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 |
|---|---|---|---|---|---|
pong3489/TEST_Mission | Lib/site-packages/scipy/misc/common.py | 53 | 10116 | """
Functions which are common and require SciPy Base and Level 1 SciPy
(special, linalg)
"""
from numpy import exp, asarray, arange, newaxis, hstack, product, array, \
where, zeros, extract, place, pi, sqrt, eye, poly1d, dot, r_
__all__ = ['factorial','factorial2','factorialk','comb',
'c... | gpl-3.0 |
bigdataelephants/scikit-learn | examples/neighbors/plot_regression.py | 349 | 1402 | """
============================
Nearest Neighbors regression
============================
Demonstrate the resolution of a regression problem
using a k-Nearest Neighbor and the interpolation of the
target using both barycenter and constant weights.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@... | bsd-3-clause |
StanczakDominik/PythonBiotSavart | biot.py | 1 | 30332 | from __future__ import division, print_function
import numpy as np
import matplotlib.pyplot as plt
from numpy import pi, sin, cos, mgrid
from mayavi import mlab
import os.path
import scipy.spatial
import sys
import shutil
import h5py
import pdb
import sys
#Grid parameters
NGRID=50
NZGRID=NGRID
#Region parameters
xmax... | gpl-3.0 |
olologin/scikit-learn | sklearn/ensemble/tests/test_forest.py | 21 | 41768 | """
Testing for the forest module (sklearn.ensemble.forest).
"""
# Authors: Gilles Louppe,
# Brian Holt,
# Andreas Mueller,
# Arnaud Joly
# License: BSD 3 clause
import pickle
from collections import defaultdict
from itertools import combinations
from itertools import product
import numpy ... | bsd-3-clause |
cavestruz/MLPipeline | PCAManifold.py | 1 | 2769 |
# coding: utf-8
# In[ ]:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import ticker
from sklearn import manifold, datasets, decomposition
# In[ ]:
from astroML.plotting import setup_text_plots
setup_text_plots(fontsize=8, usetex=True)
# In[ ]:
np.random.seed(0)
n_points = 4000 #110... | mit |
dhenrygithub/QGIS | python/plugins/processing/algs/qgis/VectorLayerHistogram.py | 15 | 3006 | # -*- coding: utf-8 -*-
"""
***************************************************************************
EquivalentNumField.py
---------------------
Date : January 2013
Copyright : (C) 2013 by Victor Olaya
Email : volayaf at gmail dot com
*******************... | gpl-2.0 |
probml/pyprobml | scripts/lms_demo.py | 1 | 6196 | # SGD on linear regression aka least mean squares
# Written by Duane Rich
# Based on https://github.com/probml/pmtk3/blob/master/demos/LMSdemoSimple.m
import numpy as np
import matplotlib.pyplot as plt
from pyprobml_utils import save_fig
#from mpl_toolkits.mplot3d import Axes3D
from scipy.optimize import minimize
... | mit |
mufid/berkilau | ws/CSUIBotClass2014/test/test_plot_particles.py | 1 | 1997 | #!/usr/bin/python
# @author: vektor dewanto
# @obj: demonstrate how to plot particles in an occupancy grid map, _although_, for now, all positions are valid
import matplotlib.pyplot as plt
import numpy as np
import math
import matplotlib.cm as cmx
from matplotlib import colors
# Construct the occupancy grid map
grid... | mit |
devincornell/semanticanlysis | dictionary.py | 1 | 5447 | import spacy
from .parallel import *
import re
import functools
#from .topicmodel import TopicModel
''' This class parses data according to the MFD format. Available are the empath, mft and mft2.0 dictionaries.
For further information about the format of the dictionary files, see Haidt et al.'s example:
http://www.m... | mit |
DarkEnergyScienceCollaboration/Twinkles | python/desc/twinkles/obsHistIDOrdering.py | 2 | 10882 | from __future__ import absolute_import, division, print_function
import os
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
from lsst.utils import getPackageDir
from .phosim_cpu_pred import CpuPred
__all__ = ['OpSimOrdering']
class OpSimOrdering(object):
"""
Code to split the Twink... | mit |
phoebe-project/phoebe2 | tests/nosetests/test_mesh/test_marching_meshing.py | 1 | 4816 | """
Testing marching triangulation algorithm directly from libphoebe
"""
import numpy as np
from numpy import linalg as la
import libphoebe
import matplotlib.pyplot as plt
def potential_roche(r, q, F, d):
r1 = np.array([r[0]- d, r[1], r[2]]);
return 1/la.norm(r) + q*(1/la.norm(r1) - r[0]/d**2) + F**2*(1+q)*(r[... | gpl-3.0 |
deepesch/Data-Science-45min-Intros | support-vector-machines-101/rbf-circles.py | 26 | 1504 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
__author__="Josh Montague"
__license__="MIT License"
import sys
import json
import numpy as np
import matplotlib.pyplot as plt
try:
import seaborn as sns
except ImportError as e:
sys.stderr.write("seaborn not installed. Using default matplotlib templates.")
from sk... | unlicense |
mlperf/training_results_v0.6 | Intel/benchmarks/minigo/implementations/tensorflow/oneoffs/embeddings_graphs.py | 8 | 3394 | #!/usr/bin/env python3
# Copyright 2018 Google 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 applicable law o... | apache-2.0 |
sam81/pychoacoustics | tests/test_weighted_up_down.py | 1 | 2655 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import numpy, os, sys, unittest
import pandas as pd
from test_utility_functions import*
rootPath = "../../pychoacoustics_data/test_data/"
class TestWeightedUpDown(unittest.TestCase):
def testGeometric(self):
resFileRoot = "res_geometric"
removePrevio... | gpl-3.0 |
biosustain/marsi | marsi/cli/controllers/modeling.py | 1 | 11810 | # Copyright 2017 Chr. Hansen A/S and The 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.... | apache-2.0 |
zaxtax/scikit-learn | examples/cluster/plot_cluster_comparison.py | 246 | 4684 | """
=========================================================
Comparing different clustering algorithms on toy datasets
=========================================================
This example aims at showing characteristics of different
clustering algorithms on datasets that are "interesting"
but still in 2D. The last ... | bsd-3-clause |
intelligent-agent/redeem | tools/bed_compensation.py | 1 | 6746 | """
This script allows plotting the surface of the bed.
"""
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import random
single = True
# With reset of probe
before = [{
"Y": 0.0,
"X": 0.065,
"Z": -0.0020124999999999991
}, {
"Y": 0.0325,
"X": 0.05629,
... | gpl-3.0 |
steverobbins/mycli | mycli/packages/tabulate.py | 28 | 38075 | # -*- coding: utf-8 -*-
"""Pretty-print tabular data."""
from __future__ import print_function
from __future__ import unicode_literals
from collections import namedtuple
from decimal import Decimal
from platform import python_version_tuple
from wcwidth import wcswidth
import re
if python_version_tuple()[0] < "3":
... | bsd-3-clause |
andyraib/data-storage | python_scripts/env/lib/python3.6/site-packages/pandas/tests/series/test_constructors.py | 7 | 28387 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
from datetime import datetime, timedelta
from numpy import nan
import numpy as np
import numpy.ma as ma
import pandas as pd
from pandas.types.common import is_categorical_dtype, is_datetime64tz_dtype
from pandas import Index, Series, isnull, date_range, period_range
f... | apache-2.0 |
caseyclements/blaze | blaze/tests/test_interactive.py | 2 | 10339 | from blaze.interactive import Data, compute, concrete_head, expr_repr, to_html
import datetime
from odo import into, append
from odo.backends.csv import CSV
from blaze import discover, transform
from blaze.compute.core import compute
from blaze.compute.python import compute
from blaze.expr import symbol
from datashape... | bsd-3-clause |
zorojean/scikit-learn | sklearn/datasets/base.py | 196 | 18554 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import shutil
from os import environ
from os.pa... | bsd-3-clause |
winklerand/pandas | pandas/tests/plotting/common.py | 2 | 19541 | #!/usr/bin/env python
# coding: utf-8
import pytest
import os
import warnings
from pandas import DataFrame, Series
from pandas.compat import zip, iteritems
from pandas.util._decorators import cache_readonly
from pandas.core.dtypes.api import is_list_like
import pandas.util.testing as tm
from pandas.util.testing impor... | bsd-3-clause |
plotly/python-api | packages/python/plotly/plotly/figure_factory/_ohlc.py | 2 | 10741 | from __future__ import absolute_import
from plotly import exceptions
from plotly.graph_objs import graph_objs
from plotly.figure_factory import utils
# Default colours for finance charts
_DEFAULT_INCREASING_COLOR = "#3D9970" # http://clrs.cc
_DEFAULT_DECREASING_COLOR = "#FF4136"
def validate_ohlc(open, high, low,... | mit |
qiime2/qiime2 | qiime2/metadata/base.py | 2 | 2057 | # ----------------------------------------------------------------------------
# Copyright (c) 2016-2021, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/sklearn/utils/tests/test_extmath.py | 6 | 24129 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis Engemann <denis-alexander.engemann@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from scipy import linalg
from scipy import stats
from sklearn.utils.testing import ... | mit |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/lib/matplotlib/table.py | 2 | 17111 | """
Place a table below the x-axis at location loc.
The table consists of a grid of cells.
The grid need not be rectangular and can have holes.
Cells are added by specifying their row and column.
For the purposes of positioning the cell at (0, 0) is
assumed to be at the top left and the cell at (max_row, max_col)
i... | mit |
IngoKl/TweetPinna | TweetPinnaGraphs.py | 1 | 7816 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""TweetPinna - Twitter Status Archiver - Dashboard.
TweetPinna streams Twitter statuses into a
MongoDB database based on given search terms.
It is also capable of retrieving a user's timeline.
This script generates graphs for the dashboard.
It is supposed to run... | mit |
nathawkins/PHY451_FS_2017 | Cavendish_Experiment/Scripts/reduce-2.py | 2 | 34081 | # -*- coding: utf-8 -*-
"""
Spinlab Curve Fitting Library
File: SpinlabCF.py
Author: Steve Fromm
Last Modified: 2017-09-05
This library provides an easy to use interface to perform non-linear function
fitting to a provided data set. The underlying curve-fitting algorithm is
from the scipy.optimize package.... | gpl-3.0 |
appapantula/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 35 | 15016 | from __future__ import division
from collections import defaultdict
from functools import partial
import numpy as np
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
fr... | bsd-3-clause |
dilawar/moose-full | moose-examples/snippets/gssaCylinderDiffusion.py | 2 | 6418 | #########################################################################
## This program is part of 'MOOSE', the
## Messaging Object Oriented Simulation Environment.
## Copyright (C) 2014 Upinder S. Bhalla. and NCBS
## It is made available under the terms of the
## GNU Lesser General Public License version 2... | gpl-2.0 |
modelblocks/modelblocks-release | resource-naturalstoriesfmri/scripts/get_sound_power.py | 1 | 4677 | import sys
import re
import numpy as np
import pandas as pd
import librosa
import argparse
argparser = argparse.ArgumentParser('''
Utility for computing sound power metrics from the Natural Stories audio stimuli
''')
argparser.add_argument('files', nargs='+', help='Paths to audio files for processing')
argpars... | gpl-3.0 |
bearishtrader/trading-with-python | lib/classes.py | 76 | 7847 | """
worker classes
@author: Jev Kuznetsov
Licence: GPL v2
"""
__docformat__ = 'restructuredtext'
import os
import logger as logger
import yahooFinance as yahoo
from functions import returns, rank
from datetime import date
from pandas import DataFrame, Series
import numpy as np
import pandas as pd
im... | bsd-3-clause |
timnon/pyschedule | examples/switch-types.py | 1 | 1505 |
import sys
sys.path += ['../src','src']
import getopt
opts, _ = getopt.getopt(sys.argv[1:], 't:', ['test'])
from pyschedule import Scenario, solvers, plotters
horizon = 20
S = Scenario('switch',horizon=horizon)
# Set some colors for the tasks
task_colors = dict()
task_group_colors = { 'A': 'green', 'B': 'red', 'C':'b... | apache-2.0 |
eblossom/gnuradio | gr-analog/examples/fmtest.py | 40 | 7941 | #!/usr/bin/env python
#
# Copyright 2009,2012,2013 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 ... | gpl-3.0 |
googledatalab/pydatalab | google/datalab/ml/_dataset.py | 2 | 8647 | # Copyright 2017 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 agreed ... | apache-2.0 |
dsquareindia/scikit-learn | sklearn/metrics/cluster/supervised.py | 25 | 31477 | """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>
# Arnaud Fouchet ... | bsd-3-clause |
markomanninen/strongs | isopsephy/search.py | 5 | 1537 | #!/usr/local/bin/python
# -*- coding: utf-8 -*-
# file: search.py
def find_cumulative_indices(list_of_numbers, search_sum):
"""
find_cumulative_indices([70, 58, 81, 909, 70, 215, 70, 1022, 580, 930, 898], 285) ->
[[4, 5],[5, 6]]
"""
u = 0
y = 0
result = []
for idx, val in enumerate(lis... | mit |
pprett/scikit-learn | sklearn/preprocessing/data.py | 8 | 68191 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Olivier Grisel <olivier.grisel@ensta.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Eric Martin <eric@ericmart.in>
# Giorgio Patrini <giorgio.patrini@anu.edu.au>
# Lic... | bsd-3-clause |
OshynSong/scikit-learn | sklearn/tests/test_cross_validation.py | 31 | 46699 | """Test the cross_validation module"""
from __future__ import division
import warnings
import numpy as np
from scipy.sparse import coo_matrix
from scipy.sparse import csr_matrix
from scipy import stats
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.test... | bsd-3-clause |
MVilstrup/visualize | learning_curves.py | 1 | 3902 | # I have not had the time to test this method yet
# so do not use it in its current state
import numpy as np
import matplotlib.pyplot as plt
def plot_learning_curves(training_data,
training_targets,
test_data,
test_targets,
... | mit |
ClimbsRocks/scikit-learn | sklearn/neighbors/tests/test_nearest_centroid.py | 305 | 4121 | """
Testing for the nearest centroid module.
"""
import numpy as np
from scipy import sparse as sp
from numpy.testing import assert_array_equal
from numpy.testing import assert_equal
from sklearn.neighbors import NearestCentroid
from sklearn import datasets
from sklearn.metrics.pairwise import pairwise_distances
# t... | bsd-3-clause |
subutai/htmresearch | htmresearch/frameworks/union_temporal_pooling/activation/excite_functions/excite_functions_all.py | 9 | 3762 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
qwertzuhr/2015_Data_Analyst_Project_3 | Project/audit_quality_map.py | 3 | 3625 | ## Note: you must install Levenshtein module
# pip install python-Levenshtein
# for this Microsoft Visual C++ 9.0 is required. Get it from http://aka.ms/vcpython27
# more info - see: http://stackoverflow.com/questions/18134437/where-can-the-documentation-for-python-levenshtein-be-found-online
from pymongo import Mongo... | agpl-3.0 |
suku248/nest-simulator | pynest/examples/spatial/connex_ew.py | 14 | 2269 | # -*- coding: utf-8 -*-
#
# connex_ew.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, or
#... | gpl-2.0 |
capaulson/pyKriging | pyKriging/GlobalSensitivity.py | 1 | 3359 | """
Created on Tue Dec 23 09:18:20 2014
@author: Giorgos
"""
import numpy as np
from matplotlib import pyplot as plt
# at the moment this class is working only for a two dimensional proplem. I will
# improve it very soon to work for more variables.
class SobolSensitivity():
"""
class which calculates the Glo... | mit |
stonebig/bokeh | examples/plotting/file/custom_tooltip.py | 2 | 1888 | import pandas as pd
from bokeh.plotting import figure, show
from bokeh.sampledata.periodic_table import elements
elements = elements.copy()
elements = elements[elements.group != "-"]
elements.sort_values('metal', inplace=True)
colormap = {
"alkali metal" : "#a6cee3",
"alkaline earth metal" : "#1f78b4... | bsd-3-clause |
jjx02230808/project0223 | 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 |
xavierwu/scikit-learn | sklearn/metrics/__init__.py | 214 | 3440 | """
The :mod:`sklearn.metrics` module includes score functions, performance metrics
and pairwise metrics and distance computations.
"""
from .ranking import auc
from .ranking import average_precision_score
from .ranking import coverage_error
from .ranking import label_ranking_average_precision_score
from .ranking imp... | bsd-3-clause |
gomesfelipe/BDA_py_demos | demos_ch5/demo5_2.py | 19 | 3326 | """Bayesian Data Analysis, 3rd ed
Chapter 5, demo 2
Hierarchical model for SAT-example data (BDA3, p. 102)
"""
from __future__ import division
import numpy as np
from scipy.stats import norm
import scipy.io # For importing a matlab file
import matplotlib.pyplot as plt
# Edit default plot settings (colours from colo... | gpl-3.0 |
phobson/mpl-probscale | probscale/transforms.py | 1 | 3801 | import numpy
from matplotlib.transforms import Transform
def _mask_out_of_bounds(a):
"""
Return a Numpy array where all values outside ]0, 1[ are
replaced with NaNs. If all values are inside ]0, 1[, the original
array is returned.
"""
a = numpy.array(a, float)
mask = (a <= 0.0) | (a >= 1.0... | bsd-3-clause |
Monika319/EWEF-1 | Cw2Rezonans/Karolina/Oscyloskop/Fourier moduł i faza/OscyloskopZ5W2Fourier.py | 1 | 1961 | # -*- coding: utf-8 -*-
"""
Plot oscilloscope files from MultiSim
"""
import numpy as np
import matplotlib.pyplot as plt
import sys
import os
from matplotlib import rc
rc('font',family="Consolas")
files=["real_zad5_05f_p2.txt"]
for NazwaPliku in files:
print NazwaPliku
Plik=open(NazwaPliku)
#print DeltaT
... | gpl-2.0 |
loli/semisupervisedforests | benchmarks/bench_sample_without_replacement.py | 397 | 8008 | """
Benchmarks for sampling without replacement of integer.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import operator
import matplotlib.pyplot as plt
import numpy as np
import random
from sklearn.externals.six.moves i... | bsd-3-clause |
zhenv5/scikit-learn | doc/datasets/mldata_fixture.py | 367 | 1183 | """Fixture module to skip the datasets loading when offline
Mock urllib2 access to mldata.org and create a temporary data folder.
"""
from os import makedirs
from os.path import join
import numpy as np
import tempfile
import shutil
from sklearn import datasets
from sklearn.utils.testing import install_mldata_mock
fr... | bsd-3-clause |
olafhauk/mne-python | mne/viz/misc.py | 3 | 48874 | # -*- coding: utf-8 -*-
"""Functions to make simple plots with M/EEG data."""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
# Cathy Nangini... | bsd-3-clause |
jereze/scikit-learn | sklearn/datasets/tests/test_lfw.py | 230 | 7880 | """This test for the LFW require medium-size data dowloading and processing
If the data has not been already downloaded by running the examples,
the tests won't run (skipped).
If the test are run, the first execution will be long (typically a bit
more than a couple of minutes) but as the dataset loader is leveraging
... | bsd-3-clause |
abimannans/scikit-learn | examples/linear_model/plot_iris_logistic.py | 283 | 1678 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic Regression 3-class Classifier
=========================================================
Show below is a logistic-regression classifiers decision boundaries on the
`iris <http://en.wikipedia.org/wiki/Iris_f... | bsd-3-clause |
khadka0/Spotify-Track-Generator | SpotifyPlaylistGenerator.py | 1 | 1203 | # Program to create a playlist out of the words of a message
from nltk import trigrams
from pandas import Series
import spotipy
# Fetch the message and split it into most popular phrases
message = raw_input("Enter text : ")
grams = Series(trigrams(message.split()))
list_of_phrases = []
for phrase in grams:
l... | mit |
rmcgibbo/osprey | osprey/config.py | 1 | 13890 | from __future__ import print_function, absolute_import, division
"""config.py
This module contains the parser and in-memory representation of the config
osprey job file file. The config file has four major sections:
- estimator: the specification for the estimator/model to be fit, an
instance... | apache-2.0 |
thunderhoser/GewitterGefahr | gewittergefahr/dissertation/plot_data_augmentation.py | 1 | 9894 | """Plots data augmentation."""
import argparse
import numpy
import matplotlib
matplotlib.use('agg')
from matplotlib import pyplot
from gewittergefahr.gg_utils import radar_utils
from gewittergefahr.gg_utils import time_conversion
from gewittergefahr.gg_utils import file_system_utils
from gewittergefahr.gg_utils import... | mit |
borismarin/genesis2.4gamma | Scripts/gpython-tools/G3Plot.py | 1 | 21705 | #!/usr/bin/env python
# A prototype of a stand-alone application for plotting the output of
# GENESIS 3 models. This uses a basic wxPython frame to hold a matplotlib
# figure for plotting. It defines some basic menu items, and a control
# panel of buttons and toggles, each with bindings to a function to execute
# on... | gpl-2.0 |
bokeh/bokeh | sphinx/source/docs/user_guide/examples/plotting_band.py | 2 | 1155 | import numpy as np
import pandas as pd
from bokeh.models import Band, ColumnDataSource
from bokeh.plotting import figure, output_file, show
output_file("band.html", title="band.py example")
# Create some random data
x = np.random.random(2500) * 140 - 20
y = np.random.normal(size=2500) * 2 + 5
df = pd.DataFrame(data... | bsd-3-clause |
timzhangau/ml_nano | finding_donors/visuals.py | 11 | 5391 | ###########################################
# Suppress matplotlib user warnings
# Necessary for newer version of matplotlib
import warnings
warnings.filterwarnings("ignore", category = UserWarning, module = "matplotlib")
#
# Display inline matplotlib plots with IPython
from IPython import get_ipython
get_ipython().run_... | mit |
mit0110/activepipe | test_activepipe.py | 1 | 11860 |
import unittest
import numpy as np
import mock
from activepipe import ActivePipeline
from corpus import Corpus
from featureforge.vectorizer import Vectorizer
from scipy.sparse import csr_matrix
from sklearn.preprocessing import normalize
testing_config = {
'features': Vectorizer([lambda x : x]),
'em_adding_i... | mit |
jmargeta/scikit-learn | examples/cluster/plot_cluster_iris.py | 4 | 2573 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
K-means Clustering
=========================================================
The plots display firstly what a K-means algorithm would yield
using three clusters. It is then shown what the effect of a bad
initializa... | bsd-3-clause |
simon-pepin/scikit-learn | sklearn/decomposition/tests/test_truncated_svd.py | 240 | 6055 | """Test truncated SVD transformer."""
