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 |
|---|---|---|---|---|---|
dbjohnson/flhackday | categorical.py | 1 | 1439 | from matplotlib import colors as clr
import pylab as plt
import seaborn as sns
import numpy as np
background = -1<<30
def heatmap(image, ncolors=None, transform=True):
distinct_values = list(sorted(np.unique(image)))
if background in distinct_values:
distinct_values.remove(background)
if ncolors... | mit |
Alkxzv/categorical-kernels | kcat/kernels/search.py | 1 | 8564 | """Classes to perform GridSearch on the custom kernels defined in
:mod:`kcat.kernels.functions`.
Their interface is very similar to scikit-learn's
`GridSearchCV <http://scikit-learn.org/stable/modules/generated/sklearn\
.grid_search.GridSearchCV.html#sklearn.grid_search.GridSearchCV>`_,
and the same parameters should ... | mit |
kou/arrow | python/pyarrow/tests/test_plasma.py | 4 | 44011 | # 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 |
aetilley/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 130 | 50966 | # 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 |
cvanoort/USDrugUseAnalysis | Report1/Code/afu_use30.py | 1 | 2851 | import csv
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
from scipy.optimize import curve_fit
def countKey(key,listDataDicts):
outDict = {}
for row in listDataDicts:
try:
outDict[row[key]] += 1
except KeyError:
outDict[row[key]] = 1
... | isc |
wzbozon/scikit-learn | sklearn/feature_selection/tests/test_from_model.py | 244 | 1593 | import numpy as np
import scipy.sparse as sp
from nose.tools import assert_raises, assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_greater
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
from sklearn.linear_model import SGD... | bsd-3-clause |
mikemull/midaspy | tests/test_mix.py | 1 | 6296 | import pytest
import datetime
import pandas as pd
from midas import mix
@pytest.fixture()
def lf_data():
df = pd.DataFrame({'date': ['2009-04-01', '2009-07-01', '2009-10-01', '2010-01-01', '2010-04-01'],
'val': [1.0, 2.0, 3.0, 4.0, 5.0]})
df['date'] = pd.to_datetime(df['date'])
df.... | mit |
RouxRC/gazouilleur | gazouilleur/lib/plots.py | 1 | 3416 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# punchcard drawing adapted from HgPunchcard (GPL 2+ https://bitbucket.org/birkenfeld/hgpunchcard/src/f4d38c737147cdf966909c2957a79573a6a5c517/hgpunchcard.py?at=default )
import os
import matplotlib
matplotlib.use('Agg', warn=False)
import matplotlib.pyplot as plt
from pyla... | agpl-3.0 |
sserkez/ocelot | utils/correlate_field.py | 2 | 1249 | from ocelot.adaptors.genesis import *
import matplotlib.animation as anim
import numpy as np
import matplotlib.pyplot as plt
#file='/home/iagapov/data/fel/genesis_runs/flash_40fsec/2900A/run_1/run.1.gout'
file='/home/iagapov/tmp/workshop/run_1/run.1.gout'
g = readGenesisOutput(file)
npoints = g('ncar')
zstop = g('zst... | gpl-3.0 |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/lib/matplotlib/backends/backend_wx.py | 1 | 78403 | from __future__ import division
"""
backend_wx.py
A wxPython backend for matplotlib, based (very heavily) on
backend_template.py and backend_gtk.py
Author: Jeremy O'Donoghue (jeremy@o-donoghue.com)
Derived from original copyright work by John Hunter
(jdhunter@ace.bsd.uchicago.edu)
Copyright (C) Jeremy O'Don... | gpl-2.0 |
tgquintela/pythonUtils | pythonUtils/ExploreDA/Statistics/stats_functions.py | 1 | 1108 |
"""
Calcular estadistiques.
"""
import numpy as np
import pandas as pd
## Creation of cnae index at a given level
def cnae_index_level(col_cnae, level):
pass
# Distance
def distance_cnae(col_cnae):
pass
def finantial_per_year(servicios):
"""Function which transform the servicios data to a data for ... | mit |
IamMoondance/Attempts | Упрощённый метод Ньютона.py | 1 | 8430 | #Шибанова Дарья ИУ7-22
