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 |
|---|---|---|---|---|---|
jwkanggist/EveryBodyTensorFlow | run_slim_lenet5_nmist.py | 1 | 16249 | #-*- coding: utf-8 -*-
#! /usr/bin/env python
'''
filename: run_tf_slim_lenet5_mnist.py
description: simple end-to-end LetNet5 implementation
- For the purpose of EverybodyTensorFlow tutorial
-
- training with Mnist data set from Yann's website.
- the benchmark test error ra... | unlicense |
0asa/scikit-learn | examples/manifold/plot_compare_methods.py | 259 | 4031 | """
=========================================
Comparison of Manifold Learning methods
=========================================
An illustration of dimensionality reduction on the S-curve dataset
with various manifold learning methods.
For a discussion and comparison of these algorithms, see the
:ref:`manifold module... | bsd-3-clause |
emon10005/sympy | sympy/plotting/tests/test_plot.py | 43 | 8577 | from sympy import (pi, sin, cos, Symbol, Integral, summation, sqrt, log,
oo, LambertW, I, meijerg, exp_polar, Max, Piecewise)
from sympy.plotting import (plot, plot_parametric, plot3d_parametric_line,
plot3d, plot3d_parametric_surface)
from sympy.plotting.plot import unset... | bsd-3-clause |
DamienIrving/ocean-analysis | visualisation/water_cycle/plot_pe_region_data_global.py | 1 | 6007 | """Plot output from calc_pe_spatial_totals.py for globe basin only"""
# Import general Python modules
import sys, os, pdb
import argparse
import matplotlib.pyplot as plt
import iris
import iris.coord_categorisation
# Import my modules
cwd = os.getcwd()
repo_dir = '/'
for directory in cwd.split('/')[1:]:
repo_di... | mit |
nicholasmalaya/arcanus | uq/ps3/compute.py | 2 | 3719 | #!/usr/bin/env python
import os
import numpy as np
import matplotlib.mlab as mlab
from scipy.integrate import simps
from read_data import read_data
from hpd import hpd, plotpdfandobs
from integral_alt import integral
###############################################################################
# Get data (observa... | mit |
marcelotrevisani/vtky | vtky/BaseArray.py | 1 | 9900 | import numpy as np
import pandas as pd
import vtk
from vtk.util import numpy_support as ns
class BaseArray(object):
def __init__(self, array, type_array=None):
'''
:param array: Receives a pandas DataFrame, or numpy array or vtkDataArray
:param type_array: Receives the vtk data type or a... | mit |
detrout/debian-statsmodels | docs/source/plots/graphics_gofplots_qqplot.py | 38 | 1911 | # -*- coding: utf-8 -*-
"""
Created on Sun May 06 05:32:15 2012
Author: Josef Perktold
editted by: Paul Hobson (2012-08-19)
"""
from scipy import stats
from matplotlib import pyplot as plt
import statsmodels.api as sm
#example from docstring
data = sm.datasets.longley.load()
data.exog = sm.add_constant(data.exog, pre... | bsd-3-clause |
wzbozon/scikit-learn | sklearn/tests/test_cross_validation.py | 15 | 47366 | """Test the cross_validation module"""
from __future__ import division
import warnings
import numpy as np
from scipy.sparse import coo_matrix
from scipy.sparse import csr_matrix
from scipy import stats
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.test... | bsd-3-clause |
rainwoodman/pypm | examples/nbody.py | 3 | 10288 | from mpi4py import MPI
import numpy
from argparse import ArgumentParser
from nbodykit.cosmology import Planck15
from nbodykit.cosmology import EHPower
from nbodykit.cosmology.perturbation import PerturbationGrowth
from scipy.integrate import quad
PowerSpectrum = EHPower(Planck15, redshift=0.0)
pt = PerturbationGrowth... | gpl-3.0 |
LohithBlaze/scikit-learn | examples/manifold/plot_lle_digits.py | 181 | 8510 | """
=============================================================================
Manifold learning on handwritten digits: Locally Linear Embedding, Isomap...
=============================================================================
An illustration of various embeddings on the digits dataset.
The RandomTreesEmbed... | bsd-3-clause |
sonnyhu/scikit-learn | examples/cluster/plot_digits_agglomeration.py | 377 | 1694 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Feature agglomeration
=========================================================
These images how similar features are merged together using
feature agglomeration.
"""
print(__doc__)
# Code source: Gaël Varoquaux
#... | bsd-3-clause |
joshloyal/scikit-learn | sklearn/gaussian_process/kernels.py | 31 | 67169 | """Kernels for Gaussian process regression and classification.
The kernels in this module allow kernel-engineering, i.e., they can be
combined via the "+" and "*" operators or be exponentiated with a scalar
via "**". These sum and product expressions can also contain scalar values,
which are automatically converted to... | bsd-3-clause |
macks22/scikit-learn | benchmarks/bench_plot_ward.py | 290 | 1260 | """
Benchmark scikit-learn's Ward implement compared to SciPy's
"""
import time
import numpy as np
from scipy.cluster import hierarchy
import pylab as pl
from sklearn.cluster import AgglomerativeClustering
ward = AgglomerativeClustering(n_clusters=3, linkage='ward')
n_samples = np.logspace(.5, 3, 9)
n_features = n... | bsd-3-clause |
alvaroing12/CADL | session-5/libs/gif.py | 5 | 1834 | """Utility for creating a GIF.
Creative Applications of Deep Learning w/ Tensorflow.
Kadenze, Inc.
Copyright Parag K. Mital, June 2016.
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def build_gif(imgs, interval=0.1, dpi=72,
save_gif=True, saveto='animat... | apache-2.0 |
ngoix/OCRF | sklearn/utils/tests/test_multiclass.py | 34 | 13405 |
from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sp... | bsd-3-clause |
petosegan/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 |
Morwenn/vergesort | bench/bars.py | 1 | 2973 | import math
import os
import numpy
from matplotlib import pyplot as plt
distribution_names = {
"shuffled_16_values_int": "Shuffled (16 values)",
"shuffled_int": "Shuffled",
"all_equal_int": "All equal",
"ascending_int": "Ascending",
"descending_int": "Descending",
"pipe_organ_int": "Pipe org... | mit |
jreback/pandas | pandas/core/flags.py | 6 | 3567 | import weakref
class Flags:
"""
Flags that apply to pandas objects.
.. versionadded:: 1.2.0
Parameters
----------
obj : Series or DataFrame
The object these flags are associated with.
allows_duplicate_labels : bool, default True
Whether to allow duplicate labels in this o... | bsd-3-clause |
fredhusser/scikit-learn | examples/svm/plot_custom_kernel.py | 171 | 1546 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
xcbat/vnpy | docker/dockerTrader/ctaStrategy/tools/multiTimeFrame/strategyBreakOut.py | 5 | 11813 | # encoding: UTF-8
"""
This file tweaks ctaTemplate Module to suit multi-TimeFrame strategies.
"""
from ctaBase import *
from ctaTemplate import CtaTemplate
import numpy as np
########################################################################
class BreakOut(CtaTemplate):
"""
"infoArray" 字典是用来储存辅助品种信息的, ... | mit |
0x0all/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 |
pprett/statsmodels | statsmodels/examples/tsa/ex_var.py | 4 | 1237 |
import numpy as np
import statsmodels.api as sm
from statsmodels.tsa.api import VAR
# some example data
mdata = sm.datasets.macrodata.load().data
mdata = mdata[['realgdp','realcons','realinv']]
names = mdata.dtype.names
data = mdata.view((float,3))
use_growthrate = False #True #False
if use_growthrate:
data = 10... | bsd-3-clause |
kjyv/dynamical-system-identification | excitation/optimizer.py | 2 | 25323 | from __future__ import division
from __future__ import print_function
from builtins import range
from builtins import object
from typing import List, Tuple, Dict
import sys
import random
import numpy as np
import numpy.linalg as la
import matplotlib
import matplotlib.pyplot as plt
from distutils.version import LooseV... | lgpl-3.0 |
wangmiao1981/spark | python/pyspark/pandas/missing/indexes.py | 16 | 9920 | #
# 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 |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/examples/pylab_examples/tripcolor_demo.py | 3 | 4220 | """
Pseudocolor plots of unstructured triangular grids.
