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CholmodSimplicialLLT< _MatrixType, _UpLo > Class Template Reference
CholmodSupport module

Detailed Description

template<typename _MatrixType, int _UpLo = Lower>
class Eigen::CholmodSimplicialLLT< _MatrixType, _UpLo >

A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod.

This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization using the Cholmod library. This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Therefore, it has little practical interest. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices X and B can be either dense or sparse.

Template Parameters
_MatrixTypethe type of the sparse matrix A, it must be a SparseMatrix<>
_UpLothe triangular part that will be used for the computations. It can be Lower or Upper. Default is Lower.

This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.

See Also
Sparse solvers, class CholmodSupernodalLLT, class SimplicialLLT
+ Inheritance diagram for CholmodSimplicialLLT< _MatrixType, _UpLo >:

Public Member Functions

void analyzePattern (const MatrixType &matrix)
 
cholmod_common & cholmod ()
 
CholmodSimplicialLLT
< _MatrixType, _UpLo > & 		compute (const MatrixType &matrix)
 
void factorize (const MatrixType &matrix)
 
ComputationInfo info () const
 Reports whether previous computation was successful. More...
 
CholmodSimplicialLLT
< _MatrixType, _UpLo > & 		setShift (const RealScalar &offset)
 
const internal::solve_retval
< CholmodBase, Rhs > 		solve (const MatrixBase< Rhs > &b) const
 
const
internal::sparse_solve_retval
< CholmodBase, Rhs > 		solve (const SparseMatrixBase< Rhs > &b) const
 

Member Function Documentation

void analyzePattern ( const MatrixType &  matrix)
inlineinherited

Performs a symbolic decomposition on the sparsity pattern of matrix.

This function is particularly useful when solving for several problems having the same structure.

See Also
factorize()

References Eigen::Success, and Eigen::viewAsCholmod().

cholmod_common& cholmod ( )
inlineinherited

Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations. See the Cholmod user guide for details.

CholmodSimplicialLLT< _MatrixType, _UpLo > & compute ( const MatrixType &  matrix)
inlineinherited

Computes the sparse Cholesky decomposition of matrix

References CholmodBase< _MatrixType, _UpLo, Derived >::analyzePattern(), and CholmodBase< _MatrixType, _UpLo, Derived >::factorize().

void factorize ( const MatrixType &  matrix)
inlineinherited

Performs a numeric decomposition of matrix

The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed.

See Also
analyzePattern()

References Eigen::NumericalIssue, Eigen::Success, and Eigen::viewAsCholmod().

ComputationInfo info ( ) const
inlineinherited

Reports whether previous computation was successful.

Returns
Success if computation was succesful, NumericalIssue if the matrix.appears to be negative.
CholmodSimplicialLLT< _MatrixType, _UpLo > & setShift ( const RealScalar &  offset)
inlineinherited

Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.

During the numerical factorization, an offset term is added to the diagonal coefficients:
d_ii = offset + d_ii

The default is offset=0.

Returns
a reference to *this.
const internal::solve_retval<CholmodBase, Rhs> solve ( const MatrixBase< Rhs > &  b) const
inlineinherited
Returns
the solution x of $ A x = b $ using the current decomposition of A.
See Also
compute()
const internal::sparse_solve_retval<CholmodBase, Rhs> solve ( const SparseMatrixBase< Rhs > &  b) const
inlineinherited
Returns
the solution x of $ A x = b $ using the current decomposition of A.
See Also
compute()

References EigenBase< Derived >::derived(), and SparseMatrixBase< Derived >::rows().

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