def TICL_iterations(process): process.FEVTDEBUGHLTEventContent.outputCommands.extend(['keep *_MultiClustersFromTracksters*_*_*']) process.TICLLayerTileProducer = ticlLayerTileProducer.clone() process.FilteredLayerClustersMIP = filteredLayerClustersProducer.clone( clusterFilter = "ClusterFilterBySize", algo_number = 8, max_cluster_size = 2, # inclusive iteration_label = "MIP" ) process.TrackstersMIP = trackstersProducer.clone( filtered_mask = cms.InputTag("FilteredLayerClustersMIP", "MIP"), missing_layers = 3, min_clusters_per_ntuplet = 15, min_cos_theta = 0.985 # ~10 degrees ) process.MultiClustersFromTrackstersMIP = multiClustersFromTrackstersProducer.clone( label = "MIPMultiClustersFromTracksterByCA", Tracksters = "TrackstersMIP" ) process.FilteredLayerClusters = filteredLayerClustersProducer.clone( algo_number = 8, iteration_label = "algo8" ) process.Tracksters = trackstersProducer.clone( original_mask = "TrackstersMIP", filtered_mask = cms.InputTag("FilteredLayerClusters", "algo8"), missing_layers = 2, min_clusters_per_ntuplet = 15, min_cos_theta = 0.94, # ~20 degrees min_cos_pointing = 0.7 ) process.MultiClustersFromTracksters = multiClustersFromTrackstersProducer.clone( Tracksters = "Tracksters" ) process.HGCalUncalibRecHit = HGCalUncalibRecHit process.HGCalRecHit = HGCalRecHit process.hgcalLayerClusters = hgcalLayerClusters process.hgcalMultiClusters = hgcalMultiClusters process.TICL_Task = cms.Task(process.HGCalUncalibRecHit, process.HGCalRecHit, process.hgcalLayerClusters, process.FilteredLayerClustersMIP, process.TICLLayerTileProducer, process.TrackstersMIP, process.MultiClustersFromTrackstersMIP, process.FilteredLayerClusters, process.Tracksters, process.MultiClustersFromTracksters, process.hgcalMultiClusters) process.schedule = cms.Schedule(process.raw2digi_step,process.FEVTDEBUGHLToutput_step) process.schedule.associate(process.TICL_Task) return process
def TICL_iterations(process): process.FEVTDEBUGHLTEventContent.outputCommands.extend(['keep *_MultiClustersFromTracksters*_*_*']) process.FilteredLayerClustersMIP = filteredLayerClustersProducer.clone( clusterFilter = "ClusterFilterBySize", algo_number = 8, max_cluster_size = 2, # inclusive iteration_label = "MIP" ) process.TrackstersMIP = trackstersProducer.clone( filtered_mask = cms.InputTag("FilteredLayerClustersMIP", "MIP"), missing_layers = 3, min_clusters_per_ntuplet = 15, min_cos_theta = 0.985 # ~10 degrees ) process.MultiClustersFromTrackstersMIP = multiClustersFromTrackstersProducer.clone( label = "MIPMultiClustersFromTracksterByCA", Tracksters = "TrackstersMIP" ) process.FilteredLayerClusters = filteredLayerClustersProducer.clone( algo_number = 8, iteration_label = "algo8" ) process.Tracksters = trackstersProducer.clone( original_mask = "TrackstersMIP", filtered_mask = cms.InputTag("FilteredLayerClusters", "algo8"), missing_layers = 2, min_clusters_per_ntuplet = 15, min_cos_theta = 0.94, # ~20 degrees min_cos_pointing = 0.7 ) process.MultiClustersFromTracksters = multiClustersFromTrackstersProducer.clone( Tracksters = "Tracksters" ) process.HGCalUncalibRecHit = HGCalUncalibRecHit process.HGCalRecHit = HGCalRecHit process.hgcalLayerClusters = hgcalLayerClusters process.hgcalMultiClusters = hgcalMultiClusters process.TICL_Task = cms.Task(process.HGCalUncalibRecHit, process.HGCalRecHit, process.hgcalLayerClusters, process.FilteredLayerClustersMIP, process.TrackstersMIP, process.MultiClustersFromTrackstersMIP, process.FilteredLayerClusters, process.Tracksters, process.MultiClustersFromTracksters, process.hgcalMultiClusters) process.schedule = cms.Schedule(process.raw2digi_step,process.FEVTDEBUGHLToutput_step) process.schedule.associate(process.TICL_Task) return process
