deal.II version 9.7.0
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PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData Class Reference

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

Detailed Description

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

Class for parameters.

Definition at line 578 of file precondition.h.

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

Member Typedef Documentation

◆ EigenvalueAlgorithm

template<typename MatrixType = SparseMatrix<double>, typename PreconditionerType = IdentityMatrix>
using PreconditionRelaxation< MatrixType, PreconditionerType >::AdditionalData::EigenvalueAlgorithm = internal::EigenvalueAlgorithm

Definition at line 582 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 599 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 605 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 159 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 167 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 173 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 180 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 186 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 191 of file precondition.h.

◆ preconditioner

template<typename PreconditionerType>
std::shared_ptr<PreconditionerType> internal::EigenvalueAlgorithmAdditionalData< PreconditionerType >::preconditioner
inherited

Preconditioner.

Definition at line 196 of file precondition.h.

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