LAPACK  3.7.1
LAPACK: Linear Algebra PACKage
sdrvsg.f
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1 *> \brief \b SDRVSG
2 *
3 * =========== DOCUMENTATION ===========
4 *
5 * Online html documentation available at
6 * http://www.netlib.org/lapack/explore-html/
7 *
8 * Definition:
9 * ===========
10 *
11 * SUBROUTINE SDRVSG( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
12 * NOUNIT, A, LDA, B, LDB, D, Z, LDZ, AB, BB, AP,
13 * BP, WORK, NWORK, IWORK, LIWORK, RESULT, INFO )
14 *
15 * .. Scalar Arguments ..
16 * INTEGER INFO, LDA, LDB, LDZ, LIWORK, NOUNIT, NSIZES,
17 * $ NTYPES, NWORK
18 * REAL THRESH
19 * ..
20 * .. Array Arguments ..
21 * LOGICAL DOTYPE( * )
22 * INTEGER ISEED( 4 ), IWORK( * ), NN( * )
23 * REAL A( LDA, * ), AB( LDA, * ), AP( * ),
24 * $ B( LDB, * ), BB( LDB, * ), BP( * ), D( * ),
25 * $ RESULT( * ), WORK( * ), Z( LDZ, * )
26 * ..
27 *
28 *
29 *> \par Purpose:
30 * =============
31 *>
32 *> \verbatim
33 *>
34 *> SDRVSG checks the real symmetric generalized eigenproblem
35 *> drivers.
36 *>
37 *> SSYGV computes all eigenvalues and, optionally,
38 *> eigenvectors of a real symmetric-definite generalized
39 *> eigenproblem.
40 *>
41 *> SSYGVD computes all eigenvalues and, optionally,
42 *> eigenvectors of a real symmetric-definite generalized
43 *> eigenproblem using a divide and conquer algorithm.
44 *>
45 *> SSYGVX computes selected eigenvalues and, optionally,
46 *> eigenvectors of a real symmetric-definite generalized
47 *> eigenproblem.
48 *>
49 *> SSPGV computes all eigenvalues and, optionally,
50 *> eigenvectors of a real symmetric-definite generalized
51 *> eigenproblem in packed storage.
52 *>
53 *> SSPGVD computes all eigenvalues and, optionally,
54 *> eigenvectors of a real symmetric-definite generalized
55 *> eigenproblem in packed storage using a divide and
56 *> conquer algorithm.
57 *>
58 *> SSPGVX computes selected eigenvalues and, optionally,
59 *> eigenvectors of a real symmetric-definite generalized
60 *> eigenproblem in packed storage.
61 *>
62 *> SSBGV computes all eigenvalues and, optionally,
63 *> eigenvectors of a real symmetric-definite banded
64 *> generalized eigenproblem.
65 *>
66 *> SSBGVD computes all eigenvalues and, optionally,
67 *> eigenvectors of a real symmetric-definite banded
68 *> generalized eigenproblem using a divide and conquer
69 *> algorithm.
70 *>
71 *> SSBGVX computes selected eigenvalues and, optionally,
72 *> eigenvectors of a real symmetric-definite banded
73 *> generalized eigenproblem.
74 *>
75 *> When SDRVSG is called, a number of matrix "sizes" ("n's") and a
76 *> number of matrix "types" are specified. For each size ("n")
77 *> and each type of matrix, one matrix A of the given type will be
78 *> generated; a random well-conditioned matrix B is also generated
79 *> and the pair (A,B) is used to test the drivers.
80 *>
81 *> For each pair (A,B), the following tests are performed:
82 *>
83 *> (1) SSYGV with ITYPE = 1 and UPLO ='U':
84 *>
85 *> | A Z - B Z D | / ( |A| |Z| n ulp )
86 *>
87 *> (2) as (1) but calling SSPGV
88 *> (3) as (1) but calling SSBGV
89 *> (4) as (1) but with UPLO = 'L'
90 *> (5) as (4) but calling SSPGV
91 *> (6) as (4) but calling SSBGV
92 *>
93 *> (7) SSYGV with ITYPE = 2 and UPLO ='U':
94 *>
95 *> | A B Z - Z D | / ( |A| |Z| n ulp )
96 *>
97 *> (8) as (7) but calling SSPGV
98 *> (9) as (7) but with UPLO = 'L'
99 *> (10) as (9) but calling SSPGV
100 *>
101 *> (11) SSYGV with ITYPE = 3 and UPLO ='U':
102 *>
103 *> | B A Z - Z D | / ( |A| |Z| n ulp )
104 *>
105 *> (12) as (11) but calling SSPGV
106 *> (13) as (11) but with UPLO = 'L'
107 *> (14) as (13) but calling SSPGV
108 *>
109 *> SSYGVD, SSPGVD and SSBGVD performed the same 14 tests.
110 *>
111 *> SSYGVX, SSPGVX and SSBGVX performed the above 14 tests with
112 *> the parameter RANGE = 'A', 'N' and 'I', respectively.
113 *>
114 *> The "sizes" are specified by an array NN(1:NSIZES); the value
115 *> of each element NN(j) specifies one size.
116 *> The "types" are specified by a logical array DOTYPE( 1:NTYPES );
117 *> if DOTYPE(j) is .TRUE., then matrix type "j" will be generated.
118 *> This type is used for the matrix A which has half-bandwidth KA.
119 *> B is generated as a well-conditioned positive definite matrix
120 *> with half-bandwidth KB (<= KA).
121 *> Currently, the list of possible types for A is:
122 *>
123 *> (1) The zero matrix.
124 *> (2) The identity matrix.
125 *>
126 *> (3) A diagonal matrix with evenly spaced entries
127 *> 1, ..., ULP and random signs.
128 *> (ULP = (first number larger than 1) - 1 )
129 *> (4) A diagonal matrix with geometrically spaced entries
130 *> 1, ..., ULP and random signs.
131 *> (5) A diagonal matrix with "clustered" entries
132 *> 1, ULP, ..., ULP and random signs.
133 *>
134 *> (6) Same as (4), but multiplied by SQRT( overflow threshold )
135 *> (7) Same as (4), but multiplied by SQRT( underflow threshold )
136 *>
137 *> (8) A matrix of the form U* D U, where U is orthogonal and
138 *> D has evenly spaced entries 1, ..., ULP with random signs
139 *> on the diagonal.
140 *>
141 *> (9) A matrix of the form U* D U, where U is orthogonal and
142 *> D has geometrically spaced entries 1, ..., ULP with random
143 *> signs on the diagonal.
144 *>
145 *> (10) A matrix of the form U* D U, where U is orthogonal and
146 *> D has "clustered" entries 1, ULP,..., ULP with random
147 *> signs on the diagonal.
