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']