A base class for sums of 'generalised' objective functions, i.e. objective functions for which at least a 'gradient' is defined. More...

#include "stir/recon_buildblock/SumOfGeneralisedObjectiveFunctions.h"

Inheritance diagram for stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, ParentT >:

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Public Member Functions
template<typename IterT>
	SumOfGeneralisedObjectiveFunctions (IterT begin, IterT end)

template<typename IterT>
void	set_functions (IterT begin, IterT end)

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

virtual void	compute_sub_gradient_without_penalty (TargetT &gradient, const TargetT &current_estimate, const int subset_num)
	This computes the gradient of the unregularised objective function at the current_estimate.

virtual double	actual_compute_objective_function_without_penalty (const TargetT &current_estimate, const int subset_num)
	Implementation of function that computes the objective function for the current subset.

virtual int	set_num_subsets (const int num_subsets)
	Attempts to change the number of subsets.

Public Member Functions inherited from stir::GeneralisedObjectiveFunction< TargetT >
virtual TargetT *	construct_target_ptr () const =0
	Creates a suitable target as determined by the parameters.

virtual void	compute_sub_gradient (TargetT &gradient, const TargetT &current_estimate, const int subset_num)
	Compute the subset-gradient of the objective function at current_estimate.

virtual void	compute_gradient (TargetT &gradient, const TargetT &current_estimate)
	Compute the gradient of the objective function at the current_estimate.

virtual void	compute_gradient_without_penalty (TargetT &gradient, const TargetT &current_estimate)
	Compute the gradient of the unregularised objective function at the current_estimate.

virtual double	compute_objective_function_without_penalty (const TargetT &current_estimate, const int subset_num)
	Compute the value of the unregularised sub-objective function at the current_estimate.

virtual double	compute_objective_function_without_penalty (const TargetT &current_estimate)
	Compute the value of the unregularised objective function at the current_estimate.

double	compute_penalty (const TargetT &current_estimate, const int subset_num)
	Compute the value of the sub-penalty at the current_estimate.

double	compute_penalty (const TargetT &current_estimate)
	Compute the value of the penalty at the current_estimate.

double	compute_objective_function (const TargetT &current_estimate, const int subset_num)
	Compute the value of the sub-objective function at the current_estimate.

double	compute_objective_function (const TargetT &current_estimate)
	Compute the value of the objective function at the current_estimate.

double	compute_value (const TargetT &current_estimate)
	Alias for compute_objective_function(const TargetT&)

virtual void	fill_nonidentifiable_target_parameters (TargetT &target, const float value) const
	Fill any elements that we cannot estimate with a fixed value.

Succeeded	add_multiplication_with_approximate_sub_Hessian_without_penalty (TargetT &output, const TargetT &input, const int subset_num) const
	Functions that multiply the approximate (sub)Hessian with a \'vector\'.

Succeeded	add_multiplication_with_approximate_sub_Hessian (TargetT &output, const TargetT &input, const int subset_num) const

Succeeded	add_multiplication_with_approximate_Hessian_without_penalty (TargetT &output, const TargetT &input) const

Succeeded	add_multiplication_with_approximate_Hessian (TargetT &output, const TargetT &input) const

Succeeded	accumulate_Hessian_times_input (TargetT &output, const TargetT &current_image_estimate, const TargetT &input) const
	Functions that multiply the True (sub)Hessian with a \'vector\'.

Succeeded	accumulate_Hessian_times_input_without_penalty (TargetT &output, const TargetT &current_image_estimate, const TargetT &input) const

Succeeded	accumulate_sub_Hessian_times_input (TargetT &output, const TargetT &current_image_estimate, const TargetT &input, const int subset_num) const

Succeeded	accumulate_sub_Hessian_times_input_without_penalty (TargetT &output, const TargetT &current_image_estimate, const TargetT &input, const int subset_num) const

std::string	get_objective_function_values_report (const TargetT &current_estimate)
	Construct a string with info on the value of objective function with and without penalty.

int	get_num_subsets () const
	Return the number of subsets in-use.

virtual std::unique_ptr< ExamInfo >	get_exam_info_uptr_for_target () const

bool	subsets_are_approximately_balanced () const
	Checks of the current subset scheme is approximately balanced.

bool	subsets_are_approximately_balanced (std::string &warning_message) const
	Checks of the current subset scheme is approximately balanced and constructs a warning message.

bool	prior_is_zero () const
	check if the prior is set (or the penalisation factor is 0)

GeneralisedPrior< TargetT > *const	get_prior_ptr () const
	Read-only access to the prior.

shared_ptr< GeneralisedPrior< TargetT > >	get_prior_sptr ()

void	set_prior_sptr (const shared_ptr< GeneralisedPrior< TargetT > > &)
	Change the prior.

virtual void	set_input_data (const shared_ptr< ExamData > &)=0
	set_input_data

virtual const ExamData &	get_input_data () const =0
	get input data

virtual void	set_additive_proj_data_sptr (const shared_ptr< ExamData > &)=0
	set_additive_proj_data_sptr

virtual void	set_normalisation_sptr (const shared_ptr< BinNormalisation > &)=0
	set_normalisation_sptr

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

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

ParsingObject &	operator= (const ParsingObject &)

bool	parse (std::istream &f)

bool	parse (const char *const filename)

void	ask_parameters ()

virtual std::string	parameter_info ()

Protected Types
typedef std::vector< ObjFuncT >	_functions_type

typedef _functions_type::iterator	_functions_iterator_type

typedef _functions_type::const_iterator	_functions_const_iterator_type

Protected Types inherited from stir::RegisteredObject< GeneralisedObjectiveFunction< TargetT > >
typedef GeneralisedObjectiveFunction< TargetT > (	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.

