m.Systematics = [ Systematic(Name="Central", Direction=0, Year=-1) ]
for s in tmp_Systematics:
isCorr = IsCorrelated(s)
if isCorr:
m.Systematics.append( Systematic(Name=s, Direction=+1, Year=-1) )
m.Systematics.append( Systematic(Name=s, Direction=-1, Year=-1) )
else:
if args.Year>0:
m.Systematics.append( Systematic(Name=s, Direction=+1, Year=args.Year) )
m.Systematics.append( Systematic(Name=s, Direction=-1, Year=args.Year) )
else:
for Y in [2016,2017,2018]:
m.Systematics.append( Systematic(Name=s, Direction=+1, Year=Y) )
m.Systematics.append( Systematic(Name=s, Direction=-1, Year=Y) )
m.PrintSystematics()
#### Binning infos
m.SetBinningFilepath(
WORKING_DIR+'/data/'+dataset+'/'+str_Year+'/CR_rebins.txt',
WORKING_DIR+'/data/'+dataset+'/'+str_Year+'/CR_xaxis.txt',
WORKING_DIR+'/data/'+dataset+'/'+str_Year+'/CR_yaxis.txt',
)
#### Predef samples
from PredefinedSamples import *
if args.ApplyZPtRwg:
SampleGroup_DY_2016.Samples=['DYJets_MG_HT_Reweighted']
SampleGroup_DY_2017.Samples=['DYJets_MG_HT_Reweighted']
SampleGroup_DY_2018.Samples=['DYJets_MG_HT_Reweighted']
if args.ApplyDYReshape:
