Annotation of rpl/lapack/lapack/dgesvxx.f, revision 1.16
1.5 bertrand 1: *> \brief <b> DGESVXX computes the solution to system of linear equations A * X = B for GE matrices</b>
2: *
3: * =========== DOCUMENTATION ===========
4: *
1.12 bertrand 5: * Online html documentation available at
6: * http://www.netlib.org/lapack/explore-html/
1.5 bertrand 7: *
8: *> \htmlonly
1.12 bertrand 9: *> Download DGESVXX + dependencies
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11: *> [TGZ]</a>
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14: *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dgesvxx.f">
1.5 bertrand 15: *> [TXT]</a>
1.12 bertrand 16: *> \endhtmlonly
1.5 bertrand 17: *
18: * Definition:
19: * ===========
20: *
21: * SUBROUTINE DGESVXX( FACT, TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV,
22: * EQUED, R, C, B, LDB, X, LDX, RCOND, RPVGRW,
23: * BERR, N_ERR_BNDS, ERR_BNDS_NORM,
24: * ERR_BNDS_COMP, NPARAMS, PARAMS, WORK, IWORK,
25: * INFO )
1.12 bertrand 26: *
1.5 bertrand 27: * .. Scalar Arguments ..
28: * CHARACTER EQUED, FACT, TRANS
29: * INTEGER INFO, LDA, LDAF, LDB, LDX, N, NRHS, NPARAMS,
30: * $ N_ERR_BNDS
31: * DOUBLE PRECISION RCOND, RPVGRW
32: * ..
33: * .. Array Arguments ..
34: * INTEGER IPIV( * ), IWORK( * )
35: * DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ),
36: * $ X( LDX , * ),WORK( * )
37: * DOUBLE PRECISION R( * ), C( * ), PARAMS( * ), BERR( * ),
38: * $ ERR_BNDS_NORM( NRHS, * ),
39: * $ ERR_BNDS_COMP( NRHS, * )
40: * ..
1.12 bertrand 41: *
1.5 bertrand 42: *
43: *> \par Purpose:
44: * =============
45: *>
46: *> \verbatim
47: *>
48: *> DGESVXX uses the LU factorization to compute the solution to a
49: *> double precision system of linear equations A * X = B, where A is an
50: *> N-by-N matrix and X and B are N-by-NRHS matrices.
51: *>
52: *> If requested, both normwise and maximum componentwise error bounds
53: *> are returned. DGESVXX will return a solution with a tiny
54: *> guaranteed error (O(eps) where eps is the working machine
55: *> precision) unless the matrix is very ill-conditioned, in which
56: *> case a warning is returned. Relevant condition numbers also are
57: *> calculated and returned.
58: *>
59: *> DGESVXX accepts user-provided factorizations and equilibration
60: *> factors; see the definitions of the FACT and EQUED options.
61: *> Solving with refinement and using a factorization from a previous
62: *> DGESVXX call will also produce a solution with either O(eps)
63: *> errors or warnings, but we cannot make that claim for general
64: *> user-provided factorizations and equilibration factors if they
65: *> differ from what DGESVXX would itself produce.
66: *> \endverbatim
67: *
68: *> \par Description:
69: * =================
70: *>
71: *> \verbatim
72: *>
73: *> The following steps are performed:
74: *>
75: *> 1. If FACT = 'E', double precision scaling factors are computed to equilibrate
76: *> the system:
77: *>
78: *> TRANS = 'N': diag(R)*A*diag(C) *inv(diag(C))*X = diag(R)*B
79: *> TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B
80: *> TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*B
81: *>
82: *> Whether or not the system will be equilibrated depends on the
83: *> scaling of the matrix A, but if equilibration is used, A is
84: *> overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if TRANS='N')
85: *> or diag(C)*B (if TRANS = 'T' or 'C').
86: *>
87: *> 2. If FACT = 'N' or 'E', the LU decomposition is used to factor
88: *> the matrix A (after equilibration if FACT = 'E') as
89: *>
90: *> A = P * L * U,
91: *>
92: *> where P is a permutation matrix, L is a unit lower triangular
93: *> matrix, and U is upper triangular.
94: *>
95: *> 3. If some U(i,i)=0, so that U is exactly singular, then the
96: *> routine returns with INFO = i. Otherwise, the factored form of A
97: *> is used to estimate the condition number of the matrix A (see
98: *> argument RCOND). If the reciprocal of the condition number is less
99: *> than machine precision, the routine still goes on to solve for X
100: *> and compute error bounds as described below.
101: *>
102: *> 4. The system of equations is solved for X using the factored form
103: *> of A.
104: *>
105: *> 5. By default (unless PARAMS(LA_LINRX_ITREF_I) is set to zero),
106: *> the routine will use iterative refinement to try to get a small
107: *> error and error bounds. Refinement calculates the residual to at
108: *> least twice the working precision.
109: *>
110: *> 6. If equilibration was used, the matrix X is premultiplied by
111: *> diag(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') so
112: *> that it solves the original system before equilibration.
113: *> \endverbatim
114: *
115: * Arguments:
116: * ==========
117: *
118: *> \verbatim
119: *> Some optional parameters are bundled in the PARAMS array. These
120: *> settings determine how refinement is performed, but often the
121: *> defaults are acceptable. If the defaults are acceptable, users
122: *> can pass NPARAMS = 0 which prevents the source code from accessing
123: *> the PARAMS argument.
124: *> \endverbatim
125: *>
126: *> \param[in] FACT
127: *> \verbatim
128: *> FACT is CHARACTER*1
129: *> Specifies whether or not the factored form of the matrix A is
130: *> supplied on entry, and if not, whether the matrix A should be
131: *> equilibrated before it is factored.
132: *> = 'F': On entry, AF and IPIV contain the factored form of A.
133: *> If EQUED is not 'N', the matrix A has been
134: *> equilibrated with scaling factors given by R and C.
135: *> A, AF, and IPIV are not modified.
136: *> = 'N': The matrix A will be copied to AF and factored.
137: *> = 'E': The matrix A will be equilibrated if necessary, then
138: *> copied to AF and factored.
139: *> \endverbatim
140: *>
141: *> \param[in] TRANS
142: *> \verbatim
143: *> TRANS is CHARACTER*1
144: *> Specifies the form of the system of equations:
145: *> = 'N': A * X = B (No transpose)
146: *> = 'T': A**T * X = B (Transpose)
147: *> = 'C': A**H * X = B (Conjugate Transpose = Transpose)
148: *> \endverbatim
149: *>
150: *> \param[in] N
151: *> \verbatim
152: *> N is INTEGER
153: *> The number of linear equations, i.e., the order of the
154: *> matrix A. N >= 0.
155: *> \endverbatim
156: *>
157: *> \param[in] NRHS
158: *> \verbatim
159: *> NRHS is INTEGER
160: *> The number of right hand sides, i.e., the number of columns
161: *> of the matrices B and X. NRHS >= 0.
162: *> \endverbatim
163: *>
164: *> \param[in,out] A
165: *> \verbatim
166: *> A is DOUBLE PRECISION array, dimension (LDA,N)
167: *> On entry, the N-by-N matrix A. If FACT = 'F' and EQUED is
168: *> not 'N', then A must have been equilibrated by the scaling
169: *> factors in R and/or C. A is not modified if FACT = 'F' or
170: *> 'N', or if FACT = 'E' and EQUED = 'N' on exit.
171: *>
172: *> On exit, if EQUED .ne. 'N', A is scaled as follows:
173: *> EQUED = 'R': A := diag(R) * A
174: *> EQUED = 'C': A := A * diag(C)
175: *> EQUED = 'B': A := diag(R) * A * diag(C).
176: *> \endverbatim
177: *>
178: *> \param[in] LDA
179: *> \verbatim
180: *> LDA is INTEGER
181: *> The leading dimension of the array A. LDA >= max(1,N).
182: *> \endverbatim
183: *>
184: *> \param[in,out] AF
185: *> \verbatim
1.7 bertrand 186: *> AF is DOUBLE PRECISION array, dimension (LDAF,N)
1.5 bertrand 187: *> If FACT = 'F', then AF is an input argument and on entry
188: *> contains the factors L and U from the factorization
189: *> A = P*L*U as computed by DGETRF. If EQUED .ne. 'N', then
190: *> AF is the factored form of the equilibrated matrix A.
191: *>
192: *> If FACT = 'N', then AF is an output argument and on exit
193: *> returns the factors L and U from the factorization A = P*L*U
194: *> of the original matrix A.
195: *>
196: *> If FACT = 'E', then AF is an output argument and on exit
197: *> returns the factors L and U from the factorization A = P*L*U
198: *> of the equilibrated matrix A (see the description of A for
199: *> the form of the equilibrated matrix).
