SUBROUTINE SLARRE( RANGE, N, VL, VU, IL, IU, D, E, E2,
$ RTOL1, RTOL2, SPLTOL, NSPLIT, ISPLIT, M,
$ W, WERR, WGAP, IBLOCK, INDEXW, GERS, PIVMIN,
$ WORK, IWORK, INFO )
IMPLICIT NONE
*
* -- LAPACK auxiliary routine (version 3.1) --
* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
* November 2006
*
* .. Scalar Arguments ..
CHARACTER RANGE
INTEGER IL, INFO, IU, M, N, NSPLIT
REAL PIVMIN, RTOL1, RTOL2, SPLTOL, VL, VU
* ..
* .. Array Arguments ..
INTEGER IBLOCK( * ), ISPLIT( * ), IWORK( * ),
$ INDEXW( * )
REAL D( * ), E( * ), E2( * ), GERS( * ),
$ W( * ),WERR( * ), WGAP( * ), WORK( * )
* ..
*
* Purpose
* =======
*
* To find the desired eigenvalues of a given real symmetric
* tridiagonal matrix T, SLARRE sets any "small" off-diagonal
* elements to zero, and for each unreduced block T_i, it finds
* (a) a suitable shift at one end of the block's spectrum,
* (b) the base representation, T_i - sigma_i I = L_i D_i L_i^T, and
* (c) eigenvalues of each L_i D_i L_i^T.
* The representations and eigenvalues found are then used by
* SSTEMR to compute the eigenvectors of T.
* The accuracy varies depending on whether bisection is used to
* find a few eigenvalues or the dqds algorithm (subroutine SLASQ2) to
* conpute all and then discard any unwanted one.
* As an added benefit, SLARRE also outputs the n
* Gerschgorin intervals for the matrices L_i D_i L_i^T.
*
* Arguments
* =========
*
* RANGE (input) CHARACTER
* = 'A': ("All") all eigenvalues will be found.
* = 'V': ("Value") all eigenvalues in the half-open interval
* (VL, VU] will be found.
* = 'I': ("Index") the IL-th through IU-th eigenvalues (of the
* entire matrix) will be found.
*
* N (input) INTEGER
* The order of the matrix. N > 0.
*
* VL (input/output) REAL
* VU (input/output) REAL
* If RANGE='V', the lower and upper bounds for the eigenvalues.
* Eigenvalues less than or equal to VL, or greater than VU,
* will not be returned. VL < VU.
* If RANGE='I' or ='A', SLARRE computes bounds on the desired
* part of the spectrum.
*
* IL (input) INTEGER
* IU (input) INTEGER
* If RANGE='I', the indices (in ascending order) of the
* smallest and largest eigenvalues to be returned.
* 1 <= IL <= IU <= N.
*
* D (input/output) REAL array, dimension (N)
* On entry, the N diagonal elements of the tridiagonal
* matrix T.
* On exit, the N diagonal elements of the diagonal
* matrices D_i.
*
* E (input/output) REAL array, dimension (N)
* On entry, the first (N-1) entries contain the subdiagonal
* elements of the tridiagonal matrix T; E(N) need not be set.
* On exit, E contains the subdiagonal elements of the unit
* bidiagonal matrices L_i. The entries E( ISPLIT( I ) ),
* 1 <= I <= NSPLIT, contain the base points sigma_i on output.
*
* E2 (input/output) REAL array, dimension (N)
* On entry, the first (N-1) entries contain the SQUARES of the
* subdiagonal elements of the tridiagonal matrix T;
* E2(N) need not be set.
* On exit, the entries E2( ISPLIT( I ) ),
* 1 <= I <= NSPLIT, have been set to zero
*
* RTOL1 (input) REAL
* RTOL2 (input) REAL
* Parameters for bisection.
* An interval [LEFT,RIGHT] has converged if
* RIGHT-LEFT.LT.MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) )
*
* SPLTOL (input) REAL
* The threshold for splitting.
*
* NSPLIT (output) INTEGER
* The number of blocks T splits into. 1 <= NSPLIT <= N.
*
* ISPLIT (output) INTEGER array, dimension (N)
* The splitting points, at which T breaks up into blocks.
* The first block consists of rows/columns 1 to ISPLIT(1),
* the second of rows/columns ISPLIT(1)+1 through ISPLIT(2),
* etc., and the NSPLIT-th consists of rows/columns
* ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N.
