repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
monikascholz/pWARP | fluowarp.py | 1 | 9385 |
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 4 19:53:51 2014
Phase correlation drift correction.
Used papers Cross-correlation image tracking for drift correction and
adsorbate analysis B. A. Mantooth, Z. J. Donhauser, K. F. Kelly, and P. S. Weiss
for inspiration.
@author: Monika Kauer
"""
import numpy as np
impor... | gpl-2.0 |
nrhine1/scikit-learn | sklearn/neighbors/base.py | 22 | 31143 | """Base and mixin classes for nearest neighbors"""
# Authors: Jake Vanderplas <vanderplas@astro.washington.edu>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Sparseness support by Lars Buitinck <L.J.Buitinck@uva.nl>
# Multi-output... | bsd-3-clause |
LiaoPan/scikit-learn | examples/ensemble/plot_bias_variance.py | 357 | 7324 | """
============================================================
Single estimator versus bagging: bias-variance decomposition
============================================================
This example illustrates and compares the bias-variance decomposition of the
expected mean squared error of a single estimator again... | bsd-3-clause |
Cophy08/ggplot | ggplot/tests/test_element_text.py | 12 | 1362 | from nose.tools import assert_equal, assert_true
from ggplot.tests import image_comparison, cleanup
from ggplot import *
from numpy import linspace
from pandas import DataFrame
df = DataFrame({"blahblahblah": linspace(999, 1111, 9),
"yadayadayada": linspace(999, 1111, 9)})
simple_gg = ggplot(aes(x="b... | bsd-2-clause |
hgn/pmu-tools | interval-plot.py | 3 | 3566 | #!/usr/bin/python
# plot interval CSV output from perf/toplev
# perf stat -I1000 -x, -o file ...
# toplev -I1000 -x, -o file ...
# interval-plot.py file (or stdin)
# delimeter must be ,
# this is for data that is not normalized
# TODO: move legend somewhere else where it doesn't overlap?
import csv
import sys
import m... | gpl-2.0 |
phronesis-mnemosyne/census-schema-alignment | algn-merge.py | 1 | 4062 | import re
import json
import argparse
import numpy as np
import pandas as pd
import sys
sys.path.append('wit')
from mmd import *
from munkres import Munkres
# --
# Alignment functions
def align(dist):
'''
Munkres alignment between a single pair of schemas
'''
if dist.shape[0] > dist.shape[1]:
... | apache-2.0 |
henrykironde/scikit-learn | examples/tree/plot_tree_regression.py | 206 | 1476 | """
===================================================================
Decision Tree Regression
===================================================================
A 1D regression with decision tree.
The :ref:`decision trees <tree>` is
used to fit a sine curve with addition noisy observation. As a result, it
learns ... | bsd-3-clause |
MartinDelzant/scikit-learn | sklearn/utils/graph.py | 289 | 6239 | """
Graph utilities and algorithms
Graphs are represented with their adjacency matrices, preferably using
sparse matrices.
"""
# Authors: Aric Hagberg <hagberg@lanl.gov>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Jake Vanderplas <vanderplas@astro.washington.edu>
# License: BSD 3 clause
impo... | bsd-3-clause |
jrderuiter/pyim | src/pyim/annotate/annotators/window.py | 1 | 5561 | from collections import namedtuple
from itertools import chain
from pathlib import Path
import pandas as pd
from pyim.vendor.genopandas import GenomicDataFrame
from .base import Annotator, AnnotatorCommand, CisAnnotator
from ..util import filter_blacklist, select_closest, annotate_insertion
class WindowAnnotator(A... | mit |
moutai/scikit-learn | examples/model_selection/randomized_search.py | 44 | 3253 | """
=========================================================================
Comparing randomized search and grid search for hyperparameter estimation
=========================================================================
Compare randomized search and grid search for optimizing hyperparameters of a
random forest.
