __... | mit |
wazeerzulfikar/scikit-learn | sklearn/gaussian_process/gpc.py | 18 | 31958 | """Gaussian processes classification."""
# Authors: Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
#
# License: BSD 3 clause
import warnings
from operator import itemgetter
import numpy as np
from scipy.linalg import cholesky, cho_solve, solve
from scipy.optimize import fmin_l_bfgs_b
from scipy.special import erf... | bsd-3-clause |
nyuszika7h/youtube-dl | youtube_dl/extractor/wsj.py | 30 | 4694 | # coding: utf-8
from __future__ import unicode_literals
from .common import InfoExtractor
from ..utils import (
int_or_none,
float_or_none,
unified_strdate,
)
class WSJIE(InfoExtractor):
_VALID_URL = r'''(?x)
(?:
https?://video-api\.wsj\.com/api-vid... | unlicense |
GenericMappingTools/gmt-python | pygmt/src/x2sys_cross.py | 1 | 9403 | """
x2sys_cross - Calculate crossovers between track data files.
"""
import contextlib
import os
from pathlib import Path
import pandas as pd
from pygmt.clib import Session
from pygmt.exceptions import GMTInvalidInput
from pygmt.helpers import (
GMTTempFile,
build_arg_string,
data_kind,
dummy_context,
... | bsd-3-clause |
CJ8664/servo | tests/heartbeats/process_logs.py | 139 | 16143 | #!/usr/bin/env python
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import argparse
import matplotlib.pyplot as plt
import numpy as np
import os
from os import path
... | mpl-2.0 |
KristianJensen/cameo | tests/test_webmodels.py | 1 | 1527 | # Copyright 2015 Novo Nordisk Foundation Center for Biosustainability, DTU.
# 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 ... | apache-2.0 |
PYPIT/PYPIT | pypeit/core/flat.py | 1 | 52113 | """ Core module for methods related to flat fielding
"""
from __future__ import (print_function, absolute_import, division, unicode_literals)
import inspect
import numpy as np
import os
from scipy import interpolate
from pypeit import msgs
from pypeit.core import parse
from pypeit.core import qa
from pypeit.core imp... | gpl-3.0 |
bhargav/scikit-learn | examples/covariance/plot_outlier_detection.py | 41 | 4216 | """
==========================================
Outlier detection with several methods.
==========================================
When the amount of contamination is known, this example illustrates three
different ways of performing :ref:`outlier_detection`:
- based on a robust estimator of covariance, which is assum... | bsd-3-clause |
jakobj/nest-simulator | pynest/nest/voltage_trace.py | 18 | 7432 | # -*- coding: utf-8 -*-
#
# voltage_trace.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, ... | gpl-2.0 |
lucidfrontier45/scikit-learn | examples/linear_model/plot_ols.py | 2 | 1958 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Linear Regression Example
=========================================================
This example uses the only the first feature of the `diabetes` dataset, in
order to illustrate a two-dimensional plot of this regre... | bsd-3-clause |
msyriac/orphics | tests/legacy/testBinOptimization.py | 1 | 2506 |
import numpy as np
import orphics.tools.io as io
import matplotlib.pyplot as plt
import sys
from orphics.tools.catalogs import split_samples, optimize_splits
"""
This script shows you how to optimize bin edges to get equal S/N.
The example used is a fake data set composed of measurements of
richness that follow an... | bsd-2-clause |
bw4sz/DeepMeerkat | training/Keras/trainer/retrain.py | 1 | 5778 | import os
import sys
import glob
import argparse
from keras import __version__
from keras.applications.inception_v3 import InceptionV3, preprocess_input
from keras.models import Model
from keras.layers import Dense, GlobalAveragePooling2D
from keras.preprocessing.image import ImageDataGenerator
from keras.optimizers i... | gpl-3.0 |
tracierenea/gnuradio | gr-dtv/examples/atsc_ctrlport_monitor.py | 21 | 6089 | #!/usr/bin/env python
#
# Copyright 2015 Free Software Foundation
#
# 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, or (at your option)
# any later version.
#
# This program is... | gpl-3.0 |
meduz/NeuroTools | test/test_stgen.py | 2 | 9471 | """
Unit tests for the NeuroTools.stgen module
"""
import matplotlib
matplotlib.use('Agg')
import unittest
from NeuroTools import stgen
from NeuroTools import signals
import numpy
class StatisticalError(Exception):
pass
class StGenInitTest(unittest.TestCase):
def setUp(self):
pass
def tearDo... | gpl-2.0 |
britodasilva/pyhfo | pyhfo/core/pre_processing.py | 1 | 12090 | # -*- coding: utf-8 -*-
"""
Pre-processing using Data_dict
Created on Fri Apr 17 13:15:57 2015
@author: anderson
"""
import scipy.signal as sig
import numpy as np
from pyhfo.core import DataObj
import matplotlib.pyplot as plt
import itertools
def decimate(Data,q):
'''
Use scipy decimate to create a new DataOb... | mit |
annahs/atmos_research | WHI_long_term_make_SP2_GC_comparison_table-v2.py | 1 | 12794 | import matplotlib.pyplot as plt
import sys
import os
import numpy as np
from pprint import pprint
from datetime import datetime
from datetime import timedelta
import mysql.connector
import pickle
import math
import calendar
from math import log10, floor
GC_error = True
test_case = 'Van'#'default' #default, Van, wet_s... | mit |
MartinSavc/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 128 | 4761 | """
===================================
Compare cross decomposition methods
===================================
Simple usage of various cross decomposition algorithms:
- PLSCanonical
- PLSRegression, with multivariate response, a.k.a. PLS2
- PLSRegression, with univariate response, a.k.a. PLS1
- CCA
Given 2 multivari... | bsd-3-clause |
dp7-PU/QCLAS_public | src/mplCanvasWidget.py | 1 | 3235 | """
Define the widget for showing matplotlib in main GUI.
"""
from PyQt5 import QtCore, QtGui, QtWidgets
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
import sys
class mplCanvas(FigureCanvas):
def __init__(self, paren... | mit |
tmrowco/electricitymap | parsers/CR.py | 1 | 7979 | #!/usr/bin/env python3
# coding=utf-8
import logging
import arrow
import pandas as pd
import requests
from bs4 import BeautifulSoup
TIMEZONE = 'America/Costa_Rica'
DATE_FORMAT = 'DD/MM/YYYY'
MONTH_FORMAT = 'MM/YYYY'
POWER_PLANTS = {
u'Aeroenergía': 'wind',
u'Altamira': 'wind',
u'Angostura': 'hydro',
... | gpl-3.0 |
xlhtc007/blaze | blaze/compute/pyfunc.py | 7 | 6410 | from __future__ import absolute_import, division, print_function
import pandas as pd
from ..expr import (Expr, Symbol, Field, Arithmetic, Math,
Date, Time, DateTime, Millisecond, Microsecond, broadcast,
sin, cos, Map, UTCFromTimestamp, DateTimeTruncate, symbol,
... | bsd-3-clause |
mrshu/board2slides | project.py | 1 | 1597 | #!/usr/bin/env python
import sys
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
# Returns index of highest and lowest
# element in a array
def getMinMaxIndex(arr):
max = arr[0]
min = arr[0]
maxi = 0
mini = 0
for i in range(arr.shape[0]):
if max < arr[i]:
max = arr[i]
maxi = i
i... | apache-2.0 |
mwv/scikit-learn | sklearn/linear_model/tests/test_coordinate_descent.py | 114 | 25281 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from sys import version_info
import numpy as np
from scipy import interpolate, sparse
from copy import deepcopy
from sklearn.datasets import load_boston
from sklearn.utils.testing ... | bsd-3-clause |
cjayb/mne-python | mne/stats/tests/test_regression.py | 10 | 5761 | # Authors: Teon Brooks <teon.brooks@gmail.com>
# Denis A. Engemann <denis.engemann@gmail.com>
# Jona Sassenhagen <jona.sassenhagen@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose, assert_equal
import pytest
... | bsd-3-clause |
PascalSteger/gravimage | programs/sphere/gi_loglike.py | 1 | 11131 | #!/usr/bin/env ipython3
## @file
# define log likelihood function to be called by multinest
# spherical version
# (c) GPL v3 2015 ETHZ Pascal Steger, pascal@steger.aero
import numpy as np
import pdb
from scipy.interpolate import splev, splrep
#from pylab import *
#from multiprocessing import Pool
# import matplotli... | gpl-2.0 |
astrodsg/latbin | latbin/interpolation.py | 1 | 1953 | from copy import copy
import numpy as np
import scipy.sparse
import pandas as pd
from latbin.lattice import *
from latbin.matching import MatchingIndexer
class KernelWeightedMatchingInterpolator(object):
def __init__(self, x, y, x_scale, weighting_kernel=None, match_tolerance=6.0):
if weighting_kern... | bsd-3-clause |
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