148 *>
149 *> (11) Same as (8), but multiplied by SQRT( overflow threshold )
150 *> (12) Same as (8), but multiplied by SQRT( underflow threshold )
151 *>
152 *> (13) symmetric matrix with random entries chosen from (-1,1).
153 *> (14) Same as (13), but multiplied by SQRT( overflow threshold )
154 *> (15) Same as (13), but multiplied by SQRT( underflow threshold)
155 *>
156 *> (16) Same as (8), but with KA = 1 and KB = 1
157 *> (17) Same as (8), but with KA = 2 and KB = 1
158 *> (18) Same as (8), but with KA = 2 and KB = 2
159 *> (19) Same as (8), but with KA = 3 and KB = 1
160 *> (20) Same as (8), but with KA = 3 and KB = 2
161 *> (21) Same as (8), but with KA = 3 and KB = 3
162 *> \endverbatim
163 *
164 * Arguments:
165 * ==========
166 *
167 *> \verbatim
168 *> NSIZES INTEGER
169 *> The number of sizes of matrices to use. If it is zero,
170 *> SDRVSG does nothing. It must be at least zero.
171 *> Not modified.
172 *>
173 *> NN INTEGER array, dimension (NSIZES)
174 *> An array containing the sizes to be used for the matrices.
175 *> Zero values will be skipped. The values must be at least
176 *> zero.
177 *> Not modified.
178 *>
179 *> NTYPES INTEGER
180 *> The number of elements in DOTYPE. If it is zero, SDRVSG
181 *> does nothing. It must be at least zero. If it is MAXTYP+1
182 *> and NSIZES is 1, then an additional type, MAXTYP+1 is
183 *> defined, which is to use whatever matrix is in A. This
184 *> is only useful if DOTYPE(1:MAXTYP) is .FALSE. and
185 *> DOTYPE(MAXTYP+1) is .TRUE. .
186 *> Not modified.
187 *>
188 *> DOTYPE LOGICAL array, dimension (NTYPES)
189 *> If DOTYPE(j) is .TRUE., then for each size in NN a
190 *> matrix of that size and of type j will be generated.
191 *> If NTYPES is smaller than the maximum number of types
192 *> defined (PARAMETER MAXTYP), then types NTYPES+1 through
193 *> MAXTYP will not be generated. If NTYPES is larger
194 *> than MAXTYP, DOTYPE(MAXTYP+1) through DOTYPE(NTYPES)
195 *> will be ignored.
196 *> Not modified.
197 *>
198 *> ISEED INTEGER array, dimension (4)
199 *> On entry ISEED specifies the seed of the random number
200 *> generator. The array elements should be between 0 and 4095;
201 *> if not they will be reduced mod 4096. Also, ISEED(4) must
202 *> be odd. The random number generator uses a linear
203 *> congruential sequence limited to small integers, and so
204 *> should produce machine independent random numbers. The
205 *> values of ISEED are changed on exit, and can be used in the
206 *> next call to SDRVSG to continue the same random number
207 *> sequence.
208 *> Modified.
209 *>
210 *> THRESH REAL
211 *> A test will count as "failed" if the "error", computed as
212 *> described above, exceeds THRESH. Note that the error
213 *> is scaled to be O(1), so THRESH should be a reasonably
214 *> small multiple of 1, e.g., 10 or 100. In particular,
215 *> it should not depend on the precision (single vs. double)
216 *> or the size of the matrix. It must be at least zero.
217 *> Not modified.
218 *>
219 *> NOUNIT INTEGER
220 *> The FORTRAN unit number for printing out error messages
221 *> (e.g., if a routine returns IINFO not equal to 0.)
222 *> Not modified.
223 *>
224 *> A REAL array, dimension (LDA , max(NN))
225 *> Used to hold the matrix whose eigenvalues are to be
226 *> computed. On exit, A contains the last matrix actually
227 *> used.
228 *> Modified.
229 *>
230 *> LDA INTEGER
231 *> The leading dimension of A and AB. It must be at
232 *> least 1 and at least max( NN ).
233 *> Not modified.
234 *>
235 *> B REAL array, dimension (LDB , max(NN))
236 *> Used to hold the symmetric positive definite matrix for
237 *> the generailzed problem.
238 *> On exit, B contains the last matrix actually
239 *> used.
240 *> Modified.
241 *>
242 *> LDB INTEGER
243 *> The leading dimension of B and BB. It must be at
244 *> least 1 and at least max( NN ).
245 *> Not modified.
246 *>
247 *> D REAL array, dimension (max(NN))
248 *> The eigenvalues of A. On exit, the eigenvalues in D
249 *> correspond with the matrix in A.
250 *> Modified.
251 *>
252 *> Z REAL array, dimension (LDZ, max(NN))
253 *> The matrix of eigenvectors.
254 *> Modified.
255 *>
256 *> LDZ INTEGER
257 *> The leading dimension of Z. It must be at least 1 and
258 *> at least max( NN ).
259 *> Not modified.
260 *>
261 *> AB REAL array, dimension (LDA, max(NN))
262 *> Workspace.
263 *> Modified.
264 *>
265 *> BB REAL array, dimension (LDB, max(NN))
266 *> Workspace.
267 *> Modified.
268 *>
269 *> AP REAL array, dimension (max(NN)**2)
270 *> Workspace.
271 *> Modified.
272 *>
273 *> BP REAL array, dimension (max(NN)**2)
274 *> Workspace.
275 *> Modified.
276 *>
277 *> WORK REAL array, dimension (NWORK)
278 *> Workspace.
279 *> Modified.
280 *>
281 *> NWORK INTEGER
282 *> The number of entries in WORK. This must be at least
283 *> 1+5*N+2*N*lg(N)+3*N**2 where N = max( NN(j) ) and
284 *> lg( N ) = smallest integer k such that 2**k >= N.
285 *> Not modified.
286 *>
287 *> IWORK INTEGER array, dimension (LIWORK)
288 *> Workspace.
289 *> Modified.
290 *>
291 *> LIWORK INTEGER
292 *> The number of entries in WORK. This must be at least 6*N.
293 *> Not modified.
294 *>
295 *> RESULT REAL array, dimension (70)
296 *> The values computed by the 70 tests described above.
297 *> Modified.
298 *>
299 *> INFO INTEGER
300 *> If 0, then everything ran OK.
301 *> -1: NSIZES < 0
302 *> -2: Some NN(j) < 0
303 *> -3: NTYPES < 0
304 *> -5: THRESH < 0
305 *> -9: LDA < 1 or LDA < NMAX, where NMAX is max( NN(j) ).
306 *> -16: LDZ < 1 or LDZ < NMAX.
307 *> -21: NWORK too small.
308 *> -23: LIWORK too small.
