void plot2(RooRealVar *mass, RooAbsPdf *pdf, RooAbsPdf *pdf1, RooAbsPdf *pdf2, float frac, RooDataSet *data, string name, int bins, int mhLow, int mhHigh){
RooPlot *plot = mass->frame();
mass->setRange("unblindReg_1",85,95);
mass->setRange("unblindReg_2",110,120);
if (BLIND) {
data->plotOn(plot,Binning(bins),CutRange("unblindReg_1"));
data->plotOn(plot,Binning(bins),CutRange("unblindReg_2"));
data->plotOn(plot,Binning(bins),Invisible());
}
else data->plotOn(plot,Binning(bins));
TCanvas *canv = new TCanvas();
pdf->plotOn(plot);
pdf->plotOn(plot,Components(*pdf1),LineColor(kRed),LineStyle(2)) ;
pdf->plotOn(plot,Components(*pdf2),LineColor(kGreen),LineStyle(2)) ;
//,RooFit::NormRange("fitdata_1,fitdata_2"));
//pdf->paramOn(plot,RooFit::Layout(0.35,0.89,0.89),RooFit::Format("NEA",AutoPrecision(1)));
//plot->getAttText()->SetTextSize(0.01);
//plot->SetMaximum(plot->GetMaximum()*2);
if (BLIND) plot->SetMinimum(0.0001);
plot->SetTitle("");
plot->SetYTitle(Form("Events / %.2fGeV",float(mhHigh-mhLow)/float(bins)));
//plot->GetYaxis()->SetLabelSize(0.05);
plot->SetTitleSize(0.045, "Y");
plot->SetTitleOffset(1.,"Y");
//plot->GetXaxis()->SetLabelSize(0.15);
//plot->GetYaxis()->SetLabelSize(0.15);
plot->SetXTitle("m_{#gamma#gamma}(GeV)");
plot->SetTitleSize(0.15, "X");
plot->Draw();
TLatex *lat = new TLatex();
lat->SetNDC();
lat->SetTextFont(42);
lat->DrawLatex(0.68,0.93,"19.7fb^{-1}(8TeV)");
lat->DrawLatex(0.12,0.85,"CMS Preliminary");
lat->DrawLatex(0.7,0.7,Form("Frac = %.3f",frac));
string nameTemp = name;
int catNum = nameTemp.find("cat");
string catNameOLD = nameTemp.replace(0, catNum, "");
string catName = catNameOLD.replace(catNameOLD.length()-4, 4, "");
lat->DrawLatex(0.1,0.92, Form("%s", catName.c_str()));
TLegend *leg = new TLegend(0.12,0.7,0.32,0.8);
leg->SetFillColor(0);
leg->SetLineColor(1);
leg->AddEntry(data,"Data","lep");
leg->Draw("same");
canv->SaveAs(Form("%s.png",name.c_str()));
canv->SaveAs(Form("%s.pdf",name.c_str()));
delete canv;
delete lat;
}
void crossfeeds_nondiag(TString title,
TString bkgfile,
TString epsfile,
TString txtfile,
Double_t alpha_,
Double_t mass_,
Double_t n_,
Double_t sigma_
)
{
RooRealVar mbc("mbc", "m_{BC}", 1.83, 1.89, "GeV");
RooRealVar ebeam("ebeam", "Ebeam", 0., 100., "GeV");
RooRealVar chg("chg", "Charge", -2, 2);
RooCategory passed("passed", "Event should be used for plot");
passed.defineType("yes", 1);
passed.defineType("no", 0);
RooRealVar arg_cutoff ("arg_cutoff", "Argus cutoff", 1.8865, 1.885, 1.8875,"GeV");
RooRealVar arg_slope ("arg_slope", "Argus slope", -13, -100, 40);
RooRealVar mbc_float ("mbc_float", "Floating D mass", mass_, "GeV");
RooRealVar sigma ("sigma", "CB width", sigma_, "GeV");
RooRealVar alpha("alpha", "CB shape cutoff", alpha_);
RooRealVar n("n", "CB tail parameter", n_);
RooCBShape cb_float ("cb_float", "Floating Crystal Barrel", mbc, mbc_float, sigma, alpha, n);
RooArgusBG argus("argus", "Argus BG", mbc, arg_cutoff, arg_slope);
RooRealVar yld("yield", "D yield", 0, -30, 100000);
RooRealVar bkg("bkg", "Background", 20, 0, 40000);
// Build pdf
RooAddPdf sumpdf_float("sumpdf_float", "Generic D sum pdf", RooArgList(cb_float, argus),
