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ctgsja.f 20 kB

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  1. *> \brief \b CTGSJA
  2. *
  3. * =========== DOCUMENTATION ===========
  4. *
  5. * Online html documentation available at
  6. * http://www.netlib.org/lapack/explore-html/
  7. *
  8. *> \htmlonly
  9. *> Download CTGSJA + dependencies
  10. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/ctgsja.f">
  11. *> [TGZ]</a>
  12. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/ctgsja.f">
  13. *> [ZIP]</a>
  14. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/ctgsja.f">
  15. *> [TXT]</a>
  16. *> \endhtmlonly
  17. *
  18. * Definition:
  19. * ===========
  20. *
  21. * SUBROUTINE CTGSJA( JOBU, JOBV, JOBQ, M, P, N, K, L, A, LDA, B,
  22. * LDB, TOLA, TOLB, ALPHA, BETA, U, LDU, V, LDV,
  23. * Q, LDQ, WORK, NCYCLE, INFO )
  24. *
  25. * .. Scalar Arguments ..
  26. * CHARACTER JOBQ, JOBU, JOBV
  27. * INTEGER INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N,
  28. * $ NCYCLE, P
  29. * REAL TOLA, TOLB
  30. * ..
  31. * .. Array Arguments ..
  32. * REAL ALPHA( * ), BETA( * )
  33. * COMPLEX A( LDA, * ), B( LDB, * ), Q( LDQ, * ),
  34. * $ U( LDU, * ), V( LDV, * ), WORK( * )
  35. * ..
  36. *
  37. *
  38. *> \par Purpose:
  39. * =============
  40. *>
  41. *> \verbatim
  42. *>
  43. *> CTGSJA computes the generalized singular value decomposition (GSVD)
  44. *> of two complex upper triangular (or trapezoidal) matrices A and B.
  45. *>
  46. *> On entry, it is assumed that matrices A and B have the following
  47. *> forms, which may be obtained by the preprocessing subroutine CGGSVP
  48. *> from a general M-by-N matrix A and P-by-N matrix B:
  49. *>
  50. *> N-K-L K L
  51. *> A = K ( 0 A12 A13 ) if M-K-L >= 0;
  52. *> L ( 0 0 A23 )
  53. *> M-K-L ( 0 0 0 )
  54. *>
  55. *> N-K-L K L
  56. *> A = K ( 0 A12 A13 ) if M-K-L < 0;
  57. *> M-K ( 0 0 A23 )
  58. *>
  59. *> N-K-L K L
  60. *> B = L ( 0 0 B13 )
  61. *> P-L ( 0 0 0 )
  62. *>
  63. *> where the K-by-K matrix A12 and L-by-L matrix B13 are nonsingular
  64. *> upper triangular; A23 is L-by-L upper triangular if M-K-L >= 0,
  65. *> otherwise A23 is (M-K)-by-L upper trapezoidal.
  66. *>
  67. *> On exit,
  68. *>
  69. *> U**H *A*Q = D1*( 0 R ), V**H *B*Q = D2*( 0 R ),
  70. *>
  71. *> where U, V and Q are unitary matrices.
  72. *> R is a nonsingular upper triangular matrix, and D1
  73. *> and D2 are ``diagonal'' matrices, which are of the following
  74. *> structures:
  75. *>
  76. *> If M-K-L >= 0,
  77. *>
  78. *> K L
  79. *> D1 = K ( I 0 )
  80. *> L ( 0 C )
  81. *> M-K-L ( 0 0 )
  82. *>
  83. *> K L
  84. *> D2 = L ( 0 S )
  85. *> P-L ( 0 0 )
  86. *>
  87. *> N-K-L K L
  88. *> ( 0 R ) = K ( 0 R11 R12 ) K
  89. *> L ( 0 0 R22 ) L
  90. *>
  91. *> where
  92. *>
  93. *> C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
  94. *> S = diag( BETA(K+1), ... , BETA(K+L) ),
  95. *> C**2 + S**2 = I.
  96. *>
  97. *> R is stored in A(1:K+L,N-K-L+1:N) on exit.
