Public Member Functions
UmfPackLU< _MatrixType > Class Template Reference

A sparse LU factorization and solver based on UmfPack. More...

#include <UmfPackSupport.h>

Inherits noncopyable.

List of all members.

Public Member Functions

void analyzePattern (const MatrixType &matrix)
void compute (const MatrixType &matrix)
void factorize (const MatrixType &matrix)
ComputationInfo info () const
 Reports whether previous computation was successful.
template<typename Rhs >
const internal::solve_retval
< UmfPackLU, Rhs > 
solve (const MatrixBase< Rhs > &b) const

Detailed Description

template<typename _MatrixType>
class Eigen::UmfPackLU< _MatrixType >

A sparse LU factorization and solver based on UmfPack.

This class allows to solve for A.X = B sparse linear problems via a LU factorization using the UmfPack library. The sparse matrix A must be squared and full rank. The vectors or matrices X and B can be either dense or sparse.

The input matrix A should be in a compressed and column-major form. Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.

Template Parameters:
_MatrixTypethe type of the sparse matrix A, it must be a SparseMatrix<>
See also:
Solving linear problems

Member Function Documentation

void analyzePattern ( const MatrixType &  matrix) [inline]
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(), compute()

References Eigen::InvalidInput, and Eigen::Success.

Referenced by UmfPackLU< _MatrixType >::compute().

void compute ( const MatrixType &  matrix) [inline]

Computes the sparse Cholesky decomposition of matrix Note that the matrix should be column-major, and in compressed format for best performance.

See also:
SparseMatrix::makeCompressed().

References UmfPackLU< _MatrixType >::analyzePattern(), and UmfPackLU< _MatrixType >::factorize().

void factorize ( const MatrixType &  matrix) [inline]

Performs a numeric decomposition of matrix

The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed.

See also:
analyzePattern(), compute()

References Eigen::NumericalIssue, and Eigen::Success.

Referenced by UmfPackLU< _MatrixType >::compute().

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 internal::solve_retval<UmfPackLU, 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: