using namespace RooFit;

void GaussFlat()
{
  RooRealVar x("x", "x", -10, 10);
  RooRealVar mean("mean", "mean of Gaussian", 5., -10, 10);
  RooRealVar sigma("sigma", "width of Gaussian", 3, -10, 10);

  RooGaussian gauss("gauss", "Gaussian PDF", x, mean, sigma);


  TCanvas * c1 = new TCanvas("c1", "Curva Gaussiana");
  TCanvas * c2 = new TCanvas("c2", "Flat");
  TCanvas * c3 = new TCanvas("c3", "Gaussiana+Flat");
  TCanvas * c4 = new TCanvas("c4", "Dati-model Fit");
 
  //Generate a toy MC sample
  RooDataSet * data = gauss.generate(x, 10000);


  c1->cd();
  RooPlot * xframe = x.frame(Title("MC Gaussian data"));
  data->plotOn (xframe);
  xframe->Draw();

  RooRealVar coeff1("coeff1", "Line coefficient 1", 0);
  RooPolynomial flat("flat", "flat", x, coeff1);

  
  RooDataSet * data1 = flat.generate(x, 10000);
  
  c2->cd();
  RooPlot * xframe = x.frame(Title("MC flat data"));
  data1-> plotOn (xframe);
  xframe->Draw();


  RooRealVar f("f","fraction", 0.3, 0.0, 1.0);
  RooAddPdf sum ("sum", "", RooArgList(gauss, flat), RooArgList(f));
  
  RooDataSet * data2 = sum.generate(x,10000);
  
  c3-> cd();
  RooPlot * xframe = x.frame(Title("Gauss _flat MC data"));
  data2->plotOn(xframe);
  xframe-> Draw();

  //ML fit of gauss to data
  c4->cd();
  sum.fitTo(*data2);
  mean.Print();
  sigma.Print();


  RooPlot * xframe = x.frame(Title("Fit to MC data (Gauss+Flat)"));
   data2->plotOn(xframe, Name("myHist"));
   sum.plotOn(xframe, Name("myCurve"));
   gauss.paramOn(xframe);
   xframe->Draw();
 
  Double_t chi2 = xframe->chiSquare("myCurve", "myHist");
  cout<< "chi2 = " <<chi2 << endl;
}