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 |
|---|---|---|---|---|---|
liangz0707/scikit-learn | examples/linear_model/plot_polynomial_interpolation.py | 251 | 1895 | #!/usr/bin/env python
"""
========================
Polynomial interpolation
========================
This example demonstrates how to approximate a function with a polynomial of
degree n_degree by using ridge regression. Concretely, from n_samples 1d
points, it suffices to build the Vandermonde matrix, which is n_samp... | bsd-3-clause |
bdh1011/wau | venv/lib/python2.7/site-packages/pandas/tests/test_multilevel.py | 1 | 87291 | # -*- coding: utf-8 -*-
# pylint: disable-msg=W0612,E1101,W0141
import datetime
import itertools
import nose
from numpy.random import randn
import numpy as np
from pandas.core.index import Index, MultiIndex
from pandas import Panel, DataFrame, Series, notnull, isnull, Timestamp
from pandas.util.testing import (asser... | mit |
zoranzhao/NoSSim | NoS_ECG/ga_dse.py | 1 | 7996 | #!/usr/bin/env python2.7
# NoSSim exploration framework
# Author: Zhuoran Zhao
# Date: 2017/03/18
# This GA-based exploration is developed with DEAP library
# Single/Multi-Object GA are encapsulated in different functions main_ga, main_moga
import random
import array
import json
import numpy
import pprint... | bsd-3-clause |
MartinDelzant/scikit-learn | examples/gaussian_process/gp_diabetes_dataset.py | 223 | 1976 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
========================================================================
Gaussian Processes regression: goodness-of-fit on the 'diabetes' dataset
========================================================================
In this example, we fit a Gaussian Process model onto... | bsd-3-clause |
Nyker510/scikit-learn | examples/cluster/plot_segmentation_toy.py | 258 | 3336 | """
===========================================
Spectral clustering for image segmentation
===========================================
In this example, an image with connected circles is generated and
spectral clustering is used to separate the circles.
In these settings, the :ref:`spectral_clustering` approach solve... | bsd-3-clause |
amolkahat/pandas | pandas/tests/indexes/interval/test_interval.py | 1 | 47391 | from __future__ import division
from itertools import permutations
import pytest
import numpy as np
import re
from pandas import (
Interval, IntervalIndex, Index, isna, notna, interval_range, Timestamp,
Timedelta, date_range, timedelta_range)
from pandas.compat import lzip
import pandas.core.common as com
from... | bsd-3-clause |
yuliang419/K2tools | ecentroid.py | 1 | 3828 | """
Plots any selected star(s) to use as reference star(s) for detrending.
Writes good frame numbers into file named ref_cad.dat, and centroids into ref_centroid.dat (for one chosen star only,
but we can probably average a few).
"""
from pixel2flux import *
import matplotlib.pyplot as plt
plt.ion()
import numpy as np
... | mit |
olologin/scikit-learn | examples/classification/plot_classifier_comparison.py | 36 | 5123 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=====================
Classifier comparison
=====================
A comparison of a several classifiers in scikit-learn on synthetic datasets.
The point of this example is to illustrate the nature of decision boundaries
of different classifiers.
This should be taken with ... | bsd-3-clause |
idlead/scikit-learn | examples/linear_model/plot_ard.py | 18 | 2827 | """
==================================================
Automatic Relevance Determination Regression (ARD)
==================================================
Fit regression model with Bayesian Ridge Regression.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary l... | bsd-3-clause |
pylayers/pylayers | pylayers/simul/link.py | 1 | 78614 | #
# -*- coding: utf-8 -*-
#
from __future__ import print_function
r"""
.. currentmodule:: pylayers.simul.link
.. autosummary::
:members:
"""
try:
from tvtk.api import tvtk
from mayavi.sources.vtk_data_source import VTKDataSource
from mayavi import mlab
except:
print('Layout:Mayavi is not install... | mit |
pkruskal/scikit-learn | sklearn/cross_decomposition/pls_.py | 187 | 28507 | """
The :mod:`sklearn.pls` module implements Partial Least Squares (PLS).
"""
# Author: Edouard Duchesnay <edouard.duchesnay@cea.fr>
# License: BSD 3 clause
from ..base import BaseEstimator, RegressorMixin, TransformerMixin
from ..utils import check_array, check_consistent_length
from ..externals import six
import w... | bsd-3-clause |
ContinuumIO/blaze | blaze/compute/sql.py | 3 | 49986 | """
>>> from blaze import *
>>> accounts = symbol('accounts', 'var * {name: string, amount: int}')
>>> deadbeats = accounts[accounts['amount'] < 0]['name']
>>> from sqlalchemy import Table, Column, MetaData, Integer, String
>>> t = Table('accounts', MetaData(),
... Column('name', String, primary_key = True... | bsd-3-clause |
sbg2133/miscellaneous_projects | carina/planck_lic.py | 1 | 4381 | from getIQU import IQU
from subprocess import call
import sys, os
import numpy as np
import matplotlib.pyplot as plt
from astropy.convolution import convolve, Gaussian2DKernel
from astropy.io import fits
from astropy.wcs import WCS
import scipy.ndimage
from skimage import filters
plt.ion()
stokes = ['I', 'Q', 'U']
pl... | gpl-3.0 |
shipci/sympy | examples/intermediate/mplot3d.py | 14 | 1261 | #!/usr/bin/env python
"""Matplotlib 3D plotting example
Demonstrates plotting with matplotlib.
"""
import sys
from sample import sample
from sympy import sin, Symbol
from sympy.external import import_module
def mplot3d(f, var1, var2, show=True):
"""
Plot a 3d function using matplotlib/Tk.
"""
im... | bsd-3-clause |
kagayakidan/scikit-learn | sklearn/utils/tests/test_random.py | 230 | 7344 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from scipy.misc import comb as combinations
from numpy.testing import assert_array_almost_equal
from sklearn.utils.random import sample_without_replacement
from sklearn.utils.random import random_choice_csc
from sklearn.utils.testing import ... | bsd-3-clause |
bellwethers-in-se/defects | src/old/Test Oracle/Prediction.py | 1 | 1996 | from __future__ import division
from sklearn.ensemble import RandomForestClassifier
from methods1 import *
from smote import *
def formatData(tbl):
""" Convert Tbl to Pandas DataFrame
:param tbl: Thing object created using function createTbl
:returns table in a DataFrame format
"""
Rows = [i.ce... | mit |
grhawk/ASE | ase/io/png.py | 4 | 1758 | from ase.io.eps import EPS
class PNG(EPS):
def write_header(self):
from matplotlib.backends.backend_agg import RendererAgg
try:
from matplotlib.transforms import Value
except ImportError:
dpi = 72
else:
dpi = Value(72)
self.renderer = R... | gpl-2.0 |
e-koch/VLA_Lband | 14B-088/HI/imaging/imaging_tests/HI_testing_analysis.py | 1 | 2781 |
'''
Split from HI_testing_comparison because I didn't feel like getting statsmodels
to play nice within CASA.
'''
import os
import pandas as pd
import statsmodels.formula.api as sm
data_path = os.path.expanduser("~/MyRAID/M33/14B-088/HI/channel_testing")
data = pd.read_csv(os.path.join(data_path, "property_values.c... | mit |
shahankhatch/scikit-learn | examples/neural_networks/plot_rbm_logistic_classification.py | 258 | 4609 | """
==============================================================
Restricted Boltzmann Machine features for digit classification
==============================================================
For greyscale image data where pixel values can be interpreted as degrees of
blackness on a white background, like handwritten... | bsd-3-clause |
mromanello/CitationExtractor | citation_extractor/ned/matchers.py | 1 | 39974 | # -*- coding: utf-8 -*-
# author: Matteo Romanello, matteo.romanello@gmail.com, Matteo Filipponi
"""Contains various implementations of citation matchers."""
from __future__ import print_function
import os
import pickle
import sys
import pdb
import time
import logging
import multiprocessing
from operator import itemg... | gpl-3.0 |
lpsinger/astropy | astropy/nddata/ccddata.py | 5 | 27852 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""This module implements the base CCDData class."""
import itertools
import numpy as np
from .compat import NDDataArray
from .nduncertainty import (
StdDevUncertainty, NDUncertainty, VarianceUncertainty, InverseVariance)
from astropy.io import fits... | bsd-3-clause |
ODM2/ODM2YODAParser | yodatools/excelparser/excelParser.py | 2 | 22474 | import os
import re
from collections import defaultdict
from uuid import uuid4
import wx
from datetime import datetime
from pubsub import pub
from pandas import isnull, DataFrame, NaT
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm.exc import NoResultFound
from sqlalchemy.orm.session import Session
impor... | bsd-3-clause |
Stargrazer82301/CAAPR | CAAPR/CAAPR_AstroMagic/PTS/pts/core/plot/grids.py | 1 | 6267 | #!/usr/bin/env python
# -*- coding: utf8 -*-
# *****************************************************************
# ** PTS -- Python Toolkit for working with SKIRT **
# ** © Astronomical Observatory, Ghent University **
# *****************************************************************
##... | mit |
fyffyt/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 |
kreczko/rootpy | setup.py | 1 | 4867 | #!/usr/bin/env python
# Copyright 2012 the rootpy developers
# distributed under the terms of the GNU General Public License
import sys
# check Python version
if sys.version_info < (2, 6):
sys.exit("rootpy only supports python 2.6 and above")
# check that ROOT can be imported
try:
import ROOT
except ImportEr... | gpl-3.0 |
samuroi/SamuROI | samuroi/gui/widgets/traceview.py | 1 | 5505 | import numpy
from PyQt5 import QtCore, QtGui
from PyQt5.QtWidgets import QDockWidget, QWidget, QHBoxLayout
from .canvasbase import CanvasBase
class TraceViewCanvas(CanvasBase):
"""Plot a set of traces for a selection defined by a QtSelectionModel"""
def __init__(self, segmentation, selectionmodel):
... | mit |
zooniverse/aggregation | experimental/algorithms/serengeti_2.py | 2 | 3778 | #!/usr/bin/env python
__author__ = 'greg'
import pymongo
import matplotlib.pyplot as plt
import numpy
import math
import random
import csv
import scipy.stats as stats
# import numpy as np
import pylab as pl
import scipy.special as ss
from scipy.stats import beta as beta_func
# load subject data from CSV
subjects_index... | apache-2.0 |
bavardage/statsmodels | statsmodels/sandbox/examples/ex_cusum.py | 3 | 3212 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 02 11:41:25 2010
Author: josef-pktd
"""
import numpy as np
from scipy import stats
from numpy.testing import assert_almost_equal
import statsmodels.api as sm
from statsmodels.sandbox.regression.onewaygls import OneWayLS
from statsmodels.stats.diagnostic import recursive... | bsd-3-clause |
xuewei4d/scikit-learn | examples/miscellaneous/plot_johnson_lindenstrauss_bound.py | 14 | 7785 | r"""
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected i... | bsd-3-clause |
MalkIPP/ipp_work | ipp_work/simulations/charges_deductibles.py | 1 | 3436 | # -*- coding: utf-8 -*-
"""
Created on Tue May 5 11:54:08 2015
@author: malkaguillot
"""
# -*- coding: utf-8 -*-
# OpenFisca -- A versatile microsimulation software
# By: OpenFisca Team <contact@openfisca.fr>
#
# Copyright (C) 2011, 2012, 2013, 2014, 2015 OpenFisca Team
# https://github.com/openfisca
#
# This file... | agpl-3.0 |
tkaitchuck/nupic | external/linux64/lib/python2.6/site-packages/matplotlib/artist.py | 69 | 33042 | from __future__ import division
import re, warnings
import matplotlib
import matplotlib.cbook as cbook
from transforms import Bbox, IdentityTransform, TransformedBbox, TransformedPath
from path import Path
## Note, matplotlib artists use the doc strings for set and get
# methods to enable the introspection methods of ... | gpl-3.0 |
riddhishb/ipython-notebooks | Poisson Editing/seamlesscloning.py | 1 | 1270 | import cv2
import numpy as np
import matplotlib.pyplot as plt
im_cloned = cv2.imread("stinkbug_cloned.png", cv2.IMREAD_GRAYSCALE)
im_mask = cv2.imread("stinkbug_cloned_mask.png", cv2.IMREAD_GRAYSCALE)
it = 500; # Set number of iterations
im_temp = im_cloned.copy()
im_seamless = im_temp.copy()
sigma = []
for i in ra... | gpl-3.0 |
nettorta/yandex-tank | yandextank/plugins/Phantom/tests/test_reader.py | 2 | 2081 | from threading import Event
import pandas as pd
from yandextank.common.util import FileMultiReader
from yandextank.plugins.Phantom.reader import PhantomReader, PhantomStatsReader, string_to_df_microsec
class TestPhantomReader(object):
def setup_class(self):
stop = Event()
self.multireader = File... | lgpl-2.1 |
jmargeta/scikit-learn | sklearn/tests/test_preprocessing.py | 3 | 25863 | import warnings
import numpy as np
import numpy.linalg as la
import scipy.sparse as sp
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils... | bsd-3-clause |
