LAPACK  3.4.2
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sdrges.f
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1 *> \brief \b SDRGES
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 SDRGES( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
12 * NOUNIT, A, LDA, B, S, T, Q, LDQ, Z, ALPHAR,
13 * ALPHAI, BETA, WORK, LWORK, RESULT, BWORK,
14 * INFO )
15 *
16 * .. Scalar Arguments ..
17 * INTEGER INFO, LDA, LDQ, LWORK, NOUNIT, NSIZES, NTYPES
18 * REAL THRESH
19 * ..
20 * .. Array Arguments ..
21 * LOGICAL BWORK( * ), DOTYPE( * )
22 * INTEGER ISEED( 4 ), NN( * )
23 * REAL A( LDA, * ), ALPHAI( * ), ALPHAR( * ),
24 * $ B( LDA, * ), BETA( * ), Q( LDQ, * ),
25 * $ RESULT( 13 ), S( LDA, * ), T( LDA, * ),
26 * $ WORK( * ), Z( LDQ, * )
27 * ..
28 *
29 *
30 *> \par Purpose:
31 * =============
32 *>
33 *> \verbatim
34 *>
35 *> SDRGES checks the nonsymmetric generalized eigenvalue (Schur form)
36 *> problem driver SGGES.
37 *>
38 *> SGGES factors A and B as Q S Z' and Q T Z' , where ' means
39 *> transpose, T is upper triangular, S is in generalized Schur form
40 *> (block upper triangular, with 1x1 and 2x2 blocks on the diagonal,
41 *> the 2x2 blocks corresponding to complex conjugate pairs of
42 *> generalized eigenvalues), and Q and Z are orthogonal. It also
43 *> computes the generalized eigenvalues (alpha(j),beta(j)), j=1,...,n,
44 *> Thus, w(j) = alpha(j)/beta(j) is a root of the characteristic
45 *> equation
46 *> det( A - w(j) B ) = 0
47 *> Optionally it also reorder the eigenvalues so that a selected
48 *> cluster of eigenvalues appears in the leading diagonal block of the
49 *> Schur forms.
50 *>
51 *> When SDRGES is called, a number of matrix "sizes" ("N's") and a
52 *> number of matrix "TYPES" are specified. For each size ("N")
53 *> and each TYPE of matrix, a pair of matrices (A, B) will be generated
54 *> and used for testing. For each matrix pair, the following 13 tests
55 *> will be performed and compared with the threshhold THRESH except
56 *> the tests (5), (11) and (13).
57 *>
58 *>
59 *> (1) | A - Q S Z' | / ( |A| n ulp ) (no sorting of eigenvalues)
60 *>
61 *>
62 *> (2) | B - Q T Z' | / ( |B| n ulp ) (no sorting of eigenvalues)
63 *>
64 *>
65 *> (3) | I - QQ' | / ( n ulp ) (no sorting of eigenvalues)
66 *>
67 *>
68 *> (4) | I - ZZ' | / ( n ulp ) (no sorting of eigenvalues)
69 *>
70 *> (5) if A is in Schur form (i.e. quasi-triangular form)
71 *> (no sorting of eigenvalues)
72 *>
73 *> (6) if eigenvalues = diagonal blocks of the Schur form (S, T),
74 *> i.e., test the maximum over j of D(j) where:
75 *>
76 *> if alpha(j) is real:
77 *> |alpha(j) - S(j,j)| |beta(j) - T(j,j)|
78 *> D(j) = ------------------------ + -----------------------
79 *> max(|alpha(j)|,|S(j,j)|) max(|beta(j)|,|T(j,j)|)
80 *>
81 *> if alpha(j) is complex:
82 *> | det( s S - w T ) |
83 *> D(j) = ---------------------------------------------------
84 *> ulp max( s norm(S), |w| norm(T) )*norm( s S - w T )
85 *>
86 *> and S and T are here the 2 x 2 diagonal blocks of S and T
87 *> corresponding to the j-th and j+1-th eigenvalues.
88 *> (no sorting of eigenvalues)
89 *>
90 *> (7) | (A,B) - Q (S,T) Z' | / ( | (A,B) | n ulp )
91 *> (with sorting of eigenvalues).
92 *>
93 *> (8) | I - QQ' | / ( n ulp ) (with sorting of eigenvalues).
94 *>
95 *> (9) | I - ZZ' | / ( n ulp ) (with sorting of eigenvalues).
96 *>
97 *> (10) if A is in Schur form (i.e. quasi-triangular form)
98 *> (with sorting of eigenvalues).
99 *>
100 *> (11) if eigenvalues = diagonal blocks of the Schur form (S, T),
101 *> i.e. test the maximum over j of D(j) where:
102 *>
103 *> if alpha(j) is real:
104 *> |alpha(j) - S(j,j)| |beta(j) - T(j,j)|
105 *> D(j) = ------------------------ + -----------------------
106 *> max(|alpha(j)|,|S(j,j)|) max(|beta(j)|,|T(j,j)|)
107 *>
108 *> if alpha(j) is complex:
109 *> | det( s S - w T ) |
110 *> D(j) = ---------------------------------------------------
111 *> ulp max( s norm(S), |w| norm(T) )*norm( s S - w T )
112 *>
113 *> and S and T are here the 2 x 2 diagonal blocks of S and T
114 *> corresponding to the j-th and j+1-th eigenvalues.
115 *> (with sorting of eigenvalues).
116 *>
117 *> (12) if sorting worked and SDIM is the number of eigenvalues
118 *> which were SELECTed.
