FitStruct getFitResults( const std::string& outputdir, TTree* tree, const std::string& name, float xMin, float xMax, std::string& cut, std::string& whatToProject ) {
DrawTools::setStyle();
std::string histoName(Form("h1_%s", name.c_str() ));
std::string histoName2(Form("h2_%s", name.c_str() ));
TH1D* h1;
TF1* f1;
gStyle->SetOptFit(1);
h1 = new TH1D(histoName.c_str(), "", 5000, xMin, xMax);
tree->Project( histoName.c_str(), whatToProject.c_str(), cut.c_str() );
f1 = new TF1( Form("gaus_%s", name.c_str()), "gaus", xMin, xMax);
h1->Fit( f1, "RQN" );
f1->SetLineColor(kRed);
double peakpos = h1->GetMean();
double sigma = h1->GetRMS();
// double peakpos = f1->GetParameter(1);
// double sigma = f1->GetParameter(2);
double fitmin;
double fitmax;
if( (peakpos-8*sigma) < 4000 ) {
fitmin = 4000;
} else {
fitmin = peakpos-8*sigma;
}
if(((peakpos>0) && (sigma > 2*peakpos)) ) {
fitmax = 2*peakpos;
} else {
fitmax = peakpos+5*sigma;
}
if (sigma < 500) sigma = 500;
TH1D* h2 = new TH1D("h2", "", 200, fitmin,fitmax);
tree->Project( "h2", whatToProject.c_str(), cut.c_str() );
RooRealVar x("x","ADC Channels", fitmin, fitmax);
RooDataHist data("data","dataset with x",x,Import(*h2) );
RooPlot* frame;
RooPlot* xframe = x.frame();
frame = x.frame("Title");
data.plotOn(frame); //this will show histogram data points on canvas
// data.statOn(frame); //this will display hist stat on canvas
RooRealVar meanr("meanr","Mean",peakpos,peakpos-sigma, peakpos+ sigma);
RooRealVar width("width","#sigma",sigma *0.3, 150.0, 5.*sigma);
RooRealVar A("A","Dist",2., 0.0, 7.0);
RooRealVar N("N","Deg",5, 0.0, 10);
meanr.setRange( 30000. , 1000000.);
width.setRange(500, 22000);
RooCBShape fit_fct("fit_fct","fit_fct",x,meanr,width,A,N);
int ndf = 4;
fit_fct.fitTo(data);
fit_fct.plotOn(frame,LineColor(4));//this will show fit overlay on canvas
// fit_fct.paramOn(frame); //this will display the fit parameters on canvas
double mean = meanr.getVal();
double meanErr = meanr.getError();
double rms = width.getVal();
double rmsErr = width.getError();
double reso = 100.* rms/mean; //in percent
double resoErr = 100.* getRatioError( rms, mean, meanErr, rmsErr );
TCanvas* cans = new TCanvas("cans", "un canvas", 600,600);
cans->cd();
frame->Draw();
TLegend* lego = new TLegend(0.6, 0.7, 0.9, 0.92);
lego->SetTextSize(0.038);
lego->AddEntry( (TObject*)0 ,Form("#mu = %.0f #pm %.0f", meanr.getVal(), meanr.getError() ), "");
lego->AddEntry( (TObject*)0 ,Form("#sigma = %.0f #pm %.0f ", width.getVal(), width.getError() ), "");
lego->AddEntry( (TObject*)0 ,Form("#chi^{2} = %.2f / %d ", frame->chiSquare(ndf) , ndf ), "");
lego->AddEntry( (TObject*)0 ,Form("#sigma/#mu = %.1f #pm %.1f %s ", reso , resoErr ,"%"), "");
lego->SetFillColor(0);
lego->Draw("same");
cans->SaveAs( Form( "%s/CBFit_%s.png", outputdir.c_str(), name.c_str() ) );
FitStruct fs;
fs.mean = mean;
fs.mean_err = meanErr;
fs.sigma = rms;
fs.sigma_err = rmsErr;
fs.reso = reso;
fs.reso_err = resoErr;
delete h1;
delete f1;
delete h2;
delete cans;
return fs;
}
void fitDilMass(){
using namespace RooFit;
gROOT->SetStyle("Plain");
//declare variables
RooRealVar mll("mll", "dilepton mass", 0,100 ,"GeV");
RooRealVar edge("edge", "dilepton mass edge", 0,100 ,"GeV");
RooRealVar min("min", "min dilepton mass", 0,100 ,"GeV");
RooRealVar k("k", "constant", 0,100 ,"GeV");
RooRealVar mean("mean", "mean of mll resolution", 0,100 ,"GeV");
RooRealVar sigma("sigma", "sigma of mll resolution", 0,10 ,"GeV");
//set variables
mll.setBins(100);
edge.setVal(50.);
mean.setVal(0.);
sigma.setVal(2.);
min.setVal(10.);
min.setConstant();
k.setVal(1.);
mean.setConstant();
sigma.setConstant();
mll.setMin(0);
mll.setMax(100);
//get data
TFile* file = TFile::Open("LM0_dilmass.root");
TH1D* hist = static_cast<TH1D *>((file)->Get("dilmass"));
RooDataHist data("data","data histogram",RooArgSet(mll),hist);
//declare and make PDFs
RooGenericPdf tri("tri","( (mll < min && mll > 0) * k + (mll > min && mll < edge ) * (mll - min) + (mll > edge && mll < 200) * k)", RooArgList(mll , edge, min, k) );
RooGaussian gaus("gaus","Detector Gaussian",mll,mean,sigma);
RooNumConvPdf trigaus("trigaus","triangle + gaussian function",mll,tri,gaus);
trigaus.setConvolutionWindow(mean,sigma,25);
//do fit
RooFitResult *result = trigaus.fitTo( data , Save() , Minos(kFALSE) , SumW2Error(kFALSE));
//make plot
TCanvas *c1=new TCanvas("c1","",800,600);
c1->cd();
RooPlot* frame = mll.frame();
frame->SetXTitle("dilepton mass (GeV)");
frame->SetYTitle("");
frame->SetTitle("");
data.plotOn(frame);
tri.plotOn(frame , LineStyle(kDashed));
trigaus.plotOn( frame );
trigaus.paramOn( frame );
frame->Draw();
//frame->SetMinimum(-10);
//frame->SetMaximum(100);
int nfloatpars = result->floatParsFinal().getSize();
int ndf = 20 - nfloatpars;
float chi2 = frame->chiSquare(nfloatpars)*ndf;
float prob = TMath::Prob(chi2,ndf);
cout << endl << endl;
cout << "Fit Results-------------------------------------------" << endl;
cout << "chi2/ndf = " << chi2 << " / " << ndf << endl;
cout << "prob = " << prob << endl;
cout << "edge = " << edge.getVal() << " +/- " << edge.getError() << endl;
cout << "k = " << k.getVal() << " +/- " << k.getError() << endl;
cout << "------------------------------------------------------" << endl;
cout << endl << endl;
}
void deFit(const int mode = 0, const int svd = 2, const bool only_d0 = false){
TChain* tree = new TChain("TEvent");
const double bdtg_min = -0.44;
const double deMin = -0.12;
const double deMax = 0.3;
const double mbcMin = 5.272;
const double mbcMax = 5.287;
// const double sz_sig_max = 0.2;
// const double sz_asc_max = 0.2;
// const double chisq_sig_max = only_d0 ? 10000 : 50;
// const double chisq_asc_max = 50;
const double atckpi_pi_max = 0.8;
const double cm2ps = 78.48566945838871754705;
const double de_min = -0.035;
const double de_max = 0.035;
const bool cComb = false;
const bool cSig = true;
const bool simple_peak = false;
if(mode){
tree->Add("FIL_b2dpi_charged_v2_0_10.root");
tree->Add("FIL_b2dpi_charm_0_v2_10.root");
} else{
tree->Add("FIL_b2dpi_data_v2.root");
}
RooArgSet argset;
RooCategory exp("exp","exp");
if(svd == 1){
exp.defineType("7",7);
exp.defineType("9",9);
exp.defineType("11",11);
exp.defineType("13",13);
exp.defineType("15",15);
exp.defineType("17",17);
exp.defineType("19",19);
exp.defineType("21",21);
exp.defineType("23",23);
exp.defineType("25",25);
exp.defineType("27",27);
} else{
exp.defineType("31",31);
exp.defineType("33",33);
exp.defineType("35",35);
exp.defineType("37",37);
exp.defineType("39",39);
exp.defineType("41",41);
exp.defineType("43",43);
exp.defineType("45",45);
exp.defineType("47",47);
exp.defineType("49",49);
exp.defineType("51",51);
exp.defineType("55",55);
exp.defineType("61",61);
exp.defineType("63",63);
exp.defineType("65",65);
}
argset.add(exp);
RooCategory ndf_z_asc("ndf_z_asc","ndf_z_asc");
ndf_z_asc.defineType("0",0);
ndf_z_asc.defineType("2",2);
ndf_z_asc.defineType("4",4);
ndf_z_asc.defineType("6",6);
ndf_z_asc.defineType("8",8);
ndf_z_asc.defineType("10",10);
ndf_z_asc.defineType("12",12);
ndf_z_asc.defineType("14",14);
ndf_z_asc.defineType("16",16);
ndf_z_asc.defineType("18",18);
argset.add(ndf_z_asc);
RooCategory good_icpv_mlt("good_icpv_mlt","good_icpv_mlt");
good_icpv_mlt.defineType("good",1);
RooCategory good_icpv_sgl("good_icpv_sgl","good_icpv_sgl");
good_icpv_sgl.defineType("good",1);
if(only_d0){
argset.add(good_icpv_sgl);
} else{
argset.add(good_icpv_mlt);
}
RooRealVar mbc("mbc","M_{bc}",mbcMin,mbcMax,"GeV"); argset.add(mbc);
RooRealVar de("de","#DeltaE",deMin,deMax,"GeV"); argset.add(de);
de.setRange("Signal",de_min,de_max);
if(!only_d0){ RooRealVar dz("dz","#Deltaz",-70./cm2ps,70./cm2ps,"cm"); argset.add(dz);}
else { RooRealVar dz("dz_d0","#Deltaz",-70./cm2ps,70./cm2ps,"cm"); argset.add(dz);}
RooRealVar bdtg("bdtg","bdtg",bdtg_min,1.); argset.add(bdtg);
RooRealVar atckpi_pi("atckpi_pi","atckpi_pi",0.,atckpi_pi_max); argset.add(atckpi_pi);
// if(!only_d0){ RooRealVar sz_sig("sz_sig","sz_sig",0.,sz_sig_max,"mm"); argset.add(sz_sig);}
// else { RooRealVar sz_sig("sz_sig_d0","#sigma_{z}^{sig}",0.,sz_sig_max,"mm"); argset.add(sz_sig);}
// RooRealVar sz_asc("sz_asc","sz_asc",0.,sz_asc_max,"mm"); argset.add(sz_asc);
// if(!only_d0 || true){ RooRealVar chisq_z_sig("chisq_z_sig","chisq_z_sig",0.,chisq_sig_max); argset.add(chisq_z_sig);}
// RooRealVar chisq_z_asc("chisq_z_asc","chisq_z_asc",0.,chisq_asc_max); argset.add(chisq_z_asc);
// RooDataSet ds("ds","ds",tree,argset,"mbc>0||mbc<=0 && (ndf_z_asc == 0 || 1.*chisq_z_asc/(ndf_z_asc+0.001)<10)");
RooDataSet ds("ds","ds",tree,argset,"mbc>0||mbc<=0");
RooRealVar de0DK("de0DK","de0DK",-0.049,-0.055,-0.040); de0DK.setConstant(kTRUE);
RooRealVar sDK("sDK","sDK",0.017,0.013,0.016); sDK.setConstant(kTRUE);
RooGaussian gDK("gDK","gDK",de,de0DK,sDK);
RooRealVar Nrho("NDK","NDK",50,0.,5000);// Nrho.setConstant(kTRUE);
RooRealVar c1("c1","c1",-6.96922e-01,-10.,10.); if(cComb) c1.setConstant(kTRUE);
RooRealVar c2("c2","c2",1.72017e-01,-10.,10.); if(cComb) c2.setConstant(kTRUE);
RooChebychev pdf_comb("pdf_comb","pdf_comb",de,RooArgSet(c1,c2));
RooRealVar Ncmb("NComb","NComb",10000,0.,50000);
RooRealVar de0("de0","de0",0.,-0.005,0.005);
RooRealVar s("s","s",1.19644e-02,0.010,0.015);
if(simple_peak){
RooGaussian pdf_sig("pdf_sig","pdf_sig",de,de0,s);
} else{
RooGaussian g1("g1","g1",de,de0,s);
// RooRealVar nl("nl","nl",4.93610e+00,0.,100.); if(cSig) nl.setConstant(kTRUE);
RooRealVar nl("nl","nl",7.78037e+00,0.,100.); if(cSig) nl.setConstant(kTRUE);
RooRealVar alphal("alphal","alphal",-1,-10.,10.); alphal.setConstant(kTRUE);
// RooRealVar nr("nr","nr",4.91073e+00,0.,100.); if(cSig) nr.setConstant(kTRUE);
RooRealVar nr("nr","nr",1.29892e+01,0.,100.); if(cSig) nr.setConstant(kTRUE);
RooRealVar alphar("alphar","alphar",1,-10.,10.); alphar.setConstant(kTRUE);
RooCBShape CBl("CBl","CBl",de,de0,s,alphal,nl);
RooCBShape CBr("CBr","CBr",de,de0,s,alphar,nr);
// RooRealVar fCBl("fCBl","fCBl",2.40571e-01,0.,1.); if(cSig) fCBl.setConstant(kTRUE);
// RooRealVar fCBr("fCBr","fCBr",2.20385e-01,0.,1.); if(cSig) fCBr.setConstant(kTRUE);
RooRealVar fCBl("fCBl","fCBl",2.22046e-01,0.,1.); if(cSig) fCBl.setConstant(kTRUE);
RooRealVar fCBr("fCBr","fCBr",2.21964e-01,0.,1.); if(cSig) fCBr.setConstant(kTRUE);
RooAddPdf pdf_sig("pdf_sig","pdf_sig",RooArgList(CBl,CBr,g1),RooArgSet(fCBl,fCBr));
}
RooRealVar Nsig("NSig","NSig",20000,0.,25000);
RooAddPdf pdf("pdf","pdf",RooArgSet(gDK,pdf_comb,pdf_sig),RooArgList(Nrho,Ncmb,Nsig));
pdf.fitTo(ds,Verbose(),Timer(true));
RooAbsReal* intSig = pdf_sig.createIntegral(RooArgSet(de),NormSet(RooArgSet(de)),Range("Signal"));
RooAbsReal* intRho = gDK.createIntegral(RooArgSet(de),NormSet(RooArgSet(de)),Range("Signal"));
RooAbsReal* intCmb = pdf_comb.createIntegral(RooArgSet(de),NormSet(RooArgSet(de)),Range("Signal"));
const double nsig = intSig->getVal()*Nsig.getVal();
const double nsig_err = intSig->getVal()*Nsig.getError();
const double nsig_err_npq = TMath::Sqrt(nsig*(Nsig.getVal()-nsig)/Nsig.getVal());
const double nsig_err_total = TMath::Sqrt(nsig_err*nsig_err+nsig_err_npq*nsig_err_npq);
const double nrho = intRho->getVal()*Nrho.getVal();
const double nrho_err = intRho->getVal()*Nrho.getError();
const double nrho_err_npq = TMath::Sqrt(nrho*(Nrho.getVal()-nrho)/Nrho.getVal());
const double nrho_err_total = TMath::Sqrt(nrho_err*nrho_err+nrho_err_npq*nrho_err_npq);
const double ncmb = intCmb->getVal()*Ncmb.getVal();
const double ncmb_err = intCmb->getVal()*Ncmb.getError();
const double ncmb_err_npq = TMath::Sqrt(ncmb*(Ncmb.getVal()-ncmb)/Ncmb.getVal());
const double ncmb_err_total = TMath::Sqrt(ncmb_err*ncmb_err+ncmb_err_npq*ncmb_err_npq);
const double purity = nsig/(nsig+nrho+ncmb);
const double purity_err = nsig_err_total/(nsig+nrho+ncmb);
double sig_frac;
double pdf_sig_val;
double pdf_DK_val;
double pdf_smooth_val;
fstream ofile("de_sig_fraction.txt",fstream::out);
for(int i=0; i<1000; i++){
const double dde = 0.2/1000;
de.setVal(-0.1+(i+0.5)*dde);
pdf_sig_val = Nsig.getVal()*pdf_sig.getVal(de);
pdf_DK_val = Nrho.getVal()*gDK.getVal(de);
pdf_smooth_val = Ncmb.getVal()*pdf_comb.getVal(de);
sig_frac = pdf_sig_val/(pdf_sig_val+pdf_DK_val+pdf_smooth_val);
ofile << de.getVal() << " " << sig_frac << endl;
}
ofile.close();
/////////////
// Plots //
/////////////
// de //
RooPlot* deFrame = de.frame();
ds.plotOn(deFrame,DataError(RooAbsData::SumW2),MarkerSize(1));
pdf.plotOn(deFrame,Components(gDK),LineStyle(kDashed));
pdf.plotOn(deFrame,Components(pdf_sig),LineStyle(kDashed));
pdf.plotOn(deFrame,Components(pdf_comb),LineStyle(kDashed));
pdf.plotOn(deFrame,LineWidth(2));
RooHist* hdepull = deFrame->pullHist();
RooPlot* dePull = de.frame(Title("#Delta E pull distribution"));
dePull->addPlotable(hdepull,"P");
dePull->GetYaxis()->SetRangeUser(-5,5);
TCanvas* cm = new TCanvas("Delta E","Delta E",600,700);
cm->cd();
TPad *pad3 = new TPad("pad3","pad3",0.01,0.20,0.99,0.99);
TPad *pad4 = new TPad("pad4","pad4",0.01,0.01,0.99,0.20);
pad3->Draw();
pad4->Draw();
pad3->cd();
pad3->SetLeftMargin(0.15);
pad3->SetFillColor(0);
pad3->SetGrid();
deFrame->GetXaxis()->SetTitleSize(0.05);
deFrame->GetXaxis()->SetTitleOffset(0.85);
deFrame->GetXaxis()->SetLabelSize(0.04);
deFrame->GetYaxis()->SetTitleOffset(1.6);
deFrame->Draw();
const int height = svd == 2 ? 500 : 120;
TLine *de_line_RIGHT = new TLine(de_max,0,de_max,height);
de_line_RIGHT->SetLineColor(kRed);
de_line_RIGHT->SetLineStyle(1);
de_line_RIGHT->SetLineWidth((Width_t)2.);
de_line_RIGHT->Draw();
TLine *de_line_LEFT = new TLine(de_min,0,de_min,height);
de_line_LEFT->SetLineColor(kRed);
de_line_LEFT->SetLineStyle(1);
de_line_LEFT->SetLineWidth((Width_t)2.);
de_line_LEFT->Draw();
stringstream out1;
TPaveText *pt = new TPaveText(0.4,0.65,0.98,0.9,"brNDC");
pt->SetFillColor(0);
pt->SetTextAlign(12);
out1.str("");
out1 << "#chi^{2}/n.d.f = " << deFrame->chiSquare();
pt->AddText(out1.str().c_str());
out1.str("");
out1 << "S: " << (int)(nsig+0.5) << " #pm " << (int)(nsig_err_total+0.5);
pt->AddText(out1.str().c_str());
out1.str("");
out1 << "Purity: " << std::fixed << std::setprecision(2) << purity*100. << " #pm " << purity_err*100;
pt->AddText(out1.str().c_str());
pt->Draw();
pad4->cd(); pad4->SetLeftMargin(0.15); pad4->SetFillColor(0);
dePull->SetMarkerSize(0.05); dePull->Draw();
TLine *de_lineUP = new TLine(deMin,3,deMax,3);
de_lineUP->SetLineColor(kBlue);
de_lineUP->SetLineStyle(2);
de_lineUP->Draw();
TLine *de_line = new TLine(deMin,0,deMax,0);
de_line->SetLineColor(kBlue);
de_line->SetLineStyle(1);
de_line->SetLineWidth((Width_t)2.);
de_line->Draw();
TLine *de_lineDOWN = new TLine(deMin,-3,deMax,-3);
de_lineDOWN->SetLineColor(kBlue);
de_lineDOWN->SetLineStyle(2);
de_lineDOWN->Draw();
cm->Update();
// cout << "Nsig = " << nsig <<" +- " << nsig_err << endl;
// cout << "NDK = " << nrho <<" +- " << nrho_err << endl;
// cout << "Ncmb = " << ncmb <<" +- " << ncmb_err << endl;
// cout << "Purity = " << purity << " +- " << purity_err << endl;
cout << "Nsig = " << nsig <<" +- " << nsig_err << " +- " << nsig_err_npq << " (" << nsig_err_total << ")" << endl;
cout << "NDK = " << nrho <<" +- " << nrho_err << " +- " << nrho_err_npq << " (" << nrho_err_total << ")" << endl;
cout << "Ncmb = " << ncmb <<" +- " << ncmb_err << " +- " << ncmb_err_npq << " (" << ncmb_err_total << ")" << endl;
cout << "Pury = " << purity << " +- " << purity_err << endl;
}
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 MakeSpinPlots::DrawBlindFit(TString tag, TString mcName,TString cosThetaBin){
TString fitTag="FULLFIT";
TString cat = "evtcat";
if(cosThetaBin!=""){
tag+="_"+cosThetaBin;
fitTag="FULLCOSTFIT";
cat = "evtcat_cosT";
}
TString dataTag = "_Combined";
if(cosThetaBin!="") dataTag+="_CosTBin";
TCanvas *cv = new TCanvas(Form("%s_%s",mcName.Data(),tag.Data()));
RooRealVar* mass = ws->var("mass");
mass->setBins( (mass->getMax() - mass->getMin())/1.5 ); //enfore 1.5GeV bin width
RooPlot* frame = mass->frame();
double Nb = ws->var(Form("Data_BKGFIT_%s_Nbkg",tag.Data()))->getVal();
cout << Nb << endl;
RooDataSet *blind = (RooDataSet*)ws->data("Data"+dataTag)->reduce(TString("((mass<119) || (mass>135.5)) && ")+cat+"=="+cat+"::"+tag);
blind->plotOn(frame);
tPair lbl(mcName,tag);
double nBkg = ws->data("Data"+dataTag)->sumEntries(cat+"=="+cat+"::"+tag);
ws->pdf( Form("Data_BKGFIT_%s_bkgModel",tag.Data()) )->plotOn(frame,RooFit::Range("all"),RooFit::Normalization(nBkg/blind->sumEntries()),
RooFit::LineColor(kRed));
//TLatex *prelim = new TLatex(250,x->GetXmax()-40.,"CMS Preliminary");
TLatex *prelim = new TLatex(0.12,0.96,"CMS Preliminary");
TLatex *lum = new TLatex(0.7,0.96,Form("#sqrt{s}=8 TeV L = %0.1f fb^{-1}",lumi));
prelim->SetNDC();
lum->SetNDC();
prelim->SetTextSize(0.045);
prelim->SetTextColor(kBlack);
lum->SetTextSize(0.045);
lum->SetTextColor(kBlack);
TLatex *owner = new TLatex(0.6,0.88,"Caltech-CMS Preliminary");
owner->SetNDC();
owner->SetTextSize(0.045);
owner->SetTextColor(kBlack);
TLatex *Nbkg = new TLatex(0.7,0.8,Form("N_{bkg}= %0.1f #pm %0.1f",nBackground[lbl].first,nBackground[lbl].second));
Nbkg->SetNDC();
Nbkg->SetTextSize(0.045);
TLatex *sig = new TLatex(0.7,0.72,Form("#sigma_{eff} = %0.1f #pm %0.2f",fitSigEff[lbl].first,fitSigEff[lbl].second));
sig->SetNDC();
sig->SetTextSize(0.045);
TLatex *expBkg = new TLatex(0.7,0.64,Form("B @ 125 = %0.1f",fitBkg1Sigma[lbl].first));
expBkg->SetNDC();
expBkg->SetTextSize(0.045);
frame->addObject(prelim);
frame->addObject(lum);
//frame->addObject(owner);
frame->addObject(Nbkg);
frame->addObject(sig);
frame->addObject(expBkg);
frame->Draw();
cv->SaveAs( basePath+Form("/mgg-%s-%s-%s_BLIND.png",outputTag.Data(),mcName.Data(),tag.Data()) );
cv->SaveAs( basePath+Form("/C/mgg-%s-%s-%s_BLIND.C",outputTag.Data(),mcName.Data(),tag.Data()) );
cv->SaveAs( basePath+Form("/mgg-%s-%s-%s_BLIND.pdf",outputTag.Data(),mcName.Data(),tag.Data()) );
delete cv;
}
void drawCtauFrom2DPlot(RooWorkspace& myws, // Local workspace
string outputDir, // Output directory
struct InputOpt opt, // Variable with run information (kept for legacy purpose)
struct KinCuts cut, // Variable with current kinematic cuts
map<string, string> parIni, // Variable containing all initial parameters
string plotLabel, // The label used to define the output file name
// Select the type of datasets to fit
string DSTAG, // Specifies the type of datasets: i.e, DATA, MCJPSINP, ...
bool isPbPb, // Define if it is PbPb (True) or PP (False)
// Select the type of object to fit
bool incJpsi, // Includes Jpsi model
bool incPsi2S, // Includes Psi(2S) model
bool incBkg, // Includes Background model
// Select the fitting options
// Select the drawing options
bool setLogScale, // Draw plot with log scale
bool incSS, // Include Same Sign data
double binWidth // Bin width
)
{
RooMsgService::instance().getStream(0).removeTopic(Caching);
RooMsgService::instance().getStream(1).removeTopic(Caching);
RooMsgService::instance().getStream(0).removeTopic(Plotting);
RooMsgService::instance().getStream(1).removeTopic(Plotting);
RooMsgService::instance().getStream(0).removeTopic(Integration);
RooMsgService::instance().getStream(1).removeTopic(Integration);
RooMsgService::instance().setGlobalKillBelow(RooFit::WARNING) ;
if (DSTAG.find("_")!=std::string::npos) DSTAG.erase(DSTAG.find("_"));
string pdfTotName = Form("pdfCTAUMASS_Tot_%s", (isPbPb?"PbPb":"PP"));
string dsOSName = Form("dOS_%s_%s", DSTAG.c_str(), (isPbPb?"PbPb":"PP"));
string dsOSNameCut = dsOSName+"_CTAUCUT";
string hOSName = Form("dhCTAUERRTot_Tot_%s", (isPbPb?"PbPb":"PP"));
string hOSNameBkg = Form("dhCTAUERR_Bkg_%s", (isPbPb?"PbPb":"PP"));
string hOSNameJpsi = Form("dhCTAUERR_Jpsi_%s", (isPbPb?"PbPb":"PP"));
string hOSNamePsi2S = Form("dhCTAUERR_Psi2S_%s", (isPbPb?"PbPb":"PP"));
string dsSSName = Form("dSS_%s_%s", DSTAG.c_str(), (isPbPb?"PbPb":"PP"));
bool isWeighted = myws.data(dsOSName.c_str())->isWeighted();
vector<double> range; range.push_back(cut.dMuon.ctau.Min); range.push_back(cut.dMuon.ctau.Max);
double minRange = -4.0;
double maxRange = 7.0;
Double_t outTot = myws.data(dsOSName.c_str())->numEntries();
Double_t outErr = myws.data(dsOSName.c_str())->reduce(Form("(ctau>%.6f || ctau<%.6f)", range[1], range[0]))->numEntries();
int nBins = min(int( round((maxRange - minRange)/binWidth) ), 1000);
double normDSTot = 1.0; if (myws.data(dsOSNameCut.c_str())) { normDSTot = myws.data(dsOSName.c_str())->sumEntries()/myws.data(dsOSNameCut.c_str())->sumEntries(); }
double normJpsi = 1.0; if (myws.data(hOSNameJpsi.c_str())) { normJpsi = myws.data(dsOSName.c_str())->sumEntries()*normDSTot/myws.data(hOSNameJpsi.c_str())->sumEntries(); }
double normPsi2S = 1.0; if (myws.data(hOSNamePsi2S.c_str())) { normPsi2S = myws.data(dsOSName.c_str())->sumEntries()*normDSTot/myws.data(hOSNamePsi2S.c_str())->sumEntries(); }
double normBkg = 1.0; if (myws.data(hOSNameBkg.c_str())) { normBkg = myws.data(dsOSName.c_str())->sumEntries()*normDSTot/myws.data(hOSNameBkg.c_str())->sumEntries(); }
double normTot = 1.0; if (myws.data(hOSName.c_str())) { normTot = myws.data(dsOSName.c_str())->sumEntries()*normDSTot/myws.data(hOSName.c_str())->sumEntries(); }
// Create the main plot of the fit
RooPlot* frame = myws.var("ctau")->frame(Bins(nBins), Range(minRange, maxRange));
frame->updateNormVars(RooArgSet(*myws.var("invMass"), *myws.var("ctau"), *myws.var("ctauErr"))) ;
myws.data(dsOSName.c_str())->plotOn(frame, Name("dOS"), DataError(RooAbsData::SumW2), XErrorSize(0), MarkerColor(kBlack), LineColor(kBlack), MarkerSize(1.2));
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PDF"),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSNameCut.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
FillStyle(1001), FillColor(kViolet+6), VLines(), DrawOption("LF"), NumCPU(32), LineColor(kBlack)
);
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("BKG"),Components(RooArgSet( *myws.pdf(Form("pdfCTAUMASS_Bkg_%s", (isPbPb?"PbPb":"PP"))) )),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
FillStyle(1001), FillColor(kAzure-9), VLines(), DrawOption("LF"), NumCPU(32)
);
if (incJpsi) {
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("JPSIPR"),Components(RooArgSet( *myws.pdf(Form("pdfCTAUMASS_JpsiPR_%s", (isPbPb?"PbPb":"PP"))) )),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kRed+3), Precision(1e-5), NumCPU(32)
);
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("JPSINOPR"),Components(RooArgSet( *myws.pdf(Form("pdfCTAUMASS_JpsiNoPR_%s", (isPbPb?"PbPb":"PP"))) )),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kGreen+3), Precision(1e-5), NumCPU(32)
);
}
if (incPsi2S) {
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PSI2SPR"),Components(RooArgSet( *myws.pdf(Form("pdfCTAUMASS_Psi2SPR_%s", (isPbPb?"PbPb":"PP"))) )),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kRed+3), Precision(1e-5), NumCPU(32)
);
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PSI2SNOPR"),Components(RooArgSet( *myws.pdf(Form("pdfCTAUMASS_Psi2SNo_%s", (isPbPb?"PbPb":"PP"))) )),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSName.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kGreen+3), Precision(1e-5), NumCPU(32)
);
}
if (incSS) {
myws.data(dsSSName.c_str())->plotOn(frame, Name("dSS"), MarkerColor(kRed), LineColor(kRed), MarkerSize(1.2));
}
myws.data(dsOSName.c_str())->plotOn(frame, Name("dOS"), DataError(RooAbsData::SumW2), XErrorSize(0), MarkerColor(kBlack), LineColor(kBlack), MarkerSize(1.2));
myws.pdf(pdfTotName.c_str())->plotOn(frame,Name("PDFLINE"),
ProjWData(RooArgSet(*myws.var("ctauErr")), *myws.data(dsOSNameCut.c_str()), kTRUE),
Normalization(normDSTot, RooAbsReal::NumEvent),
LineColor(kBlack), NumCPU(32)
);
// set the CMS style
setTDRStyle();
// Create the pull distribution of the fit
RooHist *hpull = frame->pullHist(0, "PDF", true);
hpull->SetName("hpull");
RooPlot* frame2 = myws.var("ctau")->frame(Title("Pull Distribution"), Bins(nBins), Range(minRange, maxRange));
frame2->addPlotable(hpull, "PX");
// Create the main canvas
TCanvas *cFig = new TCanvas(Form("cCtauFig_%s", (isPbPb?"PbPb":"PP")), "cCtauFig",800,800);
TPad *pad1 = new TPad(Form("pad1_%s", (isPbPb?"PbPb":"PP")),"",0,0.23,1,1);
TPad *pad2 = new TPad(Form("pad2_%s", (isPbPb?"PbPb":"PP")),"",0,0,1,.228);
TLine *pline = new TLine(minRange, 0.0, maxRange, 0.0);
TPad *pad4 = new TPad("pad4","This is pad4",0.55,0.46,0.97,0.87);
pad4->SetFillStyle(0);
pad4->SetLeftMargin(0.28);
pad4->SetRightMargin(0.10);
pad4->SetBottomMargin(0.21);
pad4->SetTopMargin(0.072);
frame->SetTitle("");
frame->GetXaxis()->SetTitle("");
frame->GetXaxis()->CenterTitle(kTRUE);
frame->GetXaxis()->SetTitleSize(0.045);
frame->GetXaxis()->SetTitleFont(42);
frame->GetXaxis()->SetTitleOffset(3);
frame->GetXaxis()->SetLabelOffset(3);
frame->GetYaxis()->SetLabelSize(0.04);
frame->GetYaxis()->SetTitleSize(0.04);
frame->GetYaxis()->SetTitleOffset(1.7);
frame->GetYaxis()->SetTitleFont(42);
setCtauFrom2DRange(myws, frame, dsOSNameCut, setLogScale, range, outErr);
cFig->cd();
pad2->SetTopMargin(0.02);
pad2->SetBottomMargin(0.4);
pad2->SetFillStyle(4000);
pad2->SetFrameFillStyle(4000);
pad1->SetBottomMargin(0.015);
//plot fit
pad1->Draw();
pad1->cd();
frame->Draw();
printCtauFrom2DParameters(myws, pad1, isPbPb, pdfTotName, isWeighted);
pad1->SetLogy(setLogScale);
// Drawing the text in the plot
TLatex *t = new TLatex(); t->SetNDC(); t->SetTextSize(0.032);
float dy = 0;
t->SetTextSize(0.03);
t->DrawLatex(0.21, 0.86-dy, "2015 HI Soft Muon ID"); dy+=0.045;
if (isPbPb) {
t->DrawLatex(0.21, 0.86-dy, "HLT_HIL1DoubleMu0_v1"); dy+=0.045;
} else {
t->DrawLatex(0.21, 0.86-dy, "HLT_HIL1DoubleMu0_v1"); dy+=0.045;
}
t->DrawLatex(0.21, 0.86-dy, Form("%.1f #leq p_{T}^{#mu#mu} < %.1f GeV/c",cut.dMuon.Pt.Min,cut.dMuon.Pt.Max)); dy+=0.045;
t->DrawLatex(0.21, 0.86-dy, Form("%.1f #leq |y^{#mu#mu}| < %.1f",cut.dMuon.AbsRap.Min,cut.dMuon.AbsRap.Max)); dy+=0.045;
if (isPbPb) {t->DrawLatex(0.21, 0.86-dy, Form("Cent. %d-%d%%", (int)(cut.Centrality.Start/2), (int)(cut.Centrality.End/2))); dy+=0.045;}
if (outErr>0.0) {
t->DrawLatex(0.21, 0.86-dy, Form("Excl: (%.4f%%) %.0f evts", (outErr*100.0/outTot), outErr)); dy+=1.5*0.045;
}
// Drawing the Legend
double ymin = 0.7602;
if (incPsi2S && incJpsi && incSS) { ymin = 0.7202; }
if (incPsi2S && incJpsi && !incSS) { ymin = 0.7452; }
TLegend* leg = new TLegend(0.5175, ymin, 0.7180, 0.8809); leg->SetTextSize(0.03);
leg->AddEntry(frame->findObject("dOS"), (incSS?"Opposite Charge":"Data"),"pe");
if (incSS) { leg->AddEntry(frame->findObject("dSS"),"Same Charge","pe"); }
if(frame->findObject("PDF")) { leg->AddEntry(frame->findObject("PDF"),"Total fit","fl"); }
if((incBkg && (incJpsi || incPsi2S)) && frame->findObject("BKG")) { leg->AddEntry(frame->findObject("BKG"),"Background","fl"); }
if(incBkg && incJpsi && frame->findObject("JPSIPR")) { leg->AddEntry(frame->findObject("JPSIPR"),"J/#psi Prompt","l"); }
if(incBkg && incJpsi && frame->findObject("JPSINOPR")) { leg->AddEntry(frame->findObject("JPSINOPR"),"J/#psi Non-Prompt","l"); }
if(incBkg && incPsi2S && frame->findObject("PSI2SPR")) { leg->AddEntry(frame->findObject("PSI2SPR"),"#psi(2S) Prompt","l"); }
if(incBkg && incPsi2S && frame->findObject("PSI2SNOPR")) { leg->AddEntry(frame->findObject("PSI2SNOPR"),"#psi(2S) Non-Prompt","l"); }
leg->Draw("same");
//Drawing the title
TString label;
if (isPbPb) {
if (opt.PbPb.RunNb.Start==opt.PbPb.RunNb.End){
label = Form("PbPb Run %d", opt.PbPb.RunNb.Start);
} else {
label = Form("%s [%s %d-%d]", "PbPb", "HIOniaL1DoubleMu0", opt.PbPb.RunNb.Start, opt.PbPb.RunNb.End);
}
} else {
if (opt.pp.RunNb.Start==opt.pp.RunNb.End){
label = Form("PP Run %d", opt.pp.RunNb.Start);
} else {
label = Form("%s [%s %d-%d]", "PP", "DoubleMu0", opt.pp.RunNb.Start, opt.pp.RunNb.End);
}
}
//CMS_lumi(pad1, isPbPb ? 105 : 104, 33, label);
CMS_lumi(pad1, isPbPb ? 108 : 107, 33, "");
gStyle->SetTitleFontSize(0.05);
pad1->Update();
cFig->cd();
//---plot pull
pad2->Draw();
pad2->cd();
frame2->SetTitle("");
frame2->GetYaxis()->CenterTitle(kTRUE);
frame2->GetYaxis()->SetTitleOffset(0.4);
frame2->GetYaxis()->SetTitleSize(0.1);
frame2->GetYaxis()->SetLabelSize(0.1);
frame2->GetYaxis()->SetTitle("Pull");
frame2->GetXaxis()->CenterTitle(kTRUE);
frame2->GetXaxis()->SetTitleOffset(1);
frame2->GetXaxis()->SetTitleSize(0.12);
frame2->GetXaxis()->SetLabelSize(0.1);
frame2->GetXaxis()->SetTitle("#font[12]{l}_{J/#psi} (mm)");
frame2->GetYaxis()->SetRangeUser(-7.0, 7.0);
frame2->Draw();
// *** Print chi2/ndof
printChi2(myws, pad2, frame, "ctau", dsOSName.c_str(), pdfTotName.c_str(), nBins, false);
pline->Draw("same");
pad2->Update();
// Save the plot in different formats
gSystem->mkdir(Form("%sctauMass/%s/plot/root/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFig->SaveAs(Form("%sctauMass/%s/plot/root/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.root", outputDir.c_str(), DSTAG.c_str(), "CTAU", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
gSystem->mkdir(Form("%sctauMass/%s/plot/png/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFig->SaveAs(Form("%sctauMass/%s/plot/png/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.png", outputDir.c_str(), DSTAG.c_str(), "CTAU", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
gSystem->mkdir(Form("%sctauMass/%s/plot/pdf/", outputDir.c_str(), DSTAG.c_str()), kTRUE);
cFig->SaveAs(Form("%sctauMass/%s/plot/pdf/PLOT_%s_%s_%s%s_pt%.0f%.0f_rap%.0f%.0f_cent%d%d.pdf", outputDir.c_str(), DSTAG.c_str(), "CTAU", DSTAG.c_str(), (isPbPb?"PbPb":"PP"), plotLabel.c_str(), (cut.dMuon.Pt.Min*10.0), (cut.dMuon.Pt.Max*10.0), (cut.dMuon.AbsRap.Min*10.0), (cut.dMuon.AbsRap.Max*10.0), cut.Centrality.Start, cut.Centrality.End));
cFig->Clear();
cFig->Close();
}
void eregtesting_13TeV_Pi0(bool dobarrel=true, bool doele=false,int gammaID=0) {
//output dir
TString EEorEB = "EE";
if(dobarrel)
{
EEorEB = "EB";
}
TString gammaDir = "bothGammas";
if(gammaID==1)
{
gammaDir = "gamma1";
}
else if(gammaID==2)
{
gammaDir = "gamma2";
}
TString dirname = TString::Format("ereg_test_plots/%s_%s",gammaDir.Data(),EEorEB.Data());
gSystem->mkdir(dirname,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("../../ereg_ws/%s/%s",gammaDir.Data(),fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
if(dobarrel)
{
TFile *fdin = TFile::Open("/afs/cern.ch/work/z/zhicaiz/public/ECALpro_MC_TreeForRegression/Gun_Pi0_Pt1To15_FlatPU0to50RAW_withHLT_80X_mcRun2_GEN-SIM-RAW_ALL_EcalNtp_ALL_EB_combine_test.root");//("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
else
{
TFile *fdin = TFile::Open("/afs/cern.ch/work/z/zhicaiz/public/ECALpro_MC_TreeForRegression/Gun_Pi0_Pt1To15_FlatPU0to50RAW_withHLT_80X_mcRun2_GEN-SIM-RAW_ALL_EcalNtp_ALL_EE_combine_test.root");//("root://eoscms.cern.ch///eos/cms/store/cmst3/user/bendavid/idTreesAug1/hgg-2013Final8TeV_ID_s12-h124gg-gf-v7n_noskim.root");
// TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterPreselNoSmear");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
}
//selection cuts for testing
//TCut selcut = "(STr2_enG1_true/cosh(STr2_Eta_1)>1.0) && (STr2_S4S9_1>0.75)";
TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)>60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_nocor/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
/*
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
*/
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(Entry$%10==0)";
TCut prescale10alt = "(Entry$%10==1)";
TCut prescale25 = "(Entry$%25==0)";
TCut prescale100 = "(Entry$%100==0)";
TCut prescale1000 = "(Entry$%1000==0)";
TCut evenevents = "(Entry$%2==0)";
TCut oddevents = "(Entry$%2==1)";
TCut prescale100alt = "(Entry$%100==1)";
TCut prescale1000alt = "(Entry$%1000==1)";
TCut prescale50alt = "(Entry$%50==1)";
TCut Events3_4 = "(Entry$%4==3)";
TCut Events1_4 = "(Entry$%4==1)";
TCut Events2_4 = "(Entry$%4==2)";
TCut Events0_4 = "(Entry$%4==0)";
TCut Events01_4 = "(Entry$%4<2)";
TCut Events23_4 = "(Entry$%4>1)";
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scetavar = ws->var("var_1");
RooRealVar *scphivar = ws->var("var_2");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
RooAbsReal *sigalphalim = ws->function("sigalphalim");
RooAbsReal *sigalpha2lim = ws->function("sigalpha2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
RooRealVar *alphavar = (RooRealVar*)hdataclone->addColumn(*sigalphalim);
RooRealVar *alpha2var = (RooRealVar*)hdataclone->addColumn(*sigalpha2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.pdf");
craw->SaveAs("RawE.png");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.pdf");
craw->SaveAs("RawElog.png");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.pdf");
cmean->SaveAs("mean.png");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.pdf");
cwidth->SaveAs("width.png");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.pdf");
cn->SaveAs("n.png");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.pdf");
cn2->SaveAs("n2.png");
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,5.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.pdf");
calpha->SaveAs("alpha.png");
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,5.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.pdf");
calpha2->SaveAs("alpha2.png");
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.pdf");
ceta->SaveAs("eta.png");
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw;// = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor;// = hdata->createHistogram("hecor",*ecorvar);
if (EEorEB == "EB")
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.8,1.1));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(800,0.8,1.1));
}
else
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(200,0.,2.));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(200,0.,2.));
}
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
heraw->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
hecor->GetXaxis()->SetRangeUser(0.0,1.5);
heraw->GetXaxis()->SetRangeUser(0.0,1.5);
/*if(EEorEB == "EE")
{
heraw->GetYaxis()->SetRangeUser(10.0,200.0);
hecor->GetYaxis()->SetRangeUser(10.0,200.0);
}
*/
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
double effsigma_cor, effsigma_raw, fwhm_cor, fwhm_raw;
if(EEorEB == "EB")
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
else
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
TCanvas *cresponse = new TCanvas;
gStyle->SetOptStat(0);
gStyle->SetPalette(107);
hecor->SetTitle("");
heraw->SetTitle("");
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
//show errSigma in the plot
TLegend *leg = new TLegend(0.1, 0.75, 0.7, 0.9);
leg->AddEntry(hecor,Form("E_{cor}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_cor, fwhm_cor),"l");
leg->AddEntry(heraw,Form("E_{raw}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_raw, fwhm_raw),"l");
leg->SetFillStyle(0);
leg->SetBorderSize(0);
// leg->SetTextColor(kRed);
leg->Draw();
cresponse->SaveAs("response.pdf");
cresponse->SaveAs("response.png");
cresponse->SetLogy();
cresponse->SaveAs("responselog.pdf");
cresponse->SaveAs("responselog.png");
// draw CCs vs eta and phi
TCanvas *c_eta = new TCanvas;
TH1 *h_eta = hdata->createHistogram("h_eta",*scetavar,Binning(100,-3.2,3.2));
h_eta->Draw("HIST");
c_eta->SaveAs("heta.pdf");
c_eta->SaveAs("heta.png");
TCanvas *c_phi = new TCanvas;
TH1 *h_phi = hdata->createHistogram("h_phi",*scphivar,Binning(100,-3.2,3.2));
h_phi->Draw("HIST");
c_phi->SaveAs("hphi.pdf");
c_phi->SaveAs("hphi.png");
RooRealVar *scetaiXvar = ws->var("var_6");
RooRealVar *scphiiYvar = ws->var("var_7");
if(EEorEB=="EB")
{
scetaiXvar->setRange(-90,90);
scetaiXvar->setBins(180);
scphiiYvar->setRange(0,360);
scphiiYvar->setBins(360);
}
else
{
scetaiXvar->setRange(0,50);
scetaiXvar->setBins(50);
scphiiYvar->setRange(0,50);
scphiiYvar->setBins(50);
}
ecorvar->setRange(0.5,1.5);
ecorvar->setBins(800);
rawvar->setRange(0.5,1.5);
rawvar->setBins(800);
TCanvas *c_cor_eta = new TCanvas;
TH2F *h_CC_eta = hdata->createHistogram(*scetaiXvar, *ecorvar, "","cor_vs_eta");
if(EEorEB=="EB")
{
h_CC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetXaxis()->SetTitle("iX");
}
h_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_eta->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta.pdf");
c_cor_eta->SaveAs("cor_vs_eta.png");
TCanvas *c_cor_phi = new TCanvas;
TH2F *h_CC_phi = hdata->createHistogram(*scphiiYvar, *ecorvar, "","cor_vs_phi");
if(EEorEB=="EB")
{
h_CC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetXaxis()->SetTitle("iY");
}
h_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_phi->Draw("COLZ");
c_cor_phi->SaveAs("cor_vs_phi.pdf");
c_cor_phi->SaveAs("cor_vs_phi.png");
TCanvas *c_raw_eta = new TCanvas;
TH2F *h_RC_eta = hdata->createHistogram(*scetaiXvar, *rawvar, "","raw_vs_eta");
if(EEorEB=="EB")
{
h_RC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_RC_eta->GetXaxis()->SetTitle("iX");
}
h_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_eta->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta.pdf");
c_raw_eta->SaveAs("raw_vs_eta.png");
TCanvas *c_raw_phi = new TCanvas;
TH2F *h_RC_phi = hdata->createHistogram(*scphiiYvar, *rawvar, "","raw_vs_phi");
if(EEorEB=="EB")
{
h_RC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_RC_phi->GetXaxis()->SetTitle("iY");
}
h_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_phi->Draw("COLZ");
c_raw_phi->SaveAs("raw_vs_phi.pdf");
c_raw_phi->SaveAs("raw_vs_phi.png");
//on2,5,20, etc
if(EEorEB == "EB")
{
TCanvas *myC_iCrystal_mod = new TCanvas;
RooRealVar *iEtaOn5var = ws->var("var_8");
iEtaOn5var->setRange(0,5);
iEtaOn5var->setBins(5);
TH2F *h_CC_iEtaOn5 = hdata->createHistogram(*iEtaOn5var, *ecorvar, "","cor_vs_iEtaOn5");
h_CC_iEtaOn5->GetXaxis()->SetTitle("iEtaOn5");
h_CC_iEtaOn5->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iEtaOn5->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn5.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn5.png");
TH2F *h_RC_iEtaOn5 = hdata->createHistogram(*iEtaOn5var, *rawvar, "","raw_vs_iEtaOn5");
h_RC_iEtaOn5->GetXaxis()->SetTitle("iEtaOn5");
h_RC_iEtaOn5->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iEtaOn5->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn5.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn5.png");
RooRealVar *iPhiOn2var = ws->var("var_9");
iPhiOn2var->setRange(0,2);
iPhiOn2var->setBins(2);
TH2F *h_CC_iPhiOn2 = hdata->createHistogram(*iPhiOn2var, *ecorvar, "","cor_vs_iPhiOn2");
h_CC_iPhiOn2->GetXaxis()->SetTitle("iPhiOn2");
h_CC_iPhiOn2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iPhiOn2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn2.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn2.png");
TH2F *h_RC_iPhiOn2 = hdata->createHistogram(*iPhiOn2var, *rawvar, "","raw_vs_iPhiOn2");
h_RC_iPhiOn2->GetXaxis()->SetTitle("iPhiOn2");
h_RC_iPhiOn2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iPhiOn2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn2.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn2.png");
RooRealVar *iPhiOn20var = ws->var("var_10");
iPhiOn20var->setRange(0,20);
iPhiOn20var->setBins(20);
TH2F *h_CC_iPhiOn20 = hdata->createHistogram(*iPhiOn20var, *ecorvar, "","cor_vs_iPhiOn20");
h_CC_iPhiOn20->GetXaxis()->SetTitle("iPhiOn20");
h_CC_iPhiOn20->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iPhiOn20->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn20.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iPhiOn20.png");
TH2F *h_RC_iPhiOn20 = hdata->createHistogram(*iPhiOn20var, *rawvar, "","raw_vs_iPhiOn20");
h_RC_iPhiOn20->GetXaxis()->SetTitle("iPhiOn20");
h_RC_iPhiOn20->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iPhiOn20->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn20.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iPhiOn20.png");
RooRealVar *iEtaOn2520var = ws->var("var_11");
iEtaOn2520var->setRange(-25,25);
iEtaOn2520var->setBins(50);
TH2F *h_CC_iEtaOn2520 = hdata->createHistogram(*iEtaOn2520var, *ecorvar, "","cor_vs_iEtaOn2520");
h_CC_iEtaOn2520->GetXaxis()->SetTitle("iEtaOn2520");
h_CC_iEtaOn2520->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_iEtaOn2520->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn2520.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_iEtaOn2520.png");
TH2F *h_RC_iEtaOn2520 = hdata->createHistogram(*iEtaOn2520var, *rawvar, "","raw_vs_iEtaOn2520");
h_RC_iEtaOn2520->GetXaxis()->SetTitle("iEtaOn2520");
h_RC_iEtaOn2520->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_iEtaOn2520->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn2520.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_iEtaOn2520.png");
}
// other variables
TCanvas *myC_variables = new TCanvas;
RooRealVar *Nxtalvar = ws->var("var_3");
Nxtalvar->setRange(0,10);
Nxtalvar->setBins(10);
TH2F *h_CC_Nxtal = hdata->createHistogram(*Nxtalvar, *ecorvar, "","cor_vs_Nxtal");
h_CC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_CC_Nxtal->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Nxtal.pdf");
myC_variables->SaveAs("cor_vs_Nxtal.png");
TH2F *h_RC_Nxtal = hdata->createHistogram(*Nxtalvar, *rawvar, "","raw_vs_Nxtal");
h_RC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_RC_Nxtal->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Nxtal.pdf");
myC_variables->SaveAs("raw_vs_Nxtal.png");
RooRealVar *S4S9var = ws->var("var_4");
int Nbins_S4S9 = 100;
double Low_S4S9 = 0.6;
double High_S4S9 = 1.0;
S4S9var->setRange(Low_S4S9,High_S4S9);
S4S9var->setBins(Nbins_S4S9);
TH2F *h_CC_S4S9 = hdata->createHistogram(*S4S9var, *ecorvar, "","cor_vs_S4S9");
h_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h_CC_S4S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S4S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S4S9.pdf");
myC_variables->SaveAs("cor_vs_S4S9.png");
TH2F *h_RC_S4S9 = hdata->createHistogram(*S4S9var, *rawvar, "","raw_vs_S4S9");
h_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h_RC_S4S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S4S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S4S9.pdf");
myC_variables->SaveAs("raw_vs_S4S9.png");
/*
RooRealVar *S1S9var = ws->var("var_5");
S1S9var->setRange(0.3,1.0);
S1S9var->setBins(100);
TH2F *h_CC_S1S9 = hdata->createHistogram(*S1S9var, *ecorvar, "","cor_vs_S1S9");
h_CC_S1S9->GetXaxis()->SetTitle("S1S9");
h_CC_S1S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S1S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S1S9.pdf");
TH2F *h_RC_S1S9 = hdata->createHistogram(*S1S9var, *rawvar, "","raw_vs_S1S9");
h_RC_S1S9->GetXaxis()->SetTitle("S1S9");
h_RC_S1S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S1S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S1S9.pdf");
*/
RooRealVar *S2S9var = ws->var("var_5");
int Nbins_S2S9 = 100;
double Low_S2S9 = 0.5;
double High_S2S9 = 1.0;
S2S9var->setRange(Low_S2S9,High_S2S9);
S2S9var->setBins(Nbins_S2S9);
TH2F *h_CC_S2S9 = hdata->createHistogram(*S2S9var, *ecorvar, "","cor_vs_S2S9");
h_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h_CC_S2S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S2S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S2S9.pdf");
myC_variables->SaveAs("cor_vs_S2S9.png");
TH2F *h_RC_S2S9 = hdata->createHistogram(*S2S9var, *rawvar, "","raw_vs_S2S9");
h_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h_RC_S2S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S2S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S2S9.pdf");
myC_variables->SaveAs("raw_vs_S2S9.png");
TH2F *h_S2S9_eta = hdata->createHistogram(*scetaiXvar, *S2S9var, "","S2S9_vs_eta");
h_S2S9_eta->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S2S9_eta->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_eta.pdf");
myC_variables->SaveAs("S2S9_vs_eta.png");
TH2F *h_S4S9_eta = hdata->createHistogram(*scetaiXvar, *S4S9var, "","S4S9_vs_eta");
h_S4S9_eta->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S4S9_eta->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_eta.pdf");
myC_variables->SaveAs("S4S9_vs_eta.png");
TH2F *h_S2S9_phi = hdata->createHistogram(*scphiiYvar, *S2S9var, "","S2S9_vs_phi");
h_S2S9_phi->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S2S9_phi->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_phi.pdf");
myC_variables->SaveAs("S2S9_vs_phi.png");
TH2F *h_S4S9_phi = hdata->createHistogram(*scphiiYvar, *S4S9var, "","S4S9_vs_phi");
h_S4S9_phi->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S4S9_phi->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_phi.pdf");
myC_variables->SaveAs("S4S9_vs_phi.png");
/*
RooRealVar *DeltaRvar = ws->var("var_6");
DeltaRvar->setRange(0.0,0.1);
DeltaRvar->setBins(100);
TH2F *h_CC_DeltaR = hdata->createHistogram(*DeltaRvar, *ecorvar, "","cor_vs_DeltaR");
h_CC_DeltaR->GetXaxis()->SetTitle("#Delta R");
h_CC_DeltaR->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_DeltaR->Draw("COLZ");
myC_variables->SaveAs("cor_vs_DeltaR.pdf");
myC_variables->SaveAs("cor_vs_DeltaR.png");
TH2F *h_RC_DeltaR = hdata->createHistogram(*DeltaRvar, *rawvar, "","raw_vs_DeltaR");
h_RC_DeltaR->GetXaxis()->SetTitle("#Delta R");
h_RC_DeltaR->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_DeltaR->Draw("COLZ");
myC_variables->SaveAs("raw_vs_DeltaR.pdf");
myC_variables->SaveAs("raw_vs_DeltaR.png");
*/
if(EEorEB=="EE")
{
/* RooRealVar *Es_e1var = ws->var("var_9");
Es_e1var->setRange(0.0,200.0);
Es_e1var->setBins(1000);
TH2F *h_CC_Es_e1 = hdata->createHistogram(*Es_e1var, *ecorvar, "","cor_vs_Es_e1");
h_CC_Es_e1->GetXaxis()->SetTitle("Es_e1");
h_CC_Es_e1->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Es_e1->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Es_e1.pdf");
myC_variables->SaveAs("cor_vs_Es_e1.png");
TH2F *h_RC_Es_e1 = hdata->createHistogram(*Es_e1var, *rawvar, "","raw_vs_Es_e1");
h_RC_Es_e1->GetXaxis()->SetTitle("Es_e1");
h_RC_Es_e1->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Es_e1->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Es_e1.pdf");
myC_variables->SaveAs("raw_vs_Es_e1.png");
RooRealVar *Es_e2var = ws->var("var_10");
Es_e2var->setRange(0.0,200.0);
Es_e2var->setBins(1000);
TH2F *h_CC_Es_e2 = hdata->createHistogram(*Es_e2var, *ecorvar, "","cor_vs_Es_e2");
h_CC_Es_e2->GetXaxis()->SetTitle("Es_e2");
h_CC_Es_e2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Es_e2->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Es_e2.pdf");
myC_variables->SaveAs("cor_vs_Es_e2.png");
TH2F *h_RC_Es_e2 = hdata->createHistogram(*Es_e2var, *rawvar, "","raw_vs_Es_e2");
h_RC_Es_e2->GetXaxis()->SetTitle("Es_e2");
h_RC_Es_e2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Es_e2->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Es_e2.pdf");
myC_variables->SaveAs("raw_vs_Es_e2.png");
*/
}
TProfile *p_CC_eta = h_CC_eta->ProfileX("p_CC_eta",1,-1,"s");
p_CC_eta->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB == "EB")
{
// p_CC_eta->GetYaxis()->SetRangeUser(0.85,1.0);
// p_CC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_eta->SetTitle("");
p_CC_eta->Draw();
myC_variables->SaveAs("profile_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_cor_vs_eta.png");
TProfile *p_RC_eta = h_RC_eta->ProfileX("p_RC_eta",1,-1,"s");
p_RC_eta->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB=="EB")
{
// p_RC_eta->GetYaxis()->SetRangeUser(0.80,0.95);
// p_RC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_eta->SetTitle("");
p_RC_eta->Draw();
myC_variables->SaveAs("profile_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_raw_vs_eta.png");
int Nbins_iEta = EEorEB=="EB" ? 180 : 50;
int nLow_iEta = EEorEB=="EB" ? -90 : 0;
int nHigh_iEta = EEorEB=="EB" ? 90 : 50;
TH1F *h1_RC_eta = new TH1F("h1_RC_eta","h1_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_RC_eta->SetBinContent(i,p_RC_eta->GetBinError(i));
}
h1_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_RC_eta->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_eta->SetTitle("");
h1_RC_eta->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.png");
TH1F *h1_CC_eta = new TH1F("h1_CC_eta","h1_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_CC_eta->SetBinContent(i,p_CC_eta->GetBinError(i));
}
h1_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_CC_eta->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_eta->SetTitle("");
h1_CC_eta->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.png");
TProfile *p_CC_phi = h_CC_phi->ProfileX("p_CC_phi",1,-1,"s");
p_CC_phi->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB == "EB")
{
// p_CC_phi->GetYaxis()->SetRangeUser(0.94,1.00);
}
p_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_phi->SetTitle("");
p_CC_phi->Draw();
myC_variables->SaveAs("profile_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_cor_vs_phi.png");
TProfile *p_RC_phi = h_RC_phi->ProfileX("p_RC_phi",1,-1,"s");
p_RC_phi->GetYaxis()->SetRangeUser(0.7,1.2);
if(EEorEB=="EB")
{
// p_RC_phi->GetYaxis()->SetRangeUser(0.89,0.95);
}
p_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_phi->SetTitle("");
p_RC_phi->Draw();
myC_variables->SaveAs("profile_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_raw_vs_phi.png");
int Nbins_iPhi = EEorEB=="EB" ? 360 : 50;
int nLow_iPhi = EEorEB=="EB" ? 0 : 0;
int nHigh_iPhi = EEorEB=="EB" ? 360 : 50;
TH1F *h1_RC_phi = new TH1F("h1_RC_phi","h1_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_RC_phi->SetBinContent(i,p_RC_phi->GetBinError(i));
}
h1_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_RC_phi->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_phi->SetTitle("");
h1_RC_phi->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.png");
TH1F *h1_CC_phi = new TH1F("h1_CC_phi","h1_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_CC_phi->SetBinContent(i,p_CC_phi->GetBinError(i));
}
h1_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_CC_phi->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_phi->SetTitle("");
h1_CC_phi->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.png");
// FWHM over sigma_eff vs. eta/phi
TH1F *h1_FoverS_RC_phi = new TH1F("h1_FoverS_RC_phi","h1_FoverS_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_CC_phi = new TH1F("h1_FoverS_CC_phi","h1_FoverS_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_RC_eta = new TH1F("h1_FoverS_RC_eta","h1_FoverS_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_eta = new TH1F("h1_FoverS_CC_eta","h1_FoverS_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_S2S9 = new TH1F("h1_FoverS_CC_S2S9","h1_FoverS_CC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_RC_S2S9 = new TH1F("h1_FoverS_RC_S2S9","h1_FoverS_RC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_CC_S4S9 = new TH1F("h1_FoverS_CC_S4S9","h1_FoverS_CC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
TH1F *h1_FoverS_RC_S4S9 = new TH1F("h1_FoverS_RC_S4S9","h1_FoverS_RC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
float FWHMoverSigmaEff = 0.0;
TH1F *h_tmp_rawvar = new TH1F("tmp_rawvar","tmp_rawvar",800,0.5,1.5);
TH1F *h_tmp_corvar = new TH1F("tmp_corvar","tmp_corvar",800,0.5,1.5);
for(int i=1;i<=Nbins_iPhi;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_phi->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_phi->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_phi->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_phi->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_CC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_phi->SetTitle("");
h1_FoverS_CC_phi->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.png");
h1_FoverS_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_RC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_phi->SetTitle("");
h1_FoverS_RC_phi->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.png");
for(int i=1;i<=Nbins_iEta;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_eta->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_eta->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_eta->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_eta->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_CC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_eta->SetTitle("");
h1_FoverS_CC_eta->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.png");
h1_FoverS_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_RC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_eta->SetTitle("");
h1_FoverS_RC_eta->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.png");
for(int i=1;i<=Nbins_S2S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S2S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S2S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_CC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S2S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S2S9->SetTitle("");
h1_FoverS_CC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.png");
h1_FoverS_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_RC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S2S9->SetTitle("");
h1_FoverS_RC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.png");
for(int i=1;i<=Nbins_S4S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S4S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S4S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_CC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S4S9->GetYaxis()->SetRangeUser(0.0,1.0);
h1_FoverS_CC_S4S9->SetTitle("");
h1_FoverS_CC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.png");
h1_FoverS_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_RC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S4S9->SetTitle("");
h1_FoverS_RC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.png");
printf("calc effsigma\n");
std::cout<<"_"<<EEorEB<<std::endl;
printf("corrected curve effSigma= %5f, FWHM=%5f \n",effsigma_cor, fwhm_cor);
printf("raw curve effSigma= %5f FWHM=%5f \n",effsigma_raw, fwhm_raw);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void fitlambda(bool realdata=1){
gSystem->Load("libRooFit");
using namespace RooFit;
TFile *data;
if (realdata==1) data=new TFile("./RecoRoutines_Z-selection_data36pb.rew2.corr1.root","read");
if (realdata==0) data=new TFile("./RecoRoutines_Z-selection_ZJets_TuneZ2_7TeV_alpgen_tauola.rew2.corr1.root","read");
TString dir="MuPtScale0toinf/";
TString title="dimuonstree";
TTree *tree = (TTree*)data->Get((dir+title).Data());
RooRealVar RMpPt("RMpPt","RMpPt",0,400);
RooRealVar RMpEta("RMpEta","RMpEta",-10,10);
RooRealVar RMpPhi("RMpPhi","RMpPhi",-10,10);
RooRealVar RMmPt("RMmPt","RMmPt",0,400);
RooRealVar RMmEta("RMmEta","RMmEta",-10,10);
RooRealVar RMmPhi("RMmPhi","RMmPhi",-10,10);
RooRealVar RZmass("RZmass","RZmass",81.2,101.2);
RooDataSet dataset("dataset","dataset",RooArgSet(RMpPt,RMpEta,RMpPhi,RMmPt,RMmEta,RMmPhi,RZmass),StoreError(RooArgSet(RZmass)));
Double_t MpPt ;
Double_t MpEta;
Double_t MpPhi;
Double_t MmPt;
Double_t MmEta;
Double_t MmPhi;
Double_t Zmass;
Double_t EvWeight;
tree->SetBranchAddress("MpPt",&MpPt);
tree->SetBranchAddress("MpEta",&MpEta);
tree->SetBranchAddress("MpPhi",&MpPhi);
tree->SetBranchAddress("MmPt",&MmPt);
tree->SetBranchAddress("MmEta",&MmEta);
tree->SetBranchAddress("MmPhi",&MmPhi);
tree->SetBranchAddress("Zmass",&Zmass);
tree->SetBranchAddress("EvWeight",&EvWeight);
Long64_t nentries = tree->GetEntries();
for (Long64_t i=0;i<nentries;i++) {
tree->GetEntry(i);
RMpPt=MpPt;
RMpEta=MpEta;
RMpPhi=MpPhi;
RMmPt=MmPt;
RMmEta=MmEta;
RMmPhi=MmPhi;
RZmass=Zmass;
RZmass.setError(3);
dataset.add(RooArgSet(RMpPt,RMpEta,RMpPhi,RMmPt,RMmEta,RMmPhi,RZmass),EvWeight);
}
RooRealVar mean("mean","mean",91.2,85.0,95.0);
RooRealVar cs01("cs01","cs01",0,-0.00,0.00);
RooRealVar cs02("cs02","cs02",0,-0.00,0.00);
RooRealVar ca01("ca01","ca01",0,-0.00,0.00);
RooRealVar ca02("ca02","ca02",0,-0.05,0.05);
RooRealVar cas1("cas1","cas1",0,-0.00,0.00);
RooRealVar cas2("cas2","cas2",0,-0.05,0.05);
RooRealVar phase("phase","phase",0,-3.14,3.14);
RooRealVar cae1("cae1","cae1",0,-0.00,0.00);
RooRealVar caeB2("caeB2","caeB2",0,-0.05,0.05);
RooRealVar caeE2("caeE2","caeE2",0,-0.05,0.05);
RooArgSet deps(RMpPt,RMmPt,RMpPhi,RMmPhi,RMpEta,RMmEta);
deps.add(mean);
deps.add(cs01);
deps.add(cs02);
deps.add(ca01);
deps.add(ca02);
deps.add(cas1);
deps.add(cas2);
deps.add(phase);
deps.add(cae1);
deps.add(caeB2);
deps.add(caeE2);
// corrfunction:
// dp/p = CS01+CS02*p+charge*(CA01+CA02*p)+charge*(CAS1+CAS2*p)*sin(phi+PHASE)+charge*(CAE1+CAE2*p)*eta
// 0.5*(caeB2+caeE2+TMath::Sign(caeB2,1-abs(eta))+TMath::Sign(caeE2,abs(eta)-1))
RooFormulaVar model("model","mean+mean/2*(cs01+cs02*RMpPt/100+(ca01+ca02*RMpPt/100)+(cas1+cas2*RMpPt/100)*sin(RMpPhi+phase)+\
(cae1+0.5*(caeB2+caeE2+TMath::Sign(caeB2,0.5-abs(RMpEta))+TMath::Sign(caeE2,abs(RMpEta)-0.5))*RMpPt/100)*RMpEta)\
+mean/2*(cs01+cs02*RMmPt/100-(ca01+ca02*RMmPt/100)-(cas1+cas2*RMmPt/100)*sin(RMmPhi+phase)-\
(cae1+0.5*(caeB2+caeE2+TMath::Sign(caeB2,0.5-abs(RMmEta))+TMath::Sign(caeE2,abs(RMmEta)-0.5))*RMmPt/100)*RMmEta)",deps);
RooFitResult *r = model.chi2FitTo(dataset,YVar(RZmass),Save());
r->Print();
RooPlot* frame = RMpPhi.frame() ;
dataset.plotOnXY(frame,YVar(RZmass));
model.plotOn(frame);
frame->Draw();
};
RooSimultaneous *SignalPDFs(TString url="EventSummaries.root",TString chSelector="")
{
gStyle->SetOptStat(0);
TCanvas *c = new TCanvas("signalpdfs","Signal PDFs");
//the mass points
typedef std::pair<TString,Float_t> MassPoint_t;
std::vector<MassPoint_t> MassPointCollection;
MassPointCollection.push_back( MassPoint_t("TTJets_mass_161v5",161.5) );
MassPointCollection.push_back( MassPoint_t("TTJets_mass_163v5",163.5) );
// MassPointCollection.push_back( MassPoint_t("TTJets_mass_166v5",166.5) );
MassPointCollection.push_back( MassPoint_t("TTJets_mass_169v5",169.5) );
MassPointCollection.push_back( MassPoint_t("TTJets", 172.5) );
MassPointCollection.push_back( MassPoint_t("TTJets_mass_175v5",175.5) );
MassPointCollection.push_back( MassPoint_t("TTJets_mass_178v5",178.5) );
MassPointCollection.push_back( MassPoint_t("TTJets_mass181v5", 181.5) );
MassPointCollection.push_back( MassPoint_t("TTJets_mass184v5", 184.5) );
std::map<std::string,TH1*> hmap;
//get pdfs from file
RooCategory sample("signal","") ;
TFile *f = TFile::Open(url);
for(size_t ipt=0; ipt<MassPointCollection.size(); ipt++)
{
TString sName("m"); sName += (ipt+1);
TString tname=MassPointCollection[ipt].first + "/data";
TTree *t = (TTree *) f->Get(tname);
if(t==0) continue;
t->Draw("evmeasurements[0]>>hmass(80,100,500)","evmeasurements[0]>0" + chSelector);
TH1D *h = (TH1D*) gDirectory->Get("hmass");
if(h==0) continue;
h = (TH1D *) h->Clone(sName);
h->SetDirectory(0);
h->GetYaxis()->SetTitle("Events / (5 GeV/c^{2})");
h->GetXaxis()->SetTitle("Mass [GeV/c^{2}]");
h->GetXaxis()->SetTitleOffset(0.8);
h->GetYaxis()->SetTitleOffset(0.8);
char titbuf[20];
sprintf(titbuf,"m=%3.1lf",MassPointCollection[ipt].second);
h->SetTitle(titbuf);
sample.defineType(TString(sName));
hmap[sName.Data()] = h;
}
f->Close();
delete c;
// divide the binned data in categories according to the generated top quark mass
RooRealVar mass("m","Mass", 100, 500);
RooDataHist combData("combData", "combined data",mass, sample, hmap );
//the parameters to fit and the variable
RooRealVar g_mean_slope("#mu_{G}(slope)","g_mean_slope",0.01,0.,1.);
RooRealVar g_mean_shift("#mu_{G}(intercept)","g_mean_shift",162,100,180);
RooRealVar g_sigma_slope("#sigma_{G}(slope)","g_sigma_slope",0.01,0.,1.);
RooRealVar g_sigma_shift("#sigma_{G}(intercept)","g_sigma_shift",10,0.,25);
RooRealVar l_mean_slope("mpv_{L}(slope)","l_mean_slope",0.,0.,1.);//1,0,10);
RooRealVar l_mean_shift("mpv_{L}(intercept)","l_mean_shift",212,150,250);
RooRealVar l_sigma_slope("#sigma_{L}(slope)","l_sigma_slope",0.,0.,1.);//1,0,10);
RooRealVar l_sigma_shift("#sigma_{L}(intercept)","l_sigma_shift",10,0,25);
RooRealVar massfrac_slope("#alpha(slope)","massfrac_slope",0,0,0.01);
RooRealVar massfrac_shift("#alpha(intercept)","massfrac_shift",0.38,0.,1.);
//build the prototype pdf
RooRealVar topmass( "mtop","mtop",100,300);
RooFormulaVar g_mean( "g_mean", "(@0-172)*@1+@2", RooArgSet(topmass,g_mean_slope,g_mean_shift));
RooFormulaVar g_sigma( "g_sigma", "(@0-172)*@1+@2", RooArgSet(topmass,g_sigma_slope,g_sigma_shift));
RooGaussian gaus("gaus", "Mass component 1", mass, g_mean, g_sigma);
RooFormulaVar l_mean( "l_mean", "(@0-172)*@1+@2", RooArgSet(topmass,l_mean_slope,l_mean_shift));
RooFormulaVar l_sigma( "l_sigma", "(@0-172)*@1+@2", RooArgSet(topmass,l_sigma_slope,l_sigma_shift));
RooLandau lan("lan", "Mass component 2", mass, l_mean, l_sigma);
RooFormulaVar massfrac( "#alpha", "(@0-172)*@1+@2", RooArgSet(topmass,massfrac_slope,massfrac_shift));
RooAddPdf massmodel("model","Model",RooArgList(lan,gaus),massfrac);
//RooNumConvPdf massmodel("model","Model",topmass,lan,gaus);
//now split per categories
RooSimPdfBuilder builder(massmodel) ;
RooArgSet* config = builder.createProtoBuildConfig() ;
config->setStringValue("physModels","model"); // Name of the PDF we are going to work with
config->setStringValue("splitCats","signal"); // Category used to differentiate sub-datasets
config->setStringValue("model","signal : mtop"); // Prescription to taylor PDF parameters mtop for each subset in signal
RooSimultaneous* simPdf = builder.buildPdf(*config,&combData) ;
config = simPdf->getParameters(combData);
for(size_t ipt=0; ipt<MassPointCollection.size(); ipt++)
{
TString sName("m"); sName+=(ipt+1);
Float_t imass=MassPointCollection[ipt].second;
(((RooRealVar &)(*config)["mtop_"+sName])).setRange(imass,imass);
(((RooRealVar &)(*config)["mtop_"+sName])).setVal(imass);
}
//fit to data
simPdf->fitTo(combData,Range(100.,400.));
//display
for(size_t ipt=0; ipt<MassPointCollection.size(); ipt++)
{
if(ipt%5==0)
{
TString name("SignalPDFs_"); name+=ipt;
c = new TCanvas(name,name);
c->SetBorderSize(0);
c->SetFillStyle(0);
c->SetFillColor(0);
c->SetWindowSize(1750,350);
c->Clear();
c->Divide(5,1);
}
TPad *p = (TPad *)c->cd(ipt%5+1);
p->SetGridx();
p->SetGridy();
TString procName("m"); procName += (ipt+1);
char buf[100];
sprintf(buf,"m_{t}=%3.1lf GeV/c^{2}",MassPointCollection[ipt].second);
RooPlot* frame = mass.frame(Title(buf));
RooDataSet* dataslice = (RooDataSet *)combData.reduce("signal==signal::"+procName);
dataslice->plotOn(frame,DataError(RooAbsData::SumW2));
RooCategory newCat(procName,procName);
simPdf->plotOn(frame,Slice(newCat),ProjWData(mass,*dataslice));
frame->GetYaxis()->SetTitleOffset(1.0);
frame->GetYaxis()->SetTitle("Events");
frame->GetXaxis()->SetTitleOffset(0.8);
frame->GetXaxis()->SetTitle("Reconstructed Mass [GeV/c^{2}]");
frame->Draw();
TPaveText *pt = new TPaveText(0.75,0.85,0.97,0.95,"brNDC");
pt->SetBorderSize(0);
pt->SetFillColor(0);
pt->SetFillStyle(0);
char buf2[50];
sprintf(buf2,"%3.1lf GeV/c^{2}",MassPointCollection[ipt].second);
pt->AddText(buf2);
pt->Draw();
}
return simPdf;
}
void fit_and_weights_norm(){
gROOT->ProcessLine(".x ~/cern/scripts/lhcbStyle.C");
//lhcbStyle();
gStyle->SetLabelSize(0.05,"x");
gStyle->SetLabelSize(0.05,"y");
gStyle->SetTitleSize(0.05,"x");
gStyle->SetPaperSize(20,26);
gStyle->SetPadTopMargin(0.0);
gStyle->SetPadRightMargin(0.05); // increase for colz plots
gStyle->SetPadBottomMargin(0.0);
gStyle->SetPadLeftMargin(0.14);
gStyle->SetTitleH(0.01);
//
const std::string filename("/afs/cern.ch/work/a/apmorris/private/cern/ntuples/new_tuples/normalisation_samples/Lb2JpsipK_2011_2012_signal_withbdt_cut_05.root");
const std::string treename = "withbdt";
const std::string out_file_mass("~/cern/plots/fitting/Lb2JpsipK_2011_2012_mass_fit_after_bdtg3_05.png");
//
TFile* file = TFile::Open( filename.c_str() );
if( !file ) std::cout << "file " << filename << " does not exist" << std::endl;
TTree* tree = (TTree*)file->Get( treename.c_str() );
if( !tree ) std::cout << "tree " << treename << " does not exist" << std::endl;
// -- signal, mass shape
RooRealVar Lambda_b0_DTF_MASS_constr1("Lambda_b0_DTF_MASS_constr1","m(#chi_{c}pK^{-})", 5550., 5700., "MeV/c^{2}");
RooRealVar Jpsi_M("Jpsi_M","m(#mu#mu)", 3000., 3200., "MeV/c^{2}");
//RooRealVar chi_c_M("chi_c_M","m(J/#psi#gamma)", 3400., 3700., "MeV/c^{2}");
RooRealVar mean("mean","mean", 5630., 5610., 5650.);
RooRealVar sigma1("sigma1","sigma1", 10., 1., 100.);
RooRealVar sigma2("sigma2","sigma2", 30.0, 5.0, 300.0);
RooRealVar alpha1("alpha1","alpha1", 1.0, 0.5, 5.0);
RooRealVar n1("n1","n1", 1.8, 0.2, 15.0);
RooRealVar alpha2("alpha2","alpha2", -0.5, -5.5, 0.0);
RooRealVar n2("n2","n2", 0.7, 0.2, 10.0);
//RooRealVar bkgcat_chic("bkgcat_chic","bkgcat_chic", 0, 100);
RooRealVar bdtg3("bdtg3", "bdtg3", -1.0, 1.0); //
RooRealVar frac2("frac2","frac2", 0.3, 0., 1.);
Lambda_b0_DTF_MASS_constr1.setBins(75);
RooGaussian gauss1("gauss1","gauss1", Lambda_b0_DTF_MASS_constr1, mean, sigma1);
RooGaussian gauss2("gauss2","gauss2", Lambda_b0_DTF_MASS_constr1, mean, sigma2);
RooCBShape cb1("cb1","cb1", Lambda_b0_DTF_MASS_constr1, mean, sigma1, alpha1, n1);
RooCBShape cb2("cb2","cb2", Lambda_b0_DTF_MASS_constr1, mean, sigma2, alpha2, n2);
RooAddPdf sig("sig", "sig", RooArgList(cb1, cb2), RooArgList( frac2 ));
RooRealVar cbRatio("cbRatio","cb Ratio", 0.8, 0.1, 1.0);
RooRealVar sigYield("sigYield","sig Yield", 4e2, 1e1, 1e4);
RooRealVar bgYield("bgYield","bg Yield", 1e2, 1e0, 5e5);
//put in values from fit_MC here <<--- DON'T FORGET TO CHANGE THESE IF THE FIT CHANGES!!!
/*
EXT PARAMETER INTERNAL INTERNAL
NO. NAME VALUE ERROR STEP SIZE VALUE
1 alpha1 1.74154e+00 3.36750e-02 1.24897e-04 -4.64754e-01
2 alpha2 -2.02379e+00 6.38694e-02 1.18078e-04 2.87434e+00
3 cbRatio 3.81630e-01 2.53217e-02 1.04396e-03 -3.83487e-01
4 mean 5.61983e+03 1.06900e-02 5.57074e-05 -9.73350e-02
5 n1 3.61886e+00 1.29299e-01 2.50836e-04 -5.68053e-01
6 n2 3.28978e+00 1.59452e-01 3.00100e-04 -3.78398e-01
7 sigma1 7.37006e+00 1.49989e-01 2.60360e-05 -1.05787e+00
8 sigma2 4.90330e+00 4.88847e-02 5.78092e-06 -1.44570e+00
*/
alpha1.setVal( 1.74154e+00 );
alpha2.setVal( -2.02379e+00 );
n1.setVal( 3.61886e+00 );
n2.setVal( 3.28978e+00 );
frac2.setVal( 3.81630e-01 );
sigma1.setVal( 7.37006e+00 );
sigma2.setVal( 4.90330e+00 );
alpha1.setConstant( true );
alpha2.setConstant( true );
frac2.setConstant( true );
n1.setConstant( true );
n2.setConstant( true );
sigma1.setConstant( true );
sigma2.setConstant( true );
// -- bg, mass shape
RooRealVar a1("a1","a1", -0.1, -0.5, 0.5);
RooChebychev comb("comb","comb", Lambda_b0_DTF_MASS_constr1, a1);
RooRealVar mean3("mean3","mean3", 5560., 5500., 5600.);
RooRealVar sigma3("sigma3","sigma3", 5., 1., 10.);
RooRealVar frac3("frac3","frac", 0.2, 0.0, 0.3);
RooGaussian gauss3("gauss3","gauss3", Lambda_b0_DTF_MASS_constr1, mean3, sigma3);
RooAddPdf bg("bg","bg", RooArgList(gauss3, comb), RooArgList(frac3));
// -- add signal & bg
RooAddPdf pdf("pdf", "pdf", RooArgList(sig, comb), RooArgList( sigYield, bgYield));
RooArgSet obs;
obs.add(Lambda_b0_DTF_MASS_constr1);
obs.add(Jpsi_M);
//obs.add(chi_c_M);
//obs.add(proton_ProbNNp);
//obs.add(proton_ProbNNk);
//obs.add(kaon_ProbNNp);
//obs.add(kaon_ProbNNk);
RooDataSet ds("ds","ds", obs, RooFit::Import(*tree));
RooPlot* plot = Lambda_b0_DTF_MASS_constr1.frame();
RooFitResult * result = pdf.fitTo( ds, RooFit::Extended() );
ds.plotOn( plot );
pdf.plotOn( plot );
RooPlot* plotPullMass = Lambda_b0_DTF_MASS_constr1.frame();
plotPullMass->addPlotable( plot->pullHist() );
//plotPullMass->SetMinimum();
//plotPullMass->SetMaximum();
TCanvas* c = new TCanvas();
TPad* pad1 = new TPad("pad1","pad1", 0, 0.3, 1, 1.0);
pad1->SetBottomMargin(0.0);
pad1->SetTopMargin(0.01);
pad1->Draw();
c->cd();
TPad* pad2 = new TPad("pad2","pad2", 0, 0., 1, 0.3);
pad2->SetBottomMargin(0.0);
pad2->SetTopMargin(0.0);
pad2->Draw();
pdf.plotOn( plot, RooFit::Components( sig ), RooFit::LineColor( kTeal ), RooFit::LineStyle(kDashed) );
pdf.plotOn( plot, RooFit::Components( comb ), RooFit::LineColor( kOrange ), RooFit::LineStyle(kDashed) );
pdf.plotOn( plot, RooFit::Components( gauss3 ), RooFit::LineColor( kViolet ), RooFit::LineStyle(kDashed) );
pad1->cd();
plot->Draw();
pad2->cd();
plotPullMass->Draw("AP");
c->SaveAs(out_file_mass.c_str());
/*
RooStats::SPlot* sData = new RooStats::SPlot("sData","An SPlot",
ds, &pdf, RooArgList(sigYield, bgYield) );
RooDataSet * dataw_z = new RooDataSet(ds.GetName(),ds.GetTitle(),&ds,*(ds.get()),0,"sigYield_sw") ;
TTree *tree_data = (TTree*)dataw_z->tree();
TFile * newfile = TFile::Open("/afs/cern.ch/work/a/apmorris/private/cern/ntuples/new_tuples/weighted_data.root","RECREATE");
tree_data->Write();
newfile->Close();
*/
/*
TCanvas* d = new TCanvas();
RooPlot* w_chi_c_Mp = chi_c_Mp.frame();
dataw_z->plotOn(w_chi_c_Mp, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ;
w_chi_c_Mp->Draw();
d->SaveAs("m_chicp_sweighted.png");
TCanvas* e = new TCanvas();
RooPlot* w_mass_pK = mass_pK.frame();
dataw_z->plotOn(w_mass_pK, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ;
w_mass_pK->Draw();
e->SaveAs("m_pK_sweighted.png");
*/
/*
TCanvas* f = new TCanvas();
RooPlot* w_Jpsi_M = Jpsi_M.frame();
dataw_z->plotOn(w_Jpsi_M, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ;
w_Jpsi_M->Draw();
f->SaveAs("~/cern/plots/m_Jpsi_sweighted.png");
TCanvas* g = new TCanvas();
RooPlot* w_chi_c_M = chi_c_M.frame();
dataw_z->plotOn(w_chi_c_M, RooFit::DataError(RooAbsData::SumW2), RooFit::Binning(20)) ;
w_chi_c_M->Draw();
g->SaveAs("~/cern/plots/m_Chic_sweighted.png");
*/
}
RooWorkspace* makefit(char* filename, char* FitTitle, char* Outfile, double minMass, double maxMass, double mean_bw, double gamma_bw, double cutoff_cb, const char* plotOpt, const int nbins) {
gROOT->ProcessLine(".L tdrstyle.C");
setTDRStyle();
gStyle->SetPadRightMargin(0.05);
//Create Data Set
RooRealVar mass("mass","m(EE)",minMass,maxMass,"GeV/c^{2}");
RooDataSet *data = RooDataSet::read(filename,RooArgSet(mass));
//====================== Parameters===========================
//Crystal Ball parameters
RooRealVar cbBias ("#Deltam_{CB}", "CB Bias", -.01, -10, 10, "GeV/c^{2}");
RooRealVar cbSigma("sigma_{CB}", "CB Width", 1.7, 0.02, 5.0, "GeV/c^{2}");
RooRealVar cbCut ("a_{CB}","CB Cut", 1.05, 0.1, 3.0);
RooRealVar cbPower("n_{CB}","CB Order", 2.45, 0.1, 20.0);
cbCut.setVal(cutoff_cb);
//Breit_Wigner parameters
RooRealVar bwMean("m_{Z}","BW Mean", 91.1876, "GeV/c^{2}");
bwMean.setVal(mean_bw);
RooRealVar bwWidth("#Gamma_{Z}", "BW Width", 2.4952, "GeV/c^{2}");
bwWidth.setVal(gamma_bw);
// Fix the Breit-Wigner parameters to PDG values
bwMean.setConstant(kTRUE);
bwWidth.setConstant(kTRUE);
// Exponential Background parameters
RooRealVar expRate("#lambda_{exp}", "Exponential Rate", -0.064, -1, 1);
RooRealVar c0("c_{0}", "c0", 1., 0., 50.);
//Number of Signal and Background events
RooRealVar nsig("N_{S}", "# signal events", 524, 0.1, 10000000000.);
RooRealVar nbkg("N_{B}", "# background events", 43, 1., 10000000.);
//============================ P.D.F.s=============================
// Mass signal for two decay electrons p.d.f.
RooBreitWigner bw("bw", "bw", mass, bwMean, bwWidth);
RooCBShape cball("cball", "Crystal Ball", mass, cbBias, cbSigma, cbCut, cbPower);
RooFFTConvPdf BWxCB("BWxCB", "bw X crystal ball", mass, bw, cball);
// Mass background p.d.f.
RooExponential bg("bg", "exp. background", mass, expRate);
// Mass model for signal electrons p.d.f.
RooAddPdf model("model", "signal", RooArgList(BWxCB), RooArgList(nsig));
TStopwatch t ;
t.Start() ;
model.fitTo(*data,FitOptions("mh"),Optimize(0),Timer(1));
t.Print() ;
TCanvas* c = new TCanvas("c","Unbinned Invariant Mass Fit", 0,0,800,600);
//========================== Plotting ============================
//Create a frame
RooPlot* plot = mass.frame(Range(minMass,maxMass),Bins(nbins));
data->plotOn(plot);
model.plotOn(plot);
model.paramOn(plot, Format(plotOpt, AutoPrecision(1)), Parameters(RooArgSet(cbBias, cbSigma, cbCut, cbPower, bwMean, bwWidth, expRate, nsig, nbkg)), Layout(0.66,0.63));
plot->getAttText()->SetTextSize(.03);
plot->Draw();
// Print Fit Values
TLatex *tex = new TLatex();
tex->SetNDC();
tex->SetTextSize(.04);
tex->SetTextFont(2);
tex->DrawLatex(0.195,0.875, "CMS ECAL, 2012");
tex->Draw();
tex->SetTextSize(0.022);
tex->DrawLatex(0.195, 0.81, FitTitle);
tex->DrawLatex(0.195, 0.75, "Z #rightarrow ee^{+}");
tex->SetTextSize(0.024);
tex->DrawLatex(0.645, 0.59, Form("BW Mean = %.2f GeV/c^{2}", bwMean.getVal()));
tex->DrawLatex(0.645, 0.54, Form("BW #sigma = %.2f GeV/c^{2}", bwWidth.getVal()));
c->Update();
c->Print(Outfile);
RooWorkspace *w = new RooWorkspace("zfit");
w->import(model);
w->import(*data);
return w;
}
void StandardHistFactoryPlotsWithCategories(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData"){
double nSigmaToVary=5.;
double muVal=0;
bool doFit=false;
// -------------------------------------------------------
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
// -------------------------------------------------------
// Tutorial starts here
// -------------------------------------------------------
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
// -------------------------------------------------------
// now use the profile inspector
RooRealVar* obs = (RooRealVar*)mc->GetObservables()->first();
TList* list = new TList();
RooRealVar * firstPOI = dynamic_cast<RooRealVar*>(mc->GetParametersOfInterest()->first());
firstPOI->setVal(muVal);
// firstPOI->setConstant();
if(doFit){
mc->GetPdf()->fitTo(*data);
}
// -------------------------------------------------------
mc->GetNuisanceParameters()->Print("v");
int nPlotsMax = 1000;
cout <<" check expectedData by category"<<endl;
RooDataSet* simData=NULL;
RooSimultaneous* simPdf = NULL;
if(strcmp(mc->GetPdf()->ClassName(),"RooSimultaneous")==0){
cout <<"Is a simultaneous PDF"<<endl;
simPdf = (RooSimultaneous *)(mc->GetPdf());
} else {
cout <<"Is not a simultaneous PDF"<<endl;
}
if(doFit) {
RooCategory* channelCat = (RooCategory*) (&simPdf->indexCat());
TIterator* iter = channelCat->typeIterator() ;
RooCatType* tt = NULL;
tt=(RooCatType*) iter->Next();
RooAbsPdf* pdftmp = ((RooSimultaneous*)mc->GetPdf())->getPdf(tt->GetName()) ;
RooArgSet* obstmp = pdftmp->getObservables(*mc->GetObservables()) ;
obs = ((RooRealVar*)obstmp->first());
RooPlot* frame = obs->frame();
cout <<Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())<<endl;
cout << tt->GetName() << " " << channelCat->getLabel() <<endl;
data->plotOn(frame,MarkerSize(1),Cut(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())),DataError(RooAbsData::None));
Double_t normCount = data->sumEntries(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())) ;
pdftmp->plotOn(frame,LineWidth(2.),Normalization(normCount,RooAbsReal::NumEvent)) ;
frame->Draw();
cout <<"expected events = " << mc->GetPdf()->expectedEvents(*data->get()) <<endl;
return;
}
int nPlots=0;
if(!simPdf){
TIterator* it = mc->GetNuisanceParameters()->createIterator();
RooRealVar* var = NULL;
while( (var = (RooRealVar*) it->Next()) != NULL){
RooPlot* frame = obs->frame();
frame->SetYTitle(var->GetName());
data->plotOn(frame,MarkerSize(1));
var->setVal(0);
mc->GetPdf()->plotOn(frame,LineWidth(1.));
var->setVal(1);
mc->GetPdf()->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(1));
var->setVal(-1);
mc->GetPdf()->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(1));
list->Add(frame);
var->setVal(0);
}
} else {
RooCategory* channelCat = (RooCategory*) (&simPdf->indexCat());
// TIterator* iter = simPdf->indexCat().typeIterator() ;
TIterator* iter = channelCat->typeIterator() ;
RooCatType* tt = NULL;
while(nPlots<nPlotsMax && (tt=(RooCatType*) iter->Next())) {
cout << "on type " << tt->GetName() << " " << endl;
// Get pdf associated with state from simpdf
RooAbsPdf* pdftmp = simPdf->getPdf(tt->GetName()) ;
// Generate observables defined by the pdf associated with this state
RooArgSet* obstmp = pdftmp->getObservables(*mc->GetObservables()) ;
// obstmp->Print();
obs = ((RooRealVar*)obstmp->first());
TIterator* it = mc->GetNuisanceParameters()->createIterator();
RooRealVar* var = NULL;
while(nPlots<nPlotsMax && (var = (RooRealVar*) it->Next())){
TCanvas* c2 = new TCanvas("c2");
RooPlot* frame = obs->frame();
frame->SetName(Form("frame%d",nPlots));
frame->SetYTitle(var->GetName());
cout <<Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())<<endl;
cout << tt->GetName() << " " << channelCat->getLabel() <<endl;
data->plotOn(frame,MarkerSize(1),Cut(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())),DataError(RooAbsData::None));
Double_t normCount = data->sumEntries(Form("%s==%s::%s",channelCat->GetName(),channelCat->GetName(),tt->GetName())) ;
if(strcmp(var->GetName(),"Lumi")==0){
cout <<"working on lumi"<<endl;
var->setVal(w->var("nominalLumi")->getVal());
var->Print();
} else{
var->setVal(0);
}
// w->allVars().Print("v");
// mc->GetNuisanceParameters()->Print("v");
// pdftmp->plotOn(frame,LineWidth(2.));
// mc->GetPdf()->plotOn(frame,LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
//pdftmp->plotOn(frame,LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
normCount = pdftmp->expectedEvents(*obs);
pdftmp->plotOn(frame,LineWidth(2.),Normalization(normCount,RooAbsReal::NumEvent)) ;
if(strcmp(var->GetName(),"Lumi")==0){
cout <<"working on lumi"<<endl;
var->setVal(w->var("nominalLumi")->getVal()+0.05);
var->Print();
} else{
var->setVal(nSigmaToVary);
}
// pdftmp->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2));
// mc->GetPdf()->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
//pdftmp->plotOn(frame,LineColor(kRed),LineStyle(kDashed),LineWidth(2.),Slice(*channelCat,tt->GetName()),ProjWData(*data));
normCount = pdftmp->expectedEvents(*obs);
pdftmp->plotOn(frame,LineWidth(2.),LineColor(kRed),LineStyle(kDashed),Normalization(normCount,RooAbsReal::NumEvent)) ;
if(strcmp(var->GetName(),"Lumi")==0){
cout <<"working on lumi"<<endl;
var->setVal(w->var("nominalLumi")->getVal()-0.05);
var->Print();
} else{
var->setVal(-nSigmaToVary);
}
// pdftmp->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2));
// mc->GetPdf()->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2),Slice(*channelCat,tt->GetName()),ProjWData(*data));
//pdftmp->plotOn(frame,LineColor(kGreen),LineStyle(kDashed),LineWidth(2),Slice(*channelCat,tt->GetName()),ProjWData(*data));
normCount = pdftmp->expectedEvents(*obs);
pdftmp->plotOn(frame,LineWidth(2.),LineColor(kGreen),LineStyle(kDashed),Normalization(normCount,RooAbsReal::NumEvent)) ;
// set them back to normal
if(strcmp(var->GetName(),"Lumi")==0){
cout <<"working on lumi"<<endl;
var->setVal(w->var("nominalLumi")->getVal());
var->Print();
} else{
var->setVal(0);
}
list->Add(frame);
// quit making plots
++nPlots;
frame->Draw();
c2->SaveAs(Form("%s_%s_%s.pdf",tt->GetName(),obs->GetName(),var->GetName()));
delete c2;
}
}
}
// -------------------------------------------------------
// now make plots
TCanvas* c1 = new TCanvas("c1","ProfileInspectorDemo",800,200);
if(list->GetSize()>4){
double n = list->GetSize();
int nx = (int)sqrt(n) ;
int ny = TMath::CeilNint(n/nx);
nx = TMath::CeilNint( sqrt(n) );
c1->Divide(ny,nx);
} else
c1->Divide(list->GetSize());
for(int i=0; i<list->GetSize(); ++i){
c1->cd(i+1);
list->At(i)->Draw();
}
}
/***********************************************************************
***********************************************************************
* CONSTRUCTOR MAKES ALLLLLLLL
*******************************************************************
*************************************************
*****************************
*****
*/
Tbroomfit(double xlow, double xhi, TH1 *h2, int npeak, double *peak, double *sigm, const char *chpol="p0"){
int iq=0;
printf("constructor - %d %ld", iq++, (int64_t)h2 );
h2->Print();
/*
* get global area, ranges for sigma, x
*/
npeaks=npeak; // class defined int
// double areah2=h2->Integral( int(xlow), int(xhi) ); // WRONG - BINS
min= h2->GetXaxis()->GetFirst();
printf("constructor - %d %f", iq++, min );
max= h2->GetXaxis()->GetLast();
printf("constructor - %d %f", iq++, max );
double areah2=h2->Integral( min, max );
printf("constructor - %d %f", iq++, areah2 );
min=xlow;
max=xhi;
double sigmamin=(max-min)/300;
double sigmamax=(max-min)/4;
double areamin=0;
double areamax=2*areah2;
printf("x:(%f,%f) s:(%f,%f) a:(%f,%f) \n", min,max,sigmamin, sigmamax,areamin, areamax );
/*
* definition of variables..............
*
*/
RooRealVar x("x", "x", min, max);
int MAXPEAKS=6; // later from 5 to 6 ???
printf("RooFit: npeaks=%d\n", npeaks );
// ABOVE: RooRealVar *msat[14][5]; // POINTERS TO ALL variables
// 0 m Mean
// 1 s Sigma
// 2 a Area
// 3 t Tail
// 4 [0] nalpha
// 5 [0] n1
for (int ii=0;ii<14;ii++){
for (int jj=0;jj<MAXPEAKS;jj++){
msat[ii][jj]=NULL;
msat_values[ii][jj]=0.0;
} //for for
}// for for
printf("delete fitresult, why crash?\n%s","");
fitresult=NULL;
printf("delete fitresult, no crash?\n%s","");
RooRealVar mean1("mean1", "mean", 1*(max-min)/(npeaks+1)+min, min,max);msat[0][0]=&mean1;
RooRealVar mean2("mean2", "mean", 2*(max-min)/(npeaks+1)+min, min,max);msat[0][1]=&mean2;
RooRealVar mean3("mean3", "mean", 3*(max-min)/(npeaks+1)+min, min,max);msat[0][2]=&mean3;
RooRealVar mean4("mean4", "mean", 4*(max-min)/(npeaks+1)+min, min,max);msat[0][3]=&mean4;
RooRealVar mean5("mean5", "mean", 5*(max-min)/(npeaks+1)+min, min,max);msat[0][4]=&mean5;
RooRealVar mean6("mean6", "mean", 6*(max-min)/(npeaks+1)+min, min,max);msat[0][5]=&mean6;
RooRealVar sigma1("sigma1","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][0]=&sigma1;
RooRealVar sigma2("sigma2","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][1]=&sigma2;
RooRealVar sigma3("sigma3","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][2]=&sigma3;
RooRealVar sigma4("sigma4","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][3]=&sigma4;
RooRealVar sigma5("sigma5","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][4]=&sigma5;
RooRealVar sigma6("sigma6","sigma", (max-min)/10, sigmamin, sigmamax );msat[1][5]=&sigma6;
RooRealVar area1("area1", "area", areah2/npeaks, areamin, areamax );msat[2][0]=&area1;
RooRealVar area2("area2", "area", areah2/npeaks, areamin, areamax );msat[2][1]=&area2;
RooRealVar area3("area3", "area", areah2/npeaks, areamin, areamax );msat[2][2]=&area3;
RooRealVar area4("area4", "area", areah2/npeaks, areamin, areamax );msat[2][3]=&area4;
RooRealVar area5("area5", "area", areah2/npeaks, areamin, areamax );msat[2][4]=&area5;
RooRealVar area6("area6", "area", areah2/npeaks, areamin, areamax );msat[2][5]=&area6;
RooRealVar bgarea("bgarea", "bgarea", areah2/5, 0, 2*areah2);
double tailstart=-1.0;// tune the tails....
double tailmin=-1e+4;
double tailmax=1e+4;
RooRealVar tail1("tail1", "tail", tailstart, tailmin, tailmax );msat[3][0]=&tail1;
RooRealVar tail2("tail2", "tail", tailstart, tailmin, tailmax );msat[3][1]=&tail2;
RooRealVar tail3("tail3", "tail", tailstart, tailmin, tailmax );msat[3][2]=&tail3;
RooRealVar tail4("tail4", "tail", tailstart, tailmin, tailmax );msat[3][3]=&tail4;
RooRealVar tail5("tail5", "tail", tailstart, tailmin, tailmax );msat[3][4]=&tail5;
RooRealVar tail6("tail6", "tail", tailstart, tailmin, tailmax );msat[3][5]=&tail6;
// for CBShape
RooRealVar nalpha1("nalpha1", "nalpha", 1.3, 0, 100 );msat[4][0]=&nalpha1;
RooRealVar n1("n1", "n", 5.1, 0, 100 ); msat[5][0]=&n1;
/*
* initial values for peak positions................
*/
if (npeaks>=1) {mean1=peak[0];sigma1=sigm[0];}
if (npeaks>=2) {mean2=peak[1];sigma2=sigm[1];}
if (npeaks>=3) {mean3=peak[2];sigma3=sigm[2];}
if (npeaks>=4) {mean4=peak[3];sigma4=sigm[3];}
if (npeaks>=5) {mean5=peak[4];sigma5=sigm[4];}
if (npeaks>=6) {mean6=peak[5];sigma6=sigm[5];}
/*
* RooAbsPdf -> RooGaussian
* RooNovosibirsk
* RooLandau
*/
RooAbsPdf *pk[6]; // MAXIMUM PEAKS ==5 6 NOW!!
RooAbsPdf *pk_dicto[14][6]; // ALL DICTIONARY OF PEAKS..........
// Abstract Class.... carrefuly
RooGaussian gauss1("gauss1","gauss(x,mean,sigma)", x, mean1, sigma1);pk_dicto[0][0]=&gauss1;
RooGaussian gauss2("gauss2","gauss(x,mean,sigma)", x, mean2, sigma2);pk_dicto[0][1]=&gauss2;
RooGaussian gauss3("gauss3","gauss(x,mean,sigma)", x, mean3, sigma3);pk_dicto[0][2]=&gauss3;
RooGaussian gauss4("gauss4","gauss(x,mean,sigma)", x, mean4, sigma4);pk_dicto[0][3]=&gauss4;
RooGaussian gauss5("gauss5","gauss(x,mean,sigma)", x, mean5, sigma5);pk_dicto[0][4]=&gauss5;
RooGaussian gauss6("gauss6","gauss(x,mean,sigma)", x, mean6, sigma6);pk_dicto[0][5]=&gauss6;
RooNovosibirsk ns1("ns1","novosib(x,mean,sigma,tail)", x, mean1,sigma1, tail1 );pk_dicto[1][0]=&ns1;
RooNovosibirsk ns2("ns2","novosib(x,mean,sigma,tail)", x, mean2,sigma2, tail2 );pk_dicto[1][1]=&ns2;
RooNovosibirsk ns3("ns3","novosib(x,mean,sigma,tail)", x, mean3,sigma3, tail3 );pk_dicto[1][2]=&ns3;
RooNovosibirsk ns4("ns4","novosib(x,mean,sigma,tail)", x, mean4,sigma4, tail4 );pk_dicto[1][3]=&ns4;
RooNovosibirsk ns5("ns5","novosib(x,mean,sigma,tail)", x, mean5,sigma5, tail5 );pk_dicto[1][4]=&ns5;
// BreitWiegner is Lorentzian...?
RooBreitWigner bw1("bw1","BreitWigner(x,mean,sigma)", x, mean1, sigma1 );pk_dicto[2][0]=&bw1;
RooBreitWigner bw2("bw2","BreitWigner(x,mean,sigma)", x, mean2, sigma2 );pk_dicto[2][1]=&bw2;
RooBreitWigner bw3("bw3","BreitWigner(x,mean,sigma)", x, mean3, sigma3 );pk_dicto[2][2]=&bw3;
RooBreitWigner bw4("bw4","BreitWigner(x,mean,sigma)", x, mean4, sigma4 );pk_dicto[2][3]=&bw4;
RooBreitWigner bw5("bw5","BreitWigner(x,mean,sigma)", x, mean5, sigma5 );pk_dicto[2][4]=&bw5;
RooCBShape cb1("cb1","CBShape(x,mean,sigma)", x, mean1, sigma1, nalpha1, n1 );pk_dicto[3][0]=&cb1;
RooCBShape cb2("cb2","CBShape(x,mean,sigma)", x, mean2, sigma2, nalpha1, n1 );pk_dicto[3][1]=&cb2;
RooCBShape cb3("cb3","CBShape(x,mean,sigma)", x, mean3, sigma3, nalpha1, n1 );pk_dicto[3][2]=&cb3;
RooCBShape cb4("cb4","CBShape(x,mean,sigma)", x, mean4, sigma4, nalpha1, n1 );pk_dicto[3][3]=&cb4;
RooCBShape cb5("cb5","CBShape(x,mean,sigma)", x, mean5, sigma5, nalpha1, n1 );pk_dicto[3][4]=&cb5;
RooCBShape cb6("cb6","CBShape(x,mean,sigma)", x, mean6, sigma6, nalpha1, n1 );pk_dicto[3][5]=&cb6;
/*
* PEAK TYPES BACKGROUND TYPE ......... COMMAND BOX OPTIONS ......
*/
/****************************************************************************
* PLAY WITH THE DEFINITION COMMANDLINE...................... POLYNOM + PEAKS
*/
// CALSS DECLARED TString s;
s=chpol;
/*
* peaks+bg== ALL BEFORE ; or : (after ... it is a conditions/options)
*/
TString command;
int comstart=s.Index(":"); if (comstart<0){ comstart=s.Index(";");}
if (comstart<0){ command="";}else{
command=s(comstart+1, s.Length()-comstart -1 ); // without ;
s=s(0,comstart); // without ;
printf("COMMANDLINE : %s\n", command.Data() );
if (TPRegexp("scom").Match(command)!=0){
}// COMMANDS -
}// there is some command
/*************************************************
* PLAY WITH peaks+bg.................. s
*/
s.Append("+"); s.Prepend("+"); s.ReplaceAll(" ","+");
s.ReplaceAll("++++","+"); s.ReplaceAll("+++","+"); s.ReplaceAll("++","+");s.ReplaceAll("++","+");
printf (" regextp = %s\n", s.Data() );
if (TPRegexp("\\+p[\\dn]\\+").Match(s)==0){ // no match
printf("NO polynomial demanded =>: %s\n", "appending pn command" ); s.Append("pn+");
}
TString spk=s; TString sbg=s;
TPRegexp("\\+p[\\dn]\\+").Substitute(spk,"+"); // remove +p.+
TPRegexp(".+(p[\\dn]).+").Substitute(sbg,"$1"); // remove all but +p+
printf ("PEAKS=%s BG=%s\n", spk.Data() , sbg.Data() );
spk.ReplaceAll("+",""); // VARIANT 1 ------- EACH LETTER MEANS ONE PEAK
/************************************************************************
* PREPARE PEAKS FOLLOWING THE COMMAND BOX................
*/
//default PEAK types
pk[0]=&gauss1;
pk[1]=&gauss2;
pk[2]=&gauss3;
pk[3]=&gauss4;
pk[4]=&gauss5;
pk[5]=&gauss6;
int maxi=spk.Length();
if (maxi>npeaks){maxi=npeaks;}
for (int i=0;i<maxi;i++){
if (spk[i]=='n'){
pk[i]=pk_dicto[1][i];//novosibirsk
printf("PEAK #%d ... Novosibirsk\n", i );
}else if(spk[i]=='b'){
pk[i]=pk_dicto[2][i];//BreitWiegner
printf("PEAK #%d ... BreitWigner\n", i );
}else if(spk[i]=='c'){
pk[i]=pk_dicto[3][i];//CBShape
printf("PEAK #%d ... CBShape\n", i );
}else if(spk[i]=='y'){
}else if(spk[i]=='z'){
}else{
pk[i]=pk_dicto[0][i]; //gauss
printf("PEAK #%d ... Gaussian\n", i );
}// ELSE CHAIN
}//i to maxi
for (int i=0;i<npeaks;i++){ printf("Peak %d at %f s=%f: PRINT:\n " , i, peak[i], sigm[i] );pk[i]->Print();}
/******************************************************** BACKGROUND pn-p4
* a0 == level - also skew
* a1 == p2
* a2 == p3
*/
// Build Chebychev polynomial p.d.f.
// RooRealVar a0("a0","a0", 0.) ;
RooRealVar a0("a0","a0", 0., -10, 10) ;
RooRealVar a1("a1","a1", 0., -10, 10) ;
RooRealVar a2("a2","a2", 0., -10, 10) ;
RooRealVar a3("a3","a3", 0., -10, 10) ;
RooArgSet setcheb;
if ( sbg=="pn" ){ setcheb.add(a0); a0=0.; a0.setConstant(kTRUE);bgarea=0.; bgarea.setConstant(kTRUE);}
if ( sbg=="p0" ){ setcheb.add(a0); a0=0.; a0.setConstant(kTRUE); }
if ( sbg=="p1" ){ setcheb.add(a0); }
if ( sbg=="p2" ){ setcheb.add(a1); setcheb.add(a0); }
if ( sbg=="p3" ){ setcheb.add(a2); setcheb.add(a1); setcheb.add(a0); }
if ( sbg=="p4" ){ setcheb.add(a3);setcheb.add(a2); setcheb.add(a1); setcheb.add(a0); }
// RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1,a2,a3) ) ;
RooChebychev bkg("bkg","Background",x, setcheb ) ;
/**********************************************************************
* MODEL
*/
RooArgList rl;
if (npeaks>0)rl.add( *pk[0] );
if (npeaks>1)rl.add( *pk[1] );
if (npeaks>2)rl.add( *pk[2] );
if (npeaks>3)rl.add( *pk[3] );
if (npeaks>4)rl.add( *pk[4] );
if (npeaks>5)rl.add( *pk[5] );
rl.add( bkg );
RooArgSet rs;
if (npeaks>0)rs.add( area1 );
if (npeaks>1)rs.add( area2 );
if (npeaks>2)rs.add( area3 );
if (npeaks>3)rs.add( area4 );
if (npeaks>4)rs.add( area5 );
if (npeaks>5)rs.add( area6 );
rs.add( bgarea );
RooAddPdf modelV("model","model", rl, rs );
/*
* WITH CUSTOMIZER - I can change parameters inside. But
* - then all is a clone and I dont know how to reach it
*/
RooCustomizer cust( modelV ,"cust");
/*
* Possibility to fix all sigma or tails....
*/
if (TPRegexp("scom").Match(command)!=0){//----------------------SCOM
printf("all sigma have common values.....\n%s", "");
if (npeaks>1)cust.replaceArg(sigma2,sigma1) ;
if (npeaks>2)cust.replaceArg(sigma3,sigma1) ;
if (npeaks>3)cust.replaceArg(sigma4,sigma1) ;
if (npeaks>4)cust.replaceArg(sigma5,sigma1) ;
if (npeaks>5)cust.replaceArg(sigma6,sigma1) ;
}
if (TPRegexp("tcom").Match(command)!=0){//----------------------TCOM
printf("all tails have common values.....\n%s", "");
if (npeaks>1)cust.replaceArg(tail2,tail1) ;
if (npeaks>2)cust.replaceArg(tail3,tail1) ;
if (npeaks>3)cust.replaceArg(tail4,tail1) ;
if (npeaks>4)cust.replaceArg(tail5,tail1) ;
if (npeaks>5)cust.replaceArg(tail6,tail1) ;
}
/* if (TPRegexp("tcom").Match(command)!=0){//----------------------TCOM Neni dalsi ACOM,NCOM pro CB...
printf("all tails have common values.....\n%s", "");
if (npeaks>1)cust.replaceArg(tail2,tail1) ;
if (npeaks>2)cust.replaceArg(tail3,tail1) ;
if (npeaks>3)cust.replaceArg(tail4,tail1) ;
if (npeaks>4)cust.replaceArg(tail5,tail1) ;
}
*/
if (TPRegexp("p1fix").Match(command)!=0){//----------------------
mean1.setConstant();printf("position 1 set constant%s\n","");
}
if (TPRegexp("p2fix").Match(command)!=0){//----------------------
mean2.setConstant();printf("position 2 set constant%s\n","");
}
if (TPRegexp("p3fix").Match(command)!=0){//----------------------
mean3.setConstant();printf("position 3 set constant%s\n","");
}
if (TPRegexp("p4fix").Match(command)!=0){//----------------------
mean4.setConstant();printf("position 4 set constant%s\n","");
}
if (TPRegexp("p5fix").Match(command)!=0){//----------------------
mean5.setConstant();printf("position 5 set constant%s\n","");
}
if (TPRegexp("p6fix").Match(command)!=0){//----------------------
mean6.setConstant();printf("position 6 set constant%s\n","");
}
if (TPRegexp("s1fix").Match(command)!=0){//----------------------
sigma1.setConstant();printf("sigma 1 set constant%s\n","");
}
if (TPRegexp("s2fix").Match(command)!=0){//----------------------
sigma2.setConstant();printf("sigma 2 set constant%s\n","");
}
if (TPRegexp("s3fix").Match(command)!=0){//----------------------
sigma3.setConstant();printf("sigma 3 set constant%s\n","");
}
if (TPRegexp("s4fix").Match(command)!=0){//----------------------
sigma4.setConstant();printf("sigma 4 set constant%s\n","");
}
if (TPRegexp("s5fix").Match(command)!=0){//----------------------
sigma5.setConstant();printf("sigma 5 set constant%s\n","");
}
if (TPRegexp("s6fix").Match(command)!=0){//----------------------
sigma6.setConstant();printf("sigma 6 set constant%s\n","");
}
RooAbsPdf* model = (RooAbsPdf*) cust.build(kTRUE) ; //build a clone...comment on changes...
// model->Print("t") ;
//delete model ; // eventualy delete the model...
/*
* DISPLAY RESULTS >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
*/
TPad *orig_gpad=(TPad*)gPad;
TCanvas *c;
c=(TCanvas*)gROOT->GetListOfCanvases()->FindObject("fitresult");
if (c==NULL){
printf("making new canvas\n%s","");
c=new TCanvas("fitresult",h2->GetName(),1000,700);
}else{
printf("using old canvas\n%s","");
c->SetTitle( h2->GetName() );
}
c->Clear();
printf(" canvas cleared\n%s","");
c->Divide(1,2) ;
printf(" canvas divided\n%s","");
c->Modified();c->Update();
RooDataHist datah("datah","datah with x",x,h2);
RooPlot* xframe = x.frame();
datah.plotOn(xframe, DrawOption("logy") );
// return;
if (TPRegexp("chi2").Match(command)!=0){//----------------------CHI2
//from lorenzo moneta
// TH1 * h1 = datah.createHistogram(x);
// TF1 * f = model->asTF(RooArgList(x) , parameters ); //???
// h2->Fit(f);
//It will work but you need to create a THNSparse and fit it
//or use directly the ROOT::Fit::BinData class to create a ROOT::Fit::Chi2Function to minimize.
// THIS CANNOT DO ZERO BINS
fitresult = model->chi2FitTo( datah , Save() );
}else{
// FIT FIT FIT FIT FIT FIT FIT FIT FIT FIT
fitresult = model->fitTo( datah , Save() );
}
fitresult->SetTitle( h2->GetName() ); // I PUT histogram name to global fitresult
// will be done by printResult ... fitresult->Print("v") ;
//duplicite fitresult->floatParsFinal().Print("s") ;
// later - after parsfinale .... : printResult();
// model->Print(); // not interesting........
model->plotOn(xframe, LineColor(kRed), DrawOption("l0z") );
//,Minos(kFALSE)
/*
* Posledni nakreslena vec je vychodiskem pro xframe->resid...?
* NA PORADI ZALEZI....
*/
//unused RooHist* hresid = xframe->residHist() ;
RooHist* hpull = xframe->pullHist() ;
// RooPlot* xframe2 = x.frame(Title("Residual Distribution")) ;
// xframe2->addPlotable(hresid,"P") ;
// Construct a histogram with the pulls of the data w.r.t the curve
RooPlot* xframe3 = x.frame(Title("Pull Distribution")) ;
xframe3->addPlotable(hpull,"P") ;
/*
* plot components at the end.... PLOT >>>>>>>>>>>>>>>>
*/
int colorseq[10]={kRed,kGreen,kBlue,kYellow,kCyan,kMagenta,kViolet,kAzure,kGray,kOrange};
// RooArgSet* model_params = model->getParameters(x); // this returns all parameters
RooArgSet* model_params = model->getComponents();
TIterator* iter = model_params->createIterator() ;
RooAbsArg* arg ; int icomp=0, ipeak=0;
// printf("ENTERING COMPONENT ITERATOR x%dx.....................\n", icomp );
while((arg=(RooAbsArg*)iter->Next())) {
// printf("printing COMPONENT %d\n", icomp );
// arg->Print();
// printf("NAME==%s\n", arg->Class_Name() ); //This returns only RooAbsArg
// printf("NAME==%s\n", arg->ClassName() ); //This RooGaussian RooChebychev
if ( IsPeak( arg->ClassName() )==1 ){
pk[ipeak]=(RooAbsPdf*)arg; //?
// pk[ipeak]->Print();
ipeak++;
// printf("adresses ... %d - %d - %d\n", pk[0], pk[1], pk[2] );
}// yes peak.
icomp++;
}//iterations over all components
model->plotOn(xframe, Components(bkg), LineColor(kRed), LineStyle(kDashed), DrawOption("l0z") );
for (int i=0;i<npeaks;i++){
// printf("plotting %d. peak, color %d\n", i, colorseq[i+1] );
// printf("adresses ... %d - %d - %d\n", pk[0], pk[1], pk[2] );
// pk[i]->Print();
model->plotOn(xframe, Components( RooArgSet(*pk[i],bkg) ), LineColor(colorseq[i+1]), LineStyle(kDashed),
DrawOption("l0z") );
// DrawOption("pz"),DataError(RooAbsData::SumW2) );??? pz removes complains...warnings
// model.plotOn(xframe, Components( RooArgSet(*pk[i],bkg) ), LineColor(colorseq[i+1]), LineStyle(kDashed));
}
// WE SET THE 1st PAD in "fitresult" to LOGY.... 1
// ..... if the original window is LOGY..... :)
//
// printf("########### ORIGPAD LOGY==%d #########3\n", orig_gpad->GetLogy() );
c->cd(1); xframe->Draw(); gPad->SetLogy( orig_gpad->GetLogy() );
// c->cd(2); xframe2->Draw();
c->cd(2); xframe3->Draw();
c->Modified();c->Update();
orig_gpad->cd();
// printf("msat reference to peak 0 0 = %d, (%f)\n", msat[0][0] , msat[0][0]->getVal() );
for (int ii=0;ii<14;ii++){
for (int jj=0;jj<MAXPEAKS;jj++){
if ( msat[ii][jj]!=NULL){
msat_values[ii][jj]=msat[ii][jj]->getVal();
}//if
} //for for
}// for for
printf("at the total end of the constructor....%s\n","");
// done in pirntResult .. fitresult->floatParsFinal().Print("s") ;
printResult();
}; // constructor
void higgsMassFit(const int& mH, const std::string& mode = "exclusion", const bool& drawPlots = false, const int& nToys = 10000)
{
using namespace RooFit;
RooMsgService::instance().deleteStream(0);
RooMsgService::instance().deleteStream(1);
std::string varName = "lepNuW_m";
int step = 16;
char treeName[50];
sprintf(treeName, "ntu_%d", step);
float lumi = 1000.;
int nBins = 50;
double xMin = 0.;
double xMax = 1000.;
double xMin_signal = 0.;
double xMax_signal = 0.;
SetXSignal(xMin_signal,xMax_signal,mH);
RooRealVar x("x",varName.c_str(),xMin,xMax);
x.setRange("low", xMin, xMin_signal);
x.setRange("signal",xMin_signal,xMax_signal);
x.setRange("high", xMax_signal,xMax);
RooRealVar w("w","weight",0.,1000000000.);
char signalCut[50];
sprintf(signalCut,"x > %f && x < %f",xMin_signal,xMax_signal);
//-------------------
// define the outfile
char outFileName[50];
sprintf(outFileName,"higgsMassFit_H%d_%s.root",mH,mode.c_str());
TFile* outFile = new TFile(outFileName,"RECREATE");
outFile -> cd();
//-------------------
// define the infiles
char higgsMass[50];
sprintf(higgsMass,"%d",mH);
std::string BKGPath = "/grid_mnt/vol__vol1__u/llr/cms/abenagli/COLLISIONS7TeV/Fall10/VBFAnalysisPackage/data/VBFAnalysis_AK5PF_H" +
std::string(higgsMass) +
"_ET30_maxDeta_minDeta_Spring11_EGMu_noHiggsMassCut/";
std::string WJetsFolder = "WJetsToLNu_TuneZ2_7TeV-madgraph-tauola_Spring11-PU_S1_START311_V1G1-v1/";
std::string TTJetsFolder = "TTJets_TuneZ2_7TeV-madgraph-tauola_Spring11-PU_S1_START311_V1G1-v1/";
//std::string ZJetsFolder =
//std::string GJets_HT40To100Folder
//std::string GJets_HT100To200Folder
//std::string GJets_HT200Folder
//std::string WWFolder
//std::string WZFolder
//std::string TJets_schannelFolder
//std::string TJets_tchannelFolder
//std::string TJets_tWchannelFolder
std::string GluGluHToLNuQQFolder = "GluGluToHToWWToLNuQQ_M-" + std::string(higgsMass) + "_7TeV-powheg-pythia6_Spring11-PU_S1_START311_V1G1-v1/";
std::string GluGluHToTauNuQQFolder = "GluGluToHToWWToTauNuQQ_M-" + std::string(higgsMass) + "_7TeV-powheg-pythia6_Spring11-PU_S1_START311_V1G1-v1/";
std::string VBFHToLNuQQFolder = "VBF_HToWWToLNuQQ_M-" + std::string(higgsMass) + "_7TeV-powheg-pythia6_Spring11-PU_S1_START311_V1G1-v1/";
std::string VBFHToTauNuQQFolder = "VBF_HToWWToTauNuQQ_M-" + std::string(higgsMass) + "_7TeV-powheg-pythia6_Spring11-PU_S1_START311_V1G1-v1/";
//---------------------------------------
// define the background shape histograms
int nBKG = 2;
TH1F** BKGShapeHisto = new TH1F*[nBKG];
TH1F* BKGTotShapeHisto = new TH1F("BKGTotShapeHisto","",nBins,xMin,xMax);
THStack* BKGShapeStack = new THStack();
RooDataSet** rooBKGDataSet = new RooDataSet*[nBKG];
std::string* BKGNames = new std::string[nBKG];
BKGNames[1] = BKGPath+WJetsFolder+"VBFAnalysis_AK5PF.root";
BKGNames[0] = BKGPath+TTJetsFolder+"VBFAnalysis_AK5PF.root";
//BKGNames[1] = BKGPath+ZJetsFolder+"VBFAnalysis_AK5PF.root";
//BKGNames[2] = BKGPath+GJets_HT40To100Folder+"VBFAnalysis_AK5PF.root";
//BKGNames[3] = BKGPath+GJets_HT100To200Folder+"VBFAnalysis_AK5PF.root";
//BKGNames[4] = BKGPath+GJets_HT200Folder+"VBFAnalysis_AK5PF.root";
//BKGNames[6] = BKGPath+WWFolder+"VBFAnalysis_AK5PF.root";
//BKGNames[7] = BKGPath+WZFolder+"VBFAnalysis_AK5PF.root";
//BKGNames[8] = BKGPath+TJets_schannelFolder+"VBFAnalysis_AK5PF.root";
//BKGNames[9] = BKGPath+TJets_tchannelFolder+"VBFAnalysis_AK5PF.root";
//BKGNames[10] = BKGPath+TJets_tWchannelFolder+"VBFAnalysis_AK5PF.root";
std::string* BKGShortNames = new std::string[nBKG];
BKGShortNames[1] = "WJets";
BKGShortNames[0] = "TTJets";
//BKGShortNames[1] = "ZJets";
//BKGShortNames[2] = "GJets_HT40To100";
//BKGShortNames[3] = "GJets_HT100To200";
//BKGShortNames[4] = "GJets_HT200";
//BKGShortNames[6] = "WW";
//BKGShortNames[7] = "WZ";
//BKGShortNames[8] = "TJets_schannel";
//BKGShortNames[9] = "TJets_tchannel";
//BKGShortNames[10] = "TJets_tWchannel";
Color_t* BKGColors = new Color_t[nBKG];
BKGColors[1] = kOrange-708;
BKGColors[0] = kAzure-795;
//-----------------------------------
// define the signal shape histograms
int nSIG = 2;
TH1F* SIGShapeHisto = new TH1F("SIGShapeHisto","",4*nBins,xMin,xMax);
SIGShapeHisto -> Sumw2();
SIGShapeHisto -> SetLineWidth(1);
SIGShapeHisto -> SetLineStyle(1);
RooDataSet* rooSIGDataSet = new RooDataSet("rooSIGDataSet","",RooArgSet(x,w),WeightVar(w));
std::string* SIGNames = new std::string[nSIG];
SIGNames[0] = BKGPath+GluGluHToLNuQQFolder+"VBFAnalysis_AK5PF.root";
SIGNames[1] = BKGPath+VBFHToLNuQQFolder+"VBFAnalysis_AK5PF.root";
std::string* SIGShortNames = new std::string[nSIG];
SIGShortNames[1] = "ggH";
SIGShortNames[0] = "qqH";
//----------------------
// loop over backgrounds
std::cout << "***********************************************************************" << std::endl;
std::cout << ">>> Fill the background shapes" << std::endl;
for(int i = 0; i < nBKG; ++i)
{
TFile* inFile_BKGShape = TFile::Open((BKGNames[i]).c_str());
inFile_BKGShape -> cd();
TTree* BKGShapeTree = (TTree*)(inFile_BKGShape -> Get(treeName));
BKGShapeHisto[i] = new TH1F(("BKGShapeHisto_"+BKGShortNames[i]).c_str(),"",nBins,xMin,xMax);
enum EColor color = (enum EColor)(BKGColors[i]);
BKGShapeHisto[i] -> SetFillColor(color);
BKGShapeHisto[i] -> Sumw2();
rooBKGDataSet[i] = new RooDataSet(("rooBKGDataSet_"+BKGShortNames[i]).c_str(),"",RooArgSet(x,w),WeightVar(w));
TH1F* eventsHisto;
inFile_BKGShape -> GetObject("events", eventsHisto);
float totEvents = eventsHisto -> GetBinContent(1);
// set branch addresses
float crossSection;
float var;
BKGShapeTree -> SetBranchAddress("crossSection", &crossSection);
BKGShapeTree -> SetBranchAddress(varName.c_str(),&var);
// loop over the entries
for(int entry = 0; entry < BKGShapeTree->GetEntries(); ++entry)
{
BKGShapeTree -> GetEntry(entry);
x = var;
w = 1./totEvents*crossSection*lumi;
BKGShapeHisto[i] -> Fill(var, 1./totEvents*crossSection*lumi);
BKGTotShapeHisto -> Fill(var, 1./totEvents*crossSection*lumi);
rooBKGDataSet[i] -> add(RooArgSet(x,w));
}
BKGShapeStack -> Add(BKGShapeHisto[i]);
}
//------------------
// loop over signals
std::cout << ">>> Fill the signal shapes" << std::endl;
for(int i = 0; i < nSIG; ++i)
{
TFile* inFile_SIGShape = TFile::Open((SIGNames[i]).c_str());
inFile_SIGShape -> cd();
TTree* SIGShapeTree = (TTree*)(inFile_SIGShape -> Get(treeName));
TH1F* eventsHisto = (TH1F*)(inFile_SIGShape -> Get("events"));
float totEvents = eventsHisto -> GetBinContent(1);
// set branch addresses
float crossSection;
float var;
SIGShapeTree -> SetBranchAddress("crossSection", &crossSection);
SIGShapeTree -> SetBranchAddress(varName.c_str(),&var);
// loop over the entries
for(int entry = 0; entry < SIGShapeTree->GetEntries(); ++entry)
{
SIGShapeTree -> GetEntry(entry);
x = var;
w= 1./totEvents*crossSection*lumi;
SIGShapeHisto -> Fill(var, 1./totEvents*crossSection*lumi);
rooSIGDataSet -> add(RooArgSet(x,w));
}
}
//-----------------------------------
// draw the background + signal stack
if( drawPlots )
{
TCanvas* c1 = new TCanvas("BKGShapeStack","BKGShapeStack");
c1 -> SetGridx();
c1 -> SetGridy();
BKGShapeStack -> Draw("HIST");
SIGShapeHisto -> Draw("HIST,same");
char pngFileName[50];
sprintf(pngFileName,"BKGShapeStack_H%d_%s.png",mH,mode.c_str());
c1 -> Print(pngFileName,"png");
}
//---------------------------------
// define the bkg shape with roofit
std::cout << ">>> Define the background pdf" << std::endl;
RooKeysPdf** rooBKGPdf = new RooKeysPdf*[nBKG];
RooRealVar** rooNBKG = new RooRealVar*[nBKG];
RooRealVar* rooNBKGTot = new RooRealVar("rooNBKGTot","",BKGTotShapeHisto->Integral(),0.,1000000.);
for(int i = 0; i < nBKG; ++i)
{
rooBKGPdf[i] = new RooKeysPdf(("rooBKGPdf_"+BKGShortNames[i]).c_str(),"",x,*rooBKGDataSet[i]);
rooNBKG[i] = new RooRealVar(("rooNBKG_"+BKGShortNames[i]).c_str(),"",BKGShapeHisto[i]->Integral(),BKGShapeHisto[i]->Integral()),BKGShapeHisto[i]->Integral();
}
RooAddPdf* rooBKGTotPdf = new RooAddPdf("rooBKGTotPdf","",RooArgList(*rooBKGPdf[0],*rooBKGPdf[1]),RooArgList(*rooNBKG[0],*rooNBKG[1]));
//---------------------------------
// define the sig shape with roofit
std::cout << ">>> Define the signal pdf" << std::endl;
RooKeysPdf* rooSIGPdf = new RooKeysPdf("rooSIGPdf","",x,*rooSIGDataSet);
RooRealVar* rooNSIG = new RooRealVar("rooNSIG","",1.,-1000000.,1000000.);
//---------------------------------
// define the tot shape with roofit
std::cout << ">>> Define the total pdf" << std::endl;
RooAddPdf* rooTotPdf = NULL;
if( mode == "exclusion") rooTotPdf = new RooAddPdf("rooTotPdf","",RooArgList(*rooBKGTotPdf),RooArgList(*rooNBKGTot));
if( mode == "discovery") rooTotPdf = new RooAddPdf("rooTotPdf","",RooArgList(*rooBKGTotPdf,*rooSIGPdf),RooArgList(*rooNBKGTot,*rooNSIG));
//----
// plot
if( drawPlots )
{
TCanvas* c2 = new TCanvas("rooTotPdf","rooTotPdf");
c2 -> SetGridx();
c2 -> SetGridy();
RooPlot* rooBKGPlot = x.frame();
rooBKGTotPdf -> plotOn(rooBKGPlot,LineColor(kBlack));
enum EColor color = (enum EColor)(BKGColors[0]);
rooBKGTotPdf -> plotOn(rooBKGPlot,Components(("rooBKGPdf_"+BKGShortNames[0]).c_str()),LineColor(color));
color = (enum EColor)(BKGColors[1]);
rooBKGTotPdf -> plotOn(rooBKGPlot,Components(("rooBKGPdf_"+BKGShortNames[1]).c_str()),LineColor(color));
rooSIGPdf -> plotOn(rooBKGPlot,LineColor(kBlack),LineStyle(1),LineWidth(1));
rooBKGPlot->Draw();
TH1F* BKGShapeHistoNorm = (TH1F*) BKGTotShapeHisto -> Clone();
BKGShapeHistoNorm -> Scale(1./BKGTotShapeHisto->Integral()/nBKG);
BKGShapeHistoNorm -> Draw("HIST,same");
char pngFileName[50];
sprintf(pngFileName,"BKGShapeNorm_H%d_%s.png",mH,mode.c_str());
c2 -> Print(pngFileName,"png");
}
//------------------------
// generate toy experiment
std::cout << "***********************************************************************" << std::endl;
std::cout << ">>> 1st toy experiment - " << mode << " mode" << std::endl;
int NBKGToy = int(BKGTotShapeHisto->Integral());
int NSIGToy = 0;
if( mode == "discovery" ) NSIGToy = int(SIGShapeHisto->Integral());
RooDataSet* rooBKGToyDataSet = rooBKGTotPdf->generate(RooArgSet(x),NBKGToy);
RooDataSet* rooSIGToyDataSet = rooSIGPdf->generate(RooArgSet(x),NSIGToy);
rooBKGToyDataSet -> append(*rooSIGToyDataSet);
float NBKGToy_signal = rooBKGToyDataSet->sumEntries(signalCut);
float NBKGToy_signal_fit = 0.;
// fit
if( mode == "exclusion" ) rooTotPdf -> fitTo(*rooBKGToyDataSet,Extended(kTRUE),PrintLevel(-1),Range("low,high"));
if( mode == "discovery" ) rooTotPdf -> fitTo(*rooBKGToyDataSet,Extended(kTRUE),PrintLevel(-1));
// count events
if( mode == "exclusion" )
{
RooAbsReal* rooTotIntegral = rooTotPdf -> createIntegral(x,NormSet(x),Range("signal"));
NBKGToy_signal_fit = rooTotIntegral->getVal() * rooNBKGTot->getVal();
std::cout << ">>>>>> BKG toy events (true) in signal region in " << lumi << "/pb: " << NBKGToy_signal << std::endl;
std::cout << ">>>>>> BKG toy events (fit) in signal region in " << lumi << "/pb: " << NBKGToy_signal_fit << std::endl;
}
if( mode == "discovery" )
{
std::cout << ">>>>>> BKG toy events (true) in " << lumi << "/pb: " << NBKGToy << std::endl;
std::cout << ">>>>>> BKG toy events (fit) in " << lumi << "/pb: " << rooNBKGTot->getVal() << std::endl;
std::cout << ">>>>>> SIG toy events (true) in " << lumi << "/pb: " << NSIGToy << std::endl;
std::cout << ">>>>>> SIG toy events (fit) in " << lumi << "/pb: " << rooNSIG->getVal() << std::endl;
}
if( drawPlots )
{
TCanvas* c3 = new TCanvas("TOY","TOY");
c3 -> SetGridx();
c3 -> SetGridy();
RooPlot* rooTOYPlot = x.frame();
rooBKGToyDataSet -> plotOn(rooTOYPlot,MarkerSize(0.7));
rooTotPdf -> plotOn(rooTOYPlot, LineColor(kRed));
rooTotPdf -> plotOn(rooTOYPlot, Components("rooSIGPdf"), LineColor(kRed));
rooTOYPlot->Draw();
char pngFileName[50];
sprintf(pngFileName,"BKGToyFit_H%d_%s.png",mH,mode.c_str());
c3 -> Print(pngFileName,"png");
}
//-------------------------
// generate toy experiments
TH1F* h_BKGRes = new TH1F("h_BKGRes","",200,-400,400);
TH1F* h_SIGRes = new TH1F("h_SIGRes","",200,-400,400);
TRandom3 B;
TRandom3 S;
for(int j = 0; j < nToys; ++j)
{
if( j%100 == 0 )
std::cout << ">>>>>> generating toy experiment " << j << std::endl;
NBKGToy = B.Poisson(BKGTotShapeHisto->Integral());
NSIGToy = 0;
if( mode == "discovery" ) NSIGToy = S.Poisson(SIGShapeHisto->Integral());
rooBKGToyDataSet = rooBKGTotPdf->generate(RooArgSet(x),NBKGToy);
rooSIGToyDataSet = rooSIGPdf->generate(RooArgSet(x),NSIGToy);
rooBKGToyDataSet -> append(*rooSIGToyDataSet);
NBKGToy_signal = rooBKGToyDataSet->sumEntries(signalCut);
NBKGToy_signal_fit = 0.;
// fit
if( mode == "exclusion" ) rooTotPdf -> fitTo(*rooBKGToyDataSet,Extended(kTRUE),PrintLevel(-1),Range("low,high"));
if( mode == "discovery" ) rooTotPdf -> fitTo(*rooBKGToyDataSet,Extended(kTRUE),PrintLevel(-1));
// count events
if( mode == "exclusion" )
{
RooAbsReal* rooTotIntegral = rooTotPdf -> createIntegral(x,NormSet(x),Range("signal"));
NBKGToy_signal_fit = rooTotIntegral->getVal() * rooNBKGTot->getVal();
h_BKGRes -> Fill(NBKGToy_signal_fit - NBKGToy_signal);
h_SIGRes -> Fill(0.);
}
if( mode == "discovery" )
{
h_BKGRes -> Fill(rooNBKGTot->getVal() - NBKGToy);
h_SIGRes -> Fill(rooNSIG->getVal() - NSIGToy);
}
}
outFile -> cd();
h_BKGRes -> Write();
h_SIGRes -> Write();
outFile -> Close();
}
//before: gROOT->ProcessLine(".include /afs/cern.ch/cms/slc5_ia32_gcc434/lcg/roofit/5.26.00-cms5/include")
//5_3_6: gROOT->ProcessLine(".include /afs/cern.ch/cms/slc5_amd64_gcc462/lcg/roofit/5.32.03-cms9/include/")
//Usage: .x Gaussian_fit.C+("Compare2012DMINECCnot","2012D_EtaRingMY_Vs_MYnoCC.root")
void Gaussian_fit( string Dir, string File ){
string PathL = Dir + "/" + File;
TCanvas* myc1 = new TCanvas("myc1", "CMS", 600, 600);
TString outname = Dir + "/Gaus_Fit.root";
//Files
cout<<"Opening: "<<PathL<<endl;
TFile* fin = TFile::Open(PathL.c_str());
//Histos
string List[4]={"Ratio1D_EB","Ratio1D_EEm","Ratio1D_EEp","Ratio1D_EB_eta1"};
for(int nH=0; nH<4; nH++){
TH1F *h_toFit = (TH1F*) fin->Get( List[nH].c_str() );
float hmean = h_toFit->GetMean();
float hrms = h_toFit->GetRMS();
TString outName = Dir + "/" + "Ratio1D_EB.png";
if(nH==1) outName = Dir + "/" + "Ratio1D_EEm.png";
if(nH==2) outName = Dir + "/" + "Ratio1D_EEp.png";
if(nH==3) outName = Dir + "/" + "Ratio1D_EB_eta1.png";
//Fit Method
RooRealVar x("x","IC distribution",hmean-1.6*hrms, hmean+1.6*hrms, "");
RooDataHist dh("dh","#gamma#gamma invariant mass",RooArgList(x),h_toFit);
RooRealVar mean("mean","mean",hmean, hmean-1.5*hrms,hmean+1.5*hrms,"");
RooRealVar sigma("sigma","#sigma",hrms, hrms-hrms/40.,hrms+hrms/40.,"");
mean.setRange(hmean-hmean/2.,hmean+hmean/2.);
sigma.setRange(0.,hrms+hrms/2.);
RooGaussian gaus("gaus","Core Gaussian",x, mean,sigma);
RooRealVar Nsig("Nsig","#pi^{0} yield",1000.,0.,1.e7);
Nsig.setVal( h_toFit->Integral()-h_toFit->Integral()/1000. );
Nsig.setRange(h_toFit->Integral()/50.,h_toFit->Integral());
RooRealVar cb0("cb0","cb0", 0.2, -1.,1.);
RooRealVar cb1("cb1","cb1",-0.1, -1.,1.);
RooRealVar cb2("cb2","cb2", 0.1, -1.,1.);
RooArgList cbpars(cb0,cb1,cb2);
RooChebychev bkg("bkg","bkg model", x, cbpars );
RooRealVar Nbkg("Nbkg","background yield",h_toFit->Integral()/100.,0.,h_toFit->Integral());
Nbkg.setVal( h_toFit->Integral()/100. );
RooAddPdf model1("model","only_gaus",RooArgList(gaus),RooArgList(Nsig));
RooAddPdf model2("model","sig+bkg",RooArgList(gaus,bkg),RooArgList(Nsig,Nbkg));
RooAbsPdf* model=0; model = &model2;
RooNLLVar nll("nll","log likelihood var",*model,dh);//,Extended());
RooMinuit m(nll);
m.setVerbose(kFALSE);
m.migrad();
//RooFitResult* res = m.save();
RooPlot* xframe = x.frame(h_toFit->GetNbinsX());
xframe->SetTitle("");
dh.plotOn(xframe);
model->plotOn(xframe);
//model->plotOn(xframe,Components(bkg),LineStyle(kDashed), LineColor(kRed));
h_toFit->Draw();
xframe->Draw("same");
//myc1->SaveAs(outName.Data());
float sigma_plot = sigma.getVal();
TLatex lat;
char line[300];
lat.SetNDC();
lat.SetTextSize(0.030);
lat.SetTextColor(1);
sprintf(line,"SIGMA: %.6f ", sigma_plot );
float xmin(0.55), yhi(0.80);// ypass(0.05);
lat.DrawLatex(xmin,yhi, line);
myc1->SaveAs(outName.Data());
}
//rms_EB->Write();
//rms_EEp->Write();
//rms_EEm->Write();
//output->Close();
}
fit_info* do_oneflavor_fit(double scale, TString bg, TString chrg, bool temp, bool redice) {
RooRealVar *x = new RooRealVar("x","LP variable",-0.4,1.6) ;
/* RooRealVar *f1 = new RooRealVar("f_{L}","f_{L}",500.,0.,10000.) ; */
/* RooRealVar *f2 = new RooRealVar("f_{R}","f_{R}",100.,0.,10000.) ; */
RooRealVar *f1 = new RooRealVar("f_{L}","f_{L}",0.51,0.,1.) ;
RooRealVar *f2 = new RooRealVar("f_{R}","f_{R}",0.29,0.,1.) ;
// RooRealVar *f3 = new RooRealVAr("f_{0}","f_{0}",(1-0.51-0.29),0.,1.);
bool addqcd=false;
if(bg.Contains("qcd")) addqcd=true;
PDF ePDF = PDF(chrg, scale,addqcd,x,f1,f2,redice);
// Toy MC Study
TString canvasName_2="pulls";
canvasName_2+=scale;
if (addqcd) canvasName_2+="_qcd";
else canvasName_2+="_Wonly";
TCanvas *cp0 = new TCanvas(canvasName_2,"");
TLegend *leg = new TLegend(.5,.5,.8,.8,"");
leg->SetTextSize(0.04);
leg->SetFillColor(0);
leg->SetLineColor(0);
// Correction factors
TH1D *temp1=ePDF.mc1->Clone(); TH1D *temp2=ePDF.mc2->Clone(); TH1D *temp3=ePDF.mc3->Clone();
float allmc = temp1->Integral()+temp2->Integral()+temp3->Integral();
float scalef_1 = allmc/temp1->Integral();
float scalef_2 = allmc/temp2->Integral();
float scalef_3 = allmc/temp3->Integral();
/*
RooCategory tagCat("tagCat","tagging Category");
tagCat.defineType("eplus"); tagCat.defineType("eminus");
// Construct combined dataset in (x,tagCat)
if (redice) {
RooDataSet combData("ecombData","combined data",*x,Index(tagCat),Import("eplus",*(ePDF.test1_plus)),
Import("eminus",*(ePDF.test1_minus)) );
} else {
RooDataHist combData("ecombData","combined data",*x,Index(tagCat),Import("eplus",*(ePDF.rtest1_plus)),
Import("eminus",*(ePDF.rtest1_minus)) );
}
*/
// (*ePDF.model).fitTo(*ePDF.rtest1,Minos(kTRUE));
RooNLLVar nll("nll","nll",*ePDF.model,*ePDF.rtest1);
RooMinuit m(nll);
// Activate constant-term optimization (always recommended)
m.optimizeConst(kTRUE) ;
// Activate profile timing
m.setProfile(kTRUE) ;
// Activate verbose logging
m.setVerbose(kTRUE) ;
// Run HESSE (mx,my,sx,sy free)
m.hesse() ;
// Deactivate verbose logging
m.setVerbose(kFALSE) ;
// Run MIGRAD (mx,my free)
m.migrad() ;
// Run MINOS (mx,my,sx free)
m.minos() ;
RooFitResult *fitr=m.save();
fitr->Print();
// return;
// if (redice) {
// RooDataSet mdata("d","d",ePDF.test1,*x);
// } else {
// RooDataHist mdata("d","d",*x,*ePDF.rtest1);
// }
// RooFormulaVar con("constrain","(1-f_{L}-f_{R})<0.",RooArgList(*f1,*f2));
// RooFitResult *fitr = (*ePDF.model).fitTo(*ePDF.rtest1,Minos(kTRUE),Save(kTRUE));
fit_info* fit=new fit_info();
/*
fit->val1 = f1->getVal();
fit->val2 = f2->getVal();
fit->err1 = f1->getError();
fit->err2 = f2->getError();
*/
// Change interpretation of parameters
fit->val1 = f1->getVal();
fit->val2 = (1-fit->val1)*f2->getVal();
fit->err1 = f1->getError();
double alpha=(1-fit->val1); double beta=fit->val2;
double dalpha=-fit->err1; double dbeta=f2->getError();
fit->err2 = sqrt( beta*beta*dalpha*dalpha + alpha*alpha*dbeta*dbeta +
2.*alpha*beta*dalpha*dbeta*fitr->correlation(*f1,*f2) );
// fit->err2 = sqrt( (dalpha/alpha)*(dalpha/alpha) + (dbeta/beta)*(dbeta/beta) +
// 2. *((dalpha*dbeta)/(alpha*beta))*fitr->correlation(*f1,*f2) );
fit->corr1 = 3*scalef_1/(scalef_1+scalef_2+scalef_3);
fit->corr2 = 3*scalef_2/(scalef_1+scalef_2+scalef_3);
fit->corr3 = 3*scalef_3/(scalef_1+scalef_2+scalef_3);
fit->val1_corr = fit->val1 * fit->corr1;
fit->val2_corr = fit->val2 * fit->corr2;
fit->err1_corr = fit->err1 * fit->corr1;
fit->err2_corr = fit->err2 * fit->corr2;
fit->gcor1 = fitr->globalCorr(*f1);
fit->gcor2 = fitr->globalCorr(*f2);
fit->gcor12 = fitr->correlation(*f1,*f2);
TString ecanvasName="e";
TString canvasName="c";
canvasName+=scale;
ecanvasName+=scale;
// if( plus) canvasName+="plus";
// else canvasName+="Minus";
if (addqcd) {
canvasName+="_qcd";
}
else canvasName+="_Wonly";
ecanvasName+=canvasName;
setStyles();
TCanvas *ce = new TCanvas(ecanvasName,"");
RooPlot * xframe = x->frame();
(*ePDF.rtest1).plotOn(xframe,Binning(20));
(*ePDF.model).plotOn(xframe); (*ePDF.model).paramOn(xframe);
(*ePDF.model).plotOn(xframe,Components(*ePDF.h1),LineColor(kRed),LineStyle(kDashed));
(*ePDF.model).plotOn(xframe,Components(*ePDF.h2),LineColor(kGreen),LineStyle(kDashed));
(*ePDF.model).plotOn(xframe,Components(*ePDF.h3),LineColor(kYellow),LineStyle(kDashed));
if (addqcd) {
(*ePDF.model).plotOn(xframe,Components(*ePDF.bkg),LineColor(kBlack),LineStyle(kDashed));
}
xframe->Draw();
ce->Update();
// return;
// Likelihood contours in two-dimensions
TString canvasName_1="nll";
canvasName_1+=scale;
// if( plus) canvasName+="plus";
// else canvasName+="Minus";
if (addqcd) canvasName_1+="_qcd";
else canvasName_1+="_Wonly";
TString canvasName_2="pulls_";
canvasName_2+=canvasName_1;
TCanvas *c0 = new TCanvas(canvasName_1,"");
TLegend *leg = new TLegend(.5,.5,.8,.8,"");
leg->SetTextSize(0.04);
leg->SetFillColor(0);
leg->SetLineColor(0);
double lumi=(10.*scale);
TString head="L ="; head+=lumi; head+=" pb-1";
if (addqcd) head+=" (W+QCD)";
leg->SetHeader(head);
c0->Divide(2,1);
c0->cd(1);
RooPlot *contour = m.contour(*f1,*f2);
contour->Draw();
// m.contour(*f1,*f2)->Draw();
contour->SetTitle(";f_{1};f_{2}");
leg->Draw("SAME");
c0->cd(2);
RooPlot *ncontour = transform(contour,1.,1.,0);
// RooPlot *ncontour = transform(contour,fit->corr1,fit->corr2,0);
ncontour->Draw();
// ncontour->SetTitle(";f_{L};f_{R}");
// if (addqcd)
return fit;
// MC STudies
Int_t nevt=(int)ePDF.stat;
RooMCStudy mgr(*ePDF.model,*ePDF.model,*x,"","mhv");
mgr.generateAndFit(500,nevt,kTRUE);
TCanvas *cp0 = new TCanvas(canvasName_2,"");
RooPlot* m1pframe = mgr.plotPull(*f1,-4,4,40,kTRUE);
m1pframe->Draw();
canvasName_2+="_fr";
TCanvas *cp02 = new TCanvas(canvasName_2,"");
RooPlot* m2pframe = mgr.plotPull(*f2,-4,4,40,kTRUE);
m2pframe->Draw();
canvasName_2+="_f0";
TCanvas *cp03 = new TCanvas(canvasName_2,"");
RooPlot* m3pframe = mgr.plotPull(*ePDF.f3,-4,4,40,kTRUE);
m3pframe->Draw();
return fit;
}
void makeModel(RooWorkspace& w) {
TFile *_file0 = TFile::Open("plots/htotal_root_ZprimeRecomass.root");
TH1F *Histo = (TH1F*)_file0->Get("htotaldata");
RooRealVar invm("invm","invm",200.,4000.);
RooDataHist* data = new RooDataHist("data","data",invm,Import(*Histo)) ;
// TTree* tree = new TTree("simple","data from ascii file");
// Long64_t nlines = tree->ReadFile("list_mll_200_2016.txt","x1:x2:x3:invm:x5:x6");
// Long64_t nlines = tree->ReadFile("a.txt","x1:x2:x3:invm:x5:x6");
// printf(" found %lld pointsn",nlines);
// tree->Write();
// tree->GetEntries();
RooRealVar mass("mass","mass", 300., 200., 1600.);
RooRealVar nsig("nsig","Number of signal events", 0., 5000.);
RooRealVar nbkg("nbkg","Number of background events", 0., 300000.);
w.import(mass);
w.import(nsig);
w.import(nbkg);
// RooRealVar invm("invm","Invariant mass", 200., 4000.);
// RooDataSet* data = new RooDataSet("data", "Data", invm, RooFit::Import(*tree));
data->Print("v");
w.import(invm);
w.import(*data);
w.factory("expr::sigma('invm*(0.01292 + 0.00001835 * invm - 0.0000000002733 * invm*invm)',invm)");
w.factory("expr::width('0.03*invm',invm)");
w.factory("CEXPR::bkgpdf('exp(24.9327 - 2.39287e-03*invm + 3.19926e-07*invm*invm - 3.38799e-11*invm*invm*invm)*pow(invm,-3.3634)',invm)");
w.factory("Voigtian::sigpdf(invm,mass,width,sigma)");
w.factory("SUM::model(nbkg*bkgpdf, nsig*sigpdf)");
RooAbsPdf* sigpdf = w.pdf("sigpdf");
RooAbsPdf* bkgpdf = w.pdf("bkgpdf");
RooAbsPdf* model = w.pdf("model");
RooStats::ModelConfig* mc = new ModelConfig("mc",&w);
mc->SetPdf(*w.pdf("model"));
mc->SetParametersOfInterest(*w.var("nsig"));
mc->SetObservables(*w.var("invm"));
w.defineSet("nuisParams","nbkg");
mc->SetNuisanceParameters(*w.set("nuisParams"));
w.var("mass")->setConstant(true);
w.import(*mc);
w.Print("tree");
w.writeToFile("MyModel_workspace.root");
TCanvas* c1 = new TCanvas("c1","Control Plots", 900, 700);
RooPlot* plot = w.var("invm")->frame();
w.data("data")->plotOn(plot);
w.pdf("model")->plotOn(plot);
w.pdf("model")->plotOn(plot, Components("bkgpdf"),LineStyle(kDashed));
w.pdf("model")->plotOn(plot, Components("sigpdf"),LineColor(kRed));
plot->Draw();
return;
}
RooPlot *transform(RooPlot *contour, double corx, double cory, bool mode) {
RooPlot *h;
if (mode) {
h = new RooPlot(0.,1.,0.,1.);//contour->Clone(); h->Reset();
} else {
h = new RooPlot(0.,1.,0.,1.2);
}
contour->Print();
TGraph *g1 = (TGraph*)contour->findObject("contour_nll_n1.000000");
TGraph *g2 = (TGraph*)contour->findObject("contour_nll_n2.000000");
TMarker *point= (TMarker*)contour->findObject("TMarker");
Double_t ix1[50], ix2[50];
Double_t iy1prime[50], iy2prime[50];
Double_t idiff1[50], isum1[50];
Double_t idiff2[50], isum2[50];
for (int i=0; i<50; i++) {
ix1[i]=corx*g1->GetX()[i];
ix2[i]=corx*g2->GetX()[i];
iy1prime[i]=cory*(1.-(g1->GetX()[i]))*(g1->GetY()[i]);
iy2prime[i]=cory*(1.-(g2->GetX()[i]))*(g2->GetY()[i]);
idiff1[i]=ix1[i]-iy1prime[i];
isum1[i]=ix1[i]+iy1prime[i];
idiff2[i]=ix2[i]-iy2prime[i];
isum2[i]=ix2[i]+iy2prime[i];
}
Double_t mx=corx*point->GetX();
Double_t my=cory*(1-point->GetX())*point->GetY();
TMarker *dpoint; //= new TMarker(mx, my, 8);
TGraph *c1, *c2;
if (mode) {
c1 = new TGraph(50,ix1,iy1prime);
c2 = new TGraph(50,ix2,iy2prime);
dpoint=new TMarker(mx,my,8);
h->SetTitle(";f_{L};f_{R}");
} else {
c1 = new TGraph(50,idiff1,isum1);
