#include <elxAdaptiveStochasticLBFGS.h>

Detailed Description

template<typename TElastix>
class elastix::AdaptiveStochasticLBFGS< TElastix >

A gradient descent optimizer with an adaptive gain.

This class is a wrap around the AdaptiveStochasticVarianceReducedGradientOptimizer class. It takes care of setting parameters and printing progress information. For more information about the optimization method, please read the documentation of the AdaptiveStochasticVarianceReducedGradientOptimizer class.

This optimizer is very suitable to be used in combination with the Random image sampler, or with the RandomCoordinate image sampler, with the setting (NewSamplesEveryIteration "true"). Much effort has been spent on providing reasonable default values for all parameters, to simplify usage. In most registration problems, good results should be obtained without specifying any of the parameters described below (except the first of course, which defines the optimizer to use).

This optimization method is described in the following references:

[1] Y.Qiao, Z.Sun, B.P.F. Lelieveldt, M.Staring A stochastic quasi-newton method for non-rigid image registration Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 297-304, 2015. http://dx.doi.org/10.1007/978-3-319-24571-3_36

The parameters used in this class are:

Parameters

Optimizer: Select this optimizer as follows:
(Optimizer "AdaptiveStochasticLBFGS")

MaximumNumberOfIterations: The maximum number of iterations in each resolution.
example: (MaximumNumberOfIterations 100 100 50)
Default/recommended value: 500. When you are in a hurry, you may go down to 250 for example. When you have plenty of time, and want to be absolutely sure of the best results, a setting of 2000 is reasonable. In general, 500 gives satisfactory results.

MaximumNumberOfSamplingAttempts: The maximum number of sampling attempts. Sometimes not enough corresponding samples can be drawn, upon which an exception is thrown. With this parameter it is possible to try to draw another set of samples.
example: (MaximumNumberOfSamplingAttempts 10 15 10)
Default value: 0, i.e. just fail immediately, for backward compatibility.

AutomaticParameterEstimation: When this parameter is set to "true", many other parameters are calculated automatically: SP_a, SP_alpha, SigmoidMax, SigmoidMin, and SigmoidScale. In the elastix.log file the actually chosen values for these parameters can be found.
example: (AutomaticParameterEstimation "true")
Default/recommended value: "true". The parameter can be specified for each resolution, or for all resolutions at once.

UseAdaptiveStepSizes: When this parameter is set to "true", the adaptive step size mechanism described in the documentation of itk::AdaptiveStochasticVarianceReducedGradientOptimizer is used. The parameter can be specified for each resolution, or for all resolutions at once.
example: (UseAdaptiveStepSizes "true")
Default/recommend value: "true", because it makes the registration more robust. In case of using a RandomCoordinate sampler, with (UseRandomSampleRegion "true"), the adaptive step size mechanism is turned off, no matter the user setting.

MaximumStepLength: Also called $\delta$ . This parameter can be considered as the maximum voxel displacement between two iterations. The larger this parameter, the more aggressive the optimization. The parameter can be specified for each resolution, or for all resolutions at once.
example: (MaximumStepLength 1.0)
Default: mean voxel spacing of fixed and moving image. This seems to work well in general. This parameter only has influence when AutomaticParameterEstimation is used.

Todo: : this class contains a lot of functional code, which actually does not belong here.

See also: AdaptiveStochasticLBFGS

Definition at line 103 of file elxAdaptiveStochasticLBFGS.h.

Inheritance diagram for elastix::AdaptiveStochasticLBFGS< TElastix >:

Classes
struct	MultiThreaderParameterType

Public Types
using	ConstPointer = itk::SmartPointer<const Self>
using	ITKBaseType = typename Superclass2::ITKBaseType
using	LineOptimizerPointer = LineOptimizerType::Pointer
using	LineOptimizerType = itk::MoreThuenteLineSearchOptimizer
using	LineSearchOptimizerPointer = LineSearchOptimizerType::Pointer
using	LineSearchOptimizerType = itk::LineSearchOptimizer
using	Pointer = itk::SmartPointer<Self>
using	Self = AdaptiveStochasticLBFGS
using	SizeValueType = itk::SizeValueType
using	Superclass1 = AdaptiveStochasticLBFGSOptimizer
using	Superclass2 = OptimizerBase<TElastix>
using	ThreadIdType = unsigned int
Public Types inherited from itk::AdaptiveStochasticLBFGSOptimizer
using	ConstPointer = SmartPointer<const Self>
using	Pointer = SmartPointer<Self>
using	Self = AdaptiveStochasticLBFGSOptimizer
using	Superclass = StandardStochasticGradientOptimizer
Public Types inherited from itk::StandardStochasticGradientOptimizer
using	ConstPointer = SmartPointer<const Self>
using	Pointer = SmartPointer<Self>
using	Self = StandardStochasticGradientOptimizer
enum	StopConditionType
using	Superclass = StochasticGradientDescentOptimizer
Public Types inherited from itk::StochasticGradientDescentOptimizer
using	ConstPointer = SmartPointer<const Self>
using	Pointer = SmartPointer<Self>
using	ScaledCostFunctionPointer
using	ScaledCostFunctionType
using	ScalesType
using	Self = StochasticGradientDescentOptimizer
enum	StopConditionType { MaximumNumberOfIterations , MetricError , MinimumStepSize , InvalidDiagonalMatrix , GradientMagnitudeTolerance , LineSearchError }
using	Superclass = ScaledSingleValuedNonLinearOptimizer
Public Types inherited from itk::ScaledSingleValuedNonLinearOptimizer
using	ConstPointer = SmartPointer<const Self>
using	Pointer = SmartPointer<Self>
using	ScaledCostFunctionPointer = ScaledCostFunctionType::Pointer
using	ScaledCostFunctionType = ScaledSingleValuedCostFunction
using	ScalesType = NonLinearOptimizer::ScalesType
using	Self = ScaledSingleValuedNonLinearOptimizer
using	Superclass = SingleValuedNonLinearOptimizer
Public Types inherited from elastix::OptimizerBase< TElastix >
using	ElastixType
using	ITKBaseType = itk::Optimizer
using	ParametersType = typename ITKBaseType::ParametersType
using	RegistrationType
using	Self = OptimizerBase
using	Superclass = BaseComponentSE<TElastix>
Public Types inherited from elastix::BaseComponentSE< TElastix >
using	ElastixType = TElastix
using	RegistrationType = typename ElastixType::RegistrationBaseType
using	Self = BaseComponentSE
using	Superclass = BaseComponent

