          SUBROUTINE DLASD2( NL, NR, SQRE, K, D, Z, ALPHA, BETA, U, LDU, VT,
         $                   LDVT, DSIGMA, U2, LDU2, VT2, LDVT2, IDXP, IDX,
         $                   IDXC, IDXQ, COLTYP, INFO )
    *
    *  -- LAPACK auxiliary routine (version 3.1) --
    *     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
    *     November 2006
    *
    *     .. Scalar Arguments ..
          INTEGER            INFO, K, LDU, LDU2, LDVT, LDVT2, NL, NR, SQRE
          DOUBLE PRECISION   ALPHA, BETA
    *     ..
    *     .. Array Arguments ..
          INTEGER            COLTYP( * ), IDX( * ), IDXC( * ), IDXP( * ),
         $                   IDXQ( * )
          DOUBLE PRECISION   D( * ), DSIGMA( * ), U( LDU, * ),
         $                   U2( LDU2, * ), VT( LDVT, * ), VT2( LDVT2, * ),
         $                   Z( * )
    *     ..
    *
    *  Purpose
    *  =======
    *
    *  DLASD2 merges the two sets of singular values together into a single
    *  sorted set.  Then it tries to deflate the size of the problem.
    *  There are two ways in which deflation can occur:  when two or more
    *  singular values are close together or if there is a tiny entry in the
    *  Z vector.  For each such occurrence the order of the related secular
    *  equation problem is reduced by one.
    *
    *  DLASD2 is called from DLASD1.
    *
    *  Arguments
    *  =========
    *
    *  NL     (input) INTEGER
    *         The row dimension of the upper block.  NL >= 1.
    *
    *  NR     (input) INTEGER
    *         The row dimension of the lower block.  NR >= 1.
    *
    *  SQRE   (input) INTEGER
    *         = 0: the lower block is an NR-by-NR square matrix.
    *         = 1: the lower block is an NR-by-(NR+1) rectangular matrix.
    *
    *         The bidiagonal matrix has N = NL + NR + 1 rows and
    *         M = N + SQRE >= N columns.
    *
    *  K      (output) INTEGER
    *         Contains the dimension of the non-deflated matrix,
    *         This is the order of the related secular equation. 1 <= K <=N.
    *
    *  D      (input/output) DOUBLE PRECISION array, dimension(N)
    *         On entry D contains the singular values of the two submatrices
    *         to be combined.  On exit D contains the trailing (N-K) updated
    *         singular values (those which were deflated) sorted into
    *         increasing order.
    *
    *  Z      (output) DOUBLE PRECISION array, dimension(N)
    *         On exit Z contains the updating row vector in the secular
    *         equation.
    *
    *  ALPHA  (input) DOUBLE PRECISION
    *         Contains the diagonal element associated with the added row.
    *
    *  BETA   (input) DOUBLE PRECISION
    *         Contains the off-diagonal element associated with the added
    *         row.
    *
    *  U      (input/output) DOUBLE PRECISION array, dimension(LDU,N)
    *         On entry U contains the left singular vectors of two
    *         submatrices in the two square blocks with corners at (1,1),
    *         (NL, NL), and (NL+2, NL+2), (N,N).
    *         On exit U contains the trailing (N-K) updated left singular
    *         vectors (those which were deflated) in its last N-K columns.
    *
    *  LDU    (input) INTEGER
    *         The leading dimension of the array U.  LDU >= N.
    *
    *  VT     (input/output) DOUBLE PRECISION array, dimension(LDVT,M)
    *         On entry VT' contains the right singular vectors of two
    *         submatrices in the two square blocks with corners at (1,1),
    *         (NL+1, NL+1), and (NL+2, NL+2), (M,M).
    *         On exit VT' contains the trailing (N-K) updated right singular
    *         vectors (those which were deflated) in its last N-K columns.
    *         In case SQRE =1, the last row of VT spans the right null
    *         space.
    *
    *  LDVT   (input) INTEGER
    *         The leading dimension of the array VT.  LDVT >= M.
    *
    *  DSIGMA (output) DOUBLE PRECISION array, dimension (N)
    *         Contains a copy of the diagonal elements (K-1 singular values
    *         and one zero) in the secular equation.
    *
    *  U2     (output) DOUBLE PRECISION array, dimension(LDU2,N)
    *         Contains a copy of the first K-1 left singular vectors which
    *         will be used by DLASD3 in a matrix multiply (DGEMM) to solve
    *         for the new left singular vectors. U2 is arranged into four
    *         blocks. The first block contains a column with 1 at NL+1 and
    *         zero everywhere else; the second block contains non-zero
    *         entries only at and above NL; the third contains non-zero
    *         entries only below NL+1; and the fourth is dense.
    *
    *  LDU2   (input) INTEGER
    *         The leading dimension of the array U2.  LDU2 >= N.
    *
    *  VT2    (output) DOUBLE PRECISION array, dimension(LDVT2,N)
    *         VT2' contains a copy of the first K right singular vectors
    *         which will be used by DLASD3 in a matrix multiply (DGEMM) to
    *         solve for the new right singular vectors. VT2 is arranged into
    *         three blocks. The first block contains a row that corresponds
    *         to the special 0 diagonal element in SIGMA; the second block
    *         contains non-zeros only at and before NL +1; the third block
    *         contains non-zeros only at and after  NL +2.
    *
    *  LDVT2  (input) INTEGER
    *         The leading dimension of the array VT2.  LDVT2 >= M.
    *
    *  IDXP   (workspace) INTEGER array dimension(N)
    *         This will contain the permutation used to place deflated
    *         values of D at the end of the array. On output IDXP(2:K)
    *         points to the nondeflated D-values and IDXP(K+1:N)
    *         points to the deflated singular values.
    *
    *  IDX    (workspace) INTEGER array dimension(N)
    *         This will contain the permutation used to sort the contents of
    *         D into ascending order.
    *
    *  IDXC   (output) INTEGER array dimension(N)
    *         This will contain the permutation used to arrange the columns
    *         of the deflated U matrix into three groups:  the first group
    *         contains non-zero entries only at and above NL, the second
    *         contains non-zero entries only below NL+2, and the third is
    *         dense.
    *
    *  IDXQ   (input/output) INTEGER array dimension(N)
    *         This contains the permutation which separately sorts the two
    *         sub-problems in D into ascending order.  Note that entries in
    *         the first hlaf of this permutation must first be moved one
    *         position backward; and entries in the second half
    *         must first have NL+1 added to their values.
    *
    *  COLTYP (workspace/output) INTEGER array dimension(N)
    *         As workspace, this will contain a label which will indicate
    *         which of the following types a column in the U2 matrix or a
    *         row in the VT2 matrix is:
    *         1 : non-zero in the upper half only
    *         2 : non-zero in the lower half only
    *         3 : dense
    *         4 : deflated
    *
    *         On exit, it is an array of dimension 4, with COLTYP(I) being
    *         the dimension of the I-th type columns.
    *
    *  INFO   (output) INTEGER
    *          = 0:  successful exit.
    *          < 0:  if INFO = -i, the i-th argument had an illegal value.
    *
    *  Further Details
    *  ===============
    *
    *  Based on contributions by
    *     Ming Gu and Huan Ren, Computer Science Division, University of
    *     California at Berkeley, USA
    *
    *  =====================================================================
    *
    *     .. Parameters ..
          DOUBLE PRECISION   ZERO, ONE, TWO, EIGHT
          PARAMETER          ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0,
         $                   EIGHT = 8.0D+0 )
    *     ..
    *     .. Local Arrays ..
          INTEGER            CTOT( 4 ), PSM( 4 )
    *     ..
    *     .. Local Scalars ..
          INTEGER            CT, I, IDXI, IDXJ, IDXJP, J, JP, JPREV, K2, M,
         $                   N, NLP1, NLP2
          DOUBLE PRECISION   C, EPS, HLFTOL, S, TAU, TOL, Z1
    *     ..
    *     .. External Functions ..
