repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
gtrensch/nest-simulator | pynest/nest/raster_plot.py | 15 | 9348 | # -*- coding: utf-8 -*-
#
# raster_plot.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or... | gpl-2.0 |
gagneurlab/concise | tests/devel_concise_quasi_X.py | 2 | 1030 | # test quasi X
import sys
import os
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../")
from functions.tests import concise_load_data as ld
from functions import concise
from functions import get_data
import pandas as pd
import numpy as np
from imp import reload
from pprint import pprint
pd.set_opt... | mit |
sameeptandon/sail-car-log | process/ProjectMapOnVideoDense.py | 1 | 5676 | from Q50_config import *
import sys, os
from GPSReader import *
from GPSTransforms import *
from VideoReader import *
from LidarTransforms import *
from ColorMap import *
from transformations import euler_matrix
import numpy as np
import cv2
from ArgParser import *
from scipy.interpolate import griddata
import matplotl... | bsd-2-clause |
geodynamics/specfem1d | Fortran_version/plot_script_using_python.py | 2 | 1288 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 22 15:52:24 2014
Script to plot the seismograms generated by SPECFEM2D.
The arguments must be correct paths to existing 2D seismogram files or
an existing option (--hold, --grid)
@author: Alexis Bottero (alexis.bottero@gmail.com)
"""
from __future__ i... | gpl-2.0 |
bikong2/scikit-learn | sklearn/tests/test_base.py | 216 | 7045 | # Author: Gael Varoquaux
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing impo... | bsd-3-clause |
nlholdem/icodoom | ICO1/deep_feedback_learning_old/testImgProc.py | 3 | 3766 | #!/usr/bin/python3
import deep_feedback_learning
import numpy as np
import matplotlib.pyplot as plt
import cv2
import sys
import itertools
from PIL import Image
def buildFilters():
ksize = 35
sigma = 5.
gamma = 1.
theta_vals = np.linspace(0., np.pi, 4, endpoint=False)
# lambd_vals = (3,7)
# sigm... | gpl-3.0 |
equialgo/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 |
pnedunuri/scikit-learn | sklearn/manifold/locally_linear.py | 206 | 25061 | """Locally Linear Embedding"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) INRIA 2011
import numpy as np
from scipy.linalg import eigh, svd, qr, solve
from scipy.sparse import eye, csr_matrix
from ..base import B... | bsd-3-clause |
mespe/SolRad | collection/compare_cimis_cfsr/compare_cimis_cfsr.py | 1 | 2737 | import pandas as pd
import matplotlib.pyplot as plt
from netCDF4 import Dataset
import netCDF4
def load_CFSR_data():
my_example_nc_file = 'RES.nc' # latitude, longitude = (39.5, -122)
fh = Dataset(my_example_nc_file, mode='r')
print(fh.variables.keys())
print(help(fh.variables['time'... | mit |
ProstoMaxim/incubator-airflow | tests/contrib/hooks/test_bigquery_hook.py | 16 | 8098 | # -*- 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 |
douglasbagnall/py_bh_tsne | test_radial.py | 1 | 1367 | #!/usr/bin/python
import gzip, cPickle
import numpy as np
import matplotlib.pyplot as plt
import sys
from fasttsne import fast_tsne
import random
random.seed(1)
def generate_angular_clusters(n, d, extra_d=10):
data = []
classes = []
for i in range(n):
scale = random.random() * 5 + 0.1
cent... | bsd-3-clause |
Edu-Glez/Bank_sentiment_analysis | env/lib/python3.6/site-packages/ipykernel/inprocess/tests/test_kernel.py | 8 | 2417 | # Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
from __future__ import print_function
import sys
import unittest
from ipykernel.inprocess.blocking import BlockingInProcessKernelClient
from ipykernel.inprocess.manager import InProcessKernelManager
from ipykernel.in... | apache-2.0 |
timmyshen/kaggle-titanic | python_script/myfirstforest.py | 26 | 4081 | """ Writing my first randomforest code.
Author : AstroDave
Date : 23rd September 2012
Revised: 15 April 2014
please see packages.python.org/milk/randomforests.html for more
"""
import pandas as pd
import numpy as np
import csv as csv
from sklearn.ensemble import RandomForestClassifier
# Data cleanup
# TRAIN DATA
tra... | mit |
alexandrwang/6882project | strens/experiment.py | 1 | 2946 | import numpy as np
class Experiment(object):
""" An experiment matches up a task with an agent and handles their interactions.
"""
def __init__(self, task, agent):
self.task = task
self.agent = agent
self.stepid = 0
def doInteractions(self, number=1):
""" The default i... | mit |
arokem/sklearn-forest-ci | examples/plot_mpg_svr.py | 2 | 1964 | """
======================================
Plotting Bagging Regression Error Bars
======================================
This example demonstrates using `forestci` to calculate the error bars of
the predictions of a :class:`sklearn.ensemble.BaggingRegressor` object.
The data used here are a classical machine learning... | mit |
wavelets/ThinkStats2 | code/chap12ex_soln.py | 68 | 4459 | """This file contains code for use with "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2014 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function
import pandas
import numpy as np
import statsmodels.formula.api as smf
import t... | gpl-3.0 |
bm2-lab/cage | src/core/seqfs/seqfeature_mtlas_selector.py | 1 | 1888 | from __future__ import division
import numpy as np
import pandas as pd
from lxml import etree
from collections import namedtuple
from seqfeature_extractor import ExtractSeqFeature
from src.core import ml
Fr = namedtuple('Fr', ['fs', 'ups', 'dws'])
def __SaveFeatureReport(fr, str_of_fesrep):
f_fesrep = open(str_of... | mit |
odwyer-lab/microbial-innovations | bin/merge_tax.py | 2 | 1368 | import sys
import os
import re
from Bio import SeqIO
import numpy
import pandas
in_file1 = sys.argv[1]
in_file2 = sys.argv[2]
out_file = sys.argv[3]
# in_file1 = './data/LTPs123_unique.nr_v123.wang.taxonomy'
# in_file2 = './data/LTPs123_unique.taxonomy'
# out_file = './data/LTPs123.unique.full.taxonomy'
tax1 = pandas... | gpl-3.0 |
matthiasdiener/spack | var/spack/repos/builtin/packages/paraview/package.py | 4 | 8421 | ##############################################################################
# Copyright (c) 2013-2018, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
#
# This file is part of Spack.
# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
# LLNL-CODE-64... | lgpl-2.1 |
Akshay0724/scikit-learn | sklearn/grid_search.py | 16 | 40213 | """
The :mod:`sklearn.grid_search` includes utilities to fine-tune the parameters
of an estimator.
"""
from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# ... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/pandas/tests/scalar/test_period.py | 6 | 50302 | import pytest
import numpy as np
from datetime import datetime, date, timedelta
import pandas as pd
import pandas.util.testing as tm
import pandas.core.indexes.period as period
from pandas.compat import text_type, iteritems
from pandas.compat.numpy import np_datetime64_compat
from pandas._libs import tslib, period a... | mit |
AlexRobson/scikit-learn | examples/feature_selection/plot_rfe_with_cross_validation.py | 226 | 1384 | """
===================================================
Recursive feature elimination with cross-validation
===================================================
A recursive feature elimination example with automatic tuning of the
number of features selected with cross-validation.
"""
print(__doc__)
import matplotlib.p... | bsd-3-clause |
hsiaoyi0504/scikit-learn | examples/mixture/plot_gmm_pdf.py | 284 | 1528 | """
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import ma... | bsd-3-clause |
mbalasso/mynumpy | numpy/fft/fftpack.py | 9 | 39261 | """
Discrete Fourier Transforms
Routines in this module:
fft(a, n=None, axis=-1)
ifft(a, n=None, axis=-1)
rfft(a, n=None, axis=-1)
irfft(a, n=None, axis=-1)
hfft(a, n=None, axis=-1)
ihfft(a, n=None, axis=-1)
fftn(a, s=None, axes=None)
ifftn(a, s=None, axes=None)
rfftn(a, s=None, axes=None)
irfftn(a, s=None, axes=None... | bsd-3-clause |
michaelneuder/image_quality_analysis | bin/nets/wip/ssim_nets/ssim_net2.py | 2 | 9518 | #!/usr/bin/env python3
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import tensorflow as tf
import matplotlib as mpl
import matplotlib.gridspec as gridspec
import pandas as pd
import numpy as np
mpl.use('Agg')
import time
import matplotlib.pyplot as plt
def convolve_inner_layers(x, W, b):
'''
inner layers ... | mit |
jskDr/jamespy | tflearn/linear_regression.py | 7 | 2600 | '''
A linear regression learning algorithm example using TensorFlow library.
Author: Aymeric Damien
Project: https://github.com/aymericdamien/TensorFlow-Examples/
'''
import tensorflow as tf
import numpy
import matplotlib.pyplot as plt
rng = numpy.random
# Parameters
learning_rate = 0.01
training_epochs = 2000
displ... | mit |
lukeiwanski/tensorflow-opencl | 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 |
rajathkumarmp/BinPy | BinPy/analog/sig_gen.py | 4 | 22882 | from BinPy import *
import threading
import math
import time
import sys
class SignalGenerator(threading.Thread):
"""
Signal Generator Block
======================
Create a SignalGenerator object ( runs on a child thread ) used to generate
an analog voltage signal of the desired type. The frequen... | bsd-3-clause |
stefantkeller/VECSELsetup | eval/gen_functions.py | 1 | 16307 | #! /usr/bin/python2.7
# -*- coding: utf-8 -*-
from os.path import exists
import csv
import re
from itertools import izip as zip, count # izip for maximum efficiency: http://stackoverflow.com/questions/176918/finding-the-index-of-an-item-given-a-list-containing-it-in-python
import numpy as np
import matplotlib.pyplot ... | mit |
akionakamura/scikit-learn | sklearn/ensemble/tests/test_partial_dependence.py | 365 | 6996 | """
Testing for the partial dependence module.
"""
import numpy as np
from numpy.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import if_matplotlib
from sklearn.ensemble.partial_dependence import partial_dependence
from sklearn.ensemble.partial_dependence... | bsd-3-clause |
jyheo/pywsn | chart.py | 1 | 1761 | #!/usr/bin/python
# -*- coding: utf-8 -*-
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
color_tuples = [(255,128,128), (255,160,128), (255,255,152), (152,255,152), (128,255,208), (128,255,255),
(128,160,255), (128,128,255), (192,128,255), (255,128,255)]
def colors_str():
... | gpl-3.0 |
zorojean/scikit-learn | sklearn/datasets/species_distributions.py | 198 | 7923 | """
=============================
Species distribution dataset
=============================
This dataset represents the geographic distribution of species.
The dataset is provided by Phillips et. al. (2006).
The two species are:
- `"Bradypus variegatus"
<http://www.iucnredlist.org/apps/redlist/details/3038/0>`_... | bsd-3-clause |
actuaryzhang/spark | python/pyspark/sql/context.py | 12 | 21873 | #
# 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 |
justincassidy/scikit-learn | doc/tutorial/text_analytics/solutions/exercise_01_language_train_model.py | 254 | 2253 | """Build a language detector model
The goal of this exercise is to train a linear classifier on text features
that represent sequences of up to 3 consecutive characters so as to be
recognize natural languages by using the frequencies of short character
sequences as 'fingerprints'.
"""
# Author: Olivier Grisel <olivie... | bsd-3-clause |
laurensstoop/HiSPARC-BONZ | egg/legacy/egg_saskia_v3.3.py | 1 | 7620 | # -*- coding: utf-8 -*-
"""
===================================
Created on Thu Mar 24 13:17:57 2016
@author: Laurens Stoop
===================================
"""
################################## HEADER ##################################
"""
Import of Packages
"""
import sapphire # The HiSp... | gpl-3.0 |
anilmuthineni/tensorflow | tensorflow/contrib/learn/python/learn/estimators/_sklearn.py | 153 | 6723 | # 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 |
jniediek/combinato | tools/plot_thr_and_artifacts.py | 1 | 4805 | # -*- encoding: utf-8 -*-
