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 |
|---|---|---|---|---|---|
anhnv-3991/VoltDB | tools/vis2.py | 2 | 13955 | #!/usr/bin/env python
# This is a visualizer which pulls TPC-C benchmark results from the MySQL
# databases and visualizes them. Four graphs will be generated, latency graph on
# sinigle node and multiple nodes, and throughput graph on single node and
# multiple nodes.
#
# Run it without any arguments to see what argu... | agpl-3.0 |
Riverscapes/pyBRAT | Capacity_Validation.py | 2 | 24291 | # -------------------------------------------------------------------------------
# Name: BRAT Validation
# Purpose: Tests the output of BRAT against a shape file of beaver dams
#
# Author: Braden Anderson
#
# Created: 05/2018
# -----------------------------------------------------------------------... | gpl-3.0 |
kazemakase/scikit-learn | sklearn/preprocessing/label.py | 35 | 28877 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Olivier Grisel <olivier.grisel@ensta.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Joel Nothman <joel.nothman@gmail.com>
# Hamzeh Alsalhi <ha258@cornell.edu>
# Licens... | bsd-3-clause |
larsmans/scikit-learn | sklearn/linear_model/least_angle.py | 8 | 48477 | """
Least Angle Regression algorithm. See the documentation on the
Generalized Linear Model for a complete discussion.
"""
from __future__ import print_function
# Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux
#
# License: BSD 3 ... | bsd-3-clause |
nelson-liu/scikit-learn | sklearn/externals/joblib/__init__.py | 23 | 5101 | """ Joblib is a set of tools to provide **lightweight pipelining in
Python**. In particular, joblib offers:
1. transparent disk-caching of the output values and lazy re-evaluation
(memoize pattern)
2. easy simple parallel computing
3. logging and tracing of the execution
Joblib is optimized to be **fast*... | bsd-3-clause |
bioShaun/OMrnaseq | rnaseq/modules/quantification/quant.py | 1 | 5665 | #!/usr/bin/env python
from __future__ import print_function
import sys
import luigi
from luigi.util import requires, inherits
import os
from rnaseq.utils import config
from rnaseq.utils.util_functions import txt_to_excel, add_gene_annotation
from rnaseq.utils.util_functions import get_compare_names, pattern2files
from... | gpl-3.0 |
adykstra/mne-python | examples/forward/plot_forward_sensitivity_maps.py | 3 | 2498 | """
.. _ex-sensitivity-maps:
================================================
Display sensitivity maps for EEG and MEG sensors
================================================
Sensitivity maps can be produced from forward operators that
indicate how well different sensor types will be able to detect
neural currents f... | bsd-3-clause |
madmax983/h2o-3 | h2o-py/h2o/model/metrics_base.py | 2 | 22127 | from h2o.model.confusion_matrix import ConfusionMatrix
import imp
class MetricsBase(object):
"""
A parent class to house common metrics available for the various Metrics types.
The methods here are available across different model categories, and so appear here.
"""
def __init__(self, metric_json,on=None,a... | apache-2.0 |
UDST/activitysim | activitysim/abm/models/trip_purpose_and_destination.py | 2 | 5215 | # ActivitySim
# See full license in LICENSE.txt.
from __future__ import (absolute_import, division, print_function, )
from future.standard_library import install_aliases
install_aliases() # noqa: E402
import logging
import pandas as pd
from activitysim.core import tracing
from activitysim.core import config
from a... | bsd-3-clause |
mrGeen/metaseq | metaseq/colormap_adjust.py | 2 | 5167 | """
Module to handle custom colormaps.
`cmap_powerlaw_adjust`, `cmap_center_adjust`, and
`cmap_center_adjust` are from
https://sites.google.com/site/theodoregoetz/notes/matplotlib_colormapadjust
"""
import math
import copy
import numpy
import numpy as np
from matplotlib import pyplot, colors, cm
import matplotlib
imp... | mit |
clemkoa/scikit-learn | sklearn/cluster/birch.py | 18 | 23684 | # Authors: Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Joel Nothman <joel.nothman@gmail.com>
# License: BSD 3 clause
from __future__ import division
import warnings
import numpy as np
from scipy import sparse
from math import sqrt
fro... | bsd-3-clause |
adammenges/statsmodels | statsmodels/graphics/dotplots.py | 31 | 18190 | import numpy as np
from statsmodels.compat import range
from . import utils
def dot_plot(points, intervals=None, lines=None, sections=None,
styles=None, marker_props=None, line_props=None,
split_names=None, section_order=None, line_order=None,
stacked=False, styles_order=None, s... | bsd-3-clause |
ch3ll0v3k/scikit-learn | examples/hetero_feature_union.py | 288 | 6236 | """
=============================================
Feature Union with Heterogeneous Data Sources
=============================================
Datasets can often contain components of that require different feature
extraction and processing pipelines. This scenario might occur when:
1. Your dataset consists of hetero... | bsd-3-clause |
cloudera/ibis | ibis/backends/impala/tests/test_udf.py | 1 | 19002 | import unittest
from decimal import Decimal
from posixpath import join as pjoin
import numpy as np
import pandas as pd
import pytest
import ibis
import ibis.backends.impala as api # noqa: E402
import ibis.common.exceptions as com
import ibis.expr.datatypes as dt
import ibis.expr.rules as rules
import ibis.expr.types... | apache-2.0 |
alephu5/Soundbyte | environment/lib/python3.3/site-packages/matplotlib/widgets.py | 1 | 52856 | """
GUI Neutral widgets
===================
Widgets that are designed to work for any of the GUI backends.
All of these widgets require you to predefine an :class:`matplotlib.axes.Axes`
instance and pass that as the first arg. matplotlib doesn't try to
be too smart with respect to layout -- you will have to figure ou... | gpl-3.0 |
charman2/rsas | examples/solutes.py | 1 | 6055 | # -*- coding: utf-8 -*-
"""Storage selection (SAS) functions: example with three solutes
Runs the rSAS model for a synthetic dataset with two fluxes out
and three solutes
Theory is presented in:
Harman, C. J. (2014), Time-variable transit time distributions and transport:
Theory and application to storage-dependent t... | mit |
toobaz/pandas | pandas/tests/groupby/conftest.py | 1 | 2605 | import numpy as np
import pytest
from pandas import DataFrame, MultiIndex
from pandas.core.groupby.base import reduction_kernels
from pandas.util import testing as tm
@pytest.fixture
def mframe():
index = MultiIndex(
levels=[["foo", "bar", "baz", "qux"], ["one", "two", "three"]],
codes=[[0, 0, 0,... | bsd-3-clause |
ageron/tensorflow | tensorflow/contrib/factorization/python/ops/kmeans_test.py | 16 | 21836 | # 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 |
nistats/nistats | examples/02_first_level_models/plot_bids_features.py | 1 | 7375 | """
First level analysis of a complete BIDS dataset from openneuro
===============================================================
Full step-by-step example of fitting a GLM to perform a first level analysis
in an openneuro BIDS dataset. We demonstrate how BIDS derivatives can be
exploited to perform a simple one sub... | bsd-3-clause |
jm-begon/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 75 | 34122 | from __future__ import unicode_literals
import warnings
from sklearn.feature_extraction.text import strip_tags
from sklearn.feature_extraction.text import strip_accents_unicode
from sklearn.feature_extraction.text import strip_accents_ascii
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.fe... | bsd-3-clause |
parloma/robotcontrol | python/DEMO_INPUT_kinect_free.py | 1 | 5176 | #Parameters: RF First Classification Layer - RF Second Classification Layer
#Import required
import sys
from os import path,sep,mkdir
import numpy as np
from cv2 import *
from hand_grabber import PyOpenNIHandGrabber
from pose_recognizer import PyPoseRecognizer
import xml.etree.ElementTree as ET
import Image
from rando... | gpl-2.0 |
mabevillar/rmtk | rmtk/plotting/damage_dist/plot_damage_dist.py | 3 | 4650 | '''
Post-process damage calculation outputs to plot damage distibution charts
'''
import os
import csv
import argparse
import numpy as np
from collections import OrderedDict
from matplotlib import pyplot
from mpl_toolkits.mplot3d import Axes3D
import parse_damage_dist as parsedd
xmlNRML = '{http://openquake.org/xmlns... | agpl-3.0 |
oemof/examples | oemof_examples/oemof.solph/v0.1.x/storage_investment/storage_investment.py | 2 | 10074 | # -*- coding: utf-8 -*-
"""
General description:
---------------------
The example models the following energy system:
input/output bgas bel
| | | |
| | | |
wind(FixedSource) |------------------>| |
... | gpl-3.0 |
JanNash/sms-tools | lectures/03-Fourier-properties/plots-code/convolution-2.py | 24 | 1259 | import matplotlib.pyplot as plt
import numpy as np
from scipy.fftpack import fft, fftshift
plt.figure(1, figsize=(9.5, 7))
M = 64
N = 64
x1 = np.hanning(M)
x2 = np.cos(2*np.pi*2/M*np.arange(M))
y1 = x1*x2
mY1 = 20 * np.log10(np.abs(fftshift(fft(y1, N))))
plt.subplot(3,2,1)
plt.title('x1 (hanning)')
plt.plot(np.arange... | agpl-3.0 |
lukecwik/incubator-beam | sdks/python/apache_beam/io/parquetio.py | 1 | 20134 | #
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not us... | apache-2.0 |
pratapvardhan/pandas | pandas/tests/arrays/categorical/test_indexing.py | 2 | 4603 | # -*- coding: utf-8 -*-
import pytest
import numpy as np
import pandas.util.testing as tm
from pandas import Categorical, Index, CategoricalIndex, PeriodIndex
from pandas.tests.arrays.categorical.common import TestCategorical
class TestCategoricalIndexingWithFactor(TestCategorical):
def test_getitem(self):
... | bsd-3-clause |
jarvis-fga/Projetos | Problema 2/lucas/src/text_classification.py | 1 | 5048 | # Create by Lucas Andrade
# On 11 / 09 / 2017
import pandas as pd
import codecs
import numpy as np
from sklearn import svm
from sklearn.svm import SVC
from sklearn.model_selection import cross_val_score
from sklearn.naive_bayes import MultinomialNB
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble impo... | mit |
blink1073/scikit-image | skimage/filters/_gabor.py | 23 | 6926 | import numpy as np
from scipy import ndimage as ndi
from .._shared.utils import assert_nD
__all__ = ['gabor_kernel', 'gabor']
def _sigma_prefactor(bandwidth):
b = bandwidth
# See http://www.cs.rug.nl/~imaging/simplecell.html
return 1.0 / np.pi * np.sqrt(np.log(2) / 2.0) * \
(2.0 ** b + 1) / (2.0... | bsd-3-clause |
depet/scikit-learn | sklearn/decomposition/__init__.py | 1 | 1235 | """
The :mod:`sklearn.decomposition` module includes matrix decomposition
algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
this module can be regarded as dimensionality reduction techniques.
"""
from .nmf import NMF, ProjectedGradientNMF
from .pca import PCA, RandomizedPCA, ProbabilisticPC... | bsd-3-clause |
joekasp/ionic_liquids | ionic_liquids/test/test_utils.py | 1 | 5560 | #default python modules
import os
from datetime import datetime
#external packages
import numpy as np
import pandas as pd
from sklearn.externals import joblib
from sklearn.linear_model import Lasso
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.neural_network import MLPClassifier
from s... | mit |
dbtsai/spark | dev/sparktestsupport/modules.py | 3 | 17852 | #
# 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 |
ptonner/GPy | GPy/models/gplvm.py | 8 | 3049 | # Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from .. import kern
from ..core import GP, Param
from ..likelihoods import Gaussian
from .. import util
class GPLVM(GP):
"""
Gaussian Process Latent Variable Model
"... | bsd-3-clause |
ozansener/tf_base | src/forward_greedy_facility.py | 1 | 6769 | # -*- coding: utf-8 -*-
"""Forward greedy facility location"""
import numpy as np
import warnings
from sklearn.base import BaseEstimator, ClusterMixin, TransformerMixin
from sklearn.metrics.pairwise import PAIRWISE_DISTANCE_FUNCTIONS
from sklearn.metrics import normalized_mutual_info_score
from sklearn.utils import c... | mit |
jb1361/RS3GEPredictionModel | predictionTesting/predictOneItem2.py | 1 | 8655 | import time
import sqlite3
import pandas as pd
import numpy as np
import scipy as sp
from scipy import stats
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
traindataframes = []
testDataFrame = []
#this defines how many items we are looking at
#max = 20
predicted_Item = 0
#def predict_next_day():
#re... | mit |
joeyginorio/Markov-Decision-Process | src/GridWorld.py | 1 | 6386 | # Joey Velez-Ginorio
# Gridworld Implementation
# ---------------------------------
from MDP import MDP
from Grid import Grid
from scipy.stats import uniform
from scipy.stats import beta
from scipy.stats import expon
import numpy as np
import random
import pyprind
import matplotlib.pyplot as plt
class GridWorld(MDP):... | mit |
surhudm/scipy | scipy/signal/signaltools.py | 2 | 115985 | # Author: Travis Oliphant
# 1999 -- 2002
from __future__ import division, print_function, absolute_import
import warnings
import threading
import sys
import timeit
from . import sigtools, dlti
from ._upfirdn import upfirdn, _UpFIRDn, _output_len
from scipy._lib.six import callable
from scipy._lib._version import Num... | bsd-3-clause |
lbybee/vc_network_learning_project | code/test_ab_net.py | 1 | 1162 | from datetime import datetime
import pandas as pd
import process_data as prd
test_inp = [{"c_name": "1", "f_name": "a", "c_mn_group": "1",
"inv_date": datetime(2000, 1, 1), "c_success": 1},
{"c_name": "1", "f_name": "b", "c_mn_group": "1",
"inv_date": datetime(2000, 1, 1), "c_suc... | gpl-2.0 |
arielmakestuff/loadlimit | test/unit/cli/test_statsetup.py | 1 | 5917 | # -*- coding: utf-8 -*-
# test/unit/cli/test_statsetup.py
# Copyright (C) 2016 authors and contributors (see AUTHORS file)
#
# This module is released under the MIT License.
"""Test StatSetup"""
# ============================================================================
# Imports
# ================================... | mit |
rafaelmds/fatiando | fatiando/inversion/hyper_param.py | 6 | 16629 | r"""
Classes for hyper parameter estimation (like the regularizing parameter).
