int main(int argc, char** argv){
gROOT->SetStyle("Plain");
double fMin , fMax, lumi, scaleLumi =1;
int seed;
Bool_t toy = kFALSE;
Bool_t fitFromData = kFALSE;
string infile, outfile;
int rebinZMuMu =1, rebinZMuSa = 1, rebinZMuTk = 1, rebinZMuMuNoIso=1, rebinZMuMuHlt = 1;
po::options_description desc("Allowed options");
desc.add_options()
("help,h", "produce help message")
("toy,t", "toy enabled")
("seed,s", po::value<int>(&seed)->default_value(34567), "seed value for toy")
("luminosity,l", po::value<double>(&lumi)->default_value(45.), "luminosity value for toy ")
("fit,f", "fit from data enabled")
("rebin,r", po::value< vector<int> > (), "rebin value: r_mutrk r mumuNotIso r_musa r _muhlt")
("input-file,i", po::value< string> (&infile), "input file")
("output-file,o", po::value< string> (&outfile), "output file with fit results")
("min,m", po::value<double>(&fMin)->default_value(60), "minimum value for fit range")
("max,M", po::value<double>(&fMax)->default_value(120), "maximum value for fit range");
po::positional_options_description p;
p.add("rebin", -1);
po::variables_map vm;
po::store(po::command_line_parser(argc, argv).
options(desc).positional(p).run(), vm);
po::notify(vm);
if (vm.count("help")) {
cout << "Usage: options_description [options]\n";
cout << desc;
return 0;
}
if (vm.count("toy")) {
cout << "toy enabled with seed " << seed << "\n";
toy = kTRUE;
//RooRandom::randomGenerator()->SetSeed(seed) ;
// lumi should be intented as pb-1 and passed from outside
scaleLumi= lumi / 45.0 ; // 45 is the current lumi correspondent to the histogram.....
}
if (vm.count("fit")) {
cout << "fit from data enabled \n";
fitFromData = kTRUE;
}
if (!vm.count("toy") && !vm.count("fit")) {
cerr << "Choose one beetween fitting form data or with a toy MC \n";
return 1;
}
if ( toy == fitFromData ){
cerr << "Choose if fit from data or with a toy MC \n";
return 1;
}
if (vm.count("rebin") ) {
vector<int> v_rebin = vm["rebin"].as< vector<int> >();
if (v_rebin.size()!=4){
cerr << " please provide 4 numbers in the given order:r_mutrk r mumuNotIso r_musa r _muhlt \n";
return 1;
}
rebinZMuTk = v_rebin[0]; rebinZMuMuNoIso=v_rebin[1]; rebinZMuSa = v_rebin[2];rebinZMuMuHlt = v_rebin[3];
}
RooRealVar * mass = new RooRealVar("mass", "mass (GeV/c^{2})", fMin, fMax );
TFile * root_file = new TFile(infile.c_str(), "read");
int range = (int)(fMax - fMin);
int numberOfBins = range/rebinZMuSa + range/rebinZMuTk + range/rebinZMuMuNoIso + 2* range/rebinZMuMuHlt ;
// zmm histograms used for pdf
TH1F * zmm = getHisto(root_file, "goodZToMuMuPlots/zMass",fMin, fMax, rebinZMuMu );
// zmsta used for pdf
TH1F *zmsta = getHisto(root_file, "zmumuSaMassHistogram/zMass",fMin, fMax, 1); // histogramms to fit.....
