NanoAOD/python/nanoDQM_cff.py

0001 import FWCore.ParameterSet.Config as cms
0002 import copy
0003
0004 from PhysicsTools.NanoAOD.nanoDQM_cfi import nanoDQM
0005 from PhysicsTools.NanoAOD.nanoDQM_tools_cff import *
0006 from PhysicsTools.NanoAOD.nano_eras_cff import *
0007
0008 ## Modify plots accordingly to era
0009 _vplots80X = nanoDQM.vplots.clone()
0010 # Tau plots
0011 _tauPlots80X = cms.VPSet()
0012 for plot in _vplots80X.Tau.plots:
0013     if (plot.name.value().find("MVA")>-1 and plot.name.value().find("2017")>-1) or (plot.name.value().find("AntiEle")>-1 and plot.name.value().find("2018")>-1) or (plot.name.value().find("AntiEleDeadECal")>-1) or (plot.name.value().find("DeepTau")>-1):
0014         continue
0015     _tauPlots80X.append(plot)
0016 _tauPlots80X.extend([Plot1D('idMVAnewDM', 'idMVAnewDM', 64, -0.5, 63.5, 'IsolationMVArun2v1DBnewDMwLT ID working point: bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight, 32 = VVTight'),
0017                      Plot1D('idMVAoldDM', 'idMVAoldDM', 64, -0.5, 63.5, 'IsolationMVArun2v1DBnewDMwLT ID working point: bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight, 32 = VVTight'),
0018                      Plot1D('idMVAoldDMdR03', 'idMVAoldDMdR03', 64, -0.5, 63.5, 'IsolationMVArun2v1DBdR03oldDMwLT ID working point: bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight, 32 = VVTight'),
0019                      Plot1D('rawMVAnewDM', 'rawMVAnewDM', 20, -1, 1, 'byIsolationMVArun2v1DBnewDMwLT raw output discriminator'),
0020                      Plot1D('rawMVAoldDM', 'rawMVAoldDM', 20, -1, 1, 'byIsolationMVArun2v1DBnewDMwLT raw output discriminator'),
0021                      Plot1D('rawMVAoldDMdR03', 'rawMVAoldDMdR03', 20, -1, 1, 'byIsolationMVArun2v1DBdR03oldDMwLT raw output discriminator'),
0022                      Plot1D('idAntiEle', 'idAntiEle', 32, -0.5, 31.5, 'Anti-electron MVA discriminator V6: bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight'),
0023                      Plot1D('rawAnti', 'rawAntiEle', 20, -100, 100, 'Anti-electron MVA discriminator V6 raw output discriminator'),
0024                      Plot1D('rawAntiEleCat', 'rawAntiEleCat', 17, -1.5, 15.5, 'Anti-electron MVA discriminator V6 category')
0025 ])
0026 _vplots80X.Tau.plots = _tauPlots80X
0027 run2_miniAOD_80XLegacy.toModify(nanoDQM,
0028                                 vplots = _vplots80X
0029 )
0030 _tauPlotsPreV9 = cms.VPSet()
0031 for plot in nanoDQM.vplots.Tau.plots:
0032     if plot.name.value()!="idDecayModeOldDMs":
0033         _tauPlotsPreV9.append(plot)
0034 _tauPlotsPreV9.extend([
0035                 Plot1D('idDecayMode', 'idDecayMode', 2, -0.5, 1.5, "tauID('decayModeFinding')"),
0036                 Plot1D('idDecayModeNewDMs', 'idDecayModeNewDMs', 2, -0.5, 1.5, "tauID('decayModeFindingNewDMs')"),
0037                 Plot1D('idAntiEle', 'idAntiEle', 32, -0.5, 31.5, 'Anti-electron MVA discriminator V6: bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight'),
0038                 Plot1D('idAntiEle2018', 'idAntiEle2018', 32, -0.5, 31.5, 'Anti-electron MVA discriminator V6 (2018): bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight'),
