Int_t TMinuit::Eval(Int_t &npar, Double_t *grad, Double_t &fval, Double_t *par, Int_t flag)
// Evaluate the minimisation function
//  Input parameters:
//    npar:    number of currently variable parameters
//    par:     array of (constant and variable) parameters
//    flag:    Indicates what is to be calculated (see example below)
//    grad:    array of gradients
//  Output parameters:
//    fval:    The calculated function value.
//    grad:    The (optional) vector of first derivatives).
//
// The meaning of the parameters par is of course defined by the user,
// who uses the values of those parameters to calculate his function value.
// The starting values must be specified by the user.
// Later values are determined by Minuit as it searches for the minimum
// or performs whatever analysis is requested by the user.
//
// Note that this virtual function may be redefined in a class derived from TMinuit.
// The default function calls the function specified in SetFCN
//
// Example of Minimisation function:
/*
   if (flag == 1) {
      read input data,
      calculate any necessary constants, etc.
   }
   if (flag == 2) {
      calculate GRAD, the first derivatives of FVAL
     (this is optional)
   }
   Always calculate the value of the function, FVAL,
   which is usually a chisquare or log likelihood.
   if (iflag == 3) {
      will come here only after the fit is finished.
      Perform any final calculations, output fitted data, etc.
   }
*/
//  See concrete examples in TH1::H1FitChisquare, H1FitLikelihood


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