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Eigen::PardisoLDLT< _MatrixType, Options > Class Template Reference

Detailed Description

template<typename _MatrixType, int Options = Upper>
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
MatrixTypethe type of the sparse matrix A, it must be a SparseMatrix<>
Optionscan 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.

This class follows the sparse solver concept .

See Also
Sparse solver concept, class SimplicialLDLT

Inherits Eigen::PardisoImpl< Derived >.

Additional Inherited Members

- Public Member Functions inherited from Eigen::PardisoImpl< Derived >
Derived & analyzePattern (const MatrixType &matrix)
 
Derived & factorize (const MatrixType &matrix)
 
ComputationInfo info () const
 Reports whether previous computation was successful. More...
 
ParameterTypepardisoParameterArray ()
 
- Public Member Functions inherited from Eigen::SparseSolverBase< Derived >
template<typename Rhs >
const Solve< Derived, Rhs > solve (const MatrixBase< Rhs > &b) const
 
template<typename Rhs >
const Solve< Derived, Rhs > solve (const SparseMatrixBase< Rhs > &b) const
 
 SparseSolverBase ()
 

The documentation for this class was generated from the following file: