#include <sample_step.h>

Inheritance diagram for Basic_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >:

Public Types
typedef Abstract_hmc_step < Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >	Parent

typedef Parent::Target_distribution	Target_distribution

typedef Parent::Gradient	Gradient

typedef Parent::Move_parameter	Move_parameter

typedef Parent::Get_step_size	Get_step_size

typedef Parent::Get_dimension	Get_dimension

typedef Parent::Get_parameter	Get_parameter

typedef Parent::Get_lower_bounds	Get_lower_bounds

typedef Parent::Get_upper_bounds	Get_upper_bounds

Public Types inherited from Abstract_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >
typedef Model_evaluator< Model > ::Type	Target_distribution

typedef Model_parameter_evaluator < Model >::Type	Gradient

typedef Move_model_parameter < Model >::Type	Move_parameter

typedef Model_parameter_evaluator < Model >::Type	Get_step_size

typedef Model_dimension< Model > ::Type	Get_dimension

typedef Get_model_parameter < Model >::Type	Get_parameter

typedef Model_parameter_evaluator < Model >::Type	Get_lower_bounds

typedef Model_parameter_evaluator < Model >::Type	Get_upper_bounds

Public Member Functions
	Basic_hmc_step (const Target_distribution &log_target, int num_dynamics_steps, const Gradient &gradient, const Move_parameter &move_parameter, const Get_step_size &get_step_size, const Get_dimension &get_dimension, double alpha=0.0)
	Creates a Basic_hmc_step by initializing target and proposer functors (or functions) to the given arguments. More...

	Basic_hmc_step (const Target_distribution &log_target, int num_dynamics_steps, const Gradient &gradient, const Move_parameter &move_parameter, const Get_step_size &get_step_size, const Get_dimension &get_dimension, const Get_parameter &get_parameter, const Get_lower_bounds &get_lower_bounds, const Get_upper_bounds &get_upper_bounds, double alpha=0.0)

void	record_extra (bool enable)

void	set_post_move_callback (const boost::function2< void, Model &, kjb::Vector & > &f)
	Copy-constructor. More...

virtual	~Basic_hmc_step ()

virtual const Target_distribution &	get_log_target () const
	Returns a reference to the target distribution. Returned object must comply with the ModelEvaluator concept. More...

virtual const Gradient &	get_gradient () const
	Returns a reference to the mechanism to compute the gradient of the target distribution. More...

virtual const Move_parameter &	get_move_parameter () const
	Returns a reference to the parameter-changing mechanism. Must comply with the ChangeParameter concept. More...

virtual const Get_step_size &	get_step_size_function () const
	Returns a reference to the mechanism for choosing the neighborhoods for each parameters. More...

virtual const Get_dimension &	get_dimension_function () const
	Returns a reference to the mechanism for computing the dimension of the model. More...

virtual bool	record_extra () const
	if true is returned, the step log will contain metadata about the step More...

virtual const Get_parameter &	get_parameter_function () const
	Returns a reference to the mechanism for getting the value of a dimension of the model. More...

virtual const Get_lower_bounds &	get_lower_bounds_function () const
	Returns a reference to the mechanism for getting the lower bounds of a function. More...

virtual const Get_upper_bounds &	get_upper_bounds_function () const
	Returns a reference to the mechanism for getting the upper bounds of a function. More...

virtual void	post_move_callback (Model &q, kjb::Vector &p) const

Public Member Functions inherited from Abstract_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >
	BOOST_CONCEPT_ASSERT ((BaseModel< Model >))

	Abstract_hmc_step (int num_dynamics_steps, double alpha)

bool	is_first_p_full (const bool alpha, const bool accept_step, const bool reversible)

bool	is_last_p_ignored (const bool alpha, const bool accept_step, const bool reversible)

	Abstract_hmc_step (const Abstract_hmc_step &ahs)

virtual Step_log< Model >	operator() (Model &q, double lt_q) const
	Runs a step of Hybrid Monte-Carlo (HMC) on a model m. More...

void	set_temperature (const double T)

virtual	~Abstract_hmc_step ()

Protected Attributes
Target_distribution	m_log_target

Gradient	m_gradient

Move_parameter	m_move_parameter

Get_step_size	m_get_step_size

Get_dimension	m_get_dimension

bool	m_record_extra

Get_parameter	m_get_parameter

Get_lower_bounds	m_get_lower_bounds

Get_upper_bounds	m_get_upper_bounds

boost::function2< void, Model &, kjb::Vector & >	m_post_move_callback

Protected Attributes inherited from Abstract_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >
const int	m_num_dynamics_steps
	The number of leapfrog steps in the trajectory, "choosing a suitable trajectory length is crucial if HMC is to explore the stae space systematically, rather than by a random walk". "For a problem thought to be airly difficult, a trajectory with m_length = 100 might be a suitable starting point. More...

double	m_alpha
	Amount of stochastic update to apply to momentum. Set to zero for strict HMC. More...

kjb::Vector	p
	Momentum. More...

bool	m_first_p_full
	Optimization constants. Set to false for true MCMC. More...

bool	m_last_p_ignore

double	m_temperature

Detailed Description

template<typename Model, bool CONSTRAINED_TARGET = false, bool INCLUDE_ACCEPT_STEP = true, bool REVERSIBLE = true>
class Basic_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >

Template Parameters

Model	The model type. Must comply with HmcModel concept.
accept_step	Do a accept/reject step? This is true by default, which, if alpha = 0, makes this a true HMC step.

Basic_hmc_step is a functor that runs a single step of the generalized Hybrid Monte Carlo algorithm on a model.

This class is a subclass of the abstract class Abstract_hmc_step. It implements the get_* member functions from the abstract class in the obvious way: it returns references to private members of the correct types. These members are initialized from references received in the constructor.