fr.cnes.sirius.patrius.math.optim.nonlinear.scalar

Class GradientMultivariateOptimizer

java.lang.Object

fr.cnes.sirius.patrius.math.optim.BaseOptimizer<T>

fr.cnes.sirius.patrius.math.optim.BaseMultivariateOptimizer<PointValuePair>

fr.cnes.sirius.patrius.math.optim.nonlinear.scalar.MultivariateOptimizer

fr.cnes.sirius.patrius.math.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 18108 2017-10-04 06:45:27Z bignon $

Field Summary

Fields inherited from class fr.cnes.sirius.patrius.math.optim.BaseOptimizer

evaluations, iterations

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)

Method Summary

Modifier and Type	Method and Description
protected double[]	computeObjectiveGradient(double[] params) Compute the gradient vector.
PointValuePair	optimize(OptimizationData... optData) Stores data and performs the optimization.

Methods inherited from class fr.cnes.sirius.patrius.math.optim.nonlinear.scalar.MultivariateOptimizer

computeObjectiveValue, getGoalType

Methods inherited from class fr.cnes.sirius.patrius.math.optim.BaseMultivariateOptimizer

getLowerBound, getStartPoint, getUpperBound

Methods inherited from class fr.cnes.sirius.patrius.math.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)

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).

Overrides:

optimize in class MultivariateOptimizer

Parameters:

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

• MaxEval
• InitialGuess
• SimpleBounds
• ObjectiveFunction
• GoalType
• 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.