... | bsd-3-clause |
lepy/phuzzy | phuzzy/data/plots.py | 1 | 2069 | # -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
def p_estimates(df, ax=None, show=False):
if ax is None:
fig, ax = plt.subplots(1, 1, figsize=(10,5))
else:
fig = plt.gcf()
for col in [c for c in df.columns if c.startswith("p_")]:
ax.... | mit |
tapomayukh/projects_in_python | classification/Classification_with_kNN/Single_Contact_Classification/Spatial_Resolution/space_resolution_per_meter_mov_fixed_percent.py | 1 | 4190 |
# Principal Component Analysis Code :
from numpy import mean,cov,double,cumsum,dot,linalg,array,rank,size,flipud
from pylab import *
import numpy as np
import matplotlib.pyplot as pp
#from enthought.mayavi import mlab
import scipy.ndimage as ni
import roslib; roslib.load_manifest('sandbox_tapo_darpa_m3')
import ro... | mit |
HEHenson/CanDataPY | misc.py | 1 | 1202 | # -*- coding: utf-8 -*-
"""
Created on Tue Oct 18 19:57:47 2016
@author: lancehermes
"""
import glob
import shutil
from pandas import Series, DataFrame, HDFStore
import pandas.rpy.common as com
import feather
from rpy2.robjects import pandas2ri
def copycsv():
rootdir = "/home/lancehermes/Dropbox/business/Project... | unlicense |
drammock/expyfun | expyfun/visual/_visual.py | 2 | 46036 | """
Visual stimulus design
======================
Tools for drawing shapes and text on the screen.
"""
# Authors: Dan McCloy <drmccloy@uw.edu>
# Eric Larson <larsoner@uw.edu>
# Ross Maddox <rkmaddox@uw.edu>
#
# License: BSD (3-clause)
from ctypes import (cast, pointer, POINTER, create_string_buffer... | bsd-3-clause |
pratapvardhan/scikit-image | skimage/transform/tests/test_radon_transform.py | 13 | 14551 | from __future__ import print_function, division
import numpy as np
from numpy.testing import assert_raises
import itertools
import os.path
from skimage.transform import radon, iradon, iradon_sart, rescale
from skimage.io import imread
from skimage import data_dir
from skimage._shared.testing import test_parallel
from... | bsd-3-clause |
agiovann/CalBlitz | calblitz/granule_cells/utils_granule.py | 1 | 44647 | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 16 17:56:14 2016
@author: agiovann
"""
import os
import cv2
import h5py
import numpy as np
import pylab as pl
from glob import glob
# import ca_source_extraction as cse
import calblitz as cb
from scipy import signal
import scipy
import sys
from ipyparallel import Client
f... | gpl-3.0 |
deroneriksson/systemml | projects/breast_cancer/breastcancer/preprocessing.py | 15 | 26035 | #-------------------------------------------------------------
#
# 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... | apache-2.0 |
mdjurfeldt/nest-simulator | topology/doc/user_manual_scripts/layers.py | 8 | 10527 | # -*- coding: utf-8 -*-
#
# layers.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
# (a... | gpl-2.0 |
google-research/google-research | constrained_language_typology/compute_associations_main.py | 1 | 9567 | # coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# 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 applicab... | apache-2.0 |
XiaoxiaoLiu/morphology_analysis | IVSCC/add_extra_ratio_features.py | 1 | 2313 | import pandas as pd
import platform
if (platform.system() == "Linux"):
WORK_PATH = "/local1/xiaoxiaol/work"
else:
WORK_PATH = "/Users/xiaoxiaoliu/work"
###############################################################################
#data_DIR = '/data/mat/xiaoxiaol/data/lims2/0903_filtered_ephys_qc'
data_DIR =... | gpl-3.0 |
harshaneelhg/scikit-learn | examples/applications/plot_model_complexity_influence.py | 323 | 6372 | """
==========================
Model Complexity Influence
==========================
Demonstrate how model complexity influences both prediction accuracy and
computational performance.
The dataset is the Boston Housing dataset (resp. 20 Newsgroups) for
regression (resp. classification).
For each class of models we m... | bsd-3-clause |
jmschrei/scikit-learn | examples/cluster/plot_mini_batch_kmeans.py | 265 | 4081 | """
====================================================================
Comparison of the K-Means and MiniBatchKMeans clustering algorithms
====================================================================
We want to compare the performance of the MiniBatchKMeans and KMeans:
the MiniBatchKMeans is faster, but give... | bsd-3-clause |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/matplotlib/backends/backend_gtk3.py | 2 | 32330 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import os, sys
try:
import gi
except ImportError:
raise ImportError("Gtk3 backend requires pygobject to be installed.")
try:
gi.require_version("Gtk", "3.0")
except AttributeError:
... | mit |
bowang/tensorflow | tensorflow/examples/learn/text_classification.py | 17 | 6649 | # 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 |
kmike/scikit-learn | examples/svm/plot_svm_regression.py | 8 | 1431 | """
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
===================================================================
Toy example of 1D regression using linear, polynominial and RBF
kernels.
"""
print(__doc__)
#################... | bsd-3-clause |
harisbal/pandas | pandas/tests/indexes/timedeltas/test_ops.py | 1 | 14479 | from datetime import timedelta
import numpy as np
import pytest
import pandas as pd
import pandas.util.testing as tm
from pandas import (
Series, Timedelta, TimedeltaIndex, Timestamp, timedelta_range,
to_timedelta
)
from pandas.core.dtypes.generic import ABCDateOffset
from pandas.tests.test_base import Ops
fr... | bsd-3-clause |
danieljwest/mycli | mycli/packages/tabulate.py | 16 | 38129 | # -*- coding: utf-8 -*-
"""Pretty-print tabular data."""
from __future__ import print_function
from __future__ import unicode_literals
from collections import namedtuple
from decimal import Decimal
from platform import python_version_tuple
from wcwidth import wcswidth
import re
if python_version_tuple()[0] < "3":
... | bsd-3-clause |
momenteg/python_scripts | hidden_supernova_search/read_and_plot_data_injected_in_Sndaq.py | 1 | 4011 | #!/usr/bin/python
import pandas as pd
import numpy as np
import glob
import matplotlib.pyplot as plt
import seaborn
import subprocess
import os
import re
def mount_mogon():
print("mounting mogon via sshfs")
string_ = "sshfs -o nonempty dummy_user@dummy_address:/etapfs02/icecubehpc/gmoment/output_hidden_super... | gpl-3.0 |
arjunkhode/ASP | lectures/07-Sinusoidal-plus-residual-model/plots-code/stochasticModelAnalSynth.py | 5 | 1619 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, hanning, resample
from scipy.fftpack import fft, ifft
import time
import sys, os
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import utilFunctions as UF
import stochasticMode... | agpl-3.0 |
mikofski/pvlib-python | pvlib/iotools/bsrn.py | 3 | 6686 | """Functions to read data from the Baseline Surface Radiation Network (BSRN).
.. codeauthor:: Adam R. Jensen<adam-r-j@hotmail.com>
"""
import pandas as pd
import gzip
COL_SPECS = [(0, 3), (4, 9), (10, 16), (16, 22), (22, 27), (27, 32), (32, 39),
(39, 45), (45, 50), (50, 55), (55, 64), (64, 70), (... | bsd-3-clause |
lbdreyer/iris | docs/iris/gallery_code/general/plot_inset.py | 3 | 2280 | """
Test Data Showing Inset Plots
=============================
This example demonstrates the use of a single 3D data cube with time, latitude
and longitude dimensions to plot a temperature series for a single latitude
coordinate, with an inset plot of the data region.
"""
import cartopy.crs as ccrs
import matplotli... | lgpl-3.0 |
hhuangmeso/cmaps | setup.py | 1 | 2866 | from glob import glob
from setuptools import setup
import os
VERSION = '1.0.3'
CMAPSFILE_DIR = os.path.join('./cmaps/colormaps')
def write_version_py(version=VERSION, filename='cmaps/_version.py'):
cnt = '# THIS FILE IS GENERATED FROM SETUP.PY\n' + \
'__version__ = "%(version)s"\n'
a = open(filena... | gpl-3.0 |
kelseyoo14/Wander | venv_2_7/lib/python2.7/site-packages/pandas/core/ops.py | 9 | 48430 | """
Arithmetic operations for PandasObjects
This is not a public API.
"""
# necessary to enforce truediv in Python 2.X
from __future__ import division
import operator
import warnings
import numpy as np
import pandas as pd
import datetime
from pandas import compat, lib, tslib
import pandas.index as _index
from pandas.u... | artistic-2.0 |
abyssxsy/gnuradio | gr-filter/examples/interpolate.py | 58 | 8816 | #!/usr/bin/env python
#
# Copyright 2009,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your ... | gpl-3.0 |
waddell/urbansim | urbansim/utils/tests/test_testing.py | 5 | 2190 |
import pandas as pd
import pytest
from .. import testing
def test_frames_equal_not_frames():
frame = pd.DataFrame({'a': [1]})
with pytest.raises(AssertionError) as info:
testing.assert_frames_equal(frame, 1)
assert info.value.message == 'Inputs must both be pandas DataFrames.'
def test_frames... | bsd-3-clause |
chatelak/RMG-Py | rmgpy/stats.py | 4 | 8698 | #!/usr/bin/python
# -*- coding: utf-8 -*-
################################################################################
#
# RMG - Reaction Mechanism Generator
#
# Copyright (c) 2002-2012 Prof. Richard H. West (r.west@neu.edu),
# Prof. William H. Green (whgreen@mit.edu)
# ... | mit |
danielhomola/mifs | mifs/mi.py | 1 | 5334 | """
Methods for calculating Mutual Information in an embarrassingly parallel way.
