BaseAbstractMultivariateVectorOptimizer (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateVectorOptimizer<FUNC>

Type Parameters:
FUNC - the type of the objective function to be optimized

All Implemented Interfaces:

BaseMultivariateVectorOptimizer<FUNC>, BaseOptimizer<PointVectorValuePair>

Direct Known Subclasses:

AbstractLeastSquaresOptimizer

Deprecated.
As of 3.1 (to be removed in 4.0).
```
@Deprecated
public abstract class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>
extends Object
implements BaseMultivariateVectorOptimizer<FUNC>
```
Base class for implementing optimizers for multivariate scalar functions. This base class handles the boiler-plate methods associated to thresholds settings, iterations and evaluations counting.

Since:

3.0

Field Summary

Fields
Modifier and Type Field and Description

protected Incrementor evaluations
Deprecated.

Evaluations counter.

Fields
Modifier and Type	Field and Description
`protected Incrementor`	`evaluations` Deprecated. Evaluations counter.

Constructor Summary

Constructors
Modifier	Constructor and Description
`protected`	`BaseAbstractMultivariateVectorOptimizer()` Deprecated. See `SimpleVectorValueChecker.SimpleVectorValueChecker()`
`protected`	`BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)` Deprecated.

Method Summary

Methods
Modifier and Type	Method and Description
`protected double[]`	`computeObjectiveValue(double[] point)` Deprecated. Compute the objective function value.
`protected abstract PointVectorValuePair`	`doOptimize()` Deprecated. Perform the bulk of the optimization algorithm.
`ConvergenceChecker<PointVectorValuePair>`	`getConvergenceChecker()` Deprecated. Get the convergence checker.
`int`	`getEvaluations()` Deprecated. Get the number of evaluations of the objective function.
`int`	`getMaxEvaluations()` Deprecated. Get the maximal number of function evaluations.
`protected FUNC`	`getObjectiveFunction()` Deprecated. Gets the objective vector function.
`double[]`	`getStartPoint()` Deprecated. Gets the initial values of the optimized parameters.
`double[]`	`getTarget()` Deprecated. Gets the observed values to be matched by the objective vector function.
`protected double[]`	`getTargetRef()` Deprecated. As of 3.1.
`RealMatrix`	`getWeight()` Deprecated. Gets the weight matrix of the observations.
`protected double[]`	`getWeightRef()` Deprecated. As of 3.1.
`PointVectorValuePair`	`optimize(int maxEval, FUNC f, double[] t, double[] w, double[] startPoint)` Deprecated. As of 3.1. Please use `optimize(int,MultivariateVectorFunction,OptimizationData[])` instead.
`protected PointVectorValuePair`	`optimize(int maxEval, FUNC f, OptimizationData... optData)` Deprecated. Optimize an objective function.
`protected PointVectorValuePair`	`optimizeInternal(int maxEval, FUNC f, double[] t, double[] w, double[] startPoint)` Deprecated. As of 3.1. Please use `optimizeInternal(int,MultivariateVectorFunction,OptimizationData[])` instead.
`protected PointVectorValuePair`	`optimizeInternal(int maxEval, FUNC f, OptimizationData... optData)` Deprecated. Optimize an objective function.
`protected void`	`setUp()` Deprecated. Method which a subclass must override whenever its internal state depend on the `input` parsed by this base class.

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

- Field Detail
  - evaluations
```
protected final Incrementor evaluations
```
    Deprecated.
    
    Evaluations counter.
- Constructor Detail
  - BaseAbstractMultivariateVectorOptimizer
```
@Deprecated
protected BaseAbstractMultivariateVectorOptimizer()
```
    Deprecated. See SimpleVectorValueChecker.SimpleVectorValueChecker()
    
    Simple constructor with default settings. The convergence check is set to a SimpleVectorValueChecker.
  - BaseAbstractMultivariateVectorOptimizer
```
protected BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)
```
    Deprecated.
    
    Parameters:
    checker - Convergence checker.
- Method Detail
  - getMaxEvaluations
```
public int getMaxEvaluations()
```
    Deprecated.
    
    Get the maximal number of function evaluations.
    
    Specified by:
    
    getMaxEvaluations in interface BaseOptimizer<PointVectorValuePair>
    
    Returns:
    the maximal number of function evaluations.
  - getEvaluations
```
public int getEvaluations()
```
    Deprecated.
    
    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 BaseOptimizer<PointVectorValuePair>
    
    Returns:
    the number of evaluations of the objective function.
  - getConvergenceChecker
```
public ConvergenceChecker<PointVectorValuePair> getConvergenceChecker()
```
    Deprecated.
    
    Get the convergence checker.
    
    Specified by:
    
    getConvergenceChecker in interface BaseOptimizer<PointVectorValuePair>
    
    Returns:
    the object used to check for convergence.
  - computeObjectiveValue
```
protected double[] computeObjectiveValue(double[] point)
```
    Deprecated.
    
    Compute the objective function value.
    