119 *>
120 *> Test Matrices
121 *> =============
122 *>
123 *> The sizes of the test matrices are specified by an array
124 *> NN(1:NSIZES); the value of each element NN(j) specifies one size.
125 *> The "types" are specified by a logical array DOTYPE( 1:NTYPES ); if
126 *> DOTYPE(j) is .TRUE., then matrix type "j" will be generated.
127 *> Currently, the list of possible types is:
128 *>
129 *> (1) ( 0, 0 ) (a pair of zero matrices)
130 *>
131 *> (2) ( I, 0 ) (an identity and a zero matrix)
132 *>
133 *> (3) ( 0, I ) (an identity and a zero matrix)
134 *>
135 *> (4) ( I, I ) (a pair of identity matrices)
136 *>
137 *> t t
138 *> (5) ( J , J ) (a pair of transposed Jordan blocks)
139 *>
140 *> t ( I 0 )
141 *> (6) ( X, Y ) where X = ( J 0 ) and Y = ( t )
142 *> ( 0 I ) ( 0 J )
143 *> and I is a k x k identity and J a (k+1)x(k+1)
144 *> Jordan block; k=(N-1)/2
145 *>
146 *> (7) ( D, I ) where D is diag( 0, 1,..., N-1 ) (a diagonal
147 *> matrix with those diagonal entries.)
148 *> (8) ( I, D )
149 *>
150 *> (9) ( big*D, small*I ) where "big" is near overflow and small=1/big
151 *>
152 *> (10) ( small*D, big*I )
153 *>
154 *> (11) ( big*I, small*D )
155 *>
156 *> (12) ( small*I, big*D )
157 *>
158 *> (13) ( big*D, big*I )
159 *>
160 *> (14) ( small*D, small*I )
161 *>
162 *> (15) ( D1, D2 ) where D1 is diag( 0, 0, 1, ..., N-3, 0 ) and
163 *> D2 is diag( 0, N-3, N-4,..., 1, 0, 0 )
164 *> t t
165 *> (16) Q ( J , J ) Z where Q and Z are random orthogonal matrices.
166 *>
167 *> (17) Q ( T1, T2 ) Z where T1 and T2 are upper triangular matrices
168 *> with random O(1) entries above the diagonal
169 *> and diagonal entries diag(T1) =
170 *> ( 0, 0, 1, ..., N-3, 0 ) and diag(T2) =
171 *> ( 0, N-3, N-4,..., 1, 0, 0 )
172 *>
173 *> (18) Q ( T1, T2 ) Z diag(T1) = ( 0, 0, 1, 1, s, ..., s, 0 )
174 *> diag(T2) = ( 0, 1, 0, 1,..., 1, 0 )
175 *> s = machine precision.
176 *>
177 *> (19) Q ( T1, T2 ) Z diag(T1)=( 0,0,1,1, 1-d, ..., 1-(N-5)*d=s, 0 )
178 *> diag(T2) = ( 0, 1, 0, 1, ..., 1, 0 )
179 *>
180 *> N-5
181 *> (20) Q ( T1, T2 ) Z diag(T1)=( 0, 0, 1, 1, a, ..., a =s, 0 )
182 *> diag(T2) = ( 0, 1, 0, 1, ..., 1, 0, 0 )
183 *>
184 *> (21) Q ( T1, T2 ) Z diag(T1)=( 0, 0, 1, r1, r2, ..., r(N-4), 0 )
185 *> diag(T2) = ( 0, 1, 0, 1, ..., 1, 0, 0 )
186 *> where r1,..., r(N-4) are random.
187 *>
188 *> (22) Q ( big*T1, small*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
189 *> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
190 *>
191 *> (23) Q ( small*T1, big*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
192 *> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
193 *>
194 *> (24) Q ( small*T1, small*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
195 *> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
196 *>
197 *> (25) Q ( big*T1, big*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
198 *> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
199 *>
200 *> (26) Q ( T1, T2 ) Z where T1 and T2 are random upper-triangular
201 *> matrices.
202 *>
203 *> \endverbatim
204 *
205 * Arguments:
206 * ==========
207 *
208 *> \param[in] NSIZES
209 *> \verbatim
210 *> NSIZES is INTEGER
211 *> The number of sizes of matrices to use. If it is zero,
212 *> SDRGES does nothing. NSIZES >= 0.
213 *> \endverbatim
214 *>
215 *> \param[in] NN
216 *> \verbatim
217 *> NN is INTEGER array, dimension (NSIZES)
218 *> An array containing the sizes to be used for the matrices.
219 *> Zero values will be skipped. NN >= 0.
220 *> \endverbatim
221 *>
222 *> \param[in] NTYPES
223 *> \verbatim
224 *> NTYPES is INTEGER
225 *> The number of elements in DOTYPE. If it is zero, SDRGES
226 *> does nothing. It must be at least zero. If it is MAXTYP+1
227 *> and NSIZES is 1, then an additional type, MAXTYP+1 is
228 *> defined, which is to use whatever matrix is in A on input.
229 *> This is only useful if DOTYPE(1:MAXTYP) is .FALSE. and
230 *> DOTYPE(MAXTYP+1) is .TRUE. .
231 *> \endverbatim
232 *>
233 *> \param[in] DOTYPE
234 *> \verbatim
235 *> DOTYPE is LOGICAL array, dimension (NTYPES)
236 *> If DOTYPE(j) is .TRUE., then for each size in NN a
237 *> matrix of that size and of type j will be generated.
238 *> If NTYPES is smaller than the maximum number of types
239 *> defined (PARAMETER MAXTYP), then types NTYPES+1 through
240 *> MAXTYP will not be generated. If NTYPES is larger
241 *> than MAXTYP, DOTYPE(MAXTYP+1) through DOTYPE(NTYPES)
242 *> will be ignored.
243 *> \endverbatim
244 *>
245 *> \param[in,out] ISEED
246 *> \verbatim
247 *> ISEED is INTEGER array, dimension (4)
248 *> On entry ISEED specifies the seed of the random number
249 *> generator. The array elements should be between 0 and 4095;
250 *> if not they will be reduced mod 4096. Also, ISEED(4) must
251 *> be odd. The random number generator uses a linear
252 *> congruential sequence limited to small integers, and so
253 *> should produce machine independent random numbers. The
254 *> values of ISEED are changed on exit, and can be used in the
255 *> next call to SDRGES to continue the same random number
256 *> sequence.
257 *> \endverbatim
258 *>
259 *> \param[in] THRESH
260 *> \verbatim
261 *> THRESH is REAL
262 *> A test will count as "failed" if the "error", computed as
263 *> described above, exceeds THRESH. Note that the error is
264 *> scaled to be O(1), so THRESH should be a reasonably small
265 *> multiple of 1, e.g., 10 or 100. In particular, it should
266 *> not depend on the precision (single vs. double) or the size
267 *> of the matrix. THRESH >= 0.
268 *> \endverbatim
269 *>
270 *> \param[in] NOUNIT
271 *> \verbatim
272 *> NOUNIT is INTEGER
273 *> The FORTRAN unit number for printing out error messages
274 *> (e.g., if a routine returns IINFO not equal to 0.)
275 *> \endverbatim
276 *>
277 *> \param[in,out] A
278 *> \verbatim
279 *> A is REAL array,
280 *> dimension(LDA, max(NN))
281 *> Used to hold the original A matrix. Used as input only
282 *> if NTYPES=MAXTYP+1, DOTYPE(1:MAXTYP)=.FALSE., and
283 *> DOTYPE(MAXTYP+1)=.TRUE.
284 *> \endverbatim
285 *>
286 *> \param[in] LDA
287 *> \verbatim
288 *> LDA is INTEGER
289 *> The leading dimension of A, B, S, and T.
290 *> It must be at least 1 and at least max( NN ).
291 *> \endverbatim
292 *>
293 *> \param[in,out] B
294 *> \verbatim
295 *> B is REAL array,
296 *> dimension(LDA, max(NN))
297 *> Used to hold the original B matrix. Used as input only
298 *> if NTYPES=MAXTYP+1, DOTYPE(1:MAXTYP)=.FALSE., and
299 *> DOTYPE(MAXTYP+1)=.TRUE.
300 *> \endverbatim
301 *>
302 *> \param[out] S
303 *> \verbatim
304 *> S is REAL array, dimension (LDA, max(NN))
305 *> The Schur form matrix computed from A by SGGES. On exit, S
306 *> contains the Schur form matrix corresponding to the matrix
307 *> in A.
308 *> \endverbatim
309 *>
310 *> \param[out] T
311 *> \verbatim
312 *> T is REAL array, dimension (LDA, max(NN))
313 *> The upper triangular matrix computed from B by SGGES.
314 *> \endverbatim
315 *>
316 *> \param[out] Q
317 *> \verbatim
318 *> Q is REAL array, dimension (LDQ, max(NN))
319 *> The (left) orthogonal matrix computed by SGGES.
320 *> \endverbatim
321 *>
322 *> \param[in] LDQ
323 *> \verbatim
324 *> LDQ is INTEGER
325 *> The leading dimension of Q and Z. It must
326 *> be at least 1 and at least max( NN ).
327 *> \endverbatim
328 *>
329 *> \param[out] Z
330 *> \verbatim
331 *> Z is REAL array, dimension( LDQ, max(NN) )
332 *> The (right) orthogonal matrix computed by SGGES.
333 *> \endverbatim
334 *>
335 *> \param[out] ALPHAR
336 *> \verbatim
337 *> ALPHAR is REAL array, dimension (max(NN))
338 *> \endverbatim
339 *>
340 *> \param[out] ALPHAI
341 *> \verbatim
342 *> ALPHAI is REAL array, dimension (max(NN))
343 *> \endverbatim
344 *>
345 *> \param[out] BETA
346 *> \verbatim
347 *> BETA is REAL array, dimension (max(NN))
348 *>
349 *> The generalized eigenvalues of (A,B) computed by SGGES.
350 *> ( ALPHAR(k)+ALPHAI(k)*i ) / BETA(k) is the k-th
351 *> generalized eigenvalue of A and B.
352 *> \endverbatim
353 *>
354 *> \param[out] WORK
355 *> \verbatim
356 *> WORK is REAL array, dimension (LWORK)
357 *> \endverbatim
358 *>
359 *> \param[in] LWORK
360 *> \verbatim
361 *> LWORK is INTEGER
362 *> The dimension of the array WORK.
363 *> LWORK >= MAX( 10*(N+1), 3*N*N ), where N is the largest
364 *> matrix dimension.
365 *> \endverbatim
366 *>
367 *> \param[out] RESULT
368 *> \verbatim
369 *> RESULT is REAL array, dimension (15)
370 *> The values computed by the tests described above.
371 *> The values are currently limited to 1/ulp, to avoid overflow.
