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 |
|---|---|---|---|---|---|
rs2/pandas | pandas/tests/extension/test_integer.py | 2 | 7327 | """
This file contains a minimal set of tests for compliance with the extension
array interface test suite, and should contain no other tests.
The test suite for the full functionality of the array is located in
`pandas/tests/arrays/`.
The tests in this file are inherited from the BaseExtensionTests, and only
minimal ... | bsd-3-clause |
scienceopen/transcarread | plasma_state.py | 1 | 1292 | #!/usr/bin/env python
"""
Reads output of Transcar sim, yielding Incoherent Scatter Radar plasma parameters.
python transcar2isr.py tests/data/beam52
"""
from pathlib import Path
from matplotlib.pyplot import show
from argparse import ArgumentParser
from datetime import datetime
#
import transcarread.plots as pl... | gpl-3.0 |
dingocuster/scikit-learn | sklearn/tests/test_learning_curve.py | 225 | 10791 | # Author: Alexander Fabisch <afabisch@informatik.uni-bremen.de>
#
# License: BSD 3 clause
import sys
from sklearn.externals.six.moves import cStringIO as StringIO
import numpy as np
import warnings
from sklearn.base import BaseEstimator
from sklearn.learning_curve import learning_curve, validation_curve
from sklearn.u... | bsd-3-clause |
aolindahl/polarization-monitor | offline_handler.py | 1 | 9272 | # -*- coding: utf-8 -*-
"""
Created on Wed May 27 12:59:34 2015
@author: antlin
"""
import h5py
import numpy as np
import sys
import matplotlib.pyplot as plt
from aolPyModules import cookie_box
import lmfit
photo_roi = [[236.5, 250],
[236.5, 250],
[242.0, 260],
[242.0, 260],
... | gpl-2.0 |
jenfly/python-practice | maps/maps.py | 1 | 2641 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from datetime import datetime
# Globe with Orthographic projection
# ----------------------------------
# lon_0, lat_0 are the center point of the projection.
# resolution = 'l' means use low resolution coastlines.
lon_0, lat_0... | mit |
agoose77/hivesystem | manual/movingpanda/panda-13.py | 1 | 9853 | import dragonfly
import dragonfly.pandahive
import bee
from bee import connect
import dragonfly.scene.unbound, dragonfly.scene.bound
import dragonfly.std
import dragonfly.io
import dragonfly.canvas
import dragonfly.convert.pull
import dragonfly.logic
import dragonfly.bind
import Spyder
# ## random matrix generator
f... | bsd-2-clause |
TPeterW/Bitcoin-Price-Prediction | data_collection/flip_sheets.py | 1 | 1705 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
import pandas as pd
def main():
if len(sys.argv) >= 2:
filenames = sys.argv[1:]
for filename in filenames:
flipfile(filename)
# else:
# files = ["Anoncoin.csv", "Argentum.csv", "BBQCoin.csv", "BetaCoin.csv", "BitB... | mit |
cwu2011/scikit-learn | sklearn/utils/validation.py | 66 | 23629 | """Utilities for input validation"""
# Authors: Olivier Grisel
# Gael Varoquaux
# Andreas Mueller
# Lars Buitinck
# Alexandre Gramfort
# Nicolas Tresegnie
# License: BSD 3 clause
import warnings
import numbers
import numpy as np
import scipy.sparse as sp
from ..externals i... | bsd-3-clause |
dingocuster/scikit-learn | sklearn/semi_supervised/tests/test_label_propagation.py | 307 | 1974 | """ test the label propagation module """
import nose
import numpy as np
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {'kernel': 'rbf'}),
(label_propa... | bsd-3-clause |
jreback/pandas | pandas/tests/indexing/common.py | 2 | 5245 | """ common utilities """
import itertools
import numpy as np
from pandas import DataFrame, Float64Index, MultiIndex, Series, UInt64Index, date_range
import pandas._testing as tm
def _mklbl(prefix, n):
return [f"{prefix}{i}" for i in range(n)]
def _axify(obj, key, axis):
# create a tuple accessor
axes ... | bsd-3-clause |
mwaskom/seaborn | seaborn/regression.py | 2 | 39418 | """Plotting functions for linear models (broadly construed)."""
import copy
from textwrap import dedent
import warnings
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
try:
import statsmodels
assert statsmodels
_has_statsmodels = True
except ImportError:
... | bsd-3-clause |
JeanKossaifi/scikit-learn | sklearn/datasets/species_distributions.py | 198 | 7923 | """
=============================
Species distribution dataset
=============================
This dataset represents the geographic distribution of species.
The dataset is provided by Phillips et. al. (2006).
The two species are:
- `"Bradypus variegatus"
<http://www.iucnredlist.org/apps/redlist/details/3038/0>`_... | bsd-3-clause |
ronekko/spatial_transformer_network | main.py | 1 | 8637 | # -*- coding: utf-8 -*-
"""
Created on Mon Sep 14 21:17:12 2015
@author: sakurai
"""
import argparse
import time
import copy
import numpy as np
import matplotlib.pyplot as plt
import chainer.functions as F
from chainer import optimizers
from chainer import Variable, FunctionSet
from chainer import cuda
import spatial... | mit |
theonaun/surgeo | tests/app/test_cli.py | 1 | 5819 | import os
import pathlib
import subprocess
import sys
import tempfile
import unittest
import numpy as np
import pandas as pd
import surgeo.app.surgeo_cli
class TestSurgeoCLI(unittest.TestCase):
_CLI_SCRIPT = surgeo.app.surgeo_cli.__file__
_DATA_FOLDER = pathlib.Path(__file__).resolve().parents[1] / 'data'... | mit |
lneuhaus/pyrpl | pyrpl/software_modules/spectrum_analyzer.py | 1 | 29677 | ###############################################################################
# pyrpl - DSP servo controller for quantum optics with the RedPitaya
# Copyright (C) 2014-2016 Leonhard Neuhaus (neuhaus@spectro.jussieu.fr)
#
# This program is free software: you can redistribute it and/or modify
# it under t... | gpl-3.0 |
nicococo/ClusterSvdd | scripts/test_ad_svdd.py | 1 | 7209 | import matplotlib.pyplot as plt
import sklearn.metrics as metrics
import sklearn.datasets as datasets
import numpy as np
from ClusterSVDD.svdd_primal_sgd import SvddPrimalSGD
from ClusterSVDD.svdd_dual_qp import SvddDualQP
from ClusterSVDD.cluster_svdd import ClusterSvdd
def generate_data_uniform(datapoints, cluster... | mit |
michrawson/nyu_ml_lectures | notebooks/figures/plot_rbf_svm_parameters.py | 19 | 2018 | import matplotlib.pyplot as plt
import numpy as np
from sklearn.svm import SVC
from sklearn.datasets import make_blobs
from .plot_2d_separator import plot_2d_separator
def make_handcrafted_dataset():
# a carefully hand-designed dataset lol
X, y = make_blobs(centers=2, random_state=4, n_samples=30)
y[np.ar... | cc0-1.0 |
wzbozon/statsmodels | statsmodels/sandbox/examples/try_multiols.py | 33 | 1243 | # -*- coding: utf-8 -*-
"""
Created on Sun May 26 13:23:40 2013
Author: Josef Perktold, based on Enrico Giampieri's multiOLS
"""
#import numpy as np
import pandas as pd
import statsmodels.api as sm
from statsmodels.sandbox.multilinear import multiOLS, multigroup
data = sm.datasets.longley.load_pandas()
df = data.e... | bsd-3-clause |
yanboliang/spark | python/pyspark/sql/types.py | 2 | 67075 | #
# 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 |
scottpurdy/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/dates.py | 15 | 33969 | """
Matplotlib provides sophisticated date plotting capabilities, standing
on the shoulders of python :mod:`datetime`, the add-on modules
:mod:`pytz` and :mod:`dateutils`. :class:`datetime` objects are
converted to floating point numbers which represent the number of days
since 0001-01-01 UTC. The helper functions :f... | agpl-3.0 |
xwolf12/scikit-learn | sklearn/ensemble/tests/test_bagging.py | 127 | 25365 | """
Testing for the bagging ensemble module (sklearn.ensemble.bagging).
"""
# Author: Gilles Louppe
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.te... | bsd-3-clause |
jimsrc/seatos | mixed.icmes/src/report/tt2a.py | 1 | 11159 | #!/usr/bin/env ipython
from pylab import *
import numpy as np
from scipy.io.netcdf import netcdf_file
import os, sys
import matplotlib.patches as patches
import matplotlib.transforms as transforms
from numpy import array
from matplotlib.gridspec import GridSpec
import matplotlib.pyplot as plt
from os.path import isdir,... | mit |
andrewnc/scikit-learn | sklearn/ensemble/partial_dependence.py | 251 | 15097 | """Partial dependence plots for tree ensembles. """
# Authors: Peter Prettenhofer
# License: BSD 3 clause
from itertools import count
import numbers
import numpy as np
from scipy.stats.mstats import mquantiles
from ..utils.extmath import cartesian
from ..externals.joblib import Parallel, delayed
from ..externals im... | bsd-3-clause |
bert9bert/statsmodels | statsmodels/stats/mediation.py | 4 | 16140 | """
Mediation analysis
Implements algorithm 1 ('parametric inference') and algorithm 2
('nonparametric inference') from:
Imai, Keele, Tingley (2010). A general approach to causal mediation
analysis. Psychological Methods 15:4, 309-334.
http://imai.princeton.edu/research/files/BaronKenny.pdf
The algorithms are desc... | bsd-3-clause |
gengliangwang/spark | python/pyspark/pandas/missing/__init__.py | 16 | 1907 | #
# 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 |
artem279/cbrf | cbrWebService/analytics.py | 1 | 27529 | import numpy as np
from pandas import DataFrame, Series
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as s
import json
from . import cbrWebService
# cbr = cbrWebService.CreditOrgInfo()
class Metrics:
def __init__(self):
self.__cbr = cbrWebService.CreditOrgInfo()
self.__banks... | mit |
chuajiesheng/twitter-sentiment-analysis | step_4/scripts/train_sentiment_model.py | 1 | 6222 | import numpy as np
import nltk
import sklearn
import tokenizers
import multiprocessing
import itertools
import functools
import pandas as pd
import scipy
import os
import shlex
INPUT_FILE = './step_4/input/sentiment.xlsx'
CV = 10
TRAIN_SIZE = 0.8
RANDOM_SEED = 42
K_BEST = 100
SAMPLE_SIZE = 1500
dataset = pd.read_excel... | apache-2.0 |
paurichardson/trading-with-python | lib/extra.py | 77 | 2540 | '''
Created on Apr 28, 2013
Copyright: Jev Kuznetsov
License: BSD
'''
from __future__ import print_function
import sys
import urllib
import os
import xlrd # module for excel file reading
import pandas as pd
class ProgressBar:
def __init__(self, iterations):
self.iterations = iterations
... | bsd-3-clause |
pgandhi999/spark | python/pyspark/sql/functions.py | 1 | 143545 | #
# 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 |
MiniPlayer/log-island | logisland-plugins/logisland-scripting-processors-plugin/src/main/resources/nltk/draw/dispersion.py | 7 | 1744 | # Natural Language Toolkit: Dispersion Plots
#
# Copyright (C) 2001-2016 NLTK Project
# Author: Steven Bird <stevenbird1@gmail.com>
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT
"""
A utility for displaying lexical dispersion.
"""
def dispersion_plot(text, words, ignore_case=False, title="Lexic... | apache-2.0 |
derDavidT/sympy | sympy/physics/quantum/state.py | 58 | 29186 | """Dirac notation for states."""
from __future__ import print_function, division
from sympy import (cacheit, conjugate, Expr, Function, integrate, oo, sqrt,
Tuple)
from sympy.core.compatibility import u, range
from sympy.printing.pretty.stringpict import stringPict
from sympy.physics.quantum.qexpr ... | bsd-3-clause |
grandtiger/trading-with-python | lib/functions.py | 76 | 11627 | # -*- coding: utf-8 -*-
"""
twp support functions
@author: Jev Kuznetsov
Licence: GPL v2
"""
from scipy import polyfit, polyval
import datetime as dt
#from datetime import datetime, date
from pandas import DataFrame, Index, Series
import csv
import matplotlib.pyplot as plt
import numpy as np
import p... | bsd-3-clause |
sthenc/nc_packer | tools/htk_mfcc_visualize.py | 1 | 5379 | #!/usr/bin/python
import numpy as np
import matplotlib as ml
import matplotlib.pyplot as plt
import htkmfc as hm
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("filename", help="Input mfcc.htk file")
parser.add_argument("-on", "--output-norm",
help="Normalize using output mean and stddev val... | mit |
tkaitchuck/nupic | external/linux64/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... | gpl-3.0 |
crichardson17/starburst_atlas | Low_resolution_sims/Dusty_LowRes/Geneva_inst_Rot/Geneva_inst_Rot_0/fullgrid/UV2.py | 31 | 9339 | import csv
import matplotlib.pyplot as plt
from numpy import *
import scipy.interpolate
import math
from pylab import *
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import matplotlib.patches as patches
from matplotlib.path import Path
import os
# --------------------------------------------------... | gpl-2.0 |
Erotemic/ubelt | tests/test_progiter.py | 1 | 14480 | # -*- coding: utf-8 -*-
"""
pytest ubelt/tests/test_progiter.py
"""
from six.moves import cStringIO
from xdoctest.utils import strip_ansi
from ubelt.progiter import ProgIter
import sys
def test_rate_format_string():
# Less of a test than a demo
rates = [1 * 10 ** i for i in range(-10, 10)]
texts = []
... | apache-2.0 |
yonglehou/scikit-learn | sklearn/metrics/tests/test_score_objects.py | 138 | 14048 | 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 |
espenhgn/nest-simulator | pynest/examples/gap_junctions_inhibitory_network.py | 5 | 5989 | # -*- coding: utf-8 -*-
#
# gap_junctions_inhibitory_network.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 |
ellipsis14/dolfin-adjoint | tests_dolfin/ode_solver/ode_solver.py | 1 | 3453 | try:
from dolfin import BackwardEuler
except ImportError:
from dolfin import info_red
info_red("Need dolfin > 1.2.0 for ode_solver test.")
import sys; sys.exit(0)
from dolfin import *
from dolfin_adjoint import *
import ufl.algorithms
if not hasattr(MultiStageScheme, "to_tlm"):
info_red("Need dolfin > 1.2.0... | lgpl-3.0 |
davidgbe/scikit-learn | examples/model_selection/plot_train_error_vs_test_error.py | 349 | 2577 | """
=========================
Train error vs Test error
=========================
Illustration of how the performance of an estimator on unseen data (test data)
is not the same as the performance on training data. As the regularization
increases the performance on train decreases while the performance on test
is optim... | bsd-3-clause |
obreitwi/nest-simulator | pynest/examples/plot_weight_matrices.py | 17 | 6243 | # -*- coding: utf-8 -*-
#
# plot_weight_matrices.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 |
nikitasingh981/scikit-learn | examples/applications/plot_model_complexity_influence.py | 323 | 6372 | """
==========================
Model Complexity Influence
==========================
Demonstrate how model complexity influences both prediction accuracy and
computational performance.
The dataset is the Boston Housing dataset (resp. 20 Newsgroups) for
regression (resp. classification).
For each class of models we m... | bsd-3-clause |
Git3251/trading-with-python | cookbook/getDataFromYahooFinance.py | 77 | 1391 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 16 18:37:23 2011
@author: jev
"""
from urllib import urlretrieve
from urllib2 import urlopen
from pandas import Index, DataFrame
from datetime import datetime
import matplotlib.pyplot as plt
sDate = (2005,1,1)
eDate = (2011,10,1)
symbol = 'SPY'
fNa... | bsd-3-clause |
krousey/test-infra | queue_health/graph/graph.py | 5 | 16021 | #!/usr/bin/env python
# Copyright 2016 The Kubernetes Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | apache-2.0 |
mikeheddes/Intersection-Control | traffic_time.py | 1 | 3580 | # System
import re
import time
# Third party
import traci
from traci import trafficlights as tratl
from traci import vehicle as trave
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
class TrafficTime():
def setTimeTillGreen(self):
for laneID, time in self.timeTillG... | apache-2.0 |
fjxhkj/PTVS | Python/Product/ML/ProjectTemplates/ClusteringTemplate/clustering.py | 18 | 10394 | '''
This script perfoms the basic process for applying a machine learning
algorithm to a dataset using Python libraries.
The four steps are:
1. Download a dataset (using pandas)
2. Process the numeric data (using numpy)
3. Train and evaluate learners (using scikit-learn)
4. Plot and compare results... | apache-2.0 |
macruz21/trading-with-python | historicDataDownloader/historicDataDownloader.py | 77 | 4526 | '''
Created on 4 aug. 2012
Copyright: Jev Kuznetsov
License: BSD
a module for downloading historic data from IB
'''
import ib
import pandas
from ib.ext.Contract import Contract
from ib.opt import ibConnection, message
from time import sleep
import tradingWithPython.lib.logger as logger
from pandas impor... | bsd-3-clause |
toobaz/pandas | pandas/tests/io/parser/test_converters.py | 2 | 3993 | """
Tests column conversion functionality during parsing
for all of the parsers defined in parsers.py
"""
from io import StringIO
from dateutil.parser import parse
import numpy as np
import pytest
import pandas as pd
from pandas import DataFrame, Index
import pandas.util.testing as tm
def test_converters_type_must_... | bsd-3-clause |
alshedivat/tensorflow | tensorflow/contrib/learn/python/learn/estimators/__init__.py | 39 | 12688 | # 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 |
jdavidrcamacho/Tests_GP | MSc_results/speed_test7.py | 2 | 13319 | # -*- coding: utf-8 -*-
import Gedi as gedi
import george
import numpy as np; np.random.seed(17654)
import matplotlib.pylab as pl; pl.close('all')
from time import time,sleep
import emcee
import sys
##### INITIAL DATA ###########################################################
burns, runs = 1000, 2000
nrep = 5
pontos=... | mit |
jeffshek/betterself | analytics/events/tests/test_analytics.py | 1 | 5714 | import datetime
import pandas as pd
from django.test import TestCase
# python manage.py test analytics.events.tests.test_analytics
from analytics.events.analytics import DataFrameEventsAnalyzer
class DataFrameEventsAnalyzerTests(TestCase):
PRODUCTIVITY_COLUMN = 'Productivity'
NEGATIVE_PRODUCTIVITY_COLUMN = ... | mit |
raghavrv/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 26 | 5953 | """
===============================================================================
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 |
Curious72/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 |
tyarkoni/featureX | pliers/extractors/text.py | 1 | 36443 | '''
Extractors that operate primarily or exclusively on Text stimuli.
'''
import sys
import itertools
import logging
import numpy as np
import pandas as pd
import scipy
import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from pliers.stimuli.text import TextStim, ComplexTextStim
from pliers.extract... | bsd-3-clause |
pravsripad/mne-python | mne/cov.py | 4 | 79476 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Matti Hämäläinen <msh@nmr.mgh.harvard.edu>
# Denis A. Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
from copy import deepcopy
from distutils.version import LooseVersion
import itertools as itt
from math import log
import ... | bsd-3-clause |
BiaDarkia/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 21 | 26665 | """
Todo: cross-check the F-value with stats model
"""
from __future__ import division
import itertools
import warnings
import numpy as np
from scipy import stats, sparse
from numpy.testing import run_module_suite
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from... | bsd-3-clause |
Barmaley-exe/scikit-learn | examples/svm/plot_rbf_parameters.py | 35 | 8096 | '''
==================
RBF SVM parameters
==================
This example illustrates the effect of the parameters ``gamma`` and ``C`` of
the Radius Basis Function (RBF) kernel SVM.
Intuitively, the ``gamma`` parameter defines how far the influence of a single
training example reaches, with low values meaning 'far' a... | bsd-3-clause |
codevlabs/pandashells | pandashells/test/p_regress_tests.py | 7 | 3090 | #! /usr/bin/env python
import sys
import re
from mock import patch, MagicMock
from unittest import TestCase
import numpy as np
import pandas as pd
from pandashells.bin.p_regress import main
class MainTests(TestCase):
@patch(
'pandashells.bin.p_regress.sys.argv',
'p.regress -m y~x'.split())
@p... | bsd-2-clause |
wlamond/scikit-learn | examples/linear_model/plot_lasso_model_selection.py | 39 | 5425 | """
===================================================
Lasso model selection: Cross-Validation / AIC / BIC
===================================================
Use the Akaike information criterion (AIC), the Bayes Information
criterion (BIC) and cross-validation to select an optimal value
of the regularization paramet... | bsd-3-clause |
facemelters/data-science | Atlas/test-youtube2.py | 1 | 5639 | #!/usr/bin/python
from datetime import datetime, timedelta
import httplib2
import os
import sys
import pandas as pd
from pprint import pprint as pp
from apiclient.discovery import build
from apiclient.errors import HttpError
from oauth2client.client import flow_from_clientsecrets
from oauth2client.file import Storage... | gpl-2.0 |
keit0222/force-plate-analizer | openForce/force_analyzer.py | 1 | 14375 |
# coding: utf-8
import numpy as np
# Libraries necessary for visualizing
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import warnings
from scipy.signal import argrelmax,argrelmin
import matplotlib.font_manager as fm
import copy
from data_reader import DataRea... | mit |
yuyakanemoto/neural-style-loss | neural_style_loss_multi.py | 1 | 3697 | import os
import scipy.misc
import pandas as pd
from argparse import ArgumentParser
import time
from neural_style_loss import styleloss, imread
# default arguments
OUTPUT = 'output.csv'
LAYER_WEIGHT_EXP = 1
VGG_PATH = 'imagenet-vgg-verydeep-19.mat'
POOLING = 'max'
NORMALIZE = 1
VERBOSE = 1
TIMEIT = 1
def build_parse... | mit |
ccasotto/rmtk | tests/vulnerability/tests_TO_BE_CHANGED/NSP/fragility_process/test_fragility.py | 4 | 1770 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 23 11:24:59 2015
@author: chiaracasotto
"""
# Clear existing variables
def clearall():
all = [var for var in globals() if var[0] != "_"]
for var in all:
del globals()[var]
clearall()
# Import functions
import matplotlib.pyplot as plt
import numpy as np
i... | agpl-3.0 |
rhiever/tpot | tests/feature_transformers_tests.py | 3 | 2511 | from sklearn.datasets import load_iris
from tpot.builtins import CategoricalSelector, ContinuousSelector
from nose.tools import assert_equal, assert_raises
iris_data = load_iris().data
def test_CategoricalSelector():
"""Assert that CategoricalSelector works as expected."""
cs = CategoricalSelector()
X_tra... | lgpl-3.0 |
mhallett/MeDaReDa | demos/demo1/plotccys.py | 1 | 2727 | # plot10ccy.py
'''
Plot the ccy rates, and the product
'''
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import datetime
import medareda_lib
def get_conn():
return medareda_lib.get_conn()
# select count from vPrice
connpg = get_conn()
curpg = connpg.cursor()
cu... | mit |
xzh86/scikit-learn | sklearn/cross_decomposition/pls_.py | 187 | 28507 | """
The :mod:`sklearn.pls` module implements Partial Least Squares (PLS).
"""
# Author: Edouard Duchesnay <edouard.duchesnay@cea.fr>
# License: BSD 3 clause
from ..base import BaseEstimator, RegressorMixin, TransformerMixin
from ..utils import check_array, check_consistent_length
from ..externals import six
import w... | bsd-3-clause |
aleksandr-bakanov/astropy | astropy/modeling/functional_models.py | 3 | 79385 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Mathematical models."""
import numpy as np
from astropy import units as u
from astropy.units import Quantity, UnitsError
from astropy.utils.decorators import deprecated
from .core import (Fittable1DModel, Fittable2DModel,
ModelDefi... | bsd-3-clause |
fibbo/DIRAC | Core/Utilities/Graphs/CurveGraph.py | 10 | 5056 | ########################################################################
# $HeadURL$
########################################################################
""" CurveGraph represents simple line graphs with markers.
The DIRAC Graphs package is derived from the GraphTool plotting package of the
CMS/Phedex... | gpl-3.0 |
zihua/scikit-learn | sklearn/decomposition/tests/test_dict_learning.py | 46 | 9267 | import numpy as np
from sklearn.exceptions import ConvergenceWarning
from sklearn.utils import check_array
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from... | bsd-3-clause |
CoderHam/Machine_Learning_Projects | outliers/outlier_removal_regression.py | 1 | 2724 | #!/usr/bin/python
import random
import numpy
import matplotlib.pyplot as plt
import pickle
from time import time
from outlier_cleaner import outlierCleaner
### some data with outliers in it
ages = pickle.load( open("practice_outliers_ages.pkl", "r") )
net_worths = pickle.load( open("practice_outliers_net_worths.pkl"... | gpl-2.0 |
cython-testbed/pandas | pandas/core/groupby/base.py | 1 | 5184 | """
Provide basic components for groupby. These defintiions
hold the whitelist of methods that are exposed on the
SeriesGroupBy and the DataFrameGroupBy objects.
"""
import types
from pandas.util._decorators import make_signature
from pandas.core.dtypes.common import is_scalar, is_list_like
class GroupByMixin(object... | bsd-3-clause |
LiZoRN/lizorn.github.io | talks/python-workshop/code/txt/PacificRimSpider.py | 3 | 42651 | # _*_ coding: utf-8 _*_
__author__ = 'lizorn'
__date__ = '2018/4/5 19:56'
from urllib import request
from urllib.error import URLError, HTTPError
from bs4 import BeautifulSoup as bs
import re
import jieba # 分词包
import pandas as pd
import numpy #numpy计算包
import matplotlib.pyplot as plt
import matplotlib
from wordcl... | mit |
redreamality/learning-to-rank | lerot/comparison/test/evaluateData.py | 2 | 7948 | '''
Created on 15 jan. 2015
@author: Jos
'''
from datetime import datetime
import os
import matplotlib.pyplot as plt
import numpy as np
params = {
#'text.latex.preamble': r"\usepackage{lmodern}",
#'text.usetex' : True,
#'font.size' : 11,
#'font.family' : 'lmodern',
#'text.latex.unicode': True,
}
plt.rcParams.update(... | gpl-3.0 |
cmry/simple-queries | sec3_data.py | 1 | 22791 | """Scripts to run the Data Collection part of the paper."""
import json
from misc_keys import twitter_keys
import pandas as pd
from time import localtime
from time import sleep
from time import strftime
import tweepy
def log(message):
"""Print simple timestamped message log."""
entry = "{0} - {1}".format(str... | mit |
ltiao/networkx | examples/multigraph/chess_masters.py | 54 | 5146 | #!/usr/bin/env python
"""
An example of the MultiDiGraph clas
The function chess_pgn_graph reads a collection of chess
matches stored in the specified PGN file
(PGN ="Portable Game Notation")
Here the (compressed) default file ---
chess_masters_WCC.pgn.bz2 ---
contains all 685 World Chess Championship matches
from... | bsd-3-clause |
chen0031/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/offsetbox.py | 69 | 17728 | """
The OffsetBox is a simple container artist. The child artist are meant
to be drawn at a relative position to its parent. The [VH]Packer,
DrawingArea and TextArea are derived from the OffsetBox.
The [VH]Packer automatically adjust the relative postisions of their
children, which should be instances of the OffsetBo... | agpl-3.0 |
westurner/house_prices | house_prices/analysis.py | 1 | 5123 | #!/usr/bin/env python
"""
| Src: https://rhiever.github.io/tpot/examples/Boston_Example/
| Src: https://github.com/rhiever/tpot/blob/master/docs/sources/examples/Boston_Example.md
| License: GPLv3 https://github.com/rhiever/tpot/blob/master/LICENSE
"""
import json
import logging
import os
import os.path
from collecti... | bsd-3-clause |
henrykironde/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 129 | 10192 | import pickle
import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors.ball_tree import (BallTree, NeighborsHeap,
simultaneous_sort, kernel_norm,
nodeheap_sort, DTYPE, ITYPE)
from sklearn.neighbors.dis... | bsd-3-clause |
mne-tools/mne-tools.github.io | 0.22/_downloads/85d0b2d795ffd9861aeed8a9b6c1ffdc/plot_dipole_fit.py | 12 | 4835 | # -*- coding: utf-8 -*-
"""
============================================================
Source localization with equivalent current dipole (ECD) fit
============================================================
This shows how to fit a dipole :footcite:`Sarvas1987` using mne-python.
For a comparison of fits between MN... | bsd-3-clause |
kjung/scikit-learn | examples/svm/plot_rbf_parameters.py | 44 | 8096 | '''
==================
RBF SVM parameters
==================
This example illustrates the effect of the parameters ``gamma`` and ``C`` of
the Radial Basis Function (RBF) kernel SVM.
Intuitively, the ``gamma`` parameter defines how far the influence of a single
training example reaches, with low values meaning 'far' a... | bsd-3-clause |
ssaeger/scikit-learn | sklearn/ensemble/__init__.py | 153 | 1382 | """
The :mod:`sklearn.ensemble` module includes ensemble-based methods for
classification, regression and anomaly detection.
"""
from .base import BaseEnsemble
from .forest import RandomForestClassifier
from .forest import RandomForestRegressor
from .forest import RandomTreesEmbedding
from .forest import ExtraTreesCla... | bsd-3-clause |
abigailStev/stingray | stingray/crossspectrum.py | 1 | 34738 | from __future__ import division, absolute_import, print_function
import numpy as np
import scipy
import scipy.stats
import scipy.fftpack
import scipy.optimize
from stingray.lightcurve import Lightcurve
from stingray.utils import rebin_data, simon, rebin_data_log
from stingray.exceptions import StingrayError
from stin... | mit |
ashhher3/scikit-learn | sklearn/neighbors/tests/test_nearest_centroid.py | 21 | 4207 | """
Testing for the nearest centroid module.
"""
import numpy as np
from scipy import sparse as sp
from numpy.testing import assert_array_equal
from numpy.testing import assert_equal
from sklearn.neighbors import NearestCentroid
from sklearn import datasets
from sklearn.metrics.pairwise import pairwise_distances
# t... | bsd-3-clause |
khkaminska/scikit-learn | sklearn/manifold/tests/test_spectral_embedding.py | 216 | 8091 | from nose.tools import assert_true
from nose.tools import assert_equal
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
from nose.tools import assert_raises
from nose.plugins.skip import SkipTest
from sk... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/pandas/tests/frame/test_indexing.py | 7 | 104529 | # -*- coding: utf-8 -*-
from __future__ import print_function
from warnings import catch_warnings
from datetime import datetime, date, timedelta, time
from pandas.compat import map, zip, range, lrange, lzip, long
from pandas import compat
from numpy import nan
from numpy.random import randn
import pytest
import nu... | mit |
aemerick/galaxy_analysis | grackle/cooling_cell_test.py | 1 | 10203 | import matplotlib.pyplot as plt
import os
import numpy as np
import yt
from pygrackle import \
FluidContainer, \
chemistry_data, \
evolve_constant_density
from pygrackle.utilities.physical_constants import \
mass_hydrogen_cgs, \
sec_per_Myr, \
cm_per_mpc
import sys
from multiprocessing impor... | mit |
georgetown-analytics/skidmarks | bin/AggressiveTurn.py | 1 | 3643 |
# -*- coding: utf-8 -*-
###############################################################################
# Information
###############################################################################
# Created by Linwood Creekmore
# Input by Vikkram Mittal
# In partial fulfillment of the requirements for the Georget... | mit |
JsNoNo/scikit-learn | sklearn/linear_model/setup.py | 146 | 1713 | import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('linear_model', parent_package, top_path)
cblas_libs, blas_info = get_blas_info... | bsd-3-clause |
nkundiushuti/pydata2017bcn | dataset.py | 1 | 7589 | """
This file is based on DeepConvSep.
Copyright (c) 2014-2017 Marius Miron <miron.marius at gmail.com>
DeepConvSep 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 Li... | gpl-3.0 |
SuLab/RASLseqAligner | src/RASLseqAnalysis_NAR.py | 1 | 21108 |
# Libraries
import pandas as pd
import editdist
import mmap
import os
import sys
import time
import itertools
import gzip
import numpy as np
from collections import Counter
import random
# ALIGNER BLAST
def rasl_probe_blast(read_file_path, blastn_path, db_path):
"""
This function returns blast results ... | mit |
nelson-liu/scikit-learn | examples/ensemble/plot_random_forest_embedding.py | 47 | 3599 | """
=========================================================
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 |
ndingwall/scikit-learn | sklearn/linear_model/_ransac.py | 9 | 19646 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
import warnings
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..base import MultiOutputMixin
from ..utils import check_random_state, check_consistent_length
from ..utils.random import sample... | bsd-3-clause |
rahuldhote/scikit-learn | examples/linear_model/plot_sgd_penalties.py | 249 | 1563 | """
==============
SGD: Penalties
==============
Plot the contours of the three penalties.
All of the above are supported by
:class:`sklearn.linear_model.stochastic_gradient`.
"""
from __future__ import division
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def l1(xs):
return np.array([np.... | bsd-3-clause |
kn45/ClickBaits | Split.py | 1 | 1192 | #!/usr/bin/env python
import cPickle
import logging
import numpy as np
import os
import sys
from sklearn.cross_validation import StratifiedKFold
logging.basicConfig(level=logging.INFO, format="[%(levelname)s]: %(message)s")
# data_file = 'data_raw/data_cln'
# train_file = 'data_train/data_train'
# valid_file = 'data... | mit |
Michal-Fularz/decision_tree | tests/histogram_calculations.py | 2 | 1270 | import numpy as np
import skimage
import matplotlib.pyplot as plt
import sklearn.preprocessing
# this is a test function for checking different ways of calculating the histogram
def calculate_histogram(image, number_of_bins):
# different ways to calculate histogram
histogram_from_np, bins_from_np = np.histogr... | mit |
CORE-GATECH-GROUP/serpent-tools | serpentTools/utils/plot.py | 1 | 9218 | """
Utilties for assisting with plots
"""
from matplotlib import pyplot
from matplotlib.axes import Axes
from matplotlib.colors import Normalize, LogNorm
from serpentTools.messages import warning
from serpentTools.utils.docstrings import magicPlotDocDecorator
__all__ = [
'DETECTOR_PLOT_LABELS',
'DEPLETION_PL... | mit |
krez13/scikit-learn | sklearn/gaussian_process/gaussian_process.py | 17 | 34896 | # -*- coding: utf-8 -*-
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# (mostly translation, see implementation details)
# Licence: BSD 3 clause
from __future__ import print_function
import numpy as np
from scipy import linalg, optimize
from ..base import BaseEstimator, RegressorMixin
from ..metrics... | bsd-3-clause |
jreback/pandas | pandas/core/missing.py | 1 | 24498 | """
Routines for filling missing data.
"""
from functools import partial
from typing import TYPE_CHECKING, Any, List, Optional, Set, Union
import numpy as np
from pandas._libs import algos, lib
from pandas._typing import ArrayLike, Axis, DtypeObj
from pandas.compat._optional import import_optional_dependency
from pa... | bsd-3-clause |
mnwhite/HARK | ConsumptionSaving/Demos/NonDurables_During_Great_Recession.py | 1 | 11290 | """
At the onset of the Great Recession, there was a large drop (6.32%, according to FRED) in consumer
spending on non-durables. Some economists have proffered that this could be attributed to precautionary
motives-- a perceived increase in household income uncertainty induces more saving (less consumption)
to prote... | apache-2.0 |
google/prediction_framework | cfs/prepare_transactions/main.py | 1 | 12907 | # Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... | apache-2.0 |
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