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 |
|---|---|---|---|---|---|
chrissly31415/amimanera | convnet_utils/rotate_offline.py | 1 | 4162 | #!/usr/bin/python
# coding: utf-8
import os,glob,sys
from datetime import datetime
from random import random,randint,choice
import matplotlib.pyplot as plt
import numpy as np
import PIL
from PIL import Image,ImageFilter,ImageChops
#Usage: python ./rotate_offline.py /home/xxx/data/train
#rotation_angles = [180]
d... | lgpl-3.0 |
aswolf/xmeos | examples/test-RTpress-MgSiO3/fit-RTpress-mdsim-Spera2011.py | 1 | 148710 | import numpy as np
import matplotlib as mpl
# mpl.use('WXAgg',warn=False, force=True)
# mpl.use('GTKAgg',warn=False, force=True) # Gtk* backend requires pygtk to be installed.
# mpl.use('Qt4Agg',warn=False, force=True) # PyQt4
# mpl.use('GTK3Agg',warn=False, force=True) # PyQt4
# mpl.use('TKAgg',warn=False, force=True... | mit |
RPGOne/Skynet | scikit-learn-0.18.1/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 |
lukeshingles/artistools | artistools/nltepops/plotnltepops.py | 1 | 24895 | #!/usr/bin/env python3
"""Artistools - NLTE population related functions."""
import argparse
import math
import multiprocessing
import os
# import re
# import sys
# from functools import lru_cache
# from functools import partial
from pathlib import Path
# from itertools import chain
import matplotlib.pyplot as plt
imp... | mit |
MatthieuBizien/scikit-learn | examples/gaussian_process/plot_gpr_noisy_targets.py | 64 | 3706 | """
=========================================================
Gaussian Processes regression: basic introductory example
=========================================================
A simple one-dimensional regression example computed in two different ways:
1. A noise-free case
2. A noisy case with known noise-level per ... | bsd-3-clause |
michigraber/scikit-learn | sklearn/utils/tests/test_class_weight.py | 140 | 11909 | import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_blobs
from sklearn.utils.class_weight import compute_class_weight
from sklearn.utils.class_weight import compute_sample_weight
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testin... | bsd-3-clause |
PatrickOReilly/scikit-learn | examples/svm/plot_rbf_parameters.py | 3 | 8010 | '''
==================
RBF SVM parameters
==================
This example illustrates the effect of the parameters ``gamma`` and ``C`` of
the Radial Basis Function (RBF) kernel SVM.
Intuitively, the ``gamma`` parameter defines how far the influence of a single
training example reaches, with low values meaning 'far' a... | bsd-3-clause |
lekshmideepu/nest-simulator | pynest/nest/tests/test_synapsecollection.py | 13 | 15095 | # -*- coding: utf-8 -*-
#
# test_synapsecollection.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 ... | gpl-2.0 |
pydata/xarray | xarray/core/dataset.py | 1 | 288325 | import copy
import datetime
import inspect
import sys
import warnings
from collections import defaultdict
from html import escape
from numbers import Number
from operator import methodcaller
from pathlib import Path
from typing import (
TYPE_CHECKING,
Any,
Callable,
Collection,
DefaultDict,
Dict... | apache-2.0 |
3manuek/scikit-learn | benchmarks/bench_20newsgroups.py | 377 | 3555 | from __future__ import print_function, division
from time import time
import argparse
import numpy as np
from sklearn.dummy import DummyClassifier
from sklearn.datasets import fetch_20newsgroups_vectorized
from sklearn.metrics import accuracy_score
from sklearn.utils.validation import check_array
from sklearn.ensemb... | bsd-3-clause |
CivicKnowledge/rowgenerators | rowgenerators/appurl/file/shapefile.py | 1 | 2514 | # -*- coding: utf-8 -*-
# Copyright (c) 2016 Civic Knowledge. This file is licensed under the terms of the
# MIT License, included in this distribution as LICENSE.txt
"""
"""
from .file import FileUrl
from rowgenerators.appurl.web import WebUrl
from rowgenerators.appurl.archive.zip import ZipUrl
class ShapefileUrl... | mit |
nguyentu1602/statsmodels | statsmodels/datasets/statecrime/data.py | 25 | 3128 | #! /usr/bin/env python
"""Statewide Crime Data"""
__docformat__ = 'restructuredtext'
COPYRIGHT = """Public domain."""
TITLE = """Statewide Crime Data 2009"""
SOURCE = """
All data is for 2009 and was obtained from the American Statistical Abstracts except as indicated below.
"""
DESCRSHORT = """State ... | bsd-3-clause |
togawa28/mousestyles | mousestyles/ultradian/tests/test_ultradian.py | 3 | 9797 | from __future__ import (absolute_import, division,
print_function, unicode_literals)
import numpy as np
import pandas as pd
import statsmodels
import mousestyles.ultradian as ultradian
import pytest
# aggregate_interval test
def test_aggregate_interval():
with pytest.raises(ValueError) as... | bsd-2-clause |
CoolProp/CoolProp | dev/scripts/fit_avoid_ECS.py | 2 | 4679 | from CoolProp import CoolProp as CP
from PDSim.misc.datatypes import Collector
import numpy as np
import matplotlib.pyplot as plt
from scipy.odr import *
import textwrap
#
#fluid = 'Propane'
#Rfluid = 'REFPROP-propane'
#e_k = 263.88
#sigma = 0.49748
#
fluid = 'DimethylEther'
Rfluid = 'REFPROP-DME'
e_k = 329.72
sigma =... | mit |
karvenka/sp17-i524 | project/S17-IR-P012/code/binarize.py | 21 | 1096 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 4 15:56:31 2017
I524 Project: OCR
Preprocessing
Binarization
@author: saber
"""
import numpy as np
import cv2
import matplotlib.pyplot as plt
image_path = 'sample1.png'
image_arr = cv2.imread(image_path, 0)
plt.figure(1)
plt.subplot(311)
# Plot hi... | apache-2.0 |
vortex-ape/scikit-learn | sklearn/preprocessing/tests/test_base.py | 18 | 3566 | import numpy as np
import pytest
from scipy import sparse
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raise_message
from sklearn.preprocessing._encoders import _transform_selected
from sklearn.preprocessing.data import Binarizer
def toarray(a):
if hasattr(a, "toa... | bsd-3-clause |
barney-NG/pyCAMTracker | src/filterpy/kalman/tests/test_fm.py | 2 | 2152 | # -*- coding: utf-8 -*-
"""Copyright 2015 Roger R Labbe Jr.
FilterPy library.
http://github.com/rlabbe/filterpy
Documentation at:
https://filterpy.readthedocs.org
Supporting book at:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
This is licensed under an MIT license. See the readme.MD file
for mor... | mit |
johannah/iceview | iceview/build_mosaic.py | 1 | 8615 | #!/usr/bin/env python
from shutil import copyfile
import subprocess
from subprocess import Popen, PIPE
from multiprocessing import Pool, freeze_support, cpu_count
import matplotlib.pyplot as plt
import itertools
import os
from glob import glob
import numpy as np
import argparse
import sys
import logging
from copy imp... | bsd-3-clause |
dipanjanS/text-analytics-with-python | Old-First-Edition/Ch07_Semantic_and_Sentiment_Analysis/wordnet_demo.py | 1 | 5420 | # -*- coding: utf-8 -*-
"""
Created on Thu Sep 22 23:00:59 2016
@author: DIP
"""
from nltk.corpus import wordnet as wn
import pandas as pd
term = 'fruit'
synsets = wn.synsets(term)
print 'Total Synsets:', len(synsets)
# synsets for fruit
for synset in synsets:
print 'Synset:', synset
print 'Part of speech... | apache-2.0 |
lail3344/sms-tools | lectures/06-Harmonic-model/plots-code/spectral-peaks.py | 22 | 1161 | 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 |
jmetzen/scikit-learn | sklearn/datasets/__init__.py | 72 | 3807 | """
The :mod:`sklearn.datasets` module includes utilities to load datasets,
including methods to load and fetch popular reference datasets. It also
features some artificial data generators.
"""
from .base import load_diabetes
from .base import load_digits
from .base import load_files
from .base import load_iris
from .... | bsd-3-clause |
jpautom/scikit-learn | examples/manifold/plot_mds.py | 45 | 2731 | """
=========================
Multi-dimensional scaling
=========================
An illustration of the metric and non-metric MDS on generated noisy data.
The reconstructed points using the metric MDS and non metric MDS are slightly
shifted to avoid overlapping.
