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jets_cff.py
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1 import FWCore.ParameterSet.Config as cms
2 from PhysicsTools.NanoAOD.nano_eras_cff import *
3 
4 from PhysicsTools.NanoAOD.common_cff import *
5 from RecoJets.JetProducers.ak4PFJetsBetaStar_cfi import *
6 
7 ##################### User floats producers, selectors ##########################
8 from RecoJets.JetProducers.ak4PFJets_cfi import ak4PFJets
9 
10 chsForSATkJets = cms.EDFilter("CandPtrSelector", src = cms.InputTag("packedPFCandidates"), cut = cms.string('charge()!=0 && pvAssociationQuality()>=5 && vertexRef().key()==0'))
11 softActivityJets = ak4PFJets.clone(src = 'chsForSATkJets', doAreaFastjet = False, jetPtMin=1)
12 softActivityJets10 = cms.EDFilter("CandPtrSelector", src = cms.InputTag("softActivityJets"), cut = cms.string('pt>10'))
13 softActivityJets5 = cms.EDFilter("CandPtrSelector", src = cms.InputTag("softActivityJets"), cut = cms.string('pt>5'))
14 softActivityJets2 = cms.EDFilter("CandPtrSelector", src = cms.InputTag("softActivityJets"), cut = cms.string('pt>2'))
15 
16 from PhysicsTools.PatAlgos.recoLayer0.jetCorrFactors_cfi import *
17 # Note: Safe to always add 'L2L3Residual' as MC contains dummy L2L3Residual corrections (always set to 1)
18 # (cf. https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookJetEnergyCorrections#CMSSW_7_6_4_and_above )
19 jetCorrFactorsNano = patJetCorrFactors.clone(src='slimmedJets',
20  levels = cms.vstring('L1FastJet',
21  'L2Relative',
22  'L3Absolute',
23  'L2L3Residual'),
24  primaryVertices = cms.InputTag("offlineSlimmedPrimaryVertices"),
25 )
26 jetCorrFactorsAK8 = patJetCorrFactors.clone(src='slimmedJetsAK8',
27  levels = cms.vstring('L1FastJet',
28  'L2Relative',
29  'L3Absolute',
30  'L2L3Residual'),
31  payload = cms.string('AK8PFPuppi'),
32  primaryVertices = cms.InputTag("offlineSlimmedPrimaryVertices"),
33 )
34 run2_miniAOD_80XLegacy.toModify(jetCorrFactorsAK8, payload = cms.string('AK8PFchs')) # ak8PFJetsCHS in 2016 80X miniAOD
35 
36 from PhysicsTools.PatAlgos.producersLayer1.jetUpdater_cfi import *
37 
38 updatedJets = updatedPatJets.clone(
39  addBTagInfo=False,
40  jetSource='slimmedJets',
41  jetCorrFactorsSource=cms.VInputTag(cms.InputTag("jetCorrFactorsNano") ),
42 )
43 
44 updatedJetsAK8 = updatedPatJets.clone(
45  addBTagInfo=False,
46  jetSource='slimmedJetsAK8',
47  jetCorrFactorsSource=cms.VInputTag(cms.InputTag("jetCorrFactorsAK8") ),
48 )
49 
50 
51 looseJetId = cms.EDProducer("PatJetIDValueMapProducer",
52  filterParams=cms.PSet(
53  version = cms.string('WINTER16'),
54  quality = cms.string('LOOSE'),
55  ),
56  src = cms.InputTag("updatedJets")
57 )
58 tightJetId = cms.EDProducer("PatJetIDValueMapProducer",
59  filterParams=cms.PSet(
60  version = cms.string('SUMMER18'),
61  quality = cms.string('TIGHT'),
62  ),
63  src = cms.InputTag("updatedJets")
64 )
65 tightJetIdLepVeto = cms.EDProducer("PatJetIDValueMapProducer",
66  filterParams=cms.PSet(
67  version = cms.string('SUMMER18'),
68  quality = cms.string('TIGHTLEPVETO'),
69  ),
70  src = cms.InputTag("updatedJets")
71 )
72 run2_jme_2016.toModify( tightJetId.filterParams, version = "WINTER16" )
73 run2_jme_2016.toModify( tightJetIdLepVeto.filterParams, version = "WINTER16" )
74 run2_jme_2017.toModify( tightJetId.filterParams, version = "WINTER17" )
75 run2_jme_2017.toModify( tightJetIdLepVeto.filterParams, version = "WINTER17" )
76 for modifier in run2_nanoAOD_106Xv1, run2_nanoAOD_106Xv2, run2_miniAOD_devel:
77  modifier.toModify( tightJetId.filterParams, version = "RUN2ULCHS" )
78  modifier.toModify( tightJetIdLepVeto.filterParams, version = "RUN2ULCHS" )
79 (run2_jme_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( tightJetId.filterParams, version = "RUN2UL16CHS" )
80 (run2_jme_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( tightJetIdLepVeto.filterParams, version = "RUN2UL16CHS" )
81 
82 
83 looseJetIdAK8 = cms.EDProducer("PatJetIDValueMapProducer",
84  filterParams=cms.PSet(
85  version = cms.string('WINTER16'),
86  quality = cms.string('LOOSE'),
87  ),
88  src = cms.InputTag("updatedJetsAK8")
89 )
90 tightJetIdAK8 = cms.EDProducer("PatJetIDValueMapProducer",
91  filterParams=cms.PSet(
92  version = cms.string('SUMMER18PUPPI'),
93  quality = cms.string('TIGHT'),
94  ),
95  src = cms.InputTag("updatedJetsAK8")
96 )
97 tightJetIdLepVetoAK8 = cms.EDProducer("PatJetIDValueMapProducer",
98  filterParams=cms.PSet(
99  version = cms.string('SUMMER18PUPPI'),
100  quality = cms.string('TIGHTLEPVETO'),
101  ),
102  src = cms.InputTag("updatedJetsAK8")
103 )
104 run2_jme_2016.toModify( tightJetIdAK8.filterParams, version = "WINTER16" )
105 run2_jme_2016.toModify( tightJetIdLepVetoAK8.filterParams, version = "WINTER16" )
106 run2_jme_2017.toModify( tightJetIdAK8.filterParams, version = "WINTER17PUPPI" )
107 run2_jme_2017.toModify( tightJetIdLepVetoAK8.filterParams, version = "WINTER17PUPPI" )
108 for modifier in run2_nanoAOD_106Xv1, run2_nanoAOD_106Xv2, run2_miniAOD_devel:
109  modifier.toModify( tightJetIdAK8.filterParams, version = "RUN2ULPUPPI" )
110  modifier.toModify( tightJetIdLepVetoAK8.filterParams, version = "RUN2ULPUPPI" )
111 (run2_jme_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( tightJetIdAK8.filterParams, version = "RUN2UL16PUPPI" )
112 (run2_jme_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( tightJetIdLepVetoAK8.filterParams, version = "RUN2UL16PUPPI" )
113 
114 
115 bJetVars = cms.EDProducer("JetRegressionVarProducer",
116  pvsrc = cms.InputTag("offlineSlimmedPrimaryVertices"),
117  src = cms.InputTag("updatedJets"),
118  svsrc = cms.InputTag("slimmedSecondaryVertices"),
119  gpsrc = cms.InputTag("prunedGenParticles"),
120  #musrc = cms.InputTag("slimmedMuons"),
121  #elesrc = cms.InputTag("slimmedElectrons")
122 )
123 
124 jercVars = cms.EDProducer("BetaStarPackedCandidateVarProducer",
125  srcJet = cms.InputTag("updatedJets"),
126  srcPF = cms.InputTag("packedPFCandidates"),
127  maxDR = cms.double(0.4)
128 )
129 
130 updatedJetsWithUserData = cms.EDProducer("PATJetUserDataEmbedder",
131  src = cms.InputTag("updatedJets"),
132  userFloats = cms.PSet(
133  leadTrackPt = cms.InputTag("bJetVars:leadTrackPt"),
134  leptonPtRel = cms.InputTag("bJetVars:leptonPtRel"),
135  leptonPtRatio = cms.InputTag("bJetVars:leptonPtRatio"),
136  leptonPtRelInv = cms.InputTag("bJetVars:leptonPtRelInv"),
137  leptonPtRelv0 = cms.InputTag("bJetVars:leptonPtRelv0"),
138  leptonPtRatiov0 = cms.InputTag("bJetVars:leptonPtRatiov0"),
139  leptonPtRelInvv0 = cms.InputTag("bJetVars:leptonPtRelInvv0"),
140  leptonDeltaR = cms.InputTag("bJetVars:leptonDeltaR"),
141  leptonPt = cms.InputTag("bJetVars:leptonPt"),
142  vtxPt = cms.InputTag("bJetVars:vtxPt"),
143  vtxMass = cms.InputTag("bJetVars:vtxMass"),
144  vtx3dL = cms.InputTag("bJetVars:vtx3dL"),
145  vtx3deL = cms.InputTag("bJetVars:vtx3deL"),
146  ptD = cms.InputTag("bJetVars:ptD"),
147  genPtwNu = cms.InputTag("bJetVars:genPtwNu"),
148  qgl = cms.InputTag('qgtagger:qgLikelihood'),
149  puId94XDisc = cms.InputTag('pileupJetId94X:fullDiscriminant'),
150  puId102XDisc = cms.InputTag('pileupJetId102X:fullDiscriminant'),
151  puId106XUL16Disc = cms.InputTag('pileupJetId106XUL16:fullDiscriminant'),
152  puId106XUL16APVDisc = cms.InputTag('pileupJetId106XUL16APV:fullDiscriminant'),
153  puId106XUL17Disc = cms.InputTag('pileupJetId106XUL17:fullDiscriminant'),
154  puId106XUL18Disc = cms.InputTag('pileupJetId106XUL18:fullDiscriminant'),
155  chFPV0EF = cms.InputTag("jercVars:chargedFromPV0EnergyFraction"),
156  ),
157  userInts = cms.PSet(
158  tightId = cms.InputTag("tightJetId"),
159  tightIdLepVeto = cms.InputTag("tightJetIdLepVeto"),
160  vtxNtrk = cms.InputTag("bJetVars:vtxNtrk"),
161  leptonPdgId = cms.InputTag("bJetVars:leptonPdgId"),
162  puId106XUL16Id = cms.InputTag('pileupJetId106XUL16:fullId'),
163  puId106XUL16APVId = cms.InputTag('pileupJetId106XUL16APV:fullId'),
164  puId106XUL17Id = cms.InputTag('pileupJetId106XUL17:fullId'),
165  puId106XUL18Id = cms.InputTag('pileupJetId106XUL18:fullId'),
166  ),
167 )
168 run2_jme_2016.toModify(updatedJetsWithUserData.userInts,
169  looseId = cms.InputTag("looseJetId"),
170 )
171 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify(updatedJetsWithUserData.userFloats,
172  chFPV1EF = cms.InputTag("jercVars:chargedFromPV1EnergyFraction"),
173  chFPV2EF = cms.InputTag("jercVars:chargedFromPV2EnergyFraction"),
174  chFPV3EF = cms.InputTag("jercVars:chargedFromPV3EnergyFraction"),
175 )
176 
177 updatedJetsAK8WithUserData = cms.EDProducer("PATJetUserDataEmbedder",
178  src = cms.InputTag("updatedJetsAK8"),
179  userInts = cms.PSet(
180  tightId = cms.InputTag("tightJetIdAK8"),
181  tightIdLepVeto = cms.InputTag("tightJetIdLepVetoAK8"),
182  ),
183 )
184 run2_jme_2016.toModify(updatedJetsAK8WithUserData.userInts,
185  looseId = cms.InputTag("looseJetIdAK8"),
186 )
187 
188 
189 finalJets = cms.EDFilter("PATJetRefSelector",
190  src = cms.InputTag("updatedJetsWithUserData"),
191  cut = cms.string("pt > 15")
192 )
193 
194 finalJetsAK8 = cms.EDFilter("PATJetRefSelector",
195  src = cms.InputTag("updatedJetsAK8WithUserData"),
196  cut = cms.string("pt > 170")
197 )
198 
199 lepInJetVars = cms.EDProducer("LepInJetProducer",
200  src = cms.InputTag("updatedJetsAK8WithUserData"),
201  srcEle = cms.InputTag("finalElectrons"),
202  srcMu = cms.InputTag("finalMuons")
203 )
204 
205 
206 
207 ##################### Tables for final output and docs ##########################
208 
209 
210 
211 jetTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
212  src = cms.InputTag("linkedObjects","jets"),
213  cut = cms.string(""), #we should not filter on cross linked collections
214  name = cms.string("Jet"),
215  doc = cms.string("slimmedJets, i.e. ak4 PFJets CHS with JECs applied, after basic selection (" + finalJets.cut.value()+")"),
216  singleton = cms.bool(False), # the number of entries is variable
217  extension = cms.bool(False), # this is the main table for the jets
218  externalVariables = cms.PSet(
219  bRegCorr = ExtVar(cms.InputTag("bjetNN:corr"),float, doc="pt correction for b-jet energy regression",precision=10),
220  bRegRes = ExtVar(cms.InputTag("bjetNN:res"),float, doc="res on pt corrected with b-jet regression",precision=6),
221  cRegCorr = ExtVar(cms.InputTag("cjetNN:corr"),float, doc="pt correction for c-jet energy regression",precision=10),
222  cRegRes = ExtVar(cms.InputTag("cjetNN:res"),float, doc="res on pt corrected with c-jet regression",precision=6),
223  ),
224  variables = cms.PSet(P4Vars,
225  area = Var("jetArea()", float, doc="jet catchment area, for JECs",precision=10),
226  nMuons = Var("?hasOverlaps('muons')?overlaps('muons').size():0", int, doc="number of muons in the jet"),
227  muonIdx1 = Var("?overlaps('muons').size()>0?overlaps('muons')[0].key():-1", int, doc="index of first matching muon"),
228  muonIdx2 = Var("?overlaps('muons').size()>1?overlaps('muons')[1].key():-1", int, doc="index of second matching muon"),
229  electronIdx1 = Var("?overlaps('electrons').size()>0?overlaps('electrons')[0].key():-1", int, doc="index of first matching electron"),
230  electronIdx2 = Var("?overlaps('electrons').size()>1?overlaps('electrons')[1].key():-1", int, doc="index of second matching electron"),
231  nElectrons = Var("?hasOverlaps('electrons')?overlaps('electrons').size():0", int, doc="number of electrons in the jet"),
232  btagDeepB = Var("?(bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb'))>=0?bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb'):-1",float,doc="DeepCSV b+bb tag discriminator",precision=10),
233  btagDeepFlavB = Var("bDiscriminator('pfDeepFlavourJetTags:probb')+bDiscriminator('pfDeepFlavourJetTags:probbb')+bDiscriminator('pfDeepFlavourJetTags:problepb')",float,doc="DeepJet b+bb+lepb tag discriminator",precision=10),
234  btagCSVV2 = Var("bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",float,doc=" pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",precision=10),
235  btagDeepCvL = Var("?bDiscriminator('pfDeepCSVJetTags:probc')>=0?bDiscriminator('pfDeepCSVJetTags:probc')/(bDiscriminator('pfDeepCSVJetTags:probc')+bDiscriminator('pfDeepCSVJetTags:probudsg')):-1", float,doc="DeepCSV c vs udsg discriminator",precision=10),
236  btagDeepCvB = Var("?bDiscriminator('pfDeepCSVJetTags:probc')>=0?bDiscriminator('pfDeepCSVJetTags:probc')/(bDiscriminator('pfDeepCSVJetTags:probc')+bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb')):-1",float,doc="DeepCSV c vs b+bb discriminator",precision=10),
237  btagDeepFlavCvL = Var("?(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probuds')+bDiscriminator('pfDeepFlavourJetTags:probg'))>0?bDiscriminator('pfDeepFlavourJetTags:probc')/(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probuds')+bDiscriminator('pfDeepFlavourJetTags:probg')):-1",float,doc="DeepJet c vs uds+g discriminator",precision=10),
238  btagDeepFlavCvB = Var("?(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probb')+bDiscriminator('pfDeepFlavourJetTags:probbb')+bDiscriminator('pfDeepFlavourJetTags:problepb'))>0?bDiscriminator('pfDeepFlavourJetTags:probc')/(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probb')+bDiscriminator('pfDeepFlavourJetTags:probbb')+bDiscriminator('pfDeepFlavourJetTags:problepb')):-1",float,doc="DeepJet c vs b+bb+lepb discriminator",precision=10),
239  btagDeepFlavQG = Var("?(bDiscriminator('pfDeepFlavourJetTags:probg')+bDiscriminator('pfDeepFlavourJetTags:probuds'))>0?bDiscriminator('pfDeepFlavourJetTags:probg')/(bDiscriminator('pfDeepFlavourJetTags:probg')+bDiscriminator('pfDeepFlavourJetTags:probuds')):-1",float,doc="DeepJet g vs uds discriminator",precision=10),
240  puIdDisc = Var("userFloat('puId106XUL18Disc')", float,doc="Pileup ID discriminant with 106X (2018) training",precision=10),
241  puId = Var("userInt('puId106XUL18Id')", int,doc="Pileup ID flags with 106X (2018) training"),
242  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"),
243  qgl = Var("?userFloat('qgl')>0?userFloat('qgl'):-1",float,doc="Quark vs Gluon likelihood discriminator",precision=10),
244  nConstituents = Var("numberOfDaughters()","uint8",doc="Number of particles in the jet"),
245  rawFactor = Var("1.-jecFactor('Uncorrected')",float,doc="1 - Factor to get back to raw pT",precision=6),
246  chHEF = Var("chargedHadronEnergyFraction()", float, doc="charged Hadron Energy Fraction", precision= 6),
247  neHEF = Var("neutralHadronEnergyFraction()", float, doc="neutral Hadron Energy Fraction", precision= 6),
248  chEmEF = Var("chargedEmEnergyFraction()", float, doc="charged Electromagnetic Energy Fraction", precision= 6),
249  neEmEF = Var("neutralEmEnergyFraction()", float, doc="neutral Electromagnetic Energy Fraction", precision= 6),
250  muEF = Var("muonEnergyFraction()", float, doc="muon Energy Fraction", precision= 6),
251  chFPV0EF = Var("userFloat('chFPV0EF')", float, doc="charged fromPV==0 Energy Fraction (energy excluded from CHS jets). Previously called betastar.", precision= 6),
252  )
253 )
254 
255 #jets are not as precise as muons
256 jetTable.variables.pt.precision=10
257 
258 ### Era dependent customization
259 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016, run2_nanoAOD_94XMiniAODv1, run2_nanoAOD_94XMiniAODv2, run2_nanoAOD_102Xv1, run2_nanoAOD_106Xv1:
260  # Deprecated after 106X
261  modifier.toModify(jetTable.variables,
262  btagCMVA = Var("bDiscriminator('pfCombinedMVAV2BJetTags')",float,doc="CMVA V2 btag discriminator",precision=10),
263  btagDeepC = Var("bDiscriminator('pfDeepCSVJetTags:probc')",float,doc="DeepCSV charm btag discriminator",precision=10),
264  btagDeepFlavC = Var("bDiscriminator('pfDeepFlavourJetTags:probc')",float,doc="DeepFlavour charm tag discriminator",precision=10),
265  )
266 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016:
267  modifier.toModify( jetTable.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"))
268 ( (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel) | run2_nanoAOD_102Xv1 ).toModify( jetTable.variables, puIdDisc = Var("userFloat('puId102XDisc')",float,doc="Pileup ID discriminant with 102X (2018) training", precision=10) )
269 ( (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel) | run2_nanoAOD_102Xv1 ).toModify( jetTable.variables, puId = Var("userInt('pileupJetId:fullId')",int,doc="Pileup ID flags for pre-UL trainings") )
270 run2_jme_2016.toModify( jetTable.variables, puIdDisc = Var("userFloat('pileupJetId:fullDiscriminant')",float,doc="Pileup ID discriminant with 80X (2016) training",precision=10))
271 run2_jme_2016.toModify( jetTable.variables, puId = Var("userInt('pileupJetId:fullId')",int,doc="Pileup ID flags for pre-UL trainings"))
272 (run2_jme_2016 & ~tracker_apv_vfp30_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( jetTable.variables, puId = Var("userInt('puId106XUL16Id')",int,doc="Pileup ID flags with 106X (2016) training"))
273 (run2_jme_2016 & ~tracker_apv_vfp30_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( jetTable.variables, puIdDisc = Var("userFloat('puId106XUL16Disc')",float,doc="Pileup ID discriminant with 106X (2016) training",precision=10))
274 (run2_jme_2016 & tracker_apv_vfp30_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( jetTable.variables, puId = Var("userInt('puId106XUL16APVId')",int,doc="Pileup ID flags with 106X (2016APV) training"))
275 (run2_jme_2016 & tracker_apv_vfp30_2016 & (run2_nanoAOD_106Xv2 | run2_miniAOD_devel)).toModify( jetTable.variables, puIdDisc = Var("userFloat('puId106XUL16APVDisc')",float,doc="Pileup ID discriminant with 106X (2016APV) training",precision=10))
276 run2_jme_2017.toModify( jetTable.variables, puId = Var("userInt('puId106XUL17Id')", int,doc="Pileup ID flags with 106X (2017) training"))
277 run2_jme_2017.toModify( jetTable.variables, puIdDisc = Var("userFloat('puId106XUL17Disc')", float,doc="Pileup ID discriminant with 106X (2017) training",precision=10))
278 for modifier in run2_nanoAOD_94XMiniAODv1, run2_nanoAOD_94XMiniAODv2:
279  modifier.toModify( jetTable.variables, puIdDisc = Var("userFloat('puId94XDisc')", float,doc="Pileup ID discriminant with 94X (2017) training",precision=10))
280  modifier.toModify( jetTable.variables, puId = Var("userInt('pileupJetId:fullId')",int,doc="Pileup ID flags for 2016/2017/2018 EOY trainings"))
281 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify(jetTable.variables, chFPV1EF = Var("userFloat('chFPV1EF')", float, doc="charged fromPV==1 Energy Fraction (component of the total charged Energy Fraction).", precision= 6))
282 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify(jetTable.variables, chFPV2EF = Var("userFloat('chFPV2EF')", float, doc="charged fromPV==2 Energy Fraction (component of the total charged Energy Fraction).", precision= 6))
283 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify(jetTable.variables, chFPV3EF = Var("userFloat('chFPV3EF')", float, doc="charged fromPV==3 Energy Fraction (component of the total charged Energy Fraction).", precision= 6))
284 
285 bjetNN= cms.EDProducer("BJetEnergyRegressionMVA",
286  backend = cms.string("TF"),
287  src = cms.InputTag("linkedObjects","jets"),
288  pvsrc = cms.InputTag("offlineSlimmedPrimaryVertices"),
289  svsrc = cms.InputTag("slimmedSecondaryVertices"),
290  rhosrc = cms.InputTag("fixedGridRhoFastjetAll"),
291 
292  weightFile = cms.FileInPath("PhysicsTools/NanoAOD/data/breg_training_2018.pb"),
293  name = cms.string("JetRegNN"),
294  isClassifier = cms.bool(False),
295  variablesOrder = cms.vstring(["Jet_pt","Jet_eta","rho","Jet_mt","Jet_leadTrackPt","Jet_leptonPtRel","Jet_leptonDeltaR","Jet_neHEF",
296  "Jet_neEmEF","Jet_vtxPt","Jet_vtxMass","Jet_vtx3dL","Jet_vtxNtrk","Jet_vtx3deL",
297  "Jet_numDaughters_pt03","Jet_energyRing_dR0_em_Jet_rawEnergy","Jet_energyRing_dR1_em_Jet_rawEnergy",
298  "Jet_energyRing_dR2_em_Jet_rawEnergy","Jet_energyRing_dR3_em_Jet_rawEnergy","Jet_energyRing_dR4_em_Jet_rawEnergy",
299  "Jet_energyRing_dR0_neut_Jet_rawEnergy","Jet_energyRing_dR1_neut_Jet_rawEnergy","Jet_energyRing_dR2_neut_Jet_rawEnergy",
300  "Jet_energyRing_dR3_neut_Jet_rawEnergy","Jet_energyRing_dR4_neut_Jet_rawEnergy","Jet_energyRing_dR0_ch_Jet_rawEnergy",
301  "Jet_energyRing_dR1_ch_Jet_rawEnergy","Jet_energyRing_dR2_ch_Jet_rawEnergy","Jet_energyRing_dR3_ch_Jet_rawEnergy",
302  "Jet_energyRing_dR4_ch_Jet_rawEnergy","Jet_energyRing_dR0_mu_Jet_rawEnergy","Jet_energyRing_dR1_mu_Jet_rawEnergy",
303  "Jet_energyRing_dR2_mu_Jet_rawEnergy","Jet_energyRing_dR3_mu_Jet_rawEnergy","Jet_energyRing_dR4_mu_Jet_rawEnergy",
304  "Jet_chHEF","Jet_chEmEF","Jet_leptonPtRelInv","isEle","isMu","isOther","Jet_mass","Jet_ptd"]),
305  variables = cms.PSet(
306  Jet_pt = cms.string("pt*jecFactor('Uncorrected')"),
307  Jet_mt = cms.string("mt*jecFactor('Uncorrected')"),
308  Jet_eta = cms.string("eta"),
309  Jet_mass = cms.string("mass*jecFactor('Uncorrected')"),
310  Jet_ptd = cms.string("userFloat('ptD')"),
311  Jet_leadTrackPt = cms.string("userFloat('leadTrackPt')"),
312  Jet_vtxNtrk = cms.string("userInt('vtxNtrk')"),
313  Jet_vtxMass = cms.string("userFloat('vtxMass')"),
314  Jet_vtx3dL = cms.string("userFloat('vtx3dL')"),
315  Jet_vtx3deL = cms.string("userFloat('vtx3deL')"),
316  Jet_vtxPt = cms.string("userFloat('vtxPt')"),
317  #Jet_leptonPt = cms.string("userFloat('leptonPt')"),
318  Jet_leptonPtRel = cms.string("userFloat('leptonPtRelv0')"),
319  Jet_leptonPtRelInv = cms.string("userFloat('leptonPtRelInvv0')*jecFactor('Uncorrected')"),
320  Jet_leptonDeltaR = cms.string("userFloat('leptonDeltaR')"),
321  #Jet_leptonPdgId = cms.string("userInt('leptonPdgId')"),
322  Jet_neHEF = cms.string("neutralHadronEnergyFraction()"),
323  Jet_neEmEF = cms.string("neutralEmEnergyFraction()"),
324  Jet_chHEF = cms.string("chargedHadronEnergyFraction()"),
325  Jet_chEmEF = cms.string("chargedEmEnergyFraction()"),
326  isMu = cms.string("?abs(userInt('leptonPdgId'))==13?1:0"),
327  isEle = cms.string("?abs(userInt('leptonPdgId'))==11?1:0"),
328  isOther = cms.string("?userInt('leptonPdgId')==0?1:0"),
329  ),
330  inputTensorName = cms.string("ffwd_inp"),
331  outputTensorName = cms.string("ffwd_out/BiasAdd"),
332  outputNames = cms.vstring(["corr","res"]),
333  outputFormulas = cms.vstring(["at(0)*0.27912887930870056+1.0545977354049683","0.5*(at(2)-at(1))*0.27912887930870056"]),
334  nThreads = cms.uint32(1),
335  singleThreadPool = cms.string("no_threads"),
336 
337 )
338 
339 cjetNN= cms.EDProducer("BJetEnergyRegressionMVA",
340  backend = cms.string("TF"),
341  src = cms.InputTag("linkedObjects","jets"),
342  pvsrc = cms.InputTag("offlineSlimmedPrimaryVertices"),
343  svsrc = cms.InputTag("slimmedSecondaryVertices"),
344  rhosrc = cms.InputTag("fixedGridRhoFastjetAll"),
345 
346  weightFile = cms.FileInPath("PhysicsTools/NanoAOD/data/creg_training_2018.pb"),
347  name = cms.string("JetRegNN"),
348  isClassifier = cms.bool(False),
