repo_name stringlengths 6 96 | path stringlengths 4 191 | copies stringclasses 322
values | size stringlengths 4 6 | content stringlengths 762 753k | license stringclasses 15
values |
|---|---|---|---|---|---|
aestrivex/ielu | ielu/plotting_utils.py | 1 | 6230 |
import os
import numpy as np
import nibabel as nib
from traits.api import HasTraits, Float, Int, Tuple
from traitsui.api import View, Item, CSVListEditor
from .geometry import get_vox2rasxfm, apply_affine, get_std_orientation
from .utils import get_subjects_dir
def force_render( figure=None ):
from mayavi impor... | gpl-3.0 |
albu5/deepGroup | group-detection/vis_kernel_affinity.py | 1 | 6897 |
"""
Visualize and save group detections
"""
from utils import read_cad_frames, read_cad_annotations, get_interaction_features, add_annotation, custom_interaction_features
from matplotlib import pyplot as plt
from keras.models import Model
from keras.layers import Input, Dense
from keras.layers.merge import add
from k... | mit |
MohammedWasim/scikit-learn | sklearn/linear_model/tests/test_base.py | 101 | 12205 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.linear_model.... | bsd-3-clause |
ibell/coolprop | wrappers/Python/CoolProp/Plots/PsychChart.py | 1 | 5652 | """
This file implements a psychrometric chart for air at 1 atm
"""
import CoolProp
HAProps = CoolProp.HumidAirProp.HAProps
InlineLabel = CoolProp.Plots.Plots.InlineLabel
import matplotlib, numpy, textwrap
import_template=(
"""
import numpy, matplotlib
from CoolProp.HumidAirProp import HAProps
from CoolProp.Plots.Plo... | mit |
ulno/micropython-extra-ulno | examples/plot_log/liveplot2d.py | 2 | 4391 | #!/usr/bin/env python3
# tail a file into a plot
#
# take parameter of filename
#
# Resources:
# - http://stackoverflow.com/questions/11874767/real-time-plotting-in-while-loop-with-matplotlib
# - from: https://lethain.com/tailing-in-python/
#
# Author: ulno
# Create date: 2017-04-30
#
import time
from optparse import ... | mit |
henriquemiranda/yambo-py | tutorial/mos2/proj_mos2.py | 2 | 2428 | from __future__ import print_function, division
#
# Author: Henrique Pereira Coutada Miranda
# Example script to plot the weigth of the atomic species in the bandstructure
#
from qepy import *
import sys
import argparse
import matplotlib.pyplot as plt
folder = 'bands'
npoints = 20
p = Path([ [[0.0, 0.0, 0.0],'G'],
... | bsd-3-clause |
Ichaelus/Github-Classifier | Application/Models/ClassificationModules/metaonlyrandomforest.py | 1 | 2706 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from Models.FeatureProcessing import *
import sklearn
from sklearn.ensemble import RandomForestClassifier
import numpy as np
import abc
from ClassificationModule import ClassificationModule
class metaonlyrandomforest(ClassificationModule):
"""A basic Random Forest ... | mit |
NicovincX2/Python-3.5 | Analyse (mathématiques)/Analyse numérique/Équations différentielles numériques/Méthode des éléments finis/hpfem2d.py | 1 | 6104 | # -*- coding: utf-8 -*-
"""
Program for generating 2D hp finite element trial functions and their
derivatives
Copyright (C) 2013 Greg von Winckel
This program 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... | gpl-3.0 |
voxlol/scikit-learn | sklearn/utils/__init__.py | 132 | 14185 | """
The :mod:`sklearn.utils` module includes various utilities.
"""
from collections import Sequence
import numpy as np
from scipy.sparse import issparse
import warnings
from .murmurhash import murmurhash3_32
from .validation import (as_float_array,
assert_all_finite,
... | bsd-3-clause |
tgy/facedetect | script/plot_mblbp.py | 1 | 2423 | #!/usr/bin/env python3
'''Visualize randomly chosen mblbp features in a given window'''
import random
import os
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.animation as animation
import matplotlib.image as mpimg
from PIL import Image
COLORS = ['#1a535c', '#4ecdc4', '#ff6b6... | mit |
cmap/cmapPy | cmapPy/math/tests/test_fast_cov.py | 1 | 17355 | import unittest
import logging
import cmapPy.pandasGEXpress.setup_GCToo_logger as setup_logger
import cmapPy.math.fast_cov as fast_cov
import numpy
import tempfile
import os
logger = logging.getLogger(setup_logger.LOGGER_NAME)
class TestFastCov(unittest.TestCase):
@staticmethod
def build_standard_x_y():
... | bsd-3-clause |
drpngx/tensorflow | tensorflow/contrib/learn/python/learn/estimators/dnn_test.py | 30 | 60826 | # 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 |
ibayer/fastFM-fork | fastFM/validation.py | 1 | 10668 | # Static versions of non-core sklearn.utils functions.
# Placed here since they are subject to change.
"""Utilities for input validation"""
# Authors: Olivier Grisel
# Gael Varoquaux
# Andreas Mueller
# Lars Buitinck
# Alexandre Gramfort
# Nicolas Tresegnie
# License: BSD ... | bsd-3-clause |
Akshay0724/scikit-learn | sklearn/utils/testing.py | 29 | 25405 | """Testing utilities."""
# Copyright (c) 2011, 2012
# Authors: Pietro Berkes,
# Andreas Muller
# Mathieu Blondel
# Olivier Grisel
# Arnaud Joly
# Denis Engemann
# Giorgio Patrini
# Thierry Guillemot
# License: BSD 3 clause
import os
import inspect
import p... | bsd-3-clause |
abimannans/scikit-learn | sklearn/cluster/tests/test_hierarchical.py | 230 | 19795 | """
Several basic tests for hierarchical clustering procedures
"""
# Authors: Vincent Michel, 2010, Gael Varoquaux 2012,
# Matteo Visconti di Oleggio Castello 2014
# License: BSD 3 clause
from tempfile import mkdtemp
import shutil
from functools import partial
import numpy as np
from scipy import sparse
from... | bsd-3-clause |
colour-science/colour | colour/plotting/tm3018/tests/test_report.py | 1 | 3449 | # -*- coding: utf-8 -*-
"""
Defines the unit tests for the :mod:`colour.plotting.tm3018.report` module.
"""
import unittest
from matplotlib.pyplot import Axes, Figure
from colour.colorimetry import SDS_ILLUMINANTS
from colour.plotting.tm3018.report import (
plot_single_sd_colour_rendition_report_full,
plot_si... | bsd-3-clause |
nrjl/GPN | plot_statruns.py | 1 | 1555 | import numpy as np
import matplotlib.pyplot as plt
import pickle
from Tkinter import Tk
from tkFileDialog import askopenfilename, askdirectory
from test_data import ObsObject
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
data_dir = askdirectory() # show an "Open" dialog box and ret... | mit |
jm-begon/scikit-learn | examples/cluster/plot_agglomerative_clustering_metrics.py | 402 | 4492 | """
Agglomerative clustering with different metrics
===============================================
Demonstrates the effect of different metrics on the hierarchical clustering.
The example is engineered to show the effect of the choice of different
metrics. It is applied to waveforms, which can be seen as
high-dimens... | bsd-3-clause |
anurag313/scikit-learn | sklearn/kernel_ridge.py | 155 | 6545 | """Module :mod:`sklearn.kernel_ridge` implements kernel ridge regression."""
# Authors: Mathieu Blondel <mathieu@mblondel.org>
# Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# License: BSD 3 clause
import numpy as np
from .base import BaseEstimator, RegressorMixin
from .metrics.pairwise import pairwise... | bsd-3-clause |
nomadcube/scikit-learn | sklearn/manifold/locally_linear.py | 206 | 25061 | """Locally Linear Embedding"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) INRIA 2011
import numpy as np
from scipy.linalg import eigh, svd, qr, solve
from scipy.sparse import eye, csr_matrix
from ..base import B... | bsd-3-clause |
boland1992/SeisSuite | seissuite/spectrum/S_spectrum.py | 6 | 14461 | # -*- coding: utf-8 -*-
"""
Created on Fri July 6 11:04:03 2015
@author: boland
"""
import os
import glob
import scipy
import datetime
import numpy as np
import datetime as dt
import multiprocessing as mp
import matplotlib.pyplot as plt
from numpy.lib.stride_tricks import as_strided
from numpy.fft import rfft, irfft
... | gpl-3.0 |
Moriadry/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/feeding_queue_runner_test.py | 62 | 5053 | # 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 |
psychopy/versions | psychopy/data/utils.py | 1 | 23574 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
# from future import standard_library
# standard_library.install_aliases()
from builtins import str
from builtins import range
from past.builtins import basestring
import os
import re
import ast
import pickl... | gpl-3.0 |
mne-tools/mne-python | mne/cov.py | 4 | 79191 | # 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 |
moonbury/notebooks | github/MasteringMLWithScikit-learn/8365OS_04_Codes/reuters.py | 3 | 1368 | __author__ = 'gavin'
import glob
from scipy.sparse import vstack
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.linear_model import LogisticRegression
# Create X and raw y
X = None
labels_for_all_instances = []
vectorizer = HashingVectorizer()
d = {d[0]: d[1:] for d in [l.strip()[9:].split(... | gpl-3.0 |
hsuantien/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 |
Ecotrust/madrona-priorities | util/test_scenarios.py | 3 | 6555 | from django.core.management import setup_environ
import os
import sys
sys.path.append(os.path.dirname(os.path.join('..','priorities',__file__)))
import settings
setup_environ(settings)
#==================================#
from seak.models import Scenario, ConservationFeature, PlanningUnit, Cost, PuVsCf, PuVsCost
from ... | bsd-3-clause |
rueckstiess/dopamine | scripts/cart_bas_rbf.py | 1 | 1405 | from dopamine.environments import CartPoleEnvironment, CartPoleRenderer
from dopamine.agents import BASAgent, RBFEstimator, NNEstimator
from dopamine.experiments import Experiment
from dopamine.adapters import EpsilonGreedyExplorer, NormalizingAdapter, IndexingAdapter
from matplotlib import pyplot as plt
from numpy im... | gpl-3.0 |
JazzeYoung/VeryDeepAutoEncoder | pylearn2/pylearn2/sandbox/cuda_convnet/bench.py | 44 | 3589 | __authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"
from pylearn2.testing.skip import skip_if_no_gpu
skip_if_no_gpu()
import numpy as np
from theano.... | bsd-3-clause |
RomainSabathe/kaggle_airbnb2015 | Code/enhance_data.py | 1 | 5756 | import pandas as pd
import numpy as np
""" SETTINGS """
is_training_data = True
complete_enhancing = True
""" CODE """
""" Recovering the data """
if complete_enhancing:
type_of_data = 'base'
else:
type_of_data = 'enhanced'
if is_training_data:
dataname = 'learning_data'
else:
dataname = 'testing_data... | mit |
fmfn/UnbalancedDataset | examples/over-sampling/plot_comparison_over_sampling.py | 2 | 10842 | """
==============================
Compare over-sampling samplers
==============================
The following example attends to make a qualitative comparison between the
different over-sampling algorithms available in the imbalanced-learn package.
"""
# Authors: Guillaume Lemaitre <g.lemaitre58@gmail.com>
# License... | mit |
benjaminpope/pysco | kergain_sim_disk.py | 2 | 15139 | import numpy as np
import matplotlib.pyplot as plt
import pysco
from pysco.core import *
import fitsio
from time import time as clock
from old_diffract_tools import *
import pymultinest
from pysco.diffract_tools import shift_image_ft
from pysco.common_tasks import shift_image
from swiftmask import swiftpupil
import ... | gpl-3.0 |
NunoEdgarGub1/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/image.py | 69 | 28764 | """
The image module supports basic image loading, rescaling and display
operations.
"""
from __future__ import division
import os, warnings
import numpy as np
from numpy import ma
from matplotlib import rcParams
from matplotlib import artist as martist
from matplotlib import colors as mcolors
from matplotlib import... | gpl-3.0 |
rgommers/statsmodels | statsmodels/sandbox/distributions/otherdist.py | 33 | 10145 | '''Parametric Mixture Distributions
Created on Sat Jun 04 2011
Author: Josef Perktold
Notes:
Compound Poisson has mass point at zero
http://en.wikipedia.org/wiki/Compound_Poisson_distribution
and would need special treatment
need a distribution that has discrete mass points and contiuous range, e.g.
compound Pois... | bsd-3-clause |
eramirem/astroML | doc/sphinxext/exfile.py | 3 | 4259 | """
Execfile is a tool that enables open a python script, extracting the
file-level docstring, executing the file, and saving the resulting
matplotlib figures.
"""
from __future__ import print_function, division
import sys
import os
import traceback
import token
import tokenize
import gc
import matplotlib
matplotlib.... | bsd-2-clause |
trungnt13/scikit-learn | examples/ensemble/plot_random_forest_embedding.py | 286 | 3531 | """
=========================================================
Hashing feature transformation using Totally Random Trees
=========================================================
RandomTreesEmbedding provides a way to map data to a
very high-dimensional, sparse representation, which might
be beneficial for classificati... | bsd-3-clause |
georgid/SourceFilterContoursMelody | smstools/software/models_interface/hprModel_function.py | 1 | 3840 | # function to call the extractHarmSpec analysis/synthesis functions in software/models/hprModel.py
import numpy as np
import matplotlib.pyplot as plt
import os, sys
from scipy.signal import get_window
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../models/'))
import utilFunctions as UF
im... | gpl-3.0 |
miloharper/neural-network-animation | matplotlib/tests/test_delaunay.py | 14 | 7090 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange
import warnings
import numpy as np
from matplotlib.testing.decorators import image_comparison, knownfailureif
from matplotlib.cbook import MatplotlibDeprecationWarning
... | mit |
jseabold/scikit-learn | examples/exercises/plot_cv_digits.py | 135 | 1223 | """
=============================================
Cross-validation on Digits Dataset Exercise
=============================================
A tutorial exercise using Cross-validation with an SVM on the Digits dataset.
This exercise is used in the :ref:`cv_generators_tut` part of the
:ref:`model_selection_tut` section... | bsd-3-clause |
nyu-dl/dl4mt-simul-trans | insepection.py | 1 | 9509 | # -*- coding: utf-8 -*-
import matplotlib
# matplotlib.use('agg')
import copy
import numpy
import os
import seaborn as sns
import pandas as pd
sns.set(context="paper", font="monospace", style='whitegrid')
from matplotlib import pyplot as plot
from matplotlib import rc
rc('font',**{'family':'Verdana', 'weight': 'normal... | bsd-3-clause |
kjs73/pele | playground/plate_folding/geometric_folding.py | 5 | 10127 | from itertools import izip
import numpy as np
from pele.angleaxis import RBTopology, RBSystem, RigidFragment, RBPotentialWrapper
from pele.potentials import BasePotential
from pele.utils import rotations
from plate_potential import PlatePotential
EDGE1_TYPE = "O"
EDGE2_TYPE = "C"
EDGE3_TYPE = "N"
OTHER_TYPE = "H"
... | gpl-3.0 |
bowenliu16/deepchem | deepchem/models/sklearn_models/__init__.py | 3 | 2360 | """
Code for processing datasets using scikit-learn.
"""
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import LogisticRegression
from sklearn.linear_model import LinearRegression
from sklearn.linear_model import RidgeC... | gpl-3.0 |
vortex-ape/scikit-learn | examples/decomposition/plot_pca_iris.py | 32 | 1516 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
PCA example with Iris Data-set
=========================================================
Principal Component Analysis applied to the Iris dataset.
See `here <https://en.wikipedia.org/wiki/Iris_flower_data_set>`_ f... | bsd-3-clause |
eteq/bokeh | bokeh/charts/builder/histogram_builder.py | 43 | 9142 | """This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the Histogram class which lets you build your histograms just passing
the arguments to the Chart class and calling the proper functions.
"""
#-------------------------------------------------------------... | bsd-3-clause |
aminert/scikit-learn | examples/hetero_feature_union.py | 288 | 6236 | """
=============================================
Feature Union with Heterogeneous Data Sources
=============================================
Datasets can often contain components of that require different feature
extraction and processing pipelines. This scenario might occur when:
1. Your dataset consists of hetero... | bsd-3-clause |
Wyliodrin/wyliodrin-app-server | source/libraries/notebook/loader.py | 1 | 3374 | import sys
import json
import os
import traceback
import types
import redis
wyliodrin_redis = redis.StrictRedis ()
#import matplotlib
#matplotlib.use ('Agg')
from pygments import highlight
from pygments.formatters import HtmlFormatter
from pygments.lexers import PythonTracebackLexer
wyliodrin_formatter = HtmlFor... | gpl-3.0 |
beepee14/scikit-learn | examples/model_selection/grid_search_digits.py | 227 | 2665 | """
============================================================
Parameter estimation using grid search with cross-validation
============================================================
This examples shows how a classifier is optimized by cross-validation,
which is done using the :class:`sklearn.grid_search.GridSearc... | bsd-3-clause |
CuchulainX/featherweight.light | fit_camera.py | 3 | 4000 | #!/usr/bin/python
# Copyright 2011 Google Inc. 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 a... | apache-2.0 |
nburn42/tensorflow | tensorflow/examples/learn/text_classification_cnn.py | 21 | 5221 | # 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 |
antgonza/qiime | tests/test_make_2d_plots.py | 15 | 13517 | #!/usr/bin/env python
# file test_make_2d_plots.py
__author__ = "Jesse Stombaugh"
__copyright__ = "Copyright 2011, The QIIME Project" # consider project name
# remember to add yourself
__credits__ = ["Jesse Stombaugh", "Jose Antonio Navas Molina"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Jesse ... | gpl-2.0 |
johankaito/fufuka | graph-tool/src/graph_tool/draw/graphviz_draw.py | 2 | 24109 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
#
# graph_tool -- a general graph manipulation python module
#
# Copyright (C) 2006-2015 Tiago de Paula Peixoto <tiago@skewed.de>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by... | apache-2.0 |
hajicj/MUSCIMarker | MUSCIMarker/syntax/dependency_parsers.py | 1 | 11720 | """This module implements a class that..."""
from __future__ import print_function, unicode_literals
from builtins import object
import collections
import logging
import numpy
from muscima.cropobject import cropobject_distance
from muscima.graph import find_beams_incoherent_with_stems
from muscima.inference_engine_co... | apache-2.0 |
elkingtonmcb/scikit-learn | sklearn/linear_model/sag.py | 64 | 9815 | """Solvers for Ridge and LogisticRegression using SAG algorithm"""
# Authors: Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
#
# Licence: BSD 3 clause
import numpy as np
import warnings
from ..utils import ConvergenceWarning
from ..utils import check_array
from .base import make_dataset
from .sgd_fast import Log, Squ... | bsd-3-clause |
decvalts/cartopy | lib/cartopy/examples/eyja_volcano.py | 1 | 1831 | # -*- coding: utf-8 -*-
"""
Map tile acquisition
--------------------
Demonstrates cartopy's ability to draw map tiles which are downloaded on
demand from the Stamen tile server. Internally these tiles are then combined
into a single image and displayed in the cartopy GeoAxes.
"""
__tags__ = ["Scalar data"]
import m... | gpl-3.0 |
davidam/python-examples | scikit/text-classifier-example.py | 1 | 2200 | import sklearn
import numpy as np
from glob import glob
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.linear_model import SGDClassifier
from sklearn i... | gpl-3.0 |
dhhjx880713/GPy | doc/source/conf.py | 4 | 12135 | # -*- coding: utf-8 -*-
#
# GPy documentation build configuration file, created by
# sphinx-quickstart on Fri Sep 18 18:16:28 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All c... | bsd-3-clause |
zhenv5/scikit-learn | sklearn/tests/test_common.py | 70 | 7717 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
from __future__ import print_function
import os
import warnings
import sys
import pkgutil
from sklearn.externals.six import PY3
fr... | bsd-3-clause |
chenyyx/scikit-learn-doc-zh | examples/en/feature_selection/plot_feature_selection.py | 53 | 2840 | """
===============================
Univariate Feature Selection
===============================
An example showing univariate feature selection.
Noisy (non informative) features are added to the iris data and
univariate feature selection is applied. For each feature, we plot the
p-values for the univariate feature s... | gpl-3.0 |
iproduct/course-social-robotics | 11-dnn-keras/venv/Lib/site-packages/pandas/core/internals/concat.py | 1 | 20709 | from collections import defaultdict
import copy
from typing import TYPE_CHECKING, Any, Dict, List, Sequence, Tuple, cast
import numpy as np
from pandas._libs import NaT, internals as libinternals
from pandas._typing import DtypeObj, Shape
from pandas.util._decorators import cache_readonly
from pandas.core.dtypes.cas... | gpl-2.0 |
fergalbyrne/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/__init__.py | 72 | 2225 |
import matplotlib
import inspect
import warnings
# ipython relies on interactive_bk being defined here
from matplotlib.rcsetup import interactive_bk
__all__ = ['backend','show','draw_if_interactive',
'new_figure_manager', 'backend_version']
backend = matplotlib.get_backend() # validates, to match all_bac... | agpl-3.0 |
justacec/bokeh | bokeh/charts/glyphs.py | 3 | 36943 | from __future__ import absolute_import, division
from collections import defaultdict
import numpy as np
import pandas as pd
from six import iteritems
from bokeh.charts import DEFAULT_PALETTE
from bokeh.core.enums import DashPattern
from bokeh.models.glyphs import Rect, Segment, Line, Patches, Arc
from bokeh.models.r... | bsd-3-clause |
bestwpw/BDA_py_demos | demos_ch10/demo10_2.py | 19 | 1606 | """Bayesian data analysis
Chapter 10, demo 2
Importance sampling example
"""
from __future__ import division
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
# edit default plot settings (colours from colorbrewer2.org)
plt.rc('font', size=14)
plt.rc('lines', color='#377eb8', linewidth=2, m... | gpl-3.0 |
thp44/delphin_6_automation | data_process/wp6_run/sim_reports/utils.py | 1 | 7429 | __author__ = "Christian Kongsgaard"
__license__ = 'MIT'
# -------------------------------------------------------------------------------------------------------------------- #
# IMPORTS
# Modules
import os
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = [10, 5]
import datetime
fro... | mit |
TengdaHan/Convolutional_Sketch_Inversion | src/utils/simple_utils.py | 1 | 1499 | import matplotlib.pyplot as plt
import numpy as np
def plot_batch_train(model, img_size, batch_size, sketch, color, epoch, idx, tag, nb_img=5):
img_sketch = np.array(sketch[0:nb_img])
img_color = np.array(color[0:nb_img])
img_gen = model.predict(sketch, batch_size=batch_size)[0][0:nb_img]
for i in ran... | mit |
wdurhamh/statsmodels | examples/python/tsa_filters.py | 34 | 4559 |
## Time Series Filters
from __future__ import print_function
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
dta = sm.datasets.macrodata.load_pandas().data
index = pd.Index(sm.tsa.datetools.dates_from_range('1959Q1', '2009Q3'))
print(index)
dta.index = index
del dta['year']
del... | bsd-3-clause |
great-expectations/great_expectations | great_expectations/cli/datasource.py | 1 | 28903 | import enum
import logging
import os
import sys
from typing import Optional, Union
import click
from great_expectations import DataContext
from great_expectations.cli import toolkit
from great_expectations.cli.pretty_printing import cli_message, cli_message_dict
from great_expectations.cli.util import verify_library_... | apache-2.0 |
pratapvardhan/pandas | scripts/find_undoc_args.py | 5 | 5098 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Script that compares the signature arguments with the ones in the docsting
and returns the differences in plain text or GitHub task list format.
Usage::
$ ./find_undoc_args.py (see arguments below)
"""
from __future__ import print_function
import sys
from collecti... | bsd-3-clause |
azogue/enerpi | enerpi/database.py | 1 | 9124 | # -*- coding: utf-8 -*-
"""
ENERPI - Database methods:
- Get/Init/Update ENERPI data catalog
- Process or clear log files
- Method for appending raw data to ENERPI catalog from the ENERPI Logger
...
"""
import datetime as dt
import os
import pandas as pd
from time import time
import re
from enerpi.base import CONFIG,... | mit |
DavidJahn86/terapy | spectroComparism.py | 1 | 7513 | #!/usr/bin/env python
'''
SNR Plot in FD&TD, DR Plot in FD&TD, TD with u for reference files from two different spectrometers/runs
'''
import argparse
import sys
import matplotlib.pyplot as plt
import glob
import Terapy
import TeraData
from matplotlib2tikz import save as tikz_save
plt.rc('text',usetex=True)
parser =... | gpl-2.0 |
bgris/ODL_bgris | lib/python3.5/site-packages/matplotlib/testing/jpl_units/UnitDblFormatter.py | 23 | 1485 | #===========================================================================
#
# UnitDblFormatter
#
#===========================================================================
"""UnitDblFormatter module containing class UnitDblFormatter."""
#==========================================================================... | gpl-3.0 |
anntzer/scikit-learn | sklearn/neural_network/_multilayer_perceptron.py | 8 | 56999 | """Multi-layer Perceptron
"""
# Authors: Issam H. Laradji <issam.laradji@gmail.com>
# Andreas Mueller
# Jiyuan Qian
# License: BSD 3 clause
import numpy as np
from abc import ABCMeta, abstractmethod
import warnings
import scipy.optimize
from ..base import BaseEstimator, ClassifierMixin, Regressor... | bsd-3-clause |
LoLab-VU/pymc | pymc/diagnostics.py | 3 | 5373 | """Convergence diagnostics and model validation"""
import numpy as np
from .stats import autocorr, autocov, statfunc
from copy import copy
__all__ = ['geweke', 'gelman_rubin', 'trace_to_dataframe']
@statfunc
def geweke(x, first=.1, last=.5, intervals=20):
"""Return z-scores for convergence diagnostics.