TH1F *zmmsta = getHisto(root_file, "goodZToMuMuOneStandAloneMuonPlots/zMass",fMin, fMax, rebinZMuSa/rebinZMuMu);
TH1F *zmt = getHisto(root_file, "goodZToMuMuOneTrackPlots/zMass", fMin, fMax, rebinZMuTk / rebinZMuMu);
TH1F *zmmNotIso = getHisto(root_file,"nonIsolatedZToMuMuPlots/zMass", fMin, fMax, rebinZMuMuNoIso / rebinZMuMu);
TH1F *zmm1hlt = getHisto(root_file, "goodZToMuMu1HLTPlots/zMass", fMin, fMax, rebinZMuMuHlt / rebinZMuMu);
TH1F *zmm2hlt = getHisto(root_file, "goodZToMuMu2HLTPlots/zMass", fMin, fMax, rebinZMuMuHlt / rebinZMuMu);
// creating a pdf for Zmt
RooHistPdf * ZmtPdf = createHistPdf( "ZmtPdf", zmm, mass, rebinZMuTk/ rebinZMuMu );
// creating a pdf for Zmm not iso
RooHistPdf * ZmmNoIsoPdf = createHistPdf( "ZmmNoIsoPdf", zmm, mass, rebinZMuMuNoIso/ rebinZMuMu );
// creating a pdf for Zms from zmsta!!!
RooHistPdf * ZmsPdf = createHistPdf( "ZmsPdf", zmsta, mass, rebinZMuSa/ rebinZMuMu );
// creating a pdf for Zmmhlt
RooHistPdf * ZmmHltPdf = createHistPdf( "ZmmHltPdf", zmm, mass, rebinZMuMuHlt/ rebinZMuMu );
// creating the variable with random init values
RooRealVar Yield("Yield","Yield", 15000.,345.,3567890.) ;
RooRealVar nbkg_mutrk("nbkg_mutrk","background _mutrk fraction",500,0.,100000.) ;
RooRealVar nbkg_mumuNotIso("nbkg_mumuNotIso","background fraction",500,0.,100000.) ;
RooRealVar nbkg_musa("nbkg_musa","background fraction",50,0.,100000.) ;
RooRealVar eff_tk("eff_tk","signal _mutrk fraction",.99,0.8,1.0) ;
RooRealVar eff_sa("eff_sa","eff musta",0.99,0.8,1.0) ;
RooRealVar eff_iso("eff_iso","eff mumuNotIso",.99,0.8,1.0) ;
RooRealVar eff_hlt("eff_hlt","eff 1hlt",0.99, 0.8,1.0) ;
RooRealVar alpha ("alpha","coefficient alpha", -0.01 , -1000, 1000.) ;
RooRealVar a0 ("a0","coefficient 0", 1,-1000.,1000.) ;
RooRealVar a1 ("a1","coefficient 1", -0.001,-1000,1000.) ;
RooRealVar a2 ("a2","coefficient 2", 0.0,-1000.,1000.) ;
RooRealVar beta ("beta","coefficient beta", -0.01,-1000 , 1000. ) ;
RooRealVar b0 ("b0","coefficient 0", 1,-1000.,1000.) ;
RooRealVar b1 ("b1","coefficient 1", -0.001,-1000,1000.) ;
RooRealVar b2("b2","coefficient 2", 0.0,-1000.,1000.) ;
RooRealVar gamma ("gamma","coefficient gamma", -0.01,-1000 , 1000. ) ;
RooRealVar c0 ("c0","coefficient 0", 1,-1000.,1000.) ;
RooRealVar c1 ("c1","coefficient 1", -0.001,-1000,1000.) ;
// fit parameters setted from datacard
filebuf fb;
fb.open ("zMuMuRooFit.txt",ios::in);
istream is(&fb);
char line[1000];
Yield.readFromStream(is.getline(line, 1000), kFALSE);
nbkg_mutrk.readFromStream(is.getline(line,1000), kFALSE);
nbkg_mumuNotIso.readFromStream(is.getline(line,1000), kFALSE);
nbkg_musa.readFromStream(is.getline(line,1000), kFALSE);
eff_tk.readFromStream(is.getline(line,1000), kFALSE);
eff_sa.readFromStream(is.getline(line,1000), kFALSE);
eff_iso.readFromStream(is.getline(line,1000), kFALSE);
eff_hlt.readFromStream(is.getline(line,1000), kFALSE);
alpha.readFromStream(is.getline(line,1000), kFALSE);
a0.readFromStream(is.getline(line,1000), kFALSE);
a1.readFromStream(is.getline(line,1000), kFALSE );
a2.readFromStream(is.getline(line,1000), kFALSE);
beta.readFromStream(is.getline(line,1000), kFALSE);
b0.readFromStream(is.getline(line,1000), kFALSE);
b1.readFromStream(is.getline(line,1000), kFALSE);
b2.readFromStream(is.getline(line,1000), kFALSE);
gamma.readFromStream(is.getline(line,1000), kFALSE);
c0.readFromStream(is.getline(line,1000), kFALSE);
c1.readFromStream(is.getline(line,1000), kFALSE);
fb.close();
// scaling to lumi if toy is enabled...
