dlaqsb

Langue: en

Version: 316742 (ubuntu - 07/07/09)

Section: 3 (Bibliothèques de fonctions)

NAME

DLAQSB - equilibrate a symmetric band matrix A using the scaling factors in the vector S

SYNOPSIS

SUBROUTINE DLAQSB(
UPLO, N, KD, AB, LDAB, S, SCOND, AMAX, EQUED )

    
CHARACTER EQUED, UPLO

    
INTEGER KD, LDAB, N

    
DOUBLE PRECISION AMAX, SCOND

    
DOUBLE PRECISION AB( LDAB, * ), S( * )

PURPOSE

DLAQSB equilibrates a symmetric band matrix A using the scaling factors in the vector S.

ARGUMENTS

UPLO (input) CHARACTER*1
Specifies whether the upper or lower triangular part of the symmetric matrix A is stored. = 'U': Upper triangular
= 'L': Lower triangular
N (input) INTEGER
The order of the matrix A. N >= 0.
KD (input) INTEGER
The number of super-diagonals of the matrix A if UPLO = 'U', or the number of sub-diagonals if UPLO = 'L'. KD >= 0.
AB (input/output) DOUBLE PRECISION array, dimension (LDAB,N)
On entry, the upper or lower triangle of the symmetric band matrix A, stored in the first KD+1 rows of the array. The j-th column of A is stored in the j-th column of the array AB as follows: if UPLO = 'U', AB(kd+1+i-j,j) = A(i,j) for max(1,j-kd)<=i<=j; if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+kd).

On exit, if INFO = 0, the triangular factor U or L from the Cholesky factorization A = U'*U or A = L*L' of the band matrix A, in the same storage format as A.

LDAB (input) INTEGER
The leading dimension of the array AB. LDAB >= KD+1.
S (output) DOUBLE PRECISION array, dimension (N)
The scale factors for A.
SCOND (input) DOUBLE PRECISION
Ratio of the smallest S(i) to the largest S(i).
AMAX (input) DOUBLE PRECISION
Absolute value of largest matrix entry.
EQUED (output) CHARACTER*1
Specifies whether or not equilibration was done. = 'N': No equilibration.
= 'Y': Equilibration was done, i.e., A has been replaced by diag(S) * A * diag(S).

PARAMETERS

THRESH is a threshold value used to decide if scaling should be done based on the ratio of the scaling factors. If SCOND < THRESH, scaling is done.

LARGE and SMALL are threshold values used to decide if scaling should be done based on the absolute size of the largest matrix element. If AMAX > LARGE or AMAX < SMALL, scaling is done.