def TICL_iterations(process): process.ticlLayerTileProducer = ticlLayerTileProducer.clone() process.ticlSeedingGlobal = ticlSeedingRegionProducer.clone(algoId=2) process.filteredLayerClustersMIP = filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterBySize", algo_number=8, max_cluster_size=2, # inclusive iteration_label="MIP") process.trackstersMIP = trackstersProducer.clone( filtered_mask="filteredLayerClustersMIP:MIP", seeding_regions="ticlSeedingGlobal", skip_layers=3, min_layers_per_trackster=15, min_cos_theta=0.99, # ~10 degrees ) process.filteredLayerClusters = filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=2, algo_number=8, iteration_label="algo8") process.tracksters = trackstersProducer.clone( original_mask="trackstersMIP", filtered_mask="filteredLayerClusters:algo8", seeding_regions="ticlSeedingGlobal", skip_layers=2, min_layers_per_trackster=15, min_cos_theta=0.94, # ~20 degrees min_cos_pointing=0.7) process.HGCalUncalibRecHit = HGCalUncalibRecHit process.HGCalRecHit = HGCalRecHit process.hgcalLayerClusters = hgcalLayerClusters process.hgcalMultiClusters = hgcalMultiClusters process.TICL_Task = cms.Task( process.HGCalUncalibRecHit, process.HGCalRecHit, process.hgcalLayerClusters, process.filteredLayerClustersMIP, process.ticlLayerTileProducer, process.ticlSeedingGlobal, process.trackstersMIP, process.filteredLayerClusters, process.tracksters, process.hgcalMultiClusters) process.schedule = cms.Schedule(process.raw2digi_step, process.FEVTDEBUGHLToutput_step) process.schedule.associate(process.TICL_Task) return process
filteredLayerClustersHAD = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=3, # inclusive algo_number=8, iteration_label="HAD", LayerClustersInputMask="ticlTrackstersTrk") # CA - PATTERN RECOGNITION ticlTrackstersHAD = _trackstersProducer.clone( filtered_mask="filteredLayerClustersHAD:HAD", original_mask='ticlTrackstersTrk', seeding_regions="ticlSeedingGlobal", # For the moment we mask everything w/o requirements since we are last # filter_on_categories = [5], # filter neutral hadrons # pid_threshold = 0.7, pluginPatternRecognitionByCA=dict( skip_layers=1, min_layers_per_trackster=12, min_cos_theta=0.866, # ~30 degrees min_cos_pointing=0.819, # ~35 degrees max_delta_time=-1), itername="HAD") ticlHADStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersHAD, ticlTrackstersHAD) filteredLayerClustersHFNoseHAD = _filteredLayerClustersProducer.clone( min_cluster_size=2, # inclusive algo_number=9, iteration_label="HADn", LayerClusters='hgcalLayerClustersHFNose',
def TICL_iterations_withReco(process): process.FEVTDEBUGHLTEventContent.outputCommands.extend(['keep *_multiClustersFromTracksters*_*_*']) process.ticlLayerTileProducer = ticlLayerTileProducer.clone() process.ticlSeedingTrk = ticlSeedingRegionProducer.clone( algoId = 1 ) process.filteredLayerClustersTrk = filteredLayerClustersProducer.clone( clusterFilter = "ClusterFilterByAlgo", algo_number = 8, iteration_label = "Trk" ) process.trackstersTrk = trackstersProducer.clone( filtered_mask = cms.InputTag("filteredLayerClustersTrk", "Trk"), seeding_regions = "ticlSeedingTrk", missing_layers = 3, min_clusters_per_ntuplet = 5, min_cos_theta = 0.99, # ~10 degrees min_cos_pointing = 0.9 ) process.multiClustersFromTrackstersTrk = multiClustersFromTrackstersProducer.clone( label = "TrkMultiClustersFromTracksterByCA", Tracksters = "trackstersTrk" ) process.ticlSeedingGlobal = ticlSeedingRegionProducer.clone( algoId = 2 ) process.filteredLayerClustersMIP = filteredLayerClustersProducer.clone( clusterFilter = "ClusterFilterBySize", algo_number = 8, max_cluster_size = 2, # inclusive iteration_label = "MIP" ) process.trackstersMIP = trackstersProducer.clone( filtered_mask = cms.InputTag("filteredLayerClustersMIP", "MIP"), seeding_regions = "ticlSeedingGlobal", missing_layers = 3, min_clusters_per_ntuplet = 15, min_cos_theta = 0.99, # ~10 degrees min_cos_pointing = 0.9, out_in_dfs = False, ) process.multiClustersFromTrackstersMIP = multiClustersFromTrackstersProducer.clone( label = "MIPMultiClustersFromTracksterByCA", Tracksters = "trackstersMIP" ) process.filteredLayerClusters = filteredLayerClustersProducer.clone( clusterFilter = "ClusterFilterByAlgoAndSize", min_cluster_size = 2, algo_number = 8, iteration_label = "algo8", LayerClustersInputMask = "trackstersMIP" ) process.trackstersEM = trackstersProducer.clone( original_mask = "trackstersMIP", filtered_mask = cms.InputTag("filteredLayerClusters", "algo8"), seeding_regions = "ticlSeedingGlobal", missing_layers = 2, min_clusters_per_ntuplet = 10, min_cos_theta = 0.94, # ~20 degrees min_cos_pointing = 0.7 ) process.multiClustersFromTrackstersEM = multiClustersFromTrackstersProducer.clone( Tracksters = "trackstersEM" ) process.trackstersHAD = trackstersProducer.clone( filtered_mask = cms.InputTag("filteredLayerClusters", "algo8"), seeding_regions = "ticlSeedingGlobal", missing_layers = 2, min_clusters_per_ntuplet = 10, min_cos_theta = 0.8, min_cos_pointing = 0.7 ) process.multiClustersFromTrackstersHAD = multiClustersFromTrackstersProducer.clone( Tracksters = "trackstersHAD" ) process.hgcalMultiClusters = hgcalMultiClusters process.TICL_Task = cms.Task( process.ticlLayerTileProducer, process.ticlSeedingTrk, process.filteredLayerClustersTrk, process.trackstersTrk, process.multiClustersFromTrackstersTrk, process.ticlSeedingGlobal, process.filteredLayerClustersMIP, process.trackstersMIP, process.multiClustersFromTrackstersMIP, process.filteredLayerClusters, process.trackstersEM, process.multiClustersFromTrackstersEM, process.trackstersHAD, process.multiClustersFromTrackstersHAD) process.schedule.associate(process.TICL_Task) return process
clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=2, # inclusive algo_number=8, LayerClustersInputMask='ticlTrackstersTrk', iteration_label="EM") # CA - PATTERN RECOGNITION ticlTrackstersEM = _trackstersProducer.clone( filtered_mask="filteredLayerClustersEM:EM", original_mask='ticlTrackstersTrk', seeding_regions="ticlSeedingGlobal", filter_on_categories=[0, 1], pid_threshold=0.8, max_out_in_hops=4, missing_layers=1, min_clusters_per_ntuplet=10, min_cos_theta=0.978, # ~12 degrees min_cos_pointing=0.9, # ~25 degrees max_delta_time=3., itername="EM", algo_verbosity=0, ) # MULTICLUSTERS ticlMultiClustersFromTrackstersEM = _multiClustersFromTrackstersProducer.clone( Tracksters="ticlTrackstersEM") ticlEMStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersEM, ticlTrackstersEM, ticlMultiClustersFromTrackstersEM)
LayerClustersInputMask = 'ticlTrackstersTrkEM', iteration_label = "EM" ) # CA - PATTERN RECOGNITION ticlTrackstersEM = _trackstersProducer.clone( filtered_mask = "filteredLayerClustersEM:EM", original_mask = 'ticlTrackstersTrkEM', seeding_regions = "ticlSeedingGlobal", filter_on_categories = [0, 1], pid_threshold = 0.5, energy_em_over_total_threshold = 0.9, max_longitudinal_sigmaPCA = 10, shower_start_max_layer = 5, #inclusive max_out_in_hops = 1, skip_layers = 2, max_missing_layers_in_trackster = 1, min_layers_per_trackster = 10, min_cos_theta = 0.97, # ~14 degrees min_cos_pointing = 0.9, # ~25 degrees max_delta_time = 3., itername = "EM", algo_verbosity = 0, ) # MULTICLUSTERS ticlMultiClustersFromTrackstersEM = _multiClustersFromTrackstersProducer.clone( Tracksters = "ticlTrackstersEM" )
from RecoHGCal.TICL.trackstersProducer_cfi import trackstersProducer as _trackstersProducer from RecoHGCal.TICL.filteredLayerClustersProducer_cfi import filteredLayerClustersProducer as _filteredLayerClustersProducer from RecoHGCal.TICL.multiClustersFromTrackstersProducer_cfi import multiClustersFromTrackstersProducer as _multiClustersFromTrackstersProducer # CLUSTER FILTERING/MASKING filteredLayerClustersCLUE3DHigh = _filteredLayerClustersProducer.clone( clusterFilter = "ClusterFilterByAlgoAndSize", min_cluster_size = 2, # inclusive algo_number = 8, iteration_label = "CLUE3DHigh" ) # PATTERN RECOGNITION ticlTrackstersCLUE3DHigh = _trackstersProducer.clone( filtered_mask = "filteredLayerClustersCLUE3DHigh:CLUE3DHigh", seeding_regions = "ticlSeedingGlobal", itername = "CLUE3DHigh", patternRecognitionBy = "CLUE3D", pluginPatternRecognitionByCLUE3D = dict ( criticalEtaPhiDistance = 0.025 ) ) ticlCLUE3DHighStepTask = cms.Task(ticlSeedingGlobal ,filteredLayerClustersCLUE3DHigh ,ticlTrackstersCLUE3DHigh)
iteration_label = "TrkEM" ) # CA - PATTERN RECOGNITION ticlTrackstersTrkEM = _trackstersProducer.clone( filtered_mask = "filteredLayerClustersTrkEM:TrkEM", seeding_regions = "ticlSeedingTrk", pluginPatternRecognitionByCA = dict( algo_verbosity = 0, filter_on_categories = [0, 1], pid_threshold = 0.5, energy_em_over_total_threshold = 0.9, max_longitudinal_sigmaPCA = 10, shower_start_max_layer = 5, #inclusive max_out_in_hops = 1, max_missing_layers_in_trackster = 2, skip_layers = 2, min_layers_per_trackster = 10, min_cos_theta = 0.97, # ~14 degrees min_cos_pointing = 0.94, # ~20 degrees root_doublet_max_distance_from_seed_squared = 2.5e-3, # dR=0.05 max_delta_time = 3. ), itername = "TrkEM", ) ticlTrkEMStepTask = cms.Task(ticlSeedingTrk ,filteredLayerClustersTrkEM ,ticlTrackstersTrkEM)
