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 |
|---|---|---|---|---|---|
mmottahedi/neuralnilm_prototype | scripts/e209.py | 2 | 6719 | 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
from lasagne.objectives import crossentropy, mse... | mit |
hantek/deeplearn_hsi | pavia_SdA.py | 1 | 9361 | import os
import sys
import time
import scipy.io as sio
import numpy
import scipy
import theano
import theano.tensor as T
from scipy.stats import t
from sklearn import svm
from theano.tensor.shared_randomstreams import RandomStreams
import PIL.Image
from SdA import SdA
from hsi_utils import *
cmap = numpy.asarray( [[... | bsd-2-clause |
fredhusser/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 |
ttm/mass | src/aux/amostras4.py | 1 | 2236 | #-*- coding: utf-8 -*-
# http://matplotlib.sourceforge.net/examples/api/legend_demo.html
#
import pylab as p, numpy as n
f=n.fft.fft
#n4=n.random.rand(4)*2-1
n4=n.array([ 0.58003705, -0.30828309, -0.29797696, -0.99219078])
p.figure(figsize=(12.,6.))
p.subplots_adjust(left=0.06,bottom=0.12,right=0.995,top=0.995)
p.plo... | gpl-3.0 |
kernc/scikit-learn | examples/plot_digits_pipe.py | 70 | 1813 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Pipelining: chaining a PCA and a logistic regression
=========================================================
The PCA does an unsupervised dimensionality reduction, while the logistic
regression does the predictio... | bsd-3-clause |
dssg/cincinnati2015-public | blight_risk_prediction/util.py | 1 | 4914 | #!/usr/bin/env python
import logging
import numpy as np
import pdb
import matplotlib.pyplot as plt
import pandas as pd
from sqlalchemy import create_engine
import datetime
import dbconfig
import config
logger = logging.getLogger(__name__)
years = ['2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '20... | mit |
ishanic/scikit-learn | sklearn/cluster/tests/test_birch.py | 342 | 5603 | """
Tests for the birch clustering algorithm.
"""
from scipy import sparse
import numpy as np
from sklearn.cluster.tests.common import generate_clustered_data
from sklearn.cluster.birch import Birch
from sklearn.cluster.hierarchical import AgglomerativeClustering
from sklearn.datasets import make_blobs
from sklearn.l... | bsd-3-clause |
jayhetee/pandashells | pandashells/lib/config_lib.py | 9 | 1826 | #! /usr/bin/env python
import os
import json
# the name of the file in which to store configuration
CONFIG_FILE_NAME = '.pandashells'
# valid options (option_name, [valid, option, list])
CONFIG_OPTS = sorted(
[
('io_input_type', ['csv', 'table']),
('io_output_type', ['csv', 'table', 'html']),
... | bsd-2-clause |
connordurkin/CPSC_458 | final_project_py2.py | 1 | 16751 |
# Connor Durkin
# Final Project for CPSC_458
# python 2 version
import yahoo_finance
from yahoo_finance import Share
import numpy as np
import pandas
import matplotlib.pyplot as plt
import datetime
import cvxopt as opt
from cvxopt import blas, solvers
# We will do a lot of optimizations,
# and don't want to see each ... | mit |
cmaclell/concept_formation | concept_formation/examples/cobweb3_predict_iris.py | 1 | 2228 | from __future__ import print_function
from __future__ import unicode_literals
from __future__ import absolute_import
from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
from random import seed
from concept_formation.examples.examples_utils import avg_lines
from concept_formation.evaluat... | mit |
Djabbz/scikit-learn | examples/applications/plot_species_distribution_modeling.py | 254 | 7434 | """
=============================
Species distribution modeling
=============================
Modeling species' geographic distributions is an important
problem in conservation biology. In this example we
model the geographic distribution of two south american
mammals given past observations and 14 environmental
varia... | bsd-3-clause |
mit-crpg/openmc | tests/unit_tests/test_data_photon.py | 8 | 5177 | #!/usr/bin/env python
from collections.abc import Mapping, Callable
import os
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
import openmc.data
@pytest.fixture(scope='module')
def elements_endf():
"""Dictionary of element ENDF data indexed by atomic symbol."""
endf_data = os.e... | mit |
wmvanvliet/mne-python | examples/decoding/plot_decoding_spoc_CMC.py | 9 | 3007 | """
====================================
Continuous Target Decoding with SPoC
====================================
Source Power Comodulation (SPoC) :footcite:`DahneEtAl2014` allows to identify
the composition of
orthogonal spatial filters that maximally correlate with a continuous target.
SPoC can be seen as an exten... | bsd-3-clause |
v00d00dem0n/PyCrashCourse | work/ch15/colormap_example.py | 1 | 3677 | """
==================
Colormap reference
==================
Reference for colormaps included with Matplotlib.
This reference example shows all colormaps included with Matplotlib. Note that
any colormap listed here can be reversed by appending "_r" (e.g., "pink_r").
These colormaps are divided into the following cate... | gpl-3.0 |
murphy214/berrl | example/example2.py | 1 | 2073 | import berrl as bl
import pandas as pd
import numpy as np
import itertools
# please, if possible, don't abuse this key its not difficult to get your own
apikey='your api key'
# all the colors currently available for input
colors=['default','light green', 'blue', 'red', 'yellow', 'light blue', 'orange', 'purple', 'gre... | apache-2.0 |
sammosummo/sammosummo.github.io | assets/scripts/bsem.py | 1 | 8112 | """Example of Bayesian confirmatory factor analysis in PyMC3.
"""
import numpy as np
import pandas as pd
import pymc3 as pm
import theano.tensor as tt
import matplotlib.pyplot as plt
from os.path import exists
from matplotlib import rcParams
from pymc3.math import matrix_dot, matrix_inverse
from tabulate import tabul... | mit |
KellyChan/Python | python/crawlers/crawler/catalogs/lowes/lowes_catalogs_products_recheck.py | 3 | 2796 | __author__ = "Kelly Chan"
__date__ = "Sept 9 2014"
__version__ = "1.0.0"
import os
import sys
reload(sys)
sys.setdefaultencoding( "utf-8" )
import mechanize
import cookielib
import re
import time
import urllib
import urllib2
from bs4 import BeautifulSoup
import pandas
def openBrowser():
# Browser
br =... | mit |
astraw/mplsizer | mpl_toolkits/mplsizer/mplsizer.py | 2 | 20954 | from __future__ import division
import math
import matplotlib.numerix as nx
from matplotlib.axes import Axes
_axes_sizer_elements = {}
_sizer_flags = ['left','right','bottom','top','all',
'expand',
'align_centre',
'align_centre_vertical',
'align_centre_ho... | mit |
0u812/matplotlib2tikz | test/acidtest.py | 1 | 6448 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2010--2014 Nico Schlömer
#
# This file is part of matplotlib2tikz.
#
# matplotlib2tikz 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 ver... | lgpl-3.0 |
amozie/amozie | studzie/abu_test/abu_test_a.py | 1 | 1346 | import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import abupy
abupy.env.disable_example_env_ipython()
from abupy import ABuSymbolPd
df = ABuSymbolPd.make_kl_df('601398')
from abupy import EMarketDataFetchMode, abu
abupy.env.g_data_fetch_mode = EMarketDataFetchMode.E_DATA... | apache-2.0 |
jetuk/pywr | tests/test_core.py | 1 | 13701 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
import pytest
from fixtures import *
from helpers import *
from pywr._core import Timestep, ScenarioIndex
from pywr.core import *
from pywr.domains.river import *
from pywr.parameters import Parameter, ConstantParameter, DataFramePar... | gpl-3.0 |
HealthCatalystSLC/healthcareai-py | setup.py | 4 | 2465 | # -*- coding: utf-8 -*-
# from __future__ import unicode_literals
from setuptools import setup, find_packages
def readme():
# I really prefer Markdown to reStructuredText. PyPi does not. This allows me
# to have things how I'd like, but not throw complaints when people are trying
# to install the packag... | mit |
UASLab/ImageAnalysis | scripts/archive/6b-delaunay3.py | 1 | 10722 | #!/usr/bin/python
import sys
sys.path.insert(0, "/usr/local/opencv3/lib/python2.7/site-packages/")
import argparse
import commands
import cPickle as pickle
import cv2
import fnmatch
import itertools
#import json
import math
import matplotlib.pyplot as plt
import numpy as np
import os.path
from progress.bar import Bar... | mit |
khalibartan/pgmpy | pgmpy/estimators/base.py | 1 | 16920 | #!/usr/bin/env python
from warnings import warn
from functools import lru_cache
import numpy as np
import pandas as pd
from scipy.stats import chisquare
from pgmpy.utils.decorators import convert_args_tuple
class BaseEstimator(object):
def __init__(self, data, state_names=None, complete_samples_only=True):
... | mit |
daleloogn/singerID-BTechProject-neuralnet | prog1.py | 1 | 5136 | import os
import sys
import numpy
from numpy import *
from numpy import random
from scipy import optimize as op
from scipy import io
import pylab
from matplotlib import *
import matplotlib.pyplot as plt
from tempfile import TemporaryFile
from PIL import Image
def plotData(image):
'''plots the input data '''
... | apache-2.0 |
vatika/Automated-Essay-Grading | Data/feature_extractor.py | 1 | 10539 | # Copyright 2015 - Vatika Harlalka, Anurag Ghosh, Abhijeet Kumar
import csv
import nltk
import string
import json
from collections import Counter
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.te... | gpl-2.0 |
nishnik/networkx | doc/make_gallery.py | 35 | 2453 | """
Generate a thumbnail gallery of examples.
"""
from __future__ import print_function
import os, glob, re, shutil, sys
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot
import matplotlib.image
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCa... | bsd-3-clause |
manashmndl/scikit-learn | examples/text/document_classification_20newsgroups.py | 222 | 10500 | """
======================================================
Classification of text documents using sparse features
======================================================
This is an example showing how scikit-learn can be used to classify documents
by topics using a bag-of-words approach. This example uses a scipy.spars... | bsd-3-clause |
BorisJeremic/Real-ESSI-Examples | education_examples/_Chapter_Material_Behaviour_Examples/Multi_Yield_Surface_von_Mises_GGmax/plot_stress_strain_loop.py | 2 | 2628 | import numpy as np
import matplotlib.pyplot as plt
# target
userInput1= [0,3.16200000000000e-07,1.00000000000000e-06,3.16227766016838e-06,1.00000000000000e-05,2.23606797749979e-05,5.00000000000000e-05,7.07106781186548e-05,0.000100000000000000,0.000223606797749979,0.000500000000000000,0.000707106781186548,0.001000000... | cc0-1.0 |
googleinterns/amt-xpub | examples/plot_signal_to_noise_ratio_analysis_results.py | 1 | 3393 | # Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | apache-2.0 |
alexeyum/scikit-learn | examples/cluster/plot_birch_vs_minibatchkmeans.py | 333 | 3694 | """
=================================
Compare BIRCH and MiniBatchKMeans
=================================
This example compares the timing of Birch (with and without the global
clustering step) and MiniBatchKMeans on a synthetic dataset having
100,000 samples and 2 features generated using make_blobs.
If ``n_clusters... | bsd-3-clause |
pnedunuri/scipy | scipy/interpolate/fitpack.py | 25 | 46138 | #!/usr/bin/env python
"""
fitpack (dierckx in netlib) --- A Python-C wrapper to FITPACK (by P. Dierckx).
FITPACK is a collection of FORTRAN programs for curve and surface
fitting with splines and tensor product splines.
See
http://www.cs.kuleuven.ac.be/cwis/research/nalag/research/topics/fitpack.html
... | bsd-3-clause |
yunque/librosa | librosa/display.py | 1 | 23327 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Display
=======
.. autosummary::
:toctree: generated/
specshow
waveplot
time_ticks
cmap
"""
import numpy as np
import copy
import matplotlib as mpl
import matplotlib.image as img
import matplotlib.pyplot as plt
import warnings
from . import cache
... | isc |
ChengeLi/VehicleTracking | utilities/inspect_data.py | 1 | 2397 | # This is a program for inspecting data files
import cv2
import os
import sys
import pdb
import pickle
import numpy as np
import glob as glob
from scipy.io import loadmat,savemat
from scipy.sparse import csr_matrix
import matplotlib.pyplot as plt
from DataPathclass import *
DataPathobj = DataPath(dataSource,VideoIndex)... | mit |
turbomanage/training-data-analyst | blogs/feature_column_normalization/model_code/trainer/model.py | 2 | 4279 | #!/usr/bin/env python
# Copyright 2018 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 require... | apache-2.0 |
andaag/scikit-learn | sklearn/cluster/setup.py | 263 | 1449 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
cblas_libs, blas_info = ... | bsd-3-clause |
kalaytan/findatapy | findatapy/timeseries/calculations.py | 1 | 24533 | __author__ = 'saeedamen' # Saeed Amen
#
# Copyright 2016 Cuemacro
#
# 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 l... | apache-2.0 |
annahs/atmos_research | NC_POLAR6_flighttrack_map.py | 1 | 6786 | import sys
import os
import numpy as np
from pprint import pprint
from datetime import datetime
from datetime import timedelta
import mysql.connector
import pickle
import math
import calendar
import matplotlib.pyplot as plt
from matplotlib import colorbar
import matplotlib.colors
from mpl_toolkits.basemap import Basema... | mit |
Vvucinic/Wander | venv_2_7/lib/python2.7/site-packages/pandas/tests/test_generic.py | 9 | 69277 | # -*- coding: utf-8 -*-
# pylint: disable-msg=E1101,W0612
from datetime import datetime, timedelta
import nose
import numpy as np
from numpy import nan
import pandas as pd
from pandas import (Index, Series, DataFrame, Panel,
isnull, notnull, date_range, period_range)
from pandas.core.index import ... | artistic-2.0 |
Project-Bonfire/EHA | Scripts/include/viz_traffic.py | 3 | 9766 | # Copyright (C) 2017 Siavoosh Payandeh Azad
# you can run it for example with the following:
# python -c 'from viz_traffic import *; viz_traffic(2)'
# this should be added later to the simulate.py script
# there are some things you should be carefull with:
# - if you have different packets with the same source, des... | gpl-3.0 |
scikit-optimize/scikit-optimize.github.io | dev/_downloads/365fdab27864494141feaa35987b301b/partial-dependence-plot-2D.py | 3 | 3291 | """
===========================
Partial Dependence Plots 2D
===========================
Hvass-Labs Dec 2017
Holger Nahrstaedt 2020
.. currentmodule:: skopt
Simple example to show the new 2D plots.
"""
print(__doc__)
import numpy as np
from math import exp
from skopt import gp_minimize
from skopt.space import Real, ... | bsd-3-clause |
Eric89GXL/mne-python | examples/preprocessing/plot_muscle_detection.py | 18 | 3308 | """
===========================
Annotate muscle artifacts
===========================
Muscle contractions produce high frequency activity that can mask brain signal
of interest. Muscle artifacts can be produced when clenching the jaw,
swallowing, or twitching a cranial muscle. Muscle artifacts are most
noticeable in t... | bsd-3-clause |
oduwa/Pic-Numero | PicNumero/count.py | 2 | 1729 | import os, sys
import tqdm
from scipy import misc
from skimage.feature import blob_dog, blob_log, blob_doh
from skimage.color import rgb2gray
# Way to import from matplotlib without warning according to
# https://github.com/matplotlib/matplotlib/issues/5836#issuecomment-223997114
import warnings;
with warnings.catch_... | mit |
wzbozon/scikit-learn | sklearn/svm/tests/test_sparse.py | 70 | 12992 | from nose.tools import assert_raises, assert_true, assert_false
import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from sklearn import datasets, svm, linear_model, base
from sklearn.datasets import make_classif... | bsd-3-clause |
venzozhang/GProject | src/flow-monitor/examples/wifi-olsr-flowmon.py | 108 | 7439 | # -*- Mode: Python; -*-
# Copyright (c) 2009 INESC Porto
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation;
#
# This program is distributed in the hope that it will be useful,
#... | gpl-2.0 |
kazemakase/scikit-learn | sklearn/utils/extmath.py | 142 | 21102 | """
Extended math utilities.
"""
# Authors: Gael Varoquaux
# Alexandre Gramfort
# Alexandre T. Passos
# Olivier Grisel
# Lars Buitinck
# Stefan van der Walt
# Kyle Kastner
# License: BSD 3 clause
from __future__ import division
from functools import partial
import ... | bsd-3-clause |
ishank08/scikit-learn | sklearn/neighbors/tests/test_lof.py | 34 | 4142 | # Authors: Nicolas Goix <nicolas.goix@telecom-paristech.fr>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
from math import sqrt
import numpy as np
from sklearn import neighbors
from numpy.testing import assert_array_equal
from sklearn import metrics
from sklearn.metr... | bsd-3-clause |
twareproj/tware | examples/mimic2/logreg.py | 2 | 7417 | import numpy as np
import sys
from sets import Set
#classifiers
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegression
#preprocess
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import StandardScaler
#eval
from sklearn.cross_validation impor... | apache-2.0 |
yuanagain/seniorthesis | src/2017-04-06.py | 1 | 6190 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import math
import numdifftools as nd
default_lambda_1, default_lambda_2, default_lambda_3 = 0.086, 0.141, 0.773
default_start = (0.372854105052, 0.393518965248, -0.0359026080443, -0.216701666067)
x_0 = default_start
res = 0.01... | mit |
edlectrico/twitter_nltk_volkswagen | sentiment_mod.py | 2 | 2898 | import nltk
import random
#from nltk.corpus import movie_reviews
from nltk.classify.scikitlearn import SklearnClassifier
import pickle
from sklearn.naive_bayes import MultinomialNB, BernoulliNB
from sklearn.linear_model import LogisticRegression, SGDClassifier
from sklearn.svm import SVC, LinearSVC, NuSVC
from nltk.cla... | apache-2.0 |
chili-epfl/shape_learning | tools/dataset-preprocessing/preprocessDataset.py | 3 | 3918 | import itertools
import numpy
from scipy import interpolate
#from scipy.cluster.vq import vq, kmeans, whiten
from sklearn.cluster import MeanShift
MIN_CLUSTER_SIZE = 8
NB_POINTS=70
def interpolate_shape(shape,numDesiredPoints):
""" Interpolate the shape to reach a predefined number of points, and
switch from ... | isc |
eljost/rassiparse | rassiparse/mcscan_dash.py | 1 | 8715 | #!/usr/bin/env python3
import argparse
import base64
import glob
import logging
import pprint
import os
import sys
import tarfile
import dash
import dash_core_components as dcc
import dash.dependencies as dep
import dash_html_components as html
from natsort import natsorted
import plotly.graph_objs as go
import nump... | gpl-3.0 |
gvanhorn38/multibox | visualize_detect.py | 1 | 9994 | """
Visualize detection results.
"""
import argparse
import cPickle as pickle
import json
import logging
from matplotlib import pyplot as plt
import numpy as np
import os
import pprint
import sys
import tensorflow as tf
import tensorflow.contrib.slim as slim
import time
from config import parse_config_file
from dete... | mit |
LiaoPan/scikit-learn | benchmarks/bench_sgd_regression.py | 283 | 5569 | """
Benchmark for SGD regression
Compares SGD regression against coordinate descent and Ridge
on synthetic data.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
# License: BSD 3 clause
import numpy as np
import pylab as pl
import gc
from time import time
from sklearn.linear_model i... | bsd-3-clause |
tornadozou/tensorflow | tensorflow/contrib/timeseries/examples/known_anomaly.py | 53 | 6786 | # Copyright 2017 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 |
Lawrence-Liu/scikit-learn | sklearn/metrics/cluster/tests/test_bicluster.py | 394 | 1770 | """Testing for bicluster metrics module"""
import numpy as np
from sklearn.utils.testing import assert_equal, assert_almost_equal
from sklearn.metrics.cluster.bicluster import _jaccard
from sklearn.metrics import consensus_score
def test_jaccard():
a1 = np.array([True, True, False, False])
a2 = np.array([T... | bsd-3-clause |
ngoix/OCRF | examples/linear_model/plot_sgd_penalties.py | 124 | 1877 | """
==============
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 |
yonglehou/scikit-learn | sklearn/ensemble/forest.py | 176 | 62555 | """Forest of trees-based ensemble methods
Those methods include random forests and extremely randomized trees.
The module structure is the following:
- The ``BaseForest`` base class implements a common ``fit`` method for all
the estimators in the module. The ``fit`` method of the base ``Forest``
class calls the ... | bsd-3-clause |
hello-base/web | apps/correlations/views.py | 1 | 2963 | # -*- coding: utf-8 -*-
from collections import defaultdict, OrderedDict
from itertools import groupby
from django.views.generic.dates import YearArchiveView
from django.views.generic import DetailView
from braces.views import JSONResponseMixin
from pandas import DataFrame
from .constants import SUBJECTS
from .model... | apache-2.0 |
ntim/g4sipm | sample/plots/json/celltriggers.py | 1 | 1725 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Plots the distribution of the cell triggers into a 2d-histogram.