import numpy as np
import scipy.sparse as sp
from sklearn.decomposition import TruncatedSVD
from sklearn.utils import check_random_state
from sklearn.utils.testing import (assert_array_almost_equal, assert_equal,
assert_raises, assert_greater,
... | bsd-3-clause |
heli522/scikit-learn | examples/applications/plot_out_of_core_classification.py | 255 | 13919 | """
======================================================
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 |
plissonf/scikit-learn | examples/model_selection/randomized_search.py | 201 | 3214 | """
=========================================================================
Comparing randomized search and grid search for hyperparameter estimation
=========================================================================
Compare randomized search and grid search for optimizing hyperparameters of a
random forest.
... | bsd-3-clause |
fabianp/scikit-learn | benchmarks/bench_plot_incremental_pca.py | 374 | 6430 | """
========================
IncrementalPCA benchmark
========================
Benchmarks for IncrementalPCA
"""
import numpy as np
import gc
from time import time
from collections import defaultdict
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_lfw_people
from sklearn.decomposition import Incre... | bsd-3-clause |
fixbugs/py-fixbugs-tools | test/machlearn/7650.py | 1 | 5032 | #!/usr/bin/env python
#coding=utf8
import numpy as np
#from scipy import linalg
from scipy.sparse.linalg import svds
from scipy import sparse
#import matplotlib.pyplot as plt
# a = np.random.randn(9, 6) + 1.j*np.random.randn(9, 6)
# print a
# U, s, Vh = linalg.svd(a)
# print U.shape, Vh.shape, s.shape
# U, s, Vh =... | gpl-3.0 |
Milias/ModellingSimulation | Shared/python/graphs.py | 1 | 1193 | #!/usr/bin/env python
# -*- coding: utf8 -*-
from numpy import *
import matplotlib.pyplot as plt
import sys
import json
def PlotQuantityVsStep(filename, key, ax, start, kwargs):
try:
f = open(filename, "r")
except Exception as e:
print(e)
return 0.0
data = json.loads(f.read())
f.close()
avg = ... | mit |
nelson-liu/scikit-learn | sklearn/discriminant_analysis.py | 27 | 26804 | """
Linear Discriminant Analysis and Quadratic Discriminant Analysis
"""
# Authors: Clemens Brunner
# Martin Billinger
# Matthieu Perrot
# Mathieu Blondel
# License: BSD 3-Clause
from __future__ import print_function
import warnings
import numpy as np
from scipy import linalg
from .extern... | bsd-3-clause |
epidataio/epidata-community | ipython/test/test_automated_test.py | 1 | 22845 | #
# Copyright (c) 2015-2017 EpiData, Inc.
#
from datetime import datetime, timedelta
from epidata.context import ec
from epidata_common.data_types import Waveform
import numpy
import pandas
from pyspark.sql import Row
from pyspark.sql import Column
import unittest
AutomatedTest = Row(
'company',
'site',
... | apache-2.0 |
nok/sklearn-porter | examples/estimator/regressor/MLPRegressor/js/basics.pct.py | 1 | 1225 | # %% [markdown]
# # sklearn-porter
#
# Repository: [https://github.com/nok/sklearn-porter](https://github.com/nok/sklearn-porter)
#
# ## MLPRegressor
#
# Documentation: [sklearn.neural_network.MLPRegressor](http://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html)
# %%
import sys
sys.p... | mit |
mikebenfield/scikit-learn | sklearn/decomposition/truncated_svd.py | 6 | 8517 | """Truncated SVD for sparse matrices, aka latent semantic analysis (LSA).
"""
