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dgesvdq.f 58 kB

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  1. *> \brief <b> DGESVDQ computes the singular value decomposition (SVD) with a QR-Preconditioned QR SVD Method for GE matrices</b>
  2. *
  3. * =========== DOCUMENTATION ===========
  4. *
  5. * Online html documentation available at
  6. * http://www.netlib.org/lapack/explore-html/
  7. *
  8. *> \htmlonly
  9. *> Download DGESVDQ + dependencies
  10. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dgesvdq.f">
  11. *> [TGZ]</a>
  12. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dgesvdq.f">
  13. *> [ZIP]</a>
  14. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dgesvdq.f">
  15. *> [TXT]</a>
  16. *> \endhtmlonly
  17. *
  18. * Definition:
  19. * ===========
  20. *
  21. * SUBROUTINE DGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
  22. * S, U, LDU, V, LDV, NUMRANK, IWORK, LIWORK,
  23. * WORK, LWORK, RWORK, LRWORK, INFO )
  24. *
  25. * .. Scalar Arguments ..
  26. * IMPLICIT NONE
  27. * CHARACTER JOBA, JOBP, JOBR, JOBU, JOBV
  28. * INTEGER M, N, LDA, LDU, LDV, NUMRANK, LIWORK, LWORK, LRWORK,
  29. * INFO
  30. * ..
  31. * .. Array Arguments ..
  32. * DOUBLE PRECISION A( LDA, * ), U( LDU, * ), V( LDV, * ), WORK( * )
  33. * DOUBLE PRECISION S( * ), RWORK( * )
  34. * INTEGER IWORK( * )
  35. * ..
  36. *
  37. *
  38. *> \par Purpose:
  39. * =============
  40. *>
  41. *> \verbatim
  42. *>
  43. *> DGESVDQ computes the singular value decomposition (SVD) of a real
  44. *> M-by-N matrix A, where M >= N. The SVD of A is written as
  45. *> [++] [xx] [x0] [xx]
  46. *> A = U * SIGMA * V^*, [++] = [xx] * [ox] * [xx]
  47. *> [++] [xx]
  48. *> where SIGMA is an N-by-N diagonal matrix, U is an M-by-N orthonormal
  49. *> matrix, and V is an N-by-N orthogonal matrix. The diagonal elements
  50. *> of SIGMA are the singular values of A. The columns of U and V are the
  51. *> left and the right singular vectors of A, respectively.
  52. *> \endverbatim
  53. *
  54. * Arguments:
  55. * ==========
  56. *
  57. *> \param[in] JOBA
  58. *> \verbatim
  59. *> JOBA is CHARACTER*1
  60. *> Specifies the level of accuracy in the computed SVD
  61. *> = 'A' The requested accuracy corresponds to having the backward
  62. *> error bounded by || delta A ||_F <= f(m,n) * EPS * || A ||_F,
  63. *> where EPS = DLAMCH('Epsilon'). This authorises DGESVDQ to
  64. *> truncate the computed triangular factor in a rank revealing
  65. *> QR factorization whenever the truncated part is below the
  66. *> threshold of the order of EPS * ||A||_F. This is aggressive
  67. *> truncation level.
  68. *> = 'M' Similarly as with 'A', but the truncation is more gentle: it
  69. *> is allowed only when there is a drop on the diagonal of the
  70. *> triangular factor in the QR factorization. This is medium
  71. *> truncation level.
  72. *> = 'H' High accuracy requested. No numerical rank determination based
  73. *> on the rank revealing QR factorization is attempted.
  74. *> = 'E' Same as 'H', and in addition the condition number of column
  75. *> scaled A is estimated and returned in RWORK(1).
  76. *> N^(-1/4)*RWORK(1) <= ||pinv(A_scaled)||_2 <= N^(1/4)*RWORK(1)
  77. *> \endverbatim
  78. *>
  79. *> \param[in] JOBP
  80. *> \verbatim
  81. *> JOBP is CHARACTER*1
  82. *> = 'P' The rows of A are ordered in decreasing order with respect to
  83. *> ||A(i,:)||_\infty. This enhances numerical accuracy at the cost
  84. *> of extra data movement. Recommended for numerical robustness.
  85. *> = 'N' No row pivoting.
  86. *> \endverbatim
  87. *>
  88. *> \param[in] JOBR
  89. *> \verbatim
  90. *> JOBR is CHARACTER*1
  91. *> = 'T' After the initial pivoted QR factorization, DGESVD is applied to
  92. *> the transposed R**T of the computed triangular factor R. This involves
  93. *> some extra data movement (matrix transpositions). Useful for
  94. *> experiments, research and development.
  95. *> = 'N' The triangular factor R is given as input to DGESVD. This may be
  96. *> preferred as it involves less data movement.
  97. *> \endverbatim
  98. *>
  99. *> \param[in] JOBU
  100. *> \verbatim
  101. *> JOBU is CHARACTER*1
  102. *> = 'A' All M left singular vectors are computed and returned in the
  103. *> matrix U. See the description of U.
  104. *> = 'S' or 'U' N = min(M,N) left singular vectors are computed and returned
  105. *> in the matrix U. See the description of U.
  106. *> = 'R' Numerical rank NUMRANK is determined and only NUMRANK left singular
  107. *> vectors are computed and returned in the matrix U.
  108. *> = 'F' The N left singular vectors are returned in factored form as the
  109. *> product of the Q factor from the initial QR factorization and the
  110. *> N left singular vectors of (R**T , 0)**T. If row pivoting is used,
  111. *> then the necessary information on the row pivoting is stored in
  112. *> IWORK(N+1:N+M-1).
  113. *> = 'N' The left singular vectors are not computed.
  114. *> \endverbatim
  115. *>
  116. *> \param[in] JOBV
  117. *> \verbatim
  118. *> JOBV is CHARACTER*1
  119. *> = 'A', 'V' All N right singular vectors are computed and returned in
  120. *> the matrix V.
  121. *> = 'R' Numerical rank NUMRANK is determined and only NUMRANK right singular
  122. *> vectors are computed and returned in the matrix V. This option is
  123. *> allowed only if JOBU = 'R' or JOBU = 'N'; otherwise it is illegal.
  124. *> = 'N' The right singular vectors are not computed.
  125. *> \endverbatim
  126. *>
  127. *> \param[in] M
  128. *> \verbatim
  129. *> M is INTEGER
  130. *> The number of rows of the input matrix A. M >= 0.
  131. *> \endverbatim
  132. *>
  133. *> \param[in] N
  134. *> \verbatim
  135. *> N is INTEGER
  136. *> The number of columns of the input matrix A. M >= N >= 0.
  137. *> \endverbatim
  138. *>
  139. *> \param[in,out] A
  140. *> \verbatim
  141. *> A is DOUBLE PRECISION array of dimensions LDA x N
  142. *> On entry, the input matrix A.
  143. *> On exit, if JOBU .NE. 'N' or JOBV .NE. 'N', the lower triangle of A contains
  144. *> the Householder vectors as stored by DGEQP3. If JOBU = 'F', these Householder
  145. *> vectors together with WORK(1:N) can be used to restore the Q factors from
  146. *> the initial pivoted QR factorization of A. See the description of U.
  147. *> \endverbatim
  148. *>
  149. *> \param[in] LDA
  150. *> \verbatim
  151. *> LDA is INTEGER.
  152. *> The leading dimension of the array A. LDA >= max(1,M).
  153. *> \endverbatim
  154. *>
  155. *> \param[out] S
  156. *> \verbatim
  157. *> S is DOUBLE PRECISION array of dimension N.
  158. *> The singular values of A, ordered so that S(i) >= S(i+1).
  159. *> \endverbatim
  160. *>
  161. *> \param[out] U
  162. *> \verbatim
  163. *> U is DOUBLE PRECISION array, dimension
  164. *> LDU x M if JOBU = 'A'; see the description of LDU. In this case,
  165. *> on exit, U contains the M left singular vectors.
  166. *> LDU x N if JOBU = 'S', 'U', 'R' ; see the description of LDU. In this
  167. *> case, U contains the leading N or the leading NUMRANK left singular vectors.
  168. *> LDU x N if JOBU = 'F' ; see the description of LDU. In this case U
  169. *> contains N x N orthogonal matrix that can be used to form the left
  170. *> singular vectors.
  171. *> If JOBU = 'N', U is not referenced.
  172. *> \endverbatim
  173. *>
  174. *> \param[in] LDU
  175. *> \verbatim
  176. *> LDU is INTEGER.
  177. *> The leading dimension of the array U.
  178. *> If JOBU = 'A', 'S', 'U', 'R', LDU >= max(1,M).
  179. *> If JOBU = 'F', LDU >= max(1,N).
  180. *> Otherwise, LDU >= 1.
  181. *> \endverbatim
  182. *>
  183. *> \param[out] V
  184. *> \verbatim
  185. *> V is DOUBLE PRECISION array, dimension
  186. *> LDV x N if JOBV = 'A', 'V', 'R' or if JOBA = 'E' .
  187. *> If JOBV = 'A', or 'V', V contains the N-by-N orthogonal matrix V**T;
  188. *> If JOBV = 'R', V contains the first NUMRANK rows of V**T (the right
  189. *> singular vectors, stored rowwise, of the NUMRANK largest singular values).
