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 |
|---|---|---|---|---|---|
eranchetz/nupic | examples/audiostream/audiostream_tp.py | 32 | 9991 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions ... | agpl-3.0 |
chenyyx/scikit-learn-doc-zh | examples/en/covariance/plot_outlier_detection.py | 15 | 5121 | """
==========================================
Outlier detection with several methods.
==========================================
When the amount of contamination is known, this example illustrates three
different ways of performing :ref:`outlier_detection`:
- based on a robust estimator of covariance, which is assum... | gpl-3.0 |
jjongbloets/julesTk | julesTk/view/plot.py | 1 | 3049 | """Implement a Frame with a matplotlib"""
from julesTk.view import *
import matplotlib
matplotlib.use("TkAgg")
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
from matplotlib.figure import Figure
class PlotFrame(Frame, object):
def __init__(self, parent):
super(... | mit |
jiegzhan/multi-class-text-classification-cnn-rnn | train.py | 1 | 6685 | import os
import sys
import json
import time
import shutil
import pickle
import logging
import data_helper
import numpy as np
import pandas as pd
import tensorflow as tf
from text_cnn_rnn import TextCNNRNN
from sklearn.model_selection import train_test_split
logging.getLogger().setLevel(logging.INFO)
def train_cnn_rn... | apache-2.0 |
henridwyer/scikit-learn | sklearn/utils/tests/test_sparsefuncs.py | 57 | 13752 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from numpy.testing import assert_array_almost_equal, assert_array_equal
from sklearn.datasets import make_classification
from sklearn.utils.sparsefuncs import (mean_variance_axis,
inplace_column_scale,
... | bsd-3-clause |
LeeKamentsky/CellProfiler | cellprofiler/modules/measureobjectradialdistribution.py | 1 | 41744 | """<b>Measure Object Radial Distribution</b> measures the radial distribution
of intensities within each object.
<hr>
Given an image with objects identified, this module measures the
intensity distribution from each object's center to its boundary
within a user-controlled number of bins, i.e. rings.
<p>The distribut... | gpl-2.0 |
heroxbd/SHTOOLS | examples/python/TestLegendre/TestLegendre.py | 1 | 4995 | #!/usr/bin/env python
"""
This script tests and plots all Geodesy normalized Legendre functions.
Parameters can be changed in the main function.
"""
from __future__ import absolute_import, division, print_function
import os
import sys
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
sys.pat... | bsd-3-clause |
jeffery-do/Vizdoombot | doom/lib/python3.5/site-packages/matplotlib/testing/jpl_units/__init__.py | 8 | 3266 | #=======================================================================
"""
This is a sample set of units for use with testing unit conversion
of matplotlib routines. These are used because they use very strict
enforcement of unitized data which will test the entire spectrum of how
unitized data might be used (it is... | mit |
ragnarekker/Ice-modelling | utilities/getregobsdata.py | 1 | 50189 | # -*- coding: utf-8 -*-
import datetime as dt
import requests
import os as os
import copy as cp
from icemodelling import ice as ice, constants as const
from utilities import makepickle as mp, makelogs as ml, doconversions as dc
from utilities import getmisc as gm
import setenvironment as se
import pandas as pd
__autho... | mit |
ppp2006/runbot_number0 | qbo_stereo_anaglyph/hrl_lib/src/hrl_lib/matplotlib_util.py | 3 | 8282 | #
# Copyright (c) 2009, Georgia Tech Research Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, thi... | lgpl-2.1 |
cloudera/ibis | ibis/backends/clickhouse/tests/test_operators.py | 1 | 7561 | import operator
from datetime import date, datetime
import numpy as np
import pandas as pd
import pandas.testing as tm
import pytest
import ibis
import ibis.expr.datatypes as dt
from ibis import literal as L
pytest.importorskip('clickhouse_driver')
pytestmark = pytest.mark.clickhouse
@pytest.mark.parametrize(
... | apache-2.0 |
wanggang3333/scikit-learn | sklearn/feature_extraction/text.py | 110 | 50157 | # -*- coding: utf-8 -*-
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Robert Layton <robertlayton@gmail.com>
# Jochen Wersdörfer <jochen@wersdoerfer.de>
# Roman Sinayev <roman.sinayev@gma... | bsd-3-clause |
BiaDarkia/scikit-learn | sklearn/manifold/tests/test_mds.py | 99 | 1873 | import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.manifold import mds
from sklearn.utils.testing import assert_raises
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 |
oferb/OpenTrains | webserver/opentrain/algorithm/django_examples.py | 1 | 1925 | import gtfs.models
import analysis.models
import numpy as np
from scipy import spatial
import shelve
try:
import matplotlib.pyplot as plt
except ImportError:
pass
import simplekml
import config
import itertools
import os
def print_all(route_id):
results = gtfs.models.Trip.objects.filter(route_id=route_id... | bsd-3-clause |
LxMLS/lxmls-toolkit | labs/scripts/non_linear_sequence_classifiers/exercise_2.py | 1 | 3448 |
# coding: utf-8
# ### WSJ Data
# In[ ]:
# Load Part-of-Speech data
from lxmls.readers.pos_corpus import PostagCorpusData
data = PostagCorpusData()
# ### Check Numpy and Pytorch Gradients match
# As we did with the feed-forward network, we will no implement a Recurrent Neural Network (RNN) in Pytorch. For this c... | mit |
Openergy/oplus | oplus/output_table.py | 1 | 4492 | import os
import pandas as pd
from oplus.configuration import CONF
def to_float_if_possible(s):
try:
return float(s)
except ValueError:
if s.strip() == "":
return None
else:
return s
class OutputTable:
def __init__(self, path):
if not os.path.isf... | mpl-2.0 |
tdhopper/scikit-learn | sklearn/manifold/isomap.py | 229 | 7169 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
yanboliang/spark | python/pyspark/sql/session.py | 3 | 37286 | #
# 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 |
mholtrop/Phys605 | Python/Getting_Started/CSV_Multi_Plot.py | 1 | 3996 | #!/usr/bin/env python
#
# This example expands on the CSV_Plot.py. It will open all the
# csv files that are given on the command line, and plot the data found
# in the files in a single plot.
#
import sys
import argparse
#
import os.path as path
import csv
import numpy as np # This gives numpy the shorthand np
impor... | gpl-3.0 |
kazemakase/scikit-learn | sklearn/datasets/tests/test_lfw.py | 230 | 7880 | """This test for the LFW require medium-size data dowloading and processing
If the data has not been already downloaded by running the examples,
the tests won't run (skipped).
If the test are run, the first execution will be long (typically a bit
more than a couple of minutes) but as the dataset loader is leveraging
... | bsd-3-clause |
jwcarr/flatlanders | analysis/plot.py | 1 | 16473 | from math import isinf, isnan
import matplotlib.pyplot as plt
from matplotlib import gridspec
import basics
# Colour palettes adapted from:
# http://wesandersonpalettes.tumblr.com
# https://github.com/karthik/wesanderson
# https://github.com/jiffyclub/palettable
Bottle_Rocket = ["#9B110E", "#3F5151", "#0C1707",... | mit |
NixaSoftware/CVis | venv/lib/python2.7/site-packages/pandas/tests/frame/test_join.py | 11 | 5226 | # -*- coding: utf-8 -*-
import pytest
import numpy as np
from pandas import DataFrame, Index, PeriodIndex
from pandas.tests.frame.common import TestData
import pandas.util.testing as tm
@pytest.fixture
def frame_with_period_index():
return DataFrame(
data=np.arange(20).reshape(4, 5),
columns=lis... | apache-2.0 |
COHRINT/cops_and_robots | src/cops_and_robots/helpers/visualizations.py | 1 | 3212 | from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
def plot_multisurface(X, Y, Z, ax, cmaps=None, min_alpha=0.6, **kwargs):
num_surfs = Z.shape[2]
if cmaps == None:
cmaps = ['Greys', 'Reds', 'Purples', 'Oranges', 'Greens', 'Blues',
'RdPu']
... | apache-2.0 |
mjgrav2001/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 |
lukeshingles/artistools | artistools/nonthermal.py | 1 | 13926 | #!/usr/bin/env python3
import argparse
# import glob
import math
# import re
import multiprocessing
import os
from collections import namedtuple
from functools import lru_cache
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
# import matplotlib.ticker as ticker
import pandas as pd
from astr... | mit |
sanketloke/scikit-learn | examples/cluster/plot_color_quantization.py | 297 | 3443 | # -*- coding: utf-8 -*-
"""
==================================
Color Quantization using K-Means
==================================
Performs a pixel-wise Vector Quantization (VQ) of an image of the summer palace
(China), reducing the number of colors required to show the image from 96,615
unique colors to 64, while pre... | bsd-3-clause |
bert9bert/statsmodels | examples/python/glm.py | 5 | 3979 |
## Generalized Linear Models
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
from scipy import stats
from matplotlib import pyplot as plt
# ## GLM: Binomial response data
#
# ### Load data
#
# In this example, we use the Star98 dataset which was taken with permission
# from Je... | bsd-3-clause |
CJ-Wright/scikit-beam | doc/sphinxext/tests/test_docscrape.py | 12 | 14257 | # -*- encoding:utf-8 -*-
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
from docscrape_sphinx import SphinxDocString, SphinxClassDoc
from nose.tools import *
doc_txt = '''\
numpy.multivariate_normal(mean, cov, shape=No... | bsd-3-clause |
nfoti/StarCluster | utils/scimage_11_10.py | 20 | 15705 | #!/usr/bin/env python
"""
This script is meant to be run inside of a ubuntu cloud image available at
uec-images.ubuntu.com::
$ EC2_UBUNTU_IMG_URL=http://uec-images.ubuntu.com/oneiric/current
$ wget $EC2_UBUNTU_IMG_URL/oneiric-server-cloudimg-amd64.tar.gz
or::
$ wget $EC2_UBUNTU_IMG_URL/oneiric-server-clo... | lgpl-3.0 |
zkraime/osf.io | scripts/analytics/links.py | 55 | 1227 | # -*- coding: utf-8 -*-
import os
import matplotlib.pyplot as plt
from framework.mongo import database
from website import settings
from .utils import plot_dates, mkdirp
link_collection = database['privatelink']
FIG_PATH = os.path.join(settings.ANALYTICS_PATH, 'figs', 'features')
mkdirp(FIG_PATH)
def analyze_vi... | apache-2.0 |
justacec/bokeh | bokeh/charts/builders/timeseries_builder.py | 6 | 3925 | """This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the TimeSeries chart, which provides a convenient interface for
generating different charts using series-like data by transforming the data
to a consistent format and producing renderers.
"""
# ---------... | bsd-3-clause |
stevengt/Degrees-of-Separation | degreesOfSeparation.py | 1 | 3467 |
"""These methods use SQLite to search an IMDb snapshot to
determine the degrees of separation among movies."""
import sqlite3 as sql
import sys
import Queue
import matplotlib.pyplot as plot
visitedActors = set()
visitedMovies = set()
indexByActors = dict()
indexByMovies = dict()
def graphDegrees(degreesOfSepar... | mit |
larsmans/scikit-learn | benchmarks/bench_plot_incremental_pca.py | 374 | 6430 | """
========================
IncrementalPCA benchmark
========================
Benchmarks for IncrementalPCA
"""
import numpy as np
import gc
from time import time
from collections import defaultdict
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_lfw_people
from sklearn.decomposition import Incre... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/pandas/io/date_converters.py | 10 | 1827 | """This module is designed for community supported date conversion functions"""
from pandas.compat import range, map
import numpy as np
import pandas._libs.lib as lib
def parse_date_time(date_col, time_col):
date_col = _maybe_cast(date_col)
time_col = _maybe_cast(time_col)
return lib.try_parse_date_and_ti... | mit |
jbloomlab/phydms | tests/test_omegabysite.py | 1 | 4286 | """Tests ``--omegabysite`` option to ``phydms`` on simulate data.
Written by Jesse Bloom.
"""
import os
import unittest
import subprocess
import random
import pandas
import phydmslib.file_io
import phydmslib.models
import phydmslib.simulate
from phydmslib.constants import N_NT
import pyvolve
import numpy
class tes... | gpl-3.0 |
rubikloud/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 |
liyu1990/sklearn | sklearn/gaussian_process/tests/test_gpc.py | 28 | 6061 | """Testing for Gaussian process classification """
# Author: Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Licence: BSD 3 clause
import numpy as np
from scipy.optimize import approx_fprime
from sklearn.gaussian_process import GaussianProcessClassifier
from sklearn.gaussian_process.kernels import RBF, Constant... | bsd-3-clause |
lbdreyer/cartopy | docs/source/conf.py | 1 | 11935 | # (C) British Crown Copyright 2011 - 2013, Met Office
#
# This file is part of cartopy.
#
# cartopy 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 License, or
# (at your option)... | lgpl-3.0 |
Juanlu001/aquagpusph | examples/2D/spheric_testcase9_tld/cMake/plot_m.py | 1 | 6867 | #******************************************************************************
# *
# * ** * * * * *
# * * * * * * * * * *
... | gpl-3.0 |
astocko/statsmodels | statsmodels/tsa/statespace/sarimax.py | 6 | 80033 | """
SARIMAX Model
Author: Chad Fulton
License: Simplified-BSD
"""
from __future__ import division, absolute_import, print_function
from warnings import warn
import numpy as np
from .mlemodel import MLEModel, MLEResults
from .tools import (
companion_matrix, diff, is_invertible, constrain_stationary_univariate,
... | bsd-3-clause |
lcnature/brainiak | tests/funcalign/test_srm.py | 4 | 10913 | # Copyright 2016 Intel Corporation
#
# 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... | apache-2.0 |
jseabold/statsmodels | statsmodels/tsa/filters/hp_filter.py | 4 | 3240 |
import numpy as np
from scipy import sparse
from scipy.sparse.linalg import spsolve
from statsmodels.tools.validation import array_like, PandasWrapper
def hpfilter(x, lamb=1600):
"""
Hodrick-Prescott filter.
Parameters
----------
x : array_like
The time series to filter, 1-d.
lamb : ... | bsd-3-clause |
mrcslws/nupic.research | projects/whydense/mnist/analyze_noise.py | 3 | 5135 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2019, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
pgr-me/metis_projects | 05-lights/library/_02_clean.py | 1 | 1176 | import geopandas as gpd
import pandas as pd
import pickle
# load, clean, and normalize country-level lights data
with open('data/geo/pickles/zonal_stats_c.pickle') as f:
gdf = pickle.load(f)
gdf = pd.DataFrame(gdf)
gdf = gdf.drop_duplicates(subset='WB_A3')
gdf = gdf.set_index('WB_A3')
gdf.drop(['ADMIN', 'CONTINEN... | gpl-3.0 |
Edu-Glez/Bank_sentiment_analysis | env/lib/python3.6/site-packages/pandas/tests/test_panelnd.py | 7 | 3952 | # -*- coding: utf-8 -*-
import nose
from pandas.core import panelnd
from pandas.core.panel import Panel
from pandas.util.testing import assert_panel_equal
import pandas.util.testing as tm
class TestPanelnd(tm.TestCase):
def setUp(self):
pass
def test_4d_construction(self):
with tm.assert_... | apache-2.0 |
VirusTotal/msticpy | msticpy/sectools/tiproviders/azure_sent_byoti.py | 1 | 4854 | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
Azure ... | mit |
alexlib/image_registration | examples/benchmarks_shift.py | 4 | 6045 | """
imsize map_coordinates fourier_shift
50 0.016211 0.00944495
84 0.0397182 0.0161059
118 0.077543 0.0443089
153 0.132948 0.058187
187 0.191808 0.0953341
221 0.276543 0.... | mit |
zfrenchee/pandas | pandas/tests/scalar/test_nat.py | 1 | 9659 | import pytest
from datetime import datetime, timedelta
import pytz
import numpy as np
from pandas import (NaT, Index, Timestamp, Timedelta, Period,
DatetimeIndex, PeriodIndex,
TimedeltaIndex, Series, isna)
from pandas.util import testing as tm
from pandas._libs.tslib import iNa... | bsd-3-clause |
hotpxl/nebuchadnezzar | slides_plots.py | 1 | 9381 | #!/usr/bin/env python3.4
import datetime
import math
import matplotlib.pyplot as plt
import matplotlib.dates
import numpy as np
import pandas
import statsmodels.tsa.api
import statsmodels.tsa.stattools
import stats.data
all_plots = []
def register_plot(func):
def ret(*args, **kwargs):
kwargs['func_name'] ... | mit |
1kastner/analyse_weather_data | interpolation/visualise_semivariogram.py | 1 | 4838 | """
"""
import logging
import datetime
import numpy
import pandas
from matplotlib import pyplot
import dateutil.parser
from pykrige.ok import OrdinaryKriging
import geopy
import geopy.distance
from filter_weather_data import RepositoryParameter, get_repository_parameters
from filter_weather_data.filters import Stat... | agpl-3.0 |
ilyes14/scikit-learn | sklearn/linear_model/bayes.py | 220 | 15248 | """
Various bayesian regression
"""
from __future__ import print_function
# Authors: V. Michel, F. Pedregosa, A. Gramfort
# License: BSD 3 clause
from math import log
import numpy as np
from scipy import linalg
from .base import LinearModel
from ..base import RegressorMixin
from ..utils.extmath import fast_logdet, p... | bsd-3-clause |
danieldmm/minerva | models/models_util.py | 1 | 1139 | import matplotlib.pyplot as plt