Public Member Functions
void	AdvanceOneStep () override
void	AfterEachIteration () override
void	AfterEachResolution () override
void	AfterRegistration () override
void	BeforeEachResolution () override
void	BeforeRegistration () override
	elxClassNameMacro ("AdaptiveStochasticLBFGS")
virtual bool	GetAutomaticLBFGSStepsizeEstimation () const
virtual bool	GetAutomaticParameterEstimation () const
virtual const SizeValueType &	GetMaximumNumberOfSamplingAttempts ()
virtual double	GetMaximumStepLength () const
	ITK_DISALLOW_COPY_AND_MOVE (AdaptiveStochasticLBFGS)
	itkOverrideGetNameOfClassMacro (AdaptiveStochasticLBFGS)
virtual void	LBFGSUpdate ()
void	MetricErrorResponse (itk::ExceptionObject &err) override
void	ResumeOptimization () override
virtual void	SetAutomaticLBFGSStepsizeEstimation (bool _arg)
virtual void	SetAutomaticParameterEstimation (bool _arg)
virtual void	SetMaximumNumberOfSamplingAttempts (SizeValueType _arg)
virtual void	SetMaximumStepLength (double _arg)
void	SetNumberOfWorkUnits (ThreadIdType numberOfThreads)
void	StartOptimization () override
void	StopOptimization () override
Public Member Functions inherited from itk::AdaptiveStochasticLBFGSOptimizer
virtual double	GetSigmoidMax () const
virtual double	GetSigmoidMin () const
virtual double	GetSigmoidScale () const
virtual bool	GetUseAdaptiveStepSizes () const
virtual bool	GetUseSearchDirForAdaptiveStepSize () const
	ITK_DISALLOW_COPY_AND_MOVE (AdaptiveStochasticLBFGSOptimizer)
	itkOverrideGetNameOfClassMacro (AdaptiveStochasticLBFGSOptimizer)
virtual void	SetSigmoidMax (double _arg)
virtual void	SetSigmoidMin (double _arg)
virtual void	SetSigmoidScale (double _arg)
virtual void	SetUseAdaptiveStepSizes (bool _arg)
virtual void	SetUseSearchDirForAdaptiveStepSize (bool _arg)
Public Member Functions inherited from itk::StandardStochasticGradientOptimizer
void	AdvanceOneStep () override
virtual double	GetCurrentTime () const
virtual double	GetInitialTime () const
virtual double	GetParam_A () const
virtual double	GetParam_a () const
virtual double	GetParam_alpha () const
virtual double	GetParam_beta () const
	ITK_DISALLOW_COPY_AND_MOVE (StandardStochasticGradientOptimizer)
	itkOverrideGetNameOfClassMacro (StandardStochasticGradientOptimizer)
virtual void	ResetCurrentTimeToInitialTime ()
virtual void	SetInitialTime (double _arg)
virtual void	SetParam_A (double _arg)
virtual void	SetParam_a (double _arg)
virtual void	SetParam_alpha (double _arg)
virtual void	SetParam_beta (double _arg)
void	StartOptimization () override
Public Member Functions inherited from itk::StochasticGradientDescentOptimizer
virtual unsigned int	GetCurrentInnerIteration () const
virtual unsigned int	GetCurrentIteration () const
virtual const DerivativeType &	GetGradient ()
virtual unsigned int	GetLBFGSMemory () const
virtual const double &	GetLearningRate ()
virtual const unsigned long &	GetNumberOfInnerIterations ()
virtual const unsigned long &	GetNumberOfIterations ()
virtual const DerivativeType &	GetPreviousGradient ()
virtual const ParametersType &	GetPreviousPosition ()
virtual const DerivativeType &	GetSearchDir ()
virtual const StopConditionType &	GetStopCondition ()
virtual const double &	GetValue ()
	ITK_DISALLOW_COPY_AND_MOVE (StochasticGradientDescentOptimizer)
	itkOverrideGetNameOfClassMacro (StochasticGradientDescentOptimizer)
virtual void	MetricErrorResponse (ExceptionObject &err)
virtual void	SetLearningRate (double _arg)
virtual void	SetNumberOfIterations (unsigned long _arg)
void	SetNumberOfWorkUnits (ThreadIdType numberOfThreads)
virtual void	SetPreviousGradient (DerivativeType _arg)
virtual void	SetPreviousPosition (ParametersType _arg)
virtual void	SetUseEigen (bool _arg)
virtual void	SetUseMultiThread (bool _arg)
void	StartOptimization () override
Public Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
const ParametersType &	GetCurrentPosition () const override
virtual bool	GetMaximize () const
virtual const ScaledCostFunctionType *	GetScaledCostFunction ()
virtual const ParametersType &	GetScaledCurrentPosition ()
bool	GetUseScales () const
virtual void	InitializeScales ()
	ITK_DISALLOW_COPY_AND_MOVE (ScaledSingleValuedNonLinearOptimizer)
	itkOverrideGetNameOfClassMacro (ScaledSingleValuedNonLinearOptimizer)
virtual void	MaximizeOff ()
virtual void	MaximizeOn ()
void	SetCostFunction (CostFunctionType *costFunction) override
virtual void	SetMaximize (bool _arg)
virtual void	SetUseScales (bool arg)
Public Member Functions inherited from elastix::OptimizerBase< TElastix >
void	AfterRegistrationBase () override
void	BeforeEachResolutionBase () override
ITKBaseType *	GetAsITKBaseType ()
const ITKBaseType *	GetAsITKBaseType () const
	ITK_DISALLOW_COPY_AND_MOVE (OptimizerBase)
	itkOverrideGetNameOfClassMacro (OptimizerBase)
virtual void	SetCurrentPositionPublic (const ParametersType &param)
virtual void	SetSinusScales (double amplitude, double frequency, unsigned long numberOfParameters)
Public Member Functions inherited from elastix::BaseComponentSE< TElastix >
void	AddTargetCellToIterationInfo (const char *const name)
const Configuration *	GetConfiguration () const
ElastixType *	GetElastix () const
auto &	GetIterationInfoAt (const char *const name)
itk::Statistics::MersenneTwisterRandomVariateGenerator &	GetRandomVariateGenerator ()
RegistrationType *	GetRegistration () const
	ITK_DISALLOW_COPY_AND_MOVE (BaseComponentSE)
void	RemoveTargetCellFromIterationInfo (const char *const name)
void	SetConfiguration (const Configuration *_arg)
void	SetElastix (ElastixType *_arg)
Public Member Functions inherited from elastix::BaseComponent
virtual void	AfterEachIterationBase ()
virtual void	AfterEachResolutionBase ()
virtual int	BeforeAll ()
virtual int	BeforeAllBase ()
virtual void	BeforeRegistrationBase ()
virtual const char *	elxGetClassName () const
const char *	GetComponentLabel () const
	ITK_DISALLOW_COPY_AND_MOVE (BaseComponent)
	itkVirtualGetNameOfClassMacro (BaseComponent)
void	SetComponentLabel (const char *label, unsigned int idx)

