task_4_3.C

#include "common.h"

void task_4_3()
{

    using namespace RooFit;   

    unsigned int cate = 0;
    double bdt_min = 0.8;
    
    RooRealVar m("m","",4.9,5.9);
    RooDataSet *rds = new RooDataSet("rds","",RooArgSet(m));
    
    TFile *fin = new TFile("/eos/uscms/store/user/cmsdas/2025/long_exercises/long-ex-bs-mumu/bsmmMc.root");
    TTree *tin = (TTree*)fin->Get("bsmmMc");
        
    unsigned int cate_t;
    float m_t,bdt_t;
    tin->SetBranchAddress("cate",&cate_t);
    tin->SetBranchAddress("m",&m_t);
    tin->SetBranchAddress("bdt",&bdt_t);
    
    int evtcount[2] = {0,0};
    for(int evt=0; evt<tin->GetEntries(); evt++) {
        tin->GetEntry(evt);
        if (cate_t!=cate) continue;
        evtcount[0]++;
        if (bdt_t<=bdt_min) continue;
        evtcount[1]++;
        m.setVal(m_t);
        rds->add(RooArgSet(m));
    }

    double eff = (double)evtcount[1]/(double)evtcount[0] * effyield[cate][Eff_bsmmMc];
    double eff_error = effyield[cate][dEff_bsmmMc]/effyield[cate][Eff_bsmmMc]*eff; // ignore MC statistical error
    delete fin;
    
    RooRealVar bs_mean1("bs_mean1","",5.37,5.2,5.5);
    RooRealVar bs_mean2("bs_mean2","",5.37,5.2,5.5);
    RooRealVar bs_sigma1("bs_sigma1","",0.030,0.005,0.060);
    RooRealVar bs_sigma2("bs_sigma2","",0.080,0.040,0.200);
    RooRealVar bs_cbalpha("bs_cbalpha","",1.,0.,4.);
    RooRealVar bs_cbn("bs_cbn","",1.,0.,4.);
    RooRealVar bs_frac("bs_frac","",0.7,0.,1.);
    RooGaussian bs_gaus("bs_gaus", "", m, bs_mean1, bs_sigma1);
    RooCBShape bs_cbline("bs_cbline", "", m, bs_mean2, bs_sigma2, bs_cbalpha, bs_cbn);
    RooAddPdf pdf("pdf","",RooArgList(bs_gaus,bs_cbline),RooArgList(bs_frac));
    pdf.fitTo(*rds);
    
    RooPlot *frame = m.frame(Title(" "),Bins(100));
    rds->plotOn(frame, Name("t_rds"));
    pdf.plotOn(frame, Name("t_pdf"), LineWidth(3));
    
    TCanvas* canvas = new TCanvas("canvas", "", 600, 600);
    canvas->SetMargin(0.15,0.06,0.13,0.07);
    
    frame->GetYaxis()->SetTitleOffset(1.50);
    frame->GetYaxis()->SetTitle("Entries / 0.01 GeV");
    frame->GetXaxis()->SetTitleOffset(1.15);
    frame->GetXaxis()->SetLabelOffset(0.01);
    frame->GetXaxis()->SetTitle("M(#mu#mu) [GeV]");
    frame->GetXaxis()->SetTitleSize(0.043);
    frame->GetYaxis()->SetTitleSize(0.043);
    frame->Draw();
    
    TLegend* leg = new TLegend(0.58,0.77,0.93,0.92);
    leg->SetFillStyle(0);
    leg->SetLineWidth(0);
    leg->SetHeader(Form("Category %d",cate));
    leg->AddEntry(frame->findObject("t_rds"),"Simluation","EP");
    leg->AddEntry(frame->findObject("t_pdf"),"PDF","L");
    leg->Draw();
    
    canvas->Print("task_4_3.pdf");
    canvas->Print("task_4_3.png");
    
    cout << "Category: " << cate << endl;
    cout << "BDT min: " << bdt_min << endl;
    cout << "Selection efficiency: " << eff << " +- " << eff_error << endl;
}