org.apache.commons.math3.optim.nonlinear.scalar
Class GradientMultivariateOptimizer

java.lang.Object
  org.apache.commons.math3.optim.BaseOptimizer<PAIR>
      org.apache.commons.math3.optim.BaseMultivariateOptimizer<PointValuePair>
          org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
              org.apache.commons.math3.optim.nonlinear.scalar.GradientMultivariateOptimizer

Direct Known Subclasses:

NonLinearConjugateGradientOptimizer

public abstract class GradientMultivariateOptimizer
extends MultivariateOptimizer

Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.

Since:

3.1

Version:

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

GradientMultivariateOptimizer

protected GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)

Parameters:

checker - Convergence checker.

computeObjectiveGradient

protected double[] computeObjectiveGradient(double[] params)

Compute the gradient vector.

Parameters:

params - Point at which the gradient must be evaluated.

Returns:

the gradient at the specified point.

optimize

public PointValuePair optimize(OptimizationData... optData)
                        throws TooManyEvaluationsException

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 MultivariateOptimizer

Parameters:

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

• ObjectiveFunctionGradient

Returns:

a point/value pair that satifies the convergence criteria.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations (of the objective function) is exceeded.

parseOptimizationData

protected void parseOptimizationData(OptimizationData... optData)

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

Overrides:

parseOptimizationData in class MultivariateOptimizer

Parameters:

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

• ObjectiveFunctionGradient