repo_name stringlengths 7 92 | path stringlengths 5 149 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 911 693k | license stringclasses 15
values |
|---|---|---|---|---|---|
microhh/microhh | kernel_tuner/statistics.py | 5 | 1185 | import matplotlib.pyplot as pl
import numpy as np
import json
import glob
pl.close('all')
pl.ion()
def get_timings(kernel_name, gridsizes):
dt = np.zeros_like(gridsizes, dtype=float)
for i,gridsize in enumerate(gridsizes):
with open( '{0}_{1:03d}.json'.format(kernel_name, gridsize) ) as f:
... | gpl-3.0 |
altairpearl/scikit-learn | examples/manifold/plot_mds.py | 88 | 2731 | """
=========================
Multi-dimensional scaling
=========================
An illustration of the metric and non-metric MDS on generated noisy data.
The reconstructed points using the metric MDS and non metric MDS are slightly
shifted to avoid overlapping.
"""
# Author: Nelle Varoquaux <nelle.varoquaux@gmail.... | bsd-3-clause |
timpalpant/KaggleTSTextClassification | scripts/plot_feature_label_correlations.py | 1 | 1976 | #!/usr/bin/env python
'''
Compute mutual information between individual features
and labels
'''
import argparse
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from common import *
def opts():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('feat... | gpl-3.0 |
harlowja/networkx | examples/algorithms/blockmodel.py | 32 | 3009 | #!/usr/bin/env python
# encoding: utf-8
"""
Example of creating a block model using the blockmodel function in NX. Data used is the Hartford, CT drug users network:
@article{,
title = {Social Networks of Drug Users in {High-Risk} Sites: Finding the Connections},
volume = {6},
shorttitle = {Social Networks of Drug ... | bsd-3-clause |
MannyGrewal/Manny.CIFAR | Manny.CIFAR/CIFAR/CIFARPlotter.py | 1 | 1321 | import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import pylab
########################################################################
# 2017 - Manny Grewal
# Purpose of this class is to visualise a list of images from the CIFAR dataset
# How many columns to show... | mit |
terkkila/scikit-learn | sklearn/cross_decomposition/cca_.py | 209 | 3150 | from .pls_ import _PLS
__all__ = ['CCA']
class CCA(_PLS):
"""CCA Canonical Correlation Analysis.
CCA inherits from PLS with mode="B" and deflation_mode="canonical".
Read more in the :ref:`User Guide <cross_decomposition>`.
Parameters
----------
n_components : int, (default 2).
numb... | bsd-3-clause |
mailhexu/pyDFTutils | pyDFTutils/vasp/procar_reader.py | 2 | 3569 | #!/usr/bin/env python
from numpy import zeros,inner
import numpy as np
import re
from pyDFTutils.ase_utils import symbol_number
import matplotlib.pyplot as plt
def fix_line(line):
line=re.sub("(\d)-(\d)", r'\1 -\2',line)
return line
class procar_reader():
def __init__(self,fname='PROCAR'):
self.re... | lgpl-3.0 |
alalbiol/trading-with-python | lib/qtpandas.py | 77 | 7937 | '''
Easy integration of DataFrame into pyqt framework
Copyright: Jev Kuznetsov
Licence: BSD
'''
from PyQt4.QtCore import (QAbstractTableModel,Qt,QVariant,QModelIndex,SIGNAL)
from PyQt4.QtGui import (QApplication,QDialog,QVBoxLayout, QHBoxLayout, QTableView, QPushButton,
QWidget,QTabl... | bsd-3-clause |
shiinoandra/wavegano | Program/Wavegano/Wavegano/Wavegano.py | 1 | 21939 | import operation as op
import random
import math
import Helper
import GRDEI
import RDE
import GDE
import Wave
import os
import numpy
import matplotlib.pyplot as plt
numpy.set_printoptions(threshold=numpy.nan)
#def encode(payload_path,cover_path,threshold,segment_size,partition_segment_size,method):
# file_name = c... | mit |
drandykass/fatiando | gallery/gravmag/eqlayer_transform.py | 6 | 3046 | """
Equivalent layer for griding and upward-continuing gravity data
-------------------------------------------------------------------------
The equivalent layer is one of the best methods for griding and upward
continuing gravity data and much more. The trade-off is that performing this
requires an inversion and lat... | bsd-3-clause |
g2p/systems | lib/systems/context.py | 1 | 17949 | # vim: set fileencoding=utf-8 sw=2 ts=2 et :
from __future__ import absolute_import
from __future__ import with_statement
from logging import getLogger
import networkx as NX
import yaml
from systems.collector import Aggregate, CResource
from systems.registry import get_registry
from systems.typesystem import EResour... | gpl-2.0 |
hsiaoyi0504/scikit-learn | sklearn/manifold/t_sne.py | 106 | 20057 | # Author: Alexander Fabisch -- <afabisch@informatik.uni-bremen.de>
# License: BSD 3 clause (C) 2014
# This is the standard t-SNE implementation. There are faster modifications of
# the algorithm:
# * Barnes-Hut-SNE: reduces the complexity of the gradient computation from
# N^2 to N log N (http://arxiv.org/abs/1301.... | bsd-3-clause |
canast02/csci544_fall2016_project | yelp-sentiment/experiments/sentiment_stochasticGradientDescent.py | 1 | 2641 | import numpy as np
from nltk import TweetTokenizer, accuracy
from nltk.stem.snowball import EnglishStemmer
from sklearn import svm, linear_model
from sklearn.cross_validation import StratifiedKFold
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics import accuracy_score
from sklearn.metric... | gpl-3.0 |
Lyleo/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/numerix/__init__.py | 69 | 5473 | """
numerix imports either Numeric or numarray based on various selectors.
