void fitM3()
{
// LOAD HISTOGRAMS FROM FILES
/////////////////////////////////
TH1F *hTTjets;
TH1F *hWjets;
TH1F *hM3;
TH1F *hZjets;
TH1F *hQCD;
TH1F *hST_s;
TH1F *hST_t;
TH1F *hST_tW;
// histograms from nonimal sample
///////////
TFile *infile0 = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_TTJets-madgraph_Fall08_all_all.root");
//TFile *infile0 = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_TauolaTTbar.root");
hTTjets = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infile1 = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_WJets_madgraph_Fall08_all.root");
hWjets = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infile1Fast = TFile::Open("nominal_IPsig3_Iso95_Fast/TopAnalysis_Wjets_madgraph_Winter09_v2_all.root");
hWjetsFast = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileZ = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_ZJets_madgraph_Fall08_all.root");
hZjets = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileZFast = TFile::Open("nominal_IPsig3_Iso95_Fast/TopAnalysis_Zjets_madgraph_Winter09_v2_all.root");
hZjetsFast = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileST_s = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_ST_s.root");
hST_s = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileST_t = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_ST_t.root");
hST_t = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileST_tW = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_ST_tW.root");
hST_tW = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileQCD = TFile::Open("nominal_IPsig3_Iso95/TopAnalysis_InclusiveMuPt15_Summer08_all.root");
hQCD = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
// histograms from systematic samples
//////////
TFile *infile0S = TFile::Open("nominal_JESUp/TopAnalysis_TTJets-madgraph_Fall08_all_all.root");
hTTjetsS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infile1S = TFile::Open("nominal_JESUp/TopAnalysis_WJets_madgraph_Fall08_all.root");// from FullSim
hWjetsS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
//TFile *infile1SF = TFile::Open("nominal_JESUp_Fast/TopAnalysis_WJets_madgraph_Fall08_all.root");// from FastSim
//TFile *infile1SF = TFile::Open("nominal_IPsig3_Iso95_Fast/TopAnalysis_Wjets_ScaleUp_madgraph_Winter09_all.root");
TFile *infile1SF = TFile::Open("nominal_IPsig3_Iso95_Fast/TopAnalysis_WJets_Threshold20GeV_madgraph_Winter09_all.root");
hWjetsSFast = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileZS = TFile::Open("nominal_JESUp/TopAnalysis_ZJets_madgraph_Fall08_all.root");// from FullSim
hZjetsS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileZSF = TFile::Open("nominal_JESUp_Fast/TopAnalysis_ZJets_madgraph_Fall08_all.root");// from FullSim
hZjetsSFast = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileST_sS = TFile::Open("nominal_JESUp/TopAnalysis_ST_s.root");
hST_sS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileST_tS = TFile::Open("nominal_JESUp/TopAnalysis_ST_t.root");
hST_tS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileST_tWS = TFile::Open("nominal_JESUp/TopAnalysis_ST_tW.root");
hST_tWS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
TFile *infileQCDS = TFile::Open("nominal_JESUp/TopAnalysis_InclusiveMuPt15_Summer08_all.root");//
hQCDS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
//TFile *infileQCD_CS = TFile::Open("nominal_antiMuon/TopAnalysis_InclusiveMuPt15_Summer08_all.root");
//hQCD_CS = (TH1F*) gDirectory->Get("Mass/HadronicTop_mass_cut1");
// write templates to file
//TFile *outfile = TFile::Open("templates.root","RECREATE");
//hTTjets->Write("ttbar");
//hWjets->Write("Wjets");
//outfile->Close();
// Add over/underflow bins if requested
bool UseOverflow = true;
bool UseUnderflow = true;
if (UseOverflow) {
int maxbin=hTTjets->GetNbinsX();
hTTjets->SetBinContent(maxbin, hTTjets->GetBinContent(maxbin+1)+hTTjets->GetBinContent(maxbin) );
hWjets->SetBinContent(maxbin, hWjets->GetBinContent(maxbin+1)+hWjets->GetBinContent(maxbin) );
hWjetsFast->SetBinContent(maxbin, hWjetsFast->GetBinContent(maxbin+1)+hWjetsFast->GetBinContent(maxbin) );
hZjets->SetBinContent(maxbin, hZjets->GetBinContent(maxbin+1)+hZjets->GetBinContent(maxbin) );
hZjetsFast->SetBinContent(maxbin, hZjetsFast->GetBinContent(maxbin+1)+hZjetsFast->GetBinContent(maxbin) );
hQCD->SetBinContent(maxbin, hQCD->GetBinContent(maxbin+1)+hQCD->GetBinContent(maxbin) );
//hQCD_CS->SetBinContent(maxbin, hQCD_CS->GetBinContent(maxbin+1)+hQCD_CS->GetBinContent(maxbin) );
hST_s->SetBinContent(maxbin, hST_s->GetBinContent(maxbin+1)+hST_s->GetBinContent(maxbin) );
hST_t->SetBinContent(maxbin, hST_t->GetBinContent(maxbin+1)+hST_t->GetBinContent(maxbin) );
hST_tW->SetBinContent(maxbin, hST_tW->GetBinContent(maxbin+1)+hST_tW->GetBinContent(maxbin) );
}
//underflow bin
if (UseUnderflow) {
int maxbin=1;
hTTjets->SetBinContent(maxbin, hTTjets->GetBinContent(maxbin-1)+hTTjets->GetBinContent(maxbin) );
hWjets->SetBinContent(maxbin, hWjets->GetBinContent(maxbin-1)+hWjets->GetBinContent(maxbin) );
hWjetsFast->SetBinContent(maxbin, hWjetsFast->GetBinContent(maxbin-1)+hWjetsFast->GetBinContent(maxbin) );
hZjets->SetBinContent(maxbin, hZjets->GetBinContent(maxbin-1)+hZjets->GetBinContent(maxbin) );
hZjetsFast->SetBinContent(maxbin, hZjetsFast->GetBinContent(maxbin-1)+hZjetsFast->GetBinContent(maxbin) );
hQCD->SetBinContent(maxbin, hQCD->GetBinContent(maxbin-1)+hQCD->GetBinContent(maxbin) );
//hQCD_CS->SetBinContent(maxbin, hQCD_CS->GetBinContent(maxbin-1)+hQCD_CS->GetBinContent(maxbin) );
hST_s->SetBinContent(maxbin, hST_s->GetBinContent(maxbin-1)+hST_s->GetBinContent(maxbin) );
hST_t->SetBinContent(maxbin, hST_t->GetBinContent(maxbin-1)+hST_t->GetBinContent(maxbin) );
hST_tW->SetBinContent(maxbin, hST_tW->GetBinContent(maxbin-1)+hST_tW->GetBinContent(maxbin) );
}
//syst.
