repo_name stringlengths 6 112 | path stringlengths 4 204 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 714 810k | license stringclasses 15
values |
|---|---|---|---|---|---|
samuel1208/scikit-learn | sklearn/covariance/tests/test_covariance.py | 142 | 11068 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_alm... | bsd-3-clause |
e-koch/FilFinder | examples/paper_figures/run_gouldbelt.py | 3 | 6521 | # Licensed under an MIT open source license - see LICENSE
'''
Script to run fil_finder on the Herschel Gould Belt data set.
Can be run on multiple cores.
Data can be downloaded at http://www.herschel.fr/cea/gouldbelt/en/Phocea/Vie_des_labos/Ast/ast_visu.php?id_ast=66.
'''
from fil_finder import *
from astrop... | mit |
hrjn/scikit-learn | sklearn/utils/estimator_checks.py | 16 | 64623 | from __future__ import print_function
import types
import warnings
import sys
import traceback
import pickle
from copy import deepcopy
import numpy as np
from scipy import sparse
from scipy.stats import rankdata
import struct
from sklearn.externals.six.moves import zip
from sklearn.externals.joblib import hash, Memor... | bsd-3-clause |
arokem/nipy | doc/conf.py | 5 | 6641 | # emacs: -*- coding: utf-8; mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# sampledoc documentation build configuration file, created by
# sphinx-quickstart on Tue Jun 3 12:40:24 2008.
#
# This file is execfile()d with the current directory set to its containing... | bsd-3-clause |
toobaz/pandas | doc/source/conf.py | 1 | 23559 | #
# pandas documentation build configuration file, created by
#
# This file is execfile()d with the current directory set to its containing
# dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# se... | bsd-3-clause |
aewhatley/scikit-learn | sklearn/tests/test_grid_search.py | 68 | 28778 | """
Testing for grid search module (sklearn.grid_search)
"""
from collections import Iterable, Sized
from sklearn.externals.six.moves import cStringIO as StringIO
from sklearn.externals.six.moves import xrange
from itertools import chain, product
import pickle
import sys
import numpy as np
import scipy.sparse as sp
... | bsd-3-clause |
nanophotonics/nplab | nplab/analysis/__init__.py | 1 | 9190 | __author__ = 'alansanders'
import numpy as np
from pathlib import Path
import h5py
from scipy.ndimage import gaussian_filter
from functools import cached_property
def load_h5(location='.'):
'''return the latest h5 in a given directory. If location is left blank,
loads the latest file in the current directory.... | gpl-3.0 |
dinos66/termAnalysis | forTateDataset/quiverTest.py | 1 | 2810 |
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import interactive
from scipy.spatial import distance
from matplotlib.pyplot import cm
import matplotlib.colors as colors
n_columns, n_rows = 200, 120
X1 = [43, 51, 31, 5, 66, 22, 194, 66, 20, 45]
Y1 = [76, 54, 35, 3, 69, 16, 100, 46, 53, 101]
X2 = [... | apache-2.0 |
marcocaccin/scikit-learn | sklearn/linear_model/setup.py | 146 | 1713 | import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('linear_model', parent_package, top_path)
cblas_libs, blas_info = get_blas_info... | bsd-3-clause |
sabyasachi087/sp17-i524 | project/S17-IO-3012/code/bin/benchmark_replicas_find.py | 19 | 5441 | import matplotlib.pyplot as plt
import sys
import pandas as pd
def get_parm():
"""retrieves mandatory parameter to program
@param: none
@type: n/a
"""
try:
return sys.argv[1]
except:
print ('Must enter file name as parameter')
exit()
def read_file(filename):
"""... | apache-2.0 |
adammenges/statsmodels | statsmodels/datasets/strikes/data.py | 25 | 1951 | #! /usr/bin/env python
"""U.S. Strike Duration Data"""
__docformat__ = 'restructuredtext'
COPYRIGHT = """This is public domain."""
TITLE = __doc__
SOURCE = """
This is a subset of the data used in Kennan (1985). It was originally
published by the Bureau of Labor Statistics.
