#include <elxAdaptiveStochasticLBFGS.h>

Detailed Description

template<class 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 >:

[legend]

Data Structures
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 char *	GetClassName () const

virtual const SizeValueType &	GetMaximumNumberOfSamplingAttempts ()

virtual double	GetMaximumStepLength () const

	ITK_DISALLOW_COPY_AND_MOVE (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)

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)

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)

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)

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)

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)

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)

	itkTypeMacroNoParent (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	ComputeJacobianTermsType = itk::ComputeJacobianTerms<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

RandomGeneratorType::Pointer	m_RandomGenerator

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<class 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 279 of file elxAdaptiveStochasticLBFGS.h.

◆ ComputeDisplacementDistributionType

template<class TElastix >

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

protected

Definition at line 248 of file elxAdaptiveStochasticLBFGS.h.

◆ ComputeJacobianTermsType

template<class TElastix >

using elastix::AdaptiveStochasticLBFGS< TElastix >::ComputeJacobianTermsType = itk::ComputeJacobianTerms<FixedImageType, TransformType>

protected

Definition at line 244 of file elxAdaptiveStochasticLBFGS.h.

◆ ConstPointer

template<class TElastix >

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

Definition at line 115 of file elxAdaptiveStochasticLBFGS.h.

◆ CoordinateRepresentationType

template<class TElastix >

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

protected

Definition at line 278 of file elxAdaptiveStochasticLBFGS.h.

◆ DiagonalMatrixType

template<class TElastix >

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

protected

Definition at line 287 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImageIndexType

template<class TElastix >

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

protected

Definition at line 239 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImagePointType

template<class TElastix >

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

protected

Definition at line 240 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImageRegionType

template<class TElastix >

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

protected

Definition at line 238 of file elxAdaptiveStochasticLBFGS.h.

◆ FixedImageType

template<class TElastix >

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

protected

Protected typedefs

Definition at line 235 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageGridSamplerPointer

template<class TElastix >

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

protected

Definition at line 267 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageGridSamplerType

template<class TElastix >

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

protected

Image grid sampler.

Definition at line 266 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRadomSampleContainerPointer

template<class TElastix >

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

protected

Definition at line 263 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRadomSampleContainerType

template<class TElastix >

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

protected

Definition at line 262 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomCoordinateSamplerPointer

template<class TElastix >

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

protected

Definition at line 256 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomCoordinateSamplerType

template<class TElastix >

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

protected

Definition at line 255 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerBasePointer

template<class TElastix >

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

protected

Definition at line 254 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerBaseType

template<class TElastix >

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

protected

Definition at line 253 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerPointer

template<class TElastix >

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

protected

Definition at line 261 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageRandomSamplerType

template<class TElastix >

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

protected

Image random sampler.

Definition at line 260 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSampleContainerPointer

template<class TElastix >

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

protected

Definition at line 269 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSampleContainerType

template<class TElastix >

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

protected

Definition at line 268 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSamplerBasePointer

template<class TElastix >

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

protected

Definition at line 252 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSamplerBaseType

template<class TElastix >

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

protected

Samplers:

Definition at line 251 of file elxAdaptiveStochasticLBFGS.h.

◆ ImageSampleType

template<class TElastix >

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

protected

Definition at line 257 of file elxAdaptiveStochasticLBFGS.h.

◆ ITKBaseType

template<class TElastix >

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

Definition at line 137 of file elxAdaptiveStochasticLBFGS.h.

◆ itkRegistrationType

template<class TElastix >

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

protected

Definition at line 241 of file elxAdaptiveStochasticLBFGS.h.

◆ JacobianType

template<class TElastix >

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

protected

Definition at line 243 of file elxAdaptiveStochasticLBFGS.h.

◆ JacobianValueType

template<class TElastix >

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

protected

Definition at line 245 of file elxAdaptiveStochasticLBFGS.h.

◆ LineOptimizerPointer

template<class TElastix >

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

Definition at line 151 of file elxAdaptiveStochasticLBFGS.h.

◆ LineOptimizerType

template<class TElastix >

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

Definition at line 150 of file elxAdaptiveStochasticLBFGS.h.

◆ LineSearchOptimizerPointer

template<class TElastix >

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

Definition at line 149 of file elxAdaptiveStochasticLBFGS.h.

◆ LineSearchOptimizerType

template<class TElastix >

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

Definition at line 147 of file elxAdaptiveStochasticLBFGS.h.

◆ MovingImageType

template<class TElastix >

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

protected

Definition at line 236 of file elxAdaptiveStochasticLBFGS.h.

◆ NonZeroJacobianIndicesType

template<class TElastix >

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

protected

Definition at line 281 of file elxAdaptiveStochasticLBFGS.h.

◆ Pointer

template<class TElastix >

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

Definition at line 114 of file elxAdaptiveStochasticLBFGS.h.

◆ RandomGeneratorType

template<class TElastix >

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

protected

Other protected typedef

Definition at line 272 of file elxAdaptiveStochasticLBFGS.h.

◆ RhoType

template<class TElastix >

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

protected

For L-BFGS usage.

Definition at line 284 of file elxAdaptiveStochasticLBFGS.h.

◆ Self

template<class TElastix >

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

Standard ITK.

Definition at line 111 of file elxAdaptiveStochasticLBFGS.h.

◆ SettingsVectorType

template<class TElastix >

using elastix::OptimizerBase< TElastix >::SettingsVectorType

protected

Definition at line 133 of file elxOptimizerBase.h.

◆ SizeValueType

template<class TElastix >

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

Definition at line 138 of file elxAdaptiveStochasticLBFGS.h.

◆ SType

template<class TElastix >

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

protected

Definition at line 285 of file elxAdaptiveStochasticLBFGS.h.

◆ Superclass1

template<class TElastix >

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

Definition at line 112 of file elxAdaptiveStochasticLBFGS.h.

◆ Superclass2

template<class TElastix >

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

Definition at line 113 of file elxAdaptiveStochasticLBFGS.h.

◆ ThreadIdType

template<class 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<class TElastix >

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

protected

Typedefs for support of sparse Jacobians and AdvancedTransforms.

Definition at line 275 of file elxAdaptiveStochasticLBFGS.h.

◆ TransformType

template<class TElastix >

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

protected

Definition at line 242 of file elxAdaptiveStochasticLBFGS.h.

◆ YType

template<class TElastix >

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

protected

Definition at line 286 of file elxAdaptiveStochasticLBFGS.h.

Constructor & Destructor Documentation

◆ AdaptiveStochasticLBFGS()

template<class TElastix >

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

protected

◆ ~AdaptiveStochasticLBFGS()

template<class TElastix >

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

overrideprotecteddefault

Member Function Documentation

◆ AddRandomPerturbation()

template<class 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<class TElastix >

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

overridevirtual

AdvanceOneStep.

Reimplemented from itk::StochasticGradientDescentOptimizer.

◆ AdvanceOneStepThreaderCallback()

template<class TElastix >

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

staticprivate

The callback function.

◆ AfterEachIteration()

template<class TElastix >

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

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ AfterEachResolution()

template<class TElastix >

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

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ AfterRegistration()

template<class TElastix >

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

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ AutomaticLBFGSStepsizeEstimation()

template<class TElastix >

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

protectedvirtual

◆ AutomaticParameterEstimation()

template<class 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<class 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<class 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<class TElastix >

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

overridevirtual

Reimplemented from elastix::BaseComponent.

◆ BeforeRegistration()

template<class 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<class 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<class 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<class 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<class TElastix >

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

virtual

◆ GetAutomaticParameterEstimation()

template<class TElastix >

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

virtual

◆ GetClassName()

template<class TElastix >

virtual const char * elastix::AdaptiveStochasticLBFGS< TElastix >::GetClassName ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::AdaptiveStochasticLBFGSOptimizer.

◆ GetMaximumNumberOfSamplingAttempts()

template<class TElastix >

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

virtual

Get the MaximumNumberOfSamplingAttempts.

◆ GetMaximumStepLength()

template<class TElastix >

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

virtual

◆ GetScaledDerivativeWithExceptionHandling()

template<class 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<class TElastix >

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

◆ itkStaticConstMacro() [1/2]

template<class TElastix >

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

protected

◆ itkStaticConstMacro() [2/2]

template<class TElastix >

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

protected

◆ LBFGSUpdate()

template<class TElastix >

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

virtual

LBFGS Update step.

◆ MetricErrorResponse()

template<class TElastix >

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

override

Stop optimization and pass on exception.

◆ New()

template<class TElastix >

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

static

Method for creation through the object factory.

◆ ResumeOptimization()

template<class 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<class 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<class TElastix >

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

virtual

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

◆ SetAutomaticParameterEstimation()

template<class 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<class TElastix >

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

virtual

Set the MaximumNumberOfSamplingAttempts.

◆ SetMaximumStepLength()

template<class TElastix >

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

virtual

Set/Get maximum step length.

◆ SetNumberOfWorkUnits()

template<class TElastix >

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

inline

Set the number of threads.

Definition at line 228 of file elxAdaptiveStochasticLBFGS.h.

◆ StartOptimization()

template<class 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<class TElastix >

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

overridevirtual

Stop optimization.

See also: StopOptimization

Reimplemented from itk::StochasticGradientDescentOptimizer.

◆ StoreCurrentPoint()

template<class 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<class TElastix >

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

inlineprivate

The threaded implementation of AdvanceOneStep().

Field Documentation

◆ elxOverrideGetSelfMacro

template<class TElastix >

elastix::AdaptiveStochasticLBFGS< TElastix >::elxOverrideGetSelfMacro

private

Definition at line 393 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AdvancedTransform

template<class TElastix >

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

protected

The transform stored as AdvancedTransform

Definition at line 301 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AutomaticLBFGSStepsizeEstimation

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_AutomaticLBFGSStepsizeEstimation

private

Definition at line 411 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AutomaticParameterEstimation

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_AutomaticParameterEstimation

private

Definition at line 410 of file elxAdaptiveStochasticLBFGS.h.

◆ m_AutomaticParameterEstimationDone

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_AutomaticParameterEstimationDone

private

Definition at line 418 of file elxAdaptiveStochasticLBFGS.h.

◆ m_Bound

template<class TElastix >

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

protected

Definition at line 384 of file elxAdaptiveStochasticLBFGS.h.

◆ m_CurrentNumberOfSamplingAttempts

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_CurrentNumberOfSamplingAttempts

private

Definition at line 416 of file elxAdaptiveStochasticLBFGS.h.

◆ m_CurrentT

template<class TElastix >

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

protected

Definition at line 382 of file elxAdaptiveStochasticLBFGS.h.

◆ m_HessianFillValue

template<class TElastix >

RhoType elastix::AdaptiveStochasticLBFGS< TElastix >::m_HessianFillValue

protected

Definition at line 389 of file elxAdaptiveStochasticLBFGS.h.

◆ m_MaxBandCovSize

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_MaxBandCovSize

private

Private variables for band size estimation of covariance matrix.

Definition at line 423 of file elxAdaptiveStochasticLBFGS.h.

◆ m_MaximumNumberOfSamplingAttempts

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_MaximumNumberOfSamplingAttempts

private

Private variables for the sampling attempts.

Definition at line 415 of file elxAdaptiveStochasticLBFGS.h.

◆ m_MaximumStepLength

template<class TElastix >

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_MaximumStepLength

private

Definition at line 412 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NoiseFactor

template<class TElastix >

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_NoiseFactor

protected

Definition at line 381 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfBandStructureSamples

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfBandStructureSamples

private

Definition at line 424 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfGradientMeasurements

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfGradientMeasurements

protected

Some options for automatic parameter estimation.

Definition at line 296 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfInnerLoopSamples

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfInnerLoopSamples

private

Definition at line 425 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfJacobianMeasurements

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfJacobianMeasurements

protected

Definition at line 297 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfSamplesForExactGradient

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfSamplesForExactGradient

protected

Definition at line 298 of file elxAdaptiveStochasticLBFGS.h.

◆ m_NumberOfSpatialSamples

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_NumberOfSpatialSamples

private

Definition at line 426 of file elxAdaptiveStochasticLBFGS.h.

◆ m_OriginalButSigmoidToDefault

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_OriginalButSigmoidToDefault

private

Definition at line 430 of file elxAdaptiveStochasticLBFGS.h.

◆ m_OutsideIterations

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_OutsideIterations

private

Definition at line 420 of file elxAdaptiveStochasticLBFGS.h.

◆ m_PreviousCurvatureGradient

template<class 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 379 of file elxAdaptiveStochasticLBFGS.h.

◆ m_PreviousErrorAtIteration

template<class TElastix >

SizeValueType elastix::AdaptiveStochasticLBFGS< TElastix >::m_PreviousErrorAtIteration

private

Definition at line 417 of file elxAdaptiveStochasticLBFGS.h.

◆ m_PreviousT

template<class TElastix >

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

protected

Definition at line 383 of file elxAdaptiveStochasticLBFGS.h.

◆ m_RandomGenerator

template<class TElastix >

RandomGeneratorType::Pointer elastix::AdaptiveStochasticLBFGS< TElastix >::m_RandomGenerator

protected

RandomGenerator for AddRandomPerturbation.

Definition at line 304 of file elxAdaptiveStochasticLBFGS.h.

◆ m_Rho

template<class TElastix >

RhoType elastix::AdaptiveStochasticLBFGS< TElastix >::m_Rho

protected

Definition at line 386 of file elxAdaptiveStochasticLBFGS.h.

◆ m_S

template<class TElastix >

SType elastix::AdaptiveStochasticLBFGS< TElastix >::m_S

protected

Definition at line 387 of file elxAdaptiveStochasticLBFGS.h.

◆ m_SettingsVector

template<class TElastix >

SettingsVectorType elastix::AdaptiveStochasticLBFGS< TElastix >::m_SettingsVector

protected

Variable to store the automatically determined settings for each resolution.

Definition at line 293 of file elxAdaptiveStochasticLBFGS.h.

◆ m_SigmoidScaleFactor

template<class TElastix >

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_SigmoidScaleFactor

protected

Definition at line 306 of file elxAdaptiveStochasticLBFGS.h.

◆ m_UseAdaptiveLBFGSStepSizes

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_UseAdaptiveLBFGSStepSizes

private

Definition at line 433 of file elxAdaptiveStochasticLBFGS.h.

◆ m_UseNoiseCompensation

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_UseNoiseCompensation

private

The flag of using noise compensation.

Definition at line 429 of file elxAdaptiveStochasticLBFGS.h.

◆ m_UseNoiseFactor

template<class TElastix >

bool elastix::AdaptiveStochasticLBFGS< TElastix >::m_UseNoiseFactor

private

Definition at line 431 of file elxAdaptiveStochasticLBFGS.h.

◆ m_WindowScale

template<class TElastix >

double elastix::AdaptiveStochasticLBFGS< TElastix >::m_WindowScale

protected

Definition at line 390 of file elxAdaptiveStochasticLBFGS.h.

◆ m_Y

template<class TElastix >

YType elastix::AdaptiveStochasticLBFGS< TElastix >::m_Y

protected

Definition at line 388 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

Data Structures

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

◆ ComputeJacobianTermsType

◆ 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()