if (UseOverflow) {
int maxbin=hTTjetsS->GetNbinsX();
hTTjetsS->SetBinContent(maxbin, hTTjetsS->GetBinContent(maxbin+1)+hTTjetsS->GetBinContent(maxbin) );
hWjetsS->SetBinContent(maxbin, hWjetsS->GetBinContent(maxbin+1)+hWjetsS->GetBinContent(maxbin) );
hWjetsSFast->SetBinContent(maxbin, hWjetsSFast->GetBinContent(maxbin+1)+hWjetsSFast->GetBinContent(maxbin) );
hZjetsS->SetBinContent(maxbin, hZjetsS->GetBinContent(maxbin+1)+hZjetsS->GetBinContent(maxbin) );
hZjetsSFast->SetBinContent(maxbin, hZjetsSFast->GetBinContent(maxbin+1)+hZjetsSFast->GetBinContent(maxbin) );
hQCDS->SetBinContent(maxbin, hQCDS->GetBinContent(maxbin+1)+hQCDS->GetBinContent(maxbin) );
hST_sS->SetBinContent(maxbin, hST_sS->GetBinContent(maxbin+1)+hST_sS->GetBinContent(maxbin) );
hST_tS->SetBinContent(maxbin, hST_tS->GetBinContent(maxbin+1)+hST_tS->GetBinContent(maxbin) );
hST_tWS->SetBinContent(maxbin, hST_tWS->GetBinContent(maxbin+1)+hST_tWS->GetBinContent(maxbin) );
}
if (UseUnderflow) {
//underflow bin
int maxbin=1;
hTTjetsS->SetBinContent(maxbin, hTTjetsS->GetBinContent(maxbin-1)+hTTjetsS->GetBinContent(maxbin) );
hWjetsS->SetBinContent(maxbin, hWjetsS->GetBinContent(maxbin-1)+hWjetsS->GetBinContent(maxbin) );
hWjetsSFast->SetBinContent(maxbin, hWjetsSFast->GetBinContent(maxbin-1)+hWjetsSFast->GetBinContent(maxbin) );
hZjetsS->SetBinContent(maxbin, hZjetsS->GetBinContent(maxbin-1)+hZjetsS->GetBinContent(maxbin) );
hZjetsSFast->SetBinContent(maxbin, hZjetsSFast->GetBinContent(maxbin-1)+hZjetsSFast->GetBinContent(maxbin) );
hQCDS->SetBinContent(maxbin, hQCDS->GetBinContent(maxbin-1)+hQCDS->GetBinContent(maxbin) );
hST_sS->SetBinContent(maxbin, hST_sS->GetBinContent(maxbin-1)+hST_sS->GetBinContent(maxbin) );
hST_tS->SetBinContent(maxbin, hST_tS->GetBinContent(maxbin-1)+hST_tS->GetBinContent(maxbin) );
hST_tWS->SetBinContent(maxbin, hST_tWS->GetBinContent(maxbin-1)+hST_tWS->GetBinContent(maxbin) );
}
// scale histograms to 20/pb
hTTjets->Scale(0.0081); // madgraph
//hTTjets->Scale(0.0777);//Tauola
hWjets->Scale(0.0883);
//hWjetsFast->Scale(0.0091); //fastsim
hWjetsFast->Scale(hWjets->Integral() / hWjetsFast->Integral()); // scale to FullSim
hZjets->Scale(0.0731);
hZjetsFast->Scale(hZjets->Integral()/hZjetsFast->Integral()); //scale to FullSim
hQCD->Scale(0.4003);
hQCD_WFast = (TH1F*) hWjetsFast->Clone("hQCD_WFast"); //take shape from Wjets
hQCD_WFast->Scale(hQCD->Integral()/hQCD_WFast->Integral()); //scale to FullSim
hST_t->Scale(0.003);
hST_s->Scale(0.0027);
hST_tW->Scale(0.0034);
hTTjetsS->Scale(0.0081); //
//hTTjetsS->Scale(0.0008); // for fastsim
hWjetsS->Scale(0.0883);
//hWjetsS->Scale(0.0091);// from fastsim
//hWjetsSFast->Scale(hWjetsS->Integral() / hWjetsSFast->Integral()); // scale to FullSim
//hWjetsSFast->Scale(0.6642); // scaleUP
//hWjetsSFast->Scale(0.8041); // scaleDown
//hWjetsSFast->Scale(0.0605); // threshold 5gev
hWjetsSFast->Scale(0.042); // threshold 20gev
hZjetsS->Scale(0.0731);
//hZjetsS->Scale(0.0085);// from fastsim
hZjetsSFast->Scale(hZjetsS->Integral() / hZjetsSFast->Integral()); // scale to FullSim
hQCDS->Scale(0.4003);
//hQCDS_WFast = (TH1F*) hWjetsS->Clone("hQCDS_WFast");
//hQCDS_WFast->Scale(hQCDS->Integral()/hQCDS_WFast->Integral());
hST_tS->Scale(0.003);
hST_sS->Scale(0.0027);
hST_tWS->Scale(0.0034);
cout << " N expected ttbar+jets events = " << hTTjets->Integral() << endl;
cout << " N expected W+jets events = " << hWjets->Integral() << endl;
cout << " N expected Z+jets events = " << hZjets->Integral() << endl;
cout << " N expected ST s events = " << hST_s->Integral() << endl;