  98. *>
  99. *> If M-K-L < 0,
  100. *>
  101. *> K M-K K+L-M
  102. *> D1 = K ( I 0 0 )
  103. *> M-K ( 0 C 0 )
  104. *>
  105. *> K M-K K+L-M
  106. *> D2 = M-K ( 0 S 0 )
  107. *> K+L-M ( 0 0 I )
  108. *> P-L ( 0 0 0 )
  109. *>
  110. *> N-K-L K M-K K+L-M
  111. *> ( 0 R ) = K ( 0 R11 R12 R13 )
  112. *> M-K ( 0 0 R22 R23 )
  113. *> K+L-M ( 0 0 0 R33 )
  114. *>
  115. *> where
  116. *> C = diag( ALPHA(K+1), ... , ALPHA(M) ),
  117. *> S = diag( BETA(K+1), ... , BETA(M) ),
  118. *> C**2 + S**2 = I.
  119. *>
  120. *> R = ( R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N) and R33 is stored
  121. *> ( 0 R22 R23 )
  122. *> in B(M-K+1:L,N+M-K-L+1:N) on exit.
  123. *>
  124. *> The computation of the unitary transformation matrices U, V or Q
  125. *> is optional. These matrices may either be formed explicitly, or they
  126. *> may be postmultiplied into input matrices U1, V1, or Q1.
  127. *> \endverbatim
  128. *
  129. * Arguments:
  130. * ==========
  131. *
  132. *> \param[in] JOBU
  133. *> \verbatim
  134. *> JOBU is CHARACTER*1
  135. *> = 'U': U must contain a unitary matrix U1 on entry, and
  136. *> the product U1*U is returned;
  137. *> = 'I': U is initialized to the unit matrix, and the
  138. *> unitary matrix U is returned;
  139. *> = 'N': U is not computed.
  140. *> \endverbatim
  141. *>
  142. *> \param[in] JOBV
  143. *> \verbatim
  144. *> JOBV is CHARACTER*1
  145. *> = 'V': V must contain a unitary matrix V1 on entry, and
  146. *> the product V1*V is returned;
  147. *> = 'I': V is initialized to the unit matrix, and the
  148. *> unitary matrix V is returned;
  149. *> = 'N': V is not computed.
  150. *> \endverbatim
  151. *>
  152. *> \param[in] JOBQ
  153. *> \verbatim
  154. *> JOBQ is CHARACTER*1
  155. *> = 'Q': Q must contain a unitary matrix Q1 on entry, and
  156. *> the product Q1*Q is returned;
  157. *> = 'I': Q is initialized to the unit matrix, and the
  158. *> unitary matrix Q is returned;
  159. *> = 'N': Q is not computed.
  160. *> \endverbatim
  161. *>
  162. *> \param[in] M
  163. *> \verbatim
  164. *> M is INTEGER
  165. *> The number of rows of the matrix A. M >= 0.
  166. *> \endverbatim
  167. *>
  168. *> \param[in] P
  169. *> \verbatim
  170. *> P is INTEGER
  171. *> The number of rows of the matrix B. P >= 0.
  172. *> \endverbatim
  173. *>
  174. *> \param[in] N
  175. *> \verbatim
  176. *> N is INTEGER
  177. *> The number of columns of the matrices A and B. N >= 0.
  178. *> \endverbatim
  179. *>
  180. *> \param[in] K
  181. *> \verbatim
  182. *> K is INTEGER
  183. *> \endverbatim
  184. *>
  185. *> \param[in] L
  186. *> \verbatim
  187. *> L is INTEGER
  188. *>
  189. *> K and L specify the subblocks in the input matrices A and B:
  190. *> A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,,N-L+1:N)
  191. *> of A and B, whose GSVD is going to be computed by CTGSJA.
  192. *> See Further Details.
  193. *> \endverbatim
  194. *>
  195. *> \param[in,out] A
  196. *> \verbatim
  197. *> A is COMPLEX array, dimension (LDA,N)
  198. *> On entry, the M-by-N matrix A.
