def addTauIdAnalyses(process, dataVersion, prefix, prototype, commonSequence,
additionalCounters):
from HiggsAnalysis.HeavyChHiggsToTauNu.HChTools import addAnalysis
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetCorrection as MetCorrection
selections = tauSelections[:]
names = tauSelectionNames[:]
# Remove TCTau from list
tctauIndex = selections.index(tauSelectionCaloTauCutBased)
del selections[tctauIndex]
del names[tctauIndex]
# Remove PF shrinking cone from list
pfShrinkingConeIndex = selections.index(tauSelectionShrinkingConeCutBased)
del selections[pfShrinkingConeIndex]
del names[pfShrinkingConeIndex]
# Remove TaNC from list
tancIndex = selections.index(tauSelectionShrinkingConeTaNCBased)
del selections[tancIndex]
del names[tancIndex]
# HPS loose
hpsLoose = selections.index(tauSelectionHPSLooseTauBased)
#del selections[hpsLoose]
#del names[hpsLoose]
# TCTau can be missing in tau embedding case
try:
caloTauIndex = selections.index(tauSelectionCaloTauCutBased)
del selections[caloTauIndex]
del names[caloTauIndex]
except ValueError:
pass
# Remove combined HPS TaNC from list
combinedHPSTaNCIndex = selections.index(
tauSelectionCombinedHPSTaNCTauBased)
del selections[combinedHPSTaNCIndex]
del names[combinedHPSTaNCIndex]
for selection, name in zip(selections, names):
module = prototype.clone()
module.tauSelection = selection.clone()
# Calculate type 1 MET
(type1Sequence,
type1Met) = MetCorrection.addCorrectedMet(process,
dataVersion,
module.tauSelection,
module.jetSelection,
postfix=name)
module.MET.type1Src = type1Met
seq = cms.Sequence(commonSequence * type1Sequence)
setattr(process, "commonSequence" + name, seq)
addAnalysis(process,
prefix + name,
module,
preSequence=seq,
additionalCounters=additionalCounters)
def addTauIdAnalyses(process, dataVersion, prefix, prototype, commonSequence, additionalCounters):
from HiggsAnalysis.HeavyChHiggsToTauNu.HChTools import addAnalysis
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetCorrection as MetCorrection
selections = tauSelections[:]
names = tauSelectionNames[:]
# Remove TCTau from list
tctauIndex = selections.index(tauSelectionCaloTauCutBased)
del selections[tctauIndex]
del names[tctauIndex]
# Remove PF shrinking cone from list
pfShrinkingConeIndex = selections.index(tauSelectionShrinkingConeCutBased)
del selections[pfShrinkingConeIndex]
del names[pfShrinkingConeIndex]
# Remove TaNC from list
tancIndex = selections.index(tauSelectionShrinkingConeTaNCBased)
del selections[tancIndex]
del names[tancIndex]
# HPS loose
hpsLoose = selections.index(tauSelectionHPSLooseTauBased)
#del selections[hpsLoose]
#del names[hpsLoose]
# TCTau can be missing in tau embedding case
try:
caloTauIndex = selections.index(tauSelectionCaloTauCutBased)
del selections[caloTauIndex]
del names[caloTauIndex]
except ValueError:
pass
# Remove combined HPS TaNC from list
combinedHPSTaNCIndex = selections.index(tauSelectionCombinedHPSTaNCTauBased)
