itk::AmoebaOptimizer Class Reference
[Numerics, Optimizers]

Wrap of the vnl_amoeba algorithm. More...

#include <itkAmoebaOptimizer.h>

Inheritance diagram for itk::AmoebaOptimizer:

[legend]Collaboration diagram for itk::AmoebaOptimizer:

[legend]List of all members.

Public Types
typedef AmoebaOptimizer	Self
typedef SingleValuedNonLinearVnlOptimizer	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::ParametersType	ParametersType
typedef vnl_vector< double >	InternalParametersType
typedef vnl_amoeba	InternalOptimizerType
Public Member Functions
virtual const char *	GetNameOfClass () const
vnl_amoeba *	GetOptimizer (void)
void	StartOptimization (void)
virtual void	SetCostFunction (SingleValuedCostFunction *costFunction)
MeasureType	GetValue () const
virtual void	SetMaximumNumberOfIterations (unsigned int n)
virtual unsigned int	GetMaximumNumberOfIterations ()
virtual void	SetAutomaticInitialSimplex (bool _arg)
virtual void	AutomaticInitialSimplexOn ()
virtual void	AutomaticInitialSimplexOff ()
virtual bool	GetAutomaticInitialSimplex ()
virtual void	SetInitialSimplexDelta (ParametersType _arg)
virtual ParametersType	GetInitialSimplexDelta ()
virtual void	SetParametersConvergenceTolerance (double tol)
virtual double	GetParametersConvergenceTolerance ()
virtual void	SetFunctionConvergenceTolerance (double tol)
virtual double	GetFunctionConvergenceTolerance ()
Static Public Member Functions
Pointer	New ()
Protected Types
typedef Superclass::CostFunctionAdaptorType	CostFunctionAdaptorType
Protected Member Functions
	AmoebaOptimizer ()
virtual	~AmoebaOptimizer ()
void	PrintSelf (std::ostream &os, Indent indent) const

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Detailed Description

Wrap of the vnl_amoeba algorithm.

AmoebaOptimizer is a wrapper around the vnl_amoeba algorithm which is an implementation of the Nelder-Meade downhill simplex problem. For most problems, it is a few times slower than a Levenberg-Marquardt algorithm but does not require derivatives of its cost function. It works by creating a simplex (n+1 points in ND space). The cost function is evaluated at each corner of the simplex. The simplex is then modified (by reflecting a corner about the opposite edge, by shrinking the entire simplex, by contracting one edge of the simplex, or by expanding the simplex) in searching for the minimum of the cost function.

The methods AutomaticInitialSimplex() and SetInitialSimplexDelta() control whether the optimizer defines the initial simplex automatically (by constructing a very small simplex around the initial position) or uses a user supplied simplex size.

AmoebaOptimizer can only minimize a function.

Definition at line 49 of file itkAmoebaOptimizer.h.

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Member Typedef Documentation

typedef SmartPointer<const Self> itk::AmoebaOptimizer::ConstPointer

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer. Definition at line 57 of file itkAmoebaOptimizer.h.

typedef Superclass::CostFunctionAdaptorType itk::AmoebaOptimizer::CostFunctionAdaptorType [protected]

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer. Definition at line 132 of file itkAmoebaOptimizer.h.

typedef vnl_amoeba itk::AmoebaOptimizer::InternalOptimizerType

Internal optimizer type. Definition at line 73 of file itkAmoebaOptimizer.h.

typedef vnl_vector<double> itk::AmoebaOptimizer::InternalParametersType

InternalParameters typedef. Definition at line 70 of file itkAmoebaOptimizer.h.

typedef Superclass::ParametersType itk::AmoebaOptimizer::ParametersType

Parameters type. It defines a position in the optimization search space. Reimplemented from itk::SingleValuedNonLinearOptimizer. Definition at line 67 of file itkAmoebaOptimizer.h.

typedef SmartPointer<Self> itk::AmoebaOptimizer::Pointer

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer. Definition at line 56 of file itkAmoebaOptimizer.h.

typedef AmoebaOptimizer itk::AmoebaOptimizer::Self

Standard "Self" typedef. Reimplemented from itk::SingleValuedNonLinearVnlOptimizer. Definition at line 54 of file itkAmoebaOptimizer.h.

typedef SingleValuedNonLinearVnlOptimizer itk::AmoebaOptimizer::Superclass

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer. Definition at line 55 of file itkAmoebaOptimizer.h.