200: *> \endverbatim
201: *>
202: *> \param[in] LDAF
203: *> \verbatim
204: *> LDAF is INTEGER
205: *> The leading dimension of the array AF. LDAF >= max(1,N).
206: *> \endverbatim
207: *>
208: *> \param[in,out] IPIV
209: *> \verbatim
1.7 bertrand 210: *> IPIV is INTEGER array, dimension (N)
1.5 bertrand 211: *> If FACT = 'F', then IPIV is an input argument and on entry
212: *> contains the pivot indices from the factorization A = P*L*U
213: *> as computed by DGETRF; row i of the matrix was interchanged
214: *> with row IPIV(i).
215: *>
216: *> If FACT = 'N', then IPIV is an output argument and on exit
217: *> contains the pivot indices from the factorization A = P*L*U
218: *> of the original matrix A.
219: *>
220: *> If FACT = 'E', then IPIV is an output argument and on exit
221: *> contains the pivot indices from the factorization A = P*L*U
222: *> of the equilibrated matrix A.
223: *> \endverbatim
224: *>
225: *> \param[in,out] EQUED
226: *> \verbatim
1.7 bertrand 227: *> EQUED is CHARACTER*1
1.5 bertrand 228: *> Specifies the form of equilibration that was done.
229: *> = 'N': No equilibration (always true if FACT = 'N').
230: *> = 'R': Row equilibration, i.e., A has been premultiplied by
231: *> diag(R).
232: *> = 'C': Column equilibration, i.e., A has been postmultiplied
233: *> by diag(C).
234: *> = 'B': Both row and column equilibration, i.e., A has been
235: *> replaced by diag(R) * A * diag(C).
236: *> EQUED is an input argument if FACT = 'F'; otherwise, it is an
237: *> output argument.
238: *> \endverbatim
239: *>
240: *> \param[in,out] R
241: *> \verbatim
1.7 bertrand 242: *> R is DOUBLE PRECISION array, dimension (N)
1.5 bertrand 243: *> The row scale factors for A. If EQUED = 'R' or 'B', A is
244: *> multiplied on the left by diag(R); if EQUED = 'N' or 'C', R
245: *> is not accessed. R is an input argument if FACT = 'F';
246: *> otherwise, R is an output argument. If FACT = 'F' and
247: *> EQUED = 'R' or 'B', each element of R must be positive.
248: *> If R is output, each element of R is a power of the radix.
249: *> If R is input, each element of R should be a power of the radix
250: *> to ensure a reliable solution and error estimates. Scaling by
251: *> powers of the radix does not cause rounding errors unless the
252: *> result underflows or overflows. Rounding errors during scaling
253: *> lead to refining with a matrix that is not equivalent to the
254: *> input matrix, producing error estimates that may not be
255: *> reliable.
256: *> \endverbatim
257: *>
258: *> \param[in,out] C
259: *> \verbatim
1.7 bertrand 260: *> C is DOUBLE PRECISION array, dimension (N)
1.5 bertrand 261: *> The column scale factors for A. If EQUED = 'C' or 'B', A is
262: *> multiplied on the right by diag(C); if EQUED = 'N' or 'R', C
263: *> is not accessed. C is an input argument if FACT = 'F';
264: *> otherwise, C is an output argument. If FACT = 'F' and
265: *> EQUED = 'C' or 'B', each element of C must be positive.
266: *> If C is output, each element of C is a power of the radix.
267: *> If C is input, each element of C should be a power of the radix
268: *> to ensure a reliable solution and error estimates. Scaling by
269: *> powers of the radix does not cause rounding errors unless the
270: *> result underflows or overflows. Rounding errors during scaling
271: *> lead to refining with a matrix that is not equivalent to the
272: *> input matrix, producing error estimates that may not be
273: *> reliable.
274: *> \endverbatim
275: *>
276: *> \param[in,out] B
277: *> \verbatim
278: *> B is DOUBLE PRECISION array, dimension (LDB,NRHS)
279: *> On entry, the N-by-NRHS right hand side matrix B.
280: *> On exit,
281: *> if EQUED = 'N', B is not modified;
282: *> if TRANS = 'N' and EQUED = 'R' or 'B', B is overwritten by
283: *> diag(R)*B;
284: *> if TRANS = 'T' or 'C' and EQUED = 'C' or 'B', B is
285: *> overwritten by diag(C)*B.
286: *> \endverbatim
287: *>
288: *> \param[in] LDB
289: *> \verbatim
290: *> LDB is INTEGER
291: *> The leading dimension of the array B. LDB >= max(1,N).
292: *> \endverbatim
293: *>
294: *> \param[out] X
295: *> \verbatim
296: *> X is DOUBLE PRECISION array, dimension (LDX,NRHS)
297: *> If INFO = 0, the N-by-NRHS solution matrix X to the original
298: *> system of equations. Note that A and B are modified on exit
299: *> if EQUED .ne. 'N', and the solution to the equilibrated system is
300: *> inv(diag(C))*X if TRANS = 'N' and EQUED = 'C' or 'B', or
301: *> inv(diag(R))*X if TRANS = 'T' or 'C' and EQUED = 'R' or 'B'.
302: *> \endverbatim
303: *>
304: *> \param[in] LDX
305: *> \verbatim
306: *> LDX is INTEGER
307: *> The leading dimension of the array X. LDX >= max(1,N).
308: *> \endverbatim
309: *>
310: *> \param[out] RCOND
311: *> \verbatim
312: *> RCOND is DOUBLE PRECISION
313: *> Reciprocal scaled condition number. This is an estimate of the
314: *> reciprocal Skeel condition number of the matrix A after
315: *> equilibration (if done). If this is less than the machine
316: *> precision (in particular, if it is zero), the matrix is singular
317: *> to working precision. Note that the error may still be small even
318: *> if this number is very small and the matrix appears ill-
319: *> conditioned.
320: *> \endverbatim
321: *>
322: *> \param[out] RPVGRW
323: *> \verbatim
324: *> RPVGRW is DOUBLE PRECISION
325: *> Reciprocal pivot growth. On exit, this contains the reciprocal
326: *> pivot growth factor norm(A)/norm(U). The "max absolute element"
327: *> norm is used. If this is much less than 1, then the stability of
328: *> the LU factorization of the (equilibrated) matrix A could be poor.
329: *> This also means that the solution X, estimated condition numbers,
330: *> and error bounds could be unreliable. If factorization fails with
331: *> 0<INFO<=N, then this contains the reciprocal pivot growth factor
332: *> for the leading INFO columns of A. In DGESVX, this quantity is
333: *> returned in WORK(1).
334: *> \endverbatim
335: *>
336: *> \param[out] BERR
337: *> \verbatim
338: *> BERR is DOUBLE PRECISION array, dimension (NRHS)
339: *> Componentwise relative backward error. This is the
340: *> componentwise relative backward error of each solution vector X(j)
341: *> (i.e., the smallest relative change in any element of A or B that
342: *> makes X(j) an exact solution).
343: *> \endverbatim
344: *>
345: *> \param[in] N_ERR_BNDS
346: *> \verbatim
347: *> N_ERR_BNDS is INTEGER
348: *> Number of error bounds to return for each right hand side
349: *> and each type (normwise or componentwise). See ERR_BNDS_NORM and
350: *> ERR_BNDS_COMP below.
351: *> \endverbatim
352: *>
353: *> \param[out] ERR_BNDS_NORM
354: *> \verbatim
355: *> ERR_BNDS_NORM is DOUBLE PRECISION array, dimension (NRHS, N_ERR_BNDS)
356: *> For each right-hand side, this array contains information about
357: *> various error bounds and condition numbers corresponding to the
358: *> normwise relative error, which is defined as follows:
359: *>
360: *> Normwise relative error in the ith solution vector:
361: *> max_j (abs(XTRUE(j,i) - X(j,i)))
362: *> ------------------------------
363: *> max_j abs(X(j,i))
364: *>
365: *> The array is indexed by the type of error information as described
366: *> below. There currently are up to three pieces of information
367: *> returned.
368: *>
369: *> The first index in ERR_BNDS_NORM(i,:) corresponds to the ith
370: *> right-hand side.
371: *>
372: *> The second index in ERR_BNDS_NORM(:,err) contains the following
373: *> three fields:
374: *> err = 1 "Trust/don't trust" boolean. Trust the answer if the
375: *> reciprocal condition number is less than the threshold
376: *> sqrt(n) * dlamch('Epsilon').
377: *>
378: *> err = 2 "Guaranteed" error bound: The estimated forward error,
379: *> almost certainly within a factor of 10 of the true error
380: *> so long as the next entry is greater than the threshold
381: *> sqrt(n) * dlamch('Epsilon'). This error bound should only
382: *> be trusted if the previous boolean is true.
383: *>
384: *> err = 3 Reciprocal condition number: Estimated normwise
385: *> reciprocal condition number. Compared with the threshold
386: *> sqrt(n) * dlamch('Epsilon') to determine if the error
387: *> estimate is "guaranteed". These reciprocal condition
388: *> numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
389: *> appropriately scaled matrix Z.
390: *> Let Z = S*A, where S scales each row by a power of the
391: *> radix so all absolute row sums of Z are approximately 1.
392: *>
393: *> See Lapack Working Note 165 for further details and extra
394: *> cautions.
395: *> \endverbatim
396: *>
397: *> \param[out] ERR_BNDS_COMP
398: *> \verbatim
399: *> ERR_BNDS_COMP is DOUBLE PRECISION array, dimension (NRHS, N_ERR_BNDS)
400: *> For each right-hand side, this array contains information about
401: *> various error bounds and condition numbers corresponding to the
402: *> componentwise relative error, which is defined as follows:
403: *>
404: *> Componentwise relative error in the ith solution vector:
405: *> abs(XTRUE(j,i) - X(j,i))
406: *> max_j ----------------------
407: *> abs(X(j,i))
408: *>
409: *> The array is indexed by the right-hand side i (on which the
410: *> componentwise relative error depends), and the type of error
411: *> information as described below. There currently are up to three
412: *> pieces of information returned for each right-hand side. If
413: *> componentwise accuracy is not requested (PARAMS(3) = 0.0), then
1.15 bertrand 414: *> ERR_BNDS_COMP is not accessed. If N_ERR_BNDS < 3, then at most
1.5 bertrand 415: *> the first (:,N_ERR_BNDS) entries are returned.
416: *>
417: *> The first index in ERR_BNDS_COMP(i,:) corresponds to the ith
418: *> right-hand side.
419: *>
420: *> The second index in ERR_BNDS_COMP(:,err) contains the following
421: *> three fields:
422: *> err = 1 "Trust/don't trust" boolean. Trust the answer if the
423: *> reciprocal condition number is less than the threshold
424: *> sqrt(n) * dlamch('Epsilon').
425: *>
426: *> err = 2 "Guaranteed" error bound: The estimated forward error,
427: *> almost certainly within a factor of 10 of the true error
428: *> so long as the next entry is greater than the threshold
429: *> sqrt(n) * dlamch('Epsilon'). This error bound should only
430: *> be trusted if the previous boolean is true.
431: *>
432: *> err = 3 Reciprocal condition number: Estimated componentwise
433: *> reciprocal condition number. Compared with the threshold
434: *> sqrt(n) * dlamch('Epsilon') to determine if the error
435: *> estimate is "guaranteed". These reciprocal condition
436: *> numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
437: *> appropriately scaled matrix Z.
438: *> Let Z = S*(A*diag(x)), where x is the solution for the
439: *> current right-hand side and S scales each row of
440: *> A*diag(x) by a power of the radix so all absolute row
441: *> sums of Z are approximately 1.
442: *>
443: *> See Lapack Working Note 165 for further details and extra
444: *> cautions.
445: *> \endverbatim
446: *>
447: *> \param[in] NPARAMS
448: *> \verbatim
449: *> NPARAMS is INTEGER
1.15 bertrand 450: *> Specifies the number of parameters set in PARAMS. If <= 0, the
1.5 bertrand 451: *> PARAMS array is never referenced and default values are used.
452: *> \endverbatim
453: *>
454: *> \param[in,out] PARAMS
455: *> \verbatim
1.7 bertrand 456: *> PARAMS is DOUBLE PRECISION array, dimension (NPARAMS)
1.15 bertrand 457: *> Specifies algorithm parameters. If an entry is < 0.0, then
1.5 bertrand 458: *> that entry will be filled with default value used for that
459: *> parameter. Only positions up to NPARAMS are accessed; defaults
460: *> are used for higher-numbered parameters.
461: *>
462: *> PARAMS(LA_LINRX_ITREF_I = 1) : Whether to perform iterative
463: *> refinement or not.
464: *> Default: 1.0D+0
1.15 bertrand 465: *> = 0.0: No refinement is performed, and no error bounds are
1.5 bertrand 466: *> computed.
1.15 bertrand 467: *> = 1.0: Use the extra-precise refinement algorithm.
1.5 bertrand 468: *> (other values are reserved for future use)
469: *>
470: *> PARAMS(LA_LINRX_ITHRESH_I = 2) : Maximum number of residual
471: *> computations allowed for refinement.
472: *> Default: 10
473: *> Aggressive: Set to 100 to permit convergence using approximate
474: *> factorizations or factorizations other than LU. If
475: *> the factorization uses a technique other than
476: *> Gaussian elimination, the guarantees in
477: *> err_bnds_norm and err_bnds_comp may no longer be
478: *> trustworthy.
479: *>
480: *> PARAMS(LA_LINRX_CWISE_I = 3) : Flag determining if the code
481: *> will attempt to find a solution with small componentwise
482: *> relative error in the double-precision algorithm. Positive
483: *> is true, 0.0 is false.
484: *> Default: 1.0 (attempt componentwise convergence)
485: *> \endverbatim
486: *>
487: *> \param[out] WORK
488: *> \verbatim
489: *> WORK is DOUBLE PRECISION array, dimension (4*N)
490: *> \endverbatim
491: *>
492: *> \param[out] IWORK
493: *> \verbatim
494: *> IWORK is INTEGER array, dimension (N)
495: *> \endverbatim
496: *>
497: *> \param[out] INFO
498: *> \verbatim
499: *> INFO is INTEGER
500: *> = 0: Successful exit. The solution to every right-hand side is
501: *> guaranteed.
502: *> < 0: If INFO = -i, the i-th argument had an illegal value
503: *> > 0 and <= N: U(INFO,INFO) is exactly zero. The factorization
504: *> has been completed, but the factor U is exactly singular, so
505: *> the solution and error bounds could not be computed. RCOND = 0
506: *> is returned.
507: *> = N+J: The solution corresponding to the Jth right-hand side is
508: *> not guaranteed. The solutions corresponding to other right-
509: *> hand sides K with K > J may not be guaranteed as well, but
510: *> only the first such right-hand side is reported. If a small
511: *> componentwise error is not requested (PARAMS(3) = 0.0) then
512: *> the Jth right-hand side is the first with a normwise error
513: *> bound that is not guaranteed (the smallest J such
514: *> that ERR_BNDS_NORM(J,1) = 0.0). By default (PARAMS(3) = 1.0)
515: *> the Jth right-hand side is the first with either a normwise or
516: *> componentwise error bound that is not guaranteed (the smallest
517: *> J such that either ERR_BNDS_NORM(J,1) = 0.0 or
518: *> ERR_BNDS_COMP(J,1) = 0.0). See the definition of
519: *> ERR_BNDS_NORM(:,1) and ERR_BNDS_COMP(:,1). To get information
520: *> about all of the right-hand sides check ERR_BNDS_NORM or
521: *> ERR_BNDS_COMP.
522: *> \endverbatim
523: *
524: * Authors:
525: * ========
526: *
1.12 bertrand 527: *> \author Univ. of Tennessee
528: *> \author Univ. of California Berkeley
529: *> \author Univ. of Colorado Denver
530: *> \author NAG Ltd.
1.5 bertrand 531: *
532: *> \ingroup doubleGEsolve
533: *
534: * =====================================================================
1.1 bertrand 535: SUBROUTINE DGESVXX( FACT, TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV,
536: $ EQUED, R, C, B, LDB, X, LDX, RCOND, RPVGRW,
537: $ BERR, N_ERR_BNDS, ERR_BNDS_NORM,
538: $ ERR_BNDS_COMP, NPARAMS, PARAMS, WORK, IWORK,
539: $ INFO )
540: *
1.16 ! bertrand 541: * -- LAPACK driver routine --
1.5 bertrand 542: * -- LAPACK is a software package provided by Univ. of Tennessee, --
543: * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
1.1 bertrand 544: *
545: * .. Scalar Arguments ..
546: CHARACTER EQUED, FACT, TRANS
547: INTEGER INFO, LDA, LDAF, LDB, LDX, N, NRHS, NPARAMS,
548: $ N_ERR_BNDS
549: DOUBLE PRECISION RCOND, RPVGRW
550: * ..
551: * .. Array Arguments ..
