TMtxOptimization.GradHessProcedureEvent Event

Copyusing Dew.Math;
using Dew.Math.Units;

namespace Dew.Examples
{
    // Objective function
    double Banana(TVec pars, TVec consts, params object[] obj)
    {
        return 100.0*Math387.IntPower(pars[1]- Math387.IntPower(pars[0],2),2)
            + Math387.IntPower(1.0-pars[0],2);
    }

    // Analytical gradient of the objective function
    void GradHessBanana(TRealFunction Fun, TVec pars, TVec consts, object[] obj, TVec grad, TMtx Hess)
    {
        grad.Values[0] = -400*(pars[1]-Math387.IntPower(pars[0],2))*pars[0] - 2*(1-pars[0]);
        grad.Values[1] = 200*(pars[1]-Math387.IntPower(pars[0],2));
        Hess.Values1D[0] = -400*Pars[1]+1200*Math387.IntPower(Pars[0],2)+2;
        Hess.Values1D[1] = -400*Pars[0];
        Hess.Values1D[2] = -400*Pars[0];
        Hess.Values1D[3] = 200;
    }

    private void Example(TMtxOptimization opt)
    {
        opt.VariableParameters.SetIt(new double[] {2,-1});
        opt.RealFunction = Banana;
        opt.OptimizationMethod = TOptimizationMethod.optBFGS;
        // use exact gradient and Hessian calculation
        // NOTE : set opt.GradHessProcedure to null if you
            //        want to use internal numeric gradient calculation
        opt.GradHessProcedure = GradHessBanana;
        opt.Recalculate();
    }
}