Author: Daniel Homola <dani.homola@gmail.com>
License: BSD 3 clause
"""
import numpy as np
from scipy.special import gamma, psi
from sklearn.neighbors import NearestNeighbors
from joblib import Parallel, delayed
def get_mi_vector(MI_FS... | bsd-3-clause |
q1ang/scikit-learn | examples/ensemble/plot_ensemble_oob.py | 259 | 3265 | """
=============================
OOB Errors for Random Forests
=============================
The ``RandomForestClassifier`` is trained using *bootstrap aggregation*, where
each new tree is fit from a bootstrap sample of the training observations
:math:`z_i = (x_i, y_i)`. The *out-of-bag* (OOB) error is the average er... | bsd-3-clause |
jaduimstra/nilmtk | nilmtk/metergroup.py | 2 | 70088 | from __future__ import print_function, division
import networkx as nx
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
from datetime import timedelta
from warnings import warn
from sys import stdout
from collections import Counter
from copy import copy, ... | apache-2.0 |
avmarchenko/exatomic | exatomic/algorithms/displacement.py | 3 | 1635 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2018, Exa Analytics Development Team
# Distributed under the terms of the Apache License 2.0
"""
Computation of Displacement
############################
"""
import numpy as np
import pandas as pd
def absolute_squared_displacement(universe, ref_frame=None):
... | apache-2.0 |
saiwing-yeung/scikit-learn | sklearn/datasets/tests/test_20news.py | 280 | 3045 | """Test the 20news downloader, if the data is available."""
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import SkipTest
from sklearn import datasets
def test_20news():
try:
data = dat... | bsd-3-clause |
pprett/scikit-learn | examples/model_selection/plot_confusion_matrix.py | 63 | 3231 | """
================
Confusion matrix
================
Example of confusion matrix usage to evaluate the quality
of the output of a classifier on the iris data set. The
diagonal elements represent the number of points for which
the predicted label is equal to the true label, while
off-diagonal elements are those that ... | bsd-3-clause |
hugobowne/scikit-learn | sklearn/kernel_approximation.py | 258 | 17973 | """
The :mod:`sklearn.kernel_approximation` module implements several
approximate kernel feature maps base on Fourier transforms.
"""
# Author: Andreas Mueller <amueller@ais.uni-bonn.de>
#
# License: BSD 3 clause
import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import svd
from .base im... | bsd-3-clause |
adrn/streams | streams/io/tests/test_lm10.py | 1 | 4462 | # coding: utf-8
"""
Make sure the satellite starting position coincides with the particles
"""
from __future__ import absolute_import, unicode_literals, division, print_function
__author__ = "adrn <adrn@astro.columbia.edu>"
# Standard library
import os, sys
# Third-party
import astropy.units as u
from astropy.c... | mit |
YinongLong/scikit-learn | sklearn/semi_supervised/tests/test_label_propagation.py | 307 | 1974 | """ test the label propagation module """
import nose
import numpy as np
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {'kernel': 'rbf'}),
(label_propa... | bsd-3-clause |
nowls/gnuradio | gr-filter/examples/decimate.py | 58 | 6061 | #!/usr/bin/env python
#
# Copyright 2009,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your ... | gpl-3.0 |
sandeepgupta2k4/tensorflow | tensorflow/contrib/learn/python/learn/estimators/kmeans.py | 34 | 10130 | # 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 |
mughanibu/Deep-Learning-for-Inverse-Problems | PLOT.py | 1 | 2433 | import matplotlib.pyplot as plt
import pickle, glob
import numpy as np
import sys
psnr_prefix = './psnr/*'
psnr_paths = sorted(glob.glob(psnr_prefix))
psnr_means = {}
def filter_by_scale(row, scale):
return row[-1]==scale
for i, psnr_path in enumerate(psnr_paths):
print ""
print psnr_path
psnr_dict = None
epoch... | mit |
mschmidt87/nest-simulator | extras/ConnPlotter/examples/connplotter_tutorial.py | 18 | 27730 | # -*- coding: utf-8 -*-
#
# connplotter_tutorial.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 Li... | gpl-2.0 |
CtraliePubs/SOCGMM2016_SlidingWindowVideo | JumpingJacks/plotPixel.py | 1 | 1320 | import numpy as np
import matplotlib.pyplot as plt
import scipy.misc
import sys
sys.path.append("../")
sys.path.append("../S3DGLPy")
from VideoTools import *
from PCAGL import *
if __name__ == '__main__':
(Vid, IDims) = loadCVVideo('jumpingjackscropped.avi')
N = Vid.shape[1]
loc = [70, 323]
vals ... | apache-2.0 |
zhenv5/scikit-learn | sklearn/ensemble/partial_dependence.py | 251 | 15097 | """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 |
bbci/mushu | test/test_triggerdelay.py | 3 | 3724 | #!/usr/bin/env python
# test_triggerdelay.py
# Copyright (C) 2013 Bastian Venthur
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any l... | gpl-2.0 |
automl/paramsklearn | tests/components/feature_preprocessing/test_liblinear.py | 1 | 2085 | import unittest
from sklearn.linear_model import RidgeClassifier
from ParamSklearn.components.feature_preprocessing.liblinear_svc_preprocessor import \
LibLinear_Preprocessor
from ParamSklearn.util import _test_preprocessing, PreprocessingTestCase, \
get_dataset
import sklearn.metrics
class LiblinearComponen... | bsd-3-clause |
0x0all/scikit-learn | benchmarks/bench_plot_ward.py | 290 | 1260 | """
Benchmark scikit-learn's Ward implement compared to SciPy's
"""
import time
import numpy as np
from scipy.cluster import hierarchy
import pylab as pl
from sklearn.cluster import AgglomerativeClustering
ward = AgglomerativeClustering(n_clusters=3, linkage='ward')
n_samples = np.logspace(.5, 3, 9)
n_features = n... | bsd-3-clause |
dsilvestro/PyRate | experimental_code/plot_BDNN.py | 1 | 13787 | import numpy as np
np.set_printoptions(suppress= 1, precision=3)
import os, csv
import pandas as pd
def softPlus(z):
return np.log(np.exp(z) + 1)
def get_rate_BDNN(rate, x, w):
# n: n species, j: traits, i: nodes
z = np.einsum('nj,ij->ni', x, w[0])
z[z < 0] = 0
z = np.einsum('ni,i->n', z, w[1])... | agpl-3.0 |
fabianp/scikit-learn | sklearn/feature_selection/tests/test_base.py | 170 | 3666 | import numpy as np
from scipy import sparse as sp
from nose.tools import assert_raises, assert_equal
from numpy.testing import assert_array_equal
from sklearn.base import BaseEstimator
from sklearn.feature_selection.base import SelectorMixin
from sklearn.utils import check_array
class StepSelector(SelectorMixin, Ba... | bsd-3-clause |
dsavransky/plandb.sioslab.com | getDataFromIPAC_composite.py | 1 | 44449 | import requests
import pandas
from StringIO import StringIO
import astropy.units as u
import astropy.constants as const
import EXOSIMS.PlanetPhysicalModel.Forecaster
from sqlalchemy import create_engine
import getpass,keyring
import numpy as np
import os
from scipy.interpolate import interp1d, interp2d, RectBivariateSp... | mit |
rahul-c1/scikit-learn | examples/linear_model/plot_bayesian_ridge.py | 248 | 2588 | """
=========================
Bayesian Ridge Regression
=========================
Computes a Bayesian Ridge Regression on a synthetic dataset.
See :ref:`bayesian_ridge_regression` for more information on the regressor.
Compared to the OLS (ordinary least squares) estimator, the coefficient
weights are slightly shift... | bsd-3-clause |
mdeff/ntds_2017 | projects/reports/wikipedia_hyperlink/utils.py | 1 | 9130 | import wikipedia
import pickle
import matplotlib.pyplot as plt
import seaborn as sns
import networkx as nx
import numpy as np
import plotly.graph_objs as go
from sklearn import linear_model
def explore_page(page_title, network, to_explore, inner=False, all_nodes=None):
"""
This function explores the Wikipedi... | mit |
rseubert/scikit-learn | sklearn/metrics/setup.py | 299 | 1024 | import os
import os.path
import numpy
from numpy.distutils.misc_util import Configuration
from sklearn._build_utils import get_blas_info
def configuration(parent_package="", top_path=None):
config = Configuration("metrics", parent_package, top_path)
cblas_libs, blas_info = get_blas_info()
if os.name ==... | bsd-3-clause |
uglyboxer/linear_neuron | net-p3/lib/python3.5/site-packages/matplotlib/style/core.py | 11 | 4957 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
"""
Core functions and attributes for the matplotlib style library:
``use``
Select style sheet to override the current matplotlib settings.
``context``
Context manager to use a style sheet ... | mit |
jaytlennon/Dimensions | Aim3/papers/DD/PythonScripts/Env_Geo_Bootstrap.py | 4 | 6308 | from __future__ import division
import matplotlib.pyplot as plt
import geopy
from geopy.distance import vincenty
import skbio
import skbio.diversity
import skbio.diversity.beta
from skbio.diversity import beta_diversity
import pandas as pd
import linecache
import numpy as np
import scipy as sc
import scipy.spatial.... | gpl-3.0 |
asnorkin/sentiment_analysis | site/lib/python2.7/site-packages/sklearn/neighbors/tests/test_approximate.py | 55 | 19053 | """
Testing for the approximate neighbor search using
Locality Sensitive Hashing Forest module
(sklearn.neighbors.LSHForest).
"""
# Author: Maheshakya Wijewardena, Joel Nothman
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_a... | mit |
ioam/holoviews | holoviews/tests/plotting/matplotlib/testelementplot.py | 2 | 6569 | import numpy as np
from holoviews.core.spaces import DynamicMap
from holoviews.element import Image, Curve, Scatter, Scatter3D
from holoviews.streams import Stream
from .testplot import TestMPLPlot, mpl_renderer
try:
from matplotlib.ticker import FormatStrFormatter, FuncFormatter, PercentFormatter
except:
pa... | bsd-3-clause |
hainm/open-forcefield-group | nmr/ace_x_y_nh2/code/analyze_scalar_couplings.py | 2 | 1531 | import pandas as pd
import mdtraj as md
from ace_x_y_nh2_parameters import *
larger = pd.read_csv("./data/larger_couplings.csv")
smaller = pd.read_csv("./data/smaller_couplings.csv")
reference = []
for aa in amino_acids:
value = smaller.ix["G"][aa]
xyz = ["G%s" % aa, 0, value]
reference.append(xyz)
... | gpl-2.0 |
kaichogami/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 |
wkfwkf/statsmodels | statsmodels/tsa/vector_ar/var_model.py | 25 | 50516 | """
Vector Autoregression (VAR) processes
References
----------
Lutkepohl (2005) New Introduction to Multiple Time Series Analysis
"""
from __future__ import division, print_function
from statsmodels.compat.python import (range, lrange, string_types, StringIO, iteritems,
cStringIO)
fr... | bsd-3-clause |
BlueBrain/NeuroM | examples/end_to_end_distance.py | 1 | 4398 | #!/usr/bin/env python
# Copyright (c) 2015, Ecole Polytechnique Federale de Lausanne, Blue Brain Project
# All rights reserved.
#
# This file is part of NeuroM <https://github.com/BlueBrain/NeuroM>
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the fol... | bsd-3-clause |
harterj/moose | modules/porous_flow/doc/content/modules/porous_flow/tests/sinks/sinks.py | 9 | 10282 | #!/usr/bin/env python3
#* This file is part of the MOOSE framework
#* https://www.mooseframework.org
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moose/blob/master/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgp... | lgpl-2.1 |
glenioborges/ibis | ibis/sql/sqlite/tests/test_client.py | 6 | 2772 | # 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 |
deepmind/deepmind-research | meshgraphnets/plot_cloth.py | 1 | 2159 | # Lint as: python3
# pylint: disable=g-bad-file-header
# Copyright 2020 DeepMind Technologies Limited. 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.a... | apache-2.0 |
MaxHalford/Prince | tests/test_pca.py | 1 | 3331 | import unittest
import matplotlib as mpl
import numpy as np
import pandas as pd
from sklearn import datasets
from sklearn import decomposition
from sklearn.utils import estimator_checks
import prince
class TestPCA(unittest.TestCase):
def setUp(self):
X, _ = datasets.load_iris(return_X_y=True)
c... | mit |
userdw/RaspberryPi_3_Starter_Kit | 08_Image_Processing/Color_Spaces/hls/hls.py | 1 | 1179 | import os, cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
_projectDirectory = os.path.dirname(__file__)
_imagesDirectory = os.path.join(_projectDirectory, "images")
_images = []
for _root, _dirs, _files in os.walk(_imagesDirectory):
for _file in _files:
i... | mit |
jjhelmus/artview | docs/sphinxext/numpydoc/tests/test_docscrape.py | 3 | 17864 | # -*- encoding:utf-8 -*-
from __future__ import division, absolute_import, print_function
import sys, textwrap
from numpydoc.docscrape import NumpyDocString, FunctionDoc, ClassDoc
from numpydoc.docscrape_sphinx import SphinxDocString, SphinxClassDoc
from nose.tools import *
doc_txt = '''\
numpy.multivariate_normal... | bsd-3-clause |
anhaidgroup/py_entitymatching | py_entitymatching/matcher/svmmatcher.py | 1 | 1145 | """
This module contains the functions for SVM classifier.
"""
from py_entitymatching.matcher.mlmatcher import MLMatcher
from py_entitymatching.matcher.matcherutils import get_ts
from sklearn.svm import SVC
class SVMMatcher(MLMatcher):
"""
SVM matcher.
Args:
*args,**kwargs: The arguments to scik... | bsd-3-clause |
phdowling/scikit-learn | sklearn/tests/test_calibration.py | 213 | 12219 | # Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from sklearn.utils.testing import (assert_array_almost_equal, assert_equal,
assert_greater, assert_almost_equal,
... | bsd-3-clause |
MichaelAquilina/numpy | 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... | bsd-3-clause |
Unpluralized/PyAE | pridb_filters.py | 1 | 19158 | # coding: utf-8
import pandas as pd
from numpy import gradient as np_gradient
import ConfigParser
from numba import jit
import time
import pickle
config = ConfigParser.ConfigParser()
config.read('./pridb_filter_config.ini')
def apply_filters(df, name, **kwargs):
"""
:param df: Pandas dataframe with ... | gpl-3.0 |
RobertABT/heightmap | build/matplotlib/examples/axes_grid/simple_anchored_artists.py | 16 | 1950 | import matplotlib.pyplot as plt
def draw_text(ax):
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredText
at = AnchoredText("Figure 1a",
loc=2, prop=dict(size=8), frameon=True,
)
at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
ax.add_artis... | mit |
nicholasmalaya/paleologos | exp/press_trans/code/read_incline_error.py | 2 | 2212 | #!/bin/py
#
# open file
# read contents
# (re)start when third column found
#
import sys
#
# open and read file
#
path="../data/statistics_incl.lvm"
file = open(path, "r+")
#
# data objects
#
set_names = []
voltage = []
std = []
height = []
voltage2 = []
std2 = []
height2 = []
for line in file:
... | mit |
lssfau/walberla | apps/benchmarks/UniformGrid/ecmModel.py | 1 | 2190 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
kernels = dict()
class Kernel:
def __init__(self, name, cyclesFirstLoop=0, cyclesSecondLoop=0, cyclesRegPerLUP=0):
self.name = name
if cyclesRegPerLUP <= 0:
self.cyclesFirstLoop = cyclesFirstLoop
self.c... | gpl-3.0 |
vlouf/cpol_processing | cpol_processing/filtering.py | 1 | 9055 | """
Codes for creating and manipulating gate filters. New functions: use of trained
Gaussian Mixture Models to remove noise and clutter from CPOL data before 2009.
@title: filtering.py
@author: Valentin Louf <valentin.louf@bom.gov.au>
@institutions: Monash University and the Australian Bureau of Meteorology
@created: ... | mit |
brev/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/texmanager.py | 69 | 16818 | """
This module supports embedded TeX expressions in matplotlib via dvipng
and dvips for the raster and postscript backends. The tex and
dvipng/dvips information is cached in ~/.matplotlib/tex.cache for reuse between
sessions
Requirements:
* latex
* \*Agg backends: dvipng
* PS backend: latex w/ psfrag, dvips, and Gh... | agpl-3.0 |
MaxInGaussian/SCFGP | SCFGP/SCFGP.py | 1 | 13766 | ################################################################################
# SCFGP: Sparsely Correlated Fourier Features Based Gaussian Process
# Github: https://github.com/MaxInGaussian/SCFGP
# Author: Max W. Y. Lam (maxingaussian@gmail.com)
####################################################################... | bsd-3-clause |
finfou/tushare | tushare/stock/trading.py | 1 | 23685 | # -*- coding:utf-8 -*-
"""
交易数据接口
Created on 2014/07/31
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
from __future__ import division
import time
import json
import lxml.html
from lxml import etree
import pandas as pd
import numpy as np
from tushare.stock import cons as ct
import... | bsd-3-clause |
jmausolf/Python_Tutorials | PostgreSQL_with_Python/prepare.py | 1 | 10406 | import sys
import os
import pandas as pd
import subprocess
import argparse
import pdb
import pickle
from setup import setup_environment
"""
Code to take top performing recent models and
put them in the evaluation webapp for further
examination.
