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dlasdq.f 13 kB

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  1. *> \brief \b DLASDQ computes the SVD of a real bidiagonal matrix with diagonal d and off-diagonal e. Used by sbdsdc.
  2. *
  3. * =========== DOCUMENTATION ===========
  4. *
  5. * Online html documentation available at
  6. * http://www.netlib.org/lapack/explore-html/
  7. *
  8. *> \htmlonly
  9. *> Download DLASDQ + dependencies
  10. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlasdq.f">
  11. *> [TGZ]</a>
  12. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlasdq.f">
  13. *> [ZIP]</a>
  14. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlasdq.f">
  15. *> [TXT]</a>
  16. *> \endhtmlonly
  17. *
  18. * Definition:
  19. * ===========
  20. *
  21. * SUBROUTINE DLASDQ( UPLO, SQRE, N, NCVT, NRU, NCC, D, E, VT, LDVT,
  22. * U, LDU, C, LDC, WORK, INFO )
  23. *
  24. * .. Scalar Arguments ..
  25. * CHARACTER UPLO
  26. * INTEGER INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU, SQRE
  27. * ..
  28. * .. Array Arguments ..
  29. * DOUBLE PRECISION C( LDC, * ), D( * ), E( * ), U( LDU, * ),
  30. * $ VT( LDVT, * ), WORK( * )
  31. * ..
  32. *
  33. *
  34. *> \par Purpose:
  35. * =============
  36. *>
  37. *> \verbatim
  38. *>
  39. *> DLASDQ computes the singular value decomposition (SVD) of a real
  40. *> (upper or lower) bidiagonal matrix with diagonal D and offdiagonal
  41. *> E, accumulating the transformations if desired. Letting B denote
  42. *> the input bidiagonal matrix, the algorithm computes orthogonal
  43. *> matrices Q and P such that B = Q * S * P**T (P**T denotes the transpose
  44. *> of P). The singular values S are overwritten on D.
  45. *>
  46. *> The input matrix U is changed to U * Q if desired.
  47. *> The input matrix VT is changed to P**T * VT if desired.
  48. *> The input matrix C is changed to Q**T * C if desired.
  49. *>
  50. *> See "Computing Small Singular Values of Bidiagonal Matrices With
  51. *> Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan,
  52. *> LAPACK Working Note #3, for a detailed description of the algorithm.
  53. *> \endverbatim
  54. *
  55. * Arguments:
  56. * ==========
  57. *
  58. *> \param[in] UPLO
  59. *> \verbatim
  60. *> UPLO is CHARACTER*1
  61. *> On entry, UPLO specifies whether the input bidiagonal matrix
  62. *> is upper or lower bidiagonal, and whether it is square are
  63. *> not.
  64. *> UPLO = 'U' or 'u' B is upper bidiagonal.
  65. *> UPLO = 'L' or 'l' B is lower bidiagonal.
  66. *> \endverbatim
  67. *>
  68. *> \param[in] SQRE
  69. *> \verbatim
  70. *> SQRE is INTEGER
  71. *> = 0: then the input matrix is N-by-N.
  72. *> = 1: then the input matrix is N-by-(N+1) if UPLU = 'U' and
  73. *> (N+1)-by-N if UPLU = 'L'.
  74. *>
  75. *> The bidiagonal matrix has
  76. *> N = NL + NR + 1 rows and
  77. *> M = N + SQRE >= N columns.
  78. *> \endverbatim
  79. *>
  80. *> \param[in] N
  81. *> \verbatim
  82. *> N is INTEGER
  83. *> On entry, N specifies the number of rows and columns
  84. *> in the matrix. N must be at least 0.
  85. *> \endverbatim
  86. *>
  87. *> \param[in] NCVT
  88. *> \verbatim
  89. *> NCVT is INTEGER
  90. *> On entry, NCVT specifies the number of columns of
  91. *> the matrix VT. NCVT must be at least 0.
  92. *> \endverbatim
  93. *>
  94. *> \param[in] NRU
  95. *> \verbatim
  96. *> NRU is INTEGER
  97. *> On entry, NRU specifies the number of rows of
  98. *> the matrix U. NRU must be at least 0.
  99. *> \endverbatim
  100. *>
  101. *> \param[in] NCC
  102. *> \verbatim
  103. *> NCC is INTEGER
  104. *> On entry, NCC specifies the number of columns of
  105. *> the matrix C. NCC must be at least 0.
  106. *> \endverbatim
  107. *>
  108. *> \param[in,out] D
  109. *> \verbatim
  110. *> D is DOUBLE PRECISION array, dimension (N)
  111. *> On entry, D contains the diagonal entries of the
  112. *> bidiagonal matrix whose SVD is desired. On normal exit,
  113. *> D contains the singular values in ascending order.
  114. *> \endverbatim
  115. *>
  116. *> \param[in,out] E
  117. *> \verbatim
  118. *> E is DOUBLE PRECISION array.
  119. *> dimension is (N-1) if SQRE = 0 and N if SQRE = 1.
  120. *> On entry, the entries of E contain the offdiagonal entries
  121. *> of the bidiagonal matrix whose SVD is desired. On normal
  122. *> exit, E will contain 0. If the algorithm does not converge,
  123. *> D and E will contain the diagonal and superdiagonal entries
  124. *> of a bidiagonal matrix orthogonally equivalent to the one
  125. *> given as input.
  126. *> \endverbatim
  127. *>
  128. *> \param[in,out] VT
  129. *> \verbatim
  130. *> VT is DOUBLE PRECISION array, dimension (LDVT, NCVT)
  131. *> On entry, contains a matrix which on exit has been
  132. *> premultiplied by P**T, dimension N-by-NCVT if SQRE = 0
  133. *> and (N+1)-by-NCVT if SQRE = 1 (not referenced if NCVT=0).
  134. *> \endverbatim
  135. *>
  136. *> \param[in] LDVT
  137. *> \verbatim
  138. *> LDVT is INTEGER
  139. *> On entry, LDVT specifies the leading dimension of VT as
  140. *> declared in the calling (sub) program. LDVT must be at
  141. *> least 1. If NCVT is nonzero LDVT must also be at least N.
  142. *> \endverbatim
  143. *>
  144. *> \param[in,out] U
  145. *> \verbatim
  146. *> U is DOUBLE PRECISION array, dimension (LDU, N)
  147. *> On entry, contains a matrix which on exit has been
  148. *> postmultiplied by Q, dimension NRU-by-N if SQRE = 0
  149. *> and NRU-by-(N+1) if SQRE = 1 (not referenced if NRU=0).
  150. *> \endverbatim
  151. *>
  152. *> \param[in] LDU
  153. *> \verbatim
  154. *> LDU is INTEGER
  155. *> On entry, LDU specifies the leading dimension of U as
  156. *> declared in the calling (sub) program. LDU must be at
  157. *> least max( 1, NRU ) .
  158. *> \endverbatim
  159. *>
  160. *> \param[in,out] C
  161. *> \verbatim
  162. *> C is DOUBLE PRECISION array, dimension (LDC, NCC)
  163. *> On entry, contains an N-by-NCC matrix which on exit
  164. *> has been premultiplied by Q**T dimension N-by-NCC if SQRE = 0
  165. *> and (N+1)-by-NCC if SQRE = 1 (not referenced if NCC=0).
  166. *> \endverbatim
  167. *>
  168. *> \param[in] LDC
  169. *> \verbatim
  170. *> LDC is INTEGER
  171. *> On entry, LDC specifies the leading dimension of C as
  172. *> declared in the calling (sub) program. LDC must be at
  173. *> least 1. If NCC is nonzero, LDC must also be at least N.
  174. *> \endverbatim
  175. *>
  176. *> \param[out] WORK
  177. *> \verbatim
  178. *> WORK is DOUBLE PRECISION array, dimension (4*N)
  179. *> Workspace. Only referenced if one of NCVT, NRU, or NCC is
  180. *> nonzero, and if N is at least 2.
  181. *> \endverbatim
  182. *>
  183. *> \param[out] INFO
  184. *> \verbatim
  185. *> INFO is INTEGER
  186. *> On exit, a value of 0 indicates a successful exit.
  187. *> If INFO < 0, argument number -INFO is illegal.
  188. *> If INFO > 0, the algorithm did not converge, and INFO
  189. *> specifies how many superdiagonals did not converge.
  190. *> \endverbatim
  191. *
  192. * Authors:
  193. * ========
  194. *
  195. *> \author Univ. of Tennessee
  196. *> \author Univ. of California Berkeley
  197. *> \author Univ. of Colorado Denver
  198. *> \author NAG Ltd.
  199. *
  200. *> \date June 2016
  201. *
  202. *> \ingroup OTHERauxiliary
  203. *
  204. *> \par Contributors:
  205. * ==================
  206. *>
  207. *> Ming Gu and Huan Ren, Computer Science Division, University of
  208. *> California at Berkeley, USA
  209. *>
  210. * =====================================================================
  211. SUBROUTINE DLASDQ( UPLO, SQRE, N, NCVT, NRU, NCC, D, E, VT, LDVT,
  212. $ U, LDU, C, LDC, WORK, INFO )
  213. *
  214. * -- LAPACK auxiliary routine (version 3.7.0) --
  215. * -- LAPACK is a software package provided by Univ. of Tennessee, --
  216. * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
  217. * June 2016
  218. *
  219. * .. Scalar Arguments ..
  220. CHARACTER UPLO
  221. INTEGER INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU, SQRE
  222. * ..
  223. * .. Array Arguments ..
  224. DOUBLE PRECISION C( LDC, * ), D( * ), E( * ), U( LDU, * ),
  225. $ VT( LDVT, * ), WORK( * )
  226. * ..
  227. *
  228. * =====================================================================
  229. *
  230. * .. Parameters ..
  231. DOUBLE PRECISION ZERO
  232. PARAMETER ( ZERO = 0.0D+0 )
  233. * ..
  234. * .. Local Scalars ..
  235. LOGICAL ROTATE
  236. INTEGER I, ISUB, IUPLO, J, NP1, SQRE1
  237. DOUBLE PRECISION CS, R, SMIN, SN
  238. * ..
  239. * .. External Subroutines ..
  240. EXTERNAL DBDSQR, DLARTG, DLASR, DSWAP, XERBLA
  241. * ..
  242. * .. External Functions ..
  243. LOGICAL LSAME
  244. EXTERNAL LSAME
  245. * ..
  246. * .. Intrinsic Functions ..
  247. INTRINSIC MAX
  248. * ..
  249. * .. Executable Statements ..
  250. *
  251. * Test the input parameters.
  252. *
  253. INFO = 0
  254. IUPLO = 0
  255. IF( LSAME( UPLO, 'U' ) )
  256. $ IUPLO = 1
  257. IF( LSAME( UPLO, 'L' ) )
  258. $ IUPLO = 2
  259. IF( IUPLO.EQ.0 ) THEN
  260. INFO = -1
  261. ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN
  262. INFO = -2
  263. ELSE IF( N.LT.0 ) THEN
  264. INFO = -3
  265. ELSE IF( NCVT.LT.0 ) THEN
  266. INFO = -4
  267. ELSE IF( NRU.LT.0 ) THEN
  268. INFO = -5
  269. ELSE IF( NCC.LT.0 ) THEN
  270. INFO = -6
  271. ELSE IF( ( NCVT.EQ.0 .AND. LDVT.LT.1 ) .OR.
  272. $ ( NCVT.GT.0 .AND. LDVT.LT.MAX( 1, N ) ) ) THEN
  273. INFO = -10
  274. ELSE IF( LDU.LT.MAX( 1, NRU ) ) THEN
  275. INFO = -12
  276. ELSE IF( ( NCC.EQ.0 .AND. LDC.LT.1 ) .OR.
  277. $ ( NCC.GT.0 .AND. LDC.LT.MAX( 1, N ) ) ) THEN
  278. INFO = -14
  279. END IF
  280. IF( INFO.NE.0 ) THEN
  281. CALL XERBLA( 'DLASDQ', -INFO )
  282. RETURN
  283. END IF
  284. IF( N.EQ.0 )
  285. $ RETURN
  286. *
  287. * ROTATE is true if any singular vectors desired, false otherwise
  288. *
  289. ROTATE = ( NCVT.GT.0 ) .OR. ( NRU.GT.0 ) .OR. ( NCC.GT.0 )
  290. NP1 = N + 1
  291. SQRE1 = SQRE
  292. *
  293. * If matrix non-square upper bidiagonal, rotate to be lower
  294. * bidiagonal. The rotations are on the right.
  295. *
  296. IF( ( IUPLO.EQ.1 ) .AND. ( SQRE1.EQ.1 ) ) THEN
  297. DO 10 I = 1, N - 1
  298. CALL DLARTG( D( I ), E( I ), CS, SN, R )
  299. D( I ) = R
  300. E( I ) = SN*D( I+1 )
  301. D( I+1 ) = CS*D( I+1 )
  302. IF( ROTATE ) THEN
  303. WORK( I ) = CS
  304. WORK( N+I ) = SN
  305. END IF
  306. 10 CONTINUE
  307. CALL DLARTG( D( N ), E( N ), CS, SN, R )
  308. D( N ) = R
  309. E( N ) = ZERO
  310. IF( ROTATE ) THEN
  311. WORK( N ) = CS
  312. WORK( N+N ) = SN
  313. END IF
  314. IUPLO = 2
  315. SQRE1 = 0
  316. *
  317. * Update singular vectors if desired.