*
* M (output) INTEGER
* The total number of eigenvalues (of all L_i D_i L_i^T)
* found.
*
* W (output) REAL array, dimension (N)
* The first M elements contain the eigenvalues. The
* eigenvalues of each of the blocks, L_i D_i L_i^T, are
* sorted in ascending order ( SLARRE may use the
* remaining N-M elements as workspace).
*
* WERR (output) REAL array, dimension (N)
* The error bound on the corresponding eigenvalue in W.
*
* WGAP (output) REAL array, dimension (N)
* The separation from the right neighbor eigenvalue in W.
* The gap is only with respect to the eigenvalues of the same block
* as each block has its own representation tree.
* Exception: at the right end of a block we store the left gap
*
* IBLOCK (output) INTEGER array, dimension (N)
* The indices of the blocks (submatrices) associated with the
* corresponding eigenvalues in W; IBLOCK(i)=1 if eigenvalue
* W(i) belongs to the first block from the top, =2 if W(i)
* belongs to the second block, etc.
*
* INDEXW (output) INTEGER array, dimension (N)
* The indices of the eigenvalues within each block (submatrix);
* for example, INDEXW(i)= 10 and IBLOCK(i)=2 imply that the
* i-th eigenvalue W(i) is the 10-th eigenvalue in block 2
*
* GERS (output) REAL array, dimension (2*N)
* The N Gerschgorin intervals (the i-th Gerschgorin interval
* is (GERS(2*i-1), GERS(2*i)).
*
* PIVMIN (output) DOUBLE PRECISION
* The minimum pivot in the Sturm sequence for T.
*
* WORK (workspace) REAL array, dimension (6*N)
* Workspace.
*
* IWORK (workspace) INTEGER array, dimension (5*N)
* Workspace.
*
* INFO (output) INTEGER
* = 0: successful exit
* > 0: A problem occured in SLARRE.
* < 0: One of the called subroutines signaled an internal problem.
* Needs inspection of the corresponding parameter IINFO
* for further information.
*
* =-1: Problem in SLARRD.
* = 2: No base representation could be found in MAXTRY iterations.
* Increasing MAXTRY and recompilation might be a remedy.
* =-3: Problem in SLARRB when computing the refined root
* representation for SLASQ2.
* =-4: Problem in SLARRB when preforming bisection on the
* desired part of the spectrum.
* =-5: Problem in SLASQ2.
* =-6: Problem in SLASQ2.
*
* Further Details
* The base representations are required to suffer very little
* element growth and consequently define all their eigenvalues to
* high relative accuracy.
* ===============
*
* Based on contributions by
* Beresford Parlett, University of California, Berkeley, USA
* Jim Demmel, University of California, Berkeley, USA
* Inderjit Dhillon, University of Texas, Austin, USA
* Osni Marques, LBNL/NERSC, USA
* Christof Voemel, University of California, Berkeley, USA
*
* =====================================================================
*
* .. Parameters ..
REAL FAC, FOUR, FOURTH, FUDGE, HALF, HNDRD,
$ MAXGROWTH, ONE, PERT, TWO, ZERO
PARAMETER ( ZERO = 0.0E0, ONE = 1.0E0,
$ TWO = 2.0E0, FOUR=4.0E0,
$ HNDRD = 100.0E0,
$ PERT = 4.0E0,
$ HALF = ONE/TWO, FOURTH = ONE/FOUR, FAC= HALF,
$ MAXGROWTH = 64.0E0, FUDGE = 2.0E0 )
INTEGER MAXTRY, ALLRNG, INDRNG, VALRNG
PARAMETER ( MAXTRY = 6, ALLRNG = 1, INDRNG = 2,
$ VALRNG = 3 )
* ..
* .. Local Scalars ..
LOGICAL FORCEB, NOREP, USEDQD
INTEGER CNT, CNT1, CNT2, I, IBEGIN, IDUM, IEND, IINFO,
$ IN, INDL, INDU, IRANGE, J, JBLK, MB, MM,
$ WBEGIN, WEND
REAL AVGAP, BSRTOL, CLWDTH, DMAX, DPIVOT, EABS,
$ EMAX, EOLD, EPS, GL, GU, ISLEFT, ISRGHT, RTL,
$ RTOL, S1, S2, SAFMIN, SGNDEF, SIGMA, SPDIAM,
$ TAU, TMP, TMP1
* ..
* .. Local Arrays ..
INTEGER ISEED( 4 )
* ..
* .. External Functions ..
LOGICAL LSAME
REAL SLAMCH
EXTERNAL SLAMCH, LSAME
* ..
* .. External Subroutines ..
EXTERNAL SCOPY, SLARNV, SLARRA, SLARRB, SLARRC, SLARRD,
$ SLASQ2
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, MAX, MIN
* ..
* .. Executable Statements ..
*
INFO = 0
*
* Decode RANGE
*
IF( LSAME( RANGE, 'A' ) ) THEN
IRANGE = ALLRNG
ELSE IF( LSAME( RANGE, 'V' ) ) THEN
IRANGE = VALRNG
ELSE IF( LSAME( RANGE, 'I' ) ) THEN
IRANGE = INDRNG
END IF
M = 0
* Get machine constants
SAFMIN = SLAMCH( 'S' )
EPS = SLAMCH( 'P' )
* Set parameters
RTL = HNDRD*EPS
* If one were ever to ask for less initial precision in BSRTOL,
* one should keep in mind that for the subset case, the extremal
* eigenvalues must be at least as accurate as the current setting
* (eigenvalues in the middle need not as much accuracy)
BSRTOL = SQRT(EPS)*(0.5E-3)
* Treat case of 1x1 matrix for quick return
IF( N.EQ.1 ) THEN
IF( (IRANGE.EQ.ALLRNG).OR.
$ ((IRANGE.EQ.VALRNG).AND.(D(1).GT.VL).AND.(D(1).LE.VU)).OR.
$ ((IRANGE.EQ.INDRNG).AND.(IL.EQ.1).AND.(IU.EQ.1)) ) THEN
M = 1
W(1) = D(1)
* The computation error of the eigenvalue is zero
WERR(1) = ZERO
WGAP(1) = ZERO
IBLOCK( 1 ) = 1
INDEXW( 1 ) = 1
GERS(1) = D( 1 )
GERS(2) = D( 1 )
ENDIF
* store the shift for the initial RRR, which is zero in this case
E(1) = ZERO
RETURN
END IF
* General case: tridiagonal matrix of order > 1
*
* Init WERR, WGAP. Compute Gerschgorin intervals and spectral diameter.
* Compute maximum off-diagonal entry and pivmin.
GL = D(1)
GU = D(1)
EOLD = ZERO
EMAX = ZERO
E(N) = ZERO
DO 5 I = 1,N
WERR(I) = ZERO
WGAP(I) = ZERO
EABS = ABS( E(I) )
IF( EABS .GE. EMAX ) THEN
EMAX = EABS
END IF
TMP1 = EABS + EOLD
GERS( 2*I-1) = D(I) - TMP1
GL = MIN( GL, GERS( 2*I - 1))
GERS( 2*I ) = D(I) + TMP1
GU = MAX( GU, GERS(2*I) )
EOLD = EABS
5 CONTINUE
* The minimum pivot allowed in the Sturm sequence for T
PIVMIN = SAFMIN * MAX( ONE, EMAX**2 )
* Compute spectral diameter. The Gerschgorin bounds give an
* estimate that is wrong by at most a factor of SQRT(2)
SPDIAM = GU - GL
* Compute splitting points
CALL SLARRA( N, D, E, E2, SPLTOL, SPDIAM,
$ NSPLIT, ISPLIT, IINFO )
* Can force use of bisection instead of faster DQDS.
* Option left in the code for future multisection work.
FORCEB = .FALSE.
IF( (IRANGE.EQ.ALLRNG) .AND. (.NOT. FORCEB) ) THEN
* Set interval [VL,VU] that contains all eigenvalues
VL = GL
VU = GU
ELSE
* We call SLARRD to find crude approximations to the eigenvalues
* in the desired range. In case IRANGE = INDRNG, we also obtain the
* interval (VL,VU] that contains all the wanted eigenvalues.
* An interval [LEFT,RIGHT] has converged if
* RIGHT-LEFT.LT.RTOL*MAX(ABS(LEFT),ABS(RIGHT))
* SLARRD needs a WORK of size 4*N, IWORK of size 3*N
CALL SLARRD( RANGE, 'B', N, VL, VU, IL, IU, GERS,
$ BSRTOL, D, E, E2, PIVMIN, NSPLIT, ISPLIT,
$ MM, W, WERR, VL, VU, IBLOCK, INDEXW,
$ WORK, IWORK, IINFO )
IF( IINFO.NE.0 ) THEN
INFO = -1
RETURN
ENDIF
* Make sure that the entries M+1 to N in W, WERR, IBLOCK, INDEXW are 0
DO 14 I = MM+1,N
W( I ) = ZERO
WERR( I ) = ZERO
IBLOCK( I ) = 0
INDEXW( I ) = 0
14 CONTINUE
END IF
***
* Loop over unreduced blocks
IBEGIN = 1
WBEGIN = 1
DO 170 JBLK = 1, NSPLIT
IEND = ISPLIT( JBLK )
IN = IEND - IBEGIN + 1
* 1 X 1 block
IF( IN.EQ.1 ) THEN
IF( (IRANGE.EQ.ALLRNG).OR.( (IRANGE.EQ.VALRNG).AND.
$ ( D( IBEGIN ).GT.VL ).AND.( D( IBEGIN ).LE.VU ) )
$ .OR. ( (IRANGE.EQ.INDRNG).AND.(IBLOCK(WBEGIN).EQ.JBLK))
$ ) THEN
M = M + 1
W( M ) = D( IBEGIN )
WERR(M) = ZERO
* The gap for a single block doesn't matter for the later
* algorithm and is assigned an arbitrary large value
WGAP(M) = ZERO
IBLOCK( M ) = JBLK
INDEXW( M ) = 1
WBEGIN = WBEGIN + 1
ENDIF
* E( IEND ) holds the shift for the initial RRR
E( IEND ) = ZERO
IBEGIN = IEND + 1
GO TO 170
END IF
*
* Blocks of size larger than 1x1
*
* E( IEND ) will hold the shift for the initial RRR, for now set it =0
E( IEND ) = ZERO
*
* Find local outer bounds GL,GU for the block
GL = D(IBEGIN)
GU = D(IBEGIN)
DO 15 I = IBEGIN , IEND
GL = MIN( GERS( 2*I-1 ), GL )
GU = MAX( GERS( 2*I ), GU )
15 CONTINUE
SPDIAM = GU - GL
IF(.NOT. ((IRANGE.EQ.ALLRNG).AND.(.NOT.FORCEB)) ) THEN
* Count the number of eigenvalues in the current block.
MB = 0
DO 20 I = WBEGIN,MM
IF( IBLOCK(I).EQ.JBLK ) THEN
MB = MB+1
ELSE
GOTO 21
ENDIF
20 CONTINUE
21 CONTINUE
IF( MB.EQ.0) THEN
* No eigenvalue in the current block lies in the desired range
* E( IEND ) holds the shift for the initial RRR
E( IEND ) = ZERO
IBEGIN = IEND + 1
GO TO 170
ELSE
* Decide whether dqds or bisection is more efficient
USEDQD = ( (MB .GT. FAC*IN) .AND. (.NOT.FORCEB) )
WEND = WBEGIN + MB - 1
* Calculate gaps for the current block
* In later stages, when representations for individual
* eigenvalues are different, we use SIGMA = E( IEND ).
SIGMA = ZERO
DO 30 I = WBEGIN, WEND - 1
WGAP( I ) = MAX( ZERO,
$ W(I+1)-WERR(I+1) - (W(I)+WERR(I)) )
30 CONTINUE
WGAP( WEND ) = MAX( ZERO,
$ VU - SIGMA - (W( WEND )+WERR( WEND )))
* Find local index of the first and last desired evalue.
