#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/"