RooArgList(yld, bkg));
RooDataSet* dset = RooDataSet::read(bkgfile, RooArgList(mbc, ebeam, passed), "", "");
RooPlot* xframe = mbc.frame();
RooDataSet* dset2 = dset->reduce("passed==1");
dset2->plotOn(xframe);
// RooFitResult* rv = sumpdf_float.fitTo(*dset2, Extended(kTRUE), Save(kTRUE),
// Hesse(kTRUE), Verbose(kTRUE));
RooFitResult* rv = sumpdf_float.fitTo(*dset2, "ermh");
sumpdf_float.paramOn(xframe, dset2);
if ((yld.getVal() < 0) && (-yld.getVal()/bkg.getVal() > 0.5)){
yld.setVal(0);
bkg.setVal(1);
}
sumpdf_float.plotOn(xframe);
sumpdf_float.plotOn(xframe, Components(RooArgSet(argus)),
LineColor(kRed), LineStyle(kDashed));
TCanvas* c1 = new TCanvas("c1","Canvas", 2);
xframe->SetTitleOffset(2.2, "Y");
xframe->SetTitleOffset(1.1, "X");
xframe->SetTitle(title);
c1->SetLeftMargin(0.17);
xframe->Draw();
if ( rv && rv->covQual() != 3){
// fit has failed
TText *txt = new TText();
txt->SetTextSize(.08);
txt->SetTextAlign(22);
txt->SetTextAngle(30);
txt->DrawTextNDC(0.5, 0.5, "FAILED");
}
c1->Update();
c1->Print(epsfile);
c1->Clear();
FILE* table = fopen(txtfile.Data(), "w+");
fprintf(table, "Name\t|| Value\t|| Error\n");
// fprintf(table, "yldsigma\t| %.10f\t| \n", yld.getVal()/yld.getError());
fprintf(table, "entries\t| %.10f\t| \n", dset->numEntries());
fprintf(table, "yld\t| %.10f\t| %.10f\n", yld.getVal(), yld.getError());
// fprintf(table, "ratio\t| %.10f\t| \n", yld.getVal()/dset->numEntries());
// fprintf(table, "ratioerr\t| %.10f\t| \n", yld.getError()/dset->numEntries());
fclose(table);
cout << "Saved output as: " << txtfile << endl;
rv->Delete();
}
int main(){
RooRealVar zero("zero","",0,0,150);
//input parameters for the distribution
double alpha_double = 2.38;
double beta_double = 0.092;
double lambda_double = 2.21;
double theta_double = 1.12;
double c_frac = 0.5;
//RooRealVar fsig("fsig","signal fraction",0.3) ;
string epsname = "plots/gamma_pion20";
hit_info multi_shower("fullsim/example_pi20Gev.root");
//hit_info multi_shower("fullsim/example_ele_20GeV.root");
double beta_gflash_factor = 1.49;
double theta_gflash_factor = 16.42;
beta_double = beta_double/beta_gflash_factor;
theta_double = theta_double/theta_gflash_factor;
// --- Observable ---
RooRealVar depth("depth","depth [cm]",0,800);
depth.removeMax(); // set infinite range
// --- Weight ---
RooRealVar* weight = new RooRealVar("weight","1/E dE/dr", 0.0, 1.0);
// --- Gamma pdf ---
//if one of the Values is set to const you can not ask for it in RooFitModel, otherwise the program will crash
//RooRealVar alpha("alpha","alpha",alpha_double,0.0,4);
RooRealVar alpha("alpha","alpha",0.0,20.);
//alpha.removeMax(); // set infinite range
//RooRealVar beta("beta","beta",1./beta_double,0.0,100.);
RooRealVar beta("beta","beta",0.1,.1,3.5);
//beta.removeMax(); // set infinite range
RooRealVar mu("mu","mu",0); // no ranges means variable is fixed in fit
RooRealVar nu("nu","nu",0); // no ranges means variable is fixed in fit
//RooRealVar lambda("lambda","lambda",lambda_double,0.0,6.);
RooRealVar lambda("lambda","lambda",0.0,40.);
//lambda.removeMax(); // set infinite range
//RooRealVar theta("theta","theta",1./theta_double,0.0,100.) ;
RooRealVar theta("theta","theta",1.,47) ;
//theta.removeMax(); // set infinite range
RooGamma gamma_one("gamma_one","gamma_one pdf",depth,alpha,beta,mu) ;
RooGamma gamma_two("gamma_two","gamma_two pdf",depth,lambda,theta,nu) ;
RooRealVar fsig("fsig","signal fraction",c_frac,0.0,1.);
//RooRealVar fsig("fsig","signal fraction",c_frac);
RooAddPdf model("model","model",RooArgList(gamma_two,gamma_one),fsig) ;
RooDataSet mean("mean","mean",RooArgSet(depth,weight),"weight");
TH1F* mean_fithist = new TH1F("mean_fithist"," mean fit hist",50,0,150);
TH1F* log_alpha1 = new TH1F("log_alpha1"," log(#alpha_{1})",20,-1,3);
TH1F* log_beta1 = new TH1F("log_beta1"," log(#beta_{1})",20,-1,3);
TH2F* log_corr1 = new TH2F("log_corr1"," correlation #alpha_{1} #beta_{1}",20,-1,3,20,-1,3);
TH1F* log_alpha2 = new TH1F("log_alpha2"," log(#alpha_{2})",20,-1,3);
TH1F* log_beta2 = new TH1F("log_beta2"," log(#beta_{2})",20,-1,3);
TH2F* log_corr2 = new TH2F("log_corr2"," correlation #alpha_{2} #beta_{2}",20,-1,3,20,-1,3);
TH2F* mean_hist = new TH2F("mean_hist"," mean hist",100,0,150,100.,0.,.0015);
TCanvas * can = new TCanvas("can", "can", 600, 500);
can->cd();
set_style();
//can->Print(epsname+"[");
double c_tot =0;
unsigned int n_part =100;
for(unsigned int p = 0; p<n_part ; ++p){
TLegend * legend = new TLegend(0.5,0.65,.88,0.88);
legend->SetTextFont(72);
legend->SetTextSize(0.04);
legend->SetFillColor(kWhite);
legend->SetBorderSize(0);
one_shower shower = multi_shower.all_shower.at(p);
//DataSet I am looking at
RooDataSet full_sim_data("full_sim_data","full_sim_data",RooArgSet(depth,weight),"weight");
TH1F* datahisto = new TH1F("datahist","datahist",15,0,120);
double sumHCAL=0;
double deltar =-1;
for(unsigned int i = 0; i < shower.mytype.size(); ++i){
sumHCAL += shower.myenergy.at(i);
double x_val = shower.myz.at(i);
double y_val = shower.myy.at(i);
double z_val = shower.myz.at(i);
z_val = z_val - shower.interactPoint;
double distance=-1;
if(sqrt(x_val*x_val+y_val*y_val+z_val*z_val)/10 < 200) distance = sqrt(x_val*x_val+y_val*y_val+z_val*z_val)/10;
if(deltar < distance) deltar = z_val;
}
deltar=deltar/shower.mytype.size();
c_tot += shower.ePi0first_energy/n_part;
fsig.setVal(shower.ePi0first_energy);
fsig.setRange(shower.ePi0first_energy-0.05 > 0 ? shower.ePi0first_energy-0.05: 0,shower.ePi0first_energy+0.05<1?shower.ePi0first_energy+0.05:1);
//fsig.setRange(1-shower.ePi0first_energy-0.05 > 0 ? 1-shower.ePi0first_energy-0.05: 0,1-shower.ePi0first_energy+0.05<1 ? 1-shower.ePi0first_energy+0.05:1);
for(unsigned int i = 0; i < shower.mytype.size(); ++i){
double x_val = shower.myx.at(i);
double y_val = shower.myy.at(i);
double z_val = shower.myz.at(i);
// if(shower.mytype.at(i) !=2)continue;
z_val = z_val - shower.interactPoint;
//if(z_val<=0) continue;
depth.setVal(sqrt(x_val*x_val+y_val*y_val+z_val*z_val)/10);
//depth.setVal(z_val);
//cout <<depth.getVal()<<endl;
datahisto->Fill(depth.getVal(),shower.myenergy.at(i)/sumHCAL/deltar);
mean_fithist->Fill(depth.getVal(),shower.myenergy.at(i)/sumHCAL/deltar/n_part);
mean_hist->Fill(depth.getVal(),shower.myenergy.at(i)/sumHCAL/deltar);