Com... | apache-2.0 |
sid88in/incubator-airflow | airflow/hooks/druid_hook.py | 6 | 6122 | # -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
#... | apache-2.0 |
amolkahat/pandas | pandas/tests/io/json/test_compression.py | 3 | 4389 | import pytest
import pandas as pd
import pandas.util.testing as tm
import pandas.util._test_decorators as td
from pandas.util.testing import assert_frame_equal, assert_raises_regex
def test_compression_roundtrip(compression):
df = pd.DataFrame([[0.123456, 0.234567, 0.567567],
[12.32112, 12... | bsd-3-clause |
nelson-liu/scikit-learn | sklearn/decomposition/tests/test_sparse_pca.py | 160 | 6028 | # Author: Vlad Niculae
# License: BSD 3 clause
import sys
import numpy as np
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import ass... | bsd-3-clause |
mhue/scikit-learn | examples/linear_model/plot_ridge_path.py | 254 | 1655 | """
===========================================================
Plot Ridge coefficients as a function of the regularization
===========================================================
Shows the effect of collinearity in the coefficients of an estimator.
.. currentmodule:: sklearn.linear_model
:class:`Ridge` Regressi... | bsd-3-clause |
rjenc29/numerical | tests/test_ewma.py | 1 | 1275 | import pandas as pd
import numpy as np
from utilities.ewma import ewma
def sample_data_series():
data = np.arange(50).astype(float)
data[3] = np.nan
data[4] = np.nan
return pd.Series(data)
def test_ewma_adjust_and_ignore_na():
series = sample_data_series()
alpha = 0.1
expected = series... | mit |
kirbs-/edX-Learning-From-Data-Solutions | Final/Python/by_Mark_B2/hw8.py | 3 | 5383 | '''
Created on
@author: Mark
'''
import numpy as np
import sklearn.svm as svm
from hw6 import readIn
import random
from sklearn.cross_validation import KFold
from ctypes.test.test_bitfields import func
def getData():
return readIn('features.train'), readIn('features.test')
def classificationError(Y, Y_in):
r... | apache-2.0 |
sergiohzlz/complejos | Logistica/logisticmap.py | 1 | 1255 | #!/usr/bin/python
#-*-coding:utf8-*-
import sys
from pylab import *
import matplotlib
matplotlib.use('TkAgg')
from matplotlib import pyplot as plt
plt.style.use('ggplot')
def logistica(x0,r, n=1000):
L = [x0]
for i in range(n):
x_act = L[-1]
L.append(r*x_act*(1-x_act))
return L
def bifurc... | gpl-2.0 |
kmspriyatham/symath | scipy/scipy/interpolate/tests/test_rbf.py | 4 | 4162 | #!/usr/bin/env python
# Created by John Travers, Robert Hetland, 2007
""" Test functions for rbf module """
from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.testing import (assert_, assert_array_almost_equal,
assert_almost_equal, run_module_suit... | apache-2.0 |
frank-tancf/scikit-learn | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 408 | 8061 | import re
import inspect
import textwrap
import pydoc
from .docscrape import NumpyDocString
from .docscrape import FunctionDoc
from .docscrape import ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config=None):
config = {} if config is None else config
self.use_plots... | bsd-3-clause |
dpshelio/scikit-image | skimage/viewer/tests/test_tools.py | 19 | 5681 | from collections import namedtuple
import numpy as np
from numpy.testing import assert_equal
from numpy.testing.decorators import skipif
from skimage import data
from skimage.viewer import ImageViewer, has_qt
from skimage.viewer.canvastools import (
LineTool, ThickLineTool, RectangleTool, PaintTool)
from skimage.v... | bsd-3-clause |
florian-f/sklearn | examples/plot_johnson_lindenstrauss_bound.py | 4 | 7402 | """
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected in... | bsd-3-clause |
WindCanDie/spark | python/pyspark/sql/tests/test_pandas_udf_grouped_agg.py | 7 | 18847 | #
# 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 |
pratapvardhan/scikit-learn | sklearn/linear_model/tests/test_sag.py | 33 | 28228 | # Authors: Danny Sullivan <dbsullivan23@gmail.com>
# Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
#
# Licence: BSD 3 clause
import math
import numpy as np
import scipy.sparse as sp
from sklearn.linear_model.sag import get_auto_step_size
from sklearn.linear_model.sag_fast import _multinomial_grad_loss_all_sa... | bsd-3-clause |
datapythonista/pandas | pandas/tests/window/test_groupby.py | 3 | 34849 | import numpy as np
import pytest
from pandas import (
DataFrame,
Index,
MultiIndex,
Series,
Timestamp,
date_range,
to_datetime,
)
import pandas._testing as tm
from pandas.api.indexers import BaseIndexer
from pandas.core.groupby.groupby import get_groupby
class TestRolling:
def setup_m... | bsd-3-clause |
anjalisood/spark-tk | regression-tests/sparktkregtests/testcases/frames/ecdf_test.py | 13 | 3032 | # vim: set encoding=utf-8
# Copyright (c) 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 require... | apache-2.0 |
pochoi/SHTOOLS | examples/python/ClassInterface/ClassExample.py | 2 | 1931 | #!/usr/bin/env python
"""
This script tests the python class interface
"""
from __future__ import division
from __future__ import print_function
# standard imports:
import os
import sys
import numpy as np
import matplotlib as mpl
# import shtools:
sys.path.append(os.path.join(os.path.dirname(__file__), "../../.."))
... | bsd-3-clause |
ronw/siplca-segmentation | plot_pages.py | 1 | 3604 | # Copyright (C) 2009 Ron J. Weiss (ronweiss@gmail.com)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This progra... | gpl-3.0 |
AdrienGuille/TOM | tom_lib/nlp/topic_model.py | 1 | 13558 | # coding: utf-8
import itertools
from abc import ABCMeta, abstractmethod
import numpy as np
import tom_lib.stats
from scipy import spatial, cluster
from scipy.sparse import coo_matrix
from sklearn.decomposition import NMF, LatentDirichletAllocation as LDA
#import lda
from tom_lib.structure.corpus import Corpus
__auth... | mit |
lukauskas/scipy | scipy/integrate/quadrature.py | 26 | 27908 | from __future__ import division, print_function, absolute_import
__all__ = ['fixed_quad','quadrature','romberg','trapz','simps','romb',
'cumtrapz','newton_cotes']
from scipy.special.orthogonal import p_roots
from scipy.special import gammaln
from numpy import sum, ones, add, diff, isinf, isscalar, \
a... | bsd-3-clause |
jjx02230808/project0223 | examples/svm/plot_svm_nonlinear.py | 268 | 1091 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learned by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn imp... | bsd-3-clause |
google/fuzzbench | analysis/test_coverage_data_utils.py | 1 | 3522 | # 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | apache-2.0 |
TariqAHassan/BioVida | biovida/genomics/disgenet_interface.py | 1 | 8839 | # coding: utf-8
"""
DisGeNET Interface
~~~~~~~~~~~~~~~~~~
"""
import os
import requests
import pandas as pd
# Tool to create required caches
from biovida.support_tools._cache_management import package_cache_creator
# BioVida Support Tools
from biovida.support_tools.support_tools import header, camel_to_sna... | bsd-3-clause |
fako/datascope | src/core/utils/tests/data.py | 1 | 14820 | from mock import patch, Mock
import numpy as np
import pandas as pd
from pandas.testing import assert_frame_equal
from django.test import TestCase
from core.utils.data import NumericFeaturesFrame
from core.models import Collective, Individual
from core.exceptions import DSFileLoadError
class TestNumericFeaturesFra... | gpl-3.0 |
crukci-bioinformatics/claritypy-ngsreports | legacy/audit_clarity.py | 2 | 16330 | """
Python script create_billing_summary
Created by Anne Pajon under user 'pajon01' on 09/06/2016
"""
import csv
import json
import numpy as np
import os
import pandas as pd
import shutil
import string
import subprocess
import logging
import argparse
from dateutil.relativedelta import *
from dateutil.parser import *
... | mit |
murali-munna/scikit-learn | examples/mixture/plot_gmm_pdf.py | 284 | 1528 | """
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import ma... | bsd-3-clause |
Weihonghao/ECM | Vpy34/lib/python3.5/site-packages/pandas/tests/io/parser/test_read_fwf.py | 7 | 15261 | # -*- coding: utf-8 -*-
"""
Tests the 'read_fwf' function in parsers.py. This
test suite is independent of the others because the
engine is set to 'python-fwf' internally.
"""
from datetime import datetime
import pytest
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas import DataF... | agpl-3.0 |
benthomasson/stdeb | stdeb/util.py | 3 | 60220 | #
# This module contains most of the code of stdeb.
#
import re, sys, os, shutil, select
import codecs
try:
# Python 2.x
import ConfigParser
except ImportError:
# Python 3.x
import configparser as ConfigParser
import subprocess
import tempfile
import stdeb
from stdeb import log, __version__ as __stdeb_v... | mit |
JanNash/sms-tools | lectures/05-Sinusoidal-model/plots-code/sineModelAnal-bendir.py | 24 | 1245 | import numpy as np
import matplotlib.pyplot as plt
import sys, os, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import stft as STFT
import sineModel as SM
import utilFunctions as UF
(fs, x) = UF.wavread(os.path.join(os.path.dirname(os.path.realpath(__fi... | agpl-3.0 |
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