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 |
|---|---|---|---|---|---|
DJArmstrong/autovet | Features/Centroiding/scripts/old/simulate_signal.py | 4 | 8723 | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 2 15:05:11 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
import batman
import eb
def simulate(... | gpl-3.0 |
surligas/gnuradio | gr-digital/examples/berawgn.py | 32 | 4886 | #!/usr/bin/env python
#
# Copyright 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 optio... | gpl-3.0 |
JsNoNo/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 |
kohr-h/odl | odl/tomo/analytic/filtered_back_projection.py | 2 | 21537 | # coding: utf-8
# Copyright 2014-2019 The ODL contributors
#
# This file is part of ODL.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
from __future__ import print... | mpl-2.0 |
justincassidy/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 |
timqian/sms-tools | lectures/6-Harmonic-model/plots-code/f0-TWM-errors-1.py | 22 | 3586 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackman
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
def TWM (pfreq, p... | agpl-3.0 |
mwcraig/aplpy | aplpy/tests/test_beam.py | 3 | 4530 | import os
import matplotlib
matplotlib.use('Agg')
import numpy as np
from astropy.tests.helper import pytest
from astropy import units as u
from astropy.io import fits
from .. import FITSFigure
header_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data/2d_fits')
HEADER = fits.Header.fromtextfile(... | mit |
BRD-CD/superset | tests/celery_tests.py | 8 | 11738 | """Unit tests for Superset Celery worker"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import json
import os
import subprocess
import time
import unittest
from past.builtins import basestring
import pandas as pd
... | apache-2.0 |
dotpmrcunha/gnuradio | gr-digital/examples/ofdm/gr_plot_ofdm.py | 77 | 10957 | #!/usr/bin/env python
#
# Copyright 2007 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 option)
... | gpl-3.0 |
alvarofierroclavero/scikit-learn | examples/ensemble/plot_forest_importances_faces.py | 403 | 1519 | """
=================================================
Pixel importances with a parallel forest of trees
=================================================
This example shows the use of forests of trees to evaluate the importance
of the pixels in an image classification task (faces). The hotter the pixel,
the more impor... | bsd-3-clause |
cathywu/Sentiment-Analysis | PyML-0.7.9/PyML/evaluators/resultsObjects.py | 2 | 28145 | import numpy
import random
import math
import os
import tempfile
import copy
import time
from PyML.utils import myio,misc
from PyML.evaluators import roc as roc_module
"""functionality for assessing classifier performance"""
__docformat__ = "restructuredtext en"
def scatter(r1, r2, statistic = 'roc', x1Label = '', ... | gpl-2.0 |
funbaker/astropy | astropy/visualization/tests/test_norm.py | 2 | 6687 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from numpy import ma
from numpy.testing import assert_allclose
from ..mpl_normalize import ImageNormalize, simple_norm
from ..interval import ManualInterval
from ..stretch import SqrtStretch
try:
import matplotlib ... | bsd-3-clause |
Fireblend/scikit-learn | sklearn/externals/joblib/parallel.py | 86 | 35087 | """
Helpers for embarrassingly parallel code.
"""
# Author: Gael Varoquaux < gael dot varoquaux at normalesup dot org >
# Copyright: 2010, Gael Varoquaux
# License: BSD 3 clause
from __future__ import division
import os
import sys
import gc
import warnings
from math import sqrt
import functools
import time
import thr... | bsd-3-clause |
DeveloperJose/Vision-Rat-Brain | feature_matching_v3/slider.py | 2 | 1193 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons
fig, ax = plt.subplots()
plt.subplots_adjust(left=0.25, bottom=0.25)
t = np.arange(0.0, 1.0, 0.001)
a0 = 5
f0 = 3
s = a0*np.sin(2*np.pi*f0*t)
l, = plt.plot(t, s, lw=2, color='red')
plt.axis([0, 1, -10, 10])
... | mit |
yunque/librosa | librosa/feature/rhythm.py | 1 | 5253 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''Rhythmic feature extraction'''
import numpy as np
import scipy.signal
import six
from .. import util
from ..core.audio import autocorrelate
from ..util.exceptions import ParameterError
__all__ = ['tempogram']
# -- Rhythmic features -- #
def tempogram(y=None, sr=22... | isc |
DailyActie/Surrogate-Model | 01-codes/scikit-learn-master/benchmarks/bench_plot_parallel_pairwise.py | 1 | 1250 | # Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD 3 clause
import time
import pylab as pl
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils import check_random_state
def plot(func):
random_state = check_random_state(0)
... | mit |
BhallaLab/moose-examples | neuroml/LIF/twoLIFxml_firing.py | 2 | 3087 | # -*- coding: utf-8 -*-
## all SI units
########################################################################################
## Plot the membrane potential for a leaky integrate and fire neuron with current injection
## Author: Aditya Gilra
## Creation Date: 2012-06-08
## Modification Date: 2012-06-08
#############... | gpl-2.0 |
dominicelse/scipy | scipy/interpolate/tests/test_rbf.py | 14 | 4604 | # Created by John Travers, Robert Hetland, 2007
""" Test functions for rbf module """
from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.testing import (assert_, assert_array_almost_equal,
assert_almost_equal, run_module_suite)
from numpy import l... | bsd-3-clause |
Vishluck/sympy | sympy/interactive/session.py | 43 | 15119 | """Tools for setting up interactive sessions. """
from __future__ import print_function, division
from distutils.version import LooseVersion as V
from sympy.core.compatibility import range
from sympy.external import import_module
from sympy.interactive.printing import init_printing
preexec_source = """\
from __futu... | bsd-3-clause |
pizzathief/numpy | numpy/lib/recfunctions.py | 2 | 56721 | """
Collection of utilities to manipulate structured arrays.
Most of these functions were initially implemented by John Hunter for
matplotlib. They have been rewritten and extended for convenience.
"""
from __future__ import division, absolute_import, print_function
import sys
import itertools
import numpy as np
im... | bsd-3-clause |
GuessWhoSamFoo/pandas | pandas/tests/arrays/test_integer.py | 1 | 22287 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from pandas.core.dtypes.generic import ABCIndexClass
import pandas as pd
from pandas.api.types import is_float, is_float_dtype, is_integer, is_scalar
from pandas.core.arrays import IntegerArray, integer_array
from pandas.core.arrays.integer import (
Int8Dty... | bsd-3-clause |
hlin117/scikit-learn | examples/calibration/plot_calibration_multiclass.py | 95 | 6971 | """
==================================================
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 |
srowen/spark | python/pyspark/pandas/tests/test_window.py | 15 | 13671 | #
# 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 |
giuliavezzani/giuliavezzani.github.io | markdown_generator/talks.py | 199 | 4000 |
# coding: utf-8
# # Talks markdown generator for academicpages
#
# Takes a TSV of talks with metadata and converts them for use with [academicpages.github.io](academicpages.github.io). This is an interactive Jupyter notebook ([see more info here](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_i... | mit |
liberatorqjw/scikit-learn | sklearn/semi_supervised/tests/test_label_propagation.py | 307 | 1974 | """ test the label propagation module """
import nose
import numpy as np
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {'kernel': 'rbf'}),
(label_propa... | bsd-3-clause |
imapp-pl/golem | scripts/blenderstats.py | 3 | 2743 | import click
import statistics
import math
import random
import matplotlib.pyplot as plt
@click.command()
@click.argument("results")
@click.option("--probs", default=0)
@click.option("--name", default="Rendering time")
@click.option("--plot/--no-plot", default=True)
@click.option("--repeat_prob/--no-repeat_prob", def... | gpl-3.0 |
roaminsight/roamresearch | BlogPosts/Outlier_detection/roam_outliers.py | 1 | 4609 | import numpy as np
import pandas as pd
from rpy2.robjects.packages import importr
from rpy2.robjects import pandas2ri
outlier = importr('outlierDetection')
anomaly = importr('AnomalyDetection')
def make_time_series(start_dt, end_dt, time_step, functions, random_state=None):
"""
Sklearn-style dataset creation... | apache-2.0 |
olgabot/seaborn | seaborn/palettes.py | 4 | 28814 | from __future__ import division
import colorsys
from itertools import cycle
import numpy as np
import matplotlib as mpl
from .external import husl
from .external.six import string_types
from .external.six.moves import range
from .utils import desaturate, set_hls_values, get_color_cycle
from .xkcd_rgb import xkcd_rgb... | bsd-3-clause |
blutooth/gp-svi | examples/maxsvi.py | 1 | 4900 | from __future__ import absolute_import
from __future__ import print_function
import matplotlib.pyplot as plt
import autograd.numpy as np
import autograd.numpy.random as npr
import autograd.scipy.stats.multivariate_normal as mvn
import autograd.scipy.stats.norm as norm
import gaussian_process as gp
import autograd.scip... | mit |
a-holm/MachinelearningAlgorithms | Regression/SimpleLinearRegression/regularLinearRegression2.py | 1 | 1740 | # -*- coding: utf-8 -*-
"""Simple linear regression for machine learning.
This file demonstrate knowledge of linear regression. By using
conventional libraries.The idea of linear regression is to take continuous
data and find the best fit of it to a line.
Simple linear regression just refers to the fact that the feat... | mit |
licode/xray-vision | xray_vision/qt_widgets/real_time.py | 6 | 10948 | # ######################################################################
# Copyright (c) 2014, Brookhaven Science Associates, Brookhaven #
# National Laboratory. All rights reserved. #
# #
# Redistribution and use in ... | bsd-3-clause |
dwillmer/numpy | numpy/core/fromnumeric.py | 9 | 98023 | """Module containing non-deprecated functions borrowed from Numeric.
"""
from __future__ import division, absolute_import, print_function
import types
import warnings
import numpy as np
from .. import VisibleDeprecationWarning
from . import multiarray as mu
from . import umath as um
from . import numerictypes as nt
... | bsd-3-clause |
quantumlib/Cirq | cirq-google/cirq_google/engine/calibration_test.py | 1 | 6828 | # Copyright 2019 The Cirq Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... | apache-2.0 |
joferkington/tutorials | 1512_Semblance_coherence_and_discontinuity/figures/figure_2.py | 1 | 5644 | """
Note that this is a very hackish script to put together this figure.
Forgive the sloppy approach.
"""
import numpy as np
import scipy.ndimage
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import basic_methods
from parent_directory import image_dir
def main():
fig, axe... | apache-2.0 |
UKPLab/sentence-transformers | examples/training/distillation/dimensionality_reduction.py | 1 | 4588 | """
The pre-trained models produce embeddings of size 512 - 1024. However, when storing a large
number of embeddings, this requires quite a lot of memory / storage.
In this example, we reduce the dimensionality of the embeddings to e.g. 128 dimensions. This significantly
reduces the required memory / storage while mai... | apache-2.0 |
bzero/statsmodels | statsmodels/tools/tests/test_pca.py | 25 | 13934 | from __future__ import print_function, division
from unittest import TestCase
import warnings
import numpy as np
from numpy.testing import assert_allclose, assert_equal, assert_raises
from numpy.testing.decorators import skipif
import pandas as pd
try:
import matplotlib.pyplot as plt
missing_matplotlib = Fal... | bsd-3-clause |
rahul-c1/scikit-learn | examples/applications/plot_model_complexity_influence.py | 25 | 6378 | """
==========================
Model Complexity Influence
==========================
Demonstrate how model complexity influences both prediction accuracy and
computational performance.
The dataset is the Boston Housing dataset (resp. 20 Newsgroups) for
regression (resp. classification).
For each class of models we m... | bsd-3-clause |
jmmease/pandas | pandas/tests/io/parser/header.py | 2 | 9626 | # -*- coding: utf-8 -*-
"""
Tests that the file header is properly handled or inferred
during parsing for all of the parsers defined in parsers.py
"""
import pytest
import numpy as np
import pandas.util.testing as tm
from pandas import DataFrame, Index, MultiIndex
from pandas.compat import StringIO, lrange, u
cla... | bsd-3-clause |
jamiebull1/geomeppy | geomeppy/view_geometry.py | 1 | 5755 | """Tool for visualising geometry."""
from typing import Optional, TYPE_CHECKING # noqa
if TYPE_CHECKING:
from geomeppy import IDF
from eppy.function_helpers import getcoords
from eppy.iddcurrent import iddcurrent
from six import StringIO
from six.moves.tkinter import TclError
try:
from mpl_toolkits.mplot3d i... | mit |
trislett/TFCE_mediation | tfce_mediation/misc_scripts/ica_tmi.py | 1 | 10476 | #!/usr/bin/env python
# tm_maths: math functions for vertex and voxel images
# Copyright (C) 2016 Tristram Lett
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License,... | gpl-3.0 |
kazemakase/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 |
rafiqsaleh/VERCE | verce-hpc-pe/src/wavePlot_INGV.py | 2 | 3058 | from verce.processing import *
import matplotlib.pyplot as plt
import matplotlib.dates as mdt
class WavePlot_INGV(SeismoPreprocessingActivity):
def compute(self):
self.outputdest=self.outputdest+"%s" % (self.parameters["filedestination"],);
try:
i... | mit |
hrjn/scikit-learn | sklearn/datasets/base.py | 13 | 29166 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import sys
import shutil
from os import environ... | bsd-3-clause |
jjx02230808/project0223 | sklearn/cluster/tests/test_hierarchical.py | 230 | 19795 | """
Several basic tests for hierarchical clustering procedures
"""
# Authors: Vincent Michel, 2010, Gael Varoquaux 2012,
# Matteo Visconti di Oleggio Castello 2014
# License: BSD 3 clause
from tempfile import mkdtemp
import shutil
from functools import partial
import numpy as np
from scipy import sparse
from... | bsd-3-clause |
CVML/scikit-learn | examples/svm/plot_svm_nonlinear.py | 268 | 1091 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learned by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn imp... | bsd-3-clause |
m3wolf/scimap | scimap/fullprof_refinement.py | 1 | 33866 | # -*- coding: utf-8 -*-
import logging
log = logging.getLogger(__name__)
from enum import Enum
import math
import os
from shutil import copy2
import re
from subprocess import call
import contextlib
import logging
log = logging.getLogger(__name__)
import warnings
import jinja2
import pandas as pd
import numpy as np
... | gpl-3.0 |
cmorgan/trading-with-python | historicDataDownloader/historicDataDownloader.py | 77 | 4526 | '''
Created on 4 aug. 2012
Copyright: Jev Kuznetsov
License: BSD
a module for downloading historic data from IB
'''
import ib
import pandas
from ib.ext.Contract import Contract
from ib.opt import ibConnection, message
from time import sleep
import tradingWithPython.lib.logger as logger
from pandas impor... | bsd-3-clause |
xwolf12/scikit-learn | sklearn/metrics/cluster/tests/test_unsupervised.py | 230 | 2823 | import numpy as np
from scipy.sparse import csr_matrix
from sklearn import datasets
from sklearn.metrics.cluster.unsupervised import silhouette_score
from sklearn.metrics import pairwise_distances
from sklearn.utils.testing import assert_false, assert_almost_equal
from sklearn.utils.testing import assert_raises_regexp... | bsd-3-clause |
voxlol/scikit-learn | examples/plot_multilabel.py | 87 | 4279 | # Authors: Vlad Niculae, Mathieu Blondel
# License: BSD 3 clause
"""
=========================
Multilabel classification
=========================
This example simulates a multi-label document classification problem. The
dataset is generated randomly based on the following process:
- pick the number of labels: n ... | bsd-3-clause |
nmartensen/pandas | pandas/tests/groupby/test_nth.py | 4 | 10186 | import numpy as np
import pandas as pd
from pandas import DataFrame, MultiIndex, Index, Series, isna
from pandas.compat import lrange
from pandas.util.testing import (
assert_frame_equal,
assert_produces_warning,
assert_series_equal)
from .common import MixIn
class TestNth(MixIn):
def test_first_las... | bsd-3-clause |
cshallue/models | research/keypointnet/main.py | 4 | 21991 | # Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | apache-2.0 |
scienceopen/starscale | PlotContrastStretch.py | 1 | 1828 | #!/usr/bin/env python
"""
Example of the Contrast Stretch options in AstroPy, that you might find handy
in cytometry or other non-astronomical pursuits as well.
