MOAB  4.9.3pre
Eigen::BiCGSTAB< _MatrixType, _Preconditioner > Class Template Reference

A bi conjugate gradient stabilized solver for sparse square problems. More...

#include <BiCGSTAB.h>

Inheritance diagram for Eigen::BiCGSTAB< _MatrixType, _Preconditioner >:
Collaboration diagram for Eigen::BiCGSTAB< _MatrixType, _Preconditioner >:

List of all members.

Public Types

typedef _MatrixType MatrixType
typedef MatrixType::Scalar Scalar
typedef MatrixType::RealScalar RealScalar
typedef _Preconditioner Preconditioner

Public Member Functions

 BiCGSTAB ()
template<typename MatrixDerived >
 BiCGSTAB (const EigenBase< MatrixDerived > &A)
 ~BiCGSTAB ()
template<typename Rhs , typename Dest >
void _solve_with_guess_impl (const Rhs &b, Dest &x) const
template<typename Rhs , typename Dest >
void _solve_impl (const MatrixBase< Rhs > &b, Dest &x) const

Private Types

typedef IterativeSolverBase
< BiCGSTAB
Base

Detailed Description

template<typename _MatrixType, typename _Preconditioner>
class Eigen::BiCGSTAB< _MatrixType, _Preconditioner >

A bi conjugate gradient stabilized solver for sparse square problems.

This class allows to solve for A.x = b sparse linear problems using a bi conjugate gradient stabilized algorithm. The vectors x and b can be either dense or sparse.

Template Parameters:
_MatrixTypethe type of the sparse matrix A, can be a dense or a sparse matrix.
_Preconditionerthe type of the preconditioner. Default is DiagonalPreconditioner

The maximal number of iterations and tolerance value can be controlled via the setMaxIterations() and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations and NumTraits<Scalar>::epsilon() for the tolerance.

The tolerance corresponds to the relative residual error: |Ax-b|/|b|

Performance: when using sparse matrices, best performance is achied for a row-major sparse matrix format. Moreover, in this case multi-threading can be exploited if the user code is compiled with OpenMP enabled. See TopicMultiThreading for details.

This class can be used as the direct solver classes. Here is a typical usage example:

By default the iterations start with x=0 as an initial guess of the solution. One can control the start using the solveWithGuess() method.

BiCGSTAB can also be used in a matrix-free context, see the following example .

See also:
class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner

Definition at line 158 of file BiCGSTAB.h.


Member Typedef Documentation

template<typename _MatrixType , typename _Preconditioner >
typedef IterativeSolverBase<BiCGSTAB> Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::Base [private]
template<typename _MatrixType , typename _Preconditioner >
typedef _MatrixType Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::MatrixType
template<typename _MatrixType , typename _Preconditioner >
typedef _Preconditioner Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::Preconditioner
template<typename _MatrixType , typename _Preconditioner >
typedef MatrixType::RealScalar Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::RealScalar
template<typename _MatrixType , typename _Preconditioner >
typedef MatrixType::Scalar Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::Scalar

Constructor & Destructor Documentation

template<typename _MatrixType , typename _Preconditioner >
Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::BiCGSTAB ( ) [inline]

Default constructor.

Definition at line 175 of file BiCGSTAB.h.

: Base() {}
template<typename _MatrixType , typename _Preconditioner >
template<typename MatrixDerived >
Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::BiCGSTAB ( const EigenBase< MatrixDerived > &  A) [inline, explicit]

Initialize the solver with matrix A for further Ax=b solving.

This constructor is a shortcut for the default constructor followed by a call to compute().

Warning:
this class stores a reference to the matrix A as well as some precomputed values that depend on it. Therefore, if A is changed this class becomes invalid. Call compute() to update it with the new matrix A, or modify a copy of A.

Definition at line 188 of file BiCGSTAB.h.

: Base(A.derived()) {}
template<typename _MatrixType , typename _Preconditioner >
Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::~BiCGSTAB ( ) [inline]

Definition at line 190 of file BiCGSTAB.h.

{}

Member Function Documentation

template<typename _MatrixType , typename _Preconditioner >
template<typename Rhs , typename Dest >
void Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::_solve_impl ( const MatrixBase< Rhs > &  b,
Dest &  x 
) const [inline]

Definition at line 215 of file BiCGSTAB.h.

  {
    x.resize(this->rows(),b.cols());
    x.setZero();
    _solve_with_guess_impl(b,x);
  }
template<typename _MatrixType , typename _Preconditioner >
template<typename Rhs , typename Dest >
void Eigen::BiCGSTAB< _MatrixType, _Preconditioner >::_solve_with_guess_impl ( const Rhs &  b,
Dest &  x 
) const [inline]

Definition at line 194 of file BiCGSTAB.h.

  {    
    bool failed = false;
    for(Index j=0; j<b.cols(); ++j)
    {
      m_iterations = Base::maxIterations();
      m_error = Base::m_tolerance;
      
      typename Dest::ColXpr xj(x,j);
      if(!internal::bicgstab(matrix(), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error))
        failed = true;
    }
    m_info = failed ? NumericalIssue
           : m_error <= Base::m_tolerance ? Success
           : NoConvergence;
    m_isInitialized = true;
  }

The documentation for this class was generated from the following file:
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines