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

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

Field Summary
 
Fields inherited from class org.apache.commons.math3.optim.BaseOptimizer
evaluations, iterations
 
Constructor Summary
protected GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)
           
 
Method Summary
protected  double[] computeObjectiveGradient(double[] params)
          Compute the gradient vector.
 PointValuePair 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.nonlinear.scalar.MultivariateOptimizer
computeObjectiveValue, getGoalType
 
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

GradientMultivariateOptimizer

protected GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)
Parameters:
checker - Convergence checker.
Method Detail

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:
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:


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