[Insight-users] Re: Problems with understanding the parameters in the amoeba optimizer

[Arne Hansen]

Okay, i have been investigeting the matter a bit more.
It seems that it actually has an effect when i set the
optimizer->SetMaximumNumberOfIterations

It moves in intervals of 9. So if i set the MaximumNumberOfIterations = 1 it
corresponds to 17 iterations.
if i set it to 10 it corresponds to 26 and so on.
In short:
value:
1-9    : 17 iterations
 10-18 : 26 iterations
 19-27 : 35 iterations
 28-36 : 44 iterations
 37-46 : 53 iterations
etc.

I find this very odd.
I read this reply made by Luis once:

>* The Amoeba optimizer in ITK is a wrapper around the vnl
*>* amoeba optimizer. Since VNL does not send any events during
*>* the iterations of its optimizers, ITK implemented a trick in *>* the
following way:
*>*
*>*     itkAmoebaOptimizer  wraps vnl_amoeba
*>*
*>*    SingleValuedVnlCostFunctionAdaptor
*>*                         wraps vnl_cost_function
*>*
*>*
*>* vnl_amoeba calls the f() method of the vnl_cost_function,
*>* that in turn calls the GetValue() method of the ITK
*>* SingleValuedVnlCostFunctionAdaptor.
*>*
*>* The SingleValuedVnlCostFunctionAdaptor sends events that
*>* are "observed" by the itkAmoebaOptimizer and resent as
*>* iteration events.
*>*
*>* In this way, we get events *per evaluation* of the cost
*>* function. Note that this is not completely equivalent
*>* to events per iteration of the amoeba_optimizer,.... but
*>* it is better than nothing.
*>*
*>* as a rule of thumb you could expect that N evaluations of
*>* the cost_function are equivalent to one iteration of the
*>* amoeba optimizer, where N is the dimensionality of the
*>* parametric space of the cost function.
*
 So i should expect that my amount of parameters is 9. The problem is that
it is only 7, since i use the
itkSimilarity3DTransform ie. (Rx,Ry,Rz,Tx,Ty,Tz,S = 7)
So i cannot understand why the iteration count behaves like this.

Any suggestions?
*
*



2006/11/29, Arne Hansen <bsd.diverse at gmail.com>:
>
> Hello.
> I am using an amoeba optimizer to minimize overlap (itkKappaStatistic)
> between 2 binary volumes.
>
> My problem is that it seems that when i set parameters
> optimizer->SetMaximumNumberOfIterations(1);
> optimizer->SetParametersConvergenceTolerance(10);
> optimizer->SetFunctionConvergenceTolerance(10);
>
> they dont seem to have any affect at all. Even though i tell it to maximal
> do 1 iteration, it still does 17 iterations in the first layer of my
> itkMultiResolutionImageRegistrationMethod.
>
> Furthermore, as i am doing kappastatistic, the maximum function value is
> of course 1 for perfectly
> gemetric aligned images. So the function value is -1 all the time(Because
> i told the optimizer to maximize and not nminimize. But still, it does first
> convergeafter the 17 iterationss in the top pyramid. And the same for the
> rest of the pyramid.
> Here is the result from a 2-layered pyramid.......
>
>
> Iteration count : 0
>
> ///////////////////////////////////////////////////////////
>
> Pyramid level0
>
> ///////////////////////////////////////////////////////////
>
> -1:
>
> //[]
>
> [0, 0, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.00025, 0, 0, 0, 0, 0, 1]
>
> -1:
>
> [0, 0.00025, 0, 0, 0, 0, 1]
>
> -1:
>
> [0, 0, 0.00025, 0, 0, 0, 1]
>
> -1:
>
> [0, 0, 0, 0.025, 0, 0, 1]
>
> -1:
>
> [0, 0, 0, 0, 0.025, 0, 1]
>
> -1:
>
> [0, 0, 0, 0, 0, 0.025, 1]
>
> -1:
>
> [0, 0, 0, 0, 0, 0, 1.05]
>
> -1:
>
> [7.1428571429e-005, 7.1428571429e-005, 7.1428571429e-005, 0.0071428571429,
> 0.0071428571429, 0.0071428571429, 1.0142857143]
>
> -1:
>
> [1.7857142857e-005, 1.7857142857e-005, 1.7857142857e-005, 0.0017857142857,
> 0.0017857142857, 0.0017857142857, 1.0035714286]
>
> -1:
>
> [0.000125, 0.000125, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.000125, 0, 0.000125, 0, 0, 0, 1]
>
> -1:
>
> [0.000125, 0, 0, 0.0125, 0, 0, 1]
>
> -1:
>
> [0.000125, 0, 0, 0, 0.0125, 0, 1]
>
> -1:
>
> [0.000125, 0, 0, 0, 0, 0.0125, 1]
>
> -1:
>
> [0.000125, 0, 0, 0, 0, 0, 1.025]
>
> -1:
>
> [0.000125, 0, 0, 0, 0, 0, 1]
>
> Iteration count : 17
>
> ///////////////////////////////////////////////////////////
>
> Pyramid level1
>
> ///////////////////////////////////////////////////////////
>
> -1:
>
> [0.000125, 0.000125, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.00025, 0.000125, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.000125, 0.00025, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.000125, 0.000125, 0.00025, 0, 0, 0, 1]
>
> -1:
>
> [0.000125, 0.000125, 0, 0.025, 0, 0, 1]
>
> -1:
>
> [0.000125, 0.000125, 0, 0, 0.025, 0, 1]
>
> -1:
>
> [0.000125, 0.000125, 0, 0, 0, 0.025, 1]
>
> -0.97433615191:
>
> [0.000125, 0.000125, 0, 0, 0, 0, 1.05]
>
> -0.96254003621:
>
> [0.00016071428571, 0.00016071428571, 7.1428571429e-005, 0.0071428571429,
> 0.0071428571429, 0.0071428571429, 0.95]
>
> -1:
>
> [0.00013392857143, 0.00013392857143, 1.7857142857e-005, 0.0017857142857,
> 0.0017857142857, 0.0017857142857, 1.025]
>
> -1:
>
> [0.0001875, 0.0001875, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.0001875, 0.000125, 0.000125, 0, 0, 0, 1]
>
> -1:
>
> [0.0001875, 0.000125, 0, 0.0125, 0, 0, 1]
>
> -1:
>
> [0.0001875, 0.000125, 0, 0, 0.0125, 0, 1]
>
> -1:
>
> [0.0001875, 0.000125, 0, 0, 0, 0.0125, 1]
>
> -1:
>
> [0.0001875, 0.000125, 0, 0, 0, 0, 1]
>
> -1:
>
> [0.0001875, 0.000125, 0, 0, 0, 0, 1.025]
>
> ----------------------------Registration completed-------------------
>
>
>
> Result :
>
> Translation X = 0
>
> Translation Y = 0
>
> Translation Z = 0
>
> Rotation X = 0.70710678119
>
> Rotation Y = 0.70710678119
>
> Rotation Z = 0
>
> GetAngle = 0.0005303300921
>
> Offset = -0.021839980215 0.021839980215 -0.0025979353519
>
> Matrix =
>
> 0.99999992969 7.03125e-008 0.00037499998682
>
> 7.03125e-008 0.99999992969 -0.00037499998682
>
> -0.00037499998682 0.00037499998682 0.99999985938
>
> Offset =
>
> [-0.021839980215, 0.021839980215, -0.0025979353519]
>
> Culd someone help my. Than you very much
>
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