372 *> \endverbatim
373 *>
374 *> \param[out] BWORK
375 *> \verbatim
376 *> BWORK is LOGICAL array, dimension (N)
377 *> \endverbatim
378 *>
379 *> \param[out] INFO
380 *> \verbatim
381 *> INFO is INTEGER
382 *> = 0: successful exit
383 *> < 0: if INFO = -i, the i-th argument had an illegal value.
384 *> > 0: A routine returned an error code. INFO is the
385 *> absolute value of the INFO value returned.
386 *> \endverbatim
387 *
388 * Authors:
389 * ========
390 *
391 *> \author Univ. of Tennessee
392 *> \author Univ. of California Berkeley
393 *> \author Univ. of Colorado Denver
394 *> \author NAG Ltd.
395 *
396 *> \date November 2011
397 *
398 *> \ingroup single_eig
399 *
400 * =====================================================================
401  SUBROUTINE sdrges( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
402  $ nounit, a, lda, b, s, t, q, ldq, z, alphar,
403  $ alphai, beta, work, lwork, result, bwork,
404  $ info )
405 *
406 * -- LAPACK test routine (version 3.4.0) --
407 * -- LAPACK is a software package provided by Univ. of Tennessee, --
408 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
409 * November 2011
410 *
411 * .. Scalar Arguments ..
412  INTEGER info, lda, ldq, lwork, nounit, nsizes, ntypes
413  REAL thresh
414 * ..
415 * .. Array Arguments ..
416  LOGICAL bwork( * ), dotype( * )
417  INTEGER iseed( 4 ), nn( * )
418  REAL a( lda, * ), alphai( * ), alphar( * ),
419  $ b( lda, * ), beta( * ), q( ldq, * ),
420  $ result( 13 ), s( lda, * ), t( lda, * ),
421  $ work( * ), z( ldq, * )
422 * ..
423 *
424 * =====================================================================
425 *
426 * .. Parameters ..
427  REAL zero, one
428  parameter( zero = 0.0e+0, one = 1.0e+0 )
429  INTEGER maxtyp
430  parameter( maxtyp = 26 )
431 * ..
432 * .. Local Scalars ..
433  LOGICAL badnn, ilabad
434  CHARACTER sort
435  INTEGER i, i1, iadd, ierr, iinfo, in, isort, j, jc, jr,
436  $ jsize, jtype, knteig, maxwrk, minwrk, mtypes,
437  $ n, n1, nb, nerrs, nmats, nmax, ntest, ntestt,
438  $ rsub, sdim
439  REAL safmax, safmin, temp1, temp2, ulp, ulpinv
440 * ..
441 * .. Local Arrays ..
442  INTEGER iasign( maxtyp ), ibsign( maxtyp ),
443  $ ioldsd( 4 ), kadd( 6 ), kamagn( maxtyp ),
444  $ katype( maxtyp ), kazero( maxtyp ),
445  $ kbmagn( maxtyp ), kbtype( maxtyp ),
446  $ kbzero( maxtyp ), kclass( maxtyp ),
447  $ ktrian( maxtyp ), kz1( 6 ), kz2( 6 )
448  REAL rmagn( 0: 3 )
449 * ..
450 * .. External Functions ..
451  LOGICAL slctes
452  INTEGER ilaenv
453  REAL slamch, slarnd
454  EXTERNAL slctes, ilaenv, slamch, slarnd
455 * ..
456 * .. External Subroutines ..
457  EXTERNAL alasvm, sget51, sget53, sget54, sgges, slabad,
459 * ..
460 * .. Intrinsic Functions ..
461  INTRINSIC abs, max, min, REAL, sign
462 * ..
463 * .. Data statements ..
464  DATA kclass / 15*1, 10*2, 1*3 /
465  DATA kz1 / 0, 1, 2, 1, 3, 3 /
466  DATA kz2 / 0, 0, 1, 2, 1, 1 /
467  DATA kadd / 0, 0, 0, 0, 3, 2 /
468  DATA katype / 0, 1, 0, 1, 2, 3, 4, 1, 4, 4, 1, 1, 4,
469  $ 4, 4, 2, 4, 5, 8, 7, 9, 4*4, 0 /
470  DATA kbtype / 0, 0, 1, 1, 2, -3, 1, 4, 1, 1, 4, 4,
471  $ 1, 1, -4, 2, -4, 8*8, 0 /
472  DATA kazero / 6*1, 2, 1, 2*2, 2*1, 2*2, 3, 1, 3,
473  $ 4*5, 4*3, 1 /
474  DATA kbzero / 6*1, 1, 2, 2*1, 2*2, 2*1, 4, 1, 4,
475  $ 4*6, 4*4, 1 /
476  DATA kamagn / 8*1, 2, 3, 2, 3, 2, 3, 7*1, 2, 3, 3,
477  $ 2, 1 /
478  DATA kbmagn / 8*1, 3, 2, 3, 2, 2, 3, 7*1, 3, 2, 3,
479  $ 2, 1 /
480  DATA ktrian / 16*0, 10*1 /
481  DATA iasign / 6*0, 2, 0, 2*2, 2*0, 3*2, 0, 2, 3*0,
482  $ 5*2, 0 /
483  DATA ibsign / 7*0, 2, 2*0, 2*2, 2*0, 2, 0, 2, 9*0 /
484 * ..
485 * .. Executable Statements ..
486 *
487 * Check for errors
488 *
489  info = 0
490 *
491  badnn = .false.
492  nmax = 1
493  DO 10 j = 1, nsizes
494  nmax = max( nmax, nn( j ) )
495  IF( nn( j ).LT.0 )
496  $ badnn = .true.
