georegression.fitting.cylinder

Class CylinderToPointSignedDistanceJacobian_F32

java.lang.Object

georegression.fitting.cylinder.CylinderToPointSignedDistanceJacobian_F32

All Implemented Interfaces:

FunctionNtoMxN

public class CylinderToPointSignedDistanceJacobian_F32
extends java.lang.Object
implements FunctionNtoMxN

Jacobian of CylinderToPointSignedDistance_F32.

Constructor Summary

Constructors

Constructor and Description
CylinderToPointSignedDistanceJacobian_F32()

Method Summary

Modifier and Type	Method and Description
int	getNumOfInputsN() Number of input parameters and columns in output matrix.
int	getNumOfOutputsM() Number of rows in output matrix.
void	process(double[] input, double[] output) Processes the input vector to output a 2D a matrix.
void	setPoints(java.util.List<Point3D_F32> points)

Methods inherited from class java.lang.Object

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

Constructor Detail

CylinderToPointSignedDistanceJacobian_F32

public CylinderToPointSignedDistanceJacobian_F32()

Method Detail

setPoints

public void setPoints(java.util.List<Point3D_F32> points)

getNumOfInputsN

public int getNumOfInputsN()

Description copied from interface: FunctionNtoMxN

Number of input parameters and columns in output matrix. Typically the parameters you are optimizing.

Specified by:

getNumOfInputsN in interface FunctionNtoMxN

Returns:

Number of input parameters

getNumOfOutputsM

public int getNumOfOutputsM()

Description copied from interface: FunctionNtoMxN

Number of rows in output matrix. Typically the functions that are being optimized.

Specified by:

getNumOfOutputsM in interface FunctionNtoMxN

Returns:

Number of rows in output matrix.

process

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

Description copied from interface: FunctionNtoMxN

Processes the input vector to output a 2D a matrix. The matrix has a dimension of M rows and N columns and is formatted as a row major 1D-array. EJML can be used to provide a matrix wrapper around the output array: DenseMatrix J = DenseMatrix.wrap(m,n,output);

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

Specified by:

process in interface FunctionNtoMxN

Parameters:

input - Vector with input parameters.

output - Row major array with M rows and N columns.