.TH DLAQSY 1 "November 2006" " LAPACK auxiliary routine (version 3.1) " " LAPACK auxiliary routine (version 3.1) "
.SH NAME
DLAQSY - a symmetric matrix A using the scaling factors in the vector S
.SH SYNOPSIS
.TP 19
SUBROUTINE DLAQSY(
UPLO, N, A, LDA, S, SCOND, AMAX, EQUED )
.TP 19
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CHARACTER
EQUED, UPLO
.TP 19
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INTEGER
LDA, N
.TP 19
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DOUBLE
PRECISION AMAX, SCOND
.TP 19
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DOUBLE
PRECISION A( LDA, * ), S( * )
.SH PURPOSE
DLAQSY equilibrates a symmetric matrix A using the scaling factors
in the vector S.
.SH ARGUMENTS
.TP 8
UPLO (input) CHARACTER*1
Specifies whether the upper or lower triangular part of the
symmetric matrix A is stored.
= \(aqU\(aq: Upper triangular
.br
= \(aqL\(aq: Lower triangular
.TP 8
N (input) INTEGER
The order of the matrix A. N >= 0.
.TP 8
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = \(aqU\(aq, the leading
n by n upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = \(aqL\(aq, the
leading n by n lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit, if EQUED = \(aqY\(aq, the equilibrated matrix:
diag(S) * A * diag(S).
.TP 8
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(N,1).
.TP 8
S (input) DOUBLE PRECISION array, dimension (N)
The scale factors for A.
.TP 8
SCOND (input) DOUBLE PRECISION
Ratio of the smallest S(i) to the largest S(i).
.TP 8
AMAX (input) DOUBLE PRECISION
Absolute value of largest matrix entry.
.TP 8
EQUED (output) CHARACTER*1
Specifies whether or not equilibration was done.
= \(aqN\(aq: No equilibration.
.br
= \(aqY\(aq: Equilibration was done, i.e., A has been replaced by
diag(S) * A * diag(S).
.SH 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.