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 |
|---|---|---|---|---|---|
ondrejch/MSBR-ORNL-4528 | scripts/analyze-lattices/initlattices.py | 1 | 7150 | #!/usr/bin/python3
#
# Analysis module for MSBR lattice akin to ORNL-4528
# Ondrej Chvala, ochvala@utk.edu
# 2016-07-16
# GNU/GPL
from array import array
import matplotlib.pyplot as plt
from lattice import Lattice
beep_every = 100 # Print something every beep_ever lattices read
debug = 1 # Ver... | gpl-2.0 |
kashefy/caffe_sandbox | nideep/datasets/amfed/amfed.py | 3 | 8027 | '''
Created on Mar 28, 2017
@author: kashefy
'''
import logging
import os
import random
from collections import namedtuple
import numpy as np
import pandas as pd
import nideep.iow.file_system_utils as fs
from comparables import list_comparables
from nideep.datasets.amfed.entity import Entity
class AMFED(object):
... | bsd-2-clause |
giorgiop/scikit-learn | examples/datasets/plot_iris_dataset.py | 35 | 1929 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
The Iris Dataset
=========================================================
This data sets consists of 3 different types of irises'
(Setosa, Versicolour, and Virginica) petal and sepal
length, stored in a 150x4 numpy... | bsd-3-clause |
nesterione/scikit-learn | sklearn/neighbors/tests/test_kde.py | 208 | 5556 | import numpy as np
from sklearn.utils.testing import (assert_allclose, assert_raises,
assert_equal)
from sklearn.neighbors import KernelDensity, KDTree, NearestNeighbors
from sklearn.neighbors.ball_tree import kernel_norm
from sklearn.pipeline import make_pipeline
from sklearn.dataset... | bsd-3-clause |
mmottahedi/neuralnilm_prototype | scripts/experiment030.py | 2 | 3432 | from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
import theano
import theano.tensor as T
import lasagne
from gen_data_029 import gen_data, N_BATCH, LENGTH
theano.config.compute_test_value = 'raise'
"""
tanh output
lower learning rate
* does just about learn something sensible, but not... | mit |
axbaretto/beam | sdks/python/apache_beam/dataframe/schemas_test.py | 2 | 10543 | #
# 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 |
PubuduSaneth/genome4d | juicebox2hibrowse_v2.py | 1 | 3871 |
# coding: utf-8
# # Read juicebox dump output and reformat to 7 column format
# ## Juicebox dump output format - Input of the program
# <pre>
# chr1:start chr2:start Normalized_interactions
# 10000 10000 311.05484
# 10000 20000 92.60087
# 20000 20000 296.0056
# 10000 30000 47.701942
# </pre>
# ## 7 column format - ... | gpl-3.0 |
dvro/UnbalancedDataset | imblearn/under_sampling/instance_hardness_threshold.py | 2 | 7926 | """Class to perform under-sampling based on the instance hardness
threshold."""
from __future__ import print_function
from __future__ import division
import numpy as np
from collections import Counter
from sklearn.cross_validation import StratifiedKFold
from ..base import BaseBinarySampler
ESTIMATOR_KIND = ('knn'... | mit |
Marcdnd/electrum-cesc | plugins/plot/qt.py | 1 | 3562 | from PyQt4.QtGui import *
from electrum_cesc.plugins import BasePlugin, hook
from electrum_cesc.i18n import _
import datetime
from electrum_cesc.util import format_satoshis
from electrum_cesc.bitcoin import COIN
try:
import matplotlib.pyplot as plt
import matplotlib.dates as md
from matplotlib.patches im... | mit |
milapour/palm | palm/probability_matrix.py | 1 | 1534 | import numpy
from pandas import DataFrame
from collections import defaultdict
def make_prob_matrix_from_state_ids(index_id_collection,
column_id_collection=None):
pm = ProbabilityMatrix()
index_id_list = index_id_collection.as_list()
if column_id_collection:
colu... | bsd-2-clause |
astroML/astroML | examples/datasets/plot_nasa_atlas.py | 2 | 1674 | """
NASA Sloan Atlas
----------------
This shows some visualizations of the data from the NASA SDSS Atlas
"""
# Author: Jake VanderPlas <vanderplas@astro.washington.edu>
# License: BSD
# The figure is an example from astroML: see http://astroML.github.com
import numpy as np
from matplotlib import pyplot as plt
from... | bsd-2-clause |
OceanPARCELS/parcels | parcels/examples/example_nemo_curvilinear.py | 1 | 4599 | from argparse import ArgumentParser