  199. *> On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular
  200. *> matrix R or part of R. See Purpose for details.
  201. *> \endverbatim
  202. *>
  203. *> \param[in] LDA
  204. *> \verbatim
  205. *> LDA is INTEGER
  206. *> The leading dimension of the array A. LDA >= max(1,M).
  207. *> \endverbatim
  208. *>
  209. *> \param[in,out] B
  210. *> \verbatim
  211. *> B is COMPLEX array, dimension (LDB,N)
  212. *> On entry, the P-by-N matrix B.
  213. *> On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains
  214. *> a part of R. See Purpose for details.
  215. *> \endverbatim
  216. *>
  217. *> \param[in] LDB
  218. *> \verbatim
  219. *> LDB is INTEGER
  220. *> The leading dimension of the array B. LDB >= max(1,P).
  221. *> \endverbatim
  222. *>
  223. *> \param[in] TOLA
  224. *> \verbatim
  225. *> TOLA is REAL
  226. *> \endverbatim
  227. *>
  228. *> \param[in] TOLB
  229. *> \verbatim
  230. *> TOLB is REAL
  231. *>
  232. *> TOLA and TOLB are the convergence criteria for the Jacobi-
  233. *> Kogbetliantz iteration procedure. Generally, they are the
  234. *> same as used in the preprocessing step, say
  235. *> TOLA = MAX(M,N)*norm(A)*MACHEPS,
  236. *> TOLB = MAX(P,N)*norm(B)*MACHEPS.
  237. *> \endverbatim
  238. *>
  239. *> \param[out] ALPHA
  240. *> \verbatim
  241. *> ALPHA is REAL array, dimension (N)
  242. *> \endverbatim
  243. *>
  244. *> \param[out] BETA
  245. *> \verbatim
  246. *> BETA is REAL array, dimension (N)
  247. *>
  248. *> On exit, ALPHA and BETA contain the generalized singular
  249. *> value pairs of A and B;
  250. *> ALPHA(1:K) = 1,
  251. *> BETA(1:K) = 0,
  252. *> and if M-K-L >= 0,
  253. *> ALPHA(K+1:K+L) = diag(C),
  254. *> BETA(K+1:K+L) = diag(S),
  255. *> or if M-K-L < 0,
  256. *> ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0
  257. *> BETA(K+1:M) = S, BETA(M+1:K+L) = 1.
  258. *> Furthermore, if K+L < N,
  259. *> ALPHA(K+L+1:N) = 0
  260. *> BETA(K+L+1:N) = 0.
  261. *> \endverbatim
  262. *>
  263. *> \param[in,out] U
  264. *> \verbatim
  265. *> U is COMPLEX array, dimension (LDU,M)
  266. *> On entry, if JOBU = 'U', U must contain a matrix U1 (usually
  267. *> the unitary matrix returned by CGGSVP).
  268. *> On exit,
  269. *> if JOBU = 'I', U contains the unitary matrix U;
  270. *> if JOBU = 'U', U contains the product U1*U.
  271. *> If JOBU = 'N', U is not referenced.
  272. *> \endverbatim
  273. *>
  274. *> \param[in] LDU
  275. *> \verbatim
  276. *> LDU is INTEGER
  277. *> The leading dimension of the array U. LDU >= max(1,M) if
  278. *> JOBU = 'U'; LDU >= 1 otherwise.
  279. *> \endverbatim
  280. *>
  281. *> \param[in,out] V
  282. *> \verbatim
  283. *> V is COMPLEX array, dimension (LDV,P)
  284. *> On entry, if JOBV = 'V', V must contain a matrix V1 (usually
  285. *> the unitary matrix returned by CGGSVP).
  286. *> On exit,
  287. *> if JOBV = 'I', V contains the unitary matrix V;
  288. *> if JOBV = 'V', V contains the product V1*V.
  289. *> If JOBV = 'N', V is not referenced.
  290. *> \endverbatim
  291. *>
  292. *> \param[in] LDV
  293. *> \verbatim
  294. *> LDV is INTEGER
  295. *> The leading dimension of the array V. LDV >= max(1,P) if
  296. *> JOBV = 'V'; LDV >= 1 otherwise.