309 *> If SLATMR, SLATMS, SSYGV, SSPGV, SSBGV, SSYGVD, SSPGVD,
310 *> SSBGVD, SSYGVX, SSPGVX or SSBGVX returns an error code,
311 *> the absolute value of it is returned.
312 *> Modified.
313 *>
314 *> ----------------------------------------------------------------------
315 *>
316 *> Some Local Variables and Parameters:
317 *> ---- ----- --------- --- ----------
318 *> ZERO, ONE Real 0 and 1.
319 *> MAXTYP The number of types defined.
320 *> NTEST The number of tests that have been run
321 *> on this matrix.
322 *> NTESTT The total number of tests for this call.
323 *> NMAX Largest value in NN.
324 *> NMATS The number of matrices generated so far.
325 *> NERRS The number of tests which have exceeded THRESH
326 *> so far (computed by SLAFTS).
327 *> COND, IMODE Values to be passed to the matrix generators.
328 *> ANORM Norm of A; passed to matrix generators.
329 *>
330 *> OVFL, UNFL Overflow and underflow thresholds.
331 *> ULP, ULPINV Finest relative precision and its inverse.
332 *> RTOVFL, RTUNFL Square roots of the previous 2 values.
333 *> The following four arrays decode JTYPE:
334 *> KTYPE(j) The general type (1-10) for type "j".
335 *> KMODE(j) The MODE value to be passed to the matrix
336 *> generator for type "j".
337 *> KMAGN(j) The order of magnitude ( O(1),
338 *> O(overflow^(1/2) ), O(underflow^(1/2) )
339 *> \endverbatim
340 *
341 * Authors:
342 * ========
343 *
344 *> \author Univ. of Tennessee
345 *> \author Univ. of California Berkeley
346 *> \author Univ. of Colorado Denver
347 *> \author NAG Ltd.
348 *
349 *> \date December 2016
350 *
351 *> \ingroup single_eig
352 *
353 * =====================================================================
354  SUBROUTINE sdrvsg( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
355  $ NOUNIT, A, LDA, B, LDB, D, Z, LDZ, AB, BB, AP,
356  $ BP, WORK, NWORK, IWORK, LIWORK, RESULT, INFO )
357 *
358 * -- LAPACK test routine (version 3.7.0) --
359 * -- LAPACK is a software package provided by Univ. of Tennessee, --
360 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
361 * December 2016
362 *
363 * .. Scalar Arguments ..
364  INTEGER INFO, LDA, LDB, LDZ, LIWORK, NOUNIT, NSIZES,
365  $ ntypes, nwork
366  REAL THRESH
367 * ..
368 * .. Array Arguments ..
369  LOGICAL DOTYPE( * )
370  INTEGER ISEED( 4 ), IWORK( * ), NN( * )
371  REAL A( lda, * ), AB( lda, * ), AP( * ),
372  $ b( ldb, * ), bb( ldb, * ), bp( * ), d( * ),
373  $ result( * ), work( * ), z( ldz, * )
374 * ..
375 *
376 * =====================================================================
377 *
378 * .. Parameters ..
379  REAL ZERO, ONE, TEN
380  parameter( zero = 0.0e0, one = 1.0e0, ten = 10.0e0 )
381  INTEGER MAXTYP
382  parameter( maxtyp = 21 )
383 * ..
384 * .. Local Scalars ..
385  LOGICAL BADNN
386  CHARACTER UPLO
387  INTEGER I, IBTYPE, IBUPLO, IINFO, IJ, IL, IMODE, ITEMP,
388  $ itype, iu, j, jcol, jsize, jtype, ka, ka9, kb,
389  $ kb9, m, mtypes, n, nerrs, nmats, nmax, ntest,
390  $ ntestt
391  REAL ABSTOL, ANINV, ANORM, COND, OVFL, RTOVFL,
392  $ rtunfl, ulp, ulpinv, unfl, vl, vu
393 * ..
394 * .. Local Arrays ..
395  INTEGER IDUMMA( 1 ), IOLDSD( 4 ), ISEED2( 4 ),
396  $ kmagn( maxtyp ), kmode( maxtyp ),
397  $ ktype( maxtyp )
398 * ..
399 * .. External Functions ..
400  LOGICAL LSAME
401  REAL SLAMCH, SLARND
402  EXTERNAL lsame, slamch, slarnd
403 * ..
404 * .. External Subroutines ..
405  EXTERNAL slabad, slacpy, slafts, slaset, slasum, slatmr,
406  $ slatms, ssbgv, ssbgvd, ssbgvx, ssgt01, sspgv,
407  $ sspgvd, sspgvx, ssygv, ssygvd, ssygvx, xerbla
408 * ..
409 * .. Intrinsic Functions ..
410  INTRINSIC abs, max, min, REAL, SQRT
411 * ..
412 * .. Data statements ..
413  DATA ktype / 1, 2, 5*4, 5*5, 3*8, 6*9 /
414  DATA kmagn / 2*1, 1, 1, 1, 2, 3, 1, 1, 1, 2, 3, 1,
415  $ 2, 3, 6*1 /
416  DATA kmode / 2*0, 4, 3, 1, 4, 4, 4, 3, 1, 4, 4, 0,
417  $ 0, 0, 6*4 /
418 * ..
419 * .. Executable Statements ..
420 *
421 * 1) Check for errors
422 *
423  ntestt = 0
424  info = 0
425 *
426  badnn = .false.
427  nmax = 0
428  DO 10 j = 1, nsizes
429  nmax = max( nmax, nn( j ) )
430  IF( nn( j ).LT.0 )
431  $ badnn = .true.