349  variablesOrder = cms.vstring(["Jet_pt","Jet_eta","rho","Jet_mt","Jet_leadTrackPt","Jet_leptonPtRel","Jet_leptonDeltaR",
350  "Jet_neHEF","Jet_neEmEF","Jet_vtxPt","Jet_vtxMass","Jet_vtx3dL","Jet_vtxNtrk","Jet_vtx3deL",
351  "Jet_numDaughters_pt03","Jet_chEmEF","Jet_chHEF", "Jet_ptd","Jet_mass",
352  "Jet_energyRing_dR0_em_Jet_rawEnergy","Jet_energyRing_dR1_em_Jet_rawEnergy",
353  "Jet_energyRing_dR2_em_Jet_rawEnergy","Jet_energyRing_dR3_em_Jet_rawEnergy","Jet_energyRing_dR4_em_Jet_rawEnergy",
354  "Jet_energyRing_dR0_neut_Jet_rawEnergy","Jet_energyRing_dR1_neut_Jet_rawEnergy","Jet_energyRing_dR2_neut_Jet_rawEnergy",
355  "Jet_energyRing_dR3_neut_Jet_rawEnergy","Jet_energyRing_dR4_neut_Jet_rawEnergy","Jet_energyRing_dR0_ch_Jet_rawEnergy",
356  "Jet_energyRing_dR1_ch_Jet_rawEnergy","Jet_energyRing_dR2_ch_Jet_rawEnergy","Jet_energyRing_dR3_ch_Jet_rawEnergy",
357  "Jet_energyRing_dR4_ch_Jet_rawEnergy","Jet_energyRing_dR0_mu_Jet_rawEnergy","Jet_energyRing_dR1_mu_Jet_rawEnergy",
358  "Jet_energyRing_dR2_mu_Jet_rawEnergy","Jet_energyRing_dR3_mu_Jet_rawEnergy","Jet_energyRing_dR4_mu_Jet_rawEnergy"]),
359  variables = cms.PSet(
360  Jet_pt = cms.string("pt*jecFactor('Uncorrected')"),
361  Jet_mt = cms.string("mt*jecFactor('Uncorrected')"),
362  Jet_eta = cms.string("eta"),
363  Jet_mass = cms.string("mass*jecFactor('Uncorrected')"),
364  Jet_ptd = cms.string("userFloat('ptD')"),
365  Jet_leadTrackPt = cms.string("userFloat('leadTrackPt')"),
366  Jet_vtxNtrk = cms.string("userInt('vtxNtrk')"),
367  Jet_vtxMass = cms.string("userFloat('vtxMass')"),
368  Jet_vtx3dL = cms.string("userFloat('vtx3dL')"),
369  Jet_vtx3deL = cms.string("userFloat('vtx3deL')"),
370  Jet_vtxPt = cms.string("userFloat('vtxPt')"),
371  #Jet_leptonPt = cms.string("userFloat('leptonPt')"),
372  Jet_leptonPtRel = cms.string("userFloat('leptonPtRelv0')"),
373  Jet_leptonPtRelInv = cms.string("userFloat('leptonPtRelInvv0')*jecFactor('Uncorrected')"),
374  Jet_leptonDeltaR = cms.string("userFloat('leptonDeltaR')"),
375  #Jet_leptonPdgId = cms.string("userInt('leptonPdgId')"),
376  Jet_neHEF = cms.string("neutralHadronEnergyFraction()"),
377  Jet_neEmEF = cms.string("neutralEmEnergyFraction()"),
378  Jet_chHEF = cms.string("chargedHadronEnergyFraction()"),
379  Jet_chEmEF = cms.string("chargedEmEnergyFraction()"),
380  isMu = cms.string("?abs(userInt('leptonPdgId'))==13?1:0"),
381  isEle = cms.string("?abs(userInt('leptonPdgId'))==11?1:0"),
382  isOther = cms.string("?userInt('leptonPdgId')==0?1:0"),
383  ),
384  inputTensorName = cms.string("ffwd_inp"),
385  outputTensorName = cms.string("ffwd_out/BiasAdd"),
386  outputNames = cms.vstring(["corr","res"]),
387  outputFormulas = cms.vstring(["at(0)*0.24325256049633026+0.993854820728302","0.5*(at(2)-at(1))*0.24325256049633026"]),
388  nThreads = cms.uint32(1),
389  singleThreadPool = cms.string("no_threads"),
390 )
391 
392 
393 ##### Soft Activity tables
394 saJetTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
395  src = cms.InputTag("softActivityJets"),
396  cut = cms.string(""),
397  maxLen = cms.uint32(6),
398  name = cms.string("SoftActivityJet"),
399  doc = cms.string("jets clustered from charged candidates compatible with primary vertex (" + chsForSATkJets.cut.value()+")"),
400  singleton = cms.bool(False), # the number of entries is variable
401  extension = cms.bool(False), # this is the main table for the jets
402  variables = cms.PSet(P3Vars,
403  )
404 )
405 
406 saJetTable.variables.pt.precision=10
407 saJetTable.variables.eta.precision=8
408 saJetTable.variables.phi.precision=8
409 
410 saTable = cms.EDProducer("GlobalVariablesTableProducer",
411  variables = cms.PSet(
412  SoftActivityJetHT = ExtVar( cms.InputTag("softActivityJets"), "candidatescalarsum", doc = "scalar sum of soft activity jet pt, pt>1" ),
413  SoftActivityJetHT10 = ExtVar( cms.InputTag("softActivityJets10"), "candidatescalarsum", doc = "scalar sum of soft activity jet pt , pt >10" ),
414  SoftActivityJetHT5 = ExtVar( cms.InputTag("softActivityJets5"), "candidatescalarsum", doc = "scalar sum of soft activity jet pt, pt>5" ),
415  SoftActivityJetHT2 = ExtVar( cms.InputTag("softActivityJets2"), "candidatescalarsum", doc = "scalar sum of soft activity jet pt, pt >2" ),
416  SoftActivityJetNjets10 = ExtVar( cms.InputTag("softActivityJets10"), "candidatesize", doc = "number of soft activity jet pt, pt >2" ),
417  SoftActivityJetNjets5 = ExtVar( cms.InputTag("softActivityJets5"), "candidatesize", doc = "number of soft activity jet pt, pt >5" ),
418  SoftActivityJetNjets2 = ExtVar( cms.InputTag("softActivityJets2"), "candidatesize", doc = "number of soft activity jet pt, pt >10" ),
419 
420  )
421 )
422 
423 
424 
425 ## BOOSTED STUFF #################
426 fatJetTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
427  src = cms.InputTag("finalJetsAK8"),
428  cut = cms.string(" pt > 170"), #probably already applied in miniaod
429  name = cms.string("FatJet"),
430  doc = cms.string("slimmedJetsAK8, i.e. ak8 fat jets for boosted analysis"),
431  singleton = cms.bool(False), # the number of entries is variable
432  extension = cms.bool(False), # this is the main table for the jets
433  variables = cms.PSet(P4Vars,
434  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"),
435  area = Var("jetArea()", float, doc="jet catchment area, for JECs",precision=10),
436  rawFactor = Var("1.-jecFactor('Uncorrected')",float,doc="1 - Factor to get back to raw pT",precision=6),
437  tau1 = Var("userFloat('NjettinessAK8Puppi:tau1')",float, doc="Nsubjettiness (1 axis)",precision=10),
438  tau2 = Var("userFloat('NjettinessAK8Puppi:tau2')",float, doc="Nsubjettiness (2 axis)",precision=10),
439  tau3 = Var("userFloat('NjettinessAK8Puppi:tau3')",float, doc="Nsubjettiness (3 axis)",precision=10),
440  tau4 = Var("userFloat('NjettinessAK8Puppi:tau4')",float, doc="Nsubjettiness (4 axis)",precision=10),
441  n2b1 = Var("userFloat('ak8PFJetsPuppiSoftDropValueMap:nb1AK8PuppiSoftDropN2')", float, doc="N2 with beta=1", precision=10),
442  n3b1 = Var("userFloat('ak8PFJetsPuppiSoftDropValueMap:nb1AK8PuppiSoftDropN3')", float, doc="N3 with beta=1", precision=10),
443  msoftdrop = Var("groomedMass('SoftDropPuppi')",float, doc="Corrected soft drop mass with PUPPI",precision=10),
444  btagDeepB = Var("?(bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb'))>=0?bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb'):-1",float,doc="DeepCSV b+bb tag discriminator",precision=10),
445  btagCSVV2 = Var("bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",float,doc=" pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",precision=10),
446  btagHbb = Var("bDiscriminator('pfBoostedDoubleSecondaryVertexAK8BJetTags')",float,doc="Higgs to BB tagger discriminator",precision=10),
447  btagDDBvLV2 = Var("bDiscriminator('pfMassIndependentDeepDoubleBvLV2JetTags:probHbb')",float,doc="DeepDoubleX V2(mass-decorrelated) discriminator for H(Z)->bb vs QCD",precision=10),
448  btagDDCvLV2 = Var("bDiscriminator('pfMassIndependentDeepDoubleCvLV2JetTags:probHcc')",float,doc="DeepDoubleX V2 (mass-decorrelated) discriminator for H(Z)->cc vs QCD",precision=10),
449  btagDDCvBV2 = Var("bDiscriminator('pfMassIndependentDeepDoubleCvBV2JetTags:probHcc')",float,doc="DeepDoubleX V2 (mass-decorrelated) discriminator for H(Z)->cc vs H(Z)->bb",precision=10),
450  deepTag_TvsQCD = Var("bDiscriminator('pfDeepBoostedDiscriminatorsJetTags:TvsQCD')",float,doc="DeepBoostedJet tagger top vs QCD discriminator",precision=10),
451  deepTag_WvsQCD = Var("bDiscriminator('pfDeepBoostedDiscriminatorsJetTags:WvsQCD')",float,doc="DeepBoostedJet tagger W vs QCD discriminator",precision=10),