Static Public Member Functions
static Pointer	New ()
Static Public Member Functions inherited from itk::AdaptiveStochasticLBFGSOptimizer
static Pointer	New ()
Static Public Member Functions inherited from itk::StandardStochasticGradientOptimizer
static Pointer	New ()
Static Public Member Functions inherited from itk::StochasticGradientDescentOptimizer
static Pointer	New ()
Static Public Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
static Pointer	New ()
Static Public Member Functions inherited from elastix::BaseComponent
template<typename TBaseComponent>
static auto	AsITKBaseType (TBaseComponent *const baseComponent) -> decltype(baseComponent->GetAsITKBaseType())
static void	InitializeElastixExecutable ()
static bool	IsElastixLibrary ()

Protected Types
using	AdvancedTransformType
using	ComputeDisplacementDistributionType = itk::ComputeDisplacementDistribution<FixedImageType, TransformType>
using	CoordinateRepresentationType = typename TransformType::ScalarType
using	DiagonalMatrixType = itk::Array<double>
using	FixedImageIndexType = typename FixedImageType::IndexType
using	FixedImagePointType = typename FixedImageType::PointType
using	FixedImageRegionType = typename FixedImageType::RegionType
using	FixedImageType = typename RegistrationType::FixedImageType
using	ImageGridSamplerPointer = typename ImageGridSamplerType::Pointer
using	ImageGridSamplerType = itk::ImageGridSampler<FixedImageType>
using	ImageRadomSampleContainerPointer = typename ImageRadomSampleContainerType::Pointer
using	ImageRadomSampleContainerType = typename ImageRandomSamplerType::ImageSampleContainerType
using	ImageRandomCoordinateSamplerPointer = typename ImageRandomCoordinateSamplerType::Pointer
using	ImageRandomCoordinateSamplerType = itk::ImageRandomCoordinateSampler<FixedImageType>
using	ImageRandomSamplerBasePointer = typename ImageRandomSamplerBaseType::Pointer
using	ImageRandomSamplerBaseType = itk::ImageRandomSamplerBase<FixedImageType>
using	ImageRandomSamplerPointer = typename ImageRandomSamplerType::Pointer
using	ImageRandomSamplerType = itk::ImageRandomSampler<FixedImageType>
using	ImageSampleContainerPointer = typename ImageSampleContainerType::Pointer
using	ImageSampleContainerType = typename ImageGridSamplerType::ImageSampleContainerType
using	ImageSamplerBasePointer = typename ImageSamplerBaseType::Pointer
using	ImageSamplerBaseType = itk::ImageSamplerBase<FixedImageType>
using	ImageSampleType = typename ImageSamplerBaseType::ImageSampleType
using	itkRegistrationType = typename RegistrationType::ITKBaseType
using	JacobianType = typename TransformType::JacobianType
using	JacobianValueType = typename JacobianType::ValueType
using	MovingImageType = typename RegistrationType::MovingImageType
using	NonZeroJacobianIndicesType = typename AdvancedTransformType::NonZeroJacobianIndicesType
using	RandomGeneratorType = itk::Statistics::MersenneTwisterRandomVariateGenerator
using	RhoType = itk::Array<double>
using	SettingsVectorType
using	SType = std::vector<ParametersType>
using	TransformJacobianType = JacobianType
using	TransformType = typename itkRegistrationType::TransformType
using	YType = std::vector<DerivativeType>
Protected Types inherited from itk::StochasticGradientDescentOptimizer
using	ThreadInfoType = MultiThreaderBase::WorkUnitInfo
Protected Types inherited from elastix::OptimizerBase< TElastix >
using	SettingsVectorType = typename std::vector<SettingsType>