c2 = new TGraph(50,idiff2,isum2);
dpoint=new TMarker((mx-my),(mx+my),8);
h->SetTitle(";f_{L}-f_{R};f_{L}+f_{R}");
}
c1->SetLineStyle(1) ;
c1->SetLineWidth(2) ;
c1->SetLineColor(kBlue) ;
c2->SetLineStyle(2) ;
c2->SetLineWidth(2) ;
c2->SetLineColor(kBlue) ;
// c1->Draw("A");
h->addObject(dpoint);
h->addObject(c1,"L");
h->addObject(c2,"L");
/*
for (int ix=0; ix<=contour->GetNbinsX(); ix++) {
for (int iy=0; iy<=contour->GetNbinsY(); iy++) {
double content=contour->GetBinContent(ix,iy);
double y1=contour->GetXaxis()->GetBinCenter(ix);
double y2=contour->GetYaxis()->GetBinCenter(iy);
double yprime=(1-y1)*y2;
int iyprime=contour->GetYaxis()->FindBin(yprime);
h->SetBinContent(ix,iyprime);
}
}
*/
// h->Draw();
return h;
}
void toyMC(
int collId = kAADATA,
float ptLow=0, float ptHigh=5,
float yLow=0, float yHigh=2.4,
int cLow=0, int cHigh=200,
float muPtCut=4.0,
int inputOption=kChPol4, //kChPol3,
int nGen = 10000,
int useCentIntBkgShape = 1,
int nToys = 1000
)
{
using namespace RooFit;
RooRandom::randomGenerator()->SetSeed(111);
gStyle->SetEndErrorSize(0);
float Val_2S_1S_nom = 0;
float Val_2S_1S_alt = 0;
float Dev_2S_1S = 0;
TString fcoll;
TString finput;
if(collId == kAADATA) fcoll = "AA";
else if(collId == kPPDATA) fcoll = "PP";
if(inputOption == 3) finput = "4th poly";
else if(inputOption == 4) finput = "Nominal+Exp";
TFile *wf = new TFile(Form("%s_fit_pt%.1f-%.1f_rap%.1f-%.1f_cent%d-%d_Gen%d_input%d_useCentBkg%d_nToys%d.root",fcoll.Data(),ptLow,ptHigh,yLow,yHigh,cLow,cHigh,nGen,inputOption,useCentIntBkgShape,nToys),"recreate");
TH1D *h1 = new TH1D("h1",Form("SR Nominal, %d toys, %d events, cent %d-%d;2S/1S nom;Counts",nToys,nGen,cLow,cHigh),100,0,1);
TH1D *h2 = new TH1D("h2",Form("SR %s, %d toys, %d events, cent %d-%d;2S/1S nom;Counts",finput.Data(),nToys,nGen,cLow,cHigh),100,0,1);
TH1D *h3 = new TH1D("h3","Deviation;2S/1S dev;Counts",1000,0,100);
//----****************--------for loop -----*******************-----------------
//----****************--------for loop -----*******************-----------------
//----****************--------for loop -----*******************-----------------
//----****************--------for loop -----*******************-----------------
//----****************--------for loop -----*******************-----------------
for(int i=0;i<nToys;i++){
float massLow = 8. ;
float massHigh = 14.;
int nMassBin = (massHigh-massLow)*10;
RooWorkspace *ws = new RooWorkspace("ws");
RooWorkspace *wsinp = new RooWorkspace("wsinp");
RooRealVar mass("mass","mass", massLow, massHigh);
ws->import(mass);
wsinp->import(mass);
mass.Print();
RooRealVar mRatio21("mRatio21","mRatio21",pdgMass.Y2S / pdgMass.Y1S );
RooRealVar mRatio31("mRatio31","mRatio31",pdgMass.Y3S / pdgMass.Y1S );
RooRealVar mean1s("m_{#Upsilon(1S)}","mean of the signal gaussian mass PDF",pdgMass.Y1S, pdgMass.Y1S -0.1, pdgMass.Y1S + 0.1 ) ;
PSet3SingleCB InitialSetUpsilons = getUpsilonPsets( collId, ptLow, ptHigh, yLow, yHigh, cLow, cHigh, muPtCut) ;
RooRealVar sigma1s_1("sigma1s_1","width/sigma of the signal gaussian mass PDF",0.05, 0.05, 0.14);
RooRealVar sigma2s_1("sigma2s_1","width/sigma of the signal gaussian mass PDF",0.05, 0.05, 0.14);
RooRealVar sigma1s_2("sigma1s_2","width/sigma of the signal gaussian mass PDF",0.05, 0.05, 0.14);
RooRealVar sigma2s_2("sigma2s_2","width/sigma of the signal gaussian mass PDF",0.05, 0.05, 0.14);
RooRealVar alpha1s_1("alpha1s_1","tail shift", 5. , 1.0, 9.8);
RooRealVar alpha2s_1("alpha2s_1","tail shift", 5. , 1.15, 9.2);
RooRealVar alpha1s_2("alpha1s_2","tail shift", 5. , 1.0, 9.2);
RooRealVar alpha2s_2("alpha2s_2","tail shift", 2.5, 1.10, 10.);
RooRealVar n1s_1("n1s_1","power order", 5. , 1.4, 10.);
RooRealVar n2s_1("n2s_1","power order", 6. , 1.1, 9.5);
RooRealVar n1s_2("n1s_2","power order", 5. , 1.4, 10.);
RooRealVar n2s_2("n2s_2","power order", 6. , 1.1, 9.5);
RooRealVar *f1S = new RooRealVar("f1S","1S CB fraction", InitialSetUpsilons.MCf, InitialSetUpsilons.MCf*0.9, InitialSetUpsilons.MCf*1.1);
f1S->setVal(InitialSetUpsilons.MCf); f1S->setConstant();
RooRealVar X1S("X1S","sigma fraction 1S 2nd CB", InitialSetUpsilons.MCX, InitialSetUpsilons.MCX*0.9, InitialSetUpsilons.MCX*1.1);
// Fix the parameters
n1s_1.setVal(InitialSetUpsilons.MCN); n1s_1.setConstant();
n1s_2.setVal(InitialSetUpsilons.MCN); n1s_2.setConstant();
n2s_1.setVal(InitialSetUpsilons.MCN); n2s_1.setConstant();
n2s_2.setVal(InitialSetUpsilons.MCN); n2s_2.setConstant();
alpha1s_1.setVal(InitialSetUpsilons.MCAlpha); alpha1s_1.setConstant();
alpha1s_2.setVal(InitialSetUpsilons.MCAlpha); alpha1s_2.setConstant();
alpha2s_1.setVal(InitialSetUpsilons.MCAlpha); alpha2s_1.setConstant();
alpha2s_2.setVal(InitialSetUpsilons.MCAlpha); alpha2s_2.setConstant();
sigma1s_1.setVal(InitialSetUpsilons.MCSigma1S); sigma1s_1.setConstant();
sigma1s_2.setVal(InitialSetUpsilons.MCSigma1S); sigma1s_2.setConstant();
sigma2s_1.setVal(InitialSetUpsilons.MCSigma1S * InitialSetUpsilons.MCX ); sigma2s_1.setConstant();
sigma2s_2.setVal(InitialSetUpsilons.MCSigma1S * InitialSetUpsilons.MCX ); sigma2s_2.setConstant();
mean1s.setVal(InitialSetUpsilons.bkg_mass_res); mean1s.setConstant();
RooFormulaVar mean2s("mean2s","m_{#Upsilon(1S)}*mRatio21", RooArgSet(mean1s,mRatio21) );
RooFormulaVar mean3s("mean3s","m_{#Upsilon(1S)}*mRatio31", RooArgSet(mean1s,mRatio31) );
RooCBShape* cb1s_1 = new RooCBShape("cball1s_1", "cystal Ball", mass, mean1s, sigma1s_1, alpha1s_1, n1s_1);
RooCBShape* cb2s_1 = new RooCBShape("cball2s_1", "cystal Ball", mass, mean2s, sigma2s_1, alpha2s_1, n2s_1);
RooCBShape* cb1s_2 = new RooCBShape("cball1s_2", "cystal Ball", mass, mean1s, sigma1s_2, alpha1s_2, n1s_2);
RooCBShape* cb2s_2 = new RooCBShape("cball2s_2", "cystal Ball", mass, mean2s, sigma2s_2, alpha2s_2, n2s_2);
RooAddPdf* cb1s = new RooAddPdf();
RooAddPdf* cb2s = new RooAddPdf();
cb1s = new RooAddPdf("cb1s","Signal 1S",RooArgList(*cb1s_1,*cb1s_2), RooArgList(*f1S) );
cb2s = new RooAddPdf("cb2s","Signal 2S",RooArgList(*cb2s_1,*cb2s_2), RooArgList(*f1S) );
// Input model
PSet3SingleCB bkgParm = getUpsilonPsets( collId, ptLow, ptHigh, yLow, yHigh, cLow, cHigh, muPtCut) ;
PSet3SingleCB bkgParmCentInt;
if ( !( (cLow==0) && (cHigh==200) ) && (collId==kAADATA) ) {
bkgParmCentInt = getUpsilonPsets( collId, ptLow, ptHigh, yLow, yHigh, 0, 200, muPtCut) ;
cout << " ok done " << endl;
}
// if ( inputOption == kErrExp )
RooRealVar err_mu1("#mu1","err_mu1", bkgParm.bkg_mu1 ) ;
RooRealVar err_sigma1("#sigma1","err_sigma1", bkgParm.bkg_sigma1);
RooRealVar m_decay1("#lambda1","m_decay1", bkgParm.bkg_lambda1);
RooRealVar err_mu2("#mu2","err_mu2", bkgParm.bkg_mu2 ) ;
RooRealVar err_sigma2("#sigma2","err_sigma2", bkgParm.bkg_sigma2);
RooRealVar m_decay2("#lambda2","m_decay2", bkgParm.bkg_lambda2);
float the_ch3_k1 = bkgParm.ch3_k1 ; float the_ch3_k2 = bkgParm.ch3_k2 ; float the_ch3_k3 = bkgParm.ch3_k3 ;
float the_ch4_k1 = bkgParm.ch4_k1 ; float the_ch4_k2 = bkgParm.ch4_k2 ; float the_ch4_k3 = bkgParm.ch4_k3 ; float the_ch4_k4 = bkgParm.ch4_k4 ;
float the_bkg4_mu = bkgParm.bkg4_mu ; float the_bkg4_sigma = bkgParm.bkg4_sigma;
float the_bkg4_lambda = bkgParm.bkg4_lambda ; float the_bkg4_lambda2 = bkgParm.bkg4_lambda2 ;
if ( !( (cLow==0) && (cHigh==200) ) && (collId==kAADATA) && useCentIntBkgShape ) {
the_ch3_k1 = bkgParmCentInt.ch3_k1 ; the_ch3_k2 = bkgParmCentInt.ch3_k2 ; the_ch3_k3 = bkgParmCentInt.ch3_k3 ;
the_ch4_k1 = bkgParmCentInt.ch4_k1 ; the_ch4_k2 = bkgParmCentInt.ch4_k2 ; the_ch4_k3 = bkgParmCentInt.ch4_k3 ; the_ch4_k4 = bkgParmCentInt.ch4_k4 ;
the_bkg4_mu = bkgParmCentInt.bkg4_mu ; bkgParmCentInt.bkg4_sigma =bkgParmCentInt.bkg4_sigma;
the_bkg4_lambda = bkgParmCentInt.bkg4_lambda ; the_bkg4_lambda2 = bkgParmCentInt.bkg4_lambda2 ;
}
// if ( inputOption == kChPol3 )
RooRealVar ch3_k1("pol3_k1","pol3_k1", the_ch3_k1 ) ;
RooRealVar ch3_k2("pol3_k2","pol3_k2", the_ch3_k2 ) ;
RooRealVar ch3_k3("pol3_k3","pol3_k3", the_ch3_k3 ) ;
// if ( inputOption == kChPol4 )
RooRealVar ch4_k1("pol4_k1","pol4_k1", the_ch4_k1 , the_ch4_k1*0.3, the_ch4_k1*1.6) ;
RooRealVar ch4_k2("pol4_k2","pol4_k2", the_ch4_k2 , the_ch4_k2*0.3, the_ch4_k2*1.6) ;
RooRealVar ch4_k3("pol4_k3","pol4_k3", the_ch4_k3 , the_ch4_k3*0.3, the_ch4_k3*1.6) ;
RooRealVar ch4_k4("pol4_k4","pol4_k4", the_ch4_k4 , the_ch4_k4*0.3, the_ch4_k4*1.6) ;
// if (inputOption == kErrExpExp )
RooRealVar err4_mu("err4_mu","err4_mu", the_bkg4_mu , the_bkg4_mu*0.4,the_bkg4_mu*1.4) ;
RooRealVar err4_sigma("err4_sigma","err4_sigma", the_bkg4_sigma, the_bkg4_sigma*0.4, the_bkg4_sigma*1.4);
RooRealVar m4_decay("err4_lambda","m4_decay", the_bkg4_lambda, the_bkg4_lambda*0.4, the_bkg4_lambda*1.4);
RooRealVar m4_decay2("err4_lambda2","m4_decay2", the_bkg4_lambda2, the_bkg4_lambda2*0.4, the_bkg4_lambda2*1.4);
RooGenericPdf *bkgErrExp1;
RooGenericPdf *bkgErrExp2;
RooGenericPdf *bkg4ErrExp ; // kErrExpExp
RooGenericPdf *bkg4Exp = new RooGenericPdf("bkg4Exp","bkg4Exp","TMath::Exp(-@0/@1)",RooArgList(mass,m4_decay2));
if ( ptLow == 0) {
bkg4ErrExp = new RooGenericPdf("bkg4ErrExp","bkg4ErrExp","(TMath::Erf((@0-@1)/(TMath::Sqrt(2)*@2))+1)*0.5*TMath::Exp(-@0/@3)",RooArgList(mass,err4_mu,err4_sigma,m4_decay));
bkgErrExp1 = new RooGenericPdf("bkgErrExp1","Background1","(TMath::Erf((@0-@1)/(TMath::Sqrt(2)*@2))+1)*0.5*TMath::Exp(-@0/@3)",RooArgList(mass,err_mu1,err_sigma1,m_decay1));
bkgErrExp2 = new RooGenericPdf("bkgErrExp2","Background2","(TMath::Erf((@0-@1)/(TMath::Sqrt(2)*@2))+1)*0.5*TMath::Exp(-@0/@3)",RooArgList(mass,err_mu2,err_sigma2,m_decay2));
}
else { // if ptLow >= 5
bkg4ErrExp = new RooGenericPdf("bkg4ErrExp","bkg4ErrExp", "TMath::Exp(-@0/@1)",RooArgList(mass,m4_decay));
bkgErrExp1 = new RooGenericPdf("bkgErrExp1","Background1","TMath::Exp(-@0/@1)",RooArgList(mass,m_decay1));
bkgErrExp2 = new RooGenericPdf("bkgErrExp2","Background2","TMath::Exp(-@0/@1)",RooArgList(mass,m_decay2));
}
RooRealVar* rBkg2nd = new RooRealVar("rBkg2over1","rBkg2over1", bkgParm.rBkg42over1); // bkgParm.rBkgErr2over1
RooAddPdf* bkgDblErr = new RooAddPdf("bkgDblErrExp","Bkg Only",RooArgList(*bkgErrExp2, *bkgErrExp1),RooArgList(*rBkg2nd)); // if ( inputOption == kErrExp )
RooAddPdf* bkgComp4 = new RooAddPdf("bkgComp4","bkgComp4",RooArgList(*bkg4Exp, *bkg4ErrExp),RooArgList(*rBkg2nd)); // if ( inputOption == kErrExp )
RooChebychev * bkgChPol3 = new RooChebychev("cPolBkg","Background1",mass,RooArgSet(ch3_k1,ch3_k2,ch3_k3)); // if ( inputOption == kChPol3 )
RooChebychev * bkgChPol4 = new RooChebychev("cPol4Bkg","Background4",mass,RooArgSet(ch4_k1,ch4_k2,ch4_k3,ch4_k4)); // if ( inputOption == kChPol3 )
float r1S_overTot = bkgParm.nSignal1s / ( bkgParm.nSignal1s + bkgParm.nSignal2s + bkgParm.nBkg ) ; // Numbers obtained from the real data
float r2S_overTot = bkgParm.nSignal2s / ( bkgParm.nSignal1s + bkgParm.nSignal2s + bkgParm.nBkg ) ;
float rBkg_overTot = bkgParm.nBkg / ( bkgParm.nSignal1s + bkgParm.nSignal2s + bkgParm.nBkg ) ;
RooRealVar *nSig1sInp = new RooRealVar("nSig1sInp","nSig1sInp", nGen * r1S_overTot, 0, nGen);
RooRealVar *nSig2sInp = new RooRealVar("nSig2sInp","nSig2sInp", nGen * r2S_overTot, 0, nGen);
RooRealVar *nBkgInp = new RooRealVar("nBkgInp","n_bkgInp", nGen * rBkg_overTot, 0, nGen);
//----------------------------------------------------------------------------------------
//Generating function from nominal fit
RooRealVar err_mu_gen("err_mu_gen","err_mu_gen", bkgParm.bkg_mu_res) ;
RooRealVar err_sigma_gen("err_sigma_gen","err_sigma_gen", bkgParm.bkg_sigma_res);
RooRealVar m_decay_gen("err_lambda_gen","m_decay_gen", bkgParm.bkg_lambda_res);
err_mu_gen.setVal(bkgParm.bkg_mu_res); err_mu_gen.setConstant();
err_sigma_gen.setVal(bkgParm.bkg_sigma_res); err_sigma_gen.setConstant();
m_decay_gen.setVal(bkgParm.bkg_lambda_res); m_decay_gen.setConstant();
RooGenericPdf* bkgInp_gen;
RooGenericPdf *bkgInp_in;
if ( ptLow == 0) {
bkgInp_in = new RooGenericPdf("bkgInp_gen","Background Gen","(TMath::Erf((@0-@1)/(TMath::Sqrt(2)*@2))+1)*0.5*TMath::Exp(-@0/@3)",RooArgList(mass,err_mu_gen,err_sigma_gen,m_decay_gen));
}
else {
bkgInp_in = new RooGenericPdf("bkgInp_gen","Background Gen","TMath::Exp(-@0/@1)",RooArgList(mass,m_decay_gen));
}
bkgInp_gen = bkgInp_in;
RooAddPdf* modelInput_gen;
modelInput_gen = new RooAddPdf("modelInput_gen","1S+2S + Bkg",RooArgList(*cb1s, *cb2s, *bkgInp_gen),RooArgList(*nSig1sInp,*nSig2sInp,*nBkgInp));
//----------------------------------------------------------------------------------------
//----------------------------------------------------------------------------------------
RooAddPdf* modelInput;
RooGenericPdf* bkgInp;
if ( inputOption == kErrExp ) {
bkgInp = (RooGenericPdf*) bkgDblErr;
}
else if ( inputOption == kChPol3 ) {
bkgInp = (RooGenericPdf*) bkgChPol3;
}
else if ( inputOption == kChPol4 ) {
bkgInp = (RooGenericPdf*) bkgChPol4;
}
else if ( inputOption == kErrExpExp ) {
bkgInp = (RooGenericPdf*) bkgComp4;
}
modelInput = new RooAddPdf("modelInput","1S+2S + Bkg",RooArgList(*cb1s, *cb2s, *bkgInp),RooArgList(*nSig1sInp,*nSig2sInp,*nBkgInp));
wsinp->import(*modelInput);
Val_2S_1S_nom=0;
Val_2S_1S_alt=0;
Dev_2S_1S=0;
RooDataSet *data = modelInput_gen->generate(mass,nGen) ;
RooPlot* xframe = ws->var("mass")->frame(nMassBin); // bins
xframe->SetXTitle("mass (Gev/c^{2})");
xframe->GetXaxis()->CenterTitle();
xframe->GetYaxis()->CenterTitle();
RooPlot* xframe2 = (RooPlot*)xframe->Clone("xframe2");
RooFitResult* fitResInput = wsinp->pdf("modelInput")->fitTo(*data,Save(), Hesse(kTRUE),Range(massLow, massHigh),Minos(0), SumW2Error(kTRUE));
data->plotOn(xframe,Name("dataHist"),MarkerSize(0.7)) ;
wsinp->pdf("modelInput")->plotOn(xframe, Name("inputModelHist"));
wsinp->pdf("modelInput")->plotOn(xframe, Components(RooArgSet(*bkgInp)),LineColor(kBlack),LineStyle(kDashed));
if ( inputOption == kErrExp )
{
modelInput->plotOn(xframe,Components(RooArgSet(*bkgDblErr)),LineColor(kRed),LineStyle(kDashed));
modelInput->plotOn(xframe,Components(RooArgSet(*bkgErrExp1)),LineColor(kBlack),LineStyle(kDashed));
modelInput->plotOn(xframe,Components(RooArgSet(*bkgErrExp2)),LineColor(kBlack),LineStyle(kDashed));
}
else if ( inputOption == kChPol3 )
modelInput->plotOn(xframe,Components(RooArgSet(*bkgChPol3)),LineColor(kBlack),LineStyle(kDashed));
else if ( inputOption == kChPol4 )
modelInput->plotOn(xframe,Components(RooArgSet(*bkgChPol4)),LineColor(kBlack),LineStyle(kDashed));
else if (inputOption == kErrExpExp ) {
modelInput->plotOn(xframe,Components(RooArgSet(*bkgComp4)),LineColor(kBlack),LineStyle(kDashed));
modelInput->plotOn(xframe,Components(RooArgSet(*bkg4ErrExp)),LineColor(kBlack),LineStyle(kDashed));
modelInput->plotOn(xframe,Components(RooArgSet(*bkg4Exp)),LineColor(kBlack),LineStyle(kDashed));
}
// New fit
float the_bkg_mu = bkgParm.bkg_mu ;
float the_bkg_sigma = bkgParm.bkg_sigma ;
float the_bkg_lambda = bkgParm.bkg_lambda ;
if ( !( (cLow==0) && (cHigh==200) ) && (collId==kAADATA) && useCentIntBkgShape ) {
the_bkg_mu = bkgParmCentInt.bkg_mu ;
the_bkg_sigma = bkgParmCentInt.bkg_sigma ;
the_bkg_lambda = bkgParmCentInt.bkg_lambda ;
}
//RooRealVar err_mu("err_mu","err_mu", the_bkg_mu, 0.0, 40);
RooRealVar err_mu("err_mu","err_mu", the_bkg_mu, the_bkg_mu*0.4, the_bkg_mu*1.4);
//RooRealVar err_mu("err_mu","err_mu", 1., 0.0, 30);
//RooRealVar err_sigma("err_sigma","err_sigma", 1.2, 1.1,55);
//RooRealVar err_sigma("err_sigma","err_sigma", 10.,0,20);
RooRealVar err_sigma("err_sigma","err_sigma", the_bkg_sigma, the_bkg_sigma*0.4, the_bkg_sigma*1.4);
//RooRealVar m_decay("m_decay","m_decay", 10., 6.5, 30);
RooRealVar m_decay("m_decay","m_decay",the_bkg_lambda, the_bkg_lambda*0.4, the_bkg_lambda*1.4);
if( ( ptLow == (float)0 ) && (ptHigh == (float)30 ) && (yLow == (float)0 ) && (yHigh == (float)2.4) && collId==kPPDATA)
{
err_sigma.setVal(1.055);
err_sigma.setConstant();
}
if( ( ptLow == (float)0 ) && (ptHigh == (float)30 ) && (yLow == (float)0 ) && (yHigh == (float)2.4) && collId==kAADATA)
{
err_sigma.setVal(1.103);
err_sigma.setConstant();
}
RooGenericPdf *bkgFitOut;
if ( ptLow == 0) {
bkgFitOut = new RooGenericPdf("bkgFitOut","BackgroundOut","(TMath::Erf((@0-@1)/(TMath::Sqrt(2)*@2))+1)*0.5*TMath::Exp(-@0/@3)",RooArgList(mass,err_mu,err_sigma,m_decay));
}
else {
bkgFitOut = new RooGenericPdf("bkgFitOut","BackgroundOut","TMath::Exp(-@0/@1)",RooArgList(mass,m_decay));
}
RooRealVar *nSig1sOut = new RooRealVar("nSig1sOut","nSig1sOut", r1S_overTot*nGen, 0, r1S_overTot*2.*nGen);
RooRealVar *nSig2sOut = new RooRealVar("nSig2sOut","nSig2sOut", r2S_overTot*nGen, 0, r2S_overTot*2.*nGen);
RooRealVar *nBkgOut = new RooRealVar("nBkgOut","n_bkgOut",nGen * rBkg_overTot, 0, nGen);
RooAddPdf* cb1sOut = (RooAddPdf*)cb1s->Clone("cb1sOutput");
RooAddPdf* cb2sOut = (RooAddPdf*)cb2s->Clone("cb2sOutput");
RooAddPdf* modelOutput = new RooAddPdf("modelOutput","1S+2S + Bkg",RooArgList(*cb1sOut, *cb2sOut, *bkgFitOut),RooArgList(*nSig1sOut,*nSig2sOut,*nBkgOut));
ws->import(*modelOutput);
RooFitResult* fitRes = ws->pdf("modelOutput")->fitTo(*data,Save(), Hesse(kTRUE),Range(massLow, massHigh),Minos(0), SumW2Error(kTRUE));
data->plotOn(xframe2,Name("dataHist2"),MarkerSize(0.7)) ;
ws->pdf("modelOutput")->plotOn(xframe2, Name("outputModelHist"));
ws->pdf("modelOutput")->plotOn(xframe2, Components(RooArgSet(*bkgFitOut)),LineColor(kBlack),LineStyle(kDashed));
Val_2S_1S_nom = (float)(ws->var("nSig2sOut")->getVal() / ws->var("nSig1sOut")->getVal());
Val_2S_1S_alt = (float)(wsinp->var("nSig2sInp")->getVal() / wsinp->var("nSig1sInp")->getVal());
Dev_2S_1S = (Val_2S_1S_alt/Val_2S_1S_nom - 1) * 100;
h1->Fill(Val_2S_1S_nom);
h2->Fill(Val_2S_1S_alt);
h3->Fill(Dev_2S_1S);
// DRAW!
if(i == 0){
TCanvas* c1 = new TCanvas("canvas2","My plots",4,45,800,400);
c1->cd();
TPad *pad1 = new TPad("pad1", "pad1", 0, 0.25, 0.49, 1.0);
pad1->SetTicks(1,1);
pad1->Draw(); pad1->cd();
pad1->SetBottomMargin(0); // Upper and lower plot are joined
xframe->GetYaxis()->SetTitleOffset(1.4) ; xframe->Draw() ;
drawText(Form("#Upsilon(2S)/#Upsilon(1S) = %.5f",(float)(wsinp->var("nSig2sInp")->getVal() / wsinp->var("nSig1sInp")->getVal())),0.2,0.54,1,16) ;
if (inputOption==kChPol4 )
drawText("4th order poly. Bkg.",0.2,0.62,2,15) ;
if (inputOption==kErrExpExp )
drawText("Erf*exp + exp Bkg.",0.2,0.62,2,15) ;
if(collId == kAADATA)
drawText("PbPb",0.4,0.45,1,15);
if(collId == kPPDATA)
drawText("pp", 0.4,0.45,1,15);
drawText(Form("%.1f < p_{T}^{#mu#mu} < %.1f GeV",ptLow,ptHigh ),0.5,0.60,1,12);
drawText(Form("%.1f < y^{#mu#mu} < %.1f",yLow,yHigh ), 0.5,0.55,1,12);
TString perc = "%";
if(collId == kAADATA)
drawText(Form("Cent %d-%d%s",cLow/2,cHigh/2,perc.Data()),0.5,0.5,4,12);
TLatex *tex = new TLatex(0.4,0.88,"Toy MC generated");
tex->SetTextFont(43);
tex->SetTextSize(15);
tex->SetNDC();
// tex->SetTextAngle(180);
tex->Draw();
RooArgList paramListinp = fitResInput->floatParsFinal();
paramListinp.Print("v");
RooPlot* legFrameinp = wsinp->var("mass")->frame(Name("Fit Results"), Title("Fit Results"));
wsinp->pdf("modelInput")->paramOn(legFrameinp,Layout(.6,.9, .5),Parameters(paramListinp));
legFrameinp->getAttText()->SetTextAlign(11);
legFrameinp->getAttText()->SetTextSize(0.028);
TPaveText* hhinp = (TPaveText*)legFrameinp->findObject(Form("%s_paramBox",wsinp->pdf("modelInput")->GetName()));
hhinp->SetY1(0.35); hhinp->SetY2(0.83);
hhinp->Draw();
// PULL
TPad *pad2 = new TPad("pad2", "pad2", 0, 0.05, 0.49, 0.25);
c1->cd();
pad2->Draw();
pad2->cd();
RooHist* hpull = xframe->pullHist("dataHist","inputModelHist");
RooPlot* pullFrame = wsinp->var("mass")->frame(Title("Pull Distribution")) ;
pullFrame->addPlotable(hpull,"P") ;
pullFrame->SetTitleSize(2.57);
pullFrame->GetYaxis()->SetTitleOffset(1.8) ;
pullFrame->GetYaxis()->SetLabelSize(0.16) ;
pullFrame->GetYaxis()->SetRange(-10,10) ;
pullFrame->GetXaxis()->SetTitleOffset(0.7) ;
pullFrame->GetXaxis()->SetLabelSize(0.1) ;
pullFrame->GetXaxis()->SetTitleSize(0.13) ;
pullFrame->Draw() ;
TPad *pad3 = new TPad("pad3", "pad3", 0.51, 0.25, 0.99, 1);
pad3->SetTicks(1,1);
pad3->SetBottomMargin(0); // Upper and lower plot are joined
c1->cd();
pad3->Draw(); pad3->cd();
xframe2->GetYaxis()->SetTitleOffset(1.4) ; xframe2->Draw() ;
TLatex *tex2 = new TLatex(0.4,0.9,"Fitted by Nominal function");
tex2->SetTextFont(43);
tex2->SetTextSize(15);
tex2->SetTextColor(2);
tex2->SetNDC();
tex2->Draw();
drawText(Form("#Upsilon(2S)/#Upsilon(1S) = %.5f",(float)(ws->var("nSig2sOut")->getVal() / ws->var("nSig1sOut")->getVal())), 0.4,0.85,1,16 );
// *~*~*~*~*~*~*~* Draw the parameters in the plot *~*~*~*~*~*~*~* //
RooArgList paramList = fitRes->floatParsFinal();
paramList.Print("v");
RooPlot* legFrame = ws->var("mass")->frame(Name("Fit Results"), Title("Fit Results"));
ws->pdf("modelOutput")->paramOn(legFrame,Layout(.6,.9, .5),Parameters(paramList));
legFrame->getAttText()->SetTextAlign(11);
legFrame->getAttText()->SetTextSize(0.028);
TPaveText* hh = (TPaveText*)legFrame->findObject(Form("%s_paramBox",ws->pdf("modelOutput")->GetName()));
hh->SetY1(0.35); hh->SetY2(0.83);
hh->Draw();
TPad *pad4 = new TPad("pad4", "pad4", 0.51, 0.05, 0.99, 0.25);
// pad4->SetBottomMargin(0); // Upper and lower plot are joined
c1->cd();
pad4->Draw();
pad4->cd();
RooHist* hpullOut = xframe2->pullHist("dataHist2","outputModelHist");
RooPlot* pullOutFrm = ws->var("mass")->frame(Title("Pull Distribution")) ;
pullOutFrm->addPlotable(hpullOut,"P") ;
pullOutFrm->SetTitleSize(2.57);
pullOutFrm->GetYaxis()->SetTitleOffset(1.8) ;
pullOutFrm->GetYaxis()->SetLabelSize(0.16) ;
pullOutFrm->GetYaxis()->SetRange(-10,10) ;
pullOutFrm->GetXaxis()->SetTitleOffset(0.7) ;
pullOutFrm->GetXaxis()->SetLabelSize(0.1) ;
pullOutFrm->GetXaxis()->SetTitleSize(0.13) ;
pullOutFrm->Draw() ;
// *~*~*~*~*~*~*~* Print the results *~*~*~*~*~*~*~* //
//cout << "nSig2sInp/nSig1sInp = " << nSig2sInp->getVal() / nSig1sInp->getVal() << endl;
cout << "input fit ratio = " << wsinp->var("nSig2sInp")->getVal() / wsinp->var("nSig1sInp")->getVal() << endl;
cout << "output fit ratio = " << ws->var("nSig2sOut")->getVal() / ws->var("nSig1sOut")->getVal() << endl;
c1->SaveAs(Form( "toyMCFit_collId%d_pt%.0f-%.0fGeV_y%.0f-%.0f_cBin%d-%d_muPtCut%.0fGeV_BkgPDFOpt%d_nGen%d_useCentIntBkgShape%d.png",
collId, ptLow, ptHigh, yLow*10, yHigh*10, cLow, cHigh, muPtCut, inputOption, nGen,useCentIntBkgShape) );
float r1 = wsinp->var("nSig2sInp")->getVal() / wsinp->var("nSig1sInp")->getVal() ;
float r2 = ws->var("nSig2sOut")->getVal() / ws->var("nSig1sOut")->getVal() ;
cout << Form( "collId: %d, pt: %.0f - %.0fGeV, y: %.1f - %.1f, cBin: %d - %d", collId, ptLow, ptHigh, yLow, yHigh, cLow, cHigh ) << endl;
cout << "Uncertainty = " << (r2 - r1 ) / r1 << endl;
}
}
wf->cd();
h1->Write();
h2->Write();
h3->Write();
}
void plotPdf_5D_XZZ() {
gROOT->ProcessLine(".L ~/tdrstyle.C");
setTDRStyle();
gStyle->SetPadLeftMargin(0.16);
// Declaration of the PDFs to use
gROOT->ProcessLine(".L PDFs/RooSpinTwo_5D.cxx++");
// Observables (5D)
RooRealVar* h1 = new RooRealVar("costheta1","h1",-1,1);
RooRealVar* h2 = new RooRealVar("costheta2","h2",-1,1);
RooRealVar* hs = new RooRealVar("costhetastar","hs",-1,1);
RooRealVar* Phi = new RooRealVar("phi","Phi",-TMath::Pi(),TMath::Pi());
RooRealVar* Phi1 = new RooRealVar("phistar1","Phi1",-TMath::Pi(),TMath::Pi());
// angular variables
// These values correspond to the 2m+
RooRealVar* fppVal = new RooRealVar("fppVal", "fppVal", 0.013);
RooRealVar* fmmVal = new RooRealVar("fmmVal", "fmmVal", 0.013);
RooRealVar* fpmVal = new RooRealVar("fpmVal", "fpmVal", 0.282);
RooRealVar* fp0Val = new RooRealVar("fp0Val", "fp0Val", 0.075);
RooRealVar* f0mVal = new RooRealVar("f0mVal", "f0mVal", 0.075);
RooRealVar* phippVal = new RooRealVar("phippVal", "phippVal", 0);
RooRealVar* phimmVal = new RooRealVar("phimmVal", "phimmVal", 0);
RooRealVar* phipmVal = new RooRealVar("phipmVal", "phipmVal", 0);
RooRealVar* phip0Val = new RooRealVar("phip0Val", "phip0Val", 0);
RooRealVar* phi0mVal = new RooRealVar("phi0mVal", "phi0mVal", 0);
// related to the gg/qq productions
RooRealVar* fz1Val = new RooRealVar("fz1Val", "fz1Val", 0);
RooRealVar* fz2Val = new RooRealVar("fz2Val", "fz2Val", 1.0);
// Even more parameters, do not have to touch, based on Z couplings
RooRealVar* R1Val = new RooRealVar("R1Val","R1Val",0.15);
RooRealVar* R2Val = new RooRealVar("R2Val","R2Val",0.15);
// these are the acceptance terms associated with the production angles
// the default setting is for setting no-acceptance
RooRealVar* para2 = new RooRealVar("para2", "para2", 0);
RooRealVar* para4 = new RooRealVar("para4", "para4", 0);
RooRealVar* para6 = new RooRealVar("para6", "para6", 0);
RooRealVar* para8 = new RooRealVar("para8", "para8", 0);
RooRealVar* acca0 = new RooRealVar("acca0", "acca0", 1);
RooRealVar* acca1 = new RooRealVar("acca1", "acca1", 0);
RooRealVar* acca2 = new RooRealVar("acca2", "acca2", 0);
RooRealVar* acca4 = new RooRealVar("acca4", "acca4", 0);
// PDF definition SM Higgs (JP = 2+)
RooSpinTwo_5D *myPDF = new RooSpinTwo_5D("myPDF","myPDF", *h1, *h2, *hs, *Phi, *Phi1, *fppVal, *fmmVal, *fpmVal, *fp0Val, *f0mVal, *phippVal, *phimmVal, *phipmVal, *phip0Val, *phi0mVal, *fz1Val, *fz2Val, *R1Val, *R2Val, *para2, *para4, *para6, *para8, *acca0, *acca1, *acca2, *acca4);
// dataset for (JP = 2+)
TFile* fin = new TFile("THiggsZZ_250_JHU.root");
TTree* tin = (TTree*) fin->Get("angles");
RooDataSet data("data","data",tin,RooArgSet(*h1,*h2, *hs, *Phi, *Phi1));
/*
for (int i=1;i<10;i++) {
RooArgSet* row = data.get(i);
row->Print("v");
std::cout << "weight: " << data.weight() << std::endl;
}
*/
// setting for 2-
RooRealVar* fppValp = new RooRealVar("fppValp", "fppValp", 0.1251);
RooRealVar* fmmValp = new RooRealVar("fmmValp", "fmmValp", 0.1251);
RooRealVar* fpmValp = new RooRealVar("fpmValp", "fpmValp", 0.);
RooRealVar* fp0Valp = new RooRealVar("fp0Valp", "fp0Valp", 0.1874);
RooRealVar* f0mValp = new RooRealVar("f0mValp", "f0mValp", 0.1874);
RooRealVar* phippValp = new RooRealVar("phippValp", "phippValp", TMath::Pi());
RooRealVar* phimmValp = new RooRealVar("phimmValp", "phimmValp", 0);
RooRealVar* phipmValp = new RooRealVar("phipmValp", "phipmValp", 0);
RooRealVar* phip0Valp = new RooRealVar("phip0Valp", "phip0Valp", TMath::Pi());
RooRealVar* phi0mValp = new RooRealVar("phi0mValp", "phi0mValp", 0);
RooSpinTwo_5D *myPDFA = new RooSpinTwo_5D("myPDF","myPDF", *h1, *h2, *hs, *Phi, *Phi1, *fppValp, *fmmValp, *fpmValp, *fp0Valp, *f0mValp, *phippValp, *phimmValp, *phipmValp, *phip0Valp, *phi0mValp, *fz1Val, *fz2Val, *R1Val, *R2Val, *para2, *para4, *para6, *para8, *acca0, *acca1, *acca2, *acca4);
// dataset for (JP = 2-)
TFile* fin2 = new TFile("PTHiggsZZ_250_JHU.root");
TTree* tin2 = (TTree*) fin2->Get("angles");
RooDataSet data2("data2","data2",tin2,RooArgSet(*h1,*h2, *hs, *Phi, *Phi1));
// setting for 2L+
RooRealVar* fppVal2L = new RooRealVar("fppVal2L", "fppVal2L", 0.104);
RooRealVar* fmmVal2L = new RooRealVar("fmmVal2L", "fmmVal2L", 0.104);
RooRealVar* fpmVal2L = new RooRealVar("fpmVal2L", "fpmVal2L", 0.);
RooRealVar* fp0Val2L = new RooRealVar("fp0Val2L", "fp0Val2L", 0.);
RooRealVar* f0mVal2L = new RooRealVar("f0mVal2L", "f0mVal2L", 0.);
RooRealVar* phippVal2L = new RooRealVar("phippVal2L", "phippVal2L", TMath::Pi());
RooRealVar* phimmVal2L = new RooRealVar("phimmVal2L", "phimmVal2L", TMath::Pi());
RooRealVar* phipmVal2L = new RooRealVar("phipmVal2L", "phipmVal2L", 0);
RooRealVar* phip0Val2L = new RooRealVar("phip0Val2L", "phip0Val2L", 0);
RooRealVar* phi0mVal2L = new RooRealVar("phi0mVal2L", "phi0mVal2L", 0);
RooRealVar* fz1Val2L = new RooRealVar("fz1Val2L", "fz1Val2L", 0);
RooRealVar* fz2Val2L = new RooRealVar("fz2Val2L", "fz2Val2L", 0.4);
RooSpinTwo_5D *myPDF2L = new RooSpinTwo_5D("myPDF","myPDF", *h1, *h2, *hs, *Phi, *Phi1, *fppVal2L, *fmmVal2L, *fpmVal2L, *fp0Val2L, *f0mVal2L, *phippVal2L, *phimmVal2L, *phipmVal2L, *phip0Val2L, *phi0mVal2L, *fz1Val2L, *fz2Val2L, *R1Val, *R2Val, *para2, *para4, *para6, *para8, *acca0, *acca1, *acca2, *acca4);
// dataset for (JP = 2-)
TFile* fin3 = new TFile("2LZZ_250_JHU.root");
TTree* tin3 = (TTree*) fin3->Get("angles");
RooDataSet data3("data3","data3",tin3,RooArgSet(*h1,*h2, *hs, *Phi, *Phi1));
// P L O T . . .
