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 |
|---|---|---|---|---|---|
dsullivan7/scikit-learn | sklearn/metrics/cluster/supervised.py | 21 | 26876 | """Utilities to evaluate the clustering performance of models
Functions named as *_score return a scalar value to maximize: the higher the
better.
"""
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Wei LI <kuantkid@gmail.com>
# Diego Molla <dmolla-aliod@gmail.com>
# License: BSD 3 clause
fr... | bsd-3-clause |
florisvb/FlyPlumeTracking | plot_fly_trajectory.py | 1 | 3152 | # (c) 2013 Floris van Breugel
#
# This script is programmed to read a file, "sim_data.pickle," created by the simulation "fly_plume_sim.py," and make the corresponding figure/animation.
# The code relies on plotting packages that are freely available from https://github.com/florisvb
import pickle
import fly_plot_lib.... | gpl-3.0 |
algorithmic-music-exploration/amen | tests/test_synthesize.py | 1 | 2488 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import six
import pandas as pd
import numpy as np
import librosa
import pytest
from amen.audio import Audio
from amen.utils import example_audio_file
from amen.utils import example_mono_audio_file
from amen.synthesize import _format_inputs
from amen.synthesize import synth... | bsd-2-clause |
adamgreenhall/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 |
GehenHe/Recognize-Face-on-Android | tensorflow/contrib/learn/python/learn/dataframe/dataframe.py | 85 | 4704 | # 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 |
aktech/sympy | sympy/interactive/tests/test_ipythonprinting.py | 24 | 6208 | """Tests that the IPython printing module is properly loaded. """
from sympy.interactive.session import init_ipython_session
from sympy.external import import_module
from sympy.utilities.pytest import raises
# run_cell was added in IPython 0.11
ipython = import_module("IPython", min_module_version="0.11")
# disable ... | bsd-3-clause |
shahankhatch/scikit-learn | examples/covariance/plot_mahalanobis_distances.py | 348 | 6232 | r"""
================================================================
Robust covariance estimation and Mahalanobis distances relevance
================================================================
An example to show covariance estimation with the Mahalanobis
distances on Gaussian distributed data.
For Gaussian dis... | bsd-3-clause |
lbishal/scikit-learn | examples/semi_supervised/plot_label_propagation_structure.py | 45 | 2433 | """
==============================================
Label Propagation learning a complex structure
==============================================
Example of LabelPropagation learning a complex internal structure
to demonstrate "manifold learning". The outer circle should be
labeled "red" and the inner circle "blue". Be... | bsd-3-clause |
cogmission/nupic.research | projects/sequence_prediction/continuous_sequence/data/processSineWave.py | 13 | 2231 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
nithyanandan/PRISim | scripts/run_prisim.py | 1 | 122758 | #!python
import os, shutil, subprocess, pwd, errno, warnings
from mpi4py import MPI
import yaml
import h5py
import argparse
import copy
import numpy as NP
from astropy.io import fits, ascii
from astropy.coordinates import Galactic, FK5, ICRS, SkyCoord, AltAz, EarthLocation
from astropy import units as U
from astropy.t... | mit |
leylabmpi/leylab_pipelines | leylab_pipelines/DB/TaxID2LinTbl.py | 1 | 9181 | # import
## batteries
import re
import os
import sys
import gzip
import tempfile
import multiprocessing
import argparse
import logging
import urllib
import tarfile
## 3rd party
import pandas as pd
## package
from leylab_pipelines import Utils
# logging
logging.basicConfig(
level=logging.DEBUG, format='%(asctime)s... | mit |
dancingdan/tensorflow | tensorflow/contrib/losses/python/metric_learning/metric_loss_ops.py | 30 | 40476 | # 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 |
neurodroid/sima | examples/spikeinference.py | 6 | 4351 | from __future__ import division
from __future__ import print_function
from builtins import str
from builtins import range
from scipy import signal
from scipy.stats import uniform, norm
import numpy as np
import seaborn as sns
import matplotlib.mlab as ml
import matplotlib.pyplot as plt
from sima import spikes
######... | gpl-2.0 |
BalticPinguin/libmesh | doc/statistics/github_traffic_base.py | 5 | 6343 | #!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
import math
