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*> \brief \b SLAHQR computes the eigenvalues and Schur factorization of an upper Hessenberg matrix, using the double-shift/single-shift QR algorithm.
*
*  =========== DOCUMENTATION ===========
*
* Online html documentation available at
*            http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download SLAHQR + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/slahqr.f">
*> [TGZ]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/slahqr.f">
*> [ZIP]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/slahqr.f">
*> [TXT]</a>
*> \endhtmlonly
*
*  Definition:
*  ===========
*
*       SUBROUTINE SLAHQR( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI,
*                          ILOZ, IHIZ, Z, LDZ, INFO )
*
*       .. Scalar Arguments ..
*       INTEGER            IHI, IHIZ, ILO, ILOZ, INFO, LDH, LDZ, N
*       LOGICAL            WANTT, WANTZ
*       ..
*       .. Array Arguments ..
*       REAL               H( LDH, * ), WI( * ), WR( * ), Z( LDZ, * )
*       ..
*
*
*> \par Purpose:
*  =============
*>
*> \verbatim
*>
*>    SLAHQR is an auxiliary routine called by SHSEQR to update the
*>    eigenvalues and Schur decomposition already computed by SHSEQR, by
*>    dealing with the Hessenberg submatrix in rows and columns ILO to
*>    IHI.
*> \endverbatim
*
*  Arguments:
*  ==========
*
*> \param[in] WANTT
*> \verbatim
*>          WANTT is LOGICAL
*>          = .TRUE. : the full Schur form T is required;
*>          = .FALSE.: only eigenvalues are required.
*> \endverbatim
*>
*> \param[in] WANTZ
*> \verbatim
*>          WANTZ is LOGICAL
*>          = .TRUE. : the matrix of Schur vectors Z is required;
*>          = .FALSE.: Schur vectors are not required.
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*>          N is INTEGER
*>          The order of the matrix H.  N >= 0.
*> \endverbatim
*>
*> \param[in] ILO
*> \verbatim
*>          ILO is INTEGER
*> \endverbatim
*>
*> \param[in] IHI
*> \verbatim
*>          IHI is INTEGER
*>          It is assumed that H is already upper quasi-triangular in
*>          rows and columns IHI+1:N, and that H(ILO,ILO-1) = 0 (unless
*>          ILO = 1). SLAHQR works primarily with the Hessenberg
*>          submatrix in rows and columns ILO to IHI, but applies
*>          transformations to all of H if WANTT is .TRUE..
*>          1 <= ILO <= max(1,IHI); IHI <= N.
*> \endverbatim
*>
*> \param[in,out] H
*> \verbatim
*>          H is REAL array, dimension (LDH,N)
*>          On entry, the upper Hessenberg matrix H.
*>          On exit, if INFO is zero and if WANTT is .TRUE., H is upper
*>          quasi-triangular in rows and columns ILO:IHI, with any
*>          2-by-2 diagonal blocks in standard form. If INFO is zero
*>          and WANTT is .FALSE., the contents of H are unspecified on
*>          exit.  The output state of H if INFO is nonzero is given
*>          below under the description of INFO.
*> \endverbatim
*>
*> \param[in] LDH
*> \verbatim
*>          LDH is INTEGER
*>          The leading dimension of the array H. LDH >= max(1,N).
*> \endverbatim
*>
*> \param[out] WR
*> \verbatim
*>          WR is REAL array, dimension (N)
*> \endverbatim
*>
*> \param[out] WI
*> \verbatim
*>          WI is REAL array, dimension (N)
*>          The real and imaginary parts, respectively, of the computed
*>          eigenvalues ILO to IHI are stored in the corresponding
*>          elements of WR and WI. If two eigenvalues are computed as a
*>          complex conjugate pair, they are stored in consecutive
*>          elements of WR and WI, say the i-th and (i+1)th, with
*>          WI(i) > 0 and WI(i+1) < 0. If WANTT is .TRUE., the
*>          eigenvalues are stored in the same order as on the diagonal
*>          of the Schur form returned in H, with WR(i) = H(i,i), and, if
*>          H(i:i+1,i:i+1) is a 2-by-2 diagonal block,
*>          WI(i) = sqrt(H(i+1,i)*H(i,i+1)) and WI(i+1) = -WI(i).
*> \endverbatim
*>
*> \param[in] ILOZ
*> \verbatim
*>          ILOZ is INTEGER
*> \endverbatim
*>
*> \param[in] IHIZ
*> \verbatim
*>          IHIZ is INTEGER
*>          Specify the rows of Z to which transformations must be
*>          applied if WANTZ is .TRUE..
*>          1 <= ILOZ <= ILO; IHI <= IHIZ <= N.
*> \endverbatim
*>
*> \param[in,out] Z
*> \verbatim
*>          Z is REAL array, dimension (LDZ,N)
*>          If WANTZ is .TRUE., on entry Z must contain the current
*>          matrix Z of transformations accumulated by SHSEQR, and on
*>          exit Z has been updated; transformations are applied only to
*>          the submatrix Z(ILOZ:IHIZ,ILO:IHI).
*>          If WANTZ is .FALSE., Z is not referenced.
*> \endverbatim
*>
*> \param[in] LDZ
*> \verbatim
*>          LDZ is INTEGER
*>          The leading dimension of the array Z. LDZ >= max(1,N).
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*>          INFO is INTEGER
*>           =   0: successful exit
*>          .GT. 0: If INFO = i, SLAHQR failed to compute all the
*>                  eigenvalues ILO to IHI in a total of 30 iterations
*>                  per eigenvalue; elements i+1:ihi of WR and WI
*>                  contain those eigenvalues which have been
*>                  successfully computed.
*>
*>                  If INFO .GT. 0 and WANTT is .FALSE., then on exit,
*>                  the remaining unconverged eigenvalues are the
*>                  eigenvalues of the upper Hessenberg matrix rows
*>                  and columns ILO thorugh INFO of the final, output
*>                  value of H.
*>
*>                  If INFO .GT. 0 and WANTT is .TRUE., then on exit
*>          (*)       (initial value of H)*U  = U*(final value of H)
*>                  where U is an orthognal matrix.    The final
*>                  value of H is upper Hessenberg and triangular in
*>                  rows and columns INFO+1 through IHI.
*>
*>                  If INFO .GT. 0 and WANTZ is .TRUE., then on exit
*>                      (final value of Z)  = (initial value of Z)*U
*>                  where U is the orthogonal matrix in (*)
*>                  (regardless of the value of WANTT.)
*> \endverbatim
*
*  Authors:
*  ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date December 2016
*
*> \ingroup realOTHERauxiliary
*
*> \par Further Details:
*  =====================
*>
*> \verbatim
*>
*>     02-96 Based on modifications by
*>     David Day, Sandia National Laboratory, USA
*>
*>     12-04 Further modifications by
*>     Ralph Byers, University of Kansas, USA
*>     This is a modified version of SLAHQR from LAPACK version 3.0.
*>     It is (1) more robust against overflow and underflow and
*>     (2) adopts the more conservative Ahues & Tisseur stopping
*>     criterion (LAWN 122, 1997).
*> \endverbatim
*>
*  =====================================================================
      SUBROUTINE SLAHQR( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI,
     $                   ILOZ, IHIZ, Z, LDZ, INFO )
*
*  -- LAPACK auxiliary routine (version 3.7.0) --
*  -- LAPACK is a software package provided by Univ. of Tennessee,    --
*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
*     December 2016
*
*     .. Scalar Arguments ..
      INTEGER            IHI, IHIZ, ILO, ILOZ, INFO, LDH, LDZ, N
      LOGICAL            WANTT, WANTZ
*     ..
*     .. Array Arguments ..
      REAL               H( LDH, * ), WI( * ), WR( * ), Z( LDZ, * )
*     ..
*
*  =========================================================
*
*     .. Parameters ..
      REAL               ZERO, ONE, TWO
      PARAMETER          ( ZERO = 0.0e0, ONE = 1.0e0, TWO = 2.0e0 )
      REAL               DAT1, DAT2
      PARAMETER          ( DAT1 = 3.0e0 / 4.0e0, DAT2 = -0.4375e0 )
*     ..
*     .. Local Scalars ..
      REAL               AA, AB, BA, BB, CS, DET, H11, H12, H21, H21S,
     $                   H22, RT1I, RT1R, RT2I, RT2R, RTDISC, S, SAFMAX,
     $                   SAFMIN, SMLNUM, SN, SUM, T1, T2, T3, TR, TST,
     $                   ULP, V2, V3
      INTEGER            I, I1, I2, ITS, ITMAX, J, K, L, M, NH, NR, NZ
*     ..
*     .. Local Arrays ..
      REAL               V( 3 )
*     ..
*     .. External Functions ..
      REAL               SLAMCH
      EXTERNAL           SLAMCH
*     ..
*     .. External Subroutines ..
      EXTERNAL           SCOPY, SLABAD, SLANV2, SLARFG, SROT
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          ABS, MAX, MIN, REAL, SQRT
*     ..
*     .. Executable Statements ..
*
      INFO = 0
*
*     Quick return if possible
*
      IF( N.EQ.0 )
     $   RETURN
      IF( ILO.EQ.IHI ) THEN
         WR( ILO ) = H( ILO, ILO )
         WI( ILO ) = ZERO
         RETURN
      END IF
*
*     ==== clear out the trash ====
      DO 10 J = ILO, IHI - 3
         H( J+2, J ) = ZERO
         H( J+3, J ) = ZERO
   10 CONTINUE
      IF( ILO.LE.IHI-2 )
     $   H( IHI, IHI-2 ) = ZERO
*
      NH = IHI - ILO + 1
      NZ = IHIZ - ILOZ + 1
*
*     Set machine-dependent constants for the stopping criterion.
*
      SAFMIN = SLAMCH( 'SAFE MINIMUM' )
      SAFMAX = ONE / SAFMIN
      CALL SLABAD( SAFMIN, SAFMAX )
      ULP = SLAMCH( 'PRECISION' )
      SMLNUM = SAFMIN*( REAL( NH ) / ULP )
*
*     I1 and I2 are the indices of the first row and last column of H
*     to which transformations must be applied. If eigenvalues only are
*     being computed, I1 and I2 are set inside the main loop.
*
      IF( WANTT ) THEN
         I1 = 1
         I2 = N
      END IF
*
*     ITMAX is the total number of QR iterations allowed.
*
      ITMAX = 30 * MAX( 10, NH )
*
*     The main loop begins here. I is the loop index and decreases from
*     IHI to ILO in steps of 1 or 2. Each iteration of the loop works
*     with the active submatrix in rows and columns L to I.
*     Eigenvalues I+1 to IHI have already converged. Either L = ILO or
*     H(L,L-1) is negligible so that the matrix splits.
*
      I = IHI
   20 CONTINUE
      L = ILO
      IF( I.LT.ILO )
     $   GO TO 160
*
*     Perform QR iterations on rows and columns ILO to I until a
*     submatrix of order 1 or 2 splits off at the bottom because a
*     subdiagonal element has become negligible.
*
      DO 140 ITS = 0, ITMAX
*
*        Look for a single small subdiagonal element.
*
         DO 30 K = I, L + 1, -1
            IF( ABS( H( K, K-1 ) ).LE.SMLNUM )
     $         GO TO 40
            TST = ABS( H( K-1, K-1 ) ) + ABS( H( K, K ) )
            IF( TST.EQ.ZERO ) THEN
               IF( K-2.GE.ILO )
     $            TST = TST + ABS( H( K-1, K-2 ) )
               IF( K+1.LE.IHI )
     $            TST = TST + ABS( H( K+1, K ) )
            END IF
*           ==== The following is a conservative small subdiagonal
*           .    deflation  criterion due to Ahues & Tisseur (LAWN 122,
*           .    1997). It has better mathematical foundation and
*           .    improves accuracy in some cases.  ====
            IF( ABS( H( K, K-1 ) ).LE.ULP*TST ) THEN
               AB = MAX( ABS( H( K, K-1 ) ), ABS( H( K-1, K ) ) )
               BA = MIN( ABS( H( K, K-1 ) ), ABS( H( K-1, K ) ) )
               AA = MAX( ABS( H( K, K ) ),
     $              ABS( H( K-1, K-1 )-H( K, K ) ) )
               BB = MIN( ABS( H( K, K ) ),
     $              ABS( H( K-1, K-1 )-H( K, K ) ) )
               S = AA + AB
               IF( BA*( AB / S ).LE.MAX( SMLNUM,
     $             ULP*( BB*( AA / S ) ) ) )GO TO 40
            END IF
   30    CONTINUE
   40    CONTINUE
         L = K
         IF( L.GT.ILO ) THEN
*
*           H(L,L-1) is negligible
*
            H( L, L-1 ) = ZERO
         END IF
*
*        Exit from loop if a submatrix of order 1 or 2 has split off.
*
         IF( L.GE.I-1 )
     $      GO TO 150
*
*        Now the active submatrix is in rows and columns L to I. If
*        eigenvalues only are being computed, only the active submatrix
*        need be transformed.
*
         IF( .NOT.WANTT ) THEN
            I1 = L
            I2 = I
         END IF
*
         IF( ITS.EQ.10 ) THEN
*
*           Exceptional shift.
*
            S = ABS( H( L+1, L ) ) + ABS( H( L+2, L+1 ) )
            H11 = DAT1*S + H( L, L )
            H12 = DAT2*S
            H21 = S
            H22 = H11
         ELSE IF( ITS.EQ.20 ) THEN
*
*           Exceptional shift.
*
            S = ABS( H( I, I-1 ) ) + ABS( H( I-1, I-2 ) )
            H11 = DAT1*S + H( I, I )
            H12 = DAT2*S
            H21 = S
            H22 = H11
         ELSE
*
*           Prepare to use Francis' double shift
*           (i.e. 2nd degree generalized Rayleigh quotient)
*
            H11 = H( I-1, I-1 )
            H21 = H( I, I-1 )
            H12 = H( I-1, I )
            H22 = H( I, I )
         END IF
         S = ABS( H11 ) + ABS( H12 ) + ABS( H21 ) + ABS( H22 )
         IF( S.EQ.ZERO ) THEN
            RT1R = ZERO
            RT1I = ZERO
            RT2R = ZERO
            RT2I = ZERO
         ELSE
            H11 = H11 / S
            H21 = H21 / S
            H12 = H12 / S
            H22 = H22 / S
            TR = ( H11+H22 ) / TWO
            DET = ( H11-TR )*( H22-TR ) - H12*H21
            RTDISC = SQRT( ABS( DET ) )
            IF( DET.GE.ZERO ) THEN
*
*              ==== complex conjugate shifts ====
*
               RT1R = TR*S
               RT2R = RT1R
               RT1I = RTDISC*S
               RT2I = -RT1I
            ELSE
*
*              ==== real shifts (use only one of them)  ====
*
               RT1R = TR + RTDISC
               RT2R = TR - RTDISC
               IF( ABS( RT1R-H22 ).LE.ABS( RT2R-H22 ) ) THEN
                  RT1R = RT1R*S
                  RT2R = RT1R
               ELSE
                  RT2R = RT2R*S
                  RT1R = RT2R
               END IF
               RT1I = ZERO
               RT2I = ZERO
            END IF
         END IF
*
*        Look for two consecutive small subdiagonal elements.
*
         DO 50 M = I - 2, L, -1
*           Determine the effect of starting the double-shift QR
*           iteration at row M, and see if this would make H(M,M-1)
*           negligible.  (The following uses scaling to avoid
*           overflows and most underflows.)
*
            H21S = H( M+1, M )
            S = ABS( H( M, M )-RT2R ) + ABS( RT2I ) + ABS( H21S )
            H21S = H( M+1, M ) / S
            V( 1 ) = H21S*H( M, M+1 ) + ( H( M, M )-RT1R )*
     $               ( ( H( M, M )-RT2R ) / S ) - RT1I*( RT2I / S )
            V( 2 ) = H21S*( H( M, M )+H( M+1, M+1 )-RT1R-RT2R )
            V( 3 ) = H21S*H( M+2, M+1 )
            S = ABS( V( 1 ) ) + ABS( V( 2 ) ) + ABS( V( 3 ) )
            V( 1 ) = V( 1 ) / S
            V( 2 ) = V( 2 ) / S
            V( 3 ) = V( 3 ) / S
            IF( M.EQ.L )
     $         GO TO 60
            IF( ABS( H( M, M-1 ) )*( ABS( V( 2 ) )+ABS( V( 3 ) ) ).LE.
     $          ULP*ABS( V( 1 ) )*( ABS( H( M-1, M-1 ) )+ABS( H( M,
     $          M ) )+ABS( H( M+1, M+1 ) ) ) )GO TO 60
   50    CONTINUE
   60    CONTINUE
*
*        Double-shift QR step
*
         DO 130 K = M, I - 1
*
*           The first iteration of this loop determines a reflection G
*           from the vector V and applies it from left and right to H,
*           thus creating a nonzero bulge below the subdiagonal.
*
*           Each subsequent iteration determines a reflection G to
*           restore the Hessenberg form in the (K-1)th column, and thus
*           chases the bulge one step toward the bottom of the active
*           submatrix. NR is the order of G.
*
            NR = MIN( 3, I-K+1 )
            IF( K.GT.M )
     $         CALL SCOPY( NR, H( K, K-1 ), 1, V, 1 )
            CALL SLARFG( NR, V( 1 ), V( 2 ), 1, T1 )
            IF( K.GT.M ) THEN
               H( K, K-1 ) = V( 1 )
               H( K+1, K-1 ) = ZERO
               IF( K.LT.I-1 )
     $            H( K+2, K-1 ) = ZERO
            ELSE IF( M.GT.L ) THEN
*               ==== Use the following instead of
*               .    H( K, K-1 ) = -H( K, K-1 ) to
*               .    avoid a bug when v(2) and v(3)
*               .    underflow. ====
               H( K, K-1 ) = H( K, K-1 )*( ONE-T1 )
            END IF
            V2 = V( 2 )
            T2 = T1*V2
            IF( NR.EQ.3 ) THEN
               V3 = V( 3 )
               T3 = T1*V3
*
*              Apply G from the left to transform the rows of the matrix
*              in columns K to I2.