"""
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import math
# Creating a Triangulation without specifying the triangles results in the
# Delaunay triangulation of the points.
# First create the x and y coordinates of the point... | gpl-2.0 |
meduz/scikit-learn | benchmarks/bench_tree.py | 131 | 3647 | """
To run this, you'll need to have installed.
* scikit-learn
Does two benchmarks
First, we fix a training set, increase the number of
samples to classify and plot number of classified samples as a
function of time.
In the second benchmark, we increase the number of dimensions of the
training set, classify a sam... | bsd-3-clause |
xunyou/vincent | examples/line_chart_examples.py | 9 | 2109 | # -*- coding: utf-8 -*-
"""
Vincent Line Examples
"""
#Build a Line Chart from scratch
from vincent import *
import pandas as pd
import pandas.io.data as web
import datetime
all_data = {}
date_start = datetime.datetime(2010, 1, 1)
date_end = datetime.datetime(2014, 1, 1)
for ticker in ['AAPL', 'IBM', 'YHOO', 'MSFT'... | mit |
wzbozon/statsmodels | statsmodels/sandbox/tsa/movstat.py | 34 | 14871 | '''using scipy signal and numpy correlate to calculate some time series
statistics
original developer notes
see also scikits.timeseries (movstat is partially inspired by it)
added 2009-08-29
timeseries moving stats are in c, autocorrelation similar to here
I thought I saw moving stats somewhere in python, maybe not)... | bsd-3-clause |
nvoron23/scikit-learn | examples/linear_model/plot_sparse_recovery.py | 243 | 7461 | """
============================================================
Sparse recovery: feature selection for sparse linear models
============================================================
Given a small number of observations, we want to recover which features
of X are relevant to explain y. For this :ref:`sparse linear ... | bsd-3-clause |
kernsuite-debian/lofar | LCU/checkhardware/show_bad_spectra.py | 1 | 2645 | #!/usr/bin/env python3
import os
import numpy as np
import matplotlib.pyplot as plt
import time
obs_id_to_plot = ''
station_to_plot = ''
spectraPath = r'/localhome/stationtest/bad_spectra'
def main():
files = full_listdir(spectraPath)
for file_name in files:
file_data = file_name[file_name.rfind('/... | gpl-3.0 |
dparks1134/DBB | dbb/plots/gcCoveragePlot.py | 1 | 8081 | ###############################################################################
# #
# 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 #
... | gpl-3.0 |
KeplerGO/kpub | scripts/science-categories/categorize.py | 1 | 2061 | """Categorize publications into fine-grained categories
"""
from pprint import pprint
import pandas as pd
import kpub
FILENAME = "k2-categories.csv"
CATEGORIES = {
'as': 'Asteroseismology',
'ga': 'Galactic Archaeology',
'wd': 'White Dwarfs',
'cv': 'Cataclysmic V... | mit |
bloomberg/bqplot | bqplot/market_map.py | 1 | 9455 | # Copyright 2015 Bloomberg Finance L.P.
#
# 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 i... | apache-2.0 |
ElDeveloper/scikit-learn | examples/linear_model/plot_lasso_model_selection.py | 311 | 5431 | """
===================================================
Lasso model selection: Cross-Validation / AIC / BIC
===================================================
Use the Akaike information criterion (AIC), the Bayes Information
criterion (BIC) and cross-validation to select an optimal value
of the regularization paramet... | bsd-3-clause |
yavalvas/yav_com | build/matplotlib/lib/mpl_examples/pylab_examples/cursor_demo.py | 6 | 2028 | #!/usr/bin/env python
# -*- noplot -*-
"""
This example shows how to use matplotlib to provide a data cursor. It
uses matplotlib to draw the cursor and may be a slow since this
requires redrawing the figure with every mouse move.
Faster cursoring is possible using native GUI drawing, as in
wxcursor_demo.py
"""
from... | mit |
nitish-tripathi/Simplery | Scikit/DataPreprocessing.py | 1 | 2093 |
from io import StringIO
import numpy as np
import pandas as pd
from sklearn.preprocessing import Imputer, OneHotEncoder
def imput_missing_data(data):
"""
Method that demonstrates imputing missing data
"""
print data.isnull().sum()
print data.values
# Add Missing value using interpolation
#... | mit |
aigamedev/nuclai15 | dota2/extract_data_vectors.py | 2 | 3546 | from __future__ import (print_function, absolute_import)
import io
import collections
from smoke.io.wrap import demo as io_wrp_dm
from smoke.replay import demo as rply_dm
from smoke.replay.const import Data
import pandas as pd
import config
with io.open('1481687622.dem', 'rb') as infile:
demo_io = io_wrp_dm.Wrap... | gpl-3.0 |
jakobworldpeace/scikit-learn | sklearn/tests/test_metaestimators.py | 52 | 4990 | """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 |
jhnnsnk/nest-simulator | pynest/examples/hh_phaseplane.py | 12 | 5096 | # -*- coding: utf-8 -*-
#
# hh_phaseplane.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, ... | gpl-2.0 |
liuzhaoguo/FreeROI-1 | froi/gui/component/unused/volumedintensitydialog.py | 6 | 2368 | __author__ = 'zhouguangfu'
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import matplotlib.pyplot as plt
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplo... | bsd-3-clause |
evertrol/healpy | setup.py | 2 | 18554 | #!/usr/bin/env python
# Bootstrap setuptools installation. We require setuptools >= 3.2 because of a
# bug in earlier versions regarding C++ sources generated with Cython. See:
# https://pypi.python.org/pypi/setuptools/3.6#id171
try:
import pkg_resources
pkg_resources.require("setuptools >= 3.2")
except:
... | gpl-2.0 |
norbert/fickle | test/backend_test.py | 1 | 1757 | from sklearn import datasets
from fickle.testing import TestCase
from fickle.predictors import GenericSVMClassifier as Backend
class BackendTest(TestCase):
def test_load(self):
backend = Backend()
dataset = datasets.load_iris()
self.assertTrue(backend.load(dataset))
def test_isloade... | mit |
DailyActie/Surrogate-Model | 01-codes/scikit-learn-master/sklearn/metrics/__init__.py | 1 | 3388 | """
The :mod:`sklearn.metrics` module includes score functions, performance metrics
and pairwise metrics and distance computations.
"""
from . import cluster
from .classification import accuracy_score
from .classification import brier_score_loss
from .classification import classification_report
from .classification im... | mit |
chainer/chainercv | chainercv/visualizations/vis_instance_segmentation.py | 2 | 6121 | from __future__ import division
import numpy as np
from chainercv.utils.mask.mask_to_bbox import mask_to_bbox
from chainercv.visualizations.colormap import voc_colormap
from chainercv.visualizations import vis_image
def vis_instance_segmentation(
img, mask, label=None, score=None, label_names=None,
... | mit |
andyraib/data-storage | python_scripts/env/lib/python3.6/site-packages/mpl_toolkits/axisartist/axis_artist.py | 18 | 52709 | """
axis_artist.py module provides axis-related artists. They are
* axis line
* tick lines
* tick labels
* axis label
* grid lines
The main artist class is a AxisArtist and a GridlinesCollection. The
GridlinesCollection is responsible for drawing grid lines and the
AxisArtist is responsible for all other artists... | apache-2.0 |
robcarver17/pysystemtrade | sysproduction/data/volumes.py | 1 | 3936 | import datetime as datetime
import pandas as pd
from syscore.objects import missing_contract, arg_not_supplied, missing_data
from sysdata.arctic.arctic_futures_per_contract_prices import arcticFuturesContractPriceData
from sysdata.futures.futures_per_contract_prices import futuresContractPriceData
from sysobjects.contr... | gpl-3.0 |
costypetrisor/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 242 | 5885 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
wedgeCountry/SMP | Test.py | 1 | 2664 | from SMP import SMP
import sklearn.datasets
from sklearn.multiclass import OneVsRestClassifier
import numpy as np
import pylab as pl
from matplotlib.colors import ListedColormap
class Classifier_1vsA():
def __init__(self, classifier, max_it = 400, disp=1):
self.disp = disp
self.classifier = classifier
self.cl... | gpl-3.0 |
ericmjl/bokeh | examples/plotting/file/elements.py | 1 | 1856 | import pandas as pd
from bokeh.models import ColumnDataSource, LabelSet
from bokeh.plotting import figure, output_file, show
from bokeh.sampledata.periodic_table import elements
elements = elements.copy()
elements = elements[elements["atomic number"] <= 82]
elements = elements[~pd.isnull(elements["melting point"])]
m... | bsd-3-clause |
JsNoNo/scikit-learn | examples/covariance/plot_covariance_estimation.py | 250 | 5070 | """
=======================================================================
Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood
=======================================================================
When working with covariance estimation, the usual approach is to use
a maximum likelihood estimator,... | bsd-3-clause |
aabadie/scikit-learn | sklearn/gaussian_process/tests/test_gpr.py | 8 | 11823 | """Testing for Gaussian process regression """
# Author: Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# License: 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 |
PmagPy/PmagPy | programs/dmag_magic.py | 1 | 2595 | #!/usr/bin/env python
# -*- python-indent-offset: 4; -*-
# -*- mode: python-mode; python-indent-offset: 4 -*-
import sys
import os
import matplotlib
if matplotlib.get_backend() != "TKAgg":
matplotlib.use("TKAgg")
from pmagpy import ipmag
from pmagpy import pmag
def main():
"""
NAME
dmag_magic.py
... | bsd-3-clause |
rs2/pandas | pandas/tests/indexes/period/test_partial_slicing.py | 2 | 5323 | import numpy as np
import pytest
from pandas import DataFrame, Series, date_range, period_range
import pandas._testing as tm
class TestPeriodIndex:
def test_pindex_slice_index(self):
pi = period_range(start="1/1/10", end="12/31/12", freq="M")
s = Series(np.random.rand(len(pi)), index=pi)
... | bsd-3-clause |
Winand/pandas | doc/sphinxext/numpydoc/plot_directive.py | 89 | 20530 | """
A special directive for generating a matplotlib plot.
.. warning::
This is a hacked version of plot_directive.py from Matplotlib.
It's very much subject to change!
Usage
-----
Can be used like this::
.. plot:: examples/example.py
.. plot::
import matplotlib.pyplot as plt
plt.plot... | bsd-3-clause |
brainsqueeze/Image_correction | src/workers/correct.py | 1 | 4955 | # __author__ = 'Dave'
import cv2
from skimage import io
from skimage.transform import probabilistic_hough_line
import matplotlib.pyplot as plt
import os
import warnings
import random
import numpy as np
warnings.filterwarnings('ignore', category=RuntimeWarning)
class CorrectImage(object):
def __init__(self):
... | mit |
googledatalab/pydatalab | tests/stackdriver/commands/monitoring_tests.py | 4 | 4798 | # Copyright 2016 Google Inc. 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 applicable law or agreed ... | apache-2.0 |
treycausey/scikit-learn | sklearn/linear_model/tests/test_ridge.py | 1 | 17457 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
ikaee/bfr-attendant | facerecognitionlibrary/jni-build/jni/include/tensorflow/examples/skflow/out_of_core_data_classification.py | 9 | 2462 | # 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 |
chrsrds/scikit-learn | examples/plot_anomaly_comparison.py | 9 | 6338 | """
============================================================================
Comparing anomaly detection algorithms for outlier detection on toy datasets
============================================================================
This example shows characteristics of different anomaly detection algorithms
on 2D d... | bsd-3-clause |
dimitri-justeau/niamoto-core | niamoto/data_marts/dimensions/base_dimension.py | 2 | 12926 | # coding: utf-8
import io
from datetime import datetime
from sqlalchemy.engine.reflection import Inspector
from geoalchemy2 import Geography, Geometry
import sqlalchemy as sa
import pandas as pd
from niamoto.db import metadata as meta
from niamoto.db.connector import Connector
from niamoto.conf import settings
from ... | gpl-3.0 |
aayushidwivedi01/spark-tk | regression-tests/sparktkregtests/testcases/dicom/dicom_export_dcm_test.py | 11 | 4051 | # 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 |
gboeing/osmnx | osmnx/osm_xml.py | 1 | 14677 | """Read/write .osm formatted XML files."""
