OSMAPOSL_test_lmf.par

OSMAPOSLParameters := 
objective function type:=  PoissonLogLikelihoodWithLinearModelForMeanAndListModeDataWithProjMatrixByBin
PoissonLogLikelihoodWithLinearModelForMeanAndListModeDataWithProjMatrixByBin Parameters:= 
	list mode filename := PET_ACQ_small.l.hdr.STIR
	max ring difference num to process :=  2
	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:= 3
   ; 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:= my_acfs.hs
	End Bin Normalisation From ProjData:=

	;num_events_to_store := 100
	recompute sensitivity :=1
	use subset sensitivities:= 0
	sensitivity filename:=  my_sens_t_lm_pr_seg2.hv
	zoom :=  1

additive sinogram := my_MLrandoms_f1.hs

end PoissonLogLikelihoodWithLinearModelForMeanAndListModeDataWithProjMatrixByBin Parameters:= 
enforce initial positivity condition:=  1
number of subsets:= 1
number of subiterations:= 1
save estimates at subiteration intervals:= 1
output filename prefix := my_output_t_lm_pr_seg2
END :=