*
               DO 70 J = K, I2
                  SUM = H( K, J ) + V2*H( K+1, J ) + V3*H( K+2, J )
                  H( K, J ) = H( K, J ) - SUM*T1
                  H( K+1, J ) = H( K+1, J ) - SUM*T2
                  H( K+2, J ) = H( K+2, J ) - SUM*T3
   70          CONTINUE
*
*              Apply G from the right to transform the columns of the
*              matrix in rows I1 to min(K+3,I).
*
               DO 80 J = I1, MIN( K+3, I )
                  SUM = H( J, K ) + V2*H( J, K+1 ) + V3*H( J, K+2 )
                  H( J, K ) = H( J, K ) - SUM*T1
                  H( J, K+1 ) = H( J, K+1 ) - SUM*T2
                  H( J, K+2 ) = H( J, K+2 ) - SUM*T3
   80          CONTINUE
*
               IF( WANTZ ) THEN
*
*                 Accumulate transformations in the matrix Z
*
                  DO 90 J = ILOZ, IHIZ
                     SUM = Z( J, K ) + V2*Z( J, K+1 ) + V3*Z( J, K+2 )
                     Z( J, K ) = Z( J, K ) - SUM*T1
                     Z( J, K+1 ) = Z( J, K+1 ) - SUM*T2
                     Z( J, K+2 ) = Z( J, K+2 ) - SUM*T3
   90             CONTINUE
               END IF
            ELSE IF( NR.EQ.2 ) THEN
*
*              Apply G from the left to transform the rows of the matrix
*              in columns K to I2.
*
               DO 100 J = K, I2
                  SUM = H( K, J ) + V2*H( K+1, J )
                  H( K, J ) = H( K, J ) - SUM*T1
                  H( K+1, J ) = H( K+1, J ) - SUM*T2
  100          CONTINUE
*
*              Apply G from the right to transform the columns of the
*              matrix in rows I1 to min(K+3,I).
*
               DO 110 J = I1, I
                  SUM = H( J, K ) + V2*H( J, K+1 )
                  H( J, K ) = H( J, K ) - SUM*T1
                  H( J, K+1 ) = H( J, K+1 ) - SUM*T2
  110          CONTINUE
*
               IF( WANTZ ) THEN
*
*                 Accumulate transformations in the matrix Z
*
                  DO 120 J = ILOZ, IHIZ
                     SUM = Z( J, K ) + V2*Z( J, K+1 )
                     Z( J, K ) = Z( J, K ) - SUM*T1
                     Z( J, K+1 ) = Z( J, K+1 ) - SUM*T2
  120             CONTINUE
               END IF
            END IF
  130    CONTINUE
*
  140 CONTINUE
*
*     Failure to converge in remaining number of iterations
*
      INFO = I
      RETURN
*
  150 CONTINUE
*
      IF( L.EQ.I ) THEN
*
*        H(I,I-1) is negligible: one eigenvalue has converged.
*
         WR( I ) = H( I, I )
         WI( I ) = ZERO
      ELSE IF( L.EQ.I-1 ) THEN
*
*        H(I-1,I-2) is negligible: a pair of eigenvalues have converged.
*
*        Transform the 2-by-2 submatrix to standard Schur form,
*        and compute and store the eigenvalues.
*
         CALL SLANV2( H( I-1, I-1 ), H( I-1, I ), H( I, I-1 ),
     $                H( I, I ), WR( I-1 ), WI( I-1 ), WR( I ), WI( I ),
     $                CS, SN )
*
         IF( WANTT ) THEN
*
*           Apply the transformation to the rest of H.
*
            IF( I2.GT.I )
     $         CALL SROT( I2-I, H( I-1, I+1 ), LDH, H( I, I+1 ), LDH,
     $                    CS, SN )
            CALL SROT( I-I1-1, H( I1, I-1 ), 1, H( I1, I ), 1, CS, SN )
         END IF
         IF( WANTZ ) THEN
*
*           Apply the transformation to Z.
*
            CALL SROT( NZ, Z( ILOZ, I-1 ), 1, Z( ILOZ, I ), 1, CS, SN )
         END IF
      END IF
*
*     return to start of the main loop with new value of I.
*
      I = L - 1
      GO TO 20
*
  160 CONTINUE
      RETURN
*
*     End of SLAHQR
*
      END