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| Real_hmc_step (const Target_distribution &log_target, int num_dynamics_steps, const Gradient &gradient, const Get_step_size &get_step_size, double alpha=0.0) |
| Creates a Real_hmc_step. More...
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| Real_hmc_step (const Target_distribution &log_target, int num_dynamics_steps, const Gradient &gradient, double step_size, double alpha=0.0) |
| Creates a Real_hmc_step with a constant step size. More...
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| Real_hmc_step (const Target_distribution &log_target, int num_dynamics_steps, const Gradient &gradient, double step_size, double lower_bound, double upper_bound, double alpha=0.0) |
| Creates a Real_hmc_step with a constant step size. More...
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virtual | ~Real_hmc_step () |
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| 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...
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| 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) |
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void | record_extra (bool enable) |
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void | set_post_move_callback (const boost::function2< void, Model &, kjb::Vector & > &f) |
| Copy-constructor. More...
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virtual | ~Basic_hmc_step () |
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virtual const Target_distribution & | get_log_target () const |
| Returns a reference to the target distribution. Returned object must comply with the ModelEvaluator concept. More...
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virtual const Gradient & | get_gradient () const |
| Returns a reference to the mechanism to compute the gradient of the target distribution. More...
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virtual const Move_parameter & | get_move_parameter () const |
| Returns a reference to the parameter-changing mechanism. Must comply with the ChangeParameter concept. More...
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virtual const Get_step_size & | get_step_size_function () const |
| Returns a reference to the mechanism for choosing the neighborhoods for each parameters. More...
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virtual const Get_dimension & | get_dimension_function () const |
| Returns a reference to the mechanism for computing the dimension of the model. More...
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virtual bool | record_extra () const |
| if true is returned, the step log will contain metadata about the step More...
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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...
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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...
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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...
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virtual void | post_move_callback (Model &q, kjb::Vector &p) const |
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| BOOST_CONCEPT_ASSERT ((BaseModel< Model >)) |
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| Abstract_hmc_step (int num_dynamics_steps, double alpha) |
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bool | is_first_p_full (const bool alpha, const bool accept_step, const bool reversible) |
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bool | is_last_p_ignored (const bool alpha, const bool accept_step, const bool reversible) |
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| Abstract_hmc_step (const Abstract_hmc_step &ahs) |
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virtual Step_log< Model > | operator() (Model &q, double lt_q) const |
| Runs a step of Hybrid Monte-Carlo (HMC) on a model m. More...
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void | set_temperature (const double T) |
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virtual | ~Abstract_hmc_step () |
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template<typename Model, bool CONSTRAINED_TARGET = false, bool INCLUDE_ACCEPT_STEP = true, bool REVERSIBLE = true>
class Real_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE >
- Template Parameters
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Model | The model type. Must comply with VectorModel concept; i.e.,. must have [] and .size() defined and its elements must be convertible to double. |
Real_hmc_step is a functor that runs a single step of hybrid Monte Carlo on a vector model