A class that optimises a function using a Quasi-Newton or other method. More...

#include <OptimizeBFGS.h>

Inheritance diagram for molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >:

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Collaboration diagram for molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >:

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Detailed Description

template<class R, class Q = R, class P = std::map<size_t, typename R::value_type>>
class molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >

A class that optimises a function using a Quasi-Newton or other method.

Template Parameters

R	The class encapsulating solution and residual vectors
Q	Used internally as a class for storing vectors on backing store

Public Types
using	SolverTemplate = IterativeSolverTemplate< Optimize, R, Q, P >

using	SubspaceSolver = subspace::SubspaceSolverOptBFGS< R, Q, P >

Public Types inherited from molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >
using	value_type = typename R::value_type
	The underlying type of elements of vectors. More...

using	scalar_type = typename array::ArrayHandler< R, R >::value_type

using	value_type_abs = typename array::ArrayHandler< R, R >::value_type_abs

using	VectorP = std::vector< value_type >

using	fapply_on_p_type = std::function< void(const std::vector< VectorP > &, const CVecRef< std::map< size_t, typename R::value_type > > &, const VecRef< R > &)>

Public Member Functions
	OptimizeBFGS (const std::shared_ptr< ArrayHandlers< R, Q, P > > &handlers, const std::shared_ptr< Logger > &logger_=std::make_shared< Logger >())

bool	nonlinear () const override
	Report whether the class is a non-linear solver. More...

int	add_vector (R &parameters, R &residual, value_type value) override

void	BFGS_update_1 (R &residual, std::shared_ptr< const subspace::IXSpace< R, Q, P > > xspace, const Matrix< double > &H)

void	BFGS_update_2 (R &z, std::shared_ptr< const subspace::IXSpace< R, Q, P > > xspace, const Matrix< double > &H)

size_t	end_iteration (const VecRef< R > &parameters, const VecRef< R > &action) override
	Behaviour depends on the solver. More...

size_t	end_iteration (std::vector< R > &parameters, std::vector< R > &action) override

size_t	end_iteration (R &parameters, R &actions) override

void	set_value_errors () override
	Implementation class should overload this to set errors in the current values (e.g. change in eigenvalues) More...

void	set_max_size_qspace (int n)

int	get_max_size_qspace () const

void	set_options (const Options &options) override

std::shared_ptr< Options >	get_options () const override

void	report (std::ostream &cout, bool endl=true) const override
	Writes a report to cout output stream. More...

void	report (std::ostream &cout, bool endl=true) const override
	Writes a report to cout output stream. More...

void	report () const override
	Writes a report to std::cout. More...

Public Member Functions inherited from molpro::linalg::itsolv::IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > >
	IterativeSolverTemplate ()=delete

	IterativeSolverTemplate (const IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > > &)=delete

	IterativeSolverTemplate (IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > > &&) noexcept=default

IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > > &	operator= (const IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > > &)=delete

IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > > &	operator= (IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > > &&) noexcept=default

int	add_vector (const VecRef< R > &parameters, const VecRef< R > &actions) override

int	add_vector (std::vector< R > &parameters, std::vector< R > &actions) override

int	add_vector (R &parameters, R &actions, value_type value=0) override

size_t	add_p (const CVecRef< std::map< size_t, typename R::value_type > > &pparams, const array::Span< value_type > &pp_action_matrix, const VecRef< R > &parameters, const VecRef< R > &actions, fapply_on_p_type apply_p) override

void	clearP () override

void	solution (const std::vector< int > &roots, const VecRef< R > &parameters, const VecRef< R > &residual) override

void	solution (const std::vector< int > &roots, std::vector< R > &parameters, std::vector< R > &residual) override

void	solution (R &parameters, R &residual) override

void	solution_params (const std::vector< int > &roots, std::vector< R > &parameters) override

void	solution_params (const std::vector< int > &roots, const VecRef< R > &parameters) override

void	solution_params (R &parameters) override

std::vector< size_t >	suggest_p (const CVecRef< R > &solution, const CVecRef< R > &residual, size_t max_number, double threshold) override

const std::vector< int > &	working_set () const override

size_t	n_roots () const override

void	set_n_roots (size_t roots) override

void	set_options (const Options &options) override

std::shared_ptr< Options >	get_options () const override

const std::vector< scalar_type > &	errors () const override

const Statistics &	statistics () const override

void	report (std::ostream &cout, bool endl=true) const override

void	report () const override

void	set_convergence_threshold (double thresh) override

double	convergence_threshold () const override

void	set_convergence_threshold_value (double thresh) override

double	convergence_threshold_value () const override

void	set_verbosity (Verbosity v) override

void	set_verbosity (int v) override

Verbosity	get_verbosity () const override

void	set_max_iter (int n) override

int	get_max_iter () const override

void	set_max_p (int n) override

int	get_max_p () const override

void	set_p_threshold (double threshold) override

double	get_p_threshold () const override

const subspace::Dimensions &	dimensions () const override
	Access dimensions of the subspace. More...

scalar_type	value () const override

void	set_profiler (molpro::profiler::Profiler &profiler) override

const std::shared_ptr< molpro::profiler::Profiler > &	profiler () const override

bool	solve (const VecRef< R > &parameters, const VecRef< R > &actions, const Problem< R > &problem, bool generate_initial_guess=false) override

bool	solve (R &parameters, R &actions, const Problem< R > &problem, bool generate_initial_guess=false) override

bool	solve (std::vector< R > &parameters, std::vector< R > &actions, const Problem< R > &problem, bool generate_initial_guess=false) override

bool	test_problem (const Problem< R > &problem, R &v0, R &v1, int verbosity, double threshold) const override

Public Member Functions inherited from molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >
virtual	~IterativeSolver ()=default

	IterativeSolver ()=default

	IterativeSolver (const IterativeSolver< R, R, std::map< size_t, typename R::value_type > > &)=delete

	IterativeSolver (IterativeSolver< R, R, std::map< size_t, typename R::value_type > > &&) noexcept=default

IterativeSolver< R, R, std::map< size_t, typename R::value_type > > &	operator= (const IterativeSolver< R, R, std::map< size_t, typename R::value_type > > &)=delete

IterativeSolver< R, R, std::map< size_t, typename R::value_type > > &	operator= (IterativeSolver< R, R, std::map< size_t, typename R::value_type > > &&) noexcept=default

virtual bool	solve (const VecRef< R > &parameters, const VecRef< R > &actions, const Problem< R > &problem, bool generate_initial_guess=false)=0
	Simplified one-call solver. More...

virtual bool	solve (R &parameters, R &actions, const Problem< R > &problem, bool generate_initial_guess=false)=0

virtual bool	solve (std::vector< R > &parameters, std::vector< R > &actions, const Problem< R > &problem, bool generate_initial_guess=false)=0

virtual int	add_vector (const VecRef< R > &parameters, const VecRef< R > &actions)=0
	Take, typically, a current solution and residual, and add it to the solution space. More...

virtual int	add_vector (std::vector< R > &parameters, std::vector< R > &action)=0

virtual int	add_vector (R &parameters, R &action, value_type value=0)=0

virtual size_t	add_p (const CVecRef< std::map< size_t, typename R::value_type > > &pparams, const array::Span< value_type > &pp_action_matrix, const VecRef< R > &parameters, const VecRef< R > &action, fapply_on_p_type apply_p)=0
	Add P-space vectors to the expansion set for linear methods. More...

virtual void	clearP ()=0

virtual void	solution (const std::vector< int > &roots, const VecRef< R > &parameters, const VecRef< R > &residual)=0
	Construct solution and residual for a given set of roots. More...

virtual void	solution (const std::vector< int > &roots, std::vector< R > &parameters, std::vector< R > &residual)=0

virtual void	solution (R &parameters, R &residual)=0

virtual void	solution_params (const std::vector< int > &roots, const VecRef< R > &parameters)=0
	Constructs parameters of selected roots. More...

virtual void	solution_params (const std::vector< int > &roots, std::vector< R > &parameters)=0

virtual void	solution_params (R &parameters)=0

virtual size_t	end_iteration (const VecRef< R > &parameters, const VecRef< R > &residual)=0
	Behaviour depends on the solver. More...

virtual size_t	end_iteration (std::vector< R > &parameters, std::vector< R > &action)=0

virtual size_t	end_iteration (R &parameters, R &action)=0

virtual bool	end_iteration_needed ()=0
	signal whether end_iteration should be called More...

virtual std::vector< size_t >	suggest_p (const CVecRef< R > &solution, const CVecRef< R > &residual, size_t max_number, double threshold)=0
	Get the solver's suggestion of which degrees of freedom would be best to add to the P-space. More...

virtual const std::vector< int > &	working_set () const=0
	Working set of roots that are not yet converged. More...

virtual std::vector< scalar_type >	working_set_eigenvalues () const

virtual size_t	n_roots () const=0

virtual void	set_n_roots (size_t nroots)=0

virtual const std::vector< scalar_type > &	errors () const=0

virtual const Statistics &	statistics () const=0

virtual void	report (std::ostream &cout, bool endl=true) const=0
	Writes a report to cout output stream. More...

virtual void	report () const=0
	Writes a report to std::cout. More...

virtual void	set_convergence_threshold (double thresh)=0
	Sets the convergence threshold. More...

virtual double	convergence_threshold () const=0
	Reports the convergence threshold. More...

virtual void	set_convergence_threshold_value (double thresh)=0
	Sets the value convergence threshold. More...

virtual double	convergence_threshold_value () const=0
	Reports the value convergence threshold. More...

virtual void	set_verbosity (Verbosity v)=0

virtual void	set_verbosity (int v)=0

virtual Verbosity	get_verbosity () const=0

virtual void	set_max_iter (int n)=0

virtual int	get_max_iter () const=0

virtual void	set_max_p (int n)=0

virtual int	get_max_p () const=0

virtual void	set_p_threshold (double thresh)=0

virtual double	get_p_threshold () const=0

virtual const subspace::Dimensions &	dimensions () const=0

virtual void	set_options (const Options &options)=0

virtual std::shared_ptr< Options >	get_options () const=0

virtual scalar_type	value () const=0
	Report the function value for the current optimum solution. More...

virtual bool	nonlinear () const=0
	Report whether the class is a non-linear solver. More...

virtual void	set_profiler (molpro::profiler::Profiler &profiler)=0
	Attach a profiler in order to collect performance data. More...

virtual const std::shared_ptr< molpro::profiler::Profiler > &	profiler () const=0

virtual bool	test_problem (const Problem< R > &problem, R &v0, R &v1, int verbosity=0, double threshold=1e-5) const=0
	Test a supplied problem class. More...

Public Attributes
std::shared_ptr< Logger >	logger

Protected Member Functions
void	construct_residual (const std::vector< int > &roots, const CVecRef< R > &params, const VecRef< R > &actions) override
	Constructs residual for given roots provided their parameters and actions. More...

Protected Member Functions inherited from molpro::linalg::itsolv::IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > >
	IterativeSolverTemplate (std::shared_ptr< subspace::IXSpace< R, R, std::map< size_t, typename R::value_type > > > xspace, std::shared_ptr< subspace::ISubspaceSolver< R, R, std::map< size_t, typename R::value_type > > > solver, std::shared_ptr< ArrayHandlers< R, R, std::map< size_t, typename R::value_type > > > handlers, std::shared_ptr< Statistics > stats, std::shared_ptr< Logger > logger)

virtual	~IterativeSolverTemplate ()

virtual void	set_value_errors ()
	Implementation class should overload this to set errors in the current values (e.g. change in eigenvalues) More...

virtual void	construct_residual (const std::vector< int > &roots, const CVecRef< R > &params, const VecRef< R > &actions)=0
	Constructs residual for given roots provided their parameters and actions. More...

virtual bool	linearEigensystem () const

size_t	solve_and_generate_working_set (const VecRef< R > &parameters, const VecRef< R > &action)
	Solves the subspace problems and selects the working set of roots, returning their parameters and residual in parameters and action. More...

void	check_consistent_number_of_roots_and_solutions (const std::vector< TTT > &roots, const size_t nparams)

bool	end_iteration_needed () override

Protected Attributes
std::vector< double >	m_BFGS_update_alpha

bool	m_linesearch

bool	m_last_iteration_linesearching = false

int	m_max_size_qspace = std::numeric_limits<int>::max()
	maximum size of Q space More...

bool	m_strong_Wolfe = true
	Whether to use strong or weak Wolfe conditions. More...

double	m_Wolfe_1 = 1e-4
	Acceptance parameter for function value; recommended value Nocedal and Wright p142. More...

