using namespace RooFit;

void LandauConvGauss()
{

// Observable 
RooRealVar t("t","t",-10,30) ; 
 
// Theoretical model 
RooRealVar ml("ml","mean landau",2., 1., 5.) ; 
RooRealVar sl("sl","sigma landau",1, 0.1, 0.5) ; 
RooLandau landau("lx","lx",t,ml,sl) ; 
 
// Detector response function 
RooRealVar mg("mg","mg",0) ; 
RooRealVar sg("sg","sg",2) ; 
RooGaussian gauss("gauss","gauss",t,mg,sg) ; 
 
 
 TCanvas * c1 = new TCanvas("c1", "c1");
 TCanvas * c2 = new TCanvas("c2", "c2");
// Define sampling frequency 
t.setBins(500) ; 

c1->cd();
 
// Construct convolution 
RooNumConvPdf model("model", "Landau convolved with a Gaussian", t, landau,gauss);
RooPlot * frame = t.frame(Title("landau (x) gauss convolution"));
model.plotOn(frame);
landau.plotOn(frame, LineStyle(kDashed));
frame->Draw();


c2->cd();
//RooFFTConvPdf model("model","landau (X) gauss",t,landau,gauss) ; 
// Sample 1000 events in t from model 
//RooDataSet* data = model.generate(t,1000) ; 
RooDataSet* data = model.generate(t,10000) ; 
 
 t.setBins(50);
// Fit model to data 
model.fitTo(*data) ; 
 
// Plot data, fitted p.d.f 
RooPlot* frame = t.frame(Title("Sample from Convolved PDF")) ; 
data->plotOn(frame) ; 
model.plotOn(frame) ; 
landau.plotOn(frame,LineStyle(kDashed)) ; 
frame->Draw();


}