  190. *> If JOBV = 'N' and JOBA = 'E', V is used as a workspace.
  191. *> If JOBV = 'N', and JOBA.NE.'E', V is not referenced.
  192. *> \endverbatim
  193. *>
  194. *> \param[in] LDV
  195. *> \verbatim
  196. *> LDV is INTEGER
  197. *> The leading dimension of the array V.
  198. *> If JOBV = 'A', 'V', 'R', or JOBA = 'E', LDV >= max(1,N).
  199. *> Otherwise, LDV >= 1.
  200. *> \endverbatim
  201. *>
  202. *> \param[out] NUMRANK
  203. *> \verbatim
  204. *> NUMRANK is INTEGER
  205. *> NUMRANK is the numerical rank first determined after the rank
  206. *> revealing QR factorization, following the strategy specified by the
  207. *> value of JOBA. If JOBV = 'R' and JOBU = 'R', only NUMRANK
  208. *> leading singular values and vectors are then requested in the call
  209. *> of DGESVD. The final value of NUMRANK might be further reduced if
  210. *> some singular values are computed as zeros.
  211. *> \endverbatim
  212. *>
  213. *> \param[out] IWORK
  214. *> \verbatim
  215. *> IWORK is INTEGER array, dimension (max(1, LIWORK)).
  216. *> On exit, IWORK(1:N) contains column pivoting permutation of the
  217. *> rank revealing QR factorization.
  218. *> If JOBP = 'P', IWORK(N+1:N+M-1) contains the indices of the sequence
  219. *> of row swaps used in row pivoting. These can be used to restore the
  220. *> left singular vectors in the case JOBU = 'F'.
  221. *>
  222. *> If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0,
  223. *> LIWORK(1) returns the minimal LIWORK.
  224. *> \endverbatim
  225. *>
  226. *> \param[in] LIWORK
  227. *> \verbatim
  228. *> LIWORK is INTEGER
  229. *> The dimension of the array IWORK.
  230. *> LIWORK >= N + M - 1, if JOBP = 'P' and JOBA .NE. 'E';
  231. *> LIWORK >= N if JOBP = 'N' and JOBA .NE. 'E';
  232. *> LIWORK >= N + M - 1 + N, if JOBP = 'P' and JOBA = 'E';
  233. *> LIWORK >= N + N if JOBP = 'N' and JOBA = 'E'.
  234. *
  235. *> If LIWORK = -1, then a workspace query is assumed; the routine
  236. *> only calculates and returns the optimal and minimal sizes
  237. *> for the WORK, IWORK, and RWORK arrays, and no error
  238. *> message related to LWORK is issued by XERBLA.
  239. *> \endverbatim
  240. *>
  241. *> \param[out] WORK
  242. *> \verbatim
  243. *> WORK is DOUBLE PRECISION array, dimension (max(2, LWORK)), used as a workspace.
  244. *> On exit, if, on entry, LWORK.NE.-1, WORK(1:N) contains parameters
  245. *> needed to recover the Q factor from the QR factorization computed by
  246. *> DGEQP3.
  247. *>
  248. *> If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0,
  249. *> WORK(1) returns the optimal LWORK, and
  250. *> WORK(2) returns the minimal LWORK.
  251. *> \endverbatim
  252. *>
  253. *> \param[in,out] LWORK
  254. *> \verbatim
  255. *> LWORK is INTEGER
  256. *> The dimension of the array WORK. It is determined as follows:
  257. *> Let LWQP3 = 3*N+1, LWCON = 3*N, and let
  258. *> LWORQ = { MAX( N, 1 ), if JOBU = 'R', 'S', or 'U'
  259. *> { MAX( M, 1 ), if JOBU = 'A'
  260. *> LWSVD = MAX( 5*N, 1 )
  261. *> LWLQF = MAX( N/2, 1 ), LWSVD2 = MAX( 5*(N/2), 1 ), LWORLQ = MAX( N, 1 ),
  262. *> LWQRF = MAX( N/2, 1 ), LWORQ2 = MAX( N, 1 )
  263. *> Then the minimal value of LWORK is:
  264. *> = MAX( N + LWQP3, LWSVD ) if only the singular values are needed;
  265. *> = MAX( N + LWQP3, LWCON, LWSVD ) if only the singular values are needed,
  266. *> and a scaled condition estimate requested;
  267. *>
  268. *> = N + MAX( LWQP3, LWSVD, LWORQ ) if the singular values and the left
  269. *> singular vectors are requested;
  270. *> = N + MAX( LWQP3, LWCON, LWSVD, LWORQ ) if the singular values and the left
  271. *> singular vectors are requested, and also
  272. *> a scaled condition estimate requested;
  273. *>
  274. *> = N + MAX( LWQP3, LWSVD ) if the singular values and the right
  275. *> singular vectors are requested;
  276. *> = N + MAX( LWQP3, LWCON, LWSVD ) if the singular values and the right
  277. *> singular vectors are requested, and also
  278. *> a scaled condition etimate requested;
  279. *>
  280. *> = N + MAX( LWQP3, LWSVD, LWORQ ) if the full SVD is requested with JOBV = 'R';
  281. *> independent of JOBR;
  282. *> = N + MAX( LWQP3, LWCON, LWSVD, LWORQ ) if the full SVD is requested,
  283. *> JOBV = 'R' and, also a scaled condition
  284. *> estimate requested; independent of JOBR;
  285. *> = MAX( N + MAX( LWQP3, LWSVD, LWORQ ),
  286. *> N + MAX( LWQP3, N/2+LWLQF, N/2+LWSVD2, N/2+LWORLQ, LWORQ) ) if the
  287. *> full SVD is requested with JOBV = 'A' or 'V', and
  288. *> JOBR ='N'
  289. *> = MAX( N + MAX( LWQP3, LWCON, LWSVD, LWORQ ),
  290. *> N + MAX( LWQP3, LWCON, N/2+LWLQF, N/2+LWSVD2, N/2+LWORLQ, LWORQ ) )
  291. *> if the full SVD is requested with JOBV = 'A' or 'V', and
  292. *> JOBR ='N', and also a scaled condition number estimate
  293. *> requested.
  294. *> = MAX( N + MAX( LWQP3, LWSVD, LWORQ ),
  295. *> N + MAX( LWQP3, N/2+LWQRF, N/2+LWSVD2, N/2+LWORQ2, LWORQ ) ) if the
  296. *> full SVD is requested with JOBV = 'A', 'V', and JOBR ='T'
  297. *> = MAX( N + MAX( LWQP3, LWCON, LWSVD, LWORQ ),
  298. *> N + MAX( LWQP3, LWCON, N/2+LWQRF, N/2+LWSVD2, N/2+LWORQ2, LWORQ ) )
  299. *> if the full SVD is requested with JOBV = 'A' or 'V', and
  300. *> JOBR ='T', and also a scaled condition number estimate
  301. *> requested.
  302. *> Finally, LWORK must be at least two: LWORK = MAX( 2, LWORK ).
  303. *>
  304. *> If LWORK = -1, then a workspace query is assumed; the routine
  305. *> only calculates and returns the optimal and minimal sizes
  306. *> for the WORK, IWORK, and RWORK arrays, and no error
  307. *> message related to LWORK is issued by XERBLA.
  308. *> \endverbatim
  309. *>
  310. *> \param[out] RWORK
  311. *> \verbatim
  312. *> RWORK is DOUBLE PRECISION array, dimension (max(1, LRWORK)).
  313. *> On exit,
  314. *> 1. If JOBA = 'E', RWORK(1) contains an estimate of the condition
  315. *> number of column scaled A. If A = C * D where D is diagonal and C
  316. *> has unit columns in the Euclidean norm, then, assuming full column rank,
  317. *> N^(-1/4) * RWORK(1) <= ||pinv(C)||_2 <= N^(1/4) * RWORK(1).
  318. *> Otherwise, RWORK(1) = -1.
  319. *> 2. RWORK(2) contains the number of singular values computed as
  320. *> exact zeros in DGESVD applied to the upper triangular or trapeziodal
  321. *> R (from the initial QR factorization). In case of early exit (no call to
  322. *> DGESVD, such as in the case of zero matrix) RWORK(2) = -1.
  323. *>
  324. *> If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0,
  325. *> RWORK(1) returns the minimal LRWORK.
  326. *> \endverbatim
  327. *>
  328. *> \param[in] LRWORK
  329. *> \verbatim
  330. *> LRWORK is INTEGER.
  331. *> The dimension of the array RWORK.
  332. *> If JOBP ='P', then LRWORK >= MAX(2, M).
  333. *> Otherwise, LRWORK >= 2
  334. *
  335. *> If LRWORK = -1, then a workspace query is assumed; the routine
  336. *> only calculates and returns the optimal and minimal sizes
  337. *> for the WORK, IWORK, and RWORK arrays, and no error
  338. *> message related to LWORK is issued by XERBLA.
  339. *> \endverbatim
  340. *>
  341. *> \param[out] INFO
  342. *> \verbatim
  343. *> INFO is INTEGER
  344. *> = 0: successful exit.
