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 |
|---|---|---|---|---|---|
tosolveit/scikit-learn | sklearn/metrics/regression.py | 175 | 16953 | """Metrics to assess performance on regression task
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.gramfort@inria.fr>
# Ma... | bsd-3-clause |
themrmax/scikit-learn | sklearn/cross_decomposition/pls_.py | 4 | 30509 | """
The :mod:`sklearn.pls` module implements Partial Least Squares (PLS).
"""
# Author: Edouard Duchesnay <edouard.duchesnay@cea.fr>
# License: BSD 3 clause
import warnings
from abc import ABCMeta, abstractmethod
import numpy as np
from scipy.linalg import pinv2, svd
from scipy.sparse.linalg import svds
from ..base... | bsd-3-clause |
reflectometry/osrefl | osrefl/loaders/binned_data.py | 1 | 32960 | #!/usr/bin/python
# -*- coding: utf-8 -*-
#
# check to see if all parameters are set on the command line
# if they are, then don't open GUI interface
from math import *
import sys
#from Tkinter import *
#import tkMessageBox
#import tkFileDialog
#from FileDialog import *
from osrefl.loaders.reduction import *
import osr... | bsd-3-clause |
bigswitch/snac-nox | src/scripts/buildtest/lookup.py | 1 | 1569 | #!/usr/bin/python
import matplotlib
matplotlib.use('Agg')
import pickle
import pwd
import os
import info
import graph
def create_image(argv):
p = info.Profile()
b = info.Build()
t = info.Test()
r = info.Result()
values = []
for v in argv[1:]:
if v == 'Tru... | gpl-3.0 |
krikru/tensorflow-opencl | 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 |
rekhajoshm/spark | python/pyspark/ml/clustering.py | 5 | 50284 | #
# 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 |
cloudera/ibis | ibis/backends/tests/test_geospatial.py | 2 | 17942 | """ Tests for geo spatial data types"""
import numpy as np
import pytest
from numpy import testing
from pytest import param
import ibis
geopandas = pytest.importorskip('geopandas')
shapely = pytest.importorskip('shapely')
shapely_wkt = pytest.importorskip('shapely.wkt')
# geo literals declaration
point_0 = ibis.lite... | apache-2.0 |
juvoinc/airflow | airflow/hooks/presto_hook.py | 24 | 3472 | # -*- 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 |
hypergravity/hrs | setup.py | 1 | 1199 | from distutils.core import setup
if __name__ == '__main__':
setup(
name='hrs',
version='1.2.2',
author='Bo Zhang',
author_email='bozhang@nao.cas.cn',
# py_modules=['hrs'],
description='High Resolution Spectrograph (2.16m) Reduction pipeline.', # short description
... | bsd-3-clause |
CGATOxford/proj029 | scripts/PipelineProj029.py | 1 | 11837 | #################################################
# classes and functions for pipeline_proj029.py
#################################################
import sqlite3
import os, re, sys
import collections
from pandas import *
import CGAT.Pipeline as P
from rpy2.robjects import r as R
def buildRelativeAbundanceMatrix(dat... | bsd-3-clause |
CVML/scikit-learn | examples/cluster/plot_adjusted_for_chance_measures.py | 286 | 4353 | """
==========================================================
Adjustment for chance in clustering performance evaluation
==========================================================
The following plots demonstrate the impact of the number of clusters and
number of samples on various clustering performance evaluation me... | bsd-3-clause |
CooperLuan/crm_for_shaodong | main.py | 1 | 4965 | import os
from datetime import datetime
import logbook
from flask import Flask, render_template, jsonify, request
import pandas as pd
import numpy as np
app = Flask('StatsWeb')
log = logbook
DATA = {
'df': None,
'select_cols': [],
'sum_cols': [],
}
def _setup(stream):
global DATA
df = pd.read_ex... | mit |
kevin-intel/scikit-learn | sklearn/cluster/tests/test_affinity_propagation.py | 2 | 9355 | """
Testing for Clustering methods
"""
import numpy as np
import pytest
from scipy.sparse import csr_matrix
from sklearn.exceptions import ConvergenceWarning
from sklearn.utils._testing import assert_array_equal
from sklearn.cluster import AffinityPropagation
from sklearn.cluster._affinity_propagation import (
... | bsd-3-clause |
rmeertens/paparazzi | sw/airborne/test/stabilization/compare_ref_quat.py | 48 | 1123 | #! /usr/bin/env python
from __future__ import division, print_function, absolute_import
import numpy as np
import matplotlib.pyplot as plt
from ref_quat_float import RefQuatFloat
from ref_quat_int import RefQuatInt
steps = 512 * 2
ref_float_res = np.zeros((steps, 3))
ref_int_res = np.zeros((steps, 3))
ref_float = ... | gpl-2.0 |
schets/scikit-learn | sklearn/semi_supervised/tests/test_label_propagation.py | 307 | 1974 | """ test the label propagation module """
import nose
import numpy as np
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {'kernel': 'rbf'}),
(label_propa... | bsd-3-clause |
mne-tools/mne-tools.github.io | 0.16/_downloads/plot_ssp_projs_sensitivity_map.py | 11 | 1268 | """
==================================
Sensitivity map of SSP projections
==================================
This example shows the sources that have a forward field
similar to the first SSP vector correcting for ECG.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause... | bsd-3-clause |
chrisburr/scikit-learn | examples/feature_stacker.py | 50 | 1910 | """
=================================================
Concatenating multiple feature extraction methods
=================================================
In many real-world examples, there are many ways to extract features from a
dataset. Often it is beneficial to combine several methods to obtain good
performance. Th... | bsd-3-clause |
xzh86/scikit-learn | examples/cluster/plot_dict_face_patches.py | 337 | 2747 | """
Online learning of a dictionary of parts of faces
==================================================
This example uses a large dataset of faces to learn a set of 20 x 20
images patches that constitute faces.
From the programming standpoint, it is interesting because it shows how
to use the online API of the sciki... | bsd-3-clause |
ryanjmccall/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/lines.py | 69 | 48233 | """
This module contains all the 2D line class which can draw with a
variety of line styles, markers and colors.
"""
# TODO: expose cap and join style attrs
from __future__ import division
import numpy as np
from numpy import ma
from matplotlib import verbose
import artist
from artist import Artist
from cbook import ... | gpl-3.0 |
margulies/topography | utils/network_eigenvector_centrality.py | 6 | 2062 | import os, h5py
from time import time
import numpy as np
from scipy import sparse
from sklearn.utils import extmath
"""Import data:
"""
def importData(sub)
f = h5py.File(('/scr/litauen1/%s.hcp.lh.mat' % sub),'r')
data = np.array(f.get('connData'))
cortex = np.array(f.get('cortex')) - 1
return data, c... | mit |
williford/nolearn | nolearn/lasagne/tests/test_base.py | 1 | 21757 | import pickle
from lasagne.layers import ConcatLayer
from lasagne.layers import DenseLayer
from lasagne.layers import InputLayer
from lasagne.layers import Layer
from lasagne.nonlinearities import identity
from lasagne.nonlinearities import softmax
from lasagne.objectives import categorical_crossentropy
from lasagne.u... | mit |
CDIPS-AI-2017/pensieve | Notebooks/word2vec/run_Word2Vec.py | 1 | 4391 | # *******************************************************************************
# **
# ** Author: Michael Lomnitz (mrlomnitz@lbl.gov)
# ** Python module to run word embedding (word2vec) using skipgram or continuos
# ** bag of words (CBOW) models. Output is then plotted using SKlearn ... | apache-2.0 |
janelia-idf/sleep_assay | host/python/sleep_assay/sleep_assay.py | 2 | 31231 | # -*- coding: utf-8 -*-
from __future__ import print_function, division
import serial
import time
import atexit
import yaml
import sys
import argparse
import datetime
import platform
import json
import csv
import os
import numpy as np
import matplotlib.pyplot as plt
import math
from serial_device2 import SerialDevice,... | bsd-3-clause |
nmartensen/pandas | pandas/core/generic.py | 1 | 251892 | # pylint: disable=W0231,E1101
import collections
import warnings
import operator
import weakref
import gc
import json
import numpy as np
import pandas as pd
from pandas._libs import tslib, lib
from pandas.core.dtypes.common import (
_ensure_int64,
_ensure_object,
is_scalar,
is_number,
is_integer, ... | bsd-3-clause |
tlawrence3/tsfm | docs/conf.py | 1 | 5972 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# tsfm documentation build configuration file, created by
# sphinx-quickstart on Thu Aug 31 15:30:57 2017.
#
# 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
# autog... | lgpl-3.0 |
wanggang3333/scikit-learn | sklearn/neighbors/approximate.py | 128 | 22351 | """Approximate nearest neighbor search"""
# Author: Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>
# Joel Nothman <joel.nothman@gmail.com>
import numpy as np
import warnings
from scipy import sparse
from .base import KNeighborsMixin, RadiusNeighborsMixin
from ..base import BaseEstimator
from ..utils.va... | bsd-3-clause |
sileht/gnocchi | gnocchi/carbonara.py | 1 | 34814 | # -*- encoding: utf-8 -*-
#
# Copyright © 2016-2018 Red Hat, Inc.
# Copyright © 2014-2015 eNovance
#
# 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/LICE... | apache-2.0 |
olafhauk/mne-python | mne/tests/test_source_space.py | 7 | 43205 | # -*- coding: utf-8 -*-
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
from shutil import copytree
import pytest
import scipy
import numpy as np
from numpy.testing import (assert_array_equal, assert_allclose... | bsd-3-clause |
ceos-seo/Data_Cube_v2 | agdc-v2/datacube/analytics/utils/analytics_utils.py | 1 | 5498 | # ------------------------------------------------------------------------------
# Name: analytics_utils.py
# Purpose: Helper utilities
#
# Author: Peter Wang
#
# Created: 14 July 2015
# Copyright: 2015 Commonwealth Scientific and Industrial Research Organisation
# (CSIRO)
# Ada... | apache-2.0 |
diegocavalca/Studies | programming/Python/Machine-Learning/Introduction-Udacity/final_project/tester.py | 14 | 4509 | #!/usr/bin/pickle
""" a basic script for importing student's POI identifier,
and checking the results that they get from it
requires that the algorithm, dataset, and features list
be written to my_classifier.pkl, my_dataset.pkl, and
my_feature_list.pkl, respectively
that process should happen a... | cc0-1.0 |
idlead/scikit-learn | examples/cluster/plot_color_quantization.py | 297 | 3443 | # -*- coding: utf-8 -*-
"""
==================================
Color Quantization using K-Means
==================================
Performs a pixel-wise Vector Quantization (VQ) of an image of the summer palace
(China), reducing the number of colors required to show the image from 96,615
unique colors to 64, while pre... | bsd-3-clause |
ishank08/scikit-learn | examples/classification/plot_classification_probability.py | 138 | 2871 | """
===============================
Plot classification probability
===============================
Plot the classification probability for different classifiers. We use a 3
class dataset, and we classify it with a Support Vector classifier, L1
and L2 penalized logistic regression with either a One-Vs-Rest or multinom... | bsd-3-clause |
vlsd/nlsymb | flat_sim.py | 1 | 4781 | # this is written for python2.7
# will not work with python3.3
# TODO figure out why!?
import numpy as np
import sympy as sym
from sympy import Symbol as S
import nlsymb
# nlsymb = reload(nlsymb)
from nlsymb import Timer, LineSearch, np, colored
from nlsymb.sys import *
from nlsymb.lqr import *
# coming soon to a ... | mit |
fhirschmann/penchy | penchy/jobs/plots.py | 1 | 14963 | """
This module provides plotting filters.
.. moduleauthor:: Pascal Wittmann <mail@pascal-wittmann.de>
:copyright: PenchY Developers 2011-2012, see AUTHORS
:license: MIT License, see LICENSE
"""
from __future__ import division
import itertools
import logging
from penchy.jobs.elements import Filter
from penchy... | mit |
CWSL/access-cm-tools | visualise/zonal_movie.py | 1 | 13846 | #!/usr/bin/env python
import sys
import numpy as np
import netCDF4 as nc
import argparse
import os
import shutil
import glob
import subprocess as sp
import matplotlib
#matplotlib.use('Agg')
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import matplotlib.colors as colors
"""
Make a movie whi... | apache-2.0 |
hillairet/analysis-for-safer-roads | CSVtoSQLconverter.py | 2 | 9874 | #!/usr/bin/python
import pandas as pd
from pandas import DataFrame,Series
import numpy as np
import datetime as dt
from optparse import OptionParser
import mysql.connector
from sqlalchemy import create_engine
import netrc
def clean_up_characteristics(Year):
'''Return the cleaned up dataframe of the characteris... | gpl-3.0 |
saifrahmed/bokeh | bokeh/charts/builder/timeseries_builder.py | 26 | 6252 | """This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the TimeSeries class which lets you build your TimeSeries charts just
passing the arguments to the Chart class and calling the proper functions.
