SUBROUTINE SLARRR( N, D, E, INFO ) * * -- LAPACK auxiliary routine (version 3.2.2) -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * June 2010 * * .. Scalar Arguments .. INTEGER N, INFO * .. * .. Array Arguments .. REAL D( * ), E( * ) * .. * * * Purpose * ======= * * Perform tests to decide whether the symmetric tridiagonal matrix T * warrants expensive computations which guarantee high relative accuracy * in the eigenvalues. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. N > 0. * * D (input) REAL array, dimension (N) * The N diagonal elements of the tridiagonal matrix T. * * 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) is set to ZERO. * * INFO (output) INTEGER * INFO = 0(default) : the matrix warrants computations preserving * relative accuracy. * INFO = 1 : the matrix warrants computations guaranteeing * only absolute accuracy. * * Further Details * =============== * * 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 ZERO, RELCOND PARAMETER ( ZERO = 0.0E0, \$ RELCOND = 0.999E0 ) * .. * .. Local Scalars .. INTEGER I LOGICAL YESREL REAL EPS, SAFMIN, SMLNUM, RMIN, TMP, TMP2, \$ OFFDIG, OFFDIG2 * .. * .. External Functions .. REAL SLAMCH EXTERNAL SLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS * .. * .. Executable Statements .. * * As a default, do NOT go for relative-accuracy preserving computations. INFO = 1 SAFMIN = SLAMCH( 'Safe minimum' ) EPS = SLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS RMIN = SQRT( SMLNUM ) * Tests for relative accuracy * * Test for scaled diagonal dominance * Scale the diagonal entries to one and check whether the sum of the * off-diagonals is less than one * * The sdd relative error bounds have a 1/(1- 2*x) factor in them, * x = max(OFFDIG + OFFDIG2), so when x is close to 1/2, no relative * accuracy is promised. In the notation of the code fragment below, * 1/(1 - (OFFDIG + OFFDIG2)) is the condition number. * We don't think it is worth going into "sdd mode" unless the relative * condition number is reasonable, not 1/macheps. * The threshold should be compatible with other thresholds used in the * code. We set OFFDIG + OFFDIG2 <= .999 =: RELCOND, it corresponds * to losing at most 3 decimal digits: 1 / (1 - (OFFDIG + OFFDIG2)) <= 1000 * instead of the current OFFDIG + OFFDIG2 < 1 * YESREL = .TRUE. OFFDIG = ZERO TMP = SQRT(ABS(D(1))) IF (TMP.LT.RMIN) YESREL = .FALSE. IF(.NOT.YESREL) GOTO 11 DO 10 I = 2, N TMP2 = SQRT(ABS(D(I))) IF (TMP2.LT.RMIN) YESREL = .FALSE. IF(.NOT.YESREL) GOTO 11 OFFDIG2 = ABS(E(I-1))/(TMP*TMP2) IF(OFFDIG+OFFDIG2.GE.RELCOND) YESREL = .FALSE. IF(.NOT.YESREL) GOTO 11 TMP = TMP2 OFFDIG = OFFDIG2 10 CONTINUE 11 CONTINUE IF( YESREL ) THEN INFO = 0 RETURN ELSE ENDIF * * * *** MORE TO BE IMPLEMENTED *** * * * Test if the lower bidiagonal matrix L from T = L D L^T * (zero shift facto) is well conditioned * * * Test if the upper bidiagonal matrix U from T = U D U^T * (zero shift facto) is well conditioned. * In this case, the matrix needs to be flipped and, at the end * of the eigenvector computation, the flip needs to be applied * to the computed eigenvectors (and the support) * * RETURN * * END OF SLARRR * END