Sparse supernodal LU factorization for general matrices. More...

#include <SparseLU.h>

Inheritance diagram for Eigen::SparseLU< _MatrixType, _OrderingType >:

Public Types
typedef internal::SparseLUImpl< Scalar, Index >	Base

typedef MatrixType::Index	Index

typedef Matrix< Index, Dynamic, 1 >	IndexVector

typedef _MatrixType	MatrixType

typedef SparseMatrix< Scalar, ColMajor, Index >	NCMatrix

typedef _OrderingType	OrderingType

typedef PermutationMatrix< Dynamic, Dynamic, Index >	PermutationType

typedef MatrixType::RealScalar	RealScalar

typedef MatrixType::Scalar	Scalar

typedef Matrix< Scalar, Dynamic, 1 >	ScalarVector

typedef internal::MappedSuperNodalMatrix< Scalar, Index >	SCMatrix

Public Types inherited from Eigen::internal::SparseLUImpl< _MatrixType::Scalar, _MatrixType::Index >
typedef Ref< Matrix< _MatrixType::Index, Dynamic, 1 > >	BlockIndexVector

typedef Ref< Matrix< _MatrixType::Scalar, Dynamic, 1 > >	BlockScalarVector

typedef LU_GlobalLU_t< IndexVector, ScalarVector >	GlobalLU_t

typedef Matrix< _MatrixType::Index, Dynamic, 1 >	IndexVector

typedef SparseMatrix< _MatrixType::Scalar, ColMajor, _MatrixType::Index >	MatrixType

typedef ScalarVector::RealScalar	RealScalar

typedef Matrix< _MatrixType::Scalar, Dynamic, 1 >	ScalarVector

Public Member Functions
template<typename Rhs , typename Dest >
bool	_solve (const MatrixBase< Rhs > &B, MatrixBase< Dest > &_X) const

Scalar	absDeterminant ()

void	analyzePattern (const MatrixType &matrix)

Index	cols () const

const PermutationType &	colsPermutation () const

void	compute (const MatrixType &matrix)

void	factorize (const MatrixType &matrix)

ComputationInfo	info () const
	Reports whether previous computation was successful. More...

void	isSymmetric (bool sym)

std::string	lastErrorMessage () const

Scalar	logAbsDeterminant () const

SparseLUMatrixLReturnType< SCMatrix >	matrixL () const

SparseLUMatrixUReturnType< SCMatrix, MappedSparseMatrix< Scalar, ColMajor, Index > >	matrixU () const

Index	rows () const

const PermutationType &	rowsPermutation () const

void	setPivotThreshold (const RealScalar &thresh)

Scalar	signDeterminant ()

void	simplicialfactorize (const MatrixType &matrix)

template<typename Rhs >
const internal::solve_retval< SparseLU, Rhs >	solve (const MatrixBase< Rhs > &B) const

template<typename Rhs >
const internal::sparse_solve_retval< SparseLU, Rhs >	solve (const SparseMatrixBase< Rhs > &B) const

	SparseLU ()

	SparseLU (const MatrixType &matrix)

	~SparseLU ()

Protected Member Functions
void	initperfvalues ()

Protected Member Functions inherited from Eigen::internal::SparseLUImpl< _MatrixType::Scalar, _MatrixType::Index >
_MatrixType::Index	column_bmod (const _MatrixType::Index jcol, const _MatrixType::Index nseg, BlockScalarVector dense, ScalarVector &tempv, BlockIndexVector segrep, BlockIndexVector repfnz, _MatrixType::Index fpanelc, GlobalLU_t &glu)
	Performs numeric block updates (sup-col) in topological order. More...

_MatrixType::Index	column_dfs (const _MatrixType::Index m, const _MatrixType::Index jcol, IndexVector &perm_r, _MatrixType::Index maxsuper, _MatrixType::Index &nseg, BlockIndexVector lsub_col, IndexVector &segrep, BlockIndexVector repfnz, IndexVector &xprune, IndexVector &marker, IndexVector &parent, IndexVector &xplore, GlobalLU_t &glu)
	Performs a symbolic factorization on column jcol and decide the supernode boundary. More...

