repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
MartinDelzant/scikit-learn | sklearn/datasets/lfw.py | 141 | 19372 | """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 |
crichardson17/starburst_atlas | Low_resolution_sims/DustFree_LowRes/Geneva_noRot_cont/Geneva_noRot_cont_age4/peaks_reader.py | 33 | 2761 | import csv
import matplotlib.pyplot as plt
from numpy import *
import scipy.interpolate
import math
from pylab import *
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import matplotlib.patches as patches
from matplotlib.path import Path
import os
# ---------------------------------------------------... | gpl-2.0 |
mprelee/data-incubator-capstone | src/tinker.py | 1 | 1701 | # Look at words
# Matt Prelee
import pandas as pd
import numpy as np
import matplotlib
#matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
import pickle
import nltk
import re
from sklearn import base
from sklearn.linear_model import LinearRegression, Lasso, ElasticNet
from sklearn.feature_extr... | gpl-2.0 |
vivekmishra1991/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 65 | 50308 | # 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 |
jpautom/scikit-learn | sklearn/__check_build/__init__.py | 345 | 1671 | """ Module to give helpful messages to the user that did not
compile the scikit properly.
"""
import os
INPLACE_MSG = """
It appears that you are importing a local scikit-learn source tree. For
this, you need to have an inplace install. Maybe you are in the source
directory and you need to try from another location.""... | bsd-3-clause |
kambysese/mne-python | tutorials/misc/plot_report.py | 3 | 13606 | """
.. _tut-report:
Getting started with ``mne.Report``
===================================
This tutorial covers making interactive HTML summaries with
:class:`mne.Report`.
As usual we'll start by importing the modules we need and loading some
:ref:`example data <sample-dataset>`:
"""
import os
import matplotlib.py... | bsd-3-clause |
dikien/Machine-Learning-Newspaper | nytimes/step4_BernoulliNB.py | 1 | 2163 | # -*- coding: UTF-8 -*-
from time import time
from step3_feature_engineering import preprocess_2
from sklearn.naive_bayes import BernoulliNB
from nltk.stem.snowball import SnowballStemmer
import numpy as np
features, labels, vectorizer, selector, le = preprocess_2("pkl/article_2_people.pkl", "pkl/lable_2_people.pkl")... | bsd-3-clause |
GaZ3ll3/scikit-image | doc/examples/plot_blob.py | 18 | 2796 | """
==============
Blob Detection
==============
Blobs are bright on dark or dark on bright regions in an image. In
this example, blobs are detected using 3 algorithms. The image used
in this case is the Hubble eXtreme Deep Field. Each bright dot in the
image is a star or a galaxy.
Laplacian of Gaussian (LoG)
-------... | bsd-3-clause |
vortex-exoplanet/VIP | vip_hci/var/shapes.py | 2 | 27456 | #! /usr/bin/env python
"""
Module with various functions to create shapes, annuli and segments.
"""
__author__ = 'Carlos Alberto Gomez Gonzalez'
__all__ = ['dist',
'dist_matrix',
'frame_center',
'get_square',
'get_circle',
'get_ellipse',
'get_annulus_s... | mit |
mugizico/scikit-learn | sklearn/tests/test_kernel_approximation.py | 244 | 7588 | import numpy as np
from scipy.sparse import csr_matrix
from sklearn.utils.testing import assert_array_equal, assert_equal, assert_true
from sklearn.utils.testing import assert_not_equal
from sklearn.utils.testing import assert_array_almost_equal, assert_raises
from sklearn.utils.testing import assert_less_equal
from ... | bsd-3-clause |
GedRap/voyager | backtesting/Portfolio.py | 2 | 5132 | import pandas as pd
import numpy as np
import math
import copy
import QSTK.qstkutil.qsdateutil as du
import datetime as dt
import QSTK.qstkutil.DataAccess as da
import QSTK.qstkutil.tsutil as tsu
from pandas import *
#Holds portfolio related data such as cash available and assets held
#Performs calculations related t... | mit |
yousrabk/mne-python | examples/forward/plot_make_forward.py | 20 | 2669 | """
======================================================
Create a forward operator and display sensitivity maps
======================================================
Sensitivity maps can be produced from forward operators that
indicate how well different sensor types will be able to detect
neural currents from diff... | bsd-3-clause |
jreback/pandas | pandas/tests/io/parser/test_c_parser_only.py | 1 | 23042 | """
Tests that apply specifically to the CParser. Unless specifically stated
as a CParser-specific issue, the goal is to eventually move as many of
these tests out of this module as soon as the Python parser can accept
further arguments when parsing.
