amr::Criteria::Random< CriteriaType > Class Template Reference

Randomly refine (or coarsen) an Element in each dimension. More...

#include <Random.hpp>

Classes
struct	ProbabilityWeights

Public Types
using	options = tmpl::list<ProbabilityWeights>
using	compute_tags_for_observation_box = tmpl::list<>
using	argument_tags = tmpl::list<>

Public Member Functions
	Random (std::unordered_map< amr::Flag, size_t > probability_weights)
Type	type () override
std::string	observation_name () override
template<size_t Dim, typename Metavariables>
auto	operator() (Parallel::GlobalCache< Metavariables > &, const ElementId< Dim > &element_id) const
void	pup (PUP::er &p) override
Public Member Functions inherited from amr::Criterion
	Criterion (CkMigrateMessage *msg)
	WRAPPED_PUPable_abstract (Criterion)
template<typename ComputeTagsList, typename DataBoxType, typename Metavariables>
auto	evaluate (const ObservationBox< ComputeTagsList, DataBoxType > &box, Parallel::GlobalCache< Metavariables > &cache, const ElementId< Metavariables::volume_dim > &element_id) const
	Evaluates the AMR criteria by selecting the appropriate derived class and forwarding its argument_tags from the ObservationBox (along with the GlobalCache and ArrayIndex) to the call operator of the derived class.

Static Public Member Functions
static std::string	name ()

Static Public Attributes
static constexpr Options::String	help

Detailed Description

template<Type CriteriaType>
class amr::Criteria::Random< CriteriaType >

Randomly refine (or coarsen) an Element in each dimension.

You can specify a probability for each possible amr::Flag. It is evaluated in each dimension separately. Details:

• Probabilities are specified as integer weights. The probability for an amr::Flag is its weight over the sum of all weights.
• Flags with weight zero do not need to be specified.
• If all weights are zero, amr::Flag::DoNothing is always chosen.

Member Function Documentation

observation_name()

template<Type CriteriaType>

std::string amr::Criteria::Random< CriteriaType >::observation_name ( )

inlineoverridevirtual

Implements amr::Criterion.

type()

template<Type CriteriaType>

Type amr::Criteria::Random< CriteriaType >::type ( )

inlineoverridevirtual

Implements amr::Criterion.

Member Data Documentation

help

template<Type CriteriaType>

Options::String amr::Criteria::Random< CriteriaType >::help

staticconstexpr

Initial value:

= {
      "Randomly refine (or coarsen) the grid"}

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

• src/ParallelAlgorithms/Amr/Criteria/Random.hpp