full_sim_data.add(depth,shower.myenergy.at(i)/sumHCAL/deltar,0);
mean.add(depth,shower.myenergy.at(i)/sumHCAL/deltar,0);
}
RooDataHist roodatahist("roodatahist","roodatahist",depth,Import(*datahisto)) ;
//model.fitTo(roodatahist, Strategy(2) );
model.fitTo(full_sim_data);
RooDataHist* full_sim_binned = full_sim_data.binnedClone("full_sim_binned","full sim binned");
//prepare to plot fits
RooPlot * depthFrame = depth.frame(0,120,100);
depthFrame->SetTitle("");
depthFrame->SetTitleOffset(1.2,"Y");
depthFrame->SetLabelSize(0.02,"Y");
depthFrame->SetYTitle("1/E dE/dr");
//zero.plotOn(depthFrame,LineStyle(kDashed),LineColor(kBlack));
//full_sim_data.plotOn(depthFrame);
roodatahist.plotOn(depthFrame);
//full_sim_binned->plotOn(depthFrame);
model.plotOn(depthFrame,Components(gamma_one),LineStyle(kDashed),LineColor(kGreen),Name("gamma_one"));
model.plotOn(depthFrame,Components(gamma_two),LineStyle(kDashed),LineColor(kRed),Name("gamma_two"));
model.plotOn(depthFrame,Name("model"));
stringstream gamma_one_text;
gamma_one_text.precision(3);
gamma_one_text << "#Gamma_{1} ("<<alpha.getVal()<<","<<(1/beta.getVal()*beta_gflash_factor)<<")"<<endl;
stringstream gamma_two_text;
gamma_two_text.precision(3);
gamma_two_text << "#Gamma_{2} (" <<lambda.getVal()<<","<<(1/theta.getVal()*theta_gflash_factor)<< ")"<<endl;
stringstream gamma_text;
gamma_text.precision(2);
gamma_text << "#Gamma_{1/2} c=" <<fsig.getVal() <<"("<<shower.ePi0first_energy<<")"<<endl;
stringstream chi2;
chi2.precision(2);
chi2 << "#chi^{2} prob. = " << TMath::Prob(depthFrame->chiSquare(),14) <<endl;
legend->AddEntry(depthFrame->findObject("gamma_one"),gamma_one_text.str().c_str(),"L");
legend->AddEntry(depthFrame->findObject("gamma_two"),gamma_two_text.str().c_str(),"L");
legend->AddEntry(depthFrame->findObject("model"),gamma_text.str().c_str(),"L");
legend->AddEntry((TObject*)0, chi2.str().c_str(), "");
cout << "alpha, beta "<< alpha.getVal() << " " << 1/beta.getVal()*beta_gflash_factor << std::endl;
cout << "lambda, theta "<<lambda.getVal() << " " << 1/theta.getVal()*theta_gflash_factor << std::endl;
cout <<"c, chi2 "<< fsig.getVal() << " "<<depthFrame->chiSquare()<< std::endl;
cout <<"starting , interacting Points "<<shower.startingPoint<<" "<<shower.interactPoint <<endl;
cout<< "pi0first, pi0tot "<<shower.ePi0first_energy <<" "<<shower.ePi0tot_energy<<endl;
/*
log_alpha1->Fill(log10(alpha.getVal()));
log_alpha2->Fill(log10(lambda.getVal()));
//cout<<log(1/beta.getVal()*beta_gflash_factor)<<endl;
log_beta1 ->Fill(log10(1/beta.getVal()*beta_gflash_factor));
log_beta2 ->Fill(log10(1/theta.getVal()*theta_gflash_factor));
log_corr1 ->Fill(log10(alpha.getVal()),log10(1/beta.getVal()*beta_gflash_factor));
log_corr2 ->Fill(log10(lambda.getVal()),log10(1/theta.getVal()*theta_gflash_factor));
*/
if(fsig.getVal()>0.1)log_alpha1->Fill(log(alpha.getVal()));
if(fsig.getVal()<0.9)log_alpha2->Fill(log(lambda.getVal()));
//cout<<log(1/beta.getVal()*beta_gflash_factor)<<endl;
if(fsig.getVal()>0.1)log_beta1 ->Fill(log(1/beta.getVal()*beta_gflash_factor));
if(fsig.getVal()<0.9)log_beta2 ->Fill(log(1/theta.getVal()*theta_gflash_factor));