// (All parameters fixed, no fitting, just looking at the shape of the PDFs w.r.t. the data)
TH1F* dum0 = new TH1F("dum0","dum0",1,0,1); dum0->SetLineColor(kRed); dum0->SetMarkerColor(kBlack); dum0->SetLineWidth(3); // 2m+
TH1F* dum1 = new TH1F("dum1","dum1",1,0,1); dum1->SetLineColor(kBlue); dum1->SetMarkerColor(kBlack); dum1->SetMarkerStyle(24), dum1->SetLineWidth(3); // 2-
TH1F* dum2 = new TH1F("dum2","dum2",1,0,1); dum2->SetLineColor(kGreen); dum2->SetMarkerColor(kBlack); dum2->SetMarkerStyle(21), dum2->SetLineWidth(3); // 2L+
TLegend * box3 = new TLegend(0.1,0.1,0.9,0.92);
box3->SetFillColor(0);
box3->SetBorderSize(0);
box3->AddEntry(dum0,"X#rightarrow ZZ JP = 2m+","lp");
box3->AddEntry(dum1,"X#rightarrow ZZ JP = 2-","lp");
box3->AddEntry(dum2,"X#rightarrow ZZ JP = 2L+","lp");
RooPlot* h1frame = h1->frame(55);
data.plotOn(h1frame, LineColor(kBlack));
myPDF->plotOn(h1frame, LineColor(kRed));
data2.plotOn(h1frame, LineColor(kBlack), MarkerStyle(24));
myPDFA->plotOn(h1frame, LineColor(kBlue));
data3.plotOn(h1frame, LineColor(kBlack), MarkerStyle(21));
myPDF2L->plotOn(h1frame, LineColor(kGreen));
RooPlot* h2frame = h2->frame(55);
data.plotOn(h2frame, LineColor(kBlack));
myPDF->plotOn(h2frame, LineColor(kRed));
data2.plotOn(h2frame, LineColor(kBlack), MarkerStyle(24));
myPDFA->plotOn(h2frame, LineColor(kBlue));
data3.plotOn(h2frame, LineColor(kBlack), MarkerStyle(21));
myPDF2L->plotOn(h2frame, LineColor(kGreen));
RooPlot* hsframe = hs->frame(55);
data.plotOn(hsframe, LineColor(kBlack));
myPDF->plotOn(hsframe, LineColor(kRed));
data2.plotOn(hsframe, LineColor(kBlack), MarkerStyle(24));
myPDFA->plotOn(hsframe, LineColor(kBlue));
data3.plotOn(hsframe, LineColor(kBlack), MarkerStyle(21));
myPDF2L->plotOn(hsframe, LineColor(kGreen));
RooPlot* Phiframe = Phi->frame(55);
data.plotOn(Phiframe, LineColor(kBlack));
myPDF->plotOn(Phiframe, LineColor(kRed));
data2.plotOn(Phiframe, LineColor(kBlack), MarkerStyle(24));
myPDFA->plotOn(Phiframe, LineColor(kBlue));
data3.plotOn(Phiframe, LineColor(kBlack), MarkerStyle(21));
myPDF2L->plotOn(Phiframe, LineColor(kGreen));
RooPlot* Phi1frame = Phi1->frame(55);
data.plotOn(Phi1frame, LineColor(kBlack));
myPDF->plotOn(Phi1frame, LineColor(kRed));
data2.plotOn(Phi1frame, LineColor(kBlack), MarkerStyle(24));
myPDFA->plotOn(Phi1frame, LineColor(kBlue));
data3.plotOn(Phi1frame, LineColor(kBlack), MarkerStyle(21));
myPDF2L->plotOn(Phi1frame, LineColor(kGreen));
TCanvas* czz = new TCanvas( "czz", "czz", 1000, 600 );
czz->Divide(3,2);
czz->cd(1);
hsframe->Draw();
czz->cd(2);
Phi1frame->Draw();
czz->cd(3);
box3->Draw();
czz->cd(4);
h1frame->Draw();
czz->cd(5);
h2frame->Draw();
czz->cd(6);
Phiframe->Draw();
czz->SaveAs("epsfiles/angles_TZZ250_JHU.eps");
czz->SaveAs("pngfiles/angles_TZZ250_JHU.png");
}
void StandardBayesianNumericalDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData") {
// option definitions
double confLevel = optBayes.confLevel;
TString integrationType = optBayes.integrationType;
int nToys = optBayes.nToys;
bool scanPosterior = optBayes.scanPosterior;
int nScanPoints = optBayes.nScanPoints;
int intervalType = optBayes.intervalType;
int maxPOI = optBayes.maxPOI;
double nSigmaNuisance = optBayes.nSigmaNuisance;
// -------------------------------------------------------
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
// -------------------------------------------------------
// Tutorial starts here
// -------------------------------------------------------
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
// ------------------------------------------
// create and use the BayesianCalculator
// to find and plot the 95% credible interval
// on the parameter of interest as specified
// in the model config
// before we do that, we must specify our prior
// it belongs in the model config, but it may not have
// been specified
RooUniform prior("prior","",*mc->GetParametersOfInterest());
w->import(prior);
mc->SetPriorPdf(*w->pdf("prior"));
// do without systematics
//mc->SetNuisanceParameters(RooArgSet() );
if (nSigmaNuisance > 0) {
RooAbsPdf * pdf = mc->GetPdf();
assert(pdf);
RooFitResult * res = pdf->fitTo(*data, Save(true), Minimizer(ROOT::Math::MinimizerOptions::DefaultMinimizerType().c_str()), Hesse(true),
PrintLevel(ROOT::Math::MinimizerOptions::DefaultPrintLevel()-1) );
res->Print();
RooArgList nuisPar(*mc->GetNuisanceParameters());
for (int i = 0; i < nuisPar.getSize(); ++i) {
RooRealVar * v = dynamic_cast<RooRealVar*> (&nuisPar[i] );
assert( v);
v->setMin( TMath::Max( v->getMin(), v->getVal() - nSigmaNuisance * v->getError() ) );
v->setMax( TMath::Min( v->getMax(), v->getVal() + nSigmaNuisance * v->getError() ) );
std::cout << "setting interval for nuisance " << v->GetName() << " : [ " << v->getMin() << " , " << v->getMax() << " ]" << std::endl;
}
}
BayesianCalculator bayesianCalc(*data,*mc);
bayesianCalc.SetConfidenceLevel(confLevel); // 95% interval
// default of the calculator is central interval. here use shortest , central or upper limit depending on input
// doing a shortest interval might require a longer time since it requires a scan of the posterior function
if (intervalType == 0) bayesianCalc.SetShortestInterval(); // for shortest interval
if (intervalType == 1) bayesianCalc.SetLeftSideTailFraction(0.5); // for central interval
if (intervalType == 2) bayesianCalc.SetLeftSideTailFraction(0.); // for upper limit
if (!integrationType.IsNull() ) {
bayesianCalc.SetIntegrationType(integrationType); // set integrationType
bayesianCalc.SetNumIters(nToys); // set number of iterations (i.e. number of toys for MC integrations)
}
// in case of toyMC make a nuisance pdf
if (integrationType.Contains("TOYMC") ) {
RooAbsPdf * nuisPdf = RooStats::MakeNuisancePdf(*mc, "nuisance_pdf");
cout << "using TOYMC integration: make nuisance pdf from the model " << std::endl;
nuisPdf->Print();
bayesianCalc.ForceNuisancePdf(*nuisPdf);
scanPosterior = true; // for ToyMC the posterior is scanned anyway so used given points
}
// compute interval by scanning the posterior function
if (scanPosterior)
bayesianCalc.SetScanOfPosterior(nScanPoints);
RooRealVar* poi = (RooRealVar*) mc->GetParametersOfInterest()->first();
if (maxPOI != -999 && maxPOI > poi->getMin())
poi->setMax(maxPOI);
SimpleInterval* interval = bayesianCalc.GetInterval();
// print out the interval on the first Parameter of Interest
cout << "\n>>>> RESULT : " << confLevel*100 << "% interval on " << poi->GetName()<<" is : ["<<
interval->LowerLimit() << ", "<<
interval->UpperLimit() <<"] "<<endl;
// make a plot
// since plotting may take a long time (it requires evaluating
// the posterior in many points) this command will speed up
// by reducing the number of points to plot - do 50
// ignore errors of PDF if is zero
RooAbsReal::setEvalErrorLoggingMode(RooAbsReal::Ignore) ;
cout << "\nDrawing plot of posterior function....." << endl;
// always plot using numer of scan points
bayesianCalc.SetScanOfPosterior(nScanPoints);
RooPlot * plot = bayesianCalc.GetPosteriorPlot();
plot->Draw();
}
void roo_fitWH()
{
TString poscharge = "Plus";
TString negcharge = "Minus";
std::vector<TString> charge(2);
charge.at(0) = poscharge;
charge.at(1) = negcharge;
TString canvas_name_plus = "muon_MC_WHelicityFramePlots_PlusICVar";
TCanvas *c0 = new TCanvas(canvas_name_plus,"",450,400);
TString canvas_name_minus = "muon_MC_WHelicityFramePlots_MinusICVar";
TCanvas *c1 = new TCanvas(canvas_name_minus,"",450,400);
// Run both for + and - charges
for(unsigned int j=0; j<charge.size(); j++) {
// if (j==1) break; // do only + charge fit
if (realData) { sfactor=36; }
// Nominal values are taken from a fit to the MC W data (scaled to 100pb-1)
RooRealVar *fLnom, *fRnom, *f0nom;
if (j==0) {
fLnom=new RooRealVar("fL_nom","fLnom",0.556);
fRnom=new RooRealVar("fR_nom","fRnom",0.234);
f0nom=new RooRealVar("f0_nom","f0nom",0.210);
} else {
fLnom=new RooRealVar("fL_nom","fLnom",0.523);
fRnom=new RooRealVar("fR_nom","fRnom",0.265);
f0nom=new RooRealVar("f0_nom","f0nom",0.212);
}
TString Hist1 = "RECO_PolPlots_50toinf/RECO_ICVarPF"+ charge.at(j) + "_LH";
TString Hist2 = "RECO_PolPlots_50toinf/RECO_ICVarPF"+ charge.at(j) + "_RH";
TString Hist3 = "RECO_PolPlots_50toinf/RECO_ICVarPF"+ charge.at(j) + "_LO";
TString Hist_data1 = "RECO_PolPlots_50toinf/RECO_ICVarPF"+ charge.at(j);
TH1D *mc1 = (TH1D*)sigfile->Get(Hist1);
TH1D *mc2 = (TH1D*)sigfile->Get(Hist2);
TH1D *mc3 = (TH1D*)sigfile->Get(Hist3);
TH1D *sighist = (TH1D*)sigfile->Get(Hist_data1); // W signal histogram
TH1D *bkghist=(TH1D*)bkgfile->Get(Hist_data1); // Bkg histogram
TH1D *hdata=(TH1D*)datafile->Get(Hist_data1); // Real data histogram
// //we are only fitting for fL and fR
// double accFactor1 = refTempHist1->Integral() / mc1->Integral();
// double accFactor2 = refTempHist2->Integral() / mc2->Integral();
// double accFactor3 = refTempHist3->Integral() / mc3->Integral();
// double normFactor = (mc1->Integral() + mc2->Integral() + mc3->Integral()) / (refTempHist1->Integral() + refTempHist2->Integral() + refTempHist3->Integral());
mc1->Rebin(rbin); mc2->Rebin(rbin); mc3->Rebin(rbin);
sighist->Rebin(rbin); bkghist->Rebin(rbin); hdata->Rebin(rbin);
// Scale to sfactor/pb if MC
//if (!realData) {
if (toyMC) sfactor=400;
sighist->Scale(sfactor); bkghist->Scale(sfactor);
// }
//datahist->Scale(invWeightW);//to get MC errors - otherwise comment out
Double_t nbkg=0;
TH1D *datahist;
if (realData) { datahist=hdata;
} else {
datahist=(TH1D*)sighist->Clone();
if (addbkg) {datahist->Add(bkghist); }
}
if (addbkg) {
//nbkg=bkghist->Integral();
nbkg=bkghist->Integral(bkghist->FindBin(xmin+quanta),bkghist->FindBin(xmax-quanta));
}
//Double_t istat=datahist->Integral();
//Double_t f_sig=(sighist->Integral())/istat; // signal fraction
Double_t istat=datahist->Integral(datahist->FindBin(xmin+quanta),datahist->FindBin(xmax-quanta));
Double_t f_sig=(sighist->Integral(sighist->FindBin(xmin+quanta),sighist->FindBin(xmax-quanta)))/istat;
Double_t f_bkg=nbkg/istat; // bkg fraction
// Start RooFit session
RooRealVar x("x","LP",xmin,xmax);
// Import binned Data
RooDataHist data1("data1","dataset with WHICVarPlus",x,mc1);
RooDataHist data2("data2","dataset with WHICVarPlus",x,mc2);
RooDataHist data3("data3","dataset with WHICVarPlus",x,mc3);
RooDataHist test("data","dataset with WHICVarPlus",x,datahist);
RooDataHist data_bkg("data4","dataset with ICVar",x,bkghist);
// Relative fractions - allow them to float to negative values too if needs be
// if (fitMode==0) {
RooRealVar f1("fL","fL fraction",fLnom->getVal(),0.,1.);
RooRealVar f2("fR","fR fraction", fRnom->getVal(),0.,1.);
RooFormulaVar f3("f0","1-fL-fR",RooArgList(f1,f2));
if (fitMode) {
f1.setVal((fLnom->getVal()-fRnom->getVal())); f1.setRange(-1.,1.);
f1.setPlotLabel("f_{L}-f_{R}");
f2.setVal(f0nom->getVal());
f2.setPlotLabel("f_{0}");
}
// } else {
// RooRealVar f1("fL","fL fraction",(fLnom->getVal()-fRnom->getVal()),-1.,1.);
// RooRealVar f2("fR","fR fraction", (fLnom->getVal()+fRnom->getVal()),-1.,1.);
// RooFormulaVar f3("f0","1-fL-fR",RooArgList(f1,f2));
// }
RooRealVar fsub("fsub","fsub par",(fLnom->getVal()-fRnom->getVal()),-1.,1.);
RooRealVar fsum("fsum","fsum par",(fLnom->getVal()+fRnom->getVal()), -1.,1.);
// Background template
RooHistPdf *bkg = new RooHistPdf("bkg","bkg",x,data_bkg);
// Bkg fraction
RooRealVar fbkg("f_{bkg}","f_bkg fraction",f_bkg);
// Templates
RooHistPdf h1("h1","h1",x,data1); // left-handed template histogram
RooHistPdf h2("h2","h2",x,data2); // right-handed template histo
RooHistPdf h3("h3","h3",x,data3); // longitudinal template histo
// Construct model PDF
RooAbsPdf *sig, *model;
if (charge.at(j) == "Plus") { // plus charge PDFs
if (addParameter) { sig = new RooWPlusExtended("sigmodel","model",x,f1,f2,fsub);
} else { sig = new RooWPlus("sigmodel","model",x,f1,f2); }
} else if (charge.at(j) == "Minus") { // minus charge PDFs
if (addParameter) { sig = new RooWMinusExtended("sigmodel","model",x,f1,f2,fsub);
} else { sig = new RooWMinus("sigmodel","model",x,f1,f2); }
}
if (addbkg) {
model = new RooAddPdf("model","model",RooArgList(*bkg,*sig),fbkg);
} else { model = sig; }
// Set the Fit Range
x.setRange("fitrange",-0.0,1.3);
// Construct likelihood ( + penalty term)
RooNLLVar nll("nll","nll",*model,test,Range("fitrange"));
RooRealVar pen("pen","penalty term",(0.5*1./(0.01*0.01)));
RooFormulaVar nllPen("nllPen","nll+pen*fsub^2",RooArgList(nll,pen,fsub));
// Fitting
RooMinuit *m;
if (!addParameter) { m = new RooMinuit(nll); }
else { m = new RooMinuit(nllPen);}
if (!toyMC) {
m->migrad(); m->hesse();
}
RooFitResult *res1 = m->save();
// Re-diced data
// Int_t nevt=static_cast<int>(istat);
// RooDataSet *gtest = model->generate(x,nevt);
// Fitting
// RooFitResult * res1 = model.fitTo(test,Minos(kFALSE), Save());
// res1->Print();
if(makePlots) {
// Temp PDF for plotting purposes
// RooAddPdf temp("temp","component 1",RooArgList(*h1,*h2,*h3),RooArgList(*f1,*f2)) ;
// Plotting
gROOT->SetStyle("Plain");
gStyle->SetOptFit(0);
gStyle->SetOptTitle(0);
gStyle->SetOptStat(0); //gStyle->SetCanvasDefH(600); //Height of canvas
//gStyle->SetCanvasDefW(600); //Width of canvas
if(charge.at(j) == "Plus") { c0->cd();
//c0->Divide(2,1);c0->cd(1);
}
if(charge.at(j) == "Minus") { c1->cd();
//c1->Divide(2,1);c1->cd(1);
}
//RooPlot* frame = new RooPlot(0.0,1.3,0,800);
RooPlot* frame = x.frame();
test.plotOn(frame,Name("data"));
model->plotOn(frame,Name("model"));
// model->paramOn(frame);//, Format("NELU", AutoPrecision(2)), Layout(0.1,0.5,0.9));
// h1.plotOn(frame);
// h2.plotOn(frame);
// h3.plotOn(frame);
// model->plotOn(frame, Components(h1),LineColor(kRed),LineStyle(kDashed));
// temp->plotOn(frame, Components(h2),LineColor(kGreen),LineStyle(kDashed));
// temp->plotOn(frame, Components(h3),LineColor(kYellow),LineStyle(kDashed));
if (addbkg) {
// model->plotOn(frame, Components(h1),FillColor(5),DrawOption("F"));
//model->plotOn(frame,Components(*bkg),FillColor(5),DrawOption(""));
}
hdata->GetYaxis()->SetTitle("Events / 0.1");
if(charge.at(j) == "Plus") { hdata->GetXaxis()->SetTitle("#it{L_{P}}(#mu^{+})");}
if(charge.at(j) == "Minus") {hdata->GetXaxis()->SetTitle("#it{L_{P}}(#mu^{-})");}
hdata->GetXaxis()->SetTitleSize(0.06);
hdata->GetXaxis()->SetTitleOffset(1.);
hdata->GetYaxis()->SetTitleSize(0.06);
hdata->GetYaxis()->SetTitleOffset(1.2);
hdata->GetXaxis()->SetLabelSize(0.055);
hdata->GetYaxis()->SetLabelSize(0.055);
hdata->GetXaxis()->SetRangeUser(0.0,1.29);
hdata->GetYaxis()->SetRangeUser(0.0,600);
hdata->SetMarkerStyle(20);
// mc1->Draw("same");
// Goodness-of-fit
Double_t chi2= frame->chiSquare("model","data",3);
Double_t nllmin=res1->minNll();
cout << "" << endl;
cout << "Printing out the goodness-of-fit measure:" << endl;
cout << "chi2 = " << chi2 << "\t" << "min NLL = " << nllmin << endl;
res1->Print();
// TCanvas* testt = new TCanvas ("testt","hj");
cout <<"intetral: "<< hdata->Integral()<<endl;
hdata->GetXaxis()->SetRangeUser(0.0,1.29);
cout << hdata->Integral()<<endl;
hdata->Draw("");
// frame->Draw("same");
mc1->GetXaxis()->SetRangeUser(0.0,1.29);
float f_l_a = mc1->Integral();
mc2->GetXaxis()->SetRangeUser(0.0,1.29);
float f_r_a = mc2->Integral();
mc3->GetXaxis()->SetRangeUser(0.0,1.29);
float f_0_a = mc3->Integral();
float allData = hdata->Integral();
float EWKBkg = allData*(f_bkg);
float WData = allData*(1-f_bkg);
float f_l = 0.5*(1-f2.getVal()+f1.getVal());
float f_r = 0.5*(1-f2.getVal()-f1.getVal());
float f_0 = f2.getVal();
cout << "f_l: "<< f_l<< ",f_r: "<< f_r<< ", f_0: "<< f_0<< " 1= "<< f_l+f_r+f_0<< endl;
float allW = f_l*f_l_a+f_r*f_r_a+f_0*f_0_a;
//hdata->Draw("");
// bkghist->GetXaxis()->SetRangeUser(0.0,1.3);
bkghist->Scale(EWKBkg/bkghist->Integral());
bkghist->Draw("samehist");
bkghist->SetLineColor(kYellow);
bkghist->SetFillColor(kYellow);
mc1->Scale(f_l*WData/allW);
mc2->Scale(f_r*WData/allW);
mc3->Scale(f_0*WData/allW);
mc1->SetLineColor(kRed);
mc2->SetLineColor(kGreen);
mc3->SetLineColor(kBlue);
mc1->SetLineWidth(3);
mc2->SetLineWidth(3);
mc3->SetLineWidth(3);
mc1->SetLineStyle(2);
mc2->SetLineStyle(3);
mc3->SetLineStyle(4);
mc1->Draw("samehist");
mc2->Draw("samehist");
mc3->Draw("samehist");
TH1D* allHists = (TH1D*)mc1->Clone();
allHists->Add(mc2,1);
allHists->Add(mc3,1);
allHists->Add(bkghist,1);
allHists->SetLineWidth(3);
// frame->SetOptFit(0);
frame->Draw("same");
// allHists->Draw("same");
TLegend* aleg;
//if(charge.at(j) == "Minus") aleg = new TLegend(0.2,0.69,0.6,0.9,"");
// if(charge.at(j) == "Plus")
//aleg = new TLegend(0.5,0.6,0.7,0.9,"");//new TLegend(0.8,0.69,0.95,0.9,"");
aleg = new TLegend(0.2017937,0.7419355,0.4775785,0.9193548,NULL,"brNDC");
aleg->SetNColumns(2);
aleg->SetFillColor(0);
aleg->SetLineColor(0);
aleg->AddEntry(mc1,"f_{L}","lf");
aleg->AddEntry(mc2,"f_{R}","lf");
aleg->AddEntry(mc3,"f_{0}","lf");
aleg->AddEntry(bkghist,"EWK","lf");
TH1* dummyhist = new TH1F("", "", 1, 0, 1);
dummyhist->SetLineColor(kBlue);
dummyhist->SetLineWidth(3);
aleg->AddEntry(dummyhist, "fit result", "lf");
aleg->AddEntry(hdata, "data","P");
aleg->Draw("same");
//TLatex* preliminary;
//TLatex* text;
//if(false) {
//text = new TLatex(0.35,480,"#splitline{f_{L}-f_{R}=0.240#pm0.036(stat.)#pm0.031(syst.)}{f_{0}=0.183#pm0.087(stat.)#pm0.123(syst.)}");
//preliminary = new TLatex(0.35,550,"CMS preliminary: #it{L} = 36pb^{-1}@ 7 TeV");
//}
//if(true){
//text = new TLatex(0.05,480,"#splitline{f_{L}-f_{R}=0.310#pm0.036(stat.)#pm0.017(syst.)}{f_{0}=0.171#pm0.085(stat.)#pm0.099(syst.)}");
//preliminary = new TLatex(0.05,550,"#splitline{CMS, #sqrt{s} = 7 TeV,}{#it{L_{int}} = 36 pb^{-1}}");}
//preliminary->SetTextSize(0.043);
//preliminary->Draw("same");
//text->SetTextSize(0.043);
// text->Draw("same");
/*
// Draw Minuit contours
if(charge.at(j) == "Plus") { c0->cd(2);
} else { c1->cd(2); }
// RooPlot *rcont=m->contour(f1,f2,1,2);
// rcont->Draw();
RooPlot *rcontour=new RooPlot(f1,f2);
res1->plotOn(rcontour,f1,f2,"ME123VHB");
rcontour->Draw();
if (fitMode) {
rcontour->GetXaxis()->SetTitle("f_{L}-f_{R}");
rcontour->GetYaxis()->SetTitle("f_{0}");
} else {
rcontour->GetXaxis()->SetTitle("f_{L}");
rcontour->GetYaxis()->SetTitle("f_{R}");
}
*/
}
TLatex * text = new TLatex(0.7451931,500.8655,"#splitline{CMS, #sqrt{s} = 7 TeV}{L_{ int} = 36 pb^{-1}}");
text->SetTextSize(0.043);
text->SetLineWidth(2);
text->Draw("same");
const TMatrixDSym& cor = res1->correlationMatrix();
const TMatrixDSym& cov = res1->covarianceMatrix();
//Print correlation, covariance matrix
cout << "correlation matrix" << endl; cor.Print();
cout << "covariance matrix" << endl; cov.Print();
cout << f1 << endl; cout << f2 << endl;
if (!fitMode) {
cout << "f0 = " << f3 << " +/- " << f3.getPropagatedError(*res1) << endl;
}
}
if(makePlots) {
c0->Print(canvas_name_plus+".pdf");
c1->Print(canvas_name_minus+".pdf");
}
if (toyMC) {
// MC STudies
Int_t nevt=istat;
Int_t nEXP=100;
RooMCStudy mgr(*model,*model,x,"","mhrv");
mgr.generateAndFit(nEXP,nevt,kTRUE);
TCanvas *cp0 = new TCanvas("c0","",1200,400);
cp0->Divide(3,1);
cp0->cd(1);
RooPlot *p1=mgr.plotParam(f1); p1->Draw();
if (fitMode) p1->SetTitle(";f_{L}-f_{R};number of toys");
cp0->cd(2);
RooPlot *p2 = mgr.plotError(f1); p2->Draw();
if (fitMode) p2->SetTitle(";#delta (f_{L}-f_{R});number of toys");
cp0->cd(3);
// f1 pull
RooPlot* m1pframe = mgr.plotPull(f1,-3.,3.,30,kTRUE);
m1pframe->Draw();
if (fitMode) {
m1pframe->SetTitle(";f_{L}-f_{R};number of toys");
}
TCanvas *cp02 = new TCanvas("c1","",1200,400);
cp02->Divide(3,1);
cp02->cd(1);
RooPlot *p3=mgr.plotParam(f2); p3->Draw();
if (fitMode) p3->SetTitle(";f_{0};number of toys");
cp02->cd(2);
RooPlot *p4=mgr.plotError(f2); p4->Draw();
if (fitMode) p4->SetTitle(";#delta f_{0}; number of toys");
cp02->cd(3);
// f2 pull
RooPlot* m2pframe = mgr.plotPull(f2,-3.,3.,30,kTRUE);
m2pframe->Draw();
if (fitMode) {
m2pframe->SetTitle(";f_{0};number of toys");
}
TCanvas *cnll = new TCanvas("cnll","");
RooPlot* nllframe = mgr.plotNLL();
// nllframe->Draw();
}
return;
}
int main (int argc, char **argv) {
TFile *tf = TFile::Open("tmp/DataSets.root");
RooWorkspace *w = (RooWorkspace*)tf->Get("w");
RooDataSet *Data = (RooDataSet*)w->data("Data2011")->Clone("Data");
Data->append( *((RooDataSet*)w->data("Data2012")) );
RooDataSet *Bs2Kst0Kst0_MC = (RooDataSet*)w->data("Bs2Kst0Kst0_MC2011")->Clone("Bs2KstKst0_MC");
Bs2Kst0Kst0_MC->append( *((RooDataSet*)w->data("Bs2Kst0Kst0_MC2012")) );
RooDataSet *Bs2Kst0Kst01430_MC = (RooDataSet*)w->data("Bs2Kst0Kst01430_MC2011")->Clone("Bs2KstKst0_MC");
Bs2Kst0Kst01430_MC->append( *((RooDataSet*)w->data("Bs2Kst0Kst01430_MC2012")) );
RooDataSet *Bs2Kst01430Kst01430_MC = (RooDataSet*)w->data("Bs2Kst01430Kst01430_MC2011")->Clone("Bs2KstKst0_MC");
Bs2Kst01430Kst01430_MC->append( *((RooDataSet*)w->data("Bs2Kst01430Kst01430_MC2012")) );
RooDataSet *Bd2Kst0Kst0_MC = (RooDataSet*)w->data("Bd2Kst0Kst0_MC2011")->Clone("Bs2KstKst0_MC");
Bd2Kst0Kst0_MC->append( *((RooDataSet*)w->data("Bd2Kst0Kst0_MC2012")) );
RooDataSet *Bd2PhiKst0_MC = (RooDataSet*)w->data("Bd2PhiKst0_MC2011")->Clone("Bs2KstKst0_MC");
Bd2PhiKst0_MC->append( *((RooDataSet*)w->data("Bd2PhiKst0_MC2012")) );
RooDataSet *Bs2PhiKst0_MC = (RooDataSet*)w->data("Bs2PhiKst0_MC2011")->Clone("Bs2KstKst0_MC");
Bs2PhiKst0_MC->append( *((RooDataSet*)w->data("Bs2PhiKst0_MC2012")) );
RooDataSet *Bd2RhoKst0_MC = (RooDataSet*)w->data("Bd2RhoKst0_MC2011")->Clone("Bs2KstKst0_MC");
Bd2RhoKst0_MC->append( *((RooDataSet*)w->data("Bd2RhoKst0_MC2012")) );
RooDataSet *Lb2ppipipi_MC = (RooDataSet*)w->data("Lb2ppipipi_MC2011")->Clone("Bs2KstKst0_MC");
Lb2ppipipi_MC->append( *((RooDataSet*)w->data("Lb2ppipipi_MC2012")) );
RooDataSet *Lb2pKpipi_MC = (RooDataSet*)w->data("Lb2pKpipi_MC2011")->Clone("Bs2KstKst0_MC");
Lb2pKpipi_MC->append( *((RooDataSet*)w->data("Lb2pKpipi_MC2012")) );
w->import(*Data);
w->import(*Bs2Kst0Kst0_MC);
w->import(*Bs2Kst0Kst01430_MC);
w->import(*Bs2Kst01430Kst01430_MC);
w->import(*Bd2Kst0Kst0_MC);
w->import(*Bd2PhiKst0_MC);
w->import(*Bs2PhiKst0_MC);
w->import(*Bd2RhoKst0_MC);
w->import(*Lb2ppipipi_MC);
w->import(*Lb2pKpipi_MC);
RooRealVar *mass = (RooRealVar*)w->var("B_s0_DTF_B_s0_M");
fitIpatia( w, "bs2kstkst_mc", "Bs2KstKst0_MC");
// Make the PDF here
RooRealVar *p1 = new RooRealVar("p1","p1",-0.002,-0.004,0.);
RooExponential *exp = new RooExponential("exp","exp",*mass,*p1);
//RooRealVar *m1 = new RooRealVar("m1","m1",5320,5380);
//RooRealVar *s1 = new RooRealVar("s1","s1",1,20);
//RooGaussian *sig = new RooGaussian("sig","sig",*mass,*m1,*s1);
RooRealVar *m2 = new RooRealVar("m2","m2",5320,5380);
RooRealVar *s2 = new RooRealVar("s2","s2",1,20);
RooGaussian *sig_bd = new RooGaussian("sig_bd","sig_bd",*mass,*m2,*s2);
//
RooRealVar *bs2kstkst_l = new RooRealVar( "bs2kstkst_l" ,"", -5, -20, -1.);
RooConstVar *bs2kstkst_zeta = new RooConstVar( "bs2kstkst_zeta","",0. );
RooConstVar *bs2kstkst_fb = new RooConstVar( "bs2kstkst_fb" ,"",0. );
RooRealVar *bs2kstkst_sigma = new RooRealVar( "bs2kstkst_sigma","",15 ,10 ,20 );
RooRealVar *bs2kstkst_mu = new RooRealVar( "bs2kstkst_mu" ,"",5350 ,5380 );
RooRealVar *bs2kstkst_a = new RooRealVar( "bs2kstkst_a" ,"",2.5 , 0 ,10 );
RooRealVar *bs2kstkst_n = new RooRealVar( "bs2kstkst_n" ,"",2.5 , 0 ,10 );
RooRealVar *bs2kstkst_a2 = new RooRealVar( "bs2kstkst_a2" ,"",2.5 , 0 ,10 );
RooRealVar *bs2kstkst_n2 = new RooRealVar( "bs2kstkst_n2" ,"",2.5 , 0 ,10 );
RooIpatia2 *sig = new RooIpatia2("sig","sig",*mass,*bs2kstkst_l,*bs2kstkst_zeta,*bs2kstkst_fb,*bs2kstkst_sigma,*bs2kstkst_mu,*bs2kstkst_a,*bs2kstkst_n,*bs2kstkst_a2,*bs2kstkst_n2);
RooRealVar *bkg_y = new RooRealVar("bkg_y","bkg_y",10e3,10e5);
RooRealVar *sig_y = new RooRealVar("sig_y","sig_y",0,20e3);
RooRealVar *sig_bd_y = new RooRealVar("sig_bd_y","sig_bd_y",0,3000);
RooArgList *pdfs = new RooArgList();
RooArgList *yields = new RooArgList();
pdfs->add( *exp );
pdfs->add( *sig );
pdfs->add( *sig_bd );
yields->add( *bkg_y );
yields->add( *sig_y );
yields->add( *sig_bd_y );
RooAddPdf *pdf = new RooAddPdf("pdf","pdf",*pdfs,*yields);
pdf->fitTo(*Data, Extended() );
RooPlot *plot = mass->frame();
Data->plotOn(plot);
// set fit params constant;
pdf->plotOn(plot);
TCanvas *c = new TCanvas();
plot->Draw();
c->Print("tmp/mass.pdf");
// Plots Kst Ms with no sweights
TCanvas *c1 = new TCanvas("c1","c1",800,1200);
c1->Divide(1,2);
c1->cd(1);
RooPlot *c1p1 = w->var("B_s0_DTF_KST1_M")->frame();
Data->plotOn(c1p1);
c1p1->Draw();
c1->cd(2);
RooPlot *c1p2 = w->var("B_s0_DTF_KST2_M")->frame();
Data->plotOn(c1p2);
c1p2->Draw();
c1->Print("tmp/nosw.pdf");
// set fit params constant
p1->setConstant(true);
//m1->setConstant(true);
//s1->setConstant(true);
bs2kstkst_l->setConstant(true);
//bs2kstkst_zeta->setConstant(true);
//bs2kstkst_fb->setConstant(true);
bs2kstkst_sigma->setConstant(true);
bs2kstkst_mu->setConstant(true);
bs2kstkst_a->setConstant(true);
bs2kstkst_n->setConstant(true);
bs2kstkst_a2->setConstant(true);
bs2kstkst_n2->setConstant(true);
m2->setConstant(true);
s2->setConstant(true);
RooStats::SPlot *sData = new RooStats::SPlot("sData","sData", *Data, pdf, *yields);
w->import(*sData);
w->import(*Data,Rename("Data_wsweights"));
RooDataSet *swdata = new RooDataSet("Data_wsweights", "Data", Data, *Data->get(), 0 , "sig_y_sw");
// Plots Kst Ms with no sweights
TCanvas *c2 = new TCanvas("c2","c2",800,1200);
c2->Divide(1,2);
c2->cd(1);
RooPlot *c2p1 = w->var("B_s0_DTF_KST1_M")->frame();
swdata->plotOn(c2p1);
c2p1->Draw();
c2->cd(2);
RooPlot *c2p2 = w->var("B_s0_DTF_KST2_M")->frame();
swdata->plotOn(c2p2);
c2p2->Draw();
c2->Print("tmp/withsw.pdf");
tf->Close();
return 0;
}
void eregtesting_13TeV_Pi0(bool dobarrel=true, bool doele=false,int gammaID=0) {
//output dir
TString EEorEB = "EE";
if(dobarrel)
{
EEorEB = "EB";
}
TString gammaDir = "bothGammas";
if(gammaID==1)
{
gammaDir = "gamma1";
}
else if(gammaID==2)
{
gammaDir = "gamma2";
}
TString dirname = TString::Format("ereg_test_plots_Pi0/%s_%s",gammaDir.Data(),EEorEB.Data());
TString dirname_fits = TString::Format("ereg_test_plots_Pi0/%s_%s/fits",gammaDir.Data(),EEorEB.Data());
gSystem->mkdir(dirname,true);
gSystem->mkdir(dirname_fits,true);
gSystem->cd(dirname);
//read workspace from training
TString fname;
if (doele && dobarrel)
fname = "wereg_ele_eb.root";
else if (doele && !dobarrel)
fname = "wereg_ele_ee.root";
else if (!doele && dobarrel)
fname = "wereg_ph_eb.root";
else if (!doele && !dobarrel)
fname = "wereg_ph_ee.root";
TString infile = TString::Format("../../ereg_ws_Pi0/%s/%s",gammaDir.Data(),fname.Data());
TFile *fws = TFile::Open(infile);
RooWorkspace *ws = (RooWorkspace*)fws->Get("wereg");
//read variables from workspace
RooGBRTargetFlex *meantgt = static_cast<RooGBRTargetFlex*>(ws->arg("sigmeant"));
RooRealVar *tgtvar = ws->var("tgtvar");
RooArgList vars;
vars.add(meantgt->FuncVars());
vars.add(*tgtvar);
//read testing dataset from TTree
RooRealVar weightvar("weightvar","",1.);
TTree *dtree;
if (doele) {
//TFile *fdin = TFile::Open("root://eoscms.cern.ch//eos/cms/store/cmst3/user/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TFile *fdin = TFile::Open("/data/bendavid/regTreesAug1/hgg-2013Final8TeV_reg_s12-zllm50-v7n_noskim.root");
TDirectory *ddir = (TDirectory*)fdin->FindObjectAny("PhotonTreeWriterSingleInvert");
dtree = (TTree*)ddir->Get("hPhotonTreeSingle");
}
else {
//TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiPion_FlatPt-1To15/Gun_FlatPt1to15_MultiPion_withPhotonPtFilter_pythia8/photons_0_half2.root");
TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiPion_FlatPt-1To15/Gun_FlatPt1to15_MultiPion_withPhotonPtFilter_pythia8/photons_20171008_half2.root");
//TFile *fdin = TFile::Open("/eos/cms/store/group/dpg_ecal/alca_ecalcalib/piZero2017/zhicaiz/Gun_MultiEta_FlatPt-1To15/Gun_FlatPt1to15_MultiEta_withPhotonPtFilter_pythia8/photons_22Aug2017_V3_half2.root");
if(gammaID==0)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma");
}
else if(gammaID==1)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma1");
}
else if(gammaID==2)
{
dtree = (TTree*)fdin->Get("Tree_Optim_gamma2");
}
}
//selection cuts for testing
//TCut selcut = "(STr2_enG1_true/cosh(STr2_Eta_1)>1.0) && (STr2_S4S9_1>0.75)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_enG_true/STr2_enG_rec)<3.0 && STr2_EOverEOther < 10.0 && STr2_EOverEOther > 0.1";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_mPi0_nocor>0.1)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2)";
TCut selcut = "";
//if(dobarrel) selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.2) && (STr2_mPi0_nocor < 1.0) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)<1.479 && (!STr2_fromPi0)";
if(dobarrel) selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)<1.479";
//else selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.2) && (STr2_mPi0_nocor < 1.0) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)>1.479 && (!STr2_fromPi0)";
else selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_Nxtal > 6) && (STr2_mPi0_nocor>0.1) && (STr2_mPi0_nocor < 0.2) && (STr2_ptPi0_nocor > 2.0) && abs(STr2_Eta)>1.479";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (STr2_iEta_on2520==0 || STr2_iPhi_on20==0) ";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.75) && (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)>60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03) && (abs(STr2_iEtaiX)<60)";
//TCut selcut = "(STr2_enG_rec/cosh(STr2_Eta)>1.0) && (STr2_S4S9 > 0.9) && (STr2_S2S9>0.85)&& (STr2_isMerging < 2) && (STr2_DeltaR < 0.03)";
/*
TCut selcut;
if (dobarrel)
selcut = "ph.genpt>25. && ph.isbarrel && ph.ispromptgen";
else
selcut = "ph.genpt>25. && !ph.isbarrel && ph.ispromptgen";
*/
TCut selweight = "xsecweight(procidx)*puweight(numPU,procidx)";
TCut prescale10 = "(Entry$%10==0)";
TCut prescale10alt = "(Entry$%10==1)";
TCut prescale25 = "(Entry$%25==0)";
TCut prescale100 = "(Entry$%100==0)";
TCut prescale1000 = "(Entry$%1000==0)";
TCut evenevents = "(Entry$%2==0)";
TCut oddevents = "(Entry$%2==1)";
TCut prescale100alt = "(Entry$%100==1)";
TCut prescale1000alt = "(Entry$%1000==1)";
TCut prescale50alt = "(Entry$%50==1)";
TCut Events3_4 = "(Entry$%4==3)";
TCut Events1_4 = "(Entry$%4==1)";
TCut Events2_4 = "(Entry$%4==2)";
TCut Events0_4 = "(Entry$%4==0)";
TCut Events01_4 = "(Entry$%4<2)";
TCut Events23_4 = "(Entry$%4>1)";
TCut EventsTest = "(Entry$%2==1)";
//weightvar.SetTitle(EventsTest*selcut);
weightvar.SetTitle(selcut);
/*
if (doele)
weightvar.SetTitle(prescale100alt*selcut);
else
weightvar.SetTitle(selcut);
*/
//make testing dataset
RooDataSet *hdata = RooTreeConvert::CreateDataSet("hdata",dtree,vars,weightvar);
if (doele)
weightvar.SetTitle(prescale1000alt*selcut);
else
weightvar.SetTitle(prescale10alt*selcut);
//make reduced testing dataset for integration over conditional variables
RooDataSet *hdatasmall = RooTreeConvert::CreateDataSet("hdatasmall",dtree,vars,weightvar);
//retrieve full pdf from workspace
RooAbsPdf *sigpdf = ws->pdf("sigpdf");
//input variable corresponding to sceta
RooRealVar *scEraw = ws->var("var_0");
scEraw->setRange(1.,2.);
scEraw->setBins(100);
// RooRealVar *scetavar = ws->var("var_1");
// RooRealVar *scphivar = ws->var("var_2");
//regressed output functions
RooAbsReal *sigmeanlim = ws->function("sigmeanlim");
RooAbsReal *sigwidthlim = ws->function("sigwidthlim");
RooAbsReal *signlim = ws->function("signlim");
RooAbsReal *sign2lim = ws->function("sign2lim");
// RooAbsReal *sigalphalim = ws->function("sigalphalim");
//RooAbsReal *sigalpha2lim = ws->function("sigalpha2lim");
//formula for corrected energy/true energy ( 1.0/(etrue/eraw) * regression mean)
RooFormulaVar ecor("ecor","","1./(@0)*@1",RooArgList(*tgtvar,*sigmeanlim));
RooRealVar *ecorvar = (RooRealVar*)hdata->addColumn(ecor);
ecorvar->setRange(0.,2.);
ecorvar->setBins(800);
//formula for raw energy/true energy (1.0/(etrue/eraw))
RooFormulaVar raw("raw","","1./@0",RooArgList(*tgtvar));
RooRealVar *rawvar = (RooRealVar*)hdata->addColumn(raw);
rawvar->setRange(0.,2.);
rawvar->setBins(800);
//clone data and add regression outputs for plotting
RooDataSet *hdataclone = new RooDataSet(*hdata,"hdataclone");
RooRealVar *meanvar = (RooRealVar*)hdataclone->addColumn(*sigmeanlim);
RooRealVar *widthvar = (RooRealVar*)hdataclone->addColumn(*sigwidthlim);
RooRealVar *nvar = (RooRealVar*)hdataclone->addColumn(*signlim);
RooRealVar *n2var = (RooRealVar*)hdataclone->addColumn(*sign2lim);
// RooRealVar *alphavar = (RooRealVar*)hdataclone->addColumn(*sigalphalim);
// RooRealVar *alpha2var = (RooRealVar*)hdataclone->addColumn(*sigalpha2lim);
//plot target variable and weighted regression prediction (using numerical integration over reduced testing dataset)
TCanvas *craw = new TCanvas;
//RooPlot *plot = tgtvar->frame(0.6,1.2,100);
RooPlot *plot = tgtvar->frame(0.6,2.0,100);
hdata->plotOn(plot);
sigpdf->plotOn(plot,ProjWData(*hdatasmall));
plot->Draw();
craw->SaveAs("RawE.pdf");
craw->SaveAs("RawE.png");
craw->SetLogy();
plot->SetMinimum(0.1);
craw->SaveAs("RawElog.pdf");
craw->SaveAs("RawElog.png");
//plot distribution of regressed functions over testing dataset
TCanvas *cmean = new TCanvas;
RooPlot *plotmean = meanvar->frame(0.8,2.0,100);
hdataclone->plotOn(plotmean);
plotmean->Draw();
cmean->SaveAs("mean.pdf");
cmean->SaveAs("mean.png");
TCanvas *cwidth = new TCanvas;
RooPlot *plotwidth = widthvar->frame(0.,0.05,100);
hdataclone->plotOn(plotwidth);
plotwidth->Draw();
cwidth->SaveAs("width.pdf");
cwidth->SaveAs("width.png");
TCanvas *cn = new TCanvas;
RooPlot *plotn = nvar->frame(0.,111.,200);
hdataclone->plotOn(plotn);
plotn->Draw();
cn->SaveAs("n.pdf");
cn->SaveAs("n.png");
TCanvas *cn2 = new TCanvas;
RooPlot *plotn2 = n2var->frame(0.,111.,100);
hdataclone->plotOn(plotn2);
plotn2->Draw();
cn2->SaveAs("n2.pdf");
cn2->SaveAs("n2.png");
/*
TCanvas *calpha = new TCanvas;
RooPlot *plotalpha = alphavar->frame(0.,5.,200);
hdataclone->plotOn(plotalpha);
plotalpha->Draw();
calpha->SaveAs("alpha.pdf");
calpha->SaveAs("alpha.png");
TCanvas *calpha2 = new TCanvas;
RooPlot *plotalpha2 = alpha2var->frame(0.,5.,200);
hdataclone->plotOn(plotalpha2);
plotalpha2->Draw();
calpha2->SaveAs("alpha2.pdf");
calpha2->SaveAs("alpha2.png");
*/
/*
TCanvas *ceta = new TCanvas;
RooPlot *ploteta = scetavar->frame(-2.6,2.6,200);
hdataclone->plotOn(ploteta);
ploteta->Draw();
ceta->SaveAs("eta.pdf");
ceta->SaveAs("eta.png");
*/
//create histograms for eraw/etrue and ecor/etrue to quantify regression performance
TH1 *heraw;// = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.));
TH1 *hecor;// = hdata->createHistogram("hecor",*ecorvar);
if (EEorEB == "EB")
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(800,0.,2.0));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(800,0.,2.0));
}
else
{
heraw = hdata->createHistogram("hraw",*rawvar,Binning(200,0.,2.));
hecor = hdata->createHistogram("hecor",*ecorvar, Binning(200,0.,2.));
}
//heold->SetLineColor(kRed);
hecor->SetLineColor(kBlue);
heraw->SetLineColor(kMagenta);
hecor->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
heraw->GetYaxis()->SetRangeUser(1.0,1.3*hecor->GetMaximum());
hecor->GetXaxis()->SetRangeUser(0.0,1.5);
heraw->GetXaxis()->SetRangeUser(0.0,1.5);
/*if(EEorEB == "EE")
{
heraw->GetYaxis()->SetRangeUser(10.0,200.0);
hecor->GetYaxis()->SetRangeUser(10.0,200.0);
}
*/
//heold->GetXaxis()->SetRangeUser(0.6,1.2);
double effsigma_cor, effsigma_raw, fwhm_cor, fwhm_raw;
if(EEorEB == "EB")
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(800,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(800,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
else
{
TH1 *hecorfine = hdata->createHistogram("hecorfine",*ecorvar,Binning(200,0.,2.));
effsigma_cor = effSigma(hecorfine);
fwhm_cor = FWHM(hecorfine);
TH1 *herawfine = hdata->createHistogram("herawfine",*rawvar,Binning(200,0.,2.));
effsigma_raw = effSigma(herawfine);
fwhm_raw = FWHM(herawfine);
}
TCanvas *cresponse = new TCanvas;
gStyle->SetOptStat(0);
gStyle->SetPalette(107);
hecor->SetTitle("");
heraw->SetTitle("");
hecor->Draw("HIST");
//heold->Draw("HISTSAME");
heraw->Draw("HISTSAME");
//show errSigma in the plot
TLegend *leg = new TLegend(0.1, 0.75, 0.7, 0.9);
leg->AddEntry(hecor,Form("E_{cor}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_cor, fwhm_cor),"l");
leg->AddEntry(heraw,Form("E_{raw}/E_{true}, #sigma_{eff}=%4.3f, FWHM=%4.3f", effsigma_raw, fwhm_raw),"l");
leg->SetFillStyle(0);
leg->SetBorderSize(0);
// leg->SetTextColor(kRed);
leg->Draw();
cresponse->SaveAs("response.pdf");
cresponse->SaveAs("response.png");
cresponse->SetLogy();
cresponse->SaveAs("responselog.pdf");
cresponse->SaveAs("responselog.png");
// draw CCs vs eta and phi
/*
TCanvas *c_eta = new TCanvas;
TH1 *h_eta = hdata->createHistogram("h_eta",*scetavar,Binning(100,-3.2,3.2));
h_eta->Draw("HIST");
c_eta->SaveAs("heta.pdf");
c_eta->SaveAs("heta.png");
TCanvas *c_phi = new TCanvas;
TH1 *h_phi = hdata->createHistogram("h_phi",*scphivar,Binning(100,-3.2,3.2));
h_phi->Draw("HIST");
c_phi->SaveAs("hphi.pdf");
c_phi->SaveAs("hphi.png");
*/
RooRealVar *scetaiXvar = ws->var("var_4");
RooRealVar *scphiiYvar = ws->var("var_5");
if(EEorEB=="EB")
{
scetaiXvar->setRange(-90,90);
scetaiXvar->setBins(180);
scphiiYvar->setRange(0,360);
scphiiYvar->setBins(360);
}
else
{
scetaiXvar->setRange(0,50);
scetaiXvar->setBins(50);
scphiiYvar->setRange(0,50);
scphiiYvar->setBins(50);
}
ecorvar->setRange(0.5,1.5);
ecorvar->setBins(800);
rawvar->setRange(0.5,1.5);
rawvar->setBins(800);
TCanvas *c_cor_eta = new TCanvas;
TH3F *h3_CC_eta_phi = (TH3F*) hdata->createHistogram("var_5,var_4,ecor",(EEorEB=="EB") ? 170 : 100, (EEorEB=="EB") ? 360 : 100,25);
TProfile2D *h_CC_eta_phi = h3_CC_eta_phi->Project3DProfile();
h_CC_eta_phi->SetTitle("E_{cor}/E_{true}");
if(EEorEB=="EB")
{
h_CC_eta_phi->GetXaxis()->SetTitle("i#eta");
h_CC_eta_phi->GetYaxis()->SetTitle("i#phi");
h_CC_eta_phi->GetXaxis()->SetRangeUser(-85,85);
h_CC_eta_phi->GetYaxis()->SetRangeUser(0,360);
}
else
{
h_CC_eta_phi->GetXaxis()->SetTitle("iX");
h_CC_eta_phi->GetYaxis()->SetTitle("iY");
}
h_CC_eta_phi->SetMinimum(0.5);
h_CC_eta_phi->SetMaximum(1.5);
h_CC_eta_phi->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta_phi.pdf");
c_cor_eta->SaveAs("cor_vs_eta_phi.png");
TH2F *h_CC_eta = hdata->createHistogram(*scetaiXvar, *ecorvar, "","cor_vs_eta");
if(EEorEB=="EB")
{
h_CC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetXaxis()->SetTitle("iX");
}
h_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_eta->Draw("COLZ");
c_cor_eta->SaveAs("cor_vs_eta.pdf");
c_cor_eta->SaveAs("cor_vs_eta.png");
TCanvas *c_cor_scEraw = new TCanvas;
TH2F *h_CC_scEraw = hdata->createHistogram(*scEraw, *ecorvar, "","cor_vs_scEraw");
h_CC_scEraw->GetXaxis()->SetTitle("E_{raw}");
h_CC_scEraw->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_scEraw->Draw("COLZ");
c_cor_scEraw->SaveAs("cor_vs_scEraw.pdf");
c_cor_scEraw->SaveAs("cor_vs_scEraw.png");
TCanvas *c_raw_scEraw = new TCanvas;
TH2F *h_RC_scEraw = hdata->createHistogram(*scEraw, *rawvar, "","raw_vs_scEraw");
h_RC_scEraw->GetXaxis()->SetTitle("E_{raw}");
h_RC_scEraw->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_scEraw->Draw("COLZ");
c_raw_scEraw->SaveAs("raw_vs_scEraw.pdf");
c_raw_scEraw->SaveAs("raw_vs_scEraw.png");
TCanvas *c_cor_phi = new TCanvas;
TH2F *h_CC_phi = hdata->createHistogram(*scphiiYvar, *ecorvar, "","cor_vs_phi");
if(EEorEB=="EB")
{
h_CC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetXaxis()->SetTitle("iY");
}
h_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_phi->Draw("COLZ");
c_cor_phi->SaveAs("cor_vs_phi.pdf");
c_cor_phi->SaveAs("cor_vs_phi.png");
//2D map of Eraw/Etrue and Ecor/Etrue of ieta and iphi
TCanvas *c_raw_eta = new TCanvas;
TH3F *h3_RC_eta_phi = (TH3F*) hdata->createHistogram("var_5,var_4,raw",(EEorEB=="EB") ? 170 : 100, (EEorEB=="EB") ? 360 : 100,25);
TProfile2D *h_RC_eta_phi = h3_RC_eta_phi->Project3DProfile();
h_RC_eta_phi->SetTitle("E_{raw}/E_{true}");
if(EEorEB=="EB")
{
h_RC_eta_phi->GetXaxis()->SetTitle("i#eta");
h_RC_eta_phi->GetYaxis()->SetTitle("i#phi");
h_RC_eta_phi->GetXaxis()->SetRangeUser(-85,85);
h_RC_eta_phi->GetYaxis()->SetRangeUser(0,360);
}
else
{
h_RC_eta_phi->GetXaxis()->SetTitle("iX");
h_RC_eta_phi->GetYaxis()->SetTitle("iY");
}
h_RC_eta_phi->SetMinimum(0.5);
h_RC_eta_phi->SetMaximum(1.5);
h_RC_eta_phi->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta_phi.pdf");
c_raw_eta->SaveAs("raw_vs_eta_phi.png");
TH2F *h_RC_eta = hdata->createHistogram(*scetaiXvar, *rawvar, "","raw_vs_eta");
if(EEorEB=="EB")
{
h_RC_eta->GetXaxis()->SetTitle("i#eta");
}
else
{
h_RC_eta->GetXaxis()->SetTitle("iX");
}
h_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_eta->Draw("COLZ");
c_raw_eta->SaveAs("raw_vs_eta.pdf");
c_raw_eta->SaveAs("raw_vs_eta.png");
TCanvas *c_raw_phi = new TCanvas;
TH2F *h_RC_phi = hdata->createHistogram(*scphiiYvar, *rawvar, "","raw_vs_phi");
if(EEorEB=="EB")
{
h_RC_phi->GetXaxis()->SetTitle("i#phi");
}
else
{
h_RC_phi->GetXaxis()->SetTitle("iY");
}
h_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_phi->Draw("COLZ");
c_raw_phi->SaveAs("raw_vs_phi.pdf");
c_raw_phi->SaveAs("raw_vs_phi.png");
//on2,5,20, etc
if(EEorEB == "EB")
{
TCanvas *myC_iCrystal_mod = new TCanvas;
RooRealVar *SM_distvar = ws->var("var_6");
SM_distvar->setRange(0,10);
SM_distvar->setBins(10);
TH2F *h_CC_SM_dist = hdata->createHistogram(*SM_distvar, *ecorvar, "","cor_vs_SM_dist");
h_CC_SM_dist->GetXaxis()->SetTitle("SM_dist");
h_CC_SM_dist->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_SM_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_SM_dist.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_SM_dist.png");
TH2F *h_RC_SM_dist = hdata->createHistogram(*SM_distvar, *rawvar, "","raw_vs_SM_dist");
h_RC_SM_dist->GetXaxis()->SetTitle("distance to SM gap");
h_RC_SM_dist->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_SM_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_SM_dist.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_SM_dist.png");
RooRealVar *M_distvar = ws->var("var_7");
M_distvar->setRange(0,13);
M_distvar->setBins(10);
TH2F *h_CC_M_dist = hdata->createHistogram(*M_distvar, *ecorvar, "","cor_vs_M_dist");
h_CC_M_dist->GetXaxis()->SetTitle("M_dist");
h_CC_M_dist->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_M_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_M_dist.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_M_dist.png");
TH2F *h_RC_M_dist = hdata->createHistogram(*M_distvar, *rawvar, "","raw_vs_M_dist");
h_RC_M_dist->GetXaxis()->SetTitle("distance to module gap");
h_RC_M_dist->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_M_dist->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_M_dist.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_M_dist.png");
/*
RooRealVar *DeltaRG1G2var = ws->var("var_8");
DeltaRG1G2var->setRange(0,0.2);
DeltaRG1G2var->setBins(100);
TH2F *h_CC_DeltaRG1G2 = hdata->createHistogram(*DeltaRG1G2var, *ecorvar, "","cor_vs_DeltaRG1G2");
h_CC_DeltaRG1G2->GetXaxis()->SetTitle("DeltaRG1G2");
h_CC_DeltaRG1G2->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_DeltaRG1G2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("cor_vs_DeltaRG1G2.pdf");
myC_iCrystal_mod->SaveAs("cor_vs_DeltaRG1G2.png");
TH2F *h_RC_DeltaRG1G2 = hdata->createHistogram(*DeltaRG1G2var, *rawvar, "","raw_vs_DeltaRG1G2");
h_RC_DeltaRG1G2->GetXaxis()->SetTitle("distance to module gap");
h_RC_DeltaRG1G2->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_DeltaRG1G2->Draw("COLZ");
myC_iCrystal_mod->SaveAs("raw_vs_DeltaRG1G2.pdf");
myC_iCrystal_mod->SaveAs("raw_vs_DeltaRG1G2.png");
*/
}
// other variables
TCanvas *myC_variables = new TCanvas;
RooRealVar *Nxtalvar = ws->var("var_1");
Nxtalvar->setRange(0,10);
Nxtalvar->setBins(10);
TH2F *h_CC_Nxtal = hdata->createHistogram(*Nxtalvar, *ecorvar, "","cor_vs_Nxtal");
h_CC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_CC_Nxtal->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("cor_vs_Nxtal.pdf");
myC_variables->SaveAs("cor_vs_Nxtal.png");
TH2F *h_RC_Nxtal = hdata->createHistogram(*Nxtalvar, *rawvar, "","raw_vs_Nxtal");
h_RC_Nxtal->GetXaxis()->SetTitle("Nxtal");
h_RC_Nxtal->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_Nxtal->Draw("COLZ");
myC_variables->SaveAs("raw_vs_Nxtal.pdf");
myC_variables->SaveAs("raw_vs_Nxtal.png");
RooRealVar *S4S9var = ws->var("var_2");
int Nbins_S4S9 = 100;
double Low_S4S9 = 0.6;
double High_S4S9 = 1.0;
S4S9var->setRange(Low_S4S9,High_S4S9);
S4S9var->setBins(Nbins_S4S9);
TH2F *h_CC_S4S9 = hdata->createHistogram(*S4S9var, *ecorvar, "","cor_vs_S4S9");
h_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h_CC_S4S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S4S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S4S9.pdf");
myC_variables->SaveAs("cor_vs_S4S9.png");
TH2F *h_RC_S4S9 = hdata->createHistogram(*S4S9var, *rawvar, "","raw_vs_S4S9");
h_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h_RC_S4S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S4S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S4S9.pdf");
myC_variables->SaveAs("raw_vs_S4S9.png");
RooRealVar *S2S9var = ws->var("var_3");
int Nbins_S2S9 = 100;
double Low_S2S9 = 0.5;
double High_S2S9 = 1.0;
S2S9var->setRange(Low_S2S9,High_S2S9);
S2S9var->setBins(Nbins_S2S9);
TH2F *h_CC_S2S9 = hdata->createHistogram(*S2S9var, *ecorvar, "","cor_vs_S2S9");
h_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h_CC_S2S9->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h_CC_S2S9->Draw("COLZ");
myC_variables->SaveAs("cor_vs_S2S9.pdf");
myC_variables->SaveAs("cor_vs_S2S9.png");
TH2F *h_RC_S2S9 = hdata->createHistogram(*S2S9var, *rawvar, "","raw_vs_S2S9");
h_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h_RC_S2S9->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h_RC_S2S9->Draw("COLZ");
myC_variables->SaveAs("raw_vs_S2S9.pdf");
myC_variables->SaveAs("raw_vs_S2S9.png");
TH2F *h_S2S9_eta = hdata->createHistogram(*scetaiXvar, *S2S9var, "","S2S9_vs_eta");
h_S2S9_eta->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S2S9_eta->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_eta.pdf");
myC_variables->SaveAs("S2S9_vs_eta.png");
TH2F *h_S4S9_eta = hdata->createHistogram(*scetaiXvar, *S4S9var, "","S4S9_vs_eta");
h_S4S9_eta->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_eta->GetYaxis()->SetTitle("i#eta");
}
else
{
h_CC_eta->GetYaxis()->SetTitle("iX");
}
h_S4S9_eta->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_eta.pdf");
myC_variables->SaveAs("S4S9_vs_eta.png");
TH2F *h_S2S9_phi = hdata->createHistogram(*scphiiYvar, *S2S9var, "","S2S9_vs_phi");
h_S2S9_phi->GetYaxis()->SetTitle("S2S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S2S9_phi->Draw("COLZ");
myC_variables->SaveAs("S2S9_vs_phi.pdf");
myC_variables->SaveAs("S2S9_vs_phi.png");
TH2F *h_S4S9_phi = hdata->createHistogram(*scphiiYvar, *S4S9var, "","S4S9_vs_phi");
h_S4S9_phi->GetYaxis()->SetTitle("S4S9");
if(EEorEB=="EB")
{
h_CC_phi->GetYaxis()->SetTitle("i#phi");
}
else
{
h_CC_phi->GetYaxis()->SetTitle("iY");
}
h_S4S9_phi->Draw("COLZ");
myC_variables->SaveAs("S4S9_vs_phi.pdf");
myC_variables->SaveAs("S4S9_vs_phi.png");
if(EEorEB=="EE")
{
}
TProfile *p_CC_eta = h_CC_eta->ProfileX("p_CC_eta");//,1,-1,"s");
p_CC_eta->GetYaxis()->SetRangeUser(0.8,1.05);
if(EEorEB == "EB")
{
// p_CC_eta->GetYaxis()->SetRangeUser(0.85,1.0);
// p_CC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_eta->SetTitle("");
p_CC_eta->Draw();
myC_variables->SaveAs("profile_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_cor_vs_eta.png");
// fill the E/Etrue vs. eta with each point taken from fits
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_CC_eta = new TH1F("h1_fit_CC_eta","h1_fit_CC_eta",(EEorEB=="EB") ? 180 : 50,(EEorEB=="EB") ? -90 : 0, (EEorEB=="EB") ? 90 : 50);
for(int ix = 1;ix <= h_CC_eta->GetNbinsX(); ix++)
{
stringstream os_iEta;
os_iEta << ((EEorEB=="EB") ? (-90 + ix -1) : (0 + ix -1));
string ss_iEta = os_iEta.str();
TH1D * h_temp = h_CC_eta->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.95,1.07);
h_temp->Fit("f_temp","R");
h1_fit_CC_eta->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_CC_eta->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{cor}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".pdf").c_str());
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".png").c_str());
myC_variables->SaveAs(("fits/CC_iEta_"+ss_iEta+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_CC_eta->GetYaxis()->SetRangeUser((gammaID==1) ? 0.95 : 0.9 , (gammaID==1) ? 1.05 : 1.1);
h1_fit_CC_eta->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h1_fit_CC_eta->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#eta" : "iX");
h1_fit_CC_eta->SetTitle("");
h1_fit_CC_eta->Draw();
myC_variables->SaveAs("profile_fit_cor_vs_eta.pdf");
myC_variables->SaveAs("profile_fit_cor_vs_eta.png");
myC_variables->SaveAs("profile_fit_cor_vs_eta.C");
TProfile *p_RC_eta = h_RC_eta->ProfileX("p_RC_eta");//,1,-1,"s");
p_RC_eta->GetYaxis()->SetRangeUser(0.8,1.05);
if(EEorEB=="EB")
{
// p_RC_eta->GetYaxis()->SetRangeUser(0.80,0.95);
// p_RC_eta->GetXaxis()->SetRangeUser(-1.5,1.5);
}
p_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_eta->SetTitle("");
p_RC_eta->Draw();
myC_variables->SaveAs("profile_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_raw_vs_eta.png");
// fill the E/Etrue vs. eta with each point taken from fits
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_RC_eta = new TH1F("h1_fit_RC_eta","h1_fit_RC_eta",(EEorEB=="EB") ? 180 : 50,(EEorEB=="EB") ? -90 : 0, (EEorEB=="EB") ? 90 : 50);
for(int ix = 1;ix <= h_RC_eta->GetNbinsX(); ix++)
{
stringstream os_iEta;
os_iEta << ((EEorEB=="EB") ? (-90 + ix -1) : (0 + ix -1));
string ss_iEta = os_iEta.str();
TH1D * h_temp = h_RC_eta->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.87,1.05);
h_temp->Fit("f_temp","R");
h1_fit_RC_eta->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_RC_eta->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{raw}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".pdf").c_str());
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".png").c_str());
myC_variables->SaveAs(("fits/RC_iEta_"+ss_iEta+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_RC_eta->GetYaxis()->SetRangeUser((gammaID==1) ? 0.9 : 0.8,1.0);
h1_fit_RC_eta->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h1_fit_RC_eta->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#eta" : "iX");
h1_fit_RC_eta->SetTitle("");
h1_fit_RC_eta->Draw();
myC_variables->SaveAs("profile_fit_raw_vs_eta.pdf");
myC_variables->SaveAs("profile_fit_raw_vs_eta.png");
myC_variables->SaveAs("profile_fit_raw_vs_eta.C");
int Nbins_iEta = EEorEB=="EB" ? 180 : 50;
int nLow_iEta = EEorEB=="EB" ? -90 : 0;
int nHigh_iEta = EEorEB=="EB" ? 90 : 50;
TH1F *h1_RC_eta = new TH1F("h1_RC_eta","h1_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_RC_eta->SetBinContent(i,p_RC_eta->GetBinError(i));
}
h1_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_RC_eta->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_eta->SetTitle("");
h1_RC_eta->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_eta.png");
TH1F *h1_CC_eta = new TH1F("h1_CC_eta","h1_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
for(int i=1;i<=Nbins_iEta;i++)
{
h1_CC_eta->SetBinContent(i,p_CC_eta->GetBinError(i));
}
h1_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_CC_eta->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_eta->SetTitle("");
h1_CC_eta->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_eta.png");
TProfile *p_CC_phi = h_CC_phi->ProfileX("p_CC_phi");//,1,-1,"s");
p_CC_phi->GetYaxis()->SetRangeUser( (gammaID==1) ? 0.9 : 0.8,1.0);
if(EEorEB == "EB")
{
// p_CC_phi->GetYaxis()->SetRangeUser(0.94,1.00);
}
p_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
p_CC_phi->SetTitle("");
p_CC_phi->Draw();
myC_variables->SaveAs("profile_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_cor_vs_phi.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_CC_phi = new TH1F("h1_fit_CC_phi","h1_fit_CC_phi",(EEorEB=="EB") ? 360 : 50,(EEorEB=="EB") ? 0 : 0, (EEorEB=="EB") ? 360 : 50);
for(int ix = 1;ix <= h_CC_phi->GetNbinsX(); ix++)
{
stringstream os_iPhi;
os_iPhi << ((EEorEB=="EB") ? (0 + ix -1) : (0 + ix -1));
string ss_iPhi = os_iPhi.str();
TH1D * h_temp = h_CC_phi->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.95,1.07);
h_temp->Fit("f_temp","R");
h1_fit_CC_phi->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_CC_phi->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{cor}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".pdf").c_str());
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".png").c_str());
myC_variables->SaveAs(("fits/CC_iPhi_"+ss_iPhi+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_CC_phi->GetYaxis()->SetRangeUser((gammaID==1) ? 0.95 : 0.9,(gammaID==1) ? 1.05 : 1.1);
h1_fit_CC_phi->GetYaxis()->SetTitle("E_{cor}/E_{true}");
h1_fit_CC_phi->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#phi" : "iX");
h1_fit_CC_phi->SetTitle("");
h1_fit_CC_phi->Draw();
myC_variables->SaveAs("profile_fit_cor_vs_phi.pdf");
myC_variables->SaveAs("profile_fit_cor_vs_phi.png");
myC_variables->SaveAs("profile_fit_cor_vs_phi.C");
TProfile *p_RC_phi = h_RC_phi->ProfileX("p_RC_phi");//,1,-1,"s");
p_RC_phi->GetYaxis()->SetRangeUser((gammaID==1) ? 0.9 : 0.8,1.0);
if(EEorEB=="EB")
{
// p_RC_phi->GetYaxis()->SetRangeUser(0.89,0.95);
}
p_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
p_RC_phi->SetTitle("");
p_RC_phi->Draw();
myC_variables->SaveAs("profile_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_raw_vs_phi.png");
gStyle->SetOptStat(111);
gStyle->SetOptFit(1);
TH1F *h1_fit_RC_phi = new TH1F("h1_fit_RC_phi","h1_fit_RC_phi",(EEorEB=="EB") ? 360 : 50,(EEorEB=="EB") ? 0 : 0, (EEorEB=="EB") ? 360 : 50);
for(int ix = 1;ix <= h_RC_phi->GetNbinsX(); ix++)
{
stringstream os_iPhi;
os_iPhi << ((EEorEB=="EB") ? (0 + ix -1) : (0 + ix -1));
string ss_iPhi = os_iPhi.str();
TH1D * h_temp = h_RC_phi->ProjectionY("h_temp",ix,ix);
h_temp->Rebin(4);
TF1 *f_temp = new TF1("f_temp","gaus(0)",0.87,1.05);
h_temp->Fit("f_temp","R");
h1_fit_RC_phi->SetBinContent(ix, f_temp->GetParameter(1));
h1_fit_RC_phi->SetBinError(ix, f_temp->GetParError(1));
h_temp->GetXaxis()->SetTitle("E_{raw}/E_{true}");
h_temp->SetTitle("");
h_temp->Draw();
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".pdf").c_str());
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".png").c_str());
myC_variables->SaveAs(("fits/RC_iPhi_"+ss_iPhi+".C").c_str());
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
h1_fit_RC_phi->GetYaxis()->SetRangeUser((gammaID==1) ? 0.9 : 0.8,1.0);
h1_fit_RC_phi->GetYaxis()->SetTitle("E_{raw}/E_{true}");
h1_fit_RC_phi->GetXaxis()->SetTitle((EEorEB=="EB") ? "i#phi" : "iX");
h1_fit_RC_phi->SetTitle("");
h1_fit_RC_phi->Draw();
myC_variables->SaveAs("profile_fit_raw_vs_phi.pdf");
myC_variables->SaveAs("profile_fit_raw_vs_phi.png");
myC_variables->SaveAs("profile_fit_raw_vs_phi.C");
int Nbins_iPhi = EEorEB=="EB" ? 360 : 50;
int nLow_iPhi = EEorEB=="EB" ? 0 : 0;
int nHigh_iPhi = EEorEB=="EB" ? 360 : 50;
TH1F *h1_RC_phi = new TH1F("h1_RC_phi","h1_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_RC_phi->SetBinContent(i,p_RC_phi->GetBinError(i));
}
h1_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_RC_phi->GetYaxis()->SetTitle("#sigma_{E_{raw}/E_{true}}");
h1_RC_phi->SetTitle("");
h1_RC_phi->Draw();
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Eraw_Etrue_vs_phi.png");
TH1F *h1_CC_phi = new TH1F("h1_CC_phi","h1_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
for(int i=1;i<=Nbins_iPhi;i++)
{
h1_CC_phi->SetBinContent(i,p_CC_phi->GetBinError(i));
}
h1_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_CC_phi->GetYaxis()->SetTitle("#sigma_{E_{cor}/E_{true}}");
h1_CC_phi->SetTitle("");
h1_CC_phi->Draw();
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("sigma_Ecor_Etrue_vs_phi.png");
// FWHM over sigma_eff vs. eta/phi
TH1F *h1_FoverS_RC_phi = new TH1F("h1_FoverS_RC_phi","h1_FoverS_RC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_CC_phi = new TH1F("h1_FoverS_CC_phi","h1_FoverS_CC_phi",Nbins_iPhi,nLow_iPhi,nHigh_iPhi);
TH1F *h1_FoverS_RC_eta = new TH1F("h1_FoverS_RC_eta","h1_FoverS_RC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_eta = new TH1F("h1_FoverS_CC_eta","h1_FoverS_CC_eta",Nbins_iEta,nLow_iEta,nHigh_iEta);
TH1F *h1_FoverS_CC_S2S9 = new TH1F("h1_FoverS_CC_S2S9","h1_FoverS_CC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_RC_S2S9 = new TH1F("h1_FoverS_RC_S2S9","h1_FoverS_RC_S2S9",Nbins_S2S9,Low_S2S9,High_S2S9);
TH1F *h1_FoverS_CC_S4S9 = new TH1F("h1_FoverS_CC_S4S9","h1_FoverS_CC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
TH1F *h1_FoverS_RC_S4S9 = new TH1F("h1_FoverS_RC_S4S9","h1_FoverS_RC_S4S9",Nbins_S4S9,Low_S4S9,High_S4S9);
float FWHMoverSigmaEff = 0.0;
TH1F *h_tmp_rawvar = new TH1F("tmp_rawvar","tmp_rawvar",800,0.5,1.5);
TH1F *h_tmp_corvar = new TH1F("tmp_corvar","tmp_corvar",800,0.5,1.5);
for(int i=1;i<=Nbins_iPhi;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_phi->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_phi->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_phi->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_phi->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_phi->GetXaxis()->SetRangeUser(0,2.0);
h1_FoverS_CC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_CC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_phi->SetTitle("");
h1_FoverS_CC_phi->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_phi.png");
h1_FoverS_RC_phi->GetXaxis()->SetRangeUser(0,2.0);
h1_FoverS_RC_phi->GetXaxis()->SetTitle("i#phi");
h1_FoverS_RC_phi->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_phi->SetTitle("");
h1_FoverS_RC_phi->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_phi.png");
for(int i=1;i<=Nbins_iEta;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_eta->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_eta->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_eta->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_eta->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_eta->GetXaxis()->SetRangeUser(0,2.0);
h1_FoverS_CC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_CC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_eta->SetTitle("");
h1_FoverS_CC_eta->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_eta.png");
h1_FoverS_RC_eta->GetXaxis()->SetRangeUser(0,2.0);
h1_FoverS_RC_eta->GetXaxis()->SetTitle("i#eta");
h1_FoverS_RC_eta->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_eta->SetTitle("");
h1_FoverS_RC_eta->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_eta.png");
for(int i=1;i<=Nbins_S2S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S2S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S2S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S2S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_CC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_CC_S2S9->SetTitle("");
h1_FoverS_CC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S2S9.png");
h1_FoverS_RC_S2S9->GetXaxis()->SetTitle("S2S9");
h1_FoverS_RC_S2S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S2S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S2S9->SetTitle("");
h1_FoverS_RC_S2S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S2S9.png");
for(int i=1;i<=Nbins_S4S9;i++)
{
float FWHM_tmp = 0.0;
float effSigma_tmp = 0.0;
for(int j=1;j<=800;j++)
{
h_tmp_rawvar->SetBinContent(j,h_RC_S4S9->GetBinContent(i,j));
h_tmp_corvar->SetBinContent(j,h_CC_S4S9->GetBinContent(i,j));
}
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_rawvar);
effSigma_tmp = effSigma(h_tmp_rawvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_RC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
FWHMoverSigmaEff = 0.0;
FWHM_tmp= FWHM(h_tmp_corvar);
effSigma_tmp = effSigma(h_tmp_corvar);
if(effSigma_tmp>0.000001) FWHMoverSigmaEff = FWHM_tmp/effSigma_tmp;
h1_FoverS_CC_S4S9->SetBinContent(i, FWHMoverSigmaEff);
}
h1_FoverS_CC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_CC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{cor}/E_{true}");
h1_FoverS_CC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_CC_S4S9->SetTitle("");
h1_FoverS_CC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Ecor_Etrue_vs_S4S9.png");
h1_FoverS_RC_S4S9->GetXaxis()->SetTitle("S4S9");
h1_FoverS_RC_S4S9->GetYaxis()->SetTitle("FWHM/#sigma_{eff} of E_{raw}/E_{true}");
h1_FoverS_RC_S4S9->GetYaxis()->SetRangeUser(0.0,2.0);
h1_FoverS_RC_S4S9->SetTitle("");
h1_FoverS_RC_S4S9->Draw();
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.pdf");
myC_variables->SaveAs("FoverS_Eraw_Etrue_vs_S4S9.png");
printf("calc effsigma\n");
std::cout<<"_"<<EEorEB<<std::endl;
printf("corrected curve effSigma= %5f, FWHM=%5f \n",effsigma_cor, fwhm_cor);
printf("raw curve effSigma= %5f FWHM=%5f \n",effsigma_raw, fwhm_raw);
/* new TCanvas;
RooPlot *ploteold = testvar.frame(0.6,1.2,100);
hdatasigtest->plotOn(ploteold);
ploteold->Draw();
new TCanvas;
RooPlot *plotecor = ecorvar->frame(0.6,1.2,100);
hdatasig->plotOn(plotecor);
plotecor->Draw(); */
}
void MakeSpinPlots::DrawIndFit(TString tag, TString mcName){
TCanvas *cv = new TCanvas(Form("%s_%s",mcName.Data(),tag.Data()));
if(ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcName.Data(),tag.Data()) ) == 0) return;
RooRealVar* mass = ws->var("mass");
mass->setBins( (mass->getMax() - mass->getMin())/1.5 ); //enfore 1.5GeV bin width
RooPlot* frame = mass->frame();
tPair lbl(mcName,tag);
double Ns = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcName.Data(),tag.Data()) )->getVal();
double Nb = ws->var( Form("Data_%s_INDFIT_%s_Nbkg",mcName.Data(),tag.Data()) )->getVal();
double Nblind = ws->data("Data_Combined")->reduce("(mass>100 && mass<119) || (mass>135.5 && mass<170)")->sumEntries(TString("evtcat==evtcat::")+tag);
double Ntot = ws->data("Data_Combined")->sumEntries(TString("evtcat==evtcat::")+tag);
RooFitResult* fitres = (RooFitResult*)ws->obj(Form("Data_%s_INDFIT_fitResult",mcName.Data()));
std::cout << fitres << std::endl;
ws->data("Data_Combined")->reduce(TString("evtcat==evtcat::")+tag)->plotOn(frame,RooFit::LineColor(kWhite),RooFit::MarkerColor(kWhite));
//Data_Hgg125_INDFIT_EB_0
ws->pdf(Form("Data_%s_INDFIT_%s",mcName.Data(),tag.Data()))->plotOn(frame, RooFit::FillColor(kGreen),RooFit::VisualizeError(*fitres,2.0));
ws->pdf(Form("Data_%s_INDFIT_%s",mcName.Data(),tag.Data()))->plotOn(frame, RooFit::FillColor(kYellow),RooFit::VisualizeError(*fitres,1.0));
ws->pdf(Form("Data_%s_INDFIT_%s",mcName.Data(),tag.Data()))->plotOn(frame, RooFit::LineColor(kRed));
std::cout << "1" << std::endl;
ws->pdf(Form("Data_BKGFIT_%s_bkgModel",tag.Data()))->plotOn(frame, RooFit::Normalization(Nb/(Nb+Ns)),RooFit::LineColor(kRed),RooFit::LineStyle(kDashed));
std::cout << "2" << std::endl;
ws->data("Data_Combined")->reduce(TString("evtcat==evtcat::")+tag)->plotOn(frame);
frame->Draw();
//TLatex *prelim = new TLatex(250,x->GetXmax()-40.,"CMS Preliminary");
TLatex *prelim = new TLatex(0.12,0.96,"CMS Preliminary");
TLatex *lum = new TLatex(0.7,0.96,Form("#sqrt{s}=8 TeV L = %0.1f fb^{-1}",lumi));
prelim->SetNDC();
lum->SetNDC();
prelim->SetTextSize(0.045);
prelim->SetTextColor(kBlack);
lum->SetTextSize(0.045);
lum->SetTextColor(kBlack);
TLatex *owner = new TLatex(0.6,0.88,"Alex Mott (Nov. 13, 2012)");
owner->SetNDC();
owner->SetTextSize(0.045);
owner->SetTextColor(kBlack);
TLatex *mu = new TLatex(0.7,0.8,Form("#mu = %0.1f #pm %0.2f", fitMean[lbl].first,fitMean[lbl].second));
mu->SetNDC();
mu->SetTextSize(0.045);
TLatex *sig = new TLatex(0.7,0.72,Form("#sigma_{eff} = %0.1f #pm %0.2f", fitSigEff[lbl].first,fitSigEff[lbl].second));
sig->SetNDC();
sig->SetTextSize(0.045);
float nSig = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcName.Data(),tag.Data()) )->getVal();
float nSigErr = ws->var( Form("Data_%s_INDFIT_%s_Nsig",mcName.Data(),tag.Data()) )->getError();
TLatex *Nsig = new TLatex(0.7,0.64,Form("N_{sig}= %0.1f #pm %0.1f",nSig,nSigErr));
Nsig->SetNDC();
Nsig->SetTextSize(0.045);
frame->addObject(prelim);
frame->addObject(lum);
//frame->addObject(owner);
frame->addObject(mu);
frame->addObject(sig);
frame->addObject(Nsig);
frame->Draw();
cv->SaveAs( basePath+Form("/mgg-FloatedFraction-%s-%s-%s.png",outputTag.Data(),mcName.Data(),tag.Data()) );
cv->SaveAs( basePath+Form("/C/mgg-FloatedFraction-%s-%s-%s.C",outputTag.Data(),mcName.Data(),tag.Data()) );
cv->SaveAs( basePath+Form("/mgg-FloatedFraction-%s-%s-%s.pdf",outputTag.Data(),mcName.Data(),tag.Data()) );
delete cv;
}
RooAddPdf fitScaledMuMuGammaMass(
const char *histoname = "scaledMmgMass_00",
const char *filename = "scaledMmgHistos.root",
const char* plotOpt = "NEU",
const int nbins = 20)
{
gROOT->ProcessLine(".L tdrstyle.C");
setTDRStyle();
gStyle->SetPadRightMargin(0.05);
double minMass = 60;
double maxMass = 120;
RooRealVar mass("mass","m(#mu#mu#gamma)", minMass, maxMass,"GeV/c^{2}");
// Read data set
TFile * file = new TFile(filename);
TH1F * hh = (TH1F*) file->Get(histoname);
if (!hh) {
cout << "Didn't find " << histoname << " in " << filename << endl;
return;
}
RooDataHist *data = new RooDataHist("data", "data", RooArgSet(mass), hh);
// RooDataSet *data = RooDataSet::read(filename,RooArgSet(mass));
// RooDataSet *dataB = RooDataSet::read(filenameB,RooArgSet(mass));
// Build p.d.f.
