Le 03/07/2011 14:47, jeesh a écrit :
Hi everyone,
Hi Jeesh,
I'm somewhat new to java, but I'm looking to build a least squares
optimization routine for a 2D Gaussian Fit based on this link (about half
way down) http://commons.apache.org/math/userguide/optimization.html.
Just a general question - how would I go about structuring the Jacobian
matrix for a two component function?
You can organize the rows as you want. In the quadratic example of the
user guide page you cite, the rows correspond to simply to different
measurement points. For simplicity, they have been put in x increasing
order, but they could have been put in any order. So in your case, you
could choose something like:
index 0 : (x0, y0)
index 1 : (x0, y1)
index 2 : (x0, y2)
...
index n-1: (x0, yn-1)
index n : (x1, y0)
index n+1: (x1, y1)
...
or the other way round:
index 0 : (x0, y0)
index 1 : (x1, y0)
index 2 : (x2, y0)
...
index m-1: (xm-1, y0)
index m : (x0, y1)
index m+1: (x1, y1)
...
or even a random order, and your (xi,yj) samples may even not be
regularly spaced but could be random points.
Once you have chose some ordering, you should use the same order for the
rows of the jacobian matrix and the values of the function as returned
by the respectively the jacobian method and the value method of your
DifferentiableMultivariateVectorialFunction implementation. The same
order should also be used for the target array you pass to the optimize
method of the optimizer.
best regards,
Luc
Any help would be appreciated.
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