# Метод: упрощённый метод Ньютона.
# 1. Уточнение корней уравнения. Задание большого отрезка,
# шага, точности, максимального числа итераций.
# Вывести: полученный корень, значение функции в точке корня
# по спецификации типа e с минимальным числом цифр в мантиссе,
# реально... | mit |
GbalsaC/bitnamiP | venv/share/doc/networkx-1.7/examples/multigraph/chess_masters.py | 4 | 5136 | #!/usr/bin/env python
"""
An example of the MultiDiGraph clas
The function chess_pgn_graph reads a collection of chess
matches stored in the specified PGN file
(PGN ="Portable Game Notation")
Here the (compressed) default file ---
chess_masters_WCC.pgn.bz2 ---
contains all 685 World Chess Championship matches
from... | agpl-3.0 |
ltiao/scikit-learn | sklearn/__init__.py | 4 | 3052 | """
Machine learning module for Python
==================================
sklearn is a Python module integrating classical machine
learning algorithms in the tightly-knit world of scientific Python
packages (numpy, scipy, matplotlib).
It aims to provide simple and efficient solutions to learning problems
that are acc... | bsd-3-clause |
kernelmilowill/PDMQBACKTEST | vn.datayes/storage.py | 29 | 18623 | import os
import json
import pymongo
import pandas as pd
from datetime import datetime, timedelta
from api import Config, PyApi
from api import BaseDataContainer, History, Bar
from errors import (VNPAST_ConfigError, VNPAST_RequestError,
VNPAST_DataConstructorError, VNPAST_DatabaseError)
class DBConfig(Co... | mit |
yonglehou/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 286 | 2378 | """
=====================================================================
Decision boundary of label propagation versus SVM on the Iris dataset
=====================================================================
Comparison for decision boundary generated on iris dataset
between Label Propagation and SVM.
This demon... | bsd-3-clause |
harisbal/pandas | pandas/tests/frame/test_analytics.py | 2 | 87234 | # -*- coding: utf-8 -*-
from __future__ import print_function
import warnings
from datetime import timedelta
import operator
import pytest
from string import ascii_lowercase
from numpy import nan
from numpy.random import randn
import numpy as np
from pandas.compat import lrange, PY35
from pandas import (compat, isn... | bsd-3-clause |
vybstat/scikit-learn | examples/manifold/plot_mds.py | 261 | 2616 | """
=========================
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 |
jamesturner246/mpfa | experiments/fig5/fig5.py | 1 | 7145 |
import numpy as np
import matplotlib.pyplot as plt
from contextlib import ExitStack
from itertools import islice
# SETUP
# %load_ext autoreload
# %autoreload 2
# from experiments.experiment_2 import experiment_2
# #####
def experiment_2 ():
experiment = 'fig2'
experiment_new = 'fig5'
v_name = 'nrn1_V_... | lgpl-3.0 |
AlexGrig/GPy | GPy/plotting/matplot_dep/svig_plots.py | 15 | 1323 | # Copyright (c) 2012, James Hensman and Nicolo' Fusi
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from matplotlib import pyplot as pb
def plot(model, ax=None, fignum=None, Z_height=None, **kwargs):
if ax is None:
fig = pb.figure(num=fignum)
ax = fig.add_subplot(... | bsd-3-clause |
roryk/exomeCov | ecov/variants.py | 1 | 1705 | import os
import os.path as op
import pandas as pd
# from collections import Counter
from bcbio.utils import rbind, file_exists, splitext_plus
from bcbio.provenance import do
from bcbio.distributed.transaction import file_transaction
from bcbio.log import logger
from bcbio.pipeline import config_utils
from bcbio impor... | mit |
tosolveit/scikit-learn | sklearn/decomposition/base.py | 313 | 5647 | """Principal Component Analysis Base Classes"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Kyle Kastner <kastnerkyle@gmail.com>
#
# Licen... | bsd-3-clause |
zihua/scikit-learn | sklearn/tests/test_isotonic.py | 34 | 14159 | import warnings
import numpy as np
import pickle
import copy
from sklearn.isotonic import (check_increasing, isotonic_regression,
IsotonicRegression)
from sklearn.utils.testing import (assert_raises, assert_array_equal,
assert_true, assert_false, assert... | bsd-3-clause |
jtaylor/pysfm | sfm/model.py | 1 | 8435 | import numpy as np
from util import norm, normed, rotvecs_to_Rs
def point_set_error(Ps, Qs):
return norm(Ps - Qs, axis=1).mean(axis=-1)
class Scene(object):
def __init__(self, Ss = None, S = None, Rs = None, Ts = None):
# Try to use S if Ss is not defined.
if Ss == None:
... | bsd-3-clause |
anjalisood/spark-tk | regression-tests/generatedata/gmm_datagen.py | 14 | 1129 | # 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 |
lamastex/scalable-data-science | dbcArchives/2021/000_0-sds-3-x-projects/student-project-13_group-Genomics/01_1000genomes.py | 1 | 25595 | # Databricks notebook source
# MAGIC %md
# MAGIC ScaDaMaLe Course [site](https://lamastex.github.io/scalable-data-science/sds/3/x/) and [book](https://lamastex.github.io/ScaDaMaLe/index.html)
# COMMAND ----------
# MAGIC %md
# MAGIC
# MAGIC # Genomics Analysis with Glow and Spark
# MAGIC
# MAGIC
# MAGIC **Link to ... | unlicense |
cheeseywhiz/cheeseywhiz | math/Taylor Series/main.py | 1 | 1884 | #!/usr/bin/python3
import math
import sys
import inspect
import matplotlib.pyplot as plt
import differentiable
xmin, xmax = -2, 4
ymin, ymax = -4, 4
h = 1 / 1000
dx = differentiable.equations()
def taylor(f, center, order):
"""Plot a Taylor polynomial and its parent function
taylor(differentiable equation f... | mit |
alexeyum/scikit-learn | examples/ensemble/plot_isolation_forest.py | 65 | 2363 | """
==========================================
IsolationForest example
==========================================
An example using IsolationForest for anomaly detection.
The IsolationForest 'isolates' observations by randomly selecting a feature
and then randomly selecting a split value between the maximum and minimu... | bsd-3-clause |
abhishekgahlot/scikit-learn | sklearn/datasets/__init__.py | 74 | 3616 | """
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 |
ptorrey/torrey_cmf | examples/plot_illustris_cvdf.py | 1 | 1204 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import torrey_cmf
tc = torrey_cmf.number_density()
redshift_list = np.arange(7)
n_bin = 100
l_min_vd = 1.8
l_max_vd = 2.7
r = l_max_vd - l_min_vd
vd_array = np.arange(l_min_vd, l_max_vd, r / n_bin)
fontsize=14
cm = pl... | gpl-2.0 |
Supermem/ibis | ibis/expr/api.py | 6 | 47950 | # Copyright 2015 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 |
godfatherofpolka/SaliencyMapInPython | saliency.py | 1 | 3107 | #!/usr/bin/env python
'''
Copyright 2015 Samuel Bucheli
This file is part of SaliencyMapInPython.
SaliencyMapInPython 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
(at your... | gpl-2.0 |
calico/basenji | bin/basenji_sad_ref.py | 1 | 12179 | #!/usr/bin/env python
# Copyright 2017 Calico 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 ... | apache-2.0 |
shusenl/scikit-learn | sklearn/feature_extraction/tests/test_feature_hasher.py | 258 | 2861 | from __future__ import unicode_literals
import numpy as np
from sklearn.feature_extraction import FeatureHasher
from nose.tools import assert_raises, assert_true
from numpy.testing import assert_array_equal, assert_equal
def test_feature_hasher_dicts():
h = FeatureHasher(n_features=16)
assert_equal("dict",... | bsd-3-clause |
vsmolyakov/ml | sgd/python/sgd_lr.py | 1 | 4627 | import numpy as np
import matplotlib.pyplot as plt
import time
from sklearn.datasets import load_iris
np.random.seed(0)
class sgdlr:
def __init__(self):
self.num_iter = 100
self.lmbda = 1e-9
self.tau0 = 10
self.kappa = 1
self.batchsize = 200
... | mit |
samshara/Stock-Market-Analysis-and-Prediction | smap_nepse/prediction/recurrent.py | 1 | 3734 | # time series prediction of stock data
# using recurrent neural network with LSTM layer
from pybrain.datasets import SequentialDataSet
from itertools import cycle
from pybrain.tools.shortcuts import buildNetwork
from pybrain.structure.modules import LSTMLayer
from pybrain.supervised import RPropMinusTrainer
from pybrai... | mit |
COOLMASON/ThinkStats2 | code/brfss.py | 69 | 4708 | """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 math
import sys
import pandas
import numpy as np
import thinkstats2
impo... | gpl-3.0 |
yonghenglh6/cuda-convnet2 | convdata.py | 174 | 14675 | # Copyright 2014 Google Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | apache-2.0 |
fabioticconi/scikit-learn | benchmarks/bench_random_projections.py | 397 | 8900 | """
===========================
Random projection benchmark
===========================
Benchmarks for random projections.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import collections
import numpy as np
import scipy.s... | bsd-3-clause |
TitasNandi/Summer_Project | yodaqa/data/ml/answertrain.py | 3 | 12914 | """
Generic framework for training answer classifiers using sklearn
on an answer TSV dataset.