  297. *> \endverbatim
  298. *>
  299. *> \param[in,out] Q
  300. *> \verbatim
  301. *> Q is COMPLEX array, dimension (LDQ,N)
  302. *> On entry, if JOBQ = 'Q', Q must contain a matrix Q1 (usually
  303. *> the unitary matrix returned by CGGSVP).
  304. *> On exit,
  305. *> if JOBQ = 'I', Q contains the unitary matrix Q;
  306. *> if JOBQ = 'Q', Q contains the product Q1*Q.
  307. *> If JOBQ = 'N', Q is not referenced.
  308. *> \endverbatim
  309. *>
  310. *> \param[in] LDQ
  311. *> \verbatim
  312. *> LDQ is INTEGER
  313. *> The leading dimension of the array Q. LDQ >= max(1,N) if
  314. *> JOBQ = 'Q'; LDQ >= 1 otherwise.
  315. *> \endverbatim
  316. *>
  317. *> \param[out] WORK
  318. *> \verbatim
  319. *> WORK is COMPLEX array, dimension (2*N)
  320. *> \endverbatim
  321. *>
  322. *> \param[out] NCYCLE
  323. *> \verbatim
  324. *> NCYCLE is INTEGER
  325. *> The number of cycles required for convergence.
  326. *> \endverbatim
  327. *>
  328. *> \param[out] INFO
  329. *> \verbatim
  330. *> INFO is INTEGER
  331. *> = 0: successful exit
  332. *> < 0: if INFO = -i, the i-th argument had an illegal value.
  333. *> = 1: the procedure does not converge after MAXIT cycles.
  334. *> \endverbatim
  335. *
  336. *> \par Internal Parameters:
  337. * =========================
  338. *>
  339. *> \verbatim
  340. *> MAXIT INTEGER
  341. *> MAXIT specifies the total loops that the iterative procedure
  342. *> may take. If after MAXIT cycles, the routine fails to
  343. *> converge, we return INFO = 1.
  344. *> \endverbatim
  345. *
  346. * Authors:
  347. * ========
  348. *
  349. *> \author Univ. of Tennessee
  350. *> \author Univ. of California Berkeley
  351. *> \author Univ. of Colorado Denver
  352. *> \author NAG Ltd.
  353. *
  354. *> \date December 2016
  355. *
  356. *> \ingroup complexOTHERcomputational
  357. *
  358. *> \par Further Details:
  359. * =====================
  360. *>
  361. *> \verbatim
  362. *>
  363. *> CTGSJA essentially uses a variant of Kogbetliantz algorithm to reduce
  364. *> min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L
  365. *> matrix B13 to the form:
  366. *>
  367. *> U1**H *A13*Q1 = C1*R1; V1**H *B13*Q1 = S1*R1,
  368. *>
  369. *> where U1, V1 and Q1 are unitary matrix.
  370. *> C1 and S1 are diagonal matrices satisfying
  371. *>
  372. *> C1**2 + S1**2 = I,
  373. *>
  374. *> and R1 is an L-by-L nonsingular upper triangular matrix.
  375. *> \endverbatim
  376. *>
  377. * =====================================================================
  378. SUBROUTINE CTGSJA( JOBU, JOBV, JOBQ, M, P, N, K, L, A, LDA, B,
  379. $ LDB, TOLA, TOLB, ALPHA, BETA, U, LDU, V, LDV,
  380. $ Q, LDQ, WORK, NCYCLE, INFO )
  381. *
  382. * -- LAPACK computational routine (version 3.7.0) --
  383. * -- LAPACK is a software package provided by Univ. of Tennessee, --
  384. * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
  385. * December 2016
  386. *
  387. * .. Scalar Arguments ..
  388. CHARACTER JOBQ, JOBU, JOBV
  389. INTEGER INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N,
  390. $ NCYCLE, P
  391. REAL TOLA, TOLB
  392. * ..
  393. * .. Array Arguments ..
