UmfPackLU< _MatrixType > Class Template Reference
[UmfPackSupport module]

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

Inherits Eigen::internal::noncopyable.

List of all members.

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.
template<typename Rhs >
const internal::sparse_solve_retval < UmfPackLU, Rhs >	solve (const SparseMatrixBase< Rhs > &b) const
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.

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:

_MatrixType

the type of the sparse matrix A, it must be a SparseMatrix<>

See also:

Sparse solvers

---

Member Function Documentation

void 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()

void 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().

void 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()

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::sparse_solve_retval<UmfPackLU, Rhs> solve

(

const SparseMatrixBase< Rhs > &

b

)

const [inline]

Returns:

the solution x of using the current decomposition of A.

See also:

compute()

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

const internal::solve_retval<UmfPackLU, Rhs> solve

(

const MatrixBase< Rhs > &

b

)

const [inline]

Returns:

the solution x of using the current decomposition of A.

See also:

compute()

---

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

• UmfPackSupport.h