from datetime import timedelta as delta
from glob import glob
from os import path
import numpy as np
import pytest
from parcels import AdvectionRK4, AdvectionAnalytical
from parcels import FieldSet
from parcels import JITParticle
from parcels import ParticleFile
from parcels import... | mit |
billy-inn/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 |
wubr2000/zipline | zipline/finance/risk/cumulative.py | 17 | 17736 | #
# Copyright 2014 Quantopian, Inc.
#
# 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 wr... | apache-2.0 |
miltonsarria/dsp-python | images/3_example1_notMNIST.py | 1 | 4584 | #Milton Orlando Sarria
#USC
#realizar una primera clasificacion
import matplotlib.pyplot as plt
import numpy as np
import os
from sklearn.linear_model import LogisticRegression
from six.moves import cPickle as pickle
from tools_dnn import *
####################################################################
#en este ... | mit |
abhitopia/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/arithmetic_transform_test.py | 62 | 2343 | # 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 |
quaquel/EMAworkbench | ema_workbench/em_framework/parameters.py | 1 | 19220 | """parameters and collections of parameters"""
import abc
import itertools
import numbers
import warnings
import pandas
import six
from .util import (NamedObject, Variable, NamedObjectMap, Counter,
NamedDict, combine)
from ..util import get_module_logger
# Created on Jul 14, 2016
#
# .. codeauthor... | bsd-3-clause |
wiso/dask | docs/source/scripts/scheduling.py | 18 | 3236 | from toolz import merge
from time import time
import dask
from dask import threaded, multiprocessing, async
from random import randint
from collections import Iterator
import matplotlib.pyplot as plt
def noop(x):
pass
nrepetitions = 1
def trivial(width, height):
""" Embarassingly parallel dask """
d = {... | bsd-3-clause |
annarev/tensorflow | tensorflow/lite/micro/kernels/vexriscv/utils/log_parser.py | 15 | 8798 | # Copyright 2020 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 |
mhvk/astropy | astropy/timeseries/tests/test_sampled.py | 11 | 16315 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
from datetime import datetime
import pytest
from numpy.testing import assert_equal, assert_allclose
from astropy.table import Table, Column
from astropy.time import Time, TimeDelta
from astropy import units as u
from astropy.units import Quantity
from ... | bsd-3-clause |
Aasmi/scikit-learn | sklearn/linear_model/tests/test_bayes.py | 299 | 1770 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.linear_model.bayes import BayesianRidge, ARDRegres... | bsd-3-clause |
rmelo19/rmelo19-arduino | python/6Sensors.py | 1 | 1995 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import serial
import time
sr = serial.Serial('/dev/ttyACM0', 115200)
time.sleep(1)
currentLine = sr.readline()
count = 0
while currentLine.find('PRESSURES: ') == -1 or count < 10:
currentLine = sr.readline()
if (currentLine.find('PRESSURES... | gpl-3.0 |
cmorgan/zipline | zipline/sources/data_frame_source.py | 26 | 5253 | #
# Copyright 2015 Quantopian, Inc.
#
# 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 wr... | apache-2.0 |
krisht/Krishna-Thesis | Research/src/runner.py | 1 | 1205 | #!/usr/bin/env python2.7
import random
import tensorflow as tf
from sklearn.svm import SVC
from BrainNet import BrainNet
alphas = [0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4]
learning_rates = [1e-1, 1e-2, 1e-3, 1e-4, 1e-5]
l2_weights = [1e-1, 1e-2, 1e-3, 1e-4, 1e-5]
batch_sizes = [500, 1000, 5000, 10000, 50000, 100000]
for run... | mit |
ch3ll0v3k/scikit-learn | examples/linear_model/plot_sgd_comparison.py | 167 | 1659 | """
==================================
Comparing various online solvers
==================================
An example showing how different online solvers perform
on the hand-written digits dataset.
"""
# Author: Rob Zinkov <rob at zinkov dot com>
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot a... | bsd-3-clause |
caisq/tensorflow | tensorflow/contrib/learn/python/learn/grid_search_test.py | 137 | 2035 | # 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 |
misgeatgit/opencog | opencog/python/spatiotemporal/demo.py | 33 | 1221 | __author__ = 'sebastian'
from spatiotemporal.temporal_events.trapezium import TemporalEventTrapezium
from spatiotemporal.temporal_events.relation_formulas import FormulaCreator
from spatiotemporal.temporal_events.composition.non_linear_least_squares import DecompositionFitter
import matplotlib.pyplot as plt
all_rel... | agpl-3.0 |
yt-project/unyt | paper/benchmark_plot.py | 1 | 6184 | import numpy as np
import perf
from collections import OrderedDict
from matplotlib import pyplot as plt
from matplotlib.patches import Patch
ALPHA_MAP = {"small": 0.3333, "medium": 0.666, "big": 1.0}
COLOR_MAP = {"unyt": "C0", "astropy": "C1", "pint": "C2"}
SIZE_LABELS = {"small": "3", "medium": "$10^3$", "big": "$10^... | bsd-3-clause |
pratapvardhan/pandas | pandas/tests/dtypes/test_common.py | 3 | 23804 | # -*- coding: utf-8 -*-
import pytest
import numpy as np
import pandas as pd
from pandas.core.dtypes.dtypes import (DatetimeTZDtype, PeriodDtype,
CategoricalDtype, IntervalDtype)
import pandas.core.dtypes.common as com
import pandas.util.testing as tm
import pandas.util._test_d... | bsd-3-clause |
DiCarloLab-Delft/PycQED_py3 | pycqed/analysis_v2/full_tomo_tfd.py | 1 | 13763 | """
Analysis for Thermal Field Double state VQE experiment
"""
import os
import matplotlib.pylab as pl
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
import numpy as np
import pycqed.analysis_v2.base_analysis as ba
from pycqed.analysis.analysis_toolbox import get_datafilepath_fro... | mit |
iiSeymour/pandashells | pandashells/test/parallel_lib_tests.py | 10 | 8652 | #! /usr/bin/env python
import sys
from unittest import TestCase
from pandashells.lib import parallel_lib
from mock import patch, MagicMock
import datetime
import multiprocessing as mp
class ParallelLibTests(TestCase):
def setUp(self):
pass
def tearDown(self):
pass
@patch('pandashells.lib... | bsd-2-clause |
hwroitzsch/BikersLifeSaver | lib/python3.5/site-packages/numpy/linalg/linalg.py | 32 | 75738 | """Lite version of scipy.linalg.
Notes
-----
This module is a lite version of the linalg.py module in SciPy which
contains high-level Python interface to the LAPACK library. The lite
version only accesses the following LAPACK functions: dgesv, zgesv,
dgeev, zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetr... | mit |
mrakgr/futhark | tools/compare-compilers.py | 1 | 3657 | #!/usr/bin/env python
#
# Quick hack to compare performance changes when you're hacking on the
# compiler.
import os
import sys
import subprocess
import matplotlib
import re
matplotlib.use('Agg') # For headless use
import numpy as np
import matplotlib.pyplot as plt
red = sys.argv[1] # first compiler
blue = sys.argv... | bsd-3-clause |
boomsbloom/dtm-fmri | DTM/for_gensim/lib/python2.7/site-packages/scipy/interpolate/_cubic.py | 37 | 29281 | """Interpolation algorithms using piecewise cubic polynomials."""
from __future__ import division, print_function, absolute_import
import numpy as np
from scipy._lib.six import string_types
from . import BPoly, PPoly
from .polyint import _isscalar
from scipy._lib._util import _asarray_validated
from scipy.linalg im... | mit |
Tong-Chen/scikit-learn | sklearn/cross_decomposition/tests/test_pls.py | 22 | 9838 | import numpy as np
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.datasets import load_linnerud
from sklearn.cross_decomposition import pls_
from nose.tools import assert_equal
def test_pls():
d = load_linnerud()
X = d.data
Y = d.target
# 1) Canonical (symmetric) PLS (PLS 2 b... | bsd-3-clause |
rhyolight/nupic.research | projects/associative_network/run_hopfield_network_experiment.py | 11 | 15603 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, 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... | gpl-3.0 |
dossier/dossier.models | dossier/models/linker/model.py | 1 | 4514 | '''Create a keyword searches from an entity profile. Given a labeled
collection of feature collections, train a classifier to identify the
entity using such as scikit-learn Bernoulli naive Bayes:
http://scikit-learn.org/stable/modules/naive_bayes.html
http://scikit-learn.org/stable/modules/generated/sklearn.naive_ba... | mit |
ZhangXinNan/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 |
dmlc/xgboost | tests/python/test_basic_models.py | 1 | 19253 | import numpy as np
import xgboost as xgb
import os
import json
import testing as tm
import pytest
import locale
import tempfile
dpath = os.path.join(tm.PROJECT_ROOT, 'demo/data/')
dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')
dtest = xgb.DMatrix(dpath + 'agaricus.txt.test')
rng = np.random.RandomState(1994)
de... | apache-2.0 |
Srisai85/scikit-learn | sklearn/cluster/tests/test_bicluster.py | 226 | 9457 | """Testing for Spectral Biclustering methods"""
import numpy as np
from scipy.sparse import csr_matrix, issparse
from sklearn.grid_search import ParameterGrid
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from... | bsd-3-clause |
Scapogo/zipline | tests/pipeline/test_column.py | 5 | 2504 | """
Tests BoundColumn attributes and methods.
"""
from contextlib2 import ExitStack
from unittest import TestCase
from pandas import date_range, DataFrame
from pandas.util.testing import assert_frame_equal
from zipline.lib.labelarray import LabelArray
from zipline.pipeline import Pipeline
from zipline.pipeline.data.t... | apache-2.0 |
yaukwankiu/armor | tests/modifiedMexicanHatTest8.py | 1 | 5809 | # modified mexican hat wavelet test.py
# spectral analysis for RADAR and WRF patterns
import os, shutil
import time
import pickle
import numpy as np
from scipy import signal, ndimage
import matplotlib.pyplot as plt
from armor import defaultParameters as dp
from armor import pattern
from armor import objects4 as ob
... | cc0-1.0 |
googleapis/python-automl | tests/system/gapic/v1beta1/test_system_tables_client_v1.py | 1 | 11353 | # -*- coding: utf-8 -*-
#
# Copyright 2019 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... | apache-2.0 |
JT5D/scikit-learn | sklearn/tests/test_qda.py | 23 | 2833 | import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_greater
from sklearn import qda
# Data is just 6 separable points in the plane
X = np.array([[0, 0... | bsd-3-clause |
lilleswing/deepchem | contrib/mpnn/mpnn.py | 5 | 5567 | # 2017 DeepCrystal Technologies - Patrick Hop
#
# Message Passing Neural Network SELU [MPNN-S] for Chemical Multigraphs
#
# MIT License - have fun!!
# ===========================================================
import math
import deepchem as dc
from rdkit import Chem, DataStructs
from rdkit.Chem import AllChem
impor... | mit |
avicorp/firstLook | src/mnist_loader.py | 1 | 4390 |
# This file contains code samples from the book:
# "Neural Networks and Deep Learning".
"""
mnist_loader
~~~~~~~~~~~~
A library to load the MNIST image data. For details of the data
structures that are returned, see the doc strings for ``load_data``
and ``load_data_wrapper``. In practice, ``load_data_wrapper`` is ... | apache-2.0 |
jorik041/scikit-learn | sklearn/tests/test_kernel_ridge.py | 342 | 3027 | import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_regression
from sklearn.linear_model import Ridge
from sklearn.kernel_ridge import KernelRidge
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils.testing import ignore_warnings
from sklearn.utils.testing import assert... | bsd-3-clause |
mjgrav2001/scikit-learn | benchmarks/bench_plot_fastkmeans.py | 294 | 4676 | from __future__ import print_function
from collections import defaultdict
from time import time
import numpy as np
from numpy import random as nr
from sklearn.cluster.k_means_ import KMeans, MiniBatchKMeans
def compute_bench(samples_range, features_range):
it = 0
results = defaultdict(lambda: [])
chun... | bsd-3-clause |
poryfly/scikit-learn | sklearn/utils/random.py | 234 | 10510 | # Author: Hamzeh Alsalhi <ha258@cornell.edu>
#
# License: BSD 3 clause
from __future__ import division
import numpy as np
import scipy.sparse as sp
import operator
import array
from sklearn.utils import check_random_state
from sklearn.utils.fixes import astype
from ._random import sample_without_replacement
__all__ =... | bsd-3-clause |
tomasreimers/tensorflow-emscripten | tensorflow/examples/learn/text_classification.py | 13 | 4967 | # 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 |
henry-ngo/VIP | vip_hci/stats/im_stats.py | 1 | 2055 | #! /usr/bin/env python
"""
Module for image statistics.
"""
from __future__ import division
__author__ = 'C. Gomez @ ULg'
__all__ = ['frame_histo_stats']
import numpy as np
from matplotlib import pyplot as plt
def frame_histo_stats(image_array, plot=True):
"""Plots a frame with a colorbar, its histogram and s... | mit |
choderalab/openpathsampling | openpathsampling/collectivevariable.py | 1 | 24671 | import openpathsampling as paths
import openpathsampling.netcdfplus.chaindict as cd
from openpathsampling.integration_tools import md, error_if_no_mdtraj
from openpathsampling.engines.openmm.tools import trajectory_to_mdtraj
from openpathsampling.netcdfplus import WeakKeyCache, \
ObjectJSON, create_to_dict, ObjectS... | lgpl-2.1 |
ky822/scikit-learn | examples/ensemble/plot_forest_importances_faces.py | 403 | 1519 | """
=================================================
Pixel importances with a parallel forest of trees
=================================================
This example shows the use of forests of trees to evaluate the importance
of the pixels in an image classification task (faces). The hotter the pixel,
the more impor... | bsd-3-clause |
energyPATHWAYS/energyPATHWAYS | energyPATHWAYS/supply_technologies.py | 1 | 21354 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 28 16:06:06 2015
@author: Ben
"""
import inspect
from datamapfunctions import Abstract
import util
import copy
import numpy as np
import config as cfg
from shared_classes import StockItem
from supply_classes import SupplySalesShare, SupplySales, SupplySpecifiedStock
impo... | mit |
JackKelly/neuralnilm_prototype | scripts/e256.py | 2 | 4031 | from __future__ import print_function, division
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import Net, RealApplianceSource, BLSTMLayer, DimshuffleLayer
from lasagne.nonlinearities import sigmoid, rectify, tanh
from lasagne.objectives import crossentrop... | mit |
cainiaocome/scikit-learn | sklearn/svm/tests/test_svm.py | 116 | 31653 | """
Testing for Support Vector Machine module (sklearn.svm)
TODO: remove hard coded numerical results when possible
"""
import numpy as np
import itertools
from numpy.testing import assert_array_equal, assert_array_almost_equal
from numpy.testing import assert_almost_equal
from scipy import sparse
from nose.tools im... | bsd-3-clause |
optbot/quotepuller | src/timing_mgr.py | 1 | 1262 | """
.. Copyright (c) 2015 Marshall Farrier
license http://opensource.org/licenses/MIT
Time to wait until next run
===========================
"""
import datetime as dt
from pandas.tseries.offsets import BDay
from pytz import timezone
def secs_to_next_run(logger, runtoday):
logger.info('determining wait time')... | mit |
Sentient07/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 |
cpcloud/arrow | python/pyarrow/tests/test_types.py | 1 | 11021 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
squirrelo/qiime | scripts/plot_semivariogram.py | 9 | 15002 | #!/usr/bin/env python
# File created on 09 Feb 2010
from __future__ import division
__author__ = "Antonio Gonzalez Pena"
__copyright__ = "Copyright 2011, The QIIME Project"
__credits__ = ["Antonio Gonzalez Pena", "Kyle Patnode", "Yoshiki Vazquez-Baeza"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "A... | gpl-2.0 |
selinerguncu/Yelp-Spatial-Analysis | maps/foliumMaps.py | 1 | 9568 | import folium
from folium import plugins
import numpy as np
import sqlite3 as sqlite
import os
import sys
import pandas as pd
#extract data from yelp DB and clean it:
DB_PATH = "/Users/selinerguncu/Desktop/PythonProjects/Fun Projects/Yelp/data/yelpCleanDB.sqlite"
conn = sqlite.connect(DB_PATH)
##################... | mit |
h2educ/scikit-learn | sklearn/decomposition/base.py | 313 | 5647 | """Principal Component Analysis Base Classes"""
# 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>
# Kyle Kastner <kastnerkyle@gmail.com>
#
# Licen... | bsd-3-clause |
mojoboss/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 |
inkenbrandt/WellApplication | wellapplication/usgs.py | 1 | 24274 | # -*- coding: utf-8 -*-
"""
Created on Sun Jan 3 00:30:36 2016
@author: p
"""
from __future__ import absolute_import, division, print_function, unicode_literals
import pandas as pd
from datetime import datetime
from pylab import rcParams
import matplotlib.pyplot as plt
import numpy as np
import requests... | mit |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/mplot3d/lines3d.py | 1 | 1346 | '''
================
Parametric Curve
================
This example demonstrates plotting a parametric curve in 3D.
'''
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt
# nodebox section
if __name__ == '__builtin__':
# were in nodebox
import ... | mit |
MartinDelzant/scikit-learn | sklearn/covariance/robust_covariance.py | 198 | 29735 | """
Robust location and covariance estimators.
Here are implemented estimators that are resistant to outliers.
"""
# Author: Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import warnings
import numbers
import numpy as np
from scipy import linalg
from scipy.stats import chi2
from . import empir... | bsd-3-clause |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/misc/patheffect_demo.py | 1 | 2340 | """
===============
Patheffect Demo
===============
"""
import matplotlib.pyplot as plt
import matplotlib.patheffects as PathEffects
import numpy as np
# nodebox section
if __name__ == '__builtin__':
# were in nodebox
import os
import tempfile
W = 800
inset = 20
size(W, 600)
plt.cla()
... | mit |
ericdill/bokeh | bokeh/charts/builder/dot_builder.py | 43 | 6160 | """This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the Dot class which lets you build your Dot charts just
passing the arguments to the Chart class and calling the proper functions.
"""
#-------------------------------------------------------------------... | bsd-3-clause |
pastas/pasta | pastas/rfunc.py | 1 | 11676 | # coding=utf-8
"""This module contains all the response functions available in Pastas.
More information on how to write a response class can be found `here
<http://pastas.readthedocs.io/en/latest/developers.html>_`.
Routines in Module
------------------
Fully supported and tested routines in this module are:
- .. c... | mit |
MadMax93/acc_sensor_rr-python | Code/Visualization.py | 1 | 9091 | __author__ = 'Maximilian Kurscheidt @MadMax93'
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as signal
import peakutils
import matplotlib.gridspec as gridspec
from peakutils.plot import plot as pplot
from matplotlib.offsetbox import AnchoredText
class Visual... | mit |
alexmojaki/blaze | blaze/compute/numpy.py | 7 | 11207 | from __future__ import absolute_import, division, print_function
import datetime
import numpy as np
from pandas import DataFrame, Series
from datashape import to_numpy, to_numpy_dtype
from numbers import Number
from ..expr import (
Reduction, Field, Projection, Broadcast, Selection, ndim,
Distinct, Sort, Tai... | bsd-3-clause |
relisher/ferretextras | updateOutput.py | 1 | 1461 | from EyeFeatureFinder import *
from FastRadialFeatureFinder import *
from SubpixelStarburstEyeFeatureFinder import *
from PipelinedFeatureFinder import *
from numpy import *
from scipy import *
from matplotlib import *
from CompositeEyeFeatureFinder import *
from FastRadialFeatureFinder import *
from threading import T... | mit |
pearsonlab/thunder | thunder/rdds/images.py | 2 | 29337 | from numpy import ndarray, arange, amax, amin, greater, size, asarray
from thunder.rdds.data import Data
from thunder.rdds.keys import Dimensions
class Images(Data):
"""
Distributed collection of images or volumes.
Backed by an RDD of key-value pairs, where the key
is an identifier and the value is ... | apache-2.0 |
HolgerPeters/scikit-learn | examples/svm/plot_custom_kernel.py | 43 | 1546 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
phbradley/tcr-dist | plot_nbrdist_distributions.py | 1 | 21549 | from basic import *
import html_colors
import tcr_distances
import util
with Parser(locals()) as p:
#p.str('args').unspecified_default().multiple().required()
p.str('clones_file').required() ##
p.int('nbrdist_percentile').default(10)
#p.float('float_arg') # --float_arg 9.6
p.flag('show') ... | mit |
ChanderG/scikit-learn | examples/feature_selection/plot_rfe_with_cross_validation.py | 226 | 1384 | """
===================================================
Recursive feature elimination with cross-validation
===================================================
A recursive feature elimination example with automatic tuning of the
number of features selected with cross-validation.
"""
print(__doc__)
import matplotlib.p... | bsd-3-clause |
untom/scikit-learn | sklearn/datasets/tests/test_svmlight_format.py | 12 | 10796 | from bz2 import BZ2File
import gzip
from io import BytesIO
import numpy as np
import os
import shutil
from tempfile import NamedTemporaryFile
from sklearn.externals.six import b
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert... | bsd-3-clause |
wasade/qiita | qiita_db/test/test_analysis.py | 1 | 22656 | from unittest import TestCase, main
from os import remove
from os.path import exists, join
from datetime import datetime
from shutil import move
from biom import load_table
import pandas as pd
from qiita_core.util import qiita_test_checker
from qiita_db.analysis import Analysis, Collection
from qiita_db.job import Jo... | bsd-3-clause |
andim/scipy | doc/source/tutorial/stats/plots/kde_plot4.py | 142 | 1457 | from functools import partial
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
def my_kde_bandwidth(obj, fac=1./5):
"""We use Scott's Rule, multiplied by a constant factor."""
return np.power(obj.n, -1./(obj.d+4)) * fac
loc1, scale1, size1 = (-2, 1, 175)
loc2, scale2, size2 = (2, ... | bsd-3-clause |
justacec/bokeh | examples/charts/file/donut_multi.py | 6 | 1394 | from bokeh.charts import Donut, show, output_file, vplot
from bokeh.sampledata.autompg import autompg
import pandas as pd
# simple examples with inferred meaning
# implied index
d1 = Donut([2, 4, 5, 2, 8])
# explicit index
d2 = Donut(pd.Series([2, 4, 5, 2, 8], index=['a', 'b', 'c', 'd', 'e']))
# given a categorica... | bsd-3-clause |
vsoch/repofish | repofish/github.py | 1 | 13634 | '''
Functions for parsing Github repositories
Copyright (c) 2016-2018 Vanessa Sochat
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 without limitation the rights
... | mit |
wasit7/recognition | pub/ss.py | 2 | 10760 | """
GNU GENERAL PUBLIC LICENSE Version 2
Created on Tue Oct 14 18:52:01 2014
@author: Wasit
"""
import numpy as np
import os
from PIL import Image
from scipy.ndimage import filters
try:
import json
except ImportError:
import simplejson as json
#1800
num_img=100
spi=5
rootdir="dataset"
mrec=64
mtran=64
margin... | gpl-2.0 |
fedspendingtransparency/data-act-broker-backend | tests/unit/dataactbroker/test_validation_helper.py | 1 | 24369 | import pandas as pd
from pandas.util.testing import assert_frame_equal
import numpy as np
import os
from dataactbroker.helpers import validation_helper
from dataactvalidator.app import ValidationManager, ValidationError
from dataactvalidator.filestreaming.csvReader import CsvReader
from dataactcore.models.validationMo... | cc0-1.0 |
wazeerzulfikar/scikit-learn | benchmarks/bench_text_vectorizers.py | 36 | 2112 | """
To run this benchmark, you will need,
* scikit-learn
* pandas
* memory_profiler
* psutil (optional, but recommended)
"""
from __future__ import print_function
import timeit
import itertools
import numpy as np
import pandas as pd
from memory_profiler import memory_usage
from sklearn.datasets import fetch_... | bsd-3-clause |
liyu1990/sklearn | doc/datasets/mldata_fixture.py | 367 | 1183 | """Fixture module to skip the datasets loading when offline
Mock urllib2 access to mldata.org and create a temporary data folder.
"""
from os import makedirs
from os.path import join
import numpy as np
import tempfile
import shutil
from sklearn import datasets
from sklearn.utils.testing import install_mldata_mock
fr... | bsd-3-clause |
nickos556/pandas-qt | pandasqt/views/CustomDelegates.py | 4 | 12642 | # -*- coding: utf-8 -*-
from pandasqt.compat import Qt, QtCore, QtGui, Signal, Slot
import numpy
from pandasqt.views.BigIntSpinbox import BigIntSpinbox
from pandasqt.models.DataFrameModel import DataFrameModel
from pandasqt.models.SupportedDtypes import SupportedDtypes
def createDelegate(dtype, column, view):
t... | mit |
microhh/microhh | cases/conservation/conservation_test.py | 5 | 7180 | import sys
import shutil
import numpy as np
import netCDF4 as nc
from matplotlib import pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
sys.path.append('../../python/')
import microhh_tools as mht
no_opts = {}
opt_mpi = {
'master': {'npx': 2, 'npy': 2}}
dict_rk = {
'rk3': {'time': {'r... | gpl-3.0 |
fredhusser/scikit-learn | examples/mixture/plot_gmm.py | 248 | 2817 | """
=================================
Gaussian Mixture Model Ellipsoids
=================================
Plot the confidence ellipsoids of a mixture of two Gaussians with EM
and variational Dirichlet process.
Both models have access to five components with which to fit the
data. Note that the EM model will necessari... | bsd-3-clause |
YinongLong/scikit-learn | examples/svm/plot_custom_kernel.py | 43 | 1546 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
Achuth17/scikit-learn | benchmarks/bench_plot_nmf.py | 206 | 5890 | """
Benchmarks of Non-Negative Matrix Factorization
"""
from __future__ import print_function
from collections import defaultdict
import gc
from time import time
import numpy as np
from scipy.linalg import norm
from sklearn.decomposition.nmf import NMF, _initialize_nmf
from sklearn.datasets.samples_generator import... | bsd-3-clause |
n-west/gnuradio-volk | gr-utils/python/utils/plot_data.py | 59 | 5818 | #
# Copyright 2007,2008,2011 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio 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, or (at your option)
# any later ve... | gpl-3.0 |
rstoneback/pysat | pysat/instruments/supermag_magnetometer.py | 2 | 32219 | # -*- coding: utf-8 -*-
"""Supports SuperMAG ground magnetometer measurements and SML/SMU indices.
Downloading is supported; please follow their rules of the road:
http://supermag.jhuapl.edu/info/?page=rulesoftheroad
Parameters
----------
platform : string
'supermag'
name : string
'magnetometer'
tag : stri... | bsd-3-clause |
loli/sklearn-ensembletrees | examples/plot_multilabel.py | 9 | 4299 | # Authors: Vlad Niculae, Mathieu Blondel
# License: BSD 3 clause
"""
=========================
Multilabel classification
=========================
This example simulates a multi-label document classification problem. The
dataset is generated randomly based on the following process:
- pick the number of labels: n ... | bsd-3-clause |
potash/scikit-learn | examples/linear_model/plot_multi_task_lasso_support.py | 102 | 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 |
ningchi/scikit-learn | examples/feature_stacker.py | 246 | 1906 | """
=================================================
Concatenating multiple feature extraction methods
=================================================
In many real-world examples, there are many ways to extract features from a
dataset. Often it is beneficial to combine several methods to obtain good
performance. Th... | bsd-3-clause |
idlead/scikit-learn | examples/linear_model/plot_sgd_iris.py | 286 | 2202 | """
========================================
Plot multi-class SGD on the iris dataset
========================================
Plot decision surface of multi-class SGD on iris dataset.
The hyperplanes corresponding to the three one-versus-all (OVA) classifiers
are represented by the dashed lines.
"""
print(__doc__)
... | bsd-3-clause |
rajat1994/scikit-learn | examples/svm/plot_custom_kernel.py | 171 | 1546 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
nrhine1/scikit-learn | examples/ensemble/plot_adaboost_multiclass.py | 354 | 4124 | """
=====================================
Multi-class AdaBoosted Decision Trees
=====================================
This example reproduces Figure 1 of Zhu et al [1] and shows how boosting can
improve prediction accuracy on a multi-class problem. The classification
dataset is constructed by taking a ten-dimensional ... | bsd-3-clause |
lucidfrontier45/scikit-learn | sklearn/feature_selection/tests/test_rfe.py | 5 | 3077 | """
Testing Recursive feature elimination
"""
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
from nose.tools import assert_equal
from scipy import sparse
from sklearn.feature_selection.rfe import RFE, RFECV
from sklearn.datasets import load_iris
from sklearn.metrics import ... | bsd-3-clause |
anaderi/lhcb_trigger_ml | hep_ml/experiments/fasttree.py | 1 | 20043 | """
This is fast version of DecisionTreeRegressor for only one target function.
(This is the most simple case, but even multi-class boosting doesn't need more complicated things)
I need numpy implementation mostly for further experiments, rather than for real speedup.
This tree shouldn't be used by itself, only in boo... | mit |
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