#yp.prepKappaHist(hist)
#yp.prepRatio(hist)
# normalize to central value
#hist.Divide(hCentral)
hists.append(hist)
#for hist in hists: print hist.GetName()
# make stack/total syst hists
#total = yp.getTotal(hists)
stack = yp.getStack(hists)
#sqHist = yp.getSquaredSum(hists)
sqHist = yp.getSquaredSum(hists[::-1])
hCentralUncert = yp.getHistWithError(hCentral, sqHist)
hCentral.GetYaxis().SetRangeUser(0, 5.9)
hCentral.GetYaxis().SetTitleSize(0.15)
hCentral.GetYaxis().SetTitleOffset(0.17)
# save hists
allhists += hists + [hCentral, hCentralUncert, stack, sqHist]
canv = yp.plotHists(var + "_" + signame, [stack, sqHist],
[hCentral, hCentralUncert],
"TLC",
1200,
600,
# 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 ##
###########################
## Create Yield Storage
hist.GetYaxis().SetTitle("Relative uncertainty")
hist.GetYaxis().SetTitleSize(0.04)
hist.GetYaxis().SetTitleOffset(0.8)
#yp.prepKappaHist(hist)
#yp.prepRatio(hist)
# normalize to central value
#hist.Divide(hCentral)
hists.append(hist)
# make stack/total syst hists
#total = yp.getTotal(hists)
stack = yp.getStack(hists)
sqHist = yp.getSquaredSum(hists)
hCentral.GetYaxis().SetTitle("#kappa_{EWK}")
hCentral.GetYaxis().SetTitleSize(0.15)
hCentral.GetYaxis().SetTitleOffset(0.15)
hCentralUncert = yp.getHistWithError(hCentral, sqHist, True)
'''
for bin in range(1,hCentral.GetNbinsX()+1):
print bin
print hCentral.GetBinContent(bin), hCentralUncert.GetBinContent(bin)
print hCentral.GetBinError(bin), hCentralUncert.GetBinError(bin)
'''
#canv = yp.plotHists(var+"_"+samp+"_Syst",[stack,sqHist],[hCentral,hCentralUncert],"TM", 1200, 600, nCols = 5)
canv = yp.plotHists(var + "_" + samp + "_Syst", [stack, sqHist],
# 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 ##
###########################
## Create Yield Storage
hist.GetYaxis().SetTitle("Relative uncertainty")
hist.GetYaxis().SetTitleSize(0.04)
hist.GetYaxis().SetTitleOffset(0.8)
#yp.prepKappaHist(hist)
#yp.prepRatio(hist)
# normalize to central value
#hist.Divide(hCentral)
hists.append(hist)
# make stack/total syst hists
#total = yp.getTotal(hists)
stack = yp.getStack(hists)
sqHist = yp.getSquaredSum(hists)
hCentralUncert = yp.getHistWithError(hCentral, sqHist)
canv = yp.plotHists(var+"_"+samp+"_Syst",[stack,sqHist],[hCentral,hCentralUncert],"TM", 1200, 600)
# canv = yp.plotHists(var+"_"+samp+"_Syst",[sqHist]+hists,[hCentral,hCentralUncert],"TM", 1200, 600)
# canv = yp.plotHists(var+"_"+samp+"_Stat",[stack,sqHist],hCentral,"TM", 1200, 600)
canvs.append(canv)
if not yp._batchMode: raw_input("Enter any key to exit")
# Save canvases
exts = [".pdf",".png",".root"]
#exts = [".pdf"]
#odir = "BinPlots/Syst/Combine/test/allSF_noPU_Wpol/Method1A/"
odir = "BinPlots/Syst/Combine/allSF_noPU_Wpol/Method1A/"
