def AddJetID(proc, jetName="", jetSrc="", jetTableName="", jetSequenceName=""):
"""
Setup modules to calculate PF jet ID
"""
isPUPPIJet = True if "Puppi" in jetName else False
looseJetId = "looseJetId{}".format(jetName)
setattr(proc, looseJetId, proc.looseJetId.clone(
src = jetSrc,
filterParams=proc.looseJetId.filterParams.clone(
version ="WINTER16"
),
)
)
tightJetId = "tightJetId{}".format(jetName)
setattr(proc, tightJetId, proc.tightJetId.clone(
src = jetSrc,
filterParams=proc.tightJetId.filterParams.clone(
version = "SUMMER18{}".format("PUPPI" if isPUPPIJet else "")
),
)
)
tightJetIdLepVeto = "tightJetIdLepVeto{}".format(jetName)
setattr(proc, tightJetIdLepVeto, proc.tightJetIdLepVeto.clone(
src = jetSrc,
filterParams=proc.tightJetIdLepVeto.filterParams.clone(
version = "SUMMER18{}".format("PUPPI" if isPUPPIJet else "")
),
)
)
run2_jme_2016.toModify(getattr(proc, tightJetId) .filterParams, version = "WINTER16" )
run2_jme_2016.toModify(getattr(proc, tightJetIdLepVeto) .filterParams, version = "WINTER16" )
run2_jme_2017.toModify(getattr(proc, tightJetId) .filterParams, version = "WINTER17{}".format("PUPPI" if isPUPPIJet else ""))
run2_jme_2017.toModify(getattr(proc, tightJetIdLepVeto) .filterParams, version = "WINTER17{}".format("PUPPI" if isPUPPIJet else ""))
#
# Save variables as userInts in each jet
#
patJetWithUserData = "{}WithUserData".format(jetSrc)
getattr(proc, patJetWithUserData).userInts.tightId = cms.InputTag(tightJetId)
getattr(proc, patJetWithUserData).userInts.tightIdLepVeto = cms.InputTag(tightJetIdLepVeto)
run2_jme_2016.toModify(getattr(proc, patJetWithUserData).userInts, looseId = cms.InputTag(looseJetId))
#
# Specfiy variables in the jetTable to save in NanoAOD
#
getattr(proc, jetTableName).variables.jetId = Var("userInt('tightId')*2+4*userInt('tightIdLepVeto')",int,doc="Jet ID flags bit1 is loose (always false in 2017 since it does not exist), bit2 is tight, bit3 is tightLepVeto")
run2_jme_2016.toModify(getattr(proc, jetTableName).variables, jetId = Var("userInt('tightIdLepVeto')*4+userInt('tightId')*2+userInt('looseId')",int, doc="Jet ID flags bit1 is loose, bit2 is tight, bit3 is tightLepVeto"))
getattr(proc,jetSequenceName).insert(getattr(proc,jetSequenceName).index(getattr(proc, jetSrc))+1, getattr(proc, tightJetId))
getattr(proc,jetSequenceName).insert(getattr(proc,jetSequenceName).index(getattr(proc, tightJetId))+1, getattr(proc, tightJetIdLepVeto))
setattr(proc,"_"+jetSequenceName+"_2016", getattr(proc,jetSequenceName).copy())
getattr(proc,"_"+jetSequenceName+"_2016").insert(getattr(proc, "_"+jetSequenceName+"_2016").index(getattr(proc, tightJetId)), getattr(proc, looseJetId))
