void test_random()

{
  using namespace RooFit;


  //------------reading the roofit result to extract covariance matrix-------------//
  TFile *f = new TFile("sigf_SM.root","READ");
  RooFitResult *r = (RooFitResult*)f->Get("sigf");
  r->Print();

  //--------covariance matrix-----------------//
  const TMatrixDSym &cov = r->covarianceMatrix();
  //  cov.Print();

  //---------------declaring the random numbers-------//
  TRandom3 *rnd[12];

  for(int i=0;i<12;i++)
    {
      rnd[i] = new TRandom3();
    }

  double  mean[12] = {0.679,0.1313,0.94125,0.4988,13.097,9.3146,2.2049,0.83226,18.973,7.268,2.2058,5.2193};

  double  sigma[12] ;

  int sel_indx[12] = {0,1,2,3,10,11,12,13,15,16,17,18};
  
  for(int i=0;i<12;i++)
    {
      sigma[i] = sqrt(cov(sel_indx[i],sel_indx[i]));
    }


  //---------covariance matrix for the 12 parameters---------//
   TArrayD cov_l1(144);
   TMatrixDSym cov_l1m(12,12); //matrix to store the reduced covariance matrix
   int fill_indx=0;
   for(int i=0;i<12;i++)
     {
       for(int j=0;j<12;j++)
	 {
	   //cout<<cov(i,i)<<endl;                                                                                                                    
	   cov_l1[fill_indx] = cov(sel_indx[i],sel_indx[j]);
	   //      cout<<cov1[fill_indx]<<endl;                                                                                                       
	   fill_indx++;
	 }       
     }
   cov_l1m.SetMatrixArray(cov_l1.GetArray());



   
   //---------
  TMatrixD randx(12,1); // matrix to store the uncorrelated random numbers sampled from gaussian
  TArrayD randxa(12);

  //-----  generating uncorrelated random numbers---------//
   for (int i = 0; i < 12; i++)
     {
      randxa[i] = rnd[i]->Gaus(mean[i],sigma[i]);
     }
   randx.SetMatrixArray(randxa.GetArray());


   //----------applying the cholesky decomposition-------
   TDecompChol rd(cov_l1m);  
   //   TMatrixD randy = rd*randx; // randy is to store the correlated random  numbers

   
}