cout << " N expected ST t events = " << hST_t->Integral() << endl;
cout << " N expected ST tW events = " << hST_tW->Integral() << endl;
cout << " N expected qcd events = " << hQCD->Integral() << endl;
cout << endl;
cout << " N expected W+jets fast = " << hWjetsFast->Integral() << endl;
cout << " N expected z+jets fast = " << hZjetsFast->Integral() << endl;
cout << " N expected qcd Wfast = " << hQCD_WFast->Integral() << endl;
cout << "\n systematics: " << endl;
cout << " N expected W+jets fast = " << hWjetsSFast->Integral() << endl;
cout << " N expected z+jets fast = " << hZjetsS->Integral() << endl;
cout << " N expected qcd Wfast = " << hQCDS->Integral() << endl;
// add all three single top samples
// for systematics
//hST_t->Scale(2.);
hST_t->Add(hST_s);
hST_t->Add(hST_tW);
cout << " number of ST = " << hST_t->Integral() << endl;
// syst. uncertainty in single top
//double tmpST = 0.6* hST_t->Integral();
//hST_t->Scale(0.6);
//cout << tmpST << endl;
cout << " New number of ST = " << hST_t->Integral() << endl;
hST_tS->Add(hST_sS);
hST_tS->Add(hST_tWS);
// dump scaled histograms in root file
//TFile *output = TFile::Open("fitM3.root","RECREATE");
//hTTjets->SetName("ttbar");hTTjets->Write();
//hWjetsFast->SetName("WjetsFast");hWjetsFast->Write();
//hST_t->SetName("ST");hST_t->Write();
//output->Close();
hM3 = (TH1F*) hTTjets->Clone("hM3");
hM3->Add(hWjets);
hM3->Add(hZjets);
hM3->Add(hQCD);
hM3->Add(hST_t);
int Nbins = hM3->GetNbinsX();
// --- Observable ---
RooRealVar mass("mass","M3'(#chi^{2})",100,500,"GeV/c^{2}") ;
RooRealVar Ntt("Ntt","number of t#bar{t} events", hTTjets->Integral(), -100 , 1000);
RooRealVar NW("NW","number of W+jets events", hWjetsFast->Integral(), -500 , 1000);
RooRealVar NST("NST","number of single top events", hST_t->Integral(), -500,100);
RooRealVar NZjets("NZjets","number of Z+jets events", hZjetsS->Integral(), -500,500);
RooRealVar Nqcd("Nqcd","number of QCD events", hQCD_WFast->Integral(), -500,100);
//RooRealVar Nbkg("Nbkg","number of bkg events", hWjetsFast->Integral()+hST_t->Integral()+hZjetsFast->Integral()+hQCD_WFast->Integral(), -500 , 1000);
//RooRealVar Nbkg("Nbkg","number of W+jets events", hWjets->Integral(), -500 , 1000); // 2 templates
RooRealVar Nbkg("Nbkg","number of bkg events", hWjetsFast->Integral()+hZjets->Integral()+hQCD_WFast->Integral(), -500 , 1000);
//RooRealVar Nbkg("Nbkg","number of bkg events", hWjetsFast->Integral(), -500 , 1000);
// for systematics
//RooRealVar Nbkg("Nbkg","number of bkg events", hWjetsSFast->Integral()+hZjetsS->Integral()+hQCDS->Integral(), -500 , 1000);
//RooRealVar Nbkg("Nbkg","number of bkg events", hWjetsSFast->Integral(), -500 , 1000);
mass.setBins(Nbins);
// RooFit datasets
RooDataHist hdata_ttbar("hdata_ttbar","ttbar", mass, hTTjets);
//RooDataHist hdata_wjets("hdata_wjets","wjets", mass, hWjets);
RooDataHist hdata_wjetsFast("hdata_wjetsFast","wjets_Fast", mass, hWjetsFast);
RooDataHist hdata_ST("hdata_ST","ST", mass, hST_t);
RooDataHist hdata_zjets("hdata_zjets","zjets", mass, hZjets);
//RooDataHist hdata_qcd("hdata_qcd","qcd", mass, hQCD);
RooDataHist hdata_zjetsFast("hdata_zjetsFast","zjets_Fast", mass, hZjetsFast);
RooDataHist hdata_qcdWFast("hdata_qcdWFast","qcd WFast", mass, hQCD_WFast);
RooHistPdf hpdf_ttbar("hpdf_ttbar","signal pdf", mass, hdata_ttbar, 0 );
//RooHistPdf hpdf_wjets("hpdf_wjets","W+jets pdf", mass, hdata_wjets, 0 );
RooHistPdf hpdf_wjetsFast("hpdf_wjetsFast","W+jets pdf", mass, hdata_wjetsFast, 0 );