if (vm.count("toy")) {
Yield.setVal(scaleLumi * (Yield.getVal()));
nbkg_mutrk.setVal(scaleLumi * (nbkg_mutrk.getVal()));
nbkg_mumuNotIso.setVal(scaleLumi * (nbkg_mumuNotIso.getVal()));
}
//efficiency term
//zMuMuEff1HLTTerm = _2 * (effTk ^ _2) * (effSa ^ _2) * (effIso ^ _2) * effHLT * (_1 - effHLT);
RooFormulaVar zMuMu1HLTEffTerm("zMuMu1HLTEffTerm", "Yield * (2.* (eff_tk)^2 * (eff_sa)^2 * (eff_iso)^2 * eff_hlt *(1.- eff_hlt))",
RooArgList(eff_tk, eff_sa,eff_iso, eff_hlt, Yield)); //zMuMuEff2HLTTerm = (effTk ^ _2) * (effSa ^ _2) * (effIso ^ _2) * (effHLT ^ _2) ;
RooFormulaVar zMuMu2HLTEffTerm("zMuMu2HLTEffTerm", "Yield * ((eff_tk)^2 * (eff_sa)^2 * (eff_iso)^2 * (eff_hlt)^2)",
RooArgList(eff_tk, eff_sa,eff_iso, eff_hlt, Yield));
//zMuMuNoIsoEffTerm = (effTk ^ _2) * (effSa ^ _2) * (_1 - (effIso ^ _2)) * (_1 - ((_1 - effHLT)^_2));
RooFormulaVar zMuMuNoIsoEffTerm("zMuMuNoIsoEffTerm", "Yield * ((eff_tk)^2 * (eff_sa)^2 * (1.- (eff_iso)^2) * (1.- ((1.-eff_hlt)^2)))",
RooArgList(eff_tk, eff_sa,eff_iso, eff_hlt, Yield));
//zMuTkEffTerm = _2 * (effTk ^ _2) * effSa * (_1 - effSa) * (effIso ^ _2) * effHLT;
RooFormulaVar zMuTkEffTerm("zMuTkEffTerm", "Yield * (2. *(eff_tk)^2 * eff_sa * (1.-eff_sa)* (eff_iso)^2 * eff_hlt)",
RooArgList(eff_tk, eff_sa,eff_iso, eff_hlt, Yield));
//zMuSaEffTerm = _2 * (effSa ^ _2) * effTk * (_1 - effTk) * (effIso ^ _2) * effHLT;
RooFormulaVar zMuSaEffTerm("zMuSaEffTerm", "Yield * (2. *(eff_sa)^2 * eff_tk * (1.-eff_tk)* (eff_iso)^2 * eff_hlt)",
RooArgList(eff_tk, eff_sa,eff_iso, eff_hlt, Yield));
// creating model for the fit
// z mu track
RooGenericPdf *bkg_mutrk = new RooGenericPdf("bkg_mutrk","zmt bkg_model", "exp(alpha*mass) * ( a0 + a1 * mass + a2 * mass^2 )", RooArgSet( *mass, alpha, a0, a1,a2) );
// RooFormulaVar fracSigMutrk("fracSigMutrk", "@0 / (@0 + @1)", RooArgList(zMuTkEffTerm, nbkg_mutrk ));
RooAddPdf * model_mutrk= new RooAddPdf("model_mutrk","model_mutrk",RooArgList(*ZmtPdf,*bkg_mutrk),RooArgList(zMuTkEffTerm , nbkg_mutrk)) ;
// z mu mu not Iso
// creating background pdf for zmu mu not Iso
RooGenericPdf *bkg_mumuNotIso = new RooGenericPdf("bkg_mumuNotIso","zmumuNotIso bkg_model", "exp(beta * mass) * (b0 + b1 * mass + b2 * mass^2)", RooArgSet( *mass, beta, b0, b1,b2) );
