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itk::AmoebaOptimizer Class Reference
[NumericsOptimizers]

Wrap of the vnl_amoeba algorithm. More...

#include <itkAmoebaOptimizer.h>

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List of all members.

Public Types

typedef ReceptorMemberCommand
< Self
CommandType
typedef SmartPointer< const SelfConstPointer
typedef CostFunctionType::Pointer CostFunctionPointer
typedef SingleValuedCostFunction CostFunctionType
typedef
CostFunctionType::DerivativeType 
DerivativeType
typedef vnl_amoeba InternalOptimizerType
typedef vnl_vector< double > InternalParametersType
typedef
CostFunctionType::MeasureType 
MeasureType
typedef Superclass::ParametersType ParametersType
typedef SmartPointer< SelfPointer
typedef Superclass::ScalesType ScalesType
typedef AmoebaOptimizer Self
typedef
SingleValuedNonLinearVnlOptimizer 
Superclass

Public Member Functions

virtual LightObject::Pointer CreateAnother () const
virtual void DebugOff () const
virtual void DebugOn () const
virtual void Delete ()
CommandGetCommand (unsigned long tag)
virtual const CostFunctionTypeGetCostFunction ()
virtual const ParametersTypeGetCurrentPosition ()
bool GetDebug () const
virtual const ParametersTypeGetInitialPosition ()
const MetaDataDictionaryGetMetaDataDictionary (void) const
MetaDataDictionaryGetMetaDataDictionary (void)
virtual unsigned long GetMTime () const
virtual const char * GetNameOfClass () const
vnl_amoeba * GetOptimizer (void)
virtual int GetReferenceCount () const
virtual const ScalesTypeGetScales ()
const std::string GetStopConditionDescription () const
MeasureType GetValue (const ParametersType &parameters) const
MeasureType GetValue () const
bool HasObserver (const EventObject &event) const
void InvokeEvent (const EventObject &)
void InvokeEvent (const EventObject &) const
virtual void Modified () const
void Print (std::ostream &os, Indent indent=0) const
virtual void Register () const
void RemoveAllObservers ()
void RemoveObserver (unsigned long tag)
virtual void SetCostFunction (CostFunctionType *costFunction)
virtual void SetCostFunction (SingleValuedCostFunction *costFunction)
void SetDebug (bool debugFlag) const
virtual void SetInitialPosition (const ParametersType &param)
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void SetReferenceCount (int)
void SetScales (const ScalesType &scales)
void StartOptimization (void)
virtual void UnRegister () const

virtual void SetMaximumNumberOfIterations (unsigned int n)
virtual unsigned int GetMaximumNumberOfIterations () const

virtual void SetAutomaticInitialSimplex (bool _arg)
virtual void AutomaticInitialSimplexOn ()
virtual void AutomaticInitialSimplexOff ()
virtual bool GetAutomaticInitialSimplex () const

virtual void SetInitialSimplexDelta (ParametersType _arg)
virtual ParametersType GetInitialSimplexDelta () const

virtual void SetParametersConvergenceTolerance (double tol)
virtual double GetParametersConvergenceTolerance () const
virtual void SetFunctionConvergenceTolerance (double tol)
virtual double GetFunctionConvergenceTolerance () const

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 ()

virtual const MeasureTypeGetCachedValue ()
virtual const DerivativeTypeGetCachedDerivative ()
virtual const ParametersTypeGetCachedCurrentPosition ()

unsigned long AddObserver (const EventObject &event, Command *)
unsigned long AddObserver (const EventObject &event, Command *) const

Static Public Member Functions

static void BreakOnError ()
static Pointer New ()

static void SetGlobalWarningDisplay (bool flag)
static bool GetGlobalWarningDisplay ()
static void GlobalWarningDisplayOn ()
static void GlobalWarningDisplayOff ()

Protected Types

typedef
Superclass::CostFunctionAdaptorType 
CostFunctionAdaptorType

typedef int InternalReferenceCountType

Protected Member Functions

 AmoebaOptimizer ()
const CostFunctionAdaptorTypeGetCostFunctionAdaptor (void) const
CostFunctionAdaptorTypeGetCostFunctionAdaptor (void)
CostFunctionAdaptorTypeGetNonConstCostFunctionAdaptor (void) const
bool PrintObservers (std::ostream &os, Indent indent) const
void PrintSelf (std::ostream &os, Indent indent) const
void SetCostFunctionAdaptor (CostFunctionAdaptorType *adaptor)
virtual void SetCurrentPosition (const ParametersType &param)
virtual ~AmoebaOptimizer ()

virtual void PrintHeader (std::ostream &os, Indent indent) const
virtual void PrintTrailer (std::ostream &os, Indent indent) const

Protected Attributes

CostFunctionPointer m_CostFunction
ParametersType m_CurrentPosition
InternalReferenceCountType m_ReferenceCount
SimpleFastMutexLock m_ReferenceCountLock
bool m_ScalesInitialized

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.


Member Typedef Documentation

Command observer that will interact with the ITK-VNL 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.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 57 of file itkAmoebaOptimizer.h.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 135 of file itkAmoebaOptimizer.h.

Derivative type. It defines a type used to return the cost function derivative.

Definition at line 64 of file itkSingleValuedNonLinearOptimizer.h.

Internal optimizer type.

Definition at line 73 of file itkAmoebaOptimizer.h.

InternalParameters typedef.

Definition at line 70 of file itkAmoebaOptimizer.h.

typedef int itk::LightObject::InternalReferenceCountType [protected, inherited]

Define the type of the reference count according to the target. This allows the use of atomic operations

Definition at line 139 of file itkLightObject.h.

Measure type. It defines a type used to return the cost function value.

Definition at line 60 of file itkSingleValuedNonLinearOptimizer.h.

Parameters type. It defines a position in the optimization search space.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Definition at line 63 of file itkAmoebaOptimizer.h.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 56 of file itkAmoebaOptimizer.h.

Scale type. This array defines scale to be applied to parameters before being evaluated in the cost function. This allows to map to a more convenient space. In particular this is used to normalize parameter spaces in which some parameters have a different dynamic range.

Reimplemented from itk::Optimizer.

Definition at line 52 of file itkNonLinearOptimizer.h.

Standard "Self" typedef.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 54 of file itkAmoebaOptimizer.h.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 55 of file itkAmoebaOptimizer.h.


Constructor & Destructor Documentation

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

Member Function Documentation

unsigned long itk::Object::AddObserver ( const EventObject event,
Command  
) [inherited]

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

unsigned long itk::Object::AddObserver ( const EventObject event,
Command  
) const [inherited]

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

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]].

static void itk::LightObject::BreakOnError (  )  [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

virtual LightObject::Pointer itk::Object::CreateAnother (  )  const [virtual, inherited]
virtual void itk::Object::DebugOff (  )  const [virtual, inherited]

Turn debugging output off.

virtual void itk::Object::DebugOn (  )  const [virtual, inherited]

Turn debugging output on.

virtual void itk::LightObject::Delete (  )  [virtual, inherited]

Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.

virtual bool itk::AmoebaOptimizer::GetAutomaticInitialSimplex (  )  const [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 const ParametersType& itk::SingleValuedNonLinearVnlOptimizer::GetCachedCurrentPosition (  )  [virtual, inherited]

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, inherited]

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, inherited]

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* itk::Object::GetCommand ( unsigned long  tag  )  [inherited]

Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.

virtual const CostFunctionType* itk::SingleValuedNonLinearOptimizer::GetCostFunction (  )  [virtual, inherited]

Get the cost function.

const CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void   )  const [protected, inherited]
CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void   )  [protected, inherited]
virtual const ParametersType& itk::Optimizer::GetCurrentPosition (  )  [virtual, inherited]

Get current position of the optimization.

bool itk::Object::GetDebug (  )  const [inherited]

Get the value of the debug flag.

virtual double itk::AmoebaOptimizer::GetFunctionConvergenceTolerance (  )  const [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.

static bool itk::Object::GetGlobalWarningDisplay (  )  [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

virtual const ParametersType& itk::Optimizer::GetInitialPosition (  )  [virtual, inherited]

Get the position to initialize the optimization.

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

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

virtual const bool& itk::SingleValuedNonLinearVnlOptimizer::GetMaximize (  )  [virtual, inherited]

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 unsigned int itk::AmoebaOptimizer::GetMaximumNumberOfIterations (  )  const [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.

MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void   )  [inherited]
Returns:
A reference to this objects MetaDataDictionary.
Warning:
This reference may be changed.
const MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void   )  const [inherited]
Returns:
A constant reference to this objects MetaDataDictionary.
bool itk::SingleValuedNonLinearVnlOptimizer::GetMinimize (  )  const [inline, inherited]

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 unsigned long itk::Object::GetMTime (  )  const [virtual, inherited]

Return this objects modified time.

Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectRegistrationMethod< TFixedImage, TMovingSpatialObject >, itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage >, itk::PointSetToImageRegistrationMethod< TFixedPointSet, TMovingImage >, itk::PointSetToPointSetRegistrationMethod< TFixedPointSet, TMovingPointSet >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::ImageAdaptor< TImage, TAccessor >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::TransformToDeformationFieldSource< TOutputImage, TTransformPrecisionType >, itk::ImageSpatialObject< TDimension, TPixelType >, itk::MeshSpatialObject< TMesh >, itk::SceneSpatialObject< TSpaceDimension >, itk::SpatialObject< TDimension >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, itk::ImageSpatialObject< TDimension, unsigned char >, itk::SpatialObject< 3 >, and itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >.

Referenced by itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >::GetObjectMTime().

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

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

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

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

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

Method for getting access to the internal optimizer.

virtual double itk::AmoebaOptimizer::GetParametersConvergenceTolerance (  )  const [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 int itk::LightObject::GetReferenceCount (  )  const [inline, virtual, inherited]

Gets the reference count on this object.

