LAPACK 3.11.0 LAPACK: Linear Algebra PACKage
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dlarrr.f
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1*> \brief \b DLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants expensive computations which guarantee high relative accuracy in the eigenvalues.
2*
3* =========== DOCUMENTATION ===========
4*
5* Online html documentation available at
6* http://www.netlib.org/lapack/explore-html/
7*
8*> \htmlonly
10*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlarrr.f">
11*> [TGZ]</a>
12*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlarrr.f">
13*> [ZIP]</a>
14*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlarrr.f">
15*> [TXT]</a>
16*> \endhtmlonly
17*
18* Definition:
19* ===========
20*
21* SUBROUTINE DLARRR( N, D, E, INFO )
22*
23* .. Scalar Arguments ..
24* INTEGER N, INFO
25* ..
26* .. Array Arguments ..
27* DOUBLE PRECISION D( * ), E( * )
28* ..
29*
30*
31*
32*> \par Purpose:
33* =============
34*>
35*> \verbatim
36*>
37*> Perform tests to decide whether the symmetric tridiagonal matrix T
38*> warrants expensive computations which guarantee high relative accuracy
39*> in the eigenvalues.
40*> \endverbatim
41*
42* Arguments:
43* ==========
44*
45*> \param[in] N
46*> \verbatim
47*> N is INTEGER
48*> The order of the matrix. N > 0.
49*> \endverbatim
50*>
51*> \param[in] D
52*> \verbatim
53*> D is DOUBLE PRECISION array, dimension (N)
54*> The N diagonal elements of the tridiagonal matrix T.
55*> \endverbatim
56*>
57*> \param[in,out] E
58*> \verbatim
59*> E is DOUBLE PRECISION array, dimension (N)
60*> On entry, the first (N-1) entries contain the subdiagonal
61*> elements of the tridiagonal matrix T; E(N) is set to ZERO.
62*> \endverbatim
63*>
64*> \param[out] INFO
65*> \verbatim
66*> INFO is INTEGER
67*> INFO = 0(default) : the matrix warrants computations preserving
68*> relative accuracy.
69*> INFO = 1 : the matrix warrants computations guaranteeing
70*> only absolute accuracy.
71*> \endverbatim
72*
73* Authors:
74* ========
75*
76*> \author Univ. of Tennessee
77*> \author Univ. of California Berkeley
78*> \author Univ. of Colorado Denver
79*> \author NAG Ltd.
80*
81*> \ingroup OTHERauxiliary
82*
83*> \par Contributors:
84* ==================
85*>
86*> Beresford Parlett, University of California, Berkeley, USA \n
87*> Jim Demmel, University of California, Berkeley, USA \n
88*> Inderjit Dhillon, University of Texas, Austin, USA \n
89*> Osni Marques, LBNL/NERSC, USA \n
90*> Christof Voemel, University of California, Berkeley, USA
91*
92* =====================================================================
93 SUBROUTINE dlarrr( N, D, E, INFO )
94*
95* -- LAPACK auxiliary routine --
96* -- LAPACK is a software package provided by Univ. of Tennessee, --
97* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
98*
99* .. Scalar Arguments ..
100 INTEGER N, INFO
101* ..
102* .. Array Arguments ..
103 DOUBLE PRECISION D( * ), E( * )
104* ..
105*
106*
107* =====================================================================
108*
109* .. Parameters ..
110 DOUBLE PRECISION ZERO, RELCOND
111 parameter( zero = 0.0d0,
112 \$ relcond = 0.999d0 )
113* ..
114* .. Local Scalars ..
115 INTEGER I
116 LOGICAL YESREL
117 DOUBLE PRECISION EPS, SAFMIN, SMLNUM, RMIN, TMP, TMP2,
118 \$ OFFDIG, OFFDIG2
119
120* ..
121* .. External Functions ..
122 DOUBLE PRECISION DLAMCH
123 EXTERNAL dlamch
124* ..
125* .. Intrinsic Functions ..
126 INTRINSIC abs
127* ..
128* .. Executable Statements ..
129*
130* Quick return if possible
131*
132 IF( n.LE.0 ) THEN
133 info = 0
134 RETURN
135 END IF
136*
137* As a default, do NOT go for relative-accuracy preserving computations.
138 info = 1
139
140 safmin = dlamch( 'Safe minimum' )
141 eps = dlamch( 'Precision' )
142 smlnum = safmin / eps
143 rmin = sqrt( smlnum )
144
145* Tests for relative accuracy
146*
147* Test for scaled diagonal dominance
148* Scale the diagonal entries to one and check whether the sum of the
149* off-diagonals is less than one
150*
151* The sdd relative error bounds have a 1/(1- 2*x) factor in them,
152* x = max(OFFDIG + OFFDIG2), so when x is close to 1/2, no relative
153* accuracy is promised. In the notation of the code fragment below,
154* 1/(1 - (OFFDIG + OFFDIG2)) is the condition number.
155* We don't think it is worth going into "sdd mode" unless the relative
156* condition number is reasonable, not 1/macheps.
157* The threshold should be compatible with other thresholds used in the
158* code. We set OFFDIG + OFFDIG2 <= .999 =: RELCOND, it corresponds
159* to losing at most 3 decimal digits: 1 / (1 - (OFFDIG + OFFDIG2)) <= 1000
160* instead of the current OFFDIG + OFFDIG2 < 1
161*
162 yesrel = .true.
163 offdig = zero
164 tmp = sqrt(abs(d(1)))
165 IF (tmp.LT.rmin) yesrel = .false.
166 IF(.NOT.yesrel) GOTO 11
167 DO 10 i = 2, n
168 tmp2 = sqrt(abs(d(i)))
169 IF (tmp2.LT.rmin) yesrel = .false.
170 IF(.NOT.yesrel) GOTO 11
171 offdig2 = abs(e(i-1))/(tmp*tmp2)
172 IF(offdig+offdig2.GE.relcond) yesrel = .false.
173 IF(.NOT.yesrel) GOTO 11
174 tmp = tmp2
175 offdig = offdig2
176 10 CONTINUE
177 11 CONTINUE
178
179 IF( yesrel ) THEN
180 info = 0
181 RETURN
182 ELSE
183 ENDIF
184*
185
186*
187* *** MORE TO BE IMPLEMENTED ***
188*
189
190*
191* Test if the lower bidiagonal matrix L from T = L D L^T
192* (zero shift facto) is well conditioned
193*
194
195*
196* Test if the upper bidiagonal matrix U from T = U D U^T
197* (zero shift facto) is well conditioned.
198* In this case, the matrix needs to be flipped and, at the end
199* of the eigenvector computation, the flip needs to be applied
200* to the computed eigenvectors (and the support)
201*
202
203*
204 RETURN
205*
206* End of DLARRR
207*
208 END
subroutine dlarrr(N, D, E, INFO)
DLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants expensive computa...
Definition: dlarrr.f:94