"""
# Author: Nelle Varoquaux <nelle.varoquaux@gmail.... | bsd-3-clause |
altairpearl/scikit-learn | examples/cluster/plot_segmentation_toy.py | 91 | 3522 | """
===========================================
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 |
Kate-Willett/HadISDH_Marine_Build | EUSTACE_SST_MAT/PlotMetaData_APR2016.py | 1 | 47963 | #!/usr/local/sci/bin/python
# PYTHON2.7
#
# Author: Kate Willett
# Created: 1 April 2016
# Last update: 1 April 2016
# Location: /data/local/hadkw/HADCRUH2/MARINE/EUSTACEMDS/EUSTACE_SST_MAT/
# GitHub: https://github.com/Kate-Willett/HadISDH_Marine_Build/
# -----------------------
# CODE PURPOSE AND OUTPUT
# -----... | cc0-1.0 |
cainiaocome/scikit-learn | sklearn/utils/tests/test_estimator_checks.py | 202 | 3757 | import scipy.sparse as sp
import numpy as np
import sys
from sklearn.externals.six.moves import cStringIO as StringIO
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.utils.testing import assert_raises_regex, assert_true
from sklearn.utils.estimator_checks import check_estimator
from sklearn.utils.... | bsd-3-clause |
rbalda/neural_ocr | env/lib/python2.7/site-packages/matplotlib/_cm.py | 15 | 94005 | """
Nothing here but dictionaries for generating LinearSegmentedColormaps,
and a dictionary of these dictionaries.
Documentation for each is in pyplot.colormaps()
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
_binary_data = {
... | mit |
gdikos/trade-smart | analyzer.py | 1 | 2760 | import datetime as dt
import math
import numpy as np
import pandas as pd
# QSTK Imports
import QSTK.qstkutil.DataAccess as da
import QSTK.qstkutil.tsutil as tsu
def get_values_list(s_file_path):
df_values_list = pd.read_csv(s_file_path, sep=',', header=None)
df_values_list.columns = ["year", "month", "day", "... | mit |
bhillmann/gingivere | gingivere/process.py | 2 | 2014 | from classifiers import make_simple_lr
import numpy as np
from sklearn.cross_validation import StratifiedKFold
from sklearn.metrics import roc_auc_score
from sklearn.metrics import classification_report
from gingivere.utilities.shelve import insert_shelve, load_shelve
def process_data(target, X, y, paths, submission=... | mit |
mikaem/spectralDNS | demo/OrrSommerfeld.py | 4 | 8935 | """Orr-Sommerfeld"""
import warnings
from numpy import real, pi, exp, zeros, imag, sqrt, log10, sum
from spectralDNS import config, get_solver, solve
from spectralDNS.utilities import dx
#from spectralDNS.utilities import reset_profile
from OrrSommerfeld_shen import OrrSommerfeld
try:
import matplotlib.pyplot as p... | gpl-3.0 |
JosmanPS/scikit-learn | examples/feature_stacker.py | 246 | 1906 | """
=================================================
Concatenating multiple feature extraction methods
=================================================
In many real-world examples, there are many ways to extract features from a
dataset. Often it is beneficial to combine several methods to obtain good
performance. Th... | bsd-3-clause |
stwunsch/gnuradio | gr-utils/python/utils/plot_fft_base.py | 23 | 10512 | #!/usr/bin/env python
#
# Copyright 2007,2008,2011 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your ... | gpl-3.0 |
amirhmoin/recodev | RecoDev-Prototype/extend_data/extend.py | 1 | 1108 | '''
import sys
sys.path.append('..')
'''
from master_utils import *
import numpy as np
import os
import MySQLdb
from lda import LDA
from sklearn.decomposition import LatentDirichletAllocation
import datetime
import lda_t1
class BugEvent:
def __init__(self, start, end, topic, id, final):
self.star... | bsd-3-clause |
crichardson17/starburst_atlas | Low_resolution_sims/DustFree_LowRes/Padova_inst/padova_inst_2/UV2.py | 33 | 7365 | import csv
import matplotlib.pyplot as plt
from numpy import *
import scipy.interpolate
import math
from pylab import *
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import matplotlib.patches as patches
from matplotlib.path import Path
import os
# --------------------------------------------------... | gpl-2.0 |
PhenixI/machine-learning | 1_supervised_classification/15-SVM/svm/svm.py | 1 | 1315 | #for more info and material (source codes )about lr please visit: https:https://github.com/PhenixI/machine-learning/tree/master/15-SVM
#load dataset
from sklearn import datasets
import numpy as np
iris = datasets.load_iris()
X= iris.data[:,[2,3]]
y = iris.target
#split the dataset into separate training and test da... | gpl-2.0 |
Lokke/eden | modules/tests/smoke/broken_links.py | 16 | 26739 | """ Sahana Eden Test Framework
@copyright: 2011-2015 (c) Sahana Software Foundation
@license: MIT
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, incl... | mit |
heistermann/wradlib | wradlib/tests/test_vis.py | 1 | 6099 | #!/usr/bin/env python
# Copyright (c) 2011-2018, wradlib developers.
# Distributed under the MIT License. See LICENSE.txt for more info.
import sys
import unittest
import wradlib.vis as vis
import wradlib.georef as georef
import numpy as np
import matplotlib.pyplot as pl
pl.interactive(True) # noqa
from tempfile imp... | mit |
HyperloopTeam/FullOpenMDAO | lib/python2.7/site-packages/mpl_toolkits/exceltools.py | 8 | 3830 | """
Some io tools for excel -- requires xlwt
Example usage:
import matplotlib.mlab as mlab
import mpl_toolkits.exceltools as exceltools
r = mlab.csv2rec('somefile.csv', checkrows=0)
formatd = dict(
weight = mlab.FormatFloat(2),
change = mlab.FormatPercent(2),
cost = mlab.Fo... | gpl-2.0 |
devs1991/test_edx_docmode | venv/lib/python2.7/site-packages/sklearn/manifold/isomap.py | 2 | 7813 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD, (C) 2011
import numpy as np
import warnings
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_arrays
from ..utils.gra... | agpl-3.0 |
RMKD/networkx | examples/graph/unix_email.py | 62 | 2683 | #!/usr/bin/env python
"""
Create a directed graph, allowing multiple edges and self loops, from
a unix mailbox. The nodes are email addresses with links
that point from the sender to the recievers. The edge data
is a Python email.Message object which contains all of
the email message data.
This example shows the po... | bsd-3-clause |
kinverarity1/geotransect | autowrap.py | 2 | 3875 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Defines various data containers for plotting a transect.
From http://stackoverflow.com/questions/4018860
:author: Joe Kington
:copyright: 2010 Joe Kington
:license: CC-BY-SA
"""
def on_draw(event, axis=None):
"""
Auto-wraps all text objects in a figure at dr... | apache-2.0 |
ZeromusSoftware/RPi3500 | big_data/pi_performance/pi_performance.py | 1 | 2243 | import numpy as np
import time
import matplotlib.pyplot as plt
from scipy.stats import pearsonr
#we are going to calculate pi with an integration of
#arctan(x)' between 0 and 1 (that calculates pi/4)
def darctan(x) : # we introduce the arctan(x)'function
result = 1/(1+x**2)
return result
def pi(n) : # n will be ... | gpl-2.0 |
untom/scikit-learn | benchmarks/bench_sample_without_replacement.py | 397 | 8008 | """
Benchmarks for sampling without replacement of integer.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import operator
import matplotlib.pyplot as plt
import numpy as np
import random
from sklearn.externals.six.moves i... | bsd-3-clause |
mmilutinovic1313/zipline-with-algorithms | zipline/history/history_container.py | 18 | 33931 | #
# Copyright 2014 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... | apache-2.0 |
dimroc/tensorflow-mnist-tutorial | lib/python3.6/site-packages/tensorflow/contrib/learn/__init__.py | 8 | 2286 | # 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 |
Delosari/dazer | quality_checks/compare_reddening_laws.py | 1 | 3890 | import pyneb as pn
import matplotlib.pyplot as plt
from numpy import linspace, array
from bin.dazer_methods import Dazer
rc = pn.RedCorr()
red_curve, Rv = 'G03', 2.5
rc.R_V = Rv
rc.law = 'G03 LMC'
dz = Dazer()
f, ax = plt.subplots(figsize = (10,10))
rc.plot(laws='G03 LMC', ax=ax)
wave = linspace(3000, 70... | mit |
robcarver17/pysystemtrade | sysobjects/fills.py | 1 | 3211 | from collections import namedtuple
import pandas as pd
from syscore.objects import missing_order
from sysexecution.orders.list_of_orders import listOfOrders
from sysexecution.orders.base_orders import Order
Fill = namedtuple("Fill", ["date", "qty", "price"])
class listOfFills(list):
def __init__(self, list_of_... | gpl-3.0 |
hrjn/scikit-learn | sklearn/feature_extraction/tests/test_image.py | 38 | 11165 | # Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
import numpy as np
import scipy as sp
from scipy import ndimage
from numpy.testing import assert_raises
from sklearn.feature_extraction.image import (
img_to_gra... | bsd-3-clause |
pfnet/chainercv | chainercv/visualizations/vis_point.py | 3 | 2009 | from __future__ import division
import numpy as np
import six
from chainercv.visualizations.vis_image import vis_image
def vis_point(img, point, visible=None, ax=None):
"""Visualize points in an image.