# Author: Lars Buitinck
# Olivier Grisel <olivier.grisel@ensta.org>
# Michael Becker <mike@beckerfuffle.com>
# License: 3-clause BSD.
import numpy as np
import scipy.sparse as sp
try:
from scipy.sparse.linalg import svd... | bsd-3-clause |
lin-credible/scikit-learn | sklearn/metrics/tests/test_common.py | 43 | 44042 | from __future__ import division, print_function
from functools import partial
from itertools import product
import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_multilabel_classification
from sklearn.preprocessing import LabelBinarizer, MultiLabelBinarizer
from sklearn.utils.multiclass impo... | bsd-3-clause |
aabadie/scikit-learn | sklearn/linear_model/tests/test_sparse_coordinate_descent.py | 94 | 10801 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_true
from sklearn.utils.t... | bsd-3-clause |
YinongLong/scikit-learn | sklearn/neural_network/rbm.py | 46 | 12291 | """Restricted Boltzmann Machine
"""
# Authors: Yann N. Dauphin <dauphiya@iro.umontreal.ca>
# Vlad Niculae
# Gabriel Synnaeve
# Lars Buitinck
# License: BSD 3 clause
import time
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator
from ..base import TransformerMixi... | bsd-3-clause |
huzq/scikit-learn | sklearn/cluster/tests/test_bicluster.py | 6 | 9508 | """Testing for Spectral Biclustering methods"""
import numpy as np
import pytest
from scipy.sparse import csr_matrix, issparse
from sklearn.model_selection import ParameterGrid
from sklearn.utils._testing import assert_almost_equal
from sklearn.utils._testing import assert_array_equal
from sklearn.utils._testing imp... | bsd-3-clause |
procoder317/scikit-learn | sklearn/linear_model/least_angle.py | 61 | 54324 | """
Least Angle Regression algorithm. See the documentation on the
Generalized Linear Model for a complete discussion.
"""
from __future__ import print_function
# Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux
#
# License: BSD 3 ... | bsd-3-clause |
ningchi/scikit-learn | examples/applications/plot_prediction_latency.py | 234 | 11277 | """
==================
Prediction Latency
==================
This is an example showing the prediction latency of various scikit-learn
estimators.
The goal is to measure the latency one can expect when doing predictions
either in bulk or atomic (i.e. one by one) mode.
The plots represent the distribution of the pred... | bsd-3-clause |
TomAugspurger/pandas | pandas/tests/tseries/offsets/test_yqm_offsets.py | 3 | 50930 | """
Tests for Year, Quarter, and Month-based DateOffset subclasses
"""
from datetime import datetime
import pytest
import pandas as pd
from pandas import Timestamp
from pandas.tseries.offsets import (
BMonthBegin,
BMonthEnd,
BQuarterBegin,
BQuarterEnd,
BYearBegin,
BYearEnd,
MonthBegin,
... | bsd-3-clause |
LohithBlaze/scikit-learn | sklearn/utils/tests/test_extmath.py | 130 | 16270 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis Engemann <d.engemann@fz-juelich.de>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from scipy import linalg
from scipy import stats
from sklearn.utils.testing import assert_eq... | bsd-3-clause |
jlabroquere/SU2 | SU2_PY/SU2/util/filter_adjoint.py | 6 | 16496 | #!/usr/bin/env python
## \file filter_adjoint.py
# \brief Applies various filters to the adjoint surface sensitivities of an airfoil
# \author T. Lukaczyk, F. Palacios
# \version 4.0.1 "Cardinal"
#
# SU2 Lead Developers: Dr. Francisco Palacios (Francisco.D.Palacios@boeing.com).
# Dr. Thomas D.... | lgpl-2.1 |
wallinm1/kaggle-loan-default | clf_selector.py | 1 | 1837 | from sklearn.ensemble import ExtraTreesClassifier, GradientBoostingClassifier
from sklearn.cross_validation import ShuffleSplit
import numpy as np
from sklearn.metrics import f1_score, roc_auc_score
def main():
xtrain=np.load('data/x_train.npy')
ytrain=np.load('data/y_train.npy')
#train-test split
... | mit |
MikhailZherebtsov/russian_twitter_analysis | Analysis/Conversation_polarization.py | 1 | 6179 | import MySQLdb, sys, logging
import pandas as pd
#-------------------------------------------------------
class ConvoMatrix:
'''
This script creates the file 'Polarization_matrices.xlsx' - which is reports
the matrix of polarization by community. The Retweets, the mentions and the
replies are p... | mit |
birlrobotics/HMM | hmm_for_baxter_using_only_success_trials/hmm_model_training.py | 1 | 3082 | #!/usr/bin/env python
import os
import numpy as np
from sklearn.externals import joblib
from sklearn.preprocessing import (
scale,
normalize
)
import util
import ipdb
import copy
from birl_hmm.hmm_training import train_model
def run(model_save_path,
model_type,
model_config,
score_metric,
... | bsd-3-clause |
david-ragazzi/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backend_bases.py | 69 | 69740 | """
Abstract base classes define the primitives that renderers and
graphics contexts must implement to serve as a matplotlib backend
:class:`RendererBase`
An abstract base class to handle drawing/rendering operations.
:class:`FigureCanvasBase`
The abstraction layer that separates the
:class:`matplotlib.fi... | gpl-3.0 |
isithot/isithotrightnow | databackup/populate_daily-all_files.py | 1 | 3533 | '''this script populates databackup/[date]-all.csv type files in the form:
014015,Australia/Darwin,-12.4239,130.8925,32.5,2019-04-10T05:44:00Z,25.3,2019-04-09T21:37:00Z
015590,Australia/Darwin,-23.7951,133.8890,32.8,2019-04-10T05:43:00Z,20.2,2019-04-09T21:24:00Z
066062,Australia/Sydney,-33.8607,151.2050,21.3,2019-04-10... | mit |
fducau/AAE_pytorch | script/viz.py | 1 | 2800 | import matplotlib
import matplotlib.pyplot as plt
from matplotlib import gridspec
import numpy as np
from torch.autograd import Variable
import torch
def get_X_batch(data_loader, params, size=None):
if size is None:
size = data_loader.batch_size
for X, target in data_loader:
break
train_b... | gpl-3.0 |
zhouxiao-coder/Paddle | demo/gan/gan_trainer.py | 13 | 12731 | # Copyright (c) 2016 PaddlePaddle 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 applic... | apache-2.0 |
yanlend/scikit-learn | sklearn/metrics/cluster/bicluster.py | 359 | 2797 | from __future__ import division
import numpy as np
from sklearn.utils.linear_assignment_ import linear_assignment
from sklearn.utils.validation import check_consistent_length, check_array
__all__ = ["consensus_score"]
def _check_rows_and_columns(a, b):
"""Unpacks the row and column arrays and checks their shap... | bsd-3-clause |
kdebrab/pandas | pandas/tests/tslibs/test_period_asfreq.py | 7 | 3951 | # -*- coding: utf-8 -*-
from pandas._libs.tslibs.frequencies import get_freq
from pandas._libs.tslibs.period import period_ordinal, period_asfreq
class TestPeriodFreqConversion(object):
def test_intraday_conversion_factors(self):
assert period_asfreq(1, get_freq('D'), get_freq('H'), False) == 24
... | bsd-3-clause |
QuantSoftware/QuantSoftwareToolkit | Legacy/Legacy/alphaGenerators/Bollingerbands.py | 5 | 5265 | '''
Created on Jul 30, 2010
@author: sjoshi42
@summary: This module generates alpha values based on bollinger bands
'''
import DataAccess
import dircache
import numpy
import alphaDataModel.AlphaDataModel as adm
#import alphaGenerator.AlphaDataModel as adm
from matplotlib.backends.backend_agg import Figure... | bsd-3-clause |
shaunstanislaus/BDA_py_demos | demos_ch3/demo3_6.py | 19 | 2810 | """Bayesian Data Analysis, 3rd ed
Chapter 3, demo 6
Illustrate posterior inference for Bioassay data (BDA3 p. 74-).
Instructions for exercise (3.11 in BDA3)
- Check that the range and spacing of A and B are sensible for the
alternative prior
- Compute the log-posterior in a grid
- Scale the log-posterior by subtra... | gpl-3.0 |
huzq/scikit-learn | sklearn/preprocessing/_label.py | 2 | 29659 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Olivier Grisel <olivier.grisel@ensta.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Joel Nothman <joel.nothman@gmail.com>
# Hamzeh Alsalhi <ha258@cornell.edu>
# Licens... | bsd-3-clause |
aglankit/recommendation_engine | scripts/algos/cf_users_knn.py | 1 | 3203 | import csv
import sys
import numpy as np
from sets import Set
from scipy import spatial
from sklearn.metrics import mean_absolute_error
from sklearn.metrics import mean_squared_error
def getReviewsSet(row):
global max_items
list = Set()
for column in range(0,max_items):
if Utility[row][column] > 0:
lis... | gpl-2.0 |
fredhusser/scikit-learn | sklearn/decomposition/tests/test_pca.py | 199 | 10949 | import numpy as np
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_greater
from sklearn.utils.testing import assert_rai... | bsd-3-clause |
janhui/test_engine | dev/old/shape/overlap-plot.py | 1 | 1307 | # Take collection of circles, see which overlap then plot the shapes with the amended overlaps.
from shapely.geometry import Polygon, Point
from shapely.ops import cascaded_union
from matplotlib import pyplot
from shapely.validation import explain_validity
# definses one polygon square.
plist = [[(0, 0), (0, 2), (2, ... | lgpl-2.1 |
mikebenfield/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 19 | 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 |
russel1237/scikit-learn | sklearn/metrics/classification.py | 95 | 67713 | """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 |
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