          DOUBLE PRECISION   DLAMCH, DLAPY2
          EXTERNAL           DLAMCH, DLAPY2
    *     ..
    *     .. External Subroutines ..
          EXTERNAL           DCOPY, DLACPY, DLAMRG, DLASET, DROT, XERBLA
    *     ..
    *     .. Intrinsic Functions ..
          INTRINSIC          ABS, MAX
    *     ..
    *     .. Executable Statements ..
    *
    *     Test the input parameters.
    *
          INFO = 0
    *
          IF( NL.LT.1 ) THEN
             INFO = -1
          ELSE IF( NR.LT.1 ) THEN
             INFO = -2
          ELSE IF( ( SQRE.NE.1 ) .AND. ( SQRE.NE.0 ) ) THEN
             INFO = -3
          END IF
    *
          N = NL + NR + 1
          M = N + SQRE
    *
          IF( LDU.LT.N ) THEN
             INFO = -10
          ELSE IF( LDVT.LT.M ) THEN
             INFO = -12
          ELSE IF( LDU2.LT.N ) THEN
             INFO = -15
          ELSE IF( LDVT2.LT.M ) THEN
             INFO = -17
          END IF
          IF( INFO.NE.0 ) THEN
             CALL XERBLA( 'DLASD2', -INFO )
             RETURN
          END IF
    *
          NLP1 = NL + 1
          NLP2 = NL + 2
    *
    *     Generate the first part of the vector Z; and move the singular
    *     values in the first part of D one position backward.
    *
          Z1 = ALPHA*VT( NLP1, NLP1 )
          Z( 1 ) = Z1
          DO 10 I = NL, 1, -1
             Z( I+1 ) = ALPHA*VT( I, NLP1 )
             D( I+1 ) = D( I )
             IDXQ( I+1 ) = IDXQ( I ) + 1
       10 CONTINUE
    *
    *     Generate the second part of the vector Z.
    *
          DO 20 I = NLP2, M
             Z( I ) = BETA*VT( I, NLP2 )
       20 CONTINUE
    *
    *     Initialize some reference arrays.
    *
          DO 30 I = 2, NLP1
             COLTYP( I ) = 1
       30 CONTINUE
          DO 40 I = NLP2, N
             COLTYP( I ) = 2
       40 CONTINUE
    *
    *     Sort the singular values into increasing order
    *
          DO 50 I = NLP2, N
             IDXQ( I ) = IDXQ( I ) + NLP1
       50 CONTINUE
    *
    *     DSIGMA, IDXC, IDXC, and the first column of U2
    *     are used as storage space.
    *
          DO 60 I = 2, N
             DSIGMA( I ) = D( IDXQ( I ) )
             U2( I, 1 ) = Z( IDXQ( I ) )
             IDXC( I ) = COLTYP( IDXQ( I ) )
       60 CONTINUE
    *
          CALL DLAMRG( NL, NR, DSIGMA( 2 ), 1, 1, IDX( 2 ) )
    *
          DO 70 I = 2, N
             IDXI = 1 + IDX( I )
             D( I ) = DSIGMA( IDXI )
             Z( I ) = U2( IDXI, 1 )
             COLTYP( I ) = IDXC( IDXI )
       70 CONTINUE
    *
    *     Calculate the allowable deflation tolerance
    *
          EPS = DLAMCH( 'Epsilon' )
          TOL = MAX( ABS( ALPHA ), ABS( BETA ) )
          TOL = EIGHT*EPS*MAX( ABS( D( N ) ), TOL )
    *
    *     There are 2 kinds of deflation -- first a value in the z-vector
    *     is small, second two (or more) singular values are very close
    *     together (their difference is small).
    *
    *     If the value in the z-vector is small, we simply permute the
    *     array so that the corresponding singular value is moved to the
    *     end.
    *
    *     If two values in the D-vector are close, we perform a two-sided
    *     rotation designed to make one of the corresponding z-vector
    *     entries zero, and then permute the array so that the deflated
    *     singular value is moved to the end.
    *
    *     If there are multiple singular values then the problem deflates.
