repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
ilo10/scikit-learn | examples/neighbors/plot_regression.py | 349 | 1402 | """
============================
Nearest Neighbors regression
============================
Demonstrate the resolution of a regression problem
using a k-Nearest Neighbor and the interpolation of the
target using both barycenter and constant weights.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@... | bsd-3-clause |
mfjb/scikit-learn | examples/neighbors/plot_approximate_nearest_neighbors_hyperparameters.py | 227 | 5170 | """
=================================================
Hyper-parameters of Approximate Nearest Neighbors
=================================================
This example demonstrates the behaviour of the
accuracy of the nearest neighbor queries of Locality Sensitive Hashing
Forest as the number of candidates and the numb... | bsd-3-clause |
zuku1985/scikit-learn | sklearn/utils/tests/test_metaestimators.py | 86 | 2304 | from sklearn.utils.testing import assert_true, assert_false
from sklearn.utils.metaestimators import if_delegate_has_method
class Prefix(object):
def func(self):
pass
class MockMetaEstimator(object):
"""This is a mock meta estimator"""
a_prefix = Prefix()
@if_delegate_has_method(delegate="a... | bsd-3-clause |
snario/geopandas | geopandas/base.py | 6 | 17504 | from warnings import warn
from shapely.geometry import MultiPoint, MultiLineString, MultiPolygon
from shapely.geometry.base import BaseGeometry
from shapely.ops import cascaded_union, unary_union
import shapely.affinity as affinity
import numpy as np
import pandas as pd
from pandas import Series, DataFrame, MultiInde... | bsd-3-clause |
adamgonzalez/analysis | RfromZB_highres.py | 1 | 6153 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
@author: adamg
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib
from scipy.stats import gaussian_kde
import random
import time
import os
matplotlib.rcParams.update({'font.size': 18})
matplotlib.rcParams['axes.linewidth'] = 1 #set the value glo... | mit |
pravsripad/mne-python | mne/tests/test_import_nesting.py | 8 | 1372 | # Author: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import sys
from mne.utils import run_subprocess
run_script = """
import sys
import mne
out = set()
# check scipy (Numba imports it to check the version)
ok_scipy_submodules = set(['scipy', 'numpy', # these appear in old scipy
... | bsd-3-clause |
RPGOne/Skynet | scikit-learn-0.18.1/examples/cluster/plot_kmeans_silhouette_analysis.py | 83 | 5888 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
cb01/lxy | scripts/optimizationviz.py | 1 | 1387 | import numpy as np
import numpy.random
import matplotlib.pyplot as plt
import sys
import click
# Visualize a dotplot to compare two orderings of a list
# e.g. python scripts/scaffplot.py --inferred data/test/scaffolding.inferred.txt --actual data/test/scaffolding.key.txt --outpath data/test/test2.png
@click.command()... | bsd-3-clause |
vitaliykomarov/NEUCOGAR | nest/noradrenaline/nest-2.10.0/topology/examples/test_3d_gauss.py | 13 | 2641 | # -*- coding: utf-8 -*-
#
# test_3d_gauss.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, ... | gpl-2.0 |
rsteed11/GAT | gat/core/sna/sna.py | 1 | 36487 | import tempfile
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
from networkx.algorithms import bipartite as bi
from networkx.algorithms import centrality
from itertools import product
from collections import defaultdict, namedtuple
import pandas as pd
import datetime
from gat.core.sna import ... | mit |
eclee25/flu-SDI-exploratory-age | scripts/OR_seasonseverity.py | 1 | 2365 | #!/usr/bin/python
##############################################
###Python template
###Author: Elizabeth Lee
###Date: 7/25/13
###Function: Draw OR by season severity plots where season severity is defined as attack rate per 100,000 in acute care or inpatient facilities in flu peak weeks
###Import data: SQL_export/OR_... | mit |
annehutter/grid-model | analysis_tools/size_distribution_neutral.py | 1 | 5060 | import sys
import os
import numpy as np
import matplotlib as m
m.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from statistics import *
import read_parameterfile as rp
import read_fields as rf
def round_down(num):
if num < 0:
return -np.ceil(abs(num))
else:
r... | gpl-2.0 |
great-expectations/great_expectations | tests/execution_engine/test_pandas_execution_engine.py | 1 | 26181 | import datetime
import os
import random
from pathlib import Path
from typing import List
import boto3
import pandas as pd
import pytest
from botocore.errorfactory import ClientError
from moto import mock_s3
import great_expectations.exceptions.exceptions as ge_exceptions
from great_expectations.core.batch import Batc... | apache-2.0 |
akleber/fronius-json-tools | logdata-data2csv.py | 1 | 3241 |
"""
Work-in-progress!!!
Reads the logdata-data json files generated by the Fronius Push Service.
Extracts some data and writes it to a excel compatible csv file.
Also generates a graph from some data.
"""
import json
import csv
import collections
import matplotlib.pyplot as plt
from pprint import pprint
def to_tim... | mit |
jungla/ICOM-fluidity-toolbox | 2D/U/plot_W_v_avg.py | 1 | 2883 | from memory_profiler import memory_usage
from matplotlib.colors import LinearSegmentedColormap
import os, sys
import gc
import fio, myfun
import vtktools
import numpy as np
import matplotlib as mpl
mpl.use('ps')
import matplotlib.pyplot as plt
gc.enable()
## READ archive (too many points... somehow)
# args: name, day... | gpl-2.0 |
aetilley/scikit-learn | sklearn/linear_model/tests/test_theil_sen.py | 234 | 9928 | """
Testing for Theil-Sen module (sklearn.linear_model.theil_sen)
"""
# Author: Florian Wilhelm <florian.wilhelm@gmail.com>
# License: BSD 3 clause
from __future__ import division, print_function, absolute_import
import os
import sys
from contextlib import contextmanager
import numpy as np
from numpy.testing import ... | bsd-3-clause |
danielvdende/incubator-airflow | airflow/contrib/plugins/metastore_browser/main.py | 16 | 6015 | # -*- coding: utf-8 -*-
#
# 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
#... | apache-2.0 |
Solid-Mechanics/matplotlib-4-abaqus | matplotlib/backend_bases.py | 3 | 106958 | """
Abstract base classes define the primitives that renderers and
graphics contexts must implement to serve as a matplotlib backend
:class:`RendererBase`
An abstract base class to handle drawing/rendering operations.
:class:`FigureCanvasBase`
The abstraction layer that separates the
:class:`matplotlib.fi... | mit |
canast02/microsoft-malware-classification-challenge | solution4b5.py | 1 | 3910 | import os
from csv import writer
from sklearn import cross_validation
from sklearn.ensemble import ExtraTreesClassifier, RandomForestClassifier
from sklearn.neighbors import KNeighborsClassifier
import six
import utilities
# Decide read/write mode based on python version
read_mode, write_mode = ('r', 'w') if six.P... | apache-2.0 |
NelisVerhoef/scikit-learn | sklearn/covariance/tests/test_covariance.py | 69 | 11116 | # 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 |
SSJohns/osf.io | scripts/analytics/utils.py | 16 | 2605 | # -*- coding: utf-8 -*-
import os
import unicodecsv as csv
from bson import ObjectId
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import requests
from website import util
from website import settings as website_settings
def oid_to_datetime(oid):
return ObjectId(oid).generation_time
def ... | apache-2.0 |
acorg/dark-matter | dark/proteins.py | 1 | 44260 | from __future__ import print_function, division
import os
from collections import defaultdict, Counter
import numpy as np
from os.path import dirname, exists, join
from operator import itemgetter
import re
from six.moves.urllib.parse import quote
from textwrap import fill
from dark.dimension import dimensionalIterato... | mit |
dieterich-lab/rp-bp | rpbp/analysis/rpbp_predictions/create_rpbp_predictions_report.py | 1 | 32174 | #! /usr/bin/env python3
import argparse
import itertools
import logging
import os
import shlex
import sys
import yaml
import pbio.misc.latex as latex
import pbio.misc.logging_utils as logging_utils
import pbio.misc.parallel as parallel
import pbio.misc.shell_utils as shell_utils
import pbio.misc.slurm as slurm
import... | mit |
BiRG/Omics-Dashboard | omics/omics_dashboard/dashboards/nmr_metabolomics/collection_editor/model.py | 1 | 7721 | import os
import dash_bootstrap_components as dbc
import dash_html_components as html
from flask_login import current_user
from flask import url_for
import pandas as pd
from dashboards.dashboard_model import DashboardModel
from data_tools.db_models import collection_analysis_membership, db, Analysis
from data_tools.w... | mit |
Jimmy-Morzaria/scikit-learn | examples/ensemble/plot_adaboost_twoclass.py | 347 | 3268 | """
==================
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 |
caslei/TfModels | slim/ExampleVGG.py | 1 | 14684 | #http://lib.csdn.net/article/machinelearning/39582
#https://github.com/warmspringwinds/tensorflow_notes/blob/master/image_segmentation_conditional_random_fields.ipynb
from __future__ import division
import os, time
import sys
import tensorflow as tf
#import skimage.io as io
import numpy as np
from matplotlib import py... | apache-2.0 |
waynenilsen/statsmodels | statsmodels/sandbox/nonparametric/kde2.py | 34 | 3158 | # -*- coding: utf-8 -*-
from __future__ import print_function
from statsmodels.compat.python import lzip, zip
import numpy as np
from . import kernels
#TODO: should this be a function?
class KDE(object):
"""
Kernel Density Estimator
Parameters
----------
x : array-like
N-dimensional array... | bsd-3-clause |
pratapvardhan/scikit-learn | sklearn/metrics/ranking.py | 17 | 27697 | """Metrics to assess performance on classification task given scores
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.... | bsd-3-clause |
goodfeli/pylearn2 | pylearn2/train_extensions/plots.py | 34 | 9617 | """
Plot monitoring extensions while training.
"""
__authors__ = "Laurent Dinh"
__copyright__ = "Copyright 2014, Universite de Montreal"
__credits__ = ["Laurent Dinh"]
__license__ = "3-clause BSD"
__maintainer__ = "Laurent Dinh"
__email__ = "dinhlaur@iro"
import logging
import os
import os.path
import stat
import num... | bsd-3-clause |
kdmurray91/scikit-bio | skbio/diversity/alpha/tests/test_faith_pd.py | 2 | 8645 | # ----------------------------------------------------------------------------
# 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 |
xuanyuanking/spark | python/pyspark/pandas/data_type_ops/categorical_ops.py | 5 | 2506 | #
# 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 |
meduz/scikit-learn | examples/svm/plot_svm_regression.py | 120 | 1520 | """
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
===================================================================
Toy example of 1D regression using linear, polynomial and RBF kernels.
"""
print(__doc__)
import numpy as np
... | bsd-3-clause |
mrshu/scikit-learn | sklearn/tests/test_grid_search.py | 2 | 8915 | """
Testing for grid search module (sklearn.grid_search)
"""
from cStringIO import StringIO
import sys
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_true
from sklearn.utils.testing ... | bsd-3-clause |
zodiacnan/Masterarbeit | moduls/results/excelwrite.py | 1 | 3091 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 15 12:55:07 2017
@author: DINGNAN
"""
#write the excel table of Ld-Lq identifikation
import os
os.chdir('C:\\Users\\DINGNAN\\Desktop\\machines\\res\\')
import xlwt
import numpy as np
import matplotlib
from datetime import date,datetime
import pandas as pd
import math
Nb... | gpl-3.0 |
Eric89GXL/mne-python | tutorials/raw/plot_40_visualize_raw.py | 4 | 8569 | # -*- coding: utf-8 -*-
"""
.. _tut-visualize-raw:
Built-in plotting methods for Raw objects
=========================================
This tutorial shows how to plot continuous data as a time series, how to plot
the spectral density of continuous data, and how to plot the sensor locations
and projectors stored in `~... | bsd-3-clause |
antkillerfarm/antkillerfarm_crazy | python/ml/tc/tc0209.py | 1 | 6167 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import MySQLdb
import numpy as np
from datetime import datetime
import matplotlib.pyplot as plt
class statistics_info:
def __init__(self):
self.num = 0
self.sum = 0.0
self.weeks = []
self.user_sum = [0 for i in range(7)]
class week_info:
... | gpl-3.0 |
chugunovyar/factoryForBuild | env/lib/python2.7/site-packages/matplotlib/backends/backend_wxagg.py | 10 | 5840 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import matplotlib
from matplotlib.figure import Figure
from .backend_agg import FigureCanvasAgg
from . import wx_compat as wxc
from . import backend_wx
from .backend_wx import (FigureManagerWx, Fi... | gpl-3.0 |
ishay2b/tensorflow | tensorflow/examples/learn/text_classification_character_cnn.py | 29 | 5666 | # 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 |
pkonarzewski/data-processors | tests/test_dateutils.py | 1 | 4085 | # -- coding: utf-8 -*-
import unittest
from pandas import DataFrame, Series, NaT
from datetime import datetime, date
import pandas.util.testing as pdtest
from processors import dateutils as dtu
class TestDateTimeParse(unittest.TestCase):
def test_unify_cases_df(self):
# floor datetime series
df ... | mit |
florian-f/sklearn | examples/plot_johnson_lindenstrauss_bound.py | 4 | 7402 | """
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected in... | bsd-3-clause |
orangeYao/twiOpinion | mainLearning.py | 1 | 2006 | #!/usr/bin/env python
#copied from zhiyao@combo: /home/zhiyao/FYPstart/largeTestData
#only library in sklearnClassify included currently
import functions
import sklearnClassify
import pandas as pd
import random
import datetime
numberForTraining = 4000
numberForTesting = 400
numberUsedAll = numberForTraining + numberFo... | mit |
rallured/PyXFocus | examples/axro/stressCompensation.py | 1 | 3389 | import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
import pdb,os,pyfits
import utilities.imaging.fitting as fit
import traces.sources as sources
import traces.transformations as tran
import traces.surfaces as surf
import traces.analyses as anal
#Get distortion coefficients
os.chd... | mit |
wlamond/scikit-learn | sklearn/model_selection/_search.py | 4 | 49846 | """
The :mod:`sklearn.model_selection._search` includes utilities to fine-tune the
parameters of an estimator.
"""
from __future__ import print_function
from __future__ import division
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas... | bsd-3-clause |
VirusTotal/msticpy | msticpy/nbtools/security_event.py | 1 | 3507 | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""Module ... | mit |
av8ramit/tensorflow | tensorflow/contrib/factorization/python/ops/kmeans_test.py | 12 | 20083 | # 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 |
marinkaz/orange3 | Orange/widgets/visualize/owscatterplot.py | 2 | 24824 | from bisect import bisect_left
import sys
import numpy as np
from PyQt4.QtCore import QSize, Qt, QTimer
from PyQt4 import QtGui
from PyQt4.QtGui import QApplication, QTableView, QStandardItemModel, \
QStandardItem
from sklearn.neighbors import NearestNeighbors
from sklearn.metrics import r2_score
import Orange
fr... | bsd-2-clause |
patmarion/director | src/python/scripts/logReporter.py | 5 | 4906 | import os
import sys
import time
import lcm
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
from director import lcmspy as spy
import scipy.signal as sig
def sizeof_fmt(num, suffix='B'):
for unit in ['','Ki','Mi','Gi','Ti','Pi','Ei','Zi']:
if abs(num) < 1024.0:
return "... | bsd-3-clause |
nmayorov/scikit-learn | sklearn/model_selection/tests/test_search.py | 20 | 30855 | """Test the search module"""
from collections import Iterable, Sized
from sklearn.externals.six.moves import cStringIO as StringIO
from sklearn.externals.six.moves import xrange
from itertools import chain, product
import pickle
import sys
import numpy as np
import scipy.sparse as sp
from sklearn.utils.fixes import ... | bsd-3-clause |
mraspaud/dask | dask/dataframe/io/sql.py | 2 | 5272 | import numpy as np
import pandas as pd
import six
from ... import delayed
from .io import from_delayed
def read_sql_table(table, uri, index_col, divisions=None, npartitions=None,
limits=None, columns=None, bytes_per_chunk=256 * 2**20,
**kwargs):
"""
Create dataframe from... | bsd-3-clause |
ycaihua/scikit-learn | benchmarks/bench_glmnet.py | 297 | 3848 | """
To run this, you'll need to have installed.
* glmnet-python
* scikit-learn (of course)
Does two benchmarks
First, we fix a training set and increase the number of
samples. Then we plot the computation time as function of
the number of samples.
In the second benchmark, we increase the number of dimensions of... | bsd-3-clause |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/matplotlib/tests/test_style.py | 2 | 5014 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import shutil
import tempfile
import warnings
from collections import OrderedDict
from contextlib import contextmanager
import pytest
import matplotlib as mpl
from matplotlib import style
from matpl... | mit |
jorik041/scikit-learn | benchmarks/bench_random_projections.py | 397 | 8900 | """
===========================
Random projection benchmark
===========================
Benchmarks for random projections.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import collections
import numpy as np
import scipy.s... | bsd-3-clause |
yask123/scikit-learn | sklearn/decomposition/pca.py | 192 | 23117 | """ Principal Component Analysis
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Michael Eickenberg <michael.eickenberg@inria.fr>
#
# Lice... | bsd-3-clause |
romainx/panorama | panorama/chart_factory.py | 1 | 4286 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from functools import partial
from pandas import Series, DataFrame
# !! Import required to instantiate charts, do not remove
from nvd3 import *
import numpy
# A dict used for chart configuration.
# DEFAULT settings can be overwritten and/or completed by... | mit |
futurulus/scipy | scipy/signal/signaltools.py | 5 | 88094 | # Author: Travis Oliphant
# 1999 -- 2002
from __future__ import division, print_function, absolute_import
import warnings
import threading
from . import sigtools
from scipy._lib.six import callable
from scipy._lib._version import NumpyVersion
from scipy import fftpack, linalg
from numpy import (allclose, angle, aran... | bsd-3-clause |
saurv4u/Deep-Learning-for-Content-Retrieval | Code/clustering.py | 1 | 2507 | import matplotlib.pyplot as plt
import numpy
from sklearn.cluster import DBSCAN
from sklearn.cluster import AgglomerativeClustering
from sklearn.cluster import KMeans
from cluster import HierarchicalClustering
from sklearn import metrics
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import pairw... | mit |
zaxtax/scikit-learn | sklearn/ensemble/tests/test_partial_dependence.py | 365 | 6996 | """
Testing for the partial dependence module.
"""
import numpy as np
from numpy.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import if_matplotlib
from sklearn.ensemble.partial_dependence import partial_dependence
from sklearn.ensemble.partial_dependence... | bsd-3-clause |
mahak/spark | python/pyspark/pandas/tests/plot/test_series_plot_plotly.py | 14 | 8485 | #
# 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 |
Mecanon/morphing_wing | experimental/sma_database/convert_transformation_temperatures.py | 1 | 4418 | # -*- coding: utf-8 -*-
"""
Created on Fri Jul 15 16:39:31 2016
@author: Eduardo Tancredo & Pedro Leal
"""
import math
import numpy as np
#import matplotlib.pyplot as plt
n_1 = 0.1919
n_2 = 0.1823
n_3 = 0.1623
n_4 = 0.2188
Ms_list = np.array([ 68.74, 75.71, 82.33, 84.77, 88.27])
Mf_list = np.array([ 57.74, 65.39, 7... | mit |
Martin09/E-BeamPatterns | 111 Wafers - 1.2cm Triangles/111A Nanowires/v1.3/gdsCAD_v045/core.py | 4 | 74577 | # -*- coding: utf-8 -*-
"""
The primary geometry elements, layout and organization classes.
The objects found here are intended to correspond directly to elements found in
the GDSII specification.
The fundamental gdsCAD object is the Layout, which contains all the information
to be sent to the mask shop. A Layout can... | gpl-3.0 |
cactusbin/nyt | matplotlib/lib/matplotlib/pyplot.py | 4 | 114926 | # Note: The first part of this file can be modified in place, but the latter
# part is autogenerated by the boilerplate.py script.
"""
Provides a MATLAB-like plotting framework.
:mod:`~matplotlib.pylab` combines pyplot with numpy into a single namespace.
This is convenient for interactive work, but for programming it
... | unlicense |
Garrett-R/scikit-learn | examples/ensemble/plot_adaboost_hastie_10_2.py | 355 | 3576 | """
=============================
Discrete versus Real AdaBoost
=============================
This example is based on Figure 10.2 from Hastie et al 2009 [1] and illustrates
the difference in performance between the discrete SAMME [2] boosting
algorithm and real SAMME.R boosting algorithm. Both algorithms are evaluate... | bsd-3-clause |
alorenzo175/pvlib-python | pvlib/iotools/surfrad.py | 1 | 7027 | """
Import functions for NOAA SURFRAD Data.