0. If the value "--numpy","--numarray" or "--Numeric" is specified on the
command line, then numerix imports the specified
array package.
1. The value of numerix in matplotlibrc: either Numeric or numarray
2. If none of the above is... | gpl-3.0 |
sliwhu/UWHousingTeam | model/house_price_model.py | 1 | 6622 | """
Contains the house price model.
DON'T USE THIS MODEL! Use the HousePriceModel in house_price_model_2.py.
"""
import os
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import RidgeCV
# Constants
BASE_DATE = pd.to_datetime('20140101', format='%Y%... | mit |
renatopp/liac | liac/dataset/__init__.py | 1 | 3050 | # =============================================================================
# Federal University of Rio Grande do Sul (UFRGS)
# Connectionist Artificial Intelligence Laboratory (LIAC)
# Renato de Pontes Pereira - rppereira@inf.ufrgs.br
# =============================================================================
... | mit |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/scipy/signal/spectral.py | 4 | 66089 | """Tools for spectral analysis.
"""
from __future__ import division, print_function, absolute_import
import numpy as np
from scipy import fftpack
from . import signaltools
from .windows import get_window
from ._spectral import _lombscargle
from ._arraytools import const_ext, even_ext, odd_ext, zero_ext
import warning... | gpl-3.0 |
se4u/pylearn2 | pylearn2/sandbox/cuda_convnet/bench.py | 44 | 3589 | __authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"
from pylearn2.testing.skip import skip_if_no_gpu
skip_if_no_gpu()
import numpy as np
from theano.... | bsd-3-clause |
0asa/sparklingpandas | sparklingpandas/test/pandas_groupby_tests.py | 2 | 9480 | """
Test our groupby support based on the pandas groupby tests.
"""
#
# This file is licensed under the Pandas 3 clause BSD license.
#
from tempfile import NamedTemporaryFile
from sparklingpandas.test.sparklingpandastestcase import \
SparklingPandasTestCase
import sys
import pandas as pd
from pandas import date_ra... | apache-2.0 |
boomsbloom/dtm-fmri | DTM/for_gensim/lib/python2.7/site-packages/matplotlib/tests/test_coding_standards.py | 7 | 12216 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from fnmatch import fnmatch
import os
from nose.tools import assert_equal
from nose.plugins.skip import SkipTest
from matplotlib.testing.noseclasses import KnownFailureTest
try:
import pep8
except ImportE... | mit |
tedmeeds/tcga_encoder | tcga_encoder/utils/helpers.py | 1 | 3776 | import tensorflow
import tcga_encoder
import sys, os, yaml
import numpy as np
import scipy as sp
import pylab as pp
import pandas as pd
from sklearn.metrics import roc_auc_score, roc_curve
from sklearn.model_selection import KFold
from collections import *
import itertools
import pdb
def xval_folds( n, K, randomize = F... | mit |
weidel-p/nest-simulator | pynest/nest/tests/test_spatial/test_plotting.py | 12 | 5748 | # -*- coding: utf-8 -*-
#
# test_plotting.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 |
mattilyra/scikit-learn | sklearn/__init__.py | 27 | 3086 | """
Machine learning module for Python
==================================
sklearn is a Python module integrating classical machine
learning algorithms in the tightly-knit world of scientific Python
packages (numpy, scipy, matplotlib).
It aims to provide simple and efficient solutions to learning problems
that are acc... | bsd-3-clause |
samgoodgame/sf_crime | iterations/KK_scripts/transform_test_data.py | 2 | 6405 | # -*- coding: utf-8 -*-
"""
Created on Sun Aug 20 11:25:06 2017
@author: kalvi
"""
#required imports
import pandas as pd
import numpy as np
import csv
import time
import calendar
def get_test_data(test_transformed_path, test_path, earlyWeatherDataPath, weatherData1, weatherData2):
x_data = pd.read_csv(test_tran... | mit |
NelisVerhoef/scikit-learn | examples/cluster/plot_kmeans_digits.py | 230 | 4524 | """
===========================================================
A demo of K-Means clustering on the handwritten digits data
===========================================================
In this example we compare the various initialization strategies for
K-means in terms of runtime and quality of the results.
As the gr... | bsd-3-clause |
justinbois/fish-activity | tests/test_parse.py | 1 | 8083 | import pytest
import numpy as np
import pandas as pd
from pandas.util.testing import assert_frame_equal
import fishact
def test_sniffer():
n_header, delimiter, line = fishact.parse._sniff_file_info(
'tests/single_gtype.txt')
assert n_header == 2
assert deli... | mit |
CVML/scikit-learn | examples/neighbors/plot_approximate_nearest_neighbors_hyperparameters.py | 227 | 5170 | """
=================================================
Hyper-parameters of Approximate Nearest Neighbors
=================================================
This example demonstrates the behaviour of the
accuracy of the nearest neighbor queries of Locality Sensitive Hashing
Forest as the number of candidates and the numb... | bsd-3-clause |
huzq/scikit-learn | examples/cluster/plot_mean_shift.py | 23 | 1775 | """
=============================================
A demo of the mean-shift clustering algorithm
=============================================
Reference:
Dorin Comaniciu and Peter Meer, "Mean Shift: A robust approach toward
feature space analysis". IEEE Transactions on Pattern Analysis and
Machine Intelligence. 2002. ... | bsd-3-clause |
waterponey/scikit-learn | examples/neighbors/plot_lof.py | 30 | 1939 | """
=================================================
Anomaly detection with Local Outlier Factor (LOF)
=================================================
This example presents the Local Outlier Factor (LOF) estimator. The LOF
algorithm is an unsupervised outlier detection method which computes the local
density deviat... | bsd-3-clause |
ryfeus/lambda-packs | LightGBM_sklearn_scipy_numpy/source/scipy/spatial/tests/test__plotutils.py | 15 | 2140 | from __future__ import division, print_function, absolute_import
import pytest
from numpy.testing import assert_, assert_array_equal
from scipy._lib._numpy_compat import suppress_warnings
try:
import matplotlib
matplotlib.rcParams['backend'] = 'Agg'
import matplotlib.pyplot as plt
from matplotlib.coll... | mit |
anntzer/seaborn | seaborn/_core.py | 1 | 44884 | import warnings
import itertools
from copy import copy
from functools import partial
from collections.abc import Iterable, Sequence, Mapping
from numbers import Number
from datetime import datetime
import numpy as np
import pandas as pd
import matplotlib as mpl
from ._decorators import (
share_init_params_with_ma... | bsd-3-clause |
jeffwdoak/free_energies | free_energies/electronicdos.py | 1 | 14960 | #!/usr/bin/python
# electronicdos.py v0.5 5-16-2012 Jeff Doak jeff.w.doak@gmail.com
import numpy as np
from scipy.interpolate import UnivariateSpline
from scipy.integrate import quad
from scipy.optimize import fsolve
import sys, subprocess
BOLTZCONST = 8.617e-5 #eV/K
class ElectronicDOS:
"""
Class to calcula... | mit |
magne-max/zipline-ja | tests/history/generate_csvs.py | 8 | 5432 | #
# Copyright 2015 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 |
xwolf12/scikit-learn | examples/model_selection/grid_search_digits.py | 227 | 2665 | """
============================================================
Parameter estimation using grid search with cross-validation
============================================================
This examples shows how a classifier is optimized by cross-validation,
which is done using the :class:`sklearn.grid_search.GridSearc... | bsd-3-clause |
DouglasLeeTucker/DECam_PGCM | bin/rawdata_se_objects_split.py | 1 | 5996 | #!/usr/bin/env python
"""
rawdata_se_objects_split.py
Example:
rawdata_se_objects_split.py --help
rawdata_se_objects_split.py --inputFileListFile inputfilelist.csv
--outputFileListFile outputfilelist.csv
--verbose 2
"""
###... | gpl-3.0 |
arabenjamin/scikit-learn | sklearn/linear_model/tests/test_sgd.py | 129 | 43401 | import pickle
import unittest
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing ... | bsd-3-clause |
