lambda p, i: concentrator.create_supertriggercell( p, i, stcSize=cms.vuint32(4, 8, 8, 8), fixedDataSizePerHGCROC=True)) chains.register_concentrator( "Equalshare", lambda p, i: concentrator.create_supertriggercell( p, i, stcSize=cms.vuint32(4, 8, 8, 8), fixedDataSizePerHGCROC=True, type_energy_division='equalShare')) chains.register_concentrator("Onebit", concentrator.create_onebitfraction) ## BE1 chains.register_backend1("Dummy", clustering2d.create_dummy) ## BE2 chains.register_backend2("Histomax", clustering3d.create_histoMax_variableDr) chains.register_backend2( "Histomaxshape15", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, shape_threshold=1.5)) ### Varies seed threshold chains.register_backend2( "Histomaxth0", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=0.)) chains.register_backend2( "Histomaxth0shape15", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=0., shape_threshold=1.5)) chains.register_backend2( "Histomaxth20", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=20.)) chains.register_backend2( "Histomaxth20shape15", lambda p, i: clustering3d. create_histoMax_variableDr(p, i, seed_threshold=20., shape_threshold=1.5)) ### Varies clustering distance from L1Trigger.L1THGCal.customClustering import dr_layerbylayer
# Register algorithms ## VFE chains.register_vfe("Floatingpoint8", lambda p: vfe.create_compression(p, 4, 4, True)) ## ECON chains.register_concentrator("Supertriggercell", concentrator.create_supertriggercell) chains.register_concentrator("Threshold", concentrator.create_threshold) ## BE1 chains.register_backend1("Ref2d", clustering2d.create_constrainedtopological) chains.register_backend1("Dummy", clustering2d.create_dummy) ## BE2 chains.register_backend2("Ref3d", clustering3d.create_distance) chains.register_backend2("Histomax", clustering3d.create_histoMax) chains.register_backend2( "Histomaxvardrth0", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=0.)) chains.register_backend2( "Histomaxvardrth10", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=10.)) chains.register_backend2( "Histomaxvardrth20", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=20.)) # Register ntuples # Store gen info only in the reference ntuple ntuple_list_ref = ['event', 'gen', 'multiclusters'] ntuple_list = ['event', 'multiclusters'] chains.register_ntuple( "Genclustersntuple", lambda p, i: ntuple.create_ntuple(p, i, ntuple_list_ref)) chains.register_ntuple("Clustersntuple", lambda p, i: ntuple.create_ntuple(p, i, ntuple_list))
import L1Trigger.L1THGCalUtilities.clustering2d as clustering2d import L1Trigger.L1THGCalUtilities.clustering3d as clustering3d chain = HGCalTriggerChains() chain.register_vfe("VFEfp7", vfe.create_compression) chain.register_concentrator("tcTh", concentrator.create_threshold) chain.register_concentrator("sTC", concentrator.create_supertriggercell) chain.register_backend1("dRNNC2d", clustering2d.create_constrainedtopological) chain.register_backend1("dummyC2d", clustering2d.create_dummy) chain.register_backend2("histoMaxC3dVR", clustering3d.create_histoMax_variableDr) chain.register_backend2( "histoMaxC3dVRPhiBins", lambda p, i: clustering3d.create_histoMax_variableDr(p, i, nBins_Phi=108)) chain.register_backend2("dRC3d", clustering3d.create_distance) # chain.register_chain('VFEfp7', 'tcTh', 'dummyC2d', 'histoMaxC3d') chain.register_chain('VFEfp7', 'tcTh', 'dummyC2d', 'histoMaxC3dVR') chain.register_chain('VFEfp7', 'tcTh', 'dummyC2d', 'histoMaxC3dVRPhiBins') chain.register_chain('VFEfp7', 'sTC', 'dummyC2d', 'histoMaxC3dVR') chain.register_chain('VFEfp7', 'tcTh', 'dRNNC2d', 'dRC3d') # chain.register_chain('Floatingpoint7', 'Threshold', 'Dummy', 'Histothreshold') # chain.register_chain('Floatingpoint7', 'Bestchoice', 'Dummy', 'Histothreshold') process = chain.create_sequences(process) process.load("L1Trigger.L1THGCalUtilities.caloTruthCells_cff") process.caloTruthCellsProducer.triggerCells = cms.InputTag(
chains = HGCalTriggerChains() # Register algorithms ## VFE chains.register_vfe("Floatingpoint8", lambda p : vfe.create_compression(p, 4, 4, True)) ## ECON chains.register_concentrator("Supertriggercell", concentrator.create_supertriggercell) chains.register_concentrator("Threshold", concentrator.create_threshold) ## BE1 chains.register_backend1("Ref2d", clustering2d.create_constrainedtopological) chains.register_backend1("Dummy", clustering2d.create_dummy) ## BE2 chains.register_backend2("Ref3d", clustering3d.create_distance) chains.register_backend2("Histomax", clustering3d.create_histoMax) chains.register_backend2("Histomaxvardrth0", lambda p,i : clustering3d.create_histoMax_variableDr(p,i,seed_threshold=0.)) chains.register_backend2("Histomaxvardrth10", lambda p,i : clustering3d.create_histoMax_variableDr(p,i,seed_threshold=10.)) chains.register_backend2("Histomaxvardrth20", lambda p,i : clustering3d.create_histoMax_variableDr(p,i,seed_threshold=20.)) # Register ntuples # Store gen info only in the reference ntuple ntuple_list_ref = ['event', 'gen', 'multiclusters'] ntuple_list = ['event', 'multiclusters'] chains.register_ntuple("Genclustersntuple", lambda p,i : ntuple.create_ntuple(p,i, ntuple_list_ref)) chains.register_ntuple("Clustersntuple", lambda p,i : ntuple.create_ntuple(p,i, ntuple_list)) # Register trigger chains ## Reference chain chains.register_chain('Floatingpoint8', "Threshold", 'Ref2d', 'Ref3d', 'Genclustersntuple') concentrator_algos = ['Supertriggercell', 'Threshold'] backend_algos = ['Histomax', 'Histomaxvardrth0', 'Histomaxvardrth10', 'Histomaxvardrth20'] ## Make cross product fo ECON and BE algos
chains.register_concentrator( "Equalshare", lambda p, i: concentrator.create_supertriggercell( p, i, stcSize=cms.vuint32(4, 8, 8, 8), fixedDataSizePerHGCROC=True, type_energy_division='equalShare')) chains.register_concentrator("Onebit", concentrator.create_onebitfraction) ## BE1 chains.register_backend1("Ref2d", clustering2d.create_constrainedtopological) chains.register_backend1("Dummy", clustering2d.create_dummy) ## BE2 chains.register_backend2("Ref3d", clustering3d.create_distance) ### Varies seed threshold chains.register_backend2( "Histomaxth0", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=0.)) chains.register_backend2( "Histomaxth10", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=10.)) chains.register_backend2( "Histomaxth20", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, seed_threshold=20.)) ### Varies clustering distance from L1Trigger.L1THGCal.customClustering import dr_layerbylayer dr_layerbylayer_25 = [dr * 1.25 for dr in dr_layerbylayer] dr_layerbylayer_50 = [dr * 1.5 for dr in dr_layerbylayer] dr_layerbylayer_100 = [dr * 2. for dr in dr_layerbylayer] chains.register_backend2( "Histomaxdr25", lambda p, i: clustering3d.create_histoMax_variableDr( p, i, distances=dr_layerbylayer_25, seed_threshold=10.)) chains.register_backend2(
chains = HGCalTriggerChains() # Register algorithms ## VFE chains.register_vfe("Floatingpoint8", lambda p: vfe.create_compression(p, 4, 4, True)) ## ECON chains.register_concentrator("Threshold", concentrator.create_threshold) chains.register_concentrator("Supertriggercell", concentrator.create_supertriggercell) ## BE1 chains.register_backend1("Dummy", clustering2d.create_dummy) ## BE2 chains.register_backend2( "Histomaxvardr", lambda p, i: clustering3d.create_histoMax_variableDr(p, i)) # Register ntuples # Store gen info only in the reference ntuple ntuple_list_ref = ['event', 'gen', 'multiclusters'] ntuple_list = ['event', 'multiclusters'] chains.register_ntuple( "Genclustersntuple", lambda p, i: ntuple.create_ntuple(p, i, ntuple_list_ref)) chains.register_ntuple("Clustersntuple", lambda p, i: ntuple.create_ntuple(p, i, ntuple_list)) # Register trigger chains concentrator_algos = ['Threshold', 'Supertriggercell'] backend_algos = ['Histomaxvardr'] ## Make cross product fo ECON and BE algos import itertools
chains = HGCalTriggerChains() # Register algorithms ## VFE chains.register_vfe("Floatingpoint8", lambda p : vfe.create_compression(p, 4, 4, True)) ## ECON chains.register_concentrator("Supertriggercell", concentrator.create_supertriggercell) chains.register_concentrator("Threshold", concentrator.create_threshold) ## BE1 chains.register_backend1("Ref2d", clustering2d.create_constrainedtopological) chains.register_backend1("Dummy", clustering2d.create_dummy) ## BE2 chains.register_backend2("Ref3d", clustering3d.create_distance) chains.register_backend2("Histomax", clustering3d.create_histoMax) chains.register_backend2("Histomaxvardrth0", lambda p,i : clustering3d.create_histoMax_variableDr(p,i,seed_threshold=0.)) chains.register_backend2("Histomaxvardrth10", lambda p,i : clustering3d.create_histoMax_variableDr(p,i,seed_threshold=10.)) chains.register_backend2("Histomaxvardrth20", lambda p,i : clustering3d.create_histoMax_variableDr(p,i,seed_threshold=20.)) # Register selector chains.register_selector("Genmatch", selectors.create_genmatch) # Register ntuples # Store gen info only in the reference ntuple ntuple_list_ref = ['event', 'gen', 'multiclusters'] ntuple_list = ['event', 'multiclusters'] chains.register_ntuple("Genclustersntuple", lambda p,i : ntuple.create_ntuple(p,i, ntuple_list_ref)) chains.register_ntuple("Clustersntuple", lambda p,i : ntuple.create_ntuple(p,i, ntuple_list)) # Register trigger chains ## Reference chain chains.register_chain('Floatingpoint8', "Threshold", 'Ref2d', 'Ref3d', 'Genmatch', 'Genclustersntuple') concentrator_algos = ['Supertriggercell', 'Threshold']