Classes | Public Types | Public Member Functions | Protected Attributes
SimplicialCholesky< _MatrixType, _UpLo > Class Template Reference

A direct sparse Cholesky factorization. More...

List of all members.

Classes

struct  keep_diag

Public Types

enum  { UpLo }
typedef SparseMatrix< Scalar,
ColMajor, Index > 
CholMatrixType
typedef MatrixType::Index Index
typedef _MatrixType MatrixType
typedef MatrixType::RealScalar RealScalar
typedef MatrixType::Scalar Scalar
typedef Matrix< Scalar,
MatrixType::ColsAtCompileTime, 1 > 
VectorType

Public Member Functions

void analyzePattern (const MatrixType &a)
Index cols () const
SimplicialCholeskycompute (const MatrixType &matrix)
template<typename Stream >
void dumpMemory (Stream &s)
void factorize (const MatrixType &a)
ComputationInfo info () const
 Reports whether previous computation was successful.
const PermutationMatrix
< Dynamic > & 
permutationP () const
const PermutationMatrix
< Dynamic > & 
permutationPinv () const
Index rows () const
SimplicialCholeskysetMode (SimplicialCholeskyMode mode)
 SimplicialCholesky (const MatrixType &matrix)
template<typename Rhs >
const internal::solve_retval
< SimplicialCholesky, Rhs > 
solve (const MatrixBase< Rhs > &b) const

Protected Attributes

bool m_analysisIsOk
VectorType m_diag
bool m_factorizationIsOk
ComputationInfo m_info
bool m_isInitialized
bool m_LDLt
CholMatrixType m_matrix
VectorXi m_nonZerosPerCol
PermutationMatrix< Dynamic > m_P
VectorXi m_parent
PermutationMatrix< Dynamic > m_Pinv

Detailed Description

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

A direct sparse Cholesky factorization.

This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization. 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.

Member Function Documentation

void analyzePattern ( const MatrixType &  a)
Returns:
the solution x of $ A x = b $ using the current decomposition of A.
See also:
compute() 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()
SimplicialCholesky& compute ( const MatrixType &  matrix) [inline]

Computes the sparse Cholesky decomposition of matrix

void factorize ( const MatrixType &  a)

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()
ComputationInfo info ( ) const [inline]

Reports whether previous computation was successful.

Returns:
Success if computation was succesful, NumericalIssue if the matrix.appears to be negative.
const PermutationMatrix<Dynamic>& permutationP ( ) const [inline]
Returns:
the permutation P
See also:
permutationPinv()
const PermutationMatrix<Dynamic>& permutationPinv ( ) const [inline]
Returns:
the inverse P^-1 of the permutation P
See also:
permutationP()
const internal::solve_retval<SimplicialCholesky, Rhs> solve ( const MatrixBase< Rhs > &  b) const [inline]
Returns:
the solution x of $ A x = b $ using the current decomposition of A.
See also:
compute()

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