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: MultivariateVectorOptimizer.java 1443444 2013-02-07 12:41:36Z erans $

Field Summary

Fields

Modifier and Type	Field and Description
private MultivariateVectorFunction	model Model function.
private double[]	target Target values for the model function at optimum.
private RealMatrix	weightMatrix Weight matrix.

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

evaluations, iterations

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	MultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)

Method Summary

Methods

Modifier and Type	Method and Description
private void	checkParameters() Check parameters consistency.
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.
protected void	parseOptimizationData(OptimizationData... optData) Scans the list of (required and optional) optimization data that characterize the problem.

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

Field Detail

target

private double[] target

Target values for the model function at optimum.

weightMatrix

private RealMatrix weightMatrix

Weight matrix.

model

private MultivariateVectorFunction model

Model function.

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.
The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.
When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).
Important note: Subclasses must override BaseOptimizer.parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

Overrides:

optimize in class BaseMultivariateOptimizer<PointVectorValuePair>

Parameters:

optData - Optimization data. In addition to those documented in BaseMultivariateOptimizer, this method will register the following data:

• 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.

parseOptimizationData

protected void parseOptimizationData(OptimizationData... optData)

Scans the list of (required and optional) optimization data that characterize the problem.

Overrides:

parseOptimizationData in class BaseMultivariateOptimizer<PointVectorValuePair>

Parameters:

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

• Target
• Weight
• ModelFunction

checkParameters

private void checkParameters()

Check parameters consistency.

Throws:

DimensionMismatchException - if target and weightMatrix have inconsistent dimensions.