452  deepTag_ZvsQCD = Var("bDiscriminator('pfDeepBoostedDiscriminatorsJetTags:ZvsQCD')",float,doc="DeepBoostedJet tagger Z vs QCD discriminator",precision=10),
453  deepTag_H = Var("bDiscriminator('pfDeepBoostedJetTags:probHbb')+bDiscriminator('pfDeepBoostedJetTags:probHcc')+bDiscriminator('pfDeepBoostedJetTags:probHqqqq')",float,doc="DeepBoostedJet tagger H(bb,cc,4q) sum",precision=10),
454  deepTag_QCD = Var("bDiscriminator('pfDeepBoostedJetTags:probQCDbb')+bDiscriminator('pfDeepBoostedJetTags:probQCDcc')+bDiscriminator('pfDeepBoostedJetTags:probQCDb')+bDiscriminator('pfDeepBoostedJetTags:probQCDc')+bDiscriminator('pfDeepBoostedJetTags:probQCDothers')",float,doc="DeepBoostedJet tagger QCD(bb,cc,b,c,others) sum",precision=10),
455  deepTag_QCDothers = Var("bDiscriminator('pfDeepBoostedJetTags:probQCDothers')",float,doc="DeepBoostedJet tagger QCDothers value",precision=10),
456  deepTagMD_TvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:TvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger top vs QCD discriminator",precision=10),
457  deepTagMD_WvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:WvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger W vs QCD discriminator",precision=10),
458  deepTagMD_ZvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:ZvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger Z vs QCD discriminator",precision=10),
459  deepTagMD_ZHbbvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:ZHbbvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger Z/H->bb vs QCD discriminator",precision=10),
460  deepTagMD_ZbbvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:ZbbvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger Z->bb vs QCD discriminator",precision=10),
461  deepTagMD_HbbvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:HbbvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger H->bb vs QCD discriminator",precision=10),
462  deepTagMD_ZHccvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:ZHccvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger Z/H->cc vs QCD discriminator",precision=10),
463  deepTagMD_H4qvsQCD = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:H4qvsQCD')",float,doc="Mass-decorrelated DeepBoostedJet tagger H->4q vs QCD discriminator",precision=10),
464  deepTagMD_bbvsLight = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:bbvsLight')",float,doc="Mass-decorrelated DeepBoostedJet tagger Z/H/gluon->bb vs light flavour discriminator",precision=10),
465  deepTagMD_ccvsLight = Var("bDiscriminator('pfMassDecorrelatedDeepBoostedDiscriminatorsJetTags:ccvsLight')",float,doc="Mass-decorrelated DeepBoostedJet tagger Z/H/gluon->cc vs light flavour discriminator",precision=10),
466  particleNet_TvsQCD = Var("bDiscriminator('pfParticleNetDiscriminatorsJetTags:TvsQCD')",float,doc="ParticleNet tagger top vs QCD discriminator",precision=10),
467  particleNet_WvsQCD = Var("bDiscriminator('pfParticleNetDiscriminatorsJetTags:WvsQCD')",float,doc="ParticleNet tagger W vs QCD discriminator",precision=10),
468  particleNet_ZvsQCD = Var("bDiscriminator('pfParticleNetDiscriminatorsJetTags:ZvsQCD')",float,doc="ParticleNet tagger Z vs QCD discriminator",precision=10),
469  particleNet_HbbvsQCD = Var("bDiscriminator('pfParticleNetDiscriminatorsJetTags:HbbvsQCD')",float,doc="ParticleNet tagger H(->bb) vs QCD discriminator",precision=10),
470  particleNet_HccvsQCD = Var("bDiscriminator('pfParticleNetDiscriminatorsJetTags:HccvsQCD')",float,doc="ParticleNet tagger H(->cc) vs QCD discriminator",precision=10),
471  particleNet_H4qvsQCD = Var("bDiscriminator('pfParticleNetDiscriminatorsJetTags:H4qvsQCD')",float,doc="ParticleNet tagger H(->VV->qqqq) vs QCD discriminator",precision=10),
472  particleNet_QCD = Var("bDiscriminator('pfParticleNetJetTags:probQCDbb')+bDiscriminator('pfParticleNetJetTags:probQCDcc')+bDiscriminator('pfParticleNetJetTags:probQCDb')+bDiscriminator('pfParticleNetJetTags:probQCDc')+bDiscriminator('pfParticleNetJetTags:probQCDothers')",float,doc="ParticleNet tagger QCD(bb,cc,b,c,others) sum",precision=10),
473  particleNet_mass = Var("bDiscriminator('pfParticleNetMassRegressionJetTags:mass')",float,doc="ParticleNet mass regression",precision=10),
474  particleNetMD_Xbb = Var("bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probXbb')",float,doc="Mass-decorrelated ParticleNet tagger raw X->bb score. For X->bb vs QCD tagging, use Xbb/(Xbb+QCD)",precision=10),
475  particleNetMD_Xcc = Var("bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probXcc')",float,doc="Mass-decorrelated ParticleNet tagger raw X->cc score. For X->cc vs QCD tagging, use Xcc/(Xcc+QCD)",precision=10),
476  particleNetMD_Xqq = Var("bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probXqq')",float,doc="Mass-decorrelated ParticleNet tagger raw X->qq (uds) score. For X->qq vs QCD tagging, use Xqq/(Xqq+QCD). For W vs QCD tagging, use (Xcc+Xqq)/(Xcc+Xqq+QCD)",precision=10),
477  particleNetMD_QCD = Var("bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probQCDbb')+bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probQCDcc')+bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probQCDb')+bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probQCDc')+bDiscriminator('pfMassDecorrelatedParticleNetJetTags:probQCDothers')",float,doc="Mass-decorrelated ParticleNet tagger raw QCD score",precision=10),
478  subJetIdx1 = Var("?nSubjetCollections()>0 && subjets('SoftDropPuppi').size()>0?subjets('SoftDropPuppi')[0].key():-1", int,
479  doc="index of first subjet"),
480  subJetIdx2 = Var("?nSubjetCollections()>0 && subjets('SoftDropPuppi').size()>1?subjets('SoftDropPuppi')[1].key():-1", int,
481  doc="index of second subjet"),
482 
483 # btagDeepC = Var("bDiscriminator('pfDeepCSVJetTags:probc')",float,doc="CMVA V2 btag discriminator",precision=10),
484 #puIdDisc = Var("userFloat('pileupJetId:fullDiscriminant')",float,doc="Pileup ID discriminant",precision=10),
485  nConstituents = Var("numberOfDaughters()","uint8",doc="Number of particles in the jet"),
486  ),
487  externalVariables = cms.PSet(
488  lsf3 = ExtVar(cms.InputTag("lepInJetVars:lsf3"),float, doc="Lepton Subjet Fraction (3 subjets)",precision=10),
489  muonIdx3SJ = ExtVar(cms.InputTag("lepInJetVars:muIdx3SJ"),int, doc="index of muon matched to jet"),
490  electronIdx3SJ = ExtVar(cms.InputTag("lepInJetVars:eleIdx3SJ"),int,doc="index of electron matched to jet"),
491  )
492 )
493 ### Era dependent customization
494 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify(
495  fatJetTable.variables, func=lambda v: delattr(v, 'particleNet_mass')
496 )
497 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016, run2_nanoAOD_94XMiniAODv1, run2_nanoAOD_94XMiniAODv2, run2_nanoAOD_102Xv1, run2_nanoAOD_106Xv1:
498  modifier.toModify( fatJetTable.variables.n2b1, expr = cms.string("userFloat('ak8PFJetsPuppiSoftDropValueMap:nb1AK8PuppiSoftDropN2')"),)
499  modifier.toModify( fatJetTable.variables.n3b1, expr = cms.string("userFloat('ak8PFJetsPuppiSoftDropValueMap:nb1AK8PuppiSoftDropN3')"),)
500  # Deprecated after 106X
501  modifier.toModify( fatJetTable.variables,
502  btagCMVA = Var("bDiscriminator('pfCombinedMVAV2BJetTags')",float,doc="CMVA V2 btag discriminator",precision=10),
503  btagDDBvL_noMD = Var("bDiscriminator('pfDeepDoubleBvLJetTags:probHbb')",float,doc="DeepDoubleX discriminator (no mass-decorrelation) for H(Z)->bb vs QCD",precision=10),
504  btagDDCvL_noMD = Var("bDiscriminator('pfDeepDoubleCvLJetTags:probHcc')",float,doc="DeepDoubleX discriminator (no mass-decorrelation) for H(Z)->cc vs QCD",precision=10),