"""
#-----------------------------------------------------... | bsd-3-clause |
cainesap/mapMakeR | languagesOfTheWorld/fetchGlottologData.py | 1 | 4909 | ## parse Glottolog JSON data
## PRELIMS
# libs
import json, urllib2
import pandas as pd
# vars
withgeoCount = 0 # count languoids with lat/long coordinates
nongeoCount = 0 # count languoids without lat/long coordinates
maxclass = 0 # what's the longest classification?
NONGEOs = []; IDs = []; NAMEs = []; TYPEs = []... | mit |
abhitopia/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py | 88 | 31139 | # 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 |
abhisg/scikit-learn | sklearn/cross_decomposition/tests/test_pls.py | 215 | 11427 | import numpy as np
from sklearn.utils.testing import (assert_array_almost_equal,
assert_array_equal, assert_true, assert_raise_message)
from sklearn.datasets import load_linnerud
from sklearn.cross_decomposition import pls_
from nose.tools import assert_equal
def test_pls():
d =... | bsd-3-clause |
zaxliu/deepnap | experiments/kdd-exps/experiment_message_2016-6-12_G5_BUF2_AR1_b5_legacy.py | 1 | 4372 | # System built-in modules
import time
from datetime import datetime
import sys
import os
from multiprocessing import Pool
# Project dependency modules
import pandas as pd
pd.set_option('mode.chained_assignment', None) # block warnings due to DataFrame value assignment
import lasagne
# Project modules
sys.path.append('... | bsd-3-clause |
dancingdan/tensorflow | tensorflow/contrib/factorization/python/ops/kmeans_test.py | 9 | 21832 | # 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 |
rs2/pandas | pandas/tests/indexes/timedeltas/test_partial_slicing.py | 3 | 1347 | import numpy as np
import pytest
from pandas import Series, timedelta_range
import pandas._testing as tm
class TestSlicing:
def test_partial_slice(self):
rng = timedelta_range("1 day 10:11:12", freq="h", periods=500)
s = Series(np.arange(len(rng)), index=rng)
result = s["5 day":"6 day"]
... | bsd-3-clause |
peterwilletts24/Python-Scripts | plot_scripts/Rain/Diurnal/sea_diurnal_rain_plot_domain_constrain_large_domain.py | 2 | 10610 | """
Load npy xy, plot and save
"""
import os, sys
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
import matplotlib.pyplot as plt
import matplotlib.cm as mpl_cm
from matplotlib import rc
from matplotlib.font_manager import FontProperties
from matplotlib import rcPa... | mit |
jperla/happynews | model/tlc_ppc.py | 1 | 2120 | #!/usr/bin/env python
"""
Runs PPC on a TLC model I made and graphs them.
Copyright (C) 2011 Joseph Perla
GNU Affero General Public License. See <http://www.gnu.org/licenses/>.
"""
import glob
import numpy as np
import jsondata
import ppc
if __name__=='__main__':
s = 'midterm/mytlc-output-15-%s'
... | agpl-3.0 |
cauchycui/scikit-learn | sklearn/svm/tests/test_svm.py | 116 | 31653 | """
Testing for Support Vector Machine module (sklearn.svm)
TODO: remove hard coded numerical results when possible
"""
import numpy as np
import itertools
from numpy.testing import assert_array_equal, assert_array_almost_equal
from numpy.testing import assert_almost_equal
from scipy import sparse
from nose.tools im... | bsd-3-clause |
jreback/pandas | pandas/tests/io/parser/test_parse_dates.py | 1 | 48127 | """
Tests date parsing functionality for all of the
parsers defined in parsers.py
"""
from datetime import date, datetime
from io import StringIO
from dateutil.parser import parse as du_parse
from hypothesis import given, settings, strategies as st
import numpy as np
import pytest
import pytz
from pandas._libs.tslib... | bsd-3-clause |
boada/HETDEXCluster | analysis/examples/emcee_cosmo.py | 1 | 4356 | import numpy as np
import emcee
from astroML.datasets import generate_mu_z
from astroML.cosmology import Cosmology
import matplotlib.pyplot as plt
#from astLib import astCalc as aca
def compute_sigma_level(trace1, trace2, nbins=20):
"""From a set of traces, bin by number of standard deviations"""
L, xbins, yb... | mit |
TGM-HIT/eqep-api | eqep/shakemap/shakemap.py | 1 | 6596 | import matplotlib.pyplot as plot
from eqep.data.earthquake import EarthQuake
class ShakeMap:
"""This class represents a ShakeMap, i.e. a visual representation of
interpolated earthquake peak ground velocities in a certain area.
