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 |
|---|---|---|---|---|---|
kelseyoo14/Wander | venv_2_7/lib/python2.7/site-packages/pandas/sandbox/qtpandas.py | 13 | 4347 | '''
Easy integration of DataFrame into pyqt framework
@author: Jev Kuznetsov
'''
# GH9615
import warnings
warnings.warn("The pandas.sandbox.qtpandas module is deprecated and will be "
"removed in a future version. We refer users to the external package "
"here: https://github.com/datalyze... | artistic-2.0 |
shikhardb/scikit-learn | benchmarks/bench_sgd_regression.py | 283 | 5569 | """
Benchmark for SGD regression
Compares SGD regression against coordinate descent and Ridge
on synthetic data.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
# License: BSD 3 clause
import numpy as np
import pylab as pl
import gc
from time import time
from sklearn.linear_model i... | bsd-3-clause |
deepesch/scikit-learn | sklearn/grid_search.py | 32 | 36586 | """
The :mod:`sklearn.grid_search` includes utilities to fine-tune the parameters
of an estimator.
"""
from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# ... | bsd-3-clause |
nuclear-wizard/moose | test/tests/time_integrators/scalar/run_stiff.py | 12 | 5982 | #!/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 |
clingsz/GAE | main.py | 1 | 1502 | # -*- coding: utf-8 -*-
"""
Created on Wed May 10 12:38:40 2017
@author: cling
"""
def summarizing_cross_validation():
import misc.cv.collect_ND5_3 as cv
cv.fig_boxplot_cverr()
def test_trainer():
import misc.data_gen as dg
import gae.model.trainer as tr
data = dg.get_training_data()
... | gpl-3.0 |
internetmosquito/image-tagging-apis | image_tagging.py | 1 | 16562 |
import os
import yaml
import json
import zipfile
import pandas
import simplejson
import ntpath
import base64
import time
from httplib2 import HttpLib2Error
from googleapiclient import discovery
from googleapiclient.errors import HttpError
from oauth2client.client import GoogleCredentials
from watson_developer_clou... | mit |
codevlabs/pandashells | pandashells/bin/p_linspace.py | 7 | 1450 | #! /usr/bin/env python
# standard library imports
import sys # NOQA import sys to allow for mocking sys.argv in tests
import argparse
import textwrap
from pandashells.lib import module_checker_lib, arg_lib, io_lib
# import required dependencies
module_checker_lib.check_for_modules(['numpy', 'pandas'])
import numpy... | bsd-2-clause |
gclenaghan/scikit-learn | examples/gaussian_process/plot_compare_gpr_krr.py | 67 | 5191 | """
==========================================================
Comparison of kernel ridge and Gaussian process regression
==========================================================
Both kernel ridge regression (KRR) and Gaussian process regression (GPR) learn
a target function by employing internally the "kernel trick... | bsd-3-clause |
m3wolf/xanespy | tests/test_importers.py | 1 | 48905 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright © 2016 Mark Wolf
#
# This file is part of Xanespy.
#
# Xanespy is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# ... | gpl-3.0 |
ywcui1990/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/rcsetup.py | 69 | 23344 | """
The rcsetup module contains the default values and the validation code for
customization using matplotlib's rc settings.
Each rc setting is assigned a default value and a function used to validate any
attempted changes to that setting. The default values and validation functions
are defined in the rcsetup module, ... | agpl-3.0 |
soulmachine/scikit-learn | sklearn/ensemble/tests/test_bagging.py | 7 | 21070 | """
Testing for the bagging ensemble module (sklearn.ensemble.bagging).