  394. REAL ALPHA( * ), BETA( * )
  395. COMPLEX A( LDA, * ), B( LDB, * ), Q( LDQ, * ),
  396. $ U( LDU, * ), V( LDV, * ), WORK( * )
  397. * ..
  398. *
  399. * =====================================================================
  400. *
  401. * .. Parameters ..
  402. INTEGER MAXIT
  403. PARAMETER ( MAXIT = 40 )
  404. REAL ZERO, ONE
  405. PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 )
  406. COMPLEX CZERO, CONE
  407. PARAMETER ( CZERO = ( 0.0E+0, 0.0E+0 ),
  408. $ CONE = ( 1.0E+0, 0.0E+0 ) )
  409. * ..
  410. * .. Local Scalars ..
  411. *
  412. LOGICAL INITQ, INITU, INITV, UPPER, WANTQ, WANTU, WANTV
  413. INTEGER I, J, KCYCLE
  414. REAL A1, A3, B1, B3, CSQ, CSU, CSV, ERROR, GAMMA,
  415. $ RWK, SSMIN
  416. COMPLEX A2, B2, SNQ, SNU, SNV
  417. * ..
  418. * .. External Functions ..
  419. LOGICAL LSAME
  420. EXTERNAL LSAME
  421. * ..
  422. * .. External Subroutines ..
  423. EXTERNAL CCOPY, CLAGS2, CLAPLL, CLASET, CROT, CSSCAL,
  424. $ SLARTG, XERBLA
  425. * ..
  426. * .. Intrinsic Functions ..
  427. INTRINSIC ABS, CONJG, MAX, MIN, REAL
  428. * ..
  429. * .. Executable Statements ..
  430. *
  431. * Decode and test the input parameters
  432. *
  433. INITU = LSAME( JOBU, 'I' )
  434. WANTU = INITU .OR. LSAME( JOBU, 'U' )
  435. *
  436. INITV = LSAME( JOBV, 'I' )
  437. WANTV = INITV .OR. LSAME( JOBV, 'V' )
  438. *
  439. INITQ = LSAME( JOBQ, 'I' )
  440. WANTQ = INITQ .OR. LSAME( JOBQ, 'Q' )
  441. *
  442. INFO = 0
  443. IF( .NOT.( INITU .OR. WANTU .OR. LSAME( JOBU, 'N' ) ) ) THEN
  444. INFO = -1
  445. ELSE IF( .NOT.( INITV .OR. WANTV .OR. LSAME( JOBV, 'N' ) ) ) THEN
  446. INFO = -2
  447. ELSE IF( .NOT.( INITQ .OR. WANTQ .OR. LSAME( JOBQ, 'N' ) ) ) THEN
  448. INFO = -3
  449. ELSE IF( M.LT.0 ) THEN
  450. INFO = -4
  451. ELSE IF( P.LT.0 ) THEN
  452. INFO = -5
  453. ELSE IF( N.LT.0 ) THEN
  454. INFO = -6
  455. ELSE IF( LDA.LT.MAX( 1, M ) ) THEN
  456. INFO = -10
  457. ELSE IF( LDB.LT.MAX( 1, P ) ) THEN
  458. INFO = -12
  459. ELSE IF( LDU.LT.1 .OR. ( WANTU .AND. LDU.LT.M ) ) THEN
  460. INFO = -18
  461. ELSE IF( LDV.LT.1 .OR. ( WANTV .AND. LDV.LT.P ) ) THEN
  462. INFO = -20
  463. ELSE IF( LDQ.LT.1 .OR. ( WANTQ .AND. LDQ.LT.N ) ) THEN
  464. INFO = -22
  465. END IF
  466. IF( INFO.NE.0 ) THEN
  467. CALL XERBLA( 'CTGSJA', -INFO )
  468. RETURN
  469. END IF
  470. *
  471. * Initialize U, V and Q, if necessary
  472. *
  473. IF( INITU )
  474. $ CALL CLASET( 'Full', M, M, CZERO, CONE, U, LDU )
  475. IF( INITV )
  476. $ CALL CLASET( 'Full', P, P, CZERO, CONE, V, LDV )
  477. IF( INITQ )
  478. $ CALL CLASET( 'Full', N, N, CZERO, CONE, Q, LDQ )
  479. *
  480. * Loop until convergence
  481. *
  482. UPPER = .FALSE.
  483. DO 40 KCYCLE = 1, MAXIT
  484. *
  485. UPPER = .NOT.UPPER
  486. *
  487. DO 20 I = 1, L - 1
  488. DO 10 J = I + 1, L
  489. *
  490. A1 = ZERO
  491. A2 = CZERO
  492. A3 = ZERO
  493. IF( K+I.LE.M )
  494. $ A1 = REAL( A( K+I, N-L+I ) )
  495. IF( K+J.LE.M )
  496. $ A3 = REAL( A( K+J, N-L+J ) )
  497. *
  498. B1 = REAL( B( I, N-L+I ) )
  499. B3 = REAL( B( J, N-L+J ) )
  500. *
  501. IF( UPPER ) THEN
  502. IF( K+I.LE.M )
  503. $ A2 = A( K+I, N-L+J )
  504. B2 = B( I, N-L+J )
  505. ELSE
  506. IF( K+J.LE.M )
  507. $ A2 = A( K+J, N-L+I )
  508. B2 = B( J, N-L+I )
  509. END IF
  510. *
  511. CALL CLAGS2( UPPER, A1, A2, A3, B1, B2, B3, CSU, SNU,
  512. $ CSV, SNV, CSQ, SNQ )
  513. *
  514. * Update (K+I)-th and (K+J)-th rows of matrix A: U**H *A
  515. *
  516. IF( K+J.LE.M )
  517. $ CALL CROT( L, A( K+J, N-L+1 ), LDA, A( K+I, N-L+1 ),
  518. $ LDA, CSU, CONJG( SNU ) )
  519. *
  520. * Update I-th and J-th rows of matrix B: V**H *B
  521. *
  522. CALL CROT( L, B( J, N-L+1 ), LDB, B( I, N-L+1 ), LDB,
  523. $ CSV, CONJG( SNV ) )
  524. *
  525. * Update (N-L+I)-th and (N-L+J)-th columns of matrices
  526. * A and B: A*Q and B*Q
  527. *
  528. CALL CROT( MIN( K+L, M ), A( 1, N-L+J ), 1,
  529. $ A( 1, N-L+I ), 1, CSQ, SNQ )
  530. *
  531. CALL CROT( L, B( 1, N-L+J ), 1, B( 1, N-L+I ), 1, CSQ,
  532. $ SNQ )
  533. *
  534. IF( UPPER ) THEN
  535. IF( K+I.LE.M )
  536. $ A( K+I, N-L+J ) = CZERO
  537. B( I, N-L+J ) = CZERO
  538. ELSE
  539. IF( K+J.LE.M )
  540. $ A( K+J, N-L+I ) = CZERO
  541. B( J, N-L+I ) = CZERO
  542. END IF
  543. *
  544. * Ensure that the diagonal elements of A and B are real.
  545. *
  546. IF( K+I.LE.M )
  547. $ A( K+I, N-L+I ) = REAL( A( K+I, N-L+I ) )
  548. IF( K+J.LE.M )
  549. $ A( K+J, N-L+J ) = REAL( A( K+J, N-L+J ) )
  550. B( I, N-L+I ) = REAL( B( I, N-L+I ) )
  551. B( J, N-L+J ) = REAL( B( J, N-L+J ) )
  552. *
  553. * Update unitary matrices U, V, Q, if desired.
  554. *
  555. IF( WANTU .AND. K+J.LE.M )
  556. $ CALL CROT( M, U( 1, K+J ), 1, U( 1, K+I ), 1, CSU,
  557. $ SNU )
  558. *
  559. IF( WANTV )
  560. $ CALL CROT( P, V( 1, J ), 1, V( 1, I ), 1, CSV, SNV )
  561. *
  562. IF( WANTQ )
  563. $ CALL CROT( N, Q( 1, N-L+J ), 1, Q( 1, N-L+I ), 1, CSQ,
  564. $ SNQ )
  565. *
  566. 10 CONTINUE
  567. 20 CONTINUE
  568. *
  569. IF( .NOT.UPPER ) THEN
  570. *
  571. * The matrices A13 and B13 were lower triangular at the start
  572. * of the cycle, and are now upper triangular.
