repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
alexandrebarachant/mne-python | tutorials/plot_object_epochs.py | 5 | 6185 | """
.. _tut_epochs_objects:
The :class:`Epochs <mne.Epochs>` data structure: epoched data
=============================================================
"""
from __future__ import print_function
import mne
import os.path as op
import numpy as np
from matplotlib import pyplot as plt
##################################... | bsd-3-clause |
sinhrks/scikit-learn | sklearn/linear_model/tests/test_sparse_coordinate_descent.py | 34 | 9987 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_true
from sklearn.utils.t... | bsd-3-clause |
fsimkovic/cptbx | conkit/plot/sequencecoverage.py | 2 | 5705 | # BSD 3-Clause License
#
# Copyright (c) 2016-19, University of Liverpool
# 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 code must retain the above copyright notic... | gpl-3.0 |
sjl767/woo | py/eudoxos.py | 1 | 14383 | # encoding: utf-8
# 2008 © Václav Šmilauer <eudoxos@arcig.cz>
#
# I doubt there functions will be useful for anyone besides me.
#
"""Miscillaneous functions that are not believed to be generally usable,
therefore kept in my "private" module here.
They comprise notably oofem export and various CPM-related functions.
""... | gpl-2.0 |
wyom/sympy | sympy/physics/quantum/state.py | 58 | 29186 | """Dirac notation for states."""
from __future__ import print_function, division
from sympy import (cacheit, conjugate, Expr, Function, integrate, oo, sqrt,
Tuple)
from sympy.core.compatibility import u, range
from sympy.printing.pretty.stringpict import stringPict
from sympy.physics.quantum.qexpr ... | bsd-3-clause |
Richert/BrainNetworks | BasalGanglia/stn_gpe_simple_cfit.py | 1 | 6712 | import os
import warnings
import numpy as np
from pyrates.utility.genetic_algorithm import CGSGeneticAlgorithm
from pandas import DataFrame, read_hdf
from copy import deepcopy
class CustomGOA(CGSGeneticAlgorithm):
def eval_fitness(self, target: list, **kwargs):
# define simulation conditions
wor... | apache-2.0 |
pmathiot/PyChart | pychart.py | 1 | 19903 | #!/usr/bin/python
import sys
import argparse
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import lib_misc as libpc
def sanity_check(args):
# sanity check
if args.spfid:
if len(args.spfid) != len(args.mapf):
print('title list and file list not the same leng... | gpl-3.0 |
davidgbe/scikit-learn | sklearn/ensemble/tests/test_base.py | 284 | 1328 | """
Testing for the base module (sklearn.ensemble.base).
"""
# Authors: Gilles Louppe
# License: BSD 3 clause
from numpy.testing import assert_equal
from nose.tools import assert_true
from sklearn.utils.testing import assert_raise_message
from sklearn.datasets import load_iris
from sklearn.ensemble import BaggingCla... | bsd-3-clause |
orangehdc/GUI_for_PandF | draw_kline.py | 1 | 4424 | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 12 19:45:23 2014
input table_name, start_price, unit
@author: Administrator
"""
import numpy
import matplotlib
import sqlite3
matplotlib.use('Agg')
''' Very important! It must be put immediately after import matplotlib!'''
import matplotlib.pyplot as plt
def process(line)... | gpl-2.0 |
frank-tancf/scikit-learn | examples/ensemble/plot_gradient_boosting_regularization.py | 355 | 2843 | """
================================
Gradient Boosting regularization
================================
Illustration of the effect of different regularization strategies
for Gradient Boosting. The example is taken from Hastie et al 2009.
The loss function used is binomial deviance. Regularization via
shrinkage (``lear... | bsd-3-clause |
AllenDowney/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 |
Tong-Chen/scikit-learn | sklearn/ensemble/__init__.py | 44 | 1228 | """
The :mod:`sklearn.ensemble` module includes ensemble-based methods for
classification and regression.
"""
from .base import BaseEnsemble
from .forest import RandomForestClassifier
from .forest import RandomForestRegressor
from .forest import RandomTreesEmbedding
from .forest import ExtraTreesClassifier
from .fores... | bsd-3-clause |
ischurov/qqmbr | qqmbr/qqhtml.py | 1 | 57419 | # (c) Ilya V. Schurov, 2016
# Available under MIT license (see LICENSE file in the root folder)
from indentml.parser import QqTag
from yattag import Doc
import re
import inspect
import hashlib
import os
import urllib.parse
from mako.template import Template
from fuzzywuzzy import process
from html import escape as htm... | mit |
davidovitch/freeyaw-ojf-wt-tests | ojfdb_dict.py | 1 | 97176 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 17 17:37:00 2012
Make a database of all the test and their results
@author: dave
"""
#import sys
import os
import pickle
#import logging
#import copy
import string
import shutil
import numpy as np
import matplotlib as mpl
import pandas as pd
import ojfresult
import pl... | gpl-3.0 |
flightgong/scikit-learn | examples/linear_model/plot_multi_task_lasso_support.py | 249 | 2211 | #!/usr/bin/env python
"""
=============================================
Joint feature selection with multi-task Lasso
=============================================
The multi-task lasso allows to fit multiple regression problems
jointly enforcing the selected features to be the same across
tasks. This example simulates... | bsd-3-clause |
chugunovyar/factoryForBuild | env/lib/python2.7/site-packages/scipy/signal/windows.py | 20 | 54134 | """The suite of window functions."""
from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from scipy import fftpack, linalg, special
from scipy._lib.six import string_types
__all__ = ['boxcar', 'triang', 'parzen', 'bohman', 'blackman', 'nuttall',
'blackmanhar... | gpl-3.0 |
juanchopanza/NeuroM | neurom/tests/test_viewer.py | 2 | 3519 | # Copyright (c) 2015, Ecole Polytechnique Federale de Lausanne, Blue Brain Project
# All rights reserved.
#
# This file is part of NeuroM <https://github.com/BlueBrain/NeuroM>
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are ... | bsd-3-clause |
jereze/scikit-learn | sklearn/linear_model/tests/test_least_angle.py | 98 | 20870 | from nose.tools import assert_equal
import numpy as np
from scipy import linalg
from sklearn.cross_validation import train_test_split
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing impor... | bsd-3-clause |
nealchenzhang/Py4Invst | Market_Analysis/Futures_Market/AMH.py | 1 | 5223 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
###############################################################################
#
# Created on Mon Mar 20 17:00:38 2017
# @author: NealChenZhang
# This program is personal trading platform designed when employed in
# Aihui Asset Management as a quantitative analyst.
#
# ... | mit |
shl198/Pipeline | RibosomeProfilePipeline/04_RNA_process.py | 2 | 4620 | import os,sys
sys.path.append('/home/shangzhong/Codes/Pipeline')
from Modules.f04_htseq import htseq_count_py
from natsort import natsorted
from multiprocessing import Process
import subprocess
from Modules.f05_IDConvert import geneSymbol2EntrezID
import pandas as pd
from f02_RiboDataModule import *
import shutil
#====... | mit |
rahul-c1/scikit-learn | sklearn/utils/tests/test_murmurhash.py | 261 | 2836 | # Author: Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import numpy as np
from sklearn.externals.six import b, u
from sklearn.utils.murmurhash import murmurhash3_32
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
from nose.tools import assert_equa... | bsd-3-clause |
tacwon/DPL | wi_act_histogram.py | 1 | 1778 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 4 07:29:40 2017
@author: tacwon
"""
import numpy as np
import matplotlib.pyplot as plt
from MultiLayerNet import DPLMultiLayerNet
def sigmoid(x):
return 1 / (1 + np.exp(-x))
def ReLU(x):
return np.maximum(0, x)
def tanh(x):
return ... | mit |
jungla/ICOM-fluidity-toolbox | Detectors/offline_advection/plot_diffusivity_Okubo_Cb_fast.py | 1 | 3989 | #!~/python
import matplotlib as mpl
mpl.use('ps')
import matplotlib.pyplot as plt
import myfun
import numpy as np
import os, csv
import advect_functions
import lagrangian_stats
# read offline
print 'reading offline'
label = 'm_25_1b_particles'
filename2D = './csv/RD_2D_'+label+'.csv'
filename3D = './csv/RD_3D_'+labe... | gpl-2.0 |
cl4rke/scikit-learn | examples/linear_model/plot_lasso_coordinate_descent_path.py | 254 | 2639 | """
=====================
Lasso and Elastic Net
=====================
Lasso and elastic net (L1 and L2 penalisation) implemented using a
coordinate descent.
The coefficients can be forced to be positive.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
import num... | bsd-3-clause |
droundy/deft | papers/thesis-scheirer/final/cotangent.py | 1 | 10941 | import scipy as sp
from scipy.optimize import fsolve
import pylab as plt
import matplotlib
import SW
import numpy as np
###############################################################################################
# Author: Ryan Scheirer #
# Emai... | gpl-2.0 |
mrbeam/grbl | doc/script/fit_nonlinear_spindle.py | 3 | 18023 | """
---------------------
The MIT License (MIT)
Copyright (c) 2017-2018 Sungeun K. Jeon for Gnea Research LLC
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including withou... | gpl-3.0 |
diana-hep/carl | tests/ratios/test_classifier.py | 1 | 2546 | # 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
from numpy.testing import assert_array_almost_equal
from carl.distributions import Normal
from carl.ratios import ClassifierRatio
from carl.learning ... | bsd-3-clause |
simvisage/oricreate | docs/conf.py | 1 | 8690 | # -*- coding: utf-8 -*-
#
# oricreate documentation build configuration file, created by
# sphinx-quickstart on Mon Feb 27 11:03:20 2012.
#
# 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... | gpl-3.0 |
kashif/scikit-learn | examples/text/document_clustering.py | 9 | 8357 | """
=======================================
Clustering text documents using k-means
=======================================
This is an example showing how the scikit-learn can be used to cluster
documents by topics using a bag-of-words approach. This example uses
a scipy.sparse matrix to store the features instead of ... | bsd-3-clause |
zaxtax/scikit-learn | sklearn/utils/deprecation.py | 77 | 2417 | import warnings
__all__ = ["deprecated", ]
class deprecated(object):
"""Decorator to mark a function or class as deprecated.
Issue a warning when the function is called/the class is instantiated and
adds a warning to the docstring.
The optional extra argument will be appended to the deprecation mes... | bsd-3-clause |
Rossonero/bmlswp | ch04/build_lda.py | 22 | 2443 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
from __future__ import print_function
try:
import nltk.corpus
except ImportError:
print("nltk n... | mit |
BursonLab/Silica-Coding-Project | Misc Parts/Silicon and Oxygen from Centers using Delaunay.py | 1 | 17703 | import math
import numpy
import matplotlib.pyplot as plt
# - * - coding: utf - 8 - * -
"""
Created on Wed May 31 15:27:40 2017
@author: Kristen
"""
# - * - coding: utf - 8 - * -
"""
Created on Tue May 30 09:40:34 2017
@author: Kristen
"""
def distance(position1, position2):
""" Finds the... | apache-2.0 |
sckott/pytaxize | pytaxize/itis/itis.py | 1 | 35780 | import sys
import time
import requests
import warnings
from enum import Enum
from pytaxize.refactor import Refactor
try:
import pandas as pd
except ImportError:
warnings.warn("Pandas library not installed, dataframes disabled")
pd = None
itis_base = "http://www.itis.gov/ITISWebService/jsonservice/"
def a... | mit |
Chuban/moose | python/peacock/tests/postprocessor_tab/test_LineSettingsWidget.py | 6 | 3957 | #!/usr/bin/env python
import sys
from PyQt5 import QtCore, QtWidgets
from peacock.PostprocessorViewer.plugins.LineSettingsWidget import main
from peacock.utils import Testing
class TestLineSettingsWidget(Testing.PeacockImageTestCase):
"""
Test class for the LineSettingsWidget.
"""
#: QApplication: Th... | lgpl-2.1 |
fredhusser/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 143 | 22295 | """
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 sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
boomsbloom/dtm-fmri | DTM/for_gensim/lib/python2.7/site-packages/pandas/io/tests/parser/test_read_fwf.py | 7 | 13483 | # -*- coding: utf-8 -*-
"""
Tests the 'read_fwf' function in parsers.py. This
test suite is independent of the others because the
engine is set to 'python-fwf' internally.
"""
from datetime import datetime
import nose
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas import DataFra... | mit |
harisbal/pandas | pandas/tests/indexes/multi/test_duplicates.py | 2 | 9505 | # -*- coding: utf-8 -*-
from itertools import product
import numpy as np
import pytest
import pandas.util.testing as tm
from pandas import DatetimeIndex, MultiIndex
from pandas._libs import hashtable
from pandas.compat import range, u
@pytest.mark.parametrize('names', [None, ['first', 'second']])
def test_unique(n... | bsd-3-clause |
jorge2703/scikit-learn | sklearn/cluster/tests/test_k_means.py | 132 | 25860 | """Testing for K-means"""
import sys
import numpy as np
from scipy import sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing i... | bsd-3-clause |
cfriedt/gnuradio | gr-dtv/examples/atsc_ctrlport_monitor.py | 21 | 6089 | #!/usr/bin/env python
#
# Copyright 2015 Free Software Foundation
#
# 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, or (at your option)
# any later version.
#
# This program is... | gpl-3.0 |
billy-inn/scikit-learn | sklearn/decomposition/tests/test_truncated_svd.py | 240 | 6055 | """Test truncated SVD transformer."""
import numpy as np
import scipy.sparse as sp
from sklearn.decomposition import TruncatedSVD
from sklearn.utils import check_random_state
from sklearn.utils.testing import (assert_array_almost_equal, assert_equal,
assert_raises, assert_greater,
... | bsd-3-clause |
lucidfrontier45/scikit-learn | sklearn/tests/test_common.py | 1 | 30811 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD Style.
import os
import warnings
import sys
import traceback
import inspect
import numpy as np
from scipy import sparse
from sklearn.utils.... | bsd-3-clause |
EvanzzzZ/mxnet | example/rcnn/rcnn/pycocotools/coco.py | 17 | 18296 | __author__ = 'tylin'
__version__ = '2.0'
# Interface for accessing the Microsoft COCO dataset.
# Microsoft COCO is a large image dataset designed for object detection,
# segmentation, and caption generation. pycocotools is a Python API that
# assists in loading, parsing and visualizing the annotations in COCO.
# Pleas... | apache-2.0 |
DiCarloLab-Delft/PycQED_py3 | pycqed/simulations/ramsey_simulations_v2.py | 1 | 15596 | from importlib import reload
from pycqed.measurement import measurement_control as mc
import adaptive
from pycqed.instrument_drivers.meta_instrument.LutMans import flux_lutman_vcz as flm
from pycqed.instrument_drivers.virtual_instruments import sim_control_CZ_v2 as scCZ_v2
from pycqed.simulations import cz_superopera... | mit |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/datasets/samples_generator.py | 7 | 56557 | """
Generate samples of synthetic data sets.
"""
# Authors: B. Thirion, G. Varoquaux, A. Gramfort, V. Michel, O. Grisel,
# G. Louppe, J. Nothman
# License: BSD 3 clause
import numbers
import array
import numpy as np
from scipy import linalg
import scipy.sparse as sp
from ..preprocessing import MultiLabelBin... | mit |
gfyoung/pandas | pandas/tests/io/pytables/test_time_series.py | 1 | 1931 | import datetime
import numpy as np
import pytest
from pandas import DataFrame, Series, _testing as tm
from pandas.tests.io.pytables.common import ensure_clean_store
pytestmark = pytest.mark.single
def test_store_datetime_fractional_secs(setup_path):
with ensure_clean_store(setup_path) as store:
dt = d... | bsd-3-clause |
gnauhnoj/coco | PythonAPI/pycocotools/coco.py | 4 | 14801 | __author__ = 'tylin'
__version__ = '1.0.1'
# Interface for accessing the Microsoft COCO dataset.
# Microsoft COCO is a large image dataset designed for object detection,
# segmentation, and caption generation. pycocotools is a Python API that
# assists in loading, parsing and visualizing the annotations in COCO.
# Ple... | bsd-2-clause |
jamessergeant/pylearn2 | pylearn2/cross_validation/tests/test_cross_validation.py | 49 | 6767 | """
Tests for cross-validation module.
"""
import os
import tempfile
from pylearn2.config import yaml_parse
from pylearn2.testing.skip import skip_if_no_sklearn
def test_train_cv():
"""Test TrainCV class."""
skip_if_no_sklearn()
handle, layer0_filename = tempfile.mkstemp()
handle, layer1_filename = t... | bsd-3-clause |
dongjoon-hyun/spark | python/pyspark/pandas/data_type_ops/udt_ops.py | 14 | 1092 | #
# 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 |
jamesnorth/libsim | libsim.py | 2 | 8119 | # -*- coding: utf-8 -*-
### libsim - My Simulation Library
### ==============================
###
### Copyright © 2009, James North
###
### Permission is hereby granted, free of charge, to any person
### obtaining a copy of this software and associated documentation
### files (the "Software"), to deal in the Software... | mit |
blbarker/spark-tk | integration-tests/tests/test_frame_pandas.py | 12 | 1882 | # vim: set encoding=utf-8
# Copyright (c) 2016 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | apache-2.0 |
jreback/pandas | asv_bench/benchmarks/io/csv.py | 1 | 12945 | from io import BytesIO, StringIO
import random
import string
import numpy as np
from pandas import Categorical, DataFrame, date_range, read_csv, to_datetime
from ..pandas_vb_common import BaseIO, tm
class ToCSV(BaseIO):
fname = "__test__.csv"
params = ["wide", "long", "mixed"]
param_names = ["kind"]
... | bsd-3-clause |
soravux/skymangler | test_AE.py | 1 | 22909 | """
This tutorial introduces denoising auto-encoders (dA) using Theano.
Denoising autoencoders are the building blocks for SdA.
They are based on auto-encoders as the ones used in Bengio et al. 2007.
An autoencoder takes an input x and first maps it to a hidden representation
y = f_{\theta}(x) = s(Wx+b), paramete... | lgpl-3.0 |
fmv1992/data_utilities | data_utilities/tests/test_pandas_utilities.py | 1 | 9769 | """Test pandas_utilities from this module."""
import itertools
import random
import unittest
import numpy as np
import pandas as pd
from data_utilities import pandas_utilities as pu
from data_utilities.tests.test_support import (
TestDataUtilitiesTestCase, TestMetaClass)
def setUpModule():
"""Set up TestDa... | gpl-3.0 |
cwu2011/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 75 | 34122 | from __future__ import unicode_literals
import warnings
from sklearn.feature_extraction.text import strip_tags
from sklearn.feature_extraction.text import strip_accents_unicode
from sklearn.feature_extraction.text import strip_accents_ascii
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.fe... | bsd-3-clause |
kevinyu98/spark | python/pyspark/sql/functions.py | 4 | 135164 | #
# 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 |
yk-tanigawa/QLoop-dev | old/src/plt_res.py | 1 | 5265 | import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
from scipy import io
import math
import argparse
import os.path
sns.set_style("ticks")
sns.set_context("paper", font_scale=2.0)
def read_res(file):
names = ('axis', 'gamma', 'residu... | mit |
rknLA/sms-tools | lectures/09-Sound-description/plots-code/knn.py | 25 | 1718 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import os, sys
from numpy import random
from scipy.stats import mode
def eucDist(vec1, vec2):
return np.sqrt(np.sum(np.power(np.array(vec1) - np.array(vec2), 2)))
n = 30
qn = 8
K = 3
class1 = np.transpose(np.array([np.random.norm... | agpl-3.0 |
mpa46/PiNN_Caffe2 | dc_iv_api.py | 1 | 15457 | import caffe2_paths
import os
import pickle
from caffe2.python import (
workspace, layer_model_helper, schema, optimizer, net_drawer
)
import caffe2.python.layer_model_instantiator as instantiator
import numpy as np
from pinn.pinn_lib import build_pinn, init_model_with_schemas
import pinn.data_reader as data_reader
im... | mit |
jmcq89/megaman | examples/megaman_tutorial.py | 4 | 14494 | ## Example: Synethetic Data
'''
In this tutorial we're going to use a synthetic data set in particular
one that lies on a 2 dimensional manifold in 3 dimensional space
that can be embedded isometrically into 2 dimensions -- an S curve.
'''
import numpy as np
from sklearn import datasets
N = 1000
X, color = datasets.sam... | bsd-2-clause |
deepakantony/sms-tools | lectures/05-Sinusoidal-model/plots-code/sineModel-anal-synth.py | 24 | 1483 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import sys, os, functools, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import sineModel as SM
import utilFunctions as UF
(fs, x) = UF.wavread(os.p... | agpl-3.0 |
CompPhysics/ComputationalPhysics2 | doc/src/MCsummary/src/qdoteminim.py | 2 | 5916 | # 2-electron VMC code for 2dim quantum dot with importance sampling
# Using gaussian rng for new positions and Metropolis- Hastings
# Added energy minimization
# Common imports
from math import exp, sqrt
from random import random, seed, normalvariate
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits... | cc0-1.0 |
shenzebang/scikit-learn | sklearn/cluster/bicluster.py | 211 | 19443 | """Spectral biclustering algorithms.
Authors : Kemal Eren
License: BSD 3 clause
"""
from abc import ABCMeta, abstractmethod
import numpy as np
from scipy.sparse import dia_matrix
from scipy.sparse import issparse
from . import KMeans, MiniBatchKMeans
from ..base import BaseEstimator, BiclusterMixin
from ..external... | bsd-3-clause |
mwengren/sensorml2iso | sensorml2iso/sensorml2iso.py | 1 | 35374 | import os
import errno
import io
import sys
from datetime import datetime, timedelta
from dateutil import parser
import pytz
from six import iteritems
try:
from urllib.parse import unquote, unquote_plus, urlencode, urlparse # Python 3
except ImportError:
from urllib import unquote, unquote_plus, urlencode #... | mit |
deepakantony/sms-tools | workspace/A4/submitA4.py | 1 | 10889 | ### The only things you'll have to edit (unless you're porting this script over to a different language)
### are at the bottom of this file.
import urllib
import urllib2
import email
import email.message
import email.encoders
import sys
import pickle
import json
import base64
import numpy as np
import subprocess
impor... | agpl-3.0 |
foxtrotmike/pairpred | analyzeTAC.py | 1 | 4918 | # -*- coding: utf-8 -*-
"""
Created on Thu Jun 27 22:44:32 2013
Plots the binding associated changes in torsion angles after clustering analysis for a number of proteins
@author: root
"""
import numpy as np
import myPickle
from scipy.cluster.vq import *
import matplotlib
import matplotlib.pyplot as plt
#from scipy.spat... | gpl-3.0 |
leesavide/pythonista-docs | Documentation/matplotlib/mpl_examples/api/scatter_piecharts.py | 6 | 1194 | """
This example makes custom 'pie charts' as the markers for a scatter plotqu
Thanks to Manuel Metz for the example
"""
import math
import numpy as np
import matplotlib.pyplot as plt
# first define the ratios
r1 = 0.2 # 20%
r2 = r1 + 0.4 # 40%
# define some sizes of the scatter marker
sizes = [60,80,120]
# ca... | apache-2.0 |
larsoner/mne-python | examples/stats/plot_linear_regression_raw.py | 18 | 2385 | """
========================================
Regression on continuous data (rER[P/F])
========================================
This demonstrates how rER[P/F]s - regressing the continuous data - is a
generalisation of traditional averaging. If all preprocessing steps
are the same, no overlap between epochs exists, and ... | bsd-3-clause |
Garrett-R/scikit-learn | sklearn/cross_decomposition/cca_.py | 18 | 3129 | from .pls_ import _PLS
__all__ = ['CCA']
class CCA(_PLS):
"""CCA Canonical Correlation Analysis.
CCA inherits from PLS with mode="B" and deflation_mode="canonical".
Parameters
----------
n_components : int, (default 2).
number of components to keep.
scale : boolean, (default True)
... | bsd-3-clause |
nathanielvarona/airflow | docs/conf.py | 1 | 22928 | # flake8: noqa
# Disable Flake8 because of all the sphinx imports
#
# 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 un... | apache-2.0 |
sanketloke/scikit-learn | sklearn/exceptions.py | 35 | 4329 | """
The :mod:`sklearn.exceptions` module includes all custom warnings and error
classes used across scikit-learn.
"""
__all__ = ['NotFittedError',
'ChangedBehaviorWarning',
'ConvergenceWarning',
'DataConversionWarning',
'DataDimensionalityWarning',
'EfficiencyWarn... | bsd-3-clause |
penguinscontrol/Spinal-Cord-Modeling | Python/run_main.py | 1 | 1581 | debugging = 1
import os
from neuron import h
if debugging:
from neuron import gui
else:
h.load_file('noload.hoc')
from mpi4py import MPI
from matplotlib import pyplot
from neuronpy.graphics import spikeplot
import helper_functions as hf
import Ia_network as Ia_net
os.chdir('E:\\Google Drive\\Github\\Spinal-C... | gpl-2.0 |
annahs/atmos_research | WHI_2012_incand_calib.py | 1 | 2195 | import sys
import os
import datetime
import pickle
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
from pprint import pprint
import sqlite3
import calendar
from datetime import datetime
from datetime import timedelta
import math
import numpy.polynomial.po... | mit |
YerevaNN/mimic3-benchmarks | mimic3models/phenotyping/logistic/main.py | 1 | 5894 | from __future__ import absolute_import
from __future__ import print_function
from sklearn.preprocessing import Imputer, StandardScaler
from sklearn.linear_model import LogisticRegression
from mimic3benchmark.readers import PhenotypingReader
from mimic3models import common_utils
from mimic3models import metrics
from mi... | mit |
astocko/statsmodels | statsmodels/tools/print_version.py | 23 | 7951 | #!/usr/bin/env python
from __future__ import print_function
from statsmodels.compat.python import reduce
import sys
from os.path import dirname
def safe_version(module, attr='__version__'):
