nanoDQM_cfi.py

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# automatically generated by prepareDQM.py
import FWCore.ParameterSet.Config as cms
from PhysicsTools.NanoAOD.nanoDQM_tools_cff import *

from DQMServices.Core.DQMEDAnalyzer import DQMEDAnalyzer
nanoDQM = DQMEDAnalyzer("NanoAODDQM",
    vplots = cms.PSet(
        CaloMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('sumEt', 'sumEt', 20, 200, 3000, 'scalar sum of Et'),
            )
        ),
        ChsMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'raw chs PF MET phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'raw chs PF MET pt'),
                Plot1D('sumEt', 'sumEt', 20, 600, 5000, 'raw chs PF scalar sum of Et'),
            )
        ),
        CorrT1METJet = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 20, -0.5, 19.5, 'Additional low-pt jets for Type-1 MET re-correction'),
                Plot1D('area', 'area', 20, 0.2, 0.8, 'jet catchment area, for JECs'),
                Plot1D('eta', 'eta', 20, -5, 5, 'eta'),
                Plot1D('muonSubtrFactor', 'muonSubtrFactor', 20, 0, 1, '1-(muon-subtracted raw pt)/(raw pt)'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('rawPt', 'rawPt', 20, 5, 25, "pt()*jecFactor('Uncorrected')"),
            )
        ),
        DeepMETResolutionTune = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'Deep MET Resolution Tune phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'Deep MET Response Tune pt'),
            )
        ),
        DeepMETResponseTune = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'Deep MET Response Tune phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'Deep MET Response Tune pt'),
            )
        ),
        Electron = cms.PSet(
            sels = cms.PSet(
                Good = cms.string('pt > 15 && abs(dxy) < 0.2 && abs(dz) < 0.5 && cutBased >= 3 && miniPFRelIso_all < 0.4')
            ),
            plots = cms.VPSet(
                Count1D('_size', 8, -0.5, 7.5, 'slimmedElectrons after basic selection (pt > 5 )'),
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'electric charge'),
                Plot1D('convVeto', 'convVeto', 2, -0.5, 1.5, 'pass conversion veto'),
                Plot1D('cutBased', 'cutBased', 5, -0.5, 4.5, 'cut-based ID (0:fail, 1:veto, 2:loose, 3:medium, 4:tight)'),
                Plot1D('cutBased_Fall17V2', 'cutBased_Fall17V2', 5, -0.5, 4.5, 'cut-based ID Fall17 V2 (0:fail, 1:veto, 2:loose, 3:medium, 4:tight)'),
                Plot1D('cutBased_HEEP', 'cutBased_HEEP', 2, -0.5, 1.5, 'cut-based HEEP ID'),
                Plot1D('deltaEtaSC', 'deltaEtaSC', 20, -0.2, 0.2, 'delta eta (SC,ele) with sign'),
                Plot1D('dr03EcalRecHitSumEt', 'dr03EcalRecHitSumEt', 20, 0, 30, 'Non-PF Ecal isolation within a delta R cone of 0.3 with electron pt > 35 GeV'),
                Plot1D('dr03HcalDepth1TowerSumEt', 'dr03HcalDepth1TowerSumEt', 20, 0, 20, 'Non-PF Hcal isolation within a delta R cone of 0.3 with electron pt > 35 GeV'),
                Plot1D('dr03TkSumPt', 'dr03TkSumPt', 20, 0, 40, 'Non-PF track isolation within a delta R cone of 0.3 with electron pt > 35 GeV'),
                Plot1D('dr03TkSumPtHEEP', 'dr03TkSumPtHEEP', 20, 0, 40, 'Non-PF track isolation within a delta R cone of 0.3 with electron pt > 35 GeV used in HEEP ID'),
                Plot1D('dxy', 'dxy', 20, -0.1, 0.1, 'dxy (with sign) wrt first PV, in cm'),
                Plot1D('dxyErr', 'dxyErr', 20, 0, 0.2, 'dxy uncertainty, in cm'),
                Plot1D('dz', 'dz', 20, -0.3, 0.3, 'dz (with sign) wrt first PV, in cm'),
                Plot1D('dzErr', 'dzErr', 20, 0, 0.2, 'dz uncertainty, in cm'),
                Plot1D('fbrem', 'fbrem', 20, -5.0, 5.0, 'Fraction of brem'),
                Plot1D('rawEnergy', 'rawEnergy', 100, 0, 1000.0, 'raw energy of Supercluster'),
                Plot1D('PreshowerEnergy', 'PreshowerEnergy', 20, 0, 100.0, 'energy deposited in the preshower'),
                Plot1D('ecalEnergy', 'ecalEnergy', 100, 0, 1000.0, 'energy after ECAL-only regression applied'),
                Plot1D('ecalEnergyError', 'ecalEnergyError', 20, 0, 100.0, 'ecalEnergy error'),
                Plot1D('gsfTrkpMode', 'gsfTrkpMode', 100, 0, 1000000.0, 'GSF track pMode'),
                Plot1D('gsfTrkpModeErr', 'gsfTrkpModeErr', 100, 0, 1000000.0, 'GSF track pMode error'),
                Plot1D('gsfTrketaMode', 'gsfTrketaMode', 20, -3.5, 3.5, 'GSF track eta Mode'),
                Plot1D('gsfTrkphiMode', 'gsfTrkphiMode', 20, -4, 4, 'GSF track phi Mode'),
                Plot1D('isEcalDriven', 'isEcalDriven', 2, -0.5, 1.5, 'is ECAL driven if true'),
                Plot1D('isEB', 'isEB', 2, -0.5, 1.5, 'object in barrel if true derived from the seedCrystal and detID information'),
                Plot1D('eInvMinusPInv', 'eInvMinusPInv', 20, -0.1, 0.1, '1/E_SC - 1/p_trk'),
                Plot1D('energyErr', 'energyErr', 20, 0, 90, 'energy error of the cluster-track combination'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('genPartFlav', 'genPartFlav', 20, 0, 30, 'Flavour of genParticle for MC matching to status==1 electrons or photons: 1 = prompt electron (including gamma*->mu mu), 15 = electron from prompt tau, 22 = prompt photon (likely conversion), 5 = electron from b, 4 = electron from c, 3 = electron from light or unknown, 0 = unmatched'),
                NoPlot('genPartIdx'),
                Plot1D('hoe', 'hoe', 20, 0, 1, 'H over E'),
                Plot1D('ip3d', 'ip3d', 20, 0, 0.2, '3D impact parameter wrt first PV, in cm'),
                Plot1D('isPFcand', 'isPFcand', 2, -0.5, 1.5, 'electron is PF candidate'),
                NoPlot('jetIdx'),
                Plot1D('jetPtRelv2', 'jetPtRelv2', 20, 0, 60, 'Relative momentum of the lepton with respect to the closest jet after subtracting the lepton'),
                Plot1D('jetRelIso', 'jetRelIso', 20, -0.2, 1.8, 'Relative isolation in matched jet (1/ptRatio-1, pfRelIso04_all if no matched jet)'),
                Plot1D('jetRelIso_Fall17V2', 'jetRelIso_Fall17V2', 20, -0.2, 1.8, 'Relative isolation in matched jet (1/ptRatio-1, pfRelIso04_all if no matched jet)'),
                Plot1D('lostHits', 'lostHits', 4, -0.5, 3.5, 'number of missing inner hits'),
                Plot1D('jetNDauCharged', 'jetNDauCharged', 20, -0.5, 19.5, 'number of charged daughters of the closest jet'),
                NoPlot('mass'),
                Plot1D('mvaIso_Fall17V2', 'mvaIso_Fall17V2', 20, -1, 1, 'MVA Iso ID score, Fall17V2'),
                Plot1D('mvaIso_Fall17V2_WP80', 'mvaIso_Fall17V2_WP80', 2, -0.5, 1.5, 'MVA Iso ID WP80, Fall17V2'),
                Plot1D('mvaIso_Fall17V2_WP90', 'mvaIso_Fall17V2_WP90', 2, -0.5, 1.5, 'MVA Iso ID WP90, Fall17V2'),
                Plot1D('mvaIso_Fall17V2_WPL', 'mvaIso_Fall17V2_WPL', 2, -0.5, 1.5, 'MVA Iso ID loose WP, Fall17V2'),
                Plot1D('mvaIso', 'mvaIso', 20, -1, 1, 'MVA Iso ID score, Winter22V1'),
                Plot1D('mvaIso_WP80', 'mvaIso_WP80', 2, -0.5, 1.5, 'MVA Iso ID WP80, Winter22V1'),
                Plot1D('mvaIso_WP90', 'mvaIso_WP90', 2, -0.5, 1.5, 'MVA Iso ID WP90, Winter22V1'),
                Plot1D('mvaNoIso', 'mvaNoIso', 20, -1, 1, 'MVA noIso ID score, Winter22V1'),
                Plot1D('mvaNoIso_WP80', 'mvaNoIso_WP80', 2, -0.5, 1.5, 'MVA noIso ID WP80, Winter22V1'),
                Plot1D('mvaNoIso_WP90', 'mvaNoIso_WP90', 2, -0.5, 1.5, 'MVA noIso ID WP90, Winter22V1'),
                Plot1D('mvaNoIso_Fall17V2', 'mvaNoIso_Fall17V2', 20, -1, 1, 'MVA noIso ID score, Fall17V2'),
                Plot1D('mvaNoIso_Fall17V2_WP80', 'mvaNoIso_Fall17V2_WP80', 2, -0.5, 1.5, 'MVA noIso ID WP80, Fall17V2'),
                Plot1D('mvaNoIso_Fall17V2_WP90', 'mvaNoIso_Fall17V2_WP90', 2, -0.5, 1.5, 'MVA noIso ID WP90, Fall17V2'),
                Plot1D('mvaNoIso_Fall17V2_WPL', 'mvaNoIso_Fall17V2_WPL', 2, -0.5, 1.5, 'MVA noIso ID loose WP, Fall17V2'),
                Plot1D('mvaHZZIso', 'mvaHZZIso', 20, -1, 1, 'HZZ MVA Iso ID score'),
                Plot1D('mvaIso_WPHZZ', 'mvaIso_WPHZZ', 2, -0.5, 1.5, 'MVA Iso ID WPHZZ, Winter22V1'),
                Plot1D('mvaTTH', 'mvaTTH', 20, -1, 1, 'TTH MVA lepton ID score'),
                Plot1D('pdgId', 'pdgId', 27, -13.5, 13.5, 'PDG code assigned by the event reconstruction (not by MC truth)'),
                Plot1D('miniPFRelIso_all', 'miniPFRelIso_all', 20, 0, 1, 'mini PF relative isolation, total (with scaled rho*EA PU corrections)'),
                Plot1D('miniPFRelIso_chg', 'miniPFRelIso_chg', 20, 0, 1, 'mini PF relative isolation, charged component'),
                Plot1D('pfRelIso03_all', 'pfRelIso03_all', 20, 0, 2, 'PF relative isolation dR=0.3, total (with rho*EA PU corrections)'),
                Plot1D('pfRelIso03_chg', 'pfRelIso03_chg', 20, 0, 2, 'PF relative isolation dR=0.3, charged component'),
                Plot1D('miniPFRelIso_all_Fall17V2', 'miniPFRelIso_all_Fall17V2', 20, 0, 1, 'mini PF relative isolation, total (with scaled rho*EA PU corrections)'),
                Plot1D('miniPFRelIso_chg_Fall17V2', 'miniPFRelIso_chg_Fall17V2', 20, 0, 1, 'mini PF relative isolation, charged component'),
                Plot1D('pfRelIso03_all_Fall17V2', 'pfRelIso03_all_Fall17V2', 20, 0, 2, 'PF relative isolation dR=0.3 with 94 EffArea, total (with rho*EA PU corrections)'),
                Plot1D('pfRelIso03_chg_Fall17V2', 'pfRelIso03_chg_Fall17V2', 20, 0, 2, 'PF relative isolation dR=0.3 with 94 EffArea, charged component'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                NoPlot('photonIdx'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt (corrected)'),
                Plot1D('r9', 'r9', 20, 0, 1.1, 'R9 of the supercluster, calculated with full 5x5 region'),
                Plot1D('scEtOverPt', 'scEtOverPt', 20, -0.5, 0.5, '(supercluster transverse energy)/pt - 1'),
                Plot1D('seedGain', 'seedGain', 12, 0.5, 12.5, 'Gain of the seed crystal'),
                Plot1D('seediEtaOriX', 'seediEtaOriX', 200, -90, 110, 'iEta/iX of seed crystal'),
                Plot1D('seediPhiOriY', 'seediPhiOriY', 380, -10, 370, 'iPhi/iY of seed crystal'),
                Plot1D('sieie', 'sieie', 20, 0, 0.05, 'sigma_IetaIeta of the supercluster, calculated with full 5x5 region'),
                Plot1D('sip3d', 'sip3d', 20, 0, 20, '3D impact parameter significance wrt first PV, in cm'),
                Plot1D('tightCharge', 'tightCharge', 3, -0.5, 2.5, 'Tight charge criteria (0:none, 1:isGsfScPixChargeConsistent, 2:isGsfCtfScPixChargeConsistent)'),
                NoPlot('vidNestedWPBitmap'),
                NoPlot('vidNestedWPBitmap_Fall17V2'),
                NoPlot('vidNestedWPBitmapHEEP'),
            )
        ),

        LowPtElectron = cms.PSet(
            sels = cms.PSet(
                Good = cms.string('pt > 1. && ID > 5.')
            ),
            plots = cms.VPSet(
                #
                Count1D('_size', 8, -0.5, 7.5, 'slimmedLowPtElectrons after basic selection'),
                # CandVars
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'electric charge'),
                Plot1D('eta', 'eta', 20, -3., 3., 'eta'),
                NoPlot('mass'),
                Plot1D('pdgId', 'pdgId', 101, -50.5, 50.5, 'PDG code assigned by the event reconstruction (not by MC truth)'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 40, 0., 20., 'pt (corrected)'),
                # BDT scores and WPs
                Plot1D('embeddedID', 'embeddedID', 40, -10., 10., 'Embedded ID, BDT (raw) score'),
                Plot1D('ID', 'ID', 40, -10., 10., 'ID, BDT (raw) score'),
                Plot1D('unbiased', 'unbiased', 40, -10., 10., 'ElectronSeed, pT- and dxy- agnostic BDT (raw) score'),
                Plot1D('ptbiased', 'ptbiased', 40, -10., 10., 'ElectronSeed, pT- and dxy- dependent BDT (raw) score'),
                # Isolation
                Plot1D('miniPFRelIso_chg', 'miniPFRelIso_chg', 20, 0., 1., 'mini PF relative isolation, charged component'),
                Plot1D('miniPFRelIso_all', 'miniPFRelIso_all', 20, 0., 1., 'mini PF relative isolation, total (with scaled rho*EA PU corrections)'),
                # Conversions
                Plot1D('convVeto', 'convVeto', 2, -0.5, 1.5, 'pass conversion veto'),
                Plot1D('convWP', 'convWP', 8, -0.5, 7.5, 'conversion flag bit map: 1=Veto, 2=Loose, 3=Tight'),
                Plot1D('convVtxRadius', 'convVtxRadius', 40, 0., 20.0, 'conversion vertex radius (cm)'),
                # Tracking
                Plot1D('lostHits', 'lostHits', 4, -0.5, 3.5, 'number of missing inner hits'),
                # Cluster-related
                Plot1D('energyErr', 'energyErr', 40, 0., 20., 'energy error of the cluster from regression'),
                Plot1D('deltaEtaSC', 'deltaEtaSC', 20, -0.2, 0.2, 'delta eta (SC,ele) with sign'),
                Plot1D('r9', 'r9', 20, 0, 1.1, 'R9 of the supercluster, calculated with full 5x5 region'),
                Plot1D('sieie', 'sieie', 20, 0, 0.05, 'sigma_IetaIeta of the supercluster, calculated with full 5x5 region'),
                Plot1D('eInvMinusPInv', 'eInvMinusPInv', 20, -0.1, 0.1, '1/E_SC - 1/p_trk'),
                Plot1D('scEtOverPt', 'scEtOverPt', 20, -0.5, 0.5, '(supercluster transverse energy)/pt - 1'),
                Plot1D('hoe', 'hoe', 20, 0, 0.6, 'H over E'),
                # Displacement
                Plot1D('dxy', 'dxy', 20, -0.1, 0.1, 'dxy (with sign) wrt first PV, in cm'),
                Plot1D('dz', 'dz', 20, -0.3, 0.3, 'dz (with sign) wrt first PV, in cm'),
                Plot1D('dxyErr', 'dxyErr', 20, 0., 0.2, 'dxy uncertainty, in cm'),
                Plot1D('dzErr', 'dzErr', 20, 0., 0.2, 'dz uncertainty, in cm'),
            ),
        ),

        FatJet = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 6, -0.5, 5.5, 'slimmedJetsAK8, i.e. ak8 fat jets for boosted analysis'),
                Plot1D('area', 'area', 20, 2, 4, 'jet catchment area, for JECs'),
                Plot1D('btagCMVA', 'btagCMVA', 20, -1, 1, 'CMVA V2 btag discriminator'),
                Plot1D('btagDDBvL', 'btagDDBvL', 20, -1, 1, 'DeepDoubleX (mass-decorrelated) discriminator for H(Z)->bb vs QCD'),
                Plot1D('btagDDBvLV2', 'btagDDBvLV2', 20, 0, 1, 'DeepDoubleX V2(mass-decorrelated) discriminator for H(Z)->bb vs QCD'),
                Plot1D('btagDDBvL_noMD', 'btagDDBvL_noMD', 20, 0, 1, 'DeepDoubleX discriminator (no mass-decorrelation) for H(Z)->bb vs QCD'),
                Plot1D('btagDDCvB', 'btagDDCvB', 20, -1, 1, 'DeepDoubleX (mass-decorrelated) discriminator for H(Z)->cc vs H(Z)->bb'),
                Plot1D('btagDDCvBV2', 'btagDDCvBV2', 20, 0, 1, 'DeepDoubleX V2 (mass-decorrelated) discriminator for H(Z)->cc vs H(Z)->bb'),
                Plot1D('btagDDCvB_noMD', 'btagDDCvB_noMD', 20, 0, 1, 'DeepDoubleX discriminator (no mass-decorrelation) for H(Z)->cc vs H(Z)->bb'),
                Plot1D('btagDDCvL', 'btagDDCvL', 20, -1, 1, 'DeepDoubleX (mass-decorrelated) discriminator for H(Z)->cc vs QCD'),
                Plot1D('btagDDCvLV2', 'btagDDCvLV2', 20, 0, 1, 'DeepDoubleX V2 (mass-decorrelated) discriminator for H(Z)->cc vs QCD'),
                Plot1D('btagDDCvL_noMD', 'btagDDCvL_noMD', 20, 0, 1, 'DeepDoubleX discriminator (no mass-decorrelation) for H(Z)->cc vs QCD'),
                Plot1D('btagDeepB', 'btagDeepB', 20, -1, 1, 'Deep B+BB btag discriminator'),
                Plot1D('particleNetWithMass_QCD', 'particleNetWithMass_QCD', 20, -1, 1, 'ParticleNet (mass-correlated) QCD score'),
                Plot1D('particleNetWithMass_TvsQCD', 'particleNetWithMass_TvsQCD', 20, 0, 1, 'ParticleNet (mass-correlated) top vs. QCD score'),
                Plot1D('particleNetWithMass_WvsQCD', 'particleNetWithMass_WvsQCD', 20, 0, 1, 'ParticleNet (mass-correlated) W vs. QCD score'),
                Plot1D('particleNetWithMass_ZvsQCD', 'particleNetWithMass_ZvsQCD', 20, 0, 1, 'ParticleNet (mass-correlated) Z vs. QCD score'),
                Plot1D('particleNetWithMass_H4qvsQCD', 'particleNetWithMass_H4qvsQCD', 20, 0, 1, 'ParticleNet (mass-correlated) H(->VV->qqqq) vs. QCD score'),
                Plot1D('particleNetWithMass_HbbvsQCD', 'particleNetWithMass_HbbvsQCD', 20, 0, 1, 'ParticleNet (mass-correlated) H->bb vs. QCD score'),
                Plot1D('particleNetWithMass_HccvsQCD', 'particleNetWithMass_HccvsQCD', 20, 0, 1, 'ParticleNet (mass-correlated) H->cc vs. QCD score'),
                Plot1D('particleNet_QCD', 'particleNet_QCD', 20, 0, 1, 'ParticleNet QCD score'),
                Plot1D('particleNet_QCD2HF', 'particleNet_QCD2HF', 20, 0, 1, 'ParticleNet QCD 2HF (b,c) score'),
                Plot1D('particleNet_QCD1HF', 'particleNet_QCD1HF', 20, 0, 1, 'ParticleNet QCD 1HF (b,c) score'),
                Plot1D('particleNet_QCD0HF', 'particleNet_QCD0HF', 20, 0, 1, 'ParticleNet QCD 0HF (b,c) score'),
                Plot1D('particleNet_massCorr', 'particleNet_massCorr', 20, 0, 2, 'ParticleNet mass regression, correction relative to jet mass'),
                Plot1D('particleNet_XbbVsQCD', 'particleNet_XbbVsQCD', 20, 0, 1, 'ParticleNet X->bb vs. QCD score'),
                Plot1D('particleNet_XccVsQCD', 'particleNet_XccVsQCD', 20, 0, 1, 'ParticleNet X->cc vs. QCD score'),
                Plot1D('particleNet_XqqVsQCD', 'particleNet_XqqVsQCD', 20, 0, 1, 'ParticleNet X->qq (uds) vs. QCD score'),
                Plot1D('particleNet_XggVsQCD', 'particleNet_XggVsQCD', 20, 0, 1, 'ParticleNet X->gg vs. QCD score'),
                Plot1D('particleNet_XttVsQCD', 'particleNet_XttVsQCD', 20, 0, 1, 'ParticleNet X->tautau vs. QCD score'),
                Plot1D('particleNet_XtmVsQCD', 'particleNet_XtmVsQCD', 20, 0, 1, 'ParticleNet X->mutau vs. QCD score'),
                Plot1D('particleNet_XteVsQCD', 'particleNet_XteVsQCD', 20, 0, 1, 'ParticleNet X->etau vs. QCD score'),
                Plot1D('btagHbb', 'btagHbb', 20, -1, 1, 'Higgs to BB tagger discriminator'),
                NoPlot('electronIdx3SJ'),
                Plot1D('eta', 'eta', 20, -4, 4, 'eta'),
                NoPlot('genJetAK8Idx'),
                Plot1D('hadronFlavour', 'hadronFlavour', 6, -0.5, 5.5, 'flavour from hadron ghost clustering'),
                Plot1D('jetId', 'jetId', 3, 0, 3, 'Jet ID flags bit1 is loose (always false in 2017 since it does not exist), bit2 is tight, bit3 is tightLepVeto', bitset=True),
                Plot1D('lsf3', 'lsf3', 20, -1, 1, 'Lepton Subjet Fraction (3 subjets)'),
                Plot1D('mass', 'mass', 20, 0, 300, 'mass'),
                Plot1D('msoftdrop', 'msoftdrop', 20, -300, 300, 'Soft drop mass'),
                NoPlot('muonIdx3SJ'),
                Plot1D('n2b1', 'n2b1', 20, 0, 1, 'N2 (beta=1)'),
                Plot1D('n3b1', 'n3b1', 20, 0, 5, 'N3 (beta=1)'),
                Plot1D('nConstituents', 'nConstituents', 20, 0, 80, 'Number of particles in the jet'),
                Plot1D('chMultiplicity', 'chMultiplicity', 20, 0, 80, '(Puppi-weighted) Number of charged particles in the jet'),
                Plot1D('neMultiplicity', 'neMultiplicity', 20, 0, 80, '(Puppi-weighted) Number of neutral particles in the jet'),
                Plot1D('chEmEF', 'chEmEF', 20, 0, 1, 'charged Electromagnetic Energy Fraction'),
                Plot1D('chHEF', 'chHEF', 20, 0, 2, 'charged Hadron Energy Fraction'),
                Plot1D('muEF', 'muEF', 20, 0, 1, 'muon Energy Fraction'),
                Plot1D('neEmEF', 'neEmEF', 20, 0, 1, 'charged Electromagnetic EnergyFraction'),
                Plot1D('neHEF', 'neHEF', 20, 0, 1, 'neutral Hadron Energy Fraction'),
                Plot1D('nBHadrons', 'nBHadrons', 4, -0.5, 3.5, 'number of b-hadrons'),
                Plot1D('nCHadrons', 'nCHadrons', 4, -0.5, 3.5, 'number of c-hadrons'),
                Plot1D('particleNetMD_QCD', 'particleNetMD_QCD', 20, 0, 1, 'Mass-decorrelated ParticleNet tagger raw QCD score'),
