HLIBpro  3.0
TFacInvMatrix< T_value > Class Template Referenceabstract

Baseclass for representing the inverse of factorised matrices. More...

#include <TFacInvMatrix.hh>

Inheritance diagram for TFacInvMatrix< T_value >:
TLinearOperator< T_value > TTypeInfo TLDLInvMatrix< T_value > TLDUInvMatrix< T_value > TLLInvMatrix< T_value > TLUInvMatrix< T_value >

Public Member Functions

template<typename T_mat >
 TFacInvMatrix (T_mat &&afac_matrix, const eval_type_t aeval_type=CFG::Arith::eval_type, const storage_type_t astorage_type=CFG::Arith::storage_type)
 
template<typename T_mat >
 TFacInvMatrix (T_mat &&afac_matrix, const TTruncAcc &aacc, const eval_type_t aeval_type=CFG::Arith::eval_type, const storage_type_t astorage_type=CFG::Arith::storage_type)
 
template<typename T_mat >
 TFacInvMatrix (const TScalarVector< value_t > *D1, T_mat &&afac_matrix, const TScalarVector< value_t > *D2, const eval_type_t aeval_type=CFG::Arith::eval_type, const storage_type_t astorage_type=CFG::Arith::storage_type)
 
virtual ~TFacInvMatrix ()
 dtor
 
const TMatrix< value_t > * matrix () const
 access factorised matrix
 
bool has_scaling () const
 return true if diagonal scaling is used
 
const TScalarVector< value_t > & scaling_left () const
 return left scaling matrix
 
const TScalarVector< value_t > & scaling_right () const
 return right scaling matrix
 
eval_type_t eval_type () const
 return evaluation type (pointwise/blockwise)
 
storage_type_t storage_type () const
 return evaluation type (pointwise/blockwise)
 
const TTruncAcc accuracy () const
 return internal accuracy for matrix arithmetic
 
void set_accuracy (const TTruncAcc &aacc)
 set internal accuracy for matrix arithmetic
 
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

template<typename T_value>
class Hpro::TFacInvMatrix< T_value >

      TFacInvMatrix and the derived classes represent operators based on
      factorised matrices providing the ability to evaluate the inverse
      of the corresponding matrix (in factorised form), e.g. for \f$ A = LU \f$
      the inverse \f$ (LU)^{-1} \f$ is applied.

      Optionally, diagonal scalings from left and right may have been
      applied before the factorisation and now taken into account in the
      evaluation.

Constructor & Destructor Documentation

◆ TFacInvMatrix() [1/3]

TFacInvMatrix ( T_mat &&  afac_matrix,
const eval_type_t  aeval_type = CFG::Arith::eval_type,
const storage_type_t  astorage_type = CFG::Arith::storage_type 
)
inline

construct inverse operator with factorised matrix afac_matrix (no diagonal scaling applied)

◆ TFacInvMatrix() [2/3]

TFacInvMatrix ( T_mat &&  afac_matrix,
const TTruncAcc aacc,
const eval_type_t  aeval_type = CFG::Arith::eval_type,
const storage_type_t  astorage_type = CFG::Arith::storage_type 
)
inline

construct inverse operator with factorised matrix afac_matrix with accuracy for matrix arithmetic (without diagonal scaling)

◆ TFacInvMatrix() [3/3]

TFacInvMatrix ( const TScalarVector< value_t > *  D1,
T_mat &&  afac_matrix,
const TScalarVector< value_t > *  D2,
const eval_type_t  aeval_type = CFG::Arith::eval_type,
const storage_type_t  astorage_type = CFG::Arith::storage_type 
)
inline

construct inverse operator with factorised matrix afac_matrix and additional row and column scaling factors D1 and D2, e.g. A = D1·Ã·D2, with à = afac_matrix

Member Function Documentation

◆ apply()

virtual void apply ( const TVector< value_t > *  x,
TVector< value_t > *  y,
const matop_t  op = apply_normal 
) const
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 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

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 void apply_add ( const value_t  alpha,
const TVector< value_t > *  x,
TVector< value_t > *  y,
const matop_t  op = apply_normal 
) const
virtual

mapping function with update: yy + α A( x ). Depending on op, either A, A^T or A^H is applied.

Implements TLinearOperator< T_value >.