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

[paul.carrico at free.fr]

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

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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