                Plot1D('particleNetMD_Xbb', 'particleNetMD_Xbb', 20, 0, 1, 'Mass-decorrelated ParticleNet tagger raw X->bb score. For X->bb vs QCD tagging, use Xbb/(Xbb+QCD)'),
                Plot1D('particleNetMD_Xcc', 'particleNetMD_Xcc', 20, 0, 1, 'Mass-decorrelated ParticleNet tagger raw X->cc score. For X->cc vs QCD tagging, use Xcc/(Xcc+QCD)'),
                Plot1D('particleNetMD_Xqq', 'particleNetMD_Xqq', 20, 0, 1, '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)'),
                Plot1D('particleNet_H4qvsQCD', 'particleNet_H4qvsQCD', 20, 0, 1, 'ParticleNet tagger H(->VV->qqqq) vs QCD discriminator'),
                Plot1D('particleNet_HbbvsQCD', 'particleNet_HbbvsQCD', 20, 0, 1, 'ParticleNet tagger H(->bb) vs QCD discriminator'),
                Plot1D('particleNet_HccvsQCD', 'particleNet_HccvsQCD', 20, 0, 1, 'ParticleNet tagger H(->cc) vs QCD discriminator'),
                Plot1D('particleNet_QCD', 'particleNet_QCD', 20, 0, 1, 'ParticleNet tagger QCD(bb,cc,b,c,others) sum'),
                Plot1D('particleNet_TvsQCD', 'particleNet_TvsQCD', 20, 0, 1, 'ParticleNet tagger top vs QCD discriminator'),
                Plot1D('particleNet_WvsQCD', 'particleNet_WvsQCD', 20, 0, 1, 'ParticleNet tagger W vs QCD discriminator'),
                Plot1D('particleNet_ZvsQCD', 'particleNet_ZvsQCD', 20, 0, 1, 'ParticleNet tagger Z vs QCD discriminator'),
                Plot1D('particleNet_mass', 'particleNet_mass', 25, 0, 250, 'ParticleNet mass regression'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 800, 'pt'),
                Plot1D('rawFactor', 'rawFactor', 20, -0.5, 0.5, '1 - Factor to get back to raw pT'),
                NoPlot('subJetIdx1'),
                NoPlot('subJetIdx2'),
                Plot1D('tau1', 'tau1', 20, 0, 1, 'Nsubjettiness (1 axis)'),
                Plot1D('tau2', 'tau2', 20, 0, 1, 'Nsubjettiness (2 axis)'),
                Plot1D('tau3', 'tau3', 20, 0, 1, 'Nsubjettiness (3 axis)'),
                Plot1D('tau4', 'tau4', 20, 0, 1, 'Nsubjettiness (4 axis)'),
            )
        ),
        Flag = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('BadChargedCandidateFilter', 'BadChargedCandidateFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('BadChargedCandidateSummer16Filter', 'BadChargedCandidateSummer16Filter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('BadPFMuonFilter', 'BadPFMuonFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('BadPFMuonDzFilter', 'BadPFMuonDzFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('BadPFMuonSummer16Filter', 'BadPFMuonSummer16Filter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('CSCTightHalo2015Filter', 'CSCTightHalo2015Filter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('CSCTightHaloFilter', 'CSCTightHaloFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('CSCTightHaloTrkMuUnvetoFilter', 'CSCTightHaloTrkMuUnvetoFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('EcalDeadCellBoundaryEnergyFilter', 'EcalDeadCellBoundaryEnergyFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('EcalDeadCellTriggerPrimitiveFilter', 'EcalDeadCellTriggerPrimitiveFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('HBHENoiseFilter', 'HBHENoiseFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('HBHENoiseIsoFilter', 'HBHENoiseIsoFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('HcalStripHaloFilter', 'HcalStripHaloFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('METFilters', 'METFilters', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('chargedHadronTrackResolutionFilter', 'chargedHadronTrackResolutionFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('ecalBadCalibFilter', 'ecalBadCalibFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('ecalBadCalibFilterV2', 'ecalBadCalibFilterV2', 1, 0.5, 1.5, 'Bad ECAL calib flag (updated xtal list)'),
                Plot1D('ecalLaserCorrFilter', 'ecalLaserCorrFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('eeBadScFilter', 'eeBadScFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('globalSuperTightHalo2016Filter', 'globalSuperTightHalo2016Filter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('globalTightHalo2016Filter', 'globalTightHalo2016Filter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('hfNoisyHitsFilter', 'hfNoisyHitsFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('goodVertices', 'goodVertices', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('hcalLaserEventFilter', 'hcalLaserEventFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('muonBadTrackFilter', 'muonBadTrackFilter', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('trkPOGFilters', 'trkPOGFilters', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('trkPOG_logErrorTooManyClusters', 'trkPOG_logErrorTooManyClusters', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('trkPOG_manystripclus53X', 'trkPOG_manystripclus53X', 2, -0.5, 1.5, 'Trigger/flag bit'),
                Plot1D('trkPOG_toomanystripclus53X', 'trkPOG_toomanystripclus53X', 2, -0.5, 1.5, 'Trigger/flag bit'),
            )
        ),
        FsrPhoton = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 4, -0.5, 3.5, 'Final state radiation photons emitted by muons'),
                Plot1D('dROverEt2', 'dROverEt2', 20, 0, 0.05, 'deltaR to associated muon divided by photon et2'),
                Plot1D('eta', 'eta', 20, -2.5, 2.5, 'eta'),
                NoPlot('muonIdx'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 40, 'pt'),
                Plot1D('relIso03', 'relIso03', 20, 0, 2, 'relative isolation in a 0.3 cone without CHS'),
            )
        ),
        GenDressedLepton = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 25, -0.5, 24.5, 'Dressed leptons from Rivet-based ParticleLevelProducer'),
                Plot1D('eta', 'eta', 20, -7, 7, 'eta'),
                Plot1D('hasTauAnc', 'hasTauAnc', 2, -0.5, 1.5, 'true if Dressed lepton has a tau as ancestor'),
                Plot1D('mass', 'mass', 20, 0, 200, 'mass'),
                Plot1D('pdgId', 'pdgId', 40, -20, 20, 'pdgId'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
            )
        ),
        GenIsolatedPhoton = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 10, -0.5, 9.5, 'Isolated photons from Rivet-based ParticleLevelProducer'),
                Plot1D('eta', 'eta', 20, -7, 7, 'eta'),
                NoPlot('mass'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
            )
        ),
        GenJet = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 25, -0.5, 24.5, 'slimmedGenJets, i.e. ak4 Jets made with visible genparticles'),
                Plot1D('eta', 'eta', 20, -7, 7, 'eta'),
                Plot1D('hadronFlavour', 'hadronFlavour', 6, -0.5, 5.5, 'flavour from hadron ghost clustering'),
                Plot1D('mass', 'mass', 20, 0, 200, 'mass'),
                Plot1D('partonFlavour', 'partonFlavour', 40, -9.5, 30.5, 'flavour from parton matching'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
            )
        ),
        GenJetAK8 = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 25, -0.5, 24.5, 'slimmedGenJetAK8, i.e. ak8 Jets made with visible genparticles'),
                Plot1D('eta', 'eta', 20, -7, 7, 'eta'),
                Plot1D('hadronFlavour', 'hadronFlavour', 6, -0.5, 5.5, 'flavour from hadron ghost clustering'),
                Plot1D('mass', 'mass', 20, 0, 200, 'mass'),
                Plot1D('partonFlavour', 'partonFlavour', 40, -9.5, 30.5, 'flavour from parton matching'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
            )
        ),
        GenMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
            )
        ),
        GenPart = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 40, -0.5, 124.5, 'interesting gen particles '),
                Plot1D('eta', 'eta', 20, -30000, 30000, 'eta'),
                NoPlot('genPartIdxMother'),
                Plot1D('mass', 'mass', 20, 0, 300, 'Mass stored for all particles with mass > 10 GeV and photons with mass > 1 GeV. For other particles you can lookup from PDGID'),
                Plot1D('pdgId', 'pdgId', 20, -6000, 6000, 'PDG id'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('status', 'status', 20, 0, 100, 'Particle status. 1=stable'),
                Plot1D('statusFlags', 'statusFlags', 15, 0, 15, 'gen status flags stored bitwise, bits are: 0 : isPrompt, 1 : isDecayedLeptonHadron, 2 : isTauDecayProduct, 3 : isPromptTauDecayProduct, 4 : isDirectTauDecayProduct, 5 : isDirectPromptTauDecayProduct, 6 : isDirectHadronDecayProduct, 7 : isHardProcess, 8 : fromHardProcess, 9 : isHardProcessTauDecayProduct, 10 : isDirectHardProcessTauDecayProduct, 11 : fromHardProcessBeforeFSR, 12 : isFirstCopy, 13 : isLastCopy, 14 : isLastCopyBeforeFSR, ', bitset=True),
            )
        ),
        GenVtx = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('x', 'x', 50, -0.5, 0.5, 'Gen vertex x position'),
                Plot1D('y', 'y', 50, -0.5, 0.5, 'Gen vertex y position'),
                Plot1D('z', 'z', 30, -15, 15, 'Gen vertex z position'),
                Plot1D('t0', 't0', 20, -1, 1, 'Gen vertex time (t0)'),
            )
        ),
        GenVisTau = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 4, -0.5, 3.5, 'gen hadronic taus '),
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'charge'),
                Plot1D('eta', 'eta', 20, -5, 5, 'eta'),
                NoPlot('genPartIdxMother'),
                Plot1D('mass', 'mass', 20, 0, 2, 'mass'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('status', 'status', 16, -0.5, 15.5, 'Hadronic tau decay mode. 0=OneProng0PiZero, 1=OneProng1PiZero, 2=OneProng2PiZero, 10=ThreeProng0PiZero, 11=ThreeProng1PiZero, 15=Other'),
            )
        ),
        IsoTrack = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 5, -0.5, 4.5, 'isolated tracks after basic selection (pt > 10 && abs(dxy) < 0.02 && abs(dz) < 0.1 && isHighPurityTrack && miniPFIsolation.chargedHadronIso/pt < 0.2) and lepton veto'),
                Plot1D('dxy', 'dxy', 20, -0.02, 0.02, 'dxy (with sign) wrt first PV, in cm'),
                Plot1D('dz', 'dz', 20, -0.09, 0.09, 'dz (with sign) wrt first PV, in cm'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('fromPV', 'fromPV', 5, -1.5, 3.5, 'provenance from primary vertex'),
                Plot1D('isFromLostTrack', 'isFromLostTrack', 2, -0.5, 1.5, 'if isolated track comes from a lost track'),
                Plot1D('isHighPurityTrack', 'isHighPurityTrack', 2, -0.5, 1.5, 'track is high purity'),
                Plot1D('isPFcand', 'isPFcand', 2, -0.5, 1.5, 'if isolated track is a PF candidate'),
                Plot1D('miniPFRelIso_all', 'miniPFRelIso_all', 20, 0, 2, 'mini PF relative isolation, total (with scaled rho*EA PU corrections)'),
                Plot1D('miniPFRelIso_chg', 'miniPFRelIso_chg', 20, 0, 2, 'mini PF relative isolation, charged component'),
                Plot1D('pdgId', 'pdgId', 20, -300, 300, 'PDG id of PF cand'),
                Plot1D('pfRelIso03_all', 'pfRelIso03_all', 20, 0, 2, 'PF relative isolation dR=0.3, total (deltaBeta corrections)'),
                Plot1D('pfRelIso03_chg', 'pfRelIso03_chg', 20, 0, 2, 'PF relative isolation dR=0.3, charged component'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'electric charge')
            )
        ),
        Jet = cms.PSet(
            sels = cms.PSet(
                CentralPt30 = cms.string('abs(eta) < 2.4 && pt > 30'),
                ForwardPt30 = cms.string('abs(eta) > 2.4 && pt > 30')
            ),
            plots = cms.VPSet(
                Count1D('_size', 20, -0.5, 19.5, 'slimmedJets, i.e. ak4 PFJets CHS with JECs applied, after basic selection (pt > 15)'),
                Plot1D('area', 'area', 20, 0.2, 0.8, 'jet catchment area, for JECs'),
                Plot1D('bRegCorr', 'bRegCorr', 20, 0, 3, 'pt correction for b-jet energy regression'),
                Plot1D('bRegRes', 'bRegRes', 20, 0, 0.6, 'res on pt corrected with b-jet regression'),
                Plot1D('btagDeepFlavB', 'btagDeepFlavB', 20, 0, 1, 'DeepFlavour b+bb tag discriminator'),
                Plot1D('btagDeepFlavC', 'btagDeepFlavC', 20, 0, 1, 'DeepFlavour charm tag discriminator'),
                Plot1D('btagDeepFlavCvB', 'btagDeepFlavCvB', 20, -1, 1, 'DeepJet c vs b+bb+lepb discriminator'),
                Plot1D('btagDeepFlavCvL', 'btagDeepFlavCvL', 20, -1, 1, 'DeepJet c vs uds+g discriminator'),
                Plot1D('btagDeepFlavQG', 'btagDeepFlavQG', 20, -1, 1, 'DeepJet g vs uds discriminator'),
                Plot1D('btagRobustParTAK4B', 'btagRobustParTAK4B', 20, 0, 1, 'RobustParTAK4 b+bb+lepb tag discriminator'),
                Plot1D('btagRobustParTAK4CvB', 'btagRobustParTAK4CvB', 20, -1, 1, 'RobustParTAK4 c vs b+bb+lepb discriminator'),
                Plot1D('btagRobustParTAK4CvL', 'btagRobustParTAK4CvL', 20, -1, 1, 'RobustParTAK4 c vs uds+g discriminator'),
                Plot1D('btagRobustParTAK4QG', 'btagRobustParTAK4QG', 20, -1, 1, 'RobustParTAK4 g vs uds discriminator'),
                Plot1D('cRegCorr', 'cRegCorr', 20, 0.6, 2, 'pt correction for c-jet energy regression'),
                Plot1D('cRegRes', 'cRegRes', 20, 0.05, 0.4, 'res on pt corrected with c-jet regression'),
                Plot1D('btagPNetB', 'btagPNetB', 20, 0, 1, 'ParticleNet b tag discriminator'),
                Plot1D('btagPNetCvL', 'btagPNetCvL', 20, 0, 1, 'ParticleNet c vs. light (udsg) discriminator'),
                Plot1D('btagPNetCvB', 'btagPNetCvB', 20, 0, 1, 'ParticleNet c vs. b discriminator'),
                Plot1D('btagPNetQvG', 'btagPNetQvG', 20, 0, 1, 'ParticleNet quark (udsbc) vs. gluon discriminator'),
                Plot1D('btagPNetTauVJet', 'btagPNetTauVJet', 20, 0, 1, 'ParticleNet tau vs. jet discriminator'),
                Plot1D('PNetRegPtRawCorr', 'PNetRegPtRawCorr', 20, 0, 2, 'ParticleNet visible pT regression, correction relative to raw pT'),
                Plot1D('PNetRegPtRawCorrNeutrino', 'PNetRegPtRawCorrNeutrino', 20, 0, 2, 'ParticleNet neutrino pT correction, relative to regressed visible pT'),
                Plot1D('PNetRegPtRawRes', 'PNetRegPtRawRes', 20, 0, 0.5, 'ParticleNet per-jet resolution estimator: (q84 - q16)/2'),
                Plot1D('chEmEF', 'chEmEF', 20, 0, 1, 'charged Electromagnetic Energy Fraction'),
                Plot1D('chFPV0EF', 'chFPV0EF', 20, 0, 2, 'charged fromPV==0 Energy Fraction (energy excluded from CHS jets). Previously called betastar.'),
                Plot1D('chHEF', 'chHEF', 20, 0, 2, 'charged Hadron Energy Fraction'),
                NoPlot('electronIdx1'),
                NoPlot('electronIdx2'),
                Plot1D('eta', 'eta', 20, -6, 6, 'eta'),
                NoPlot('genJetIdx'),
                Plot1D('hadronFlavour', 'hadronFlavour', 6, -0.5, 5.5, 'flavour from hadron ghost clustering'),
                Plot1D('jetId', 'jetId', 3, 0, 3, 'Jet ID flags bit1 is loose (always false in 2017 since it does not exist), bit2 is tight, bit3 is tightLepVeto', bitset=True),
                Plot1D('mass', 'mass', 20, 0, 200, 'mass'),
                Plot1D('muEF', 'muEF', 20, 0, 1, 'muon Energy Fraction'),
                NoPlot('muonIdx1'),
                NoPlot('muonIdx2'),
                Plot1D('muonSubtrFactor', 'muonSubtrFactor', 20, 0, 1, '1-(muon-subtracted raw pt)/(raw pt)'),
                Plot1D('nConstituents', 'nConstituents', 20, 0, 80, 'Number of particles in the jet'),
                Plot1D('chMultiplicity', 'chMultiplicity', 20, 0, 80, '(Puppi-weighted) Number of charged particles in the jet'),
                Plot1D('neMultiplicity', 'neMultiplicity', 20, 0, 80, '(Puppi-weighted) Number of neutral particles in the jet'),
                Plot1D('nElectrons', 'nElectrons', 5, -0.5, 4.5, 'number of electrons in the jet'),
                Plot1D('nMuons', 'nMuons', 4, -0.5, 3.5, 'number of muons in the jet'),
                Plot1D('neEmEF', 'neEmEF', 20, 0, 1, 'charged Electromagnetic EnergyFraction'),
                Plot1D('neHEF', 'neHEF', 20, 0, 1, 'neutral Hadron Energy Fraction'),
                Plot1D('partonFlavour', 'partonFlavour', 40, -9.5, 30.5, 'flavour from parton matching'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('puId', 'puId', 8, -0.5, 7.5, 'Pilup ID flags'),
                Plot1D('puIdDisc', 'puIdDisc', 20, -1, 1, 'Pilup ID discriminant with 102X (2018) training'),
                Plot1D('qgl', 'qgl', 20, 0, 1, 'Quark vs Gluon likelihood discriminator'),
                Plot1D('hfHEF', 'hfHEF',  20, 0, 1, 'hadronic Energy Fraction in HF'),
                Plot1D('hfEmEF', 'hfEmEF', 20, 0, 1, 'electromagnetic Energy Fraction in HF'),
                Plot1D('hfsigmaEtaEta', 'hfsigmaEtaEta', 20, 0, 0.2, 'sigmaEtaEta for HF jets (noise discriminating variable)'),
                Plot1D('hfsigmaPhiPhi', 'hfsigmaPhiPhi', 20, 0, 0.2, 'sigmaPhiPhi for HF jets (noise discriminating variable)'),
                Plot1D('hfcentralEtaStripSize', 'hfcentralEtaStripSize', 10, 0, 10, 'eta size of the central tower strip in HF (noise discriminating variable)'),
                Plot1D('hfadjacentEtaStripsSize', 'hfadjacentEtaStripsSize', 10, 0, 10, 'eta size of the strips next to the central tower strip in HF (noise discriminating variable)'),
                Plot1D('rawFactor', 'rawFactor', 20, -0.5, 0.5, '1 - Factor to get back to raw pT'),
            )
        ),
        LHEPart = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 20, 0, 20, 'LHE particles'),
                Plot1D('eta', 'eta', 20, -30000, 30000, 'eta'),
                Plot1D('pdgId', 'pdgId', 20, -6000, 6000, 'PDG id'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
            )
        ),
        LHEPdfWeight = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 1000, 0, 2000, 'LHE PDF weights'),
                Plot1D('', '', 100, 0, 2, 'all weights'),
            )
        ),
