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 |
|---|---|---|---|---|---|
licode/xray-vision | xray_vision/messenger/__init__.py | 5 | 8285 | # ######################################################################
# Copyright (c) 2014, Brookhaven Science Associates, Brookhaven #
# National Laboratory. All rights reserved. #
# #
# Redistribution and use in ... | bsd-3-clause |
nvoron23/statsmodels | statsmodels/examples/ex_multivar_kde.py | 34 | 1504 |
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import axes3d
import statsmodels.api as sm
"""
This example illustrates the nonparametric estimation of a
bivariate bi-modal distribution that is a mixture of two normal
distri... | bsd-3-clause |
SanPen/PracticalGridModeling | examples/topology_engine.py | 1 | 22254 | import numpy as np
import pandas as pd
from scipy.sparse import csc_matrix, lil_matrix, diags
from JacobianBased import IwamotoNR
np.set_printoptions(linewidth=10000, precision=3)
# pd.set_option('display.height', 1000)
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('d... | gpl-3.0 |
ychfan/tensorflow | tensorflow/contrib/learn/python/learn/grid_search_test.py | 137 | 2035 | # 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 |
thientu/scikit-learn | examples/feature_selection/plot_rfe_with_cross_validation.py | 226 | 1384 | """
===================================================
Recursive feature elimination with cross-validation
===================================================
A recursive feature elimination example with automatic tuning of the
number of features selected with cross-validation.
"""
print(__doc__)
import matplotlib.p... | bsd-3-clause |
hj3938/panda3d | direct/src/ffi/jGenPyCode.py | 8 | 3101 | ##############################################################
#
# This module should be invoked by a shell-script that says:
#
# python -c "import direct.ffi.jGenPyCode" <arguments>
#
# Before invoking python, the shell-script may need to set
# these environment variables, to make sure that everything
# can be loca... | bsd-3-clause |
coreyabshire/stacko | src/competition_utilities.py | 1 | 5336 | from __future__ import division
from collections import Counter
import csv
import dateutil
from datetime import datetime
from dateutil.relativedelta import relativedelta
import numpy as np
import os
import pandas as pd
import pymongo
data_path = "C:/Projects/ML/stacko/data2"
submissions_path = data_path
if not data_pa... | bsd-2-clause |
valexandersaulys/prudential_insurance_kaggle | venv/lib/python2.7/site-packages/pandas/io/data.py | 9 | 45748 | """
Module contains tools for collecting data from various remote sources
"""
import warnings
import tempfile
import datetime as dt
import time
from collections import defaultdict
import numpy as np
from pandas.compat import(
StringIO, bytes_to_str, range, lmap, zip
)
import pandas.compat as compat
from pandas... | gpl-2.0 |
DougBurke/astropy | astropy/utils/timer.py | 2 | 10783 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""General purpose timer related functions."""
# STDLIB
import time
import warnings
from collections import Iterable, OrderedDict
from functools import partial, wraps
# THIRD-PARTY
import numpy as np
# LOCAL
from .. import units as u
from .. import log
... | bsd-3-clause |
hupili/bearcart | examples/random_data.py | 5 | 1449 | # -*- coding: utf-8 -*-
'''
An example for Bearcart
'''
import random
import bearcart
import pandas as pd
html_path = r'index.html'
data_path = r'data.json'
js_path = 'rickshaw.min.js'
css_path = 'rickshaw.min.css'
tabular_data_1 = [random.randint(10, 100) for x in range(0, 25, 1)]
tabular_data_2 = [random.randint(1... | mit |
sandeepdsouza93/TensorFlow-15712 | tensorflow/contrib/learn/python/learn/estimators/dnn_test.py | 5 | 40857 | # 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 |
DJArmstrong/autovet | Features/Centroiding/scripts/detrend_centroid_external.py | 2 | 12681 | # -*- coding: utf-8 -*-
"""
Created on Tue Oct 25 14:57:36 2016
@author:
Maximilian N. Guenther
Battcock Centre for Experimental Astrophysics,
Cavendish Laboratory,
JJ Thomson Avenue
Cambridge CB3 0HE
Email: mg719@cam.ac.uk
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
from astropy.s... | gpl-3.0 |
timy/dm_spec | ana/seidner/plot_orien.py | 1 | 1642 | from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from itertools import product, combinations
n_dir, n_esmb = 44, 200
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
data = np.loadtxt("res/euler.dat")
#draw cube
# r = [-1, 1]
# for s, e in combinations... | mit |
YosefLab/scVI | scvi/data/_built_in_data/_pbmc.py | 1 | 4405 | import os
import pickle
from typing import List
import anndata
import numpy as np
import pandas as pd
from scvi.data import setup_anndata
from scvi.data._built_in_data._dataset_10x import _load_dataset_10x
from scvi.data._built_in_data._download import _download
def _load_purified_pbmc_dataset(
save_path: str =... | bsd-3-clause |
giorgiop/scikit-learn | sklearn/covariance/__init__.py | 389 | 1157 | """
The :mod:`sklearn.covariance` module includes methods and algorithms to
robustly estimate the covariance of features given a set of points. The
precision matrix defined as the inverse of the covariance is also estimated.
