#include "TFile.h"
#include "RooRealVar.h"
#include "RooGaussian.h"
#include "RooDataSet.h"
#include "RooExponential.h"
#include "RooProdPdf.h"
#include "TTree.h"

int main() {
  RooRealVar x("x", "x", -10, 10);
  RooRealVar y("y", "y", -10, 10);
  RooRealVar mux("mux", "average-x'", 0, -1, 1);
  RooRealVar sigmax("sigmax", "sigma-x'", 0.5, 0, 5);
  RooGaussian gaussx("gaussx","gaussian PDF x'", x, mux, sigmax);
  RooRealVar muy("muy", "average-y'", 0, -1, 1);
  RooRealVar sigmay("sigmay", "sigma-y'", 1.5, 0, 5);
  RooGaussian gaussy("gaussy","gaussian PDF y'", y, muy, sigmay);
  RooProdPdf gaussxy("gaussxy", "gaussxy", RooArgSet(gaussx, gaussy));
 
  RooRealVar lambdax("lambdax", "log-slope x", -0.1, -5., 0.);
  RooExponential expox("expox", "exponential PDF x", x, lambdax);
  RooRealVar lambday("lambday", "log-slope y", -0.1, -5., 0.);
  RooExponential expoy("expoy", "exponential PDF y", y, lambday);
  RooProdPdf expoxy("expoxy", "expoxy", RooArgSet(expox, expoy));

  TFile training("tmva-in.root", "RECREATE");

  RooDataSet * sigSample = gaussxy.generate(RooArgSet(x,y), 200000);
  RooDataSet * bkgSample = expoxy.generate(RooArgSet(x,y), 200000);
  TTree sampleTree("sampleTree","Sample tree");
  double xv, yv, isSignal;
  sampleTree.Branch("x", &xv, "x/D");
  sampleTree.Branch("y", &yv, "y/D"); 
  sampleTree.Branch("isSignal", &isSignal, "signal/D"); 
  isSignal = 1;
  for(int i = 0; i != sigSample->numEntries(); ++i) {
    const RooArgSet * tuple = sigSample->get(i);
    xv = tuple->getRealValue("x");
    yv = tuple->getRealValue("y");
    sampleTree.Fill();
  } 
  isSignal = 0;
  for(int i = 0; i != bkgSample->numEntries(); ++i) {
    const RooArgSet * tuple = bkgSample->get(i);
    xv = tuple->getRealValue("x");
    yv = tuple->getRealValue("y");
    sampleTree.Fill();
  }
  sampleTree.Write();

  training.Close();

  return 0;
}