Eigen  3.4.90 (git rev 67eeba6e720c5745abc77ae6c92ce0a44aa7b7ae)
Eigen::CholmodBase< MatrixType_, UpLo_, Derived > Class Template Reference

Detailed Description

template<typename MatrixType_, int UpLo_, typename Derived>
class Eigen::CholmodBase< MatrixType_, UpLo_, Derived >

The base class for the direct Cholesky factorization of Cholmod.

See also
class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
+ Inheritance diagram for Eigen::CholmodBase< MatrixType_, UpLo_, Derived >:

Public Member Functions

void analyzePattern (const MatrixType &matrix)
 
cholmod_common & cholmod ()
 
Derived & compute (const MatrixType &matrix)
 
Scalar determinant () const
 
void factorize (const MatrixType &matrix)
 
ComputationInfo info () const
 Reports whether previous computation was successful. More...
 
Scalar logDeterminant () const
 
Derived & setShift (const RealScalar &offset)
 
- 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 ()
 

Member Function Documentation

◆ analyzePattern()

template<typename MatrixType_ , int UpLo_, typename Derived >
void Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::analyzePattern ( const MatrixType &  matrix)
inline

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()

◆ cholmod()

template<typename MatrixType_ , int UpLo_, typename Derived >
cholmod_common& Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::cholmod ( )
inline

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.

◆ compute()

template<typename MatrixType_ , int UpLo_, typename Derived >
Derived& Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::compute ( const MatrixType &  matrix)
inline

Computes the sparse Cholesky decomposition of matrix

◆ determinant()

template<typename MatrixType_ , int UpLo_, typename Derived >
Scalar Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::determinant ( ) const
inline
Returns
the determinant of the underlying matrix from the current factorization

◆ factorize()

template<typename MatrixType_ , int UpLo_, typename Derived >
void Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::factorize ( const MatrixType &  matrix)
inline

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()

◆ info()

template<typename MatrixType_ , int UpLo_, typename Derived >
ComputationInfo Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::info ( ) const
inline

Reports whether previous computation was successful.

Returns
Success if computation was successful, NumericalIssue if the matrix.appears to be negative.

◆ logDeterminant()

template<typename MatrixType_ , int UpLo_, typename Derived >
Scalar Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::logDeterminant ( ) const
inline
Returns
the log determinant of the underlying matrix from the current factorization

◆ setShift()

template<typename MatrixType_ , int UpLo_, typename Derived >
Derived& Eigen::CholmodBase< MatrixType_, UpLo_, Derived >::setShift ( const RealScalar &  offset)
inline

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.

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