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dlaein.f
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*> \brief \b DLAEIN computes a specified right or left eigenvector of an upper Hessenberg matrix by inverse iteration.
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download DLAEIN + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlaein.f">
*> [TGZ]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlaein.f">
*> [ZIP]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlaein.f">
*> [TXT]</a>
*> \endhtmlonly
*
* Definition:
* ===========
*
* SUBROUTINE DLAEIN( RIGHTV, NOINIT, N, H, LDH, WR, WI, VR, VI, B,
* LDB, WORK, EPS3, SMLNUM, BIGNUM, INFO )
*
* .. Scalar Arguments ..
* LOGICAL NOINIT, RIGHTV
* INTEGER INFO, LDB, LDH, N
* DOUBLE PRECISION BIGNUM, EPS3, SMLNUM, WI, WR
* ..
* .. Array Arguments ..
* DOUBLE PRECISION B( LDB, * ), H( LDH, * ), VI( * ), VR( * ),
* $ WORK( * )
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> DLAEIN uses inverse iteration to find a right or left eigenvector
*> corresponding to the eigenvalue (WR,WI) of a real upper Hessenberg
*> matrix H.
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] RIGHTV
*> \verbatim
*> RIGHTV is LOGICAL
*> = .TRUE. : compute right eigenvector;
*> = .FALSE.: compute left eigenvector.
*> \endverbatim
*>
*> \param[in] NOINIT
*> \verbatim
*> NOINIT is LOGICAL
*> = .TRUE. : no initial vector supplied in (VR,VI).
*> = .FALSE.: initial vector supplied in (VR,VI).
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*> N is INTEGER
*> The order of the matrix H. N >= 0.
*> \endverbatim
*>
*> \param[in] H
*> \verbatim
*> H is DOUBLE PRECISION array, dimension (LDH,N)
*> The upper Hessenberg matrix H.
*> \endverbatim
*>
*> \param[in] LDH
*> \verbatim
*> LDH is INTEGER
*> The leading dimension of the array H. LDH >= max(1,N).
*> \endverbatim
*>
*> \param[in] WR
*> \verbatim
*> WR is DOUBLE PRECISION
*> \endverbatim
*>
*> \param[in] WI
*> \verbatim
*> WI is DOUBLE PRECISION
*> The real and imaginary parts of the eigenvalue of H whose
*> corresponding right or left eigenvector is to be computed.
*> \endverbatim
*>
*> \param[in,out] VR
*> \verbatim
*> VR is DOUBLE PRECISION array, dimension (N)
*> \endverbatim
*>
*> \param[in,out] VI
*> \verbatim
*> VI is DOUBLE PRECISION array, dimension (N)
*> On entry, if NOINIT = .FALSE. and WI = 0.0, VR must contain
*> a real starting vector for inverse iteration using the real
*> eigenvalue WR; if NOINIT = .FALSE. and WI.ne.0.0, VR and VI
*> must contain the real and imaginary parts of a complex
*> starting vector for inverse iteration using the complex
*> eigenvalue (WR,WI); otherwise VR and VI need not be set.
*> On exit, if WI = 0.0 (real eigenvalue), VR contains the
*> computed real eigenvector; if WI.ne.0.0 (complex eigenvalue),
*> VR and VI contain the real and imaginary parts of the
*> computed complex eigenvector. The eigenvector is normalized
*> so that the component of largest magnitude has magnitude 1;
*> here the magnitude of a complex number (x,y) is taken to be
*> |x| + |y|.
*> VI is not referenced if WI = 0.0.
*> \endverbatim
*>
*> \param[out] B
*> \verbatim
*> B is DOUBLE PRECISION array, dimension (LDB,N)
*> \endverbatim
*>
*> \param[in] LDB
*> \verbatim
*> LDB is INTEGER
*> The leading dimension of the array B. LDB >= N+1.
*> \endverbatim
*>
*> \param[out] WORK
*> \verbatim
*> WORK is DOUBLE PRECISION array, dimension (N)
*> \endverbatim
*>
*> \param[in] EPS3
*> \verbatim
*> EPS3 is DOUBLE PRECISION
*> A small machine-dependent value which is used to perturb
*> close eigenvalues, and to replace zero pivots.
