[Insight-developers] itkInitializationBiasedParticleSwarmOptimizerTest: intermittent failures

[Bill Lorensen]

Ziv,

It should stay as a unit test. Perhaps the test can provide a fixed
seed. If we have to, we can experiment to get the test to pass on all
platforms.

Bill

On Sun, Sep 18, 2011 at 3:27 PM, Yaniv, Ziv
<ZYaniv at childrensnational.org> wrote:
>
>
> --
> Ziv Yaniv, PhD.,
> Principal Investigator,
> The Sheikh Zayed Institute for Pediatric Surgical Innovation
> Children's National Medical Center
> 6th Floor Main Hospital, Room M7740
> 111 Michigan Ave., N.W
> Washington, D.C 20010
> Phone: 202-476-1288
> email: zyaniv at childrensnational.org
>
> Hi Bill,
>
> This is not a bug but a feature (excuses, excuses). The theory of this
> heuristic family of algorithms does not guarantee convergence to a local
> optimum. The method's claim to fame is as an efficient approach to searching
> the parameter space.
> Most often a standard optimizer is run afterwards to ensure that the end
> result is indeed a local optimum. The problem is with the way I designed the
> tests and not the algorithm. I don't have a good idea of how to design a
> better unit test for this optimizer. If I run a standard algorithm
> afterwards it is a combined test for two optimizers. Does this seem like a
> valid approach to you?
>
>           thanks
>              Ziv
>
>
> -----Original Message-----
> From: Bill Lorensen [mailto:bill.lorensen at gmail.com]
> Sent: Sun 9/18/2011 2:57 PM
> To: Yaniv, Ziv
> Cc: Insight Developers
> Subject: itkInitializationBiasedParticleSwarmOptimizerTest: intermittent
> failures
>
> Ziv,
>
> The subject test is having intermittent failures. I realize that the test
> use random numbers for initialization, but the failure indicates that even
> though the convergence criterion is met, the results does not pass a
> tolerance test. This may indicate a bug in selecting the parameters after
> convergence.
>
> Bill
>
>