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MLClient_cfi.py
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1 import FWCore.ParameterSet.Config as cms
2 
3 from DQM.EcalMonitorTasks.OccupancyTask_cfi import ecalOccupancyTask
4 
5 #parameters derived from training
6 EBThreshold = 0.00017
7 EEpThreshold = 0.0003009
8 EEmThreshold = 0.0004360
9 
10 EB_PUcorr_slope = 9087.286563128135
11 EB_PUcorr_intercept = 391987.0277612837
12 
13 EEp_PUcorr_slope = 2.097273231210836457e+03
14 EEp_PUcorr_intercept= 4.905224959496531665e+04
15 
16 EEm_PUcorr_slope = 2.029645065864053095e+03
17 EEm_PUcorr_intercept= 4.874167219924630626e+04
18 
19 ecalMLClient = cms.untracked.PSet(
20  params = cms.untracked.PSet(
21  EBThreshold = cms.untracked.double(EBThreshold),
22  EEpThreshold = cms.untracked.double(EEpThreshold),
23  EEmThreshold = cms.untracked.double(EEmThreshold),
24  EB_PUcorr_slope = cms.untracked.double(EB_PUcorr_slope),
25  EB_PUcorr_intercept = cms.untracked.double(EB_PUcorr_intercept),
26  EEp_PUcorr_slope = cms.untracked.double(EEp_PUcorr_slope),
27  EEp_PUcorr_intercept = cms.untracked.double(EEp_PUcorr_intercept),
28  EEm_PUcorr_slope = cms.untracked.double(EEm_PUcorr_slope),
29  EEm_PUcorr_intercept = cms.untracked.double(EEm_PUcorr_intercept)
30  ),
31  sources = cms.untracked.PSet(
32  DigiAllByLumi = ecalOccupancyTask.MEs.DigiAllByLumi,
33  AELoss = ecalOccupancyTask.MEs.AELoss,
34  AEReco = ecalOccupancyTask.MEs.AEReco,
35  PU = ecalOccupancyTask.MEs.PU,
36  NumEvents = ecalOccupancyTask.MEs.NEvents,
37  BadTowerCount = ecalOccupancyTask.MEs.BadTowerCount,
38  BadTowerCountNorm = ecalOccupancyTask.MEs.BadTowerCountNorm
39  ),
40  MEs = cms.untracked.PSet(
41  MLQualitySummary = cms.untracked.PSet(
42  path = cms.untracked.string('%(subdet)s/%(prefix)sSummaryClient/%(prefix)sOT%(suffix)s ML quality summary'),
43  kind = cms.untracked.string('TH2F'),
44  otype = cms.untracked.string('Ecal3P'),
45  btype = cms.untracked.string('SuperCrystal'),
46  description = cms.untracked.string('Quality summary from the ML inference.')
47  ),
48  EventsperMLImage = cms.untracked.PSet(
49  path = cms.untracked.string('Ecal/Trends/Number of Events used per ML image'),
50  kind = cms.untracked.string('TProfile'),
51  otype = cms.untracked.string('Ecal2P'),
52  btype = cms.untracked.string('Trend'),
53  description = cms.untracked.string('Trend of the number of events in an image fed into the ML model')
54  ),
55  TrendMLBadTower = cms.untracked.PSet(
56  path = cms.untracked.string('Ecal/Trends/Number of bad towers from MLDQM %(prefix)s'),
57  kind = cms.untracked.string('TProfile'),
58  otype = cms.untracked.string('Ecal2P'),
59  btype = cms.untracked.string('Trend'),
60  description = cms.untracked.string('Trend of the number of bad towers flagged by the MLDQM model')
61  )
62  )
63 )