// RooFormulaVar fracSigMuMuNoIso("fracSigMuMuNoIso", "@0 / (@0 + @1)", RooArgList(zMuMuNoIsoEffTerm, nbkg_mumuNotIso ));
RooAddPdf * model_mumuNotIso= new RooAddPdf("model_mumuNotIso","model_mumuNotIso",RooArgList(*ZmmNoIsoPdf,*bkg_mumuNotIso), RooArgList(zMuMuNoIsoEffTerm, nbkg_mumuNotIso));
// z mu sta
// RooGenericPdf model_musta("model_musta", " ZmsPdf * zMuSaEffTerm ", RooArgSet( *ZmsPdf, zMuSaEffTerm)) ;
RooGenericPdf *bkg_musa = new RooGenericPdf("bkg_musa","zmusa bkg_model", "exp(gamma * mass) * (c0 + c1 * mass )", RooArgSet( *mass, gamma, c0, c1) );
// RooAddPdf * eZmsSig= new RooAddPdf("eZmsSig","eZmsSig",RooArgList(*,*bkg_mumuNotIso), RooArgList(zMuMuNoIsoEffTerm, nbkg_mumuNotIso));
RooAddPdf *eZmsSig = new RooAddPdf("eZmsSig","eZmsSig",RooArgList(*ZmsPdf,*bkg_musa),RooArgList(zMuSaEffTerm , nbkg_musa)) ;
//RooExtendPdf * eZmsSig= new RooExtendPdf("eZmsSig","extended signal p.d.f for zms ",*ZmsPdf, zMuSaEffTerm ) ;
// z mu mu HLT
// count ZMuMu Yield
double nZMuMu = 0.;
double nZMuMu1HLT = 0.;
double nZMuMu2HLT = 0.;
unsigned int nBins = zmm->GetNbinsX();
double xMin = zmm->GetXaxis()->GetXmin();
double xMax = zmm->GetXaxis()->GetXmax();
double deltaX =(xMax - xMin) / nBins;
for(unsigned int i = 0; i < nBins; ++i) {
double x = xMin + (i +.5) * deltaX;
if(x > fMin && x < fMax){
nZMuMu += zmm->GetBinContent(i+1);
nZMuMu1HLT += zmm1hlt->GetBinContent(i+1);
nZMuMu2HLT += zmm2hlt->GetBinContent(i+1);
}
}
cout << ">>> count of ZMuMu yield in the range [" << fMin << ", " << fMax << "]: " << nZMuMu << endl;
cout << ">>> count of ZMuMu (1HLT) yield in the range [" << fMin << ", " << fMax << "]: " << nZMuMu1HLT << endl;
cout << ">>> count of ZMuMu (2HLT) yield in the range [" << fMin << ", " << fMax << "]: " << nZMuMu2HLT << endl;
// we set eff_hlt
//eff_hlt.setVal( 1. / (1. + (nZMuMu1HLT/ (2 * nZMuMu2HLT))) ) ;
// creating the pdf for z mu mu 1hlt
RooExtendPdf * eZmm1hltSig= new RooExtendPdf("eZmm1hltSig","extended signal p.d.f for zmm 1hlt",*ZmmHltPdf, zMuMu1HLTEffTerm ) ;
// creating the pdf for z mu mu 2hlt
RooExtendPdf * eZmm2hltSig= new RooExtendPdf("eZmm2hltSig","extended signal p.d.f for zmm 2hlt",*ZmmHltPdf, zMuMu2HLTEffTerm ) ;
// getting the data if fit otherwise constructed the data for model if toy....