    *     Here the number of equal singular values are found.  As each equal
    *     singular value is found, an elementary reflector is computed to
    *     rotate the corresponding singular subspace so that the
    *     corresponding components of Z are zero in this new basis.
    *
          K = 1
          K2 = N + 1
          DO 80 J = 2, N
             IF( ABS( Z( J ) ).LE.TOL ) THEN
    *
    *           Deflate due to small z component.
    *
                K2 = K2 - 1
                IDXP( K2 ) = J
                COLTYP( J ) = 4
                IF( J.EQ.N )
         $         GO TO 120
             ELSE
                JPREV = J
                GO TO 90
             END IF
       80 CONTINUE
       90 CONTINUE
          J = JPREV
      100 CONTINUE
          J = J + 1
          IF( J.GT.N )
         $   GO TO 110
          IF( ABS( Z( J ) ).LE.TOL ) THEN
    *
    *        Deflate due to small z component.
    *
             K2 = K2 - 1
             IDXP( K2 ) = J
             COLTYP( J ) = 4
          ELSE
    *
    *        Check if singular values are close enough to allow deflation.
    *
             IF( ABS( D( J )-D( JPREV ) ).LE.TOL ) THEN
    *
    *           Deflation is possible.
    *
                S = Z( JPREV )
                C = Z( J )
    *
    *           Find sqrt(a**2+b**2) without overflow or
    *           destructive underflow.
    *
                TAU = DLAPY2( C, S )
                C = C / TAU
                S = -S / TAU
                Z( J ) = TAU
                Z( JPREV ) = ZERO
    *
    *           Apply back the Givens rotation to the left and right
    *           singular vector matrices.
    *
                IDXJP = IDXQ( IDX( JPREV )+1 )
                IDXJ = IDXQ( IDX( J )+1 )
                IF( IDXJP.LE.NLP1 ) THEN
                   IDXJP = IDXJP - 1
                END IF
                IF( IDXJ.LE.NLP1 ) THEN
                   IDXJ = IDXJ - 1
                END IF
                CALL DROT( N, U( 1, IDXJP ), 1, U( 1, IDXJ ), 1, C, S )
                CALL DROT( M, VT( IDXJP, 1 ), LDVT, VT( IDXJ, 1 ), LDVT, C,
         $                 S )
                IF( COLTYP( J ).NE.COLTYP( JPREV ) ) THEN
                   COLTYP( J ) = 3
                END IF
                COLTYP( JPREV ) = 4
                K2 = K2 - 1
                IDXP( K2 ) = JPREV
                JPREV = J
             ELSE
                K = K + 1
                U2( K, 1 ) = Z( JPREV )
                DSIGMA( K ) = D( JPREV )
                IDXP( K ) = JPREV
                JPREV = J
             END IF
          END IF
          GO TO 100
      110 CONTINUE
    *
    *     Record the last singular value.
    *
          K = K + 1
          U2( K, 1 ) = Z( JPREV )
          DSIGMA( K ) = D( JPREV )
          IDXP( K ) = JPREV
    *
      120 CONTINUE
    *
    *     Count up the total number of the various types of columns, then
    *     form a permutation which positions the four column types into
    *     four groups of uniform structure (although one or more of these
    *     groups may be empty).
    *
          DO 130 J = 1, 4
             CTOT( J ) = 0
      130 CONTINUE
          DO 140 J = 2, N
             CT = COLTYP( J )
             CTOT( CT ) = CTOT( CT ) + 1
      140 CONTINUE
    *
    *     PSM(*) = Position in SubMatrix (of types 1 through 4)
    *
          PSM( 1 ) = 2
          PSM( 2 ) = 2 + CTOT( 1 )
          PSM( 3 ) = PSM( 2 ) + CTOT( 2 )
          PSM( 4 ) = PSM( 3 ) + CTOT( 3 )
    *
    *     Fill out the IDXC array so that the permutation which it induces
    *     will place all type-1 columns first, all type-2 columns next,
    *     then all type-3's, and finally all type-4's, starting from the
    *     second column. This applies similarly to the rows of VT.