497  10 continue
498 *
499  IF( nsizes.LT.0 ) THEN
500  info = -1
501  ELSE IF( badnn ) THEN
502  info = -2
503  ELSE IF( ntypes.LT.0 ) THEN
504  info = -3
505  ELSE IF( thresh.LT.zero ) THEN
506  info = -6
507  ELSE IF( lda.LE.1 .OR. lda.LT.nmax ) THEN
508  info = -9
509  ELSE IF( ldq.LE.1 .OR. ldq.LT.nmax ) THEN
510  info = -14
511  END IF
512 *
513 * Compute workspace
514 * (Note: Comments in the code beginning "Workspace:" describe the
515 * minimal amount of workspace needed at that point in the code,
516 * as well as the preferred amount for good performance.
517 * NB refers to the optimal block size for the immediately
518 * following subroutine, as returned by ILAENV.
519 *
520  minwrk = 1
521  IF( info.EQ.0 .AND. lwork.GE.1 ) THEN
522  minwrk = max( 10*( nmax+1 ), 3*nmax*nmax )
523  nb = max( 1, ilaenv( 1, 'SGEQRF', ' ', nmax, nmax, -1, -1 ),
524  $ ilaenv( 1, 'SORMQR', 'LT', nmax, nmax, nmax, -1 ),
525  $ ilaenv( 1, 'SORGQR', ' ', nmax, nmax, nmax, -1 ) )
526  maxwrk = max( 10*( nmax+1 ), 2*nmax+nmax*nb, 3*nmax*nmax )
527  work( 1 ) = maxwrk
528  END IF
529 *
530  IF( lwork.LT.minwrk )
531  $ info = -20
532 *
533  IF( info.NE.0 ) THEN
534  CALL xerbla( 'SDRGES', -info )
535  return
536  END IF
537 *
538 * Quick return if possible
539 *
540  IF( nsizes.EQ.0 .OR. ntypes.EQ.0 )
541  $ return
542 *
543  safmin = slamch( 'Safe minimum' )
544  ulp = slamch( 'Epsilon' )*slamch( 'Base' )
545  safmin = safmin / ulp
546  safmax = one / safmin
547  CALL slabad( safmin, safmax )
548  ulpinv = one / ulp
549 *
550 * The values RMAGN(2:3) depend on N, see below.
551 *
552  rmagn( 0 ) = zero
553  rmagn( 1 ) = one
554 *
555 * Loop over matrix sizes
556 *
557  ntestt = 0
558  nerrs = 0
559  nmats = 0
560 *
561  DO 190 jsize = 1, nsizes
562  n = nn( jsize )
563  n1 = max( 1, n )
564  rmagn( 2 ) = safmax*ulp / REAL( n1 )
565  rmagn( 3 ) = safmin*ulpinv*REAL( n1 )
566 *
567  IF( nsizes.NE.1 ) THEN
568  mtypes = min( maxtyp, ntypes )
569  ELSE
570  mtypes = min( maxtyp+1, ntypes )
571  END IF
572 *
573 * Loop over matrix types
574 *
575  DO 180 jtype = 1, mtypes
576  IF( .NOT.dotype( jtype ) )
577  $ go to 180
578  nmats = nmats + 1
579  ntest = 0
580 *
581 * Save ISEED in case of an error.
582 *
583  DO 20 j = 1, 4
584  ioldsd( j ) = iseed( j )
585  20 continue
586 *
587 * Initialize RESULT
588 *
589  DO 30 j = 1, 13
590  result( j ) = zero
591  30 continue
592 *
593 * Generate test matrices A and B
594 *
595 * Description of control parameters:
596 *
597 * KCLASS: =1 means w/o rotation, =2 means w/ rotation,
598 * =3 means random.
599 * KATYPE: the "type" to be passed to SLATM4 for computing A.
600 * KAZERO: the pattern of zeros on the diagonal for A:
601 * =1: ( xxx ), =2: (0, xxx ) =3: ( 0, 0, xxx, 0 ),
602 * =4: ( 0, xxx, 0, 0 ), =5: ( 0, 0, 1, xxx, 0 ),
603 * =6: ( 0, 1, 0, xxx, 0 ). (xxx means a string of
604 * non-zero entries.)
605 * KAMAGN: the magnitude of the matrix: =0: zero, =1: O(1),
606 * =2: large, =3: small.
607 * IASIGN: 1 if the diagonal elements of A are to be
608 * multiplied by a random magnitude 1 number, =2 if
609 * randomly chosen diagonal blocks are to be rotated
610 * to form 2x2 blocks.
611 * KBTYPE, KBZERO, KBMAGN, IBSIGN: the same, but for B.
612 * KTRIAN: =0: don't fill in the upper triangle, =1: do.
613 * KZ1, KZ2, KADD: used to implement KAZERO and KBZERO.
614 * RMAGN: used to implement KAMAGN and KBMAGN.
