[Insight-users] understanding vnl_amoeba

[Luis Ibanez]

Hi Katya,

Yes, your expectation is correct.

The final value of the optimizer should be lower than the initial value.

Did the optimizer terminated with any error value ?

For how many iterations did the optimizer run before stoppping ?

What may be happening in your case it that the optimizer may not
have converged to a solution, and/or that it may have gone out
of the valid domain of your cost function.

In ITK, the wrapper around the vnl_amoeba optimizer allows you to
connect observers to it, so that you can track the values of the
optimizer at every iteration.

You may find useful to implement a similar monitoring mechanism
in order to debug your optimization.


     Regards,


        Luis


-------------------------
Ekaterina Syrkina wrote:
> Hello,
> 
> I'm not ITK-user, but I address my question to this list as there is a
> wrapper around the vnl_amoeba algorithm in ITK. Hope some of you may
> help me.
> 
> I'm using vnl_amoeba class for minimisation of my multidimensional
> function and observe some confusing behaviour... The result of the
> optimisation ("minimisation") is bigger than the starting value. Has
> anyone experienced similar problems?
> 
> My understanding of the Downhill Simplex Method is that we always keep
> "lowest" simplex point, so we never get function value which is worse
> than initial. Is it correct?
> 
> Thanks,
> Katya
> 
> 
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