nhuntwalker/astroML | book_figures/chapter5/fig_posterior_gaussgauss.py | 3 | 4803 | """
Gaussian Distribution with Gaussian Errors
------------------------------------------
Figure 5.8
The solid lines show marginalized posterior pdfs for :math:`\mu` (left) and
:math:`\sigma` (right) for a Gaussian distribution with heteroscedastic
Gaussian measurement errors (i.e., integrals over :math:`\sigma` and
:... | bsd-2-clause |
phageParser/phageParser | populate.py | 3 | 6935 | #!/usr/bin/env python
import argparse
import os
import pickle
import pandas
import requests
from Bio import Entrez, SeqIO
from lxml import html, etree
from tqdm import tqdm
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'phageAPI.settings')
import django
django.setup()
from util.acc import read_accession_file
fro... | mit |
roxyboy/scikit-learn | sklearn/metrics/tests/test_common.py | 83 | 41144 | from __future__ import division, print_function
from functools import partial
from itertools import product
import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_multilabel_classification
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils.multiclass import type_of_target
fro... | bsd-3-clause |
LingboTang/LearningFiles | load_dat.py | 1 | 7385 | import os
import sys
import re
import numpy as np
import random
import getopt
import time
import matplotlib.pyplot as plt
from scipy.interpolate import splrep, pchip, splmake, splev, spline, interp1d
import signal
# ========================================= Exception ================================================= #... | apache-2.0 |
alexeyum/scikit-learn | sklearn/decomposition/dict_learning.py | 42 | 46134 | """ Dictionary learning
"""
from __future__ import print_function
# Author: Vlad Niculae, Gael Varoquaux, Alexandre Gramfort
# License: BSD 3 clause
import time
import sys
import itertools
from math import sqrt, ceil
import numpy as np
from scipy import linalg
from numpy.lib.stride_tricks import as_strided
from ..b... | bsd-3-clause |
warmspringwinds/scikit-image | doc/examples/plot_watershed.py | 4 | 2335 | """
======================
Watershed segmentation
======================
The watershed is a classical algorithm used for **segmentation**, that
is, for separating different objects in an image.
Starting from user-defined markers, the watershed algorithm treats
pixels values as a local topography (elevation). The algo... | bsd-3-clause |
xuewei4d/scikit-learn | examples/release_highlights/plot_release_highlights_0_22_0.py | 10 | 10186 | """
========================================
Release Highlights for scikit-learn 0.22
========================================
.. currentmodule:: sklearn
We are pleased to announce the release of scikit-learn 0.22, which comes
with many bug fixes and new features! We detail below a few of the major
features of this r... | bsd-3-clause |
zorroblue/scikit-learn | benchmarks/bench_plot_parallel_pairwise.py | 127 | 1270 | # Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD 3 clause
import time
import matplotlib.pyplot as plt
from sklearn.utils import check_random_state
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.metrics.pairwise import pairwise_kernels
def plot(func):
random_state = check_rand... | bsd-3-clause |
wogsland/QSTK | Bin/Data_CSV.py | 5 | 3301 | #File to read the data from mysql and push into CSV.
# Python imports
import datetime as dt
import csv
import copy
import os
import pickle
# 3rd party imports
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# QSTK imports
from QSTK.qstkutil import qsdateutil as du
import QSTK.qstkutil.DataEvol... | bsd-3-clause |
arokem/nipy | nipy/labs/viz_tools/maps_3d.py | 3 | 14510 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
3D visualization of activation maps using Mayavi
"""
# Author: Gael Varoquaux <gael dot varoquaux at normalesup dot org>
# License: BSD
import os
import tempfile
# Standard scientific libraries impo... | bsd-3-clause |
Lab603/PicEncyclopedias | jni-build/jni/include/tensorflow/contrib/learn/python/learn/tests/dataframe/in_memory_source_test.py | 30 | 3738 | # Copyright 2015 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... | mit |
nok/sklearn-porter | sklearn_porter/estimator/classifier/AdaBoostClassifier/__init__.py | 1 | 12399 | # -*- coding: utf-8 -*-
import os
from json import encoder
from json import dumps
from sklearn.tree.tree import DecisionTreeClassifier
from sklearn_porter.estimator.classifier.Classifier import Classifier
class AdaBoostClassifier(Classifier):
"""
See also
--------
sklearn.ensemble.AdaBoostClassifie... | mit |
htimko/ArcPIC | pic2d/GLEanalysis/2Dpic_current_PerProcess.py | 1 | 17220 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2010-2015 CERN and Helsinki Institute of Physics.