def plot_model_performance(train_loss, train_acc, train_val_loss, train_val_acc):
""" Plot model loss and accuracy through epochs. """
green = '#72C29B'
orange = '#FFA577'
with plt.xkcd():
# plot model loss
fig, ax1 = plt.subplots()
ax1.plot(ra... | gpl-3.0 |
jjaner/essentia-musicbricks | src/examples/python/experimental/beatogram.py | 10 | 26647 | #!/usr/bin/env python
# Copyright (C) 2006-2013 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 |
benoitsteiner/tensorflow | tensorflow/examples/learn/boston.py | 33 | 1981 | # 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 |
peterk87/sistr_cmd | sistr/misc/add_ref_genomes.py | 1 | 20097 | #!/usr/bin/env python
import argparse
from collections import defaultdict
import logging, shutil
import os
from subprocess import Popen
import re
from datetime import datetime
import sys
import pandas as pd
import numpy as np
from sistr.misc.reduce_to_centroid_alleles import run_allele_reduction
from sistr.sistr_cmd ... | apache-2.0 |
bendemott/Python-Shapely-Examples | shapelyAreaSearch.py | 2 | 2419 | '''
@author Ben DeMott
@file shapely_radius_plot.py
In this example we will perform an area/radius search.
We will create a bunch of points in a 2d coordinate system and then we will
create a circle or a perimeter. The we will do a search for any points that
are within the circles perimeter! :) :) :)
'''
import r... | mit |
jungla/ICOM-fluidity-toolbox | functions.py/detect_peaks.py | 2 | 6546 | from __future__ import division, print_function
import numpy as np
__author__ = "Marcos Duarte, https://github.com/demotu/BMC"
__version__ = "1.0.4"
__license__ = "MIT"
def detect_peaks(x, mph=None, mpd=1, threshold=0, edge='rising',
kpsh=False, valley=False, show=False, ax=None):
"""Detect pea... | gpl-2.0 |
NunoEdgarGub1/scikit-learn | sklearn/cluster/spectral.py | 233 | 18153 | # -*- coding: utf-8 -*-
"""Algorithms for spectral clustering"""
# Author: Gael Varoquaux gael.varoquaux@normalesup.org
# Brian Cheung
# Wei LI <kuantkid@gmail.com>
# License: BSD 3 clause
import warnings
import numpy as np
from ..base import BaseEstimator, ClusterMixin
from ..utils import check_rand... | bsd-3-clause |
rohanp/scikit-learn | sklearn/gaussian_process/tests/test_gpr.py | 28 | 11870 | """Testing for Gaussian process regression """
# Author: Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Licence: BSD 3 clause
import numpy as np
from scipy.optimize import approx_fprime
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels \
import RBF, Constan... | bsd-3-clause |
zingale/pyro2 | analysis/sedov_compare.py | 2 | 4306 | #!/usr/bin/env python3
from __future__ import print_function
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from util import io
import argparse
mpl.rcParams["text.usetex"] = True
mpl.rcParams['mathtext.fontset'] = 'cm'
mpl.rcParams['mathtext.rm'] = 'serif'
# font sizes
mpl.rcParams['fon... | bsd-3-clause |
talbarda/kaggle_predict_house_prices | Build Model.py | 1 | 2629 | import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
import pandas as pd
import sklearn.linear_model as lm
from sklearn.model_selection import learning_curve
from sklearn.metrics import accuracy_score
from sklearn.metrics import make_scorer
from sklearn.model_selection import Grid... | mit |
466152112/scikit-learn | sklearn/mixture/tests/test_gmm.py | 200 | 17427 | import unittest
import copy
import sys
from nose.tools import assert_true
import numpy as np
from numpy.testing import (assert_array_equal, assert_array_almost_equal,
assert_raises)
from scipy import stats
from sklearn import mixture
from sklearn.datasets.samples_generator import make_spd_ma... | bsd-3-clause |
Obus/scikit-learn | examples/linear_model/plot_ols.py | 220 | 1940 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Linear Regression Example
=========================================================
This example uses the only the first feature of the `diabetes` dataset, in
order to illustrate a two-dimensional plot of this regre... | bsd-3-clause |
hitszxp/scikit-learn | examples/tree/plot_tree_regression_multioutput.py | 43 | 1791 | """
===================================================================
Multi-output Decision Tree Regression
===================================================================
An example to illustrate multi-output regression with decision tree.
