org.apache.commons.math3.optimization.direct

Class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>

java.lang.Object

org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateVectorOptimizer<FUNC>

Type Parameters:

FUNC - the type of the objective function to be optimized

All Implemented Interfaces:

BaseMultivariateVectorOptimizer<FUNC>, BaseOptimizer<PointVectorValuePair>

Direct Known Subclasses:

AbstractLeastSquaresOptimizer

public abstract class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>
extends Object
implements BaseMultivariateVectorOptimizer<FUNC>

Base class for implementing optimizers for multivariate scalar functions. This base class handles the boiler-plate methods associated to thresholds settings, iterations and evaluations counting.

Since:

3.0

Version:

$Id$

Field Summary

Fields

Modifier and Type	Field and Description
protected Incrementor	evaluations Evaluations counter.

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	BaseAbstractMultivariateVectorOptimizer() Simple constructor with default settings.
protected	BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)

Method Summary

Methods

Modifier and Type	Method and Description
protected double[]	computeObjectiveValue(double[] point) Compute the objective function value.
protected abstract PointVectorValuePair	doOptimize() Perform the bulk of the optimization algorithm.
ConvergenceChecker<PointVectorValuePair>	getConvergenceChecker() Get the convergence checker.
int	getEvaluations() Get the number of evaluations of the objective function.
int	getMaxEvaluations() Get the maximal number of function evaluations.
double[]	getStartPoint()
protected double[]	getTargetRef()
protected double[]	getWeightRef()
PointVectorValuePair	optimize(int maxEval, FUNC f, double[] t, double[] w, double[] startPoint) Optimize an objective function.

Methods inherited from class java.lang.Object

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

Field Detail

evaluations

protected final Incrementor evaluations

Evaluations counter.

Constructor Detail

BaseAbstractMultivariateVectorOptimizer

protected BaseAbstractMultivariateVectorOptimizer()

Simple constructor with default settings. The convergence check is set to a SimpleVectorValueChecker and the allowed number of evaluations is set to Integer.MAX_VALUE.

BaseAbstractMultivariateVectorOptimizer

protected BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)

Parameters:

checker - Convergence checker.

Method Detail

getMaxEvaluations

public int getMaxEvaluations()

Get the maximal number of function evaluations.

Specified by:

getMaxEvaluations in interface BaseOptimizer<PointVectorValuePair>

Returns:

the maximal number of function evaluations.

getEvaluations

public int getEvaluations()

Get the number of evaluations of the objective function. The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.

Specified by:

getEvaluations in interface BaseOptimizer<PointVectorValuePair>

Returns:

the number of evaluations of the objective function.

getConvergenceChecker

public ConvergenceChecker<PointVectorValuePair> getConvergenceChecker()

Get the convergence checker.

Specified by:

getConvergenceChecker in interface BaseOptimizer<PointVectorValuePair>

Returns:

the object used to check for convergence.

computeObjectiveValue

protected double[] computeObjectiveValue(double[] point)

Compute the objective function value.

Parameters:

point - Point at which the objective function must be evaluated.

Returns:

the objective function value at the specified point.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.

optimize

public PointVectorValuePair optimize(int maxEval,
                            FUNC f,
                            double[] t,
                            double[] w,
                            double[] startPoint)

Optimize an objective function. Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weighti(objectivei - targeti)2

Specified by:

optimize in interface BaseMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>

Parameters:

maxEval - Maximum number of function evaluations.

f - Objective function.

t - Target value for the objective functions at optimum.

w - Weights for the least squares cost computation.

startPoint - Start point for optimization.

Returns:

the point/value pair giving the optimal value for objective function.

getStartPoint

public double[] getStartPoint()

Returns:

the initial guess.

doOptimize

protected abstract PointVectorValuePair doOptimize()

Perform the bulk of the optimization algorithm.

Returns:

the point/value pair giving the optimal value for the objective function.

getTargetRef

protected double[] getTargetRef()

Returns:

a reference to the array.

getWeightRef

protected double[] getWeightRef()

Returns:

a reference to the array.