615 *
616  IF( mtypes.GT.maxtyp )
617  $ go to 110
618  iinfo = 0
619  IF( kclass( jtype ).LT.3 ) THEN
620 *
621 * Generate A (w/o rotation)
622 *
623  IF( abs( katype( jtype ) ).EQ.3 ) THEN
624  in = 2*( ( n-1 ) / 2 ) + 1
625  IF( in.NE.n )
626  $ CALL slaset( 'Full', n, n, zero, zero, a, lda )
627  ELSE
628  in = n
629  END IF
630  CALL slatm4( katype( jtype ), in, kz1( kazero( jtype ) ),
631  $ kz2( kazero( jtype ) ), iasign( jtype ),
632  $ rmagn( kamagn( jtype ) ), ulp,
633  $ rmagn( ktrian( jtype )*kamagn( jtype ) ), 2,
634  $ iseed, a, lda )
635  iadd = kadd( kazero( jtype ) )
636  IF( iadd.GT.0 .AND. iadd.LE.n )
637  $ a( iadd, iadd ) = one
638 *
639 * Generate B (w/o rotation)
640 *
641  IF( abs( kbtype( jtype ) ).EQ.3 ) THEN
642  in = 2*( ( n-1 ) / 2 ) + 1
643  IF( in.NE.n )
644  $ CALL slaset( 'Full', n, n, zero, zero, b, lda )
645  ELSE
646  in = n
647  END IF
648  CALL slatm4( kbtype( jtype ), in, kz1( kbzero( jtype ) ),
649  $ kz2( kbzero( jtype ) ), ibsign( jtype ),
650  $ rmagn( kbmagn( jtype ) ), one,
651  $ rmagn( ktrian( jtype )*kbmagn( jtype ) ), 2,
652  $ iseed, b, lda )
653  iadd = kadd( kbzero( jtype ) )
654  IF( iadd.NE.0 .AND. iadd.LE.n )
655  $ b( iadd, iadd ) = one
656 *
657  IF( kclass( jtype ).EQ.2 .AND. n.GT.0 ) THEN
658 *
659 * Include rotations
660 *
661 * Generate Q, Z as Householder transformations times
662 * a diagonal matrix.
663 *
664  DO 50 jc = 1, n - 1
665  DO 40 jr = jc, n
666  q( jr, jc ) = slarnd( 3, iseed )
667  z( jr, jc ) = slarnd( 3, iseed )
668  40 continue
669  CALL slarfg( n+1-jc, q( jc, jc ), q( jc+1, jc ), 1,
670  $ work( jc ) )
671  work( 2*n+jc ) = sign( one, q( jc, jc ) )
672  q( jc, jc ) = one
673  CALL slarfg( n+1-jc, z( jc, jc ), z( jc+1, jc ), 1,
674  $ work( n+jc ) )
675  work( 3*n+jc ) = sign( one, z( jc, jc ) )
676  z( jc, jc ) = one
677  50 continue
678  q( n, n ) = one
679  work( n ) = zero
680  work( 3*n ) = sign( one, slarnd( 2, iseed ) )
681  z( n, n ) = one
682  work( 2*n ) = zero
683  work( 4*n ) = sign( one, slarnd( 2, iseed ) )
684 *
685 * Apply the diagonal matrices
686 *
687  DO 70 jc = 1, n
688  DO 60 jr = 1, n
689  a( jr, jc ) = work( 2*n+jr )*work( 3*n+jc )*
690  $ a( jr, jc )
691  b( jr, jc ) = work( 2*n+jr )*work( 3*n+jc )*
692  $ b( jr, jc )
693  60 continue
694  70 continue
695  CALL sorm2r( 'L', 'N', n, n, n-1, q, ldq, work, a,
696  $ lda, work( 2*n+1 ), iinfo )
697  IF( iinfo.NE.0 )
698  $ go to 100
699  CALL sorm2r( 'R', 'T', n, n, n-1, z, ldq, work( n+1 ),
700  $ a, lda, work( 2*n+1 ), iinfo )
701  IF( iinfo.NE.0 )
702  $ go to 100
703  CALL sorm2r( 'L', 'N', n, n, n-1, q, ldq, work, b,
704  $ lda, work( 2*n+1 ), iinfo )
705  IF( iinfo.NE.0 )
706  $ go to 100
707  CALL sorm2r( 'R', 'T', n, n, n-1, z, ldq, work( n+1 ),
708  $ b, lda, work( 2*n+1 ), iinfo )
709  IF( iinfo.NE.0 )
710  $ go to 100
711  END IF
712  ELSE
713 *
714 * Random matrices
715 *
716  DO 90 jc = 1, n
717  DO 80 jr = 1, n
718  a( jr, jc ) = rmagn( kamagn( jtype ) )*
719  $ slarnd( 2, iseed )
720  b( jr, jc ) = rmagn( kbmagn( jtype ) )*
721  $ slarnd( 2, iseed )
722  80 continue
723  90 continue
724  END IF
725 *
726  100 continue
727 *
728  IF( iinfo.NE.0 ) THEN
729  WRITE( nounit, fmt = 9999 )'Generator', iinfo, n, jtype,
730  $ ioldsd
731  info = abs( iinfo )
732  return
733  END IF
734 *
735  110 continue
736 *
737  DO 120 i = 1, 13
738  result( i ) = -one
739  120 continue
740 *
741 * Test with and without sorting of eigenvalues
742 *
743  DO 150 isort = 0, 1
744  IF( isort.EQ.0 ) THEN
745  sort = 'N'
746  rsub = 0
747  ELSE
748  sort = 'S'
749  rsub = 5
750  END IF
751 *
752 * Call SGGES to compute H, T, Q, Z, alpha, and beta.