Example:
>>> import chainercv
>>> import matplotlib.pyplot as plt
>>> dataset = ... | mit |
rusucosmin/courses | ml/ex03/template/plots.py | 3 | 1381 | # -*- coding: utf-8 -*-
"""a function of ploting figures."""
import numpy as np
from build_polynomial import *
import matplotlib.pyplot as plt
def plot_fitted_curve(y, x, weights, degree, ax):
"""plot the fitted curve."""
ax.scatter(x, y, color='b', s=12, facecolors='none', edgecolors='r')
xvals = np.aran... | mit |
sci-wms/sci-wms | wms/data_handler.py | 1 | 2886 | # -*- coding: utf-8 -*-
import io
import numpy as np
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg
from django.http.response import HttpResponse
def lat_lon_subset_idx(lon, lat, lonmin, latmin, lonmax, latmax, padding=0.18):
"""
A function to return the ind... | gpl-3.0 |
zerothi/sisl | sisl/viz/plotly/input_fields/queries.py | 1 | 17709 | # 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 collections import defaultdict
import itertools
import numpy as np
from .._input_field import InputField
from .dro... | lgpl-3.0 |
YihaoLu/statsmodels | statsmodels/tsa/statespace/tests/test_structural.py | 4 | 9003 | """
Tests for structural time series models
Author: Chad Fulton
License: Simplified-BSD
"""
from __future__ import division, absolute_import, print_function
import numpy as np
import pandas as pd
import os
import warnings
from statsmodels.datasets import macrodata
from statsmodels.tsa.statespace import structural
fr... | bsd-3-clause |
ClimbsRocks/scikit-learn | sklearn/metrics/tests/test_common.py | 2 | 42544 | from __future__ import division, print_function
from functools import partial
from itertools import product
import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_multilabel_classification
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils.multiclass import type_of_target
fro... | bsd-3-clause |
pprett/scikit-learn | examples/preprocessing/plot_robust_scaling.py | 85 | 2698 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Robust Scaling on Toy Data
=========================================================
Making sure that each Feature has approximately the same scale can be a
crucial preprocessing step. However, when data contains o... | bsd-3-clause |
meduz/scikit-learn | examples/neural_networks/plot_mlp_training_curves.py | 58 | 3692 | """
========================================================
Compare Stochastic learning strategies for MLPClassifier
========================================================
This example visualizes some training loss curves for different stochastic
learning strategies, including SGD and Adam. Because of time-constrai... | bsd-3-clause |
fperez/sympy | examples/intermediate/mplot3d.py | 6 | 1197 | #!/usr/bin/env python
"""Matplotlib 3D plotting example
Demonstrates plotting with matplotlib.
"""
from sympy import Basic, sin, Symbol
from sample import sample
def mplot3d(f, var1, var2, show=True):
"""
Plot a 3d function using matplotlib/Tk.
"""
import warnings
warnings.filterwarnings("ignore... | bsd-3-clause |
pazeshun/jsk_apc | demos/instance_occlsegm/instance_occlsegm_lib/datasets/apc/apc2016/mit.py | 2 | 4747 | import itertools
import os
import os.path as osp
import chainer
import numpy as np
import skimage.io
try:
from sklearn.model_selection import train_test_split
except ImportError:
from sklearn.cross_validation import train_test_split
from .base import class_names_apc2016
import instance_occlsegm_lib.data
impor... | bsd-3-clause |
poidl/yassy | doc/python/frei_appendix_B2.py | 1 | 4132 | #!/bin/python
# pylint: disable=C0103
"""Python translation of Frei Appendix B1 and B2."""
# Frei, B.: Digital sound generation. Institute for Computer Music and
# Sound Technology (ICST) Zurich University of the Arts.
import numpy as np
import scipy.signal as sig
import matplotlib
matplotlib.use('Agg')
import matpl... | gpl-2.0 |
rl-institut/reegis-hp | reegis_hp/berlin_hp/plot.py | 3 | 2926 | import logging
from oemof import outputlib
from matplotlib import pyplot as plt
import oemof.solph as solph
import pandas as pd
def test_plots(berlin_e_system):
logging.info('Plot the results')
cdict = {'wind': '#5b5bae',
'pv': '#ffde32',
'storage': '#42c77a',
'pp_gas':... | gpl-3.0 |
boltunoff/turo | turo_api_search/turo_api_search.py | 1 | 2216 | # Found at: https://stackoverflow.com/questions/54593816/scraping-through-python-selenium-or-beautifulsoup
# https://turo.com/search?airportCode=EWR&customDelivery=true&defaultZoomLevel=11&endDate=04%2F05%2F2019&endTime=11%3A00&international=true&isMapSearch=false&itemsPerPage=200&location=EWR&locationType=Airport&ma... | gpl-3.0 |
pandegroup/osprey | osprey/search_space.py | 2 | 10503 | from __future__ import print_function, absolute_import, division
"""searchspace.py
This module contains code for specifying the hyperparameter search space.
The search space is specified as a product of bounded intervals. Each dimension
can be either an integer, floating-point or enumeration.
The base measure on the ... | apache-2.0 |
sinhrks/scikit-learn | examples/covariance/plot_covariance_estimation.py | 99 | 5074 | """
=======================================================================
Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood
=======================================================================
When working with covariance estimation, the usual approach is to use
a maximum likelihood estimator,... | bsd-3-clause |
NixaSoftware/CVis | venv/lib/python2.7/site-packages/pandas/tests/series/test_missing.py | 2 | 46754 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
import pytz
import pytest
from datetime import timedelta, datetime
from distutils.version import LooseVersion
from numpy import nan
import numpy as np
import pandas as pd
from pandas import (Series, DataFrame, isna, date_range,
MultiIndex, Index, ... | apache-2.0 |
ahye/FYS2140-Resources | src/ForwardEuler/ForwardEulerPotentialWell.py | 1 | 4827 | #!/usr/bin/env python
"""
Created on Tir 29 Oct 2013.
Script uses the forward euler method to solve the Schrodinger equation for a
potential well.
Animation is done using the matplotlib.pyplot library.
Usage:
python ForwardEulerPotentialWell.py
or equivalent:
./ForwardEulerPotentialWell.py
No commandline arg... | mit |
dalejung/ibis | ibis/expr/tests/test_timestamp.py | 13 | 3761 | # Copyright 2014 Cloudera Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, so... | apache-2.0 |
drix00/pysemeels | pysemeels/analysis/zero_loss_peak.py | 1 | 6069 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
.. py:currentmodule:: pysemeels.analysis.zero_loss_peak
.. moduleauthor:: Hendrix Demers <hendrix.demers@mail.mcgill.ca>
Analyze the zero loss peak from an EELS spectrum.
"""
###############################################################################
# Copyright... | apache-2.0 |
LiaoPan/scikit-learn | sklearn/linear_model/ransac.py | 191 | 14261 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.valid... | bsd-3-clause |
KhanSuleyman/scikit-neuralnetwork | docs/conf.py | 5 | 1814 | # -*- coding: utf-8 -*-
#
# scikit-neuralnetwork documentation build configuration file, created by
# sphinx-quickstart on Tue Mar 31 20:28:10 2015.
import sys
import os
project = u'scikit-neuralnetwork'
copyright = u'2015, scikit-neuralnetwork developers (BSD License)'
# -- Configuration of documentation --------... | bsd-3-clause |
maxiee/MyCodes | KalmanAndBesianFiltersInPython/Chapter1_g_h_filters/utils/stat.py | 3 | 11807 | """
Author: Roger Labbe
Copyright: 2014
This code performs various basic statistics functions for the
Kalman and Bayesian Filters in Python book. Much of this code
is non-optimal; production code should call the equivalent scipy.stats
functions. I wrote the code in this form to make explicit how the
computations are d... | gpl-3.0 |
jgoodacre71/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 |
dataewan/deep-learning | image-classification/helper.py | 155 | 5631 | import pickle
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import LabelBinarizer
def _load_label_names():
"""
Load the label names from file
"""
return ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
def load_cfar10_batch(ci... | mit |
formath/mxnet | example/bayesian-methods/bdk_demo.py | 45 | 15837 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
aiguofer/bokeh | tests/compat/polycollection.py | 13 | 1311 | from matplotlib.collections import PolyCollection
import matplotlib.pyplot as plt
import numpy as np
from bokeh import mpl
from bokeh.plotting import output_file, show
# Generate data. In this case, we'll make a bunch of center-points and generate
# verticies by subtracting random offsets from those center-points
num... | bsd-3-clause |
ryfeus/lambda-packs | Keras_tensorflow/source/tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py | 88 | 31139 | # 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... | mit |
gfyoung/pandas | pandas/tests/arrays/test_datetimes.py | 1 | 23268 | """
Tests for DatetimeArray
"""
import operator
import numpy as np
import pytest
from pandas.core.dtypes.dtypes import DatetimeTZDtype
import pandas as pd
from pandas import NaT
import pandas._testing as tm
from pandas.core.arrays import DatetimeArray
from pandas.core.arrays.datetimes import sequence_to_dt64ns
cla... | bsd-3-clause |
appapantula/scikit-learn | sklearn/datasets/__init__.py | 176 | 3671 | """
The :mod:`sklearn.datasets` module includes utilities to load datasets,
including methods to load and fetch popular reference datasets. It also
features some artificial data generators.
