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 |
|---|---|---|---|---|---|
harisbal/pandas | pandas/core/frame.py | 1 | 295341 | # pylint: disable=E1101
# pylint: disable=W0212,W0703,W0622
"""
DataFrame
---------
An efficient 2D container for potentially mixed-type time series or other
labeled data series.
Similar to its R counterpart, data.frame, except providing automatic data
alignment and a host of useful data manipulation methods having to... | bsd-3-clause |
phobson/statsmodels | statsmodels/iolib/tests/test_foreign.py | 4 | 7304 | """
Tests for iolib/foreign.py
"""
import os
import warnings
from datetime import datetime
from numpy.testing import *
import numpy as np
from pandas import DataFrame, isnull
import pandas.util.testing as ptesting
from statsmodels.compat.python import BytesIO, asbytes
import statsmodels.api as sm
from statsmodels.iol... | bsd-3-clause |
harri314/Navigation | diagrams/rust_auxiliary.py | 1 | 3097 | # Copyright 2014 Harri Ojanen
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the h... | gpl-3.0 |
SPJ-AI/lesson | training_python/mlp_text.py | 1 | 3129 | # -*- coding: utf-8 -*-
#! /usr/bin/python
import MeCab # TokenizerとしてMeCabを使用
from sklearn.neural_network import MLPClassifier
mecab = MeCab.Tagger("-Ochasen") # MeCabのインスタンス化
f = open('text.tsv') # トレーニングファイルの読み込み
lines = f.readlines()
words = [] # 単語トークン表層一覧を保持するリスト
count = 0
dict = {} # テキスト:カテゴリのペアを保持する辞書
for li... | gpl-3.0 |
Britefury/scikit-image | skimage/external/tifffile/tifffile_local.py | 1 | 173368 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# tifffile.py
# Copyright (c) 2008-2014, Christoph Gohlke
# Copyright (c) 2008-2014, The Regents of the University of California
# Produced at the Laboratory for Fluorescence Dynamics
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or wit... | bsd-3-clause |
josauder/procedural_city_generation | procedural_city_generation/polygons/construct_polygons.py | 2 | 3651 | from __future__ import division
import numpy as np
import math
import matplotlib
import matplotlib.pyplot as plt
class Wedge(object):
def __init__(self, a, b, c, alpha):
self.a=a
self.b=b
self.c=c
self.alpha=alpha
def __repr__(self):
return "W["+str(se... | mpl-2.0 |
p-lauer/spotpy | spotpy/examples/3dplot.py | 3 | 1623 | '''
Copyright 2015 by Tobias Houska
This file is part of Statistical Parameter Estimation Tool (SPOTPY).
:author: Tobias Houska
This file shows how to make 3d surface plots.
'''
import spotpy
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
from matplo... | mit |
republic-analytics/luigi | examples/pyspark_wc.py | 17 | 3388 | # -*- coding: utf-8 -*-
#
# Copyright 2012-2015 Spotify AB
#
# 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... | apache-2.0 |
Agent007/deepchem | examples/clintox/datasets/aacttox_sweetfda_join.py | 8 | 4151 | # -*- coding: utf-8 -*-
"""
Join sweetfda and aacttox data
@author Caleb Geniesse
"""
import pandas as pd
##############################################################################
### save dataset
##############################################################################
### load datasets
# load sweetfda
swe... | mit |
ameliecordier/IIK | master.py | 1 | 11629 | from datahandler import expertPatterns
from datahandler import miningPatterns
from datahandler import analyser as analyser
from matplotlib import pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import os
import time
def plot_two_results(norev, rev, fignum, legend, pp):
"""
Utilitaire d'affic... | mit |
andrewnc/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 |
ethereum/cpp-ethereum | scripts/plot_sync_perf.py | 1 | 2075 | #!/usr/bin/env python3
import json
import matplotlib.pyplot as plt
import sys
if len(sys.argv) < 3:
print("USAGE: plot_sync_perf.py.py gas_per_sec|avg_gas_per_sec|avg_gas_per_sec_1000blocks|sync_time LOG_FILE")
sys.exit(-1)
mode = sys.argv[1]
log_file = open(sys.argv[2], "r")
print("processing...")
perf_rec... | gpl-3.0 |
vsmolyakov/cv | visual_words/visual_words.py | 1 | 9664 | import numpy as np
import cv2
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_olivetti_faces
from sklearn.cluster import MiniBatchKMeans
from sklearn.decomposition import LatentDirichletAllocation
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.neighbors i... | mit |
NunoEdgarGub1/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 143 | 22295 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
benjaminpope/whisky | geometry/mk_plain.py | 2 | 2914 | #!/usr/bin/env python
''' -------------------------------------------------------
This procedure generates a coordinates file for a hex
pupil made of an arbitrary number of rings.
Additional constraints on the location of spiders make
it look like the your favorite telescope primary mirror
--------... | gpl-3.0 |
nkhuyu/SFrame | oss_src/unity/python/sframe/data_structures/sframe.py | 1 | 211694 | """
This module defines the SFrame class which provides the
ability to create, access and manipulate a remote scalable dataframe object.
SFrame acts similarly to pandas.DataFrame, but the data is completely immutable
and is stored column wise on the GraphLab Server side.
"""
'''
Copyright (C) 2015 Dato, Inc.
All righ... | bsd-3-clause |
MicrosoftGenomics/FaST-LMM | fastlmm/feature_selection/feature_selection_cv.py | 1 | 38663 | """
Created on 2013-07-28
@author: Christian Widmer <chris@shogun-toolbox.org>
@summary: Module for feature selection strategies using efficient caching where possible
"""
# std modules
from collections import defaultdict
import gzip
import bz2
import cPickle
import time
import os
import gc
import subprocess
import ... | apache-2.0 |
lazywei/scikit-learn | examples/preprocessing/plot_robust_scaling.py | 221 | 2702 | #!/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 |
liweitianux/atoolbox | astro/calc_psd.py | 1 | 14723 | #!/usr/bin/env python3
#
# Copyright (c) 2015-2017 Aaron LI
# MIT License
#
"""
Compute the radial (i.e., azimuthally averaged) power spectral density
(a.k.a. power spectrum) of a FITS image.
NOTE: The input image must be square.
Credit
------
* Radially averaged power spectrum of 2D real-valued matrix
Evan Ruzans... | mit |
BenjaminBossan/nolearn | docs/conf.py | 2 | 4002 | # -*- coding: utf-8 -*-
import sys, os
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#sys.path.insert(0, os.path.abspath('.'))... | mit |
scottyaz/reactive-vaccination-hotspots | Source/python/megaplot-multipleyears.py | 1 | 11705 | import scipy.integrate as spi
import numpy as np
import pylab as pl
import warnings
from matplotlib.font_manager import FontProperties as fmp
import sys
import pdb
import vacfunctions as vf
import re
import os
import time
pvacs = np.linspace(0.0,499999.0/500000,21) # note this is % of single patch not
# full populatio... | gpl-2.0 |
linsalrob/crAssphage | bin/map_drawing/bivariate.py | 1 | 5778 | """
In this example, we only have dots. The Size of the dots are the number of strains at each point
and the color of the dots are the number of connnections to that dot.
"""
import os
import sys
import argparse
import matplotlib.pyplot as plt
# set the figure size. This should be in inches?
plt.rcParams["figure.figs... | mit |
wdurhamh/statsmodels | statsmodels/sandbox/tsa/examples/ex_mle_arma.py | 33 | 4587 | # -*- coding: utf-8 -*-
"""
TODO: broken because of changes to arguments and import paths
fixing this needs a closer look
Created on Thu Feb 11 23:41:53 2010
Author: josef-pktd
copyright: Simplified BSD see license.txt
"""
from __future__ import print_function
import numpy as np
from numpy.testing import assert_almost... | bsd-3-clause |
e2crawfo/dps | motmetrics/io.py | 1 | 7426 | # -- coding: utf-8 --
"""py-motmetrics - metrics for multiple object tracker (MOT) benchmarking.
Christoph Heindl, 2017
https://github.com/cheind/py-motmetrics
"""
from enum import Enum
import pandas as pd
import numpy as np
import io
class Format(Enum):
"""Enumerates supported file formats."""
MOT16 = 'mo... | apache-2.0 |
astropy/astropy | examples/io/plot_fits-image.py | 11 | 1898 | # -*- coding: utf-8 -*-
"""
=======================================
Read and plot an image from a FITS file
=======================================
This example opens an image stored in a FITS file and displays it to the screen.
This example uses `astropy.utils.data` to download the file, `astropy.io.fits` to open
th... | bsd-3-clause |
agrimaldi/metaseq | metaseq/results_table.py | 3 | 40294 | import copy
from textwrap import dedent
import numpy as np
import pandas
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib.patches as patches
import matplotlib
import plotutils
from matplotlib.transforms import blended_transform_factory
from matplotlib.collec... | mit |
DGrady/pandas | pandas/tests/io/test_sql.py | 2 | 94598 | """SQL io tests
The SQL tests are broken down in different classes:
- `PandasSQLTest`: base class with common methods for all test classes
- Tests for the public API (only tests with sqlite3)
- `_TestSQLApi` base class
- `TestSQLApi`: test the public API with sqlalchemy engine
- `TestSQLiteFallbackApi`: t... | bsd-3-clause |
justincassidy/scikit-learn | sklearn/cross_validation.py | 8 | 58526 | """
The :mod:`sklearn.cross_validation` module includes utilities for cross-
validation and performance evaluation.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>,
# Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
from... | bsd-3-clause |
itaiin/arrow | python/benchmarks/convert_pandas.py | 9 | 3913 | # 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 |
wlamond/scikit-learn | examples/mixture/plot_gmm_covariances.py | 89 | 4724 | """
===============
GMM covariances
===============
Demonstration of several covariances types for Gaussian mixture models.
See :ref:`gmm` for more information on the estimator.
Although GMM are often used for clustering, we can compare the obtained
clusters with the actual classes from the dataset. We initialize th... | bsd-3-clause |
cdawei/digbeta | python/digbeta/heuristics.py | 2 | 18020 | """ Heuristics used to query the most uncertain candidate out of the unlabelled pool. """
import numpy as np
from joblib import Parallel, delayed
from numpy.random import permutation
from sklearn.preprocessing import LabelBinarizer
from sklearn.base import clone
def random_h(candidate_mask, n_candidates, **kwargs):
... | gpl-3.0 |
ratnania/vale | tests/test_biharmonic_2d.py | 1 | 3166 | # coding: utf-8
from vale import ValeCodegen
from vale import ValeParser
from vale import construct_model
from sympy import S
from sympy.core.sympify import sympify
import numpy as np
# ...
def run(filename):
# ...
from caid.cad_geometry import square
geometry = square()
from clapp.spl.mapping impo... | mit |
simon-pepin/scikit-learn | examples/applications/face_recognition.py | 191 | 5513 | """
===================================================
Faces recognition example using eigenfaces and SVMs
===================================================
The dataset used in this example is a preprocessed excerpt of the
"Labeled Faces in the Wild", aka LFW_:
http://vis-www.cs.umass.edu/lfw/lfw-funneled.tgz (2... | bsd-3-clause |
ElDeveloper/scikit-learn | examples/tree/unveil_tree_structure.py | 67 | 4824 | """
=========================================
Understanding the decision tree structure
=========================================
The decision tree structure can be analysed to gain further insight on the
relation between the features and the target to predict. In this example, we
show how to retrieve:
- the binary t... | bsd-3-clause |
ericmjl/flu-sequence-predictor | utils/webplots.py | 1 | 7849 | from collections import defaultdict
from datetime import datetime
import pandas as pd
import yaml
from bokeh.embed import components
from bokeh.layouts import row
from bokeh.models import (
ColumnDataSource,
CrosshairTool,
HoverTool,
PanTool,
Range1d,
ResetTool,
SaveTool,
)
from bokeh.palet... | bsd-3-clause |
zooniverse/aggregation | active_weather/old/extract_digits.py | 1 | 2589 | import numpy as np
import math
import matplotlib.pyplot as plt
from scipy import spatial
from sklearn.cluster import DBSCAN
import Image
import cv2
def line_removal(pts,num_col,num_row):
global_tree = spatial.KDTree(pts)
plt.plot(num_row,num_col,"o",color="red")
def extract(image):
digits = []
confi... | apache-2.0 |
ClinicalGraphics/scikit-image | doc/examples/edges/plot_medial_transform.py | 11 | 2257 | """
===========================
Medial axis skeletonization
===========================
The medial axis of an object is the set of all points having more than one
closest point on the object's boundary. It is often called the **topological
skeleton**, because it is a 1-pixel wide skeleton of the object, with the same
... | bsd-3-clause |
blink1073/qgrid | qgrid/grid.py | 1 | 11436 | import pandas as pd
import numpy as np
import uuid
import os
import json
from numbers import Integral
from IPython.display import display_html, display_javascript
try:
from ipywidgets import widgets
except ImportError:
from IPython.html import widgets
from IPython.display import display, Javascript
try:
fr... | apache-2.0 |
aaronprunty/starfish | vezda/plotWiggles.py | 1 | 31532 | # Copyright 2017-2018 Aaron C. Prunty
#
# 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 agree... | apache-2.0 |
grlee77/scipy | scipy/stats/tests/test_morestats.py | 2 | 103011 | # Author: Travis Oliphant, 2002
#
# Further enhancements and tests added by numerous SciPy developers.
#
import warnings
import numpy as np
from numpy.random import RandomState
from numpy.testing import (assert_array_equal,
assert_almost_equal, assert_array_less, assert_array_almost_equal,
assert_, assert_all... | bsd-3-clause |
aetilley/scikit-learn | sklearn/decomposition/tests/test_fastica.py | 272 | 7798 | """
Test the fastica algorithm.
"""
import itertools
import warnings
import numpy as np
from scipy import stats
from nose.tools import assert_raises
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from skl... | bsd-3-clause |
pslacerda/GromacsWrapper | gromacs/fileformats/xpm.py | 1 | 10370 | # GromacsWrapper: xpm.py
# Copyright (c) 2012 Oliver Beckstein <orbeckst@gmail.com>
# Copyright (c) 2010 Tsjerk Wassenaar <tsjerkw@gmail.com>
# Released under the GNU Public License 3 (or higher, your choice)
# See the file COPYING for details.
"""
Gromacs XPM file format
=======================
Gromacs stores matrix ... | gpl-3.0 |
karenlmasters/ComputationalPhysicsUnit | GraphicsVisualisation/double_pendulum_animated.py | 1 | 2314 | # Double pendulum formula translated from the C code at
# http://www.physics.usyd.edu.au/~wheat/dpend_html/solve_dpend.c
from numpy import sin, cos, pi, array
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as integrate
import matplotlib.animation as animation
G = 9.8 # acceleration due to ... | apache-2.0 |
costypetrisor/scikit-learn | examples/applications/plot_stock_market.py | 227 | 8284 | """
=======================================
Visualizing the stock market structure
=======================================
This example employs several unsupervised learning techniques to extract
the stock market structure from variations in historical quotes.
The quantity that we use is the daily variation in quote ... | bsd-3-clause |
kevin-intel/scikit-learn | examples/neighbors/plot_regression.py | 25 | 1441 | """
============================
Nearest Neighbors regression
============================
Demonstrate the resolution of a regression problem
using a k-Nearest Neighbor and the interpolation of the
target using both barycenter and constant weights.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@... | bsd-3-clause |
nesterione/scikit-learn | examples/cluster/plot_cluster_comparison.py | 246 | 4684 | """
=========================================================
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 |
edx/ease | ease/predictor_extractor.py | 1 | 2830 | """
Extracts features for an arbitrary set of textual and numeric inputs
"""
import numpy
import re
import nltk
import sys
from sklearn.feature_extraction.text import CountVectorizer
import pickle
import os
from itertools import chain
import copy
import operator
import logging
import math
from .feature_extractor impor... | agpl-3.0 |
cbertinato/pandas | pandas/tests/arrays/interval/test_interval.py | 1 | 2320 | import numpy as np
import pytest
import pandas as pd
from pandas import Index, Interval, IntervalIndex, date_range, timedelta_range
from pandas.core.arrays import IntervalArray
import pandas.util.testing as tm
@pytest.fixture(params=[
(Index([0, 2, 4]), Index([1, 3, 5])),
(Index([0., 1., 2.]), Index([1., 2.,... | bsd-3-clause |
astocko/statsmodels | statsmodels/sandbox/examples/try_multiols.py | 33 | 1243 | # -*- coding: utf-8 -*-
"""
Created on Sun May 26 13:23:40 2013
Author: Josef Perktold, based on Enrico Giampieri's multiOLS
"""
#import numpy as np
import pandas as pd
import statsmodels.api as sm
from statsmodels.sandbox.multilinear import multiOLS, multigroup
data = sm.datasets.longley.load_pandas()
df = data.e... | bsd-3-clause |
xodus7/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/data_feeder_test.py | 25 | 13554 | # 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 |
