Apache Commons Math 3.6.1 · org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer

Modifier and Type	Field and Description
private ConvergenceChecker<PointValuePair>	checker Deprecated as a consequence of `ConvergenceChecker` being deprecated. Convergence checker.
protected final Incrementor	evaluations Deprecated as a consequence of `Incrementor` being deprecated. Evaluations counter.
private MultivariateFunction	function Objective function.
private GoalType	goal Deprecated as a consequence of `GoalType` being deprecated. Type of optimization.
private double[]	lowerBound Lower bounds.
private double[]	start Initial guess.
private double[]	upperBound Upper bounds.

Access	Constructor and Description
protected	BaseAbstractMultivariateOptimizer() Deprecated See `SimpleValueChecker#SimpleValueChecker()` Simple constructor with default settings.
protected	BaseAbstractMultivariateOptimizer(ConvergenceChecker<PointValuePair> Convergence checker. checker) Deprecated as a consequence of `ConvergenceChecker` being deprecated.

Method Summary

Modifier and Type	Method and Description
private void	checkParameters() Check parameters consistency.
protected double	Returns: the objective function value at the specified point. computeObjectiveValue(double[] Point at which the objective function must be evaluated. point) Compute the objective function value.
protected abstract PointValuePair	Returns: the point/value pair giving the optimal value of the objective function. doOptimize() Deprecated as a consequence of `PointValuePair` being deprecated. Perform the bulk of the optimization algorithm.
public ConvergenceChecker<PointValuePair>	getConvergenceChecker() Implements org.apache.commons.math3.optimization.BaseOptimizer.getConvergenceChecker. Deprecated as a consequence of `ConvergenceChecker` being deprecated. Get the convergence checker.
public int	getEvaluations() Implements org.apache.commons.math3.optimization.BaseOptimizer.getEvaluations. Get the number of evaluations of the objective function.
public GoalType	Returns: the optimization type. getGoalType() Deprecated as a consequence of `GoalType` being deprecated.
public double[]	Returns: the lower bounds. getLowerBound()
public int	getMaxEvaluations() Implements org.apache.commons.math3.optimization.BaseOptimizer.getMaxEvaluations. Get the maximal number of function evaluations.
public double[]	Returns: the initial guess. getStartPoint()
public double[]	Returns: the upper bounds. getUpperBound()
public PointValuePair	optimize(int Maximum number of function evaluations. maxEval, FUNC Objective function. f, GoalType Type of optimization goal: either `GoalType#MAXIMIZE` or `GoalType#MINIMIZE`. goalType, double[] Start point for optimization. startPoint) Implements org.apache.commons.math3.optimization.BaseMultivariateOptimizer.optimize. Deprecated As of 3.1. Optimize an objective function.
public PointValuePair	Returns: the point/value pair giving the optimal value of the objective function. optimize(int Allowed number of evaluations of the objective function. maxEval, FUNC Objective function. f, GoalType Optimization type. goalType, OptimizationData... Optimization data. The following data will be looked for: `InitialGuess` `SimpleBounds` optData) Deprecated as a consequence of `GoalType`, `OptimizationData` and `PointValuePair` being deprecated. Optimize an objective function.
protected PointValuePair	Returns: the point/value pair giving the optimal value for objective function. optimizeInternal(int Maximum number of function evaluations. maxEval, FUNC Objective function. f, GoalType Type of optimization goal: either `GoalType#MAXIMIZE` or `GoalType#MINIMIZE`. goalType, double[] Start point for optimization. startPoint) Deprecated As of 3.1. Optimize an objective function.
protected PointValuePair	Returns: the point/value pair giving the optimal value of the objective function. optimizeInternal(int Allowed number of evaluations of the objective function. maxEval, FUNC Objective function. f, GoalType Optimization type. goalType, OptimizationData... Optimization data. The following data will be looked for: `InitialGuess` `SimpleBounds` optData) Deprecated as a consequence of `GoalType`, `OptimizationData` and `PointValuePair` being deprecated. Optimize an objective function.
private void	parseOptimizationData(OptimizationData... Optimization data. The following data will be looked for: `InitialGuess` `SimpleBounds` optData) Deprecated as a consequence of `OptimizationData` being deprecated. Scans the list of (required and optional) optimization data that characterize the problem.

Inherited from java.lang.Object:: clone equals finalize getClass hashCode notify notifyAll toString wait wait wait

checker	back to summary
private ConvergenceChecker<PointValuePair> checker Deprecated as a consequence of `ConvergenceChecker` being deprecated. See corresponding docs for further information. Convergence checker.

evaluations	back to summary
protected final Incrementor evaluations Deprecated as a consequence of `Incrementor` being deprecated. See corresponding docs for further information. Evaluations counter.

function	back to summary
private MultivariateFunction function Objective function.

goal	back to summary
private GoalType goal Deprecated as a consequence of `GoalType` being deprecated. See corresponding docs for further information. Type of optimization.

lowerBound	back to summary
private double[] lowerBound Lower bounds.

start	back to summary
private double[] start Initial guess.

upperBound	back to summary
private double[] upperBound Upper bounds.

BaseAbstractMultivariateOptimizer	back to summary
protected BaseAbstractMultivariateOptimizer() Deprecated See `SimpleValueChecker#SimpleValueChecker()` Simple constructor with default settings. The convergence check is set to a `SimpleValueChecker`. Annotations @Deprecated

BaseAbstractMultivariateOptimizer	back to summary
protected BaseAbstractMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) Deprecated as a consequence of `ConvergenceChecker` being deprecated. See corresponding docs for further information. Parameters checker:ConvergenceChecker<PointValuePair> Convergence checker.

Method Detail

checkParameters	back to summary
private void checkParameters() Check parameters consistency.

computeObjectiveValue	back to summary
protected double computeObjectiveValue(double[] point) Compute the objective function value. Parameters point:double[] Point at which the objective function must be evaluated. Returns:double the objective function value at the specified point. Exceptions TooManyEvaluationsException: if the maximal number of evaluations is exceeded.

computeObjectiveValue

back to summary

protected double computeObjectiveValue(double[] point)

Compute the objective function value.

Parameters

point:double[]: Point at which the objective function must be evaluated.

Returns:double

the objective function value at the specified point.

Exceptions

TooManyEvaluationsException:: if the maximal number of evaluations is exceeded.

doOptimize back to summary

doOptimize	back to summary
protected abstract PointValuePair doOptimize() Deprecated as a consequence of `PointValuePair` being deprecated. See corresponding docs for further information. Perform the bulk of the optimization algorithm. Returns:PointValuePair the point/value pair giving the optimal value of the objective function.

protected abstract PointValuePair doOptimize()

Deprecated

as a consequence of PointValuePair being deprecated. See corresponding docs for further information.

Perform the bulk of the optimization algorithm.

Returns:PointValuePair: the point/value pair giving the optimal value of the objective function.

getConvergenceChecker back to summary

getConvergenceChecker	back to summary
public ConvergenceChecker<PointValuePair> getConvergenceChecker() Implements org.apache.commons.math3.optimization.BaseOptimizer.getConvergenceChecker. Doc from org.apache.commons.math3.optimization.BaseOptimizer.getConvergenceChecker. Deprecated as a consequence of `ConvergenceChecker` being deprecated. See corresponding docs for further information. Get the convergence checker. Returns:ConvergenceChecker<PointValuePair> the object used to check for convergence.

public ConvergenceChecker<PointValuePair> getConvergenceChecker()

Implements org.apache.commons.math3.optimization.BaseOptimizer.getConvergenceChecker.

Doc from org.apache.commons.math3.optimization.BaseOptimizer.getConvergenceChecker.

Deprecated

as a consequence of ConvergenceChecker being deprecated. See corresponding docs for further information.

Get the convergence checker.

Returns:ConvergenceChecker<PointValuePair>: the object used to check for convergence.

getEvaluations back to summary

getEvaluations	back to summary
public int getEvaluations() Implements org.apache.commons.math3.optimization.BaseOptimizer.getEvaluations. Doc from org.apache.commons.math3.optimization.BaseOptimizer.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. Returns:int the number of evaluations of the objective function.

public int getEvaluations()

Implements org.apache.commons.math3.optimization.BaseOptimizer.getEvaluations.

Doc from org.apache.commons.math3.optimization.BaseOptimizer.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.

Returns:int: the number of evaluations of the objective function.

getGoalType	back to summary
public GoalType getGoalType() Deprecated as a consequence of `GoalType` being deprecated. See corresponding docs for further information. Returns:GoalType the optimization type.

getLowerBound	back to summary
public double[] getLowerBound() Returns:double[] the lower bounds. Since 3.1

getMaxEvaluations	back to summary
public int getMaxEvaluations() Implements org.apache.commons.math3.optimization.BaseOptimizer.getMaxEvaluations. Doc from org.apache.commons.math3.optimization.BaseOptimizer.getMaxEvaluations. Get the maximal number of function evaluations. Returns:int the maximal number of function evaluations.

getMaxEvaluations

back to summary

public int getMaxEvaluations()

Implements org.apache.commons.math3.optimization.BaseOptimizer.getMaxEvaluations.

Doc from org.apache.commons.math3.optimization.BaseOptimizer.getMaxEvaluations.

Get the maximal number of function evaluations.

Returns:int: the maximal number of function evaluations.

getStartPoint	back to summary
public double[] getStartPoint() Returns:double[] the initial guess.

getUpperBound	back to summary
public double[] getUpperBound() Returns:double[] the upper bounds. Since 3.1

optimize back to summary

optimize	back to summary
public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType, double[] startPoint) Implements org.apache.commons.math3.optimization.BaseMultivariateOptimizer.optimize. Doc from org.apache.commons.math3.optimization.BaseMultivariateOptimizer.optimize. Deprecated As of 3.1. Please use `optimize(int, MultivariateFunction, GoalType, OptimizationData[])` instead. Optimize an objective function. Parameters maxEval:int Maximum number of function evaluations. f:FUNC Objective function. goalType:GoalType Type of optimization goal: either `GoalType#MAXIMIZE` or `GoalType#MINIMIZE`. startPoint:double[] Start point for optimization. Returns:PointValuePair the point/value pair giving the optimal value for objective function. Annotations @Deprecated

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

Implements org.apache.commons.math3.optimization.BaseMultivariateOptimizer.optimize.

Doc from org.apache.commons.math3.optimization.BaseMultivariateOptimizer.optimize.

Deprecated

As of 3.1. Please use optimize(int, MultivariateFunction, GoalType, OptimizationData[]) instead.

Optimize an objective function.

Parameters

maxEval:int: Maximum number of function evaluations.
f:FUNC: Objective function.
goalType:GoalType: Type of optimization goal: either GoalType#MAXIMIZE or GoalType#MINIMIZE.
startPoint:double[]: Start point for optimization.

Returns:PointValuePair

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

Annotations

@Deprecated

optimize back to summary

optimize	back to summary
public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType, OptimizationData... optData) Deprecated as a consequence of `GoalType`, `OptimizationData` and `PointValuePair` being deprecated. See corresponding docs for further information. Optimize an objective function. Parameters maxEval:int Allowed number of evaluations of the objective function. f:FUNC Objective function. goalType:GoalType Optimization type. optData:OptimizationData[] Optimization data. The following data will be looked for: `InitialGuess` `SimpleBounds` Returns:PointValuePair the point/value pair giving the optimal value of the objective function. Since 3.1

public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType, OptimizationData... optData)

Deprecated

as a consequence of GoalType, OptimizationData and PointValuePair being deprecated. See corresponding docs for further information.