"""
import io
from urllib.request import urlopen, Request
import pandas as pd
import numpy as np
SURFRAD_COLUMNS = [
'year', 'jday', 'month', 'day', 'hour', 'minute', 'dt', 'zen',
'dw_solar', 'dw_solar_flag', 'uw_solar', 'uw_solar_flag', 'direct_n',
'direct_n_fla... | bsd-3-clause |
amueller/astro_hackweek | plots/plot_rbf_svm_parameters.py | 15 | 2061 | import matplotlib.pyplot as plt
import numpy as np
from sklearn.svm import SVC
from sklearn.datasets import make_blobs
from sklearn.externals.joblib import Memory
from .plot_2d_separator import plot_2d_separator
def make_handcrafted_dataset():
# a carefully hand-designed dataset lol
X, y = make_blobs(centers=2... | bsd-2-clause |
idlead/scikit-learn | sklearn/metrics/tests/test_classification.py | 20 | 50188 | from __future__ import division, print_function
import numpy as np
from scipy import linalg
from functools import partial
from itertools import product
import warnings
from sklearn import datasets
from sklearn import svm
from sklearn.datasets import make_multilabel_classification
from sklearn.preprocessing import la... | bsd-3-clause |
ozsolarwind/siren | flexiplot.py | 1 | 46585 | #!/usr/bin/python3
#
# Copyright (C) 2020-2021 Sustainable Energy Now Inc., Angus King
#
# flexiplot.py - This file is possibly part of SIREN.
#
# SIREN 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 Foundati... | agpl-3.0 |
Ziqi-Li/bknqgis | pandas/pandas/core/reshape/merge.py | 1 | 56841 | """
SQL-style merge routines
"""
import copy
import warnings
import string
import numpy as np
from pandas.compat import range, lzip, zip, map, filter
import pandas.compat as compat
from pandas import (Categorical, Series, DataFrame,
Index, MultiIndex, Timedelta)
from pandas.core.frame import _mer... | gpl-2.0 |
gregcaporaso/scikit-bio | skbio/diversity/tests/test_util.py | 4 | 10265 | # ----------------------------------------------------------------------------
# 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 |
carpyncho/feets | feets/datasets/ogle3.py | 1 | 9206 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# The MIT License (MIT)
# Copyright (c) 2017 Juan Cabral
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including withou... | mit |
spallavolu/scikit-learn | sklearn/neighbors/regression.py | 100 | 11017 | """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 |
carrillo/scikit-learn | sklearn/decomposition/pca.py | 192 | 23117 | """ Principal Component Analysis
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Michael Eickenberg <michael.eickenberg@inria.fr>
#
# Lice... | bsd-3-clause |
credp/lisa | external/workload-automation/wa/utils/misc.py | 3 | 25178 | # Copyright 2013-2018 ARM Limited
#
# 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 w... | apache-2.0 |
hugobowne/scikit-learn | sklearn/linear_model/tests/test_theil_sen.py | 58 | 9948 | """
Testing for Theil-Sen module (sklearn.linear_model.theil_sen)
"""
# Author: Florian Wilhelm <florian.wilhelm@gmail.com>
# License: BSD 3 clause
from __future__ import division, print_function, absolute_import
import os
import sys
from contextlib import contextmanager
import numpy as np
from numpy.testing import ... | bsd-3-clause |
rs2/pandas | pandas/tests/plotting/test_boxplot_method.py | 2 | 18166 | import itertools
import string
import numpy as np
from numpy import random
import pytest
import pandas.util._test_decorators as td
from pandas import DataFrame, MultiIndex, Series, date_range, timedelta_range
import pandas._testing as tm
from pandas.tests.plotting.common import TestPlotBase, _check_plot_works
impor... | bsd-3-clause |
ericpre/hyperspy | hyperspy/drawing/_widgets/range.py | 2 | 22610 | # -*- coding: utf-8 -*-
# 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... | gpl-3.0 |
ewulczyn/talk_page_abuse | src/analysis/load_utils.py | 1 | 3146 | import os
import pandas as pd
import re
def load_diffs(keep_diff = False):
nick_map = {
'talk_diff_no_admin_sample.tsv': 'sample',
'talk_diff_no_admin_2015.tsv': '2015',
'all_blocked_user.tsv': 'blocked',
'd_annotated.tsv': 'annotated',
}
base = '../../data/samples/'
... | apache-2.0 |
leeamen/eva | 2017/tfidf.py | 1 | 3251 | # coding:utf-8
import jieba
import jieba.posseg as pseg
import os
import sys
from sklearn import feature_extraction
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.ensemble import GradientBoostingClassifier
import nump... | apache-2.0 |
kevin-intel/scikit-learn | examples/linear_model/plot_multi_task_lasso_support.py | 77 | 2319 | #!/usr/bin/env python
"""
=============================================
Joint feature selection with multi-task Lasso
=============================================
The multi-task lasso allows to fit multiple regression problems
jointly enforcing the selected features to be the same across
tasks. This example simulates... | bsd-3-clause |
kernc/scikit-learn | sklearn/utils/tests/test_validation.py | 56 | 18600 | """Tests for input validation functions"""
import warnings
from tempfile import NamedTemporaryFile
from itertools import product
import numpy as np
from numpy.testing import assert_array_equal
import scipy.sparse as sp
from nose.tools import assert_raises, assert_true, assert_false, assert_equal
from sklearn.utils.... | bsd-3-clause |
iandriver/RNA-sequence-tools | FPKM_Parsing/filter_outliers.py | 2 | 13254 | import os
import fnmatch
import pickle as pickle
import numpy as np
import pandas as pd
from collections import OrderedDict
import matplotlib.pyplot as plt
#This section will take fpkm matrix input and make pandas dataframe
#path to fpkm file (usually cuffnorm output)
path_to_file = '/Volumes/Drobo/hisat2_chapmanh-hu... | mit |
anirudhjayaraman/scikit-learn | sklearn/utils/tests/test_murmurhash.py | 261 | 2836 | # Author: Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import numpy as np
from sklearn.externals.six import b, u
from sklearn.utils.murmurhash import murmurhash3_32
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
from nose.tools import assert_equa... | bsd-3-clause |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/lib/mpl_examples/event_handling/lasso_demo.py | 3 | 2508 | """
Show how to use a lasso to select a set of points and get the indices
of the selected points. A callback is used to change the color of the
selected points
This is currently a proof-of-concept implementation (though it is
usable as is). There will be some refinement of the API and the
inside polygon detection ro... | gpl-2.0 |
wangmiao1981/spark | python/pyspark/pandas/extensions.py | 11 | 12362 | #
# 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 |
wlamond/scikit-learn | sklearn/utils/tests/test_testing.py | 29 | 7316 | import warnings
import unittest
import sys
from sklearn.utils.testing import (
assert_raises,
assert_less,
assert_greater,
assert_less_equal,
assert_greater_equal,
assert_warns,
assert_no_warnings,
assert_equal,
set_random_state,
assert_raise_message,
ignore_warnings)
from ... | bsd-3-clause |
ARudiuk/mne-python | examples/decoding/plot_decoding_spatio_temporal_source.py | 5 | 5963 | """
==========================
Decoding source space data
==========================
Decoding, a.k.a MVPA or supervised machine learning applied to MEG
data in source space on the left cortical surface. Here f-test feature
selection is employed to confine the classification to the potentially
relevant features. The cl... | bsd-3-clause |
HeraclesHX/scikit-learn | sklearn/cluster/mean_shift_.py | 106 | 14056 | """Mean shift clustering algorithm.
Mean shift clustering aims to discover *blobs* in a smooth density of
samples. It is a centroid based algorithm, which works by updating candidates
for centroids to be the mean of the points within a given region. These
candidates are then filtered in a post-processing stage to elim... | bsd-3-clause |
LohithBlaze/scikit-learn | benchmarks/bench_plot_omp_lars.py | 266 | 4447 | """Benchmarks of orthogonal matching pursuit (:ref:`OMP`) versus least angle
regression (:ref:`least_angle_regression`)
The input data is mostly low rank but is a fat infinite tail.