INDL = INDEXW(WBEGIN)
INDU = INDEXW( WEND )
ENDIF
ENDIF
IF(( (IRANGE.EQ.ALLRNG) .AND. (.NOT. FORCEB) ).OR.USEDQD) THEN
* Case of DQDS
* Find approximations to the extremal eigenvalues of the block
CALL SLARRK( IN, 1, GL, GU, D(IBEGIN),
$ E2(IBEGIN), PIVMIN, RTL, TMP, TMP1, IINFO )
IF( IINFO.NE.0 ) THEN
INFO = -1
RETURN
ENDIF
ISLEFT = MAX(GL, TMP - TMP1
$ - HNDRD * EPS* ABS(TMP - TMP1))
CALL SLARRK( IN, IN, GL, GU, D(IBEGIN),
$ E2(IBEGIN), PIVMIN, RTL, TMP, TMP1, IINFO )
IF( IINFO.NE.0 ) THEN
INFO = -1
RETURN
ENDIF
ISRGHT = MIN(GU, TMP + TMP1
$ + HNDRD * EPS * ABS(TMP + TMP1))
* Improve the estimate of the spectral diameter
SPDIAM = ISRGHT - ISLEFT
ELSE
* Case of bisection
* Find approximations to the wanted extremal eigenvalues
ISLEFT = MAX(GL, W(WBEGIN) - WERR(WBEGIN)
$ - HNDRD * EPS*ABS(W(WBEGIN)- WERR(WBEGIN) ))
ISRGHT = MIN(GU,W(WEND) + WERR(WEND)
$ + HNDRD * EPS * ABS(W(WEND)+ WERR(WEND)))
ENDIF
* Decide whether the base representation for the current block
* L_JBLK D_JBLK L_JBLK^T = T_JBLK - sigma_JBLK I
* should be on the left or the right end of the current block.
* The strategy is to shift to the end which is "more populated"
* Furthermore, decide whether to use DQDS for the computation of
* the eigenvalue approximations at the end of SLARRE or bisection.
* dqds is chosen if all eigenvalues are desired or the number of
* eigenvalues to be computed is large compared to the blocksize.
IF( ( IRANGE.EQ.ALLRNG ) .AND. (.NOT.FORCEB) ) THEN
* If all the eigenvalues have to be computed, we use dqd
USEDQD = .TRUE.
* INDL is the local index of the first eigenvalue to compute
INDL = 1
INDU = IN
* MB = number of eigenvalues to compute
MB = IN
WEND = WBEGIN + MB - 1
* Define 1/4 and 3/4 points of the spectrum
S1 = ISLEFT + FOURTH * SPDIAM
S2 = ISRGHT - FOURTH * SPDIAM
ELSE
* SLARRD has computed IBLOCK and INDEXW for each eigenvalue
* approximation.
* choose sigma
IF( USEDQD ) THEN
S1 = ISLEFT + FOURTH * SPDIAM
S2 = ISRGHT - FOURTH * SPDIAM
ELSE
TMP = MIN(ISRGHT,VU) - MAX(ISLEFT,VL)
S1 = MAX(ISLEFT,VL) + FOURTH * TMP
S2 = MIN(ISRGHT,VU) - FOURTH * TMP
ENDIF
ENDIF
* Compute the negcount at the 1/4 and 3/4 points
IF(MB.GT.1) THEN
CALL SLARRC( 'T', IN, S1, S2, D(IBEGIN),
$ E(IBEGIN), PIVMIN, CNT, CNT1, CNT2, IINFO)
ENDIF
IF(MB.EQ.1) THEN
SIGMA = GL
SGNDEF = ONE
ELSEIF( CNT1 - INDL .GE. INDU - CNT2 ) THEN
IF( ( IRANGE.EQ.ALLRNG ) .AND. (.NOT.FORCEB) ) THEN
SIGMA = MAX(ISLEFT,GL)
ELSEIF( USEDQD ) THEN
* use Gerschgorin bound as shift to get pos def matrix
* for dqds
SIGMA = ISLEFT
ELSE
* use approximation of the first desired eigenvalue of the
* block as shift
SIGMA = MAX(ISLEFT,VL)
ENDIF
SGNDEF = ONE
ELSE
IF( ( IRANGE.EQ.ALLRNG ) .AND. (.NOT.FORCEB) ) THEN
SIGMA = MIN(ISRGHT,GU)
ELSEIF( USEDQD ) THEN
* use Gerschgorin bound as shift to get neg def matrix
* for dqds
SIGMA = ISRGHT
ELSE
* use approximation of the first desired eigenvalue of the
* block as shift
SIGMA = MIN(ISRGHT,VU)
ENDIF
SGNDEF = -ONE
ENDIF
* An initial SIGMA has been chosen that will be used for computing
* T - SIGMA I = L D L^T
* Define the increment TAU of the shift in case the initial shift
* needs to be refined to obtain a factorization with not too much
* element growth.
IF( USEDQD ) THEN
* The initial SIGMA was to the outer end of the spectrum
* the matrix is definite and we need not retreat.
