Eigen  3.2.92
Eigen::UmfPackLU< _MatrixType > Class Template Reference

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.

Warning
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
TutorialSparseDirectSolvers
+ Inheritance diagram for Eigen::UmfPackLU< _MatrixType >:

Public Member Functions

template<typename InputMatrixType >
void analyzePattern (const InputMatrixType &matrix)
 
template<typename InputMatrixType >
void compute (const InputMatrixType &matrix)
 
template<typename InputMatrixType >
void factorize (const InputMatrixType &matrix)
 
ComputationInfo info () const
 Reports whether previous computation was successful. More...
 
const Solve< UmfPackLU< _MatrixType >, Rhs > solve (const MatrixBase< Rhs > &b) const
 
const Solve< UmfPackLU< _MatrixType >, Rhs > solve (const SparseMatrixBase< Rhs > &b) const
 
const UmfpackControlumfpackControl () const
 
UmfpackControlumfpackControl ()
 
int umfpackFactorizeReturncode () const
 

Member Function Documentation

template<typename _MatrixType >
template<typename InputMatrixType >
void Eigen::UmfPackLU< _MatrixType >::analyzePattern ( const InputMatrixType &  matrix)
inline

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()
template<typename _MatrixType >
template<typename InputMatrixType >
void Eigen::UmfPackLU< _MatrixType >::compute ( const InputMatrixType &  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().
template<typename _MatrixType >
template<typename InputMatrixType >
void Eigen::UmfPackLU< _MatrixType >::factorize ( const InputMatrixType &  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()
template<typename _MatrixType >
ComputationInfo Eigen::UmfPackLU< _MatrixType >::info ( ) const
inline

Reports whether previous computation was successful.

Returns
Success if computation was succesful, NumericalIssue if the matrix.appears to be negative.
const Solve<UmfPackLU< _MatrixType > , Rhs> Eigen::SparseSolverBase< UmfPackLU< _MatrixType > >::solve ( const MatrixBase< Rhs > &  b) const
inlineinherited
Returns
an expression of the solution x of $ A x = b $ using the current decomposition of A.
See also
compute()
const Solve<UmfPackLU< _MatrixType > , Rhs> Eigen::SparseSolverBase< UmfPackLU< _MatrixType > >::solve ( const SparseMatrixBase< Rhs > &  b) const
inlineinherited
Returns
an expression of the solution x of $ A x = b $ using the current decomposition of A.
See also
compute()
template<typename _MatrixType >
const UmfpackControl& Eigen::UmfPackLU< _MatrixType >::umfpackControl ( ) const
inline

Provides access to the control settings array used by UmfPack.

If this array contains NaN's, the default values are used.

See UMFPACK documentation for details.

template<typename _MatrixType >
UmfpackControl& Eigen::UmfPackLU< _MatrixType >::umfpackControl ( )
inline

Provides access to the control settings array used by UmfPack.

If this array contains NaN's, the default values are used.

See UMFPACK documentation for details.

template<typename _MatrixType >
int Eigen::UmfPackLU< _MatrixType >::umfpackFactorizeReturncode ( ) const
inline

Provides the return status code returned by UmfPack during the numeric factorization.

See also
factorize(), compute()

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