#
import sys, os, glob
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import persistency
def get_digi_cell_position(model, digi):
"""
Determines the cell position.... | gpl-3.0 |
HeraclesHX/scikit-learn | examples/linear_model/plot_logistic.py | 312 | 1426 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logit function
=========================================================
Show in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or two, u... | bsd-3-clause |
manulera/ModellingCourse | ReAct/Python/GenerateMasterEq.py | 1 | 1118 |
import numpy as np
from Gilles import *
import matplotlib.pyplot as plt
from DeviationAnalysis import *
from mpl_toolkits.mplot3d import Axes3D
# Initial conditions
user_input = ['A', 100,
'B', 0]
# Constants (this is not necessary, they could be filled up already in the reaction tuple)
k = (10,10)
# Re... | gpl-3.0 |
roxyboy/scikit-learn | examples/exercises/plot_cv_digits.py | 232 | 1206 | """
=============================================
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 |
saiwing-yeung/scikit-learn | sklearn/ensemble/partial_dependence.py | 25 | 15121 | """Partial dependence plots for tree ensembles. """
# Authors: Peter Prettenhofer
# License: BSD 3 clause
from itertools import count
import numbers
import numpy as np
from scipy.stats.mstats import mquantiles
from ..utils.extmath import cartesian
from ..externals.joblib import Parallel, delayed
from ..externals im... | bsd-3-clause |
RPGOne/Skynet | scikit-learn-0.18.1/sklearn/feature_selection/tests/test_rfe.py | 56 | 11274 | """
Testing Recursive feature elimination
"""
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
from scipy import sparse
from sklearn.feature_selection.rfe import RFE, RFECV
from sklearn.datasets import load_iris, make_friedman1
from sklearn.metrics import zero_one_loss
from sk... | bsd-3-clause |
mjudsp/Tsallis | examples/bicluster/plot_spectral_biclustering.py | 403 | 2011 | """
=============================================
A demo of the Spectral Biclustering algorithm
=============================================
This example demonstrates how to generate a checkerboard dataset and
bicluster it using the Spectral Biclustering algorithm.
The data is generated with the ``make_checkerboard`... | bsd-3-clause |
shyamalschandra/scikit-learn | examples/cluster/plot_mini_batch_kmeans.py | 86 | 4092 | """
====================================================================
Comparison of the K-Means and MiniBatchKMeans clustering algorithms
====================================================================
We want to compare the performance of the MiniBatchKMeans and KMeans:
the MiniBatchKMeans is faster, but give... | bsd-3-clause |
bbarrefors/CUADRnT | setup.py | 4 | 8025 | #!/usr/bin/env python
"""
Standard python setup.py file for cuadrnt package
To build : python setup.py build
To install : python setup.py install --prefix=<some dir>
To clean : python setup.py clean
To build doc : python setup.py doc
To run tests : python setup.py test
"""
# system modules
#import logging
im... | mit |
jakobj/nest-simulator | pynest/examples/spatial/conncon_sources.py | 20 | 3212 | # -*- coding: utf-8 -*-
#
# conncon_sources.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License... | gpl-2.0 |
rolandwz/pymisc | strader/trader.py | 2 | 6455 | # -*- coding: utf-8 -*-
import os, datetime
from numpy import array
import pylab as pl
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.dates import DateFormatter
from matplotlib.widgets import MultiCursor
from utils.rwlogging import tradeLogger as logt
from utils.rwlogging import balLogger as ... | mit |
SnakeJenny/TensorFlow | tensorflow/contrib/learn/python/learn/estimators/kmeans_test.py | 44 | 19373 | # 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 |
RayMick/scikit-learn | sklearn/feature_extraction/tests/test_image.py | 205 | 10378 | # Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# License: BSD 3 clause
import numpy as np
import scipy as sp
from scipy import ndimage
from nose.tools import assert_equal, assert_true
from numpy.testing import assert_raises
from sklearn... | bsd-3-clause |
JanSchulz/knitpy | knitpy/documents.py | 1 | 17172 | from __future__ import absolute_import, unicode_literals
import os
import tempfile
import re
from collections import OrderedDict
try:
#py3
from base64 import decodebytes
except ImportError:
# py2
from base64 import decodestring as decodebytes
from pypandoc import convert as pandoc
# Basic things f... | bsd-3-clause |
aburrell/davitpy | davitpy/__init__.py | 2 | 20379 | # -*- coding: utf-8 -*-
# Copyright (C) 2012 VT SuperDARN Lab
# Full license can be found in LICENSE.txt
"""
davitpy
-------
The SuperDARN Data Visualization Toolkit in Python
Modules
-------------------------------------------------
pydarn superdarn data I/O and plotting utilities
utils general utilities
models py... | gpl-3.0 |
IntelLabs/hpat | examples/series/series_quantile.py | 1 | 1768 | # *****************************************************************************
# Copyright (c) 2020, Intel 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 sou... | bsd-2-clause |
aabadie/scikit-learn | sklearn/svm/classes.py | 22 | 41116 | import warnings
import numpy as np
from .base import _fit_liblinear, BaseSVC, BaseLibSVM
from ..base import BaseEstimator, RegressorMixin
from ..linear_model.base import LinearClassifierMixin, SparseCoefMixin, \
LinearModel
from ..feature_selection.from_model import _LearntSelectorMixin
from ..utils import check_X... | bsd-3-clause |
kernsuite-debian/lofar | CEP/Pipeline/helper_scripts/aggregate_stats.py | 1 | 35696 | # LOFAR PIPELINE FRAMEWORK
#
# aggregate stats
# Wouter Klijn, 2014
# klijn@astron.nl
# -... | gpl-3.0 |
sullivancolin/hexpy | tests/test_models.py | 1 | 14073 | # -*- coding: utf-8 -*-
"""Tests for model validation."""
import logging
from typing import List
import pandas as pd
import pendulum
import pytest
import responses
from _pytest.capture import CaptureFixture
from pydantic import ValidationError
from hexpy import ContentUploadAPI, HexpySession, MonitorAPI, Project
from... | mit |
nelango/ViralityAnalysis | model/lib/sklearn/linear_model/ransac.py | 25 | 14262 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.valid... | mit |
vivekmishra1991/scikit-learn | examples/cluster/plot_lena_segmentation.py | 271 | 2444 | """
=========================================
Segmenting the picture of Lena in regions
=========================================
This example uses :ref:`spectral_clustering` on a graph created from
voxel-to-voxel difference on an image to break this image into multiple
partly-homogeneous regions.
This procedure (spe... | bsd-3-clause |
yyjiang/scikit-learn | examples/model_selection/plot_learning_curve.py | 250 | 4171 | """
========================
Plotting Learning Curves
========================
On the left side the learning curve of a naive Bayes classifier is shown for
the digits dataset. Note that the training score and the cross-validation score
are both not very good at the end. However, the shape of the curve can be found
in ... | bsd-3-clause |
sambitgaan/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/blocking_input.py | 69 | 12119 | """
This provides several classes used for blocking interaction with figure windows:
:class:`BlockingInput`
creates a callable object to retrieve events in a blocking way for interactive sessions
:class:`BlockingKeyMouseInput`
creates a callable object to retrieve key or mouse clicks in a blocking way for int... | agpl-3.0 |
herilalaina/scikit-learn | examples/linear_model/plot_logistic.py | 73 | 1568 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic function
=========================================================
Shown in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or tw... | bsd-3-clause |
trankmichael/scikit-learn | sklearn/utils/tests/test_extmath.py | 130 | 16270 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis Engemann <d.engemann@fz-juelich.de>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from scipy import linalg
from scipy import stats
from sklearn.utils.testing import assert_eq... | bsd-3-clause |
osergeev/bike | example.py | 1 | 2271 | import matplotlib.pyplot as mpl
from surface import Surface
import numpy as np
import zoom
# enable animation mode
mpl.ion()
# enable animation mode
#fig, ax = figure.subplots()
surface1 = Surface(100,100)
surfacepoints = surface1.getPoints()
xw1=1.5
yw1=1.5
xw2=3
yw2=1.5
xp1=1.7
yp1=2.5
xp2=2.7... | gpl-2.0 |
jon-courtney/cnn-autonomous-drone | shared/bagreader.py | 1 | 1056 | #!/usr/bin/env python
import pandas as pd
import rosbag_pandas
import sys, os, pdb
from PIL import Image
from io import BytesIO
sys.path.append(os.path.abspath('../..')) # Not clean
from annotate_base import AnnotateBase
class BagReader(AnnotateBase):
def __init__(self, num_actions=2, newtopic=True):
sup... | bsd-2-clause |
h-mayorquin/camp_india_2016 | project3_sustained_activity/dynamical_study.py | 1 | 2389 | from brian2 import *
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(font_scale=2.0)
# Neuron Parameters
g_l = 0.05 * msiemens / cm2
cm = 1.0 * ufarad / cm2 # Specific membrane capacitance
E_l = -60 * mV # Resting potential
V_t = -50 * mV # Threshold
tau_w = 600 * ms # Adaptation ... | mit |
hbldh/skboost | skboost/datasets/hastie/__init__.py | 1 | 1474 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
:mod:`hastie`
===========
.. module:: hastie
:platform: Unix, Windows
:synopsis:
.. moduleauthor:: hbldh <henrik.blidh@nedomkull.com>
Created on 2015-11-10
"""
from __future__ import division
from __future__ import print_function
from __future__ import unic... | mit |
itdxer/neupy | examples/competitive/sofm_compare_weight_init.py | 1 | 1754 | from itertools import product
import matplotlib.pyplot as plt
from neupy import algorithms, utils, init
from utils import plot_2d_grid, make_circle, make_elipse, make_square
plt.style.use('ggplot')
utils.reproducible()
if __name__ == '__main__':
GRID_WIDTH = 4
GRID_HEIGHT = 4
datasets = [
mak... | mit |
samuel1208/scikit-learn | sklearn/metrics/cluster/tests/test_bicluster.py | 394 | 1770 | """Testing for bicluster metrics module"""
import numpy as np
from sklearn.utils.testing import assert_equal, assert_almost_equal
from sklearn.metrics.cluster.bicluster import _jaccard
from sklearn.metrics import consensus_score
def test_jaccard():
a1 = np.array([True, True, False, False])
a2 = np.array([T... | bsd-3-clause |
aubreyli/hmmlearn | examples/plot_hmm_stock_analysis.py | 2 | 2681 | """
Gaussian HMM of stock data
--------------------------
This script shows how to use Gaussian HMM on stock price data from
Yahoo! finance. For more information on how to visualize stock prices
with matplotlib, please refer to ``date_demo1.py`` of matplotlib.
"""
from __future__ import print_function
import datetim... | bsd-3-clause |
winklerand/pandas | pandas/tests/groupby/test_timegrouper.py | 3 | 26859 | """ test with the TimeGrouper / grouping with datetimes """
import pytest
import pytz
from datetime import datetime
import numpy as np
from numpy import nan
import pandas as pd
from pandas import (DataFrame, date_range, Index,
Series, MultiIndex, Timestamp, DatetimeIndex)
from pandas.compat impor... | bsd-3-clause |
nysbc/Anisotropy | ThreeDFSC/ThreeDFSC_Start.py | 1 | 12504 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
### Require Anaconda3
### ============================
### 3D FSC Software Wrapper
### Written by Philip Baldwin
### Edited by Yong Zi Tan and Dmitry Lyumkis
### Anaconda environment and Numba CUDA support by Carl Negro
### Downloaded from https://github.com/nysbc/Anisotro... | mit |
Edu-Glez/Bank_sentiment_analysis | env/lib/python3.6/site-packages/pandas/tools/tests/test_join.py | 7 | 30695 | # pylint: disable=E1103
import nose
from numpy.random import randn
import numpy as np
import pandas as pd
from pandas.compat import lrange
import pandas.compat as compat
from pandas.tools.merge import merge, concat
from pandas.util.testing import assert_frame_equal
from pandas import DataFrame, MultiIndex, Series
i... | apache-2.0 |
abimannans/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 |
WafaaT/spark-tk | regression-tests/sparktkregtests/testcases/frames/frame_sort_test.py | 10 | 6152 | # 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 |
olafhauk/mne-python | mne/channels/layout.py | 4 | 36277 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
# Marijn van Vliet <w.m.vanvliet@gmail.com>
# Jona Sassenhagen <jona.sassenhagen@gmai... | bsd-3-clause |
kpj/SDEMotif | formula_investigator.py | 1 | 4469 | """
Investigate chemical formulas
"""
import pickle
import itertools
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from tqdm import tqdm
import reaction_finder
def read_combinatorial_compounds(fname='cache/rf_raw_reaction_data.pkl'):
with open(fname, 'rb') as fd:
comps = p... | mit |
tgsmith61591/skutil | skutil/preprocessing/tests/test_impute.py | 1 | 6525 | from __future__ import print_function
import pandas as pd
import numpy as np
from numpy.random import choice
from sklearn.datasets import load_iris
from skutil.preprocessing import *
from skutil.utils import shuffle_dataframe
from skutil.testing import assert_fails
from sklearn.ensemble import RandomForestClassifier
... | bsd-3-clause |
kdheepak89/mpld3 | mpld3/tests/test_elements.py | 3 | 5689 | """
Test creation of basic plot elements
"""
import numpy as np
import matplotlib.pyplot as plt
from .. import fig_to_dict, fig_to_html
from numpy.testing import assert_equal
def test_line():
fig, ax = plt.subplots()
ax.plot(np.arange(10), np.random.random(10),
'--k', alpha=0.3, zorder=10, lw=2)
... | bsd-3-clause |
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