"""
from pathlib import Path
from astropy.io import fits
import astropy.visualization as vis
from astropy.visualization.mpl_normalize import ImageNormalize
fro... | gpl-3.0 |
eseidel/native_client_patches | tools/modular-build/btarget.py | 1 | 20589 |
# Copyright 2010 The Native Client Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can
# be found in the LICENSE file.
import hashlib
import itertools
import optparse
import os
import re
import subprocess
import sys
import dirtree
import treemappers
def Unrepr(x):
... | bsd-3-clause |
jreback/pandas | pandas/core/indexes/interval.py | 1 | 41420 | """ define the IntervalIndex """
from functools import wraps
from operator import le, lt
import textwrap
from typing import TYPE_CHECKING, Any, List, Optional, Tuple, Union, cast
import numpy as np
from pandas._config import get_option
from pandas._libs import lib
from pandas._libs.interval import Interval, Interval... | bsd-3-clause |
vitaly-krugl/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_qtagg.py | 73 | 4972 | """
Render to qt from agg
"""
from __future__ import division
import os, sys
import matplotlib
from matplotlib import verbose
from matplotlib.figure import Figure
from backend_agg import FigureCanvasAgg
from backend_qt import qt, FigureManagerQT, FigureCanvasQT,\
show, draw_if_interactive, backend_version, \
... | agpl-3.0 |
wrightni/OSSP | lib/debug_tools.py | 1 | 6515 | from skimage import segmentation, exposure
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn import metrics
from lib import utils
def display_image(raw,watershed,classified,type):
# Save a color
empty_color... | mit |
studywolf/REACH-paper | analysis/06b-CB_correlations_plot.py | 1 | 4942 | import matplotlib.pyplot as plt
import numpy as np
import seaborn
import sys
folder = 'data/correlations-CB'
filename = 'CB_spikes'
n_trials = 10 # can be up to 100
n_neurons = 10000
# to plot correlations with different movement parameters call
# script with an argument corresponding to data type you want to plot
... | gpl-3.0 |
wanderknight/trading-with-python | lib/vixFutures.py | 79 | 4157 | # -*- coding: utf-8 -*-
"""
set of tools for working with VIX futures
@author: Jev Kuznetsov
Licence: GPL v2
"""
import datetime as dt
from pandas import *
import os
import urllib2
#from csvDatabase import HistDataCsv
m_codes = dict(zip(range(1,13),['F','G','H','J','K','M','N','Q','U','V','X','Z'])) #m... | bsd-3-clause |
jamesjarlathlong/resourceful | two_agents.py | 1 | 8233 | import os
from agent import *
import asyncio
from qlearn import QLearn
from sarsa import Sarsa
import itertools
import functools
import json
import random
import sklearn
import collections
import websockets
import json
import copy
import time
###Helper functions###
def merge(dicts):
super_dict = collections.defaul... | mit |
rbaravalle/imfractal | tests/testcomparison.py | 1 | 8144 | """
Copyright (c) 2013 Rodrigo Baravalle
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following... | bsd-3-clause |
fermiPy/fermipy | fermipy/stack/stack_plotting_utils.py | 1 | 13559 | #!/usr/bin/env python
#
"""
Utilities to plot dark matter analyses
"""
import numpy as np
from fermipy import sed_plotting
ENERGY_AXIS_LABEL = r'Energy [MeV]'
ENERGY_FLUX_AXIS_LABEL = r'Energy Flux [MeV s$^{-1}$ cm$^{-2}$]'