*> \endverbatim
*>
*> \param[in] SMLNUM
*> \verbatim
*> SMLNUM is DOUBLE PRECISION
*> A machine-dependent value close to the underflow threshold.
*> \endverbatim
*>
*> \param[in] BIGNUM
*> \verbatim
*> BIGNUM is DOUBLE PRECISION
*> A machine-dependent value close to the overflow threshold.
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*> INFO is INTEGER
*> = 0: successful exit
*> = 1: inverse iteration did not converge; VR is set to the
*> last iterate, and so is VI if WI.ne.0.0.
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \ingroup doubleOTHERauxiliary
*
* =====================================================================
SUBROUTINE DLAEIN( RIGHTV, NOINIT, N, H, LDH, WR, WI, VR, VI, B,
$ LDB, WORK, EPS3, SMLNUM, BIGNUM, INFO )
*
* -- LAPACK auxiliary routine --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
*
* .. Scalar Arguments ..
LOGICAL NOINIT, RIGHTV
INTEGER INFO, LDB, LDH, N
DOUBLE PRECISION BIGNUM, EPS3, SMLNUM, WI, WR
* ..
* .. Array Arguments ..
DOUBLE PRECISION B( LDB, * ), H( LDH, * ), VI( * ), VR( * ),
$ WORK( * )
* ..
*
* =====================================================================
*
* .. Parameters ..
DOUBLE PRECISION ZERO, ONE, TENTH
PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TENTH = 1.0D-1 )
* ..
* .. Local Scalars ..
CHARACTER NORMIN, TRANS
INTEGER I, I1, I2, I3, IERR, ITS, J
DOUBLE PRECISION ABSBII, ABSBJJ, EI, EJ, GROWTO, NORM, NRMSML,
$ REC, ROOTN, SCALE, TEMP, VCRIT, VMAX, VNORM, W,
$ W1, X, XI, XR, Y
* ..
* .. External Functions ..
INTEGER IDAMAX
DOUBLE PRECISION DASUM, DLAPY2, DNRM2
EXTERNAL IDAMAX, DASUM, DLAPY2, DNRM2
* ..
* .. External Subroutines ..
EXTERNAL DLADIV, DLATRS, DSCAL
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, DBLE, MAX, SQRT
* ..
* .. Executable Statements ..
*
INFO = 0
*
* GROWTO is the threshold used in the acceptance test for an
* eigenvector.
*
ROOTN = SQRT( DBLE( N ) )
GROWTO = TENTH / ROOTN
NRMSML = MAX( ONE, EPS3*ROOTN )*SMLNUM
*
* Form B = H - (WR,WI)*I (except that the subdiagonal elements and
* the imaginary parts of the diagonal elements are not stored).
*
DO 20 J = 1, N
DO 10 I = 1, J - 1
B( I, J ) = H( I, J )
10 CONTINUE
B( J, J ) = H( J, J ) - WR
20 CONTINUE
*
IF( WI.EQ.ZERO ) THEN
*
* Real eigenvalue.
*
IF( NOINIT ) THEN
*
* Set initial vector.
*
DO 30 I = 1, N
VR( I ) = EPS3
30 CONTINUE
ELSE
*
* Scale supplied initial vector.
*
VNORM = DNRM2( N, VR, 1 )
CALL DSCAL( N, ( EPS3*ROOTN ) / MAX( VNORM, NRMSML ), VR,
$ 1 )
END IF
*
IF( RIGHTV ) THEN
*
* LU decomposition with partial pivoting of B, replacing zero
* pivots by EPS3.
*
DO 60 I = 1, N - 1
EI = H( I+1, I )
IF( ABS( B( I, I ) ).LT.ABS( EI ) ) THEN
*
* Interchange rows and eliminate.
