repo_name stringlengths 7 92 | path stringlengths 5 149 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 911 693k | license stringclasses 15
values |
|---|---|---|---|---|---|
girving/tensorflow | tensorflow/contrib/learn/python/learn/estimators/__init__.py | 39 | 12688 | # 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 |
18padx08/PPTex | PPTexEnv_x86_64/lib/python2.7/site-packages/matplotlib/tests/test_transforms.py | 9 | 19984 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange, zip
import unittest
from nose.tools import assert_equal, assert_raises
import numpy.testing as np_test
from numpy.testing import assert_almost_equal
from matplotlib.tr... | mit |
samuelstjean/dipy | scratch/very_scratch/diffusion_sphere_stats.py | 20 | 18082 | import nibabel
import os
import numpy as np
import dipy as dp
#import dipy.core.generalized_q_sampling as dgqs
import dipy.reconst.gqi as dgqs
import dipy.reconst.dti as ddti
import dipy.reconst.recspeed as rp
import dipy.io.pickles as pkl
import scipy as sp
from matplotlib.mlab import find
#import dipy.core.sphere_pl... | bsd-3-clause |
blab/antibody-response-pulse | bcell-array/code/Virus_Bcell_IgM_IgG_Landscape.py | 1 | 11385 |
# coding: utf-8
# # Antibody Response Pulse
# https://github.com/blab/antibody-response-pulse
#
# ### B-cells evolution --- cross-reactive antibody response after influenza virus infection or vaccination
# ### Adaptive immune response for repeated infection
# In[1]:
'''
author: Alvason Zhenhua Li
date: 04/09/201... | gpl-2.0 |
only4hj/fast-rcnn | lib/roi_data_layer/minibatch.py | 1 | 22641 | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Compute minibatch blobs for training a Fast R-CNN network."""
impor... | mit |
rodluger/everest | docs/mcmc.py | 1 | 2721 | """MCMC example for transit fitting."""
import matplotlib.pyplot as pl
from everest import Everest, TransitModel
import numpy as np
import emcee
from tqdm import tqdm
from corner import corner
def lnprior(x):
"""Return the log prior given parameter vector `x`."""
per, t0, b = x
if b < -1 or b > 1:
... | mit |
cxcsds/ciao-contrib | crates_contrib/images.py | 1 | 4630 | #
# Copyright (C) 2012, 2015, 2016, 2019
# 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 2 of the License, or
# (at you... | gpl-3.0 |
rasbt/python-machine-learning-book | code/optional-py-scripts/ch05.py | 1 | 19830 | # Sebastian Raschka, 2015 (http://sebastianraschka.com)
# Python Machine Learning - Code Examples
#
# Chapter 5 - Compressing Data via Dimensionality Reduction
#
# S. Raschka. Python Machine Learning. Packt Publishing Ltd., 2015.
# GitHub Repo: https://github.com/rasbt/python-machine-learning-book
#
# License: MIT
# ht... | mit |
LewBurton/sklearn_pycon2015 | notebooks/fig_code/sgd_separator.py | 54 | 1148 | import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import SGDClassifier
from sklearn.datasets.samples_generator import make_blobs
def plot_sgd_separator():
# we create 50 separable points
X, Y = make_blobs(n_samples=50, centers=2,
random_state=0, cluster_std=0.60... | bsd-3-clause |
sodafree/backend | build/ipython/IPython/frontend/terminal/console/app.py | 3 | 5217 | """ A minimal application using the ZMQ-based terminal IPython frontend.
This is not a complete console app, as subprocess will not be able to receive
input, there is no real readline support, among other limitations.
Authors:
* Min RK
* Paul Ivanov
"""
#------------------------------------------------------------... | bsd-3-clause |
RachitKansal/scikit-learn | sklearn/manifold/isomap.py | 229 | 7169 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
alekz112/xlwings | xlwings/tests/test_xlwings.py | 1 | 33895 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
import os
import sys
import shutil
import pytz
import nose
from nose.tools import assert_equal, raises, assert_true, assert_false, assert_not_equal
from datetime import datetime, date
from xlwings import Application, Workbook, Sheet, Range, Chart, ChartTy... | apache-2.0 |
vybstat/scikit-learn | sklearn/ensemble/__init__.py | 217 | 1307 | """
The :mod:`sklearn.ensemble` module includes ensemble-based methods for
classification and regression.