run2_jme_2016.toReplaceWith(getattr(proc,jetSequenceName), getattr(proc, "_"+jetSequenceName+"_2016"))
return proc
def setupAK15(process, runOnMC=False, path=None, runParticleNetMD=True):
# recluster Puppi jets
bTagDiscriminators = [
'pfJetProbabilityBJetTags',
'pfCombinedInclusiveSecondaryVertexV2BJetTags',
'pfDeepCSVJetTags:probb',
'pfDeepCSVJetTags:probbb',
]
subjetBTagDiscriminators = [
'pfJetProbabilityBJetTags',
'pfCombinedInclusiveSecondaryVertexV2BJetTags',
'pfDeepCSVJetTags:probb',
'pfDeepCSVJetTags:probbb',
]
JETCorrLevels = ['L2Relative', 'L3Absolute', 'L2L3Residual']
from PhysicsTools.PFNano.jetToolbox_cff import jetToolbox
jetToolbox(process,
'ak15',
'dummySeqAK15',
'noOutput',
PUMethod='Puppi',
JETCorrPayload='AK8PFPuppi',
JETCorrLevels=JETCorrLevels,
Cut='pt > 160.0 && abs(rapidity()) < 2.4',
runOnMC=runOnMC,
addNsub=True,
maxTau=3,
addSoftDrop=True,
addSoftDropSubjets=True,
subJETCorrPayload='AK4PFPuppi',
subJETCorrLevels=JETCorrLevels,
bTagDiscriminators=bTagDiscriminators,
subjetBTagDiscriminators=subjetBTagDiscriminators)
if runOnMC:
process.ak15GenJetsNoNu.jetPtMin = 100
process.ak15GenJetsNoNuSoftDrop.jetPtMin = 100
from PhysicsTools.PatAlgos.tools.jetTools import updateJetCollection
from RecoBTag.ONNXRuntime.pfParticleNet_cff import _pfParticleNetJetTagsProbs as pfParticleNetJetTagsProbs
from RecoBTag.ONNXRuntime.pfParticleNet_cff import _pfMassDecorrelatedParticleNetJetTagsProbs as pfMassDecorrelatedParticleNetJetTagsProbs
bTagDiscriminators += pfParticleNetJetTagsProbs
if runParticleNetMD:
bTagDiscriminators += pfMassDecorrelatedParticleNetJetTagsProbs
#from RecoBTag.ONNXRuntime.pfDeepBoostedJet_cff import _pfDeepBoostedJetTagsProbs, _pfMassDecorrelatedDeepBoostedJetTagsProbs, _pfDeepBoostedJetTagsMetaDiscrs, _pfMassDecorrelatedDeepBoostedJetTagsMetaDiscrs
#bTagDiscriminators += _pfDeepBoostedJetTagsProbs + _pfMassDecorrelatedDeepBoostedJetTagsProbs + _pfDeepBoostedJetTagsMetaDiscrs + _pfMassDecorrelatedDeepBoostedJetTagsMetaDiscrs
updateJetCollection(
process,
jetSource=cms.InputTag('packedPatJetsAK15PFPuppiSoftDrop'),
rParam=1.5,
jetCorrections=('AK8PFPuppi', cms.vstring(JETCorrLevels), 'None'),
btagDiscriminators=bTagDiscriminators,
postfix='AK15ParticleNet',
)
from RecoBTag.ONNXRuntime.pfParticleNet_cff import pfMassDecorrelatedParticleNetJetTags
if runParticleNetMD:
process.pfParticleNetTagInfosAK15ParticleNet.jet_radius = 1.5
process.pfMassDecorrelatedParticleNetJetTagsAK15ParticleNet = pfMassDecorrelatedParticleNetJetTags.clone(
src=process.pfMassDecorrelatedParticleNetJetTagsAK15ParticleNet.
