Package 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

@Deprecated
public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateOptimizer

Deprecated.

As of 3.1 (to be removed in 4.0).

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

Since:

2.0

Field Summary

Fields

Modifier and Type	Field	Description
private MultivariateVectorFunction	gradient	Deprecated. Objective function gradient.

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

evaluations

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	AbstractScalarDifferentiableOptimizer()	Deprecated. See SimpleValueChecker()
protected	AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)	Deprecated.

Method Summary

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

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

computeObjectiveValue, doOptimize, getConvergenceChecker, getEvaluations, getGoalType, getLowerBound, getMaxEvaluations, getStartPoint, getUpperBound, optimize, optimize, optimizeInternal

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.BaseMultivariateOptimizer

optimize

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

getConvergenceChecker, getEvaluations, getMaxEvaluations

Field Detail

gradient

private MultivariateVectorFunction gradient

Deprecated.

Objective function gradient.

Constructor Detail

AbstractScalarDifferentiableOptimizer

@Deprecated
protected AbstractScalarDifferentiableOptimizer()

Deprecated.

See SimpleValueChecker()

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

AbstractScalarDifferentiableOptimizer

protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)

Deprecated.

Parameters:

checker - Convergence checker.

Method Detail

computeObjectiveGradient

protected double[] computeObjectiveGradient(double[] evaluationPoint)

Deprecated.

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.

optimizeInternal

protected PointValuePair optimizeInternal(int maxEval,
                                          DifferentiableMultivariateFunction f,
                                          GoalType goalType,
                                          double[] startPoint)

Deprecated.

Optimize an objective function.

Overrides:

optimizeInternal 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.

optimize

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

Deprecated.

Optimize an objective function.

Parameters:

f - Objective function.

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

startPoint - Start point for optimization.

maxEval - Maximum number of function evaluations.

Returns:

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

Throws:

DimensionMismatchException - if the start point dimension is wrong.

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.

NullArgumentException - if any argument is null.