35 @deftypefn {Built-in Function} {@var{c} =} rcond (@var{A})\n\
36 Compute the 1-norm estimate of the reciprocal condition number as returned\n\
37 by @sc{lapack}. If the matrix is well-conditioned then @var{c} will be near\n\
38 1 and if the matrix is poorly conditioned it will be close to zero.\n\
40 The matrix @var{A} must not be sparse. If the matrix is sparse then\n\
41 @code{condest (@var{A})} or @code{rcond (full (@var{A}))} should be used\n\
43 @seealso{cond, condest}\n\
48 int nargin = args.
length ();
52 else if (args(0).is_sparse_type ())
53 error (
"rcond: for sparse matrices use 'rcond (full (a))' or 'condest (a)' instead");
54 else if (args(0).is_single_type ())
56 if (args(0).is_complex_type ())
60 retval = m.
rcond (mattyp);
61 args(0).matrix_type (mattyp);
67 retval = m.
rcond (mattyp);
68 args(0).matrix_type (mattyp);
71 else if (args(0).is_complex_type ())
75 retval = m.
rcond (mattyp);
76 args(0).matrix_type (mattyp);
80 Matrix m = args(0).matrix_value ();
82 retval = m.
rcond (mattyp);
83 args(0).matrix_type (mattyp);