Class markov::ClusterWalker

ClusterWalker is an abstract base class for quantum like space explorers

A ClusterWalker stores multiple state and costs and has pointers to a model and random number generator to make steps. It is specifically designed to allow copy assignment (assuming the Model::State_T does), such that it can be duplicated in population markovs. The Walker provides a base implementation of the step function, which

  • proposes a random new states,
  • computes the cost differences,
  • uses virtual method to decide whether to create cluster binded
  • variables from multiple states
  • invokes a pure virtual method to decide whether to accept, and
  • modifies the internal states using cluster if true is returned.

From this we can implement a QuantumWalker by returning acceptance rate based on quantum transverse field.

Inheritance
utils::Component
markov::ClusterWalker
markov::QuantumWalker
Inherited Members

Constructors

ClusterWalker()

The rng and model must be set before the object can be used. cost is only intialized after a call to init()

Declaration
markov::ClusterWalker<Model>::ClusterWalker()

Methods

init()

Must be called after the rng_ and model_ have been set. It initializes the walker to a random state and precomputes its current cost.

Note

This is typically the only direct call to calculate_cost; from here the current cost_ is updated from the computed difference at each step.

Declaration
virtual void markov::ClusterWalker<Model>::init(size_t n_states=1)

init_state()

Declaration
void markov::ClusterWalker<Model>::init_state(size_t state_index, ::utils::RandomGenerator&rng)

accept()

Implementations of the walker interface must provide a method to decide which steps to accept/reject. Currently this is only based on cost_difference, but the state or transition could be added.

Declaration
virtual bool markov::ClusterWalker<Model>::accept(const typename Model::Cost_T&cost_difference, ::utils::RandomGenerator&rng)=0

accept_cluster()

Implementations of the walker interface must provide a method to decide which cluster to accept/reject.

Declaration
virtual bool markov::ClusterWalker<Model>::accept_cluster(::utils::RandomGenerator&rng)=0

get_transition()

For models with a 'size_t' transition type, do an ordered sweep.

Declaration
std::enable_if<std::is_same<TT, size_t>::value, void>::type markov::ClusterWalker<Model>::get_transition(size_t variable_index, typename Model::Transition_T&transition, utils::RandomGenerator&)

get_transition()

For any other transition type, do a random sweep.

Declaration
std::enable_if<!std::is_same<TT, size_t>::value, void>::type markov::ClusterWalker<Model>::get_transition(size_t, typename Model::Transition_T&transition, utils::RandomGenerator&rng)

set_model()

Provide a pointer to the (non-owned) model to use for cost calculations and proposing new steps.

Declaration
void markov::ClusterWalker<Model>::set_model(const Model *model)

model()

Return a constant reference to the model being used.

Declaration
const Model&markov::ClusterWalker<Model>::model()

get_evaluation_counter()

Declaration
solver::EvaluationCounter markov::ClusterWalker<Model>::get_evaluation_counter()

add_difference_evaluations()

Declaration
void markov::ClusterWalker<Model>::add_difference_evaluations(size_t number_evals)

add_function_evaluations()

Declaration
void markov::ClusterWalker<Model>::add_function_evaluations(size_t number_evals)

reset_evaluation_counter()

Declaration
void markov::ClusterWalker<Model>::reset_evaluation_counter()

get_lowest_cost()

Declaration
Model::Cost_T markov::ClusterWalker<Model>::get_lowest_cost() const

get_lowest_state()

Declaration
const Model::State_T&markov::ClusterWalker<Model>::get_lowest_state() const

get_states()

Declaration
const std::vector<typename Model::State_T>&markov::ClusterWalker<Model>::get_states()

get_costs()

Declaration
const std::vector<typename Model::Cost_T>&markov::ClusterWalker<Model>::get_costs()

size()

Declaration
size_t markov::ClusterWalker<Model>::size()

try_form_clusters()

Declaration
void markov::ClusterWalker<Model>::try_form_clusters(size_t state_index, const typename Model::Transition_T&transition, utils::RandomGenerator&rng)

try_flip_clusters()

Declaration
void markov::ClusterWalker<Model>::try_flip_clusters(size_t state_index, utils::RandomGenerator&rng)

calculate_cost_diff()

For models derived from model::FacedGraphModel, an extra parameter for a cost object is necessary to communicate cached calculations.

Declaration
std::enable_if<!std::is_base_of<model::FacedGraphModel<TS, TT>, TM>::value, void>::type markov::ClusterWalker<Model>::calculate_cost_diff(size_t state_index, const typename Model::Transition_T&transition)

calculate_cost_diff()

For models derived from model::FacedGraphModel, an extra parameter for a cost object is necessary to communicate cached calculations.

Declaration
std::enable_if<std::is_base_of<model::FacedGraphModel<TS, TT>, TM>::value, void>::type markov::ClusterWalker<Model>::calculate_cost_diff(size_t state_index, const typename Model::Transition_T&transition)

apply_transition()

For models derived from model::FacedGraphModel, an extra parameter for a cost object is necessary to communicate cached calculations.

Declaration
std::enable_if<!std::is_base_of<model::FacedGraphModel<TS, TT>, TM>::value, void>::type markov::ClusterWalker<Model>::apply_transition(size_t state_index, const typename Model::Transition_T&transition)

apply_transition()

For models derived from model::FacedGraphModel, an extra parameter for a cost object is necessary to communicate cached calculations.

Declaration
std::enable_if<std::is_base_of<model::FacedGraphModel<TS, TT>, TM>::value, void>::type markov::ClusterWalker<Model>::apply_transition(size_t state_index, const typename Model::Transition_T&transition)

save_lowest()

Store the current lowest state as the lowest.

Declaration
void markov::ClusterWalker<Model>::save_lowest()

memory_estimate()

Estimate memory consumtion using model parameters.

Declaration
static size_t markov::ClusterWalker<Model>::memory_estimate(const Model&model, size_t n_states)

compare()

Declaration
static bool markov::ClusterWalker<Model>::compare(const ClusterWalker<Model>&w1, const ClusterWalker<Model>&w2)