Covariance estimation is closely related to the theory of Gaussian Graphical
Models.
"""
from ... | bsd-3-clause |
sonnyhu/scikit-learn | examples/gaussian_process/plot_gpr_co2.py | 131 | 5705 | """
========================================================
Gaussian process regression (GPR) on Mauna Loa CO2 data.
========================================================
This example is based on Section 5.4.3 of "Gaussian Processes for Machine
Learning" [RW2006]. It illustrates an example of complex kernel engine... | bsd-3-clause |
shenzebang/scikit-learn | sklearn/utils/tests/test_utils.py | 215 | 8100 | import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import pinv2
from itertools import chain
from sklearn.utils.testing import (assert_equal, assert_raises, assert_true,
assert_almost_equal, assert_array_equal,
SkipTest, ... | bsd-3-clause |
adamgreenhall/scikit-learn | sklearn/neighbors/base.py | 71 | 31147 | """Base and mixin classes for nearest neighbors"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck <L.J.Buitinck@uva.nl>
# Multi-output... | bsd-3-clause |
gfyoung/pandas | pandas/tests/arrays/test_array.py | 2 | 13512 | import datetime
import decimal
import numpy as np
import pytest
import pytz
from pandas.core.dtypes.base import registry
import pandas as pd
import pandas._testing as tm
from pandas.api.extensions import register_extension_dtype
from pandas.api.types import is_scalar
from pandas.arrays import (
BooleanArray,
... | bsd-3-clause |
RayMick/scikit-learn | sklearn/datasets/tests/test_lfw.py | 230 | 7880 | """This test for the LFW require medium-size data dowloading and processing
If the data has not been already downloaded by running the examples,
the tests won't run (skipped).
If the test are run, the first execution will be long (typically a bit
more than a couple of minutes) but as the dataset loader is leveraging
... | bsd-3-clause |
andrewcbennett/iris | docs/iris/src/conf.py | 6 | 10757 | # (C) British Crown Copyright 2010 - 2015, Met Office
#
# This file is part of Iris.
#
# Iris is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any l... | gpl-3.0 |
mverzett/rootpy | rootpy/plotting/base.py | 4 | 36584 | # Copyright 2012 the rootpy developers
# distributed under the terms of the GNU General Public License
"""
This module contains base classes defining core funcionality
"""
from __future__ import absolute_import
from functools import wraps
import warnings
import sys
import ROOT
from .. import asrootpy
from ..decorato... | gpl-3.0 |
lail3344/sms-tools | lectures/06-Harmonic-model/plots-code/piano-spectrum.py | 24 | 1038 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import math
import sys, os, functools, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel as DFT
import utilFunctions as UF
(fs, x) = UF... | agpl-3.0 |
DonBeo/scikit-learn | sklearn/cluster/birch.py | 18 | 22657 | # 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 |
smsbda/trading-with-python | lib/interactivebrokers.py | 77 | 18140 | """
Copyright: Jev Kuznetsov
Licence: BSD
Interface to interactive brokers together with gui widgets
"""
import sys
# import os
from time import sleep
from PyQt4.QtCore import (SIGNAL, SLOT)
from PyQt4.QtGui import (QApplication, QFileDialog, QDialog, QVBoxLayout, QHBoxLayout, QDialogButtonBox,
... | bsd-3-clause |
blink1073/scikit-image | doc/examples/color_exposure/plot_log_gamma.py | 14 | 2442 | """
=================================
Gamma and log contrast adjustment
=================================
This example adjusts image contrast by performing a Gamma and a Logarithmic
correction on the input image.
"""
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from skimage import data, img_a... | bsd-3-clause |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/manifold/isomap.py | 50 | 7515 | """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 import check_array
from ..utils.graph import... | mit |
RPGOne/Skynet | scikit-learn-0.18.1/examples/model_selection/grid_search_text_feature_extraction.py | 99 | 4163 |
"""
==========================================================
Sample pipeline for text feature extraction and evaluation
==========================================================
The dataset used in this example is the 20 newsgroups dataset which will be
automatically downloaded and then cached and reused for the d... | bsd-3-clause |
endlessm/chromium-browser | third_party/catapult/third_party/google-endpoints/future/utils/__init__.py | 36 | 20238 | """
A selection of cross-compatible functions for Python 2 and 3.
This module exports useful functions for 2/3 compatible code:
* bind_method: binds functions to classes
* ``native_str_to_bytes`` and ``bytes_to_native_str``
* ``native_str``: always equal to the native platform string object (because
... | bsd-3-clause |
r-mart/scikit-learn | examples/linear_model/plot_sgd_loss_functions.py | 249 | 1095 | """
==========================
SGD: convex loss functions
==========================
A plot that compares the various convex loss functions supported by
:class:`sklearn.linear_model.SGDClassifier` .
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def modified_huber_loss(y_true, y_pred):
z ... | bsd-3-clause |
anhaidgroup/py_entitymatching | py_entitymatching/debugmatcher/debug_randomforest_matcher.py | 1 | 4166 | """
This module contains functions for debugging random fores matcher.
"""
import logging
import pandas as pd
from py_entitymatching.debugmatcher.debug_decisiontree_matcher import \
_debug_decisiontree_matcher, _get_prob
from py_entitymatching.matcher.rfmatcher import RFMatcher
from py_entitymatching.utils.valida... | bsd-3-clause |
awacha/cct | cct/processinggui/graphing/outliertestresults.py | 1 | 11179 | import time
from typing import Union, Any
import dateutil.parser
import numpy as np
from PyQt5 import QtWidgets
from matplotlib.axes import Axes
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT, FigureCanvasQTAgg
from matplotlib.figure import Figure
from matplotlib.lines import Line2D
from .onedim ... | bsd-3-clause |
yuginboy/from_GULP_to_FEFF | feff/libs/GaMnAs_concentration.py | 1 | 39959 | import sys
import os
from io import StringIO
import inspect
import numpy as np
import matplotlib.gridspec as gridspec
from matplotlib import pylab
import matplotlib.pyplot as plt
import scipy as sp
from scipy.interpolate import interp1d
from scipy.interpolate import Rbf, InterpolatedUnivariateSpline, splrep, splev, spl... | gpl-3.0 |
CanisMajoris/ThinkStats2 | code/hinc.py | 67 | 1494 | """This file contains code used in "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2014 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function
import numpy as np
import pandas
import thinkplot
import thinkstats2
def Clean(s):... | gpl-3.0 |
I--P/numpy | numpy/core/code_generators/ufunc_docstrings.py | 14 | 90528 | """
Docstrings for generated ufuncs
The syntax is designed to look like the function add_newdoc is being
called from numpy.lib, but in this file add_newdoc puts the docstrings
in a dictionary. This dictionary is used in
numpy/core/code_generators/generate_umath.py to generate the docstrings
for the ufuncs in numpy.co... | bsd-3-clause |
Ernestyj/PyStudy | finance/WeekTest/AdaboostSGDTest.py | 1 | 2612 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import talib
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 30)
pd.set_option('precision', 7)
pd.options.display.float_format = '{:,... | apache-2.0 |
jblackburne/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 |
JeanKossaifi/scikit-learn | sklearn/tests/test_discriminant_analysis.py | 35 | 11709 | try:
# Python 2 compat
reload
except NameError:
# Regular Python 3+ import
from importlib import reload
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.t... | bsd-3-clause |
kushalbhola/MyStuff | Practice/PythonApplication/env/Lib/site-packages/pandas/core/accessor.py | 2 | 8470 | """
accessor.py contains base classes for implementing accessor properties
that can be mixed into or pinned onto other pandas classes.