  345. *> < 0: if INFO = -i, the i-th argument had an illegal value.
  346. *> > 0: if DBDSQR did not converge, INFO specifies how many superdiagonals
  347. *> of an intermediate bidiagonal form B (computed in DGESVD) did not
  348. *> converge to zero.
  349. *> \endverbatim
  350. *
  351. *> \par Further Details:
  352. * ========================
  353. *>
  354. *> \verbatim
  355. *>
  356. *> 1. The data movement (matrix transpose) is coded using simple nested
  357. *> DO-loops because BLAS and LAPACK do not provide corresponding subroutines.
  358. *> Those DO-loops are easily identified in this source code - by the CONTINUE
  359. *> statements labeled with 11**. In an optimized version of this code, the
  360. *> nested DO loops should be replaced with calls to an optimized subroutine.
  361. *> 2. This code scales A by 1/SQRT(M) if the largest ABS(A(i,j)) could cause
  362. *> column norm overflow. This is the minial precaution and it is left to the
  363. *> SVD routine (CGESVD) to do its own preemptive scaling if potential over-
  364. *> or underflows are detected. To avoid repeated scanning of the array A,
  365. *> an optimal implementation would do all necessary scaling before calling
  366. *> CGESVD and the scaling in CGESVD can be switched off.
  367. *> 3. Other comments related to code optimization are given in comments in the
  368. *> code, enlosed in [[double brackets]].
  369. *> \endverbatim
  370. *
  371. *> \par Bugs, examples and comments
  372. * ===========================
  373. *
  374. *> \verbatim
  375. *> Please report all bugs and send interesting examples and/or comments to
  376. *> drmac@math.hr. Thank you.
  377. *> \endverbatim
  378. *
  379. *> \par References
  380. * ===============
  381. *
  382. *> \verbatim
  383. *> [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for
  384. *> Computing the SVD with High Accuracy. ACM Trans. Math. Softw.
  385. *> 44(1): 11:1-11:30 (2017)
  386. *>
  387. *> SIGMA library, xGESVDQ section updated February 2016.
  388. *> Developed and coded by Zlatko Drmac, Department of Mathematics
  389. *> University of Zagreb, Croatia, drmac@math.hr
  390. *> \endverbatim
  391. *
  392. *
  393. *> \par Contributors:
  394. * ==================
  395. *>
  396. *> \verbatim
  397. *> Developed and coded by Zlatko Drmac, Department of Mathematics
  398. *> University of Zagreb, Croatia, drmac@math.hr
  399. *> \endverbatim
  400. *
  401. * Authors:
  402. * ========
  403. *
  404. *> \author Univ. of Tennessee
  405. *> \author Univ. of California Berkeley
  406. *> \author Univ. of Colorado Denver
  407. *> \author NAG Ltd.
  408. *
  409. *> \date November 2018
  410. *
  411. *> \ingroup doubleGEsing
  412. *
  413. * =====================================================================
  414. SUBROUTINE DGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
  415. $ S, U, LDU, V, LDV, NUMRANK, IWORK, LIWORK,
  416. $ WORK, LWORK, RWORK, LRWORK, INFO )
  417. * .. Scalar Arguments ..
  418. IMPLICIT NONE
  419. CHARACTER JOBA, JOBP, JOBR, JOBU, JOBV
  420. INTEGER M, N, LDA, LDU, LDV, NUMRANK, LIWORK, LWORK, LRWORK,
  421. $ INFO
  422. * ..
  423. * .. Array Arguments ..
  424. DOUBLE PRECISION A( LDA, * ), U( LDU, * ), V( LDV, * ), WORK( * )
  425. DOUBLE PRECISION S( * ), RWORK( * )
  426. INTEGER IWORK( * )
  427. *
  428. * =====================================================================
  429. *
  430. * .. Parameters ..
  431. DOUBLE PRECISION ZERO, ONE
  432. PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 )
  433. * .. Local Scalars ..
  434. INTEGER IERR, IWOFF, NR, N1, OPTRATIO, p, q
  435. INTEGER LWCON, LWQP3, LWRK_DGELQF, LWRK_DGESVD, LWRK_DGESVD2,
  436. $ LWRK_DGEQP3, LWRK_DGEQRF, LWRK_DORMLQ, LWRK_DORMQR,
  437. $ LWRK_DORMQR2, LWLQF, LWQRF, LWSVD, LWSVD2, LWORQ,
  438. $ LWORQ2, LWORLQ, MINWRK, MINWRK2, OPTWRK, OPTWRK2,
  439. $ IMINWRK, RMINWRK
  440. LOGICAL ACCLA, ACCLM, ACCLH, ASCALED, CONDA, DNTWU, DNTWV,
  441. $ LQUERY, LSVC0, LSVEC, ROWPRM, RSVEC, RTRANS, WNTUA,
  442. $ WNTUF, WNTUR, WNTUS, WNTVA, WNTVR
  443. DOUBLE PRECISION BIG, EPSLN, RTMP, SCONDA, SFMIN
  444. * .. Local Arrays
  445. DOUBLE PRECISION RDUMMY(1)
  446. * ..
  447. * .. External Subroutines (BLAS, LAPACK)
  448. EXTERNAL DGELQF, DGEQP3, DGEQRF, DGESVD, DLACPY, DLAPMT,
  449. $ DLASCL, DLASET, DLASWP, DSCAL, DPOCON, DORMLQ,
  450. $ DORMQR, XERBLA
  451. * ..
  452. * .. External Functions (BLAS, LAPACK)
  453. LOGICAL LSAME
  454. INTEGER IDAMAX
  455. DOUBLE PRECISION DLANGE, DNRM2, DLAMCH
  456. EXTERNAL DLANGE, LSAME, IDAMAX, DNRM2, DLAMCH
  457. * ..
  458. * .. Intrinsic Functions ..
  459. *
  460. INTRINSIC ABS, MAX, MIN, DBLE, SQRT
  461. *
  462. * Test the input arguments
  463. *
  464. WNTUS = LSAME( JOBU, 'S' ) .OR. LSAME( JOBU, 'U' )
  465. WNTUR = LSAME( JOBU, 'R' )
  466. WNTUA = LSAME( JOBU, 'A' )
  467. WNTUF = LSAME( JOBU, 'F' )
  468. LSVC0 = WNTUS .OR. WNTUR .OR. WNTUA
  469. LSVEC = LSVC0 .OR. WNTUF
  470. DNTWU = LSAME( JOBU, 'N' )
  471. *
  472. WNTVR = LSAME( JOBV, 'R' )
  473. WNTVA = LSAME( JOBV, 'A' ) .OR. LSAME( JOBV, 'V' )
  474. RSVEC = WNTVR .OR. WNTVA
  475. DNTWV = LSAME( JOBV, 'N' )
  476. *
  477. ACCLA = LSAME( JOBA, 'A' )
  478. ACCLM = LSAME( JOBA, 'M' )
  479. CONDA = LSAME( JOBA, 'E' )
  480. ACCLH = LSAME( JOBA, 'H' ) .OR. CONDA
  481. *
  482. ROWPRM = LSAME( JOBP, 'P' )
  483. RTRANS = LSAME( JOBR, 'T' )
  484. *
  485. IF ( ROWPRM ) THEN
  486. IF ( CONDA ) THEN
  487. IMINWRK = MAX( 1, N + M - 1 + N )
  488. ELSE
  489. IMINWRK = MAX( 1, N + M - 1 )
  490. END IF
  491. RMINWRK = MAX( 2, M )
  492. ELSE
  493. IF ( CONDA ) THEN
  494. IMINWRK = MAX( 1, N + N )
  495. ELSE
  496. IMINWRK = MAX( 1, N )
  497. END IF
  498. RMINWRK = 2
  499. END IF
  500. LQUERY = (LIWORK .EQ. -1 .OR. LWORK .EQ. -1 .OR. LRWORK .EQ. -1)
  501. INFO = 0
  502. IF ( .NOT. ( ACCLA .OR. ACCLM .OR. ACCLH ) ) THEN
  503. INFO = -1
  504. ELSE IF ( .NOT.( ROWPRM .OR. LSAME( JOBP, 'N' ) ) ) THEN
  505. INFO = -2
  506. ELSE IF ( .NOT.( RTRANS .OR. LSAME( JOBR, 'N' ) ) ) THEN
  507. INFO = -3
  508. ELSE IF ( .NOT.( LSVEC .OR. DNTWU ) ) THEN
  509. INFO = -4
  510. ELSE IF ( WNTUR .AND. WNTVA ) THEN
  511. INFO = -5
  512. ELSE IF ( .NOT.( RSVEC .OR. DNTWV )) THEN
  513. INFO = -5
  514. ELSE IF ( M.LT.0 ) THEN
  515. INFO = -6
  516. ELSE IF ( ( N.LT.0 ) .OR. ( N.GT.M ) ) THEN
  517. INFO = -7
  518. ELSE IF ( LDA.LT.MAX( 1, M ) ) THEN
  519. INFO = -9
  520. ELSE IF ( LDU.LT.1 .OR. ( LSVC0 .AND. LDU.LT.M ) .OR.
  521. $ ( WNTUF .AND. LDU.LT.N ) ) THEN
  522. INFO = -12
  523. ELSE IF ( LDV.LT.1 .OR. ( RSVEC .AND. LDV.LT.N ) .OR.
  524. $ ( CONDA .AND. LDV.LT.N ) ) THEN
  525. INFO = -14
  526. ELSE IF ( LIWORK .LT. IMINWRK .AND. .NOT. LQUERY ) THEN
  527. INFO = -17
  528. END IF
  529. *
  530. *
  531. IF ( INFO .EQ. 0 ) THEN
  532. * .. compute the minimal and the optimal workspace lengths
  533. * [[The expressions for computing the minimal and the optimal
  534. * values of LWORK are written with a lot of redundancy and
  535. * can be simplified. However, this detailed form is easier for
  536. * maintenance and modifications of the code.]]
