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 |
|---|---|---|---|---|---|
youprofit/shogun | examples/undocumented/python_modular/graphical/so_multiclass_BMRM.py | 16 | 2853 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from modshogun import RealFeatures
from modshogun import MulticlassModel, MulticlassSOLabels, RealNumber, DualLibQPBMSOSVM
from modshogun import BMRM, PPBMRM, P3BMRM
from modshogun import StructuredAccuracy
def fill_data(cnt, minv, maxv):
x1 =... | gpl-3.0 |
arokem/scipy | doc/source/tutorial/stats/plots/kde_plot3.py | 132 | 1229 | import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
np.random.seed(12456)
x1 = np.random.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(figsi... | bsd-3-clause |
ywcui1990/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/cm.py | 70 | 5385 | """
This module contains the instantiations of color mapping classes
"""
import numpy as np
from numpy import ma
import matplotlib as mpl
import matplotlib.colors as colors
import matplotlib.cbook as cbook
from matplotlib._cm import *
def get_cmap(name=None, lut=None):
"""
Get a colormap instance, defaultin... | agpl-3.0 |
lfairchild/PmagPy | pmagpy/ipmag.py | 1 | 476806 | # /usr/bin/env/pythonw
from past.utils import old_div
import codecs
import copy
import numpy as np
import pandas as pd
from scipy import stats
import random
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from matplotlib.pylab import polyfit
import matplotlib.ticker as mtick
import os
import sys... | bsd-3-clause |
henry0312/LightGBM | examples/python-guide/dask/prediction.py | 2 | 1325 | import dask.array as da
from distributed import Client, LocalCluster
from sklearn.datasets import make_regression
from sklearn.metrics import mean_squared_error
import lightgbm as lgb
if __name__ == "__main__":
print("loading data")
X, y = make_regression(n_samples=1000, n_features=50)
print("initializi... | mit |
jonyroda97/redbot-amigosprovaveis | lib/matplotlib/tests/test_rcparams.py | 2 | 18156 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import io
import os
import warnings
from collections import OrderedDict
from cycler import cycler, Cycler
import pytest
try:
from unittest import mock
except ImportError:
import mock
impor... | gpl-3.0 |
jseabold/scikit-learn | sklearn/tree/tree.py | 23 | 40423 | """
This module gathers tree-based methods, including decision, regression and
randomized trees. Single and multi-output problems are both handled.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Da... | bsd-3-clause |
dkriegner/xrayutilities | examples/xrayutilities_experiment_Powder_example_Iron.py | 1 | 2057 | # This file is part of xrayutilities.
#
# xrayutilities 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 later version.
#
# This program is distributed... | gpl-2.0 |
kjung/scikit-learn | sklearn/svm/tests/test_sparse.py | 35 | 13182 | from nose.tools import assert_raises, assert_true, assert_false
import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from sklearn import datasets, svm, linear_model, base
from sklearn.datasets import make_classif... | bsd-3-clause |
Lab603/PicEncyclopedias | jni-build/jni/include/tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py | 8 | 21806 | # 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 |
BigDataforYou/movie_recommendation_workshop_1 | big_data_4_you_demo_1/venv/lib/python2.7/site-packages/pandas/tests/test_util.py | 1 | 11190 | # -*- coding: utf-8 -*-
import nose
from collections import OrderedDict
from pandas.util._move import move_into_mutable_buffer, BadMove
from pandas.util.decorators import deprecate_kwarg
from pandas.util.validators import (validate_args, validate_kwargs,
validate_args_and_kwargs)
i... | mit |
cswiercz/sympy | sympy/interactive/printing.py | 31 | 15830 | """Tools for setting up printing in interactive sessions. """
from __future__ import print_function, division
import sys
from distutils.version import LooseVersion as V
from io import BytesIO
from sympy import latex as default_latex
from sympy import preview
from sympy.core.compatibility import integer_types
from sy... | bsd-3-clause |
lvniqi/tianchi_power | code/preprocess.py | 1 | 32964 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sat May 13 17:36:18 2017
@author: boweiy
"""
from sklearn.model_selection import train_test_split
import pandas as pd
import numpy as np
import os
import xgboost as xgb
from multiprocessing import Pool as m_Pool
from sklearn import preprocessing
from sklea... | mit |
yunfeilu/scikit-learn | doc/tutorial/text_analytics/skeletons/exercise_01_language_train_model.py | 254 | 2005 | """Build a language detector model
The goal of this exercise is to train a linear classifier on text features
that represent sequences of up to 3 consecutive characters so as to be
recognize natural languages by using the frequencies of short character
sequences as 'fingerprints'.
"""
# Author: Olivier Grisel <olivie... | bsd-3-clause |
synergetics/spectrum | src/conventional/cumest.py | 1 | 2697 | #!/usr/bin/env python
from __future__ import division
import numpy as np
from scipy.linalg import hankel
import scipy.io as sio
import matplotlib.pyplot as plt
from ..tools import *
from cum2est import *
from cum3est import *
from cum4est import *
def cumest(y, norder=2, maxlag=0 ,nsamp=None, overlap=0, flag='biase... | mit |
rvraghav93/scikit-learn | sklearn/linear_model/omp.py | 3 | 31718 | """Orthogonal matching pursuit algorithms
"""
# Author: Vlad Niculae
#
# License: BSD 3 clause
import warnings
import numpy as np
from scipy import linalg
from scipy.linalg.lapack import get_lapack_funcs
from .base import LinearModel, _pre_fit
from ..base import RegressorMixin
from ..utils import as_float_array, ch... | bsd-3-clause |
synthicity/urbansim | urbansim/urbanchoice/tests/test_interaction.py | 3 | 1744 | import numpy as np
import numpy.testing as npt
import pandas as pd
import pytest
from .. import interaction as inter
@pytest.fixture
def choosers():
return pd.DataFrame(
{'var1': range(5, 10),
'thing_id': ['a', 'c', 'e', 'g', 'i']})
@pytest.fixture
def alternatives():
return pd.DataFrame(
... | bsd-3-clause |
Keleir/glances | glances/core/glances_main.py | 11 | 15502 | # -*- coding: utf-8 -*-
#
# This file is part of Glances.
#
# Copyright (C) 2015 Nicolargo <nicolas@nicolargo.com>
#
# Glances is free software; you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the Lic... | lgpl-3.0 |
IBT-FMI/SAMRI | samri/pipelines/extra_functions.py | 1 | 36883 | # -*- coding: utf-8 -*-
import csv
import inspect
import os
import re
import json
import shutil
from copy import deepcopy
import pandas as pd
# PyBIDS 0.6.5 and 0.10.2 compatibility
try:
from bids.grabbids import BIDSLayout
except ModuleNotFoundError:
from bids.layout import BIDSLayout
BEST_GUESS_MODALITY_MATCH = ... | gpl-3.0 |
jreback/pandas | pandas/tests/util/test_doc.py | 8 | 1492 | from textwrap import dedent
from pandas.util._decorators import doc
@doc(method="cumsum", operation="sum")
def cumsum(whatever):
"""
This is the {method} method.
It computes the cumulative {operation}.
"""
@doc(
cumsum,
dedent(
"""
Examples
--------
>>> cum... | bsd-3-clause |
trungnt13/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 |
drivendataorg/metrics | metrics.py | 1 | 10482 | import editdistance
import numpy as np
from sklearn.metrics import roc_auc_score, r2_score
# Defined for your convenience; these are the
# class_column_indices for the Box-Plots for Education competition
# www.drivendata.org/competitions/4/
BOX_PLOTS_COLUMN_INDICES = [range(37),
range(37, 4... | mit |
gclenaghan/scikit-learn | sklearn/base.py | 22 | 18131 | """Base classes for all estimators."""
# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
import copy
import warnings
import numpy as np
from scipy import sparse
from .externals import six
from .utils.fixes import signature
from .utils.deprecation import deprecated
from .exceptions impor... | bsd-3-clause |
neurospin/pylearn-epac | epac/sklearn_plugins/estimators.py | 1 | 11147 | """
Estimator wrap ML procedure into EPAC Node. To be EPAC compatible, one should
inherit from BaseNode and implement the "transform" method.
InternalEstimator and LeafEstimator aim to provide automatic wrapper to objects
that implement fit and predict methods.
@author: edouard.duchesnay@cea.fr
@author: jinpeng.li@ce... | bsd-3-clause |
datapythonista/pandas | pandas/tests/scalar/timedelta/test_arithmetic.py | 2 | 33869 | """
Tests for scalar Timedelta arithmetic ops
"""
from datetime import (
datetime,
timedelta,
)
import operator
import numpy as np
import pytest
from pandas.compat import is_numpy_dev
from pandas.errors import OutOfBoundsTimedelta
import pandas as pd
from pandas import (
NaT,
Timedelta,
Timestamp... | bsd-3-clause |
SpatialMetabolomics/SM_distributed | sm/engine/fdr.py | 2 | 4132 | import logging
import numpy as np
import pandas as pd
logger = logging.getLogger('engine')
DECOY_ADDUCTS = ['+He', '+Li', '+Be', '+B', '+C', '+N', '+O', '+F', '+Ne', '+Mg', '+Al', '+Si', '+P', '+S', '+Cl', '+Ar', '+Ca', '+Sc', '+Ti', '+V', '+Cr', '+Mn', '+Fe', '+Co', '+Ni', '+Cu', '+Zn', '+Ga', '+Ge', '+As', '+Se', ... | apache-2.0 |
rfablet/PB_ANDA | AnDA_Multiscale_Assimilation.py | 1 | 11561 | import numpy as np
from pyflann import *
from sklearn.decomposition import PCA
from AnDA_analog_forecasting import AnDA_analog_forecasting as AnDA_AF
from AnDA_data_assimilation import AnDA_data_assimilation
from AnDA_variables import General_AF, AnDA_result
from AnDA_stat_functions import AnDA_RMSE, AnDA_correla... | gpl-3.0 |
MAKOMO/artisan | src/setup-win.py | 2 | 7374 | """
This is a set up script for py2exe
USAGE: python setup-win py2exe
"""
from distutils.core import setup
import matplotlib as mpl
import py2exe
import numpy
import os
import sys
# add any numpy directory containing a dll file to sys.path
def numpy_dll_paths_fix():
paths = set()
np_path ... | gpl-3.0 |
VisTrails/vistrails-contrib-legacy | NumSciPy/ArrayPlot.py | 6 | 24193 | import core.modules
import core.modules.module_registry
from core.modules.vistrails_module import Module, ModuleError
from core.modules.basic_modules import PythonSource
from Array import *
from Matrix import *
import pylab
import matplotlib
import urllib
import random
class ArrayPlot(object):
namespace = 'numpy|... | bsd-3-clause |
jmargeta/scikit-learn | sklearn/svm/classes.py | 2 | 26517 | from .base import BaseLibLinear, BaseSVC, BaseLibSVM
from ..base import RegressorMixin
from ..linear_model.base import LinearClassifierMixin, SparseCoefMixin
from ..feature_selection.selector_mixin import SelectorMixin
class LinearSVC(BaseLibLinear, LinearClassifierMixin, SelectorMixin,
SparseCoefMixi... | bsd-3-clause |
bthirion/scikit-learn | examples/ensemble/plot_ensemble_oob.py | 58 | 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 |
HyperloopTeam/FullOpenMDAO | lib/python2.7/site-packages/matplotlib/backends/backend_template.py | 20 | 9358 | """
This is a fully functional do nothing backend to provide a template to
backend writers. It is fully functional in that you can select it as
a backend with
import matplotlib
matplotlib.use('Template')
and your matplotlib scripts will (should!) run without error, though
no output is produced. This provides a ... | gpl-2.0 |
ndingwall/scikit-learn | examples/ensemble/plot_adaboost_twoclass.py | 72 | 3333 | """
==================
Two-class AdaBoost
==================
This example fits an AdaBoosted decision stump on a non-linearly separable
classification dataset composed of two "Gaussian quantiles" clusters
(see :func:`sklearn.datasets.make_gaussian_quantiles`) and plots the decision
boundary and decision scores. The di... | bsd-3-clause |
sarahgrogan/scikit-learn | sklearn/linear_model/passive_aggressive.py | 97 | 10879 | # Authors: Rob Zinkov, Mathieu Blondel
# License: BSD 3 clause
from .stochastic_gradient import BaseSGDClassifier
from .stochastic_gradient import BaseSGDRegressor
from .stochastic_gradient import DEFAULT_EPSILON
class PassiveAggressiveClassifier(BaseSGDClassifier):
"""Passive Aggressive Classifier
Read mor... | bsd-3-clause |
MattNolanLab/ei-attractor | grid_cell_model/plotting/connections.py | 1 | 2559 | '''Functions/methods to plot connectivity matrices.
.. currentmodule:: grid_cell_model.plotting.connections
Classes / Functions
-------------------
.. autosummary::
plotConnHistogram
plot2DWeightMatrix
'''
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ti
from global_defs im... | gpl-3.0 |
marcelovilaca/DIRAC | Core/Utilities/Graphs/PlotBase.py | 10 | 9309 | ########################################################################
# $HeadURL$
########################################################################
""" PlotBase is a base class for various Graphs plots
The DIRAC Graphs package is derived from the GraphTool plotting package of the
CMS/Phedex Proj... | gpl-3.0 |
jarrison/trEFM-learn | trEFMlearn/process_image.py | 1 | 2175 | import numpy as np
import util
from sklearn import preprocessing
from pandas import read_csv
def analyze_image(path, reg_object):
"""
This function analyzes data from a trEFM image that has been pre-processed
and placed in a folder. The path must be given, as well as a previously fit
SVR model to be us... | mit |
kashif/scikit-learn | examples/exercises/plot_iris_exercise.py | 323 | 1602 | """
================================
SVM Exercise
================================
A tutorial exercise for using different SVM kernels.
This exercise is used in the :ref:`using_kernels_tut` part of the
:ref:`supervised_learning_tut` section of the :ref:`stat_learn_tut_index`.
"""
print(__doc__)
import numpy as np
i... | bsd-3-clause |
dsavoiu/kafe2 | examples/007_cost_functions/01_poisson_cost_function.py | 1 | 5063 | #!/usr/bin/env python
"""
kafe2 example: Poisson cost function
====================================
In data analysis the uncertainty on measurement data is most often assumed to resemble a normal distribution.
For many use cases this assumption works reasonably well but there is a problem: to get meaningful fit result... | gpl-3.0 |
ua-snap/downscale | snap_scripts/baseline_climatologies/calc_ra_monthly_L48.py | 1 | 4827 | # # # # # # # # # # # # # # # # # # # # # # # #
# PORT S.McAffee's Ra SCRIPT TO Python
# # # # # # # # # # # # # # # # # # # # # # # #
def coordinates( fn=None, meta=None, numpy_array=None, input_crs=None, to_latlong=False ):
'''
take a raster file as input and return the centroid coords for each
of the grid cells... | mit |
lgbouma/astrobase | astrobase/checkplot/pkl_utils.py | 1 | 76493 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# pkl_utils.py - Waqas Bhatti (wbhatti@astro.princeton.edu) - Feb 2019
# License: MIT.
'''
This contains utility functions that support checkplot.pkl public functions.
'''
#############
## LOGGING ##
#############
import logging
from astrobase import log_sub, log_fmt, l... | mit |
tomazberisa/custom_db | validate_bootstrap.py | 1 | 3561 | #!/usr/bin/env python3
import commanderline.commander_line as cl
import pandas as pd
import gzip
ancestry_translation = { "ARABIAN" : "NEAREAST",
"ASHKENAZI" : "ASHKENAZI-EMED",
"BALOCHI-MAKRANI-BRAHUI" : "CASIA",
"BANTUKENYA" : "EAFRICA",
... | mit |
daler/Pharmacogenomics_Prediction_Pipeline_P3 | tools/pipeline_helpers.py | 4 | 7419 | import os
import yaml
import numpy as np
import pandas as pd
import string
def sanitize(s):
"""
Replace special characters with underscore
"""
valid = "-_.()" + string.ascii_letters + string.digits
return ''.join(i if i in valid else "_" for i in s)
def index_converter(df, label):
"""
San... | cc0-1.0 |
elingg/tensorflow | tensorflow/contrib/factorization/python/ops/gmm.py | 11 | 12252 | # 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 |
ningchi/scikit-learn | examples/feature_selection/plot_feature_selection.py | 249 | 2827 | """
===============================
Univariate Feature Selection
===============================
An example showing univariate feature selection.
Noisy (non informative) features are added to the iris data and
univariate feature selection is applied. For each feature, we plot the
p-values for the univariate feature s... | bsd-3-clause |
altaetran/bayesianoracle | tests/quadraticBayesianAveraging/paper_examples/StatisticalQuadraticModels1D.py | 1 | 9162 | import numpy as np
import bayesianoracle as bo
import bayesianoracle.plot as boplotter
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib import colors as cl
from matplotlib import gridspec, ticker
# Import function information
from function_data import *
execfile("func... | apache-2.0 |
JosmanPS/scikit-learn | sklearn/datasets/mldata.py | 309 | 7838 | """Automatically download MLdata datasets."""
# Copyright (c) 2011 Pietro Berkes
# License: BSD 3 clause
import os
from os.path import join, exists
import re
import numbers
try:
# Python 2
from urllib2 import HTTPError
from urllib2 import quote
from urllib2 import urlopen
except ImportError:
# Pyt... | bsd-3-clause |
kagayakidan/scikit-learn | sklearn/decomposition/tests/test_nmf.py | 130 | 6059 | import numpy as np
from scipy import linalg
from sklearn.decomposition import nmf
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import raises
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_gr... | bsd-3-clause |
liyu1990/sklearn | sklearn/manifold/tests/test_mds.py | 324 | 1862 | import numpy as np
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_raises
from sklearn.manifold import mds
def test_smacof():
# test metric smacof using the data of "Modern Multidimensional Scaling",
# Borg & Groenen, p 154
sim = np.array([[0, 5, 3, 4],
... | bsd-3-clause |
boscotsang/BayesDigitClassify | classify_gf2.py | 1 | 4586 | import numpy
from sklearn.metrics import confusion_matrix
def load_data():
train_labels = []
with open('digitdata/traininglabels', 'rb') as f:
for i, line in enumerate(f):
train_labels.append(int(line))
train_labels = numpy.array(train_labels, dtype=int)
train_x = numpy.zeros((trai... | mit |
pllim/ginga | ginga/examples/matplotlib/example2_mpl.py | 3 | 10002 | #! /usr/bin/env python
#
# example2_mpl.py -- Simple, configurable FITS viewer using a matplotlib
# QtAgg backend for Ginga and embedded in a Qt program.
#
# This is open-source software licensed under a BSD license.
# Please see the file LICENSE.txt for details.
#
"""
Usage:
example2_mpl.py [fi... | bsd-3-clause |
iamaris/anaMini | hist.py | 7 | 1039 | """
Demo of the histogram (hist) function with a few features.
In addition to the basic histogram, this demo shows a few optional features:
* Setting the number of data bins
* The ``normed`` flag, which normalizes bin heights so that the integral of
the histogram is 1. The resulting histogram is a proba... | mit |
madjelan/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 |
MTG/essentia | test/src/QA/clipping/test_clipping.py | 1 | 10356 | #!/usr/bin/env python
# Copyright (C) 2006-2021 Music Technology Group - Universitat Pompeu Fabra
#
# This file is part of Essentia
#
# Essentia 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 (FSF), e... | agpl-3.0 |
ueshin/apache-spark | python/pyspark/pandas/categorical.py | 15 | 5290 | #
# 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 us... | apache-2.0 |
kaleoyster/ProjectNBI | nbi-utilities/data_gen/decisionFlowChart/validation.py | 1 | 14013 | """
description: Validation of the decision tree outputs
"""
import csv
import os
from sklearn.metrics import confusion_matrix, classification_report
from collections import namedtuple
from collections import defaultdict
from collections import Counter
__author__ = 'Akshay Kale'
__copyright__ = 'GPL'
# Year: 2019 ( ... | gpl-2.0 |
oaelhara/numbbo | code-postprocessing/bbob_pproc/ppfigparam.py | 1 | 9900 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""Generate ERT vs param. figures.
The figures will show the performance in terms of ERT on a log scale
w.r.t. parameter. On the y-axis, data is represented as
a number of function evaluations. Crosses (+) give the median number of
function evaluations for the smallest r... | bsd-3-clause |
cauchycui/scikit-learn | examples/mixture/plot_gmm_classifier.py | 250 | 3918 | """
==================
GMM classification
==================
Demonstration of Gaussian mixture models for classification.
See :ref:`gmm` for more information on the estimator.
Plots predicted labels on both training and held out test data using a
variety of GMM classifiers on the iris dataset.
Compares GMMs with sp... | bsd-3-clause |
madjelan/scikit-learn | sklearn/neighbors/regression.py | 106 | 10572 | """Nearest Neighbor Regression"""
# 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 Arna... | bsd-3-clause |
ericpre/hyperspy | hyperspy/tests/drawing/test_plot_signal1d.py | 1 | 11462 | # Copyright 2007-2021 The HyperSpy developers
#
# This file is part of HyperSpy.
#
# HyperSpy is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later ... | gpl-3.0 |
nuclear-wizard/moose | modules/tensor_mechanics/test/tests/tensile/small_deform_hard3.py | 12 | 1286 | #!/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 |
UBC-Astrophysics/ObsPlan | ObsPlan.py | 1 | 9933 | #!/usr/bin/env python
#
# ObsPlan.py
#
# Elisa Antolini
# Jeremy Heyl
# UBC Southern Observatory
#
# This script takes the LIGO-Virgo Skymap (P(d|m)) and optionally a
# galaxy-density map (P(m)) and finds the most likely fields to
# observe (P(m|d)). The fields are assumed to be healpix regions from a
# tesselation wi... | gpl-3.0 |
Barmaley-exe/scikit-learn | sklearn/metrics/tests/test_score_objects.py | 2 | 13929 | import pickle
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_raises_regexp
from sklearn.utils.testing import assert_true
from sklearn.utils.testing im... | bsd-3-clause |
laszlocsomor/tensorflow | tensorflow/examples/tutorials/input_fn/boston.py | 76 | 2920 | # 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 |
empirical-org/WikipediaSentences | notebooks/BERT-4 Experiments Multilabel.py | 1 | 19268 | #!/usr/bin/env python
# coding: utf-8
# # Multilabel BERT Experiments
#
# In this notebook we do some first experiments with BERT: we finetune a BERT model+classifier on each of our datasets separately and compute the accuracy of the resulting classifier on the test data.
# For these experiments we use the `pytorch_... | agpl-3.0 |
antlr/codebuff | python/src/tsql_noisy_one_file_capture.py | 1 | 3111 | #
# AUTO-GENERATED FILE. DO NOT EDIT
# CodeBuff 1.4.19 'Sat Jun 18 16:50:22 PDT 2016'
#
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = plt.subplot(111)
labels = ["backupset_queries.sql", "buffer_pool_usage_by_db.sql", "compare_db_powershell.sql", "compare_tables.sql", "create_columnlist.sql... | bsd-2-clause |
Jozhogg/iris | docs/iris/example_code/General/SOI_filtering.py | 6 | 3050 | """
Applying a filter to a time-series
==================================
This example demonstrates low pass filtering a time-series by applying a
weighted running mean over the time dimension.
The time-series used is the Darwin-only Southern Oscillation index (SOI),
which is filtered using two different Lanczos filt... | lgpl-3.0 |
victorfsf/eva | setup.py | 1 | 1454 | # -*- coding: utf-8 -*-
from setuptools import setup
from setuptools import find_packages
version = '0.0.1'
setup(
name='eva',
packages=find_packages(exclude=['tests']),
package_data={
'eva': [],
},
install_requires=[
'nltk==3.2.4',
'numpy==1.12.1',
'pandas==0.20.... | gpl-3.0 |
lenovor/scikit-learn | sklearn/ensemble/tests/test_voting_classifier.py | 40 | 6991 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble import RandomForestCl... | bsd-3-clause |
jjx02230808/project0223 | examples/ensemble/plot_random_forest_embedding.py | 286 | 3531 | """
=========================================================
Hashing feature transformation using Totally Random Trees
=========================================================
RandomTreesEmbedding provides a way to map data to a
very high-dimensional, sparse representation, which might
be beneficial for classificati... | bsd-3-clause |
costypetrisor/scikit-learn | sklearn/tree/tests/test_tree.py | 72 | 47440 | """
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 |
dimroc/tensorflow-mnist-tutorial | lib/python3.6/site-packages/matplotlib/textpath.py | 10 | 16668 | # -*- coding: utf-8 -*-
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from collections import OrderedDict
import six
from six.moves import zip
import warnings
import numpy as np
from matplotlib.path import Path
from matplotlib import rcParams
import m... | apache-2.0 |
droundy/deft | papers/fuzzy-fmt/nm_hist2_work_in_progress.py | 1 | 1064 | #!/usr/bin/python2
#NOTE: Run this script from deft/papers/fuzzy-fmt with the
#command ./nm_hist.py
#MODIFYING this program to take command line arguments...
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import os
seeds=50
mcprefactor=40000
for gw in [.05]:
#for gw in [0.01, 0.... | gpl-2.0 |
sahana/Turkey | controllers/msg.py | 5 | 80604 | # -*- coding: utf-8 -*-
"""
Messaging Module - Controllers
"""
module = request.controller
resourcename = request.function
if not settings.has_module(module):
raise HTTP(404, body="Module disabled: %s" % module)
# -----------------------------------------------------------------------------
def index():
... | mit |
akionakamura/scikit-learn | examples/svm/plot_svm_scale_c.py | 223 | 5375 | """
==============================================
Scaling the regularization parameter for SVCs
==============================================
The following example illustrates the effect of scaling the
regularization parameter when using :ref:`svm` for
:ref:`classification <svm_classification>`.
For SVC classificati... | bsd-3-clause |
weidel-p/nest-simulator | extras/ConnPlotter/examples/connplotter_tutorial.py | 12 | 27772 | # -*- 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 |
jkleve/Optimization-Algorithms | tests/ga_analysis.py | 1 | 6534 | import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import numpy as np
import sys
sys.path.append("../utils")
sys.path.append("../functions")
sys.path.append("../genetic_algorithm")
import genetic_algorithm
import ackley_function
import easom_function
import rosenbrock_fun... | mit |
has2k1/plydata | plydata/one_table_verbs.py | 1 | 33733 | """
One table verb initializations
"""
import itertools
from .operators import DataOperator
from .expressions import Expression
__all__ = ['define', 'create', 'sample_n', 'sample_frac', 'select',
'rename', 'distinct', 'unique', 'arrange', 'group_by',
'ungroup', 'group_indices', 'summarize',
... | bsd-3-clause |
bond-/udacity-ml | src/numpy-pandas-tutorials/quiz-create-dataframe.py | 1 | 1819 | from pandas import DataFrame, Series
#################
# Syntax Reminder:
#
# The following code would create a two-column pandas DataFrame
# named df with columns labeled 'name' and 'age':
#
# people = ['Sarah', 'Mike', 'Chrisna']
# ages = [28, 32, 25]
# df = DataFrame({'name' : Series(people),
# 'a... | apache-2.0 |
harisbal/pandas | pandas/tests/io/test_common.py | 2 | 10380 | """
Tests for the pandas.io.common functionalities
"""
import mmap
import os
import pytest
import pandas as pd
import pandas.io.common as icom
import pandas.util._test_decorators as td
import pandas.util.testing as tm
from pandas.compat import (
is_platform_windows,
StringIO,
FileNotFoundError,
)
class ... | bsd-3-clause |
draperjames/bokeh | bokeh/core/compat/mpl_helpers.py | 14 | 5432 | "Helpers function for mpl module."
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#-----... | bsd-3-clause |
xzh86/scikit-learn | benchmarks/bench_plot_nmf.py | 206 | 5890 | """
Benchmarks of Non-Negative Matrix Factorization
"""
from __future__ import print_function
from collections import defaultdict
import gc
from time import time
import numpy as np
from scipy.linalg import norm
from sklearn.decomposition.nmf import NMF, _initialize_nmf
from sklearn.datasets.samples_generator import... | bsd-3-clause |
boada/HETDEXCluster | legacy/stats/rejectOutliers.py | 4 | 5284 | import glob
import pandas as pd
import pylab as pyl
from astLib import astCoords as aco
from astLib import astStats as ast
from astLib import astCalc as aca
def parseResults(files):
''' Reads all of the results files and puts them into a list with the
results. Returns field, dither, fiber, and redshift.
'... | mit |
ephes/scikit-learn | examples/covariance/plot_mahalanobis_distances.py | 348 | 6232 | r"""
================================================================
Robust covariance estimation and Mahalanobis distances relevance
================================================================
An example to show covariance estimation with the Mahalanobis
distances on Gaussian distributed data.
For Gaussian dis... | bsd-3-clause |
george-montanez/LICORScabinet | TruncatedKDE.py | 1 | 1467 | from __future__ import division
import numpy as np
from sklearn.neighbors import NearestNeighbors
from DensityEstimator import DensityEstimator
from VectorGaussianKernel import VectorGaussianKernel
from multi_flatten import multi_flatten
class TruncatedKDE(DensityEstimator):
def __init__(self, d_points, num_subsam... | gpl-2.0 |
rerpy/rerpy | doc/sphinxext/ipython_directive.py | 1 | 27232 | # -*- coding: utf-8 -*-
"""Sphinx directive to support embedded IPython code.