753 *
754  CALL slacpy( 'Full', n, n, a, lda, s, lda )
755  CALL slacpy( 'Full', n, n, b, lda, t, lda )
756  ntest = 1 + rsub + isort
757  result( 1+rsub+isort ) = ulpinv
758  CALL sgges( 'V', 'V', sort, slctes, n, s, lda, t, lda,
759  $ sdim, alphar, alphai, beta, q, ldq, z, ldq,
760  $ work, lwork, bwork, iinfo )
761  IF( iinfo.NE.0 .AND. iinfo.NE.n+2 ) THEN
762  result( 1+rsub+isort ) = ulpinv
763  WRITE( nounit, fmt = 9999 )'SGGES', iinfo, n, jtype,
764  $ ioldsd
765  info = abs( iinfo )
766  go to 160
767  END IF
768 *
769  ntest = 4 + rsub
770 *
771 * Do tests 1--4 (or tests 7--9 when reordering )
772 *
773  IF( isort.EQ.0 ) THEN
774  CALL sget51( 1, n, a, lda, s, lda, q, ldq, z, ldq,
775  $ work, result( 1 ) )
776  CALL sget51( 1, n, b, lda, t, lda, q, ldq, z, ldq,
777  $ work, result( 2 ) )
778  ELSE
779  CALL sget54( n, a, lda, b, lda, s, lda, t, lda, q,
780  $ ldq, z, ldq, work, result( 7 ) )
781  END IF
782  CALL sget51( 3, n, a, lda, t, lda, q, ldq, q, ldq, work,
783  $ result( 3+rsub ) )
784  CALL sget51( 3, n, b, lda, t, lda, z, ldq, z, ldq, work,
785  $ result( 4+rsub ) )
786 *
787 * Do test 5 and 6 (or Tests 10 and 11 when reordering):
788 * check Schur form of A and compare eigenvalues with
789 * diagonals.
790 *
791  ntest = 6 + rsub
792  temp1 = zero
793 *
794  DO 130 j = 1, n
795  ilabad = .false.
796  IF( alphai( j ).EQ.zero ) THEN
797  temp2 = ( abs( alphar( j )-s( j, j ) ) /
798  $ max( safmin, abs( alphar( j ) ), abs( s( j,
799  $ j ) ) )+abs( beta( j )-t( j, j ) ) /
800  $ max( safmin, abs( beta( j ) ), abs( t( j,
801  $ j ) ) ) ) / ulp
802 *
803  IF( j.LT.n ) THEN
804  IF( s( j+1, j ).NE.zero ) THEN
805  ilabad = .true.
806  result( 5+rsub ) = ulpinv
807  END IF
808  END IF
809  IF( j.GT.1 ) THEN
810  IF( s( j, j-1 ).NE.zero ) THEN
811  ilabad = .true.
812  result( 5+rsub ) = ulpinv
813  END IF
814  END IF
815 *
816  ELSE
817  IF( alphai( j ).GT.zero ) THEN
818  i1 = j
819  ELSE
820  i1 = j - 1
821  END IF
822  IF( i1.LE.0 .OR. i1.GE.n ) THEN
823  ilabad = .true.
824  ELSE IF( i1.LT.n-1 ) THEN
825  IF( s( i1+2, i1+1 ).NE.zero ) THEN
826  ilabad = .true.
827  result( 5+rsub ) = ulpinv
828  END IF
829  ELSE IF( i1.GT.1 ) THEN
830  IF( s( i1, i1-1 ).NE.zero ) THEN
831  ilabad = .true.
832  result( 5+rsub ) = ulpinv
833  END IF
834  END IF
835  IF( .NOT.ilabad ) THEN
836  CALL sget53( s( i1, i1 ), lda, t( i1, i1 ), lda,
837  $ beta( j ), alphar( j ),
838  $ alphai( j ), temp2, ierr )
839  IF( ierr.GE.3 ) THEN
840  WRITE( nounit, fmt = 9998 )ierr, j, n,
841  $ jtype, ioldsd
842  info = abs( ierr )
843  END IF
844  ELSE
845  temp2 = ulpinv
846  END IF
847 *
848  END IF
849  temp1 = max( temp1, temp2 )
850  IF( ilabad ) THEN
851  WRITE( nounit, fmt = 9997 )j, n, jtype, ioldsd
852  END IF
853  130 continue
854  result( 6+rsub ) = temp1
855 *
856  IF( isort.GE.1 ) THEN
857 *
858 * Do test 12
859 *
860  ntest = 12
861  result( 12 ) = zero
862  knteig = 0
863  DO 140 i = 1, n
864  IF( slctes( alphar( i ), alphai( i ),
865  $ beta( i ) ) .OR. slctes( alphar( i ),
866  $ -alphai( i ), beta( i ) ) ) THEN
867  knteig = knteig + 1
868  END IF
869  IF( i.LT.n ) THEN
870  IF( ( slctes( alphar( i+1 ), alphai( i+1 ),
871  $ beta( i+1 ) ) .OR. slctes( alphar( i+1 ),
872  $ -alphai( i+1 ), beta( i+1 ) ) ) .AND.
873  $ ( .NOT.( slctes( alphar( i ), alphai( i ),
874  $ beta( i ) ) .OR. slctes( alphar( i ),
875  $ -alphai( i ), beta( i ) ) ) ) .AND.
876  $ iinfo.NE.n+2 ) THEN
877  result( 12 ) = ulpinv
878  END IF
879  END IF
880  140 continue
881  IF( sdim.NE.knteig ) THEN
882  result( 12 ) = ulpinv
883  END IF
884  END IF
885 *
886  150 continue
887 *
888 * End of Loop -- Check for RESULT(j) > THRESH
889 *
890  160 continue
891 *
892  ntestt = ntestt + ntest
893 *
894 * Print out tests which fail.
