TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec > Class Template Reference#
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DiFfRG
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Public Types |
Public Member Functions |
Private Types |
Private Member Functions |
List of all members
DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec > Class Template Reference
A class to perform time stepping using adaptive Boost Runge-Kutta methods. This stepper uses adaptive time steps and is fully explicit. More...
#include <boost_rk.hh>
Inheritance diagram for DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >:
Public Types | |
| using | NumberType = typename Base::NumberType |
| using | InverseSparseMatrixType = typename Base::InverseSparseMatrixType |
| using | BlockVectorType = typename Base::BlockVectorType |
| using | error_stepper_type = typename stepperChoice<prec>::value |
Public Member Functions | |
| virtual void | run (AbstractFlowingVariables< NumberType > *initial_condition, const double t_start, const double t_stop) override |
| Run the time stepping algorithm. | |
Public Member Functions inherited from DiFfRG::AbstractTimestepper< VectorType, SparseMatrixType, dim > | |
| AbstractTimestepper (const JSONValue &json, AbstractAssembler< VectorType, SparseMatrixType, dim > *assembler, DataOutput< dim, VectorType > *data_out=nullptr, AbstractAdaptor< VectorType > *adaptor=nullptr) | |
| Construct a new Abstract Timestepper object. | |
| DataOutput< dim, VectorType > * | get_data_out () |
| Utility function to obtain a DataOutput object. If no DataOutput object is provided, a default one is created. | |
| AbstractAdaptor< VectorType > * | get_adaptor () |
| Utility function to obtain an Adaptor object. If no Adaptor object is provided, a default one is created, which is the NoAdaptivity object, i.e. no mesh adaptivity is used. | |
Private Types | |
| using | Base = AbstractTimestepper<VectorType, SparseMatrixType, dim> |
Private Member Functions | |
| void | run (VectorType &initial_data, const double t_start, const double t_stop) |
| void | run (BlockVectorType &initial_data, const double t_start, const double t_stop) |
| void | run_vars (VectorType &initial_data, const double t_start, const double t_stop) |
Detailed Description
template<typename VectorType, typename SparseMatrixType, uint dim, int prec>
class DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >
class DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >
A class to perform time stepping using adaptive Boost Runge-Kutta methods. This stepper uses adaptive time steps and is fully explicit.
- Template Parameters
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VectorType Type of the vector dim Dimension of the problem prec Algorithm choice: 0 for Cash-Karp54 (5th order), 1 for Fehlberg78 (8th order)
Member Typedef Documentation
◆ Base
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private |
◆ BlockVectorType
| using DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >::BlockVectorType = typename Base::BlockVectorType |
◆ error_stepper_type
| using DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >::error_stepper_type = typename stepperChoice<prec>::value |
◆ InverseSparseMatrixType
| using DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >::InverseSparseMatrixType = typename Base::InverseSparseMatrixType |
◆ NumberType
| using DiFfRG::TimeStepperBoostRK< VectorType, SparseMatrixType, dim, prec >::NumberType = typename Base::NumberType |
Member Function Documentation
◆ run() [1/3]
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overridevirtual |
Run the time stepping algorithm.
Implements DiFfRG::AbstractTimestepper< VectorType, SparseMatrixType, dim >.
◆ run() [2/3]
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private |
◆ run() [3/3]
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private |
◆ run_vars()
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private |
The documentation for this class was generated from the following file:
- /home/runner/work/DiFfRG_current/DiFfRG_current/DiFfRG/include/DiFfRG/timestepping/boost_rk.hh
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Public Member Functions inherited from