| | DEFUN_DLD (symbfact, args, nargout,"-*- texinfo -*-\n\
@deftypefn {Loadable Function} {[@var{count}, @var{h}, @var{parent}, @var{post}, @var{r}] =} symbfact (@var{S})\n\
@deftypefnx {Loadable Function} {[@dots{}] =} symbfact (@var{S}, @var{typ})\n\
@deftypefnx {Loadable Function} {[@dots{}] =} symbfact (@var{S}, @var{typ}, @var{mode})\n\
\n\
Perform a symbolic factorization analysis on the sparse matrix @var{S}.\n\
Where\n\
\n\
@table @var\n\
@item S\n\
@var{S} is a complex or real sparse matrix.\n\
\n\
@item typ\n\
Is the type of the factorization and can be one of\n\
\n\
@table @samp\n\
@item sym\n\
Factorize @var{S}. This is the default.\n\
\n\
@item col\n\
Factorize @code{@var{S}' * @var{S}}.\n\
\n\
@item row\n\
Factorize @code{@var{S} * @var{S}'}.\n\
\n\
@item lo\n\
Factorize @code{@var{S}'}\n\
@end table\n\
\n\
@item mode\n\
The default is to return the Cholesky@tie{}factorization for @var{r}, and if\n\
@var{mode} is 'L', the conjugate transpose of the Cholesky@tie{}factorization\n\
is returned. The conjugate transpose version is faster and uses less\n\
memory, but returns the same values for @var{count}, @var{h}, @var{parent}\n\
and @var{post} outputs.\n\
@end table\n\
\n\
The output variables are\n\
\n\
@table @var\n\
@item count\n\
The row counts of the Cholesky@tie{}factorization as determined by @var{typ}.\n\
\n\
@item h\n\
The height of the elimination tree.\n\
\n\
@item parent\n\
The elimination tree itself.\n\
\n\
@item post\n\
A sparse boolean matrix whose structure is that of the Cholesky\n\
factorization as determined by @var{typ}.\n\
@end table\n\
@end deftypefn") |