*
X = B( I, I ) / EI
B( I, I ) = EI
DO 40 J = I + 1, N
TEMP = B( I+1, J )
B( I+1, J ) = B( I, J ) - X*TEMP
B( I, J ) = TEMP
40 CONTINUE
ELSE
*
* Eliminate without interchange.
*
IF( B( I, I ).EQ.ZERO )
$ B( I, I ) = EPS3
X = EI / B( I, I )
IF( X.NE.ZERO ) THEN
DO 50 J = I + 1, N
B( I+1, J ) = B( I+1, J ) - X*B( I, J )
50 CONTINUE
END IF
END IF
60 CONTINUE
IF( B( N, N ).EQ.ZERO )
$ B( N, N ) = EPS3
*
TRANS = 'N'
*
ELSE
*
* UL decomposition with partial pivoting of B, replacing zero
* pivots by EPS3.
*
DO 90 J = N, 2, -1
EJ = H( J, J-1 )
IF( ABS( B( J, J ) ).LT.ABS( EJ ) ) THEN
*
* Interchange columns and eliminate.
*
X = B( J, J ) / EJ
B( J, J ) = EJ
DO 70 I = 1, J - 1
TEMP = B( I, J-1 )
B( I, J-1 ) = B( I, J ) - X*TEMP
B( I, J ) = TEMP
70 CONTINUE
ELSE
*
* Eliminate without interchange.
*
IF( B( J, J ).EQ.ZERO )
$ B( J, J ) = EPS3
X = EJ / B( J, J )
IF( X.NE.ZERO ) THEN
DO 80 I = 1, J - 1
B( I, J-1 ) = B( I, J-1 ) - X*B( I, J )
80 CONTINUE
END IF
END IF
90 CONTINUE
IF( B( 1, 1 ).EQ.ZERO )
$ B( 1, 1 ) = EPS3
*
TRANS = 'T'
*
END IF
*
NORMIN = 'N'
DO 110 ITS = 1, N
*
* Solve U*x = scale*v for a right eigenvector
* or U**T*x = scale*v for a left eigenvector,
* overwriting x on v.
*
CALL DLATRS( 'Upper', TRANS, 'Nonunit', NORMIN, N, B, LDB,
$ VR, SCALE, WORK, IERR )
NORMIN = 'Y'
*
* Test for sufficient growth in the norm of v.
*
VNORM = DASUM( N, VR, 1 )
IF( VNORM.GE.GROWTO*SCALE )
$ GO TO 120
*
* Choose new orthogonal starting vector and try again.
*
TEMP = EPS3 / ( ROOTN+ONE )
VR( 1 ) = EPS3
DO 100 I = 2, N
VR( I ) = TEMP
100 CONTINUE
VR( N-ITS+1 ) = VR( N-ITS+1 ) - EPS3*ROOTN
110 CONTINUE
*
* Failure to find eigenvector in N iterations.
*
INFO = 1
*
120 CONTINUE
*
* Normalize eigenvector.
*
I = IDAMAX( N, VR, 1 )
CALL DSCAL( N, ONE / ABS( VR( I ) ), VR, 1 )
ELSE
*
* Complex eigenvalue.
*
IF( NOINIT ) THEN
*
* Set initial vector.
*
DO 130 I = 1, N
VR( I ) = EPS3
VI( I ) = ZERO
130 CONTINUE
ELSE
*
* Scale supplied initial vector.
*
NORM = DLAPY2( DNRM2( N, VR, 1 ), DNRM2( N, VI, 1 ) )
REC = ( EPS3*ROOTN ) / MAX( NORM, NRMSML )
CALL DSCAL( N, REC, VR, 1 )
CALL DSCAL( N, REC, VI, 1 )
END IF
*
IF( RIGHTV ) THEN
*
* LU decomposition with partial pivoting of B, replacing zero
* pivots by EPS3.
*
* The imaginary part of the (i,j)-th element of U is stored in
* B(j+1,i).
*
B( 2, 1 ) = -WI
DO 140 I = 2, N
B( I+1, 1 ) = ZERO
140 CONTINUE
*
DO 170 I = 1, N - 1
ABSBII = DLAPY2( B( I, I ), B( I+1, I ) )
EI = H( I+1, I )
IF( ABSBII.LT.ABS( EI ) ) THEN
*
* Interchange rows and eliminate.
*
XR = B( I, I ) / EI
XI = B( I+1, I ) / EI
B( I, I ) = EI
B( I+1, I ) = ZERO
DO 150 J = I + 1, N
TEMP = B( I+1, J )
B( I+1, J ) = B( I, J ) - XR*TEMP
B( J+1, I+1 ) = B( J+1, I ) - XI*TEMP
B( I, J ) = TEMP
B( J+1, I ) = ZERO
150 CONTINUE
B( I+2, I ) = -WI
B( I+1, I+1 ) = B( I+1, I+1 ) - XI*WI
B( I+2, I+1 ) = B( I+2, I+1 ) + XR*WI
ELSE
*
* Eliminate without interchanging rows.
*
IF( ABSBII.EQ.ZERO ) THEN
B( I, I ) = EPS3
B( I+1, I ) = ZERO
ABSBII = EPS3
END IF
EI = ( EI / ABSBII ) / ABSBII
XR = B( I, I )*EI
XI = -B( I+1, I )*EI
DO 160 J = I + 1, N
B( I+1, J ) = B( I+1, J ) - XR*B( I, J ) +
$ XI*B( J+1, I )
B( J+1, I+1 ) = -XR*B( J+1, I ) - XI*B( I, J )
160 CONTINUE
B( I+2, I+1 ) = B( I+2, I+1 ) - WI
END IF
*
* Compute 1-norm of offdiagonal elements of i-th row.
*
WORK( I ) = DASUM( N-I, B( I, I+1 ), LDB ) +
$ DASUM( N-I, B( I+2, I ), 1 )
170 CONTINUE
IF( B( N, N ).EQ.ZERO .AND. B( N+1, N ).EQ.ZERO )
$ B( N, N ) = EPS3
WORK( N ) = ZERO
*
I1 = N
I2 = 1
I3 = -1
ELSE
*
* UL decomposition with partial pivoting of conjg(B),
* replacing zero pivots by EPS3.
*
* The imaginary part of the (i,j)-th element of U is stored in
* B(j+1,i).
*
B( N+1, N ) = WI
DO 180 J = 1, N - 1
B( N+1, J ) = ZERO
180 CONTINUE
*
DO 210 J = N, 2, -1
EJ = H( J, J-1 )
ABSBJJ = DLAPY2( B( J, J ), B( J+1, J ) )
IF( ABSBJJ.LT.ABS( EJ ) ) THEN
*
* Interchange columns and eliminate
*
XR = B( J, J ) / EJ
XI = B( J+1, J ) / EJ
B( J, J ) = EJ
B( J+1, J ) = ZERO
DO 190 I = 1, J - 1
TEMP = B( I, J-1 )
B( I, J-1 ) = B( I, J ) - XR*TEMP
B( J, I ) = B( J+1, I ) - XI*TEMP
B( I, J ) = TEMP
B( J+1, I ) = ZERO
190 CONTINUE
B( J+1, J-1 ) = WI
B( J-1, J-1 ) = B( J-1, J-1 ) + XI*WI
B( J, J-1 ) = B( J, J-1 ) - XR*WI
ELSE
*
* Eliminate without interchange.
*
IF( ABSBJJ.EQ.ZERO ) THEN
B( J, J ) = EPS3
B( J+1, J ) = ZERO
ABSBJJ = EPS3
END IF
EJ = ( EJ / ABSBJJ ) / ABSBJJ
XR = B( J, J )*EJ
XI = -B( J+1, J )*EJ
DO 200 I = 1, J - 1
B( I, J-1 ) = B( I, J-1 ) - XR*B( I, J ) +
$ XI*B( J+1, I )
B( J, I ) = -XR*B( J+1, I ) - XI*B( I, J )
200 CONTINUE
B( J, J-1 ) = B( J, J-1 ) + WI
END IF
*
* Compute 1-norm of offdiagonal elements of j-th column.