  537. *
  538. * .. minimal workspace length for DGEQP3 of an M x N matrix
  539. LWQP3 = 3 * N + 1
  540. * .. minimal workspace length for DORMQR to build left singular vectors
  541. IF ( WNTUS .OR. WNTUR ) THEN
  542. LWORQ = MAX( N , 1 )
  543. ELSE IF ( WNTUA ) THEN
  544. LWORQ = MAX( M , 1 )
  545. END IF
  546. * .. minimal workspace length for DPOCON of an N x N matrix
  547. LWCON = 3 * N
  548. * .. DGESVD of an N x N matrix
  549. LWSVD = MAX( 5 * N, 1 )
  550. IF ( LQUERY ) THEN
  551. CALL DGEQP3( M, N, A, LDA, IWORK, RDUMMY, RDUMMY, -1,
  552. $ IERR )
  553. LWRK_DGEQP3 = INT( RDUMMY(1) )
  554. IF ( WNTUS .OR. WNTUR ) THEN
  555. CALL DORMQR( 'L', 'N', M, N, N, A, LDA, RDUMMY, U,
  556. $ LDU, RDUMMY, -1, IERR )
  557. LWRK_DORMQR = INT( RDUMMY(1) )
  558. ELSE IF ( WNTUA ) THEN
  559. CALL DORMQR( 'L', 'N', M, M, N, A, LDA, RDUMMY, U,
  560. $ LDU, RDUMMY, -1, IERR )
  561. LWRK_DORMQR = INT( RDUMMY(1) )
  562. ELSE
  563. LWRK_DORMQR = 0
  564. END IF
  565. END IF
  566. MINWRK = 2
  567. OPTWRK = 2
  568. IF ( .NOT. (LSVEC .OR. RSVEC )) THEN
  569. * .. minimal and optimal sizes of the workspace if
  570. * only the singular values are requested
  571. IF ( CONDA ) THEN
  572. MINWRK = MAX( N+LWQP3, LWCON, LWSVD )
  573. ELSE
  574. MINWRK = MAX( N+LWQP3, LWSVD )
  575. END IF
  576. IF ( LQUERY ) THEN
  577. CALL DGESVD( 'N', 'N', N, N, A, LDA, S, U, LDU,
  578. $ V, LDV, RDUMMY, -1, IERR )
  579. LWRK_DGESVD = INT( RDUMMY(1) )
  580. IF ( CONDA ) THEN
  581. OPTWRK = MAX( N+LWRK_DGEQP3, N+LWCON, LWRK_DGESVD )
  582. ELSE
  583. OPTWRK = MAX( N+LWRK_DGEQP3, LWRK_DGESVD )
  584. END IF
  585. END IF
  586. ELSE IF ( LSVEC .AND. (.NOT.RSVEC) ) THEN
  587. * .. minimal and optimal sizes of the workspace if the
  588. * singular values and the left singular vectors are requested
  589. IF ( CONDA ) THEN
  590. MINWRK = N + MAX( LWQP3, LWCON, LWSVD, LWORQ )
  591. ELSE
  592. MINWRK = N + MAX( LWQP3, LWSVD, LWORQ )
  593. END IF
  594. IF ( LQUERY ) THEN
  595. IF ( RTRANS ) THEN
  596. CALL DGESVD( 'N', 'O', N, N, A, LDA, S, U, LDU,
  597. $ V, LDV, RDUMMY, -1, IERR )
  598. ELSE
  599. CALL DGESVD( 'O', 'N', N, N, A, LDA, S, U, LDU,
  600. $ V, LDV, RDUMMY, -1, IERR )
  601. END IF
  602. LWRK_DGESVD = INT( RDUMMY(1) )
  603. IF ( CONDA ) THEN
  604. OPTWRK = N + MAX( LWRK_DGEQP3, LWCON, LWRK_DGESVD,
  605. $ LWRK_DORMQR )
  606. ELSE
  607. OPTWRK = N + MAX( LWRK_DGEQP3, LWRK_DGESVD,
  608. $ LWRK_DORMQR )
  609. END IF
  610. END IF
  611. ELSE IF ( RSVEC .AND. (.NOT.LSVEC) ) THEN
  612. * .. minimal and optimal sizes of the workspace if the
  613. * singular values and the right singular vectors are requested
  614. IF ( CONDA ) THEN
  615. MINWRK = N + MAX( LWQP3, LWCON, LWSVD )
  616. ELSE
  617. MINWRK = N + MAX( LWQP3, LWSVD )
  618. END IF
  619. IF ( LQUERY ) THEN
  620. IF ( RTRANS ) THEN
  621. CALL DGESVD( 'O', 'N', N, N, A, LDA, S, U, LDU,
  622. $ V, LDV, RDUMMY, -1, IERR )
  623. ELSE
  624. CALL DGESVD( 'N', 'O', N, N, A, LDA, S, U, LDU,
  625. $ V, LDV, RDUMMY, -1, IERR )
  626. END IF
  627. LWRK_DGESVD = INT( RDUMMY(1) )
  628. IF ( CONDA ) THEN
  629. OPTWRK = N + MAX( LWRK_DGEQP3, LWCON, LWRK_DGESVD )
  630. ELSE
  631. OPTWRK = N + MAX( LWRK_DGEQP3, LWRK_DGESVD )
  632. END IF
  633. END IF
  634. ELSE
  635. * .. minimal and optimal sizes of the workspace if the
  636. * full SVD is requested
  637. IF ( RTRANS ) THEN
  638. MINWRK = MAX( LWQP3, LWSVD, LWORQ )
  639. IF ( CONDA ) MINWRK = MAX( MINWRK, LWCON )
  640. MINWRK = MINWRK + N
  641. IF ( WNTVA ) THEN
  642. * .. minimal workspace length for N x N/2 DGEQRF
  643. LWQRF = MAX( N/2, 1 )
  644. * .. minimal workspace lengt for N/2 x N/2 DGESVD
  645. LWSVD2 = MAX( 5 * (N/2), 1 )
  646. LWORQ2 = MAX( N, 1 )
  647. MINWRK2 = MAX( LWQP3, N/2+LWQRF, N/2+LWSVD2,
  648. $ N/2+LWORQ2, LWORQ )
  649. IF ( CONDA ) MINWRK2 = MAX( MINWRK2, LWCON )
  650. MINWRK2 = N + MINWRK2
  651. MINWRK = MAX( MINWRK, MINWRK2 )
  652. END IF
  653. ELSE
  654. MINWRK = MAX( LWQP3, LWSVD, LWORQ )
  655. IF ( CONDA ) MINWRK = MAX( MINWRK, LWCON )
  656. MINWRK = MINWRK + N
  657. IF ( WNTVA ) THEN
  658. * .. minimal workspace length for N/2 x N DGELQF
  659. LWLQF = MAX( N/2, 1 )
  660. LWSVD2 = MAX( 5 * (N/2), 1 )
  661. LWORLQ = MAX( N , 1 )
  662. MINWRK2 = MAX( LWQP3, N/2+LWLQF, N/2+LWSVD2,
  663. $ N/2+LWORLQ, LWORQ )
  664. IF ( CONDA ) MINWRK2 = MAX( MINWRK2, LWCON )
  665. MINWRK2 = N + MINWRK2
  666. MINWRK = MAX( MINWRK, MINWRK2 )
  667. END IF
  668. END IF
  669. IF ( LQUERY ) THEN
  670. IF ( RTRANS ) THEN
  671. CALL DGESVD( 'O', 'A', N, N, A, LDA, S, U, LDU,
  672. $ V, LDV, RDUMMY, -1, IERR )
  673. LWRK_DGESVD = INT( RDUMMY(1) )
  674. OPTWRK = MAX(LWRK_DGEQP3,LWRK_DGESVD,LWRK_DORMQR)
  675. IF ( CONDA ) OPTWRK = MAX( OPTWRK, LWCON )
  676. OPTWRK = N + OPTWRK
  677. IF ( WNTVA ) THEN
  678. CALL DGEQRF(N,N/2,U,LDU,RDUMMY,RDUMMY,-1,IERR)
  679. LWRK_DGEQRF = INT( RDUMMY(1) )
  680. CALL DGESVD( 'S', 'O', N/2,N/2, V,LDV, S, U,LDU,
  681. $ V, LDV, RDUMMY, -1, IERR )
  682. LWRK_DGESVD2 = INT( RDUMMY(1) )
  683. CALL DORMQR( 'R', 'C', N, N, N/2, U, LDU, RDUMMY,
  684. $ V, LDV, RDUMMY, -1, IERR )
  685. LWRK_DORMQR2 = INT( RDUMMY(1) )
  686. OPTWRK2 = MAX( LWRK_DGEQP3, N/2+LWRK_DGEQRF,
  687. $ N/2+LWRK_DGESVD2, N/2+LWRK_DORMQR2 )
  688. IF ( CONDA ) OPTWRK2 = MAX( OPTWRK2, LWCON )
  689. OPTWRK2 = N + OPTWRK2
  690. OPTWRK = MAX( OPTWRK, OPTWRK2 )
  691. END IF
  692. ELSE
  693. CALL DGESVD( 'S', 'O', N, N, A, LDA, S, U, LDU,