foolcage/fooltrader | fooltrader/spiders/america/sp500_spider.py | 1 | 3418 | # -*- coding: utf-8 -*-
import pandas as pd
import scrapy
from scrapy import Request
from scrapy import Selector
from scrapy import signals
from fooltrader.contract.files_contract import get_kdata_path
from fooltrader.utils.utils import index_df_with_time, to_time_str, to_float
class Sp500Spider(scrapy.Spider):
... | mit |
flennerhag/mlens | mlens/ensemble/tests/test_a_sklearn.py | 1 | 7958 | """
Test Scikit-learn
"""
import numpy as np
from mlens.ensemble import SuperLearner, Subsemble, BlendEnsemble, TemporalEnsemble
from mlens.testing.dummy import return_pickled
try:
from sklearn.utils.estimator_checks import check_estimator
from sklearn.linear_model import Lasso, LinearRegression
from sklear... | mit |
paveldedik/thesis | models/models.py | 1 | 30072 | # -*- coding: utf-8 -*-
"""
Evaluation Models
=================
"""
from __future__ import division
from copy import copy
from itertools import izip
from collections import defaultdict
import numpy as np
import pandas as pd
import tools
__all__ = (
'DummyPriorModel',
'EloModel',
'EloResponseTime',
... | mit |
gotomypc/scikit-learn | examples/linear_model/plot_sgd_iris.py | 286 | 2202 | """
========================================
Plot multi-class SGD on the iris dataset
========================================
Plot decision surface of multi-class SGD on iris dataset.
The hyperplanes corresponding to the three one-versus-all (OVA) classifiers
are represented by the dashed lines.
"""
print(__doc__)
... | bsd-3-clause |
giruenf/GRIPy | app/app_utils.py | 1 | 29345 | import re
import os
import json
import importlib
import timeit
import inspect
import collections
from enum import Enum
from pathlib import Path
import numpy as np
from matplotlib.cm import cmap_d
import wx
import app
import fileio
from classes.om.base.manager import ObjectManager
from app import log
... | apache-2.0 |
DEVELByte/incubator-airflow | airflow/www/views.py | 2 | 91943 | # -*- coding: utf-8 -*-
#
# 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 writing, software
... | apache-2.0 |
woutdenolf/spectrocrunch | spectrocrunch/visualization/tests/test_scene.py | 1 | 2667 | # -*- coding: utf-8 -*-
import unittest
import matplotlib.pyplot as plt
import numpy as np
from .. import scene
from ...patch.pint import ureg
class test_scene(unittest.TestCase):
def test_images(self):
n0, n1 = 5, 10
img = np.arange(n0 * n1).reshape(n0, n1)
unit0 = ureg.mm
uni... | mit |
dato-code/SFrame | oss_src/unity/python/sframe/test/test_sarray.py | 5 | 120681 | # -*- coding: utf-8 -*-
'''
Copyright (C) 2016 Turi
All rights reserved.
This software may be modified and distributed under the terms
of the BSD license. See the LICENSE file for details.
'''
from ..data_structures.sarray import SArray
from ..util.timezone import GMT
from . import util
import binascii
import pandas ... | bsd-3-clause |
paultopia/auto-sklearn | autosklearn/data/competition_data_manager.py | 5 | 16248 | # Functions performing various input/output operations for the ChaLearn AutoML challenge
# Main contributor: Arthur Pesah, August 2014
# Edits: Isabelle Guyon, October 2014
# ALL INFORMATION, SOFTWARE, DOCUMENTATION, AND DATA ARE PROVIDED "AS-IS".
# ISABELLE GUYON, CHALEARN, AND/OR OTHER ORGANIZERS OR CODE AUTHORS DI... | bsd-3-clause |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/pandas/tests/api/test_types.py | 15 | 3674 | # -*- coding: utf-8 -*-
import pytest
from warnings import catch_warnings
import numpy as np
import pandas
from pandas.core import common as com
from pandas.api import types
from pandas.util import testing as tm
from .test_api import Base
class TestTypes(Base):
allowed = ['is_bool', 'is_bool_dtype',
... | mit |
lmallin/coverage_test | python_venv/lib/python2.7/site-packages/pandas/tests/test_common.py | 3 | 4870 | # -*- coding: utf-8 -*-
import pytest
import numpy as np
from pandas import Series, Timestamp
from pandas.compat import range, lmap
import pandas.core.common as com
import pandas.util.testing as tm
def test_mut_exclusive():
msg = "mutually exclusive arguments: '[ab]' and '[ab]'"
with tm.assert_raises_regex... | mit |
adybbroe/atrain_match | atrain_match/reshaped_files_scr/plot_ctth_boxplots_mlvl2_temperature_pressure_height.py | 1 | 16002 | """Read all matched data and make some plotting
"""
import os
import re
from glob import glob
import numpy as np
from matchobject_io import (readCaliopImagerMatchObj,
CalipsoImagerTrackObject)
from plot_kuipers_on_area_util import (PerformancePlottingObject,
... | gpl-3.0 |
afruizc/microsoft_malware_challenge | src/models/first_model/get_conf_matrix.py | 2 | 2842 | """
This is a script that is used to generate a confussion matrix for
a classification method. This uses 10-k cross_validation with in
order to provide sensible resutls and not overfit.
"""
__author__ = "Andres Ruiz"
__license__ = "Apache"
__email__ = "afruizc __thingy__ cs unm edu"
import numpy as np
from sklearn.cr... | apache-2.0 |
carrillo/scikit-learn | sklearn/utils/tests/test_testing.py | 107 | 4210 | import warnings
import unittest
import sys
from nose.tools import assert_raises
from sklearn.utils.testing import (
_assert_less,
_assert_greater,
assert_less_equal,
assert_greater_equal,
assert_warns,
assert_no_warnings,
assert_equal,
set_random_state,
assert_raise_message)
from ... | bsd-3-clause |
hmtai6/universe_NeonRace-v0 | DQN_breakout/DQN.py | 1 | 9601 | import argparse
import logging
import sys
import gc
import cv2
import matplotlib.pyplot as plt
import gym
import universe # register the universe environments
from universe import wrappers
from collections import deque
from skimage.color import rgb2gray
from skimage.transform import resize
import numpy as np
import t... | mit |
trungnt13/scikit-learn | sklearn/tests/test_kernel_ridge.py | 342 | 3027 | 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.testing import assert... | bsd-3-clause |
IamJeffG/geopandas | geopandas/io/tests/test_io.py | 1 | 1794 | from __future__ import absolute_import
import fiona
from geopandas import read_postgis, read_file
from geopandas.tests.util import download_nybb, connect, create_db, \
PANDAS_NEW_SQL_API, unittest, validate_boro_df
class TestIO(unittest.TestCase):
def setUp(self):
nybb_filename, nybb_zip_path = dow... | bsd-3-clause |
libAtoms/matscipy | examples/electrochemistry/pnp_batch/cell_1d/stern_layer_sweep/pnp_plot.py | 2 | 6741 | # positional args
# datadir, figfile, param, param_label
import os.path, re, sys
import numpy as np
from glob import glob
from cycler import cycler
from itertools import cycle
from itertools import groupby
import matplotlib.pyplot as plt
# Ensure variable is defined
try:
datadir
except NameError:
try:
... | gpl-2.0 |
jakobworldpeace/scikit-learn | sklearn/metrics/tests/test_score_objects.py | 33 | 17877 | import pickle
import tempfile
import shutil
import os
import numbers
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_raises_regexp
from sklearn.utils.t... | bsd-3-clause |
vortex-ape/scikit-learn | sklearn/kernel_approximation.py | 4 | 23032 | """
The :mod:`sklearn.kernel_approximation` module implements several
approximate kernel feature maps base on Fourier transforms.
"""
# Author: Andreas Mueller <amueller@ais.uni-bonn.de>
#
# License: BSD 3 clause
import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import svd
from .base im... | bsd-3-clause |
evanthebouncy/nnhmm | uai_network/draw.py | 7 | 2929 | import numpy as np
import matplotlib.pylab as plt
import multiprocessing as mp
from matplotlib import figure
from data import *
FIG = plt.figure()
def draw_coord(coord, name, lab=[1.0, 0.0]):
color = 1.0 if lab[0] > lab[1] else -1.0
ret = np.zeros(shape=[L,L,1])
coord_x, coord_y = coord
coord_x_idx = np.argm... | mit |
droter/trading-with-python | lib/backtest.py | 74 | 7381 | #-------------------------------------------------------------------------------
# Name: backtest
# Purpose: perform routine backtesting tasks.
# This module should be useable as a stand-alone library outide of the TWP package.
#
# Author: Jev Kuznetsov
#
# Created: 03/07/2014
... | bsd-3-clause |
Upward-Spiral-Science/claritycontrol | code/scripts/roi_analysis.py | 1 | 2744 | #!/usr/bin/python
#-*- coding:utf-8 -*-
__author__ = 'david'
from __builtin__ import *
import gc
import numpy as np
from skimage.feature import greycomatrix, greycoprops
import matplotlib as mpl
mpl.use('TkAgg') # Solve runtime issue
import matplotlib.pyplot as plt
## Fake imge and label volumes to fast test funct... | apache-2.0 |
kostajaitachi/shogun | examples/undocumented/python_modular/graphical/regression_lars.py | 26 | 3327 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
from modshogun import RegressionLabels, RealFeatures
from modshogun import LeastAngleRegression, LinearRidgeRegression, LeastSquaresRegression
from modshogun import MeanSquaredError
# we compare LASSO with ordinary least-squares (OLE)
# in the idea... | gpl-3.0 |
kmiernik/Pyspectr | bin/spectrum_fitter.py | 1 | 6663 | #!/usr/bin/env python3
"""
K. Miernik 2013
k.a.miernik@gmail.com
GPL v3
Spectrum fitting code
"""
import argparse
import math
import numpy
import os
import sys
import time
import xml.etree.ElementTree as ET
import matplotlib.pyplot as plt
from lmfit import minimize, Parameters, report_errors
from P... | gpl-3.0 |
SeldonIO/seldon-server | python/seldon/pipeline/sklearn_transform.py | 2 | 1944 | from collections import defaultdict
import pandas as pd
import numpy as np
from sklearn.base import BaseEstimator,TransformerMixin
from seldon.util import DeprecationHelper
class SklearnTransform(BaseEstimator,TransformerMixin):
"""
Allow sklearn transformers to be run on Pandas dataframes.
Parameters
... | apache-2.0 |
mlperf/training_results_v0.6 | NVIDIA/benchmarks/minigo/implementations/tensorflow/minigo/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 |
erp12/pyshgp | pyshgp/gp/evaluation.py | 1 | 7737 | """The :mod:`evaluation` module defines classes to evaluate program CodeBlocks."""
from abc import ABC, abstractmethod
from typing import Sequence, Union, Callable
from collections import defaultdict
import numpy as np
import pandas as pd
from pyshgp.push.interpreter import PushInterpreter, Program
from pyshgp.tap imp... | mit |
madjelan/scikit-learn | sklearn/semi_supervised/label_propagation.py | 128 | 15312 | # 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 |
calatre/epidemics_network | treat/excel_clipper.py | 1 | 1352 | # Universidade de Aveiro - Physics Department
# 2016/2017 Project - Andre Calatre, 73207
# "Simulation of an epidemic" - 28/6/2017
# Selecting Data from an excel file to another
#import numpy as np
import pandas as pd
from openpyxl import load_workbook
#r = [0, 301, 302, 303, 304, 305, 306]
#desired = ['S_Avg', 'I_Av... | apache-2.0 |
piskvorky/gensim | gensim/sklearn_api/atmodel.py | 4 | 10965 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Author: Chinmaya Pancholi <chinmayapancholi13@gmail.com>
# Copyright (C) 2017 Radim Rehurek <radimrehurek@seznam.cz>
# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
"""Scikit learn interface for :class:`~gensim.models.atmodel.AuthorTopicModel... | lgpl-2.1 |
wesleybowman/karsten | project/rawADCPclass.py | 1 | 4107 | from __future__ import division
import numpy as np
import sys
sys.path.append('/home/wesley/github/UTide/')
from utide import ut_solv, ut_reconstr
#from shortest_element_path import shortest_element_path
#import matplotlib.pyplot as plt
#import matplotlib.tri as Tri
#import matplotlib.ticker as ticker
#import seaborn
i... | mit |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/semi_supervised/tests/test_label_propagation.py | 5 | 1998 | """ test the label propagation module """
import numpy as np
from sklearn.utils.testing import assert_equal
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {... | mit |
RPGOne/Skynet | scikit-learn-0.18.1/sklearn/manifold/tests/test_mds.py | 99 | 1873 | import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.manifold import mds
from sklearn.utils.testing import assert_raises
def test_smacof():
# test metric smacof using the data of "Modern Multidimensional Scaling",
# Borg & Groenen, p 154
sim = np.array([[0, 5, 3, 4],
... | bsd-3-clause |
runt18/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/colors.py | 1 | 31702 | """
A module for converting numbers or color arguments to *RGB* or *RGBA*
*RGB* and *RGBA* are sequences of, respectively, 3 or 4 floats in the
range 0-1.
This module includes functions and classes for color specification
conversions, and for mapping numbers to colors in a 1-D array of
colors called a colormap. Color... | agpl-3.0 |
agoose77/hivesystem | manual/movingpanda/panda-11d.py | 1 | 6687 | import dragonfly
import dragonfly.pandahive
import bee
from bee import connect
import math, functools
from panda3d.core import NodePath
import dragonfly.scene.unbound, dragonfly.scene.bound
import dragonfly.std
import dragonfly.io
import dragonfly.canvas
import Spyder
# ## random matrix generator
from random impor... | bsd-2-clause |
smunaut/gnuradio | gr-filter/examples/fir_filter_ccc.py | 6 | 4023 | #!/usr/bin/env python
#
# Copyright 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 option)
# ... | gpl-3.0 |
harisbal/pandas | pandas/core/reshape/merge.py | 2 | 61308 | """
SQL-style merge routines
"""
import copy
import string
import warnings
import numpy as np
from pandas._libs import hashtable as libhashtable, join as libjoin, lib
import pandas.compat as compat
from pandas.compat import filter, lzip, map, range, zip
from pandas.errors import MergeError
from pandas.util._decorato... | bsd-3-clause |
ajm/pulp | explore/management/commands/okapibm25.py | 2 | 2542 | # This file is part of PULP.
#
# PULP 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 later version.
#
# PULP is distributed in the hope that it will ... | gpl-3.0 |
Aasmi/scikit-learn | sklearn/datasets/mldata.py | 309 | 7838 | """Automatically download MLdata datasets."""
# Copyright (c) 2011 Pietro Berkes
# License: BSD 3 clause
import os
from os.path import join, exists
import re
import numbers
try:
# Python 2
from urllib2 import HTTPError
from urllib2 import quote
from urllib2 import urlopen
except ImportError:
# Pyt... | bsd-3-clause |
xzturn/tensorflow | tensorflow/lite/micro/examples/micro_speech/apollo3/compare_1k.py | 9 | 5012 | # Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
djgagne/scikit-learn | examples/linear_model/plot_ols.py | 220 | 1940 | #!/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 |
natasasdj/OpenWPM | analysis/05_images_pixels.py | 2 | 6264 | import os
import sqlite3
import pandas as pd
from matplotlib.colors import LogNorm
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
from statsmodels.distributions.empirical_distribution import ECDF
def thousands(x, pos):
if x>=1e9:
return '%dB' % (x*1e-9)
elif x>=1e6:
... | gpl-3.0 |
semiautomaticgit/SemiAutomaticClassificationPlugin | semiautomaticclassificationplugin.py | 1 | 86616 | # -*- coding: utf-8 -*-
'''
/**************************************************************************************************************************
SemiAutomaticClassificationPlugin
The Semi-Automatic Classification Plugin for QGIS allows for the supervised classification of remote sensing images,
provid... | gpl-3.0 |
ran5515/DeepDecision | tensorflow/examples/learn/text_classification_cnn.py | 29 | 5677 | # 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 |
drammock/mne-python | tutorials/stats-sensor-space/40_cluster_1samp_time_freq.py | 10 | 5666 | """
===============================================================
Non-parametric 1 sample cluster statistic on single trial power
===============================================================
This script shows how to estimate significant clusters
in time-frequency power estimates. It uses a non-parametric
statisti... | bsd-3-clause |
nikhilgahlawat/ThinkStats2 | code/populations.py | 68 | 2609 | """This file contains code used in "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2010 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function
import csv
import logging
import sys
import numpy as np
import pandas
import thinkpl... | gpl-3.0 |
pdamodaran/yellowbrick | tests/rand.py | 1 | 3176 | # tests.random
# A visualizer that draws a random scatter plot for testing.
#
# Author: Benjamin Bengfort <bbengfort@districtdatalabs.com>
# Created: Wed Mar 21 17:51:15 2018 -0400
#
# ID: random.py [] benjamin@bengfort.com $
"""
A visualizer that draws a random scatter plot for testing.