# Import stuff for working with dates
from datetime import datetime
from matplotlib.dates import date2num, num2date
import calendar
# Github has a "traffic" page now, but it doesn't seem like you can
# put in an arbitrary date range?... | lgpl-2.1 |
joshgabriel/dft-crossfilter | CompleteApp/crossfilter_app/main.py | 1 | 25701 | import os
from os.path import dirname, join
from collections import OrderedDict
import pandas as pd
import numpy as np
import json
from bokeh.io import curdoc
from bokeh.layouts import row, widgetbox, column, gridplot, layout
from bokeh.models import Select, Div, Column, \
HoverTool, ColumnDataSource, Button, RadioB... | mit |
CERT-Solucom/certitude | crossbokeh.py | 2 | 8483 | import pandas as pd
import io
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from config import CERTITUDE_DATABASE, LISTEN_ADDRESS, LISTEN_PORT
from helpers.queue_models import Task
from helpers.results_models import Result, IOCDetection
from helpers.misc_models import ConfigurationProfi... | gpl-2.0 |
jrderuiter/genemap | src/genemap/mappers/base.py | 1 | 4608 | # -*- coding: utf-8 -*-
# pylint: disable=wildcard-import,redefined-builtin,unused-wildcard-import
from __future__ import absolute_import, division, print_function
from builtins import *
# pylint: enable=wildcard-import,redefined-builtin,unused-wildcard-import
import pandas as pd
from . import util
_registry = {}
_... | mit |
samzhang111/scikit-learn | sklearn/naive_bayes.py | 11 | 28770 | # -*- coding: utf-8 -*-
"""
The :mod:`sklearn.naive_bayes` module implements Naive Bayes algorithms. These
are supervised learning methods based on applying Bayes' theorem with strong
(naive) feature independence assumptions.
"""
# Author: Vincent Michel <vincent.michel@inria.fr>
# Minor fixes by Fabian Pedre... | bsd-3-clause |
chenkianwee/envuo | setup.py | 1 | 1430 | from setuptools import setup, find_packages
__author__ = "CHEN Kian Wee"
__copyright__ = "Copyright 2016, Chen Kian Wee"
__credits__ = ["CHEN Kian Wee"]
__license__ = "GPL3"
__version__ = "0.32"
__maintainer__ = "Chen Kian Wee"
__email__ = "chenkianwee@gmail.com"
__status__ = "Development"
LONG_DESCRIPTION = "refer t... | gpl-3.0 |
powerjg/gem5-ci-test | util/dram_lat_mem_rd_plot.py | 10 | 5156 | #!/usr/bin/env python2
# Copyright (c) 2015 ARM Limited
# All rights reserved
#
# The license below extends only to copyright in the software and shall
# not be construed as granting a license to any other intellectual
# property including but not limited to intellectual property relating
# to a hardware implementatio... | bsd-3-clause |
potash/scikit-learn | examples/cluster/plot_segmentation_toy.py | 91 | 3522 | """
===========================================
Spectral clustering for image segmentation
===========================================
In this example, an image with connected circles is generated and
spectral clustering is used to separate the circles.
In these settings, the :ref:`spectral_clustering` approach solve... | bsd-3-clause |
nextgis-borsch/borsch | opt/tools.py | 1 | 25068 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
################################################################################
##
## Project: NextGIS Borsch build system
## Purpose: Various tools
## Author: Dmitry Baryshnikov <dmitry.baryshnikov@nextgis.com>
## Author: Maxim Dubinin <maim.dubinin@nextgis.com>
## Copyri... | gpl-2.0 |
ninotoshi/tensorflow | tensorflow/python/client/notebook.py | 26 | 4596 | # Copyright 2015 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 applicable law or a... | apache-2.0 |
RohitMetaCube/test_code | MakeMyTrip/train_model.py | 1 | 4961 | # -*- coding: utf-8 -*-
import os
import random
from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.linear_model import SGDClassifier
import numpy as np
from sklearn.decomposition import TruncatedSVD
... | gpl-3.0 |
mlperf/training_results_v0.5 | v0.5.0/google/cloud_v3.8/resnet-tpuv3-8/code/resnet/model/models/official/utils/data/file_io.py | 4 | 7242 | # Copyright 2018 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 |
lin-credible/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 286 | 2378 | """
=====================================================================
Decision boundary of label propagation versus SVM on the Iris dataset
=====================================================================
Comparison for decision boundary generated on iris dataset
between Label Propagation and SVM.