if not isinstance(attr, list):
attr = [attr]
try:
return reduce(getattr, [module] + attr)
except Att... | bsd-3-clause |
hsaputra/tensorflow | tensorflow/examples/learn/iris_custom_decay_dnn.py | 43 | 3572 | # 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 appl... | apache-2.0 |
Winand/pandas | pandas/plotting/_compat.py | 11 | 1602 | # being a bit too dynamic
# pylint: disable=E1101
from __future__ import division
from distutils.version import LooseVersion
def _mpl_le_1_2_1():
try:
import matplotlib as mpl
return (str(mpl.__version__) <= LooseVersion('1.2.1') and
str(mpl.__version__)[0] != '0')
except Impo... | bsd-3-clause |
Srisai85/scikit-learn | examples/mixture/plot_gmm_pdf.py | 284 | 1528 | """
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import ma... | bsd-3-clause |
bbfamily/abu | abupy/UtilBu/ABuDateUtil.py | 1 | 10596 | # -*- encoding:utf-8 -*-
"""
时间日期工具模块
"""
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
import datetime
import time
from datetime import datetime as dt
from ..CoreBu.ABuFixes import six
# noinspection PyUnresolvedReferences
from ..CoreBu.ABuFixes imp... | gpl-3.0 |
BrentVanwildemeersch/ML_StockPrediction | Flask Test/flasktest.py | 1 | 6999 | from flask import Flask, request
from flask import render_template
from datetime import datetime,timedelta
import pandas_datareader.data as web
from sklearn import linear_model
from sklearn.cross_validation import train_test_split
import tensorflow as tf
from keras.models import Sequential
from keras.layers import Acti... | apache-2.0 |
yashchandak/GNN | Sample_Run/Dynamic_Bi/Eval_Calculate_Performance.py | 3 | 4587 | from sklearn.metrics import coverage_error
from sklearn.metrics import label_ranking_loss
from sklearn.metrics import label_ranking_average_precision_score
from sklearn.metrics import hamming_loss
from sklearn import metrics
from collections import Counter
import math
import numpy as np
def patk(predictions, labels):... | mit |
tmerrick1/spack | var/spack/repos/builtin/packages/r-viridis/package.py | 5 | 1803 | ##############################################################################
# Copyright (c) 2013-2018, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
#
# This file is part of Spack.
# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
# LLNL-CODE-64... | lgpl-2.1 |
jat255/hyperspy | hyperspy/drawing/_widgets/range.py | 4 | 22490 | # -*- coding: utf-8 -*-
# Copyright 2007-2020 The HyperSpy developers
#
# This file is part of HyperSpy.
#
# HyperSpy is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at... | gpl-3.0 |
mr3bn/DAT210x | Module5/assignment8.py | 1 | 4856 | import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot') # Look Pretty
def drawLine(model, X_test, y_test, title):
# This convenience method will take care of plotting your
# test observations, comparing them to the regression line,
# an... | mit |
AminMahpour/pyHeat | pyHeat2.py | 1 | 5772 | #!/usr/bin/env python3
import operator
import pyBigWig
import sys
import matplotlib.pyplot as pp
import numpy as np
bed1 = ""
bw1 = ""
bw2 = ""
bw3 = ""
bw4 = ""
class BigwigObj:
def __init__(self, url):
myurl = url
self.bw = pyBigWig.open(myurl)
def get_scores(self, pos):
return s... | gpl-2.0 |
jkarnows/scikit-learn | examples/neighbors/plot_nearest_centroid.py | 264 | 1804 | """
===============================
Nearest Centroid Classification
===============================
Sample usage of Nearest Centroid classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
f... | bsd-3-clause |
seanli9jan/tensorflow | tensorflow/contrib/learn/python/learn/estimators/kmeans.py | 27 | 11083 | # 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 |
tmhm/scikit-learn | examples/neighbors/plot_classification.py | 287 | 1790 | """
================================
Nearest Neighbors Classification
================================
Sample usage of Nearest Neighbors classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColorm... | bsd-3-clause |
JrtPec/opengrid | opengrid/library/forecastwrapper.py | 1 | 19719 | # -*- coding: utf-8 -*-
__author__ = 'Jan Pecinovsky'
import datetime as dt
import forecastio
from forecastio.models import Forecast
from geopy import Location, Point, GoogleV3
import numpy as np
import pandas as pd
import pytz
from cached_property import cached_property
from tqdm import tqdm
import os
import pickle
... | apache-2.0 |
guillaumedavidphd/simple-data-science-challenges | Challenge1/counting_vitae.py | 1 | 3459 | """This script converts my LaTeX resume into a text file then reads it and
count the number of characters for each character. Finally, the result is
plotted as a histogram.
