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nanoDQM_cff.py
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1 import FWCore.ParameterSet.Config as cms
2 import copy
3 
4 from PhysicsTools.NanoAOD.nanoDQM_cfi import nanoDQM
7 
8 _boostedTauPlotsV10 = cms.VPSet()
9 for plot in nanoDQM.vplots.boostedTau.plots:
10  _boostedTauPlotsV10.append(plot)
11 _boostedTauPlotsV10.extend([
12  Plot1D('idMVAoldDMdR032017v2', 'idMVAoldDMdR032017v2', 11, -0.5, 10.5, 'IsolationMVArun2017v2DBoldDMdR0p3wLT ID working point (2017v2): int 1 = VVLoose, 2 = VLoose, 3 = Loose, 4 = Medium, 5 = Tight, 6 = VTight, 7 = VVTight'),
13  Plot1D('rawMVAoldDMdR032017v2', 'rawMVAoldDMdR032017v2', 20, -1, 1, 'byIsolationMVArun2017v2DBoldDMdR0p3wLT raw output discriminator (2017v2)')
14 ])
15 
16 (run2_nanoAOD_106Xv2).toModify(
17  nanoDQM.vplots.boostedTau,
18  plots = _boostedTauPlotsV10
19 )
20 
21 _Electron_Run2_plots = cms.VPSet()
22 for plot in nanoDQM.vplots.Electron.plots:
23  if 'Fall17V2' not in plot.name.value():
24  _Electron_Run2_plots.append(plot)
25 _Electron_Run2_plots.extend([
26  Plot1D('dEscaleUp', 'dEscaleUp', 100, -0.01, 0.01, '#Delta E scaleUp'),
27  Plot1D('dEscaleDown', 'dEscaleDown', 100, -0.01, 0.01, '#Delta E scaleDown'),
28  Plot1D('dEsigmaUp', 'dEsigmaUp', 100, -0.1, 0.1, '#Delta E sigmaUp'),
29  Plot1D('dEsigmaDown', 'dEsigmaDown', 100, -0.1, 0.1, '#Delta E sigmaDown'),
30  Plot1D('eCorr', 'eCorr', 20, 0.8, 1.2, 'ratio of the calibrated energy/miniaod energy'),
31 ])
32 run2_egamma.toModify(
33  nanoDQM.vplots.Electron,
34  plots = _Electron_Run2_plots
35 )
36 
37 _Photon_Run2_plots = cms.VPSet()
38 def _match(name):
39  if 'Fall17V2' in name: return True
40  if '_quadratic' in name: return True
41  if 'hoe_PUcorr' in name: return True
42  return False
43 for plot in nanoDQM.vplots.Photon.plots:
44  if not _match(plot.name.value()):
45  _Photon_Run2_plots.append(plot)
46 _Photon_Run2_plots.extend([
47  Plot1D('pfRelIso03_all', 'pfRelIso03_all', 20, 0, 2, 'PF relative isolation dR=0.3, total (with rho*EA PU Fall17V2 corrections)'),
48  Plot1D('pfRelIso03_chg', 'pfRelIso03_chg', 20, 0, 2, 'PF relative isolation dR=0.3, charged component (with rho*EA PU Fall17V2 corrections)'),
49  Plot1D('dEscaleUp', 'dEscaleUp', 100, -0.01, 0.01, '#Delta E scaleUp'),
50  Plot1D('dEscaleDown', 'dEscaleDown', 100, -0.01, 0.01, '#Delta E scaleDown'),
51  Plot1D('dEsigmaUp', 'dEsigmaUp', 100, -0.1, 0.1, '#Delta E sigmaUp'),
52  Plot1D('dEsigmaDown', 'dEsigmaDown', 100, -0.1, 0.1, '#Delta E sigmaDown'),
53  Plot1D('eCorr', 'eCorr', 20, 0.8, 1.2, 'ratio of the calibrated energy/miniaod energy'),
54 ])
55 run2_egamma.toModify(
56  nanoDQM.vplots.Photon,
57  plots = _Photon_Run2_plots
58 )
59 
60 _FatJet_Run2_plots = cms.VPSet()
61 for plot in nanoDQM.vplots.FatJet.plots:
