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dggbal.f 16 kB

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  1. *> \brief \b DGGBAL
  2. *
  3. * =========== DOCUMENTATION ===========
  4. *
  5. * Online html documentation available at
  6. * http://www.netlib.org/lapack/explore-html/
  7. *
  8. *> \htmlonly
  9. *> Download DGGBAL + dependencies
  10. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dggbal.f">
  11. *> [TGZ]</a>
  12. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dggbal.f">
  13. *> [ZIP]</a>
  14. *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dggbal.f">
  15. *> [TXT]</a>
  16. *> \endhtmlonly
  17. *
  18. * Definition:
  19. * ===========
  20. *
  21. * SUBROUTINE DGGBAL( JOB, N, A, LDA, B, LDB, ILO, IHI, LSCALE,
  22. * RSCALE, WORK, INFO )
  23. *
  24. * .. Scalar Arguments ..
  25. * CHARACTER JOB
  26. * INTEGER IHI, ILO, INFO, LDA, LDB, N
  27. * ..
  28. * .. Array Arguments ..
  29. * DOUBLE PRECISION A( LDA, * ), B( LDB, * ), LSCALE( * ),
  30. * $ RSCALE( * ), WORK( * )
  31. * ..
  32. *
  33. *
  34. *> \par Purpose:
  35. * =============
  36. *>
  37. *> \verbatim
  38. *>
  39. *> DGGBAL balances a pair of general real matrices (A,B). This
  40. *> involves, first, permuting A and B by similarity transformations to
  41. *> isolate eigenvalues in the first 1 to ILO$-$1 and last IHI+1 to N
  42. *> elements on the diagonal; and second, applying a diagonal similarity
  43. *> transformation to rows and columns ILO to IHI to make the rows
  44. *> and columns as close in norm as possible. Both steps are optional.
  45. *>
  46. *> Balancing may reduce the 1-norm of the matrices, and improve the
  47. *> accuracy of the computed eigenvalues and/or eigenvectors in the
  48. *> generalized eigenvalue problem A*x = lambda*B*x.
  49. *> \endverbatim
  50. *
  51. * Arguments:
  52. * ==========
  53. *
  54. *> \param[in] JOB
  55. *> \verbatim
  56. *> JOB is CHARACTER*1
  57. *> Specifies the operations to be performed on A and B:
  58. *> = 'N': none: simply set ILO = 1, IHI = N, LSCALE(I) = 1.0
  59. *> and RSCALE(I) = 1.0 for i = 1,...,N.
  60. *> = 'P': permute only;
  61. *> = 'S': scale only;
  62. *> = 'B': both permute and scale.
  63. *> \endverbatim
  64. *>
  65. *> \param[in] N
  66. *> \verbatim
  67. *> N is INTEGER
  68. *> The order of the matrices A and B. N >= 0.
  69. *> \endverbatim
  70. *>
  71. *> \param[in,out] A
  72. *> \verbatim
  73. *> A is DOUBLE PRECISION array, dimension (LDA,N)
  74. *> On entry, the input matrix A.
  75. *> On exit, A is overwritten by the balanced matrix.
  76. *> If JOB = 'N', A is not referenced.
  77. *> \endverbatim
  78. *>
  79. *> \param[in] LDA
  80. *> \verbatim
  81. *> LDA is INTEGER
  82. *> The leading dimension of the array A. LDA >= max(1,N).
  83. *> \endverbatim
  84. *>
  85. *> \param[in,out] B
  86. *> \verbatim
  87. *> B is DOUBLE PRECISION array, dimension (LDB,N)
  88. *> On entry, the input matrix B.
  89. *> On exit, B is overwritten by the balanced matrix.
  90. *> If JOB = 'N', B is not referenced.
  91. *> \endverbatim
  92. *>
  93. *> \param[in] LDB
  94. *> \verbatim
  95. *> LDB is INTEGER
  96. *> The leading dimension of the array B. LDB >= max(1,N).
  97. *> \endverbatim
  98. *>
  99. *> \param[out] ILO
  100. *> \verbatim
  101. *> ILO is INTEGER
  102. *> \endverbatim
  103. *>
  104. *> \param[out] IHI
  105. *> \verbatim
  106. *> IHI is INTEGER
  107. *> ILO and IHI are set to integers such that on exit
  108. *> A(i,j) = 0 and B(i,j) = 0 if i > j and
  109. *> j = 1,...,ILO-1 or i = IHI+1,...,N.
  110. *> If JOB = 'N' or 'S', ILO = 1 and IHI = N.
  111. *> \endverbatim
  112. *>
  113. *> \param[out] LSCALE
  114. *> \verbatim
  115. *> LSCALE is DOUBLE PRECISION array, dimension (N)
  116. *> Details of the permutations and scaling factors applied
  117. *> to the left side of A and B. If P(j) is the index of the
  118. *> row interchanged with row j, and D(j)
  119. *> is the scaling factor applied to row j, then
  120. *> LSCALE(j) = P(j) for J = 1,...,ILO-1
  121. *> = D(j) for J = ILO,...,IHI
  122. *> = P(j) for J = IHI+1,...,N.
  123. *> The order in which the interchanges are made is N to IHI+1,
  124. *> then 1 to ILO-1.
  125. *> \endverbatim
  126. *>
  127. *> \param[out] RSCALE
  128. *> \verbatim
  129. *> RSCALE is DOUBLE PRECISION array, dimension (N)
  130. *> Details of the permutations and scaling factors applied
  131. *> to the right side of A and B. If P(j) is the index of the
  132. *> column interchanged with column j, and D(j)
  133. *> is the scaling factor applied to column j, then
  134. *> LSCALE(j) = P(j) for J = 1,...,ILO-1
  135. *> = D(j) for J = ILO,...,IHI
  136. *> = P(j) for J = IHI+1,...,N.
  137. *> The order in which the interchanges are made is N to IHI+1,
  138. *> then 1 to ILO-1.
  139. *> \endverbatim
  140. *>
  141. *> \param[out] WORK
  142. *> \verbatim
  143. *> WORK is DOUBLE PRECISION array, dimension (lwork)
  144. *> lwork must be at least max(1,6*N) when JOB = 'S' or 'B', and
  145. *> at least 1 when JOB = 'N' or 'P'.
  146. *> \endverbatim
  147. *>
  148. *> \param[out] INFO
  149. *> \verbatim
  150. *> INFO is INTEGER
  151. *> = 0: successful exit
  152. *> < 0: if INFO = -i, the i-th argument had an illegal value.
  153. *> \endverbatim
  154. *
  155. * Authors:
  156. * ========
  157. *
  158. *> \author Univ. of Tennessee
  159. *> \author Univ. of California Berkeley
  160. *> \author Univ. of Colorado Denver
  161. *> \author NAG Ltd.
  162. *
  163. *> \ingroup doubleGBcomputational
  164. *
  165. *> \par Further Details:
  166. * =====================
  167. *>
  168. *> \verbatim
  169. *>
  170. *> See R.C. WARD, Balancing the generalized eigenvalue problem,
  171. *> SIAM J. Sci. Stat. Comp. 2 (1981), 141-152.
  172. *> \endverbatim
  173. *>
  174. * =====================================================================
  175. SUBROUTINE DGGBAL( JOB, N, A, LDA, B, LDB, ILO, IHI, LSCALE,
  176. $ RSCALE, WORK, INFO )
  177. *
  178. * -- LAPACK computational routine --
  179. * -- LAPACK is a software package provided by Univ. of Tennessee, --
  180. * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
  181. *
  182. * .. Scalar Arguments ..
  183. CHARACTER JOB
  184. INTEGER IHI, ILO, INFO, LDA, LDB, N
  185. * ..
  186. * .. Array Arguments ..
  187. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), LSCALE( * ),
  188. $ RSCALE( * ), WORK( * )
  189. * ..
  190. *
  191. * =====================================================================
  192. *
  193. * .. Parameters ..
