print "#Saving yields to pickle"
# save to pickle
import cPickle as pickle
pickle.dump( ydsSyst, open( pckname, "wb" ) )
# Sys types
# systs = ["btagHF","Wxsec","topPt","PU","DLSlope","DLConst"]#,"JEC"]
# systs = ["Wxsec","PU","JEC","btagHF","btagLF","topPt"]
# systs = ["Wxsec","PU","JEC","btagHF","btagLF","topPt","DLConst","DLSlope","JER"]
systs = ["TTVxsec","Wpol","Wxsec","PU","JEC","btagHF","btagLF","topPt","DLConst","DLSlope"]
# Kappa systematics
samp = "EWK"; var = "Kappa"
systSamps = [(samp+"_"+syst+"_syst",var) for syst in systs]
systHists = yp.makeSampHists(ydsSyst,systSamps)
hKappaSysts = yp.getSquaredSum(systHists)
print "Created syst hist", hKappaSysts
# MC systematics
samp = "EWK"; var = "SR_MB"
systSamps = [(samp+"_"+syst+"_syst",var) for syst in systs]
systHists = yp.makeSampHists(ydsSyst,systSamps)
hMCSysts = yp.getSquaredSum(systHists)
###########################
## Make Prediction plots ##
###########################
hPredUnc.SetFillStyle(3244)
hPredUnc.SetMarkerColor(col)
hPredUnc.SetMarkerStyle(0)
hPredUnc.GetYaxis().SetTitle(ratio.GetYaxis().GetTitle())
hPredUnc.GetYaxis().SetRangeUser(0,3.9)
# set error
for i in xrange(1,hPredUnc.GetNbinsX()+1):
try:
hPredUnc.SetBinError(i,hDataPred.GetBinError(i)/hDataPred.GetBinContent(i))
except ZeroDivisionError:
hPredUnc.SetBinError(i, 0.)
# MC samps
samps = [(samp,cat) for samp in mcSamps]
mcHists = yp.makeSampHists(yds,samps)
# Scale MC hists to Prediction
scaleToHist(mcHists,hDataPred)
mcStack = yp.getStack(mcHists)
hUncert = hDataPred.Clone("uncert")
hUncert.SetTitle("Statistical Uncertainty only")
yp.setUnc(hUncert)
#canv = plotHists("DataNJ45_"+cat,[stack,hMCpred,hDataPred,hData,total],ratio)
width = 1200
height = 600
legPos = "TM"
if doSquare == True:
print "#Saving yields to pickle"
# save to pickle
import cPickle as pickle
pickle.dump( ydsSyst, open( "allSysts.pck", "wb" ) )
# Sys types
# systs = ["btagHF","Wxsec","topPt","PU","DLSlope","DLConst"]#,"JEC"]
# systs = ["Wxsec","PU","JEC","btagHF","btagLF","topPt"]
# systs = ["Wxsec","PU","JEC","btagHF","btagLF","topPt","DLConst","DLSlope","JER"]
systs = ["TTVxsec","Wpol","Wxsec","PU","JEC","btagHF","btagLF","topPt","DLConst","DLSlope"]
# Kappa systematics
samp = "EWK"; var = "Kappa"
systSamps = [(samp+"_"+syst+"_syst",var) for syst in systs]
systHists = yp.makeSampHists(ydsSyst,systSamps)
hKappaSysts = yp.getSquaredSum(systHists)
print "Created syst hist", hKappaSysts
# MC systematics
samp = "EWK"; var = "SR_MB"
systSamps = [(samp+"_"+syst+"_syst",var) for syst in systs]
systHists = yp.makeSampHists(ydsSyst,systSamps)
hMCSysts = yp.getSquaredSum(systHists)
###########################
## Make Prediction plots ##
###########################
