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

java.lang.Object
  org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer

All Implemented Interfaces:

DifferentiableMultivariateRealOptimizer

Direct Known Subclasses:

NonLinearConjugateGradientOptimizer, PowellOptimizer

public abstract class AbstractScalarDifferentiableOptimizer
extends Object
implements DifferentiableMultivariateRealOptimizer

Base class for implementing optimizers for multivariate scalar functions.

This base class handles the boilerplate methods associated to thresholds settings, iterations and evaluations counting.

Since:

2.0

Field Summary

static int

DEFAULT_MAX_ITERATIONS Default maximal number of iterations allowed.

Method Summary

RealConvergenceChecker	getConvergenceChecker() Get the convergence checker.
int	getEvaluations() Get the number of evaluations of the objective function.
int	getGradientEvaluations() Get the number of evaluations of the objective function gradient.
int	getIterations() Get the number of iterations realized by the algorithm.
int	getMaxEvaluations() Get the maximal number of functions evaluations.
int	getMaxIterations() Get the maximal number of iterations of the algorithm.
RealPointValuePair	optimize(DifferentiableMultivariateRealFunction f, GoalType goalType, double[] startPoint) Optimizes an objective function.
void	setConvergenceChecker(RealConvergenceChecker convergenceChecker) Set the convergence checker.
void	setMaxEvaluations(int maxEvaluations) Set the maximal number of functions evaluations.
void	setMaxIterations(int maxIterations) Set the maximal number of iterations of the algorithm.

Methods inherited from class java.lang.Object

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

Field Detail

DEFAULT_MAX_ITERATIONS

public static final int DEFAULT_MAX_ITERATIONS

Default maximal number of iterations allowed.

See Also:

Constant Field Values

Method Detail

setMaxIterations

public void setMaxIterations(int maxIterations)

Set the maximal number of iterations of the algorithm.

Specified by:

setMaxIterations in interface DifferentiableMultivariateRealOptimizer

Parameters:

maxIterations - maximal number of function calls

getMaxIterations

public int getMaxIterations()

Get the maximal number of iterations of the algorithm.

Specified by:

getMaxIterations in interface DifferentiableMultivariateRealOptimizer

Returns:

maximal number of iterations

getIterations

public int getIterations()

Get the number of iterations realized by the algorithm.

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:

getIterations in interface DifferentiableMultivariateRealOptimizer

Returns:

number of iterations

setMaxEvaluations

public void setMaxEvaluations(int maxEvaluations)

Set the maximal number of functions evaluations.

Specified by:

setMaxEvaluations in interface DifferentiableMultivariateRealOptimizer

Parameters:

maxEvaluations - maximal number of function evaluations

getMaxEvaluations

public int getMaxEvaluations()

Get the maximal number of functions evaluations.

Specified by:

getMaxEvaluations in interface DifferentiableMultivariateRealOptimizer

Returns:

maximal number of functions 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 DifferentiableMultivariateRealOptimizer

Returns:

number of evaluations of the objective function

getGradientEvaluations

public int getGradientEvaluations()

Get the number of evaluations of the objective function gradient.

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:

getGradientEvaluations in interface DifferentiableMultivariateRealOptimizer

Returns:

number of evaluations of the objective function gradient

setConvergenceChecker

public void setConvergenceChecker(RealConvergenceChecker convergenceChecker)

Set the convergence checker.

Specified by:

setConvergenceChecker in interface DifferentiableMultivariateRealOptimizer

Parameters:

convergenceChecker - object to use to check for convergence

getConvergenceChecker

public RealConvergenceChecker getConvergenceChecker()

Get the convergence checker.

Specified by:

getConvergenceChecker in interface DifferentiableMultivariateRealOptimizer

Returns:

object used to check for convergence

optimize

public RealPointValuePair optimize(DifferentiableMultivariateRealFunction f,
                                   GoalType goalType,
                                   double[] startPoint)
                            throws FunctionEvaluationException,
                                   OptimizationException,
                                   IllegalArgumentException

Optimizes an objective function.

Specified by:

optimize in interface DifferentiableMultivariateRealOptimizer

Parameters:

f - objective function

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

startPoint - the start point for optimization

Returns:

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

Throws:

FunctionEvaluationException - if the objective function throws one during the search

OptimizationException - if the algorithm failed to converge

IllegalArgumentException - if the start point dimension is wrong