# JN 2015-05-11
# what do I want in this script?
# * extraction thresholds in each region
# (and regression line, or other measure of variability)
# * rationale it's interesting to see whether highly variable channels are
# in one macro
# * firing rate stability for non-artifacts (correlated ... | mit |
yavalvas/yav_com | build/matplotlib/examples/api/custom_projection_example.py | 9 | 18246 | from __future__ import unicode_literals
import matplotlib
from matplotlib.axes import Axes
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import NullLocator, Formatter, FixedLocator
from matplotlib.transforms import Affine2D, BboxTransformTo, Transform
from matplotlib.pro... | mit |
alantian/polyglot | docs/conf.py | 4 | 10864 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# complexity documentation build configuration file, created by
# sphinx-quickstart on Tue Jul 9 22:26:36 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
# ... | gpl-3.0 |
jcouvy/convnet-nolearn | src/blog/net1.py | 1 | 1958 | # -------------------- Loading Data-set --------------------
import cPickle
import pandas as pd
import numpy as np
# The competition datafiles are in the directory ../input
# Read training and test data files
train = pd.read_csv("../../input/train.csv")
test = pd.read_csv("../../input/test.csv")
train_images = trai... | mit |
jjx02230808/project0223 | sklearn/metrics/cluster/supervised.py | 22 | 30444 | """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 |
kshedstrom/pyroms | examples/NWGOA3/Fetch_Pacific/get_pacific_v.py | 1 | 5086 | import matplotlib
matplotlib.use('Agg')
import numpy as np
import netCDF4
from datetime import datetime
import pyroms
import pyroms_toolbox
import sys
year = int(sys.argv[1])
def create_HYCOM_file(name):
global nc
print 'Creating file %s' %name
#create netCDF file
nc = netCDF4.Dataset(name, 'w', fo... | bsd-3-clause |
planetarymike/IDL-Colorbars | IDL_py_test/042_CB-Dark2.py | 1 | 8651 | from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
cm_data = [[0.105882, 0.619608, 0.466667],
[0.12549, 0.611765, 0.454902],
[0.14902, 0.607843, 0.443137],
[0.168627, 0.6, 0.427451],
[0.188235, 0.592157, 0.415686],
[0.207843, 0.584314, 0.403922],
[0.231373, 0.580392, 0.392157],
[0.25098, 0... | gpl-2.0 |
rseubert/scikit-learn | examples/ensemble/plot_bias_variance.py | 357 | 7324 | """
============================================================
Single estimator versus bagging: bias-variance decomposition
============================================================
This example illustrates and compares the bias-variance decomposition of the
expected mean squared error of a single estimator again... | bsd-3-clause |
rsivapr/scikit-learn | examples/neighbors/plot_classification.py | 8 | 1769 | """
================================
Nearest Neighbors Classification
================================
Sample usage of Nearest Neighbors classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import pylab as pl
from matplotlib.colors import ListedColormap
from sklea... | bsd-3-clause |
myinxd/agn-ae | utils/sample-class.py | 1 | 2956 | # Copyright (C) 2017 Zhixian MA <zxma_sjtu@qq.com>
"""
Rename samples of Best into the JHHMMSS.ss+/-DDMMSS.s style
Reference
=========
[1] math.modf
http://www.runoob.com/python/func-number-modf.html
"""
import os
import math
import numpy as np
import time
import argparse
import pickle
def batch_class_csv(listp... | mit |
amueller/advanced_training | mglearn/plot_improper_preprocessing.py | 2 | 3016 | import matplotlib.pyplot as plt
def make_bracket(s, xy, textxy, width, ax):
annotation = ax.annotate(
s, xy, textxy, ha="center", va="center", size=20,
arrowprops=dict(arrowstyle="-[", fc="w", ec="k",
lw=2,), bbox=dict(boxstyle="square", fc="w"))
annotation.arrow_patch.... | bsd-2-clause |
BorisJeremic/Real-ESSI-Examples | analytic_solution/test_cases/Contact/Static_Normal_Contact/Normal_Behviour/SoftContact_ElPPlShear/plot.py | 6 | 1583 | #!/usr/bin/python
import h5py
import matplotlib.pylab as plt
import sys
import numpy as np;
################ Node # 2 Displacement #############################
#######################################
## Analytical Solution
#######################################
finput = h5py.File('Analytical_Solution.feioutput')
... | cc0-1.0 |
sam81/pychoacoustics | tests/test_transformed_up_down_interleaved.py | 1 | 3880 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import numpy, os, sys, unittest
import pandas as pd
from test_utility_functions import*
rootPath = "../../pychoacoustics_data/test_data/"
class TestTransformedUpDown(unittest.TestCase):
def testGeometric(self):
resFileRoot = "res_geometric"
removePre... | gpl-3.0 |
maxlit/powerindex | powerindex/powerindex.py | 1 | 12803 | import math
import itertools as it
class Party:
def __init__(self,weight,name):
self.weight=weight
self.name=name
def __eq__(self,other):
if self.name==other.name:
return True
else:
return False
def __ne__(self,other):
return not (self==other)... | mit |
vighneshbirodkar/scikit-image | doc/examples/features_detection/plot_windowed_histogram.py | 4 | 5150 | """
========================
Sliding window histogram
========================
Histogram matching can be used for object detection in images [1]_. This
example extracts a single coin from the ``skimage.data.coins`` image and uses
histogram matching to attempt to locate it within the original image.
First, a box-shape... | bsd-3-clause |
gfyoung/pandas | pandas/tests/scalar/timedelta/test_timedelta.py | 2 | 19427 | """ test the scalar Timedelta """
from datetime import timedelta
import numpy as np
import pytest
from pandas._libs.tslibs import NaT, iNaT
import pandas as pd
from pandas import Timedelta, TimedeltaIndex, offsets, to_timedelta
import pandas._testing as tm
class TestTimedeltaUnaryOps:
def test_unary_ops(self):... | bsd-3-clause |
kaiserroll14/301finalproject | main/pandas/io/packers.py | 9 | 23542 | """
Msgpack serializer support for reading and writing pandas data structures
to disk
"""
# portions of msgpack_numpy package, by Lev Givon were incorporated
# into this module (and tests_packers.py)
"""
License
=======
Copyright (c) 2013, Lev Givon.
All rights reserved.
Redistribution and use in source and binary ... | gpl-3.0 |
CompPhysics/MachineLearning | doc/src/SupportVMachines/Programs/cancer.py | 2 | 1731 | import matplotlib.pyplot as plt
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_breast_cancer
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
# Load the data
cancer = load_breast_... | cc0-1.0 |
sonnyhu/scikit-learn | sklearn/metrics/cluster/supervised.py | 11 | 33436 | """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>
# Arnaud Fouchet ... | bsd-3-clause |
shenzebang/scikit-learn | examples/model_selection/plot_validation_curve.py | 229 | 1823 | """
==========================
Plotting Validation Curves
==========================
In this plot you can see the training scores and validation scores of an SVM
for different values of the kernel parameter gamma. For very low values of
gamma, you can see that both the training score and the validation score are
low. ... | bsd-3-clause |
glouppe/scikit-learn | sklearn/feature_selection/tests/test_from_model.py | 62 | 6762 | import numpy as np
import scipy.sparse as sp
from nose.tools import assert_raises, assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.ut... | bsd-3-clause |
anetasie/sherpa | sherpa/conftest.py | 1 | 17067 | #
# Copyright (C) 2016, 2017, 2018, 2019, 2020
# Smithsonian Astrophysical Observatory
#
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
... | gpl-3.0 |
alexmojaki/blaze | blaze/compute/tests/test_hdfstore.py | 14 | 1791 | import pytest
tables = pytest.importorskip('tables')
from blaze.compute.hdfstore import *
from blaze.utils import tmpfile
from blaze import symbol, discover, compute
import pandas as pd
from datetime import datetime
from odo import Chunks, resource, into
import os
try:
f = pd.HDFStore('foo')
except (RuntimeError... | bsd-3-clause |
eubr-bigsea/tahiti | migrations/versions/54147db30380_fixing_some_sklearn_operations.py | 1 | 8064 | """fixing some sklearn operations.
Revision ID: 54147db30380
Revises: 29ecca388884
Create Date: 2020-01-23 12:51:44.638796
"""
from alembic import context
from alembic import op
from sqlalchemy import String, Integer, Text
from sqlalchemy.orm import sessionmaker
from sqlalchemy.sql import table, column
# revision i... | apache-2.0 |
vermouthmjl/scikit-learn | sklearn/cross_validation.py | 4 | 67659 |
"""
The :mod:`sklearn.cross_validation` module includes utilities for cross-
validation and performance evaluation.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>,
# Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
fro... | bsd-3-clause |
blond-admin/BLonD | blond/toolbox/filters_and_fitting.py | 2 | 7393 | # coding: utf-8
# Copyright 2017 CERN. This software is distributed under the
# terms of the GNU General Public Licence version 3 (GPL Version 3),
# copied verbatim in the file LICENCE.md.
# In applying this licence, CERN does not waive the privileges and immunities
# granted to it by virtue of its status as an In... | gpl-3.0 |
klim-/pyplane | gui/App_PyPlane.py | 1 | 21182 | # -*- coding: utf-8 -*-
# Copyright (C) 2013
# by Klemens Fritzsche, pyplane@leckstrom.de
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# ... | gpl-3.0 |
SaganBolliger/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/dates.py | 54 | 33991 | #!/usr/bin/env python
"""
Matplotlib provides sophisticated date plotting capabilities, standing
on the shoulders of python :mod:`datetime`, the add-on modules
:mod:`pytz` and :mod:`dateutils`. :class:`datetime` objects are
converted to floating point numbers which represent the number of days
since 0001-01-01 UTC. T... | agpl-3.0 |
daniilsorokin/Web-Mining-Exercises | src/correlations.py | 1 | 1064 | '''
Created on Jun 21, 2015
@author: Daniil Sorokin<sorokin@ukp.informatik.tu-darmstadt.de>
'''
import argparse
from vector_representation import read_vectors_from_csv
from classfiers import NBClassifier
import matplotlib.pyplot as plt
import numpy as np
if __name__ == '__main__':
parser = argparse.ArgumentParser... | mit |
kkk669/mxnet | python/mxnet/model.py | 17 | 39894 | # 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 |
PredictiveScienceLab/GPy | GPy/testing/likelihood_tests.py | 8 | 35323 | # Copyright (c) 2014, Alan Saul
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
import unittest
import GPy
from GPy.models import GradientChecker
import functools
import inspect
from GPy.likelihoods import link_functions
from functools import partial
fixed_seed = 7
#np.seterr(divide='rai... | bsd-3-clause |
bmassman/fake_news | fake_news/pipeline/build_df.py | 1 | 1826 | #!/usr/bin/env python3
"""
Module to build dataframe of news articles from sqlite3 database.
"""
import os
import re
from urllib.parse import urlparse
import sqlite3
from contextlib import closing
from datetime import datetime
from typing import Optional
import pandas as pd
DB_FILE_NAME = os.path.join('fake_news', 'ar... | mit |
ssaeger/scikit-learn | benchmarks/bench_isolation_forest.py | 40 | 3136 | """
==========================================
IsolationForest benchmark
==========================================
A test of IsolationForest on classical anomaly detection datasets.
"""
print(__doc__)
from time import time
import numpy as np
import matplotlib.pyplot as plt
from sklearn.ensemble import IsolationFore... | bsd-3-clause |
mattjj/pyhawkes | experiments/harness.py | 2 | 16840 | """
Test harness for fitting the competing models.
"""
import time
import cPickle
import copy
import os
import gzip
import numpy as np
from collections import namedtuple
from pybasicbayes.util.text import progprint_xrange
# Use the Agg backend in running on a server without the DISPLAY variable
if "DISPLAY" not in o... | mit |
lokeshpancharia/BuildingMachineLearningSystemsWithPython | ch10/neighbors.py | 21 | 1787 | # This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
import numpy as np
import mahotas as mh
from glob import glob
from features import texture, color_histogram
from matplotlib import pyplot as plt
from ... | mit |
mmottahedi/neuralnilm_prototype | scripts/e507.py | 2 | 6411 | from __future__ import print_function, division
import matplotlib
import logging
from sys import stdout
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import (Net, RealApplianceSource,
BLSTMLayer, DimshuffleLayer,
Bidirectiona... | mit |
carrillo/scikit-learn | examples/ensemble/plot_adaboost_twoclass.py | 347 | 3268 | """
==================
Two-class AdaBoost
==================
This example fits an AdaBoosted decision stump on a non-linearly separable
classification dataset composed of two "Gaussian quantiles" clusters
(see :func:`sklearn.datasets.make_gaussian_quantiles`) and plots the decision
boundary and decision scores. The di... | bsd-3-clause |
paulirish/dadi | dadi/__init__.py | 10 | 1326 | """
For examples of dadi's usage, see the examples directory in the source
distribution.
Documentation of all methods can be found in doc/api/index.html of the source
distribution.
"""
import logging
logging.basicConfig()
import Demographics1D
import Demographics2D
import Inference
import Integration
import Misc
impo... | bsd-3-clause |
alexsavio/scikit-learn | sklearn/datasets/tests/test_base.py | 13 | 8907 | import os
import shutil
import tempfile
import warnings
import numpy
from pickle import loads
from pickle import dumps
from sklearn.datasets import get_data_home
from sklearn.datasets import clear_data_home
from sklearn.datasets import load_files
from sklearn.datasets import load_sample_images
from sklearn.datasets im... | bsd-3-clause |
meee1/pymavlink | examples/mavgraph.py | 1 | 5880 | #!/usr/bin/env python
'''
graph a MAVLink log file
Andrew Tridgell August 2011
'''
import sys, struct, time, os, datetime
import math, re
import pylab, pytz, matplotlib
from math import *
# allow import from the parent directory, where mavlink.py is
sys.path.insert(0, os.path.join(os.path.dirname(os.path.realpath(__f... | lgpl-3.0 |
karstenw/nodebox-pyobjc | examples/Extended Application/sklearn/examples/covariance/plot_lw_vs_oas.py | 1 | 3759 | """
=============================
Ledoit-Wolf vs OAS estimation
=============================
The usual covariance maximum likelihood estimate can be regularized
using shrinkage. Ledoit and Wolf proposed a close formula to compute
the asymptotically optimal shrinkage parameter (minimizing a MSE
criterion), yielding th... | mit |
blancha/abcngspipelines | rnaseq/cuffdiff.py | 1 | 3767 | #!/usr/bin/env python3
# Version 1.1
# Author Alexis Blanchet-Cohen
# Date: 09/06/2014
import argparse
from collections import OrderedDict
import glob
import os
import os.path
import pandas
import subprocess
import util
# Read the command line arguments.
parser = argparse.ArgumentParser(description="Generates Cuffdi... | gpl-3.0 |
bond-/udacity-ml | src/numpy-pandas-tutorials/quiz-avg-bronze-medals.py | 1 | 1951 | from pandas import DataFrame, Series
import numpy
def avg_medal_count():
'''
Compute the average number of bronze medals earned by countries who
earned at least one gold medal.
Save this to a variable named avg_bronze_at_least_one_gold. You do not
need to call the function in your code whe... | apache-2.0 |
icexelloss/spark | python/pyspark/worker.py | 3 | 19219 | #
# 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 |
GuessWhoSamFoo/pandas | pandas/tests/io/test_packers.py | 1 | 33322 | import datetime
from distutils.version import LooseVersion
import glob
import os
from warnings import catch_warnings
import numpy as np
import pytest
from pandas._libs.tslib import iNaT
from pandas.compat import PY3, u
from pandas.errors import PerformanceWarning
import pandas
from pandas import (
Categorical, D... | bsd-3-clause |
cybernet14/scikit-learn | sklearn/linear_model/tests/test_coordinate_descent.py | 114 | 25281 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from sys import version_info
import numpy as np
from scipy import interpolate, sparse
from copy import deepcopy
from sklearn.datasets import load_boston
from sklearn.utils.testing ... | bsd-3-clause |
kazemakase/scikit-learn | examples/decomposition/plot_kernel_pca.py | 353 | 2011 | """
==========
Kernel PCA
==========
This example shows that Kernel PCA is able to find a projection of the data
that makes data linearly separable.
"""
print(__doc__)
# Authors: Mathieu Blondel
# Andreas Mueller
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomp... | bsd-3-clause |
soulmachine/scikit-learn | sklearn/metrics/cluster/unsupervised.py | 10 | 8104 | """ Unsupervised evaluation metrics. """
# Authors: Robert Layton <robertlayton@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ...utils import check_random_state
from ..pairwise import pairwise_distances
def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random... | bsd-3-clause |
glouppe/scikit-learn | sklearn/_build_utils/__init__.py | 21 | 1125 | """
Utilities useful during the build.
"""
# author: Andy Mueller, Gael Varoquaux
# license: BSD
from __future__ import division, print_function, absolute_import
HASH_FILE = 'cythonize.dat'
DEFAULT_ROOT = 'sklearn'
# WindowsError is not defined on unix systems
try:
WindowsError
except NameError:
WindowsError... | bsd-3-clause |
ubic135/odoo-design | 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 |
ktaneishi/deepchem | contrib/dragonn/models.py | 6 | 16267 | from __future__ import absolute_import, division, print_function
import matplotlib
import numpy as np
import os
import subprocess
import sys
import tempfile
matplotlib.use('pdf')
import matplotlib.pyplot as plt
from dragonn.metrics import ClassificationResult
from keras.layers.core import (Activation, Dense, Dropout, F... | mit |
pnedunuri/scikit-learn | examples/cluster/plot_lena_ward_segmentation.py | 271 | 1998 | """
===============================================================
A demo of structured Ward hierarchical clustering on Lena image
===============================================================
Compute the segmentation of a 2D image with Ward hierarchical
clustering. The clustering is spatially constrained in order
... | bsd-3-clause |
SamHames/scikit-image | skimage/viewer/tests/test_tools.py | 1 | 6018 | from collections import namedtuple
import numpy as np
from numpy.testing import assert_equal
from numpy.testing.decorators import skipif
from skimage import data
from skimage.viewer import ImageViewer, viewer_available
from skimage.viewer.canvastools import (
LineTool, ThickLineTool, RectangleTool, PaintTool)
from... | bsd-3-clause |
soulmachine/scikit-learn | sklearn/tests/test_base.py | 19 | 6858 |
# Author: Gael Varoquaux
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing imp... | bsd-3-clause |
brianlorenz/COSMOS_IMACS_Redshifts | PlotCodes/SED_Ratio.py | 1 | 13733 | #Finds the ratio between our observed spectra and the ULTRAVista ones so that we can flux calibrate the data
#Usage: run SED_Ratio.py a6 to find the ratio for the a6 mask.