import bz2
import xml.sax
from pathlib import Path
from xml.etree import ElementTree as etree
import networkx as nx
import numpy as np
import pandas as pd
from . import settings
from . import utils
from . import utils_graph
class _OSMContentHandler(xml.sax.handler.Content... | mit |
phbradley/tcr-dist | tcrdist/processing.py | 1 | 8021 | import pandas as pd
import numpy as np
from .blast import parse_unpaired_dna_sequence_blastn, get_qualstring
from .objects import TCRChain, TCRClone
from . import util
from .compute_probs import *
from .find_clones import findClones
__all__ = ['processNT',
'readPairedSequences',
'filterOutRow',
... | mit |
francescorandi/optics | Datasets.py | 1 | 8249 | # -*- coding: utf-8 -*-
"""
Dataset class.
"""
import matplotlib.pyplot as pyplot
from numpy import array, loadtxt, savetxt, imag, real, dtype
from scipy.constants import physical_constants
energyUnits = ('eV', 'cm-1', 'THz') #List of energy units available
__wavelength = 'electron volt-inverse meter relationship'
_... | gpl-3.0 |
openfisca/openfisca-tunisia | setup.py | 1 | 1844 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""Tunisia specific model for OpenFisca -- a versatile microsimulation free software"""
from setuptools import setup, find_packages
classifiers = """\
Development Status :: 2 - Pre-Alpha
License :: OSI Approved :: GNU Affero General Public License v3
Operating System... | agpl-3.0 |
gheinrich/DIGITS-GAN | digits/extensions/view/imageSegmentation/view.py | 1 | 10053 | # Copyright (c) 2016, NVIDIA CORPORATION. All rights reserved.
from __future__ import absolute_import
import json
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import PIL.Image
import skfmm
import digits
from digits.utils import subclass, override
from digits.utils.constants ... | bsd-3-clause |
chenyyx/scikit-learn-doc-zh | examples/zh/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... | gpl-3.0 |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/lib/mpl_examples/pylab_examples/annotation_demo2.py | 12 | 6310 |
from matplotlib.pyplot import figure, show
from matplotlib.patches import Ellipse
import numpy as np
if 1:
fig = figure(1,figsize=(8,5))
ax = fig.add_subplot(111, autoscale_on=False, xlim=(-1,5), ylim=(-4,3))
t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2*np.pi*t)
line, = ax.plot(t, s, lw=3, color='p... | gpl-2.0 |
mfjb/scikit-learn | sklearn/tests/test_calibration.py | 213 | 12219 | # Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from sklearn.utils.testing import (assert_array_almost_equal, assert_equal,
assert_greater, assert_almost_equal,
... | bsd-3-clause |
tayebzaidi/HonorsThesisTZ | ThesisCode/gen_lightcurves/parse_periodic_spaceMod.py | 1 | 7678 | import sys
import os
import json
import numpy as np
from ANTARES_object import LAobject
import scipy.interpolate as scinterp
from mpi4py import MPI
sys.path.append('../classification/')
import bandMap
import pickle
import glob
import pandas as pd
def periodicProcessing():
"""
This method does the equivalent t... | gpl-3.0 |
ldirer/scikit-learn | examples/neural_networks/plot_rbm_logistic_classification.py | 99 | 4608 | """
==============================================================
Restricted Boltzmann Machine features for digit classification
==============================================================
For greyscale image data where pixel values can be interpreted as degrees of
blackness on a white background, like handwritten... | bsd-3-clause |
arjoly/scikit-learn | sklearn/metrics/tests/test_classification.py | 20 | 50188 | from __future__ import division, print_function
import numpy as np
from scipy import linalg
from functools import partial
from itertools import product
import warnings
from sklearn import datasets
from sklearn import svm
from sklearn.datasets import make_multilabel_classification
from sklearn.preprocessing import la... | bsd-3-clause |
QuLogic/cartopy | lib/cartopy/io/ogc_clients.py | 2 | 34553 | # Copyright Cartopy Contributors
#
# This file is part of Cartopy and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
"""
Implements RasterSource classes which can retrieve imagery from web services
such as WMS and WMTS.
