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enum | { UpLo = Options&(Upper|Lower)
} |
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typedef Base::StorageIndex | StorageIndex |
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enum | |
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typedef Matrix< StorageIndex, MatrixType::RowsAtCompileTime, 1 > | IntColVectorType |
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typedef Matrix< StorageIndex, 1, MatrixType::ColsAtCompileTime > | IntRowVectorType |
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typedef Traits::MatrixType | MatrixType |
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typedef Array< StorageIndex, 64, 1, DontAlign > | ParameterType |
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typedef Traits::RealScalar | RealScalar |
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typedef Traits::Scalar | Scalar |
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typedef SparseMatrix< Scalar, RowMajor, StorageIndex > | SparseMatrixType |
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typedef Traits::StorageIndex | StorageIndex |
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typedef Matrix< Scalar, Dynamic, 1 > | VectorType |
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void | getMatrix (const MatrixType &matrix) |
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| PardisoLDLT () |
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| PardisoLDLT (const MatrixType &matrix) |
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void | _solve_impl (const MatrixBase< Rhs > &b, MatrixBase< Dest > &dest) const |
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PardisoLDLT< MatrixType, Options > & | analyzePattern (const MatrixType &matrix) |
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Index | cols () const |
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PardisoLDLT< MatrixType, Options > & | compute (const MatrixType &matrix) |
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PardisoLDLT< MatrixType, Options > & | factorize (const MatrixType &matrix) |
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ComputationInfo | info () const |
| Reports whether previous computation was successful. More...
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| PardisoImpl () |
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ParameterType & | pardisoParameterArray () |
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Index | rows () const |
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| ~PardisoImpl () |
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void | _solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const |
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PardisoLDLT< MatrixType, Options > & | derived () |
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const PardisoLDLT< MatrixType, Options > & | derived () const |
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const Solve< PardisoLDLT< MatrixType, Options >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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const Solve< PardisoLDLT< MatrixType, Options >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
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| SparseSolverBase () |
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| ~SparseSolverBase () |
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template<typename MatrixType, int Options>
class Eigen::PardisoLDLT< MatrixType, Options >
A sparse direct Cholesky (LDLT) factorization and solver based on the PARDISO library.
This class allows to solve for A.X = B sparse linear problems via a LDL^T Cholesky factorization using the Intel MKL PARDISO library. The sparse matrix A is assumed to be selfajoint and positive definite. For complex matrices, A can also be symmetric only, see the Options template parameter. The vectors or matrices X and B can be either dense or sparse.
By default, it runs in in-core mode. To enable PARDISO's out-of-core feature, set:
solver.pardisoParameterArray()[59] = 1;
- Template Parameters
-
MatrixType | the type of the sparse matrix A, it must be a SparseMatrix<> |
Options | can be any bitwise combination of Upper, Lower, and Symmetric. The default is Upper, meaning only the upper triangular part has to be used. Symmetric can be used for symmetric, non-selfadjoint complex matrices, the default being to assume a selfadjoint matrix. Upper|Lower can be used to tell both triangular parts can be used as input. |
- See also
- TutorialSparseSolverConcept, class SimplicialLDLT
Definition at line 39 of file PardisoSupport.h.