The :ref:`decision trees <tree>`
is used to predict simultaneously the ... | bsd-3-clause |
dsullivan7/scikit-learn | examples/applications/svm_gui.py | 287 | 11161 | """
==========
Libsvm GUI
==========
A simple graphical frontend for Libsvm mainly intended for didactic
purposes. You can create data points by point and click and visualize
the decision region induced by different kernels and parameter settings.
To create positive examples click the left mouse button; to create
neg... | bsd-3-clause |
rahuldhote/scikit-learn | sklearn/tests/test_metaestimators.py | 226 | 4954 | """Common tests for metaestimators"""
import functools
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.externals.six import iterkeys
from sklearn.datasets import make_classification
from sklearn.utils.testing import assert_true, assert_false, assert_raises
from sklearn.pipeline import Pipeline... | bsd-3-clause |
saiwing-yeung/scikit-learn | examples/linear_model/plot_theilsen.py | 100 | 3846 | """
====================
Theil-Sen Regression
====================
Computes a Theil-Sen Regression on a synthetic dataset.
See :ref:`theil_sen_regression` for more information on the regressor.
Compared to the OLS (ordinary least squares) estimator, the Theil-Sen
estimator is robust against outliers. It has a breakd... | bsd-3-clause |
sgoodm/python-distance-rasters | src/distancerasters/main.py | 1 | 4523 |
from __future__ import absolute_import
import time
import numpy as np
from affine import Affine
from scipy.spatial import cKDTree
from .utils import export_raster, convert_index_to_coords, calc_haversine_distance
def build_distance_array(raster_array, affine=None, output=None, conditional=None):
"""build distanc... | bsd-3-clause |
google-research/google-research | using_dl_to_annotate_protein_universe/hmm_baseline/hmmer_utils_test.py | 1 | 16884 | # coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | apache-2.0 |
yask123/scikit-learn | sklearn/utils/testing.py | 71 | 26178 | """Testing utilities."""
# Copyright (c) 2011, 2012
# Authors: Pietro Berkes,
# Andreas Muller
# Mathieu Blondel
# Olivier Grisel
# Arnaud Joly
# Denis Engemann
# License: BSD 3 clause
import os
import inspect
import pkgutil
import warnings
import sys
import re
import platf... | bsd-3-clause |
lukauskas/scipy | scipy/stats/_binned_statistic.py | 26 | 17723 | from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from scipy._lib.six import callable
from collections import namedtuple
__all__ = ['binned_statistic',
'binned_statistic_2d',
'binned_statistic_dd']
def binned_statistic(x, values, statistic='me... | bsd-3-clause |
wdurhamh/statsmodels | statsmodels/datasets/tests/test_utils.py | 26 | 1697 | import os
import sys
from statsmodels.datasets import get_rdataset, webuse, check_internet
from numpy.testing import assert_, assert_array_equal, dec
cur_dir = os.path.dirname(os.path.abspath(__file__))
def test_get_rdataset():
# smoke test
if sys.version_info[0] >= 3:
#NOTE: there's no way to test bo... | bsd-3-clause |
kagayakidan/scikit-learn | examples/model_selection/plot_validation_curve.py | 229 | 1823 | """
==========================
Plotting Validation Curves
==========================
In this plot you can see the training scores and validation scores of an SVM
for different values of the kernel parameter gamma. For very low values of
gamma, you can see that both the training score and the validation score are
low. ... | bsd-3-clause |
Dannnno/odo | odo/backends/tests/test_csv.py | 1 | 12718 | from __future__ import absolute_import, division, print_function
import pytest
import sys
import os
import pandas as pd
import pandas.util.testing as tm
import gzip
import datashape
from datashape import Option, string
from collections import Iterator
from odo.backends.csv import (CSV, append, convert, resource,
... | bsd-3-clause |
bfelbo/deepmoji | deepmoji/finetuning.py | 2 | 23552 | """ Finetuning functions for doing transfer learning to new datasets.
"""
from __future__ import print_function
import sys
import uuid
from time import sleep
import h5py
import math
import pickle
import numpy as np
from keras.layers.wrappers import Bidirectional, TimeDistributed
from sklearn.metrics import f1_score
... | mit |
johndpope/tensorflow | tensorflow/python/estimator/inputs/pandas_io_test.py | 89 | 8340 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
aaichsmn/tacc_stats | setup.py | 1 | 18706 | #!/usr/bin/env python
"""
Parts of this file were taken from the pyzmq project
(https://github.com/zeromq/pyzmq) which have been permitted for use under the
BSD license. Parts are from lxml (https://github.com/lxml/lxml)
"""
import os
import sys
import shutil
import warnings
import re
import ConfigParser
import multi... | lgpl-2.1 |
jcmgray/xarray | xarray/core/computation.py | 1 | 42875 | """
Functions for applying functions that act on arrays to xarray's labeled data.
"""
from __future__ import absolute_import, division, print_function
from distutils.version import LooseVersion
import functools
import itertools
import operator
from collections import Counter
import numpy as np
from . import duck_arra... | apache-2.0 |
gietal/Stocker | sandbox/udacity/1.py | 1 | 1188 | import pandas as pd
import matplotlib.pyplot as plt
def testRun():
df = pd.read_csv("data/MSFT.csv")
print df.head()
def getMaxClose(symbol):
df = pd.read_csv("data/{}.csv".format(symbol)) # read data
return df['Close'].max()
def getMeanVolume(symbol):
df = pd.read_csv("data/{}.csv".f... | mit |
gheshu/synth | src/plot.py | 1 | 1372 | import math
import matplotlib.pyplot as plt
tau = 6.2831853
pi = 3.141592
samples = 10
dphase = tau / samples
def lerp(a, b, alpha):
return (1.0 - alpha) * a + alpha * b
def saw_wave(phase):
return lerp(-1.0, 1.0, phase / tau)
def sine_wave(phase):
return math.sin(phase)
def square_wave(phase):
if phase... | apache-2.0 |
samuel1208/scikit-learn | examples/exercises/plot_cv_diabetes.py | 231 | 2527 | """
===============================================
Cross-validation on diabetes Dataset Exercise
===============================================
A tutorial exercise which uses cross-validation with linear models.
This exercise is used in the :ref:`cv_estimators_tut` part of the
:ref:`model_selection_tut` section of ... | bsd-3-clause |
YuanGunGun/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 |
CERNDocumentServer/invenio | modules/bibauthorid/lib/bibauthorid_tortoise.py | 3 | 16189 | # -*- coding: utf-8 -*-
#
# This file is part of Invenio.
# Copyright (C) 2011, 2012 CERN.
#
# Invenio 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... | gpl-2.0 |
rsignell-usgs/notebook | People/csherwood/read_garmin_gpx_calc_effort.py | 1 | 5449 |
# coding: utf-8
# # Read Garmin GPX with heartrate
#
# In[1]:
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
import pandas as pd
from lxml import etree
get_ipython().magic(u'matplotlib inline')
# In[2]:
fn = "activity_721671330.gpx"
tree = etree.parse(fn)
# In[3]:
namespace... | mit |
amitjamadagni/sympy | sympy/plotting/plot.py | 1 | 58450 | """Plotting module for Sympy.
A plot is represented by the ``Plot`` class that contains a reference to the
backend and a list of the data series to be plotted. The data series are
instances of classes meant to simplify getting points and meshes from sympy
expressions. ``plot_backends`` is a dictionary with all the bac... | bsd-3-clause |
h2educ/scikit-learn | sklearn/linear_model/tests/test_ransac.py | 216 | 13290 | import numpy as np
from numpy.testing import assert_equal, assert_raises
from numpy.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raises_regexp
from scipy import sparse
from sklearn.utils.testing import assert_less
from sklearn.linear_model import LinearRegression, RANSACRegressor
f... | bsd-3-clause |
MartinIsoz/MuPhFInCE | 00_utilities/procLogOnlineSS.py | 2 | 12534 | #!/usr/bin/python
#FILE DESCRIPTION=======================================================
#
# Simple python script to see the residuals evolution and other
# simulation characteristics of the steady state OpenFOAM runs
#
# Required:
# - file log.*Foam
# - file log.blockMesh or log.snappyHexMesh or direct specific... | gpl-2.0 |
henridwyer/scikit-learn | examples/manifold/plot_compare_methods.py | 259 | 4031 | """
=========================================
Comparison of Manifold Learning methods
=========================================
An illustration of dimensionality reduction on the S-curve dataset
with various manifold learning methods.