  694. $ V, LDV, RDUMMY, -1, IERR )
  695. LWRK_DGESVD = INT( RDUMMY(1) )
  696. OPTWRK = MAX(LWRK_DGEQP3,LWRK_DGESVD,LWRK_DORMQR)
  697. IF ( CONDA ) OPTWRK = MAX( OPTWRK, LWCON )
  698. OPTWRK = N + OPTWRK
  699. IF ( WNTVA ) THEN
  700. CALL DGELQF(N/2,N,U,LDU,RDUMMY,RDUMMY,-1,IERR)
  701. LWRK_DGELQF = INT( RDUMMY(1) )
  702. CALL DGESVD( 'S','O', N/2,N/2, V, LDV, S, U, LDU,
  703. $ V, LDV, RDUMMY, -1, IERR )
  704. LWRK_DGESVD2 = INT( RDUMMY(1) )
  705. CALL DORMLQ( 'R', 'N', N, N, N/2, U, LDU, RDUMMY,
  706. $ V, LDV, RDUMMY,-1,IERR )
  707. LWRK_DORMLQ = INT( RDUMMY(1) )
  708. OPTWRK2 = MAX( LWRK_DGEQP3, N/2+LWRK_DGELQF,
  709. $ N/2+LWRK_DGESVD2, N/2+LWRK_DORMLQ )
  710. IF ( CONDA ) OPTWRK2 = MAX( OPTWRK2, LWCON )
  711. OPTWRK2 = N + OPTWRK2
  712. OPTWRK = MAX( OPTWRK, OPTWRK2 )
  713. END IF
  714. END IF
  715. END IF
  716. END IF
  717. *
  718. MINWRK = MAX( 2, MINWRK )
  719. OPTWRK = MAX( 2, OPTWRK )
  720. IF ( LWORK .LT. MINWRK .AND. (.NOT.LQUERY) ) INFO = -19
  721. *
  722. END IF
  723. *
  724. IF (INFO .EQ. 0 .AND. LRWORK .LT. RMINWRK .AND. .NOT. LQUERY) THEN
  725. INFO = -21
  726. END IF
  727. IF( INFO.NE.0 ) THEN
  728. CALL XERBLA( 'DGESVDQ', -INFO )
  729. RETURN
  730. ELSE IF ( LQUERY ) THEN
  731. *
  732. * Return optimal workspace
  733. *
  734. IWORK(1) = IMINWRK
  735. WORK(1) = OPTWRK
  736. WORK(2) = MINWRK
  737. RWORK(1) = RMINWRK
  738. RETURN
  739. END IF
  740. *
  741. * Quick return if the matrix is void.
  742. *
  743. IF( ( M.EQ.0 ) .OR. ( N.EQ.0 ) ) THEN
  744. * .. all output is void.
  745. RETURN
  746. END IF
  747. *
  748. BIG = DLAMCH('O')
  749. ASCALED = .FALSE.
  750. IWOFF = 1
  751. IF ( ROWPRM ) THEN
  752. IWOFF = M
  753. * .. reordering the rows in decreasing sequence in the
  754. * ell-infinity norm - this enhances numerical robustness in
  755. * the case of differently scaled rows.
  756. DO 1904 p = 1, M
  757. * RWORK(p) = ABS( A(p,ICAMAX(N,A(p,1),LDA)) )
  758. * [[DLANGE will return NaN if an entry of the p-th row is Nan]]
  759. RWORK(p) = DLANGE( 'M', 1, N, A(p,1), LDA, RDUMMY )
  760. * .. check for NaN's and Inf's
  761. IF ( ( RWORK(p) .NE. RWORK(p) ) .OR.
  762. $ ( (RWORK(p)*ZERO) .NE. ZERO ) ) THEN
  763. INFO = -8
  764. CALL XERBLA( 'DGESVDQ', -INFO )
  765. RETURN
  766. END IF
  767. 1904 CONTINUE
  768. DO 1952 p = 1, M - 1
  769. q = IDAMAX( M-p+1, RWORK(p), 1 ) + p - 1
  770. IWORK(N+p) = q
  771. IF ( p .NE. q ) THEN
  772. RTMP = RWORK(p)
  773. RWORK(p) = RWORK(q)
  774. RWORK(q) = RTMP
  775. END IF
  776. 1952 CONTINUE
  777. *
  778. IF ( RWORK(1) .EQ. ZERO ) THEN
  779. * Quick return: A is the M x N zero matrix.
  780. NUMRANK = 0
  781. CALL DLASET( 'G', N, 1, ZERO, ZERO, S, N )
  782. IF ( WNTUS ) CALL DLASET('G', M, N, ZERO, ONE, U, LDU)
  783. IF ( WNTUA ) CALL DLASET('G', M, M, ZERO, ONE, U, LDU)
  784. IF ( WNTVA ) CALL DLASET('G', N, N, ZERO, ONE, V, LDV)
  785. IF ( WNTUF ) THEN
  786. CALL DLASET( 'G', N, 1, ZERO, ZERO, WORK, N )
  787. CALL DLASET( 'G', M, N, ZERO, ONE, U, LDU )
  788. END IF
  789. DO 5001 p = 1, N
  790. IWORK(p) = p
  791. 5001 CONTINUE
  792. IF ( ROWPRM ) THEN
  793. DO 5002 p = N + 1, N + M - 1
  794. IWORK(p) = p - N
  795. 5002 CONTINUE
  796. END IF
  797. IF ( CONDA ) RWORK(1) = -1
  798. RWORK(2) = -1
  799. RETURN
  800. END IF
  801. *
  802. IF ( RWORK(1) .GT. BIG / SQRT(DBLE(M)) ) THEN
  803. * .. to prevent overflow in the QR factorization, scale the
  804. * matrix by 1/sqrt(M) if too large entry detected
  805. CALL DLASCL('G',0,0,SQRT(DBLE(M)),ONE, M,N, A,LDA, IERR)
  806. ASCALED = .TRUE.
  807. END IF
  808. CALL DLASWP( N, A, LDA, 1, M-1, IWORK(N+1), 1 )
  809. END IF
  810. *
  811. * .. At this stage, preemptive scaling is done only to avoid column
  812. * norms overflows during the QR factorization. The SVD procedure should
  813. * have its own scaling to save the singular values from overflows and
  814. * underflows. That depends on the SVD procedure.
  815. *
  816. IF ( .NOT.ROWPRM ) THEN
  817. RTMP = DLANGE( 'M', M, N, A, LDA, RDUMMY )
  818. IF ( ( RTMP .NE. RTMP ) .OR.
  819. $ ( (RTMP*ZERO) .NE. ZERO ) ) THEN
  820. INFO = -8
  821. CALL XERBLA( 'DGESVDQ', -INFO )
  822. RETURN
  823. END IF
  824. IF ( RTMP .GT. BIG / SQRT(DBLE(M)) ) THEN
  825. * .. to prevent overflow in the QR factorization, scale the
  826. * matrix by 1/sqrt(M) if too large entry detected
  827. CALL DLASCL('G',0,0, SQRT(DBLE(M)),ONE, M,N, A,LDA, IERR)
  828. ASCALED = .TRUE.
  829. END IF
  830. END IF
  831. *
  832. * .. QR factorization with column pivoting
  833. *
  834. * A * P = Q * [ R ]
  835. * [ 0 ]
  836. *
  837. DO 1963 p = 1, N
  838. * .. all columns are free columns
  839. IWORK(p) = 0
  840. 1963 CONTINUE
  841. CALL DGEQP3( M, N, A, LDA, IWORK, WORK, WORK(N+1), LWORK-N,
  842. $ IERR )
  843. *
  844. * If the user requested accuracy level allows truncation in the
  845. * computed upper triangular factor, the matrix R is examined and,
  846. * if possible, replaced with its leading upper trapezoidal part.
  847. *
  848. EPSLN = DLAMCH('E')
  849. SFMIN = DLAMCH('S')
  850. * SMALL = SFMIN / EPSLN
  851. NR = N
  852. *
  853. IF ( ACCLA ) THEN
  854. *
  855. * Standard absolute error bound suffices. All sigma_i with
  856. * sigma_i < N*EPS*||A||_F are flushed to zero. This is an
  857. * aggressive enforcement of lower numerical rank by introducing a
  858. * backward error of the order of N*EPS*||A||_F.
