!>
!> SBDT05 reconstructs a bidiagonal matrix B from its (partial) SVD:
!>    S = U' * B * V
!> where U and V are orthogonal matrices and S is diagonal.
!>
!> The test ratio to test the singular value decomposition is
!>    RESID = norm( S - U' * B * V ) / ( n * norm(B) * EPS )
!> where VT = V' and EPS is the machine precision.
!> 

M

!>          M is INTEGER
!>          The number of rows of the matrices A and U.
!> 

N

!>          N is INTEGER
!>          The number of columns of the matrices A and VT.
!> 

A

!>          A is REAL array, dimension (LDA,N)
!>          The m by n matrix A.
!> 

LDA

!>          LDA is INTEGER
!>          The leading dimension of the array A.  LDA >= max(1,M).
!> 

S

!>          S is REAL array, dimension (NS)
!>          The singular values from the (partial) SVD of B, sorted in
!>          decreasing order.
!> 

NS

!>          NS is INTEGER
!>          The number of singular values/vectors from the (partial)
!>          SVD of B.
!> 

U

!>          U is REAL array, dimension (LDU,NS)
!>          The n by ns orthogonal matrix U in S = U' * B * V.
!> 

LDU

!>          LDU is INTEGER
!>          The leading dimension of the array U.  LDU >= max(1,N)
!> 

VT

!>          VT is REAL array, dimension (LDVT,N)
!>          The n by ns orthogonal matrix V in S = U' * B * V.
!> 

LDVT

!>          LDVT is INTEGER
!>          The leading dimension of the array VT.
!> 

WORK

!>          WORK is REAL array, dimension (M,N)
!> 

RESID

!>          RESID is REAL
!>          The test ratio:  norm(S - U' * A * V) / ( n * norm(A) * EPS )
!> 

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