432  10 CONTINUE
433 *
434 * Check for errors
435 *
436  IF( nsizes.LT.0 ) THEN
437  info = -1
438  ELSE IF( badnn ) THEN
439  info = -2
440  ELSE IF( ntypes.LT.0 ) THEN
441  info = -3
442  ELSE IF( lda.LE.1 .OR. lda.LT.nmax ) THEN
443  info = -9
444  ELSE IF( ldz.LE.1 .OR. ldz.LT.nmax ) THEN
445  info = -16
446  ELSE IF( 2*max( nmax, 3 )**2.GT.nwork ) THEN
447  info = -21
448  ELSE IF( 2*max( nmax, 3 )**2.GT.liwork ) THEN
449  info = -23
450  END IF
451 *
452  IF( info.NE.0 ) THEN
453  CALL xerbla( 'SDRVSG', -info )
454  RETURN
455  END IF
456 *
457 * Quick return if possible
458 *
459  IF( nsizes.EQ.0 .OR. ntypes.EQ.0 )
460  $ RETURN
461 *
462 * More Important constants
463 *
464  unfl = slamch( 'Safe minimum' )
465  ovfl = slamch( 'Overflow' )
466  CALL slabad( unfl, ovfl )
467  ulp = slamch( 'Epsilon' )*slamch( 'Base' )
468  ulpinv = one / ulp
469  rtunfl = sqrt( unfl )
470  rtovfl = sqrt( ovfl )
471 *
472  DO 20 i = 1, 4
473  iseed2( i ) = iseed( i )
474  20 CONTINUE
475 *
476 * Loop over sizes, types
477 *
478  nerrs = 0
479  nmats = 0
480 *
481  DO 650 jsize = 1, nsizes
482  n = nn( jsize )
483  aninv = one / REAL( MAX( 1, N ) )
484 *
485  IF( nsizes.NE.1 ) THEN
486  mtypes = min( maxtyp, ntypes )
487  ELSE
488  mtypes = min( maxtyp+1, ntypes )
489  END IF
490 *
491  ka9 = 0
492  kb9 = 0
493  DO 640 jtype = 1, mtypes
494  IF( .NOT.dotype( jtype ) )
495  $ GO TO 640
496  nmats = nmats + 1
497  ntest = 0
498 *
499  DO 30 j = 1, 4
500  ioldsd( j ) = iseed( j )
501  30 CONTINUE
502 *
503 * 2) Compute "A"
504 *
505 * Control parameters:
506 *
507 * KMAGN KMODE KTYPE
508 * =1 O(1) clustered 1 zero
509 * =2 large clustered 2 identity
510 * =3 small exponential (none)
511 * =4 arithmetic diagonal, w/ eigenvalues
512 * =5 random log hermitian, w/ eigenvalues
513 * =6 random (none)
514 * =7 random diagonal
515 * =8 random hermitian
516 * =9 banded, w/ eigenvalues
517 *
518  IF( mtypes.GT.maxtyp )
519  $ GO TO 90
520 *
521  itype = ktype( jtype )
522  imode = kmode( jtype )
523 *
524 * Compute norm
525 *
526  GO TO ( 40, 50, 60 )kmagn( jtype )
527 *
528  40 CONTINUE
529  anorm = one
530  GO TO 70
531 *
532  50 CONTINUE
533  anorm = ( rtovfl*ulp )*aninv
534  GO TO 70
535 *
536  60 CONTINUE
537  anorm = rtunfl*n*ulpinv
538  GO TO 70
539 *
540  70 CONTINUE
541 *
542  iinfo = 0
543  cond = ulpinv
544 *
545 * Special Matrices -- Identity & Jordan block
546 *
547  IF( itype.EQ.1 ) THEN
548 *
549 * Zero
550 *
551  ka = 0
552  kb = 0
553  CALL slaset( 'Full', lda, n, zero, zero, a, lda )
554 *
555  ELSE IF( itype.EQ.2 ) THEN
556 *
557 * Identity
558 *
559  ka = 0
560  kb = 0
561  CALL slaset( 'Full', lda, n, zero, zero, a, lda )
562  DO 80 jcol = 1, n
563  a( jcol, jcol ) = anorm
564  80 CONTINUE
565 *
566  ELSE IF( itype.EQ.4 ) THEN
567 *
568 * Diagonal Matrix, [Eigen]values Specified
569 *
570  ka = 0
571  kb = 0
572  CALL slatms( n, n, 'S', iseed, 'S', work, imode, cond,
573  $ anorm, 0, 0, 'N', a, lda, work( n+1 ),
574  $ iinfo )
575 *
576  ELSE IF( itype.EQ.5 ) THEN
577 *
578 * symmetric, eigenvalues specified
579 *
580  ka = max( 0, n-1 )
581  kb = ka
582  CALL slatms( n, n, 'S', iseed, 'S', work, imode, cond,
583  $ anorm, n, n, 'N', a, lda, work( n+1 ),
584  $ iinfo )
585 *
586  ELSE IF( itype.EQ.7 ) THEN
587 *
588 * Diagonal, random eigenvalues
589 *
590  ka = 0
591  kb = 0
592  CALL slatmr( n, n, 'S', iseed, 'S', work, 6, one, one,
593  $ 'T', 'N', work( n+1 ), 1, one,
594  $ work( 2*n+1 ), 1, one, 'N', idumma, 0, 0,
595  $ zero, anorm, 'NO', a, lda, iwork, iinfo )
596 *
597  ELSE IF( itype.EQ.8 ) THEN
598 *
599 * symmetric, random eigenvalues
600 *
601  ka = max( 0, n-1 )
602  kb = ka
603  CALL slatmr( n, n, 'S', iseed, 'H', work, 6, one, one,
604  $ 'T', 'N', work( n+1 ), 1, one,
605  $ work( 2*n+1 ), 1, one, 'N', idumma, n, n,
606  $ zero, anorm, 'NO', a, lda, iwork, iinfo )
607 *
608  ELSE IF( itype.EQ.9 ) THEN
609 *
610 * symmetric banded, eigenvalues specified
611 *
612 * The following values are used for the half-bandwidths:
613 *
614 * ka = 1 kb = 1
615 * ka = 2 kb = 1
616 * ka = 2 kb = 2
617 * ka = 3 kb = 1
618 * ka = 3 kb = 2
619 * ka = 3 kb = 3
620 *
621  kb9 = kb9 + 1
622  IF( kb9.GT.ka9 ) THEN
623  ka9 = ka9 + 1
624  kb9 = 1
625  END IF
626  ka = max( 0, min( n-1, ka9 ) )
627  kb = max( 0, min( n-1, kb9 ) )
628  CALL slatms( n, n, 'S', iseed, 'S', work, imode, cond,
629  $ anorm, ka, ka, 'N', a, lda, work( n+1 ),
630  $ iinfo )
631 *
632  ELSE
633 *
634  iinfo = 1
635  END IF
636 *
637  IF( iinfo.NE.0 ) THEN
638  WRITE( nounit, fmt = 9999 )'Generator', iinfo, n, jtype,
639  $ ioldsd
640  info = abs( iinfo )
641  RETURN
642  END IF
643 *
644  90 CONTINUE
645 *
646  abstol = unfl + unfl
647  IF( n.LE.1 ) THEN
648  il = 1
649  iu = n
650  ELSE
651  il = 1 + ( n-1 )*slarnd( 1, iseed2 )
652  iu = 1 + ( n-1 )*slarnd( 1, iseed2 )
653  IF( il.GT.iu ) THEN
654  itemp = il
655  il = iu
656  iu = itemp
657  END IF
658  END IF
659 *
660 * 3) Call SSYGV, SSPGV, SSBGV, SSYGVD, SSPGVD, SSBGVD,
661 * SSYGVX, SSPGVX, and SSBGVX, do tests.
662 *
663 * loop over the three generalized problems
664 * IBTYPE = 1: A*x = (lambda)*B*x
665 * IBTYPE = 2: A*B*x = (lambda)*x
666 * IBTYPE = 3: B*A*x = (lambda)*x
667 *
668  DO 630 ibtype = 1, 3
669 *
670 * loop over the setting UPLO
671 *
672  DO 620 ibuplo = 1, 2
673  IF( ibuplo.EQ.1 )
674  $ uplo = 'U'
675  IF( ibuplo.EQ.2 )
676  $ uplo = 'L'
677 *
678 * Generate random well-conditioned positive definite
679 * matrix B, of bandwidth not greater than that of A.
680 *
681  CALL slatms( n, n, 'U', iseed, 'P', work, 5, ten, one,
682  $ kb, kb, uplo, b, ldb, work( n+1 ),
683  $ iinfo )
684 *
685 * Test SSYGV
686 *
687  ntest = ntest + 1
688 *
689  CALL slacpy( ' ', n, n, a, lda, z, ldz )
690  CALL slacpy( uplo, n, n, b, ldb, bb, ldb )
691 *
692  CALL ssygv( ibtype, 'V', uplo, n, z, ldz, bb, ldb, d,
693  $ work, nwork, iinfo )
694  IF( iinfo.NE.0 ) THEN
695  WRITE( nounit, fmt = 9999 )'SSYGV(V,' // uplo //
696  $ ')', iinfo, n, jtype, ioldsd
697  info = abs( iinfo )
698  IF( iinfo.LT.0 ) THEN
699  RETURN
700  ELSE
701  result( ntest ) = ulpinv
702  GO TO 100
703  END IF
704  END IF
705 *
706 * Do Test
707 *
708  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
709  $ ldz, d, work, result( ntest ) )
710 *
711 * Test SSYGVD
712 *
713  ntest = ntest + 1
714 *
715  CALL slacpy( ' ', n, n, a, lda, z, ldz )
716  CALL slacpy( uplo, n, n, b, ldb, bb, ldb )
717 *
718  CALL ssygvd( ibtype, 'V', uplo, n, z, ldz, bb, ldb, d,
719  $ work, nwork, iwork, liwork, iinfo )
720  IF( iinfo.NE.0 ) THEN
721  WRITE( nounit, fmt = 9999 )'SSYGVD(V,' // uplo //
722  $ ')', iinfo, n, jtype, ioldsd
723  info = abs( iinfo )
724  IF( iinfo.LT.0 ) THEN
725  RETURN
726  ELSE
727  result( ntest ) = ulpinv
728  GO TO 100
729  END IF
730  END IF
731 *
732 * Do Test
733 *
734  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
735  $ ldz, d, work, result( ntest ) )
736 *
737 * Test SSYGVX
738 *
739  ntest = ntest + 1
740 *
741  CALL slacpy( ' ', n, n, a, lda, ab, lda )
742  CALL slacpy( uplo, n, n, b, ldb, bb, ldb )
743 *
744  CALL ssygvx( ibtype, 'V', 'A', uplo, n, ab, lda, bb,
745  $ ldb, vl, vu, il, iu, abstol, m, d, z,
746  $ ldz, work, nwork, iwork( n+1 ), iwork,
747  $ iinfo )
748  IF( iinfo.NE.0 ) THEN
749  WRITE( nounit, fmt = 9999 )'SSYGVX(V,A' // uplo //
750  $ ')', iinfo, n, jtype, ioldsd
751  info = abs( iinfo )
752  IF( iinfo.LT.0 ) THEN
753  RETURN
754  ELSE
755  result( ntest ) = ulpinv
756  GO TO 100
757  END IF
758  END IF
759 *
760 * Do Test
761 *
762  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
763  $ ldz, d, work, result( ntest ) )
764 *
765  ntest = ntest + 1
766 *
767  CALL slacpy( ' ', n, n, a, lda, ab, lda )
768  CALL slacpy( uplo, n, n, b, ldb, bb, ldb )
769 *
770 * since we do not know the exact eigenvalues of this
771 * eigenpair, we just set VL and VU as constants.
772 * It is quite possible that there are no eigenvalues
773 * in this interval.
774 *
775  vl = zero
776  vu = anorm
777  CALL ssygvx( ibtype, 'V', 'V', uplo, n, ab, lda, bb,
778  $ ldb, vl, vu, il, iu, abstol, m, d, z,
779  $ ldz, work, nwork, iwork( n+1 ), iwork,
780  $ iinfo )
781  IF( iinfo.NE.0 ) THEN
782  WRITE( nounit, fmt = 9999 )'SSYGVX(V,V,' //
783  $ uplo // ')', iinfo, n, jtype, ioldsd
784  info = abs( iinfo )
785  IF( iinfo.LT.0 ) THEN
786  RETURN
787  ELSE
788  result( ntest ) = ulpinv
789  GO TO 100
790  END IF
791  END IF
792 *
793 * Do Test
794 *
795  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
796  $ ldz, d, work, result( ntest ) )
797 *
798  ntest = ntest + 1
799 *
800  CALL slacpy( ' ', n, n, a, lda, ab, lda )
801  CALL slacpy( uplo, n, n, b, ldb, bb, ldb )
802 *
803  CALL ssygvx( ibtype, 'V', 'I', uplo, n, ab, lda, bb,
804  $ ldb, vl, vu, il, iu, abstol, m, d, z,
805  $ ldz, work, nwork, iwork( n+1 ), iwork,
806  $ iinfo )
807  IF( iinfo.NE.0 ) THEN
808  WRITE( nounit, fmt = 9999 )'SSYGVX(V,I,' //
809  $ uplo // ')', iinfo, n, jtype, ioldsd
810  info = abs( iinfo )
811  IF( iinfo.LT.0 ) THEN
812  RETURN
813  ELSE
814  result( ntest ) = ulpinv
815  GO TO 100
816  END IF
817  END IF
818 *
819 * Do Test
820 *
821  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
822  $ ldz, d, work, result( ntest ) )
823 *
824  100 CONTINUE
825 *
826 * Test SSPGV
827 *
828  ntest = ntest + 1
829 *
830 * Copy the matrices into packed storage.
831 *
832  IF( lsame( uplo, 'U' ) ) THEN
833  ij = 1
834  DO 120 j = 1, n
835  DO 110 i = 1, j
836  ap( ij ) = a( i, j )
837  bp( ij ) = b( i, j )
838  ij = ij + 1
839  110 CONTINUE
840  120 CONTINUE
841  ELSE
842  ij = 1
843  DO 140 j = 1, n
844  DO 130 i = j, n
845  ap( ij ) = a( i, j )
846  bp( ij ) = b( i, j )
847  ij = ij + 1
848  130 CONTINUE
849  140 CONTINUE
850  END IF
851 *
852  CALL sspgv( ibtype, 'V', uplo, n, ap, bp, d, z, ldz,
853  $ work, iinfo )
854  IF( iinfo.NE.0 ) THEN
855  WRITE( nounit, fmt = 9999 )'SSPGV(V,' // uplo //
856  $ ')', iinfo, n, jtype, ioldsd
857  info = abs( iinfo )
858  IF( iinfo.LT.0 ) THEN
859  RETURN
860  ELSE
861  result( ntest ) = ulpinv
862  GO TO 310
863  END IF
864  END IF
865 *
866 * Do Test
867 *
868  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
869  $ ldz, d, work, result( ntest ) )
870 *
871 * Test SSPGVD
872 *
873  ntest = ntest + 1
874 *
875 * Copy the matrices into packed storage.
876 *
877  IF( lsame( uplo, 'U' ) ) THEN
878  ij = 1
879  DO 160 j = 1, n
880  DO 150 i = 1, j
881  ap( ij ) = a( i, j )
882  bp( ij ) = b( i, j )
883  ij = ij + 1
884  150 CONTINUE
885  160 CONTINUE
886  ELSE
887  ij = 1
888  DO 180 j = 1, n
889  DO 170 i = j, n
890  ap( ij ) = a( i, j )
891  bp( ij ) = b( i, j )
892  ij = ij + 1
893  170 CONTINUE
894  180 CONTINUE
895  END IF
896 *
897  CALL sspgvd( ibtype, 'V', uplo, n, ap, bp, d, z, ldz,
898  $ work, nwork, iwork, liwork, iinfo )
899  IF( iinfo.NE.0 ) THEN
900  WRITE( nounit, fmt = 9999 )'SSPGVD(V,' // uplo //
901  $ ')', iinfo, n, jtype, ioldsd
902  info = abs( iinfo )
903  IF( iinfo.LT.0 ) THEN
904  RETURN
905  ELSE
906  result( ntest ) = ulpinv
907  GO TO 310
908  END IF
909  END IF
910 *
911 * Do Test
912 *
913  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
914  $ ldz, d, work, result( ntest ) )
915 *
916 * Test SSPGVX
917 *
918  ntest = ntest + 1
919 *
920 * Copy the matrices into packed storage.
921 *
922  IF( lsame( uplo, 'U' ) ) THEN
923  ij = 1
924  DO 200 j = 1, n
925  DO 190 i = 1, j
926  ap( ij ) = a( i, j )
927  bp( ij ) = b( i, j )
928  ij = ij + 1
929  190 CONTINUE
930  200 CONTINUE
931  ELSE
932  ij = 1
933  DO 220 j = 1, n
934  DO 210 i = j, n
935  ap( ij ) = a( i, j )
936  bp( ij ) = b( i, j )
937  ij = ij + 1
938  210 CONTINUE
939  220 CONTINUE
940  END IF
941 *
942  CALL sspgvx( ibtype, 'V', 'A', uplo, n, ap, bp, vl,
943  $ vu, il, iu, abstol, m, d, z, ldz, work,
944  $ iwork( n+1 ), iwork, info )
945  IF( iinfo.NE.0 ) THEN
946  WRITE( nounit, fmt = 9999 )'SSPGVX(V,A' // uplo //
947  $ ')', iinfo, n, jtype, ioldsd
948  info = abs( iinfo )
949  IF( iinfo.LT.0 ) THEN
950  RETURN
951  ELSE
952  result( ntest ) = ulpinv
953  GO TO 310
954  END IF
955  END IF
956 *
957 * Do Test
958 *
959  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
960  $ ldz, d, work, result( ntest ) )
961 *
962  ntest = ntest + 1
963 *
964 * Copy the matrices into packed storage.
965 *
966  IF( lsame( uplo, 'U' ) ) THEN
967  ij = 1
968  DO 240 j = 1, n
969  DO 230 i = 1, j
970  ap( ij ) = a( i, j )
971  bp( ij ) = b( i, j )
972  ij = ij + 1
973  230 CONTINUE
974  240 CONTINUE
975  ELSE
976  ij = 1
977  DO 260 j = 1, n
978  DO 250 i = j, n
979  ap( ij ) = a( i, j )
980  bp( ij ) = b( i, j )
981  ij = ij + 1
982  250 CONTINUE
983  260 CONTINUE
984  END IF
985 *
986  vl = zero
987  vu = anorm
988  CALL sspgvx( ibtype, 'V', 'V', uplo, n, ap, bp, vl,
989  $ vu, il, iu, abstol, m, d, z, ldz, work,
990  $ iwork( n+1 ), iwork, info )
991  IF( iinfo.NE.0 ) THEN
992  WRITE( nounit, fmt = 9999 )'SSPGVX(V,V' // uplo //
993  $ ')', iinfo, n, jtype, ioldsd
994  info = abs( iinfo )
995  IF( iinfo.LT.0 ) THEN
996  RETURN
997  ELSE
998  result( ntest ) = ulpinv
999  GO TO 310
1000  END IF
1001  END IF
1002 *
1003 * Do Test
1004 *
1005  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
1006  $ ldz, d, work, result( ntest ) )
1007 *
1008  ntest = ntest + 1
1009 *
1010 * Copy the matrices into packed storage.
1011 *
1012  IF( lsame( uplo, 'U' ) ) THEN
1013  ij = 1
1014  DO 280 j = 1, n
1015  DO 270 i = 1, j
1016  ap( ij ) = a( i, j )
1017  bp( ij ) = b( i, j )
1018  ij = ij + 1
1019  270 CONTINUE
1020  280 CONTINUE
1021  ELSE
1022  ij = 1
1023  DO 300 j = 1, n
1024  DO 290 i = j, n
1025  ap( ij ) = a( i, j )
1026  bp( ij ) = b( i, j )
1027  ij = ij + 1
1028  290 CONTINUE
1029  300 CONTINUE
1030  END IF
1031 *
1032  CALL sspgvx( ibtype, 'V', 'I', uplo, n, ap, bp, vl,
1033  $ vu, il, iu, abstol, m, d, z, ldz, work,
1034  $ iwork( n+1 ), iwork, info )
1035  IF( iinfo.NE.0 ) THEN
1036  WRITE( nounit, fmt = 9999 )'SSPGVX(V,I' // uplo //
1037  $ ')', iinfo, n, jtype, ioldsd
1038  info = abs( iinfo )
1039  IF( iinfo.LT.0 ) THEN
1040  RETURN
1041  ELSE
1042  result( ntest ) = ulpinv
1043  GO TO 310
1044  END IF
1045  END IF
1046 *
1047 * Do Test
1048 *
1049  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
1050  $ ldz, d, work, result( ntest ) )
1051 *
1052  310 CONTINUE
1053 *
1054  IF( ibtype.EQ.1 ) THEN
1055 *
1056 * TEST SSBGV
1057 *
1058  ntest = ntest + 1
1059 *
1060 * Copy the matrices into band storage.
