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itk::LBFGSBOptimizer Class Reference
[NumericsOptimizers]

Limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds. More...

#include <itkLBFGSBOptimizer.h>

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List of all members.

Public Types

typedef Array< long > BoundSelectionType
typedef Array< double > BoundValueType
typedef ReceptorMemberCommand
< Self
CommandType
typedef SmartPointer< const SelfConstPointer
typedef CostFunctionType::Pointer CostFunctionPointer
typedef SingleValuedCostFunction CostFunctionType
typedef
CostFunctionType::DerivativeType 
DerivativeType
typedef vnl_vector< long > InternalBoundSelectionType
typedef vnl_vector< double > InternalBoundValueType
typedef LBFGSBOptimizerHelper InternalOptimizerType
typedef
CostFunctionType::MeasureType 
MeasureType
typedef Superclass::ParametersType ParametersType
typedef SmartPointer< SelfPointer
typedef Superclass::ScalesType ScalesType
typedef LBFGSBOptimizer 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 unsigned int & GetCurrentIteration ()
virtual const ParametersTypeGetCurrentPosition ()
bool GetDebug () const
virtual const double & GetInfinityNormOfProjectedGradient ()
virtual const ParametersTypeGetInitialPosition ()
MetaDataDictionaryGetMetaDataDictionary (void)
const MetaDataDictionaryGetMetaDataDictionary (void) const
virtual unsigned long GetMTime () const
virtual const char * GetNameOfClass () const
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 SetScales (const ScalesType &)
void StartOptimization (void)
virtual void UnRegister () const

virtual void SetTrace (bool flag)
virtual bool GetTrace ()
virtual void TraceOn ()
virtual void TraceOff ()

virtual void SetLowerBound (const BoundValueType &value)
virtual const BoundValueTypeGetLowerBound ()

virtual void SetUpperBound (const BoundValueType &value)
virtual const BoundValueTypeGetUpperBound ()

virtual void SetBoundSelection (const BoundSelectionType &select)
virtual const BoundSelectionTypeGetBoundSelection ()

virtual void SetCostFunctionConvergenceFactor (double)
virtual double GetCostFunctionConvergenceFactor ()

virtual void SetProjectedGradientTolerance (double)
virtual double GetProjectedGradientTolerance ()

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

virtual void SetMaximumNumberOfEvaluations (unsigned int)
virtual unsigned int GetMaximumNumberOfEvaluations ()

virtual void SetMaximumNumberOfCorrections (unsigned int)
virtual unsigned int GetMaximumNumberOfCorrections ()

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

const CostFunctionAdaptorTypeGetCostFunctionAdaptor (void) const
CostFunctionAdaptorTypeGetCostFunctionAdaptor (void)
CostFunctionAdaptorTypeGetNonConstCostFunctionAdaptor (void) const
 LBFGSBOptimizer ()
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 ~LBFGSBOptimizer ()

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

Friends

class LBFGSBOptimizerHelper

Detailed Description

Limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds.

This class is a wrapper for converted fortan code for performing limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds. The algorithm miminizes a nonlinear function f(x) of n variables subject to simple bound constraints of l <= x <= u.

See also the documentation in Numerics/lbfgsb.c

References:

[1] R. H. Byrd, P. Lu and J. Nocedal. A Limited Memory Algorithm for Bound Constrained Optimization, (1995), SIAM Journal on Scientific and Statistical Computing , 16, 5, pp. 1190-1208.

[2] C. Zhu, R. H. Byrd and J. Nocedal. L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization (1997), ACM Transactions on Mathematical Software, Vol 23, Num. 4, pp. 550 - 560.

Definition at line 59 of file itkLBFGSBOptimizer.h.


Member Typedef Documentation

BoundSelection type Use for defining the boundary condition for each variables.

Definition at line 83 of file itkLBFGSBOptimizer.h.

BoundValue type. Use for defining the lower and upper bounds on the variables.

Definition at line 73 of file itkLBFGSBOptimizer.h.

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 67 of file itkLBFGSBOptimizer.h.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 186 of file itkLBFGSBOptimizer.h.

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

Definition at line 64 of file itkSingleValuedNonLinearOptimizer.h.

Internal boundary selection storage type

Definition at line 89 of file itkLBFGSBOptimizer.h.

Internal boundary value storage type

Definition at line 86 of file itkLBFGSBOptimizer.h.

The vnl optimizer

Definition at line 92 of file itkLBFGSBOptimizer.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::NonLinearOptimizer.

Reimplemented in itk::AmoebaOptimizer, itk::FRPROptimizer, itk::PowellOptimizer, and itk::QuaternionRigidTransformGradientDescentOptimizer.

Definition at line 48 of file itkSingleValuedNonLinearOptimizer.h.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 66 of file itkLBFGSBOptimizer.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 64 of file itkLBFGSBOptimizer.h.

Reimplemented from itk::SingleValuedNonLinearVnlOptimizer.

Definition at line 65 of file itkLBFGSBOptimizer.h.


Constructor & Destructor Documentation

itk::LBFGSBOptimizer::LBFGSBOptimizer (  )  [protected]
virtual itk::LBFGSBOptimizer::~LBFGSBOptimizer (  )  [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

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 const BoundSelectionType& itk::LBFGSBOptimizer::GetBoundSelection (  )  [virtual]

Set the boundary condition for each variable, where select[i] = 0 if x[i] is unbounded, = 1 if x[i] has only a lower bound, = 2 if x[i] has both lower and upper bounds, and = 3 if x[1] has only an upper bound

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.

CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void   )  [protected, inherited]
const CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void   )  const [protected, inherited]
virtual double itk::LBFGSBOptimizer::GetCostFunctionConvergenceFactor (  )  [virtual]

Set/Get the CostFunctionConvergenceFactor. Algorithm terminates when the reduction in cost function is less than factor * epsmcj where epsmch is the machine precision. Typical values for factor: 1e+12 for low accuracy; 1e+7 for moderate accuracy and 1e+1 for extremely high accuracy.

virtual const unsigned int& itk::LBFGSBOptimizer::GetCurrentIteration (  )  [virtual]

Get the current iteration number.

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.

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 double& itk::LBFGSBOptimizer::GetInfinityNormOfProjectedGradient (  )  [virtual]

Get the current infinity norm of the project gradient of the cost function.

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

Get the position to initialize the optimization.

virtual const BoundValueType& itk::LBFGSBOptimizer::GetLowerBound (  )  [virtual]

Set the lower bound value for each variable.

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::LBFGSBOptimizer::GetMaximumNumberOfCorrections (  )  [virtual]

Set/Get the MaximumNumberOfCorrections. Default is 5

virtual unsigned int itk::LBFGSBOptimizer::GetMaximumNumberOfEvaluations (  )  [virtual]

Set/Get the MaximumNumberOfEvaluations. Default is 500

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

Set/Get the MaximumNumberOfIterations. Default 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::LBFGSBOptimizer::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

virtual double itk::LBFGSBOptimizer::GetProjectedGradientTolerance (  )  [virtual]

Set/Get the ProjectedGradientTolerance. Algorithm terminates when the project gradient is below the tolerance. Default value is 1e-5.

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::LBFGSBOptimizer::GetStopConditionDescription (  )  const [virtual]

Get the reason for termination

Reimplemented from itk::Optimizer.

virtual bool itk::LBFGSBOptimizer::GetTrace (  )  [virtual]

Set/Get the optimizer trace flag. If set to true, the optimizer prints out information every iteration.

virtual const BoundValueType& itk::LBFGSBOptimizer::GetUpperBound (  )  [virtual]

Set the upper bound value for each variable.

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

Get the cost function value at the given parameters.

Reimplemented in itk::SPSAOptimizer.

MeasureType itk::LBFGSBOptimizer::GetValue (  )  const

Get the current cost function value.

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  )  [inherited]

Call Execute on all the Commands observing this event id.

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.

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::LBFGSBOptimizer::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::LBFGSBOptimizer::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::LBFGSBOptimizer::SetBoundSelection ( const BoundSelectionType select  )  [virtual]

Set the boundary condition for each variable, where select[i] = 0 if x[i] is unbounded, = 1 if x[i] has only a lower bound, = 2 if x[i] has both lower and upper bounds, and = 3 if x[1] has only an upper bound

virtual void itk::LBFGSBOptimizer::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::LBFGSBOptimizer::SetCostFunctionConvergenceFactor ( double   )  [virtual]

Set/Get the CostFunctionConvergenceFactor. Algorithm terminates when the reduction in cost function is less than factor * epsmcj where epsmch is the machine precision. Typical values for factor: 1e+12 for low accuracy; 1e+7 for moderate accuracy and 1e+1 for extremely high accuracy.

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.

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::LBFGSBOptimizer::SetLowerBound ( const BoundValueType value  )  [virtual]

Set the lower bound value for each variable.

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::LBFGSBOptimizer::SetMaximumNumberOfCorrections ( unsigned  int  )  [virtual]

Set/Get the MaximumNumberOfCorrections. Default is 5

virtual void itk::LBFGSBOptimizer::SetMaximumNumberOfEvaluations ( unsigned  int  )  [virtual]

Set/Get the MaximumNumberOfEvaluations. Default is 500

virtual void itk::LBFGSBOptimizer::SetMaximumNumberOfIterations ( unsigned  int  )  [virtual]

Set/Get the MaximumNumberOfIterations. Default 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::LBFGSBOptimizer::SetProjectedGradientTolerance ( double   )  [virtual]

Set/Get the ProjectedGradientTolerance. Algorithm terminates when the project gradient is below the tolerance. Default value is 1e-5.

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

Sets the reference count (use with care)

Reimplemented from itk::LightObject.

void itk::LBFGSBOptimizer::SetScales ( const ScalesType  )  [inline]

This optimizer does not support scaling of the derivatives.

Definition at line 163 of file itkLBFGSBOptimizer.h.

References itkExceptionMacro.

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

Set current parameters scaling.

virtual void itk::LBFGSBOptimizer::SetTrace ( bool  flag  )  [virtual]

Set/Get the optimizer trace flag. If set to true, the optimizer prints out information every iteration.

virtual void itk::LBFGSBOptimizer::SetUpperBound ( const BoundValueType value  )  [virtual]

Set the upper bound value for each variable.

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

Start optimization with an initial value.

Reimplemented from itk::Optimizer.

virtual void itk::LBFGSBOptimizer::TraceOff (  )  [virtual]

Set/Get the optimizer trace flag. If set to true, the optimizer prints out information every iteration.

virtual void itk::LBFGSBOptimizer::TraceOn (  )  [virtual]

Set/Get the optimizer trace flag. If set to true, the optimizer prints out information every iteration.

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

Decrease the reference count (release by another object).

Reimplemented from itk::LightObject.


Friends And Related Function Documentation

friend class LBFGSBOptimizerHelper [friend]

Definition at line 194 of file itkLBFGSBOptimizer.h.


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 23:53:21 for ITK by doxygen 1.7.1 written by Dimitri van Heesch, © 1997-2000