Re: An issue with function signatures

[Julien Bect]

Le 21/12/2018 à 09:16, Juan Pablo Carbajal a écrit :
> Thank you for your thoughts. Unless we get another answer I see this
> as a weakness on the signature and we should discourage it in future
> function.


I agree with you.  It think that is usually better to require that user 
should provide *one* objective function :

[f_val, f_grad, f_hessian] = objfun (x)


One further argument in this direction : this is the Matlab-way ; see, e.g.,

https://fr.mathworks.com/help/optim/ug/writing-scalar-objective-functions.html

This is also the NLopt-way :

https://nlopt.readthedocs.io/en/latest/NLopt_Matlab_Reference/


Switching to this kind of signature for sqp (the only nonlinear solver 
in Octave core) would mean breaking compatibility with earlier versions 
of Octave.  @OctaveMaintainer : what is your position about this ?

In the optim package, as far as I can see, the current situation is a 
mix of both signatures.  For instance, bfgs_min uses the all-in-one 
signature, while cg_min has a separate df argument. @Olaf : can you 
comment on that ?


@++
Julien