Examples:
--------
python prepare.py '2016-08-03' 'auc'
python prepare.py ... | mit |
scott-maddox/simplepl | setup.py | 1 | 3692 | #
# Copyright (c) 2014, Scott J Maddox
#
# This file is part of Plot Liberator.
#
# Plot Liberator 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, or
# (at y... | agpl-3.0 |
szredinger/graph-constr-group-testing | graph_constr_group_testing/results_analyser.py | 1 | 1187 | import collections
import csv
from graph_constr_group_testing.core import base_types
import pandas
def averageQueriesForSize(results):
result = []
count = collections.defaultdict(int)
sumallqueries = collections.defaultdict(int)
for solver, problem, statistics in results:
n = base_types.size_o... | mit |
pythonvietnam/scikit-learn | examples/semi_supervised/plot_label_propagation_digits.py | 268 | 2723 | """
===================================================
Label Propagation digits: Demonstrating performance
===================================================
This example demonstrates the power of semisupervised learning by
training a Label Spreading model to classify handwritten digits
with sets of very few labels.... | bsd-3-clause |
HesselTjeerdsma/Cyber-Physical-Pacman-Game | Algor/flask/lib/python2.7/site-packages/scipy/integrate/quadrature.py | 20 | 28269 | from __future__ import division, print_function, absolute_import
import numpy as np
import math
import warnings
# trapz is a public function for scipy.integrate,
# even though it's actually a numpy function.
from numpy import trapz
from scipy.special import roots_legendre
from scipy.special import gammaln
from scipy.... | apache-2.0 |
deepesch/scikit-learn | sklearn/covariance/tests/test_covariance.py | 142 | 11068 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_alm... | bsd-3-clause |
mxjl620/scikit-learn | examples/ensemble/plot_partial_dependence.py | 249 | 4456 | """
========================
Partial Dependence Plots
========================
Partial dependence plots show the dependence between the target function [1]_
and a set of 'target' features, marginalizing over the
values of all other features (the complement features). Due to the limits
of human perception the size of t... | bsd-3-clause |
DillonNovak/Programming-for-Chemical-Engineering-Applications | Breast+Cancer+Diagnosis.py | 1 | 5376 |
# coding: utf-8
# ## Predicting Malignant Tumors
# ### Wisconsin Diagnostic Beast Cancer Dataset
# https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)
#
# Dataset attributes:
#
# 0. diagnosis (malignant or benign)
#
# 1. radius (mean of distances from center to points o... | gpl-3.0 |
Nyker510/scikit-learn | examples/linear_model/plot_sgd_penalties.py | 249 | 1563 | """
==============
SGD: Penalties
==============
Plot the contours of the three penalties.
All of the above are supported by
:class:`sklearn.linear_model.stochastic_gradient`.
"""
from __future__ import division
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def l1(xs):
return np.array([np.... | bsd-3-clause |
bhermanmit/openmc | openmc/mgxs/mdgxs.py | 1 | 116899 | from __future__ import division
from collections import Iterable, OrderedDict
import itertools
from numbers import Integral
import warnings
import os
import sys
import copy
from abc import ABCMeta
from six import add_metaclass, string_types
import numpy as np
import openmc
from openmc.mgxs import MGXS
from openmc.mg... | mit |
severinson/coded-computing-tools | rateless.py | 2 | 15846 | '''Optimize rateless codes for distributed computing
'''
import math
import random
import logging
import numpy as np
import pandas as pd
import pyrateless
import stats
import complexity
import overhead
import pynumeric
import tempfile
import subprocess
from os import path
from multiprocessing import Pool
def optimi... | apache-2.0 |
jwlawson/tensorflow | tensorflow/examples/tutorials/word2vec/word2vec_basic.py | 6 | 10430 | # 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 |
jpinsonault/android_sensor_logger | python_scripts/cluster_light.py | 1 | 2894 | import numpy as np
import argparse
from pprint import pprint
from sklearn import mixture
from sklearn import datasets
import matplotlib.pyplot as plt
from sklearn import decomposition
from LogEntry import LogEntry
from LogEntry import db
from datetime import datetime
from matplotlib.dates import DayLocator, HourLocator... | mit |
blaisb/cfdemUtilities | independentTests/dragSphere.py | 2 | 1890 | # This program is a simple ODE solver for the case of the drag around a single sphere
# This can be used to predict the stability of the CFDEM coupling time and to play around with the concepts
# Time integration is Euler scheme and Euler form for the drag is assumed
# TODO
# Verlet integration should be added to see ... | lgpl-3.0 |
TAMU-CLASS/barnfire | src/materials_bondarenko.py | 1 | 17178 | '''
Andrew Till
Summer 2014
Bondarenko iteration utility for materials
'''
#STDLIB
import os
import shutil
#TPL
import numpy as np
#MINE
from materials_util import is_fissionable
import materials_util as util
from directories import get_common_directories
import Readgroupr as readgroupr
import PDTXS as pdtxs
def per... | mit |
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