Refs #247. Included lapack source codes. Avoid downloading tar.gz from netlib.org
Based on 3.4.2 version, apply patch.for_lapack-3.4.2.
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Zhang Xianyi
204
lapack-netlib/SRC/slarrr.f
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204
lapack-netlib/SRC/slarrr.f
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*> \brief \b SLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants expensive computations which guarantee high relative accuracy in the eigenvalues.
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*
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* =========== DOCUMENTATION ===========
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*
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* Online html documentation available at
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* http://www.netlib.org/lapack/explore-html/
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*
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*> \htmlonly
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*> Download SLARRR + dependencies
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/slarrr.f">
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*> [TGZ]</a>
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/slarrr.f">
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*> [ZIP]</a>
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/slarrr.f">
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*> [TXT]</a>
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*> \endhtmlonly
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*
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* Definition:
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* ===========
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*
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* SUBROUTINE SLARRR( N, D, E, INFO )
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*
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* .. Scalar Arguments ..
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* INTEGER N, INFO
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* ..
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* .. Array Arguments ..
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* REAL D( * ), E( * )
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* ..
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*
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*
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*
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*> \par Purpose:
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* =============
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*>
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*> \verbatim
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*>
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*> Perform tests to decide whether the symmetric tridiagonal matrix T
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*> warrants expensive computations which guarantee high relative accuracy
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*> in the eigenvalues.
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*> \endverbatim
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*
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* Arguments:
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* ==========
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*
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*> \param[in] N
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*> \verbatim
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*> N is INTEGER
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*> The order of the matrix. N > 0.
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*> \endverbatim
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*>
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*> \param[in] D
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*> \verbatim
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*> D is REAL array, dimension (N)
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*> The N diagonal elements of the tridiagonal matrix T.
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*> \endverbatim
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*>
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*> \param[in,out] E
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*> \verbatim
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*> E is REAL array, dimension (N)
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*> On entry, the first (N-1) entries contain the subdiagonal
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*> elements of the tridiagonal matrix T; E(N) is set to ZERO.
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*> \endverbatim
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*>
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*> \param[out] INFO
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*> \verbatim
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*> INFO is INTEGER
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*> INFO = 0(default) : the matrix warrants computations preserving
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*> relative accuracy.
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*> INFO = 1 : the matrix warrants computations guaranteeing
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*> only absolute accuracy.
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*> \endverbatim
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*
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* Authors:
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* ========
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*
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*> \author Univ. of Tennessee
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*> \author Univ. of California Berkeley
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*> \author Univ. of Colorado Denver
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*> \author NAG Ltd.
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*
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*> \date September 2012
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*
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*> \ingroup auxOTHERauxiliary
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*
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*> \par Contributors:
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* ==================
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*>
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*> Beresford Parlett, University of California, Berkeley, USA \n
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*> Jim Demmel, University of California, Berkeley, USA \n
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*> Inderjit Dhillon, University of Texas, Austin, USA \n
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*> Osni Marques, LBNL/NERSC, USA \n
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*> Christof Voemel, University of California, Berkeley, USA
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*
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* =====================================================================
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SUBROUTINE SLARRR( N, D, E, INFO )
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*
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* -- LAPACK auxiliary routine (version 3.4.2) --
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* -- LAPACK is a software package provided by Univ. of Tennessee, --
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* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
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* September 2012
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*
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* .. Scalar Arguments ..
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INTEGER N, INFO
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* ..
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* .. Array Arguments ..
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REAL D( * ), E( * )
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* ..
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*
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*
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* =====================================================================
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*
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* .. Parameters ..
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REAL ZERO, RELCOND
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PARAMETER ( ZERO = 0.0E0,
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$ RELCOND = 0.999E0 )
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* ..
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* .. Local Scalars ..
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INTEGER I
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LOGICAL YESREL
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REAL EPS, SAFMIN, SMLNUM, RMIN, TMP, TMP2,
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$ OFFDIG, OFFDIG2
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* ..
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* .. External Functions ..
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REAL SLAMCH
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EXTERNAL SLAMCH
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* ..
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* .. Intrinsic Functions ..
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INTRINSIC ABS
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* ..
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* .. Executable Statements ..
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*
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* As a default, do NOT go for relative-accuracy preserving computations.
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INFO = 1
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SAFMIN = SLAMCH( 'Safe minimum' )
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EPS = SLAMCH( 'Precision' )
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SMLNUM = SAFMIN / EPS
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RMIN = SQRT( SMLNUM )
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* Tests for relative accuracy
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*
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* Test for scaled diagonal dominance
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* Scale the diagonal entries to one and check whether the sum of the
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* off-diagonals is less than one
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*
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* The sdd relative error bounds have a 1/(1- 2*x) factor in them,
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* x = max(OFFDIG + OFFDIG2), so when x is close to 1/2, no relative
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* accuracy is promised. In the notation of the code fragment below,
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* 1/(1 - (OFFDIG + OFFDIG2)) is the condition number.
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* We don't think it is worth going into "sdd mode" unless the relative
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* condition number is reasonable, not 1/macheps.
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* The threshold should be compatible with other thresholds used in the
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* code. We set OFFDIG + OFFDIG2 <= .999 =: RELCOND, it corresponds
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* to losing at most 3 decimal digits: 1 / (1 - (OFFDIG + OFFDIG2)) <= 1000
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* instead of the current OFFDIG + OFFDIG2 < 1
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*
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YESREL = .TRUE.
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OFFDIG = ZERO
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TMP = SQRT(ABS(D(1)))
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IF (TMP.LT.RMIN) YESREL = .FALSE.
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IF(.NOT.YESREL) GOTO 11
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DO 10 I = 2, N
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TMP2 = SQRT(ABS(D(I)))
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IF (TMP2.LT.RMIN) YESREL = .FALSE.
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IF(.NOT.YESREL) GOTO 11
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OFFDIG2 = ABS(E(I-1))/(TMP*TMP2)
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IF(OFFDIG+OFFDIG2.GE.RELCOND) YESREL = .FALSE.
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IF(.NOT.YESREL) GOTO 11
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TMP = TMP2
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OFFDIG = OFFDIG2
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10 CONTINUE
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11 CONTINUE
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IF( YESREL ) THEN
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INFO = 0
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RETURN
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ELSE
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ENDIF
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*
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*
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* *** MORE TO BE IMPLEMENTED ***
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*
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*
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* Test if the lower bidiagonal matrix L from T = L D L^T
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* (zero shift facto) is well conditioned
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*
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*
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* Test if the upper bidiagonal matrix U from T = U D U^T
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* (zero shift facto) is well conditioned.
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* In this case, the matrix needs to be flipped and, at the end
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* of the eigenvector computation, the flip needs to be applied
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* to the computed eigenvectors (and the support)
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*
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*
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RETURN
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*
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* END OF SLARRR
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*
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END
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