Protected Member Functions
	AdaptiveStochasticLBFGS ()
virtual void	AddRandomPerturbation (ParametersType &parameters, double sigma)
virtual void	AutomaticLBFGSStepsizeEstimation ()
virtual void	AutomaticParameterEstimation ()
virtual void	AutomaticParameterEstimationOriginal ()
virtual void	AutomaticParameterEstimationUsingDisplacementDistribution ()
virtual void	ComputeDiagonalMatrix (DiagonalMatrixType &diag_H0)
virtual void	ComputeSearchDirection (const DerivativeType &gradient, DerivativeType &searchDir)
virtual void	GetScaledDerivativeWithExceptionHandling (const ParametersType &parameters, DerivativeType &derivative)
	itkStaticConstMacro (FixedImageDimension, unsigned int, FixedImageType::ImageDimension)
	itkStaticConstMacro (MovingImageDimension, unsigned int, MovingImageType::ImageDimension)
virtual void	SampleGradients (const ParametersType &mu0, double perturbationSigma, double &gg, double &ee)
virtual void	StoreCurrentPoint (const ParametersType &step, const DerivativeType &grad_dif)
	~AdaptiveStochasticLBFGS () override=default
Protected Member Functions inherited from itk::AdaptiveStochasticLBFGSOptimizer
	AdaptiveStochasticLBFGSOptimizer ()
void	UpdateCurrentTime () override
	~AdaptiveStochasticLBFGSOptimizer () override=default
Protected Member Functions inherited from itk::StandardStochasticGradientOptimizer
virtual double	Compute_a (double k) const
virtual double	Compute_beta (double k) const
	StandardStochasticGradientOptimizer ()
	~StandardStochasticGradientOptimizer () override=default
Protected Member Functions inherited from itk::StochasticGradientDescentOptimizer
void	PrintSelf (std::ostream &os, Indent indent) const override
	StochasticGradientDescentOptimizer ()
	~StochasticGradientDescentOptimizer () override=default
Protected Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
virtual void	GetScaledDerivative (const ParametersType &parameters, DerivativeType &derivative) const
virtual MeasureType	GetScaledValue (const ParametersType &parameters) const
virtual void	GetScaledValueAndDerivative (const ParametersType &parameters, MeasureType &value, DerivativeType &derivative) const
void	PrintSelf (std::ostream &os, Indent indent) const override
	ScaledSingleValuedNonLinearOptimizer ()
void	SetCurrentPosition (const ParametersType &param) override
virtual void	SetScaledCurrentPosition (const ParametersType &parameters)
	~ScaledSingleValuedNonLinearOptimizer () override=default
Protected Member Functions inherited from elastix::OptimizerBase< TElastix >
virtual bool	GetNewSamplesEveryIteration () const
	OptimizerBase ()=default
virtual void	SelectNewSamples ()
	~OptimizerBase () override=default
Protected Member Functions inherited from elastix::BaseComponentSE< TElastix >
	BaseComponentSE ()=default
	~BaseComponentSE () override=default
Protected Member Functions inherited from elastix::BaseComponent
	BaseComponent ()=default
virtual	~BaseComponent ()=default

Protected Attributes
AdvancedTransformType::Pointer	m_AdvancedTransform
unsigned int	m_Bound
unsigned int	m_CurrentT
RhoType	m_HessianFillValue
double	m_NoiseFactor
SizeValueType	m_NumberOfGradientMeasurements
SizeValueType	m_NumberOfJacobianMeasurements
SizeValueType	m_NumberOfSamplesForExactGradient
DerivativeType	m_PreviousCurvatureGradient
unsigned int	m_PreviousT
RhoType	m_Rho
SType	m_S
SettingsVectorType	m_SettingsVector
double	m_SigmoidScaleFactor
double	m_WindowScale
YType	m_Y
Protected Attributes inherited from itk::AdaptiveStochasticLBFGSOptimizer
double	m_SearchLengthScale { 10 }
std::string	m_StepSizeStrategy {}
unsigned long	m_UpdateFrequenceL {}
bool	m_UseAdaptiveStepSizes { true }
bool	m_UseSearchDirForAdaptiveStepSize {}
Protected Attributes inherited from itk::StandardStochasticGradientOptimizer
double	m_CurrentTime { 0.0 }
bool	m_UseConstantStep {}
Protected Attributes inherited from itk::StochasticGradientDescentOptimizer
unsigned long	m_CurrentInnerIteration {}
unsigned long	m_CurrentIteration { 0 }
DerivativeType	m_Gradient {}
unsigned long	m_LBFGSMemory { 0 }
double	m_LearningRate { 1.0 }
ParametersType	m_MeanSearchDir {}
unsigned long	m_NumberOfInnerIterations {}
unsigned long	m_NumberOfIterations { 100 }
DerivativeType	m_PrePreviousGradient {}
ParametersType	m_PrePreviousSearchDir {}
DerivativeType	m_PreviousGradient {}
ParametersType	m_PreviousPosition {}
ParametersType	m_PreviousSearchDir {}
ParametersType	m_SearchDir {}
bool	m_Stop { false }
StopConditionType	m_StopCondition { MaximumNumberOfIterations }
MultiThreaderBase::Pointer	m_Threader { MultiThreaderBase::New() }
double	m_Value { 0.0 }
Protected Attributes inherited from itk::ScaledSingleValuedNonLinearOptimizer
ScaledCostFunctionPointer	m_ScaledCostFunction {}
ParametersType	m_ScaledCurrentPosition {}
Protected Attributes inherited from elastix::BaseComponentSE< TElastix >
Configuration::ConstPointer	m_Configuration {}
itk::WeakPointer< TElastix >	m_Elastix {}
RegistrationType *	m_Registration {}

Private Member Functions
void	ThreadedAdvanceOneStep (ThreadIdType threadId, ParametersType &newPosition)

Static Private Member Functions
static itk::ITK_THREAD_RETURN_TYPE	AdvanceOneStepThreaderCallback (void *arg)

Additional Inherited Members
Static Protected Member Functions inherited from elastix::OptimizerBase< TElastix >
static void	PrintSettingsVector (const SettingsVectorType &settings)

Member Typedef Documentation

◆ AdvancedTransformType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::AdvancedTransformType

protected

Initial value:

itk::AdvancedTransform<CoordinateRepresentationType, Self::FixedImageDimension, Self::MovingImageDimension>

itk::AdvancedTransform

Transform maps points, vectors and covariant vectors from an input space to an output space.

Definition itkAdvancedTransform.h:84

Definition at line 278 of file elxAdaptiveStochasticLBFGS.h.

◆ ComputeDisplacementDistributionType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ComputeDisplacementDistributionType = itk::ComputeDisplacementDistribution<FixedImageType, TransformType>

protected

Definition at line 247 of file elxAdaptiveStochasticLBFGS.h.

◆ ConstPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ConstPointer = itk::SmartPointer<const Self>

Definition at line 115 of file elxAdaptiveStochasticLBFGS.h.

◆ CoordinateRepresentationType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::CoordinateRepresentationType = typename TransformType::ScalarType

protected

Definition at line 277 of file elxAdaptiveStochasticLBFGS.h.

◆ DiagonalMatrixType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::DiagonalMatrixType = itk::Array<double>

protected

Definition at line 286 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImageIndexType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::FixedImageIndexType = typename FixedImageType::IndexType

protected

Definition at line 239 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImagePointType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::FixedImagePointType = typename FixedImageType::PointType

protected

Definition at line 240 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImageRegionType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::FixedImageRegionType = typename FixedImageType::RegionType

protected

Definition at line 238 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImageType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::FixedImageType = typename RegistrationType::FixedImageType

protected

Protected typedefs

Definition at line 235 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageGridSamplerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageGridSamplerPointer = typename ImageGridSamplerType::Pointer

protected

Definition at line 266 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageGridSamplerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageGridSamplerType = itk::ImageGridSampler<FixedImageType>

protected

Image grid sampler.

Definition at line 265 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRadomSampleContainerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRadomSampleContainerPointer = typename ImageRadomSampleContainerType::Pointer

protected

Definition at line 262 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRadomSampleContainerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRadomSampleContainerType = typename ImageRandomSamplerType::ImageSampleContainerType

protected

Definition at line 261 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomCoordinateSamplerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRandomCoordinateSamplerPointer = typename ImageRandomCoordinateSamplerType::Pointer

protected

Definition at line 255 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomCoordinateSamplerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRandomCoordinateSamplerType = itk::ImageRandomCoordinateSampler<FixedImageType>

protected

Definition at line 254 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerBasePointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRandomSamplerBasePointer = typename ImageRandomSamplerBaseType::Pointer

protected

Definition at line 253 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerBaseType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRandomSamplerBaseType = itk::ImageRandomSamplerBase<FixedImageType>

protected

Definition at line 252 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRandomSamplerPointer = typename ImageRandomSamplerType::Pointer

protected

Definition at line 260 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageRandomSamplerType = itk::ImageRandomSampler<FixedImageType>

protected

Image random sampler.

Definition at line 259 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSampleContainerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageSampleContainerPointer = typename ImageSampleContainerType::Pointer

protected

Definition at line 268 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSampleContainerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageSampleContainerType = typename ImageGridSamplerType::ImageSampleContainerType

protected

Definition at line 267 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSamplerBasePointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageSamplerBasePointer = typename ImageSamplerBaseType::Pointer

protected

Definition at line 251 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSamplerBaseType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageSamplerBaseType = itk::ImageSamplerBase<FixedImageType>

protected

Samplers:

Definition at line 250 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSampleType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ImageSampleType = typename ImageSamplerBaseType::ImageSampleType

protected

Definition at line 256 of file elxAdaptiveStochasticLBFGS.h.

◆ ITKBaseType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ITKBaseType = typename Superclass2::ITKBaseType

Definition at line 137 of file elxAdaptiveStochasticLBFGS.h.

◆ itkRegistrationType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::itkRegistrationType = typename RegistrationType::ITKBaseType

protected

Definition at line 241 of file elxAdaptiveStochasticLBFGS.h.

◆ JacobianType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::JacobianType = typename TransformType::JacobianType

protected

Definition at line 243 of file elxAdaptiveStochasticLBFGS.h.

◆ JacobianValueType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::JacobianValueType = typename JacobianType::ValueType

protected

Definition at line 244 of file elxAdaptiveStochasticLBFGS.h.

◆ LineOptimizerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::LineOptimizerPointer = LineOptimizerType::Pointer

Definition at line 151 of file elxAdaptiveStochasticLBFGS.h.

◆ LineOptimizerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::LineOptimizerType = itk::MoreThuenteLineSearchOptimizer

Definition at line 150 of file elxAdaptiveStochasticLBFGS.h.

◆ LineSearchOptimizerPointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::LineSearchOptimizerPointer = LineSearchOptimizerType::Pointer

Definition at line 149 of file elxAdaptiveStochasticLBFGS.h.

◆ LineSearchOptimizerType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::LineSearchOptimizerType = itk::LineSearchOptimizer

Definition at line 147 of file elxAdaptiveStochasticLBFGS.h.

◆ MovingImageType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::MovingImageType = typename RegistrationType::MovingImageType

protected

Definition at line 236 of file elxAdaptiveStochasticLBFGS.h.

◆ NonZeroJacobianIndicesType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::NonZeroJacobianIndicesType = typename AdvancedTransformType::NonZeroJacobianIndicesType

protected

Definition at line 280 of file elxAdaptiveStochasticLBFGS.h.

◆ Pointer

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::Pointer = itk::SmartPointer<Self>

Definition at line 114 of file elxAdaptiveStochasticLBFGS.h.

◆ RandomGeneratorType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::RandomGeneratorType = itk::Statistics::MersenneTwisterRandomVariateGenerator

protected

Other protected typedef

Definition at line 271 of file elxAdaptiveStochasticLBFGS.h.

◆ RhoType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::RhoType = itk::Array<double>

protected

For L-BFGS usage.

Definition at line 283 of file elxAdaptiveStochasticLBFGS.h.

◆ Self

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::Self = AdaptiveStochasticLBFGS

Standard ITK.

Definition at line 111 of file elxAdaptiveStochasticLBFGS.h.

◆ SettingsVectorType

template<typename TElastix>

using elastix::OptimizerBase< TElastix >::SettingsVectorType

protected

Definition at line 133 of file elxOptimizerBase.h.

◆ SizeValueType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::SizeValueType = itk::SizeValueType

Definition at line 138 of file elxAdaptiveStochasticLBFGS.h.

◆ SType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::SType = std::vector<ParametersType>

protected

Definition at line 284 of file elxAdaptiveStochasticLBFGS.h.

◆ Superclass1

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::Superclass1 = AdaptiveStochasticLBFGSOptimizer

Definition at line 112 of file elxAdaptiveStochasticLBFGS.h.

◆ Superclass2

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::Superclass2 = OptimizerBase<TElastix>

Definition at line 113 of file elxAdaptiveStochasticLBFGS.h.

◆ ThreadIdType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::ThreadIdType = unsigned int

Type to count and reference number of threads

Definition at line 224 of file elxAdaptiveStochasticLBFGS.h.

◆ TransformJacobianType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::TransformJacobianType = JacobianType

protected

Typedefs for support of sparse Jacobians and AdvancedTransforms.

Definition at line 274 of file elxAdaptiveStochasticLBFGS.h.

