!>
!> This routine is deprecated and has been replaced by routine ZGELSY.
!>
!> ZGELSX computes the minimum-norm solution to a complex linear least
!> squares problem:
!>     minimize || A * X - B ||
!> using a complete orthogonal factorization of A.  A is an M-by-N
!> matrix which may be rank-deficient.
!>
!> Several right hand side vectors b and solution vectors x can be
!> handled in a single call; they are stored as the columns of the
!> M-by-NRHS right hand side matrix B and the N-by-NRHS solution
!> matrix X.
!>
!> The routine first computes a QR factorization with column pivoting:
!>     A * P = Q * [ R11 R12 ]
!>                 [  0  R22 ]
!> with R11 defined as the largest leading submatrix whose estimated
!> condition number is less than 1/RCOND.  The order of R11, RANK,
!> is the effective rank of A.
!>
!> Then, R22 is considered to be negligible, and R12 is annihilated
!> by unitary transformations from the right, arriving at the
!> complete orthogonal factorization:
!>    A * P = Q * [ T11 0 ] * Z
!>                [  0  0 ]
!> The minimum-norm solution is then
!>    X = P * Z**H [ inv(T11)*Q1**H*B ]
!>                 [        0         ]
!> where Q1 consists of the first RANK columns of Q.
!> 

M

!>          M is INTEGER
!>          The number of rows of the matrix A.  M >= 0.
!> 

N

!>          N is INTEGER
!>          The number of columns of the matrix A.  N >= 0.
!> 

NRHS

!>          NRHS is INTEGER
!>          The number of right hand sides, i.e., the number of
!>          columns of matrices B and X. NRHS >= 0.
!> 

A

!>          A is COMPLEX*16 array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A has been overwritten by details of its
!>          complete orthogonal factorization.
!> 

LDA

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

B

!>          B is COMPLEX*16 array, dimension (LDB,NRHS)
!>          On entry, the M-by-NRHS right hand side matrix B.
!>          On exit, the N-by-NRHS solution matrix X.
!>          If m >= n and RANK = n, the residual sum-of-squares for
!>          the solution in the i-th column is given by the sum of
!>          squares of elements N+1:M in that column.
!> 

LDB

!>          LDB is INTEGER
!>          The leading dimension of the array B. LDB >= max(1,M,N).
!> 

JPVT

!>          JPVT is INTEGER array, dimension (N)
!>          On entry, if JPVT(i) .ne. 0, the i-th column of A is an
!>          initial column, otherwise it is a free column.  Before
!>          the QR factorization of A, all initial columns are
!>          permuted to the leading positions; only the remaining
!>          free columns are moved as a result of column pivoting
!>          during the factorization.
!>          On exit, if JPVT(i) = k, then the i-th column of A*P
!>          was the k-th column of A.
!> 

RCOND

!>          RCOND is DOUBLE PRECISION
!>          RCOND is used to determine the effective rank of A, which
!>          is defined as the order of the largest leading triangular
!>          submatrix R11 in the QR factorization with pivoting of A,
!>          whose estimated condition number < 1/RCOND.
!> 

RANK

!>          RANK is INTEGER
!>          The effective rank of A, i.e., the order of the submatrix
!>          R11.  This is the same as the order of the submatrix T11
!>          in the complete orthogonal factorization of A.
!> 

WORK

!>          WORK is COMPLEX*16 array, dimension
!>                      (min(M,N) + max( N, 2*min(M,N)+NRHS )),
!> 

RWORK

!>          RWORK is DOUBLE PRECISION array, dimension (2*N)
!> 

INFO

!>          INFO is INTEGER
!>          = 0:  successful exit
!>          < 0:  if INFO = -i, the i-th argument had an illegal value
!> 

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