552: INTEGER IPIV( * ), IWORK( * )
553: DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ),
554: $ X( LDX , * ),WORK( * )
555: DOUBLE PRECISION R( * ), C( * ), PARAMS( * ), BERR( * ),
556: $ ERR_BNDS_NORM( NRHS, * ),
557: $ ERR_BNDS_COMP( NRHS, * )
558: * ..
559: *
1.5 bertrand 560: * =====================================================================
1.1 bertrand 561: *
562: * .. Parameters ..
563: DOUBLE PRECISION ZERO, ONE
564: PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 )
565: INTEGER FINAL_NRM_ERR_I, FINAL_CMP_ERR_I, BERR_I
566: INTEGER RCOND_I, NRM_RCOND_I, NRM_ERR_I, CMP_RCOND_I
567: INTEGER CMP_ERR_I, PIV_GROWTH_I
568: PARAMETER ( FINAL_NRM_ERR_I = 1, FINAL_CMP_ERR_I = 2,
569: $ BERR_I = 3 )
570: PARAMETER ( RCOND_I = 4, NRM_RCOND_I = 5, NRM_ERR_I = 6 )
571: PARAMETER ( CMP_RCOND_I = 7, CMP_ERR_I = 8,
572: $ PIV_GROWTH_I = 9 )
573: * ..
574: * .. Local Scalars ..
575: LOGICAL COLEQU, EQUIL, NOFACT, NOTRAN, ROWEQU
576: INTEGER INFEQU, J
577: DOUBLE PRECISION AMAX, BIGNUM, COLCND, RCMAX, RCMIN, ROWCND,
578: $ SMLNUM
579: * ..
580: * .. External Functions ..
1.7 bertrand 581: EXTERNAL LSAME, DLAMCH, DLA_GERPVGRW
1.1 bertrand 582: LOGICAL LSAME
1.7 bertrand 583: DOUBLE PRECISION DLAMCH, DLA_GERPVGRW
1.1 bertrand 584: * ..
585: * .. External Subroutines ..
586: EXTERNAL DGEEQUB, DGETRF, DGETRS, DLACPY, DLAQGE,
587: $ XERBLA, DLASCL2, DGERFSX
588: * ..
589: * .. Intrinsic Functions ..
590: INTRINSIC MAX, MIN
591: * ..
592: * .. Executable Statements ..
593: *
594: INFO = 0
595: NOFACT = LSAME( FACT, 'N' )
596: EQUIL = LSAME( FACT, 'E' )
597: NOTRAN = LSAME( TRANS, 'N' )
598: SMLNUM = DLAMCH( 'Safe minimum' )
599: BIGNUM = ONE / SMLNUM
600: IF( NOFACT .OR. EQUIL ) THEN
601: EQUED = 'N'
602: ROWEQU = .FALSE.
603: COLEQU = .FALSE.
604: ELSE
605: ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' )
606: COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' )
607: END IF
608: *
609: * Default is failure. If an input parameter is wrong or
610: * factorization fails, make everything look horrible. Only the
611: * pivot growth is set here, the rest is initialized in DGERFSX.
612: *
613: RPVGRW = ZERO
614: *
615: * Test the input parameters. PARAMS is not tested until DGERFSX.
616: *
617: IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.
618: $ LSAME( FACT, 'F' ) ) THEN
619: INFO = -1
620: ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) .AND. .NOT.
621: $ LSAME( TRANS, 'C' ) ) THEN
622: INFO = -2
623: ELSE IF( N.LT.0 ) THEN
624: INFO = -3
625: ELSE IF( NRHS.LT.0 ) THEN
626: INFO = -4
627: ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
628: INFO = -6
629: ELSE IF( LDAF.LT.MAX( 1, N ) ) THEN
630: INFO = -8
631: ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT.