::
Kennan, J. 1985. "The... | bsd-3-clause |
marmarko/ml101 | tensorflow/examples/skflow/text_classification_builtin_rnn_model.py | 11 | 2984 | # 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... | bsd-2-clause |
loli/sklearn-ensembletrees | sklearn/tests/test_hmm.py | 31 | 28118 | from __future__ import print_function
import numpy as np
from numpy.testing import assert_array_equal, assert_array_almost_equal
from unittest import TestCase
from sklearn.datasets.samples_generator import make_spd_matrix
from sklearn import hmm
from sklearn import mixture
from sklearn.utils.extmath import logsumexp
... | bsd-3-clause |
xiaohan2012/lst | util.py | 1 | 4112 | import codecs
import ujson as json
import math
import gensim
import collections
import functools
import pandas as pd
from datetime import datetime, timedelta
from collections import defaultdict
def load_items_by_line(path):
with codecs.open(path, 'r', 'utf8') as f:
items = set([l.strip()
... | mit |
riastrad/newSeer | driver/dum.py | 1 | 2292 | #!/usr/bin/env python3
#
# @Author: Josh Erb <josh.erb>
# @Date: 06-Mar-2017 15:03
# @Email: josh.erb@excella.com
# @Last modified by: josh.erb
# @Last modified time: 24-Apr-2017 22:04
"""
Quick script to glob up a bunch of tsv files and insert them into a local
sqlite3 database.
Will only work if files have bee... | mit |
Garrett-R/scikit-learn | examples/applications/plot_stock_market.py | 29 | 8284 | """
=======================================
Visualizing the stock market structure
=======================================
This example employs several unsupervised learning techniques to extract
the stock market structure from variations in historical quotes.
The quantity that we use is the daily variation in quote ... | bsd-3-clause |
CforED/Machine-Learning | examples/ensemble/plot_gradient_boosting_regression.py | 87 | 2510 | """
============================
Gradient Boosting regression
============================
Demonstrate Gradient Boosting on the Boston housing dataset.
This example fits a Gradient Boosting model with least squares loss and
500 regression trees of depth 4.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prett... | bsd-3-clause |
fengzhyuan/scikit-learn | examples/model_selection/plot_roc_crossval.py | 247 | 3253 | """
=============================================================
Receiver Operating Characteristic (ROC) with cross validation
=============================================================
Example of Receiver Operating Characteristic (ROC) metric to evaluate
classifier output quality using cross-validation.
ROC curv... | bsd-3-clause |
lakshayg/tensorflow | tensorflow/contrib/timeseries/examples/multivariate.py | 67 | 5155 | # Copyright 2017 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 |
Achuth17/scikit-learn | examples/cluster/plot_lena_ward_segmentation.py | 271 | 1998 | """
===============================================================
A demo of structured Ward hierarchical clustering on Lena image
===============================================================
Compute the segmentation of a 2D image with Ward hierarchical
clustering. The clustering is spatially constrained in order
... | bsd-3-clause |
dhiapet/PyMC3 | pymc3/glm/glm.py | 14 | 5720 | import numpy as np
from ..core import *
from ..distributions import *
from ..tuning.starting import find_MAP
import patsy
import theano
import pandas as pd
from collections import defaultdict
from pandas.tools.plotting import scatter_matrix
from . import families
def linear_component(formula, data, priors=None,
... | apache-2.0 |
eickenberg/scikit-learn | sklearn/semi_supervised/label_propagation.py | 1 | 14906 | # coding=utf8
"""
Label propagation in the context of this module refers to a set of
semisupervised classification algorithms. In the high level, these algorithms
work by forming a fully-connected graph between all points given and solving
for the steady-state distribution of labels at each point.