For a discussion and comparison of these algorithms, see the
:ref:`manifold module... | bsd-3-clause |
eclee25/flu-SDI-exploratory-age | scripts/create_fluseverity_figs_v5/ILINet_incid_time_v5.py | 1 | 4261 | #!/usr/bin/python
##############################################
###Python template
###Author: Elizabeth Lee
###Date: 11/4/14
###Function: Incidence per 100,000 vs. week number for flu weeks (wks 40-20). Incidence is per 100,000 for the US population in the second calendar year of the flu season. ILINet data
## 11/4/1... | mit |
zehpunktbarron/iOSMAnalyzer | scripts/c3_highway_actuality.py | 1 | 6584 | # -*- coding: utf-8 -*-
#!/usr/bin/python2.7
#description :This file creates a plot: Calculates the actuality of the total OSM highway. Additionally plots the first version for comparison purposes
#author :Christopher Barron @ http://giscience.uni-hd.de/
#date :19.01.2013
#version :0.1
... | gpl-3.0 |
oztalha/News-Commentary-Tweets-of-Elites | scrapers/scrape-theplazz.py | 2 | 1332 | # -*- coding: utf-8 -*-
"""
Created on Thu Jan 08 15:41:01 2015
@author: Talha
"""
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import pandas as pd
import time
#initialize variables
df = pd.DataFrame(columns=('title', 'twcount', 'href'))
driver = webdriver.Chrome()
# thePlazz.com H... | mit |
ngoix/OCRF | sklearn/gaussian_process/gaussian_process.py | 16 | 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 |
jpautom/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 |
linwoodc3/gdeltPyR | tests/test_info.py | 1 | 3552 | # #!/usr/bin/python
# # -*- coding: utf-8 -*-
#
# # Author:
# # Linwood Creekmore
# # Email: valinvescap@gmail.com
#
# ##############################
# # Standard Library Import
# ##############################
#
# import os
# from unittest import TestCase
#
# ##############################
# # Third Party Libraries
# ... | gpl-3.0 |
quasars100/Resonance_testing_scripts | alice/plotdata.py | 1 | 2845 | import matplotlib.pyplot as plt
import pylab
import numpy
import rebound
import reboundxf
from pylab import *
data = numpy.loadtxt('data.txt', unpack = True)
time = data[0]
e1 = data[1]
e2 = data[2]
pratio = data[3]
l1 = data[4]
l2 = data[5]
varpi1 = data[6]
varpi2 = data[7]
a1 = data[8]
a2 = data[9]
sumpr = 0
for i... | gpl-3.0 |
vinodkc/spark | python/pyspark/sql/session.py | 8 | 31156 | #
# 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 |
Eric89GXL/scikit-learn | sklearn/decomposition/tests/test_truncated_svd.py | 8 | 2692 | """Test truncated SVD transformer."""
import numpy as np
import scipy.sparse as sp
from sklearn.decomposition import TruncatedSVD
from sklearn.utils import check_random_state
from sklearn.utils.testing import (assert_array_almost_equal, assert_equal,
assert_raises)
# Make an X tha... | bsd-3-clause |
pwcazenave/PySeidon | pyseidon/adcpClass/plotsAdcp.py | 2 | 3698 | #!/usr/bin/python2.7
# encoding: utf-8
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.tri as Tri
import matplotlib.ticker as ticker
import seaborn
from windrose import WindroseAxes
from interpolation_utils import *
class PlotsAdcp:
"""'Plots' subset of FVCOM c... | agpl-3.0 |
hbp-unibi/SNABSuite | source/SNABs/mnist/python/mnist_view.py | 1 | 1496 | from __future__ import print_function
from keras.datasets import mnist
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
# the data, split between train and test sets
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = x_train.reshape(60000, 784)
x_test = x_test.reshape(10000, 7... | gpl-3.0 |
tomkooij/sapphire | scripts/kascade/reconstruction_efficiency.py | 1 | 14972 | from __future__ import division
import tables
import numpy as np
import pylab as plt
from scipy import optimize, stats
from sapphire.analysis import landau
import utils
from artist import GraphArtist
import artist.utils
RANGE_MAX = 40000
N_BINS = 400
LOW, HIGH = 500, 5500
VNS = .57e-3 * 2.5
USE_TEX = True
# F... | gpl-3.0 |
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