This demon... | bsd-3-clause |
minireference/noBSLAnotebooks | aspynb/Linear_algebra_chapters_overview.py | 1 | 23478 | def cells():
'''
# Linear algebra overview
'''
'''
'''
'''
Linear algebra is the study of **vectors** and **linear transformations**. This notebook introduces concepts form linear algebra in a birds-eye overview. The goal is not to get into the details, but to give the reader a taste of th... | mit |
wateraccounting/wa | Collect/MYD13/DataAccess.py | 2 | 15226 | # -*- coding: utf-8 -*-
# -*- coding: utf-8 -*-
"""
Authors: Tim Hessels
UNESCO-IHE 2016
Contact: t.hessels@unesco-ihe.org
Repository: https://github.com/wateraccounting/wa
Module: Collect/MOD13
"""
# import general python modules
import os
import numpy as np
import pandas as pd
import gdal
import urllib
impo... | apache-2.0 |
NeuroanatomyAndConnectivity/pipelines | src/clustering/clustering/cons_cluster.py | 2 | 2675 | import os
from nipype.interfaces.base import BaseInterface, \
BaseInterfaceInputSpec, traits, File, TraitedSpec
from nipype.utils.filemanip import split_filename
from sklearn.cluster import spectral_clustering as spectral
from sklearn.cluster import KMeans as km
from sklearn.cluster import Ward
from sklearn.cluste... | mit |
datapythonista/pandas | pandas/tests/indexes/multi/test_setops.py | 1 | 16895 | import numpy as np
import pytest
import pandas as pd
from pandas import (
CategoricalIndex,
Index,
IntervalIndex,
MultiIndex,
Series,
)
import pandas._testing as tm
@pytest.mark.parametrize("case", [0.5, "xxx"])
@pytest.mark.parametrize(
"method", ["intersection", "union", "difference", "symm... | bsd-3-clause |
numenta/htmresearch | projects/energy_based_pooling/energy_based_models/utils.py | 7 | 2554 | # ----------------------------------------------------------------------
# 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... | agpl-3.0 |
bbfamily/abu | abupy/TradeBu/ABuMLFeature.py | 1 | 33599 | # -*- encoding:utf-8 -*-
"""
内置特征定义，以及用户特征扩展，定义模块
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import ast
import datetime
import os
import numpy as np
from ..CoreBu import ABuEnv
# noinspection PyUnresolvedReferences
from ..CoreBu.ABuFixes impo... | gpl-3.0 |
shangwuhencc/shogun | examples/undocumented/python_modular/graphical/group_lasso.py | 26 | 7792 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
from numpy.random import rand, randn, permutation, multivariate_normal
from modshogun import BinaryLabels, RealFeatures, IndexBlock, IndexBlockGroup, FeatureBlockLogisticRegression
def generate_synthetic_logistic_data(n, p, L, blk_nnz, gcov, nstd)... | gpl-3.0 |
LiaoPan/scikit-learn | examples/neural_networks/plot_rbm_logistic_classification.py | 258 | 4609 | """
==============================================================
Restricted Boltzmann Machine features for digit classification
==============================================================
For greyscale image data where pixel values can be interpreted as degrees of
blackness on a white background, like handwritten... | bsd-3-clause |
leofdecarvalho/MachineLearning | 9. Artificial_Neural_Networks/evaluating_improving_tuning.py | 5 | 5048 | # Artificial Neural Network
