zgbequ (l) - Linux Manuals
zgbequ: computes row and column scalings intended to equilibrate an M-by-N band matrix A and reduce its condition number
NAME
ZGBEQU - computes row and column scalings intended to equilibrate an M-by-N band matrix A and reduce its condition numberSYNOPSIS
- SUBROUTINE ZGBEQU(
- M, N, KL, KU, AB, LDAB, R, C, ROWCND, COLCND, AMAX, INFO )
- INTEGER INFO, KL, KU, LDAB, M, N
- DOUBLE PRECISION AMAX, COLCND, ROWCND
- DOUBLE PRECISION C( * ), R( * )
- COMPLEX*16 AB( LDAB, * )
PURPOSE
ZGBEQU computes row and column scalings intended to equilibrate an M-by-N band matrix A and reduce its condition number. R returns the row scale factors and C the column scale factors, chosen to try to make the largest element in each row and column of the matrix B with elements B(i,j)=R(i)*A(i,j)*C(j) have absolute value 1.R(i) and C(j) are restricted to be between SMLNUM = smallest safe number and BIGNUM = largest safe number. Use of these scaling factors is not guaranteed to reduce the condition number of A but works well in practice.
ARGUMENTS
- M (input) INTEGER
- The number of rows of the matrix A. M >= 0.
- N (input) INTEGER
- The number of columns of the matrix A. N >= 0.
- KL (input) INTEGER
- The number of subdiagonals within the band of A. KL >= 0.
- KU (input) INTEGER
- The number of superdiagonals within the band of A. KU >= 0.
- AB (input) COMPLEX*16 array, dimension (LDAB,N)
- The band matrix A, stored in rows 1 to KL+KU+1. The j-th column of A is stored in the j-th column of the array AB as follows: AB(ku+1+i-j,j) = A(i,j) for max(1,j-ku)<=i<=min(m,j+kl).
- LDAB (input) INTEGER
- The leading dimension of the array AB. LDAB >= KL+KU+1.
- R (output) DOUBLE PRECISION array, dimension (M)
- If INFO = 0, or INFO > M, R contains the row scale factors for A.
- C (output) DOUBLE PRECISION array, dimension (N)
- If INFO = 0, C contains the column scale factors for A.
- ROWCND (output) DOUBLE PRECISION
- If INFO = 0 or INFO > M, ROWCND contains the ratio of the smallest R(i) to the largest R(i). If ROWCND >= 0.1 and AMAX is neither too large nor too small, it is not worth scaling by R.
- COLCND (output) DOUBLE PRECISION
- If INFO = 0, COLCND contains the ratio of the smallest C(i) to the largest C(i). If COLCND >= 0.1, it is not worth scaling by C.
- AMAX (output) DOUBLE PRECISION
- Absolute value of largest matrix element. If AMAX is very close to overflow or very close to underflow, the matrix should be scaled.
- INFO (output) INTEGER
-
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, and i is
<= M: the i-th row of A is exactly zero
> M: the (i-M)-th column of A is exactly zero