"""
from __future__ import print_function
import gc
import sys
from time import time
import numpy as np
from sklearn.linear_model impo... | bsd-3-clause |
RobertABT/heightmap | build/matplotlib/examples/api/sankey_demo_rankine.py | 7 | 3810 | """Demonstrate the Sankey class with a practicle example of a Rankine power cycle.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.sankey import Sankey
fig = plt.figure(figsize=(8, 9))
ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[],
title="Rankine Power Cycle: Example 8... | mit |
Horta/limix | limix/_data/_conform.py | 1 | 10152 | from __future__ import unicode_literals
from collections import Counter
from .._bits.dask import array_shape_reveal
from .._bits.xarray import set_coord
from .._bits.deco import return_none_if_none
from ._dataarray import fix_dim_hint, rename_dims
from ._data import is_data_name, is_short_data_name, to_data_name, get... | apache-2.0 |
gpetretto/pymatgen | pymatgen/vis/tests/test_plotters.py | 7 | 1629 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
import os
import unittest
import json
from monty.json import MontyDecoder
import numpy as np
import matplotlib
matplotlib.use("pdf")
from pymatgen.util.testing import PymatgenTest
from pymatgen.analysis.xas.s... | mit |
bdestombe/flopy-1 | flopy/utils/util_list.py | 1 | 38930 | """
util_list module. Contains the mflist class.
This classes encapsulates modflow-style list inputs away
from the individual packages. The end-user should not need to
instantiate this class directly.
some more info
"""
from __future__ import division, print_function
import os
import warnings
i... | bsd-3-clause |
sk2/ank_le | AutoNetkit/plotting/plot.py | 1 | 11321 | # -*- coding: utf-8 -*-
"""
Plotting
"""
__author__ = "\n".join(['Simon Knight'])
# Copyright (C) 2009-2011 by Simon Knight, Hung Nguyen
__all__ = ['plot', 'plot_graph', 'plot_paths']
import networkx as nx
import AutoNetkit as ank
import logging
import os
import pprint
try:
import matplotlib.cm as cm
impor... | bsd-3-clause |
trungnt13/scikit-learn | examples/neighbors/plot_regression.py | 349 | 1402 | """
============================
Nearest Neighbors regression
============================
Demonstrate the resolution of a regression problem
using a k-Nearest Neighbor and the interpolation of the
target using both barycenter and constant weights.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@... | bsd-3-clause |
henrykironde/scikit-learn | sklearn/covariance/tests/test_robust_covariance.py | 213 | 3359 | # 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 |
malcolmw/SeismicPython | seispy/pandas/io/schema.py | 3 | 2734 | import os
import pandas as pd
import pickle
import pkg_resources
def get_schema(schema, ext=False):
schema_file = pkg_resources.resource_filename("seispy",
os.path.join("data",
"schemas",
... | gpl-3.0 |
krzychb/rtd-test-bed | tools/tiny-test-fw/Utility/LineChart.py | 1 | 1742 | # Copyright 2015-2017 Espressif Systems (Shanghai) PTE LTD
#
# 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 ... | apache-2.0 |
mne-tools/mne-tools.github.io | 0.16/_downloads/ftclient_rt_compute_psd.py | 18 | 2442 | """
==============================================================
Compute real-time power spectrum density with FieldTrip client
==============================================================
Please refer to `ftclient_rt_average.py` for instructions on
how to get the FieldTrip connector working in MNE-Python.
This e... | bsd-3-clause |
jklenzing/pysat | pysat/instruments/icon_fuv.py | 2 | 8464 | # -*- coding: utf-8 -*-
"""Supports the Far Ultraviolet (FUV) imager onboard the Ionospheric
CONnection Explorer (ICON) satellite. Accesses local data in
netCDF format.
Parameters
----------
platform : string
'icon'
name : string
'fuv'
tag : string
None supported
Warnings
--------
- The cleaning paramete... | bsd-3-clause |
bensondaled/pyfluo | pyfluo/sandbox/series_pd.py | 1 | 6211 | # External imports
import pandas as pd, numpy as np, matplotlib.pyplot as pl
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap, BoundaryNorm
import warnings
# Internal imports
from .config import *
class Series(pd.DataFrame):
"""Series object
"""
_metadata = [... | bsd-2-clause |
humdings/zipline | zipline/utils/cache.py | 1 | 10994 | """
Caching utilities for zipline
"""
from collections import MutableMapping
import errno
import os
import pickle
from distutils import dir_util
from shutil import rmtree, move
from tempfile import mkdtemp, NamedTemporaryFile
import pandas as pd
from .context_tricks import nop_context
from .paths import ensure_direct... | apache-2.0 |
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