RooHistPdf hpdf_ST("hpdf_ST","ST pdf", mass, hdata_ST, 0 );
//RooHistPdf hpdf_zjets("hpdf_zjets","Z+jets pdf", mass, hdata_zjets, 0 );
//RooHistPdf hpdf_qcd("hpdf_qcd","qcd pdf", mass, hdata_qcd, 0 );
RooHistPdf hpdf_zjetsFast("hpdf_zjetsFast","Z+jets pdf", mass, hdata_zjetsFast, 0 );
RooHistPdf hpdf_qcdWFast("hpdf_qcdWFast","qcd WFast pdf", mass, hdata_qcdWFast, 0 );
// for systematics
RooDataHist hdata_ttbarS("hdata_ttbarS","ttbar", mass, hTTjetsS);
RooDataHist hdata_wjetsS("hdata_wjetsS","wjets", mass, hWjetsSFast);
RooDataHist hdata_STS("hdata_STS","ST", mass, hST_tS);
RooDataHist hdata_zjetsS("hdata_zjetsS","zjets", mass, hZjetsSFast);
RooDataHist hdata_qcdS("hdata_qcdS","qcd", mass, hQCDS);
//RooDataHist hdata_qcdSWFast("hdata_qcdSWFast","qcd WFast", mass, hQCDS_WFast);
RooHistPdf hpdf_ttbarS("hpdf_ttbarS","signal pdf", mass, hdata_ttbarS, 0 );
RooHistPdf hpdf_wjetsS("hpdf_wjetsS","W+jets pdf", mass, hdata_wjetsS, 0 );
RooHistPdf hpdf_STS("hpdf_STS","ST pdf", mass, hdata_STS, 0 );
RooHistPdf hpdf_zjetsS("hpdf_zjetsS","Z+jets pdf", mass, hdata_zjetsS, 0 );
RooHistPdf hpdf_qcdS("hpdf_qcdS","qcd pdf", mass, hdata_qcdS, 0 );
//RooHistPdf hpdf_qcdSWFast("hpdf_qcdSWFast","qcd WFast pdf", mass, hdata_qcdSWFast, 0 );
//RooAddPdf hpdf_bkg("hpdf_bkg","bkg", RooArgList(hpdf_wjetsFast,hpdf_ST,hpdf_qcdWFast),
// RooArgList(NW,NST,Nqcd) );
//RooAddPdf hpdf_bkg("hpdf_bkg","bkg", RooArgList(hpdf_wjetsFast,hpdf_ST,hpdf_zjetsFast,hpdf_qcdWFast),
//RooAddPdf hpdf_bkg("hpdf_bkg","bkg", RooArgList(hpdf_wjetsS,hpdf_STS,hpdf_zjetsS,hpdf_qcdSWFast),
//RooArgList(NW,NST,NZjets,Nqcd) );
// only two pdfs: ttbar + Wjets
//RooHistPdf hpdf_bkg = hpdf_wjetsFast;
//RooAddPdf model_M3("modelM3","all", RooArgList(hpdf_ttbar,hpdf_wjetsFast,hpdf_ST,hpdf_zjetsFast,hpdf_qcdWFast),
// RooArgList(Ntt,Nbkg,NST,NZjets,Nqcd));
// for systematics
RooAddPdf model_M3("modelM3","all", RooArgList(hpdf_ttbar,hpdf_wjetsFast,hpdf_ST),//RooArgList(hpdf_ttbar,hpdf_wjetsS,hpdf_ST),
RooArgList(Ntt,Nbkg,NST) );
//RooAddPdf model_M3("modelM3","all",RooArgList(hpdf_ttbar,hpdf_bkg),
// RooArgList(Ntt,Nbkg) );
//RooArgList(Ntt,Nbkg,NST,Nqcd) );
RooAddPdf model_histpdf("model", "TTjets+Wjets", RooArgList(hpdf_ttbar,hpdf_wjetsFast,hpdf_ST),
RooArgList(Ntt, Nbkg, NST) ) ;
// Construct another Gaussian constraint p.d.f on parameter f at n with resolution of sqrt(n)
RooGaussian STgaussConstraint("STgaussConstraint","STgaussConstraint",NST,RooConst(hST_t->Integral()),RooConst(sqrt(hST_t->Integral() + (0.3*hST_t->Integral())*(0.3*hST_t->Integral()))) );
//RooGaussian fconstext2("fconstext2","fconstext2",NZjets,RooConst(hZjets->Integral()),RooConst(sqrt(hZjets->Integral())) );
// --- Generate a toyMC sample
//RooMCStudy *mcstudyM3 = new RooMCStudy(model_M3, mass, Binned(kTRUE),Silence(),Extended(),
// FitOptions(Save(kTRUE),Minos(kTRUE),Extended(), ExternalConstraints(fconstext)) );
// generate PEs
int Nsamples = 1000;
// PEs for ttbar
/*
RooExtendPdf ext_hpdf_ttbar("ext_hpdf_ttbar","ext_hpdf_ttbar",hpdf_ttbar,Ntt);
RooExtendPdf ext_hpdf_wjets("ext_hpdf_wjets","ext_hpdf_wjets",hpdf_wjetsFast,NW);
RooExtendPdf ext_hpdf_zjets("ext_hpdf_zjets","ext_hpdf_zjets",hpdf_zjetsFast,NZjets);
RooExtendPdf ext_hpdf_qcd("ext_hpdf_qcd","ext_hpdf_qcd",hpdf_qcdWFast,Nqcd);
RooExtendPdf ext_hpdf_ST("ext_hpdf_ST","ext_hpdf_ST",hpdf_ST,NST);
RooMCStudy *mc_ttbar = new RooMCStudy(ext_hpdf_ttbar,mass,Binned(kTRUE),Silence(kTRUE));
mc_ttbar->generate(Nsamples,0,kFALSE,"data/toymc_ttbar_%04d.dat");
RooMCStudy *mc_wjets = new RooMCStudy(ext_hpdf_wjets,mass,Binned(kTRUE),Silence(kTRUE));
mc_wjets->generate(Nsamples,0,kFALSE,"data/toymc_wjets_%04d.dat");
RooMCStudy *mc_zjets = new RooMCStudy(ext_hpdf_zjets,mass,Binned(kTRUE),Silence(kTRUE));
mc_zjets->generate(Nsamples,0,kFALSE,"data/toymc_zjets_%04d.dat");
RooMCStudy *mc_qcd = new RooMCStudy(ext_hpdf_qcd,mass,Binned(kTRUE),Silence(kTRUE));
mc_qcd->generate(Nsamples,0,kFALSE,"data/toymc_qcd_%04d.dat");
RooMCStudy *mc_ST = new RooMCStudy(ext_hpdf_ST,mass,Binned(kTRUE),Silence(kTRUE),FitOptions(ExternalConstraints(STgaussConstraint)));
mc_ST->generate(Nsamples,0,kFALSE,"data/toymc_ST_%04d.dat");
return;
*/
RooMCStudy *mcstudy = new RooMCStudy(model_M3, mass, FitModel(model_histpdf),Binned(kTRUE),Silence(kTRUE), Extended() ,
//FitOptions(Save(kTRUE),Minos(kTRUE),Extended()) );
FitOptions(Save(kTRUE),Minos(kTRUE),Extended(),ExternalConstraints(STgaussConstraint)));//RooArgList(fconstext,fconstext2)) )); //gaussian constraint
//mcstudyM3->generate(Nsamples,0,kFALSE,"toymc.dat");
//mcstudyM3->generateAndFit(Nsamples,0,kFALSE,"toymc.dat");
//TList dataList;
//for (int isample=0; isample<Nsamples; ++isample) dataList.Add( mcstudyM3->genData(isample));
// Fit
mcstudy->generateAndFit(Nsamples,0,kTRUE);
//mcstudy->fit(Nsamples, "data/toymc_%04d.dat");
gDirectory->Add(mcstudy) ;
// E x p l o r e r e s u l t s o f s t u d y
// ------------------------------------------------
// Make plots of the distributions of mean, the error on mean and the pull of mean
RooPlot* frame1 = mcstudy->plotParam(Ntt,Bins(40));
RooPlot* frame2 = mcstudy->plotError(Ntt,Bins(40)) ;
RooPlot* frame3 = mcstudy->plotPull(Ntt,Bins(40),FitGauss(kTRUE)) ;
RooPlot* frame1w = mcstudy->plotParam(Nbkg,Bins(40)) ;
RooPlot* frame2w = mcstudy->plotError(Nbkg,Bins(40)) ;
RooPlot* frame3w = mcstudy->plotPull(Nbkg,Bins(40),FitGauss(kTRUE)) ;
RooPlot* frame1st = mcstudy->plotParam(NST,Bins(40)) ;
RooPlot* frame2st = mcstudy->plotError(NST,Bins(40)) ;
//RooPlot* frame3st = mcstudy->plotPull(NST,Bins(40),FitGauss(kTRUE)) ;
// Plot distribution of minimized likelihood
RooPlot* frame4 = mcstudy->plotNLL(Bins(40)) ;
// Make some histograms from the parameter dataset
TH1* hh_cor_ttbar_w = mcstudy->fitParDataSet().createHistogram("hh",Ntt,YVar(Nbkg)) ;
// Access some of the saved fit results from individual toys
//TH2* corrHist000 = mcstudy->fitResult(0)->correlationHist("c000") ;
//TH2* corrHist127 = mcstudy->fitResult(127)->correlationHist("c127") ;
//TH2* corrHist953 = mcstudy->fitResult(953)->correlationHist("c953") ;
// Draw all plots on a canvas
gStyle->SetPalette(1) ;
gStyle->SetOptStat(0) ;
TCanvas* cv = new TCanvas("cv","cv",600,600) ;
hM3->SetFillColor(kRed);
hWjets->SetFillColor(kGreen);
hM3->Draw();
hWjets->Draw("same");
gPad->RedrawAxis();
TCanvas* cva = new TCanvas("cva","cva",1800,600) ;
cva->Divide(3);
cva->cd(1) ;
RooPlot *initialframe = mass.frame();
//initial->SetMaximum(10);
hpdf_ttbar.plotOn(initialframe,LineColor(kRed));
hpdf_wjetsFast.plotOn(initialframe,LineColor(kGreen));
hpdf_ST.plotOn(initialframe,LineColor(kYellow));
initialframe->Draw();
//initialframe->SetTitle();
cva->cd(2);
//retrieve data for only one PE
int Npe = 10;
RooPlot *genframe = mass.frame(Nbins);
RooDataSet *gendata = mcstudy->genData(Npe);
cout << " N events = " << gendata->numEntries() << endl;
gendata->plotOn(genframe);
//mcstudy->fitResult(Npe)->plotOn(genframe, model_histpdf);
genframe->Draw();
cva->cd(3);
RooPlot *genframe2 = mass.frame(Nbins);
mcstudy->fitResult(Npe)->Print("v");
gendata->plotOn(genframe2);
