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 |
|---|---|---|---|---|---|
agile-geoscience/welly | welly/utils.py | 1 | 14357 | """
Utility functions for welly.
:copyright: 2021 Agile Scientific
:license: Apache 2.0
"""
import re
import glob
import warnings
import inspect
import functools
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
def deprecated(instructions):
"""
Flags a method as deprecated... | apache-2.0 |
jstoxrocky/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 |
r-mart/scikit-learn | sklearn/preprocessing/tests/test_function_transformer.py | 176 | 2169 | from nose.tools import assert_equal
import numpy as np
from sklearn.preprocessing import FunctionTransformer
def _make_func(args_store, kwargs_store, func=lambda X, *a, **k: X):
def _func(X, *args, **kwargs):
args_store.append(X)
args_store.extend(args)
kwargs_store.update(kwargs)
... | bsd-3-clause |
yanlend/scikit-learn | sklearn/decomposition/truncated_svd.py | 9 | 7737 | """Truncated SVD for sparse matrices, aka latent semantic analysis (LSA).
"""
# Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# Olivier Grisel <olivier.grisel@ensta.org>
# Michael Becker <mike@beckerfuffle.com>
# License: 3-clause BSD.
import numpy as np
import scipy.sparse as sp
try:
from scipy.sp... | bsd-3-clause |
pnedunuri/scikit-learn | sklearn/decomposition/tests/test_dict_learning.py | 69 | 8605 | import numpy as np
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
jereze/scikit-learn | sklearn/decomposition/tests/test_kernel_pca.py | 57 | 8062 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import (assert_array_almost_equal, assert_less,
assert_equal, assert_not_equal,
assert_raises)
from sklearn.decomposition import PCA, KernelPCA
from sklearn.datasets import mak... | bsd-3-clause |
JeanKossaifi/scikit-learn | sklearn/tests/test_random_projection.py | 79 | 14035 | 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 |
ssaeger/scikit-learn | examples/covariance/plot_lw_vs_oas.py | 159 | 2951 | """
=============================
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... | bsd-3-clause |
clemkoa/scikit-learn | sklearn/svm/tests/test_sparse.py | 63 | 13366 | 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_classification, load_digits, make_blobs
from sklearn.svm.tests import te... | bsd-3-clause |
metaml/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/projections/__init__.py | 69 | 2179 | from geo import AitoffAxes, HammerAxes, LambertAxes
from polar import PolarAxes
from matplotlib import axes
class ProjectionRegistry(object):
"""
Manages the set of projections available to the system.
"""
def __init__(self):
self._all_projection_types = {}
def register(self, *projections)... | agpl-3.0 |
wallarelvo/TVD | examples/generate_graph_example.py | 2 | 1548 |
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
import tvd
import matplotlib.pyplot as plt
import networkx as nx
def tvd_example():
m = tvd.read_pgm("imgs/strongly_connected.pgm")
G, rg, vor = tvd.topo_decomp(m, all_graphs=True)
mg = tvd.partition(G, 4)
tvd.draw_... | apache-2.0 |
nlalevee/spark | python/pyspark/sql/group.py | 4 | 10631 | #
# 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 |
jayflo/scikit-learn | sklearn/tests/test_common.py | 127 | 7665 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
from __future__ import print_function
import os
import warnings
import sys
import pkgutil
from sklearn.externals.six import PY3
fr... | bsd-3-clause |
PyWavelets/pywt | pywt/_doc_utils.py | 3 | 5823 | """Utilities used to generate various figures in the documentation."""
from itertools import product
import numpy as np
from matplotlib import pyplot as plt
from ._dwt import pad
__all__ = ['wavedec_keys', 'wavedec2_keys', 'draw_2d_wp_basis',
'draw_2d_fswavedecn_basis', 'boundary_mode_subplot']
def wave... | mit |
wzbozon/statsmodels | statsmodels/sandbox/nonparametric/tests/ex_smoothers.py | 33 | 1413 | # -*- coding: utf-8 -*-
"""
Created on Fri Nov 04 10:51:39 2011
@author: josef
"""
from __future__ import print_function
import numpy as np
from numpy.testing import assert_almost_equal, assert_equal
from statsmodels.sandbox.nonparametric import smoothers, kernels
from statsmodels.regression.linear_model import OLS, ... | bsd-3-clause |
danche354/Sequence-Labeling | ner_BIOES/senna-hash-2-pos-chunk-gazetteer-no-dropout-128-64-rmsprop5.py | 1 | 7836 | from keras.models import Model
from keras.layers import Input, Masking, Dense, LSTM
from keras.layers import Dropout, TimeDistributed, Bidirectional, merge
from keras.layers.embeddings import Embedding
from keras.utils import np_utils
from keras.optimizers import RMSprop
import numpy as np
import pandas as pd
import ... | mit |
466152112/scikit-learn | examples/missing_values.py | 233 | 3056 | """
======================================================
Imputing missing values before building an estimator
======================================================
This example shows that imputing the missing values can give better results
than discarding the samples containing any missing value.
Imputing does not ... | bsd-3-clause |
Parallel-in-Time/pySDC | pySDC/playgrounds/deprecated/Dedalus/periodic_playground_2D_parallel.py | 1 | 5213 | import sys
import numpy as np
import matplotlib.pyplot as plt
from mpi4py import MPI
from pySDC.helpers.stats_helper import filter_stats, sort_stats
from pySDC.implementations.collocation_classes.gauss_radau_right import CollGaussRadau_Right
from pySDC.implementations.controller_classes.controller_MPI import controll... | bsd-2-clause |
hirofumi0810/tensorflow_end2end_speech_recognition | examples/erato/metrics/attention.py | 1 | 9245 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""Define evaluation method for the Attention-based model (ERATO corpus)."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import re
import numpy as np
import pandas as pd
from tqdm import tqdm
from utils.i... | mit |
tedmeeds/tcga_encoder | tcga_encoder/models/pytorch/bootstrap_linear_regression.py | 1 | 2238 | import numpy as np
import pylab as pp
import scipy as sp
import sklearn
def bootstraps( x, m ):
# samples from arange(n) with replacement, m times.
#x = np.arange(n, dtype=int)
n = len(x)
N = np.zeros( (m,n), dtype=int)
for i in range(m):
N[i,:] = sklearn.utils.resample( x, replace = True )
return ... | mit |
benanne/theano-tutorial | 3_logistic_regression.py | 2 | 1394 | import theano
import theano.tensor as T
import numpy as np
import matplotlib.pyplot as plt
plt.ion()
import load
# load data
x_train, t_train, x_test, t_test = load.cifar10(dtype=theano.config.floatX)
labels_test = np.argmax(t_test, axis=1)
# visualize data
plt.imshow(x_train[0].reshape(32, 32), cmap=plt.cm.gray)
... | mit |
vibhorag/scikit-learn | examples/linear_model/plot_ransac.py | 250 | 1673 | """
===========================================
Robust linear model estimation using RANSAC
===========================================
In this example we see how to robustly fit a linear model to faulty data using
the RANSAC algorithm.
"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import ... | bsd-3-clause |
DTMilodowski/SPA_tools | construct_drivers/downscale_rs_data_random_forests.py | 1 | 1110 | import numpy as np
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split
def downsample_with_randomforest(rs_variables,target_variable,n_trees_in_forest = 100, min_samples_leaf = 50, n_cores = 1):
print "\t downsampling with random forest regression"
# first of... | gpl-3.0 |
simondona/img-fft-filter-bec-tn | libraries/imagelab.py | 1 | 47424 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright (C) 2014-2016 Simone Donadello
#
# 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) an... | gpl-3.0 |
WafaaT/spark-tk | regression-tests/sparktkregtests/testcases/graph/graph_connected_test.py | 11 | 2429 | # vim: set encoding=utf-8
# Copyright (c) 2016 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | apache-2.0 |
winklerand/pandas | pandas/compat/__init__.py | 1 | 12006 | """
compat
======
Cross-compatible functions for Python 2 and 3.
Key items to import for 2/3 compatible code:
* iterators: range(), map(), zip(), filter(), reduce()
* lists: lrange(), lmap(), lzip(), lfilter()
* unicode: u() [no unicode builtin in Python 3]
* longs: long (int in Python 3)
* callable
* iterable method... | bsd-3-clause |
L3nzian/AutoPermit | TmdlGui.py | 1 | 198879 | import wx
from wx import aui,grid
from wx.lib import colourdb
import wxmpl_plus
import matplotlib.dates
import _winreg
import TmdlFrame
if wx.Platform == '__WXMSW__':
import wx.lib.iewin as iewin
import TmdlLogic
import datetime
from dateutil import parser as DateParse, relativedelta as Relative
import types
from c... | gpl-2.0 |
pmeier82/SpikePlot | spikeplot/plot_waveforms.py | 1 | 5398 | # -*- coding: utf-8 -*-
#
# spikeplot - plot_waveforms.py
#
# Philipp Meier <pmeier82 at googlemail dot com>
# 2011-09-29
#
"""scatter plot for clustering data"""
__docformat__ = 'restructuredtext'
__all__ = ['waveforms']
##---IMPORTS
import scipy as sp
from .common import COLOURS, save_figure, check_plotting_handl... | mit |
dvro/UnbalancedDataset | examples/under-sampling/plot_nearmiss_1.py | 3 | 1837 | """
==========
Nearmiss 1
==========
An illustration of the nearmiss 1 method.
"""
print(__doc__)
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
# Define some color for the plotting
almost_black = '#262626'
palette = sns.color_palette()
from sklearn.datasets import make_classification
from sklear... | mit |
phdowling/scikit-learn | examples/ensemble/plot_adaboost_multiclass.py | 354 | 4124 | """
=====================================
Multi-class AdaBoosted Decision Trees
=====================================
This example reproduces Figure 1 of Zhu et al [1] and shows how boosting can
improve prediction accuracy on a multi-class problem. The classification
dataset is constructed by taking a ten-dimensional ... | bsd-3-clause |
untom/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 |
JFriel/honours_project | venv/lib/python2.7/site-packages/nltk/tbl/demo.py | 7 | 14715 | # -*- coding: utf-8 -*-
# Natural Language Toolkit: Transformation-based learning
#
# Copyright (C) 2001-2016 NLTK Project
# Author: Marcus Uneson <marcus.uneson@gmail.com>
# based on previous (nltk2) version by
# Christopher Maloof, Edward Loper, Steven Bird
# URL: <http://nltk.org/>
# For license information, see... | gpl-3.0 |
andrewv587/pycharm-project | VOC-CAM.py | 1 | 9896 | import glob
import keras.backend as K
from keras.applications.imagenet_utils import preprocess_input
from keras.callbacks import ModelCheckpoint
from keras.engine import Input
from keras.engine import Model
from keras.models import Sequential, load_model
from keras.layers.core import Flatten, Dense
from keras.layers.c... | apache-2.0 |
jcchin/Hyperloop_v2 | paper/images/trade_scripts/overland_structural_trades_plot.py | 4 | 1193 | import numpy as np
import matplotlib.pyplot as plt
m_pod = np.loadtxt('../data_files/overland_structural_trades/m_pod.txt', delimiter = '\t')
A_tube = np.loadtxt('../data_files/overland_structural_trades/A_tube.txt', delimiter = '\t')
dx = np.loadtxt('../data_files/overland_structural_trades/dx.txt', delimiter = '\t')... | apache-2.0 |
shyamalschandra/scikit-learn | examples/cluster/plot_lena_compress.py | 271 | 2229 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Vector Quantization Example
=========================================================
The classic image processing example, Lena, an 8-bit grayscale
bit-depth, 512 x 512 sized image, is used here to illustrate
how ... | bsd-3-clause |
passiweinberger/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/font_manager.py | 69 | 42655 | """
A module for finding, managing, and using fonts across platforms.
This module provides a single :class:`FontManager` instance that can
be shared across backends and platforms. The :func:`findfont`
function returns the best TrueType (TTF) font file in the local or
system font path that matches the specified :class... | agpl-3.0 |
nvoron23/statsmodels | statsmodels/sandbox/stats/stats_mstats_short.py | 34 | 14910 | '''get versions of mstats percentile functions that also work with non-masked arrays
uses dispatch to mstats version for difficult cases:
- data is masked array
- data requires nan handling (masknan=True)
- data should be trimmed (limit is non-empty)
handle simple cases directly, which doesn't require apply_alon... | bsd-3-clause |
cbertinato/pandas | pandas/tests/resample/test_datetime_index.py | 1 | 50749 | from datetime import datetime, timedelta
from functools import partial
from io import StringIO
import numpy as np
import pytest
import pytz
from pandas.errors import UnsupportedFunctionCall
import pandas as pd
from pandas import DataFrame, Series, Timedelta, Timestamp, isna, notna
from pandas.core.groupby.grouper im... | bsd-3-clause |
jblackburne/scikit-learn | sklearn/mixture/tests/test_gaussian_mixture.py | 9 | 39845 | # Author: Wei Xue <xuewei4d@gmail.com>
# Thierry Guillemot <thierry.guillemot.work@gmail.com>
# License: BSD 3 clauseimport warnings
import sys
import warnings
import numpy as np
from scipy import stats, linalg
from sklearn.covariance import EmpiricalCovariance
from sklearn.datasets.samples_generator import... | bsd-3-clause |
swift-lang/swift-e-lab | parsl/monitoring/web_app/apps/workflows.py | 1 | 1514 | import pandas as pd
import dash_html_components as html
from parsl.monitoring.web_app.app import get_db, close_db
from parsl.monitoring.web_app.utils import dataframe_to_html_table
sql_conn = get_db()
layout = html.Div(children=[
html.H1("Workflows"),
dataframe_to_html_table(id='workflows_table',
... | apache-2.0 |
kpj/SDEMotif | reaction_finder.py | 1 | 54567 | """
Find reactions via combinatoric investigations of data files
"""
import os
import csv
import copy
import pickle
import random
import itertools
import collections
import numpy as np
import pandas as pd
import networkx as nx
import scipy.stats as scis
import seaborn as sns
import matplotlib as mpl
import matplotli... | mit |
liberatorqjw/scikit-learn | sklearn/qda.py | 15 | 7139 | """
Quadratic Discriminant Analysis
"""
# Author: Matthieu Perrot <matthieu.perrot@gmail.com>
#
# License: BSD 3 clause
import warnings
import numpy as np
from .base import BaseEstimator, ClassifierMixin
from .externals.six.moves import xrange
from .utils import check_array, check_X_y
__all__ = ['QDA']
class QDA... | bsd-3-clause |
snowzjx/ns3-buffer-management | src/core/examples/sample-rng-plot.py | 188 | 1246 | # -*- Mode:Python; -*-
# /*
# * This program is free software; you can redistribute it and/or modify
# * it under the terms of the GNU General Public License version 2 as
# * published by the Free Software Foundation
# *
# * This program is distributed in the hope that it will be useful,
# * but WITHOUT ANY WARRA... | gpl-2.0 |
davidlmorton/spikepy | spikepy/plotting_utils/import_matplotlib.py | 1 | 1221 | # Copyright (C) 2012 David Morton
#
# 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 distribut... | gpl-3.0 |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/plotly/matplotlylib/mplexporter/tools.py | 75 | 1732 | """
Tools for matplotlib plot exporting
"""
def ipynb_vega_init():
"""Initialize the IPython notebook display elements
This function borrows heavily from the excellent vincent package:
http://github.com/wrobstory/vincent
"""
try:
from IPython.core.display import display, HTML
except I... | apache-2.0 |
igryski/TRMM_blend | src/satellite/remove_SEA_points_from_TRMM.py | 1 | 3930 | # =============================================
# Remove all sea points from all TRMM data
# Author: I.Stepanov
# : KNMI
# : 16.08.2016.
# =============================================
# Load python modules
import netCDF4
import pylab as pl
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as ... | gpl-3.0 |
xbresson/graph_convnets_pytorch | lib/coarsening.py | 1 | 9169 | import numpy as np
import scipy.sparse
import sklearn.metrics
def laplacian(W, normalized=True):
"""Return graph Laplacian"""
# Degree matrix.
d = W.sum(axis=0)
# Laplacian matrix.
if not normalized:
D = scipy.sparse.diags(d.A.squeeze(), 0)
L = D - W
else:
d += np.spa... | mit |
sergpolly/Thermal_adapt_scripts | ArchNew/DONE_extract_asm_termo.py | 1 | 5627 | import pandas as pd
import numpy as np
import re
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
import copy
# archaea genomes description from /ftp...ncbi/genomes/genbank/archaea/...
asm = pd.read_csv("assembly_summary_arch_ncbi.txt",sep='\t')
# # geomes description and connection with organism names/assem... | mit |
aleksandr-bakanov/astropy | astropy/convolution/utils.py | 3 | 10909 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import ctypes
import numpy as np
from astropy.modeling.core import FittableModel, custom_model
__all__ = ['discretize_model']
class DiscretizationError(Exception):
"""
Called when discretization of models goes wrong.
"""
class KernelSizeE... | bsd-3-clause |
castelao/AutoQC | util/benchmarks.py | 3 | 4332 | import util.combineTests as combinatorics
import matplotlib.pyplot as plt
import numpy as np
def compare_to_truth(combos, trueResult):
'''Given the results from all the possible combinations of tests (combos)
and a set of truth results (trueResult), the false positive rate and the
true positive rate ... | mit |
sarathid/Python-works | Intro_to_ML/tools/startup.py | 6 | 1170 | #!/usr/bin/python
print
print "checking for nltk"
try:
import nltk
except ImportError:
print "you should install nltk before continuing"
print "checking for numpy"
try:
import numpy
except ImportError:
print "you should install numpy before continuing"
print "checking for scipy"
try:
import scipy... | gpl-3.0 |
ThunderShiviah/runtime_visualizer | rtviz/main.py | 1 | 3371 | from time import time
from random import randrange
from concurrent.futures import ThreadPoolExecutor
from functools import partial
from matplotlib import pyplot as plt
def func_timer(func, *params, verbose=False):
"""Takes in a function and some parameters to the function and returns the execution time"""
... | mit |
samzhang111/scikit-learn | sklearn/ensemble/gradient_boosting.py | 4 | 69888 | """Gradient Boosted Regression Trees
This module contains methods for fitting gradient boosted regression trees for
both classification and regression.
The module structure is the following:
- The ``BaseGradientBoosting`` base class implements a common ``fit`` method
for all the estimators in the module. Regressio... | bsd-3-clause |
ContinuumIO/dask | dask/array/numpy_compat.py | 1 | 11515 | from distutils.version import LooseVersion
import numpy as np
import warnings
from ..utils import derived_from
_numpy_115 = LooseVersion(np.__version__) >= "1.15.0"
_numpy_116 = LooseVersion(np.__version__) >= "1.16.0"
_numpy_117 = LooseVersion(np.__version__) >= "1.17.0"
_numpy_118 = LooseVersion(np.__version__) >=... | bsd-3-clause |
jnmclarty/trump | trump/test/test_orm.py | 2 | 17330 | from trump.orm import Symbol, SetupTrump, SymbolManager, ConversionManager, \
SymbolLogEvent
from trump.templating.templates import GoogleFinanceFT, YahooFinanceFT,\
SimpleExampleMT, CSVFT, FFillIT, FeedsMatchVT, DateExistsVT, PctChangeMT
import pandas as pd
import pytest
from pytest import mark... | bsd-3-clause |
nikdavis/livefft | fft_tones.py | 1 | 4210 | import matplotlib
#required by OS X, must be done before other matplotlib imports
matplotlib.use('TKAgg')
from cmath import exp
from math import pi, log10
import matplotlib.pyplot as plt
from matplotlib import animation
import pyaudio
import struct
import sys
#based on wikipedia's FFT psuedocode, expects floats
def f... | mit |
saiwing-yeung/scikit-learn | examples/decomposition/plot_pca_vs_lda.py | 176 | 2027 | """
=======================================================
Comparison of LDA and PCA 2D projection of Iris dataset
=======================================================
The Iris dataset represents 3 kind of Iris flowers (Setosa, Versicolour
and Virginica) with 4 attributes: sepal length, sepal width, petal length
a... | bsd-3-clause |
Duke-QCD/freestream | animate.py | 1 | 3294 | #!/usr/bin/env python3
import argparse
import multiprocessing
import sys
# workaround possible backend bug
import matplotlib
matplotlib.use('agg')
import numpy as np
import h5py
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import freestream
class RepeatingFreeStreamer:
def __init__(self,... | mit |
pslacerda/GromacsWrapper | gromacs/utilities.py | 1 | 21856 | # GromacsWrapper: utilities.py
# Copyright (c) 2009 Oliver Beckstein <orbeckst@gmail.com>
# Released under the GNU Public License 3 (or higher, your choice)
# See the file COPYING for details.
"""
:mod:`gromacs.utilities` -- Helper functions and classes
========================================================
The mod... | gpl-3.0 |
YinongLong/scikit-learn | sklearn/tests/test_learning_curve.py | 59 | 10869 | # Author: Alexander Fabisch <afabisch@informatik.uni-bremen.de>
#
# License: BSD 3 clause
import sys
from sklearn.externals.six.moves import cStringIO as StringIO
import numpy as np
import warnings
from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import ... | bsd-3-clause |
nruggero/Standard-curve-analysis | generate_peptide_plot.py | 1 | 3923 | import subprocess
import os
import argparse
import csv
from collections import OrderedDict
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot as plt
import numpy as np
NCOL = 3
def main(input_directory, output_directory):
# Get all files in input directory
input_files = os.listdir(input_director... | mit |
Huyuwei/tvm | tutorials/frontend/deploy_ssd_gluoncv.py | 1 | 4348 | # 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 |
murali-munna/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 |
gibiansky/tensorflow | tensorflow/python/client/notebook.py | 33 | 4608 | # Copyright 2015 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 |
benizl/pymoku | examples/basic_phasemeter.py | 1 | 4514 | #
# pymoku example: Phasemeter networking streaming
#
# This example provides a network stream of Phasemeter
# data samples from Channel 1 and Channel 2. These samples
# are output in the form (I,Q,F,phi,counter) for each channel.
#
# (c) 2016 Liquid Instruments Pty. Ltd.
#
# The phasemeter is a little more complex th... | mit |
lindsayberry/lindsayberry.github.io | markdown_generator/talks.py | 199 | 4000 |
# coding: utf-8
# # Talks markdown generator for academicpages
#
# Takes a TSV of talks with metadata and converts them for use with [academicpages.github.io](academicpages.github.io). This is an interactive Jupyter notebook ([see more info here](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_i... | mit |
ArteliaTelemac/PostTelemac | PostTelemac/meshlayerparsers/libs_telemac/parsers/parserSELAFIN.py | 1 | 56945 | """@author Christopher J. Cawthorn and Sebastien E. Bourban
"""
"""@note ... this work is based on a collaborative effort between
.________. ,--.
HR Wallingford | | EDF - LNHE . ( ( Bundesanstalt fur +- -+
... | gpl-3.0 |
Midafi/scikit-image | doc/examples/plot_watershed.py | 7 | 2336 | """
======================
Watershed segmentation
======================
The watershed is a classical algorithm used for **segmentation**, that
is, for separating different objects in an image.
Starting from user-defined markers, the watershed algorithm treats
pixels values as a local topography (elevation). The algo... | bsd-3-clause |
cowlicks/dask | dask/dataframe/partitionquantiles.py | 1 | 18529 | """Determine new partition divisions using approximate percentiles.
We use a custom algorithm to calculate approximate, evenly-distributed
percentiles of arbitrarily-ordered data for any dtype in a distributed
fashion with one pass over the data. This is used to determine new
partition divisions when changing the ind... | bsd-3-clause |
Tiggels/opencog | opencog/python/spatiotemporal/temporal_events/membership_function.py | 34 | 4673 | from math import fabs
from random import random
from scipy.stats.distributions import rv_frozen
from spatiotemporal.time_intervals import TimeInterval
from spatiotemporal.unix_time import random_time, UnixTime
from utility.generic import convert_dict_to_sorted_lists
from utility.functions import Function, FunctionPiece... | agpl-3.0 |
akalicki/genomics-snack-to-sequence | quality-assessment/group3_report1_question8.py | 1 | 1830 | """
Usage: (python) group3_report1_question8.py
Takes in 2d_files.txt and times.txt from group3_report1_question8.sh
Matches files with those in tabular that are 2d. Extracts read_length and unix_timestamp
from times nanopore function. Makes a scatter plot with the data.
Run these commands before:
poretools tabular -q... | gpl-2.0 |
ales-erjavec/scipy | scipy/interpolate/ndgriddata.py | 45 | 7161 | """
Convenience interface to N-D interpolation
.. versionadded:: 0.9
"""
from __future__ import division, print_function, absolute_import
import numpy as np
from .interpnd import LinearNDInterpolator, NDInterpolatorBase, \
CloughTocher2DInterpolator, _ndim_coords_from_arrays
from scipy.spatial import cKDTree
_... | bsd-3-clause |
ferasboulala/Robot_Project | Robot_Project_GUI/Robot.py | 1 | 11000 | from tkinter import *
from tkinter.messagebox import *
from HW_Classes import *
import time, _thread, pigpio, matplotlib, math, os, numpy as np
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
# The following function works on my desktop ... | gpl-3.0 |
rrohan/scikit-learn | sklearn/cluster/bicluster.py | 211 | 19443 | """Spectral biclustering algorithms.
Authors : Kemal Eren
License: BSD 3 clause
"""
from abc import ABCMeta, abstractmethod
import numpy as np
from scipy.sparse import dia_matrix
from scipy.sparse import issparse
from . import KMeans, MiniBatchKMeans
from ..base import BaseEstimator, BiclusterMixin
from ..external... | bsd-3-clause |
PALab/pyjamaseis | pyjamaseis/pyjamaseisv1.0.py | 1 | 40544 | #=================================================================================================================
# Structure of PyjAmaseis
#
# - IMPORTS
# - STATION INFORMATION USER INTERFACE CODE (class myFrame4)
# - SECONDARY OPTIONS UI WINDOW CODE (class selectionWindow)
# - alignToBottomRight Function - aligns s... | gpl-2.0 |
kaichogami/scikit-learn | sklearn/decomposition/truncated_svd.py | 30 | 7896 | """Truncated SVD for sparse matrices, aka latent semantic analysis (LSA).
"""
# Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# Olivier Grisel <olivier.grisel@ensta.org>
# Michael Becker <mike@beckerfuffle.com>
# License: 3-clause BSD.
import numpy as np
import scipy.sparse as sp
try:
from scipy.sp... | bsd-3-clause |
mantidproject/mantid | scripts/test/MultiPlotting/Gridspec_test.py | 3 | 1317 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
from... | gpl-3.0 |
xiaoxiamii/scikit-learn | sklearn/decomposition/tests/test_fastica.py | 272 | 7798 | """
Test the fastica algorithm.
"""
import itertools
import warnings
import numpy as np
from scipy import stats
from nose.tools import assert_raises
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 skl... | bsd-3-clause |
swook/autocrop | suitability/Trainer.py | 1 | 2972 | from multiprocessing import cpu_count
from sklearn import svm
from sklearn.externals import joblib
from sklearn.grid_search import GridSearchCV
from sklearn.linear_model import LassoCV
from sklearn.preprocessing import StandardScaler
import numpy as np
import config
class Trainer:
clf = None
svm = None
... | mit |
pianomania/scikit-learn | examples/svm/plot_oneclass.py | 80 | 2338 | """
==========================================
One-class SVM with non-linear kernel (RBF)
==========================================
An example using a one-class SVM for novelty detection.
:ref:`One-class SVM <svm_outlier_detection>` is an unsupervised
algorithm that learns a decision function for novelty detection:
... | bsd-3-clause |
kazemakase/scikit-learn | examples/classification/plot_digits_classification.py | 289 | 2397 | """
================================
Recognizing hand-written digits
================================
An example showing how the scikit-learn can be used to recognize images of
hand-written digits.
This example is commented in the
:ref:`tutorial section of the user manual <introduction>`.
"""
print(__doc__)
# Autho... | bsd-3-clause |
vberaudi/scipy | scipy/stats/stats.py | 18 | 169352 | # Copyright (c) Gary Strangman. All rights reserved
#
# Disclaimer
#
# This software is provided "as-is". There are no expressed or implied
# warranties of any kind, including, but not limited to, the warranties
# of merchantability and fitness for a given application. In no event
# shall Gary Strangman be liable fo... | bsd-3-clause |
rexshihaoren/scikit-learn | sklearn/decomposition/nmf.py | 15 | 19103 | """ Non-negative matrix factorization
"""
# Author: Vlad Niculae
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Author: Chih-Jen Lin, National Taiwan University (original projected gradient
# NMF implementation)
# Author: Anthony Di Franco (original Python and NumPy port)
# License: BSD 3 clause
from __future__ ... | bsd-3-clause |
laurensstoop/HiSPARC-BONZ | egg/legacy/egg_saskia_v2.1_multifile.py | 1 | 3693 | # -*- coding: utf-8 -*-
"""
===================================
Created on Thu Mar 24 13:17:57 2016
@author: Laurens Stoop
===================================
"""
################################## HEADER ##################################
"""
Import of Packages
"""
import sapphire # The HiSparc Python Framework
... | gpl-3.0 |
johnmgregoire/NanoCalorimetry | accal_mcattempt.py | 1 | 2195 | import numpy, h5py, pylab, copy
from PnSC_h5io import *
from PnSC_math import *
from matplotlib.ticker import FuncFormatter
def myexpformat(x, pos):
for ndigs in range(5):
lab=(('%.'+'%d' %ndigs+'e') %x).replace('e+0','e').replace('e+','e').replace('e0','').replace('e-0','e-')
if eval(lab)==x:
... | bsd-3-clause |
nelango/ViralityAnalysis | model/lib/pandas/computation/ops.py | 9 | 15234 | """Operator classes for eval.
"""
import operator as op
from functools import partial
from datetime import datetime
import numpy as np
import pandas as pd
from pandas.compat import PY3, string_types, text_type
import pandas.core.common as com
from pandas.core.base import StringMixin
from pandas.computation.common im... | mit |
AlexRobson/scikit-learn | examples/neighbors/plot_approximate_nearest_neighbors_hyperparameters.py | 227 | 5170 | """
=================================================
Hyper-parameters of Approximate Nearest Neighbors
=================================================
This example demonstrates the behaviour of the
accuracy of the nearest neighbor queries of Locality Sensitive Hashing
Forest as the number of candidates and the numb... | bsd-3-clause |
moonbury/pythonanywhere | github/Numpy/Chapter9/emalegend.py | 2 | 1648 | from matplotlib.finance import quotes_historical_yahoo
from matplotlib.dates import DateFormatter
from matplotlib.dates import DayLocator
from matplotlib.dates import MonthLocator
import sys
from datetime import date
import matplotlib.pyplot as plt
import numpy as np
today = date.today()
start = (today.year - 1, today... | gpl-3.0 |
tarthy6/dozer-thesis | py/pre/horse.py | 3 | 11731 | # encoding: utf-8
from woo.dem import *
from woo.fem import *
import woo.core
import woo.dem
import woo.pyderived
import woo.models
import math
from minieigen import *
class FallingHorse(woo.core.Preprocessor,woo.pyderived.PyWooObject):
'''Preprocessor for the falling horse simulation. The falling horse is historica... | gpl-2.0 |
niltonlk/nest-simulator | pynest/examples/clopath_synapse_small_network.py | 8 | 7493 | # -*- coding: utf-8 -*-
#
# clopath_synapse_small_network.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 ... | gpl-2.0 |
rpcoelho17/Simulated-Annealing | RodsAnnealMultiV2_2.py | 1 | 27872 | from __future__ import print_function
import numpy as np
import math
import csv
import time
from matplotlib import cm
import matplotlib.animation as animation
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from mpl_toolkits.mplot3d import axis3d
import matplotlib.pyplot as plt
import random
... | bsd-3-clause |
zorojean/scikit-learn | sklearn/feature_extraction/tests/test_dict_vectorizer.py | 276 | 3790 | # Authors: Lars Buitinck <L.J.Buitinck@uva.nl>
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from random import Random
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from sklearn.utils.testing import (assert_equal, assert_in,
... | bsd-3-clause |
dyoung418/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 |
lucidfrontier45/scikit-learn | examples/covariance/plot_outlier_detection.py | 2 | 3866 | """
==========================================
Outlier detection with several methods.
==========================================
This example illustrates two ways of performing :ref:`outlier_detection`
when the amount of contamination is known:
- based on a robust estimator of covariance, which is assuming that the
... | bsd-3-clause |
huangziwei/MorphoPy | morphopy/_utils/utils.py | 1 | 13733 | import numpy as np
import pandas as pd
import networkx as nx
from copy import deepcopy
import logging
from .summarize import *
def get_logger(loglevel):
"""
Log out useful or debug infos.
Parameters
---------
loglevel: str
'debug', 'info', 'warning', 'error', 'critical'.
Returns
... | mit |
jm-begon/scikit-learn | sklearn/preprocessing/tests/test_data.py | 113 | 38432 | import warnings
import numpy as np
import numpy.linalg as la
from scipy import sparse
from distutils.version import LooseVersion
from sklearn.utils.testing import assert_almost_equal, clean_warning_registry
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal... | bsd-3-clause |
LennonLab/simplex | tools/SADfits/SADfits.py | 9 | 3639 | from __future__ import division
import matplotlib.pyplot as plt
import sys
import os
from random import shuffle
import numpy as np
########### PATHS ##############################################################
mydir = os.path.expanduser("~/GitHub/residence-time")
tools = os.path.expanduser(mydir + "/tools")
sys.p... | mit |
wanggang3333/scikit-learn | examples/classification/plot_lda_qda.py | 164 | 4806 | """
====================================================================
Linear and Quadratic Discriminant Analysis with confidence ellipsoid
====================================================================
Plot the confidence ellipsoids of each class and decision boundary
"""
print(__doc__)
from scipy import lin... | bsd-3-clause |
rudaoshi/keras | examples/kaggle_otto_nn.py | 70 | 3775 | from __future__ import absolute_import
from __future__ import print_function
import numpy as np
import pandas as pd
np.random.seed(1337) # for reproducibility
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.layers.normalization import BatchNormalization
from ke... | mit |
nvoron23/scikit-learn | sklearn/datasets/tests/test_20news.py | 280 | 3045 | """Test the 20news downloader, if the data is available."""
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import SkipTest
from sklearn import datasets
def test_20news():
try:
data = dat... | bsd-3-clause |
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