double	m_Wolfe_2 = 0.9
	Acceptance parameter for function gradient; recommended value Nocedal and Wright p142. More...

double	m_linesearch_tolerance = .2

double	m_linesearch_grow_factor
	If the predicted line search step is extrapolation, limit the step to this factor times the current step. More...

double	m_quasinewton_maximum_step = std::numeric_limits<double>::max()

Protected Attributes inherited from molpro::linalg::itsolv::IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > >
std::shared_ptr< ArrayHandlers< R, R, std::map< size_t, typename R::value_type > > >	m_handlers
	Array handlers. More...

std::shared_ptr< subspace::IXSpace< R, R, std::map< size_t, typename R::value_type > > >	m_xspace
	manages the subspace and associated data More...

std::shared_ptr< subspace::ISubspaceSolver< R, R, std::map< size_t, typename R::value_type > > >	m_subspace_solver
	solves the subspace problem More...

std::vector< double >	m_errors
	errors from the most recent solution More...

std::vector< double >	m_value_errors
	value errors from the most recent solution More...

std::vector< int >	m_working_set
	indices of roots in the working set More...

size_t	m_nroots
	number of roots the solver is searching for More...

double	m_convergence_threshold
	residual norms less than this mark a converged solution More...

double	m_convergence_threshold_value
	value changes less than this mark a converged solution More...

std::shared_ptr< Statistics >	m_stats
	accumulates statistics of operations performed by the solver More...

std::shared_ptr< Logger >	m_logger
	logger More...

bool	m_normalise_solution
	whether to normalise the solutions More...

fapply_on_p_type	m_apply_p
	function that evaluates effect of action on the P space projection More...

Verbosity	m_verbosity
	how much output to print in solve() More...

int	m_max_iter
	maximum number of iterations in solve() More...

size_t	m_max_p
	maximum size of P space More...

double	m_p_threshold
	threshold for selecting P space More...

bool	m_end_iteration_needed
	whether end_iteration should be called after any preconditioner More...

Member Typedef Documentation

◆ SolverTemplate

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

using molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::SolverTemplate = IterativeSolverTemplate<Optimize, R, Q, P>

◆ SubspaceSolver

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

using molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::SubspaceSolver = subspace::SubspaceSolverOptBFGS<R, Q, P>

Constructor & Destructor Documentation

◆ OptimizeBFGS()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::OptimizeBFGS	(	const std::shared_ptr< ArrayHandlers< R, Q, P > > &	handlers,
		const std::shared_ptr< Logger > &	logger_ = `std::make_shared<Logger>()`
	)

inlineexplicit

Member Function Documentation

◆ add_vector()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

int molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::add_vector	(	R &	parameters,
		R &	residual,
		value_type	value
	)

inlineoverridevirtual

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ BFGS_update_1()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::BFGS_update_1	(	R &	residual,
		std::shared_ptr< const subspace::IXSpace< R, Q, P > >	xspace,
		const Matrix< double > &	H
	)

inline

◆ BFGS_update_2()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::BFGS_update_2	(	R &	z,
		std::shared_ptr< const subspace::IXSpace< R, Q, P > >	xspace,
		const Matrix< double > &	H
	)

inline

◆ construct_residual()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::construct_residual	(	const std::vector< int > &	roots,
		const CVecRef< R > &	params,
		const VecRef< R > &	actions
	)

inlineoverrideprotectedvirtual

Constructs residual for given roots provided their parameters and actions.

Implements molpro::linalg::itsolv::IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > >.

◆ end_iteration() [1/3]

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

size_t molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::end_iteration	(	const VecRef< R > &	parameters,
		const VecRef< R > &	residual
	)

inlineoverridevirtual

Behaviour depends on the solver.

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ end_iteration() [2/3]

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

size_t molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::end_iteration	(	R &	parameters,
		R &	actions
	)

inlineoverridevirtual

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ end_iteration() [3/3]

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

size_t molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::end_iteration	(	std::vector< R > &	parameters,
		std::vector< R > &	action
	)

inlineoverridevirtual

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ get_max_size_qspace()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

int molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::get_max_size_qspace ( ) const

inline

◆ get_options()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

std::shared_ptr< Options > molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::get_options ( ) const

inlineoverridevirtual

Return all options. This is no different than using getters, but can be used with forward declaration.

