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[14_1_X] Update the egamma regression for 2023 UPC PbPb rereco and the corresponding GTs in autoCond #46685

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Nov 26, 2024
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[14_1_X] Update the egamma regression for 2023 UPC PbPb rereco and the corresponding GTs in autoCond #46685

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4 changes: 2 additions & 2 deletions Configuration/AlCa/python/autoCond.py
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Expand Up @@ -38,7 +38,7 @@
# GlobalTag for Run3 data relvals (prompt GT): same as 141X_dataRun3_Prompt_v3 but with snapshot at 2024-09-12 11:03:32 (UTC)
'run3_data_prompt' : '141X_dataRun3_Prompt_frozen_v3',
# GlobalTag for Run3 offline data reprocessing - snapshot at 2024-11-12 07:39:42 (UTC)
'run3_data' : '140X_dataRun3_v17',
'run3_data' : '141X_dataRun3_v4',
# GlobalTag for Run3 offline data reprocessing with Prompt GT, currently for 2022FG - snapshot at 2024-02-12 12:00:00 (UTC)
'run3_data_PromptAnalysis' : '140X_dataRun3_PromptAnalysis_v2',
# GlobalTag for MC production with perfectly aligned and calibrated detector for Phase1 2017 (and 0,0,~0-centred beamspot)
Expand Down Expand Up @@ -88,7 +88,7 @@
# GlobalTag for MC production (cosmics) with perfectly aligned and calibrated detector for Phase1 2023, Strip tracker in DECO mode
'phase1_2023_cosmics_design' : '140X_mcRun3_2023cosmics_design_deco_v1',
# GlobalTag for MC production with realistic conditions for Phase1 2023 detector for Heavy Ion
'phase1_2023_realistic_hi' : '141X_mcRun3_2023_realistic_HI_v3',
'phase1_2023_realistic_hi' : '141X_mcRun3_2023_realistic_HI_v4',
# GlobalTag for MC production with perfectly aligned and calibrated detector for Phase1 2024
'phase1_2024_design' : '140X_mcRun3_2024_design_v11',
# GlobalTag for MC production with realistic conditions for Phase1 2024
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2 changes: 1 addition & 1 deletion Configuration/PyReleaseValidation/python/relval_steps.py
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Expand Up @@ -2739,7 +2739,7 @@ def lhegensim2018ml(fragment,howMuch):

steps['RECODR2_2016_UPC']=merge([{'--conditions':'auto:run2_data', '--era':'Run2_2016_UPC', '-s':'RAW2DIGI,L1Reco,RECO,DQM:@commonFakeHLT+@standardDQMFakeHLT', '--repacked':''},steps['RECODR2_2016']])
steps['RECODR3_2023_HIN']=merge([{'--conditions':'auto:run3_data_prompt', '-s':'RAW2DIGI,L1Reco,RECO,DQM:@commonFakeHLT+@standardDQMFakeHLT', '--repacked':'', '-n':1000},steps['RECODR3_2023']])
steps['RECODR3_2023_UPC']=merge([{'--era':'Run3_2023_UPC'},steps['RECODR3_2023_HIN']])
steps['RECODR3_2023_UPC']=merge([{'--conditions':'auto:run3_data', '--era':'Run3_2023_UPC'},steps['RECODR3_2023_HIN']])
steps['RECODR3_2024_HIN']=merge([{'--conditions':'auto:run3_data_prompt', '-s':'RAW2DIGI,L1Reco,RECO,DQM:@commonFakeHLT+@standardDQMFakeHLT', '--repacked':'', '-n':1000},steps['RECODR3_2024']])
steps['RECODR3_2024_UPC']=merge([{'--era':'Run3_2024_UPC'},steps['RECODR3_2024_HIN']])

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6 changes: 6 additions & 0 deletions RecoEcal/EgammaClusterProducers/python/particleFlowSuperClusterECAL_cfi.py
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Expand Up @@ -28,3 +28,9 @@
thresh_PFClusterSeedBarrel = 0.5,
thresh_PFClusterSeedEndcap = 0.5)

from Configuration.Eras.Era_Run3_2023_UPC_cff import Run3_2023_UPC
(egamma_lowPt_exclusive & Run3_2023_UPC).toModify(particleFlowSuperClusterECAL, regressionConfig = dict(
regressionKeyEB = 'pfscecal_ebCorrection_offline_v2',
uncertaintyKeyEB = 'pfscecal_ebUncertainty_offline_v2',
regressionKeyEE = 'pfscecal_eeCorrection_offline_v2',
uncertaintyKeyEE = 'pfscecal_eeUncertainty_offline_v2'))
35 changes: 35 additions & 0 deletions RecoEgamma/EgammaElectronProducers/python/lowPtGsfElectrons_cfi.py
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Expand Up @@ -39,6 +39,41 @@
),
)

from RecoEgamma.EgammaTools.regressionModifier_cfi import regressionModifier103XLowPtPho
_lowPtRegressionModifierUPC = regressionModifier103XLowPtPho.clone(
eleRegs = dict(
ecalOnlyMean = dict(
ebLowEtForestName = ":lowPtElectron_eb_ecalOnly_1To20_0p2To2_mean",
ebHighEtForestName = ":lowPtElectron_eb_ecalOnly_1To20_0p2To2_mean",
eeLowEtForestName = ":lowPtElectron_ee_ecalOnly_1To20_0p2To2_mean",
eeHighEtForestName = ":lowPtElectron_ee_ecalOnly_1To20_0p2To2_mean",
),
ecalOnlySigma = dict(
ebLowEtForestName = ":lowPtElectron_eb_ecalOnly_1To20_0p0002To0p5_sigma",
ebHighEtForestName = ":lowPtElectron_eb_ecalOnly_1To20_0p0002To0p5_sigma",
eeLowEtForestName = ":lowPtElectron_ee_ecalOnly_1To20_0p0002To0p5_sigma",
eeHighEtForestName = ":lowPtElectron_ee_ecalOnly_1To20_0p0002To0p5_sigma",
),
epComb = dict(
ecalTrkRegressionConfig = dict(
ebLowEtForestName = ":lowPtElectron_eb_ecalTrk_1To20_0p2To2_mean",
ebHighEtForestName = ":lowPtElectron_eb_ecalTrk_1To20_0p2To2_mean",
eeLowEtForestName = ":lowPtElectron_ee_ecalTrk_1To20_0p2To2_mean",
eeHighEtForestName = ":lowPtElectron_ee_ecalTrk_1To20_0p2To2_mean",
),
ecalTrkRegressionUncertConfig = dict(
ebLowEtForestName = ":lowPtElectron_eb_ecalTrk_1To20_0p0002To0p5_sigma",
ebHighEtForestName = ":lowPtElectron_eb_ecalTrk_1To20_0p0002To0p5_sigma",
eeLowEtForestName = ":lowPtElectron_ee_ecalTrk_1To20_0p0002To0p5_sigma",
eeHighEtForestName = ":lowPtElectron_ee_ecalTrk_1To20_0p0002To0p5_sigma",
),
)
),
)
from Configuration.Eras.Era_Run3_2023_UPC_cff import Run3_2023_UPC
from Configuration.ProcessModifiers.egamma_lowPt_exclusive_cff import egamma_lowPt_exclusive
(egamma_lowPt_exclusive & Run3_2023_UPC).toReplaceWith(lowPtRegressionModifier,_lowPtRegressionModifierUPC)

from RecoEgamma.EgammaElectronProducers.lowPtGsfElectronFinalizer_cfi import lowPtGsfElectronFinalizer
lowPtGsfElectrons = lowPtGsfElectronFinalizer.clone(
previousGsfElectronsTag = "lowPtGsfElectronsPreRegression",
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17 changes: 17 additions & 0 deletions RecoEgamma/EgammaTools/python/regressionModifier_cfi.py
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Expand Up @@ -266,5 +266,22 @@
from Configuration.Eras.Modifier_run3_egamma_cff import run3_egamma
run3_egamma.toReplaceWith(regressionModifier,regressionModifierRun3)

from Configuration.Eras.Era_Run3_2023_UPC_cff import Run3_2023_UPC
from Configuration.Eras.Modifier_run3_egamma_2023_cff import run3_egamma_2023
(run3_egamma_2023 & Run3_2023_UPC).toModify(regressionModifier103XLowPtPho,
eleRegs = dict(
ecalOnlyMean = dict(
rangeMinHighEt = 0.2,
rangeMaxHighEt = 2.0
)
),
phoRegs = dict(
ecalOnlyMean = dict(
rangeMinHighEt = 0.2,
rangeMaxHighEt = 2.0
)
)
)

from Configuration.ProcessModifiers.egamma_lowPt_exclusive_cff import egamma_lowPt_exclusive
egamma_lowPt_exclusive.toReplaceWith(regressionModifier,regressionModifier103XLowPtPho)