1061 *
1062  IF( lsame( uplo, 'U' ) ) THEN
1063  DO 340 j = 1, n
1064  DO 320 i = max( 1, j-ka ), j
1065  ab( ka+1+i-j, j ) = a( i, j )
1066  320 CONTINUE
1067  DO 330 i = max( 1, j-kb ), j
1068  bb( kb+1+i-j, j ) = b( i, j )
1069  330 CONTINUE
1070  340 CONTINUE
1071  ELSE
1072  DO 370 j = 1, n
1073  DO 350 i = j, min( n, j+ka )
1074  ab( 1+i-j, j ) = a( i, j )
1075  350 CONTINUE
1076  DO 360 i = j, min( n, j+kb )
1077  bb( 1+i-j, j ) = b( i, j )
1078  360 CONTINUE
1079  370 CONTINUE
1080  END IF
1081 *
1082  CALL ssbgv( 'V', uplo, n, ka, kb, ab, lda, bb, ldb,
1083  $ d, z, ldz, work, iinfo )
1084  IF( iinfo.NE.0 ) THEN
1085  WRITE( nounit, fmt = 9999 )'SSBGV(V,' //
1086  $ uplo // ')', iinfo, n, jtype, ioldsd
1087  info = abs( iinfo )
1088  IF( iinfo.LT.0 ) THEN
1089  RETURN
1090  ELSE
1091  result( ntest ) = ulpinv
1092  GO TO 620
1093  END IF
1094  END IF
1095 *
1096 * Do Test
1097 *
1098  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
1099  $ ldz, d, work, result( ntest ) )
1100 *
1101 * TEST SSBGVD
1102 *
1103  ntest = ntest + 1
1104 *
1105 * Copy the matrices into band storage.
1106 *
1107  IF( lsame( uplo, 'U' ) ) THEN
1108  DO 400 j = 1, n
1109  DO 380 i = max( 1, j-ka ), j
1110  ab( ka+1+i-j, j ) = a( i, j )
1111  380 CONTINUE
1112  DO 390 i = max( 1, j-kb ), j
1113  bb( kb+1+i-j, j ) = b( i, j )
1114  390 CONTINUE
1115  400 CONTINUE
1116  ELSE
1117  DO 430 j = 1, n
1118  DO 410 i = j, min( n, j+ka )
1119  ab( 1+i-j, j ) = a( i, j )
1120  410 CONTINUE
1121  DO 420 i = j, min( n, j+kb )
1122  bb( 1+i-j, j ) = b( i, j )
1123  420 CONTINUE
1124  430 CONTINUE
1125  END IF
1126 *
1127  CALL ssbgvd( 'V', uplo, n, ka, kb, ab, lda, bb,
1128  $ ldb, d, z, ldz, work, nwork, iwork,
1129  $ liwork, iinfo )
1130  IF( iinfo.NE.0 ) THEN
1131  WRITE( nounit, fmt = 9999 )'SSBGVD(V,' //
1132  $ uplo // ')', iinfo, n, jtype, ioldsd
1133  info = abs( iinfo )
1134  IF( iinfo.LT.0 ) THEN
1135  RETURN
1136  ELSE
1137  result( ntest ) = ulpinv
1138  GO TO 620
1139  END IF
1140  END IF
1141 *
1142 * Do Test
1143 *
1144  CALL ssgt01( ibtype, uplo, n, n, a, lda, b, ldb, z,
1145  $ ldz, d, work, result( ntest ) )
1146 *
1147 * Test SSBGVX
1148 *
1149  ntest = ntest + 1
1150 *
1151 * Copy the matrices into band storage.
1152 *
1153  IF( lsame( uplo, 'U' ) ) THEN
1154  DO 460 j = 1, n
1155  DO 440 i = max( 1, j-ka ), j
1156  ab( ka+1+i-j, j ) = a( i, j )
1157  440 CONTINUE
1158  DO 450 i = max( 1, j-kb ), j
1159  bb( kb+1+i-j, j ) = b( i, j )
1160  450 CONTINUE
1161  460 CONTINUE
1162  ELSE
1163  DO 490 j = 1, n
1164  DO 470 i = j, min( n, j+ka )
1165  ab( 1+i-j, j ) = a( i, j )
1166  470 CONTINUE
1167  DO 480 i = j, min( n, j+kb )
1168  bb( 1+i-j, j ) = b( i, j )
1169  480 CONTINUE
1170  490 CONTINUE
1171  END IF
1172 *
1173  CALL ssbgvx( 'V', 'A', uplo, n, ka, kb, ab, lda,
1174  $ bb, ldb, bp, max( 1, n ), vl, vu, il,
1175  $ iu, abstol, m, d, z, ldz, work,
1176  $ iwork( n+1 ), iwork, iinfo )
1177  IF( iinfo.NE.0 ) THEN
1178  WRITE( nounit, fmt = 9999 )'SSBGVX(V,A' //
1179  $ uplo // ')', iinfo, n, jtype, ioldsd
1180  info = abs( iinfo )
1181  IF( iinfo.LT.0 ) THEN
1182  RETURN
1183  ELSE
1184  result( ntest ) = ulpinv
1185  GO TO 620
1186  END IF
1187  END IF
1188 *
1189 * Do Test
1190 *
1191  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
1192  $ ldz, d, work, result( ntest ) )
1193 *
1194 *
1195  ntest = ntest + 1
1196 *
1197 * Copy the matrices into band storage.
1198 *
1199  IF( lsame( uplo, 'U' ) ) THEN
1200  DO 520 j = 1, n
1201  DO 500 i = max( 1, j-ka ), j
1202  ab( ka+1+i-j, j ) = a( i, j )
1203  500 CONTINUE
1204  DO 510 i = max( 1, j-kb ), j
1205  bb( kb+1+i-j, j ) = b( i, j )
1206  510 CONTINUE
1207  520 CONTINUE
1208  ELSE
1209  DO 550 j = 1, n
1210  DO 530 i = j, min( n, j+ka )
1211  ab( 1+i-j, j ) = a( i, j )
1212  530 CONTINUE
1213  DO 540 i = j, min( n, j+kb )
1214  bb( 1+i-j, j ) = b( i, j )
1215  540 CONTINUE
1216  550 CONTINUE
1217  END IF
1218 *
1219  vl = zero
1220  vu = anorm
1221  CALL ssbgvx( 'V', 'V', uplo, n, ka, kb, ab, lda,
1222  $ bb, ldb, bp, max( 1, n ), vl, vu, il,
1223  $ iu, abstol, m, d, z, ldz, work,
1224  $ iwork( n+1 ), iwork, iinfo )
1225  IF( iinfo.NE.0 ) THEN
1226  WRITE( nounit, fmt = 9999 )'SSBGVX(V,V' //
1227  $ uplo // ')', iinfo, n, jtype, ioldsd
1228  info = abs( iinfo )
1229  IF( iinfo.LT.0 ) THEN
1230  RETURN
1231  ELSE
1232  result( ntest ) = ulpinv
1233  GO TO 620
1234  END IF
1235  END IF
1236 *
1237 * Do Test
1238 *
1239  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
1240  $ ldz, d, work, result( ntest ) )
1241 *
1242  ntest = ntest + 1
1243 *
1244 * Copy the matrices into band storage.
