Computes the reciprocal pivot growth factor norm(A)/norm(U) for a general matrix.
FORTRAN 77:
call sla_rpvgrw( n, ncols, a, lda, af, ldaf )
call dla_rpvgrw( n, ncols, a, lda, af, ldaf )
call cla_rpvgrw( n, ncols, a, lda, af, ldaf )
call zla_rpvgrw( n, ncols, a, lda, af, ldaf )
The ?la_rpvgrw routine computes the reciprocal pivot growth factor norm(A)/norm(U). The max absolute element norm is used. If this is much less than 1, the stability of the LU factorization of the equilibrated matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
n |
INTEGER. The number of linear equations, the order of the matrix A; n ≥ 0. |
ncols |
INTEGER. The number of columns of the matrix A; ncols ≥ 0. |
a, af |
REAL for sla_rpvgrw DOUBLE PRECISION for dla_rpvgrw COMPLEX for cla_rpvgrw DOUBLE COMPLEX for zla_rpvgrw. Arrays: a(lda,*), af(ldaf,*). The array a contains the input n-by-n matrix A. The second dimension of a must be at least max(1,n). The array af contains the factors L and U from the factorization triangular factor L or U from the Cholesky factorization A = P*L*U as computed by ?getrf. The second dimension of af must be at least max(1,n). |
lda |
INTEGER. The leading dimension of a; lda ≥ max(1,n). |
ldaf |
INTEGER. The leading dimension of af; ldaf ≥ max(1,n). |