src,
preprocess_json=
'PhysicsTools/PFNano/data/ParticleNet-MD/ak15/preprocess.json',
model_path=
'PhysicsTools/PFNano/data/ParticleNet-MD/ak15/particle-net.onnx',
)
# src
srcJets = cms.InputTag('selectedUpdatedPatJetsAK15ParticleNet')
# jetID
process.looseJetIdAK15Puppi = cms.EDProducer(
"PatJetIDValueMapProducer",
filterParams=cms.PSet(
version=cms.string('WINTER16'),
quality=cms.string('LOOSE'),
),
src=srcJets)
process.tightJetIdAK15Puppi = cms.EDProducer(
"PatJetIDValueMapProducer",
filterParams=cms.PSet(
version=cms.string('SUMMER18PUPPI'),
quality=cms.string('TIGHT'),
),
src=srcJets)
process.tightJetIdLepVetoAK15Puppi = cms.EDProducer(
"PatJetIDValueMapProducer",
filterParams=cms.PSet(
version=cms.string('SUMMER18PUPPI'),
quality=cms.string('TIGHTLEPVETO'),
),
src=srcJets)
run2_jme_2016.toModify(process.tightJetIdAK15Puppi.filterParams,
version="WINTER16")
run2_jme_2016.toModify(process.tightJetIdLepVetoAK15Puppi.filterParams,
version="WINTER16")
run2_jme_2017.toModify(process.tightJetIdAK15Puppi.filterParams,
version="WINTER17PUPPI")
run2_jme_2017.toModify(process.tightJetIdLepVetoAK15Puppi.filterParams,
version="WINTER17PUPPI")
process.ak15WithUserData = cms.EDProducer(
"PATJetUserDataEmbedder",
src=srcJets,
userFloats=cms.PSet(),
userInts=cms.PSet(
tightId=cms.InputTag("tightJetIdAK15Puppi"),
tightIdLepVeto=cms.InputTag("tightJetIdLepVetoAK15Puppi"),
),
)
run2_jme_2016.toModify(
process.ak15WithUserData.userInts,
looseId=cms.InputTag("looseJetIdAK15Puppi"),
tightIdLepVeto=None,
)
process.ak15Table = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("ak15WithUserData"),
name=cms.string("FatJetAK15"), # AK15Puppi
cut=cms.string(""),
doc=cms.string("ak15 puppi jets"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(False), # this is the main table for the jets
variables=cms.PSet(
P4Vars,
jetId=Var(
"userInt('tightId')*2+4*userInt('tightIdLepVeto')",
int,
doc=
"Jet ID flags bit1 is loose (always false in 2017 since it does not exist), bit2 is tight, bit3 is tightLepVeto"
),
area=Var("jetArea()",
float,
doc="jet catchment area, for JECs",
precision=10),
rawFactor=Var("1.-jecFactor('Uncorrected')",
float,
doc="1 - Factor to get back to raw pT",
precision=6),
nPFConstituents=Var("numberOfDaughters()",
int,
doc="Number of PF candidate constituents"),
tau1=Var("userFloat('NjettinessAK15Puppi:tau1')",
float,
doc="Nsubjettiness (1 axis)",
precision=10),
tau2=Var("userFloat('NjettinessAK15Puppi:tau2')",
float,
doc="Nsubjettiness (2 axis)",
precision=10),
tau3=Var("userFloat('NjettinessAK15Puppi:tau3')",
float,
doc="Nsubjettiness (3 axis)",
precision=10),
msoftdrop=Var("groomedMass()",
float,
doc="Corrected soft drop mass with PUPPI",
precision=10),
btagCSVV2=Var(
"bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",
float,
doc=
"pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",
precision=10),
btagDeepB=Var(
"bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb')",
float,
doc="DeepCSV b+bb tag discriminator",
precision=10),
btagJP=Var(
"bDiscriminator('pfJetProbabilityBJetTags')",
float,
doc="pfJetProbabilityBJetTags b-tag discriminator (aka JP)",
precision=10),
nBHadrons=Var("jetFlavourInfo().getbHadrons().size()",
int,
doc="number of b-hadrons"),
nCHadrons=Var("jetFlavourInfo().getcHadrons().size()",
int,
doc="number of c-hadrons"),
subJetIdx1=Var(
"?nSubjetCollections()>0 && subjets().size()>0?subjets()[0].key():-1",
int,
doc="index of first subjet"),
subJetIdx2=Var(
"?nSubjetCollections()>0 && subjets().size()>1?subjets()[1].key():-1",
int,
doc="index of second subjet"),
))
run2_jme_2016.toModify(
process.ak15Table.variables,
jetId=Var("userInt('tightId')*2+userInt('looseId')",
int,
doc="Jet ID flags bit1 is loose, bit2 is tight"))
process.ak15Table.variables.pt.precision = 10
# add mass-decorelated taggers
for prob in pfParticleNetJetTagsProbs:
name = 'ParticleNet_' + prob.split(':')[1]
setattr(
process.ak15Table.variables, name,
Var("bDiscriminator('%s')" % prob, float, doc=prob, precision=-1))
if runParticleNetMD:
for prob in pfMassDecorrelatedParticleNetJetTagsProbs:
name = 'ParticleNetMD_' + prob.split(':')[1]
name = name.replace('QCDothers', 'QCD') # FIXME
setattr(
process.ak15Table.variables, name,
Var("bDiscriminator('%s')" % prob,
float,
doc=prob,
precision=-1))
process.ak15SubJetTable = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("selectedPatJetsAK15PFPuppiSoftDropPacked",
"SubJets"),
cut=cms.string(""),
name=cms.string("FatJetAK15SubJet"), # AK15PuppiSubJet
doc=cms.string("ak15 puppi subjets"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(False), # this is the main table for the jets
variables=cms.PSet(
P4Vars,
area=Var("jetArea()",
float,
doc="jet catchment area, for JECs",
precision=10),
rawFactor=Var("1.-jecFactor('Uncorrected')",
float,
doc="1 - Factor to get back to raw pT",
precision=6),
btagDeepB=Var(
"bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb')",
float,
doc="DeepCSV b+bb tag discriminator",
precision=10),
btagCSVV2=Var(
"bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",
float,
doc=
" pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",
precision=10),
btagJP=Var(
"bDiscriminator('pfJetProbabilityBJetTags')",
float,
doc="pfJetProbabilityBJetTags b-tag discriminator (aka JP)",
precision=10),
nBHadrons=Var("jetFlavourInfo().getbHadrons().size()",
int,
doc="number of b-hadrons"),
nCHadrons=Var("jetFlavourInfo().getcHadrons().size()",
int,
doc="number of c-hadrons"),
))
process.ak15SubJetTable.variables.pt.precision = 10
process.ak15Task = cms.Task(
process.tightJetIdAK15Puppi,
process.tightJetIdLepVetoAK15Puppi,
process.ak15WithUserData,
process.ak15Table,
process.ak15SubJetTable,
)
if runOnMC:
process.genJetAK15Table = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("ak15GenJetsNoNu"),
cut=cms.string("pt > 100."),
name=cms.string("GenJetAK15"),
doc=cms.string("AK15 GenJets made with visible genparticles"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(
False), # this is the main table for the genjets
variables=cms.PSet(P4Vars, ))
process.genJetAK15Table.variables.pt.precision = 10
process.genSubJetAK15Table = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("ak15GenJetsNoNuSoftDrop", "SubJets"),
cut=cms.string(""),
name=cms.string("GenSubJetAK15"),
doc=cms.string("AK15 Gen-SubJets made with visible genparticles"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(
False), # this is the main table for the genjets
variables=cms.PSet(P4Vars, ))
process.genSubJetAK15Table.variables.pt.precision = 10
process.ak15Task.add(process.genJetAK15Table)
process.ak15Task.add(process.genSubJetAK15Table)
###### hack to avoid circular dependency ######
process.jetMC.remove(process.patJetPartons)
process.ak15Task.add(process.patJetPartons)
###############################################
_ak15Task_2016 = process.ak15Task.copy()
_ak15Task_2016.replace(process.tightJetIdLepVetoAK15Puppi,
process.looseJetIdAK15Puppi)
run2_jme_2016.toReplaceWith(process.ak15Task, _ak15Task_2016)
if path is None:
process.schedule.associate(process.ak15Task)
else:
getattr(process, path).associate(process.ak15Task)
def setupCustomizedAK8(process, runOnMC=False, path=None):
# recluster Puppi jets
bTagDiscriminators = [
'pfCombinedInclusiveSecondaryVertexV2BJetTags',
'pfBoostedDoubleSecondaryVertexAK8BJetTags',
]
subjetBTagDiscriminators = [
'pfCombinedInclusiveSecondaryVertexV2BJetTags',
'pfDeepCSVJetTags:probb',
'pfDeepCSVJetTags:probbb',
]
JETCorrLevels = ['L2Relative', 'L3Absolute', 'L2L3Residual']
from PhysicsTools.NanoTuples.jetToolbox_cff import jetToolbox
jetToolbox(process,
'ak8',
'dummySeqAK8',
'noOutput',
PUMethod='Puppi',
JETCorrPayload='AK8PFPuppi',
JETCorrLevels=JETCorrLevels,
Cut='pt > 170.0 && abs(rapidity()) < 2.4',
runOnMC=runOnMC,
addNsub=True,
maxTau=3,
addSoftDrop=True,
addSoftDropSubjets=True,
subJETCorrPayload='AK4PFPuppi',
subJETCorrLevels=JETCorrLevels,
bTagDiscriminators=bTagDiscriminators,
subjetBTagDiscriminators=subjetBTagDiscriminators)
if runOnMC:
process.ak8GenJetsNoNu.jetPtMin = 100
process.ak8GenJetsNoNuSoftDrop.jetPtMin = 100
from PhysicsTools.PatAlgos.tools.jetTools import updateJetCollection
from RecoBTag.ONNXRuntime.pfDeepBoostedJet_cff import _pfDeepBoostedJetTagsProbs, _pfMassDecorrelatedDeepBoostedJetTagsProbs
from RecoBTag.MXNet.pfParticleNet_cff import _pfParticleNetJetTagsProbs, _pfMassDecorrelatedParticleNetJetTagsProbs
updateJetCollection(
process,
jetSource=cms.InputTag('packedPatJetsAK8PFPuppiSoftDrop'),
rParam=0.8,
jetCorrections=('AK8PFPuppi', cms.vstring(JETCorrLevels), 'None'),
btagDiscriminators=bTagDiscriminators + _pfDeepBoostedJetTagsProbs +
_pfMassDecorrelatedDeepBoostedJetTagsProbs +
_pfParticleNetJetTagsProbs +
_pfMassDecorrelatedParticleNetJetTagsProbs,
postfix='AK8WithPuppiDaughters',
)
# src
srcJets = cms.InputTag('selectedUpdatedPatJetsAK8WithPuppiDaughters')
# jetID
process.looseJetIdCustomAK8 = cms.EDProducer(
"PatJetIDValueMapProducer",
filterParams=cms.PSet(
version=cms.string('WINTER16'),
quality=cms.string('LOOSE'),
),
src=srcJets)
process.tightJetIdCustomAK8 = cms.EDProducer(
"PatJetIDValueMapProducer",
filterParams=cms.PSet(
version=cms.string('SUMMER18PUPPI'),
quality=cms.string('TIGHT'),
),
src=srcJets)
process.tightJetIdLepVetoCustomAK8 = cms.EDProducer(
"PatJetIDValueMapProducer",
filterParams=cms.PSet(
version=cms.string('SUMMER18PUPPI'),
quality=cms.string('TIGHTLEPVETO'),
),
src=srcJets)
run2_jme_2016.toModify(process.tightJetIdCustomAK8.filterParams,
version="WINTER16")
run2_jme_2016.toModify(process.tightJetIdLepVetoCustomAK8.filterParams,
version="WINTER16")
run2_jme_2017.toModify(process.tightJetIdCustomAK8.filterParams,
version="WINTER17PUPPI")
run2_jme_2017.toModify(process.tightJetIdLepVetoCustomAK8.filterParams,
version="WINTER17PUPPI")
process.customAK8WithUserData = cms.EDProducer(
"PATJetUserDataEmbedder",
src=srcJets,
userFloats=cms.PSet(),
userInts=cms.PSet(
tightId=cms.InputTag("tightJetIdCustomAK8"),
tightIdLepVeto=cms.InputTag("tightJetIdLepVetoCustomAK8"),
),
)
run2_jme_2016.toModify(
process.customAK8WithUserData.userInts,
looseId=cms.InputTag("looseJetIdCustomAK8"),
tightIdLepVeto=None,
)
process.customAK8Table = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("customAK8WithUserData"),
name=cms.string("CustomAK8Puppi"),
cut=cms.string(""),
doc=cms.string("reclustered ak8 puppi jets"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(False), # this is the main table for the jets
variables=cms.PSet(
P4Vars,
jetId=Var(
"userInt('tightId')*2+4*userInt('tightIdLepVeto')",
int,
doc=
"Jet ID flags bit1 is loose (always false in 2017 since it does not exist), bit2 is tight, bit3 is tightLepVeto"
),
area=Var("jetArea()",
float,
doc="jet catchment area, for JECs",
precision=10),
rawFactor=Var("1.-jecFactor('Uncorrected')",
float,
doc="1 - Factor to get back to raw pT",
precision=6),
nPFConstituents=Var("numberOfDaughters()",
int,
doc="Number of PF candidate constituents"),
