1 files changed, 122 insertions, 0 deletions
diff --git a/silx/math/medianfilter/test/benchmark.py b/silx/math/medianfilter/test/benchmark.py
new file mode 100644
index 0000000..0d1da94
--- /dev/null
+++ b/silx/math/medianfilter/test/benchmark.py
@@ -0,0 +1,122 @@
+# 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_()