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SUBROUTINE sla_SVDCOV (N, NP, NC, W, V, WORK, CVM)
*+
* - - - - - - -
* S V D C O V
* - - - - - - -
*
* From the W and V matrices from the SVD factorisation of a matrix
* (as obtained from the sla_SVD routine), obtain the covariance matrix.
*
* (double precision)
*
* Given:
* N i number of rows and columns in matrices W and V
* NP i first dimension of array containing matrix V
* NC i first dimension of array to receive CVM
* W d(N) NxN diagonal matrix W (diagonal elements only)
* V d(NP,NP) array containing NxN orthogonal matrix V
*
* Returned:
* WORK d(N) workspace
* CVM d(NC,NC) array to receive covariance matrix
*
* Reference:
* Numerical Recipes, section 14.3.
*
* P.T.Wallace Starlink December 1988
*
* Copyright (C) 1995 Rutherford Appleton Laboratory
*-
IMPLICIT NONE
INTEGER N,NP,NC
DOUBLE PRECISION W(N),V(NP,NP),WORK(N),CVM(NC,NC)
INTEGER I,J,K
DOUBLE PRECISION S
DO I=1,N
S=W(I)
IF (S.NE.0D0) THEN
WORK(I)=1D0/(S*S)
ELSE
WORK(I)=0D0
END IF
END DO
DO I=1,N
DO J=1,I
S=0D0
DO K=1,N
S=S+V(I,K)*V(J,K)*WORK(K)
END DO
CVM(I,J)=S
CVM(J,I)=S
END DO
END DO
END
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