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SkylineInplaceLU< MatrixType > Class Template Reference
Skyline module

Detailed Description

template<typename MatrixType>
class Eigen::SkylineInplaceLU< MatrixType >

Inplace LU decomposition of a skyline matrix and associated features.

Parameters
MatrixTypethe type of the matrix of which we are computing the LU factorization

Public Member Functions

void compute ()
 
int flags () const
 
RealScalar precision () const
 
void setFlags (int f)
 
void setPrecision (RealScalar v)
 
 SkylineInplaceLU (MatrixType &matrix, int flags=0)
 
template<typename BDerived , typename XDerived >
bool solve (const MatrixBase< BDerived > &b, MatrixBase< XDerived > *x, const int transposed=0) const
 
bool succeeded (void) const
 

Constructor & Destructor Documentation

SkylineInplaceLU ( MatrixType &  matrix,
int  flags = 0 
)
inline

Creates a LU object and compute the respective factorization of matrix using flags flags.

References SkylineInplaceLU< MatrixType >::compute().

Member Function Documentation

void compute ( )

Computes/re-computes the LU factorization

Computes / recomputes the in place LU decomposition of the SkylineInplaceLU. using the default algorithm.

Referenced by SkylineInplaceLU< MatrixType >::SkylineInplaceLU().

int flags ( ) const
inline
Returns
the current flags
RealScalar precision ( ) const
inline
Returns
the current precision.
See Also
setPrecision()
void setFlags ( int  f)
inline

Sets the flags. Possible values are:

  • CompleteFactorization
  • IncompleteFactorization
  • MemoryEfficient
  • one of the ordering methods
  • etc...
See Also
flags()
void setPrecision ( RealScalar  v)
inline

Sets the relative threshold value used to prune zero coefficients during the decomposition.

Setting a value greater than zero speeds up computation, and yields to an imcomplete factorization with fewer non zero coefficients. Such approximate factors are especially useful to initialize an iterative solver.

Note that the exact meaning of this parameter might depends on the actual backend. Moreover, not all backends support this feature.

See Also
precision()
bool solve ( const MatrixBase< BDerived > &  b,
MatrixBase< XDerived > *  x,
const int  transposed = 0 
) const
Returns
the lower triangular matrix L
the upper triangular matrix U

Computes *x = U^-1 L^-1 b

If transpose is set to SvTranspose or SvAdjoint, the solution of the transposed/adjoint system is computed instead.

Not all backends implement the solution of the transposed or adjoint system.

bool succeeded ( void  ) const
inline
Returns
true if the factorization succeeded
The documentation for this class was generated from the following file: