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 |
|---|---|---|---|---|---|
weidel-p/nest-simulator | pynest/examples/sinusoidal_gamma_generator.py | 5 | 12680 | # -*- coding: utf-8 -*-
#
# sinusoidal_gamma_generator.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 ... | gpl-2.0 |
elkingtonmcb/h2o-2 | py/testdir_single_jvm/test_summary2_unifiles.py | 9 | 10223 | import unittest, time, sys, random, math, getpass
sys.path.extend(['.','..','../..','py'])
import h2o, h2o_cmd, h2o_import as h2i, h2o_util, h2o_browse as h2b, h2o_print as h2p
import h2o_summ
DO_TRY_SCIPY = False
if getpass.getuser()=='kevin' or getpass.getuser()=='jenkins':
DO_TRY_SCIPY = True
DO_MEDIAN = True
... | apache-2.0 |
pli1988/portfolioFactory | portfolioFactory/utils/utils.py | 1 | 3534 | # -*- coding: utf-8 -*-
"""
Created on Mon Dec 8 22:09:49 2014
Author: Peter Li and Israel
"""
import numpy as np
from . import customExceptions
from .customExceptions import *
import pandas as pd
def processData(data):
""" Function to process timeseries data
processData performs 2 steps:
- che... | mit |
jjhelmus/wradlib | examples/histo_cut_example.py | 1 | 2258 | # -*- coding: iso-8859-1 -*-
# -------------------------------------------------------------------------------
# Name: module1
# Purpose:
# Author: jacobi
# Created: 05.04.2011
# -------------------------------------------------------------------------------
#!/usr/bin/env python
import wradli... | mit |
grlee77/scipy | scipy/optimize/minpack.py | 2 | 34805 | import warnings
from . import _minpack
import numpy as np
from numpy import (atleast_1d, dot, take, triu, shape, eye,
transpose, zeros, prod, greater,
asarray, inf,
finfo, inexact, issubdtype, dtype)
from scipy.linalg import svd, cholesky, solve_triangular, LinA... | bsd-3-clause |
boada/ICD | sandbox/plot_snippets/heatmap_ex.py | 1 | 1211 | #!/usr/bin/env python
# File: heatmap_ex.py
# Created on: Tue 07 Aug 2012 01:48:35 PM CDT
# Last Change: Tue 07 Aug 2012 02:06:20 PM CDT
# Purpose of script: <+INSERT+>
# Author: Steven Boada
from matplotlib import pyplot as PLT
from matplotlib import cm as CM
from matplotlib import mlab as ML
import numpy as NP
impor... | mit |
shangwuhencc/scikit-learn | examples/mixture/plot_gmm_selection.py | 248 | 3223 | """
=================================
Gaussian Mixture Model Selection
=================================
This example shows that model selection can be performed with
Gaussian Mixture Models using information-theoretic criteria (BIC).
Model selection concerns both the covariance type
and the number of components in th... | bsd-3-clause |
dsquareindia/scikit-learn | sklearn/linear_model/least_angle.py | 15 | 57631 | """
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 |
wlamond/scikit-learn | examples/cluster/plot_cluster_iris.py | 350 | 2593 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
K-means Clustering
=========================================================
The plots display firstly what a K-means algorithm would yield
using three clusters. It is then shown what the effect of a bad
initializa... | bsd-3-clause |
Denisolt/Tensorflow_Chat_Bot | local/lib/python2.7/site-packages/numpy/lib/recfunctions.py | 148 | 35012 | """
Collection of utilities to manipulate structured arrays.
Most of these functions were initially implemented by John Hunter for
matplotlib. They have been rewritten and extended for convenience.
"""
from __future__ import division, absolute_import, print_function
import sys
import itertools
import numpy as np
im... | gpl-3.0 |
iismd17/scikit-learn | sklearn/linear_model/passive_aggressive.py | 97 | 10879 | # Authors: Rob Zinkov, Mathieu Blondel
# License: BSD 3 clause
from .stochastic_gradient import BaseSGDClassifier
from .stochastic_gradient import BaseSGDRegressor
from .stochastic_gradient import DEFAULT_EPSILON
class PassiveAggressiveClassifier(BaseSGDClassifier):
"""Passive Aggressive Classifier
Read mor... | bsd-3-clause |
Vimos/scikit-learn | sklearn/datasets/base.py | 4 | 28293 | """
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 |
madjelan/scikit-learn | sklearn/covariance/tests/test_graph_lasso.py | 272 | 5245 | """ Test the graph_lasso module.
"""
import sys
import numpy as np
from scipy import linalg
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_less
from sklearn.covariance import (graph_lasso, GraphLasso, GraphLassoCV,
empirical_... | bsd-3-clause |
GrimDerp/numpy | numpy/linalg/linalg.py | 31 | 75612 | """Lite version of scipy.linalg.
Notes
-----
This module is a lite version of the linalg.py module in SciPy which
contains high-level Python interface to the LAPACK library. The lite
version only accesses the following LAPACK functions: dgesv, zgesv,
dgeev, zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetr... | bsd-3-clause |
ryfeus/lambda-packs | pytorch/source/numpy/core/function_base.py | 3 | 16336 | from __future__ import division, absolute_import, print_function
import functools
import warnings
import operator
from . import numeric as _nx
from .numeric import (result_type, NaN, shares_memory, MAY_SHARE_BOUNDS,
TooHardError, asanyarray)
from numpy.core.multiarray import add_docstring
from n... | mit |
tornadomeet/mxnet | example/deep-embedded-clustering/data.py | 16 | 1384 | # 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 |
lbishal/scikit-learn | sklearn/gaussian_process/tests/test_gpr.py | 28 | 11870 | """Testing for Gaussian process regression """
# Author: Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Licence: BSD 3 clause
import numpy as np
from scipy.optimize import approx_fprime
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels \
import RBF, Constan... | bsd-3-clause |
eredmiles/Fraud-Corruption-Detection-Data-Science-Pipeline-DSSG2015 | WorldBank2015/Code/data_pipeline_src/contracts_feature_gen.py | 2 | 7030 | #feature generation script for contracts
#Emily Grace and Elissa Redmiles
import pandas as pd
import argparse
import datetime as dt
import numpy as np
from matplotlib import pyplot as plt
import currency
#arguments section
# inputs are:
# -f name of file to clean
# -p name of the column containing "procurement method... | mit |
ericxk/MachineLearningExercise | ML_in_action/chapter7/adaboost.py | 1 | 6050 | from numpy import *
def loadSimpData():
datMat = matrix([[ 1. , 2.1],
[ 2. , 1.1],
[ 1.3, 1. ],
[ 1. , 1. ],
[ 2. , 1. ]])
classLabels = [1.0, 1.0, -1.0, -1.0, 1.0]
return datMat,classLabels
##通过阈值比较对数据进行分类，在阈值一边的数据会分到类别-1，其中lt是小于等于
def stumpClassify(dataM... | mit |
sergiy-evision/math-algorithms | sf-crime/main.py | 1 | 3238 | from __future__ import division
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.cross_validation import KFold
from sklearn.cross_validation import cross_val_score
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ens... | mit |
meduz/scikit-learn | sklearn/linear_model/coordinate_descent.py | 4 | 81531 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Gael Varoquaux <gael.varoquaux@inria.fr>
#
# License: BSD 3 clause
import sys
import warnings
from abc import ABCMeta, abstractmethod
import n... | bsd-3-clause |
PKU-ComNet/school-fiesta | schools/test_main_page_externals.py | 1 | 1835 | #!/usr/bin/env python
"""
Find all external links in the main page with 3 layers or above
Also draw a network diagram
"""
import util
import networkx as nx # draw diagram
import matplotlib.pyplot as plt
from Queue import Queue
if __name__ == '__main__':
cs_depart_urls = [
'http://www.cs.ucla.edu/graduat... | apache-2.0 |
mmottahedi/neuralnilm_prototype | scripts/e321.py | 2 | 6279 | 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,
Bidirectio... | mit |
judithfan/pix2svg | generative/tests/compare_test/sketch_unroll/rdm_sketch.py | 1 | 3736 | from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import os
import sys
import json
import numpy as np
from tqdm import tqdm
from collections import defaultdict
import torch
import torch.nn.functional as F
from torch.autograd import Variable
from dataset_sket... | mit |
mxjl620/scikit-learn | examples/linear_model/plot_ols_ridge_variance.py | 387 | 2060 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Ordinary Least Squares and Ridge Regression Variance
=========================================================
Due to the few points in each dimension and the straight
line that linear regression uses to follow thes... | bsd-3-clause |
HeraclesHX/scikit-learn | examples/neighbors/plot_digits_kde_sampling.py | 251 | 2022 | """
=========================
