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 |
|---|---|---|---|---|---|
lpeska/BRDTI | cmf.py | 1 | 4613 | '''
We base the CMF implementation on the one from PyDTI project, https://github.com/stephenliu0423/PyDTI, changes were made to the evaluation procedure
[1] X. Zheng, H. Ding, H. Mamitsuka, and S. Zhu, "Collaborative matrix factorization with multiple similarities for predicting drug-target interaction", KDD, 2013.
... | gpl-2.0 |
jniediek/mne-python | mne/tests/test_label.py | 3 | 33801 | import os
import os.path as op
import shutil
import glob
import warnings
import numpy as np
from scipy import sparse
from numpy.testing import assert_array_equal, assert_array_almost_equal
from nose.tools import assert_equal, assert_true, assert_false, assert_raises
from mne.datasets import testing
from mne import (... | bsd-3-clause |
thilbern/scikit-learn | sklearn/metrics/tests/test_common.py | 2 | 42318 | 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, MultiLabelBinarizer
from sklearn.utils.multiclass impo... | bsd-3-clause |
shangwuhencc/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 |
metpy/MetPy | examples/meteogram_metpy.py | 6 | 8767 | # Copyright (c) 2017 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Meteogram
=========
Plots time series data as a meteogram.
"""
import datetime as dt
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from metpy.ca... | bsd-3-clause |
WillieMaddox/numpy | numpy/core/function_base.py | 7 | 6565 | from __future__ import division, absolute_import, print_function
__all__ = ['logspace', 'linspace']
from . import numeric as _nx
from .numeric import result_type, NaN, shares_memory, MAY_SHARE_BOUNDS, TooHardError
def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None):
"""
Return evenly... | bsd-3-clause |
totalgood/nlpia | src/nlpia/mavis_greetings.py | 1 | 1246 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Constants and discovered values, like path to current installation of pug-nlp."""
# -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals, division, absolute_import
from builtins import (bytes, dict, int, list, object, range, str, # noqa
asci... | mit |
DSLituiev/scikit-learn | sklearn/neighbors/graph.py | 14 | 6609 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
import warnings
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def _check_params(X, metric, p, metric_... | bsd-3-clause |
wwf5067/statsmodels | statsmodels/examples/tsa/ex_arma_all.py | 34 | 1982 |
from __future__ import print_function
import numpy as np
from numpy.testing import assert_almost_equal
import matplotlib.pyplot as plt
import statsmodels.sandbox.tsa.fftarma as fa
from statsmodels.tsa.descriptivestats import TsaDescriptive
from statsmodels.tsa.arma_mle import Arma
x = fa.ArmaFft([1, -0.5], [1., 0.4]... | bsd-3-clause |
abhijeetmote/python_stuff | to_csv.py | 1 | 1381 | import xml.etree.ElementTree as ET
import os
import sys
import fnmatch
import csv
import pdb
import glob
import tempfile
import shutil
import gzip
import datetime
import tarfile
import time
import pandas as pd
import pdb
file_name = "/home/abhijeet/test/file.xml"
output = "/home/abhijeet/test/file.csv"
#Handeling unpar... | gpl-3.0 |
hitszxp/scikit-learn | benchmarks/bench_plot_nmf.py | 206 | 5890 | """
Benchmarks of Non-Negative Matrix Factorization
"""
from __future__ import print_function
from collections import defaultdict
import gc
from time import time
import numpy as np
from scipy.linalg import norm
from sklearn.decomposition.nmf import NMF, _initialize_nmf
from sklearn.datasets.samples_generator import... | bsd-3-clause |