        LHEScaleWeight = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 20, 0, 20, 'LHE scale weights'),
                Plot1D('', '', 100, 0, 2, 'all weights'),
            )
        ),

        MET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('MetUnclustEnUpDeltaX', 'MetUnclustEnUpDeltaX', 20, -20, 20, 'Delta (METx_mod-METx) Unclustered Energy Up'),
                Plot1D('MetUnclustEnUpDeltaY', 'MetUnclustEnUpDeltaY', 20, -10, 10, 'Delta (METy_mod-METy) Unclustered Energy Up'),
                Plot1D('covXX', 'covXX', 20, 0, 40000, 'xx element of met covariance matrix'),
                Plot1D('covXY', 'covXY', 20, -8000, 8000, 'xy element of met covariance matrix'),
                Plot1D('covYY', 'covYY', 20, 0, 50000, 'yy element of met covariance matrix'),
                Plot1D('fiducialGenPhi', 'fiducialGenPhi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('fiducialGenPt', 'fiducialGenPt', 20, 0, 400, 'pt'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('significance', 'significance', 20, 0, 200, 'MET significance'),
                Plot1D('sumEt', 'sumEt', 20, 600, 5000, 'scalar sum of Et'),
                Plot1D('sumPtUnclustered', 'sumPtUnclustered', 20, 0, 3000, 'sumPt used for MET significance'),
            )
        ),
        Muon = cms.PSet(
            sels = cms.PSet(
                Good = cms.string('pt > 15 && abs(dxy) < 0.2 && abs(dz) < 0.5 && mediumId && miniPFRelIso_all < 0.4')
            ),
            plots = cms.VPSet(
                Count1D('_size', 5, -0.5, 4.5, 'slimmedMuons after basic selection (pt > 3 && track.isNonnull && isLooseMuon)'),
                Plot1D('bsConstrainedPt', '', 20, 0., 200., 'pt with beamspot constraint'),
                Plot1D('bsConstrainedPtErr', '', 20, 0., 20., 'pt error w. beamspot constraint'),
                Plot1D('bsConstrainedChi2', '', 20, 0., 40., 'chi2 of beamspot constraint'),
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'electric charge'),
                Plot1D('dxy', 'dxy', 20, -0.1, 0.1, 'dxy (with sign) wrt first PV, in cm'),
                Plot1D('dxyErr', 'dxyErr', 20, 0, 0.1, 'dxy uncertainty, in cm'),
                Plot1D('dxybs', 'dxybs', 20, -0.1, 0.1, 'dxy (with sign) wrt the beam spot, in cm'),
                Plot1D('dz', 'dz', 20, -0.3, 0.3, 'dz (with sign) wrt first PV, in cm'),
                Plot1D('dzErr', 'dzErr', 20, 0, 0.2, 'dz uncertainty, in cm'),
                Plot1D('eta', 'eta', 20, -2.5, 2.5, 'eta'),
                NoPlot('fsrPhotonIdx'),
                Plot1D('genPartFlav', 'genPartFlav', 16, -0.5, 15.5, 'Flavour of genParticle for MC matching to status==1 muons: 1 = prompt muon (including gamma*->mu mu), 15 = muon from prompt tau, 5 = muon from b, 4 = muon from c, 3 = muon from light or unknown, 0 = unmatched'),
                NoPlot('genPartIdx'),
                Plot1D('highPtId', 'highPtId', 3, -0.5, 2.5, 'POG highPt muon ID (1 = tracker high pT, 2 = global high pT, which includes tracker high pT)'),
                Plot1D('highPurity', 'highPurity', 2, -0.5, 1.5, 'inner track is high purity'),
                Plot1D('inTimeMuon', 'inTimeMuon', 2, -0.5, 1.5, 'inTimeMuon ID'),
                Plot1D('ip3d', 'ip3d', 20, 0, 0.2, '3D impact parameter wrt first PV, in cm'),
                Plot1D('isGlobal', 'isGlobal', 2, -0.5, 1.5, 'muon is global muon'),
                Plot1D('isPFcand', 'isPFcand', 2, -0.5, 1.5, 'muon is PF candidate'),
                Plot1D('isTracker', 'isTracker', 2, -0.5, 1.5, 'muon is tracker muon'),
                Plot1D('isStandalone', 'isStandalone', 2, -0.5, 1.5, 'muon is a standalone muon'),
                NoPlot('jetIdx'),
                Plot1D('jetPtRelv2', 'jetPtRelv2', 20, 0, 30, 'Relative momentum of the lepton with respect to the closest jet after subtracting the lepton'),
                Plot1D('jetRelIso', 'jetRelIso', 20, -0.2, 1.8, 'Relative isolation in matched jet (1/ptRatio-1, pfRelIso04_all if no matched jet)'),
                Plot1D('looseId', 'looseId', 2, -0.5, 1.5, 'muon is loose muon'),
                NoPlot('mass'),
                Profile1D('mediumId', 'mediumId', 'pt', 16, 0, 80, 'POG Medium muon ID (using the relaxed cuts in the data Run 2016 B-F periods, and standard cuts elsewhere)'),
                Plot1D('mediumPromptId', 'mediumPromptId', 2, -0.5, 1.5, 'cut-based ID, medium prompt WP'),
                Plot1D('miniIsoId', 'miniIsoId', 5, -0.5, 4.5, 'MiniIso ID from miniAOD selector (1=MiniIsoLoose, 2=MiniIsoMedium, 3=MiniIsoTight, 4=MiniIsoVeryTight)'),
                Plot1D('miniPFRelIso_all', 'miniPFRelIso_all', 20, 0, 1, 'mini PF relative isolation, total (with scaled rho*EA PU corrections)'),
                Plot1D('miniPFRelIso_chg', 'miniPFRelIso_chg', 20, 0, 1, 'mini PF relative isolation, charged component'),
                Plot1D('multiIsoId', 'multiIsoId', 3, -0.5, 2.5, 'MultiIsoId from miniAOD selector (1=MultiIsoLoose, 2=MultiIsoMedium)'),
                Plot1D('mvaLowPt', 'mvaLowPt', 20, -1, 1, 'Low pt muon ID score'),
                Plot1D('mvaTTH', 'mvaTTH', 20, -1, 1, 'TTH MVA lepton ID score'),
                Plot1D('mvaMuID', 'mvaMuID', 20, 0, 1, 'Score of MVA-based muon ID'),
                Plot1D('mvaMuID_WP', 'mvaMuID_WP',  3, -0.5, 2.5, 'MVA-based ID selector WPs (1=MVAIDwpMedium,2=MVAIDwpTight)'),
                Plot1D('nStations', 'nStations', 5, -0.5, 4.5, 'number of matched stations with default arbitration (segment & track)'),
                Plot1D('nTrackerLayers', 'nTrackerLayers', 15, 2.5, 17.5, 'number of layers in the tracker'),
                Plot1D('jetNDauCharged', 'jetNDauCharged', 20, -0.5, 19.5, 'number of charged daughters of the closest jet'),
                Plot1D('pdgId', 'pdgId', 27, -13.5, 13.5, 'PDG code assigned by the event reconstruction (not by MC truth)'),
                Plot1D('pfIsoId', 'pfIsoId', 7, -0.5, 6.5, 'PFIso ID from miniAOD selector (1=PFIsoVeryLoose, 2=PFIsoLoose, 3=PFIsoMedium, 4=PFIsoTight, 5=PFIsoVeryTight, 6=PFIsoVeryVeryTight)'),
                Plot1D('pfRelIso03_all', 'pfRelIso03_all', 20, 0, 2, 'PF relative isolation dR=0.3, total (deltaBeta corrections)'),
                Plot1D('pfRelIso03_chg', 'pfRelIso03_chg', 20, 0, 2, 'PF relative isolation dR=0.3, charged component'),
                Plot1D('pfRelIso04_all', 'pfRelIso04_all', 20, 0, 2, 'PF relative isolation dR=0.4, total (deltaBeta corrections)'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('ptErr', 'ptErr', 20, 0, 20, 'ptError of the muon track'),
                Plot1D('segmentComp', 'segmentComp', 20, 0, 1, 'muon segment compatibility'),
                Plot1D('sip3d', 'sip3d', 20, 0, 20, '3D impact parameter significance wrt first PV'),
                Profile1D('softId', 'softId', 'pt', 20, 0, 40, 'POG Soft muon ID (using the relaxed cuts in the data Run 2016 B-F periods, and standard cuts elsewhere)'),
                Plot1D('softMva', 'softMva', 20, -1, 1, 'soft MVA ID score'),
                Plot1D('softMvaRun3', 'softMvaRun3', 20, 0, 1, 'soft MVA ID score for Run3'),
                Plot1D('softMvaId', 'softMvaId', 2, -0.5, 1.5, 'soft MVA ID'),
                Plot1D('tightCharge', 'tightCharge', 1, 1.5, 2.5, 'Tight charge criterion using pterr/pt of muonBestTrack (0:fail, 2:pass)'),
                Profile1D('tightId', 'tightId', 'pt', 16, 0, 80, 'POG Tight muon ID'),
                Plot1D('tkIsoId', 'tkIsoId', 3, -0.5, 2.5, 'TkIso ID (1=TkIsoLoose, 2=TkIsoTight)'),
                Plot1D('tkRelIso', 'tkRelIso', 100, 0, 1, 'Tracker-based relative isolation dR=0.3 for highPt, trkIso/tunePpt'),
                Plot1D('triggerIdLoose', 'triggerIdLoose', 2, -0.5, 1.5, 'TriggerIdLoose ID'),
                Plot1D('tunepRelPt', 'tunepRelPt', 200, 0, 200, 'TuneP relative pt, tunePpt/pt'),
            )
        ),
        OtherPV = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                NoPlot('_size'),
                Plot1D('z', 'z', 20, -20, 20, 'Z position of other primary vertices, excluding the main PV'),
                Plot1D('score', 'score', 20, 0, 300000, 'scores of other primary vertices, excluding the main PV'),
            )
        ),
        PPSLocalTrack = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 26, -0.5, 25.5, 'ppsLocalTrack variables'),
                Plot1D('decRPId', 'decRPId', 20, 0, 200, 'local track detector dec id'),
                NoPlot('multiRPProtonIdx'),
                Plot1D('rpType', 'rpType', 2, 3.5, 5.5, 'strip=3, pixel=4, diamond=5, timing=6'),
                Plot1D('time', 'time', 20, -2, 2, 'local track time'),
                Plot1D('timeUnc', 'timeUnc', 20, 0, 0.3, 'local track time uncertainty'),
                Plot1D('x', 'x', 20, 2, 30, 'local track x'),
                Plot1D('y', 'y', 20, -20, 20, 'local track y'),
            )
        ),
        PSWeight = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('', '', 20, 0, 2, 'All PS weights (w_var / w_nominal)'),
                Count1D('_size', 46, -0.5, 45.5, 'Number of PS weights'),
