using namespace RooFit;

void rvtest(int nsgn=8000, int nbkg=40000)
{
  // Variables
  RooRealVar x("x","x",0,1);
  RooRealVar y("y","y",-1,1);

  // Build 2D bkg model
  RooRealVar bkgA("bkgA","bkgA",-.2,-1,0);
  RooExponential bkgPdfX("bkgPdfX","bkgPdfX",x,bkgA);
  RooUniform bkgPdfY("bkgPdfY","bkgPdfY",y);
  RooProdPdf bkgPdf("bkgPdf","bkgPdf",RooArgSet(bkgPdfX,bkgPdfY));

  // Build 1st signal model
  RooRealVar dmA0("dmA0","dmA0",.5,-.2,.2);
  RooRealVar dmA1("dmA1","dmA1",.2,-1,1);
  RooPolyVar meanA("meanA","meanA",y,RooArgList(dmA0,dmA1));
  RooRealVar sigmaA("sigmaA","sigmaA",.1,.05,.2);
  RooGaussian sgnPdfA("sgnPdfA","sgnPdfA",x,meanA,sigmaA);

  // Build 2nd signal model
  RooRealVar dmB0("dmB0","dmB0",.5,-.2,.2);
  RooRealVar dmB1("dmB1","dmB1",-.2,-1,1);
  RooPolyVar meanB("meanB","meanB",y,RooArgList(dmB0,dmB1));
  RooRealVar sigmaB("sigmaB","sigmaB",.08,.05,.2);
  RooGaussian sgnPdfB("sgnPdfB","sgnPdfB",x,meanB,sigmaB);

  // Define the yields
  RooRealVar bkgN("bkgN","bkgN",nbkg,.5*nbkg,1.5*nbkg);
  RooRealVar sgnAN("sgnAN","sgnAN",nsgn,.5*nsgn,1.5*nsgn);
  RooRealVar sgnBN("sgnBN","sgnBN",.9*nsgn,.9*.5*nsgn,.9*1.5*nsgn);

  // Define the fractions
  RooRealVar fracA("fracA","fracA",.20,.1,.3);
  RooRealVar fracB("fracB","fracB",.18,.1,.3);
  
  // Compose the global model
  RooAddPdf model("model","Model",
		  RooArgList(sgnPdfA,sgnPdfB,bkgPdf),
		  //RooArgSet(sgnAN,sgnBN,bkgN));
		  RooArgList(fracA,fracB));


  
  // genera dei dati *verosimili*
  RooDataSet *data = model.generate(RooArgSet(x,y),nsgn+nbkg);

  model.fitTo(*data);


  TCanvas *canvas = new TCanvas("canvas","canvas",750,250);
  canvas->Divide(3);
  canvas->cd(1);
  Info("rvtest","Plot X projection");
  RooPlot *frameX = x.frame();
  model.plotOn(frameX);
  data->plotOn(frameX);
  frameX->Draw();
  canvas->cd(2);
  Info("rvtest","Plot Y projection");
  RooPlot *frameY = y.frame();
  model.plotOn(frameY);
  data->plotOn(frameY);
  frameY->Draw();
  canvas->cd(3);
  Info("rvtest","Plot 2D projection");
  TH1 *hh_model = model.createHistogram("hh_model",x,Binning(50),
					YVar(y,Binning(50)));
  hh_model->Draw("surf");

}