Annotation of rpl/lapack/lapack/zggbal.f, revision 1.19
1.8 bertrand 1: *> \brief \b ZGGBAL
2: *
3: * =========== DOCUMENTATION ===========
4: *
1.16 bertrand 5: * Online html documentation available at
6: * http://www.netlib.org/lapack/explore-html/
1.8 bertrand 7: *
8: *> \htmlonly
1.16 bertrand 9: *> Download ZGGBAL + dependencies
10: *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/zggbal.f">
11: *> [TGZ]</a>
12: *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/zggbal.f">
13: *> [ZIP]</a>
14: *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/zggbal.f">
1.8 bertrand 15: *> [TXT]</a>
1.16 bertrand 16: *> \endhtmlonly
1.8 bertrand 17: *
18: * Definition:
19: * ===========
20: *
21: * SUBROUTINE ZGGBAL( JOB, N, A, LDA, B, LDB, ILO, IHI, LSCALE,
22: * RSCALE, WORK, INFO )
1.16 bertrand 23: *
1.8 bertrand 24: * .. Scalar Arguments ..
25: * CHARACTER JOB
26: * INTEGER IHI, ILO, INFO, LDA, LDB, N
27: * ..
28: * .. Array Arguments ..
29: * DOUBLE PRECISION LSCALE( * ), RSCALE( * ), WORK( * )
30: * COMPLEX*16 A( LDA, * ), B( LDB, * )
31: * ..
1.16 bertrand 32: *
1.8 bertrand 33: *
34: *> \par Purpose:
35: * =============
36: *>
37: *> \verbatim
38: *>
39: *> ZGGBAL balances a pair of general complex 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 COMPLEX*16 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 COMPLEX*16 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) is the scaling factor
119: *> 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) is the scaling
133: *> factor applied to column j, then
134: *> RSCALE(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
1.14 bertrand 143: *> WORK is DOUBLE PRECISION array, dimension (lwork)
1.8 bertrand 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: *
1.16 bertrand 158: *> \author Univ. of Tennessee
159: *> \author Univ. of California Berkeley
160: *> \author Univ. of Colorado Denver
161: *> \author NAG Ltd.
1.8 bertrand 162: *
163: *> \ingroup complex16GBcomputational
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: * =====================================================================
1.1 bertrand 175: SUBROUTINE ZGGBAL( JOB, N, A, LDA, B, LDB, ILO, IHI, LSCALE,
176: $ RSCALE, WORK, INFO )
177: *
1.19 ! bertrand 178: * -- LAPACK computational routine --
1.1 bertrand 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 LSCALE( * ), RSCALE( * ), WORK( * )
188: COMPLEX*16 A( LDA, * ), B( LDB, * )
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: COMPLEX*16 CZERO
199: PARAMETER ( CZERO = ( 0.0D+0, 0.0D+0 ) )
200: * ..
201: * .. Local Scalars ..
202: INTEGER I, ICAB, IFLOW, IP1, IR, IRAB, IT, J, JC, JP1,
203: $ K, KOUNT, L, LCAB, LM1, LRAB, LSFMAX, LSFMIN,
204: $ M, NR, NRP2
205: DOUBLE PRECISION ALPHA, BASL, BETA, CAB, CMAX, COEF, COEF2,
206: $ COEF5, COR, EW, EWC, GAMMA, PGAMMA, RAB, SFMAX,
207: $ SFMIN, SUM, T, TA, TB, TC
208: COMPLEX*16 CDUM
209: * ..
210: * .. External Functions ..
211: LOGICAL LSAME
212: INTEGER IZAMAX
213: DOUBLE PRECISION DDOT, DLAMCH
214: EXTERNAL LSAME, IZAMAX, DDOT, DLAMCH
215: * ..
216: * .. External Subroutines ..
217: EXTERNAL DAXPY, DSCAL, XERBLA, ZDSCAL, ZSWAP
218: * ..
219: * .. Intrinsic Functions ..
220: INTRINSIC ABS, DBLE, DIMAG, INT, LOG10, MAX, MIN, SIGN
221: * ..
222: * .. Statement Functions ..
223: DOUBLE PRECISION CABS1
224: * ..
225: * .. Statement Function definitions ..
226: CABS1( CDUM ) = ABS( DBLE( CDUM ) ) + ABS( DIMAG( CDUM ) )
227: * ..
228: * .. Executable Statements ..
229: *
230: * Test the input parameters
231: *
232: INFO = 0
233: IF( .NOT.LSAME( JOB, 'N' ) .AND. .NOT.LSAME( JOB, 'P' ) .AND.
