def run():
""" Run the macro
"""
# This input generates empty spills, to be filled by the beam maker later on
my_input = MAUS.InputCppRootData()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# Pre detector set up
#my_map.append(MAUS.MapCppMCReconSetup()) # geant4 simulation
# SciFi
my_map.append(MAUS.MapCppTrackerMCDigitization()) # SciFi electronics model
my_map.append(MAUS.MapCppTrackerClusterRecon()) # SciFi channel clustering
my_map.append(MAUS.MapCppTrackerSpacePointRecon()) # SciFi spacepoint recon
my_map.append(MAUS.MapCppTrackerPatternRecognition()) # SciFi track finding
my_map.append(MAUS.MapCppTrackerPRSeed()) # Set the Seed from PR
my_map.append(MAUS.MapCppTrackerTrackFit()) # SciFi track fit
my_map.append(MAUS.MapCppTrackerTOFCombinedFit())
#my_map.append(MAUS.MapCppTrackerDownstreamReFit())
# Then construct a MAUS output component - filename comes from datacards
my_output = MAUS.OutputCppRoot()
# can specify datacards here or by using appropriate command line calls
datacards = io.StringIO(u"")
# The Go() drives all the components you pass in, then check the file
# (default simulation.out) for output
MAUS.Go(my_input, my_map, MAUS.ReducePyDoNothing(), my_output, datacards)
def run():
""" Run the macro
"""
# Use the G4BL JSON chunks as an input to the simulation
my_input = MAUS.InputPyJSON()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# No need for the beam maker, as we use G4BL chunks
# my_map.append(MAUS.MapPyBeamMaker()) # beam construction
# Run the GEANT4 simulation
my_map.append(MAUS.MapCppSimulation()) # geant4 simulation
# Pre detector set up
my_map.append(MAUS.MapCppMCReconSetup()) # geant4 simulation
# TOF
my_map.append(MAUS.MapCppTOFMCDigitizer()) # TOF MC Digitizer
my_map.append(MAUS.MapCppTOFSlabHits()) # TOF MC Slab Hits
my_map.append(MAUS.MapCppTOFSpacePoints()) # TOF Space Points
# KL
my_map.append(MAUS.MapCppKLMCDigitizer()) # KL MC Digitizer
my_map.append(MAUS.MapCppKLCellHits()) # KL CellHit Reco
# SciFi
my_map.append(
MAUS.MapCppTrackerMCDigitization()) # SciFi electronics model
my_map.append(MAUS.MapCppTrackerClusterRecon()) # SciFi channel clustering
my_map.append(
MAUS.MapCppTrackerSpacePointRecon()) # SciFi spacepoint recon
my_map.append(
MAUS.MapCppTrackerPatternRecognition()) # SciFi track finding
my_map.append(MAUS.MapCppTrackerPRSeed()) # Set the Seed from PR
my_map.append(MAUS.MapCppTrackerTrackFit()) # SciFi track fit
my_map.append(
MAUS.MapCppTrackerTOFCombinedFit()) # ScifFi Tracker/TOF combined fit
# EMR
my_map.append(MAUS.MapCppEMRMCDigitization()) # EMR MC Digitization
my_map.append(MAUS.MapCppEMRSpacePoints()) # EMR MC Digitization
my_map.append(MAUS.MapCppEMRRecon()) # EMR Recon
# Ckov
my_map.append(MAUS.MapCppCkovMCDigitizer())
my_map.append(
MAUS.MapCppGlobalReconImport()) # import tracks for global matching
my_map.append(MAUS.MapCppGlobalTrackMatching()) # global track matching
# Cuts
# my_map.append(MAUS.MapCppCuts())
# Global Digits - post detector digitisation
# Then construct a MAUS output component - filename comes from datacards
my_output = MAUS.OutputCppRoot()
# can specify datacards here or by using appropriate command line calls
datacards = io.StringIO(u"")
# The Go() drives all the components you pass in, then check the file
# (default simulation.out) for output
MAUS.Go(my_input, my_map, MAUS.ReducePyDoNothing(), my_output, datacards)