0039                 Plot1D('idMVAnewDM2017v2', 'idMVAnewDM2017v2', 128, -0.5, 127.5, 'IsolationMVArun2v1DBnewDMwLT ID working point (2017v2): bitmask 1 = VVLoose, 2 = VLoose, 4 = Loose, 8 = Medium, 16 = Tight, 32 = VTight, 64 = VVTight'),
0040                 Plot1D('idMVAoldDM', 'idMVAoldDM', 64, -0.5, 63.5, 'IsolationMVArun2v1DBoldDMwLT ID working point: bitmask 1 = VLoose, 2 = Loose, 4 = Medium, 8 = Tight, 16 = VTight, 32 = VVTight'),
0041                 Plot1D('idMVAoldDM2017v1', 'idMVAoldDM2017v1', 128, -0.5, 127.5, 'IsolationMVArun2v1DBoldDMwLT ID working point (2017v1): bitmask 1 = VVLoose, 2 = VLoose, 4 = Loose, 8 = Medium, 16 = Tight, 32 = VTight, 64 = VVTight'),
0042                 Plot1D('idMVAoldDM2017v2', 'idMVAoldDM2017v2', 128, -0.5, 127.5, 'IsolationMVArun2v1DBoldDMwLT ID working point (2017v2): bitmask 1 = VVLoose, 2 = VLoose, 4 = Loose, 8 = Medium, 16 = Tight, 32 = VTight, 64 = VVTight'),
0043                 Plot1D('idMVAoldDMdR032017v2', 'idMVAoldDMdR032017v2', 128, -0.5, 127.5, 'IsolationMVArun2v1DBdR03oldDMwLT ID working point (217v2): bitmask 1 = VVLoose, 2 = VLoose, 4 = Loose, 8 = Medium, 16 = Tight, 32 = VTight, 64 = VVTight'),
0044                 Plot1D('rawAntiEle', 'rawAntiEle', 20, -100, 100, 'Anti-electron MVA discriminator V6 raw output discriminator'),
0045                 Plot1D('rawAntiEle2018', 'rawAntiEle2018', 20, -100, 100, 'Anti-electron MVA discriminator V6 raw output discriminator (2018)'),
0046                 Plot1D('rawAntiEleCat', 'rawAntiEleCat', 17, -1.5, 15.5, 'Anti-electron MVA discriminator V6 category'),
0047                 Plot1D('rawAntiEleCat2018', 'rawAntiEleCat2018', 17, -1.5, 15.5, 'Anti-electron MVA discriminator V6 category (2018)'),
0048                 Plot1D('rawMVAnewDM2017v2', 'rawMVAnewDM2017v2', 20, -1, 1, 'byIsolationMVArun2v1DBnewDMwLT raw output discriminator (2017v2)'),
0049                 Plot1D('rawMVAoldDM', 'rawMVAoldDM', 20, -1, 1, 'byIsolationMVArun2v1DBoldDMwLT raw output discriminator'),
0050                 Plot1D('rawMVAoldDM2017v1', 'rawMVAoldDM2017v1', 20, -1, 1, 'byIsolationMVArun2v1DBoldDMwLT raw output discriminator (2017v1)'),
0051                 Plot1D('rawMVAoldDM2017v2', 'rawMVAoldDM2017v2', 20, -1, 1, 'byIsolationMVArun2v1DBoldDMwLT raw output discriminator (2017v2)'),
0052                 Plot1D('rawMVAoldDMdR032017v2', 'rawMVAoldDMdR032017v2', 20, -1, 1, 'byIsolationMVArun2v1DBdR03oldDMwLT raw output discriminator (2017v2)')
0053 ])
0054
0055 (run2_nanoAOD_92X | run2_nanoAOD_94XMiniAODv1 | run2_nanoAOD_94XMiniAODv2 | run2_nanoAOD_94X2016 | run2_nanoAOD_102Xv1 | run2_nanoAOD_106Xv1).toModify(nanoDQM.vplots.Tau, plots = _tauPlotsPreV9)
0056
0057 _boostedTauPlotsV10 = cms.VPSet()
0058 for plot in nanoDQM.vplots.boostedTau.plots:
0059     _boostedTauPlotsV10.append(plot)
0060 _boostedTauPlotsV10.extend([
0061     Plot1D('idMVAoldDMdR032017v2', 'idMVAoldDMdR032017v2', 128, -0.5, 127.5, 'IsolationMVArun2017v2DBoldDMdR0p3wLT ID working point (2017v2): bitmask 1 = VVLoose, 2 = VLoose, 4 = Loose, 8 = Medium, 16 = Tight, 32 = VTight, 64 = VVTight'),
0062     Plot1D('rawMVAoldDMdR032017v2', 'rawMVAoldDMdR032017v2', 20, -1, 1, 'byIsolationMVArun2017v2DBoldDMdR0p3wLT raw output discriminator (2017v2)')
0063 ])
0064