"""
from io import BytesIO, StringIO, TextIOWrapper
import mmap
impo... | bsd-3-clause |
nickgentoo/scikit-learn-graph | scripts/Keras_calculate_cv_allkernels.py | 1 | 7678 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 13 13:02:41 2015
Copyright 2015 Nicolo' Navarin
This file is part of scikit-learn-graph.
scikit-learn-graph 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 ... | gpl-3.0 |
asnorkin/sentiment_analysis | site/lib/python2.7/site-packages/sklearn/feature_selection/tests/test_feature_select.py | 10 | 26399 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from numpy.testing import run_module_suite
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from... | mit |
plotly/plotly.py | packages/python/plotly/plotly/tests/test_optional/test_matplotlylib/test_axis_scales.py | 2 | 1336 | from __future__ import absolute_import
import pytest
from plotly import optional_imports
from plotly.tests.utils import compare_dict, strip_dict_params
from plotly.tests.test_optional.optional_utils import run_fig
from plotly.tests.test_optional.test_matplotlylib.data.axis_scales import *
matplotlylib = optional_imp... | mit |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/blocking_input.py | 10 | 11766 | """
This provides several classes used for blocking interaction with figure
windows:
:class:`BlockingInput`
creates a callable object to retrieve events in a blocking way for
interactive sessions
:class:`BlockingKeyMouseInput`
creates a callable object to retrieve key or mouse clicks in a blocking
way... | gpl-3.0 |
linebp/pandas | pandas/tests/sparse/test_combine_concat.py | 15 | 13923 | # pylint: disable-msg=E1101,W0612
import numpy as np
import pandas as pd
import pandas.util.testing as tm
class TestSparseSeriesConcat(object):
def test_concat(self):
val1 = np.array([1, 2, np.nan, np.nan, 0, np.nan])
val2 = np.array([3, np.nan, 4, 0, 0])
for kind in ['integer', 'block'... | bsd-3-clause |
sgranitz/nw | predict400/week9.py | 2 | 1496 | ## Week 9: Probability Density Functions
# Consider the probability density function f(x) = (3/26)x2 on [1, 3].
# On the same interval, consider the functions g(x) = (3/26)x3 and
# h(x) = (x – 30/13)(3/26)x3, which when integrated over the interval [1, 3]
# represent the mean and variance, respectively. Using Python... | mit |
krez13/scikit-learn | sklearn/neighbors/approximate.py | 30 | 22370 | """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 |
davidwhogg/Avast | code/triangle_basis.py | 1 | 10392 | """
This file is part of the Avast project.
Copyright 2016 Megan Bedell (Chicago) and David W. Hogg (NYU).
"""
import glob
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
from scipy.optimize import minimize
from scipy.linalg import svd
from scipy.io.i... | mit |
larsoner/mne-python | mne/tests/test_label.py | 8 | 41281 | from itertools import product
import glob
import os
import os.path as op
import pickle
import shutil
import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_equal, assert_array_almost_equal,
assert_equal)
import pytest
from mne.datasets import testing
from mne ... | bsd-3-clause |
Divergent914/kddcup2015 | modeling.py | 1 | 8187 | #! /usr/local/bin/python3
# -*- utf-8 -*-
"""
Generate model with respect to dataset.
"""
import logging
import sys
import util
import dataset
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG,
format='%(asctime)s %(name)s %(levelname)s\t%(message)s')
logger = logging.getLogger('modeli... | gpl-2.0 |
martinggww/lucasenlights | MachineLearning/DataScience/SparkKMeans.py | 3 | 1894 | from pyspark.mllib.clustering import KMeans
from numpy import array, random
from math import sqrt
from pyspark import SparkConf, SparkContext
from sklearn.preprocessing import scale
K = 5
# Boilerplate Spark stuff:
conf = SparkConf().setMaster("local").setAppName("SparkKMeans")
sc = SparkContext(conf = conf... | cc0-1.0 |
chanceraine/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/texmanager.py | 69 | 16818 | """
This module supports embedded TeX expressions in matplotlib via dvipng
and dvips for the raster and postscript backends. The tex and
dvipng/dvips information is cached in ~/.matplotlib/tex.cache for reuse between
sessions
Requirements:
* latex
* \*Agg backends: dvipng
* PS backend: latex w/ psfrag, dvips, and Gh... | agpl-3.0 |
namvo88/Thesis-Quadrotor-Code | sw/airborne/test/math/compare_utm_enu.py | 77 | 2714 | #!/usr/bin/env python
from __future__ import division, print_function, absolute_import
import sys
import os
PPRZ_SRC = os.getenv("PAPARAZZI_SRC", "../../../..")
sys.path.append(PPRZ_SRC + "/sw/lib/python")
from pprz_math.geodetic import *
from pprz_math.algebra import DoubleRMat, DoubleEulers, DoubleVect3
from math ... | gpl-2.0 |
dhhjx880713/GPy | GPy/plotting/plotly_dep/plot_definitions.py | 4 | 16743 | #===============================================================================
# Copyright (c) 2015, Max Zwiessele
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source... | bsd-3-clause |
anugrah-saxena/pycroscopy | pycroscopy/io/translators/beps_data_generator.py | 1 | 26908 | """
Utility functions for the Fake BEPS generator
"""
import os
import numpy as np
from PIL import Image
from sklearn.utils import gen_batches
from skimage.measure import block_reduce
# Pycroscopy imports
from ..io_hdf5 import ioHDF5
from ..hdf_utils import calc_chunks, getH5DsetRefs, link_as_main, get_attr, buildRedu... | mit |
zhoulingjun/zipline | tests/modelling/test_modelling_algo.py | 9 | 7105 | """
Tests for Algorithms running the full FFC stack.
"""
from unittest import TestCase
from os.path import (
dirname,
join,
realpath,
)
from numpy import (
array,
full_like,
nan,
)
from numpy.testing import assert_almost_equal
from pandas import (
concat,
DataFrame,
DatetimeIndex,
... | apache-2.0 |
ZenDevelopmentSystems/scikit-learn | sklearn/feature_selection/tests/test_from_model.py | 244 | 1593 | import numpy as np
import scipy.sparse as sp
from nose.tools import assert_raises, assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_greater
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
from sklearn.linear_model import SGD... | bsd-3-clause |
zaxtax/scikit-learn | examples/linear_model/plot_logistic_l1_l2_sparsity.py | 384 | 2601 | """
==============================================
L1 Penalty and Sparsity in Logistic Regression
==============================================
Comparison of the sparsity (percentage of zero coefficients) of solutions when
L1 and L2 penalty are used for different values of C. We can see that large
values of C give mo... | bsd-3-clause |
datacommonsorg/tools | stat_var_renaming/stat_var_renaming.py | 1 | 27748 | # 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under t... | apache-2.0 |
haisland0909/Denoising-Dirty-Documents | script/classify.py | 1 | 4675 | '''
Created on 2015/08/28
@author: haisland0909
'''
from sklearn.pipeline import FeatureUnion
from sklearn.grid_search import GridSearchCV
from sklearn import cross_validation
from sklearn import preprocessing
from sklearn.metrics import mean_absolute_error
import sklearn.linear_model
import sklearn.ensemble
import im... | apache-2.0 |
h2educ/scikit-learn | examples/neighbors/plot_regression.py | 349 | 1402 | """
============================
Nearest Neighbors regression
============================
Demonstrate the resolution of a regression problem
using a k-Nearest Neighbor and the interpolation of the
target using both barycenter and constant weights.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@... | bsd-3-clause |
maweigert/biobeam | tests/test_core/test_dn_mode.py | 1 | 1287 | """
mweigert@mpi-cbg.de
"""
from __future__ import absolute_import
from __future__ import print_function
import numpy as np
from biobeam import Bpm3d
from six.moves import zip
import matplotlib.pyplot as plt
def test_plane():
dx = .02
lam = .5
Nx = 128
Ny = 256
Nz = 400
dn0 = .1
dn = d... | bsd-3-clause |
alexsavio/scikit-learn | sklearn/decomposition/__init__.py | 76 | 1490 | """
The :mod:`sklearn.decomposition` module includes matrix decomposition
algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
this module can be regarded as dimensionality reduction techniques.
"""
from .nmf import NMF, ProjectedGradientNMF, non_negative_factorization
from .pca import PCA, Ra... | bsd-3-clause |
JapuDCret/RocketMap-Do | pogom/geofence.py | 14 | 5762 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import sys
import timeit
import logging
from .utils import get_args
log = logging.getLogger(__name__)
args = get_args()
# Trying to import matplotlib, which is not compatible with all hardware.
# Matlplotlib is faster for big calculations.
try:
from matplotlib.path imp... | agpl-3.0 |
lweasel/piquant | test/test_tpms.py | 1 | 7975 | import numpy as np
import numpy.testing as npt
import pandas as pd
import piquant.tpms as t
REAL_TPMS_VALS = [0.05, 0.02, 15, 2, 10, 30, 11]
CALC_TPMS_VALS = [0.03, 20, 3, 0.01, 5, 20, 10]
GROUPS = [0, 1, 0, 1, 0, 1, 1]
GROUP_TEST_COL = "group_test"
NOT_PRESENT_CUTOFF = 0.1
def _get_test_tpms():
tpms = pd.DataF... | mit |
cadowd/proppy | plane_estimate.py | 1 | 4272 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 10 12:04:48 2016
Flying wing drag polar estimator for low Re model scales
@author: c.dowd
"""
import numpy as np
import consumption_functions
import matplotlib.pyplot as plt
def getSpans(U_stall, plane, atmosphere):
"""
Returns the drag of a given pl... | gpl-3.0 |
rahuldhote/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 |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/examples/api/radar_chart.py | 3 | 6539 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib.projections.polar import PolarAxes
from matplotlib.projections import register_projection
def radar_factory(num_vars, frame='circle'):
"""Create a radar chart with `num_vars` axes."""
