OSchip
/
OpenBLAS

*> \brief \b SSTERF
*
*  =========== DOCUMENTATION ===========
*
* Online html documentation available at
*            http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
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*> [TXT]</a>
*> \endhtmlonly
*
*  Definition:
*  ===========
*
*       SUBROUTINE SSTERF( N, D, E, INFO )
*
*       .. Scalar Arguments ..
*       INTEGER            INFO, N
*       ..
*       .. Array Arguments ..
*       REAL               D( * ), E( * )
*       ..
*
*
*> \par Purpose:
*  =============
*>
*> \verbatim
*>
*> SSTERF computes all eigenvalues of a symmetric tridiagonal matrix
*> using the Pal-Walker-Kahan variant of the QL or QR algorithm.
*> \endverbatim
*
*  Arguments:
*  ==========
*
*> \param[in] N
*> \verbatim
*>          N is INTEGER
*>          The order of the matrix.  N >= 0.
*> \endverbatim
*>
*> \param[in,out] D
*> \verbatim
*>          D is REAL array, dimension (N)
*>          On entry, the n diagonal elements of the tridiagonal matrix.
*>          On exit, if INFO = 0, the eigenvalues in ascending order.
*> \endverbatim
*>
*> \param[in,out] E
*> \verbatim
*>          E is REAL array, dimension (N-1)
*>          On entry, the (n-1) subdiagonal elements of the tridiagonal
*>          matrix.
*>          On exit, E has been destroyed.
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*>          INFO is INTEGER
*>          = 0:  successful exit
*>          < 0:  if INFO = -i, the i-th argument had an illegal value
*>          > 0:  the algorithm failed to find all of the eigenvalues in
*>                a total of 30*N iterations; if INFO = i, then i
*>                elements of E have not converged to zero.
*> \endverbatim
*
*  Authors:
*  ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date December 2016
*
*> \ingroup auxOTHERcomputational
*
*  =====================================================================
      SUBROUTINE SSTERF( N, D, E, INFO )
*
*  -- LAPACK computational 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            INFO, N
*     ..
*     .. Array Arguments ..
      REAL               D( * ), E( * )
*     ..
*
*  =====================================================================
*
*     .. Parameters ..
      REAL               ZERO, ONE, TWO, THREE
      PARAMETER          ( ZERO = 0.0E0, ONE = 1.0E0, TWO = 2.0E0,
     $                   THREE = 3.0E0 )
      INTEGER            MAXIT
      PARAMETER          ( MAXIT = 30 )
*     ..
*     .. Local Scalars ..
      INTEGER            I, ISCALE, JTOT, L, L1, LEND, LENDSV, LSV, M,
     $                   NMAXIT
      REAL               ALPHA, ANORM, BB, C, EPS, EPS2, GAMMA, OLDC,
     $                   OLDGAM, P, R, RT1, RT2, RTE, S, SAFMAX, SAFMIN,
     $                   SIGMA, SSFMAX, SSFMIN
*     ..
*     .. External Functions ..
      REAL               SLAMCH, SLANST, SLAPY2
      EXTERNAL           SLAMCH, SLANST, SLAPY2
*     ..
*     .. External Subroutines ..
      EXTERNAL           SLAE2, SLASCL, SLASRT, XERBLA
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          ABS, SIGN, SQRT
*     ..
*     .. Executable Statements ..
*
*     Test the input parameters.
*
      INFO = 0
*
*     Quick return if possible
*
      IF( N.LT.0 ) THEN
         INFO = -1
         CALL XERBLA( 'SSTERF', -INFO )
         RETURN
      END IF
      IF( N.LE.1 )
     $   RETURN
*
*     Determine the unit roundoff for this environment.
*
      EPS = SLAMCH( 'E' )
      EPS2 = EPS**2
      SAFMIN = SLAMCH( 'S' )
      SAFMAX = ONE / SAFMIN
      SSFMAX = SQRT( SAFMAX ) / THREE
      SSFMIN = SQRT( SAFMIN ) / EPS2
*
*     Compute the eigenvalues of the tridiagonal matrix.
