LAPACK  3.6.1
LAPACK: Linear Algebra PACKage
dpbsvx.f
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1 *> \brief <b> DPBSVX computes the solution to system of linear equations A * X = B for OTHER 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 DPBSVX + dependencies
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11 *> [TGZ]</a>
12 *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dpbsvx.f">
13 *> [ZIP]</a>
14 *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dpbsvx.f">
15 *> [TXT]</a>
16 *> \endhtmlonly
17 *
18 * Definition:
19 * ===========
20 *
21 * SUBROUTINE DPBSVX( FACT, UPLO, N, KD, NRHS, AB, LDAB, AFB, LDAFB,
22 * EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR,
23 * WORK, IWORK, INFO )
24 *
25 * .. Scalar Arguments ..
26 * CHARACTER EQUED, FACT, UPLO
27 * INTEGER INFO, KD, LDAB, LDAFB, LDB, LDX, N, NRHS
28 * DOUBLE PRECISION RCOND
29 * ..
30 * .. Array Arguments ..
31 * INTEGER IWORK( * )
32 * DOUBLE PRECISION AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ),
33 * $ BERR( * ), FERR( * ), S( * ), WORK( * ),
34 * $ X( LDX, * )
35 * ..
36 *
37 *
38 *> \par Purpose:
39 * =============
40 *>
41 *> \verbatim
42 *>
43 *> DPBSVX uses the Cholesky factorization A = U**T*U or A = L*L**T to
44 *> compute the solution to a real system of linear equations
45 *> A * X = B,
46 *> where A is an N-by-N symmetric positive definite band matrix and X
47 *> and B are N-by-NRHS matrices.
48 *>
49 *> Error bounds on the solution and a condition estimate are also
50 *> provided.
51 *> \endverbatim
52 *
53 *> \par Description:
54 * =================
55 *>
56 *> \verbatim
57 *>
58 *> The following steps are performed:
59 *>
60 *> 1. If FACT = 'E', real scaling factors are computed to equilibrate
61 *> the system:
62 *> diag(S) * A * diag(S) * inv(diag(S)) * X = diag(S) * B
63 *> Whether or not the system will be equilibrated depends on the
64 *> scaling of the matrix A, but if equilibration is used, A is
65 *> overwritten by diag(S)*A*diag(S) and B by diag(S)*B.
66 *>
67 *> 2. If FACT = 'N' or 'E', the Cholesky decomposition is used to
68 *> factor the matrix A (after equilibration if FACT = 'E') as
69 *> A = U**T * U, if UPLO = 'U', or
70 *> A = L * L**T, if UPLO = 'L',
71 *> where U is an upper triangular band matrix, and L is a lower
72 *> triangular band matrix.
73 *>
74 *> 3. If the leading i-by-i principal minor is not positive definite,
75 *> then the routine returns with INFO = i. Otherwise, the factored
76 *> form of A is used to estimate the condition number of the matrix
77 *> A. If the reciprocal of the condition number is less than machine
78 *> precision, INFO = N+1 is returned as a warning, but the routine
79 *> still goes on to solve for X and compute error bounds as
80 *> described below.
81 *>
82 *> 4. The system of equations is solved for X using the factored form
83 *> of A.
84 *>
85 *> 5. Iterative refinement is applied to improve the computed solution
86 *> matrix and calculate error bounds and backward error estimates
87 *> for it.
88 *>
89 *> 6. If equilibration was used, the matrix X is premultiplied by
90 *> diag(S) so that it solves the original system before
91 *> equilibration.
92 *> \endverbatim
93 *
94 * Arguments:
95 * ==========
96 *
97 *> \param[in] FACT
98 *> \verbatim
99 *> FACT is CHARACTER*1
100 *> Specifies whether or not the factored form of the matrix A is
101 *> supplied on entry, and if not, whether the matrix A should be
102 *> equilibrated before it is factored.
103 *> = 'F': On entry, AFB contains the factored form of A.
104 *> If EQUED = 'Y', the matrix A has been equilibrated
105 *> with scaling factors given by S. AB and AFB will not
106 *> be modified.
107 *> = 'N': The matrix A will be copied to AFB and factored.
108 *> = 'E': The matrix A will be equilibrated if necessary, then
109 *> copied to AFB and factored.
110 *> \endverbatim
111 *>
112 *> \param[in] UPLO
113 *> \verbatim
114 *> UPLO is CHARACTER*1
115 *> = 'U': Upper triangle of A is stored;
116 *> = 'L': Lower triangle of A is stored.
117 *> \endverbatim
118 *>
119 *> \param[in] N
120 *> \verbatim
121 *> N is INTEGER
122 *> The number of linear equations, i.e., the order of the
123 *> matrix A. N >= 0.
124 *> \endverbatim
125 *>
126 *> \param[in] KD
127 *> \verbatim
128 *> KD is INTEGER
129 *> The number of superdiagonals of the matrix A if UPLO = 'U',
130 *> or the number of subdiagonals if UPLO = 'L'. KD >= 0.
131 *> \endverbatim
132 *>
133 *> \param[in] NRHS
134 *> \verbatim
135 *> NRHS is INTEGER
136 *> The number of right-hand sides, i.e., the number of columns
137 *> of the matrices B and X. NRHS >= 0.
138 *> \endverbatim
139 *>
140 *> \param[in,out] AB
141 *> \verbatim
142 *> AB is DOUBLE PRECISION array, dimension (LDAB,N)
143 *> On entry, the upper or lower triangle of the symmetric band
144 *> matrix A, stored in the first KD+1 rows of the array, except
145 *> if FACT = 'F' and EQUED = 'Y', then A must contain the
146 *> equilibrated matrix diag(S)*A*diag(S). The j-th column of A
147 *> is stored in the j-th column of the array AB as follows:
148 *> if UPLO = 'U', AB(KD+1+i-j,j) = A(i,j) for max(1,j-KD)<=i<=j;
149 *> if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(N,j+KD).
150 *> See below for further details.
151 *>
152 *> On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by
153 *> diag(S)*A*diag(S).
154 *> \endverbatim
155 *>
156 *> \param[in] LDAB
157 *> \verbatim
158 *> LDAB is INTEGER
159 *> The leading dimension of the array A. LDAB >= KD+1.
160 *> \endverbatim
161 *>
162 *> \param[in,out] AFB
163 *> \verbatim
164 *> AFB is DOUBLE PRECISION array, dimension (LDAFB,N)
165 *> If FACT = 'F', then AFB is an input argument and on entry
166 *> contains the triangular factor U or L from the Cholesky
167 *> factorization A = U**T*U or A = L*L**T of the band matrix
168 *> A, in the same storage format as A (see AB). If EQUED = 'Y',
169 *> then AFB is the factored form of the equilibrated matrix A.
170 *>
171 *> If FACT = 'N', then AFB is an output argument and on exit
172 *> returns the triangular factor U or L from the Cholesky
173 *> factorization A = U**T*U or A = L*L**T.
174 *>
175 *> If FACT = 'E', then AFB is an output argument and on exit
176 *> returns the triangular factor U or L from the Cholesky
177 *> factorization A = U**T*U or A = L*L**T of the equilibrated
178 *> matrix A (see the description of A for the form of the
179 *> equilibrated matrix).
180 *> \endverbatim
181 *>
182 *> \param[in] LDAFB
183 *> \verbatim
184 *> LDAFB is INTEGER
185 *> The leading dimension of the array AFB. LDAFB >= KD+1.
186 *> \endverbatim
187 *>
188 *> \param[in,out] EQUED
189 *> \verbatim
190 *> EQUED is CHARACTER*1
191 *> Specifies the form of equilibration that was done.
192 *> = 'N': No equilibration (always true if FACT = 'N').
193 *> = 'Y': Equilibration was done, i.e., A has been replaced by
194 *> diag(S) * A * diag(S).
195 *> EQUED is an input argument if FACT = 'F'; otherwise, it is an
196 *> output argument.
197 *> \endverbatim
198 *>
199 *> \param[in,out] S
200 *> \verbatim
201 *> S is DOUBLE PRECISION array, dimension (N)
202 *> The scale factors for A; not accessed if EQUED = 'N'. S is
203 *> an input argument if FACT = 'F'; otherwise, S is an output
204 *> argument. If FACT = 'F' and EQUED = 'Y', each element of S
205 *> must be positive.
206 *> \endverbatim
207 *>
208 *> \param[in,out] B
209 *> \verbatim
210 *> B is DOUBLE PRECISION array, dimension (LDB,NRHS)
211 *> On entry, the N-by-NRHS right hand side matrix B.
212 *> On exit, if EQUED = 'N', B is not modified; if EQUED = 'Y',
213 *> B is overwritten by diag(S) * B.
214 *> \endverbatim
215 *>
216 *> \param[in] LDB
217 *> \verbatim
218 *> LDB is INTEGER
219 *> The leading dimension of the array B. LDB >= max(1,N).
220 *> \endverbatim
221 *>
222 *> \param[out] X
223 *> \verbatim
224 *> X is DOUBLE PRECISION array, dimension (LDX,NRHS)
225 *> If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to
226 *> the original system of equations. Note that if EQUED = 'Y',
227 *> A and B are modified on exit, and the solution to the
228 *> equilibrated system is inv(diag(S))*X.
229 *> \endverbatim
230 *>
231 *> \param[in] LDX
232 *> \verbatim
233 *> LDX is INTEGER
234 *> The leading dimension of the array X. LDX >= max(1,N).
235 *> \endverbatim
236 *>
237 *> \param[out] RCOND
238 *> \verbatim
239 *> RCOND is DOUBLE PRECISION
240 *> The estimate of the reciprocal condition number of the matrix
241 *> A after equilibration (if done). If RCOND is less than the
242 *> machine precision (in particular, if RCOND = 0), the matrix
243 *> is singular to working precision. This condition is
244 *> indicated by a return code of INFO > 0.
245 *> \endverbatim
246 *>
247 *> \param[out] FERR
248 *> \verbatim
249 *> FERR is DOUBLE PRECISION array, dimension (NRHS)
250 *> The estimated forward error bound for each solution vector
251 *> X(j) (the j-th column of the solution matrix X).
252 *> If XTRUE is the true solution corresponding to X(j), FERR(j)
253 *> is an estimated upper bound for the magnitude of the largest
254 *> element in (X(j) - XTRUE) divided by the magnitude of the
255 *> largest element in X(j). The estimate is as reliable as
256 *> the estimate for RCOND, and is almost always a slight
257 *> overestimate of the true error.
258 *> \endverbatim
259 *>
260 *> \param[out] BERR
261 *> \verbatim
262 *> BERR is DOUBLE PRECISION array, dimension (NRHS)
263 *> The componentwise relative backward error of each solution
264 *> vector X(j) (i.e., the smallest relative change in
265 *> any element of A or B that makes X(j) an exact solution).
266 *> \endverbatim
267 *>
268 *> \param[out] WORK
269 *> \verbatim
270 *> WORK is DOUBLE PRECISION array, dimension (3*N)
271 *> \endverbatim
272 *>
273 *> \param[out] IWORK
274 *> \verbatim
275 *> IWORK is INTEGER array, dimension (N)
276 *> \endverbatim
277 *>
278 *> \param[out] INFO
279 *> \verbatim
280 *> INFO is INTEGER
281 *> = 0: successful exit
282 *> < 0: if INFO = -i, the i-th argument had an illegal value
283 *> > 0: if INFO = i, and i is
284 *> <= N: the leading minor of order i of A is
285 *> not positive definite, so the factorization
286 *> could not be completed, and the solution has not
287 *> been computed. RCOND = 0 is returned.
288 *> = N+1: U is nonsingular, but RCOND is less than machine
289 *> precision, meaning that the matrix is singular
290 *> to working precision. Nevertheless, the
291 *> solution and error bounds are computed because
292 *> there are a number of situations where the
293 *> computed solution can be more accurate than the
294 *> value of RCOND would suggest.
295 *> \endverbatim
296 *
297 * Authors:
298 * ========
299 *
300 *> \author Univ. of Tennessee
301 *> \author Univ. of California Berkeley
302 *> \author Univ. of Colorado Denver
303 *> \author NAG Ltd.
304 *
305 *> \date April 2012
306 *
307 *> \ingroup doubleOTHERsolve
308 *
309 *> \par Further Details:
310 * =====================
311 *>
312 *> \verbatim
313 *>
314 *> The band storage scheme is illustrated by the following example, when
315 *> N = 6, KD = 2, and UPLO = 'U':
316 *>
317 *> Two-dimensional storage of the symmetric matrix A:
318 *>
319 *> a11 a12 a13
320 *> a22 a23 a24
321 *> a33 a34 a35
322 *> a44 a45 a46
323 *> a55 a56
324 *> (aij=conjg(aji)) a66
325 *>
326 *> Band storage of the upper triangle of A:
327 *>
328 *> * * a13 a24 a35 a46
329 *> * a12 a23 a34 a45 a56
330 *> a11 a22 a33 a44 a55 a66
331 *>
332 *> Similarly, if UPLO = 'L' the format of A is as follows:
333 *>
334 *> a11 a22 a33 a44 a55 a66
335 *> a21 a32 a43 a54 a65 *
336 *> a31 a42 a53 a64 * *
337 *>
338 *> Array elements marked * are not used by the routine.
339 *> \endverbatim
340 *>
341 * =====================================================================
342  SUBROUTINE dpbsvx( FACT, UPLO, N, KD, NRHS, AB, LDAB, AFB, LDAFB,
343  $ equed, s, b, ldb, x, ldx, rcond, ferr, berr,
344  $ work, iwork, info )
345 *
346 * -- LAPACK driver routine (version 3.4.1) --
347 * -- LAPACK is a software package provided by Univ. of Tennessee, --
348 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
349 * April 2012
350 *
351 * .. Scalar Arguments ..
352  CHARACTER EQUED, FACT, UPLO
353  INTEGER INFO, KD, LDAB, LDAFB, LDB, LDX, N, NRHS
354  DOUBLE PRECISION RCOND
355 * ..
356 * .. Array Arguments ..
357  INTEGER IWORK( * )
358  DOUBLE PRECISION AB( ldab, * ), AFB( ldafb, * ), B( ldb, * ),
359  $ berr( * ), ferr( * ), s( * ), work( * ),
360  $ x( ldx, * )
361 * ..
362 *
363 * =====================================================================
364 *
365 * .. Parameters ..
366  DOUBLE PRECISION ZERO, ONE
367  parameter ( zero = 0.0d+0, one = 1.0d+0 )
368 * ..
369 * .. Local Scalars ..
370  LOGICAL EQUIL, NOFACT, RCEQU, UPPER
371  INTEGER I, INFEQU, J, J1, J2
372  DOUBLE PRECISION AMAX, ANORM, BIGNUM, SCOND, SMAX, SMIN, SMLNUM
373 * ..
374 * .. External Functions ..
375  LOGICAL LSAME
376  DOUBLE PRECISION DLAMCH, DLANSB
377  EXTERNAL lsame, dlamch, dlansb
378 * ..
379 * .. External Subroutines ..
380  EXTERNAL dcopy, dlacpy, dlaqsb, dpbcon, dpbequ, dpbrfs,
381  $ dpbtrf, dpbtrs, xerbla
382 * ..
383 * .. Intrinsic Functions ..
384  INTRINSIC max, min
385 * ..
386 * .. Executable Statements ..
387 *
388  info = 0
389  nofact = lsame( fact, 'N' )
390  equil = lsame( fact, 'E' )
391  upper = lsame( uplo, 'U' )
392  IF( nofact .OR. equil ) THEN
393  equed = 'N'
394  rcequ = .false.
395  ELSE
396  rcequ = lsame( equed, 'Y' )
397  smlnum = dlamch( 'Safe minimum' )
398  bignum = one / smlnum
399  END IF
400 *
401 * Test the input parameters.
402 *
403  IF( .NOT.nofact .AND. .NOT.equil .AND. .NOT.lsame( fact, 'F' ) )
404  $ THEN
405  info = -1
406  ELSE IF( .NOT.upper .AND. .NOT.lsame( uplo, 'L' ) ) THEN
407  info = -2
408  ELSE IF( n.LT.0 ) THEN
409  info = -3
410  ELSE IF( kd.LT.0 ) THEN
411  info = -4
412  ELSE IF( nrhs.LT.0 ) THEN
413  info = -5
414  ELSE IF( ldab.LT.kd+1 ) THEN
415  info = -7
416  ELSE IF( ldafb.LT.kd+1 ) THEN
417  info = -9
418  ELSE IF( lsame( fact, 'F' ) .AND. .NOT.
419  $ ( rcequ .OR. lsame( equed, 'N' ) ) ) THEN
420  info = -10
421  ELSE
422  IF( rcequ ) THEN
423  smin = bignum
424  smax = zero
425  DO 10 j = 1, n
426  smin = min( smin, s( j ) )
427  smax = max( smax, s( j ) )
428  10 CONTINUE
429  IF( smin.LE.zero ) THEN
430  info = -11
431  ELSE IF( n.GT.0 ) THEN
432  scond = max( smin, smlnum ) / min( smax, bignum )
433  ELSE
434  scond = one
435  END IF
436  END IF
437  IF( info.EQ.0 ) THEN
438  IF( ldb.LT.max( 1, n ) ) THEN
439  info = -13
440  ELSE IF( ldx.LT.max( 1, n ) ) THEN
441  info = -15
442  END IF
443  END IF
444  END IF
445 *
446  IF( info.NE.0 ) THEN
447  CALL xerbla( 'DPBSVX', -info )
448  RETURN
449  END IF
450 *
451  IF( equil ) THEN
452 *
453 * Compute row and column scalings to equilibrate the matrix A.
454 *
455  CALL dpbequ( uplo, n, kd, ab, ldab, s, scond, amax, infequ )
456  IF( infequ.EQ.0 ) THEN
457 *
458 * Equilibrate the matrix.
459 *
460  CALL dlaqsb( uplo, n, kd, ab, ldab, s, scond, amax, equed )
461  rcequ = lsame( equed, 'Y' )
462  END IF
463  END IF
464 *
465 * Scale the right-hand side.
466 *
467  IF( rcequ ) THEN
468  DO 30 j = 1, nrhs
469  DO 20 i = 1, n
470  b( i, j ) = s( i )*b( i, j )
471  20 CONTINUE
472  30 CONTINUE
473  END IF
474 *
475  IF( nofact .OR. equil ) THEN
476 *
477 * Compute the Cholesky factorization A = U**T *U or A = L*L**T.
478 *
479  IF( upper ) THEN
480  DO 40 j = 1, n
481  j1 = max( j-kd, 1 )
482  CALL dcopy( j-j1+1, ab( kd+1-j+j1, j ), 1,
483  $ afb( kd+1-j+j1, j ), 1 )
484  40 CONTINUE
485  ELSE
486  DO 50 j = 1, n
487  j2 = min( j+kd, n )
488  CALL dcopy( j2-j+1, ab( 1, j ), 1, afb( 1, j ), 1 )
489  50 CONTINUE
490  END IF
491 *
492  CALL dpbtrf( uplo, n, kd, afb, ldafb, info )
493 *
494 * Return if INFO is non-zero.
495 *
496  IF( info.GT.0 )THEN
497  rcond = zero
498  RETURN
499  END IF
500  END IF
501 *
502 * Compute the norm of the matrix A.
503 *
504  anorm = dlansb( '1', uplo, n, kd, ab, ldab, work )
505 *
506 * Compute the reciprocal of the condition number of A.
507 *
508  CALL dpbcon( uplo, n, kd, afb, ldafb, anorm, rcond, work, iwork,
509  $ info )
510 *
511 * Compute the solution matrix X.
512 *
513  CALL dlacpy( 'Full', n, nrhs, b, ldb, x, ldx )
514  CALL dpbtrs( uplo, n, kd, nrhs, afb, ldafb, x, ldx, info )
515 *
516 * Use iterative refinement to improve the computed solution and
517 * compute error bounds and backward error estimates for it.
518 *
519  CALL dpbrfs( uplo, n, kd, nrhs, ab, ldab, afb, ldafb, b, ldb, x,
520  $ ldx, ferr, berr, work, iwork, info )
521 *
522 * Transform the solution matrix X to a solution of the original
523 * system.
524 *
525  IF( rcequ ) THEN
526  DO 70 j = 1, nrhs
527  DO 60 i = 1, n
528  x( i, j ) = s( i )*x( i, j )
529  60 CONTINUE
530  70 CONTINUE
531  DO 80 j = 1, nrhs
532  ferr( j ) = ferr( j ) / scond
533  80 CONTINUE
534  END IF
535 *
536 * Set INFO = N+1 if the matrix is singular to working precision.
537 *
538  IF( rcond.LT.dlamch( 'Epsilon' ) )
539  $ info = n + 1
540 *
541  RETURN
542 *
543 * End of DPBSVX
544 *
545  END
subroutine dcopy(N, DX, INCX, DY, INCY)
DCOPY
Definition: dcopy.f:53
subroutine dpbcon(UPLO, N, KD, AB, LDAB, ANORM, RCOND, WORK, IWORK, INFO)
DPBCON
Definition: dpbcon.f:134
subroutine dlaqsb(UPLO, N, KD, AB, LDAB, S, SCOND, AMAX, EQUED)
DLAQSB scales a symmetric/Hermitian band matrix, using scaling factors computed by spbequ...
Definition: dlaqsb.f:142
subroutine dlacpy(UPLO, M, N, A, LDA, B, LDB)
DLACPY copies all or part of one two-dimensional array to another.
Definition: dlacpy.f:105
subroutine dpbequ(UPLO, N, KD, AB, LDAB, S, SCOND, AMAX, INFO)
DPBEQU
Definition: dpbequ.f:131
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:62
subroutine dpbtrf(UPLO, N, KD, AB, LDAB, INFO)
DPBTRF
Definition: dpbtrf.f:144
subroutine dpbsvx(FACT, UPLO, N, KD, NRHS, AB, LDAB, AFB, LDAFB, EQUED, S, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, IWORK, INFO)
DPBSVX computes the solution to system of linear equations A * X = B for OTHER matrices ...
Definition: dpbsvx.f:345
subroutine dpbtrs(UPLO, N, KD, NRHS, AB, LDAB, B, LDB, INFO)
DPBTRS
Definition: dpbtrs.f:123
subroutine dpbrfs(UPLO, N, KD, NRHS, AB, LDAB, AFB, LDAFB, B, LDB, X, LDX, FERR, BERR, WORK, IWORK, INFO)
DPBRFS
Definition: dpbrfs.f:191