jade::basic_optimizer< TValue > Class Template Reference

A template for a class that optimizes the Q and F matrices. More...

#include <jade.optimizer.hpp>

Collaboration diagram for jade::basic_optimizer< TValue >:

Public Types
typedef TValue	value_type
	The value type. More...
typedef basic_matrix< value_type >	matrix_type
	The matrix type. More...
typedef basic_options< value_type >	options_type
	The options type. More...
typedef basic_settings< value_type >	settings_type
	The settings type. More...
typedef basic_improver< value_type >	improver_type
	The improver type. More...
typedef TValue	value_type
	The value type. More...
typedef basic_controller< value_type >	controller_type
	The controller type. More...
typedef basic_controller_factory< value_type >	controller_factory_type
	The controller factory type. More...
typedef basic_settings< value_type >	settings_type
	The settings type. More...
typedef controller_type::simplex_type	simplex_type
	The simplex type. More...
typedef simplex_type::container_type	container_type
	The container type for the simplex. More...
typedef simplex_type::log_args	log_args_type
	The log arguments type for the simplex. More...
typedef TValue	value_type
	The value type. More...
typedef basic_matrix< value_type >	matrix_type
	The matrix type. More...
typedef basic_options< value_type >	options_type
	The options type. More...
typedef basic_settings< value_type >	settings_type
	The settings type. More...
typedef basic_improver< value_type >	improver_type
	The improver type. More...

Static Public Member Functions
static void	execute (const settings_type &settings, matrix_type &q0, matrix_type &f0)
	Executes the optimization process. More...
static void	execute (const settings_type &settings)
	Executes the optimizer based on the specified settings. More...
static void	execute (const settings_type &settings, matrix_type &q0, matrix_type &f0)
	Executes the optimization process. More...

Detailed Description

template<typename TValue>
class jade::basic_optimizer< TValue >

A template for a class that optimizes the Q and F matrices.

A template for a class that optimizes specified program settings.

Definition at line 20 of file cpax/jade.optimizer.hpp.

Member Typedef Documentation

container_type

template<typename TValue >

typedef simplex_type::container_type jade::basic_optimizer< TValue >::container_type

The container type for the simplex.

Definition at line 37 of file nemeco/jade.optimizer.hpp.

controller_factory_type

template<typename TValue >

typedef basic_controller_factory<value_type> jade::basic_optimizer< TValue >::controller_factory_type

The controller factory type.

Definition at line 28 of file nemeco/jade.optimizer.hpp.

controller_type

template<typename TValue >

typedef basic_controller<value_type> jade::basic_optimizer< TValue >::controller_type

The controller type.

Definition at line 25 of file nemeco/jade.optimizer.hpp.

improver_type [1/2]

template<typename TValue >

typedef basic_improver<value_type> jade::basic_optimizer< TValue >::improver_type

The improver type.

Definition at line 36 of file cpax/jade.optimizer.hpp.

improver_type [2/2]

template<typename TValue >

typedef basic_improver<value_type> jade::basic_optimizer< TValue >::improver_type

The improver type.

Definition at line 36 of file qpas/jade.optimizer.hpp.

log_args_type

template<typename TValue >

typedef simplex_type::log_args jade::basic_optimizer< TValue >::log_args_type

The log arguments type for the simplex.

Definition at line 40 of file nemeco/jade.optimizer.hpp.

matrix_type [1/2]

template<typename TValue >

typedef basic_matrix<value_type> jade::basic_optimizer< TValue >::matrix_type

The matrix type.

Definition at line 27 of file cpax/jade.optimizer.hpp.

matrix_type [2/2]

template<typename TValue >

typedef basic_matrix<value_type> jade::basic_optimizer< TValue >::matrix_type

The matrix type.

Definition at line 27 of file qpas/jade.optimizer.hpp.

options_type [1/2]

template<typename TValue >

typedef basic_options<value_type> jade::basic_optimizer< TValue >::options_type

The options type.

Definition at line 30 of file cpax/jade.optimizer.hpp.

options_type [2/2]

template<typename TValue >

typedef basic_options<value_type> jade::basic_optimizer< TValue >::options_type

The options type.

