Package org.apache.commons.math3.optimization.general

Class AbstractDifferentiableOptimizer

java.lang.Object

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

org.apache.commons.math3.optimization.general.AbstractDifferentiableOptimizer

All Implemented Interfaces:

BaseMultivariateOptimizer<MultivariateDifferentiableFunction>, BaseOptimizer<PointValuePair>

@Deprecated
public abstract class AbstractDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<MultivariateDifferentiableFunction>

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:

3.1

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	AbstractDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)	Deprecated.

Method Summary

Modifier and Type	Method	Description
protected double[]	computeObjectiveGradient(double[] evaluationPoint)	Deprecated. Compute the gradient vector.
protected PointValuePair	optimizeInternal(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, double[] startPoint)	Deprecated. In 3.1.
protected PointValuePair	optimizeInternal(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, OptimizationData... optData)	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

Methods inherited from class java.lang.Object

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

Field Detail

gradient

private MultivariateVectorFunction gradient

Deprecated.

Objective function gradient.

Constructor Detail

AbstractDifferentiableOptimizer

protected AbstractDifferentiableOptimizer(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.

optimizeInternal

@Deprecated
protected PointValuePair optimizeInternal(int maxEval,
                                          MultivariateDifferentiableFunction f,
                                          GoalType goalType,
                                          double[] startPoint)

Deprecated.

In 3.1. Please use optimizeInternal(int,MultivariateDifferentiableFunction,GoalType,OptimizationData[]) instead.

Optimize an objective function.

Overrides:

optimizeInternal in class BaseAbstractMultivariateOptimizer<MultivariateDifferentiableFunction>

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.

optimizeInternal

protected PointValuePair optimizeInternal(int maxEval,
                                          MultivariateDifferentiableFunction f,
                                          GoalType goalType,
                                          OptimizationData... optData)

Deprecated.

Optimize an objective function.

Overrides:

optimizeInternal in class BaseAbstractMultivariateOptimizer<MultivariateDifferentiableFunction>

Parameters:

maxEval - Allowed number of evaluations of the objective function.

f - Objective function.

goalType - Optimization type.

optData - Optimization data. The following data will be looked for:

• InitialGuess
• SimpleBounds

Returns:

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