AbstractScalarDifferentiableOptimizer (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
- - org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer

All Implemented Interfaces:

BaseMultivariateOptimizer<DifferentiableMultivariateFunction>, BaseOptimizer<PointValuePair>, DifferentiableMultivariateOptimizer

Direct Known Subclasses:

NonLinearConjugateGradientOptimizer

Deprecated.
As of 3.1 (to be removed in 4.0).
```
@Deprecated
public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateOptimizer
```
Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.

Since:

2.0

Field Summary
- Fields inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
  evaluations

Constructor Summary

Constructors
Modifier	Constructor and Description
`protected`	`AbstractScalarDifferentiableOptimizer()` Deprecated. See `SimpleValueChecker.SimpleValueChecker()`
`protected`	`AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)` Deprecated.

Method Summary

Methods
Modifier and Type	Method and Description
`protected double[]`	`computeObjectiveGradient(double[] evaluationPoint)` Deprecated. Compute the gradient vector.
`PointValuePair`	`optimize(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, double[] startPoint)` Deprecated. Optimize an objective function.
`protected PointValuePair`	`optimizeInternal(int maxEval, DifferentiableMultivariateFunction f, GoalType goalType, double[] startPoint)` 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, optimizeInternal

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.commons.math3.optimization.BaseMultivariateOptimizer
optimize

Methods inherited from interface org.apache.commons.math3.optimization.BaseOptimizer
getConvergenceChecker, getEvaluations, getMaxEvaluations

- Constructor Detail
  - AbstractScalarDifferentiableOptimizer
```
@Deprecated
protected AbstractScalarDifferentiableOptimizer()
```
    Deprecated. See SimpleValueChecker.SimpleValueChecker()
    
    Simple constructor with default settings. The convergence check is set to a SimpleValueChecker.
  - AbstractScalarDifferentiableOptimizer
```
protected AbstractScalarDifferentiableOptimizer(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.
    
    Throws:
    
    TooManyEvaluationsException - if the allowed number of evaluations is exceeded.
  - optimizeInternal
```
protected PointValuePair optimizeInternal(int maxEval,
                              DifferentiableMultivariateFunction f,
                              GoalType goalType,
                              double[] startPoint)
```
    Deprecated.
    
    Optimize an objective function.
    
    Overrides:
    
    optimizeInternal in class BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
    
    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.
  - optimize
```
public PointValuePair optimize(int maxEval,
                      MultivariateDifferentiableFunction f,
                      GoalType goalType,
                      double[] startPoint)
```
    Deprecated.
    
    Optimize an objective function.
    
    Parameters:
    f - Objective function.
    goalType - Type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE.
    startPoint - Start point for optimization.
    maxEval - Maximum number of function evaluations.
    
    Returns:
    the point/value pair giving the optimal value for objective function.
    
    Throws:
    
    DimensionMismatchException - if the start point dimension is wrong.
    
    TooManyEvaluationsException - if the maximal number of evaluations is exceeded.
    
    NullArgumentException - if any argument is null.

Class AbstractScalarDifferentiableOptimizer

Field Summary

Fields inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer

Constructor Summary

Method Summary

Methods inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer

Methods inherited from class java.lang.Object

Methods inherited from interface org.apache.commons.math3.optimization.BaseMultivariateOptimizer

Methods inherited from interface org.apache.commons.math3.optimization.BaseOptimizer

Constructor Detail

AbstractScalarDifferentiableOptimizer

AbstractScalarDifferentiableOptimizer

Method Detail

computeObjectiveGradient

optimizeInternal

optimize