"""
import pandas as pd
import re
import matplotlib.pyplot as plt
import matplotlib
from subprocess import call
import string
matplotlib.style.us... | gpl-3.0 |
Djabbz/scikit-learn | examples/gaussian_process/plot_gpr_noisy.py | 104 | 3778 | """
=============================================================
Gaussian process regression (GPR) with noise-level estimation
=============================================================
This example illustrates that GPR with a sum-kernel including a WhiteKernel can
estimate the noise level of data. An illustration... | bsd-3-clause |
espenhgn/nest-simulator | pynest/examples/brunel_alpha_nest.py | 2 | 13724 | # -*- coding: utf-8 -*-
#
# brunel_alpha_nest.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the Licen... | gpl-2.0 |
EPFL-LCSB/pytfa | doc/conf.py | 1 | 6034 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# pytfa documentation build configuration file, created by
# sphinx-quickstart on Sat Jul 1 12:44:20 2017.
#
# 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
# auto... | apache-2.0 |
kcavagnolo/astroML | book_figures/chapter3/fig_beta_distribution.py | 3 | 2433 | """
Example of a Beta distribution
------------------------------
Figure 3.17.
This shows an example of a beta distribution with various parameters.
We'll generate the distribution using::
dist = scipy.stats.beta(...)
Where ... should be filled in with the desired distribution parameters
Once we have defined the... | bsd-2-clause |
rcrowder/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_emf.py | 69 | 22336 | """
Enhanced Metafile backend. See http://pyemf.sourceforge.net for the EMF
driver library.
"""
from __future__ import division
try:
import pyemf
except ImportError:
raise ImportError('You must first install pyemf from http://pyemf.sf.net')
import os,sys,math,re
from matplotlib import verbose, __version__,... | agpl-3.0 |
mfjb/scikit-learn | benchmarks/bench_plot_svd.py | 325 | 2899 | """Benchmarks of Singular Value Decomposition (Exact and Approximate)
The data is mostly low rank but is a fat infinite tail.
"""
import gc
from time import time
import numpy as np
from collections import defaultdict
from scipy.linalg import svd
from sklearn.utils.extmath import randomized_svd
from sklearn.datasets.s... | bsd-3-clause |
ky822/scikit-learn | examples/svm/plot_svm_anova.py | 250 | 2000 | """
=================================================
SVM-Anova: SVM with univariate feature selection
=================================================
This example shows how to perform univariate feature before running a SVC
(support vector classifier) to improve the classification scores.
"""
print(__doc__)
import... | bsd-3-clause |
ashhher3/scikit-learn | examples/decomposition/plot_pca_iris.py | 253 | 1801 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
PCA example with Iris Data-set
=========================================================
Principal Component Analysis applied to the Iris dataset.
See `here <http://en.wikipedia.org/wiki/Iris_flower_data_set>`_ fo... | bsd-3-clause |
rahuldhote/scikit-learn | benchmarks/bench_lasso.py | 297 | 3305 | """
Benchmarks of Lasso vs LassoLars
First, we fix a training set and increase the number of
samples. Then we plot the computation time as function of
the number of samples.
In the second benchmark, we increase the number of dimensions of the
training set. Then we plot the computation time as function of
the number o... | bsd-3-clause |
alexsavio/scikit-learn | examples/mixture/plot_gmm_covariances.py | 89 | 4724 | """
===============
GMM covariances
===============
Demonstration of several covariances types for Gaussian mixture models.
See :ref:`gmm` for more information on the estimator.
Although GMM are often used for clustering, we can compare the obtained
clusters with the actual classes from the dataset. We initialize th... | bsd-3-clause |
deepesch/scikit-learn | examples/missing_values.py | 233 | 3056 | """
======================================================
Imputing missing values before building an estimator
======================================================
This example shows that imputing the missing values can give better results
than discarding the samples containing any missing value.
Imputing does not ... | bsd-3-clause |
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