"""
# Author: Gilles Louppe
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.u... | bsd-3-clause |
bartslinger/paparazzi | sw/airborne/test/math/compare_utm_enu.py | 77 | 2714 | #!/usr/bin/env python
from __future__ import division, print_function, absolute_import
import sys
import os
PPRZ_SRC = os.getenv("PAPARAZZI_SRC", "../../../..")
sys.path.append(PPRZ_SRC + "/sw/lib/python")
from pprz_math.geodetic import *
from pprz_math.algebra import DoubleRMat, DoubleEulers, DoubleVect3
from math ... | gpl-2.0 |
Adai0808/scikit-learn | benchmarks/bench_plot_parallel_pairwise.py | 297 | 1247 | # Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD 3 clause
import time
import pylab as pl
from sklearn.utils import check_random_state
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.metrics.pairwise import pairwise_kernels
def plot(func):
random_state = check_random_state(0)
... | bsd-3-clause |
VaclavDedik/classifier | classifier/selectors.py | 1 | 9474 | import numpy as np
from nltk.corpus import stopwords
from sklearn.decomposition import TruncatedSVD
from sklearn import feature_selection
from sklearn.feature_extraction.text import CountVectorizer
import utils
class AbstractSelector(object):
"""Abstract feature selector. When implementing a subclass, you have ... | mit |
GbalsaC/bitnamiP | venv/lib/python2.7/site-packages/sklearn/qda.py | 3 | 6694 | """
Quadratic Discriminant Analysis
"""
# Author: Matthieu Perrot <matthieu.perrot@gmail.com>
#
# License: BSD Style.
import warnings
import numpy as np
from .base import BaseEstimator, ClassifierMixin
from .utils.fixes import unique
from .utils import check_arrays
__all__ = ['QDA']
class QDA(BaseEstimator, Clas... | agpl-3.0 |
sunny94/temp | sympy/plotting/tests/test_plot_implicit.py | 17 | 2600 | import warnings
from sympy import (plot_implicit, cos, Symbol, Eq, sin, re, And, Or, exp, I,
tan, pi)
from sympy.plotting.plot import unset_show
from tempfile import NamedTemporaryFile
from sympy.utilities.pytest import skip
from sympy.external import import_module
#Set plots not to show
unset_show(... | bsd-3-clause |
animeshh/nuclei-analysis | hackrpi/plot_dbscan.py | 2 | 3735 | import numpy as np
from scipy.spatial import distance
from sklearn.cluster import DBSCAN
from sklearn import metrics
#from os import getcwd
##############################################################################
# Generate sample data
#centers = [[1, 1], [-1, -1], [1, -1]]
#X, labels_true = make_blobs(n_sampl... | mit |
mmottahedi/neuralnilm_prototype | scripts/e470.py | 2 | 7017 | 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,
Bidirectiona... | mit |
stefanhenneking/mxnet | example/bayesian-methods/bdk_demo.py | 45 | 15837 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
igsr/igsr_analysis | scripts/VCF/QC/generate_report.py | 1 | 6092 | import argparse
import glob
import re
import pdb
import os
import pandas as pd
import openpyxl
from tabulate import tabulate
def check_variantype(value):
if value !='snps' and value!='indels':
raise argparse.ArgumentTypeError("%s is an invalid variant type" % value)
return value
parser = argparse.Ar... | apache-2.0 |
superbobry/hyperopt-sklearn | hpsklearn/tests/test_estimator.py | 4 | 1604 |
try:
import unittest2 as unittest
except:
import unittest
import numpy as np
from hpsklearn.estimator import hyperopt_estimator
from hpsklearn import components
class TestIter(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.X = np.random.randn(1000, 2)
self.Y = (sel... | bsd-3-clause |
matthew-tucker/mne-python | examples/inverse/plot_label_source_activations.py | 32 | 2269 | """
====================================================
Extracting the time series of activations in a label
====================================================
We first apply a dSPM inverse operator to get signed activations
in a label (with positive and negative values) and we then
compare different strategies to ... | bsd-3-clause |
glennq/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 |
bzero/statsmodels | statsmodels/genmod/_prediction.py | 27 | 9437 | # -*- coding: utf-8 -*-
"""
Created on Fri Dec 19 11:29:18 2014
Author: Josef Perktold
License: BSD-3
"""
import numpy as np
from scipy import stats
# this is similar to ContrastResults after t_test, partially copied and adjusted
class PredictionResults(object):
def __init__(self, predicted_mean, var_pred_mean... | bsd-3-clause |
grevutiu-gabriel/sympy | examples/intermediate/mplot3d.py | 93 | 1252 | #!/usr/bin/env python
"""Matplotlib 3D plotting example
Demonstrates plotting with matplotlib.
"""
import sys
from sample import sample
from sympy import sin, Symbol
from sympy.external import import_module
def mplot3d(f, var1, var2, show=True):
"""
Plot a 3d function using matplotlib/Tk.
"""
im... | bsd-3-clause |
ssaeger/scikit-learn | sklearn/neighbors/classification.py | 132 | 14388 | """Nearest Neighbor Classification"""
# 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 support by ... | bsd-3-clause |
EnSpec/SpecDAL | specdal/gui/gui.py | 1 | 7156 | import os
import sys
import tkinter as tk
from tkinter import ttk
from tkinter import filedialog
import tkinter.simpledialog as tksd
sys.path.insert(0, os.path.abspath("../.."))
import matplotlib
matplotlib.use('TkAgg')
from specdal.spectrum import Spectrum
from specdal.collection import Collection
from viewer import V... | mit |
bsaleil/lc | tools/benchtime.py | 1 | 8755 | #!/usr/bin/python3
#---------------------------------------------------------------------------
#
# Copyright (c) 2015, Baptiste Saleil. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
# 1. ... | bsd-3-clause |
bgris/ODL_bgris | lib/python3.5/site-packages/IPython/lib/tests/test_latextools.py | 8 | 3869 | # encoding: utf-8
"""Tests for IPython.utils.path.py"""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
try:
from unittest.mock import patch
except ImportError:
from mock import patch
import nose.tools as nt
from IPython.lib import latextools
from IPython... | gpl-3.0 |
vaxin/captcha | line.py | 1 | 3107 | import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import random
import util
def _fpart(x):
return x - int(x)
def _rfpart(x):
return 1 - _fpart(x)
def getpixel(img, xy):
if xy[0] >= len(img) or xy[1] >= len(img[xy[0]]):
return (255., 255., 255.)
return img[xy[0]][xy[1]]
def p... | mit |
pythonvietnam/scikit-learn | examples/model_selection/plot_confusion_matrix.py | 244 | 2496 | """
================
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 |
jm-begon/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 |
Fireblend/scikit-learn | examples/preprocessing/plot_function_transformer.py | 161 | 1949 | """
=========================================================
Using FunctionTransformer to select columns
=========================================================
Shows how to use a function transformer in a pipeline. If you know your
dataset's first principle component is irrelevant for a classification task,
you ca... | bsd-3-clause |
xavierwu/scikit-learn | sklearn/linear_model/tests/test_sag.py | 93 | 25649 | # Authors: Danny Sullivan <dbsullivan23@gmail.com>
# Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
#
# Licence: BSD 3 clause
import math
import numpy as np
import scipy.sparse as sp
from sklearn.linear_model.sag import get_auto_step_size
from sklearn.linear_model.sag_fast import get_max_squared_sum
from skle... | bsd-3-clause |
leesavide/pythonista-docs | Documentation/matplotlib/users/plotting/examples/annotate_simple04.py | 6 | 1048 | import matplotlib.pyplot as plt
plt.figure(1, figsize=(3,3))
ax = plt.subplot(111)
ann = ax.annotate("Test",
xy=(0.2, 0.2), xycoords='data',
xytext=(0.8, 0.8), textcoords='data',
size=20, va="center", ha="center",
bbox=dict(boxstyle="round4", fc=... | apache-2.0 |
ahoyosid/scikit-learn | sklearn/neighbors/classification.py | 18 | 13871 | """Nearest Neighbor Classification"""
# 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 support by ... | bsd-3-clause |
YinongLong/scikit-learn | examples/mixture/plot_gmm.py | 122 | 3265 | """
=================================
Gaussian Mixture Model Ellipsoids
=================================
Plot the confidence ellipsoids of a mixture of two Gaussians
obtained with Expectation Maximisation (``GaussianMixture`` class) and
Variational Inference (``BayesianGaussianMixture`` class models with
a Dirichlet ... | bsd-3-clause |
Cignite/primdb | primdb_app/plot/massrange.py | 2 | 1421 | '''
Counting the number of precursor ion masses in a define range from the database data.
'''
import numpy.numarray as na
import matplotlib.pyplot as plt
import psycopg2
#establish connection with the postgres server with the given configuration
conn = psycopg2.connect(host="localhost",user="primuser",password... | agpl-3.0 |
CarlosA-Lopez/Proyecto_Embebidos_Grupo2 | plotly-1.2.9/plotly/matplotlylib/mplexporter/utils.py | 4 | 11384 | """
Utility Routines for Working with Matplotlib Objects
====================================================
"""
import itertools
import io
import base64
import numpy as np
import warnings
import matplotlib
from matplotlib.colors import colorConverter
from matplotlib.path import Path
from matplotlib.markers import ... | unlicense |
lucidfrontier45/scikit-learn | examples/cluster/plot_lena_segmentation.py | 2 | 2410 | """
=========================================
Segmenting the picture of Lena in regions
=========================================
This example uses :ref:`spectral_clustering` on a graph created from
voxel-to-voxel difference on an image to break this image into multiple
partly-homogenous regions.
This procedure (spec... | bsd-3-clause |
shenzebang/scikit-learn | examples/linear_model/plot_omp.py | 385 | 2263 | """
===========================
Orthogonal Matching Pursuit
===========================
Using orthogonal matching pursuit for recovering a sparse signal from a noisy
measurement encoded with a dictionary
"""
print(__doc__)
import matplotlib.pyplot as plt
import numpy as np
from sklearn.linear_model import OrthogonalM... | bsd-3-clause |
potash/scikit-learn | sklearn/ensemble/tests/test_gradient_boosting.py | 43 | 39945 | """
Testing for the gradient boosting module (sklearn.ensemble.gradient_boosting).
"""
import warnings
import numpy as np
from itertools import product
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import coo_matrix
from sklearn import datasets
from sklearn.base import clo... | bsd-3-clause |
rohanp/scikit-learn | sklearn/metrics/cluster/unsupervised.py | 230 | 8281 | """ Unsupervised evaluation metrics. """
# Authors: Robert Layton <robertlayton@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ...utils import check_random_state
from ..pairwise import pairwise_distances
def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random... | bsd-3-clause |
yanlend/scikit-learn | setup.py | 76 | 9370 | #! /usr/bin/env python
#
# Copyright (C) 2007-2009 Cournapeau David <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# License: 3-clause BSD
descr = """A set of python modules for machine learning and data mining"""
import sys
import os
import shutil
from distutils.command.clean ... | bsd-3-clause |
aswolf/xmeos | xmeos/test/test_models_composite.py | 1 | 40896 | import numpy as np
import xmeos
from xmeos import models
from xmeos.models import core
import pytest
import matplotlib.pyplot as plt
import matplotlib as mpl
from abc import ABCMeta, abstractmethod
import copy
import test_models
#====================================================================
# Define "slow" te... | mit |
ageron/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py | 39 | 32726 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
rahulremanan/python_tutorial | NLP/00-Multivariate_LSTM/src/binary_classification.py | 1 | 12229 | '''
Created on 06 lug 2017
@author: mantica
https://github.com/Azure/lstms_for_predictive_maintenance/blob/master/Deep%20Learning%20Basics%20for%20Predictive%20Maintenance.ipynb
https://ti.arc.nasa.gov/tech/dash/pcoe/prognostic-data-repository/#turbofan
Binary classification: Predict if an asset will fail within cer... | mit |
henrykironde/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 |
perimosocordiae/scipy | doc/source/tutorial/stats/plots/kde_plot3.py | 12 | 1249 | import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
rng = np.random.default_rng()
x1 = rng.normal(size=200) # random data, normal distribution
xs = np.linspace(x1.min()-1, x1.max()+1, 200)
kde1 = stats.gaussian_kde(x1)
kde2 = stats.gaussian_kde(x1, bw_method='silverman')
fig = plt.figure(fig... | bsd-3-clause |
jdrudolph/scikit-bio | skbio/stats/distance/_bioenv.py | 12 | 9577 | # ----------------------------------------------------------------------------
# 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 |
mjgrav2001/scikit-learn | setup.py | 143 | 7364 | #! /usr/bin/env python
#
# Copyright (C) 2007-2009 Cournapeau David <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# License: 3-clause BSD
descr = """A set of python modules for machine learning and data mining"""
import sys
import os
import shutil
from distutils.command.clean ... | 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 |
tafdata/cardinal | app/organizer/jyoriku.py | 1 | 3647 | import numpy as np
import mojimoji
import pandas as pd
from django.db.models.aggregates import Count
from django.db.models import Max
from django.core.exceptions import ObjectDoesNotExist
# Models
from competitions.models import Comp, Event, EventStatus, GR as GRecord
from organizer.models import Entry
from organizer... | mit |
jzt5132/scikit-learn | examples/svm/plot_separating_hyperplane.py | 294 | 1273 | """
=========================================
SVM: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a Support Vector Machine classifier with
linear kernel.
"""
print(__doc__)
import numpy as np
impor... | bsd-3-clause |
timqian/sms-tools | lectures/8-Sound-transformations/plots-code/hps-morph-total.py | 24 | 3956 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import get_window
import sys, os
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/transformations/'))
i... | agpl-3.0 |
SuperDARNCanada/placeholderOS | tools/testing_utils/filter_testing/filter_rawrf.py | 2 | 1174 | #
# Filter written rawrf data using remai filter.
#
# Then beamform and produce output_samples_iq
import json
import matplotlib
from scipy.fftpack import fft
import math
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
import sys
import collections
import os
import deepdish
import argparse
im... | gpl-3.0 |
wazeerzulfikar/scikit-learn | examples/model_selection/plot_roc.py | 102 | 5056 | """
=======================================
Receiver Operating Characteristic (ROC)
=======================================
Example of Receiver Operating Characteristic (ROC) metric to evaluate
classifier output quality.
ROC curves typically feature true positive rate on the Y axis, and false
positive rate on the X a... | bsd-3-clause |
FordyceLab/AcqPack | acqpack/autosampler.py | 1 | 5202 | import numpy as np
import pandas as pd
import utils as ut
class Autosampler:
"""
A high-level wrapper that coordinates XY and Z axes to create an autosampler.
Incorporates a deck.
"""
def __init__(self, z, xy):
# TODO: ditch frames; just have position_tables, each of which stores should t... | mit |
mantidproject/mantid | scripts/SCD_Reduction/SCDCalibratePanels2PanelDiagnostics.py | 3 | 15813 | #!/usr/bin/env python
# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identi... | gpl-3.0 |
andrewnc/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
lazywei/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 |
yyjiang/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 |
TimBizeps/BachelorAP | V504_Thermische Elektronenemission/auswertung3.py | 1 | 1423 | import matplotlib as mpl
mpl.use('pgf')
import numpy as np
import scipy.constants as const
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from uncertainties import ufloat
import uncertainties.unumpy as unp
from uncertainties.unumpy import (nominal_values as noms, std_devs as stds)
mpl.rcParams.upd... | gpl-3.0 |
SeyVu/subscription_renewal | support_functions.py | 1 | 2424 | #########################################################################################################
# Description: Collection of support functions that'll be used often
#
#########################################################################################################
import numpy as np
import pandas as ... | mit |
adbroido/LRTanalysis | code/sortgmls.py | 2 | 3782 | import numpy as np
import igraph
import glob
import os
import pickle
import pandas as pd
""" Assorted functions to check whether a graph (as an igraph object) has
certain properties. All are meant to be called directly.