# Installing Theano
# pip install --upgrade --no-deps git+git://github.com/Theano/Theano.git
# Installing Tensorflow
# pip install tensorflow
# Installing Keras
# pip install --upgrade keras
# Part 1 - Data Preprocessing
# Importing the libraries
import numpy as np
import matplotlib.pyp... | mit |
olafhauk/mne-python | mne/utils/__init__.py | 4 | 4476 | # # # WARNING # # #
# This list must also be updated in doc/_templates/autosummary/class.rst if it
# is changed here!
_doc_special_members = ('__contains__', '__getitem__', '__iter__', '__len__',
'__add__', '__sub__', '__mul__', '__div__',
'__neg__', '__hash__')
from ._b... | bsd-3-clause |
ZwEin27/digoie-annotation | digoie/core/ml/dataset/vector.py | 1 | 3874 | import re
import os
from sklearn.feature_extraction.text import CountVectorizer
from digoie.conf.storage import __root_dir__, __ml_datasets_dir__
from digoie.utils.symbols import do_newline_symbol
from operator import itemgetter
import numpy as np
def vectorize(raw, my_min_df=0.0005, my_max_df=0.5, update_feature_... | mit |
elkingtonmcb/scikit-learn | sklearn/feature_selection/variance_threshold.py | 238 | 2594 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: 3-clause BSD
import numpy as np
from ..base import BaseEstimator
from .base import SelectorMixin
from ..utils import check_array
from ..utils.sparsefuncs import mean_variance_axis
from ..utils.validation import check_is_fitted
class VarianceThreshold(BaseEstim... | bsd-3-clause |
equialgo/scikit-learn | sklearn/linear_model/setup.py | 83 | 1719 | import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('linear_model', parent_package, top_path)
cblas_libs, blas_info = get_blas_info... | bsd-3-clause |
mrustl/flopy | autotest/t020_test.py | 1 | 4369 | # Test modflow write adn run
import numpy as np
def analyticalWaterTableSolution(h1, h2, z, R, K, L, x):
h = np.zeros((x.shape[0]), np.float)
b1 = h1 - z
b2 = h2 - z
h = np.sqrt(b1 ** 2 - (x / L) * (b1 ** 2 - b2 ** 2) + (R * x / K) * (L - x)) + z
return h
def test_mfnwt_run():
import os
... | bsd-3-clause |
all-umass/ller | demo.py | 1 | 1074 | from ller import LLER, LocallyLinearEmbedding
from mpl_toolkits.mplot3d import Axes3D
from optparse import OptionParser
from sklearn.datasets import make_swiss_roll
import matplotlib.pyplot as plt
def demo(k):
X, t = make_swiss_roll(noise=1)
lle = LocallyLinearEmbedding(n_components=2, n_neighbors=k)
lle... | bsd-3-clause |
micahhausler/pandashells | pandashells/bin/p_example_data.py | 8 | 2130 | #! /usr/bin/env python
# standard library imports
import os
import sys # noqa
import argparse
import textwrap
import pandashells
def main():
# create a dict of data-set names and corresponding files
package_dir = os.path.dirname(os.path.realpath(pandashells.__file__))
sample_data_dir = os.path.realpath... | bsd-2-clause |
BigDataforYou/movie_recommendation_workshop_1 | big_data_4_you_demo_1/venv/lib/python2.7/site-packages/pandas/io/tests/sas/test_xport.py | 1 | 4258 | import pandas as pd
import pandas.util.testing as tm
from pandas.io.sas.sasreader import read_sas
import numpy as np
import os
# CSV versions of test xpt files were obtained using the R foreign library
# Numbers in a SAS xport file are always float64, so need to convert
# before making comparisons.
def numeric_as_f... | mit |
marcocaccin/scikit-learn | sklearn/datasets/base.py | 6 | 22957 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import sys
import shutil
from os import environ... | bsd-3-clause |
leonardbinet/Transilien-Api | api_etl/builder_feature_matrix.py | 2 | 35646 | """Module containing class to build feature matrices for prediction.
There are two kinds of features:
- either features for direct prediction model
- either features for recursive prediction model
Only the first one is used for now.
"""
from os import path, makedirs
import logging
from datetime import datetime, tim... | mit |
alex314159/bondpricer | BondDataModel.py | 1 | 29284 | """
Bond pricer - displays data from Bloomberg and Front, MVC architecture.
Written by Alexandre Almosni alexandre.almosni@gmail.com
(C) 2014-2017 Alexandre Almosni
Released under Apache 2.0 license. More info at http://www.apache.org/licenses/LICENSE-2.0
Classes:
MessageContainer: simple wrapper
RFDdata: us... | apache-2.0 |
potash/scikit-learn | examples/mixture/plot_concentration_prior.py | 25 | 5631 | """
========================================================================
Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture
========================================================================
This example plots the ellipsoids obtained from a toy dataset (mixture of three
Gaussians) fitte... | bsd-3-clause |
fyffyt/scikit-learn | 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 |
yavalvas/yav_com | build/matplotlib/lib/mpl_examples/pylab_examples/trigradient_demo.py | 7 | 3075 | """
Demonstrates computation of gradient with matplotlib.tri.CubicTriInterpolator.
"""
from matplotlib.tri import Triangulation, UniformTriRefiner,\
CubicTriInterpolator
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import math
#-----------------------------------------------------... | mit |
tracek/Ornithokrites | features.py | 1 | 6464 | # -*- coding: utf-8 -*-
"""
Created on Mon Dec 02 12:07:49 2013
@author: ltracews
"""
import os
import sys
import itertools
import numpy as np
import matplotlib.pyplot as plt
import yaafelib
class FeatureExtractor(object):
def __init__(self, app_config, rate):
self.ExtractedFeaturesList = ['LPC1_mean',... | gpl-3.0 |
juancruzgassoloncan/Udacity-Robo-nanodegree | src/rover/ex_4/extra_functions.py | 1 | 2040 | import numpy as np
import cv2
import matplotlib.image as mpimg
def perspect_transform(img, src, dst):
# Get transform matrix using cv2.getPerspectivTransform()
M = cv2.getPerspectiveTransform(src, dst)
# Warp image using cv2.warpPerspective()
# keep same size as input image
warped = cv2.warpPersp... | mit |
pcmoritz/arrow | python/pyarrow/tests/test_feather.py | 2 | 17854 | # 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 |
thunderhoser/GewitterGefahr | gewittergefahr/prediction_paper_2019/make_detection_figure.py | 1 | 16649 | """Makes figure to explain storm detection."""