            )
        ),
        PV = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('chi2', 'chi2', 20, 0.5, 3, 'main primary vertex reduced chi2'),
                Plot1D('ndof', 'ndof', 20, 0, 500, 'main primary vertex number of degree of freedom'),
                Plot1D('npvs', 'npvs', 20, 0, 60, 'total number of reconstructed primary vertices'),
                Plot1D('npvsGood', 'npvsGood', 20, 0, 60, 'total number of Good primary vertices'),
                Plot1D('score', 'score', 20, 0, 300000, 'main primary vertex score, i.e. sum pt2 of clustered objects'),
                Plot1D('sumpt2', 'sumpt2', 100, 0, 300000, 'main primary vertex sum pt2 of the charged pf candidates'),
                Plot1D('x', 'x', 20, -0.3, 0.3, 'main primary vertex position x coordinate'),
                Plot1D('y', 'y', 20, -0.3, 0.3, 'main primary vertex position y coordinate'),
                Plot1D('z', 'z', 20, -20, 20, 'main primary vertex position z coordinate'),
            )
        ),
        Photon = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 9, -0.5, 8.5, 'slimmedPhotons after basic selection (pt > 5 )'),
                Plot1D('charge', 'charge', 1, -0.5, 0.5, 'electric charge'),
                Plot1D('cutBased', 'cutBased', 4, -0.5, 3.5,'cut-based ID bitmap, (0:fail, 1:loose, 2:medium, 3:tight)'),
                Plot1D('cutBased_Fall17V2', 'cutBased_Fall17V2', 4, -0.5, 3.5, 'cut-based ID bitmap, Fall17V2, (0:fail, 1:loose, 2:medium, 3:tight)'),
                NoPlot('electronIdx'),
                Plot1D('electronVeto', 'electronVeto', 2, -0.5, 1.5, 'pass electron veto'),
                Plot1D('energyErr', 'energyErr', 20, 0, 300, 'energy error of the cluster from regression'),
                Plot1D('energyRaw', 'energyRaw', 100, 0, 300, 'raw energy of photon supercluster'),
                Plot1D('superclusterEta', 'superclusterEta', 20, -3, 3, 'supercluster eta'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('genPartFlav', 'genPartFlav', 14, -0.5, 13.5, 'Flavour of genParticle for MC matching to status==1 photons or electrons: 1 = prompt photon, 13 = prompt electron, 0 = unknown or unmatched'),
                NoPlot('genPartIdx'),
                Plot1D('hoe', 'hoe', 20, 0, 0.6, 'H over E'),
                Plot1D('hoe_PUcorr', 'hoe_PUcorr', 20, 0, 0.6, 'H over E with PU correction'),
                Plot1D('isScEtaEB', 'isScEtaEB', 2, -0.5, 1.5, 'is supercluster eta within barrel acceptance'),
                Plot1D('isScEtaEE', 'isScEtaEE', 2, -0.5, 1.5, 'is supercluster eta within endcap acceptance'),
                NoPlot('jetIdx'),
                NoPlot('mass'),
                Plot1D('mvaID', 'mvaID', 20, -1, 1, 'MVA ID score'),
                Plot1D('mvaID_WP80', 'mvaID_WP80', 2, -0.5, 1.5, 'MVA ID WP80'),
                Plot1D('mvaID_WP90', 'mvaID_WP90', 2, -0.5, 1.5, 'MVA ID WP90'),
                Plot1D('mvaID_Fall17V2', 'mvaID_Fall17V2', 20, -1, 1, 'Fall17V2 MVA ID score'),
                Plot1D('mvaID_Fall17V2_WP80', 'mvaID_WP80_Fall17V2', 2, -0.5, 1.5, 'Fall17V2 MVA ID WP80'),
                Plot1D('mvaID_Fall17V2_WP90', 'mvaID_WP90_Fall17V2', 2, -0.5, 1.5, 'Fall17V2 MVA ID WP90'),
                Plot1D('trkSumPtHollowConeDR03', 'trkSumPtHollowConeDR03', 100, 0, 8, 'Sum of track pT in a hollow cone of outer radius, inner radius'),
                Plot1D('trkSumPtSolidConeDR04', 'trkSumPtSolidConeDR04', 100, 0, 8, 'Sum of track pT in a cone of dR=0.4'),
                Plot1D('ecalPFClusterIso', 'ecalPFClusterIso', 100, 0, 10, 'sum pt of ecal clusters, vetoing clusters part of photon'),
                Plot1D('hcalPFClusterIso', 'hcalPFClusterIso', 100, 0, 10, 'sum pt of hcal clusters, vetoing clusters part of photon'),
                Plot1D('pfPhoIso03', 'pfPhoIso03', 100, 0, 1, 'PF absolute isolation dR=0.3, photon component (uncorrected)'),
                Plot1D('pfChargedIso', 'pfChargedIso', 100, 0, 10, 'PF absolute isolation dR=0.3, charged component with dxy,dz match to PV'),
                Plot1D('pfChargedIsoPFPV', 'pfChargedIsoPFPV', 100, 0, 5, 'PF absolute isolation dR=0.3, charged component (PF PV only)'),
                Plot1D('pfChargedIsoWorstVtx', 'pfChargedIsoWorstVtx', 100, 0, 10,'PF absolute isolation dR=0.3, charged component (Vertex with largest isolation)'),
                Plot1D('pdgId', 'pdgId', 1, 21.5, 22.5, 'PDG code assigned by the event reconstruction (not by MC truth)'),
                Plot1D('pfRelIso03_all_Fall17V2', 'pfRelIso03_all_Fall17V2', 20, 0, 2, 'PF relative isolation dR=0.3, total (with rho*EA PU Fall17V2 corrections)'),
                Plot1D('pfRelIso03_chg_Fall17V2', 'pfRelIso03_chg_Fall17V2', 20, 0, 2, 'PF relative isolation dR=0.3, charged component (with rho*EA PU Fall17V2 corrections)'),
                Plot1D('pfRelIso03_all_quadratic', 'pfRelIso03_all_quadratic', 20, 0, 2, 'PF relative isolation dR=0.3, total (with quadraticEA*rho*rho + linearEA*rho corrections)'),
                Plot1D('pfRelIso03_chg_quadratic', 'pfRelIso03_chg_quadratic', 20, 0, 2, 'PF relative isolation dR=0.3, charged hadron component (with quadraticEA*rho*rho + linearEA*rho corrections)'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pixelSeed', 'pixelSeed', 2, -0.5, 1.5, 'has pixel seed'),
                Plot1D('hasConversionTracks', 'hasConversionTracks', 2, -0.5, 1.5, 'Variable specifying if photon has associated conversion tracks (one-legged or two-legged)'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt (corrected)'),
                Plot1D('r9', 'r9', 20, 0, 1.1, 'R9 of the supercluster, calculated with full 5x5 region'),
                Plot1D('seedGain', 'seedGain', 12, 0.5, 12.5, 'Gain of the seed crystal'),
                Plot1D('seediEtaOriX', 'seediEtaOriX', 200, -90, 110, 'iEta/iX of seed crystal'),
                Plot1D('seediPhiOriY', 'seediPhiOriY', 380, -10, 370, 'iPhi/iY of seed crystal'),
                Plot1D('sieie', 'sieie', 100, 0, 0.05, 'sigma_IetaIeta of the supercluster, calculated with full 5x5 region'),
                Plot1D('sipip', 'sipip', 100, 0, 0.05, 'sigmaIphiIphi of the supercluster'),
                Plot1D('sieip', 'sieip', 100, -0.0002, 0.0002, 'sigma_IetaIphi of the supercluster, calculated with full 5x5 region'),
                Plot1D('s4', 's4', 100, 0.4, 1, 'e2x2/e5x5 of the supercluster, calculated with full 5x5 region'),
                Plot1D('etaWidth', 'etaWidth', 100, 0, 0.03, 'Width of the photon supercluster in eta'),
                Plot1D('phiWidth', 'phiWidth', 100, 0, 0.1, 'Width of the photon supercluster in phi'),
                Plot1D('x_calo', 'x_calo', 100, -150, 150, 'photon supercluster position on calorimeter, x coordinate (cm)'),
                Plot1D('y_calo', 'y_calo', 100, -150, 150, 'photon supercluster position on calorimeter, y coordinate (cm)'),
                Plot1D('z_calo', 'z_calo', 100, -330, 330, 'photon supercluster position on calorimeter, y coordinate (cm)'),
                Plot1D('esEffSigmaRR', 'esEffSigmaRR', 100, 0, 10, 'preshower sigmaRR'),
                Plot1D('esEnergyOverRawE', 'esEnergyOverRawE', 100, 0, 0.2, 'ratio of preshower energy to raw supercluster energy'),
                NoPlot('vidNestedWPBitmap'),
                NoPlot('vidNestedWPBitmap_Fall17V2'),
            )
        ),
        Proton_multiRP = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 3, -0.5, 2.5, 'bon'),
                Plot1D('arm', 'arm', 2, -0.5, 1.5, '0 = sector45, 1 = sector56'),
                Plot1D('t', 't', 20, -500, -0.003, 'Mandelstam variable t'),
                Plot1D('thetaX', 'thetaX', 20, -0.0004, 0.0004, 'scattering angle in the y direction'),
                Plot1D('thetaY', 'thetaY', 20, -0.001, 0.001, 'scattering angle in the x direction'),
                Plot1D('time', 'time', 20, -1000, -1000, 'time'),
                Plot1D('timeUnc', 'timeUnc', 20, 0, 0, 'time uncertainty'),
                Plot1D('xi', 'xi', 20, 0, 0.3, 'fractional momentum loss'),
            )
        ),
        Proton_singleRP = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 3, -0.5, 2.5, 'bon'),
                Plot1D('xi', 'xi', 20, 0, 0.3, 'fractional momentum loss'),
                Plot1D('thetaY', 'thetaY', 20, -0.001, 0.001, 'scattering angle in the x direction'),
                Plot1D('decRPId', 'decRPId', 20, 0, 200, 'Detector ID'),
            )
        ),
        Pileup = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('gpudensity', 'gpudensity', 20, 0, 0.9, 'Generator-level PU vertices / mm'),
                Plot1D('nPU', 'nPU', 20, 0, 60, 'the number of pileup interactions that have been added to the event in the current bunch crossing'),
                Plot1D('nTrueInt', 'nTrueInt', 20, 0, 60, 'the true mean number of the poisson distribution for this event from which the number of interactions each bunch crossing has been sampled'),
                Plot1D('pudensity', 'pudensity', 5, -0.5, 4.5, 'PU vertices / mm'),