These algorithms per... | bsd-3-clause |
zimenglan-sysu-512/pose_action_caffe | tools/train_svms.py | 42 | 13247 | #!/usr/bin/env python
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""
Train post-hoc SVMs using the algorithm and ... | mit |
tedunderwood/biographies | topicmodel/interpret/evaluate_hypotheses_docadjusted.py | 1 | 4227 | # evaluate_hypotheses_docadjusted.py
# This script evaluates our preregistered hypotheses using
# the doctopics file produced by MALLET.
import sys, csv
import numpy as np
import pandas as pd
from scipy.spatial.distance import euclidean, cosine
def getdoc(anid):
'''
Gets the docid part of a character id
... | mit |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/examples/pylab_examples/custom_cmap.py | 3 | 4967 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
"""
Example: suppose you want red to increase from 0 to 1 over the bottom
half, green to do the same over the middle half, and blue over the top
half. Then you would use:
cdict = {'red': ... | gpl-2.0 |
kcavagnolo/astroML | book_figures/appendix/fig_fft_text_example.py | 3 | 2376 | """
Example of a Fourier Transform
------------------------------
Figure E.1
An example of approximating the continuous Fourier transform of a function
using the fast Fourier transform.
"""
# Author: Jake VanderPlas
# License: BSD
# The figure produced by this code is published in the textbook
# "Statistics, Data ... | bsd-2-clause |
mne-tools/mne-tools.github.io | 0.17/_downloads/440494db0a9c51c8c5092ad97fd1ce2a/plot_topo_customized.py | 13 | 1927 | """
========================================
Plot custom topographies for MEG sensors
========================================
This example exposes the `iter_topography` function that makes it
very easy to generate custom sensor topography plots.
Here we will plot the power spectrum of each channel on a topographic
la... | bsd-3-clause |
GuessWhoSamFoo/pandas | pandas/tests/scalar/timedelta/test_formats.py | 9 | 1068 | # -*- coding: utf-8 -*-
import pytest
from pandas import Timedelta
@pytest.mark.parametrize('td, expected_repr', [
(Timedelta(10, unit='d'), "Timedelta('10 days 00:00:00')"),
(Timedelta(10, unit='s'), "Timedelta('0 days 00:00:10')"),
(Timedelta(10, unit='ms'), "Timedelta('0 days 00:00:00.010000')"),
... | bsd-3-clause |
alexeyum/scikit-learn | sklearn/calibration.py | 18 | 19402 | """Calibration of predicted probabilities."""
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Balazs Kegl <balazs.kegl@gmail.com>
# Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Mathieu Blondel <mathieu@mblondel.org>
#
# License: BSD 3 clause
from __future__ impo... | bsd-3-clause |
bmazin/ARCONS-pipeline | examples/Pal2014_throughput/throughputCalc_aperturePhot.py | 1 | 12594 | from util import utils
import sys,os
import tables
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from util.ObsFile import ObsFile
from util import MKIDStd
from util.readDict import readDict
from util.rebin import rebin
import matplotlib
from scipy import interpolate
from scipy.optimize.m... | gpl-2.0 |
RuthAngus/chronometer | chronometer/chronometer.py | 1 | 16573 | """
Now use Gibbs sampling to update individual star parameters and global gyro
parameters.
"""
import os
import time
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from isochrones import StarModel
from isochrones.mist import MIST_Isochrone
import h5py
import corner
import priors
from models ... | mit |
Kleptobismol/scikit-bio | doc/sphinxext/numpydoc/numpydoc/tests/test_docscrape.py | 39 | 18326 | # -*- encoding:utf-8 -*-
from __future__ import division, absolute_import, print_function
import sys, textwrap
from numpydoc.docscrape import NumpyDocString, FunctionDoc, ClassDoc
from numpydoc.docscrape_sphinx import SphinxDocString, SphinxClassDoc
from nose.tools import *
if sys.version_info[0] >= 3:
sixu = la... | bsd-3-clause |
iABC2XYZ/abc | Epics/DataAna11.3.py | 1 | 8055 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 27 15:44:34 2017
@author: p
"""
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
plt.close('all')
def GenWeight(shape):
initial = tf.truncated_normal(shape, stddev=1.)