import argparse
import numpy
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as pyplot
from gewittergefahr.gg_io import myrorss_and_mrms_io
from gewittergefahr.gg_io import storm_tracking_io as tracking_io
from gewittergefahr.gg_utils import time_conversi... | mit |
ElricleNecro/LibThese | scripts/animationv2.py | 1 | 1156 | #! /usr/bin/env python3
# -*- coding:Utf8 -*-
import os
import sys
import logging as log
import importlib
import matplotlib as ml
ml.use('agg')
import LibThese.Plot.Animation as lpa
from LibThese.Plot import Animate as an
PREFIX = os.path.dirname(__file__)
PLUGINS_DIR = os.path.abspath(
os.path.join(
PR... | lgpl-3.0 |
impactlab/eemeter | tests/structures/test_energy_trace.py | 1 | 4624 | from eemeter.structures import EnergyTrace
from eemeter.io.serializers import ArbitrarySerializer
import pandas as pd
import numpy as np
from datetime import datetime
import pytz
import pytest
@pytest.fixture
def interpretation():
return 'ELECTRICITY_CONSUMPTION_SUPPLIED'
def test_no_data_no_placeholder(interp... | mit |
nikitasingh981/scikit-learn | examples/neural_networks/plot_mlp_alpha.py | 58 | 4088 | """
================================================
Varying regularization in Multi-layer Perceptron
================================================
A comparison of different values for regularization parameter 'alpha' on
synthetic datasets. The plot shows that different alphas yield different
decision functions.
A... | bsd-3-clause |
Cyberface/nrutils_dev | review/notebooks/check-strain.py | 1 | 1492 | '''
The goal of this script is to compare the output of nrutils' strain calculation
method to the output of an independent MATLAB code of the same method. For convinience,
ascii data for the MATLAB routine's output is saved within this repository.
-- lionel.london@ligo.org 2016 --
'''
# Import useful things
from os.pa... | mit |
dhwang99/statistics_introduction | bayes_estimate/ex2.py | 1 | 3051 | #encoding: utf8
import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt
import pdb
'''
X1, X2..., Xn ~ N(mu, 1)
a. simulate a data set (using mu=5) consisting 100 observations
b. take f(mu)=1 and find the posterior desity. plot it
c. simulate 1000 draws from the posterior. Plot a histogram... | gpl-3.0 |
amarszalek/PyOrderedFuzzyTools | pyorderedfuzzy/ofmodels/ofgarch.py | 1 | 2859 | # -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
from pyorderedfuzzy.ofnumbers.ofnumber import OFNumber
from pyorderedfuzzy.ofmodels.ofseries import OFSeries
from arch import arch_model
__author__ = "amarszalek"
class OFGARCH(object):
def __init__(self):
super(OFGARCH, self).__init__()
... | mit |
lmallin/coverage_test | python_venv/lib/python2.7/site-packages/pandas/tests/io/json/test_json_table_schema.py | 9 | 18572 | """Tests for Table Schema integration."""
import json
from collections import OrderedDict
import numpy as np
import pandas as pd
import pytest
from pandas import DataFrame
from pandas.core.dtypes.dtypes import (
PeriodDtype, CategoricalDtype, DatetimeTZDtype)
from pandas.io.json.table_schema import (
as_json_... | mit |
supernifty/mgsa | mgsa/generate_all_reports.py | 1 | 131319 | #
# build the charts used in the final report
# generally these assume the analysis has been done; the command to do this is included in the function
#
import collections
import datetime
import math
import os
import re
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import pylab
import sys
... | mit |
ThinkOpen-Solutions/odoo | addons/resource/faces/timescale.py | 170 | 3902 | ############################################################################
# Copyright (C) 2005 by Reithinger GmbH
# mreithinger@web.de
#
# This file is part of faces.
#
# faces is free software; you can redistribute it and/or modify
# ... | agpl-3.0 |
ngoix/OCRF | sklearn/naive_bayes.py | 5 | 28895 | # -*- coding: utf-8 -*-
"""
The :mod:`sklearn.naive_bayes` module implements Naive Bayes algorithms. These
are supervised learning methods based on applying Bayes' theorem with strong
(naive) feature independence assumptions.
"""
# Author: Vincent Michel <vincent.michel@inria.fr>
# Minor fixes by Fabian Pedre... | bsd-3-clause |
dgies/incubator-airflow | airflow/contrib/hooks/bigquery_hook.py | 9 | 38929 | # -*- coding: utf-8 -*-
#
# 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, software
... | apache-2.0 |
ScottHull/Exoplanet-Pocketknife | old/strip_hefesto2.py | 1 | 1637 | import os
import pandas as pd
if __name__ == "__main__":
print("In what directory shall we parse?")
to_dir = input(">>> ")
for root, dirs, files in os.walk(os.getcwd() + "/" + to_dir, topdown=False):
operating_dir = root
if "fort.58" in str(root):
if "strip_hefe... | cc0-1.0 |
tdhopper/scikit-learn | sklearn/gaussian_process/tests/test_gaussian_process.py | 267 | 6813 | """
Testing for Gaussian Process module (sklearn.gaussian_process)
"""
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# Licence: BSD 3 clause
from nose.tools import raises
from nose.tools import assert_true
import numpy as np
from sklearn.gaussian_process import GaussianProcess
from sklearn.gaussian_process ... | bsd-3-clause |
HeraclesHX/scikit-learn | examples/gaussian_process/gp_diabetes_dataset.py | 223 | 1976 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
========================================================================
Gaussian Processes regression: goodness-of-fit on the 'diabetes' dataset
========================================================================
In this example, we fit a Gaussian Process model onto... | bsd-3-clause |
nanophotonics/nplab | nplab/analysis/calculate_MPEs.py | 1 | 3595 | # -*- coding: utf-8 -*-
"""
Created on Wed May 23 16:51:45 2018
@author: wmd22
A few functions for quick calculation ofs MPE's
"""
from __future__ import division
from past.utils import old_div
import matplotlib
#%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
#,average_power, rep_rate = 80E6,... | gpl-3.0 |
CospanDesign/python | image_processor/opencv_harris_test.py | 1 | 1036 | #! /usr/bin/env python
import cv2
import numpy as np
import matplotlib.pyplot as plt
from image_processor import *
print (TCOLORS.PURPLE + "OpenCV Harris Corner Detector" + TCOLORS.NORMAL)
try:
filename = FILENAME
except NameError:
#filename = 'chessboard.png'
#filename = 'chessboard.jpg'
filename ... | mit |
TNT-Samuel/Coding-Projects | DNS Server/Source - Copy/Lib/site-packages/dask/dataframe/io/json.py | 5 | 6650 | from __future__ import absolute_import
import io
import pandas as pd
from dask.bytes import open_files, read_bytes
import dask
def to_json(df, url_path, orient='records', lines=None, storage_options=None,
compute=True, encoding='utf-8', errors='strict',
compression=None, **kwargs):
"""Wri... | gpl-3.0 |
phobson/statsmodels | examples/python/ols.py | 30 | 5601 |
## Ordinary Least Squares
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
from statsmodels.sandbox.regression.predstd import wls_prediction_std
np.random.seed(9876789)
# ## OLS estimation
#
# Artificial data:
nsample = 100
x = np.linspace(0, 1... | bsd-3-clause |
huobaowangxi/scikit-learn | sklearn/__check_build/__init__.py | 345 | 1671 | """ Module to give helpful messages to the user that did not
compile the scikit properly.
"""
import os
INPLACE_MSG = """
It appears that you are importing a local scikit-learn source tree. For
this, you need to have an inplace install. Maybe you are in the source
directory and you need to try from another location.""... | bsd-3-clause |
MartinDelzant/scikit-learn | examples/cluster/plot_cluster_comparison.py | 246 | 4684 | """
=========================================================
Comparing different clustering algorithms on toy datasets
=========================================================
This example aims at showing characteristics of different
clustering algorithms on datasets that are "interesting"
but still in 2D. The last ... | bsd-3-clause |
botswana-harvard/microbiome | export/export_model.py | 1 | 2281 | import os
import pandas as pd
from datetime import date
from edc_model_to_dataframe import EdcModelToDataFrame
class ExportModel:
def __init__(self, model, consent_model, visit_lookup=None):
self.add_columns_for = visit_lookup or 'registered_subject'
self.visit_lookup = visit_lookup
sel... | gpl-2.0 |
rew4332/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/arithmetic_transform_test.py | 4 | 2327 | # Copyright 2016 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 applicable law or a... | apache-2.0 |
ashhher3/scikit-learn | sklearn/covariance/tests/test_graph_lasso.py | 37 | 2901 | """ Test the graph_lasso module.
"""
import sys
import numpy as np
from scipy import linalg
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_less
from sklearn.covariance import (graph_lasso, GraphLasso, GraphLassoCV,
empirical_... | bsd-3-clause |
mattgiguere/scikit-learn | sklearn/manifold/t_sne.py | 8 | 20008 | # Author: Alexander Fabisch -- <afabisch@informatik.uni-bremen.de>
# License: BSD 3 clause (C) 2014
# This is the standard t-SNE implementation. There are faster modifications of
# the algorithm:
# * Barnes-Hut-SNE: reduces the complexity of the gradient computation from
# N^2 to N log N (http://arxiv.org/abs/1301.... | bsd-3-clause |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/lib/mpl_toolkits/axes_grid1/axes_rgb.py | 7 | 4658 | import numpy as np
from axes_divider import make_axes_locatable, Size, locatable_axes_factory
def make_rgb_axes(ax, pad=0.01, axes_class=None, add_all=True):
"""
pad : fraction of the axes height.
"""
divider = make_axes_locatable(ax)
pad_size = Size.Fraction(pad, Size.AxesY(ax))
xsize = Siz... | mit |
njchiang/task-fmri-utils | fmri_core/rsa.py | 1 | 15154 | from scipy.stats import wilcoxon # , spearmanr <- this has a bug
from scipy.spatial.distance import pdist, squareform
from sklearn.model_selection import LeaveOneOut
from scipy.stats import mstats_basic
from scipy.stats import rankdata, distributions
import numpy as np
import warnings
from .utils import write_to_logge... | mit |
jblupus/PyLoyaltyProject | ccdf/ccdf.py | 1 | 3062 | from collections import Counter
import json
import math
import numpy as np
import pandas as pd
def get_language_data():
df = pd.read_csv('../data/profile/users_profile_data.csv')
df['language'] = map(lambda lang: 'en' if 'en-' in lang else lang, df['language'])
df['language'] = map(lambda lang: 'es' if ... | bsd-2-clause |
liyu1990/sklearn | sklearn/linear_model/tests/test_sparse_coordinate_descent.py | 244 | 9986 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_true
from sklearn.utils.t... | bsd-3-clause |
cin/spark | python/pyspark/sql/functions.py | 1 | 85981 | #
# 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 |
nmih/ssbio | ssbio/pipeline/atlas2.py | 2 | 68022 | import logging
import os
import os.path as op
import sys
import cobra.flux_analysis
import cobra.manipulation
import numpy as np
import pandas as pd
from Bio import SeqIO
from cobra.core import DictList
import json
import ssbio.core.modelpro
import ssbio.databases.ncbi
import ssbio.databases.patric
import ssbio.protei... | mit |
beercanlah/flapibrew | runserver.py | 1 | 5566 | import tornado.httpserver
import tornado.websocket
import tornado.ioloop
import tornado.web
from tornado.wsgi import WSGIContainer
import json
import numpy as np
import pandas as pd
import datetime
from cStringIO import StringIO
from collections import namedtuple
from flapibrew import app
import matplotlib
import mat... | mit |
arogozhnikov/OBDT | pruning/_matrixnetapplier.py | 2 | 8855 | from __future__ import print_function, division, absolute_import
"""
This class is used to build predictions of MatrixNet classifier
it uses .mx format of MatrixNet formula.
"""
__author__ = 'Alex Rogozhnikov, Egor Khairullin'
import struct
import numpy
class MatrixnetClassifier(object):
def __init__(self, form... | mit |
fspaolo/scikit-learn | sklearn/metrics/metrics.py | 2 | 72648 | # -*- coding: utf-8 -*-
"""Utilities to evaluate the predictive performance of models
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandr... | bsd-3-clause |
Ziqi-Li/bknqgis | numpy/doc/source/conf.py | 2 | 10015 | # -*- coding: utf-8 -*-
from __future__ import division, absolute_import, print_function
import sys, os, re
# Check Sphinx version
import sphinx
if sphinx.__version__ < "1.2.1":
raise RuntimeError("Sphinx 1.2.1 or newer required")
needs_sphinx = '1.0'
# ----------------------------------------------------------... | gpl-2.0 |
yohanashima/envelope | horakusen.py | 1 | 1847 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid.axislines import SubplotZero
# 図の背景の諸体裁を設定
# 作図スペースを用意(?)。個々のコードの意味がわかりません。
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
# 軸の設定
ax.axhline(linewidth=1.2, color="black")
ax.axvline(linewidth... | gpl-3.0 |
heprom/pymicro | examples/plotting/radon.py | 1 | 1136 | import os, numpy as np
from pymicro.file.file_utils import HST_read
from skimage.transform import radon
from matplotlib import pyplot as plt
if __name__ == '__main__':
'''
Example of use of the radon transform.
