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TJacobi< T_value > Class Template Reference
implements Jacobi preconditioner More...
#include <TJacobi.hh>
Inheritance diagram for TJacobi< T_value >:
Public Member Functions | |
| TJacobi (const TMatrix< value_t > *A, const real_t damping=real_t(1), const size_t block_size=1, const TTruncAcc &acc_block=acc_exact) | |
| const TMatrix< value_t > * | matrix () const |
| return sparse matrix | |
| real_t | damping_factor () const |
| return damping factor | |
| bool | is_complex () const |
| return true, if field type is complex | |
| bool | is_self_adjoint () const |
| return true, of operator is self adjoint | |
| virtual void | apply (const TVector< value_t > *x, TVector< value_t > *y, const matop_t op=apply_normal) const |
| virtual void | apply_add (const value_t alpha, const TVector< value_t > *x, TVector< value_t > *y, const matop_t op=apply_normal) const |
| virtual void | apply_add (const value_t alpha, const BLAS::Vector< value_t > &x, BLAS::Vector< value_t > &y, const matop_t op=apply_normal) const |
| virtual size_t | domain_dim () const |
| return dimension of domain | |
| virtual size_t | range_dim () const |
| return dimension of range | |
| virtual auto | domain_vector () const -> std::unique_ptr< TVector< value_t > > |
| return vector in domain space | |
| virtual auto | range_vector () const -> std::unique_ptr< TVector< value_t > > |
| return vector in range space | |
 Public Member Functions inherited from TLinearOperator< T_value > | |
| virtual bool | is_real () const |
| return true, if field type is real valued | |
| Public Member Functions inherited from TTypeInfo | |
| virtual typeid_t | type () const =0 |
| return type ID of object | |
| virtual bool | is_type (const typeid_t t) const |
| return true if local object is of given type ID t | |
| virtual std::string | typestr () const |
| return string representation of type | |
Detailed Description
TJacobi provides application of a Jacobi type preconditioner for a given
matrix A, e.g. \f$ D^{-1} \f$ with \f$D\f$ being the diagonal of A. Here,
A may be of any type, e.g. dense, low-rank, block or sparse matrix. The
diagonal elements are assumed to be non-zero.
Also support block-wise mode, i.e., diagonal blocks are inverted. For this,
the size of diagonal block is defined during construction. If this equals 1
point-wise Jacobi is used. Please note, that for block-wise mode, the leaf
blocks define the smallest block size.
Constructor & Destructor Documentation
◆ TJacobi()
| TJacobi | ( | const TMatrix< value_t > * | A, |
| const real_t | damping = real_t(1), |
||
| const size_t | block_size = 1, |
||
| const TTruncAcc & | acc_block = acc_exact |
||
| ) |
construct Jacobi preconditioner based on matrix A with damping factor damping
Member Function Documentation
◆ apply()
|
virtual |
mapping function of linear operator \(A\), e.g. \( y := A(x)\). Depending on op, either \(A\), \(A^T\) or \(A^H\) is applied.
Implements TLinearOperator< T_value >.
◆ apply_add() [1/2]
|
virtual |
same as above but only the dimension of the vector spaces is tested, not the corresponding index sets
Implements TLinearOperator< T_value >.
◆ apply_add() [2/2]
|
virtual |
mapping function with update: \( y := y + \alpha A(x)\). Depending on op, either \(A\), \(A^T\) or \(A^H\) is applied.
Implements TLinearOperator< T_value >.