RooArgList arglist = mcstudy->fitResult(Npe)->floatParsFinal();
//cout << "name of argument:" << arglist[2].GetName() << endl;
//cout << "name of argument:" << arglist[1].GetName() << endl;
//cout << "name of argument:" << arglist[0].GetName() << endl;
RooAddPdf model_histpdf_fitted("modelfitted", "TTjets+Wjets", RooArgList(hpdf_ttbar,hpdf_wjetsFast,hpdf_ST),
RooArgList(arglist[2],arglist[1],arglist[0]) ) ;
model_histpdf_fitted.plotOn(genframe2,LineColor(kRed));
model_histpdf_fitted.plotOn(genframe2,Components(hpdf_wjetsFast),LineColor(kGreen));
model_histpdf_fitted.plotOn(genframe2,Components(hpdf_ST),LineColor(kYellow));
genframe2->Draw();
TCanvas* cvb = new TCanvas("cvb","cvb",1800,600) ;
cvb->Divide(3);
cvb->cd(1) ; frame1->Draw();
cvb->cd(2) ; frame2->Draw();
cvb->cd(3) ; frame3->Draw();
TCanvas* cvbb = new TCanvas("cvbb","cvbb",1800,600) ;
cvbb->Divide(3);
cvbb->cd(1) ; frame1w->Draw();
cvbb->cd(2) ; frame2w->Draw();
cvbb->cd(3) ; frame3w->Draw();
TCanvas* cvbbb = new TCanvas("cvbbb","cvbbb",1200,600) ;
cvbbb->Divide(2);
cvbbb->cd(1) ; frame1st->Draw();
cvbbb->cd(2) ; frame2st->Draw();
//cvbbb->cd(3) ; frame3st->Draw();
TCanvas* cvbc = new TCanvas("cvbc","cvbc",600,600) ;
TH2 *h2 = Ntt.createHistogram("Nttbar vs NWjets",Nbkg);
mcstudy->fitParDataSet().fillHistogram(h2,RooArgList(Ntt,Nbkg));
h2->Draw("box");
TCanvas* cvc = new TCanvas("cvc","cvc",600,600) ;
// Plot distribution of minimized likelihood
RooPlot* frame4 = mcstudy->plotNLL(Bins(40)) ;
frame4->Draw();
//return;//debuging
TCanvas* cvd = new TCanvas("cvd","cvd",600,600) ;
TCanvas* cve = new TCanvas("cve","cve",1200,600) ;
TCanvas* cvf = new TCanvas("cvf","cvf",600,600) ;
TH1F *hNgen = new TH1F("hNgen","Number of observed events",30,350,650);
hNgen->SetXTitle("Number of observed events");
TH1F *hNttresults = new TH1F("hNttresults","number of ttbar events",50,20,600);
TH1F *hNWresults = new TH1F("hNWresults","number of W events",50,-150,400);
TH1F *hNSTresults = new TH1F("hNSTresults","number of ttbar events",50,5,25);
bool gotone = false;
int Nfailed = 0;
for ( int i=0; i< Nsamples; i++)
{
RooFitResult *r = mcstudy->fitResult(i);
RooArgList list = r->floatParsFinal();
RooRealVar *rrv_nt = (RooRealVar*)list.at(2);
double nt = rrv_nt->getVal();
//double nte= rrv_nt->getError();
RooRealVar *rrv_nw = (RooRealVar*)list.at(1);
double nw = rrv_nw->getVal();
//double nwe= rrv_nw->getError();
RooRealVar *rrv_nst = (RooRealVar*)list.at(0);
double nst = rrv_nst->getVal();
hNttresults->Fill(nt);
hNWresults->Fill(nw);
hNSTresults->Fill(nst);
RooDataSet *adata = mcstudy->genData(i);
hNgen->Fill(adata->numEntries());
if ( r->numInvalidNLL() > 0 ) Nfailed++;
/*
if ( false ) {
cout << " sample # " << i << endl;
gotone = true;
r->Print("v");
cout << " invalidNLL = "<< r->numInvalidNLL() << endl;
cout << " N events = " << adata->numEntries() << endl;
RooAddPdf amodel("amodel", "TTjets+Wjets", RooArgList(hpdf_ttbar,hpdf_wjets,hpdf_ST),
RooArgList(list[2],list[1],list[0])) ;
RooPlot *d2 = new RooPlot(Ntt,NW,0,500,-200,200);
r->plotOn(d2,Ntt,NW,"ME12ABHV");
cvd->cd();
d2->Draw();
RooNLLVar nll("nll","nll", amodel, *adata, Extended() );//, Extended(), PrintEvalErrors(-1) );
RooMinuit myminuit(nll)
myminuit.migrad();
myminuit.hesse();
myminuit.minos();
//myminuit.Save()->Print("v");
cve->Divide(2);
RooPlot *nllframett = Ntt.frame(Bins(50),Range(100,600));//,Range(10,2000));
nll.plotOn(nllframett);//,ShiftToZero());
RooProfileLL pll_ntt("pll_ntt","pll_ntt",nll,Ntt);
pll_ntt.plotOn(nllframett,LineColor(kRed));