505  btagDDCvB_noMD = Var("bDiscriminator('pfDeepDoubleCvBJetTags:probHcc')",float,doc="DeepDoubleX discriminator (no mass-decorrelation) for H(Z)->cc vs H(Z)->bb",precision=10),
506  btagDDBvL = Var("bDiscriminator('pfMassIndependentDeepDoubleBvLJetTags:probHbb')",float,doc="DeepDoubleX (mass-decorrelated) discriminator for H(Z)->bb vs QCD",precision=10),
507  btagDDCvL = Var("bDiscriminator('pfMassIndependentDeepDoubleCvLJetTags:probHcc')",float,doc="DeepDoubleX (mass-decorrelated) discriminator for H(Z)->cc vs QCD",precision=10),
508  btagDDCvB = Var("bDiscriminator('pfMassIndependentDeepDoubleCvBJetTags:probHcc')",float,doc="DeepDoubleX (mass-decorrelated) discriminator for H(Z)->cc vs H(Z)->bb",precision=10),
509  )
510 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables, msoftdrop_chs = Var("userFloat('ak8PFJetsCHSSoftDropMass')",float, doc="Legacy uncorrected soft drop mass with CHS",precision=10))
511 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables.tau1, expr = cms.string("userFloat(\'ak8PFJetsPuppiValueMap:NjettinessAK8PuppiTau1\')"),)
512 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables.tau2, expr = cms.string("userFloat(\'ak8PFJetsPuppiValueMap:NjettinessAK8PuppiTau2\')"),)
513 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables.tau3, expr = cms.string("userFloat(\'ak8PFJetsPuppiValueMap:NjettinessAK8PuppiTau3\')"),)
514 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables, tau4 = None)
515 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables, n2b1 = None)
516 run2_miniAOD_80XLegacy.toModify( fatJetTable.variables, n3b1 = None)
517 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify( fatJetTable.variables, nConstituents = None)
518 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016:
519  modifier.toModify( fatJetTable.variables, jetId = Var("userInt('tightId')*2+userInt('looseId')",int,doc="Jet ID flags bit1 is loose, bit2 is tight"))
520 
521 run2_jme_2016.toModify( bjetNN, weightFile = cms.FileInPath("PhysicsTools/NanoAOD/data/breg_training_2016.pb") )
522 run2_jme_2016.toModify( bjetNN,outputFormulas = cms.vstring(["at(0)*0.31976690888404846+1.047176718711853","0.5*(at(2)-at(1))*0.31976690888404846"]))
523 
524 run2_jme_2017.toModify( bjetNN, weightFile = cms.FileInPath("PhysicsTools/NanoAOD/data/breg_training_2017.pb") )
525 run2_jme_2017.toModify( bjetNN,outputFormulas = cms.vstring(["at(0)*0.28225210309028625+1.055067777633667","0.5*(at(2)-at(1))*0.28225210309028625"]))
526 
527 run2_jme_2016.toModify( cjetNN, weightFile = cms.FileInPath("PhysicsTools/NanoAOD/data/creg_training_2016.pb") )
528 run2_jme_2016.toModify( cjetNN,outputFormulas = cms.vstring(["at(0)*0.28862622380256653+0.9908722639083862","0.5*(at(2)-at(1))*0.28862622380256653"]))
529 
530 run2_jme_2017.toModify( cjetNN, weightFile = cms.FileInPath("PhysicsTools/NanoAOD/data/creg_training_2017.pb") )
531 run2_jme_2017.toModify( cjetNN,outputFormulas = cms.vstring(["at(0)*0.24718524515628815+0.9927206635475159","0.5*(at(2)-at(1))*0.24718524515628815"]))
532 
533 
534 #
535 # ML-based FastSim refinement
536 #
537 from Configuration.Eras.Modifier_fastSim_cff import fastSim
538 def nanoAOD_refineFastSim_bTagDeepFlav(process):
539 
540 
541  fastSim.toModify( process.jetTable.variables,
542  btagDeepFlavBunrefined = process.jetTable.variables.btagDeepFlavB.clone(),
543  btagDeepFlavCvBunrefined = process.jetTable.variables.btagDeepFlavCvB.clone(),
544  btagDeepFlavCvLunrefined = process.jetTable.variables.btagDeepFlavCvL.clone(),
545  btagDeepFlavQGunrefined = process.jetTable.variables.btagDeepFlavQG.clone(),
546  )
547 
548  fastSim.toModify( process.jetTable.variables,
549  btagDeepFlavB = None,
550  btagDeepFlavCvB = None,
551  btagDeepFlavCvL = None,
552  btagDeepFlavQG = None,
553  )
554 
555  fastSim.toModify( process.jetTable.externalVariables,
556  btagDeepFlavB = ExtVar(cms.InputTag("btagDeepFlavRefineNN:btagDeepFlavBrefined"), float, doc="DeepJet b+bb+lepb tag discriminator", precision=10),
557  btagDeepFlavCvB = ExtVar(cms.InputTag("btagDeepFlavRefineNN:btagDeepFlavCvBrefined"), float, doc="DeepJet c vs b+bb+lepb discriminator", precision=10),
558  btagDeepFlavCvL = ExtVar(cms.InputTag("btagDeepFlavRefineNN:btagDeepFlavCvLrefined"), float, doc="DeepJet c vs uds+g discriminator", precision=10),
559  btagDeepFlavQG = ExtVar(cms.InputTag("btagDeepFlavRefineNN:btagDeepFlavQGrefined"), float, doc="DeepJet g vs uds discriminator", precision=10),
560  )
561 
562  process.btagDeepFlavRefineNN= cms.EDProducer("JetBaseMVAValueMapProducer",
563  backend = cms.string("ONNX"),
564  batch_eval = cms.bool(True),
565  disableONNXGraphOpt = cms.bool(True),
566 
567  src = cms.InputTag("linkedObjects","jets"),
568 
569  weightFile=cms.FileInPath("PhysicsTools/NanoAOD/data/btagDeepFlavRefineNN_CHS.onnx"),
570  name = cms.string("btagDeepFlavRefineNN"),
571 
572  isClassifier = cms.bool(False),
573  variablesOrder = cms.vstring(["GenJet_pt","GenJet_eta","Jet_hadronFlavour",
574  "Jet_btagDeepFlavB","Jet_btagDeepFlavCvB","Jet_btagDeepFlavCvL","Jet_btagDeepFlavQG"]),
575  variables = cms.PSet(
576  GenJet_pt = cms.string("?genJetFwdRef().backRef().isNonnull()?genJetFwdRef().backRef().pt():pt"),
577  GenJet_eta = cms.string("?genJetFwdRef().backRef().isNonnull()?genJetFwdRef().backRef().eta():eta"),
578  Jet_hadronFlavour = cms.string("hadronFlavour()"),
579  Jet_btagDeepFlavB = cms.string("bDiscriminator('pfDeepFlavourJetTags:probb')+bDiscriminator('pfDeepFlavourJetTags:probbb')+bDiscriminator('pfDeepFlavourJetTags:problepb')"),
580  Jet_btagDeepFlavCvB = cms.string("?(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probb')+bDiscriminator('pfDeepFlavourJetTags:probbb')+bDiscriminator('pfDeepFlavourJetTags:problepb'))>0?bDiscriminator('pfDeepFlavourJetTags:probc')/(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probb')+bDiscriminator('pfDeepFlavourJetTags:probbb')+bDiscriminator('pfDeepFlavourJetTags:problepb')):-1"),
581  Jet_btagDeepFlavCvL = cms.string("?(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probuds')+bDiscriminator('pfDeepFlavourJetTags:probg'))>0?bDiscriminator('pfDeepFlavourJetTags:probc')/(bDiscriminator('pfDeepFlavourJetTags:probc')+bDiscriminator('pfDeepFlavourJetTags:probuds')+bDiscriminator('pfDeepFlavourJetTags:probg')):-1"),
582  Jet_btagDeepFlavQG = cms.string("?(bDiscriminator('pfDeepFlavourJetTags:probg')+bDiscriminator('pfDeepFlavourJetTags:probuds'))>0?bDiscriminator('pfDeepFlavourJetTags:probg')/(bDiscriminator('pfDeepFlavourJetTags:probg')+bDiscriminator('pfDeepFlavourJetTags:probuds')):-1"),
583  ),
584  inputTensorName = cms.string("input"),
585  outputTensorName = cms.string("output"),
586  outputNames = cms.vstring(["btagDeepFlavBrefined","btagDeepFlavCvBrefined","btagDeepFlavCvLrefined","btagDeepFlavQGrefined"]),
587  outputFormulas = cms.vstring(["at(0)","at(1)","at(2)","at(3)"]),
588  )
589 
590  fastSim.toModify(process.jetTables, process.jetTables.insert(0,process.btagDeepFlavRefineNN))
591 
592  return process
593 
594 
595 subJetTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
596  src = cms.InputTag("slimmedJetsAK8PFPuppiSoftDropPacked","SubJets"),
597  cut = cms.string(""), #probably already applied in miniaod
598  name = cms.string("SubJet"),
599  doc = cms.string("slimmedJetsAK8, i.e. ak8 fat jets for boosted analysis"),
600  singleton = cms.bool(False), # the number of entries is variable
601  extension = cms.bool(False), # this is the main table for the jets
602  variables = cms.PSet(P4Vars,
603  btagDeepB = Var("bDiscriminator('pfDeepCSVJetTags:probb')+bDiscriminator('pfDeepCSVJetTags:probbb')",float,doc="DeepCSV b+bb tag discriminator",precision=10),