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Constructor & Destructor Documentation

itk::AmoebaOptimizer::AmoebaOptimizer (   )  [protected]

virtual itk::AmoebaOptimizer::~AmoebaOptimizer (   )  [protected, virtual]

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Member Function Documentation

virtual void itk::AmoebaOptimizer::AutomaticInitialSimplexOff (   )  [virtual]

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual void itk::AmoebaOptimizer::AutomaticInitialSimplexOn (   )  [virtual]

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual bool itk::AmoebaOptimizer::GetAutomaticInitialSimplex (   )  [virtual]

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual double itk::AmoebaOptimizer::GetFunctionConvergenceTolerance (   )  [virtual]

The optimization algorithm will terminate when the simplex diameter and the difference in cost function at the corners of the simplex falls below user specified thresholds. The simplex diameter threshold is set via method SetParametersConvergenceTolerance() with the default value being 1e-8. The cost function convergence threshold is set via method SetFunctionConvergenceTolerance() with the default value being 1e-4.

virtual ParametersType itk::AmoebaOptimizer::GetInitialSimplexDelta (   )  [virtual]

Set/Get the deltas that are used to define the initial simplex when AutomaticInitialSimplex is off.

virtual unsigned int itk::AmoebaOptimizer::GetMaximumNumberOfIterations (   )  [virtual]

Set/Get the maximum number of iterations. The optimization algorithm will terminate after the maximum number of iterations has been reached. The default value is 500.

virtual const char* itk::AmoebaOptimizer::GetNameOfClass (   )  const [virtual]

Run-time type information (and related methods). Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

vnl_amoeba* itk::AmoebaOptimizer::GetOptimizer (  void   )

Method for getting access to the internal optimizer.

virtual double itk::AmoebaOptimizer::GetParametersConvergenceTolerance (   )  [virtual]

The optimization algorithm will terminate when the simplex diameter and the difference in cost function at the corners of the simplex falls below user specified thresholds. The simplex diameter threshold is set via method SetParametersConvergenceTolerance() with the default value being 1e-8. The cost function convergence threshold is set via method SetFunctionConvergenceTolerance() with the default value being 1e-4.

MeasureType itk::AmoebaOptimizer::GetValue (   )  const

Return Current Value

Pointer itk::AmoebaOptimizer::New (   )  [static]

Method for creation through the object factory. Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::AmoebaOptimizer::PrintSelf (  std::ostream &  os, Indent  indent )  const [protected, virtual]

Print out internal state Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

virtual void itk::AmoebaOptimizer::SetAutomaticInitialSimplex (  bool  _arg  )  [virtual]

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual void itk::AmoebaOptimizer::SetCostFunction (  SingleValuedCostFunction *  costFunction  )  [virtual]

Plug in a Cost Function into the optimizer Implements itk::SingleValuedNonLinearVnlOptimizer.

virtual void itk::AmoebaOptimizer::SetFunctionConvergenceTolerance (  double  tol  )  [virtual]

The optimization algorithm will terminate when the simplex diameter and the difference in cost function at the corners of the simplex falls below user specified thresholds. The simplex diameter threshold is set via method SetParametersConvergenceTolerance() with the default value being 1e-8. The cost function convergence threshold is set via method SetFunctionConvergenceTolerance() with the default value being 1e-4.

virtual void itk::AmoebaOptimizer::SetInitialSimplexDelta (  ParametersType  _arg  )  [virtual]

Set/Get the deltas that are used to define the initial simplex when AutomaticInitialSimplex is off.

virtual void itk::AmoebaOptimizer::SetMaximumNumberOfIterations (  unsigned int  n  )  [virtual]

Set/Get the maximum number of iterations. The optimization algorithm will terminate after the maximum number of iterations has been reached. The default value is 500.

virtual void itk::AmoebaOptimizer::SetParametersConvergenceTolerance (  double  tol  )  [virtual]

The optimization algorithm will terminate when the simplex diameter and the difference in cost function at the corners of the simplex falls below user specified thresholds. The simplex diameter threshold is set via method SetParametersConvergenceTolerance() with the default value being 1e-8. The cost function convergence threshold is set via method SetFunctionConvergenceTolerance() with the default value being 1e-4.

void itk::AmoebaOptimizer::StartOptimization (  void   )  [virtual]

Start optimization with an initial value. Reimplemented from itk::Optimizer.

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The documentation for this class was generated from the following file:

• itkAmoebaOptimizer.h

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