                Plot1D('sumEOOT', 'sumEOOT', 20, 0, 800, 'number of early out of time pileup'),
                Plot1D('sumLOOT', 'sumLOOT', 20, 0, 300, 'number of late out of time pileup'),
                Plot1D('pthatmax','pthatmax',20, 0, 400, 'Maximum pt-hat'),
            )
        ),
        PuppiMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('phiJERUp', 'phiJERUp', 20, -3.14159, 3.14159, 'JER up phi'),
                Plot1D('phiJERDown', 'phiJERDown', 20, -3.14159, 3.14159, 'JER down phi'),
                Plot1D('phiJESUp', 'phiJESUp', 20, -3.14159, 3.14159, 'JES up phi'),
                Plot1D('phiJESDown', 'phiJESDown', 20, -3.14159, 3.14159, 'JES down phi'),
                Plot1D('phiUnclusteredUp', 'phiUnclusteredUp', 20, -3.14159, 3.14159, 'Unclustered up phi'),
                Plot1D('phiUnclusteredDown', 'phiUnclusteredDown', 20, -3.14159, 3.14159, 'Unclustered down phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('ptJERUp', 'ptJERUp', 20, 0, 400, 'JER up pt'),
                Plot1D('ptJERDown', 'ptJERDown', 20, 0, 400, 'JER down pt'),
                Plot1D('ptJESUp', 'ptJESUp', 20, 0, 400, 'JES up pt'),
                Plot1D('ptJESDown', 'ptJESDown', 20, 0, 400, 'JES down pt'),
                Plot1D('ptUnclusteredUp', 'ptUnclusteredUp', 20, 0, 400, 'Unclustered up pt'),
                Plot1D('ptUnclusteredDown', 'ptUnclusteredDown', 20, 0, 400, 'Unclustered down pt'),
                Plot1D('sumEt', 'sumEt', 20, 200, 3000, 'scalar sum of Et'),
            )
        ),
        RawMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('sumEt', 'sumEt', 20, 400, 4000, 'scalar sum of Et'),
            )
        ),
        RawPuppiMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('sumEt', 'sumEt', 20, 400, 4000, 'scalar sum of Et'),
            )
        ),
        SV = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 14, -0.5, 13.5),
                Plot1D('chi2', 'chi2', 20, -2000, 2000, 'reduced chi2, i.e. chi/ndof'),
                Plot1D('dlen', 'dlen', 20, 0, 4, 'decay length in cm'),
                Plot1D('dlenSig', 'dlenSig', 20, 0, 50, 'decay length significance'),
                Plot1D('dxy', 'dxy', 20, 0, 4, '2D decay length in cm'),
                Plot1D('dxySig', 'dxySig', 20, 0, 50, '2D decay length significance'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('mass', 'mass', 20, 0, 8, 'mass'),
                Plot1D('ndof', 'ndof', 20, -1, 19, 'number of degrees of freedom'),
                Plot1D('pAngle', 'pAngle', 20, -3.1416, 3.1416, 'pointing angle, i.e. acos(p_SV * (SV - PV)) '),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('x', 'x', 20, -0.5, 0.5, 'secondary vertex X position, in cm'),
                Plot1D('y', 'y', 20, -0.5, 0.5, 'secondary vertex Y position, in cm'),
                Plot1D('z', 'z', 20, -10, 10, 'secondary vertex Z position, in cm'),
                Plot1D('ntracks', 'ntracks', 11, -0.5, 10.5, 'number of tracks'),
                Plot1D('charge', 'charge', 11 , -0.5, 10.5, 'sum of the charge of the SV tracks'),
            )
        ),
        SoftActivityJet = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 7, -0.5, 6.5, 'jets clustered from charged candidates compatible with primary vertex (charge()!=0 && pvAssociationQuality()>=5 && vertexRef().key()==0)'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
            )
        ),
        SubJet = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 9, -0.5, 8.5, 'slimmedJetsAK8PFPuppiSoftDropPacked::SubJets, i.e. soft-drop subjets for ak8 fat jets for boosted'),
                Plot1D('btagCMVA', 'btagCMVA', 20, -1, 1, 'CMVA V2 btag discriminator'),
                Plot1D('btagDeepB', 'btagDeepB', 20, -1, 1, 'Deep B+BB btag discriminator'),
                Plot1D('eta', 'eta', 20, -4, 4, 'eta'),
                Plot1D('hadronFlavour', 'hadronFlavour', 6, -0.5, 5.5, 'flavour from hadron ghost clustering'),
                Plot1D('mass', 'mass', 20, -200, 200, 'mass'),
                Plot1D('n2b1', 'n2b1', 20, 0, 1, 'N2 (beta=1)'),
                Plot1D('n3b1', 'n3b1', 20, 0, 5, 'N3 (beta=1)'),
                Plot1D('nBHadrons', 'nBHadrons', 4, -0.5, 3.5, 'number of b-hadrons'),
                Plot1D('nCHadrons', 'nCHadrons', 4, -0.5, 3.5, 'number of c-hadrons'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('rawFactor', 'rawFactor', 20, -0.5, 0.5, '1 - Factor to get back to raw pT'),
                Plot1D('area', 'area', 25, 0, 2.5, 'jet catchment area, for JECs'),
                Plot1D('tau1', 'tau1', 20, 0, 1, 'Nsubjettiness (1 axis)'),
                Plot1D('tau2', 'tau2', 20, 0, 1, 'Nsubjettiness (2 axis)'),
                Plot1D('tau3', 'tau3', 20, 0, 1, 'Nsubjettiness (3 axis)'),
                Plot1D('tau4', 'tau4', 20, 0, 1, 'Nsubjettiness (4 axis)'),
            )
        ),
        Tau = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 7, -0.5, 6.5, "slimmedTaus after basic selection (pt > 18 && tauID('decayModeFindingNewDMs') && (tauID('byLooseCombinedIsolationDeltaBetaCorr3Hits') || tauID('byVLooseIsolationMVArun2v1DBoldDMwLT') || tauID('byVLooseIsolationMVArun2v1DBnewDMwLT') || tauID('byVLooseIsolationMVArun2v1DBdR03oldDMwLT')))"),
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'electric charge'),
                Plot1D('chargedIso', 'chargedIso', 20, 0, 200, 'charged isolation'),
                Plot1D('decayMode', 'decayMode', 12, -0.5, 11.5, 'decayMode()'),
                Plot1D('decayModePNet', 'decayModePNet', 13, -1.5, 11.5, 'decay mode of the highest PNet tau score'),
                Plot1D('dxy', 'dxy', 20, -1000, 1000, 'd_{xy} of lead track with respect to PV, in cm (with sign)'),
                Plot1D('dz', 'dz', 20, -20, 20, 'd_{z} of lead track with respect to PV, in cm (with sign)'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('genPartFlav', 'genPartFlav', 6, -0.5, 5.5, 'Flavour of genParticle for MC matching to status==2 taus: 1 = prompt electron, 2 = prompt muon, 3 = tau->e decay, 4 = tau->mu decay, 5 = hadronic tau decay, 0 = unknown or unmatched'),
                NoPlot('genPartIdx'),
                Plot1D('idAntiEleDeadECal', 'idAntiEleDeadECal', 2, -0.5, 1.5, "tauID('againstElectronDeadECAL')"),
                Plot1D('idAntiMu', 'idAntiMu', 11, -0.5, 10.5, 'Anti-muon discriminator V3: : int 1 = Loose, 2 = Tight'),
                Plot1D('idDecayModeOldDMs', 'idDecayModeOldDMs', 2, -0.5, 1.5, "tauID('decayModeFinding')"),
                Plot1D('idDecayModeNewDMs', 'idDecayModeNewDMs', 2, -0.5, 1.5, "tauID('decayModeFindingNewDMs')"),
                Plot1D('idDeepTau2017v2p1VSe', 'idDeepTau2017v2p1VSe', 11, -0.5, 10.5, 'byDeepTau2017v2p1VSe ID working points (deepTau2017v2p1): int 1 = VVVLoose, 2 = VVLoose, 3 = VLoose, 4 = Loose, 5 = Medium, 6 = Tight, 7 = VTight, 8 = VVTight'),
                Plot1D('idDeepTau2017v2p1VSjet', 'idDeepTau2017v2p1VSjet', 11, -0.5, 10.5, 'byDeepTau2017v2p1VSjet ID working points (deepTau2017v2p1): int 1 = VVVLoose, 2 = VVLoose, 3 = VLoose, 4 = Loose, 5 = Medium, 6 = Tight, 7 = VTight, 8 = VVTight'),
                Plot1D('idDeepTau2017v2p1VSmu', 'idDeepTau2017v2p1VSmu', 11, -0.5, 10.5, 'byDeepTau2017v2p1VSmu ID working points (deepTau2017v2p1): int 1 = VLoose, 2 = Loose, 3 = Medium, 4 = Tight'),
                Plot1D('idDeepTau2018v2p5VSe', 'idDeepTau2018v2p5VSe', 11, -0.5, 10.5, 'byDeepTau2018v2p5VSe ID working points (deepTau2018v2p5): int 1 = VVVLoose, 2 = VVLoose, 3 = VLoose, 4 = Loose, 5 = Medium, 6 = Tight, 7 = VTight, 8 = VVTight'),
                Plot1D('idDeepTau2018v2p5VSjet', 'idDeepTau2018v2p5VSjet', 11, -0.5, 10.5, 'byDeepTau2018v2p5VSjet ID working points (deepTau2018v2p5): int 1 = VVVLoose, 2 = VVLoose, 3 = VLoose, 4 = Loose, 5 = Medium, 6 = Tight, 7 = VTight, 8 = VVTight'),
                Plot1D('idDeepTau2018v2p5VSmu', 'idDeepTau2018v2p5VSmu', 11, -0.5, 10.5, 'byDeepTau2018v2p5VSmu ID working points (deepTau2018v2p5): int 1 = VLoose, 2 = Loose, 3 = Medium, 4 = Tight'),
                NoPlot('jetIdx'),
                Plot1D('leadTkDeltaEta', 'leadTkDeltaEta', 20, -0.1, 0.1, 'eta of the leading track, minus tau eta'),
                Plot1D('leadTkDeltaPhi', 'leadTkDeltaPhi', 20, -0.1, 0.1, 'phi of the leading track, minus tau phi'),
                Plot1D('leadTkPtOverTauPt', 'leadTkPtOverTauPt', 20, 0, 2, 'pt of the leading track divided by tau pt'),
                Plot1D('mass', 'mass', 20, 0, 5, 'mass'),
                Plot1D('neutralIso', 'neutralIso', 20, 0, 200, 'neutral (photon) isolation'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('photonsOutsideSignalCone', 'photonsOutsideSignalCone', 20, 0, 30, 'sum of photons outside signal cone'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('puCorr', 'puCorr', 20, 0, 90, 'pileup correction'),
                Plot1D('rawDeepTau2017v2p1VSe', 'rawDeepTau2017v2p1VSe', 20, 0, 1, 'byDeepTau2017v2p1VSe raw output discriminator (deepTau2017v2p1)'),
                Plot1D('rawDeepTau2017v2p1VSjet', 'rawDeepTau2017v2p1VSjet', 20, 0, 1, 'byDeepTau2017v2p1VSjet raw output discriminator (deepTau2017v2p1)'),
                Plot1D('rawDeepTau2017v2p1VSmu', 'rawDeepTau2017v2p1VSmu', 20, 0, 1, 'byDeepTau2017v2p1VSmu raw output discriminator (deepTau2017v2p1)'),
                Plot1D('rawDeepTau2018v2p5VSe', 'rawDeepTau2018v2p5VSe', 20, 0, 1, 'byDeepTau2018v2p5VSe raw output discriminator (deepTau2018v2p5)'),
                Plot1D('rawDeepTau2018v2p5VSjet', 'rawDeepTau2018v2p5VSjet', 20, 0, 1, 'byDeepTau2018v2p5VSjet raw output discriminator (deepTau2018v2p5)'),
                Plot1D('rawDeepTau2018v2p5VSmu', 'rawDeepTau2018v2p5VSmu', 20, 0, 1, 'byDeepTau2018v2p5VSmu raw output discriminator (deepTau2018v2p5)'),
                Plot1D('rawPNetVSe', 'rawPNetVSe', 20, 0, 1, 'byPNetVSe raw output discriminator (PNet 2023)'),
                Plot1D('rawPNetVSjet', 'rawPNetVSjet', 20, 0, 1, 'byPNetVSjet raw output discriminator (PNet 2023)'),
                Plot1D('rawPNetVSmu', 'rawPNetVSmu', 20, 0, 1, 'byPNetVSmu raw output discriminator (PNet 2023)'),
                Plot1D('rawIso', 'rawIso', 20, 0, 200, 'combined isolation (deltaBeta corrections)'),
                Plot1D('rawIsodR03', 'rawIsodR03', 20, 0, 200, 'combined isolation (deltaBeta corrections, dR=0.3)'),
                Plot1D('ptCorrPNet', 'ptCorrPNet', 20, 0, 2, 'pt correction (PNet 2023)'),
                Plot1D('qConfPNet', 'qConfPNet', 20, -0.5, 0.5, 'signed charge confidence (PNet 2023)'),
                Plot1D('probDM0PNet', 'probDM0PNet', 20, 0, 1, 'normalised probablity of decayMode 0, 1h+0pi0 (PNet 2023)'),
                Plot1D('probDM1PNet', 'probDM1PNet', 20, 0, 1, 'normalised probablity of decayMode 1, 1h+1pi0 (PNet 2023)'),
                Plot1D('probDM2PNet', 'probDM2PNet', 20, 0, 1, 'normalised probablity of decayMode 2, 1h+2pi0 (PNet 2023)'),
                Plot1D('probDM10PNet', 'probDM10PNet', 20, 0, 1, 'normalised probablity of decayMode 10, 3h+0pi0 (PNet 2023)'),
                Plot1D('probDM11PNet', 'probDM11PNet', 20, 0, 1, 'normalised probablity of decayMode 11, 3h+1pi0 (PNet 2023)'),
            )
        ),
        TauProd = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 40, -0.5, 5.5, 'tau decay products'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('eta', 'eta', 20, -5, 5, 'eta'),
                Plot1D('pdgId', 'pdgId', 200, -10250, 10250, 'PDG code assigned by the event reconstruction (not by MC truth)'),
                NoPlot('status'),
            )
        ),        
        TkMET = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 20, 0, 400, 'pt'),
                Plot1D('sumEt', 'sumEt', 20, 0, 2000, 'scalar sum of Et'),
            )
        ),
        TrigObj = cms.PSet(
            sels = cms.PSet(
                Electron = cms.string('id == 11'),
                HT = cms.string('id == 3'),
                Jet = cms.string('id == 1'),
                MET = cms.string('id == 2'),
                MHT = cms.string('id == 4'),
                Muon = cms.string('id == 13'),
                Photon = cms.string('id == 22'),
                Tau = cms.string('id == 15')
            ),
            plots = cms.VPSet(
                Count1D('_size', 28, -0.5, 27.5),
                Plot1D('eta', 'eta', 20, -5, 5, 'eta'),
                Plot1D('filterBits', 'filterBits', 31, 0, 31, 'extra bits of associated information, object- and era-dependent: see branch documentation', bitset=True),
                Plot1D('id', 'id', 20, 0, 30, 'ID of the object: 11 = Electron (PixelMatched e/gamma), 22 = Photon (PixelMatch-vetoed e/gamma), 13 = Muon, 14 = Tau, 1 = Jet, 2 = MET, 3 = HT, 4 = MHT'),
                Plot1D('l1charge', 'l1charge', 3, -1.5, 1.5, 'charge of associated L1 seed'),
                Plot1D('l1iso', 'l1iso', 4, -0.5, 3.5, 'iso of associated L1 seed'),
                Plot1D('l1pt', 'l1pt', 20, 0, 200, 'pt of associated L1 seed'),
                Plot1D('l1pt_2', 'l1pt_2', 20, 0, 200, 'pt of associated secondary L1 seed'),
                Plot1D('l2pt', 'l2pt', 20, 0, 200, "pt of associated 'L2' seed (i.e. HLT before tracking/PF)"),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('pt', 'pt', 40, 0, 400, 'pt'),
            )
        ),
        boostedTau = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Count1D('_size', 7, -0.5, 6.5, "slimmedBoostedTaus after basic selection (pt > 40 && tauID('decayModeFindingNewDMs') && (tauID('byVVLooseIsolationMVArun2017v2DBoldDMwLT2017') || tauID('byVVLooseIsolationMVArun2017v2DBoldDMdR0p3wLT2017') || tauID('byVVLooseIsolationMVArun2017v2DBnewDMwLT2017')))"),
                Plot1D('charge', 'charge', 3, -1.5, 1.5, 'electric charge'),
                Plot1D('chargedIso', 'chargedIso', 20, 0, 200, 'charged isolation'),
                Plot1D('decayMode', 'decayMode', 12, -0.5, 11.5, 'decayMode()'),
                Plot1D('eta', 'eta', 20, -3, 3, 'eta'),
                Plot1D('genPartFlav', 'genPartFlav', 6, -0.5, 5.5, 'Flavour of genParticle for MC matching to status==2 taus: 1 = prompt electron, 2 = prompt muon, 3 = tau->e decay, 4 = tau->mu decay, 5 = hadronic tau decay, 0 = unknown or unmatched'),
                NoPlot('genPartIdx'),
                Plot1D('idAntiEle2018', 'idAntiEle2018', 11, -0.5, 10.5, 'Anti-electron MVA discriminator V6 (2018): int 1 = VLoose, 2 = Loose, 3 = Medium, 4 = Tight, 5 = VTight'),
                Plot1D('idAntiMu', 'idAntiMu', 11, -0.5, 10.5, 'Anti-muon discriminator V3: : int 1 = Loose, 2 = Tight'),
                Plot1D('idMVAnewDM2017v2', 'idMVAnewDM2017v2', 11, -0.5, 10.5, 'IsolationMVArun2017v2DBnewDMwLT ID working point (2017v2): int 1 = VVLoose, 2 = VLoose, 3 = Loose, 4 = Medium, 5 = Tight, 6 = VTight, 7 = VVTight'),
                Plot1D('idMVAoldDM2017v2', 'idMVAoldDM2017v2', 11, -0.5, 10.5, 'IsolationMVArun2017v2DBoldDMwLT ID working point (2017v2): int 1 = VVLoose, 2 = VLoose, 3 = Loose, 4 = Medium, 5 = Tight, 6 = VTight, 7 = VVTight'),
                NoPlot('jetIdx'),
                Plot1D('leadTkDeltaEta', 'leadTkDeltaEta', 20, -0.1, 0.1, 'eta of the leading track, minus tau eta'),
                Plot1D('leadTkDeltaPhi', 'leadTkDeltaPhi', 20, -0.1, 0.1, 'phi of the leading track, minus tau phi'),
                Plot1D('leadTkPtOverTauPt', 'leadTkPtOverTauPt', 20, 0, 2, 'pt of the leading track divided by tau pt'),
                Plot1D('mass', 'mass', 20, 0, 5, 'mass'),
                Plot1D('neutralIso', 'neutralIso', 20, 0, 200, 'neutral (photon) isolation'),
                Plot1D('phi', 'phi', 20, -3.14159, 3.14159, 'phi'),
                Plot1D('photonsOutsideSignalCone', 'photonsOutsideSignalCone', 20, 0, 30, 'sum of photons outside signal cone'),
                Plot1D('pt', 'pt', 20, 0, 200, 'pt'),
                Plot1D('puCorr', 'puCorr', 20, 0, 90, 'pileup correction'),
                Plot1D('rawAntiEle2018', 'rawAntiEle2018', 20, -100, 100, 'Anti-electron MVA discriminator V6 raw output discriminator (2018)'),
                Plot1D('rawAntiEleCat2018', 'rawAntiEleCat2018', 20, -100, 100, 'Anti-electron MVA discriminator V6 category (2018)'),
                Plot1D('rawIso', 'rawIso', 20, 0, 200, 'combined isolation (deltaBeta corrections)'),
                Plot1D('rawIsodR03', 'rawIsodR03', 20, 0, 200, 'combined isolation (deltaBeta corrections, dR=0.3)'),
                Plot1D('rawMVAnewDM2017v2', 'rawMVAnewDM2017v2', 20, -1, 1, 'byIsolationMVArun2017v2DBnewDMwLT raw output discriminator (2017v2)'),
                Plot1D('rawMVAoldDM2017v2', 'rawMVAoldDM2017v2', 20, -1, 1, 'byIsolationMVArun2017v2DBoldDMwLT raw output discriminator (2017v2)'),
            )
        ),
        L1PreFiringWeight = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('Nom', 'Nom', 21, 0.8, 1.01, 'L1 prefiring weight nominal'),
                Plot1D('Up', 'Up', 21, 0.8, 1.01, 'L1 prefiring weight uncertainy up'),
                Plot1D('Dn', 'Dn', 21, 0.8, 1.01, 'L1 prefiring weight uncertainty down'),
                Plot1D('ECAL_Nom', 'ECAL_Nom', 21, 0.8, 1.01, 'L1 prefiring weight for ECAL objects nominal'),
                Plot1D('Muon_Nom', 'Muon_Nom', 21, 0.8, 1.01, 'L1 prefiring weight for muons nominal'),
            )

        ),
        BeamSpot = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('z', 'z', 20, 0.5, 1.5, 'BeamSpot center, z coordinate (cm)'),
                Plot1D('zError', 'zError', 20, 0., 0.01, 'Error on BeamSpot center, z coordinate (cm)'),
                Plot1D('sigmaZ', 'sigmaZ', 20, 0., 10, 'Width of BeamSpot in z (cm)'),
                Plot1D('sigmaZError', 'sigmaZError', 20, 0., 0.01, 'Error on width of BeamSpot in z (cm)'),
            )
        ),
        Rho = cms.PSet(
            sels = cms.PSet(),
            plots = cms.VPSet(
                Plot1D('fixedGridRhoAll', 'fixedGridRhoAll', 100, 0, 80, 'rho from all PF Candidates, no foreground removal (for isolation of prompt photons)'),
            )
        ),
    )
)