gergopokol/renate-od | visualization/profiles.py | 1 | 9125 | import matplotlib.pyplot
import utility
from matplotlib.backends.backend_pdf import PdfPages
import datetime
from crm_solver.atomic_db import RenateDB
class BeamletProfiles:
def __init__(self, param_path='output/beamlet/beamlet_test.xml', key=['profiles']):
self.param_path = param_path
self.param ... | lgpl-3.0 |
anve8004/trading-with-python | lib/cboe.py | 76 | 4433 | # -*- coding: utf-8 -*-
"""
toolset working with cboe data
@author: Jev Kuznetsov
Licence: BSD
"""
from datetime import datetime, date
import urllib2
from pandas import DataFrame, Index
from pandas.core import datetools
import numpy as np
import pandas as pd
def monthCode(month):
"""
perfo... | bsd-3-clause |
fberanizo/sin5006 | tests/optimization/utils.py | 1 | 2030 | # -*- coding: utf-8 -*-
import numpy, matplotlib.pyplot, pandas, seaborn
def plot(execution_info, title='', description=''):
for generation_info in execution_info:
x = numpy.arange(1, len(generation_info)+1)
max = numpy.asarray(map(lambda individual: individual["max"], generation_info))
a... | bsd-2-clause |
MrNuggelz/sklearn-glvq | sklearn_lvq/tests/test_glvq.py | 1 | 10494 | import numpy as np
from .. import GlvqModel
from .. import GrlvqModel
from .. import GmlvqModel
from .. import GrmlvqModel
from .. import LgmlvqModel
from sklearn.utils.testing import assert_greater, assert_raise_message, \
assert_allclose
from sklearn import datasets
from sklearn.utils import check_random_state
... | bsd-3-clause |
manashmndl/scikit-learn | sklearn/neighbors/graph.py | 208 | 7031 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
import warnings
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def _check_params(X, metric, p, metric_... | bsd-3-clause |
zymsys/sms-tools | lectures/07-Sinusoidal-plus-residual-model/plots-code/hprModelFrame.py | 22 | 2847 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import math
from scipy.fftpack import fft, ifft, fftshift
import sys, os, functools, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel a... | agpl-3.0 |
robin-lai/scikit-learn | examples/decomposition/plot_pca_vs_fa_model_selection.py | 142 | 4467 | """
===============================================================
Model selection with Probabilistic PCA and Factor Analysis (FA)
===============================================================
Probabilistic PCA and Factor Analysis are probabilistic models.
The consequence is that the likelihood of new data can be u... | bsd-3-clause |
voxlol/scikit-learn | benchmarks/bench_tree.py | 297 | 3617 | """
To run this, you'll need to have installed.
* scikit-learn
Does two benchmarks
First, we fix a training set, increase the number of
samples to classify and plot number of classified samples as a
function of time.
In the second benchmark, we increase the number of dimensions of the
training set, classify a sam... | bsd-3-clause |
Winand/pandas | pandas/tests/scalar/test_period_asfreq.py | 15 | 35624 | import pandas as pd
from pandas import Period, offsets
from pandas.util import testing as tm
from pandas.tseries.frequencies import _period_code_map
class TestFreqConversion(object):
"""Test frequency conversion of date objects"""
def test_asfreq_corner(self):
val = Period(freq='A', year=2007)
... | bsd-3-clause |
larsmans/scikit-learn | examples/bicluster/plot_spectral_biclustering.py | 403 | 2011 | """
=============================================
A demo of the Spectral Biclustering algorithm
=============================================
This example demonstrates how to generate a checkerboard dataset and
bicluster it using the Spectral Biclustering algorithm.
The data is generated with the ``make_checkerboard`... | bsd-3-clause |
jerome-nexedi/pulp-or | doc/source/_static/plotter.py | 4 | 1267 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
from matplotlib import rc
rc('text', usetex=True)
rc('font', family='serif')
def plot_interval(a,c,x_left, x_right,i, fbound):
lh = c*(1-a[0])
rh = c*(1+a[1])
x=arange(x_left, x_right+1)
y=0*x
arrow_r = Arrow(c,0, c*a[1],0,0.2)
arrow_l = Arrow(... | mit |
rgommers/statsmodels | statsmodels/miscmodels/try_mlecov.py | 33 | 7414 | '''Multivariate Normal Model with full covariance matrix
toeplitz structure is not exploited, need cholesky or inv for toeplitz
Author: josef-pktd
'''
from __future__ import print_function
import numpy as np
#from scipy import special #, stats
from scipy import linalg
from scipy.linalg import norm, toeplitz
import ... | bsd-3-clause |
pmelchior/shear-stacking-tests | run_quadrant_check.py | 2 | 6519 | #!/bin/env python
import json, errno
import healpy as hp
import healpix_util as hu
import numpy as np
from sys import argv
from shear_stacking import *
def makeDensityMap(outfile, config, shapes, nside=512):
ipix = hp.ang2pix(nside, (90-shapes[config['shape_dec_key']])/180*np.pi, shapes[config['shape_ra_key']]/18... | mit |
infoelliex/addons-yelizariev | import_custom/import_custom.py | 16 | 10226 | # -*- coding: utf-8 -*-
import logging
import os
_logger = logging.getLogger(__name__)
try:
import MySQLdb
import MySQLdb.cursors
except ImportError:
pass
from openerp.addons.import_framework.import_base import import_base
try:
from pandas import merge, DataFrame
except ImportError:
pass
from ope... | lgpl-3.0 |
plissonf/scikit-learn | sklearn/decomposition/dict_learning.py | 104 | 44632 | """ 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 |
jaeilepp/mne-python | mne/viz/tests/test_utils.py | 3 | 4893 | # Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: Simplified BSD
import os.path as op
import warnings
import numpy as np
from nose.tools import assert_true, assert_raises
from numpy.testing import assert_allclose
from mne.viz.utils import (compare_fiff, _fake_click, _compute_scaling... | bsd-3-clause |
cybernet14/scikit-learn | sklearn/utils/multiclass.py | 45 | 12390 |
# Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
#
# License: BSD 3 clause
"""
Multi-class / multi-label utility function
==========================================
"""
from __future__ import division
from collections import Sequence
from itertools import chain
from scipy.sparse import issparse
from scipy.sparse.... | bsd-3-clause |
cython-testbed/pandas | pandas/io/formats/console.py | 3 | 4533 | """
Internal module for console introspection
"""
import sys
import locale
from pandas.io.formats.terminal import get_terminal_size
# -----------------------------------------------------------------------------
# Global formatting options
_initial_defencoding = None
def detect_console_encoding():
"""
Try t... | bsd-3-clause |
robin-lai/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 |
adammenges/statsmodels | statsmodels/sandbox/examples/thirdparty/ex_ratereturn.py | 33 | 4394 | # -*- coding: utf-8 -*-
"""Playing with correlation of DJ-30 stock returns
this uses pickled data that needs to be created with findow.py
to see graphs, uncomment plt.show()
Created on Sat Jan 30 16:30:18 2010
Author: josef-pktd
"""
import numpy as np
import matplotlib.finance as fin
import matplotlib.pyplot as plt... | bsd-3-clause |
lazywei/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 |
fyffyt/scikit-learn | sklearn/gaussian_process/gaussian_process.py | 78 | 34552 | # -*- coding: utf-8 -*-
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# (mostly translation, see implementation details)
# Licence: BSD 3 clause
from __future__ import print_function
import numpy as np
from scipy import linalg, optimize
from ..base import BaseEstimator, RegressorMixin
from ..metrics... | bsd-3-clause |
nmartensen/pandas | doc/sphinxext/numpydoc/plot_directive.py | 89 | 20530 | """
A special directive for generating a matplotlib plot.
.. warning::
This is a hacked version of plot_directive.py from Matplotlib.
It's very much subject to change!
Usage
-----
Can be used like this::
.. plot:: examples/example.py
.. plot::
import matplotlib.pyplot as plt
plt.plot... | bsd-3-clause |
tbenthompson/codim1 | test/test_elastic_kernel.py | 1 | 13129 | from codim1.fast_lib import DisplacementKernel,\
TractionKernel,\
AdjointTractionKernel,\
HypersingularKernel,\
RegularizedHypersingularKernel,\
SemiRegularizedHypersingularKernel,... | mit |
jorge2703/scikit-learn | examples/covariance/plot_outlier_detection.py | 235 | 3891 | """
==========================================
Outlier detection with several methods.
==========================================
When the amount of contamination is known, this example illustrates two
different ways of performing :ref:`outlier_detection`:
- based on a robust estimator of covariance, which is assumin... | bsd-3-clause |
konder/tushare | tushare/datayes/fundamental.py | 16 | 18026 | # -*- coding:utf-8 -*-
"""
通联数据
Created on 2015/08/24
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
from pandas.compat import StringIO
import pandas as pd
from tushare.util import vars as vs
from tushare.util.common import Client
from tushare.util import upass as up
class Fundamental():
... | bsd-3-clause |
bzcheeseman/phys211 | Alex/Relativistic Electron Dispersion/plotter.py | 1 | 3556 | from scipy import optimize
import numpy as np
import matplotlib.pyplot as plt
a = 1.42372210086
aerr = 0.00295712984228
b = 0.0770992785753
berr = 0.00969212354148
cedges = np.array([338,234,749,279,614,186,634,773])
cedgerr = np.array([3,3,3,3,3,4,3,4])
cpeaks = np.array([469,353,900,405,758,296,782,922])
cperr = np... | lgpl-3.0 |
pjryan126/solid-start-careers | store/api/zillow/venv/lib/python2.7/site-packages/pandas/sparse/scipy_sparse.py | 18 | 5516 | """
Interaction with scipy.sparse matrices.
Currently only includes SparseSeries.to_coo helpers.
"""
from pandas.core.index import MultiIndex, Index
from pandas.core.series import Series
from pandas.compat import OrderedDict, lmap
def _check_is_partition(parts, whole):
whole = set(whole)
parts = [set(x) for ... | gpl-2.0 |
exxeleron/qPython | doc/source/conf.py | 1 | 8654 | # -*- coding: utf-8 -*-
#
# qPython documentation build configuration file, created by
# sphinx-quickstart on Tue Sep 09 07:11:15 2014.
#
# 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.
#
# A... | apache-2.0 |
roxyboy/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 |
h2educ/scikit-learn | sklearn/linear_model/tests/test_ridge.py | 68 | 23597 | 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 |
fredhusser/scikit-learn | examples/model_selection/grid_search_digits.py | 227 | 2665 | """
============================================================
Parameter estimation using grid search with cross-validation
============================================================
This examples shows how a classifier is optimized by cross-validation,
which is done using the :class:`sklearn.grid_search.GridSearc... | bsd-3-clause |
MMaus/mutils | libshai/phaser.py | 1 | 17012 | from numpy import *
from util import *
from scipy import signal
import warnings
from exceptions import Warning
"""
The phaser module provides an implementation of the phase estimation algorithm
of "Estimating the phase of synchronized oscillators";
S. Revzen & J. M. Guckenheimer; Phys. Rev. E; 2008, v. 78, pp. 051... | gpl-2.0 |
marcsans/cnn-physics-perception | phy/lib/python2.7/site-packages/matplotlib/fontconfig_pattern.py | 8 | 6538 | """
A module for parsing and generating fontconfig patterns.
See the `fontconfig pattern specification
<http://www.fontconfig.org/fontconfig-user.html>`_ for more
information.
"""
# This class is defined here because it must be available in:
# - The old-style config framework (:file:`rcsetup.py`)
# - The traits-b... | mit |
majetideepak/arrow | python/pyarrow/parquet.py | 1 | 51904 | # 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 |
sebp/scikit-survival | sksurv/svm/naive_survival_svm.py | 1 | 7047 | # 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, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# bu... | gpl-3.0 |
holdenk/spark | python/pyspark/sql/tests/test_pandas_udf_typehints.py | 22 | 9603 | #
# 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 |
pli1988/portfolioFactory | portfolioFactory/metrics/retMetrics.py | 1 | 2342 | """
retMetrics is a module that contains a collection of functions to compute
return metrics on Pandas timeseries.