FLUX_AXIS_LABEL = r'Flux [ph s$^{-1}$ cm$^{-2}$]'
DELTA_LOGLIKE_AXIS_LABEL = r'$\Delta \log... | bsd-3-clause |
ckinzthompson/biasd | biasd/gui/plotter.py | 1 | 2859 | # -*- coding: utf-8 -*-®
'''
PyQt trace plotter widget
'''
from PyQt5.QtWidgets import QWidget,QSizePolicy
# Make sure that we are using QT5
import matplotlib
matplotlib.use('Qt5Agg')
import numpy as np
from matplotlib.backends.backend_qt5agg import FigureCanvas
import matplotlib.pyplot as plt
class trace_plotter(Fi... | mit |
ZhangXinNan/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py | 39 | 32726 | # 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 |
stinebuu/nest-simulator | pynest/examples/mc_neuron.py | 12 | 7554 | # -*- coding: utf-8 -*-
#
# mc_neuron.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 License, or
#... | gpl-2.0 |
sebastian-nagel/cc-crawl-statistics | plot/crawl_size.py | 1 | 10348 | import pandas
import re
import sys
import types
from collections import defaultdict
from hyperloglog import HyperLogLog
from crawlplot import CrawlPlot
from crawlstats import CST, CrawlStatsJSONDecoder, HYPERLOGLOG_ERROR,\
MonthlyCrawl
class CrawlSizePlot(CrawlPlot):
def __init__(self):
self.size =... | apache-2.0 |
mashaoze/esp-idf | tools/tiny-test-fw/Utility/LineChart.py | 3 | 1681 | # Copyright 2015-2017 Espressif Systems (Shanghai) PTE LTD
#
# 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 ... | apache-2.0 |
mefortunato/pysimm | Examples/11_pim_adsorption/run.py | 1 | 6555 | from pysimm import cassandra
from pysimm import system
from os import path as osp
import numpy
import re
from matplotlib import pyplot as mplp
try:
import pyiast
import pandas
except ImportError:
print('Either PyIAST or Pandas (that is PyIAST dependence) packages are not installed or cannot be found by thi... | mit |
vidartf/hyperspyUI | hyperspyui/mdi_mpl_backend.py | 1 | 11413 | # -*- coding: utf-8 -*-
# Copyright 2014-2016 The HyperSpyUI developers
#
# This file is part of HyperSpyUI.
#
# HyperSpyUI 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
#... | gpl-3.0 |
LiuVII/Machine_learning_and_AI | Tensorflow_MNIST/fcnn_2hl_mnist.py | 1 | 3743 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import numpy as np
import math
import csv
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", o... | mit |
perimosocordiae/scipy | scipy/special/_precompute/wright_bessel.py | 12 | 12928 | """Precompute coefficients of several series expansions
of Wright's generalized Bessel function Phi(a, b, x).
See https://dlmf.nist.gov/10.46.E1 with rho=a, beta=b, z=x.
"""
from argparse import ArgumentParser, RawTextHelpFormatter
import numpy as np
from scipy.integrate import quad
from scipy.optimize import minimize... | bsd-3-clause |
mikebenfield/scikit-learn | sklearn/utils/tests/test_testing.py | 29 | 7316 | import warnings
import unittest
import sys
from sklearn.utils.testing import (
assert_raises,
assert_less,
assert_greater,
assert_less_equal,
assert_greater_equal,
assert_warns,
assert_no_warnings,
assert_equal,
set_random_state,
assert_raise_message,
ignore_warnings)
from ... | bsd-3-clause |
tencrance/cool-config | ml_keras_learn/tutorials/sklearnTUT/sk7_normalization.py | 2 | 1190 | # View more python learning tutorial on my Youtube and Youku channel!!!
# Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg
# Youku video tutorial: http://i.youku.com/pythontutorial
"""
Please note, this code is only for python 3+. If you are using python 2+, please modify the code acco... | mit |
eickenberg/scikit-learn | examples/cluster/plot_cluster_comparison.py | 8 | 4865 | """
=========================================================
Comparing different clustering algorithms on toy datasets
=========================================================
This example aims at showing characteristics of different
clustering algorithms on datasets that are "interesting"
but still in 2D. The last ... | bsd-3-clause |
tiagofrepereira2012/tensorflow | tensorflow/contrib/metrics/python/kernel_tests/histogram_ops_test.py | 130 | 9577 | # 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 |
cactusbin/nyt | matplotlib/examples/mplot3d/trisurf3d_demo2.py | 8 | 1761 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.tri as mtri
# u, v are parameterisation variables
u = (np.linspace(0, 2.0 * np.pi, endpoint=True, num=50) * np.ones((10, 1))).flatten()
v = np.repeat(np.linspace(-0.5, 0.5, endpoint=True, num=10), repeats=50).f... | unlicense |
ElectronicNose/Electronic-Nose | analysis.py | 1 | 27688 | #analysis files
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtWidgets import QFileDialog
from analysis_gui import Ui_Analysis
import numpy as np
import matplotlib,math,csv
matplotlib.use('Qt5Agg')
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backen... | mit |
huobaowangxi/scikit-learn | benchmarks/bench_plot_incremental_pca.py | 374 | 6430 | """
========================
IncrementalPCA benchmark
========================
Benchmarks for IncrementalPCA
"""
import numpy as np
import gc
from time import time
from collections import defaultdict
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_lfw_people
from sklearn.decomposition import Incre... | bsd-3-clause |
bioinfo-core-BGU/neatseq-flow_modules | neatseq_flow_modules/Liron/cgMLST_and_MLST_typing_module/Merge_tab_files.py | 2 | 7863 | import os, re
import argparse
import pandas as pd
STRING_TYPES = (str, str, bytes)
parser = argparse.ArgumentParser(description='Merge tabular files')
parser.add_argument('-D', type=str,dest='directory', nargs='+',
help='Location to search')
parser.add_argument('-R', dest='Regular', type=str,
... | gpl-3.0 |
georgetown-analytics/skidmarks | bin/stop.py | 1 | 3543 | # -*- coding: utf-8 -*-
###############################################################################
# Information
###############################################################################
# Created by Linwood Creekmore
# Input by Vikram Mittal
# In partial fulfillment of the requirements for the Georgetow... | mit |
JT5D/scikit-learn | examples/decomposition/plot_pca_iris.py | 8 | 1783 | #!/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 |
BhallaLab/moose-full | moose-core/tests/python/Rallpacks/rallpacks_cable_hhchannel.py | 2 | 8099 | #!/usr/bin/env python
"""rallpacks_cable_hhchannel.py:
A cable with 1000 compartments with HH-type channels in it.
Last modified: Wed May 21, 2014 09:51AM
"""
__author__ = "Dilawar Singh"
__copyright__ = "Copyright 2013, NCBS Bangalore"
__credits__ = ["NCBS Bangalore", "Bhalla L... | gpl-2.0 |
kojiagile/CLAtoolkit | clatoolkit_project/dashboard/utils.py | 1 | 63217 | from django.db import connection
from gensim import corpora, models, similarities
from collections import defaultdict
import pyLDAvis.gensim
import os
import re
import json
import copy
import funcy as fp
import numpy as np
import subprocess
import jgraph
import igraph
import datetime
from pprint import pprint
from coll... | gpl-3.0 |
desihub/desispec | py/desispec/desi_create_bias_dark.py | 1 | 4950 | import argparse
import os
import fitsio
import astropy.io.fits as pyfits
from astropy.io import fits
import subprocess
import pandas as pd
import time
import numpy as np
import psycopg2
import hashlib
import pdb
from os import listdir
import matplotlib.pyplot as plt
"""
################################################... | bsd-3-clause |
mkraemer67/pylearn2 | pylearn2/models/independent_multiclass_logistic.py | 44 | 2491 | """
Multiclass-classification by taking the max over a set of one-against-rest
logistic classifiers.
"""
__authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googleg... | bsd-3-clause |
AndrewRook/PyWPA | nflwin/model.py | 1 | 25071 | """Tools for creating and running the model."""
from __future__ import print_function, division
import os
import numpy as np
from scipy import integrate
from scipy import stats
from sklearn.ensemble import RandomForestClassifier
from sklearn.externals import joblib
from sklearn.linear_model import LogisticRegression... | mit |
abhishekgahlot/scikit-learn | sklearn/preprocessing/tests/test_imputation.py | 28 | 11950 | import numpy as np
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_true
from sklearn.preprocessing.imputa... | bsd-3-clause |
ligovirgo/gwdetchar | gwdetchar/scattering/tests/test_plot.py | 1 | 1814 | # -*- coding: utf-8 -*-
# Copyright (C) Alex Urban (2019)
#
# This file is part of the GW DetChar python package.
#
# GW DetChar is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License,... | gpl-3.0 |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/misc/coords_report.py | 1 | 1190 | """
=============
Coords Report
=============
Override the default reporting of coords.
