georegression.fitting.sphere

Class SphereToPointSignedDistance_F64

java.lang.Object

georegression.fitting.sphere.SphereToPointSignedDistance_F64

All Implemented Interfaces:

FunctionNtoM

public class SphereToPointSignedDistance_F64
extends java.lang.Object
implements FunctionNtoM

Computes the signed Euclidean distance between a sphere and a set of points, see Distance3D_F64.distance(georegression.struct.shapes.Sphere3D_F64, georegression.struct.point.Point3D_F64). See CodecSphere3D_F64 for how the model is parametrized. For use in least-squares non-linear minimization.

Constructor Summary

Constructors

Constructor and Description
SphereToPointSignedDistance_F64()

Method Summary

Modifier and Type	Method and Description
int	getNumOfInputsN() Number of input elements.
int	getNumOfOutputsM() Number of output elements.
void	process(double[] input, double[] output) Processes the input to compute the values found in the output array.
void	setPoints(java.util.List<Point3D_F64> points)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SphereToPointSignedDistance_F64

public SphereToPointSignedDistance_F64()

Method Detail

setPoints

public void setPoints(java.util.List<Point3D_F64> points)

getNumOfInputsN

public int getNumOfInputsN()

Description copied from interface: FunctionNtoM

Number of input elements. Typically the parameters you are optimizing.

Specified by:

getNumOfInputsN in interface FunctionNtoM

Returns:

number of input elements

getNumOfOutputsM

public int getNumOfOutputsM()

Description copied from interface: FunctionNtoM

Number of output elements. Typically the functions that are being optimized.

Specified by:

getNumOfOutputsM in interface FunctionNtoM

Returns:

number of output elements

process

public void process(double[] input,
                    double[] output)

Description copied from interface: FunctionNtoM

Processes the input to compute the values found in the output array. The output's meaning depends on the application. For least-squares it is the residual error. See UnconstrainedLeastSquares.

The user can modify the input parameters here and the optimizer must use those changes.

Specified by:

process in interface FunctionNtoM

Parameters:

input - Parameters for input model.

output - Storage for the output give the model.