# This software is distributed under the terms of the
# GNU General Public License version 3 (GPL Version 3),
# copied verbatim in the file LICENCE.md. In applying this
# license, CERN does not waive the privil... | gpl-3.0 |
andrewbolster/thesis | posters/PDW-15/figures/figgen.py | 1 | 1760 |
import matplotlib.pyplot as plt
import networkx as nx
import scipy.constants
w=5
cut = 1.06
nodedict = {"A":(25,35),"B":(30,30),"C":(25,25),"D":(35,25),"E":(35,35)}
direct = {'type':'Direct', 'color':'g', 'weight':4}
indirect = {'type':'Indirect', 'color':'r', 'weight':2}
recommend = {'type':'Recommendation', 'colo... | epl-1.0 |
poojavade/Genomics_Docker | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/ipython-2.2.0-py2.7.egg/IPython/qt/console/rich_ipython_widget.py | 5 | 14894 | #-----------------------------------------------------------------------------
# Copyright (c) 2010, IPython Development Team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
#--------------------------------------------------... | apache-2.0 |
aetilley/scikit-learn | sklearn/linear_model/tests/test_ridge.py | 130 | 22974 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
great-expectations/great_expectations | tests/data_context/test_data_context_config_ui.py | 1 | 52921 | import copy
import os
from typing import Dict, Optional
import pytest
from great_expectations import DataContext
from great_expectations.data_context import BaseDataContext
from great_expectations.data_context.types.base import (
BaseStoreBackendDefaults,
DatabaseStoreBackendDefaults,
DataContextConfig,
... | apache-2.0 |
ajaech/username_analytics | MyClassifier.py | 1 | 9130 | import code
import collections
import gzip
import math
import morfessor
import numpy
import pandas
import random
import segmenter
import sklearn.metrics
from matplotlib import pylab
random.seed(666)
model = None
def LoadUsernames(filename, maxload=400000000):
if filename.endswith('.gz'):
f = gzip.open(filename... | gpl-2.0 |
fredhusser/scikit-learn | sklearn/tests/test_base.py | 216 | 7045 | # Author: Gael Varoquaux
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing impo... | bsd-3-clause |
Adai0808/scikit-learn | examples/classification/plot_lda.py | 164 | 2224 | """
====================================================================
Normal and Shrinkage Linear Discriminant Analysis for classification
====================================================================
Shows how shrinkage improves classification.
"""
from __future__ import division
import numpy as np
import... | bsd-3-clause |
dsm054/pandas | asv_bench/benchmarks/io/stata.py | 5 | 1526 | import numpy as np
from pandas import DataFrame, date_range, read_stata
import pandas.util.testing as tm
from ..pandas_vb_common import BaseIO
class Stata(BaseIO):
params = ['tc', 'td', 'tm', 'tw', 'th', 'tq', 'ty']
param_names = ['convert_dates']
def setup(self, convert_dates):
self.fname = '_... | bsd-3-clause |
ngoix/OCRF | examples/linear_model/plot_lasso_and_elasticnet.py | 73 | 2074 | """
========================================
Lasso and Elastic Net for Sparse Signals
========================================
Estimates Lasso and Elastic-Net regression models on a manually generated
sparse signal corrupted with an additive noise. Estimated coefficients are
compared with the ground-truth.
"""
print(... | bsd-3-clause |
bavardage/statsmodels | statsmodels/sandbox/panel/mixed.py | 4 | 20977 | """
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 |
hhain/sdap17 | notebooks/pawel_ueb2/filters.py | 1 | 2457 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from features import *
from utility import *
## filter functions
def distortion_filter(data, column_key = "_ifft_0", label = 'target', std_thresh = 100.):
"""
replaces distortions in the data by checking for high std
replaceme... | mit |
neurosnap/mudicom | mudicom/image.py | 1 | 4474 | # -*- coding: utf-8 -*-
"""
mudicom.image
~~~~~~~~~~~~~
Primary image module that converts DICOM pixel data into a numpy array
as well as saving the image using Matplotlib or Pillow.
"""
import os.path
import sys
import numpy
import gdcm
class Image(object):
""" This class attempts to extract an i... | mit |
valexandersaulys/airbnb_kaggle_contest | venv/lib/python3.4/site-packages/sklearn/ensemble/tests/test_gradient_boosting.py | 6 | 39791 | """
Testing for the gradient boosting module (sklearn.ensemble.gradient_boosting).
"""
import warnings
import numpy as np
from itertools import product
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import coo_matrix
from sklearn import datasets
from sklearn.base import clo... | gpl-2.0 |
frank-tancf/scikit-learn | sklearn/utils/tests/test_seq_dataset.py | 47 | 2486 | # Author: Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
#
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.seq_dataset import ArrayDataset, CSRDataset
from sklearn.datasets import load_iris
from numpy.testing import assert_array_equal
from nose.tools import assert_equal
iris =... | bsd-3-clause |
lbeltrame/mnegri-ov170 | programs/extract_shared_mutations.py | 1 | 20417 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 2014 Luca Beltrame <luca.beltrame@marionegri.it>
#
# This program 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,... | gpl-2.0 |
evgchz/scikit-learn | sklearn/ensemble/tests/test_weight_boosting.py | 9 | 15843 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_array_equal, assert_array_less
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_raises, assert_rais... | bsd-3-clause |
BryanCutler/spark | python/pyspark/pandas/tests/test_config.py | 1 | 6435 | #
# 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 |
Extintor/piva | practica4/p4script5.py | 1 | 1108 | # -*- coding: utf-8 -*-
"""
Created on Wed Apr 6 18:04:51 2016
@author: paul
"""
from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
def turn_to_grayscale(img):
try:
red = img[:,:,0]
green = img[:,:,1]
blue = img[:,:,2]
img = np.uint8(np.add(np.add(... | gpl-3.0 |
ltiao/networkx | examples/graph/unix_email.py | 26 | 2678 | #!/usr/bin/env python
"""
Create a directed graph, allowing multiple edges and self loops, from
a unix mailbox. The nodes are email addresses with links
that point from the sender to the recievers. The edge data
is a Python email.Message object which contains all of
the email message data.
This example shows the po... | bsd-3-clause |
automl/paramsklearn | tests/components/feature_preprocessing/test_select_percentile_classification.py | 1 | 4693 | import unittest
import numpy as np
import scipy.sparse
import sklearn.preprocessing
from ParamSklearn.components.feature_preprocessing.select_percentile_classification import SelectPercentileClassification
from ParamSklearn.util import _test_preprocessing, get_dataset
class SelectPercentileClassificationTest(unitte... | bsd-3-clause |
Myasuka/scikit-learn | examples/mixture/plot_gmm.py | 248 | 2817 | """
=================================
Gaussian Mixture Model Ellipsoids
=================================
Plot the confidence ellipsoids of a mixture of two Gaussians with EM
and variational Dirichlet process.
Both models have access to five components with which to fit the
data. Note that the EM model will necessari... | bsd-3-clause |
wlamond/scikit-learn | examples/mixture/plot_concentration_prior.py | 16 | 5657 | """
========================================================================
Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture
========================================================================
This example plots the ellipsoids obtained from a toy dataset (mixture of three
Gaussians) fitte... | bsd-3-clause |
matbra/bokeh | bokeh/tests/test_protocol.py | 42 | 3959 | from __future__ import absolute_import
import unittest
from unittest import skipIf
import numpy as np
try:
import pandas as pd
is_pandas = True
except ImportError as e:
is_pandas = False
class TestBokehJSONEncoder(unittest.TestCase):
def setUp(self):
from bokeh.protocol import BokehJSONEnc... | bsd-3-clause |
diana-hep/carl | tests/distributions/test_exponential.py | 1 | 1703 | # Carl is free software; you can redistribute it and/or modify it
# under the terms of the Revised BSD License; see LICENSE file for
# more details.
import numpy as np
import scipy.stats as st
from numpy.testing import assert_array_almost_equal
from sklearn.utils import check_random_state
from carl.distributions imp... | bsd-3-clause |
bert9bert/statsmodels | statsmodels/tsa/filters/bk_filter.py | 4 | 3244 | from __future__ import absolute_import
import numpy as np
from scipy.signal import fftconvolve
from ._utils import _maybe_get_pandas_wrapper
def bkfilter(X, low=6, high=32, K=12):
"""
Baxter-King bandpass filter
Parameters
----------
X : array-like
A 1 or 2d ndarray. If 2d, variables are ... | bsd-3-clause |
RomainBrault/scikit-learn | sklearn/neighbors/__init__.py | 71 | 1025 | """
The :mod:`sklearn.neighbors` module implements the k-nearest neighbors
algorithm.
"""
from .ball_tree import BallTree
from .kd_tree import KDTree
from .dist_metrics import DistanceMetric
from .graph import kneighbors_graph, radius_neighbors_graph
from .unsupervised import NearestNeighbors
from .classification impo... | bsd-3-clause |
pdebuyl/RMPCDMD | experiments/03-single-janus/plot_planar.py | 2 | 1110 | #!/usr/bin/env python
"""
Display the planar concentration and velocity fields of a RMPCDMD simulation.
