Top Description Fields Constructors Methods
org.apache.commons.math3.optim.nonlinear.scalar

public abstract Class GradientMultivariateOptimizer

extends MultivariateOptimizer
Class Inheritance
Known Direct Subclasses
org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer
Imports
org.apache.commons.math3.analysis.MultivariateVectorFunction, org.apache.commons.math3.optim.ConvergenceChecker, .OptimizationData, .PointValuePair, org.apache.commons.math3.exception.TooManyEvaluationsException

Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.
Since
3.1

Field Summary

Modifier and TypeField and Description
private MultivariateVectorFunction
gradient

Gradient of the objective function.

Constructor Summary

AccessConstructor and Description
protected

Method Summary

Modifier and TypeMethod and Description
protected double[]

Returns:

the gradient at the specified point.
computeObjectiveGradient
(final double[]
Point at which the gradient must be evaluated.
params
)

Compute the gradient vector.

public PointValuePair

Returns:

a point/value pair that satisfies the convergence criteria.
optimize
(OptimizationData...
Optimization data. In addition to those documented in MultivariateOptimizer, this method will register the following data:
optData
)

Overrides org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer.optimize.

Stores data and performs the optimization.

protected void
parseOptimizationData(OptimizationData...
Optimization data. The following data will be looked for:
optData
)

Overrides org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer.parseOptimizationData.

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

Inherited from org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer:
computeObjectiveValuegetGoalType

Field Detail

gradientback to summary
private MultivariateVectorFunction gradient

Gradient of the objective function.

Constructor Detail

GradientMultivariateOptimizerback to summary
protected GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)
Parameters
checker:ConvergenceChecker<PointValuePair>

Convergence checker.

Method Detail

computeObjectiveGradientback to summary
protected double[] computeObjectiveGradient(final double[] params)

Compute the gradient vector.

Parameters
params:double[]

Point at which the gradient must be evaluated.

Returns:double[]

the gradient at the specified point.

optimizeback to summary
public PointValuePair optimize(OptimizationData... optData) throws TooManyEvaluationsException

Overrides org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer.optimize.

Doc from org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer.optimize.

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 parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

Parameters
optData:OptimizationData[]

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

Returns:PointValuePair

a point/value pair that satisfies the convergence criteria.

Annotations
@Override
Exceptions
TooManyEvaluationsException:
if the maximal number of evaluations (of the objective function) is exceeded.
parseOptimizationDataback to summary
protected void parseOptimizationData(OptimizationData... optData)

Overrides org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer.parseOptimizationData.

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

Parameters
optData:OptimizationData[]

Optimization data. The following data will be looked for:

Annotations
@Override