'''
data = HST_read('../data/mousse_250x250x250_uint8.raw', autoparse_filename=True, zrange=... | mit |
googleinterns/cabby | cabby/data/metagraph/utils.py | 1 | 11492 | # coding=utf-8
# 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 ... | apache-2.0 |
h2educ/scikit-learn | sklearn/utils/fixes.py | 39 | 13318 | """Compatibility fixes for older version of python, numpy and scipy
If you add content to this file, please give the version of the package
at which the fixe is no longer needed.
"""
# Authors: Emmanuelle Gouillart <emmanuelle.gouillart@normalesup.org>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# ... | bsd-3-clause |
kevin-intel/scikit-learn | examples/kernel_approximation/plot_scalable_poly_kernels.py | 15 | 7266 | """
=======================================================
Scalable learning with polynomial kernel aproximation
=======================================================
This example illustrates the use of :class:`PolynomialCountSketch` to
efficiently generate polynomial kernel feature-space approximations.
This is us... | bsd-3-clause |
takkasila/TwitGeoSpa | province_connection_table.py | 1 | 5080 | import sys
sys.path.insert(0, './Province')
import csv
import twit_extract_feature
import pandas
from provinces import *
from user_tracker import *
from math import floor
class ProvinceTable:
def __init__(self, provinces):
self.provinces = provinces
self.table = [[0 for x in range(len(provinces))] ... | mit |
aewhatley/scikit-learn | sklearn/metrics/classification.py | 28 | 67703 | """Metrics to assess performance on classification task given classe prediction
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gram... | bsd-3-clause |
ashhher3/seaborn | doc/conf.py | 25 | 9149 | # -*- coding: utf-8 -*-
#
# seaborn documentation build configuration file, created by
# sphinx-quickstart on Mon Jul 29 23:25:46 2013.
#
# 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... | bsd-3-clause |
AlexanderFabisch/scikit-learn | examples/manifold/plot_mds.py | 45 | 2731 | """
=========================
Multi-dimensional scaling
=========================
An illustration of the metric and non-metric MDS on generated noisy data.
The reconstructed points using the metric MDS and non metric MDS are slightly
shifted to avoid overlapping.
"""
# Author: Nelle Varoquaux <nelle.varoquaux@gmail.... | bsd-3-clause |
marionleborgne/nupic.research | projects/sound_encoder/live_sound_encoding_demo.py | 12 | 2494 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions ... | agpl-3.0 |
Caranarq/01_Dmine | 99_Descentralizacion/P9901/P9901.py | 1 | 2791 | # -*- coding: utf-8 -*-
"""
Started on thu, jun 21st, 2018
@author: carlos.arana
"""
# Librerias utilizadas
import pandas as pd
import sys
module_path = r'D:\PCCS\01_Dmine\Scripts'
if module_path not in sys.path:
sys.path.append(module_path)
from VarInt.VarInt import VarInt
from classes.Meta import Meta
from Comp... | gpl-3.0 |
florian-wagner/gimli | python/pygimli/viewer/modelview.py | 1 | 5493 | # -*- coding: utf-8 -*-
"""pygimli model viewer functions."""
import matplotlib.pyplot as plt
import numpy as np
import pygimli as pg
from matplotlib.patches import Rectangle
# from math import sqrt, floor, ceil
def showmymatrix(A, x, y, dx=2, dy=1, xlab=None, ylab=None, cbar=None):
"""
Pls.
insert short... | gpl-3.0 |
xmnlab/minilab | labtrans/daq/mswim_finite.py | 1 | 3511 | # -*- coding: utf-8 -*-
"""
Created on Tue Oct 8 16:11:48 2013
@author: ivan
"""
from __future__ import print_function, division
from PyDAQmx import *
from PyDAQmx.DAQmxFunctions import *
from PyDAQmx.DAQmxConstants import *
from matplotlib import pyplot as plt
import numpy as np
import time
class AcquisitionFinit... | gpl-3.0 |
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