604  btagCSVV2 = Var("bDiscriminator('pfCombinedInclusiveSecondaryVertexV2BJetTags')",float,doc=" pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)",precision=10),
605  rawFactor = Var("1.-jecFactor('Uncorrected')",float,doc="1 - Factor to get back to raw pT",precision=6),
606  tau1 = Var("userFloat('NjettinessAK8Subjets:tau1')",float, doc="Nsubjettiness (1 axis)",precision=10),
607  tau2 = Var("userFloat('NjettinessAK8Subjets:tau2')",float, doc="Nsubjettiness (2 axis)",precision=10),
608  tau3 = Var("userFloat('NjettinessAK8Subjets:tau3')",float, doc="Nsubjettiness (3 axis)",precision=10),
609  tau4 = Var("userFloat('NjettinessAK8Subjets:tau4')",float, doc="Nsubjettiness (4 axis)",precision=10),
610  n2b1 = Var("userFloat('nb1AK8PuppiSoftDropSubjets:ecfN2')", float, doc="N2 with beta=1", precision=10),
611  n3b1 = Var("userFloat('nb1AK8PuppiSoftDropSubjets:ecfN3')", float, doc="N3 with beta=1", precision=10),
612  )
613 )
614 
615 # Deprecation/backcomp
616 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016, run2_nanoAOD_94XMiniAODv1, run2_nanoAOD_94XMiniAODv2, run2_nanoAOD_102Xv1, run2_nanoAOD_106Xv1:
617  # post 106X
618  modifier.toModify(subJetTable.variables,
619  btagCMVA = Var("bDiscriminator('pfCombinedMVAV2BJetTags')",float,doc="CMVA V2 btag discriminator",precision=10),
620  )
621 
622 #jets are not as precise as muons
623 fatJetTable.variables.pt.precision=10
624 subJetTable.variables.pt.precision=10
625 
626 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, tau1 = None)
627 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, tau2 = None)
628 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, tau3 = None)
629 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, tau4 = None)
630 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, n2b1 = None)
631 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, n3b1 = None)
632 run2_miniAOD_80XLegacy.toModify( subJetTable.variables, btagCMVA = None, btagDeepB = None)
633 
634 
635 corrT1METJetTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
636  src = cms.InputTag("corrT1METJets"),
637  cut = cms.string(""),
638  name = cms.string("CorrT1METJet"),
639  doc = cms.string("Additional low-pt jets for Type-1 MET re-correction"),
640  singleton = cms.bool(False), # the number of entries is variable
641  extension = cms.bool(False), # this is the main table for the jets
642  variables = cms.PSet(
643  rawPt = Var("pt()*jecFactor('Uncorrected')",float,precision=10),
644  eta = Var("eta", float,precision=12),
645  phi = Var("phi", float, precision=12),
646  area = Var("jetArea()", float, doc="jet catchment area, for JECs",precision=10),
647  )
648 )
649 
650 
651 
652 ## MC STUFF ######################
653 jetMCTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
654  src = cms.InputTag("linkedObjects","jets"),
655  cut = cms.string(""), #we should not filter on cross linked collections
656  name = cms.string("Jet"),
657  singleton = cms.bool(False), # the number of entries is variable
658  extension = cms.bool(True), # this is an extension table for the jets
659  variables = cms.PSet(
660  partonFlavour = Var("partonFlavour()", int, doc="flavour from parton matching"),
661  hadronFlavour = Var("hadronFlavour()", int, doc="flavour from hadron ghost clustering"),
662  genJetIdx = Var("?genJetFwdRef().backRef().isNonnull()?genJetFwdRef().backRef().key():-1", int, doc="index of matched gen jet"),
663  )
664 )
665 genJetTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
666  src = cms.InputTag("slimmedGenJets"),
667  cut = cms.string("pt > 10"),
668  name = cms.string("GenJet"),
669  doc = cms.string("slimmedGenJets, i.e. ak4 Jets made with visible genparticles"),
670  singleton = cms.bool(False), # the number of entries is variable
671  extension = cms.bool(False), # this is the main table for the genjets
672  variables = cms.PSet(P4Vars,
673  #anything else?
674  )
675 )
676 patJetPartons = cms.EDProducer('HadronAndPartonSelector',
677  src = cms.InputTag("generator"),
678  particles = cms.InputTag("prunedGenParticles"),
679  partonMode = cms.string("Auto"),
680  fullChainPhysPartons = cms.bool(True)
681 )
682 genJetFlavourAssociation = cms.EDProducer("JetFlavourClustering",
683  jets = genJetTable.src,
684  bHadrons = cms.InputTag("patJetPartons","bHadrons"),
685  cHadrons = cms.InputTag("patJetPartons","cHadrons"),
686  partons = cms.InputTag("patJetPartons","physicsPartons"),
687  leptons = cms.InputTag("patJetPartons","leptons"),
688  jetAlgorithm = cms.string("AntiKt"),
689  rParam = cms.double(0.4),
690  ghostRescaling = cms.double(1e-18),
691  hadronFlavourHasPriority = cms.bool(False)
692 )
693 genJetFlavourTable = cms.EDProducer("GenJetFlavourTableProducer",
694  name = genJetTable.name,
695  src = genJetTable.src,
696  cut = genJetTable.cut,
697  deltaR = cms.double(0.1),
698  jetFlavourInfos = cms.InputTag("slimmedGenJetsFlavourInfos"),
699 )
700 
701 genJetAK8Table = cms.EDProducer("SimpleCandidateFlatTableProducer",
702  src = cms.InputTag("slimmedGenJetsAK8"),
703  cut = cms.string("pt > 100."),
704  name = cms.string("GenJetAK8"),
705  doc = cms.string("slimmedGenJetsAK8, i.e. ak8 Jets made with visible genparticles"),
706  singleton = cms.bool(False), # the number of entries is variable
707  extension = cms.bool(False), # this is the main table for the genjets
708  variables = cms.PSet(P4Vars,
709  #anything else?
710  )
711 )
712 genJetAK8FlavourAssociation = cms.EDProducer("JetFlavourClustering",
713  jets = genJetAK8Table.src,
714  bHadrons = cms.InputTag("patJetPartons","bHadrons"),
715  cHadrons = cms.InputTag("patJetPartons","cHadrons"),
716  partons = cms.InputTag("patJetPartons","physicsPartons"),
717  leptons = cms.InputTag("patJetPartons","leptons"),
718  jetAlgorithm = cms.string("AntiKt"),
719  rParam = cms.double(0.8),
720  ghostRescaling = cms.double(1e-18),
721  hadronFlavourHasPriority = cms.bool(False)
722 )
723 genJetAK8FlavourTable = cms.EDProducer("GenJetFlavourTableProducer",
724  name = genJetAK8Table.name,
725  src = genJetAK8Table.src,
726  cut = genJetAK8Table.cut,
727  deltaR = cms.double(0.1),
728  jetFlavourInfos = cms.InputTag("genJetAK8FlavourAssociation"),
729 )
730 fatJetMCTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
731  src = fatJetTable.src,
732  cut = fatJetTable.cut,
733  name = fatJetTable.name,
734  singleton = cms.bool(False),
735  extension = cms.bool(True),
736  variables = cms.PSet(
737  nBHadrons = Var("jetFlavourInfo().getbHadrons().size()", "uint8", doc="number of b-hadrons"),
738  nCHadrons = Var("jetFlavourInfo().getcHadrons().size()", "uint8", doc="number of c-hadrons"),
739  hadronFlavour = Var("hadronFlavour()", int, doc="flavour from hadron ghost clustering"),
740  genJetAK8Idx = Var("?genJetFwdRef().backRef().isNonnull() && genJetFwdRef().backRef().pt() > 100.?genJetFwdRef().backRef().key():-1", int, doc="index of matched gen AK8 jet"),
741  )
742 )
743 
744 genSubJetAK8Table = cms.EDProducer("SimpleCandidateFlatTableProducer",
745  src = cms.InputTag("slimmedGenJetsAK8SoftDropSubJets"),
746  cut = cms.string(""), ## These don't get a pt cut, but in miniAOD only subjets from fat jets with pt > 100 are kept
747  name = cms.string("SubGenJetAK8"),
748  doc = cms.string("slimmedGenJetsAK8SoftDropSubJets, i.e. subjets of ak8 Jets made with visible genparticles"),
749  singleton = cms.bool(False), # the number of entries is variable
750  extension = cms.bool(False), # this is the main table for the genjets
751  variables = cms.PSet(P4Vars,
752  #anything else?