These classes copy the interface of the standard inversion classes based on
:class:`~fatiando.inversion.misfit.Misfit` (i.e.,
``solver.config(...).fit().estimate_``). When their ``fit`` method is called,
they perform many runs of the invers... | bsd-3-clause |
emanuele/jstsp2015 | figures.py | 1 | 5427 | """Code to generate figures of the manuscript.
Author: Sandro Vega-Pons, Emanuele Olivetti
"""
import numpy as np
import matplotlib.pyplot as plt
import pickle
import os
import scipy.stats as ss
sites = ["Beijing_Zang",
"Berlin_Margulies",
"Cambridge_Buckner",
"Cleveland",
"Dalla... | mit |
UO-CAES/paparazzi | sw/airborne/test/stabilization/compare_ref_quat.py | 38 | 1206 | #! /usr/bin/env python
from __future__ import division, print_function, absolute_import
import numpy as np
import matplotlib.pyplot as plt
import ref_quat_float
import ref_quat_int
steps = 512 * 2
ref_eul_res = np.zeros((steps, 3))
ref_quat_res = np.zeros((steps, 3))
ref_quat_float.init()
ref_quat_int.init()
# re... | gpl-2.0 |
bmazin/SDR | Projects/FirmwareTests/stream/parsePacketDump.py | 1 | 3552 | """
File: parsePacketDump.py
Author: Matt Strader
"""
import matplotlib, time, struct
import matplotlib.pyplot as plt
import numpy as np
from Utils import binTools
import sys
if len(sys.argv) > 1:
path = sys.argv[1]
else:
path = 'photonDump.bin'
with open(path,'rb') as dumpFile:
data = dumpFile.... | gpl-2.0 |
rahulsrma26/code-gems | RL/bellman/jackCarRentalCpp.py | 1 | 2830 | import warnings
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from cppLib.bellman import JacksCarRental
def data_formatter(data):
def format_coord(x, y):
ix, iy = int(x), int(y)
v = 'N/A'
try:
v = data[iy][ix]
except IndexError:
pa... | mit |
tacaswell/bokeh | bokeh/properties.py | 4 | 42855 | """ Properties are objects that can be assigned as class level
attributes on Bokeh models, to provide automatic serialization
and validation.
For example, the following defines a model that has integer,
string, and list[float] properties::
class Model(HasProps):
foo = Int
bar = String
baz ... | bsd-3-clause |
BhallaLab/moose | moose-core/tests/python/test_rdesigneur_random_syn_input.py | 2 | 1402 | # -*- coding: utf-8 -*-
from __future__ import print_function, division
# This example demonstrates random (Poisson) synaptic input to a cell.
# Copyright (C) Upinder S. Bhalla NCBS 2018
# Released under the terms of the GNU Public License V3. No warranty.
# Changelog:
# Thursday 20 September 2018 09:53:27 AM IST
# - ... | gpl-3.0 |
toastedcornflakes/scikit-learn | sklearn/ensemble/tests/test_iforest.py | 9 | 6928 | """
Testing for Isolation Forest algorithm (sklearn.ensemble.iforest).
"""
# Authors: Nicolas Goix <nicolas.goix@telecom-paristech.fr>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.u... | bsd-3-clause |
Garrett-R/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 |
bbfamily/abu | abupy/TradeBu/ABuTradeProxy.py | 1 | 14496 | # -*- encoding:utf-8 -*-
"""
交易执行代理模块
"""
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
from contextlib import contextmanager
from functools import total_ordering
from enum import Enum
import numpy as np
import pandas as pd
from . import ABuTradeDra... | gpl-3.0 |
mattions/TimeScales | helpers/plotter_walker_calcium.py | 1 | 2618 | import matplotlib.pyplot as plt
import os
from helpers.plotter import DoublePlotter, StimulPlotter
import neuronvisio.manager
filename = 'storage.h5'
stimulated_spines = ['spine554', 'spine555', 'spine556',
'spine558', 'spine559', 'spine560',
'spine562', 'spine563', 'spin... | bsd-3-clause |
mlindauer/AutoFolio | autofolio/selector/joint_regression.py | 1 | 4040 | import logging
import traceback
import numpy as np
import pandas as pd
from ConfigSpace.hyperparameters import CategoricalHyperparameter, \
UniformFloatHyperparameter, UniformIntegerHyperparameter
from ConfigSpace.conditions import EqualsCondition, InCondition
from ConfigSpace.configuration_space import Configura... | bsd-2-clause |
burgerdev/hostload | test/testOpSVM.py | 1 | 3635 |
import unittest
import numpy as np
import vigra
from sklearn.svm import SVC
from sklearn.svm import SVR
from lazyflow.graph import Graph
from tsdl.classifiers import OpSVMTrain
from tsdl.classifiers import OpSVMPredict
class TestOpSVM(unittest.TestCase):
def setUp(self):
X = np.array([[-1, -1], [-2, ... | mit |
ycaihua/scikit-learn | examples/decomposition/plot_pca_vs_fa_model_selection.py | 30 | 4516 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=================================================================
Model selection with Probabilistic (PCA) and Factor Analysis (FA)
=================================================================
Probabilistic PCA and Factor Analysis are probabilistic models.
The conseq... | bsd-3-clause |
miloharper/neural-network-animation | matplotlib/streamplot.py | 11 | 19119 | """
Streamline plotting for 2D vector fields.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange
import numpy as np
import matplotlib
import matplotlib.cm as cm
import matplotlib.colors as mcolors
import matplotlib.... | mit |
aditiiyer/CERR | CERR_core/ModelImplementationLibrary/SegmentationModels/ModelDependencies/MR_Lung_TumorAware/run_code.py | 1 | 5022 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed May 31 23:10:12 2017
@author: jiangj1
"""
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed May 31 15:58:04 2017
@author: jiangj1
"""
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sun Apr 30 11:30:40 2017
@author: cc... | lgpl-2.1 |
hilario/trep | src/discopt/doptimizer.py | 1 | 22991 | import time
import datetime
import numpy as np
import trep
import dlqr
import numpy.linalg
from numpy import dot
try:
import matplotlib.pyplot as pyplot
pyplot_available = True
except ImportError:
pyplot_available = False
class DOptimizerMonitor(object):
"""
This is the base class for Optimizer... | gpl-3.0 |
cowlicks/blaze | blaze/compute/tests/test_pandas_compute.py | 2 | 28576 | from __future__ import absolute_import, division, print_function
import pytest
from datetime import datetime, timedelta
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas import DataFrame, Series
from string import ascii_lowercase
from blaze.compute.core import compute
from blaze.... | bsd-3-clause |
ocefpaf/ulmo | ulmo/cpc/drought/core.py | 1 | 11079 | """
ulmo.cpc.drought.core
~~~~~~~~~~~~~~~~~~~~~
This module provides direct access to `Climate Predicition Center`_ `Weekly
Drought Index`_ dataset.
.. _Climate Prediction Center: http://www.cpc.ncep.noaa.gov/
.. _Weekly Drought Index: http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/... | bsd-3-clause |
stephenslab/dsc2 | src/query_jupyter.py | 1 | 5969 | #!/usr/bin/env python
__author__ = "Gao Wang"
__copyright__ = "Copyright 2016, Stephens lab"
__email__ = "gaow@uchicago.edu"
__license__ = "MIT"
import os
import json
def get_home_doc(db, description):
return '''
This page displays contents of database `{0}.db` generated by [this DSC]({0}.html).
{1}
'''.format(
... | mit |
bsipocz/ginga | ginga/cmap.py | 1 | 507604 | #
# cmap.py -- color maps for fits viewing
#
# Eric Jeschke (eric@naoj.org)
#
# Copyright (c) Eric R. Jeschke. All rights reserved.
# This is open-source software licensed under a BSD license.
# Please see the file LICENSE.txt for details.
#
from __future__ import print_function
import numpy
from ginga.util.six.move... | bsd-3-clause |
MrNuggelz/sklearn-glvq | sklearn_lvq/tests/test_docstring_parameters.py | 1 | 7619 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Raghav RV <rvraghav93@gmail.com>
# License: BSD 3 clause
import inspect
import sys
import warnings
import importlib
from pkgutil import walk_packages
from inspect import getsource, isabstract
from sklearn.base import signature
from sklearn.utils.... | bsd-3-clause |
jeffersonfparil/GTWAS_POOL_RADseq_SIM | BACKUP_SCRIPTS_20170930/basisPlots_GWAS_ROC.py | 2 | 3740 | #!/usr/bin/env python
import os, subprocess, sys, math
import pandas
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from collections import Counter
from sklearn import metrics
#from statsmodels.formula.api import ols
import scipy
workDIR = sys.argv[1]
phenotypeFile = sys.arg... | gpl-3.0 |
OshynSong/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 176 | 12155 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from scipy.spatial import distance
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing im... | bsd-3-clause |
pprett/sklearn_pycon2014 | notebooks/solutions/05_eigen_faces.py | 1 | 1221 | from sklearn.datasets import fetch_olivetti_faces
from sklearn.decomposition import PCA
faces = fetch_olivetti_faces()
X = faces.data
pca = PCA(n_components=100).fit(X)
# set up the figure
fig = plt.figure(figsize=(6, 6)) # figure size in inches
fig.subplots_adjust(left=0, right=1, bottom=0, top=1, hspace=0.05, wsp... | bsd-3-clause |
pratapvardhan/pandas | pandas/tests/indexes/multi/test_indexing.py | 2 | 11610 | # -*- coding: utf-8 -*-
from datetime import timedelta
import numpy as np
import pytest
import pandas as pd
import pandas.util.testing as tm
from pandas import (Categorical, CategoricalIndex, Index, IntervalIndex,
MultiIndex, date_range)
from pandas.compat import lrange
from pandas.core.indexes.... | bsd-3-clause |
goulu/Goulib | tests/test_Goulib_image.py | 1 | 21217 | from nose.tools import assert_equal
from nose import SkipTest
# lines above are inserted automatically by pythoscope. Line below overrides them
from Goulib.tests import * # pylint: disable=wildcard-import, unused-wildcard-import
from Goulib.image import * # pylint: disable=wildcard-import, unused-wildcard-import
fr... | lgpl-3.0 |
drpjm/udacity-mle-project1 | boston_housing.py | 1 | 7856 | """Load the Boston dataset and examine its target (label) distribution."""
# (c) 2015 Patrick Martin and Udacity
# MIT License
# Load libraries
import numpy as np
import pylab as pl
import sklearn as skl
from sklearn import datasets
from sklearn.tree import DecisionTreeRegressor
################################
### A... | mit |
lilleswing/deepchem | examples/bace/bace_rf.py | 5 | 4200 | """This example implements RF experiments from https://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00290"""
import sys
import os
import deepchem
import deepchem as dc
import tempfile, shutil
from bace_datasets import load_bace
from deepchem.hyper import HyperparamOpt
from sklearn.ensemble import RandomForestRegressor
from ... | mit |
andrewcmyers/tensorflow | tensorflow/contrib/learn/python/learn/estimators/debug_test.py | 46 | 32817 | # 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 |
mlyundin/scikit-learn | sklearn/externals/joblib/parallel.py | 79 | 35628 | """
Helpers for embarrassingly parallel code.
"""
# Author: Gael Varoquaux < gael dot varoquaux at normalesup dot org >
# Copyright: 2010, Gael Varoquaux
# License: BSD 3 clause
from __future__ import division
import os
import sys
import gc
import warnings
from math import sqrt
import functools
import time
import thr... | bsd-3-clause |
thinrope/GNU_parallel | src/optional/python/tests/test_loader.py | 4 | 1533 | import pandas as pd
import unittest
from gnuparallel import load
result_dir = '../../testresults'
class TestLoader(unittest.TestCase):
def test_basics(self):
df = load(result_dir)
self.assertEqual(set(df.columns), set(['a', 'b', 'resfile', '_stream']))
self.assertEqual(df.shape[0], 4)
... | gpl-3.0 |
ClaudioNahmad/Servicio-Social | Parametros/CosmoMC/CosmoMC-master/python/setup.py | 1 | 1503 | #!/usr/bin/env python
from __future__ import absolute_import
import io
import re
import os
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
def find_version():
version_file = io.open(os.path.join(os.path.dirname(__file__), 'getdist/__init__.py')).read()
version_m... | gpl-3.0 |
ClimbsRocks/scikit-learn | sklearn/ensemble/__init__.py | 153 | 1382 | """
The :mod:`sklearn.ensemble` module includes ensemble-based methods for
classification, regression and anomaly detection.
"""
from .base import BaseEnsemble
from .forest import RandomForestClassifier
from .forest import RandomForestRegressor
from .forest import RandomTreesEmbedding
from .forest import ExtraTreesCla... | bsd-3-clause |
MTgeophysics/mtpy | examples/scripts/ModEM_PlotRMS_by_site.py | 1 | 1089 | # -*- coding: utf-8 -*-
"""
Created on Tue Oct 04 13:13:29 2016
@author: Alison Kirkby
Plot root-mean-square misfit (RMS across all periods) at each site
"""
import os.path as op
import os
os.chdir(r'C:/mtpywin/mtpy')
#from mtpy.imaging.plot_response import PlotResponse
from mtpy.modeling.modem import Residual
impo... | gpl-3.0 |
kushalbhola/MyStuff | Practice/PythonApplication/env/Lib/site-packages/pandas/core/indexing.py | 1 | 85223 | import textwrap
from typing import Tuple
import warnings
import numpy as np
from pandas._libs.indexing import _NDFrameIndexerBase
from pandas._libs.lib import item_from_zerodim
from pandas.errors import AbstractMethodError
from pandas.util._decorators import Appender
from pandas.core.dtypes.common import (
ensur... | apache-2.0 |
hlin117/statsmodels | statsmodels/examples/ex_pandas.py | 29 | 4021 | # -*- coding: utf-8 -*-
"""Examples using Pandas
"""
from __future__ import print_function
from statsmodels.compat.python import zip
from datetime import datetime
import numpy as np
from pandas import DataFrame, Series, datetools
import statsmodels.api as sm
import statsmodels.tsa.api as tsa
data = sm.datasets.... | bsd-3-clause |
natasasdj/OpenWPM | analysis/07_jpeg_pix_size.py | 1 | 5197 | import os
import sqlite3
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from matplotlib.ticker import FuncFormatter
def thousands(x, pos):
if x>=1e9:
return '%.1fB' % (x*1e-9)
elif x>=1e6:
return '%.1fM' % (x*1e-6)
elif x>=1e3:
return '%.1f... | gpl-3.0 |
kuntzer/SALSA-public | absolute_maps/resources/figures.py | 2 | 1647 | ''' figures.py
