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# coding: utf-8
# /*##########################################################################
# Copyright (C) 2017 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ############################################################################*/
"""Tests of the median filter"""
__authors__ = ["H. Payno"]
__license__ = "MIT"
__date__ = "02/05/2017"
from silx.gui import qt
from silx.math.medianfilter import medfilt2d as medfilt2d_silx
import numpy
import numpy.random
from timeit import Timer
from silx.gui.plot import Plot1D
import logging
try:
import scipy
except:
scipy = None
else:
import scipy.ndimage
try:
import PyMca5.PyMca as pymca
except:
pymca = None
else:
from PyMca5.PyMca.median import medfilt2d as medfilt2d_pymca
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
class BenchmarkMedianFilter(object):
"""Simple benchmark of the median fiter silx vs scipy"""
NB_ITER = 3
def __init__(self, imageWidth, kernels):
self.img = numpy.random.rand(imageWidth, imageWidth)
self.kernels = kernels
self.run()
def run(self):
self.execTime = {}
for kernel in self.kernels:
self.execTime[kernel] = self.bench(kernel)
def bench(self, width):
def execSilx():
medfilt2d_silx(self.img, width)
def execScipy():
scipy.ndimage.median_filter(input=self.img,
size=width,
mode='nearest')
def execPymca():
medfilt2d_pymca(self.img, width)
execTime = {}
t = Timer(execSilx)
execTime["silx"] = t.timeit(BenchmarkMedianFilter.NB_ITER)
logger.info(
'exec time silx (kernel size = %s) is %s' % (width, execTime["silx"]))
if scipy is not None:
t = Timer(execScipy)
execTime["scipy"] = t.timeit(BenchmarkMedianFilter.NB_ITER)
logger.info(
'exec time scipy (kernel size = %s) is %s' % (width, execTime["scipy"]))
if pymca is not None:
t = Timer(execPymca)
execTime["pymca"] = t.timeit(BenchmarkMedianFilter.NB_ITER)
logger.info(
'exec time pymca (kernel size = %s) is %s' % (width, execTime["pymca"]))
return execTime
def getExecTimeFor(self, id):
res = []
for k in self.kernels:
res.append(self.execTime[k][id])
return res
global app # QApplication must be global to avoid seg fault on quit
app = qt.QApplication([])
kernels = [3, 5, 7, 11, 15]
benchmark = BenchmarkMedianFilter(imageWidth=1000, kernels=kernels)
plot = Plot1D()
plot.addCurve(x=kernels, y=benchmark.getExecTimeFor("silx"), legend='silx')
if scipy is not None:
plot.addCurve(x=kernels, y=benchmark.getExecTimeFor("scipy"), legend='scipy')
if pymca is not None:
plot.addCurve(x=kernels, y=benchmark.getExecTimeFor("pymca"), legend='pymca')
plot.show()
app.exec_()
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