TAU = SPDIAM*EPS*N + TWO*PIVMIN
ELSE
IF(MB.GT.1) THEN
CLWDTH = W(WEND) + WERR(WEND) - W(WBEGIN) - WERR(WBEGIN)
AVGAP = ABS(CLWDTH / REAL(WEND-WBEGIN))
IF( SGNDEF.EQ.ONE ) THEN
TAU = HALF*MAX(WGAP(WBEGIN),AVGAP)
TAU = MAX(TAU,WERR(WBEGIN))
ELSE
TAU = HALF*MAX(WGAP(WEND-1),AVGAP)
TAU = MAX(TAU,WERR(WEND))
ENDIF
ELSE
TAU = WERR(WBEGIN)
ENDIF
ENDIF
*
DO 80 IDUM = 1, MAXTRY
* Compute L D L^T factorization of tridiagonal matrix T - sigma I.
* Store D in WORK(1:IN), L in WORK(IN+1:2*IN), and reciprocals of
* pivots in WORK(2*IN+1:3*IN)
DPIVOT = D( IBEGIN ) - SIGMA
WORK( 1 ) = DPIVOT
DMAX = ABS( WORK(1) )
J = IBEGIN
DO 70 I = 1, IN - 1
WORK( 2*IN+I ) = ONE / WORK( I )
TMP = E( J )*WORK( 2*IN+I )
WORK( IN+I ) = TMP
DPIVOT = ( D( J+1 )-SIGMA ) - TMP*E( J )
WORK( I+1 ) = DPIVOT
DMAX = MAX( DMAX, ABS(DPIVOT) )
J = J + 1
70 CONTINUE
* check for element growth
IF( DMAX .GT. MAXGROWTH*SPDIAM ) THEN
NOREP = .TRUE.
ELSE
NOREP = .FALSE.
ENDIF
IF( USEDQD .AND. .NOT.NOREP ) THEN
* Ensure the definiteness of the representation
* All entries of D (of L D L^T) must have the same sign
DO 71 I = 1, IN
TMP = SGNDEF*WORK( I )
IF( TMP.LT.ZERO ) NOREP = .TRUE.
71 CONTINUE
ENDIF
IF(NOREP) THEN
* Note that in the case of IRANGE=ALLRNG, we use the Gerschgorin
* shift which makes the matrix definite. So we should end up
* here really only in the case of IRANGE = VALRNG or INDRNG.
IF( IDUM.EQ.MAXTRY-1 ) THEN
IF( SGNDEF.EQ.ONE ) THEN
* The fudged Gerschgorin shift should succeed
SIGMA =
$ GL - FUDGE*SPDIAM*EPS*N - FUDGE*TWO*PIVMIN
ELSE
SIGMA =
$ GU + FUDGE*SPDIAM*EPS*N + FUDGE*TWO*PIVMIN
END IF
ELSE
SIGMA = SIGMA - SGNDEF * TAU
TAU = TWO * TAU
END IF
ELSE
* an initial RRR is found
GO TO 83
END IF
80 CONTINUE
* if the program reaches this point, no base representation could be
* found in MAXTRY iterations.
INFO = 2
RETURN
83 CONTINUE
* At this point, we have found an initial base representation
* T - SIGMA I = L D L^T with not too much element growth.
* Store the shift.
E( IEND ) = SIGMA
* Store D and L.
CALL SCOPY( IN, WORK, 1, D( IBEGIN ), 1 )
CALL SCOPY( IN-1, WORK( IN+1 ), 1, E( IBEGIN ), 1 )
IF(MB.GT.1 ) THEN
*
* Perturb each entry of the base representation by a small
* (but random) relative amount to overcome difficulties with
* glued matrices.
*
DO 122 I = 1, 4
ISEED( I ) = 1
122 CONTINUE
CALL SLARNV(2, ISEED, 2*IN-1, WORK(1))
DO 125 I = 1,IN-1
D(IBEGIN+I-1) = D(IBEGIN+I-1)*(ONE+EPS*PERT*WORK(I))
E(IBEGIN+I-1) = E(IBEGIN+I-1)*(ONE+EPS*PERT*WORK(IN+I))
125 CONTINUE
D(IEND) = D(IEND)*(ONE+EPS*FOUR*WORK(IN))
*
ENDIF
*
* Don't update the Gerschgorin intervals because keeping track
* of the updates would be too much work in SLARRV.
* We update W instead and use it to locate the proper Gerschgorin
* intervals.
