Class of conjugate gradient method for optimization. More...

#include <num_collect/opt/conjugate_gradient_optimizer.h>

Inheritance diagram for num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >:

Collaboration diagram for num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >:

Public Types
using	base_type = descent_method_base<this_type, LineSearcher>
	Type of base class.

using	objective_function_type
	Type of the objective function.

using	this_type
	This class.

using	value_type
	Type of function values.

using	variable_scalar_type = typename variable_type::Scalar
	Type of scalars in variables.

using	variable_type
	Type of variables.

Public Types inherited from num_collect::opt::descent_method_base< Derived, LineSearcher >
using	line_searcher_type = LineSearcher
	Type of class to perform line search.

using	objective_function_type
	Type of the objective function.

using	value_type = typename objective_function_type::value_type
	Type of function values.

using	variable_type = typename objective_function_type::variable_type
	Type of variables.

Public Member Functions
	conjugate_gradient_optimizer (const objective_function_type &obj_fun=objective_function_type())
	Constructor.

auto	calc_direction () -> variable_type
	Calculate search direction.

void	configure_iteration_logger (logging::iterations::iteration_logger< this_type > &iteration_logger) const
	Configure an iteration logger.

auto	evaluations () const noexcept -> index_type
	Get the number of function evaluations.

auto	gradient () const -> const variable_type &
	Get gradient for current optimal variable.

auto	gradient_norm () const -> value_type
	Calculate norm of gradient.

void	init (const variable_type &init_variable)
	Initialize.

auto	iterations () const noexcept -> index_type
	Get the number of iterations.

auto	line_searcher () -> line_searcher_type &
	Access object to perform line search.

auto	line_searcher () const -> const line_searcher_type &
	Access object to perform line search.

auto	opt_value () const -> const value_type &
	Get current optimal value.

auto	opt_variable () const -> const variable_type &
	Get current optimal variable.

Public Member Functions inherited from num_collect::opt::descent_method_base< Derived, LineSearcher >
auto	calc_direction () -> variable_type
	Calculate search direction.

auto	evaluations () const noexcept -> index_type
	Get the number of function evaluations.

auto	gradient () const -> const variable_type &
	Get gradient for current optimal variable.

auto	gradient_norm () const -> value_type
	Calculate norm of gradient.

void	init (const variable_type &init_variable)
	Initialize.

auto	is_stop_criteria_satisfied () const -> bool
	Determine if stopping criteria of the algorithm are satisfied.

void	iterate ()
	Iterate the algorithm once.

auto	iterations () const noexcept -> index_type
	Get the number of iterations.

auto	line_searcher () -> line_searcher_type &
	Access object to perform line search.

auto	line_searcher () const -> const line_searcher_type &
	Access object to perform line search.

auto	opt_value () const -> const value_type &
	Get current optimal value.

auto	opt_variable () const -> const variable_type &
	Get current optimal variable.

auto	tol_gradient_norm (const value_type &value) -> Derived &
	Set tolerance of norm of gradient.

Public Member Functions inherited from num_collect::opt::optimizer_base< Derived >
	optimizer_base (logging::log_tag_view tag)
	Constructor.

auto	evaluations () const noexcept -> index_type
	Get the number of function evaluations.

auto	iterations () const noexcept -> index_type
	Get the number of iterations.

auto	opt_value () const
	Get current optimal value.

auto	opt_variable () const
	Get current optimal variable.

Public Member Functions inherited from num_collect::base::iterative_solver_base< Derived >
	iterative_solver_base (logging::log_tag_view tag)
	Constructor.

auto	is_stop_criteria_satisfied () const -> bool
	Determine if stopping criteria of the algorithm are satisfied.

void	iterate ()
	Iterate the algorithm once.

void	solve ()
	Solve the problem.

Public Member Functions inherited from num_collect::logging::logging_mixin
	logging_mixin (log_tag_view tag)
	Constructor.

template<typename Child >
void	configure_child_algorithm_logger_if_exists (Child &child)
	Configure a logger of a child algorithm if exists.

auto	logger () const noexcept -> const num_collect::logging::logger &
	Access to the logger.

auto	logger () noexcept -> num_collect::logging::logger &
	Access to the logger.

Public Member Functions inherited from num_collect::logging::iterations::iteration_logger_mixin< Derived >
	iteration_logger_mixin ()=default
	Constructor.

void	configure_iteration_logger (num_collect::logging::iterations::iteration_logger< Derived > &iteration_logger) const
	Configure an iteration logger.

auto	initialize_iteration_logger () -> num_collect::logging::iterations::iteration_logger< Derived > &
	Get the iteration logger.

Private Attributes
variable_type	direction_ {}
	Search direction.

bool	has_first_iteration_done_ {false}
	Whether the first iteration has been done.

variable_type	prev_grad_ {}
	Previous gradient.

Additional Inherited Members
Protected Member Functions inherited from num_collect::opt::descent_method_base< Derived, LineSearcher >
	descent_method_base (logging::log_tag_view tag, const objective_function_type &obj_fun=objective_function_type())
	Constructor.

Protected Member Functions inherited from num_collect::base::iterative_solver_base< Derived >
auto	derived () const noexcept -> const Derived &
	Access derived object.

auto	derived () noexcept -> Derived &
	Access derived object.

Detailed Description

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>
class num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >

Class of conjugate gradient method for optimization.

Warning: This implementation assumes Eigen's dense vector types for variable types.

Template Parameters

ObjectiveFunction	Type of the objective function.
LineSearcher	Type of class to perform line search.

Todo: Conjugate gradient method for optimization may need to be fixed for faster convergence.

Definition at line 52 of file conjugate_gradient_optimizer.h.