753  )
754 )
755 subjetMCTable = cms.EDProducer("SimpleCandidateFlatTableProducer",
756  src = subJetTable.src,
757  cut = subJetTable.cut,
758  name = subJetTable.name,
759  singleton = cms.bool(False),
760  extension = cms.bool(True),
761  variables = cms.PSet(
762  nBHadrons = Var("jetFlavourInfo().getbHadrons().size()", "uint8", doc="number of b-hadrons"),
763  nCHadrons = Var("jetFlavourInfo().getcHadrons().size()", "uint8", doc="number of c-hadrons"),
764  hadronFlavour = Var("hadronFlavour()", int, doc="flavour from hadron ghost clustering"),
765  )
766 )
767 
768 ### Era dependent customization
769 run2_miniAOD_80XLegacy.toModify( genJetFlavourTable, jetFlavourInfos = cms.InputTag("genJetFlavourAssociation"),)
770 (run2_nanoAOD_106Xv1 & ~run2_nanoAOD_devel).toModify( fatJetMCTable.variables, genJetAK8Idx = Var("?genJetFwdRef().backRef().isNonnull()?genJetFwdRef().backRef().key():-1", int, doc="index of matched gen AK8 jet"))
771 from RecoJets.JetProducers.QGTagger_cfi import QGTagger
772 qgtagger=QGTagger.clone(srcJets="updatedJets",srcVertexCollection="offlineSlimmedPrimaryVertices")
773 
774 from RecoJets.JetProducers.PileupJetID_cfi import pileupJetId, _chsalgos_94x, _chsalgos_102x, _chsalgos_106X_UL16, _chsalgos_106X_UL16APV,_chsalgos_106X_UL17, _chsalgos_106X_UL18
775 pileupJetId94X=pileupJetId.clone(jets="updatedJets",algos = cms.VPSet(_chsalgos_94x),inputIsCorrected=True,applyJec=False,vertexes="offlineSlimmedPrimaryVertices")
776 pileupJetId102X=pileupJetId.clone(jets="updatedJets",algos = cms.VPSet(_chsalgos_102x),inputIsCorrected=True,applyJec=False,vertexes="offlineSlimmedPrimaryVertices")
777 pileupJetId106XUL16=pileupJetId.clone(jets="updatedJets",algos = cms.VPSet(_chsalgos_106X_UL16),inputIsCorrected=True,applyJec=False,vertexes="offlineSlimmedPrimaryVertices")
778 pileupJetId106XUL16APV=pileupJetId.clone(jets="updatedJets",algos = cms.VPSet(_chsalgos_106X_UL16APV),inputIsCorrected=True,applyJec=False,vertexes="offlineSlimmedPrimaryVertices")
779 pileupJetId106XUL17=pileupJetId.clone(jets="updatedJets",algos = cms.VPSet(_chsalgos_106X_UL17),inputIsCorrected=True,applyJec=False,vertexes="offlineSlimmedPrimaryVertices")
780 pileupJetId106XUL18=pileupJetId.clone(jets="updatedJets",algos = cms.VPSet(_chsalgos_106X_UL18),inputIsCorrected=True,applyJec=False,vertexes="offlineSlimmedPrimaryVertices")
781 
782 
783 #before cross linking
784 jetSequence = cms.Sequence(jetCorrFactorsNano+updatedJets+tightJetId+tightJetIdLepVeto+bJetVars+qgtagger+jercVars+pileupJetId94X+pileupJetId102X+pileupJetId106XUL16+pileupJetId106XUL16APV+pileupJetId106XUL17+pileupJetId106XUL18+updatedJetsWithUserData+jetCorrFactorsAK8+updatedJetsAK8+tightJetIdAK8+tightJetIdLepVetoAK8+updatedJetsAK8WithUserData+chsForSATkJets+softActivityJets+softActivityJets2+softActivityJets5+softActivityJets10+finalJets+finalJetsAK8)
785 
786 _jetSequence_2016 = jetSequence.copy()
787 _jetSequence_2016.insert(_jetSequence_2016.index(tightJetId), looseJetId)
788 _jetSequence_2016.insert(_jetSequence_2016.index(tightJetIdAK8), looseJetIdAK8)
789 run2_jme_2016.toReplaceWith(jetSequence, _jetSequence_2016)
790 
791 
792 #HF shower shape variables:
793 #In 106X the variables are not computed/stored by default, but can be accessed/recomputed via modifiers
794 #For the two following modifiers, the producer is run on MINIAOD and one can directly access the variables
795 for modifier in run2_nanoAOD_106Xv2, run2_miniAOD_devel:
796  modifier.toModify( jetTable.variables, hfsigmaEtaEta = Var("userFloat('hfJetShowerShape:sigmaEtaEta')",float,doc="sigmaEtaEta for HF jets (noise discriminating variable)",precision=10))
797  modifier.toModify( jetTable.variables, hfsigmaPhiPhi = Var("userFloat('hfJetShowerShape:sigmaPhiPhi')",float,doc="sigmaPhiPhi for HF jets (noise discriminating variable)",precision=10))
798  modifier.toModify( jetTable.variables, hfcentralEtaStripSize = Var("userInt('hfJetShowerShape:centralEtaStripSize')", int, doc="eta size of the central tower strip in HF (noise discriminating variable) "))
799  modifier.toModify( jetTable.variables, hfadjacentEtaStripsSize = Var("userInt('hfJetShowerShape:adjacentEtaStripsSize')", int, doc="eta size of the strips next to the central tower strip in HF (noise discriminating variable) "))
800 
801 #For the following modifiers, the producer is not run on MINIAOD and one needs to run the producer in the NANOAOD step
802 from RecoJets.JetProducers.hfJetShowerShape_cfi import hfJetShowerShape
803 hfJetShowerShapeforNanoAOD = hfJetShowerShape.clone(jets="updatedJets",vertices="offlineSlimmedPrimaryVertices")
804 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016, run2_nanoAOD_94XMiniAODv1, run2_nanoAOD_94XMiniAODv2, run2_nanoAOD_102Xv1, run2_nanoAOD_106Xv1:
805  modifier.toModify(updatedJetsWithUserData.userFloats,
806  hfsigmaEtaEta = cms.InputTag('hfJetShowerShapeforNanoAOD:sigmaEtaEta'),
807  hfsigmaPhiPhi = cms.InputTag('hfJetShowerShapeforNanoAOD:sigmaPhiPhi'),
808  )
809  modifier.toModify(updatedJetsWithUserData.userInts,
810  hfcentralEtaStripSize = cms.InputTag('hfJetShowerShapeforNanoAOD:centralEtaStripSize'),
811  hfadjacentEtaStripsSize = cms.InputTag('hfJetShowerShapeforNanoAOD:adjacentEtaStripsSize'),
812  )
813  modifier.toModify( jetTable.variables, hfsigmaEtaEta = Var("userFloat('hfsigmaEtaEta')",float,doc="sigmaEtaEta for HF jets (noise discriminating variable)",precision=10))
814  modifier.toModify( jetTable.variables, hfsigmaPhiPhi = Var("userFloat('hfsigmaPhiPhi')",float,doc="sigmaPhiPhi for HF jets (noise discriminating variable)",precision=10))
815  modifier.toModify( jetTable.variables, hfcentralEtaStripSize = Var("userInt('hfcentralEtaStripSize')", int, doc="eta size of the central tower strip in HF (noise discriminating variable) "))
816  modifier.toModify( jetTable.variables, hfadjacentEtaStripsSize = Var("userInt('hfadjacentEtaStripsSize')", int, doc="eta size of the strips next to the central tower strip in HF (noise discriminating variable) "))
817  _jetSequence_rerunHFshowershape = jetSequence.copy()
818  _jetSequence_rerunHFshowershape.insert(_jetSequence_rerunHFshowershape.index(updatedJetsWithUserData), hfJetShowerShapeforNanoAOD)
819  modifier.toReplaceWith(jetSequence, _jetSequence_rerunHFshowershape)
820 
821 #after lepton collections have been run
822 jetLepSequence = cms.Sequence(lepInJetVars)
823 
824 #after cross linkining
825 jetTables = cms.Sequence(bjetNN+cjetNN+jetTable+fatJetTable+subJetTable+saJetTable+saTable)
826 
827 #MC only producers and tables
828 jetMC = cms.Sequence(jetMCTable+genJetTable+patJetPartons+genJetFlavourTable+genJetAK8Table+genJetAK8FlavourAssociation+genJetAK8FlavourTable+fatJetMCTable+genSubJetAK8Table+subjetMCTable)
829 _jetMC_pre94X = jetMC.copy()
830 _jetMC_pre94X.insert(_jetMC_pre94X.index(genJetFlavourTable),genJetFlavourAssociation)
831 _jetMC_pre94X.remove(genSubJetAK8Table)
832 run2_miniAOD_80XLegacy.toReplaceWith(jetMC, _jetMC_pre94X)
833 
834 
PileupJetID_cfi
jets_cff.nanoAOD_refineFastSim_bTagDeepFlav
def nanoAOD_refineFastSim_bTagDeepFlav(process)
Definition: jets_cff.py:538
common_cff.ExtVar
def ExtVar(tag, valtype, compression=None, doc=None, mcOnly=False, precision=-1)
Definition: common_cff.py:31
QGTagger_cfi
nano_eras_cff
jetCorrFactors_cfi
jetUpdater_cfi
common_cff.Var
def Var(expr, valtype, compression=None, doc=None, mcOnly=False, precision=-1)
Definition: common_cff.py:20
ak4PFJetsBetaStar_cfi
ak4PFJets_cfi
common_cff
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