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// LMfunc.java
// Modified by Reece Arnott 22nd December 2009 to take out grad method which is now included as a private method in the LM class.
// Also val now returns an x,y point rather than a single number
package ZS.Solve;
import org.reprap.scanning.Geometry.Point2d;
/**
* Caller implement this interface to specify the
* function to be minimized and its gradient.
*
* Optionally return an initial guess and some test data,
* though the LM.java only uses this in its optional main() test program.
* Return null if these are not needed.
*/
public interface LMfunc
{
/**
* x is a single point, but domain may be mulidimensional
*/
//double val(double[] x, double[] a);
Point2d val(double[] x, double[] a);
/***
* Adjust does any post adjustments to the y point using the parameters
* For example polynomial radial distortion estimation is based on the distance between y and the image centre and is not easily expressible in terms of x (real world point to be transformed to image coordinates)
* So to compare apples to apples you use the adjust method to undo the radial distortion of an image and use the ordinary solve to transform a world point to an undistorted image point.
*
* Note that this does not apply when talking about an invertible distortion matrix as it can be inverted and applied to the x vector
*
* If there are no adjustments to do just return y
*/
Point2d adjust(Point2d y, double[] a);
/**
* return the kth component of the gradient df(x,a)/da_k
*
* This has been taken out and replaced with a private method within LM take gives a generic partial derivative
*/
//double grad(double[] x, double[] a, int ak);
/**
* return initial guess at a[]
*/
double[] initial();
/**
* return an array[4] of x,a,y,s for a test case;
* a is the desired final answer.
*/
Object[] testdata();
} //LMfunc
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