Package org.ddogleg.optimization.derivative

Class NumericalGradientForward

java.lang.Object

org.ddogleg.optimization.derivative.NumericalGradientForward

All Implemented Interfaces:

FunctionNtoN

public class NumericalGradientForward
extends Object
implements FunctionNtoN

Finite difference numerical gradient calculation using forward equation. Forward difference equation, f'(x) = f(x+h)-f(x)/h. Scaling is taken in account by h based upon the magnitude of the elements in variable x.

NOTE: If multiple input parameters are modified by the function when a single one is changed numerical derivatives aren't reliable.

Constructor Summary

Constructors

Constructor	Description
NumericalGradientForward(FunctionNtoS function)
NumericalGradientForward(FunctionNtoS function, double differenceScale)

Method Summary

Modifier and Type	Method	Description
int	getN()	Returns the number of inputs and outputs for this function.
void	process(double[] input, double[] output)	Processes the function.

Methods inherited from class java.lang.Object

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

Constructor Details

NumericalGradientForward

public NumericalGradientForward(FunctionNtoS function,
 double differenceScale)

NumericalGradientForward

public NumericalGradientForward(FunctionNtoS function)

Method Details

getN

public int getN()

Description copied from interface: FunctionNtoN

Returns the number of inputs and outputs for this function.

Specified by:

getN in interface FunctionNtoN

process

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

Description copied from interface: FunctionNtoN

Processes the function.

Specified by:

process in interface FunctionNtoN

Parameters:

input - Array with the inputs of length N. Not modified.

output - Array for storing the output of length N. Modified.