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 |
|---|---|---|---|---|---|
hainm/scikit-learn | 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 |
ua-snap/downscale | old/bin/hur_cru_ts31_to_cl20_downscaling.py | 3 | 22421 | # # #
# Current implementation of the cru ts31 (ts32) delta downscaling procedure
#
# Author: Michael Lindgren (malindgren@alaska.edu)
# # #
import numpy as np
def write_gtiff( output_arr, template_meta, output_filename, compress=True ):
'''
DESCRIPTION:
------------
output a GeoTiff given a numpy ndarray, rasterio... | mit |
r-mart/scikit-learn | sklearn/metrics/tests/test_ranking.py | 127 | 40813 | from __future__ import division, print_function
import numpy as np
from itertools import product
import warnings
from scipy.sparse import csr_matrix
from sklearn import datasets
from sklearn import svm
from sklearn import ensemble
from sklearn.datasets import make_multilabel_classification
from sklearn.random_projec... | bsd-3-clause |
cqychen/quants | quants/loaddata/skyeye_ods_invest_refer_sh_margins_detail.py | 1 | 2670 | #coding=utf8
import tushare as ts;
import pymysql;
import time as dt
from datashape.coretypes import string
from pandas.io.sql import SQLDatabase
import sqlalchemy
import datetime
from sqlalchemy import create_engine
from pandas.io import sql
import threading
import pandas as pd;
import sys
sys.path.append('../') #添加配... | epl-1.0 |
jundongl/scikit-feature | skfeature/example/test_JMI.py | 3 | 1482 | import scipy.io
from sklearn.metrics import accuracy_score
from sklearn import cross_validation
from sklearn import svm
from skfeature.function.information_theoretical_based import JMI
def main():
# load data
mat = scipy.io.loadmat('../data/colon.mat')
X = mat['X'] # data
X = X.astype(float)
y ... | gpl-2.0 |
jtwhite79/pyemu | pyemu/utils/gw_utils.py | 1 | 110032 | """MODFLOW support utilities"""
import os
from datetime import datetime
import shutil
import warnings
import numpy as np
import pandas as pd
import re
pd.options.display.max_colwidth = 100
from pyemu.pst.pst_utils import (
SFMT,
IFMT,
FFMT,
pst_config,
parse_tpl_file,
try_process_output_file,
)... | bsd-3-clause |
MadsJensen/agency_connectivity | tf_functions.py | 1 | 5293 | """
Functions for TF analysis.
@author: mje
@email: mads [] cnru.dk
"""
import mne
from mne.time_frequency import (psd_multitaper, tfr_multitaper, tfr_morlet,
cwt_morlet)
from mne.viz import iter_topography
import matplotlib.pyplot as plt
import numpy as np
def calc_psd_epochs(epochs... | bsd-3-clause |
sassoftware/saspy | saspy/sasiocom.py | 1 | 37140 | #
# Copyright SAS Institute
#
# 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 |
ycaihua/scikit-learn | sklearn/decomposition/tests/test_incremental_pca.py | 23 | 8317 | """Tests for Incremental PCA."""
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_raises
from sklearn import datasets
from sklearn.decomposition import PCA, IncrementalPCA
iris = datasets.load... | bsd-3-clause |
yangw1234/BigDL | pyspark/bigdl/optim/optimizer.py | 2 | 40389 | #
# Copyright 2016 The BigDL Authors.
#
# 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 ... | apache-2.0 |
idlead/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 |
kikocorreoso/mplutils | mplutils/axes.py | 1 | 8516 | # -*- coding: utf-8 -*-
"""
Created on Sun Feb 21 23:43:37 2016
@author: kiko
"""
from __future__ import division, absolute_import
from .settings import RICH_DISPLAY
import numpy as np
if RICH_DISPLAY:
from IPython.display import display
def axes_set_better_defaults(ax,
axes_color ... | mit |
abimannans/scikit-learn | sklearn/linear_model/__init__.py | 270 | 3096 | """
The :mod:`sklearn.linear_model` module implements generalized linear models. It
includes Ridge regression, Bayesian Regression, Lasso and Elastic Net
estimators computed with Least Angle Regression and coordinate descent. It also
implements Stochastic Gradient Descent related algorithms.
"""
# See http://scikit-le... | bsd-3-clause |
DiamondLightSource/auto_tomo_calibration-experimental | measure_resolution/lmfit-py/examples/confidence_interval.py | 4 | 2924 | # -*- coding: utf-8 -*-
"""
Created on Sun Apr 15 19:47:45 2012
@author: Tillsten
"""
import numpy as np
from lmfit import Parameters, Minimizer, conf_interval, report_fit, report_ci
from numpy import linspace, zeros, sin, exp, random, sqrt, pi, sign
from scipy.optimize import leastsq
try:
import matplotlib.pypl... | apache-2.0 |
lizardsystem/threedilib | threedilib/modeling/convert.py | 1 | 8275 | # (c) Nelen & Schuurmans. GPL licensed, see LICENSE.rst.
# -*- coding: utf-8 -*-
"""
Convert shapefiles with z coordinates. Choose from the following formats:
'inp' to create an inp file, 'img' to create an image with a plot of the
feature, or 'shp' to output a shapefile with the average height of a
feature stored in ... | gpl-3.0 |
JackKelly/neuralnilm_prototype | scripts/e115.py | 2 | 3654 | from __future__ import print_function, division
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import Net, RealApplianceSource, BLSTMLayer, SubsampleLayer, DimshuffleLayer
from lasagne.nonlinearities import sigmoid, rectify
from lasagne.objectives import c... | mit |
sinhrks/scikit-learn | examples/decomposition/plot_pca_vs_lda.py | 176 | 2027 | """
=======================================================
Comparison of LDA and PCA 2D projection of Iris dataset
=======================================================
The Iris dataset represents 3 kind of Iris flowers (Setosa, Versicolour
and Virginica) with 4 attributes: sepal length, sepal width, petal length
a... | bsd-3-clause |
Pymatteo/QtNMR | build/exe.win32-3.4/scipy/cluster/tests/test_hierarchy.py | 7 | 34863 | #! /usr/bin/env python
#
# Author: Damian Eads
# Date: April 17, 2008
#
# Copyright (C) 2008 Damian Eads
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copy... | gpl-3.0 |
lbishal/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 234 | 12267 | # Authors: Lars Buitinck
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from array import array
from collections import Mapping
from operator import itemgetter
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..ext... | bsd-3-clause |
Universal-Model-Converter/UMC3.0a | data/Python/x86/Lib/site-packages/scipy/misc/common.py | 2 | 14711 | """
Functions which are common and require SciPy Base and Level 1 SciPy
(special, linalg)
"""
from __future__ import division, print_function, absolute_import
from scipy.lib.six.moves import xrange
from numpy import exp, log, asarray, arange, newaxis, hstack, product, array, \
where, zeros, extract... | mit |
kiyoto/statsmodels | statsmodels/sandbox/panel/mixed.py | 31 | 21019 | """
Mixed effects models
Author: Jonathan Taylor
Author: Josef Perktold
License: BSD-3
Notes
------
It's pretty slow if the model is misspecified, in my first example convergence
in loglike is not reached within 2000 iterations. Added stop criteria based
on convergence of parameters instead.
With correctly specifi... | bsd-3-clause |
ElDeveloper/scikit-learn | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 408 | 8061 | import re
import inspect
import textwrap
import pydoc
from .docscrape import NumpyDocString
from .docscrape import FunctionDoc
from .docscrape import ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config=None):
config = {} if config is None else config
self.use_plots... | bsd-3-clause |
Garrett-R/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 |
iismd17/scikit-learn | sklearn/feature_selection/tests/test_chi2.py | 221 | 2398 | """
Tests for chi2, currently the only feature selection function designed
specifically to work with sparse matrices.
"""
import numpy as np
from scipy.sparse import coo_matrix, csr_matrix
import scipy.stats
from sklearn.feature_selection import SelectKBest, chi2
from sklearn.feature_selection.univariate_selection im... | bsd-3-clause |
UNR-AERIAL/scikit-learn | sklearn/cluster/birch.py | 207 | 22706 | # Authors: Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Joel Nothman <joel.nothman@gmail.com>
# License: BSD 3 clause
from __future__ import division
import warnings
import numpy as np
from scipy import sparse
from math import sqrt
fro... | bsd-3-clause |
Titan-C/scikit-learn | examples/cluster/plot_ward_structured_vs_unstructured.py | 1 | 3369 | """
===========================================================
Hierarchical clustering: structured vs unstructured ward
===========================================================
Example builds a swiss roll dataset and runs
hierarchical clustering on their position.
For more information, see :ref:`hierarchical_clus... | bsd-3-clause |
petebachant/PXL | pxl/tests/test_fdiff.py | 1 | 1436 | from __future__ import division, print_function
from .. import fdiff
from ..fdiff import *
import matplotlib.pyplot as plt
import pandas as pd
import os
import numpy as np
from uncertainties import unumpy
plot = False
def test_second_order_diff():
"""Test `second_order_diff`."""
# Create a non-equally space... | gpl-3.0 |
JT5D/scikit-learn | examples/linear_model/lasso_dense_vs_sparse_data.py | 13 | 1862 | """
==============================
Lasso on dense and sparse data
==============================
We show that linear_model.Lasso provides the same results for dense and sparse
data and that in the case of sparse data the speed is improved.
"""
print(__doc__)
from time import time
from scipy import sparse
from scipy ... | bsd-3-clause |
loli/sklearn-ensembletrees | examples/plot_rfe_with_cross_validation.py | 24 | 1384 | """
===================================================
Recursive feature elimination with cross-validation
===================================================
A recursive feature elimination example with automatic tuning of the
number of features selected with cross-validation.
"""
print(__doc__)
from sklearn.svm im... | bsd-3-clause |
jm-begon/scikit-learn | sklearn/cluster/spectral.py | 233 | 18153 | # -*- coding: utf-8 -*-
"""Algorithms for spectral clustering"""
# Author: Gael Varoquaux gael.varoquaux@normalesup.org
# Brian Cheung
# Wei LI <kuantkid@gmail.com>
# License: BSD 3 clause
import warnings
import numpy as np
from ..base import BaseEstimator, ClusterMixin
from ..utils import check_rand... | bsd-3-clause |
edfall/vnpy | vn.datayes/storage.py | 29 | 18623 | import os
import json
import pymongo
import pandas as pd
from datetime import datetime, timedelta
from api import Config, PyApi
from api import BaseDataContainer, History, Bar
from errors import (VNPAST_ConfigError, VNPAST_RequestError,
VNPAST_DataConstructorError, VNPAST_DatabaseError)
class DBConfig(Co... | mit |
tomlof/scikit-learn | examples/manifold/plot_lle_digits.py | 138 | 8594 | """
=============================================================================
Manifold learning on handwritten digits: Locally Linear Embedding, Isomap...
=============================================================================
An illustration of various embeddings on the digits dataset.
The RandomTreesEmbed... | bsd-3-clause |
craigcitro/pydatalab | solutionbox/code_free_ml/test_mltoolbox/test_transform.py | 2 | 8503 | from __future__ import absolute_import
from __future__ import print_function
import json
import os
import pandas as pd
from PIL import Image
import shutil
from six.moves.urllib.request import urlopen
import subprocess
import tempfile
import unittest
import uuid
import tensorflow as tf
from tensorflow.python.lib.io im... | apache-2.0 |
barjacks/pythonrecherche | 07 Selenium, more beautifulsoup/zh_wie_neu.py | 1 | 1387 |
# coding: utf-8
from bs4 import BeautifulSoup
import pandas as pd
import requests
import time
import progressbar
bar = progressbar.ProgressBar()
lst = []
lst_pass = []
for elem,i in zip(range(1697,13000), bar((range(1697,13000)))):
url = "https://www.zueriwieneu.ch/report/" + str(elem)
response = requests.... | mit |
mne-tools/mne-tools.github.io | 0.21/_downloads/33b5e3cff5c172d72c79c6eec192b031/plot_label_from_stc.py | 20 | 4093 | """
=================================================
Generate a functional label from source estimates
=================================================
Threshold source estimates and produce a functional label. The label
is typically the region of interest that contains high values.
Here we compare the average time ... | bsd-3-clause |
glouppe/scikit-learn | sklearn/manifold/isomap.py | 229 | 7169 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
freeman-lab/dask | dask/tests/test_core.py | 7 | 3541 | from dask.utils import raises
from dask.core import (istask, get, get_dependencies, flatten, subs,
preorder_traversal)
def contains(a, b):
"""
>>> contains({'x': 1, 'y': 2}, {'x': 1})
True
>>> contains({'x': 1, 'y': 2}, {'z': 3})
False
"""
return all(a.get(k) == v for k, v in b.it... | bsd-3-clause |
latticelabs/Mitty | mitty/benchmarking/misalignment_plot.py | 1 | 9184 | """Prepare a binned matrix of misalignments and plot it in different ways"""
import click
import pysam
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.path import Path
import matplotlib.patches as patches
from matplotlib.colors import LogNorm
import numpy as np
def we_have_too... | gpl-2.0 |
idf/scipy_util | scipy_util/image/color_kmeans.py | 1 | 2314 | # USAGE
# python color_kmeans.py --image images/jp.png --clusters 3
# Author: Adrian Rosebrock
# Website: www.pyimagesearch.com
# import the necessary packages
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
import numpy as np
import argparse
import cv2
def centroid_histogram(clt):
# grab the... | bsd-3-clause |
robogen/CMS-Mining | RunScripts/es_mainreduce.py | 1 | 20005 | from elasticsearch import Elasticsearch
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib.dates import AutoDateLocator, AutoDateFormatter
import numpy as np
import datetime as dt
import math
import json
with open('sites.json', 'r+') as txt:
sitesArray = json.load(... | mit |
psci2195/espresso-ffans | samples/lb_profile.py | 1 | 2856 | # Copyright (C) 2010-2019 The ESPResSo project
#
# This file is part of ESPResSo.
#
# ESPResSo 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 v... | gpl-3.0 |
adamgreenhall/scikit-learn | examples/linear_model/plot_logistic_path.py | 349 | 1195 | #!/usr/bin/env python
"""
=================================
Path with L1- Logistic Regression
=================================
Computes path on IRIS dataset.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from datetime import datetime
import numpy as np
import... | bsd-3-clause |
pypot/scikit-learn | sklearn/preprocessing/tests/test_label.py | 48 | 18419 | import numpy as np
from scipy.sparse import issparse
from scipy.sparse import coo_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import dok_matrix
from scipy.sparse import lil_matrix
from sklearn.utils.multiclass import type_of_target
from sklearn.utils.testing impor... | bsd-3-clause |
czhengsci/veidt | veidt/utils/data_selection.py | 1 | 4503 | # coding: utf-8
# Copyright (c) Materials Virtual Lab
# Distributed under the terms of the BSD License.
from __future__ import division, print_function, unicode_literals, \
absolute_import
import random
import numpy as np
import pandas as pd
from copy import copy
from pymatgen import Structure
class MonteCarloS... | bsd-3-clause |
to266/hyperspy | hyperspy/drawing/marker.py | 2 | 4900 | # -*- coding: utf-8 -*-
# Copyright 2007-2016 The HyperSpy developers
#
# This file is part of HyperSpy.
#
# HyperSpy 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... | gpl-3.0 |
JohanComparat/pySU | spm/bin_spiders/spiders_last_burst_vs_radius.py | 1 | 5578 | import astropy.cosmology as co
aa=co.Planck15
import astropy.io.fits as fits
import astropy.units as u
from astropy.coordinates import angles
#import AngularSeparation
from astropy import coordinates as coord
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as p
import numpy as n
import os
import sys
... | cc0-1.0 |
ryanpbrewster/SciVis-2015 | examples/sdf_example.py | 1 | 2689 | """
The Example is from http://darksky.slac.stanford.edu/scivis2015/examples.html
"""
from sdfpy import load_sdf
from thingking import loadtxt
prefix = "../data/"
# Load N-body particles from a = 1.0 dataset. Particles have positions with
# units of proper kpc, and velocities with units of km/s.
particles = load_sdf... | mit |
valexandersaulys/prudential_insurance_kaggle | venv/lib/python2.7/site-packages/pandas/__init__.py | 9 | 2140 | # pylint: disable-msg=W0614,W0401,W0611,W0622
__docformat__ = 'restructuredtext'
try:
from pandas import hashtable, tslib, lib
except ImportError as e: # pragma: no cover
module = str(e).lstrip('cannot import name ') # hack but overkill to use re
raise ImportError("C extension: {0} not built. If you wa... | gpl-2.0 |
harisbal/pandas | pandas/tests/arrays/categorical/test_missing.py | 1 | 3078 | # -*- coding: utf-8 -*-
import collections
import numpy as np
import pytest
from pandas.compat import lrange
from pandas.core.dtypes.dtypes import CategoricalDtype
from pandas import Categorical, Index, isna
import pandas.util.testing as tm
class TestCategoricalMissing(object):
def test_na_flags_int_categori... | bsd-3-clause |
justincassidy/scikit-learn | examples/covariance/plot_outlier_detection.py | 235 | 3891 | """
==========================================
Outlier detection with several methods.
==========================================
When the amount of contamination is known, this example illustrates two
different ways of performing :ref:`outlier_detection`:
- based on a robust estimator of covariance, which is assumin... | bsd-3-clause |
b-carter/numpy | numpy/core/tests/test_multiarray.py | 1 | 260744 | from __future__ import division, absolute_import, print_function
import collections
import tempfile
import sys
import shutil
import warnings
import operator
import io
import itertools
import functools
import ctypes
import os
import gc
from contextlib import contextmanager
if sys.version_info[0] >= 3:
import builti... | bsd-3-clause |
nwjs/chromium.src | tools/perf/cli_tools/soundwave/worker_pool.py | 10 | 2508 | # Copyright 2018 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.
"""
Use a pool of workers to concurrently process a sequence of items.
Example usage:
from soundwave import worker_pool
def MyWorker(args):
... | bsd-3-clause |
ndaniels/Ammolite | scripts/figure-generators/smsdIsoCompare.py | 1 | 1534 | import matplotlib.pyplot as plt
from pylab import polyfit, poly1d, show, savefig
import sys
def isNumber( s):
try:
float(s)
return True
except ValueError:
return False
def makeGraph(X,Y, xName, yName, name="NoName"):
fig = plt.figure()
ax = fig.add_subplot(111)
superName = "Comparison of {} and {}".format(... | gpl-2.0 |
waterponey/scikit-learn | sklearn/neighbors/tests/test_kd_tree.py | 159 | 7852 | import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors.kd_tree import (KDTree, NeighborsHeap,
simultaneous_sort, kernel_norm,
nodeheap_sort, DTYPE, ITYPE)
from sklearn.neighbors.dist_metrics import Dista... | bsd-3-clause |
RPGOne/Skynet | scikit-learn-c604ac39ad0e5b066d964df3e8f31ba7ebda1e0e/sklearn/neighbors/tests/test_dist_metrics.py | 48 | 4949 | import itertools
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 nose import SkipTest
def cmp_version(version1, version2):
version1 = tuple(map(int, version1.split('.')[:2]... | bsd-3-clause |
boomsbloom/dtm-fmri | DTM/for_gensim/lib/python2.7/site-packages/pandas/computation/ops.py | 7 | 15881 | """Operator classes for eval.
"""
import operator as op
from functools import partial
from datetime import datetime
import numpy as np
from pandas.types.common import is_list_like, is_scalar
import pandas as pd
from pandas.compat import PY3, string_types, text_type
import pandas.core.common as com
from pandas.format... | mit |
themrmax/scikit-learn | sklearn/manifold/tests/test_t_sne.py | 11 | 25443 | import sys
from sklearn.externals.six.moves import cStringIO as StringIO
import numpy as np
import scipy.sparse as sp
from sklearn.neighbors import BallTree
from sklearn.utils.testing import assert_less_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from skle... | bsd-3-clause |
hirofumi0810/asr_preprocessing | swbd/main.py | 1 | 15071 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""Make dataset for the End-to-End model (Switchboard corpus).
Note that feature extraction depends on transcripts.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from os.path import join, isfile
impor... | mit |
zrhans/pythonanywhere | pyscripts/ply_wrose.py | 1 | 1678 | """
DATA,Chuva,Chuva_min,Chuva_max,VVE,VVE_min,VVE_max,DVE,DVE_min,DVE_max,Temp.,Temp._min,Temp._max,Umidade,Umidade_min,Umidade_max,Rad.,Rad._min,Rad._max,Pres.Atm.,Pres.Atm._min,Pres.Atm._max,Temp.Int.,Temp.Int._min,Temp.Int._max,CH4,CH4_min,CH4_max,HCnM,HCnM_min,HCnM_max,HCT,HCT_min,HCT_max,SO2,SO2_min,SO2_max,O3,O3... | apache-2.0 |
gdementen/PyTables | c-blosc/bench/plot-speeds.py | 11 | 6852 | """Script for plotting the results of the 'suite' benchmark.
Invoke without parameters for usage hints.
:Author: Francesc Alted
:Date: 2010-06-01
"""
import matplotlib as mpl
from pylab import *
KB_ = 1024
MB_ = 1024*KB_
GB_ = 1024*MB_
NCHUNKS = 128 # keep in sync with bench.c
linewidth=2
#markers= ['+', ',', 'o... | bsd-3-clause |
andres-liiver/IAPB13_suvendatud | Kodutoo_16/Kodutoo_16_Andres.py | 1 | 2985 | '''
Kodutoo 16
14.11.2014
Andres Liiver
'''
import time
from matplotlib import pyplot as plt
from Tund16gen import *
def timeFunc(func, *args):
start = time.clock()
func(*args)
return time.clock() - start
def linear_search(lst, num):
for item in lst:
if item == num:
return True
... | mit |
MartinDelzant/scikit-learn | sklearn/linear_model/tests/test_coordinate_descent.py | 114 | 25281 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from sys import version_info
import numpy as np
from scipy import interpolate, sparse
from copy import deepcopy
from sklearn.datasets import load_boston
from sklearn.utils.testing ... | bsd-3-clause |
datapythonista/pandas | pandas/core/arrays/sparse/accessor.py | 2 | 11479 | """Sparse accessor"""
import numpy as np
from pandas.compat._optional import import_optional_dependency
from pandas.core.dtypes.cast import find_common_type
from pandas.core.accessor import (
PandasDelegate,
delegate_names,
)
from pandas.core.arrays.sparse.array import SparseArray
from pandas.core.arrays.sp... | bsd-3-clause |
alanmcruickshank/superset-dev | superset/connectors/druid/models.py | 1 | 45334 | # pylint: disable=invalid-unary-operand-type
from collections import OrderedDict
from copy import deepcopy
from datetime import datetime, timedelta
import json
import logging
from multiprocessing import Pool
from dateutil.parser import parse as dparse
from flask import escape, Markup
from flask_appbuilder import Model... | apache-2.0 |
hunse/vrep-python | dvs-play.py | 1 | 1515 | """
Play DVS events in real time
TODO: deal with looping event times for recordings > 65 s
"""
import numpy as np
import matplotlib.pyplot as plt
import dvs
def close(a, b, atol=1e-8, rtol=1e-5):
return np.abs(a - b) < atol + rtol * b
def imshow(image, ax=None):
ax = plt.gca() if ax is None else ax
ax.i... | gpl-2.0 |
Barmaley-exe/scikit-learn | sklearn/metrics/cluster/tests/test_bicluster.py | 394 | 1770 | """Testing for bicluster metrics module"""
import numpy as np
from sklearn.utils.testing import assert_equal, assert_almost_equal
from sklearn.metrics.cluster.bicluster import _jaccard
from sklearn.metrics import consensus_score
def test_jaccard():
a1 = np.array([True, True, False, False])
a2 = np.array([T... | bsd-3-clause |
Srisai85/scikit-learn | examples/covariance/plot_sparse_cov.py | 300 | 5078 | """
======================================
Sparse inverse covariance estimation
======================================
Using the GraphLasso estimator to learn a covariance and sparse precision
from a small number of samples.
To estimate a probabilistic model (e.g. a Gaussian model), estimating the
precision matrix, t... | bsd-3-clause |
joshbohde/scikit-learn | examples/plot_roc_crossval.py | 2 | 2019 | """
=============================================================
Receiver operating characteristic (ROC) with cross validation
=============================================================
Example of Receiver operating characteristic (ROC) metric to
evaluate the quality of the output of a classifier using
cross-valid... | bsd-3-clause |
Griger/Intel-CervicalCancer-KaggleCompetition | featureHOG.py | 1 | 1456 | from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
import numpy as np
from math import pi
from keras.preprocessing.image import ImageDataGenerator
import cv2
from sklearn.cluster import KMeans
import sklearn.preprocessing as prepro
# Generamos nuevos ejemplos
'''
... | gpl-3.0 |
WladimirSidorenko/SentiLex | scripts/vo.py | 1 | 10974 | #!/usr/bin/env python2.7
# -*- mode: python; coding: utf-8; -*-
"""Module for generating lexicon using Velikovich's method (2010).
"""
##################################################################
# Imports
from __future__ import unicode_literals, print_function
from collections import Counter
from copy import... | mit |
belkinsky/SFXbot | src/pyAudioAnalysis/audioTrainTest.py | 1 | 46228 | import sys
import numpy
import time
import os
import glob
import pickle
import shutil
import audioop
import signal
import csv
import ntpath
from . import audioFeatureExtraction as aF
from . import audioBasicIO
from matplotlib.mlab import find
import matplotlib.pyplot as plt
import scipy.io as sIO
from scipy import lina... | mit |
cmbclh/vnpy1.7 | vnpy/trader/app/login/uiLoginWidget.py | 1 | 7055 | # encoding: UTF-8
'''
登陆模块相关的GUI控制组件
'''
import sys
sys.path.append('../')
#sys.path.append('D:\\tr\\vnpy-master\\vn.trader\\DAO')
sys.path.append('D:\\tr\\vnpy-1.7\\vnpy\\DAO')
sys.path.append('D:\\tr\\vnpy-1.7\\vnpy\\common')
import vnpy.DAO
import vnpy.common
from vnpy.DAO import *
import pandas as pd
import Tki... | mit |
Texju/DIT-Machine_Learning | Codes/validation.py | 1 | 1983 | # -*- coding: utf-8 -*-
"""
Created on Wed May 24 15:00:15 2017
@author: Julien Couillard & Jean Thevenet
"""
from sklearn import cross_validation
from sklearn import metrics
import numpy
class MLValidation:
"""This class calculates the preciseness of our tree against a set of data"""
def __init__(self, ... | gpl-3.0 |
SU-ECE-17-7/hotspotter | _graveyard/voting_rules1.py | 2 | 20685 |
#_________________
# OLD
def build_voters_profile(hs, qcx, K):
'''This is too similar to assign_matches_vsmany right now'''
cx2_nx = hs.tables.cx2_nx
hs.ensure_matcher(match_type='vsmany', K=K)
K += 1
cx2_desc = hs.feats.cx2_desc
cx2_kpts = hs.feats.cx2_kpts
cx2_rchip_size = hs.get_cx2_rch... | apache-2.0 |
wxiang7/airflow | airflow/hooks/dbapi_hook.py | 3 | 7095 |
from builtins import str
from past.builtins import basestring
from datetime import datetime
import numpy
import logging
from airflow.hooks.base_hook import BaseHook
from airflow.exceptions import AirflowException
class DbApiHook(BaseHook):
"""
Abstract base class for sql hooks.
