[Scilab-users] Optim use and 'err' flag

[Paul Bignier]

Hello Paul,

Running your script gives me "err=12", which is not documented but I 
don't get how you got 3?

I see though that you reached 'evals' & 'iters', perhaps optim wanted to 
continue but was capped by those.

Feel free to use the format 
<https://help.scilab.org/docs/6.0.0/en_US/format.html> function to get 
more on-screen precision to your values.

I will surely commit something soon in order to fix the "12" flag.

Have a good evening,

Paul


On 01/13/2017 02:39 PM, paul.carrico at free.fr wrote:
> Hi all
>
> I’m trying to improve how to use Optim in Scilab, so I’m still using 
> the basic Rosembrock function; in the example hereafter, one can see 
> that Optim goes back the Error flag to 3 and I do not understand why?
>
> The goal is to be able to check all the values of this flag in order 
> to validate the result ; while the values are the optimized ones, the 
> calculation indicates that the optimization fails …
>
> I’m a bit loss … so any feedback will be appreciated
>
> Thanks
>
> Paul
>
> ################################################################################### 
>
> In my understanding:
> -    err = 9 : everything went well … ok
>
> -    err = 3 : Optimization stops because of too small variations for x
> -    err=1 : Norm of projected gradient lower than …
> -    err=2 : At last iteration f decreases by less than …
> -    err=4 : Optim stops: maximum number of calls to f is reached ==> 
> increase nocf
> -    err=5 : Optim stops: maximum number of iterations is reached. ==> 
> increase niter
> -    err=6 : Optim stops: too small variations in gradient direction.
> -    err=7 : Stop during calculation of descent direction.
> -    err=8 : Stop during calculation of estimated hessian.
> -    err=10 : End of optimization (linear search fails).
>
>
>
> // Rosembrock function
> function f=rosembrock(x)
>     f = ( 1 - x(1))^2 + 100*( x(2)-x(1)^2 )^2;
> endfunction
>
> // Cost function
> function [f, g, ind]=cost(x, ind)
>     f = rosembrock(x);
>     //        g = derivative(rosembrock, x.',order = 4);
> //            g = numderivative(rosembrock, x.',order = 4);
>     g = numderivative(rosembrock, x.',0.1, order = 4);
> endfunction
>
> initial_parameters = [10 100]
> lower_bounds = [0 0];
> upper_bounds = [1000 1000];
> nocf = 100000;      // number of call of f
> niter = 100000;    // number of iterations
> [fopt, xopt, gopt, work, iters, evals, err] = 
> optim(cost,'b',lower_bounds,upper_bounds,initial_parameters,'qn','ar',nocf,niter);
> xopt
> fopt
> iters
> evals
> err
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-- 
Paul BIGNIER
Development engineer
-----------------------------------------------------------
Scilab Enterprises
143bis rue Yves Le Coz - 78000 Versailles, France
Phone: +33.1.80.77.04.68
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