0065 (run2_nanoAOD_106Xv2).toModify(nanoDQM.vplots.boostedTau, plots = _boostedTauPlotsV10)
0066
0067 _METFixEE2017_DQMentry = nanoDQM.vplots.MET.clone()
0068 _METFixEE2017_plots = cms.VPSet()
0069 for plot in _METFixEE2017_DQMentry.plots:
0070     if plot.name.value().find("fiducial")>-1: continue
0071     _METFixEE2017_plots.append(plot)
0072 _METFixEE2017_DQMentry.plots = _METFixEE2017_plots
0073 for modifier in run2_nanoAOD_94XMiniAODv1, run2_nanoAOD_94XMiniAODv2:
0074     modifier.toModify(nanoDQM.vplots, METFixEE2017 = _METFixEE2017_DQMentry)
0075
0076 _Electron_plots_2016 = copy.deepcopy(nanoDQM.vplots.Electron.plots)
0077 _Electron_plots_2016.append(Plot1D('cutBased_HLTPreSel', 'cutBased_HLTPreSel', 2, -0.5, 1.5, 'cut-based HLT pre-selection ID'))
0078 _Electron_plots_2016.append(Plot1D('cutBased_Spring15', 'cutBased_Spring15', 5, -0.5, 4.5, 'cut-based Spring15 ID (0:fail, 1:veto, 2:loose, 3:medium, 4:tight)'))
0079 _Electron_plots_2016.append(Plot1D('mvaSpring16GP', 'mvaSpring16GP', 20, -1, 1, 'MVA Spring16 general-purpose ID score'))
0080 _Electron_plots_2016.append(Plot1D('mvaSpring16GP_WP80', 'mvaSpring16GP_WP80', 2, -0.5, 1.5, 'MVA Spring16 general-purpose ID WP80'))
0081 _Electron_plots_2016.append(Plot1D('mvaSpring16GP_WP90', 'mvaSpring16GP_WP90', 2, -0.5, 1.5, 'MVA Spring16 general-purpose ID WP90'))
0082 _Electron_plots_2016.append(Plot1D('mvaSpring16HZZ', 'mvaSpring16HZZ', 20, -1, 1, 'MVA Spring16 HZZ ID score'))
0083 _Electron_plots_2016.append(Plot1D('mvaSpring16HZZ_WPL', 'mvaSpring16HZZ_WPL', 2, -0.5, 1.5, 'MVA Spring16 HZZ ID loose WP'))
0084 _Electron_plots_2016.append(NoPlot('vidNestedWPBitmapSpring15'))
0085
0086 #putting back the fall17V1 plots for non v9 case
0087 _Electron_plots_withFall17V1 = copy.deepcopy(nanoDQM.vplots.Electron.plots)
0088 _Electron_plots_withFall17V1.append(Plot1D('cutBased_Fall17_V1', 'cutBased_Fall17_V1', 5, -0.5, 4.5, 'cut-based ID Fall17 V1 (0:fail, 1:veto, 2:loose, 3:medium, 4:tight)'))
0089 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1Iso', 'mvaFall17V1Iso', 20, -1, 1, 'MVA Iso ID V1 score'))
0090 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1Iso_WP80', 'mvaFall17V1Iso_WP80', 2, -0.5, 1.5, 'MVA Iso ID V1 WP80'))
0091 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1Iso_WP90', 'mvaFall17V1Iso_WP90', 2, -0.5, 1.5, 'MVA Iso ID V1 WP90'))
0092 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1Iso_WPL', 'mvaFall17V1Iso_WPL', 2, -0.5, 1.5, 'MVA Iso ID V1 loose WP'))
0093 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1noIso', 'mvaFall17V1noIso', 20, -1, 1, 'MVA noIso ID V1 score'))
0094 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1noIso_WP80', 'mvaFall17V1noIso_WP80', 2, -0.5, 1.5, 'MVA noIso ID V1 WP80'))
0095 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1noIso_WP90', 'mvaFall17V1noIso_WP90', 2, -0.5, 1.5, 'MVA noIso ID V1 WP90'))
0096 _Electron_plots_withFall17V1.append(Plot1D('mvaFall17V1noIso_WPL', 'mvaFall17V1noIso_WPL', 2, -0.5, 1.5, 'MVA noIso ID V1 loose WP'))
0097
0098 _Photon_plots_2016 = copy.deepcopy(nanoDQM.vplots.Photon.plots)
0099 _Photon_plots_2016.append(Plot1D('cutBased', 'cutBased', 4, -0.5, 3.5, 'cut-based Spring16-V2p2 ID (0:fail, 1::loose, 2:medium, 3:tight)'))