del selections[combinedHPSTaNCIndex]
del names[combinedHPSTaNCIndex]
for selection, name in zip(selections, names):
module = prototype.clone()
module.tauSelection = selection.clone()
# Calculate type 1 MET
(type1Sequence, type1Met) = MetCorrection.addCorrectedMet(process, dataVersion, module.tauSelection, module.jetSelection, postfix=name)
module.MET.type1Src = type1Met
seq = cms.Sequence(
commonSequence *
type1Sequence
)
setattr(process, "commonSequence"+name, seq)
addAnalysis(process, prefix+name, module,
preSequence=seq,
additionalCounters=additionalCounters)
# process.QCDMeasurement.factorization = cms.untracked.PSet()
# mettableCoeff.METTableFactorizationCoefficients.METTables_Coefficients = cms.untracked.vdouble( *(
# 0.0, 0.0, 0.0223602484, 0.0263059, 0.0210332103, 0.016273393, 0.018639329, 0.0176211454, 0.0183615819, 0.0159055926, 0.025789813, 0.0652346858
# ) )
mettableCoeff.METTableFactorizationCoefficients.factorizationSourceName = cms.untracked.string(
"PMET70_afterJetSelection_fromData_v3"
)
process.QCDMeasurement.factorization = mettables.METTableParameters
process.QCDMeasurement.factorization.factorizationTables = mettableCoeff.METTableFactorizationCoefficients
# Type 1 MET
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetCorrection as MetCorrection
(sequence, type1Met) = MetCorrection.addCorrectedMet(
process, dataVersion, process.QCDMeasurement.tauSelection, process.QCDMeasurement.jetSelection
)
process.commonSequence *= sequence
process.QCDMeasurement.MET.type1Src = type1Met
# Prescale fetching done automatically for data
if dataVersion.isData() and not disablePrescales:
process.load("HiggsAnalysis.HeavyChHiggsToTauNu.HPlusPrescaleWeightProducer_cfi")
process.hplusPrescaleWeightProducer.prescaleWeightTriggerResults.setProcessName(dataVersion.getTriggerProcess())
process.hplusPrescaleWeightProducer.prescaleWeightHltPaths = param.trigger.triggers.value()
process.commonSequence *= process.hplusPrescaleWeightProducer
process.QCDMeasurement.prescaleSource = cms.untracked.InputTag("hplusPrescaleWeightProducer")
# Print output
print "\nVertexWeight:", process.QCDMeasurement.vertexWeight
print "\nTrigger:", process.QCDMeasurement.trigger
def addJESVariationAnalysis(process, dataVersion, prefix, name, prototype, additionalCounters, variation, etaVariation, unclusteredEnergyVariationForMET, doJetVariation=True):
variationName = name
tauVariationName = name+"TauVariation"
jetVariationName = name+"JetVariation"
jetsForMetVariation = name+"JetsForMetVariation"
rawMetVariationName = name+"RawMetVariation"
type1MetVariationName = name+"Type1MetVariation"
analysisName = prefix+name
countersName = analysisName+"Counters"
pathName = analysisName+"Path"
# Tau variation
tauv = tauVariation.clone(
src = prototype.tauSelection.src.value(),
energyVariation = variation,
energyEtaVariation = etaVariation,
)
setattr(process, tauVariationName, tauv)