=========================
AIM: Provide several specific functions to save beautiful figures
INPUT: function depend
OUTPUT: function depend
CMD: To include: import resources.figures as figures
ISSUES: <none known>
REQUIRES: standard python libraries, specific libraries in resources/
REMARKS: in gene... | bsd-3-clause |
weinbe58/QuSpin | examples/notebooks/GPE.py | 2 | 5907 | from __future__ import print_function, division
import sys,os
# line 4 and line 5 below are for development purposes and can be removed
qspin_path = os.path.join(os.getcwd(),"../../")
sys.path.insert(0,qspin_path)
#
from quspin.operators import hamiltonian # Hamiltonians and operators
from quspin.basis import boson_bas... | bsd-3-clause |
AtsushiHashimoto/fujino_mthesis | tools/module/ontology.py | 1 | 1123 | # _*_ coding: utf-8 -*-
import pandas as pd
def load_food_synonym(synonym_path, key="swing", seasoning=True):
"""
input
synonym_path: full path of synonym.tsv
key: setting of dictionary of result; "swing" swing->concept "concept" concept->swing
seasoning: use seasoning?
output
dictionay ... | bsd-2-clause |
ningchi/scikit-learn | sklearn/tree/export.py | 6 | 15622 | """
This module defines export functions for decision trees.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Dawe <noel@dawe.me>
# Satrajit Gosh <satrajit.ghosh@gmail.com>
# Trevor... | bsd-3-clause |
dhruv13J/scikit-learn | examples/linear_model/plot_logistic_path.py | 349 | 1195 | #!/usr/bin/env python
"""
=================================
Path with L1- Logistic Regression
=================================
Computes path on IRIS dataset.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from datetime import datetime
import numpy as np
import... | bsd-3-clause |
P1R/cinves | TrabajoFinal/tubo350cm/Experimentos-04-2015/TvsFreq-FM.py | 1 | 1237 | import numpy as np
import matplotlib.pyplot as plt
#la frecuencia de la modulada FM es de 50 hz en todas las variaciones de la portadora
Freq=np.array([20,30,40,50,60,70,80,90,100,110,120,130,140,150,160,170,180,190,200,210,220,230,240,250,260]);
DeltaTemp=np.array([0.5,1.2,3.2,4.1,2.3,2.0,1.8,0.8,0.2,1.2,2.3,4.1,8.5,3... | apache-2.0 |
cshallue/models | research/fivo/experimental/summary_utils.py | 4 | 13834 | # 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 applicab... | apache-2.0 |
fivejjs/pybasicbayes | examples/animation.py | 2 | 1504 | from __future__ import division
from __future__ import print_function
import numpy as np
import numpy.random as npr
from matplotlib import pyplot as plt
plt.ion()
from pybasicbayes import models, distributions
###############
# load data #
###############
data = np.loadtxt('data.txt')
plt.figure()
plt.plot(data[... | mit |
sonnyhu/scikit-learn | examples/decomposition/plot_pca_3d.py | 354 | 2432 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Principal components analysis (PCA)
=========================================================
These figures aid in illustrating how a point cloud
can be very flat in one direction--which is where PCA
comes in to ch... | bsd-3-clause |
DanielAndreasen/SWEET-Cat | checkDuplicates.py | 1 | 4561 | import pandas as pd
import numpy as np
import warnings
from clint.textui import colored
warnings.simplefilter("ignore")
class Sweetcat:
"""Load SWEET-Cat database"""
def __init__(self):
# self.fname_sc = 'WEBSITE_online_EU-NASA_full_database.rdb'
self.fname_sc = 'WEBSITE_online_EU-NASA_full_d... | mit |
ethz-asl/segmatch | segmappy/bin/plot_reconstructions.py | 1 | 5540 | from __future__ import print_function
from builtins import input
import numpy as np
import os
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import random
from sklearn import metrics
import ensure_segmappy_is_installed
from segmappy import Dataset
from segmappy.tools.import_export import load_... | bsd-3-clause |
MikeDacre/mike_tools | python/ldlink_pairs.py | 1 | 11433 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Investigate linkage disequilibrium between pairs of SNPs.
Uses the LDLink API to search for pairs of SNPs and builds a simple class
(SNP_Pair) with the results.