rhiever/scipy_2015_sklearn_tutorial | notebooks/figures/plot_digits_datasets.py | 19 | 2750 | # Taken from example in scikit-learn examples
# Authors: Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Gael Varoquaux
# License: BSD 3 clause (C) INRIA 2011
import numpy as np
import matplotlib.pyplot as pl... | cc0-1.0 |
kiith-sa/QGIS | python/plugins/processing/algs/RasterLayerHistogram.py | 6 | 3219 | # -*- coding: utf-8 -*-
"""
***************************************************************************
RasterLayerHistogram.py
---------------------
Date : January 2013
Copyright : (C) 2013 by Victor Olaya
Email : volayaf at gmail dot com
*****************... | gpl-2.0 |
ephes/scikit-learn | sklearn/feature_extraction/hashing.py | 183 | 6155 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: BSD 3 clause
import numbers
import numpy as np
import scipy.sparse as sp
from . import _hashing
from ..base import BaseEstimator, TransformerMixin
def _iteritems(d):
"""Like d.iteritems, but accepts any collections.Mapping."""
return d.iteritems() if... | bsd-3-clause |
wazeerzulfikar/scikit-learn | sklearn/feature_extraction/tests/test_dict_vectorizer.py | 110 | 3768 | # Authors: Lars Buitinck
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from random import Random
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from sklearn.utils.testing import (assert_equal, assert_in,
assert_false... | bsd-3-clause |
rothnic/bokeh | bokeh/charts/builder/tests/test_line_builder.py | 33 | 2376 | """ This is the Bokeh charts testing interface.
"""
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with thi... | bsd-3-clause |
rehassachdeva/restaurant_stats | setup.py | 1 | 1041 | #!/usr/bin/env python2
from restaurant_stats import __version__
try:
from setuptools import setup, find_packages
except ImportError:
from distutils.core import setup, find_packages
setup (
name = 'restaurant_stats',
version = __version__,
author = 'Rehas Sachdeva',
author_email = 'aquannie@gm... | mit |
Averroes/statsmodels | docs/source/conf.py | 27 | 11559 | # -*- coding: utf-8 -*-
#
# statsmodels documentation build configuration file, created by
# sphinx-quickstart on Sat Jan 22 11:17:58 2011.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
#... | bsd-3-clause |
SciLifeLab/NouGAT | utils/produce_assembly_report.py | 3 | 21059 | import sys, os, yaml, glob
import subprocess
import argparse
import pandas as pd
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt
import shutil as sh
def main(args):
workingDir = os.getcwd()
assemblers = sum(args.assemblers, [])
if not os.path.exists(args.validation_dir):
... | mit |
mtat76/atm-py | atmPy/aerosols/instrument/DMA/smps.py | 3 | 21254 | import sys
import tkinter as tk
from datetime import datetime as dt
from datetime import timedelta
from math import floor
from tkinter import filedialog as fd
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import statsmodels.api as sm
from scipy.interpolate import interp1d
from at... | mit |
GroestlCoin/electrum-grs | electrum_grs/gui/qt/history_list.py | 1 | 31502 | #!/usr/bin/env python
#
# Electrum - lightweight Bitcoin client
# Copyright (C) 2015 Thomas Voegtlin
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation files
# (the "Software"), to deal in the Software without restriction,
# including without... | gpl-3.0 |
rickyHong/Tensorflow_modi | tensorflow/python/client/notebook.py | 5 | 3848 | """Notebook front-end to TensorFlow.
When you run this binary, you'll see something like below, which indicates
the serving URL of the notebook:
The IPython Notebook is running at: http://127.0.0.1:8888/
Press "Shift+Enter" to execute a cell
Press "Enter" on a cell to go into edit mode.
Press "Escape" to go back ... | apache-2.0 |
AaltoUrbanWater/opendatafmi | get_livi_stations.py | 2 | 4413 | #!/usr/bin/env python
"""Get a list of road weather stations and save as a shapefile.
Copyright (C) 2018 Tero Niemi, Aalto University School of Engineering
This file is part of FetchFMIOpen.
FetchFMIOpen is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public ... | gpl-3.0 |
dsquareindia/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 |
shusenl/scikit-learn | examples/cluster/plot_cluster_iris.py | 350 | 2593 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
K-means Clustering
=========================================================
The plots display firstly what a K-means algorithm would yield
using three clusters. It is then shown what the effect of a bad
initializa... | bsd-3-clause |
mne-tools/mne-python | tutorials/intro/40_sensor_locations.py | 2 | 13698 | """
.. _tut-sensor-locations:
Working with sensor locations
=============================
This tutorial describes how to read and plot sensor locations, and how
MNE-Python handles physical locations of sensors.
As usual we'll start by importing the modules we need and loading some
:ref:`example data <sample-dataset>... | bsd-3-clause |
Barmaley-exe/scikit-learn | sklearn/ensemble/partial_dependence.py | 36 | 14909 | """Partial dependence plots for tree ensembles. """
# Authors: Peter Prettenhofer
# License: BSD 3 clause
from itertools import count
import numbers
import numpy as np
from scipy.stats.mstats import mquantiles
from ..utils.extmath import cartesian
from ..externals.joblib import Parallel, delayed
from ..externals im... | bsd-3-clause |
miyyer/qb | qanta/buzz_example.py | 2 | 10938 | import math
import os
import pickle
from collections import defaultdict
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import plotnine as p9
import typer
from pedroai.io import read_json, write_json
from pedroai.plot import theme_pedroai
from rich.console import Console
from r... | mit |
meissnert/StarCluster | utils/scimage_13_04.py | 19 | 17696 | #!/usr/bin/env python
"""
This script is meant to be run inside of a ubuntu cloud image available at
uec-images.ubuntu.com::
$ EC2_UBUNTU_IMG_URL=http://uec-images.ubuntu.com/precise/current
$ wget $EC2_UBUNTU_IMG_URL/precise-server-cloudimg-amd64.tar.gz
or::
$ wget $EC2_UBUNTU_IMG_URL/precise-server-clo... | gpl-3.0 |
ioreshnikov/wells | stability_eigenvalue.py | 1 | 2880 | #!/usr/bin/env python3
import argparse
import scipy
import matplotlib.pyplot as plot
import wells.publisher as publisher
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--interactive",
help="Interactive mode",
action="store_true")
parser.add_argument("-e", "--ex... | mit |
uvchik/pvlib-python | pvlib/test/test_atmosphere.py | 1 | 5239 | import itertools
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_allclose
from pvlib import atmosphere
from pvlib import solarposition
latitude, longitude, tz, altitude = 32.2, -111, 'US/Arizona', 700
times = pd.date_range(start='20140626', end='20140626', freq='6h', tz=tz)
e... | bsd-3-clause |
nan86150/ImageFusion | lib/python2.7/site-packages/matplotlib/tri/triplot.py | 21 | 3124 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from matplotlib.tri.triangulation import Triangulation
def triplot(ax, *args, **kwargs):
"""
Draw a unstructured triangular grid as lines and/or markers.
The triang... | mit |
Kongsea/tensorflow | tensorflow/contrib/training/python/training/feeding_queue_runner_test.py | 76 | 5052 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
rb-roomba/music | read_MusicXML/read_musicXML.py | 1 | 2750 | #! /usr/bin/python
# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import matplotlib.pyplot as plt
import seaborn
import pandas as pd
def height(pitch):
""" Calculate absolute height of given pitch. """
# pitch example: [u'G', u'5']
cde_list = ["c","d","e","f","g","a","b"]
h = int(pitch[1])*7
... | mit |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/pandas/tests/indexes/test_datetimelike.py | 7 | 52802 | # -*- coding: utf-8 -*-
from datetime import datetime, timedelta, time
import numpy as np
from pandas import (DatetimeIndex, Float64Index, Index, Int64Index,
NaT, Period, PeriodIndex, Series, Timedelta,
TimedeltaIndex, date_range, period_range,
timedelta_ra... | gpl-3.0 |
ArtsiomCh/tensorflow | tensorflow/examples/learn/iris_custom_decay_dnn.py | 37 | 3774 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | apache-2.0 |
sarahgrogan/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 110 | 34127 | from __future__ import unicode_literals
import warnings
from sklearn.feature_extraction.text import strip_tags
from sklearn.feature_extraction.text import strip_accents_unicode
from sklearn.feature_extraction.text import strip_accents_ascii
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.fe... | bsd-3-clause |
Islandman93/reinforcepy | examples/ALE/DQN_Async/run_dqnexpreplay.py | 1 | 1901 | import sys
import json
import datetime
from reinforcepy.environments import ALEEnvironment
from reinforcepy.networks.dqn.tflow.target_dqn import TargetDQN
from reinforcepy.learners.dqn.asynchronous.exp_replay_q_thread_learner import ExpQThreadLearner
from reinforcepy.learners.dqn.asynchronous.async_thread_host import A... | gpl-3.0 |
yanlend/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 181 | 15664 | from __future__ import division
from collections import defaultdict
from functools import partial
import numpy as np
import scipy.sparse as sp
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing imp... | bsd-3-clause |
Nyker510/scikit-learn | examples/datasets/plot_random_multilabel_dataset.py | 93 | 3460 | """
==============================================
Plot randomly generated multilabel dataset
==============================================
This illustrates the `datasets.make_multilabel_classification` dataset
generator. Each sample consists of counts of two features (up to 50 in
total), which are differently distri... | bsd-3-clause |
jorge2703/scikit-learn | sklearn/decomposition/tests/test_kernel_pca.py | 155 | 8058 | 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 |
weleen/mxnet | example/autoencoder/data.py | 18 | 1348 | # 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 |
treverhines/PyGeoNS | demo/demo1/.write_synthetic.py | 1 | 3079 | import numpy as np
from pygeons.mjd import mjd
from pygeons.io.io import text_from_dict
from pygeons.basemap import make_basemap
import matplotlib.pyplot as plt
np.random.seed(1)
## observation points
#####################################################################
pos_geo = np.array([[-83.74,42.28,0.0],
... | mit |
PredictiveScienceLab/py-orthpol | demos/demo10.py | 2 | 2341 | """
Generate the orthogonal polynomials using a scipy.stats random variable.
This particular demo generates polynomials orthogonal with respect to a
truncated normal distribution.
This demo demonstrates how to:
+ Construct a set of orthogonal univariate polynomials given a scipy.stats
random variable.
+ ... | lgpl-2.1 |
atamazian/traffic-proc-tools | Schreiber.py | 1 | 3070 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (C) 2016 by Araik Tamazian, Viet Duc Nguyen
#import pandas as pd
import numpy as np
import math
import scipy.special as sp
import cmath as cm
def DFA(indata,q,m):
scale = np.logspace(np.log10(10**1),np.log10(10**3),10)
scale = scale.astype(int)
y ... | mit |
grehx/spark-tk | regression-tests/sparktkregtests/testcases/dicom/dicom_extract_tag_test.py | 1 | 6765 | # vim: set encoding=utf-8
# Copyright (c) 2016 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | apache-2.0 |
nelson-liu/scikit-learn | sklearn/manifold/locally_linear.py | 19 | 25916 | """Locally Linear Embedding"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) INRIA 2011
import numpy as np
from scipy.linalg import eigh, svd, qr, solve
from scipy.sparse import eye, csr_matrix
from ..base import B... | bsd-3-clause |
rajat1994/scikit-learn | sklearn/feature_selection/rfe.py | 137 | 17066 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Vincent Michel <vincent.michel@inria.fr>
# Gilles Louppe <g.louppe@gmail.com>
#
# License: BSD 3 clause
"""Recursive feature elimination for feature ranking"""
import warnings
import numpy as np
from ..utils import check_X_y, safe_sqr
fro... | bsd-3-clause |
eustislab/horton | horton/grid/test/test_poisson.py | 1 | 6118 | # -*- coding: utf-8 -*-
# HORTON: Helpful Open-source Research TOol for N-fermion systems.
# Copyright (C) 2011-2015 The HORTON Development Team
#
# This file is part of HORTON.
#
# HORTON is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by th... | gpl-3.0 |
Denisolt/Tensorflow_Chat_Bot | local/lib/python2.7/site-packages/numpy/doc/creation.py | 118 | 5507 | """
==============
Array Creation
==============
Introduction
============
There are 5 general mechanisms for creating arrays:
1) Conversion from other Python structures (e.g., lists, tuples)
2) Intrinsic numpy array array creation objects (e.g., arange, ones, zeros,
etc.)