"""
from .base import BaseEnsemble
from .forest import RandomForestClassifier
from .forest import RandomForestRegressor
from .forest import RandomTreesEmbedding
from .forest import ExtraTreesClassifier
from .fores... | bsd-3-clause |
arahuja/scikit-learn | sklearn/calibration.py | 12 | 18774 | """Calibration of predicted probabilities."""
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Balazs Kegl <balazs.kegl@gmail.com>
# Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Mathieu Blondel <mathieu@mblondel.org>
#
# License: BSD 3 clause
from __future__ impo... | bsd-3-clause |
dudulianangang/vps | EneConsTest.py | 1 | 5969 | import sdf
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
plt.style.use('seaborn-white')
# plt.rcParams['font.family'] = 'sans-serif'
# plt.rcParams['font.sans-serif'] = 'Tahoma'
# # plt.rcParams['font.monospace'] = 'Ubuntu Mono'
plt.rcParams['font.size'] = 16
# plt.rcParams['axes.labelsiz... | apache-2.0 |
taknevski/tensorflow-xsmm | tensorflow/contrib/learn/python/learn/dataframe/tensorflow_dataframe.py | 75 | 29377 | # 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 |
pleoni/game-of-life | plot/old/test_perf_mpi/life_perf_compilers.py | 1 | 1863 | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from numpy import *
import sys
import datetime
datafile1="life_host_icc.out"
datafile2="life_host_gnu.out"
datafile3="life_host_pgi.out"
if len(sys.argv) > 1:
datafile=sys.argv[1]
plotfile="compilers_perf_eurora.png"
data1 = loadtxt(datafile... | gpl-2.0 |
DistrictDataLabs/yellowbrick | yellowbrick/classifier/rocauc.py | 1 | 29053 | # yellowbrick.classifier.rocauc
# Implements visual ROC/AUC curves for classification evaluation.
#
# Author: Rebecca Bilbro
# Author: Benjamin Bengfort
# Author: Neal Humphrey
# Created: Tue May 03 18:15:42 2017 -0400
#
# Copyright (C) 2016 The scikit-yb developers
# For license information, see LICENSE.txt
#
#... | apache-2.0 |
Wonjuseo/Project101 | others/sine_RNN.py | 1 | 4425 | import tensorflow as tf
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.utils import shuffle
def sin(x, T=100):
return np.sin(2.0*np.pi*x/T)
def problem(T=100,ampl=0.05):
x = np.arange(0,2*T+1)
noise = ampl*np.random.uniform(low=-1.0,high=1.0,size=len(x))
... | apache-2.0 |
Srisai85/scikit-learn | examples/linear_model/plot_iris_logistic.py | 283 | 1678 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logistic Regression 3-class Classifier
=========================================================
Show below is a logistic-regression classifiers decision boundaries on the
`iris <http://en.wikipedia.org/wiki/Iris_f... | bsd-3-clause |
mjudsp/Tsallis | sklearn/tests/test_random_projection.py | 141 | 14040 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from sklearn.metrics import euclidean_distances
from sklearn.random_projection import johnson_lindenstrauss_min_dim
from sklearn.random_projection import gaussian_random_matrix
from sklearn.random_projection import sparse_random_matrix
from... | bsd-3-clause |
mugizico/scikit-learn | sklearn/externals/joblib/__init__.py | 36 | 4795 | """ 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 |
nagordon/mechpy | mechpy/composites.py | 1 | 71681 | # coding: utf-8
'''
Module for composite material analysis
Hyer-Stress Analysis of Fiber-Reinforced Composite Materials
Herakovich-Mechanics of Fibrous Composites
Daniel-Engineering Mechanics of Composite Materials
Kollar-Mechanics of COmposite Structures
NASA- Basic Mechancis of Lamianted Composites
ht... | mit |
guziy/basemap | setup.py | 1 | 6013 | from __future__ import (absolute_import, division, print_function)
import glob
import io
import os
import sys
from setuptools.dist import Distribution
if sys.version_info < (2, 6):
raise SystemExit("""matplotlib and the basemap toolkit require Python 2.6 or later.""")
# Do not require numpy for just querying the... | gpl-2.0 |
YuepengGuo/zipline | zipline/history/history.py | 11 | 11707 | #
# Copyright 2014 Quantopian, Inc.
#
# 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 wr... | apache-2.0 |
chugunovyar/factoryForBuild | env/lib/python2.7/site-packages/matplotlib/sphinxext/mathmpl.py | 12 | 3822 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import os
import sys
from hashlib import md5
from docutils import nodes
from docutils.parsers.rst import directives
import warnings
from matplotlib import rcParams
from matplotlib.mathtext import ... | gpl-3.0 |
pylayers/pylayers | pylayers/antprop/examples/ex_signature.py | 3 | 3411 | #!/usr/bin/python
#-*- coding:Utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import networkx as nx
from pylayers.gis.layout import *
from pylayers.antprop.signature import *
# load the layout graphs
def showr2(L,r2d,tx,rx,k,l):
col = ['r','b','g','c','m','k','y']
r = r2d[str(k)]
pts = r['pt'... | mit |
aldian/tensorflow | tensorflow/python/estimator/inputs/queues/feeding_functions_test.py | 59 | 13552 | # 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 |
matbra/bokeh | examples/compat/mpl/listcollection.py | 34 | 1602 | from matplotlib.collections import LineCollection
import matplotlib.pyplot as plt
import numpy as np
from bokeh import mpl
from bokeh.plotting import output_file, show
def make_segments(x, y):
'''
Create list of line segments from x and y coordinates.
'''
points = np.array([x, y]).T.reshape(-1, 1, 2... | bsd-3-clause |
sgenoud/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 3 | 2890 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from numpy.testing import assert_equal
from scipy.spatial import distance
from sklearn.cluster.dbscan_ import DBSCAN, dbscan
from .common import generate_clustered_data
n_clusters = 3
X = generate_clustered_data(n_clusters=n_clusters)
... | bsd-3-clause |
nekrut/tools-iuc | tools/vsnp/vsnp_add_zero_coverage.py | 12 | 6321 | #!/usr/bin/env python
import argparse
import os
import re
import shutil
import pandas
import pysam
from Bio import SeqIO
def get_sample_name(file_path):
base_file_name = os.path.basename(file_path)
if base_file_name.find(".") > 0:
# Eliminate the extension.
return os.path.splitext(base_file_... | mit |
eduardoneira/SistemasDistribuidos_TPFinal | CentroMonitoreoCiudad/FaceRecognizer/modules/old_feature_matcher.py | 1 | 4628 | #!/bin/python3
import numpy as np
import cv2
import base64
import pdb
from tkinter import *
from matplotlib import pyplot as plt
class FeatureMatcher:
__PORC_DISTANCE = 0.7
def __init__(self,feature_extractor='SURF',upright=True,min_match_count=10,threshold=400):
self.MIN_MATCH_COUNT = min_match_count
... | gpl-3.0 |
DTOcean/dtocean-core | tests/test_data_definitions_simplepie.py | 1 | 2601 | import pytest
import matplotlib.pyplot as plt
from aneris.control.factory import InterfaceFactory
from dtocean_core.core import (AutoFileInput,
AutoFileOutput,
AutoPlot,
Core)
from dtocean_core.data import CoreMetaData
from d... | gpl-3.0 |
buntyke/GPy | GPy/core/gp.py | 8 | 37031 | # Copyright (c) 2012-2014, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
import sys
from .. import kern
from .model import Model
from .parameterization import ObsAr
from .mapping import Mapping
from .. import likelihoods
from ..inference.latent_function_i... | mit |
jiyfeng/RSTParser | model.py | 1 | 3945 | ## model.py
## Author: Yangfeng Ji
## Date: 09-09-2014
## Time-stamp: <yangfeng 11/05/2014 20:44:25>
## Last changed: umashanthi 11/19/2014
""" As a parsing model, it includes the following functions
1, Mini-batch training on the data generated by the Data class
2, Shift-Reduce RST parsing for a given text sequence
3... | mit |
sinhrks/scikit-learn | examples/manifold/plot_lle_digits.py | 138 | 8594 | """
=============================================================================
Manifold learning on handwritten digits: Locally Linear Embedding, Isomap...
=============================================================================
An illustration of various embeddings on the digits dataset.