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import ascii
import sys, os, string
import pandas as pd
from astropy... | mit |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/pandas/tseries/tests/test_base.py | 7 | 116023 | from __future__ import print_function
from datetime import datetime, timedelta
import numpy as np
import pandas as pd
from pandas import (Series, Index, Int64Index, Timestamp, Period,
DatetimeIndex, PeriodIndex, TimedeltaIndex,
Timedelta, timedelta_range, date_range, Float64Index... | gpl-3.0 |
dandye/expedia | PythonBenchmark/data_io.py | 3 | 1229 | import csv
from operator import itemgetter
import os
import json
import pickle
import pandas as pd
def get_paths():
paths = json.loads(open("SETTINGS.json").read())
for key in paths:
paths[key] = os.path.expandvars(paths[key])
return paths
def read_train():
train_path = get_paths()["train_path... | bsd-3-clause |
PrashntS/scikit-learn | examples/neighbors/plot_kde_1d.py | 347 | 5100 | """
===================================
Simple 1D Kernel Density Estimation
===================================
This example uses the :class:`sklearn.neighbors.KernelDensity` class to
demonstrate the principles of Kernel Density Estimation in one dimension.
The first plot shows one of the problems with using histogram... | bsd-3-clause |
paris-saclay-cds/ramp-workflow | rampwf/utils/scoring.py | 1 | 5037 | # coding: utf-8
"""
Scoring utilities
"""
import numpy as np
import pandas as pd
from .pretty_print import IS_COLOR_TERM
from .pretty_print import print_warning
def reorder_df_scores(df_scores, score_types):
"""Reorder scores according to the order in score_types.
Parameters
----------
df_scores : p... | bsd-3-clause |
nhuntwalker/astroML | book_figures/chapter5/fig_likelihood_gaussgauss.py | 3 | 3082 | """
Gaussian Distribution with Gaussian Errors
------------------------------------------
Figure 5.7
The logarithm of the posterior probability density function for :math:`\mu`
and :math:`\sigma`, :math:`L_p(\mu,\sigma)`, for a Gaussian distribution with
heteroscedastic Gaussian measurement errors (sampled uniformly f... | bsd-2-clause |
huongttlan/statsmodels | statsmodels/tools/tests/test_tools.py | 26 | 18818 | """
Test functions for models.tools
"""
from statsmodels.compat.python import lrange, range
import numpy as np
from numpy.random import standard_normal
from numpy.testing import (assert_equal, assert_array_equal,
assert_almost_equal, assert_string_equal, TestCase)
from nose.tools import (asse... | bsd-3-clause |
sunyihuan326/DeltaLab | Andrew_NG_learning/class_one/week_three/syh_01.py | 1 | 5963 | # coding:utf-8
'''
Created on 2017/11/6
@author: sunyihuan
'''
import numpy as np
import matplotlib.pyplot as plt
from class_one.week_three import testCases
import sklearn
import sklearn.datasets
import sklearn.linear_model
import class_one.week_three.testCases
from class_one.week_three.planar_utils import plot_decisi... | mit |
kdebrab/pandas | pandas/tests/extension/base/interface.py | 2 | 2196 | import numpy as np
import pandas as pd
from pandas.compat import StringIO
from pandas.core.dtypes.common import is_extension_array_dtype
from pandas.core.dtypes.dtypes import ExtensionDtype
from .base import BaseExtensionTests
class BaseInterfaceTests(BaseExtensionTests):
"""Tests that the basic interface is sa... | bsd-3-clause |
ResByte/graph_slam | scripts/robot.py | 1 | 1487 | #!/usr/bin/env python
import roslib
import rospy
import sys
from geometry_msgs.msg import Twist
import numpy as np
from nav_msgs.msg import Odometry
from tf.transformations import euler_from_quaternion
import matplotlib.pyplot as plt
from sensor_msgs.msg import PointCloud2
import sensor_msgs.point_cloud2 as pc2
imp... | gpl-2.0 |
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