* Compute the required eigenvalues of L D L' by bisection or dqds
IF ( .NOT.USEDQD ) THEN
* If SLARRD has been used, shift the eigenvalue approximations
* according to their representation. This is necessary for
* a uniform SLARRV since dqds computes eigenvalues of the
* shifted representation. In SLARRV, W will always hold the
* UNshifted eigenvalue approximation.
DO 134 J=WBEGIN,WEND
W(J) = W(J) - SIGMA
WERR(J) = WERR(J) + ABS(W(J)) * EPS
134 CONTINUE
* call SLARRB to reduce eigenvalue error of the approximations
* from SLARRD
DO 135 I = IBEGIN, IEND-1
WORK( I ) = D( I ) * E( I )**2
135 CONTINUE
* use bisection to find EV from INDL to INDU
CALL SLARRB(IN, D(IBEGIN), WORK(IBEGIN),
$ INDL, INDU, RTOL1, RTOL2, INDL-1,
$ W(WBEGIN), WGAP(WBEGIN), WERR(WBEGIN),
$ WORK( 2*N+1 ), IWORK, PIVMIN, SPDIAM,
$ IN, IINFO )
IF( IINFO .NE. 0 ) THEN
INFO = -4
RETURN
END IF
* SLARRB computes all gaps correctly except for the last one
* Record distance to VU/GU
WGAP( WEND ) = MAX( ZERO,
$ ( VU-SIGMA ) - ( W( WEND ) + WERR( WEND ) ) )
DO 138 I = INDL, INDU
M = M + 1
IBLOCK(M) = JBLK
INDEXW(M) = I
138 CONTINUE
ELSE
* Call dqds to get all eigs (and then possibly delete unwanted
* eigenvalues).
* Note that dqds finds the eigenvalues of the L D L^T representation
* of T to high relative accuracy. High relative accuracy
* might be lost when the shift of the RRR is subtracted to obtain
* the eigenvalues of T. However, T is not guaranteed to define its
* eigenvalues to high relative accuracy anyway.
* Set RTOL to the order of the tolerance used in SLASQ2
* This is an ESTIMATED error, the worst case bound is 4*N*EPS
* which is usually too large and requires unnecessary work to be
* done by bisection when computing the eigenvectors
RTOL = LOG(REAL(IN)) * FOUR * EPS
J = IBEGIN
DO 140 I = 1, IN - 1
WORK( 2*I-1 ) = ABS( D( J ) )
WORK( 2*I ) = E( J )*E( J )*WORK( 2*I-1 )
J = J + 1
140 CONTINUE
WORK( 2*IN-1 ) = ABS( D( IEND ) )
WORK( 2*IN ) = ZERO
CALL SLASQ2( IN, WORK, IINFO )
IF( IINFO .NE. 0 ) THEN
* If IINFO = -5 then an index is part of a tight cluster
* and should be changed. The index is in IWORK(1) and the
* gap is in WORK(N+1)
INFO = -5
RETURN
ELSE
* Test that all eigenvalues are positive as expected
DO 149 I = 1, IN
IF( WORK( I ).LT.ZERO ) THEN
INFO = -6
RETURN
ENDIF
149 CONTINUE
END IF
IF( SGNDEF.GT.ZERO ) THEN
DO 150 I = INDL, INDU
M = M + 1
W( M ) = WORK( IN-I+1 )
IBLOCK( M ) = JBLK
INDEXW( M ) = I
150 CONTINUE
ELSE
DO 160 I = INDL, INDU
M = M + 1
W( M ) = -WORK( I )
IBLOCK( M ) = JBLK
INDEXW( M ) = I
160 CONTINUE
END IF
DO 165 I = M - MB + 1, M
* the value of RTOL below should be the tolerance in SLASQ2
WERR( I ) = RTOL * ABS( W(I) )
165 CONTINUE
DO 166 I = M - MB + 1, M - 1
* compute the right gap between the intervals
WGAP( I ) = MAX( ZERO,
$ W(I+1)-WERR(I+1) - (W(I)+WERR(I)) )
166 CONTINUE
WGAP( M ) = MAX( ZERO,
$ ( VU-SIGMA ) - ( W( M ) + WERR( M ) ) )
END IF
* proceed with next block
IBEGIN = IEND + 1
WBEGIN = WEND + 1
170 CONTINUE
*
RETURN
*
* end of SLARRE
*
END