The RandomTreesEmbed... | bsd-3-clause |
sebp/scikit-survival | sksurv/preprocessing.py | 1 | 3945 | # 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
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# bu... | gpl-3.0 |
jeffknupp/arrow | python/scripts/test_leak.py | 6 | 1847 | #!/usr/bin/env python
# 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
# "L... | apache-2.0 |
jreback/pandas | pandas/tests/io/parser/usecols/test_strings.py | 6 | 2564 | """
Tests the usecols functionality during parsing
for all of the parsers defined in parsers.py
"""
from io import StringIO
import pytest
from pandas import DataFrame
import pandas._testing as tm
_msg_validate_usecols_arg = (
"'usecols' must either be list-like "
"of all strings, all unicode, all "
"inte... | bsd-3-clause |
yaojenkuo/stockflow | ctrls/CandleDrawer.py | 2 | 3513 | #!/bin/python
# -*- coding: utf-8 -*-
import numpy as np
from settings import *
from datetime import datetime
from ctrls.Reader import Reader
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick_ohlc
class CandleDrawer():
'''畫出近 n 天 K 線圖＋Ma20布林通道+高低通道+量'''
def _getBooleanBand(self, seri... | mit |
allenlavoie/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/pandas_io.py | 28 | 5024 | # 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 |
PatrickChrist/scikit-learn | examples/svm/plot_svm_anova.py | 250 | 2000 | """
=================================================
SVM-Anova: SVM with univariate feature selection
=================================================
This example shows how to perform univariate feature before running a SVC
(support vector classifier) to improve the classification scores.
"""
print(__doc__)
import... | bsd-3-clause |
NEONScience/NEON-Data-Skills | tutorials/Python/Lidar/lidar-biomass/calc-biomass_py/calc-biomass_py.py | 1 | 20510 | #!/usr/bin/env python
# coding: utf-8
# ---
# syncID: e6ccf19a4b454ca594388eeaa88ebe12
# title: "Calculate Vegetation Biomass from LiDAR Data in Python"
# description: "Learn to calculate the biomass of standing vegetation using a canopy height model data product."
# dateCreated: 2017-06-21
# authors: Tristan Goulde... | agpl-3.0 |
herilalaina/scikit-learn | sklearn/feature_selection/tests/test_rfe.py | 15 | 11812 | """
Testing Recursive feature elimination
"""
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
from scipy import sparse
from sklearn.feature_selection.rfe import RFE, RFECV
from sklearn.datasets import load_iris, make_friedman1
from sklearn.metrics import zero_one_loss
from sk... | bsd-3-clause |
antoinecarme/pyaf | setup.py | 1 | 1126 | from setuptools import setup
from setuptools import find_packages
with open("README.md", "r") as fh:
pyaf_long_description = fh.read()
setup(name='pyaf',
version='3.0-RC1',
description='Python Automatic Forecasting',
long_description=pyaf_long_description,
long_description_content_type... | bsd-3-clause |
thorwhalen/ut | ml/sk/transformers.py | 1 | 4610 |
__author__ = 'thor'
from sklearn.base import TransformerMixin, BaseEstimator
from sklearn.neighbors import KNeighborsRegressor
from pandas import DataFrame
import numpy as np
from nltk import word_tokenize
from functools import reduce
class HourOfDayTransformer(TransformerMixin):
def __init__(self, date_field=... | mit |
HBNLdev/DataStore | db/sas_tools.py | 1 | 2566 | ''' tools for working with .sas7bdat files '''
import os
from collections import OrderedDict
import pandas as pd
from sas7bdat import SAS7BDAT
from .knowledge.questionnaires import map_ph4, map_ph4_ssaga
map_subject = {'core': {'file_pfixes': []}}
parent_dir = '/processed_data/zork/zork-phase4-69/sessi... | gpl-3.0 |
saimn/astropy | astropy/visualization/wcsaxes/frame.py | 8 | 10649 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import abc
from collections import OrderedDict
import numpy as np
from matplotlib import rcParams
from matplotlib.lines import Line2D, Path
from matplotlib.patches import PathPatch
__all__ = ['RectangularFrame1D', 'Spine', 'BaseFrame', 'RectangularFr... | bsd-3-clause |
mne-tools/mne-tools.github.io | 0.11/_downloads/plot_evoked_topomap.py | 18 | 1498 | """
========================================
Plotting topographic maps of evoked data
========================================
Load evoked data and plot topomaps for selected time points.
"""
# Authors: Christian Brodbeck <christianbrodbeck@nyu.edu>
# Tal Linzen <linzen@nyu.edu>
# Denis A. Engeman <... | bsd-3-clause |
gracecox/MagPySV | magpysv/tests/test_tools.py | 2 | 1568 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 2 16:45:42 2017
Testing functions for tools.py.
@author: Grace Cox and Will Brown
"""
import unittest
import os
from .. import tools
import pandas as pd
import datetime as dt
class DataResamplingTestCase(unittest.TestCase):
"""Set up test case for data resampling"... | mit |
kaiserroll14/301finalproject | main/pandas/tseries/timedeltas.py | 9 | 3765 | """
timedelta support tools
"""
import re
import numpy as np
import pandas.tslib as tslib
from pandas import compat
from pandas.core.common import (ABCSeries, is_integer_dtype,
is_timedelta64_dtype, is_list_like,
isnull, _ensure_object, ABCIndexClass)
fro... | gpl-3.0 |
nikitasingh981/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 50 | 2378 | """
=====================================================================
Decision boundary of label propagation versus SVM on the Iris dataset
=====================================================================
Comparison for decision boundary generated on iris dataset
between Label Propagation and SVM.
This demon... | bsd-3-clause |
DongjunLee/kino-bot | kino/slack/plot.py | 1 | 2684 | from matplotlib import pyplot as plt
import matplotlib.dates as dt
import seaborn
seaborn.set()
import datetime
class Plot(object):
def __init__(self):
pass
def make_bar(
x,
y,
f_name,
title=None,
legend=None,
x_label=None,
y_label=None,
... | mit |
sylvchev/mdla | examples/example_benchmark_performance.py | 1 | 6309 | """Benchmarking dictionary learning algorithms on random dataset"""
from multiprocessing import cpu_count
from time import time
import matplotlib.pyplot as plt
import numpy as np
from numpy import array
from numpy.linalg import norm
from numpy.random import permutation, rand, randint, randn
from mdla import MiniBatc... | gpl-3.0 |
nkhuyu/blaze | blaze/compute/core.py | 5 | 14061 | from __future__ import absolute_import, division, print_function
import numbers
from datetime import date, datetime
import toolz
from toolz import first, concat, memoize, unique, assoc
import itertools
from collections import Iterator
from ..compatibility import basestring
from ..expr import Expr, Field, Symbol, symb... | bsd-3-clause |
cl4rke/scikit-learn | sklearn/svm/tests/test_sparse.py | 95 | 12156 | from nose.tools import assert_raises, assert_true, assert_false
import numpy as np
from scipy import sparse
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from sklearn import datasets, svm, linear_model, base
from sklearn.datasets import make_classif... | bsd-3-clause |
david-ragazzi/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/axes.py | 69 | 259904 | from __future__ import division, generators
import math, sys, warnings, datetime, new
import numpy as np
from numpy import ma
import matplotlib
rcParams = matplotlib.rcParams
import matplotlib.artist as martist
import matplotlib.axis as maxis
import matplotlib.cbook as cbook
import matplotlib.collections as mcoll
im... | gpl-3.0 |
cbertinato/pandas | pandas/tests/frame/test_duplicates.py | 1 | 14578 | import numpy as np
import pytest
from pandas import DataFrame, Series
import pandas.util.testing as tm
@pytest.mark.parametrize('subset', ['a', ['a'], ['a', 'B']])
def test_duplicated_with_misspelled_column_name(subset):
# GH 19730
df = DataFrame({'A': [0, 0, 1],
'B': [0, 0, 1],
... | bsd-3-clause |
fabioticconi/scikit-learn | benchmarks/bench_plot_lasso_path.py | 301 | 4003 | """Benchmarks of Lasso regularization path computation using Lars and CD
The input data is mostly low rank but is a fat infinite tail.
"""
from __future__ import print_function
from collections import defaultdict
import gc
import sys
from time import time
import numpy as np
from sklearn.linear_model import lars_pat... | bsd-3-clause |
FluidityProject/multifluids | tests/sloshing_tank/plot_freesurface.py | 5 | 2631 | #!/usr/bin/env python
import settings
import ana_sol
import sys
import math
import commands
import matplotlib.pyplot as plt
import getopt
from scipy.special import erf
from numpy import poly1d
from matplotlib.pyplot import figure, show
from numpy import pi, sin, linspace
from matplotlib.mlab import stineman_interp
... | lgpl-2.1 |
mupif/mupif | mupif/Field.py | 1 | 42683 | #
# MuPIF: Multi-Physics Integration Framework
# Copyright (C) 2010-2015 Borek Patzak
#
# Czech Technical University, Faculty of Civil Engineering,
# Department of Structural Mechanics, 166 29 Prague, Czech Republic
#
# This library is free software; you can redistribute it and/or
# modify i... | lgpl-3.0 |
miloharper/neural-network-animation | matplotlib/tests/test_ticker.py | 9 | 4261 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import nose.tools
from nose.tools import assert_raises
from numpy.testing import assert_almost_equal
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as m... | mit |
marionleborgne/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/contour.py | 69 | 42063 | """
These are classes to support contour plotting and
labelling for the axes class
"""
from __future__ import division
import warnings
import matplotlib as mpl
import numpy as np
from numpy import ma
import matplotlib._cntr as _cntr
import matplotlib.path as path
import matplotlib.ticker as ticker
import matplotlib.cm... | agpl-3.0 |
numenta/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/colorbar.py | 69 | 27260 | '''
Colorbar toolkit with two classes and a function:
:class:`ColorbarBase`
the base class with full colorbar drawing functionality.