"""
# Override to pro... | apache-2.0 |
lenovor/scikit-learn | sklearn/tests/test_qda.py | 155 | 3481 | import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import ignore_war... | bsd-3-clause |
beepee14/scikit-learn | sklearn/linear_model/__init__.py | 270 | 3096 | """
The :mod:`sklearn.linear_model` module implements generalized linear models. It
includes Ridge regression, Bayesian Regression, Lasso and Elastic Net
estimators computed with Least Angle Regression and coordinate descent. It also
implements Stochastic Gradient Descent related algorithms.
"""
# See http://scikit-le... | bsd-3-clause |
arcyfelix/ML-DL-AI | Supervised Learning/GANs/GAN.py | 1 | 3364 | # -*- coding: utf-8 -*-
""" GAN Example
Use a generative adversarial network (GAN) to generate digit images from a
noise distribution.
References:
- Generative adversarial nets. I Goodfellow, J Pouget-Abadie, M Mirza,
B Xu, D Warde-Farley, S Ozair, Y. Bengio. Advances in neural information
processing system... | apache-2.0 |
cauchycui/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 |
ssaeger/scikit-learn | sklearn/feature_selection/tests/test_base.py | 143 | 3670 | import numpy as np
from scipy import sparse as sp
from nose.tools import assert_raises, assert_equal
from numpy.testing import assert_array_equal
from sklearn.base import BaseEstimator
from sklearn.feature_selection.base import SelectorMixin
from sklearn.utils import check_array
class StepSelector(SelectorMixin, Ba... | bsd-3-clause |
Daniel-Brosnan-Blazquez/DIT-100 | debugging/trajectory_planning_profiles/trapezoidal-profile.py | 1 | 7690 | import numpy
import time
from matplotlib import pyplot
def main (params):
angle = params['p0']
vel = params['v0']
sign = params['sign']
# Plan the trajectory if it is not planned
T = 0
Ta = 0
Td = 0 ... | gpl-3.0 |
samuel1208/scikit-learn | sklearn/tests/test_pipeline.py | 162 | 14875 | """
Test the pipeline module.
"""
import numpy as np
from scipy import sparse
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_raises, assert_raises_regex, assert_raise_message
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_false
from sklearn... | bsd-3-clause |
rigetticomputing/grove | grove/tomography/state_tomography.py | 1 | 11664 | ##############################################################################
# Copyright 2017-2018 Rigetti Computing
#
# 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... | apache-2.0 |
kevin-intel/scikit-learn | sklearn/datasets/_openml.py | 2 | 34451 | import gzip
import json
import os
import shutil
import hashlib
from os.path import join
from warnings import warn
from contextlib import closing
from functools import wraps
from typing import Callable, Optional, Dict, Tuple, List, Any, Union
import itertools
from collections.abc import Generator
from collections import... | bsd-3-clause |
RachitKansal/scikit-learn | sklearn/neighbors/tests/test_approximate.py | 71 | 18815 | """
Testing for the approximate neighbor search using
Locality Sensitive Hashing Forest module
(sklearn.neighbors.LSHForest).
"""
# Author: Maheshakya Wijewardena, Joel Nothman
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
kaiserroll14/301finalproject | main/pandas/sparse/panel.py | 9 | 18717 | """
Data structures for sparse float data. Life is made simpler by dealing only
with float64 data
"""
# pylint: disable=E1101,E1103,W0231
import warnings
from pandas.compat import range, lrange, zip
from pandas import compat
import numpy as np
from pandas.core.index import Index, MultiIndex, _ensure_index
from panda... | gpl-3.0 |
duonys/deep-learning-chainer | dlchainer/SdA.py | 1 | 5225 | #-*- coding: utf-8 -*-
from abc import ABCMeta, abstractmethod
import copy
import numpy as np
from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin
from sklearn.externals.six import with_metaclass
from chainer import Variable, FunctionSet, optimizers, cuda
import chainer.functions as F
from .dA impor... | mit |
robbymeals/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 114 | 11393 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from scipy.spatial import distance
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing im... | bsd-3-clause |
EclipseXuLu/DataHouse | DataHouse/crawler/university_spider.py | 1 | 3941 | import requests
from bs4 import BeautifulSoup
from lxml import etree
import pandas as pd
from io import StringIO, BytesIO
university_list = []
class University():
def __init__(self, name='', is_985=False, is_211=False, has_institute=False, location='', orgnization='',
education_level='', educat... | mit |
reinaldomaslim/Singaboat_RobotX2016 | robotx_nav/nodes/task2_toplevel_try.py | 3 | 4644 | #!/usr/bin/env python
import multiprocessing as mp
import rospy
from visualization_msgs.msg import MarkerArray, Marker
from geometry_msgs.msg import Point, Quaternion
import numpy as np
from sklearn.cluster import KMeans, DBSCAN
from sklearn import svm
from move_base_loiter import Loiter
from move_base_waypoint import ... | gpl-3.0 |
natsheh/semantic_query | api.py | 1 | 4747 | # -*- coding: utf-8 -*-
#
# This file is part of semantic_query.
# Copyright (C) 2016 CIAPPLE.
#
# This is a free software; you can redistribute it and/or modify it
# under the terms of the Revised BSD License; see LICENSE file for
# more details.
# Semantic Query API
# Author: Hussein AL-NATSHEH <h.natsheh@ciapple.c... | bsd-3-clause |
giorgiop/scikit-learn | examples/linear_model/plot_sgd_loss_functions.py | 73 | 1232 | """
==========================
SGD: convex loss functions
==========================
A plot that compares the various convex loss functions supported by
:class:`sklearn.linear_model.SGDClassifier` .
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def modified_huber_loss(y_true, y_pred):
z ... | bsd-3-clause |
trungnt13/scikit-learn | sklearn/datasets/lfw.py | 38 | 19042 | """Loader for the Labeled Faces in the Wild (LFW) dataset
This dataset is a collection of JPEG pictures of famous people collected
over the internet, all details are available on the official website:
http://vis-www.cs.umass.edu/lfw/
Each picture is centered on a single face. The typical task is called
Face Veri... | bsd-3-clause |
fmfn/UnbalancedDataset | examples/applications/plot_outlier_rejections.py | 2 | 4354 | """
===============================================================
Customized sampler to implement an outlier rejections estimator
===============================================================
This example illustrates the use of a custom sampler to implement an outlier
rejections estimator. It can be used easily wi... | mit |
Nyker510/scikit-learn | sklearn/decomposition/tests/test_incremental_pca.py | 297 | 8265 | """Tests for Incremental PCA."""
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_raises
from sklearn import datasets
from sklearn.decomposition import PCA, IncrementalPCA
iris = datasets.load... | bsd-3-clause |
nmih/ssbio | ssbio/databases/pdb.py | 1 | 34959 | """
PDBProp
=======
"""
import gzip
import json
import logging
import os.path as op
import mmtf
import os
from cobra.core import DictList
import pandas as pd
import requests
import deprecation
from Bio.PDB import PDBList
from lxml import etree
from six.moves.urllib_error import URLError
from six.moves.urllib.request i... | mit |
weidel-p/nest-simulator | pynest/examples/pulsepacket.py | 12 | 11358 | # -*- coding: utf-8 -*-
#
# pulsepacket.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 |
Lyleo/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_fltkagg.py | 69 | 20839 | """
A backend for FLTK
Copyright: Gregory Lielens, Free Field Technologies SA and
John D. Hunter 2004
This code is released under the matplotlib license
"""
from __future__ import division
import os, sys, math
import fltk as Fltk
from backend_agg import FigureCanvasAgg
import os.path
import matplotli... | gpl-3.0 |
BhallaLab/moose-full | moose-examples/snippets/switchKineticSolvers.py | 2 | 5089 | #########################################################################
## 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 |
zhenv5/scikit-learn | sklearn/neighbors/approximate.py | 71 | 22357 | """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 |
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