# calculate evenly-spaced axis angles
theta = 2*np... | gpl-2.0 |
gigglesninja/senior-design | MissionPlanner/Lib/site-packages/scipy/signal/fir_filter_design.py | 53 | 18572 | """Functions for FIR filter design."""
from math import ceil, log
import numpy as np
from numpy.fft import irfft
from scipy.special import sinc
import sigtools
# Some notes on function parameters:
#
# `cutoff` and `width` are given as a numbers between 0 and 1. These
# are relative frequencies, expressed as a fracti... | gpl-2.0 |
anthrotype/freetype-py | examples/glyph-outline.py | 3 | 1282 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
#
# FreeType high-level python API - Copyright 2011-2015 Nicolas P. Rougier
# Distributed under the terms of the new BSD license.
#
# ----------------------------------------------------------... | bsd-3-clause |
kylerbrown/scikit-learn | examples/applications/plot_outlier_detection_housing.py | 243 | 5577 | """
====================================
Outlier detection on a real data set
====================================
This example illustrates the need for robust covariance estimation
on a real data set. It is useful both for outlier detection and for
a better understanding of the data structure.
We selected two sets o... | bsd-3-clause |
catalyst-cooperative/pudl | src/pudl/analysis/service_territory.py | 1 | 19410 | """
Compile historical utility and balancing area territories.
Use the mapping of utilities to counties, and balancing areas to utilities, available
within the EIA 861, in conjunction with the US Census geometries for counties, to
infer the historical spatial extent of utility and balancing area territories. Output
th... | mit |
weaponsjtu/Kaggle_xBle | gen_ensemble.py | 1 | 19995 | ###
# ensemble.py
# author: Weipeng Zhang
#
#
# 1. check each weight by hyperopt
# 2. apply the weight to train/test
###
from sklearn.metrics import mean_squared_error as MSE
from sklearn.linear_model import LinearRegression, LogisticRegression, Ridge
import cPickle as pickle
import numpy as np
import pandas as pd
im... | gpl-2.0 |
wzbozon/statsmodels | statsmodels/examples/ex_kernel_semilinear_dgp.py | 33 | 4969 | # -*- coding: utf-8 -*-
"""
Created on Sun Jan 06 09:50:54 2013
Author: Josef Perktold
"""
from __future__ import print_function
if __name__ == '__main__':
import numpy as np
import matplotlib.pyplot as plt
#from statsmodels.nonparametric.api import KernelReg
import statsmodels.sandbox.nonparametr... | bsd-3-clause |
avistous/QSTK | qstkstrat/strategies.py | 2 | 9521 | '''
(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 Sep 27, 2011
@author: John Cornwell
@contact: JohnWCornwellV@gmail.com
@summary: Various simple trading st... | bsd-3-clause |
storpipfugl/airflow | airflow/hooks/presto_hook.py | 37 | 2626 | from builtins import str
from pyhive import presto
from pyhive.exc import DatabaseError
from airflow.hooks.dbapi_hook import DbApiHook
import logging
logging.getLogger("pyhive").setLevel(logging.INFO)
class PrestoException(Exception):
pass
class PrestoHook(DbApiHook):
"""
Interact with Presto through ... | apache-2.0 |
poldrack/myconnectome | myconnectome/taskfmri/encoding_model.py | 2 | 3311 | """
do encoding model across sessions
"""
import os,glob,sys,ctypes
import nibabel.gifti.giftiio
import numpy
import sklearn.linear_model
from myconnectome.utils.array_to_gifti import array_to_gifti_32k
basedir = os.environ['MYCONNECTOME_DIR']
datadir='/corral-repl/utexas/poldracklab/data/selftracking'
def get_codes... | mit |
stulp/dmpbbo | demos_cpp/dynamicalsystems/demoExponentialSystemWrapper.py | 1 | 2205 | # This file is part of DmpBbo, a set of libraries and programs for the
