# load appropriate scale and smearing bins here
# systematics customization scripts will take care of adjusting flashggDiPhotonSystematics
if "Run2015" in customize.datasetName() or "76X" in customize.datasetName():
process.load('flashgg.Systematics.escales.escale76X_16DecRereco_2015')
print "energy corrections file is escale76X_16DecRereco_2015"
else:
## process.load('flashgg.Systematics.escales.test_2016B_corr_DCSOnly')
## process.load('flashgg.Systematics.escales.Golden10June_plus_DCS')
## process.load('flashgg.Systematics.escales.Golden22June')
## process.load('flashgg.Systematics.escales.80X_DCS05July_plus_Golden22')
process.load('flashgg.Systematics.escales.80X_ichep_2016_pho')
print "energy corrections file is test_2016B_corr"
#
# input and output
#
process.source = cms.Source("PoolSource",
fileNames=cms.untracked.vstring(
"file:diphotonsMicroAOD.root"
)
)
process.TFileService = cms.Service("TFileService",
fileName = cms.string("test.root")
)
# this will call customize(process), configure the analysis paths and make the process unscheduled
analysis.customize(process,customize)
True), ## removeIndex(es), label, dumpTree, dumpWorkspace, dumpHistos
(1, "NoPhoIso", False, False, True),
(2, "NoNeuIso", False, False, True),
(3, "NoHoverE", False, False, True),
(4, "NoSigmaIetaIeta", False, False, True),
(5, "NoEleVeto", False, False, True),
## Sidebands
## removeIndex, (ignoreIndex(es),ingnoreNtimes), dumpTree, dumpWorkspace, dumpHistos, splitByIso
((0, 1), (4, 1), "NoChIsoSB", True, False, True, False),
(1, (4, 1), "NoPhoIsoSB", False, False, True, False)
])
# make sure process doesn't get stuck due to slow I/O
process.watchDog = cms.EDAnalyzer(
"IdleWatchdog",
minIdleFraction=cms.untracked.double(0.5),
tolerance=cms.untracked.int32(10),
checkEvery=cms.untracked.int32(100),
)
process.watch = cms.Path(process.watchDog)
# final customization
from diphotons.MetaData.JobConfig import customize
customize.setDefault("maxEvents", 10000)
customize.setDefault("targetLumi", 1.e+3)
# this will call customize(process), configure the analysis paths and make the process unscheduled
analysis.customize(process, customize)
## print process.dumpPython()