*
      NMAXIT = N*MAXIT
      SIGMA = ZERO
      JTOT = 0
*
*     Determine where the matrix splits and choose QL or QR iteration
*     for each block, according to whether top or bottom diagonal
*     element is smaller.
*
      L1 = 1
*
   10 CONTINUE
      IF( L1.GT.N )
     $   GO TO 170
      IF( L1.GT.1 )
     $   E( L1-1 ) = ZERO
      DO 20 M = L1, N - 1
         IF( ABS( E( M ) ).LE.( SQRT( ABS( D( M ) ) )*
     $       SQRT( ABS( D( M+1 ) ) ) )*EPS ) THEN
            E( M ) = ZERO
            GO TO 30
         END IF
   20 CONTINUE
      M = N
*
   30 CONTINUE
      L = L1
      LSV = L
      LEND = M
      LENDSV = LEND
      L1 = M + 1
      IF( LEND.EQ.L )
     $   GO TO 10
*
*     Scale submatrix in rows and columns L to LEND
*
      ANORM = SLANST( 'M', LEND-L+1, D( L ), E( L ) )
      ISCALE = 0
      IF( ANORM.EQ.ZERO )
     $   GO TO 10
      IF( ANORM.GT.SSFMAX ) THEN
         ISCALE = 1
         CALL SLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L+1, 1, D( L ), N,
     $                INFO )
         CALL SLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L, 1, E( L ), N,
     $                INFO )
      ELSE IF( ANORM.LT.SSFMIN ) THEN
         ISCALE = 2
         CALL SLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L+1, 1, D( L ), N,
     $                INFO )
         CALL SLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L, 1, E( L ), N,
     $                INFO )
      END IF
*
      DO 40 I = L, LEND - 1
         E( I ) = E( I )**2
   40 CONTINUE
*
*     Choose between QL and QR iteration
*
      IF( ABS( D( LEND ) ).LT.ABS( D( L ) ) ) THEN
         LEND = LSV
         L = LENDSV
      END IF
*
      IF( LEND.GE.L ) THEN
*
*        QL Iteration
*
*        Look for small subdiagonal element.
*
   50    CONTINUE
         IF( L.NE.LEND ) THEN
            DO 60 M = L, LEND - 1
               IF( ABS( E( M ) ).LE.EPS2*ABS( D( M )*D( M+1 ) ) )
     $            GO TO 70
   60       CONTINUE
         END IF
         M = LEND
*
   70    CONTINUE
         IF( M.LT.LEND )
     $      E( M ) = ZERO
         P = D( L )
         IF( M.EQ.L )
     $      GO TO 90
*
*        If remaining matrix is 2 by 2, use SLAE2 to compute its
*        eigenvalues.
*
         IF( M.EQ.L+1 ) THEN
            RTE = SQRT( E( L ) )
            CALL SLAE2( D( L ), RTE, D( L+1 ), RT1, RT2 )
            D( L ) = RT1
            D( L+1 ) = RT2
            E( L ) = ZERO
            L = L + 2
            IF( L.LE.LEND )
     $         GO TO 50
            GO TO 150
         END IF
*
         IF( JTOT.EQ.NMAXIT )
     $      GO TO 150
         JTOT = JTOT + 1
*
*        Form shift.
*
         RTE = SQRT( E( L ) )
         SIGMA = ( D( L+1 )-P ) / ( TWO*RTE )
         R = SLAPY2( SIGMA, ONE )
         SIGMA = P - ( RTE / ( SIGMA+SIGN( R, SIGMA ) ) )
*
         C = ONE
         S = ZERO
         GAMMA = D( M ) - SIGMA
         P = GAMMA*GAMMA
*
*        Inner loop
*
         DO 80 I = M - 1, L, -1
            BB = E( I )
            R = P + BB
            IF( I.NE.M-1 )
     $         E( I+1 ) = S*R
            OLDC = C
            C = P / R
            S = BB / R
            OLDGAM = GAMMA
            ALPHA = D( I )
            GAMMA = C*( ALPHA-SIGMA ) - S*OLDGAM
            D( I+1 ) = OLDGAM + ( ALPHA-GAMMA )
            IF( C.NE.ZERO ) THEN
               P = ( GAMMA*GAMMA ) / C
            ELSE
               P = OLDC*BB
            END IF
   80    CONTINUE
*
         E( L ) = S*P
         D( L ) = SIGMA + GAMMA
         GO TO 50
*
*        Eigenvalue found.
