org.apache.commons.math3.optimization.general
Class AbstractScalarDifferentiableOptimizer

java.lang.Object
  extended by org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
      extended by org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer
All Implemented Interfaces:
BaseMultivariateOptimizer<DifferentiableMultivariateFunction>, BaseOptimizer<PointValuePair>, DifferentiableMultivariateOptimizer
Direct Known Subclasses:
NonLinearConjugateGradientOptimizer

Deprecated. As of 3.1 (to be removed in 4.0).

@Deprecated
public abstract class AbstractScalarDifferentiableOptimizer
extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
implements DifferentiableMultivariateOptimizer

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

Since:
2.0
Version:
$Id: AbstractScalarDifferentiableOptimizer.java 1422230 2012-12-15 12:11:13Z erans $

Field Summary
 
Fields inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
evaluations
 
Constructor Summary
protected AbstractScalarDifferentiableOptimizer()
          Deprecated. See SimpleValueChecker.SimpleValueChecker()
protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker)
          Deprecated.  
 
Method Summary
protected  double[] computeObjectiveGradient(double[] evaluationPoint)
          Deprecated. Compute the gradient vector.
 PointValuePair optimize(int maxEval, MultivariateDifferentiableFunction f, GoalType goalType, double[] startPoint)
          Deprecated. Optimize an objective function.
protected  PointValuePair optimizeInternal(int maxEval, DifferentiableMultivariateFunction f, GoalType goalType, double[] startPoint)
          Deprecated. Optimize an objective function.
 
Methods inherited from class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
computeObjectiveValue, doOptimize, getConvergenceChecker, getEvaluations, getGoalType, getLowerBound, getMaxEvaluations, getStartPoint, getUpperBound, optimize, optimize, optimizeInternal
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface org.apache.commons.math3.optimization.BaseMultivariateOptimizer
optimize
 
Methods inherited from interface org.apache.commons.math3.optimization.BaseOptimizer
getConvergenceChecker, getEvaluations, getMaxEvaluations
 

Constructor Detail

AbstractScalarDifferentiableOptimizer

@Deprecated
protected AbstractScalarDifferentiableOptimizer()
Deprecated. See SimpleValueChecker.SimpleValueChecker()

Simple constructor with default settings. The convergence check is set to a SimpleValueChecker.


AbstractScalarDifferentiableOptimizer

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

computeObjectiveGradient

protected double[] computeObjectiveGradient(double[] evaluationPoint)
Deprecated. 
Compute the gradient vector.

Parameters:
evaluationPoint - Point at which the gradient must be evaluated.
Returns:
the gradient at the specified point.
Throws:
TooManyEvaluationsException - if the allowed number of evaluations is exceeded.

optimizeInternal

protected PointValuePair optimizeInternal(int maxEval,
                                          DifferentiableMultivariateFunction f,
                                          GoalType goalType,
                                          double[] startPoint)
Deprecated. 
Optimize an objective function.

Overrides:
optimizeInternal in class BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
Parameters:
maxEval - Maximum number of function evaluations.
f - Objective function.
goalType - Type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE.
startPoint - Start point for optimization.
Returns:
the point/value pair giving the optimal value for objective function.

optimize

public PointValuePair optimize(int maxEval,
                               MultivariateDifferentiableFunction f,
                               GoalType goalType,
                               double[] startPoint)
Deprecated. 
Optimize an objective function.

Parameters:
f - Objective function.
goalType - Type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE.
startPoint - Start point for optimization.
maxEval - Maximum number of function evaluations.
Returns:
the point/value pair giving the optimal value for objective function.
Throws:
DimensionMismatchException - if the start point dimension is wrong.
TooManyEvaluationsException - if the maximal number of evaluations is exceeded.
NullArgumentException - if any argument is null.


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