h-refine the grid based on a smoothness indicator More...

#include <Loehner.hpp>

Public Types
using	options = tmpl::list< VariablesToMonitor, RelativeTolerance, AbsoluteTolerance, CoarseningFactor >

using	compute_tags_for_observation_box = tmpl::list<>

using	argument_tags = tmpl::list<::Tags::DataBox >

Public Member Functions
	Loehner (std::vector< std::string > vars_to_monitor, double relative_tolerance, double absolute_tolerance, double coarsening_factor, const Options::Context &context={})

template<typename DbTagsList , typename Metavariables >
std::array< Flag, Dim >	operator() (const db::DataBox< DbTagsList > &box, Parallel::GlobalCache< Metavariables > &cache, 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. More...

Static Public Attributes
static constexpr Options::String	help

Detailed Description

template<size_t Dim, typename TensorTags>
class amr::Criteria::Loehner< Dim, TensorTags >

h-refine the grid based on a smoothness indicator

The smoothness indicator used here is based on the magnitude of second derivatives. See amr::Criteria::loehner_smoothness_indicator for details and caveats.

Member Data Documentation

template<size_t Dim, typename TensorTags >

staticconstexpr

Initial value:

= {
      "Refine the grid towards resolving an estimated error in the second "
      "derivative"}

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