  194. DOUBLE PRECISION ZERO, HALF, ONE
  195. PARAMETER ( ZERO = 0.0D+0, HALF = 0.5D+0, ONE = 1.0D+0 )
  196. DOUBLE PRECISION THREE, SCLFAC
  197. PARAMETER ( THREE = 3.0D+0, SCLFAC = 1.0D+1 )
  198. * ..
  199. * .. Local Scalars ..
  200. INTEGER I, ICAB, IFLOW, IP1, IR, IRAB, IT, J, JC, JP1,
  201. $ K, KOUNT, L, LCAB, LM1, LRAB, LSFMAX, LSFMIN,
  202. $ M, NR, NRP2
  203. DOUBLE PRECISION ALPHA, BASL, BETA, CAB, CMAX, COEF, COEF2,
  204. $ COEF5, COR, EW, EWC, GAMMA, PGAMMA, RAB, SFMAX,
  205. $ SFMIN, SUM, T, TA, TB, TC
  206. * ..
  207. * .. External Functions ..
  208. LOGICAL LSAME
  209. INTEGER IDAMAX
  210. DOUBLE PRECISION DDOT, DLAMCH
  211. EXTERNAL LSAME, IDAMAX, DDOT, DLAMCH
  212. * ..
  213. * .. External Subroutines ..
  214. EXTERNAL DAXPY, DSCAL, DSWAP, XERBLA
  215. * ..
  216. * .. Intrinsic Functions ..
  217. INTRINSIC ABS, DBLE, INT, LOG10, MAX, MIN, SIGN
  218. * ..
  219. * .. Executable Statements ..
  220. *
  221. * Test the input parameters
  222. *
  223. INFO = 0
  224. IF( .NOT.LSAME( JOB, 'N' ) .AND. .NOT.LSAME( JOB, 'P' ) .AND.
  225. $ .NOT.LSAME( JOB, 'S' ) .AND. .NOT.LSAME( JOB, 'B' ) ) THEN
  226. INFO = -1
  227. ELSE IF( N.LT.0 ) THEN
  228. INFO = -2
  229. ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
  230. INFO = -4
  231. ELSE IF( LDB.LT.MAX( 1, N ) ) THEN
  232. INFO = -6
  233. END IF
  234. IF( INFO.NE.0 ) THEN
  235. CALL XERBLA( 'DGGBAL', -INFO )
  236. RETURN
  237. END IF
  238. *
  239. * Quick return if possible
  240. *
  241. IF( N.EQ.0 ) THEN
  242. ILO = 1
  243. IHI = N
  244. RETURN
  245. END IF
  246. *
  247. IF( N.EQ.1 ) THEN
  248. ILO = 1
  249. IHI = N
  250. LSCALE( 1 ) = ONE
  251. RSCALE( 1 ) = ONE
  252. RETURN
  253. END IF
  254. *
  255. IF( LSAME( JOB, 'N' ) ) THEN
  256. ILO = 1
  257. IHI = N
  258. DO 10 I = 1, N
  259. LSCALE( I ) = ONE
  260. RSCALE( I ) = ONE
  261. 10 CONTINUE
  262. RETURN
  263. END IF
  264. *
  265. K = 1
  266. L = N
  267. IF( LSAME( JOB, 'S' ) )
  268. $ GO TO 190
  269. *
  270. GO TO 30
  271. *
  272. * Permute the matrices A and B to isolate the eigenvalues.