return tf.Variable(initial)
def GenBi... | gpl-3.0 |
ai-se/XTREE | src/tools/oracle.py | 1 | 6506 | from __future__ import division
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from collections import Counter
from scipy.spatial.distance import euclidean
from random import choice, seed as rseed, uniform as rand
import pandas as pd
import numpy as np
from texttable import Texttable
from st... | mit |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/streamplot.py | 10 | 20629 | """
Streamline plotting for 2D vector fields.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange
import numpy as np
import matplotlib
import matplotlib.cm as cm
import matplotlib.colors as mcolors
import matplotlib.... | gpl-3.0 |
LEX2016WoKaGru/pyClamster | scripts/session/FE3_session_600.py | 1 | 1705 | #!/usr/bin/env python3
import pyclamster
import logging
import pickle
import os,sys
import matplotlib.pyplot as plt
# set up logging
logging.basicConfig(level=logging.DEBUG)
sessionfile = "data/sessions/FE3_session_new_600.pk"
try: # maybe there is already a session
session = pickle.load(open(sessionfile,"rb"))
e... | gpl-3.0 |
xubenben/scikit-learn | examples/ensemble/plot_adaboost_hastie_10_2.py | 355 | 3576 | """
=============================
Discrete versus Real AdaBoost
=============================
This example is based on Figure 10.2 from Hastie et al 2009 [1] and illustrates
the difference in performance between the discrete SAMME [2] boosting
algorithm and real SAMME.R boosting algorithm. Both algorithms are evaluate... | bsd-3-clause |
ajdawson/windspharm | examples/cdms/sfvp_example.py | 1 | 2297 | """
Compute streamfunction and velocity potential from the long-term-mean
flow.
This example uses the cdms interface.
Additional requirements for this example:
* cdms2 (http://uvcdat.llnl.gov/)
* matplotlib (http://matplotlib.org/)
* cartopy (http://scitools.org.uk/cartopy/)
"""
import cartopy.crs as ccrs
import cd... | mit |
google/makani | analysis/aero/avl/avl_reader.py | 1 | 21745 | #!/usr/bin/python
# Copyright 2020 Makani Technologies LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | apache-2.0 |
mfjb/scikit-learn | examples/svm/plot_svm_regression.py | 249 | 1451 | """
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
===================================================================
Toy example of 1D regression using linear, polynomial and RBF kernels.
"""
print(__doc__)
import numpy as np
... | bsd-3-clause |
Anton04/SolarDataRESTfulAPI | SolarDataRESTapi.py | 1 | 16625 | #!/bin/python
from flask import Flask, jsonify, abort,request,Response
import InfluxDBInterface
import json
import IoTtoolkit
#from elasticsearch import Elasticsearch
from ElasticsearchInterface import ESinterface
import os, sys
import time
import pandas as pd
app = Flask(__name__)
app.config.update(dict(
# DATAB... | mit |
francis-liberty/kaggle | Titanic/Viz/single_class.py | 1 | 2557 | # survival rate concerning class, sex and marriage status.
from pandas import Series, DataFrame
import pandas as pd
import matplotlib.pyplot as plt
import pylab
df = pd.read_csv('../Data/train.csv')
# slice
idx_male = df.Sex[df.Sex == 'male'].index
idx_female = df.index.diff(idx_male)
idx_single = df.SibSp[df.SibSp... | gpl-2.0 |
clemkoa/scikit-learn | doc/conf.py | 8 | 9924 | # -*- coding: utf-8 -*-
#
# scikit-learn documentation build configuration file, created by
# sphinx-quickstart on Fri Jan 8 09:13:42 2010.
#
# This file is execfile()d with the current directory set to its containing
# dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
... | bsd-3-clause |
dsullivan7/scikit-learn | sklearn/cluster/tests/test_affinity_propagation.py | 341 | 2620 | """
Testing for Clustering methods
"""
import numpy as np
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.cluster.affinity_propagation_ import AffinityPropagation
from sklearn.cluster.affinity_propagatio... | bsd-3-clause |
zaxtax/scikit-learn | sklearn/neighbors/approximate.py | 40 | 22369 | """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 |
jorik041/scikit-learn | examples/exercises/plot_cv_diabetes.py | 231 | 2527 | """
===============================================
Cross-validation on diabetes Dataset Exercise
===============================================
A tutorial exercise which uses cross-validation with linear models.