62  _FatJet_Run2_plots.append(plot)
63 _FatJet_Run2_plots.extend([
64  Plot1D('btagCSVV2', 'btagCSVV2', 20, -1, 1, ' pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)'),
65  Plot1D('deepTagMD_H4qvsQCD', 'deepTagMD_H4qvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger H->4q vs QCD discriminator'),
66  Plot1D('deepTagMD_HbbvsQCD', 'deepTagMD_HbbvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger H->bb vs QCD discriminator'),
67  Plot1D('deepTagMD_TvsQCD', 'deepTagMD_TvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger top vs QCD discriminator'),
68  Plot1D('deepTagMD_WvsQCD', 'deepTagMD_WvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger W vs QCD discriminator'),
69  Plot1D('deepTagMD_ZHbbvsQCD', 'deepTagMD_ZHbbvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger Z/H->bb vs QCD discriminator'),
70  Plot1D('deepTagMD_ZHccvsQCD', 'deepTagMD_ZHccvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger Z/H->cc vs QCD discriminator'),
71  Plot1D('deepTagMD_ZbbvsQCD', 'deepTagMD_ZbbvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger Z->bb vs QCD discriminator'),
72  Plot1D('deepTagMD_ZvsQCD', 'deepTagMD_ZvsQCD', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger Z vs QCD discriminator'),
73  Plot1D('deepTagMD_bbvsLight', 'deepTagMD_bbvsLight', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger Z/H/gluon->bb vs light flavour discriminator'),
74  Plot1D('deepTagMD_ccvsLight', 'deepTagMD_ccvsLight', 20, 0, 1, 'Mass-decorrelated DeepBoostedJet tagger Z/H/gluon->cc vs light flavour discriminator'),
75  Plot1D('deepTag_H', 'deepTag_H', 20, 0, 1, 'DeepBoostedJet tagger H(bb,cc,4q) sum'),
76  Plot1D('deepTag_QCD', 'deepTag_QCD', 20, 0, 1, 'DeepBoostedJet tagger QCD(bb,cc,b,c,others) sum'),
77  Plot1D('deepTag_QCDothers', 'deepTag_QCDothers', 20, 0, 1, 'DeepBoostedJet tagger QCDothers value'),
78  Plot1D('deepTag_TvsQCD', 'deepTag_TvsQCD', 20, 0, 1, 'DeepBoostedJet tagger top vs QCD discriminator'),
79  Plot1D('deepTag_WvsQCD', 'deepTag_WvsQCD', 20, 0, 1, 'DeepBoostedJet tagger W vs QCD discriminator'),
80  Plot1D('deepTag_ZvsQCD', 'deepTag_ZvsQCD', 20, 0, 1, 'DeepBoostedJet tagger Z vs QCD discriminator'),
81  Plot1D('particleNetLegacy_mass', 'particleNetLegacy_mass', 25, 0, 250, 'ParticleNet Legacy Run-2 mass regression'),
82  Plot1D('particleNetLegacy_Xbb', 'particleNetLegacy_Xbb', 20, 0, 1, 'ParticleNet Legacy Run-2 X->bb score'),
83  Plot1D('particleNetLegacy_Xcc', 'particleNetLegacy_Xcc', 20, 0, 1, 'ParticleNet Legacy Run-2 X->cc score'),
84  Plot1D('particleNetLegacy_Xqq', 'particleNetLegacy_Xqq', 20, 0, 1, 'ParticleNet Legacy Run-2 X->qq (uds) score'),
85  Plot1D('particleNetLegacy_QCD', 'particleNetLegacy_QCD', 20, 0, 1, 'ParticleNet Legacy Run-2 QCD score'),
86 ])
87 
88 _FatJet_EarlyRun3_plots = cms.VPSet()
