# coding: utf-8
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"""Benchmark file."""
__authors__ = ["H. Payno"]
__license__ = "MIT"
__date__ = "05/07/2016"
import freeart
from freeart.utils import reconstrutils, exampleutils, outgoingrayalgorithm, raypointsmethod
from silx.gui.plot import Plot2D
from silx.gui import qt
import sys
savingToPdf = False
[docs]def benchmark_tx_projection(oversamplings, widthsToTest, nbAngle):
"""
Create a graph for benchmarking the transmission forward projector
:param oversamplings: the list of oversamplings to test
:param widthsToTest: the list of phantom width to test
:param nbAngle: the number of projection to test
"""
times = {}
for oversamp in oversamplings :
bid = "oversamp=" + str(oversamp)
times[bid] = {}
for width in widthsToTest :
times[bid][width] = exampleutils.produce_tx_SheppLogan_sinogram(oversamp, nbAngle, width, save=False)[2]
print("tx forward projection - execution time for oversamp = " + str(oversamp) + ", width = " + str(width) + " toke : " + str(times[bid][width]) + " s")
if savingToPdf :
title= "tx_benchmatk_for_forward_projection_on_" + str(nbAngle) + "_angles"
plot = plot2D(title=title )
for curve in times:
plot.addCurve(widthsToTest, times[curve].values(), legend=curve )
plot.legendsDockWidget.show()
plot.saveGraph(filename=title + '.png', fileFormat='png')
plot.hide()
[docs]def benchmark_tx_reconstruction(oversamplings, widthsToTest, nbAngle, nbIter):
"""
Create a graph for benchmarking the transmission reconstructor
:param oversamplings: the list of oversamplings to test
:param widthsToTest: the list of phantom width to test
:param nbAngle: the number of projection to test
:param nbIter: the number of iteration to test (one iteration launch nbAngle back projection)
"""
times = {}
for oversamp in oversamplings :
bid = "oversamp=" + str(oversamp)
times[bid] = {}
for width in widthsToTest :
sino, angles, time = exampleutils.produce_tx_SheppLogan_sinogram(_oversampling=oversamp, _anglesNb=nbAngle, width=width, save=False )
times[bid][width] = exampleutils.make_tx_reconstruction(sino, angles, _nbIter=nbIter)[1]
print("tx reconstruction - execution time for oversamp = " + str(oversamp) + ", width = " + str(width) + " toke : " + str(times[bid][width]) + " s")
if savingToPdf :
title = "tx_benchmatk_for_reconstruction_on_" + str(nbAngle) + "_angles_and_" + str(nbIter) + "_iteration"
plot = plot2D(title=title )
for curve in times:
plot.addCurve(widthsToTest, times[curve].values(), legend=curve )
plot.legendsDockWidget.show()
plot.saveGraph(filename=(title + ".png"), fileFormat="png")
plot.hide()
[docs]def benchmark_fluo_projection(oversamplings, widthsToTest, nbAngle, outgoingraypointsmethods):
"""
Benchmark the fluo projection
:param oversamplings: the list of oversamplings to test
:param widthsToTest: the list of phantom width to test
:param nbAngle: the number of projection to test
:param outgoingraypointsmethods: the list of outgoingrayalgorithm to test
"""
times = {}
for oversamp in oversamplings :
for obmc in outgoingraypointsmethods:
bid = "method="+ str(obmc) + "_oversamp=" + str(oversamp)
times[bid] = {}
for width in widthsToTest :
times[bid][width] = exampleutils.produce_fluo_SheppLogan_sinogram(oversamp, nbAngle, detSetup, width, save=False)[4]
print("fluo projection - execution time for " + str(oversamp) + " oversampling, with = " + str(width) + " toke : " + str(times[bid][width]))
if savingToPdf :
for obmc in outgoingraypointsmethods:
title = "fluo_benchmark_for_projection_method_" + str(obmc) + "_on_" + str(nbAngle) + "_angles_and_"
plot = plot2D(title=title )
for curve in times:
plot.addCurve(widthsToTest, times[curve].values(), legend=curve )
plot.legendsDockWidget.show()
plot.saveGraph(filename=(title + ".png"), fileFormat="png")
plot.hide()
[docs]def benchmark_fluo_reconstruction(oversamplings, widthsToTest, nbAngle, outgoingraypointsmethods, nbIter):
"""
benchmark the fluo reconstruction
:param oversamplings: the list of oversamplings to test
:param widthsToTest: the list of phantom width to test
:param nbAngle: the number of projection to test
:param outgoingraypointsmethods: the list of outgoingrayalgorithm to test
:param nbIter: the number of iteration to test (one iteration launch nbAngle back projection)
"""
times = {}
for oversamp in oversamplings :
for obmc in outgoingraypointsmethods:
bid = "method="+ str(obmc) + "_oversamp=" + str(oversamp)
times[bid] = {}
for width in widthsToTest :
sinogram, angles, absMat, selfAbsMat, time = exampleutils.produce_fluo_SheppLogan_sinogram(oversamp, nbAngle, detSetup, width, save=False)
times[bid][width] = exampleutils.make_fluo_reconstruction(sinogram, angles, absMat, selfAbsMat, detSetup, nbIter, oversamp)[1]
print("fluo reconstruction - execution time for " + str(oversamp) + " oversampling, with = " + str(width) +
", method = " + str(obmc) + " toke : " + str(times[bid][width]))
if savingToPdf :
for obmc in outgoingraypointsmethods:
title=("fluo_benchmark_for_reconstruction_method_" + str(obmc) + "_on_" + str(nbAngle) + "_angles_and_" + str(nbIter) + "_iteration")
plot = plot2D(title=title )
for curve in times:
plot.addCurve(widthsToTest, times[curve].values(), legend=curve )
plot.legendsDockWidget.show()
plot.saveGraph(filename=(title + ".png"), fileFormat="png")
plot.hide()
if __name__ == "__main__":
if ('--saving' or '--s') in sys.argv :
savingToPdf=True
# benchmark the transmission
oversamplings = [1, 2, 4, 8]
widths = [16, 32, 64, 128, 356, 1024]
methodsBeamsGeneral = [raypointsmethod.withInterpolation ]
methodsOutgoing = [ outgoingrayalgorithm.rawApproximation,
outgoingrayalgorithm.createOneRayPerSamplePoint,
outgoingrayalgorithm.matriceSubdivision]
if savingToPdf :
global app # QApplication must be global to avoid seg fault on quit
app = qt.QApplication([])
# TODO : compute mean error
benchmark_tx_projection(oversamplings, widths, nbAngle = 100)
benchmark_tx_reconstruction(oversamplings, widths, nbAngle = 100, nbIter=1)
detPos = (1000, 0, 0)
detectorRadius = 10
detSetup = [(detPos, detectorRadius)]
benchmark_fluo_projection(oversamplings, widths, 100, methodsOutgoing)
benchmark_fluo_reconstruction(oversamplings, widths, 100, methodsOutgoing, nbIter=1)
if savingToPdf :
app.exec_()