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Eigen  3.2.5
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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 $ A x = b $ 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 $ A x = b $ using the current decomposition of A.
See also:
compute()

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