"""
# filepath to error file
errorfp = 'gmlerror.txt'
def weighted(g, fp=''):
""" Check whe... | gpl-3.0 |
InstaSketch/image-picker | imagePicker/image_query/management/commands/query.py | 1 | 2326 | import os
import io
import cProfile
import cv2
import requests
import pstats
import numpy as np
from matplotlib import pyplot as plt
from django.core.management.base import BaseCommand, CommandError
from image_api.imageloader import Imageloader
from image_query import query
class Command(BaseCommand):
help = 'Que... | apache-2.0 |
xyguo/scikit-learn | sklearn/svm/tests/test_bounds.py | 280 | 2541 | import nose
from nose.tools import assert_equal, assert_true
from sklearn.utils.testing import clean_warning_registry
import warnings
import numpy as np
from scipy import sparse as sp
from sklearn.svm.bounds import l1_min_c
from sklearn.svm import LinearSVC
from sklearn.linear_model.logistic import LogisticRegression... | bsd-3-clause |
YinongLong/scikit-learn | examples/calibration/plot_compare_calibration.py | 82 | 5012 | """
========================================
Comparison of Calibration of Classifiers
========================================
Well calibrated classifiers are probabilistic classifiers for which the output
of the predict_proba method can be directly interpreted as a confidence level.
For instance a well calibrated (bi... | bsd-3-clause |
OpringaoDoTurno/airflow | tests/operators/hive_operator.py | 40 | 14061 | # -*- coding: utf-8 -*-
#
# 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, software
... | apache-2.0 |
depet/scikit-learn | examples/svm/plot_rbf_parameters.py | 6 | 4080 | '''
==================
RBF SVM parameters
==================
This example illustrates the effect of the parameters `gamma`
and `C` of the rbf kernel SVM.
Intuitively, the `gamma` parameter defines how far the influence
of a single training example reaches, with low values meaning 'far'
and high values meaning 'close'... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/pandas/tests/scalar/test_interval.py | 7 | 3606 | from __future__ import division
import pytest
from pandas import Interval
import pandas.util.testing as tm
class TestInterval(object):
def setup_method(self, method):
self.interval = Interval(0, 1)
def test_properties(self):
assert self.interval.closed == 'right'
assert self.interval... | mit |
amiremadmarvasti/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 |
kristoforcarlson/nest-simulator-fork | pynest/examples/intrinsic_currents_subthreshold.py | 9 | 7172 | # -*- coding: utf-8 -*-
#
# intrinsic_currents_subthreshold.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 ... | gpl-2.0 |
konstantint/matplotlib-venn | tests/region_test.py | 1 | 4302 | '''
Venn diagram plotting routines.
Test module (meant to be used via py.test).
Tests of the classes and methods in _regions.py
Copyright 2014, Konstantin Tretyakov.
http://kt.era.ee/
Licensed under MIT license.
'''
import pytest
import os
import numpy as np
from tests.utils import exec_ipynb
from matplotlib_venn._r... | mit |
huzq/scikit-learn | examples/preprocessing/plot_scaling_importance.py | 34 | 5381 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Importance of Feature Scaling
=========================================================
Feature scaling through standardization (or Z-score normalization)
can be an important preprocessing step for many machine lear... | bsd-3-clause |
bartslinger/paparazzi | sw/misc/attitude_reference/pat/utils.py | 42 | 6283 | #
# Copyright 2013-2014 Antoine Drouin (poinix@gmail.com)
#
# This file is part of PAT.
#
# PAT 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-2.0 |
ashhher3/scikit-learn | sklearn/tree/tests/test_tree.py | 9 | 46546 | """
Testing for the tree module (sklearn.tree).
"""
import pickle
from functools import partial
from itertools import product
import platform
import numpy as np
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from sklearn.random_projection import sparse_rand... | bsd-3-clause |
Pybonacci/bezierbuilder | bezierbuilder.py | 1 | 6844 | # BézierBuilder
#
# Copyright (c) 2013, Juan Luis Cano Rodríguez <juanlu001@gmail.com>
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification,
# are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above... | bsd-2-clause |
billy-inn/scikit-learn | sklearn/cluster/tests/test_spectral.py | 262 | 7954 | """Testing for Spectral Clustering methods"""
from sklearn.externals.six.moves import cPickle
dumps, loads = cPickle.dumps, cPickle.loads
import numpy as np
from scipy import sparse
from sklearn.utils import check_random_state
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
aolindahl/streaking | area_fill.py | 1 | 3843 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 29 08:55:06 2015
@author: antlin
"""
import numpy as np
import process_hdf5
import matplotlib.pyplot as plt
def zero_crossing_area(y):
# Find zero crossings around peak
i_max = np.argmax(y)
i_end = i_max + np.argmax(y[i_max:] < 0)
i_start = i_max - np.... | gpl-2.0 |
jrh154/ChibbarGroup | Phylogeny Scripts/sequence_combiner.py | 2 | 1372 | '''
Combines fasta files based on a list of accession numbers with formated headers
Usage:
python sequence_combiner.py file_info.csv fasta_directory out_directory
'''
from os import listdir, remove
from os.path import join, isfile
import pandas as pd
import sys
def File_Reader(file_info):
data_dict = {}
df = pd.... | mit |
gef756/seaborn | seaborn/timeseries.py | 8 | 15217 | """Timeseries plotting functions."""
from __future__ import division
import numpy as np
import pandas as pd
from scipy import stats, interpolate
import matplotlib as mpl
import matplotlib.pyplot as plt
from .external.six import string_types
from . import utils
from . import algorithms as algo
from .palettes import c... | bsd-3-clause |
shuggiefisher/brain4k | brain4k/transforms/b4k/__init__.py | 2 | 3461 | import logging
import itertools
from copy import deepcopy
import pandas as pd
from brain4k.transforms import PipelineStage
class DataJoin(PipelineStage):
"""
Perform a left join across two datasources.
Useful in case one stage of the pipeline depends upon results generated
at a prior stage, and the... | apache-2.0 |
appapantula/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 |
SciTools/cartopy | lib/cartopy/tests/mpl/test_web_services.py | 2 | 1691 | # Copyright Cartopy Contributors
#
# This file is part of Cartopy and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import cleanup
import pytest
from cartopy.tests.mpl ... | lgpl-3.0 |
jkarnows/scikit-learn | examples/ensemble/plot_voting_decision_regions.py | 230 | 2386 | """
==================================================
Plot the decision boundaries of a VotingClassifier
==================================================
Plot the decision boundaries of a `VotingClassifier` for
two features of the Iris dataset.
Plot the class probabilities of the first sample in a toy dataset
pred... | bsd-3-clause |
kambysese/mne-python | tutorials/source-modeling/plot_beamformer_lcmv.py | 10 | 12809 | """
Source reconstruction using an LCMV beamformer
==============================================
This tutorial gives an overview of the beamformer method
and shows how to reconstruct source activity using an LCMV beamformer.
"""
# Authors: Britta Westner <britta.wstnr@gmail.com>
# Eric Larson <larson.eric.d@... | bsd-3-clause |
uvchik/pvlib-python | pvlib/test/test_forecast.py | 1 | 4065 | from datetime import datetime, timedelta
import inspect
from math import isnan
from pytz import timezone
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_allclose
from conftest import requires_siphon, has_siphon, skip_windows
pytestmark = pytest.mark.skipif(not has_siphon, reaso... | bsd-3-clause |
pystockhub/book | ch14/03.py | 1 | 1207 | import pandas_datareader.data as web
import datetime
import matplotlib.pyplot as plt
from zipline.api import order_target, record, symbol
from zipline.algorithm import TradingAlgorithm
start = datetime.datetime(2010, 1, 1)
end = datetime.datetime(2016, 3, 29)
data = web.DataReader("AAPL", "yahoo", start, end)
#plt.pl... | mit |
mhue/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 75 | 34122 | 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 |
minglong-cse2016/stupidlang | docs/conf.py | 1 | 8724 | # -*- coding: utf-8 -*-
#
# 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.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys
# ... | mit |
jimsrc/seatos | etc/n_CR/individual/check_pos.py | 1 | 2610 | #!/usr/bin/env ipython
from pylab import *
#from load_data import sh, mc, cr
import func_data as fd
import share.funcs as ff
#import CythonSrc.funcs as ff
import matplotlib.patches as patches
import matplotlib.transforms as transforms
from os import environ as env
from os.path import isfile, isdir
from h5py import File... | mit |
webmasterraj/FogOrNot | flask/lib/python2.7/site-packages/pandas/tseries/index.py | 2 | 71968 | # pylint: disable=E1101
import operator
from datetime import time, datetime
from datetime import timedelta
import numpy as np
import warnings
from pandas.core.common import (_NS_DTYPE, _INT64_DTYPE,
_values_from_object, _maybe_box,
ABCSeries, is_intege... | gpl-2.0 |
pprett/scikit-learn | sklearn/gaussian_process/tests/test_gaussian_process.py | 46 | 7057 | """
Testing for Gaussian Process module (sklearn.gaussian_process)
"""
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# License: BSD 3 clause
import numpy as np
from sklearn.gaussian_process import GaussianProcess
from sklearn.gaussian_process import regression_models as regression
from sklearn.gaussian_proce... | bsd-3-clause |
neale/CS-program | 534-MachineLearning2/decision_tree/decision_tree.py | 1 | 5371 | import os
import sys
import operator
import itertools
import matplotlib.pyplot as plt
import numpy as np
import collections
verbose = False
def import_data():
with open('iris_test-1.csv', 'rb') as f:
X = f.readlines()
for i, l in enumerate(X):
X[i] = X[i].strip('\r\n').split(';')
... | unlicense |
MMTObservatory/mmtwfs | mmtwfs/wfs.py | 1 | 72281 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
# coding=utf-8
"""
Classes and utilities for operating the wavefront sensors of the MMTO and analyzing the data they produce
"""
import warnings
import pathlib
import numpy as np
import photutils
import matplotlib.pyplot as plt
import matplotlib.cm as... | bsd-3-clause |
drammock/mne-python | tutorials/preprocessing/70_fnirs_processing.py | 5 | 14145 | """
.. _tut-fnirs-processing:
Preprocessing functional near-infrared spectroscopy (fNIRS) data
================================================================
This tutorial covers how to convert functional near-infrared spectroscopy
(fNIRS) data from raw measurements to relative oxyhaemoglobin (HbO) and
deoxyhaemogl... | bsd-3-clause |
apache/incubator-airflow | tests/providers/amazon/aws/transfers/test_hive_to_dynamodb.py | 7 | 4590 | #
# 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... | apache-2.0 |
boland1992/seissuite_iran | build/lib/seissuite/ant/pscrosscorr.py | 1 | 151866 | #!/usr/bin/env python
"""
Module that contains classes holding cross-correlations and related
processing, such as frequency-time analysis (FTAN) to measure
dispersion curves.
"""
from seissuite.ant import pserrors, psutils, pstomo
import obspy.signal
try:
import obspy.io.xseed
except:
import obspy.xseed
... | gpl-3.0 |
UDST/urbansim | urbansim/utils/sampling.py | 4 | 7852 | import math
import numpy as np
import pandas as pd
def get_probs(data, prob_column=None):
"""
Checks for presence of a probability column and returns the result
as a numpy array. If the probabilities are weights (i.e. they don't
sum to 1), then this will be recalculated.
Parameters
----------... | bsd-3-clause |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.