89 for plot in _FatJet_Run2_plots:
90  if 'particleNet_' not in plot.name.value() and 'btagCSVV2' not in plot.name.value():
91  _FatJet_EarlyRun3_plots.append(plot)
92 
93 _Jet_Run2_plots = cms.VPSet()
94 for plot in nanoDQM.vplots.Jet.plots:
95  _Jet_Run2_plots.append(plot)
96 _Jet_Run2_plots.extend([
97  Plot1D('btagCSVV2', 'btagCSVV2', 20, -1, 1, ' pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)'),
98  Plot1D('btagCMVA', 'btagCMVA', 20, -1, 1, 'CMVA V2 btag discriminator'),
99  Plot1D('btagDeepB', 'btagDeepB', 20, -1, 1, 'Deep B+BB btag discriminator'),
100  Plot1D('btagDeepC', 'btagDeepC', 20, 0, 1, 'DeepCSV charm btag discriminator'),
101  Plot1D('btagDeepCvB', 'btagDeepCvB', 20, -1, 1, 'DeepCSV c vs b+bb discriminator'),
102  Plot1D('btagDeepCvL', 'btagDeepCvL', 20, -1, 1, 'DeepCSV c vs udsg discriminator')
103 ])
104 
105 _Jet_EarlyRun3_plots = cms.VPSet()
106 for plot in nanoDQM.vplots.Jet.plots:
107  if 'PNet' not in plot.name.value():
108  _Jet_EarlyRun3_plots.append(plot)
109 
110 _SubJet_Run2_plots = cms.VPSet()
111 for plot in nanoDQM.vplots.SubJet.plots:
112  _SubJet_Run2_plots.append(plot)
113 _SubJet_Run2_plots.extend([
114  Plot1D('btagCSVV2', 'btagCSVV2', 20, -1, 1, ' pfCombinedInclusiveSecondaryVertexV2 b-tag discriminator (aka CSVV2)'),
115 ])
116 
117 run2_nanoAOD_ANY.toModify(
118  nanoDQM.vplots.FatJet,
119  plots = _FatJet_Run2_plots
120 ).toModify(
121  nanoDQM.vplots.Jet,
122  plots = _Jet_Run2_plots
123 ).toModify(
124  nanoDQM.vplots.SubJet,
125  plots = _SubJet_Run2_plots
126 )
127 
128 (run3_nanoAOD_122 | run3_nanoAOD_124).toModify(
129  nanoDQM.vplots.FatJet,
130  plots = _FatJet_EarlyRun3_plots
131 ).toModify(
132  nanoDQM.vplots.Jet,
133  plots = _Jet_EarlyRun3_plots
134 )
135 
136 
137 nanoDQMMC = nanoDQM.clone()
138 nanoDQMMC.vplots.Electron.sels.Prompt = cms.string("genPartFlav == 1")
139 nanoDQMMC.vplots.LowPtElectron.sels.Prompt = cms.string("genPartFlav == 1")
140 nanoDQMMC.vplots.Muon.sels.Prompt = cms.string("genPartFlav == 1")
141 nanoDQMMC.vplots.Photon.sels.Prompt = cms.string("genPartFlav == 1")
142 nanoDQMMC.vplots.Tau.sels.Prompt = cms.string("genPartFlav == 5")
143 nanoDQMMC.vplots.Jet.sels.Prompt = cms.string("genJetIdx != 1")
144 nanoDQMMC.vplots.Jet.sels.PromptB = cms.string("genJetIdx != 1 && hadronFlavour == 5")
145 
146 from DQMServices.Core.DQMQualityTester import DQMQualityTester
147 nanoDQMQTester = DQMQualityTester(
148  qtList = cms.untracked.FileInPath('PhysicsTools/NanoAOD/test/dqmQualityTests.xml'),
149  prescaleFactor = cms.untracked.int32(1),
150  testInEventloop = cms.untracked.bool(False),
151  qtestOnEndLumi = cms.untracked.bool(False),
152  verboseQT = cms.untracked.bool(True)
153 )
154 
155 nanoHarvest = cms.Sequence( nanoDQMQTester )
def _match(name)
Definition: nanoDQM_cff.py:38