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 ## ###########################