  318. *
  319. IF( NCVT.GT.0 )
  320. $ CALL DLASR( 'L', 'V', 'F', NP1, NCVT, WORK( 1 ),
  321. $ WORK( NP1 ), VT, LDVT )
  322. END IF
  323. *
  324. * If matrix lower bidiagonal, rotate to be upper bidiagonal
  325. * by applying Givens rotations on the left.
  326. *
  327. IF( IUPLO.EQ.2 ) THEN
  328. DO 20 I = 1, N - 1
  329. CALL DLARTG( D( I ), E( I ), CS, SN, R )
  330. D( I ) = R
  331. E( I ) = SN*D( I+1 )
  332. D( I+1 ) = CS*D( I+1 )
  333. IF( ROTATE ) THEN
  334. WORK( I ) = CS
  335. WORK( N+I ) = SN
  336. END IF
  337. 20 CONTINUE
  338. *
  339. * If matrix (N+1)-by-N lower bidiagonal, one additional
  340. * rotation is needed.
  341. *
  342. IF( SQRE1.EQ.1 ) THEN
  343. CALL DLARTG( D( N ), E( N ), CS, SN, R )
  344. D( N ) = R
  345. IF( ROTATE ) THEN
  346. WORK( N ) = CS
  347. WORK( N+N ) = SN
  348. END IF
  349. END IF
  350. *
  351. * Update singular vectors if desired.
  352. *
  353. IF( NRU.GT.0 ) THEN
  354. IF( SQRE1.EQ.0 ) THEN
  355. CALL DLASR( 'R', 'V', 'F', NRU, N, WORK( 1 ),
  356. $ WORK( NP1 ), U, LDU )
  357. ELSE
  358. CALL DLASR( 'R', 'V', 'F', NRU, NP1, WORK( 1 ),
  359. $ WORK( NP1 ), U, LDU )
  360. END IF
  361. END IF
  362. IF( NCC.GT.0 ) THEN
  363. IF( SQRE1.EQ.0 ) THEN
  364. CALL DLASR( 'L', 'V', 'F', N, NCC, WORK( 1 ),
  365. $ WORK( NP1 ), C, LDC )
  366. ELSE
  367. CALL DLASR( 'L', 'V', 'F', NP1, NCC, WORK( 1 ),
  368. $ WORK( NP1 ), C, LDC )
  369. END IF
  370. END IF
  371. END IF
  372. *
  373. * Call DBDSQR to compute the SVD of the reduced real
  374. * N-by-N upper bidiagonal matrix.
  375. *
  376. CALL DBDSQR( 'U', N, NCVT, NRU, NCC, D, E, VT, LDVT, U, LDU, C,
  377. $ LDC, WORK, INFO )
  378. *
  379. * Sort the singular values into ascending order (insertion sort on
  380. * singular values, but only one transposition per singular vector)
  381. *
  382. DO 40 I = 1, N
  383. *
  384. * Scan for smallest D(I).
  385. *
  386. ISUB = I
  387. SMIN = D( I )
  388. DO 30 J = I + 1, N
  389. IF( D( J ).LT.SMIN ) THEN
  390. ISUB = J
  391. SMIN = D( J )
  392. END IF
  393. 30 CONTINUE
  394. IF( ISUB.NE.I ) THEN
  395. *
  396. * Swap singular values and vectors.
  397. *
  398. D( ISUB ) = D( I )
  399. D( I ) = SMIN
  400. IF( NCVT.GT.0 )
  401. $ CALL DSWAP( NCVT, VT( ISUB, 1 ), LDVT, VT( I, 1 ), LDVT )
  402. IF( NRU.GT.0 )
  403. $ CALL DSWAP( NRU, U( 1, ISUB ), 1, U( 1, I ), 1 )
  404. IF( NCC.GT.0 )
  405. $ CALL DSWAP( NCC, C( ISUB, 1 ), LDC, C( I, 1 ), LDC )
  406. END IF
  407. 40 CONTINUE
  408. *
  409. RETURN
  410. *
  411. * End of DLASDQ
  412. *
  413. END