1245 *
1246  IF( lsame( uplo, 'U' ) ) THEN
1247  DO 580 j = 1, n
1248  DO 560 i = max( 1, j-ka ), j
1249  ab( ka+1+i-j, j ) = a( i, j )
1250  560 CONTINUE
1251  DO 570 i = max( 1, j-kb ), j
1252  bb( kb+1+i-j, j ) = b( i, j )
1253  570 CONTINUE
1254  580 CONTINUE
1255  ELSE
1256  DO 610 j = 1, n
1257  DO 590 i = j, min( n, j+ka )
1258  ab( 1+i-j, j ) = a( i, j )
1259  590 CONTINUE
1260  DO 600 i = j, min( n, j+kb )
1261  bb( 1+i-j, j ) = b( i, j )
1262  600 CONTINUE
1263  610 CONTINUE
1264  END IF
1265 *
1266  CALL ssbgvx( 'V', 'I', uplo, n, ka, kb, ab, lda,
1267  $ bb, ldb, bp, max( 1, n ), vl, vu, il,
1268  $ iu, abstol, m, d, z, ldz, work,
1269  $ iwork( n+1 ), iwork, iinfo )
1270  IF( iinfo.NE.0 ) THEN
1271  WRITE( nounit, fmt = 9999 )'SSBGVX(V,I' //
1272  $ uplo // ')', iinfo, n, jtype, ioldsd
1273  info = abs( iinfo )
1274  IF( iinfo.LT.0 ) THEN
1275  RETURN
1276  ELSE
1277  result( ntest ) = ulpinv
1278  GO TO 620
1279  END IF
1280  END IF
1281 *
1282 * Do Test
1283 *
1284  CALL ssgt01( ibtype, uplo, n, m, a, lda, b, ldb, z,
1285  $ ldz, d, work, result( ntest ) )
1286 *
1287  END IF
1288 *
1289  620 CONTINUE
1290  630 CONTINUE
1291 *
1292 * End of Loop -- Check for RESULT(j) > THRESH
1293 *
1294  ntestt = ntestt + ntest
1295  CALL slafts( 'SSG', n, n, jtype, ntest, result, ioldsd,
1296  $ thresh, nounit, nerrs )
1297  640 CONTINUE
1298  650 CONTINUE
1299 *
1300 * Summary
1301 *
1302  CALL slasum( 'SSG', nounit, nerrs, ntestt )
1303 *
1304  RETURN
1305 *
1306 * End of SDRVSG
1307 *
1308  9999 FORMAT( ' SDRVSG: ', a, ' returned INFO=', i6, '.', / 9x, 'N=',
1309  $ i6, ', JTYPE=', i6, ', ISEED=(', 3( i5, ',' ), i5, ')' )
1310  END
ssygv
subroutine ssygv(ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, LWORK, INFO)
SSYGV
Definition: ssygv.f:177
sspgv
subroutine sspgv(ITYPE, JOBZ, UPLO, N, AP, BP, W, Z, LDZ, WORK, INFO)
SSPGV
Definition: sspgv.f:162
sspgvd
subroutine sspgvd(ITYPE, JOBZ, UPLO, N, AP, BP, W, Z, LDZ, WORK, LWORK, IWORK, LIWORK, INFO)
SSPGVD
Definition: sspgvd.f:212
ssbgv
subroutine ssbgv(JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, W, Z, LDZ, WORK, INFO)
SSBGV
Definition: ssbgv.f:179
ssgt01
subroutine ssgt01(ITYPE, UPLO, N, M, A, LDA, B, LDB, Z, LDZ, D, WORK, RESULT)
SSGT01
Definition: ssgt01.f:148
slafts
subroutine slafts(TYPE, M, N, IMAT, NTESTS, RESULT, ISEED, THRESH, IOUNIT, IE)
SLAFTS
Definition: slafts.f:101
slatms
subroutine slatms(M, N, DIST, ISEED, SYM, D, MODE, COND, DMAX, KL, KU, PACK, A, LDA, WORK, INFO)
SLATMS
Definition: slatms.f:323
ssbgvd
subroutine ssbgvd(JOBZ, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, W, Z, LDZ, WORK, LWORK, IWORK, LIWORK, INFO)
SSBGVD
Definition: ssbgvd.f:229
xerbla
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:62
slaset
subroutine slaset(UPLO, M, N, ALPHA, BETA, A, LDA)
SLASET initializes the off-diagonal elements and the diagonal elements of a matrix to given values...
Definition: slaset.f:112
ssbgvx
subroutine ssbgvx(JOBZ, RANGE, UPLO, N, KA, KB, AB, LDAB, BB, LDBB, Q, LDQ, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, IFAIL, INFO)
SSBGVX
Definition: ssbgvx.f:296
slabad
subroutine slabad(SMALL, LARGE)
SLABAD
Definition: slabad.f:76
slatmr
subroutine slatmr(M, N, DIST, ISEED, SYM, D, MODE, COND, DMAX, RSIGN, GRADE, DL, MODEL, CONDL, DR, MODER, CONDR, PIVTNG, IPIVOT, KL, KU, SPARSE, ANORM, PACK, A, LDA, IWORK, INFO)
SLATMR
Definition: slatmr.f:473
sspgvx
subroutine sspgvx(ITYPE, JOBZ, RANGE, UPLO, N, AP, BP, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, IFAIL, INFO)
SSPGVX
Definition: sspgvx.f:274
sdrvsg
subroutine sdrvsg(NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH, NOUNIT, A, LDA, B, LDB, D, Z, LDZ, AB, BB, AP, BP, WORK, NWORK, IWORK, LIWORK, RESULT, INFO)
SDRVSG
Definition: sdrvsg.f:357
ssygvd
subroutine ssygvd(ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, LWORK, IWORK, LIWORK, INFO)
SSYGVD
Definition: ssygvd.f:229
slacpy
subroutine slacpy(UPLO, M, N, A, LDA, B, LDB)
SLACPY copies all or part of one two-dimensional array to another.
Definition: slacpy.f:105
slasum
subroutine slasum(TYPE, IOUNIT, IE, NRUN)
SLASUM
Definition: slasum.f:42
ssygvx
subroutine ssygvx(ITYPE, JOBZ, RANGE, UPLO, N, A, LDA, B, LDB, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, LWORK, IWORK, IFAIL, INFO)
SSYGVX
Definition: ssygvx.f:299