"""
import matplotlib.pyplot as plt
import numpy as np
# nodebox section
if __name__ == '__builtin__':
# were in nodebox
import os
import tempfile
W = 800
inset = 20
size(W, 600)
plt.cla()
plt.clf(... | mit |
mantidproject/mantid | Framework/PythonInterface/test/python/mantid/plots/compatabilityTest.py | 3 | 8145 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
# T... | gpl-3.0 |
breznak/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/mlab.py | 69 | 104273 | """
Numerical python functions written for compatability with matlab(TM)
commands with the same names.
Matlab(TM) compatible functions
-------------------------------
:func:`cohere`
Coherence (normalized cross spectral density)
:func:`csd`
Cross spectral density uing Welch's average periodogram
:func:`detrend`... | agpl-3.0 |
moutai/scikit-learn | examples/linear_model/plot_sgd_iris.py | 58 | 2202 | """
========================================
Plot multi-class SGD on the iris dataset
========================================
Plot decision surface of multi-class SGD on iris dataset.
The hyperplanes corresponding to the three one-versus-all (OVA) classifiers
are represented by the dashed lines.
"""
print(__doc__)
... | bsd-3-clause |
beepee14/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 65 | 50308 | # Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com> (main author)
# Mathieu Blondel (partial_fit support)
#
# License: BSD 3 clause
"""Classification and regression using Stochastic Gradient Descent (SGD)."""
import numpy as np
import scipy.sparse as sp
from abc import ABCMeta, abstractmethod
from ... | bsd-3-clause |
wazeerzulfikar/scikit-learn | sklearn/ensemble/tests/test_bagging.py | 7 | 29340 | """
Testing for the bagging ensemble module (sklearn.ensemble.bagging).
"""
# Author: Gilles Louppe
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.te... | bsd-3-clause |
stylianos-kampakis/scikit-learn | sklearn/metrics/ranking.py | 79 | 25426 | """Metrics to assess performance on classification task given scores
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.... | bsd-3-clause |
LevinJ/ud730-Deep-Learning | A1_notmnistdataset/extractimage.py | 1 | 2248 | from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
import tarfile
from IPython.display import display, Image
from scipy import ndimage
from sklearn.linear_model import LogisticRegression
from six.moves.urllib.request import urlretrieve
from six.moves import cPi... | gpl-2.0 |
deuxpi/pytrainer | pytrainer/gui/windowmain.py | 1 | 103653 | #!/usr/bin/python
# -*- coding: utf-8 -*-
#Copyright (C) Fiz Vazquez vud1@sindominio.net
# Modified by dgranda
#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 2
#of the License, or... | gpl-2.0 |
google/eng-edu | ml/guides/text_classification/vectorize_data.py | 1 | 3645 | """Module to vectorize data.
Converts the given training and validation texts into numerical tensors.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import numpy as np
from tensorflow.python.keras.preprocessing import sequence
... | apache-2.0 |
maciekcc/tensorflow | tensorflow/contrib/learn/python/learn/dataframe/transforms/in_memory_source.py | 26 | 6490 | # 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 |
zooniverse/aggregation | active_weather/old/paper_otsu.py | 1 | 5306 | import matplotlib
import matplotlib.pyplot as plt
import cv2
from skimage import data
from skimage.morphology import disk
from skimage.filters import threshold_otsu, rank
from skimage.util import img_as_ubyte
from os import popen
from active_weather import ActiveWeather
import numpy as np
directory = "/home/ggdhines/D... | apache-2.0 |
Nyker510/scikit-learn | sklearn/covariance/graph_lasso_.py | 127 | 25626 | """GraphLasso: sparse inverse covariance estimation with an l1-penalized
estimator.
"""
# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
# Copyright: INRIA
import warnings
import operator
import sys
import time
import numpy as np
from scipy import linalg
from .empirical_covariance_ im... | bsd-3-clause |
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