It is completely customizable in interpolation algorithm, scale and styling.
... | mit |
bgris/ODL_bgris | lib/python3.5/site-packages/scipy/interpolate/fitpack2.py | 12 | 61523 | """
fitpack --- curve and surface fitting with splines
fitpack is based on a collection of Fortran routines DIERCKX
by P. Dierckx (see http://www.netlib.org/dierckx/) transformed
to double routines by Pearu Peterson.
"""
# Created by Pearu Peterson, June,August 2003
from __future__ import division, print_function, abs... | gpl-3.0 |
andrewnc/scikit-learn | sklearn/datasets/tests/test_rcv1.py | 322 | 2414 | """Test the rcv1 loader.
Skipped if rcv1 is not already downloaded to data_home.
"""
import errno
import scipy.sparse as sp
import numpy as np
from sklearn.datasets import fetch_rcv1
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing i... | bsd-3-clause |
OpenSourcePolicyCenter/taxdata | puf_stage1/stage1.py | 1 | 14312 | import pandas as pd
import os
CUR_PATH = os.path.abspath(os.path.dirname(__file__))
SYR = 2011 # calendar year used to normalize factors
BEN_SYR = 2014 # calendar year used just for the benefit start year
EYR = 2029 # last calendar year we have data for
SOI_YR = 2014 # most recently available SOI estimates
# defi... | mit |
seckcoder/lang-learn | python/sklearn/examples/linear_model/plot_sgd_separating_hyperplane.py | 8 | 1200 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print __doc__
import numpy as np... | unlicense |
ECP-CANDLE/Benchmarks | Pilot1/Uno_UQ/calibration/calibration_HET.py | 1 | 4100 | #! /usr/bin/env python
from __future__ import division, print_function
import pandas as pd
import sys
import os
import pickle
import dill
lib_path2 = os.path.abspath(os.path.join('..', '..', 'common'))
sys.path.append(lib_path2)
import candle_keras as candle
def read_file(path, filename):
df_data = pd.read_cs... | mit |
wdurhamh/statsmodels | statsmodels/genmod/generalized_estimating_equations.py | 19 | 97130 | """
Procedures for fitting marginal regression models to dependent data
using Generalized Estimating Equations.
References
----------
KY Liang and S Zeger. "Longitudinal data analysis using
generalized linear models". Biometrika (1986) 73 (1): 13-22.
S Zeger and KY Liang. "Longitudinal Data Analysis for Discrete and
... | bsd-3-clause |
sarahgrogan/scikit-learn | examples/applications/plot_prediction_latency.py | 234 | 11277 | """
==================
Prediction Latency
==================
This is an example showing the prediction latency of various scikit-learn
estimators.
The goal is to measure the latency one can expect when doing predictions
either in bulk or atomic (i.e. one by one) mode.
The plots represent the distribution of the pred... | bsd-3-clause |
lht142934/trading-with-python | lib/widgets.py | 78 | 3012 | # -*- coding: utf-8 -*-
"""
A collection of widgets for gui building
Copyright: Jev Kuznetsov
License: BSD
"""
from __future__ import division
import sys
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import numpy as np
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as Figur... | bsd-3-clause |
ljwolf/pysal | pysal/contrib/geotable/ops/tests/test_accessors.py | 6 | 19829 | from ....pdio import read_files as rf
from .. import _accessors as to_test
from .....cg import Point, Chain, Polygon, Rectangle, LineSegment
from .....common import pandas, RTOL, ATOL
from .....examples import get_path
import numpy as np
import unittest as ut
PANDAS_EXTINCT = pandas is None
@ut.skipIf(PANDAS_EXTINCT, ... | bsd-3-clause |
raingo/coco-caption | pycocotools/coco.py | 5 | 15190 | __author__ = 'tylin'