# black-box optimization of dynamical movement primitives.
# Copyright (C) 2014 Freek Stulp, ENSTA-ParisTech
#
# DmpBbo is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as publis... | lgpl-2.1 |
araichev/make_gtfs | tests/test_main.py | 1 | 6169 | import pandas as pd
import gtfs_kit as gk
import shapely.geometry as sg
import geopandas as gpd
from .context import make_gtfs, DATA_DIR
from make_gtfs import *
# Load test ProtoFeed
pfeed = read_protofeed(DATA_DIR / "auckland")
def test_get_duration():
ts1 = "01:01:01"
ts2 = "01:05:01"
get = get_durat... | mit |
eclee25/flu-SDI-exploratory-age | scripts/Znorm_OR_relative.py | 1 | 9452 | #!/usr/bin/python
##############################################
###Python template
###Author: Elizabeth Lee
###Date: 4/9/14
###Function: calculate average z-ORs where the early warning and classification periods are defined as relative dates
## early warning period begins on the week after Thanksgiving and the two su... | mit |
ChinaQuants/pyfolio | setup.py | 1 | 2520 | #!/usr/bin/env python
from setuptools import setup
import versioneer
DISTNAME = 'pyfolio'
DESCRIPTION = "pyfolio is a Python library for performance and risk analysis of financial portfolios"
LONG_DESCRIPTION = """pyfolio is a Python library for performance and risk analysis of
financial portfolios developed by `Qua... | apache-2.0 |
bmazin/ARCONS-pipeline | examples/Pal2012-sdss/curve_average.py | 1 | 2036 | import numpy as np
import matplotlib.pyplot as plt
from util import utils
t08 = np.load('/home/pszypryt/sdss_data/20121208/Blue-Fit.npz')
t10 = np.load('/home/pszypryt/sdss_data/20121210/Blue10-Fit.npz')
t11 = np.load('/home/pszypryt/sdss_data/20121211/seq5Blue-Fit.npz')
params08 = t08['params']
params10 = t10['param... | gpl-2.0 |
Caranarq/01_Dmine | 07_Movilidad/P0706/P0706.py | 1 | 3153 | # -*- coding: utf-8 -*-
"""
Started on tue, feb 21st, 2018
@author: carlos.arana
"""
# Librerias utilizadas
import pandas as pd
import sys
module_path = r'D:\PCCS\01_Dmine\Scripts'
if module_path not in sys.path:
sys.path.append(module_path)
from VarInt.VarInt import VarInt
from classes.Meta import Meta
from Com... | gpl-3.0 |
terkkila/scikit-learn | examples/exercises/plot_cv_digits.py | 232 | 1206 | """
=============================================
Cross-validation on Digits Dataset Exercise
=============================================
A tutorial exercise using Cross-validation with an SVM on the Digits dataset.
This exercise is used in the :ref:`cv_generators_tut` part of the
:ref:`model_selection_tut` section... | bsd-3-clause |
CDNoyes/EDL-Py | EntryGuidance/Simulation.py | 1 | 40755 | import sys
from os import path
# sys.path.append( path.dirname( path.dirname( path.abspath(__file__) ) ) )
sys.path.append("./")
sys.path.append("../")
from Utils.RK4 import RK4
from Utils import DA as da
import pandas as pd
import numpy as np
from scipy.integrate import odeint, trapz
from scipy import linalg
from sci... | gpl-3.0 |
smartscheduling/scikit-learn-categorical-tree | sklearn/tests/test_pipeline.py | 10 | 14095 | """
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
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import ... | bsd-3-clause |
ammarkhann/FinalSeniorCode | lib/python2.7/site-packages/pandas/tests/series/test_alter_axes.py | 3 | 6584 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
import pytest
from datetime import datetime
import numpy as np
import pandas as pd
from pandas import Index, Series
from pandas.core.index import MultiIndex, RangeIndex
from pandas.compat import lrange, range, zip
from pandas.util.testing import assert_series_equal,... | mit |
DataReplyUK/datareplyuk | eu_tweet_classifier/train_model.py | 1 | 20044 | # General IMPORTS --------------------------------------------------------------------------------------------------#
import os
import re
import sys
import pickle
import pandas
import random
import itertools
import collections
import matplotlib.pyplot as plt
# NLTK IMPORTS --------------------------------------------... | apache-2.0 |
bsipocz/seaborn | doc/conf.py | 25 | 9149 | # -*- coding: utf-8 -*-
#
# seaborn documentation build configuration file, created by
# sphinx-quickstart on Mon Jul 29 23:25:46 2013.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All... | bsd-3-clause |
dh4gan/oberon | plot/plot_positions.py | 1 | 1034 | '''
Created on 7/3/14
@author: dh4gan
Show the positions of the bodies in the system
'''
from sys import argv
from matplotlib import pyplot as plt
import io_oberon.io_nbody
# Data file can be read from the command line or from argument
if len(argv)==1:
input_file = raw_input("Enter the datafil... | gpl-3.0 |
nixingyang/Kaggle-Competitions | Customer Analytics/ensemble.py | 3 | 1660 | import file_operations
import glob
import numpy as np
import os
import pandas as pd
import solution
import time
OLD_SUBMISSION_FOLDER_PATH = solution.SUBMISSION_FOLDER_PATH
NEW_SUBMISSION_FOLDER_PATH = "./"
def perform_ensembling(low_threshold, high_threshold):
print("Reading the submission files from disk ...")... | mit |
INCF/BIDS2ISATab | bids2isatab/main.py | 1 | 25918 | #!/usr/bin/env python
#
# import modules used here -- sys is a very standard one
from __future__ import print_function
import argparse
import logging
from collections import OrderedDict
from glob import glob
import os
from os.path import exists, join as opj, split as psplit
import sys
import nibabel
import json
impo... | apache-2.0 |
DigitalSlideArchive/HistomicsTK | setup.py | 1 | 3031 | #! /usr/bin/env python
import os
import sys
from setuptools import find_packages
try:
from skbuild import setup
except ImportError:
sys.stderr.write("""scikit-build is required to build from source or run tox.