# CLUSTER FILTERING/MASKING filteredLayerClustersTrk = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=3, # inclusive algo_number=8, LayerClustersInputMask='ticlTrackstersEM', iteration_label="Trk") # CA - PATTERN RECOGNITION ticlTrackstersTrk = _trackstersProducer.clone( filtered_mask="filteredLayerClustersTrk:Trk", seeding_regions="ticlSeedingTrk", original_mask='ticlTrackstersEM', pluginPatternRecognitionByCA=dict( filter_on_categories=[2, 4], # filter muons and charged hadrons pid_threshold=0.0, skip_layers=3, min_layers_per_trackster=10, min_cos_theta=0.866, # ~30 degrees min_cos_pointing=0.798, # ~ 37 degrees max_delta_time=-1., algo_verbosity=2, oneTracksterPerTrackSeed=True, promoteEmptyRegionToTrackster=True), itername="Trk") ticlTrkStepTask = cms.Task(ticlSeedingTrk, filteredLayerClustersTrk, ticlTrackstersTrk)
# CLUSTER FILTERING/MASKING filteredLayerClustersMIP = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterBySize", algo_number=8, max_cluster_size=2, # inclusive iteration_label="MIP") # CA - PATTERN RECOGNITION ticlTrackstersMIP = _trackstersProducer.clone( filtered_mask="filteredLayerClustersMIP:MIP", seeding_regions="ticlSeedingGlobal", pluginPatternRecognitionByCA=dict( skip_layers=3, min_layers_per_trackster=10, min_cos_theta=0.99, # ~10 degrees min_cos_pointing=0.5, out_in_dfs=False, max_delta_time=-1), itername="MIP") ticlMIPStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersMIP, ticlTrackstersMIP) filteredLayerClustersHFNoseMIP = filteredLayerClustersMIP.clone( LayerClusters='hgcalLayerClustersHFNose', LayerClustersInputMask="hgcalLayerClustersHFNose:InitialLayerClustersMask", iteration_label="MIPn", algo_number=9)
# CLUSTER FILTERING/MASKING filteredLayerClustersMIP = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterBySize", algo_number=8, max_cluster_size=2, # inclusive iteration_label="MIP") # CA - PATTERN RECOGNITION ticlTrackstersMIP = _trackstersProducer.clone( filtered_mask="filteredLayerClustersMIP:MIP", seeding_regions="ticlSeedingGlobal", missing_layers=3, min_clusters_per_ntuplet=10, min_cos_theta=0.99, # ~10 degrees min_cos_pointing=0.5, out_in_dfs=False, itername="MIP", max_delta_time=-1) # MULTICLUSTERS ticlMultiClustersFromTrackstersMIP = _multiClustersFromTrackstersProducer.clone( Tracksters="ticlTrackstersMIP") ticlMIPStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersMIP, ticlTrackstersMIP, ticlMultiClustersFromTrackstersMIP) filteredLayerClustersHFNoseMIP = filteredLayerClustersMIP.clone(
from RecoHGCal.TICL.multiClustersFromTrackstersProducer_cfi import multiClustersFromTrackstersProducer as _multiClustersFromTrackstersProducer # CLUSTER FILTERING/MASKING filteredLayerClustersTrk = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgo", algo_number=8, iteration_label="Trk") # CA - PATTERN RECOGNITION ticlTrackstersTrk = _trackstersProducer.clone( filtered_mask="filteredLayerClustersTrk:Trk", seeding_regions="ticlSeedingTrk", filter_on_categories=[2, 4], # filter muons and charged hadrons pid_threshold=0.0, missing_layers=3, min_clusters_per_ntuplet=10, min_cos_theta=0.866, # ~30 degrees min_cos_pointing=0.798, # ~ 37 degrees max_delta_time=-1., algo_verbosity=2, oneTracksterPerTrackSeed=True, promoteEmptyRegionToTrackster=True, itername="TRK") # MULTICLUSTERS ticlMultiClustersFromTrackstersTrk = _multiClustersFromTrackstersProducer.clone( Tracksters="ticlTrackstersTrk") ticlTrkStepTask = cms.Task(ticlSeedingTrk, filteredLayerClustersTrk, ticlTrackstersTrk, ticlMultiClustersFromTrackstersTrk)