if(fsig.getVal()>0.1)log_corr1 ->Fill(log(alpha.getVal()),log(1/beta.getVal()*beta_gflash_factor));
if(fsig.getVal()<0.9)log_corr2 ->Fill(log(lambda.getVal()),log(1/theta.getVal()*theta_gflash_factor));
//prepare to dump all the plots in the ps file
// one data sample and its fit is drawn
/*
datahisto->Draw();
datahisto0->SetLineColor(kRed);
datahisto0->Draw("same");
datahisto1->SetLineColor(kGreen);
datahisto1->Draw("same");
datahisto2->SetLineColor(kBlue);
datahisto2->Draw("same");
can->Print(epsname);
*/
//if(depthFrame->chiSquare()>5) continue;
depthFrame->Draw("HIST p");
legend->Draw();
stringstream particle_number;
particle_number.precision(1);
particle_number << p <<endl;
can->Print((epsname+"_"+particle_number.str()+".pdf").c_str());
}
RooDataHist roomeandatahist("roomeandatahist","roomeandatahist",depth,Import(*mean_fithist)) ;
fsig.setVal(c_tot);
alpha.removeMax(); // set infinite range
beta.removeMax(); // set infinite range
lambda.removeMax(); // set infinite range
theta.removeMax(); // set infinite range
//model.fitTo(roomeandatahist);
//model.fitTo(mean,SumW2Error(kTRUE));
TLegend * mean_legend = new TLegend(0.5,0.65,.9,0.9);
mean_legend->SetTextFont(72);
mean_legend->SetTextSize(0.04);
mean_legend->SetFillColor(kWhite);
mean_legend->SetBorderSize(0);
stringstream mean_gamma_one_text;
mean_gamma_one_text.precision(3);
mean_gamma_one_text << "#Gamma_{1} ("<<alpha.getVal()<<","<<(1/beta.getVal()*beta_gflash_factor)<<")"<<endl;
stringstream mean_gamma_two_text;
mean_gamma_two_text.precision(3);
mean_gamma_two_text << "#Gamma_{2} (" <<lambda.getVal()<<","<<(1/theta.getVal()*theta_gflash_factor)<< ")"<<endl;
stringstream mean_gamma_text;
mean_gamma_text.precision(2);
mean_gamma_text << "#Gamma_{1/2} c=" <<fsig.getVal() <<"("<< c_tot<<")"<<endl;
stringstream mean_chi2;
mean_chi2.precision(2);
//mean_chi2 << "#chi^{2} " <<depthFrame->chiSquare() <<endl;
RooPlot * meanFrame = depth.frame(0,120,200);
//meanFrame->SetMaximum(1);
meanFrame->SetTitle("Mean Fit");
meanFrame->SetYTitle("1/E dE/dr");
model.plotOn(meanFrame,Components(gamma_one),LineStyle(kDashed),LineColor(kGreen),Name("gamma_one"));
model.plotOn(meanFrame,Components(gamma_two),LineStyle(kDashed),LineColor(kRed),Name("gamma_two"));
model.plotOn(meanFrame,Name("model"));
//mean.plotOn(meanFrame);
//roomeandatahist.plotOn(meanFrame);
mean_legend->AddEntry(meanFrame->findObject("gamma_one"),mean_gamma_one_text.str().c_str(),"L");
mean_legend->AddEntry(meanFrame->findObject("gamma_two"),mean_gamma_two_text.str().c_str(),"L");
mean_legend->AddEntry(meanFrame->findObject("model"),mean_gamma_text.str().c_str(),"L");
meanFrame->Draw();
mean_legend->Draw();
//datahisto->Draw();
//can->Print(epsname);
//mean_hist->Draw("box");
//can->Print(epsname);
can->Print((epsname+"_mean.pdf").c_str());
log_alpha1->Draw();
can->Print((epsname+"_alpha1_log.pdf").c_str());
log_beta1->Draw();
can->Print((epsname+"_beta1_log.pdf").c_str());
log_corr1->Draw("colz");
can->Print((epsname+"corr1_log.pdf").c_str());
log_alpha2->Draw();
can->Print((epsname+"apha2_log.pdf").c_str());
log_beta2->Draw();
can->Print((epsname+"beta2_log.pdf").c_str());
log_corr2->Draw("colz");
can->Print((epsname+"corr2_log.pdf").c_str());
///can->Print(epsname+"]");
return 0;
}
void testChebychev()
{
TCanvas* cnv = new TCanvas("cnv","",800,600);
Int_t xNbins = (Int_t)((xFullMax-xFullMin)/xBinSize);
RooRealVar* x = new RooRealVar("x","x [units]",xFullMin,xFullMax);
x->setBins(xNbins);
x->setRange("range_x", xFullMin,xFullMax);
x->setRange("range_left", xFullMin,xBlindMin);
x->setRange("range_right", xBlindMax,xFullMax);
x->setRange("range_blind", xBlindMin,xBlindMax);
x->setRange("range_signal", xSignalmin,xSignalmax);
TString fitrange = "range_left,range_right"; // "range_x"
// RooRealVar* a0 = new RooRealVar("a0","a0", -1.42803e-01, -1.0, 1.0);
// RooRealVar* a1 = new RooRealVar("a1","a1", +2.87161e-02, -1.0, 1.0);
// RooRealVar* a2 = new RooRealVar("a2","a2", -1.45196e-03, -1.0, 1.0);
// RooRealVar* a3 = new RooRealVar("a3","a3", -6.00993e-04, -1.0, 1.0);
RooRealVar* a0 = new RooRealVar("a0","a0", -0.3497, -1.0, 1.0);
RooRealVar* a1 = new RooRealVar("a1","a1", -0.1187, -1.0, 1.0);
RooRealVar* a2 = new RooRealVar("a2","a2", -0.0885, -1.0, 1.0);
RooRealVar* a3 = new RooRealVar("a3","a3", -0.0040, -1.0, 1.0);
RooChebychev* pdfCheb = new RooChebychev("pdfCheb","pdfCheb",*x,RooArgSet(*a0,*a1,*a2,*a3));
RooAbsData* xData = pdfCheb->generate(*x,1000,Range(fitrange));
RooRealVar* b0 = new RooRealVar("b0","b0",1.,0.,100.);
RooRealVar* b1 = new RooRealVar("b1","b1",1.,0.,100.);
RooRealVar* b2 = new RooRealVar("b2","b2",1.,0.,100.);
RooRealVar* b3 = new RooRealVar("b3","b3",1.,0.,100.);
RooRealVar* b4 = new RooRealVar("b4","b4",1.,0.,100.);
RooRealVar* b5 = new RooRealVar("b5","b5",1.,0.,100.);
RooRealVar* b6 = new RooRealVar("b6","b6",1.,0.,100.);
RooBernstein* pdfBern = new RooBernstein("pdfBern","pdfBern",*x,RooArgSet(*b0,*b1,*b2,*b3,*b4,*b5,*b6));
// RooChebychev* pdf = pdfCheb;
RooBernstein* pdf = pdfBern;
RooFitResult* fitresult = pdf->fitTo(*xData,Minos(kTRUE),Range(fitrange),Strategy(2),Save(kTRUE),Timer(kTRUE));
TString stat = gMinuit->fCstatu;
cout << "Minuit: " << stat << endl;
fitresult->Print("v");
RooPlot* xFrame = x->frame(Name("xFrame"),Title("Chebychev sideband fit test"));
xData->plotOn(xFrame,Name("x"),MarkerSize(1),Binning(xNbins));
pdf->plotOn(xFrame,LineWidth(2),LineColor(kBlue),Range(fitrange),NormRange(fitrange));
pdf->plotOn(xFrame,LineWidth(2),LineColor(kRed),LineStyle(kDashed),Range("range_blind"),NormRange(fitrange));
pdf->paramOn(xFrame,Layout(0.62,0.88,0.4), Format("NEU", AutoPrecision(3)));
xFrame->getAttText()->SetTextSize(0.03);
cnv->SetLeftMargin(0.2);
xFrame->SetTitleOffset(2,"Y");
xFrame->Draw();
cnv->SaveAs("testChebychev.pdf");
RooAbsReal* integralFull = pdf->createIntegral(*x,Range("range_x"));
RooAbsReal* integralSR = pdf->createIntegral(*x,Range("range_signal"));
RooAbsReal* integralSBleft = pdf->createIntegral(*x,Range("range_left"));
RooAbsReal* integralSBright = pdf->createIntegral(*x,Range("range_right"));
float nSB0 = integralSBleft->getVal()+integralSBright->getVal();
float nSR0 = integralSR->getVal();
float nAll = integralFull->getVal();
cout << "nAll=" << nAll << endl;
cout << "nSB0=" << nSB0 << endl;
cout << "nSR0=" << nSR0 << endl;
}