This module contains a generic train / test function and cross-validation
routine, but does not define the actual classifier to use; it is expected
that the calling scripts will provide these.
"""
import math
from multiproce... | apache-2.0 |
CalebBell/thermo | thermo/utils/t_dependent_property.py | 1 | 145532 | # -*- coding: utf-8 -*-
'''Chemical Engineering Design Library (ChEDL). Utilities for process modeling.
Copyright (C) 2016, 2017, 2018, 2019, 2020 Caleb Bell <Caleb.Andrew.Bell@gmail.com>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (t... | mit |
mogeiwang/nest | pynest/examples/twoneurons.py | 8 | 1209 | # -*- coding: utf-8 -*-
#
# twoneurons.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 |
bmcage/stickproject | stick/utils/process_bednetdata.py | 1 | 1426 | import os
import fipy
import matplotlib.pyplot as plt
import numpy as np
treshold = 2e-6
FIGFILEEXT = '.png'
times = []
xpos = None
for file in sorted(os.listdir('.')):
if file[-3:] == '.gz':
data = fipy.tools.dump.read(file)
times.append(data['time'])
if xpos is None:
xpos = d... | gpl-2.0 |
zymsys/sms-tools | lectures/04-STFT/plots-code/window-size.py | 22 | 1498 | import math
import matplotlib.pyplot as plt
import numpy as np
import time, os, sys
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel as DF
import utilFunctions as UF
(fs, x) = UF.wavread('../../../sounds/oboe-A4.wav')
N = 128
start = .81*fs
x1 =... | agpl-3.0 |
dankolbman/CleverTind | figures/wc_hist.py | 1 | 1432 | # Create a histogram for word count data
# Dan Kolbman 2014
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
font = {'family' : 'normal',
'weight' : 'bold',
'size' : 28}
matplotlib.rc('font', **font)
def main( path ):
wc = []
pct = []
# Read wc data
with ope... | mit |
Eric89GXL/scikit-learn | sklearn/cluster/tests/test_affinity_propagation.py | 8 | 2686 | """
Testing for Clustering methods
"""
import numpy as np
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_array_equal
from sklearn.cluster.affinity_propagation_ import Affinit... | bsd-3-clause |
lukauskas/scipy | scipy/stats/morestats.py | 20 | 92783 | # Author: Travis Oliphant, 2002
#
# Further updates and enhancements by many SciPy developers.
#
from __future__ import division, print_function, absolute_import
import math
import warnings
from collections import namedtuple
import numpy as np
from numpy import (isscalar, r_, log, around, unique, asarray,
... | bsd-3-clause |
rjeli/scikit-image | doc/examples/features_detection/plot_blob.py | 12 | 2998 | """
==============
Blob Detection
==============
Blobs are bright on dark or dark on bright regions in an image. In
this example, blobs are detected using 3 algorithms. The image used
in this case is the Hubble eXtreme Deep Field. Each bright dot in the
image is a star or a galaxy.
Laplacian of Gaussian (LoG)
-------... | bsd-3-clause |
mrshu/scikit-learn | examples/cluster/plot_adjusted_for_chance_measures.py | 5 | 4318 | """
==========================================================
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 |
antoinecarme/pyaf | tests/time_res/test_ozone_Daily.py | 1 | 1760 | import pandas as pd
import numpy as np
import pyaf.ForecastEngine as autof
import pyaf.Bench.TS_datasets as tsds
#get_ipython().magic('matplotlib inline')
b1 = tsds.load_ozone()
df = b1.mPastData
for k in [1 , 5]:
df[b1.mTimeVar + "_" + str(k) + '_Daily'] = pd.date_range('2000-1-1', periods=df.shape[0], freq=st... | bsd-3-clause |
AlexRobson/scikit-learn | examples/neighbors/plot_species_kde.py | 282 | 4059 | """
================================================
Kernel Density Estimate of Species Distributions
================================================
This shows an example of a neighbors-based query (in particular a kernel
density estimate) on geospatial data, using a Ball Tree built upon the
Haversine distance metric... | bsd-3-clause |
pyoceans/python-ctd | ctd/extras.py | 2 | 8451 | """
Extra functionality for plotting and post-processing.
"""
import matplotlib.pyplot as plt
import numpy as np
import numpy.ma as ma
from pandas import Series
def _extrap1d(interpolator):
"""
How to make scipy.interpolate return an extrapolated result beyond the
input range.
This is usually bad in... | bsd-3-clause |
h2oai/h2o-dev | h2o-py/tests/testdir_algos/pca/pyunit_PUBDEV_4314_varimp.py | 2 | 1303 | from __future__ import print_function
import sys
sys.path.insert(1,"../../../")
import h2o
from tests import pyunit_utils
from h2o.estimators.pca import H2OPrincipalComponentAnalysisEstimator as H2OPCA
from h2o.utils.typechecks import assert_is_type
from pandas import DataFrame
# This test aims to test that our PCA w... | apache-2.0 |
riccardoklinger/gis-code-answer | points2stations/__init__.py | 1 | 8219 | # -*- coding: utf-8 -*-
"""
/***************************************************************************
points to bus
A python workflow
derives bus stations from point data
-------------------
begin : 2016-03-01
git sha : $Format:%H$
copyright : (C) 2016 by Riccardo Klinger
email ... | gpl-3.0 |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/scipy/fftpack/basic.py | 7 | 21733 | """
Discrete Fourier Transforms - basic.py
"""
# Created by Pearu Peterson, August,September 2002
from __future__ import division, print_function, absolute_import
__all__ = ['fft','ifft','fftn','ifftn','rfft','irfft',
'fft2','ifft2']
from numpy import zeros, swapaxes
import numpy
from . import _fftpack
im... | mit |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/pandas/tests/frame/test_apply.py | 7 | 17403 | # -*- coding: utf-8 -*-
from __future__ import print_function
from datetime import datetime
import warnings
import numpy as np
from pandas import (notnull, DataFrame, Series, MultiIndex, date_range,
Timestamp, compat)
import pandas as pd
from pandas.types.dtypes import CategoricalDtype
from pand... | gpl-3.0 |
linearregression/airflow | airflow/hooks/presto_hook.py | 2 | 2601 | from pyhive import presto
from pyhive.exc import DatabaseError
from airflow.hooks.dbapi_hook import DbApiHook
import logging
logging.getLogger("pyhive").setLevel(logging.INFO)
class PrestoException(Exception):
pass
class PrestoHook(DbApiHook):
"""
Interact with Presto through PyHive!
>>> ph = Pre... | apache-2.0 |
tdhopper/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 |
manjunaths/tensorflow | tensorflow/tools/dist_test/python/census_widendeep.py | 54 | 11900 | # 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 |
yipenggao/moose | modules/combined/test/tests/thm_rehbinder/thm_rehbinder.py | 3 | 5870 | #!/usr/bin/env python
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
def rehbinder(r):
# Results from Rehbinder with parameters used in the MOOSE simulation.
# Rehbinder's manuscript contains a few typos - I've corrected them here.
# G Rehbinder "Analytic solutions of stationary c... | lgpl-2.1 |
foreversand/QSTK | Bin/investors_report.py | 5 | 6911 | #
# report.py
#
# Generates a html file containing a report based
# off a timeseries of funds from a pickle file.
#
# Drew Bratcher
#
from pylab import *
import numpy
from QSTK.qstkutil import DataAccess as da
from QSTK.qstkutil import qsdateutil as du
from QSTK.qstkutil import tsutil as tsu
from QSTK.q... | bsd-3-clause |
justacec/bokeh | examples/app/crossfilter/main.py | 6 | 6813 | import math
import numpy as np
import pandas as pd
from functools import partial
from bokeh import palettes
from bokeh.io import curdoc
from bokeh.models import HBox, Select
from bokeh.plotting import Figure
from bokeh.sampledata.autompg import autompg
from models import StyleableBox, StatsBox
from models.helpers im... | bsd-3-clause |
Adai0808/scikit-learn | benchmarks/bench_sparsify.py | 323 | 3372 | """
Benchmark SGD prediction time with dense/sparse coefficients.
Invoke with
-----------
$ kernprof.py -l sparsity_benchmark.py
$ python -m line_profiler sparsity_benchmark.py.lprof
Typical output
--------------
input data sparsity: 0.050000
true coef sparsity: 0.000100
test data sparsity: 0.027400
model sparsity:... | bsd-3-clause |
mtb-za/fatiando | cookbook/seismic_wavefd_rayleigh_wave.py | 9 | 2865 | """
Seismic: 2D finite difference simulation of elastic P and SV wave propagation
in a medium with a discontinuity (i.e., Moho), generating Rayleigh waves
"""
import numpy as np
from matplotlib import animation
from fatiando import gridder
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the para... | bsd-3-clause |
jowr/jopy | jopy/styles/__init__.py | 1 | 2133 |
import matplotlib.pyplot as plt
try:
from .plots import Figure
except:
from jopy.styles.plots import Figure
def get_figure(orientation='landscape',width=110,fig=None,axs=False):
"""Creates a figure with some initial properties
The object can be customised with the parameters. But since it is an... | mit |
aewhatley/scikit-learn | examples/linear_model/plot_lasso_model_selection.py | 311 | 5431 | """
===================================================
Lasso model selection: Cross-Validation / AIC / BIC
===================================================
Use the Akaike information criterion (AIC), the Bayes Information
criterion (BIC) and cross-validation to select an optimal value
of the regularization paramet... | bsd-3-clause |
jrcohen02/brainx_archive2 | brainx/version.py | 4 | 2781 | """brainx version/release information"""
# Format expected by setup.py and doc/source/conf.py: string of form "X.Y.Z"
_version_major = 0
_version_minor = 1
_version_micro = '' # use '' for first of series, number for 1 and above
_version_extra = 'dev'
#_version_extra = '' # Uncomment this for full releases
# Construc... | bsd-3-clause |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/pandas/tests/series/test_operators.py | 6 | 70514 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
import pytest
from collections import Iterable
from datetime import datetime, timedelta
import operator
from itertools import product, starmap
from numpy import nan, inf
import numpy as np
import pandas as pd
from pandas import (Index, Series, DataFrame, isnull, bdat... | mit |
STREAM3/pyisc | unittests/test_p_ConditionalGaussianDependencyMatrix.py | 1 | 4102 | import unittest
from unittest import TestCase
from numpy import array,r_
from numpy.ma.testutils import assert_close
from numpy.testing.utils import assert_allclose, assert_equal
from scipy.stats import norm
from scipy.stats.stats import pearsonr
from sklearn.utils import shuffle
from pyisc import AnomalyDetector, ... | lgpl-3.0 |
AlexRobson/nilmtk | nilmtk/datastore/hdfdatastore.py | 6 | 11833 | from __future__ import print_function, division
import pandas as pd
from itertools import repeat, tee
from time import time
from copy import deepcopy
from collections import OrderedDict
import numpy as np
import yaml
from os.path import isdir, isfile, join, exists, dirname
from os import listdir, makedirs, rem... | apache-2.0 |
thorwhalen/ut | daf/plot.py | 1 | 1671 | __author__ = 'thor'
import numpy as np
import ut.pplot.hist
import pandas as pd
import matplotlib.pylab as plt
from ut.util.utime import utc_ms_to_utc_datetime
def count_hist(sr, sort_by='value', reverse=True, horizontal=None, ratio=False, **kwargs):
horizontal = horizontal or isinstance(sr.iloc[0], str)
ut.... | mit |
agdestine/machine-learning | code/abalone.py | 3 | 1912 | # abalone
# Classification and Clustering of Wheat Dataset
#
# Author: Author: Benjamin Bengfort <bbengfort@districtdatalabs.com>
# Created: Thu Feb 26 17:56:52 2015 -0500
#
# Copyright (C) 2015 District Data Labs
# For license information, see LICENSE.txt
#
# ID: abalone.py [] benjamin@bengfort.com $
"""
Classif... | mit |
marcino239/vtracker | common.py | 1 | 6362 | #!/usr/bin/env python
'''
This module contains some common routines used by other samples.
'''
import numpy as np
import cv2
# built-in modules
import os
import itertools as it
from contextlib import contextmanager
image_extensions = ['.bmp', '.jpg', '.jpeg', '.png', '.tif', '.tiff', '.pbm', '.pgm', '.ppm']
class ... | gpl-2.0 |
StructuralNeurobiologyLab/SyConn | syconn/proc/image.py | 1 | 17513 | # -*- coding: utf-8 -*-
# SyConn - Synaptic connectivity inference toolkit
#
# Copyright (c) 2016 - now
# Max Planck Institute of Neurobiology, Martinsried, Germany
# Authors: Sven Dorkenwald, Philipp Schubert, Joergen Kornfeld
import numpy as np
from ..proc import log_proc
__cv2__ = True
try:
from cv2 import cre... | gpl-2.0 |
jskDr/keraspp | old/ae_conv_mnist.py | 1 | 3199 | #########################################################
# Convolutional layer based AE with MNIST, Models/Class
#########################################################
###########################
# AE 모델링
###########################
from keras import layers, models
def Conv2D(filters, kernel_size, padding='same'... | mit |
mailhexu/pyDFTutils | build/lib/pyDFTutils/tightbinding/mypythTB.py | 2 | 18994 | # -*- coding: utf-8 -*-
#!/usr/bin/env python3
from pythtb import tb_model,w90
from ase.calculators.interface import Calculator,DFTCalculator
from ase.dft.dos import DOS
from ase.dft.kpoints import monkhorst_pack
import numpy as np
#from tetrahedronDos import tetrahedronDosClass
from occupations import Occupations
from... | lgpl-3.0 |
Khreas/Tiramisu-authorRecognition | mlp.py | 1 | 10720 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
import os
import sys
import random
import numpy
import argparse
import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.preprocessing import StandardScaler
from sklearn.neural_network import MLPClassifier
alphabet... | unlicense |
BonexGu/Blik2D-SDK | Blik2D/addon/tensorflow-1.2.1_for_blik/tensorflow/contrib/learn/python/learn/learn_io/data_feeder_test.py | 71 | 12923 | # 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 |
louispotok/pandas | pandas/tests/indexing/test_ix.py | 3 | 12521 | """ test indexing with ix """
import pytest
from warnings import catch_warnings
import numpy as np
import pandas as pd
from pandas.core.dtypes.common import is_scalar
from pandas.compat import lrange
from pandas import Series, DataFrame, option_context, MultiIndex
from pandas.util import testing as tm
from pandas.e... | bsd-3-clause |
wchan/tensorflow | tensorflow/contrib/learn/python/learn/estimators/_sklearn.py | 1 | 6535 | """sklearn cross-support."""
# Copyright 2015-present The Scikit Flow 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/LI... | apache-2.0 |
ThomasMiconi/htmresearch | projects/sequence_prediction/continuous_sequence/run_tm_model.py | 3 | 16639 | ## ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013-2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This ... | agpl-3.0 |
GiggleLiu/QuRBM | sstate.py | 1 | 2572 | '''Sparse State Representation.'''
from numpy import *
import numbers
__all__=['SparseState','visualize_sstate','vec2sstate','soverlap']
def _compact_form(ws,configs):
'''Merge duplicate configs.'''
ws,configs=asarray(ws),asarray(configs)
order=lexsort(configs.T)
configs=configs[order]
ws=ws[orde... | mit |
reuk/wayverb | demo/evaluation/receivers/binaural.py | 2 | 1438 | #!/usr/local/bin/python
import numpy as np
import matplotlib
render = True
if render:
matplotlib.use('pgf')
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from string import split
import scipy.signal as signal
import pysndfile
import math
import os
import re
import json
def main():
files = [
... | gpl-2.0 |
bnaul/scikit-learn | sklearn/tree/tests/test_export.py | 6 | 18311 | """
Testing for export functions of decision trees (sklearn.tree.export).
"""
from re import finditer, search
from textwrap import dedent
from numpy.random import RandomState
import pytest
from sklearn.base import is_classifier
from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
from sklearn.ensemb... | bsd-3-clause |
dhruv13J/scikit-learn | examples/covariance/plot_outlier_detection.py | 235 | 3891 | """
==========================================
Outlier detection with several methods.
==========================================
When the amount of contamination is known, this example illustrates two
different ways of performing :ref:`outlier_detection`:
- based on a robust estimator of covariance, which is assumin... | bsd-3-clause |
kwailamchan/programming-languages | python/tensorflow/demos/tensorflow/concepts/conway.py | 3 | 1463 | import numpy as np
import tensorflow as tf
from scipy.signal import convolve2d
from matplotlib import pyplot as plt
import matplotlib.animation as animation
class Conway(object):
def __init__(self):
self.shape = (50, 50)
self.session = tf.Session()
def run(self):
initial_board = se... | mit |
ElDeveloper/qiime | qiime/make_distance_boxplots.py | 15 | 12397 | #!/usr/bin/env python
from __future__ import division
__author__ = "Jai Ram Rideout"
__copyright__ = "Copyright 2012, The QIIME project"
__credits__ = ["Jai Ram Rideout"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Jai Ram Rideout"
__email__ = "jai.rideout@gmail.com"
"""Contains functions used in ... | gpl-2.0 |
geoscixyz/em_examples | em_examples/InductionSphereTEM.py | 1 | 19333 | from __future__ import print_function
from __future__ import absolute_import
from __future__ import unicode_literals
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter, FormatStrFormatter
from matplotlib.path import Path
import matplotlib.patches as patc... | mit |
mxjl620/scikit-learn | sklearn/svm/classes.py | 126 | 40114 | import warnings
import numpy as np
from .base import _fit_liblinear, BaseSVC, BaseLibSVM
from ..base import BaseEstimator, RegressorMixin
from ..linear_model.base import LinearClassifierMixin, SparseCoefMixin, \
LinearModel
from ..feature_selection.from_model import _LearntSelectorMixin
from ..utils import check_X... | bsd-3-clause |
ForschungszentrumJuelich/phenoVein | General/Modules/Macros/FZJveinThickness/veinThickness_fitInLogSpace.py | 1 | 7063 | # Copyright (c) 2015, Forschungszentrum Jülich GmbH
