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template<typename Rhs , typename Dest > |
void | _solve_vector_with_guess_impl (const Rhs &b, Dest &x) const |
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| BiCGSTAB () |
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template<typename MatrixDerived > |
| BiCGSTAB (const EigenBase< MatrixDerived > &A) |
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| ~BiCGSTAB () |
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void | _solve_impl (const Rhs &b, Dest &x) const |
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std::enable_if_t< Rhs::ColsAtCompileTime!=1 &&DestDerived::ColsAtCompileTime!=1 > | _solve_with_guess_impl (const Rhs &b, MatrixBase< DestDerived > &aDest) const |
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std::enable_if_t< Rhs::ColsAtCompileTime==1||DestDerived::ColsAtCompileTime==1 > | _solve_with_guess_impl (const Rhs &b, MatrixBase< DestDerived > &dest) const |
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void | _solve_with_guess_impl (const Rhs &b, SparseMatrixBase< DestDerived > &aDest) const |
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BiCGSTAB< MatrixType_, Preconditioner_ > & | analyzePattern (const EigenBase< MatrixDerived > &A) |
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EIGEN_CONSTEXPR Index | cols () const EIGEN_NOEXCEPT |
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BiCGSTAB< MatrixType_, Preconditioner_ > & | compute (const EigenBase< MatrixDerived > &A) |
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BiCGSTAB< MatrixType_, Preconditioner_ > & | derived () |
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const BiCGSTAB< MatrixType_, Preconditioner_ > & | derived () const |
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RealScalar | error () const |
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BiCGSTAB< MatrixType_, Preconditioner_ > & | factorize (const EigenBase< MatrixDerived > &A) |
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ComputationInfo | info () const |
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Index | iterations () const |
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| IterativeSolverBase () |
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| IterativeSolverBase (const EigenBase< MatrixDerived > &A) |
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| IterativeSolverBase (IterativeSolverBase &&)=default |
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Index | maxIterations () const |
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Preconditioner & | preconditioner () |
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const Preconditioner & | preconditioner () const |
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EIGEN_CONSTEXPR Index | rows () const EIGEN_NOEXCEPT |
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BiCGSTAB< MatrixType_, Preconditioner_ > & | setMaxIterations (Index maxIters) |
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BiCGSTAB< MatrixType_, Preconditioner_ > & | setTolerance (const RealScalar &tolerance) |
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const SolveWithGuess< BiCGSTAB< MatrixType_, Preconditioner_ >, Rhs, Guess > | solveWithGuess (const MatrixBase< Rhs > &b, const Guess &x0) const |
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RealScalar | tolerance () const |
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| ~IterativeSolverBase () |
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Derived & | derived () |
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const Derived & | derived () const |
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template<typename Rhs > |
const Solve< Derived, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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template<typename Rhs > |
const Solve< Derived, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
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| SparseSolverBase () |
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| SparseSolverBase (SparseSolverBase &&other) |
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| ~SparseSolverBase () |
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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
-
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 |
This class follows the sparse solver concept .
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 Eigen and multi-threading for details.
This class can be used as the direct solver classes. Here is a typical usage example:
SparseMatrix<double>
A(
n,
n);
BiCGSTAB<SparseMatrix<double> >
solver;
std::cout <<
"#iterations: " <<
solver.iterations() << std::endl;
std::cout <<
"estimated error: " <<
solver.error() << std::endl;
BiCGSTAB< SparseMatrix< double > > solver
Matrix< double, Dynamic, 1 > VectorXd
DynamicĂ—1 vector of type double.
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 160 of file BiCGSTAB.h.
template<typename MatrixType_ , typename Preconditioner_ >
template<typename MatrixDerived >
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 190 of file BiCGSTAB.h.
190 :
Base(
A.derived()) {}