Package org.apache.commons.math4.legacy.optim.univariate

Class UnivariateOptimizer

java.lang.Object

org.apache.commons.math4.legacy.optim.BaseOptimizer<UnivariatePointValuePair>

org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer

Direct Known Subclasses:

BrentOptimizer, MultiStartUnivariateOptimizer

public abstract class UnivariateOptimizer
extends BaseOptimizer<UnivariatePointValuePair>

Base class for a univariate scalar function optimizer.

Since:

3.1

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	UnivariateOptimizer(ConvergenceChecker<UnivariatePointValuePair> checker)

Method Summary

Modifier and Type	Method	Description
protected double	computeObjectiveValue(double x)	Deprecated. Use getObjectiveFunction() instead.
GoalType	getGoalType()
double	getMax()
double	getMin()
protected UnivariateFunction	getObjectiveFunction()
double	getStartValue()
UnivariatePointValuePair	optimize(OptimizationData... optData)	Stores data and performs the optimization.
protected void	parseOptimizationData(OptimizationData... optData)	Scans the list of (required and optional) optimization data that characterize the problem.

Methods inherited from class org.apache.commons.math4.legacy.optim.BaseOptimizer

doOptimize, getAbsoluteTolerance, getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, getRelativeTolerance, incrementEvaluationCount, incrementIterationCount, optimize

Methods inherited from class java.lang.Object

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

Constructor Detail

UnivariateOptimizer

protected UnivariateOptimizer(ConvergenceChecker<UnivariatePointValuePair> checker)

Parameters:

checker - Convergence checker.

Method Detail

optimize

public UnivariatePointValuePair optimize(OptimizationData... optData)
                                  throws TooManyEvaluationsException

Stores data and performs the optimization.

The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.

When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).

Important note: Subclasses must override BaseOptimizer.parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

Overrides:

optimize in class BaseOptimizer<UnivariatePointValuePair>

Parameters:

optData - Optimization data. In addition to those documented in BaseOptimizer, this method will register the following data:

• GoalType
• SearchInterval
• UnivariateObjectiveFunction

Returns:

a point/value pair that satisfies the convergence criteria.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.

getGoalType

public GoalType getGoalType()

Returns:

the optimization type.

parseOptimizationData

protected void parseOptimizationData(OptimizationData... optData)

Scans the list of (required and optional) optimization data that characterize the problem.

Overrides:

parseOptimizationData in class BaseOptimizer<UnivariatePointValuePair>

Parameters:

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

• GoalType
• SearchInterval
• UnivariateObjectiveFunction

getStartValue

public double getStartValue()

Returns:

the initial guess.

getMin

public double getMin()

Returns:

the lower bounds.

getMax

public double getMax()

Returns:

the upper bounds.

getObjectiveFunction

protected UnivariateFunction getObjectiveFunction()

Returns:

a wrapper that delegates to the user-supplied function, and counts the number of evaluations.

computeObjectiveValue

@Deprecated
protected double computeObjectiveValue(double x)

Deprecated.

Use getObjectiveFunction() instead.

Computes the objective function value. This method must be called by subclasses to enforce the evaluation counter limit.

Parameters:

x - Point at which the objective function must be evaluated.

Returns:

the objective function value at the specified point.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.