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enum | { UpLo = _UpLo
} |
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typedef Base::StorageIndex | StorageIndex |
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enum | |
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typedef Traits::MatrixType | MatrixType |
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typedef Traits::Scalar | Scalar |
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typedef Traits::RealScalar | RealScalar |
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typedef Traits::StorageIndex | StorageIndex |
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typedef SparseMatrix< Scalar, RowMajor, StorageIndex > | SparseMatrixType |
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typedef Matrix< Scalar, Dynamic, 1 > | VectorType |
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typedef Matrix< StorageIndex, 1, MatrixType::ColsAtCompileTime > | IntRowVectorType |
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typedef Matrix< StorageIndex, MatrixType::RowsAtCompileTime, 1 > | IntColVectorType |
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typedef Array< StorageIndex, 64, 1, DontAlign > | ParameterType |
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| PardisoLLT (const MatrixType &matrix) |
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Index | cols () const |
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Index | rows () const |
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ComputationInfo | info () const |
| Reports whether previous computation was successful. More...
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ParameterType & | pardisoParameterArray () |
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PardisoLLT< MatrixType, _UpLo > & | analyzePattern (const MatrixType &matrix) |
| Performs a symbolic decomposition on the sparcity of matrix. More...
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PardisoLLT< MatrixType, _UpLo > & | factorize (const MatrixType &matrix) |
| Performs a numeric decomposition of matrix. More...
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PardisoLLT< MatrixType, _UpLo > & | compute (const MatrixType &matrix) |
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void | _solve_impl (const MatrixBase< Rhs > &b, MatrixBase< Dest > &dest) const |
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void | _solve_impl (const MatrixBase< BDerived > &b, MatrixBase< XDerived > &x) const |
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| SparseSolverBase () |
| Default constructor.
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PardisoLLT< MatrixType, _UpLo > & | derived () |
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const PardisoLLT< MatrixType, _UpLo > & | derived () const |
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const Solve< PardisoLLT< MatrixType, _UpLo >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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const Solve< PardisoLLT< MatrixType, _UpLo >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
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void | _solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const |
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template<typename MatrixType, int _UpLo>
class Eigen::PardisoLLT< MatrixType, _UpLo >
A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library.
This class allows to solve for A.X = B sparse linear problems via a LL^T Cholesky factorization using the Intel MKL PARDISO library. The sparse matrix A must be selfajoint and positive definite. 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<> |
UpLo | can be any bitwise combination of Upper, Lower. The default is Upper, meaning only the upper triangular part has to be used. Upper|Lower can be used to tell both triangular parts can be used as input. |
- See also
- Sparse solver concept, class SimplicialLLT