Please run:
python -m pip install scikit-build
""")
# from setuptools import setup
sys.ex... | apache-2.0 |
wathen/PhD | MHD/FEniCS/MHD/Stabilised/SaddlePointForm/Test/SplitMatrix/ScottTest/MHDgenerator/MHDmatrixSetup.py | 3 | 5074 |
import petsc4py
import sys
petsc4py.init(sys.argv)
from petsc4py import PETSc
from dolfin import *
# from MatrixOperations import *
import numpy as np
#import matplotlib.pylab as plt
from scipy.sparse import coo_matrix, csr_matrix, spdiags, bmat
import os, inspect
from HiptmairSetup import BoundaryEdge
import matpl... | mit |
rupakc/Kaggle-Compendium | Pokemon/pokedock.py | 1 | 1692 | # -*- coding: utf-8 -*-
"""
Created on Sat Dec 24 14:04:20 2016
@author: Rupak Chakraborty
"""
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.ensemble import AdaBoostClassifier... | mit |
wzbozon/scikit-learn | sklearn/tree/tests/test_export.py | 130 | 9950 | """
Testing for export functions of decision trees (sklearn.tree.export).
"""
from re import finditer
from numpy.testing import assert_equal
from nose.tools import assert_raises
from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
from sklearn.ensemble import GradientBoostingClassifier
from sklearn... | bsd-3-clause |
ishanic/scikit-learn | sklearn/utils/fixes.py | 133 | 12882 | """Compatibility fixes for older version of python, numpy and scipy
If you add content to this file, please give the version of the package
at which the fixe is no longer needed.
"""
# Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# ... | bsd-3-clause |
vberaudi/utwt | sudoku.py | 1 | 1116 | import pandas as pd
import pandas as pd
from docplex.cp.model import *
GRNG = range(9)
problem_data = pd.read_csv("sudoku.csv", sep=";")
problem = []
for t in problem_data.itertuples(index=False):
problem.append([i for i in t])
mdl = CpoModel(name="Sudoku")
grid = [[integer_var(min=1, max=9, name="C" + str(l) + ... | apache-2.0 |
google-code-export/nmrglue | doc/_build/html/examples/el/sample_applications/apod_viewer_1win.py | 10 | 9854 | #!/usr/bin/env python
"""
An example of using wxPython to build a GUI application using nmrglue
This application displays the NMRPipe apodization windows
"""
import numpy as np
import nmrglue as ng
import matplotlib
# uncomment the following to use wx rather than wxagg
#matplotlib.use('WX')
#from matplotlib.backends... | bsd-3-clause |
TheCoSMoCompany/biopredyn | Prototype/python/biopredyn/biopredynCL.py | 1 | 3886 | #!/usr/bin/env python
# coding=utf-8
## @package biopredyn
## Copyright: [2012-2019] Cosmo Tech, All Rights Reserved
## License: BSD 3-Clause
import sys
import getopt
import textwrap
import libsbml
import libsedml
import libnuml
from biopredyn import model, workflow, result, resources
import matplotlib.pyplot as plt
... | bsd-3-clause |
BrianGasberg/filterpy | filterpy/kalman/tests/test_mmae.py | 1 | 5136 | # -*- coding: utf-8 -*-
"""Copyright 2015 Roger R Labbe Jr.
