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

java.lang.Object
  extended by org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
All Implemented Interfaces:
DifferentiableMultivariateRealOptimizer
Direct Known Subclasses:
NonLinearConjugateGradientOptimizer, PowellOptimizer

public abstract class AbstractScalarDifferentiableOptimizer
extends Object
implements DifferentiableMultivariateRealOptimizer

Base class for implementing optimizers for multivariate scalar functions.

This base class handles the boilerplate methods associated to thresholds settings, iterations and evaluations counting.

Since:
2.0

Field Summary
static int DEFAULT_MAX_ITERATIONS
          Default maximal number of iterations allowed.
 
Method Summary
 RealConvergenceChecker getConvergenceChecker()
          Get the convergence checker.
 int getEvaluations()
          Get the number of evaluations of the objective function.
 int getGradientEvaluations()
          Get the number of evaluations of the objective function gradient.
 int getIterations()
          Get the number of iterations realized by the algorithm.
 int getMaxEvaluations()
          Get the maximal number of functions evaluations.
 int getMaxIterations()
          Get the maximal number of iterations of the algorithm.
 RealPointValuePair optimize(DifferentiableMultivariateRealFunction f, GoalType goalType, double[] startPoint)
          Optimizes an objective function.
 void setConvergenceChecker(RealConvergenceChecker convergenceChecker)
          Set the convergence checker.
 void setMaxEvaluations(int maxEvaluations)
          Set the maximal number of functions evaluations.
 void setMaxIterations(int maxIterations)
          Set the maximal number of iterations of the algorithm.
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

DEFAULT_MAX_ITERATIONS

public static final int DEFAULT_MAX_ITERATIONS
Default maximal number of iterations allowed.

See Also:
Constant Field Values
Method Detail

setMaxIterations

public void setMaxIterations(int maxIterations)
Set the maximal number of iterations of the algorithm.

Specified by:
setMaxIterations in interface DifferentiableMultivariateRealOptimizer
Parameters:
maxIterations - maximal number of function calls

getMaxIterations

public int getMaxIterations()
Get the maximal number of iterations of the algorithm.

Specified by:
getMaxIterations in interface DifferentiableMultivariateRealOptimizer
Returns:
maximal number of iterations

getIterations

public int getIterations()
Get the number of iterations realized by the algorithm.

The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.

Specified by:
getIterations in interface DifferentiableMultivariateRealOptimizer
Returns:
number of iterations

setMaxEvaluations

public void setMaxEvaluations(int maxEvaluations)
Set the maximal number of functions evaluations.

Specified by:
setMaxEvaluations in interface DifferentiableMultivariateRealOptimizer
Parameters:
maxEvaluations - maximal number of function evaluations

getMaxEvaluations

public int getMaxEvaluations()
Get the maximal number of functions evaluations.

Specified by:
getMaxEvaluations in interface DifferentiableMultivariateRealOptimizer
Returns:
maximal number of functions evaluations

getEvaluations

public int getEvaluations()
Get the number of evaluations of the objective function.

The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.

Specified by:
getEvaluations in interface DifferentiableMultivariateRealOptimizer
Returns:
number of evaluations of the objective function

getGradientEvaluations

public int getGradientEvaluations()
Get the number of evaluations of the objective function gradient.

The number of evaluations corresponds to the last call to the optimize method. It is 0 if the method has not been called yet.

Specified by:
getGradientEvaluations in interface DifferentiableMultivariateRealOptimizer
Returns:
number of evaluations of the objective function gradient

setConvergenceChecker

public void setConvergenceChecker(RealConvergenceChecker convergenceChecker)
Set the convergence checker.

Specified by:
setConvergenceChecker in interface DifferentiableMultivariateRealOptimizer
Parameters:
convergenceChecker - object to use to check for convergence

getConvergenceChecker

public RealConvergenceChecker getConvergenceChecker()
Get the convergence checker.

Specified by:
getConvergenceChecker in interface DifferentiableMultivariateRealOptimizer
Returns:
object used to check for convergence

optimize

public RealPointValuePair optimize(DifferentiableMultivariateRealFunction f,
                                   GoalType goalType,
                                   double[] startPoint)
                            throws FunctionEvaluationException,
                                   OptimizationException,
                                   IllegalArgumentException
Optimizes an objective function.

Specified by:
optimize in interface DifferentiableMultivariateRealOptimizer
Parameters:
f - objective function
goalType - type of optimization goal: either GoalType.MAXIMIZE or GoalType.MINIMIZE
startPoint - the start point for optimization
Returns:
the point/value pair giving the optimal value for objective function
Throws:
FunctionEvaluationException - if the objective function throws one during the search
OptimizationException - if the algorithm failed to converge
IllegalArgumentException - if the start point dimension is wrong


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