////////////////////////////////////////////////
// Parameters //
////////////////////////////////////////////////
// Signal p.d.f. parameters
// Parameters for a Gaussian and a Crystal Ball Lineshape
RooRealVar cbBias ("#Deltam_{CB}", "CB Bias", 0.05, -10, 10,"GeV/c^{2}");
RooRealVar cbSigma("#sigma_{CB}","CB Width", 1.6, 0.001, 10.0,"GeV/c^{2}");
RooRealVar cbCut ("a_{CB}","CB Cut", 1.5, 0.1, 2.0);
RooRealVar cbPower("n_{CB}","CB Power", 1.3, 0.1, 20.0);
// cbSigma.setConstant(kTRUE);
// cbCut.setConstant(kTRUE);
// cbPower.setConstant(kTRUE);
// Parameters for Breit-Wigner
RooRealVar bwMean("m_{Z}","BW Mean", 91.1876, "GeV/c^{2}");
RooRealVar bwWidth("#Gamma_{Z}", "BW Width", 2.4952, "GeV/c^{2}");
// Keep Breit-Wigner parameters fixed to the PDG values
// bwMean.setConstant(kTRUE);
// bwWidth.setConstant(kTRUE);
// Background p.d.f. parameters
// Parameters for exponential
RooRealVar expRate("#lambda_{exp}", "Exponential Rate", -0.119, -10, 1);
// expRate.setConstant(kTRUE);
// fraction of signal
// RooRealVar frac("frac", "Signal Fraction", 0.1,0.,0.3.);
/* RooRealVar nsig("N_{S}", "#signal events", 9000, 0.,10000.);
RooRealVar nbkg("N_{B}", "#background events", 1000,2,10000.);*/
RooRealVar nsig("N_{S}", "#signal events", 29300, 0.1, 100000.);
RooRealVar nbkg("N_{B}", "#background events", 0, 0., 10000.);
// nbkg.setConstant(kTRUE);
////////////////////////////////////////////////
// P.D.F.s //
////////////////////////////////////////////////
// Di-photon mass signal p.d.f.
RooBreitWigner bw("bw", "bw", mass, bwMean, bwWidth);
// RooGaussian signal("signal", "A Gaussian Lineshape", mass, m0, sigma);
RooCBShape cball("cball", "A Crystal Ball Lineshape", mass, cbBias, cbSigma, cbCut, cbPower);
mass.setBins(100000, "fft");
RooFFTConvPdf BWxCB("BWxCB","bw (X) crystall ball", mass, bw, cball);
// Di-photon mass background p.d.f.
RooExponential bg("bg","bkgd exp", mass, expRate);
// Di-photon mass model p.d.f.
RooAddPdf model("model", "signal + background mass model", RooArgList(BWxCB, bg), RooArgList(nsig, nbkg));
TStopwatch t ;
t.Start() ;
model.fitTo(*data,FitOptions("mh"),Optimize(0),Timer(1));
// signal->fitTo(*data,FitOptions("mh"),Optimize(0),Timer(1));
t.Print() ;
TCanvas *c = new TCanvas("c","Unbinned Invariant Mass Fit", 0,0,800,600);
// Plot the fit results
RooPlot* plot = mass.frame(Range(minMass,maxMass)/*,Bins(nbins)*/);
// Plot 1
// dataB->plotOn(plot, MarkerColor(kRed), LineColor(kRed));
data->plotOn(plot);
// model.plotOn(plot);
model.plotOn(plot);
//model.paramOn(plot, Format(plotOpt, AutoPrecision(1)), Parameters(RooArgSet(nsig, nbkg, m0, sigma)));
model.paramOn(plot, Format(plotOpt, AutoPrecision(1)), Parameters(RooArgSet(cbBias, cbSigma, cbCut, cbPower, bwMean, bwWidth, expRate, nsig, nbkg)));
// model.plotOn(plot, Components("signal"), LineStyle(kDashed), LineColor(kRed));
model.plotOn(plot, Components("bg"), LineStyle(kDashed), LineColor(kRed));
plot->Draw();
// TLatex * tex = new TLatex(0.2,0.8,"CMS preliminary");
// tex->SetNDC();
// tex->SetTextFont(42);
// tex->SetLineWidth(2);
// tex->Draw();
// tex->DrawLatex(0.2, 0.725, "7 TeV Data, L = 258 pb^{-1}");
//
// float fsig_peak = NormalizedIntegral(model,
// mass,
// cbBias.getVal() - 2.5*cbSigma.getVal(),
// cbBias.getVal() + 2.5*cbSigma.getVal()
// );
// float fbkg_peak = NormalizedIntegral(bg,
// mass,
// m0.getVal() - 2.5*sigma.getVal(),
// m0.getVal() + 2.5*sigma.getVal()
// );
/* double nsigVal = fsig_peak * nsig.getVal();
double nsigErr = fsig_peak * nsig.getError();
double nsigErrRel = nsigErr / nsigVal;*/
// double nbkgVal = fbkg_peak * nbkg.getVal();
// double nbkgErr = fbkg_peak * nbkg.getError();
// double nbkgErrRel = nbkgErr / nbkgVal;
// cout << "nsig " << nsigVal << " +/- " << nsigErr << endl;
// cout << "S/B_{#pm2.5#sigma} " << nsigVal/nbkgVal << " +/- "
// << (nsigVal/nbkgVal)*sqrt(nsigErrRel*nsigErrRel + nbkgErrRel*nbkgErrRel)
// << endl;
// tex->DrawLatex(0.2, 0.6, Form("N_{S} = %.0f#pm%.0f", nsigVal, nsigErr) );
// tex->DrawLatex(0.2, 0.525, Form("S/B_{#pm2.5#sigma} = %.1f", nsigVal/nbkgVal) );
// tex->DrawLatex(0.2, 0.45, Form("#frac{S}{#sqrt{B}}_{#pm2.5#sigma} = %.1f", nsigVal/sqrt(nbkgVal)));
// leg = new TLegend(0.65,0.6,0.9,0.75);
// leg->SetFillColor(kWhite);
// leg->SetLineColor(kWhite);
// leg->SetShadowColor(kWhite);
// leg->SetTextFont(42);
// TLegendEntry * ldata = leg->AddEntry(data, "Opposite Sign");
// TLegendEntry * ldataB = leg->AddEntry(dataB, "Same Sign");
// ldata->SetMarkerStyle(20);
// ldataB->SetMarkerStyle(20);
// ldataB->SetMarkerColor(kRed);
// leg->Draw();
cout << "histogram name, cbMean, cbMeanErr, cbWidth, cbWidthErr\n"
<< histoname << "\t"
<< cbBias.getVal() << "\t"
<< cbBias.getError() << "\t"
<< cbSigma.getVal() << "\t"
<< cbSigma.getError() << "\t"
<< std::endl << std::flush;
return model;
}
int main(){
/*Toy Model with following True parameters
Guess 20 events in Lb->pketa' (1)
and 15 events in Lb->pketa'->pipieta (2)
Lb Efficiencies=0.0002637
B+ Efficiency=0.000411 (3)
B(eta'->pi pi g)=0.291
B(eta'->pi pi eta)=0.16
fd/fL= 2.5
*/
int GenRare=40;
int GenRare2=30;
int GenControl=11000;
RooRealVar Mode2EfficiencyRatio("Mode2EfficiencyRatio","Mode2EfficiencyRatio",1.558589);
RooRealVar ModeEfficiencyRatio("ModeEfficiencyRatio","ModeEfficiencyRatio",1.558589);
RooRealVar SubBRRatio("SubBRRatio","SubBRRatio",0.645);
RooRealVar fdFl("fdFl","fdFl",2.5);
RooRealVar YieldRatio("YieldRatio","YieldRatio",0.1,0.000001,1.0);
RooRealVar YieldRatio2("YieldRatio2","YieldRatio2",0.1,0.000001,1.0);
//RooFormulaVar ObservableBFRatio("ObservableBFRatio","ObservableBFRatio","((@0*@1)+(@2*@3))*@4*@5",RooArgSet(YieldRatio,ModeEfficiencyRatio,YieldRatio2,Mode2EfficiencyRatio,SubBRRatio,fdFl));
RooRealVar ObservableBFRatio("ObservableBFRatio","ObservableBFRatio",0.5,0.00000001,10.0);
// RooRealVar ControlYield("ControlYield","ControlYield",10000.0,0.0,20000.0);
//RooRealVar RareYield("RareYield","RareYield",30.0,0.0,1100.0);
//RooFormulaVar RareArg("RareArg","RareArg","@1*@2",RooArgSet(ControlYield,YieldRatio));
RooRealVar ControlMean("ControlMean","ControlMean",5279.0,5200.0,5350.0);
RooRealVar SigmaCorrection("SigmaCorrection","SigmaCorrection",1.1,0.9,1.8);
RooRealVar LambdaMass("LambdaMass","LambdaMass",5000,6200.0);
// RooRealVar RareMean("RareMean","RareMean",5619.0,5600.0,5650.0);
RooFormulaVar RareMean("RareMean","RareMean","@0+339.72",RooArgSet(ControlMean));
RooRealVar MCRareSigma("MCRareSigma","MCRareSigma",25.0);
// RooRealVar RareSigma("RareSigma","RareSigma",29.0,20.0,40.0);
RooFormulaVar RareSigma("RareSigma","RareSigma","@0*@1",RooArgSet(MCRareSigma,SigmaCorrection));
RooGaussian RareMode("RareMode","RareMode",LambdaMass,RareMean,RareSigma);
RooRealVar K("K","K",-0.003,-0.010,-0.001);
RooExponential RareBkg("RareBkg","RareBkg",LambdaMass,K);
RooRealVar RareBkgYield("RareBkgYield","RareBkgYield",1000.0,0.0,2000.0);
RooExtendPdf ExtRareBkg("ExtRareBkg","ExtRareBkg",RareBkg,RareBkgYield);
// RooFormulaVar RareYield("RareYield","RareYield","@0*@1",RooArgSet(ControlYield,YieldRatio));
RooRealVar RareYield("RareYield","RareYield",1.0,0.0,600.0);
RooExtendPdf ExtRareSig("ExtRareSig","ExtRareSig",RareMode,RareYield);
RooAddPdf ExtRare("ExtRare","ExtRare",RooArgSet(ExtRareSig,ExtRareBkg));
RooDataSet* RareSigData=RareMode.generate(RooArgSet(LambdaMass),GenRare);
RooDataSet* RareBkgData=RareBkg.generate(RooArgSet(LambdaMass),500);
RooDataSet* RareData= new RooDataSet(*RareSigData,"RareData");
RareData->append(*RareBkgData);
RooRealVar MCRare2Sigma("MCRare2Sigma","MCRare2Sigma",17.0);
//RooRealVar Rare2Sigma("Rare2Sigma","Rare2Sigma",20.0,10.0,30.0);
RooFormulaVar Rare2Sigma("Rare2Sigma","Rare2Sigma","@0*@1",RooArgSet(MCRare2Sigma,SigmaCorrection));
RooGaussian RareMode2("RareMode2","RareMode2",LambdaMass,RareMean,Rare2Sigma);
RooDataSet* RareData2=RareMode2.generate(RooArgSet(LambdaMass),GenRare2);
//RooFormulaVar RareYield2("RareYield2","RareYield2","@0*@1",RooArgSet(ControlYield,YieldRatio2));
//RooFormulaVar RareYield2("RareYield2","RareYield2","(ControlYield*(1/Mode2EfficiencyRatio))*((ObservableBFRatio/(SubBRRatio*fdFl))-(YieldRatio*ModeEfficiencyRatio))",RooArgSet(ControlYield,Mode2EfficiencyRatio,ObservableBFRatio,SubBRRatio,fdFl,YieldRatio,ModeEfficiencyRatio));
RooRealVar RareYield2("RareYield2","RareYield2",1.0,0.0,100.0);
RooExtendPdf ExtRare2("ExtRare2","ExtRare2",RareMode2,RareYield2);
RooRealVar BMass("BMass","BMass",5000.0,5500.0);
// RooFormulaVar ControlMean("ControlMean","ControlMean","@0-339.72",RooArgSet(RareMean));
RooRealVar MCControlSigma("MCControlSigma","MCControlSigma",17.0);
RooFormulaVar ControlSigma("ControlSigma","ControlSigma","@0*@1",RooArgSet(MCControlSigma,SigmaCorrection));
//RooRealVar ControlSigma("ControlSigma","ControlSigma",20.0,10.0,40.0);
RooGaussian ControlMode("ControlMode","ControlMode",BMass,ControlMean,ControlSigma);
RooFormulaVar ControlYield("ControlYield","ControlYield","(1/ObservableBFRatio)*((ModeEfficiencyRatio*RareYield)+(Mode2EfficiencyRatio*RareYield2))*SubBRRatio*fdFl",RooArgSet(ObservableBFRatio,ModeEfficiencyRatio,RareYield,Mode2EfficiencyRatio,RareYield2,SubBRRatio,fdFl));
RooExtendPdf ExtControl("ExtControl","ExtControl",ControlMode,ControlYield);
RooDataSet* ControlData=ControlMode.generate(RooArgSet(BMass),GenControl);
RooCategory Mode("Mode","Mode");
Mode.defineType("Rare");
Mode.defineType("Rare2");
Mode.defineType("Control");
RooDataSet CombData("CombData","CombData",RooArgSet(BMass,LambdaMass),Index(Mode),Import("Rare2",*RareData2),Import("Rare",*RareData),Import("Control",*ControlData));
RooSimultaneous SimPdf("SimPdf","SimPdf",Mode);
SimPdf.addPdf(ExtRare,"Rare");
SimPdf.addPdf(ExtRare2,"Rare2");
SimPdf.addPdf(ExtControl,"Control");
RooFitResult* SimResult=SimPdf.fitTo(CombData,Save(kTRUE),Minos(kTRUE));
/* double FreeYield=-1*SimResult->minNll();
std::cout<<"With free yield = "<<SimResult->minNll()<<std::endl;
RareYield.setVal(0);
RareYield.setConstant(kTRUE);
RooFitResult* Rare1Fixed=SimPdf.fitTo(CombData,Save(kTRUE),Minos(kTRUE));
double NullYield=-1*Rare1Fixed->minNll();
std::cout<<"With not free yield = "<<Rare1Fixed->minNll()<<std::endl;
double DeltaLogLikelihood=NullYield-FreeYield;
std::cout<<"DeltaNll= "<<DeltaLogLikelihood<<std::endl;
double Significance=TMath::Sqrt(-2*DeltaLogLikelihood);
std::cout<<"Significance= "<<Significance<<std::endl;
SimPdf.fitTo(CombData,Save(kTRUE),Minos(kTRUE));*/
RooPlot* BFrame= BMass.frame(Bins(50),Title("B Mass"),Range(5200.0,5400.0));
ControlData->plotOn(BFrame);
ControlMode.plotOn(BFrame);
RooPlot* LambdaFrame = LambdaMass.frame(Bins(50),Title("Lambda mass"),Range(5200.0,6100.0));
RareData->plotOn(LambdaFrame);
ExtRare.plotOn(LambdaFrame);
RooPlot* LambdaFrame2 = LambdaMass.frame(Bins(50),Title("Lambda mass"),Range(5200.0,6100.0));
RareData2->plotOn(LambdaFrame2);
RareMode2.plotOn(LambdaFrame2);
TCanvas BCanvas;
BFrame->Draw();
BCanvas.SaveAs("BCanvas.pdf");
TCanvas LambdaCanvas;
LambdaFrame->Draw();
LambdaCanvas.SaveAs("LambdaCanvas.pdf");
TCanvas LambdaCanvas2;
LambdaFrame2->Draw();
LambdaCanvas2.SaveAs("LambdaCanvas2.pdf");
SimResult->Print("v");
// S imPdf.graphVizTree("model.dot");
std::cout<<"Real Ratio = "<<GenRare/(double)GenControl<<std::endl;
ObservableBFRatio.Print("v");
std::cout<<"Lb BF = "<<ObservableBFRatio.getVal()*7.06E-5<<" + "<<ObservableBFRatio.getErrorHi()*7.06E-5<<" - "<<ObservableBFRatio.getErrorLo()*7.06E-5<<std::endl;
//________________________________________________ATTEMPT TO SWEIGHT____________________________________________
RooStats::SPlot* sDataMass = new RooStats::SPlot("sData","An SPlot",*RareData,&ExtRare,RooArgList(RareYield,RareBkgYield));
std::cout << std::endl << "Yield of signal is " << RareYield.getVal() << ". From sWeights it is " << sDataMass->GetYieldFromSWeight("RareYield") << std::endl;
std::cout << "Yield of background is " << RareBkgYield.getVal() << ". From sWeights it is " << sDataMass->GetYieldFromSWeight("RareBkgYield") << std::endl << std::endl;
RooAbsReal* nll = SimPdf.createNLL(CombData);
RooMinuit(*nll).migrad();
RooPlot* LLFrame=ObservableBFRatio.frame(Title("Some Title"),Range(0.005,0.03));
nll->plotOn(LLFrame,ShiftToZero());
LLFrame->GetYaxis()->SetRangeUser(0.0,1000.0);
TCanvas LLCanvas;
LLFrame->Draw();
LLCanvas.SaveAs("LLCanvas.pdf");
}
double ks_YieldCal( TH1D* inputHist ){
//Starting to do RooFit:
RooRealVar x("x","mass",0.44,0.56);
RooDataHist data("data","dataset",x, inputHist );
RooPlot* xframe = x.frame(240);
data.plotOn(xframe, Name("data"));
RooRealVar mean("mean","mean",0.50,0.49,0.51);
RooRealVar sigma1("sigma1","sigma1",0.003,0.001,0.01);
RooRealVar sigma2("sigma2","sigma2",0.003,0.001,0.01);
RooRealVar sig1("sig1","signal1",10,0,10000000);
RooRealVar sig2("sig2","signal2",10,0,10000000);
RooRealVar a("a","a",0,-100000,100000);
RooRealVar b("b","b",0,-100000,100000);
RooRealVar cp("cp","cp",0,-100000,100000);
RooRealVar d("d","d",0,-100000,100000);
RooRealVar f("f","f",0,-100000,100000);
RooRealVar g("g","g",0,-100000,100000);
RooRealVar h("h","h",0,-100000,100000);
RooRealVar k("k","k",0,-100000,100000);
RooGaussian gaus1("gaus1","gaus1",x,mean,sigma1);
RooGaussian gaus2("gaus2","gaus2",x,mean,sigma2);
RooPolynomial poly("poly","poly",x,RooArgList(a,b,cp,d));
RooRealVar polysig("polysig","polysig",10,0,10000000);
RooAddPdf sum("sum","sum",RooArgList(gaus1,gaus2,poly),RooArgList(sig1,sig2,polysig));
x.setRange("cut",0.45,0.54);
sum.fitTo(data,Range("cut"));
sum.fitTo(data,Range("cut"));
sum.fitTo(data,Range("cut"));
sum.fitTo(data,Range("cut"));
sum.fitTo(data,Range("cut"));
sum.fitTo(data,Range("cut"));
sum.plotOn(xframe,Name("sum"),NormRange("cut"),LineWidth(0.5),LineColor(kRed));
sum.plotOn(xframe,Components(poly),NormRange("cut"),LineStyle(kDashed),LineWidth(0.5),LineColor(kRed));
xframe->Draw();
double chi2 = xframe->chiSquare("sum","data");
double meanf = mean.getVal();
double meanfe = mean.getError();
double sigmaf1 = sigma1.getVal();
double sigmaf2 = sigma2.getVal();
double bkgf = polysig.getVal();
double sigf1 = sig1.getVal();
double sigf2 = sig2.getVal();
double sigwf1 = sigf1 /(sigf1 +sigf2 );
double sigwf2 = sigf2 /(sigf1 +sigf2 );
double c1 = a.getVal();
double c2 = b.getVal();
double sigmaf = sqrt(sigmaf1 **2*sigwf1 + sigmaf2 **2*sigwf2 );
double massmin = meanf - 5*sigmaf ;
double massmax = meanf + 5*sigmaf ;
int nmin = inputHist ->GetXaxis()->FindBin(massmin );
int nmax = inputHist ->GetXaxis()->FindBin(massmax );
int anmin = inputHist ->GetXaxis()->FindBin(0.44);
int anmax = inputHist ->GetXaxis()->FindBin(0.56);
double awyh1 = inputHist ->Integral(anmin ,nmin );
double awyh2 = inputHist ->Integral(nmax ,anmax );
double awyh = awyh1 + awyh2 ;
double totyh = inputHist ->Integral(nmin ,nmax );
x.setRange("cut",massmin ,massmax );
RooAbsReal* ibkg = poly.createIntegral(x,NormSet(x),Range("cut"));
RooAbsReal* isig1 = gaus1.createIntegral(x,NormSet(x),Range("cut"));
RooAbsReal* isig2 = gaus2.createIntegral(x,NormSet(x),Range("cut"));
double ibkgf = ibkg ->getVal();
double bkgfe = polysig.getError();
double isig1f = isig1 ->getVal();
double isig2f = isig2 ->getVal();
double bkgy = ibkgf *bkgf ;
double bkgye = ibkgf *bkgfe ;
double sigy1 = isig1f *sigf1 ;
double sigy2 = isig2f *sigf2 ;
double sigy = sigy1 + sigy2 ;
double toty = bkgy + sigy ;
double abkgy = (1-ibkgf )*bkgf ;
double asigy1 = (1-isig1f )*sigf1 ;
double asigy2 = (1-isig2f )*sigf2 ;
double asigy = asigy1 + asigy2 ;
double awy = abkgy + asigy ;
double sigfrac = sigy /toty ;
double bkgfrac = bkgy /toty ;
double sigyh = totyh - bkgy ;
double sigfrach = sigyh /totyh ;
double bkgfrach = bkgy /totyh ;
double signif = sigyh / sqrt( totyh );
return sigyh;
}
void rf201_composite()
{
// S e t u p c o m p o n e n t p d f s
// ---------------------------------------
// Declare observable x
RooRealVar x("x","x",0,10) ;
// Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
RooRealVar mean("mean","mean of gaussians",5) ;
RooRealVar sigma1("sigma1","width of gaussians",0.5) ;
RooRealVar sigma2("sigma2","width of gaussians",1) ;
RooGaussian sig1("sig1","Signal component 1",x,mean,sigma1) ;
RooGaussian sig2("sig2","Signal component 2",x,mean,sigma2) ;
// Build Chebychev polynomial p.d.f.
RooRealVar a0("a0","a0",0.5,0.,1.) ;
RooRealVar a1("a1","a1",0.2,0.,1.) ;
RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1)) ;
// ---------------------------------------------
// M E T H O D 1 - T w o R o o A d d P d f s
// =============================================
// A d d s i g n a l c o m p o n e n t s
// ------------------------------------------
// Sum the signal components into a composite signal p.d.f.
RooRealVar sig1frac("sig1frac","fraction of component 1 in signal",0.8,0.,1.) ;
RooAddPdf sig("sig","Signal",RooArgList(sig1,sig2),sig1frac) ;
// A d d s i g n a l a n d b a c k g r o u n d
// ------------------------------------------------
// Sum the composite signal and background
RooRealVar bkgfrac("bkgfrac","fraction of background",0.5,0.,1.) ;
RooAddPdf model("model","g1+g2+a",RooArgList(bkg,sig),bkgfrac) ;
// S a m p l e , f i t a n d p l o t m o d e l
// ---------------------------------------------------
// Generate a data sample of 1000 events in x from model
RooDataSet *data = model.generate(x,1000) ;
// Fit model to data
model.fitTo(*data) ;
// Plot data and PDF overlaid
RooPlot* xframe = x.frame(Title("Example of composite pdf=(sig1+sig2)+bkg")) ;
data->plotOn(xframe) ;
model.plotOn(xframe) ;
// Overlay the background component of model with a dashed line
model.plotOn(xframe,Components(bkg),LineStyle(kDashed)) ;
// Overlay the background+sig2 components of model with a dotted line
model.plotOn(xframe,Components(RooArgSet(bkg,sig2)),LineStyle(kDotted)) ;
// Print structure of composite p.d.f.
model.Print("t") ;
// ---------------------------------------------------------------------------------------------
// M E T H O D 2 - O n e R o o A d d P d f w i t h r e c u r s i v e f r a c t i o n s
// =============================================================================================
// Construct sum of models on one go using recursive fraction interpretations
//
// model2 = bkg + (sig1 + sig2)
//
RooAddPdf model2("model","g1+g2+a",RooArgList(bkg,sig1,sig2),RooArgList(bkgfrac,sig1frac),kTRUE) ;
// NB: Each coefficient is interpreted as the fraction of the
// left-hand component of the i-th recursive sum, i.e.
//
// sum4 = A + ( B + ( C + D) with fraction fA, fB and fC expands to
//
// sum4 = fA*A + (1-fA)*(fB*B + (1-fB)*(fC*C + (1-fC)*D))
// P l o t r e c u r s i v e a d d i t i o n m o d e l
// ---------------------------------------------------------
model2.plotOn(xframe,LineColor(kRed),LineStyle(kDashed)) ;
model2.plotOn(xframe,Components(RooArgSet(bkg,sig2)),LineColor(kRed),LineStyle(kDashed)) ;
model2.Print("t") ;
// Draw the frame on the canvas
new TCanvas("rf201_composite","rf201_composite",600,600) ;
gPad->SetLeftMargin(0.15) ; xframe->GetYaxis()->SetTitleOffset(1.4) ; xframe->Draw() ;
}
fitYnSMassUnbinned(const char *filename = "YMassOS_186nb.txt",
const char* plotOpt = "NEU",
const int nbins = 40,
const char* filenameB = "YMassSS_186nb.txt")
{
gROOT->ProcessLine(".L tdrstyle.C");
setTDRStyle();
gStyle->SetPadRightMargin(0.05);
RooRealVar mass("mass","M(#mu^{+}#mu^{-})", 8.0, 12.0,"GeV/c^{2}");
// Read data set
RooDataSet *data = RooDataSet::read(filename,RooArgSet(mass));
RooDataSet *dataB = RooDataSet::read(filenameB,RooArgSet(mass));
// Build p.d.f.
////////////////////////////////////////////////
// Parameters //
////////////////////////////////////////////////
// Signal p.d.f. parameters
// Parameters for a Gaussian and a Crystal Ball Lineshape
RooRealVar m0 ("m_{0}", "Bias", 9.46, 9.2, 9.7,"GeV/c^{2}");
RooRealVar sigma("#sigma","Width", 0.04,0.01,0.1,"GeV/c^{2}");
RooRealVar cut ("#alpha","Cut", 0.6,0.6,2.0);
RooRealVar power("power","Power", 10.0, 0.5, 20.0);
// Background p.d.f. parameters
// Parameters for a polynomial lineshape
RooRealVar c0("c_{0}", "c0", 0., -10, 10);
RooRealVar c1("c_{1}", "c1", 0., -100, 0);
RooRealVar c2("c_{2}", "c2", 0., -100, 100);
// c0.setConstant();
// fraction of signal
// RooRealVar frac("frac", "Signal Fraction", 0.1,0.,0.3.);
RooRealVar nsig("N_{S}", "#signal events", 9000, 0.,10000.);
RooRealVar nbkg("N_{B}", "#background events", 1000,2,10000.);
////////////////////////////////////////////////
// P.D.F.s //
////////////////////////////////////////////////
// Di-photon mass signal p.d.f.
RooGaussian signal("signal", "A Gaussian Lineshape", mass, m0, sigma);
// RooCBShape signal("signal", "A Crystal Ball Lineshape", mass, m0,sigma, cut, power);
// Di-photon mass background p.d.f.
RooPolynomial bg("bg", "Backgroung Distribution", mass, RooArgList(c0,c1));
// Di-photon mass model p.d.f.
// RooAddPdf model("model", "Di-photon mass model", signal, bg, frac);
RooAddPdf model("model", "Di-photon mass model", RooArgList(signal, bg), RooArgList(nsig, nbkg));
TStopwatch t ;
t.Start() ;
model->fitTo(*data,FitOptions("mh"),Optimize(0),Timer(1));
t.Print() ;
c = new TCanvas("c","J/psi->mu mu Distributions", 0,0,800,600);
// Plot the fit results
RooPlot* plot = mass.frame(Range(8.0,12.0),Bins(nbins));
// Plot 1
dataB->plotOn(plot, MarkerColor(kRed));
data->plotOn(plot);
model.plotOn(plot);
//model.paramOn(plot, Format(plotOpt, AutoPrecision(1)), Parameters(RooArgSet(nsig, nbkg, m0, sigma)));
model.paramOn(plot, Format(plotOpt, AutoPrecision(1)), Parameters(RooArgSet(m0, sigma)));
/// model.plotOn(plot, Components("signal"), LineStyle(kDashed), LineColor(kRed));
model.plotOn(plot, Components("bg"), LineStyle(kDashed), LineColor(kRed));
plot->Draw();
TLatex * tex = new TLatex(0.2,0.8,"CMS preliminary");
tex->SetTextFont(42);
tex->SetNDC();
tex->SetLineWidth(2);
tex->Draw();
tex->DrawLatex(0.2, 0.725, "#sqrt{s} = 7 TeV");
tex->DrawLatex(0.2, 0.650, "L = 186 nb^{-1}");
float fsig_peak = NormalizedIntegral(signal,
mass,
m0.getVal() - 2.5*sigma.getVal(),
m0.getVal() + 2.5*sigma.getVal()
);
float fbkg_peak = NormalizedIntegral(bg,
mass,
m0.getVal() - 2.5*sigma.getVal(),
m0.getVal() + 2.5*sigma.getVal()
);
double nsigVal = fsig_peak * nsig.getVal();
double nsigErr = fsig_peak * nsig.getError();
double nsigErrRel = nsigErr / nsigVal;
double nbkgVal = fbkg_peak * nbkg.getVal();
double nbkgErr = fbkg_peak * nbkg.getError();
double nbkgErrRel = nbkgErr / nbkgVal;
cout << "nsig " << nsigVal << " +/- " << nsigErr << endl;
cout << "S/B_{#pm2.5#sigma} " << nsigVal/nbkgVal << " +/- "
<< (nsigVal/nbkgVal)*sqrt(nsigErrRel*nsigErrRel + nbkgErrRel*nbkgErrRel)
<< endl;
tex->DrawLatex(0.2, 0.5, Form("N_{S} = %.0f#pm%.0f", nsigVal, nsigErr) );
tex->DrawLatex(0.2, 0.425, Form("S/B_{#pm2.5#sigma} = %.1f", nsigVal/nbkgVal) );
tex->DrawLatex(0.2, 0.35, Form("#frac{S}{#sqrt{B}}_{#pm2.5#sigma} = %.1f", nsigVal/sqrt(nbkgVal)));
leg = new TLegend(0.65,0.6,0.9,0.75);
leg->SetFillColor(kWhite);
leg->SetLineColor(kWhite);
leg->SetShadowColor(kWhite);
leg->SetTextFont(42);
TLegendEntry * ldata = leg->AddEntry(data, "Opposite Sign");
TLegendEntry * ldataB = leg->AddEntry(dataB, "Same Sign");
ldata->SetMarkerStyle(20);
ldataB->SetMarkerStyle(20);
ldataB->SetMarkerColor(kRed);
leg->Draw();
}