3) Reading arrays from disk, either from... | gpl-3.0 |
quheng/scikit-learn | examples/applications/plot_tomography_l1_reconstruction.py | 204 | 5442 | """
======================================================================
Compressive sensing: tomography reconstruction with L1 prior (Lasso)
======================================================================
This example shows the reconstruction of an image from a set of parallel
projections, acquired along dif... | bsd-3-clause |
sanketloke/scikit-learn | examples/cluster/plot_adjusted_for_chance_measures.py | 105 | 4300 | """
==========================================================
Adjustment for chance in clustering performance evaluation
==========================================================
The following plots demonstrate the impact of the number of clusters and
number of samples on various clustering performance evaluation me... | bsd-3-clause |
ruymanengithub/vison | vison/metatests/nl.py | 1 | 29774 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 22 10:33:00 2019
@author: raf
"""
# IMPORT STUFF
from pdb import set_trace as stop
import copy
import numpy as np
from collections import OrderedDict
import string as st
import os
import matplotlib.cm as cm
from vison.fpa import fpa as fpamod
fro... | gpl-3.0 |
cpaulik/scipy | doc/source/conf.py | 40 | 10928 | # -*- coding: utf-8 -*-
import sys, os, re
# Check Sphinx version
import sphinx
if sphinx.__version__ < "1.1":
raise RuntimeError("Sphinx 1.1 or newer required")
needs_sphinx = '1.1'
# -----------------------------------------------------------------------------
# General configuration
# -----------------------... | bsd-3-clause |
xguse/bokeh | bokeh/charts/builder/tests/test_scatter_builder.py | 33 | 2895 | """ This is the Bokeh charts testing interface.
"""
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with thi... | bsd-3-clause |
astocko/statsmodels | statsmodels/tsa/tests/test_seasonal.py | 27 | 9216 | import numpy as np
from numpy.testing import assert_almost_equal, assert_equal, assert_raises
from statsmodels.tsa.seasonal import seasonal_decompose
from pandas import DataFrame, DatetimeIndex
class TestDecompose:
@classmethod
def setupClass(cls):
# even
data = [-50, 175, 149, 214, 247, 237, ... | bsd-3-clause |
eranr/mlstorlets | test/unit/test_serialize_classifier.py | 1 | 6174 | # Copyright (c) 2015-2016 itsonlyme.name
#
# 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 i... | apache-2.0 |
cainiaocome/scikit-learn | examples/applications/plot_outlier_detection_housing.py | 243 | 5577 | """
====================================
Outlier detection on a real data set
====================================
This example illustrates the need for robust covariance estimation
on a real data set. It is useful both for outlier detection and for
a better understanding of the data structure.
We selected two sets o... | bsd-3-clause |
areeda/gwpy | gwpy/testing/fixtures.py | 3 | 3700 | # -*- coding: utf-8 -*-
# Copyright (C) Duncan Macleod (2018-2020)
#
# This file is part of GWpy.
#
# GWpy is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option)... | gpl-3.0 |
mendax-grip/cfdemUtilities | couette/averageRadialScalar.py | 2 | 2000 | # This program averages a variable for each value of r for each files specified by the user
# This program must be launched from the main folder of a case from which you can access ./CFD/ and ./voidfraction/
# A FOLDER ./voidfraction/averaged must exist!
# Author : Bruno Blais
# Last modified : 15-01-2014
#Python i... | lgpl-3.0 |
mmottahedi/neuralnilm_prototype | scripts/e398.py | 4 | 23130 | from __future__ import print_function, division
import matplotlib
import logging
from sys import stdout
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import (Net, RealApplianceSource,
BLSTMLayer, DimshuffleLayer,
Bidirectio... | mit |
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