"""
from .base import load_diabetes
from .base import load_digits
from .base import load_files
from .base import load_iris
from .... | bsd-3-clause |
ryfeus/lambda-packs | Sklearn_scipy_numpy/source/sklearn/ensemble/tests/test_weight_boosting.py | 83 | 17276 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_array_equal, assert_array_less
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal, assert_true
from sklearn.utils.testing import assert_raises... | mit |
gem/oq-engine | openquake/hazardlib/tests/site_amplification_test.py | 1 | 11181 | # -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2020, GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, ... | agpl-3.0 |
beni55/hyperopt | hyperopt/tests/test_criteria.py | 7 | 1917 | import numpy as np
import hyperopt.criteria as crit
def test_ei():
rng = np.random.RandomState(123)
for mean, var in [(0, 1), (-4, 9)]:
thresholds = np.arange(-5, 5, .25) * np.sqrt(var) + mean
v_n = [crit.EI_gaussian_empirical(mean, var, thresh, rng, 10000)
for thresh in thresh... | bsd-3-clause |
zihua/scikit-learn | examples/semi_supervised/plot_label_propagation_digits_active_learning.py | 28 | 3417 | """
========================================
Label Propagation digits active learning
========================================
Demonstrates an active learning technique to learn handwritten digits
using label propagation.
We start by training a label propagation model with only 10 labeled points,
then we select the t... | bsd-3-clause |
huzq/scikit-learn | sklearn/linear_model/tests/test_perceptron.py | 5 | 1793 | import numpy as np
import scipy.sparse as sp
from sklearn.utils._testing import assert_array_almost_equal
from sklearn.utils._testing import assert_raises
from sklearn.utils import check_random_state
from sklearn.datasets import load_iris
from sklearn.linear_model import Perceptron
iris = load_iris()
random_state = ... | bsd-3-clause |
thirdwing/mxnet | example/ssd/dataset/pycocotools/coco.py | 29 | 19564 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
hainm/statsmodels | statsmodels/sandbox/stats/stats_mstats_short.py | 34 | 14910 | '''get versions of mstats percentile functions that also work with non-masked arrays
uses dispatch to mstats version for difficult cases:
- data is masked array
- data requires nan handling (masknan=True)
- data should be trimmed (limit is non-empty)
handle simple cases directly, which doesn't require apply_alon... | bsd-3-clause |
mountaindust/Parasitoids | Bayes_Plot.py | 1 | 16702 | #! /usr/bin/env python3
'''
This module is for plotting the posterior distributions from Bayes_Run.py
Author: Christopher Strickland
Email: wcstrick@live.unc.edu
'''
import sys, os
import warnings
from collections import OrderedDict
import numpy as np
import pymc as pm
import matplotlib.pyplot as plt
import matplotl... | gpl-3.0 |
0x0all/scikit-learn | sklearn/utils/tests/test_random.py | 38 | 7410 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from scipy.misc import comb as combinations
from numpy.testing import assert_array_almost_equal
from sklearn.utils.random import sample_without_replacement
from sklearn.utils.random import random_choice_csc
from sklearn.utils.testing import ... | bsd-3-clause |
MohammedWasim/scikit-learn | sklearn/externals/joblib/parallel.py | 79 | 35628 | """
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 |
JPFrancoia/scikit-learn | sklearn/decomposition/tests/test_kernel_pca.py | 74 | 8472 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import (assert_array_almost_equal, assert_less,
assert_equal, assert_not_equal,
assert_raises)
from sklearn.decomposition import PCA, KernelPCA
from sklearn.datasets import mak... | bsd-3-clause |
prheenan/IgorUtil | PythonAdapter/PxpLoader.py | 1 | 9527 | # force floating point division. Can still use integer with //