"""
import argparse
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('file', help="H5MD file")
parser.add_argument('--species', type=int, default=0)
args = parser.parse_args()
import h5py
i... | bsd-3-clause |
linksuccess/linksuccess | parsingframework/structural_statistics.py | 1 | 28185 | from __future__ import division
import numpy as np
from graph_tool.all import *
from matplotlib import pyplot as plt
import pickle
import powerlaw
import fitpowerlaw as fp
from wsd.database import MySQLDatabase
from graph_tool.all import *
from conf import *
from matplotlib import style
style.use('acm-2col-bmh')
i... | mit |
MartinSavc/scikit-learn | sklearn/feature_extraction/text.py | 110 | 50157 | # -*- coding: utf-8 -*-
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Robert Layton <robertlayton@gmail.com>
# Jochen Wersdörfer <jochen@wersdoerfer.de>
# Roman Sinayev <roman.sinayev@gma... | bsd-3-clause |
murali-munna/scikit-learn | benchmarks/bench_sgd_regression.py | 283 | 5569 | """
Benchmark for SGD regression
Compares SGD regression against coordinate descent and Ridge
on synthetic data.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
# License: BSD 3 clause
import numpy as np
import pylab as pl
import gc
from time import time
from sklearn.linear_model i... | bsd-3-clause |
yerkesobservatory/seo | modules/resource/server.py | 1 | 4061 | import io
import flask
import base64
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from typing import Dict
from routines import plots
from config import config
import logging
import colorlog
#from flask_cors import CORS
class ResourceServer(object):
""" This class is a REST endpoint desi... | gpl-3.0 |
cinepost/Copperfield_FX | copper/cop/cop_file.py | 1 | 10021 | import matplotlib.image
from PIL import Image
import pyopencl as cl
import numpy
import os
import logging
from copper.core.op.node_type import NodeTypeBase
from copper.core.op.node_type_category import Cop2NodeTypeCategory
from copper.core.op.op_data_socket import OP_DataSocket
from copper.core.data.image_data impor... | unlicense |
mortada/scipy | scipy/integrate/quadrature.py | 25 | 27849 | from __future__ import division, print_function, absolute_import
__all__ = ['fixed_quad','quadrature','romberg','trapz','simps','romb',
'cumtrapz','newton_cotes']
from scipy.special.orthogonal import p_roots
from scipy.special import gammaln
from numpy import sum, ones, add, diff, isinf, isscalar, \
a... | bsd-3-clause |
RealTimeWeb/datasets | preprocess/energy/process.py | 1 | 3434 | import pandas as pd
import json
import states
from tqdm import tqdm
df = pd.read_csv('Complete_SEDS.csv')
codes = df['MSN'].unique()
sources = [c[:2] for c in codes]
uses = [c[2:4] for c in codes]
purposes = [c[4] for c in codes]
#print(list(sorted(set(sources))))
#print(list(sorted(set(uses))))
#print(list(sorted(s... | gpl-2.0 |
e-mission/e-mission-server | bin/analysis/get_app_analytics.py | 3 | 4793 | from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from builtins import *
import logging
import emission.core.get_database as edb
import emission.stora... | bsd-3-clause |
wesm/ibis | ibis/sql/sqlite/tests/test_functions.py | 1 | 14619 | # Copyright 2015 Cloudera Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, so... | apache-2.0 |
choldgraf/download | setup.py | 1 | 1959 | #! /usr/bin/env python
#
# Copyright (C) 2015 Chris Holdgraf
# <choldgraf@gmail.com>
#
# Adapted from MNE-Python
import os
from setuptools import setup
descr = """A quick module to help downloading files using python."""
with open("./download/__init__.py", "r") as ff:
lines = ff.readlines()
for line in lines... | mit |
ceholden/yatsm | yatsm/utils.py | 1 | 7712 | from __future__ import division
from datetime import datetime as dt
import fnmatch
import os
import re
import sys
import numpy as np
import pandas as pd
import six
try:
from scandir import walk
except:
from os import walk
from .log_yatsm import logger
# JOB SPECIFIC FUNCTIONS
def distribute_jobs(job_numbe... | mit |
biokit/biokit | biokit/viz/corrplot.py | 1 | 18115 | """.. rubric:: Corrplot utilities
:author: Thomas Cokelaer
:references: http://cran.r-project.org/web/packages/corrplot/vignettes/corrplot-intro.html
"""
import string
from colormap import cmap_builder
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.patches import Ellipse... | bsd-2-clause |
sniemi/SamPy | sandbox/webserver/cgi-bin/pages.py | 1 | 15221 | '''HTML Pages'''
import os, sys, glob
import time, datetime
import matplotlib
from matplotlib import dates as MD
from matplotlib import ticker as MT
matplotlib.use('Agg')
import numpy as N
import pylab as P
from math import *
def page1(output, camera, year, response):
# Introduction
print "<html>"
print "... | bsd-2-clause |
xcgoner/dist-mxnet | example/svm_mnist/svm_mnist.py | 44 | 4094 | # 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 u... | apache-2.0 |
btabibian/scikit-learn | sklearn/feature_extraction/hashing.py | 5 | 6830 | # Author: Lars Buitinck
# License: BSD 3 clause
import numbers
import warnings
import numpy as np
import scipy.sparse as sp
from . import _hashing
from ..base import BaseEstimator, TransformerMixin
def _iteritems(d):
"""Like d.iteritems, but accepts any collections.Mapping."""
return d.iteritems() if hasat... | bsd-3-clause |
QuantCrimAtLeeds/PredictCode | open_cp/scripted/analysis.py | 1 | 9254 | """
analysis.py
~~~~~~~~~~~
Various routines to perform standard analysis, and/or visualisation, tasks.