RooDataHist *zmtMass, * zmmNotIsoMass, *zmsMass, *zmm1hltMass, *zmm2hltMass;
if (toy){
zmtMass = genHistFromModelPdf("zmtMass", model_mutrk, mass, scaleLumi, range,rebinZMuTk, seed);
zmmNotIsoMass = genHistFromModelPdf("zmmNotIsoMass", model_mumuNotIso, mass, scaleLumi, range,rebinZMuMuNoIso, seed);
zmsMass = genHistFromModelPdf("zmsMass", eZmsSig, mass, scaleLumi, range,rebinZMuSa , seed);
zmm1hltMass = genHistFromModelPdf("zmm1hltMass", eZmm1hltSig, mass, scaleLumi, range,rebinZMuMuHlt, seed );
zmm2hltMass = genHistFromModelPdf("zmm2hltMass", eZmm2hltSig, mass, scaleLumi, range,rebinZMuMuHlt, seed);
} else {// if fit from data....
zmtMass = new RooDataHist("zmtMass", "good z mu track" , RooArgList(*mass), zmt );
zmmNotIsoMass = new RooDataHist("ZmmNotIso", "good z mu mu not isolated" , RooArgList(*mass), zmmNotIso );
zmsMass = new RooDataHist("zmsMass", "good z mu sta mass" , RooArgList(*mass), zmmsta );
zmm1hltMass = new RooDataHist("zmm1hltMass", "good Z mu mu 1hlt" , RooArgList(*mass), zmm1hlt );
zmm2hltMass = new RooDataHist("zmm2hltMass", "good Z mu mu 2hlt" , RooArgList(*mass), zmm2hlt );
}
// creting the chi2s
RooChi2Var *chi2_mutrk = new RooChi2Var("chi2_mutrk","chi2_mutrk",*model_mutrk,*zmtMass, Extended(kTRUE),DataError(RooAbsData::SumW2) ) ;
RooChi2Var *chi2_mumuNotIso = new RooChi2Var("chi2_mumuNotIso","chi2_mumuNotIso",*model_mumuNotIso,*zmmNotIsoMass,Extended(kTRUE), DataError(RooAbsData::SumW2)) ;
RooChi2Var *chi2_musta = new RooChi2Var("chi2_musta","chi2_musta",*eZmsSig, *zmsMass, Extended(kTRUE) ,DataError(RooAbsData::SumW2) ) ;
// uncomment this line if you want to use logLik for mu sta
// RooNLLVar *chi2_musta = new RooNLLVar("chi2_musta","chi2_musta",*eZmsSig, *zmsMass, Extended(kTRUE), DataError(RooAbsData::SumW2) ) ;
RooChi2Var *chi2_mu1hlt = new RooChi2Var("chi2_mu1hlt","chi2_mu1hlt", *eZmm1hltSig, *zmm1hltMass, Extended(kTRUE) , DataError(RooAbsData::SumW2)) ;
RooChi2Var *chi2_mu2hlt = new RooChi2Var("chi2_mu2hlt","chi2_mu2hlt", *eZmm2hltSig, *zmm2hltMass, Extended(kTRUE), DataError(RooAbsData::SumW2) ) ;
// adding the chi2
RooAddition totChi2("totChi2","chi2_mutrk + chi2_mumuNotIso + chi2_musta + chi2_mu1hlt + chi2_mu2hlt " , RooArgSet(*chi2_mutrk ,*chi2_mumuNotIso , *chi2_musta , *chi2_mu1hlt , *chi2_mu2hlt )) ;
// printing out the model integral befor fitting
double N_zMuMu1hlt = eZmm1hltSig->expectedEvents(*mass);
double N_bkgTk = bkg_mutrk->expectedEvents(*mass);
double N_bkgIso = bkg_mumuNotIso->expectedEvents(*mass);
double N_zMuTk = zMuTkEffTerm.getVal();
double e_hlt = eff_hlt.getVal();