Protected Member Functions
virtual bool	actual_subsets_are_approximately_balanced (std::string &warning_message) const
	Implementation of function that checks subset balancing.

void	set_defaults () override
	sets any default values

void	initialise_keymap () override
	sets parsing keys

virtual Succeeded	actual_add_multiplication_with_approximate_sub_Hessian_without_penalty (TargetT &output, const TargetT &input, const int subset_num) const
	Implementation of the function that multiplies the approximate sub-Hessian with a vector.

virtual Succeeded	actual_accumulate_sub_Hessian_times_input_without_penalty (TargetT &output, const TargetT &current_image_estimate, const TargetT &input, const int subset_num) const
	Implementation of the function computes the sub-Hessian and multiplies by a vector.

virtual bool	post_processing ()
	This will be called at the end of the parsing.

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

Protected Attributes
_functions_type	_functions

int	num_subsets

bool	already_set_up

shared_ptr< GeneralisedPrior< TargetT > >	prior_sptr

KeyParser	parser

Additional Inherited Members
Static Public Member Functions inherited from stir::RegisteredObject< GeneralisedObjectiveFunction< TargetT > >
static GeneralisedObjectiveFunction< TargetT > *	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.

static GeneralisedObjectiveFunction< TargetT > *	ask_type_and_parameters ()
	ask the user for the type, and then calls read_registered_object(0, type)

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

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

Detailed Description

template<typename ObjFuncT, typename TargetT, typename ParentT = GeneralisedObjectiveFunction<TargetT>>
class stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, ParentT >

A base class for sums of 'generalised' objective functions, i.e. objective functions for which at least a 'gradient' is defined.

Todo

document why use of ParentT template

doc subsets

Member Function Documentation

◆ set_up()

template<typename ObjFuncT, typename TargetT, typename Parent>

Succeeded stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, Parent >::set_up ( shared_ptr< TargetT > const & target_sptr )

inlinevirtual

Has to be called before using this object.

Will call set_up() for all terms in the sum, but will stop as soon as one set_up() fails.

Reimplemented from stir::GeneralisedObjectiveFunction< TargetT >.

References set_up().

Referenced by set_up().

◆ compute_sub_gradient_without_penalty()

template<typename ObjFuncT, typename TargetT, typename Parent>

void stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, Parent >::compute_sub_gradient_without_penalty	(	TargetT &	gradient,
		const TargetT &	current_estimate,
		const int	subset_num )

inlinevirtual

This computes the gradient of the unregularised objective function at the current_estimate.

It is computed as the sum of the subgradients for each term, depending on the subset scheme.

Implements stir::GeneralisedObjectiveFunction< TargetT >.

References compute_sub_gradient_without_penalty().

Referenced by compute_sub_gradient_without_penalty().

◆ actual_compute_objective_function_without_penalty()

template<typename ObjFuncT, typename TargetT, typename Parent>

double stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, Parent >::actual_compute_objective_function_without_penalty	(	const TargetT &	current_estimate,
		const int	subset_num )

inlinevirtual

Implementation of function that computes the objective function for the current subset.

See also: compute_objective_function_without_penalty(const Target&,const int)

Developer\'s note

The reason we have this function is that overloading a function in a derived class, hides all functions of the same name.

Implements stir::GeneralisedObjectiveFunction< TargetT >.

Reimplemented in stir::PoissonLogLikelihoodWithLinearModelForMeanAndGatedProjDataWithMotion< TargetT >.

References actual_compute_objective_function_without_penalty().

Referenced by actual_compute_objective_function_without_penalty().

◆ set_num_subsets()

template<typename ObjFuncT, typename TargetT, typename Parent>

int stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, Parent >::set_num_subsets ( const int num_subsets )

inlinevirtual

Attempts to change the number of subsets.

Returns: The number of subsets that will be used later, which is not guaranteed to be what you asked for.

Implements stir::GeneralisedObjectiveFunction< TargetT >.

Reimplemented in stir::PoissonLogLikelihoodWithLinearModelForMeanAndGatedProjDataWithMotion< TargetT >.

References stir::error(), and set_num_subsets().

Referenced by set_num_subsets().

◆ actual_subsets_are_approximately_balanced()

template<typename ObjFuncT, typename TargetT, typename Parent>

bool stir::SumOfGeneralisedObjectiveFunctions< ObjFuncT, TargetT, Parent >::actual_subsets_are_approximately_balanced ( std::string & warning_message ) const

inlineprotectedvirtual

Implementation of function that checks subset balancing.

Todo: doc subset

Implements stir::GeneralisedObjectiveFunction< TargetT >.

Reimplemented in stir::PoissonLogLikelihoodWithLinearModelForMeanAndGatedProjDataWithMotion< TargetT >.

References actual_subsets_are_approximately_balanced().

Referenced by actual_subsets_are_approximately_balanced().

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

/home/kris/devel/STIRdistrib/STIR/src/include/stir/recon_buildblock/SumOfGeneralisedObjectiveFunctions.h
/home/kris/devel/STIRdistrib/STIR/src/include/stir/recon_buildblock/SumOfGeneralisedObjectiveFunctions.inl

Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ set_up()

◆ compute_sub_gradient_without_penalty()

◆ actual_compute_objective_function_without_penalty()

◆ set_num_subsets()

◆ actual_subsets_are_approximately_balanced()