from __future__ import division
# This file is used for importing the common utilities classes.
import numpy as np
import matplotlib.pyplot as plt
import sys
from IgorUtil.PythonAdapter import ProcessSingleWave,TimeSepForceObj
from GeneralUtil.python.LibUti... | gpl-3.0 |
oemof/reegis-hp | reegis_hp/de21/ew.py | 3 | 2788 | # http://www.geodatenzentrum.de/auftrag1/archiv/vektor/vg250_ebenen/2015/vg250-ew_2015-12-31.geo84.shape.ebenen.zip
import os
import pandas as pd
import geopandas as gpd
from oemof.tools import logger
from shapely.wkt import loads as wkt_loads
from reegis_hp.de21 import tools as t
import configuration as config
import... | gpl-3.0 |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/pandas/tests/series/test_dtypes.py | 7 | 5707 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
import sys
from datetime import datetime
import string
from numpy import nan
import numpy as np
from pandas import Series
from pandas.tseries.index import Timestamp
from pandas.tseries.tdi import Timedelta
from pandas.compat import lrange, range, u
from pandas import... | gpl-3.0 |
myselfHimanshu/Udacity-DataML | Intro to Machine Learning/text_learning/vectorize_text.py | 2 | 2636 | #!/usr/bin/python
import os
import pickle
import re
import sys
sys.path.append( "../tools/" )
from parse_out_email_text import parseOutText
"""
starter code to process the emails from Sara and Chris to extract
the features and get the documents ready for classification
the list of all the emails from Sa... | gpl-2.0 |
yanlend/scikit-learn | sklearn/metrics/cluster/tests/test_bicluster.py | 394 | 1770 | """Testing for bicluster metrics module"""
import numpy as np
from sklearn.utils.testing import assert_equal, assert_almost_equal
from sklearn.metrics.cluster.bicluster import _jaccard
from sklearn.metrics import consensus_score
def test_jaccard():
a1 = np.array([True, True, False, False])
a2 = np.array([T... | bsd-3-clause |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/pandas/tests/sparse/test_series.py | 7 | 51517 | # pylint: disable-msg=E1101,W0612
import operator
import pytest
from numpy import nan
import numpy as np
import pandas as pd
from pandas import Series, DataFrame, bdate_range
from pandas.core.common import isnull
from pandas.tseries.offsets import BDay
import pandas.util.testing as tm
from pandas.compat import range... | mit |
pprett/scikit-learn | examples/applications/plot_out_of_core_classification.py | 51 | 13651 | """
======================================================
Out-of-core classification of text documents
======================================================
This is an example showing how scikit-learn can be used for classification
using an out-of-core approach: learning from data that doesn't fit into main
memory. ... | bsd-3-clause |
AlexanderFabisch/scikit-learn | examples/svm/plot_svm_kernels.py | 329 | 1971 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
SVM-Kernels
=========================================================
Three different types of SVM-Kernels are displayed below.
The polynomial and RBF are especially useful when the
data-points are not linearly sep... | bsd-3-clause |
wkfwkf/statsmodels | examples/python/ols.py | 30 | 5601 |
## Ordinary Least Squares
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
from statsmodels.sandbox.regression.predstd import wls_prediction_std
np.random.seed(9876789)
# ## OLS estimation
#
# Artificial data:
nsample = 100
x = np.linspace(0, 1... | bsd-3-clause |
mortonjt/scipy | scipy/stats/tests/test_morestats.py | 10 | 39208 | # Author: Travis Oliphant, 2002
#
# Further enhancements and tests added by numerous SciPy developers.
#
from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from numpy.random import RandomState
from numpy.testing import (TestCase, run_module_suite, assert_array_equal,
... | bsd-3-clause |
yohanesgultom/id-openie | scripts/reverb_utils.py | 1 | 1283 | import csv
import argparse
import json
from pandas import read_csv, merge
parser = argparse.ArgumentParser()
parser.add_argument('sentences_file', help='Sentences file')
parser.add_argument('labels_file', help='Labels file')
parser.add_argument('-o', '--output', help='Output file', default='out.json')
args = parser.pa... | mit |
basnijholt/holoviews | holoviews/plotting/plotly/element.py | 2 | 18826 | from __future__ import absolute_import, division, unicode_literals
import numpy as np
import param
from ...core import util
from ...core.element import Element
from ...core.spaces import DynamicMap
from ...util.transform import dim
from ..plot import GenericElementPlot, GenericOverlayPlot
from ..util import dim_range... | bsd-3-clause |
aewhatley/scikit-learn | examples/decomposition/plot_ica_blind_source_separation.py | 349 | 2228 | """
=====================================
Blind source separation using FastICA
=====================================
An example of estimating sources from noisy data.
:ref:`ICA` is used to estimate sources given noisy measurements.
Imagine 3 instruments playing simultaneously and 3 microphones
recording the mixed si... | bsd-3-clause |
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