org.ddogleg.optimization.impl

Class DoglegStepF

java.lang.Object

org.ddogleg.optimization.impl.DoglegStepF

All Implemented Interfaces:

TrustRegionStep

public class DoglegStepF
extends java.lang.Object
implements TrustRegionStep

Constructor Summary

Constructors

Constructor and Description
DoglegStepF() Default solver
DoglegStepF(org.ejml.interfaces.linsol.LinearSolver<org.ejml.data.DenseMatrix64F> pinv) Configure internal algorithms

Method Summary

Modifier and Type	Method and Description
void	computeStep(double regionRadius, org.ejml.data.DenseMatrix64F step) Computes the next step to take for a given trust region.
void	init(int numParam, int numFunctions) Initialize internal data structures.
boolean	isMaxStep() Was a step equal to the regionRadius taken?
double	predictedReduction() Returns the predicted reduction for the step.
void	setInputs(org.ejml.data.DenseMatrix64F x, org.ejml.data.DenseMatrix64F residuals, org.ejml.data.DenseMatrix64F J, org.ejml.data.DenseMatrix64F gradient, double fx) Specifies the state of the system being optimized.

Methods inherited from class java.lang.Object

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

Constructor Detail

DoglegStepF

public DoglegStepF(org.ejml.interfaces.linsol.LinearSolver<org.ejml.data.DenseMatrix64F> pinv)

Configure internal algorithms

Parameters:

pinv - Linear solver for least-squares problem. Needs to handle

DoglegStepF

public DoglegStepF()

Default solver

Method Detail

init

public void init(int numParam,
                 int numFunctions)

Description copied from interface: TrustRegionStep

Initialize internal data structures. Only needs to be called once.

Specified by:

init in interface TrustRegionStep

Parameters:

numParam - Number of parameters being optimizes. This is the length of 'x'

numFunctions - Number of functions. Number of outputs to f(x)

setInputs

public void setInputs(org.ejml.data.DenseMatrix64F x,
                      org.ejml.data.DenseMatrix64F residuals,
                      org.ejml.data.DenseMatrix64F J,
                      org.ejml.data.DenseMatrix64F gradient,
                      double fx)

Description copied from interface: TrustRegionStep

Specifies the state of the system being optimized. Call before TrustRegionStep.computeStep(double, org.ejml.data.DenseMatrix64F).

Specified by:

setInputs in interface TrustRegionStep

Parameters:

x - Sample point being considered.

residuals - Function output: f(x)

J - Jacobian: J(x)

gradient - Gradient: J^T(x)*f(x)

fx - Residual at x: 0.5*f^T(x)*f(x)

computeStep

public void computeStep(double regionRadius,
                        org.ejml.data.DenseMatrix64F step)

Description copied from interface: TrustRegionStep

Computes the next step to take for a given trust region. Must invoke TrustRegionStep.setInputs(org.ejml.data.DenseMatrix64F, org.ejml.data.DenseMatrix64F, org.ejml.data.DenseMatrix64F, org.ejml.data.DenseMatrix64F, double) before, but it only needs to be called once.

Specified by:

computeStep in interface TrustRegionStep

Parameters:

regionRadius - Size of the trust region.

step - Output, the computed step.

predictedReduction

public double predictedReduction()

Description copied from interface: TrustRegionStep

Returns the predicted reduction for the step. A linear model is used to predict the reduction. See class description for

Specified by:

predictedReduction in interface TrustRegionStep

Returns:

The predicted reduction.

isMaxStep

public boolean isMaxStep()

Description copied from interface: TrustRegionStep

Was a step equal to the regionRadius taken?

Specified by:

isMaxStep in interface TrustRegionStep

Returns:

true if maximum step and false if less than the maximum step