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 |
|---|---|---|---|---|---|
Pragmatismo/Pigrow | scripts/gui/graph_modules/graph_thresholds_pie.py | 1 | 4158 |
#
def read_graph_options():
'''
Returns a dictionary of settings and their default values for use by the remote gui
'''
graph_module_settings_dict = {
"title_text":"",
"include_daterange_in_title":"true"
}
return graph_module_settings_dict
def make_graph(li... | gpl-3.0 |
odo22/GV-simulation | adult13.py | 1 | 5869 | from __future__ import division, print_function, absolute_import
from tmm_core import (inc_tmm, unpolarized_RT, ellips,
position_resolved, find_in_structure_with_inf)
from numpy import pi, linspace, inf, array
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
import... | mit |
marionleborgne/nupic.research | htmresearch/support/generate_sdr_dataset.py | 6 | 15022 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# 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 ... | agpl-3.0 |
HBPNeurorobotics/nest-simulator | topology/pynest/tests/test_plotting.py | 10 | 4117 | # -*- 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 |
stylianos-kampakis/scikit-learn | examples/cluster/plot_mini_batch_kmeans.py | 265 | 4081 | """
====================================================================
Comparison of the K-Means and MiniBatchKMeans clustering algorithms
====================================================================
We want to compare the performance of the MiniBatchKMeans and KMeans:
the MiniBatchKMeans is faster, but give... | bsd-3-clause |
BlueBrain/NEST | pynest/examples/twoneurons.py | 8 | 1209 | # -*- coding: utf-8 -*-
#
# twoneurons.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 |
bjsmith/motivation-simulation | SetupAASaltRatModel.py | 1 | 2882 | __author__ = 'benjaminsmith'
import numpy as np
import time
import os
import matplotlib.pyplot as plt #we might do some other tool later.
from ActionModel import ActionModel
import sys
from BisbasModel import BisbasModel
from UnitModel import *
from scipy.stats import norm
#i_pleasant_taste = 0
i_salt = 0
# i_food = ... | gpl-3.0 |
MechCoder/scikit-learn | sklearn/svm/classes.py | 5 | 42736 | import warnings
import numpy as np
from .base import _fit_liblinear, BaseSVC, BaseLibSVM
from ..base import BaseEstimator, RegressorMixin
from ..linear_model.base import LinearClassifierMixin, SparseCoefMixin, \
LinearModel
from ..utils import check_X_y
from ..utils.validation import _num_samples
from ..utils.mult... | bsd-3-clause |
ian-r-rose/SHTOOLS | examples/python/TestLegendre/TestLegendre.py | 2 | 4707 | #!/usr/bin/env python
"""
This script tests and plots all Geodesy normalized Legendre functions.
Parameters can be changed in the main function.
"""
# standard imports:
import os
import sys
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
# import shtools:
sys.path.append(os.path.join(os.pa... | bsd-3-clause |
JohnGriffiths/dipy | doc/examples/piesno.py | 11 | 3970 | """
=============================
Noise estimation using PIESNO
=============================
Often, one is interested in estimating the noise in the diffusion signal. One
of the methods to do this is the Probabilistic Identification and Estimation of
Noise (PIESNO) framework [Koay2009]_. Using this method, one can de... | bsd-3-clause |
elkingtonmcb/scikit-learn | sklearn/externals/joblib/parallel.py | 79 | 35628 | """
Helpers for embarrassingly parallel code.
"""
# Author: Gael Varoquaux < gael dot varoquaux at normalesup dot org >
# Copyright: 2010, Gael Varoquaux
# License: BSD 3 clause
from __future__ import division
import os
import sys
import gc
import warnings
from math import sqrt
import functools
import time
import thr... | bsd-3-clause |
dialounke/pylayers | pylayers/gis/selectl.py | 1 | 41748 | # -*- coding: utf-8 -*-
r"""
.. currentmodule:: pylayers.gis.selectl
.. autosummary::
"""
import os
import pdb
from PIL import Image
import numpy as np
from pylayers.util import geomutil as geu
from pylayers.util import pyutil as pyu
import pylayers.util.plotutil as plu
import matplotlib.pyplot as plt
from pylayers... | mit |
jbrundle/earthquake-forecasts | plot_ANSS_seismicity.py | 1 | 1331 | #!/opt/local/bin python
##############################################################################
# Code plots earthquake data for magnitude vs. time
# Usage: python plot_ANSS_seismicity.py NELat NELng SWLat SWLng MagLo
#
# Where: Latitude in degrees
# Longitude in... | mit |
davharris/leafpuppy | convolve.py | 1 | 1028 | from __future__ import print_function
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
from scipy import ndimage as nd
from skimage import data
from skimage.util import img_as_float
from skimage.filter import gabor_kernel
from skimage.feature import hog
from skimage import data, color, exposure
... | bsd-3-clause |
CheMcCandless/hyperopt-sklearn | hpsklearn/tests/test_estimator.py | 4 | 1604 |
try:
import unittest2 as unittest
except:
import unittest
import numpy as np
from hpsklearn.estimator import hyperopt_estimator
from hpsklearn import components
class TestIter(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.X = np.random.randn(1000, 2)
self.Y = (sel... | bsd-3-clause |
PatrickChrist/scikit-learn | examples/svm/plot_iris.py | 225 | 3252 | """
==================================================
Plot different SVM classifiers in the iris dataset
==================================================
Comparison of different linear SVM classifiers on a 2D projection of the iris
dataset. We only consider the first 2 features of this dataset:
- Sepal length
- Se... | bsd-3-clause |
INGEOTEC/microTC | microtc/textmodel.py | 1 | 18021 | # Copyright 2016-2017 Eric S. Tellez
# 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 writ... | apache-2.0 |
architecture-building-systems/CEAforArcGIS | cea/technologies/solar/photovoltaic_thermal.py | 2 | 42510 | """
Photovoltaic thermal panels
"""
import os
import time
from itertools import repeat
from math import *
import geopandas as gpd
import numpy as np
import pandas as pd
from geopandas import GeoDataFrame as gdf
from numba import jit
import cea.inputlocator
import cea.utilities.parallel
import cea.utilities.worke... | mit |
satra/NiPypeold | nipype/algorithms/rapidart.py | 1 | 22474 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
The rapidart module provides routines for artifact detection and region of
interest analysis.
These functions include:
* ArtifactDetect: performs artifact detection on functional images
* Sti... | bsd-3-clause |
zorojean/scikit-learn | sklearn/decomposition/pca.py | 192 | 23117 | """ Principal Component Analysis
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Michael Eickenberg <michael.eickenberg@inria.fr>
#
# Lice... | bsd-3-clause |
ychaim/bbg | bbg/bbg.py | 1 | 33953 | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 04 17:44:27 2014
@author: Brian Jacobowski <bjacobowski.dev@gmail.com>
"""
import time
import collections
import blpapi as bb
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
from optparse import OptionParser
fro... | bsd-3-clause |
DSLituiev/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 |
RomainBrault/OVFM | Dream3/dream3.py | 1 | 7167 | import scipy.io
import numpy as np
from sklearn import ensemble
from sklearn import cross_validation
from sklearn import metrics
from sklearn import preprocessing
from sklearn import linear_model
import OVFM.Model as md
import OVFM.FeatureMap as fm
import OVFM.Risk as rsk
import OVFM.LearningRate as lr
import OVFM.Dat... | mit |
WafaaT/spark-tk | regression-tests/sparktkregtests/testcases/dicom/create_dicom_test.py | 12 | 3719 | # vim: set encoding=utf-8
# Copyright (c) 2016 Intel Corporation
#
# 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 require... | apache-2.0 |
yavalvas/yav_com | build/matplotlib/examples/pylab_examples/quadmesh_demo.py | 14 | 1111 | #!/usr/bin/env python
"""
pcolormesh uses a QuadMesh, a faster generalization of pcolor, but
with some restrictions.
This demo illustrates a bug in quadmesh with masked data.
"""
import numpy as np
from matplotlib.pyplot import figure, show, savefig
from matplotlib import cm, colors
from numpy import ma
n = 12
x = n... | mit |
alexalemi/cancersim | code/cancer_old.py | 1 | 35053 | #Cancer Sim
from numpy import *
import scipy as sp
import pylab as py
import math
import matplotlib.cm as cm
import matplotlib.colors as colors
import cPickle as pickle
from scipy.spatial.distance import euclidean
from math import pow
from scipy.spatial import Delaunay
#from scipy.spatial import KDTree
from scipy... | mit |
thorwhalen/ut | ml/regression/recursive_regression.py | 1 | 1171 |
from sklearn.base import RegressorMixin, TransformerMixin
from sklearn.linear_model import LinearRegression
from numpy import zeros, vstack
class RecursiveRegressionTransformer(RegressorMixin, TransformerMixin):
def __init__(self, model_class=LinearRegression, n_cycles=2, **model_kwargs):
self.model_cla... | mit |
michigraber/scikit-learn | examples/linear_model/plot_ransac.py | 250 | 1673 | """
===========================================
Robust linear model estimation using RANSAC
===========================================
In this example we see how to robustly fit a linear model to faulty data using
the RANSAC algorithm.
"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import ... | bsd-3-clause |
DonBeo/scikit-learn | sklearn/metrics/scorer.py | 11 | 12934 | """
The :mod:`sklearn.metrics.scorer` submodule implements a flexible
interface for model selection and evaluation using
arbitrary score functions.
A scorer object is a callable that can be passed to
:class:`sklearn.grid_search.GridSearchCV` or
:func:`sklearn.cross_validation.cross_val_score` as the ``scoring`` parame... | bsd-3-clause |
wazeerzulfikar/scikit-learn | sklearn/tests/test_metaestimators.py | 30 | 5040 | """Common tests for metaestimators"""
import functools
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.externals.six import iterkeys
from sklearn.datasets import make_classification
from sklearn.utils.testing import assert_true, assert_false, assert_raises
from sklearn.utils.validation import... | bsd-3-clause |
miltondp/ukbrest | tests/test_postloader.py | 1 | 38352 | import os
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
from tests.settings import POSTGRESQL_ENGINE
from tests.utils import get_repository_path, DBTest
from ukbrest.common.pheno2sql import Pheno2SQL
from ukbrest.common.postloader import Postloader
class PostloaderTest(DBTest):
def... | gpl-3.0 |
hyperspy/hyperspy | hyperspy/conftest.py | 2 | 2514 | # -*- coding: utf-8 -*-
# Copyright 2007-2021 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 |
AdamRTomkins/libSpineML2NK | libSpineML2NK/examples/Narx/Narx_Gain/python/validate_model.py | 2 | 5585 | # run and validate model
from Simulator_twoGains import *
from matplotlib import pyplot as plt
import h5py
import numpy as np
from scipy import io
Params = scipy.io.loadmat("intpoint_mutant2.mat")
SortedPar = sortGainParams(Params,'x_mutant2')
SortedPar['Mean_beta_3'] = 2000
SortedPar['Gralbeta_G'] = 1000
model... | gpl-3.0 |
nrego/westpa | lib/examples/stringmethodexamples/examples/DicksonPeriodicPotential/generate_figures/voronoi.py | 1 | 2391 | #!/usr/bin/env python
# -----------------------------------------------------------------------------
# Voronoi diagram from a list of points
# Copyright (C) 2011 Nicolas P. Rougier
#
# Distributed under the terms of the BSD License.
# -----------------------------------------------------------------------------
impor... | gpl-3.0 |
xray/xray | xarray/core/nputils.py | 1 | 9531 | import warnings
import numpy as np
import pandas as pd
from numpy.core.multiarray import normalize_axis_index
try:
import bottleneck as bn
_USE_BOTTLENECK = True
except ImportError:
# use numpy methods instead
bn = np
_USE_BOTTLENECK = False
def _select_along_axis(values, idx, axis):
other_... | apache-2.0 |
KellyChan/Python | python/tensorflow/demos/tensorflow/concepts/placeholder.py | 3 | 1451 | import tensorflow as tf
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
class MarshOrchid(object):
def __init__(self, filename):
self.image = mpimg.imread(filename)
def placeholder1(self):
x = tf.placeholder("float", 3)
y = x * 2
with tf.Session() as sessio... | mit |
tmhm/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 |
0asa/scikit-learn | sklearn/covariance/robust_covariance.py | 17 | 28933 | """
Robust location and covariance estimators.
Here are implemented estimators that are resistant to outliers.
"""
# Author: Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import warnings
import numbers
import numpy as np
from scipy import linalg
from scipy.stats import chi2
from . import empir... | bsd-3-clause |
hughdbrown/QSTK-nohist | src/quicksim/strategies/OneStock.py | 1 | 1994 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on Jan 1, 2011
@author:Drew Bratcher
@contact: dbratcher@gatech.edu
@summary: Contains tutorial for... | bsd-3-clause |
zorroblue/scikit-learn | sklearn/tests/test_isotonic.py | 31 | 15103 | import warnings
import numpy as np
import pickle
import copy
from sklearn.isotonic import (check_increasing, isotonic_regression,
IsotonicRegression)
from sklearn.utils.testing import (assert_raises, assert_array_equal,
assert_true, assert_false, assert... | bsd-3-clause |
ztytiao/t4_indudstry_classify | bin/nlpClassify.py | 1 | 12322 | import jieba
import pandas as pd
import random
import numpy as np
from sklearn import feature_extraction
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.naive_bayes import Mu... | mit |
jreback/pandas | pandas/tests/util/test_show_versions.py | 3 | 1241 | import re
import pytest
import pandas as pd
@pytest.mark.filterwarnings(
# openpyxl
"ignore:defusedxml.lxml is no longer supported:DeprecationWarning"
)
@pytest.mark.filterwarnings(
# html5lib
"ignore:Using or importing the ABCs from:DeprecationWarning"
)
@pytest.mark.filterwarnings(
# fastparqu... | bsd-3-clause |
Caranarq/01_Dmine | Datasets/MV02/MV02.py | 1 | 4403 | # -*- coding: utf-8 -*-
"""
Created on Thu Sep 28 13:34:56 2017
@author: carlos.arana
Descripcion: Mineria de datos de accidentes vehiculares.
"""
# Librerias Utilizadas
import os
import pandas as pd
import datetime
import urllib
import zipfile
from simpledbf import Dbf5
# Ubicacion y descripcion de la fuente
fuen... | gpl-3.0 |
yunque/sms-tools | lectures/08-Sound-transformations/plots-code/hps-morph.py | 24 | 2691 | # function for doing a morph between two sounds using the hpsModel
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import get_window
import sys, os
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../models/'))
sys.path.append(os.path.join(os.path.dirname(os.path.re... | agpl-3.0 |
luispedro/BuildingMachineLearningSystemsWithPython | ch04/build_lda.py | 22 | 2443 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
from __future__ import print_function
try:
import nltk.corpus
except ImportError:
print("nltk n... | mit |
cmoutard/mne-python | examples/visualization/plot_evoked_delayed_ssp.py | 22 | 3873 | """
=========================================
Create evoked objects in delayed SSP mode
=========================================
This script shows how to apply SSP projectors delayed, that is,
at the evoked stage. This is particularly useful to support decisions
related to the trade-off between denoising and preservi... | bsd-3-clause |
MariaRigaki/kaggle | africa/predict.py | 1 | 1802 | __author__ = 'marik0'
#!/usr/bin/env python
# coding: utf-8
"""
prediction code for regression
"""
import sys
import numpy as np
import pandas as pd
from pylearn2.utils import serial
from theano import tensor as T
from theano import function
if __name__ == "__main__":
try:
model_path = sys.argv[1]
... | mit |
karstenw/nodebox-pyobjc | examples/Extended Application/sklearn/examples/linear_model/plot_sparse_logistic_regression_mnist.py | 1 | 3510 | """
=====================================================
MNIST classfification using multinomial logistic + L1
=====================================================
Here we fit a multinomial logistic regression with L1 penalty on a subset of
the MNIST digits classification task. We use the SAGA algorithm for this
pur... | mit |
yyjiang/scikit-learn | sklearn/utils/tests/test_multiclass.py | 72 | 15350 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from functools import partial
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse im... | bsd-3-clause |
samzhang111/scikit-learn | sklearn/tree/tree.py | 3 | 38647 | """
This module gathers tree-based methods, including decision, regression and
randomized trees. Single and multi-output problems are both handled.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Da... | bsd-3-clause |
cogmission/nupic | src/nupic/research/monitor_mixin/monitor_mixin_base.py | 13 | 7350 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2014, 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 |
zooniverse/aggregation | active_weather/old/learning.py | 1 | 9971 | # try:
# import matplotlib
# matplotlib.use('WXAgg')
# except ImportError:
# pass
from skimage.transform import probabilistic_hough_line
from skimage.feature import canny
import numpy as np
import math
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
try:
import Image
except ImportErr... | apache-2.0 |
wschenck/nest-simulator | pynest/nest/lib/hl_api_types.py | 13 | 38621 | # -*- coding: utf-8 -*-
#
# hl_api_types.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, o... | gpl-2.0 |
alexis-roche/nipy | examples/labs/multi_subject_parcellation.py | 4 | 1990 | #!/usr/bin/env python
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
from __future__ import print_function # Python 2/3 compatibility
__doc__ = """
This script contains a quick demo on a multi-subject parcellation on a toy 2D
example.
Note how the mid... | bsd-3-clause |
antgonza/qiime | tests/test_plot_taxa_summary.py | 15 | 16573 | #!/usr/bin/env python
# file test_plot_taxa_summary.py
__author__ = "Jesse Stombaugh"
__copyright__ = "Copyright 2011, The QIIME Project" # consider project name
__credits__ = ["Jesse Stombaugh", "Julia Goodrich"] # remember to add yourself
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Jesse Stomba... | gpl-2.0 |
withrocks/arteria-bcl2fastq | bcl2fastq/lib/illumina.py | 1 | 4256 |
from pandas import read_csv
class SampleRow:
"""
Provides a representation of the information presented in a Illumina Samplesheet.
Different samplesheet types (e.g. HiSeq, MiSeq, etc) will provide slightly different
information for each sample. This class aims at providing a interface to this that wil... | mit |
ericwhyne/open-catalog-generator | scripts/metrics.py | 3 | 13286 | #!/usr/bin/python
#James Tobat, 2014
import json
import sys
import time
#import matplotlib.pyplot as plt
import csv
import os.path
# Command line arguments and global constants
active_content_file = sys.argv[1]
deployed_content_file = sys.argv[2]
data_dir = sys.argv[3]
metric_log_dir = sys.argv[4]
date = time.strftime... | apache-2.0 |
rustyrazorblade/ipython-cql | cql/__init__.py | 1 | 4040 | from IPython.core.magic import Magics, magics_class, cell_magic, line_magic, needs_local_scope
from IPython.config.configurable import Configurable
from cassandra.cluster import Cluster
from cassandra.query import ordered_dict_factory, SimpleStatement
from prettytable import PrettyTable
try:
import numpy as np
... | bsd-2-clause |
bretthandrews/marvin | docs/sphinx/conf.py | 1 | 13652 | # -*- coding: utf-8 -*-
#
# Marvin documentation build configuration file, created by
# sphinx-quickstart on Sun Apr 10 08:50:42 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# Al... | bsd-3-clause |
OshynSong/scikit-learn | sklearn/tree/tree.py | 59 | 34839 | """
This module gathers tree-based methods, including decision, regression and
randomized trees. Single and multi-output problems are both handled.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Da... | bsd-3-clause |
wclark3/machine-learning | final-project/code/bigdata.py | 1 | 2184 | import argparse
import code
import os
import argcomplete
import numpy as np
import pandas as pd
import sklearn.ensemble
import sklearn.linear_model
# e.g. python bigdata.py -o=run_2015-12-06__02_26_27
def get_immediate_subdirectories(a_dir):
return [name for name in os.listdir(a_dir)
if os.path.isdir(os.path.joi... | mit |
ssh0/growing-string | triangular_lattice/random_lattice/growing.py | 1 | 10453 | #!/usr/bin/env python
# -*- coding:utf-8 -*-
#
# written by Shotaro Fujimoto
# 2017-03-22
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.tri as tri
import matplotlib.pyplot as plt
import numpy as np
from triangular import LatticeTriangular as LT
fro... | mit |
GregSilverman/cohort_rest_api | rest_api/api.py | 1 | 6076 | #!/usr/bin/env python
from gevent import monkey
monkey.patch_all()
from flask import request, jsonify
from marshmallow import Schema, fields
import time
# kludge for running pandas locally in testing mode
import os
import tempfile
os.environ['MPLCONFIGDIR'] = tempfile.mkdtemp()
import pandas as pd
from flask_cors imp... | gpl-3.0 |
ankurankan/scikit-learn | sklearn/preprocessing/tests/test_data.py | 12 | 29380 | import warnings
import numpy as np
import numpy.linalg as la
from scipy import sparse
from sklearn.utils.testing import assert_almost_equal, clean_warning_registry
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_e... | bsd-3-clause |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/pipeline.py | 5 | 28169 | """
The :mod:`sklearn.pipeline` module implements utilities to build a composite
estimator, as a chain of transforms and estimators.
"""
# Author: Edouard Duchesnay
# Gael Varoquaux
# Virgile Fritsch
# Alexandre Gramfort
# Lars Buitinck
# License: BSD
from collections import defaultdict... | mit |
avmarchenko/exatomic | exatomic/core/tests/test_basis.py | 2 | 5005 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2018, Exa Analytics Development Team
# Distributed under the terms of the Apache License 2.0
import numpy as np
import pandas as pd
from unittest import TestCase
from exatomic.core.basis import BasisSet
class TestBasisSet(TestCase):
def setUp(self):
adict = {co... | apache-2.0 |
johankaito/fufuka | microblog/flask/venv/lib/python2.7/site-packages/numpy/lib/npyio.py | 21 | 66671 | from __future__ import division, absolute_import, print_function
import sys
import os
import re
import itertools
import warnings
import weakref
from operator import itemgetter
import numpy as np
from . import format
from ._datasource import DataSource
from ._compiled_base import packbits, unpackbits
from ._iotools im... | apache-2.0 |
neurospin/pylearn-epac | epac/workflow/pipeline.py | 1 | 3604 | """
Define "Pipeline": the primitive to build sequential execution of tasks.
@author: edouard.duchesnay@cea.fr
@author: benoit.da_mota@inria.fr
"""
## Abreviations
## tr: train
## te: test
from epac.workflow.factory import NodeFactory
def __insert_node_at_leaf(node, node2insert):
"""insert a node at the leaf l... | bsd-3-clause |
dragoon/kilogram | kilogram/entity_linking/mention_rw/__init__.py | 1 | 7287 | from __future__ import division
import math
import numpy as np
import networkx as nx
from sklearn.preprocessing import normalize
from kilogram import NgramService
class Signature(object):
vector = None
mapping = None
def __init__(self, vector, G, candidate_uris):
"""
:type candidate_uris:... | apache-2.0 |
DGrady/pandas | pandas/core/indexes/frozen.py | 20 | 4619 | """
frozen (immutable) data structures to support MultiIndexing
These are used for:
- .names (FrozenList)
- .levels & .labels (FrozenNDArray)
"""
import numpy as np
from pandas.core.base import PandasObject
from pandas.core.dtypes.cast import coerce_indexer_dtype
from pandas.io.formats.printing import pprint_thing
... | bsd-3-clause |
jinghaomiao/apollo | modules/tools/realtime_plot/realtime_plot.py | 3 | 9046 | #!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo 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... | apache-2.0 |
thesuperzapper/tensorflow | tensorflow/contrib/learn/python/learn/estimators/estimator_test.py | 2 | 44417 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
alephu5/Soundbyte | environment/lib/python3.3/site-packages/IPython/core/usage.py | 7 | 23187 | # -*- coding: utf-8 -*-
"""Usage information for the main IPython applications.
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2008-2011 The IPython Development Team
# Copyright (C) 2001-2007 Fernando Perez. <fperez@colorado.edu>
#
# Distributed under the terms of... | gpl-3.0 |
jenfly/monsoon-onset | testing/testing-indices-onset_WLH.py | 1 | 13079 | import sys
sys.path.append('/home/jwalker/dynamics/python/atmos-tools')
sys.path.append('/home/jwalker/dynamics/python/atmos-read')
import xarray as xray
import numpy as np
from datetime import datetime
import matplotlib.pyplot as plt
import pandas as pd
import atmos as atm
import precipdat
from indices import onset_W... | mit |
pythonvietnam/scikit-learn | examples/svm/plot_svm_anova.py | 250 | 2000 | """
=================================================
SVM-Anova: SVM with univariate feature selection
=================================================
This example shows how to perform univariate feature before running a SVC
(support vector classifier) to improve the classification scores.
"""
print(__doc__)
import... | bsd-3-clause |
SimonStrong/pysd | pysd/functions.py | 2 | 30695 | """
functions.py
These are supports for functions that are included in modeling software but have no
straightforward equivalent in python.
"""
from __future__ import division
from functools import wraps
import pandas as pd
import pandas as _pd
import numpy as np
from . import utils
import imp
import warnings
impor... | mit |
ikaee/bfr-attendant | facerecognitionlibrary/jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/base.py | 7 | 19731 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
openfisca/openfisca-qt | openfisca_qt/scripts/tunisia/reforme_bareme.py | 1 | 5534 | # -*- coding:utf-8 -*-
"""
Created on Dec 6, 2012
@author: Mahd Ben Jelloul
openFisca, Logiciel libre de simulation du système socio-fiscal français
Copyright © 2011 Clément Schaff, Mahdi Ben Jelloul
This file is part of openFisca.
openFisca is free software: you can redistribute it and/or modify
it under th... | agpl-3.0 |
dgormez/pattern-recognition | pattern-reco.py | 1 | 25210 | """
Author : GORMEZ David
Imagery Project: Pattern recognition
"""
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.pyplot import cm
from matplotlib.collections import LineCollection
#from matplotlib import delaunay as triang
from matplotlib import colors
#from matplotlib import tri as tria
... | gpl-2.0 |
sequana/sequana | sequana/gff3.py | 1 | 22288 | # -*- coding: utf-8 -*-
#
# This file is part of Sequana software
#
# Copyright (c) 2016-2020 - Sequana Development Team
#
# File author(s):
# Thomas Cokelaer <thomas.cokelaer@pasteur.fr>
#
# Distributed under the terms of the 3-clause BSD license.
# The full license is in the LICENSE file, distributed with t... | bsd-3-clause |
apache/spark | python/pyspark/pandas/tests/data_type_ops/test_binary_ops.py | 6 | 9087 | #
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not us... | apache-2.0 |
costypetrisor/scikit-learn | examples/linear_model/plot_omp.py | 385 | 2263 | """
===========================
Orthogonal Matching Pursuit
===========================
Using orthogonal matching pursuit for recovering a sparse signal from a noisy
measurement encoded with a dictionary
"""
print(__doc__)
import matplotlib.pyplot as plt
import numpy as np
from sklearn.linear_model import OrthogonalM... | bsd-3-clause |
seckcoder/lang-learn | python/sklearn/examples/decomposition/plot_pca_vs_lda.py | 9 | 1711 | """
=======================================================
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... | unlicense |
IndraVikas/scikit-learn | sklearn/ensemble/__init__.py | 217 | 1307 | """
The :mod:`sklearn.ensemble` module includes ensemble-based methods for
classification and regression.
"""
from .base import BaseEnsemble
from .forest import RandomForestClassifier
from .forest import RandomForestRegressor
from .forest import RandomTreesEmbedding
from .forest import ExtraTreesClassifier
from .fores... | bsd-3-clause |
SiLab-Bonn/ccpdv4 | ccpdv4/scans/scan_dac_vs_current.py | 1 | 1518 | import logging
from time import sleep
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from ccpdv4.ccpdv4_run_base import Ccpdv4RunBase
from pybar.run_manager import RunManager
class Init(Ccpdv4RunBase):
'''Init scan
'''
_defau... | bsd-3-clause |
CVML/scikit-learn | examples/cluster/plot_cluster_iris.py | 350 | 2593 | #!/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 |
shl198/Projects | RibosomeProfilePipeline/06_Proteomaps.py | 2 | 24831 | from __future__ import division
import os
import pandas as pd
from natsort import natsorted
from f02_RiboDataModule import *
from Modules.f05_IDConvert import addGeneIDorNameForDESeqResult
signalP_path = '/data/shangzhong/RibosomeProfiling/signalP_part'
ribo_bam_path = '/data/shangzhong/RibosomeProfiling/Ribo_align/ba... | mit |
lakshayg/tensorflow | tensorflow/contrib/metrics/python/ops/metric_ops.py | 6 | 154353 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/scipy/integrate/odepack.py | 62 | 9420 | # Author: Travis Oliphant
from __future__ import division, print_function, absolute_import
__all__ = ['odeint']
from . import _odepack
from copy import copy
import warnings
class ODEintWarning(Warning):
pass
_msgs = {2: "Integration successful.",
1: "Nothing was done; the integration time was 0.",
... | mit |
jlegendary/scikit-learn | sklearn/covariance/tests/test_graph_lasso.py | 272 | 5245 | """ Test the graph_lasso module.
"""
import sys
import numpy as np
from scipy import linalg
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_less
from sklearn.covariance import (graph_lasso, GraphLasso, GraphLassoCV,
empirical_... | bsd-3-clause |
dcelisgarza/phd_excercises | comp_techniques/report/report.py | 1 | 11614 | # -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import matplotlib.pyplot as plt
import numpy as np
import scipy as sc
import math
# Expanded the sheath class from assignment 2. I couldn't find a way to do this with abstract classes.
class sheath:
# Initialisation subroutine.
def... | gpl-3.0 |
kursawe/MCSTracker | paper/Figures/Lloyds_relaxation_figure/make_lloyds_relaxation_plot.py | 1 | 11632 | # Copyright 2016 Jochen Kursawe. See the LICENSE file at the top-level directory
# of this distribution and at https://github.com/kursawe/MCSTracker/blob/master/LICENSE.
"""This tests our first tracking example
"""
import mesh
from mesh import Node
from mesh import Element
from mesh import Mesh
import tracking
import... | bsd-3-clause |
epruesse/ymp | src/ymp/stage/project.py | 1 | 22404 | """This module defines "Project", a Stage type defined by a project
matrix file giving units and meta data for input files.
"""
import logging
import os
import re
from collections.abc import Mapping, Sequence
import sqlite3
from typing import List, Union, Dict, Set, Optional
import ymp
from ymp.exceptions import Ymp... | gpl-3.0 |
russel1237/scikit-learn | sklearn/tree/tests/test_tree.py | 11 | 48140 | """
Testing for the tree module (sklearn.tree).
"""
import pickle
from functools import partial
from itertools import product
import platform
import numpy as np
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from sklearn.random_projection import sparse_rand... | bsd-3-clause |
akionakamura/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 130 | 50966 | # Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com> (main author)
# Mathieu Blondel (partial_fit support)
#
# License: BSD 3 clause
"""Classification and regression using Stochastic Gradient Descent (SGD)."""
import numpy as np
import scipy.sparse as sp
from abc import ABCMeta, abstractmethod
from ... | bsd-3-clause |
rrohan/scikit-learn | sklearn/decomposition/tests/test_nmf.py | 47 | 8566 | import numpy as np
from scipy import linalg
from sklearn.decomposition import nmf
from scipy.sparse import csc_matrix
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_raise_message
from sklearn.utils.testing import assert_array_almost... | bsd-3-clause |
JohanComparat/nbody-npt-functions | bin/bin_MD/otherScripts/vmax-function-0z1.py | 1 | 50194 | """
ls Multidark-lightcones/MD_*/properties/vmax-mvir/hist-Central*1.0*.dat
ls Multidark-lightcones/MD_*/properties/vmax-mvir/hist-Central*0.9*.dat
ls Multidark-lightcones/MD_*/properties/vmax-mvir/hist-Central*0.8*.dat
ls Multidark-lightcones/MD_*/properties/vmax-mvir/hist-Central*0.7*.dat
ls Multidark-lightcones/MD_... | cc0-1.0 |
henridwyer/scikit-learn | sklearn/gaussian_process/tests/test_gaussian_process.py | 267 | 6813 | """
Testing for Gaussian Process module (sklearn.gaussian_process)
"""
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# Licence: BSD 3 clause
from nose.tools import raises
from nose.tools import assert_true
import numpy as np
from sklearn.gaussian_process import GaussianProcess
from sklearn.gaussian_process ... | bsd-3-clause |
googleinterns/cabby | cabby/model/text/region_prediction/dataset.py | 1 | 3358 | # Copyright 2020 The Flax 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 wri... | apache-2.0 |
fredhusser/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 |
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