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org.apache.commons.math3.optimization.direct
Class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>

java.lang.Object
  extended by 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
Version:
$Id: BaseAbstractMultivariateVectorOptimizer.java 1422230 2012-12-15 12:11:13Z erans $

Field Summary
private  ConvergenceChecker<PointVectorValuePair> checker
          Deprecated. Convergence checker.
protected  Incrementor evaluations
          Deprecated. Evaluations counter.
private  FUNC function
          Deprecated. Objective function.
private  double[] start
          Deprecated. Initial guess.
private  double[] target
          Deprecated. Target value for the objective functions at optimum.
private  double[] weight
          Deprecated.  
private  RealMatrix weightMatrix
          Deprecated. Weight matrix.
 
Constructor Summary
protected BaseAbstractMultivariateVectorOptimizer()
          Deprecated. See SimpleVectorValueChecker.SimpleVectorValueChecker()
protected BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)
          Deprecated.  
 
Method Summary
private  void checkParameters()
          Deprecated. Check parameters consistency.
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.
private  void parseOptimizationData(OptimizationData... optData)
          Deprecated. Scans the list of (required and optional) optimization data that characterize the problem.
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.

checker

private ConvergenceChecker<PointVectorValuePair> checker
Deprecated. 
Convergence checker.

target

private double[] target
Deprecated. 
Target value for the objective functions at optimum.

weightMatrix

private RealMatrix weightMatrix
Deprecated. 
Weight matrix.

weight

private double[] weight
Deprecated. 
Weight for the least squares cost computation.

start

private double[] start
Deprecated. 
Initial guess.

function

private FUNC extends MultivariateVectorFunction function
Deprecated. 
Objective function.

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 ∑weighti(objectivei - targeti)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:
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 ∑weighti(objectivei - targeti)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:
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

parseOptimizationData

private void parseOptimizationData(OptimizationData... optData)
Deprecated. 
Scans the list of (required and optional) optimization data that characterize the problem.

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

checkParameters

private void checkParameters()
Deprecated. 
Check parameters consistency.

Throws:
DimensionMismatchException - if target and weightMatrix have inconsistent dimensions.
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