It can be used as-is to make a colorbar for a given colormap;
a mappable object (e.g., image) is not needed.
:class:`Colorbar`
the derived class ... | agpl-3.0 |
NDManh/numbbo | code-postprocessing/bbob_pproc/comp2/pptable2.py | 3 | 20251 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""Rank-sum tests table on "Final Data Points".
That is, for example, using 1/#fevals(ftarget) if ftarget was reached
and -f_final otherwise as input for the rank-sum test, where obviously
the larger the better.
One table per function and dimension.
"""
from __future__... | bsd-3-clause |
Ziqi-Li/bknqgis | pandas/pandas/core/reshape/reshape.py | 1 | 45812 | # pylint: disable=E1101,E1103
# pylint: disable=W0703,W0622,W0613,W0201
from pandas.compat import range, zip
from pandas import compat
import itertools
import re
import numpy as np
from pandas.core.dtypes.common import (
_ensure_platform_int,
is_list_like, is_bool_dtype,
needs_i8_conversion)
from pandas.c... | gpl-2.0 |
winklerand/pandas | asv_bench/benchmarks/replace.py | 1 | 2171 | from .pandas_vb_common import *
class replace_fillna(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
try:
self.rng = date_range('1/1/2000', periods=self.N, freq='min')
except NameError:
self.rng = DatetimeIndex('1/1/2000', periods=self.N, offset=date... | bsd-3-clause |
mattpitkin/GraWIToNStatisticsLectures | figures/scripts/pvalue.py | 1 | 1242 | #!/usr/bin/env python
"""
Make plots showing how to calculate the p-value
"""
import matplotlib.pyplot as pl
from scipy.stats import norm
from scipy.special import erf
import numpy as np
mu = 0. # the mean, mu
sigma = 1. # standard deviation
x = np.linspace(-4, 4, 1000) # x
# set plot to render labels using latex
... | mit |
arcade-lab/tia-infrastructure | tools/simulator/system.py | 1 | 9352 | """
Top-level system wrapper.
"""
import re
import sys
import pandas as pd
from simulator.exception import SimulatorException
class System:
"""
A system class to wrap a collection of processing and memory elements as well as the channels through which they
communicate.
"""
def __init__(self):
... | mit |
gwpy/gwpy.github.io | docs/0.8.0/plotter/colors-1.py | 7 | 1123 | from __future__ import division
import numpy
from matplotlib import (pyplot, rcParams)
from matplotlib.colors import to_hex
from gwpy.plotter import colors
rcParams.update({
'text.usetex': False,
'font.size': 15
})
th = numpy.linspace(0, 2*numpy.pi, 512)
names = [
'gwpy:geo600',
'gwpy:kagra',
'... | gpl-3.0 |
karpeev/libmesh | doc/statistics/libmesh_citations.py | 1 | 2340 | #!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
# Number of "papers using libmesh" by year.
#
# Note 1: this does not count citations "only," the authors must have actually
# used libmesh in part of their work. Therefore, these counts do not include
# things like Wolfgang citing us in his pap... | lgpl-2.1 |
numenta/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/mlab.py | 69 | 104273 | """
Numerical python functions written for compatability with matlab(TM)
commands with the same names.
Matlab(TM) compatible functions
-------------------------------
:func:`cohere`
Coherence (normalized cross spectral density)
:func:`csd`
Cross spectral density uing Welch's average periodogram
:func:`detrend`... | agpl-3.0 |
RomainBrault/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 |
notkarol/banjin | experiment/python_word_matching_speed.py | 1 | 4650 | #!/usr/bin/python
# Takes in a dictionary of words
# Verifies that all functions return the same answers
# Generates random hands from the probability of getting tiles from the bunch
# Then prints out how long each function takes to find all matching words
# Generates various hand sizes to see if there's any scaling
... | mit |
PatrickOReilly/scikit-learn | examples/model_selection/plot_validation_curve.py | 141 | 1931 | """
==========================
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 |
DSLituiev/scikit-learn | sklearn/datasets/mldata.py | 309 | 7838 | """Automatically download MLdata datasets."""
# Copyright (c) 2011 Pietro Berkes
# License: BSD 3 clause
import os
from os.path import join, exists
import re
import numbers
try:
# Python 2
from urllib2 import HTTPError
from urllib2 import quote
from urllib2 import urlopen
except ImportError:
# Pyt... | bsd-3-clause |
mortonjt/scipy | scipy/signal/wavelets.py | 23 | 10483 | from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.dual import eig
from scipy.special import comb
from scipy import linspace, pi, exp
from scipy.signal import convolve
__all__ = ['daub', 'qmf', 'cascade', 'morlet', 'ricker', 'cwt']
def daub(p):
"""
The coefficient... | bsd-3-clause |
broadinstitute/cms | cms/power/power_func.py | 1 | 8625 | ## functions for analyzing empirical/simulated CMS output
## last updated 09.14.2017 vitti@broadinstitute.org
import matplotlib as mp
mp.use('agg')
import matplotlib.pyplot as plt
import numpy as np
import math
from scipy.stats import percentileofscore
###################
## DEFINE SCORES ##
###################
def... | bsd-2-clause |
vshtanko/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 |
tashaxe/Red-DiscordBot | lib/youtube_dl/extractor/wsj.py | 7 | 4311 | # coding: utf-8
from __future__ import unicode_literals
from .common import InfoExtractor
from ..utils import (
int_or_none,
float_or_none,
unified_strdate,
)
class WSJIE(InfoExtractor):
_VALID_URL = r'''(?x)
(?:
https?://video-api\.wsj\.com/api-vid... | gpl-3.0 |
DiCarloLab-Delft/PycQED_py3 | pycqed/utilities/pulse_scheme.py | 1 | 5469 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches
def new_pulse_fig(figsize):
'''
Open a new figure and configure it to plot pulse schemes.
'''
fig, ax = plt.subplots(1, 1, figsize=figsize, frameon=False)
ax.axis('off')
fig.subplots_adjust(bottom=0, top=1, left=0, ri... | mit |
florian-f/sklearn | examples/cluster/plot_dbscan.py | 3 | 2634 | # -*- 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 scipy.spatial import distance
from sklearn.cluster import DBSCAN
from s... | bsd-3-clause |
bthirion/nipy | examples/labs/need_data/localizer_glm_ar.py | 3 | 5428 | #!/usr/bin/env python
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
from __future__ import print_function # Python 2/3 compatibility
__doc__ = """
Full step-by-step example of fitting a GLM to experimental data and visualizing
the results.
More specif... | bsd-3-clause |
kiyoto/statsmodels | statsmodels/regression/_prediction.py | 27 | 6035 | # -*- coding: utf-8 -*-
"""
Created on Fri Dec 19 11:29:18 2014
Author: Josef Perktold
License: BSD-3
"""
import numpy as np
from scipy import stats
# this is similar to ContrastResults after t_test, partially copied and adjusted
class PredictionResults(object):
def __init__(self, predicted_mean, var_pred_mean... | bsd-3-clause |
kyleam/seaborn | examples/elaborate_violinplot.py | 30 | 1055 | """
Violinplot from a wide-form dataset
===================================
_thumb: .6, .45
"""
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")
# Load the example dataset of brain network correlations
df = sns.load_dataset("brain_networks", header=[0, 1, 2], index_col=0)
# Pull out a... | bsd-3-clause |
syagev/kaggle_dsb | luna16/src/conv_net/data.py | 1 | 2668 | from __future__ import division
import numpy as np
import os
import pickle
import glob
import Image
from skimage.io import imread
from sklearn.cross_validation import train_test_split
dataset_dir = "../../data/samples"
def load():
tps = glob.glob(dataset_dir+"/*true.jpg")
fps_2 = glob.glob(dataset_dir+"/*fal... | apache-2.0 |
phoebe-project/phoebe2-docs | 2.2/tutorials/irrad_method_horvat.py | 1 | 3005 | #!/usr/bin/env python
# coding: utf-8
# Lambert Scattering (irrad_method='horvat')
# ============================
#
# Setup
# -----------------------------
# Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't wa... | gpl-3.0 |
salazardetroya/libmesh | doc/statistics/libmesh_citations.py | 1 | 2340 | #!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
# Number of "papers using libmesh" by year.
#
# Note 1: this does not count citations "only," the authors must have actually
# used libmesh in part of their work. Therefore, these counts do not include
# things like Wolfgang citing us in his pap... | lgpl-2.1 |
CI-WATER/TethysCluster | utils/scimage_12_04.py | 2 | 17224 | #!/usr/bin/env python
"""
This script is meant to be run inside of a ubuntu cloud image available at
uec-images.ubuntu.com::
$ EC2_UBUNTU_IMG_URL=http://uec-images.ubuntu.com/precise/current
$ wget $EC2_UBUNTU_IMG_URL/precise-server-cloudimg-amd64.tar.gz
or::
$ wget $EC2_UBUNTU_IMG_URL/precise-server-clo... | gpl-3.0 |
Brett777/Predict-Churn | model_management/datascience_framework.py | 1 | 8515 | import os
import io
import sys
import dill
import copy
from datetime import datetime
from .evaluator import Evaluator
from .utils import (
post_to_platform,
get_current_notebook,
strip_output,
get_current_notebook,
mkdir_p,
)
class DataScienceFramework(object):
def __init__(
self,
... | mit |
kristohr/pybayenv2 | pybayenv/compute_average_bf.py | 1 | 4066 | #!/usr/bin/python
import sys, string, re, os, commands, time, math
#from scipy import stats
#import scipy as sp
import numpy as np
#import matplotlib as mpl
#from matplotlib import pyplot as plt
class SNP:
def __init__(self, name, num_env, t):
self.name = name
self.num_env = [F... | bsd-3-clause |
liyu1990/sklearn | sklearn/cluster/tests/test_hierarchical.py | 230 | 19795 | """
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 |
davidgardenier/frbpoppy | tests/dm_snr/future.py | 1 | 6523 | """Check the log N log F slope for future surveys."""
import numpy as np
import matplotlib.pyplot as plt
from copy import copy
from frbpoppy import CosmicPopulation, Survey, LargePopulation, SurveyPopulation, hist
from frbpoppy import unpickle, pprint
import frbpoppy.direction_dists as did
import frbpoppy.galacticops ... | mit |
tu-rbo/differentiable-particle-filters | methods/dpf_kitti.py | 1 | 43029 | import os
import numpy as np
import sonnet as snt
import tensorflow as tf
import matplotlib.pyplot as plt
from utils.data_utils_kitti import wrap_angle, compute_statistics, split_data, make_batch_iterator, make_repeating_batch_iterator, rotation_matrix, load_data_for_stats
from utils.method_utils import atan2, compute... | mit |
kc-lab/dms2dfe | dms2dfe/lib/io_ml.py | 2 | 24058 | #!usr/bin/python
# Copyright 2016, Rohan Dandage <rraadd_8@hotmail.com,rohan@igib.in>
# This program is distributed under General Public License v. 3.
"""
================================
``io_ml``
================================
"""
from os.path import abspath,dirname,exists,basename
from os import makedirs
from ... | gpl-3.0 |
mjgrav2001/scikit-learn | sklearn/neighbors/graph.py | 208 | 7031 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
import warnings
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def _check_params(X, metric, p, metric_... | bsd-3-clause |
russel1237/scikit-learn | examples/plot_digits_pipe.py | 250 | 1809 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Pipelining: chaining a PCA and a logistic regression
=========================================================
The PCA does an unsupervised dimensionality reduction, while the logistic
regression does the predictio... | bsd-3-clause |
SepehrMN/nest-simulator | pynest/examples/spatial/connex_ew.py | 14 | 2269 | # -*- coding: utf-8 -*-
#
# connex_ew.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 |
alexeyum/scikit-learn | sklearn/datasets/base.py | 11 | 23497 | """
Base IO code for all datasets
"""
# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
# 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
# 2010 Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD 3 clause
import os
import csv
import sys
import shutil
from os import environ... | bsd-3-clause |
tdhopper/scikit-learn | sklearn/manifold/tests/test_mds.py | 324 | 1862 | import numpy as np
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_raises
from sklearn.manifold import mds
def test_smacof():
# test metric smacof using the data of "Modern Multidimensional Scaling",
# Borg & Groenen, p 154
sim = np.array([[0, 5, 3, 4],
... | bsd-3-clause |
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