Definition at line 106 of file itkLightObject.h.

virtual const ScalesType& itk::Optimizer::GetScales (  )  [virtual, inherited]

Get current parameters scaling.

const std::string itk::AmoebaOptimizer::GetStopConditionDescription (  )  const [virtual]

Report the reason for stopping.

Reimplemented from itk::Optimizer.

MeasureType itk::AmoebaOptimizer::GetValue (  )  const

Return Current Value

MeasureType itk::SingleValuedNonLinearOptimizer::GetValue ( const ParametersType parameters  )  const [inherited]

Get the cost function value at the given parameters.

Reimplemented in itk::SPSAOptimizer.

static void itk::Object::GlobalWarningDisplayOff (  )  [inline, static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Definition at line 100 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn (  )  [inline, static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Definition at line 98 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

bool itk::Object::HasObserver ( const EventObject event  )  const [inherited]

Return true if an observer is registered for this event.

void itk::Object::InvokeEvent ( const EventObject  )  const [inherited]

Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.

void itk::Object::InvokeEvent ( const EventObject  )  [inherited]

Call Execute on all the Commands observing this event id.

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

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, inherited]

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, inherited]

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, inherited]

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.

virtual void itk::Object::Modified (  )  const [virtual, inherited]

Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data.

Reimplemented in itk::NormalizeImageFilter< TInputImage, TOutputImage >, itk::ImageAdaptor< TImage, TAccessor >, itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, TFilter >, itk::GrayscaleDilateImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleErodeImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::MorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, and itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, RankImageFilter< TInputImage, TInputImage, FlatStructuringElement< ::itk::GetImageDimension< TInputImage >::ImageDimension > > >.

Referenced by itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::InsertNarrowBandNode(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBand(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandInnerRadius(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandTotalRadius(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

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

Method for creation through the object factory.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::LightObject::Print ( std::ostream &  os,
Indent  indent = 0 
) const [inherited]

Cause the object to print itself out.

Referenced by itk::WeakPointer< ProcessObject >::Print().

virtual void itk::LightObject::PrintHeader ( std::ostream &  os,
Indent  indent 
) const [protected, virtual, inherited]

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.

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

Print out internal state

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

virtual void itk::LightObject::PrintTrailer ( std::ostream &  os,
Indent  indent 
) const [protected, virtual, inherited]

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.

virtual void itk::Object::Register (  )  const [virtual, inherited]

Increase the reference count (mark as used by another object).

Reimplemented from itk::LightObject.

void itk::Object::RemoveAllObservers (  )  [inherited]

Remove all observers .

void itk::Object::RemoveObserver ( unsigned long  tag  )  [inherited]

Remove the observer with this tag value.

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::SingleValuedNonLinearOptimizer::SetCostFunction ( CostFunctionType costFunction  )  [virtual, inherited]

Set the cost function.

void itk::SingleValuedNonLinearVnlOptimizer::SetCostFunctionAdaptor ( CostFunctionAdaptorType adaptor  )  [protected, inherited]
virtual void itk::Optimizer::SetCurrentPosition ( const ParametersType param  )  [protected, virtual, inherited]

Set the current position.

void itk::Object::SetDebug ( bool  debugFlag  )  const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

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.

static void itk::Object::SetGlobalWarningDisplay ( bool  flag  )  [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

virtual void itk::Optimizer::SetInitialPosition ( const ParametersType param  )  [virtual, inherited]

Set the position to initialize the optimization.

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::SingleValuedNonLinearVnlOptimizer::SetMaximize ( bool  _arg  )  [virtual, inherited]

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::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.

void itk::Object::SetMetaDataDictionary ( const MetaDataDictionary rhs  )  [inherited]
Returns:
Set the MetaDataDictionary
void itk::SingleValuedNonLinearVnlOptimizer::SetMinimize ( bool  v  )  [inline, inherited]

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.

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.

virtual void itk::Object::SetReferenceCount ( int   )  [virtual, inherited]

Sets the reference count (use with care)

Reimplemented from itk::LightObject.

void itk::Optimizer::SetScales ( const ScalesType scales  )  [inherited]

Set current parameters scaling.

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

Start optimization with an initial value.

Reimplemented from itk::Optimizer.

virtual void itk::Object::UnRegister (  )  const [virtual, inherited]

Decrease the reference count (release by another object).

Reimplemented from itk::LightObject.


Member Data Documentation

Definition at line 80 of file itkSingleValuedNonLinearOptimizer.h.

Definition at line 98 of file itkOptimizer.h.

Number of uses of this object by other objects.

Definition at line 144 of file itkLightObject.h.

Mutex lock to protect modification to the reference count

Definition at line 147 of file itkLightObject.h.

bool itk::Optimizer::m_ScalesInitialized [protected, inherited]

Definition at line 93 of file itkOptimizer.h.


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

Generated at Mon Jul 12 2010 20:29:36 for ITK by doxygen 1.7.1 written by Dimitri van Heesch, © 1997-2000