double e_tk = eff_tk.getVal();
double e_sa = eff_sa.getVal();
double e_iso = eff_iso.getVal();
double Y_hlt = N_zMuMu1hlt / ((2.* (e_tk * e_tk) * (e_sa * e_sa) * (e_iso* e_iso) * e_hlt *(1.- e_hlt))) ;
double Y_mutk = N_zMuTk / ((2.* (e_tk * e_tk) * e_sa *(1.- e_sa) * (e_iso* e_iso) * e_hlt )) ;
cout << "Yield prediction from mumu1hlt integral befor fitting: " << Y_hlt << endl
;
cout << "Yield prediction from mutk integral befor fitting: " << Y_mutk << endl;
cout << "Bkg for mutk prediction from mutk integral after fitting: " << N_bkgTk << endl;
cout << "Bkg for mumuNotIso prediction from mumuNotIso integral after fitting: " << N_bkgIso << endl;
fit( totChi2, numberOfBins, outfile.c_str());
N_zMuMu1hlt = eZmm1hltSig->expectedEvents(*mass);
N_zMuTk = zMuTkEffTerm.getVal();
double N_zMuMuNoIso = zMuMuNoIsoEffTerm.getVal();
double N_Tk = model_mutrk->expectedEvents(*mass);
double N_Iso = model_mumuNotIso->expectedEvents(*mass);
e_hlt = eff_hlt.getVal();
e_tk = eff_tk.getVal();
e_sa = eff_sa.getVal();
e_iso = eff_iso.getVal();
Y_hlt = N_zMuMu1hlt / ((2.* (e_tk * e_tk) * (e_sa * e_sa) * (e_iso* e_iso) * e_hlt *(1.- e_hlt))) ;
Y_mutk = N_zMuTk / ((2.* (e_tk * e_tk) * e_sa *(1.- e_sa) * (e_iso* e_iso) * e_hlt )) ;
cout << "Yield prediction from mumu1hlt integral after fitting: " << Y_hlt << endl;
//cout << "Yield prediction from mutk integral after fitting: " << Y_mutk << endl;
cout << "N + B prediction from mutk integral after fitting: " << N_Tk << endl;
cout << "zMuTkEffTerm " << N_zMuTk << endl;
cout << "N + B prediction from mumuNotIso integral after fitting: " << N_Iso << endl;
cout << "zMuMuNoIsoEffTerm " << N_zMuMuNoIso << endl;
cout << "chi2_mutrk:" << chi2_mutrk->getVal()<< endl;
cout << "chi2_mumuNotIso:" << chi2_mumuNotIso->getVal() << endl;
cout << "chi2_musta:" << chi2_musta->getVal() << endl;
cout << "chi2_mumu1hlt:" << chi2_mu1hlt->getVal()<< endl;
cout << "chi2_mumu2hlt:" << chi2_mu2hlt->getVal()<< endl;
//plotting
RooPlot * massFrame_mutrk = mass->frame() ;
RooPlot * massFrame_mumuNotIso = mass->frame() ;
RooPlot * massFrame_musta = mass->frame() ;
RooPlot * massFrame_mumu1hlt = mass->frame() ;
RooPlot * massFrame_mumu2hlt = mass->frame() ;
TCanvas * canv1 = new TCanvas("canvas");
TCanvas * canv2 = new TCanvas("new_canvas");
canv1->Divide(2,3);
canv1->cd(1);
canv1->SetLogy(kTRUE);
zmtMass->plotOn(massFrame_mutrk, LineColor(kBlue)) ;
model_mutrk->plotOn(massFrame_mutrk,LineColor(kRed)) ;
model_mutrk->plotOn(massFrame_mutrk,Components(*bkg_mutrk),LineColor(kGreen)) ;
massFrame_mutrk->SetTitle("Z -> #mu track");
// massFrame_mutrk->GetYaxis()->SetLogScale();
massFrame_mutrk->Draw();
gPad->SetLogy(1);
canv2->cd();
canv2->SetLogy(kTRUE);
massFrame_mutrk->Draw();
canv2->SaveAs("LogZMuTk.eps");
canv2->SetLogy(kFALSE);
canv2->SaveAs("LinZMuTk.eps");
canv1->cd(2);
zmmNotIsoMass->plotOn(massFrame_mumuNotIso, LineColor(kBlue)) ;
model_mumuNotIso->plotOn(massFrame_mumuNotIso,LineColor(kRed)) ;
model_mumuNotIso->plotOn(massFrame_mumuNotIso,Components(*bkg_mumuNotIso), LineColor(kGreen)) ;
massFrame_mumuNotIso->SetTitle("Z -> #mu #mu not isolated");
massFrame_mumuNotIso->Draw();
gPad->SetLogy(1);
canv2->cd();
canv2->Clear();
canv2->SetLogy(kTRUE);
massFrame_mumuNotIso->Draw();
canv2->SaveAs("LogZMuMuNotIso.eps");
canv2->SetLogy(kFALSE);
canv2->SaveAs("LinZMuMuNotIso.eps");
canv1->cd(3);
zmsMass->plotOn(massFrame_musta, LineColor(kBlue)) ;
eZmsSig->plotOn(massFrame_musta,Components(*bkg_musa), LineColor(kGreen)) ;
eZmsSig->plotOn(massFrame_musta,LineColor(kRed)) ;
massFrame_musta->SetTitle("Z -> #mu sta");
massFrame_musta->Draw();
canv2->cd();
canv2->Clear();
canv2->SetLogy(kTRUE);
massFrame_musta->Draw();
canv2->SaveAs("LogZMuSa.eps");
canv2->SetLogy(kFALSE);
canv2->SaveAs("LinZMuSa.eps");
canv1->cd(4);
zmm1hltMass->plotOn(massFrame_mumu1hlt, LineColor(kBlue)) ;
eZmm1hltSig->plotOn(massFrame_mumu1hlt,LineColor(kRed)) ;
massFrame_mumu1hlt->SetTitle("Z -> #mu #mu 1hlt");
massFrame_mumu1hlt->Draw();
canv2->cd();
canv2->Clear();
canv2->SetLogy(kTRUE);
massFrame_mumu1hlt->Draw();
canv2->SaveAs("LogZMuMu1Hlt.eps");
canv2->SetLogy(kFALSE);
canv2->SaveAs("LinZMuMu1Hlt.eps");
canv1->cd(5);
zmm2hltMass->plotOn(massFrame_mumu2hlt, LineColor(kBlue)) ;
eZmm2hltSig->plotOn(massFrame_mumu2hlt,LineColor(kRed)) ;
massFrame_mumu2hlt->SetTitle("Z -> #mu #mu 2hlt");
massFrame_mumu2hlt->Draw();
canv1->SaveAs("mass.eps");
canv2->cd();
canv2->Clear();
canv2->SetLogy(kTRUE);
massFrame_mumu2hlt->Draw();
canv2->SaveAs("LogZMuMu2Hlt.eps");
canv2->SetLogy(kFALSE);
canv2->SaveAs("LinZMuMu2Hlt.eps");
/* how to read the fit result in root
TH1D h_Yield("h_Yield", "h_Yield", 100, 10000, 30000)
for (int i =0: i < 100; i++){
RooFitResult* r = gDirectory->Get(Form("toy_totChi2;%d)",i)
//r->floatParsFinal().Print("s");
// without s return a list, can we get the number?
RooFitResult* r = gDirectory->Get("toy_totChi2;1")
// chi2
r->minNll();
//distamce form chi2.....
//r->edm();
// yield
r->floatParsFinal()[0]->Print();
//RooAbsReal * l = r->floatParsFinal()->first()
RooAbsReal * y = r->floatParsFinal()->find("Yield");
h_Yield->Fill(y->getVal());
}
*/
delete root_file;
//delete out_root_file;
return 0;
}