  859. NR = 1
  860. RTMP = SQRT(DBLE(N))*EPSLN
  861. DO 3001 p = 2, N
  862. IF ( ABS(A(p,p)) .LT. (RTMP*ABS(A(1,1))) ) GO TO 3002
  863. NR = NR + 1
  864. 3001 CONTINUE
  865. 3002 CONTINUE
  866. *
  867. ELSEIF ( ACCLM ) THEN
  868. * .. similarly as above, only slightly more gentle (less aggressive).
  869. * Sudden drop on the diagonal of R is used as the criterion for being
  870. * close-to-rank-deficient. The threshold is set to EPSLN=DLAMCH('E').
  871. * [[This can be made more flexible by replacing this hard-coded value
  872. * with a user specified threshold.]] Also, the values that underflow
  873. * will be truncated.
  874. NR = 1
  875. DO 3401 p = 2, N
  876. IF ( ( ABS(A(p,p)) .LT. (EPSLN*ABS(A(p-1,p-1))) ) .OR.
  877. $ ( ABS(A(p,p)) .LT. SFMIN ) ) GO TO 3402
  878. NR = NR + 1
  879. 3401 CONTINUE
  880. 3402 CONTINUE
  881. *
  882. ELSE
  883. * .. RRQR not authorized to determine numerical rank except in the
  884. * obvious case of zero pivots.
  885. * .. inspect R for exact zeros on the diagonal;
  886. * R(i,i)=0 => R(i:N,i:N)=0.
  887. NR = 1
  888. DO 3501 p = 2, N
  889. IF ( ABS(A(p,p)) .EQ. ZERO ) GO TO 3502
  890. NR = NR + 1
  891. 3501 CONTINUE
  892. 3502 CONTINUE
  893. *
  894. IF ( CONDA ) THEN
  895. * Estimate the scaled condition number of A. Use the fact that it is
  896. * the same as the scaled condition number of R.
  897. * .. V is used as workspace
  898. CALL DLACPY( 'U', N, N, A, LDA, V, LDV )
  899. * Only the leading NR x NR submatrix of the triangular factor
  900. * is considered. Only if NR=N will this give a reliable error
  901. * bound. However, even for NR < N, this can be used on an
  902. * expert level and obtain useful information in the sense of
  903. * perturbation theory.
  904. DO 3053 p = 1, NR
  905. RTMP = DNRM2( p, V(1,p), 1 )
  906. CALL DSCAL( p, ONE/RTMP, V(1,p), 1 )
  907. 3053 CONTINUE
  908. IF ( .NOT. ( LSVEC .OR. RSVEC ) ) THEN
  909. CALL DPOCON( 'U', NR, V, LDV, ONE, RTMP,
  910. $ WORK, IWORK(N+IWOFF), IERR )
  911. ELSE
  912. CALL DPOCON( 'U', NR, V, LDV, ONE, RTMP,
  913. $ WORK(N+1), IWORK(N+IWOFF), IERR )
  914. END IF
  915. SCONDA = ONE / SQRT(RTMP)
  916. * For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1),
  917. * N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA
  918. * See the reference [1] for more details.
  919. END IF
  920. *
  921. ENDIF
  922. *
  923. IF ( WNTUR ) THEN
  924. N1 = NR
  925. ELSE IF ( WNTUS .OR. WNTUF) THEN
  926. N1 = N
  927. ELSE IF ( WNTUA ) THEN
  928. N1 = M
  929. END IF
  930. *
  931. IF ( .NOT. ( RSVEC .OR. LSVEC ) ) THEN
  932. *.......................................................................
  933. * .. only the singular values are requested
  934. *.......................................................................
  935. IF ( RTRANS ) THEN
  936. *
  937. * .. compute the singular values of R**T = [A](1:NR,1:N)**T
  938. * .. set the lower triangle of [A] to [A](1:NR,1:N)**T and
  939. * the upper triangle of [A] to zero.
  940. DO 1146 p = 1, MIN( N, NR )
  941. DO 1147 q = p + 1, N
  942. A(q,p) = A(p,q)
  943. IF ( q .LE. NR ) A(p,q) = ZERO
  944. 1147 CONTINUE
  945. 1146 CONTINUE
  946. *
  947. CALL DGESVD( 'N', 'N', N, NR, A, LDA, S, U, LDU,
  948. $ V, LDV, WORK, LWORK, INFO )
  949. *
  950. ELSE
  951. *
  952. * .. compute the singular values of R = [A](1:NR,1:N)
  953. *
  954. IF ( NR .GT. 1 )
  955. $ CALL DLASET( 'L', NR-1,NR-1, ZERO,ZERO, A(2,1), LDA )
  956. CALL DGESVD( 'N', 'N', NR, N, A, LDA, S, U, LDU,
  957. $ V, LDV, WORK, LWORK, INFO )
  958. *
  959. END IF
  960. *
  961. ELSE IF ( LSVEC .AND. ( .NOT. RSVEC) ) THEN
  962. *.......................................................................
  963. * .. the singular values and the left singular vectors requested
  964. *.......................................................................""""""""
  965. IF ( RTRANS ) THEN
  966. * .. apply DGESVD to R**T
  967. * .. copy R**T into [U] and overwrite [U] with the right singular
  968. * vectors of R
  969. DO 1192 p = 1, NR
  970. DO 1193 q = p, N
  971. U(q,p) = A(p,q)
  972. 1193 CONTINUE
  973. 1192 CONTINUE
  974. IF ( NR .GT. 1 )
  975. $ CALL DLASET( 'U', NR-1,NR-1, ZERO,ZERO, U(1,2), LDU )
  976. * .. the left singular vectors not computed, the NR right singular
  977. * vectors overwrite [U](1:NR,1:NR) as transposed. These
  978. * will be pre-multiplied by Q to build the left singular vectors of A.
  979. CALL DGESVD( 'N', 'O', N, NR, U, LDU, S, U, LDU,
  980. $ U, LDU, WORK(N+1), LWORK-N, INFO )
  981. *
  982. DO 1119 p = 1, NR
  983. DO 1120 q = p + 1, NR
  984. RTMP = U(q,p)
  985. U(q,p) = U(p,q)
  986. U(p,q) = RTMP
  987. 1120 CONTINUE
  988. 1119 CONTINUE
  989. *
  990. ELSE
  991. * .. apply DGESVD to R
  992. * .. copy R into [U] and overwrite [U] with the left singular vectors
  993. CALL DLACPY( 'U', NR, N, A, LDA, U, LDU )
  994. IF ( NR .GT. 1 )
  995. $ CALL DLASET( 'L', NR-1, NR-1, ZERO, ZERO, U(2,1), LDU )
  996. * .. the right singular vectors not computed, the NR left singular
  997. * vectors overwrite [U](1:NR,1:NR)
  998. CALL DGESVD( 'O', 'N', NR, N, U, LDU, S, U, LDU,
  999. $ V, LDV, WORK(N+1), LWORK-N, INFO )
  1000. * .. now [U](1:NR,1:NR) contains the NR left singular vectors of
  1001. * R. These will be pre-multiplied by Q to build the left singular
  1002. * vectors of A.
  1003. END IF
  1004. *
  1005. * .. assemble the left singular vector matrix U of dimensions
  1006. * (M x NR) or (M x N) or (M x M).
  1007. IF ( ( NR .LT. M ) .AND. ( .NOT.WNTUF ) ) THEN
  1008. CALL DLASET('A', M-NR, NR, ZERO, ZERO, U(NR+1,1), LDU)
  1009. IF ( NR .LT. N1 ) THEN
  1010. CALL DLASET( 'A',NR,N1-NR,ZERO,ZERO,U(1,NR+1), LDU )
  1011. CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
  1012. $ U(NR+1,NR+1), LDU )
  1013. END IF
  1014. END IF
  1015. *
  1016. * The Q matrix from the first QRF is built into the left singular
  1017. * vectors matrix U.
  1018. *
  1019. IF ( .NOT.WNTUF )
  1020. $ CALL DORMQR( 'L', 'N', M, N1, N, A, LDA, WORK, U,
  1021. $ LDU, WORK(N+1), LWORK-N, IERR )
  1022. IF ( ROWPRM .AND. .NOT.WNTUF )
  1023. $ CALL DLASWP( N1, U, LDU, 1, M-1, IWORK(N+1), -1 )
  1024. *
  1025. ELSE IF ( RSVEC .AND. ( .NOT. LSVEC ) ) THEN
  1026. *.......................................................................
  1027. * .. the singular values and the right singular vectors requested
  1028. *.......................................................................