# Recompute type 1 MET on the basis of variated tau. However, use
# the non-variated jets, because the jet variation is taken into
# account in the MET variation. The tau variation is taken into
# account here, because the variation can change the decision of
# which tau to select, and that tau is needed for the jet cleaning
# in the type 1 MET calculation.
tauSelection = prototype.tauSelection.clone(src=tauVariationName)
(type1sequence, type1Met) = MetCorrection.addCorrectedMet(process, dataVersion, tauSelection, prototype.jetSelection, postfix=name)
tauForMetVariation = "selectedPatTausForMetCorr"+name
# Jet variation
jetv = jetVariation.clone(
src = prototype.jetSelection.src.value(),
defaultPlusVariation = variation > 0,
doVariation = doJetVariation,
)
setattr(process, jetVariationName, jetv)
# Select (type I like) jets for MET variation, clean the selected tau from these
cutstr = process.selectedPatJetsForMETtype1p2Corr.cut.value()
cutstr += "&& pt() > %f" % process.patPFJetMETtype1p2Corr.type1JetPtThreshold.value()
jetsForMetv = cms.EDFilter("PATJetSelector",
src = cms.InputTag(jetVariationName),
cut = cms.string(cutstr),
checkOverlaps = cms.PSet(
taus = cms.PSet(
src = cms.InputTag(tauForMetVariation),
algorithm = cms.string("byDeltaR"),
preselection = cms.string(""),
deltaR = cms.double(0.1),
checkRecoComponents = cms.bool(False),
pairCut = cms.string(""),
requireNoOverlaps = cms.bool(True),
)
)
)
setattr(process, jetsForMetVariation, jetsForMetv)
# MET variation
# Use the same code for now (although this is not according to the
# latest recipe for raw). Use the selected tau, and cleaned jets
# passing the type1 selection (both tau and jet inputs should be
# the variated ones)
metrawv = metVariation.clone(
metSrc = prototype.MET.rawSrc.value(),
tauSrc = tauForMetVariation,
jetSrc = jetsForMetVariation,
unclusteredVariation = unclusteredEnergyVariationForMET
)
setattr(process, rawMetVariationName, metrawv)
mettype1v = metVariation.clone(
metSrc = type1Met,
tauSrc = tauForMetVariation,
jetSrc = jetsForMetVariation,
unclusteredVariation = unclusteredEnergyVariationForMET
)
setattr(process, type1MetVariationName, mettype1v)
# Construct the signal analysis module for this variation
# Use variated taus, jets and MET
analysis = prototype.clone()
analysis.tauSelection.src = tauVariationName
analysis.jetSelection.src = jetVariationName
analysis.MET.rawSrc = rawMetVariationName
analysis.MET.type1Src = type1MetVariationName
setattr(process, analysisName, analysis)
# Construct the counters module
counters = cms.EDAnalyzer("HPlusEventCountAnalyzer",
counterNames = cms.untracked.InputTag(analysisName, "counterNames"),
counterInstances = cms.untracked.InputTag(analysisName, "counterInstances")
)
if len(additionalCounters) > 0:
counters.counters = cms.untracked.VInputTag([cms.InputTag(c) for c in additionalCounters])
setattr(process, countersName, counters)
# Construct the path
path = cms.Path(
process.commonSequence
* tauv
* type1sequence
* jetv
* jetsForMetv
* metrawv
* mettype1v
* analysis
* counters
)
setattr(process, pathName, path)
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetTableFactorization_cfi as mettables
import HiggsAnalysis.HeavyChHiggsToTauNu.METTableFactorization_NoFactorization_cfi as mettableCoeff
#process.QCDMeasurement.factorization = cms.untracked.PSet()
#mettableCoeff.METTableFactorizationCoefficients.METTables_Coefficients = cms.untracked.vdouble( *(
#0.0, 0.0, 0.0223602484, 0.0263059, 0.0210332103, 0.016273393, 0.018639329, 0.0176211454, 0.0183615819, 0.0159055926, 0.025789813, 0.0652346858
#) )
mettableCoeff.METTableFactorizationCoefficients.factorizationSourceName = cms.untracked.string(
'PMET70_afterJetSelection_fromData_v3')
process.QCDMeasurement.factorization = mettables.METTableParameters