    *
          DO 150 J = 2, N
             JP = IDXP( J )
             CT = COLTYP( JP )
             IDXC( PSM( CT ) ) = J
             PSM( CT ) = PSM( CT ) + 1
      150 CONTINUE
    *
    *     Sort the singular values and corresponding singular vectors into
    *     DSIGMA, U2, and VT2 respectively.  The singular values/vectors
    *     which were not deflated go into the first K slots of DSIGMA, U2,
    *     and VT2 respectively, while those which were deflated go into the
    *     last N - K slots, except that the first column/row will be treated
    *     separately.
    *
          DO 160 J = 2, N
             JP = IDXP( J )
             DSIGMA( J ) = D( JP )
             IDXJ = IDXQ( IDX( IDXP( IDXC( J ) ) )+1 )
             IF( IDXJ.LE.NLP1 ) THEN
                IDXJ = IDXJ - 1
             END IF
             CALL DCOPY( N, U( 1, IDXJ ), 1, U2( 1, J ), 1 )
             CALL DCOPY( M, VT( IDXJ, 1 ), LDVT, VT2( J, 1 ), LDVT2 )
      160 CONTINUE
    *
    *     Determine DSIGMA(1), DSIGMA(2) and Z(1)
    *
          DSIGMA( 1 ) = ZERO
          HLFTOL = TOL / TWO
          IF( ABS( DSIGMA( 2 ) ).LE.HLFTOL )
         $   DSIGMA( 2 ) = HLFTOL
          IF( M.GT.N ) THEN
             Z( 1 ) = DLAPY2( Z1, Z( M ) )
             IF( Z( 1 ).LE.TOL ) THEN
                C = ONE
                S = ZERO
                Z( 1 ) = TOL
             ELSE
                C = Z1 / Z( 1 )
                S = Z( M ) / Z( 1 )
             END IF
          ELSE
             IF( ABS( Z1 ).LE.TOL ) THEN
                Z( 1 ) = TOL
             ELSE
                Z( 1 ) = Z1
             END IF
          END IF
    *
    *     Move the rest of the updating row to Z.
    *
          CALL DCOPY( K-1, U2( 2, 1 ), 1, Z( 2 ), 1 )
    *
    *     Determine the first column of U2, the first row of VT2 and the
    *     last row of VT.
    *
          CALL DLASET( 'A', N, 1, ZERO, ZERO, U2, LDU2 )
          U2( NLP1, 1 ) = ONE
          IF( M.GT.N ) THEN
             DO 170 I = 1, NLP1
                VT( M, I ) = -S*VT( NLP1, I )
                VT2( 1, I ) = C*VT( NLP1, I )
      170    CONTINUE
             DO 180 I = NLP2, M
                VT2( 1, I ) = S*VT( M, I )
                VT( M, I ) = C*VT( M, I )
      180    CONTINUE
          ELSE
             CALL DCOPY( M, VT( NLP1, 1 ), LDVT, VT2( 1, 1 ), LDVT2 )
          END IF
          IF( M.GT.N ) THEN
             CALL DCOPY( M, VT( M, 1 ), LDVT, VT2( M, 1 ), LDVT2 )
          END IF
    *
    *     The deflated singular values and their corresponding vectors go
    *     into the back of D, U, and V respectively.
    *
          IF( N.GT.K ) THEN
             CALL DCOPY( N-K, DSIGMA( K+1 ), 1, D( K+1 ), 1 )
             CALL DLACPY( 'A', N, N-K, U2( 1, K+1 ), LDU2, U( 1, K+1 ),
         $                LDU )
             CALL DLACPY( 'A', N-K, M, VT2( K+1, 1 ), LDVT2, VT( K+1, 1 ),
         $                LDVT )
          END IF
    *
    *     Copy CTOT into COLTYP for referencing in DLASD3.
    *
          DO 190 J = 1, 4
             COLTYP( J ) = CTOT( J )
      190 CONTINUE
    *
          RETURN
    *
    *     End of DLASD2
    *
          END