234: $ .NOT.LSAME( JOB, 'S' ) .AND. .NOT.LSAME( JOB, 'B' ) ) THEN
235: INFO = -1
236: ELSE IF( N.LT.0 ) THEN
237: INFO = -2
238: ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
239: INFO = -4
240: ELSE IF( LDB.LT.MAX( 1, N ) ) THEN
241: INFO = -6
242: END IF
243: IF( INFO.NE.0 ) THEN
244: CALL XERBLA( 'ZGGBAL', -INFO )
245: RETURN
246: END IF
247: *
248: * Quick return if possible
249: *
250: IF( N.EQ.0 ) THEN
251: ILO = 1
252: IHI = N
253: RETURN
254: END IF
255: *
256: IF( N.EQ.1 ) THEN
257: ILO = 1
258: IHI = N
259: LSCALE( 1 ) = ONE
260: RSCALE( 1 ) = ONE
261: RETURN
262: END IF
263: *
264: IF( LSAME( JOB, 'N' ) ) THEN
265: ILO = 1
266: IHI = N
267: DO 10 I = 1, N
268: LSCALE( I ) = ONE
269: RSCALE( I ) = ONE
270: 10 CONTINUE
271: RETURN
272: END IF
273: *
274: K = 1
275: L = N
276: IF( LSAME( JOB, 'S' ) )
277: $ GO TO 190
278: *
279: GO TO 30
280: *
281: * Permute the matrices A and B to isolate the eigenvalues.
282: *
283: * Find row with one nonzero in columns 1 through L
284: *
285: 20 CONTINUE
286: L = LM1
287: IF( L.NE.1 )
288: $ GO TO 30
289: *
290: RSCALE( 1 ) = 1
291: LSCALE( 1 ) = 1
292: GO TO 190
293: *
294: 30 CONTINUE
295: LM1 = L - 1
296: DO 80 I = L, 1, -1
297: DO 40 J = 1, LM1
298: JP1 = J + 1
299: IF( A( I, J ).NE.CZERO .OR. B( I, J ).NE.CZERO )
300: $ GO TO 50
301: 40 CONTINUE
302: J = L
303: GO TO 70
304: *
305: 50 CONTINUE
306: DO 60 J = JP1, L
307: IF( A( I, J ).NE.CZERO .OR. B( I, J ).NE.CZERO )
308: $ GO TO 80
309: 60 CONTINUE
310: J = JP1 - 1
311: *
312: 70 CONTINUE
313: M = L
314: IFLOW = 1
315: GO TO 160
316: 80 CONTINUE
317: GO TO 100
318: *
319: * Find column with one nonzero in rows K through N
320: *
321: 90 CONTINUE
322: K = K + 1
323: *
324: 100 CONTINUE
325: DO 150 J = K, L
326: DO 110 I = K, LM1
327: IP1 = I + 1
328: IF( A( I, J ).NE.CZERO .OR. B( I, J ).NE.CZERO )
329: $ GO TO 120
330: 110 CONTINUE
331: I = L
332: GO TO 140
333: 120 CONTINUE
334: DO 130 I = IP1, L
335: IF( A( I, J ).NE.CZERO .OR. B( I, J ).NE.CZERO )
336: $ GO TO 150
337: 130 CONTINUE
338: I = IP1 - 1
339: 140 CONTINUE
340: M = K
341: IFLOW = 2
342: GO TO 160
343: 150 CONTINUE
344: GO TO 190
345: *
346: * Permute rows M and I
347: *
348: 160 CONTINUE
349: LSCALE( M ) = I
350: IF( I.EQ.M )
351: $ GO TO 170
352: CALL ZSWAP( N-K+1, A( I, K ), LDA, A( M, K ), LDA )
353: CALL ZSWAP( N-K+1, B( I, K ), LDB, B( M, K ), LDB )
354: *
355: * Permute columns M and J
356: *
357: 170 CONTINUE
358: RSCALE( M ) = J
359: IF( J.EQ.M )
360: $ GO TO 180
361: CALL ZSWAP( L, A( 1, J ), 1, A( 1, M ), 1 )
362: CALL ZSWAP( L, B( 1, J ), 1, B( 1, M ), 1 )
363: *
364: 180 CONTINUE
365: GO TO ( 20, 90 )IFLOW
366: *
367: 190 CONTINUE
368: ILO = K
369: IHI = L
370: *
371: IF( LSAME( JOB, 'P' ) ) THEN
372: DO 195 I = ILO, IHI
373: LSCALE( I ) = ONE
374: RSCALE( I ) = ONE
375: 195 CONTINUE
376: RETURN
377: END IF
378: *
379: IF( ILO.EQ.IHI )
380: $ RETURN
381: *
382: * Balance the submatrix in rows ILO to IHI.
383: *
384: NR = IHI - ILO + 1
385: DO 200 I = ILO, IHI
386: RSCALE( I ) = ZERO
387: LSCALE( I ) = ZERO
388: *
389: WORK( I ) = ZERO
390: WORK( I+N ) = ZERO
391: WORK( I+2*N ) = ZERO
392: WORK( I+3*N ) = ZERO
393: WORK( I+4*N ) = ZERO
394: WORK( I+5*N ) = ZERO
395: 200 CONTINUE
396: *
397: * Compute right side vector in resulting linear equations
398: *
399: BASL = LOG10( SCLFAC )
400: DO 240 I = ILO, IHI
401: DO 230 J = ILO, IHI
402: IF( A( I, J ).EQ.CZERO ) THEN
403: TA = ZERO
404: GO TO 210
405: END IF
406: TA = LOG10( CABS1( A( I, J ) ) ) / BASL
407: *
408: 210 CONTINUE
409: IF( B( I, J ).EQ.CZERO ) THEN
410: TB = ZERO
411: GO TO 220
412: END IF
413: TB = LOG10( CABS1( B( I, J ) ) ) / BASL
414: *
415: 220 CONTINUE
416: WORK( I+4*N ) = WORK( I+4*N ) - TA - TB
417: WORK( J+5*N ) = WORK( J+5*N ) - TA - TB
418: 230 CONTINUE
419: 240 CONTINUE
420: *
421: COEF = ONE / DBLE( 2*NR )
422: COEF2 = COEF*COEF
423: COEF5 = HALF*COEF2
424: NRP2 = NR + 2
425: BETA = ZERO
426: IT = 1
427: *
428: * Start generalized conjugate gradient iteration
429: *
430: 250 CONTINUE
431: *
432: GAMMA = DDOT( NR, WORK( ILO+4*N ), 1, WORK( ILO+4*N ), 1 ) +
433: $ DDOT( NR, WORK( ILO+5*N ), 1, WORK( ILO+5*N ), 1 )
434: *
435: EW = ZERO
436: EWC = ZERO
437: DO 260 I = ILO, IHI
438: EW = EW + WORK( I+4*N )
439: EWC = EWC + WORK( I+5*N )
440: 260 CONTINUE
441: *
442: GAMMA = COEF*GAMMA - COEF2*( EW**2+EWC**2 ) - COEF5*( EW-EWC )**2
443: IF( GAMMA.EQ.ZERO )
444: $ GO TO 350
445: IF( IT.NE.1 )
446: $ BETA = GAMMA / PGAMMA
447: T = COEF5*( EWC-THREE*EW )
448: TC = COEF5*( EW-THREE*EWC )
449: *
450: CALL DSCAL( NR, BETA, WORK( ILO ), 1 )
451: CALL DSCAL( NR, BETA, WORK( ILO+N ), 1 )
452: *
453: CALL DAXPY( NR, COEF, WORK( ILO+4*N ), 1, WORK( ILO+N ), 1 )
454: CALL DAXPY( NR, COEF, WORK( ILO+5*N ), 1, WORK( ILO ), 1 )
455: *
456: DO 270 I = ILO, IHI
457: WORK( I ) = WORK( I ) + TC
458: WORK( I+N ) = WORK( I+N ) + T
459: 270 CONTINUE
460: *
461: * Apply matrix to vector
462: *
463: DO 300 I = ILO, IHI
464: KOUNT = 0
465: SUM = ZERO
466: DO 290 J = ILO, IHI
467: IF( A( I, J ).EQ.CZERO )
468: $ GO TO 280
469: KOUNT = KOUNT + 1
470: SUM = SUM + WORK( J )
471: 280 CONTINUE
472: IF( B( I, J ).EQ.CZERO )
473: $ GO TO 290
474: KOUNT = KOUNT + 1
475: SUM = SUM + WORK( J )
476: 290 CONTINUE
477: WORK( I+2*N ) = DBLE( KOUNT )*WORK( I+N ) + SUM
478: 300 CONTINUE
479: *
480: DO 330 J = ILO, IHI
481: KOUNT = 0
482: SUM = ZERO
483: DO 320 I = ILO, IHI
484: IF( A( I, J ).EQ.CZERO )
485: $ GO TO 310
486: KOUNT = KOUNT + 1
487: SUM = SUM + WORK( I+N )
488: 310 CONTINUE
489: IF( B( I, J ).EQ.CZERO )
490: $ GO TO 320
491: KOUNT = KOUNT + 1
492: SUM = SUM + WORK( I+N )
493: 320 CONTINUE
494: WORK( J+3*N ) = DBLE( KOUNT )*WORK( J ) + SUM
495: 330 CONTINUE
496: *
497: SUM = DDOT( NR, WORK( ILO+N ), 1, WORK( ILO+2*N ), 1 ) +
498: $ DDOT( NR, WORK( ILO ), 1, WORK( ILO+3*N ), 1 )
499: ALPHA = GAMMA / SUM
500: *
501: * Determine correction to current iteration
502: *
503: CMAX = ZERO
504: DO 340 I = ILO, IHI
505: COR = ALPHA*WORK( I+N )
506: IF( ABS( COR ).GT.CMAX )
507: $ CMAX = ABS( COR )
508: LSCALE( I ) = LSCALE( I ) + COR
509: COR = ALPHA*WORK( I )
510: IF( ABS( COR ).GT.CMAX )
511: $ CMAX = ABS( COR )
512: RSCALE( I ) = RSCALE( I ) + COR
513: 340 CONTINUE
514: IF( CMAX.LT.HALF )
515: $ GO TO 350
516: *
517: CALL DAXPY( NR, -ALPHA, WORK( ILO+2*N ), 1, WORK( ILO+4*N ), 1 )
518: CALL DAXPY( NR, -ALPHA, WORK( ILO+3*N ), 1, WORK( ILO+5*N ), 1 )
519: *
520: PGAMMA = GAMMA
521: IT = IT + 1
522: IF( IT.LE.NRP2 )
523: $ GO TO 250
524: *
525: * End generalized conjugate gradient iteration
526: *
527: 350 CONTINUE
528: SFMIN = DLAMCH( 'S' )
529: SFMAX = ONE / SFMIN
530: LSFMIN = INT( LOG10( SFMIN ) / BASL+ONE )
531: LSFMAX = INT( LOG10( SFMAX ) / BASL )
532: DO 360 I = ILO, IHI
533: IRAB = IZAMAX( N-ILO+1, A( I, ILO ), LDA )
534: RAB = ABS( A( I, IRAB+ILO-1 ) )
535: IRAB = IZAMAX( N-ILO+1, B( I, ILO ), LDB )
536: RAB = MAX( RAB, ABS( B( I, IRAB+ILO-1 ) ) )
537: LRAB = INT( LOG10( RAB+SFMIN ) / BASL+ONE )
1.13 bertrand 538: IR = INT(LSCALE( I ) + SIGN( HALF, LSCALE( I ) ))
1.1 bertrand 539: IR = MIN( MAX( IR, LSFMIN ), LSFMAX, LSFMAX-LRAB )
540: LSCALE( I ) = SCLFAC**IR
541: ICAB = IZAMAX( IHI, A( 1, I ), 1 )
542: CAB = ABS( A( ICAB, I ) )
543: ICAB = IZAMAX( IHI, B( 1, I ), 1 )
544: CAB = MAX( CAB, ABS( B( ICAB, I ) ) )
545: LCAB = INT( LOG10( CAB+SFMIN ) / BASL+ONE )
1.13 bertrand 546: JC = INT(RSCALE( I ) + SIGN( HALF, RSCALE( I ) ))
1.1 bertrand 547: JC = MIN( MAX( JC, LSFMIN ), LSFMAX, LSFMAX-LCAB )
548: RSCALE( I ) = SCLFAC**JC
549: 360 CONTINUE
550: *
551: * Row scaling of matrices A and B
552: *
553: DO 370 I = ILO, IHI
554: CALL ZDSCAL( N-ILO+1, LSCALE( I ), A( I, ILO ), LDA )
555: CALL ZDSCAL( N-ILO+1, LSCALE( I ), B( I, ILO ), LDB )
556: 370 CONTINUE
557: *
558: * Column scaling of matrices A and B
559: *
560: DO 380 J = ILO, IHI
561: CALL ZDSCAL( IHI, RSCALE( J ), A( 1, J ), 1 )
562: CALL ZDSCAL( IHI, RSCALE( J ), B( 1, J ), 1 )
563: 380 CONTINUE
564: *
565: RETURN
566: *
567: * End of ZGGBAL
568: *
569: END
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