def run():
"""
Analyze data from the MICE experiment
This reads in and processes data taken from the MICE
experiment.
"""
# Set up data cards.
data_cards_list = []
data_cards_list.append("output_file_name='scalers'\n")
# Convert data_cards to string.
data_cards = io.StringIO(unicode("".join(data_cards_list)))
# Set up the input that reads from DAQ
my_input = MAUS.InputCppDAQOfflineData()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
my_map.append(MAUS.MapCppTOFDigits())
my_map.append(MAUS.MapCppTOFSlabHits())
my_map.append(MAUS.MapCppTOFSpacePoints())
# Histogram reducer.
reducer = MAUS.ReducePyScalersTable()
# Save images as EPS and meta-data as JSON.
output_worker = MAUS.OutputPyFile()
# Run the workflow.
MAUS.Go(my_input, my_map, reducer, output_worker, data_cards)
def run():
""" Run the macro
"""
# This input generates empty spills, to be filled by the beam maker later on
my_input = MAUS.InputPySpillGenerator()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
my_map.append(MAUS.MapPyBeamMaker()) # beam construction
my_map.append(MAUS.MapCppSimulation()) # geant4 simulation
my_map.append(MAUS.MapCppTOFMCDigitizer()) # TOF MC Digitizer
my_map.append(MAUS.MapCppTOFSlabHits()) # TOF SlabHit Reco
my_map.append(MAUS.MapCppTOFSpacePoints()) # TOF SpacePoint Reco
#my_map.append(MAUS.MapCppTrackerRecon()) # SciFi recon
# can specify datacards here or by using appropriate command line calls
datacards = io.StringIO(u"")
reducer = MAUS.ReducePyDoNothing()
# Then construct a MAUS output component - filename comes from datacards
my_output = MAUS.OutputPyJSON()
# The Go() drives all the components you pass in, then check the file
# (default simulation.out) for output
MAUS.Go(my_input, my_map, reducer, 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
# 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())
# 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)
def run():
"""
Analyze data from the MICE experiment
This reads in and processes data taken from the MICE
experiment.
"""
# Set up data cards.
data_cards_list = []
# batch mode = runs ROOT in batch mode so that canvases are not displayed
# 1 = True, Batch Mode
# 0 = False, Interactive Mode
# setting it to false/0 will cause canvases to pop up on screen and
# will get refreshed every N spills set by the refresh_rate data
# card.
data_cards_list.append("root_batch_mode='%d'\n" % 1)
# refresh_rate = once in how many spills should canvases be updated
data_cards_list.append("refresh_rate='%d'\n" % 1)
# Add auto-numbering to the image tags. If False then each
# histogram output for successive spills will have the same tag
# so there are no spill-specific histograms. This is the
# recommended use for online reconstruction.
data_cards_list.append("histogram_auto_number=%s\n" % False)
# Default image type is eps. For online use, use PNG.
data_cards_list.append("histogram_image_type=\"png\"\n")
# Directory for images. Default: $MAUS_WEB_MEDIA_RAW if set
# else the current directory is used.
# Uncomment and change the following if you want to hard
# code a different default path.
# data_cards_list.append("image_directory='%s'\n" % os.getcwd())
# Convert data_cards to string.
data_cards = io.StringIO(unicode("".join(data_cards_list)))
# Set up the input that reads from DAQ
# my_input = MAUS.InputCppDAQData()
# my_input = MAUS.InputCppDAQOnlineData()
my_input = MAUS.InputCppDAQOnlineData() # pylint: disable = E1101
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# add ReconSetup map -- analyze_data_offline seems to have it already
my_map.append(MAUS.MapCppReconSetup())
my_map.append(MAUS.MapCppTOFDigits())
my_map.append(MAUS.MapCppTOFSlabHits())
my_map.append(MAUS.MapCppTOFSpacePoints())
my_map.append(MAUS.MapCppCkovDigits())
# Histogram reducer.
reducer = MAUS.ReducePyDoNothing()
#reducer = MAUS.ReducePyDoNothing()
# Save images as EPS and meta-data as JSON.
#output_worker = MAUS.OutputPyDoNothing()
output_worker = MAUS.OutputPyJSON()
# Run the workflow.
MAUS.Go(my_input, my_map, reducer, output_worker, data_cards)
def run():
""" Run the macro
"""
# This input generates empty spills, to be filled by the beam maker later on
my_input = MAUS.InputPySpillGenerator()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# GEANT4
my_map.append(MAUS.MapPyBeamMaker()) # beam construction
my_map.append(MAUS.MapCppSimulation()) # geant4 simulation
# Pre detector set up
my_map.append(MAUS.MapPyMCReconSetup()) # 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
# SciFi
my_map.append(MAUS.MapCppTrackerMCDigitization()) # SciFi electronics model
my_map.append(MAUS.MapCppTrackerRecon()) # SciFi Recon
# KL
my_map.append(MAUS.MapCppKLMCDigitizer()) # KL MC Digitizer
my_map.append(MAUS.MapCppKLCellHits()) # KL CellHit Reco
# EMR
my_map.append(MAUS.MapCppEMRMCDigitization()) # EMR MC Digitization
my_map.append(MAUS.MapCppEMRSpacePoints())
my_map.append(MAUS.MapCppEMRRecon()) # EMR Recon
# Ckov
my_map.append(MAUS.MapCppCkovMCDigitizer())
# Global
my_map.append(MAUS.MapCppGlobalReconImport())
my_map.append(MAUS.MapCppGlobalTrackMatching())
my_reduce = MAUS.ReducePyDoNothing()
# Then construct a MAUS output component - filename comes from datacards
#~ my_output = MAUS.OutputCppRoot()
my_output = MAUS.OutputPyDoNothing()
# 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, my_reduce, my_output, datacards)
def run():
"""
Analyze data from the MICE experiment
"""
# Set up the input that reads from DAQ
my_input = MAUS.InputCppDAQOfflineData()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# Trigger
my_map.append(MAUS.MapCppReconSetup())
# Detectors
my_map.append(MAUS.MapCppTOFDigits())
my_map.append(MAUS.MapCppTOFSlabHits())
my_map.append(MAUS.MapCppTOFSpacePoints())
my_map.append(MAUS.MapCppCkovDigits())
my_map.append(MAUS.MapCppKLDigits())
my_map.append(MAUS.MapCppKLCellHits())
my_map.append(MAUS.MapCppTrackerDigits()) # SciFi real data digitization
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.MapCppEMRPlaneHits())
my_map.append(MAUS.MapCppEMRSpacePoints())
my_map.append(MAUS.MapCppEMRRecon())
my_reduce = MAUS.ReducePyDoNothing()
# The Go() drives all the components you pass in then put all the output
# into a file called 'mausput'
MAUS.Go(my_input, my_map, my_reduce, MAUS.OutputCppRoot())
def run():
"""Analyze data from the MICE experiment
This will read in and process data taken from the MICE experiment. It will
eventually include things like cabling information, calibrations, and fits.
"""
# Set up the input that reads from DAQ
#my_input = MAUS.InputCppDAQData()
my_input = MAUS.InputCppDAQOfflineData()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
my_map.append(MAUS.MapCppTOFDigits())
my_map.append(MAUS.MapCppTOFSlabHits())
my_map.append(MAUS.MapCppTOFSpacePoints())
my_map.append(MAUS.MapCppCkovDigits())
reducer = MAUS.ReducePyCkov()
# The Go() drives all the components you pass in then put all the output
# into a file called 'mausput'
MAUS.Go(my_input, my_map, reducer, MAUS.OutputPyImage())
def run():
"""
Analyze data from the MICE experiment
"""
# Set up the input that reads from DAQ
my_input = MAUS.InputCppDAQOnlineData()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# Trigger
my_map.append(MAUS.MapCppReconSetup())
# Detectors
my_map.append(MAUS.MapCppTOFDigits())
my_map.append(MAUS.MapCppTOFSlabHits())
my_map.append(MAUS.MapCppTOFSpacePoints())
my_map.append(MAUS.MapCppCkovDigits())
my_map.append(MAUS.MapCppKLDigits())
my_map.append(MAUS.MapCppKLCellHits())
my_map.append(MAUS.MapCppTrackerDigits())
my_map.append(MAUS.MapCppTrackerRecon())
my_map.append(MAUS.MapCppEMRPlaneHits())
my_map.append(MAUS.MapCppEMRRecon())
my_reduce = MAUS.ReducePyDoNothing()
# The Go() drives all the components you pass in then put all the output
# into a file called 'mausput'
MAUS.Go(my_input, my_map, my_reduce, MAUS.OutputCppRoot())
def run():
""" Run the macro
"""
# This input generates empty spills, to be filled by the beam maker later on
my_input = MAUS.InputPySpillGenerator()
# Create an empty array of mappers, then populate it
# with the functionality you want to use.
my_map = MAUS.MapPyGroup()
# G4beamline
my_map.append(MAUS.MapPyBeamlineSimulation())
# GEANT4
# my_map.append(MAUS.MapPyBeamMaker()) # beam construction
my_map.append(MAUS.MapCppSimulation()) # geant4 simulation
# Pre detector set up
my_map.append(MAUS.MapPyMCReconSetup()) # 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
# MAUS 2.5.0
#my_map.append(MAUS.MapCppTrackerMCDigitization()) # SciFi electronics model
#my_map.append(MAUS.MapCppTrackerRecon()) # SciFi Recon
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.MapCppTrackerTOFReFit()) # SciFi track refit based on TOF
# EMR
my_map.append(MAUS.MapCppEMRMCDigitization()) # EMR MC Digitizer
my_map.append(MAUS.MapCppEMRSpacePoints()) # EMR Space Points
my_map.append(MAUS.MapCppEMRRecon()) # EMR Recon
# Global
my_map.append(MAUS.MapCppGlobalReconImport())
my_map.append(MAUS.MapCppGlobalTrackMatching())
# 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 setUpClass(cls): #pylint: disable = C0103
"""Construct a MapCppTOFSpacePoints"""
cls.mapper = MAUS.MapCppTOFSpacePoints()
cls.c = Configuration()