Definition at line 30 of file qpas/jade.optimizer.hpp.

settings_type [1/3]

template<typename TValue >

typedef basic_settings<value_type> jade::basic_optimizer< TValue >::settings_type

The settings type.

Definition at line 33 of file cpax/jade.optimizer.hpp.

settings_type [2/3]

template<typename TValue >

typedef basic_settings<value_type> jade::basic_optimizer< TValue >::settings_type

The settings type.

Definition at line 31 of file nemeco/jade.optimizer.hpp.

settings_type [3/3]

template<typename TValue >

typedef basic_settings<value_type> jade::basic_optimizer< TValue >::settings_type

The settings type.

Definition at line 33 of file qpas/jade.optimizer.hpp.

simplex_type

template<typename TValue >

typedef controller_type::simplex_type jade::basic_optimizer< TValue >::simplex_type

The simplex type.

Definition at line 34 of file nemeco/jade.optimizer.hpp.

value_type [1/3]

template<typename TValue >

typedef TValue jade::basic_optimizer< TValue >::value_type

The value type.

Definition at line 24 of file cpax/jade.optimizer.hpp.

value_type [2/3]

template<typename TValue >

typedef TValue jade::basic_optimizer< TValue >::value_type

The value type.

Definition at line 22 of file nemeco/jade.optimizer.hpp.

value_type [3/3]

template<typename TValue >

typedef TValue jade::basic_optimizer< TValue >::value_type

The value type.

Definition at line 24 of file qpas/jade.optimizer.hpp.

Member Function Documentation

execute() [1/3]

template<typename TValue >

static void jade::basic_optimizer< TValue >::execute ( const settings_type &  settings )

inlinestatic

Executes the optimizer based on the specified settings.

Parameters

settings

The settings used to optimize.

Definition at line 45 of file nemeco/jade.optimizer.hpp.

        {
            std::cout << "iter\tduration\tdelta-lle\tlog-likelihood\n";
 
            const auto & opts = settings.get_options();
 
            //
            // Depending upon whether or not the user specified a Newick tree,
            // construct the appropriate controller for the Nelder-Mead
            // algorithm, and use it to compute the objective function.
            //
            std::unique_ptr< controller_type > ctrl (
                controller_factory_type::create(settings));
            const auto objfunc = [&](const container_type & params)
                -> value_type { return ctrl->compute_objfunc(params); };
 
            //
            // Initialize the Nelder-Mead algorithm.
            //
            typedef typename simplex_type::options options_type;
            options_type options (ctrl->init_parameters());
            simplex_type simplex (objfunc, options);
 
            //
            // Instruct the Nelder-Mead algorithm to use the settings based on
            // supplied program options.
            //
            typedef typename simplex_type::execute_args execute_args_type;
            execute_args_type execute_args;
            execute_args.user    = ctrl.get();
            execute_args.logfunc = _logfunc;
            if (opts.is_max_iterations_specified())
                execute_args.max_iterations = opts.get_max_iterations();
            if (opts.is_max_time_specified())
                execute_args.max_seconds = opts.get_max_time();
            if (opts.is_epsilon_specified())
                execute_args.min_epsilon = opts.get_epsilon();
 
            //
            // Perform the minimization.
            //
            const auto condition = simplex.execute(objfunc, execute_args);
 
            //
            // Emit results.
            //
            ctrl->emit_results(opts, simplex, condition);
        }

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execute() [2/3]

template<typename TValue >

static void jade::basic_optimizer< TValue >::execute ( const settings_type &  settings, matrix_type &  q0, matrix_type &  f0  )

inlinestatic

Executes the optimization process.

Parameters

settings	The settings.
q0	The initial Q matrix.
f0	The initial F matrix.

Definition at line 41 of file cpax/jade.optimizer.hpp.

        {
            //
            // Release memory for the initial Q and F matrices.
            //
            matrix_type q, fa;
            q0.swap(q);
            f0.swap(fa);
 
            _clamp_f(settings, fa);
 
            const auto & opts = settings.get_options();
            const auto   fg   = settings.get_fg();
            const auto   fif  = settings.get_fif();
            const auto & g    = settings.get_g();
            const auto   frb  = opts.is_frb();
 
            const stopwatch sw1;
 
            matrix_type fb (fa.get_height(), fa.get_width());
            _compute_fb(fa, fb);
 
            matrix_type qfa = q * fa;
            matrix_type qfb = q * fb;
 
            auto lle = g.compute_lle(q, fa, fb, qfa, qfb);
            _emit_header(settings, sw1, lle);
 
            for (size_t iter = 1;; iter++)
            {
                if (opts.is_max_iterations_specified())
                    if (iter > opts.get_max_iterations())
                        break;
 
                if (opts.is_max_time_specified())
                    if (sw1 > opts.get_max_time())
                        break;
 
                const stopwatch sw2;
 
                if (!opts.is_fixed_q())
                {
                    q = improver_type::improve_q(g, q, fa, fb, qfa, qfb, fg);
                    matrix_type::gemm(q, fa, qfa);
                    matrix_type::gemm(q, fb, qfb);
                }
 
                if (!opts.is_fixed_f())
                {
                    fa = improver_type::improve_f(g, q, fa, fb, qfa, qfb, fif, frb);
                    _clamp_f(settings, fa);
                    _compute_fb(fa, fb);
                    matrix_type::gemm(q, fa, qfa);
                    matrix_type::gemm(q, fb, qfb);
                }
 
                const auto lle_prime = g.compute_lle(q, fa, fb, qfa, qfb);
                const auto dlle      = lle_prime - lle;
 
                _emit_line(settings, sw2, iter, lle_prime, dlle);
 
                lle = lle_prime;
 
                if (opts.is_epsilon_specified())
                    if (dlle >= value_type(0) && dlle <= opts.get_epsilon())
                        break;
            }
 
            _emit_results(settings, q, fa);
        }

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execute() [3/3]

template<typename TValue >

static void jade::basic_optimizer< TValue >::execute ( const settings_type &  settings, matrix_type &  q0, matrix_type &  f0  )

inlinestatic

Executes the optimization process.

Parameters

settings	The settings.
q0	The initial Q matrix.
f0	The initial F matrix.

Definition at line 41 of file qpas/jade.optimizer.hpp.

        {
            //
            // Release memory for the initial Q and F matrices.
            //
            matrix_type q, fa;
            q0.swap(q);
            f0.swap(fa);
 
            _clamp_f(settings, fa);
 
            const auto & opts = settings.get_options();
            const auto   fg   = settings.get_fg();
            const auto   fif  = settings.get_fif();
            const auto & g    = settings.get_g();
            const auto   frb  = opts.is_frb();
 
            const stopwatch sw1;
 
            matrix_type fb (fa.get_height(), fa.get_width());
            _compute_fb(fa, fb);
 
            matrix_type qfa = q * fa;
            matrix_type qfb = q * fb;
 
            auto lle = g.compute_lle(q, fa, fb, qfa, qfb);
            _emit_header(settings, sw1, lle);
 
            for (size_t iter = 1;; iter++)
            {
                if (opts.is_max_iterations_specified())
                    if (iter > opts.get_max_iterations())
                        break;
 
                if (opts.is_max_time_specified())
                    if (sw1 > opts.get_max_time())
                        break;
 
                const stopwatch sw2;
 
                if (!opts.is_fixed_q())
                {
                    q = improver_type::improve_q(g, q, fa, fb, qfa, qfb, fg);
                    matrix_type::gemm(q, fa, qfa);
                    matrix_type::gemm(q, fb, qfb);
                }
 
                if (!opts.is_fixed_f())
                {
                    fa = improver_type::improve_f(g, q, fa, fb, qfa, qfb, fif, frb);
                    _clamp_f(settings, fa);
                    _compute_fb(fa, fb);
                    matrix_type::gemm(q, fa, qfa);
                    matrix_type::gemm(q, fb, qfb);
                }
 
                const auto lle_prime = g.compute_lle(q, fa, fb, qfa, qfb);
                const auto dlle      = lle_prime - lle;
 
                _emit_line(settings, sw2, iter, lle_prime, dlle);
 
                lle = lle_prime;
 
                if (opts.is_epsilon_specified())
                    if (dlle >= value_type(0) && dlle <= opts.get_epsilon())
                        break;
            }
 
            _emit_results(settings, q, fa);
        }

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

• cpax/jade.optimizer.hpp