"""
import matplotlib.pyplot as _plt
import matplotlib.collections as _mpl_collections
import descartes as _descartes
import csv as _csv
import collections as _collections
import scipy.stats as _stats
import open_c... | artistic-2.0 |
WillieMaddox/numpy | doc/example.py | 81 | 3581 | """This is the docstring for the example.py module. Modules names should
have short, all-lowercase names. The module name may have underscores if
this improves readability.
Every module should have a docstring at the very top of the file. The
module's docstring may extend over multiple lines. If your docstring doe... | bsd-3-clause |
mne-tools/mne-tools.github.io | 0.21/_downloads/a5d4e64d0843ff17526c0588f9967f97/plot_covariance_whitening_dspm.py | 16 | 6905 | """
.. _ex-covariance-whitening-dspm:
===================================================
Demonstrate impact of whitening on source estimates
===================================================
This example demonstrates the relationship between the noise covariance
estimate and the MNE / dSPM source amplitudes. It c... | bsd-3-clause |
mcdeoliveira/pyctrl | examples/simulated_motor_2.py | 3 | 3579 | #!/usr/bin/env python3
def main():
# import python's standard math module and numpy
import math, numpy, sys
# import Controller and other blocks from modules
from pyctrl.timer import Controller
from pyctrl.block import Interp, Logger, Constant
from pyctrl.block.system import System, Diffe... | apache-2.0 |
georgid/SourceFilterContoursMelody | smstools/software/transformations_interface/hpsMorph_function.py | 24 | 7354 | # 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.realpath... | gpl-3.0 |
pearsonlab/nipype | doc/conf.py | 6 | 8363 | # emacs: -*- coding: utf-8; mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set fileencoding=utf-8 ft=python sts=4 ts=4 sw=4 et:
#
# nipype documentation build configuration file, created by
# sphinx-quickstart on Mon Jul 20 12:30:18 2009.
#
# This file is execfile()d with the current directory set t... | bsd-3-clause |
initNirvana/Easyphotos | env/lib/python3.4/site-packages/IPython/config/loader.py | 4 | 29399 | # encoding: utf-8
"""A simple configuration system."""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
import argparse
import copy
import logging
import os
import re
import sys
import json
from ast import literal_eval
from IPython.utils.path import filefind, get_i... | mit |
Nikea/scikit-xray | doc/sphinxext/plot_generator.py | 8 | 10150 | """
Sphinx plugin to run example scripts and create a gallery page.
Taken from seaborn project, which is turn was lightly
modified from the mpld3 project.
"""
from __future__ import division
import os
import os.path as op
import re
import glob
import token
import tokenize
import shutil
import json
import matplotlib
... | bsd-3-clause |
neogis-de/PPPP_utilities | pointcloud/patch_to_raster.py | 2 | 8028 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 23 16:38:01 2015
@author: remi
"""
import pg_pointcloud_classes as pc
reload(pc)
def translatePointArray(pt_arr, schema, pixel_size):
"""this function simply extract X,Y,Z and translate x and y and compute and allocate pixel array"""
import numpy as np
import... | lgpl-3.0 |
olinguyen/shogun | examples/undocumented/python/graphical/interactive_clustering_demo.py | 5 | 11271 | """
Shogun demo, based on PyQT Demo by Eli Bendersky
Christian Widmer
Soeren Sonnenburg
License: GPLv3
"""
import numpy
import sys, os, csv
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import matplotlib
from matplotlib.colorbar import make_axes, Colorbar
from matplotlib.backends.backend_qt4agg import FigureCa... | gpl-3.0 |
domagalski/pocketcorr | scripts/pocketcorr_adc.py | 1 | 9505 | #!/usr/bin/env python2
################################################################################
## This script is for simple ADC caputer to test the a pocket correlator.
## Copyright (C) 2014 Rachel Simone Domagalski: domagalski@berkeley.edu
##
## This program is free software: you can redistribute it and/or ... | gpl-3.0 |
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