__version__ = '1.0.1'
# Interface for accessing the Microsoft COCO dataset.
# Microsoft COCO is a large image dataset designed for object detection,
# segmentation, and caption generation. pycocotools is a Python API that
# assists in loading, parsing and visualizing the annotations in COCO.
# Ple... | bsd-2-clause |
james4424/nest-simulator | doc/nest_by_example/scripts/one_neuron_with_sine_wave.py | 4 | 1514 | # -*- coding: utf-8 -*-
#
# one_neuron_with_sine_wave.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 t... | gpl-2.0 |
DSLituiev/scikit-learn | examples/cluster/plot_face_segmentation.py | 71 | 2839 | """
===================================================
Segmenting the picture of a raccoon face 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... | bsd-3-clause |
janusassetallocation/loman | loman/visualization.py | 1 | 4378 | import matplotlib as mpl
import networkx as nx
import pydotplus
import six
from loman.consts import NodeAttributes, States
state_colors = {
None: '#ffffff', # xkcd white
States.PLACEHOLDER: '#f97306', # xkcd orange
States.UNINITIALIZED: '#0343df', # xkcd blue
States.STALE: '... | bsd-3-clause |
themrmax/scikit-learn | examples/datasets/plot_iris_dataset.py | 36 | 1929 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
The Iris Dataset
=========================================================
This data sets consists of 3 different types of irises'
(Setosa, Versicolour, and Virginica) petal and sepal
length, stored in a 150x4 numpy... | bsd-3-clause |
djgagne/scikit-learn | examples/classification/plot_classifier_comparison.py | 181 | 4699 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=====================
Classifier comparison
=====================
A comparison of a several classifiers in scikit-learn on synthetic datasets.
The point of this example is to illustrate the nature of decision boundaries
of different classifiers.
This should be taken with ... | bsd-3-clause |
aledionigi/trading-with-python | cookbook/getDataFromYahooFinance.py | 77 | 1391 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 16 18:37:23 2011
@author: jev
"""
from urllib import urlretrieve
from urllib2 import urlopen
from pandas import Index, DataFrame
from datetime import datetime
import matplotlib.pyplot as plt
sDate = (2005,1,1)
eDate = (2011,10,1)
symbol = 'SPY'
fNa... | bsd-3-clause |
suriyan/ethnicolr | ethnicolr/pred_wiki_name.py | 1 | 4512 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import argparse
import pandas as pd
import numpy as np
from keras.models import load_model
from keras.preprocessing import sequence
from pkg_resources import resource_filename
from .utils import column_exists, find_ngrams, fixup_columns
MODELFN = "models/wiki... | mit |
derDavidT/sympy | sympy/external/importtools.py | 85 | 7294 | """Tools to assist importing optional external modules."""
from __future__ import print_function, division
import sys
# Override these in the module to change the default warning behavior.
# For example, you might set both to False before running the tests so that
# warnings are not printed to the console, or set bo... | bsd-3-clause |
pv/scikit-learn | examples/text/hashing_vs_dict_vectorizer.py | 284 | 3265 | """
===========================================
FeatureHasher and DictVectorizer Comparison
===========================================
Compares FeatureHasher and DictVectorizer by using both to vectorize
text documents.
The example demonstrates syntax and speed only; it doesn't actually do
anything useful with the e... | bsd-3-clause |
brean/python-pathfinding | test/csv_pandas_test.py | 1 | 1082 | import os
import pandas
import numpy as np
from pathfinding.core.diagonal_movement import DiagonalMovement
from pathfinding.core.grid import Grid
from pathfinding.finder.a_star import AStarFinder
BASE_PATH = os.path.abspath(os.path.dirname(__file__))
CSV_FILE = os.path.join(BASE_PATH, 'csv_file.csv')
def _find(matr... | mit |
KarchinLab/2020plus | scripts/python/convert_gene_names.py | 1 | 3900 | import pandas as pd
import numpy as np
import csv
import argparse
import IPython
already_converted = {}
def parse_arguments():
info = 'Convert gene names to approved HUGO symbol'
parser = argparse.ArgumentParser(description=info)
help_str = 'Path to HUGO name file'
parser.add_argument('-hugo', '--hu... | apache-2.0 |
hainm/statsmodels | statsmodels/sandbox/tsa/examples/ex_mle_arma.py | 33 | 4587 | # -*- coding: utf-8 -*-
"""
TODO: broken because of changes to arguments and import paths
fixing this needs a closer look
Created on Thu Feb 11 23:41:53 2010
Author: josef-pktd
copyright: Simplified BSD see license.txt
"""
from __future__ import print_function
import numpy as np
from numpy.testing import assert_almost... | bsd-3-clause |
sarahgrogan/scikit-learn | examples/datasets/plot_iris_dataset.py | 283 | 1928 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
The Iris Dataset
=========================================================
This data sets consists of 3 different types of irises'
(Setosa, Versicolour, and Virginica) petal and sepal
length, stored in a 150x4 numpy... | bsd-3-clause |
SkiNgK/RNA-Diagnostico-Diabetes-Mellitus | rnaDiabetesGr3.py | 1 | 15906 | # -*- coding: utf-8 -*-
from pybrain.supervised.trainers import BackpropTrainer
from pybrain.tools.shortcuts import buildNetwork
from pybrain.structure import TanhLayer
from pybrain.structure import LinearLayer
from pybrain.structure import SigmoidLayer
from pybrain.datasets import SupervisedDataSet
from Tkinter import... | mit |
gtoonstra/airflow | airflow/contrib/hooks/salesforce_hook.py | 10 | 12428 | # -*- 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 |
nmayorov/scikit-learn | sklearn/cluster/tests/test_hierarchical.py | 58 | 19797 | """
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 |
fmacias64/deap | examples/coev/coop_evol.py | 12 | 6361 | # This file is part of DEAP.