process.QCDMeasurement.factorization.factorizationTables = mettableCoeff.METTableFactorizationCoefficients
# Type 1 MET
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetCorrection as MetCorrection
(sequence,
type1Met) = MetCorrection.addCorrectedMet(process, dataVersion,
process.QCDMeasurement.tauSelection,
process.QCDMeasurement.jetSelection)
process.commonSequence *= sequence
process.QCDMeasurement.MET.type1Src = type1Met
# Prescale fetching done automatically for data
if dataVersion.isData() and not disablePrescales:
process.load(
"HiggsAnalysis.HeavyChHiggsToTauNu.HPlusPrescaleWeightProducer_cfi")
process.hplusPrescaleWeightProducer.prescaleWeightTriggerResults.setProcessName(
dataVersion.getTriggerProcess())
process.hplusPrescaleWeightProducer.prescaleWeightHltPaths = param.trigger.triggers.value(
)
process.commonSequence *= process.hplusPrescaleWeightProducer
process.QCDMeasurement.prescaleSource = cms.untracked.InputTag(
"hplusPrescaleWeightProducer")
def addJESVariationAnalysis(process,
dataVersion,
prefix,
name,
prototype,
additionalCounters,
variation,
etaVariation,
unclusteredEnergyVariationForMET,
doJetVariation=True):
variationName = name
tauVariationName = name + "TauVariation"
jetVariationName = name + "JetVariation"
jetsForMetVariation = name + "JetsForMetVariation"
rawMetVariationName = name + "RawMetVariation"
type1MetVariationName = name + "Type1MetVariation"
analysisName = prefix + name
countersName = analysisName + "Counters"
pathName = analysisName + "Path"
# Tau variation
tauv = tauVariation.clone(
src=prototype.tauSelection.src.value(),
energyVariation=variation,
energyEtaVariation=etaVariation,
)
setattr(process, tauVariationName, tauv)
# Recompute type 1 MET on the basis of variated tau. However, use
# the non-variated jets, because the jet variation is taken into
# account in the MET variation. The tau variation is taken into
# account here, because the variation can change the decision of
# which tau to select, and that tau is needed for the jet cleaning
# in the type 1 MET calculation.
tauSelection = prototype.tauSelection.clone(src=tauVariationName)
(type1sequence,
type1Met) = MetCorrection.addCorrectedMet(process,
dataVersion,
tauSelection,
prototype.jetSelection,
postfix=name)
tauForMetVariation = "selectedPatTausForMetCorr" + name
# Jet variation
jetv = jetVariation.clone(
src=prototype.jetSelection.src.value(),
defaultPlusVariation=variation > 0,
doVariation=doJetVariation,
)
setattr(process, jetVariationName, jetv)
# Select (type I like) jets for MET variation, clean the selected tau from these
cutstr = process.selectedPatJetsForMETtype1p2Corr.cut.value()
cutstr += "&& pt() > %f" % process.patPFJetMETtype1p2Corr.type1JetPtThreshold.value(
)
jetsForMetv = cms.EDFilter("PATJetSelector",
src=cms.InputTag(jetVariationName),
cut=cms.string(cutstr),
checkOverlaps=cms.PSet(taus=cms.PSet(
src=cms.InputTag(tauForMetVariation),
algorithm=cms.string("byDeltaR"),
preselection=cms.string(""),
deltaR=cms.double(0.1),
checkRecoComponents=cms.bool(False),
pairCut=cms.string(""),
requireNoOverlaps=cms.bool(True),
)))
setattr(process, jetsForMetVariation, jetsForMetv)
# MET variation
# Use the same code for now (although this is not according to the
# latest recipe for raw). Use the selected tau, and cleaned jets
# passing the type1 selection (both tau and jet inputs should be
# the variated ones)
metrawv = metVariation.clone(
metSrc=prototype.MET.rawSrc.value(),
tauSrc=tauForMetVariation,
jetSrc=jetsForMetVariation,
unclusteredVariation=unclusteredEnergyVariationForMET)
setattr(process, rawMetVariationName, metrawv)
mettype1v = metVariation.clone(
metSrc=type1Met,
tauSrc=tauForMetVariation,
jetSrc=jetsForMetVariation,
unclusteredVariation=unclusteredEnergyVariationForMET)
setattr(process, type1MetVariationName, mettype1v)