The matplotlib in... | lgpl-3.0 |
secimTools/SECIMTools | src/secimtools/anovaModules/changeDFOrder.py | 2 | 1307 | import pandas as pd
import copy as copy
def changeDFOrder(data,combN,factors):
"""
Since OLS (ANOVA method) takes the first group as base line we need to
change the order of the DF to get all the possible contrasts. This function
adds a "1_" before the name of the group, that way we can change the or... | mit |
sekikn/incubator-airflow | airflow/providers/exasol/hooks/exasol.py | 5 | 7205 | #
# 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... | apache-2.0 |
jstoxrocky/statsmodels | statsmodels/tsa/ar_model.py | 20 | 34034 | from __future__ import division
from statsmodels.compat.python import iteritems, range, string_types, lmap
import numpy as np
from numpy import dot, identity
from numpy.linalg import inv, slogdet
from scipy.stats import norm
from statsmodels.regression.linear_model import OLS
from statsmodels.tsa.tsatools import (lagm... | bsd-3-clause |
astocko/statsmodels | statsmodels/sandbox/tsa/examples/ex_mle_arma.py | 33 | 4587 | # -*- coding: utf-8 -*-
"""
TODO: broken because of changes to arguments and import paths
fixing this needs a closer look
Created on Thu Feb 11 23:41:53 2010
Author: josef-pktd
copyright: Simplified BSD see license.txt
"""
from __future__ import print_function
import numpy as np
from numpy.testing import assert_almost... | bsd-3-clause |
mmottahedi/neuralnilm_prototype | scripts/e390.py | 2 | 6051 | 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 |
florian-f/sklearn | sklearn/manifold/tests/test_isomap.py | 31 | 3991 | from itertools import product
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from sklearn import datasets
from sklearn import manifold
from sklearn import neighbors
from sklearn import pipeline
from sklearn import preprocessing
from sklearn.utils.testing import assert_less
... | bsd-3-clause |
kdebrab/pandas | pandas/tests/tslibs/test_parsing.py | 3 | 6380 | # -*- coding: utf-8 -*-
"""
Tests for Timestamp parsing, aimed at pandas/_libs/tslibs/parsing.pyx
"""
from datetime import datetime
import numpy as np
import pytest
from dateutil.parser import parse
import pandas.util._test_decorators as td
from pandas import compat
from pandas.util import testing as tm
from pandas._l... | bsd-3-clause |
henridwyer/scikit-learn | sklearn/linear_model/tests/test_sgd.py | 129 | 43401 | import pickle
import unittest
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing ... | bsd-3-clause |
Nathx/think_stats | code/timeseries.py | 66 | 18035 | """This file contains code for use with "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2014 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function
import pandas
import numpy as np
import statsmodels.formula.api as smf
import st... | gpl-3.0 |
thjashin/tensorflow | tensorflow/contrib/labeled_tensor/python/ops/ops.py | 32 | 46479 | # 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 |
anne-urai/serialDDM | graphicalModels/setup.py | 6 | 1246 | #!/usr/bin/env python
try:
from setuptools import setup, Extension
setup, Extension
except ImportError:
from distutils.core import setup
from distutils.extension import Extension
setup, Extension
import os
import re
import sys
if sys.argv[-1] == "publish":
os.system("python setup.py sdist up... | mit |
hantek/deeplearn_hsi | hsi_utils.py | 1 | 29258 | #!/usr/bin/python
#
# Copyright (c) 2013-2015, Zhouhan LIN
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# l... | bsd-2-clause |
mantidproject/mantid | qt/python/mantidqt/widgets/sliceviewer/test/test_sliceviewer_zoom.py | 3 | 1599 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2020 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 +
# T... | gpl-3.0 |
keflavich/fil_finder | fil_finder/rollinghough.py | 2 | 5684 | # Licensed under an MIT open source license - see LICENSE
import numpy as np
from scipy.stats import scoreatpercentile
import matplotlib.pyplot as p
def rht(mask, radius, ntheta=180, background_percentile=25, verbose=False):
'''
Parameters
----------
mask : numpy.ndarray
Boolean or integ... | mit |
timothydmorton/bokeh | examples/interactions/interactive_bubble/data.py | 49 | 1265 | import numpy as np
from bokeh.palettes import Spectral6
def process_data():
from bokeh.sampledata.gapminder import fertility, life_expectancy, population, regions
# Make the column names ints not strings for handling
columns = list(fertility.columns)
years = list(range(int(columns[0]), int(columns[-... | bsd-3-clause |
rubikloud/scikit-learn | benchmarks/bench_random_projections.py | 397 | 8900 | """
===========================
Random projection benchmark
===========================
Benchmarks for random projections.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import collections
import numpy as np
import scipy.s... | bsd-3-clause |
songtaohe/Map | Parser.py | 1 | 3074 | import xml.etree.ElementTree
import numpy as np
import matplotlib.pyplot as plt
import code
from MyRTree import RTree
roadForMotorDict = {'motorway','trunk','primary','secondary','tertiary','unclassified','residential','service'}
roadForMotorBlackList = {'None', 'pedestrian','footway','bridleway','steps','path','side... | mit |
trungnt13/scikit-learn | sklearn/linear_model/least_angle.py | 42 | 49357 | """
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 |
themrmax/scikit-learn | examples/cluster/plot_birch_vs_minibatchkmeans.py | 333 | 3694 | """
=================================
Compare BIRCH and MiniBatchKMeans
=================================
This example compares the timing of Birch (with and without the global
clustering step) and MiniBatchKMeans on a synthetic dataset having
100,000 samples and 2 features generated using make_blobs.
If ``n_clusters... | bsd-3-clause |
paulromano/openmc | openmc/data/photon.py | 8 | 44955 | from collections import OrderedDict
from collections.abc import Mapping, Callable
from copy import deepcopy
from io import StringIO
from math import pi
from numbers import Integral, Real
import os
import h5py
import numpy as np
import pandas as pd
from scipy.interpolate import CubicSpline
import openmc.checkvalue as ... | mit |
Vutshi/qutip | qutip/gui/about.py | 1 | 14367 | # This file is part of QuTiP.
#
# QuTiP 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.
#
# QuTiP is distributed in the ... | gpl-3.0 |
fraricci/pymatgen | pymatgen/analysis/surface_analysis.py | 4 | 82693 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
This module defines tools to analyze surface and adsorption related
quantities as well as related plots. If you use this module, please
consider citing the following works::
R. Tran, Z. Xu, B. Radhakri... | mit |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/build/lib.linux-i686-2.7/matplotlib/testing/jpl_units/__init__.py | 6 | 3064 | #=======================================================================
"""
This is a sample set of units for use with testing unit conversion
of matplotlib routines. These are used because they use very strict
enforcement of unitized data which will test the entire spectrum of how
unitized data might be used (it is... | mit |
Unofficial-Extend-Project-Mirror/openfoam-extend-Breeder-other-scripting-PyFoam | PyFoam/Basics/RunDatabase.py | 1 | 10646 | # ICE Revision: $Id: $
"""
Collects data about runs in a small SQLite database
"""
# don't look at it too closely. It's my first sqlite-code
import sqlite3
from os import path
import datetime
import re
import sys
from PyFoam.Error import error
from .CSVCollection import CSVCollection
from PyFoam.ThirdParty.six imp... | gpl-2.0 |
JensWehner/votca-scripts | xtp/xtp_timecorrelation.py | 2 | 5380 | #!/usr/bin/env python
import sqlite3
import sys
import numpy as np
#import scipy.stats as st
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.patches as mpatches
import argparse
from matplotlib.pyplot import cm
import itertools
import numpy.ma as ma
import os
class MyParser(argparse.Argumen... | apache-2.0 |
ina-foss/ID-Fits | lib/tools.py | 1 | 3158 | # ID-Fits
# Copyright (c) 2015 Institut National de l'Audiovisuel, INA, All rights reserved.
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 3.0 of the License, or (at... | lgpl-3.0 |
zyndagj/bedgraph-ica | bedgraph-ica.py | 1 | 12302 | #!/usr/bin/python
from os.path import splitext
import numpy as np
import sys
from sklearn.decomposition import FastICA
from sklearn.utils.linear_assignment_ import linear_assignment as hungarian
import pywt
import argparse
myColors = ("#85BEFF", "#986300", "#009863", "#F2EC00", "#F23600", "#C21BFF", "#85FFC7")
colorD... | bsd-2-clause |
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