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

java.lang.Object
  extended by org.apache.commons.math3.optim.BaseOptimizer<PAIR>
      extended by org.apache.commons.math3.optim.BaseMultivariateOptimizer<PointVectorValuePair>
          extended by 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 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.
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
 

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:
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:


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