This exercise is used in the :ref:`cv_estimators_tut` part of the
:ref:`model_selection_tut` section of ... | bsd-3-clause |
indashnet/InDashNet.Open.UN2000 | android/external/chromium_org/chrome/test/nacl_test_injection/buildbot_chrome_nacl_stage.py | 24 | 10036 | #!/usr/bin/python
# Copyright (c) 2012 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Do all the steps required to build and test against nacl."""
import optparse
import os.path
import re
import shutil
import subproc... | apache-2.0 |
Windy-Ground/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 |
madjelan/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 |
PawarPawan/h2o-v3 | py2/h2o_cmd.py | 20 | 16497 |
import h2o_nodes
from h2o_test import dump_json, verboseprint
import h2o_util
import h2o_print as h2p
from h2o_test import OutputObj
#************************************************************************
def runStoreView(node=None, **kwargs):
print "FIX! disabling runStoreView for now"
return {}
if no... | apache-2.0 |
arabenjamin/scikit-learn | benchmarks/bench_plot_approximate_neighbors.py | 244 | 6011 | """
Benchmark for approximate nearest neighbor search using
locality sensitive hashing forest.
There are two types of benchmarks.
First, accuracy of LSHForest queries are measured for various
hyper-parameters and index sizes.
Second, speed up of LSHForest queries compared to brute force
method in exact nearest neigh... | bsd-3-clause |
tosolveit/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 159 | 10196 | 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 |
anomam/pvlib-python | pvlib/tests/iotools/test_midc.py | 1 | 2919 | import pandas as pd
from pandas.util.testing import network
import pytest
import pytz
from pvlib.iotools import midc
from conftest import DATA_DIR, RERUNS, RERUNS_DELAY
@pytest.fixture
def test_mapping():
return {
'Direct Normal [W/m^2]': 'dni',
'Global PSP [W/m^2]': 'ghi',
'Rel Humidity ... | bsd-3-clause |
anorfleet/kaggle-titanic | KaggleAux/predict.py | 6 | 3114 | import numpy as np
from pandas import DataFrame
from patsy import dmatrices
def get_dataframe_intersection(df, comparator1, comparator2):
"""
Return a dataframe with only the columns found in a comparative dataframe.
Parameters
----------
comparator1: DataFrame
DataFrame to preform compar... | apache-2.0 |
gerritholl/pyatmlab | pyatmlab/graphics.py | 1 | 9084 | #!/usr/bin/env python
# coding: utf-8
"""Interact with matplotlib and other plotters
"""
import os.path
import datetime
now = datetime.datetime.now
import logging
import subprocess
import sys
import pickle
import lzma
import pathlib
import numpy
import matplotlib
import matplotlib.cbook
import matplotlib.pyplot
imp... | bsd-3-clause |
lancezlin/ml_template_py | lib/python2.7/site-packages/matplotlib/delaunay/interpolate.py | 8 | 7288 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
import numpy as np
from matplotlib._delaunay import compute_planes, linear_interpolate_grid
from matplotlib._delaunay import nn_interpolate_grid
from matplotlib._delaunay ... | mit |
duyhtq/cuda-convnet2 | shownet.py | 180 | 18206 | # Copyright 2014 Google Inc. 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 applicable law or... | apache-2.0 |
soligschlager/topography | sandbox/macaque/clustering_embedding_macaque.py | 2 | 1476 | #!/usr/bin/python
import sys, os, h5py, scipy, numpy as np
from sklearn.utils.arpack import eigsh
from sklearn.cluster import KMeans
from scipy.io.matlab import savemat
def main(argv):
# Set defaults:
n_components_embedding = 25
comp_min = 2
comp_max = 20 + 1
varname = 'data'
filename = '... | mit |
mkrapp/semic | optimize/plot_costs.py | 2 | 1367 | '''
plot the best PSO positions.
'''
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import sys
from tools import get_params
def plot_costs(fnm,show=True,savefig=False):
params, par_names = get_params()
print params
data = np.loadtxt(fnm,unpack=True)
mpl.rcParams[... | mit |
levjj/rticomp | experiment-jpeg.py | 1 | 5075 | '''
File compress.py
Created on 11 Feb 2014
@author: Christopher Schuster, cschuste@ucsc.edu
'''
# General imports
from __future__ import print_function
import os,sys,subprocess,struct,io
# Possible use of matplotlib from http://http://matplotlib.sourceforge.net/
from pylab import *
import matplotlib.pyplot as plt
#... | mit |
ajheaps/cf-plot | cfplot/cfplot.py | 1 | 336361 | """
Climate contour/vector plots using cf-python, matplotlib and cartopy.
Andy Heaps NCAS-CMS April 2021
"""
import numpy as np
import subprocess
from scipy import interpolate
import matplotlib
from copy import deepcopy
import os
import sys
import matplotlib.pyplot as plot
from matplotlib.collections import PolyCollect... | mit |
ephes/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 142 | 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 |
paalge/scikit-image | doc/examples/features_detection/plot_multiblock_local_binary_pattern.py | 9 | 2603 | """
===========================================================
Multi-Block Local Binary Pattern for texture classification
===========================================================
This example shows how to compute multi-block local binary pattern (MB-LBP)
features as well as how to visualize them.
The features ar... | bsd-3-clause |
felipeacsi/python-acoustics | acoustics/_signal.py | 1 | 36315 | import itertools
import matplotlib.pyplot as plt
import numpy as np
from scipy.io import wavfile
from scipy.signal import detrend, lfilter, bilinear, spectrogram, filtfilt, resample, fftconvolve
import acoustics
from acoustics.standards.iso_tr_25417_2007 import REFERENCE_PRESSURE
from acoustics.standards.iec_61672_1_2... | bsd-3-clause |
udacity/ggplot | ggplot/components/smoothers.py | 12 | 2576 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from pandas.lib import Timestamp
import pandas as pd
import statsmodels.api as sm
from statsmodels.nonparametric.smoothers_lowess import lowess as smlowess
from statsmodels.sandbox.regression.... | bsd-2-clause |
appapantula/scikit-learn | sklearn/utils/validation.py | 67 | 24013 | """Utilities for input validation"""
# Authors: Olivier Grisel
# Gael Varoquaux
# Andreas Mueller
# Lars Buitinck
# Alexandre Gramfort
# Nicolas Tresegnie
# License: BSD 3 clause
import warnings
import numbers
import numpy as np
import scipy.sparse as sp
from ..externals i... | bsd-3-clause |
zedoul/AnomalyDetection | test_discretization/test_spectralclustering3.py | 1 | 8781 | # -*- coding: utf-8 -*-
"""
http://www.astroml.org/sklearn_tutorial/dimensionality_reduction.html
"""
print (__doc__)
import numpy as np
import copy
import matplotlib
import matplotlib.mlab
import matplotlib.pyplot as plt
from matplotlib import gridspec
from sklearn.cluster import KMeans
import pandas as pd
import ... | mit |
cactusbin/nyt | matplotlib/lib/mpl_toolkits/mplot3d/proj3d.py | 7 | 6832 | #!/usr/bin/python
# 3dproj.py
#
"""
Various transforms used for by the 3D code
"""
from matplotlib.collections import LineCollection
from matplotlib.patches import Circle
import numpy as np
import numpy.linalg as linalg
def line2d(p0, p1):
"""
Return 2D equation of line in the form ax+by+c = 0
"""
#... | unlicense |
bsautermeister/machine-learning-examples | dnn_classification/tf_learn/custom_dnn_abalone.py | 1 | 8357 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import argparse
import tempfile
from six.moves import urllib
import numpy as np
import tensorflow as tf
import sklearn.metrics
tf.logging.set_verbosity(tf.logging.INFO)
def maybe_download(train_d... | mit |
ryfeus/lambda-packs | LightGBM_sklearn_scipy_numpy/source/sklearn/linear_model/setup.py | 83 | 1719 | import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('linear_model', parent_package, top_path)
cblas_libs, blas_info = get_blas_info... | mit |
bakfu/benchmark | bench/tools.py | 1 | 2989 | import os
import random
import numpy as np
from sklearn.ensemble import RandomForestClassifier
import nltk
from bakfu.core.routes import register
from bakfu.core.classes import Processor
import logging
log = logger = logging.getLogger('bench')
result_logger = logging.getLogger('bench_results')
@register('... | bsd-3-clause |
depet/scikit-learn | sklearn/tests/test_base.py | 9 | 5815 |
# 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 imp... | bsd-3-clause |
agartland/pysieve | distance.py | 1 | 31210 | """
distance.py
Distance functions to be called by the analysis functions.
TODO:
- Standardize inputs to distance functions to make the architecture more "plug-n-play"
- Release a version of seqtools with the required functions to satisfy dependencies
Generally a distance function should have the following inputs:
... | mit |
marqh/iris | lib/iris/tests/unit/plot/test_contour.py | 11 | 2995 | # (C) British Crown Copyright 2014 - 2016, Met Office
#
# This file is part of Iris.
#
# Iris is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any l... | lgpl-3.0 |
SU-ECE-17-7/ibeis | _scripts/win32bootstrap.py | 2 | 23140 | # -*- coding: utf-8 -*-
r"""
Hacky file to download win packages
Please only download files as needed.
Args:
--dl {pkgname:str} : package name to download
--run : if true runs installer on win32
CommandLine:
python _scripts\win32bootstrap.py --dl winapi --run
python _scripts\win32bootstrap.py --dl pyp... | apache-2.0 |
istellartech/OpenGoddard | examples/04_Goddard_0knot.py | 1 | 6069 | # -*- coding: utf-8 -*-
# Copyright 2017 Interstellar Technologies Inc. All Rights Reserved.
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
from OpenGoddard.optimize import Problem, Guess, Condition, Dynamics
class Rocket:
g0 = 1.0 # Gravity at surface [-]
def __in... | mit |
abhishekkrthakur/scikit-learn | sklearn/decomposition/__init__.py | 99 | 1331 | """
The :mod:`sklearn.decomposition` module includes matrix decomposition
algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
this module can be regarded as dimensionality reduction techniques.
"""
from .nmf import NMF, ProjectedGradientNMF
from .pca import PCA, RandomizedPCA
from .incrementa... | bsd-3-clause |
m3wolf/scimap | scimap/peakfitting.py | 1 | 16766 | # -*- coding: utf-8 -*-
#
# Copyright © 2016 Mark Wolf
#
# This file is part of scimap.
#
# Scimap is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any lat... | gpl-3.0 |
Obus/scikit-learn | sklearn/metrics/pairwise.py | 104 | 42995 | # -*- 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 |
bowenliu16/deepchem | deepchem/dock/binding_pocket.py | 1 | 11449 | """
Computes putative binding pockets on protein.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
__author__ = "Bharath Ramsundar"
__copyright__ = "Copyright 2017, Stanford University"
__license__ = "GPL"
import os
import tempfile
import numpy as np
im... | gpl-3.0 |
mganeva/mantid | scripts/test/directtools/DirectToolsTest.py | 1 | 17930 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source
# & Institut Laue - Langevin
# SPDX - License - Identifier: GPL - 3.0 +
from __future__ import (absolute_import, divi... | gpl-3.0 |
petebachant/seaborn | seaborn/categorical.py | 19 | 102299 | from __future__ import division
from textwrap import dedent
import colorsys
import numpy as np
from scipy import stats
import pandas as pd
from pandas.core.series import remove_na
import matplotlib as mpl
import matplotlib.pyplot as plt
import warnings
from .external.six import string_types
from .external.six.moves im... | bsd-3-clause |
kazemakase/scikit-learn | sklearn/decomposition/base.py | 313 | 5647 | """Principal Component Analysis Base Classes"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Kyle Kastner <kastnerkyle@gmail.com>
#
# Licen... | bsd-3-clause |
zhenwendai/RGP | autoreg/benchmark/run.py | 1 | 2773 | # Copyright (c) 2015, Zhenwen Dai
# Licensed under the BSD 3-clause license (see LICENSE.txt)
from __future__ import print_function
from evaluation import RMSE
from methods import Autoreg_onelayer, Autoreg_onelayer_bfgs
from tasks import all_tasks
from outputs import PickleOutput, CSV_Summary
import numpy as np
import... | bsd-3-clause |
manashmndl/scikit-learn | sklearn/utils/tests/test_sparsefuncs.py | 57 | 13752 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from numpy.testing import assert_array_almost_equal, assert_array_equal
from sklearn.datasets import make_classification
from sklearn.utils.sparsefuncs import (mean_variance_axis,
inplace_column_scale,
... | bsd-3-clause |
samzhang111/scikit-learn | examples/gaussian_process/plot_gpr_co2.py | 9 | 5718 | """
========================================================
Gaussian process regression (GPR) on Mauna Loa CO2 data.