Kernel Density Estimation
=========================
This example shows how kernel density estimation (KDE), a powerful
non-parametric density estimation technique, can be used to learn
a generative model for a dataset. With this generative model in place,
new samples can be drawn. These... | bsd-3-clause |
Ziqi-Li/bknqgis | pandas/pandas/tests/io/parser/header.py | 4 | 9794 | # -*- coding: utf-8 -*-
"""
Tests that the file header is properly handled or inferred
during parsing for all of the parsers defined in parsers.py
"""
import pytest
import numpy as np
import pandas.util.testing as tm
from pandas import DataFrame, Index, MultiIndex
from pandas.compat import StringIO, lrange, u
cla... | gpl-2.0 |
TinghuiWang/ActivityLearning | examples/mnist_sda/mnist_sda_sgd.py | 1 | 4377 | from actlearn.data.mnist import *
from actlearn.models.StackedDenoisingAutoencoder import StackedDenoisingAutoencoder
from actlearn.utils.tile_image import tile_image
from actlearn.utils.confusion_matrix import get_confusion_matrix
from actlearn.utils.classifier_performance import get_performance_array, performance_ind... | bsd-3-clause |
davidgbe/scikit-learn | sklearn/metrics/regression.py | 175 | 16953 | """Metrics to assess performance on regression task
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Ma... | bsd-3-clause |
selective-inference/selective-inference | doc/learning_examples/standalone/cleaner_basic_example.py | 3 | 2625 | import numpy as np
from selection.learning.core import (infer_general_target,
normal_sampler,
logit_fit,
probit_fit)
def simulate(n=100):
# description of statistical problem
truth = np.array([2. , -2.]) / ... | bsd-3-clause |
zhoulingjun/zipline | tests/modelling/test_modelling_algo.py | 9 | 7105 | """
Tests for Algorithms running the full FFC stack.
"""
from unittest import TestCase
from os.path import (
dirname,
join,
realpath,
)
from numpy import (
array,
full_like,
nan,
)
from numpy.testing import assert_almost_equal
from pandas import (
concat,
DataFrame,
DatetimeIndex,
... | apache-2.0 |
yandexdataschool/Practical_RL | week04_[recap]_deep_learning/notmnist.py | 1 | 1778 | import os
from glob import glob
import numpy as np
from imageio import imread
from skimage.transform import resize
from sklearn.model_selection import train_test_split
def load_notmnist(path='./notMNIST_small', letters='ABCDEFGHIJ',
img_shape=(28, 28), test_size=0.25, one_hot=False):
# download... | unlicense |
wathen/PhD | MHD/FEniCS/MHD/Stabilised/SaddlePointForm/Test/GeneralisedEigen/NoBC/MHDfluid.py | 1 | 12468 |
import petsc4py
import sys
petsc4py.init(sys.argv)
from petsc4py import PETSc
Print = PETSc.Sys.Print
from dolfin import *
# from MatrixOperations import *
import numpy as np
#import matplotlib.pylab as plt
import PETScIO as IO
import common
import scipy
import scipy.io
import time
import BiLinear as forms
import... | mit |
zhenv5/scikit-learn | sklearn/feature_extraction/hashing.py | 183 | 6155 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: BSD 3 clause
import numbers
import numpy as np
import scipy.sparse as sp
from . import _hashing
from ..base import BaseEstimator, TransformerMixin
def _iteritems(d):
"""Like d.iteritems, but accepts any collections.Mapping."""
return d.iteritems() if... | bsd-3-clause |
zuku1985/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 |
petrosgk/Kaggle-Carvana-Image-Masking-Challenge | test_submit.py | 1 | 1793 | import cv2
import numpy as np
import pandas as pd
from tqdm import tqdm
import params
input_size = params.input_size
batch_size = params.batch_size
orig_width = params.orig_width
orig_height = params.orig_height
threshold = params.threshold
model = params.model_factory()
df_test = pd.read_csv('input/sample_submissio... | mit |
wesleyegberto/courses-projects | ia/machine-learning-sklearn-classificacao/1_classificacao_animais.py | 1 | 1069 | # -*- coding: utf-8 -*-
"""
Introdução a Machine Learning e Classificação - 1
"""
# features (1 sim, 0 não)
# pelo longo?
# perna curta?
# faz auau?
porco1 = [0, 1, 0]
porco2 = [0, 1, 1]
porco3 = [1, 1, 0]
cachorro1 = [0, 1, 1]
cachorro2 = [1, 0, 1]
cachorro3 = [1, 1, 1]
# 1 => porco, 0 => cachorro
treino_x = [porco1... | apache-2.0 |
TomAugspurger/pandas | pandas/core/arrays/sparse/scipy_sparse.py | 1 | 5381 | """
Interaction with scipy.sparse matrices.
Currently only includes to_coo helpers.
"""
from pandas.core.indexes.api import Index, MultiIndex
from pandas.core.series import Series
def _check_is_partition(parts, whole):
whole = set(whole)
parts = [set(x) for x in parts]
if set.intersection(*parts) != set(... | bsd-3-clause |
mjudsp/Tsallis | examples/applications/plot_out_of_core_classification.py | 32 | 13829 | """
======================================================
Out-of-core classification of text documents
======================================================
This is an example showing how scikit-learn can be used for classification
using an out-of-core approach: learning from data that doesn't fit into main
memory. ... | bsd-3-clause |
rahuldhote/scikit-learn | sklearn/semi_supervised/label_propagation.py | 128 | 15312 | # coding=utf8
"""
Label propagation in the context of this module refers to a set of
semisupervised classification algorithms. In the high level, these algorithms
work by forming a fully-connected graph between all points given and solving
for the steady-state distribution of labels at each point.
These algorithms per... | bsd-3-clause |
anirudhjayaraman/scikit-learn | examples/ensemble/plot_partial_dependence.py | 249 | 4456 | """
========================
Partial Dependence Plots
========================
Partial dependence plots show the dependence between the target function [1]_
and a set of 'target' features, marginalizing over the
values of all other features (the complement features). Due to the limits
of human perception the size of t... | bsd-3-clause |
woodem/woo | examples/old/concrete/uniax.py | 1 | 8050 | #!/usr/bin/python
# -*- coding: utf-8 -*-
from woo import utils,plot,pack,timing,eudoxos
import time, sys, os, copy
#import matplotlib
#matplotlib.rc('text',usetex=True)
#matplotlib.rc('text.latex',preamble=r'\usepackage{concrete}\usepackage{euler}')
"""
A fairly complex script performing uniaxial tension-compress... | gpl-2.0 |
h2educ/scikit-learn | sklearn/metrics/scorer.py | 211 | 13141 | """
The :mod:`sklearn.metrics.scorer` submodule implements a flexible
interface for model selection and evaluation using
arbitrary score functions.
A scorer object is a callable that can be passed to
:class:`sklearn.grid_search.GridSearchCV` or
:func:`sklearn.cross_validation.cross_val_score` as the ``scoring`` parame... | bsd-3-clause |
datapythonista/pandas | pandas/io/formats/csvs.py | 2 | 10077 | """
Module for formatting output data into CSV files.
"""
from __future__ import annotations
import csv as csvlib
import os
from typing import (
TYPE_CHECKING,
Any,
Hashable,
Iterator,
Sequence,
cast,
)
import numpy as np
from pandas._libs import writers as libwriters
from pandas._typing imp... | bsd-3-clause |
techmuch/jupyter-handsontables | handsontablesjs/__init__.py | 2 | 6095 | import json
import numpy as np
import pandas as pd
try:
# prefer Jupyter (i.e. IPyhton 4.x)
from traitlets import (
Instance,
Unicode,
)
from ipywidgets import widgets
except ImportError:
from IPython.utils.traitlets import (
Instance,
Unicode,
)
from IP... | mit |
ky822/scikit-learn | sklearn/covariance/tests/test_covariance.py | 69 | 11116 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_alm... | bsd-3-clause |
luo66/scikit-learn | sklearn/tests/test_naive_bayes.py | 70 | 17509 | import pickle
from io import BytesIO
import numpy as np
import scipy.sparse
from sklearn.datasets import load_digits, load_iris
from sklearn.cross_validation import cross_val_score, train_test_split
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.te... | bsd-3-clause |
lenovor/scikit-learn | sklearn/utils/multiclass.py | 92 | 13986 | # Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
#
# License: BSD 3 clause
"""
Multi-class / multi-label utility function
==========================================
"""
from __future__ import division
from collections import Sequence
from itertools import chain
import warnings
from scipy.sparse import issparse
fro... | bsd-3-clause |
lukaspetr/FEniCSopt | supg_anisotrop.py | 1 | 1713 | from dolfin import *
from scipy.optimize import minimize
import numpy as np
import time as pyt
import pprint
import matplotlib.pyplot as plt
coth = lambda x: 1./np.tanh(x)
from fenicsopt.core.convdif import *
from fenicsopt.examples.sc_examples import sc_setup
import fenicsopt.exports.results as rs
##################... | mit |
rs2/pandas | pandas/tests/util/test_hashing.py | 2 | 10860 | import numpy as np
import pytest
import pandas as pd
from pandas import DataFrame, Index, MultiIndex, Series
import pandas._testing as tm
from pandas.core.util.hashing import hash_tuples
from pandas.util import hash_array, hash_pandas_object
@pytest.fixture(
params=[
Series([1, 2, 3] * 3, dtype="int32"),... | bsd-3-clause |
xiaoxiamii/scikit-learn | examples/linear_model/plot_ols_ridge_variance.py | 387 | 2060 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Ordinary Least Squares and Ridge Regression Variance
=========================================================
Due to the few points in each dimension and the straight
line that linear regression uses to follow thes... | bsd-3-clause |
belltailjp/scikit-learn | examples/cluster/plot_kmeans_stability_low_dim_dense.py | 338 | 4324 | """
============================================================
Empirical evaluation of the impact of k-means initialization
============================================================
Evaluate the ability of k-means initializations strategies to make
the algorithm convergence robust as measured by the relative stan... | bsd-3-clause |
ilo10/scikit-learn | examples/neighbors/plot_species_kde.py | 282 | 4059 | """
================================================
Kernel Density Estimate of Species Distributions
================================================
This shows an example of a neighbors-based query (in particular a kernel
density estimate) on geospatial data, using a Ball Tree built upon the
Haversine distance metric... | bsd-3-clause |
ntim/g4sipm | sample/plots/luigi/dynamic_range_compare.py | 1 | 5235 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import os, sys, glob
import numpy as np
import sqlite3
import matplotlib.pyplot as plt
import pickle
from contrib import histogram
parser = argparse.ArgumentParser()
parser.add_argument("path", help="the path to the luigi simulation results directory conta... | gpl-3.0 |
mne-tools/mne-tools.github.io | 0.16/_downloads/plot_mne_inverse_connectivity_spectrum.py | 8 | 3468 | """
==============================================================
Compute full spectrum source space connectivity between labels
==============================================================
The connectivity is computed between 4 labels across the spectrum
between 7.5 and 40 Hz.
"""
# Authors: Alexandre Gramfort <al... | bsd-3-clause |
xavierwu/scikit-learn | sklearn/tree/tests/test_tree.py | 11 | 48140 | """
Testing for the tree module (sklearn.tree).
"""
import pickle
from functools import partial
from itertools import product
import platform
import numpy as np
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from sklearn.random_projection import sparse_rand... | bsd-3-clause |
zedyang/oaForex | oanda.py | 2 | 6345 | import requests
import pandas as pd
from utils import update_datetime
from statics import API_NAME_OANDA_PRACTICE
from statics import PARAMS_NAME_OANDA_ACC, PARAMS_NAME_OANDA_COUNT, \
PARAMS_NAME_OANDA_END, PARAMS_NAME_OANDA_START, PARAMS_NAME_OANDA_D_ALIGN, \
PARAMS_NAME_OANDA_W_ALIGN, PARAMS_NAME_OANDA_INSTRU... | mit |
h2oai/h2o-3 | h2o-py/h2o/estimators/estimator_base.py | 2 | 27083 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
#
# Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
#
from __future__ import absolute_import, division, print_function, unicode_literals
from h2o.utils.compatibility import * # NOQA
from datetime import datetime
import inspect
import warning... | apache-2.0 |
joelvbernier/hexrd-sandbox | multipanel_ff/dexela_scripts/findorientations.py | 1 | 10116 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 22 19:04:10 2017
@author: bernier2
"""
from __future__ import print_function
import os
import glob
import multiprocessing
import numpy as np
from scipy import ndimage
import timeit
try:
import dill as cpl
except(ImportError):
import c... | gpl-3.0 |
CKehl/pylearn2 | pylearn2/expr/tests/test_probabilistic_max_pooling.py | 44 | 24662 | from __future__ import print_function
import numpy as np
import warnings
from theano.compat.six.moves import xrange
from theano import config
from theano import function
import theano.tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams
from pylearn2.expr.probabilistic_max_pooling import max_pool_python
... | bsd-3-clause |
doyubkim/fluid-engine-dev | src/examples/python_examples/apic_example01.py | 1 | 1798 | #!/usr/bin/env python
"""
Copyright (c) 2018 Doyub Kim
I am making my contributions/submissions to this project solely in my personal
capacity and am not conveying any rights to any intellectual property of any
third parties.
