# 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_()