  273. *
  274. * Find row with one nonzero in columns 1 through L
  275. *
  276. 20 CONTINUE
  277. L = LM1
  278. IF( L.NE.1 )
  279. $ GO TO 30
  280. *
  281. RSCALE( 1 ) = ONE
  282. LSCALE( 1 ) = ONE
  283. GO TO 190
  284. *
  285. 30 CONTINUE
  286. LM1 = L - 1
  287. DO 80 I = L, 1, -1
  288. DO 40 J = 1, LM1
  289. JP1 = J + 1
  290. IF( A( I, J ).NE.ZERO .OR. B( I, J ).NE.ZERO )
  291. $ GO TO 50
  292. 40 CONTINUE
  293. J = L
  294. GO TO 70
  295. *
  296. 50 CONTINUE
  297. DO 60 J = JP1, L
  298. IF( A( I, J ).NE.ZERO .OR. B( I, J ).NE.ZERO )
  299. $ GO TO 80
  300. 60 CONTINUE
  301. J = JP1 - 1
  302. *
  303. 70 CONTINUE
  304. M = L
  305. IFLOW = 1
  306. GO TO 160
  307. 80 CONTINUE
  308. GO TO 100
  309. *
  310. * Find column with one nonzero in rows K through N
  311. *
  312. 90 CONTINUE
  313. K = K + 1
  314. *
  315. 100 CONTINUE
  316. DO 150 J = K, L
  317. DO 110 I = K, LM1
  318. IP1 = I + 1
  319. IF( A( I, J ).NE.ZERO .OR. B( I, J ).NE.ZERO )
  320. $ GO TO 120
  321. 110 CONTINUE
  322. I = L
  323. GO TO 140
  324. 120 CONTINUE
  325. DO 130 I = IP1, L
  326. IF( A( I, J ).NE.ZERO .OR. B( I, J ).NE.ZERO )
  327. $ GO TO 150
  328. 130 CONTINUE
  329. I = IP1 - 1
  330. 140 CONTINUE
  331. M = K
  332. IFLOW = 2
  333. GO TO 160
  334. 150 CONTINUE
  335. GO TO 190
  336. *
  337. * Permute rows M and I
  338. *
  339. 160 CONTINUE
  340. LSCALE( M ) = I
  341. IF( I.EQ.M )
  342. $ GO TO 170
  343. CALL DSWAP( N-K+1, A( I, K ), LDA, A( M, K ), LDA )
  344. CALL DSWAP( N-K+1, B( I, K ), LDB, B( M, K ), LDB )
  345. *
  346. * Permute columns M and J
  347. *
  348. 170 CONTINUE
  349. RSCALE( M ) = J
  350. IF( J.EQ.M )
  351. $ GO TO 180
  352. CALL DSWAP( L, A( 1, J ), 1, A( 1, M ), 1 )
  353. CALL DSWAP( L, B( 1, J ), 1, B( 1, M ), 1 )
  354. *
  355. 180 CONTINUE
  356. GO TO ( 20, 90 )IFLOW
  357. *
  358. 190 CONTINUE
  359. ILO = K
  360. IHI = L
  361. *
  362. IF( LSAME( JOB, 'P' ) ) THEN
  363. DO 195 I = ILO, IHI
  364. LSCALE( I ) = ONE
  365. RSCALE( I ) = ONE
  366. 195 CONTINUE
  367. RETURN
  368. END IF
  369. *
  370. IF( ILO.EQ.IHI )
  371. $ RETURN
  372. *
  373. * Balance the submatrix in rows ILO to IHI.
