def scaleToHist(hists, hRef):
hTotal = yp.getTotal(hists)
for hist in hists:
hist.Divide(hTotal)
hist.Multiply(hRef)
mcSamps = ['DY','TTV','SingleT','WJets','TT']
#mcSamps = ['EWK']
# update colors
yp.colorDict["MC_prediction"] = yp.kRed
yp.colorDict["Data_prediction"] = yp.kRed
# Category
cat = "SR_MB_predict"
# MC samps
samps = [(samp,cat) for samp in mcSamps]
mcHists = yp.makeSampHists(yds,samps)
mcStack = yp.getStack(mcHists)
hTotal = yp.getTotal(mcHists)
# for MC closure
mcsamp = "EWK_poisson"
mcsamp = "background_poisson_QCDsubtr"
hMCpred = yp.makeSampHisto(yds,mcsamp,cat,"MC_prediction"); hMCpred.SetTitle("MC (Pred)")
# DATA
hDataPred = yp.makeSampHisto(yds,"data_QCDsubtr",cat,"Data_prediction"); hDataPred.SetTitle("Data (Pred)")
hData = yp.makeSampHisto(yds,"data_QCDsubtr","SR_MB","Data"); hData.SetTitle("Data")
## Append Systematics to prediction
print "Appending syst. unc. to prediction and total MC"
hDataPred = yp.getHistWithError(hDataPred, hKappaSysts, new = False)
hTotal = yp.getHistWithError(hTotal, hMCSysts, new = False)
# mcSamps = ["EWK","TTJets","WJets","SingleTop","DY","TTV"]
#mcSamps = ['TTdiLep','TTsemiLep','WJets','TTV','SingleT','DY']
mcSamps = ['DY', 'TTV', 'SingleT', 'WJets', 'TTdiLep', 'TTsemiLep']
cat = "SR_MB"
#logY = True
logY = False
print "Making plot for", cat
# MC samps
samps = [(samp, cat) for samp in mcSamps]
mcHists = yp.makeSampHists(ydsMC, samps)
hMC = yp.getStack(mcHists)
hTotal = yp.getTotal(mcHists)
# Signals
sighists = []
masses = []
mass = "mGo1500_mLSP100"
massName = "(1500,100)"
masses.append((mass, massName, yp.kMagenta))
mass = "mGo1200_mLSP800"
massName = "(1200,800)"
masses.append((mass, massName, yp.kBlack))
for (mass, massName, col) in masses:
