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taus_cff.py
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1 import FWCore.ParameterSet.Config as cms
2 from PhysicsTools.NanoAOD.common_cff import *
3 from PhysicsTools.NanoAOD.nano_eras_cff import run3_nanoAOD_124
4 from PhysicsTools.NanoAOD.simpleCandidateFlatTableProducer_cfi import simpleCandidateFlatTableProducer
5 
6 from PhysicsTools.JetMCAlgos.TauGenJets_cfi import tauGenJets
7 from PhysicsTools.JetMCAlgos.TauGenJetsDecayModeSelectorAllHadrons_cfi import tauGenJetsSelectorAllHadrons
8 
9 
11 from PhysicsTools.NanoAOD.taus_updatedMVAIds_cff import *
12 
13 
14 
15 # Original DeepTau v2p5 in 12_4_X doesn't include WPs in MINIAOD
16 # Import thresholds here to define WPs manually from raw scores
17 from RecoTauTag.RecoTau.tauIdWPsDefs import WORKING_POINTS_v2p5
18 
19 finalTaus = cms.EDFilter("PATTauRefSelector",
20  src = cms.InputTag("slimmedTaus"),
21  cut = cms.string("pt > 18 && ((tauID('decayModeFindingNewDMs') > 0.5 && (tauID('byLooseCombinedIsolationDeltaBetaCorr3Hits') || (tauID('chargedIsoPtSumdR03')+max(0.,tauID('neutralIsoPtSumdR03')-0.072*tauID('puCorrPtSum'))<2.5) || tauID('byVVVLooseDeepTau2017v2p1VSjet') || tauID('byVVVLooseDeepTau2018v2p5VSjet'))) || (?isTauIDAvailable('byPNetVSjetraw')?tauID('byPNetVSjetraw'):-1) > {})".format(0.05))
22 )
23 
24 run3_nanoAOD_124.toModify(
25  finalTaus,
26  cut = cms.string("pt > 18 && ((tauID('decayModeFindingNewDMs') > 0.5 && (tauID('byLooseCombinedIsolationDeltaBetaCorr3Hits') || (tauID('chargedIsoPtSumdR03')+max(0.,tauID('neutralIsoPtSumdR03')-0.072*tauID('puCorrPtSum'))<2.5) || tauID('byVVVLooseDeepTau2017v2p1VSjet') || (tauID('byDeepTau2018v2p5VSjetraw') > {}))) || (?isTauIDAvailable('byPNetVSjetraw')?tauID('byPNetVSjetraw'):-1) > {})".format(WORKING_POINTS_v2p5["jet"]["VVVLoose"],0.05))
27 )
28 
29 
30 def _tauIdWPMask(pattern, choices, doc="", from_raw=False, wp_thrs=None):
31  if from_raw:
32  assert wp_thrs is not None, "wp_thrs argument in _tauIdWPMask() is None, expect it to be dict-like"
33 
34  var_definition = []
35  for wp_name in choices:
36  if not isinstance(wp_thrs[wp_name], float):
37  raise TypeError("Threshold for WP=%s is not a float number." % wp_name)
38  wp_definition = "test_bit(tauID('{}')-{}+1,0)".format(pattern, wp_thrs[wp_name])
39  var_definition.append(wp_definition)
40  var_definition = " + ".join(var_definition)
41  var_definition = ("?isTauIDAvailable('%s')?(" % pattern) + var_definition + "):0"
42  else:
43  var_definition = " + ".join(["tauID('%s')" % (pattern % c) for c in choices])
44  var_definition = ("?isTauIDAvailable('%s')?(" % (pattern % choices[0])) + var_definition + "):0"
45 
46  doc = doc + ": "+", ".join(["%d = %s" % (i,c) for (i,c) in enumerate(choices, start=1)])
47  return Var(var_definition, "uint8", doc=doc)
48 
49 
50 tauTable = simpleCandidateFlatTableProducer.clone(
51  src = cms.InputTag("linkedObjects","taus"),
52  name= cms.string("Tau"),
53  doc = cms.string("slimmedTaus after basic selection (" + finalTaus.cut.value()+")")
54 )
55 
56 _tauVarsBase = cms.PSet(P4Vars,
57  charge = Var("charge", "int16", doc="electric charge"),
58  jetIdx = Var("?hasUserCand('jet')?userCand('jet').key():-1", "int16", doc="index of the associated jet (-1 if none)"),
59  eleIdx = Var("?overlaps('electrons').size()>0?overlaps('electrons')[0].key():-1", "int16", doc="index of first matching electron"),
60  muIdx = Var("?overlaps('muons').size()>0?overlaps('muons')[0].key():-1", "int16", doc="index of first matching muon"),
61  svIdx1 = Var("?overlaps('vertices').size()>0?overlaps('vertices')[0].key():-1", "int16", doc="index of first matching secondary vertex"),
62  svIdx2 = Var("?overlaps('vertices').size()>1?overlaps('vertices')[1].key():-1", "int16", doc="index of second matching secondary vertex"),
63  nSVs = Var("?hasOverlaps('vertices')?overlaps('vertices').size():0", "uint8", doc="number of secondary vertices in the tau"),
64  decayMode = Var("decayMode()", "uint8"),
65  idDecayModeOldDMs = Var("(?isTauIDAvailable('decayModeFinding')?tauID('decayModeFinding'):-1) > 0", bool),
66  idDecayModeNewDMs = Var("(?isTauIDAvailable('decayModeFindingNewDMs')?tauID('decayModeFindingNewDMs'):-1) > 0", bool),
67  leadTkPtOverTauPt = Var("?leadChargedHadrCand.isNonnull()?leadChargedHadrCand.pt/pt:1",float, doc="pt of the leading track divided by tau pt",precision=10),
68  leadTkDeltaEta = Var("?leadChargedHadrCand.isNonnull()?(leadChargedHadrCand.eta - eta):0",float, doc="eta of the leading track, minus tau eta",precision=8),
69  leadTkDeltaPhi = Var("?leadChargedHadrCand.isNonnull()?deltaPhi(leadChargedHadrCand.phi, phi):0",float, doc="phi of the leading track, minus tau phi",precision=8),
70 
71  dxy = Var("?leadChargedHadrCand.isNonnull()?leadChargedHadrCand().dxy():0",float, doc="d_{xy} of lead track with respect to PV, in cm (with sign)",precision=10),
72  dz = Var("?leadChargedHadrCand.isNonnull()?leadChargedHadrCand().dz():0",float, doc="d_{z} of lead track with respect to PV, in cm (with sign)",precision=14),
73 
74  # these are too many, we may have to suppress some
75  rawIso = Var("?isTauIDAvailable('byCombinedIsolationDeltaBetaCorrRaw3Hits')?tauID('byCombinedIsolationDeltaBetaCorrRaw3Hits'):-1", float, doc = "combined isolation (deltaBeta corrections)", precision=10),
76  rawIsodR03 = Var("?isTauIDAvailable('chargedIsoPtSumdR03')?(tauID('chargedIsoPtSumdR03')+max(0.,tauID('neutralIsoPtSumdR03')-0.072*tauID('puCorrPtSum'))):-1", float, doc = "combined isolation (deltaBeta corrections, dR=0.3)", precision=10),
77  chargedIso = Var("?isTauIDAvailable('chargedIsoPtSum')?tauID('chargedIsoPtSum'):-1", float, doc = "charged isolation", precision=10),
78  neutralIso = Var("?isTauIDAvailable('neutralIsoPtSum')?tauID('neutralIsoPtSum'):-1", float, doc = "neutral (photon) isolation", precision=10),
79  puCorr = Var("?isTauIDAvailable('puCorrPtSum')?tauID('puCorrPtSum'):-1", float, doc = "pileup correction", precision=10),
80  photonsOutsideSignalCone = Var("?isTauIDAvailable('photonPtSumOutsideSignalCone')?tauID('photonPtSumOutsideSignalCone'):-1", float, doc = "sum of photons outside signal cone", precision=10),
81 
82  idAntiMu = _tauIdWPMask("againstMuon%s3", choices=("Loose","Tight"), doc= "Anti-muon discriminator V3: "),
83  idAntiEleDeadECal = Var("(?isTauIDAvailable('againstElectronDeadECAL')?tauID('againstElectronDeadECAL'):-1) > 0", bool, doc = "Anti-electron dead-ECal discriminator"),
84 
85 )
86 
87 _deepTauVars2017v2p1 = cms.PSet(
88  rawDeepTau2017v2p1VSe = Var("?isTauIDAvailable('byDeepTau2017v2p1VSeraw')?tauID('byDeepTau2017v2p1VSeraw'):-1", float, doc="byDeepTau2017v2p1VSe raw output discriminator (deepTau2017v2p1)", precision=10),
89  rawDeepTau2017v2p1VSmu = Var("?isTauIDAvailable('byDeepTau2017v2p1VSmuraw')?tauID('byDeepTau2017v2p1VSmuraw'):-1", float, doc="byDeepTau2017v2p1VSmu raw output discriminator (deepTau2017v2p1)", precision=10),
90  rawDeepTau2017v2p1VSjet = Var("?isTauIDAvailable('byDeepTau2017v2p1VSjetraw')?tauID('byDeepTau2017v2p1VSjetraw'):-1", float, doc="byDeepTau2017v2p1VSjet raw output discriminator (deepTau2017v2p1)", precision=10),
91  idDeepTau2017v2p1VSe = _tauIdWPMask("by%sDeepTau2017v2p1VSe",
92  choices=("VVVLoose","VVLoose","VLoose","Loose","Medium","Tight","VTight","VVTight"),
93  doc="byDeepTau2017v2p1VSe ID working points (deepTau2017v2p1)"),
94  idDeepTau2017v2p1VSmu = _tauIdWPMask("by%sDeepTau2017v2p1VSmu",
95  choices=("VLoose", "Loose", "Medium", "Tight"),
96  doc="byDeepTau2017v2p1VSmu ID working points (deepTau2017v2p1)"),
97  idDeepTau2017v2p1VSjet = _tauIdWPMask("by%sDeepTau2017v2p1VSjet",
98  choices=("VVVLoose","VVLoose","VLoose","Loose","Medium","Tight","VTight","VVTight"),
99  doc="byDeepTau2017v2p1VSjet ID working points (deepTau2017v2p1)"),
100 )
101 _deepTauVars2018v2p5 = cms.PSet(
102  rawDeepTau2018v2p5VSe = Var("?isTauIDAvailable('byDeepTau2018v2p5VSeraw')?tauID('byDeepTau2018v2p5VSeraw'):-1", float, doc="byDeepTau2018v2p5VSe raw output discriminator (deepTau2018v2p5)", precision=10),
103  rawDeepTau2018v2p5VSmu = Var("?isTauIDAvailable('byDeepTau2018v2p5VSmuraw')?tauID('byDeepTau2018v2p5VSmuraw'):-1", float, doc="byDeepTau2018v2p5VSmu raw output discriminator (deepTau2018v2p5)", precision=10),
104  rawDeepTau2018v2p5VSjet = Var("?isTauIDAvailable('byDeepTau2018v2p5VSjetraw')?tauID('byDeepTau2018v2p5VSjetraw'):-1", float, doc="byDeepTau2018v2p5VSjet raw output discriminator (deepTau2018v2p5)", precision=10),
105  idDeepTau2018v2p5VSe = _tauIdWPMask("by%sDeepTau2018v2p5VSe",
106  choices=("VVVLoose","VVLoose","VLoose","Loose","Medium","Tight","VTight","VVTight"),
107  doc="byDeepTau2018v2p5VSe ID working points (deepTau2018v2p5)"),
108  idDeepTau2018v2p5VSmu = _tauIdWPMask("by%sDeepTau2018v2p5VSmu",
109  choices=("VLoose", "Loose", "Medium", "Tight"),
110  doc="byDeepTau2018v2p5VSmu ID working points (deepTau2018v2p5)"),
111  idDeepTau2018v2p5VSjet = _tauIdWPMask("by%sDeepTau2018v2p5VSjet",
112  choices=("VVVLoose","VVLoose","VLoose","Loose","Medium","Tight","VTight","VVTight"),
113  doc="byDeepTau2018v2p5VSjet ID working points (deepTau2018v2p5)"),
114 )
115 
116 _pnet2023 = cms.PSet(
117  decayModePNet = Var("?isTauIDAvailable('byPNetDecayMode')?tauID('byPNetDecayMode'):-1", "int16",doc="decay mode of the highest tau score of ParticleNet"),
118  rawPNetVSe = Var("?isTauIDAvailable('byPNetVSeraw')?tauID('byPNetVSeraw'):-1", float, doc="raw output of ParticleNetVsE discriminator (PNet 2023)", precision=10),
119  rawPNetVSmu = Var("?isTauIDAvailable('byPNetVSmuraw')?tauID('byPNetVSmuraw'):-1", float, doc="raw output of ParticleNetVsMu discriminator (PNet 2023)", precision=10),
120  rawPNetVSjet = Var("?isTauIDAvailable('byPNetVSjetraw')?tauID('byPNetVSjetraw'):-1", float, doc="raw output of ParticleNetVsJet discriminator (PNet 2023)", precision=10),
121  ptCorrPNet = Var("?isTauIDAvailable('byPNetPtCorr')?tauID('byPNetPtCorr'):1", float, doc="pt correction (PNet 2023)", precision=10),
122  qConfPNet = Var("?isTauIDAvailable('byPNetQConf')?tauID('byPNetQConf'):0", float, doc="signed charge confidence (PNet 2023)", precision=10),
123  probDM0PNet = Var("?isTauIDAvailable('byPNetProb1h0pi0')?tauID('byPNetProb1h0pi0'):-1", float, doc="normalised probablity of decayMode 0, 1h+0pi0 (PNet 2023)", precision=10),
124  probDM1PNet = Var("?isTauIDAvailable('byPNetProb1h1pi0')?tauID('byPNetProb1h1pi0'):-1", float, doc="normalised probablity of decayMode 1, 1h+1pi0 (PNet 2023)", precision=10),
125  probDM2PNet = Var("?isTauIDAvailable('byPNetProb1h2pi0')?tauID('byPNetProb1h2pi0'):-1", float, doc="normalised probablity of decayMode 2, 1h+2pi0 (PNet 2023)", precision=10),
126  probDM10PNet = Var("?isTauIDAvailable('byPNetProb3h0pi0')?tauID('byPNetProb3h0pi0'):-1", float, doc="normalised probablity of decayMode 10, 3h+0pi0 (PNet 2023)", precision=10),
127  probDM11PNet = Var("?isTauIDAvailable('byPNetProb3h1pi0')?tauID('byPNetProb3h1pi0'):-1", float, doc="normalised probablity of decayMode 11, 3h+1pi0 (PNet 2023)", precision=10),
128 )
129 
130 _variablesMiniV2 = cms.PSet(
131  _tauVarsBase,
132  _deepTauVars2017v2p1,
133  _deepTauVars2018v2p5,
134  _pnet2023
135 )
136 
137 tauTable.variables = _variablesMiniV2
138 
139 run3_nanoAOD_124.toModify(
140  tauTable.variables,
141  idDeepTau2018v2p5VSe = _tauIdWPMask("byDeepTau2018v2p5VSeraw",
142  choices=("VVVLoose","VVLoose","VLoose","Loose","Medium","Tight","VTight","VVTight"),
143  doc="byDeepTau2018v2p5VSe ID working points (deepTau2018v2p5)",
144  from_raw=True, wp_thrs=WORKING_POINTS_v2p5["e"]),
145  idDeepTau2018v2p5VSmu = _tauIdWPMask("byDeepTau2018v2p5VSmuraw",
146  choices=("VLoose", "Loose", "Medium", "Tight"),
147  doc="byDeepTau2018v2p5VSmu ID working points (deepTau2018v2p5)",
148  from_raw=True, wp_thrs=WORKING_POINTS_v2p5["mu"]),
149  idDeepTau2018v2p5VSjet = _tauIdWPMask("byDeepTau2018v2p5VSjetraw",
150  choices=("VVVLoose","VVLoose","VLoose","Loose","Medium","Tight","VTight","VVTight"),
151  doc="byDeepTau2018v2p5VSjet ID working points (deepTau2018v2p5)",
152  from_raw=True, wp_thrs=WORKING_POINTS_v2p5["jet"])
153 )
154 
155 
156 tauGenJetsForNano = tauGenJets.clone(
157  GenParticles = "finalGenParticles",
158  includeNeutrinos = False
159 )
160 
161 tauGenJetsSelectorAllHadronsForNano = tauGenJetsSelectorAllHadrons.clone(
162  src = "tauGenJetsForNano"
163 )
164 
165 genVisTaus = cms.EDProducer("GenVisTauProducer",
166  src = cms.InputTag("tauGenJetsSelectorAllHadronsForNano"),
167  srcGenParticles = cms.InputTag("finalGenParticles")
168 )
169 
170 genVisTauTable = simpleCandidateFlatTableProducer.clone(
171  src = cms.InputTag("genVisTaus"),
172  cut = cms.string("pt > 10."),
173  name = cms.string("GenVisTau"),
174  doc = cms.string("gen hadronic taus "),
175  variables = cms.PSet(
176  pt = Var("pt", float,precision=8),
177  phi = Var("phi", float,precision=8),
178  eta = Var("eta", float,precision=8),
179  mass = Var("mass", float,precision=8),
180  charge = Var("charge", "int16"),
181  status = Var("status", "uint8", doc="Hadronic tau decay mode. 0=OneProng0PiZero, 1=OneProng1PiZero, 2=OneProng2PiZero, 10=ThreeProng0PiZero, 11=ThreeProng1PiZero, 15=Other"),
182  genPartIdxMother = Var("?numberOfMothers>0?motherRef(0).key():-1", "int16", doc="index of the mother particle"),
183  )
184 )
185 
186 tausMCMatchLepTauForTable = cms.EDProducer("MCMatcher", # cut on deltaR, deltaPt/Pt; pick best by deltaR
187  src = tauTable.src, # final reco collection
188  matched = cms.InputTag("finalGenParticles"), # final mc-truth particle collection
189  mcPdgId = cms.vint32(11,13), # one or more PDG ID (11 = electron, 13 = muon); absolute values (see below)
190  checkCharge = cms.bool(False), # True = require RECO and MC objects to have the same charge
191  mcStatus = cms.vint32(), # PYTHIA status code (1 = stable, 2 = shower, 3 = hard scattering)
192  maxDeltaR = cms.double(0.3), # Minimum deltaR for the match
193  maxDPtRel = cms.double(0.5), # Minimum deltaPt/Pt for the match
194  resolveAmbiguities = cms.bool(True), # Forbid two RECO objects to match to the same GEN object
195  resolveByMatchQuality = cms.bool(True), # False = just match input in order; True = pick lowest deltaR pair first
196 )
197 
198 tausMCMatchHadTauForTable = cms.EDProducer("MCMatcher", # cut on deltaR, deltaPt/Pt; pick best by deltaR
199  src = tauTable.src, # final reco collection
200  matched = cms.InputTag("genVisTaus"), # generator level hadronic tau decays
201  mcPdgId = cms.vint32(15), # one or more PDG ID (15 = tau); absolute values (see below)
202  checkCharge = cms.bool(False), # True = require RECO and MC objects to have the same charge
203  mcStatus = cms.vint32(), # CV: no *not* require certain status code for matching (status code corresponds to decay mode for hadronic tau decays)
204  maxDeltaR = cms.double(0.3), # Maximum deltaR for the match
205  maxDPtRel = cms.double(1.), # Maximum deltaPt/Pt for the match
206  resolveAmbiguities = cms.bool(True), # Forbid two RECO objects to match to the same GEN object
207  resolveByMatchQuality = cms.bool(True), # False = just match input in order; True = pick lowest deltaR pair first
208 )
209 
210 tauMCTable = cms.EDProducer("CandMCMatchTableProducer",
211  src = tauTable.src,
212  mcMap = cms.InputTag("tausMCMatchLepTauForTable"),
213  mcMapVisTau = cms.InputTag("tausMCMatchHadTauForTable"),
214  objName = tauTable.name,
215  objType = tauTable.name, #cms.string("Tau"),
216  branchName = cms.string("genPart"),
217  docString = cms.string("MC matching to status==2 taus"),
218 )
219 
220 
221 tauTask = cms.Task(finalTaus)
222 tauTablesTask = cms.Task(tauTable)
223 
224 genTauTask = cms.Task(tauGenJetsForNano,tauGenJetsSelectorAllHadronsForNano,genVisTaus,genVisTauTable)
225 tauMCTask = cms.Task(genTauTask,tausMCMatchLepTauForTable,tausMCMatchHadTauForTable,tauMCTable)
226 
TauGenJetsDecayModeSelectorAllHadrons_cfi
common_cff.Var
def Var(expr, valtype, doc=None, precision=-1)
Definition: common_cff.py:16
nano_eras_cff
taus_updatedMVAIds_cff
Updated tau collection with MVA-based tau-Ids rerun ####### Used only in some eras.
TauGenJets_cfi
join
static std::string join(char **cmd)
Definition: RemoteFile.cc:19
taus_cff._tauIdWPMask
def _tauIdWPMask(pattern, choices, doc="", from_raw=False, wp_thrs=None)
Tables for final output and docs ##########################.
Definition: taus_cff.py:30
common_cff
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