Optimize an objective function.

Parameters

maxEval:int

Allowed number of evaluations of the objective function.

f:FUNC

Objective function.

goalType:GoalType

Optimization type.

optData:OptimizationData[]

Optimization data. The following data will be looked for:

Returns:PointValuePair

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

Since

3.1

optimizeInternal back to summary

optimizeInternal	back to summary
protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType, double[] startPoint) Deprecated As of 3.1. Please use `optimize(int, MultivariateFunction, GoalType, OptimizationData[])` instead. Optimize an objective function. Parameters maxEval:int Maximum number of function evaluations. f:FUNC Objective function. goalType:GoalType Type of optimization goal: either `GoalType#MAXIMIZE` or `GoalType#MINIMIZE`. startPoint:double[] Start point for optimization. Returns:PointValuePair the point/value pair giving the optimal value for objective function. Annotations @Deprecated Exceptions DimensionMismatchException: if the start point dimension is wrong. TooManyEvaluationsException: if the maximal number of evaluations is exceeded. NullArgumentException: if any argument is `null`.

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

Deprecated

As of 3.1. Please use optimize(int, MultivariateFunction, GoalType, OptimizationData[]) instead.

Optimize an objective function.

Parameters

maxEval:int: Maximum number of function evaluations.
f:FUNC: Objective function.
goalType:GoalType: Type of optimization goal: either GoalType#MAXIMIZE or GoalType#MINIMIZE.
startPoint:double[]: Start point for optimization.

Returns:PointValuePair

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

Annotations

@Deprecated

Exceptions

DimensionMismatchException:: if the start point dimension is wrong.
TooManyEvaluationsException:: if the maximal number of evaluations is exceeded.
NullArgumentException:: if any argument is null.

optimizeInternal back to summary

optimizeInternal	back to summary
protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType, OptimizationData... optData) throws TooManyEvaluationsException Deprecated as a consequence of `GoalType`, `OptimizationData` and `PointValuePair` being deprecated. See corresponding docs for further information. Optimize an objective function. Parameters maxEval:int Allowed number of evaluations of the objective function. f:FUNC Objective function. goalType:GoalType Optimization type. optData:OptimizationData[] Optimization data. The following data will be looked for: `InitialGuess` `SimpleBounds` Returns:PointValuePair the point/value pair giving the optimal value of the objective function. Exceptions TooManyEvaluationsException: if the maximal number of evaluations is exceeded. Since 3.1

protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType, OptimizationData... optData) throws TooManyEvaluationsException

Deprecated

as a consequence of GoalType, OptimizationData and PointValuePair being deprecated. See corresponding docs for further information.

Optimize an objective function.

Parameters

maxEval:int

Allowed number of evaluations of the objective function.

f:FUNC

Objective function.

goalType:GoalType

Optimization type.

optData:OptimizationData[]

Optimization data. The following data will be looked for:

Returns:PointValuePair

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

Exceptions

TooManyEvaluationsException:: if the maximal number of evaluations is exceeded.

Since

3.1

parseOptimizationData back to summary

parseOptimizationData	back to summary
private void parseOptimizationData(OptimizationData... optData) Deprecated as a consequence of `OptimizationData` being deprecated. See corresponding docs for further information. Scans the list of (required and optional) optimization data that characterize the problem. Parameters optData:OptimizationData[] Optimization data. The following data will be looked for: `InitialGuess` `SimpleBounds`

private void parseOptimizationData(OptimizationData... optData)

Deprecated

as a consequence of OptimizationData being deprecated. See corresponding docs for further information.

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

Parameters

optData:OptimizationData[]

Optimization data. The following data will be looked for:

public abstract Class BaseAbstractMultivariateOptimizer<FUNC extends MultivariateFunction>

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