Esempi in Python per create_histoMax_variableDr

Esempio n. 1

    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

Esempio n. 2

# 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))

Esempio n. 3

File: runNtuple_v10.5.py Progetto: mcepeda/submission

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(

Esempio n. 4

File: testHGCalL1T_multialgo_cfg.py Progetto: Moanwar/cmssw

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

Esempio n. 5

File: produce_ntuple_multialgos_reduced_genmatch_v9_cfg.py Progetto: PFCal-dev/HGCTPGNtupleProduction

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(

Esempio n. 6

File: hgcal_l1t_ntupliser_v9_cfg.py Progetto: jonathon-langford/hgcal_l1t_egid

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

Esempio n. 7

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']