Info
----
Author: Michael D Dacre, mike.dacre@gmail.com
Organization: Stanford University
License: MIT Lice... | unlicense |
pratapvardhan/scikit-learn | examples/cluster/plot_dbscan.py | 346 | 2479 | # -*- coding: utf-8 -*-
"""
===================================
Demo of DBSCAN clustering algorithm
===================================
Finds core samples of high density and expands clusters from them.
"""
print(__doc__)
import numpy as np
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn... | bsd-3-clause |
hasecbinusr/pysal | pysal/esda/join_counts.py | 6 | 6826 | """
Spatial autocorrelation for binary attributes
"""
__author__ = "Sergio J. Rey <srey@asu.edu> , Luc Anselin <luc.anselin@asu.edu>"
from ..weights.spatial_lag import lag_spatial
from .tabular import _univariate_handler
import numpy as np
__all__ = ['Join_Counts']
PERMUTATIONS = 999
class Join_Counts(object):
... | bsd-3-clause |
abhisg/scikit-learn | doc/sphinxext/gen_rst.py | 106 | 40198 | """
Example generation for the scikit learn
Generate the rst files for the examples by iterating over the python
example files.
Files that generate images should start with 'plot'
"""
from __future__ import division, print_function
from time import time
import ast
import os
import re
import shutil
import traceback
i... | bsd-3-clause |
shaypal5/s3bp | s3bp/core.py | 1 | 18767 | """This package enables saving and loading of python objects to disk
while also backing to S3 storage. """
import os
import datetime
import ntpath # to extract file name from path, OS-independent
import traceback # for printing full stacktraces of errors
import concurrent.futures # for asynchronous file uploads
im... | mit |
fabianp/scikit-learn | examples/applications/wikipedia_principal_eigenvector.py | 233 | 7819 | """
===============================
Wikipedia principal eigenvector
===============================
A classical way to assert the relative importance of vertices in a
graph is to compute the principal eigenvector of the adjacency matrix
so as to assign to each vertex the values of the components of the first
eigenvect... | bsd-3-clause |
rachelalbert/image-analogies-python | image_analogies.py | 1 | 9936 | import os
import pickle
import time
import warnings
import matplotlib.pyplot as plt
import numpy as np
from algorithms import create_index, compute_feature_array, extract_pixel_feature, best_approximate_match, \
best_coherence_match, compute_distance
from config import setup_vars, save_metadat... | mit |
lbarnett/BirdID | phow_birdid_mser.py | 1 | 16736 | #!/usr/bin/env python
"""
Python rewrite of http: //www.vlfeat.org/applications/caltech-101-code.html
"""
from os.path import exists, isdir, basename, join, splitext
from os import makedirs
from glob import glob
from random import sample, seed
from scipy import ones, mod, arange, array, where, ndarray, hstack, linspac... | gpl-2.0 |
carrillo/scikit-learn | sklearn/linear_model/tests/test_least_angle.py | 98 | 20870 | from nose.tools import assert_equal
import numpy as np
from scipy import linalg
from sklearn.cross_validation import train_test_split
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing impor... | bsd-3-clause |
jm-begon/scikit-learn | examples/decomposition/plot_pca_vs_lda.py | 182 | 1743 | """
=======================================================
Comparison of LDA and PCA 2D projection of Iris dataset
=======================================================
The Iris dataset represents 3 kind of Iris flowers (Setosa, Versicolour
and Virginica) with 4 attributes: sepal length, sepal width, petal length
a... | bsd-3-clause |
kapteyn-astro/kapteyn | doc/source/EXAMPLES/mu_channelmosaic.py | 1 | 1638 | from kapteyn import maputils
from matplotlib import pylab as plt
# This is our function to convert velocity from m/s to km/s
def fx(x):
return x/1000.0
# Create an object from the FITSimage class:
fitsobj = maputils.FITSimage('ngc6946.fits')
specaxnum = fitsobj.proj.specaxnum
lonaxnum = fitsobj.proj.lonaxnum
lataxn... | bsd-3-clause |
waynenilsen/statsmodels | statsmodels/graphics/regressionplots.py | 20 | 39579 | '''Partial Regression plot and residual plots to find misspecification
Author: Josef Perktold
License: BSD-3
Created: 2011-01-23
update
2011-06-05 : start to convert example to usable functions
2011-10-27 : docstrings
'''
from statsmodels.compat.python import lrange, string_types, lzip, range
import numpy as np
imp... | bsd-3-clause |
bert9bert/statsmodels | statsmodels/tools/parallel.py | 32 | 2180 | """Parallel utility function using joblib
copied from https://github.com/mne-tools/mne-python
Author: Alexandre Gramfort <gramfort@nmr.mgh.harvard.edu>
License: Simplified BSD
changes for statsmodels (Josef Perktold)
- try import from joblib directly, (doesn't import all of sklearn)
"""
from __future__ import print... | bsd-3-clause |
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