  1029. IF ( RTRANS ) THEN
  1030. * .. apply DGESVD to R**T
  1031. * .. copy R**T into V and overwrite V with the left singular vectors
  1032. DO 1165 p = 1, NR
  1033. DO 1166 q = p, N
  1034. V(q,p) = (A(p,q))
  1035. 1166 CONTINUE
  1036. 1165 CONTINUE
  1037. IF ( NR .GT. 1 )
  1038. $ CALL DLASET( 'U', NR-1,NR-1, ZERO,ZERO, V(1,2), LDV )
  1039. * .. the left singular vectors of R**T overwrite V, the right singular
  1040. * vectors not computed
  1041. IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
  1042. CALL DGESVD( 'O', 'N', N, NR, V, LDV, S, U, LDU,
  1043. $ U, LDU, WORK(N+1), LWORK-N, INFO )
  1044. *
  1045. DO 1121 p = 1, NR
  1046. DO 1122 q = p + 1, NR
  1047. RTMP = V(q,p)
  1048. V(q,p) = V(p,q)
  1049. V(p,q) = RTMP
  1050. 1122 CONTINUE
  1051. 1121 CONTINUE
  1052. *
  1053. IF ( NR .LT. N ) THEN
  1054. DO 1103 p = 1, NR
  1055. DO 1104 q = NR + 1, N
  1056. V(p,q) = V(q,p)
  1057. 1104 CONTINUE
  1058. 1103 CONTINUE
  1059. END IF
  1060. CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
  1061. ELSE
  1062. * .. need all N right singular vectors and NR < N
  1063. * [!] This is simple implementation that augments [V](1:N,1:NR)
  1064. * by padding a zero block. In the case NR << N, a more efficient
  1065. * way is to first use the QR factorization. For more details
  1066. * how to implement this, see the " FULL SVD " branch.
  1067. CALL DLASET('G', N, N-NR, ZERO, ZERO, V(1,NR+1), LDV)
  1068. CALL DGESVD( 'O', 'N', N, N, V, LDV, S, U, LDU,
  1069. $ U, LDU, WORK(N+1), LWORK-N, INFO )
  1070. *
  1071. DO 1123 p = 1, N
  1072. DO 1124 q = p + 1, N
  1073. RTMP = V(q,p)
  1074. V(q,p) = V(p,q)
  1075. V(p,q) = RTMP
  1076. 1124 CONTINUE
  1077. 1123 CONTINUE
  1078. CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
  1079. END IF
  1080. *
  1081. ELSE
  1082. * .. aply DGESVD to R
  1083. * .. copy R into V and overwrite V with the right singular vectors
  1084. CALL DLACPY( 'U', NR, N, A, LDA, V, LDV )
  1085. IF ( NR .GT. 1 )
  1086. $ CALL DLASET( 'L', NR-1, NR-1, ZERO, ZERO, V(2,1), LDV )
  1087. * .. the right singular vectors overwrite V, the NR left singular
  1088. * vectors stored in U(1:NR,1:NR)
  1089. IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
  1090. CALL DGESVD( 'N', 'O', NR, N, V, LDV, S, U, LDU,
  1091. $ V, LDV, WORK(N+1), LWORK-N, INFO )
  1092. CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
  1093. * .. now [V](1:NR,1:N) contains V(1:N,1:NR)**T
  1094. ELSE
  1095. * .. need all N right singular vectors and NR < N
  1096. * [!] This is simple implementation that augments [V](1:NR,1:N)
  1097. * by padding a zero block. In the case NR << N, a more efficient
  1098. * way is to first use the LQ factorization. For more details
  1099. * how to implement this, see the " FULL SVD " branch.
  1100. CALL DLASET('G', N-NR, N, ZERO,ZERO, V(NR+1,1), LDV)
  1101. CALL DGESVD( 'N', 'O', N, N, V, LDV, S, U, LDU,
  1102. $ V, LDV, WORK(N+1), LWORK-N, INFO )
  1103. CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
  1104. END IF
  1105. * .. now [V] contains the transposed matrix of the right singular
  1106. * vectors of A.
  1107. END IF
  1108. *
  1109. ELSE
  1110. *.......................................................................
  1111. * .. FULL SVD requested
  1112. *.......................................................................
  1113. IF ( RTRANS ) THEN
  1114. *
  1115. * .. apply DGESVD to R**T [[this option is left for R&D&T]]
  1116. *
  1117. IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
  1118. * .. copy R**T into [V] and overwrite [V] with the left singular
  1119. * vectors of R**T
  1120. DO 1168 p = 1, NR
  1121. DO 1169 q = p, N
  1122. V(q,p) = A(p,q)
  1123. 1169 CONTINUE
  1124. 1168 CONTINUE
  1125. IF ( NR .GT. 1 )
  1126. $ CALL DLASET( 'U', NR-1,NR-1, ZERO,ZERO, V(1,2), LDV )
  1127. *
  1128. * .. the left singular vectors of R**T overwrite [V], the NR right
  1129. * singular vectors of R**T stored in [U](1:NR,1:NR) as transposed
  1130. CALL DGESVD( 'O', 'A', N, NR, V, LDV, S, V, LDV,
  1131. $ U, LDU, WORK(N+1), LWORK-N, INFO )
  1132. * .. assemble V
  1133. DO 1115 p = 1, NR
  1134. DO 1116 q = p + 1, NR
  1135. RTMP = V(q,p)
  1136. V(q,p) = V(p,q)
  1137. V(p,q) = RTMP
  1138. 1116 CONTINUE
  1139. 1115 CONTINUE
  1140. IF ( NR .LT. N ) THEN
  1141. DO 1101 p = 1, NR
  1142. DO 1102 q = NR+1, N
  1143. V(p,q) = V(q,p)
  1144. 1102 CONTINUE
  1145. 1101 CONTINUE
  1146. END IF
  1147. CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
  1148. *
  1149. DO 1117 p = 1, NR
  1150. DO 1118 q = p + 1, NR
  1151. RTMP = U(q,p)
  1152. U(q,p) = U(p,q)
  1153. U(p,q) = RTMP
  1154. 1118 CONTINUE
  1155. 1117 CONTINUE
  1156. *
  1157. IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
  1158. CALL DLASET('A', M-NR,NR, ZERO,ZERO, U(NR+1,1), LDU)
  1159. IF ( NR .LT. N1 ) THEN
  1160. CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
  1161. CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
  1162. $ U(NR+1,NR+1), LDU )
  1163. END IF
  1164. END IF
  1165. *
  1166. ELSE
  1167. * .. need all N right singular vectors and NR < N
  1168. * .. copy R**T into [V] and overwrite [V] with the left singular
  1169. * vectors of R**T
  1170. * [[The optimal ratio N/NR for using QRF instead of padding
  1171. * with zeros. Here hard coded to 2; it must be at least
  1172. * two due to work space constraints.]]
  1173. * OPTRATIO = ILAENV(6, 'DGESVD', 'S' // 'O', NR,N,0,0)
  1174. * OPTRATIO = MAX( OPTRATIO, 2 )
  1175. OPTRATIO = 2
  1176. IF ( OPTRATIO*NR .GT. N ) THEN
  1177. DO 1198 p = 1, NR
  1178. DO 1199 q = p, N
  1179. V(q,p) = A(p,q)
  1180. 1199 CONTINUE
  1181. 1198 CONTINUE
  1182. IF ( NR .GT. 1 )
  1183. $ CALL DLASET('U',NR-1,NR-1, ZERO,ZERO, V(1,2),LDV)
  1184. *
  1185. CALL DLASET('A',N,N-NR,ZERO,ZERO,V(1,NR+1),LDV)
  1186. CALL DGESVD( 'O', 'A', N, N, V, LDV, S, V, LDV,
  1187. $ U, LDU, WORK(N+1), LWORK-N, INFO )
  1188. *
  1189. DO 1113 p = 1, N
  1190. DO 1114 q = p + 1, N
  1191. RTMP = V(q,p)
  1192. V(q,p) = V(p,q)
  1193. V(p,q) = RTMP
  1194. 1114 CONTINUE
  1195. 1113 CONTINUE
  1196. CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
  1197. * .. assemble the left singular vector matrix U of dimensions
  1198. * (M x N1), i.e. (M x N) or (M x M).
  1199. *
  1200. DO 1111 p = 1, N
  1201. DO 1112 q = p + 1, N
  1202. RTMP = U(q,p)
  1203. U(q,p) = U(p,q)
  1204. U(p,q) = RTMP
  1205. 1112 CONTINUE
  1206. 1111 CONTINUE
  1207. *
  1208. IF ( ( N .LT. M ) .AND. .NOT.(WNTUF)) THEN
  1209. CALL DLASET('A',M-N,N,ZERO,ZERO,U(N+1,1),LDU)
  1210. IF ( N .LT. N1 ) THEN
  1211. CALL DLASET('A',N,N1-N,ZERO,ZERO,U(1,N+1),LDU)
  1212. CALL DLASET('A',M-N,N1-N,ZERO,ONE,
  1213. $ U(N+1,N+1), LDU )
  1214. END IF
  1215. END IF
  1216. ELSE
  1217. * .. copy R**T into [U] and overwrite [U] with the right
  1218. * singular vectors of R
  1219. DO 1196 p = 1, NR
  1220. DO 1197 q = p, N
  1221. U(q,NR+p) = A(p,q)
  1222. 1197 CONTINUE
  1223. 1196 CONTINUE
  1224. IF ( NR .GT. 1 )
  1225. $ CALL DLASET('U',NR-1,NR-1,ZERO,ZERO,U(1,NR+2),LDU)
  1226. CALL DGEQRF( N, NR, U(1,NR+1), LDU, WORK(N+1),
  1227. $ WORK(N+NR+1), LWORK-N-NR, IERR )
  1228. DO 1143 p = 1, NR
  1229. DO 1144 q = 1, N
  1230. V(q,p) = U(p,NR+q)
  1231. 1144 CONTINUE
  1232. 1143 CONTINUE
  1233. CALL DLASET('U',NR-1,NR-1,ZERO,ZERO,V(1,2),LDV)
  1234. CALL DGESVD( 'S', 'O', NR, NR, V, LDV, S, U, LDU,
  1235. $ V,LDV, WORK(N+NR+1),LWORK-N-NR, INFO )
  1236. CALL DLASET('A',N-NR,NR,ZERO,ZERO,V(NR+1,1),LDV)
  1237. CALL DLASET('A',NR,N-NR,ZERO,ZERO,V(1,NR+1),LDV)
  1238. CALL DLASET('A',N-NR,N-NR,ZERO,ONE,V(NR+1,NR+1),LDV)
  1239. CALL DORMQR('R','C', N, N, NR, U(1,NR+1), LDU,
  1240. $ WORK(N+1),V,LDV,WORK(N+NR+1),LWORK-N-NR,IERR)
  1241. CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
  1242. * .. assemble the left singular vector matrix U of dimensions
  1243. * (M x NR) or (M x N) or (M x M).
