org.apache.commons.math.optimization.general
Class AbstractScalarDifferentiableOptimizer

java.lang.Object
  org.apache.commons.math.optimization.direct.BaseAbstractScalarOptimizer<DifferentiableMultivariateRealFunction>
      org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer

All Implemented Interfaces:

BaseMultivariateRealOptimizer<DifferentiableMultivariateRealFunction>, BaseOptimizer<RealPointValuePair>, DifferentiableMultivariateRealOptimizer

Direct Known Subclasses:

NonLinearConjugateGradientOptimizer

public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractScalarOptimizer<DifferentiableMultivariateRealFunction>
implements DifferentiableMultivariateRealOptimizer

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 1166311 2011-09-07 18:48:06Z luc $

Field Summary

Fields inherited from class org.apache.commons.math.optimization.direct.BaseAbstractScalarOptimizer

evaluations

Constructor Summary

protected	AbstractScalarDifferentiableOptimizer() Simple constructor with default settings.
protected	AbstractScalarDifferentiableOptimizer(ConvergenceChecker<RealPointValuePair> checker)

Method Summary

protected double[]	computeObjectiveGradient(double[] evaluationPoint) Compute the gradient vector.
RealPointValuePair	optimize(int maxEval, DifferentiableMultivariateRealFunction f, GoalType goalType, double[] startPoint) Optimize an objective function.

Methods inherited from class org.apache.commons.math.optimization.direct.BaseAbstractScalarOptimizer

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

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.math.optimization.BaseOptimizer

getConvergenceChecker, getEvaluations, getMaxEvaluations, setConvergenceChecker

Constructor Detail

AbstractScalarDifferentiableOptimizer

protected AbstractScalarDifferentiableOptimizer()

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

AbstractScalarDifferentiableOptimizer

protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<RealPointValuePair> 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 RealPointValuePair optimize(int maxEval,
                                   DifferentiableMultivariateRealFunction f,
                                   GoalType goalType,
                                   double[] startPoint)

Optimize an objective function.

Specified by:

optimize in interface BaseMultivariateRealOptimizer<DifferentiableMultivariateRealFunction>

Overrides:

optimize in class BaseAbstractScalarOptimizer<DifferentiableMultivariateRealFunction>

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.