To complete my previous answer, the error arose from the built-in line
search algorithm (err>10 means different flavors of it failing). In your
case, it is pointing to a "too small deltaT", so yes it looks like your
algorithm is converging but it has trouble finishing.
You can get more info by using "imp=3" in your call to optim (as
documented). If you are using a nightly build then use "iprint=3" (the
online doc hasn't been updated yet).
Best regards,
Paul
On 01/13/2017 05:11 PM, Paul Bignier wrote:
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, [email protected] 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
http://www.scilab-enterprises.com
_______________________________________________
users mailing list
[email protected]
http://lists.scilab.org/mailman/listinfo/users
--
Paul BIGNIER
Development engineer
-----------------------------------------------------------
Scilab Enterprises
143bis rue Yves Le Coz - 78000 Versailles, France
Phone: +33.1.80.77.04.68
http://www.scilab-enterprises.com
_______________________________________________
users mailing list
[email protected]
http://lists.scilab.org/mailman/listinfo/users