_MatrixType::Index	copy_to_ucol (const _MatrixType::Index jcol, const _MatrixType::Index nseg, IndexVector &segrep, BlockIndexVector repfnz, IndexVector &perm_r, BlockScalarVector dense, GlobalLU_t &glu)
	Performs numeric block updates (sup-col) in topological order. More...

void	countnz (const _MatrixType::Index n, _MatrixType::Index &nnzL, _MatrixType::Index &nnzU, GlobalLU_t &glu)
	Count Nonzero elements in the factors. More...

void	dfs_kernel (const _MatrixType::Index jj, IndexVector &perm_r, _MatrixType::Index &nseg, IndexVector &panel_lsub, IndexVector &segrep, Ref< IndexVector > repfnz_col, IndexVector &xprune, Ref< IndexVector > marker, IndexVector &parent, IndexVector &xplore, GlobalLU_t &glu, _MatrixType::Index &nextl_col, _MatrixType::Index krow, Traits &traits)

_MatrixType::Index	expand (VectorType &vec, _MatrixType::Index &length, _MatrixType::Index nbElts, _MatrixType::Index keep_prev, _MatrixType::Index &num_expansions)

void	fixupL (const _MatrixType::Index n, const IndexVector &perm_r, GlobalLU_t &glu)
	Fix up the data storage lsub for L-subscripts. More...

void	heap_relax_snode (const _MatrixType::Index n, IndexVector &et, const _MatrixType::Index relax_columns, IndexVector &descendants, IndexVector &relax_end)
	Identify the initial relaxed supernodes. More...

_MatrixType::Index	memInit (_MatrixType::Index m, _MatrixType::Index n, _MatrixType::Index annz, _MatrixType::Index lwork, _MatrixType::Index fillratio, _MatrixType::Index panel_size, GlobalLU_t &glu)
	Allocate various working space for the numerical factorization phase. More...

_MatrixType::Index	memXpand (VectorType &vec, _MatrixType::Index &maxlen, _MatrixType::Index nbElts, MemType memtype, _MatrixType::Index &num_expansions)
	Expand the existing storage. More...

void	panel_bmod (const _MatrixType::Index m, const _MatrixType::Index w, const _MatrixType::Index jcol, const _MatrixType::Index nseg, ScalarVector &dense, ScalarVector &tempv, IndexVector &segrep, IndexVector &repfnz, GlobalLU_t &glu)
	Performs numeric block updates (sup-panel) in topological order. More...

void	panel_dfs (const _MatrixType::Index m, const _MatrixType::Index w, const _MatrixType::Index jcol, MatrixType &A, IndexVector &perm_r, _MatrixType::Index &nseg, ScalarVector &dense, IndexVector &panel_lsub, IndexVector &segrep, IndexVector &repfnz, IndexVector &xprune, IndexVector &marker, IndexVector &parent, IndexVector &xplore, GlobalLU_t &glu)
	Performs a symbolic factorization on a panel of columns [jcol, jcol+w) More...

_MatrixType::Index	pivotL (const _MatrixType::Index jcol, const RealScalar &diagpivotthresh, IndexVector &perm_r, IndexVector &iperm_c, _MatrixType::Index &pivrow, GlobalLU_t &glu)
	Performs the numerical pivotin on the current column of L, and the CDIV operation. More...

void	pruneL (const _MatrixType::Index jcol, const IndexVector &perm_r, const _MatrixType::Index pivrow, const _MatrixType::Index nseg, const IndexVector &segrep, BlockIndexVector repfnz, IndexVector &xprune, GlobalLU_t &glu)
	Prunes the L-structure. More...

void	relax_snode (const _MatrixType::Index n, IndexVector &et, const _MatrixType::Index relax_columns, IndexVector &descendants, IndexVector &relax_end)
	Identify the initial relaxed supernodes. More...

_MatrixType::Index	snode_bmod (const _MatrixType::Index jcol, const _MatrixType::Index fsupc, ScalarVector &dense, GlobalLU_t &glu)

_MatrixType::Index	snode_dfs (const _MatrixType::Index jcol, const _MatrixType::Index kcol, const MatrixType &mat, IndexVector &xprune, IndexVector &marker, GlobalLU_t &glu)

Protected Attributes
bool	m_analysisIsOk

Index	m_detPermR

RealScalar	m_diagpivotthresh

IndexVector	m_etree

bool	m_factorizationIsOk

Base::GlobalLU_t	m_glu

ComputationInfo	m_info

bool	m_isInitialized

std::string	m_lastError

SCMatrix	m_Lstore

NCMatrix	m_mat

Index	m_nnzL

Index	m_nnzU

internal::perfvalues< Index >	m_perfv

PermutationType	m_perm_c

PermutationType	m_perm_r

bool	m_symmetricmode

MappedSparseMatrix< Scalar, ColMajor, Index >	m_Ustore

Private Member Functions
	SparseLU (const SparseLU &)

Detailed Description

template<typename _MatrixType, typename _OrderingType>
class Eigen::SparseLU< _MatrixType, _OrderingType >

Sparse supernodal LU factorization for general matrices.

This class implements the supernodal LU factorization for general matrices. It uses the main techniques from the sequential SuperLU package (http://crd-legacy.lbl.gov/~xiaoye/SuperLU/). It handles transparently real and complex arithmetics with single and double precision, depending on the scalar type of your input matrix. The code has been optimized to provide BLAS-3 operations during supernode-panel updates. It benefits directly from the built-in high-performant Eigen BLAS routines. Moreover, when the size of a supernode is very small, the BLAS calls are avoided to enable a better optimization from the compiler. For best performance, you should compile it with NDEBUG flag to avoid the numerous bounds checking on vectors.

An important parameter of this class is the ordering method. It is used to reorder the columns (and eventually the rows) of the matrix to reduce the number of new elements that are created during numerical factorization. The cheapest method available is COLAMD. See the OrderingMethods module for the list of built-in and external ordering methods.

Simple example with key steps

VectorXd x(n), b(n);
SparseMatrix<double, ColMajor> A;
SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<Index> >   solver;
// fill A and b;
// Compute the ordering permutation vector from the structural pattern of A
solver.analyzePattern(A); 
// Compute the numerical factorization 
solver.factorize(A); 
//Use the factors to solve the linear system 
x = solver.solve(b); 

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.

Note: Unlike the initial SuperLU implementation, there is no step to equilibrate the matrix. For badly scaled matrices, this step can be useful to reduce the pivoting during factorization. If this is the case for your matrices, you can try the basic scaling method at "unsupported/Eigen/src/IterativeSolvers/Scaling.h"

Template Parameters

_MatrixType	The type of the sparse matrix. It must be a column-major SparseMatrix<>
_OrderingType	The ordering method to use, either AMD, COLAMD or METIS. Default is COLMAD

See also: TutorialSparseDirectSolvers; OrderingMethods_Module

Definition at line 17 of file SparseLU.h.

Member Typedef Documentation

◆ Base

template<typename _MatrixType , typename _OrderingType >

typedef internal::SparseLUImpl<Scalar, Index> Eigen::SparseLU< _MatrixType, _OrderingType >::Base

Definition at line 86 of file SparseLU.h.

◆ Index

template<typename _MatrixType , typename _OrderingType >

typedef MatrixType::Index Eigen::SparseLU< _MatrixType, _OrderingType >::Index

Definition at line 80 of file SparseLU.h.

◆ IndexVector

template<typename _MatrixType , typename _OrderingType >

typedef Matrix<Index,Dynamic,1> Eigen::SparseLU< _MatrixType, _OrderingType >::IndexVector

Definition at line 84 of file SparseLU.h.

◆ MatrixType

template<typename _MatrixType , typename _OrderingType >

typedef _MatrixType Eigen::SparseLU< _MatrixType, _OrderingType >::MatrixType

Definition at line 76 of file SparseLU.h.

◆ NCMatrix

template<typename _MatrixType , typename _OrderingType >

typedef SparseMatrix<Scalar,ColMajor,Index> Eigen::SparseLU< _MatrixType, _OrderingType >::NCMatrix

Definition at line 81 of file SparseLU.h.

◆ OrderingType

template<typename _MatrixType , typename _OrderingType >

typedef _OrderingType Eigen::SparseLU< _MatrixType, _OrderingType >::OrderingType

Definition at line 77 of file SparseLU.h.

◆ PermutationType

template<typename _MatrixType , typename _OrderingType >

typedef PermutationMatrix<Dynamic, Dynamic, Index> Eigen::SparseLU< _MatrixType, _OrderingType >::PermutationType

Definition at line 85 of file SparseLU.h.

◆ RealScalar

template<typename _MatrixType , typename _OrderingType >

typedef MatrixType::RealScalar Eigen::SparseLU< _MatrixType, _OrderingType >::RealScalar

Definition at line 79 of file SparseLU.h.

◆ Scalar

template<typename _MatrixType , typename _OrderingType >

typedef MatrixType::Scalar Eigen::SparseLU< _MatrixType, _OrderingType >::Scalar

Definition at line 78 of file SparseLU.h.

◆ ScalarVector

template<typename _MatrixType , typename _OrderingType >

typedef Matrix<Scalar,Dynamic,1> Eigen::SparseLU< _MatrixType, _OrderingType >::ScalarVector

Definition at line 83 of file SparseLU.h.

◆ SCMatrix

template<typename _MatrixType , typename _OrderingType >

typedef internal::MappedSuperNodalMatrix<Scalar, Index> Eigen::SparseLU< _MatrixType, _OrderingType >::SCMatrix

Definition at line 82 of file SparseLU.h.

Constructor & Destructor Documentation

◆ SparseLU() [1/3]

template<typename _MatrixType , typename _OrderingType >

Eigen::SparseLU< _MatrixType, _OrderingType >::SparseLU ( )

inline

Definition at line 89 of file SparseLU.h.

◆ SparseLU() [2/3]

template<typename _MatrixType , typename _OrderingType >

Eigen::SparseLU< _MatrixType, _OrderingType >::SparseLU ( const MatrixType & matrix )

inline

Definition at line 93 of file SparseLU.h.

◆ ~SparseLU()

template<typename _MatrixType , typename _OrderingType >

Eigen::SparseLU< _MatrixType, _OrderingType >::~SparseLU ( )

inline

Definition at line 99 of file SparseLU.h.

◆ SparseLU() [3/3]

template<typename _MatrixType , typename _OrderingType >

Eigen::SparseLU< _MatrixType, _OrderingType >::SparseLU ( const SparseLU< _MatrixType, _OrderingType > & )

private

Member Function Documentation

◆ _solve()

template<typename _MatrixType , typename _OrderingType >

template<typename Rhs , typename Dest >

bool Eigen::SparseLU< _MatrixType, _OrderingType >::_solve	(	const MatrixBase< Rhs > &	B,
		MatrixBase< Dest > &	_X
	)		const

inline

Definition at line 222 of file SparseLU.h.

◆ absDeterminant()

template<typename _MatrixType , typename _OrderingType >

Scalar Eigen::SparseLU< _MatrixType, _OrderingType >::absDeterminant ( )

inline

Returns: the absolute value of the determinant of the matrix of which *this is the QR decomposition.

Warning: a determinant can be very big or small, so for matrices of large enough dimension, there is a risk of overflow/underflow. One way to work around that is to use logAbsDeterminant() instead.

See also: logAbsDeterminant(), signDeterminant()

Definition at line 256 of file SparseLU.h.

◆ analyzePattern()

template<typename MatrixType , typename OrderingType >

void Eigen::SparseLU< MatrixType, OrderingType >::analyzePattern ( const MatrixType & mat )

Compute the column permutation to minimize the fill-in

Apply this permutation to the input matrix -
Compute the column elimination tree on the permuted matrix
Postorder the elimination tree and the column permutation

Definition at line 369 of file SparseLU.h.

◆ cols()

template<typename _MatrixType , typename _OrderingType >

Index Eigen::SparseLU< _MatrixType, _OrderingType >::cols ( void ) const

inline

Definition at line 121 of file SparseLU.h.

◆ colsPermutation()

template<typename _MatrixType , typename _OrderingType >

const PermutationType& Eigen::SparseLU< _MatrixType, _OrderingType >::colsPermutation ( ) const

inline

Returns: a reference to the column matrix permutation such that

See also: rowsPermutation()

Definition at line 161 of file SparseLU.h.

◆ compute()

template<typename _MatrixType , typename _OrderingType >

void Eigen::SparseLU< _MatrixType, _OrderingType >::compute ( const MatrixType & matrix )

inline

Compute the symbolic and numeric factorization of the input sparse matrix. The input matrix should be in column-major storage.

Definition at line 112 of file SparseLU.h.

◆ factorize()

template<typename MatrixType , typename OrderingType >

void Eigen::SparseLU< MatrixType, OrderingType >::factorize ( const MatrixType & matrix )

Numerical factorization
Interleaved with the symbolic factorization On exit, info is

= 0: successful factorization

0: if info = i, and i is

  <= A->ncol: U(i,i) is exactly zero. The factorization has
     been completed, but the factor U is exactly singular,
     and division by zero will occur if it is used to solve a
     system of equations.

  > A->ncol: number of bytes allocated when memory allocation
    failure occurred, plus A->ncol. If lwork = -1, it is
    the estimated amount of space needed, plus A->ncol.

Definition at line 452 of file SparseLU.h.

◆ info()

template<typename _MatrixType , typename _OrderingType >

ComputationInfo Eigen::SparseLU< _MatrixType, _OrderingType >::info ( ) const

inline

Reports whether previous computation was successful.

Returns: Success if computation was succesful, NumericalIssue if the LU factorization reports a problem, zero diagonal for instance InvalidInput if the input matrix is invalid

See also: iparm()

Definition at line 207 of file SparseLU.h.

◆ initperfvalues()

template<typename _MatrixType , typename _OrderingType >

void Eigen::SparseLU< _MatrixType, _OrderingType >::initperfvalues ( )

inlineprotected

Definition at line 317 of file SparseLU.h.

◆ isSymmetric()

template<typename _MatrixType , typename _OrderingType >

void Eigen::SparseLU< _MatrixType, _OrderingType >::isSymmetric ( bool sym )

inline

Indicate that the pattern of the input matrix is symmetric

Definition at line 123 of file SparseLU.h.

◆ lastErrorMessage()

template<typename _MatrixType , typename _OrderingType >

std::string Eigen::SparseLU< _MatrixType, _OrderingType >::lastErrorMessage ( ) const

inline

Returns: A string describing the type of error

Definition at line 216 of file SparseLU.h.

◆ logAbsDeterminant()

template<typename _MatrixType , typename _OrderingType >

Scalar Eigen::SparseLU< _MatrixType, _OrderingType >::logAbsDeterminant ( ) const

inline

Returns: the natural log of the absolute value of the determinant of the matrix of which **this is the QR decomposition

Note: This method is useful to work around the risk of overflow/underflow that's inherent to the determinant computation.

See also: absDeterminant(), signDeterminant()

Definition at line 286 of file SparseLU.h.

◆ matrixL()

template<typename _MatrixType , typename _OrderingType >

SparseLUMatrixLReturnType<SCMatrix> Eigen::SparseLU< _MatrixType, _OrderingType >::matrixL ( ) const

inline

Returns: an expression of the matrix L, internally stored as supernodes The only operation available with this expression is the triangular solve
y = b; matrixL().solveInPlace(y);

Definition at line 134 of file SparseLU.h.

◆ matrixU()

template<typename _MatrixType , typename _OrderingType >

SparseLUMatrixUReturnType<SCMatrix,MappedSparseMatrix<Scalar,ColMajor,Index> > Eigen::SparseLU< _MatrixType, _OrderingType >::matrixU ( ) const

inline

Returns: an expression of the matrix U, The only operation available with this expression is the triangular solve
y = b; matrixU().solveInPlace(y);

Definition at line 144 of file SparseLU.h.

◆ rows()

template<typename _MatrixType , typename _OrderingType >

Index Eigen::SparseLU< _MatrixType, _OrderingType >::rows ( void ) const

inline

Definition at line 120 of file SparseLU.h.

◆ rowsPermutation()

template<typename _MatrixType , typename _OrderingType >

const PermutationType& Eigen::SparseLU< _MatrixType, _OrderingType >::rowsPermutation ( ) const

inline

Returns: a reference to the row matrix permutation such that

See also: colsPermutation()

Definition at line 153 of file SparseLU.h.

◆ setPivotThreshold()

template<typename _MatrixType , typename _OrderingType >

void Eigen::SparseLU< _MatrixType, _OrderingType >::setPivotThreshold ( const RealScalar & thresh )

inline

Set the threshold used for a diagonal entry to be an acceptable pivot.

Definition at line 166 of file SparseLU.h.

◆ signDeterminant()

template<typename _MatrixType , typename _OrderingType >

Scalar Eigen::SparseLU< _MatrixType, _OrderingType >::signDeterminant ( )

inline

Returns: A number representing the sign of the determinant

See also: absDeterminant(), logAbsDeterminant()

Definition at line 309 of file SparseLU.h.

◆ simplicialfactorize()

template<typename _MatrixType , typename _OrderingType >

void Eigen::SparseLU< _MatrixType, _OrderingType >::simplicialfactorize ( const MatrixType & matrix )

◆ solve() [1/2]

template<typename _MatrixType , typename _OrderingType >

template<typename Rhs >

const internal::solve_retval<SparseLU, Rhs> Eigen::SparseLU< _MatrixType, _OrderingType >::solve ( const MatrixBase< Rhs > & B ) const

inline

Returns: the solution X of using the current decomposition of A.

Warning: the destination matrix X in X = this->solve(B) must be colmun-major.

See also: compute()

Definition at line 178 of file SparseLU.h.

◆ solve() [2/2]

template<typename _MatrixType , typename _OrderingType >

template<typename Rhs >

const internal::sparse_solve_retval<SparseLU, Rhs> Eigen::SparseLU< _MatrixType, _OrderingType >::solve ( const SparseMatrixBase< Rhs > & B ) const

inline

Returns: the solution X of using the current decomposition of A.

See also: compute()

Definition at line 191 of file SparseLU.h.

Member Data Documentation

◆ m_analysisIsOk

template<typename _MatrixType , typename _OrderingType >

bool Eigen::SparseLU< _MatrixType, _OrderingType >::m_analysisIsOk

protected

Definition at line 331 of file SparseLU.h.

◆ m_detPermR

template<typename _MatrixType , typename _OrderingType >

Index Eigen::SparseLU< _MatrixType, _OrderingType >::m_detPermR

protected

Definition at line 348 of file SparseLU.h.

◆ m_diagpivotthresh

template<typename _MatrixType , typename _OrderingType >

RealScalar Eigen::SparseLU< _MatrixType, _OrderingType >::m_diagpivotthresh

protected

Definition at line 346 of file SparseLU.h.

◆ m_etree

template<typename _MatrixType , typename _OrderingType >

IndexVector Eigen::SparseLU< _MatrixType, _OrderingType >::m_etree

protected

Definition at line 338 of file SparseLU.h.

◆ m_factorizationIsOk

template<typename _MatrixType , typename _OrderingType >

bool Eigen::SparseLU< _MatrixType, _OrderingType >::m_factorizationIsOk

protected

Definition at line 330 of file SparseLU.h.

◆ m_glu

template<typename _MatrixType , typename _OrderingType >

Base::GlobalLU_t Eigen::SparseLU< _MatrixType, _OrderingType >::m_glu

protected

Definition at line 340 of file SparseLU.h.

◆ m_info

template<typename _MatrixType , typename _OrderingType >

ComputationInfo Eigen::SparseLU< _MatrixType, _OrderingType >::m_info

mutableprotected

Definition at line 328 of file SparseLU.h.

◆ m_isInitialized

template<typename _MatrixType , typename _OrderingType >

bool Eigen::SparseLU< _MatrixType, _OrderingType >::m_isInitialized

protected

Definition at line 329 of file SparseLU.h.

◆ m_lastError

template<typename _MatrixType , typename _OrderingType >

std::string Eigen::SparseLU< _MatrixType, _OrderingType >::m_lastError

protected

Definition at line 332 of file SparseLU.h.

◆ m_Lstore

template<typename _MatrixType , typename _OrderingType >

SCMatrix Eigen::SparseLU< _MatrixType, _OrderingType >::m_Lstore

protected

Definition at line 334 of file SparseLU.h.

◆ m_mat

template<typename _MatrixType , typename _OrderingType >

NCMatrix Eigen::SparseLU< _MatrixType, _OrderingType >::m_mat

protected

Definition at line 333 of file SparseLU.h.

◆ m_nnzL

template<typename _MatrixType , typename _OrderingType >

Index Eigen::SparseLU< _MatrixType, _OrderingType >::m_nnzL

protected

Definition at line 347 of file SparseLU.h.

◆ m_nnzU

template<typename _MatrixType , typename _OrderingType >

Index Eigen::SparseLU< _MatrixType, _OrderingType >::m_nnzU

protected

Definition at line 347 of file SparseLU.h.

◆ m_perfv

template<typename _MatrixType , typename _OrderingType >

internal::perfvalues<Index> Eigen::SparseLU< _MatrixType, _OrderingType >::m_perfv

protected

Definition at line 345 of file SparseLU.h.

◆ m_perm_c

template<typename _MatrixType , typename _OrderingType >

PermutationType Eigen::SparseLU< _MatrixType, _OrderingType >::m_perm_c

protected

Definition at line 336 of file SparseLU.h.

◆ m_perm_r

template<typename _MatrixType , typename _OrderingType >

PermutationType Eigen::SparseLU< _MatrixType, _OrderingType >::m_perm_r

protected

Definition at line 337 of file SparseLU.h.

◆ m_symmetricmode

template<typename _MatrixType , typename _OrderingType >

bool Eigen::SparseLU< _MatrixType, _OrderingType >::m_symmetricmode

protected

Definition at line 343 of file SparseLU.h.

◆ m_Ustore

template<typename _MatrixType , typename _OrderingType >

MappedSparseMatrix<Scalar,ColMajor,Index> Eigen::SparseLU< _MatrixType, _OrderingType >::m_Ustore

protected

Definition at line 335 of file SparseLU.h.

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

SparseLU.h

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Detailed Description

template<typename _MatrixType, typename _OrderingType> class Eigen::SparseLU< _MatrixType, _OrderingType >

Member Typedef Documentation

◆ Base

◆ Index

◆ IndexVector

◆ MatrixType

◆ NCMatrix

◆ OrderingType

◆ PermutationType

◆ RealScalar

◆ Scalar

◆ ScalarVector

◆ SCMatrix

Constructor & Destructor Documentation

◆ SparseLU() [1/3]

◆ SparseLU() [2/3]

◆ ~SparseLU()

◆ SparseLU() [3/3]

Member Function Documentation

◆ _solve()

◆ absDeterminant()

◆ analyzePattern()

◆ cols()

◆ colsPermutation()

◆ compute()

◆ factorize()

◆ info()

◆ initperfvalues()

◆ isSymmetric()

◆ lastErrorMessage()

◆ logAbsDeterminant()

◆ matrixL()

◆ matrixU()

◆ rows()

◆ rowsPermutation()

◆ setPivotThreshold()

◆ signDeterminant()

◆ simplicialfactorize()

◆ solve() [1/2]

◆ solve() [2/2]

Member Data Documentation

◆ m_analysisIsOk

◆ m_detPermR

◆ m_diagpivotthresh

◆ m_etree

◆ m_factorizationIsOk

◆ m_glu

◆ m_info

◆ m_isInitialized

◆ m_lastError

◆ m_Lstore

◆ m_mat

◆ m_nnzL

◆ m_nnzU

◆ m_perfv

◆ m_perm_c

◆ m_perm_r

◆ m_symmetricmode

◆ m_Ustore

template<typename _MatrixType, typename _OrderingType>
class Eigen::SparseLU< _MatrixType, _OrderingType >