Author: Peter Li
"""
import pandas as pd
import numpy as np
from ..utils import utils as utils
from ..utils import customExceptions as customExceptions
def main():
pass
def averageHorizonReturn(da... | mit |
vdods/heisenberg | attic/shooting_method_2.py | 1 | 15304 | import abc
import itertools
import library.monte_carlo
import numpy as np
import scipy.integrate
import scipy.linalg
import sympy as sp
import time
import vorpy.symbolic
"""
Notes
Define "return map" R : T^* Q -> T^* Q (really R^3xR^3 -> R^3xR^3, because it's coordinate dependent):
R(q,p) is defined as the closest po... | mit |
btabibian/scikit-learn | sklearn/cluster/birch.py | 11 | 23640 | # Authors: Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Joel Nothman <joel.nothman@gmail.com>
# License: BSD 3 clause
from __future__ import division
import warnings
import numpy as np
from scipy import sparse
from math import sqrt
fro... | bsd-3-clause |
meduz/scikit-learn | sklearn/decomposition/tests/test_dict_learning.py | 46 | 9267 | import numpy as np
from sklearn.exceptions import ConvergenceWarning
from sklearn.utils import check_array
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.testing import assert_true
from... | bsd-3-clause |
wagavulin/arrow | python/pyarrow/__init__.py | 1 | 8314 | # 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 |
ClementLancien/convertToEntrezGeneID | script/conversion/info.py | 1 | 4970 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 22 16:42:44 2017
@author: clancien
"""
try:
import ConfigParser
except ImportError:
import configparser as ConfigParser
import os
import pandas
import logging
from logging.handlers import RotatingFileHandler
import sys
class Info():
def __init__(self):
... | mit |
pllim/astropy | astropy/utils/compat/optional_deps.py | 2 | 1548 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Checks for optional dependencies using lazy import from
`PEP 562 <https://www.python.org/dev/peps/pep-0562/>`_.
"""
import importlib
import warnings
# First, the top-level packages:
# TODO: This list is a duplicate of the dependencies in setup.cfg "all... | bsd-3-clause |
dpaiton/OpenPV | pv-core/analysis/python/plot_time_stability_all_k.py | 1 | 18262 | """
Plots the time stability
"""
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.cm as cm
import PVReadWeights as rw
import PVConversions as conv
import scipy.cluster.vq as sp
import math
if len(sys.argv) < 5:
print "usage: time_stability file... | epl-1.0 |
walterreade/scikit-learn | sklearn/ensemble/tests/test_weight_boosting.py | 58 | 17158 | """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, assert_true
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
DGrady/pandas | pandas/tests/frame/test_subclass.py | 15 | 9524 | # -*- coding: utf-8 -*-
from __future__ import print_function
from warnings import catch_warnings
import numpy as np
from pandas import DataFrame, Series, MultiIndex, Panel
import pandas as pd
import pandas.util.testing as tm
from pandas.tests.frame.common import TestData
class TestDataFrameSubclassing(TestData):... | bsd-3-clause |
GunoH/intellij-community | python/helpers/pydev/pydevd.py | 9 | 90108 | '''
Entry point module (keep at root):
This module starts the debugger.
'''
import os
import sys
from contextlib import contextmanager
import weakref
# allow the debugger to work in isolated mode Python
here = os.path.dirname(os.path.abspath(__file__))
if here not in sys.path:
sys.path.insert(0, here)
from _pyde... | apache-2.0 |
kazemakase/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
tkuipers/mycli | mycli/packages/tabulate.py | 28 | 38075 | # -*- coding: utf-8 -*-
"""Pretty-print tabular data."""
from __future__ import print_function
from __future__ import unicode_literals
from collections import namedtuple
from decimal import Decimal
from platform import python_version_tuple
from wcwidth import wcswidth
import re
if python_version_tuple()[0] < "3":
... | bsd-3-clause |
7even7/DAT210x | Module6/assignment6.py | 8 | 2431 | import pandas as pd
import time
# Grab the DLA HAR dataset from:
# http://groupware.les.inf.puc-rio.br/har
# http://groupware.les.inf.puc-rio.br/static/har/dataset-har-PUC-Rio-ugulino.zip
#
# TODO: Load up the dataset into dataframe 'X'
#
# .. your code here ..
#
# TODO: Encode the gender column, 0 as male, 1 as ... | mit |
MattNolanLab/ei-attractor | grid_cell_model/simulations/007_noise/figures/paper/i_place_cells/config.py | 1 | 2423 | '''Network test configuration file.'''
from __future__ import absolute_import, print_function
import os.path
from configobj import ConfigObj
import matplotlib.ticker as ti
scale_factor = 1.
tick_width = 1. * scale_factor
tick_len = 6. * scale_factor
DATA_ROOT = ['simulation_data', 'i_place_cells']
def get_conf... | gpl-3.0 |
BiaDarkia/scikit-learn | sklearn/mixture/tests/test_dpgmm.py | 84 | 7866 | # Important note for the deprecation cleaning of 0.20 :
# All the function and classes of this file have been deprecated in 0.18.
# When you remove this file please also remove the related files
# - 'sklearn/mixture/dpgmm.py'
# - 'sklearn/mixture/gmm.py'
# - 'sklearn/mixture/test_gmm.py'
import unittest
import sys
imp... | bsd-3-clause |
luca-s/alphalens | alphalens/tears.py | 1 | 26976 | #
# Copyright 2017 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... | apache-2.0 |
google-research/FirstOrderLp.jl | scripts/analyze_csv_data.py | 1 | 29257 | # Copyright 2021 The FirstOrderLp 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... | apache-2.0 |
astroJeff/dart_board | paper/scripts/J0513_evidence.py | 1 | 2610 | import sys
import numpy as np
import time
import matplotlib
matplotlib.use('Agg')
sys.path.append("../pyBSE/")
import pybse
import dart_board
from dart_board import sf_history
LMC_metallicity = 0.008
# Load the star formation history
sf_history.lmc.load_sf_history()
def lmc_sfh_J0513(ra, dec, ln_t_b):
""" S... | mit |
kcavagnolo/astroML | book_figures/chapter6/fig_density_estimation.py | 3 | 4407 | """
Comparison of 1D Density Estimators
-----------------------------------
Figure 6.5
A comparison of different density estimation methods for two simulated
one-dimensional data sets (cf. figure 5.21). The generating distribution is
same in both cases and shown as the dotted line; the samples include 500
(top panel) ... | bsd-2-clause |
nmayorov/scikit-learn | examples/classification/plot_classification_probability.py | 138 | 2871 | """
===============================
Plot classification probability
===============================
Plot the classification probability for different classifiers. We use a 3
class dataset, and we classify it with a Support Vector classifier, L1
and L2 penalized logistic regression with either a One-Vs-Rest or multinom... | bsd-3-clause |
rjl09c/ysp2017 | katiecodeorderverification.py | 1 | 9000 | import yt
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import pylab
from yt.analysis_modules.halo_finding.api import HaloFinder
from pylab import*
from numpy import ma
from numpy import linalg as LA
#deriveswith respect to x
def derivx(vel,xcoords):
distance = xcoords[1][0] + xcoords[0][1] - 2*... | gpl-3.0 |
chapman-phys227-2016s/cw-3-classwork-team | sequence_limits.py | 1 | 3024 | #! /usr/bin/env python
"""
File: sequence_limits.py
Copyright (c) 2016 Austin Ayers
License: MIT
Course: PHYS227
Assignment: A. 1
Date: Feb 11, 2016
Email: ayers111@mail.chapman.edu
Name: Austin Ayers
Description: Determines the limit of a sequence
"""
import numpy as np
import matplotlib.pyplot as plt
def seq_a(n):... | mit |
flaviovdf/aflux | aflux/dataio.py | 1 | 3090 | #-*- coding: utf8
from __future__ import division, print_function
from collections import defaultdict
from collections import OrderedDict
import numpy as np
import pandas as pd
def save_model(out_fpath, model):
store = pd.HDFStore(out_fpath, 'w')
for model_key in model:
model_val = model[model_key]
... | bsd-3-clause |
ronalcc/zipline | zipline/sources/simulated.py | 18 | 5422 | #
# Copyright 2014 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... | apache-2.0 |
plotly/python-api | packages/python/plotly/_plotly_utils/tests/validators/test_pandas_series_input.py | 1 | 4531 | import pytest
import numpy as np
import pandas as pd
from datetime import datetime
from _plotly_utils.basevalidators import (
NumberValidator,
IntegerValidator,
DataArrayValidator,
ColorValidator,
)
@pytest.fixture
def data_array_validator(request):
return DataArrayValidator("prop", "parent")
@p... | mit |
huongttlan/statsmodels | statsmodels/graphics/dotplots.py | 31 | 18190 | import numpy as np
from statsmodels.compat import range
from . import utils
def dot_plot(points, intervals=None, lines=None, sections=None,
styles=None, marker_props=None, line_props=None,
split_names=None, section_order=None, line_order=None,
stacked=False, styles_order=None, s... | bsd-3-clause |
JingJunYin/tensorflow | tensorflow/contrib/training/python/training/feeding_queue_runner_test.py | 76 | 5052 | # 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... | apache-2.0 |
lizardsystem/lizard-damage | lizard_damage/results.py | 1 | 10390 | """Process results for a DamageEvent.
The idea is that during a calculation a ResultCollector object is kept
around, and generated results (like land use images for a given tile) can
be "thrown to" it."""
import glob
import os
import shutil
import subprocess
import tempfile
import zipfile
from PIL import Image
from ... | gpl-3.0 |
Reagankm/KnockKnock | venv/lib/python3.4/site-packages/matplotlib/container.py | 11 | 3370 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import matplotlib.cbook as cbook
class Container(tuple):
"""
Base class for containers.
"""
def __repr__(self):
return "<Container object of %d artists>" % (len(self))
... | gpl-2.0 |
ajamesl/VectorTarget | plot.py | 1 | 2392 | import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.patches import FancyArrowPatch
import numpy as np
from mpl_toolkits.mplot3d import proj3d
x = []
y = []
z = []
#Reading two sets of x, y, z coordinates from a txt file
with open('data.txt', 'r') as csvfile:
coords = csv.reader... | mit |
russel1237/scikit-learn | sklearn/linear_model/bayes.py | 220 | 15248 | """
Various bayesian regression
"""
from __future__ import print_function
# Authors: V. Michel, F. Pedregosa, A. Gramfort
# License: BSD 3 clause
from math import log
import numpy as np
from scipy import linalg
from .base import LinearModel
from ..base import RegressorMixin
from ..utils.extmath import fast_logdet, p... | bsd-3-clause |
syl20bnr/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/projections/geo.py | 69 | 19738 | import math
import numpy as np
import numpy.ma as ma
import matplotlib
rcParams = matplotlib.rcParams
from matplotlib.artist import kwdocd
from matplotlib.axes import Axes
from matplotlib import cbook
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import Formatter, Locat... | gpl-3.0 |
arcyfelix/Courses | 18-11-22-Deep-Learning-with-PyTorch/02-Introduction to PyTorch/helper.py | 1 | 2719 | import matplotlib.pyplot as plt
import numpy as np
from torch import nn, optim
from torch.autograd import Variable
def test_network(net, trainloader):
criterion = nn.MSELoss()
optimizer = optim.Adam(net.parameters(), lr=0.001)
dataiter = iter(trainloader)
images, labels = dataiter.next()
# Crea... | apache-2.0 |
xuewei4d/scikit-learn | sklearn/manifold/_isomap.py | 11 | 9747 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils.validation import check_is_fitted
from ..uti... | bsd-3-clause |
bgossele/geminicassandra | geminicassandra/scripts/gemini_install.py | 1 | 15544 | #!/usr/bin/env python
"""Installer for geminicassandra: a lightweight db framework for disease and population genetics.
https://github.com/bgossele/geminicassandra
Handles installation of:
- Required third party software
- Required Python libraries
- Gemini application
- Associated data files
Requires: Python 2.7 (... | mit |
pv/scikit-learn | sklearn/linear_model/bayes.py | 220 | 15248 | """
Various bayesian regression
"""
from __future__ import print_function
# Authors: V. Michel, F. Pedregosa, A. Gramfort
# License: BSD 3 clause
from math import log
import numpy as np
from scipy import linalg
from .base import LinearModel
from ..base import RegressorMixin
from ..utils.extmath import fast_logdet, p... | bsd-3-clause |
JeanKossaifi/scikit-learn | examples/feature_selection/plot_permutation_test_for_classification.py | 250 | 2233 | """
=================================================================
Test with permutations the significance of a classification score
=================================================================
In order to test if a classification score is significative a technique
in repeating the classification procedure aft... | bsd-3-clause |
cancan101/tensorflow | tensorflow/examples/learn/wide_n_deep_tutorial.py | 24 | 8941 | # 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 |
wzbozon/statsmodels | statsmodels/graphics/tsaplots.py | 16 | 10392 | """Correlation plot functions."""
import numpy as np
from statsmodels.graphics import utils
from statsmodels.tsa.stattools import acf, pacf
def plot_acf(x, ax=None, lags=None, alpha=.05, use_vlines=True, unbiased=False,
fft=False, **kwargs):
"""Plot the autocorrelation function
Plots lags on th... | bsd-3-clause |
loli/semisupervisedforests | sklearn/cluster/tests/test_spectral.py | 11 | 7958 | """Testing for Spectral Clustering methods"""
from sklearn.externals.six.moves import cPickle
dumps, loads = cPickle.dumps, cPickle.loads
import numpy as np
from scipy import sparse
from sklearn.utils import check_random_state
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
nsat/gnuradio | gr-filter/examples/channelize.py | 58 | 7003 | #!/usr/bin/env python
#
# Copyright 2009,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your ... | gpl-3.0 |
procoder317/scikit-learn | benchmarks/bench_plot_fastkmeans.py | 294 | 4676 | from __future__ import print_function
from collections import defaultdict
from time import time
import numpy as np
from numpy import random as nr
from sklearn.cluster.k_means_ import KMeans, MiniBatchKMeans
def compute_bench(samples_range, features_range):
it = 0
results = defaultdict(lambda: [])
chun... | bsd-3-clause |
jorik041/scikit-learn | sklearn/svm/tests/test_svm.py | 116 | 31653 | """
Testing for Support Vector Machine module (sklearn.svm)
TODO: remove hard coded numerical results when possible
"""
import numpy as np
import itertools
from numpy.testing import assert_array_equal, assert_array_almost_equal
from numpy.testing import assert_almost_equal
from scipy import sparse
from nose.tools im... | bsd-3-clause |
blondegeek/pymatgen | pymatgen/analysis/phase_diagram.py | 2 | 83137 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
import re
import collections
import itertools
import math
import logging
from monty.json import MSONable, MontyDecoder
from functools import lru_cache
import numpy as np
from scipy.spatial import ConvexHull
... | mit |
tomlof/scikit-learn | sklearn/model_selection/_validation.py | 6 | 38471 | """
The :mod:`sklearn.model_selection._validation` module includes classes and
functions to validate the model.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>,
# Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
from __... | bsd-3-clause |
parekhmitchell/Machine-Learning | Machine Learning A-Z Template Folder/Part 2 - Regression/Section 6 - Polynomial Regression/polynomial_regression.py | 4 | 2115 | # Polynomial Regression
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Position_Salaries.csv')
X = dataset.iloc[:, 1:2].values
y = dataset.iloc[:, 2].values
# Splitting the dataset into the Training set and Test set
"""f... | mit |
kaiserroll14/301finalproject | main/pandas/tests/test_multilevel.py | 9 | 90175 | # -*- 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... | gpl-3.0 |
tmhm/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 |
amolkahat/pandas | pandas/tests/indexes/multi/test_set_ops.py | 2 | 6118 | # -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas import MultiIndex, Series
def test_setops_errorcases(idx):
# # non-iterable input
cases = [0.5, 'xxx']
methods = [idx.intersection, idx.union, idx.difference,
idx.symmetric_differenc... | bsd-3-clause |
KnHuq/Dynamic-Tensorflow-Tutorial | BiDirectional LSTM/bi_directional_lstm.py | 2 | 12777 | import tensorflow as tf
from sklearn import datasets
from sklearn.cross_validation import train_test_split
import pylab as pl
from IPython import display
import sys
# # Bi-LSTM class and functions
class Bi_LSTM_cell(object):
"""
Bi directional LSTM cell object which takes 3 arguments for initialization.
... | mit |
btabibian/scikit-learn | benchmarks/bench_random_projections.py | 397 | 8900 | """
===========================
Random projection benchmark
===========================
Benchmarks for random projections.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import collections
import numpy as np
import scipy.s... | bsd-3-clause |
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