OSVR-Core
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A bi conjugate gradient stabilized solver for sparse square problems. More...
#include <BiCGSTAB.h>
Public Types | |
typedef _MatrixType | MatrixType |
typedef MatrixType::Scalar | Scalar |
typedef MatrixType::Index | Index |
typedef MatrixType::RealScalar | RealScalar |
typedef _Preconditioner | Preconditioner |
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typedef internal::traits< BiCGSTAB< _MatrixType, _Preconditioner > >::MatrixType | MatrixType |
typedef internal::traits< BiCGSTAB< _MatrixType, _Preconditioner > >::Preconditioner | Preconditioner |
typedef MatrixType::Scalar | Scalar |
typedef MatrixType::Index | Index |
typedef MatrixType::RealScalar | RealScalar |
Public Member Functions | |
BiCGSTAB () | |
Default constructor. More... | |
template<typename MatrixDerived > | |
BiCGSTAB (const EigenBase< MatrixDerived > &A) | |
Initialize the solver with matrix A for further Ax=b solving. More... | |
template<typename Rhs , typename Guess > | |
const internal::solve_retval_with_guess< BiCGSTAB, Rhs, Guess > | solveWithGuess (const MatrixBase< Rhs > &b, const Guess &x0) const |
template<typename Rhs , typename Dest > | |
void | _solveWithGuess (const Rhs &b, Dest &x) const |
template<typename Rhs , typename Dest > | |
void | _solve (const Rhs &b, Dest &x) const |
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BiCGSTAB< _MatrixType, _Preconditioner > & | derived () |
const BiCGSTAB< _MatrixType, _Preconditioner > & | derived () const |
IterativeSolverBase () | |
Default constructor. More... | |
IterativeSolverBase (const EigenBase< InputDerived > &A) | |
Initialize the solver with matrix A for further Ax=b solving. More... | |
BiCGSTAB< _MatrixType, _Preconditioner > & | analyzePattern (const EigenBase< InputDerived > &A) |
Initializes the iterative solver for the sparcity pattern of the matrix A for further solving Ax=b problems. More... | |
BiCGSTAB< _MatrixType, _Preconditioner > & | factorize (const EigenBase< InputDerived > &A) |
Initializes the iterative solver with the numerical values of the matrix A for further solving Ax=b problems. More... | |
BiCGSTAB< _MatrixType, _Preconditioner > & | compute (const EigenBase< InputDerived > &A) |
Initializes the iterative solver with the matrix A for further solving Ax=b problems. More... | |
Index | rows () const |
Index | cols () const |
RealScalar | tolerance () const |
BiCGSTAB< _MatrixType, _Preconditioner > & | setTolerance (const RealScalar &tolerance) |
Sets the tolerance threshold used by the stopping criteria. | |
Preconditioner & | preconditioner () |
const Preconditioner & | preconditioner () const |
int | maxIterations () const |
BiCGSTAB< _MatrixType, _Preconditioner > & | setMaxIterations (int maxIters) |
Sets the max number of iterations. | |
int | iterations () const |
RealScalar | error () const |
const internal::solve_retval< BiCGSTAB< _MatrixType, _Preconditioner >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
const internal::sparse_solve_retval< IterativeSolverBase, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
ComputationInfo | info () const |
void | _solve_sparse (const Rhs &b, SparseMatrix< DestScalar, DestOptions, DestIndex > &dest) const |
Additional Inherited Members | |
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void | grabInput (const EigenBase< InputDerived > &A) |
void | grabInput_impl (const EigenBase< InputDerived > &A) |
void | grabInput_impl (MatrixType &A) |
void | init () |
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MatrixType | m_copyMatrix |
const MatrixType * | mp_matrix |
Preconditioner | m_preconditioner |
int | m_maxIterations |
RealScalar | m_tolerance |
RealScalar | m_error |
int | m_iterations |
ComputationInfo | m_info |
bool | m_isInitialized |
bool | m_analysisIsOk |
bool | m_factorizationIsOk |
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.
_MatrixType | the type of the sparse matrix A, can be a dense or a sparse matrix. |
_Preconditioner | the 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.
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.
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inline |
Default constructor.
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inlineexplicit |
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().
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inline |