Hello,
thanks for the reply. But i wonder what is the input for value and
gradient. in DifferentiableMultivariateRealFunction this needs to be a
double array but what needs to be provided there? The parameters for the
function to optimize?
Thank you very much again
Andreas
Am 14.05.2012 10:34, schrieb Sébastien Brisard:
Hi Andreas,
My Question: Can someone show me an example for the usage of
DifferentiableMultivariateRealFunction and a matching optimizer. I
understand the concept but the implementational details are hard to find.
Here is what i understood:
value: the value of the function.
gradient(): an array containing all partial derivitivs gradients for the
parameters.
partialDerivitive: Value containing only one gradient of the function
if i provide this basic implementation i should pass this to the optimizer.
Or do i have to provide an extra target function to the optimizer as
inicated by some optinmizers with the<FUNC> operator?
The user guide [1] shows a detailed example of the use of the
Levenberg-Marquardt optimized. Also, you can have a look to the new
AbstractLeastSquaresOptimizerAbstractTest [2] (available only through
svn). The doTestStRD is another illustration.
Hope this helps,
Sébastien
[1] http://commons.apache.org/math/userguide/optimization.html
[2]
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/general/AbstractLeastSquaresOptimizerAbstractTest.java?view=markup,
line 470
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