# Construct the signal analysis module for this variation
# Use variated taus, jets and MET
analysis = prototype.clone()
analysis.tauSelection.src = tauVariationName
analysis.jetSelection.src = jetVariationName
analysis.MET.rawSrc = rawMetVariationName
analysis.MET.type1Src = type1MetVariationName
setattr(process, analysisName, analysis)
# Construct the counters module
counters = cms.EDAnalyzer(
"HPlusEventCountAnalyzer",
counterNames=cms.untracked.InputTag(analysisName, "counterNames"),
counterInstances=cms.untracked.InputTag(analysisName,
"counterInstances"))
if len(additionalCounters) > 0:
counters.counters = cms.untracked.VInputTag(
[cms.InputTag(c) for c in additionalCounters])
setattr(process, countersName, counters)
# Construct the path
path = cms.Path(process.commonSequence * tauv * type1sequence * jetv *
jetsForMetv * metrawv * mettype1v * analysis * counters)
setattr(process, pathName, path)
tauSelection = param.tauSelectionHPSTightTauBased,
jetSelection = param.jetSelection,
MET = param.MET,
bTagging = param.bTagging,
fakeMETVeto = param.fakeMETVeto,
jetTauInvMass = param.jetTauInvMass,
topSelection = param.topSelection,
forwardJetVeto = param.forwardJetVeto,
transverseMassCut = param.transverseMassCut,
EvtTopology = param.EvtTopology,
vertexWeight = param.vertexWeight,
GenParticleAnalysis = param.GenParticleAnalysis,
Tree = param.tree,
)
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetCorrection as MetCorrection
(sequence, type1Met) = MetCorrection.addCorrectedMet(process, dataVersion, process.signalAnalysis.tauSelection, process.signalAnalysis.jetSelection)
process.commonSequence *= sequence
process.signalAnalysis.MET.type1Src = type1Met
# Prescale fetching done automatically for data
if dataVersion.isData() and options.tauEmbeddingInput == 0:
process.load("HiggsAnalysis.HeavyChHiggsToTauNu.HPlusPrescaleWeightProducer_cfi")
process.hplusPrescaleWeightProducer.prescaleWeightTriggerResults.setProcessName(dataVersion.getTriggerProcess())
process.hplusPrescaleWeightProducer.prescaleWeightHltPaths = param.trigger.triggers.value()
process.commonSequence *= process.hplusPrescaleWeightProducer
process.signalAnalysis.prescaleSource = cms.untracked.InputTag("hplusPrescaleWeightProducer")
# Print output
print "Trigger:", process.signalAnalysis.trigger
print "Trigger scale factor mode:", process.signalAnalysis.triggerEfficiencyScaleFactor.mode
print "VertexWeight:",process.signalAnalysis.vertexWeight
param.MET.METCut = cms.untracked.double(0.0)
param.bTagging.discriminatorCut = cms.untracked.double(-999)
param.GlobalMuonVeto.MuonPtCut = cms.untracked.double(999)
# Signal analysis module for the "golden analysis"
import HiggsAnalysis.HeavyChHiggsToTauNu.signalAnalysis as signalAnalysis
process.signalAnalysis = signalAnalysis.createEDFilter(param)
# process.signalAnalysis.GlobalMuonVeto = param.NonIsolatedMuonVeto
# Change default tau algorithm here if needed
#process.signalAnalysis.tauSelection.tauSelectionHPSTightTauBased # HPS Tight is the default
# Add type 1 MET
import HiggsAnalysis.HeavyChHiggsToTauNu.HChMetCorrection as MetCorrection
(sequence,
type1Met) = MetCorrection.addCorrectedMet(process, dataVersion,
process.signalAnalysis.tauSelection,
process.signalAnalysis.jetSelection)
process.commonSequence *= sequence
process.signalAnalysis.MET.type1Src = type1Met
# Prescale fetching done automatically for data
if dataVersion.isData() and options.tauEmbeddingInput == 0:
process.load(
"HiggsAnalysis.HeavyChHiggsToTauNu.HPlusPrescaleWeightProducer_cfi")
process.hplusPrescaleWeightProducer.prescaleWeightTriggerResults.setProcessName(
dataVersion.getTriggerProcess())
process.hplusPrescaleWeightProducer.prescaleWeightHltPaths = param.trigger.triggers.value(
)
process.commonSequence *= process.hplusPrescaleWeightProducer
process.signalAnalysis.prescaleSource = cms.untracked.InputTag(
"hplusPrescaleWeightProducer")
