org.ddogleg.example

Class FunctionLineDistanceEuclidean

java.lang.Object

org.ddogleg.example.FunctionLineDistanceEuclidean

All Implemented Interfaces:

FunctionNtoM

public class FunctionLineDistanceEuclidean
extends java.lang.Object
implements FunctionNtoM

Computes the distance a point is from a line in 2D. The line is defined using the tangent from origin equation.

Constructor Summary

Constructors

Constructor and Description
FunctionLineDistanceEuclidean(java.util.List<Point2D> data)

Method Summary

Modifier and Type	Method and Description
int	getNumOfInputsN() Number of parameters used to define the line.
int	getNumOfOutputsM() Number of output error functions.
void	process(double[] input, double[] output) Processes the input to compute the values found in the output array.

Methods inherited from class java.lang.Object

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

Constructor Detail

FunctionLineDistanceEuclidean

public FunctionLineDistanceEuclidean(java.util.List<Point2D> data)

Method Detail

getNumOfInputsN

public int getNumOfInputsN()

Number of parameters used to define the line.

Specified by:

getNumOfInputsN in interface FunctionNtoM

Returns:

number of input elements

getNumOfOutputsM

public int getNumOfOutputsM()

Number of output error functions. Two for each point.

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.