"""
from pyjet import *
import numpy as np
import matplotlib.pyplot as plt
import matplotli... | mit |
nolanliou/tensorflow | tensorflow/contrib/timeseries/examples/known_anomaly.py | 53 | 6786 | # 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 |
FluidityProject/fluidity | examples/restratification_after_oodc/plot_mixing_stats.py | 6 | 2455 | import fluidity_tools
import pylab
from matplotlib.pyplot import *
subplot(121)
labels=['0<= T <0.1', '0.1<= T <0.2', '0.2<= T <0.3', '0.3<= T <0.4', '0.4<= T <0.5', '0.5<= T <0.6', '0.6<= T <0.7', '0.7<= T <0.8', '0.8<= T <0.9', '0.9<= T < 1.0', '1.0<= T < 1.1', '1.1<= T <1.2', '1.2<= T <1.3', '1.3<= T <1.4', '1.4<=... | lgpl-2.1 |
michaelaye/pyciss | pyciss/meta.py | 1 | 2895 | """This module deals with the metadata I have received from collaborators.
It defines the location of ring resonances for the RingCube plotting.
"""
import pandas as pd
import pkg_resources as pr
def get_order(name):
ratio = name.split()[1]
a, b = ratio.split(":")
return int(a) - int(b)
def get_resonan... | isc |
xiaoxiamii/scikit-learn | sklearn/utils/graph.py | 289 | 6239 | """
Graph utilities and algorithms
Graphs are represented with their adjacency matrices, preferably using
sparse matrices.
"""
# Authors: Aric Hagberg <hagberg@lanl.gov>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Jake Vanderplas <vanderplas@astro.washington.edu>
# License: BSD 3 clause
impo... | bsd-3-clause |
anilmuthineni/tensorflow | tensorflow/tools/dist_test/python/census_widendeep.py | 54 | 11900 | # 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 |
gviejo/ThalamusPhysio | python/main_test_mutual_information.py | 1 | 13015 | import ternary
import numpy as np
import pandas as pd
from functions import *
import sys
from functools import reduce
from sklearn.manifold import *
from sklearn.cluster import *
from pylab import *
import _pickle as cPickle
from skimage.filters import gaussian
#########################################################... | gpl-3.0 |
demianw/dipy | dipy/viz/tests/test_fvtk.py | 8 | 2879 | """ Testing vizualization with fvtk
"""
import numpy as np
from dipy.viz import fvtk
from dipy import data
import numpy.testing as npt
@npt.dec.skipif(not fvtk.have_vtk)
@npt.dec.skipif(not fvtk.have_vtk_colors)
def test_fvtk_functions():
# Create a renderer
r = fvtk.ren()
# Create 2 lines with 2 diff... | bsd-3-clause |
vital-ai/beaker-notebook | plugin/ipythonPlugins/src/dist/python3/beaker_runtime3.py | 1 | 19742 | # Copyright 2014 TWO SIGMA OPEN SOURCE, LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... | apache-2.0 |
xavierwu/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 234 | 12267 | # Authors: Lars Buitinck
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from array import array
from collections import Mapping
from operator import itemgetter
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..ext... | bsd-3-clause |
tdhoang0412/python-class | Monday_2017-04-24/code/bessel_recursion.py | 1 | 1278 | # Verification of scipys Bessel function implementation
# - recursion relation
import scipy.special as ss
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
# for nicer plots, make fonts larger and lines thicker
matplotlib.rcParams['font.size'] = 12
matplotlib.rcParams['axes.linewidth'] = 2.0
# No... | gpl-3.0 |
patverga/torch-relation-extraction | bin/analysis/plot-sent-len-bar.py | 1 | 1198 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.colors
import sys
matplotlib.rc('text', usetex=True)
fontsize = 22
font = {'family' : 'serif',
'serif' : 'Times Roman',
'size' : fontsize}
matplotlib.rc('font', **font)
output_dir = "doc/naacl201... | mit |
hrjn/scikit-learn | sklearn/decomposition/tests/test_pca.py | 12 | 21107 | import numpy as np
import scipy as sp
from itertools import product
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_gre... | bsd-3-clause |
adammenges/statsmodels | statsmodels/tsa/statespace/tools.py | 19 | 12762 | """
Statespace Tools
Author: Chad Fulton
License: Simplified-BSD
"""
from __future__ import division, absolute_import, print_function
import numpy as np
from statsmodels.tools.data import _is_using_pandas
from . import _statespace
try:
from scipy.linalg.blas import find_best_blas_type
except ImportError: # prag... | bsd-3-clause |
xubenben/scikit-learn | sklearn/tests/test_metaestimators.py | 226 | 4954 | """Common tests for metaestimators"""
import functools
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.externals.six import iterkeys
from sklearn.datasets import make_classification
from sklearn.utils.testing import assert_true, assert_false, assert_raises
from sklearn.pipeline import Pipeline... | bsd-3-clause |
Yllescas/OCR | OCR.py | 1 | 43143 | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 8 14:47:42 2016
@author: MAQUINA-03
"""
import os #Aquí se importa el objeto para recorrer las carpetas
import matplotlib.image as mpimg #Este objeto se importa para recorrer los archivos
import csv #Esté es e... | gpl-3.0 |
bthirion/scikit-learn | examples/svm/plot_svm_nonlinear.py | 62 | 1119 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learned by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn imp... | bsd-3-clause |
mattilyra/scikit-learn | benchmarks/bench_plot_parallel_pairwise.py | 127 | 1270 | # Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD 3 clause
import time
import matplotlib.pyplot as plt
from sklearn.utils import check_random_state
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.metrics.pairwise import pairwise_kernels
def plot(func):
random_state = check_rand... | bsd-3-clause |
platinhom/ManualHom | Coding/Python/scipy-html-0.16.1/generated/scipy-signal-filtfilt-1.py | 1 | 2375 | # The examples will use several functions from `scipy.signal`.
from scipy import signal
import matplotlib.pyplot as plt
# First we create a one second signal that is the sum of two pure sine
# waves, with frequencies 5 Hz and 250 Hz, sampled at 2000 Hz.
t = np.linspace(0, 1.0, 2001)
xlow = np.sin(2 * np.pi * 5 * t)
... | gpl-2.0 |
karstenw/nodebox-pyobjc | examples/Extended Application/sklearn/examples/model_selection/plot_randomized_search.py | 47 | 3287 | """
=========================================================================
Comparing randomized search and grid search for hyperparameter estimation
=========================================================================
Compare randomized search and grid search for optimizing hyperparameters of a
random forest.
... | mit |
cbmoore/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 |
procoder317/scikit-learn | sklearn/ensemble/tests/test_weight_boosting.py | 83 | 17276 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_array_equal, assert_array_less
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal, assert_true
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
Midafi/scikit-image | doc/examples/plot_shapes.py | 22 | 1913 | """
======
Shapes
======
This example shows how to draw several different shapes:
- line
- Bezier curve
- polygon
- circle
- ellipse
Anti-aliased drawing for:
- line
- circle
"""
import math
import numpy as np
import matplotlib.pyplot as plt
from skimage.draw import (line, polygon, circle,
... | bsd-3-clause |
Hiyorimi/scikit-image | doc/examples/features_detection/plot_orb.py | 33 | 1807 | """
==========================================
ORB feature detector and binary descriptor
==========================================
This example demonstrates the ORB feature detection and binary description
algorithm. It uses an oriented FAST detection method and the rotated BRIEF
descriptors.
Unlike BRIEF, ORB is c... | bsd-3-clause |
ethertricity/bluesky | check.py | 1 | 4049 | #!/usr/bin/python
from __future__ import print_function
import traceback
print("This script checks the availability of the libraries required by BlueSky, and the capabilities of your system.")
print()
np = sp = mpl = qt = gl = glhw = pg = False
# Basic libraries
print("Checking for numpy ", end=' ')
try:
... | gpl-3.0 |
longyangking/ML | tensorflow/pde.py | 1 | 1666 | import tensorflow as tf
import numpy as np
#import PIL.Image
#from io import StringIO
#from IPython.display import clear_output, Image, display
import matplotlib.pyplot as plt
#def DisplayArray(a,fmt='jpeg',rng=[0,1]):
# a = (a - rng[0])/float(rng[1] - rng[0])*255
# a = np.uint8(np.clip(a,0,255))
# f = St... | lgpl-3.0 |
Widukind/dlstats | dlstats/fetchers/esri.py | 1 | 26324 | # -*- coding: utf-8 -*-
"""
Created on Fri Oct 16 10:59:20 2015
@author: salimeh
"""
import time
from datetime import datetime
from urllib.parse import urljoin
import logging
import re
import pandas
from lxml import etree
import requests
from dlstats.utils import Downloader, get_ordinal_from_period, make_store_path... | agpl-3.0 |
aabadie/scikit-learn | examples/feature_selection/plot_permutation_test_for_classification.py | 94 | 2264 | """
=================================================================
Test with permutations the significance of a classification score
=================================================================
In order to test if a classification score is significative a technique
in repeating the classification procedure aft... | bsd-3-clause |
tsilifis/chaos_basispy | demos/demos_quad/poly_quad_CC.py | 1 | 1248 | import numpy as np
import scipy.stats as st
import matplotlib.pyplot as plt
import chaos_basispy as cb
def f(xi, a, b, c, W):
assert xi.shape[0] == 10
assert W.shape[0] == 10
return a + b * np.dot(W.T, xi) + c * np.dot(xi.reshape(1,xi.shape[0]), np.dot(np.dot(W, W.T) , xi))
dim = 10
np.random.seed(1234... | gpl-3.0 |
tapomayukh/projects_in_python | sandbox_tapo/src/skin_related/BMED_8813_HAP/Features/single_feature/best_kNN_PC/cross_validate_categories_kNN_PC_BMED_8813_HAP_scaled_method_II_shape.py | 1 | 4446 |
# Principal Component Analysis Code :
from numpy import mean,cov,double,cumsum,dot,linalg,array,rank,size,flipud
from pylab import *
import numpy as np
import matplotlib.pyplot as pp
#from enthought.mayavi import mlab
import scipy.ndimage as ni
import roslib; roslib.load_manifest('sandbox_tapo_darpa_m3')
import ro... | mit |
gpetretto/pymatgen | pymatgen/apps/battery/plotter.py | 9 | 3443 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
from __future__ import division, unicode_literals
"""
This module provides plotting capabilities for battery related applications.
"""
__author__ = "Shyue Ping Ong"
__copyright__ = "Copyright 2012, The Mater... | mit |
runt18/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/projections/polar.py | 1 | 21012 | import math
import numpy as npy
import matplotlib
rcParams = matplotlib.rcParams
from matplotlib.artist import kwdocd
from matplotlib.axes import Axes
from matplotlib import cbook
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import Formatter, Locator
from matplotlib.tr... | agpl-3.0 |
trankmichael/scikit-learn | examples/linear_model/plot_ols.py | 220 | 1940 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Linear Regression Example
=========================================================
This example uses the only the first feature of the `diabetes` dataset, in
order to illustrate a two-dimensional plot of this regre... | bsd-3-clause |
Cophy08/rodeo | rodeo/kernel.py | 8 | 7985 | # start compatibility with IPython Jupyter 4.0+
try:
from jupyter_client import BlockingKernelClient
except ImportError:
from IPython.kernel import BlockingKernelClient
# python3/python2 nonsense
try:
from Queue import Empty
except:
from queue import Empty
import atexit
import subprocess
import uuid
i... | bsd-2-clause |
davidwhogg/HoneyComb | exptime/code/exptime.py | 1 | 12174 | """
This file is part of the HoneyComb project.
Copyright 2015 David W. Hogg (NYU).
"""
import os
import numpy as np
import cPickle as pickle
import matplotlib.pyplot as pl
import matplotlib.transforms as transforms
pl.rc("text", usetex=True)
pl.rc("font", family="serif")
# multiprocessing trix DON'T WORK
from multipr... | mit |
pedrofeijao/RINGO | src/ringo/plot_ml_estimate.py | 1 | 1794 | #!/usr/bin/env python2
import argparse
import pandas as pd
import matplotlib
matplotlib.use('Agg') # Force matplotlib to not use any Xwindows backend.
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="Plots a boxplot ... | mit |
arabenjamin/pybrain | examples/rl/environments/linear_fa/bicycle.py | 26 | 14462 | from __future__ import print_function
"""An attempt to implement Randlov and Alstrom (1998). They successfully
use reinforcement learning to balance a bicycle, and to control it to drive
to a specified goal location. Their work has been used since then by a few
researchers as a benchmark problem.
We only implement th... | bsd-3-clause |
JPFrancoia/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 |
salomanders/NbodyPythonTools | nbdpt/cosmography.py | 1 | 6058 | import scipy as sp
#from scipy import trapz
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import pylab as pl
from pylab import *
import sys
#ApJ Komatsu et al. 2009
omega_M=.274
omega_L=.726
omega_K=1.-omega_M-omega_L
omega_K=0
h=.705
age=13.72
"""
print ' *** *** *** *** *** *** *** ***... | mit |
LUTAN/tensorflow | tensorflow/examples/learn/iris_custom_model.py | 50 | 2613 | # 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 appl... | apache-2.0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.