FilterPy library.
http://github.com/rlabbe/filterpy
Documentation at:
https://filterpy.readthedocs.org
Supporting book at:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
This is licensed under an MIT license. See the readme.MD file
for mo... | mit |
lucarebuffi/OASYS1 | oasys/widgets/error_profile/ow_abstract_dabam_height_profile.py | 1 | 53621 | import os, sys
import time
import numpy
import threading
from PyQt5.QtCore import QRect, Qt
from PyQt5.QtWidgets import QApplication, QMessageBox, QScrollArea, QTableWidget, QTableWidgetItem, QHeaderView, QAbstractItemView, QWidget, QLabel, QSizePolicy
from PyQt5.QtGui import QTextCursor,QFont, QPalette, QColor, QPain... | gpl-3.0 |
yavuzovski/playground | machine learning/Udacity/ud120-projects/outliers/enron_outliers.py | 1 | 1299 | #!/usr/bin/python
import pickle
import sys
import matplotlib.pyplot
sys.path.append("../tools/")
from feature_format import featureFormat, targetFeatureSplit
import numpy as np
### read in data dictionary, convert to numpy array
data_dict = pickle.load( open("../final_project/final_project_dataset.pkl", "r") )
featur... | gpl-3.0 |
OXPHOS/shogun | applications/tapkee/swissroll_embedding.py | 12 | 2600 | import numpy
numpy.random.seed(40)
tt = numpy.genfromtxt('../../data/toy/swissroll_color.dat',unpack=True).T
X = numpy.genfromtxt('../../data/toy/swissroll.dat',unpack=True).T
N = X.shape[1]
converters = []
from shogun import LocallyLinearEmbedding
lle = LocallyLinearEmbedding()
lle.set_k(9)
converters.append((lle, "L... | gpl-3.0 |
btabibian/scikit-learn | sklearn/cluster/tests/test_affinity_propagation.py | 341 | 2620 | """
Testing for Clustering methods
"""
import numpy as np
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.cluster.affinity_propagation_ import AffinityPropagation
from sklearn.cluster.affinity_propagatio... | bsd-3-clause |
NunoEdgarGub1/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/_cm.py | 70 | 375423 | """
Color data and pre-defined cmap objects.
This is a helper for cm.py, originally part of that file.
Separating the data (this file) from cm.py makes both easier
to deal with.
Objects visible in cm.py are the individual cmap objects ('autumn',
etc.) and a dictionary, 'datad', including all of these objects.
"""
im... | gpl-3.0 |
gfyoung/pandas | pandas/tests/scalar/timestamp/test_arithmetic.py | 4 | 9023 | from datetime import datetime, timedelta
import numpy as np
import pytest
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
Timedelta,
Timestamp,
offsets,
to_offset,
)
import pandas._testing as tm
class TestTimestampArithmetic:
def test_overflow_offset(self):
# no overflow expe... | bsd-3-clause |
wvconnors/pysleeg | eegclassy.py | 1 | 1976 | # -*- coding: utf-8 -*-
"""
2/8/17, Will Connors
eegclassy.py - A program to take EDF polysomnography data and phase annotations, format, and create a classifier
"""
import numpy as np
#import pandas
#import io
#import tensorflow as tf
#import matplotlib as plot
class Eeg:
'''a class'''
def __init__(sel... | gpl-3.0 |
benjaminy/ManyHands | Client/Source/Crypto/beau/test/plotter.py | 1 | 3473 | import matplotlib.pyplot as plt
import json
ns = []
random_times = []
best_times = []
worst_times = []
timesr = []
min_i = 2
max_i = 27
n_base = 1.3
f = open('./results_with_crypto/nano_array_sorting','r')
input_arr = f.read()
nano_array_sorting = json.loads(input_arr)
f.close()
f = open('./results_with_crypt... | mit |
saiwing-yeung/scikit-learn | examples/model_selection/grid_search_digits.py | 8 | 2760 | """
============================================================
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.model_selection.GridS... | bsd-3-clause |
jreback/pandas | pandas/tests/extension/test_period.py | 2 | 4619 | import numpy as np
import pytest
from pandas._libs import iNaT
from pandas.core.dtypes.dtypes import PeriodDtype
import pandas as pd
from pandas.core.arrays import PeriodArray
from pandas.tests.extension import base
@pytest.fixture
def dtype():
return PeriodDtype(freq="D")
@pytest.fixture
def data(dtype):
... | bsd-3-clause |
hitszxp/scikit-learn | examples/svm/plot_svm_scale_c.py | 26 | 5353 | """
==============================================
Scaling the regularization parameter for SVCs
==============================================
The following example illustrates the effect of scaling the
regularization parameter when using :ref:`svm` for
:ref:`classification <svm_classification>`.
For SVC classificati... | bsd-3-clause |
andaag/scikit-learn | sklearn/ensemble/tests/test_voting_classifier.py | 140 | 6926 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble import RandomForestCl... | bsd-3-clause |
vanceeasleaf/aces | aces/runners/shengbte.py | 1 | 28228 | # -*- coding: utf-8 -*-
# @Author: YangZhou
# @Date: 2017-06-13 00:44:48
# @Last Modified by: YangZhou
# @Last Modified time: 2017-06-23 18:53:35
import aces.config as config
from ase import io
from aces.graph import plot, series
import numpy as np
from aces.runners.phonopy import runner as Runner
import pandas as... | gpl-2.0 |
vicky2135/lucious | oscar/lib/python2.7/site-packages/IPython/sphinxext/ipython_directive.py | 6 | 42602 | # -*- coding: utf-8 -*-
"""
Sphinx directive to support embedded IPython code.