This directive allows pasting of entire interactive IPython sessions, prompts
and all, and their code will actually get re-executed at doc build time, with
all prompts renumbered sequentially. It also allows you to input code as a pure
pytho... | gpl-2.0 |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/pandas/tests/series/test_analytics.py | 4 | 63970 | # coding=utf-8
# pylint: disable-msg=E1101,W0612
from itertools import product
from distutils.version import LooseVersion
import pytest
from numpy import nan
import numpy as np
import pandas as pd
from pandas import (Series, Categorical, DataFrame, isnull, notnull,
bdate_range, date_range, _np_v... | mit |
DeercoderResearch/deepnet | deepnet/ais.py | 10 | 7589 | """Computes partition function for RBM-like models using Annealed Importance Sampling."""
import numpy as np
from deepnet import dbm
from deepnet import util
from deepnet import trainer as tr
from choose_matrix_library import *
import sys
import numpy as np
import pdb
import time
import itertools
import matplotlib.pypl... | bsd-3-clause |
kevinyu98/spark | python/pyspark/testing/sqlutils.py | 9 | 7813 | #
# 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 us... | apache-2.0 |
drewokane/seaborn | seaborn/timeseries.py | 4 | 15212 | """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 |
PrieureDeSion/intelligent-agents | sin(x) Neural Network/Neural Network.py | 1 | 2675 | '''
Function Approximator
This neural network uses Universal Approximator technique to predict the value of function in a closed domain.
This works on the theorem that any function in a closed domain which is continuous or discontinuous at finitely many points
can be approximated using piece-wise constant functions.
... | gpl-3.0 |
saiwing-yeung/scikit-learn | examples/manifold/plot_mds.py | 88 | 2731 | """
=========================
Multi-dimensional scaling
=========================
An illustration of the metric and non-metric MDS on generated noisy data.
The reconstructed points using the metric MDS and non metric MDS are slightly
shifted to avoid overlapping.
"""
# Author: Nelle Varoquaux <nelle.varoquaux@gmail.... | bsd-3-clause |
QBI-Microscopy/omero-user-scripts | Image_Processing/ExtractROIs.py | 1 | 31955 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Title: Extract ROIs from images
Description: Extracts multiple polygon or rectangle ROIs from an image or set of images
and creates individual images from them with associated links to parent image.
__author__ Liz Cooper-Williams, QBI
This script is based on compon... | gpl-2.0 |
JoostHuizinga/ea-plotting-scripts | createPlots.py | 1 | 77159 | #!/usr/bin/env python3
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib.patches import Polygon
import os
import sys
import io
import copy
import argparse as ap
from createPlotUtils import *
__author__ = "Joost Huizinga"
__version__ = "1.7 (Dec. 19 2019)"
initO... | mit |
exowanderer/SpitzerDeepLearningNetwork | Python Scripts/spitzer_cal_NALU_train.py | 1 | 15910 | from multiprocessing import set_start_method, cpu_count
#set_start_method('forkserver')
import os
os.environ["OMP_NUM_THREADS"] = str(cpu_count()) # or to whatever you want
from argparse import ArgumentParser
from datetime import datetime
from sklearn.model_selection import train_test_split
from sklearn.metrics impo... | mit |
Unidata/MetPy | v1.0/_downloads/6405360ec40d7796ed64eb783f2ffe55/NEXRAD_Level_2_File.py | 7 | 2016 | # Copyright (c) 2015,2018,2019 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
NEXRAD Level 2 File
===================
Use MetPy to read information from a NEXRAD Level 2 (volume) file and plot
"""
import matplotlib.pyplot as plt
import numpy as ... | bsd-3-clause |
evidation-health/bokeh | bokeh/tests/test_protocol.py | 42 | 3959 | from __future__ import absolute_import
import unittest
from unittest import skipIf
import numpy as np
try:
import pandas as pd
is_pandas = True
except ImportError as e:
is_pandas = False
class TestBokehJSONEncoder(unittest.TestCase):
def setUp(self):
from bokeh.protocol import BokehJSONEnc... | bsd-3-clause |
chilang/zeppelin | python/src/main/resources/python/bootstrap_sql.py | 60 | 1189 | # 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 use ... | apache-2.0 |
tangyouze/tushare | tushare/stock/shibor.py | 38 | 5010 | # -*- coding:utf-8 -*-
"""
上海银行间同业拆放利率（Shibor）数据接口
Created on 2014/07/31
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
import pandas as pd
import numpy as np
from tushare.stock import cons as ct
from tushare.util import dateu as du
def shibor_data(year=None):
"""
获取上海银行间同业拆放利率（Shibor）
P... | bsd-3-clause |
vibhorag/scikit-learn | sklearn/utils/tests/test_multiclass.py | 128 | 12853 |
from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sp... | bsd-3-clause |
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