895 *
896  DO 170 jr = 1, ntest
897  IF( result( jr ).GE.thresh ) THEN
898 *
899 * If this is the first test to fail,
900 * print a header to the data file.
901 *
902  IF( nerrs.EQ.0 ) THEN
903  WRITE( nounit, fmt = 9996 )'SGS'
904 *
905 * Matrix types
906 *
907  WRITE( nounit, fmt = 9995 )
908  WRITE( nounit, fmt = 9994 )
909  WRITE( nounit, fmt = 9993 )'Orthogonal'
910 *
911 * Tests performed
912 *
913  WRITE( nounit, fmt = 9992 )'orthogonal', '''',
914  $ 'transpose', ( '''', j = 1, 8 )
915 *
916  END IF
917  nerrs = nerrs + 1
918  IF( result( jr ).LT.10000.0 ) THEN
919  WRITE( nounit, fmt = 9991 )n, jtype, ioldsd, jr,
920  $ result( jr )
921  ELSE
922  WRITE( nounit, fmt = 9990 )n, jtype, ioldsd, jr,
923  $ result( jr )
924  END IF
925  END IF
926  170 continue
927 *
928  180 continue
929  190 continue
930 *
931 * Summary
932 *
933  CALL alasvm( 'SGS', nounit, nerrs, ntestt, 0 )
934 *
935  work( 1 ) = maxwrk
936 *
937  return
938 *
939  9999 format( ' SDRGES: ', a, ' returned INFO=', i6, '.', / 9x, 'N=',
940  $ i6, ', JTYPE=', i6, ', ISEED=(', 4( i4, ',' ), i5, ')' )
941 *
942  9998 format( ' SDRGES: SGET53 returned INFO=', i1, ' for eigenvalue ',
943  $ i6, '.', / 9x, 'N=', i6, ', JTYPE=', i6, ', ISEED=(',
944  $ 4( i4, ',' ), i5, ')' )
945 *
946  9997 format( ' SDRGES: S not in Schur form at eigenvalue ', i6, '.',
947  $ / 9x, 'N=', i6, ', JTYPE=', i6, ', ISEED=(', 3( i5, ',' ),
948  $ i5, ')' )
949 *
950  9996 format( / 1x, a3, ' -- Real Generalized Schur form driver' )
951 *
952  9995 format( ' Matrix types (see SDRGES for details): ' )
953 *
954  9994 format( ' Special Matrices:', 23x,
955  $ '(J''=transposed Jordan block)',
956  $ / ' 1=(0,0) 2=(I,0) 3=(0,I) 4=(I,I) 5=(J'',J'') ',
957  $ '6=(diag(J'',I), diag(I,J''))', / ' Diagonal Matrices: ( ',
958  $ 'D=diag(0,1,2,...) )', / ' 7=(D,I) 9=(large*D, small*I',
959  $ ') 11=(large*I, small*D) 13=(large*D, large*I)', /
960  $ ' 8=(I,D) 10=(small*D, large*I) 12=(small*I, large*D) ',
961  $ ' 14=(small*D, small*I)', / ' 15=(D, reversed D)' )
962  9993 format( ' Matrices Rotated by Random ', a, ' Matrices U, V:',
963  $ / ' 16=Transposed Jordan Blocks 19=geometric ',
964  $ 'alpha, beta=0,1', / ' 17=arithm. alpha&beta ',
965  $ ' 20=arithmetic alpha, beta=0,1', / ' 18=clustered ',
966  $ 'alpha, beta=0,1 21=random alpha, beta=0,1',
967  $ / ' Large & Small Matrices:', / ' 22=(large, small) ',
968  $ '23=(small,large) 24=(small,small) 25=(large,large)',
969  $ / ' 26=random O(1) matrices.' )
970 *
971  9992 format( / ' Tests performed: (S is Schur, T is triangular, ',
972  $ 'Q and Z are ', a, ',', / 19x,
973  $ 'l and r are the appropriate left and right', / 19x,
974  $ 'eigenvectors, resp., a is alpha, b is beta, and', / 19x, a,
975  $ ' means ', a, '.)', / ' Without ordering: ',
976  $ / ' 1 = | A - Q S Z', a,
977  $ ' | / ( |A| n ulp ) 2 = | B - Q T Z', a,
978  $ ' | / ( |B| n ulp )', / ' 3 = | I - QQ', a,
979  $ ' | / ( n ulp ) 4 = | I - ZZ', a,
980  $ ' | / ( n ulp )', / ' 5 = A is in Schur form S',
981  $ / ' 6 = difference between (alpha,beta)',
982  $ ' and diagonals of (S,T)', / ' With ordering: ',
983  $ / ' 7 = | (A,B) - Q (S,T) Z', a,
984  $ ' | / ( |(A,B)| n ulp ) ', / ' 8 = | I - QQ', a,
985  $ ' | / ( n ulp ) 9 = | I - ZZ', a,
986  $ ' | / ( n ulp )', / ' 10 = A is in Schur form S',
987  $ / ' 11 = difference between (alpha,beta) and diagonals',
988  $ ' of (S,T)', / ' 12 = SDIM is the correct number of ',
989  $ 'selected eigenvalues', / )
990  9991 format( ' Matrix order=', i5, ', type=', i2, ', seed=',
991  $ 4( i4, ',' ), ' result ', i2, ' is', 0p, f8.2 )
992  9990 format( ' Matrix order=', i5, ', type=', i2, ', seed=',
993  $ 4( i4, ',' ), ' result ', i2, ' is', 1p, e10.3 )
994 *
995 * End of SDRGES
996 *
997  END