◆ TransformType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::TransformType = typename itkRegistrationType::TransformType

protected

Definition at line 242 of file elxAdaptiveStochasticLBFGS.h.

◆ YType

template<typename TElastix>

using elastix::AdaptiveStochasticLBFGS< TElastix >::YType = std::vector<DerivativeType>

protected

Definition at line 285 of file elxAdaptiveStochasticLBFGS.h.

Constructor & Destructor Documentation

◆ AdaptiveStochasticLBFGS()

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::AdaptiveStochasticLBFGS ( )

protected

◆ ~AdaptiveStochasticLBFGS()

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::~AdaptiveStochasticLBFGS ( )

overrideprotecteddefault

Member Function Documentation

◆ AddRandomPerturbation()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::AddRandomPerturbation	(	ParametersType &	parameters,
		double	sigma )

protectedvirtual

Helper function that adds a random perturbation delta to the input parameters, with delta ~ sigma * N(0,I). Used by SampleGradients.

◆ AdvanceOneStep()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::AdvanceOneStep ( )

overridevirtual

AdvanceOneStep.

Reimplemented from itk::StochasticGradientDescentOptimizer.

◆ AdvanceOneStepThreaderCallback()

template<typename TElastix>

itk::ITK_THREAD_RETURN_TYPE elastix::AdaptiveStochasticLBFGS< TElastix >::AdvanceOneStepThreaderCallback ( void * arg )

staticprivate

The callback function.

◆ AfterEachIteration()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::AfterEachIteration ( )

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ AfterEachResolution()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::AfterEachResolution ( )

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ AfterRegistration()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::AfterRegistration ( )

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ AutomaticLBFGSStepsizeEstimation()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::AutomaticLBFGSStepsizeEstimation ( )

protectedvirtual

◆ AutomaticParameterEstimation()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::AutomaticParameterEstimation ( )

protectedvirtual

Select different method to estimate some reasonable values for the parameters SP_a, SP_alpha (=1), SigmoidMin, SigmoidMax (=1), and SigmoidScale.

◆ AutomaticParameterEstimationOriginal()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::AutomaticParameterEstimationOriginal ( )

protectedvirtual

Original estimation method to get the reasonable values for the parameters SP_a, SP_alpha (=1), SigmoidMin, SigmoidMax (=1), and SigmoidScale.

◆ AutomaticParameterEstimationUsingDisplacementDistribution()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::AutomaticParameterEstimationUsingDisplacementDistribution ( )

protectedvirtual

Estimates some reasonable values for the parameters using displacement distribution SP_a, SP_alpha (=1)

◆ BeforeEachResolution()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::BeforeEachResolution ( )

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ BeforeRegistration()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::BeforeRegistration ( )

overridevirtual

Methods invoked by elastix, in which parameters can be set and progress information can be printed.

Reimplemented from elastix::BaseComponent.

◆ ComputeDiagonalMatrix()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::ComputeDiagonalMatrix ( DiagonalMatrixType & diag_H0 )

protectedvirtual

Compute H0

Override this method if not satisfied with the default choice.

◆ ComputeSearchDirection()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::ComputeSearchDirection	(	const DerivativeType &	gradient,
		DerivativeType &	searchDir )

protectedvirtual

Compute -Hg

COMPUTE -H*G USING THE FORMULA GIVEN IN: Nocedal, J. 1980, "Updating quasi-Newton matrices with limited storage", Mathematics of Computation, Vol.24, No.151, pp. 773-782.

◆ elxClassNameMacro()

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::elxClassNameMacro ( "AdaptiveStochasticLBFGS< TElastix >" )

Name of this class. Use this name in the parameter file to select this specific optimizer. example: (Optimizer "AdaptiveStochasticLBFGS")

◆ GetAutomaticLBFGSStepsizeEstimation()

template<typename TElastix>

virtual bool elastix::AdaptiveStochasticLBFGS< TElastix >::GetAutomaticLBFGSStepsizeEstimation ( ) const

virtual

◆ GetAutomaticParameterEstimation()

template<typename TElastix>

virtual bool elastix::AdaptiveStochasticLBFGS< TElastix >::GetAutomaticParameterEstimation ( ) const

virtual

◆ GetMaximumNumberOfSamplingAttempts()

template<typename TElastix>

virtual const SizeValueType & elastix::AdaptiveStochasticLBFGS< TElastix >::GetMaximumNumberOfSamplingAttempts ( )

virtual

Get the MaximumNumberOfSamplingAttempts.

◆ GetMaximumStepLength()

template<typename TElastix>

virtual double elastix::AdaptiveStochasticLBFGS< TElastix >::GetMaximumStepLength ( ) const

virtual

◆ GetScaledDerivativeWithExceptionHandling()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::GetScaledDerivativeWithExceptionHandling	(	const ParametersType &	parameters,
		DerivativeType &	derivative )

protectedvirtual

Helper function, which calls GetScaledValueAndDerivative and does some exception handling. Used by SampleGradients.

◆ ITK_DISALLOW_COPY_AND_MOVE()

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::ITK_DISALLOW_COPY_AND_MOVE ( AdaptiveStochasticLBFGS< TElastix > )

◆ itkOverrideGetNameOfClassMacro()

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::itkOverrideGetNameOfClassMacro ( AdaptiveStochasticLBFGS< TElastix > )

Run-time type information (and related methods).

◆ itkStaticConstMacro() [1/2]

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::itkStaticConstMacro	(	FixedImageDimension	,
		unsigned int	,
		FixedImageType::ImageDimension	)

protected

◆ itkStaticConstMacro() [2/2]

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::itkStaticConstMacro	(	MovingImageDimension	,
		unsigned int	,
		MovingImageType::ImageDimension	)

protected

◆ LBFGSUpdate()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::LBFGSUpdate ( )

virtual

LBFGS Update step.

◆ MetricErrorResponse()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::MetricErrorResponse ( itk::ExceptionObject & err )

override

Stop optimization and pass on exception.

◆ New()

template<typename TElastix>

Pointer elastix::AdaptiveStochasticLBFGS< TElastix >::New ( )

static

Method for creation through the object factory.