tau1=Var("userFloat('NjettinessAK8Puppi:tau1')",
float,
doc="Nsubjettiness (1 axis)",
precision=10),
tau2=Var("userFloat('NjettinessAK8Puppi:tau2')",
float,
doc="Nsubjettiness (2 axis)",
precision=10),
tau3=Var("userFloat('NjettinessAK8Puppi:tau3')",
float,
doc="Nsubjettiness (3 axis)",
precision=10),
msoftdrop=Var("groomedMass()",
float,
doc="Corrected soft drop mass with PUPPI",
precision=10),
btagCSVV2=Var(
"bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",
float,
doc=
" pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",
precision=10),
btagHbb=Var(
"bDiscriminator('pfBoostedDoubleSecondaryVertexAK8BJetTags')",
float,
doc="Higgs to BB tagger discriminator",
precision=10),
nBHadrons=Var("jetFlavourInfo().getbHadrons().size()",
int,
doc="number of b-hadrons"),
nCHadrons=Var("jetFlavourInfo().getcHadrons().size()",
int,
doc="number of c-hadrons"),
subJetIdx1=Var(
"?nSubjetCollections()>0 && subjets().size()>0?subjets()[0].key():-1",
int,
doc="index of first subjet"),
subJetIdx2=Var(
"?nSubjetCollections()>0 && subjets().size()>1?subjets()[1].key():-1",
int,
doc="index of second subjet"),
))
run2_jme_2016.toModify(
process.customAK8Table.variables,
jetId=Var("userInt('tightId')*2+userInt('looseId')",
int,
doc="Jet ID flags bit1 is loose, bit2 is tight"))
process.customAK8Table.variables.pt.precision = 10
# add DeepAK8 scores: nominal
for prob in _pfDeepBoostedJetTagsProbs:
name = 'DeepAK8_' + prob.split(':')[1]
setattr(
process.customAK8Table.variables, name,
Var("bDiscriminator('%s')" % prob, float, doc=prob, precision=-1))
# add DeepAK8 scores: mass decorrelated
for prob in _pfMassDecorrelatedDeepBoostedJetTagsProbs:
name = 'DeepAK8MD_' + prob.split(':')[1]
setattr(
process.customAK8Table.variables, name,
Var("bDiscriminator('%s')" % prob, float, doc=prob, precision=-1))
# add ParticleNet nominal taggers
for prob in _pfParticleNetJetTagsProbs:
name = 'ParticleNet_' + prob.split(':')[1]
setattr(
process.customAK8Table.variables, name,
Var("bDiscriminator('%s')" % prob, float, doc=prob, precision=-1))
# add ParticleNet mass-decorelated taggers
for prob in _pfMassDecorrelatedParticleNetJetTagsProbs:
name = 'ParticleNetMD_' + prob.split(':')[1]
setattr(
process.customAK8Table.variables, name,
Var("bDiscriminator('%s')" % prob, float, doc=prob, precision=-1))
process.customAK8SubJetTable = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("selectedPatJetsAK8PFPuppiSoftDropPacked", "SubJets"),
cut=cms.string(""),
name=cms.string("CustomAK8PuppiSubJet"),
doc=cms.string("reculstered ak8 puppi subjets"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(False), # this is the main table for the jets
variables=cms.PSet(
P4Vars,
area=Var("jetArea()",
float,
doc="jet catchment area, for JECs",
precision=10),
rawFactor=Var("1.-jecFactor('Uncorrected')",
float,
doc="1 - Factor to get back to raw pT",
precision=6),
btagDeepB=Var(
"bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb')",
float,
doc="DeepCSV b+bb tag discriminator",
precision=10),
btagCSVV2=Var(
"bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",
float,
doc=
" pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",
precision=10),
nBHadrons=Var("jetFlavourInfo().getbHadrons().size()",
int,
doc="number of b-hadrons"),
nCHadrons=Var("jetFlavourInfo().getcHadrons().size()",
int,
doc="number of c-hadrons"),
))
process.customAK8SubJetTable.variables.pt.precision = 10
process.customizedAK8Task = cms.Task(process.tightJetIdCustomAK8,
process.tightJetIdLepVetoCustomAK8,
process.customAK8WithUserData,
process.customAK8Table,
process.customAK8SubJetTable)
if runOnMC:
process.customGenJetAK8Table = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("ak8GenJetsNoNu"),