*
WORK( J ) = DASUM( J-1, B( 1, J ), 1 ) +
$ DASUM( J-1, B( J+1, 1 ), LDB )
210 CONTINUE
IF( B( 1, 1 ).EQ.ZERO .AND. B( 2, 1 ).EQ.ZERO )
$ B( 1, 1 ) = EPS3
WORK( 1 ) = ZERO
*
I1 = 1
I2 = N
I3 = 1
END IF
*
DO 270 ITS = 1, N
SCALE = ONE
VMAX = ONE
VCRIT = BIGNUM
*
* Solve U*(xr,xi) = scale*(vr,vi) for a right eigenvector,
* or U**T*(xr,xi) = scale*(vr,vi) for a left eigenvector,
* overwriting (xr,xi) on (vr,vi).
*
DO 250 I = I1, I2, I3
*
IF( WORK( I ).GT.VCRIT ) THEN
REC = ONE / VMAX
CALL DSCAL( N, REC, VR, 1 )
CALL DSCAL( N, REC, VI, 1 )
SCALE = SCALE*REC
VMAX = ONE
VCRIT = BIGNUM
END IF
*
XR = VR( I )
XI = VI( I )
IF( RIGHTV ) THEN
DO 220 J = I + 1, N
XR = XR - B( I, J )*VR( J ) + B( J+1, I )*VI( J )
XI = XI - B( I, J )*VI( J ) - B( J+1, I )*VR( J )
220 CONTINUE
ELSE
DO 230 J = 1, I - 1
XR = XR - B( J, I )*VR( J ) + B( I+1, J )*VI( J )
XI = XI - B( J, I )*VI( J ) - B( I+1, J )*VR( J )
230 CONTINUE
END IF
*
W = ABS( B( I, I ) ) + ABS( B( I+1, I ) )
IF( W.GT.SMLNUM ) THEN
IF( W.LT.ONE ) THEN
W1 = ABS( XR ) + ABS( XI )
IF( W1.GT.W*BIGNUM ) THEN
REC = ONE / W1
CALL DSCAL( N, REC, VR, 1 )
CALL DSCAL( N, REC, VI, 1 )
XR = VR( I )
XI = VI( I )
SCALE = SCALE*REC
VMAX = VMAX*REC
END IF
END IF
*
* Divide by diagonal element of B.
*
CALL DLADIV( XR, XI, B( I, I ), B( I+1, I ), VR( I ),
$ VI( I ) )
VMAX = MAX( ABS( VR( I ) )+ABS( VI( I ) ), VMAX )
VCRIT = BIGNUM / VMAX
ELSE
DO 240 J = 1, N
VR( J ) = ZERO
VI( J ) = ZERO
240 CONTINUE
VR( I ) = ONE
VI( I ) = ONE
SCALE = ZERO
VMAX = ONE
VCRIT = BIGNUM
END IF
250 CONTINUE
*
* Test for sufficient growth in the norm of (VR,VI).
*
VNORM = DASUM( N, VR, 1 ) + DASUM( N, VI, 1 )
IF( VNORM.GE.GROWTO*SCALE )
$ GO TO 280
*
* Choose a new orthogonal starting vector and try again.
*
Y = EPS3 / ( ROOTN+ONE )
VR( 1 ) = EPS3
VI( 1 ) = ZERO
*
DO 260 I = 2, N
VR( I ) = Y
VI( I ) = ZERO
260 CONTINUE
VR( N-ITS+1 ) = VR( N-ITS+1 ) - EPS3*ROOTN
270 CONTINUE
*
* Failure to find eigenvector in N iterations
*
INFO = 1
*
280 CONTINUE
*
* Normalize eigenvector.
*
VNORM = ZERO
DO 290 I = 1, N
VNORM = MAX( VNORM, ABS( VR( I ) )+ABS( VI( I ) ) )
290 CONTINUE
CALL DSCAL( N, ONE / VNORM, VR, 1 )
CALL DSCAL( N, ONE / VNORM, VI, 1 )
*
END IF
*
RETURN
*
* End of DLAEIN
*
END