import FWCore.ParameterSet.Config as cms from RecoHGCal.TICL.TICLSeedingRegions_cff import ticlSeedingGlobal, ticlSeedingGlobalHFNose from RecoHGCal.TICL.trackstersProducer_cfi import trackstersProducer as _trackstersProducer from RecoHGCal.TICL.filteredLayerClustersProducer_cfi import filteredLayerClustersProducer as _filteredLayerClustersProducer from RecoHGCal.TICL.multiClustersFromTrackstersProducer_cfi import multiClustersFromTrackstersProducer as _multiClustersFromTrackstersProducer # CLUSTER FILTERING/MASKING filteredLayerClustersCLUE3DHigh = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=2, # inclusive algo_number=8, iteration_label="CLUE3DHigh") # PATTERN RECOGNITION ticlTrackstersCLUE3DHigh = _trackstersProducer.clone( filtered_mask="filteredLayerClustersCLUE3DHigh:CLUE3DHigh", seeding_regions="ticlSeedingGlobal", itername="CLUE3DHigh", patternRecognitionBy="CLUE3D", pluginPatternRecognitionByCLUE3D=dict(criticalDensity=0.6, criticalEtaPhiDistance=0.025, kernelDensityFactor=0.2, algo_verbosity=0)) ticlCLUE3DHighStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersCLUE3DHigh, ticlTrackstersCLUE3DHigh)
def TICL_iterations_withReco(process): process.FEVTDEBUGHLTEventContent.outputCommands.extend([ 'keep *_multiClustersFromTracksters*_*_*', 'keep *_ticlCandidateFromTrackstersProducer*_*_*', 'keep *_pfTICLProducer*_*_*' ]) process.ticlLayerTileProducer = ticlLayerTileProducer.clone() process.ticlSeedingTrk = ticlSeedingRegionProducer.clone(algoId=1) process.filteredLayerClustersTrk = filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgo", algo_number=8, iteration_label="Trk") process.trackstersTrk = trackstersProducer.clone( filtered_mask="filteredLayerClustersTrk:Trk", seeding_regions="ticlSeedingTrk", missing_layers=3, min_clusters_per_ntuplet=5, min_cos_theta= 0.99, # ~10 degrees min_cos_pointing=0.9) process.multiClustersFromTrackstersTrk = multiClustersFromTrackstersProducer.clone( label="TrkMultiClustersFromTracksterByCA", Tracksters="trackstersTrk") process.ticlSeedingGlobal = ticlSeedingRegionProducer.clone(algoId=2) process.filteredLayerClustersMIP = filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterBySize", algo_number=8, max_cluster_size=2, # inclusive iteration_label="MIP") process.trackstersMIP = trackstersProducer.clone( filtered_mask="filteredLayerClustersMIP:MIP", seeding_regions="ticlSeedingGlobal", missing_layers=3, min_clusters_per_ntuplet=15, min_cos_theta=0.99, # ~10 degrees min_cos_pointing=0.9, out_in_dfs=False, ) process.multiClustersFromTrackstersMIP = multiClustersFromTrackstersProducer.clone( label="MIPMultiClustersFromTracksterByCA", Tracksters="trackstersMIP") process.filteredLayerClusters = filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=2, algo_number=8, iteration_label="algo8", LayerClustersInputMask="trackstersMIP") process.trackstersEM = trackstersProducer.clone( max_out_in_hops=4, original_mask="trackstersMIP", filtered_mask="filteredLayerClusters:algo8", seeding_regions="ticlSeedingGlobal", missing_layers=1, min_clusters_per_ntuplet=10, min_cos_theta=0.984, # ~10 degrees min_cos_pointing=0.9 # ~26 degrees ) process.multiClustersFromTrackstersEM = multiClustersFromTrackstersProducer.clone( Tracksters="trackstersEM") process.trackstersHAD = trackstersProducer.clone( filtered_mask="filteredLayerClusters:algo8", seeding_regions="ticlSeedingGlobal", missing_layers=2, min_clusters_per_ntuplet=10, min_cos_theta=0.8, min_cos_pointing=0.7) process.multiClustersFromTrackstersHAD = multiClustersFromTrackstersProducer.clone( Tracksters="trackstersHAD") process.ticlCandidateFromTrackstersProducer = ticlCandidateFromTrackstersProducer.clone( ) process.pfTICLProducer = pfTICLProducer.clone() process.hgcalMultiClusters = hgcalMultiClusters process.TICL_Task = cms.Task( process.ticlLayerTileProducer, process.ticlSeedingTrk, process.filteredLayerClustersTrk, process.trackstersTrk, process.multiClustersFromTrackstersTrk, process.ticlSeedingGlobal, process.filteredLayerClustersMIP, process.trackstersMIP, process.multiClustersFromTrackstersMIP, process.filteredLayerClusters, process.trackstersEM, process.multiClustersFromTrackstersEM, process.trackstersHAD, process.multiClustersFromTrackstersHAD, process.ticlCandidateFromTrackstersProducer, process.pfTICLProducer) process.schedule.associate(process.TICL_Task) process.ticlPFValidation = ticlPFValidation process.hgcalValidation.insert(-1, process.ticlPFValidation) if getattr(process, 'hgcalValidator'): process.hgcalValidator.label_lcl = "hgcalLayerClusters" process.hgcalValidator.label_mcl = [ "multiClustersFromTrackstersEM:MultiClustersFromTracksterByCA", "multiClustersFromTrackstersHAD:MultiClustersFromTracksterByCA" ] process.hgcalValidator.domulticlustersPlots = True return process
filteredLayerClustersHAD = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=3, # inclusive algo_number=8, iteration_label="HAD", LayerClustersInputMask="ticlTrackstersTrk") # CA - PATTERN RECOGNITION ticlTrackstersHAD = _trackstersProducer.clone( filtered_mask="filteredLayerClustersHAD:HAD", original_mask='ticlTrackstersTrk', seeding_regions="ticlSeedingGlobal", # For the moment we mask everything w/o requirements since we are last # filter_on_categories = [5], # filter neutral hadrons # pid_threshold = 0.7, skip_layers=1, min_layers_per_trackster=12, min_cos_theta=0.866, # ~30 degrees min_cos_pointing=0.819, # ~35 degrees max_delta_time=-1, itername="HADRONIC") # MULTICLUSTERS ticlMultiClustersFromTrackstersHAD = _multiClustersFromTrackstersProducer.clone( Tracksters="ticlTrackstersHAD") ticlHADStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersHAD, ticlTrackstersHAD, ticlMultiClustersFromTrackstersHAD)
import FWCore.ParameterSet.Config as cms from RecoHGCal.TICL.TICLSeedingRegions_cff import ticlSeedingGlobal, ticlSeedingGlobalHFNose from RecoHGCal.TICL.trackstersProducer_cfi import trackstersProducer as _trackstersProducer from RecoHGCal.TICL.filteredLayerClustersProducer_cfi import filteredLayerClustersProducer as _filteredLayerClustersProducer from RecoHGCal.TICL.multiClustersFromTrackstersProducer_cfi import multiClustersFromTrackstersProducer as _multiClustersFromTrackstersProducer # CLUSTER FILTERING/MASKING filteredLayerClustersFastJet = _filteredLayerClustersProducer.clone( clusterFilter="ClusterFilterByAlgoAndSize", min_cluster_size=3, # inclusive algo_number=8, iteration_label="FastJet") # PATTERN RECOGNITION ticlTrackstersFastJet = _trackstersProducer.clone( filtered_mask="filteredLayerClustersFastJet:FastJet", seeding_regions="ticlSeedingGlobal", itername="FastJet", patternRecognitionBy="FastJet", pluginPatternRecognitionByFastJet=dict(algo_verbosity=2)) ticlFastJetStepTask = cms.Task(ticlSeedingGlobal, filteredLayerClustersFastJet, ticlTrackstersFastJet)