A base class for 'generalised' priors, i.e. priors for which at least a 'gradient' is defined. More...

#include "stir/recon_buildblock/GeneralisedPrior.h"

Inheritance diagram for stir::GeneralisedPrior< DataT >:

[legend]

Public Member Functions
virtual double	compute_value (const DataT &current_estimate)=0
	compute the value of the function More...

virtual void	compute_gradient (DataT &prior_gradient, const DataT &current_estimate)=0
	This should compute the gradient of the log of the prior function at the current_estimate. More...

virtual void	compute_Hessian (DataT &prior_Hessian_for_single_densel, const BasicCoordinate< 3, int > &coords, const DataT &current_image_estimate) const
	This computes a single row of the Hessian. More...

virtual void	add_multiplication_with_approximate_Hessian (DataT &output, const DataT &input) const
	This should compute the multiplication of the Hessian with a vector and add it to output. More...

virtual void	accumulate_Hessian_times_input (DataT &output, const DataT &current_estimate, const DataT &input) const
	This should compute the multiplication of the Hessian with a vector and add it to output. More...

float	get_penalisation_factor () const

void	set_penalisation_factor (float new_penalisation_factor)

virtual Succeeded	set_up (shared_ptr< const DataT > const &target_sptr)
	Has to be called before using this object.

virtual bool	is_convex () const =0
	Indicates if the prior is a smooth convex function. More...

Public Member Functions inherited from stir::RegisteredObjectBase
virtual std::string	get_registered_name () const =0
	Returns the name of the type of the object. More...

Public Member Functions inherited from stir::ParsingObject
	ParsingObject (const ParsingObject &)

ParsingObject &	operator= (const ParsingObject &)

void	ask_parameters ()

virtual std::string	parameter_info ()

bool	parse (std::istream &f)

bool	parse (const char *const filename)

Protected Member Functions
void	set_defaults () override
	sets value for penalisation factor More...

void	initialise_keymap () override
	sets key for penalisation factor More...

virtual void	check (DataT const &current_estimate) const
	Check that the prior is ready to be used.

Protected Member Functions inherited from stir::ParsingObject
virtual bool	post_processing ()
	This will be called at the end of the parsing. More...

virtual void	set_key_values ()
	This will be called before parsing or parameter_info is called. More...

Protected Attributes
float	penalisation_factor

bool	_already_set_up

Protected Attributes inherited from stir::ParsingObject
KeyParser	parser

Additional Inherited Members
Static Public Member Functions inherited from stir::RegisteredObject< GeneralisedPrior< DataT > >
static GeneralisedPrior< DataT > *	read_registered_object (std::istream *in, const std::string &registered_name)
	Construct a new object (of a type derived from Root, its actual type determined by the registered_name parameter) by parsing the istream. More...

static GeneralisedPrior< DataT > *	ask_type_and_parameters ()
	ask the user for the type, and then calls read_registered_object(0, type) More...

static void	list_registered_names (std::ostream &stream)
	List all possible registered names to the stream. More...

Protected Types inherited from stir::RegisteredObject< GeneralisedPrior< DataT > >
typedef GeneralisedPrior< DataT > (	RootFactory) (std::istream *)
	The type of a root factory is a function, taking an istream* as argument, and returning a Root*.

typedef FactoryRegistry< std::string, RootFactory, interfile_less >	RegistryType
	The type of the registry.

Static Protected Member Functions inherited from stir::RegisteredObject< GeneralisedPrior< DataT > >
static RegistryType &	registry ()
	Static function returning the registry. More...

Detailed Description

template<typename DataT>
class stir::GeneralisedPrior< DataT >

A base class for 'generalised' priors, i.e. priors for which at least a 'gradient' is defined.

This class exists to accomodate FilterRootPrior. Otherwise we could just live with Prior as a base class.

Member Function Documentation

◆ compute_value()

template<typename DataT>

virtual double stir::GeneralisedPrior< DataT >::compute_value ( const DataT & current_estimate )

pure virtual

compute the value of the function

For derived classes where this doesn't make sense, it's recommended to return 0.

Implemented in stir::PLSPrior< elemT >, stir::RelativeDifferencePrior< elemT >, stir::LogcoshPrior< elemT >, stir::ParametricQuadraticPrior< TargetT >, stir::QuadraticPrior< elemT >, stir::QuadraticPrior< float >, stir::FilterRootPrior< DataT >, and stir::CudaRelativeDifferencePrior< elemT >.

◆ compute_gradient()

template<typename DataT>

virtual void stir::GeneralisedPrior< DataT >::compute_gradient	(	DataT &	prior_gradient,
		const DataT &	current_estimate
	)

pure virtual

This should compute the gradient of the log of the prior function at the current_estimate.

The gradient is already multiplied with the penalisation_factor.

Warning: The derived class should overwrite any data in prior_gradient.

Implemented in stir::PLSPrior< elemT >, stir::RelativeDifferencePrior< elemT >, stir::LogcoshPrior< elemT >, stir::ParametricQuadraticPrior< TargetT >, stir::QuadraticPrior< elemT >, stir::QuadraticPrior< float >, stir::FilterRootPrior< DataT >, and stir::CudaRelativeDifferencePrior< elemT >.

Referenced by stir::GeneralisedPriorTests::test_Hessian_against_numerical().

◆ compute_Hessian()

template<typename TargetT>

void stir::GeneralisedPrior< TargetT >::compute_Hessian	(	TargetT &	prior_Hessian_for_single_densel,
		const BasicCoordinate< 3, int > &	coords,
		const TargetT &	current_image_estimate
	)		const

virtual

This computes a single row of the Hessian.

Default implementation just call error(). This function needs to be overridden by the derived class.

The method computes a row (i.e. at a densel/voxel, indicated by coords) of the Hessian at current_estimate. Note that a row corresponds to an object of DataT. The method (as implemented in derived classes) should store the result in prior_Hessian_for_single_densel.

Referenced by stir::GeneralisedPriorTests::test_Hessian_against_numerical().

◆ add_multiplication_with_approximate_Hessian()

template<typename TargetT>

void stir::GeneralisedPrior< TargetT >::add_multiplication_with_approximate_Hessian	(	TargetT &	output,
		const TargetT &	input
	)		const

virtual

This should compute the multiplication of the Hessian with a vector and add it to output.

Default implementation just call error(). This function needs to be overridden by the derived class. This method assumes that the hessian of the prior is 1 and hence the function quadratic. Instead, accumulate_Hessian_times_input() should be used. This method remains for backwards comparability.

Warning: The derived class should accumulate in output.

Reimplemented in stir::ParametricQuadraticPrior< TargetT >.

◆ accumulate_Hessian_times_input()

template<typename TargetT>

void stir::GeneralisedPrior< TargetT >::accumulate_Hessian_times_input	(	TargetT &	output,
		const TargetT &	current_estimate,
		const TargetT &	input
	)		const

virtual

This should compute the multiplication of the Hessian with a vector and add it to output.

Default implementation just call error(). This function needs to be overridden by the derived class.

Warning: The derived class should accumulate in output.

Referenced by stir::GeneralisedPriorTests::test_Hessian_convexity_configuration().

◆ set_penalisation_factor()

template<typename elemT >

void stir::GeneralisedPrior< elemT >::set_penalisation_factor ( float new_penalisation_factor )

inline

Warning: Currently we allow the penalisation factor to be set after calling set_up().

Referenced by stir::GeneralisedPriorTests::test_Hessian_convexity(), and stir::GeneralisedPriorTests::test_Hessian_convexity_configuration().

◆ is_convex()

template<typename DataT>

virtual bool stir::GeneralisedPrior< DataT >::is_convex ( ) const

pure virtual

Indicates if the prior is a smooth convex function.

If true, the prior is expected to have 0th, 1st and 2nd order behaviour implemented.

Implemented in stir::RelativeDifferencePrior< elemT >, stir::PLSPrior< elemT >, stir::LogcoshPrior< elemT >, stir::QuadraticPrior< elemT >, stir::QuadraticPrior< float >, and stir::FilterRootPrior< DataT >.

Referenced by stir::GeneralisedPriorTests::test_Hessian_against_numerical(), and stir::GeneralisedPriorTests::test_Hessian_convexity().

◆ set_defaults()

template<typename TargetT >

void stir::GeneralisedPrior< TargetT >::set_defaults ( )

overrideprotectedvirtual

sets value for penalisation factor

Has to be called by set_defaults in the leaf-class

Reimplemented from stir::ParsingObject.

Reimplemented in stir::QuadraticPrior< float >.

Referenced by stir::FilterRootPrior< DataT >::compute_gradient().

◆ initialise_keymap()

template<typename TargetT >

void stir::GeneralisedPrior< TargetT >::initialise_keymap ( )

overrideprotectedvirtual

sets key for penalisation factor

Has to be called by initialise_keymap in the leaf-class

Reimplemented from stir::ParsingObject.

Reimplemented in stir::QuadraticPrior< float >.

Referenced by stir::FilterRootPrior< DataT >::compute_gradient().

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

/home/sirfuser/devel/STIRdistrib/STIR/src/include/stir/recon_buildblock/GeneralisedPrior.h
/home/sirfuser/devel/STIRdistrib/STIR/src/include/stir/recon_buildblock/GeneralisedPrior.inl
/home/sirfuser/devel/STIRdistrib/STIR/src/recon_buildblock/GeneralisedPrior.cxx

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

template<typename DataT> class stir::GeneralisedPrior< DataT >

Member Function Documentation

◆ compute_value()

◆ compute_gradient()

◆ compute_Hessian()

◆ add_multiplication_with_approximate_Hessian()

◆ accumulate_Hessian_times_input()

◆ set_penalisation_factor()

◆ is_convex()

◆ set_defaults()

◆ initialise_keymap()

template<typename DataT>
class stir::GeneralisedPrior< DataT >