A sparse direct LU factorization and solver based on the SuperLU library. More...
#include <SuperLUSupport.h>
Inheritance diagram for Eigen::SuperLU< _MatrixType >:
Public Types | |
| typedef SuperLUBase< _MatrixType, SuperLU > | Base |
| typedef _MatrixType | MatrixType |
| typedef Base::Scalar | Scalar |
| typedef Base::RealScalar | RealScalar |
| typedef Base::StorageIndex | StorageIndex |
| typedef Base::IntRowVectorType | IntRowVectorType |
| typedef Base::IntColVectorType | IntColVectorType |
| typedef Base::PermutationMap | PermutationMap |
| typedef Base::LUMatrixType | LUMatrixType |
| typedef TriangularView< LUMatrixType, Lower|UnitDiag > | LMatrixType |
| typedef TriangularView< LUMatrixType, Upper > | UMatrixType |
 Public Types inherited from Eigen::SuperLUBase< _MatrixType, SuperLU< _MatrixType > > | |
| enum | |
| typedef _MatrixType | MatrixType |
| typedef MatrixType::Scalar | Scalar |
| typedef MatrixType::RealScalar | RealScalar |
| typedef MatrixType::StorageIndex | StorageIndex |
| typedef Matrix< Scalar, Dynamic, 1 > | Vector |
| typedef Matrix< int, 1, MatrixType::ColsAtCompileTime > | IntRowVectorType |
| typedef Matrix< int, MatrixType::RowsAtCompileTime, 1 > | IntColVectorType |
| typedef Map< PermutationMatrix< Dynamic, Dynamic, int > > | PermutationMap |
| typedef SparseMatrix< Scalar > | LUMatrixType |
Public Member Functions | |
| SuperLU (const MatrixType &matrix) | |
| void | analyzePattern (const MatrixType &matrix) |
| void | factorize (const MatrixType &matrix) |
| template<typename Rhs , typename Dest > | |
| void | _solve_impl (const MatrixBase< Rhs > &b, MatrixBase< Dest > &dest) const |
| const LMatrixType & | matrixL () const |
| const UMatrixType & | matrixU () const |
| const IntColVectorType & | permutationP () const |
| const IntRowVectorType & | permutationQ () const |
| Scalar | determinant () const |
| Public Member Functions inherited from Eigen::SuperLUBase< _MatrixType, SuperLU< _MatrixType > > | |
| Index | rows () const |
| Index | cols () const |
| superlu_options_t & | options () |
| ComputationInfo | info () const |
| Reports whether previous computation was successful. More... | |
| void | compute (const MatrixType &matrix) |
| void | analyzePattern (const MatrixType &) |
| void | dumpMemory (Stream &) |
| Public Member Functions inherited from Eigen::SparseSolverBase< SuperLU< _MatrixType > > | |
| SparseSolverBase () | |
| SuperLU< _MatrixType > & | derived () |
| const SuperLU< _MatrixType > & | derived () const |
| const Solve< SuperLU< _MatrixType >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
| const Solve< SuperLU< _MatrixType >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
| void | _solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const |
Protected Member Functions | |
| void | init () |
| Protected Member Functions inherited from Eigen::SuperLUBase< _MatrixType, SuperLU< _MatrixType > > | |
| void | initFactorization (const MatrixType &a) |
| void | init () |
| void | extractData () const |
| void | clearFactors () |
| SuperLU< _MatrixType > & | derived () |
| const SuperLU< _MatrixType > & | derived () const |
Protected Attributes | |
| LUMatrixType | m_matrix |
| superlu_options_t | m_sluOptions |
| SluMatrix | m_sluA |
| SluMatrix | m_sluB |
| SluMatrix | m_sluX |
| IntColVectorType | m_p |
| IntRowVectorType | m_q |
| std::vector< int > | m_sluEtree |
| char | m_sluEqued |
| Matrix< RealScalar, Dynamic, 1 > | m_sluRscale |
| Matrix< RealScalar, Dynamic, 1 > | m_sluCscale |
| SuperMatrix | m_sluL |
| SuperMatrix | m_sluU |
| SuperLUStat_t | m_sluStat |
| Matrix< RealScalar, Dynamic, 1 > | m_sluFerr |
| Matrix< RealScalar, Dynamic, 1 > | m_sluBerr |
| LUMatrixType | m_l |
| LUMatrixType | m_u |
| int | m_analysisIsOk |
| int | m_factorizationIsOk |
| bool | m_extractedDataAreDirty |
| bool | m_isInitialized |
| ComputationInfo | m_info |
| Protected Attributes inherited from Eigen::SuperLUBase< _MatrixType, SuperLU< _MatrixType > > | |
| LUMatrixType | m_l |
| LUMatrixType | m_u |
| IntColVectorType | m_p |
| IntRowVectorType | m_q |
| LUMatrixType | m_matrix |
| SluMatrix | m_sluA |
| SuperMatrix | m_sluL |
| SuperMatrix | m_sluU |
| SluMatrix | m_sluB |
| SluMatrix | m_sluX |
| SuperLUStat_t | m_sluStat |
| superlu_options_t | m_sluOptions |
| std::vector< int > | m_sluEtree |
| Matrix< RealScalar, Dynamic, 1 > | m_sluRscale |
| Matrix< RealScalar, Dynamic, 1 > | m_sluCscale |
| Matrix< RealScalar, Dynamic, 1 > | m_sluFerr |
| Matrix< RealScalar, Dynamic, 1 > | m_sluBerr |
| char | m_sluEqued |
| ComputationInfo | m_info |
| int | m_factorizationIsOk |
| int | m_analysisIsOk |
| bool | m_extractedDataAreDirty |
| bool | m_isInitialized |
| Protected Attributes inherited from Eigen::SparseSolverBase< SuperLU< _MatrixType > > | |
| bool | m_isInitialized |
Additional Inherited Members | |
| Protected Types inherited from Eigen::SuperLUBase< _MatrixType, SuperLU< _MatrixType > > | |
| typedef SparseSolverBase< SuperLU< _MatrixType > > | Base |
Detailed Description
template<typename _MatrixType>
class Eigen::SuperLU< _MatrixType >
A sparse direct LU factorization and solver based on the SuperLU library.
This class allows to solve for A.X = B sparse linear problems via a direct LU factorization using the SuperLU library. The sparse matrix A must be squared and invertible. The vectors or matrices X and B can be either dense or sparse.
- Template Parameters
-
_MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
- Warning
- This class is only for the 4.x versions of SuperLU. The 3.x and 5.x versions are not supported.
\implsparsesolverconcept
- See also
- TutorialSparseSolverConcept, class SparseLU
Member Function Documentation
◆ analyzePattern()
template<typename _MatrixType >
|
inline |
Performs a symbolic decomposition on the sparcity of matrix.
This function is particularly useful when solving for several problems having the same structure.
- See also
- factorize()
◆ factorize()
template<typename MatrixType >
| void Eigen::SuperLU< MatrixType >::factorize | ( | const MatrixType & | matrix | ) |
Performs a numeric decomposition of matrix
The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
- See also
- analyzePattern()
The documentation for this class was generated from the following file:
