AbstractScalarDifferentiableOptimizer (Commons Math 2.2 API)

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

Version:

$Revision: 1069567 $ $Date: 2011-02-10 22:07:26 +0100 (jeu. 10 févr. 2011) $

Field Summary

Fields
Modifier and Type	Field and Description
`protected RealConvergenceChecker`	`checker` Deprecated.
`static int`	`DEFAULT_MAX_ITERATIONS` Default maximal number of iterations allowed.
`protected GoalType`	`goal` Deprecated.
`protected double[]`	`point` Deprecated.

Constructor Summary

Constructors
Modifier Constructor and Description

protected AbstractScalarDifferentiableOptimizer()
Simple constructor with default settings.

Constructors
Modifier	Constructor and Description
`protected`	`AbstractScalarDifferentiableOptimizer()` Simple constructor with default settings.

Method Summary

Methods
Modifier and Type	Method and Description
`protected double[]`	`computeObjectiveGradient(double[] evaluationPoint)` Compute the gradient vector.
`protected double`	`computeObjectiveValue(double[] evaluationPoint)` Compute the objective function value.
`protected abstract RealPointValuePair`	`doOptimize()` Perform the bulk of optimization algorithm.
`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.
`protected void`	`incrementIterationsCounter()` Increment the iterations counter by 1.
`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
clone, equals, finalize, 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
  - checker
```
@Deprecated
protected RealConvergenceChecker checker
```
    Deprecated.
    
    Convergence checker.
  - goal
```
@Deprecated
protected GoalType goal
```
    Deprecated.
    
    Type of optimization.
    
    Since:
    
    2.1
  - point
```
@Deprecated
protected double[] point
```
    Deprecated.
    
    Current point set.
- Constructor Detail
  - AbstractScalarDifferentiableOptimizer
```
protected AbstractScalarDifferentiableOptimizer()
```
    Simple constructor with default settings.
    The convergence check is set to a SimpleScalarValueChecker and the maximal number of evaluation is set to its default value.
- 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
  - incrementIterationsCounter
```
protected void incrementIterationsCounter()
                                   throws OptimizationException
```
    Increment the iterations counter by 1.
    
    Throws:
    
    OptimizationException - if the maximal number of iterations is exceeded
  - computeObjectiveGradient
```
protected double[] computeObjectiveGradient(double[] evaluationPoint)
                                     throws FunctionEvaluationException
```
    Compute the gradient vector.
    
    Parameters:
    evaluationPoint - point at which the gradient must be evaluated
    
    Returns:
    gradient at the specified point
    
    Throws:
    
    FunctionEvaluationException - if the function gradient
  - computeObjectiveValue
```
protected double computeObjectiveValue(double[] evaluationPoint)
                                throws FunctionEvaluationException
```
    Compute the objective function value.
    
    Parameters:
    evaluationPoint - point at which the objective function must be evaluated
    
    Returns:
    objective function value at specified point
    
    Throws:
    
    FunctionEvaluationException - if the function cannot be evaluated or its dimension doesn't match problem dimension or the maximal number of iterations is exceeded
  - 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
  - doOptimize
```
protected abstract RealPointValuePair doOptimize()
                                          throws FunctionEvaluationException,
                                                 OptimizationException,
                                                 IllegalArgumentException
```
    Perform the bulk of optimization algorithm.
    
    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

Class AbstractScalarDifferentiableOptimizer

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

DEFAULT_MAX_ITERATIONS

checker

goal

point

Constructor Detail

AbstractScalarDifferentiableOptimizer

Method Detail

setMaxIterations

getMaxIterations

getIterations

setMaxEvaluations

getMaxEvaluations

getEvaluations

getGradientEvaluations

setConvergenceChecker

getConvergenceChecker

incrementIterationsCounter

computeObjectiveGradient

computeObjectiveValue

optimize

doOptimize