exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets Class Reference

Code snippet generator for fixed time stepping in the Runge-Kutta schemes. More...

Inheritance diagram for exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets:

Collaboration diagram for exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets:

Public Member Functions
	__init__ (self, time_step_relaxation)
	create_start_time_step_implementation (self)
	create_finish_time_step_implementation (self)
	The superclass takes the admissible cell size and divides it by the maximum eigenvalue.
Public Member Functions inherited from exahype2.solvers.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets
	create_abstract_solver_user_declarations (self)
	create_abstract_solver_user_definitions (self)
	create_abstract_solver_constructor_statements (self)
	Set the admissible time step size as well as the predicted time step size to zero.
	create_compute_time_step_size (self)
	Within the actual compute kernels, the kernels ask the solver variant how to determine a new field.
	create_compute_new_time_step_size (self)
	This is global, fixed time stepping, i.e.

Protected Attributes
	_time_step_relaxation

Detailed Description

Code snippet generator for fixed time stepping in the Runge-Kutta schemes.

Definition at line 6 of file OptimisticAdaptiveTimeSteppingCodeSnippets.py.

Constructor & Destructor Documentation

__init__()

exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets.__init__	(		self,
			time_step_relaxation )

Definition at line 12 of file OptimisticAdaptiveTimeSteppingCodeSnippets.py.

Member Function Documentation

create_finish_time_step_implementation()

exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets.create_finish_time_step_implementation

(

self

)

The superclass takes the admissible cell size and divides it by the maximum eigenvalue.

The Finite Volume solvers however operate with patches, i.e. we have to devide by the volume count per axis.

Reimplemented from exahype2.solvers.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets.

Definition at line 45 of file OptimisticAdaptiveTimeSteppingCodeSnippets.py.

References exahype2.solvers.fv.AdaptiveSubcyclingTimeSteppingCodeSnippets.AdaptiveSubcyclingTimeSteppingCodeSnippets._time_step_relaxation, exahype2.solvers.fv.AdaptiveTimeSteppingCodeSnippets.AdaptiveTimeSteppingCodeSnippets._time_step_relaxation, exahype2.solvers.fv.LocalTimeSteppingCodeSnippets.LocalTimeSteppingCodeSnippets._time_step_relaxation, exahype2.solvers.fv.musclhancock.GlobalAdaptiveTimeStep.GlobalAdaptiveTimeStep._time_step_relaxation, exahype2.solvers.fv.riemann.GlobalAdaptiveTimeStep.GlobalAdaptiveTimeStep._time_step_relaxation, exahype2.solvers.fv.riemann.GlobalAdaptiveTimeStepWithEnclaveTasking.GlobalAdaptiveTimeStepWithEnclaveTasking._time_step_relaxation, exahype2.solvers.fv.rusanov.GlobalAdaptiveTimeStep.GlobalAdaptiveTimeStep._time_step_relaxation, exahype2.solvers.fv.rusanov.GlobalAdaptiveTimeStepWithEnclaveTasking.GlobalAdaptiveTimeStepWithEnclaveTasking._time_step_relaxation, exahype2.solvers.fv.rusanov.LocalTimeStepWithEnclaveTasking.LocalTimeStepWithEnclaveTasking._time_step_relaxation, exahype2.solvers.fv.rusanov.SubcyclingAdaptiveTimeStepWithEnclaveTasking.SubcyclingAdaptiveTimeStepWithEnclaveTasking._time_step_relaxation, exahype2.solvers.rkdg.AdaptiveTimeSteppingCodeSnippets.AdaptiveTimeSteppingCodeSnippets._time_step_relaxation, exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets._time_step_relaxation, exahype2.solvers.rkdg.rusanov.GlobalAdaptiveTimeStep.GlobalAdaptiveTimeStep._time_step_relaxation, exahype2.solvers.rkdg.rusanov.GlobalAdaptiveTimeStepWithEnclaveTasking.GlobalAdaptiveTimeStepWithEnclaveTasking._time_step_relaxation, exahype2.solvers.rkfd.AdaptiveTimeSteppingCodeSnippets.AdaptiveTimeSteppingCodeSnippets._time_step_relaxation, exahype2.solvers.rkfd.fd4.GlobalAdaptiveTimeStep.GlobalAdaptiveTimeStep._time_step_relaxation, exahype2.solvers.rkfd.fd4.GlobalAdaptiveTimeStepInExaGRyPE.GlobalAdaptiveTimeStepInExaGRyPE._time_step_relaxation, exahype2.solvers.rkfd.fd4.GlobalAdaptiveTimeStepInExaGRyPEWithEnclaveTasking.GlobalAdaptiveTimeStepInExaGRyPEWithEnclaveTasking._time_step_relaxation, exahype2.solvers.rkfd.fd4.GlobalAdaptiveTimeStepWithEnclaveTasking.GlobalAdaptiveTimeStepWithEnclaveTasking._time_step_relaxation, and exahype2.solvers.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets.create_finish_time_step_implementation().

Here is the call graph for this function:

create_start_time_step_implementation()

exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets.create_start_time_step_implementation

(

self

)

Reimplemented from exahype2.solvers.SolverCodeSnippets.SolverCodeSnippets.

Definition at line 16 of file OptimisticAdaptiveTimeSteppingCodeSnippets.py.

Field Documentation

_time_step_relaxation

exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets._time_step_relaxation

protected

Definition at line 13 of file OptimisticAdaptiveTimeSteppingCodeSnippets.py.

Referenced by exahype2.solvers.fv.AdaptiveSubcyclingTimeSteppingCodeSnippets.AdaptiveSubcyclingTimeSteppingCodeSnippets.create_finish_time_step_implementation(), exahype2.solvers.fv.AdaptiveTimeSteppingCodeSnippets.AdaptiveTimeSteppingCodeSnippets.create_finish_time_step_implementation(), exahype2.solvers.rkdg.AdaptiveTimeSteppingCodeSnippets.AdaptiveTimeSteppingCodeSnippets.create_finish_time_step_implementation(), exahype2.solvers.rkdg.OptimisticAdaptiveTimeSteppingCodeSnippets.OptimisticAdaptiveTimeSteppingCodeSnippets.create_finish_time_step_implementation(), exahype2.solvers.rkfd.AdaptiveTimeSteppingCodeSnippets.AdaptiveTimeSteppingCodeSnippets.create_finish_time_step_implementation(), exahype2.solvers.rkdg.rusanov.GlobalAdaptiveTimeStep.GlobalAdaptiveTimeStep.set_implementation(), and exahype2.solvers.rkdg.rusanov.GlobalAdaptiveTimeStepWithEnclaveTasking.GlobalAdaptiveTimeStepWithEnclaveTasking.set_implementation().

---

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

• python/exahype2/solvers/rkdg/OptimisticAdaptiveTimeSteppingCodeSnippets.py