  1244. IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
  1245. CALL DLASET('A',M-NR,NR,ZERO,ZERO,U(NR+1,1),LDU)
  1246. IF ( NR .LT. N1 ) THEN
  1247. CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
  1248. CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
  1249. $ U(NR+1,NR+1),LDU)
  1250. END IF
  1251. END IF
  1252. END IF
  1253. END IF
  1254. *
  1255. ELSE
  1256. *
  1257. * .. apply DGESVD to R [[this is the recommended option]]
  1258. *
  1259. IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
  1260. * .. copy R into [V] and overwrite V with the right singular vectors
  1261. CALL DLACPY( 'U', NR, N, A, LDA, V, LDV )
  1262. IF ( NR .GT. 1 )
  1263. $ CALL DLASET( 'L', NR-1,NR-1, ZERO,ZERO, V(2,1), LDV )
  1264. * .. the right singular vectors of R overwrite [V], the NR left
  1265. * singular vectors of R stored in [U](1:NR,1:NR)
  1266. CALL DGESVD( 'S', 'O', NR, N, V, LDV, S, U, LDU,
  1267. $ V, LDV, WORK(N+1), LWORK-N, INFO )
  1268. CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
  1269. * .. now [V](1:NR,1:N) contains V(1:N,1:NR)**T
  1270. * .. assemble the left singular vector matrix U of dimensions
  1271. * (M x NR) or (M x N) or (M x M).
  1272. IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
  1273. CALL DLASET('A', M-NR,NR, ZERO,ZERO, U(NR+1,1), LDU)
  1274. IF ( NR .LT. N1 ) THEN
  1275. CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
  1276. CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
  1277. $ U(NR+1,NR+1), LDU )
  1278. END IF
  1279. END IF
  1280. *
  1281. ELSE
  1282. * .. need all N right singular vectors and NR < N
  1283. * .. the requested number of the left singular vectors
  1284. * is then N1 (N or M)
  1285. * [[The optimal ratio N/NR for using LQ instead of padding
  1286. * with zeros. Here hard coded to 2; it must be at least
  1287. * two due to work space constraints.]]
  1288. * OPTRATIO = ILAENV(6, 'DGESVD', 'S' // 'O', NR,N,0,0)
  1289. * OPTRATIO = MAX( OPTRATIO, 2 )
  1290. OPTRATIO = 2
  1291. IF ( OPTRATIO * NR .GT. N ) THEN
  1292. CALL DLACPY( 'U', NR, N, A, LDA, V, LDV )
  1293. IF ( NR .GT. 1 )
  1294. $ CALL DLASET('L', NR-1,NR-1, ZERO,ZERO, V(2,1),LDV)
  1295. * .. the right singular vectors of R overwrite [V], the NR left
  1296. * singular vectors of R stored in [U](1:NR,1:NR)
  1297. CALL DLASET('A', N-NR,N, ZERO,ZERO, V(NR+1,1),LDV)
  1298. CALL DGESVD( 'S', 'O', N, N, V, LDV, S, U, LDU,
  1299. $ V, LDV, WORK(N+1), LWORK-N, INFO )
  1300. CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
  1301. * .. now [V] contains the transposed matrix of the right
  1302. * singular vectors of A. The leading N left singular vectors
  1303. * are in [U](1:N,1:N)
  1304. * .. assemble the left singular vector matrix U of dimensions
  1305. * (M x N1), i.e. (M x N) or (M x M).
  1306. IF ( ( N .LT. M ) .AND. .NOT.(WNTUF)) THEN
  1307. CALL DLASET('A',M-N,N,ZERO,ZERO,U(N+1,1),LDU)
  1308. IF ( N .LT. N1 ) THEN
  1309. CALL DLASET('A',N,N1-N,ZERO,ZERO,U(1,N+1),LDU)
  1310. CALL DLASET( 'A',M-N,N1-N,ZERO,ONE,
  1311. $ U(N+1,N+1), LDU )
  1312. END IF
  1313. END IF
  1314. ELSE
  1315. CALL DLACPY( 'U', NR, N, A, LDA, U(NR+1,1), LDU )
  1316. IF ( NR .GT. 1 )
  1317. $ CALL DLASET('L',NR-1,NR-1,ZERO,ZERO,U(NR+2,1),LDU)
  1318. CALL DGELQF( NR, N, U(NR+1,1), LDU, WORK(N+1),
  1319. $ WORK(N+NR+1), LWORK-N-NR, IERR )
  1320. CALL DLACPY('L',NR,NR,U(NR+1,1),LDU,V,LDV)
  1321. IF ( NR .GT. 1 )
  1322. $ CALL DLASET('U',NR-1,NR-1,ZERO,ZERO,V(1,2),LDV)
  1323. CALL DGESVD( 'S', 'O', NR, NR, V, LDV, S, U, LDU,
  1324. $ V, LDV, WORK(N+NR+1), LWORK-N-NR, INFO )
  1325. CALL DLASET('A',N-NR,NR,ZERO,ZERO,V(NR+1,1),LDV)
  1326. CALL DLASET('A',NR,N-NR,ZERO,ZERO,V(1,NR+1),LDV)
  1327. CALL DLASET('A',N-NR,N-NR,ZERO,ONE,V(NR+1,NR+1),LDV)
  1328. CALL DORMLQ('R','N',N,N,NR,U(NR+1,1),LDU,WORK(N+1),
  1329. $ V, LDV, WORK(N+NR+1),LWORK-N-NR,IERR)
  1330. CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
  1331. * .. assemble the left singular vector matrix U of dimensions
  1332. * (M x NR) or (M x N) or (M x M).
  1333. IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
  1334. CALL DLASET('A',M-NR,NR,ZERO,ZERO,U(NR+1,1),LDU)
  1335. IF ( NR .LT. N1 ) THEN
  1336. CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
  1337. CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
  1338. $ U(NR+1,NR+1), LDU )
  1339. END IF
  1340. END IF
  1341. END IF
  1342. END IF
  1343. * .. end of the "R**T or R" branch
  1344. END IF
  1345. *
  1346. * The Q matrix from the first QRF is built into the left singular
  1347. * vectors matrix U.
  1348. *
  1349. IF ( .NOT. WNTUF )
  1350. $ CALL DORMQR( 'L', 'N', M, N1, N, A, LDA, WORK, U,
  1351. $ LDU, WORK(N+1), LWORK-N, IERR )
  1352. IF ( ROWPRM .AND. .NOT.WNTUF )
  1353. $ CALL DLASWP( N1, U, LDU, 1, M-1, IWORK(N+1), -1 )
  1354. *
  1355. * ... end of the "full SVD" branch
  1356. END IF
  1357. *
  1358. * Check whether some singular values are returned as zeros, e.g.
  1359. * due to underflow, and update the numerical rank.
  1360. p = NR
  1361. DO 4001 q = p, 1, -1
  1362. IF ( S(q) .GT. ZERO ) GO TO 4002
  1363. NR = NR - 1
  1364. 4001 CONTINUE
  1365. 4002 CONTINUE
  1366. *
  1367. * .. if numerical rank deficiency is detected, the truncated
  1368. * singular values are set to zero.
  1369. IF ( NR .LT. N ) CALL DLASET( 'G', N-NR,1, ZERO,ZERO, S(NR+1), N )
  1370. * .. undo scaling; this may cause overflow in the largest singular
  1371. * values.
  1372. IF ( ASCALED )
  1373. $ CALL DLASCL( 'G',0,0, ONE,SQRT(DBLE(M)), NR,1, S, N, IERR )
  1374. IF ( CONDA ) RWORK(1) = SCONDA
  1375. RWORK(2) = p - NR
  1376. * .. p-NR is the number of singular values that are computed as
  1377. * exact zeros in DGESVD() applied to the (possibly truncated)
  1378. * full row rank triangular (trapezoidal) factor of A.
  1379. NUMRANK = NR
  1380. *
  1381. RETURN
  1382. *
  1383. * End of DGESVDQ
  1384. *
  1385. END