PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData Class Reference

#include <deal.II/lac/precondition.h>

Inheritance diagram for PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData:

Public Types
using	EigenvalueAlgorithm = internal::EigenvalueAlgorithm

Public Member Functions
	AdditionalData (const double relaxation=1., const unsigned int n_iterations=1, const double smoothing_range=0., const unsigned int eig_cg_n_iterations=8, const double eig_cg_residual=1e-2, const double max_eigenvalue=1, const EigenvalueAlgorithm eigenvalue_algorithm=EigenvalueAlgorithm::lanczos)

Public Attributes
double	relaxation
unsigned int	n_iterations
double	smoothing_range
unsigned int	eig_cg_n_iterations
double	eig_cg_residual
double	max_eigenvalue
::AffineConstraints< double >	constraints
EigenvalueAlgorithm	eigenvalue_algorithm
std::shared_ptr< PreconditionerType >	preconditioner

Detailed Description

template<typename MatrixType = SparseMatrix<double>, typename PreconditionerType = IdentityMatrix>
class PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData

Class for parameters.

Definition at line 577 of file precondition.h.

Member Typedef Documentation

EigenvalueAlgorithm

template<typename MatrixType = SparseMatrix<double>, typename PreconditionerType = IdentityMatrix>

using PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData::EigenvalueAlgorithm = internal::EigenvalueAlgorithm

Definition at line 581 of file precondition.h.

Constructor & Destructor Documentation

AdditionalData()

template<typename MatrixType = SparseMatrix<double>, typename PreconditionerType = IdentityMatrix>

PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData::AdditionalData	(	const double	relaxation = 1.,
		const unsigned int	n_iterations = 1,
		const double	smoothing_range = 0.,
		const unsigned int	eig_cg_n_iterations = 8,
		const double	eig_cg_residual = 1e-2,
		const double	max_eigenvalue = 1,
		const EigenvalueAlgorithm	eigenvalue_algorithm = EigenvalueAlgorithm::lanczos )

Constructor.

Member Data Documentation

relaxation

template<typename MatrixType = SparseMatrix<double>, typename PreconditionerType = IdentityMatrix>

double PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData::relaxation

Relaxation parameter.

Definition at line 598 of file precondition.h.

n_iterations

template<typename MatrixType = SparseMatrix<double>, typename PreconditionerType = IdentityMatrix>

unsigned int PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData::n_iterations

Number of smoothing steps to be performed in an invocation of vmult() or step().

Definition at line 604 of file precondition.h.

smoothing_range

template<typename PreconditionerType >

double internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::smoothing_range

inherited

This sets the range between the largest eigenvalue in the matrix and the smallest eigenvalue to be treated. If the parameter is set to a number less than 1, an estimate for the largest and for the smallest eigenvalue will be calculated internally. For a smoothing range larger than one, the preconditioner will act in the interval \([\lambda_\mathrm{max}/ \tt{smoothing\_range}, \lambda_\mathrm{max}]\), where \(\lambda_\mathrm{max}\) is an estimate of the maximum eigenvalue of the matrix. A choice of smoothing_range between 5 and 20 is useful in case the preconditioner is used as a smoother in multigrid.

Definition at line 158 of file precondition.h.

eig_cg_n_iterations

template<typename PreconditionerType >

unsigned int internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::eig_cg_n_iterations

inherited

Maximum number of CG iterations performed for finding the maximum eigenvalue. If set to zero, no computations are performed. Instead, the user must supply a largest eigenvalue via the variable PreconditionRelaxation::AdditionalData::max_eigenvalue.

Definition at line 166 of file precondition.h.

eig_cg_residual

template<typename PreconditionerType >

double internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::eig_cg_residual

inherited

Tolerance for iterations performed for finding the maximum eigenvalue by the eigenvalue algorithm (Lanczos or power iteration).

Definition at line 172 of file precondition.h.

max_eigenvalue

template<typename PreconditionerType >

double internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::max_eigenvalue

inherited

Maximum eigenvalue to work with. Only in effect if eig_cg_n_iterations is set to zero, otherwise this parameter is ignored.

Definition at line 179 of file precondition.h.

constraints

template<typename PreconditionerType >

::AffineConstraints<double> internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::constraints

inherited

Constraints to be used for the operator given. This variable is used to zero out the correct entries when creating an initial guess.

Definition at line 185 of file precondition.h.

eigenvalue_algorithm

template<typename PreconditionerType >

EigenvalueAlgorithm internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::eigenvalue_algorithm

inherited

Stores the preconditioner object that the Chebyshev is wrapped around.

Definition at line 190 of file precondition.h.

preconditioner

template<typename PreconditionerType >

std::shared_ptr<PreconditionerType> internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::preconditioner

inherited

Preconditioner.

Definition at line 195 of file precondition.h.

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

• include/deal.II/lac/precondition.h