*
   90    CONTINUE
         D( L ) = P
*
         L = L + 1
         IF( L.LE.LEND )
     $      GO TO 50
         GO TO 150
*
      ELSE
*
*        QR Iteration
*
*        Look for small superdiagonal element.
*
  100    CONTINUE
         DO 110 M = L, LEND + 1, -1
            IF( ABS( E( M-1 ) ).LE.EPS2*ABS( D( M )*D( M-1 ) ) )
     $         GO TO 120
  110    CONTINUE
         M = LEND
*
  120    CONTINUE
         IF( M.GT.LEND )
     $      E( M-1 ) = ZERO
         P = D( L )
         IF( M.EQ.L )
     $      GO TO 140
*
*        If remaining matrix is 2 by 2, use SLAE2 to compute its
*        eigenvalues.
*
         IF( M.EQ.L-1 ) THEN
            RTE = SQRT( E( L-1 ) )
            CALL SLAE2( D( L ), RTE, D( L-1 ), RT1, RT2 )
            D( L ) = RT1
            D( L-1 ) = RT2
            E( L-1 ) = ZERO
            L = L - 2
            IF( L.GE.LEND )
     $         GO TO 100
            GO TO 150
         END IF
*
         IF( JTOT.EQ.NMAXIT )
     $      GO TO 150
         JTOT = JTOT + 1
*
*        Form shift.
*
         RTE = SQRT( E( L-1 ) )
         SIGMA = ( D( L-1 )-P ) / ( TWO*RTE )
         R = SLAPY2( SIGMA, ONE )
         SIGMA = P - ( RTE / ( SIGMA+SIGN( R, SIGMA ) ) )
*
         C = ONE
         S = ZERO
         GAMMA = D( M ) - SIGMA
         P = GAMMA*GAMMA
*
*        Inner loop
*
         DO 130 I = M, L - 1
            BB = E( I )
            R = P + BB
            IF( I.NE.M )
     $         E( I-1 ) = S*R
            OLDC = C
            C = P / R
            S = BB / R
            OLDGAM = GAMMA
            ALPHA = D( I+1 )
            GAMMA = C*( ALPHA-SIGMA ) - S*OLDGAM
            D( I ) = OLDGAM + ( ALPHA-GAMMA )
            IF( C.NE.ZERO ) THEN
               P = ( GAMMA*GAMMA ) / C
            ELSE
               P = OLDC*BB
            END IF
  130    CONTINUE
*
         E( L-1 ) = S*P
         D( L ) = SIGMA + GAMMA
         GO TO 100
*
*        Eigenvalue found.
*
  140    CONTINUE
         D( L ) = P
*
         L = L - 1
         IF( L.GE.LEND )
     $      GO TO 100
         GO TO 150
*
      END IF
*
*     Undo scaling if necessary
*
  150 CONTINUE
      IF( ISCALE.EQ.1 )
     $   CALL SLASCL( 'G', 0, 0, SSFMAX, ANORM, LENDSV-LSV+1, 1,
     $                D( LSV ), N, INFO )
      IF( ISCALE.EQ.2 )
     $   CALL SLASCL( 'G', 0, 0, SSFMIN, ANORM, LENDSV-LSV+1, 1,
     $                D( LSV ), N, INFO )
*
*     Check for no convergence to an eigenvalue after a total
*     of N*MAXIT iterations.
*
      IF( JTOT.LT.NMAXIT )
     $   GO TO 10
      DO 160 I = 1, N - 1
         IF( E( I ).NE.ZERO )
     $      INFO = INFO + 1
  160 CONTINUE
      GO TO 180
*
*     Sort eigenvalues in increasing order.
*
  170 CONTINUE
      CALL SLASRT( 'I', N, D, INFO )
*
  180 CONTINUE
      RETURN
*
*     End of SSTERF
*
      END