Member Typedef Documentation

◆ base_type

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

using num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::base_type = descent_method_base<this_type, LineSearcher>

Type of base class.

Definition at line 62 of file conjugate_gradient_optimizer.h.

◆ objective_function_type

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

using num_collect::opt::descent_method_base< Derived, LineSearcher >::objective_function_type

Type of the objective function.

Definition at line 42 of file descent_method_base.h.

◆ this_type

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

using num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::this_type

Initial value:

conjugate_gradient_optimizer<ObjectiveFunction, LineSearcher>

num_collect::opt::conjugate_gradient_optimizer::conjugate_gradient_optimizer

conjugate_gradient_optimizer(const objective_function_type &obj_fun=objective_function_type())

Constructor.

Definition conjugate_gradient_optimizer.h:75

This class.

Definition at line 58 of file conjugate_gradient_optimizer.h.

◆ value_type

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

using num_collect::opt::descent_method_base< Derived, LineSearcher >::value_type

Type of function values.

Definition at line 49 of file descent_method_base.h.

◆ variable_scalar_type

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

using num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::variable_scalar_type = typename variable_type::Scalar

Type of scalars in variables.

Definition at line 68 of file conjugate_gradient_optimizer.h.

◆ variable_type

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

using num_collect::opt::descent_method_base< Derived, LineSearcher >::variable_type

Type of variables.

Definition at line 46 of file descent_method_base.h.

Constructor & Destructor Documentation

◆ conjugate_gradient_optimizer()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::conjugate_gradient_optimizer ( const objective_function_type & obj_fun = objective_function_type() )

inlineexplicit

Constructor.

Parameters

[in] obj_fun Objective function.

Definition at line 75 of file conjugate_gradient_optimizer.h.

Member Function Documentation

◆ calc_direction()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::calc_direction ( ) -> variable_type

inlinenodiscard

Calculate search direction.

Returns: Search direction.

Definition at line 101 of file conjugate_gradient_optimizer.h.

◆ configure_iteration_logger()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

void num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::configure_iteration_logger ( logging::iterations::iteration_logger< this_type > & iteration_logger ) const

inline

Configure an iteration logger.

Parameters

[in] iteration_logger Iteration logger.

Definition at line 122 of file conjugate_gradient_optimizer.h.

◆ evaluations()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::evaluations ( ) const -> index_type

inlinenodiscardnoexcept

Get the number of function evaluations.

Returns: Number of function evaluations.

Definition at line 127 of file descent_method_base.h.

◆ gradient()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::gradient ( ) const -> const variable_type&

inlinenodiscard

Get gradient for current optimal variable.

Returns: Gradient for current optimal variable.

Definition at line 136 of file descent_method_base.h.

◆ gradient_norm()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::gradient_norm ( ) const -> value_type

inlinenodiscard

Calculate norm of gradient.

Returns: Norm of gradient.

Definition at line 145 of file descent_method_base.h.

◆ init()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

void num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::init ( const variable_type & init_variable )

inline

Initialize.

Parameters

[in] init_variable Initial variable.

Definition at line 93 of file conjugate_gradient_optimizer.h.

◆ iterations()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::iterations ( ) const -> index_type

inlinenodiscardnoexcept

Get the number of iterations.

Returns: Number of iterations.

Definition at line 120 of file descent_method_base.h.

◆ line_searcher() [1/2]

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::line_searcher ( ) -> line_searcher_type&

inlinenodiscard

Access object to perform line search.

Returns: Object to perform line search.

Definition at line 90 of file descent_method_base.h.

◆ line_searcher() [2/2]

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::line_searcher ( ) const -> const line_searcher_type&

inlinenodiscard

Access object to perform line search.

Returns: Object to perform line search.

Definition at line 99 of file descent_method_base.h.

◆ opt_value()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::opt_value ( ) const -> const value_type&

inlinenodiscard

Get current optimal value.

Returns: Current optimal value.

Definition at line 113 of file descent_method_base.h.

◆ opt_variable()

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

auto num_collect::opt::descent_method_base< Derived, LineSearcher >::opt_variable ( ) const -> const variable_type&

inlinenodiscard

Get current optimal variable.

Returns: Current optimal variable.

Definition at line 106 of file descent_method_base.h.

Member Data Documentation

◆ direction_

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

variable_type num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::direction_ {}

private

Search direction.

Definition at line 140 of file conjugate_gradient_optimizer.h.

◆ has_first_iteration_done_

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

bool num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::has_first_iteration_done_ {false}

private

Whether the first iteration has been done.

Definition at line 143 of file conjugate_gradient_optimizer.h.

◆ prev_grad_

template<concepts::multi_variate_differentiable_objective_function ObjectiveFunction, concepts::line_searcher LineSearcher = backtracking_line_searcher<ObjectiveFunction>>

variable_type num_collect::opt::conjugate_gradient_optimizer< ObjectiveFunction, LineSearcher >::prev_grad_ {}

private

Previous gradient.

Definition at line 137 of file conjugate_gradient_optimizer.h.

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

include/num_collect/opt/conjugate_gradient_optimizer.h

Public Types

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ base_type

◆ objective_function_type

◆ this_type

◆ value_type

◆ variable_scalar_type

◆ variable_type

Constructor & Destructor Documentation

◆ conjugate_gradient_optimizer()

Member Function Documentation

◆ calc_direction()

◆ configure_iteration_logger()

◆ evaluations()

◆ gradient()

◆ gradient_norm()

◆ init()

◆ iterations()

◆ line_searcher() [1/2]

◆ line_searcher() [2/2]

◆ opt_value()

◆ opt_variable()

Member Data Documentation

◆ direction_

◆ has_first_iteration_done_

◆ prev_grad_