ITK  4.0.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Protected Types | Protected Member Functions | Private Member Functions | Private Attributes
itk::SingleValuedNonLinearVnlOptimizer Class Reference

This class is a base for the Optimization methods that optimize a single valued function. More...

#include <itkSingleValuedNonLinearVnlOptimizer.h>

Inheritance diagram for itk::SingleValuedNonLinearVnlOptimizer:
Collaboration diagram for itk::SingleValuedNonLinearVnlOptimizer:

List of all members.

Public Types

typedef ReceptorMemberCommand
< Self
CommandType
typedef SmartPointer< const SelfConstPointer
typedef SmartPointer< SelfPointer
typedef
SingleValuedNonLinearVnlOptimizer 
Self
typedef
SingleValuedNonLinearOptimizer 
Superclass

Public Member Functions

virtual const char * GetNameOfClass () const
virtual void SetCostFunction (SingleValuedCostFunction *costFunction)=0
virtual const bool & GetMaximize ()
virtual void SetMaximize (bool _arg)
virtual void MaximizeOn ()
virtual void MaximizeOff ()
bool GetMinimize () const
void SetMinimize (bool v)
void MinimizeOn ()
void MinimizeOff ()

Protected Types

typedef
SingleValuedVnlCostFunctionAdaptor 
CostFunctionAdaptorType

Protected Member Functions

const CostFunctionAdaptorTypeGetCostFunctionAdaptor (void) const
CostFunctionAdaptorTypeGetCostFunctionAdaptor (void)
CostFunctionAdaptorTypeGetNonConstCostFunctionAdaptor (void) const
void PrintSelf (std::ostream &os, Indent indent) const
void SetCostFunctionAdaptor (CostFunctionAdaptorType *adaptor)

Private Member Functions

void IterationReport (const EventObject &event)
void operator= (const Self &)
 SingleValuedNonLinearVnlOptimizer (const Self &)

Private Attributes

ParametersType m_CachedCurrentPosition
DerivativeType m_CachedDerivative
MeasureType m_CachedValue
CommandType::Pointer m_Command
CostFunctionAdaptorTypem_CostFunctionAdaptor
bool m_Maximize
virtual const MeasureTypeGetCachedValue ()
virtual const DerivativeTypeGetCachedDerivative ()
virtual const ParametersTypeGetCachedCurrentPosition ()
 SingleValuedNonLinearVnlOptimizer ()
virtual ~SingleValuedNonLinearVnlOptimizer ()

Detailed Description

This class is a base for the Optimization methods that optimize a single valued function.

It is an Adaptor class for optimizers provided by the vnl library

Definition at line 36 of file itkSingleValuedNonLinearVnlOptimizer.h.


Member Typedef Documentation

Command observer that will interact with the ITKVNL cost-function adaptor in order to generate iteration events. This will allow to overcome the limitation of VNL optimizers not offering callbacks for every iteration

Definition at line 48 of file itkSingleValuedNonLinearVnlOptimizer.h.


Constructor & Destructor Documentation

itk::SingleValuedNonLinearVnlOptimizer::SingleValuedNonLinearVnlOptimizer ( ) [protected]

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

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

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

itk::SingleValuedNonLinearVnlOptimizer::SingleValuedNonLinearVnlOptimizer ( const Self ) [private]

Member Function Documentation

virtual const ParametersType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedCurrentPosition ( ) [virtual]

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

virtual const DerivativeType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedDerivative ( ) [virtual]

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

virtual const MeasureType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedValue ( ) [virtual]

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void  ) [protected]
const CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void  ) const [protected]
virtual const bool& itk::SingleValuedNonLinearVnlOptimizer::GetMaximize ( ) [virtual]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

bool itk::SingleValuedNonLinearVnlOptimizer::GetMinimize ( ) const [inline]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 72 of file itkSingleValuedNonLinearVnlOptimizer.h.

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

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, itk::LBFGSBOptimizer, and itk::LBFGSOptimizer.

CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetNonConstCostFunctionAdaptor ( void  ) const [protected]

The purpose of this method is to get around the lack of const-correctness in VNL cost-functions and optimizers

void itk::SingleValuedNonLinearVnlOptimizer::IterationReport ( const EventObject event) [private]

Callback function for the Command Observer

virtual void itk::SingleValuedNonLinearVnlOptimizer::MaximizeOff ( ) [virtual]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

virtual void itk::SingleValuedNonLinearVnlOptimizer::MaximizeOn ( ) [virtual]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

void itk::SingleValuedNonLinearVnlOptimizer::MinimizeOff ( ) [inline]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 78 of file itkSingleValuedNonLinearVnlOptimizer.h.

void itk::SingleValuedNonLinearVnlOptimizer::MinimizeOn ( ) [inline]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 76 of file itkSingleValuedNonLinearVnlOptimizer.h.

void itk::SingleValuedNonLinearVnlOptimizer::operator= ( const Self ) [private]

Types inherited from the superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, itk::LBFGSBOptimizer, and itk::LBFGSOptimizer.

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

Print out internal state

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::AmoebaOptimizer, itk::LBFGSBOptimizer, and itk::LBFGSOptimizer.

virtual void itk::SingleValuedNonLinearVnlOptimizer::SetCostFunction ( SingleValuedCostFunction costFunction) [pure virtual]

Set the cost Function. This method has to be overloaded by derived classes because the CostFunctionAdaptor requires to know the number of parameters at construction time. This number of parameters is obtained at run-time from the itkCostFunction. As a consequence each derived optimizer should construct its own CostFunctionAdaptor when overloading this method

Implemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, itk::LBFGSBOptimizer, and itk::LBFGSOptimizer.

void itk::SingleValuedNonLinearVnlOptimizer::SetCostFunctionAdaptor ( CostFunctionAdaptorType adaptor) [protected]
virtual void itk::SingleValuedNonLinearVnlOptimizer::SetMaximize ( bool  _arg) [virtual]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

void itk::SingleValuedNonLinearVnlOptimizer::SetMinimize ( bool  v) [inline]

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 74 of file itkSingleValuedNonLinearVnlOptimizer.h.


Member Data Documentation

Definition at line 123 of file itkSingleValuedNonLinearVnlOptimizer.h.

Definition at line 125 of file itkSingleValuedNonLinearVnlOptimizer.h.

Definition at line 124 of file itkSingleValuedNonLinearVnlOptimizer.h.

Definition at line 121 of file itkSingleValuedNonLinearVnlOptimizer.h.

Definition at line 117 of file itkSingleValuedNonLinearVnlOptimizer.h.

Definition at line 119 of file itkSingleValuedNonLinearVnlOptimizer.h.


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