This directive allows pasting of entire interactive IPython sessions, prompts
and all, and their code will actually get re-executed at doc build time, with
all prompts renumbered sequentially. It also allows you to input code as a pure
pyth... | bsd-3-clause |
JanNash/sms-tools | software/transformations_interface/sineTransformations_function.py | 25 | 5018 | # function call to the transformation functions of relevance for the sineModel
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.p... | agpl-3.0 |
subodhchhabra/pandashells | pandashells/test/p_regplot_test.py | 10 | 1072 | #! /usr/bin/env python
from mock import patch
from unittest import TestCase
import numpy as np
import pandas as pd
from pandashells.bin.p_regplot import main, make_label
class MakeLabelTests(TestCase):
def test_make_label_html(self):
label = make_label(coeffs=[1, 2, 3], savefig=['test.html'])
sel... | bsd-2-clause |
gorakhargosh/ThinkStats2 | code/scatter.py | 69 | 4281 | """This file contains code for use with "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 sys
import numpy as np
import math
import brfss
import thinkplot
import ... | gpl-3.0 |
xuzetan/gemini | gemini/tool_burden_tests.py | 5 | 9907 | import math
from collections import Counter, defaultdict
import numpy as np
from scipy.stats import binom, norm
from pandas import DataFrame
import sys
import random
from itertools import islice
from scipy.misc import comb
import GeminiQuery
def burden_by_gene(args):
"""
calculates per sample the total gene... | mit |
crackmech/fly-walk | functions.py | 1 | 2324 | import matplotlib.pyplot as plt
#from skimage.io import imread
from keras import backend as K
import numpy as np
def resize_crop_image(image,scale,cutoff_percent):
image = cv2.resize(image,None,fx=scale, fy=scale, interpolation = cv2.INTER_AREA)
cut_off_vals = [image.shape[0]*cutoff_percent/100, image.shape[1]*cutof... | mit |
toobaz/pandas | pandas/plotting/_matplotlib/misc.py | 2 | 12271 | import random
import matplotlib.lines as mlines
import matplotlib.patches as patches
import numpy as np
from pandas.core.dtypes.missing import notna
from pandas.io.formats.printing import pprint_thing
from pandas.plotting._matplotlib.style import _get_standard_colors
from pandas.plotting._matplotlib.tools import _se... | bsd-3-clause |
nilgoyyou/dipy | doc/examples/restore_dti.py | 4 | 7944 | """
=====================================================
Using the RESTORE algorithm for robust tensor fitting
=====================================================
The diffusion tensor model takes into account certain kinds of noise (thermal),
but not other kinds, such as "physiological" noise. For example, if a sub... | bsd-3-clause |
kaslusimoes/SummerSchool2016 | simulation-multiple-variations.py | 1 | 7037 | #! /bin/env python2
# coding: utf-8
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
import random as rd
from pickle import dump
class Data:
def __init__(self):
self.m_list1 = []
self.m_list2 = []
N = 100
M = 100
MAX = N + M + 1
MAX_EDGE = 380
MAX_DEG = 450
ITERATIONS = 50... | apache-2.0 |
zooniverse/aggregation | active_weather/old/paper_threshold.py | 1 | 4407 | __author__ = 'ggdhines'
import cv2
import matplotlib.pyplot as plt
from active_weather import ActiveWeather
import numpy as np
from os import popen
import csv
image = cv2.imread("/home/ggdhines/region.jpg",0)
ret,th1 = cv2.threshold(image,180,255,cv2.THRESH_BINARY)
# plt.imshow(th1)
# plt.show()
# cv2.imwrite("/home/... | apache-2.0 |
M-R-Houghton/euroscipy_2015 | bokeh/bokeh/charts/builder/tests/test_horizon_builder.py | 33 | 3440 | """ This is the Bokeh charts testing interface.
"""
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with thi... | mit |
shikhardb/scikit-learn | examples/calibration/plot_calibration_curve.py | 225 | 5903 | """
==============================
Probability Calibration curves
==============================
When performing classification one often wants to predict not only the class
label, but also the associated probability. This probability gives some
kind of confidence on the prediction. This example demonstrates how to di... | bsd-3-clause |
kevin-intel/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 10 | 2760 | import itertools
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors._ball_tree import BallTree
from sklearn.neighbors import DistanceMetric
from sklearn.utils import check_random_state
from sklearn.utils.validation import check_array
from sklearn.utils._testing ... | bsd-3-clause |
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