========================================================
This example is based on Section 5.4.3 of "Gaussian Processes for Machine
Learning" [RW2006]. It illustrates an example of complex kernel engine... | bsd-3-clause |
pradyu1993/scikit-learn | sklearn/linear_model/tests/test_omp.py | 2 | 7018 | # Author: Vlad Niculae
# License: BSD style
import warnings
import numpy as np
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_arr... | bsd-3-clause |
shenzebang/scikit-learn | examples/linear_model/plot_omp.py | 385 | 2263 | """
===========================
Orthogonal Matching Pursuit
===========================
Using orthogonal matching pursuit for recovering a sparse signal from a noisy
measurement encoded with a dictionary
"""
print(__doc__)
import matplotlib.pyplot as plt
import numpy as np
from sklearn.linear_model import OrthogonalM... | bsd-3-clause |
Akshay0724/scikit-learn | sklearn/neighbors/tests/test_dist_metrics.py | 36 | 6957 | import itertools
import pickle
import numpy as np
from numpy.testing import assert_array_almost_equal
import scipy
from scipy.spatial.distance import cdist
from sklearn.neighbors.dist_metrics import DistanceMetric
from sklearn.neighbors import BallTree
from sklearn.utils.testing import SkipTest, assert_raises_regex
... | bsd-3-clause |
rjeli/scikit-image | doc/examples/features_detection/plot_holes_and_peaks.py | 9 | 2713 | """
===============================
Filling holes and finding peaks
===============================
We fill holes (i.e. isolated, dark spots) in an image using morphological
reconstruction by erosion. Erosion expands the minimal values of the seed image
until it encounters a mask image. Thus, the seed image and mask i... | bsd-3-clause |
lisitsyn/shogun | applications/easysvm/tutpaper/svm_params.py | 12 | 12908 |
#from matplotlib import rc
#rc('text', usetex=True)
fontsize = 16
contourFontsize = 12
showColorbar = False
xmin = -1
xmax = 1
ymin = -1.05
ymax = 1
import sys,os
import numpy
import shogun
from shogun import GaussianKernel, LinearKernel, PolyKernel
from shogun import RealFeatures, BinaryLabels
from shogun import L... | bsd-3-clause |
cimat/data-visualization-patterns | display-patterns/Proportions/Pruebas/A42Ring_Chart_Matplotlib.py | 1 | 2204 | library(ggplot2)
t<-table(mtcars$cyl)
x<-as.data.frame(t)
colnames(x)<-c("Cylindres", "Frequency")
bp <- ggplot(x, aes(x ="",y=Frequency, fill = Cylindres)) +
geom_bar(width = 1, stat = "identity") +labs (title="Proportion Cylindres in a Car Distribution")
pie <-bp+coord_polar("y", start=0)
pie + geom_text(aes(y =... | cc0-1.0 |
matthewfranglen/spark | python/pyspark/sql/pandas/group_ops.py | 9 | 14192 | #
# 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... | mit |
ericmjl/bokeh | tests/unit/bokeh/document/test_events__document.py | 1 | 20531 | #-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.
# All rights reserved.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#-------------------------------------------------------------------... | bsd-3-clause |
JPFrancoia/scikit-learn | sklearn/linear_model/coordinate_descent.py | 13 | 81631 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Gael Varoquaux <gael.varoquaux@inria.fr>
#
# License: BSD 3 clause
import sys
import warnings
from abc import ABCMeta, abstractmethod
import n... | bsd-3-clause |
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