"""
########################... | apache-2.0 |
mortada/tensorflow | tensorflow/examples/learn/boston.py | 33 | 1981 | # 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 |
start-jsk/jsk_apc | jsk_apc2016_common/python/jsk_apc2016_common/rbo_segmentation/evaluate.py | 1 | 7455 | from apc_data import APCDataSet, APCSample
from probabilistic_segmentation import ProbabilisticSegmentationRF, ProbabilisticSegmentationBP
import pickle
import os
import matplotlib.pyplot as plt
import numpy as np
import copy
import rospkg
def _fast_hist(a, b, n):
k = (a >= 0) & (a < n)
hist = np.bincount(n ... | bsd-3-clause |
zaxtax/scikit-learn | sklearn/svm/tests/test_sparse.py | 35 | 13182 | from nose.tools import assert_raises, assert_true, assert_false
import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from sklearn import datasets, svm, linear_model, base
from sklearn.datasets import make_classif... | bsd-3-clause |
licco/zipline | zipline/history/history_container.py | 1 | 18509 | #
# Copyright 2014 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... | apache-2.0 |
JeanKossaifi/scikit-learn | sklearn/preprocessing/tests/test_function_transformer.py | 176 | 2169 | from nose.tools import assert_equal
import numpy as np
from sklearn.preprocessing import FunctionTransformer
def _make_func(args_store, kwargs_store, func=lambda X, *a, **k: X):
def _func(X, *args, **kwargs):
args_store.append(X)
args_store.extend(args)
kwargs_store.update(kwargs)
... | bsd-3-clause |
shashankrajput/seq2seq | seq2seq/tasks/dump_attention.py | 6 | 4850 | # Copyright 2017 Google 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 writing,... | apache-2.0 |
ldirer/scikit-learn | examples/cluster/plot_digits_agglomeration.py | 377 | 1694 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Feature agglomeration
=========================================================
These images how similar features are merged together using
feature agglomeration.
"""
print(__doc__)
# Code source: Gaël Varoquaux
#... | bsd-3-clause |
souljourner/fab | EDA/FOMC.py | 2 | 5156 | from __future__ import print_function
from bs4 import BeautifulSoup
from urllib.request import urlopen
import re
import pandas as pd
import pickle
import threading
import sys
class FOMC (object):
'''
A convenient class for extracting meeting minutes from the FOMC website
Example Usage:
fomc = FOM... | mit |
gmartinvela/Incubator | Incubator/mongo_save.py | 1 | 2777 | from pymongo import MongoClient
import urllib2
import time
import datetime
import json
import sqlite3
import pandas.io.sql as psql
from data_utils import retrieve_DBs, extract_data_from_DB
mongo_client = MongoClient()
mongo_db = mongo_client.incubator
measures_collection = mongo_db.measures
local_path_SHT1xdb = "/ho... | mit |
chrisburr/scikit-learn | sklearn/metrics/ranking.py | 17 | 26927 | """Metrics to assess performance on classification task given scores
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.... | bsd-3-clause |
ZENGXH/scikit-learn | examples/bicluster/plot_spectral_biclustering.py | 403 | 2011 | """
=============================================
A demo of the Spectral Biclustering algorithm
=============================================
This example demonstrates how to generate a checkerboard dataset and
bicluster it using the Spectral Biclustering algorithm.
The data is generated with the ``make_checkerboard`... | bsd-3-clause |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/subplots_axes_and_figures/custom_figure_class.py | 1 | 1517 | """
===================
Custom Figure Class
===================
You can pass a custom Figure constructor to figure if you want to derive from
the default Figure. This simple example creates a figure with a figure title.
"""
import matplotlib.pyplot as plt #import figure, show
from matplotlib.figure import Figure
# n... | mit |
hanteng/babel | scripts/geoname_cldr.py | 1 | 2479 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#歧視無邊，回頭是岸。鍵起鍵落，情真情幻。
# url_target="https://raw.githubusercontent.com/datasets/country-codes/master/data/country-codes.csv"
import csv
import pandas as pd
import codecs
def export_to_csv(df, ex_filename, sep=','):
if sep==',':
df.to_csv(ex_filename, sep=sep, q... | bsd-3-clause |
kdebrab/pandas | pandas/tests/indexes/multi/test_set_ops.py | 2 | 8078 | # -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas import (CategoricalIndex, DatetimeIndex, MultiIndex, PeriodIndex,
Series, TimedeltaIndex)
def test_setops_errorcases(idx):
# # non-iterable input
cases = [0.5, 'xxx']
methods =... | bsd-3-clause |
LiaoPan/scikit-learn | examples/ensemble/plot_gradient_boosting_quantile.py | 392 | 2114 | """
=====================================================
Prediction Intervals for Gradient Boosting Regression
=====================================================
This example shows how quantile regression can be used
to create prediction intervals.
"""
import numpy as np
import matplotlib.pyplot as plt
from skle... | bsd-3-clause |
atantet/ergoPack | example/numericalFP/numericalFP_Hopf.py | 1 | 5115 | import numpy as np
import pylibconfig2
from scipy import sparse
from scipy.sparse import linalg
import matplotlib.pyplot as plt
from matplotlib import cm
from ergoNumAna import ChangCooper
readEigVal = False
#readEigVal = True
def hopf(x, mu, omega):
f = np.empty((2,))
f[0] = x[0] * (mu - (x[0]**2 + x[1]**2))... | gpl-3.0 |
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