  374. *
  375. NR = IHI - ILO + 1
  376. DO 200 I = ILO, IHI
  377. RSCALE( I ) = ZERO
  378. LSCALE( I ) = ZERO
  379. *
  380. WORK( I ) = ZERO
  381. WORK( I+N ) = ZERO
  382. WORK( I+2*N ) = ZERO
  383. WORK( I+3*N ) = ZERO
  384. WORK( I+4*N ) = ZERO
  385. WORK( I+5*N ) = ZERO
  386. 200 CONTINUE
  387. *
  388. * Compute right side vector in resulting linear equations
  389. *
  390. BASL = LOG10( SCLFAC )
  391. DO 240 I = ILO, IHI
  392. DO 230 J = ILO, IHI
  393. TB = B( I, J )
  394. TA = A( I, J )
  395. IF( TA.EQ.ZERO )
  396. $ GO TO 210
  397. TA = LOG10( ABS( TA ) ) / BASL
  398. 210 CONTINUE
  399. IF( TB.EQ.ZERO )
  400. $ GO TO 220
  401. TB = LOG10( ABS( TB ) ) / BASL
  402. 220 CONTINUE
  403. WORK( I+4*N ) = WORK( I+4*N ) - TA - TB
  404. WORK( J+5*N ) = WORK( J+5*N ) - TA - TB
  405. 230 CONTINUE
  406. 240 CONTINUE
  407. *
  408. COEF = ONE / DBLE( 2*NR )
  409. COEF2 = COEF*COEF
  410. COEF5 = HALF*COEF2
  411. NRP2 = NR + 2
  412. BETA = ZERO
  413. IT = 1
  414. *
  415. * Start generalized conjugate gradient iteration
  416. *
  417. 250 CONTINUE
  418. *
  419. GAMMA = DDOT( NR, WORK( ILO+4*N ), 1, WORK( ILO+4*N ), 1 ) +
  420. $ DDOT( NR, WORK( ILO+5*N ), 1, WORK( ILO+5*N ), 1 )
  421. *
  422. EW = ZERO
  423. EWC = ZERO
  424. DO 260 I = ILO, IHI
  425. EW = EW + WORK( I+4*N )
  426. EWC = EWC + WORK( I+5*N )
  427. 260 CONTINUE
  428. *
  429. GAMMA = COEF*GAMMA - COEF2*( EW**2+EWC**2 ) - COEF5*( EW-EWC )**2
  430. IF( GAMMA.EQ.ZERO )
  431. $ GO TO 350
  432. IF( IT.NE.1 )
  433. $ BETA = GAMMA / PGAMMA
  434. T = COEF5*( EWC-THREE*EW )
  435. TC = COEF5*( EW-THREE*EWC )
  436. *
  437. CALL DSCAL( NR, BETA, WORK( ILO ), 1 )
  438. CALL DSCAL( NR, BETA, WORK( ILO+N ), 1 )
  439. *
  440. CALL DAXPY( NR, COEF, WORK( ILO+4*N ), 1, WORK( ILO+N ), 1 )
  441. CALL DAXPY( NR, COEF, WORK( ILO+5*N ), 1, WORK( ILO ), 1 )
  442. *
  443. DO 270 I = ILO, IHI
  444. WORK( I ) = WORK( I ) + TC
  445. WORK( I+N ) = WORK( I+N ) + T
  446. 270 CONTINUE
  447. *
  448. * Apply matrix to vector
  449. *
  450. DO 300 I = ILO, IHI
  451. KOUNT = 0
  452. SUM = ZERO
  453. DO 290 J = ILO, IHI
  454. IF( A( I, J ).EQ.ZERO )
  455. $ GO TO 280
  456. KOUNT = KOUNT + 1
  457. SUM = SUM + WORK( J )
  458. 280 CONTINUE
  459. IF( B( I, J ).EQ.ZERO )
  460. $ GO TO 290
  461. KOUNT = KOUNT + 1
  462. SUM = SUM + WORK( J )
  463. 290 CONTINUE
  464. WORK( I+2*N ) = DBLE( KOUNT )*WORK( I+N ) + SUM
  465. 300 CONTINUE
  466. *
  467. DO 330 J = ILO, IHI
  468. KOUNT = 0
  469. SUM = ZERO
  470. DO 320 I = ILO, IHI
  471. IF( A( I, J ).EQ.ZERO )
  472. $ GO TO 310
  473. KOUNT = KOUNT + 1
  474. SUM = SUM + WORK( I+N )
  475. 310 CONTINUE
  476. IF( B( I, J ).EQ.ZERO )
  477. $ GO TO 320
  478. KOUNT = KOUNT + 1
  479. SUM = SUM + WORK( I+N )
  480. 320 CONTINUE
  481. WORK( J+3*N ) = DBLE( KOUNT )*WORK( J ) + SUM
  482. 330 CONTINUE
  483. *
  484. SUM = DDOT( NR, WORK( ILO+N ), 1, WORK( ILO+2*N ), 1 ) +
  485. $ DDOT( NR, WORK( ILO ), 1, WORK( ILO+3*N ), 1 )
  486. ALPHA = GAMMA / SUM
  487. *
  488. * Determine correction to current iteration
  489. *
  490. CMAX = ZERO
  491. DO 340 I = ILO, IHI
  492. COR = ALPHA*WORK( I+N )
  493. IF( ABS( COR ).GT.CMAX )
  494. $ CMAX = ABS( COR )
  495. LSCALE( I ) = LSCALE( I ) + COR
  496. COR = ALPHA*WORK( I )
  497. IF( ABS( COR ).GT.CMAX )
  498. $ CMAX = ABS( COR )
  499. RSCALE( I ) = RSCALE( I ) + COR
  500. 340 CONTINUE
  501. IF( CMAX.LT.HALF )
  502. $ GO TO 350
  503. *
  504. CALL DAXPY( NR, -ALPHA, WORK( ILO+2*N ), 1, WORK( ILO+4*N ), 1 )
  505. CALL DAXPY( NR, -ALPHA, WORK( ILO+3*N ), 1, WORK( ILO+5*N ), 1 )
  506. *
  507. PGAMMA = GAMMA
  508. IT = IT + 1
  509. IF( IT.LE.NRP2 )
  510. $ GO TO 250
  511. *
  512. * End generalized conjugate gradient iteration
  513. *
  514. 350 CONTINUE
  515. SFMIN = DLAMCH( 'S' )
  516. SFMAX = ONE / SFMIN
  517. LSFMIN = INT( LOG10( SFMIN ) / BASL+ONE )
  518. LSFMAX = INT( LOG10( SFMAX ) / BASL )
  519. DO 360 I = ILO, IHI
  520. IRAB = IDAMAX( N-ILO+1, A( I, ILO ), LDA )
  521. RAB = ABS( A( I, IRAB+ILO-1 ) )
  522. IRAB = IDAMAX( N-ILO+1, B( I, ILO ), LDB )
  523. RAB = MAX( RAB, ABS( B( I, IRAB+ILO-1 ) ) )
  524. LRAB = INT( LOG10( RAB+SFMIN ) / BASL+ONE )
  525. IR = INT(LSCALE( I ) + SIGN( HALF, LSCALE( I ) ))
  526. IR = MIN( MAX( IR, LSFMIN ), LSFMAX, LSFMAX-LRAB )
  527. LSCALE( I ) = SCLFAC**IR
  528. ICAB = IDAMAX( IHI, A( 1, I ), 1 )
  529. CAB = ABS( A( ICAB, I ) )
  530. ICAB = IDAMAX( IHI, B( 1, I ), 1 )
  531. CAB = MAX( CAB, ABS( B( ICAB, I ) ) )
  532. LCAB = INT( LOG10( CAB+SFMIN ) / BASL+ONE )
  533. JC = INT(RSCALE( I ) + SIGN( HALF, RSCALE( I ) ))
  534. JC = MIN( MAX( JC, LSFMIN ), LSFMAX, LSFMAX-LCAB )
  535. RSCALE( I ) = SCLFAC**JC
  536. 360 CONTINUE
  537. *
  538. * Row scaling of matrices A and B
  539. *
  540. DO 370 I = ILO, IHI
  541. CALL DSCAL( N-ILO+1, LSCALE( I ), A( I, ILO ), LDA )
  542. CALL DSCAL( N-ILO+1, LSCALE( I ), B( I, ILO ), LDB )
  543. 370 CONTINUE
  544. *
  545. * Column scaling of matrices A and B
  546. *
  547. DO 380 J = ILO, IHI
  548. CALL DSCAL( IHI, RSCALE( J ), A( 1, J ), 1 )
  549. CALL DSCAL( IHI, RSCALE( J ), B( 1, J ), 1 )
  550. 380 CONTINUE
  551. *
  552. RETURN
  553. *
  554. * End of DGGBAL
  555. *
  556. END