#
# DEAP is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as
# published by the Free Software Foundation, either version 3 of
# the License, or (at your option) any later version.
#
# DEAP is distributed ... | lgpl-3.0 |
dmsuehir/spark-tk | python/sparktk/frame/constructors/import_pandas.py | 2 | 8962 | # 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 |
bloyl/mne-python | mne/channels/tests/test_layout.py | 4 | 14417 | # 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>
#
# License: Simplified BSD
import copy
import os.path as op
import numpy as np
from numpy.testing im... | bsd-3-clause |
karstenw/nodebox-pyobjc | examples/Extended Application/sklearn/examples/model_selection/plot_train_error_vs_test_error.py | 1 | 3385 | """
=========================
Train error vs Test error
=========================
Illustration of how the performance of an estimator on unseen data (test data)
is not the same as the performance on training data. As the regularization
increases the performance on train decreases while the performance on test
is optim... | mit |
jrh154/ChibbarGroup | Phylogeny Scripts/Function_Library.py | 2 | 7275 | from Bio import SeqIO, Entrez
import pandas as pd
import numpy as np
from os.path import join, isfile, isdir
from os import remove, mkdir, listdir
import sys
Entrez.email = 'john.hayes@usask.ca'
#Reads a CSV file containing accession number, species name, family group, and protein type info
#and returns a dictionary ... | mit |
ryanpdwyer/hdf5plotter | setup.py | 1 | 1784 | #!/usr/bin/env python
import os
import sys
from setuptools import setup
# See https://github.com/warner/python-versioneer
import versioneer
versioneer.VCS = 'git'
versioneer.versionfile_source = 'hdf5plotter/_version.py'
versioneer.versionfile_build = 'hdf5plotter/_version.py'
versioneer.tag_prefix = '' # tags are l... | mit |
MuhammedHasan/metabolitics | metabolitics/preprocessing/reaction_diff_transformer.py | 1 | 1692 | from sklearn.base import TransformerMixin
from sklearn_utils.utils import average_by_label
from metabolitics.utils import load_network_model
class ReactionDiffTransformer(TransformerMixin):
"""Scaler reaction by diff"""
def __init__(self, network_model="recon2", reference_label='healthy'):
self.mode... | gpl-3.0 |
GoogleCloudPlatform/datacatalog-connectors-rdbms | google-datacatalog-postgresql-connector/tests/google/datacatalog_connectors/postgresql/scrape/metadata_scraper_test.py | 1 | 5796 | #!/usr/bin/python
#
# 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 ag... | apache-2.0 |
rth/PyAbel | examples/example_hansenlaw_Xe.py | 2 | 2430 | # -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import matplotlib.pyplot as plt
import abel
import scipy.misc
# This example demonstrates Hansen and Law inverse Abel transf... | mit |
IamJeffG/geopandas | doc/source/conf.py | 1 | 8075 | # -*- coding: utf-8 -*-
#
# GeoPandas documentation build configuration file, created by
# sphinx-quickstart on Tue Oct 15 08:08:14 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.
#
# A... | bsd-3-clause |
jmetzen/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 |
lthurlow/Network-Grapher | proj/external/numpy-1.7.0/build/lib.linux-i686-2.7/numpy/core/function_base.py | 11 | 5472 | __all__ = ['logspace', 'linspace']
import numeric as _nx
from numeric import array
def linspace(start, stop, num=50, endpoint=True, retstep=False):
"""
Return evenly spaced numbers over a specified interval.
