ITK  4.1.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Protected Types | Protected Member Functions | Private Member Functions | Private Attributes
itk::MultipleValuedNonLinearVnlOptimizer Class Reference

#include <itkMultipleValuedNonLinearVnlOptimizer.h>

+ Inheritance diagram for itk::MultipleValuedNonLinearVnlOptimizer:
+ Collaboration diagram for itk::MultipleValuedNonLinearVnlOptimizer:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef Superclass::ParametersType ParametersType
typedef SmartPointer< SelfPointer
typedef
MultipleValuedNonLinearVnlOptimizer 
Self
typedef
MultipleValuedNonLinearOptimizer 
Superclass

Public Member Functions

virtual const char * GetNameOfClass () const
bool GetUseCostFunctionGradient () const
virtual void SetCostFunction (MultipleValuedCostFunction *costFunction)=0
void SetUseCostFunctionGradient (bool)
void UseCostFunctionGradientOff ()
void UseCostFunctionGradientOn ()

Protected Types

typedef
MultipleValuedVnlCostFunctionAdaptor 
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)

Private Attributes

ParametersType m_CachedCurrentPosition
DerivativeType m_CachedDerivative
MeasureType m_CachedValue
CommandType::Pointer m_Command
CostFunctionAdaptorTypem_CostFunctionAdaptor
bool m_UseGradient
virtual const MeasureTypeGetCachedValue ()
virtual const DerivativeTypeGetCachedDerivative ()
virtual const ParametersTypeGetCachedCurrentPosition ()
 MultipleValuedNonLinearVnlOptimizer ()
virtual ~MultipleValuedNonLinearVnlOptimizer ()
typedef ReceptorMemberCommand
< Self
CommandType
 MultipleValuedNonLinearVnlOptimizer (const Self &)
void operator= (const Self &)

Detailed Description

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

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

Definition at line 36 of file itkMultipleValuedNonLinearVnlOptimizer.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 111 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 95 of file itkMultipleValuedNonLinearVnlOptimizer.h.

ParametersType typedef. It defines a position in the optimization search space.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 48 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Standard class typedefs.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 41 of file itkMultipleValuedNonLinearVnlOptimizer.h.


Constructor & Destructor Documentation

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().

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().

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


Member Function Documentation

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().

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().

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

Run-time type information (and related methods).

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

The purpose of this method is to get around the lack of const correctness in vnl cost_functions and optimizers

Callback function for the Command Observer

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

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

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

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

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

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::LevenbergMarquardtOptimizer.

Define if the Cost function should provide a customized Gradient computation or the gradient can be computed internally using a default approach

Definition at line 72 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Definition at line 67 of file itkMultipleValuedNonLinearVnlOptimizer.h.


Member Data Documentation

Definition at line 125 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Definition at line 127 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Definition at line 126 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Definition at line 123 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Definition at line 120 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Definition at line 121 of file itkMultipleValuedNonLinearVnlOptimizer.h.


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