"""
from typing import Set
import warnings
from pandas.util._decorators import Appender
class DirNamesMixin:
_accessors = set() # type: Set[str]
_deprecations = frozenset(... | apache-2.0 |
gongshijun/ystechweb | common/result.py | 1 | 1421 | # coding: utf-8
import os
import re
import pandas as pd
# run shell
def execmd(cmd):
os.system(cmd)
class final_result(object):
def __init__(self, result=None):
self.result = result
# get data from result.txt
def get_result(self,filename):
f = open(filename, 'r')
data = f... | gpl-3.0 |
adamrvfisher/TechnicalAnalysisLibrary | ADXStratOpt.py | 1 | 4717 | # -*- coding: utf-8 -*-
"""
Created on Sun Apr 9 16:36:25 2017
@author: AmatVictoriaCuramIII
"""
import pandas as pd
from pandas_datareader import data
import numpy as np
import time as t
import random as rand
ticker = '^GSPC'
s = data.DataReader(ticker, 'yahoo', start='01/01/2016', end='01/01/2050')
iterations = ra... | apache-2.0 |
madjelan/scikit-learn | sklearn/neighbors/classification.py | 106 | 13987 | """Nearest Neighbor Classification"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck <L.J.Buitinck@uva.nl>
# Multi-output support by ... | bsd-3-clause |
alexmojaki/blaze | blaze/compute/tests/test_sql_compute.py | 6 | 56473 | from __future__ import absolute_import, division, print_function
import pytest
sa = pytest.importorskip('sqlalchemy')
import itertools
import re
from distutils.version import LooseVersion
import datashape
from odo import into, resource, discover
from pandas import DataFrame
from toolz import unique
from blaze.com... | bsd-3-clause |
dpinney/omf | omf/scratch/dataShader/Graph.py | 1 | 8303 | #!/usr/bin/env python
# coding: utf-8
#Converting image imports
#import base64
#import io
import math
import numpy as np
import pandas as pd
import datashader as ds
import datashader.transfer_functions as tf
from datashader.layout import random_layout
from datashader.bundling import connect_edges
#from itertools im... | gpl-2.0 |
ShaperTools/openhtf | openhtf/core/measurements.py | 1 | 22990 | # Copyright 2014 Google Inc. 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 applicable law or agre... | apache-2.0 |
mkness/TheCannon | code/deprecated/makeplot_R3.py | 1 | 4257 | #!/usr/bin/python
import numpy
from numpy import savetxt
import matplotlib
from matplotlib import pyplot
import scipy
from scipy import interpolate
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
s = matplotlib.font_manager.FontProperties()
s.set_family('serif')
s.set_size(14)
from matplotlib import r... | mit |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/dask/dataframe/multi.py | 2 | 25292 | """
Algorithms that Involve Multiple DataFrames
===========================================
The pandas operations ``concat``, ``join``, and ``merge`` combine multiple
DataFrames. This module contains analogous algorithms in the parallel case.
There are two important cases:
1. We combine along a partitioned index
2... | gpl-3.0 |
TomAugspurger/pandas | pandas/core/computation/scope.py | 1 | 9112 | """
Module for scope operations
"""
import datetime
import inspect
from io import StringIO
import itertools
import pprint
import struct
import sys
from typing import List
import numpy as np
from pandas._libs.tslibs import Timestamp
from pandas.compat.chainmap import DeepChainMap
def ensure_scope(
level: int, g... | bsd-3-clause |
pythonvietnam/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 |
Unidata/MetPy | v0.12/_downloads/aedfcde5d540d021d02883dc8627add4/Station_Plot_with_Layout.py | 9 | 8124 | # Copyright (c) 2016,2017 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Station Plot with Layout
========================
Make a station plot, complete with sky cover and weather symbols, using a
station plot layout built into MetPy.
The stati... | bsd-3-clause |
skjerns/AutoSleepScorerDev | test_dataset_feat.py | 1 | 2550 | # -*- coding: utf-8 -*-
"""
This is python 3 code
main script for training/classifying
"""
if not '__file__' in vars(): __file__= u'C:/Users/Simon/dropbox/Uni/Masterthesis/AutoSleepScorer/main.py'
import os
import gc; gc.collect()
import matplotlib
matplotlib.use('Agg')
import numpy as np
import keras
import tools
impo... | gpl-3.0 |
mohittahiliani/PIE-ns3 | src/flow-monitor/examples/wifi-olsr-flowmon.py | 108 | 7439 | # -*- Mode: Python; -*-
# Copyright (c) 2009 INESC Porto
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation;
#
# This program is distributed in the hope that it will be useful,
#... | gpl-2.0 |
rahul-c1/scikit-learn | sklearn/neighbors/unsupervised.py | 16 | 3198 | """Unsupervised nearest neighbors learner"""
from .base import NeighborsBase
from .base import KNeighborsMixin
from .base import RadiusNeighborsMixin
from .base import UnsupervisedMixin
class NearestNeighbors(NeighborsBase, KNeighborsMixin,
RadiusNeighborsMixin, UnsupervisedMixin):
"""Unsu... | bsd-3-clause |
YinongLong/scikit-learn | sklearn/linear_model/tests/test_huber.py | 54 | 7619 | # Authors: Manoj Kumar mks542@nyu.edu
# License: BSD 3 clause
import numpy as np
from scipy import optimize, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_a... | bsd-3-clause |
pnedunuri/scikit-learn | sklearn/tests/test_isotonic.py | 230 | 11087 | import numpy as np
import pickle
from sklearn.isotonic import (check_increasing, isotonic_regression,
IsotonicRegression)
from sklearn.utils.testing import (assert_raises, assert_array_equal,
assert_true, assert_false, assert_equal,
... | bsd-3-clause |
zachmayer/vowpal_wabbit | python/vowpalwabbit/sklearn_vw.py | 1 | 20773 | # -*- coding: utf-8 -*-
# pylint: disable=line-too-long, unused-argument, invalid-name, too-many-arguments, too-many-locals
"""
Utilities to support integration of Vowpal Wabbit and scikit-learn
"""
import numpy as np
from vowpalwabbit.pyvw import vw
import re
from scipy.sparse import csr_matrix
from sklearn import me... | bsd-3-clause |
judithfan/pix2svg | generative/tests/compare_test/concat_first/train_average.py | 1 | 10419 | from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import os
import sys
import shutil
import numpy as np
from tqdm import tqdm
import torch
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable
from sklearn.metrics imp... | mit |
chrisjmccormick/simsearch | runElbowMethod.py | 1 | 3522 | # -*- coding: utf-8 -*-
"""
This script uses the elbow method to help identify a good value of 'k' to use
for k-means clustering.