0100 _Photon_plots_2016.append(Plot1D('cutBased17Bitmap', 'cutBased17Bitmap', 8, -0.5, 7.5, 'cut-based Fall17-94X-V1 ID bitmap, 2^(0:loose, 1:medium, 2:tight)'))
0101 _Photon_plots_2016.append(Plot1D('mvaID17', 'mvaID17', 20, -1, 1, 'MVA Fall17v1p1 ID score'))
0102 _Photon_plots_2016.append(Plot1D('mvaID17_WP80', 'mvaID17_WP80', 2, -0.5, 1.5, 'MVA Fall17v1p1 ID WP80'))
0103 _Photon_plots_2016.append(Plot1D('mvaID17_WP90', 'mvaID17_WP90', 2, -0.5, 1.5, 'MVA Fall17v1p1 ID WP90'))
0104
0105 _FatJet_plots_80x = copy.deepcopy(nanoDQM.vplots.FatJet.plots)
0106 _FatJet_plots_80x.append(Plot1D('msoftdrop_chs', 'msoftdrop_chs', 20, -300, 300, 'Legacy uncorrected soft drop mass with CHS'))
0107
0108 _Flag_plots_80x = copy.deepcopy(nanoDQM.vplots.Flag.plots)
0109 _Flag_plots_80x.append(Plot1D('BadGlobalMuon', 'BadGlobalMuon', 2, -0.5, 1.5, 'Bad muon flag'))
0110 _Flag_plots_80x.append(Plot1D('CloneGlobalMuon', 'CloneGlobalMuon', 2, -0.5, 1.5, 'Clone muon flag'))
0111
0112 for modifier in run2_miniAOD_80XLegacy, run2_nanoAOD_94X2016:
0113     modifier.toModify(nanoDQM.vplots.Electron, plots = _Electron_plots_2016)
0114     modifier.toModify(nanoDQM.vplots.Photon, plots = _Photon_plots_2016)
0115 run2_miniAOD_80XLegacy.toModify(nanoDQM.vplots.FatJet, plots = _FatJet_plots_80x)
0116 run2_miniAOD_80XLegacy.toModify(nanoDQM.vplots.Flag, plots = _Flag_plots_80x)
0117 (run2_nanoAOD_92X | run2_nanoAOD_94XMiniAODv1 | run2_nanoAOD_94XMiniAODv2 | run2_nanoAOD_94X2016 | run2_nanoAOD_102Xv1).toModify(nanoDQM.vplots.Electron, plots=_Electron_plots_withFall17V1)
0118
0119 run2_miniAOD_80XLegacy.toModify(nanoDQM.vplots, IsoTrack = None)
0120
0121 ## MC
0122 nanoDQMMC = nanoDQM.clone()
0123 nanoDQMMC.vplots.Electron.sels.Prompt = cms.string("genPartFlav == 1")
0124 nanoDQMMC.vplots.LowPtElectron.sels.Prompt = cms.string("genPartFlav == 1")
0125 nanoDQMMC.vplots.Muon.sels.Prompt = cms.string("genPartFlav == 1")
0126 nanoDQMMC.vplots.Photon.sels.Prompt = cms.string("genPartFlav == 1")
0127 nanoDQMMC.vplots.Tau.sels.Prompt = cms.string("genPartFlav == 5")
0128 nanoDQMMC.vplots.Jet.sels.Prompt = cms.string("genJetIdx != 1")
0129 nanoDQMMC.vplots.Jet.sels.PromptB = cms.string("genJetIdx != 1 && hadronFlavour == 5")
0130
0131 from DQMServices.Core.DQMQualityTester import DQMQualityTester
0132 nanoDQMQTester = DQMQualityTester(
0133     qtList = cms.untracked.FileInPath('PhysicsTools/NanoAOD/test/dqmQualityTests.xml'),
0134     prescaleFactor = cms.untracked.int32(1),
0135     testInEventloop = cms.untracked.bool(False),
0136     qtestOnEndLumi = cms.untracked.bool(False),
0137     verboseQT =  cms.untracked.bool(True)
0138 )
0139
0140 (run3_nanoAOD_devel).toModify(nanoDQM.vplots, Electron = None)
0141 (run3_nanoAOD_devel).toModify(nanoDQMMC.vplots, Electron = None)
0142
0143 _modifiers = ( run2_miniAOD_80XLegacy |
0144                run2_nanoAOD_94XMiniAODv1 |
0145                run2_nanoAOD_94XMiniAODv2 |
0146                run2_nanoAOD_94X2016 |
0147                run2_nanoAOD_102Xv1 |
0148                run2_nanoAOD_106Xv1 )
0149 _modifiers.toModify(nanoDQM.vplots, LowPtElectron = None)
0150 _modifiers.toModify(nanoDQMMC.vplots, LowPtElectron = None)
0151
0152 nanoHarvest = cms.Sequence( nanoDQMQTester )