    Parameters:
    point - 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.
  - optimize
```
@Deprecated
public PointVectorValuePair optimize(int maxEval,
                                       FUNC f,
                                       double[] t,
                                       double[] w,
                                       double[] startPoint)
```
    Deprecated. As of 3.1. Please use optimize(int,MultivariateVectorFunction,OptimizationData[]) instead.
    
    Optimize an objective function. Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weight_i(objective_i - target_i)²
    
    Specified by:
    
    optimize in interface BaseMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>
    
    Parameters:
    maxEval - Maximum number of function evaluations.
    f - Objective function.
    t - Target value for the objective functions at optimum.
    w - Weights for the least squares cost computation.
    startPoint - Start point for optimization.
    
    Returns:
    the point/value pair giving the optimal value for objective function.
  - optimize
```
protected PointVectorValuePair optimize(int maxEval,
                            FUNC f,
                            OptimizationData... optData)
                                 throws TooManyEvaluationsException,
                                        DimensionMismatchException
```
    Deprecated.
    
    Optimize an objective function.
    Parameters:
    maxEval - Allowed number of evaluations of the objective function.
    f - Objective function.
    optData - Optimization data. The following data will be looked for:
    
    Target
    
    Weight
    
    InitialGuess
    Returns:
    the point/value pair giving the optimal value of the objective function.
    
    Throws:
    
    TooManyEvaluationsException - if the maximal number of evaluations is exceeded.
    
    DimensionMismatchException - if the initial guess, target, and weight arguments have inconsistent dimensions.
    Since:
    
    3.1
  - optimizeInternal
```
@Deprecated
protected PointVectorValuePair optimizeInternal(int maxEval,
                                               FUNC f,
                                               double[] t,
                                               double[] w,
                                               double[] startPoint)
```
    Deprecated. As of 3.1. Please use optimizeInternal(int,MultivariateVectorFunction,OptimizationData[]) instead.
    
    Optimize an objective function. Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weight_i(objective_i - target_i)²
    
    Parameters:
    f - Objective function.
    t - Target value for the objective functions at optimum.
    w - Weights for the least squares cost computation.
    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.
  - optimizeInternal
```
protected PointVectorValuePair optimizeInternal(int maxEval,
                                    FUNC f,
                                    OptimizationData... optData)
                                         throws TooManyEvaluationsException,
                                                DimensionMismatchException
```
    Deprecated.
    
    Optimize an objective function.
    Parameters:
    maxEval - Allowed number of evaluations of the objective function.
    f - Objective function.
    optData - Optimization data. The following data will be looked for:
    
    Target
    
    Weight
    
    InitialGuess
    Returns:
    the point/value pair giving the optimal value of the objective function.
    
    Throws:
    
    TooManyEvaluationsException - if the maximal number of evaluations is exceeded.
    
    DimensionMismatchException - if the initial guess, target, and weight arguments have inconsistent dimensions.
    Since:
    
    3.1
  - getStartPoint
```
public double[] getStartPoint()
```
    Deprecated.
    
    Gets the initial values of the optimized parameters.
    
    Returns:
    the initial guess.
  - getWeight
```
public RealMatrix getWeight()
```
    Deprecated.
    
    Gets the weight matrix of the observations.
    
    Returns:
    the weight matrix.
    Since:
    
    3.1
  - getTarget
```
public double[] getTarget()
```
    Deprecated.
    
    Gets the observed values to be matched by the objective vector function.
    
    Returns:
    the target values.
    Since:
    
    3.1
  - getObjectiveFunction
```
protected FUNC getObjectiveFunction()
```
    Deprecated.
    
    Gets the objective vector function. Note that this access bypasses the evaluation counter.
    
    Returns:
    the objective vector function.
    Since:
    
    3.1
  - doOptimize
```
protected abstract PointVectorValuePair doOptimize()
```
    Deprecated.
    
    Perform the bulk of the optimization algorithm.
    
    Returns:
    the point/value pair giving the optimal value for the objective function.
  - getTargetRef
```
@Deprecated
protected double[] getTargetRef()
```
    Deprecated. As of 3.1.
    
    Returns:
    a reference to the array.
  - getWeightRef
```
@Deprecated
protected double[] getWeightRef()
```
    Deprecated. As of 3.1.
    
    Returns:
    a reference to the array.
  - setUp
```
protected void setUp()
```
    Deprecated.
    
    Method which a subclass must override whenever its internal state depend on the input parsed by this base class. It will be called after the parsing step performed in the optimize method and just before doOptimize().
    
    Since:
    
    3.1

Class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

evaluations

Constructor Detail

BaseAbstractMultivariateVectorOptimizer

BaseAbstractMultivariateVectorOptimizer

Method Detail

getMaxEvaluations

getEvaluations

getConvergenceChecker

computeObjectiveValue

optimize

optimize

optimizeInternal

optimizeInternal

getStartPoint

getWeight

getTarget

getObjectiveFunction

doOptimize

getTargetRef

getWeightRef

setUp