Returns `num` evenly spaced samples, calculated over the
interval [`start`, `stop` ].
Th... | mit |
aparna29/Implementation-of-Random-Exponential-Marking-REM-in-ns-3 | src/core/examples/sample-rng-plot.py | 188 | 1246 | # -*- Mode:Python; -*-
# /*
# * 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,
# * but WITHOUT ANY WARRA... | gpl-2.0 |
yarikoptic/pystatsmodels | statsmodels/sandbox/regression/kernridgeregress_class.py | 39 | 7941 | '''Kernel Ridge Regression for local non-parametric regression'''
import numpy as np
from scipy import spatial as ssp
from numpy.testing import assert_equal
import matplotlib.pylab as plt
def plt_closeall(n=10):
'''close a number of open matplotlib windows'''
for i in range(n): plt.close()
def kernel_rbf(x,... | bsd-3-clause |
jlegendary/pybrain | examples/rl/environments/shipsteer/shipbench_sde.py | 26 | 3454 | from __future__ import print_function
#!/usr/bin/env python
#########################################################################
# Reinforcement Learning with SPE on the ShipSteering Environment
#
# Requirements:
# pybrain (tested on rev. 1195, ship env rev. 1202)
# Synopsis:
# shipbenchm.py [<True|False> [lo... | bsd-3-clause |
manashmndl/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 |
boomsbloom/dtm-fmri | DTM/for_gensim/lib/python2.7/site-packages/sklearn/utils/multiclass.py | 41 | 14732 |
# Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
#
# License: BSD 3 clause
"""
Multi-class / multi-label utility function
==========================================
"""
from __future__ import division
from collections import Sequence
from itertools import chain
from scipy.sparse import issparse
from scipy.sparse.... | mit |
zfrenchee/pandas | pandas/util/_decorators.py | 2 | 10870 | from pandas.compat import callable, signature, PY2
from pandas._libs.properties import cache_readonly # noqa
import inspect
import types
import warnings
from textwrap import dedent, wrap
from functools import wraps, update_wrapper
def deprecate(name, alternative, alt_name=None, klass=None,
stacklevel=2... | bsd-3-clause |
modulesio/antikyth | bullet3/examples/pybullet/testrender_np.py | 1 | 1218 | import numpy as np
import matplotlib.pyplot as plt
import pybullet
import time
pybullet.connect(pybullet.DIRECT)
pybullet.loadURDF("r2d2.urdf")
camTargetPos = [0,0,0]
cameraUp = [0,0,1]
cameraPos = [1,1,1]
yaw = 40
pitch = 10.0
roll=0
upAxisIndex = 2
camDistance = 4
pixelWidth = 1920
pixelHeight = 1080
nearPlane = 0... | mit |
bhargavasana/activitysim | activitysim/defaults/models/mandatory_tour_frequency.py | 1 | 2109 | import os
import orca
import pandas as pd
from activitysim import activitysim as asim
from .util.mandatory_tour_frequency import process_mandatory_tours
"""
This model predicts the frequency of making mandatory trips (see the
alternatives above) - these trips include work and school in some combination.
"""
@orca.... | agpl-3.0 |
klocey/Emergence | tools/SADfits/SADfits.py | 9 | 3639 | from __future__ import division
import matplotlib.pyplot as plt
import sys
import os
from random import shuffle
import numpy as np
########### PATHS ##############################################################
mydir = os.path.expanduser("~/GitHub/residence-time")
tools = os.path.expanduser(mydir + "/tools")
sys.p... | mit |
wanggang3333/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 |
Dexhub/MTX | util/stats/output.py | 90 | 7981 | # Copyright (c) 2005-2006 The Regents of The University of Michigan
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met: redistributions of source code must retain the above copyright
# notice, this ... | bsd-3-clause |
nhejazi/scikit-learn | sklearn/metrics/ranking.py | 2 | 31015 | """Metrics to assess performance on classification task given scores
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.gramfort@inria.... | bsd-3-clause |
MechCoder/scikit-learn | sklearn/decomposition/tests/test_incremental_pca.py | 43 | 10272 | """Tests for Incremental PCA."""
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn import datasets
from sklearn.decomposition import PCA, IncrementalPCA
iris = datasets.load... | bsd-3-clause |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.