RooPlot *nllframeW = NW.frame(Bins(50),Range(0,250));//,Range(10,2000));
nll.plotOn(nllframeW);//,ShiftToZero());
RooProfileLL pll_nW("pll_nW","pll_nW",nll,NW);
pll_nW.plotOn(nllframeW,LineColor(kRed));
cve->cd(1);
nllframett->SetMaximum(2);
nllframett->Draw();
cve->cd(2);
nllframeW->SetMaximum(2);
nllframeW->Draw();
}
*/
}
TCanvas *tmpcv = new TCanvas("tmpcv","tmpcv",700,700);
cout << "\n ==================================" << endl;
cout << "gaussian fit of Nttbar fitted values: " << endl;
//hNttresults->Print("all");
hNttresults->Fit("gaus");
cout << "\n ==================================" << endl;
cout << "gaussian fit of NW fitted values: " << endl;
//hNWresults->Print("all");
hNWresults->Fit("gaus");
cout << "\n ==================================" << endl;
cout << "gaussian fit of NST fitted values: " << endl;
//hNSTresults->Print("all");
hNSTresults->Fit("gaus");
cout << "N failed fits = " << Nfailed << endl;
cvf->cd();
hNgen->Draw();
// Make RooMCStudy object available on command line after
// macro finishes
//gDirectory->Add(mcstudy) ;
}
void rf803_mcstudy_addons2()
{
// C r e a t e m o d e l
// -----------------------
// Simulation of signal and background of top quark decaying into
// 3 jets with background
// Observable
RooRealVar mjjj("mjjj","m(3jet) (GeV)",100,85.,350.) ;
// Signal component (Gaussian)
RooRealVar mtop("mtop","m(top)",162) ;
RooRealVar wtop("wtop","m(top) resolution",15.2) ;
RooGaussian sig("sig","top signal",mjjj,mtop,wtop) ;
// Background component (Chebychev)
RooRealVar c0("c0","Chebychev coefficient 0",-0.846,-1.,1.) ;
RooRealVar c1("c1","Chebychev coefficient 1", 0.112,-1.,1.) ;
RooRealVar c2("c2","Chebychev coefficient 2", 0.076,-1.,1.) ;
RooChebychev bkg("bkg","combinatorial background",mjjj,RooArgList(c0,c1,c2)) ;
// Composite model
RooRealVar nsig("nsig","number of signal events",53,0,1e3) ;
RooRealVar nbkg("nbkg","number of background events",103,0,5e3) ;
RooAddPdf model("model","model",RooArgList(sig,bkg),RooArgList(nsig,nbkg)) ;
// C r e a t e m a n a g e r
// ---------------------------
// Configure manager to perform binned extended likelihood fits (Binned(),Extended()) on data generated
// with a Poisson fluctuation on Nobs (Extended())
RooMCStudy* mcs = new RooMCStudy(model,mjjj,Binned(),Silence(),Extended(kTRUE),
FitOptions(Extended(kTRUE),PrintEvalErrors(-1))) ;
// C u s t o m i z e m a n a g e r
// ---------------------------------
// Add module that randomizes the summed value of nsig+nbkg
// sampling from a uniform distribution between 0 and 1000
//
// In general one can randomize a single parameter, or a
// sum of N parameters, using either a uniform or a Gaussian
// distribution. Multiple randomization can be executed
// by a single randomizer module
RooRandomizeParamMCSModule randModule ;
randModule.sampleSumUniform(RooArgSet(nsig,nbkg),50,500) ;
mcs->addModule(randModule) ;
// Add profile likelihood calculation of significance. Redo each
// fit while keeping parameter nsig fixed to zero. For each toy,
// the difference in -log(L) of both fits is stored, as well
// a simple significance interpretation of the delta(-logL)
// using Dnll = 0.5 sigma^2
RooDLLSignificanceMCSModule sigModule(nsig,0) ;
mcs->addModule(sigModule) ;
// R u n m a n a g e r , m a k e p l o t s
// ---------------------------------------------
// Run 1000 experiments. This configuration will generate a fair number
// of (harmless) MINUIT warnings due to the instability of the Chebychev polynomial fit
// at low statistics.
mcs->generateAndFit(500) ;
// Make some plots
TH1* dll_vs_ngen = mcs->fitParDataSet().createHistogram("ngen,dll_nullhypo_nsig",-40,-40) ;
TH1* z_vs_ngen = mcs->fitParDataSet().createHistogram("ngen,significance_nullhypo_nsig",-40,-40) ;
TH1* errnsig_vs_ngen = mcs->fitParDataSet().createHistogram("ngen,nsigerr",-40,-40) ;
TH1* errnsig_vs_nsig = mcs->fitParDataSet().createHistogram("nsig,nsigerr",-40,-40) ;
// Draw plots on canvas
TCanvas* c = new TCanvas("rf803_mcstudy_addons2","rf802_mcstudy_addons2",800,800) ;
c->Divide(2,2) ;
c->cd(1) ; gPad->SetLeftMargin(0.15) ; dll_vs_ngen->GetYaxis()->SetTitleOffset(1.6) ; dll_vs_ngen->Draw("box") ;
c->cd(2) ; gPad->SetLeftMargin(0.15) ; z_vs_ngen->GetYaxis()->SetTitleOffset(1.6) ; z_vs_ngen->Draw("box") ;
c->cd(3) ; gPad->SetLeftMargin(0.15) ; errnsig_vs_ngen->GetYaxis()->SetTitleOffset(1.6) ; errnsig_vs_ngen->Draw("box") ;
c->cd(4) ; gPad->SetLeftMargin(0.15) ; errnsig_vs_nsig->GetYaxis()->SetTitleOffset(1.6) ; errnsig_vs_nsig->Draw("box") ;
// Make RooMCStudy object available on command line after
// macro finishes
gDirectory->Add(mcs) ;
}
void rf802_mcstudy_addons()
{
// C r e a t e m o d e l
// -----------------------
// Observables, parameters
RooRealVar x("x","x",-10,10) ;
x.setBins(10) ;
RooRealVar mean("mean","mean of gaussian",0) ;
RooRealVar sigma("sigma","width of gaussian",5,1,10) ;
// Create Gaussian pdf
RooGaussian gauss("gauss","gaussian PDF",x,mean,sigma) ;
// C r e a t e m a n a g e r w i t h c h i ^ 2 a d d - o n m o d u l e
// ----------------------------------------------------------------------------
// Create study manager for binned likelihood fits of a Gaussian pdf in 10 bins
RooMCStudy* mcs = new RooMCStudy(gauss,x,Silence(),Binned()) ;
// Add chi^2 calculator module to mcs
RooChi2MCSModule chi2mod ;
mcs->addModule(chi2mod) ;
// Generate 1000 samples of 1000 events
mcs->generateAndFit(2000,1000) ;
// Fill histograms with distributions chi2 and prob(chi2,ndf) that
// are calculated by RooChiMCSModule
TH1* hist_chi2 = mcs->fitParDataSet().createHistogram("chi2") ;
TH1* hist_prob = mcs->fitParDataSet().createHistogram("prob") ;
// C r e a t e m a n a g e r w i t h s e p a r a t e f i t m o d e l
// ----------------------------------------------------------------------------
// Create alternate pdf with shifted mean
RooRealVar mean2("mean2","mean of gaussian 2",0.5) ;
RooGaussian gauss2("gauss2","gaussian PDF2",x,mean2,sigma) ;
// Create study manager with separate generation and fit model. This configuration
// is set up to generate bad fits as the fit and generator model have different means
// and the mean parameter is not floating in the fit
RooMCStudy* mcs2 = new RooMCStudy(gauss2,x,FitModel(gauss),Silence(),Binned()) ;
// Add chi^2 calculator module to mcs
RooChi2MCSModule chi2mod2 ;
mcs2->addModule(chi2mod2) ;
// Generate 1000 samples of 1000 events
mcs2->generateAndFit(2000,1000) ;
// Fill histograms with distributions chi2 and prob(chi2,ndf) that
// are calculated by RooChiMCSModule
TH1* hist2_chi2 = mcs2->fitParDataSet().createHistogram("chi2") ;
TH1* hist2_prob = mcs2->fitParDataSet().createHistogram("prob") ;
hist2_chi2->SetLineColor(kRed) ;
hist2_prob->SetLineColor(kRed) ;
TCanvas* c = new TCanvas("rf802_mcstudy_addons","rf802_mcstudy_addons",800,400) ;
c->Divide(2) ;
c->cd(1) ; gPad->SetLeftMargin(0.15) ; hist_chi2->GetYaxis()->SetTitleOffset(1.4) ; hist_chi2->Draw() ; hist2_chi2->Draw("esame") ;
c->cd(2) ; gPad->SetLeftMargin(0.15) ; hist_prob->GetYaxis()->SetTitleOffset(1.4) ; hist_prob->Draw() ; hist2_prob->Draw("esame") ;
// Make RooMCStudy object available on command line after
// macro finishes
gDirectory->Add(mcs) ;
}