  573. *
  574. * Convergence test: test the parallelism of the corresponding
  575. * rows of A and B.
  576. *
  577. ERROR = ZERO
  578. DO 30 I = 1, MIN( L, M-K )
  579. CALL CCOPY( L-I+1, A( K+I, N-L+I ), LDA, WORK, 1 )
  580. CALL CCOPY( L-I+1, B( I, N-L+I ), LDB, WORK( L+1 ), 1 )
  581. CALL CLAPLL( L-I+1, WORK, 1, WORK( L+1 ), 1, SSMIN )
  582. ERROR = MAX( ERROR, SSMIN )
  583. 30 CONTINUE
  584. *
  585. IF( ABS( ERROR ).LE.MIN( TOLA, TOLB ) )
  586. $ GO TO 50
  587. END IF
  588. *
  589. * End of cycle loop
  590. *
  591. 40 CONTINUE
  592. *
  593. * The algorithm has not converged after MAXIT cycles.
  594. *
  595. INFO = 1
  596. GO TO 100
  597. *
  598. 50 CONTINUE
  599. *
  600. * If ERROR <= MIN(TOLA,TOLB), then the algorithm has converged.
  601. * Compute the generalized singular value pairs (ALPHA, BETA), and
  602. * set the triangular matrix R to array A.
  603. *
  604. DO 60 I = 1, K
  605. ALPHA( I ) = ONE
  606. BETA( I ) = ZERO
  607. 60 CONTINUE
  608. *
  609. DO 70 I = 1, MIN( L, M-K )
  610. *
  611. A1 = REAL( A( K+I, N-L+I ) )
  612. B1 = REAL( B( I, N-L+I ) )
  613. *
  614. IF( A1.NE.ZERO ) THEN
  615. GAMMA = B1 / A1
  616. *
  617. IF( GAMMA.LT.ZERO ) THEN
  618. CALL CSSCAL( L-I+1, -ONE, B( I, N-L+I ), LDB )
  619. IF( WANTV )
  620. $ CALL CSSCAL( P, -ONE, V( 1, I ), 1 )
  621. END IF
  622. *
  623. CALL SLARTG( ABS( GAMMA ), ONE, BETA( K+I ), ALPHA( K+I ),
  624. $ RWK )
  625. *
  626. IF( ALPHA( K+I ).GE.BETA( K+I ) ) THEN
  627. CALL CSSCAL( L-I+1, ONE / ALPHA( K+I ), A( K+I, N-L+I ),
  628. $ LDA )
  629. ELSE
  630. CALL CSSCAL( L-I+1, ONE / BETA( K+I ), B( I, N-L+I ),
  631. $ LDB )
  632. CALL CCOPY( L-I+1, B( I, N-L+I ), LDB, A( K+I, N-L+I ),
  633. $ LDA )
  634. END IF
  635. *
  636. ELSE
  637. ALPHA( K+I ) = ZERO
  638. BETA( K+I ) = ONE
  639. CALL CCOPY( L-I+1, B( I, N-L+I ), LDB, A( K+I, N-L+I ),
  640. $ LDA )
  641. END IF
  642. 70 CONTINUE
  643. *
  644. * Post-assignment
  645. *
  646. DO 80 I = M + 1, K + L
  647. ALPHA( I ) = ZERO
  648. BETA( I ) = ONE
  649. 80 CONTINUE
  650. *
  651. IF( K+L.LT.N ) THEN
  652. DO 90 I = K + L + 1, N
  653. ALPHA( I ) = ZERO
  654. BETA( I ) = ZERO
  655. 90 CONTINUE
  656. END IF
  657. *
  658. 100 CONTINUE
  659. NCYCLE = KCYCLE
  660. *
  661. RETURN
  662. *
  663. * End of CTGSJA
  664. *
  665. END