◆ ResumeOptimization()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::ResumeOptimization ( )

overridevirtual

If automatic gain estimation is desired, then estimate SP_a, SP_alpha SigmoidScale, SigmoidMax, SigmoidMin. After that call Superclass' implementation.

Reimplemented from itk::StochasticGradientDescentOptimizer.

◆ SampleGradients()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::SampleGradients	(	const ParametersType &	mu0,
		double	perturbationSigma,
		double &	gg,
		double &	ee )

protectedvirtual

Measure some derivatives, exact and approximated. Returns the squared magnitude of the gradient and approximation error. Needed for the automatic parameter estimation. Gradients are measured at position mu_n, which are generated according to: mu_n - mu_0 ~ N(0, perturbationSigma^2 I ); gg = g^T g, etc.

◆ SetAutomaticLBFGSStepsizeEstimation()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::SetAutomaticLBFGSStepsizeEstimation ( bool _arg )

virtual

Set/Get whether automatic LBFGS step size estimation is desired.

◆ SetAutomaticParameterEstimation()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::SetAutomaticParameterEstimation ( bool _arg )

virtual

Set/Get whether automatic parameter estimation is desired. If true, make sure to set the maximum step length.

The following parameters are automatically determined: SP_a, SP_alpha (=1), SigmoidMin, SigmoidMax (=1), SigmoidScale. A usually suitable value for SP_A is 20, which is the default setting, if not specified by the user.

◆ SetMaximumNumberOfSamplingAttempts()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::SetMaximumNumberOfSamplingAttempts ( SizeValueType _arg )

virtual

Set the MaximumNumberOfSamplingAttempts.

◆ SetMaximumStepLength()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::SetMaximumStepLength ( double _arg )

virtual

Set/Get maximum step length.

◆ SetNumberOfWorkUnits()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::SetNumberOfWorkUnits ( ThreadIdType numberOfThreads )

inline

Set the number of threads.

Definition at line 228 of file elxAdaptiveStochasticLBFGS.h.

◆ StartOptimization()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::StartOptimization ( )

override

Check if any scales are set, and set the UseScales flag on or off; after that call the superclass' implementation.

◆ StopOptimization()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::StopOptimization ( )

overridevirtual

Stop optimization.

See also: StopOptimization

Reimplemented from itk::StochasticGradientDescentOptimizer.

◆ StoreCurrentPoint()

template<typename TElastix>

virtual void elastix::AdaptiveStochasticLBFGS< TElastix >::StoreCurrentPoint	(	const ParametersType &	step,
		const DerivativeType &	grad_dif )

protectedvirtual

Store s = x_k - x_k-1 and y = g_k - g_k-1 in m_S and m_Y, and store 1/(ys) in m_Rho.

◆ ThreadedAdvanceOneStep()

template<typename TElastix>

void elastix::AdaptiveStochasticLBFGS< TElastix >::ThreadedAdvanceOneStep	(	ThreadIdType	threadId,
		ParametersType &	newPosition )

inlineprivate

The threaded implementation of AdvanceOneStep().

Member Data Documentation

◆ elxOverrideGetSelfMacro

template<typename TElastix>

elastix::AdaptiveStochasticLBFGS< TElastix >::elxOverrideGetSelfMacro

private

Definition at line 389 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AdvancedTransform

template<typename TElastix>

AdvancedTransformType::Pointer elastix::AdaptiveStochasticLBFGS< TElastix >::m_AdvancedTransform

protected

The transform stored as AdvancedTransform

Definition at line 300 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AutomaticLBFGSStepsizeEstimation

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_AutomaticLBFGSStepsizeEstimation

private

Definition at line 407 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AutomaticParameterEstimation

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_AutomaticParameterEstimation

private

Definition at line 406 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AutomaticParameterEstimationDone

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_AutomaticParameterEstimationDone

private

Definition at line 414 of file elxAdaptiveStochasticLBFGS.h.

◆ m_Bound

template<typename TElastix>

unsigned int elastix::AdaptiveStochasticLBFGS< TElastix >::m_Bound

protected

Definition at line 380 of file elxAdaptiveStochasticLBFGS.h.

◆ m_CurrentNumberOfSamplingAttempts

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_CurrentNumberOfSamplingAttempts

private

Definition at line 412 of file elxAdaptiveStochasticLBFGS.h.

◆ m_CurrentT

template<typename TElastix>

unsigned int elastix::AdaptiveStochasticLBFGS< TElastix >::m_CurrentT

protected

Definition at line 378 of file elxAdaptiveStochasticLBFGS.h.

◆ m_HessianFillValue

template<typename TElastix>

RhoType elastix::AdaptiveStochasticLBFGS< TElastix >::m_HessianFillValue

protected

Definition at line 385 of file elxAdaptiveStochasticLBFGS.h.

◆ m_MaxBandCovSize

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_MaxBandCovSize

private

Private variables for band size estimation of covariance matrix.

Definition at line 419 of file elxAdaptiveStochasticLBFGS.h.

◆ m_MaximumNumberOfSamplingAttempts

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_MaximumNumberOfSamplingAttempts

private

Private variables for the sampling attempts.

Definition at line 411 of file elxAdaptiveStochasticLBFGS.h.

◆ m_MaximumStepLength

template<typename TElastix>

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_MaximumStepLength

private

Definition at line 408 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NoiseFactor

template<typename TElastix>

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_NoiseFactor

protected

Definition at line 377 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfBandStructureSamples

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfBandStructureSamples

private

Definition at line 420 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfGradientMeasurements

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfGradientMeasurements

protected

Some options for automatic parameter estimation.

Definition at line 295 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfInnerLoopSamples

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfInnerLoopSamples

private

Definition at line 421 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfJacobianMeasurements

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfJacobianMeasurements

protected

Definition at line 296 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfSamplesForExactGradient

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfSamplesForExactGradient

protected

Definition at line 297 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfSpatialSamples

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfSpatialSamples

private

Definition at line 422 of file elxAdaptiveStochasticLBFGS.h.

◆ m_OriginalButSigmoidToDefault

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_OriginalButSigmoidToDefault

private

Definition at line 426 of file elxAdaptiveStochasticLBFGS.h.

◆ m_OutsideIterations

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_OutsideIterations

private

Definition at line 416 of file elxAdaptiveStochasticLBFGS.h.

◆ m_PreviousCurvatureGradient

template<typename TElastix>

DerivativeType elastix::AdaptiveStochasticLBFGS< TElastix >::m_PreviousCurvatureGradient

protected

Setting: the minimum gradient magnitude.

The optimizer stops when: ||CurrentGradient|| < GradientMagnitudeTolerance * max(1, ||CurrentPosition||)

Definition at line 375 of file elxAdaptiveStochasticLBFGS.h.

◆ m_PreviousErrorAtIteration

template<typename TElastix>

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_PreviousErrorAtIteration

private

Definition at line 413 of file elxAdaptiveStochasticLBFGS.h.

◆ m_PreviousT

template<typename TElastix>

unsigned int elastix::AdaptiveStochasticLBFGS< TElastix >::m_PreviousT

protected

Definition at line 379 of file elxAdaptiveStochasticLBFGS.h.

◆ m_Rho

template<typename TElastix>

RhoType elastix::AdaptiveStochasticLBFGS< TElastix >::m_Rho

protected

Definition at line 382 of file elxAdaptiveStochasticLBFGS.h.

◆ m_S

template<typename TElastix>

SType elastix::AdaptiveStochasticLBFGS< TElastix >::m_S

protected

Definition at line 383 of file elxAdaptiveStochasticLBFGS.h.

◆ m_SettingsVector

template<typename TElastix>

SettingsVectorType elastix::AdaptiveStochasticLBFGS< TElastix >::m_SettingsVector

protected

Variable to store the automatically determined settings for each resolution.

Definition at line 292 of file elxAdaptiveStochasticLBFGS.h.

◆ m_SigmoidScaleFactor

template<typename TElastix>

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_SigmoidScaleFactor

protected

Definition at line 302 of file elxAdaptiveStochasticLBFGS.h.

◆ m_UseAdaptiveLBFGSStepSizes

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_UseAdaptiveLBFGSStepSizes

private

Definition at line 429 of file elxAdaptiveStochasticLBFGS.h.

◆ m_UseNoiseCompensation

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_UseNoiseCompensation

private

The flag of using noise compensation.

Definition at line 425 of file elxAdaptiveStochasticLBFGS.h.

◆ m_UseNoiseFactor

template<typename TElastix>

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_UseNoiseFactor

private

Definition at line 427 of file elxAdaptiveStochasticLBFGS.h.

◆ m_WindowScale

template<typename TElastix>

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_WindowScale

protected

Definition at line 386 of file elxAdaptiveStochasticLBFGS.h.

◆ m_Y

template<typename TElastix>

YType elastix::AdaptiveStochasticLBFGS< TElastix >::m_Y

protected

Definition at line 384 of file elxAdaptiveStochasticLBFGS.h.

Private Attributes
	elxOverrideGetSelfMacro
bool	m_AutomaticLBFGSStepsizeEstimation
bool	m_AutomaticParameterEstimation
bool	m_AutomaticParameterEstimationDone
SizeValueType	m_CurrentNumberOfSamplingAttempts
SizeValueType	m_MaxBandCovSize
SizeValueType	m_MaximumNumberOfSamplingAttempts
double	m_MaximumStepLength
SizeValueType	m_NumberOfBandStructureSamples
SizeValueType	m_NumberOfInnerLoopSamples
SizeValueType	m_NumberOfSpatialSamples
bool	m_OriginalButSigmoidToDefault
SizeValueType	m_OutsideIterations
SizeValueType	m_PreviousErrorAtIteration
bool	m_UseAdaptiveLBFGSStepSizes
bool	m_UseNoiseCompensation
bool	m_UseNoiseFactor

Detailed Description

Classes

Public Types

Public Member Functions

Static Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Private Member Functions

Static Private Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ AdvancedTransformType

◆ ComputeDisplacementDistributionType

◆ ConstPointer

◆ CoordinateRepresentationType

◆ DiagonalMatrixType

◆ FixedImageIndexType

◆ FixedImagePointType

◆ FixedImageRegionType

◆ FixedImageType

◆ ImageGridSamplerPointer

◆ ImageGridSamplerType

◆ ImageRadomSampleContainerPointer

◆ ImageRadomSampleContainerType

◆ ImageRandomCoordinateSamplerPointer

◆ ImageRandomCoordinateSamplerType

◆ ImageRandomSamplerBasePointer

◆ ImageRandomSamplerBaseType

◆ ImageRandomSamplerPointer

◆ ImageRandomSamplerType

◆ ImageSampleContainerPointer

◆ ImageSampleContainerType

◆ ImageSamplerBasePointer

◆ ImageSamplerBaseType

◆ ImageSampleType

◆ ITKBaseType

◆ itkRegistrationType

◆ JacobianType

◆ JacobianValueType

◆ LineOptimizerPointer

◆ LineOptimizerType

◆ LineSearchOptimizerPointer

◆ LineSearchOptimizerType

◆ MovingImageType

◆ NonZeroJacobianIndicesType

◆ Pointer

◆ RandomGeneratorType

◆ RhoType

◆ Self

◆ SettingsVectorType

◆ SizeValueType

◆ SType

◆ Superclass1

◆ Superclass2

◆ ThreadIdType

◆ TransformJacobianType

◆ TransformType

◆ YType

Constructor & Destructor Documentation

◆ AdaptiveStochasticLBFGS()

◆ ~AdaptiveStochasticLBFGS()

Member Function Documentation

◆ AddRandomPerturbation()

◆ AdvanceOneStep()

◆ AdvanceOneStepThreaderCallback()

◆ AfterEachIteration()

◆ AfterEachResolution()

◆ AfterRegistration()

◆ AutomaticLBFGSStepsizeEstimation()

◆ AutomaticParameterEstimation()

◆ AutomaticParameterEstimationOriginal()

◆ AutomaticParameterEstimationUsingDisplacementDistribution()

◆ BeforeEachResolution()

◆ BeforeRegistration()

◆ ComputeDiagonalMatrix()

◆ ComputeSearchDirection()

◆ elxClassNameMacro()

◆ GetAutomaticLBFGSStepsizeEstimation()