OSMAPOSL_test_proj.par

OSMAPOSLParameters := 
objective function type:=  PoissonLogLikelihoodWithLinearModelForMeanAndProjData
PoissonLogLikelihoodWithLinearModelForMeanAndProjData Parameters:= 
	input file := ${INPUT}
        additive sinogram := ${ADD_SINO}
	maximum absolute segment number to process :=  ${MAX_SEG_NUM}
	projector pair type := Matrix
  Projector Pair Using Matrix Parameters :=
  Matrix type := Ray Tracing
  Ray tracing matrix parameters :=
   ; use multiple (almost) parallel LORs for every bin in the sinogram 
   ; to avoid discretisation artefacts
   number of rays in tangential direction to trace for each bin:= 1
   ; you could disable some symmetries if you have enough memory
   ; this would for instance allow you to increase the number of subsets
   ; do_symmetry_90degrees_min_phi:=0
  End Ray tracing matrix parameters :=
  End Projector Pair Using Matrix Parameters :=


       Bin Normalisation type := From ProjData
	   Bin Normalisation From ProjData :=
	     normalisation projdata filename:= ${NORM_PROJDATA}
	 End Bin Normalisation From ProjData:=

	recompute sensitivity := 1
	use subset sensitivities:= 0
	sensitivity filename:=  ${SENS}
	zoom :=  1
  xy output image size (in pixels) := 100

end PoissonLogLikelihoodWithLinearModelForMeanAndProjData Parameters:= 
enforce initial positivity condition:=  1
number of subsets:= 1
number of subiterations:= 1
save estimates at subiteration intervals:= 1
output filename prefix := ${filename}
END :=