cut=cms.string("pt > 100."),
name=cms.string("CustomGenJetAK8"),
doc=cms.string("AK8 GenJets made with visible genparticles"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(
False), # this is the main table for the genjets
variables=cms.PSet(P4Vars, ))
process.customGenJetAK8Table.variables.pt.precision = 10
process.customGenSubJetAK8Table = cms.EDProducer(
"SimpleCandidateFlatTableProducer",
src=cms.InputTag("ak8GenJetsNoNuSoftDrop", "SubJets"),
cut=cms.string(""),
name=cms.string("CustomGenSubJetAK8"),
doc=cms.string("AK8 Gen-SubJets made with visible genparticles"),
singleton=cms.bool(False), # the number of entries is variable
extension=cms.bool(
False), # this is the main table for the genjets
variables=cms.PSet(P4Vars, ))
process.customGenSubJetAK8Table.variables.pt.precision = 10
process.customizedAK8Task.add(process.customGenJetAK8Table)
process.customizedAK8Task.add(process.customGenSubJetAK8Table)
_customizedAK8Task_80X = process.customizedAK8Task.copy()
_customizedAK8Task_80X.replace(process.tightJetIdLepVetoCustomAK8,
process.looseJetIdCustomAK8)
run2_jme_2016.toReplaceWith(process.customizedAK8Task,
_customizedAK8Task_80X)
if path is None:
process.schedule.associate(process.customizedAK8Task)
else:
getattr(process, path).associate(process.customizedAK8Task)
#before cross linking
jetSequence = cms.Sequence(jetCorrFactorsNano + updatedJets + tightJetId +
tightJetIdLepVeto + bJetVars + qgtagger + jercVars +
pileupJetId94X + pileupJetId102X +
updatedJetsWithUserData + jetCorrFactorsAK8 +
updatedJetsAK8 + tightJetIdAK8 +
tightJetIdLepVetoAK8 + updatedJetsAK8WithUserData +
chsForSATkJets + softActivityJets +
softActivityJets2 + softActivityJets5 +
softActivityJets10 + finalJets + finalJetsAK8)
_jetSequence_2016 = jetSequence.copy()
_jetSequence_2016.insert(_jetSequence_2016.index(tightJetId), looseJetId)
_jetSequence_2016.insert(_jetSequence_2016.index(tightJetIdAK8), looseJetIdAK8)
run2_jme_2016.toReplaceWith(jetSequence, _jetSequence_2016)
#after lepton collections have been run
jetLepSequence = cms.Sequence(lepInJetVars)
#after cross linkining
jetTables = cms.Sequence(bjetNN + cjetNN + jetTable + fatJetTable +
subJetTable + saJetTable + saTable)
#MC only producers and tables
jetMC = cms.Sequence(jetMCTable + genJetTable + patJetPartons +
genJetFlavourTable + genJetAK8Table +
genJetAK8FlavourAssociation + genJetAK8FlavourTable +
fatJetMCTable + genSubJetAK8Table + subjetMCTable)
_jetMC_pre94X = jetMC.copy()
_jetMC_pre94X.insert(_jetMC_pre94X.index(genJetFlavourTable),
## The muon bad track filter (2016) ________________________________________________||
from RecoMET.METFilters.BadPFMuonFilter_cfi import *
## The muon bad track filter with Dz cut (2020) _____________________________________||
from RecoMET.METFilters.BadPFMuonDzFilter_cfi import *
#HF noise filter
from RecoMET.METFilters.hfNoisyHitsFilter_cfi import *
metFilters = cms.Sequence(
goodVertices * globalSuperTightHalo2016Filter *
HBHENoiseFilterResultProducer * HBHENoiseFilter * HBHENoiseIsoFilter *
EcalDeadCellTriggerPrimitiveFilter * BadPFMuonFilter * BadPFMuonDzFilter *
hfNoisyHitsFilter * eeBadScFilter * ecalBadCalibFilter)
from Configuration.Eras.Modifier_phase2_hgcal_cff import phase2_hgcal
phase2_hgcal.toReplaceWith(
metFilters,
metFilters.copyAndExclude([
HBHENoiseFilterResultProducer,
HBHENoiseFilter,
HBHENoiseIsoFilter, # No hcalnoise for hgcal
eeBadScFilter # No EE
]))
from Configuration.Eras.Modifier_run2_jme_2016_cff import run2_jme_2016
run2_jme_2016.toReplaceWith(
metFilters,
metFilters.copyAndExclude([ecalBadCalibFilter, hfNoisyHitsFilter]))