org.apache.commons.math3.optimization.general

Class AbstractScalarDifferentiableOptimizer

java.lang.Object

org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>

org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer

All Implemented Interfaces:

BaseMultivariateOptimizer<DifferentiableMultivariateFunction>, BaseOptimizer<PointValuePair>, DifferentiableMultivariateOptimizer

Direct Known Subclasses:

NonLinearConjugateGradientOptimizer

public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateOptimizer

Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.

Since:

2.0

Version:

$Id: AbstractScalarDifferentiableOptimizer.java 1244107 2012-02-14 16:17:55Z erans $

Field Summary

Fields inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer

evaluations

Constructor Summary

Constructors

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

Method Summary

Methods

Modifier and Type	Method and Description
protected double[]	computeObjectiveGradient(double[] evaluationPoint) Compute the gradient vector.
PointValuePair	optimize(int maxEval, DifferentiableMultivariateFunction f, GoalType goalType, double[] startPoint) Optimize an objective function.

Methods inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer

computeObjectiveValue, doOptimize, getConvergenceChecker, getEvaluations, getGoalType, getMaxEvaluations, getStartPoint

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.apache.commons.math3.optimization.BaseOptimizer

getConvergenceChecker, getEvaluations, getMaxEvaluations

Constructor Detail

AbstractScalarDifferentiableOptimizer

protected AbstractScalarDifferentiableOptimizer()

Simple constructor with default settings. The convergence check is set to a SimpleValueChecker.

AbstractScalarDifferentiableOptimizer

protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)

Parameters:

checker - Convergence checker.

Method Detail

computeObjectiveGradient

protected double[] computeObjectiveGradient(double[] evaluationPoint)

Compute the gradient vector.

Parameters:

evaluationPoint - Point at which the gradient must be evaluated.

Returns:

the gradient at the specified point.

Throws:

TooManyEvaluationsException - if the allowed number of evaluations is exceeded.

optimize

public PointValuePair optimize(int maxEval,
                      DifferentiableMultivariateFunction f,
                      GoalType goalType,
                      double[] startPoint)

Optimize an objective function.

Specified by:

optimize in interface BaseMultivariateOptimizer<DifferentiableMultivariateFunction>

Overrides:

optimize in class BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>

Parameters:

maxEval - Maximum number of function evaluations.

f - Objective function.

goalType - Type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE.

startPoint - Start point for optimization.

Returns:

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