Here is a simple example:
https://wandbox.org/permlink/fbcldo9PIiHl6tfI In your case, try
something like
auto my_lambda = [&polar](Vector<double> a, Vector<double>b) {return
polar.Callback(a,b);};
opt.solve ( my_lambda, X );
Bruno
Le lun. 28 oct. 2019 à 06:30, Juan Carlos Araujo Cabarcas
<ju4...@gmail.com> a écrit :
>
> Thanks Bruno for your prompt reply,
>
> I got the important part of the code compiling, however since I am new to
> this lambda (functional) functions, I do not know how to pass the new
> definitions to SolverBFGS.
>
> Looking at your suggestion I do the following:
>
> class Shape_compute {
> public:
> Parameters par;
>
> Shape_compute (Parameters epar):par(epar) {
> Register([=]( Vector<double> ex, Vector<double> dx ){ return
> objective_fun (ex,dx); });
> }
>
> void Register(std::function<double(Vector<double>, Vector<double>)>
> Callback) {} //fun = objective_fun;
>
> double objective_fun ( Vector<double> ex, Vector<double> dx) {
>
> vector<double> x (par.design_N), grad (par.design_N);
> for (unsigned int i=0; i < x.size (); i++) {
> x [i] = ex(i);
> }
> Adaptive::DtN_Helmholtz<2> fem (par, x, true);
> fem.run ();
> double objective_function = fem.objective_function;
>
> for (unsigned int i=0; i < par.design_N; i++) {
> if (i < par.design_N) {
> vector<double> aux = x; aux [i] += h;
> Adaptive::DtN_Helmholtz<2> fem (par, aux, false);
> fem.run ();
> grad [i] = (fem.objective_function - objective_function
> )/h;
> }
> dx(i) = grad [i];
> }
> iteration++;
> return objective_function;
> }
> };
>
>
> Then, when calling the optimization routine:
>
> Vector<double> X (N);
>
> SolverControl residual_control (N, 1e-7);
> //SolverBFGS::AdditionalData data (10, true);
>
> SolverBFGS<Vector<double> > opt (residual_control);//, data);
>
> Shape_compute polar(par);
> opt.solve ( polar.Callback, X ); // If this line is commented, it
> compiles fine!
>
>
> I would appreciate guidance on how to achieve this,
>
> Thanks in advance,
> Juan Carlos Araújo
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