double compNumEvents_profileLikelihoodUpperLimit(RooDataHist* data, RooAddPdf* pdf_BSM, RooAddPdf* pdf_SM, RooRealVar* norm_AH120)
{
//--- initialize normalization factors for "background" processes
// with values best matching observed distribution of fit variables
pdf_SM->fitTo(*data, RooFit::SumW2Error(false));
//--- initialize RooStats objects
// for performing fit/computing limits via "profile-likelihood" method
RooStats::ProfileLikelihoodCalculator* significanceCalculator = new RooStats::ProfileLikelihoodCalculator(*data, *pdf_BSM, *norm_AH120);
RooStats::LikelihoodInterval* numEvents_AH120interval = significanceCalculator->GetInterval();
double numEvents_AH120_upperLimit = numEvents_AH120interval->UpperLimit(*norm_AH120);
TCanvas* canvas = new TCanvas("canvas", "canvas", 800, 600);
canvas->SetFillColor(10);
canvas->SetLogy();
RooStats::LikelihoodIntervalPlot* likelihood_AH120plot = new RooStats::LikelihoodIntervalPlot(numEvents_AH120interval);
likelihood_AH120plot->Draw();
TF1* likelihood_AH120function = (TF1*)numEvents_AH120interval->GetLikelihoodRatio()->asTF(*norm_AH120)->Clone();
likelihood_AH120function->Draw("same");
canvas->Update();
TString fileName = TString("mssmHiggsLimit").Append("_").Append("profileLikelihood");
canvas->SaveAs(fileName.Append(".png"));
delete canvas;
return numEvents_AH120_upperLimit;
}
void ComputeUpperLimit(RooAbsData *data, RooStats::ModelConfig *model, float &UpperLimit, float &signif, RooRealVar *mu, RooArgSet *nullParams,RooWorkspace *ws,REGION region,const char* tag) {
bool StoreEverything=false; // activate if you want to store frames and all
RooStats::ProfileLikelihoodCalculator *plc = new RooStats::ProfileLikelihoodCalculator(*data, *model);
plc->SetParameters(*mu);
plc->SetNullParameters(*nullParams);
plc->SetTestSize(0.05);
RooStats::LikelihoodInterval *interval = plc->GetInterval();
bool ComputationSuccessful=false;
UpperLimit = interval->UpperLimit(*mu,ComputationSuccessful);
signif = 0.0; // plc->GetHypoTest()->Significance(); // deactivated significance (to make algorithm faster)
if(!ComputationSuccessful) {
cout << "There seems to have been a problem. Returned upper limit is " << UpperLimit << " but it will be set to -999" << endl;
UpperLimit=-999;
signif=-999;
}
if(StoreEverything) {
// Store it all
RooRealVar* minv = (RooRealVar*)model->GetObservables()->first();
minv->setBins(static_cast<int>((minv->getMax()-minv->getMin())/5.));
RooPlot* frameEE = minv->frame(RooFit::Title("ee sample"));
frameEE->GetXaxis()->CenterTitle(1);
frameEE->GetYaxis()->CenterTitle(1);
RooPlot* frameMM = minv->frame(RooFit::Title("mm sample"));
frameMM->GetXaxis()->CenterTitle(1);
frameMM->GetYaxis()->CenterTitle(1);
RooPlot* frameOF = minv->frame(RooFit::Title("OF sample"));
frameOF->GetXaxis()->CenterTitle(1);
frameOF->GetYaxis()->CenterTitle(1);
data->plotOn(frameMM,RooFit::Cut("catCentral==catCentral::MMCentral"));
model->GetPdf()->plotOn(frameMM,RooFit::Slice(*ws->cat("catCentral"), "MMCentral"),RooFit::ProjWData(*data));
data->plotOn(frameEE,RooFit::Cut("catCentral==catCentral::EECentral"));
model->GetPdf()->plotOn(frameEE,RooFit::Slice(*ws->cat("catCentral"), "EECentral"),RooFit::ProjWData(*data));
data->plotOn(frameOF,RooFit::Cut("catCentral==catCentral::OFOSCentral"));
model->GetPdf()->plotOn(frameOF,RooFit::Slice(*ws->cat("catCentral"), "OFOSCentral"),RooFit::ProjWData(*data));
TFile *fout = new TFile("fout.root","UPDATE");
frameMM->Write(Concatenate(Concatenate(data->GetName(),"_MM"),tag),TObject::kOverwrite);
frameEE->Write(Concatenate(Concatenate(data->GetName(),"_EE"),tag),TObject::kOverwrite);
frameOF->Write(Concatenate(Concatenate(data->GetName(),"_OF"),tag),TObject::kOverwrite);
fout->Close();
}
delete plc;
plc=0;
}