632: $ ( ROWEQU .OR. COLEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN
633: INFO = -10
634: ELSE
635: IF( ROWEQU ) THEN
636: RCMIN = BIGNUM
637: RCMAX = ZERO
638: DO 10 J = 1, N
639: RCMIN = MIN( RCMIN, R( J ) )
640: RCMAX = MAX( RCMAX, R( J ) )
641: 10 CONTINUE
642: IF( RCMIN.LE.ZERO ) THEN
643: INFO = -11
644: ELSE IF( N.GT.0 ) THEN
645: ROWCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM )
646: ELSE
647: ROWCND = ONE
648: END IF
649: END IF
650: IF( COLEQU .AND. INFO.EQ.0 ) THEN
651: RCMIN = BIGNUM
652: RCMAX = ZERO
653: DO 20 J = 1, N
654: RCMIN = MIN( RCMIN, C( J ) )
655: RCMAX = MAX( RCMAX, C( J ) )
656: 20 CONTINUE
657: IF( RCMIN.LE.ZERO ) THEN
658: INFO = -12
659: ELSE IF( N.GT.0 ) THEN
660: COLCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM )
661: ELSE
662: COLCND = ONE
663: END IF
664: END IF
665: IF( INFO.EQ.0 ) THEN
666: IF( LDB.LT.MAX( 1, N ) ) THEN
667: INFO = -14
668: ELSE IF( LDX.LT.MAX( 1, N ) ) THEN
669: INFO = -16
670: END IF
671: END IF
672: END IF
673: *
674: IF( INFO.NE.0 ) THEN
675: CALL XERBLA( 'DGESVXX', -INFO )
676: RETURN
677: END IF
678: *
679: IF( EQUIL ) THEN
680: *
681: * Compute row and column scalings to equilibrate the matrix A.
682: *
683: CALL DGEEQUB( N, N, A, LDA, R, C, ROWCND, COLCND, AMAX,
684: $ INFEQU )
685: IF( INFEQU.EQ.0 ) THEN
686: *
687: * Equilibrate the matrix.
688: *
689: CALL DLAQGE( N, N, A, LDA, R, C, ROWCND, COLCND, AMAX,
690: $ EQUED )
691: ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' )
692: COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' )
693: END IF
694: *
695: * If the scaling factors are not applied, set them to 1.0.
696: *
697: IF ( .NOT.ROWEQU ) THEN
698: DO J = 1, N
699: R( J ) = 1.0D+0
700: END DO
701: END IF
702: IF ( .NOT.COLEQU ) THEN
703: DO J = 1, N
704: C( J ) = 1.0D+0
705: END DO
706: END IF
707: END IF
708: *
709: * Scale the right-hand side.
710: *
711: IF( NOTRAN ) THEN
712: IF( ROWEQU ) CALL DLASCL2( N, NRHS, R, B, LDB )
713: ELSE
714: IF( COLEQU ) CALL DLASCL2( N, NRHS, C, B, LDB )
715: END IF
716: *
717: IF( NOFACT .OR. EQUIL ) THEN
718: *
719: * Compute the LU factorization of A.
720: *
721: CALL DLACPY( 'Full', N, N, A, LDA, AF, LDAF )
722: CALL DGETRF( N, N, AF, LDAF, IPIV, INFO )
723: *
724: * Return if INFO is non-zero.
725: *
726: IF( INFO.GT.0 ) THEN
727: *
728: * Pivot in column INFO is exactly 0
729: * Compute the reciprocal pivot growth factor of the
730: * leading rank-deficient INFO columns of A.
731: *
1.7 bertrand 732: RPVGRW = DLA_GERPVGRW( N, INFO, A, LDA, AF, LDAF )
1.1 bertrand 733: RETURN
734: END IF
735: END IF
736: *
737: * Compute the reciprocal pivot growth factor RPVGRW.
738: *
1.7 bertrand 739: RPVGRW = DLA_GERPVGRW( N, N, A, LDA, AF, LDAF )
1.1 bertrand 740: *
741: * Compute the solution matrix X.
742: *
743: CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX )
744: CALL DGETRS( TRANS, N, NRHS, AF, LDAF, IPIV, X, LDX, INFO )
745: *
746: * Use iterative refinement to improve the computed solution and
747: * compute error bounds and backward error estimates for it.
748: *
749: CALL DGERFSX( TRANS, EQUED, N, NRHS, A, LDA, AF, LDAF,
750: $ IPIV, R, C, B, LDB, X, LDX, RCOND, BERR,
751: $ N_ERR_BNDS, ERR_BNDS_NORM, ERR_BNDS_COMP, NPARAMS, PARAMS,
752: $ WORK, IWORK, INFO )
753: *
754: * Scale solutions.
755: *
756: IF ( COLEQU .AND. NOTRAN ) THEN
757: CALL DLASCL2 ( N, NRHS, C, X, LDX )
758: ELSE IF ( ROWEQU .AND. .NOT.NOTRAN ) THEN
759: CALL DLASCL2 ( N, NRHS, R, X, LDX )
760: END IF
761: *
762: RETURN
763: *
764: * End of DGESVXX
765:
766: END
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