# All rights reserved.
# Contributors: Jonas Bühler, Daniel Pflugfelder, Siegfried Jahnke
# Address: Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
#
# Redistribution and use in source and binary forms,... | bsd-3-clause |
tjkemp/image-tractor | test_feature_sets.py | 1 | 1958 | import numpy as np
import pandas as pd
from datetime import datetime
from sklearn.metrics import accuracy_score
from sklearn.metrics import confusion_matrix
from sklearn.svm import LinearSVC
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import normalize
def get_features(inputfile):
... | mit |
gieseke/bufferkdtree | docs/sphinxext/docscrape_sphinx.py | 1 | 9437 | from __future__ import division, absolute_import, print_function
import sys, re, inspect, textwrap, pydoc
import sphinx
import collections
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
if sys.version_info[0] >= 3:
sixu = lambda s: s
else:
sixu = lambda s: unicode(s, 'unicode_escape')
class Sph... | gpl-2.0 |
kubeflow/kfserving | docs/samples/explanation/art/mnist/query_explain.py | 1 | 2045 | import requests
import json
from matplotlib import pyplot as plt
import numpy as np
from aix360.datasets import MNISTDataset
import time
import sys
if len(sys.argv) < 3:
raise Exception("No endpoint specified. ")
endpoint = sys.argv[1]
headers = {
'Host': sys.argv[2]
}
data = MNISTDataset()
test_num = 349
is_... | apache-2.0 |
colin2328/asciiclass | lectures/lec6/match.py | 3 | 4033 | import csv
from sklearn import tree
import editdist
import re
#def string_match(s1,s2):
def string_match_score(p1,p2,field):
s1 = p1[field]
s2 = p2[field]
return editdist.distance(s1.lower(),s2.lower())/float(len(s1))
def jaccard_score(p1,p2,field):
name1 = p1[field]
name2 = p2[field]
set1 = ... | mit |
nicolas998/Op_Alarmas | 02_Codigos/alarmas.py | 1 | 6511 | #!/usr/bin/env python
import os
import pandas as pd
from wmf import wmf
import numpy as np
import glob
########################################################################
# VARIABLES GLOBALES
ruta_store = None
ruta_store_bck = None
########################################################################
# ... | gpl-3.0 |
IronManMark20/pyside2 | doc/inheritance_diagram.py | 10 | 12497 | # -*- coding: utf-8 -*-
r"""
sphinx.ext.inheritance_diagram
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Defines a docutils directive for inserting inheritance diagrams.
Provide the directive with one or more classes or modules (separated
by whitespace). For modules, all of the classes in that module will
... | lgpl-2.1 |
cuevas1208/Traffic_Sign_Classifier | preprocess_augmentation.py | 1 | 8132 | ## File: preprocess _augmentation.py
## Name: Manuel Cuevas
## Date: 01/14/2017
## Project: CarND - LaneLines
## Desc: Augmentation pipeline; techniques like Random rotations, Zoom,
## brightness, shear, translation and color tones are used here.
## Usage: Data augmentation allows the network to learn the importa... | gpl-3.0 |
jairideout/scikit-bio | skbio/diversity/beta/tests/test_unifrac.py | 6 | 30062 | # ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
# --------------------------------------------... | bsd-3-clause |
jokerbea/GOAT_Genetic_Output_Analysis_Tool | bokeh_GOAT/views.py | 2 | 9957 | # 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 |
sahands/pelican_article_recommender | article_recommender.py | 1 | 3461 | """
Article recommender plug-in that uses the content of the posts to determine
post similarity. Uses scikit-learn, and nltk.
"""
from __future__ import unicode_literals
from __future__ import print_function
from codecs import open as codec_open
from docutils.frontend import OptionParser
from docutils.nodes import Fix... | mit |
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