@author: Chris McCormick
"""
from scipy.spatial.distance import cdist, pdist
from sklearn.cluster import KMeans
from simsearch import SimSearch
import numpy as np
import matplotlib.pyplot ... | mit |
jwlockhart/concept-networks | examples/person_similarity_parallel.py | 1 | 3993 | # @author Jeff Lockhart <jwlock@umich.edu>
# Example script computing the pairwise similarity of people and/or
# responses in a sample. Parallel implementation using ipyparallel.
#
# version 1.1
import pandas as pd
import ipyparallel
import sys
sys.path.insert(0,'../')
from network_utils import *
print('Creating c... | gpl-3.0 |
ros-industrial/industrial_training | exercises/Descartes_Planning_and_Execution/solution_ws/src/plan_and_run/src/generate_lemniscate_trajectory.py | 12 | 1825 | #!/usr/bin/env python
import numpy
import math
import matplotlib.pyplot as pyplot
from mpl_toolkits.mplot3d import Axes3D
def generateLemniscatePoints():
# 3D plotting setup
fig = pyplot.figure()
ax = fig.add_subplot(111,projection='3d')
a = 6.0
ro = 4.0
dtheta = 0.1
nsamples = 200
... | apache-2.0 |
cbertinato/pandas | pandas/tests/io/parser/test_compression.py | 1 | 4616 | """
Tests compressed data parsing functionality for all
of the parsers defined in parsers.py
"""
import os
import zipfile
import pytest
import pandas as pd
import pandas.util.testing as tm
@pytest.fixture(params=[True, False])
def buffer(request):
return request.param
@pytest.fixture
def parser_and_data(all_... | bsd-3-clause |
keflavich/scikit-image | skimage/viewer/canvastools/painttool.py | 23 | 6437 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
LABELS_CMAP = mcolors.ListedColormap(['white', 'red', 'dodgerblue', 'gold',
'greenyellow', 'blueviolet'])
from ...viewer.canvastools.base import CanvasToolBase
__all__ = ['PaintTool']
class P... | bsd-3-clause |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/build/lib.linux-i686-2.7/matplotlib/testing/jpl_units/UnitDblFormatter.py | 6 | 1401 | #===========================================================================
#
# UnitDblFormatter
#
#===========================================================================
"""UnitDblFormatter module containing class UnitDblFormatter."""
#==========================================================================... | mit |
zhuangjun1981/retinotopic_mapping | retinotopic_mapping/examples/visual_stimlation/example_retinotopic_mapping.py | 1 | 5154 | # -*- coding: utf-8 -*-
"""
Example script to test StimulusRoutines.CombinedStimuli class
"""
import matplotlib.pyplot as plt
import retinotopic_mapping.StimulusRoutines as stim
from retinotopic_mapping.MonitorSetup import Monitor, Indicator
from retinotopic_mapping.DisplayStimulus import DisplaySequence
# ==========... | gpl-3.0 |
pradyu1993/scikit-learn | sklearn/decomposition/tests/test_nmf.py | 1 | 5049 | import numpy as np
from sklearn.decomposition import nmf
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import raises
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_greater
random_state = np... | bsd-3-clause |
astrofrog/numpy | doc/source/conf.py | 7 | 10752 | # -*- coding: utf-8 -*-
import sys, os, re
# Check Sphinx version
import sphinx
if sphinx.__version__ < "1.0.1":
raise RuntimeError("Sphinx 1.0.1 or newer required")
needs_sphinx = '1.0'
# -----------------------------------------------------------------------------
# General configuration
# -------------------... | bsd-3-clause |
klusta-team/kwiklib | kwiklib/dataio/loader.py | 1 | 17513 | """This module provides utility classes and functions to load spike sorting
data sets."""
# -----------------------------------------------------------------------------
# Imports
# -----------------------------------------------------------------------------
import os
import os.path
import re
from collections import ... | bsd-3-clause |
mehdidc/scikit-learn | sklearn/utils/mocking.py | 38 | 1807 | from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_true
class ArraySlicingWrapper(object):
def __init__(self, array):
self.array = array
def __getitem__(self, aslice):
return MockDataFrame(self.array[aslice])
class MockDataFrame(object):
# have shape an len... | bsd-3-clause |
rlkelly/StockPy | StockPy.py | 3 | 3376 | import pandas.io.data as web
import datetime as dt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.widgets as wd
def plot_data(stkname, fig, topplt, botplt, sidplt):
#Get data from yahoo
#Calculate olling mean, mean and current value of stock
#Also calculate length... | gpl-2.0 |
marioharper182/ComputationalMethodsFinance | Homework1/GuessMyNumber.py | 1 | 1685 | __author__ = 'Mario'
import matplotlib.pyplot as plt
import numpy as np
import itertools
def Guessengine(A):
A = int(A)
# Basic Parameters
low = 0
high = 101
guess = [50]
g = 0
counter = 0
# Plotting information is stored here:
matplotlist = [50]
trieslist = [0]
while g... | apache-2.0 |
squirrelo/qiime | scripts/identify_paired_differences.py | 15 | 9191 | #!/usr/bin/env python
# File created on 19 Jun 2013
from __future__ import division
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2013, The QIIME project"
__credits__ = ["Greg Caporaso", "Jose Carlos Clemente Litran"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Greg Caporaso"
__email__ = ... | gpl-2.0 |
dessn/sn-bhm | papers/methods/snippets/efficiency.py | 1 | 1820 | import numpy as np
from scipy.stats import norm, skewnorm
import matplotlib.pyplot as plt
from matplotlib import rc
from astropy.cosmology import FlatwCDM
mbs = np.linspace(19, 27, 100)
pop = norm.pdf(mbs, 22, 1)
pop /= pop.max()
cdf_mu, cdf_sigma = 21.5, 0.5
cdf = 1 - norm.cdf(mbs, cdf_mu, cdf_sigma)
cdf_eff = pop ... | mit |
exa-analytics/exa | exa/util/constants.py | 1 | 2062 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2020, Exa Analytics Development Team
# Distributed under the terms of the Apache License 2.0
"""
Physical Constants
#######################################
Tabulated physical constants from `NIST`_. Note that all constants are float
objects (with a slightly modified repr). T... | apache-2.0 |
jorik041/scikit-learn | examples/gaussian_process/plot_gp_regression.py | 253 | 4054 | #!/usr/bin/python
# -*- coding: utf-8 -*-
r"""
=========================================================
Gaussian Processes regression: basic introductory example
=========================================================
A simple one-dimensional regression exercise computed in two different ways:
1. A noise-free cas... | bsd-3-clause |
PhE/dask | dask/dataframe/tests/test_utils_dataframe.py | 11 | 1064 | import pandas as pd
from dask.dataframe.utils import (shard_df_on_index, get_categories,
_categorize, strip_categories)
import pandas.util.testing as tm
def test_shard_df_on_index():
df = pd.DataFrame({'x': [1, 2, 3, 4, 5, 6], 'y': list('abdabd')},
index=[10, 20, 30, 40, 50, 60])
... | bsd-3-clause |
joernhees/scikit-learn | benchmarks/bench_multilabel_metrics.py | 276 | 7138 | #!/usr/bin/env python
"""
A comparison of multilabel target formats and metrics over them
"""
from __future__ import division
from __future__ import print_function
from timeit import timeit
from functools import partial
import itertools
import argparse
import sys
import matplotlib.pyplot as plt
import scipy.sparse as... | bsd-3-clause |
cpury/lstm-math | plot.py | 1 | 3569 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
def plot_2d_space(
model, one_hot_encoder, x, y, n=None, reverse=False,
save_to=None, dpi=256,
):
"""
For models trained on equations ala 'a + b', this will plot a scatter plot
with correct examples in green and incorrect ones ... | mit |
mikel-egana-aranguren/SADI-Galaxy-Docker | galaxy-dist/tools/plotting/plotter.py | 4 | 2247 | #!/usr/bin/env python
# python histogram input_file output_file column bins
import sys, os
import matplotlib; matplotlib.use('Agg')
from pylab import *
assert sys.version_info[:2] >= ( 2, 4 )
def stop_err(msg):
sys.stderr.write(msg)
sys.exit()
if __name__ == '__main__':
# parse the arguments
... | gpl-3.0 |
SusanJL/iris | docs/iris/src/sphinxext/gen_gallery.py | 9 | 6301 | #
# (C) Copyright 2012 MATPLOTLIB (vn 1.2.0)
#
'''
Generate a thumbnail gallery of examples.
'''
from __future__ import (absolute_import, division, print_function)
from six.moves import (filter, input, map, range, zip) # noqa
import os
import glob
import re
import warnings
import matplotlib.image as image
temp... | gpl-3.0 |
intuition-io/intuition | tests/test_utils.py | 1 | 2324 | '''
Tests for intuition.utils
'''
import unittest
from nose.tools import ok_, eq_, nottest
import pytz
import datetime as dt
import pandas as pd
import intuition.utils as utils
class UtilsTestCase(unittest.TestCase):
def test_is_live(self):
last_trade_date = dt.datetime(2026, 1, 1, tzinfo=pytz.utc)
... | apache-2.0 |
elenbert/allsky | src/webdatagen/system-sensors.py | 1 | 2514 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import MySQLdb
import sys
import config
def plot_cpu_temperature(sensor_data, output_file):
xdata = []
ydata = []
print 'Plotting cpu temperature graph using ' + str(len(sensor_data)) + ' db records'
for row... | gpl-2.0 |
fredhusser/scikit-learn | examples/tree/plot_iris.py | 271 | 2186 | """
================================================================
Plot the decision surface of a decision tree on the iris dataset
================================================================
Plot the decision surface of a decision tree trained on pairs
of features of the iris dataset.
See :ref:`decision tree ... | bsd-3-clause |
PanDAWMS/pilot | RunJobHpcEvent.py | 3 | 87735 | # Class definition:
# RunJobHpcEvent
# This class is the base class for the HPC Event Server classes.
# Instances are generated with RunJobFactory via pUtil::getRunJob()
# Implemented as a singleton class
# http://stackoverflow.com/questions/42558/python-and-the-singleton-pattern
import commands
import json
... | apache-2.0 |
wazeerzulfikar/scikit-learn | examples/covariance/plot_robust_vs_empirical_covariance.py | 69 | 6473 | r"""
=======================================
Robust vs Empirical covariance estimate
=======================================
The usual covariance maximum likelihood estimate is very sensitive to the
presence of outliers in the data set. In such a case, it would be better to
use a robust estimator of covariance to guar... | bsd-3-clause |
wanggang3333/scikit-learn | examples/calibration/plot_calibration_multiclass.py | 272 | 6972 | """
==================================================
Probability Calibration for 3-class classification
==================================================
This example illustrates how sigmoid calibration changes predicted
probabilities for a 3-class classification problem. Illustrated is the
standard 2-simplex, wher... | bsd-3-clause |
lnls-sirius/dev-packages | siriuspy/siriuspy/ramp/test_reconst_factory.py | 1 | 6985 | #!/usr/bin/env python-sirius
"""Test reconstrction factories."""
from copy import deepcopy as _dcopy
import argparse as _argparse
import numpy as _np
import matplotlib.pyplot as plt
from siriuspy.clientconfigdb import ConfigDBDocument
from siriuspy.ramp.ramp import BoosterRamp
from siriuspy.ramp.waveform import Wave... | gpl-3.0 |
sniemi/SamPy | bolshoi/subhaloDistances.py | 1 | 16670 | """
Find subhalo galaxy distances from the main halo as a function of redshift, halo mass, etc.
:Warning: All functions are rather poorly written as I was in a hurry.
One should improve them before using. One could remove several
loops and do many things with table joins which are now separate loop... | bsd-2-clause |
RPGOne/Skynet | scikit-learn-0.18.1/examples/model_selection/plot_confusion_matrix.py | 20 | 3180 | """
================
Confusion matrix
================
Example of confusion matrix usage to evaluate the quality
of the output of a classifier on the iris data set. The
diagonal elements represent the number of points for which
the predicted label is equal to the true label, while
off-diagonal elements are those that ... | bsd-3-clause |
Lawrence-Liu/scikit-learn | examples/classification/plot_classification_probability.py | 242 | 2624 | """
===============================
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 |
jordan-g/Segregated-Dendrite-Deep-Learning | deep_learning.py | 1 | 102639 | # encoding=utf8
'''
Code for simulations presented in
"Towards deep learning with segregated dendrites", arXiv:1610.00161
by Jordan Guergiuev, Timothy P. Lillicrap, Blake A. Richards.
