org.apache.commons.math3.optim.nonlinear.vector
Class MultivariateVectorOptimizer

java.lang.Object
  org.apache.commons.math3.optim.BaseOptimizer<PAIR>
      org.apache.commons.math3.optim.BaseMultivariateOptimizer<PointVectorValuePair>
          org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer

Direct Known Subclasses:

JacobianMultivariateVectorOptimizer

public abstract class MultivariateVectorOptimizer
extends BaseMultivariateOptimizer<PointVectorValuePair>

Base class for a multivariate vector function optimizer.

Since:

3.1

Version:

$Id$

Field Summary

Fields inherited from class org.apache.commons.math3.optim.BaseOptimizer

evaluations, iterations

Constructor Summary

protected

MultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)

Method Summary

protected double[]	computeObjectiveValue(double[] params) Computes the objective function value.
double[]	getTarget() Gets the observed values to be matched by the objective vector function.
int	getTargetSize() Gets the number of observed values.
RealMatrix	getWeight() Gets the weight matrix of the observations.
PointVectorValuePair	optimize(OptimizationData... optData) Stores data and performs the optimization.

Methods inherited from class org.apache.commons.math3.optim.BaseMultivariateOptimizer

getLowerBound, getStartPoint, getUpperBound

Methods inherited from class org.apache.commons.math3.optim.BaseOptimizer

doOptimize, getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementEvaluationCount, incrementIterationCount

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

MultivariateVectorOptimizer

protected MultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)

Parameters:

checker - Convergence checker.

Method Detail

computeObjectiveValue

protected double[] computeObjectiveValue(double[] params)

Computes the objective function value. This method must be called by subclasses to enforce the evaluation counter limit.

Parameters:

params - 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 (of the model vector function) is exceeded.

optimize

public PointVectorValuePair optimize(OptimizationData... optData)
                              throws TooManyEvaluationsException,
                                     DimensionMismatchException

Stores data and performs the optimization.

Overrides:

optimize in class BaseMultivariateOptimizer<PointVectorValuePair>

Parameters:

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

• MaxEval
• InitialGuess
• SimpleBounds
• Target
• Weight
• ModelFunction

Returns:

a point/value pair that satifies the convergence criteria.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.

DimensionMismatchException - if the initial guess, target, and weight arguments have inconsistent dimensions.

getWeight

public RealMatrix getWeight()

Gets the weight matrix of the observations.

Returns:

the weight matrix.

getTarget

public double[] getTarget()

Gets the observed values to be matched by the objective vector function.

Returns:

the target values.

getTargetSize

public int getTargetSize()

Gets the number of observed values.

Returns:

the length of the target vector.