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ nonlinear()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

bool molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::nonlinear ( ) const

inlineoverridevirtual

Report whether the class is a non-linear solver.

Returns

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ report() [1/3]

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::IterativeSolverTemplate< Solver, R, Q, P >::report ( ) const

inlineoverridevirtual

Writes a report to std::cout.

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ report() [2/3]

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::IterativeSolverTemplate< Solver, R, Q, P >::report	(	std::ostream &	cout,
		bool	endl = `true`
	)		const

inlineoverridevirtual

Writes a report to cout output stream.

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ report() [3/3]

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::report	(	std::ostream &	cout,
		bool	endl = `true`
	)		const

inlineoverridevirtual

Writes a report to cout output stream.

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ set_max_size_qspace()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::set_max_size_qspace ( int n )

inline

Set a limit on the maximum size of Q space. This does not include the size of the working space (R) and the D space

◆ set_options()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::set_options ( const Options & options )

inlineoverridevirtual

Set all spcecified options. This is no different than using setters, but can be used with forward declaration.

Implements molpro::linalg::itsolv::IterativeSolver< R, R, std::map< size_t, typename R::value_type > >.

◆ set_value_errors()

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

void molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::set_value_errors ( )

inlineoverridevirtual

Implementation class should overload this to set errors in the current values (e.g. change in eigenvalues)

Reimplemented from molpro::linalg::itsolv::IterativeSolverTemplate< Optimize, R, R, std::map< size_t, typename R::value_type > >.

Member Data Documentation

◆ logger

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

std::shared_ptr<Logger> molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::logger

◆ m_BFGS_update_alpha

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

std::vector<double> molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_BFGS_update_alpha

protected

◆ m_last_iteration_linesearching

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

bool molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_last_iteration_linesearching = false

protected

◆ m_linesearch

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

bool molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_linesearch

protected

◆ m_linesearch_grow_factor

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

double molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_linesearch_grow_factor

protected

Initial value:

=

2

If the predicted line search step is extrapolation, limit the step to this factor times the current step.

◆ m_linesearch_tolerance

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

double molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_linesearch_tolerance = .2

protected

If the predicted line search is within tolerance of the recently-evaluated point, don't bother taking it, but proceed to Quasi-Newton instead

◆ m_max_size_qspace

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

int molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_max_size_qspace = std::numeric_limits<int>::max()

protected

maximum size of Q space

◆ m_quasinewton_maximum_step

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

double molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_quasinewton_maximum_step = std::numeric_limits<double>::max()

protected

◆ m_strong_Wolfe

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

bool molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_strong_Wolfe = true

protected

Whether to use strong or weak Wolfe conditions.

◆ m_Wolfe_1

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

double molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_Wolfe_1 = 1e-4

protected

Acceptance parameter for function value; recommended value Nocedal and Wright p142.

◆ m_Wolfe_2

template<class R , class Q = R, class P = std::map<size_t, typename R::value_type>>

double molpro::linalg::itsolv::OptimizeBFGS< R, Q, P >::m_Wolfe_2 = 0.9

protected

Acceptance parameter for function gradient; recommended value Nocedal and Wright p142.

Detailed Description

Public Types

Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Member Typedef Documentation

◆ SolverTemplate

◆ SubspaceSolver

Constructor & Destructor Documentation

◆ OptimizeBFGS()

Member Function Documentation

◆ add_vector()

◆ BFGS_update_1()

◆ BFGS_update_2()

◆ construct_residual()

◆ end_iteration() [1/3]

◆ end_iteration() [2/3]

◆ end_iteration() [3/3]

◆ get_max_size_qspace()

◆ get_options()

◆ nonlinear()

◆ report() [1/3]

◆ report() [2/3]

◆ report() [3/3]

◆ set_max_size_qspace()

◆ set_options()

◆ set_value_errors()

Member Data Documentation

◆ logger

◆ m_BFGS_update_alpha

◆ m_last_iteration_linesearching

◆ m_linesearch

◆ m_linesearch_grow_factor

◆ m_linesearch_tolerance

◆ m_max_size_qspace

◆ m_quasinewton_maximum_step

◆ m_strong_Wolfe

◆ m_Wolfe_1

◆ m_Wolfe_2