Author: Jordan Guergiuev
E-mail: guerguiev.j@gmail.com
Date: May 10, 2017
Institution: University of Toronto Scarborou... | gpl-3.0 |
Ziqi-Li/bknqgis | bokeh/tests/examples/test_examples.py | 1 | 7455 | from __future__ import absolute_import, print_function
import os
import time
import pytest
import subprocess
import signal
from os.path import abspath, dirname, exists, join, split
from tests.plugins.utils import trace, info, fail, ok, red, warn, white
from tests.plugins.phantomjs_screenshot import get_phantomjs_scr... | gpl-2.0 |
bendalab/thunderfish | thunderfish/efield.py | 2 | 21468 | """
Simulations of spatial electric fields.
For simulating the spatial geometry of electric fields generated by electric fishes
and perturbed by objects, first generate monopoles and charges:
- `efish_monopoles()`: monopoles for simulating the electric field of an electric fish.
- `object_monopoles()`: monopoles for ... | gpl-3.0 |
kensugino/jGEM | jgem/merge.py | 1 | 67888 | """
.. module:: merge
:synopsis: module for merging multiple assemblies
.. moduleauthor:: Ken Sugino <ken.sugino@gmail.com>
"""
import subprocess
import os
import gzip
import logging
logging.basicConfig(level=logging.DEBUG)
LOG = logging.getLogger(__name__)
import shutil
import json
import pandas as PD
import... | mit |
Weihonghao/ECM | Vpy34/lib/python3.5/site-packages/pandas/tests/series/test_period.py | 7 | 8836 | import numpy as np
import pandas as pd
import pandas.util.testing as tm
import pandas.core.indexes.period as period
from pandas import Series, period_range, DataFrame, Period
def _permute(obj):
return obj.take(np.random.permutation(len(obj)))
class TestSeriesPeriod(object):
def setup_method(self, method):... | agpl-3.0 |
Achuth17/scikit-learn | examples/model_selection/plot_learning_curve.py | 250 | 4171 | """
========================
Plotting Learning Curves
========================
On the left side the learning curve of a naive Bayes classifier is shown for
the digits dataset. Note that the training score and the cross-validation score
are both not very good at the end. However, the shape of the curve can be found
in ... | bsd-3-clause |
milankl/swm | calc/misc/trispec_calc.py | 1 | 2830 | ## COMPUTE TRISPEC
from __future__ import print_function
path = '/home/mkloewer/python/swm/'
import os; os.chdir(path) # change working directory
import numpy as np
from scipy import sparse
import time as tictoc
from netCDF4 import Dataset
import glob
import matplotlib.pyplot as plt
# OPTIONS
runfolder = [3]
print('Ca... | gpl-3.0 |
jakevdp/seaborn | seaborn/timeseries.py | 6 | 13239 | """Timeseries plotting functions."""
from __future__ import division
import numpy as np
import pandas as pd
from scipy import stats, interpolate
import matplotlib as mpl
import matplotlib.pyplot as plt
from .external.six import string_types
from . import utils
from . import algorithms as algo
from .palettes import c... | bsd-3-clause |
cdeboever3/cdpybio | tests/plink/test_plink.py | 1 | 2431 | from copy import deepcopy
import os
from numpy import array
from numpy import nan
import numpy as np
import pandas as pd
from pandas.util.testing import assert_frame_equal
import pytest
import cdpybio as cpb
def add_root(fn):
return os.path.join(cpb._root, 'tests', 'star', fn)
LINEAR = add_root('test.glm.linear... | mit |
imec-myhdl/pycontrol-gui | Book/Examples/BallOnWheel.py | 1 | 1660 | from sympy import symbols, Matrix, pi
from sympy.physics.mechanics import *
import numpy as np
ph0, ph1, ph2 = dynamicsymbols('ph0 ph1 ph2')
w1, w2 = dynamicsymbols('w1 w2')
T = dynamicsymbols('T')
J1, J2 = symbols('J1 J2')
M1, M2 = symbols('M1 M2')
R1, R2 = symbols('R1 R2')
d1 = symbols('d1')
g = symbols('... | lgpl-2.1 |
JonasHarnau/apc | apc/tests/test_plot_residuals.py | 1 | 1196 | import unittest
import apc
import matplotlib.pyplot as plt
class TestPlotResiduals(unittest.TestCase):
def test_TA(self):
model = apc.Model()
model.data_from_df(apc.loss_TA(), data_format='CL')
model.fit('od_poisson_response', 'AC')
for sr in ('start', 'mean', 'end', False):
... | gpl-3.0 |
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