bkgmodel=RooAddPdf("bkgmodel"+name,"bkg",RooArgList(bkg),RooArgList(nbkg))
bkgmodel.fitTo(data,RooFit.SumW2Error(True))
bkgmodel.fitTo(data,RooFit.SumW2Error(True))
bkgmodel.fitTo(data,RooFit.SumW2Error(True))
chi2=RooChi2Var("chi2","chi2",bkgmodel,data,RooFit.DataError(RooAbsData.SumW2))
nbins=data.numEntries()
nfree=bkgmodel.getParameters(data).selectByAttrib("Constant",False).getSize()
xframe=mass.frame(RooFit.Title(" #chi^{2}/N="+str(int((chi2.getVal()/(nbins-nfree))*10.)/10.)))
data.plotOn(xframe,RooFit.DataError(RooAbsData.SumW2),RooFit.MarkerSize(1))
bkgmodel.plotOn(xframe,RooFit.Normalization(1.0,RooAbsReal.RelativeExpected))
canvas=TCanvas("c4","c4",0,0,600,600)
xframe.GetYaxis().SetTitle("Events")
xframe.Draw()
canvas.SaveAs(prefix+"_"+plot[0]+name+"_bkgfit.pdf")
print "generating pseudodata", nbkg.getValV()+nsigref.getValV()
pseudodata[name]=model.generateBinned(RooArgSet(mass),nbkg.getValV()+nsigref.getValV())
datalist[name]=data
modellist[name]=model
if fit=="data":
model.fitTo(data)
model.fitTo(data)
model.fitTo(data)
chi2=RooChi2Var("chi2","chi2",model,data)
else:
model.fitTo(data,RooFit.SumW2Error(True))
model.fitTo(data,RooFit.SumW2Error(True))
model.fitTo(data,RooFit.SumW2Error(True))
chi2=RooChi2Var("chi2","chi2",model,data,RooFit.DataError(RooAbsData.SumW2))
nbins=data.numEntries()
nfree=model.getParameters(data).selectByAttrib("Constant",False).getSize()
